Dataset Information

A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers.

ABSTRACT:

Background

Despite much progress in cancer research, its incidence and mortality continue to rise. A robust biomarker that would predict tumor behavior is highly desirable and could improve patient treatment and prognosis.

Methods

In a retrospective bioinformatics analysis involving patients with liver cancer (n?=?839), we developed a prognostic signature consisting of 45 genes associated with tumor-infiltrating lymphocytes and cellular responses to hypoxia. From this gene set, we were able to identify a second prognostic signature comprised of 8 genes. Its performance was further validated in five other cancers: head and neck (n?=?520), renal papillary cell (n?=?290), lung (n?=?515), pancreas (n?=?178) and endometrial (n?=?370).

Results

The 45-gene signature predicted overall survival in three liver cancer cohorts: hazard ratio (HR)?=?1.82, P?=?0.006; HR?=?1.84, P?=?0.008 and HR?=?2.67, P?=?0.003. Additionally, the reduced 8-gene signature was sufficient and effective in predicting survival in liver and five other cancers: liver (HR?=?2.36, P?=?0.0003; HR?=?2.43, P?=?0.0002 and HR?=?3.45, P?=?0.0007), head and neck (HR?=?1.64, P?=?0.004), renal papillary cell (HR?=?2.31, P?=?0.04), lung (HR?=?1.45, P?=?0.03), pancreas (HR?=?1.96, P?=?0.006) and endometrial (HR?=?2.33, P?=?0.003). Receiver operating characteristic analyses demonstrated both signatures superior performance over current tumor staging parameters. Multivariate Cox regression analyses revealed that both 45-gene and 8-gene signatures were independent of other clinicopathological features in these cancers. Combining the gene signatures with somatic mutation profiles increased their prognostic ability.

Conclusions

This study, to our knowledge, is the first to identify a gene signature uniting both tumor hypoxia and lymphocytic infiltration as a prognostic determinant in six cancer types (n?=?2712). The 8-gene signature can be used for patient risk stratification by incorporating hypoxia information to aid clinical decision making.

SUBMITTER: Chang WH

PROVIDER: S-EPMC6327401 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers.

Chang Wai Hoong WH Forde Donall D Lai Alvina G AG

Journal of translational medicine 20190109 1

<h4>Background</h4>Despite much progress in cancer research, its incidence and mortality continue to rise. A robust biomarker that would predict tumor behavior is highly desirable and could improve patient treatment and prognosis.<h4>Methods</h4>In a retrospective bioinformatics analysis involving patients with liver cancer (n = 839), we developed a prognostic signature consisting of 45 genes associated with tumor-infiltrating lymphocytes and cellular responses to hypoxia. From this gene set, we ...[more]

PMID: 30626396

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Project description:Hypoxia, a typical hallmark of numerous tumors, indicates poor infiltration of antitumor lymphocytes, as well as facilitates the development, progression, and drug resistance of malignant cells. Here, the present research was performed to identify novel hypoxia-related molecular markers and their correlation to the tumor immune microenvironment (TIME) in colon cancer. The expression of hypoxia-related gene signature was extracted from The Cancer Genome Atlas (TCGA) COAD cohort. Based on this signature, a risk score model was constructed using the Lasso regression model. Its discrimination ability and stability were validated in another independent cohort (GSE17536) from Gene Expression Omnibus (GEO) database. Moreover, molecular biology experiments (quantitative real-time PCR and multiple immunohistochemistry) were performed to validate the results of bioinformatics analyses. Three hub genes, including PPFIA4, SERPINE1, and STC2, were chosen to build the risk score model. All of these genes were increasingly expressed in the hypoxia subgroup (HS). Compared with the normoxia subgroup (NS), HS had worse pathological features (T, N, M, and stage) and overall survival (OS), more expression of immune checkpoint molecules, poorer infiltration of some pro-inflammation immune cells (CD4+ T cells and CD8+ T cells), and enriched infiltration of M0/M2 macrophages. After the risk model was proven to be valuable and stable, a nomogram was built based on this model and some clinicopathological factors. Moreover, it had been identified that three hub genes were all increasingly expressed in hypoxic conditions by quantitative real-time PCR (qPCR). The results of multiple immunohistochemistry (mIHC) also showed that higher expression of hub genes was associated with poorer infiltration of pro-inflammation immune cells (CD8+ T cells and M1 macrophages) and richer infiltration of anti-inflammation immune cells (Treg cells and M2 macrophages). In conclusion, the present study uncovered the relations among hypoxia, TIME, and clinicopathological features of colon cancer. It might provide new insight and a potential therapeutic target for immunotherapy.

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Dataset Information

A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers.

Background

Methods

Results

Conclusions

Publications

A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers.

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