Llovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E, Roayaie S, et al. Hepatocellular carcinoma. Nat Rev Dis Primers. 2021;7:6.
Article
Google Scholar
Yang C, Zhang H, Zhang L, Zhu AX, Bernards R, Qin W, et al. Evolving therapeutic landscape of advanced hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol. 2022. https://doi.org/10.1038/s41575-022-00704-9
Akhoundi M, Mohammadi M, Sahraei SS, Sheykhhasan M, Fayazi N. CAR T cell therapy as a promising approach in cancer immunotherapy: challenges and opportunities. Cell Oncol (Dordr). 2021;44:495–523.
Article
CAS
Google Scholar
Yang C, Guo Y, Qian R, Huang Y, Zhang L, Wang J, et al. Mapping the landscape of synthetic lethal interactions in liver cancer. Theranostics. 2021;11:9038–53.
Article
CAS
Google Scholar
Yang C, Zhang H, Chen M, Wang S, Qian R, Zhang L, et al. A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer. Elife. 2022;11:e71880.
Article
CAS
Google Scholar
Marusyk A, Janiszewska M, Polyak K. Intratumor heterogeneity: the Rosetta Stone of Therapy Resistance. Cancer Cell. 2020;37:471–84.
Article
CAS
Google Scholar
Craig AJ, von Felden J, Garcia-Lezana T, Sarcognato S, Villanueva A. Tumour evolution in hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol. 2020;17:139–52.
Article
Google Scholar
Rebouissou S, Nault JC. Advances in molecular classification and precision oncology in hepatocellular carcinoma. J Hepatol. 2020;72:215–29.
Article
CAS
Google Scholar
Torrecilla S, Sia D, Harrington AN, Zhang Z, Cabellos L, Cornella H, et al. Trunk mutational events present minimal intra- and inter-tumoral heterogeneity in hepatocellular carcinoma. J Hepatol. 2017;67:1222–31.
Article
Google Scholar
Dong LQ, Peng LH, Ma LJ, Liu DB, Zhang S, Luo SZ, et al. Heterogeneous immunogenomic features and distinct escape mechanisms in multifocal hepatocellular carcinoma. J Hepatol. 2020;72:896–908.
Article
CAS
Google Scholar
Friemel J, Rechsteiner M, Frick L, Böhm F, Struckmann K, Egger M, et al. Intratumor heterogeneity in hepatocellular carcinoma. Clin Cancer Res. 2015;21:1951–61.
Article
CAS
Google Scholar
Ding X, He M, Chan AWH, Song QX, Sze SC, Chen H, et al. Genomic and epigenomic features of primary and recurrent hepatocellular carcinomas. Gastroenterol. 2019;157:1630-1645.e6.
Article
CAS
Google Scholar
Zhang Q, Lou Y, Yang J, Wang J, Feng J, Zhao Y, et al. Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas. Gut. 2019;68:2019–31.
Article
CAS
Google Scholar
Losic B, Craig AJ, Villacorta-Martin C, Martins-Filho SN, Akers N, Chen X, et al. Intratumoral heterogeneity and clonal evolution in liver cancer. Nat Commun. 2020;11:291.
Article
CAS
Google Scholar
Lin DC, Mayakonda A, Dinh HQ, Huang P, Lin L, Liu X, et al. Genomic and epigenomic heterogeneity of hepatocellular carcinoma. Cancer Res. 2017;77:2255–65.
Article
CAS
Google Scholar
Buczak K, Ori A, Kirkpatrick JM, Holzer K, Dauch D, Roessler S, et al. Spatial tissue proteomics quantifies inter- and intratumor heterogeneity in hepatocellular carcinoma (HCC). Mol Cell Proteomics. 2018;17:810–25.
Article
CAS
Google Scholar
Zhang Q, Lou Y, Bai XL, Liang TB. Intratumoral heterogeneity of hepatocellular carcinoma: from single-cell to population-based studies. World J Gastroenterol. 2020;26:3720–36.
Article
CAS
Google Scholar
Gao Q, Wang ZC, Duan M, Lin YH, Zhou XY, Worthley DL, et al. Cell culture system for analysis of genetic heterogeneity within hepatocellular carcinomas and response to pharmacologic agents. Gastroenterol. 2017;152:232-242.e4.
Article
CAS
Google Scholar
Li L, Knutsdottir H, Hui K, Weiss MJ, He J, Philosophe B, et al. Human primary liver cancer organoids reveal intratumor and interpatient drug response heterogeneity. JCI Insight. 2019;4. https://doi.org/10.1172/jci.insight.121490
Huang A, Zhao X, Yang XR, Li FQ, Zhou XL, Wu K, et al. Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma. J Hepatol. 2017;67:293–301.
