Integrated Multi-omics Reveals Key Molecular Drivers and Therapeutic Strategies in a Spontaneous Cutaneous Squamous Cell Carcinoma Model of Macaques

Integrated Multi-omics Reveals Key Molecular Drivers and Therapeutic Strategies in a Spontaneous Cutaneous Squamous Cell Carcinoma Model of Macaques | 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 Integrated Multi-omics Reveals Key Molecular Drivers and Therapeutic Strategies in a Spontaneous Cutaneous Squamous Cell Carcinoma Model of Macaques Yongzhang Pan, Lihong Li, Lingling Xiao, Xin Dong, Jian Pu, Qi Geng, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8987244/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Skin cancer, especially cutaneous squamous cell carcinoma (cSCC), remains a major global health problem. Here, we report a spontaneous macaque cSCC model (5/2752 incidence; 80% mortality) that reproduces key human cSCC features. Tumors show well-differentiated squamous morphology, expression of squamous lineage markers (p63, CK5/6), and elevated Ki-67 proliferation indices. We apply whole-genome sequencing, bulk and single-cell RNA sequencing, proteomics, and functional assays to define tumor biology. Genomes display a high mutational burden with C > T dipyrimidine changes, pervasive chromosomal instability, translocations, and focal copy-number alterations. Integrated analyses reveal NF-κB–mediated inflammatory programs, macrophage-rich immune remodeling, and a shift toward aerobic glycolysis. Cross-platform data nominate MYO10 as recurrently altered and overexpressed. MYO10 knockdown reduces γ-H2AX, micronuclei, and IL-6/TNFα expression, while MYO10 overexpression induces DNA damage and inflammation in primary epithelial cells. Drug screening identifies paclitaxel as the most potent compound (IC₅₀ = 0.011 µM). Paclitaxel triggers apoptosis, G2/M arrest, and reduced migration in vitro. In mouse xenografts, it shrinks tumors by 89.4%. In a treated macaque, it produces 86.6% mean tumor regression, lowers systemic IL-6 and TNFα, and is well tolerated. This spontaneous macaque model links genomic instability to inflammation via MYO10 and offers a translational platform for studying cSCC and testing therapies. Biological sciences/Cancer Biological sciences/Cell biology Biological sciences/Computational biology and bioinformatics Biological sciences/Molecular biology Health sciences/Oncology cutaneous squamous cell carcinoma (cSCC) macaque spontaneous tumor model MYO10 genomic instability inflammation/NF-κB signaling paclitaxel Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Cutaneous squamous cell carcinoma (cSCC) is among the most common malignancies of the skin and a leading cause of morbidity and mortality from non-melanoma skin cancer worldwide 1–5 . Although many cSCCs are effectively treated by local excision or radiation when detected early, a substantial subset progress to locally advanced or metastatic disease for which therapeutic options are limited and outcomes are poor 6 . The dominant etiologic driver for most cSCCs is ultraviolet (UV) radiation, which causes characteristic dipyrimidine DNA lesions and a high somatic mutation burden 7–9 . This UV-driven mutagenesis, together with cumulative environmental and host factors, fuels genetic and chromosomal alterations that promote malignant transformation of epidermal keratinocytes 10,11 . Increasingly, it is recognized that these genomic insults do not act in isolation; rather, they interact with chronic innate and adaptive inflammatory processes and with metabolic reprogramming to create a tumor-permissive microenvironment that supports progression and therapy resistance 12–16 . Genomic instability is a hallmark of advanced cSCC 17–19 . Human tumors frequently harbor high numbers of single-nucleotide variants (SNVs), small insertions and deletions (indels), copy-number alterations (CNVs), and complex structural rearrangements 20 . Defects in DNA-repair function amplify the mutational load. Furthermore, loss of key tumor suppressors such as TP53 and NOTCH1 and gains of oncogenes, including MYC and KRAS , recur in advanced disease 21,22 . At the same time, chronic inflammation — driven by nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation, cytokine secretion, and immune cell infiltration — shapes tumor evolution 23–25 . Inflammatory mediators can promote proliferation, survival, angiogenesis, and local immunosuppression, and they can exacerbate genomic instability by inducing reactive oxygen species and perturbing DNA-damage responses 26 . Therefore, these intersecting axes of genome damage and inflammation represent both fundamental mechanisms of cSCC pathogenesis and candidate targets for therapeutic intervention. Preclinical modeling is essential for dissecting these complex, interacting processes and for testing candidate treatments. Rodent models have provided valuable mechanistic insights, but important biological differences limit their translational fidelity for human cSCC 27–30 . Rodent skin architecture, hair density, immune composition, and DNA-repair kinetics differ from those of humans. Moreover, many genetically engineered and chemically induced murine models fail to recapitulate the full spectrum of genomic complexity, immune microenvironment remodeling, and treatment responses characteristic of aggressive human cSCC 2,31–33 . Non-human primates share greater genetic, anatomical, and immunologic similarity with humans and therefore offer an attractive but underused platform for modeling spontaneous human-like cancers 30,34 . Spontaneous tumors that arise in primate colonies capture natural etiologic exposures and host-tumor interactions that are difficult to reproduce artificially, potentially yielding a more faithful substrate for mechanistic studies and translational testing. Despite this promise, spontaneous non-human primate tumor models remain rarely characterized at scale with modern molecular tools. Comprehensive profiling of spontaneous primate cSCCs using integrated genomics, transcriptomics, proteomics, and single-cell resolution techniques could reveal conserved disease drivers that are obscured in simplified models, identify candidate therapeutic targets, and enable rigorous preclinical evaluation of therapies in a biologically relevant context. Such work would also have practical benefits for veterinary care and colony management by improving the detection and treatment of spontaneous neoplasms. Against this backdrop, we investigated a cohort of spontaneous, lethal cSCCs identified in a captive macaque population. These tumors presented with clinical and histopathologic hallmarks of human cSCC, including well-differentiated squamous morphology and expression of canonical squamous lineage markers. We applied whole-genome sequencing to define mutational spectra and structural variation, bulk and single-cell RNA sequencing to resolve transcriptional programs and cellular composition, and quantitative proteomics to capture translational and metabolic changes. These multi-omics layers were integrated to map pathways linking genomic lesions to inflammatory activation and metabolic reprogramming. To probe causality, we performed targeted functional perturbations in primary and tumor-derived epithelial cells. Finally, we evaluated therapeutic vulnerabilities using drug screening, in vitro assays of mechanism, murine xenografts for in vivo efficacy and tolerability, and compassionate treatment of a macaque bearing spontaneous tumors to assess real-world activity and systemic effects. RESULTS Characterization of a spontaneous cSCC in captive macaques Among a captive colony of 2,752 macaques, five animals developed cSCC, corresponding to an incidence of 2,575.66 per million (Table S1). Tumors arose predominantly on sun-exposed skin, implicating a possible role for UV exposure. Age-adjusted incidence was higher in females than in males (1931.75 vs. 834.03 per million; Fig. 1A). Affected animals exhibited rapid clinical decline, with survival times of 44–241 days, and spanned a range of human-equivalent ages from 28 to 59.5 years (Table S2) 35 . Histopathological evaluation demonstrated well-differentiated cSCC characterized by invasive epithelial nests, prominent keratin pearls, and stromal inflammatory infiltrates—features that closely parallel human cSCC (Fig. 1B; Fig. S1A). Immunohistochemistry showed strong nuclear p63 (basal progenitor marker) and cytoplasmic cytokeratin 5/6 (CK5/6) expression with markedly elevated Ki-67 indices, consistent with a proliferative squamous epithelial phenotype and arguing against a mesenchymal origin (Fig. 1C). Primary tumor epithelial cells were isolated and purified for downstream molecular analysis (Fig. S1B). The established cSCC cell lines maintained stable proliferative capacity in culture (Fig. S1C) and remained mycoplasma-negative across passages (Fig. S1D). Comparative imaging of primary epithelial cells and purified tumor cultures confirmed exclusion of fibroblast contamination: tumor cells retained CK expression but lacked Vimentin (Fig. 1D). Cytogenetic analysis of 108 metaphase spreads revealed chromosome counts ranging from 47 to 98, consistent with marked chromosomal instability (Fig. 1, E and F; Fig. S1E). Immunofluorescence further confirmed robust expression of CK5/6, Ki-67, and Squamous Cell Carcinoma Antigen 1 (SCCA1) in macaque tumor epithelial cells, with no detectable Vimentin—an expression profile typical of squamous carcinoma cells. By contrast, macaque skin fibroblasts were Vimentin-positive and negative for CK and SCCA1, while normal macaque epithelial cells showed moderate CK expression but lacked SCCA1 and Vimentin. The macaque tumor epithelial immunophenotype closely resembled that of human cSCC epithelial cells, supporting their epithelial origin and the translational relevance of this spontaneous macaque cSCC model (Fig. 1G). Genomic landscape of cSCC tumors in macaques Karyotypic analysis revealed markedly abnormal chromosomal patterns in macaque cSCC samples, suggesting that extensive genomic instability accompanies tumorigenesis 36 . To characterize these alterations in detail, we performed whole-genome sequencing (WGS) on four pairs of macaque cSCC tissues (MSCC) and ANT (Fig. 2A). Analysis of somatic single-nucleotide variants (SNVs) showed a substantially higher mutation burden in tumor samples compared to their matched normal counterparts (Fig. 2B). Notably, several chromosomal regions exhibited elevated mutation frequencies across all four tumors, indicating potential mutational hotspots in macaque cSCC. Recurrent mutations were identified in key cancer-related genes, including TP53 , RB1 , AKT2 , CDH1 , and MYO10 (Fig. 2C), suggesting their potential involvement in cSCC pathogenesis 8 . We next analyzed the mutational spectrum of macaque cSCC. Among the six major substitution types, C>T transitions were the most prevalent (Fig. 2D), consistent with mutational signatures commonly observed in human cSCC 7 . Given the markedly altered karyotypes, we further investigated large-scale structural variations (SVs). All four tumor samples exhibited numerous chromosomal translocations, corroborating the cytogenetic observations (Fig. 2E; Fig. S2, A to C). Copy number variation (CNV) analysis further demonstrated widespread genomic imbalances (Fig. 2F; Fig. S2, D to F). Particularly, Chromosome 8 showed recurrent copy number gains across all tumor samples. This specific translocation pattern aligns with findings in human cSCC, where 3p losses (e.g., TP53 locus) and 8q gains (e.g., MYC gene) are associated with advanced disease 37-39 . Collectively, these findings demonstrate that macaque cSCC is characterized by extensive genomic instability, involving a high somatic mutation burden, recurrent structural variations, and widespread copy number alterations. Bulk and single-cell transcriptomic profiling identifies malignant epithelial populations driving transcriptional alterations in macaque cSCC To investigate the transcriptional changes underlying macaque cSCC, we conducted bulk RNA-sequencing on cells isolated from tumor tissues and matched ANT (Fig. 3A). Differential expression analysis identified pronounced transcriptional alterations in tumors (Fig. 3B). Pathway enrichment analysis revealed significant enrichment of upregulated genes (e.g., MYCN , BCL2 , E2F1 , E2F2 , E2F8 , and AKT1 ) associated with cell cycle regulation, cytoskeleton organization, and canonical oncogenic signaling. Conversely, downregulated genes (e.g., TP53 , CDKN1A , CDKN2B , BAX , MCL1 , DAPK1 , and BID ) were associated with lysosomal function, cell adhesion, apoptosis, and peroxisomal activity (Fig. 3, C and D). These findings collectively indicate a profound reprogramming of transcriptional networks during cSCC pathogenesis, characterized by the activation of pro-proliferative and anti-apoptotic programs. To characterize cellular compositions in cSCC, we performed single-cell RNA sequencing (scRNA-seq) on tumor tissues and matched ANT. Following quality control, 25,233 high-quality cells were retained for downstream analysis and visualized via Uniform Manifold Approximation and Projection (UMAP). Unsupervised clustering guided by canonical lineage markers identified 18 distinct cell populations spanning immune (e.g., T cells, monocytes, macrophages), stromal, and epithelial lineages (Fig. 3E and Fig. S3). Comparative analysis of cell-type proportions revealed significantly increased infiltration of immune populations in tumors, indicative of an active tumor immune microenvironment (Fig. 3F). Critically, we identified both a distinct cluster of malignant epithelial cells and a proliferating epithelial subset characterized by high proliferative activity, which may drive malignant expansion. Integration of bulk RNA-seq and scRNA-seq differential expression results confirmed that proliferating epithelial cells were the primary drivers of transcriptional divergence between tumor and adjacent tissues (Fig. 3G). To further assess the malignant potential of epithelial subsets, we applied inferCNV to infer large-scale chromosomal alterations. Malignant epithelial cells exhibited extensive copy number changes, including alterations on chromosomes 1, 7, and 8. Notably, a subset of proliferating epithelial cells also displayed pronounced copy number variations, supporting their malignant nature (Fig. 3H). Sub-clustering of proliferating epithelial cells revealed clear segregation between tumor- and adjacent tissue-derived subsets, highlighting their distinct transcriptional states (Fig. 3I). Functional enrichment analysis of tumor-derived proliferating epithelial cells demonstrated significant upregulation of the tube morphogenesis pathway (Fig. 3J), suggesting a potential role in tumor progression. Together, these findings indicate that transcriptional alterations in macaque cSCC are largely driven by proliferating epithelial cells, a subset of which acquires malignant genomic features, underscoring their potential importance in cSCC biology and as targets for therapeutic intervention. Proteomic profiling revealed MYO10 as a potential driver of macaque cSCC To investigate molecular drivers of macaque cSCC, we performed quantitative proteomic profiling of tumor tissues and matched ANT (Fig. 4A). This analysis identified extensive protein-level alterations (Fig. 4B), characterized by pronounced upregulation of DNA damage repair factors (e.g., ATM, APOBEC3A), inflammatory mediators (e.g., IL36A, CGAS), and cytoskeletal regulation—most notably MYO10, a protein previously implicated in genomic instability modulation and inflammatory pathway activation 40 . Functional annotation of upregulated proteins highlighted significant enrichment in RNA processing pathways (Fig. 4C), a hallmark previously reported in human squamous carcinomas such as HPV-negative head and neck SCC 41 , suggesting conserved post-transcriptional reprogramming in cSCC pathogenesis. By contrast, mitochondrial oxidative phosphorylation components were systematically downregulated (Fig. 4D), aligning with metabolic rewiring toward aerobic glycolysis (Fig. S4). Unsupervised clustering confirmed coordinated overexpression of DNA damage response, inflammatory, and cytoskeletal regulatory proteins in tumors (Fig. 4E). Western blot analysis validated the proteomic findings, demonstrating elevated expression of MYO10, γ-H2AX (a marker of DNA double-strand breaks), and phosphorylated NF-κB p65 (Ser468) in macaque cSCC tissues relative to matched adjacent samples (Fig. 4F). This indicates a distinct state of NF-κB pathway regulation in tumors, which is associated with the observed inflammatory microenvironment. To assess the clinical relevance, we analyzed human head and neck squamous cell carcinoma (HNSC) data from the UALCAN database 42 . ATM , TLR2 , and MYO10 exhibited significantly elevated expression in human HNSC tissues compared to normal controls (Fig. 4, G to L), with higher expression correlating with advanced tumor stage—supporting their roles in human squamous carcinogenesis. MYO10 contributes to tumorigenesis via regulating genomic instability and inflammation Integrated analysis of whole-exome sequencing, RNA-seq, and proteomic profiling of macaque cSCC tissues from cynomolgus macaques consistently identified MYO10 (myosin-X) as a candidate gene of interest. Somatic mutations in MYO10 were detected in 3 out of 4 tumor samples (Fig. 2C), suggesting potential functional consequences. Moreover, proteomic data demonstrated robust upregulation of MYO10 in tumor tissues compared to ANT (Fig. 4B and F). To assess the clinical relevance of this finding, we analyzed MYO10 expression across human datasets from The Cancer Genome Atlas (TCGA). MYO10 was significantly upregulated in human HNSC tissues relative to ANT (Fig. 4, K and L). Furthermore, elevated MYO10 expression positively correlates with advanced tumor stage (Fig. S5A) and nodal metastasis status in HNSC (Fig. S5B), suggesting a potential role in HNSC cancer progression. The consistent upregulation of MYO10 in tumor tissues and its correlation with advanced disease in human datasets supported the hypothesis that MYO10 may be functionally involved in the regulation of genomic stability and inflammation, two processes prominently altered in our multi-omics data. To investigate this, we performed functional assays involving MYO10 knockdown and overexpression in macaque-derived cSCC cells and primary epithelial cells, respectively. Knockdown of MYO10 reduces DNA damage and