An in vivo CRISPR screen identifies stepwise genetic dependencies of metastatic progression
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE138813 | GEO | 2022/01/27
REPOSITORIES: GEO
Similar Datasets
Project description:An in vivo CRISPR screen identifies stepwise genetic dependencies of metastatic progression
| PRJNA577413 | ENA
Project description:Metastatic colorectal cancer (mCRC) relies on the detachment of aggressive malignant cells from the primary tumor into the bloodstream, these Circulating Tumor Cells (CTC) being the principal source of the further metastasis. Here, we approached the massive molecular profiling of the CTC population isolated from mCRC patients. Clinically, the presence of CTC is associated with poor prognosis and there exists a clear necessity for more specific and efficient chemotherapies in the treatment of mCRC. Immunoisolation of CTC from these patients combined with a whole transcriptome amplification and hybridization onto gene expression arrays, lead us to specifically describe for the first time a CTC population with adhesive and migratory characteristics, in addition to a modulated expression of genes related to cell death and survival. Furthermore, bioinformatic analysis provided with an armamentarium of highly specific and sensitive valuable markers that should impact on the management and follow-up of mCRC patients. Finally, molecular profiling of CTC resulted in the identification of new therapeutic targets, like TGF-β1 impairing, specifically targeting the CTC population which should improve the efficacy in the eradication and prevention of CRC metastasis. In conclusion, molecular profiling of CTC represents an innovative and promising approach in the clinical management of mCRC patients. Circulating Tumor Cells (CTC) were immunoisolated from six metastatic colorectal patients (mCRC). Moreover, blood from three healthy donors were obtained, immunoisolating non-specific cellularity background. RNA was extracted and globally amplified with a Whole Transcriptome Amplification system. Samples were hybridized onto agilent arrays and CTC specific genes were obtained. Gene networks were built with IPA software and a gene ontology analysis was performed. Eleven candidate genes were validated by real time PCR. Finally, TGFB1 was evaluated as a potential drugable target against CTC population.
2012-06-29 | E-GEOD-31023 | biostudies-arrayexpress
Project description:Metastatic colorectal cancer (mCRC) relies on the detachment of aggressive malignant cells from the primary tumor into the bloodstream, these Circulating Tumor Cells (CTC) being the principal source of the further metastasis. Here, we approached the massive molecular profiling of the CTC population isolated from mCRC patients. Clinically, the presence of CTC is associated with poor prognosis and there exists a clear necessity for more specific and efficient chemotherapies in the treatment of mCRC. Immunoisolation of CTC from these patients combined with a whole transcriptome amplification and hybridization onto gene expression arrays, lead us to specifically describe for the first time a CTC population with adhesive and migratory characteristics, in addition to a modulated expression of genes related to cell death and survival. Furthermore, bioinformatic analysis provided with an armamentarium of highly specific and sensitive valuable markers that should impact on the management and follow-up of mCRC patients. Finally, molecular profiling of CTC resulted in the identification of new therapeutic targets, like TGF-β1 impairing, specifically targeting the CTC population which should improve the efficacy in the eradication and prevention of CRC metastasis. In conclusion, molecular profiling of CTC represents an innovative and promising approach in the clinical management of mCRC patients.
2012-06-30 | GSE31023 | GEO
Project description:The plasticity and heterogeneity of cancer cells are known to play a major role in malignant progression, yet the precise molecular drivers of metastases remain elusive. We performed single-cell RNA-Seq (scRNA-Seq) on tumours and matched lung macrometastases of patient-derived xenografts (PDXs) of breast cancer to identify molecular mechanisms of metastasis during colonization.
2022-05-13 | GSE202695 | GEO
Project description:The ability of circulating tumor cells (CTCs) to form clusters has been linked to increased metastatic potential. Yet biological features and vulnerabilities of CTC clusters remain largely unknown. Our DNA methylation analysis led us to hypothesize that CTC clusters are characterized by active TF networks that support both stemness and proliferation. To identify whether the stemness- and proliferation-related TF networks are also transcriptionally active in CTC clusters compared to single CTCs, we performed single-cell resolution RNA sequencing analysis of single CTCs and CTC clusters, matched within individual liquid biopsies and isolated from six breast cancer patients with progressive metastatic disease, and of single CTCs and CTC clusters isolated from three xenograft models. In addition, among 2,486 FDA-approved compounds, we identify Na+/K+ ATPase inhibitors that enable the dissociation of CTC clusters into single cells, leading to DNA methylation remodeling at critical sites and metastasis suppression. We performed RNA sequencing analysis of BR16 and Brx50 cells upon treatment to assess the molecular consequences of clusters dissociation.
