Comprehensive Molecular Analyses of a Six-Gene Signature for Predicting Late Recurrence of Hepatocellular Carcinoma

Abstract

A larger number of patients with stages I–III hepatocellular carcinoma (HCC) experience late recurrence (LR) after surgery. We sought to develop a novel tool to stratify patients with different LR risk for tailoring decision-making for postoperative recurrence surveillance and therapy modalities. We retrospectively enrolled two independent public cohorts and 103 HCC tissues. Using LASSO logical analysis, a six-gene model was developed in the The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) and independently validated in GSE76427. Further experimental validation using qRT-PCR assays was performed to ensure the robustness and clinical feasible of this signature. We developed a novel LR-related signature consisting of six genes. This signature was validated to be significantly associated with dismal recurrence-free survival in three cohorts TCGA-LIHC, GSE76427, and qPCR assays [HR: 2.007 (1.200–3.357), p = 0.008; HR: 2.171 (1.068, 4.412), p-value = 0.032; HR: 3.383 (2.100, 5.450), p-value <0.001]. More importantly, this signature displayed robust discrimination in predicting the LR risk, with AUCs being 0.73 (TCGA-LIHC), 0.93 (GSE76427), and 0.85 (in-house cohort). Furthermore, we deciphered the specific landscape of molecular alterations among patients in nonrecurrence (NR) and LR group to analyze the mechanism contributing to LR. For high-risk group, we also identified several potential drugs with specific sensitivity to high- and low-risk groups, which is vital to improve prognosis of LR-HCC after surgery. We discovered and experimentally validated a novel gene signature with powerful performance for identifying patients at high LR risk in stages I–III HCC.

Integrated Analysis of Multi-Omics Alteration, Immune Profile, and Pharmacological Landscape of Pyroptosis-Derived lncRNA Pairs in Gastric Cancer

“…With the combination of multi-omics with advanced algorithms, researchers can explore the molecular characteristics of GC patients in detail. This has led to the emergence of abundant prognostic and predictive gene expression signatures (Liu et al, 2021b;Wang et al, 2021;Zhang et al, 2021;Zhao et al, 2021). Nevertheless, these signatures are difficult to implement clinically due to the difficulty in unifying sequencing platforms and samples.…”

Clinical Significance and Immune Landscape of a Pyroptosis-Derived LncRNA Signature for Glioblastoma

“…Moreover, we also detected enhanced levels of immune check points in the high-risk group. Tumor immune microenvironment, mostly consisting of stromal immune cells, plays vital roles in the proliferation, migration, and invasion of tumors and may be a crucial determinant of response to immune checkpoint blockade therapy ( Mohme et al, 2020 ; Liu R. et al, 2021 ; Zhang et al, 2021 ). Unsurprisingly, the high-risk group showed higher sensitivity to immunotherapy, which indicated our model points out new directions and shows optimistic clinical application prospects in distinguishing patients suitable for immunotherapy.…”

Ferroptosis Mediation Patterns Reveal Novel Tool to Implicate Immunotherapy and Multi-Omics Characteristics in Bladder Cancer

“…With the rapid development of genetic sequencing techniques, genetic signatures derived from transcriptome information have been reported to predict different treatment responses. ( Bailey et al, 2018 ; Zhang Y et al, 2021 ; Zhang M et al, 2021 ). We reported for the first time that ferroptosis-related genes played predictive roles in bladder cancer, and the mechanisms underlying ferroptosis provide promising avenues for developing novel treatment strategies.…”

“…The GSVA was a popular bioinformatics algorithm, which was extensively utilized in cancer-related studies. ( Liu et al, 2021a ; Liu et al, 2021b ; Liu et al, 2021c ; Wang et al, 2021 ; Zhang Y et al, 2021 ). GSVA was performed to examine different biological activities among the three ferroptosis mediation patterns using the “GSVA” R package.…”