A three-gene expression score for predicting clinical benefit to anti-PD-1 blockade in advanced renal cell carcinoma.

In the advanced renal cell carcinoma (RCC) scenario, there are no consistent biomarkers to predict the clinical benefit patients derived from immune checkpoint blockade (ICB). Taking this into consideration, herein, we conducted a retrospective study in order to develop and validate a gene expression score for predicting clinical benefit to the anti-PD-1 antibody nivolumab in the context of patients diagnosed with advanced clear cell RCC enrolled in the CheckMate-009, CheckMate-010, and CheckMate-025 clinical trials. First, a three-gene expression score (3GES) with prognostic value for overall survival integrating HMGA1, NUP62, and ARHGAP42 transcripts was developed in a cohort of patients treated with nivolumab. Its prognostic value was then validated in the TCGA-KIRC cohort. Second, the predictive value for nivolumab was confirmed in a set of patients from the CheckMate-025 phase 3 clinical trial. Lastly, we explored the correlation of our 3GES with different clinical, molecular, and immune tumor characteristics. If the results of this study are definitively validated in other retrospective and large-scale, prospective studies, the 3GES will represent a valuable tool for guiding the design of ICB-based clinical trials in the aRCC scenario in the near future.

MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles.

Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA- or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-à-vis a MLH1 promoter methylation-based one in colorectal cancer.

Clinical significance of baseline Pan-Immune-Inflammation Value and its dynamics in metastatic colorectal cancer patients under first-line chemotherapy.

Pan-Immune-Inflammation Value (PIV) has been recently proposed as a new blood-based prognostic biomarker in metastatic colorectal cancer (mCRC). Herein we aimed to validate its prognostic significance and to evaluate its utility for disease monitoring in patients with mCRC receiving first-line chemotherapy. We conducted a single-centre retrospective study involving 130 previously untreated mCRC patients under first-line standard chemotherapy in a real-world scenario. PIV was calculated as (neutrophil count × platelet count × monocyte count)/lymphocyte count at three different time-points: baseline, week 4 after therapy initiation, and at disease progression. We analyzed the influence of baseline PIV on overall survival (OS), progression-free survival (PFS), disease control rate (DCR), and overall response rate (ORR). We also explored the utility of PIV dynamics for disease monitoring. Baseline PIV high was significantly associated with worse OS in univariate [hazard ratio (HR) = 2.10, 95% CI, 1.41-3.15; p = 0.000299] and multivariate (HR = 1.82, 95% CI, 1.15-2.90; p = 0.011) analyses. Baseline PIV was also associated with worse PFS in univariate (HR = 2.04, 95% CI, 1.40-2.97; p = 0.000187) and multivariate (HR = 1.56, 95% CI, 1.05-2.31; p = 0.026) analyses. Baseline PIV was not correlated either with DCR or ORR. Regarding PIV dynamics, there was a statistically significant increase from week 4 to disease progression (p = 0.0003), which was at the expense of cases with disease control as best response (p < 0.0001). In conclusion, this study validates the prognostic significance of baseline PIV in patients with mCRC receiving first-line standard chemotherapy in a real-world scenario. Moreover, it suggests the potential utility of PIV monitoring to anticipate the disease progression among those patients who achieve initial disease control.