Immunological and Molecular Insights into Acinar-Ductal Metaplasia and Atypical Flat Lesions as Precursor Lesions of Pancreatic Ductal Adenocarcinoma

Immunological and Molecular Insights into Acinar-Ductal Metaplasia and Atypical Flat Lesions as Precursor Lesions of Pancreatic Ductal Adenocarcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Immunological and Molecular Insights into Acinar-Ductal Metaplasia and Atypical Flat Lesions as Precursor Lesions of Pancreatic Ductal Adenocarcinoma Aslihan Yavas, Leon Boshoven, Kai Horny, Sebastian Haensch, Wolfgang Goering, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7660097/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jan, 2026 Read the published version in Journal of Experimental & Clinical Cancer Research → Version 1 posted 9 You are reading this latest preprint version Abstract Introduction Pancreatic ductal adenocarcinoma (PDAC) is known to develop through a stepwise progression from precursor lesions, such as pancreatic intraepithelial neoplasias (PanIN) or intraductal papillary mucinous neoplasms. An alternative carcinogenic pathway has been proposed via transformation of acinar cells, with acinar-ductal metaplasia (ADM) and atypical flat lesions (AFL). Defining the characteristics of PDAC precursors is crucial to better understand PDAC carcinogenesis. Methods 15 KC ( Ptf1a Cre/+ , Kras LSLG12D/+ ) and 15 KPC-like mice ( Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP , referred as fKPC hereafter) were sacrificed at different time points. A meticulous morphological evaluation was performed to define different pancreatic lesion types. Multiplex immunofluorescence staining was applied to define the characteristics of the immune and stromal microenvironment of the lesions (referred as TME hereafter) using variable markers. In order to investigate the association between the genetic alterations and the components of the microenvironment, all lesion types were subjected to next-generation sequencing (NGS) using a 20 genes-panel Results Multiplex immunofluorescence staining revealed that AFL had the most intense immune cell infiltration compared to PanIN and ADM. AFL were infiltrated by higher number of CD4 + helper T cells, FOXP3 + regulatory T cells and CD19 + B cells compared to all analyzed lesions. They displayed and more CD8 + cytotoxic T cells than PDAC, while peripheral and central PDAC tissues were infiltrated by macrophages in higher frequency. In addition, AFL had more prominent αSMA-expressing myofibroblastic cancer-associated fibroblasts-rich stroma than other lesions. PDAC had higher CXCL12 expression and more common CD109 + cells than other lesions. In NGS analysis, none of the lesions in fKPC mice revealed additional coding mutations, while the preneoplastic lesions in 7 KC mice showed variable coding alterations in 16 different genes. The most frequently affected genes were Arid1a, Rnf43 , and Pik3ca ; in contrast, coding Gnas, Braf , and Idh1 mutations were not found. PDAC precursors in KC mice showed more dense infiltration of adaptive immune cells than in fKPC mice, supporting the immunosuppressive role of Trp53 alterations. Conclusions Our study highlights the unique immunological and stromal features of AFL. Moreover, reinforcing their potential as precursor lesions, ADM and AFL exhibit variable alterations in the genes that have a critical role in PDAC carcinogenesis. Acinar-ductal metaplasia atypical flat lesion pancreatic cancer precursors microenvironment genetic alterations Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer with an increasing incidence and a 5-year survival rate of 11-13.3% ( 1 , 2 ). It is predicted to become the second leading cause of cancer-related deaths by 2030 due to advanced disease at diagnosis and limited treatment options ( 3 , 4 ). A stepwise progression model from precursor lesions to carcinoma has been described. The most well-known precursor lesions of PDAC with ductal differentiation are pancreatic intraepithelial neoplasias (PanIN), intraductal papillary mucinous neoplasms (IPMN), and mucinous cystic neoplasms (MCN) ( 5 – 7 ). Additionally, acinar-ductal metaplasia (ADM) and atypical flat lesions (AFL) arising from acinar cells have been proposed as potential precursor lesions of PDAC in genetically engineered mouse models (GEMMs), and lesions resembling mouse AFL have been identified in patients with familial risk of PDAC ( 8 – 11 ). PanIN, ADM, and AFL are microscopic lesions in contrast to macroscopically visible IPMN and MCN. PanIN is characterized by flat or papillary architecture with varying degrees of cytological atypia and mucin production ( 12 ). ADM exhibits tubular structures surrounded by fibrosis without significant cytological atypia. Given its origin from acinar cells that undergo metaplasia into ductal cells, ADM can express both acinar and ductal cell markers in early stages. AFL is frequently found in ADM areas and characterized by a flat epithelium with ductal differentiation consisting of atypical cells with surrounding abundant swirl-like stroma ( 8 – 10 ). Unlike the other PDAC precursors, the biological significance of ADM and AFL in PDAC carcinogenesis is still not well characterized. PDAC forms an immunosuppressive tumor microenvironment (TME) during carcinogenesis, which is characterized by complex stromal and immunological interactions. Tumor-associated macrophages represent the dominant immune cell population of the TME and play a critical role in the development of PDAC, and the progression of its precursor lesions ( 13 – 15 ). Furthermore, the function of the adaptive immune system cells including antigen-presenting cells, CD4 + helper T cells, and CD8 + cytotoxic T cells is often suppressed by the neoplastic cells via various mechanisms, such as the activation of immunosuppressive FOXP3 + regulatory T cells and myeloid-derived suppressor cells or the expression of immune checkpoint molecules ( 16 , 17 ). Acinar-ductal metaplasia occurs as a reversible event in response to acute pancreatic injury and inflammation, but becomes irreversible in the presence of chronic injury or oncogenic KRAS mutation and forms PanIN-like lesions as an initial event of PDAC carcinogenesis ( 18 ). It has been reported that the interactions between acinar cells and infiltrating immune cells, especially macrophages, determines the extent of ADM formation after acute pancreatic injury ( 13 , 19 , 20 ). Depletion of macrophages in the early regenerative stages resulted in a decrease of ADM development, whereas depletion in the late stages caused a delay of pancreatic repair leading to chronic inflammation. Moreover, it has been shown that innate immune cells such as macrophages and neutrophils promote and maintain acinar trans-differentiation, while adaptive immune cells such as B- and T-cells support normal regeneration after injury by stabilizing the inflammatory environment and limiting the numbers of innate cell populations ( 21 ). There is no detailed data about the immune microenvironment of AFL, except for macrophage accumulation around of the lesions ( 10 ). Cancer-associated fibroblasts (CAFs) are an additional significant, heterogeneous component of the TME in PDAC involved in the formation of the desmoplastic stroma and with complex growth- and immune cell-modulating functions ( 22 ). It is known that after pancreatic injury, acinar cells recruit stromal fibroblasts, which in turn play a tumorigenic role with the surrounding macrophages ( 23 , 24 ). Moreover, it has been recently reported that CAFs induce acinar to ductal cell trans-differentiation in acinar and mouse CAFs co-cultures, suggesting that CAFs secretome might play a significant role in ADM development and PDAC initiation ( 25 ). Furthermore, AFL, which are frequently found in ADM areas, have been reported to have a special swirl-like stroma composed of αSMA expressing myofibroblastic cancer-associated fibroblasts (myCAFs) ( 10 ). The CXCL12-CXR4 axis has been reported as a key player for the emergence of a tumor-promoting and immunosuppressive TME in PDAC. CXCL12 (C-X-C motif ligand 12) is a chemotactic chemokine, a marker for inflammatory CAFs (iCAFs), has been shown to promote cell survival, proliferation, immune evasion, angiogenesis, and chemoresistance in PDAC via its receptor CXCR4 (C-X-C motif receptor 4). CXCL12 is expressed primarily by activated fibroblasts in the stroma, while CXCR4 is expressed by the tumor cells ( 26 – 30 ). CXCL12 and its receptors are considered as potential therapeutic targets in PDAC; although their expression has been described in PanIN and IPMN ( 31 , 32 ), no data are available regarding their role in ADM and AFL. In addition, CD109, a glycophosphatidylinositol-binding membrane protein, interacts with TGF-ß1 (transforming growth factor ß1) and EGFR (epidermal growth factor receptor), leading to cell growth, cell differentiation or epithelial to mesenchymal transition ( 33 , 34 ). In PDAC, CD109 can be expressed both in tumor cells and in the surrounding stroma, and it is associated with shorter disease-free and overall survival, tumor progression and higher rates of distant metastases ( 35 , 36 ). CD109 therefore represents a possible prognostic marker for PDAC, but its exact role in PDAC carcinogenesis needs further investigation. In this study, we aimed at characterizing the role of ADM and AFL as alternative PDAC precursors focusing on the composition of their TME and their genetic landscape. Materials and Methods Collective The genetically modified mouse (GEMM) collective was maintained at the Central Facility for Animal Research and Scientific Animal Welfare Tasks (ZETT) of the Heinrich Heine University in Düsseldorf. The collective consisting of 15 KC ( Ptf1a Cre/+ , Kras LSLG12D/+ ) and 15 KPC-like mice ( Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP , for simplicity hereafter referred as fKPC mice) were sacrificed at different time points ranging from 1 to 7 months (Table 1 ). Harvested pancreas tissues were fixed in formalin and embedded in paraffin after tissue processing. Genotype confirmation was performed by polymerase chain reaction (PCR) analysis ( 37 , 38 ). Human formalin-fixed paraffin-embedded (FFPE) blocks containing AFL were retrieved from the archive of the Institute of Pathology at the University Hospital Düsseldorf. Tissue sections (1.5 µm) were subjected to hematoxylin-eosin staining and examined meticulously under the light microscope by two experienced pathologists (AY, IE) for lesions’ classification and annotation. Laser-captured microdissection and Next-Generation Sequencing A series of at least 15 FFPE sections with a thickness of 8 µm were generated for laser captured microdissection. Available AFL, ADM, PanIN, and PDAC areas were extracted using Zeiss Palm Microbeam Laser captured microdissection (LMD) microscope (Carl Zeiss Microscopy GmbH, Jena, Germany). At least 250,000 µm² of total tissue was excised for each lesion type per mouse. The same type lesions were pooled across all previously prepared sections. In addition, normal pancreatic tissue was collected from one KC and one fKPC mouse as reference. DNA isolation from the tissues obtained by LMD was performed using QiAMP® DNA Micro Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Libraries for IonTorrent NGS system were created using Ion AmpliSeq Library Kit 2.0 (ThermoFisher Scientific, Waltham, USA) for a 20 genes panel, which includes hotspots of the genes that are relevant for PDAC (Supp. Table 1 ). Isolated DNAs were amplified via PCR and stripped to Ion Xpress Barcodes (ThermoFisher Scientific, Waltham, USA). After purification using AMPure XP Beads (Fischer Scientific, Hampton, USA) acquired libraries were quantitated using the Ion Library TaqMan Quantitation Kit (ThermoFisher Scientific, Waltham, USA) in StepOnePlus Ultra, Real-Time PCR cycler (ThermoFisher Scientific, Waltham, USA) following the manufacturer's protocol. DNA-concentration was adjusted 100 in pM to perform massive parallel sequencing at the institute's molecular pathology laboratory on the Ion S5 system with suitable Ion chips and sequencing kits (ThermoFisher Scientific, Waltham, USA). Acquired primary data was checked for quality sufficiency and extracted as FASTQs. Sequencing data was evaluated using the DNA-Seq-Varlociraptor pipeline (version 3.22.0) ( 39 ). First, raw sequencing data was aligned to the murine reference genome mus musculus GRCm39 using BWA mem software and ensembl (release 108) ( version 0.7.17 ) ( 40 ). Then, candidate variants were called using freebayes ( version 1.3.6 ) ( 41 ) and delly (version 1.1) ( 42 ) and then processed by Varlociraptor ( 43 ). Varlociraptor is a generic, uncertainty-aware variant caller calculating maximum a posteriori probabilities for complex events. For getting probabilities and evaluating variants, we defined somatic events as following: ( 1 ) Non-zero allele frequency (AF) in one preneoplastic lesion, but not the others. ( 2 ) Non-zero AF in any preneoplastic lesion. ( 3 ) If tumor sample was available: non-zero AF in tumor but not lesional samples and ( 4 ) non-zero AF in tumor and any lesional sample. All events include being absent in the normal pancreas samples, having a resolution of 1% and 5% local false discovery rate (fdr) - control