Immunogenomic Properties Predict Exceptional Responses to Immune Checkpoint Inhibition in RCC

Renee Maria Saliby, MD, MSc

In patients with renal cell carcinoma (RCC), clonal neoantigen load (CNL) was significantly associated with exceptional responses to PD-1/PD-L1 and CTLA-4 combination therapy and tertiary lymphoid structure (TLS) formation was associated with these exceptional responses to PD-1/PD-L1 and VEGF inhibitor combination treatment, according to findings from a retrospective study published in Nature Cancer.1

“Treatment [for patients with RCC] has evolved greatly over the past couple of years with immune checkpoint inhibitors in combination with VEGF tyrosine kinase inhibitors, [which] have been serving as the cornerstone of therapy,” Renee Maria Saliby, MD, MSc, a senior author of the study and a postdoctoral research fellow at Dana-Farber Cancer Institute in Boston, Massachusetts, said in an interview with OncologyLive. “[However], kidney cancer has challenged everything we know in terms of biomarkers, and a lot of work has been done in terms of biomarkers for response vs progressive disease. Patients want deep, durable responses, so we decided to look at these patients who had a deep, durable response and called them exceptional responders. [We wanted] to understand the genomic and transcriptomic mechanisms that were underlying these responses.”

Retrospective Study Design

Saliby and her coauthors utilized whole-exome and RNA sequencing to examine genomic features associated with exceptional response to immunotherapy-based combinations in patients with clear cell RCC. An exceptional response was defined as a complete response (CR) with a progression-free survival (PFS) of at least 1 year, a partial response (PR) with at least 50% tumor shrinkage and a PFS of at least 2 years, or any PR with a PFS of at least 3 years. Investigators also defined an intermediate response as any CR or PR that was not an exceptional response.

Tumor specimens were obtained from patients with available tumor sequencing data enrolled in the phase 3 JAVELIN Renal 101 (NCT02684006) and CheckMate 214 (NCT02231749) trials. CheckMate 214 enrolled patients with previously untreated advanced or metastatic RCC to evaluate the combination of the PD-1 inhibitor nivolumab (Opdivo) and the CTLA-4 inhibitor ipilimumab (Yervoy), with primary end points around efficacy in patients classified as intermediate or poor risk based on International Metastatic RCC Database Consortium (IMDC) risk-stratifying criteria.2 The JAVELIN Renal 101 trial evaluated the PD-L1 inhibitor avelumab (Bavencio) plus the VEGF inhibitor axitinib (Inlyta) for the first-line treatment of patients with advanced RCC.3 Data from the CheckMate 214 and JAVELIN Renal 101 studies supported the FDA approvals of the regimens in their patient populations in April 2018 and May 2019, respectively.2,3

To validate these response classifications outside clinical trials, investigators used the IMDC registry to evaluate the baseline characteristics and outcomes of a real-world population of exceptional responders who received immunotherapy-based regimens.1

Patients included from CheckMate 214 trial (n = 550) had a median age of 62 years (IQR, 55-68). Most patients were male (75%) and had IMDC intermediate-risk disease (59%). Overall, these patients achieved a CR rate of 11% and a PR rate of 29%.1

Patients included from JAVELIN Renal 101 (n = 434) had a median age of 62 years (IQR, 55-67). Most were male (71%), had disease without sarcomatoid features (89%), and had IMDC intermediate-risk disease (62%). The overall CR and PR rates were 3.9% and 50%, respectively (Figure).1

Investigators evaluated the association of previously described tumor-intrinsic biomarkers with exceptional response, including total somatic tumor mutational burden (TMB), frameshift TMB, weighted genome instability index (wGII), intratumoral heterogeneity, and germline human leukocyte antigen (HLA) class I evolutionary divergence. Additionally, they defined CNL as the total number of neoantigens arising from clonal mutations and examined it as a determinant of response to immunotherapy-based combinations.1

CNL and TLS Display Association to Exceptional Response to Therapy

Findings from the analysis demonstrated that patients treated with the immunotherapy doublet in CheckMate 214 who experienced an exceptional response, an intermediate response, or disease progression all had similar TMB, frameshift insertions or deletions, mean HLA class I evolutionary divergence, wGII, tumor purity and ploidy, and loss of heterozygosity. Data from patients who received doublet therapy in JAVELIN Renal 101 also showed no correlation with exceptional response and TMB, frameshift insertions or deletions, mean HLA class I evolutionary divergence, wGII, tumor purity and ploidy, and loss of heterozygosity.1