inflammatory signaling To examine the role of MYO10 in tumor cells, we silenced its expression in cSCC cells using siRNA. Efficient knockdown was confirmed by Western blot (Fig. 5A). Following MYO10 silencing, Western blot analysis revealed reduced expression of γ-H2AX, a well-established marker of DNA double-strand breaks (Fig. 5, A and B). In parallel, we observed a significant decrease in the number of micronuclei (Fig. 5, C and D), a hallmark of genomic instability. Meanwhile, quantitative PCR analysis showed decreased expression of key DNA damage response genes, including ATM and ATR , upon MYO10 knockdown (Fig. 5, E and F). Inflammatory cytokine expression, specifically IL6 and TNF-α , was also significantly suppressed (Fig. 5, G and H), aligning with the inflammatory transcriptomic signature observed in the tumor tissues. MYO10 drives a pro-tumorigenic cascade spanning epithelial and stromal compartments To assess whether MYO10 is sufficient to induce DNA damage and inflammatory signaling, we ectopically expressed it in primary epithelial cells from healthy macaque oral mucosa. Western blot analysis confirmed successful overexpression and further revealed that MYO10 levels were substantially higher in tumor-derived epithelial cells than in normal controls (Fig. 5I). Upon MYO10 overexpression, γ-H2AX levels were markedly elevated, indicating increased DNA damage (Fig. 5J). Enforced expression of MYO10 led to a significant increase in the number of micronuclei (Fig. 5K and L), mirroring the phenotype observed in tumor cells. Quantitative PCR further demonstrated upregulated ATM and ATR mRNA levels (Fig. 5M, N), consistent with enhanced transcription of inflammatory mediators IL6 and TNF-α (Fig. 5O, P). Having established MYO10's role in driving genomic instability and inflammation within epithelial cells, we next explored its potential to remodel the skin tumor microenvironment. Strikingly, overexpression of MYO10 in human dermal fibroblasts (HDF) significantly enhanced their proliferation and induced prominent colony formation (Fig. S5C and D), demonstrating its capacity to confer transformation-associated phenotypes upon stromal cells. Collectively, these data establish MYO10 as a multi-faceted oncoprotein that drives cSCC development through integrated mechanisms: intrinsically compromising genomic integrity and fueling inflammation within keratinocytes, while extrinsically coercing dermal fibroblasts into a pro-tumorigenic state. Drug screening and cytotoxicity assessment Based on prior transcriptomic and genomic analyses, which identified genomic instability, dysregulated cell cycle progression, and chronic inflammation as key features of cSCC in macaques, six candidate drugs were selected for testing their anticancer efficacy, including paclitaxel (microtubule-stabilizing agent) 43 , Gemcitabine (nucleoside analoge) 44 , EF24 (curcumin analog with antioxidant and anti-inflammatory properties) 45 , Rapamycin (mTOR inhibitor) 46 , ABT263 (Bcl-2 family inhibitor) 47 , and Cisplatin (DNA crosslinking agent) 48 . Cytotoxicity was assessed in cSCC cells and normal epithelial cells of macaque by determining the half-maximal inhibitory concentration (IC 50 ). Among the compounds tested, paclitaxel exhibited the most potent cytotoxic effect against cSCC cells, with an IC 50 of 0.011 μM (Fig. 6A, left panel). Other compounds, such as Gemcitabine (0.035 μM) and EF24 (0.843 μM), demonstrated moderate potency, whereas ABT263 (1.086 μM), Cisplatin (1.46 μM), and Rapamycin (3.204 μM) exhibited comparatively lower effectiveness. Although Gemcitabine and EF24 exhibited relatively low IC 50 values and are typically associated with reduced toxicity to normal cells (Fig. 6A, right pannel), paclitaxel demonstrated the most favorable balance between efficacy and selectivity (Fig. 6B). It effectively killed tumor cells while exhibiting minimal toxicity to normal epithelial cells. These findings suggest that paclitaxel possesses the highest therapeutic index among the drugs tested, making it a promising candidate for further clinical development. Paclitaxel induced apoptosis, cell cycle arrest and migration inhibition in cSCC cells To elucidate the mechanisms by which paclitaxel exerts its anticancer effects in cSCC cells, we performed flow cytometry and Western blot analyses to assess apoptosis and cell cycle progression. Flow cytometry analysis revealed that treatment with paclitaxel (100 nM, 24 h) induced apoptosis in approximately 20% of cSCC cells (Fig. 6, C and D). This pro-apoptotic effect was further supported by Western blot analysis, which showed increased levels of cleaved PARP (cPARP) and cleaved Caspase-3 (cCaspase-3), indicating activation of the intrinsic apoptotic pathway (Fig. 6, E and F). In addition, flow cytometry analysis of cell cycle distribution demonstrated a marked accumulation of cells in the G2/M phase following paclitaxel treatment (Fig. 6, G and H), consistent with mitotic arrest due to microtubule stabilization and impaired spindle formation 43 . We also assessed the effect of paclitaxel on cell migration using a cell scratch assay, which revealed a significant inhibition of cSCC cell migration (Fig. 6,I and J). These results highlight the dual mechanism of paclitaxel in inducing apoptosis and cell cycle arrest in cSCC cells, contributing to its potent anticancer activity. In vivo efficacy and safety of paclitaxel in a cSCC xenograft model To assess the therapeutic potential of paclitaxel in vivo, we established a xenograft model through subcutaneous inoculation of macaque-derived cSCC cells into immunodeficient nude mice (Fig. 7A). Successful tumor engraftment was confirmed by histopathological analysis, which revealed that the xenografts retained a well-differentiated squamous cell carcinoma morphology (including invasive nests and keratin pearls; Fig. S6A, arrow) consistent with the original phenotype, and by immunohistochemistry, which demonstrated positive expression of cSCC markers p63, CK5/6, and Ki-67 (Fig. S6B). This model thus provides a robust platform for evaluating the antitumor efficacy and systemic safety of candidate therapeutics in vivo. Based on previously published studies 49-51 , we chose a low-dose, high-frequency dosing regimen for paclitaxel administration, delivering 5 mg/kg via slow intravenous injection every three days. This approach was selected to balance therapeutic efficacy with minimizing toxicity. Macroscopic examination of excised tumors from the paclitaxel-treated group showed a notable reduction in tumor size compared to vehicle-treated controls (Fig. 7B and Fig. S7A). Paclitaxel treatment resulted in a significant reduction in tumor volume by 89.4% (p < 0.001; Fig. 7C). We further examined the expression of MYO10, a candidate cSCC driver identified in our multi-omics analyses. Western blot analysis showed that MYO10 protein levels were markedly elevated in cSCC xenograft tumors compared to normal nude mouse skin, and were substantially reduced following paclitaxel treatment (Fig. 7D, E), suggesting that paclitaxel may suppress tumor growth partly through downregulating MYO10. TUNEL assay also demonstrated significant induction of apoptosis in paclitaxel-treated tumors (Fig. 7F). Despite inducing extensive tumor regression, paclitaxel treatment did not affect histopathological alterations in major organs (heart, liver, spleen, lung, and kidney) (Fig. 7G). Furthermore, no significant differences in body weight were observed between paclitaxel- and vehicle-treated mice (Fig. 7H). Blood parameters, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CRE2), blood urea nitrogen (BUN), and creatine kinase (CK), remained within normal ranges post-treatment (Fig. 7, I to M). Additionally, organ weights showed no notable changes (Fig. S7B), and all hematological parameters remained within normal physiological ranges (Fig. S7, C to L). These findings collectively demonstrate that paclitaxel has a favorable safety profile in vivo, supporting its potential for clinical translation in cSCC therapy. Antitumor efficacy and safety of a paclitaxel formulation in macaque with spontaneous cSCC To assess the therapeutic potential of paclitaxel against spontaneously arising cSCC, cSCC bearing macaque was treated and monitored for changes in tumor progression and systemic inflammation (Fig. 8A). Paclitaxel administration induced a significant reduction in tumor volume, with a mean reduction of 86.6 ± 10.1% relative to baseline (p < 0.001; n = 6 tumors in one macaque) (Fig. 8B). MRI evaluation confirmed a decrease in tumor dimensions accompanied by central necrosis, consistent with paclitaxel-induced mitotic catastrophe (Fig. 8C, yellow arrow). ELISA assay revealed significant reductions in pro-inflammatory cytokines IL-6 and TNF-α following paclitaxel treatment, indicating attenuation of systemic inflammation associated with tumor burden (Fig. 8, D and E). Concurrently, an increase in the anti-inflammatory cytokine IL-10 was observed post-treatment (Fig. 8F), suggesting a concomitant activation of compensatory anti-inflammatory mechanisms. Before intervention, the macaque exhibited notable weight loss (Fig. S8A) and elevated pro-inflammatory cytokine levels (Fig. 8,D and E), suggestive of cancer-associated cachexia 12 . No significant alterations in body temperature (Fig. S8B) or severe hematologic toxicity were observed (Fig. 8G). Cardiovascular parameters remained stable throughout treatment (Fig. S8C), and serum creatine kinase levels, despite mild elevation, were maintained within the normal physiological range (Fig. S8D). All hematological indices also remained within normal limits (Fig. S8,E and F). Apoptotic activity was significantly enhanced in tumor tissues following paclitaxel treatment, as evidenced by TUNEL staining (Fig. 8H). Together, these findings demonstrate that paclitaxel effectively induces tumor regression and apoptosis while modulating systemic inflammatory responses, with a favorable safety profile in this spontaneous non-human primate model of cSCC. DISCUSSION In this study, we present a comprehensive molecular characterization of spontaneous, lethal cSCC in macaques, integrating genomics, transcriptomics, single-cell profiling, proteomics, and functional perturbation. Our data reveal a disease program driven by extensive genomic instability and chronic innate inflammatory activation, nominate MYO10 as a previously unrecognized mediator that links these processes, and demonstrate that paclitaxel produces profound antitumor effects with an acceptable tolerability profile in both xenograft and spontaneous-tumor settings. These findings establish this spontaneous macaque cSCC as a translationally relevant model that recapitulates key molecular and phenotypic hallmarks of human disease. The genomic features of macaque cSCC closely resemble those observed in UV-induced human cSCC 7 . Whole-genome sequencing revealed a high mutational burden dominated by C > T transitions, widespread chromosomal instability, and recurrent structural variations such as chromosome 3p-8q translocations—a pattern strongly associated with UV damage 7,9,36 . Furthermore, copy number alterations in key genes, including TP53 , NOTCH1 , KRAS , and MYC , reinforce the relevance of these tumors to advanced human cSCC 2,36 . These genomic parallels suggest shared etiological mechanisms between species and provide a compelling foundation for using this model to explore conserved disease drivers. Beyond genomic alterations, multi-omics profiling uncovered significant inflammatory activation, marked by upregulation of NF-κB signaling, pro-inflammatory cytokines (e.g., IL6, TNFα), and immune cell infiltration—including a distinct CD19 + B-cell cluster comprising 18% of tumor-infiltrating cells. This immune-rich microenvironment recapitulates the chronic inflammation commonly observed in human cSCC, where it contributes to tumor progression and immune evasion 52,53 . The presence of an inflammatory "field effect" in histologically normal adjacent tissue further underscores the physiological relevance of this model, as it recapitulates a recognized feature of human field cancerization 13,16,54 . A key finding of our study is the identification of MYO10 overexpression within macaque cSCC tumors, where it appears to functionally link genomic instability and inflammatory signaling 40 . We consistently observed significant upregulation of MYO10 in tumor tissues from macaques, similar to the situation in humans, where elevated MYO10 expression correlates with advanced tumor stage. Using perturbation experiments, we demonstrated that MYO10 drives DNA damage (increased γ-H2AX and micronuclei) and inflammatory activation (elevated IL6 and TNFα) independent of cellular proliferation. These results suggest that MYO10 may act as a novel oncogene in cSCC pathogenesis, possibly acting through regulation of cytoskeletal remodeling or cGAS-STING signaling 40,55,56 . The translational potential of this model was further highlighted by the efficacy of paclitaxel, which induced significant tumor regression in both xenotransplant and spontaneous tumor settings. Its potent anti-tumor activity (IC 50 = 11 nM in vitro, > 89% inhibition in vivo) likely stems from dual targeting of mitotically active cells and the inflammatory microenvironment, as evidenced by reduced IL-6 and TNFα levels post-treatment. Importantly, treatment was initiated in a macaque presenting with multifocal tumors and tumor-associated cachexia 12 , yet still achieved profound tumor reduction (86.6%) with minimal toxicity—supporting the model’s utility for evaluating therapies under clinically relevant conditions. Several limitations merit consideration. The aggressive nature of these spontaneous tumors, coupled with their late-stage presentation, may limit the generalizability of findings to early-stage disease. Additionally, while we establish MYO10 overexpression as a functional contributor to genomic instability and inflammation, its precise molecular mechanisms remain incompletely elucidated. For instance, further mechanistic studies are needed to define the exact pathways involved. The current lack of MYO10-targeting agents also precludes immediate clinical translation, highlighting a need for future drug development efforts. CONCLUSION In summary, this work delineates the molecular landscape of spontaneous macaque cSCC, emphasizing the interplay between genomic instability and inflammation and nominating MYO10 as a key regulator of this process. The model faithfully recapitulates human cSCC that are poorly reproduced in rodents—including genomic complexity, immune microenvironment, and therapeutic response—making it a valuable platform for both mechanistic studies and preclinical evaluation. Beyond advancing cSCC research, these findings may also pave the way for managing spontaneous tumors in non-human primate colonies, contributing to both biomedical science and animal welfare. MATERIALS AND METHODS Cell lines and culture Primary tumor specimens were processed by enzymatic digestion and tissue-block culture to establish primary cSCC cell cultures. Primary cultures were purified by repeated differential adhesion and trypsinization to deplete fibroblast-like cells, yielding a predominantly epithelial population (purity > 95%). Other cell lines used in this study were obtained from the Conservation Genetics CAS Kunming Cell Bank (Kunming, China). Cells were maintained in either Pneu medium (STEMCELL Technologies, Vancouver, Canada; Cat. #05001) supplemented with 1% penicillin–streptomycin (Gibco, Rockville, MD, USA; Cat. #15140-122), 5% fetal bovine serum (Royacel Biotechnology Co., Ltd., Lanzhou, China; Cat. #RY-F22), 1% L-glutamine (Solarbio Biotech, Beijing, China; Cat. #G0200), 0.1% hydrocortisone (Rongsheng Pharmaceutical Co., Ltd., China; NDA No. H20023069), and 2% growth factor additives (STEMCELL Technologies; Cat. #05042), or in DMEM/F-12 (Gibco; Cat. #11320033) supplemented with 1% penicillin–streptomycin and 10% fetal bovine serum. All cultures were maintained at 37°C in a humidified incubator with 5% CO 2 . Cell lines were routinely screened for mycoplasma contamination. Transfection of plasmids and siRNA The MYO10 overexpression plasmids (in the pcDNA3.1 vector) were designed and constructed by YouBio (Changsha, China). When the cells reached approximately 80% confluence, the MYO10 overexpression plasmids related control plasmids were transfected into the indicated cells using Lipofectamine 3000 (Invitrogen, USA; Cat. #L3000015) according to the manufacturer's protocol. For MYO10 knockdown, all siRNAs were designed and synthesized by Sangon Biotech (Shanghai, China). All siRNAs were transfected into the indicated cells using Lipofectamine RNAiMAX (Invitrogen, USA; Cat. #13778150) following the manufacturer's instructions. Cell growth curve Macaque cSCC cells at various passages were trypsinized and seeded in 24-well plates at a density of 1 × 10 3 cells per well. After allowing cells to adhere, three wells were sampled each day and cell concentration was determined using a CytoCubeAuto fully automatic, portable, high-throughput cell counter (Newtonoptic, China). The mean value from the triplicate wells was recorded as the cell count for that day. Daily measurements were continued until cultures reached the plateau (stationary) phase; medium in the remaining wells was refreshed regularly to maintain optimal growth. A growth curve was generated with time (days) on the x-axis and daily cell count on the y-axis. Cell migration assay Macaque cSCC cells were seeded in 6-well plates at a density of 5×10 5 cells/well and cultured until they reached confluence (~ 24 h). A linear scratch was made using a sterile 200 µL pipette tip; debris was removed by washing with DPBS and wells were replenished with fresh complete medium. The experimental group was then incubated with complete medium containing 0.1 µM paclitaxel for 24 h, while the control group received complete medium alone. Images were captured using an optical microscope (Leica, Germany) at 0 and 24 h. The extent of cell migration index (%) was quantified using ImageJ software, and was calculated as follows: where A0 is the scratch area at 0 h and A is the scratch area at 24 h. Cell viability assay Cells (3 × 10 3 per well) were seeded in 96-well plates in 100 µL of 1× Pneu medium supplemented with 1% penicillin–streptomycin (Gibco; Cat. #15140-122), 5% fetal bovine serum (Royacel; Cat. #RY-F22), 1% L-glutamine (Solarbio; Cat. #G0200), hydrocortisone (1:1,000), and 2% growth factor additives. After 24 h, medium was replaced with 0.2 mL of the same medium containing the indicated concentrations of test compounds, and cells were incubated at 37°C for three days. Viability was assessed using the CellTiter-Glo Luminescent Cell Viability Assay (Promega; Cat. #G1111) according to the manufacturer’s instructions. Dose–response curves were generated and half-maximal inhibitory concentrations (IC 50 ) were calculated using GraphPad Prism v9.0.2 (GraphPad Software, San Diego, CA, USA). Cell apoptosis assay The cSCC cells were seeded in 6-well plates at 1 × 10 6 cells per well and incubated with vehicle (VEH) or 100 nM paclitaxel at 37°C for 24 h. Cells were then harvested into polystyrene round-bottom tubes (Falcon; Cat. #352058) and stained with Alexa Fluor 647-conjugated Annexin V (1:60; BioLegend; Cat. #640912) and propidium iodide (1:60; eBioscience; Cat. #00-6990) for 30 min at room temperature in the dark. Apoptosis was quantified by flow cytometry (BD LSRFortessa, USA). Cell cycle assay For cell-cycle analysis, cSCC cells were seeded in 6-well plates at 1 × 10 6 cells per well and treated with 100 nM paclitaxel for 48 h. After treatment, cells were harvested, washed twice with DPBS and fixed in 70% ethanol at 4°C overnight. Fixed cells were washed with DPBS and stained with propidium iodide (KeyGEN Biotech, Jiangsu, China; Cat. #KGA511) for 30 min at room temperature. Cell-cycle phase distribution was determined using flow cytometry (BD LSRFortessa, USA). Quantitative Real-Time PCR (qPCR) experiments Quantitative real-time PCR (qPCR) was performed to evaluate the expression level of SASP (senescence-associated secretory phenotype) genes in the indicated cells or tissues. Total RNA was extracted from cells or tissues using TRIzol reagent (Thermo Fisher Scientific, USA; Cat. #15596018) according to the manufacturer's protocol. The RNA purity and concentration were assessed spectrophotometrically. For cDNA synthesis, a reverse transcription (RT) kit (Thermo Fisher Scientific, USA; Cat. #K1622) was used following the manufacturer's instructions. qPCR was then performed to quantify the expression of target genes using specific primers for SASP genes, and β-actin (internal control), along with SYBR Green master mix (2x Master qPCR Mix TSE201, Tsingke®, Beijing, China). The qPCR primers used in this study are listed in Table S3. The relative mRNA expression levels were determined using the 2 −ΔΔCt method. Western blot assay After treatment, cells were washed with DPBS and lysed in 100 µL ice-cold RIPA buffer with EDTA and EGTA (Boston BioProducts; Cat. #BP-115DG). Lysates were collected into ice-cold tubes, incubated on ice for 30 min and centrifuged at 15,000 × g for 15 min at 4°C. Supernatants were transferred to fresh tubes, flash-frozen and stored at − 80°C. Protein concentration was measured with a BCA Protein Assay Kit (Beyotime; Cat. #P0010). Lysates were mixed with one-quarter volume of 4× Laemmli sample buffer (Bio-Rad; Cat. #1610747) containing 5% β-mercaptoethanol, heated at 95°C for 5 min, and 20 µg of protein per sample were resolved by SDS–PAGE. Proteins were transferred to 0.22 µm PVDF membranes (Millipore) using wet transfer (Bio-Rad). Membranes were blocked in 5% skim milk in TBS-T (50 mM Tris, 150 mM NaCl, 0.1% Tween-20) for 1 h at room temperature, incubated with primary antibodies overnight at 4°C, washed with TBS-T, and then incubated with light-protected secondary antibodies for 1 h at room temperature. After final washes, bands were visualized using a GeneGnome XRQ-NPC system (Synoptics) and quantified with Image Studio software. Karyotyping Primary macaque cSCC cells were grown in 6-cm dishes to 80% confluence and arrested in metaphase with colchicine (0.2 µg/mL) for 1–2 h at 37°C in 5% CO₂. Cells were trypsinized, pelleted (1,200 rpm, 5 min), resuspended in pre-warmed 0.075 M KCl hypotonic solution and incubated at 37°C for 40 min to promote chromosome spreading. Cells were fixed by three washes in freshly prepared methanol:glacial acetic acid (3:1) (1,200 rpm, 10 min per wash) with gentle resuspension between washes to ensure a monodisperse suspension. Fixed cells were dropped onto clean slides and aged at 80°C for 3 h to improve chromosome adhesion. G-banding was performed by brief trypsin digestion (0.25%, 1 min) followed by Giemsa staining (5–10 min at room temperature); banding conditions were optimized empirically. Metaphase spreads were examined by bright-field microscopy to identify recurrent numerical and structural chromosomal aberrations, with ≥ 20 metaphases analyzed per sample to confirm clonal abnormalities. Representative karyotypes were documented using computerized imaging for standardized classification. H&E staining A standard protocol was followed for H&E staining of the mandibular tumors of macaques and major organs (heart, liver, spleen, lung, and kidneys) of mice treated with saline and paclitaxel (1.5 mg/kg) using a dye (Zhuhai Besso Biotechnology Co., Ltd., Guangdong, China; Cat. #ba4025). Briefly, 6 µm paraffin sections were dried at 60 ℃ for 12 h, followed by dewaxing through xylene and rehydration in a gradient of ethanol concentrations. The slides were then stained with hematoxylin for 5 min, rinsed in running tap water, acid ethanol, and deionized water. Subsequently, the slides were stained with Alcoholic-eosin for 3 s. After staining, the slides were dehydrated and rinsed in several xylene baths. Finally, a thin layer of neutral balsam (Solarbio, Beijing, China; Cat. #G8590) was applied, a glass coverslip was placed, and the slides were imaged using an inverted microscope. Immunohistochemistry Immunohistochemistry was performed on 2 µm sections of formalin-fixed, paraffin-embedded tissues from macaques or xenografts. Slides were deparaffinized in xylene and rehydrated through a graded ethanol series (100%, 95%, 70%) and water, with each step incubated for 4 min. Antigen retrieval was achieved by boiling slides in citrate buffer (pH 6.0). Endogenous peroxidase activity was quenched with 3% H 2 O 2 for 10 min. Slides were washed 3 times with DPBS, and permeabilized with 0.5% Triton X-100 at RT for 10 min. Slides were blocked with 10% goat serum for 1 h, then incubated with diluted primary antibody at 4°C overnight, followed by incubation with diluted secondary antibody at room temperature for 1 h (details in Table S4). After development with 3,3'-diaminobenzidine (DAB) (Cat. #DAB-0031) for 3 min, slides were washed in water and counterstained with hematoxylin. Slides were dehydrated through ethanol (70%, 95%, 100%, 6 min each) and xylene (15 min), mounted with EcoMount (Thermo Fisher; Cat. #EM897L), and imaged using an inverted microscope per the manufacturer’s instructions. Immunofluorescence Formalin-fixed paraffin-embedded macaque tissues were sectioned at 2 µm, baked at 60–65 ℃ for 30 min, and sequentially deparaffinized in xylene (3 × 10 min) followed by rehydration through graded ethanol (100% to 75%) and DPBS rinses. Antigen retrieval was performed by microwaving slides in 0.01 M citrate buffer (pH 6.0) at high power until boiling (8 min), then at low power for 15 min to sustain epitope exposure. After cooling and DPBS washes (3 × 5 min), sections were permeabilized with 0.5% Triton X-100 (10 min, RT), blocked with 1% bovine serum albumin (BSA) (30 min, RT), and circumscribed with a hydrophobic barrier. The samples were then incubated with diluted primary antibody at 4 ℃ overnight, followed by DPBS washes (3 × 5 min) and room-temperature equilibration. After this, diluted secondary antibody was added and samples were incubated in the dark for 1 h at room temperature (details in Table S2). Nuclei were counterstained with 4',6-diamidino-2-phenylindole (DAPI) (5 min), and slides were mounted with Fluoromount-G® to minimize photobleaching. Fluorescence signals were visualized and imaged using a confocal microscope, with exposure settings standardized across samples to ensure comparability. The pretreated cell slides were placed into a 48-well cell culture plate. The epithelioid cells to be identified in culture flasks were digested with 0.25% trypsin, and the digestion was terminated by adding an appropriate amount of complete medium, and the cell suspension was then transferred to a 15 mL centrifuge tube to discard the supernatant and collect the cell precipitate. The cells were resuspended in fresh complete medium and inoculated into 48-well plates with 500 µL cell suspension per well. The cells were cultured in an incubator until they grew into a monolayer. The medium in the wells was aspirated, and the cells were washed with DPBS, followed by fixation with 4% paraformaldehyde (15 min). After fixation, the cells were washed with DPBS. Permeabilization was performed using 0.5% Triton X-100 (20 min) at room temperature, followed by three washes with DPBS. Excess DPBS on the cell slides was removed using absorbent paper, and each well was incubated with 500 µL of 1% BSA blocking solution for 30 min at room temperature. After removing the blocking solution, the sample was incubated with diluted primary antibody at 4 ℃ overnight, followed by DPBS washes and room-temperature equilibration. Hereafter, diluted secondary antibody was added, and the sample was incubated in the dark for 1 h at room temperature (details in Table S2), followed by washes with DPBS. Nuclei were counterstained with DAPI (5 min) in the dark, followed by washes with DPBS. The slides were carefully removed, excess liquid was blotted, and the slides were mounted with Fluoromount-G® (Cat. 0100-01) to minimize photobleaching. Fluorescence signals were visualized and imaged using a confocal microscope. TUNEL staining Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay was performed on 2 µm sections of formalin-fixed, paraffin-embedded tissues from macaques or xenografts. Slides were deparaffinized in xylene and rehydrated through a graded ethanol series (100% ethanol for 5 min, 90% ethanol for 2 min, 70% ethanol for 2 min) and water for 2 min. Proteinase K (0.2ml; Beyotime; Cat. #ST533) was applied to the sections and incubated at 20–37 ℃ for 15–30 min to facilitate antigen retrieval. Slides were washed 3 times with DPBS, then incubated with the TUNEL reaction mixture (containing terminal deoxynucleotidyl transferase (TdT) enzyme and fluorescent labeling solution) at 37 ℃ for 60 min in the dark. Slides were washed 3 times with DPBS. After sealing with anti-fluorescence quenching sealing solution, fluorescence signals were visualized and imaged using a confocal microscope, with exposure settings standardized across samples to ensure comparability. TUNEL staining was performed using a One-step TUNEL Apoptosis Assay kit (Beyotime; Cat. #C1090) following the manufacturer’s instructions. RNA sequencing and analysis RNA was extracted from nine macaque cell samples—comprising three replicates each of normal epithelial cells from healthy macaques, cancer-adjacent epithelial cells, and squamous carcinoma cells—using TRIzol reagent (Thermo Fisher Scientific, USA; Cat. #15596018CN) as per the manufacturer’s protocol. Poly(A)-enriched RNA-seq libraries were prepared and sequenced on the Illumina NovaSeq X Plus platform by Biolinker Technology (Kunming) Co., Ltd. Adapter-trimmed reads, processed with trim_galore, were aligned to the Macaca mulatta genome using STAR v2.7.11a, followed by file conversion with SAMtools v1.18. Gene expression was quantified using featureCounts v2.0.6, and differentially expressed genes (DEGs) were identified with DESeq2 (adjusted p < 0.05). Functional enrichment analysis for Gene Ontology and KEGG pathways was performed using ShinyGO v0.82. Hierarchical clustering, heatmaps, and volcano plots were generated using ClusterGVis and ggplot2 in R. Whole-genome sequencing data processing Whole-genome sequencing (WGS) was performed on tumor and matched adjacent non-tumor tissues (ANT) of rhesus macaque squamous cell carcinoma. Raw sequencing reads were subjected to quality control and adapter trimming using fastp (v0.23.2), and the clean reads were aligned to the M. mulatta reference genome (ensembl Mmul_10.113) with BWA-MEM (v0.7.18). The resulting BAM files were processed with Samtools (v1.9), and duplicates were removed using Picard (v2.18.29). Base quality score recalibration was then performed with Genome Analysis Toolkit (GATK) (v4.1.0.0) using known rhesus macaque variant sites. Somatic single-nucleotide variants (SNVs) and small insertions/deletions (indels) were identified with Strelka2 (v2.9.10), copy number variations (CNVs) were detected using CNVkit (v0.9.12) in whole-genome mode, and structural variants (SVs) were inferred with Manta (v1.6.0). Single-cell RNA-seq data processing and quality control Raw sequencing data were first processed and quantified using Cell Ranger (v6.0.0) with default parameters, generating expression matrices for downstream analyses. The matrices from tumors and ANT were further processed in Seurat (v5.3.0). Gene identifiers were mapped to gene symbols, and duplicated entries were collapsed by summing counts. Low-quality cells were excluded if they contained fewer than 200 detected genes, more than 6,000 genes, or greater than 5% mitochondrial transcript content. Potential doublets were identified and removed using DoubletFinder (v2.0.4). Data integration and clustering After quality control, datasets from all samples were normalized. Highly variable genes were identified, followed by principal component analysis (PCA). Batch effects across samples were corrected using Harmony integration. Cells were clustered using a shared nearest neighbor (SNN) modularity optimization approach at a resolution of 0.5, and clusters were visualized with UMAP. Cell type annotation and downstream analyses Differentially expressed genes (DEGs) were identified for each cluster using the FindAllMarkers function (log2FC > 0.25, adjusted p < 0.05). Cluster annotation was guided by canonical marker genes and further curated to define broad cell types, including malignant epithelial cells, fibroblasts, immune populations, endothelial cells, and stromal lineages. Cell type compositions were quantified across tumor and adjacent samples. To investigate large-scale genomic alterations, inferCNV (v1.18.1) was applied to infer copy number variation (CNV) profiles, using immune and stromal cells as reference populations. Differential expression analyses were further conducted between tumor and normal subsets. Proteomic assay Proteomic analysis was performed by Shanghai Bioprofile Biotechnology Co., Ltd. Peptide samples were separated on a µPAC Neo High-Throughput column using a Vanquish Neo UHPLC system, with a linear gradient from 4–99% solvent B over 10 min. Data-independent acquisition (DIA) was carried out on an Orbitrap Astral mass spectrometer in positive-ion mode, with an MS1 scan range of 380–980 m/z and a resolution of 240,000. Raw data were processed with DIA-NN for protein identification and quantification against the UniProtKB Macaca mulatta reference database. For data analysis, proteins with > 50% non-missing values across samples were included, and missing values were imputed. Differentially expressed proteins were defined as those with fold change > 1.5 and P < 0.05. Ectopic model of cSCC Four-week-old male BALB/c nude mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). The animals were housed under specific pathogen-free (SPF) conditions with free access to standard food and water for 2 weeks. Environmental conditions were maintained at 20–21°C with 40%–60% relative humidity under a 12-h light/dark cycle. Mice were used for experiments once they reached a body weight of approximately 20 g. All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals. To establish the ectopic cSCC model, 5 × 10 6 cSCC cells suspended in 100 µL of a 1:1 mixture of Pneu and Matrigel were inoculated subcutaneously on the left dorsal side, above the abdominal area of each mouse. Matrigel (Corning Incorporated, Corning, USA; Cat. #356234) was thawed on ice overnight prior to use. After 4 weeks, tumors reached an average volume of 100–120 mm³. Tumor volume (V) was calculated using the formula V = (L × W²) / 2, where L is tumor length and W is tumor width. Mice were then stratified into two groups based on tumor size. Following inoculation, body weight and tumor dimensions were monitored every three days. The maximal permitted tumor burden was 1500 mm³, and this limit was not exceeded in any experiment. In vivo drug treatment For murine xenografts, paclitaxel (5 mg/kg) was administered via intravenous (IV) injection in 100 µL saline every three days. The injection time for mice was approximately 1 min. In macaques, paclitaxel (80 mg/m²) was delivered as a 1 h IV infusion in 5% glucose-saline weekly. Premedication included sequential IV administration of dexamethasone (1 mL), diphenhydramine (0.5 mL), and granisetron (0.6 mL of 1 mg/mL solution) 30 min prior to treatment, respectively, to mitigate hypersensitivity and emesis. All agents were administered intravenously in strict sequence to avoid pharmacological interactions. Sampling of blood and tissue For nude mouse procedures, after a 12 h fast with ad libitum water, mice were humanely euthanized under isoflurane anesthesia via cardiac exsanguination followed by cervical dislocation, using inhalational anesthesia instead of isopentane. Similarly, for macaque blood collection, sedated macaques (ketamine 10 mg/kg IM) after a ≥ 10 h fast underwent saphenous vein venipuncture, preferred over arm veins to reduce stress, with certified technicians collecting 4 mL blood into K 3 EDTA tubes using 21-gauge safety needles at a 15–20° angle to minimize hemolysis. Blood samples were processed promptly: EDTA-treated aliquots were analyzed within 2 h using the Mindray BC-5000 Vet analyzer to ensure platelet stability, while serum tubes were clotted for 30 min, then centrifuged at 1500×g for 10 min at 4 ℃. For tissue preservation, separated tissues were fixed in 10% neutral buffered formalin for 48 h to optimize histomorphology, or snap-frozen in liquid nitrogen to prevent ice crystal artifacts, with storage at -80 ℃ in RNase-free cryovials. Blood biochemical analysis Blood cell counts were conducted by the National Resource Center for Non-Human Primates at the Kunming Institute of Zoology, Chinese Academy of Sciences. All serum parameters were quantified with Siemens Healthcare kits per the manufacturer's instructions. All samples were analyzed via