The construction of a novel ferroptosis-related lncRNA model to predict prognosis in colorectal cancer patients

Identification of a PANoptosis-related long noncoding rna risk signature for prognosis and immunology in colon adenocarcinoma

BACKGROUND

PANoptosis, a complex programmed cell death (PCD) pathway that includes apoptosis, pyroptosis and necroptosis, is significantly involved in the progression of cancers. Long noncoding RNAs (lncRNAs) play crucial roles in PCD. However, the predictive value of PANoptosis-related lncRNAs (PRlncRNAs) for colon adenocarcinoma (COAD) has not been established.

METHODS

Gene expression data and clinical characteristics of patients with COAD were obtained from The Cancer Genome Atlas database. Differential expression analysis and Pearson correlation analysis were used to identify PRlncRNAs. In addition to least absolute shrinkage and selection operator, univariate and multivariate Cox regression analyses were employed to obtain PRlncRNAs for constructing a risk signature. Patients with COAD in the training set, testing set and entire set were stratified into high- and low-risk groups for further comparison of survival prognosis, using the median risk score as the cut-off point. Time-dependent receiver operating characteristic curves, a nomogram and multivariate Cox regression analysis were conducted to validate the risk signature in the testing set and the entire set. In addition, critical pathways, immune infiltration cells, immune checkpoint-related genes, Tumor Immune Dysfunction and Exclusion (TIDE) scores and antitumour drugs were compared between the two risk groups in the entire set. Correlations between ferroptosis, cuproptosis, disulfidptosis and the PRlncRNA risk score were evaluated. Finally, a competitive endogenous RNA (ceRNA) network was established, and enrichment analysis of the predicted mRNAs was performed using Gene Ontology (GO) analysis. The Kaplan-Meier plotter database was used as an external database to confirm the accuracy of the risk signature in predicting patient prognosis. Additionally, small interfering RNA (siRNA), a cell counting kit- 8 assay, a cell colony formation assay, quantitative polymerase chain reaction (qPCR) and an apoptosis assay were further employed to investigate the roles of AP003555.1 in colon cancer.

RESULTS

A risk signature comprising four PRlncRNAs (LINC01133, FOXD3-AS1, AP001066.1, and AP003555.1) was developed to predict the prognosis of patients with COAD. Kaplan‒Meier curves demonstrated significant differences in prognosis between the high- and low-risk groups across the three sets. Multivariate Cox regression analysis confirmed that the risk signature was an independent prognostic factor across the three sets. A nomogram, receiver operating characteristic curves and calibration curves indicated strong confidence in the risk signature. Using the CIBERSORT algorithm and gene set enrichment analysis, variations in infiltrating immune cells and immune processes were observed between the two risk groups. Furthermore, TIDE algorithm suggested that the high-risk group exhibited a lower risk of immunotherapy escape and better immunotherapy outcomes than the low-risk group. Distinct responses to various antitumour drugs were observed between the two risk groups. Additionally, we constructed a ceRNA network based on PRlncRNAs, and GO enrichment analysis of the predicted mRNAs revealed different functions. In addition, the results of the Kaplan‒Meier plotter database revealed that patients who exhibited high levels of LINC01133 and FOXD3-AS1 experienced significantly shorter overall survival than those with low levels of these lncRNAs. Specifically, in terms of functionality, AP003555.1 was found to be highly expressed in colon cancer tissue and promoted viability and proliferation while suppressing the apoptosis of colon cancer cells.

CONCLUSION

We identified a novel risk signature consisting of four PRlncRNAs, which is an independent prognostic indicator for patients with COAD. This PRlncRNA risk signature is potentially relevant for immunotherapy and could serve as a therapeutic target for COAD.

