Abstract B031: A multi-gene predictor for detection and monitoring liver metastasis in lung cancer patients: An algorithmic, in-vitro and in-vivo approach

Abstract

Abstract Liver metastasis has known to affect outcome in prostate, pancreatic and colorectal cancers, but it is less explored in lung cancer with an extensively low 5-year survival rate. Late-stage diagnosis is one of the major confounders for poor prognosis, as there are no disease-specific biomarkers available for early risk prediction. Some of the major limitations of invasive tissue biopsies are inadequacy of tissue, difficulty in accessing deep sites, and potential risk for the patient. Therefore, it is crucial to identify sensitive and specific circulatory biomarkers using non-invasive techniques. In this study, we validated 8 gene panel, in CTC, cfRNA and exosomes using real time PCR in primary lung cancer patients with & without metastasis and healthy controls, identified in our previous study in the tissue samples of the same cohort. ROC curve analysis was used to determine the sensitivity and specificity of the shortlisted gene panel and its correlation with the most accurate source of liquid biopsy component for early prediction of liver metastasis. Further DEP expression, clinic-pathological factors and survival analysis correlations were performed. Lastly, the role of exosomes was identified in the development of liver metastasis by generating an in vitro and in-vivo model. Our results demonstrated that in comparison to our tissue data from the previous study, exosomes demonstrated a good discriminative value for lung cancer liver metastasis and the AUC was 0.7247, with specificity and sensitivity of 72.48 % and 96.87% respectively for the shortlisted 8 gene panel. Further when we analyzed the genes based on the individual gene patterns we shortlisted a 5- gene panel that showed an AUC of 0.9488 (p = <0.001) and 0.9924 (p = <0.001) respectively for tissue and exosomes suggesting that exosomes could be used as a non-invasive component for the early prediction of liver metastasis. Survival analysis suggested that four out of five gene expression levels in exosomal fraction, were independently associated with poor overall survival. Moreover, the in-vitro study demonstrated that exosome uptake by A549 cells induced migratory/invasive changes in a concentration and time- dependent manner and activated the cell cycle phases leading to cell proliferation. Moreover, we observed that these five genes were differentially expressed when A549 cells were treated with exosomes demonstrating an important role in altering the tumor microenvironment. In –vivo model showed an elevated level of serum SGPT & SGOT whereas histopathological examination showed patches of pneumonitis in lung and severe inflammation in the liver. Conclusively this study suggests that these exosomal gene panel could be used as potential surrogate non-invasive biomarkers for early detection and monitoring of liver metastasis in lung cancer patients. Furthermore, it depicts an undisputable role of these exosomes as key modulators in the formation of the pre-metastatic niche ultimately leading to distant metastasis. Citation Format: Kanisha Shah, Rakesh Rawal. A multi-gene predictor for detection and monitoring liver metastasis in lung cancer patients: An algorithmic, in-vitro and in-vivo approach [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr B031.