Decreased mRNA expression of GATA1 and GATA2 is associated with tumor aggressiveness and poor outcome in clear cell renal cell carcinoma

Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis

Type 2 diabetes (T2D) is a crucial risk factor for both pancreatic cancer (PC) and kidney cancer (KC). However, effective common drugs for treating PC and/or KC patients who are also suffering from T2D are currently lacking, despite the probability of their co-occurrence. Taking disease-specific multiple drugs during the co-existence of multiple diseases may lead to adverse side effects or toxicity to the patients due to drug-drug interactions. This study aimed to identify T2D-, PC and KC-causing common genomic biomarkers (cGBs) highlighting their pathogenetic mechanisms to explore effective drugs as their common treatment. We analyzed transcriptomic profile datasets, applying weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis approaches to identify T2D-, PC-, and KC-causing cGBs. We then disclosed common pathogenetic mechanisms through gene ontology (GO) terms, KEGG pathways, regulatory networks, and DNA methylation of these cGBs. Initially, we identified 78 common differentially expressed genes (cDEGs) that could distinguish T2D, PC, and KC samples from controls based on their transcriptomic profiles. From these, six top-ranked cDEGs (TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7) were selected as cGBs and considered targets for exploring common drug molecules for each of three diseases. Functional enrichment analyses, including GO terms, KEGG pathways, and regulatory network analyses involving transcription factors (TFs) and microRNAs, along with DNA methylation and immune infiltration studies, revealed critical common molecular mechanisms linked to PC, KC, and T2D. Finally, we identified six top-ranked drug molecules (NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib) as potential common treatments for PC, KC and T2D during their co-existence, supported by the literature reviews. Thus, this bioinformatics study provides valuable insights and resources for developing a genome-guided common treatment strategy for PC and/or KC patients who are also suffering from T2D.

Transcriptional Regulation of the Human MGP Promoter: Identification of Downstream Repressors

Matrix Gla protein (MGP) is a vitamin K-dependent γ-carboxylated protein that was initially identified as a physiological inhibitor of ectopic calcification, primarily affecting cartilage and the vascular system. Mutations in the MGP gene were found to be responsible for the Keutel syndrome, a condition characterized by abnormal calcifications in the cartilage, lungs, brain, and vascular system. MGP has been shown to be dysregulated in several tumors, including cervical, ovarian, urogenital, and breast cancers. Using bioinformatic approaches, transcription factor binding sites (TFBSs) containing CpG dinucleotides were identified in the MGP promoter, including those for YY1, GATA1, and C/EBPα. We carried out functional tests using transient transfections with a luciferase reporter assay, primarily for the transcription factors YY1, GATA1, C/EBPα, and RUNX2. By co-transfection analysis, we found that YY1, GATA1, and C/EBPα repressed the MGP promoter. Furthermore, the co-transfection with RUNX2 activated the MGP promoter. In addition, MGP expression is negatively or positively correlated with the studied TFs' expression levels in several cancer types. This study provides novel insights into MGP regulation by demonstrating that YY1, GATA1, and C/EBPα are negative regulators of the MGP promoter, and DNA methylation may influence their activity. The dysregulation of these mechanisms in cancer should be further elucidated.

Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications

Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.

Melatonin suppresses tumor proliferation and metastasis by targeting GATA2 in endometrial cancer

Endometrial cancer (EC) is a reproductive system disease that occurs in perimenopausal and postmenopausal women. However, its etiology is unclear. Melatonin (MT) has been identified as a therapeutic agent for EC; however, its exact mechanism remains unclear. In the present study, we determined that GATA-binding protein 2 (GATA2) is expressed at low levels in EC and regulated by MT. MT upregulates the expression of GATA2 through MT receptor 1A (MTNR1A), whereas GATA2 can promote the expression of MTNR1A by binding to its promoter region. In addition, in vivo and in vitro experiments showed that MT inhibited the proliferation and metastasis of EC cells by upregulating GATA2 expression. The protein kinase B (AKT) pathway was also affected. In conclusion, these findings suggest that MT and GATA2 play significant roles in EC development.