photometry on a Dimension EXL 200 (Erlangen, Germany). MRI study Magnetic resonance imaging (MRI) data were collected on a Shanghai United Imaging Medical Technology’s uMR NX 3.0T magnetic resonance imaging system at the Kunming Institute of Zoology using a human knee coil. Functional scans were collected using gradient echo with repetition time (TR) = 3830 s, echo time (TE) = 42.1 ms, flip angle = 90°, voxel size = 1.5 × 1.5 × 3.0 mm (slice thickness = 3.0 mm with 0% slice gap), matrix size = 64 × 100, and field of view = 96 × 95 mm. Forty axial slices were prescribed to cover the entire cortex and were scanned in order. Statistical analysis One-way ANOVA followed by Tukey’s post hoc tests was performed in GraphPad Prism 8.0 to determine differences between each group when more than two conditions were present. Unpaired two-tailed Student’s t tests were performed for two pairwise comparisons due to normal distribution and equal variances. Error bars represent standard deviation (SD) or standard error of the mean (SEM). A value of p < 0.05 was set to be a significant threshold. Declarations ACKNOWLEDGMENTS We would like to thank Kunming Cell Bank of Type Culture Collection for their technical support in culturing the cSCC cells. We thank the Core Technology Facility of the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences (CAS) for providing high-resolution in vivo and in vitro imaging. We are also grateful to Shuangjuan Yang for her technical support. Authors' contributions Yongzhang Pan: Methodology, Investigation, Visualization, Validation, Formal analysis, Data Curation, Software, Writing - Original Draft. Lihong Li: Methodology, Investigation, Visualization, Validation, Formal analysis, Data Curation. Lingling Xiao: Methodology, Investigation, Visualization, Validation, Formal analysis, Data Curation. Xin Dong: Methodology, Investigation, Visualization, Validation, Formal analysis, Data Curation, Software. Jian Pu: Methodology. Qi Geng: Methodology. Meng Zhou: Methodology. Qinghua Zeng: Methodology. Chengmei Yang: Methodology. Rui Li: Methodology. Gui Li: Methodology. Chao Liu: Methodology. Qiong Wang: Methodology. Ayesha Nisar: Writing – review & editing. Sawar Khan : Writing – review & editing. Longbao Lv: Resources, Conceptualization, Supervision, Funding acquisition, Project administration. Yonghan He : Resources, Conceptualization, Supervision, Funding acquisition, Project administration, Writing – review & editing. Ethical approval All procedures involving animals in this study were reviewed and approved by the Animal Ethics Committee of the Kunming Institute of Zoology, Chinese Academy of Sciences (Approval Nos. IACUC-PE-2025-04-006 and IACUC-RE-2025-04-006). Funding : National Key R&D Program of China (2023YFC3603300 to YHH) Yunnan Fundamental Research Projects (202305AH340006 to YHH) National Natural Science Foundation of China (82171558 and 82471599 to YHH) CAS "Light of West China" Program (xbzg-zdsys-202312 to YHH) Technology Talent and Platform Plan Program of Yunnan Province (202405AD350052, 202305AF150160, 202305AH340007 to LBL) Academician Expert Workstation of Yunnan Kunming (YSZJGZZ-2022063 to LBL) Special Project of Yunnan Provincial Key Laboratory of Ophthalmic Disease Prevention and Treatment Research ((2017DG008(2025-1) to LBL) YHH is supported by the Pioneer Hundred Talents Program of the Chinese Academy of Sciences and the Yunnan Revitalization Talent Support Program Young Talent Project. Conflict of Interest YZP, LHL, LLX, LBL and YHH are inventors on a patent for the construction and use of a macaque cSCC model. The other authors declare no competing interests. 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Supplementary Files 3SupplementaryMaterials2026.2.27.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 May, 2026 Reviewers invited by journal 06 May, 2026 Editor assigned by journal 07 Mar, 2026 Submission checks completed at journal 02 Mar, 2026 First submitted to journal 27 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8987244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":640135282,"identity":"e6cd7c45-909c-4d9f-8a2c-0b20694458c7","order_by":0,"name":"Yongzhang Pan","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yongzhang","middleName":"","lastName":"Pan","suffix":""},{"id":640135284,"identity":"5f33a98e-bd6b-4584-974f-efc1f81c2d02","order_by":1,"name":"Lihong Li","email":"","orcid":"","institution":"Kunming Institute of Zoology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lihong","middleName":"","lastName":"Li","suffix":""},{"id":640135285,"identity":"380582c9-f1e2-41bf-8192-5426f0b7d328","order_by":2,"name":"Lingling Xiao","email":"","orcid":"","institution":"University of Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lingling","middleName":"","lastName":"Xiao","suffix":""},{"id":640135286,"identity":"f50d7d02-1fc5-40e8-95d6-db0e3c0d1ff4","order_by":3,"name":"Xin Dong","email":"","orcid":"","institution":"Kunming Institute of Zoology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Dong","suffix":""},{"id":640135287,"identity":"83c6c588-829e-4358-85ac-8b9e1baa5d47","order_by":4,"name":"Jian Pu","email":"","orcid":"","institution":"The Affiliated Hospital of Yunnan 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He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYBACAwh1gIGBvYGBIaGAwYCNeC08QJxgQJIWiQQw14Cgw8zZewwfF/y6I28u+TrxwwMDBmM+/gOMH34w2OXh0mLZc8bYeGbfM8Ods3M3SwAdZsbGcIBZsochuRinw27kmEnz9hxm3HA7dwNIiw0bYwODNNCpiQ24tNx/A9Ziv+Hm2c0/wFqYGZh/49Vyg8dMmufH4cQNN3i3QRzGxsCG35YzacXGvA2Hkzecyd1mkWAgYczGw9hm2WOQjFvL8cMbH/P8OWy74fjZzTd/VNgYzu8/fPjGjwo7nFoYGDgMGBjb4DwJIAb6H3/0sD9gYPiDT8EoGAWjYBSMeAAAQohXsIqnU2EAAAAASUVORK5CYII=","orcid":"","institution":"Kunming Institute of Zoology, Chinese Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Yonghan","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2026-02-27 11:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8987244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8987244/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109343073,"identity":"83d17ab8-cb10-43fa-a550-e5dd7cdc6645","added_by":"auto","created_at":"2026-05-15 19:39:47","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":373262,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of macaque cutaneous squamous cell carcinoma (cSCC). (A)\u003c/strong\u003e Summary schematic of colony screening and observed cSCC incidence highlighting the estimated morbidity per million for female and male macaques with confirmed cSCC. Affected individuals are shown in red color. \u003cstrong\u003e(B) \u003c/strong\u003eRepresentative histopathological appearance of cSCC. Top panels show the normal skin and the bottom panels represent a mandibular mass (red dashed circle indicates lesion site), while the right panels show the corresponding H\u0026amp;E staining. Blue arrows indicate the keratinizing areas in cSCC. Scale bar: 100 μm. \u003cstrong\u003e(C)\u003c/strong\u003eImmunohistochemistry showing nuclear p63 expression, strong epithelial CK5/6 squamous differentiation, and increased Ki-67 tumor cell proliferation. Scale bar: 100 μm. (\u003cstrong\u003eD\u003c/strong\u003e) Purified macaque tumor cells (on right) in comparison to corresponding normal cells (on left). (\u003cstrong\u003eE\u003c/strong\u003e) Representative karyotype showing metaphase spread from tumor-derived cells demonstrating chromosomal abnormalities. (\u003cstrong\u003eF\u003c/strong\u003e) Quantification of karyotypes detected across analyzed metaphases. Frequency distribution of chromosomal counts (47–98) across 108 analyzable metaphase spreads from macaque cSCC cells. (\u003cstrong\u003eG\u003c/strong\u003e) Immunofluorescence staining of macaque skin fibroblasts (normal), macaque epithelial cells (normal), macaque cSCC cells (tumour) and A431 human cSCC cells (positive control). Columns show staining for CK5/6 (epithelial marker), vimentin (mesenchymal marker), Ki-67 (proliferation marker) and SCCA1 (squamous cell carcinoma antigen). Nuclei were counterstained with DAPI. Macaque tumor cells show strong CK5/6 and SCCA1 expression and elevated Ki-67 labelling compared with normal cells. Scale bar: 100 μm.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/25ed8821d08bef97a6cf1996.jpeg"},{"id":109343071,"identity":"6830934c-e91b-43a1-b499-b8c9d3de575e","added_by":"auto","created_at":"2026-05-15 19:39:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1202391,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenomic landscape of the cSCC tumors of macaques revealed by whole-genome sequencing (WGS). (A)\u003c/strong\u003e Workflow of WGS analysis for macaque cSCC and ANT. \u003cstrong\u003e(B)\u003c/strong\u003e Circos plot of the genome-wide distribution of somatic single-nucleotide variants (SNVs) in cSCC samples. \u003cstrong\u003e(C)\u003c/strong\u003e Heatmap of mutations in representative cancer-related genes across cSCC tumor samples. (\u003cstrong\u003eD\u003c/strong\u003e) Radar plot of the relative contributions of six major mutational signatures, with C\u0026gt;T transitions being the most predominant. (\u003cstrong\u003eE\u003c/strong\u003e) Circos plot of large-scale structural variations, including translocations and inversions, in cSCC genomes. (\u003cstrong\u003eF\u003c/strong\u003e)Chromosome-level copy number variation (CNV) profiles reveal widespread genomic imbalances, with recurrent gains on chromosome 8 across tumor samples.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/3054a21c2158268bfa33ad3d.png"},{"id":109343079,"identity":"83b02f3a-684c-485b-b074-e69ca8f59938","added_by":"auto","created_at":"2026-05-15 19:39:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1480596,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic alterations and cellular heterogeneity revealed by bulk and single-cell RNA-seq in macaque cSCC. (A)\u003c/strong\u003eWorkflow of bulk and single-cell RNA-seq analysis for MSCC and ANT. \u003cstrong\u003e(B)\u003c/strong\u003eVolcano plot of differentially expressed genes between cSCC cells and control cells isolated from ANT. \u003cstrong\u003e(C)\u003c/strong\u003e Bubble plots of enriched pathways for genes upregulated (left) and downregulated (right) in cSCC cells. (\u003cstrong\u003eD\u003c/strong\u003e) Heatmap of hierarchical clustering showing the differential expression of canonical. cancer markers between the MSCC cells (MSCC-C) and control cells from ANT. (\u003cstrong\u003eE\u003c/strong\u003e) UMAP visualization of scRNA-seq data highlighting 18 major cell populations. (\u003cstrong\u003eF\u003c/strong\u003e) Heatmap of the relative proportions of cell populations in cSCC and adjacent tissues, indicating increased immune infiltration in tumors. (\u003cstrong\u003eG\u003c/strong\u003e) Bar plot of the number of overlapping differentially expressed genes (DEGs) between bulk RNA-seq and each scRNA-seq cell population. The majority of overlapping DEGs were derived from proliferating epithelial cells. (\u003cstrong\u003eH\u003c/strong\u003e) InferCNV analysis reveals large-scale chromosomal copy number variations across epithelial subpopulations, including malignant and proliferating epithelial cells. (\u003cstrong\u003eI\u003c/strong\u003e) UMAP visualization of sub-clustered proliferating epithelial cells reveals a clear separation between tumor-derived and adjacent tissue-derived subsets. (\u003cstrong\u003eJ\u003c/strong\u003e) Ridge plot of single-sample GSEA (ssGSEA) scores for the tube morphogenesis pathway. Scores were elevated in tumor-derived proliferating epithelial cells.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/83fdd4f8dde0228b792b8b06.png"},{"id":109405335,"identity":"b0ebaebc-ee35-431a-a80e-f9e988c18033","added_by":"auto","created_at":"2026-05-17 13:17:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1012986,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomics analysis revealed MYO10 as a potential driver of the cSCC tumors of macaques. (A)\u003c/strong\u003e Workflow of proteomics analysis for MSCC and matched ANT. \u003cstrong\u003e(B)\u003c/strong\u003e Volcano plot of differentially expressed proteins between cSCC and ANT. \u003cstrong\u003e(C \u003c/strong\u003eand\u003cstrong\u003e D)\u003c/strong\u003e Gene Ontology (GO) enrichment analysis of upregulated (C) and downregulated (D) proteins. Bubble size represents the number of genes per term. (\u003cstrong\u003eE\u003c/strong\u003e) Heatmap of proteins upregulated in cSCC, with roles in DNA damage repair, inflammation, and cytoskeleton regulation. (\u003cstrong\u003eF\u003c/strong\u003e) Western blot analysis of MYO10, γ-H2AX, and phospho-NF-κB p65 (S468) protein levels in cSCC and matched ANT. (\u003cstrong\u003eG-L\u003c/strong\u003e) mRNA and protein expression analyses of ATM (G and H), TLR2 (I and J) and MYO10 (K and L) in human HNSC using data from the UALCAN database.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/7c4390a385a313434c046ee9.png"},{"id":109343075,"identity":"4dbce1b6-765d-4ddf-9d55-29b7cab932ec","added_by":"auto","created_at":"2026-05-15 19:39:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":576832,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe role of the MYO10 gene in regulating genomic stability and inflammation. (A) \u003c/strong\u003eWestern blot analysis showing efficient MYO10 depletion by siRNA in cSCC cells and corresponding levels of the DNA damage marker γ-H2AX. \u003cstrong\u003e(B)\u003c/strong\u003e Densitometric quantification of γ-H2AX from (B); protein levels were normalized to β-actin. \u003cstrong\u003e(C)\u003c/strong\u003e Representative images of micronuclei in Ctrl and MYO10 knockdown cSCC cells. Micronuclei formation was significantly reduced following MYO10 depletion. (\u003cstrong\u003eD\u003c/strong\u003e) Quantification of micronuclei from (C), showing a significant reduction in micronuclei frequency following MYO10 knockdown. (\u003cstrong\u003eE-H\u003c/strong\u003e) Relative mRNA expression of \u003cem\u003eATM\u003c/em\u003e (E), \u003cem\u003eATR\u003c/em\u003e (F), \u003cem\u003eIL6\u003c/em\u003e (G) and \u003cem\u003eTNF-α\u003c/em\u003e (H) in MYO10-depleted cSCC cells measured by qPCR; expression levels are reduced upon MYO10 knockdown. (\u003cstrong\u003eI\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eWestern blot of primary normal epithelial cells following MYO10 overexpression showing increased MYO10 and γ-H2AX protein levels. (\u003cstrong\u003eJ\u003c/strong\u003e) Quantification of γ-H2AX from (\u003cstrong\u003ei\u003c/strong\u003e); values were normalized to β-actin and show increased γ-H2AX upon MYO10 overexpression. (\u003cstrong\u003eK\u003c/strong\u003e) Representative images of micronuclei in MYO10-overexpressing normal epithelial cells. (\u003cstrong\u003eL\u003c/strong\u003e) Quantification of micronuclei from (K), demonstrating an increased frequency of micronuclei after MYO10 overexpression. (\u003cstrong\u003eM \u003c/strong\u003eto \u003cstrong\u003eP\u003c/strong\u003e) qPCR analysis of \u003cem\u003eATM\u003c/em\u003e (M), \u003cem\u003eATR\u003c/em\u003e(N), \u003cem\u003eIL6\u003c/em\u003e (O) and \u003cem\u003eTNF-α\u003c/em\u003e (P) mRNA in MYO10-overexpressing normal epithelial cells, showing upregulation of these genes upon MYO10 overexpression. Data are presented as mean ± SD and significance in the figure is indicated by asterisks.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/edff3c379fcae0c83bd1d147.png"},{"id":109343114,"identity":"cc44996d-68c7-440a-a9b6-0c8577f7704f","added_by":"auto","created_at":"2026-05-15 19:40:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1040977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDrug screening and cytotoxicity assessment of candidate compounds in macaque cSCC cells. (A)\u003c/strong\u003e Comparative drug efficacy screening across six candidates (EF24, Rapamycin, ABT-263, Gemcitabine, Cisplatin, Paclitaxel) in macaque cSCC cells. Paclitaxel demonstrates the highest therapeutic index (IC\u003csub\u003e50\u003c/sub\u003e: 11 nM in cSCC cells vs. 733 nM in normal epithelial cells). n=3 biological replicates. The data presented are mean ± SD. \u003cstrong\u003e(B)\u003c/strong\u003e Comparison of drug efficacy of tested compounds between the normal epithelial cells and cSCC cells of macaque. \u003cstrong\u003e(C)\u003c/strong\u003e Flow cytometry analysis of apoptosis using Annexin V-FITC/PI staining after Paclitaxel treatment (100 nM, 24 h). (\u003cstrong\u003eD\u003c/strong\u003e) Quantification of apoptosis induction in cSCC cells after Paclitaxel treatment (100 nM, 24 h), with approximately 20% of cells undergoing apoptosis. (\u003cstrong\u003eE\u003c/strong\u003e) Western blot analysis of cleaved PARP (cPARP) and cleaved Caspase-3 (cCaspase-3) protein levels in control and Paclitaxel-treated cells. (\u003cstrong\u003eF\u003c/strong\u003e) Quantification of cPARP and cCaspase-3 expression from Western blot analysis after Paclitaxel treatment. (\u003cstrong\u003eG\u003c/strong\u003e) Flow cytometry analysis of cell cycle distribution in cSCC cells after treatment with Paclitaxel (100 nM, 24 h). (\u003cstrong\u003eH\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eQuantification of G2/M phase accumulation in cSCC cells following Paclitaxel treatment (100 nM, 24 h). (\u003cstrong\u003eI\u003c/strong\u003e) The effect of paclitaxel on the migration of cSCC cells assessed by cell scratch assay. (\u003cstrong\u003eJ\u003c/strong\u003e) Quantification of migration index from (I). Data represent mean ± SD from three independent experiments. Statistical significance was determined using Student’s t-test (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/c983118eb7e817e5d5b28dd1.png"},{"id":109405565,"identity":"b539965f-c592-4867-9da4-4086ee752edf","added_by":"auto","created_at":"2026-05-17 13:19:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1389469,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of Paclitaxel on cSCC tumor development in nude mice.