Article
CAS
Google Scholar
Nguyen PHD, Ma S, Phua CZJ, Kaya NA, Lai HLH, Lim CJ, et al. Intratumoural immune heterogeneity as a hallmark of tumour evolution and progression in hepatocellular carcinoma. Nat Commun. 2021;12:227.
Article
CAS
Google Scholar
Ma L, Hernandez MO, Zhao Y, Mehta M, Tran B, Kelly M, et al. Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer. Cancer Cell. 2019;36:418-430.e6.
Article
CAS
Google Scholar
Li M, Zhang Z, Li L, Wang X. An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles. Commun Biol. 2020;3:505.
Article
Google Scholar
Bachtiary B, Boutros PC, Pintilie M, Shi W, Bastianutto C, Li JH, et al. Gene expression profiling in cervical cancer: an exploration of intratumor heterogeneity. Clin Cancer Res. 2006;12:5632–40.
Article
CAS
Google Scholar
Yan W, Shih J, Rodriguez-Canales J, Tangrea MA, Player A, Diao L, et al. Three-dimensional mRNA measurements reveal minimal regional heterogeneity in esophageal squamous cell carcinoma. Am J Pathol. 2013;182:529–39.
Article
CAS
Google Scholar
Dunne PD, Alderdice M, O’Reilly PG, Roddy AC, McCorry AMB, Richman S, et al. Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification. Nat Commun. 2017;8:15657.
Article
CAS
Google Scholar
Biswas D, Birkbak NJ, Rosenthal R, Hiley CT, Lim EL, Papp K, et al. A clonal expression biomarker associates with lung cancer mortality. Nat Med. 2019;25:1540–8.
Article
CAS
Google Scholar
Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, et al. Integrated proteogenomic characterization of HBV-related hepatocellular carcinoma. Cell. 2019;179:1240.
Article
CAS
Google Scholar
Schulze K, Imbeaud S, Letouzé E, Alexandrov LB, Calderaro J, Rebouissou S, et al. Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets. Nat Genet. 2015;47:505–11.
Article
CAS
Google Scholar
Fujimoto A, Furuta M, Totoki Y, Tsunoda T, Kato M, Shiraishi Y, et al. Whole-genome mutational landscape and characterization of noncoding and structural mutations in liver cancer. Nat Genet. 2016;48:500–9.
Article
CAS
Google Scholar
Ally A, Balasundaram M, Carlsen R, Chuah E, Clarke A, Dhalla N, et al. Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell. 2017;169(1327–1341):e23.
Google Scholar
Roessler S, Long EL, Budhu A, Chen Y, Zhao X, Ji J, et al. Integrative genomic identification of genes on 8p associated with hepatocellular carcinoma progression and patient survival. Gastroenterol. 2012;142:957-966.e12.
Article
CAS
Google Scholar
Villa E, Critelli R, Lei B, Marzocchi G, Cammà C, Giannelli G, et al. Neoangiogenesis-related genes are hallmarks of fast-growing hepatocellular carcinomas and worst survival Results from a prospective study. Gut. 2016;65:861–9.
Article
CAS
Google Scholar
Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 2011;12:323.
Article
CAS
Google Scholar
Liu J, Lichtenberg T, Hoadley KA, Poisson LM, Lazar AJ, Cherniack AD, et al. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics. Cell. 2018;173:400-416.e11.
Article
CAS
Google Scholar
Shen YC, Hsu CL, Jeng YM, Ho MC, Ho CM, Yeh CP, et al. Reliability of a single-region sample to evaluate tumor immune microenvironment in hepatocellular carcinoma. J Hepatol. 2020;72:489–97.
Article
CAS
Google Scholar
Villanueva A, Hoshida Y, Battiston C, Tovar V, Sia D, Alsinet C, et al. Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma. Gastroenterol. 2011;140:1501-12.e2.
Article
CAS
Google Scholar
Shi L, Zhang Y, Feng L, Wang L, Rong W, Wu F, et al. Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma. Oncotarget. 2017;8:34844–57.
Article
Google Scholar
Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37:907–15.
Article
CAS
Google Scholar
Liao Y, Smyth GK, Shi W. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res. 2013;41:e108.
