3331 results for "ovarian cancer"

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• Single-Cell RNA-seq of Primary High Grade Serous Carcinoma

  Single-cell RNA Sequencing of CD45- cancer cells.

  Study EGAS50000000068

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  We discovered a conserved neural tri- lineage cancer hierarchy centered around glial progenitor-like cells. We also found that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.

  Study EGAS00001004422

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166

• Primary ER-positive Breast Cancer Treated with Neoadjuvant Letrozole

  These are tumor biopsies and corresponding normal samples from patients with early stage ER+/HER2- breast cancer who had received the aromatase inhibitor letrozole for 10-21 days prior to surgery.

  Study phs000857

• The RNA, ChIP and whole exome sequencing analysis of human colorectal cancer organoids and normal colon organoids treated with (+)-JQ1

  To reveal the mechanism of anti-tumor effect of (+)-JQ1, we performed RNA, ChIP and whole exome sequencing using human colorectal cancer and normal colon organoids.

  Study JGAS000378

• Molecular Classification of Hormone Sensitive and Castration Resistant prostate cancer, using non-negative matrix factorization molecular subtyping

  We aim to identify molecular subtypes of prostate cancer using consensus non-negative matrix factorization and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

  Study EGAS00001006204

• Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

  3784 whole genome sequencing bam files were generated from plasma cell-free DNA of healthy individuals and patients with cancer. Paired reads were mapped to hg19 human reference genome.

  Study EGAS00001006553

• Identification_and_functional_validation_of_driver_mutations_in_colorectal_cancer

  Targeted exome sequencing of human colorectal cancers for the identification of novel cancer drivers.

  Study EGAS00001000044