A0f5c8f5-32cb-481a-86ed-aa64c793dc80 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006631 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Matrices of TPM-normalized counts from RNAseq data for the three phase II clinical trials (IMvigor210, POPLAR, IMmotion150) and the phase I clinical trial PCD4989g.
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Project description:Whole exome sequencing FASTq files from 469 pre-treatment tumors from IMvigor210, POPLAR and IMmotion150, with matched PBMC samples.
| EGAD00001006632 | EGA
Project description:RNAseq fastq files from 611 bulk pre-treatment tumors from two indications: metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)
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Project description:Clinical data from IMvigor210, POPLAR, IMmotion151: Clinical data include demographics, tumor type, PD-L1 IHC, tumor mutation burden, objective response rate, overall survival and progression free survival for 611 patients across IMvigor210, POPLAR and IMmotion150.
Clinical data from PCD4989g: Clinical data include tumor type, PD-L1 expression and objective response rate for 206 patients from PCD4989g.
| EGAD00001006630 | EGA
Project description:Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.
| EGAS00001004343 | EGA
Project description:This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts
| EGAD00001005976 | EGA
Project description:This is a Phase 1, open-label, dose-escalation trial of avelumab [antibody targeting programmed death ligand 1 (anti PD-L1)] with consecutive parallel group expansion in participants with selected tumor indications. New recruitment is open for all active cohorts.
Active cohorts: Escalation revised dosing regimen cohort.
Closed cohorts: Non-small cell lung cancer (NSCLC, first line), NSCLC (post-platinum), metastatic breast cancer (MBC), colorectal cancer (CRC), urothelial carcinoma (secondary), mesothelioma, gastric/GEJ cancer (first line switch maintenance and second line), and ovarian cancer (secondary and platinum refractory + liposomal doxorubicin), renal cell carcinoma (second line) melanoma and head, neck squamous cell carcinoma (HNSCC), castrate-resistant prostate cancer (CRPC), adrenocortical carcinoma (ACC) urothelial carcinoma (efficacy), gastric/gastroesophageal junction (GEJ) cancer (third line), renal cell carcinoma (RCC, first line) and escalation phase .
| 2138571 | ecrin-mdr-crc
Project description:This dataset includes full tumor transcriptomes from 891 advanced NSCLC tumors. These data originate from pre-treatment samples from two large randomized clinical trials for second-line non-small cell lung cancer (POPLAR and OAK). The patients in these trials were treated with either the PD-L1 inhibitor atezolizumab or chemotherapy.
| EGAD00001007703 | EGA
Project description:The purpose of this study is to investigate the effects of nivolumab when given under the skin with or without rHuPH20.
This study will include participants with 1 of the following advanced or metastatic tumors approved for treatment with nivolumab monotherapy:
* non-small cell lung cancer (NSCLC)
* renal cell carcinoma (RCC)
* unresectable or metastatic melanoma
* hepatocellular carcinoma (HCC)
* microsatellite instability-high or mismatch repair deficient colorectal cancer (MSI-H/dMMR CRC)
* in Part B, other solid tumors may be considered at the discretion of the Clinical Trial Physician
* In addition to the above tumors, Part E will also include participants with metastatic urothelial carcinoma (mUC).
| 2283030 | ecrin-mdr-crc
Project description:Inhibition of immune-checkpoint targets including PD1 is clinically effective in a variety of cancers. However, only a subset of patients respond and complete response remains uncommon. Given the known role of metabolites in modulating immunity, we sought to understand how individual patients’ metabolic activities adapt to PD1 immune checkpoint blockade and how they associate with therapeutic benefits. To this end, we profiled metabolites in pre- and multiple on-treatment patient serum samples from three independent immunotherapy trials using hydrophilic interaction liquid chromatography coupled with either triple quadrupole MS multiple reaction monitoring or high resolution full scan MS detection. The study consisted of two Phase I trials (CA209-038, NCT01621490; CA209-009, NCT01358721) which included 78 patients with advanced melanoma and 91 patients with metastatic renal cell carcinoma (RCC) treated with nivolumab. To investigate the generalizability of our results, we also analyzed a large randomized Phase III trial (CheckMate 025, NCT01668784) with 743 RCC patients, among which 394 received nivolumab and 349 received everolimus.
2019-08-08 | ST001235 | MetabolomicsWorkbench