Characterization of lncRNA-Associated ceRNA Network to Reveal Potential Prognostic Biomarkers in Lung Adenocarcinoma

Deciphering disulfidptosis: Uncovering a lncRNA-based signature for prognostic assessment, personalized immunotherapy, and therapeutic agent selection in lung adenocarcinoma patients

BACKGROUND

Disulfidptosis, a recently identified type of regulated cell death, plays critical roles in various biological processes of cancer; however, whether they can impact the prognosis of lung adenocarcinoma (LUAD) remains to be fully elucidated. We aimed to adopt this concept to develop and validate a lncRNA signature for LUAD prognostic prediction.

METHODS

For this study, the TCGA-LUAD dataset was used as the training cohort, and multiple datasets from the GEO database were pooled as the validation cohort. Disulfidptosis regulated genes were obtained from published studies, and various statistical methods, including Kaplan-Meier (KM), Cox, and LASSO, were used to train our gene signature DISULncSig. We utilized KM analysis, COX analysis, receiver operating characteristic analysis, time-dependent AUC analysis, principal component analysis, nomogram predictor analysis, and functional assays in our validation process. We also compared DISULncSig with previous studies. We performed analyses to evaluate DISULncSig's immunotherapeutic ability, focusing on eight immune algorithms, TMB, and TIDE. Additionally, we investigated potential drugs that could be effective in treating patients with high-risk scores. Additionally qRT-PCR examined the expression patterns of DISULncSig lncRNAs, and the ability of DISULncSig in pan-cancer was also assessed.

RESULTS

DISULncSig containing twelve lncRNAs was trained and showed strong predictive ability in the validation cohort. Compared with previous similar studies, DISULncSig had more prognostic ability advantages. DISULncSig was closely related to the immune status of LUAD, and its tight relationship with checkpoints KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28 may be the key to its potential immunotherapeutic ability. For the high DISULncSig score population, we found ten drug candidates, among which epothilone-b may have the most potential. The pan-cancer analysis found that DISULncSig was a risk factor in multiple cancers. Additionally, we discovered that some of the DISULncSig lncRNAs could play crucial roles in specific cancer types.

CONCLUSION

The current study established a powerful prognostic DISULncSig signature for LUAD that was also valid for most pan-cancers. This signature could serve as a potential target for immunotherapy and might help the more efficient application of drugs to specific populations.

Utility of auto fluorescence-guided biopsy in suspected lung cancer patients with bronchial mucosal lesions

BACKGROUND

Bronchoscopy is currently the most common technique for lung cancer diagnosis. Patients suspected of malignancy often undergo bronchoscopic examination, and biopsy is routinely used in patients with visible bronchial lesions. However, it is difficult to differentially diagnose lung cancer in patients with bronchial mucosal lesions. Thus, this study was conducted to investigate the utility of fluorescence-guided biopsy in suspected lung cancer patients with bronchial mucosal lesions.

METHODS

We conducted a retrospective study in a single screening center to assess the sensitivity and specificity of fluorescence-guided biopsy compared with white light bronchoscopy (WLB) in patients with bronchial mucosal lesions.

RESULTS

A total of 301 patients with bronchial mucosal lesions were enrolled in this study. The sensitivity for patients with fluorescence-guided biopsy was 60.3 % (95 % confidence interval [CI]: 53.1 %-67.1 %), which was higher than that of patients with WLB alone (45.2 %, 95 % CI: 38.2-52.4 %) (P = 0.0026). Additionally, compared with the WLB group, the fluorescence -guided biopsy group was found to have a significantly higher specificity (100 %, 95 % CI: 95.5-100 % versus 69.6 %, 95 % CI: 59.6-78.1 %), positive predictive value (100 %, 95 % CI: 96.1-100 % versus 74.3 %, 95 % CI: 65.5-81.7 %) and negative predictive value (56.3 %, 95 % CI: 48.8-63.6 % versus 39.4 %, 95 % CI: 32.3-47.0 %).

CONCLUSION

Fluorescence-guided biopsy can serve as an important adjunct to WLB for the differential diagnosis of lung cancer in patients with bronchial mucosal lesions.

