Exploration of gene expression profiles and immune microenvironment between high and low tumor mutation burden groups in prostate cancer.

Tumor mutation burden (TMB) has been established as a biomarker for response to immune therapy and prognosis in various cancers. However, the association between TMB and prognosis of prostate cancer (PCa) remains unclear. This study aimed to investigate the impact of TMB in biochemical recurrence (BCR) and the immune microenvironment in high and low TMB groups. Mutation data, gene expression, clinicopathological information were downloaded from The Cancer Genome Atlas (TCGA). Mutation types and TMB values were identified. All samples were divided into high and low TMB groups with median TMB value as the cutoff point. The BCR-free survival rates, Differentially expressed genes (DEGs) and immune cells infiltrations in different TMB groups were identified. The most common variant type and SNV were single nucleotide polymorphism and C > T. respectively. High TMB level was significantly associated with older age, positive lymph node, higher International Society of Urological Pathology (ISUP) grade, advanced stage and poor BCR-free survival. 132 DEGs were identified and involved in receptor ligand activity and hormone activity. High expression of six core genes UBE2C, PLK1, CDC20, BUB1, CDK1 and HJURP were associated with worse BCR-free survival. The analysis of immune cells infiltration revealed that the amount of activated CD4+ memory T cells was significantly different in high and low TMB groups. The current study comprehensively described the summary of mutation and TMB related DEGs in PCa. TMB was associated with BCR-free survival and the infiltration of activated CD4+ memory T cells in the immune microenvironment.

Luo C ，Chen J ，Chen L 《-》

Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer.

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the prognosis of HNSCC remains bleak. Numerous studies revealed that the tumor mutation burden (TMB) could predict the survival outcomes of a variety of tumors. Objectives: This study aimed to investigate the TMB and immune cell infiltration in these patients and construct an immune-related genes (IRGs) prognostic model. Methods: The expression data of 546 HNSCC patients were obtained from The Cancer Genome Atlas (TCGA) database. All patients were divided into high- and low- TMB groups, and the relationship between TMB and clinical relevance was further analyzed. The differentially expressed genes (DEGs) were identified using the R software package, limma. Functional enrichment analyses were conducted to identify the significantly enriched pathways between two groups. CIBERSORT algorithm was adopted to calculate the abundance of 22 leukocyte subtypes. The IRGs prognostic model was constructed via the multivariate Cox regression analysis. Results: Missense mutation and single nucleotide variants (SNV) were the most predominant mutation types in HNSCC. TP53, TTN, and FAT1 were the most frequently mutated genes. Patients with high TMB were observed with worse survival outcomes. The functional analysis of TMB associated DEGs showed that the identified DEGs mainly involved in spliceosome, RNA degradation, proteasome, and RNA polymerase pathways. We observed that macrophages, T cells CD8, and T cells CD4 memory were the most commonly infiltrated subtypes of immune cells in HNSCC. Finally, an IRGs prognostic model was constructed, and the AUC of the ROC curve was 0.635. Conclusions: Our results suggest that high TMB is associated with poor prognosis in HNSCC patients. The constructed model has potential prognostic value for the prognosis of these individuals, and it needs to be further validated in large-scale and prospective studies.

Jiang AM ，Ren MD ，Liu N ，Gao H ，Wang JJ ，Zheng XQ ，Fu X ，Liang X ，Ruan ZP ，Tian T ，Yao Y ... -  《International Journal of Medical Sciences》

Prognostic analysis of tumor mutation burden and immune infiltration in hepatocellular carcinoma based on TCGA data.

Liu S ，Tang Q ，Huang J ，Zhan M ，Zhao W ，Yang X ，Li Y ，Qiu L ，Zhang F ，Lu L ，He X ... -  《Aging-US》

Exploration of the Tumor Mutational Burden as a Prognostic Biomarker and Related Hub Gene Identification in Prostate Cancer.

Wang L ，Yao Y ，Xu C ，Wang X ，Wu D ，Hong Z ... -  《-》

The prognostic value of TMB and the relationship between TMB and immune infiltration in head and neck squamous cell carcinoma: A gene expression-based study.

Whether tumor mutation burden (TMB) affects prognosis and immune infiltration of tumor patients is controversial. We designed and conducted a multi-omics study with the aim of investigating the prognostic value of TMB and the relationship between TMB and immune infiltration in head and neck squamous cell carcinoma (HNSCC). TMB scores were calculated from the mutation data of 506 HNSCC samples from The Cancer Genome Atlas (TCGA), and the patients were divided into low- and high-TMB groups according to the TMB score quartiles. Differentially expressed genes (DEGs) between the low-TMB and high-TMB groups were identified. Immune cell infiltration and survival analyses were conducted between groups. High TMB in HNSCC patients was associated with a poor prognosis, large primary tumor size, advanced clinical stage and a human papillomavirus (HPV)-negative status. A total of 576 DEGs were identified, and gene set enrichment analysis (GSEA) revealed that the DEGs in the low-TMB group were enriched in immune-related pathways. Four hub genes were significantly associated with prognosis, and mutations in these genes affected immune infiltration. The estimated fractions of B memory cells and CD4+ memory resting cells were higher in the low-TMB group than in the high-TMB group, and B cell and CD4+T cell infiltration was positively correlated with prognosis in HNSCC patients. HNSCC patients with low TMB have better prognoses than those with high TMB, and TMB might affect B cell and CD4+T cell infiltration.

Zhang L ，Li B ，Peng Y ，Wu F ，Li Q ，Lin Z ，Xie S ，Xiao L ，Lin X ，Ou Z ，Cai T ，Rong H ，Fan S ，Li J ... -  《-》