Circular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC). A combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC. Six differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA–miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein–protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis. Our study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA–miRNA–mRNA network view.

Breast cancer (BC) has a complex etiology and pathogenesis, and is the most common malignant tumor type in females, in USA in 2018, yet its relevant molecular mechanisms remain largely unknown. The collagen type V α‑1 chain (COL5A1) gene is differentially expressed in renal and ovarian cancer. Using bioinformatics methods, COL5A1 was determined to also be a significant gene in BC, but its association with BC has not been sufficiently reported. COL5A1 microarray and relevant clinical data were collected from the Gene Expression Omnibus, The Cancer Genome Atlas and other databases to summarize COL5A1 expression in BC and its subtypes at the mRNA and protein levels. All associated information was comprehensively analyzed by various software. The clinical significance of the mutation was obtained via the cBioPortal. Furthermore, Gene Ontology functional annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were also performed to investigate the mechanism of COL5A1 in BC. Immunohistochemistry was also conducted to detect and confirm COL5A1 expression. It was determined that COL5A1 was highly expressed in BC tissues, compared with normal tissues at the mRNA level [standard mean difference, 0.84; 95% confidence interval (CI), 0.60‑1.07; P=0.108]. The area under the summary receiver operator characteristic curve for COL5A1 was 0.87 (95% CI, 0.84‑0.90). COL5A1 expression was altered in 32/817 (4%) sequenced samples. KEGG analysis confirmed the most notable pathways, including focal adhesion, extracellular matrix‑receptor interaction and regulation of the actin cytoskeleton. Immunohistochemical detection was used to verify the expression of COL5A1 in 136 selected cases of invasive BC tissues and 55 cases of adjacent normal tissues, while the rate of high expression of COL5A1 in BC was up to 90.4%. These results indicated that COL5A1 is highly expressed at the mRNA and protein levels in BC, and the prognosis of patients with BC with high COL5A1 expression may be reduced; therefore, COL5A1 may be used independently or combined with other detection factors in BC diagnosis.

HOTTIP functions as an independent biomarker in multiple cancers. However, the role of HOTTIP in hepatocellular carcinoma (HCC) remains unclear. In this study, we sought to investigate the HOTTIP expression in HCC and normal liver. We combined quantitative reverse transcription-polymerase chain reactions (qRT‑PCR), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), Multi Experiment Matrix (MEM) and Oncomine database to assess the clinical role and the potential molecular mechanism of HOTTIP in HCC. Furthermore, a meta‑analysis was performed to evaluate the relationship between HOTTIP and HCC tumorigenesis and development. Additionally, bioinformatics analysis, which contained Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and network analysis, were applied to investigate the underlying functions, pathways and networks of the potential genes. HOTTIP was obviously upregulated in HCC. A statistically significant higher expression of HOTTIP was found in TNM (III +Ⅳ), age (≥60), sex (male), race (white) and cirrhosis (no) compared to the control groups (P<0.05). Furthermore, the meta‑analysis of 393 cases from multiple centers indicated that HOTTIP had high diagnostic value in HCC. Additionally, according to GO and KEGG analyses, we found that the most strongly enriched functional terms were gland development, transcription factor activity and extrinsic to membrane. Also, the HOTTIP co‑expressed genes were significantly related to PPAR signaling pathway. We speculate that HOTTIP might play a vital part in HCC via regulating various pathways, especially PPAR signaling pathway. However, the detailed mechanism should be confirmed by functional experiments.

Background: The situation faced by breast cancer patients, especially those with triple-negative breast cancer, is still grave. More effective therapeutic targets are needed to optimize the clinical management of breast cancer. Although collagen type VIII alpha 1 chain (COL8A1) has been shown to be downregulated in BRIP1-knockdown breast cancer cells, its clinical role in breast cancer remains unknown. Methods: Gene microarrays and mRNA sequencing data were downloaded and integrated into larger matrices based on various platforms. Therefore, this is a multi-centered study, which contains 5048 breast cancer patients and 1161 controls. COL8A1 mRNA expression in breast cancer was compared between molecular subtypes. In-house immunohistochemistry staining was used to evaluate the protein expression of COL8A1 in breast cancer. A diagnostic test was performed to assess its clinical value. Furthermore, based on differentially expressed genes (DEGs) and co-expressed genes (CEGs) positively related to COL8A1, functional enrichment analyses were performed to explore the biological function and potential molecular mechanisms of COL8A1 underlying breast cancer. Results: COL8A1 expression was higher in breast cancer patients than in control samples (standardized mean difference = 0.79; 95% confidence interval [CI] 0.55–1.03). Elevated expression was detected in various molecular subtypes of breast cancer. An area under a summary receiver operating characteristic curve of 0.80 (95% CI 0.76–0.83) with sensitivity of 0.77 (95% CI 0.69–0.83) and specificity of 0.70 (95% CI 0.61–0.78) showed moderate capacity of COL8A1 in distinguishing breast cancer patients from control samples. Worse overall survival was found in the higher than in the lower COL8A1 expression groups. Intersected DEGs and CEGs positively related to COL8A1 were significantly clustered in the proteoglycans in cancer and ECM-receptor interaction pathways. Conclusions: Elevated COL8A1 may promote the migration of breast cancer by mediating the ECM-receptor interaction and synergistically interplaying with DEGs and its positively related CEGs independently of molecular subtypes. Several genes clustered in the proteoglycans in cancer pathway are potential targets for developing effective agents for triple-negative breast cancer.