Identification of Mutation Landscape and Immune Cell Component for Liver Hepatocellular Carcinoma Highlights Potential Therapeutic Targets and Prognostic Markers.
Identification of Mutation Landscape and Immune Cell Component for Liver Hepatocellular Carcinoma Highlights Potential Therapeutic Targets and Prognostic Markers.
复制标题
肝癌突变景观和免疫细胞成分的鉴定突出了潜在的治疗靶点和预后标志物
DOI:
10.3389/fgene.2021.737965
复制
发表时间:
2021
影响因子:
3.7
通讯作者:
Han P
中科院分区:
文献类型:
--
作者:
Wang H;Jiang W;Wang H;Wei Z;Li H;Yan H;Han P
Liver hepatocellular carcinoma (LIHC) is a primary malignancy, and there is a lack of effective treatment for advanced patients. Although numerous studies exist to reveal the carcinogenic mechanism of LIHC, few studies have integrated multi-omics data to systematically analyze pathogenesis and reveal potential therapeutic targets. Here, we integrated genomic variation data and RNA-seq profiles obtained by high-throughput sequencing to define high- and low-genomic instability samples. The mutational landscape was reported, and the advanced patients of LIHC were characterized by high-genomic instability. We found that the tumor microenvironment underwent metabolic reprograming driven by mutations accumulate to satisfy tumor proliferation and invasion. Further, the co-expression network identifies three mutant long non-coding RNAs as potential therapeutic targets, which can promote tumor progression by participating in specific carcinogenic mechanisms. Then, five potential prognostic markers (RP11-502I4.3, SPINK5, CHRM3, SLC5A12, and RP11-467L13.7) were identified by examining the association of genes and patient survival. By characterizing the immune landscape of LIHC, loss of immunogenicity was revealed as a key factor of immune checkpoint suppression. Macrophages were found to be significantly associated with patient risk scores, and high levels of macrophages accelerated patient mortality. In summary, the mutation-driven mechanism and immune landscape of LIHC revealed by this study will serve precision medicine.
登录
查看更多内容
影响因子:
16.6
作者:
Chatsirisupachai K;Lesluyes T;Paraoan L;Van Loo P;de Magalhães JP
通讯作者:
de Magalhães JP
影响因子:
81.5
作者:
Llovet, Josep M.;Zucman-Rossi, Jessica;Gores, Gregory
通讯作者:
Gores, Gregory
影响因子:
16.6
作者:
Chen Z;Zhou L;Liu L;Hou Y;Xiong M;Yang Y;Hu J;Chen K
通讯作者:
Chen K
影响因子:
14.9
作者:
Frankish A;Diekhans M;Ferreira AM;Johnson R;Jungreis I;Loveland J;Mudge JM;Sisu C;Wright J;Armstrong J;Barnes I;Berry A;Bignell A;Carbonell Sala S;Chrast J;Cunningham F;Di Domenico T;Donaldson S;Fiddes IT;García Girón C;Gonzalez JM;Grego T;Hardy M;Hourlier T;Hunt T;Izuogu OG;Lagarde J;Martin FJ;Martínez L;Mohanan S;Muir P;Navarro FCP;Parker A;Pei B;Pozo F;Ruffier M;Schmitt BM;Stapleton E;Suner MM;Sycheva I;Uszczynska-Ratajczak B;Xu J;Yates A;Zerbino D;Zhang Y;Aken B;Choudhary JS;Gerstein M;Guigó R;Hubbard TJP;Kellis M;Paten B;Reymond A;Tress ML;Flicek P
通讯作者:
Flicek P
影响因子:
4
作者:
Li SQ;Jiang YH;Lin J;Zhang J;Sun F;Gao QF;Zhang L;Chen QG;Wang XZ;Ying HQ
通讯作者:
Ying HQ