2019-01-11 | GSE111065 | GEO
Project description:In many patients with solid tumors circulating tumor cells (CTCs), that form metastases, can be identified in peripheral blood. Detection and characterization of CTCs in cancer patients provide a unique opportunity to predict patient survival, select and monitor the efficacy of treatment as well as to gain insights into the cascade of metastatic events. Here, we describe a novel approach to identify CTC-specific molecular markers. Using an integrated platform for immunomagnetic enrichment and immunofluorescent identification of CTCs, blood samples with large numbers of CTCs were identified from patients with colorectal, prostate and breast cancers. Despite enrichment, CTCs are still outnumbered by "nonspecifically" captured leukocytes. In order to determine gene expression profile for CTCs, "background" gene expression signature of white blood cells must be taken into account. To this end, following enrichment for CTCs, RNA was also extracted from the remaining CTC-depleted blood samples. The following samples were used to generate the global expression profiles for CTCs:<br><br> 1a) SAMPLE170711SUB735: CTC-enriched blood sample from a patient with breast cancer). 3700 CTCs were identified per 7.5 ml of peripheral blood in this patient.<br> 1b) SAMPLE170712SUB735: Corresponding CTC-depleted blood sample for the above patient with breast cancer.<br> 2a) SAMPLE170829SUB750: CTC-enriched blood sample from a patient with prostate cancer. 647 CTCs were identified per 7.5 ml of peripheral blood in this patient.<br> 2b) SAMPLE170830SUB750: Corresponding CTC-depleted blood sample for the above patient with prostate cancer.<br> 3a) SAMPLE170831SUB751: CTC-enriched sample from a patient with colorectal cancer. 180 CTCs were identified per 7.5 ml of peripheral blood in this patient.<br> 3b) SAMPLE170832SUB751: Corresponding CTC-depleted blood sample for the above patient with colorectal cancer.
2005-06-30 | E-MEXP-136 | biostudies-arrayexpress
Project description:Genetic Screen in a Pre-Clinical Model of Sarcoma Development Defines Drivers and Therapeutic Vulnerabilities
| PRJNA948826 | ENA
Project description:Understanding the direction of information flow is essential for characterizing how genetic networks affect phenotypes. However, methods to find genetic interactions largely fail to reveal directional dependencies. We combine two orthogonal Cas9 proteins from Streptococcus pyogenes and Staphylococcus aureus to carry out a dual screen in which one gene is activated while a second gene is deleted in the same cell. We analyze the quantitative effects of activation and knockout to calculate genetic interaction and directionality scores for each gene pair. Based on the results from over 100,000 perturbed gene pairs, we reconstruct a directional dependency network for human K562 leukemia cells and demonstrate how our approach allows the determination of directionality in activating genetic interactions. Our interaction network connects previously uncharacterized genes to well-studied pathways and identifies targets relevant for therapeutic intervention.
| S-EPMC6072461 | biostudies-literature
Project description:Hematogenous metastasis is initiated by a subset of circulating tumor cells (CTCs) shed from primary or metastatic tumors into the blood circulation. Thus, CTCs provide a unique patient biopsy resource to decipher the cellular subpopulations that initiate metastasis and their molecular properties. However, one crucial question is whether CTCs derived from patients recapitulate human metastatic disease in an animal model. Here, we show that CTC lines established from breast cancer patients are capable of generating metastases in mice with a pattern recapitulating most major organs from corresponding patients. We used ATAC-seq to assay chromatin accessibility in parental CTC and CTC-derived metastatic cells. Genome-wide sequencing analyses of metastatic variants identified novel chromatin accessibility domains predicting organ-specific metastasis identified from CTCs and facilitate the development of potential therapies targeting metastatis initiating cells in circulation.
2019-10-14 | GSE112852 | GEO
Project description:<p>Circulating tumor cells (CTCs) are recognized as direct seeds of metastasis. However, CTC count may not be the 'best' indicator of metastatic risk because their heterogeneity is generally neglected. In this study, we develop a molecular typing system to predict colorectal cancer metastasis potential based on the metabolic fingerprints of single CTCs. After identification of the metabolites potentially related to metastasis using mass spectrometry-based untargeted metabolomics, setup of a home-built single-cell quantitative mass spectrometric platform for target metabolite analysis in individual CTCs and use of a machine learning method composed of non-negative matrix factorization and logistic regression, CTCs are divided into two subgroups, C1 and C2, based on a 4-metabolite fingerprint. Both <em>in vitro</em> and <em>in vivo</em> experiments demonstrate that CTC count in C2 subgroup is closely associated with metastasis incidence. This is an interesting report on the presence of a specific population of CTCs with distinct metastatic potential at the single-cell metabolite level. </p>
2023-08-21 | MTBLS5028 | MetaboLights