Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. 2022;12:31–46.
Google Scholar
Schmitt CA, Wang B, Demaria M. Senescence and cancer – role and therapeutic opportunities. Nat Rev Clin Oncol. 2022;19:619–36.
Google Scholar
de Magalhães JP. Cellular senescence in normal physiology. Science. 2024;384:1300–1.
Google Scholar
Zhou R, Han L, Li G, Tong T. Senescence delay and repression of p16INK4a by Lsh via recruitment of histone deacetylases in human diploid fibroblasts. Nucleic Acids Res. 2009;37:5183–96.
Google Scholar
Vizioli MG, Liu T, Miller KN, Robertson NA, Gilroy K, Lagnado AB, et al. Mitochondria-to-nucleus retrograde signaling drives formation of cytoplasmic chromatin and inflammation in senescence. Genes Dev. 2020;34:428–45.
Google Scholar
Maggiorani D, Le O, Lisi V, Landais S, Moquin-Beaudry G, Lavallée VP, et al. Senescence drives immunotherapy resistance by inducing an immunosuppressive tumor microenvironment. Nat Commun. 2024;15:2435.
Google Scholar
Wang X, Ma L, Pei X, Wang H, Tang X, Pei JF, et al. Comprehensive assessment of cellular senescence in the tumor microenvironment. Brief Bioinform. 2022;23:bbac118.
Google Scholar
Wu Z, Uhl B, Gires O, Reichel CA. A transcriptomic pan-cancer signature for survival prognostication and prediction of immunotherapy response based on endothelial senescence. J Biomed Sci. 2023;30:21.
Google Scholar
Avelar RA, Ortega JG, Tacutu R, Tyler EJ, Bennett D, Binetti P, et al. A multidimensional systems biology analysis of cellular senescence in aging and disease. Genome Biol. 2020;21:91.
Google Scholar
Ye B, Fan J, Xue L, Zhuang Y, Luo P, Jiang A, et al. iMLGAM: integrated machine learning and genetic algorithm-driven multiomics analysis for pan-cancer immunotherapy response prediction. Imeta. 2025;4:e70011.
Google Scholar
Sorteberg AL, Halipi V, Wickström M, Shirazi FS. The cyclin dependent kinase inhibitor p21(Cip1/Waf1) is a therapeutic target in high-risk neuroblastoma. Front Oncol. 2022;12:906194.
Google Scholar
Lu C, Wang Y, Nie L, Chen L, Li M, Qing H, et al. Comprehensive analysis of cellular senescence-related genes in the prognosis, tumor microenvironment, and immunotherapy/chemotherapy of clear cell renal cell carcinoma. Front Immunol. 2022;13:934243.
Google Scholar
Vivian J, Rao AA, Nothaft FA, Ketchum C, Armstrong J, Novak A, et al. Toil enables reproducible, open source, big biomedical data analyses. Nat Biotechnol. 2017;35:314–6.
Google Scholar
Li S, Rouphael N, Duraisingham S, Romero-Steiner S, Presnell S, Davis C, et al. Molecular signatures of antibody responses derived from a systems biology study of five human vaccines. Nat Immunol. 2014;15:195–204.
Google Scholar
Kohli J, Wang B, Brandenburg SM, Basisty N, Evangelou K, Varela-Eirin M, et al. Algorithmic assessment of cellular senescence in experimental and clinical specimens. Nat Protoc. 2021;16:2471–98.
Google Scholar
Ellrott K, Bailey MH, Saksena G, Covington KR, Kandoth C, Stewart C, et al. Scalable open science approach for mutation calling of tumor exomes using multiple genomic pipelines. Cell Syst. 2018;6:271–.e7.
Google Scholar
Sanchez-Vega F, Mina M, Armenia J, Chatila WK, Luna A, La KC, et al. Oncogenic signaling pathways in the cancer genome atlas. Cell. 2018;173:321–.e10.
Google Scholar
Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 2016;44:e71.
Google Scholar
Chatsirisupachai K, Lesluyes T, Paraoan L, Van Loo P, de Magalhães JP. An integrative analysis of the age-associated multi-omic landscape across cancers. Nat Commun. 2021;12:2345.
Google Scholar
Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 2011;12:R41.
Google Scholar
Yuan J, Hu Z, Mahal BA, Zhao SD, Kensler KH, Pi J, et al. Integrated analysis of genetic ancestry and genomic alterations across cancers. Cancer Cell. 2018;34:549–.e9.
Google Scholar
Zhong Z, Hou J, Yao Z, Dong L, Liu F, Yue J, et al. Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics. Nat Commun. 2024;15:1929.
Google Scholar
Yu Q, Li YY, Chen Y. scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures. Commun Biol. 2025;8:504.
Google Scholar
Jerby-Arnon L, Shah P, Cuoco MS, Rodman C, Su MJ, Melms JC, et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell. 2018;175:984–.e24.
Google Scholar
Yost KE, Satpathy AT, Wells DK, Qi Y, Wang C, Kageyama R, et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat Med. 2019;25:1251–9.
Google Scholar
Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 2016;165:35–44.
