A signature of 33 immune‐related gene pairs predicts clinical outcome in hepatocellular carcinoma

Abstract

Objective: Hepatocellular carcinoma (HCC) has become the second most common tumor type that contributes to cancer-related death worldwide. The study aimed to establish a robust immune-related gene pair (IRGP) signature for predicting the prognosis of HCC patients. Methods: Two RNA-seq datasets (The Cancer Genome Atlas Program and International Cancer Genome Consortium) and one microarray dataset (GSE14520) were included in this study. We used a series of immune-related genes from the ImmPort database to construct gene pairs. Lasso penalized Cox proportional hazards regression was employed to develop the best prognostic signature. We assigned patients into two groups with low immune risk and high immune risk. Then, the prognostic ability of the signature was evaluated by a log-rank test and a Cox proportional hazards regression model. Results: After 1000 iterations, the 33-immune gene pair model obtained the highest frequency. As a result, we chose the 33 immune gene pairs to establish the immunerelated prognostic signature. As we expected, the immune-related signature accurately predicted the prognosis of HCC patients, and high-risk groups showed poor prognosis in the training datasets and testing datasets as well as in the validation datasets. Furthermore, the immune-related gene pair (IRGP) signature also showed higher predictive accuracy than three existing prognostic signatures. Conclusion: Our prognostic signature, which reflects the link between the immune microenvironment and HCC patient outcome, is promising for prognosis prediction in HCC.

Development and Validation of An Immune-Related Gene Pair Signature in Skin Cutaneous Melanoma

“…When combined sex, stage, and other clinical factors, the IRGP signature and clinical factor combination showed a higher prognostic accuracy than the individual IRGP signature. In another study of hepatocellular carcinoma [16], researchers also identi ed a signature of 33 IRGPs that can predict clinical outcomes based on TCGA and GEO data. Compared with traditional studies about gene signatures, since pairwise comparison helped to generate our IRGP, the calculation of risk score was decided by the gene expression of the same patient.…”

“…Recently, more and more studies have paid attention to immune-related gene pairs in human cancers. To be speci c, a signature of 33 immune-related gene pairs that can predict clinical outcomes of hepatocellular carcinoma was established by Sun et al [16]. In this study, they used the gene expression levels of IRGs from the TCGA database to construct IRGPs.…”

Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

“…The IRGPs signature was constructed as described by previous study [12]. In a speci c IRGP, if the rst IRG expression level was lower than the second IRG expression level, the score of this IRGP was 0; otherwise, the score was 1.…”

“…Immune-related gene pairs (IRGPs) signature has been established in several cancers including colorectal cancer [11], liver cancer [12] and ovarian cancer [13], and shown well accurate prognosis prediction. So far, there is no research using IRGPs to establish a prognosis signature in LUAD.…”

Development and validation of an immune-related gene pairs signature in lower-grade glioma

“…There exists an inevitable deviation owing to technical biases across sequencing platforms and biological heterogeneity [23]. Thus, researchers have invented the conception of immune-related gene pairs, which can eliminate the disadvantages of data processing and is considered to be a robust prognostic indicator in some tumors [24][25][26][27][28][29].…”