Abstract
Senescence is believed to be a pivotal player in the onset and progression of tumors as well as cancer therapy. However, the guiding roles of senescence in clinical outcomes and therapy selection for patients with cancer remain obscure, largely due to the absence of a feasible senescence signature. Here, by integrative analysis of single cell and bulk transcriptome data from multiple datasets of gastric cancer patients, we uncovered senescence as a veiled tumor feature characterized by senescence gene signature enriched, unexpectedly, in the noncancerous cells, and further identified two distinct senescence-associated subtypes based on the unsupervised clustering. Patients with the senescence subtype had higher tumor mutation loads and better prognosis as compared with the aggressive subtype. By the machine learning, we constructed a scoring system termed as senescore based on six signature genes: ADH1B, IL1A, SERPINE1, SPARC, EZH2, and TNFAIP2. Higher senescore demonstrated robustly predictive capability for longer overall and recurrence-free survival in 2290 gastric cancer samples, which was independently validated by the multiplex staining analysis of gastric cancer samples on the tissue microarray. Remarkably, the senescore signature served as a reliable predictor of chemotherapeutic and immunotherapeutic efficacies, with high-senescore patients benefited from immunotherapy, while low-senescore patients were responsive to chemotherapy. Collectively, we report senescence as a heretofore unrecognized hallmark of gastric cancer that impacts patient outcomes and therapeutic efficacy.
Highlights
Gastric cancer (GC) is the third leading cause of cancer death and the fifth most common cancer globally [1]
It was revealed that a wide spectrum of tumor features, such as genomic instability described as microsatellite instable (MSI) or tumor mutational burden (TMB) status and tumor-infiltrating immune cells in tumor microenvironment (TME), were associated with immunotherapy sensitivity in preclinical and clinical settings [5,6,7], it is still a daunting challenge to predict the treatment responses of chemotherapy and immunotherapy simultaneously, and to make the appropriate therapeutic options
Senescore predicts the efficacies of chemotherapy and immunotherapy Considering that cellular senescence could be induced by DNA damage drug, we explored whether senescore, the senescence scoring model, could predict the treatment efficiency of chemotherapy
Summary
Gastric cancer (GC) is the third leading cause of cancer death and the fifth most common cancer globally [1]. With the rapid advance in the high-throughput sequencing technologies, molecular subtypes of GC were established by The Cancer Genome Atlas (TCGA) including microsatellite instable (MSI), genomically stable (GS), chromosomal instability (CIN), Epstein-Barr virus (EBV) associated, and hypermutated-single-nucleotide variants (HM-SNV) [3], as well as by the Asian Cancer Research Group (ACRG) comprising microsatellite stable (MSS)/epithelial–mesenchymal transition (EMT), MSI, MSS/p53+, and MSS/p53− [4] These defined classifications face huge obstacles in the clinical translation and limitations in relevant cancer patients. It was revealed that a wide spectrum of tumor features, such as genomic instability described as MSI or tumor mutational burden (TMB) status and tumor-infiltrating immune cells in tumor microenvironment (TME), were associated with immunotherapy sensitivity in preclinical and clinical settings [5,6,7], it is still a daunting challenge to predict the treatment responses of chemotherapy and immunotherapy simultaneously, and to make the appropriate therapeutic options. We demonstrated that senescore, a senescence scoring system of tumor, exhibited robust predictive powers for the patients outcomes and for the efficacies of different therapeutic strategies including adjuvant chemotherapy and immunotherapy (Fig. 1)
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