7154 results for "canc*"

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• Pharmacokinetics and Pharmacogenomics of Ribociclib in Race-Based Cohorts (LEANORA)

  Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. This study aimed to assess the pharmacokinetics (PK) and pharmacogenomics (PGx) of ribociclib in self-identified Black women with hormone receptor positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. LEANORA (NCT04657679) was a prospective, observational, multicenter cohort study involving 14 Black women. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan microarray. CYP3A5*3, CYP3A5*6, and CYP3A5*7 variants were genotyped and CYP3A5 phenotypes were constructed from these data. We observed 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area under the curve of plasma concentration versus time curve (AUC) of ribociclib did not differ between PMs (39,230 hr*ng/mL) and IM/NMs (43,546 hr*ng/mL; P=0.38). The incidence of adverse events (AEs) was also similar. We found no association between CYP3A5 genotype and ribociclib exposure. Continued efforts are needed to include diverse populations in clinical trials to ensure equitable treatment outcomes.

  Study phs003770

• Integrated Somatic and Germline Molecular Properties Dictating Biological and Clinical Phenotypes in Cancer

  We performed single-nuclei matched RNA- and ATAC-sequencing of frozen biopsies from normal adjacent tissue, primary and metastatic esophageal adenocarcinoma specimens. The data was then further stratified into a tumor microenvironment and malignant compartment and was computationally analyzed to reveal cancer cell subtypes and programs driving malignancy.

  Study phs003438

• Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

  Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

  Study phs003284

• Cancer Moonshot Biobank

  The National Cancer Institute initiated the Cancer Moonshot Biobank to accelerate research through the collection and distribution of biospecimens for key research efforts. The Biobank will engage with over one thousand cancer patients, being treated with standard-of-care therapies, for longitudinal biospecimen and data collection. Cancer patients will be enrolled into the study from a diverse participant population engaged at medical institutions throughout the U.S. The biospecimens will be distributed to qualified scientists to accelerate research progress. The Biobank program, working closely with Leidos Biomedical, Inc. (LBR), will partner with community hospitals and other medical institutions, designated as Biospecimen Source Sites (BSS), to engage and consent eligible participants and collect biospecimens and associated clinical data; work with a central Biospecimen Core Resource (BCR) to support biospecimen collection, processing and storage activities and perform pathology quality control; work with LBR's Molecular Characterization (MoCha) lab to perform clinical tumor molecular characterization assays and return results to patients and their physicians; and make the biospecimens and associated data available to researchers to accelerate cancer research progress. Return of clinical results, a dedicated Patient and Provider Engagement (PPE) website, electronic informed consent, local participant engagement projects, and an embedded ethical, legal and social issues sub-study will together support patient and provider engagement in the program. Cancer Moonshot Biobank imaging data is being made available in The Cancer Imaging Archive (TCIA) on a release schedule that is coordinated with the program releases of data to dbGaP. The imaging data can be found at the following link: Cancer Moonshot Biobank Imaging

  Study phs002192

• scRNAseq data from metastatic breast cancer samples

  Paired-end SMARTseq2 data of EpCAM+ sorted cells from liquid biopsies from 3 patients. Sequencing was performed on Illumina HiSeq 2500.

  Dataset EGAD50000000816

• WGS and WES data of metastatic breast cancer tissues and organoids

  Paired-end WGS (x25) and WES data (x2) from metastatic breast cancer organoids, tissues and germline controls. WGS was performed on Illumina NovSeq 6000 and HiSeq X, using Illumina TruSeq Nano DNA kit. WES was performed on Illumina NovSeq 6000 and HiSeq 2000, using Agilent SureSelect XT HS + Human All Exon V7 and SureSelect Human All Exon V6+UTR (hg19).

  Dataset EGAD50000000817

• RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 28 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 and HiSeq 4000 using TruSeq Stranded mRNA Kit.

  Dataset EGAD50000000818

• DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

  This is the DAC for the study "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients." of Andreas Trumpp (a.trumpp@dkfz.de), Roberto Würth (r.wuerth@dkfz.de) and Martin Sprick (Martin.Sprick@hi-stem.de).

  Dac EGAC50000000371

• MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model

  DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence and the method estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.

  Study EGAS50000000806

• WGBS dataset for lymphnode metastasis samples from prostate cancer

  This dataset contains WGBS sequencing data of lymphnode metastasis samples from prostate cancer. Sequencing was performed on Illumina HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000001183