Genome-wide CRISPR Screen Identifies Regulators of MAPK as Suppressors of Liver Tumors in Mice
RNA Therapeutics Institute; Program in Bioinformatics and Integrative Biology; Department of Pathology; Department of Biochemistry and Molecular Pharmacology
Bioinformatics | Cancer Biology | Computational Biology | Gastroenterology | Genomics | Hepatology
BACKGROUND and AIMS: It has been a challenge to identify liver tumor suppressors or oncogenes due to the genetic heterogeneity of these tumors. We performed a genome-wide screen to identify suppressors of liver tumor formation in mice, using CRISPR-mediated genome editing.
METHODS: We performed a genome-wide CRISPR/Cas9-based knockout screen of P53-null mouse embryonic liver progenitor cells that overexpressed MYC. We infected p53-/-;Myc;Cas9 hepatocytes with the mGeCKOa lentiviral library of 67,000 single-guide RNAs (sgRNAs), targeting 20,611 mouse genes, and transplanted the transduced cells subcutaneously into nude mice. Within 1 month, all the mice that received the sgRNA library developed subcutaneous tumors. We performed high-throughput sequencing of tumor DNA and identified sgRNAs increased at least 8-fold compared to the initial cell pool. To validate the top 10 candidate tumor suppressors from this screen, we collected data from patients with hepatocellular carcinoma (HCC) using the Cancer Genome Atlas and COSMIC databases. We used CRISPR to inactivate candidate tumor suppressor genes in p53-/-;Myc;Cas9 cells and transplanted them subcutaneously into nude mice; tumor formation was monitored and tumors were analyzed by histology and immunohistochemistry. Mice with liver-specific disruption of p53 were given hydrodynamic tail-vein injections of plasmids encoding Myc and sgRNA/Cas9 designed to disrupt candidate tumor suppressors; growth of tumors and metastases was monitored. We compared gene expression profiles of liver cells with vs without tumor suppressor gene disrupted by sgRNA/Cas9. Genes found to be upregulated following tumor suppressor loss were examined in liver cancer cell lines; their expression was knocked down using small hairpin RNAs, and tumor growth was examined in nude mice. Effects of the MEK inhibitors AZD6244, U0126, and trametinib, or the multi-kinase inhibitor sorafenib, were examined in human and mouse HCC cell lines.
RESULTS: We identified 4 candidate liver tumor suppressor genes not previously associated with liver cancer (Nf1, Plxnb1, Flrt2, and B9d1). CRISPR-mediated knockout of Nf1, a negative regulator of RAS, accelerated liver tumor formation in mice. Loss of Nf1 or activation of RAS upregulated the liver progenitor cell markers HMGA2 and SOX9. RAS pathway inhibitors suppressed the activation of the Hmga2 and Sox9 genes that resulted from loss of Nf1 or oncogenic activation of RAS. Knockdown of HMGA2 delayed formation of xenograft tumors from cells that expressed oncogenic RAS. In human HCCs, low levels of NF1 mRNA or high levels of HMGA2 mRNA were associated with shorter patient survival time. Liver cancer cells with inactivation of Plxnb1, Flrt2, and B9d1 formed more tumors in mice and had increased levels of MAPK phosphorylation.
CONCLUSIONS: Using a CRISPR-based strategy, we identified Nf1, Plxnb1, Flrt2, and B9d1 as suppressors of liver tumor formation. We validated the observation that RAS signaling, via MAPK, contributes to formation of liver tumors in mice. We associated decreased levels of NF1 and increased levels of its downstream protein HMGA2 with survival times of patients with HCC. Strategies to inhibit or reduce HMGA2 might be developed to treat patients with liver cancer.
DOI of Published Version
Gastroenterology. 2016 Dec 9. pii: S0016-5085(16)35462-2. doi: 10.1053/j.gastro.2016.12.002. [Epub ahead of print] Link to article on publisher's site
Song, Chun-Qing; Li, Yingxiang; Mou, Haiwei; Moore, Jill; Park, Angela I.; Hough, Soren; Kennedy, Zachary; Fischer, Andrew H.; Conte, Darryl Jr.; Weng, Zhiping; and Xue, Wen, "Genome-wide CRISPR Screen Identifies Regulators of MAPK as Suppressors of Liver Tumors in Mice" (2016). Program in Bioinformatics and Integrative Biology Publications and Presentations. 91.