A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC

LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.

Evaluation of the Prognostic Value of Long Noncoding RNAs in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) is the most common type of lung cancer accounting for 40% to 51%. Long noncoding RNAs (lncRNAs) have been reported to play a significant role in the invasion, migration, and proliferation of lung cancer tissue cells. However, systematic identification of lncRNA signatures and evaluation of the prognostic value for LUSC are still an urgent problem. In this work, LUSC RNA-seq data were collected from TCGA database, and the limma R package was used to screen differentially expressed lncRNAs (DElncRNAs). In total, 216 DElncRNAs were identified between the LUSC and normal samples. lncRNAs associated with prognosis were calculated using univariate Cox regression analysis. The overall survival (OS) prognostic model containing 10 lncRNAs and the disease-free survival (DFS) prognostic model consisting of 11 lncRNAs were constructed using a machine learning-based algorithm, systematic LASSO-Cox regression analysis. We found that the survival rate of samples in the high-risk group was lower than that in the low-risk group. Results of ROC curves showed that both the OS and DFS risk score had better prognostic effects than the clinical characteristics, including age, stage, gender, and TNM. Two lncRNAs (LINC00519 and FAM83A-AS1) that were commonly identified as prognostic factors in both models could be further investigated for their clinical significance and therapeutic value. In conclusion, we constructed lncRNA prognostic models with considerable prognostic effect for both OS and DFS of LUSC.

PTBP3 regulates proliferation of lung squamous cell carcinoma cells via CDC25A‐mediated cell cycle progression

Background The roles of Polypyrimidine tract-binding protein 3 (PTBP3) in regulating lung squamous cell carcinoma (LUSC) cells progression is unclear. The aim of this study was to investigate the role of PTBP3 in LUSC. Methods Expression and survival analysis of PTBP3 was firstly investigated using TCGA datasets. Quantitative reverse transcription PCR and Western blot were performed to detect PTBP3 expression in clinical samples. Moreover, cell counting kit 8 (CCK-8) assays, colony formation assays and in vivo tumor formation assays were used to examine the effects of PTBP3 on LUSC cell proliferation. RNA-sequence and analysis explores pathways regulated by PTBP3.Flow cytology was used analyzed cell cycle. Cell cycle-related markers were analyzed by Western blot. Results PTBP3 was found to be overexpressed in LUSC tissues compared with normal tissues. High PTBP3 expression was significantly correlated with poor prognosis. In vitro and vivo experiments demonstrated that PTBP3 knockdown caused a significant decrease in the proliferation rate of cells. Bioinformatics analysis showed that PTBP3 involved in cell cycle pathway regulation in LUSC. Furthermore, PTBP3 knockdown arrested cell cycle progression at S phase via decreasing CDK2/Cyclin A2 complex. In addition, downregulation of PTBP3 significantly decreased the expression of CDC25A. Conclusions Our results suggest that PTBP3 regulated LUSC cell proliferation via cell cycle and might be a potential target for molecular therapy of LUSC.

Case Report: Partial Response Following Nivolumab Plus Docetaxel in a Patient With EGFR Exon 20 Deletion/Insertion (p.N771delinsGF) Mutant Lung Adenocarcinoma Transdifferentiated From Squamous Cell Carcinoma

The histological transformation from lung squamous cell carcinoma (LUSC) to lung adenocarcinoma (LUAD) and p. N771delinsGF mutations in EGFR exon 20 (ex20) are exceedingly rare in non–small cell lung carcinoma (NSCLC). EGFR ex20 mutations are insensitive to EGFR tyrosine kinase inhibitors in NSCLC. Here, we present a 76-year-old male smoker harboring LUAD with a novel p. N771delinsGF deletion/insertion mutation in EGFR ex20 transdifferentiating from advanced LUSC after chemoradiotherapy. The patient presented reduced hydrothorax and relieved tightness with the treatment of nivolumab plus docetaxel and carboplatin after the failure of second-line chemotherapy. The case highlights the importance of rebiopsy and molecular retesting after the progression of lung cancer and supports the idea that the combination of immune checkpoint blockade and chemotherapy may be an attractive option for patients with EGFR ex20 mutations associated with LUSC–LUAD transformation.

Hypoxia-mediated YTHDF2 overexpression promotes lung squamous cell carcinoma progression by activation of the mTOR/AKT axis

Background N6-methyladenosine (m6A) is a dynamic and reversible internal RNA structure of eukaryotic mRNA. YTH domain family 2 (YTHDF2), an m6A-specific reader YTH domain family, plays fundamental roles in several types of cancer. However, the function of YTHDF2 in lung squamous cell carcinoma (LUSC) remains elusive. Methods The knockdown and overexpression of YTHDF2 in LUSC cells were conducted to detect the biological characteristics of YTHDF2. In vivo assays, the role of YTHDF2 in tumor growth was further uncovered. In vitro assays, YTHDF2 was confirmed to be involved in activating the mTOR/AKT signaling and YTHDF2 overexpression induced the EMT process in LUSC. Clinically, immunohistochemical staining revealed the relationship between YTHDF2 expression levels and the clinicopathological characteristics of lung squamous cell carcinoma patients. Moreover, quantitative PCR (qPCR), western blot, CCK8 assay, transwell assay, and wound-healing assay were used to detect the expression level and function of YTHDF2 under hypoxia exposure in LUSC cells. Results The results showed that hypoxia-mediated YTHDF2 overexpression promotes cell proliferation and invasion by activating the mTOR/AKT axis, and YTHDF2 overexpression induces the EMT process in LUSC. Moreover, YTHDF2 is closely associated with pN (pN– 37.0%, pN + 73.9%; P = 0.002) and pTNM stage (pI 50.0%, PII 43.3%, pIIIa 80.6%; P = 0.007), ultimately resulting in poor survival for LUSC patients. Conclusion In brief, the results highlight high-YTHDF2 expression predicted a worse prognosis of LUSC, while hypoxia-mediated YTHDF2 overexpression promotes lung squamous cell carcinoma progression by activation of the mTOR/AKT signaling pathway.

