7154 results for "canc*"

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• Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

  Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity, and intratumoral heterogeneity (ITH) represents a significant barrier to GC patient outcomes. In this study, we applied GeoMx DSP technology to identify ITH in GC. We found spatially colocalized RNA-based intratumor subgroups within samples, each correlated with distinct spatially oriented TME and immune profiles. The findings broadening our understanding of the spatial and molecular complexity of GC ITH and offering a valuable data resource for future exploration and discovery.

  Study EGAS50000000345

• Singapore Gastric Cancer Consortium GeoMx DSP tissue microarray (SGCC TMA) cohort

  Gastric cancer (GC) remains a significant global health challenge due to its high heterogeneity, with intratumoral heterogeneity (ITH) posing a major obstacle to effective patient outcomes. In this study, utilizing GeoMx Digital Spatial Profiler (DSP) technology, we specifically investigated ITH within GC patients by comparing tumor core regions to tumor edge regions. Our findings indicate that tumor edge regions exhibit more advanced tumor activity, akin to the G2-like progressed state, compared to tumor core regions. The findings confirm the spatial locations of G2 RNA-ITH subregions and support the conclusions drawn from the discovery cohort.

  Study EGAS50000000640

• Bladder cancer subtyping study across 4 atezo clinical trials

  Checkpoint inhibitors targeting the PD-1/PD-L1 interaction have revolutionized cancer therapy across many indications. In urothelial carcinoma (UC), several PD-1/PD-L1 inhibitors have been approved for treatment in localized and metastatic disease. While these agents provide durable clinical benefit in a number of patients, the majority do not respond. A better understanding of the molecular mechanisms underlying response and resistance is needed to tailor existing treatments and develop new therapeutics in UC. We profiled tumors from 2803 patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab in metastatic UC and muscle-invasive bladder cancer by RNA-seq, a targeted DNA panel, immunohistochemistry, and digital pathology. A machine learning algorithm identified four UC transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care was observed in immune and basal tumors (45% of patients). Digital pathology showed enrichment of human interpretable features in specific molecular subtypes, and a self-supervised approach could classify molecular subtypes from H&E slides with high accuracy, suggesting that machine-based image interpretation could accelerate tumor molecular profiling. Somatic alterations showed limited capacity to identify responders. Finally, mechanisms of benefit with PD-L1 blockade appeared different in immune and basal tumors, with immune tumors benefiting from B/plasma cell enrichment, while basal tumors benefited from granulocyte enrichment. This study represents the largest integration of UC molecular and curated clinical data in randomized clinical trials to date, paving the way for prospective clinical studies tailoring treatment regimens to specific tumor molecular subtypes in UC and other indications.

  Study EGAS50000000497

• The WID-EC test for the detection and risk prediction of endometrial cancer

  Study EGAS00001005033

• The DNA methylome of cervical cells and risk of ovarian cancer

  Study EGAS00001005045

• Follicular Lymphoma Whole Genome and Transcriptome Sequencing

  Study EGAS00001006646

• plasma DNA LINE-1 targeted bisulfite sequencing: a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Study EGAS50000000446

• The function of circular RMST in neuroendocrine tumours

  Circular RNA (circRNA) is a class of noncoding RNA with regulatory potentials. Its role in the transdifferentiation of prostate and lung adenocarcinoma into neuroendocrine prostate cancer (NEPC) and small cell lung cancer (SCLC) remains unexplored. Here we identified circRMST as an exceptionally abundant circRNA predominantly expressed in NEPC using total RNA-seq profiling of patient samples. In addition, circRMST is also abundantly expressed in SCLC. Functional studies using shRNA, siRNA, CRISPR-Cas13 and Cas9 consistently demonstrate that circRMST is essential for tumour growth and the expression of ASCL1, a master regulator of neuroendocrine fate. Mechanistically, circRMST physically interacts with lineage transcription factors NKX2-1 and SOX2. Loss of circRMST induces NKX2-1 protein degradation through autophagy-lysosomal pathway and alters the genomic binding of SOX2, collectively leading to the loss of ASCL1 transcription.

  Study EGAS50000000897

• Total RNA-seq of CRPC and NEPC

  This dataset contains total RNA-seq of 10 patient samples: 5 castration resistant prostate cancer (CRPC) and 5 neuroendocrine prostate cancer (NEPC). Total RNA-seq was constructed using ribosomal RNA-depleted random hexamer-primed RNA library preparation kit and sequenced on Illumina at pair-end 150bp. Total RNA-seq allows for circular RNA and mRNA analyses. Each sample was sequenced on two separate lanes, therefore, two pairs of raw fastq files (4 files in total) are provided for each sample.

  Dataset EGAD50000001312

• South African breast cancer GWAS genotype data in VCF format

  South African breast cancer GWAS genotype data for 2823 female African breast cancer cases. The data was generated using the H3Africa Custom microarray and genotyped on the Illumina HiScan instrument. The dataset is in VCF format.

  Dataset EGAD00010002732