threshold. Variants with an AF below 5% were excluded from analysis and remaining variants annotated using ensembl variant effect predictor (vep) ( 44 ). We investigated the coding variants (defined as those annotated with a HGSVp value) and further filtered to exclude those appearing on only one strand, mutations with low amplicon coverage (< 100x), and variants present in only one of two overlapping amplicons. The variants were manually evaluated and filtered by trained experts from the molecular pathology department for sequencing artifacts and known sequencing errors typical of semiconductor-based methods, such as frameshifts in base repeats, using Integrative Genomics Viewer (IGV, source) ( 45 ). Estimation of DNA copy number variation in human AFL by low-coverage whole-genome sequencing Seven microdissected human AFL were analyzed by low-coverage whole genome sequencing as previously described ( 46 ). Genomic DNA from FFPE samples was amplified using the Ampli1™ WGA kit (Menarini Silicon Biosystems, Bologna, Italy) and purified with SPRIselect beads (Beckman Coulter, Lahntal, Germany). Libraries were prepared using the Ampli1™ low-pass kit (Menarini Silicon Biosystems). The final library concentration was determined on the fragment analyzer (Advanced Analytical technologies, AATI, Ames, Iowa, USA) with the Agilent high sensitivity genomic DNA 50kb kit (Agilent Technologies, Ratingen, Germany). Sequencing was performed on the Ion S5TM system, and data were mapped to the GRCh37/hg19 reference genome. Ion Reporter software (Version 5.12.0.0) was used to determine copy number variations (CNVs), comparing tumor to normal samples, with regions of log2 ratio > + 0.2 or < -0.2 considered significant. A median of the absolute values of all pairwise differences (MAPD) value < 0.35 was used as a quality threshold. Multiplex Immunofluorescence Staining After establishment of all antibodies by immunohistochemistry and monoplex immunfluorescence, an Opal-6-plex (Supp. Table 2 ) immunofluorescence multiplex protocol was performed according to manufacturer’s instructions. The images of the stained multiplex immunofluorescence slides were acquired using a Leica TCS SP8 STED 3X microscope (Leica Microsystems GmbH, Wetzlar, Germany) at the Center for Advanced Imaging (CAI) of the Heinrich Heine University Duesseldorf. Images were captured at 1024x1024 pixels and 8-bit depth. Each antibody with its associated fluorophore was recorded in its own sequence, corresponding to the excitation and emission wavelengths of the Opal fluorophores (Supp. Table 3 ). Image processing was performed in ImageJ (FIJI, Wayne Rasband, National Institutes of Health and the Laboratory for Optical and Computational Instrumentation, LOCI, University of Wisconsin). For each slide two pictures per lesion, if possible, were obtained. Afterwards one region of interest (ROI) was defined regarding the tumor microenvironment. Quantification of the positively stained cells was carried out semi-automatically for αSMA, CD4, CD8, CD19, CD20, CD63, CD109, F4/80, and FoxP3 by a “ Fiji ” macro. In brief, the macro applies a 20 pixel radius “ rolling ball background subtraction ” to the channel of choice, slightly adjusts the dynamic range of the image, thresholds it using the “ Mean ”-autothreshold algorithm, removes single pixel events by the “ despecle ”-function and separates fused regions by a simple “ watershed ” processing. Areas were then counted by the “ analyze particle function ” and detailed readout results (count and area) were used for downstream analysis. The Fiji-macro, exemplary input and result data are provided at: https://github.com/SHaensch/2025_F4I80Quant . To account for both tissue area and total cell density, immune cell counts were normalized by dividing the number of positive immune cells both by the ROI size (in mm²) and the total number of DAPI + cells within that ROI ( 47 , 48 ). This double normalization controls for variations in both sample size and cellularity, providing a standardized measure of immune cell presence per unit area and per cell. CXCL12 and CXCR4 were evaluated separately for epithelium and stroma using the immunoreactivity score (IRS), which measures the amount of positively stained cells (graded 0–4) and the staining intensity (graded 0–3). The IRS score is calculated by multiplying these two values (IRS = Intensity score × Percentage score); resulting in a total score between 0 and 12. Statistical Evaluation Statistical analyses were carried out using GraphPad Prism 8 (GradPad Software Inc., San Diego, USA). Data sets were tested for normality. For comparisons of 2 groups, Student t test or Mann-Whitney-U test was used. More than 2 groups were compared with each other using one-way ANOVA or Kruskal-Wallis test. P values ​​less than 0.05 were considered statistically significant (* p < 0.05, ** p < 0.01, *** p < 0.001). Results A careful morphological evaluation was performed on hematoxylin-eosin-stained slides that were generated from 15 KC and 15 fKPC mice and all identified lesion types were recorded for each mouse. AFL, ADM and PanIN were observed in all KC mice, however none of them had progressed to PDAC. In contrast, all but one of the fKPC mice had already developed PDAC within 2 months in addition to the precursor lesions. In 10 fKPC mice, the full spectrum of the investigated lesions was detected, whereas in 4 only ADM and PDAC were identified, and one mouse developed AFL, ADM and PanIN (Table 1 ). Table 1 Detailed information about the mouse cohort. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, PDAC: Pancreatic ductal adenocarcinoma. Mouse number Mouse genotype Sex Age (months) Extracted lesion types 9 Ptf1a Cre/+ , Kras LSLG12D/+ F 2 AFL, ADM, PanIN 19 Ptf1a Cre/+ , Kras LSLG12D/+ M 2 AFL, ADM, PanIN 21 Ptf1a Cre/+ , Kras LSLG12D/+ M 3 AFL, ADM, PanIN 24 Ptf1a Cre/+ , Kras LSLG12D/+ F 3 AFL, ADM, PanIN 25 Ptf1a Cre/+ , Kras LSLG12D/+ M 3 AFL, ADM, PanIN 4 Ptf1a Cre/+ , Kras LSLG12D/+ M 4 AFL, ADM, PanIN 6 Ptf1a Cre/+ , Kras LSLG12D/+ F 4 AFL, ADM, PanIN 7 Ptf1a Cre/+ , Kras LSLG12D/+ F 4 AFL, ADM, PanIN 17 Ptf1a Cre/+ , Kras LSLG12D/+ F 4 AFL, ADM, PanIN 1 Ptf1a Cre/+ , Kras LSLG12D/+ F 5 AFL, ADM, PanIN 3 Ptf1a Cre/+ , Kras LSLG12D/+ F 5 AFL, ADM, PanIN 11 Ptf1a Cre/+ , Kras LSLG12D/+ F 7 AFL, ADM, PanIN 13 Ptf1a Cre/+ , Kras LSLG12D/+ M 7 AFL, ADM, PanIN 14 Ptf1a Cre/+ , Kras LSLG12D/+ M 7 AFL, ADM, PanIN 16 Ptf1a Cre/+ , Kras LSLG12D/+ M 7 AFL, ADM, PanIN 8 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP M 1 AFL, ADM, PanIN 20 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 1 AFL, ADM, PanIN, PDAC 22 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 1 AFL, ADM, PanIN, PDAC 23 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 1 AFL, ADM, PanIN, PDAC 29 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP M 1 AFL, ADM, PanIN, PDAC 2 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP M 2 AFL, ADM, PanIN, PDAC 5 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 AFL, ADM, PanIN, PDAC 10 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 ADM, PDAC 12 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 AFL, ADM, PanIN, PDAC 15 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 AFL, ADM, PanIN, PDAC 18 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 AFL, ADM, PanIN, PDAC 26 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP M 2 ADM, PDAC 27 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP M 2 ADM, PDAC 28 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 ADM, PDAC 30 Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP F 2 AFL, ADM, PanIN, PDAC Molecular landscape of AFL and ADM Pooled DNA extracted from 96 microdissected lesions, including 26 AFL, 30 ADM, 26 PanIN, and 14 PDAC from 15 KC and 15 fKPC mice together with two normal pancreas samples were subjected to targeted next-generation sequencing. We assessed somatic variants in either a specific or any preneoplastic lesion and in 7/15 KC mice (47%) we found 106 different coding variants in 16/20 sequenced gene hotspots (Suppl. Table 4). In contrast, we found no additional coding alterations in fKPC mice that were somatic to the PDAC or any preneoplastic lesion. Table 2 Number and frequency of affected mice with an altered gene, respectively, shown for each lesion type and each gene investigated with next generation sequencing. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma KC mice (n = 15) Number / frequency (%) of mice with altered genes per lesion type Gene AFL ADM PanIN Arid1A 2 (13.3%) 2 (13.3%) 3 (20%) Alk 0 (0%) 1 (6.6%) 0 (0%) Apc 0 (0%) 2 (13.3%) 2 (13.3%) Braf 0 (0%) 0 (0%) 0 (0%) Cdkn2a 0 (0%) 2 (13.3%) 2 (13.3%) Ctnnb1 0 (0%) 1 (6.6%) 0 (0%) Egfr 1 (6.6%) 1 (6.6%) 1 (6.6%) Fbxw7 1 (6.6%) 1 (6.6%) 1 (6.6%) Fgfr2 1 (6.6%) 1 (6.6%) 1 (6.6%) Gnas 0 (0%) 0 (0%) 0 (0%) Idh1 0 (0%) 0 (0%) 0 (0%) Idh2 0 (0%) 0 (0%) 1 (6.6%) Kras 15 (100%) 15 (100%) 15 (100%) Nras 2 (13.3%) 1 (6.6%) 1 (6.6%) Pik3ca 1 (6.6%) 2 (13.3%) 3 (20%) Pten 1 (6.6%) 0 (0%) 1 (6.6%) Rnf43 2 (13.3%) 3 (20%) 1 (6.6%) Smad4 1 (6.6%) 2 (13.3%) 1 (6.6%) Stk11 0 (0%) 2 (13.3%) 1 (6.6%) Trp53 1 (6.6%) 2 (13.3%) 1 (6.6%) 4/15 (26.6%) AFL, 4/15 (26.6%) ADM and 4/15 (26.6%) PanIN were found to have coding variants in 16/20 genes (Fig. 1). Excluding Kras , the most frequently affected genes were Arid1a, Rnf43 , and Pik3ca , followed by Trp53, Smad4, Nras, Apc, Cdkn2a , Stk11 , while Alk, Ctnnb1, Egfr, Fbxw7, Fgfr2, Idh2 and Pten gene alterations were rare. Coding Braf, Gnas , and Idh1 gene alterations were not found (Table 2 , Fig. 1). AFL in mouse 14, 16 and 17 revealed alterations in only one gene; i.e., Rnf43, Arid1a or Nras , respectively. In contrast, AFL in mouse 24 showed alterations in multiple genes, also found in ADM and PanIN of the same mouse. Similar to mouse 24, ADM in mouse 13 was characterized by alterations in several genes, in contrast to ADM of mouse 9 with only Stk11 and ADM of mouse 17 with only Rnf43 alterations (Fig. 1). Variants of a given gene were unique for the single lesion type. Analysis of immune and stromal microenvironment of AFL and ADM In this study, a total of 198 regions of interest (ROIs, ranging from 7861 to 338512 µm 2 in size) including normal pancreas, AFL, ADM, PanIN, peripheral (pPDAC), and central PDAC (cPDAC) were meticulously examined by the multiplex immunofluorescence method; in detail, 101 ROIs were analyzed for the expression of CD4, CD8, FoxP3, CD19, F4/80 markers, and 97 ROIs for the expression of αSMA, CK19, CD109, CXCR4, and CXCL12. Compared to the normal pancreas, all the analyzed lesion types revealed higher number of immune cell infiltration (p < 0.0001, Fig. 2A). More importantly, the microenvironment of AFL was infiltrated more densely by immune cells (47% of DAPI + cells, 3785 cells/mm 2 ) than that of the other precursor lesions (Fig. 2A). While pPDAC showed the most intense immune cell infiltration in the surrounding tissue (63% of DAPI + cells, 4437 cells/mm 2 ), cPDAC revealed lower immune cell infiltration than AFL, but more than ADM and PanIN (Fig. 2A). The detailed phenotypical analysis revealed that precursor lesions had higher accumulation of adaptive immune cells in their TME than PDAC (precursors: 0.8% of DAPI + cells, 60 cells/mm 2 vs PDAC: 0.2% of DAPI + cells, 17 cells/mm 2 , p < 0.0001). Macrophages were the dominant population of the investigated immune cell types in all lesions and in the normal tissue and represented the largest proportion of all analyzed immune cells and all DAPI + cells in PDAC compared to precursor lesions (p = 0.007) (Table 3 ). Table 3 Distribution of the analyzed immune cells in precursor lesions and PDAC as median + cells/mm 2 and + cells/DAPI + cells x 100. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, pPDAC: Peripheral pancreatic ductal adenocarcinoma, cPDAC: Central pancreatic ductal adenocarcinoma. p < 0.05 is significant. Marker Precursors Median + cells/mm2 ( + cells/DAPI + cells) PDAC Median + cells/mm2 ( + cells/DAPI + cells) p-values F4/80 2832 (38%) 3753 (53%) p = 0.007 CD4 197 (2%) 92 (1%) p = 0.15 CD8 74 (0.9%) 19 (0.3%) p = 0.0005 FoxP3 44 (0.6%) 19 (0.2%) p = 0.003 CD19 21 (0.2%) 3 (0.04%) p = 0.002 Compared to normal tissue and other lesions, AFL revealed higher number of macrophages in the surrounding area than ADM and PanIN, but less than PDAC (Figure 2B and 3, Table 4). Moreover, AFL was infiltrated by higher number of CD4 + helper T cells, FOXP3 + regulatory T cells and CD19 + B cells than all analyzed lesion types, and higher number of CD8 + helper T cells compared to PDAC (Figure 2C-F and 3, Table 4). In addition, ADM and PanIN revealed higher number of CD4 + helper T cells, CD8 + cytotoxic T cells, FOXP3 + regulatory T cells, and CD19 + B cells than PDAC (Figure 2B-2F and 3, Table 4). These results highlight the existence of an immune active microenvironment in precursor lesions, particularly in AFL, which is different from the immunosuppressive microenvironment in PDAC. Table 4 Distribution of the analyzed immune cells in normal tissue, PDAC and its precursors as median + cells/mm 2 and + cells/DAPI + cells x 100. