Use of Comprehensive Genomic Profiling for Biomarker Discovery for the Management of Non-Small Cell Lung Cancer Brain Metastases
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PROVIDER: PRJEB65294 | ENA |
REPOSITORIES: ENA
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Project description:Genomic Characterization of Brain Metastases
| PRJNA578191 | ENA
Project description:Genomic Characterization of Brain Metastases
| PRJNA578190 | ENA
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
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
Project description:We performed microarray analysis with two different chip platforms, Affymetrix and Agilent, on bone metastasis samples from breast cancer patients with only bone metastases and metastases in bone and visceral organs. We collected bone metastases biopsies from breast cancer patients with only bone metastases and metastases in bone and visceral organs. RNA was extracted from these samples and subjected to microarray analysis with the Agilent platform. Data were compared with a signsture obtained with the Affymetrix platform, to obtain a signature of differentially regulated genes between the two groups of patients This Series represents the Agilent data only. The Affymetrix data are provided in GEO Series GSE11078.
2011-12-29 | E-GEOD-34485 | biostudies-arrayexpress
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
2014-10-15 | E-GEOD-62321 | biostudies-arrayexpress
Project description:Purpose: There is an unmet clinical need for biomarkers to identify breast cancer patients who are at increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with HER2+ brain metastasis. Experimental Design: Gene expression of 19 HER2+ breast cancer brain metastases was compared with HER2+ nonmetastatic primary tumors. Gene Set Enrichment Analysis was used to identify a signature, which was evaluated for correlation with BRCA1 mutation status and clinical outcome using published microarray datasets and for correlation with pharmacological inhibition by a PARP inhibitor and temozolomide using published microarray datasets of breast cancer cell lines. Results: A BRCA1 Deficient-Like (BD-L) gene signature is significantly correlated with HER2+ metastases in both our and an independent cohort. BD-L signature is enriched in BRCA1 mutation carrier primary tumors and HER2-/ER- sporadic tumors, but high values are found in a subset of ER+ and HER2+ tumors. Elevated BD-L signature in primary tumors is associated with increased risk of overall relapse, brain relapse, and decreased survival. The BD-L signature correlates with pharmacologic response to PARP inhibitor and temozolomide in two independent microarray datasets, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. Conclusions: The BD-L signature is enriched in breast cancer brain metastases and identifies a subset of primary tumors with increased propensity for brain metastasis. Furthermore, this signature may serve as a biomarker to identify sporadic breast cancer patients who could benefit from a therapeutic combination of PARP inhibitor and temozolomide. Gene expression of 19 HER2+ human breast cancer brain metastases was compared with gene expression of 19 HER2+ nonmetastatic primary human breast tumors.
2014-04-24 | E-GEOD-43837 | biostudies-arrayexpress
Project description:Genomic Characterization of Duke Melanoma Brain Metastases
| PRJNA865438 | ENA
Project description:Genomic Characterization of Duke Melanoma Brain Metastases
| PRJNA865437 | ENA
Project description:BACKGROUND:Breast cancer brain metastases (BCBM) develop in about 20-30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques. METHODS:We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM. RESULTS:The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1. CONCLUSIONS:Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.
| S-EPMC5747948 | biostudies-literature