A Scalable Quality Assurance Process for Curating Oncology Electronic Health Records: The Project GENIE Biopharma Collaborative Approach

Making progress against rare cancers: A case study on neuroendocrine tumors

In April 2023, the National Cancer Institute offered a roadmap for cancer research to achieve Cancer Moonshot goals. To reach these goals requires making progress for all cancers, not just those that are most common. Achieving progress against rare cancers, as well as common cancers, requires involvement of large clinical research networks. In 2020, the Patient-Centered Outcomes Research Institute (PCORI) launched an initiative on Conducting Rare Disease Research using PCORnet, the National Patient-Centered Clinical Research Network. The purpose of this commentary is to introduce the broader community of cancer researchers to the PCORnet NET-PRO study (comparing the effects of different treatment approaches for neuroendocrine tumors on patient-reported outcomes) thereby demonstrating how researchers can use the PCORnet infrastructure to conduct large-scale patient-centered studies of rare cancers.

Large-Scale Cancer Genomic Analysis Reveals Significant Disparities between Microsatellite Instability and Tumor Mutational Burden

BACKGROUND

Microsatellite instability (MSI) and tumor mutational burden (TMB) are predictive biomarkers for pan-cancer immunotherapy. The interrelationship between MSI-high (MSI-H) and TMB-high (TMB-H) in human cancers and their predictive value for immunotherapy in lung cancer remain unclear.

METHODS

We analyzed somatic mutation data from the Genomics Evidence Neoplasia Information Exchange (n = 46,320) to determine the relationship between MSI-H and TMB-H in human cancers using adjusted multivariate regression models. Patient survival was examined using the Cox proportional hazards model. The association between MSI and genetic mutations was assessed.

RESULTS

Patients (31-89%) with MSI-H had TMB-low phenotypes across 22 cancer types. Colorectal and stomach cancers showed the strongest association between TMB and MSI. TMB-H patients with lung cancer who received immunotherapy exhibited significantly higher overall survival [HR, 0.61; 95% confidence interval (CI), 0.44-0.86] and progression-free survival (HR, 0.65; 95% CI, 0.47-0.91) compared to the TMB-low group; no significant benefit was observed in the MSI-H group. Patients with TMB and MSI phenotypes showed further improvement in overall survival and PFS. We identified several mutated genes associated with MSI-H phenotypes, including known mismatch repair genes and novel mutated genes, such as ARID1A and ARID1B.

CONCLUSIONS

Our results demonstrate that TMB-H and/or a combination of MSI-H can serve as biomarkers for immunotherapies in lung cancer.

IMPACT

These findings suggest that distinct or combined biomarkers should be considered for immunotherapy in human cancers because notable discrepancies exist between MSI-H and TMB-H across different cancer types.

Effects of KRAS Genetic Interactions on Outcomes in Cancers of the Lung, Pancreas, and Colorectum

BACKGROUND

KRAS is among the most commonly mutated oncogenes in cancer, and previous studies have shown associations with survival in many cancer contexts. Evidence from both clinical observations and mouse experiments further suggests that these associations are allele- and tissue-specific. These findings motivate using clinical data to understand gene interactions and clinical covariates within different alleles and tissues.

METHODS

We analyze genomic and clinical data from the AACR Project GENIE Biopharma Collaborative for samples from lung, colorectal, and pancreatic cancers. For each of these cancer types, we report epidemiological associations for different KRAS alleles, apply principal component analysis (PCA) to discover groups of genes co-mutated with KRAS, and identify distinct clusters of patient profiles with implications for survival.

RESULTS

KRAS mutations were associated with inferior survival in lung, colon, and pancreas, although the specific mutations implicated varied by disease. Tissue- and allele-specific associations with smoking, sex, age, and race were found. Tissue-specific genetic interactions with KRAS were identified by PCA, which were clustered to produce five, four, and two patient profiles in lung, colon, and pancreas. Membership in these profiles was associated with survival in all three cancer types.

CONCLUSIONS

KRAS mutations have tissue- and allele-specific associations with inferior survival, clinical covariates, and genetic interactions.

IMPACT

Our results provide greater insight into the tissue- and allele-specific associations with KRAS mutations and identify clusters of patients that are associated with survival and clinical attributes from combinations of genetic interactions with KRAS mutations.

Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal

International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include (i) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes; (ii) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment; and (iii) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer.

SIGNIFICANCE

Enhanced cBioPortal features allow clinicians and researchers to effectively investigate longitudinal clinico-genomic data from patients with cancer, which will improve exploration of data from the AACR Project GENIE Biopharma Collaborative and similar datasets.

The GENIE BPC NSCLC Cohort: A Real-World Repository Integrating Standardized Clinical and Genomic Data for 1,846 Patients with Non-Small Cell Lung Cancer

PURPOSE

We describe the clinical and genomic landscape of the non-small cell lung cancer (NSCLC) cohort of the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC).

EXPERIMENTAL DESIGN

A total of 1,846 patients with NSCLC whose tumors were sequenced from 2014 to 2018 at four institutions participating in AACR GENIE were randomly chosen for curation using the PRISSMM data model. Progression-free survival (PFS) and overall survival (OS) were estimated for patients treated with standard therapies.

RESULTS

In this cohort, 44% of tumors harbored a targetable oncogenic alteration, with EGFR (20%), KRAS G12C (13%), and oncogenic fusions (ALK, RET, and ROS1; 5%) as the most frequent. Median OS (mOS) on first-line platinum-based therapy without immunotherapy was 17.4 months [95% confidence interval (CI), 14.9-19.5 months]. For second-line therapies, mOS was 9.2 months (95% CI, 7.5-11.3 months) for immune checkpoint inhibitors (ICI) and 6.4 months (95% CI, 5.1-8.1 months) for docetaxel ± ramucirumab. In a subset of patients treated with ICI in the second-line or later setting, median RECIST PFS (2.5 months; 95% CI, 2.2-2.8) and median real-world PFS based on imaging reports (2.2 months; 95% CI, 1.7-2.6) were similar. In exploratory analysis of the impact of tumor mutational burden (TMB) on survival on ICI treatment in the second-line or higher setting, TMB z-score harmonized across gene panels was associated with improved OS (univariable HR, 0.85; P = 0.03; n = 247 patients).

CONCLUSIONS

The GENIE BPC cohort provides comprehensive clinicogenomic data for patients with NSCLC, which can improve understanding of real-world patient outcomes.

A data processing pipeline for the AACR project GENIE biopharma collaborative data with the {genieBPC} R package

MOTIVATION

Data from the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC) represent comprehensive clinical data linked to high-throughput sequencing data, providing a multi-institution, pan-cancer, publicly available data repository. GENIE BPC data provide detailed demographic, clinical, treatment, genomic and outcome data for patients with cancer. These data result in a unique observational database of molecularly characterized tumors with comprehensive clinical annotation that can be used for health outcomes and precision medicine research in oncology. Due to the inherently complex structure of the multiple phenomic and genomic datasets, the use of these data requires a robust process for data integration and preparation in order to build analytic models.

RESULTS

We present the {genieBPC} package, a user-friendly data processing pipeline to facilitate the creation of analytic cohorts from the GENIE BPC data that are ready for clinico-genomic modeling and analyses.

AVAILABILITY AND IMPLEMENTATION

{genieBPC} is available on CRAN and GitHub.