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, pPDAC: Peripheral pancreatic ductal adenocarcinoma, cPDAC: Central pancreatic ductal adenocarcinoma. p < 0.05 is significant. Marker Normal Median + cells/mm2 ( + cells/DAPI + cells) AFL Median + cells/mm2 ( + cells/DAPI + cells) ADM Median + cells/mm2 ( + cells/DAPI + cells) PanIN Median + cells/mm2 ( + cells/DAPI + cells) pPDAC Median + cells/mm2 ( + cells/DAPI + cells) cPDAC Median + cells/mm2 ( + cells/DAPI + cells) p-values F4/80 456 (7%) 3373 (40%) 2690 (36%) 2105 (34%) 4171 (58%) 2982 (42%) p < 0.0001 CD4 41 (0.8%) 349 (4%) 178 (2%) 118 (2%) 108 (2%) 84 (1%) p = 0.04 CD8 14 (0.3%) 64 (0.8%) 76 (0.8%) 71 (0.9%) 35 (0.5%) 9 (0.1%) p = 0.005 FoxP3 12 (0.2%) 106 (1%) 43 (0.5%) 33 (0.5%) 30 (0.5%) 9 (0.1%) p = 0.001 CD19 13 (0.3%) 40 (0.4%) 27 (0.3%) 19 (0.3%) 3 (0.05%) 3 (0.04%) p = 0.07 Interestingly, the precursor lesions in KC mice revealed higher number of adaptive immune cells compared to the precursor lesions in fKPC mice (KC: 9%, 707 positive cells/mm 2 vs fKPC: 4%, 339 positive cells/mm 2 , p = 0.002). This trend was observed in all precursor subtypes and each immune cell type individually. In contrast, the precursor lesions in fKPC mice showed denser macrophage accumulation than KC mice (KC: 24%, 1810 + cells/mm 2 vs fKPC: 40%, 3276 + cells/mm 2 , p = 0.06). All analyzed lesion types demonstrated significantly higher amount of αSMA + stromal cells than the normal pancreas (0.05% of ROI, p < 0.05), with AFL, ADM and peripheral PDAC showing the strongest staining (Fig. 4A). More importantly, the peculiar “swirling” stroma of AFL showed the highest amount of αSMA expression level (26.2% of ROI) followed by peripheral PDAC (13.4% of ROI) (Fig. 4A and 5). Precursor lesions in fKPC mice showed significantly higher expression of αSMA in their TME than in KC Mice (21.2% of ROI vs 5.4% of ROI, p < 0.001). Consistently, high expression levels of CXCL12 were not detected in AFL, indicating a predominance of αSMA + myCAFs over iCAFs. In AFL, ADM, and PanIN, lower expression of CXCL12 and its receptor CXCR4 was observed compared to PDAC, which is likely due to the immunosuppressive and tumor promoting effects of CXCR4 in pancreatic carcinogenesis (CXCL12 IRS - Precursors 4 vs PDAC 8 p = 0.001, CXCR4 IRS - Precursors 8 vs PDAC 12 p = 0.01) (Fig. 4D-E and 6). In addition, stromal cells of the precursor lesions showed less frequent CD109 expression than PDAC, supporting its tumorigenic contribution (80% of pPDAC with CD109 + cells vs 27% of precursors with CD109 + cells p < 0.0001) (Fig. 4F). AFL in human samples Three available human AFL samples were also subjected to multiplex immunofluorescence staining. Similar to mice, AFL in human pancreas tissue was characterized by an increased immune cell infiltration (AFL 175 cells/mm 2 vs. normal 2 cells/mm 2 ) with macrophage predominance (44% of all immune cells) and increased αSMA expression compared to normal tissue (AFL 32% of the ROI vs. normal 1% of the ROI) (Fig. 7). Due to the small number of the cases, statistical analysis could not be performed. We therefore formulated the hypothesis that AFL may represent a site of genetic instability, leading to expression of neoantigens that induce a very early immune response. To test this hypothesis, we performed CNV analysis in 7 AFL, which revealed recurrent alterations in 4 of them (Table 5 , Fig. 8). We then compared these results with those we previously generated in PanIN lesions in a previous study ( 46 ). As shown in Table 5 , recurrent CNV were more frequent in AFL than PanIN lesions. Table 5 CNV analysis in AFL and PanIN, which revealed recurrent alterations in 4 of them. AFL: Atypical flat lesion, PanIN: Pancreatic intraepithelial neoplasia, CNA: Copy number alteration. Sample ID Precursor Lesion Type Gain Loss 148 AFL 7p; 7q; 8q; 14q; 15q; 16q; 19p No CNA 149 AFL No CNA 18q 150 AFL 2p; 2q; 3q; 4p; 4q; 5p; 5q; 6p; 6q; 7p; 7q; 14q; 15q; 18p; 18q; 19p; 19q; 22q 1p; 1q; 2q; 3p; 4q; 5q; 9p; 9p; 12p; 12p; 13q; 16p; 17p; 17q; 20p; 20q; 21q 151 AFL 1p; 1q; 3p; 9p; 9p; 18p; 18q No CNA 156 AFL No CNA No CNA 159 AFL No CNA No CNA 172 AFL No CNA No CNA 120 PanIN high grade 1q 6q; 6q; 9p; 14p; 14p 136 PanIN high grade No CNA No CNA 122 PanIN low grade No CNA No CNA 119 PanIN low grade No CNA No CNA 124 PanIN low grade No CNA No CNA 137 PanIN low grade No CNA No CNA 157 PanIN low grade No CNA No CNA 158 PanIN low grade 3q 15q; 19p 186 PanIN low grade No CNA No CNA 188 PanIN low grade No CNA No CNA 189 PanIN low grade No CNA No CNA Discussion PanIN, IPMN, and MCN, are phenotypically ductal lesions and represent PDAC precursors ( 5 – 7 ). However, increasing evidence in recent studies, particularly using genetically engineered mouse models, suggests the possibility of an alternative carcinogenic pathway, with ADM and AFL as putative PDAC precursors ( 8 – 10 , 20 , 49 – 52 ). A progression model originating in the centroacinar-acinar compartment and resulting in the development of PanIN-like lesions was proposed by our group after a meticulous analysis of 92 pancreatic resection specimens from individuals affected by PDAC and benign conditions, such as chronic pancreatitis and serous cystic neoplasms ( 9 ). In following studies, a direct progression model, which originates from ADM and leads to the development of AFL and PDAC, thus by-passing the “mucinous” PanIN pathway, was suggested ( 8 , 10 ). AFL are atypical tubular structures with enlarged, hyperchromatic nuclei, surrounded by a fibrous and cellular stroma in KC/KPC mice and patients with a familial predisposition for PDAC ( 10 ). Our comprehensive analysis underscores significant differences in immune infiltration, stromal composition, and genetic alterations across pancreatic precursor lesions, with a particular emphasis on atypical flat lesions. These differences offer valuable insights into the early pancreatic tumorigenesis process. Consistent findings in both mouse models and human tissue samples reveal that AFL are characterized by a highly active immune microenvironment. In the AFL, there was a pronounced infiltration of macrophages and adaptive immune cells, including CD4 + helper T cells, CD8 + cytotoxic T cells, and FOXP3 + regulatory T cells, significantly exceeding levels observed in other precursors. In a recent study, innate immune cells, including macrophages and neutrophils, have been identified as playing a pivotal role in the process of acinar trans-differentiation. Conversely, adaptive immune cells, including B- and T-cells, have been shown to facilitate regeneration following injury by stabilizing the inflammatory environment and constraining the proliferation of innate cell populations ( 21 ). The observed trend towards a decrease in the proportion of adaptive immune cells and an increase in the proportion of macrophages from AFL-ADM-PanIN to PDAC suggests that AFL and ADM are still under the influence of the regulatory mechanisms of the adaptive immune system against acinar dedifferentiation stimuli of innate immune cells. The elevated immune presence in AFL and other precursor lesions, suggests that these early lesions exist in a dynamic immune-active state that may represent an opportunity for immune-mediated tumor suppression or clearance. The stromal compartment of AFL also displayed distinctive features, characterized by abundant αSMA + myCAFs forming a “swirling” stromal pattern unique to these lesions. This pattern is associated with a low expression of CXCL12 (and its receptor CXCR4), a chemokine known to be expressed by iCAFs that facilitates immunosuppression and tumor progression in PDAC ( 26 – 31 ). In line with the recent studies, our findings support that the emergence of CXCL12 expressing immunosuppressive iCAFs occurs in the advanced stages of the PDAC carcinogenesis, while the αSMA + myCAFs activation is an early event already occurring in the AFL as an initial precursor lesion ( 22 , 53 ). Additionally, the lower stromal expression of CD109 in precursor lesions compared to PDAC suggests a gradual stromal activation correlating with tumorigenic progression ( 35 , 54 ). Collectively, these stromal characteristics point toward a microenvironment in AFL and other early lesions that may support immune engagement rather than suppression. Importantly, this immunological profile was mirrored in the limited human AFL samples examined by multiplex immunofluorescence. Although statistical analyses were constrained by the small number of cases, human AFL showed increased immune cell infiltration (175 cells/mm² versus 2 cells/mm² in normal tissue) with a predominance of macrophages (44% of immune cells) and a marked increase in αSMA + stromal cells (32% of ROI versus 1% in normal tissue). These findings support the translational relevance of the murine data and suggest that the immune activation observed in AFL is conserved across species. The TME of PDAC and its precursor lesions intricately gets shaped by specific genetic alterations that drive carcinogenesis and modulate stromal and immune interactions. Among the most frequently altered genes in PDAC are KRAS, TP53, CDKN2A , and SMAD4 , which not only initiate tumorigenesis but also exert profound influence on the cellular composition and functional state of the TME. It has been shown that oncogenic KRAS signaling leads to tumor cell proliferation, fibroblast activation, macrophage infiltration, and subsequently acinar cell dedifferentiation ( 55 , 56 ). Additionally, inhibition of active KRAS in PDAC leads to more immunoreactive macrophages and a decrease of myeloid derived suppressor cells in the TME ( 57 ). On the other hand, alterations of TP53 , particularly missense mutations, have been linked to reduced infiltration of cytotoxic CD8⁺ T cells and the upregulation of fibrosis-associated gene programs, contributing to an immunosuppressive microenvironment ( 58 ). In accordance with these findings, we observed that in precursor lesions such as ADM and AFL, the presence of Trp53 mutation is associated with reduced infiltration of adaptive immune cells, accompanied by increased expression of αSMA + in the surrounding stroma. These findings suggest that TP53 mutations not only drive tumorigenesis but also facilitate stromal remodeling and immune evasion at early stages. Beyond the four canonical drivers, PDAC harbors less common but recurrent mutations in genes such as RNF43 , ARID1A , TGFβR2 , GNAS , and PIK3CA ( 59 ). Based on the degree of dysplasia, similar genetic alterations have been detected also in PanIN ( 60 , 61 ). While previous studies have reported alterations in KRAS, CDKN2A , and overexpression of p53 in ADM and AFL ( 10 ), our study is the first to systematically investigate the most common PDAC-associated genes of these alternative precursor lesions using an expanded targeted sequencing panel on meticulously microdissected samples. In the KC mouse model, we identified coding somatic variants in 16 of 20 commonly altered PDAC-associated genes across AFL, ADM, and PanIN lesions. The most frequently mutated genes were Arid1a, Rnf43 , and Pik3ca , followed by Trp53, Smad4, Nras, Apc, Cdkn2a , and Stk11 . The detected genetic alterations in AFL and ADM supports the hypothesis that these lesions, like PanIN, are legitimate alternative precursors to PDAC. In contrast, lesions from fKPC mice showed no additional coding somatic mutations, suggesting that early, concurrent activation of KRAS and TP53 is sufficient to drive carcinogenesis in this model. These findings emphasize the importance of temporal and contextual factors in shaping both genetic evolution and the tumor microenvironment. Building on these findings, we hypothesized that AFL may represent sites of genetic instability that generate neoantigens, thereby triggering an early immune response. Supporting this, CNV analysis in AFL revealed recurrent alterations in more cases compared to PanIN lesions, suggesting AFL are genetically more unstable. As precursor lesions progress to highly genomic instable PDAC, the TME undergoes alterations that facilitate immune evasion ( 53 , 62 – 64 ). Therefore, AFL may represent a transitional stage where genomic instability is sufficient to elicit immune responses, whereas advanced PDAC develops mechanisms to suppress these responses despite ongoing genomic alterations. This study has limitations related to the use of a small gene panel for sequencing, thus not enabling a comprehensive analysis of the genome of ADM and AFL. NGS of laser-captured microdissected tissue allows genetic analysis of lesions that are too small for manual dissection and reduces contamination with non-lesional tissue. However, due to the very low amount of dissected tissue obtained from each single lesion, it was required to pool the same type of lesions, limiting the assessment of genetic heterogeneity. In the TME characterization, we focused on the most relevant players of TME biology; nevertheless, a further characterization of the immune cell subtypes with additional biomarkers is necessary to better understand their exact role in the progression model. In conclusion, while PanIN, IPMN, and MCN are established precursor lesions of PDAC, emerging evidence indicates an alternative pathway originating from the centroacinar-acinar compartment that may also progress to PDAC. Our study highlights the distinct immunological and stromal characteristics of AFL with significant immune cell infiltration and "swirling" stroma. Additionally, both