Genetic variation drives cancer cell adaptation to ECM stiffness.

The progression of many solid tumors is accompanied by temporal and spatial changes in the stiffness of the extracellular matrix (ECM). Cancer cells adapt to soft and stiff ECM through mechanisms that are not fully understood. It is well known that there is significant genetic heterogeneity from cell to cell in tumors, but how ECM stiffness as a parameter might interact with that genetic variation is not known.

Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes.

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes.

GSK-3484862 targets DNMT1 for degradation in cells.

Maintenance of genomic methylation patterns at DNA replication forks by DNMT1 is the key to faithful mitotic inheritance. DNMT1 is often overexpressed in cancer cells and the DNA hypomethylating agents azacytidine and decitabine are currently used in the treatment of hematologic malignancies. However, the toxicity of these cytidine analogs and their ineffectiveness in treating solid tumors have limited wider clinical use.