GPR37-centered ceRNA network contributes to metastatic potential in lung adenocarcinoma: Evidence from high-throughput sequencing

The competing endogenous RNA (ceRNA)-based profiling has been extensively studied in carcinogenesis of lung adenocarcinoma (LUAD), while it has seldomly been applied to investigate the metastatic potential of LUAD. This study aims to examine the function and in-depth mechanism of GPR37-centered ceRNA network in LUAD. Cancer tissues and adjacent normal tissues from three LUAD patients were collected for high-throughput sequencing to screen for differentially expressed genes. A PPI network was constructed to screen the key gene GPR37, followed by analysis for the functions and pathways. Clinical data from LUAD patients were integrated with gene expression data in TCGA-LUAD dataset for survival analysis. Based on the miRNAs targeting_GPR37 and lncRNAs targeting_miRNAs, a lncRNA-miRNA-mRNA ceRNA network was established. GPR37 was up-regulated in LUAD tissue samples, and it may be a key gene involved in LUAD progression. GPR37 in LUAD was mainly enriched in the mitosis-related pathways. High GPR37 expression corresponded to poor prognosis in LUAD patients. Meanwhile, GPR37 could be used as an independent factor to predict the prognosis in LUAD patients. LncRNA DLEU1, up-regulated in LUAD tissue samples, may competitively bind to miR-4458 to up-regulate the expression of the miR-4458 downstream target GPR37. DLEU1 was associated with poor prognosis and tumor metastasis in LUAD patients. Altogether, our findings reveal a novel ceRNA network of DLEU1/miR-4458/GPR37 in LUAD growth and metastasis.

A cuproptosis-associated long non-coding RNA signature for the prognosis and immunotherapy of lung squamous cell carcinoma

Cuproptosis, a copper-induced mechanism of mitochondrial-related cell death, has been implicated as a breakthrough in the treatment of cancer and has become a new treatment strategy. Furthermore, long non-coding RNA (lncRNA) can change the biological activities of tumor cells. Worldwide, lung squamous cell carcinoma (LUSC) is among the most common annoying tumors. LncRNAs related to cuproptosis are not researched at LUSC. Our research intends to develop a signature on the basis of cuproptosis-associated lncRNAs, which can predict LUSC prognosis and investigate LUSC immunological features. The TCGA database was used to retrieve LUSC transcriptome, clinical, and gene mutation data. For statistical analysis, we utilized the R program. We created a signature consisting of three cuproptosis-related lncRNAs in this investigation (including AC002467.1, LINC01740, and LINC02345). Survival analyses and Receiver Operating Characteristic curves demonstrated that this signature possessed powerful predictive capability. The signature's ability to predict was confirmed by a Receiver Operating Characteristic curve and principal component analysis. Notably, the patient with a high-risk score and a high tumor mutation burden level had a lower survival time. Furthermore, the tumor immune dysfunction and exclusion analysis showed that these individuals with low-risk scores may benefit from immunotherapy. The signature constructed by three cuproptosis-associated lncRNAs may be prognostic markers of LUSC. It contributes to immunotherapy and offers LUSC's therapy a new treatment direction.

The diagnostic potential of a circRNA-miRNA network in non-small cell lung cancer