ADM and AFL share key mutations with PanIN and PDAC, supporting their potential roles as precursor lesions. Taken together, these findings highlight the contributions of ADM and AFL to PDAC carcinogenesis, underscored by their unique microenvironments, expression profiles, and early genetic alterations. Abbreviations PDAC Pancreatic ductal adenocarcinoma PanIN Pancreatic intraepithelial neoplasia IPMN Intraductal papillary mucinous neoplasm MCN Mucinous cystic neoplasm ADM Acinar-ductal metaplasia AFL Atypical flat lesion TME Tumor microenvironment, immune and stromal microenvironment of the lesions GEMM Genetically engineered mouse models KC Ptf1a Cre/+ , Kras LSLG12D/+ mice fKPC Ptf1a Cre/+ , Kras LSLG12D/+ , Trp53 LoxP/LoxP mice NGS Next-generation sequencing CAFs Cancer-associated fibroblasts myCAFs Myofibroblastic cancer-associated fibroblasts iCAFs Inflammatory cancer-associated fibroblasts CXCR4 C-X-C motif receptor 4 CXCL12 C-X-C motif ligand 12 TGF-ß1 Transforming growth factor ß1 EGFR Epidermal growth factor receptor PCR Polymerase chain reaction FFPE Formalin-fixed paraffin-embedded LMD Laser captured microdissection ROI Region of interest IRS Immunoreactivity score Declarations Author contributions AY: Writing-original draft, Histological examination, Investigation, Data curation, Validation, Conceptualization. LB: Carrying out experiments, Formal analyses, Investigation, Data curation, Visualization, Validation, Writing. KH: Bioinformatic analysis, Writing. SH: Visualization, Writing. WG: NGS analysis. MS: Supervision for Multiplex analysis. LH: Conceptualization, Writing. IE: Project administration, Design, Histological examination, Conceptualization, Writing. All authors read and approved the final manuscript. Acknowledgements We thank all the members of Esposito Working Group, Institute of Pathology, University Hospital Duesseldorf for their support. We also thank Johannes Köster, University of Duisburg-Essen, for his help configuring events for Varlociraptor. This work represents the doctoral thesis of one of the authors (LB). Funding The experimental phase of this research project was supported by an MD-scholarship from the Düsseldorf School of Oncology (DSO). 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Supplementary Files SupplementaryTable1.xlsx SupplementaryTables2and3.docx SupplementaryTable4.xlsx Cite Share Download PDF Status: Published Journal Publication published 13 Jan, 2026 Read the published version in Journal of Experimental & Clinical Cancer Research → Version 1 posted Editorial decision: Revision requested 13 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviews received at journal 02 Oct, 2025 Reviewers agreed at journal 26 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers invited by journal 23 Sep, 2025 Editor assigned by journal 23 Sep, 2025 Submission checks completed at journal 23 Sep, 2025 First submitted to journal 19 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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22:02:45","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":211275,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/f8772860d373384125e89b37.html"},{"id":92901376,"identity":"4a39aeb7-0c22-4275-a38a-542cf5c7cbca","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":395767,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of coding variant consequences summarized for 16/20 examined genes for each KC mouse and lesion type. The left side shows columns grouped by lesion type; the right side grouped by specific mouse. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia PDAC: Pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/5c996054c8afd954668da7af.png"},{"id":92901547,"identity":"4e63548a-325b-4800-bfe7-48b4bd506248","added_by":"auto","created_at":"2025-10-06 22:02:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":317626,"visible":true,"origin":"","legend":"\u003cp\u003eA. Normalized immune cell counts to the size of ROIs (mm\u003csup\u003e2\u003c/sup\u003e) and the total DAPI\u003csup\u003e+\u003c/sup\u003e cell number. AFLs showed the densest immune cell infiltration in precursor lesions. B-F. Detailed analysis of the immune cells with F4/80, CD4, CD8, FOXP3 and CD19 markers in normal tissue, PDAC and its precursors. *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001. \u0026nbsp;AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC: Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/0fa6b846c585d0a38882343c.png"},{"id":92901379,"identity":"2f6477d8-2717-4f40-86f6-7e7ff298f251","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":912439,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images of multiplex immunofluorescence staining for F4/80, CD4, CD8, FOXP3 and CD19 markers. F4/80: pink, CD4: red, CD8: cyan, FoxP3: yellow, CD19: green, DAPI: gray. Magnification 20x. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC: Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/593c06177c1cc4f3af44514d.png"},{"id":92901548,"identity":"5691f75d-6391-4277-923f-87ae8cf4cb86","added_by":"auto","created_at":"2025-10-06 22:02:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":189170,"visible":true,"origin":"","legend":"\u003cp\u003eA. Comparison of αSMA stained areas in normal tissue, PDAC and its precursors. B-E. CXCL12 and CXCR4 expression analysis in epithelium and stromal tissue. F. Frequency of the lesions with CD109\u003csup\u003e+\u003c/sup\u003e cells in surrounding tissue. *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001. IRS: Immun reactivity score, AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC: Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/b09feb1ea2cae8791d3e0270.png"},{"id":92901404,"identity":"80347250-afc4-4355-bd42-3fd984938463","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":904193,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images of multiplex immunofluorescence staining for αSMA and CK19. αSMA: red, CK19: green, DAPI: gray. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC: Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/10673dbf8fb43a709d71753b.png"},{"id":92901405,"identity":"59df9c46-018e-4bfb-9a01-dc3af0e8d78e","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":877906,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images of multiplex immunofluorescence staining for CXCL12 and CXCR4 markers. CXL12: cyan, CXR4: pink, DAPI: gray. Magnification 20x. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC: Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/02df9a10365c20f8bc6e5bb2.png"},{"id":92901549,"identity":"f14e3e1b-8a73-40eb-840a-20a606d542d6","added_by":"auto","created_at":"2025-10-06 22:02:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":584812,"visible":true,"origin":"","legend":"\u003cp\u003eA. Immune cell infiltration in human AFL. CD4: red, CD8: cyan, CD20: green, CD68: pink, FoxP3: yellow, DAPI: gray. Magnification 20x. B. αSMA expression in human AFL. αSMA: red, CK19: green, CXCL12: cyan, CXCR4: pink, CD109: yellow, DAPI: gray. Magnification 20x.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/e98a7416dda254245c6d90c6.png"},{"id":92901394,"identity":"9e4341d0-4df5-4894-a775-06057cdd344f","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":385803,"visible":true,"origin":"","legend":"\u003cp\u003eCopy number variation (CNV) analysis in AFL and PanIN lesions. A. CNVs were detected in 4 out of 7 AFL samples (57%), indicating a relatively high frequency of genomic alterations. B. CNVs were present in 2 out of 11 PanIN samples (18%). Red color shows copy number gains and blue represents copy number losses (46). AFL: Atypical flat lesion, PanIN: Pancreatic intraepithelial neoplasia.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/d4385a824073615cf2cba962.png"},{"id":100614753,"identity":"dad9b6a8-aa7f-4f4a-b180-9880b82b966f","added_by":"auto","created_at":"2026-01-19 17:24:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5888309,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/6641be10-5556-4285-a4bc-8c6d633f3f6d.pdf"},{"id":92901381,"identity":"644ac210-2ea3-47a6-bb33-bbce6b8e9eca","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12964,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/02981608e6530381e58c61a3.xlsx"},{"id":92901378,"identity":"c3e6589d-21c7-4bcb-a650-4393b99f2966","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22182,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables2and3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/5a87ba8be8908a04a3664f02.docx"},{"id":92901382,"identity":"8f901672-e463-4d21-93d0-44b512ab4e3a","added_by":"auto","created_at":"2025-10-06 21:54:44","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":47997,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7660097/v1/0943b8e937f3148b7fc03215.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Immunological and Molecular Insights into Acinar-Ductal Metaplasia and Atypical Flat Lesions as Precursor Lesions of Pancreatic Ductal Adenocarcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer with an increasing incidence and a 5-year survival rate of 11-13.3% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It is predicted to become the second leading cause of cancer-related deaths by 2030 due to advanced disease at diagnosis and limited treatment options (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA stepwise progression model from precursor lesions to carcinoma has been described. The most well-known precursor lesions of PDAC with ductal differentiation are pancreatic intraepithelial neoplasias (PanIN), intraductal papillary mucinous neoplasms (IPMN), and mucinous cystic neoplasms (MCN) (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Additionally, acinar-ductal metaplasia (ADM) and atypical flat lesions (AFL) arising from acinar cells have been proposed as potential precursor lesions of PDAC in genetically engineered mouse models (GEMMs), and lesions resembling mouse AFL have been identified in patients with familial risk of PDAC (\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). PanIN, ADM, and AFL are microscopic lesions in contrast to macroscopically visible IPMN and MCN. PanIN is characterized by flat or papillary architecture with varying degrees of cytological atypia and mucin production (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). ADM exhibits tubular structures surrounded by fibrosis without significant cytological atypia. Given its origin from acinar cells that undergo metaplasia into ductal cells, ADM can express both acinar and ductal cell markers in early stages. AFL is frequently found in ADM areas and characterized by a flat epithelium with ductal differentiation consisting of atypical cells with surrounding abundant swirl-like stroma (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Unlike the other PDAC precursors, the biological significance of ADM and AFL in PDAC carcinogenesis is still not well characterized.\u003c/p\u003e\u003cp\u003ePDAC forms an immunosuppressive tumor microenvironment (TME) during carcinogenesis, which is characterized by complex stromal and immunological interactions. Tumor-associated macrophages represent the dominant immune cell population of the TME and play a critical role in the development of PDAC, and the progression of its precursor lesions (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, the function of the adaptive immune system cells including antigen-presenting cells, CD4\u003csup\u003e+\u003c/sup\u003e helper T cells, and CD8\u003csup\u003e+\u003c/sup\u003e cytotoxic T cells is often suppressed by the neoplastic cells via various mechanisms, such as the activation of immunosuppressive FOXP3\u003csup\u003e+\u003c/sup\u003e regulatory T cells and myeloid-derived suppressor cells or the expression of immune checkpoint molecules (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Acinar-ductal metaplasia occurs as a reversible event in response to acute pancreatic injury and inflammation, but becomes irreversible in the presence of chronic injury or oncogenic \u003cem\u003eKRAS\u003c/em\u003e mutation and forms PanIN-like lesions as an initial event of PDAC carcinogenesis (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). It has been reported that the interactions between acinar cells and infiltrating immune cells, especially macrophages, determines the extent of ADM formation after acute pancreatic injury (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Depletion of macrophages in the early regenerative stages resulted in a decrease of ADM development, whereas depletion in the late stages caused a delay of pancreatic repair leading to chronic inflammation. Moreover, it has been shown that innate immune cells such as macrophages and neutrophils promote and maintain acinar trans-differentiation, while adaptive immune cells such as B- and T-cells support normal regeneration after injury by stabilizing the inflammatory environment and limiting the numbers of innate cell populations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). There is no detailed data about the immune microenvironment of AFL, except for macrophage accumulation around of the lesions (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCancer-associated fibroblasts (CAFs) are an