The importance of enhancer methylation for epigenetic regulation of tumorigenesis in squamous lung cancer

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell lung cancer (NSCLC). LUSC occurs at the bronchi, shows a squamous appearance, and often occurs in smokers. To determine the epigenetic regulatory mechanisms of tumorigenesis, we performed a genome-wide analysis of DNA methylation in tumor and adjacent normal tissues from LUSC patients. With the Infinium Methylation EPIC Array, > 850,000 CpG sites, including ~350,000 CpG sites for enhancer regions, were profiled, and the differentially methylated regions (DMRs) overlapping promoters (pDMRs) and enhancers (eDMRs) between tumor and normal tissues were identified. Dimension reduction based on DMR profiles revealed that eDMRs alone and not pDMRs alone can differentiate tumors from normal tissues with the equivalent performance of total DMRs. We observed a stronger negative correlation of LUSC-specific gene expression with methylation for enhancers than promoters. Target genes of eDMRs rather than pDMRs were found to be enriched for tumor-associated genes and pathways. Furthermore, DMR methylation associated with immune infiltration was more frequently observed among enhancers than promoters. Our results suggest that methylation of enhancer regions rather than promoters play more important roles in epigenetic regulation of tumorigenesis and immune infiltration in LUSC.

Switched alternative splicing events as attractive features in lung squamous cell carcinoma

Background Alternative splicing (AS) plays important roles in transcriptome and proteome diversity. Its dysregulation has a close affiliation with oncogenic processes. This study aimed to evaluate AS-based biomarkers by machine learning algorithms for lung squamous cell carcinoma (LUSC) patients. Method The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database were utilized. After data composition balancing, Boruta feature selection and Spearman correlation analysis were used for differentially expressed AS events. Random forests and a nested fivefold cross-validation were applied for lymph node metastasis (LNM) classifier building. Random survival forest combined with Cox regression model was performed for a prognostic model, based on which a nomogram was developed. Functional enrichment analysis and Spearman correlation analysis were also conducted to explore underlying mechanisms. The expression of some switch-involved AS events along with parent genes was verified by qRT-PCR with 20 pairs of normal and LUSC tissues. Results We found 16 pairs of splicing events from same parent genes which were strongly related to the splicing switch (intrapair correlation coefficient = − 1). Next, we built a reliable LNM classifier based on 13 AS events as well as a nice prognostic model, in which switched AS events behaved prominently. The qRT-PCR presented consistent results with previous bioinformatics analysis, and some AS events like ITIH5-10715-AT and QKI-78404-AT showed remarkable detection efficiency for LUSC. Conclusion AS events, especially switched ones from the same parent genes, could provide new insights into the molecular diagnosis and therapeutic drug design of LUSC.

On-treatment blood TMB as predictors for camrelizumab plus chemotherapy in advanced lung squamous cell carcinoma: biomarker analysis of a phase III trial

Background Camrelizumab plus chemotherapy significantly prolonged progression-free survival (PFS) and overall survival (OS) compared to chemotherapy alone as first-line treatment in advanced lung squamous cell carcinoma (LUSC) in the phase III trial (CameL-sq), which has become an option of standard-of-cares for Chinese patients with advanced LUSC. However, the predictive biomarkers remain unknown. Methods Tumor tissue samples at baseline, and peripheral blood samples at baseline (pretreatment) and after two cycles of treatment (on-treatment) were prospectively collected from 270 LUSC patients from the CameL-sq study. Blood tumor mutation burden (bTMB) and its dynamics were analyzed to explore their predictive values. Results Pretreatment bTMB was not associated with objective response, PFS and OS in camrelizumab or placebo plus chemotherapy groups. Low on-treatment bTMB was associated with significantly better objective response (73.8% vs 27.8%, P < 0.001), PFS (median, 9.1 vs 4.1 months; P < 0.001) and OS (median, not reached vs 8.0 months; P < 0.001) in camrelizumab plus chemotherapy group whereas it did not correlate with objective response and PFS in chemotherapy alone group. Importantly, on-treatment bTMB level could discriminate patients of initially radiological stable disease who would long-term benefit from camrelizumab plus chemotherapy (low vs high, median OS, 18.2 vs 7.8 months; P = 0.001). Combing on-treatment bTMB and its dynamics improved the ability for predicting the efficacy of camrelizumab plus chemotherapy. Conclusion On-treatment bTMB together with its dynamics could serve as a predictive biomarker for camrelizumab plus chemotherapy in patients with advanced LUSC. Trial registration ClinicalTrials.gov identifier: NCT03668496.