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
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
Project description:Murine renal carcinoma RENCA cells were injected in BALB/c mice to generated either primary tumours (orthotopically) or lunge metastases (through tail vein injection, or directly forming from primary tumors). Samples were snap-frozen and processed for single nucleus isolation and RNA seq analysis. Tumor cells expressed Interleukin-34 (IL34-OE) or an empty vector as control (Ctrl). The goal is to finely dissect tumor microenvironmental changes occurring in an IL34-enriched tumor microenvironment, either in primary tumors or lung metastases.
Project description:Tissue inhibitor of metalloproteinase 1 (TIMP-1) controls matrix metalloproteinase (MMP) activity through 1:1 stochiometric binding. Human TIMP-1 fused to a glycosylphosphatidylinositol (GPI) anchor (TIMP-1-GPI) shifts the activity of TIMP-1 from the extracellular matrix to the cell surface. TIMP-1-GPI treated renal cell carcinoma cells (RCC) show increased apoptosis and reduced proliferation. Transcriptomic profiling and regulatory pathway mapping were used to identify potential mechanisms driving these effects. Significant changes in inhibitor of DNA binding (IDs), TGF-β1/SMAD and BMP pathways resulted from TIMP-1-GPI treatment. These events were linked to reduced TGF-β1 signaling mediated by inhibition of proteolytic processing of latent TGF-β1 by TIMP-1-GPI. Activity of TIMP-1 from the extracellular matrix to the cell surface. TIMP-1-GPI treated renal cell carcinoma cells (RCC) show increased apoptosis and reduced proliferation. Transcriptomic profiling and regulatory pathway mapping were used to identify potential mechanisms driving these effects. Significant changes in inhibitor of DNA binding (IDs), TGF-β1/SMAD and BMP pathways resulted from TIMP-1-GPI treatment. These events were linked to reduced TGF-β1 signaling mediated by inhibition of proteolytic processing of latent TGF-β1 by TIMP-1-GPI. Renal cell carcinoma cells were transfected with empty vector, rhTimp1 and 2 concentrations of Timp1-GPI fusion protein
Project description:Clear cell renal carcinoma (CCRC) accounts for >80% of all kidney cancers but what triggers the tumorigenesis in the kidney and metastases in the bones are still under debate. Our hypothesis is that remodeling of the genomic fabrics of certain functional pathways and their interplay beyond critical limits are key causes of CCRC. We profiled the transcriptomes of metastatic chest wall and of two primary cancerous sites of the renal medulla and compared them with that of non-cancerous kidney resection margins. Samples were collected from a 74 years old male with metastatic carcinoma, consistent with renal cell carcinoma, clear cell type, Fuhrman grade 3, who undergone total right kidney nephrectomy and resection of a chest wall mass. Transcriptomic analysis pointed the tumor region in the right kidney that led to the chest wall metastases. The tumor proved heterogeneous not only in the expression level but also in the expression control, coordination and interplay of pathways responsible for cellular processes and genetic and environmental information processing. The differently regulated pathways in the two sides of the tumor: CCRC, and HIF-1, Vegfa and mTor signaling indicate activation of distinct mechanisms. Four-conditions (CTR = control - non-cancerous kidney resection margins, PTA = primary tumor side A, PTB = primary tumor side B, MET = chest wall metastasis. Four biological replicates of each condition.
Project description:We performed whole exome sequencing and copy number analysis for 15 triplets, each comprising normal colorectal tissue, primary colorectal carcinoma, and its synchronous matched liver metastasis. We analyzed the similarities and differences between primary colorectal carcinoma and matched liver metastases in regards to somatic mutations and somatic copy number alterationss (SCNAs). The genomic profiling demonstrated mutations in APC(73%), KRAS (33%), ARID1A and PIK3CA (6.7%) genes between primary colorectal and metastatic liver tumors. TP53 mutation was observed in 47% of the primary samples and 67% in liver metastatic samples. The grouped pairs, in hierarchical clustering showed similar SCNA patterns, in contrast to the ungrouped pairs. Many mutations (including those of known key cancer driver genes) were shared in the grouped pairs. The ungrouped pairs exhibited distinct mutation patterns with no shared mutations in key driver genes. Four ungrouped liver metastasis samples had mutations in DNA mismatch repair genes along with hypermutations and a substantial number of copy number of alterations. Genomically, colorectal and metastatic liver tumors were very similar. However, in a subgroup of patients, there were genetic variations in liver metastases in the loss of DNA mismatch repair genes. Copy number analysis of Affymetrix CytoScanHD arrays was performed for 15 primary colorectal carcinoma and 15 samples of their matched liver metastases. 15 normal samples prepared from each of the patient was used as the reference for the study. Nexus Copy number 6.1 software was used for somatic copy number alteration analysis.