additional significant, heterogeneous component of the TME in PDAC involved in the formation of the desmoplastic stroma and with complex growth- and immune cell-modulating functions (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). It is known that after pancreatic injury, acinar cells recruit stromal fibroblasts, which in turn play a tumorigenic role with the surrounding macrophages (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Moreover, it has been recently reported that CAFs induce acinar to ductal cell trans-differentiation in acinar and mouse CAFs co-cultures, suggesting that CAFs secretome might play a significant role in ADM development and PDAC initiation (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Furthermore, AFL, which are frequently found in ADM areas, have been reported to have a special swirl-like stroma composed of αSMA expressing myofibroblastic cancer-associated fibroblasts (myCAFs) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe CXCL12-CXR4 axis has been reported as a key player for the emergence of a tumor-promoting and immunosuppressive TME in PDAC. CXCL12 (C-X-C motif ligand 12) is a chemotactic chemokine, a marker for inflammatory CAFs (iCAFs), has been shown to promote cell survival, proliferation, immune evasion, angiogenesis, and chemoresistance in PDAC via its receptor CXCR4 (C-X-C motif receptor 4). CXCL12 is expressed primarily by activated fibroblasts in the stroma, while CXCR4 is expressed by the tumor cells (\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). CXCL12 and its receptors are considered as potential therapeutic targets in PDAC; although their expression has been described in PanIN and IPMN (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), no data are available regarding their role in ADM and AFL. In addition, CD109, a glycophosphatidylinositol-binding membrane protein, interacts with TGF-\u0026szlig;1 (transforming growth factor \u0026szlig;1) and EGFR (epidermal growth factor receptor), leading to cell growth, cell differentiation or epithelial to mesenchymal transition (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In PDAC, CD109 can be expressed both in tumor cells and in the surrounding stroma, and it is associated with shorter disease-free and overall survival, tumor progression and higher rates of distant metastases (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). CD109 therefore represents a possible prognostic marker for PDAC, but its exact role in PDAC carcinogenesis needs further investigation.\u003c/p\u003e\u003cp\u003eIn this study, we aimed at characterizing the role of ADM and AFL as alternative PDAC precursors focusing on the composition of their TME and their genetic landscape.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCollective\u003c/h2\u003e\u003cp\u003eThe genetically modified mouse (GEMM) collective was maintained at the Central Facility for Animal Research and Scientific Animal Welfare Tasks (ZETT) of the Heinrich Heine University in D\u0026uuml;sseldorf. The collective consisting of 15 KC (\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e) and 15 KPC-like mice (\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e, for simplicity hereafter referred as fKPC mice) were sacrificed at different time points ranging from 1 to 7 months (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Harvested pancreas tissues were fixed in formalin and embedded in paraffin after tissue processing. Genotype confirmation was performed by polymerase chain reaction (PCR) analysis (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Human formalin-fixed paraffin-embedded (FFPE) blocks containing AFL were retrieved from the archive of the Institute of Pathology at the University Hospital D\u0026uuml;sseldorf. Tissue sections (1.5 \u0026micro;m) were subjected to hematoxylin-eosin staining and examined meticulously under the light microscope by two experienced pathologists (AY, IE) for lesions\u0026rsquo; classification and annotation.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLaser-captured microdissection and Next-Generation Sequencing\u003c/h3\u003e\n\u003cp\u003eA series of at least 15 FFPE sections with a thickness of 8 \u0026micro;m were generated for laser captured microdissection. Available AFL, ADM, PanIN, and PDAC areas were extracted using Zeiss Palm Microbeam Laser captured microdissection (LMD) microscope (Carl Zeiss Microscopy GmbH, Jena, Germany). At least 250,000 \u0026micro;m\u0026sup2; of total tissue was excised for each lesion type per mouse. The same type lesions were pooled across all previously prepared sections. In addition, normal pancreatic tissue was collected from one KC and one fKPC mouse as reference.\u003c/p\u003e\u003cp\u003eDNA isolation from the tissues obtained by LMD was performed using QiAMP\u0026reg; DNA Micro Kit (Qiagen, Hilden, Germany) according to the manufacturer\u0026rsquo;s instructions. Libraries for IonTorrent NGS system were created using Ion AmpliSeq Library Kit 2.0 (ThermoFisher Scientific, Waltham, USA) for a 20 genes panel, which includes hotspots of the genes that are relevant for PDAC (Supp. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Isolated DNAs were amplified via PCR and stripped to Ion Xpress Barcodes (ThermoFisher Scientific, Waltham, USA). After purification using AMPure XP Beads (Fischer Scientific, Hampton, USA) acquired libraries were quantitated using the Ion Library TaqMan Quantitation Kit (ThermoFisher Scientific, Waltham, USA) in StepOnePlus Ultra, Real-Time PCR cycler (ThermoFisher Scientific, Waltham, USA) following the manufacturer's protocol. DNA-concentration was adjusted 100 in pM to perform massive parallel sequencing at the institute's molecular pathology laboratory on the Ion S5 system with suitable Ion chips and sequencing kits (ThermoFisher Scientific, Waltham, USA). Acquired primary data was checked for quality sufficiency and extracted as FASTQs.\u003c/p\u003e\u003cp\u003eSequencing data was evaluated using the DNA-Seq-Varlociraptor pipeline (version 3.22.0) (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). First, raw sequencing data was aligned to the murine reference genome mus musculus GRCm39 using BWA mem software and ensembl (release 108) (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eversion 0.7.17\u003c/span\u003e) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Then, candidate variants were called using freebayes (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eversion 1.3.6\u003c/span\u003e) (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) and delly (version 1.1) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) and then processed by Varlociraptor (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Varlociraptor is a generic, uncertainty-aware variant caller calculating maximum a posteriori probabilities for complex events. For getting probabilities and evaluating variants, we defined somatic events as following: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Non-zero allele frequency (AF) in one preneoplastic lesion, but not the others. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Non-zero AF in any preneoplastic lesion. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) If tumor sample was available: non-zero AF in tumor but not lesional samples and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) non-zero AF in tumor and any lesional sample. All events include being absent in the normal pancreas samples, having a resolution of 1% and 5% local false discovery rate (fdr) - control threshold. Variants with an AF below 5% were excluded from analysis and remaining variants annotated using ensembl variant effect predictor (vep) (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). We investigated the coding variants (defined as those annotated with a HGSVp value) and further filtered to exclude those appearing on only one strand, mutations with low amplicon coverage (\u0026lt;\u0026thinsp;100x), and variants present in only one of two overlapping amplicons. The variants were manually evaluated and filtered by trained experts from the molecular pathology department for sequencing artifacts and known sequencing errors typical of semiconductor-based methods, such as frameshifts in base repeats, using Integrative Genomics Viewer (IGV, source) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEstimation of DNA copy number variation in human AFL by low-coverage whole-genome sequencing\u003c/h3\u003e\n\u003cp\u003eSeven microdissected human AFL were analyzed by low-coverage whole genome sequencing as previously described (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGenomic DNA from FFPE samples was amplified using the Ampli1\u0026trade; WGA kit (Menarini Silicon Biosystems, Bologna, Italy) and purified with SPRIselect beads (Beckman Coulter, Lahntal, Germany). Libraries were prepared using the Ampli1\u0026trade; low-pass kit (Menarini Silicon Biosystems). The final library concentration was determined on the fragment analyzer (Advanced Analytical technologies, AATI, Ames, Iowa, USA) with the Agilent high sensitivity genomic DNA 50kb kit (Agilent Technologies, Ratingen, Germany). Sequencing was performed on the Ion S5TM system, and data were mapped to the GRCh37/hg19 reference genome. Ion Reporter software (Version 5.12.0.0) was used to determine copy number variations (CNVs), comparing tumor to normal samples, with regions of log2 ratio\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;0.2 or \u0026lt; -0.2 considered significant. A median of the absolute values of all pairwise differences (MAPD) value\u0026thinsp;\u0026lt;\u0026thinsp;0.35 was used as a quality threshold.\u003c/p\u003e\n\u003ch3\u003eMultiplex Immunofluorescence Staining\u003c/h3\u003e\n\u003cp\u003eAfter establishment of all antibodies by immunohistochemistry and monoplex immunfluorescence, an Opal-6-plex (Supp. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) immunofluorescence multiplex protocol was performed according to manufacturer\u0026rsquo;s instructions. The images of the stained multiplex immunofluorescence slides were acquired using a Leica TCS SP8 STED 3X microscope (Leica Microsystems GmbH, Wetzlar, Germany) at the Center for Advanced Imaging (CAI) of the Heinrich Heine University Duesseldorf. Images were captured at 1024x1024 pixels and 8-bit depth. Each antibody with its associated fluorophore was recorded in its own sequence, corresponding to the excitation and emission wavelengths of the Opal fluorophores (Supp. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Image processing was performed in ImageJ (FIJI, Wayne Rasband, National Institutes of Health and the Laboratory for Optical and Computational Instrumentation, LOCI, University of Wisconsin). For each slide two pictures per lesion, if possible, were obtained. Afterwards one region of interest (ROI) was defined regarding the tumor microenvironment. Quantification of the positively stained cells was carried out semi-automatically for αSMA, CD4, CD8, CD19, CD20, CD63, CD109, F4/80, and FoxP3 by a \u0026ldquo;\u003cem\u003eFiji\u003c/em\u003e\u0026rdquo; macro. In brief, the macro applies a 20 pixel radius \u0026ldquo;\u003cem\u003erolling ball background subtraction\u003c/em\u003e\u0026rdquo; to the channel of choice, slightly adjusts the dynamic range of the image, thresholds it using the \u0026ldquo;\u003cem\u003eMean\u003c/em\u003e\u0026rdquo;-autothreshold algorithm, removes single pixel events by the \u0026ldquo;\u003cem\u003edespecle\u003c/em\u003e\u0026rdquo;-function and separates fused regions by a simple \u0026ldquo;\u003cem\u003ewatershed\u003c/em\u003e\u0026rdquo; processing. Areas were then counted by the \u0026ldquo;\u003cem\u003eanalyze particle function\u003c/em\u003e\u0026rdquo; and detailed readout results (count and area) were used for downstream analysis. The Fiji-macro, exemplary input and result data are provided at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/SHaensch/2025_F4I80Quant\u003c/span\u003e\u003cspan address=\"https://github.com/SHaensch/2025_F4I80Quant\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. To account for both tissue area and total cell density, immune cell counts were normalized by dividing the number of positive immune cells both by the ROI size (in mm\u0026sup2;) and the total number of DAPI\u003csup\u003e+\u003c/sup\u003e cells within that ROI (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). This double normalization controls for variations in both sample size and cellularity, providing a standardized measure of immune cell presence per unit area and per cell. CXCL12 and CXCR4 were evaluated separately for epithelium and stroma using the immunoreactivity score (IRS), which measures the amount of positively stained cells (graded 0\u0026ndash;4) and the staining intensity (graded 0\u0026ndash;3). The IRS score is calculated by multiplying these two values (IRS\u0026thinsp;=\u0026thinsp;Intensity score \u0026times; Percentage score); resulting in a total score between 0 and 12.