Unveiling the Hidden Players in Skin Cancer: How Fibroblasts Might Be Pulling the Strings in Cutaneous Squamous Cell Carcinoma
Imagine this: a seemingly harmless skin lesion that starts as a small, scaly patch but could escalate into a deadly cancer. This is the stark reality for millions affected by cutaneous squamous cell carcinoma (CSCC), the second most common form of non-melanoma skin cancer. But what if the key to understanding—and perhaps stopping—this progression lies not just in the cancer cells themselves, but in the supportive cells around them? Our latest research dives deep into this, using cutting-edge multi-omics techniques to explore how cancer-associated fibroblasts (CAFs) influence CSCC, especially in cases linked to human papillomavirus (HPV). And here's where it gets controversial: Could HPV infection be subtly reshaping these fibroblasts in ways that fuel tumor growth, challenging our current views on immune suppression? Stick around, because this is the part most people miss—the intricate dance between cells in the tumor environment that could hold the key to better treatments and prevention strategies.
Research Highlights
This open-access study, published on November 19, 2025, in Cancer Cell International (volume 25, article 417), combines single-cell RNA sequencing and spatial transcriptomics to dissect the cellular landscape of CSCC. It's freely available through Springer's open science initiative, ensuring accessibility for everyone interested in advancing cancer research.
Core Team and Affiliations
Lead investigators include Xiaochuan Wang, Tingrui Li, Yichao Jin, Jingjing Chen, Xin Yang, Zhen Guan, Mei Jin, Jingxian Zhang, Liangheng Xu, Sizhen Tao, Chunguang Li, and Chunping Ao. Wang and Li share first authorship, with Ao serving as the corresponding author. The work stems from the Department of Dermatology at the First People's Hospital of Yunnan Province, Yunnan Provincial Key Laboratory of Clinical Virology, and the Affiliated Hospital of Kunming University of Science and Technology in Kunming, China, as well as the People's Hospital of Mengzi in Yunnan.
Abstract: A Snapshot of Our Discoveries
In our background, we noted that HPV infection heightens the risk of CSCC, making it essential to thoroughly investigate cellular diversity in both HPV-positive and HPV-negative CSCC tumors for enhanced diagnosis and to halt disease advancement.
Methods: We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomic data from various skin tissue samples to chart the tumor microenvironment (TME) in HPV-infected and non-infected CSCC. Findings were corroborated using multiplex immunohistochemistry (mIHC) and lab experiments.
Results: We pinpointed 10 primary cell categories in CSCC and healthy skin tissues: epithelial cells, myeloid cells, T cells, fibroblasts, endothelial cells, B cells, smooth muscle cells, mast cells, melanocytes, and hair follicle cells. Crucially, fibroblasts were tied to cancer progression in CSCC, regardless of HPV status. We further delineated eight distinct CAF subtypes, where iCAFs-CXCL2 drove tumor advancement, and iCAFs-PLA2G2A inhibited it. The MDK-ITGA6 interaction facilitated communication between fibroblasts and epithelial cells in CSCC. IHC tests revealed heightened MDK and ITGA6 levels in CSCC samples. Cell co-culture assays demonstrated that MDK from CAFs boosted cancer cell movement and infiltration in CSCC.
Conclusion: Our study delivers a detailed cellular roadmap of CSCC, spotlighting CAFs' involvement in HPV's impact on CSCC progression. This could pave the way for novel diagnostic tools and predictive markers for CSCC patients.
Introduction: Setting the Stage for CSCC
CSCC stands as a formidable non-melanoma skin cancer (NMSC), originating from abnormal keratinocyte growth and often manifesting as a firm, crusted sore. For context, keratinocytes are the primary cells in the outer skin layer, and their unchecked multiplication can lead to these telltale lesions. While most CSCC cases respond well to surgical removal, leading to positive outcomes for the majority, the disease's rising global incidence is alarming. High recurrence rates, nerve involvement, and spread to distant areas contribute to its significant mortality—factors that underscore the urgent need for better insights.
Risk factors include aging, male gender, ultraviolet (UV) light exposure, radiation, immunosuppressive drugs, antifungal medications used in organ transplant patients (OTRs), β-HPV infection, smoking, genetic predispositions like fair skin or hereditary syndromes, and general immunosuppression. For beginners, think of UV radiation as the sun's invisible rays that damage DNA over time, much like how repeated sunburns weaken skin integrity.
A prevailing "hit-and-run" theory suggests β-HPV jumpstarts UV-triggered CSCC but disappears during tumor maintenance, implying β-HPV's early role in development. Studies, such as a large prospective trial, link β-HPV to CSCC in OTRs, where weakened immunity raises susceptibility. Immunosuppression acts like lowering the body's defenses, allowing viruses like HPV to linger and promote cancer. Intriguingly, β-HPV also increases CSCC risk in immunocompetent individuals, hinting at additional mechanisms beyond immune evasion, such as direct cellular changes or signaling disruptions.
