Concordance and deviations of the PDX tumors from the primary tumors of NSCLC patients: effects of murine fibroblasts on low engraftment rates

Concordance and deviations of the PDX tumors from the primary tumors of NSCLC patients: effects of murine fibroblasts on low engraftment rates | 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 Concordance and deviations of the PDX tumors from the primary tumors of NSCLC patients: effects of murine fibroblasts on low engraftment rates Jinseon Lee, Chae Hwa Seo, Bo Kyung Kim, Jung Hee Lee, Jung Hee Kang, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2930778/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Patient-derived xenograft(PDX) models of primary lung cancer have been reported. However, varying engraftment rates and their underlying mechanisms for specific subtypes of lung cancer (adenocarcinoma, squamous cell carcinoma, and large cell neuroendocrine carcinoma) have not been studied. The authors prepared subcutaneous tumors grown in NSG™ mice with primary tumors of lung cancer patients to develop lung cancer PDX models. Pathological features of the subcutaneous tumors were compared with those of the patients. One hundred seventeen lung cancer PDX models retaining the original pathologic features were obtained from 642 primary lung cancer patients. Nineteen PDX tumors and the corresponding patient tumors, representing three subtypes of cell lung cancer, were selected and analyzed with in-depth genomic and transcriptomic profiling. Results showed the PDX tumors retained most of the somatic and oncogenic mutations with limited levels of additional xenograft-specific mutations. Significant downregulation of the genes involved in hypoxia-associated angiogenesis was found compared with the corresponding human tumors. This downregulation was associated with murine fibroblasts in the PDX tumor microenvironment, which might be an important factor in low engraftment rates in primary lung cancer PDX models. hypoxia angiogenesis murine fibroblast tumor microenvironment cell types primary lung cancer Figures Figure 1 Figure 2 Introduction Lung cancer is the leading cause of cancer-related mortality worldwide 1, 2 . It is classified into two main histological categories: NSCLC (85%) and small cell lung cancer (SCLC; 15%). NSCLCs are generally subcategorized into adenocarcinomas (LUADs), squamous cell carcinomas (LUSCs), and large cell neuroendocrine carcinomas (LCNECs) 3, 4 . With the aid of next generation sequencing technology, up to 60% of LUADs were shown to have a known oncogenic driver mutation as well as fusion or amplification in signaling pathways, which allowed the development of therapeutic agents that target specific molecular pathways. Despite this improvement in targeted therapy, secondary alterations in the downstream and/or alternative pathways lead to acquired resistance and disease progression. On the contrary, therapeutic targets have not been clearly identified in LUSC 5 and in LCNEC due to the rarity of these cancers 6 . PDX models have been developed using NSG™ mice as a means to preserve the histological structures in human tumors, even for limited passages 7 . These features allow the model to be used as a preclinical model for the development of target drugs against de novo resistance 8, 9, 10, 11 and as co-clinical models for the selection or combination of treatment regimens before clinical applications 12, 13 . Cancer immunotherapy is one of the most promising approaches to refractory cancers and PDX tumors can be invaluable resources for preparing humanized PDX models for cancer immunotherapy using NSG mice infused with CD34 human hematopoietic stem cells 14 . These merits make the three major pathological subtypes of NSCLCs eligible for preparation of PDX models that can be used to find target drugs or immunotherapeutics to control lung cancer. In this study, the authors established 117 PDX models from 642 primary lung cancers. Representative models of LUAD, LUSC, and LCNEC subtypes were selected and the pathological, genomic, and transcriptomic patterns of PDX tumors were compared with those of corresponding patient tumors based on our previous studies using LUSC PDX models 15 . The factors responsible for the low success rate of the PDX models, particularly in the case of adenocarcinomas, were considered when attempting to improve the efficiency of generating PDX models, which could increase the application opportunities. Materials and methods Tumor samples from patients with primary NSCLCs Tumor samples were obtained from 642 primary NSCLC patients between September 2015 and December 2019. All patients provided signed informed consent. This study was approved by the IRB of Samsung Medical Center (2014-10-069, 2015-04-018, 2018-03-110). Table 1 shows the clinical characteristics of the NSCLC patients. Clinical features such as age, gender, preoperative chemotherapy treatments, smoking status, stage, tumor size, differentiation, recurrence, vascular invasion, perineural invasion, lymphatic invasion, visceral pleural invasion, and survival were obtained from medical records. Establishment of primary lung cancer PDX models To establish primary lung cancer PDX models, tumor samples from patients with primary lung cancer were subcutaneously implanted into the flanks of NSG mice (Jackson Laboratory, Sacramento, CA, USA). The size of a mouse subcutaneous tumor was measured with a caliper twice a week until it reached 60 mm 3 in volume. Tumor volumes were calculated as 0.5 × length × width 2 . The mice were sacrificed when the tumor size reached 600–800 mm 3. Then, the subcutaneous tumors were surgically harvested for subsequent procedures. Expansion of the tumor tissues was carried out with three passages. Formalin-fixed paraffin-embedded samples for were prepared for pathologic examination. Short tandem repeat analysis was carried out for direct identification of mouse subcutaneous tumors, and next generation sequencing analysis was subsequently performed. All animals were cared for and treated following an animal protocol that had been approved by the CHA Advanced Research Institute and Biomedical Research Institute at Seoul National University Hospital. Whole exome sequencing (WES) Three micrograms of genomic DNA were used to establish DNA libraries. Using an Agilent SureSelect Human All Exon V3 kit (Agilent Technologies, Santa Clara, CA, USA), target enrichment was performed, following the manufacturer’s instructions, to generate exome sequencing libraries. Exon capturing was then followed using an Agilent SureSelect 50Mb system. Paired-end DNA sequences were obtained with the Illumina sequencing system HiSeq 2000 (Illumina Inc., San Diego, CA, USA). The sequenced reads were aligned to the human genome information from the University of California Santa Cruz hg 19. MuTect, VarScan 2, and the GATK Somatic Indel Detector were used to identify somatic mutations, and these mutations were later verified through Sanger sequencing. Significantly mutated genes were identified with MutSigCV, and functional enrichment of the somatic mutations was assessed with Metacore (GeneGo Inc., St. Joseph, MI, USA). The GRCh37 reference was used for sequencing data analysis. Whole transcriptome sequencing (WTS) mRNA libraries (insert size of ~300 bp) were prepared with a TruSeq RNA Library Preparation Kit v2 (Illumina Inc., San Diego, CA, USA). A total of 1 μg of RNA from each case sample was used to create the library. The samples were subjected to 101-bp paired-end sequencing using the Illumina sequencing system HiSeq 2000. Library preparation and sequencing were performed at DNA Link, Inc. Differentially expressed gene (DEG) analysis Genes with at least one sample indicating a sequencing read count of at least two for each were initially screened. Differential expression of each gene was analyzed by calculating the log 2 (fold change) value for the gene expression of PDX tumors relative to that of patient tumors, or the adjacent normal tissue (ANT), depending on the purpose of the analysis. The genes with a false discovery rate 2 were selected as upregulated or downregulated genes, respectively. Pathological analysis Formalin-fixed paraffin-embedded tumor tissues from primary lung cancer patients and corresponding subcutaneous tumors were freshly cut into slices of 4 μm. Following the manufacturer’s instructions, hematoxylin and eosin (H&E) staining was performed using Symphony (Ventana Medical Systems, Inc., Roche, Basel, Switzerland). Immunohistochemical (IHC) staining for CK5, p63, TTF1, pan-cytokeratin, or CD56 was performed on a single representative block with the following procedures. Deparaffinized slides were treated with citrate buffer (pH 6.0) for antigen retrieval. Next, the primary antibody was incubated with the Dako antibody diluent (S3022, Dako, Agilent Technologies, Inc., Santa Clara, CA, USA) and then with Dako REAL EnVision Detection System (K5007, Dako, Agilent Technologies, Inc., Santa Clara, CA, USA). The images obtained from H&E and IHC staining were analyzed with a ScanScope® XT scanner (Aperio, Leica Biosystems, Newcastle, UK). Antibody sources and dilution factors are shown in Table S1. LUAD was determined by TTF-1 + CK5 - CD56 - p63 +/- , LUSC by TTF-1 - CK5 + CD56 - p63 + , and LCNEC by TTF-1 +/- CK5 - CD56 + p63 - . Pathologically unmatched subcutaneous tumors were further categorized into xenograft-associated lymphoproliferative disease (XALD) or epithelial tumor not identical to that of the patient. Statistical analyses The association between PDX model success rates and patient characteristics was investigated with a chi-squared test. The Cox proportional hazards model was used for multiple analyses of clinically significant prognostic variables. Statistical analyses were carried out with R software for Windows version 4.2.1 (The R Foundation, St. Miami, FL, USA). The odds ratio and its confidence interval were calculated with the “epitools” package of R software. All p-values were two-sided and less than 0.05 was considered statistically significant. Results Establishment of primary lung cancer PDX models A total of 642 patients with LUADs, LUSCs, and LCNECs were enrolled in the study between September 2015 and December 2019. Tumor samples from these patients were grafted into NSG mice to establish primary lung cancer PDX models for each cell type. The subcutaneous tumor generation rates were 27.0% in 118 cases from 437 LUAD tumor samples, 58.3% in 109 cases from 187 LUSC tumor samples, and 38.9% in seven cases from 18 LCNEC tumor samples, as shown in Fig. 1a. To validate pathological concordance with the patient tumors, cell types were examined with antibodies against TTF1, CK5, p63, and CD56 proteins to differentiate human LUAD, LUSC, and LCNEC. For each cell type, representative immunohistochemistry (IHC) images of PDX tumors and the corresponding patient tumors are shown in Fig. 1b. Subcutaneous tumors that did not match the cell types of the patient tumors were further classified into either epithelial or non-epithelial (XALD) cell types (Table 2a). The order of efficiency in subcutaneous tumor generation was LUSC, LCNEC, and LUAD; however, except for the pathologically irrelevant tumor, the PDX model success was in the order of LCNEC, LUSC, and LUAD. When LUAD was subtyped further into five categories based on histological characteristics, the PDX model success rates were highest in the solid subtype and lowest in the papillary subtype. LUAD had the lowest PDX model success rate (6.6% on average), which was only between 1/6 and 1/7 of those for LUSC or LCNEC (43.33% and 38.9%, respectively; Table 2b). Tumors from patients with an advanced stage of NSCLC tended to have higher PDX model success rates (Table 2c). Among the pathologically irrelevant subcutaneous tumors, the ratio between the epithelial vs. non-epithelial (XALD) cases were 22.5% vs. 77.5% in LUADs, and 28.6% vs. 71.4% in LUSCs, indicating no major difference between the two cell types. A total of 29 LUAD PDX tumors, 81 LUSC PDX tumors, and seven LCNEC PDX tumors displayed the same pathology as the patient tumors (Table 2a). Clinical parameters of 642 patients were analyzed to select 12 parameters that influenced the engraftment rates (Table 1). The odds ratios were highest in the patients who was not treated with preoperative chemotherapy and second highest in males. In males, visceral pleural invasion and pStage III or lower were next highest among the advanced stage factors, while in females, tumor size and lymphatic invasion were the next highest. [Table 1 at the end of the text in the manuscript should be placed at this space] Concordance of somatic mutations in OncoPanel genes in PDX tumors Seven LUAD cases, eight LUSC cases, and four LCNEC cases were selected from 117 pathologically relevant PDX models to compare the somatic mutations between PDX and patient tumor pairs. OncoPanel genes were analyzed to test whether the driver mutations of the patient tumors were retained in the PDX tumors 16 (Fig. S1). Somatic mutations that were absent in the ANT were classified into three groups; that is, those common to PDX models and patient tumors, those found only in patient tumors, and those only in PDX models. In general, most somatic mutations were commonly seen in both PDX models and patient tumors, but a significant number of patient- or PDX-specific somatic mutations that were different depending on the patients and the cell types were also found (Table 3). [Table 3 at the end of the text in the manuscript should be placed at this space] Most somatic mutations found in the patient tumors were retained in the PDX tumors, suggesting that the PDX models could be utilized in preclinical studies. Nonetheless, as not all mutations in the patient tumors were retained in the PDX models; e.g., KRAS mutation negative in LUAD PDX-367 in Table 3, retention of the mutations of interest should be confirmed in the early stages of use of the PDX model. Preexisting mutations might disappear or additional mutations might appear in PDX tumors, for the following reasons: 1) the patient tumor fragments used for pathological examination did not have an identical genetic makeup from those for PDX models due to intra-tumoral heterogeneity, and/or 2) de novo mutations might occur during multiple passage processes for the expansion of tumor tissues. For example, new PDX-specific mutations were found in TP53 in four independent models and in NF1, NOTCH2, CHEK2, EP300, SDHA, DOCK8, and ESR1 in more than two independent models. Deviations in gene expression in PDX tumors Despite most somatic mutations being commonly found in both the patient and PDX tumors, existence of the patient or PDX-specific mutations suggested possible discrepancies in gene expression. To address this question, 460 genes in OncoPanel were analyzed for gene expression, and those with |log 2 (fold change)|>2 with respect to the ANT were selected as DEGs in patient or PDX tumors (Fig. S1, Table 4). [Table 4 at the end of the text in the manuscript should be placed at this space] First, there was a trend for more genes to be either up- or downregulated in PDX tumors than in patient tumor tissues. HIST1H3B was significantly upregulated in both patient and PDX tumors with little exception, which might indicate a cancer-specific phenomenon, supported by the fact that it is engaged in wrapping newly synthesized DNA as a core component of the nucleosome 17 . On the other hand, ENG was downregulated in both patient and PDX tumors; particularly, in more than 60% of the cases, ENG and PDGFRA were downregulated together. Those genes related to wound healing (COL7A1) 18 , or tumor cell proliferation (HIST1H3B, BRCA1, CDKN2A, and POLQ) were upregulated, and those involved in angiogenesis, hypoxia, and connective tissue remodeling (ENG, PDGFRA, GATA2, and KDR) were downregulated 19, 20, 21, 22, 23 . It is known that extracellular matrix remodeling or angiogenesis is induced by hypoxia, and the oxygen concentration in the tumor is regulated by the master regulator HIF-1a 24 . Therefore, it was necessary to investigate the association between HIF-1a expression levels with hypoxia or angiogenesis in PDX tumors. The HIF-1a expression in PDX tumors, patient tumors, and ANTs was comparatively analyzed for hypoxia (Table S2). HIF-1a expression levels in LUAD and LUSC PDX tumors were higher than ANTs, but lower than the patient tumors, at the level of 62%~75%. In other words, hypoxia occurred in most PDX tumors at a relatively lower level than the patient tumors, which was similar to the above observation that the four genes in OncoPanel (ENG, PDGFRA, GATA2, and KDR) were involved in hypoxia and angiogenesis were downregulated in PDX tumors compared with patient tumors. Downregulated expression of hypoxia- and angiogenesis-related genes in PDX tumors To understand whether the lower expression of hypoxia- or angiogenesis-associated genes in PDX tumors was a consistent phenomenon, data from Gene Set Enrichment Analysis and the signature genes for hypoxia or angiogenesis in recent reports were consolidated to create expanded gene sets (Tables S3, Table S4). Among these two gene sets, DEGs with |log 2 (fold change)|>2 were selected from the DEG mother database described in the Methods section. The selected genes were associated with the TME component cells in which those genes were generally expressed; i.e., epithelial tumor cells, murine cancer-associated fibroblasts (CAF), endothelial cells, and immune cells of PDX tumors (Table 5). [Table 5 at the end of the text in the manuscript should be placed at this space] In comparison to the patient tumors, hypoxia-related genes that were downregulated in PDX tumors commonly to LUAD and LUSC, to LUAD and LCNEC, and to LUSC and LCNEC are listed in Table 5a. Twenty genes were mainly expressed in fibroblasts, and four genes in endothelial cells. Likewise, angiogenesis-related genes that were downregulated in PDX tumors commonly to LUAD and LUSC, to LUAD and LCNEC, and to LUSC and LCNEC are listed in Table 5b. Thirty-five genes were mainly expressed in fibroblasts and 28 genes were mainly expressed in endothelial cells. CXCR4, VCAN, FAP, FN1, FOS, TGFB3, and CCL2 were expressed in fibroblasts, and FLT1, TEK, ANGPT2, and SPP1 were expressed in endothelial cells that belonged to both hypoxia- and angiogenesis gene sets. Most hypoxia and angiogenesis-related genes that were mainly expressed in fibroblasts were downregulated. Therefore, low HIF-1a expression as well as low levels of expression in hypoxia- and angiogenesis-associated gene sets in PDX tumors might be caused by the murine TME, specifically murine fibroblasts. Unlike LUAD or late stage LUSC PDX tumors, early stage LUSC PDX tumors had relatively upregulated genes, compared to the patient tumors: For the hypoxia-related genes, CDKN3 and TPBG were expressed in fibroblasts, and