Identification of Hypoxia-Related Prognostic Signature and Competing Endogenous RNA Regulatory Axes in Hepatocellular Carcinoma

Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia

The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

LINK-A: unveiling its functional role and clinical significance in human tumors

LINK-A, also recognized as LINC01139, has emerged as a key oncological lncRNA in cancer. LINK-A is upregulated in solid and liquid tumor samples, including breast cancer, ovarian cancer, glioma, non-small-cell lung cancer, and mantle cell lymphoma. Notably, LINK-A is involved in regulating critical cancer-related pathways, such as AKT and HIF1α signaling, and is implicated in a range of oncogenic activities, including cell proliferation, apoptosis, epithelial-mesenchymal transition (EMT), cell invasion and migration, and glycolysis reprogramming. LINK-A's differential expression and its correlation with clinical features enable it to be a promising biomarker for cancer diagnosis, prognosis, and the stratification of tumor progression. Additionally, LINK-A's contribution to the development of resistance to cancer therapies, including AKT inhibitors and immunotherapy, underscores its potential as a therapeutic target. This review provides a comprehensive overview of the available data on LINK-A, focusing on its molecular regulatory pathways and clinical significance. By exploring the multifaceted nature of LINK-A in cancer, the review aims to offer a valuable resource for future research directions, potentially guiding the development of novel therapeutic strategies targeting this lncRNA in cancer treatment.

Prognostic Signature Constructed of Seven Ferroptosis-Related lncRNAs Predicts the Prognosis of HBV-Related HCC

BACKGROUND

Ferroptosis and lncRNAs both play crucial roles in cancers. But the roles of ferroptosis-related lncRNAs (FRLncs) in HBV-related HCC (HBV-HCC) remain ambiguous.

METHODS

The gene expression profile and clinical data were originated from the Cancer Genome Atlas (TCGA) database. The risk signature was constructed by FRLncs based on the Cox regression analysis. The survival curve, Cox regression analysis, and time-dependent receiver operating characteristic (ROC) curve were adopted to verify the independence and reliability of the signature. A nomogram was established. Immune-infiltrating cells, immune functions, and checkpoints were analyzed.

RESULTS

A risk signature composed of 7 FRLncs (LINC00942, AC131009.1, POLH-AS1, AC090772.3, MKLN1-AS, AC009403.1, AL031985.3) was constructed and divided HBV-HCC patients into high- and low-risk groups. Patients in the high-risk group showed a poor prognosis. The area under curves (AUC) of the signature for 1-, 3-, and 5-year was satisfactory. A nomogram composed of gender, stage, age, grade, and risk signature was established. The risk signature and nomogram displayed appreciable independence and reliability in HBV-HCC patients. The T-cell CD8 + , monocyte, and macrophage M1 were expressed differently significantly in HCC patients, while macrophage M2 showed an obvious difference in the HBV-HCC patients between the different risk groups. PDCD1 and CTL4 were expressed higher in the high-risk group of HCC patients.

CONCLUSION

A 7-lncRNA signature was identified as a potential prognostic predictor for HBV-HCC patients. Immune therapy may be a promising strategy for HCC patients, especially HBV-HCC patients.

ENO2 promotes anoikis resistance in anaplastic thyroid cancer by maintaining redox homeostasis

Background

Anoikis presents a significant barrier in the metastasis of cancer. As the most aggressive type of thyroid cancer, anaplastic thyroid cancer (ATC) exhibits a high risk of metastasis and is characterized by high mortality. Therefore, investigating the molecular mechanisms of anoikis resistance in ATC is important for devising therapeutic targets in clinical research.

Methods

Differentially Expressed Genes were screened in ATC cells under attached and detached culture conditions with RNA-seq. Investigate the impact of enolase 2 (ENO2) on apoptosis and spheroid formation by gain and loss of function. Changes of reactive oxygen species (ROS), glutathione (GSH) and nicotinamide adenine dinucleotide phosphate (NADPH) were detected to assess redox balance. The transcriptional regulatory role of signal transducer and activator of transcription 1 (STAT1) on ENO2 was validated through Dual-Luciferase Reporter Gene Assay. Explore the impact of ENO2 expression on the formation of lung metastases in nude mice.