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Schematic of the experimental design for the cSCC xenograft model. \u003cstrong\u003e(B)\u003c/strong\u003eMacroscopic views of xenograft tumors from mice after treatment with vehicle or paclitaxel. \u003cstrong\u003e(C)\u003c/strong\u003e Tumor volume measurements in nude mice after treatment initiation with vehicle or paclitaxel. Data are expressed as mean ± SD (n = 5 mice per group). #: p\u0026lt;0.0001. (\u003cstrong\u003eD\u003c/strong\u003e) Western blot analysis of MYO10 protein levels in nude mouse skin, cSCC cell-implanted tumors, and post-treatment tumor tissues. (\u003cstrong\u003eE\u003c/strong\u003e) Quantification of MYO10 protein levels from (D). (\u003cstrong\u003eF\u003c/strong\u003e) TUNEL assay indicates the induction of apoptosis in the cancer tissue following paclitaxel administration. Scale bar: 100 μm. (\u003cstrong\u003eG\u003c/strong\u003e) Representative H\u0026amp;E staining images across major organs of mice treated with Paclitaxel on the day of sacrifice. Scale bar: 100 μm. (\u003cstrong\u003eH\u003c/strong\u003e) Body weight of nude mice after treatment initiation with vehicle or paclitaxel. Data are expressed as mean ± SD (n = 9 mice per group). (\u003cstrong\u003eI-M\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eBlood biomarkers related to liver and kidney function following Paclitaxel treatment.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/98a384d6aa15087594fe10d8.png"},{"id":109343084,"identity":"4f776507-e098-4b16-acb2-660d5ed7b21e","added_by":"auto","created_at":"2026-05-15 19:39:50","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":818595,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of Paclitaxel on cSCC tumor development in macaque.\u003c/strong\u003e \u003cstrong\u003e(A) \u003c/strong\u003eSchematic of the experimental design for spontaneous tumor development and paclitaxel treatment. \u003cstrong\u003e(B)\u003c/strong\u003e Tumor growth curve showing a marked reduction in tumor volume following initiation of paclitaxel treatment. Data are presented as mean ± SEM (n = 6). \u003cstrong\u003e(C)\u003c/strong\u003e MRI revealed a decrease in tumor volume and the emergence of central necrosis within the lesion (yellow arrow). \u003cstrong\u003e(D-F) \u003c/strong\u003eSerum levels of IL-6 (D), TNF-α (E) and IL-10 (F) in healthy controls (Ctrl), tumor-bearing macaque before (Pre), and after paclitaxel treatment (PTX). (\u003cstrong\u003eG\u003c/strong\u003e) Biochemical parameters measured after paclitaxel treatment; key hepatic and renal markers remained within reference ranges. (\u003cstrong\u003eH\u003c/strong\u003e) TUNEL assay of tumor tissue indicating induction of apoptosis following paclitaxel administration.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/a75ad48eec7ccdd7de760008.png"},{"id":109406536,"identity":"230e25ea-5d73-4286-835a-5df88d994446","added_by":"auto","created_at":"2026-05-17 13:28:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8070733,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/718795d7-ee8b-444d-8a89-b937c2a0934b.pdf"},{"id":109343107,"identity":"64891762-f476-4d69-885f-f173b4eb2e01","added_by":"auto","created_at":"2026-05-15 19:39:53","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":5730396,"visible":true,"origin":"","legend":"","description":"","filename":"3SupplementaryMaterials2026.2.27.docx","url":"https://assets-eu.researchsquare.com/files/rs-8987244/v1/cdb831f8500b9e7b5f706b1b.docx"}],"financialInterests":"Competing interest reported. YZP, LHL, LLX, LBL and YHH are inventors on a patent for the construction and use of a Macaque cutaneous squamous cell carcinoma model. The other authors declare no competing interests.","formattedTitle":"Integrated Multi-omics Reveals Key Molecular Drivers and Therapeutic Strategies in a Spontaneous Cutaneous Squamous Cell Carcinoma Model of Macaques","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCutaneous squamous cell carcinoma (cSCC) is among the most common malignancies of the skin and a leading cause of morbidity and mortality from non-melanoma skin cancer worldwide\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. Although many cSCCs are effectively treated by local excision or radiation when detected early, a substantial subset progress to locally advanced or metastatic disease for which therapeutic options are limited and outcomes are poor\u003csup\u003e6\u003c/sup\u003e. The dominant etiologic driver for most cSCCs is ultraviolet (UV) radiation, which causes characteristic dipyrimidine DNA lesions and a high somatic mutation burden\u003csup\u003e7\u0026ndash;9\u003c/sup\u003e. This UV-driven mutagenesis, together with cumulative environmental and host factors, fuels genetic and chromosomal alterations that promote malignant transformation of epidermal keratinocytes\u003csup\u003e10,11\u003c/sup\u003e. Increasingly, it is recognized that these genomic insults do not act in isolation; rather, they interact with chronic innate and adaptive inflammatory processes and with metabolic reprogramming to create a tumor-permissive microenvironment that supports progression and therapy resistance\u003csup\u003e12\u0026ndash;16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGenomic instability is a hallmark of advanced cSCC\u003csup\u003e17\u0026ndash;19\u003c/sup\u003e. Human tumors frequently harbor high numbers of single-nucleotide variants (SNVs), small insertions and deletions (indels), copy-number alterations (CNVs), and complex structural rearrangements\u003csup\u003e20\u003c/sup\u003e. Defects in DNA-repair function amplify the mutational load. Furthermore, loss of key tumor suppressors such as \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eNOTCH1\u003c/em\u003e and gains of oncogenes, including \u003cem\u003eMYC\u003c/em\u003e and \u003cem\u003eKRAS\u003c/em\u003e, recur in advanced disease\u003csup\u003e21,22\u003c/sup\u003e. At the same time, chronic inflammation \u0026mdash; driven by nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation, cytokine secretion, and immune cell infiltration \u0026mdash; shapes tumor evolution\u003csup\u003e23\u0026ndash;25\u003c/sup\u003e. Inflammatory mediators can promote proliferation, survival, angiogenesis, and local immunosuppression, and they can exacerbate genomic instability by inducing reactive oxygen species and perturbing DNA-damage responses\u003csup\u003e26\u003c/sup\u003e. Therefore, these intersecting axes of genome damage and inflammation represent both fundamental mechanisms of cSCC pathogenesis and candidate targets for therapeutic intervention.\u003c/p\u003e \u003cp\u003ePreclinical modeling is essential for dissecting these complex, interacting processes and for testing candidate treatments. Rodent models have provided valuable mechanistic insights, but important biological differences limit their translational fidelity for human cSCC\u003csup\u003e27\u0026ndash;30\u003c/sup\u003e. Rodent skin architecture, hair density, immune composition, and DNA-repair kinetics differ from those of humans. Moreover, many genetically engineered and chemically induced murine models fail to recapitulate the full spectrum of genomic complexity, immune microenvironment remodeling, and treatment responses characteristic of aggressive human cSCC\u003csup\u003e2,31\u0026ndash;33\u003c/sup\u003e. Non-human primates share greater genetic, anatomical, and immunologic similarity with humans and therefore offer an attractive but underused platform for modeling spontaneous human-like cancers\u003csup\u003e30,34\u003c/sup\u003e. Spontaneous tumors that arise in primate colonies capture natural etiologic exposures and host-tumor interactions that are difficult to reproduce artificially, potentially yielding a more faithful substrate for mechanistic studies and translational testing.\u003c/p\u003e \u003cp\u003eDespite this promise, spontaneous non-human primate tumor models remain rarely characterized at scale with modern molecular tools. Comprehensive profiling of spontaneous primate cSCCs using integrated genomics, transcriptomics, proteomics, and single-cell resolution techniques could reveal conserved disease drivers that are obscured in simplified models, identify candidate therapeutic targets, and enable rigorous preclinical evaluation of therapies in a biologically relevant context. Such work would also have practical benefits for veterinary care and colony management by improving the detection and treatment of spontaneous neoplasms.\u003c/p\u003e \u003cp\u003eAgainst this backdrop, we investigated a cohort of spontaneous, lethal cSCCs identified in a captive macaque population. These tumors presented with clinical and histopathologic hallmarks of human cSCC, including well-differentiated squamous morphology and expression of canonical squamous lineage markers. We applied whole-genome sequencing to define mutational spectra and structural variation, bulk and single-cell RNA sequencing to resolve transcriptional programs and cellular composition, and quantitative proteomics to capture translational and metabolic changes. These multi-omics layers were integrated to map pathways linking genomic lesions to inflammatory activation and metabolic reprogramming. To probe causality, we performed targeted functional perturbations in primary and tumor-derived epithelial cells. Finally, we evaluated therapeutic vulnerabilities using drug screening, in vitro assays of mechanism, murine xenografts for in vivo efficacy and tolerability, and compassionate treatment of a macaque bearing spontaneous tumors to assess real-world activity and systemic effects.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eCharacterization of a spontaneous cSCC in captive macaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong a captive colony of 2,752 macaques, five animals developed cSCC, corresponding to an incidence of 2,575.66 per million (Table S1). Tumors arose predominantly on sun-exposed skin, implicating a possible role for UV exposure. Age-adjusted incidence was higher in females than in males (1931.75 vs. 834.03 per million; Fig. 1A). Affected animals exhibited rapid clinical decline, with survival times of 44–241 days, and spanned a range of human-equivalent ages from 28 to 59.5 years (Table S2)\u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHistopathological evaluation demonstrated well-differentiated cSCC characterized by invasive epithelial nests, prominent keratin pearls, and stromal inflammatory infiltrates—features that closely parallel human cSCC (Fig. 1B; Fig. S1A). Immunohistochemistry showed strong nuclear p63 (basal progenitor marker) and cytoplasmic cytokeratin 5/6 (CK5/6) expression with markedly elevated Ki-67 indices, consistent with a proliferative squamous epithelial phenotype and arguing against a mesenchymal origin (Fig. 1C).\u003c/p\u003e\n\u003cp\u003ePrimary tumor epithelial cells were isolated and purified for downstream molecular analysis (Fig. S1B). The established cSCC cell lines maintained stable proliferative capacity in culture (Fig. S1C) and remained mycoplasma-negative across passages (Fig. S1D). Comparative imaging of primary epithelial cells and purified tumor cultures confirmed exclusion of fibroblast contamination: tumor cells retained CK expression but lacked Vimentin (Fig. 1D). Cytogenetic analysis of 108 metaphase spreads revealed chromosome counts ranging from 47 to 98, consistent with marked chromosomal instability (Fig. 1, E and F; Fig. S1E).\u003c/p\u003e\n\u003cp\u003eImmunofluorescence further confirmed robust expression of CK5/6, Ki-67, and Squamous Cell Carcinoma Antigen 1 (SCCA1) in macaque tumor epithelial cells, with no detectable Vimentin—an expression profile typical of squamous carcinoma cells. By contrast, macaque skin fibroblasts were Vimentin-positive and negative for CK and SCCA1, while normal macaque epithelial cells showed moderate CK expression but lacked SCCA1 and Vimentin. The macaque tumor epithelial immunophenotype closely resembled that of human cSCC epithelial cells, supporting their epithelial origin and the translational relevance of this spontaneous macaque cSCC model (Fig. 1G).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenomic landscape of cSCC tumors in macaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaryotypic analysis revealed markedly abnormal chromosomal patterns in macaque cSCC samples, suggesting that extensive genomic instability accompanies tumorigenesis\u003csup\u003e36\u003c/sup\u003e. To characterize these alterations in detail, we performed whole-genome sequencing (WGS) on four pairs of macaque cSCC tissues (MSCC) and ANT (Fig. 2A). Analysis of somatic single-nucleotide variants (SNVs) showed a substantially higher mutation burden in tumor samples compared to their matched normal counterparts (Fig. 2B). Notably, several chromosomal regions exhibited elevated mutation frequencies across all four tumors, indicating potential mutational hotspots in macaque cSCC. Recurrent mutations were identified in key cancer-related genes, including \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eRB1\u003c/em\u003e, \u003cem\u003eAKT2\u003c/em\u003e, \u003cem\u003eCDH1\u003c/em\u003e, and \u003cem\u003eMYO10\u003c/em\u003e (Fig. 2C), suggesting their potential involvement in cSCC pathogenesis\u003csup\u003e8\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe next analyzed the mutational spectrum of macaque cSCC. Among the six major substitution types, C\u0026gt;T transitions were the most prevalent (Fig. 2D), consistent with mutational signatures commonly observed in human cSCC\u003csup\u003e7\u003c/sup\u003e. Given the markedly altered karyotypes, we further investigated large-scale structural variations (SVs). All four tumor samples exhibited numerous chromosomal translocations, corroborating the cytogenetic observations (Fig. 2E; Fig. S2, A to C). Copy number variation (CNV) analysis further demonstrated widespread genomic imbalances (Fig. 2F; Fig. S2, D to F). Particularly, Chromosome 8 showed recurrent copy number gains across all tumor samples. This specific translocation pattern aligns with findings in human cSCC, where 3p losses (e.g., \u003cem\u003eTP53\u003c/em\u003e locus) and 8q gains (e.g., \u003cem\u003eMYC\u003c/em\u003e gene) are associated with advanced disease\u003csup\u003e37-39\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCollectively, these findings demonstrate that macaque cSCC is characterized by extensive genomic instability, involving a high somatic mutation burden, recurrent structural variations, and widespread copy number alterations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBulk and single-cell transcriptomic profiling identifies malignant epithelial populations driving transcriptional alterations in macaque cSCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the transcriptional changes underlying macaque cSCC, we conducted bulk RNA-sequencing on cells isolated from tumor tissues and matched ANT (Fig. 3A). Differential expression analysis identified pronounced transcriptional alterations in tumors (Fig. 3B). Pathway enrichment analysis revealed significant enrichment of upregulated genes (e.g., \u003cem\u003eMYCN\u003c/em\u003e, \u003cem\u003eBCL2\u003c/em\u003e, \u003cem\u003eE2F1\u003c/em\u003e, \u003cem\u003eE2F2\u003c/em\u003e, \u003cem\u003eE2F8\u003c/em\u003e, and \u003cem\u003eAKT1\u003c/em\u003e) associated with cell cycle regulation, cytoskeleton organization, and canonical oncogenic signaling. Conversely, downregulated genes (e.g., \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eCDKN1A\u003c/em\u003e, \u003cem\u003eCDKN2B\u003c/em\u003e, \u003cem\u003eBAX\u003c/em\u003e, \u003cem\u003eMCL1\u003c/em\u003e, \u003cem\u003eDAPK1\u003c/em\u003e, and \u003cem\u003eBID\u003c/em\u003e) were associated with lysosomal function, cell adhesion, apoptosis, and peroxisomal activity (Fig. 3, C and D). These findings collectively indicate a profound reprogramming of transcriptional networks during cSCC pathogenesis, characterized by the activation of pro-proliferative and anti-apoptotic programs.\u003c/p\u003e\n\u003cp\u003eTo characterize cellular compositions in cSCC, we performed single-cell RNA sequencing (scRNA-seq) on tumor tissues and matched ANT. Following quality control, 25,233 high-quality cells were retained for downstream analysis and visualized via Uniform Manifold Approximation and Projection (UMAP). Unsupervised clustering guided by canonical lineage markers identified 18 distinct cell populations spanning immune (e.g., T cells, monocytes, macrophages), stromal, and epithelial lineages (Fig. 3E and Fig. S3). Comparative analysis of cell-type proportions revealed significantly increased infiltration of immune populations in tumors, indicative of an active tumor immune microenvironment (Fig. 3F). Critically, we identified both a distinct cluster of malignant epithelial cells and a proliferating epithelial subset characterized by high proliferative activity, which may drive malignant expansion. Integration of bulk RNA-seq and scRNA-seq differential expression results confirmed that proliferating epithelial cells were the primary drivers of transcriptional divergence between tumor and adjacent tissues (Fig. 3G).\u003c/p\u003e\n\u003cp\u003eTo further assess the malignant potential of epithelial subsets, we applied inferCNV to infer large-scale chromosomal alterations. Malignant epithelial cells exhibited extensive copy number changes, including alterations on chromosomes 1, 7, and 8. Notably, a subset of proliferating epithelial cells also displayed pronounced copy number variations, supporting their malignant nature\u0026nbsp;(Fig. 3H). Sub-clustering of proliferating epithelial cells revealed clear segregation between tumor- and adjacent tissue-derived subsets, highlighting their distinct transcriptional states\u0026nbsp;(Fig. 3I).\u003c/p\u003e\n\u003cp\u003eFunctional enrichment analysis of tumor-derived proliferating epithelial cells demonstrated significant upregulation of the tube morphogenesis pathway (Fig. 3J), suggesting a potential role in tumor progression. Together, these findings indicate that transcriptional alterations in macaque cSCC are largely driven by proliferating epithelial cells, a subset of which acquires malignant genomic features, underscoring their potential importance in cSCC biology and as targets for therapeutic intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProteomic profiling revealed MYO10 as a potential driver of macaque cSCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate molecular drivers of macaque cSCC, we performed quantitative proteomic profiling of tumor tissues and matched ANT (Fig. 4A). This analysis identified extensive protein-level alterations (Fig. 4B), characterized by pronounced upregulation of DNA damage repair factors\u0026nbsp;(e.g., ATM, APOBEC3A), inflammatory mediators (e.g., IL36A, CGAS), and cytoskeletal regulation—most notably MYO10, a protein previously implicated in genomic instability modulation and inflammatory pathway activation\u003csup\u003e40\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFunctional annotation of upregulated proteins highlighted significant enrichment in RNA processing pathways (Fig. 4C), a hallmark previously reported in human squamous carcinomas such as HPV-negative head and neck SCC\u003csup\u003e41\u003c/sup\u003e, suggesting conserved post-transcriptional reprogramming in cSCC pathogenesis. By contrast, mitochondrial oxidative phosphorylation components were systematically downregulated (Fig. 4D), aligning with metabolic rewiring toward aerobic glycolysis (Fig. S4). Unsupervised clustering confirmed coordinated overexpression of DNA damage response, inflammatory, and cytoskeletal regulatory proteins in tumors (Fig. 4E).