Expression and Function of C1orf132 Long-Noncoding RNA in Breast Cancer Cell Lines and Tissues

Integration of transcriptional and epigenetic regulation of TFEB reveals its dual functional roles in Pan-cancer

Transcription factor EB (TFEB) mainly regulates the autophagy-lysosomal pathway, associated with many diseases, including cancer. However, the role of TFEB in pan-cancer has not been investigated systematically. In this study, we comprehensively analyzed TFEB targets under three stresses in Hela cells by cross-validation of RNA-seq and ChIP-seq. 1712 novel TFEB targets have not been reported in the Gene Set Enrichment Analysis and ChIP Enrichment Analysis databases. We further investigated their distributions and roles among the pan-cancer co-expression networks across 32 cancers constructed by multiscale embedded gene co-expression network analysis (MEGENA) based on the Cancer Genome Atlas (TCGA) cohort. Specifically, TFEB might serve as a hidden player with multifaceted functions in regulating pan-cancer risk factors, e.g. CXCL2, PKMYT1 and BUB1, associated with cell cycle and immunosuppression. TFEB might also regulate protective factors, e.g. CD79A, related to immune promotion in the tumor microenvironment. We further developed a Shiny app website to present the comprehensive regulatory targets of TFEB under various stimuli, intending to support further research on TFEB functions. Summarily, we provided references for the TFEB downstream targets responding to three stresses and the dual roles of TFEB and its targets in pan-cancer, which are promising anticancer targets that warrant further exploration.

Construction of a cell cycle-specific lncRNA-miRNA-mRNA network reveals novel key lncRNAs in colorectal cancer

OBJECTIVE

The current study aimed to determine the roles of pivotal and novel lncRNAs associated with the cell cycle in the occurrence and development of Colorectal cancer (CRC).

METHODS

The TCGA-COAD project related to CRC was downloaded, and differential expression analysis was performed to identify differentially expressed lncRNAs, miRNAs, and mRNAs. A cell cycle-associated lncRNA-miRNA-mRNA regulatory network was constructed, and two novel lncRNAs were selected. Two subnetworks were constructed for selected lncRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were illustrated for the genes in each sub-network. qPCR analysis was used to validate the expression levels of the selected lncRNAs in CRC tissues compared to those adjacent normal tissues.

RESULTS

The differential expression analysis identified 416 lncRNAs, 317 miRNAs, and 117 mRNAs. The ceRNA subnetwork genes were associated with different pathways, including cellular senescence, DNA replication, human T-cell leukemia virus 1 infection, and oocyte meiosis. The bioinformatic results based on the TCGA project indicated the dysregulation of two novel lncRNAs, MIR29B2CHG and HELLPAR, in CRC tissues compared to adjacent normal tissues. Moreover, qPCR confirmed the dysregulation of lncRNAs in the CRC tissues. ROC curves revealed that both selected lncRNAs had acceptable specificity and sensitivity as biomarkers.

CONCLUSION

In conclusion, novel cell cycle-associated lncRNAs have the potential to be understood as the underlying molecular mechanisms that influence CRC. Therefore, these lncRNAs can be considered as promising biomarkers for the diagnosis and treatment of CRC.

A Comprehensive Bioinformatic Analysis Identifies a Tumor Suppressor Landscape of the MEG3 lncRNA in Breast Cancer

Breast cancer (BC) is the leading cause of cancer mortality in women and a major risk to world health. Therefore, effective strategies are required for prompt diagnosis and treatment. Nowadays, non-coding RNAs (ncRNAs), particularly long ncRNAs (lncRNAs), have assumed a significant role in the prognosis and diagnosis of diseases, including cancer. In the present study, surveying the bioinformatic tools, including the lncRNADisease v2.0, OncoDB, InteractiVenn, GEPIA, RAID, COXPRESdb, DAVID v6.8, GEO2R, and LncSEA, we proposed the Maternally Expressed Gene (MEG3) as a potential biomarker in BC. This lncRNA significantly downregulates in BC and is associated with tumor size, metastasis, and pathological stage. MEG3 expression is downregulated in several types of primary human cancers and tumor cell lines, which raises the possibility that it could act as a tumor suppressor. The results suggest that MEG3 may play a crucial role in fundamental pathways, including apoptosis, and interact with essential genes and proteins such as P53. It may also be associated with the prognosis, proliferation, migration, invasion, and metastasis of BC.