Enhancing Colorectal Cancer Immunotherapy: The Pivotal Role of Ferroptosis in Modulating the Tumor Microenvironment

Colorectal cancer (CRC) represents a significant challenge in oncology, with increasing incidence and mortality rates worldwide, particularly among younger adults. Despite advancements in treatment modalities, the urgent need for more effective therapies persists. Immunotherapy has emerged as a beacon of hope, offering the potential for improved outcomes and quality of life. This review delves into the critical interplay between ferroptosis, an iron-dependent form of regulated cell death, and immunotherapy within the CRC context. Ferroptosis's influence extends beyond tumor cell fate, reshaping the tumor microenvironment (TME) to enhance immunotherapy's efficacy. Investigations into Ferroptosis-related Genes (OFRGs) reveal their pivotal role in modulating immune cell infiltration and TME composition, closely correlating with tumor responsiveness to immunotherapy. The integration of ferroptosis inducers with immunotherapeutic strategies, particularly through novel approaches like ferrotherapy and targeted co-delivery systems, showcases promising avenues for augmenting treatment efficacy. Furthermore, the expression patterns of OFRGs offer novel prognostic tools, potentially guiding personalized and precision therapy in CRC. This review underscores the emerging paradigm of leveraging ferroptosis to bolster immunotherapy's impact, highlighting the need for further research to translate these insights into clinical advancements. Through a deeper understanding of the ferroptosis-immunotherapy nexus, new therapeutic strategies can be developed, promising enhanced efficacy and broader applicability in CRC treatment, ultimately improving patient outcomes and quality of life in the face of this formidable disease.

Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer

OBJECTIVE

Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs).

METHODS

In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR).

RESULTS

Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m6A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated.

CONCLUSION

Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.

The roles of lncRNA AP001469.3 in clinical implications, immune landscape and carcinogenesis of colorectal cancer

Background

Previously, long non-coding RNA (lncRNA) gene AP001469.3 was reported to participate in the construction of an immune-related lncRNA signature, which showed promising clinical predictive value in colorectal cancer (CRC) patients. However, the clinical and immunological significance and biological function of AP001469.3 in CRC remain unclear. In this study, we aim to explore the roles of AP001469.3 in CRC progression, thereby opening an avenue for CRC treatment.

Methods

Our study collected data from The Cancer Genome Atlas (TCGA) database and investigated the role of AP001469.3 in CRC through bioinformatics analysis. Cell-type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) methods evaluated the immune infiltration. The biological functions of AP001469.3 in CRC were validated by in vitro experiments. Gene set enrichment analysis (GSEA) was used to estimate the enrichment of functional pathways and gene signatures.

Results

In this work, high expression of AP001469.3 was found in CRC and was positively associated with tumor-node-metastasis (TNM) stage in CRC. AP001469.3 expression had a strong relationship with microsatellite instability (MSI) in colon adenocarcinoma (COAD). Additionally, AP001469.3 expression was associated with StromalScore, ImmuneScore, ESTIMATEScore, immune cell infiltration (ICI) levels and immune checkpoint (ICP) genes expression in CRC. Subsequent results showed that immunotherapy could be more effective in CRC patients with low-AP001469.3 expression using the immunophenoscore (IPS). We confirmed that the transcript of AP001469.3 gene ENST00000430259 was highly expressed in CRC tissues and cell lines. In vitro experiments indicated that ENST00000430259 knockdown reduced the proliferation, migration and invasion of CRC cells. Finally, our GSEA results showed that the majority of the differentially enriched signaling pathways between the high- and low-AP001469.3 expression groups were immune-related.

Conclusions

Taken together, our study demonstrates that lncRNA gene AP001469.3 is associated with immunological characteristics in CRC and promotes malignant progression of CRC. Moreover, AP001469.3 can be potentially used as an immunotherapeutic indicator and a therapeutic target for CRC patients.

Identification of prognostic RNA editing profiles for clear cell renal carcinoma

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer and currently lacks effective biomarkers. This research aims to analyze and identify RNA editing profile associated with ccRCC prognosis through bioinformatics and in vitro experiments.

Methods

Transcriptome data and clinical information for ccRCC were retrieved from the TCGA database, and RNA editing files were obtained from the Synapse database. Prognostic models were screened, developed, and assessed using consistency index analysis and independent prognostic analysis, etc. Internal validation models were also constructed for further evaluation. Differential genes were investigated using GO, KEGG, and GSEA enrichment analyses. Furthermore, qPCR was performed to determine gene expression in human renal tubular epithelial cells HK-2 and ccRCC cells A-498, 786-O, and Caki-2.