\u003c/p\u003e\n\u003cp\u003eWestern blot analysis validated the proteomic findings, demonstrating elevated expression of MYO10, γ-H2AX (a marker of DNA double-strand breaks), and phosphorylated NF-κB p65 (Ser468) in macaque cSCC tissues relative to matched adjacent samples (Fig. 4F). This indicates a distinct state of NF-κB pathway regulation in tumors, which is associated with the observed inflammatory microenvironment.\u003c/p\u003e\n\u003cp\u003eTo assess the clinical relevance, we analyzed human head and neck squamous cell carcinoma (HNSC) data from the UALCAN database\u003csup\u003e42\u003c/sup\u003e. \u003cem\u003eATM\u003c/em\u003e, \u003cem\u003eTLR2\u003c/em\u003e, and \u003cem\u003eMYO10\u0026nbsp;\u003c/em\u003eexhibited significantly elevated expression in human HNSC tissues compared to normal controls (Fig. 4, G to L), with higher expression correlating with advanced tumor stage—supporting their roles in human squamous carcinogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMYO10 contributes to tumorigenesis via regulating genomic instability and inflammation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntegrated analysis of whole-exome sequencing, RNA-seq, and proteomic profiling of macaque cSCC tissues from cynomolgus macaques consistently identified \u003cem\u003eMYO10\u003c/em\u003e (myosin-X) as a candidate gene of interest. Somatic mutations in MYO10 were detected in 3 out of 4 tumor samples (Fig. 2C), suggesting potential functional consequences. Moreover, proteomic data demonstrated robust upregulation of \u003cem\u003eMYO10\u0026nbsp;\u003c/em\u003ein tumor tissues compared to ANT (Fig. 4B and F).\u003c/p\u003e\n\u003cp\u003eTo assess the clinical relevance of this finding, we analyzed \u003cem\u003eMYO10\u0026nbsp;\u003c/em\u003eexpression across human datasets from The Cancer Genome Atlas (TCGA). \u003cem\u003eMYO10\u003c/em\u003e was significantly upregulated in human HNSC tissues relative to ANT (Fig. 4, K and L). Furthermore, elevated \u003cem\u003eMYO10\u0026nbsp;\u003c/em\u003eexpression positively correlates with advanced tumor stage (Fig. S5A) and nodal metastasis status in HNSC (Fig. S5B), suggesting a potential role in HNSC cancer progression.\u003c/p\u003e\n\u003cp\u003eThe consistent upregulation of \u003cem\u003eMYO10\u003c/em\u003e in tumor tissues and its correlation with advanced disease in human datasets supported the hypothesis that \u003cem\u003eMYO10\u003c/em\u003e may be functionally involved in the regulation of genomic stability and inflammation, two processes prominently altered in our multi-omics data. To investigate this, we performed functional assays involving \u003cem\u003eMYO10\u0026nbsp;\u003c/em\u003eknockdown and overexpression in macaque-derived cSCC cells and primary epithelial cells, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnockdown of MYO10 reduces DNA damage and inflammatory signaling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine the role of \u003cem\u003eMYO10\u003c/em\u003e in tumor cells, we silenced its expression in cSCC cells using siRNA. Efficient knockdown was confirmed by Western blot (Fig. 5A). Following MYO10 silencing, Western blot analysis revealed reduced expression of γ-H2AX, a well-established marker of DNA double-strand breaks (Fig. 5, A and B). In parallel, we observed a significant decrease in the number of micronuclei (Fig. 5, C and D), a hallmark of genomic instability. Meanwhile, quantitative PCR analysis showed decreased expression of key DNA damage response genes, including \u003cem\u003eATM\u003c/em\u003e and \u003cem\u003eATR\u003c/em\u003e, upon MYO10 knockdown (Fig. 5, E and F). Inflammatory cytokine expression, specifically \u003cem\u003eIL6\u003c/em\u003e and \u003cem\u003eTNF-α\u003c/em\u003e, was also significantly suppressed (Fig. 5, G and H), aligning with the inflammatory transcriptomic signature observed in the tumor tissues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMYO10 drives a pro-tumorigenic cascade spanning epithelial and stromal compartments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess whether MYO10 is sufficient to induce DNA damage and inflammatory signaling, we ectopically expressed it in primary epithelial cells from healthy macaque oral mucosa. Western blot analysis confirmed successful overexpression and further revealed that MYO10 levels were substantially higher in tumor-derived epithelial cells than in normal controls (Fig. 5I). Upon MYO10 overexpression, γ-H2AX levels were markedly elevated, indicating increased DNA damage (Fig. 5J). Enforced expression of MYO10 led to a significant increase in the number of micronuclei (Fig. 5K and L), mirroring the phenotype observed in tumor cells. Quantitative PCR further demonstrated upregulated ATM and ATR mRNA levels (Fig. 5M, N), consistent with enhanced transcription of inflammatory mediators IL6 and TNF-α (Fig. 5O, P). Having established MYO10's role in driving genomic instability and inflammation within epithelial cells, we next explored its potential to remodel the skin tumor microenvironment. Strikingly, overexpression of MYO10 in human dermal fibroblasts (HDF) significantly enhanced their proliferation and induced prominent colony formation (Fig. S5C and D), demonstrating its capacity to confer transformation-associated phenotypes upon stromal cells. Collectively, these data establish MYO10 as a multi-faceted oncoprotein that drives cSCC development through integrated mechanisms: intrinsically compromising genomic integrity and fueling inflammation within keratinocytes, while extrinsically coercing dermal fibroblasts into a pro-tumorigenic state.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrug screening and cytotoxicity assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on prior transcriptomic and genomic analyses, which identified genomic instability, dysregulated cell cycle progression, and chronic inflammation as key features of cSCC in macaques, six candidate drugs were selected for testing their anticancer efficacy, including paclitaxel (microtubule-stabilizing agent)\u003csup\u003e43\u003c/sup\u003e, Gemcitabine (nucleoside analoge)\u003csup\u003e44\u003c/sup\u003e, EF24 (curcumin analog with antioxidant and anti-inflammatory properties)\u003csup\u003e45\u003c/sup\u003e, Rapamycin (mTOR inhibitor)\u003csup\u003e46\u003c/sup\u003e, ABT263 (Bcl-2 family inhibitor)\u003csup\u003e47\u003c/sup\u003e, and Cisplatin (DNA crosslinking agent)\u003csup\u003e48\u003c/sup\u003e. Cytotoxicity was assessed in cSCC cells and normal epithelial cells of macaque by determining the half-maximal inhibitory concentration (IC\u003csub\u003e50\u003c/sub\u003e). Among the compounds tested, paclitaxel exhibited the most potent cytotoxic effect against cSCC cells, with an IC\u003csub\u003e50\u003c/sub\u003e of 0.011 μM (Fig. 6A, left panel). Other compounds, such as Gemcitabine (0.035 μM) and EF24 (0.843 μM), demonstrated moderate potency, whereas ABT263 (1.086 μM), Cisplatin (1.46 μM), and Rapamycin (3.204 μM) exhibited comparatively lower effectiveness. Although Gemcitabine and EF24 exhibited relatively low IC\u003csub\u003e50\u003c/sub\u003e values and are typically associated with reduced toxicity to normal cells (Fig. 6A, right pannel), paclitaxel demonstrated the most favorable balance between efficacy and selectivity (Fig. 6B). It effectively killed tumor cells while exhibiting minimal toxicity to normal epithelial cells. These findings suggest that paclitaxel possesses the highest therapeutic index among the drugs tested, making it a promising candidate for further clinical development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaclitaxel induced apoptosis, cell cycle arrest and migration inhibition in cSCC cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the mechanisms by which paclitaxel exerts its anticancer effects in cSCC cells, we performed flow cytometry and Western blot analyses to assess apoptosis and cell cycle progression. Flow cytometry analysis revealed that treatment with paclitaxel (100 nM, 24 h) induced apoptosis in approximately 20% of cSCC cells (Fig. 6, C and D). This pro-apoptotic effect was further supported by Western blot analysis, which showed increased levels of cleaved PARP (cPARP) and cleaved Caspase-3 (cCaspase-3), indicating activation of the intrinsic apoptotic pathway (Fig. 6, E and F). In addition, flow cytometry analysis of cell cycle distribution demonstrated a marked accumulation of cells in the G2/M phase following paclitaxel treatment (Fig. 6, G and H), consistent with mitotic arrest due to microtubule stabilization and impaired spindle formation\u003csup\u003e43\u003c/sup\u003e. We also assessed the effect of paclitaxel on cell migration using a cell scratch assay, which revealed a significant inhibition of cSCC cell migration (Fig. 6,I and J). These results highlight the dual mechanism of paclitaxel in inducing apoptosis and cell cycle arrest in cSCC cells, contributing to its potent anticancer activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vivo efficacy and safety of paclitaxel in a cSCC xenograft model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the therapeutic potential of paclitaxel in vivo, we established a xenograft model through subcutaneous inoculation of macaque-derived cSCC cells into immunodeficient nude mice (Fig. 7A). Successful tumor engraftment was confirmed by histopathological analysis, which revealed that the xenografts retained a well-differentiated squamous cell carcinoma morphology (including invasive nests and keratin pearls; Fig. S6A, arrow) consistent with the original phenotype, and by immunohistochemistry, which demonstrated positive expression of cSCC markers p63, CK5/6, and Ki-67 (Fig. S6B). This model thus provides a robust platform for evaluating the antitumor efficacy and systemic safety of candidate therapeutics in vivo.\u003c/p\u003e\n\u003cp\u003eBased on previously published studies\u003csup\u003e49-51\u003c/sup\u003e, we chose a low-dose, high-frequency dosing regimen for paclitaxel administration, delivering 5 mg/kg via slow intravenous injection every three days. This approach was selected to balance therapeutic efficacy with minimizing toxicity. Macroscopic examination of excised tumors from the paclitaxel-treated group showed a notable reduction in tumor size compared to vehicle-treated controls (Fig. 7B and Fig. S7A). Paclitaxel treatment resulted in a significant reduction in tumor volume by 89.4% (p \u0026lt; 0.001; Fig. 7C). We further examined the expression of MYO10, a candidate cSCC driver identified in our multi-omics analyses. Western blot analysis showed that MYO10 protein levels were markedly elevated in cSCC xenograft tumors compared to normal nude mouse skin, and were substantially reduced following paclitaxel treatment (Fig. 7D, E), suggesting that paclitaxel may suppress tumor growth partly through downregulating MYO10. TUNEL assay also demonstrated significant induction of apoptosis in paclitaxel-treated tumors (Fig. 7F).\u003c/p\u003e\n\u003cp\u003eDespite inducing extensive tumor regression, paclitaxel treatment did not affect histopathological alterations in major organs (heart, liver, spleen, lung, and kidney) (Fig. 7G). Furthermore, no significant differences in body weight were observed between paclitaxel- and vehicle-treated mice (Fig. 7H). Blood parameters, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CRE2), blood urea nitrogen (BUN), and creatine kinase (CK), remained within normal ranges post-treatment (Fig. 7, I to M). Additionally, organ weights showed no notable changes (Fig. S7B), and all hematological parameters remained within normal physiological ranges (Fig. S7, C to L). These findings collectively demonstrate that paclitaxel has a favorable safety profile in vivo, supporting its potential for clinical translation in cSCC therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntitumor efficacy and safety of a paclitaxel formulation in macaque with spontaneous cSCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the therapeutic potential of paclitaxel against spontaneously arising cSCC, cSCC bearing macaque was treated and monitored for changes in tumor progression and systemic inflammation (Fig. 8A). Paclitaxel administration induced a significant reduction in tumor volume, with a mean reduction of 86.6 ± 10.1% relative to baseline (p \u0026lt; 0.001; n = 6 tumors in one macaque) (Fig. 8B). MRI evaluation confirmed a decrease in tumor dimensions accompanied by central necrosis, consistent with paclitaxel-induced mitotic catastrophe (Fig. 8C, yellow arrow).\u003c/p\u003e\n\u003cp\u003eELISA assay revealed significant reductions in pro-inflammatory cytokines IL-6 and TNF-α following paclitaxel treatment, indicating attenuation of systemic inflammation associated with tumor burden (Fig. 8, D and E). Concurrently, an increase in the anti-inflammatory cytokine IL-10 was observed post-treatment (Fig. 8F), suggesting a concomitant activation of compensatory anti-inflammatory mechanisms. Before intervention, the macaque exhibited notable weight loss (Fig. S8A) and elevated pro-inflammatory cytokine levels (Fig. 8,D and E), suggestive of cancer-associated cachexia\u003csup\u003e12\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNo significant alterations in body temperature (Fig. S8B) or severe hematologic toxicity were observed (Fig. 8G). Cardiovascular parameters remained stable throughout treatment (Fig. S8C), and serum creatine kinase levels, despite mild elevation, were maintained within the normal physiological range (Fig. S8D). All hematological indices also remained within normal limits (Fig. S8,E and F).\u003c/p\u003e\n\u003cp\u003eApoptotic activity was significantly enhanced in tumor tissues following paclitaxel treatment, as evidenced by TUNEL staining (Fig. 8H). Together, these findings demonstrate that paclitaxel effectively induces tumor regression and apoptosis while modulating systemic inflammatory responses, with a favorable safety profile in this spontaneous non-human primate model of cSCC.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we present a comprehensive molecular characterization of spontaneous, lethal cSCC in macaques, integrating genomics, transcriptomics, single-cell profiling, proteomics, and functional perturbation. Our data reveal a disease program driven by extensive genomic instability and chronic innate inflammatory activation, nominate MYO10 as a previously unrecognized mediator that links these processes, and demonstrate that paclitaxel produces profound antitumor effects with an acceptable tolerability profile in both xenograft and spontaneous-tumor settings. These findings establish this spontaneous macaque cSCC as a translationally relevant model that recapitulates key molecular and phenotypic hallmarks of human disease.\u003c/p\u003e \u003cp\u003eThe genomic features of macaque cSCC closely resemble those observed in UV-induced human cSCC\u003csup\u003e7\u003c/sup\u003e. Whole-genome sequencing revealed a high mutational burden dominated by C\u0026thinsp;\u0026gt;\u0026thinsp;T transitions, widespread chromosomal instability, and recurrent structural variations such as chromosome 3p-8q translocations\u0026mdash;a pattern strongly associated with UV damage\u003csup\u003e7,9,36\u003c/sup\u003e. Furthermore, copy number alterations in key genes, including \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eNOTCH1\u003c/em\u003e, \u003cem\u003eKRAS\u003c/em\u003e, and \u003cem\u003eMYC\u003c/em\u003e, reinforce the relevance of these tumors to advanced human cSCC\u003csup\u003e2,36\u003c/sup\u003e. These genomic parallels suggest shared etiological mechanisms between species and provide a compelling foundation for using this model to explore conserved disease drivers.\u003c/p\u003e \u003cp\u003eBeyond genomic alterations, multi-omics profiling uncovered significant inflammatory activation, marked by upregulation of NF-κB signaling, pro-inflammatory cytokines (e.g., IL6, TNFα), and immune cell infiltration\u0026mdash;including a distinct CD19\u003csup\u003e+\u003c/sup\u003e B-cell cluster comprising 18% of tumor-infiltrating cells. This immune-rich microenvironment recapitulates the chronic inflammation commonly observed in human cSCC, where it contributes to tumor progression and immune evasion\u003csup\u003e52,53\u003c/sup\u003e. The presence of an inflammatory \"field effect\" in histologically normal adjacent tissue further underscores the physiological relevance of this model, as it recapitulates a recognized feature of human field cancerization\u003csup\u003e13,16,54\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA key finding of our study is the identification of MYO10 overexpression within macaque cSCC tumors, where it appears to functionally link genomic instability and inflammatory signaling\u003csup\u003e40\u003c/sup\u003e. We consistently observed significant upregulation of MYO10 in tumor tissues from macaques, similar to the situation in humans, where elevated MYO10 expression correlates with advanced tumor stage. Using perturbation experiments, we demonstrated that MYO10 drives DNA damage (increased γ-H2AX and micronuclei) and inflammatory activation (elevated IL6 and TNFα) independent of cellular proliferation. These results suggest that \u003cem\u003eMYO10\u003c/em\u003e may act as a novel oncogene in cSCC pathogenesis, possibly acting through regulation of cytoskeletal remodeling or cGAS-STING signaling\u003csup\u003e40,55,56\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe translational potential of this model was further highlighted by the efficacy of paclitaxel, which induced significant tumor regression in both xenotransplant and spontaneous tumor settings. Its potent anti-tumor activity (IC\u003csub\u003e50\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;11 nM in vitro, \u0026gt;\u0026thinsp;89% inhibition in vivo) likely stems from dual targeting of mitotically active cells and the inflammatory microenvironment, as evidenced by reduced IL-6 and TNFα levels post-treatment. Importantly, treatment was initiated in a macaque presenting with multifocal tumors and tumor-associated cachexia\u003csup\u003e12\u003c/sup\u003e, yet still achieved profound tumor reduction (86.6%) with minimal toxicity\u0026mdash;supporting the model\u0026rsquo;s utility for evaluating therapies under clinically relevant conditions.