Advancements in high-throughput techniques, like scRNA-seq and spatial transcriptomics (stRNA-seq), have revolutionized our view of TME cellular interactions in HPV-related cancers. scRNA-seq examines gene activity in individual cells, revealing nuances missed in bulk analyses—akin to zooming in from a group photo to focus on each person's expression. For instance, scRNA-seq has uncovered cellular complexities in HPV-triggered CSCC and surrounding tissues. CAFs, specialized fibroblasts in tumors, play pivotal roles in HPV-linked cancers: they drive progression in HPV-positive head and neck cancers, while certain CAF markers predict resistance to therapies in HPV-related cases. CAFs also contribute to immune suppression and inflammation in HPV-driven cervical cancer.
Yet, the TME's cellular makeup and CAFs' roles in HPV-positive versus HPV-negative CSCC remain enigmatic. In this research, we analyzed scRNA-seq data from HPV-positive and -negative CSCC skin samples, plus healthy controls, to map TME interactions. We combined this with experiments to validate findings in HPV-negative CSCC, building a comprehensive picture.
Materials and Methods: Our Approach to Discovery
Data Sources: We drew from publicly available datasets, including GSE139505 with 9 CSCC and 7 healthy controls, GSE144236 with 10 CSCC and 10 matched normals, GSE218170 with 5 CSCC samples, GSE262947 featuring one HPV-induced CSCC (positive for HPV6/11 but negative for 16/18) and one adjacent sample, GSE193304 with 3 CSCC and 1 in situ carcinoma (SCCIS) sample, and GSE144239 with spatial transcriptomic data from 4 CSCC samples. All accessed via the Gene Expression Omnibus (GEO).
scRNA-seq Processing: Using Seurat in R, we filtered out poor-quality cells based on gene counts (over 300 but under 7,500), mitochondrial gene percentage (under 30% for most, 50% for HPV samples). Batch effects were corrected with Harmony, normalizing and scaling data. We identified top 2,000 variable genes, reduced dimensions via PCA, clustered cells with a resolution of 0.5, and annotated types using markers from databases like CellMarker 2.0 and ACT. Visualization employed UMAP, a tool that clusters similar cells visually, much like a map grouping nearby towns.
For CAF subtypes, we isolated fibroblasts, selected genes, and subclustered similarly.
Pathway Analysis: Differential genes per subcluster were found using Seurat's FindAllMarkers. KEGG pathways were enriched via ClusterProfiler, with PROGENy assessing 14 signaling pathways (e.g., androgen, estrogen, EGFR, hypoxia, etc.) and CytoSig evaluating cytokine signals.
Cell Trajectory: Monocle 2 tracked CAF evolution, with CytoTRACE predicting differentiation states and BEAM analyzing branch-specific genes.
Cell Communication: CellChat mapped interactions via ligand-receptor pairs, focusing on pathways like MK, CD99, etc.
Spatial Analysis: StRNA-seq from GSE144239 was processed in Seurat, correcting batches, selecting 4,000 genes, and clustering. Integrated with scRNA-seq, NICHES assessed spatial interactions.
Tissue Microarray and IHC: A skin cancer array (HSkiC060pt01) with 43 CSCC, 7 normals, etc., was used. Samples were stained with Opal kits for MDK and ITGA6, scanned, and analyzed.
Clinical Samples and Cell Culture: Four CSCC tissues were collected with ethics approval (KHLL2024-KY292). Fresh tumors were minced, digested with collagenase, and cultured in DMEM/F12 with FBS. SCL1 cell line (from ATCC) was maintained similarly.
Transfections and Assays: CAFs were transfected with MDK siRNA using Lipofectamine, checked via qPCR. Co-cultures used Transwell inserts. RNA was extracted, cDNA made, and qPCR/Western blots assessed gene/protein levels. Wound healing and Transwell tests measured migration/invasion.
Statistics: Results as means ± SD from ≥3 experiments. Analyzed with GraphPad Prism via ANOVA and Tukey tests, p<0.05 significant.
Results: Key Findings Unpacked
Cellular Landscape Identification: After quality checks, 169,421 cells were analyzed. Ten types emerged: epithelial (KRT1/KRT10 markers), myeloid (HLA-DRA/LYZ), T cells (CD2/CD3D), fibroblasts (COL1A1/DCN), endothelial (VWF/RAMP2), B cells (MZB1/CD79A), smooth muscle (TAGLN/ACTA2), mast (CPA3/TPSAB1), melanocytes (DCT/PMEL), hair follicle (GJB2/GJB6). Proportions varied: epithelial cells dropped, fibroblasts rose in HPV-positive tissues versus normals. Fibroblasts were more abundant in tumors, highlighting their TME enrichment.
