Polyclonality and Metabolic Heterogeneity in a Colorectal Tumor Model
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1133005 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The monoclonal origin of cancer is widely accepted, although numerous studies suggest that some are of polyclonal origin. Loss-of checkpoints in transformed cells gives rise to carcinomas comprising a wide diversity of cell types that fulfill distinct, even complementary, metabolic functions, contrasting with a hypothetical monoclonal origin. Here, using a Drosophila intestinal tumor model, we show that, despite an identical genetic background, these tumors 1), comprise a conserved set of different metabolic-specialized clusters; 2), are always polyclonal and derive from several clones characterized by distinct metabolic specificity; 3) depend on motility of the founder clones for their growth; 4) share metabolic needs similar to those of human cancers. In summary, our study indicates that, in this model, tumor formation always requires assembly between founder clones potentially providing distinct cellular functions, as visualized by their metabolic heterogeneity. Thus, this polyclonal assembly would constitute a critical step of tumor progression.
2025-06-24 | GSE271736 | GEO
Project description:Patient derived organoids (PDOs) have been established as a 3D culture model which closely recapitulates the in vivo tumor biology. However, one limitation of this culture model is the lack of tumor microenvironment which has a significant role in tumor progression and drug response. To address this, we established and molecularly characterized a novel 3D co-culture model of colorectal cancer (CRC) based on PDOs and patient matched fibroblasts. Both normal and cancer associated fibroblasts, NFs and CAFs respectively, were able to support organoid growth without addition of niche factors to the media. Additionally, co-cultures showed closer resemblance to primary patient material than organoid mono-cultures as evaluated by histology. Finally, RNA gene expression signatures of tumor cells and fibroblasts isolated from mono- or co-cultures demonstrated that co-cultures support greater cell type heterogeneity. In this proteomics dataset we compared pairs of NFs and CAFs derived from five patients. Collectively, we present a newly established human derived organoid-fibroblast model which, closely recapitulates in vivo tumor heterogeneity and involves the tumor microenvironment.
2023-03-14 | PXD032047 | Pride
Project description:About 50% of colorectal cancer patients develop liver metastases. Patients with metastatic colorectal cancer have 5-year survival rates below 20% despite new therapeutic regimens. Tumor heterogeneity has been linked with poor clinical outcome, but was so far mainly studied via bulk genomic analyses. In this study we performed spatial proteomics via MALDI mass spectrometry imaging on six patient matched CRC primary tumor and liver metastases to characterize interpatient, intertumor and intratumor hetereogeneity. We found several peptide features that were enriched in vital tumor areas of primary tumors and liver metastasis and tentatively derived from tumor cell specific proteins such as annexin A4 and prelamin A/C. Liver metastases of colorectal cancer showed higher heterogeneity between patients than primary tumors while within patients both entities show similar intratumor heterogeneity sometimes organized in zonal pattern. Together our findings give new insights into the spatial proteomic heterogeneity of primary CRC and patient matched liver metastases.
2023-02-17 | PXD039409 | Pride
Project description:Intra-tumor heterogeneity of tumor-initiating cell (TIC) activity drives colorectal cancer (CRC) progression and therapy resistance. Here, we used single-cell mRNA-sequencing (scRNA-seq) of patient-derived CRC models to decipher distinct cell subpopulations based on their transcriptional profiles. Cell type-specific expression modules of stem-like, transit amplifying-like, and differentiated CRC cells resemble differentiation states of normal intestinal epithelial cells. Strikingly, identified subpopulations differ in proliferative activity and metabolic state. In summary, we here show at single-cell resolution that transcriptional heterogeneity identifies functional states during TIC differentiation. Targeting transcriptional states associated to cancer cell differentiation might unravel vulnerabilities in human CRC.
2021-05-07 | PXD018230 | Pride
Project description:Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcrip-tomes. Here, by scRNA-sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference of CNV-ECs revealed that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. EC phenotypes displayed metabolic transcriptome heterogeneity. Hypothesizing that conserved genes are more important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome scale metabolic modeling, and gene expression me-ta-analysis in multiple cross-species datasets, followed by functional validation, to identify the top-ranking metabolic targets SQLE and ALDH18A1, involved in EC proliferation and collagen production, respectively, as novel angiogenic targets.