\u003c/p\u003e \u003cp\u003eSeveral limitations merit consideration. The aggressive nature of these spontaneous tumors, coupled with their late-stage presentation, may limit the generalizability of findings to early-stage disease. Additionally, while we establish MYO10 overexpression as a functional contributor to genomic instability and inflammation, its precise molecular mechanisms remain incompletely elucidated. For instance, further mechanistic studies are needed to define the exact pathways involved. The current lack of MYO10-targeting agents also precludes immediate clinical translation, highlighting a need for future drug development efforts.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, this work delineates the molecular landscape of spontaneous macaque cSCC, emphasizing the interplay between genomic instability and inflammation and nominating MYO10 as a key regulator of this process. The model faithfully recapitulates human cSCC that are poorly reproduced in rodents\u0026mdash;including genomic complexity, immune microenvironment, and therapeutic response\u0026mdash;making it a valuable platform for both mechanistic studies and preclinical evaluation. Beyond advancing cSCC research, these findings may also pave the way for managing spontaneous tumors in non-human primate colonies, contributing to both biomedical science and animal welfare.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCell lines and culture\u003c/h2\u003e \u003cp\u003ePrimary tumor specimens were processed by enzymatic digestion and tissue-block culture to establish primary cSCC cell cultures. Primary cultures were purified by repeated differential adhesion and trypsinization to deplete fibroblast-like cells, yielding a predominantly epithelial population (purity\u0026thinsp;\u0026gt;\u0026thinsp;95%). Other cell lines used in this study were obtained from the Conservation Genetics CAS Kunming Cell Bank (Kunming, China). Cells were maintained in either Pneu medium (STEMCELL Technologies, Vancouver, Canada; Cat. #05001) supplemented with 1% penicillin\u0026ndash;streptomycin (Gibco, Rockville, MD, USA; Cat. #15140-122), 5% fetal bovine serum (Royacel Biotechnology Co., Ltd., Lanzhou, China; Cat. #RY-F22), 1% L-glutamine (Solarbio Biotech, Beijing, China; Cat. #G0200), 0.1% hydrocortisone (Rongsheng Pharmaceutical Co., Ltd., China; NDA No. H20023069), and 2% growth factor additives (STEMCELL Technologies; Cat. #05042), or in DMEM/F-12 (Gibco; Cat. #11320033) supplemented with 1% penicillin\u0026ndash;streptomycin and 10% fetal bovine serum. All cultures were maintained at 37\u0026deg;C in a humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e. Cell lines were routinely screened for mycoplasma contamination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eTransfection of plasmids and siRNA\u003c/h2\u003e \u003cp\u003eThe MYO10 overexpression plasmids (in the pcDNA3.1 vector) were designed and constructed by YouBio (Changsha, China). When the cells reached approximately 80% confluence, the MYO10 overexpression plasmids related control plasmids were transfected into the indicated cells using Lipofectamine 3000 (Invitrogen, USA; Cat. #L3000015) according to the manufacturer's protocol. For MYO10 knockdown, all siRNAs were designed and synthesized by Sangon Biotech (Shanghai, China). All siRNAs were transfected into the indicated cells using Lipofectamine RNAiMAX (Invitrogen, USA; Cat. #13778150) following the manufacturer's instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCell growth curve\u003c/h2\u003e \u003cp\u003eMacaque cSCC cells at various passages were trypsinized and seeded in 24-well plates at a density of 1 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells per well. After allowing cells to adhere, three wells were sampled each day and cell concentration was determined using a CytoCubeAuto fully automatic, portable, high-throughput cell counter (Newtonoptic, China). The mean value from the triplicate wells was recorded as the cell count for that day. Daily measurements were continued until cultures reached the plateau (stationary) phase; medium in the remaining wells was refreshed regularly to maintain optimal growth. A growth curve was generated with time (days) on the x-axis and daily cell count on the y-axis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eCell migration assay\u003c/h2\u003e \u003cp\u003eMacaque cSCC cells were seeded in 6-well plates at a density of 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/well and cultured until they reached confluence (~\u0026thinsp;24 h). A linear scratch was made using a sterile 200 \u0026micro;L pipette tip; debris was removed by washing with DPBS and wells were replenished with fresh complete medium. The experimental group was then incubated with complete medium containing 0.1 \u0026micro;M paclitaxel for 24 h, while the control group received complete medium alone. Images were captured using an optical microscope (Leica, Germany) at 0 and 24 h. The extent of cell migration index (%) was quantified using ImageJ software, and was calculated as follows:\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"397\" height=\"69\"\u003e\u003c/p\u003e\u003cp\u003ewhere A0 is the scratch area at 0 h and A is the scratch area at 24 h.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eCell viability assay\u003c/h2\u003e \u003cp\u003eCells (3 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e per well) were seeded in 96-well plates in 100 \u0026micro;L of 1\u0026times; Pneu medium supplemented with 1% penicillin\u0026ndash;streptomycin (Gibco; Cat. #15140-122), 5% fetal bovine serum (Royacel; Cat. #RY-F22), 1% L-glutamine (Solarbio; Cat. #G0200), hydrocortisone (1:1,000), and 2% growth factor additives. After 24 h, medium was replaced with 0.2 mL of the same medium containing the indicated concentrations of test compounds, and cells were incubated at 37\u0026deg;C for three days. Viability was assessed using the CellTiter-Glo Luminescent Cell Viability Assay (Promega; Cat. #G1111) according to the manufacturer\u0026rsquo;s instructions. Dose\u0026ndash;response curves were generated and half-maximal inhibitory concentrations (IC\u003csub\u003e50\u003c/sub\u003e) were calculated using GraphPad Prism v9.0.2 (GraphPad Software, San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eCell apoptosis assay\u003c/h2\u003e \u003cp\u003eThe cSCC cells were seeded in 6-well plates at 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per well and incubated with vehicle (VEH) or 100 nM paclitaxel at 37\u0026deg;C for 24 h. Cells were then harvested into polystyrene round-bottom tubes (Falcon; Cat. #352058) and stained with Alexa Fluor 647-conjugated Annexin V (1:60; BioLegend; Cat. #640912) and propidium iodide (1:60; eBioscience; Cat. #00-6990) for 30 min at room temperature in the dark. Apoptosis was quantified by flow cytometry (BD LSRFortessa, USA).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCell cycle assay\u003c/h2\u003e \u003cp\u003eFor cell-cycle analysis, cSCC cells were seeded in 6-well plates at 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per well and treated with 100 nM paclitaxel for 48 h. After treatment, cells were harvested, washed twice with DPBS and fixed in 70% ethanol at 4\u0026deg;C overnight. Fixed cells were washed with DPBS and stained with propidium iodide (KeyGEN Biotech, Jiangsu, China; Cat. #KGA511) for 30 min at room temperature. Cell-cycle phase distribution was determined using flow cytometry (BD LSRFortessa, USA).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative Real-Time PCR (qPCR) experiments\u003c/h2\u003e \u003cp\u003eQuantitative real-time PCR (qPCR) was performed to evaluate the expression level of SASP (senescence-associated secretory phenotype) genes in the indicated cells or tissues. Total RNA was extracted from cells or tissues using TRIzol reagent (Thermo Fisher Scientific, USA; Cat. #15596018) according to the manufacturer's protocol. The RNA purity and concentration were assessed spectrophotometrically. For cDNA synthesis, a reverse transcription (RT) kit (Thermo Fisher Scientific, USA; Cat. #K1622) was used following the manufacturer's instructions. qPCR was then performed to quantify the expression of target genes using specific primers for SASP genes, and β-actin (internal control), along with SYBR Green master mix (2x Master qPCR Mix TSE201, Tsingke\u0026reg;, Beijing, China). The qPCR primers used in this study are listed in Table S3. The relative mRNA expression levels were determined using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eWestern blot assay\u003c/h2\u003e \u003cp\u003eAfter treatment, cells were washed with DPBS and lysed in 100 \u0026micro;L ice-cold RIPA buffer with EDTA and EGTA (Boston BioProducts; Cat. #BP-115DG). Lysates were collected into ice-cold tubes, incubated on ice for 30 min and centrifuged at 15,000 \u0026times; g for 15 min at 4\u0026deg;C. Supernatants were transferred to fresh tubes, flash-frozen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. Protein concentration was measured with a BCA Protein Assay Kit (Beyotime; Cat. #P0010). Lysates were mixed with one-quarter volume of 4\u0026times; Laemmli sample buffer (Bio-Rad; Cat. #1610747) containing 5% β-mercaptoethanol, heated at 95\u0026deg;C for 5 min, and 20 \u0026micro;g of protein per sample were resolved by SDS\u0026ndash;PAGE. Proteins were transferred to 0.22 \u0026micro;m PVDF membranes (Millipore) using wet transfer (Bio-Rad). Membranes were blocked in 5% skim milk in TBS-T (50 mM Tris, 150 mM NaCl, 0.1% Tween-20) for 1 h at room temperature, incubated with primary antibodies overnight at 4\u0026deg;C, washed with TBS-T, and then incubated with light-protected secondary antibodies for 1 h at room temperature. After final washes, bands were visualized using a GeneGnome XRQ-NPC system (Synoptics) and quantified with Image Studio software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eKaryotyping\u003c/h2\u003e \u003cp\u003ePrimary macaque cSCC cells were grown in 6-cm dishes to 80% confluence and arrested in metaphase with colchicine (0.2 \u0026micro;g/mL) for 1\u0026ndash;2 h at 37\u0026deg;C in 5% CO₂. Cells were trypsinized, pelleted (1,200 rpm, 5 min), resuspended in pre-warmed 0.075 M KCl hypotonic solution and incubated at 37\u0026deg;C for 40 min to promote chromosome spreading. Cells were fixed by three washes in freshly prepared methanol:glacial acetic acid (3:1) (1,200 rpm, 10 min per wash) with gentle resuspension between washes to ensure a monodisperse suspension. Fixed cells were dropped onto clean slides and aged at 80\u0026deg;C for 3 h to improve chromosome adhesion. G-banding was performed by brief trypsin digestion (0.25%, 1 min) followed by Giemsa staining (5\u0026ndash;10 min at room temperature); banding conditions were optimized empirically. Metaphase spreads were examined by bright-field microscopy to identify recurrent numerical and structural chromosomal aberrations, with \u0026ge;\u0026thinsp;20 metaphases analyzed per sample to confirm clonal abnormalities. Representative karyotypes were documented using computerized imaging for standardized classification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eH\u0026amp;E staining\u003c/h2\u003e \u003cp\u003eA standard protocol was followed for H\u0026amp;E staining of the mandibular tumors of macaques and major organs (heart, liver, spleen, lung, and kidneys) of mice treated with saline and paclitaxel (1.5 mg/kg) using a dye (Zhuhai Besso Biotechnology Co., Ltd., Guangdong, China; Cat. #ba4025). Briefly, 6 \u0026micro;m paraffin sections were dried at 60 ℃ for 12 h, followed by dewaxing through xylene and rehydration in a gradient of ethanol concentrations. The slides were then stained with hematoxylin for 5 min, rinsed in running tap water, acid ethanol, and deionized water. Subsequently, the slides were stained with Alcoholic-eosin for 3 s. After staining, the slides were dehydrated and rinsed in several xylene baths. Finally, a thin layer of neutral balsam (Solarbio, Beijing, China; Cat. #G8590) was applied, a glass coverslip was placed, and the slides were imaged using an inverted microscope.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eImmunohistochemistry was performed on 2 \u0026micro;m sections of formalin-fixed, paraffin-embedded tissues from macaques or xenografts. Slides were deparaffinized in xylene and rehydrated through a graded ethanol series (100%, 95%, 70%) and water, with each step incubated for 4 min. Antigen retrieval was achieved by boiling slides in citrate buffer (pH 6.0). Endogenous peroxidase activity was quenched with 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e for 10 min. Slides were washed 3 times with DPBS, and permeabilized with 0.5% Triton X-100 at RT for 10 min. Slides were blocked with 10% goat serum for 1 h, then incubated with diluted primary antibody at 4\u0026deg;C overnight, followed by incubation with diluted secondary antibody at room temperature for 1 h (details in Table S4). After development with 3,3'-diaminobenzidine (DAB) (Cat. #DAB-0031) for 3 min, slides were washed in water and counterstained with hematoxylin. Slides were dehydrated through ethanol (70%, 95%, 100%, 6 min each) and xylene (15 min), mounted with EcoMount (Thermo Fisher; Cat. #EM897L), and imaged using an inverted microscope per the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence\u003c/h2\u003e \u003cp\u003e Formalin-fixed paraffin-embedded macaque tissues were sectioned at 2 \u0026micro;m, baked at 60\u0026ndash;65 ℃ for 30 min, and sequentially deparaffinized in xylene (3 \u0026times; 10 min) followed by rehydration through graded ethanol (100% to 75%) and DPBS rinses. Antigen retrieval was performed by microwaving slides in 0.01 M citrate buffer (pH 6.0) at high power until boiling (8 min), then at low power for 15 min to sustain epitope exposure. After cooling and DPBS washes (3 \u0026times; 5 min), sections were permeabilized with 0.5% Triton X-100 (10 min, RT), blocked with 1% bovine serum albumin (BSA) (30 min, RT), and circumscribed with a hydrophobic barrier. The samples were then incubated with diluted primary antibody at 4 ℃ overnight, followed by DPBS washes (3 \u0026times; 5 min) and room-temperature equilibration. After this, diluted secondary antibody was added and samples were incubated in the dark for 1 h at room temperature (details in Table S2). Nuclei were counterstained with 4',6-diamidino-2-phenylindole (DAPI) (5 min), and slides were mounted with Fluoromount-G\u0026reg; to minimize photobleaching. Fluorescence signals were visualized and imaged using a confocal microscope, with exposure settings standardized across samples to ensure comparability.\u003c/p\u003e \u003cp\u003eThe pretreated cell slides were placed into a 48-well cell culture plate. The epithelioid cells to be identified in culture flasks were digested with 0.25% trypsin, and the digestion was terminated by adding an appropriate amount of complete medium, and the cell suspension was then transferred to a 15 mL centrifuge tube to discard the supernatant and collect the cell precipitate. The cells were resuspended in fresh complete medium and inoculated into 48-well plates with 500 \u0026micro;L cell suspension per well. The cells were cultured in an incubator until they grew into a monolayer. The medium in the wells was aspirated, and the cells were washed with DPBS, followed by fixation with 4% paraformaldehyde (15 min). After fixation, the cells were washed with DPBS. Permeabilization was performed using 0.5% Triton X-100 (20 min) at room temperature, followed by three washes with DPBS. Excess DPBS on the cell slides was removed using absorbent paper, and each well was incubated with 500 \u0026micro;L of 1% BSA blocking solution for 30 min at room temperature. After removing the blocking solution, the sample was incubated with diluted primary antibody at 4 ℃ overnight, followed by DPBS washes and room-temperature equilibration. Hereafter, diluted secondary antibody was added, and the sample was incubated in the dark for 1 h at room temperature (details in Table S2), followed by washes with DPBS. Nuclei were counterstained with DAPI (5 min) in the dark, followed by washes with DPBS. The slides were carefully removed, excess liquid was blotted, and the slides were mounted with Fluoromount-G\u0026reg; (Cat. 0100-01) to minimize photobleaching. Fluorescence signals were visualized and imaged using a confocal microscope.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTUNEL staining\u003c/h3\u003e\n\u003cp\u003eTerminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay was performed on 2 \u0026micro;m sections of formalin-fixed, paraffin-embedded tissues from macaques or xenografts. Slides were deparaffinized in xylene and rehydrated through a graded ethanol series (100% ethanol for 5 min, 90% ethanol for 2 min, 70% ethanol for 2 min) and water for 2 min. Proteinase K (0.2ml; Beyotime; Cat. #ST533) was applied to the sections and incubated at 20\u0026ndash;37 ℃ for 15\u0026ndash;30 min to facilitate antigen retrieval. Slides were washed 3 times with DPBS, then incubated with the TUNEL reaction mixture (containing terminal deoxynucleotidyl transferase (TdT) enzyme and fluorescent labeling solution) at 37 ℃ for 60 min in the dark. Slides were washed 3 times with DPBS. After sealing with anti-fluorescence quenching sealing solution, fluorescence signals were visualized and imaged using a confocal microscope, with exposure settings standardized across samples to ensure comparability. TUNEL staining was performed using a One-step TUNEL Apoptosis Assay kit (Beyotime; Cat. #C1090) following the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eRNA sequencing and analysis\u003c/h2\u003e \u003cp\u003eRNA was extracted from nine macaque cell samples\u0026mdash;comprising three replicates each of normal epithelial cells from healthy macaques, cancer-adjacent epithelial cells, and squamous carcinoma cells\u0026mdash;using TRIzol reagent (Thermo Fisher Scientific, USA; Cat. #15596018CN) as per the manufacturer\u0026rsquo;s protocol. Poly(A)-enriched RNA-seq libraries were prepared and sequenced on the Illumina NovaSeq X Plus platform by Biolinker Technology (Kunming) Co., Ltd. Adapter-trimmed reads, processed with trim_galore, were aligned to the \u003cem\u003eMacaca mulatta\u003c/em\u003e genome using STAR v2.7.11a, followed by file conversion with SAMtools v1.18. Gene expression was quantified using featureCounts v2.0.6, and differentially expressed genes (DEGs) were identified with DESeq2 (adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Functional enrichment analysis for Gene Ontology and KEGG pathways was performed using ShinyGO v0.82. Hierarchical clustering, heatmaps, and volcano plots were generated using ClusterGVis and ggplot2 in R.