ERBB2 deficiency enhances colorectal cancer progression through EGFR-dependent compensatory mechanisms

ERBB2 deficiency enhances colorectal cancer progression through EGFR-dependent compensatory mechanisms | 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 Article ERBB2 deficiency enhances colorectal cancer progression through EGFR-dependent compensatory mechanisms David Threadgill, Kaitlyn Carter, Michael McGill, William Leach, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8802187/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract ERBB2 is mutated or amplified in a subset of colorectal cancers (CRCs) and may be a marker of resistance to anti-epidermal growth factor receptor (EGFR) therapeutics and help to identify patients who may benefit from ERBB2-directed therapeutic management. To further investigate the role of ERBB2, we generated a population of Erbb2 -deficient Apc Min/+ mice ( Apc Min/+ , Erbb2 f/f , Tg(Vil-Cre) ). We found that Erbb2- deficieny modulates CRC initiation but enhances progression in the Apc Min/+ model. Transcriptomic analysis predicted EGFR activation, which likely mediates the progression that leads to the larger tumors observed in the absence of functional ERBB2. Further in silico predictions confirmed this prediction and indicated involvement of oncogenic Kras mutations, which are essential in determining the progression program by which this operates, similarly to EGFR-independent CRC. Further analysis confirmed activation of EGFR and subsequent activation of MAPK pathway through MEK/ERK. These preclinical analyses suggest an important role for ERBB2 in CRC and highlight the need for further characterization to identify and predict the merit of potential combinatory therapies and patient populations that may benefit from ERBB2-directed therapy in tandem with EGFR therapy. Biological sciences/Cancer/Cancer models Biological sciences/Cancer/Cancer genetics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Colorectal cancer (CRC) is the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths in the United States and globally. Continual advancements in therapies have made substantial progress in mortality rates for older populations, but trends are on the rise for those in younger populations. These advancements have included routine colonoscopy, surgical resection, chemotherapy, immunotherapy, and combinatorial therapies, which have overall improved patient outcomes and undoubtedly reduced CRC morbidity. Continued investigations into molecular and genetic targets of various cancer types has identified additional therapeutic targets or biomarkers for positive response to existing therapies. One such target, ERBB2 , is mutated or amplified in a subset of CRCs and may be a marker of resistance to anti-Epidermal Growth Factor Receptor (EGFR) therapeutics and help identify patients who may benefit from ERBB2-directed therapeutic management. Oncogenic alterations of ERBB2 are found in multiple cancer types, including CRC. ERBB2 genomic amplification or mutations occur in roughly 7% of CRCs and 4% of metastatic CRCs, in which trastuzumab (anti-ERBB2) therapies have shown some efficacy ( 1 ). Under homeostatic conditions, stimulation of ERBB2 can result in the promotion of cell proliferation, differentiation, and suppression of apoptosis, which is tightly regulated ( 2 ). In the case of amplification leading to hyperactivation of ERBB2, these routine developmental processes continue unrestrained and can result in hyperproliferation, survival, and ultimately tumorigenesis ( 3 ). Unlike the other ERBB receptor family members, ERBB2 does not bind any known ligands; instead, its activation is mediated by heterodimerization with other ligand-bound ERBB receptor members, primarily EGFR ( 4 ), and can be activated by culture conditions through auto-phosphorylation ( 5 ). As such, recently identified somatic activating mutations in ERBB2 , which are often paired with amplification of ERBB2 , can cause constitutive activation of proliferative and survival signals that are more tumorigenic than amplification alone ( 6 ). However, ERBB2 mutations and amplification in CRC are heterogeneous in nature and result in varying expression patterns across samples ( 7 ). The elucidation of the genetic context of ERBB2 alterations is important to understand how these CRC progression programs are modulated. Alterations in ERBB2 have been reported in both Microsatellite Stable (MSS) and hypermutated Microsatellite Instable (MSI) CRC patient populations, often with an accompanying KRAS mutation ( 6 , 8 ). Consequently, further characterization is required to determine the etiological and functional implications of ERBB2 mutations in different contexts and subtypes of CRC. The status of ERBB2 alterations as a biomarker for poor prognosis in breast ( 9 ) and gastroesophageal ( 10 ) cancer is well established. Patients with these cancers exhibiting ERBB2 alterations are routinely treated with the ERBB2-directed antibody trastuzumab in combination with chemotherapy ( 11 , 12 ). Other research suggests a promising patient response to sequential treatment with ERBB2-targeted tyrosine kinase inhibitors ( 13 ). In the context of CRC, the introduction of ERBB2 mutations or amplification in immortalized murine colon epithelial cell lines has confirmed the transforming capacity of ERBB2 ( 6 ) and demonstrates its ability to confer resistance to EGFR-targeted therapeutics, including cetuximab ( 14 , 15 ). Until recently, no drugs were approved by the FDA to target ERBB2 for CRC. Combination therapy of tucatinib and trastuzumab in RAS wild-type and ERBB2 overexpressing mCRC patients has improved outcomes and warranted accelerated approval ( 16 ). Combinatorial therapy with trastuzumab and pertuzumab further highlights the importance of ERBB2 genomic status and complexity when investigating potential compensatory mechanisms in CRC progression ( 17 ). As such, the status of ERBB2 as a therapeutic target and biomarker in broader patient populations is still emerging. Aberrant expression and activation of EGFR is common in many solid tumors of epithelial origin, particularly CRC ( 18 ). However, our group has recently demonstrated that CRC is not only capable of initiating independently of EGFR but also adopts a more aggressive progression program than EGFR-dependent cancers due to IL10-mediated anergy and JAK/STAT signaling activation, creating a pro-tumoral tumor micro-environment (TME) ( 19 ). There is an association between ERBB2 upregulation and EGFR-targeted therapeutic resistance ( 14 , 15 ). However, the potential role of ERBB2 in the progression of this subset of EGFR-independent CRC has yet to be investigated. In this study, we report that ERBB2-independent cancers exhibit similarities to EGFR-independent cancers in their disposition to initiate and propensity to progress more aggressively. Using the Apc Min/+ mouse model of CRC, we found that intestinal-specific genetic ablation of Erbb2 protects against CRC initiation but enhances progression. We provide transcriptomic evidence indicating the activation of EGFR in Erbb2 -deficient tumors, providing a potential mechanism for the increased size of these tumors. Notably, GSEA using human oncogenic molecular signatures supported these predictions about EGFR activation and reinforced this mouse model's clinical relevance. Further, we present evidence that Erbb2 -deficient tumor transcriptomic profiles are enriched with genes upregulated in EGFR-independent cancers progressing with wild-type Kras , supporting the importance of KRAS status in modulating the immune environment and as a biomarker for guiding therapy. Further validation confirmed compensatory activation of EGFR through the MAPK pathway, indicated by high levels of phosphorylated MEK1/2 in Erbb2- deficient tumors relative to control. Cooperatively, these results support a role for ERBB2 in initiating CRC and suggest further characterization is needed to identify potential combinatory therapies and patient populations that may benefit from ERBB2-directed CRC management. Materials and methods Animal experiments Mice were obtained from The Jackson Laboratory (C57BL/6J- Apc Min/+ [ Apc Min/+ ]) ( 21 ) and NCI-Frederick (B6;D2- Tg(Vil-cre)20Syr [ Tg(Vil1-Cre) ] ( 22 ), which were maintained on a hemizygous B6 background. B6.129X1(Cg)- Erbb2 tm1Mll ( Erbb2 f ) ( 23 ) was obtained from the European Mutant Mouse Archive through the International Mouse Strain Resource. Strains were backcrossed for 10 generations on a C57BL/6J background and confirmed congenic by genome analysis. Mice were housed five per cage, fed Purina Mills Lab Diet 2919 ad libidum , and maintained at 22°C under a 12-hr light cycle. Mice were euthanized by CO 2 asphyxiation for tissue and serum collection. Tumor and normal adjacent tissue samples were resected from 100-day old Erbb2 -deficient Apc Min/+ mice ( Apc Min/+ , Erbb2 f/f , Tg(Vil-Cre) ) and control Apc Min/+ mice ( Apc Min/+ , Erbb2 f/f ) for analysis. Genotyping Mice were genotyped for the Apc Min allele as previously described ( 24 ). Mice were genotyped for other pertinent alleles using PCR with primers designed to amplify the target gene or transgene (Supplementary Table 1) Macroadenoma quantification Following euthanasia, the GI tract was excised and opened longitudinally. The tumor number, diameter, and location were recorded for the entire length of the small intestine and colon using a dissecting microscope and in-scope micrometer at 5x magnification. Tumor scoring was performed without knowledge of genotype by the investigator. Five colon tumors from each group were confirmed by H&E staining. Histology Intestinal and colon tissues were collected and fixed in 10% neutral buffered formalin overnight. Fixed tissues were embedded in paraffin and cut into 5µm sections. Every tenth section was stained with H&E for histologic review. Sections were deparaffinized in xylene, followed by hydration in ethanol. Slides were then incubated in fresh hematoxylin (VWR 95057-844) and washed in distilled water before differentiation in acid alcohol. After incubation in bluing solution (American Mastertech HXB00242E) and rinsing with distilled water, slides were counterstained with 0.25% eosin Y (Sigma E4382), rinsed, dehydrated, and mounted. Crypt length was measured using the Leica Application Suite X v1.4.5, and crypts in three random frames from five H&E-stained sections from each group were measured by an investigator blinded to genotype. Immunohistochemistry Sections were deparaffinized and rehydrated before antigen retrieval by boiling in sodium citrate buffer, pH 6.0, for 20 minutes. Sections were then quenched by treatment with 0.3% hydrogen peroxide in TBS for 15 minutes. After rinsing with TBS, sections were blocked in TBS with 3% goat serum for two hours before incubating with the anti-Ki67 primary antibody (Abcam ab15580, 1:1,000) overnight at 4°C. Sections were rinsed again with TBS before incubation with the HRP-conjugated goat anti-rabbit secondary antibody (Abcam ab205718, 1:20,000) in TBS for one hour. Antigen-antibody complexes were detected using the DAB substrate kit (Abcam ab64238) following the manufacturer’s instructions. Sections were counterstained with hematoxylin before dehydration, clearing, and mounting. Cells were scored as positive in three random frames from five mice per group using Fiji software ( 25 ) by an investigator blinded to genotype. Additional sections were stained with SignalStain Apoptosis (Cleaved Caspase-3) IHC Detection Kit (Cat. No:12692; Cell signaling Technology, USA) and performed to manufacturer’s