HCC subtypes based on the activity changes of immunologic and hallmark gene sets in tumor and nontumor tissues

Author:

Gong Jiao1,Li Rong2,Chen Yaqiong1,Zhuo Zhenjian3,Chen Shuru4,Cao Jing4,Zhang Qi5,Chong Yutian4,Hu Bo1ORCID

Affiliation:

1. Department of Laboratory Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, P.R. China

2. Guangdong Provincial Key Laboratory of Liver Disease Research, Guangdong Province Engineering Laboratory for Transplantation Medicine, Guangzhou 510630, China

3. Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, Guangdong, China

4. Department of Infectious Diseases, Key Laboratory of Liver Disease of Guangdong Province, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, P.R. China

5. Cell-Gene Therapy Translational Medicine Research Center, Key Laboratory of Liver Disease of Guangdong Province, Guangzhou, China

Abstract

Abstract The prognostic role of adjacent nontumor tissue in hepatocellular carcinoma (HCC) patients is still not clear. The activity changes of immunologic and hallmark gene sets in adjacent nontumor tissues may substantially impact on prognosis by affecting proliferation of liver cells and colonization of circulating tumor cells after HCC treatment measures such as hepatectomy. We aimed to identify HCC subtypes and prognostic gene sets based on the activity changes of gene sets in tumor and nontumor tissues, to improve patient outcomes. We comprehensively revealed the activity changes of immunologic and hallmark gene sets in HCC and nontumor samples by gene set variation analysis (GSVA), and identified three clinically relevant subtypes of HCC by nonnegative matrix factorization method (NMF). Patients with subtype 1 had good overall survival, whereas those with subtype 2 and subtype 3 had poor prognosis. Patients with subtype 1 in the validation group also tended to live longer. We also identified three prognostic gene sets in tumor and four prognostic gene sets in nontumor by least absolute shrinkage and selection operator method (LASSO). Interestingly, functional enrichment analysis revealed that in nontumor tissues, genes from four gene sets correlated with immune reaction, cell adhesion, whereas in tumor tissue, genes from three gene sets closely correlated with cell cycle. Our results offer new insights on accurately evaluating prognosis—the important role of gene sets in both tumor and adjacent nontumor tissues, suggesting that when selecting for HCC treatment modality, changes in tumor and nontumor tissues should also be considered, especially after hepatectomy.

Funder

National Key Research and Development Program

Science and Technology Program of Guangzhou, China

R&D Plan of Key Areas in Guangdong Province

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Science and Technology Planning Project of Guangdong Province

Sun Yat-sen University Clinical Research 5010 Programme

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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