Functional Genomic Complexity Defines Intratumor Heterogeneity and Tumor Aggressiveness in Liver Cancer

Abstract

Background: Chronic inflammation and chromosome aneuploidy are major traits of primary liver cancer (PLC), which represent the second most common cause of cancer related death worldwide. Increased cancer fitness and aggressiveness of PLC may be achieved by enhancing tumoral genomic complexity that alters tumor biology.Method: Here, we developed a scoring method, namely functional genomic complexity (FGC), to determine the degree of molecular heterogeneity among 580 liver tumors with diverse ethnicities and etiologies by assessing integrated genomic and transcriptomic data. Results:We found that tumors with higher FGC scores are associated with chromosome instability and TP53 mutations, and a worse prognosis, while tumors with lower FGC scores have elevated infiltrating lymphocytes and a better prognosis. These results indicate that FGC scores may serve as a surrogate to define genomic heterogeneity of PLC linked to chromosomal instability and evasion of immune surveillance. Conclusion:Our findings demonstrate an ability to define genomic heterogeneity and corresponding tumor biology of liver cancer based only on bulk genomic and transcriptomic data.Our data also provide a rationale for applying this approach to survey liver tumor immunity and to stratify patients for immune-based therapy.

Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer

“…To further determine the robustness of an association between VEGFA, as well as its downstream signaling and TME reprogramming, and its association with patient prognosis, we modeled VEGFA signaling in bulk transcriptome data. Diversity score of bulk tumor samples was determined using a recently established method (Kwon et al, 2019). A positive correlation of tumor diversity and VEGFA expression was observed in HCC, but not non-tumor samples, of both the TCGA and LCI cohorts ( Figure S5H).…”

“…To validate the association of VEGFA expression and tumor biodiversity in bulk transcriptomic data, a prerequisite was the evaluation of the degree of tumor diversity. We used an algorithm developed by our group to determine the diversity score (Kwon et al, 2019), which was estimated as the correlation of gene expression and CNVs of each tumor sample. Because CNV data was available for 364 samples of TCGA cohort and 64 samples of LCI cohort, and thus we only measured diversity of these samples.…”

Single-cell atlas of tumor clonal evolution in liver cancer

“…We determined the number of clones within a tumor among different branches of the tumor cell phylogenetic tree. Remarkably, we found that there was an increasing number of clones in tumors from BI-A, BI-B, and BI-C ( Figure S3A), suggesting that tumors in BI-B and BI-C were more diverse and thus likely more aggressive than tumors in BI-A, a feature described in previous studies (Andor et al, 2016;Kwon et al, 2019;Ma et al, 2019). To further assess tumor aggressiveness, we divided patients into two groups according to the number of clones within a tumor.…”

Single-cell multiomics reveals heterogeneous cell states linked to metastatic potential in liver cancer cell lines

“…This highlighted the role of CSC in tumor heterogeneity, prognosis, and hepatic CSC therapy (Zheng et al, 2018). Higher genomic complexity has also been related to a worse prognosis in HCC (Kwon et al, 2019). Single-cell genomics have revealed that genomic complexity results from mutation and copy number variations (CNVs), as well as diverse modes of clonal evolution in HBV-related HCC (Duan et al, 2018).…”