Inferring Markov Chains to Describe Convergent Tumor Evolution With CIMICE

The field of tumor phylogenetics focuses on studying the differences within cancer cell populations. Many efforts are done within the scientific community to build cancer progression models trying to understand the heterogeneity of such diseases. These models are highly dependent on the kind of data used for their construction, therefore, as the experimental technologies evolve, it is of major importance to exploit their peculiarities. In this work we describe a cancer progression model based on Single Cell DNA Sequencing data. When constructing the model, we focus on tailoring the formalism on the specificity of the data. We operate by defining a minimal set of assumptions needed to reconstruct a flexible DAG structured model, capable of identifying progression beyond the limitation of the infinite site assumption. Our proposal is conservative in the sense that we aim to neither discard nor infer knowledge which is not represented in the data. We provide simulations and analytical results to show the features of our model, test it on real data, show how it can be integrated with other approaches to cope with input noise. Moreover, our framework can be exploited to produce simulated data that follows our theoretical assumptions. Finally, we provide an open source R implementation of our approach, called CIMICE, that is publicly available on BioConductor.

A Differential Transcriptional Regulome Approach to Unpack Cancer Biology: Insights on Renal Cell Carcinoma Subtypes

Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications. DIFFREG focuses on the differential regulation between transcription factors (TFs) and their target genes rather than differential gene expression and integrates transcriptome profiling with the human transcriptional regulatory network to analyze differential gene regulation between healthy and RCC cases. In this study, RNA-seq tissue samples (n = 1020) from the Cancer Genome Atlas (TCGA), including healthy and tumor subjects, were integrated with a comprehensive human TF-gene interactome dataset (1122603 interactions between 1289 TFs and 25177 genes). Comparative analysis of DIFFREG profiles, consisting of perturbed TF-gene interactions, from three common subtypes (clear cell RCC, papillary RCC and chromophobe RCC) revealed subtype-specific alterations, supporting the hypothesis that these signatures in the transcriptional regulome profiles may be considered potential biomarkers that may play an important role in elucidating the molecular mechanisms of RCC development and translating knowledge about the genetic basis of RCC into the clinic. In addition, these indicators may help oncologists make the best decisions for diagnosis and prognosis management.

Role of the pioneer transcription factor GATA2 in health and disease

The transcription factor GATA2 is involved in human diseases ranging from hematopoietic disorders, to cancer, to infectious diseases. GATA2 is one of six GATA-family transcription factors that act as pioneering transcription factors which facilitate the opening of heterochromatin and the subsequent binding of other transcription factors to induce gene expression from previously inaccessible regions of the genome. Although GATA2 is essential for hematopoiesis and lymphangiogenesis, it is also expressed in other tissues such as the lung, prostate gland, gastrointestinal tract, central nervous system, placenta, fetal liver, and fetal heart. Gene or transcriptional abnormalities of GATA2 causes or predisposes patients to several diseases including the hematological cancers acute myeloid leukemia and acute lymphoblastic leukemia, the primary immunodeficiency MonoMAC syndrome, and to cancers of the lung, prostate, uterus, kidney, breast, gastric tract, and ovaries. Recent data has also linked GATA2 expression and mutations to responses to infectious diseases including SARS-CoV-2 and Pneumocystis carinii pneumonia, and to inflammatory disorders such as atherosclerosis. In this article we review the role of GATA2 in the etiology and progression of these various diseases.

The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates

BACKGROUND

Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate.

RESULTS

Single nucleotide variants (P = 7.0 × 10-03, Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10-06) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10-05, paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10-09, paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations.

CONCLUSIONS

Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches.

Mechanism investigation and experiment validation of capsaicin on uterine corpus endometrial carcinoma

Background: Using bioinformatics analysis and experimental operations, we intend to analyze the potential mechanism of action of capsaicin target gene GATA1 in the treatment of uterine corpus endometrial carcinoma (UCEC) and develop a prognostic model for the disease to validate this model.

Methods: By obtaining capsaicin and UCEC-related DR-DEGs, the prognosis-related gene GATA1 was screened. The survival analysis was conducted via establishing high and low expression groups of GATA1. Whether the GATA1 could be an independent prognostic factor for UCEC, it was also validated. The therapeutic mechanism of capsaicin-related genes in UCEC was further investigated using enrichment analysis and immune methods as well as in combination with single-cell sequencing data. Finally, it was validated by cell experiments.

Results: GATA1, a high-risk gene associated with prognosis, was obtained by screening. Kaplan-Meier analysis showed that the survival of the high expression group was lower than that of low expression group. ROC curves showed that the prediction effect of the model was good and stable (1-year area under curve (AUC): 0.601; 2-years AUC: 0.575; 3-years AUC: 0.610). Independent prognosis analysis showed that the GATA1 can serve as an independent prognostic factor for UCEC. Enrichment analysis showed that “neuroactive Ligand - receptor interaction and TYPE I DIABETES MELLITUS” had a significant enrichment effect. Single-cell sequencing showed that the GATA1 was significantly expressed in mast cells. Cell experiments showed that the capsaicin significantly reduced the UCEC cell activity and migration ability, as well as inhibited the expression of GATA1.