\u003c/p\u003e\n\u003ch3\u003eStatistical Evaluation\u003c/h3\u003e\n\u003cp\u003eStatistical analyses were carried out using GraphPad Prism 8 (GradPad Software Inc., San Diego, USA). Data sets were tested for normality. For comparisons of 2 groups, Student t test or Mann-Whitney-U test was used. More than 2 groups were compared with each other using one-way ANOVA or Kruskal-Wallis test. P values ​​less than 0.05 were considered statistically significant (* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA careful morphological evaluation was performed on hematoxylin-eosin-stained slides that were generated from 15 KC and 15 fKPC mice and all identified lesion types were recorded for each mouse. AFL, ADM and PanIN were observed in all KC mice, however none of them had progressed to PDAC. In contrast, all but one of the fKPC mice had already developed PDAC within 2 months in addition to the precursor lesions. In 10 fKPC mice, the full spectrum of the investigated lesions was detected, whereas in 4 only ADM and PDAC were identified, and one mouse developed AFL, ADM and PanIN (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDetailed information about the mouse cohort. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, PDAC: Pancreatic ductal adenocarcinoma.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMouse number\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMouse genotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAge (months)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eExtracted lesion types\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e24\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eADM, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eADM, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e27\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eADM, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eADM, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e30\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAFL, ADM, PanIN, PDAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMolecular landscape of AFL and ADM\u003c/h3\u003e\n\u003cp\u003ePooled DNA extracted from 96 microdissected lesions, including 26 AFL, 30 ADM, 26 PanIN, and 14 PDAC from 15 KC and 15 fKPC mice together with two normal pancreas samples were subjected to targeted next-generation sequencing. We assessed somatic variants in either a specific or any preneoplastic lesion and in 7/15 KC mice (47%) we found 106 different coding variants in 16/20 sequenced gene hotspots (Suppl. Table\u0026nbsp;4). In contrast, we found no additional coding alterations in fKPC mice that were somatic to the PDAC or any preneoplastic lesion.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNumber and frequency of affected mice with an altered gene, respectively, shown for each lesion type and each gene investigated with next generation sequencing. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia PanIN: Pancreatic intraepithelial neoplasia pPDAC Peripheral pancreatic ductal adenocarcinoma cPDAC: Central pancreatic ductal adenocarcinoma\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKC mice (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eNumber / frequency (%) of mice with altered genes per lesion type\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eADM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePanIN\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArid1A\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (20%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlk\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eApc\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBraf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCdkn2a\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCtnnb1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEgfr\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFbxw7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFgfr2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGnas\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIdh1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIdh2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKras\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNras\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePik3ca\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (20%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePten\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRnf43\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmad4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStk11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTrp53\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e4/15 (26.6%) AFL, 4/15 (26.6%) ADM and 4/15 (26.6%) PanIN were found to have coding variants in 16/20 genes (Fig.\u0026nbsp;1). Excluding \u003cem\u003eKras\u003c/em\u003e, the most frequently affected genes were \u003cem\u003eArid1a, Rnf43\u003c/em\u003e, and \u003cem\u003ePik3ca\u003c/em\u003e, followed by \u003cem\u003eTrp53, Smad4, Nras, Apc, Cdkn2a\u003c/em\u003e, \u003cem\u003eStk11\u003c/em\u003e, while \u003cem\u003eAlk, Ctnnb1, Egfr, Fbxw7, Fgfr2, Idh2\u003c/em\u003e and \u003cem\u003ePten\u003c/em\u003e gene alterations were rare. Coding \u003cem\u003eBraf, Gnas\u003c/em\u003e, and \u003cem\u003eIdh1\u003c/em\u003e gene alterations were not found (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003eAFL in mouse 14, 16 and 17 revealed alterations in only one gene; i.e., \u003cem\u003eRnf43, Arid1a\u003c/em\u003e or \u003cem\u003eNras\u003c/em\u003e, respectively. In contrast, AFL in mouse 24 showed alterations in multiple genes, also found in ADM and PanIN of the same mouse. Similar to mouse 24, ADM in mouse 13 was characterized by alterations in several genes, in contrast to ADM of mouse 9 with only \u003cem\u003eStk11\u003c/em\u003e and ADM of mouse 17 with only \u003cem\u003eRnf43\u003c/em\u003e alterations (Fig.\u0026nbsp;1). Variants of a given gene were unique for the single lesion type.\u003c/p\u003e\n\u003ch3\u003eAnalysis of immune and stromal microenvironment of AFL and ADM\u003c/h3\u003e\n\u003cp\u003eIn this study, a total of 198 regions of interest (ROIs, ranging from 7861 to 338512 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e in size) including normal pancreas, AFL, ADM, PanIN, peripheral (pPDAC), and central PDAC (cPDAC) were meticulously examined by the multiplex immunofluorescence method; in detail, 101 ROIs were analyzed for the expression of CD4, CD8, FoxP3, CD19, F4/80 markers, and 97 ROIs for the expression of αSMA, CK19, CD109, CXCR4, and CXCL12.\u003c/p\u003e\u003cp\u003eCompared to the normal pancreas, all the analyzed lesion types revealed higher number of immune cell infiltration (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;2A). More importantly, the microenvironment of AFL was infiltrated more densely by immune cells (47% of DAPI\u003csup\u003e+\u003c/sup\u003e cells, 3785 cells/mm\u003csup\u003e2\u003c/sup\u003e) than that of the other precursor lesions (Fig.\u0026nbsp;2A). While pPDAC showed the most intense immune cell infiltration in the surrounding tissue (63% of DAPI\u003csup\u003e+\u003c/sup\u003e cells, 4437 cells/mm\u003csup\u003e2\u003c/sup\u003e), cPDAC revealed lower immune cell infiltration than AFL, but more than ADM and PanIN (Fig.\u0026nbsp;2A).\u003c/p\u003e\u003cp\u003eThe detailed phenotypical analysis revealed that precursor lesions had higher accumulation of adaptive immune cells in their TME than PDAC (precursors: 0.8% of DAPI\u003csup\u003e+\u003c/sup\u003e cells, 60 cells/mm\u003csup\u003e2\u003c/sup\u003e vs PDAC: 0.2% of DAPI\u003csup\u003e+\u003c/sup\u003e cells, 17 cells/mm\u003csup\u003e2\u003c/sup\u003e, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Macrophages were the dominant population of the investigated immune cell types in all lesions and in the normal tissue and represented the largest proportion of all analyzed immune cells and all DAPI\u003csup\u003e+\u003c/sup\u003e cells in PDAC compared to precursor lesions (p\u0026thinsp;=\u0026thinsp;0.007) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of the analyzed immune cells in precursor lesions and PDAC as median\u003csup\u003e+\u003c/sup\u003ecells/mm\u003csup\u003e2\u003c/sup\u003e and \u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells x 100. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, pPDAC: Peripheral pancreatic ductal adenocarcinoma, cPDAC: Central pancreatic ductal adenocarcinoma. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is significant. \u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrecursors\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePDAC\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-values\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eF4/80\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2832 (38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3753 (53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e197 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.0005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFoxP3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (0.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (0.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eCompared to normal tissue and other lesions, AFL revealed higher number of macrophages in the surrounding area than ADM and PanIN, but less than PDAC (Figure 2B and 3, Table 4). Moreover, AFL was infiltrated by higher number of CD4\u003csup\u003e+\u003c/sup\u003e helper T cells, FOXP3\u003csup\u003e+\u003c/sup\u003e regulatory T cells and CD19\u003csup\u003e+\u003c/sup\u003e B cells than all analyzed lesion types, and higher number of CD8\u003csup\u003e+\u003c/sup\u003e helper T cells compared to PDAC (Figure 2C-F and 3, Table 4). In addition, ADM and PanIN revealed higher number of CD4\u003csup\u003e+\u003c/sup\u003e helper T cells, CD8\u003csup\u003e+\u003c/sup\u003e cytotoxic T cells, FOXP3\u003csup\u003e+\u003c/sup\u003e regulatory T cells, and CD19\u003csup\u003e+\u003c/sup\u003e B cells than PDAC (Figure 2B-2F and 3, Table 4). These results highlight the existence of an immune active microenvironment in precursor lesions, particularly in AFL, which is different from the immunosuppressive microenvironment in PDAC.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of the analyzed immune cells in normal tissue, PDAC and its precursors as median\u003csup\u003e+\u003c/sup\u003ecells/mm\u003csup\u003e2\u003c/sup\u003e and \u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells x 100. AFL: Atypical flat lesion, ADM: Acinar-ductal metaplasia, PanIN: Pancreatic intraepithelial neoplasia, pPDAC: Peripheral pancreatic ductal adenocarcinoma, cPDAC: Central pancreatic ductal adenocarcinoma. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is significant.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eADM\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePanIN\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003epPDAC\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ecPDAC\u003c/p\u003e\u003cp\u003eMedian\u003csup\u003e+\u003c/sup\u003ecells/mm2 (\u003csup\u003e+\u003c/sup\u003ecells/DAPI\u003csup\u003e+\u003c/sup\u003e cells)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep-values\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eF4/80\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e456 (7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3373 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2690 (36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2105 (34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4171 (58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2982 (42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e349 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e178 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e118 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e108 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e84 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFoxP3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19 (0.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (0.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3 (0.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInterestingly, the precursor lesions in KC mice revealed higher number of adaptive immune cells compared to the precursor lesions in fKPC mice (KC: 9%, 707 positive cells/mm\u003csup\u003e2\u003c/sup\u003e vs fKPC: 4%, 339 positive cells/mm\u003csup\u003e2\u003c/sup\u003e, p\u0026thinsp;=\u0026thinsp;0.002). This trend was observed in all precursor subtypes and each immune cell type individually. In contrast, the precursor lesions in fKPC mice showed denser macrophage accumulation than KC mice (KC: 24%, 1810\u003csup\u003e+\u003c/sup\u003ecells/mm\u003csup\u003e2\u003c/sup\u003e vs fKPC: 40%, 3276\u003csup\u003e+\u003c/sup\u003ecells/mm\u003csup\u003e2\u003c/sup\u003e, p\u0026thinsp;=\u0026thinsp;0.06).\u003c/p\u003e\u003cp\u003eAll analyzed lesion types demonstrated significantly higher amount of αSMA\u003csup\u003e+\u003c/sup\u003e stromal cells than the normal pancreas (0.05% of ROI, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with AFL, ADM and peripheral PDAC showing the strongest staining (Fig.\u0026nbsp;4A). More importantly, the peculiar \u0026ldquo;swirling\u0026rdquo; stroma of AFL showed the highest amount of αSMA expression level (26.2% of ROI) followed by peripheral PDAC (13.4% of ROI) (Fig.