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Cross Analysis of Genomic-Pathologic Features on Multiple Primary Hepatocellular Carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is a prevalent malignancy cancer worldwide with a poor prognosis. Hepatic resection is indicated as a potentially curative option for HCC patients in the early stage. However, due to multiple nodules, it leads to clinical challenges for surgical management. Approximately 41%-75% of HCC cases are multifocal at initial diagnosis, which may arise from multicentric occurrence (MO-HCC) or intrahepatic metastasis (IM-HCC) pattern with significantly different clinical outcomes. Effectively differentiating the two mechanisms is crucial to prioritize the allocation of surgery for multifocal HCC. In this study, we collected a multifocal hepatocellular carcinoma cohort of 17 patients with a total of 34 samples. We performed whole-exome sequencing and staining of pathological HE sections for each lesion. Reconstruction of the clonal evolutionary pattern using genome mutations showed that the intrahepatic metastogenesis pattern had a poorer survival performance than independent origins, with variants in the TP53, ARID1A, and higher CNV variants occurring more significantly in the metastatic pattern. Cross-modality analysis with pathology showed that molecular classification results were consistent with pathology results in 70.6% of patients, and we found that pathology results could further complement the classification for undefined patterns of occurrence. Based on these results, we propose a model to differentiate the pattern of multifocal hepatocellular carcinoma based on the pathological results and genome mutations information, which can provide guidelines for diagnosing and treating multifocal hepatocellular carcinoma.

SUBMITTER: Ren F

PROVIDER: S-EPMC9251469 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and Aims:The purpose of our study was to examine the histopathologic characteristics of hepatocellular carcinoma (HCC) with irregular rim-like arterial phase enhancement (IRE), which has been reported to be associated with more aggressive tumor behavior. Methods:We investigated 84 pathologically confirmed HCCs in 84 patients who underwent curative hepatic resection after gadoxetate-enhanced magnetic resonance imaging between January 2008 and February 2013. Two abdominal radiologists independently reviewed these images and classified HCCs into two categories: HCC showing IRE (IRE-HCC) and HCC showing hypoenhancement or diffuse arterial enhancement (non-IRE-HCC). Twenty-two HCCs were classified as IRE-HCCs, and 51 were classified as non-IRE-HCCs concordantly by both reviewers. The remaining 11 HCCs, on whose radiologic classifications the reviewers disagreed, were classified as HCCs with intermediate enhancement patterns. The HCC clinicopathologic characteristics and patient outcomes were then compared. Results:IRE-HCCs showed more frequent microvascular invasion (91 vs. 35%), lower microvascular density (246.5 vs. 426.5/mm2), higher proportions of sinusoid-like microvascular pattern (55 vs. 0%) and macrotrabecular pattern (45 vs. 0%), and larger areas of tumor necrosis (15 vs. 0%) and fibrous stroma (8.3 vs. 2.1%) than non-IRE-HCCs. IRE-HCCs also expressed higher levels of immunomarkers of hypoxia (carbonic anhydrase IX, 64 vs. 8%) and stemness (EpCAM, 50 vs. 20%). p values were < 0.001 for all comparisons except for EpCAM (p = 0.026). HCCs with intermediate enhancement patterns showed mixed/intermediate pathologic features from both IRE- and non-IRE-HCCs. IRE-HCC patients showed poorer 5-year disease-free survival after curative resection than non-IRE-HCC patients (p = 0.005). Conclusions:IRE-HCCs demonstrate aggressive histopathologic features, including more hypoxic and fibrotic tumor microenvironments and increased stemness, compared to non-IRE-HCCs. IRE might therefore serve as a noninvasive imaging biomarker for aggressive HCC.

Project description:BackgroundThe clinical pathologic stages (stage I, II, III-IV) of hepatocellular carcinoma (HCC) are closely linked to the clinical prognosis of patients. This study aims at investigating the gene expression and mutational profile in different clinical pathologic stages of HCC.MethodsBased on the TCGA-LIHC cohort, we utilized a series of analytical approaches, such as statistical analysis, random forest, decision tree, principal component analysis (PCA), to identify the differential gene expression and mutational profiles. The expression patterns of several targeting genes were also verified by analyzing the Chinese HLivH060PG02 HCC cohort, several GEO datasets, HPA database, and diethylnitrosamine-induced HCC mouse model.ResultsWe identified a series of targeting genes with copy number variation, which is statistically associated with gene expression. Non-synonymous mutations mainly existed in some genes (e.g.,TTN, TP53, CTNNB1). Nevertheless, no association between gene mutation frequency and pathologic stage distribution was detected. The random forest and decision tree modeling analysis data showed a group of genes related to different HCC pathologic stages, including GAS2L3 and SEMA3F. Additionally, our PCA data indicated several genes associated with different pathologic stages, including SNRPA and SNRPD2. Compared with adjacent normal tissues, we observed a highly expressed level of GAS2L3, SNRPA, and SNRPD2 (P = 0.002) genes in HCC tissues of our HLivH060PG02 cohort. We also detected the high expression pattern of GAS2L3, SEMA3F, SNRPA, and SNRPD2 in the datasets of GSE102079, GSE76427, GSE64041, GSE121248, GSE84005, and the qPCR assay using diethylnitrosamine-induced HCC mouse model. Moreover, SEMA3F and SNRPD2 protein were highly stained in the HCC tissues of the HPA database. The high expression level of these four genes was associated with the poor survival prognosis of HCC cases.ConclusionsOur study provides evidence regarding the gene expression and mutational profile in different clinical pathologic stages of TCGA HCC cases. Identifying four targeting genes, including GAS2L3, SNRPA, SNRPD2, and SEMA3F, offers insight into the molecular mechanisms associated with different prognoses of HCC.

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Cross Analysis of Genomic-Pathologic Features on Multiple Primary Hepatocellular Carcinoma.

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