2020-03-31 | E-MTAB-8604 | biostudies-arrayexpress
Project description:Colorectal cancer often arises from adenomatous polyps. Polyps can grow and progress to cancer, but may also remain static in size, regress, or resolve. Prediciting which progress to cancer and which remain benign is difficult. We developed a long-lived murine model of colorectal cancer with tumors that can be followed by colonoscopy. Our aim was to assess whether these tumors have similar growth patterns and histologic fates to human colorectal polyps to identify features to aid in risk stratification of colonic tumors. Long-lived Apcin/+ mice were treated with 4% dextran sodium sulfate to promote colonic tumorigenesis. Tumor growth patterns were characterized by serial colonoscopy, and pathology was determined. Serial biopsies of tumors were obtained for immunohistochemistry and gene expression profiling by microarray analysis with Affymetrix Whole Genome array. Tumors (n=424) grew, remained static, regressed, or resolved over time with different relative frequencies. Newly developed tumors demonstrated dynamic growth patterns with higher rates of growth and resolution, while more established tumors tended to remain static in size. Colonic tumors were hyperplastic lesions (3%), adenomas (73%), intramucosal carcinomas (20%), or adenocarcinomas (3%). Differentially expressed genes between adenomas and intramucosal carcinomas were identified. We did not identify differentially expressed genes between early and late biopsies from the same tumor. This novel murine model of intestinal tumorigenesis develops colonic tumors that can be monitored by serial colonoscopy, mirror growth patterns seen in human colorectal polyps, and progress to colorectal cancer. Further characterization of cellular and molecular features are needed to determine which features can be used to risk-stratify polyps for progress to colorectal cancer and potentially guide prevention strategies. F1 (SWR x C57BL/6) Apcin/+ mice who had been given two treatments of 4% dextran sodium sulfate in drinking water at weaning underwent colonoscopy around 80 days of age. Those with distal colonic tumors amenable to biopsy had two biopsies taken at that time. Tumors were monitored by colonoscopy every 14 days. Every 28 days, two additional biopsies were taken of each tumor. This protocol was repeated until mice were moribund. Six tumors were removed after sacrifice. The earliest and latest biopsies of each tumor were selected for RNA extraction and Affymetrix hybridization.
2014-05-03 | E-GEOD-46626 | biostudies-arrayexpress
Project description:Endothelial cell (EC) metabolism regulates angiogenesis and is an emerging target for anti-angiogenic therapy in tumor and choroidal neovascularization (CNV). In contrast to tumor ECs (TECs), CNV-ECs cannot be isolated for unbiased metabolic target discovery. Here we used scRNA-sequencing to profile 28,337 choroidal ECs (CECs) from mice to in silico distinguish healthy CECs from CNV-ECs. Trajectory inference suggested that CNV-ECs plastically upregulate genes in central carbon metabolism and collagen biosynthesis during differentiation from quiescent postcapillary venous ECs. CEC-tailored genome scale metabolic modeling predicted essentiality of SQLE and ALDH18A1 for proliferation and collagen production, respectively. Comparative analysis in TECs revealed more outspoken metabolic transcriptome heterogeneity in subtypes and consistent upregulation of SQLE and ALDH18A1 across tumor types. Inhibition of SQLE and ALDH18A1 reduced sprouting angiogenesis in vitro. These findings demonstrate the potential of integrated scRNA-seq analysis to identify angiogenic metabolic targets in disease ECs.
2020-06-25 | E-MTAB-8119 | biostudies-arrayexpress
Project description:Colorectal cancer arises in part from the cumulative effects of multiple gene lesions. Recent studies in selected cancer types have revealed significant intra-tumor genetic heterogeneity and highlighted its potential role in disease progression and resistance to therapy. We hypothesized the existence of significant intra-tumor genetic heterogeneity in rectal cancers involving variations in localized somatic mutations and copy number abnormalities. Two or three spatially disparate areas from each of six rectal tumors were dissected and subjected to next-generation whole exome DNA sequencing, Oncoscan SNP arrays, and targeted confirmatory sequencing and analysis. The resulting data were integrated to define subclones using SciClone. Mutant-allele tumor heterogeneity (MATH) scores, mutant allele frequency correlation, and mutation percent concordance were calculated, and Copy number analysis including measurement of correlation between samples was performed. Affymetrix OncoScan V3 arrays were run on all tumor samples. The OncoScan array platform consists of a set of 217k probes designed specifically for profiling tumors. The overall resolution of the assay for detecting copy number change generates data at 50-100kb resolution across a set of 891 cancer genes, and 300-400kb across the rest of the genome. Raw array florescence intensity data generated on the Affymetrix scanners in the form of CEL files were loaded into the OncoScan Console software v.1.1.0 (Affymetrix, Santa Clara, California). Quality control statistics as well as integrated OSCHP files were generated by OncoScan Console. The standard Affymetrix reference control file for OncoScan data was used for processing the arrays.
2015-09-24 | E-GEOD-73365 | biostudies-arrayexpress
Project description:In order to better understand the intra-tumor heterogeneity of colorectal cancer, we performed morphology-resolved profiling of stage II-IV primary tumors. The morphological patterns of interest were: complex tubular, desmoplastic, mucinous, papillary, serrated, and complex/tubular. In addition, we profiled a number of tumor-adjacent normal, supportive stroma, and polyp regions. Addionaly, several whole-tumor samples were added, from sections immediately successive to the ones used for region sampling. The manually-annotated regions were macrodissected, RNA extracted and hybridized on Clariom D (human) microarrays. The resulting gene expression profiles allowed the identification of major determinants of differences between the regions, differences that were present within tumors as well.
2023-08-02 | E-MTAB-12599 | biostudies-arrayexpress
Project description:Patient-derived organoid fibroblast co-cultures closely mimic tumor cell heterogeneity of colorectal cancer
| PRJNA816490 | ENA