Mining of immunological and prognostic-related biomarker for cervical cancer based on immune cell signatures

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Bioinformatics analysis of immune characteristics in tumors with alternative carcinogenesis pathways induced by human papillomaviruses

BACKGROUND

Human papillomaviruses (HPVs) induce a subset of head and neck squamous cell carcinomas (HNSCC) and anogenital cancers, particularly cervical cancer (CC). The major viral proteins that contribute to tumorigenesis are the E6 and E7 oncoproteins, whose expression is usually enhanced after the integration of viral DNA into the host genome. Recently, an alternative tumorigenesis pathway has been suggested in approximately half of HNSCC and CC cases associated with HPV infection. This pathway is characterized by extrachromosomal HPV persistence and increased expression of the viral E2, E4, and E5 genes. The E6, E7, E5, and E2 proteins have been shown to modify the expression of numerous cellular immune-related genes. The antitumor immune response is a critical factor in the prognosis of HPV-driven cancers, and its characterization may contribute to the prediction and personalization of the increasingly used cancer immunotherapy.

METHODS

We analyzed the immune characteristics of HPV-dependent tumors and their association with carcinogenesis types. Transcriptomic HNSCC and CC datasets from The Cancer Genome Atlas were used for this analysis.

RESULTS

Clustering with immune-related genes resulted in two clusters of HPV16-positive squamous cell carcinomas in both tumor types: cluster 1 had higher activation of immune responses, including stimulation of the antigen processing and presentation pathway, which was associated with higher immune cell infiltration and better overall survival, and cluster 2 was characterized by keratinization. In CC, the distribution of tumor samples into clusters 1 and 2 did not depend on the level of E2/E5 expression, but in HNSCC, most E2/E5-high tumors were localized in cluster 1 and E2/E5-low tumors in cluster 2. Further analysis did not reveal any association between the E2/E5 levels and the expression of immune-related genes.

CONCLUSIONS

Our results suggest that while the detection of immune responses associated with preserved expression of genes encoding components of antigen processing and presentation machinery in HPV-driven tumors may be markers of better prognosis and an important factor in therapy selection, the type of carcinogenesis does not seem to play a decisive role in the induction of antitumor immunity.