MethCORR Modelling of Methylomes From Formalin-Fixed Paraffin-Embedded Tissue Enables Characterization and Prognostication of Colorectal Cancer

Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types

Gene Expressions and High Lymphocyte Count May Predict Durable Clinical Benefits in Patients with Advanced Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors

Background: Not all patients with advanced non-small cell lung cancer (NSCLC) benefit from immune checkpoint inhibitors (ICIs). Therefore, we aimed to assess the predictive potential of gene expression profiling (GEP), peripheral immune cell counts, and clinical characteristics. Methods: The primary endpoint of this prospective, observational study was a durable clinical benefit (DCB) defined as progression-free survival >6 months. In a subgroup with histological biopsies of sufficient quality (n = 25), GEP was performed using the nCounter® PanCancer IO 360 panel. Results: DCB was observed in 49% of 123 included patients. High absolute lymphocyte count (ALC) and absence of liver metastases were associated with DCB (OR = 1.95, p = 0.038 and OR = 0.36, p = 0.046, respectively). GEP showed clustering of differentially expressed genes according to DCB, and a strong association between PD-L1 assessed by GEP (CD274) and immunohistochemistry (IHC) was observed (p = 0.00013). The TGF-β, dendritic cell, and myeloid signature scores were higher for patients without DCB, whereas the JAK/STAT loss signature scores were higher for patients with DCB (unadjusted p-values 9/L and absence of liver metastases were significantly associated with DCB in ICI-treated patients with NSCLC. GEP was only feasible in 20% of the patients. GEP-derived signatures may be associated with clinical outcomes, and PD-L1 could be assessed by GEP rather than IHC