FOSL1 and GRIN2D were expressed in endothelial cells. For angiogenesis-related genes, AURKA, BIRC5, E2F1, ECT2, and UBE2T were expressed in tumor cells, AURKB, JAG2, MBL2, SOX2 in fibroblasts, and ETV4, HMGA1, SLC7A5 in endothelial cells. Relatively high PDX engraftment rates in LUSCs appeared partly associated with upregulation of the hypoxia- and angiogenesis-related genes. On the contrary, PDX tumors of late stage LCNEC cell types had one upregulated gene (i.e., PRODH) in tumor cells and one upregulated gene (i.e., ID1) in endothelial cells. Discussion PDX animal models are generated by grafting patient-derived tumors to immunodeficient mice, which reconstitutes the tumors with pathological relevance to the original patients. It is necessary to timely generate the PDX models effectively when studies with animal models are needed for specific cancer patients. In spite of the effort paid to establish PDX models, not much in-depth discussion has occurred on the key factors that determine the PDX engraftment rates. Molecular genetic deviations from the original patient tumors, such as somatic mutations and altered gene expression 25, 26 , may produce pathologically irrelevant subcutaneous tumors, causing transitions to different epithelial cell types or to non-epithelial tumors (XALD) (70% and 30%, respectively; Table 2), resulting in low engraftment rates. In this study, by analyzing the differences in somatic mutations and gene expression between the PDX tumors and the tumor of primary NSCLC patients, we aimed to understand the reason for low PDX engraftment rates in NSCLC at a molecular level. To this end, the authors took a retrospective data-collection and analyses approach, rather than hypothesis-generation and test approach. Typically, tumors generate local hypoxia as they grow, and hypoxia-related genes, including HIF-1a, are activated. A variety of adaptive autophagic responses are initiated, such as epithelial-mesenchymal transition (EMT) of tumor cells and dedifferentiation into cancer stem cells 27, 28, 29, 30, 31 . Tumor hypoxia increases mutation burdens 32, 33 , particularly enriching driver mutations in TP53, MYC, and PTEN 34, 35 . At the same time, a local oxygen gradient appears in CAF in the TME that aids tumor subclonal evolution, resulting in further intratumor heterogeneity 36 . Through aberrant paracrine signaling and matrix remodeling, the niches necessary to maintain cancer stem cells are generated 37, 38, 39, 40 and the angiogenic signals stimulated by hypoxia support endothelial sprouting and tumor growth as well 24, 41, 42, 43, 44, 45 . Angiogenesis reoxygenates tumors and HIF-1a becomes inactivated, but as the tumor grows local hypoxia is re-generated 46, 47 . Through this cycling hypoxia, further clonal evolution facilitates an even more complex genomic situation (Fig. 2) 48, 49, 50 . When grafted to NSG mice, most tumors form internal hypoxia at a relatively early stage, as supported by increased TP53 somatic mutations in a PDX-specific manner 35, 49 (Table S2, Table 3). During serial passaging to expand the PDX tumors, the fore-mentioned cycling hypoxia increases tumor heterogeneity and diversifies growth rates, generating epithelial tumors with rare cell types that may not match the initially grated tumors of the patients 51 . Histological inter-conversion between LUAD and LUSC 52, 53, 54 or conversion from NSCLC to SCLC 55, 56 has been reported when lung cancer patients are treated with EGFR-tyrosine kinase inhibitor or chemotherapy, but the similarities and differences with our pathologically deviant PDX tumors require further investigation. Hypoxia in subcutaneous tumors affect the presence of Epstein-Barr virus (EBV), which is ubiquitous in the human body 57 . Latent EBVs in lymphocytes that are infiltrated in patient tumors are lytically reactivated by HIF-1a that is activated by tumor hypoxia, which is formed when grafted into immune-deficient NSG mice 58, 59 . Human lymphocytes transformed by P1 viral oncogenes 60 can proliferate under normoxic as well as hypoxic conditions 61 , forming XALD. As such, tumor hypoxia seems to play a key role in the generation of pathologically unmatched subcutaneous tumors, such as phenotypic conversion of cell types or XALD. In preclinical, co-clinical, or collateral studies using PDX models as a drug testbed, TME is a key factor determining the responses 62, 63 . In PDX models, many murine stromal cells are not functional and B- and T-cells do not mature, and no natural killer cells exist, and myeloid cells, such as macrophages and dendritic cells, are defective 64, 65 , leaving murine fibroblasts as the only functional stromal cells in TME. Human CAF in the patient tumor fragments is known to be diluted and gradually substituted by murine CAFs during serial passages in NSG mice 66, 67 . Therefore, to utilize PDX tumors as a copycat of the patient tumor, not only somatic mutations but also changes in gene expression caused by TME modification need to be analyzed in-depth between patient and PDX tumors. Unlike patient tumors in which the angiogenic factors are produced and released by tumor cells, CAF and tumor infiltrating immune cells, including lymphocytes and macrophages 27, 43 , in PDX tumors, the main sources of angiogenic factors, are the human tumor cells and the murine CAFs, which require effective cell-cell communication across species. In patient tumors, growing cancer cells are in continuous contact with human fibroblasts from early stages for extended periods of time to form conditioned CAFs, but in PDX tumors, direct abrupt contacts with unconditioned murine fibroblasts may cause prolonged chronic hypoxia and autophagy at an early stage. As a consequence, compared with patient tumors, HIF-1a activation levels were lowered (Table S2), and the weakened angiogenesis may delay tumor growth and decrease tumor engraftment rates, even leading to the failure of tumor formation (Table 2a). In PDX LUSC and LCNEC tumors, some of the angiogenesis-related genes were upregulated, but not in those of LUAD (Table 5). Maybe this is why LUAD had significantly lower engraftment rates in NSG mice than other cell types. When PDX tumors were used to generate a humanized PDX model, the humanized mouse infused with CD34+ human hematopoietic stem cells have fully differentiated functional human myeloid cells that substitute for the defective dendritic cells and macrophages to partly rescue TME in PDX tumors. Even so, the murine fibroblasts still have to play a role in mediating the crosstalk between the tumor mass and the tumor infiltrating immune cells as well as the endothelial cells 68, 69 . Thus, murine fibroblasts make a critical contribution to angiogenesis for the successful growth of grafted human tumors in humanized PDX models as well as in PDX models. Concordant with a number of previous studies 70 , the pathologically relevant PDX models in this study showed that various somatic mutations, including driver mutations and intra-tumoral heterogeneities, were retained through serial passages, and relative to ANT, the patient and PDX tumors showed similar expression patterns (Table 3, Table 4). Expanded after serial passages, PDX models have potential for developing targeted drugs in preclinical studies, or in co-clinical or collateral studies for immunotherapies after being grafted to the humanized NSG mice. Nonetheless, depending on the cell types of the patient tumors, some PDX tumors showed additional somatic mutations, and different fragments of the same patient tumors often showed a variety of growth patterns, which indicated that intratumor heterogeneity might be an inevitable factor causing variation in each individual, even within the specific PDX model. Unlike somatic mutations, differences in gene expression were considerable between the PDX and patient tumors. Therefore, caution is warranted when using PDX models to evaluate the systemic effects of targeted drugs and to translate the outcome into clinical applications. There have been a number of studies pointing out the intratumor heterogeneity of PDX models 71, 72, 73, 74 . To enhance the engraftment efficiencies of PDX tumors, and to minimize the clonal evolution during serial passages, mouse fibroblasts need to be conditioned quickly by the human tumors, with angiogenesis proceeding without delay, and EBV-activation needs to be interrupted effectively 75, 76 . Conclusion Current protocols for PDX model preparation often result in significantly diverse engraftment rates, depending on tumor types, and rare patient tumors that are valuable for clinical research are frequently lost during the process. For PDX models to qualify for wide use in preclinical studies for drug development as well as in collateral studies for clinical benefit, the engraftment rate needs to be elevated, and TME, especially fibroblasts, close to that of the patient tumors needs to be established in the PDX models. Murine fibroblasts, defective murine macrophages, and EBV-infected lymphocytes are some of the key factors contributing to the inefficiency of PDX tumor generation when associated with tumor hypoxia, which may provide basic knowledge for a strategic improvement in graft efficiencies in the future. Abbreviations ANT, adjacent normal tissue; CAF, cancer-associated fibroblast; DEG, differentially expressed gene; EBV, Epstein-Barr virus; EMT, epithelial-mesenchymal transition; H&E, hematoxylin and