Identification and Validation of Immune-Related Long Non-Coding RNA Signature for Predicting Immunotherapeutic Response and Prognosis in NSCLC Patients Treated With Immunotherapy

Abstract

BackgroundNumerous studies have reported that long non-coding RNAs (lncRNAs) play important roles in immune-related pathways in cancer. However, immune-related lncRNAs and their roles in predicting immunotherapeutic response and prognosis of non-small cell lung cancer (NSCLC) patients treated with immunotherapy remain largely unexplored.MethodsTranscriptomic data from NSCLC patients were used to identify novel lncRNAs by a custom pipeline. ImmuCellAI was utilized to calculate the infiltration score of immune cells. The marker genes of immunotherapeutic response-related (ITR)-immune cells were used to identify immune-related (IR)-lncRNAs. A co-expression network was constructed to determine their functions. LASSO and multivariate Cox analyses were performed on the training set to construct an immunotherapeutic response and immune-related (ITIR)-lncRNA signature for predicting the immunotherapeutic response and prognosis of NSCLC. Four independent datasets involving NSCLC and melanoma patients were used to validate the ITIR-lncRNA signature.ResultsIn total, 7,693 novel lncRNAs were identified for NSCLC. By comparing responders with non-responders, 154 ITR-lncRNAs were identified. Based on the correlation between the marker genes of ITR-immune cells and lncRNAs, 39 ITIR-lncRNAs were identified. A co-expression network was constructed and the potential functions of 38 ITIR-lncRNAs were annotated, most of which were related to immune/inflammatory-related pathways. Single-cell RNA-seq analysis was performed to confirm the functional prediction results of an ITIR-lncRNA, LINC01272. Four-ITIR-lncRNA signature was identified and verified for predicting the immunotherapeutic response and prognosis of NSCLC. Compared with non-responders, responders had a lower risk score in both NSCLC datasets (P<0.05). NSCLC patients in the high-risk group had significantly shorter PFS/OS time than those in the low-risk group in the training and testing sets (P<0.05). The AUC value was 1 of responsiveness in the training set. In melanoma validation datasets, patients in the high-risk group also had significantly shorter OS/PFS time than those in the low-risk group (P<0.05). The ITIR-lncRNA signature was an independent prognostic factor (P<0.001).ConclusionThousands of novel lncRNAs in NSCLC were identified and characterized. In total, 39 ITIR-lncRNAs were identified, 38 of which were functionally annotated. Four ITIR-lncRNAs were identified as a novel ITIR-lncRNA signature for predicting the immunotherapeutic response and prognosis in NSCLC patients treated with immunotherapy.

Differential organ-specific tumor response to first-line immune checkpoint inhibitor therapy in non-small cell lung cancer—a retrospective cohort study

“…In the phase I KEYNOTE-001 study, the subgroup of individuals with metastatic melanoma was analyzed; the highest rate of CR (42.3%) was in lung lesions, followed by peritoneal (37.3%) and liver (24.4%) ( 23 ). The findings of this research are in line with the recently published NSCLC cohort by researchers demonstrating higher OSRR and OSDCR in patients with lymph node metastases, also supporting the concept of better response in organs with postulated high pre-treatment immune cell infiltration ( 24 ). In addition, the discoveries in this study substantiate previously published studies reporting poorer activities in liver metastases ( 25 ), where the liver exhibits suppressive immune modulation attributes ( 13 ).…”

The tumor microenvironment in gastrointestinal adenocarcinomas revealed a prognostic and immunotherapeutic biomarker

“…Thus, we extra used the transcriptional sequencing data of GIAC patients and immunotherapy response status of melanoma and urothelial carcinoma patients to assess the value of TMEscore. Though this method often used in previous studies [59][60][61][62][63][64] can be serve as a tentative and preliminary expansion application, it is indeed biased and not rigorous. When relevant data is publicly available in the future, we can precisely assess the predicted value of TMEscore in matched datasets.…”

LINC02159 promotes non-small cell lung cancer progression via ALYREF/YAP1 signaling

“…Studies have shown that lncRNAs LCETRL3 and LCETRL4 on chromosome 4q12 reduce the therapeutic sensitivity of EGFR-TKI in NSCLC by stabilizing TDP43 and EIF2S1 [11]. Ma et al have constructed an immunotherapeutic response and immune-related (ITIR)-lncRNA signature, which can be used to predict the immunotherapy response and prognosis of NSCLC patients receiving immunotherapy [12]. Ling et al demonstrated that the level of exosomal lncRNA RP5-977B1 has high diagnostic ability and prognostic value in NSCLC because it is higher than that in the healthy control group [13].…”