Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

Recent Multiomics Approaches in Endometrial Cancer

Endometrial cancer is the most common gynecological cancers in developed countries. Many of the mechanisms involved in its initiation and progression remain unclear. Analysis providing comprehensive data on the genome, transcriptome, proteome, and epigenome could help in selecting molecular markers and targets in endometrial cancer. Multiomics approaches can reveal disturbances in multiple biological systems, giving a broader picture of the problem. However, they provide a large amount of data that require processing and further integration prior to analysis. There are several repositories of multiomics datasets, including endometrial cancer data, as well as portals allowing multiomics data analysis and visualization, including Oncomine, UALCAN, LinkedOmics, and miRDB. Multiomics approaches have also been applied in endometrial cancer research in order to identify novel molecular markers and therapeutic targets. This review describes in detail the latest findings on multiomics approaches in endometrial cancer.

INTS7-ABCD3 Interaction Stimulates the Proliferation and Osteoblastic Differentiation of Mouse Bone Marrow Mesenchymal Stem Cells by Suppressing Oxidative Stress

Increased adipocyte and decreased osteoblast differentiation, combined with the ectopic proliferation of bone marrow mesenchymal stem cells (BM-MSCs), represent the primary causes of osteoporosis. The dysregulation of numerous intracellular bioactive factors is responsible for the aberrant differentiation and growth of BM-MSCs. In this study, we focused on a new stimulative factor, integrator complex subunit 7 (INTS7), and its cooperative protein ATP-binding cassette subfamily D member 3 (ABCD3)/high-density lipoprotein-binding protein (HDLBP) in mouse BM-MSCs. We aimed to uncover the effects of the INTS7–ABCD3/HDLBP interaction on BM-MSC biological behaviors and the potential mechanism underlying these effects. Functional in vitro experiments showed that the suppression of the INTS7–ABCD3 interaction rather than HDLBP could impair BM-MSC proliferation and induce cell apoptosis. Moreover, Alizarin Red S and Oil Red O staining, respectively, revealed that INTS7 and ABCD3 knockdown but not HDLBP knockdown could decrease osteoblastic differentiation and accelerate the adipogenic differentiation of BM-MSCs. Mechanistically, reactive oxygen species (ROS) and histone γ-H2AX quantities significantly increased, whereas the levels of antioxidants declined due to INTS7 and ABCD3 inhibition in BM-MSCs. These findings indicated that the suppression of oxidative stress could be involved in the INTS7/ABCD3 co-regulatory mechanisms for BM-MSC proliferation and differentiation, identifying new potential candidates for osteoporosis therapy.

Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis

Hepatocellular carcinoma is recognized as one of the most frequently occurring malignant types of liver cancer globally, making the identification of biomarkers critically important. The aim of the present study was to identify the genes involved in the anticancer effects of flavonoid compounds so that they may be used as targets for cancer treatment. Sinensetin (SIN), an isolated polymethoxyflavone monomer compound, possesses broad antitumor activities in vitro. Therefore, the identification of a transcriptome profile on the condition of cells treated with SIN may aid to better understand the genes involved and its mechanism of action. Genomic profiling studies of cancer are increasing rapidly in order to provide gene expression data that can reveal prognostic biomarkers to combat liver cancer. In the present study, high-throughput RNA sequencing (RNA-seq) was performed to reveal differential gene expression patterns between SIN-treated and SIN-untreated human liver cancer HepG2 cells. A total of 43 genes were identified to be differentially expressed (39 downregulated and 4 upregulated in the SIN-treated group compared with the SIN-untreated group). An extensive network analysis for these 43 genes resulted in the identification of 10 upregulated highly interconnected hub genes that contributed to the progression of cancer. Functional enrichment analysis of these 10 hub genes revealed their involvement in the regulation of apoptotic processes, immune response and tumor necrosis factor production. Additionally, the mRNA expression levels of these 10 genes were evaluated using reverse transcription-quantitative PCR, and the results were consistent with the RNA-seq data. Overall, the results of the present study revealed differentially expressed genes involved in cancer after SIN treatment in HepG2 cells and may help to develop strategies targeting these genes for treating liver cancer.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