eosin; IHC, immunohistochemistry; IRB, institutional review board; LCNEC, large cell neuroendocrine carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; PDX, patient-derived xenograft; SCLC, small cell lung cancer; TME, tumor microenvironment; WES, whole exome sequencing; WTS, whole transcriptome sequencing; XALD, xenograft-associated lymphoproliferative disease Declarations Acknowledgements Professional English writing service was provided by Enago for the manuscript. Authors’ contributions J Lee wrote most of the manuscript. CH Seo and MY Park performed the genomic analysis. BK Kim assisted the data collection, image preparation and drafting. S-H Kim assisted the manuscript writing and editing. JH Lee, HK Kim, JH Cho, YS Choi, S Shin, J Kim provided the patients’ tumor tissues and clinical information. Y-A Choi prepared the human tumor tissue for xenograft. JH Kang collected patients’ clinical information and performed the H&E and IHC staining.HK Song, and HY Jang prepared the PDX models. J-E Lee supervised the entire process of PDX model development. S Lee supervised the genomic analysis. M Cho and D-S Son performed the statistical analysis of the patients’ clinical information and their association with engraftment efficiency of PDX. J Lee, CH Seo, and BK Kim equally contributed to this study. J Lee, J-E Lee, and J Kim supervised the entire study. All authors read and approved the final manuscript. Funding The majority of this work was supported by the Technology Innovation Program of the Ministry of Trade, Industry, and Energy, Republic of Korea (Grant No. 10050154), and partly by DNA Link, Inc. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate All patients provided written informed consents authorizing the collection and use of their body tissues for study purposes. This study was approved by the IRB of Samsung Medical Cancer (2014-10-069, 2015-04-018, 2018-03-110) Consent for publication All patients provided written informed consents authorizing the collection and use of their body tissues for study purpose. Competing interest The authors declare that they have no competing interests. Author details 1 Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea 2 DNA Link, Inc., Kangseo-gu, Seoul, South Korea 3 Division of Data Science and Data Science Convergence Research Center, College of Information Science, Hallym University, Chuncheon, South Korea 4 Ewha Research Center for Systems Biology (ERCSB) and Department of Life Science, Ewha Womans University, Seoul, South Korea References Barta JA, Powell CA, Wisnivesky JP. Global Epidemiology of Lung Cancer. Ann Glob Health. 2019;85(1):8. Park JY, Jang SH. Epidemiology of Lung Cancer in Korea: Recent Trends. Tuberc Respir Dis (Seoul). 2016;79:58-69. Casal-Mouriño A, Ruano-Ravina A, Lorenzo-González M, Rodríguez-Martínez A, Giraldo-Osorio A, Varela-Lema L, Pereiro-Brea T, Barros-Dios JM, Valdés-Cuadrado L, Pérez-Ríos M. Epidemiology of stage III lung cancer: frequency, diagnostic characteristics, and survival. 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Rituximab Decreases Lymphoproliferative Tumor Formation in Hepatopancreaticobiliary and Gastrointestinal Cancer Patient-Derived Xenografts. Scientific Reports 2019;9,Article number:5901. Butler KA, Hou X, Becker MA, Zanfagnin V, Enderica-Gonzalez S, Visscher D, Kalli KR, Tienchaianada P, Haluska P, Weroha SJ. Prevention of Human Lymphoproliferative Tumor Formation in Ovarian Cancer Patient-Derived Xenografts. Neoplasia 2017;19(8)628-636. Tables Tables 1 to 5 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Additionalfile1TableS1Primaryantibodiesusedinimmunohistochemistry.xlsx Additional file 1 Table S1 Primary antibodies used in immunohistochemistry Additionalfile2TableS2HIF1aexpressionlevelintumorsofPDXmodelsandpatients.xlsx Additional file 2 Table S2 HIF-1a expression level in tumors of PDX models and patients “Fold change” indicates the average of the fold changes in HIF-1a expression between PDX tumors and patient tumors (alternatively PDX tumors and ANT, or patient tumors and ANT) for all the models of the specified tumor cell type. Additionalfile3TableS3Hypoxiamarkersof487genes.xlsx Additional file 3 Table S3 Hypoxia markers of 487 genes Additionalfile4TableS4Angiogenesismarkersof243genes.xlsx Additional file 4 Table S4 Angiogenesis markers of 243 genes Additionalfile5FigureS1SomaticmutationsanddifferentialexpressioninOncoPanelgenesof19patientswithprimaryNSCLC.pdf Additional file 5 Fig. S1 Somatic mutations and differential expression of OncoPanel genes in 19 patients with primary NSCLC and their PDX models. WES is the source for the somatic mutations of the genes and WTS for the differentially expressed genes. The yellow boxes indicate shared somatic mutations; the red- or blue boxes indicate the upregulated or downregulated genes, respectively, in both the patient and PDX models, compared to the ANTs. The number in a box represents the frequency of somatic mutations or the log 2 (fold change) value of differential expression. 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10:59:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2930778/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2930778/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":38095684,"identity":"6205f5ea-bbbf-4aa9-852d-b0954c023c73","added_by":"auto","created_at":"2023-06-06 13:56:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":443150,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstablishment of primary lung cancer PDX models\u003c/strong\u003e. \u003cstrong\u003ea\u003c/strong\u003e A schematic diagram of the experimental procedure for proper PDX models and subsequent NGS analysis. \u003cstrong\u003eb \u003c/strong\u003eRepresentative histological and immunohistochemistry-stained images of tumor samples from patients with three major cell types of NSCLC and their PDX models. Scale bars, 500 μm.\u003c/p\u003e","description":"","filename":"Figure1EstablishmentofprimarylungcancerPDXmodels.png","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/6d5bb31a26dcd44b587f67a7.png"},{"id":38095203,"identity":"a0c57451-4c71-48c7-a1cc-b2a43bc91e8a","added_by":"auto","created_at":"2023-06-06 13:48:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":450515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTumor heterogeneity and XALD accelerated by cycling hypoxia during the engraftment process. \u003c/strong\u003eAs tumors grow, hypoxia is generated inside, increasing the mutation burden and activating the hypoxia-related genes, including HIF1a, whereby autophagy is induced, such as EMT and dedifferentiation into cancer stem cells. A local oxygen gradient is also formed in CAF in the TME, further diversifying tumor heterogeneity. Niches for cancer stem cells might be generated as well through aberrant paracrine signaling and matrix remodeling. Endothelial sprouting and tumor growth are initiated by the angiogenic signals that restore normoxia, where HIF1a expression is inactivated again and the hypoxic cycle repeats. The genomic landscape and clonal evolution is further diversified during the repeated cycles of hypoxia. When engrafted into NSG mice, latent EBV reactivates the lytic proliferation, and transformation with the viral oncogene causes the lymphocytes to proliferate to acquire XALD. CAF, cancer-associated fibroblasts; EBV, Epstein-Barr virus; EMT, epithelial-mesenchymal transition; CSC, cancer stem cells; XALD, xenograft-associated lymphoproliferative disease.\u003c/p\u003e","description":"","filename":"Figure2TumorheterogeneityandXALDfacilitatedbycyclinghypoxiaduringtheengraftmentprocess.png","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/b12191fd1ee22aeff58041f3.png"},{"id":40938842,"identity":"aa307f24-f1b6-431c-9ae4-b8c4a046bad5","added_by":"auto","created_at":"2023-08-02 09:52:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1177947,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/731a45df-8327-411b-a3b6-25f1f6bde935.pdf"},{"id":38095197,"identity":"78a25c1d-1ab1-41ac-b52a-e8d897485d18","added_by":"auto","created_at":"2023-06-06 13:48:46","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10603,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1 \u0026nbsp;Table S1 \u003cstrong\u003ePrimary antibodies used in immunohistochemistry\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Additionalfile1TableS1Primaryantibodiesusedinimmunohistochemistry.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/04cc64ec49c29b9ada0cd44e.xlsx"},{"id":38095683,"identity":"b9b48c12-3bf8-4d7a-b450-2a447d3f7d2d","added_by":"auto","created_at":"2023-06-06 13:56:46","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13874,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2 \u0026nbsp;Table S2 \u003cstrong\u003eHIF-1a expression level in tumors of PDX models and patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e“Fold change” indicates the average of the fold changes in HIF-1a expression between PDX tumors and patient tumors (alternatively PDX tumors and ANT, or patient tumors and ANT) for all the models of the specified tumor cell type.\u003c/p\u003e","description":"","filename":"Additionalfile2TableS2HIF1aexpressionlevelintumorsofPDXmodelsandpatients.