Plasma Extracellular Vesicle Long RNA in Diagnosis and Prediction in Small Cell Lung Cancer

Abstract

(1) Introduction: The aim of this study was to identify the plasma extracellular vesicle (EV)-specific transcriptional profile in small-cell lung cancer (SCLC) and to explore the application value of plasma EV long RNA (exLR) in SCLC treatment prediction and diagnosis. (2) Methods: Plasma samples were collected from 57 SCLC treatment-naive patients, 104 non-small-cell lung cancer (NSCLC) patients and 59 healthy participants. The SCLC patients were divided into chemo-sensitive and chemo-refractory groups based on the therapeutic effects. The exLR profiles of the plasma samples were analyzed by high-throughput sequencing. Bioinformatics approaches were used to investigate the differentially expressed exLRs and their biofunctions. Finally, a t-signature was constructed using logistic regression for SCLC treatment prediction and diagnosis. (3) Results: We obtained 220 plasma exLRs profiles in all the participants. Totals of 5787 and 1207 differentially expressed exLRs were identified between SCLC/healthy controls, between the chemo-sensitive/chemo-refractory groups, respectively. Furthermore, we constructed a t-signature that comprised ten exLRs, including EPCAM, CCNE2, CDC6, KRT8, LAMB1, CALB2, STMN1, UCHL1, HOXB7 and CDCA7, for SCLC treatment prediction and diagnosis. The exLR t-score effectively distinguished the chemo-sensitive from the chemo-refractory group (p = 9.268 × 10−9) with an area under the receiver operating characteristic curve (AUC) of 0.9091 (95% CI: 0.837 to 0.9811) and distinguished SCLC from healthy controls (AUC: 0.9643; 95% CI: 0.9256–1) and NSCLC (AUC: 0.721; 95% CI: 0.6384–0.8036). (4) Conclusions: This study firstly characterized the plasma exLR profiles of SCLC patients and verified the feasibility and value of identifying biomarkers based on exLR profiles in SCLC diagnosis and treatment prediction.

Exploring the Role of Vitamin D, Vitamin D-Dependent Proteins, and Vitamin D Receptor Gene Variation in Lung Cancer Risk

“…The real interest shown for calretinin in this context is due to its occasional presence observed in regular cases of lung cancer. Thus, by corroborating this fact with data that establish CABP29K as a typical mesothelioma marker, which is an aggressively malignant cancer, the conclusion is that diagnostic and therapeutic strategies may seriously interfere with the questionable expression of calretinin in lung tumors [ 58 ]. However, this issue can be easily overcome by a simple strategy proposed by researchers: the screening of other mesothelioma-specific markers, such as podoplanin, cytokeratin, or mesothelin, which can help to differentiate lung carcinoma from mesothelioma [ 59 ].…”

“…Non-small cell lung cancer [63] CALB2 Overexpression Not associated with cancer but with malignant pleural mesothelioma [57] S100-G Overexpression Non-small cell lung cancer [58]…”