7363 results for "canc*"

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• Integrated Molecular Profilting in Advanced Cancers Trial

  The present protocol seeks to provide molecular profiling data to the treating physician for patients with advanced breast, non-small cell lung, colorectal, genitourinary, pancreatobiliary gastrointestinal, upper aerodigestive tract, gynecological, melanoma, unknown primary, and rare carcinomas, as well as patients who are phase I trial candidates, in order to help identify which standard regimens or clinical trials of molecularly targeted therapies may be most appropriate for the individual patient.

  Study EGAS00001001897

• Reproducibility of variant calls in replicate next generation sequencing experiments

  In this study, we examined the reproducibility of nucleotide variant calls in replicate sequencing experiments of the same genomic DNA. We performed targeted sequencing of all known human protein kinase genes (kinome) (~3.3 Mb) using the SOLiD v4 platform. Seventeen breast cancer samples were sequenced in duplicate (n=14) or triplicate (n=3) to assess concordance of all calls and single nucleotide variant (SNV) calls.

  Study EGAS00001000826

• Spatio-temporal Profiling of a Rhabdoid Tumor Case Study

  Background Immune checkpoint inhibition (ICI) has revolutionized oncology, offering extended survival and long-term remission in previously incurable cancers. While highly effective in tumors with high mutational burden, lowly mutated cancers, including pediatric malignancies, present low response rate and limited predictive biomarkers. Patients and methods We present a framework for the identification and validation of tumor-reactive T cells as a biomarker to quantify ICI efficacy and as candidates for a personalized TCR-T cell therapy. Therefore, we profiled a pediatric malignant rhabdoid tumor patient with complete remission after ICI therapy using deep single-cell T cell receptor (TCR) repertoire sequencing of the tumor microenvironment (TME) and the peripheral blood. Results Tracking T cell dynamics longitudinally from the tumor to cells in circulation over a time course of 12 months revealed a systemic response and durable clonal expansion of tumor-resident and ICI-induced TCR clonotypes. We functionally validated tumor reactivity of TCRs identified from the TME and the blood by co-culturing patient-derived tumor cells with TCR-engineered autologous T cells. Here, we observed unexpectedly high frequencies of tumor-reactive TCR clonotypes in the TME and confirmed T cell dynamics in the blood post-ICI to predict tumor-reactivity. Conclusion These findings strongly support spatio-temporal tracking of T cell activity in response to ICI to inform therapy efficacy and to serve as a source of tumor-reactive TCRs for personalized TCR-T designs.

  Study EGAS00001008174

• RNA sequencing data of 142 samples from 142 patients with HER2+ breast cancer treated with letrozole or tamoxifen (SOLTI PAMELA trial)

  PAMELA (NCT01973660) is a non-randomized, open-label, multicentric, prospective translational research study in stage I-IIIA HER2+ breast cancer designed to evaluate the ability of the PAM50 intrinsic subtypes to predict pCR in the breast (pCRB) following 18 weeks of neoadjuvant lapatinib and trastuzumab (+/- hormonal therapy if hormone receptor [HR] positive). Patients with HR+ disease received letrozole (if postmenopausal) or tamoxifen (if pre-menopausal). The primary objective was to compare the pCRB rates of the HER2-E versus the non-HER2-E subtypes in the intent-to-treat population.

  Study EGAS00001006410

• Whole-Exome Sequencing analyses in tamoxifen-associated endometrial cancer

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Study EGAS00001006453

• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• S_CORT_Stratification_in_COloRecTal_cancer_

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Study EGAS00001001521

• High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles.

  Study EGAS00001006461

• Multimodal Epigenetic Sequencing Analysis (MESA) of Cell-free DNA for Non-invasive Cancer Detection

  Multimodal characterization of cell-free DNA (cfDNA) in the blood can enable the sensitive and non-invasive detection of human cancers but remains technically challenging and costly. Here, we developed Multimodal Epigenetic Sequencing Analysis (MESA), a flexible and sensitive method of capturing and integrating multimodal epigenetic information of cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq (EM-seq) and TET-assisted pyridine borane sequencing (TAPS). MESA can simultaneously infer cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and fragmentation profile for regions surrounding the promoters and polyadenylation sites (PASs). MESA’s integrated analysis of multimodal epigenetic features significantly improved the performance of cancer detection models compared to the usage of any single modality alone. MESA captures additional and highly complementary epigenetic information from cfDNA without additional experimental assays, highlighting the importance and clinical prospect of using multimodal epigenetic features for non-invasive cancer detection

  Study EGAS00001006462

• Edinburgh_Naevi_Cohort

  In this project we have sequenced the exome of skin moles (melanocytic naevi) and also normal skin from young and old people. We are interested in looking at the clonality of these lesions and the burden of UV mutations

  Study EGAS00001002347