Distribution of immune cells across KRAS variants
(A) B cells. (B) M1 macrophages. (C) M2 macrophages. (D) NK cells (E) CD8 T cells. (F) Treg cells. Statistical analysis indicates pairwise comparisons. Only q-values <0.01 are shown: **(<0.01), ***(<0.001), ****(<0.0001). No statistically significant differences were observed for percentage of neutrophils between KRAS variants.
Introduction and Hypothesis
Mutations in the KRAS oncogene are found in approximately 30% of patients with non-small cell lung cancer (NSCLC), but these mutations are not all the same. It is clear that different KRAS variants, such as G12C and G12D, may drive distinct tumor biology.
The research team hypothesized that a large-scale analysis of real-world data could reveal how specific KRAS variants are associated with unique features of the tumor microenvironment, particularly lipid metabolism and immune cell infiltration. Uncovering these differences is a critical step toward developing more precise and effective therapeutic strategies for each KRAS-mutant subtype.
Methodology
The team conducted a large-scale retrospective analysis of de-identified records from 5,925 NSCLC patients harboring KRAS alterations using the Tempus Lens and Workspace platforms. Utilizing genomic and transcriptomic data from the Tempus xT (DNA) and xR (RNA) assays, the researchers characterized the molecular and cellular landscape associated with different KRAS variants. The scientific approach involved several key bioinformatic techniques. The proportions of various immune cells within the tumor microenvironment were estimated using QuanTIseq. To assess metabolic activity, single-sample gene set enrichment analysis (ssGSEA) was used to calculate lipid metabolic gene enrichment scores for each patient. Additionally, key biomarkers of immunogenicity, including tumor mutational burden (TMB) and neoantigen tumor burden (NTB), were analyzed.
Impact
The analysis revealed that the metabolic and immune landscapes of NSCLC tumors differ significantly depending on the specific KRAS mutation present. Patients with KRAS G12D mutations were found to have a significantly less immunogenic, or “colder,” tumor microenvironment compared to those with the more common G12C mutation. This was evidenced by G12D tumors having a statistically significant lower TMB, lower NTB, and a smaller proportion of key anti-tumor immune cells, including CD8+ T cells and M1 macrophages. Furthermore, the study identified distinct metabolic profiles, with KRAS G12C variants showing significantly lower lipid gene enrichment scores than G12D or G12V variants.
This research provides a strong rationale for moving beyond a “one-size-fits-all” strategy for KRAS-mutant cancers. These findings suggest that the efficacy of treatments like immunotherapy could vary substantially based on a patient’s specific KRAS variant. This insight is critical for designing more intelligent clinical trials, potentially by stratifying enrollment by KRAS subtype or exploring novel combination therapies tailored to the unique biology of each variant. For example, the less immunogenic profile of G12D tumors may indicate a need for combination strategies that can activate a stronger immune response. Ultimately, this type of work can guide the development of next-generation targeted therapies and companion diagnostics that account for the distinct biology of each KRAS-driven tumor.
