Impact of KRAS mutations and co-mutations on clinical outcomes in pancreatic ductal adenocarcinoma.

The relevance of KRAS mutation alleles to clinical outcome remains inconclusive in pancreatic adenocarcinoma (PDAC). We conducted a retrospective study of 803 patients with PDAC (42% with metastatic disease) at MD Anderson Cancer Center. Overall survival (OS) analysis demonstrated that KRAS mutation status and subtypes were prognostic (p < 0.001). Relative to patients with KRAS wildtype tumors (median OS 38 months), patients with KRASG12R had a similar OS (median 34 months), while patients with KRASQ61 and KRASG12D mutated tumors had shorter OS (median 20 months [HR: 1.9, 95% CI 1.2-3.0, p = 0.006] and 22 months [HR: 1.7, 95% CI 1.3-2.3, p < 0.001], respectively). There was enrichment of KRASG12D mutation in metastatic tumors (34% vs 24%, OR: 1.7, 95% CI 1.2-2.4, p = 0.001) and enrichment of KRASG12R in well and moderately differentiated tumors (14% vs 9%, OR: 1.7, 95% CI 1.05-2.99, p = 0.04). Similar findings were observed in the external validation cohort (PanCAN's Know Your Tumor® dataset, n = 408).

Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer.

PURPOSE: Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS: The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS: Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION: The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

Impact of KRAS Mutations and Co-mutations on Clinical Outcomes in Pancreatic Ductal Adenocarcinoma.

The relevance of KRAS mutation alleles to clinical outcome remains inconclusive in pancreatic adenocarcinoma (PDAC). We conducted a retrospective study of 803 PDAC patients (42% with metastatic disease) at MD Anderson Cancer Center. Overall survival (OS) analysis demonstrated that KRAS mutation status and subtypes were prognostic (p<0.001). Relative to patients with KRAS wildtype tumors (median OS 38 months), patients with KRASG12R had a similar OS (median 34 months), while patients with KRASQ61 and KRASG12D mutated tumors had shorter OS (median 20 months [HR: 1.9, 95% CI 1.2-3.0, p=0.006] and 22 months [HR: 1.7, 95% CI 1.3-2.3, p<0.001], respectively). There was enrichment of KRASG12D mutation in metastatic tumors (34% vs 24%, OR: 1.7, 95% CI 1.2-2.4, p=0.001) and enrichment of KRASG12R in well and moderately differentiated tumors (14% vs 9%, OR: 1.7, 95% CI 1.05-2.99, p=0.04). Similar findings were observed in the external validation cohort (PanCAN's Know Your Tumor® dataset, n=408).

Leveraging patient-reported outcomes (PROs) in patients with pancreatic cancer: The Pancreatic Cancer Action Network (PanCAN) online patient registry experience.

BACKGROUND: The Pancreatic Cancer Action Network (PanCAN) Patient Registry is an online, pancreatic cancer-specific, global registry enabling patients to self-report sociodemographics, disease/management characteristics, and patient-reported outcomes (PROs). We sought to describe the creation, user experience, and research potential of the PanCAN Registry. METHODS: We obtained data to describe (1) the creation of the Registry (questionnaire development, marketing efforts, and regulatory considerations); (2) the user experience (user characteristics and interactions with the registry following inception); and (3) the research potential of the registry (comparing PROs and treatment patterns by age [±65 years] and treatment site [community or academic] for users with de novo metastatic disease). RESULTS: The Registry was conceived as part of PanCAN's strategic plan for a personalized therapy initiative. PanCAN staff and disease expert consultants developed questionnaires hosted on an electronic PRO platform. Users had the option to include their data in research efforts, and the Registry platform received institutional review board approval. From 7/2015 to 12/2020, 2187 patients visited the registry and 1697 (77.6%) completed at least one survey (median age = 64 years [range: 24-90], 47.9% women, 88.7% White, 34.0% metastatic disease). Among patients with metastatic disease (N = 567), 46.0% were ≥65 years old and 67.5% received treatment at community sites. Patients ≥65 years reported feeling less hopeful about the treatment plan (12.4% vs. 24.3%, p = 0.003), and patients treated at community sites reported more frequent treatment breaks of >2 weeks (58.2% vs. 28.1%, p < 0.001). CONCLUSIONS: Our findings demonstrate the feasibility, usability, and research potential of an online PRO registry for patients with cancer. This description of the PanCAN Registry should inform future registry-building efforts to facilitate standardized PRO reporting and provide a valuable research database. CLINICAL TRIAL REGISTRATION NUMBER: Not applicable.

Variations in DNA elucidate molecular networks that cause disease.

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.