3429 results for "ovarian cancer"

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• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Prior studies have suggested the biomarker potential of plasma circulating tumor DNA (ctDNA) in cancer patients treated with immune checkpoint inhibitors (ICIs). In order to characterize the potential role of ultrasensitive ctDNA detection in the management of these patients we have performed tumor whole-genome-informed, ultrasensitive ctDNA analysis—tracking approximately 1,800 tumor-specific mutations per patient—in a retrospective cohort (n=136) and a prospective validation cohort (n=66) across 24 cancer types treated with ICIs alone or in combination with bispecific antibodies or immune cell engagers. Analyzing 1,455 longitudinal samples, we found that ctDNA molecular response measured as early as 3 weeks after treatment initiation correlated with improved progression-free and overall survival, while ctDNA clearance at any time strongly correlated with radiological response and prolonged survival. Additionally, ctDNA dynamics distinguished true progression from pseudoprogression and predicted outcomes in patients receiving continued immunotherapy beyond initial progression. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities.

  Study EGAS50000001333

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Analysis of DNA methylation in normal B cells and chronic lymphocytic leukemia

  Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes.As second study using these samples focued on evolution and resulting intra-tumor heterogeneity in CLL. We used 450k bead-chip arrays to study DNA methylomes in 68 chronic lymphocytic leukemia (CLL) cases, including 28 serial cases. The result establishs linked evolution of epigenetic and genetic alterations in progressive disease, revealing an important aspect of the biology of epigenetics in cancer.

  Study EGAS00001000534

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Germline mutation of BRCA2 increases the lifetime risk of developing prostate cancer (PCa) by over 700%. BRCA2-mutant PCa have poorer prognosis than sporadic PCa, with rapid development of metastatic, castrate-resistant prostate cancer (mCRPC) and 5-year cancer-specific survival rates of ~50-60%1-4. Despite this, unique genomic driver events that explain the aggressiveness of localized BRCA2-mutant PCa are lacking. We used whole-genome sequencing to fully characterize 14 BRCA2-mutant PCa and demonstrate that BRCA2-mutant PCa is associated with increased genetic instability and a mutually exclusive mutational burden when compared to sporadic PCa. Importantly, BRCA2-mutated cancers are defined by unique copy number gains and hypomethylation events, including alterations in the MED12L/MED12 axis, which are found solely in mCRPC and are enriched in PCa tumours harbouring aggressive intraductal carcinoma (IDC-P) pathologic sub-types. Our findings begin to explain the clinical entity of BRCA2-mutated PCa as these tumours have a unique and aggressive genotype de novo, associated with IDC-P and mCRPC, even in the hormone-naive setting.

  Study EGAS00001001615

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Analysis of four key cell types (epithelial, fbroblast, myeloid and T cells)

  Alterations of the normal prostate epithelial cell genome trigger the emergence of carcinoma, however cancer-only analyses of genomic aberrations have resulted in little clinical translation. A deep understanding of the tumor microenvironment is likely to inform on key drivers of disease progression and novel therapeutic opportunities. We investigated the role of key cell types along disease progression, profiling the RNA abundance of 52 samples from 13 patients enriched for one of four key cell types, spanning a wide CAPRA-S risk score range. Using a novel differential transcription Bayes method, TABI, we avoided a priori patient stratification, and mapped transcriptional alteration events to specific risk scores. The developmental and cell-type resolution yielded a landscape of concurrent transcriptional alterations from the tumour microenvironment, including key hallmarks. These transcriptional signatures permitted the identification of a “high survival” patient cluster in an independent prostate cancer dataset. Most importantly, together with our integrated transcriptional analysis, differential tissue composition analysis provided evidence for a key role for monocytes and macrophages in prostate cancer progression and disease recurrence.

  Study EGAS00001003579

• METABRIC: Data from Pereira et al (2016), The somatic mutation profiles of 2433 breast cancers refine their genomic and transcriptomic landscapes. Nat Comms 7.

  The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2433 primary breast tumours that have copy number aberration (CNA), gene expression, and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters, and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intratumour heterogeneity using mutant allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intratumour heterogeneity are in general associated with worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intratumour heterogeneity. These results emphasise the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

  Study EGAS00001001753

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999