CLOCK’ing differences in DNA methylation signatures to understand the molecular etiology of lung cancer

Abstract

Lung adenocarcinoma (LUAD) is the most commonly diagnosed form of non-small cell lung cancer, and is associated with high frequency of tumor recurrence, severe malignancy and vast heterogeneity (1). Moreover, this histological diversity is compounded by the LUAD tumor microenvironment's (TME) extensive cellular diversity and accompanying immune infiltration patterns. These properties have been linked to unpredictable tumor recurrence, poor patient response to therapy, and mortality (2). Integrative application of existing tools and methods geared towards understanding epigenetic contributions to LUAD heterogeneity is imperative to answering these questions (3).In the recent issue of Clinical Cancer Research, Guidry et al. repurposed established DNA methylation patterns associated with cellular age to define signatures that can act as an index for distinct subtypes of LUAD (4). In establishing the relationship between epigenetic signatures and LUAD subtypes, they were able to ascribe phenotypic and molecular characteristics to each subclassification, including enrichment for oncogenic driver mutations and immune composition of the TME (5-9). Further to this, Guidry drew correlations between immune microenvironment composition, ethnic background and patient smoking history.Previous studies have utilized genome-wide methylation alterations within LUAD to define relevant subtypes. These investigations yielded three [3] major DNA methylation classifications in LUAD; CpG-island methylation phenotype (CIMP)-low, CIMP-intermediate, and CIMPhigh (10). DNA methylation patterns have also been associated with TME molecular characteristics and immune cell composition within LUAD tumors (11). The study by Guidry et al., improves on these associations by refining genome-wide methylation patterning to the 353 CpG sites within the Horvath DNA methylation CLOCK (6). The authors were then able to use methylation levels at these sites to subdivide LUAD into six [6] distinct subgroups, each associated with distinct pathologic and molecular features of LUAD. Subgroups with higher DNAm age were associated with better patient survival and specific oncogenic driver mutations.Aberrant oncogenic driver gene expression plays an integral role in tumorigenesis and progression in LUAD. To understand the relationship between DNAm-defined LUAD subclusters and oncogenic drivers, Guidy et al. conducted mutational analysis on tumor samples and focused on established LUAD oncogenic driver mutations