instructions. RNA sequencing and differential gene expression analysis A total of three sequencing runs were performed to sequence 20 samples (five tumor and five adjacent normal samples from both Erbb2 -deficient and littermate control Apc Min/+ mice) on an Illumina NovaSeq 6000 instrument at the North Texas Genome Center. Libraries were prepared in the Texas A&M Institute for Genome Sciences and Society Molecular Genomics Core using the S4 reagent kit v1.5. A total of ~ 920 million 150bp paired-end reads were trimmed of adapter sequences and low-quality bases using Trimmomatic ( 26 ), resulting in roughly 914 million filtered reads (99%). Filtered reads were aligned to mouse assembly mm39 using HISAT2 version 2.2.1 ( 27 ) with an overall mapping rate of ~ 96%. Raw transcript counts were generated using HTSeq version 2.0.2 ( 28 ). Read counts were normalized, and gene expression analyses were performed using DESeq2 ( 29 ). IPA (Qiagen) was used to analyze differentially expressed genes between groups. Raw and processed RNAseq data have been deposited in NCBI’s Gene Expression Omnibus ( 30 ) and are accessible through GEO Series accession number GSE241084. Gene set enrichment analysis GSEA was performed using the GSEA software version 4.3.2 ( 31 , 32 ). Feature expression levels in tumor samples were normalized, accounting for sequencing depth and RNA composition, to expression levels in corresponding adjacent normal tissue and across samples using the median of ratios method in DESeq2 ( 33 ). EGFR and MEK upregulation human molecular signatures ( 34 ) were retrieved from the Molecular Signatures Database Human Collection (MsigDB v2023.1.Hs). The EGFR-independent with wild-type Kras upregulation (n = 240 genes) and EGFR-independent with mutant Kras upregulation (n = 254) mouse molecular signatures were generated by selecting genes specific to Apc f/f , Egfr f/f or Apc f/f , Egfr f/f , Kras G12D/+ tumors with log 2 fold change > 2 and adjusted p-value < 0.05. The analysis parameters were set to rank genes by the signal-to-noise ratio in 1,000 gene set permutations to assess the statistical significance of the normalized enrichment score (NES). Gene sets with nominal p-value < 0.05 and FDR < 0.25 were considered significantly enriched and evaluated further. Reverse transcription-quantitative polymerase chain reaction Total RNA from tumors and adjacent normal tissue was isolated using Maxwell LEV simplyRNA Tissue Kit (Promega AS1280) according to the manufacturer’s instructions. Total RNA was converted to cDNA using the Transcriptor First Strand cDNA Kit (Roche 04896866001). RT-qPCR reactions were performed in triplicate using cDNA with LightCycler® 480 SYBR Green I Master Mix (Roche 04887352001) on a LightCycler® 96 System (Roche). Primer pairs were designed to amplify a fragment specific to the target gene (Supplementary Table 1). Fold expression differences were calculated using the 2 − ΔΔC T method relative to Gapdh or Actb expression ( 35 ). Enzyme-linked immunosorbent assay Neuregulin I (NRG1) concentrations in mouse serum were measured using the Mouse NRG1 ELISA Kit (Novus Biologicals NBP2-68070). Concentrations were interpolated from absorbance using a four-parameter logistic curve fit. Samples were run in triplicate in three independent tests. Western blotting analysis Tissues collected at necropsy were frozen in liquid nitrogen and stored at -80°C. Tissues were homogenized in 1X RIPA Buffer (Cell Signaling Technologies #9806) which was diluted from 10x to 1x using ddH2O. Halt Protease Inhibitor Cocktail (1x) (ThermoScientific 78430) and PMSF Protease Inhibitor (1 mM) (ThermoScientific 36978) were added to 1x RIPA Buffer prior to homogenization. The concentration of cleared lysate was measured using Pierce BCA Protein Assay Kit (ThermoScientific 2327), and 20 ug of tumor and normal adjacent lysate were added to 4–15% Mini-PROTEAN TGX Precast Gels (Bio-Rad) depending on the protein of interest, electrophoresed, and transferred to a nitrocellulose membrane (Bio-Rad #1620115). The membrane was then incubated for 1 hour in 5% non-fat dry milk (SantaCruz Biotechnology sc-2324) in 1x TBS-T. The membrane was subsequently incubated with primary antibody overnight at 4°C. After incubation with primary antibody, blot was washed with 1x TBS-T 3 times and incubated with 5% nonfat dry milk blocking solution containing goat anti-rabbit polyclonal HRP-conjugated secondary antibody for 1 hour at room temperature (Abcam ab6721). The membrane was washed 4 times with 1x TBS-T and visualized using SuperSignal West Fempto Maximum Sensitivity Substrate following 5-minute incubation (ThermoScientific 34095). The antibodies used were GAPDH, EGFR, Phospho-EGFR, Phospho-MEK1, Phospho-ERK1/2 (Cell Signaling Technologies), and MEK1, ERK1 (Abcam). Relative protein was calculated using ImageJ. Statistical analysis All biological replicate sample numbers (n) can be found in the figure legends. The number of technical replicates can be found in the details of the methods. The number of animals needed per group was estimated using JMP (SAS Institute) based on an α-value of 0.05 and a desired power of 0.8. An equal number of male and female animals were evaluated in experiments. The representative whole mount, H&E, and IHC staining images represent one of at least three biological replicates. The nonparametric Mann–Whitney U test was used to analyze tumor data. To compare the difference between the means of two groups, the Student’s t -test was used. ANOVA with post hoc Tukey’s HSD was used to compare the difference between the means among three or more groups. P-values less than 0.05 were considered statistically significant. Statistical details and p-values can be found in the figure legends. No samples or animals were excluded from the analysis, and all experiments reported in this study were repeated at least three independent times. All data are represented as mean ± SEM. Studies were conducted blind as indicated in the methods. Statistical analysis and figure generation were performed by GraphPad Prism version 9.5.1. Ethics statement Animal experiments were approved by the Institutional Animal Care and Use Committee at Texas A&M University conforming to the Guide for the Care and Use of Laboratory Animals. Results Loss of Erbb2 hinders polyp initiation but supports enhanced growth Owing to the growing interest in ERBB2 amplification as a potential targetable mechanism of resistance to EGFR-targeted therapy in patients with CRC (15, 16), paired with the increased expression of Erbb2 during EGFR-independent progression of CRC in preclinical mouse models (19), we investigated the effect of genetic ablation of Erbb2 on CRC progression using the conditional Erbb2 f allele. Ablation of Erbb2 was induced by a transgene expressing Cre recombinase under the control of the epithelial-specific Villin promoter Tg(Vil1-cre). In the Apc Min/+ model of CRC, we observed a significant reduction in the number of intestinal and colon polyps in Erbb2 -deficient ( Apc Min/+ , Erbb2 f/f , Tg ( Vil1-cre )) animals after 100 days when compared to littermate controls ( Apc Min/+ , Erbb2 f/f ) (Fig. 1A and 1B). Erbb2 -deficient and littermate control Apc Min/+ animals developed an average of 45 and 94.2 intestinal polyps per mouse, respectively. This significant reduction in intestinal polyp number was noted in each anatomical portion of the small intestine. Interestingly, polyps that were able to initiate in the context of absence of ERBB2 were significantly larger, primarily in the small intestine (Fig. 1C), as evident by a higher portion of tumors proliferating to a size greater than two millimeters (Fig. 1D). These observations regarding tumor multiplicity and size are similar to those observed in EGFR-independent CRC in the Apc Min/+ model (19). Moreover, analysis of hematoxylin and eosin-stained normal epithelium in Erbb2 -deficient and littermate control Apc Min/+ animals revealed no apparent differences in epithelial morphology, including no significant differences in crypt height. Together, these results support a double-edged role for Erbb2 expression in CRC, suggesting its presence may bolster the initiation of CRC while its absence may promote faster growth, leading to increased tumor size. To investigate the cellular mechanism responsible for the increased tumor size observed in Erbb2 -deficient tumors, we compared levels of proliferation in the adjacent normal and tumor tissue of each group (Fig. 2A). Immunohistochemical staining for the proliferation marker Ki67 revealed a significant increase in proliferation in tumors progressing without ERBB2 (Fig. 2B). Immunohistochemical staining was also performed for apoptotic marker cleaved caspase-3 (Fig. 2C), which showed a significant decrease in cell death in the Erbb2 -deficient tumor and normal adjacent tissues relative to control (Fig. 2D). Proliferation in adjacent normal tissue was primarily restricted to the proliferative zones of the crypt regardless of the Erbb2 status. Surprisingly, no significant differences were noted between the Erbb2 -deficient adjacent normal tissue and adjacent normal or tumor tissue from littermate control animals. This suggests that the increased proliferation and decreased apoptosis in the absence of ERBB2 is tumor-specific and that compensatory mechanisms likely allow transformed cells to progress more aggressively through increased proliferation in the absence of ERBB2. Overall, these results suggest that alternative means for progression may be activated in compensation for the loss of ERBB2 and must be further defined. Erbb2 -deficient tumors display a unique gene expression signature To identify potential molecular mechanisms underlying the enhanced proliferation and decrease in apoptosis in the absence of Erbb2 , we sequenced total RNA from five tumor and adjacent normal tissue samples from both Erbb2 -deficient and littermate control Apc Min/+ mice (Fig. 3A). Transcriptomic analysis revealed 1,157 significantly differentially expressed genes characterizing the Erbb2 -deficient progression program in the Apc Min/+ context (Fig. 3B). Surprisingly, in analyzing the top 50 differentially expressed features we found that Erbb2 -deficient tumors displayed a consistent reduction in transcripts reported to be associated with CRC proliferation, survival, and invasion including YEATS domain containing 4 ( Yeats4 ) (20), EGF-like domain 7 ( Egfl7 ) (21), and vascular endothelial growth factor B ( Vegfb ) (22) (Fig. 3C). Further, increased expression of nitric oxide synthase 2, inducible ( Nos2 , also called iNOS) was noted in Erbb2- deficeint tumors, which is characteristic of M1 macrophages and has been associated with favorable prognosis in CRC in patients harboring tumors highly infiltrated by iNOS+ cells (23). Notably, the EGFR-independent subtype of CRC displays a significant increase in iNOS+ M1 macrophages when compared to EGFR-dependent CRC in mice, and the addition of oncogenic a Kras G12D mutation skews the macrophage population towards a CD163 + M2 phenotype (19). Supporting the increased tumor-specific proliferation, Erbb2 -deficient tumors exhibited increased expression of cadherin 17 ( Cdh17 ), which has been associated with activation of WNT/b-catenin (24) and MAPK signaling (25), has been reported as an adenocarcinoma biomarker (26) and oncogene (27), and is currently being evaluated as a therapeutic target in Phase 1 clinical trials (NCT05411133) and has been investigated CAR T cell therapy (28) in Phase 1/2 clinical trials (NCT06055439). Collectively, these results suggest that, while unique, the transcriptomic program employed