Colitis-induced IL11 promotes colon carcinogenesis

Colitis increases the risk of colorectal cancer; however, the mechanism of the association between colitis and cancer remains largely unknown. To identify colitis-associated cancer promoting factors, we investigated gene expression changes caused by dextran sulfate sodium (DSS)-induced colitis in mice. By analyzing gene expression profiles, we found that IL11 was upregulated in DSS-induced colitis tissue and 2-amino-1-methyl-6-phenylimidazo[4,5-b]-pyridine (PhIP)/DSS-induced colon tumours in mice as well as in human colorectal cancer. By characterizing the activation/phosphorylation of STAT3 (pSTAT3), we found that pSTAT3 was induced transiently in colitis, but maintained at higher levels from hyper-proliferative dysplastic lesions to tumours. Using the IL11 receptor (IL11Rα1) knockout mice, we found that pSTAT3 in the newly regenerated crypt epithelial cells in colitis is abolished in IL11Rα1+/- and -/- mice, suggesting that colitis-induced IL11 activates STAT3 in colon crypt epithelial cells. Moreover, colitis-promoted colon carcinogenesis was significantly reduced in IL11Rα1+/- and -/- mice. To determine the roles of the IL11 in colitis, we found that the inhibition of IL11 signalling by recombinant IL11 antagonist mutein during colitis was sufficient to attenuate colitis-promoted carcinogenesis. Together, our results demonstrated that colitis-induced IL11 plays critical roles in creating cancer promoting microenvironment to facilitate the development of colon cancer from dormant premalignant cells.

Network-based identification of biomarkers for colon adenocarcinoma

Background

As one of the most common cancers with high mortality in the world, we are still facing a huge challenge in the prevention and treatment of colon cancer. With the rapid development of high throughput technologies, new biomarkers identification for colon cancer has been confronted with the new opportunities and challenges.

Methods

We firstly constructed functional networks for each sample of colon adenocarcinoma (COAD) by using a sample-specific network (SSN) method which can construct individual-specific networks based on gene expression profiles of a single sample. The functional genes and interactions were identified from the functional networks, respectively.

Results

Classification and subtyping were used to test the function of the functional genes and interactions. The results of classification showed that the functional genes could be used as diagnostic biomarkers. The subtypes displayed different mechanisms, which were shown by the functional and pathway enrichment analysis for the representative genes of each subtype. Besides, subtype-specific molecular patterns were also detected, such as subtype-specific clinical and mutation features. Finally, 12 functional genes and 13 functional edges could serve as prognosis biomarkers since they were associated with the survival rate of COAD.

Conclusions

In conclusion, the functional genes and interactions in the constructed functional network could be used as new biomarkers for COAD.

Abnormal expression of ABCD3 is an independent prognostic factor for colorectal cancer

ATP binding cassette subfamily D member 3 (ABCD3) is a member of the superfamily of ATP-binding cassette (ABC) transporters, which serve crucial roles in the process of tumor cell resistance to chemotherapy. The present study investigated the diagnostic and prognostic capabilities of ABCD3 in colorectal cancer (CRC) by bioinformatics analysis. Gene expression data and corresponding clinical information of patients with CRC were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The results demonstrated that ABCD3 mRNA level was decreased in CRC tissues compared with normal tissues following Wilcoxon test analysis. Furthermore, ABCD3 protein expression was significantly higher in normal colon tissues compared with colon adenocarcinoma tissues according to the Human Protein Atlas. In addition, the area under the Receiver Operating Characteristic curve based on comparison between the tumor and normal groups derived from TCGA and GEO databases demonstrated that the use of ABCD3 mRNA level may be used for the diagnosis of CRC. ABCD3 expression was significantly associated with clinical stage, T stage, and lymph node status following Kruskal-Wallis test or Wilcoxon rank sum test, logistic regression and χ² test. Furthermore, the results from Kaplan-Meier survival analysis indicated that low ABCD3 mRNA expression had a poorer prognosis value compared with ABCD3 high expression in patients with CRC. In addition, results from univariate Cox regression analysis indicated that ABCD3 mRNA expression was associated with overall survival (OS), and results from multivariate Cox analysis indicated that ABCD3 mRNA expression may be considered an independent prognostic factor from other clinical factors, such as clinical stage, sex and age. The results from Gene Set Enrichment Analysis demonstrated that the ABCD3 high-expression phenotype was differentially enriched in five biological processes, including apoptosis, cell cycle, renal cell carcinoma, thyroid cancer and colorectal cancer. The findings from this study demonstrated that ABCD3 mRNA expression may be considered as a potential diagnostic and prognostic biomarker in patients with CRC. ABCD3 expression levels may participate in the regulation of cell apoptosis and cell cycle. In addition, GSEA analysis identified Kyoto Encyclopaedia of Genes and Genomes pathways for renal cell carcinoma, thyroid cancer and CRC involving ABCD3.