AUTHOR=Li Mengyuan , Gao Xuejiao , Wang Xiaosheng 

TITLE=Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data

JOURNAL=Frontiers in Immunology

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1090838

DOI=10.3389/fimmu.2023.1090838

ISSN=1664-3224

ABSTRACT=<sec><title>Background</title><p>Tumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient.</p></sec><sec><title>Methods</title><p>We analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy.</p></sec><sec><title>Results</title><p>Among the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (≥ 10/Mb) cancers (49.4%), followed by lung adenocarcinoma (36.9%) and lung squamous cell carcinoma (28.1%). Three hundred seventy-six genes had significant correlations of their mutations with increased TMB in various cancers, including 11 genes (<italic>ARID1A</italic>, <italic>ARID1B</italic>, <italic>BRIP1</italic>, <italic>NOTCH2</italic>, <italic>NOTCH4</italic>, <italic>EPHA5</italic>, <italic>ROS1</italic>, <italic>FAT1</italic>, <italic>SPEN</italic>, <italic>NSD1</italic>,and <italic>PTPRT</italic>) with the characteristic of their mutations associated with a favorable response to immunotherapy. Based on the mutation profiles in three genes (<italic>ROS1</italic>, <italic>SPEN</italic>, and <italic>PTPRT</italic>), we defined the TMB prognostic score that could predict cancer survival prognosis in the immunotherapy setting but not in the non-immunotherapy setting. It suggests that the TMB prognostic score’s ability to predict cancer prognosis is associated with the positive correlation between immunotherapy response and TMB. Nine cancer-associated pathways correlated positively with TMB in various cancers, including nucleotide excision repair, DNA replication, homologous recombination, base excision repair, mismatch repair, cell cycle, spliceosome, proteasome, and RNA degradation. In contrast, seven pathways correlated inversely with TMB in multiple cancers, including Wnt, Hedgehog, PI3K-AKT, MAPK, neurotrophin, axon guidance, and pathways in cancer. High-TMB cancers displayed higher levels of antitumor immune signatures and <italic>PD-L1</italic> expression than low-TMB cancers in diverse cancers. The association between TMB and survival prognosis was positive in bladder, gastric, and endometrial cancers and negative in liver and head and neck cancers. TMB also showed significant associations with age, gender, height, weight, smoking, and race in certain cohorts.</p></sec><sec><title>Conclusions</title><p>The molecular and clinical features significantly associated with TMB could be valuable predictors for TMB and immunotherapy response and therefore have potential clinical values for cancer management.</p></sec>