Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

In vivo genome-wide CRISPR screen reveals breast cancer vulnerabilities and synergistic mTOR/Hippo targeted combination therapy.

ABSTRACT: Triple negative breast cancer (TNBC) patients exhibit poor survival outcomes and lack effective targeted therapies. Using unbiased in vivo genome-wide CRISPR screening, we interrogated cancer vulnerabilities in TNBC and identified an interplay between oncogenic and tumor suppressor pathways. This study reveals tumor regulatory functions for essential components of the mTOR and Hippo pathways in TNBC. Using in vitro drug matrix synergy models and in vivo patient-derived xenografts, we further establish the therapeutic relevance of our findings and show that pharmacological inhibition of mTORC1/2 and oncoprotein YAP efficiently reduces tumorigenesis in TNBC. At the molecular level, we find that while verteporfin-induced YAP inhibition leads to apoptosis, torin1-mediated mTORC1/2 inhibition promotes macropinocytosis. Torin1-induced macropinocytosis further facilitates verteporfin uptake, thereby greatly enhancing its pro-apoptotic effects in cancer cells. Overall, our study underscores the power and robustness of in vivo CRISPR genome-wide screens in identifying clinically relevant and innovative therapeutic modalities in cancer.

SUBMITTER: Dai M

PROVIDER: S-EPMC8144221 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Genome-wide CRISPR screen uncovers a synergistic effect of combining Haspin and Aurora kinase B inhibition.

Project description:Aurora kinases are a family of serine/threonine kinases vital for cell division. Because of the overexpression of Aurora kinases in a broad range of cancers and their important roles in mitosis, inhibitors targeting Aurora kinases have attracted attention in cancer therapy. VX-680 is an effective pan-Aurora kinase inhibitor; however, its clinical efficacy was not satisfying. In this study, we performed CRISPR/Cas9 screens to identify genes whose depletion shows synthetic lethality with VX-680. The top hit from these screens was GSG2 (also known as Haspin), a serine/threonine kinase that phosphorylates histone H3 at Thr-3 during mitosis. Moreover, both Haspin knockout and Haspin inhibitor-treated HCT116 cells were hypersensitive to VX-680. Furthermore, we showed that the synthetic lethal interaction between Haspin depletion and VX-680 was mediated by the inhibition of Haspin with Aurora kinase B (AURKB), but not with Aurora kinase A (AURKA). Strikingly, combined inhibition of Haspin and AURKB had a better efficacy than single-agent treatment in both head and neck squamous cell carcinoma and non-small cell lung cancer. Taken together, our findings have uncovered a synthetic lethal interaction between AURKB and Haspin, which provides a strong rationale for this combination therapy for cancer patients.

| S-EPMC7291820 | biostudies-literature

A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia.

Project description:Acute myeloid leukemia (AML) is an aggressive cancer with a poor prognosis, for which mainstream treatments have not changed for decades. To identify additional therapeutic targets in AML, we optimize a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening platform and use it to identify genetic vulnerabilities in AML cells. We identify 492 AML-specific cell-essential genes, including several established therapeutic targets such as DOT1L, BCL2, and MEN1, and many other genes including clinically actionable candidates. We validate selected genes using genetic and pharmacological inhibition, and chose KAT2A as a candidate for downstream study. KAT2A inhibition demonstrated anti-AML activity by inducing myeloid differentiation and apoptosis, and suppressed the growth of primary human AMLs of diverse genotypes while sparing normal hemopoietic stem-progenitor cells. Our results propose that KAT2A inhibition should be investigated as a therapeutic strategy in AML and provide a large number of genetic vulnerabilities of this leukemia that can be pursued in downstream studies.

| S-EPMC5081405 | biostudies-literature

Vulnerabilities in mIDH2 AML confer sensitivity to APL-like targeted combination therapy.