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/051775482a8520578e667e79.xlsx"},{"id":38096968,"identity":"b71081d9-b36b-4d50-a5fe-62ba0bceaa3a","added_by":"auto","created_at":"2023-06-06 14:04:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":18443,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 3 \u0026nbsp;Table S3 \u003cstrong\u003eHypoxia markers of 487 genes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Additionalfile3TableS3Hypoxiamarkersof487genes.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/95c3a315a8393daf3da224d0.xlsx"},{"id":38095201,"identity":"2896b149-d36d-4628-a5a6-4bd9c7f7ec88","added_by":"auto","created_at":"2023-06-06 13:48:46","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15691,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 4 \u0026nbsp;Table S4 \u003cstrong\u003eAngiogenesis markers of 243 genes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Additionalfile4TableS4Angiogenesismarkersof243genes.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/7ccc6720a35430c936d71037.xlsx"},{"id":38095686,"identity":"d0713ab8-af67-48b3-88ba-761d8c60259d","added_by":"auto","created_at":"2023-06-06 13:56:46","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":186393,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 5 \u0026nbsp;Fig. S1 \u003cstrong\u003eSomatic mutations and differential expression of OncoPanel genes in 19 patients with primary NSCLC and their PDX models.\u003c/strong\u003e WES is the source for the somatic mutations of the genes and WTS for the differentially expressed genes. The yellow boxes indicate shared somatic mutations; the red- or blue boxes indicate the upregulated or downregulated genes, respectively, in both the patient and PDX models, compared to the ANTs. The number in a box represents the frequency of somatic mutations or the log\u003csub\u003e2\u003c/sub\u003e(fold change) value of differential expression.\u003c/p\u003e","description":"","filename":"Additionalfile5FigureS1SomaticmutationsanddifferentialexpressioninOncoPanelgenesof19patientswithprimaryNSCLC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/2b96d6385fc7eebd6a7eaaf5.pdf"},{"id":38095199,"identity":"0fa970ab-418a-400b-9884-4dbe7529d18f","added_by":"auto","created_at":"2023-06-06 13:48:46","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":89433,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-2930778/v1/519739c0aa917e7c1186848d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Concordance and deviations of the PDX tumors from the primary tumors of NSCLC patients: effects of murine fibroblasts on low engraftment rates","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is the leading cause of cancer-related mortality worldwide\u003csup\u003e1, 2\u003c/sup\u003e. It is classified into two main histological categories: NSCLC (85%) and small cell lung cancer (SCLC; 15%). NSCLCs are generally subcategorized into adenocarcinomas (LUADs), squamous cell carcinomas (LUSCs), and large cell neuroendocrine carcinomas (LCNECs)\u003csup\u003e3, 4\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWith the aid of next generation sequencing technology, up to 60% of LUADs were shown to have a known oncogenic driver mutation as well as fusion or amplification in signaling pathways, which allowed the development of therapeutic agents that target specific molecular pathways. Despite this improvement in targeted therapy, secondary alterations in the downstream and/or alternative pathways lead to acquired resistance and disease progression. On the contrary, therapeutic targets have not been clearly identified in LUSC\u003csup\u003e5\u003c/sup\u003e and in LCNEC due to the rarity of these cancers\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003ePDX models have been developed using NSG\u0026trade;\u0026nbsp;mice as a means to preserve the histological structures in human tumors, even for limited passages\u003csup\u003e7\u003c/sup\u003e. These features allow the model to be used as a preclinical model for the development of target drugs against \u003cem\u003ede novo\u003c/em\u003e resistance\u003csup\u003e8, 9, 10, 11\u003c/sup\u003e and as co-clinical models for the selection or combination of treatment regimens before clinical applications\u003csup\u003e12, 13\u003c/sup\u003e. Cancer immunotherapy is one of the most promising approaches to refractory cancers and PDX tumors can be invaluable resources for preparing humanized PDX models for cancer immunotherapy using NSG mice infused with CD34 human hematopoietic stem cells\u003csup\u003e14\u003c/sup\u003e. These merits make the three major pathological subtypes of NSCLCs eligible for preparation of PDX models that can be used to find target drugs or immunotherapeutics to control lung cancer.\u003c/p\u003e\n\u003cp\u003eIn this study, the authors established 117 PDX models from 642 primary lung cancers. Representative models of LUAD, LUSC, and LCNEC subtypes were selected and the pathological, genomic, and transcriptomic patterns of PDX tumors were compared with those of corresponding patient tumors based on our previous studies using LUSC PDX models\u003csup\u003e15\u003c/sup\u003e. The factors responsible for the low success rate of the PDX models, particularly in the case of adenocarcinomas, were considered when attempting to improve the efficiency of generating PDX models, which could increase the application opportunities.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eTumor samples from patients with primary NSCLCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTumor samples were obtained from 642 primary NSCLC patients between September 2015 and December 2019. All patients provided signed informed consent. This study was approved by the IRB of Samsung Medical Center (2014-10-069, 2015-04-018, 2018-03-110). Table 1 shows the clinical characteristics of the NSCLC patients. Clinical features such as age, gender, preoperative chemotherapy treatments, smoking status, stage, tumor size, differentiation, recurrence, vascular invasion, perineural invasion, lymphatic invasion, visceral pleural invasion, and survival were obtained from medical records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of primary lung cancer PDX models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo establish primary lung cancer PDX models, tumor samples from patients with primary lung cancer were subcutaneously implanted into the flanks of NSG mice (Jackson Laboratory, Sacramento, CA, USA). The size of a mouse subcutaneous tumor was measured with a caliper twice a week until it reached 60 mm\u003csup\u003e3\u0026nbsp;\u003c/sup\u003ein volume. Tumor volumes were calculated as 0.5 × length × width\u003csup\u003e2\u003c/sup\u003e. The mice were sacrificed when the tumor size reached 600–800 mm\u003csup\u003e3.\u0026nbsp;\u003c/sup\u003eThen, the subcutaneous tumors were surgically harvested for subsequent procedures. Expansion of the tumor tissues was carried out with three passages. Formalin-fixed paraffin-embedded samples for were prepared for pathologic examination. Short tandem repeat analysis was carried out for direct identification of mouse subcutaneous tumors, and next generation sequencing analysis was subsequently performed. All animals were cared for and treated following an animal protocol that had been approved by the CHA Advanced Research Institute and Biomedical Research Institute at Seoul National University Hospital.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhole exome sequencing (WES)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree micrograms of genomic DNA were used to establish DNA libraries. Using an Agilent SureSelect Human All Exon V3 kit (Agilent Technologies, Santa Clara, CA, USA), target enrichment was performed, following the manufacturer’s instructions, to generate exome sequencing libraries. Exon capturing was then followed using an Agilent SureSelect 50Mb system. Paired-end DNA sequences were obtained with the Illumina sequencing system HiSeq 2000 (Illumina Inc., San Diego, CA, USA). The sequenced reads were aligned to the human genome information from the University of California Santa Cruz hg 19. MuTect, VarScan 2, and the GATK Somatic Indel Detector were used to identify somatic mutations, and these mutations were later verified through Sanger sequencing. Significantly mutated genes were identified with MutSigCV, and functional enrichment of the somatic mutations was assessed with Metacore (GeneGo Inc., St. Joseph, MI, USA). The GRCh37 reference was used for sequencing data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhole transcriptome sequencing (WTS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003emRNA libraries (insert size of ~300 bp) were prepared with a TruSeq RNA Library Preparation Kit v2 (Illumina Inc., San Diego, CA, USA). A total of 1 μg of RNA from each case sample was used to create the library. The samples were subjected to 101-bp paired-end sequencing using the Illumina sequencing system HiSeq 2000. Library preparation and sequencing were performed at DNA Link, Inc.