genieBPC

The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC) is an effort to aggregate comprehensive clinical data linked to genomic sequencing data to create a pan-cancer, publicly available data repository. These data detail clinical characteristics and drug treatment regimen information, along with high-throughput sequencing data and clinical outcomes, for cancer patients across international institutions. The GENIE BPC data repository forms a unique observational database of comprehensive clinical annotation with molecularly characterized tumors that can be used to advance precision medicine research in oncology. Linking multiple clinical and genomic datasets that vary in structure introduces an inherent complexity for data users. Therefore, use of the GENIE BPC data requires a rigorous process for preparing and merging the data to build analytic models. The {genieBPC} package is a user-friendly data processing pipeline to streamline the process for developing analytic cohorts that are ready for clinico-genomic analyses.

Installation

You can install the released version of {genieBPC} from the R Universe

install.packages('genieBPC', 
                 repos = c(mskccepibio = 'https://mskcc-epi-bio.r-universe.dev',
                           CRAN = 'https://cloud.r-project.org'))

and the development version with

remotes::install_github("GENIE-BPC/genieBPC")

Overview of {genieBPC} Functions

• Data import: pull_data_synapse() imports GENIE BPC data from Synapse into the R environment

• Data processing

  • create_analytic_cohort() selects an analytic cohort based on cancer diagnosis information and/or cancer-directed drug regimen information
    
  • select_unique_ngs() selects a unique next generation sequencing (NGS) test corresponding to the selected diagnoses

• Data visualization: drug_regimen_sunburst() creates a sunburst figure of drug regimen information corresponding to the selected diagnoses in the order that the regimens were administered

Obtaining Data Access

Access to the GENIE BPC data release folders on Synapse is required in order to use this function. To obtain access:

For public data releases:

1. Register for a Synapse account

2. Navigate to the data release and request accept terms of use (e.g., for the NSCLC 2.0-public data release, navigate to the Synapse page for the data release). Towards the top of the page, there is information including the Synapse ID, DOI, Item count, and Access. Next to Access is a link that reads Request Access.

3. Select Request Access, review the terms of data use and select Accept

For consortium data releases (restricted to GENIE consortium members & BPC pharmaceutical partners):

1. Register for a Synapse account

2. Use this link to access the GENIE BPC team list and request to join the team. Please include your full name and affiliation in the message before sending out the request.

3. Once the request is accepted, you may access the data in the GENIE Biopharma Collaborative projects.

Note: Please allow up to a week to review and grant access.

Analytic Data Guides

The analytic data guides provide details on each analytic dataset and its corresponding variables for each data release.

Public Data Releases

• NSCLC v2.0-Public Analytic Data Guide Released May 2022

Consortium Data Releases
Note that only GENIE BPC consortium users have access to the consortium releases.

• NSCLC v1.1-Consortium Analytic Data Guide

• NSCLC v2.1-Consortium Analytic Data Guide

• CRC v1.1-Consortium Analytic Data Guide

• CRC v1.2-Consortium Analytic Data Guide

• BrCa v1.1-Consortium Analytic Data Guide

Example

The following example creates an analytic cohort of patients diagnosed with Stage IV adenocarcinoma NSCLC.

Pull data for NSCLC version 2.0-public:

nsclc_2_1 <- pull_data_synapse(cohort = "NSCLC", version = "v2.0-public")

Select stage IV adenocarcinoma NSCLC diagnoses:

nsclc_stg_iv_adeno <- create_analytic_cohort(data_synapse = nsclc_2_0$NSCLC_v2.0, 
                                             stage_dx = "Stage IV", 
                                             histology = "Adenocarcinoma")

Select one unique metastatic lung adenocarcinoma genomic sample per patient in the analytic cohort returned above:

nsclc_stg_iv_adeno_unique_sample <- select_unique_ngs(
  data_cohort = nsclc_stg_iv_adeno$cohort_ngs)

Create a visualization of the treatment patterns for the first 3 regimens received by patients diagnosed with stage IV adenocarcinoma:

sunplot <- drug_regimen_sunburst(data_synapse = nsclc_2_0$NSCLC_v2.0,
                                 data_cohort = nsclc_stg_iv_adeno,
                                 max_n_regimens = 3)

Example of a sunburst plot showing 3 lines of treatment, Highlighting First Treatment Regimen: