Identification and Validation of Reference Genes Selection in Ovarian Cancer Exposed to Hypoxia

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

Screening and Identifying Reference Genes for Erythrocyte Production from Cord Blood CD34+ Cells Exposed to Hypoxia

Cord blood (CB) CD34+ cells have the potential to be used to achieve artificial hematopoiesis because of their ability to expand and differentiate in multiple directions. However, the mechanism and molecular changes underlying such differentiation are still unclear. The differentiation of CB CD34+ cells is generally driven by subtle changes in gene expression. A crucial method for examining gene expression is quantitative real-time polymerase chain reaction, but the accuracy of the results is dependent on the use of reliable reference genes. Here, the transcription levels of 10 novel candidate reference genes (EIF4G2, DYNC1H1, LUC7L3, CD46, POLR1D, WSB1, GAPVD1, HGS, LGALS8, and RBM5) and 8 traditional reference genes (GAPDH, YWHAZ, ACTB, B2MG, TBP, HMBS, PPIA, HPRT1) in CB CD34+ cells under different oxygen concentrations were screened and evaluated by using the geNorm and NormFinder algorithms. Comprehensive analysis conducted by RefFinder online tool showed that TBP (a traditional reference gene) and EIF4G2 (a novel reference gene) had the most stable expression, whereas GAPDH and HMBS were the least suitable reference genes under these conditions. These results may serve as a basis for selecting reference genes with stable expression for more accurate normalization under different oxygen concentration stimulation during CB CD34+ cells differentiation.

Reduced oxygen concentrations regulate the phenotype and function of human granulosa cells in vitro and cause a diminished steroidogenic but increased inflammatory cellular reaction

Oxygen (O2) concentrations have recently been discussed as important regulators of ovarian cells. Human IVF-derived granulosa cells (human GCs) can be maintained in vitro and are a widely used cellular model for the human ovary. Typically, GCs are cultured at atmospheric O2 levels (approximately around 20%), yet the O2 conditions in vivo, especially in the preovulatory follicle, are estimated to be much lower. Therefore, we comprehensively evaluated the consequences of atmospheric versus hypoxic (1% O2) conditions for 4 days on human GCs. We found lower cellular RNA and protein levels but unchanged cell numbers at 1% O2, indicating reduced transcriptional and/or translational activity. A proteomic analysis showed that 391 proteins were indeed decreased, yet 133 proteins were increased under hypoxic conditions. According to gene ontology (GO) enrichment analysis, pathways associated with metabolic processes, for example amino acid-catabolic-processes, mitochondrial protein biosynthesis, and steroid biosynthesis, were downregulated. Pathways associated with glycolysis, chemical homeostasis, cellular response to hypoxia, and actin filament bundle assembly were upregulated. In accordance with lower CYP11A1 (a cholesterol side-chain cleavage enzyme) levels, progesterone release was decreased. A proteome profiler, as well as IL-6 and IL-8 ELISA assays, revealed that hypoxia led to increased secretion of pro-inflammatory and angiogenic factors. Immunofluorescence studies showed nuclear localization of hypoxia-inducible factor 1α (HIF1α) in human GCs upon acute (2 h) exposure to 1% O2 but not in cells exposed to 1% O2 for 4 days. Hence, the role of HIF1α may be restricted to initiation of the hypoxic response in human GCs. The results provide a detailed picture of hypoxia-induced phenotypic changes in human GCs and reveal that chronically low O2 conditions inhibit the steroidogenic but promote the inflammatory phenotype of these cells.

Uncovering the stability status of the reputed reference genes in breast and hepatic cancer cell lines

