Qingyu Shen1,2, Jung Woo Eun1,2, Kyungbun Lee3, Hyung Seok Kim1,2, Hee Doo Yang1,2, Sang Yean Kim1,2, Eun Kyung Lee4, Taemook Kim5, Keunsoo Kang5, Seongchan Kim6, Dal-Hee Min6, Soon-Nam Oh7, Young-Joon Lee7, Hyuk Moon8, Simon Weonsang Ro8, Won Sang Park1, Jung Young Lee1, Suk Woo Nam1,2,9. 1. Department of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. 2. Functional RNomics Research Center, The Catholic University of Korea, Seoul, Republic of Korea. 3. Department of Pathology, College of Medicine, Seoul National University, Seoul, Republic of Korea. 4. Department of Biochemistry, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. 5. Department of Microbiology, College of Natural Sciences, Dankook University, Cheonan, Republic of Korea. 6. Center for RNA Research, Institute for Basic Science (IBS), Department of Chemistry, Seoul National University, Seoul, Republic of Korea. 7. Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. 8. Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea. 9. Cancer Evolution Research Center, The Catholic University of Korea, Seoul, Republic of Korea.
Abstract
An accurate tool enabling early diagnosis of hepatocellular carcinoma (HCC) is clinically important, given that early detection of HCC markedly improves survival. We aimed to investigate the molecular markers underlying early progression of HCC that can be detected in precancerous lesions. We designed a gene selection strategy to identify potential driver genes by integrative analysis of transcriptome and clinicopathological data of human multistage HCC tissues, including precancerous lesions, low- and high-grade dysplastic nodules. The gene selection process was guided by detecting the selected molecules in both HCC and precancerous lesion. Using various computational approaches, we selected 10 gene elements as a candidate and, through immunohistochemical staining, showed that barrier to autointegration factor 1 (BANF1), procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3 (PLOD3), and splicing factor 3b subunit 4 (SF3B4) are HCC decision markers with superior capability to diagnose early-stage HCC in a large cohort of HCC patients, as compared to the currently popular trio of HCC diagnostic markers: glypican 3, glutamine synthetase, and heat-shock protein 70. Targeted inactivation of BANF1, PLOD3, and SF3B4 inhibits in vitro and in vivo liver tumorigenesis by selectively modulating epithelial-mesenchymal transition and cell-cycle proteins. Treatment of nanoparticles containing small-interfering RNAs of the three genes suppressed liver tumor incidence as well as tumor growth rates in a spontaneous mouse HCC model. We also demonstrated that SF3B4 overexpression triggers SF3b complex to splice tumor suppressor KLF4 transcript to nonfunctional skipped exon transcripts. This contributes to malignant transformation and growth of hepatocyte through transcriptional inactivation of p27Kip1 and simultaneously activation of Slug genes. CONCLUSION: The findings suggest molecular markers of BANF1, PLOD3, and SF3B4 indicating early-stage HCC in precancerous lesion, and also suggest drivers for understanding the development of hepatocarcinogenesis. (Hepatology 2018;67:1360-1377).
An accurate tool enabling early diagnosis of hepatocellular carcinoma (HCC) is clinically important, given that early detection of HCC markedly improves survival. We aimed to investigate the molecular markers underlying early progression of HCC that can be detected in precancerous lesions. We designed a gene selection strategy to identify potential driver genes by integrative analysis of transcriptome and clinicopathological data of human multistage HCC tissues, including precancerous lesions, low- and high-grade dysplastic nodules. The gene selection process was guided by detecting the selected molecules in both HCC and precancerous lesion. Using various computational approaches, we selected 10 gene elements as a candidate and, through immunohistochemical staining, showed that barrier to autointegration factor 1 (BANF1), procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3 (PLOD3), and splicing factor 3b subunit 4 (SF3B4) are HCC decision markers with superior capability to diagnose early-stage HCC in a large cohort of HCC patients, as compared to the currently popular trio of HCC diagnostic markers: glypican 3, glutamine synthetase, and heat-shock protein 70. Targeted inactivation of BANF1, PLOD3, and SF3B4 inhibits in vitro and in vivo liver tumorigenesis by selectively modulating epithelial-mesenchymal transition and cell-cycle proteins. Treatment of nanoparticles containing small-interfering RNAs of the three genes suppressed liver tumor incidence as well as tumor growth rates in a spontaneous mouse HCC model. We also demonstrated that SF3B4 overexpression triggers SF3b complex to splice tumor suppressor KLF4 transcript to nonfunctional skipped exon transcripts. This contributes to malignant transformation and growth of hepatocyte through transcriptional inactivation of p27Kip1 and simultaneously activation of Slug genes. CONCLUSION: The findings suggest molecular markers of BANF1, PLOD3, and SF3B4 indicating early-stage HCC in precancerous lesion, and also suggest drivers for understanding the development of hepatocarcinogenesis. (Hepatology 2018;67:1360-1377).
Authors: Graham F Brady; Raymond Kwan; Juliana Bragazzi Cunha; Jared S Elenbaas; M Bishr Omary Journal: Gastroenterology Date: 2018-03-13 Impact factor: 22.682