How real-world data was used to assess the prognostic value of co-occurring genomic alterations

August 26, 2022

PRODUCT
Flatiron Health and Foundation Medicine Clinico-Genomic Database

ANALYSIS TYPES
Unmet Need
Natural History

TUMOR TYPE
Metastatic Non-Small Cell Lung Cancer

ENDPOINTS
OS, rwPFS

BIOMARKERS
KRAS, STK11 (LKB1)

DRUG TYPE
Immunotherapy and Chemotherapy


The clinical implications of co-occurring genomic alterations in patients with cancer has emerged as a prominent area of study for precision oncology 1, particularly their predictive and prognostic capacities. 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 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 previously available on the prognostic value of STK11 and KRAS/STK11 mutations in patients being treated in a real-world setting — in other words, outside of clinical trials.

were used to assess clinical outcomes in metastatic NSCLC patients with STK11 and KRAS mutations

In a study led by AstraZeneca, a nationwide (US-based) de-identified Flatiron Health-Foundation Medicine NSCLC clinico-genomic database (FH-FMI CGDB) was 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 CGDB, uniquely enabled this type of analysis as STK11 is not routinely assessed in current real-world clinical practice.

In this natural history study, the researchers assessed (leveraging Flatiron’s composite mortality variable) and real-world progression-free survival. Overall survival is often difficult to calculate in the real world due to the high missingness of mortality data. Flatiron’s is benchmarked against the gold standard National Death Index (NDI), and has been shown to demonstrate high sensitivity, specificity, and date accuracy. Learn more about this topic in our webinar.

can be used to determine the prognostic value of novel biomarkers for patients who may benefit from additional treatment options

The AstraZeneca study found that patients with STK11 mutations had worse real-world overall survival and 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).

The CGDB can be used to assess the prognostic value of novel biomarkers alone or in combination to corroborate clinical trial results in a real world population and identify patients who may benefit from additional treatment options. Future natural history studies using the CGDB could assess unmet medical needs and prioritize targetable alterations for future therapy development.

 

Planning a similar study? You should know:

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). https://doi.org/10.1186/s13073-020-00774-x


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