by Erbb2 -deficient colon tumors resembles the EGFR-independent subtype of CRC through potential modulation of the immune landscape and activation of alternative progression mechanisms. Transcriptomic analysis of Erbb2 -deficient colon tumors predicts activation of EGFR To further refine potential candidate pathways and mechanisms materializing in Erbb2 -deficient tumors, we utilized IPA. This analysis of downstream effects predicted activation of several canonical pathways, including the pathogen-induced cytokine storm signaling pathway (Supplementary Table 2). Subsequent analysis of upstream regulators indicated activation in multiple molecules known to drive progression and are associated with poor prognosis, including EGFR (29), AGT (30), TGFB1 (31), NPM1 (32), and IL6 (33) in addition to inhibition of PTEN, which acts to downregulate PI3K/AKT pro-survival signaling (34) (Table 1). Regulatory network analysis of EGFR revealed further support for the activation of WNT/b-catenin signaling through upregulation of Ctnnb1 by crosstalk with active MAPK signaling (Supplementary Fig. 1). To partially validate these findings regarding WNT/b-catenin and MAPK signaling, we measured the expression of Ctnnb1 , Mapk4 , and Col1a1 by RT-qPCR and found a significant increase in expression in Erbb2 -deficient tumors when compared to adjacent normal tissue and littermate controls (Fig. 4A). This outcome supports the in-silico predictions of EGFR activation and potential crosstalk between WNT/β-catenin and MAPK signaling. Table 1 Top upstream regulators of Erbb2 -deficient tumors. Upstream regulator Molecule type Predicted activation state Activation z-score p-value of overlap EGFR Kinase Activated 3.822 3.22E-06 AGT Growth factor Activated 3.756 2.25E-06 TGFB1 Growth factor Activated 3.597 5.75E-12 NPM1 Transcription regulator Activated 3.153 7.28E-06 IL6 Cytokine Activated 3.114 7.93E-07 NR3C1 Ligand-dependent nuclear receptor Inhibited -3.306 3.29E-07 PTEN Phosphatase Inhibited -3.296 5.18E-04 HNF4A Transcription regulator Inhibited -2.969 7.09E-04 Immunoglobulin Complex Inhibited -2.88 6.75E-03 FKBP10 Enzyme Inhibited -2.828 8.21E-04 EGFR, epidermal growth factor receptor; AGT, angiotensinogen; TGFB1, transforming growth factor beta 1; NPM1, nucleophosmin 1; IL6, interleukin 6; NR3C1, nuclear receptor subfamily 3 group C member 1; PTEN, phosphatase and tensin homolog; HNF4A, hepatocyte nuclear factor 4 alpha; FKBP10, FKBP prolyl isomerase 10. These predictions suggest that tumors that initiate independently of Erbb2 could display an increase in size due to activation of EGFR driven proliferation and survival pathways. Thus, GSEA was conducted to identify enriched pathways conserved in our Erbb2 -deficient model (Fig. 5A). Using this method, Erbb2 -deficient differentially expressed genes were found to be associated with multiple human gene sets, including those related to the hallmarks of epithelial to mesenchymal plasticity and TGFB signaling (35), EGFR, MEK (36), and KRAS upregulation (37), and downregulation of PTEN (38) (Supplementary Table 2). In concordance with the initial analysis, subsequent GSEA revealed significant enrichment of EGFR (NES = -1.33) and MEK upregulation (NES = -1.49) in Erbb2 -deficient tumors (Fig. 5A, 5B). Further, we observed significant enrichment of the Erbb2 -deficient signature with gene sets representing the hallmarks of epithelial to mesenchymal plasticity (NES = -2.17) and TGFB signaling activation (NES = -1.57) (Supplementary Fig. 2). These results confirm predictions from IPA through validation of upstream regulators in EGFR and TGFB1 and their role in Erbb2 -deficient tumor progression. Given the computational support for EGFR activation in this Erbb2 -deficient subset of tumors and knowing the phenotypic similarity between Erbb2 -deficient and EGFR-independent cancers in terms of tumor multiplicity and size (39), we evaluated the degree of similarity between their progression programs at the transcriptomic level. Interestingly, these analyses revealed significant enrichment in the EGFR-independent CRC gene set dependent on Kras status. We observed significant enrichment in genes expressed by EGFR-independent tumors with wild-type Kras (NES = -1.4) (Fig. 6). Conceivably, this is due to the presence of wild-type Kras in our Erbb2 -deficient model as the enrichment of genes expressed by EGFR-independent tumors progressing with the oncogenic Kras G12D mutation failed to reach statistical significance (NES = -1.19) (Supplementary Fig. 3). Knowing the general importance of the immune landscape in CRC progression and response to therapy, including EGFR-independent cancers, the delineation between their progression programs could potentially aid in predicting molecular outcomes of ERBB2 inhibition, especially in the case of resistance to EGFR-targeted therapeutics. To further investigate the intricacies of the pathway by which Erbb2 -independent tumors progress, we further investigated the upregulation of EGFR and MEK that was previously identified in GSEA analysis. Western blotting analysis demonstrated decreased expression of MEK1 and ERK1 in Erbb2- deficient normal adjacent and tumor tissues and Erbb2- containing tumor tissue (Fig. 7A, 7B). When we evaluated EGFR and phosphorylated-EGFR protein expression levels, Erbb2 -deficient tumor and normal adjacent tissue were elevated relative to Erbb2- containing tumor and normal adjacent tissue (Fig. 8A). While p-EGFR levels were increased in these samples, we observed lower EGFR relative protein levels, which could be associated with the EGFR-independent tumor transcriptomic profile. To further evaluate the phosphorylated forms of MEK and ERK and how this could contribute to in silico predictions of MEK upregulation, we confirmed an increase in relative protein level in normal adjacent and tumor tissue for Erbb2- deficient mice. This notable elevation of active MEK and ERK indicates enhanced MAPK signaling, suggesting this as a compensatory pathway and confirming transcriptomic predictions. These results suggest that while the progression programs of ERBB2 and EGFR-independent CRC are unique, there are similarities in compensatory pathways involved, and further evaluation of the robustness of the comparative features of these programs could provide valuable insight into combinatorial therapeutic strategies. Discussion We present evidence suggesting that loss of ERBB2 limits initiation of CRC but supports progression. While the precise molecular mechanism responsible for this tumor-specific increase in proliferation remains to be experimentally validated, we provide transcriptomic analyses suggesting that the increased size of tumors observed in the context of ERBB2 loss could be the result of compensatory activation of EGFR signaling, likely through MEK activation and the subsequent MAPK signaling cascade. We determined that the transcriptional programs adopted by Erbb2 -deficient tumors are significantly enriched for genes upregulated during constitutive EGFR and downstream MEK activation in human contexts, supporting the in silico transcriptional predictions and relevance of this model to human biological contexts. Further, these analyses revealed that the Erbb2 -deficient expression program is significantly enriched with genes associated with EGFR-independent CRC progression, depending on the Kras status, further validated through western blotting analysis, and emphasizes the importance of Kras mutations in determining the characteristics of CRC. Finally, we demonstrated that the increased progression observed in the absence of ERBB2 is partially due to a tumor-specific increase in proliferation. While many questions remain to be answered, the results generated thus far in this study suggest an important role for ERBB2 in the initiation of CRC and illuminate compensatory mechanisms to be explored further, such as investigation into AKT signaling to fully understand the role of proliferation following an ERBB2-independent program ( 41 ). There is significant interest in ERBB2 as a target for therapeutic management in CRC, and it has recently been approved for individuals with mCRC that are RAS wild-type and exhibiting ERBB2 amplification ( 19 ). Several clinical trials have explored the prospect of ERBB2 as a therapeutic target for mCRC using a variety of novel drugs ( 42 ). However, ERBB2 is more commonly overexpressed in CRC before progression to metastatic disease ( 1 ). This observation is insightful and could be actionable given that ERBB2 can stimulate proliferative and survival signals long before the transition into metastatic disease ( 2 , 3 ). As such, there is also significant interest in exploring ERBB2 as a target for broader therapeutic contexts and earlier stages of CRC, highlighting the need for further preclinical investigation. By leveraging mice with intestinal epithelial cell-specific deletion of Erbb2 , we observed a reduction in tumor initiation paired with an increase in tumor-specific proliferation, supporting an important role for ERBB2 in intestinal homeostasis. Of course, fundamental differences exist between the intestinal epithelial cell-specific genetic ablation reported here and pharmacological blockade through classical targeted therapeutic approaches. As a result, if the increased proliferation observed and the activation of compensatory mechanisms depend on the complete loss of ERBB2, then pharmacological blockade of ERBB2 could yield different informative outcomes. However, analysis of trastuzumab- and pertuzumab-resistant breast cancer cell lines demonstrates significant upregulation of both EGFR and ERBB3, corresponding with increased phosphorylation of ERK1/2 and leading to increased proliferation and invasiveness ( 43 ). While much remains to be investigated in the context of CRC, this suggests the potential for similarities between the compensatory progression mechanisms activated in response to genetic ablation of Erbb2 and ERBB2 pharmacological blockade. Notably, discovering any differences in response to genetic ablation or pharmacological blockade will be incredibly informative for uncovering potential contexts that would likely respond favorably to ERBB2 inhibition. Further characterization of these mechanisms will undoubtedly illuminate the potential therapeutic merit of ERBB2 during CRC. This study provides important preliminary evidence suggesting an important role for ERBB2 in initiating and determining the transcriptional progression program utilized in the Apc Min/+ model of CRC. They offer similarities between ERBB2 and EGFR-independent cancers, which could lie in compensatory signaling through ERBB3 and ERBB4 and other related pathways. Collectively, this suggests that ERBB2 contributes to early transcriptional programming in CRC through compensatory MAPK signaling networks, which modulate responsiveness to ERBB2-targeted therapies and highlight the combinatorial therapeutic approach that can overcome resistance mechanisms and enhance current approaches. Declarations Data availability Need statement Contributions Assign my initials Ethics declaration Competing interests The authors declare no competing interests. All support for this work, including grants, equipment, and reagents, has been fully disclosed in the acknowledgements and method sections. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8802187","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":587001013,"identity":"6ecb69d0-cf08-4f08-9bbd-d06eccbcd656","order_by":0,"name":"David Threadgill","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAlUlEQVRIiWNgGAWjYDCCAwyMD6BMA2K1MDMbHCBVC5sEaVr4buQfq/5Qsy2xgb15mwRRWiRvJLPdOHDsdmIDz7Ey4rQY3AZpYQNqkcgxI15LwYF/QC3yb0jQwnCwDWQLD5FaJO8/NpY423fbuI0nrdiCKC18Zw4+/FDx7bZsP/vhjTeI0gIHbKQpHwWjYBSMglGAFwAAQXMzevEQ78cAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-3538-1635","institution":"Texas A\u0026M University","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"","lastName":"Threadgill","suffix":""},{"id":587001014,"identity":"62549acb-6cbd-4261-9d7f-3f1890824fd9","order_by":1,"name":"Kaitlyn Carter","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kaitlyn","middleName":"","lastName":"Carter","suffix":""},{"id":587001015,"identity":"def1f10d-1a0a-4f2c-8f00-e351ae64fc1b","order_by":2,"name":"Michael McGill","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"McGill","suffix":""},{"id":587001016,"identity":"b7aa1a81-a12b-4425-80f0-a222cc69c481","order_by":3,"name":"William Leach","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Leach","suffix":""},{"id":587001017,"identity":"bb7f4ccc-af7e-4e32-9eb3-9c28c74ebcd8","order_by":4,"name":"Wyatt Porter","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Wyatt","middleName":"","lastName":"Porter","suffix":""},{"id":587001018,"identity":"1fef28f9-57be-43a7-a802-9eec305dcbdf","order_by":5,"name":"Meghan Si","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Meghan","middleName":"","lastName":"Si","suffix":""},{"id":587001019,"identity":"4540c845-c137-4752-98b1-8dec540402c2","order_by":6,"name":"Megan Thomas","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Thomas","suffix":""}],"badges":[],"createdAt":"2026-02-06 03:35:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8802187/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8802187/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105993165,"identity":"e18aae62-1b7c-418c-a6d7-2e040178f2ca","added_by":"auto","created_at":"2026-04-02 08:44:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":324480,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of intestinal-specific \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eErbb2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e deficiency on polyp number and size in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eApc\u003c/strong\u003e\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cstrong\u003eMin/+\u003c/strong\u003e\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003emice at 100 days of age.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Intestinal and B colon polyp multiplicity of age-matched \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg(Vil1-Cre)\u003c/em\u003e mice (n = 30 for both groups, including 15 males and 15 females per group). Each dot represents the polyp number of individual 100-day-old mice. Data represented as mean ± SEM, * p = 0.01596, **** p\u0026lt; 0.0001. C Distribution of intestinal polyp diameter by location in the gastrointestinal tract of age-matched \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e (n = 2825 polyps) and \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg(Vil1-Cre)\u003c/em\u003e (n = 1351 polyps) mice. Data represented as mean ± SEM, ** p \u0026lt; 0.01, **** p\u0026lt; 0.0001. D Fraction of polyps by the range of size of \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg(Vil1-Cre)\u003c/em\u003e mice (n = 30 for both groups, including 15 males and 15 females per group). Data represented as mean ± SEM, ** p = 0.008682, **** p\u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/e6b19f854b9c4d2225fdd523.jpg"},{"id":105993170,"identity":"58bfc220-11c5-43aa-b7cc-9890bed5f7e2","added_by":"auto","created_at":"2026-04-02 08:44:04","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":504994,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eERBB2 deficiency enhances tumor-specific proliferation and cell survival.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA \u003c/strong\u003eRepresentative images (scale bars: 100µm) and \u003cstrong\u003eB\u003c/strong\u003e quantification of Ki67-positive cells in adjacent normal tissue and size-matched colon tumors (n=15 per group). \u003cstrong\u003eC\u003c/strong\u003e Representative images (scale bars: 200µm) and \u003cstrong\u003eD\u003c/strong\u003e quantification of cCaspase-3 cells in adjacent normal tissue and size-matched colon tumors from \u003cem\u003eErbb2\u003c/em\u003e-deficient and littermate control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice (n = 5 per group). Data represented as mean ± SEM, ** p = 0.002657, **** p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/2650035b0d547af01c894f92.jpg"},{"id":105993199,"identity":"9bbafe60-5897-47d5-a0bc-4aaa932ec7be","added_by":"auto","created_at":"2026-04-02 08:44:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":522787,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptomic analysis \u003cem\u003eErbb2\u003c/em\u003e-deficient polyps.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Diagrammatic representation of the approach to RNA-seq, analysis, and identification of candidate genetic mechanisms. \u003cstrong\u003eB\u003c/strong\u003e Venn Diagram of Differentially Expressed Genes between \u003cem\u003eErbb2-\u003c/em\u003edeficient and control polyps. \u003cstrong\u003eC\u003c/strong\u003e Heat map of the top 50 features for littermate control (left columns) and \u003cem\u003eErbb2\u003c/em\u003e-deficient (right columns) \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003emice. The heat map is displayed as a spectrum from high expression (dark red) to low expression (dark blue).\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/6fd7a5b904f3c726a6deb09a.jpg"},{"id":106093658,"identity":"7b93ec43-3cc7-4e01-b073-822fd6e14a4c","added_by":"auto","created_at":"2026-04-03 11:38:27","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":307195,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of increased WNT/b-catenin and MAPK signaling pathway activation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Mean transcript levels of \u003cem\u003eCtnnb1\u003c/em\u003e, \u003cem\u003eMapk4\u003c/em\u003e, \u003cem\u003eCol1a1,\u003c/em\u003e and \u003cstrong\u003eB\u003c/strong\u003e \u003cem\u003eNrg1\u003c/em\u003e as quantified by RT-qPCR. Fold expression changes were calculated by the 2\u003csup\u003e-DDC\u003c/sup\u003e\u003csub\u003eT\u003c/sub\u003e method relative to \u003cem\u003eGapdh\u003c/em\u003e expression (n = 3 biological replicates per group). Data represented as mean ± SEM, * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001 (one-way ANOVA). \u003cstrong\u003eC \u003c/strong\u003eCirculating NRG1 levels in mouse serum as quantified by ELISA. Concentrations were interpolated using a four-parameter logistic curve fit (n = 3 biological replicates per group). Data are represented as mean ± SEM, ** p = 0.0051 (Student’s t-test).\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/ef121af679d2baa52fd2cedb.jpg"},{"id":105993166,"identity":"71ca0e88-4b23-41cc-975c-94fd0da6d22b","added_by":"auto","created_at":"2026-04-02 08:44:03","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":586045,"visible":true,"origin":"","legend":"\u003cp\u003eGene set enrichment analysis supports EGFR upregulation in \u003cem\u003eErbb2\u003c/em\u003e-deficient \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003ecolon tumors.\u003c/p\u003e\n\u003cp\u003eGSEA of \u003cstrong\u003eA\u003c/strong\u003e EGFR and \u003cstrong\u003eB\u003c/strong\u003e MEK upregulation oncogenic human molecular signatures. Green lines indicate the enrichment score of each ranked gene in the pathway, represented by black bars below the X-axis. Heatmaps display the relative gene expression of markers in the leading-edge subset. The heat map is shown as a spectrum from high expression (dark red) to low expression (dark blue).\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/927a9dc772c3ba49f6604b2d.jpg"},{"id":105993167,"identity":"cbaf3800-af92-408c-95d4-76801ef154d5","added_by":"auto","created_at":"2026-04-02 08:44:03","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":506550,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptomic profile of \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors is enriched with genes upregulated in the EGFR-independent molecular subtype.\u003c/p\u003e\n\u003cp\u003eGSEA of genes upregulated in the EGFR-independent and wild-type \u003cem\u003eKras\u003c/em\u003e (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eEgfr\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e) oncogenic mouse molecular signature. The green line indicates the enrichment score of each ranked gene in the pathway, represented by black bars below the X-axis. Heatmaps display the relative gene expression of markers in the leading-edge subset. The heat map is shown as a spectrum from high expression (dark red) to low expression (dark blue).\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/f896ff5e53c78dd0e6d4f4e1.jpg"},{"id":105993161,"identity":"f568bcb1-a9e9-43e5-8e23-71a6cd559d9e","added_by":"auto","created_at":"2026-04-02 08:44:01","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":250077,"visible":true,"origin":"","legend":"\u003cp\u003eProtein expression levels of MEK1 and ERK1 in \u003cem\u003eErbb2-\u003c/em\u003edeficient and normal tissues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Representative western blot showing expression of MEK1, ERK1, and GAPDH in \u003cem\u003eErbb2-\u003c/em\u003edeficient and \u003cem\u003eErbb2\u003c/em\u003e-containing tumor and normal adjacent tissue. \u003cstrong\u003eB\u003c/strong\u003e Protein levels were normalized to the loading control, and the relative protein level was calculated through densitometry (40). Bar graphs show relative normalized band intensity from the representative blot.\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/d8f1bd3644c3e6f5eac61f0d.jpg"},{"id":105993162,"identity":"6af437c5-432d-4a3b-8241-cc2780d78dd3","added_by":"auto","created_at":"2026-04-02 08:44:01","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":322925,"visible":true,"origin":"","legend":"\u003cp\u003eERBB2 deficiency results in increased phosphorylated EGFR and activation of MEK in tumor and normal adjacent tissue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Representative western blot showing expression of p-EGFR, EGFR, p-MEK, p-ERK, and GAPDH in \u003cem\u003eErbb2-\u003c/em\u003edeficient and \u003cem\u003eErbb2\u003c/em\u003e-amplified tumor and normal adjacent tissue. \u003cstrong\u003eB\u003c/strong\u003e Protein levels were normalized to the loading control, and the relative protein level was calculated through densitometry. Bar graphs show relative normalized band intensity from the representative blot.\u003c/p\u003e","description":"","filename":"Fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/72b1dd2f8b7c482780c2519f.jpg"},{"id":106096343,"identity":"74aaef9a-0159-4975-a25f-2280b679550f","added_by":"auto","created_at":"2026-04-03 11:54:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4291157,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/6bd4a407-79d2-4392-86a1-ace82b549533.pdf"},{"id":105993164,"identity":"73deb8b9-5c79-4d75-badf-ab83608665fb","added_by":"auto","created_at":"2026-04-02 08:44:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":938046,"visible":true,"origin":"","legend":"Supplementary Files","description":"","filename":"SupplementaryFiles.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8802187/v1/df106820ff2fc552b7159977.