Using real-world data to assess the prognostic value of co-occurring genomic alterations


The clinical implications of co-occurring genomic alterations in patients with cancer has emerged as an prominent area of study for precision oncology 1. In this setting, there is a need to understand the real-world predictive and prognostic importance of co-occurring alterations and their role in precision oncology. While novel diagnostics and personalized medicine 2 have led to major advances in oncology therapeutics, some patients still do not benefit from these targeted therapies. For example, in metastatic non-small cell lung cancer (NSCLC), actionable alterations such as ALK, EGFR and ROS-1 have been extensively studied, while co-occurring alterations 3 are just now emerging as an opportunity to maximize clinical benefit from personalized therapies.

In previous clinical trials, STK11 mutations alone or co-occurring with KRAS mutations have been associated with poor survival outcomes for patients with metastatic NSCLC undergoing immunotherapy or chemotherapy treatment. However, limited data were available on the prognostic value of STK11 and KRAS/STK11 mutations in patients being treated for their cancer in a real world setting—outside of clinical trials.

Real-world data were used to assess clinical outcomes in metastatic NSCLC patients with STK11 and KRAS mutations

In a study led by AstraZeneca, retrospective de-identified electronic medical records from the Flatiron Health and Foundation Medicine Clinico-Genomic Database (CGDB) were used to examine the prevalence of STK11 mutations, KRAS/STK11 co-mutations and clinical outcomes associated with those mutations were assessed in 2,407 patients with metastatic NSCLC who were receiving first line or second line immunotherapy or chemotherapy. The inclusion of information on alteration status for >300 genes from the FoundationOne comprehensive genomic profiling assay (including KRAS and STK11), which is included in the Flatiron Health-Foundation Medicine Clinico-Genomic Database, uniquely enabled this type of analysis as STK11 is not routinely assessed in current real-world clinical practice.

The researchers assessed real-world overall survival and real-world progression-free survival as part of this natural history study. Overall survival is often difficult to calculate in the real world due to the high missingness of mortality data. Flatiron Health’s composite mortality variable is benchmarked against the gold standard National Death Index (NDI), and has been shown to demonstrate high sensitivity, specificity, and date accuracy. [Read more about Flatiron’s mortality variable here or learn more in our Webinar].

Real world evidence can be used to determine the prognostic value of novel biomarkers to identify patients who may benefit from additional treatment options

The study found that patients with STK11 mutations had worse real-world overall survival and real-world progression free survival outcomes compared to patients without the STK11 mutation in those treated with either immunotherapy or chemotherapy. Outcomes were similar for patients with STK11 mutations and those who had both KRAS mutations and STK11 mutations (co-mutations).

This case shows how the Flatiron Health-Foundation Medicine Clinico-Genomic Database can be used to assess the prognostic value of novel biomarkers alone or in combination in order to corroborate clinical trial results in a real world population and identify patients who may benefit from additional treatment options. The CGDB could be used in studies like this to assess unmet medical needs and prioritize targetable alterations for future therapy development. 

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Given the rapidly evolving treatment landscape in oncology, we note that one limitation of this research is that it was conducted over a time period in which the introduction of immune checkpoint inhibitors and PD-L1 testing occurred part way through the study period.

  • 1 Mateo, L., Duran-Frigola, M., Gris-Oliver, A. et al. Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns. Genome Med 12, 78 (2020).

  • 2 Krzyszczyk P, Acevedo A, Davidoff EJ, et al. The growing role of precision and personalized medicine for cancer treatment. Technology (Singap World Sci). 2018;6(3-4):79-100. doi:10.1142/S2339547818300020

  • 3 Skoulidis F, Heymach JV. Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat Rev Cancer. 2019;19(9):495-509. doi:10.1038/s41568-019-0179-8