Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA393730 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Detailed Longitudinal Sampling of Glioma Stem Cells In Situ Reveals Chr7 Gain and Chr10 Loss As Repeated Events in Primary Tumor Formation and Recurrence
| PRJNA393726 | ENA
Project description:Detailed Longitudinal Sampling of Glioma Stem Cells In Situ Reveals Chr7 Gain and Chr10 Loss As Repeated Events in Primary Tumor Formation and Recurrence (SNP)
| PRJNA393731 | ENA
Project description:In this study, we developed an extensive dataset for a GBM case via the generation of polyclonal and monoclonal glioma stem cell lines from initial diagnosis, as well as from multiple sections of distant tumor locations of the deceased patient’s brain following tumor recurrence. Our analyses revealed the tissue-wide expansion of a new clone in the recurrent tumor as well as chromosome 7 gain and chromosome 10 loss as repeated genomic events in primary and recurrent disease. Moreover, chromosome 7 gain and chromosome 10 loss produced similar alterations in mRNA expression profiles in primary and recurrent tumors despite possessing other highly heterogeneous and divergent genomic alterations between the tumors. We identified ETV1 and CDK6 as putative candidate genes, and NFKB (complex), IL1B, IL6, Akt and VEGF as potential signaling regulators, as potentially central downstream effectors of chr7 gain and chr10 loss. Finally, the differences caused by the transcriptomic shift following gain of chromosome 7 and loss of chromosome 10 were consistent with those generally seen in GBM samples compared to normal brain in large-scale patient-tumor data sets.
2017-10-01 | GSE101113 | GEO
Project description:In this study, we developed an extensive dataset for a GBM case via the generation of polyclonal and monoclonal glioma stem cell lines from initial diagnosis, as well as from multiple sections of distant tumor locations of the deceased patient’s brain following tumor recurrence. Our analyses revealed the tissue-wide expansion of a new clone in the recurrent tumor as well as chromosome 7 gain and chromosome 10 loss as repeated genomic events in primary and recurrent disease. Moreover, chromosome 7 gain and chromosome 10 loss produced similar alterations in mRNA expression profiles in primary and recurrent tumors despite possessing other highly heterogeneous and divergent genomic alterations between the tumors. We identified ETV1 and CDK6 as putative candidate genes, and NFKB (complex), IL1B, IL6, Akt and VEGF as potential signaling regulators, as potentially central downstream effectors of chr7 gain and chr10 loss. Finally, the differences caused by the transcriptomic shift following gain of chromosome 7 and loss of chromosome 10 were consistent with those generally seen in GBM samples compared to normal brain in large-scale patient-tumor data sets.
2017-10-01 | GSE101110 | GEO
Project description:Glioblastomas (GBMs) are divided into CpG Island Methylator Phenotype (CIMP) and non-CIMP tumors. Non-CIMP GBMs derive from cells with non-disjunction of chromosome (chr7) and chromosome 10 (chr10), resulting in chr7 gain and chr10 loss, while CIMP GBMs have mutations in isocitrate dehydrogenase 1 or 2 (IDH1/2). Gain of chr7 is largely driven by PDGFA, but other genes on chr7 are likely to contribute to fitness gains and aggressiveness of these GBMs. We computationally investigated genes on chr7 whose gene expression correlated with survival, identifying HOXA5 as a potential driver of proneural gliomagenesis. Using a combination of human GBM cells and mouse PDGF-driven gliomas, we showed that HOXA5 drives increased proliferation and radiation resistance in culture and in vivo. These phenotypes appear to be in part due to effects on p53 and other apoptosis-related genes.
2018-04-09 | GSE89409 | GEO
Project description:Ependymoma (EPN) posterior fossa group A (PFA) has the highest rate of recurrence and the worst prognosis of all EPN types. At relapse, it is typically incurable even with re-resection and re-irradiation. The biology of recurrent PFA EPN remains largely unknown, which hinders clinical advances. In this large longitudinal multicenter study, we examined matched samples of primary and recurrent disease from PFA EPN patients (n=95) to investigate the biology of recurrence. DNA methylomic data was used to measure copy number variants (CNVs), revealing progressive large scale chromosome gains and losses in successive recurrences. These CNV changes were dominated by chromosome 1q gain and/or 6q loss (1q+/6q-), both previously identified as high-risk factors in PFA EPN, which were present in ~20% at presentation but increased to ~60% at 1st recurrence. These CNV changes were correlated with hypomethylation of heterochromatin associated DNA at presentation. Evolution of chromosomal aberrations was further explored using CNV analysis of single-nuclei RNAseq on approximately 46,000 PFA EPN cells from 6 matched pairs of primary and 1st relapse tumors that harbored CNV changes at recurrence. No evidence of rare subclones in primary tumors was observed, suggesting that chromosomal rearrangement events occur after initial presentation. Cellular and molecular characteristics associated with CNVs were examined by single-nuclei RNAseq, bulk transcriptomic analysis and immunohistochemistry, revealing that 1q+/6q- PFA have a significantly higher mitotic index, increased proportions of proliferative epithelial progenitors and decreased differentiated neoplastic subpopulations. Multivariate survival analyses showed that cases with 1q gain or 6q loss at 1st recurrence were significantly more likely to recur than cases with no 1q or 6q change. The high prevalence of 1q+/6q- at recurrence and the associated shortened survival, suggest that both these abnormalities should be routinely tested for, and used for trial stratification.
2023-06-01 | GSE227644 | GEO
Project description:Chromosomal structural mutations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural mutations, we analyzed a representative sampling of the major types of breast tumor samples for detailed structural mutations using paired-end tag sequencing of long-insert genomic DNA (DNA-PET) with matched transcriptome ascertainment by RNA-seq. Compared with other structural mutations, tandem duplications are enriched around partners of fusion transcripts and demarcate regions of high gene expression. Moreover tandem duplications appear to be early events in tumor evolution by facilitating subsequent downstream amplification and deletion of important adjacent cancer associated genes. In a detailed reconstruction of events in chr17, we found large unpaired-inversions connect a duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently co-amplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in human normal mammary epithelial cells. Finally, using in silico approaches, we determined that genes whose expression in breast tumors are associated with either poor or good clinical prognosis appear clustered together in segments of frequent amplification or deletion, suggesting that structural abnormalities induce the loss or gain of blocks of adjacent genes with oncogenic or growth suppressor function. These analyses suggest that structural mutations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously. RNA sequencing of four primary breast cancer RNA samples (SOLiD, Applied Biosystems).
2014-07-01 | E-GEOD-57914 | biostudies-arrayexpress
Project description:Intratumor heterogeneity fosters the evolution of the genome leading to metastatic progress and therapy resistance . Here, we investigate the relative contribution of tumor aneuploidy and genomic heterogeneity involving CNAs and mutational events as prognostic and predictive determinants for disease recurrence in early-stage colon cancer patients. We combined SNP arrays, targeted next-generation sequencing, fluorescence in situ hybridization and inmunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the subclonality of copy-number alterations (CNAs) and mutations, CD8+ lymphocyte infiltration levels and their association with time to recurrence (TTR).
2021-12-01 | GSE171777 | GEO
Project description:Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling.
2024-02-29 | GSE256268 | GEO
Project description:Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling.
2024-02-29 | GSE255773 | GEO