Project description:Although targeted therapies have proven effective and even curative in human leukaemia, resistance often ensues. IDH enzymes are mutated in ~20% of human AML, with targeted therapies under clinical evaluation. We here characterize leukaemia evolution from mutant IDH2 (mIDH2)-dependence to independence identifying key targetable vulnerabilities of mIDH2 leukaemia that are retained during evolution and progression from early to late stages. Mechanistically, we find that mIDH2 leukaemia are metastable and vulnerable at two distinct levels. On the one hand, they are characterized by oxidative and genotoxic stress, in spite of increased 1-carbon metabolism and glutathione levels. On the other hand, mIDH2 leukaemia display inhibition of LSD1 and a resulting transcriptional signature of all-trans retinoic acid (ATRA) sensitization, in spite of a state of suppressed ATRA signalling due to increased levels of PIN1. We further identify GSH/ROS and PIN1/LSD1 as critical nodes for leukaemia maintenance and the combination of ATRA and arsenic trioxide (ATO) as a key therapeutic modality to target these vulnerabilities. Strikingly, we demonstrate that the combination of ATRA and ATO proves to be a powerfully synergistic and effective therapy in a number of mouse and human mIDH1/2 leukemic models. Thus, our findings pave the way towards the treatment of a sizable fraction of human AMLs through targeted APL-like combinatorial therapies.

| S-EPMC6796925 | biostudies-literature

Detection of phenotype-specific therapeutic vulnerabilities in breast cells using a CRISPR loss-of-function screen.

Project description:Cellular phenotype plasticity between the epithelial and mesenchymal states has been linked to metastasis and heterogeneous responses to cancer therapy, and remains a challenge for the treatment of triple-negative breast cancer (TNBC). Here, we used isogenic human breast epithelial cell lines, D492 and D492M, representing the epithelial and mesenchymal phenotypes, respectively. We employed a CRISPR-Cas9 loss-of-function screen targeting a 2240-gene 'druggable genome' to identify phenotype-specific vulnerabilities. Cells with the epithelial phenotype were more vulnerable to the loss of genes related to EGFR-RAS-MAPK signaling, while the mesenchymal-like cells had increased sensitivity to knockout of G2 -M cell cycle regulators. Furthermore, we discovered knockouts that sensitize to the mTOR inhibitor everolimus and the chemotherapeutic drug fluorouracil in a phenotype-specific manner. Specifically, loss of EGFR and fatty acid synthase (FASN) increased the effectiveness of the drugs in the epithelial and mesenchymal phenotypes, respectively. These phenotype-associated genetic vulnerabilities were confirmed using targeted inhibitors of EGFR (gefitinib), G2 -M transition (STLC), and FASN (Fasnall). In conclusion, a CRISPR-Cas9 loss-of-function screen enables the identification of phenotype-specific genetic vulnerabilities that can pinpoint actionable targets and promising therapeutic combinations.

| S-EPMC8333781 | biostudies-literature

Genome-wide CRISPR screen

Project description:A genome-wide CRISPR screen identifies regulators of beta cell function involved in type 2 diabetes risk

| PRJEB44712 | ENA

Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions.

Project description:Identification of effective combination therapies is critical to address the emergence of drug-resistant cancers, but direct screening of all possible drug combinations is infeasible. Here we introduce a CRISPR-based double knockout (CDKO) system that improves the efficiency of combinatorial genetic screening using an effective strategy for cloning and sequencing paired single guide RNA (sgRNA) libraries and a robust statistical scoring method for calculating genetic interactions (GIs) from CRISPR-deleted gene pairs. We applied CDKO to generate a large-scale human GI map, comprising 490,000 double-sgRNAs directed against 21,321 pairs of drug targets in K562 leukemia cells and identified synthetic lethal drug target pairs for which corresponding drugs exhibit synergistic killing. These included the BCL2L1 and MCL1 combination, which was also effective in imatinib-resistant cells. We further validated this system by identifying known and previously unidentified GIs between modifiers of ricin toxicity. This work provides an effective strategy to screen synergistic drug combinations in high-throughput and a CRISPR-based tool to dissect functional GI networks.