Increasing studies demonstrate the significant contributions of circRNA-related competitive endogenous RNA (ceRNA) regulatory networks to tumorigenesis and cancer progression. Here, we aimed to construct a non-small cell lung cancer (NSCLC)-specific circRNA-miRNA network and evaluate its diagnostic potential in NSCLC. MiRNA deep sequencing was performed to screen differentially-expressed serum miRNAs in NSCLC. Four bioinformatics databases (TargetScan, miRanda, starBase, and RNAhybrid) were used to analyze the integrated circRNA-miRNA interaction network. The circRNA-miRNA network, including hsa-miR-4482-3p, hsa-miR-146a-3p, hsa_circ_0008167 and hsa_circ_0003317 was constructed based on their interactions and preliminary testing in NSCLC cells. The relative levels of the selected non-coding RNAs (ncRNAs) were quantified using quantitative real-time polymerase chain reaction (qRT-PCR) in the healthy, pneumonia, benign lung tumor and NSCLC cohorts. The diagnostic power of the circRNA-miRNA network was evaluated using receiver operating characteristic (ROC) analyses. The serum levels of hsa-miR-4482-3p, hsa-miR-146a-3p, hsa_circ_0008167, and hsa_circ_0003317 were dysregulated in NSCLC. The combination of the four ncRNAs showed the highest diagnostic value to discriminate between benign lung tumors and NSCLC. Additionally, the upregulated levels of hsa_circ_0008167 were correlated to more aggressive features of NSCLC, such as lymph node metastasis, distant metastasis, and higher stage. Furthermore, the combination of hsa_circ_0008167 + hsa-miR-4482-3p, and hsa_circ_0008167 + hsa-miR-4482-3p + hsa-miR-146a-3p had the greatest diagnostic power to differentiate between lymph node +/- metastases and higher/lower stages, respectively, compared to circRNAs or miRNAs alone, and traditional tumor markers. In conclusion, we identified a specific circRNA-miRNA network with higher sensitivity and specificity to diagnose NSCLC, thereby providing a new strategy for further development of ceRNA-related tumor markers in other cancers. KEY MESSAGES: Serum miR-4482-3p, miR-146a-3p, circ_0008167 and circ_0003317 are dysregulated in NSCLC. Higher levels of serum circ_0008167 are associated with more malignant NSCLC. Multiple combinations of circRNAs and miRNAs show higher value to diagnose NSCLC.

Systematic Analysis of the Expression Profile and Prognostic Significance of the IGF2BP Family in Lung Adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD)，the most common type of lung cancer associated with poor prognosis, has become a major health problem for human health. IGF2BPs are types of N6-methyladenosine reader proteins, comprising IGF2BP1, IGF2BP2, and IGF2BP3, that promote LUAD progression. However, the expression profiles and prognostic value of IGF2BPs in LUAD remain unclear.

OBJECTIVE

To analyze the expression profiles and prognostic significance of the IGF2BP family in lung adenocarcinoma.

METHODS

In our study, we utilized LUAD patient and normal or para-carcinoma tissue data from TCGA database and the GTEx project. Using survival analysis, Kaplan-Meier curves, and Cox proportional hazards model, we analyzed the expression profiles and prognostic significance of the IGF2BP family.

RESULTS

Patients with high expression levels of IGF2BPs showed significant association with poor overall survival (p < 0.05). Moreover, the somatic mutation rates of IGF2BP1, IGF2BP2, IGF2BP3 were determined as 2.65, 1.59, and 1.76%, respectively, by investigating the genetic mutation. In addition, there were significant associations between TMB and IGF2BP family expression profiles, which positively correlated with the expression of PD-1 (p < 0.05). Cox proportional hazard model for LUAD showed the risk score for IGF2BP1, p-TNM stage, and so forth, all independent prognostic indicators for LUAD patients. Finally, the co-expression genes were obtained to build a PPI network and analyze the hub genes of the IGF2BP family.

CONCLUSION

Our study provides further insights into the role of the IGF2BP family in LUAD and identifies 10 genes that may be associated with IGF2BPs in LUAD patients.

Development of a novel embryonic germline gene-related prognostic model of lung adenocarcinoma

BACKGROUND

Emerging evidence implicates the correlation of embryonic germline genes with the tumor progress and patient's outcome. However, the prognostic value of these genes in lung adenocarcinoma (LUAD) has not been fully studied. Here we systematically evaluated this issue, and constructed a novel signature and a nomogram associated with embryonic germline genes for predicting the outcomes of lung adenocarcinoma.

METHODS

The LUAD cohorts retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were used as training set and testing set, respectively. The embryonic germline genes were downloaded from the website https://venn.lodder.dev. Then, the differentially expressed embryonic germline genes (DEGGs) between the tumor and normal samples were identified by limma package. The functional enrichment and pathway analyses were also performed by clusterProfiler package. The prognostic model was constructed by the least absolute shrinkage and selection operator (LASSO)-Cox regression method. Survival and Receiver Operating Characteristic (ROC) analyses were performed to validate the model using training set and four testing GEO datasets. Finally, a prognostic nomogram based on the signature genes was constructed using multivariate regression method.