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"ERBB2 deficiency enhances colorectal cancer progression through EGFR-dependent compensatory mechanisms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths in the United States and globally. Continual advancements in therapies have made substantial progress in mortality rates for older populations, but trends are on the rise for those in younger populations. These advancements have included routine colonoscopy, surgical resection, chemotherapy, immunotherapy, and combinatorial therapies, which have overall improved patient outcomes and undoubtedly reduced CRC morbidity. Continued investigations into molecular and genetic targets of various cancer types has identified additional therapeutic targets or biomarkers for positive response to existing therapies. One such target, \u003cem\u003eERBB2\u003c/em\u003e, is mutated or amplified in a subset of CRCs and may be a marker of resistance to anti-Epidermal Growth Factor Receptor (EGFR) therapeutics and help identify patients who may benefit from ERBB2-directed therapeutic management.\u003c/p\u003e \u003cp\u003eOncogenic alterations of \u003cem\u003eERBB2\u003c/em\u003e are found in multiple cancer types, including CRC. \u003cem\u003eERBB2\u003c/em\u003e genomic amplification or mutations occur in roughly 7% of CRCs and 4% of metastatic CRCs, in which trastuzumab (anti-ERBB2) therapies have shown some efficacy (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Under homeostatic conditions, stimulation of ERBB2 can result in the promotion of cell proliferation, differentiation, and suppression of apoptosis, which is tightly regulated (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In the case of amplification leading to hyperactivation of ERBB2, these routine developmental processes continue unrestrained and can result in hyperproliferation, survival, and ultimately tumorigenesis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Unlike the other ERBB receptor family members, ERBB2 does not bind any known ligands; instead, its activation is mediated by heterodimerization with other ligand-bound ERBB receptor members, primarily EGFR (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and can be activated by culture conditions through auto-phosphorylation (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). As such, recently identified somatic activating mutations in \u003cem\u003eERBB2\u003c/em\u003e, which are often paired with amplification of \u003cem\u003eERBB2\u003c/em\u003e, can cause constitutive activation of proliferative and survival signals that are more tumorigenic than amplification alone (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, \u003cem\u003eERBB2\u003c/em\u003e mutations and amplification in CRC are heterogeneous in nature and result in varying expression patterns across samples (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The elucidation of the genetic context of \u003cem\u003eERBB2\u003c/em\u003e alterations is important to understand how these CRC progression programs are modulated. Alterations in \u003cem\u003eERBB2\u003c/em\u003e have been reported in both Microsatellite Stable (MSS) and hypermutated Microsatellite Instable (MSI) CRC patient populations, often with an accompanying \u003cem\u003eKRAS\u003c/em\u003e mutation (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Consequently, further characterization is required to determine the etiological and functional implications of \u003cem\u003eERBB2\u003c/em\u003e mutations in different contexts and subtypes of CRC.\u003c/p\u003e \u003cp\u003eThe status of \u003cem\u003eERBB2\u003c/em\u003e alterations as a biomarker for poor prognosis in breast (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and gastroesophageal (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) cancer is well established. Patients with these cancers exhibiting \u003cem\u003eERBB2\u003c/em\u003e alterations are routinely treated with the ERBB2-directed antibody trastuzumab in combination with chemotherapy (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Other research suggests a promising patient response to sequential treatment with ERBB2-targeted tyrosine kinase inhibitors (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In the context of CRC, the introduction of \u003cem\u003eERBB2\u003c/em\u003e mutations or amplification in immortalized murine colon epithelial cell lines has confirmed the transforming capacity of ERBB2 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and demonstrates its ability to confer resistance to EGFR-targeted therapeutics, including cetuximab (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Until recently, no drugs were approved by the FDA to target ERBB2 for CRC. Combination therapy of tucatinib and trastuzumab in \u003cem\u003eRAS\u003c/em\u003e wild-type and ERBB2 overexpressing mCRC patients has improved outcomes and warranted accelerated approval (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Combinatorial therapy with trastuzumab and pertuzumab further highlights the importance of \u003cem\u003eERBB2\u003c/em\u003e genomic status and complexity when investigating potential compensatory mechanisms in CRC progression (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). As such, the status of ERBB2 as a therapeutic target and biomarker in broader patient populations is still emerging.\u003c/p\u003e \u003cp\u003eAberrant expression and activation of EGFR is common in many solid tumors of epithelial origin, particularly CRC (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, our group has recently demonstrated that CRC is not only capable of initiating independently of EGFR but also adopts a more aggressive progression program than EGFR-dependent cancers due to IL10-mediated anergy and JAK/STAT signaling activation, creating a pro-tumoral tumor micro-environment (TME) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). There is an association between ERBB2 upregulation and EGFR-targeted therapeutic resistance (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, the potential role of ERBB2 in the progression of this subset of EGFR-independent CRC has yet to be investigated.\u003c/p\u003e \u003cp\u003eIn this study, we report that ERBB2-independent cancers exhibit similarities to EGFR-independent cancers in their disposition to initiate and propensity to progress more aggressively. Using the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mouse model of CRC, we found that intestinal-specific genetic ablation of \u003cem\u003eErbb2\u003c/em\u003e protects against CRC initiation but enhances progression. We provide transcriptomic evidence indicating the activation of EGFR in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors, providing a potential mechanism for the increased size of these tumors. Notably, GSEA using human oncogenic molecular signatures supported these predictions about EGFR activation and reinforced this mouse model's clinical relevance. Further, we present evidence that \u003cem\u003eErbb2\u003c/em\u003e-deficient tumor transcriptomic profiles are enriched with genes upregulated in EGFR-independent cancers progressing with wild-type \u003cem\u003eKras\u003c/em\u003e, supporting the importance of \u003cem\u003eKRAS\u003c/em\u003e status in modulating the immune environment and as a biomarker for guiding therapy. Further validation confirmed compensatory activation of EGFR through the MAPK pathway, indicated by high levels of phosphorylated MEK1/2 in \u003cem\u003eErbb2-\u003c/em\u003edeficient tumors relative to control. Cooperatively, these results support a role for ERBB2 in initiating CRC and suggest further characterization is needed to identify potential combinatory therapies and patient populations that may benefit from ERBB2-directed CRC management.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimal experiments\u003c/h2\u003e \u003cp\u003eMice were obtained from The Jackson Laboratory (C57BL/6J-\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e [\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e]) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and NCI-Frederick (B6;D2-\u003cem\u003eTg(Vil-cre)20Syr\u003c/em\u003e [\u003cem\u003eTg(Vil1-Cre)\u003c/em\u003e] (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), which were maintained on a hemizygous B6 background. B6.129X1(Cg)-\u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003etm1Mll\u003c/em\u003e\u003c/sup\u003e (\u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sup\u003e) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) was obtained from the European Mutant Mouse Archive through the International Mouse Strain Resource. Strains were backcrossed for 10 generations on a C57BL/6J background and confirmed congenic by genome analysis. Mice were housed five per cage, fed Purina Mills Lab Diet 2919 \u003cem\u003ead libidum\u003c/em\u003e, and maintained at 22\u0026deg;C under a 12-hr light cycle. Mice were euthanized by CO\u003csub\u003e2\u003c/sub\u003e asphyxiation for tissue and serum collection. Tumor and normal adjacent tissue samples were resected from 100-day old \u003cem\u003eErbb2\u003c/em\u003e-deficient \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg(Vil-Cre)\u003c/em\u003e) and control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e) for analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenotyping\u003c/h3\u003e\n\u003cp\u003eMice were genotyped for the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin\u003c/em\u003e\u003c/sup\u003e allele as previously described (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Mice were genotyped for other pertinent alleles using PCR with primers designed to amplify the target gene or transgene (Supplementary Table\u0026nbsp;1)\u003c/p\u003e\n\u003ch3\u003eMacroadenoma quantification\u003c/h3\u003e\n\u003cp\u003eFollowing euthanasia, the GI tract was excised and opened longitudinally. The tumor number, diameter, and location were recorded for the entire length of the small intestine and colon using a dissecting microscope and in-scope micrometer at 5x magnification. Tumor scoring was performed without knowledge of genotype by the investigator. Five colon tumors from each group were confirmed by H\u0026amp;E staining.\u003c/p\u003e\n\u003ch3\u003eHistology\u003c/h3\u003e\n\u003cp\u003eIntestinal and colon tissues were collected and fixed in 10% neutral buffered formalin overnight. Fixed tissues were embedded in paraffin and cut into 5\u0026micro;m sections. Every tenth section was stained with H\u0026amp;E for histologic review. Sections were deparaffinized in xylene, followed by hydration in ethanol. Slides were then incubated in fresh hematoxylin (VWR 95057-844) and washed in distilled water before differentiation in acid alcohol. After incubation in bluing solution (American Mastertech HXB00242E) and rinsing with distilled water, slides were counterstained with 0.25% eosin Y (Sigma E4382), rinsed, dehydrated, and mounted. Crypt length was measured using the Leica Application Suite X v1.4.5, and crypts in three random frames from five H\u0026amp;E-stained sections from each group were measured by an investigator blinded to genotype.