Identification of regulatory genes associated with POAG by integrating expression and sequencing data

BACKGROUND

Primary open-angle glaucoma (POAG) is a subtype of glaucoma that accounts for 60%~70% of all cases. Its pathogenic mechanism is intricate and its pathogenic process is concealed. Numerous significant biological processes associated with POAG continue to be elucidated.

METHODS

In this study, by exploring the expression data of POAG tissues and normal tissues, we mined the regulatory lncRNAs and mRNAs closely associated with the pathogenesis and progression of POAG by exploring a regulatory network of competing endogenous RNA (ceRNA), established by integrating gene expression data with the known lncRNA-miRNA and miRNA-mRNA-regulatory interactions. The key regulatory pathways and regulatory elements of POAG were identified by topological analysis. Simultaneously, the exome data of 28 cases with POAG and healthy controls were analyzed to identify high-frequency mutations and genes.

RESULTS

A total of 2712 differentially expressed genes were identified, including 1828 mRNAs and 884 lncRNAs. Network analysis suggested that lncRNAs such as HAGLR, HOTAIR and MIR29B2CHG, and mRNAs such as PPP6R3, BMPR2 and CFL2, may be involved in the onset and progression of POAG. In addition, 55 mutations with potential pathogenicity were identified.

CONCLUSION

These genes and mutations provide novel potential genetic heterogeneity and genetic susceptibility of POAG, as well as fresh suggestions for elucidating the molecular mechanism underlying the pathogenesis of POAG.

miRNAs as Interconnectors between Obesity and Cancer

Obesity and cancer are a concern of global interest. It is proven that obesity may trigger the development or progression of some types of cancer; however, the connection by non-coding RNAs has not been totally explored. In the present review, we discuss miRNAs and lncRNAs dysregulation involved in obesity and some cancers, shedding light on how these conditions may exacerbate one another through the dysregulation of ncRNAs. lncRNAs have been reported as regulating microRNAs. An in silico investigation of lncRNA and miRNA interplay is presented. Our investigation revealed 44 upregulated and 49 downregulated lncRNAs in obesity and cancer, respectively. miR-375, miR-494-3p, miR-1908, and miR-196 were found interacting with 1, 4, 4 and 4 lncRNAs, respectively, which are involved in PPARγ cell signaling regulation. Additionally, miR-130 was found to be downregulated in obesity and reported as modulating 5 lncRNAs controlling PPARγ cell signaling. Similarly, miR-128-3p and miR-143 were found to be downregulated in obesity and cancer, interacting with 5 and 4 lncRNAs, respectively, associated with MAPK cell signaling modulation. The delicate balance between miRNA and lncRNA expression emerges as a critical determinant in the development of obesity-associated cancers, presenting these molecules as promising biomarkers. However, additional and deeper studies are needed to reach solid conclusions about obesity and cancer connection by ncRNAs.