Article
Google Scholar
Barry WT, Kernagis DN, Dressman HK, Griffis RJ, Hunter JD, Olson JA, et al. Intratumor heterogeneity and precision of microarray-based predictors of breast cancer biology and clinical outcome. J Clin Oncol. 2010;28:2198–206.
Article
Google Scholar
Quek K, Li J, Estecio M, Zhang J, Fujimoto J, Roarty E, et al. DNA methylation intratumor heterogeneity in localized lung adenocarcinomas. Oncotarget. 2017;8:21994–2002.
Article
Google Scholar
Morrissy AS, Cavalli FMG, Remke M, Ramaswamy V, Shih DJH, Holgado BL, et al. Spatial heterogeneity in medulloblastoma. Nat Genet. 2017;49:780–8.
Article
CAS
Google Scholar
Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM 3rd, et al. Comprehensive integration of single-cell data. Cell. 2019;177:1888-1902.e21.
Article
CAS
Google Scholar
Gao R, Bai S, Henderson YC, Lin Y, Schalck A, Yan Y, et al. Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes. Nat Biotechnol. 2021;39:599–608.
Article
CAS
Google Scholar
Fox J, Carvalho MS. The RcmdrPlugin.survival Package: extending the R Commander interface to survival analysis. J Stat Softw. 2012;49:1–32.
Article
Google Scholar
Blanche P, Dartigues JF, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med. 2013;32:5381–97.
Article
Google Scholar
Ho DW, Tsui YM, Chan LK, Sze KM, Zhang X, Cheu JW, et al. Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma. Nat Commun. 2021;12:3684.
Article
CAS
Google Scholar
Sun Y, Wu L, Zhong Y, Zhou K, Hou Y, Wang Z, et al. Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma. Cell. 2021;184:404-421.e16.
Article
CAS
Google Scholar
Sharma A, Merritt E, Hu X, Cruz A, Jiang C, Sarkodie H, et al. Non-genetic intra-tumor heterogeneity is a major predictor of phenotypic heterogeneity and ongoing evolutionary dynamics in lung tumors. Cell Rep. 2019;29:2164-2174.e5.
Article
CAS
Google Scholar
Iacobuzio-Donahue CA, Litchfield K, Swanton C. Intratumor heterogeneity reflects clinical disease course. Nat Cancer. 2020;1:3–6.
Article
Google Scholar
Gerlinger M, Rowan AJ, Horswell S, Math M, Larkin J, Endesfelder D, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366:883–92.
Article
CAS
Google Scholar
Gerlinger M, Horswell S, Larkin J, Rowan AJ, Salm MP, Varela I, et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet. 2014;46:225–33.
Article
CAS
Google Scholar
Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK, Veeriah S, et al. Tracking the evolution of non-small-cell lung cancer. N Engl J Med. 2017;376:2109–21.
Article
CAS
Google Scholar
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12:453–7.
Article
CAS
Google Scholar
Paijens ST, Vledder A, de Bruyn M, Nijman HW. Tumor-infiltrating lymphocytes in the immunotherapy era. Cell Mol Immunol. 2021;18:842–59.
Article
CAS
Google Scholar
Alvarez MJ, Shen Y, Giorgi FM, Lachmann A, Ding BB, Ye BH, et al. Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nat Genet. 2016;48:838–47.
Article
CAS
Google Scholar
Obradovic A, Vlahos L, Laise P, Worley J, Tan X, Wang A, et al. PISCES: A pipeline for the systematic, protein activity-based analysis of single cell RNA sequencing data. bioRxiv. 2021;6:22.
Google Scholar
Kolde R, Laur S, Adler P, Vilo J. Robust rank aggregation for gene list integration and meta-analysis. Bioinform. 2012;28:573–80.
Article
CAS
Google Scholar
Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres-Garcia W, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612.
Article
Google Scholar
Hayat SMG, Bianconi V, Pirro M, Jaafari MR, Hatamipour M, Sahebkar A. CD47: role in the immune system and application to cancer therapy. Cell Oncol (Dordr). 2020;43:19–30.
Article
CAS
Google Scholar
Vonderheide RH. CD40 agonist antibodies in cancer immunotherapy. Annu Rev Med. 2020;71:47–58.
Article
CAS
Google Scholar
van Malenstein H, Gevaert O, Libbrecht L, Daemen A, Allemeersch J, Nevens F, et al. A seven-gene set associated with chronic hypoxia of prognostic importance in hepatocellular carcinoma. Clin Cancer Res. 2010;16:4278–88.