Conclusion: This study suggests that the capsaicin has potential value and application prospect in the treatment of UCEC. It provides new genetic markers for the prognosis of UCEC patients.

GATA1 regulates the microRNA‑328‑3p/PIM1 axis via circular RNA ITGB1 to promote renal ischemia/reperfusion injury in HK‑2 cells

Acute kidney injury (AKI) is caused by renal ischemia/reperfusion injury (IRI) during kidney transplantation. The levels of both circular RNAs (circRNAs) and microRNAs (miRNAs/miR) appear to be critical for AKI detection. While several RNA interactions in AKI have been found, the regulatory mechanisms between the molecules remain to be fully elucidated. In the present study, miRNA expression profiling analysis was conducted using an online dataset to identify the differentially expressed miRNAs in rats with IRI. miR-328-3p was also found to be downregulated in human kidney-2 (HK-2) cells subjected to hypoxia/reperfusion (H/R), and its overexpression targeting pim-1 proto-oncogene (PIM1) resulted in an increased viability and a reduced apoptosis, as well as in the decreased expression of inflammatory factors upon H/R exposure. Putative targets and circRNAs of miR-328-3p were identified using publically available databases. The inhibition of circRNA integrin beta 1 (ITGB1; circITGB1) suppressed the inflammatory response induced by H/R by sponging miR-328-3p in HK-2 cells. Furthermore, a sequence of the functional ITGB1 promoter was studied for transcription factor GATA binding protein 1 (GATA1) binding sites. GATA1 binds to the ITGB1 promoter, leading to the expression of circITGB1. On the whole, the findings of the present study revealed a regulatory pathway modulating miR-328-3p in IRI, demonstrating that the GATA1-mediated regulation of circITGB1 enhanced the H/R-induced inflammatory response via the miR-328-3p/PIM1 axis.

LINC00891 regulated by miR-128-3p/GATA2 axis impedes lung cancer cell proliferation, invasion and EMT by inhibiting RhoA pathway

Long non-coding RNA (lncRNA) LINC00891 knockdown is associated with poor prognosis of lung adenocarcinoma, but the underlying mechanism remains to be further explored. Here, we found that LINC00891 expression is downregulated in lung cancer tissues and cell lines compared with that in adjacent normal tissues and normal lung epithelial cells. LINC00891 overexpression impedes cell proliferation, invasion, migration and epithelial-to-mesenchymal transition (EMT) process in lung cancer cells. Mechanistic research showed that GATA2 directly binds to LINC00891 promoter and transcriptionally regulates LINC00891 expression. Meanwhile, GATA2 was identified as a target of miR-128-3p, and it is negatively regulated by miR-128-3p. Moreover, overexpression of GATA2 suppresses lung cancer cell proliferation, invasion, migration, and EMT process. Furthermore, LINC00891 restrains the RhoA pathway activity, and treatment with CCG-1423 (a specific RhoA pathway inhibitor) antagonizes the promoting effect of LINC00891 knockdown on cell malignant behaviors. Additionally, silencing of LINC00891 promotes xenograft tumor growth, which can be reversed by administration with CCG-1423. In summary, LINC00891 regulated by the miR-128-3p/GATA2 axis restrains lung cancer cell malignant progression and hinders xenograft tumor growth by suppressing the RhoA pathway.

Characterization of the GATA Transcription Factor Family and Exploration of Their Relevance to Immune Infiltration and Tumor Microenvironment in Pancreatic Cancer

BACKGROUND

Pancreatic cancer (PC) presents a phenomenal disease burden worldwide. The GATA transcription factor family is associated with a variety of human malignancies. However, the relation between GATA family members (GATAs) and PC has not been elucidated.

METHODS

This study integrates large-scale bioinformatics database resources to analyze the expression patterns of GATAs in PC patients and explore their underlying function mechanism and relevance to immune infiltration and other different cell types in the tumor microenvironment in pancreatic cancer. First, the expression pattern of GATAs in pancreatic cancer was detected by the Oncomine database and the Gene Expression Profile Interaction Analysis (GEPIA2) database and verified through other datasets in the R2 platform. Then, we used the cBioPortal database and the Human Protein Atlas to assess the correlation between GATAs and clinicopathological features of PC. Then, survival analyses were performed to identify candidate prognostic factors in the GATA family in PC patients. Further, we performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network, immune-infiltration correlation analysis, and cell type analysis of the tumor microenvironment at the single-cell level to explain the function of GATAs in pancreatic cancer.