UTRN as a potential biomarker in breast cancer: a comprehensive bioinformatics and in vitro study

Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer's development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN's pivotal role in tamoxifen resistance. Furthermore, the Kruskal-Wallis rank test indicated UTRN's potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN's close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN's role in breast cancer's prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

Evaluation of lncRNA Expression Pattern and Potential Role in Heart Failure Pathology

During the last few decades, the morbidity and mortality of heart failure (HF) have remained on an upward trend. Despite the advances in therapeutic and diagnostic measures, there are still many aspects requiring further research. This study is aimed at finding potential long noncoding RNAs (lncRNAs) that could aid with the diagnosis and treatment of HF. We performed RNA sequencing on the peripheral blood of healthy controls as well as HF patients. The expression of lncRNAs was validated by RT-qPCR. Bioinformatic analysis was performed to investigate the possible mechanism of differentially expressed lncRNAs and mRNAs. The diagnostic value of lncRNAs was analysed by ROC analysis. Finally, a total of 207 mRNAs and 422 lncRNAs were identified. GO and KEGG pathway analyses revealed that biological pathways such as immune response, regulation of cell membrane, and transcriptional regulatory process were associated with the pathological progress of HF. The lncRNA-mRNA coexpression network was conducted, and several mRNAs were identified as key potential pathological targets, while lncRNA CHST11, MIR29B2CHG, CR381653.1, and FP236383.2 presented a potential diagnostic value for HF. These findings provide novel insights for the underlying mechanisms and possible therapeutic targets for HF.

Identification of COL1A1/2 Mutations and Fusions With Noncoding RNA Genes in Bizarre Parosteal Osteochondromatous Proliferation (Nora Lesion)

Bizarre parosteal osteochondromatous proliferation (BPOP) (Nora lesion) is a benign bone surface lesion, which most commonly occurs in the digits of young patients and has a high rate of recurrence. Histologically, it is composed of a mixture of disorganized bone, cartilage, and spindle cells in variable proportions and characterized by amorphous "blue bone" mineralization. Recurrent chromosomal abnormalities, including t(1;17)(q32-42;q21-23) and inv(7)(q21.1-22q31.3-32), have been reported in BPOP. However, the exact genes involved in the rearrangements remain unknown. In this study, we analyzed 8 BPOP cases affecting the fingers, toe, ulna, radius, and fibula of 5 female and 3 male patients, aged 5 to 68 years. RNA sequencing of 5 cases identified genetic fusions between COL1A2 and LINC-PINT in 3 cases and COL1A1::MIR29B2CHG fusion in 1, both validated using fluorescence in situ hybridization and reverse transcription (RT)-PCR. The remaining fusion-negative case harbored 3 COL1A1 mutations as revealed by whole-exome sequencing and confirmed using Sanger sequencing. All these genetic alterations were predicted to cause frameshift and/or truncation of COL1A1/2. The chromosomal locations of COL1A2 (7q21.3), LINC-PINT (7q32.3), COL1A1 (17q21.33), and MIR29B2CHG (1q32.2) were consistent with the breakpoints identified in the previous cytogenetic studies. Subsequent screening of 3 BPOPs using fluorescence in situ hybridization identified 1 additional case each with COL1A1 or COL1A2 rearrangement. Our findings are consistent with reported chromosomal abnormalities and implicate the disruption of type I collagen, and perhaps of either noncoding RNA gene as a tumor suppressor, in the tumorigenesis of BPOP. The prevalence and tumorigenic mechanisms of these COL1A1/2 alterations in BPOP require further investigation.

Nanomaterial-assisted CRISPR gene-engineering - A hallmark for triple-negative breast cancer therapeutics advancement

Triple-negative breast cancer (TNBC) is the most violent class of tumor and accounts for 20-24% of total breast carcinoma, in which frequently rare mutation occurs in high frequency. The poor prognosis, recurrence, and metastasis in the brain, heart, liver and lungs decline the lifespan of patients by about 21 months, emphasizing the need for advanced treatment. Recently, the adaptive immunity mechanism of archaea and bacteria, called clustered regularly interspaced short palindromic repeats (CRISPR) combined with nanotechnology, has been utilized as a potent gene manipulating tool with an extensive clinical application in cancer genomics due to its easeful usage and cost-effectiveness. However, CRISPR/Cas are arguably the efficient technology that can be made efficient via organic material-assisted approaches. Despite the efficacy of the CRISPR/Cas@nano complex, problems regarding successful delivery, biodegradability, and toxicity remain to render its medical implications. Therefore, this review is different in focus from past reviews by (i) detailing all possible genetic mechanisms of TNBC occurrence; (ii) available treatments and gene therapies for TNBC; (iii) overview of the delivery system and utilization of CRISPR-nano complex in TNBC, and (iv) recent advances and related toxicity of CRISPR-nano complex towards clinical trials for TNBC.

