Browse
Submit Data
Databases
API
Help

Dataset Information

5 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The Role of Tumor-associated Macrophages in Colorectal Liver Metastases

ABSTRACT: Colorectal cancer is a major cause of mortality worldwide. Most patients develop colorectal liver metastases (CLM), and for such patients hepatectomy combined with chemotherapy may be curative. Nevertheless, in the era of precision medicine there is a critical need of prognostic markers to cope with the heterogeneity of CLM patients. Tumor-associated macrophages (TAMs) pave the way to tissue invasion and intravasation providing a nurturing microenvironment formetastases. The quantification of immune landscape of tumors has provided novel prognostic indicators of cancer progression, and the quantification of TAMs might explain the heterogeneity of CLM patients. Here, we will investigate the development of a new diagnostic tool based on TAMs with the aim to define the causative role of TAMs in CLM patients. This will open new clinical scenarios both for the diagnosis, therapy and prognosis, leading to the refinement of the therapeutic output in a personalized medicine perspective.

DISEASE(S): Neoplasm Metastasis,Neoplasms, Second Primary,Liver Metastases,Immunotherapy,Colorectal Cancer,Liver Neoplasms,Colorectal Liver Metastases

PROVIDER: 2300850 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Json Xml

Similar Datasets

Gene expression profile of tumor-associated macrophages in human colorectal liver metastasis (CLM)

Project description:The immune landscape impacts outcome and therapeutic response in many tumor types, including colorectal liver metastases (CLM). It has long been known that in vitro polarized macrophages differ in morphology. Here we tested the hypothesis that morphology of tumor-associated macrophages (TAMs) in CLM represents a correlate of function with prognostic significance. Density and morphological metrics (area and perimeter) of TAMs were measured and correlated with clinic-pathological prognostic variables. While density of TAMs did not correlate with survival of CLM patients, cell area identified small and large macrophages that associated with 5-year disease-free survival rate of 27.8% and 0.2% respectively (P<0.001). RNA sequencing of morphologically distinct macrophages identified LXR/RXR as the most enriched pathway in large macrophages and upregulation of genes involved in cholesterol metabolism, phagocytosis and downregulation of the inflammatory program. These results support that accurate, morphometric characterization can serve as a simple readout of TAM diversity with prognostic significance.

2020-08-05 | GSE131353 | GEO

Intrahepatic CD69+ Vd1 T cells recirculate in the blood of patients affected by liver metastatic colorectal cancer and predict their overall survival

Project description:More than 50% of all patients with colorectal cancer (CRC) develop liver metastasis (CLM) that are characterized by poor prognosis and lack of reliable prognostic markers. Vd1 T cells are gd T innate-like lymphocytes endowed with a broad array of antitumor functions at peripheral tissues, but little is known about their impact in the pathophysiology of CLM. We assessed the phenotype and functions by flow cytometry, clonotype by gdTCR-sequencing, transcriptional profiles by single cell RNA-sequencing and clinical impact of human Vd1 T cells isolated from peripheral blood (PB), tumor-free liver parenchyma surrounding CLM (TFLP) and metastatic tumor (MT) from a large cohort of CLM patients. We show here that CLM tissue is highly enriched of CD69+ Vd1 T effector (TEF) cells in the TFLP area. These cells have a peculiar phenotype, high anti-tumour potential and correlate with a better clinical outcome in terms of lower numbers of liver metastatic lesions and longer overall survival (OS). Moreover, the specific terminally differentiated (TEMRA) CD69+ Vd1 cells can egress CLM tissue to re-circulate in the bloodstream, where they retains high effector functions and show phenotypic/transcriptional and gdTCR profiles that resemble their liver origin. Importantly, high frequencies of CD69+TEMRA Vd1 cells in PB predict a longer OS of CLM patients that is not affected by the neo-adjuvant chemotherapy/immunotherapy regimens administered to CLM patients. The presence at high frequencies of liver memory CD69+TEMRA Vd1 cells in CLM homing to PB represents a new important target to better predict CLM clinical outcomes and to develop novel protocols of adoptive cell transfer therapies.

2023-10-03 | GSE159051 | GEO

Comparative profiling of primary colorectal carcinomas and liver metastases

Project description:PURPOSE: We sought to identify genes of clinical significance to predict survival and the risk for colorectal liver metastasis (CLM), the most common site of metastasis from colorectal cancer (CRC). PATIENTS AND METHODS: We profiled gene expression in 31 specimens from primary CRC and 32 unmatched specimens of CLM, and performed Significance Analysis of Microarrays (SAM) of the expressed genes between these two groups. To characterize the clinical relevance of two highly-ranked differentially expressed signature genes, we analyzed the expression of secreted phosphoprotein 1 (SPP1 or osteopontin) and lymphoid enhancer factor-1 (LEF1) by immunohistochemistry using a tissue microarray (TMA) representing an independent set of 154 patients with primary CRC. Supervised analysis using SAM identified 963 genes with significantly higher expression in CLM compared to primary CRC, with a false discovery rate of <0.5%. TMA analysis showed SPP1 and LEF1 protein overexpression in 60% and 44% of CRC cases, respectively. Subsequent occurrence of CLM was significantly correlated with the overexpression of LEF1 (chi-square p = 0.035), but not SPP1 (p = 0.14). Kaplan Meier analysis revealed significantly worse survival in patients with overexpression of LEF1 (p < 0.01), but not SPP1 (p = 0.11). Both univariate and multivariate analyses identified stage (p < 0.0001) and LEF1 overexpression (p < 0.05) as important prognostic markers, but not tumor grade or SPP1. CONCLUSION: Among signature genes differentially expressed between CLM and primary CRC, we demonstrate overexpression of LEF1 in primary CRC to be a prognostic factor for poor survival and increased risk for liver metastasis. cDNA microarrays from the Stanford Functional Genomics Facility were used to perform mRNA transcript profiling of 31 freshly-frozen primary colorectal cancer specimens, and compared to published profiles of 32 unmatched colorectal liver metastases and 12 normal liver specimens.

2011-03-22 | E-GEOD-22834 | biostudies-arrayexpress

Comparative profiling of primary colorectal carcinomas and liver metastases

2011-03-22 | GSE22834 | GEO

DNA methylation data comparing Wilms tumor primary samples to patient-derived xenografts

Project description:The lack of model systems limits the preclinical testing of novel therapies to address Wilms tumor patient groups with poor outcomes. Therefore, we established 45 heterotopic Wilms tumor patient-derived xenografts (WTPDX) in CB17 scid-/- mice that capture the biological heterogeneity of Wilms tumor (WT). These WTPDX include six showing diffuse anaplasia, nine from patients who went on to experience disease relapse, and thirteen from patients with bilateral disease. WTPDX retained the genetic alterations and the global transcriptomic and methylation profile of corresponding primary WT. In addition, favorable histology WTPDX were chemosensitive, while unfavorable histology WTPDX were resistant to conventional chemotherapy with vincristine, actinomycin-D, and doxorubicin. This WTPDX library is a unique scientific resource that retains the spectrum of biological heterogeneity present in WT and provides an essential tool for the testing of novel targeted therapies in the era of precision medicine.

2019-02-14 | GSE110697 | GEO

Gene expression data comparing Wilms tumor primary samples to patient-derived xenografts

2019-02-14 | GSE110696 | GEO

Single cell RNA-seq profiling of patient-derived Merkel cell carcinoma tumor samples

Project description:Merkel cell carcinoma (MCC), a rare but aggressive neuroendocrine cancer of the skin, remains a challenge in the era of precision medicine. MCC tumor heterogeneity has been attributed to the variant disease etiologies, mediated by either UV exposure or Merkel cell polyomavirus (MCPyV). However, over the years it has become clear that these two groups are largely similar in clinical presentation, prognosis, and treatment response to immune-checkpoint inhibitors. We therefore dissected the transcriptomic heterogeneity of a panel of patient tumors samples, at the single-cell resolution, to gather further insights.

2023-05-22 | GSE226438 | GEO

microRNA profiling in different stages of rheumatoid arthritis

Project description:Determine the comprehensive miRNA expression profile in RNA extracted from whole blood samples from healthy controls (CTRL), individuals positive to CCP antibodies >25UI/ml (CCP+), early rheumatoid arthritis (ERA) and established rheumatoid arthritis (CRA) according to the ACR/EULAR 2010 classification criteria. Several miRNAs were overexpressed on ERA patients. We selected 5 miRNAs (miR-361-5p, miR-23a-3p, miR-223-3p, miR-4634 and miR-128-3p) for its quantification on a bigger group of subjects by RT-qPCR and the results showed good concordance with microarray expression data.

2019-06-13 | GSE115885 | GEO

ERa profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions [ChIP-seq]

Project description:Estrogen Receptor alpha (ERa) is the main driver of luminal breast cancer development and progression, and represents the main drug target in patient care. ERa chromatin binding has been extensively studied in breast cancer cell lines and a number of human tumors, often focused on differential binding patterns between groups or conditions. However, little is known about the inter-tumor heterogeneity of ERa chromatin action. Here, we use a large set of ERa ChIP-seq data from 70 ERa+ breast cancers (40 women and 30 men) to explore general inter-patient heterogeneity in ERa DNA binding in breast cancers. We found a total universe of 84,565 and 101,653 ERa sites in females and males respectively, with merely 1.2% and 5% of sites shared in at least half of the tumors analyzed, reflecting a high level of inter-patient heterogeneity. This heterogeneity was found to be most variable at putative enhancers as opposed to promoter regions, potentially reflecting a level of functional redundancy in enhancer action. Interestingly, commonly shared ERa sites showed the highest estrogen-driven enhancer activity, as determined using a massive parallel reporter assay, and were most-engaged in long-range chromatin interactions. In addition, the most-commonly shared ERa-occupied enhancers were found enriched for breast cancer risk SNP loci. We experimentally illustrate such SNVs can impact chromatin binding potential for ER and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we could confirm these variations to associate with differences in expression for the target gene. Cumulatively, our data reveal a natural hierarchy of ERa-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ERa landscape, with the most-common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

2024-03-27 | GSE244840 | GEO

ERa profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions [Hi-C]

2024-03-27 | GSE244844 | 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