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferentially expressed gene (DEG) analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenes with at least one sample indicating a sequencing read count of at least two for each were initially screened. Differential expression of each gene was analyzed by calculating the log\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e(fold change) value for the gene expression of PDX tumors relative to that of patient tumors, or the adjacent normal tissue (ANT), depending on the purpose of the analysis. The genes with a false discovery rate \u0026lt;0.05 and a\u0026nbsp;|log\u003csub\u003e2\u003c/sub\u003e(fold change)|\u0026gt;2\u0026nbsp;were selected as upregulated or downregulated genes, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePathological analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFormalin-fixed paraffin-embedded tumor tissues from primary lung cancer patients and corresponding subcutaneous tumors were freshly cut into slices of 4 μm. Following the manufacturer’s instructions, hematoxylin and eosin (H\u0026amp;E) staining was performed using Symphony (Ventana Medical Systems, Inc., Roche, Basel, Switzerland). Immunohistochemical (IHC) staining for CK5, p63, TTF1, pan-cytokeratin, or CD56 was performed on a single representative block with the following procedures. Deparaffinized slides were treated with citrate buffer (pH 6.0) for antigen retrieval. Next, the primary antibody was incubated with the Dako antibody diluent (S3022, Dako, Agilent Technologies, Inc., Santa Clara, CA, USA) and then with Dako REAL EnVision Detection System (K5007, Dako, Agilent Technologies, Inc., Santa Clara, CA, USA). The images obtained from H\u0026amp;E and IHC staining were analyzed with a ScanScope® XT scanner (Aperio, Leica Biosystems, Newcastle, UK). Antibody sources and dilution factors are shown in Table S1.\u0026nbsp;LUAD was determined by TTF-1\u003csup\u003e+\u003c/sup\u003e CK5\u003csup\u003e-\u003c/sup\u003e CD56\u003csup\u003e-\u003c/sup\u003e p63\u003csup\u003e+/-\u003c/sup\u003e, LUSC by TTF-1\u003csup\u003e-\u003c/sup\u003e CK5\u003csup\u003e+\u003c/sup\u003e CD56\u003csup\u003e-\u003c/sup\u003e p63\u003csup\u003e+\u003c/sup\u003e, and LCNEC by TTF-1\u003csup\u003e+/-\u003c/sup\u003e CK5\u003csup\u003e-\u003c/sup\u003e CD56\u003csup\u003e+\u003c/sup\u003e p63\u003csup\u003e-\u003c/sup\u003e. Pathologically unmatched subcutaneous tumors were further categorized into xenograft-associated lymphoproliferative disease (XALD) or epithelial tumor not identical to that of the patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe association between PDX model success rates and patient characteristics was investigated with a chi-squared test. The Cox proportional hazards model was used for multiple analyses of clinically significant prognostic variables. Statistical analyses were carried out with R software for Windows version 4.2.1 (The R Foundation, St. Miami, FL, USA). The odds ratio and its confidence interval were calculated with the “epitools” package of R software. All p-values were two-sided and less than 0.05 was considered statistically significant.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eEstablishment of primary lung cancer PDX models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 642 patients with LUADs, LUSCs, and LCNECs were enrolled in the study between September 2015 and December 2019. Tumor samples from these patients were grafted into NSG mice to establish primary lung cancer PDX models for each cell type. The subcutaneous tumor generation rates were 27.0% in 118 cases from 437 LUAD tumor samples, 58.3% in 109 cases from 187 LUSC tumor samples, and 38.9% in seven cases from 18 LCNEC tumor samples, as shown in Fig. 1a.\u003c/p\u003e\n\u003cp\u003eTo validate pathological concordance with the patient tumors, cell types were examined with antibodies against TTF1, CK5, p63, and CD56 proteins to differentiate human LUAD, LUSC, and LCNEC. For each cell type, representative immunohistochemistry (IHC) images of PDX tumors and the corresponding patient tumors are shown in Fig. 1b. Subcutaneous tumors that did not match the cell types of the patient tumors were further classified into either epithelial or non-epithelial (XALD) cell types (Table 2a).\u003c/p\u003e\n\u003cp\u003eThe order of efficiency in subcutaneous tumor generation was LUSC, LCNEC, and LUAD; however, except for the pathologically irrelevant tumor, the PDX model success was in the order of LCNEC, LUSC, and LUAD. When LUAD was subtyped further into five categories based on histological characteristics, the PDX model success rates were highest in the solid subtype and lowest in the papillary subtype. LUAD had the lowest PDX model success rate (6.6% on average), which was only between 1/6 and 1/7 of those for LUSC or LCNEC (43.33% and 38.9%, respectively; Table 2b). Tumors from patients with an advanced stage of NSCLC tended to have higher PDX model success rates (Table 2c).\u003c/p\u003e\n\u003cp\u003eAmong the pathologically irrelevant subcutaneous tumors, the ratio between the epithelial vs. non-epithelial (XALD) cases were 22.5% vs. 77.5% in LUADs, and 28.6% vs. 71.4% in LUSCs, indicating no major difference between the two cell types. A total of 29 LUAD PDX tumors, 81 LUSC PDX tumors, and seven LCNEC PDX tumors displayed the same pathology as the patient tumors (Table 2a).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical parameters of 642 patients were analyzed to select 12 parameters that influenced the engraftment rates (Table 1). The odds ratios were highest in the patients who was not treated with preoperative chemotherapy and second highest in males. In males, visceral pleural invasion and pStage III or lower were next highest among the advanced stage factors, while in females, tumor size and lymphatic invasion were the next highest.\u003c/p\u003e\n\u003cp\u003e[Table 1 at the end of the text in the manuscript should be placed at this space]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConcordance of somatic mutations in OncoPanel genes in PDX tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeven LUAD cases, eight LUSC cases, and four LCNEC cases were selected from 117 pathologically relevant PDX models to compare the somatic mutations between PDX and patient tumor pairs. OncoPanel genes were analyzed to test whether the driver mutations of the patient tumors were retained in the PDX tumors\u003csup\u003e16\u0026nbsp;\u003c/sup\u003e(Fig. S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSomatic mutations that were absent in the ANT were classified into three groups; that is, those common to PDX models and patient tumors, those found only in patient tumors, and those only in PDX models. In general, most somatic mutations were commonly seen in both PDX models and patient tumors, but a significant number of patient- or PDX-specific somatic mutations that were different depending on the patients and the cell types were also found (Table 3).\u003c/p\u003e\n\u003cp\u003e[Table 3 at the end of the text in the manuscript should be placed at this space]\u003c/p\u003e\n\u003cp\u003eMost somatic mutations found in the patient tumors were retained in the PDX tumors, suggesting that the PDX models could be utilized in preclinical studies. Nonetheless, as not all mutations in the patient tumors were retained in the PDX models; e.g., KRAS mutation negative in LUAD PDX-367 in Table 3, retention of the mutations of interest should be confirmed in the early stages of use of the PDX model.\u003c/p\u003e\n\u003cp\u003ePreexisting mutations might disappear or additional mutations might appear in PDX tumors, for the following reasons: 1) the patient tumor fragments used for pathological examination did not have an identical genetic makeup from those for PDX models due to intra-tumoral heterogeneity, and/or 2) \u003cem\u003ede novo\u0026nbsp;\u003c/em\u003emutations might occur during multiple passage processes for the expansion of tumor tissues. For example, new PDX-specific mutations were found in TP53 in four independent models and in NF1, NOTCH2, CHEK2, EP300, SDHA, DOCK8, and ESR1 in more than two independent models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeviations in gene expression in PDX tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite most somatic mutations being commonly found in both the patient and PDX tumors, existence of the patient or PDX-specific mutations suggested possible discrepancies in gene expression. To address this question, 460 genes in OncoPanel were analyzed for gene expression, and those with\u0026nbsp;|log\u003csub\u003e2\u003c/sub\u003e(fold change)|\u0026gt;2 with respect to the ANT were selected as DEGs in patient or PDX tumors (Fig. S1, Table 4).