Results

We found that the glycolysis process was activated in detached ATC cells. Several genes in the glycolysis process, particularly ENO2, a member of the enolase superfamily was upregulated in ATC cells cultured in suspension. The upregulation of ENO2 enabled the maintenance of redox balance by supplying GSH and NADPH, thereby preventing cells from undergoing anoikis. In terms of mechanism, the expression of STAT1 was enhanced in anoikis resistance cells, which in turn positively regulated the expression of ENO2. In vivo, ENO2-suppressed ATC cells resulted in a significantly lower rate of lung colonization compared to control ATC cells.

Conclusions

Stable expression of ENO2 and the maintenance of redox balance played a pivotal role in facilitating anoikis resistance of ATC.

Prognostic value and immune landscapes of immunogenic cell death-related lncRNAs in hepatocellular carcinoma

BACKGROUND

Both immunogenic cell death (ICD) and long noncoding RNAs (lncRNAs) are strongly associated with tumor development, but the mechanism of action of ICD-associated lncRNAs in hepatocellular carcinoma (HCC) remains unclear.

METHODS

We collected data from 365 HCC patients from The Cancer Genome Atlas (TCGA) database. We formulated a prognostic signature of ICD-associated lncRNAs and a nomogram to predict prognosis. To explore the potential mechanisms and provide clinical guidance, survival analysis, enrichment analysis, tumor microenvironment analysis, tumor mutation burden (TMB), and drug sensitivity prediction were conducted based on the subgroups obtained from the risk score.

RESULTS

A prognostic signature of seven ICD-associated lncRNAs was constructed. Kaplan-Meier (K-M) survival curves showed a more unfavorable outcome in high-risk patients. The nomogram had a higher predictive value than the nomogram constructed without the risk model. Enrichment analysis confirmed that risk lncRNAs were closely associated with cell proliferation and mitosis. Most of the immune checkpoints currently used in therapy (e.g., PDCD1 and CTLA4) appeared to be elevated in high-risk patients. Tumor microenvironment analysis showed differential expression of lymphocytes (including natural killer cells, regulatory T cells, etc.) in the high-risk group. TMB had a higher incidence of mutations in the high-risk group (P=0.004). Chemotherapy drug sensitivity prediction provides effective guidelines for individual therapy. RT-qPCR of human HCC tissues verified the accuracy of the model.

CONCLUSION

We constructed an effective prognostic signature for patients with HCC using seven ICD-lncRNAs, which provides guidance for the prognostic assessment and personalized treatment of patients.

Construction and validation of a novel IGFBP3-related signature to predict prognosis and therapeutic decision making for Hepatocellular Carcinoma

Background

IGFBP3 plays a pivotal role in carcinogenesis by being anomalously expressed in some malignancies. However, the clinical value of IGFBP3 and the role of IGFBP3-related signature in HCC remain unclear.

Methods

Multiple bioinformatics methods were used to determine the expression and diagnostic values of IGFBP3. The expression level of IGFBP3 was validated by RT-qPCR and IHC. A IGFBP3-related risk score (IGRS) was built via correlation analysis and LASSO Cox regression analysis. Further analyses, including functional enrichment, immune status of risk groups were analyzed, and the role of IGRS in guiding clinical treatment was also evaluated.

Results

IGFBP3 expression was significantly downregulated in HCC. IGFBP3 expression correlated with multiple clinicopathological characteristics and demonstrated a powerful diagnostic capability for HCC. In addition, a novel IGRS signature was developed in TCGA, which exhibited good performance for prognosis prediction and its role was further validated in GSE14520. In TCGA and GSE14520, Cox analysis also confirmed that the IGRS could serve as an independent prognostic factor for HCC. Moreover, a nomogram with good accuracy for predicting the survival of HCC was further formulated. Additionally, enrichment analysis showed that the high-IGRS group was enriched in cancer-related pathways and immune-related pathways. Additionally, patients with high IGRS exhibited an immunosuppressive phenotype. Therefore, patients with low IGRS scores may benefit from immunotherapy.

Conclusions

IGFBP3 can act as a new diagnostic factor for HCC. IGRS signature represents a valuable predictive tool in the prognosis prediction and therapeutic decision making for Hepatocellular Carcinoma.