RESULTS

Among the identified 269 DEGGs, 249 were up-regulated and 20 were down-regulated. GO and KEGG analyses revealed that these DEGGs were mainly enriched in the process of cell proliferation and DNA damage repair. Then, 103 DEGGs with prognostic value were identified by univariate Cox regression and further filtered by LASSO method. The resulting sixteen DEGGs were included in step multivariate Cox regression and an eleven embryonic germline gene related signature (EGRS) was constructed. The model could robustly stratify the LUAD patients into high-risk and low-risk groups in both training and testing sets, and low-risk patients had much better outcomes. The multi-ROC analysis also showed that the EGRS model had the best predictive efficacy compared with other common clinicopathological factors. The EGRS model also showed robust predictive ability in four independent external datasets, and the area under curve (AUC) was 0.726 (GSE30219), 0.764 (GSE50081), 0.657 (GSE37745) and 0.668 (GSE72094). More importantly, the expression level of some genes in EGRS has a significant correlation with the progression of LUAD clinicopathology, suggesting these genes might play an important role in the progression of LUAD. Finally, based on EGRS genes, we built and calibrated a nomogram for conveniently evaluating patients' outcomes.

Integrated Analysis of a Competing Endogenous RNA Network Reveals a Prognostic Signature in Kidney Renal Papillary Cell Carcinoma

The kidney renal papillary cell carcinoma (KIRP) is a relatively rare type of renal cell carcinoma (RCC). Currently, most kidney cancer studies primarily focus on RCC, and there has been no investigation to find a robust signature to predict the survival outcome of KIRP patients. In this study, we constructed a competing endogenous RNA (ceRNA) network, including 1,251 lncRNA-miRNA-mRNA interactions. Eight differentially expressed genes (IGF2BP3, PLK1, LINC00200, NCAPG, CENPF, miR-217, GAS6-As1, and LRRC4) based on the TCGA database were selected. The prognostic signature was established by combining the univariate Cox regression method and a stepwise regression method, with its predictive value validated by time-dependent receiver operating characteristic (ROC) curves. In conclusion, we identified eight prognostic signatures with using ceRNA networks. Our study provided a global view and a systematic dissection on KIRP prognosis biomarkers, and the eight identified genes might be used as new and important prognostic factors involved in KIRP pathogenesis.

Construction and Characterization of a Synergistic lncRNA-miRNA Network Reveals a Crucial and Prognostic Role of lncRNAs in Colon Cancer

Non-coding RNAs such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been found to be indispensable factors in carcinogenesis and cancer development. Numerous studies have explored the regulatory functions of these molecules and identified the synergistic interactions among lncRNAs or miRNAs, while those between lncRNAs and miRNAs remain to be investigated. In this study, we constructed and characterized an lncRNA–miRNA synergistic network following a four-step approach by integrating the regulatory pairs and expression profiles. The synergistic interactions with more shared regulatory mRNAs were found to have higher interactional intensity. Through the analysis of nodes in the network, we found that lncRNAs played roles that are more central and had similar synergistic interactions with their neighbors when compared with miRNAs. In addition, known colon adenocarcinoma (COAD)-related RNAs were found to be enriched in this synergistic network, with higher degrees, betweenness, and closeness. Finally, we proposed a risk score model to predict the clinical outcome for COAD patients based on two prognostic hub lncRNAs, MEG3 and ZEB1-AS1. Moreover, the hierarchical networks of these two lncRNAs could contribute to the understanding of the biological mechanism of tumorigenesis. For each lncRNA–miRNA interaction in the hub-related subnetwork and two hierarchical networks, we performed RNAup method to evaluate their binding energy. Our results identified two important lncRNAs with prognostic roles in colon cancer and dissected their regulatory mechanism involving synergistic interaction with miRNAs.