\u003c/p\u003e\n\u003cp\u003e[Table 4 at the end of the text in the manuscript should be placed at this space]\u003c/p\u003e\n\u003cp\u003eFirst, there was a trend for more genes to be either up- or downregulated in PDX tumors than in patient tumor tissues. HIST1H3B was significantly upregulated in both patient and PDX tumors with little exception, which might indicate a cancer-specific phenomenon, supported by the fact that it is engaged in wrapping newly synthesized DNA as a core component of the nucleosome\u003csup\u003e17\u003c/sup\u003e. On the other hand, ENG was downregulated in both patient and PDX tumors; particularly, in more than 60% of the cases, ENG and PDGFRA were downregulated together. Those genes related to wound healing (COL7A1)\u003csup\u003e18\u003c/sup\u003e, or tumor cell proliferation\u0026nbsp;(HIST1H3B, BRCA1, CDKN2A, and POLQ)\u0026nbsp;were upregulated, and those involved in angiogenesis, hypoxia, and connective tissue remodeling (ENG, PDGFRA, GATA2, and KDR) were downregulated\u003csup\u003e19, 20, 21, 22, 23\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIt is known that extracellular matrix remodeling or angiogenesis is induced by hypoxia, and the oxygen concentration in the tumor is regulated by the master regulator HIF-1a\u003csup\u003e24\u003c/sup\u003e. Therefore, it was necessary to investigate the association between HIF-1a expression levels with hypoxia or angiogenesis in PDX tumors. The HIF-1a expression in PDX tumors, patient tumors, and ANTs was comparatively analyzed for hypoxia (Table S2). HIF-1a expression levels in LUAD and LUSC PDX tumors were higher than ANTs, but lower than the patient tumors, at the level of 62%~75%. In other words, hypoxia occurred in most PDX tumors at a relatively lower level than the patient tumors, which was similar to the above observation that the four genes in OncoPanel (ENG, PDGFRA, GATA2, and KDR) were involved in hypoxia and angiogenesis were downregulated in PDX tumors compared with patient tumors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDownregulated expression of hypoxia- and angiogenesis-related genes in PDX tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo understand whether the lower expression of hypoxia- or angiogenesis-associated genes in PDX tumors was a consistent phenomenon,\u0026nbsp;data from Gene Set Enrichment Analysis and the signature genes for hypoxia or angiogenesis in recent reports were consolidated to create expanded gene sets (Tables S3, Table S4). Among these two gene sets, DEGs with\u0026nbsp;|log\u003csub\u003e2\u003c/sub\u003e(fold change)|\u0026gt;2 were selected from the DEG mother database described in the Methods section. The selected genes were associated with the TME component cells in which those genes were generally expressed; i.e., epithelial tumor cells, murine cancer-associated fibroblasts (CAF), endothelial cells, and immune cells of PDX tumors (Table 5).\u003c/p\u003e\n\u003cp\u003e[Table 5 at the end of the text in the manuscript should be placed at this space]\u003c/p\u003e\n\u003cp\u003eIn comparison to the patient tumors, hypoxia-related genes that were downregulated in PDX tumors commonly to LUAD and LUSC, to LUAD and LCNEC, and to LUSC and LCNEC are listed in Table 5a. Twenty genes were mainly expressed in fibroblasts, and four genes in endothelial cells. Likewise, angiogenesis-related genes that were downregulated in PDX tumors commonly to LUAD and LUSC, to LUAD and LCNEC, and to LUSC and LCNEC are listed in Table 5b. Thirty-five genes were mainly expressed in fibroblasts and 28 genes were mainly expressed in endothelial cells. CXCR4, VCAN, FAP, FN1, FOS, TGFB3, and CCL2 were expressed in fibroblasts, and FLT1, TEK, ANGPT2, and SPP1 were expressed in endothelial cells that belonged to both hypoxia- and angiogenesis gene sets.\u003c/p\u003e\n\u003cp\u003eMost hypoxia and angiogenesis-related genes that were mainly expressed in fibroblasts were downregulated. Therefore, low HIF-1a expression as well as low levels of expression in hypoxia- and angiogenesis-associated gene sets in PDX tumors might be caused by the murine TME, specifically murine fibroblasts.\u003c/p\u003e\n\u003cp\u003eUnlike LUAD or late stage LUSC PDX tumors, early stage LUSC PDX tumors had relatively upregulated genes, compared to the patient tumors: For the hypoxia-related genes, CDKN3 and TPBG were expressed in fibroblasts, and FOSL1 and GRIN2D were expressed in endothelial cells. For angiogenesis-related genes, AURKA, BIRC5, E2F1, ECT2, and UBE2T were expressed in tumor cells, AURKB, JAG2, MBL2, SOX2 in fibroblasts, and ETV4, HMGA1, SLC7A5 in endothelial cells. Relatively high PDX engraftment rates in LUSCs appeared partly associated with upregulation of the hypoxia- and angiogenesis-related genes. On the contrary, PDX tumors of late stage LCNEC cell types had one upregulated gene (i.e., PRODH) in tumor cells and one upregulated gene (i.e., ID1) in endothelial cells.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePDX animal models are generated by grafting patient-derived tumors to immunodeficient mice, which reconstitutes the tumors with pathological relevance to the original patients. It is necessary to timely generate the PDX models effectively when studies with animal models are needed for specific cancer patients. In spite of the effort paid to establish PDX models, not much in-depth discussion has occurred on the key factors that determine the PDX engraftment rates. Molecular genetic deviations from the original patient tumors, such as somatic mutations and altered gene expression\u003csup\u003e25, 26\u003c/sup\u003e, may produce pathologically irrelevant subcutaneous tumors, causing transitions to different epithelial cell types or to non-epithelial tumors (XALD) (70% and 30%, respectively; Table 2), resulting in low engraftment rates.\u003c/p\u003e\n\u003cp\u003eIn this study, by analyzing the differences in somatic mutations and gene expression between the PDX tumors and the tumor of primary NSCLC patients, we aimed to understand the reason for low PDX engraftment rates in NSCLC at a molecular level. To this end, the authors took a retrospective data-collection and analyses approach, rather than hypothesis-generation and test approach.\u003c/p\u003e\n\u003cp\u003eTypically, tumors generate local hypoxia as they grow, and hypoxia-related genes, including HIF-1a, are activated. A variety of adaptive autophagic responses are initiated, such as epithelial-mesenchymal transition (EMT) of tumor cells and dedifferentiation into cancer stem cells\u003csup\u003e27, 28, 29, 30, 31\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTumor hypoxia increases mutation burdens\u003csup\u003e32, 33\u003c/sup\u003e, particularly enriching driver mutations in TP53, MYC, and PTEN\u003csup\u003e34, 35\u003c/sup\u003e. At the same time, a local oxygen gradient appears in CAF in the TME that aids tumor subclonal evolution, resulting in further intratumor heterogeneity\u003csup\u003e36\u003c/sup\u003e. Through aberrant paracrine signaling and matrix remodeling, the niches necessary to maintain cancer stem cells are generated\u003csup\u003e37, 38, 39, 40\u0026nbsp;\u003c/sup\u003eand the angiogenic signals stimulated by hypoxia support endothelial sprouting and tumor growth as well\u003csup\u003e24, 41, 42, 43, 44, 45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAngiogenesis reoxygenates tumors and HIF-1a becomes inactivated, but as the tumor grows local hypoxia is re-generated\u003csup\u003e46, 47\u003c/sup\u003e. Through this cycling hypoxia, further clonal evolution facilitates an even more complex genomic situation (Fig. 2)\u003csup\u003e48, 49, 50\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWhen grafted to NSG mice, most tumors form internal hypoxia at a relatively early stage, as supported by increased TP53 somatic mutations in a PDX-specific manner\u003csup\u003e35, 49\u003c/sup\u003e(Table S2, Table 3). During serial passaging to expand the PDX tumors, the fore-mentioned cycling hypoxia increases tumor heterogeneity and diversifies growth rates, generating epithelial tumors with rare cell types that may not match the initially grated tumors of the patients \u003csup\u003e51\u003c/sup\u003e. Histological inter-conversion between LUAD and LUSC\u003csup\u003e52, 53, 54\u003c/sup\u003e or conversion from NSCLC to SCLC\u003csup\u003e55, 56\u003c/sup\u003e has been reported when lung cancer patients are treated with EGFR-tyrosine kinase inhibitor or chemotherapy, but the similarities and differences with our pathologically deviant PDX tumors require further investigation.\u003c/p\u003e\n\u003cp\u003eHypoxia in subcutaneous tumors affect the presence of Epstein-Barr virus (EBV), which is ubiquitous in the human body\u003csup\u003e57\u003c/sup\u003e. Latent EBVs in lymphocytes that are infiltrated in patient tumors are lytically reactivated by HIF-1a that is activated by tumor hypoxia, which is formed when grafted into immune-deficient NSG mice\u003csup\u003e58, 59\u003c/sup\u003e. Human lymphocytes transformed by P1 viral oncogenes\u003csup\u003e60\u003c/sup\u003e can proliferate under normoxic as well as hypoxic conditions\u003csup\u003e61\u003c/sup\u003e, forming XALD. As such, tumor hypoxia seems to play a key role in the generation of pathologically unmatched subcutaneous tumors, such as phenotypic conversion of cell types or XALD.\u003c/p\u003e\n\u003cp\u003eIn preclinical, co-clinical, or collateral studies using PDX models as a drug testbed, TME is a key factor determining the responses\u003csup\u003e62, 63\u003c/sup\u003e. In PDX models, many murine stromal cells are not functional and B- and T-cells do not mature, and no natural killer cells exist, and myeloid cells, such as macrophages and dendritic cells, are defective\u003csup\u003e64, 65\u003c/sup\u003e, leaving murine fibroblasts as the only functional stromal cells in TME. Human CAF in the patient tumor fragments is known to be diluted and gradually substituted by murine CAFs during serial passages in NSG mice\u003csup\u003e66, 67\u003c/sup\u003e. Therefore, to utilize PDX tumors as a copycat of the patient tumor, not only somatic mutations but also changes in gene expression caused by TME modification need to be analyzed in-depth between patient and PDX tumors.\u003c/p\u003e\n\u003cp\u003eUnlike patient tumors in which the angiogenic factors are produced and released by tumor cells, CAF and tumor infiltrating immune cells, including lymphocytes and macrophages\u003csup\u003e27, 43\u003c/sup\u003e, in PDX tumors, the main sources of angiogenic factors, are the human tumor cells and the murine CAFs, which require effective cell-cell communication across species.