A novel algorithm to differentiate between primary lung tumors and distant liver metastasis in lung cancers using an exosome based multi gene biomarker panel.

The lack of non-invasive methods for detection of early metastasis is a crucial reason for the poor prognosis of lung cancer (LC) liver metastasis (LM) patients. In this study, the goal was to identify circulating biomarkers based on a biomarker model for the early diagnosis and monitoring of patients with LCLM. An 8-gene panel identified in our previous study was validated in CTC, cfRNA and exosomes isolated from primary lung cancer with & without metastasis. Further multivariate analysis including PCA & ROC was performed to determine the sensitivity and specificity of the biomarker panel. Model validation cohort (n = 79) was used to verify the stability of the constructed predictive model. Further, clinic-pathological factors, survival analysis and immune infiltration correlations were also performed. In comparison to our previous tissue data, exosomes demonstrated a good discriminative value with an AUC of 0.7247, specificity (72.48%) and sensitivity (96.87%) for the 8-gene panel. Further individual gene patterns led us to 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. Additionally, on validating the model in a larger cohort a risk score was obtained (RS > 0.2) for prediction of liver metastasis with an accuracy of 95%. Survival analysis and immune filtration markers suggested that four exosomal markers were independently associated with poor overall survival. We report a novel blood-based exosomal biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with LCLM.

Putative stemness markers octamer-binding transcription factor 4, sex-determining region Y-box 2, and NANOG in non-small cell lung carcinoma: A clinicopathological association.

BACKGROUND: The promising improvement in the clinical outcome of lung cancer can be possibly achieved by identification of the molecular events that underlie its pathogenesis. Cancer stem cell (CSC) being one of the subsets of tumor majorly participates in drug resistance and treatment failure because of the moderate cell cycle, lower proliferation, and increased expression of DNA repair and anti-apoptosis genes. Although many putative CSC markers exist, a precise characterization for non-small cell lung cancer is of utmost importance due to increased mortality rate and lack of targeted therapies. Hence, the article focuses on the expression of stemness-associated markers, namely octamer-binding transcription factor 4 (OCT4), NANOG, and sex-determining region Y-box 2 (SOX2) in non-small cell lung cancer (NSCLC) patients. METHODS: The expression of OCT4, NANOG, and SOX2 were evaluated in 32 histopathologically confirmed NSCLC tissues using real-time polymerase chain reaction. The obtained expression was correlated with clinical and pathological manifestations using the statistical test such as Student's t-test and Pearson correlation in varied statistical software. RESULTS: Results showed a significantly higher expression of OCT4 and NANOG compared to SOX2 in the tumor tissues. When the expression of these markers was correlated with the clinical parameters, higher expression was seen in males, patients with age above 60 years, and in adenocarcinoma subtype. In correlation with the habit, higher expression of OCT4 and SOX2 was observed in habituated patients. Expression of NANOG and OCT4 was higher even in patients with poor differentiation. CONCLUSION: The expression and prognostic significance of CSC markers obviously vary depending on histological NSCLC subtype. Importantly, our findings suggest that OCT4, SOX2, and NANOG network together may be promising for ongoing targeted therapies in specific NSCLC subgroups.