Accurate and reliable relative gene expression analysis via the Reverse Transcription-quantitative Real Time PCR (RT-qPCR) method strongly depends on employing several stable reference genes as normalizers. Utilization of the reference genes without analyzing their expression stability under each experimental condition causes RT-qPCR analysis error as well as false output. Similar to cancerous tissues, cancer cell lines also exhibit various gene expression profiles. It is crucial to recognize stable reference genes for well-known cancer cell lines to minimize RT-qPCR analysis error. In this study, we showed the expression level and investigated the expression stability of eight common reference genes that are ACTB, YWHAZ, HPRT1, RNA18S, TBP, GAPDH, UBC, and B2M, in two sets of cancerous cell lines. One set contains MCF7, SKBR3, and MDA-MB231 as breast cancer cell lines. Another set includes three hepatic cancer cell lines, including Huh7, HepG2, and PLC-PRF5. Three excel-based softwares comprising geNorm, BestKeeper, and NormFinder, and an online tool, namely RefFinder were used for stability analysis. Although all four algorithms did not show the same stability ranking of nominee genes, the overall results showed B2M and ACTB as the least stable reference genes for the studied breast cancer cell lines. While TBP had the lowest expression stability in the three hepatic cancer cell lines. Moreover, YWHAZ, UBC, and GAPDH showed the highest stability in breast cancer cell lines. Besides that, a panel of five nominees, including ACTB, HPRT1, UBC, YWHAZ, and B2M showed higher stability than others in hepatic cancer cell lines. We believe that our results would help researchers to find and to select the best combination of the reference genes for their own experiments involving the studied breast and hepatic cancer cell lines. To further analyze the reference genes stability for each experimental condition, we suggest researchers to consider the provided stability ranking emphasizing the unstable reference genes.

Identification and evaluation of an appropriate housekeeping gene for real time gene profiling of hepatocellular carcinoma cells cultured in three dimensional scaffold

BACKGROUND

Assessing an optimal reference gene as an internal control for target gene normalization is important during quantitative real time polymerase chain reaction (RT-qPCR) of three dimensional (3D) cell culture. Especially, gene profiling of cancer cells under a complex 3D microenvironment in a polymer scaffold provides a deeper understanding of tumor functioning in vivo.

METHODS AND RESULTS

Expression of six housekeeping genes (HKG's): Glyceraldehyde-3-phosphodehydrogenase (GAPDH), β-actin (ACTB), beta-2-microglobulin (B2M), 18S ribosomal RNA (18S rRNA), peptidyl-propyl-isomerase A (PPIA), and ribosomal protein L13 (RPL-13) during two dimensional (2D) culture, and alginate-carboxymethylcellulose scaffold based 3D culture conditioned up to 21 days was analysed for hepatocellular carcinoma (Huh-7) cells. The gene expression studies were performed by determining primer efficiency, melting curve and threshold cycle analysis. Further, RT-qPCR data was validated statistically using geNorm and NormFinder softwares. The study indicated RPL-13, 18S rRNA and B2M to be stable among selected referral HKG candidates.

CONCLUSION

An exploration of a reliable HKG is necessary for normalization of gene expression in RT-qPCR during varying cell culture conditions.

Evaluation of Reliable Reference Genes for In Vitro Erythrocyte Generation from Cord Blood CD34+ Cells

In vitro generation of red blood cells has the potential to circumvent shortfalls in the global demand for blood for transfusion applications. However, cell differentiation and proliferation are often regulated by precise changes in gene expression, but the underlying mechanisms and molecular changes remain unclear. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) can be used to evaluate multiple target genes. To make the results more reliable, suitable reference genes should be used to calibrate the error associated with qRT-PCR. In this study, we utilized bioinformatics to screen 3 novel candidate reference genes (calcium and integrin binding family member 2 [CIB2], olfactory receptor family 8 subfamily B member 8 [OR8B8], and zinc finger protein 425 [ZNF425]) along with eight traditional reference genes (glyceraldehyde-3-phosphate dehydrogenase [GAPDH], β-actin [ACTB], 18S RNA, β2-microglobulin [β2-MG], peptidylprolyl isomerase A [PPIA], TATA box-binding protein [TBP], hydroxymethylbilane synthase [HMBS], and hypoxanthine phosphoribosyltransferase 1 [HPRT1]). Two software algorithms (geNorm and NormFinder) were used to evaluate the stability of expression of the 11 genes at different stages of erythrocyte development. Comprehensive analysis showed that expression of GAPDH and TBP was the most stable, whereas ZNF425 and OR8B8 were the least suitable candidate genes. These results suggest that appropriate reference genes should be selected before performing gene expression analysis during erythroid differentiation and that GAPDH and TBP are suitable reference genes for gene expression studies on erythropoiesis.