Intratumor heterogeneity evaluation in primary HCC cells
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001001135 | EGA |
REPOSITORIES: EGA
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Project description:Cancer is a disease of the genome. Many genomic abnormalities have been found in a variety of cancer types, which are believed to be attributable to tumorigenesis as well as resistance to treatment and recurrence. Genomic heterogeneity in the same type of cancer or within a tumor reveals the complexity of cancer biology so that intratumor heterogeneity has become an inherent feature of cancer. In this study, we use whole-exome sequencing and array comparative genomic hybridization technology to examine the mutational profiling and copy number changes from multi-region samples within an esophageal cancer in order to understand the genomic phylogeny in the evolution of intratumor heterogeneity in esophageal cancer.
2014-12-31 | GSE60625 | GEO
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Project description:To examine the functional consequences of intratumor heterogeneity, subclonal populations (SCPs) were derived from the MDA-MB-468 triple-negative breast cancer cell line. Characterization of these SCPs revealed considerable variation in SCP tumor forming capacity with SCP #32 (SCP32) having an exceptional high tumor forming capacity. To investigate the proteomic differences between tumors of SCP32 and other SCPs, in TMT1, isobaric tandem mass tag (TMT) labeling combined with LC-MS/MS (TMT-MS) was performed on tumors of SCP03, SCP29 and SCP32 (n = 3 each) collected at 2 months post transplantation. In TMT2, isobaric tandem mass tag (TMT) labeling combined with LC-MS/MS (TMT-MS) was performed on tumors of the parental MDA-MB-468 cell line (n = 2), and both barcoded and non-barcoded versions SCP29 and SCP32 (two each) collected at 2 months post transplantation.
2022-02-16 | PXD022325 | Pride
Project description:Emerging biomarkers based on medical images and molecular characterization of tumor biopsies open up for combining the two disciplines and exploiting their synergy in treatment planning. We compared pretreatment classification of cervical cancer patients by two previously validated imaging- and gene-based hypoxia biomarkers, evaluated the influence of intratumor heterogeneity, and investigated the benefit of combining them in prediction of treatment failure. The imaging-based biomarker was hypoxic fraction, determined from diagnostic dynamic contrast enhanced (DCE)-MR images. The gene-based biomarker was a hypoxia gene expression signature determined from tumor biopsies. Paired data were available for 118 patients. Intratumor heterogeneity was assessed by variance analysis of MR images and multiple biopsies from the same tumor. The two biomarkers were combined using a dimension-reduction procedure. The biomarkers classified 75% of the tumors with the same hypoxia status. Both intratumor heterogeneity and distribution pattern of hypoxia from imaging were unrelated to inconsistent classification by the two biomarkers, and the hypoxia status of the slice covering the biopsy region was representative of the whole tumor. Hypoxia by genes was independent on tumor cell fraction and showed minor heterogeneity across multiple biopsies in 9 tumors. This suggested that the two biomarkers could contain complementary biological information. Combination of the biomarkers into a composite score led to improved prediction of treatment failure (HR:7.3) compared to imaging (HR:3.8) and genes (HR:3.0) and prognostic impact in multivariate analysis with clinical variables. In conclusion, combining imaging- and gene-based biomarkers enables more precise and informative assessment of hypoxia-related treatment resistance in cervical cancer, independent of intratumor heterogeneity.
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Project description:Ependymomas exist within distinct genetic subgroups, but the molecular diversity within individual ependymomas is unknown. We performed multiplatform molecular profiling of 6 spatially-distinct samples from an ependymoma with C11orf95-RELA fusion. DNA methylation and RNA sequencing distinguished clusters of samples according to neuronal development gene expression programs that could also be delineated by differences in magnetic resonance blood perfusion. Exome sequencing and phylogenetic analysis revealed epigenomic intratumor heterogeneity, and suggested that chromosomal structural alterations may precede accumulation of single nucleotide variants during ependymoma tumorigenesis. In sum, these findings shed new light on the oncogenesis and intratumor heterogeneity of ependymoma.