Article
Google Scholar
Nault JC, De Reyniès A, Villanueva A, Calderaro J, Rebouissou S, Couchy G, et al. A hepatocellular carcinoma 5-gene score associated with survival of patients after liver resection. Gastroenterology. 2013;145:176–87.
Article
CAS
Google Scholar
Fang Q, Chen H. Development of a novel autophagy-related prognostic signature and nomogram for hepatocellular carcinoma. Front Oncol. 2020;10:591356.
Article
Google Scholar
Fang Q, Chen H. The significance of m6A RNA methylation regulators in predicting the prognosis and clinical course of HBV-related hepatocellular carcinoma. Mol Med. 2020;26:60.
Article
Google Scholar
Pan Q, Qin F, Yuan H, He B, Yang N, Zhang Y, et al. Normal tissue adjacent to tumor expression profile analysis developed and validated a prognostic model based on Hippo-related genes in hepatocellular carcinoma. Cancer Med. 2021;10:3139–52.
Article
CAS
Google Scholar
Kudo M, Izumi N, Ichida T, Ku Y, Kokudo N, Sakamoto M, et al. Report of the 19th follow-up survey of primary liver cancer in Japan. Hepatol Res. 2016;46:372–90.
Article
Google Scholar
Zhai W, Lai H, Kaya NA, Chen J, Yang H, Lu B, et al. Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma: the PLANET study. Natl Sci Rev. 2022;9:192.
Article
Google Scholar
Bassiouni R, Gibbs LD, Craig DW, Carpten JD, McEachron TA. Applicability of spatial transcriptional profiling to cancer research. Mol Cell. 2021;81:1631–9.
Article
CAS
Google Scholar
Mitra A, Andrews MC, Roh W, De Macedo MP, Hudgens CW, Carapeto F, et al. Spatially resolved analyses link genomic and immune diversity and reveal unfavorable neutrophil activation in melanoma. Nat Commun. 2020;11:1839.
Article
CAS
Google Scholar
Mroz EA, Rocco JW. MATH, a novel measure of intratumor genetic heterogeneity, is high in poor-outcome classes of head and neck squamous cell carcinoma. Oral Oncol. 2013;49:211–5.
Article
CAS
Google Scholar
Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, et al. PyClone: statistical inference of clonal population structure in cancer. Nat Methods. 2014;11:396–8.
Article
CAS
Google Scholar
Andor N, Harness JV, Müller S, Mewes HW, Petritsch C. EXPANDS: expanding ploidy and allele frequency on nested subpopulations. Bioinformatics. 2014;30:50–60.
Article
CAS
Google Scholar
Park Y, Lim S, Nam JW, Kim S. Measuring intratumor heterogeneity by network entropy using RNA-seq data. Sci Rep. 2016;6:37767.
Article
CAS
Google Scholar
Wolf Y, Samuels Y. Intratumor heterogeneity and antitumor immunity shape one another bidirectionally. Clin Cancer Res. 2022;28:2994–3001.
Article
CAS
Google Scholar
Ran X, Xiao J, Zhang Y, Teng H, Cheng F, Chen H, et al. Low intratumor heterogeneity correlates with increased response to PD-1 blockade in renal cell carcinoma. Ther Adv Med Oncol. 2020;12:1758835920977117.
Article
CAS
Google Scholar
Lin Z, Meng X, Wen J, Corral JM, Andreev D, Kachler K, et al. Intratumor heterogeneity correlates with reduced immune activity and worse survival in melanoma patients. Front Oncol. 2020;10:596493.
Article
Google Scholar
Cheng AL, Qin S, Ikeda M, Galle PR, Ducreux M, Kim TY, et al. Updated efficacy and safety data from IMbrave150: atezolizumab plus bevacizumab vs. sorafenib for unresectable hepatocellular carcinoma. J Hepatol. 2022;76:862–73.
Article
CAS
Google Scholar
Schumacher TN, Thommen DS. Tertiary lymphoid structures in cancer. Sci. 2022;375:eabf9419.
Article
CAS
Google Scholar
Yang C, Wang C, Hang H. Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer. 10.5281/zenodo.7336311, Zenodo. 2022. https://zenodo.org/record/7336311#.Y3g5l-RBzZS. Accessed 19 Nov 2022.
Yang C, Wang C, Hang H. Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer. OEP002956, National Omics Data Encyclopedia. 2022. http://www.biosino.org/node/project/detail/OEP002956. Accessed 3 Jan 2022.
Yang C, Wang C, Hang H. Github. 2022. https://github.com/YangJAT/LHRS. Accessed 27 Nov 2022.