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Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDA) is a deadly cancer characterized by complex metabolic adaptations that promote survival in a severely hypoxic and nutrient-limited tumor microenvironment (TME). Modeling microenvironmental influences in cell culture has been challenging, and technical limitations have hampered the comprehensive study of tumor-specific metabolism in vivo. To systematically interrogate metabolic vulnerabilities in PDA, we employed parallel CRISPR-Cas9 screens using in vivo and in vitro systems. This work revealed striking overlap of in vivo metabolic dependencies with those in vitro. Moreover, we identified that intercellular nutrient sharing can mask dependencies in pooled screens, highlighting a limitation of this approach to study tumor metabolism. Furthermore, metabolic dependencies were similar between 2D and 3D culture, although 3D culture may better model vulnerabilities that influence certain oncogenic signaling pathways. Lastly, our work demonstrates the power of genetic screening approaches to define in vivo metabolic dependencies and pathways that may have therapeutic utility.

SUBMITTER: Biancur DE

PROVIDER: S-EPMC7790858 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPhosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers.MethodsTo discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data.ResultsThe screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets.ConclusionsSix genes showed PTEN-SSL patterns of activity in a large proportion of PTEN-deficient breast cancer cell lines and are potential specific vulnerabilities in PTEN-deficient breast cancer. Furthermore, the NUAK1 PTEN-SSL vulnerability identified by RNA interference techniques can be recapitulated and exploited using the small molecule kinase inhibitor HTH-01-015. Thus, NUAK1 inhibition may be an effective strategy for precision treatment of PTEN-deficient breast tumors.

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Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer.

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