RESULTS

We found that GATA3 and GATA6 were highly expressed in pancreatic cancer, and the expression levels of GATA4 and GATA6 correlated with the pathological stage, differentiation grade, and molecular subtype of pancreatic cancer. The survival analysis revealed that lower GATA4 of PC patients was associated with better outcomes, and higher GATA6 might be associated with longer OS. In addition, GATA3 was associated with immune cell infiltration of PC, and GATA6 was mainly distributed in the epithelial cells with ductal phenotype.

CONCLUSION

This work tentatively identified GATA3, GATA4, and GATA6 in the GATA family associated with pancreatic cancer. GATA4 may serve as a prognostic factor for PC patients, and GATA6 may act as a subtype marker for PC. In addition, GATA3 may reflect the immune-infiltration status of PC.

Deep analysis of neuroblastoma core regulatory circuitries using online databases and integrated bioinformatics shows their pan-cancer roles as prognostic predictors

AIM

Neuroblastoma is a heterogeneous childhood cancer derived from the neural crest. The dual cell identities of neuroblastoma include Mesenchymal (MES) and Adrenergic (ADRN). These identities are conferred by a small set of tightly-regulated transcription factors (TFs) binding super enhancers, collectively forming core regulatory circuitries (CRCs). The purpose of this study was to gain a deep understanding of the role of MES and ADRN TFs in neuroblastoma and other cancers as potential indicators of disease prognosis, progression, and relapse.

METHODS

To that end, we first investigated the expression and mutational profile of MES and ADRN TFs in neuroblastoma. Moreover, we established their correlation with neuroblastoma risk groups and overall survival while establishing their extended networks with long non-coding RNAs (lncRNAs). Furthermore, we analysed the pan-cancer expression and mutational profile of these TFs and their correlation with patient survival and finally their network connectivity, using a panel of bioinformatic tools including GEPIA2, human pathology atlas, TIMER2, Omicsnet, and Cytoscape.

RESULTS

We show the association of multiple MES and ADRN TFs with neuroblastoma risk groups and overall survival and find significantly higher expression of various MES and ADRN TFs compared to normal tissues and their association with overall survival and disease-free survival in multiple cancers. Moreover, we report the strong correlation of the expression of these TFs with the infiltration of stromal and immune cells in the tumour microenvironment and with stemness and metastasis-related genes. Furthermore, we reveal extended pan-cancer networks comprising these TFs that influence the tumour microenvironment and metastasis and may be useful indicators of cancer prognosis and patient survival.

CONCLUSION

Our meta-analysis shows the significance of MES and ADRN TFs as indicators of patient prognosis and the putative utility of these TFs as potential novel biomarkers.

Comprehensive Analysis of Expression and Prognostic Value of GATAs in Lung Cancer

GATAs are a family of transcription factors that play sophisticated and extensive roles in cell fate transitions and tissue morphogenesis during embryonic development. Emerging evidence indicate that GATAs are involved in tumorigenesis of lung cancer (LC). However, the distinct roles, diverse expression patterns and prognostic values of six GATA family members in LC have yet to be elucidated. In the present study, the diverse expression patterns, prognostic values, genetic mutations, protein-protein interaction(PPI) networks of GATAs, Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway in LC patients were analyzed using a serious of databases, including ONCOMINE database, Cancer Cell Line Encyclopedia database, the Human Protein Atlas, the Gene Expression Profiling Interactive Analysis database, the Kaplan-Meier plotter, cBioPortal, String database and database Database for Annotation, Visualization, and Integrated Discovery. The mRNA expression levels of GATA1/2/4/5/6 were downregulated, while GATA3 showed abnormal expressions of up-regulation and down-regulation in patients with LC. Aberrant GATAs mRNA expression was connected with prognosis. Furthermore, genetic alterations mainly appeared in GATA4. Gene Ontology enrichment and network analysis demonstrated that GATAs and their 50 interactors were primarily associated with positive regulation of transcription from RNA polymerase II promoter, transcription factor complex, transcription factor binding Jak-STAT signaling pathway. This comprehensive bioinformatic analysis demonstrated that GATA1/2/3/4/6 may be new prognosis factors, and GATA2/5/6 may be potential targets for personalized therapy for patients with LC, but further studies are requisite to analyze the mechanism of their carcinogenicity and investigate novel drug treatment. Finally, these findings would conduce to a better understanding of the unique roles of GATAs in LC.