However, patients treated in CheckMate 214 who experienced an exceptional response displayed a significantly higher CNL compared with those in the intermediate response and progressive disease groups. Comparatively, patients who experienced an exceptional response in the sunitinib malate (Sutent) arm of the study did not have a significantly higher CNL vs the intermediate response or progressive disease groups.1

Findings from a univariate Cox regression analysis showed that patients in CheckMate 214 with a higher CNL who received the doublet also had improved PFS. When patients were stratified into CNL-high (≥ 75th percentile) and CNL-low (< 25th percentile) subgroups, those who received the doublet in the CNL-high group experienced a median PFS of 16.99 months compared with 5.82 months in the CNL-low group.1

In the JAVELIN Renal 101 cohort, investigators performed a transcriptomic analysis to identify pathways and immune cell populations associated with exceptional response in patients who received combination therapy. Patients with an exceptional response were found to have a higher expression of pathways associated with adaptive immunity, including B-cell receptor pathways. Patients with exceptional responses also had tumors that were highly infiltrated with plasma and memory B cells.1

Investigators then examined the T-cell–inflamed gene expression profile, a mechanism that mediates immune response. Patients with an exceptional response to immunotherapy/VEGF inhibitor treatment had a significantly increased T-cell–inflamed signature compared with those who experienced progressive disease. Additionally, the plasma and memory B cells associated with exceptional responses were determined by investigators to be associated with TLS formation.1

Patients with an exceptional response to doublet therapy in JAVELIN Renal 101 had higher scores of Meylan, Cabrita, and Xu TLS signatures compared with those who experienced an intermediate response. The same trend of higher scores of Meylan, Cabrita, and Xu TLS signatures was observed in patients with an exceptional response vs those who experienced disease progression. These TLS signatures were not favorably associated with exceptional response among patients who received sunitinib.1

Additional findings showed that patients who experienced an exceptional response to doublet therapy and had a TLS-low signature upregulated metabolism-related pathways, including those related to peroxisome, xenobiotic metabolism, bile acid metabolism, adipogenesis, fatty acid metabolism, oxidative phosphorylation, cholesterol homeostasis, and heme metabolism.1

“[These results] showed that these elements could be used as biomarkers in the future to help select the patients who would benefit the most from these therapies and to reduce toxicities and [unnecessary] treatment for those who do not benefit,” Saliby explained. “These findings could also help us think about potential therapeutic avenues. We are going to keep using immune checkpoint inhibitors, and we [will be able to] optimize patient responses to these [agents] by targeting mechanisms [such as] CNL and TLS.”

Notably, findings from a biomarker analysis of the phase 3 KEYNOTE-426 study (NCT02853331) of pembrolizumab (Keytruda) plus axitinib vs sunitinib in patients with treatment-naive advanced RCC also demonstrated an association between a higher T-cell–inflamed gene expression profile and response to treatment. Data from the analysis presented during the 2024 American Society of Clinical Oncology Annual Meeting showed that patients with an 18-gene T-cell–inflamed gene expression profile who received the combination achieved an overall response rate, PFS, and overall survival benefit compared with those who did not display this genetic profile.4

“The most important next step is to validate [our] results in different cohorts to [ensure] that they are reproducible and not just findings we see in one cohort, which happens a lot in kidney cancer; that’s why we don’t have clear biomarkers yet,” Saliby said. “Ideally, we want to design a trial similar to the [phase 2] OPTIC RCC study [NCT05361720] that would be prospective and [allow us] to stratify patients depending on their initial biomarkers. Patients would then receive one combination or the other. If these [data] are validated, they would be important to our understanding of how we can create [agent] mechanisms and potentiate better immune environments for patients.”

References

1. Jammihal T, Saliby RM, Labaki C, et al. Immunogenomic determinants of exceptional response to immune checkpoint inhibition in renal cell carcinoma. Nat Cancer. Published online January 9, 2025. doi:10.1038/s43018-024-00896-w
2. FDA approves nivolumab plus ipilimumab combination for intermediate or poor-risk advanced renal cell carcinoma. FDA. Updated April 16, 2018. Accessed February 4, 2025. bit.ly/3WNh0fY
3. FDA approves avelumab plus axitinib for renal cell carcinoma. FDA. Updated May 15, 2019. Accessed February 4, 2025. bit.ly/4jZ08gD
4. Rini BI, Plimack ER, Stus V, et al. Biomarker analysis of the phase 3 KEYNOTE-426 study of pembrolizumab (P) plus axitinib (A) versus sunitinib (S) for advanced renal cell carcinoma (RCC). J Clin Oncol. 2024;42(suppl 16):4505. doi:10.1200/JCO.2024.42.16_suppl.4505