Abstract

Abstract Introduction:Stage is the most important prognostic factor for survival in non-small cell lung cancer (NSCLC). The current TNM (Tumor, Node, Metastasis) staging system for NSCLC uses physical exam, histology, imaging, and surgical findings to define the extent and spread of a patient’s cancer. Despite advances in molecular testing which can impact treatment and prognosis for NSCLC patients, the current system does not incorporate molecular data into staging. We proposed a novel predictive model for survival analysis which integrates molecular analysis of liquid biopsies (B) into the TNM staging system (1). In this study, we tested this new staging system and our predictive model shows TNM + B (TNMB) provides a better predictive model for survival compared to TNM alone. Methods:176 patients were identified at Atrium Health Wake Forest Baptist with Guardant 360 liquid biopsies sent at diagnosis for NSCLC. Clinical data was obtained through retrospective chart review. Molecular analysis was performed on 81 genes across all Guardant 360 liquid biopsies. Using Cox proportional hazards model, we identified significant gene mutations or genes with significant magnitude of variant allele frequency (VAF) that improved survival prediction. We then designed a novel staging system incorporating whether a patient had a positive liquid biopsy test (B1), defined by the presence of these impact gene variables, to TNM stage. Results: Three impact genes STK11 (p=0.0253), NFE2L2 (p = 0.0025), TP53 (p=0.0129) and one gene with a magnitude of VAF, ARID1A (p=0.0082) was identified which significantly improved the predictive model for survival. Patients with negative liquid biopsy test, B0, had improved survival compared to patients with a positive liquid biopsy test, B1 (p<0.005). In our cohort, TNM staging alone did not show a significant survival difference between stage II and III (p = 0.19). Whereas TNMB staging showed a significant survival difference between stage II, III and IV. Conclusions: While TNM stage remains a major prognostic factor for NSCLC patients, it fails to incorporate molecular data which has a critical impact on management and prognosis. We designed a novel method to analyze molecular data obtained by liquid biopsy to identify significant gene mutations and gene magnitude of VAF that impacts survival prediction. In our cohort, we showed 4 impact genes which we used to create a new TNMB staging system which led to improved survival prediction compared to TNM alone. Acknowledgments: Research partly supported by NIH T32 Grant (T32CA247819) and Cancer Center Support Grant (P30CA012197) Reference: (1) Yang M, Forbes ME, Bitting RL, O'Neill SS, Chou PC, Topaloglu U, Miller LD, Hawkins GA, Grant SC, DeYoung BR, Petty WJ, Chen K, Pasche BC, Zhang W. Incorporating Blood-based Liquid Biopsy Information into Cancer Staging: Time for a TNMB System? Ann Oncol. 2018 Feb 1;29(2):311-323. Citation Format: Lauren Schmalz, Cetin Urtis, Liang Liu, Elizabeth Forbes, Fang-Chi Hsu, Nury Steuerwald, Alberto de Hoyos, Thomas Lycan, Jimmy Ruiz, William Petty, Wei Zhang. Integrating blood based liquid biopsies with TNM stage improves survival prediction model for non-small cell lung cancer [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 5065.

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