\u0026nbsp;4A and 5). Precursor lesions in fKPC mice showed significantly higher expression of αSMA in their TME than in KC Mice (21.2% of ROI vs 5.4% of ROI, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Consistently, high expression levels of CXCL12 were not detected in AFL, indicating a predominance of αSMA\u003csup\u003e+\u003c/sup\u003e myCAFs over iCAFs. In AFL, ADM, and PanIN, lower expression of CXCL12 and its receptor CXCR4 was observed compared to PDAC, which is likely due to the immunosuppressive and tumor promoting effects of CXCR4 in pancreatic carcinogenesis (CXCL12 IRS - Precursors 4 vs PDAC 8 p\u0026thinsp;=\u0026thinsp;0.001, CXCR4 IRS - Precursors 8 vs PDAC 12 p\u0026thinsp;=\u0026thinsp;0.01) (Fig.\u0026nbsp;4D-E and 6). In addition, stromal cells of the precursor lesions showed less frequent CD109 expression than PDAC, supporting its tumorigenic contribution (80% of pPDAC with CD109\u003csup\u003e+\u003c/sup\u003e cells vs 27% of precursors with CD109\u003csup\u003e+\u003c/sup\u003e cells p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;4F).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAFL in human samples\u003c/h2\u003e\u003cp\u003eThree available human AFL samples were also subjected to multiplex immunofluorescence staining. Similar to mice, AFL in human pancreas tissue was characterized by an increased immune cell infiltration (AFL 175 cells/mm\u003csup\u003e2\u003c/sup\u003e vs. normal 2 cells/mm\u003csup\u003e2\u003c/sup\u003e) with macrophage predominance (44% of all immune cells) and increased αSMA expression compared to normal tissue (AFL 32% of the ROI vs. normal 1% of the ROI) (Fig.\u0026nbsp;7). Due to the small number of the cases, statistical analysis could not be performed.\u003c/p\u003e\u003cp\u003eWe therefore formulated the hypothesis that AFL may represent a site of genetic instability, leading to expression of neoantigens that induce a very early immune response. To test this hypothesis, we performed CNV analysis in 7 AFL, which revealed recurrent alterations in 4 of them (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;8). We then compared these results with those we previously generated in PanIN lesions in a previous study (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). As shown in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, recurrent CNV were more frequent in AFL than PanIN lesions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCNV analysis in AFL and PanIN, which revealed recurrent alterations in 4 of them. AFL: Atypical flat lesion, PanIN: Pancreatic intraepithelial neoplasia, CNA: Copy number alteration.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrecursor Lesion Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLoss\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e148\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7p; 7q; 8q; 14q; 15q; 16q; 19p\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e149\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18q\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e150\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2p; 2q; 3q; 4p; 4q; 5p; 5q; 6p; 6q; 7p; 7q; 14q; 15q; 18p; 18q; 19p; 19q; 22q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1p; 1q; 2q; 3p; 4q; 5q; 9p; 9p; 12p; 12p; 13q; 16p; 17p; 17q; 20p; 20q; 21q\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e151\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1p; 1q; 3p; 9p; 9p; 18p; 18q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e156\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e159\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e172\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e120\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN high grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6q; 6q; 9p; 14p; 14p\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e136\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN high grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e122\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e119\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e124\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e137\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e157\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e158\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3q\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15q; 19p\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e186\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e188\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e189\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePanIN low grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo CNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePanIN, IPMN, and MCN, are phenotypically ductal lesions and represent PDAC precursors (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, increasing evidence in recent studies, particularly using genetically engineered mouse models, suggests the possibility of an alternative carcinogenic pathway, with ADM and AFL as putative PDAC precursors (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA progression model originating in the centroacinar-acinar compartment and resulting in the development of PanIN-like lesions was proposed by our group after a meticulous analysis of 92 pancreatic resection specimens from individuals affected by PDAC and benign conditions, such as chronic pancreatitis and serous cystic neoplasms (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In following studies, a direct progression model, which originates from ADM and leads to the development of AFL and PDAC, thus by-passing the \u0026ldquo;mucinous\u0026rdquo; PanIN pathway, was suggested (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). AFL are atypical tubular structures with enlarged, hyperchromatic nuclei, surrounded by a fibrous and cellular stroma in KC/KPC mice and patients with a familial predisposition for PDAC (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur comprehensive analysis underscores significant differences in immune infiltration, stromal composition, and genetic alterations across pancreatic precursor lesions, with a particular emphasis on atypical flat lesions. These differences offer valuable insights into the early pancreatic tumorigenesis process.\u003c/p\u003e\u003cp\u003eConsistent findings in both mouse models and human tissue samples reveal that AFL are characterized by a highly active immune microenvironment. In the AFL, there was a pronounced infiltration of macrophages and adaptive immune cells, including CD4\u0026thinsp;+\u0026thinsp;helper T cells, CD8\u0026thinsp;+\u0026thinsp;cytotoxic T cells, and FOXP3\u0026thinsp;+\u0026thinsp;regulatory T cells, significantly exceeding levels observed in other precursors. In a recent study, innate immune cells, including macrophages and neutrophils, have been identified as playing a pivotal role in the process of acinar trans-differentiation. Conversely, adaptive immune cells, including B- and T-cells, have been shown to facilitate regeneration following injury by stabilizing the inflammatory environment and constraining the proliferation of innate cell populations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The observed trend towards a decrease in the proportion of adaptive immune cells and an increase in the proportion of macrophages from AFL-ADM-PanIN to PDAC suggests that AFL and ADM are still under the influence of the regulatory mechanisms of the adaptive immune system against acinar dedifferentiation stimuli of innate immune cells. The elevated immune presence in AFL and other precursor lesions, suggests that these early lesions exist in a dynamic immune-active state that may represent an opportunity for immune-mediated tumor suppression or clearance.\u003c/p\u003e\u003cp\u003eThe stromal compartment of AFL also displayed distinctive features, characterized by abundant αSMA\u003csup\u003e+\u003c/sup\u003e myCAFs forming a \u0026ldquo;swirling\u0026rdquo; stromal pattern unique to these lesions. This pattern is associated with a low expression of CXCL12 (and its receptor CXCR4), a chemokine known to be expressed by iCAFs that facilitates immunosuppression and tumor progression in PDAC (\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In line with the recent studies, our findings support that the emergence of CXCL12 expressing immunosuppressive iCAFs occurs in the advanced stages of the PDAC carcinogenesis, while the αSMA\u003csup\u003e+\u003c/sup\u003e myCAFs activation is an early event already occurring in the AFL as an initial precursor lesion (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Additionally, the lower stromal expression of CD109 in precursor lesions compared to PDAC suggests a gradual stromal activation correlating with tumorigenic progression (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Collectively, these stromal characteristics point toward a microenvironment in AFL and other early lesions that may support immune engagement rather than suppression.\u003c/p\u003e\u003cp\u003eImportantly, this immunological profile was mirrored in the limited human AFL samples examined by multiplex immunofluorescence. Although statistical analyses were constrained by the small number of cases, human AFL showed increased immune cell infiltration (175 cells/mm\u0026sup2; versus 2 cells/mm\u0026sup2; in normal tissue) with a predominance of macrophages (44% of immune cells) and a marked increase in αSMA\u003csup\u003e+\u003c/sup\u003e stromal cells (32% of ROI versus 1% in normal tissue). These findings support the translational relevance of the murine data and suggest that the immune activation observed in AFL is conserved across species.\u003c/p\u003e\u003cp\u003eThe TME of PDAC and its precursor lesions intricately gets shaped by specific genetic alterations that drive carcinogenesis and modulate stromal and immune interactions. Among the most frequently altered genes in PDAC are \u003cem\u003eKRAS, TP53, CDKN2A\u003c/em\u003e, and \u003cem\u003eSMAD4\u003c/em\u003e, which not only initiate tumorigenesis but also exert profound influence on the cellular composition and functional state of the TME. It has been shown that oncogenic \u003cem\u003eKRAS\u003c/em\u003e signaling leads to tumor cell proliferation, fibroblast activation, macrophage infiltration, and subsequently acinar cell dedifferentiation (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Additionally, inhibition of active \u003cem\u003eKRAS\u003c/em\u003e in PDAC leads to more immunoreactive macrophages and a decrease of myeloid derived suppressor cells in the TME (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). On the other hand, alterations of \u003cem\u003eTP53\u003c/em\u003e, particularly missense mutations, have been linked to reduced infiltration of cytotoxic CD8⁺ T cells and the upregulation of fibrosis-associated gene programs, contributing to an immunosuppressive microenvironment (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). In accordance with these findings, we observed that in precursor lesions such as ADM and AFL, the presence of \u003cem\u003eTrp53\u003c/em\u003e mutation is associated with reduced infiltration of adaptive immune cells, accompanied by increased expression of αSMA\u003csup\u003e+\u003c/sup\u003e in the surrounding stroma. These findings suggest that \u003cem\u003eTP53\u003c/em\u003e mutations not only drive tumorigenesis but also facilitate stromal remodeling and immune evasion at early stages.\u003c/p\u003e\u003cp\u003eBeyond the four canonical drivers, PDAC harbors less common but recurrent mutations in genes such as \u003cem\u003eRNF43\u003c/em\u003e, \u003cem\u003eARID1A\u003c/em\u003e, \u003cem\u003eTGFβR2\u003c/em\u003e, \u003cem\u003eGNAS\u003c/em\u003e, and \u003cem\u003ePIK3CA\u003c/em\u003e (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Based on the degree of dysplasia, similar genetic alterations have been detected also in PanIN (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). While previous studies have reported alterations in \u003cem\u003eKRAS, CDKN2A\u003c/em\u003e, and overexpression of p53 in ADM and AFL (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), our study is the first to systematically investigate the most common PDAC-associated genes of these alternative precursor lesions using an expanded targeted sequencing panel on meticulously microdissected samples.\u003c/p\u003e\u003cp\u003eIn the KC mouse model, we identified coding somatic variants in 16 of 20 commonly altered PDAC-associated genes across AFL, ADM, and PanIN lesions. The most frequently mutated genes were \u003cem\u003eArid1a, Rnf43\u003c/em\u003e, and \u003cem\u003ePik3ca\u003c/em\u003e, followed by \u003cem\u003eTrp53, Smad4, Nras, Apc, Cdkn2a\u003c/em\u003e, and \u003cem\u003eStk11\u003c/em\u003e. The detected genetic alterations in AFL and ADM supports the hypothesis that these lesions, like PanIN, are legitimate alternative precursors to PDAC. In contrast, lesions from fKPC mice showed no additional coding somatic mutations, suggesting that early, concurrent activation of \u003cem\u003eKRAS\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e is sufficient to drive carcinogenesis in this model. These findings emphasize the importance of temporal and contextual factors in shaping both genetic evolution and the tumor microenvironment.