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Project description:Endometrial cancer (EC) is the most common female genital malignancy and the fourth most common cancer in women in the developing world1. EC has been traditionally classified into two main groups with different clinical, pathological and molecular features2,3. Type I or endometrioid endometrial carcinomas (EECs) account for about 75% of the cases and are typically estrogen-related and low-grade tumors with good prognosis that coexist or are preceded by endometrial hyperplasia, mainly diagnosed in perimenopausal women. In contrast, type II or non-endometrioid endometrial carcinomas (NEECs) are high-grade aggressive tumors associated with endometrial atrophy and poor prognosis, unrelated to estrogen and diagnosed in older women. These comprise several histological subtypes, being the most common the serous carcinomas (SEC)4. In recent years numerous large-scale studies of primary endometrioid and serous tumors have been performed5, revealing new mutated genes and establishing a new molecular subclassification based on the results obtained by The Cancer Genome Atlas (TCGA) consortium6, which implies different clinical outcomes. More recently, the genomic evolution of EC has been analyzed through a comparative study of samples from endometrial atypical hyperplasia, primary tumors and paired metastases7, revealing the presence of intratumor heterogeneity as previously described in primary EC and other tumor types8,9. However an in-depth study considering multiple regions from primary tumor and paired metastases has not been performed up to now to our knowledge. Here we analyze by whole-exome sequencing (WES), massive parallel targeted sequencing and array comparative genomic hybridization (aCGH) the clonal evolution and intratumor heterogeneity of 7 endometrioid and 3 serous metastatic endometrial carcinomas. Different locations from the primary tumor as well as from their paired metastases were included in the study, allowing the reconstruction of the spatial and temporal phylogenetic evolution of the tumor. Different phylogenetic evolution patterns were identified, independently of the classical histological or molecular classification of the tumor, although similar patterns were found in ovarian metastasis and recurrent disease.
2022-02-14 | GSE101447 | GEO
Project description:Intratumor genomic heterogeneity in stage II colon cancer
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Project description:To explore intratumor heterogeneity in gene expression profiles from patients with cervical cancer. Experimental Design: A total of 33 biopsies were obtained from 11 patients, sampling between two and five different areas for each tumor.The extracted RNA was hybridized onto the Affymetrix U133 Plus 2.0 oligonucleotide chip. The variance of expression within a patient (W), between patients (B) and the total variance (T =W + B) were calculated for each ProbeSet, and the ratio W/T was used as a measure of intratumor heterogeneity. Gene Ontology functional analysis was done to assess the function of genes that had high W/T (top 10%) and low W/T (bottom 10%) values.
2007-11-11 | E-GEOD-5787 | biostudies-arrayexpress
Project description:Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNAseq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to lowconfluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ~10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.
2022-02-10 | GSE196245 | GEO
Project description:Intratumor mutational heterogeneity has been documented in primary non-small cell lung cancer. Here, we elucidate mechanisms of tumor evolution and heterogeneity in metastatic thoracic tumors (lung adenocarcinoma and thymic carcinoma) using whole-exome and transcriptome sequencing, SNP array for copy number alterations (CNA) and mass spectrometry-based quantitative proteomics of metastases obtained by rapid autopsy. APOBEC-mutagenesis, promoted by increased expression of APOBEC3 region transcripts and associated with a high-risk germline APOBEC3 variant, strongly correlated with mutational tumor heterogeneity. TP53 mutation status was associated with APOBEC hypermutator status. Interferon pathways were enriched in tumors with high APOBEC mutagenesis and IFN- induced expression of APOBEC3B in lung adenocarcinoma cells in culture suggesting a role for the immune microenvironment in the generation of mutational heterogeneity. CNA occurring late in tumor evolution correlated with downstream transcriptomic and proteomic heterogeneity, although global proteomic heterogeneity was significantly greater than transcriptomic and CNA heterogeneity. These results illustrate key mechanisms underlying multi-dimensional heterogeneity in metastatic thoracic tumors.
2019-05-07 | PXD012845 | Pride