Results

An RNA editing-based risk score, that effectively distinguishes between high and low-risk populations, has been identified. It includes CHD3| chr17:7815229, MYO19| chr17:34853704, OIP5-AS1| chr15:41590962, MRI1| chr19:13883962, GBP4| chr1:89649327, APOL1| chr22:36662830, FCF1| chr14:75203040 edited sites or genes and could serve as an independent prognostic factor for ccRCC patients. qPCR results showed significant up-regulation of CHD3, MYO19, MRI1, APOL1, and FCF1 in A-498, 786-O, and Caki-2 cells, while the expression of OIP5-AS1 and GBP4 was significantly down-regulated.

Conclusion

RNA editing site-based prognostic models are valuable in differentiating between high and low-risk populations. The seven identified RNA editing sites may be utilized as potential biomarkers for ccRCC.

High expression of NXPH4 correlates with poor prognosis, metabolic reprogramming, and immune infiltration in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a prevalent gastrointestinal malignant disease with high mortality rate, and identification of novel prognostic biomarkers and therapeutic targets is urgently needed. Although neurexophilin 4 (NXPH4) has been investigated in several tumors, its role in COAD remains unclear. The aim of this study was to explore the prognostic value and potential functions of NXPH4 in COAD.

Methods

The expression of NXPH4 in COAD were analyzed using The Cancer Genome Atlas (TCGA) and datasets from the Gene Expression Omnibus (GEO) database. The prognostic value of NXPH4 was determined using Kaplan-Meier analysis and Cox regression analysis. To investigate the possible mechanism underlying the role of NXPH4 in COAD, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were employed. The correlation between NXPH4 expression and immune cell infiltration levels was examined thorough single-sample gene set enrichment analysis (ssGSEA). Furthermore, the competing endogenous RNA (ceRNA) regulatory network that may be involved in NXPH4 in COAD was predicted and constructed through a variety of databases.

Results

NXPH4 expression was significantly higher in COAD tissue compared with normal colon tissues. Meanwhile, high expression of NXPH4 was associated with poor prognosis in COAD patients. GO-KEGG and GSEA analyses indicated that NXPH4 was associated with glycolysis and hypoxia pathway, and may promote COAD progression and metastasis by modulating metabolic reprogramming. ssGSEA analysis demonstrated that NXPH4 expression also associated with immune infiltration. Furthermore, we identified various microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) as upstream regulators of NXPH4 in COAD.

Conclusions

The present study revealed that high expression of NXPH4 is associated with tumor progression, metabolic reprogramming, and immune infiltration. These findings suggest that NXPH4 could serve as a reliable prognostic biomarker and a promising therapeutic target in COAD.

Drugs associated with a risk of supraventricular tachycardia: analysis using the OpenVigil database

OBJECTIVE

The OpenVigil database can be used to assess medications that may cause supraventricular tachycardia (SVT) and to produce a reference for their safe use in clinical settings.

METHODS

We analyzed first-quarter data from 2004 to 2023, obtained by searching the OpenVigil database using the keyword "supraventricular tachycardia." Trade names and generic names were obtained by querying the RxNav database, and the proportions were summarized. The proportionate reporting ratio (PRR), reporting odds ratio, and chi-square values were also summarized. We created Asahi diagrams and set the screening criteria to drug events ≥30, PRR >2, and chi-square >4. Outcomes were evaluated using the Side Effect Resource database, several scientific literature databases, and the Hangzhou Yiyao Rational Medication System.

RESULTS

A total of 2435 distinct medications were found to induce SVT between the first quarter of 2004 and 2023, leading to 22,375 documented adverse events related to SVT. Further investigation revealed that salbutamol, paroxetine, formoterol, paclitaxel, venlafaxine, and theophylline were most likely to cause SVT.

CONCLUSION

We conducted signal mining of adverse drug events using the OpenVigil database and evaluated the six drugs most likely to cause SVT. The results of this research can serve as a drug safety reference in the clinic.