Construction of ceRNA Networks Associated With CD8 T Cells in Breast Cancer

Background

The infiltration of CD8 T cells is usually linked to a favorable prognosis and may predict the therapeutic response of breast cancer patients to immunotherapy. The purpose of this research is to investigate the competing endogenous RNA (ceRNA) network correlated with the infiltration of CD8 T cells.

Methods

Based on expression profiles, CD8 T cell abundances for each breast cancer (BC) patient were inferred using the bioinformatic method by immune markers and expression profiles. We were able to extract the differentially expressed RNAs (DEmRNAs, DEmiRNAs, and DElncRNAs) between low and high CD8 T-cell samples. The ceRNA network was constructed using Cytoscape. Machine learning models were built by lncRNAs to predict CD8 T-cell abundances. The lncRNAs were used to develop a prognostic model that could predict the survival rates of BC patients. The expression of selected lncRNA (XIST) was validated by quantitative real-time PCR (qRT-PCR).

Results

A total of 1,599 DElncRNAs, 89 DEmiRNAs, and 1,794 DEmRNAs between high and low CD8 T-cell groups were obtained. Two ceRNA networks that have positive or negative correlations with CD8 T cells were built. Among the two ceRNA networks, nine lncRNAs (MIR29B2CHG, NEAT1, MALAT1, LINC00943, LINC01146, AC092718.4, AC005332.4, NORAD, and XIST) were selected for model construction. Among six prevalent machine learning models, artificial neural networks performed best, with an area under the curve (AUC) of 0.855. Patients from the high-risk category with BC had a lower survival rate compared to those from the low-risk group. The qRT-PCR results revealed significantly reduced XIST expression in normal breast samples, which was consistent with our integrated analysis.

Conclusion

These results potentially provide insights into the ceRNA networks linked with T-cell infiltration and provide accurate models for T-cell prediction.

Weighted correlation network analysis revealed novel long non-coding RNAs for colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, which after breast, lung and, prostate cancers, is the fourth prevalent cancer in the United States. Long non-coding RNAs (lncRNAs) have an essential role in the pathogenesis of CRC. Therefore, bioinformatics studies on lncRNAs and their target genes have potential importance as novel biomarkers. In the current study, publicly available microarray gene expression data of colorectal cancer (GSE106582) was analyzed with the Limma, Geoquery, Biobase package. Afterward, identified differentially expressed lncRNAs and their target genes were inserted into Weighted correlation network analysis (WGCNA) to obtain modules and hub genes. A total of nine differentially expressed lncRNAs (LINC01018, ITCH-IT, ITPK1-AS1, FOXP1-IT1, FAM238B, PAXIP1-AS1, ATP2B1-AS1, MIR29B2CHG, and SNHG32) were identified using microarray data analysis. The WGCNA has identified several hub genes for black (LMOD3, CDKN2AIPNL, EXO5, ZNF69, BMS1P5, METTL21A, IL17RD, MIGA1, CEP19, FKBP14), blue (CLCA1, GUCA2A, UGT2B17, DSC2, CA1, AQP8, ITLN1, BEST4, KLF4, IQCF6) and turquoise (PAFAH1B1, LMNB1, CACYBP, GLO1, PUM3, POC1A, ASF1B, SDCCAG3, ASNS, PDCD2L) modules. The findings of the current study will help to improve our understanding of CRC. Moreover, the hub genes that we have identified could be considered as possible prognostic/diagnostic biomarkers. This study led to the determination of nine lncRNAs with no previous association with CRC development.