Abstract 1722: Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform

Abstract Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with poor survival rates. Despite molecular and clinical heterogeneity, SCLC is currently treated as a single entity without guidance of predictive biomarkers leading to expectedly poor outcomes. A recent study suggested classifying SCLC into four subtypes (“A”, “N”, “P” and “I”), each with unique molecular features and therapeutic vulnerabilities. While initially this classification was based on gene expression (RNA-seq) data, subsequent data suggest it can be recapitulated using reduced-representation bisulfite sequencing (RRBS) methylation profile. While the classification system accurately predicts responses to therapies, including immunotherapies, in retrospective analysis, both tissue-based RNAseq and RRBS are cumbersome, time-consuming and impractical for prospective treatment assignment in an aggressive malignancy. In this pilot study, we developed a methylation-based PCR assay for classification of SCLC subtypes based on the EpiCheck platform, which combines methylation-sensitive restriction endonuclease (MSRE) digestion with qPCR amplification to detect differential methylation at the DNA level. We developed a 13-marker assay and successfully classified, in a blinded study, 96.55% of FFPE tissue samples originating from SCLC patient of A, N and P subtypes. First, a bioinformatic analysis identified 41 candidate biomarkers that are differentially methylated between pairs of SCLC subtypes (A-N, A-P, and N-P) using RRBS data from 56 RNA-seq classified SCLC tumor samples (34 “A”, 19 “N”, 3 “P”). Development of primers and probes for these markers was followed by a biochemical selection process, identifying 13 markers that displayed optimal performance. A PCR EpiCheck assay, employing these 13 markers, was applied to a blinded set of 29 DNA samples from SCLC FFPE tumor tissues (21 “A”, 6 “N”, 2 “P”). Each sample received two ranks based on methylation levels of 5 A-N and 9 P-AN markers and was classified using determined thresholds for each rank. Finally, when comparing PCR-based and RNA-seq-based classifications, the 13-marker PCR assay classified 28/29 (96.55%) of the samples concordantly, misclassifying one "P" sample as "A". This pilot demonstrates the potential of a simple PCR EpiCheck-based assay to accurately differentiate between SCLC subtypes. For complete subtype classification, “I” markers need to be added to the panel, and the assay should be further validated using a larger cohort, particularly for the “P” subtype. Early detection and classification are critical for timely personalized therapy, and such an assay, performed on cfDNA samples, could potentially be used to shorten the time between a patient diagnosis and tailored treatment initiation or clinical study inclusion from a month in best case scenarios to a few days. Citation Format: Orna Savin, Dvir Netanely, Simon Heeke, Carl Michael Gay, Marcos Roberto Estecio, Shacade Danan, Sarah Zaouch, Aharona Shuali, Mathias Ehrich, Lauren Averett Byers, John Victor Heymach, Adam Wasserstrom, Danny Frumkin. Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1722.