Novel molecular signatures and potential therapeutics in renal cell carcinomas: Insights from a comparative analysis of subtypes

Renal cell carcinomas (RCCs) are among the highest causes of cancer mortality. Although transcriptome profiling studies in the last decade have made significant molecular findings on RCCs, effective diagnosis and treatment strategies have yet to be achieved due to lack of adequate screening and comparative profiling of RCC subtypes. In this study, a comparative analysis was performed on RNA-seq based transcriptome data from each RCC subtype, namely clear cell RCC (KIRC), papillary RCC (KIRP) and kidney chromophobe (KICH), and mutual or subtype-specific reporter biomolecules were identified at RNA, protein, and metabolite levels by the integration of expression profiles with genome-scale biomolecular networks. This approach revealed already-known biomarkers in RCCs as well as novel biomarker candidates and potential therapeutic targets. Our findings also pointed out the incorporation of the molecular mechanisms of KIRC and KIRP, whereas KICH was shown to have distinct molecular signatures. Furthermore, considering the Dipeptidyl Peptidase 4 (DPP4) receptor as a potential therapeutic target specific to KICH, several drug candidates such as ZINC6745464 were identified through virtual screening of ZINC molecules. In this study, we reported valuable data for further experimental and clinical efforts, since the proposed molecules have significant potential for screening and therapeutic purposes in RCCs.

Landscape of cancer diagnostic biomarkers from specifically expressed genes

Although there has been great progress in cancer treatment, cancer remains a serious health threat to humans because of the lack of biomarkers for diagnosis, especially for early-stage diagnosis. In this study, we comprehensively surveyed the specifically expressed genes (SEGs) using the SEGtool based on the big data of gene expression from the The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) projects. In 15 solid tumors, we identified 233 cancer-specific SEGs (cSEGs), which were specifically expressed in only one cancer and showed great potential to be diagnostic biomarkers. Among them, three cSEGs (OGDH, MUDENG and ACO2) had a sample frequency >80% in kidney cancer, suggesting their high sensitivity. Furthermore, we identified 254 cSEGs as early-stage diagnostic biomarkers across 17 cancers. A two-gene combination strategy was applied to improve the sensitivity of diagnostic biomarkers, and hundreds of two-gene combinations were identified with high frequency. We also observed that 13 SEGs were targets of various drugs and nearly half of these drugs may be repurposed to treat cancers with SEGs as their targets. Several SEGs were regulated by specific transcription factors in the corresponding cancer, and 39 cSEGs were prognosis-related genes in 7 cancers. This work provides a survey of cancer biomarkers for diagnosis and early diagnosis and new insights to drug repurposing. These biomarkers may have great potential in cancer research and application.

GATA1 gene silencing inhibits invasion, proliferation and migration of cholangiocarcinoma stem cells via disrupting the PI3K/AKT pathway

Background/aims: Intrahepatic cholangiocarcinoma (CCA) is the second most prevalent type primary liver malignancy, accompanied by an increasing global incidence and mortality rate. Research has documented the contribution of the GATA binding protein-1 (GATA1) in the progression of liver cancer. Here, we aim to investigate the role of GATA1 in CCA stem cells via the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway.

Methods: Initially, microarray-based gene expression profiling was employed to identify the differentially expressed genes associated with CCA. Subsequently, an investigation was conducted to explore the potential biological significance behind the silencing of GATA1 and the regulatory mechanism between GATA1 and PI3K/AKT pathway. CCA cell lines QBC-939 and RBE were selected and treated with siRNA against GATA1 or/and a PI3K/AKT pathway inhibitor LY294002. In vivo experiment was also conducted to confirm in vitro findings.

Results: GATA1 exhibited higher expression in CCA samples and was predicted to affect the progression of CCA through blockade of the PI3K/AKT pathway. siRNA-mediated downregulation of GATA1 and LY294002 treatment resulted in reduced proliferation, migration and invasion abilities of CCA stem cells, together with impeded tumor growth, and led to increased cell apoptosis and primary cilium expression. Additionally, the siRNA-mediated GATA1 downregulation had an inhibitory effect on the PI3K/AKT pathway. LY294002 was manifested to enhance the inhibitory effects of GATA1 inhibition on CCA progression. These in vitro findings were reproduced in vivo on siRNA against GATA1 or LY294002 injected nude mice.

