Simple PCR Assay Accurately Differentiates Between Small Cell Lung Cancer Subtypes

Despite its molecular and clinical heterogeneity, SCLC is presently treated as a single entity, without the use of predictive biomarkers, which leads to poor patient outcomes. Recent research has proposed dividing SCLC into four subtypes—labeled "A", "N", "P", and "I"—each characterized by distinct molecular signatures and treatment vulnerabilities. Initially, this classification relied on gene expression (RNA-seq) data. Further studies indicated that the same categorization could be recapitulated through the use of a reduced-representation bisulfite sequencing (RRBS) methylation profile. Although this classification system effectively predicts treatment responses, including to immunotherapy, in retrospective analyses, both RNAseq and RRBS techniques are too labor-intensive and slow for quick treatment decisions in an aggressive malignancy. Now, a pilot study published in the journal Cancer Cell has demonstrated the feasibility of a simple PCR assay to accurately differentiate between SCLC SCLC subtypes.

In the pilot study, Nucleix (San Diego, CA, USA) developed a methylation-based PCR assay to distinguish SCLC subtypes using its EpiCheck platform. This technology combines methylation-sensitive restriction endonuclease (MSRE) digestion with quantitative PCR (qPCR) amplification to identify differential methylation at the DNA level. Nucleix developed the 13-marker PCR assay based on a recent study that used DNA methylation to successfully detect SCLC in plasma samples from heavy smokers—with a sensitivity of 94% and specificity of 95%. The company developed novel biomarkers to classify SCLC into subtypes, aiming to reduce the time between diagnosis and tailored treatment interventions. The 13-marker PCR assay accurately classified 97% of the SCLC tissue samples within a blinded cohort in the pilot study.

“For decades, SCLC was considered a single, monolithic entity resulting in our current clinical protocols being based on disease stage, with no consideration of biomarkers that have predictive or prognostic significance, leading to expectedly poor outcomes,” said Mathias Ehrich, M.D., chief scientific officer. “These data show that we can potentially reduce the time between patient diagnosis and initiation of tailored treatment or inclusion in clinical studies from a month, in best-case scenarios, to just a few days, by using our PCR EpiCheck-based assay for the classification of SCLC subtypes.”