CAF Subtypes: Eight emerged—mCAFs (SPON2/MMP11, matrix-focused), ECM-CAFs (MFAP5/TNN, extracellular matrix), vCAFs (MCAM/ACTA2, vascular), dCAFs (MKI67/TUBA1B, dividing), iCAFs-CXCL2 (IL6/CXCL2, inflammatory), iCAFs-PLA2G2A (C3/PLA2G2A, also inflammatory), apCAFs (HLA-DRA/CD74, antigen-presenting), EMT-like CAFs (COMP/TNC, transition-like). iCAFs-PLA2G2A enriched in HPV-negative, iCAFs-CXCL2 in HPV-positive; both rose in tumors versus normals, suggesting dual roles—iCAFs-PLA2G2A protective, iCAFs-CXCL2 harmful.
Pathway Insights: KEGG showed ECM-receptor interactions in mCAFs/EMT-like, protein digestion in mCAFs, oxidative phosphorylation in ECM/v/EMT. Cell cycle in dCAFs, Kaposi sarcoma/IL-17/TNF in iCAFs-CXCL2. Complement/coagulation in iCAFs-PLA2G2A, antigen processing in apCAFs. PROGENy highlighted EGFR/MAPK/TNF-α in iCAFs-CXCL2. CytoSig noted NO in iCAFs-CXCL2, OSM/MCSF in iCAFs-PLA2G2A. This underscores CAFs' tumorigenesis roles, especially in HPV contexts.
Trajectory Dynamics: Monocle identified three states; iCAFs-CXCL2/PLA2G2A branched differently. CytoTRACE placed dCAFs/vCAFs early, iCAFs-PLA2G2A/mCAFs late. dCAFs/vCAFs evolved to iCAFs-CXCL2. Gene patterns showed IFI6/ISG15 upregulation in iCAFs-CXCL2, aiding CSCC progression.
Communication Networks: HPV-negative CSCC had more interactions than HPV-positive. Fibroblasts sent strong signals, epithelial received them. MK/CD99 pathways dominated normals, FN1/collagen/laminin in tumors. MDK-ITGA6 emerged key for fibroblast-epithelial ties. Expression rose in tumors per GSE139505.
Spatial Insights: 7,902 spots analyzed; epithelial cells predominant, fibroblasts/B cells notable. MDK-ITGA6 prominent spatially.
IHC Validation: CSCC showed more MDK/ITGA6/ITGA6-MDK co-expression than normals. Paired samples confirmed this.
In Vitro Proof: MDK knockdown reduced MDK/ITGA6 in co-cultured SCL1 cells. CAF co-culture enhanced SCL1 migration/invasion, reversed by MDK siRNA.
Discussion: Interpreting the Implications
HPV's link to CSCC is established, but progression mechanisms unclear. Our work aligns with prior findings of CAF abundance in HPV-positive CSCC. We detailed eight subtypes, with iCAFs-CXCL2/PLA2G2A opposing: iCAFs-CXCL2 promotes via IL-17/TNF-α (linked to inflammation in HPV breast cancer) and EGFR/MAPK/NF-κB (tied to immune evasion and resistance). iCAFs-PLA2G2A suppresses, involving complement cascades and estrogen/OSM/MCSF.
Trajectory analysis showed dCAFs/vCAFs initiating to iCAFs-CXCL2, with genes like IFI6/ISG15 marking progression.
Cell interactions intensified in CSCC, with MDK-ITGA6 mediating fibroblast-epithelial crosstalk, independent of HPV status—though functional validation focused on HPV-negative due to sample limits. MDK, a growth factor, fosters metastasis and resistance; CAF-derived MDK induces drug tolerance in gastric/OSCC cancers.
Our IHC/in vitro data confirm MDK's role in enhancing CSCC cell movement/invasion. Future HPV-positive models needed for fuller understanding.
But here's the controversial angle: Does HPV's presence fundamentally alter CAF behavior, or is it just one factor in a complex web? Some might argue immunosuppressive drugs play a bigger role, potentially overshadowing HPV. What do you think—is targeting CAFs the future of CSCC treatment, or should we focus on HPV vaccines and UV protection first? Share your thoughts in the comments; does this shift your view on personalized cancer therapies?
Conclusion: Looking Ahead
We provide a detailed TME map for HPV-linked CSCC, emphasizing CAF contributions to progression. MDK-ITGA6 interactions offer potential biomarkers/targets. Future studies should explore HPV-specific dynamics.
Data Availability: All from GEO.
Acknowledgements: Thanks to GEO contributors and funding from Yunnan Provincial Key Laboratory projects.
Funding: Supported by Yunnan initiatives.
Do these findings challenge your understanding of HPV's role in cancers? Or spark ideas for new prevention strategies? We'd love to hear—drop a comment below!