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eWhole-genome sequencing data processing\u003c/h2\u003e \u003cp\u003eWhole-genome sequencing (WGS) was performed on tumor and matched adjacent non-tumor tissues (ANT) of rhesus macaque squamous cell carcinoma. Raw sequencing reads were subjected to quality control and adapter trimming using fastp (v0.23.2), and the clean reads were aligned to the \u003cem\u003eM. mulatta\u003c/em\u003e reference genome (ensembl Mmul_10.113) with BWA-MEM (v0.7.18). The resulting BAM files were processed with Samtools (v1.9), and duplicates were removed using Picard (v2.18.29). Base quality score recalibration was then performed with Genome Analysis Toolkit (GATK) (v4.1.0.0) using known rhesus macaque variant sites. Somatic single-nucleotide variants (SNVs) and small insertions/deletions (indels) were identified with Strelka2 (v2.9.10), copy number variations (CNVs) were detected using CNVkit (v0.9.12) in whole-genome mode, and structural variants (SVs) were inferred with Manta (v1.6.0).\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eSingle-cell RNA-seq data processing and quality control\u003c/h2\u003e \u003cp\u003eRaw sequencing data were first processed and quantified using Cell Ranger (v6.0.0) with default parameters, generating expression matrices for downstream analyses. The matrices from tumors and ANT were further processed in Seurat (v5.3.0). Gene identifiers were mapped to gene symbols, and duplicated entries were collapsed by summing counts. Low-quality cells were excluded if they contained fewer than 200 detected genes, more than 6,000 genes, or greater than 5% mitochondrial transcript content. Potential doublets were identified and removed using DoubletFinder (v2.0.4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eData integration and clustering\u003c/h2\u003e \u003cp\u003eAfter quality control, datasets from all samples were normalized. Highly variable genes were identified, followed by principal component analysis (PCA). Batch effects across samples were corrected using Harmony integration. Cells were clustered using a shared nearest neighbor (SNN) modularity optimization approach at a resolution of 0.5, and clusters were visualized with UMAP.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eCell type annotation and downstream analyses\u003c/h3\u003e\n\u003cp\u003eDifferentially expressed genes (DEGs) were identified for each cluster using the FindAllMarkers function (log2FC\u0026thinsp;\u0026gt;\u0026thinsp;0.25, adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cluster annotation was guided by canonical marker genes and further curated to define broad cell types, including malignant epithelial cells, fibroblasts, immune populations, endothelial cells, and stromal lineages. Cell type compositions were quantified across tumor and adjacent samples. To investigate large-scale genomic alterations, inferCNV (v1.18.1) was applied to infer copy number variation (CNV) profiles, using immune and stromal cells as reference populations. Differential expression analyses were further conducted between tumor and normal subsets.\u003c/p\u003e\n\u003ch3\u003eProteomic assay\u003c/h3\u003e\n\u003cp\u003eProteomic analysis was performed by Shanghai Bioprofile Biotechnology Co., Ltd. Peptide samples were separated on a \u0026micro;PAC Neo High-Throughput column using a Vanquish Neo UHPLC system, with a linear gradient from 4\u0026ndash;99% solvent B over 10 min. Data-independent acquisition (DIA) was carried out on an Orbitrap Astral mass spectrometer in positive-ion mode, with an MS1 scan range of 380\u0026ndash;980 m/z and a resolution of 240,000. Raw data were processed with DIA-NN for protein identification and quantification against the UniProtKB \u003cem\u003eMacaca mulatta\u003c/em\u003e reference database. For data analysis, proteins with \u0026gt;\u0026thinsp;50% non-missing values across samples were included, and missing values were imputed. Differentially expressed proteins were defined as those with fold change\u0026thinsp;\u0026gt;\u0026thinsp;1.5 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eEctopic model of cSCC\u003c/h2\u003e \u003cp\u003eFour-week-old male BALB/c nude mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). The animals were housed under specific pathogen-free (SPF) conditions with free access to standard food and water for 2 weeks. Environmental conditions were maintained at 20\u0026ndash;21\u0026deg;C with 40%\u0026ndash;60% relative humidity under a 12-h light/dark cycle. Mice were used for experiments once they reached a body weight of approximately 20 g. All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals. To establish the ectopic cSCC model, 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cSCC cells suspended in 100 \u0026micro;L of a 1:1 mixture of Pneu and Matrigel were inoculated subcutaneously on the left dorsal side, above the abdominal area of each mouse. Matrigel (Corning Incorporated, Corning, USA; Cat. #356234) was thawed on ice overnight prior to use. After 4 weeks, tumors reached an average volume of 100\u0026ndash;120 mm\u0026sup3;. Tumor volume (V) was calculated using the formula V = (L \u0026times; W\u0026sup2;) / 2, where L is tumor length and W is tumor width. Mice were then stratified into two groups based on tumor size. Following inoculation, body weight and tumor dimensions were monitored every three days. The maximal permitted tumor burden was 1500 mm\u0026sup3;, and this limit was not exceeded in any experiment.\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eIn vivo drug treatment\u003c/h2\u003e \u003cp\u003eFor murine xenografts, paclitaxel (5 mg/kg) was administered via intravenous (IV) injection in 100 \u0026micro;L saline every three days. The injection time for mice was approximately 1 min. In macaques, paclitaxel (80 mg/m\u0026sup2;) was delivered as a 1 h IV infusion in 5% glucose-saline weekly. Premedication included sequential IV administration of dexamethasone (1 mL), diphenhydramine (0.5 mL), and granisetron (0.6 mL of 1 mg/mL solution) 30 min prior to treatment, respectively, to mitigate hypersensitivity and emesis. All agents were administered intravenously in strict sequence to avoid pharmacological interactions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003eSampling of blood and tissue\u003c/h2\u003e \u003cp\u003eFor nude mouse procedures, after a 12 h fast with ad libitum water, mice were humanely euthanized under isoflurane anesthesia via cardiac exsanguination followed by cervical dislocation, using inhalational anesthesia instead of isopentane. Similarly, for macaque blood collection, sedated macaques (ketamine 10 mg/kg IM) after a\u0026thinsp;\u0026ge;\u0026thinsp;10 h fast underwent saphenous vein venipuncture, preferred over arm veins to reduce stress, with certified technicians collecting 4 mL blood into K\u003csub\u003e3\u003c/sub\u003eEDTA tubes using 21-gauge safety needles at a 15\u0026ndash;20\u0026deg; angle to minimize hemolysis. Blood samples were processed promptly: EDTA-treated aliquots were analyzed within 2 h using the Mindray BC-5000 Vet analyzer to ensure platelet stability, while serum tubes were clotted for 30 min, then centrifuged at 1500\u0026times;g for 10 min at 4 ℃. For tissue preservation, separated tissues were fixed in 10% neutral buffered formalin for 48 h to optimize histomorphology, or snap-frozen in liquid nitrogen to prevent ice crystal artifacts, with storage at -80 ℃ in RNase-free cryovials.\u003c/p\u003e \u003cdiv id=\"Sec40\" class=\"Section3\"\u003e \u003ch2\u003eBlood biochemical analysis\u003c/h2\u003e \u003cp\u003eBlood cell counts were conducted by the National Resource Center for Non-Human Primates at the Kunming Institute of Zoology, Chinese Academy of Sciences. All serum parameters were quantified with Siemens Healthcare kits per the manufacturer's instructions. All samples were analyzed via photometry on a Dimension EXL 200 (Erlangen, Germany).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMRI study\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMagnetic resonance imaging (MRI) data were collected on a Shanghai United Imaging Medical Technology\u0026rsquo;s uMR NX 3.0T magnetic resonance imaging system at the Kunming Institute of Zoology using a human knee coil. Functional scans were collected using gradient echo with repetition time (TR)\u0026thinsp;=\u0026thinsp;3830 s, echo time (TE)\u0026thinsp;=\u0026thinsp;42.1 ms, flip angle\u0026thinsp;=\u0026thinsp;90\u0026deg;, voxel size\u0026thinsp;=\u0026thinsp;1.5 \u0026times; 1.5 \u0026times; 3.0 mm (slice thickness\u0026thinsp;=\u0026thinsp;3.0 mm with 0% slice gap), matrix size\u0026thinsp;=\u0026thinsp;64 \u0026times; 100, and field of view\u0026thinsp;=\u0026thinsp;96 \u0026times; 95 mm. Forty axial slices were prescribed to cover the entire cortex and were scanned in order.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec41\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eOne-way ANOVA followed by Tukey\u0026rsquo;s post hoc tests was performed in GraphPad Prism 8.0 to determine differences between each group when more than two conditions were present. Unpaired two-tailed Student\u0026rsquo;s t tests were performed for two pairwise comparisons due to normal distribution and equal variances. Error bars represent standard deviation (SD) or standard error of the mean (SEM). A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was set to be a significant threshold.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Kunming Cell Bank of Type Culture Collection for their technical support in culturing the cSCC cells. We thank the Core Technology Facility of the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences (CAS) for providing high-resolution in vivo and in vitro imaging. We are also grateful to Shuangjuan Yang for her technical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYongzhang Pan:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Visualization, Validation, Formal analysis, Data Curation, Software, Writing - Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLihong Li:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Visualization, Validation, Formal analysis, Data Curation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLingling Xiao:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Visualization, Validation, Formal analysis, Data Curation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXin Dong:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Visualization, Validation, Formal analysis, Data Curation, Software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJian Pu:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQi Geng:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeng Zhou:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQinghua Zeng:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChengmei Yang:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRui Li:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGui Li:\u0026nbsp;\u003c/strong\u003eMethodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChao Liu:\u0026nbsp;\u003c/strong\u003eMethodology.\u003cbr\u003e\u0026nbsp;\u003cstrong\u003eQiong Wang:\u003c/strong\u003e Methodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAyesha Nisar:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSawar Khan\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLongbao Lv:\u0026nbsp;\u003c/strong\u003eResources, Conceptualization, Supervision, Funding acquisition, Project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYonghan He\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eResources, Conceptualization, Supervision, Funding acquisition, Project administration, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures involving animals in this study were reviewed and approved by the Animal Ethics Committee of the Kunming Institute of Zoology, Chinese Academy of Sciences (Approval Nos. IACUC-PE-2025-04-006 and IACUC-RE-2025-04-006).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNational Key R\u0026amp;D Program of China (2023YFC3603300 to YHH)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYunnan Fundamental Research Projects (202305AH340006 to YHH)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNational Natural Science Foundation of China (82171558 and 82471599 to YHH)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAS \"Light of West China\" Program (xbzg-zdsys-202312 to YHH)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTechnology Talent and Platform Plan Program of Yunnan Province (202405AD350052, 202305AF150160, 202305AH340007 to LBL)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcademician Expert Workstation of Yunnan Kunming (YSZJGZZ-2022063 to LBL)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecial Project of Yunnan Provincial Key Laboratory of Ophthalmic Disease Prevention and Treatment Research ((2017DG008(2025-1) to LBL)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYHH is supported by the Pioneer Hundred Talents Program of the Chinese Academy of Sciences and the Yunnan Revitalization Talent Support Program Young Talent Project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYZP, LHL, LLX, LBL and YHH are inventors on a patent for the construction and use of a macaque cSCC model. The other authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. All raw data can be accessed in the GSA database (PRJCA047204).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLapouge, G.\u003cem\u003e et al.\u003c/em\u003e Skin squamous cell carcinoma propagating cells increase with tumour progression and invasiveness. \u003cem\u003eThe EMBO Journal\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 4563-4575 (2012).\u003c/li\u003e\n\u003cli\u003eWinge, M. C.\u003cem\u003e et al.\u003c/em\u003e Advances in cutaneous squamous cell carcinoma. \u003cem\u003eNature Reviews Cancer\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 430-449 (2023).\u003c/li\u003e\n\u003cli\u003eWang, M., Gao, X. \u0026amp; Zhang, L. 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Here, we report a spontaneous macaque cSCC model (5/2752 incidence; 80% mortality) that reproduces key human cSCC features. Tumors show well-differentiated squamous morphology, expression of squamous lineage markers (p63, CK5/6), and elevated Ki-67 proliferation indices. We apply whole-genome sequencing, bulk and single-cell RNA sequencing, proteomics, and functional assays to define tumor biology. Genomes display a high mutational burden with C\u0026thinsp;\u0026gt;\u0026thinsp;T dipyrimidine changes, pervasive chromosomal instability, translocations, and focal copy-number alterations. Integrated analyses reveal NF-κB\u0026ndash;mediated inflammatory programs, macrophage-rich immune remodeling, and a shift toward aerobic glycolysis. Cross-platform data nominate MYO10 as recurrently altered and overexpressed. MYO10 knockdown reduces γ-H2AX, micronuclei, and IL-6/TNFα expression, while MYO10 overexpression induces DNA damage and inflammation in primary epithelial cells. Drug screening identifies paclitaxel as the most potent compound (IC₅₀ = 0.011 \u0026micro;M). Paclitaxel triggers apoptosis, G2/M arrest, and reduced migration in vitro. In mouse xenografts, it shrinks tumors by 89.4%. In a treated macaque, it produces 86.6% mean tumor regression, lowers systemic IL-6 and TNFα, and is well tolerated. This spontaneous macaque model links genomic instability to inflammation via MYO10 and offers a translational platform for studying cSCC and testing therapies.\u003c/p\u003e","manuscriptTitle":"Integrated Multi-omics Reveals Key Molecular Drivers and Therapeutic Strategies in a Spontaneous Cutaneous Squamous Cell Carcinoma Model of Macaques","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 19:39:23","doi":"10.21203/rs.3.rs-8987244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"265822681381431766570653170637728965398","date":"2026-05-09T11:36:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-06T14:45:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-07T16:24:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-02T11:41:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Precision Oncology","date":"2026-02-27T10:53:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-precision-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjprecisiononcology","sideBox":"Learn more about [npj Precision Oncology](http://www.nature.com/npjprecisiononcology/)","snPcode":"41698","submissionUrl":"https://submission.springernature.com/new-submission/41698/3","title":"npj Precision Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6fc7633f-f908-482d-909c-b2c769b86a84","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"265822681381431766570653170637728965398","date":"2026-05-09T11:36:42+00:00","index":47,"fulltext":""},{"type":"reviewersInvited","content":"31","date":"2026-05-06T14:45:36+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":68128867,"name":"Biological sciences/Cancer"},{"id":68128868,"name":"Biological sciences/Cell biology"},{"id":68128869,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":68128870,"name":"Biological sciences/Molecular biology"},{"id":68128871,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-05-15T19:39:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 19:39:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8987244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8987244","identity":"rs-8987244","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}