A Distinguished Roadmap of Fibroblast Senescence in Predicting Immunotherapy Response and Prognosis Across Human Cancers

Abstract

Background: While considered a significant advancement in cancer treatment, immune checkpoint inhibitors (ICI) merely offer benefits to a small portion of tumors. The potential cause of resistance to ICI may lie in cellular senescence, although conclusive clinical evidence is currently unavailable.

Methods: 40 public single-cell RNA sequencing (scRNA-seq) cohorts were enrolled to identify cell-specific senescence patterns, culminating in developing a comprehensive fibroblast senescence-associated signature. Leveraging this signature, 15 machine learning (ML) techniques were utilized to develop models for predicting ICI response and patient survival based on 13 ICI-treated cohorts and 30 pan-cancer cohorts in The Cancer Genome Atlas (TCGA). The prospective target for ICI treatment was detected through the analysis of 17 CRISPR/Cas9 datasets and was confirmed through both in vivo and in vitro experiments.

Results: Large-scale pan-cancer scRNA-seq cohorts revealed that fibroblasts demonstrate the highest levels of cellular senescence compared to cells in malignant tumors. We formulated a transcriptomic signature linked to fibroblast senescence named FSS, which showed a positive association with pro-tumorigenic signaling and disruptions in immune cell responses favoring tumor growth. Utilizing the FSS, the predictive performance of the ML algorithm in forecasting the response of ICI treatment and survival achieved an excellent AUC value in validation and testing sets. Remarkably, FSS demonstrated enhanced predictive capabilities across diverse cancer types when contrasted with previously published signatures. Following CRISPR/Cas9 screening identified that CDC6 was a universal biomarker for gauging ICI response and prognosis. Additionally, experimental evidence illustrated that the CDC6 could suppress the antitumor immunity of CD8+ T cells and switch the polarization of macrophages in pancreatic cancer, bolstering the effectiveness of immunotherapy.

Conclusions: We uncovered a strong correlation between the fibroblast senescence of tumor cells and resistance to ICI treatment, and developed an FSS, which exhibited superior efficacy compared to alternative indicators in predicting ICI outcome, offering a potential strategy for surmounting immune resistance by targeting genes associated with fibroblast senescence.

Funding: This work was supported by the National Natural Science Foundation of China (82273356; 82073326), Shanghai Shenkang Hospital Development Center (SHDC2020CR5008) and Fundamental Research Program of Shanxi Province (202303021212363 to L.Z.).

Declaration of Interest: The authors declare that they have no competing interests.

Ethical Approval: The patient study was approved by the Research Ethics Committee of Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, and complied with the Helsinki Declaration (No: 2021-161). All samples were collected with documented informed consent from the enrolled patients. The annimal experiments carried out under protocols approved by Animal Experiment Center, Shanghai Jiaotong University (No: SYXK2023-0007), and were in accordance with international ethics guidelines and the National Institutes of Health Guide, concerning the Care and Use of Laboratory Animals.

Keywords: fibroblast senescence, immunotherapy, survival prognostication, pan-cancer analysis, scRNA-seq