\u0026nbsp;In patient tumors, growing cancer cells are in continuous contact with human fibroblasts from early stages for extended periods of time to form conditioned CAFs, but in PDX tumors, direct abrupt contacts with unconditioned murine fibroblasts may cause prolonged chronic hypoxia and autophagy at an early stage. As a consequence, compared with patient tumors, HIF-1a activation levels were lowered (Table S2), and the weakened angiogenesis may delay tumor growth and decrease tumor engraftment rates, even leading to the failure of tumor formation (Table 2a). In PDX LUSC and LCNEC tumors, some of the angiogenesis-related genes were upregulated, but not in those of LUAD (Table 5). Maybe this is why LUAD had significantly lower engraftment rates in NSG mice than other cell types.\u003c/p\u003e\n\u003cp\u003eWhen PDX tumors were used to generate a humanized PDX model, the humanized mouse infused with CD34+ human hematopoietic stem cells have fully differentiated functional human myeloid cells that substitute for the defective dendritic cells and macrophages to partly rescue TME in PDX tumors. Even so, the murine fibroblasts still have to play a role in mediating the crosstalk between the tumor mass and the tumor infiltrating immune cells as well as the endothelial cells\u003csup\u003e68, 69\u003c/sup\u003e. Thus, murine fibroblasts make a critical contribution to angiogenesis for the successful growth of grafted human tumors in humanized PDX models as well as in PDX models.\u003c/p\u003e\n\u003cp\u003eConcordant with a number of previous studies \u003csup\u003e70\u003c/sup\u003e, the pathologically relevant PDX models in this study showed that various somatic mutations, including driver mutations and intra-tumoral heterogeneities, were retained through serial passages, and relative to ANT, the patient and PDX tumors showed similar expression patterns (Table 3, Table 4). Expanded after serial passages, PDX models have potential for developing targeted drugs in preclinical studies, or in co-clinical or collateral studies for immunotherapies after being grafted to the humanized NSG mice.\u003c/p\u003e\n\u003cp\u003eNonetheless, depending on the cell types of the patient tumors, some PDX tumors showed additional somatic mutations, and different fragments of the same patient tumors often showed a variety of growth patterns, which indicated that intratumor heterogeneity might be an inevitable factor causing variation in each individual, even within the specific PDX model. Unlike somatic mutations, differences in gene expression were considerable between the PDX and patient tumors. Therefore, caution is warranted when using PDX models to evaluate the systemic effects of targeted drugs and to translate the outcome into clinical applications.\u003c/p\u003e\n\u003cp\u003eThere have been a number of studies pointing out the intratumor heterogeneity of PDX models \u003csup\u003e71, 72, 73, 74\u003c/sup\u003e. To enhance the engraftment efficiencies of PDX tumors, and to minimize the clonal evolution during serial passages, mouse fibroblasts need to be conditioned quickly by the human tumors, with angiogenesis proceeding without delay, and EBV-activation needs to be interrupted effectively \u003csup\u003e75, 76\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCurrent protocols for PDX model preparation often result in significantly diverse engraftment rates, depending on tumor types, and rare patient tumors that are valuable for clinical research are frequently lost during the process. For PDX models to qualify for wide use in preclinical studies for drug development as well as in collateral studies for clinical benefit, the engraftment rate needs to be elevated, and TME, especially fibroblasts, close to that of the patient tumors needs to be established in the PDX models. Murine fibroblasts, defective murine macrophages, and EBV-infected lymphocytes are some of the key factors contributing to the inefficiency of PDX tumor generation when associated with tumor hypoxia, which may provide basic knowledge for a strategic improvement in graft efficiencies in the future.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANT, adjacent normal tissue; CAF, cancer-associated fibroblast; DEG, differentially expressed gene; EBV, Epstein-Barr virus; EMT, epithelial-mesenchymal transition; H\u0026amp;E, hematoxylin and eosin; IHC, immunohistochemistry; IRB, institutional review board; LCNEC, large cell neuroendocrine carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; PDX, patient-derived xenograft; SCLC, small cell lung cancer; TME, tumor microenvironment; WES, whole exome sequencing; WTS, whole transcriptome sequencing; XALD, xenograft-associated lymphoproliferative disease\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProfessional English writing service was provided by Enago for the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ Lee wrote most of the manuscript. CH Seo and MY Park performed the genomic analysis. BK Kim assisted the data collection, image preparation and drafting. S-H Kim assisted the manuscript writing and editing. JH Lee, HK Kim, JH Cho, YS Choi, S Shin, J Kim provided the patients’ tumor tissues and clinical information. Y-A Choi prepared the human tumor tissue for xenograft. JH Kang collected patients’ clinical information and performed the H\u0026amp;E and IHC staining.HK Song, and HY Jang prepared the PDX models. J-E Lee supervised the entire process of PDX model development. S Lee supervised the genomic analysis. M Cho and D-S Son performed the statistical analysis of the patients’ clinical information and their association with engraftment efficiency of PDX. J Lee, CH Seo, and BK Kim equally contributed to this study. J Lee, J-E Lee, and J Kim supervised the entire study. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe majority of this work was supported by the Technology Innovation Program of the Ministry of Trade, Industry, and Energy, Republic of Korea (Grant No. 10050154), and partly by DNA Link, Inc.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients provided written informed consents authorizing the collection and use of their body tissues for study purposes. This study was approved by the IRB of Samsung Medical Cancer (2014-10-069, 2015-04-018, 2018-03-110)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients provided written informed consents authorizing the collection and use of their body tissues for study purpose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDNA Link, Inc., Kangseo-gu, Seoul, South Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDivision of Data Science and Data Science Convergence Research Center, College of Information Science, Hallym University, Chuncheon, South Korea\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eEwha Research Center for Systems Biology (ERCSB) and Department of Life Science, Ewha Womans University, Seoul, South Korea\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBarta JA, Powell CA, Wisnivesky JP. 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Neoplasia 2017;19(8)628-636.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 5 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"hypoxia, angiogenesis, murine fibroblast, tumor microenvironment, cell types, primary lung cancer","lastPublishedDoi":"10.21203/rs.3.rs-2930778/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2930778/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Patient-derived xenograft(PDX) models of primary lung cancer have been reported. However, varying engraftment rates and their underlying mechanisms for specific subtypes of lung cancer (adenocarcinoma, squamous cell carcinoma, and large cell neuroendocrine carcinoma) have not been studied. The authors prepared subcutaneous tumors grown in NSG™ mice with primary tumors of lung cancer patients to develop lung cancer PDX models. Pathological features of the subcutaneous tumors were compared with those of the patients. One hundred seventeen lung cancer PDX models retaining the original pathologic features were obtained from 642 primary lung cancer patients. Nineteen PDX tumors and the corresponding patient tumors, representing three subtypes of cell lung cancer, were selected and analyzed with in-depth genomic and transcriptomic profiling. Results showed the PDX tumors retained most of the somatic and oncogenic mutations with limited levels of additional xenograft-specific mutations. Significant downregulation of the genes involved in hypoxia-associated angiogenesis was found compared with the corresponding human tumors. This downregulation was associated with murine fibroblasts in the PDX tumor microenvironment, which might be an important factor in low engraftment rates in primary lung cancer PDX models.","manuscriptTitle":"Concordance and deviations of the PDX tumors from the primary tumors of NSCLC patients: effects of murine fibroblasts on low engraftment rates","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-06 13:48:41","doi":"10.21203/rs.3.rs-2930778/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d17c55f-6569-42a7-a95a-744513b1bb26","owner":[],"postedDate":"June 6th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-02T09:44:41+00:00","versionOfRecord":[],"versionCreatedAt":"2023-06-06 13:48:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2930778","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2930778","identity":"rs-2930778","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}