INTEGRATING TUMOR MUTATIONAL BURDEN AND TRANSCRIPTOME EXPRESSION INTO PREDICTION OF IMMUNE CHECKPOINT INHIBITOR RESPONSE AND PROGNOSIS OF PATIENTS WITH COLON CANCER

L. Liang, W. Jiang, Y. Zheng, T. Liu, X. Shen, Y. Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Whether tumor mutational burden (TMB), which refers to the total number of somatic or acquired mutations per million bases in a particular region of the tumor genome, can serve as a predictive biomarker of immune checkpoint inhibitor (ICI) therapy for colon cancer remains unclear. Hereby, we retrospectively investigated the differentially expressed genes (DEGs) based on the level of TMB and tried to established a risk score model as a novel biomarker. The DNA mutation data were retrieved from the Masked Somatic Mutation in Genomic Data Commons data portal of the Cancer Genome Atlas, where the RNA sequencing data, clinical information, and survival outcomes of patients were downloaded. Patients with incomplete clinical information were excluded. The immune score and stromal score were calculated to investigate immune infiltration. The patients were grouped into TMB-high group and the TMB-low group based on the median value of TMB. An immune relevant gene set was obtained from the Immunology Database and Analysis Portal to identify immune-related DEGs. The Cox proportional hazard model and nomogram were applied to establish the risk model. In results: the TMB value was associated with age (p<0.001), clinical stage (p<0.001), N stage (p<0.001), M stage (p=0.003), and immune score (p<0.001). Twenty-nine immune-related DEGs were identified as enriched in immune response-related function or pathway and tumorigenesis signaling. Nine of 29 were determined to establish a riskScore model. The riskScore suggested a positive relationship with the TMB value (p=0.033), immune score (p<0.001), and tumor immune dysfunction and exclusion (TIDE) (p=0.002) and presented an independent prognostic factor (p<0.001, HR=1.04), which predicted the overall survival with good specificity. We concluded that the combination of TMB with transcriptome expression has a predictive and prognostic value for patients treated with ICIs.

Original languageEnglish (US)
JournalJournal of Physiology and Pharmacology
Volume73
Issue number2
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • colon cancer
  • cytotoxic T lymphocytes
  • gene set enrichment analysis
  • immune checkpoint inhibitor
  • microsatellite instability
  • prediction
  • prognosis
  • risk model
  • the Cancer Genome Atlas
  • tumor mutational burden

ASJC Scopus subject areas

  • Physiology
  • Pharmacology

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