Individualized prognostic signature for pancreatic carcinoma validated by integrating immune-related gene pairs (IRGPs)

Prognostic value and immunological role of Kruppel-like transcription factor 9 gene in pan-carcinoma

OBJECTIVE

To investigate the correlation between the expression of Kruppel-like transcription factor 9 (KLF9) and the prognostic value of tumors as well as its relationship with tumor immune invasion.

METHODS

A series of bioinformatics methods were used to analyze the relationship between KLF9 and tumor prognosis, tumor mutation burden, microsatellite instability (MSI), and immune cell infiltration in multiple carcinomas.

RESULTS

In multiple tumor tissues, the expression of KLF9 was lower compared with paracancerous tissues. Therefore, KLF9 can serve as a protective factor to improve the prognosis of carcinoma patients with certain tumor types. KLF9 was closely related to the clinical staging of various carcinomas. The expression of KLF9 was not only associated with tumor mutation burden and MSI in some tumor types, but also positively correlated with immune and stromal cells in multiple tumors. Further studies have found that, the level of immune cell infiltration was significantly related to the expression of KLF9.

CONCLUSION

KLF9 can affect the prognosis of pan-carcinoma, which is related to immune invasion. Therefore, KLF9 can be used as a potential biomarker for the prognosis of pan-carcinoma.

An immune-related gene prognostic risk index for pancreatic adenocarcinoma

Objective

Our goal is to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD), and to clarify the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy.

Method

Through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and univariate Cox regression analysis, 16 immune-related hub genes were identified using the Cancer Genome Atlas (TCGA) PAAD dataset (n = 182) and immune gene set. From these genes, we constructed an IRGPRI with the Cox regression method and the IRGPRI was verified based on the Gene Expression Omnibus (GEO) dataset (n = 45). Then, we analyzed the immune and molecular features and the benefit of ICI therapy in IRGPRI-defined subgroups.

Results

Five genes, including S100A16, CD40, VCAM1, TNFRSF4 and TRAF1 were used to construct IRGPRI. As with the results of the GEO cohort, the overall survival (OS) was more favorable in low IRGPRI patients versus high IRGPRI patients. The composite results pointed out that low IRGPRI was associated with immune response-related pathways, high level of CTLA4, low KRAS and TP53 mutation rate, more infiltration of activated memory CD4⁺ T cells, CD8⁺ T cells, and more benefits from ICIs therapy. In comparison, high IRGPRI was associated with cancer-related pathways, low expression of CTLA4, high KRAS and TP53 mutation rate, more infiltration of M2 macrophages, and less benefit from ICIs therapies.

Conclusion

This IRGPRI is an encouraging biomarker to define the prognosis, immune and molecular features, and benefits from ICIs treatments in PAAD.

The Trinity: Interplay among Cancer Cells, Fibroblasts, and Immune Cells in Pancreatic Cancer and Implication of CD8+ T Cell-Orientated Therapy

The microenvironment in tumors is complicated and is constituted by different cell types and stromal proteins. Among the cell types, the abundance of cancer cells, fibroblasts, and immune cells is high and these cells work as the “Trinity” in promoting tumorigenesis. Although unidirectional or bidirectional crosstalk between two independent cell types has been well characterized, the multi-directional interplays between cancer cells, fibroblasts, and immune cells in vitro and in vivo are still unclear. We summarize recent studies in addressing the interaction of the “Trinity” members in the tumor microenvironment and propose a functional network for how these members communicate with each other. In addition, we discuss the underlying mechanisms mediating the interplay. Moreover, correlations of the alterations in the distribution and functionality of cancer cells, fibroblasts, and immune cells under different circumstances are reviewed. Finally, we point out the future application of CD8⁺ T cell-oriented therapy in the treatment of pancreatic cancer.

Prediction of clinical prognosis in cutaneous melanoma using an immune-related gene pair signature

Cutaneous melanoma (CM) is a malignant and aggressive skin cancer that is the leading cause of skin cancer-related deaths. Increasing evidence shows that immunity plays a vital role in the prognosis of CM. In this study, we developed an immune-related gene pair (IRGP) signature to predict the clinical prognosis of patients with CM. Immune-related genes from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected to construct the IRGPs, and patients with CM in these two cohorts were assigned to low- and high-risk subgroups. Moreover, we investigated the IRGPs and their individualized prognostic signatures using Kaplan-Meier survival analysis, univariate and multivariate Cox analyses, and analysis of immune cell infiltration in CM. A 41-IRGP signature was constructed from 2498 immune genes that could significantly predict the overall survival of patients with CM in both the TCGA and GEO cohorts. Immune infiltration analysis indicated that several immune cells, especially M1 macrophages and activated CD4 T cells, were significantly associated with the prognostic effect of the IRGP signature in patients with CM. Overall, the IRGP signature constructed in this study was useful for determining the prognosis of patients with CM and for providing further understanding of CM immunotherapy.

Identification of Immune-Related LncRNA Pairs for Predicting Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma

Long noncoding RNAs (lncRNAs) have multiple functions with regard to the cancer immunity response and the tumor microenvironment. The prognosis of head and neck squamous cell carcinoma (HNSCC) is still poor currently, and it may be effective to predict the clinical outcome and immunotherapeutic response of HNSCC by immunogenic analysis. Therefore, by using univariate COX analysis and Lasso Cox regression, we identified a signature consisting of 21 immune-related lncRNA pairs (IRLPs) that predicted clinical outcome and Immunotherapeutic response in HNSCC. Specifically, it was associated with immune cell infiltration (i.e., T cells CD4 memory resting, CD8 T cells, macrophages M0, M2, and NK cells), and more importantly this signature was strongly related with immune checkpoint inhibitors (ICIs) [such as PDCD1 (r = -0.35, P < 0.001), CTLA4 (r = -0.26, P < 0.001), LAG3 (r = -0.22, P < 0.001) and HAVCR2 (r = -0.2, P < 0.001)] and immunotherapy-related biomarkers (MMR and HLA). The present study highlighted the value of the 21 IRLPs signature as a predictor of prognosis and immunotherapeutic response in HNSCC.