Breast cancer (BC) is a major human health problem due to its increasing incidence and mortality rate. CC and CXC chemokines are associated with tumorigenesis and the progression of many cancers. Since the prognostic values of CC and CXC families' expression in various types of cancers are becoming increasingly evident, we aimed to conduct a comprehensive bioinformatics analysis elucidating the prognostic values of the CC and CXC families in BC. Therefore, TCGA, UALCAN, Kaplan–Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER were utilized for analysis. We found that high levels of CCL4/5/14/19/21/22 were associated with better OS and RFS, while elevated expression of CCL24 was correlated with shorter OS in BC patients. Also, high levels of CXCL9/13 indicated longer OS, and enhanced expression of CXCL12/14 was linked with better OS and RFS in BC patients. Meanwhile, increased transcription levels of CXCL8 were associated with worse OS and RFS in BC patients. In addition, our results showed that CCL5, CCL8, CCL14, CCL20, CCL27, CXCL4, and CXCL14 were notably correlated with the clinical outcomes of BC patients. Our findings provide a new point of view that may help the clinical application of CC and CXC chemokines as prognostic biomarkers in BC.

No abstract

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein–protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

No abstract

Background: Aberrant expression of long noncoding RNAs (lncRNAs) is associated with the progression of human cancers, including gastric cancer (GC). The function of lncRNA DLGAP1-AS2, as an oncogene, has been identi ed in glioma, hepatocellular carcinoma, and cholangiocarcinoma but not in other malignancies. Therefore, this study was aimed to explore the association of DLGAP1-AS2 with gastric tumorigenesis and beyond.Methods and Results: The expression level of DLGAP1-AS2 was prevaluated in GC datasets from Gene Expression Omnibus (GEO). Moreover, qRT-PCR experiment was performed on 25 paired GC and adjacent normal tissue samples. The Cancer Genome Atlas (TCGA) data were also analyzed for further validations. Consistent with data obtained from GEO datasets, qRT-PCR results revealed that DLGAP1-AS2 was signi cantly (p < 0.0032) upregulated in GC specimens compared to normal samples, which was additionally con rmed using TCGA analysis (p<0.0001). DLGAP1-AS2 expression level was also correlated with age (p =0.0008), lymphatic and vascular invasion (p =0.0415) in internal samples. Also, a signi cant correlation was found between DLGAP1-AS2 and YAP1 expression, as its valid downstream target, in GC samples. Besides, analysis of other prevalent tumor entities using TCGA illustrated the signi cant overexpression of DLGAP1-AS2 in lung, colorectal, and prostate cancers, further indicating its promise as an oncogene. Moreover, ROC curve analysis showed the high accuracy of the DLGAP1-AS2 expression pattern as a diagnostic biomarker for gastric and colorectal cancers. Conclusion: Our ndings indicated that DLGAP1-AS2 might display oncogenic property in gastric tumorigenesis and be suggested as a therapeutic and diagnostic target.

Background: Aberrant expression of long noncoding RNAs (lncRNAs) is associated with the progression of human cancers, including gastric cancer (GC). The function of lncRNA DLGAP1-AS2, as an oncogene, has been identified in glioma, hepatocellular carcinoma, and cholangiocarcinoma but not in other malignancies. Therefore, this study was aimed to explore the association of DLGAP1-AS2 with gastric tumorigenesis and beyond.Methods and Results: The expression level of DLGAP1-AS2 was prevaluated in GC datasets from Gene Expression Omnibus (GEO). Moreover, qRT-PCR experiment was performed on 25 paired GC and adjacent normal tissue samples. The Cancer Genome Atlas (TCGA) data were also analyzed for further validations. Consistent with data obtained from GEO datasets, qRT-PCR results revealed that DLGAP1-AS2 was significantly (p < 0.0032) upregulated in GC specimens compared to normal samples, which was additionally confirmed using TCGA analysis (p<0.0001). DLGAP1-AS2 expression level was also correlated with age (p =0.0008), lymphatic and vascular invasion (p =0.0415) in internal samples. Also, a significant correlation was found between DLGAP1-AS2 and YAP1 expression, as its valid downstream target, in GC samples. Besides, analysis of other prevalent tumor entities using TCGA illustrated the significant overexpression of DLGAP1-AS2 in lung, colorectal, and prostate cancers, further indicating its promise as an oncogene. Moreover, ROC curve analysis showed the high accuracy of the DLGAP1-AS2 expression pattern as a diagnostic biomarker for gastric and colorectal cancers. Conclusion: Our findings indicated that DLGAP1-AS2 might display oncogenic property in gastric tumorigenesis and be suggested as a therapeutic and diagnostic target.

Breast cancer (BC) is a heterogeneous disease divided into four molecular subtypes that display different prognoses. Molecular alterations in breast cells contribute to breast carcinogenesis. However, the molecular characteristics involved in developing BC subtypes remain largely unknown. Further identification of molecular mechanisms involved in different BC subtypes might help improve treatment strategies and prognosis of patients. In the present study, two microarray datasets (GSE57297 and GSE65194) containing four BC subtypes were downloaded from the Gene Expression Omnibus (GEO) database. Comparative analyses were performed to identify specific differentially expressed genes (DEGs) for each BC subtype, as well as overlapped (core) between all subtypes. bc-GenExMiner and Kaplan-Meier plotter databases were respectively utilized to investigate the differential expression and prognostic value of DEGs. A total of 25 DEGs (12 specific and 13 core) were found to be significantly associated with prognosis. We found that a high level of C9orf116 predicted better OS in the Luminal A subtype. Also, increased transcription levels of FAM13A and RASIP1 were associated with shorter OS in the Luminal B subtype. High mRNA expression of PDE7A, and COTL1 conferred longer OS, while elevated expression of TM4SF1 and AREG predicted shorter OS in the TNBC subtype. Increased mRNA levels of GSR, and DAPK2 conferred better OS in the HER2 subtype; however, increased expression levels of HOTAIR, PLEKHG4, and POU6F1 predicted poor OS. For the core DEGs, increased expression of IFI6 and UBE2S predicted shorter OS. Meanwhile, increased mRNA levels of AK5, C2orf40, CNN1, HOXA5, NTRK2, PAMR1, PROS1, SCARA5, SDPR, TGFBR3, and TSHZ2 conferred better OS. In conclusion, this study strictly identified specific genes that may help to select precision prognostic biomarkers in different BC subtypes.