Multiomics analysis of tumor mutational burden across cancer types

et al. 2022

IJMS

Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Lai

Zhong

et al. 2022

IJMS

“…The number of somatic mutations present in the tumor genome was represented by TMB. High TMB score was associated with the poor prognosis of PAAD patients ( Li L. et al, 2021 ). Meanwhile, high TMB could increase the emergence of neoantigens, thereby enhancing immunotherapy response ( Lin et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Glycolysis-Related LINC02432/Hsa-miR-98–5p/HK2 Axis Inhibits Ferroptosis and Predicts Immune Infiltration, Tumor Mutation Burden, and Drug Sensitivity in Pancreatic Adenocarcinoma

Tan

et al. 2022

Front. Pharmacol.

Pancreatic adenocarcinoma (PAAD) is a malignant cancer with high incidence and mortality. Glycometabolic rearrangements (aerobic glycolysis) is a hallmark of PAAD and contributes to tumorigenesis and progression through numerous mechanisms. This study aimed to identify a novel glycolysis-related lncRNA-miRNA-mRNA ceRNA signature in PAAD and explore its potential molecular function. We first calculated the glycolysis score for each PAAD patient by the ssGSEA algorithm and found that patients with higher hallmark glycolysis scores had poorer prognosis. Subsequently, we obtained a novel glycolysis-related LINC02432/hsa-miR-98–5p/HK2 axis from the TCGA and GEO databases using comprehensive bioinformatics analysis and developed a nomogram to predict overall survival. Furthermore, functional characterization analysis revealed that LINC02432/hsa-miR-98–5p/HK2 axis risk score was negatively correlated with ferroptosis. The tumor immune infiltration analysis suggested positive correlations between ceRNA risk score and infiltrated M0 macrophage levels in PAAD. Correlation analysis found that ceRNA risk scores were positively correlated with four chemokines (CXCL3, CXCL5, CXCL8 and CCL20) and one immune checkpoint gene (SIGLEC15). Meanwhile, tumor mutation burden (TMB), an indicator for predicting response to immunotherapy, was positively correlated with ceRNA risk score. Finally, the drug sensitivity analysis showed that the high-risk score patients might be more sensitive to EGFR, MEK and ERK inhibitors than low-risk score patients. In conclusion, our study suggested that LINC02432/hsa-miR-98–5p/HK2 axis may serve as a novel diagnostic, prognostic, and therapeutic target in PAAD treatment.

“…MSI is another important index for predicting oncogenesis and tumor development. Therefore, TMB and MSI could act as predictive factors for the efficacy of immune checkpoint inhibitors ( Sha et al, 2020 ; Li et al, 2021 ). Here, we observed that the expression of HSF2 was associated with TMB and MSI in several cancer types ( Figure 10 ).…”

Section: Discussionmentioning

confidence: 99%

Pan-Cancer Integrated Analysis of HSF2 Expression, Prognostic Value and Potential Implications for Cancer Immunity

Chen

Fan

et al. 2022

Front. Mol. Biosci.

Heat shock factor 2 (HSF2), a transcription factor, plays significant roles in corticogenesis and spermatogenesis by regulating various target genes and signaling pathways. However, its expression, clinical significance and correlation with tumor-infiltrating immune cells across cancers have rarely been explored. In the present study, we comprehensively investigated the expression dysregulation and prognostic significance of HSF2, and the relationship with clinicopathological parameters and immune infiltration across cancers. The mRNA expression status of HSF2 was analyzed by TCGA, GTEx, and CCLE. Kaplan-Meier analysis and Cox regression were applied to explore the prognostic significance of HSF2 in different cancers. The relationship between HSF2 expression and DNA methylation, immune infiltration of different immune cells, immune checkpoints, tumor mutation burden (TMB), and microsatellite instability (MSI) were analyzed using data directly from the TCGA database. HSF2 expression was dysregulated in the human pan-cancer dataset. High expression of HSF2 was associated with poor overall survival (OS) in BRCA, KIRP, LIHC, and MESO but correlated with favorable OS in LAML, KIRC, and PAAD. The results of Cox regression and nomogram analyses revealed that HSF2 was an independent factor for KIRP, ACC, and LIHC prognosis. GO, KEGG, and GSEA results indicated that HSF2 was involved in various oncogenesis- and immunity-related signaling pathways. HSF2 expression was associated with TMB in 9 cancer types and associated with MSI in 5 cancer types, while there was a correlation between HSF2 expression and DNA methylation in 27 types of cancer. Additionally, HSF2 expression was correlated with immune cell infiltration, immune checkpoint genes, and the tumor immune microenvironment in various cancers, indicating that HSF2 could be a potential therapeutic target for immunotherapy. Our findings revealed the important roles of HSF2 across different cancer types.