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Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133B]

ABSTRACT: To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.

ORGANISM(S): Homo sapiens

PROVIDER: GSE62321 | GEO | 2014/10/15

SECONDARY ACCESSION(S): PRJNA263827

REPOSITORIES: GEO

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Specific extracellular matrix remodeling signature of colon hepatic metastases

Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment. 57 samples of patients with stage IV colorectal cancer. We compared using Affymetrix chips gene expression profiles between primary tumors and hepatic metastases

2013-09-01 | E-GEOD-49355 | biostudies-arrayexpress

Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133B]

2014-10-15 | E-GEOD-62321 | biostudies-arrayexpress

Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133A]

2013-09-01 | GSE49355 | GEO

Homo sapiens

Project description:Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133A]

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Homo sapiens

Project description:Specific extracellular matrix remodeling signature of colon hepatic metastases [HG-U133B]

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Proteomics analysis of the matrisome from MC38 experimental mouse liver metastases

Project description:Dissemination of primary tumors to distant anatomical sites has a substantial negative impact on patient prognosis. The liver is a common site for metastases from colorectal cancer, and patients with hepatic metastases have generally much shorter survival, raising a need to develop and implement novel strategies for targeting metastatic disease. The extracellular matrix (ECM) is a meshwork of highly crosslinked, insoluble, high molecular weight proteins maintaining tissue integrity and establishing cell-cell interactions. Emerging evidence identifies the importance of the ECM in cancer cell migration, invasion, intravasation, and metastasis. Here, we isolated the extracellular matrix from MC38 mouse liver metastases using our optimized method of mild detergent solubilization followed by biochemical enrichment. The matrices were subjected to label-free quantitative mass spectrometry analysis, revealing proteins highly abundant in the metastatic matrisome. The resulting list of differentially expressed proteins significantly predicted survival in patients with colorectal cancer but not other cancers with strong involvement of the extracellular matrix component. One of the proteins upregulated in liver metastatic ECM, Annexin A1, was not previously studied in the context of cancer-associated matrisome. Here we show that Annexin A1 was markedly upregulated in colon cancer cell lines compared to cancer cells of other origin, and also overrepresented in human primary colorectal lesions as well as hepatic metastases in comparison with their adjacent healthy tissue counterparts. In conclusion, our study provides a comprehensive ECM characterization of MC38 experimental liver metastases and proposes Annexin A1 as a putative target for this disease.

2020-05-26 | PXD013350 | Pride

CDK8 Mediator kinase drives colon cancer hepatic metastasis by regulating gene expression of the matrix metalloproteinase network [Illumina]

Project description:CDK8 Mediator kinase is amplified and overexpressed in colon cancers; elevated CDK8 expression is associated with shorter patient survival. Nevertheless, CDK8 kinase inhibitors do not generally suppress colon cancer growth. We addressed this paradox by investigating the effects of CDK8 knockdown or a CDK8 kinase inhibitor on tumor growth at primary and metastatic sites. CDK8 knockdown or inhibition had no significant effect on primary tumors but suppressed the growth of hepatic metastases in murine and human colon cancer models. The effect of CDK8 inhibition on liver metastasis is mediated by upregulation of matrix metalloproteinase (MMP) inhibitor TIMP3 and downregulation of several MMPs.

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CDK8 Mediator kinase drives colon cancer hepatic metastasis by regulating gene expression of the matrix metalloproteinase network [Affymetrix]

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Exploiting ECM signatures associated with human metastases for targeting tumors and metastases using alpaca-derived nanobodies

Project description:Jailkhani N, Clauser KR, Mak H, Rickelt S, Tian C, Whittaker CA, Tanabe KK, Purdy SR, Carr SA, and Hynes RO.2022. Metastases are hard to detect and treat, and cause most cancer-related deaths. The relative lack of therapies targeting metastases represents a major unmet clinical need. The extracellular matrix or ECM forms a major component of the tumor microenvironment in both primary and metastatic tumors and certain ECM proteins can be selectively and abundantly expressed in such tumors. We propose that nanobodies against ECM proteins that show selective abundance in metastases can be used as vehicles for delivery of imaging and therapeutic cargoes. To gain a deeper understanding of the microenvironment of human metastases, we describe here an LC-MS/MS-based ECM signature shared by human TNBC and CRC metastases to different organs and provide evidence that this conserved set of ECM proteins is selectively elevated in other tumors. We also describe phage-display libraries of nanobodies raised against ECM-enriched preparations from human metastases from TNBC and CRC. As proof of concept, we developed selective and specific, high-affinity nanobodies against an example signature protein, Tenascin-C (TNC), known to be abundant in many tumor types and to play a role in metastases. We report that TNC is abundantly expressed in patient metastases and widely expressed across diverse metastatic sites originating from several primary tumor types. Using immuno-PET/CT we showed that anti-TNC nanobodies bind TNBC tumors and metastases with excellent specificity. We propose that such generic anti-tumor nanobodies are promising cancer-agnostic, in vivo tools for the delivery of therapeutics to tumor and metastatic ECM.

2022-03-28 | MSV000089136 | MassIVE

Genomic Signatures of Metastasis in Prostate Cancer

Project description:Background: Metastases result in 90% of all cancer deaths. Prostate cancer primary tumors evolve to become metastatic through selective alterations, such as amplification and deletion of genomic DNA. Methods: Genomic DNA copy number alterations were used to develop a gene signature that measured the metastatic potential of a prostate cancer primary tumor. We studied the genomic landscape of these alterations in 294 primary tumors and 49 metastases from 5 independent cohorts. Receiver-operating characteristic cross-validation and Kaplan-Meier survival analysis were performed to assess the accuracy of our predictive model. The signature was measured in a panel of 337 cancer cell lines from 29 different tissue origins. Results: We identified 399 copy number alterations around genes that were over-represented in metastases and predictive of whether a primary tumor will metastasize. Cross-validation analysis resulted in a predictive accuracy of 80.5% and log rank analysis of the metastatic potential score was significantly related to the endpoint of metastasis-free survival (p=0.014). The metastatic signature was observed in cell lines originating from lung, breast, colon, thyroid, rectum, pancreas and melanoma. The signature was comprised in part of genes of known or putative metastatic role — 8 solute carrier genes, 6 Cadherin family genes and 5 potassium channel genes — that function in metabolism, cell-to-cell adhesion and escape from anoikis/apoptosis. Conclusions: Somatic Copy number alterations are an independent predictor of metastatic potential. The data indicate a prognostic utility for using primary tumor genomics to assist in clinical decision making and developing therapeutics for prostate and likely other cancers. genomic DNA from 29 prostate cancer tumors with matched normals run on Affymetrix 6.0 SNP arrays.

2013-12-01 | E-GEOD-27105 | biostudies-arrayexpress

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