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry\u003c/h3\u003e\n\u003cp\u003eSections were deparaffinized and rehydrated before antigen retrieval by boiling in sodium citrate buffer, pH 6.0, for 20 minutes. Sections were then quenched by treatment with 0.3% hydrogen peroxide in TBS for 15 minutes. After rinsing with TBS, sections were blocked in TBS with 3% goat serum for two hours before incubating with the anti-Ki67 primary antibody (Abcam ab15580, 1:1,000) overnight at 4\u0026deg;C. Sections were rinsed again with TBS before incubation with the HRP-conjugated goat anti-rabbit secondary antibody (Abcam ab205718, 1:20,000) in TBS for one hour. Antigen-antibody complexes were detected using the DAB substrate kit (Abcam ab64238) following the manufacturer\u0026rsquo;s instructions. Sections were counterstained with hematoxylin before dehydration, clearing, and mounting. Cells were scored as positive in three random frames from five mice per group using Fiji software (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) by an investigator blinded to genotype. Additional sections were stained with SignalStain Apoptosis (Cleaved Caspase-3) IHC Detection Kit (Cat. No:12692; Cell signaling Technology, USA) and performed to manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA sequencing and differential gene expression analysis\u003c/h2\u003e \u003cp\u003eA total of three sequencing runs were performed to sequence 20 samples (five tumor and five adjacent normal samples from both \u003cem\u003eErbb2\u003c/em\u003e-deficient and littermate control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice) on an Illumina NovaSeq 6000 instrument at the North Texas Genome Center. Libraries were prepared in the Texas A\u0026amp;M Institute for Genome Sciences and Society Molecular Genomics Core using the S4 reagent kit v1.5. A total of ~\u0026thinsp;920\u0026nbsp;million 150bp paired-end reads were trimmed of adapter sequences and low-quality bases using Trimmomatic (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), resulting in roughly 914\u0026nbsp;million filtered reads (99%). Filtered reads were aligned to mouse assembly mm39 using HISAT2 version 2.2.1 (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) with an overall mapping rate of ~\u0026thinsp;96%. Raw transcript counts were generated using HTSeq version 2.0.2 (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Read counts were normalized, and gene expression analyses were performed using DESeq2 (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). IPA (Qiagen) was used to analyze differentially expressed genes between groups. Raw and processed RNAseq data have been deposited in NCBI\u0026rsquo;s Gene Expression Omnibus (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) and are accessible through GEO Series accession number GSE241084.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGene set enrichment analysis\u003c/h3\u003e\n\u003cp\u003eGSEA was performed using the GSEA software version 4.3.2 (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Feature expression levels in tumor samples were normalized, accounting for sequencing depth and RNA composition, to expression levels in corresponding adjacent normal tissue and across samples using the median of ratios method in DESeq2 (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). EGFR and MEK upregulation human molecular signatures (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) were retrieved from the Molecular Signatures Database Human Collection (MsigDB v2023.1.Hs). The EGFR-independent with wild-type \u003cem\u003eKras\u003c/em\u003e upregulation (n\u0026thinsp;=\u0026thinsp;240 genes) and EGFR-independent with mutant \u003cem\u003eKras\u003c/em\u003e upregulation (n\u0026thinsp;=\u0026thinsp;254) mouse molecular signatures were generated by selecting genes specific to \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eEgfr\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e or \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eEgfr\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eG12D/+\u003c/em\u003e\u003c/sup\u003e tumors with log\u003csub\u003e2\u003c/sub\u003e fold change\u0026thinsp;\u0026gt;\u0026thinsp;2 and adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The analysis parameters were set to rank genes by the signal-to-noise ratio in 1,000 gene set permutations to assess the statistical significance of the normalized enrichment score (NES). Gene sets with nominal p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.25 were considered significantly enriched and evaluated further.\u003c/p\u003e\n\u003ch3\u003eReverse transcription-quantitative polymerase chain reaction\u003c/h3\u003e\n\u003cp\u003eTotal RNA from tumors and adjacent normal tissue was isolated using Maxwell LEV simplyRNA Tissue Kit (Promega AS1280) according to the manufacturer\u0026rsquo;s instructions. Total RNA was converted to cDNA using the Transcriptor First Strand cDNA Kit (Roche 04896866001). RT-qPCR reactions were performed in triplicate using cDNA with LightCycler\u0026reg; 480 SYBR Green I Master Mix (Roche 04887352001) on a LightCycler\u0026reg; 96 System (Roche). Primer pairs were designed to amplify a fragment specific to the target gene (Supplementary Table\u0026nbsp;1). Fold expression differences were calculated using the 2\u003csup\u003e\u0026minus;\u0026thinsp;ΔΔC\u003c/sup\u003e\u003csub\u003eT\u003c/sub\u003e method relative to \u003cem\u003eGapdh\u003c/em\u003e or \u003cem\u003eActb\u003c/em\u003e expression (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEnzyme-linked immunosorbent assay\u003c/h2\u003e \u003cp\u003eNeuregulin I (NRG1) concentrations in mouse serum were measured using the Mouse NRG1 ELISA Kit (Novus Biologicals NBP2-68070). Concentrations were interpolated from absorbance using a four-parameter logistic curve fit. Samples were run in triplicate in three independent tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting analysis\u003c/h2\u003e \u003cp\u003eTissues collected at necropsy were frozen in liquid nitrogen and stored at -80\u0026deg;C. Tissues were homogenized in 1X RIPA Buffer (Cell Signaling Technologies #9806) which was diluted from 10x to 1x using ddH2O. Halt Protease Inhibitor Cocktail (1x) (ThermoScientific 78430) and PMSF Protease Inhibitor (1 mM) (ThermoScientific 36978) were added to 1x RIPA Buffer prior to homogenization. The concentration of cleared lysate was measured using Pierce BCA Protein Assay Kit (ThermoScientific 2327), and 20 ug of tumor and normal adjacent lysate were added to 4\u0026ndash;15% Mini-PROTEAN TGX Precast Gels (Bio-Rad) depending on the protein of interest, electrophoresed, and transferred to a nitrocellulose membrane (Bio-Rad #1620115). The membrane was then incubated for 1 hour in 5% non-fat dry milk (SantaCruz Biotechnology sc-2324) in 1x TBS-T. The membrane was subsequently incubated with primary antibody overnight at 4\u0026deg;C. After incubation with primary antibody, blot was washed with 1x TBS-T 3 times and incubated with 5% nonfat dry milk blocking solution containing goat anti-rabbit polyclonal HRP-conjugated secondary antibody for 1 hour at room temperature (Abcam ab6721). The membrane was washed 4 times with 1x TBS-T and visualized using SuperSignal West Fempto Maximum Sensitivity Substrate following 5-minute incubation (ThermoScientific 34095). The antibodies used were GAPDH, EGFR, Phospho-EGFR, Phospho-MEK1, Phospho-ERK1/2 (Cell Signaling Technologies), and MEK1, ERK1 (Abcam). Relative protein was calculated using ImageJ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll biological replicate sample numbers (n) can be found in the figure legends. The number of technical replicates can be found in the details of the methods. The number of animals needed per group was estimated using JMP (SAS Institute) based on an α-value of 0.05 and a desired power of 0.8. An equal number of male and female animals were evaluated in experiments. The representative whole mount, H\u0026amp;E, and IHC staining images represent one of at least three biological replicates. The nonparametric Mann\u0026ndash;Whitney U test was used to analyze tumor data. To compare the difference between the means of two groups, the Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test was used. ANOVA with post hoc Tukey\u0026rsquo;s HSD was used to compare the difference between the means among three or more groups. P-values less than 0.05 were considered statistically significant. Statistical details and p-values can be found in the figure legends. No samples or animals were excluded from the analysis, and all experiments reported in this study were repeated at least three independent times. All data are represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Studies were conducted blind as indicated in the methods. Statistical analysis and figure generation were performed by GraphPad Prism version 9.5.1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement\u003c/h2\u003e \u003cp\u003eAnimal experiments were approved by the Institutional Animal Care and Use Committee at Texas A\u0026amp;M University conforming to the Guide for the Care and Use of Laboratory Animals.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eLoss of\u003c/strong\u003e \u003cstrong\u003eErbb2\u003c/strong\u003e \u003cstrong\u003ehinders polyp initiation but supports enhanced growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOwing to the growing interest in \u003cem\u003eERBB2\u003c/em\u003e amplification as a potential targetable mechanism of resistance to EGFR-targeted therapy in patients with CRC (15, 16), paired with the increased expression of \u003cem\u003eErbb2\u003c/em\u003e during EGFR-independent progression of CRC in preclinical mouse models (19), we investigated the effect of genetic ablation of \u003cem\u003eErbb2\u003c/em\u003e on CRC progression using the conditional \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sup\u003e allele. Ablation of \u003cem\u003eErbb2\u003c/em\u003e was induced by a transgene expressing Cre recombinase under the control of the epithelial-specific \u003cem\u003eVillin\u003c/em\u003e promoter \u003cem\u003eTg(Vil1-cre).\u003c/em\u003e In the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e model of CRC, we observed a significant reduction in the number of intestinal and colon polyps in \u003cem\u003eErbb2\u003c/em\u003e-deficient (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg\u003c/em\u003e(\u003cem\u003eVil1-cre\u003c/em\u003e)) animals after 100 days when compared to littermate controls (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e) (Fig.\u0026nbsp;1A and 1B). \u003cem\u003eErbb2\u003c/em\u003e-deficient and littermate control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e animals developed an average of 45 and 94.2 intestinal polyps per mouse, respectively. This significant reduction in intestinal polyp number was noted in each anatomical portion of the small intestine. Interestingly, polyps that were able to initiate in the context of absence of ERBB2 were significantly larger, primarily in the small intestine (Fig.\u0026nbsp;1C), as evident by a higher portion of tumors proliferating to a size greater than two millimeters (Fig.\u0026nbsp;1D). These observations regarding tumor multiplicity and size are similar to those observed in EGFR-independent CRC in the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e model (19). Moreover, analysis of hematoxylin and eosin-stained normal epithelium in \u003cem\u003eErbb2\u003c/em\u003e-deficient and littermate control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e animals revealed no apparent differences in epithelial morphology, including no significant differences in crypt height. Together, these results support a double-edged role for \u003cem\u003eErbb2\u003c/em\u003e expression in CRC, suggesting its presence may bolster the initiation of CRC while its absence may promote faster growth, leading to increased tumor size.\u003c/p\u003e\n\u003cp\u003eTo investigate the cellular mechanism responsible for the increased tumor size observed in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors, we compared levels of proliferation in the adjacent normal and tumor tissue of each group (Fig.