Google Scholar
Liu D, Schilling B, Liu D, Sucker A, Livingstone E, Jerby-Arnon L, et al. Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma. Nat Med. 2019;25:1916–27.
Google Scholar
Gide TN, Quek C, Menzies AM, Tasker AT, Shang P, Holst J, et al. Distinct immune cell populations define response to anti-PD-1 Monotherapy and anti-PD-1/Anti-CTLA-4 combined therapy. Cancer Cell. 2019;35:238–.e6.
Google Scholar
Riaz N, Havel JJ, Makarov V, Desrichard A, Urba WJ, Sims JS, et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell. 2017;171:934–.e16.
Google Scholar
Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350:207–11.
Google Scholar
Mariathasan S, Turley SJ, Nickles D, Castiglioni A, Yuen K, Wang Y, et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 2018;554:544–8.
Google Scholar
Snyder A, Nathanson T, Funt SA, Ahuja A, Buros NJ, Hellmann MD, et al. Contribution of systemic and somatic factors to clinical response and resistance to PD-L1 blockade in urothelial cancer: An exploratory multi-omic analysis. PLoS Med. 2017;14:e1002309.
Google Scholar
Zhao J, Chen AX, Gartrell RD, Silverman AM, Aparicio L, Chu T, et al. Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma. Nat Med. 2019;25:462–9.
Google Scholar
Kim ST, Cristescu R, Bass AJ, Kim KM, Odegaard JI, Kim K, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med. 2018;24:1449–58.
Google Scholar
Braun DA, Hou Y, Bakouny Z, Ficial M, Sant AM, Forman J, et al. Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma. Nat Med. 2020;26:909–18.
Google Scholar
Ayers M, Lunceford J, Nebozhyn M, Murphy E, Loboda A, Kaufman DR, et al. IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade. J Clin Invest. 2017;127:2930–40.
Google Scholar
Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160:48–61.
Google Scholar
Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366:2443–54.
Google Scholar
Ju M, Bi J, Wei Q, Jiang L, Guan Q, Zhang M, et al. Pan-cancer analysis of NLRP3 inflammasome with potential implications in prognosis and immunotherapy in human cancer. Brief Bioinform. 2021;22:bbaa345.
Google Scholar
Dominguez CX, Müller S, Keerthivasan S, Koeppen H, Hung J, Gierke S, et al. Single-cell RNA sequencing reveals stromal evolution into LRRC15(+) myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov. 2020;10:232–53.
Google Scholar
Xiong D, Wang Y, You M. A gene expression signature of TREM2(hi) macrophages and γδ T cells predicts immunotherapy response. Nat Commun. 2020;11:5084.
Google Scholar
Yan M, Hu J, Ping Y, Xu L, Liao G, Jiang Z, et al. Single-cell transcriptomic analysis reveals a tumor-reactive T cell signature associated with clinical outcome and immunotherapy response in melanoma. Front Immunol. 2021;12:758288.
Google Scholar
Shukla SA, Bachireddy P, Schilling B, Galonska C, Zhan Q, Bango C, et al. Cancer-germline antigen expression discriminates clinical outcome to CTLA-4 blockade. Cell. 2018;173:624–.e8.
Google Scholar
Auslander N, Zhang G, Lee JS, Frederick DT, Miao B, Moll T, et al. Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma. Nat Med. 2018;24:1545–9.
Google Scholar
Cui C, Xu C, Yang W, Chi Z, Sheng X, Si L, et al. Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma. NPJ Genom Med. 2021;6:7.
Google Scholar
Halazonetis TD, Gorgoulis VG, Bartek J. An oncogene-induced DNA damage model for cancer development. Science. 2008;319:1352–5.
Google Scholar
Evangelou K, Belogiannis K, Papaspyropoulos A, Petty R, Gorgoulis VG. Escape from senescence: molecular basis and therapeutic ramifications. J Pathol. 2023;260:649–65.
Google Scholar
Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou YTH, et al. The immune landscape of cancer. Immunity. 2018;48:812–.e14.
Google Scholar
Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017;66:683–91.
Google Scholar
Wang B, Kohli J, Demaria M. Senescent cells in cancer therapy: friends or foes. Trends Cancer. 2020;6:838–57.
Google Scholar
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7–30.
Google Scholar
Collado M, Serrano M. Senescence in tumours: evidence from mice and humans. Nat Rev Cancer. 2010;10:51–57.
Google Scholar
Stead ER, Bjedov I. Balancing DNA repair to prevent ageing and cancer. Exp Cell Res. 2021;405:112679.
Google Scholar
Nesta AV, Tafur D, Beck CR. Hotspots of human mutation. Trends Genet. 2021;37:717–29.
Google Scholar
McHugh D, Durán I, Gil J. Senescence as a therapeutic target in cancer and age-related diseases. Nat Rev Drug Discov. 2025;24:57–71.
Google Scholar
Dong Z, Luo Y, Yuan Z, Tian Y, Jin T, Xu F. Cellular senescence and SASP in tumor progression and therapeutic opportunities. Mol Cancer. 2024;23:181.
Google Scholar

