Clinical significance of circulating tumor cells and metabolic signatures in lung cancer after surgical removal

Abstract

Background Lung cancer (LC) remains the deadliest form of cancer globally. While surgery remains the optimal treatment strategy for individuals with early-stage LC, what the metabolic consequences are of such surgical intervention remains uncertain. Methods Negative enrichment-fluorescence in situ hybridization (NE-FISH) was used in an effort to detect circulating tumor cells (CTCs) in pre- and post-surgery peripheral blood samples from 51 LC patients. In addition, targeted metabolomics analyses, multivariate statistical analyses, and pathway analyses were used to explore surgery-associated metabolic changes. Results LC patients had significantly higher CTC counts relative to healthy controls with 66.67% of LC patients having at least 1 detected CTC. CTC counts were associated with clinical outcomes following surgery. In a targeted metabolomics analysis, we detected 34 amino acids, 164 lipids, and 24 fatty acids. When comparing LC patients before and after surgery to control patients, metabolic shifts were detected via PLS-DA and pathway analysis. Further surgery-associated metabolic changes were identified when comparing LA and LB groups. We identified SM 42:4, Ser, Sar, Gln, and LPC 18:0 for inclusion in a biomarker panel for early-stage LC detection based upon an AUC of 0.965 (95% CI = 0.900–1.000). This analysis revealed that SM 42:2, SM 35:1, PC (16:0/14:0), PC (14:0/16:1), Cer (d18:1/24:1), and SM 38:3 may offer diagnostic and prognostic benefits in LC. Conclusions These findings suggest that CTC detection and plasma metabolite profiling may be an effective means of diagnosing early-stage LC and identifying patients at risk for disease recurrence.

Detection of circulating tumor cells: Advances and critical concerns (Review)

“…The functional cellular characteristics of CTCs can also be analyzed, which can provide information on cancer biology (19). The existence of CTCs has been confirmed in many cancer types, including lung (20), prostate (21), liver (22), breast (23), pancreas (24), colon (25), ovarian (26) cancers and so on. Its development includes early cancer diagnosis, prognosis monitoring, treatment efficacy, drug resistance analysis, and therapeutic targeting of CTCs to prevent metastasis, hence enabling personalized therapy (27,28).…”