\u0026nbsp;2A). Immunohistochemical staining for the proliferation marker Ki67 revealed a significant increase in proliferation in tumors progressing without ERBB2 (Fig.\u0026nbsp;2B). Immunohistochemical staining was also performed for apoptotic marker cleaved caspase-3 (Fig.\u0026nbsp;2C), which showed a significant decrease in cell death in the \u003cem\u003eErbb2\u003c/em\u003e-deficient tumor and normal adjacent tissues relative to control (Fig.\u0026nbsp;2D). Proliferation in adjacent normal tissue was primarily restricted to the proliferative zones of the crypt regardless of the \u003cem\u003eErbb2\u003c/em\u003e status. Surprisingly, no significant differences were noted between the \u003cem\u003eErbb2\u003c/em\u003e-deficient adjacent normal tissue and adjacent normal or tumor tissue from littermate control animals. This suggests that the increased proliferation and decreased apoptosis in the absence of ERBB2 is tumor-specific and that compensatory mechanisms likely allow transformed cells to progress more aggressively through increased proliferation in the absence of ERBB2. Overall, these results suggest that alternative means for progression may be activated in compensation for the loss of ERBB2 and must be further defined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eErbb2\u003c/strong\u003e \u003cstrong\u003e-deficient tumors display a unique gene expression signature\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify potential molecular mechanisms underlying the enhanced proliferation and decrease in apoptosis in the absence of \u003cem\u003eErbb2\u003c/em\u003e, we sequenced total RNA from five tumor and adjacent normal tissue samples from both \u003cem\u003eErbb2\u003c/em\u003e-deficient and littermate control \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice (Fig.\u0026nbsp;3A). Transcriptomic analysis revealed 1,157 significantly differentially expressed genes characterizing the \u003cem\u003eErbb2\u003c/em\u003e-deficient progression program in the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e context (Fig.\u0026nbsp;3B). Surprisingly, in analyzing the top 50 differentially expressed features we found that \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors displayed a consistent reduction in transcripts reported to be associated with CRC proliferation, survival, and invasion including YEATS domain containing 4 (\u003cem\u003eYeats4\u003c/em\u003e) (20), EGF-like domain 7 (\u003cem\u003eEgfl7\u003c/em\u003e) (21), and vascular endothelial growth factor B (\u003cem\u003eVegfb\u003c/em\u003e) (22) (Fig.\u0026nbsp;3C). Further, increased expression of nitric oxide synthase 2, inducible (\u003cem\u003eNos2\u003c/em\u003e, also called iNOS) was noted in \u003cem\u003eErbb2-\u003c/em\u003edeficeint tumors, which is characteristic of M1 macrophages and has been associated with favorable prognosis in CRC in patients harboring tumors highly infiltrated by iNOS+ cells (23).\u003c/p\u003e\n\u003cp\u003eNotably, the EGFR-independent subtype of CRC displays a significant increase in iNOS+ M1 macrophages when compared to EGFR-dependent CRC in mice, and the addition of oncogenic a \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eG12D\u003c/em\u003e\u003c/sup\u003e mutation skews the macrophage population towards a CD163\u0026thinsp;+\u0026thinsp;M2 phenotype (19). Supporting the increased tumor-specific proliferation, \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors exhibited increased expression of cadherin 17 (\u003cem\u003eCdh17\u003c/em\u003e), which has been associated with activation of WNT/b-catenin (24) and MAPK signaling (25), has been reported as an adenocarcinoma biomarker (26) and oncogene (27), and is currently being evaluated as a therapeutic target in Phase 1 clinical trials (NCT05411133) and has been investigated CAR T cell therapy (28) in Phase 1/2 clinical trials (NCT06055439). Collectively, these results suggest that, while unique, the transcriptomic program employed by \u003cem\u003eErbb2\u003c/em\u003e-deficient colon tumors resembles the EGFR-independent subtype of CRC through potential modulation of the immune landscape and activation of alternative progression mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTranscriptomic analysis of\u003c/strong\u003e \u003cstrong\u003eErbb2\u003c/strong\u003e\u003cstrong\u003e-deficient colon tumors predicts activation of EGFR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further refine potential candidate pathways and mechanisms materializing in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors, we utilized IPA. This analysis of downstream effects predicted activation of several canonical pathways, including the pathogen-induced cytokine storm signaling pathway (Supplementary Table\u0026nbsp;2). Subsequent analysis of upstream regulators indicated activation in multiple molecules known to drive progression and are associated with poor prognosis, including EGFR (29), AGT (30), TGFB1 (31), NPM1 (32), and IL6 (33) in addition to inhibition of PTEN, which acts to downregulate PI3K/AKT pro-survival signaling (34) (Table\u0026nbsp;1). Regulatory network analysis of EGFR revealed further support for the activation of WNT/b-catenin signaling through upregulation of \u003cem\u003eCtnnb1\u003c/em\u003e by crosstalk with active MAPK signaling (Supplementary Fig.\u0026nbsp;1). To partially validate these findings regarding WNT/b-catenin and MAPK signaling, we measured the expression of \u003cem\u003eCtnnb1\u003c/em\u003e, \u003cem\u003eMapk4\u003c/em\u003e, and \u003cem\u003eCol1a1\u003c/em\u003e by RT-qPCR and found a significant increase in expression in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors when compared to adjacent normal tissue and littermate controls (Fig.\u0026nbsp;4A). This outcome supports the \u003cem\u003ein-silico\u003c/em\u003e predictions of EGFR activation and potential crosstalk between WNT/\u0026beta;-catenin and MAPK signaling.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eTop upstream regulators of \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUpstream regulator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMolecule type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ePredicted activation state\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eActivation z-score\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ep-value of overlap\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eKinase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.22E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGrowth factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.25E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTGFB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGrowth factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e5.75E-12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNPM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTranscription regulator\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.28E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIL6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCytokine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.93E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNR3C1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLigand-dependent nuclear receptor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInhibited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-3.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.29E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePTEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePhosphatase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInhibited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-3.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e5.18E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHNF4A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTranscription regulator\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInhibited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-2.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.09E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eImmunoglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eComplex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInhibited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e6.75E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFKBP10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eEnzyme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eInhibited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-2.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.21E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\n \u003cp\u003eEGFR, epidermal growth factor receptor; AGT, angiotensinogen; TGFB1, transforming growth factor beta 1; NPM1, nucleophosmin 1; IL6, interleukin 6; NR3C1, nuclear receptor subfamily 3 group C member 1; PTEN, phosphatase and tensin homolog; HNF4A, hepatocyte nuclear factor 4 alpha; FKBP10, FKBP prolyl isomerase 10.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThese predictions suggest that tumors that initiate independently of \u003cem\u003eErbb2\u003c/em\u003e could display an increase in size due to activation of EGFR driven proliferation and survival pathways.\u003c/p\u003e\n\u003cp\u003eThus, GSEA was conducted to identify enriched pathways conserved in our \u003cem\u003eErbb2\u003c/em\u003e-deficient model (Fig.\u0026nbsp;5A). Using this method, \u003cem\u003eErbb2\u003c/em\u003e-deficient differentially expressed genes were found to be associated with multiple human gene sets, including those related to the hallmarks of epithelial to mesenchymal plasticity and TGFB signaling (35), EGFR, MEK (36), and KRAS upregulation (37), and downregulation of PTEN (38) (Supplementary Table\u0026nbsp;2). In concordance with the initial analysis, subsequent GSEA revealed significant enrichment of EGFR (NES = -1.33) and MEK upregulation (NES = -1.49) in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors (Fig.\u0026nbsp;5A, 5B). Further, we observed significant enrichment of the \u003cem\u003eErbb2\u003c/em\u003e-deficient signature with gene sets representing the hallmarks of epithelial to mesenchymal plasticity (NES = -2.17) and TGFB signaling activation (NES = -1.57) (Supplementary Fig.\u0026nbsp;2). These results confirm predictions from IPA through validation of upstream regulators in EGFR and TGFB1 and their role in \u003cem\u003eErbb2\u003c/em\u003e-deficient tumor progression.\u003c/p\u003e\n\u003cp\u003eGiven the computational support for EGFR activation in this \u003cem\u003eErbb2\u003c/em\u003e-deficient subset of tumors and knowing the phenotypic similarity between \u003cem\u003eErbb2\u003c/em\u003e-deficient and EGFR-independent cancers in terms of tumor multiplicity and size (39), we evaluated the degree of similarity between their progression programs at the transcriptomic level. Interestingly, these analyses revealed significant enrichment in the EGFR-independent CRC gene set dependent on \u003cem\u003eKras\u003c/em\u003e status. We observed significant enrichment in genes expressed by EGFR-independent tumors with wild-type \u003cem\u003eKras\u003c/em\u003e (NES = -1.4) (Fig.\u0026nbsp;6). Conceivably, this is due to the presence of wild-type \u003cem\u003eKras\u003c/em\u003e in our \u003cem\u003eErbb2\u003c/em\u003e-deficient model as the enrichment of genes expressed by EGFR-independent tumors progressing with the oncogenic \u003cem\u003eKras\u003c/em\u003e\u003csup\u003e\u003cem\u003eG12D\u003c/em\u003e\u003c/sup\u003e mutation failed to reach statistical significance (NES = -1.19) (Supplementary Fig.