| S-EPMC5557292 | biostudies-literature

Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer [CRISPR Screen]

Project description:Purpose: 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 genetic screens using both in vivo and in vitro model systems. Methods: A custom library of lentiviral vectors encoding ~18,000 sgRNAs targeting ~3,000 mouse metabolic genes and performed CRISPR-Cas9 screens using a C/57BL6 (B6) mouse pancreatic cancer cell line derived from a KrasG12D-driven autochthonous PDA model. After transduction and selection, parallel screens were performed by in vitro passage or tumor implantation subcutaneously into the flanks of syngeneic hosts. Genomic DNA was then harvaested in vitro after 7 passages (21 days in culture) and in vivo 21 days after implantation. Results: This work revealed striking overlap of in vivo metabolic dependencies with those in vitro, validating that standard 2D culture conditions are a reliable system for studying cancer metabolism. Moreover, we identified that intercellular nutrient sharing can mask cancer dependencies in pooled screening experiments, highlighting an important limitation of this approach to study tumor metabolism Conclusions:Our work demonstrates the power of genetic screening approaches to define the compendium of in vivo metabolic dependencies in PDA and highlights critical metabolic pathways that may have therapeutic utility.

2020-10-01 | GSE158789 | GEO

mTOR inhibitors are synergistic with methotrexate: an effective combination to treat acute lymphoblastic leukemia.

Project description:We have previously demonstrated that mTOR inhibitors (MTIs) are active in preclinical models of acute lymphoblastic leukemia (ALL). MTIs may increase degradation of cyclin D1, a protein involved in dihydrofolate reductase (DHFR) synthesis. Because resistance to methotrexate may correlate with high DHFR expression, we hypothesized MTIs may increase sensitivity of ALL to methotrexate through decreasing DHFR by increasing turn-over of cyclin D1. We tested this hypothesis using multiple ALL cell lines and nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice xenografted with human ALL. We found MTIs and methotrexate were synergistic in combination in vitro and in vivo. Mice treated with both drugs went into a complete and durable remission whereas single agent treatment caused an initial partial response that ultimately progressed. ALL cells treated with MTIs had markedly decreased expression of DHFR and cyclin D1, providing a novel mechanistic explanation for a combined effect. We found methotrexate and MTIs are an effective and potentially synergistic combination in ALL.

| S-EPMC2518903 | biostudies-other

Hippo kinase screen

Project description:In vitro kinase screen of the Hippo kinase STK3 and 4.

2016-11-04 | MSV000080315 | MassIVE

Synergistic combination therapies involving regorafenib in experimental glioma based on genome-wide CRISPR-Cas9 functional screens

Project description:Registered systemic treatment options for glioblastoma patients are limited, particularly for progressive glioblastoma, including bevacizumab in the US and some other countries as well as lomustine. The phase II REGOMA trial suggested an improvement of overall survival in progressive glioblastoma by the multi-tyrosine kinase inhibitor regorafenib. This has not been confirmed by GBM AGILE, however. Of note, regorafenib has been administered as monotherapy in progressive glioblastoma or as an addition to standard of care in newly diagnosed glioblastoma. Rational combination therapies involving regorafenib, instead of entirely discontinuing any consideration of this compound, might be therefore a reasonable strategy. We addressed this research gap and used an innovative discovery and validation approach to identify functionally-instructed combination therapies. We applied a genome-wide CRISPR-Cas9-based functional genomics experimental approach including activation and knockout screens for the discovery of potential molecular targets modifying the therapeutic efficacy of regorafenib in experimental glioma. Selected functionally instructed molecular hits were then validated regarding synergistic interaction in vitro, ex vivo and in two orthotopic mouse models in vivo.This functional genomics approach led to the discovery of several molecular targets. Based on subsequent validation experiments including a customized compound library, we identified novel combination therapies. Particularly, the combination of regorafenib with Bcl-2/Bcl-xL inhibition was among the most promising strategies.

2024-08-21 | GSE272737 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data