\u003c/p\u003e\u003cp\u003eBuilding on these findings, we hypothesized that AFL may represent sites of genetic instability that generate neoantigens, thereby triggering an early immune response. Supporting this, CNV analysis in AFL revealed recurrent alterations in more cases compared to PanIN lesions, suggesting AFL are genetically more unstable. As precursor lesions progress to highly genomic instable PDAC, the TME undergoes alterations that facilitate immune evasion (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Therefore, AFL may represent a transitional stage where genomic instability is sufficient to elicit immune responses, whereas advanced PDAC develops mechanisms to suppress these responses despite ongoing genomic alterations.\u003c/p\u003e\u003cp\u003eThis study has limitations related to the use of a small gene panel for sequencing, thus not enabling a comprehensive analysis of the genome of ADM and AFL. NGS of laser-captured microdissected tissue allows genetic analysis of lesions that are too small for manual dissection and reduces contamination with non-lesional tissue. However, due to the very low amount of dissected tissue obtained from each single lesion, it was required to pool the same type of lesions, limiting the assessment of genetic heterogeneity. In the TME characterization, we focused on the most relevant players of TME biology; nevertheless, a further characterization of the immune cell subtypes with additional biomarkers is necessary to better understand their exact role in the progression model.\u003c/p\u003e\u003cp\u003eIn conclusion, while PanIN, IPMN, and MCN are established precursor lesions of PDAC, emerging evidence indicates an alternative pathway originating from the centroacinar-acinar compartment that may also progress to PDAC. Our study highlights the distinct immunological and stromal characteristics of AFL with significant immune cell infiltration and \"swirling\" stroma. Additionally, both ADM and AFL share key mutations with PanIN and PDAC, supporting their potential roles as precursor lesions. Taken together, these findings highlight the contributions of ADM and AFL to PDAC carcinogenesis, underscored by their unique microenvironments, expression profiles, and early genetic alterations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePDAC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pancreatic ductal adenocarcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePanIN\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pancreatic intraepithelial neoplasia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIPMN\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Intraductal papillary mucinous neoplasm\u003c/p\u003e\n\u003cp\u003eMCN\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mucinous cystic neoplasm\u003c/p\u003e\n\u003cp\u003eADM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Acinar-ductal metaplasia\u003c/p\u003e\n\u003cp\u003eAFL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Atypical flat lesion\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTME\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tumor microenvironment, immune and stromal microenvironment of the lesions\u003c/p\u003e\n\u003cp\u003eGEMM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Genetically engineered mouse models\u003c/p\u003e\n\u003cp\u003eKC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u003cem\u003ePtf1a\u003csup\u003eCre/+\u003c/sup\u003e, Kras\u003csup\u003eLSLG12D/+\u003c/sup\u003e\u003c/em\u003e mice\u003c/p\u003e\n\u003cp\u003efKPC \u003cem\u003ePtf1a\u003csup\u003eCre/+\u003c/sup\u003e, Kras\u003csup\u003eLSLG12D/+\u003c/sup\u003e, Trp53\u003csup\u003eLoxP/LoxP\u003c/sup\u003e\u003c/em\u003e mice\u003c/p\u003e\n\u003cp\u003eNGS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Next-generation sequencing\u003c/p\u003e\n\u003cp\u003eCAFs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Cancer-associated fibroblasts\u003c/p\u003e\n\u003cp\u003emyCAFs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Myofibroblastic cancer-associated fibroblasts\u003c/p\u003e\n\u003cp\u003eiCAFs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Inflammatory cancer-associated fibroblasts\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCXCR4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;C-X-C motif receptor 4\u003c/p\u003e\n\u003cp\u003eCXCL12\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;C-X-C motif ligand 12\u003c/p\u003e\n\u003cp\u003eTGF-\u0026szlig;1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Transforming growth factor \u0026szlig;1\u003c/p\u003e\n\u003cp\u003eEGFR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Epidermal growth factor receptor\u003c/p\u003e\n\u003cp\u003ePCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Polymerase chain reaction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFFPE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Formalin-fixed paraffin-embedded\u003c/p\u003e\n\u003cp\u003eLMD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Laser captured microdissection\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Region of interest\u003c/p\u003e\n\u003cp\u003eIRS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Immunoreactivity score\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAY: Writing-original draft, Histological examination, Investigation, Data curation, Validation, Conceptualization. LB: Carrying out experiments, Formal analyses, Investigation, Data curation, Visualization, Validation, Writing. KH: Bioinformatic analysis, Writing. SH: Visualization, Writing. WG: NGS analysis. MS: Supervision for Multiplex analysis. LH: Conceptualization, Writing. IE: Project administration, Design, Histological examination, Conceptualization, Writing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the members of Esposito Working Group, Institute of Pathology, University Hospital Duesseldorf for their support. We also thank Johannes K\u0026ouml;ster, University of Duisburg-Essen, for his help configuring events for Varlociraptor. This work represents the doctoral thesis of one of the authors (LB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental phase of this research project was supported by an MD-scholarship from the D\u0026uuml;sseldorf School of Oncology (DSO).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval of the State Office for Nature, Environment and Consumer Protection of North Rhine-Westphalia was granted under the reference number of 81-02.04.2021.A328. To use fully anonymized human formalin-fixed paraffin-embedded blocks from the archive of the Institute of Pathology at the University Hospital Duesseldorf ethic approval was granted under the reference number of 2170/2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information and Data Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKoch-Institut R. 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EBioMedicine. 2020;54:102714.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-experimental-and-clinical-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jecc","sideBox":"Learn more about [Journal of Experimental \u0026 Clinical Cancer Research](http://jeccr.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jecc/default.aspx","title":"Journal of Experimental \u0026 Clinical Cancer Research","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acinar-ductal metaplasia, atypical flat lesion, pancreatic cancer precursors, microenvironment, genetic alterations","lastPublishedDoi":"10.21203/rs.3.rs-7660097/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7660097/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e\u003cp\u003ePancreatic ductal adenocarcinoma (PDAC) is known to develop through a stepwise progression from precursor lesions, such as pancreatic intraepithelial neoplasias (PanIN) or intraductal papillary mucinous neoplasms. An alternative carcinogenic pathway has been proposed via transformation of acinar cells, with acinar-ductal metaplasia (ADM) and atypical flat lesions (AFL). Defining the characteristics of PDAC precursors is crucial to better understand PDAC carcinogenesis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e15 KC (\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e) and 15 KPC-like mice (\u003cem\u003ePtf1a\u003c/em\u003e\u003csup\u003e\u003cem\u003eCre/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eLSLG12D/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTrp53\u003c/em\u003e\u003csup\u003e\u003cem\u003eLoxP/LoxP\u003c/em\u003e\u003c/sup\u003e, referred as fKPC hereafter) were sacrificed at different time points. A meticulous morphological evaluation was performed to define different pancreatic lesion types. Multiplex immunofluorescence staining was applied to define the characteristics of the immune and stromal microenvironment of the lesions (referred as TME hereafter) using variable markers. In order to investigate the association between the genetic alterations and the components of the microenvironment, all lesion types were subjected to next-generation sequencing (NGS) using a 20 genes-panel\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMultiplex immunofluorescence staining revealed that AFL had the most intense immune cell infiltration compared to PanIN and ADM. AFL were infiltrated by higher number of CD4\u003csup\u003e+\u003c/sup\u003e helper T cells, FOXP3\u003csup\u003e+\u003c/sup\u003e regulatory T cells and CD19\u003csup\u003e+\u003c/sup\u003e B cells compared to all analyzed lesions. They displayed and more CD8\u003csup\u003e+\u003c/sup\u003e cytotoxic T cells than PDAC, while peripheral and central PDAC tissues were infiltrated by macrophages in higher frequency. In addition, AFL had more prominent αSMA-expressing myofibroblastic cancer-associated fibroblasts-rich stroma than other lesions. PDAC had higher CXCL12 expression and more common CD109\u003csup\u003e+\u003c/sup\u003e cells than other lesions. In NGS analysis, none of the lesions in fKPC mice revealed additional coding mutations, while the preneoplastic lesions in 7 KC mice showed variable coding alterations in 16 different genes. The most frequently affected genes were \u003cem\u003eArid1a, Rnf43\u003c/em\u003e, and \u003cem\u003ePik3ca\u003c/em\u003e; in contrast, coding \u003cem\u003eGnas, Braf\u003c/em\u003e, and \u003cem\u003eIdh1\u003c/em\u003e mutations were not found. PDAC precursors in KC mice showed more dense infiltration of adaptive immune cells than in fKPC mice, supporting the immunosuppressive role of \u003cem\u003eTrp53\u003c/em\u003e alterations.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur study highlights the unique immunological and stromal features of AFL. Moreover, reinforcing their potential as precursor lesions, ADM and AFL exhibit variable alterations in the genes that have a critical role in PDAC carcinogenesis.\u003c/p\u003e","manuscriptTitle":"Immunological and Molecular Insights into Acinar-Ductal Metaplasia and Atypical Flat Lesions as Precursor Lesions of Pancreatic Ductal Adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-06 21:54:39","doi":"10.21203/rs.3.rs-7660097/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-13T14:06:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T10:41:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-02T10:22:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31323199759187872051852488459012572374","date":"2025-09-26T07:30:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115044633064799802286071364368541187378","date":"2025-09-23T10:03:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-23T09:50:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-23T09:43:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-23T09:43:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Experimental \u0026 Clinical Cancer Research","date":"2025-09-19T15:46:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-experimental-and-clinical-cancer-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jecc","sideBox":"Learn more about [Journal of Experimental \u0026 Clinical Cancer Research](http://jeccr.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jecc/default.aspx","title":"Journal of Experimental \u0026 Clinical Cancer Research","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fb45d5b5-0d50-49cd-869e-f86568b1ba92","owner":[],"postedDate":"October 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T16:49:27+00:00","versionOfRecord":{"articleIdentity":"rs-7660097","link":"https://doi.org/10.1186/s13046-026-03643-4","journal":{"identity":"journal-of-experimental-and-clinical-cancer-research","isVorOnly":false,"title":"Journal of Experimental \u0026 Clinical Cancer Research"},"publishedOn":"2026-01-13 16:30:30","publishedOnDateReadable":"January 13th, 2026"},"versionCreatedAt":"2025-10-06 21:54:39","video":"","vorDoi":"10.1186/s13046-026-03643-4","vorDoiUrl":"https://doi.org/10.1186/s13046-026-03643-4","workflowStages":[]},"version":"v1","identity":"rs-7660097","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7660097","identity":"rs-7660097","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}