\u0026nbsp;3). Knowing the general importance of the immune landscape in CRC progression and response to therapy, including EGFR-independent cancers, the delineation between their progression programs could potentially aid in predicting molecular outcomes of ERBB2 inhibition, especially in the case of resistance to EGFR-targeted therapeutics.\u003c/p\u003e\n\u003cp\u003eTo further investigate the intricacies of the pathway by which \u003cem\u003eErbb2\u003c/em\u003e-independent tumors progress, we further investigated the upregulation of EGFR and MEK that was previously identified in GSEA analysis. Western blotting analysis demonstrated decreased expression of MEK1 and ERK1 in \u003cem\u003eErbb2-\u003c/em\u003edeficient normal adjacent and tumor tissues and \u003cem\u003eErbb2-\u003c/em\u003econtaining tumor tissue (Fig.\u0026nbsp;7A, 7B).\u003c/p\u003e\n\u003cp\u003eWhen we evaluated EGFR and phosphorylated-EGFR protein expression levels, \u003cem\u003eErbb2\u003c/em\u003e-deficient tumor and normal adjacent tissue were elevated relative to \u003cem\u003eErbb2-\u003c/em\u003econtaining tumor and normal adjacent tissue (Fig.\u0026nbsp;8A). While p-EGFR levels were increased in these samples, we observed lower EGFR relative protein levels, which could be associated with the EGFR-independent tumor transcriptomic profile. To further evaluate the phosphorylated forms of MEK and ERK and how this could contribute to \u003cem\u003ein silico\u003c/em\u003e predictions of MEK upregulation, we confirmed an increase in relative protein level in normal adjacent and tumor tissue for \u003cem\u003eErbb2-\u003c/em\u003edeficient mice. This notable elevation of active MEK and ERK indicates enhanced MAPK signaling, suggesting this as a compensatory pathway and confirming transcriptomic predictions. These results suggest that while the progression programs of ERBB2 and EGFR-independent CRC are unique, there are similarities in compensatory pathways involved, and further evaluation of the robustness of the comparative features of these programs could provide valuable insight into combinatorial therapeutic strategies.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe present evidence suggesting that loss of ERBB2 limits initiation of CRC but supports progression. While the precise molecular mechanism responsible for this tumor-specific increase in proliferation remains to be experimentally validated, we provide transcriptomic analyses suggesting that the increased size of tumors observed in the context of ERBB2 loss could be the result of compensatory activation of EGFR signaling, likely through MEK activation and the subsequent MAPK signaling cascade. We determined that the transcriptional programs adopted by \u003cem\u003eErbb2\u003c/em\u003e-deficient tumors are significantly enriched for genes upregulated during constitutive EGFR and downstream MEK activation in human contexts, supporting the \u003cem\u003ein silico\u003c/em\u003e transcriptional predictions and relevance of this model to human biological contexts. Further, these analyses revealed that the \u003cem\u003eErbb2\u003c/em\u003e-deficient expression program is significantly enriched with genes associated with EGFR-independent CRC progression, depending on the \u003cem\u003eKras\u003c/em\u003e status, further validated through western blotting analysis, and emphasizes the importance of \u003cem\u003eKras\u003c/em\u003e mutations in determining the characteristics of CRC. Finally, we demonstrated that the increased progression observed in the absence of ERBB2 is partially due to a tumor-specific increase in proliferation. While many questions remain to be answered, the results generated thus far in this study suggest an important role for ERBB2 in the initiation of CRC and illuminate compensatory mechanisms to be explored further, such as investigation into AKT signaling to fully understand the role of proliferation following an ERBB2-independent program (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is significant interest in ERBB2 as a target for therapeutic management in CRC, and it has recently been approved for individuals with mCRC that are RAS wild-type and exhibiting ERBB2 amplification (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Several clinical trials have explored the prospect of ERBB2 as a therapeutic target for mCRC using a variety of novel drugs (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). However, ERBB2 is more commonly overexpressed in CRC before progression to metastatic disease (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This observation is insightful and could be actionable given that ERBB2 can stimulate proliferative and survival signals long before the transition into metastatic disease (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). As such, there is also significant interest in exploring ERBB2 as a target for broader therapeutic contexts and earlier stages of CRC, highlighting the need for further preclinical investigation.\u003c/p\u003e \u003cp\u003eBy leveraging mice with intestinal epithelial cell-specific deletion of \u003cem\u003eErbb2\u003c/em\u003e, we observed a reduction in tumor initiation paired with an increase in tumor-specific proliferation, supporting an important role for ERBB2 in intestinal homeostasis. Of course, fundamental differences exist between the intestinal epithelial cell-specific genetic ablation reported here and pharmacological blockade through classical targeted therapeutic approaches. As a result, if the increased proliferation observed and the activation of compensatory mechanisms depend on the complete loss of ERBB2, then pharmacological blockade of ERBB2 could yield different informative outcomes. However, analysis of trastuzumab- and pertuzumab-resistant breast cancer cell lines demonstrates significant upregulation of both EGFR and ERBB3, corresponding with increased phosphorylation of ERK1/2 and leading to increased proliferation and invasiveness (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). While much remains to be investigated in the context of CRC, this suggests the potential for similarities between the compensatory progression mechanisms activated in response to genetic ablation of \u003cem\u003eErbb2\u003c/em\u003e and ERBB2 pharmacological blockade. Notably, discovering any differences in response to genetic ablation or pharmacological blockade will be incredibly informative for uncovering potential contexts that would likely respond favorably to ERBB2 inhibition. Further characterization of these mechanisms will undoubtedly illuminate the potential therapeutic merit of ERBB2 during CRC. This study provides important preliminary evidence suggesting an important role for ERBB2 in initiating and determining the transcriptional progression program utilized in the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e model of CRC. They offer similarities between ERBB2 and EGFR-independent cancers, which could lie in compensatory signaling through ERBB3 and ERBB4 and other related pathways. Collectively, this suggests that ERBB2 contributes to early transcriptional programming in CRC through compensatory MAPK signaling networks, which modulate responsiveness to ERBB2-targeted therapies and highlight the combinatorial therapeutic approach that can overcome resistance mechanisms and enhance current approaches.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNeed statement\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAssign my initials\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests. All support for this work, including grants, equipment, and reagents, has been fully disclosed in the acknowledgements and method sections.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests. All support for this work, including grants, equipment, and reagents, has been fully disclosed in the acknowledgements and method sections.\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCancer Genome Atlas N. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubin I, Yarden Y. The basic biology of HER2. Ann Oncol. 2001;12 Suppl 1:S3-8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMenard S, Pupa SM, Campiglio M, Tagliabue E. Biologic and therapeutic role of HER2 in cancer. 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J Exp Clin Cancer Res. 2020;39(1):279.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8802187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8802187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eERBB2\u003c/em\u003e is mutated or amplified in a subset of colorectal cancers (CRCs) and may be a marker of resistance to anti-epidermal growth factor receptor (EGFR) therapeutics and help to identify patients who may benefit from ERBB2-directed therapeutic management. To further investigate the role of ERBB2, we generated a population of \u003cem\u003eErbb2\u003c/em\u003e-deficient \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e mice (\u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eErbb2\u003c/em\u003e\u003csup\u003e\u003cem\u003ef/f\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eTg(Vil-Cre)\u003c/em\u003e). We found that \u003cem\u003eErbb2-\u003c/em\u003edeficieny modulates CRC initiation but enhances progression in the \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003eMin/+\u003c/em\u003e\u003c/sup\u003e model. Transcriptomic analysis predicted EGFR activation, which likely mediates the progression that leads to the larger tumors observed in the absence of functional ERBB2. Further \u003cem\u003ein silico\u003c/em\u003e predictions confirmed this prediction and indicated involvement of oncogenic \u003cem\u003eKras\u003c/em\u003e mutations, which are essential in determining the progression program by which this operates, similarly to EGFR-independent CRC. Further analysis confirmed activation of EGFR and subsequent activation of MAPK pathway through MEK/ERK. These preclinical analyses suggest an important role for ERBB2 in CRC and highlight the need for further characterization to identify and predict the merit of potential combinatory therapies and patient populations that may benefit from ERBB2-directed therapy in tandem with EGFR therapy.\u003c/p\u003e","manuscriptTitle":"ERBB2 deficiency enhances colorectal cancer progression through EGFR-dependent compensatory mechanisms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-02 08:43:39","doi":"10.21203/rs.3.rs-8802187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-05T20:57:57+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-16T14:22:55+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-16T10:01:56+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-02-16T03:32:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-06T13:27:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-06T03:34:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Oncogene","date":"2026-02-06T03:34:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9e2f5ae8-e135-47f1-abfc-a98540048e94","owner":[],"postedDate":"April 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62457198,"name":"Biological sciences/Cancer/Cancer models"},{"id":62457199,"name":"Biological sciences/Cancer/Cancer genetics"}],"tags":[],"updatedAt":"2026-04-02T08:43:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-02 08:43:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8802187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8802187","identity":"rs-8802187","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}