Conclusion: Altogether, the present study highlighted that downregulation of GATA1 via blockade of the PI3K/AKT pathway could inhibit the CCA stem cell proliferation, migration and invasion, and tumor growth, and promote cell apoptosis, primary cilium expression.

Comprehensive analysis of the GATA transcription factor gene family in breast carcinoma using gene microarrays, online databases and integrated bioinformatics

Integrated studies of accumulated data can be performed to obtain more reliable information and more feasible measures for investigating the potential diagnostic and prognostic biomarkers of breast cancer and exploring related molecular mechanisms. Our study aimed to explore the GATA family members involved in breast cancer by integrating data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and other online databases. We performed an integrated analysis of published studies from GEO and analyzed clinical data from TCGA and GTEx to evaluate the clinical significance and prognosis values of the GATA family in breast cancer. GATA3 was found to be upregulated and exhibited a favorable value in the diagnosis and prognosis of breast cancer. Through this study, we identified possible GATA3-correlated genes and core pathways that play an important role, which requires further investigation in breast cancer.

Association of melatonin membrane receptor 1A/1B gene polymorphisms with the occurrence and metastasis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent primary neoplasm of the liver, whose heterogeneous global incidence suggests the likely impact of genetic variations among individuals on the susceptibility to this disease. Increasing evidence indicates that melatonin exhibits oncostatic properties in many cancer types at least in part mediated by its membrane-bound receptors, melatonin receptor 1A (encoded by MTNR1A) and 1B (MTNR1B). In this study, the effect of melatonin receptor gene polymorphisms on the risk and progression of hepatic tumors was evaluated between 335 HCC patients and 1196 cancer-free subjects. We detected a significant association of MTNR1A single nucleotide polymorphism (SNP), rs6553010, with the elevated risk of HCC (AOR, 1.587; 95% CI, 1.053–2.389; p = 0.027) after being adjusted for two potential confounders, age and alcohol use. In addition, patients who carry at least one polymorphic allele (heterozygote or homozygote) of MTNR1A rs2119882 or rs2375801 were more prone to develop distant metastasis (OR, 5.202; 95% CI, 1.163–23.270; p = 0.031, and OR, 7.782; 95% CI, 1.015–59.663; p = 0.048, for rs2119882 and rs2375801, respectively). Further analyses revealed that rs2119882 is located on the consensus binding site of GATA2 transcription factor within the promoter region of MTNR1A gene, and that a correlation between the levels of GATA2 and melatonin receptor 1A was observed in the TCGA (The Cancer Genome Atlas) dataset. Moreover, individuals bearing a specific haplotype of four MTNR1B SNPs were more prone to develop HCC. In conclusion, our data suggest an association of melatonin receptor gene polymorphisms with the risk of HCC and hepatic cancer metastasis.

GATA binding protein 2 overexpression is associated with poor prognosis in KRAS mutant colorectal cancer

Colorectal cancer (CRC) is one of the most lethal cancers worldwide. Mutations in KRAS occur with the frequency of 30-50% in CRC leading to decreased therapeutic response to anti-epidermal growth factor receptor (EGFR) agents. Recently GATA2 was proven to be essential in the survival of KRAS mutant non-small cell lung cancer (NSCLC) cells. However, the association between KRAS mutation and GATA2 expression in CRC remains largely unknown. In the present study, dideoxy sequencing and immunohistochemistry were used to determine KRAS mutation and GATA2 expression, respectively, in a cohort of 236 patients. Cox proportional hazard regression and Kaplan-Meier survival analysis were performed to study the association between KRAS mutation or GATA2 expression and clinical outcomes. Kaplan-Meier analysis revealed that KRAS mutant patients with high expression of GATA2 had significantly worse long-term clinical outcomes than those with low expression of GATA2 (P<0.001). Further analysis showed that patients with both KRAS mutation and high GATA2 expression experienced significantly more unfavorable 5-year outcomes than patients with wild- type KRAS and low GATA2 expression (P=0.001). Univariate and multivariate Cox proportional hazard regression demonstrated the GATA2 expression level was an independent risk factor for overall survival of CRC patients (HR 1.645; 95% CI 1.004-2.696; P=0.048). In conclusion, the results of this study demonstrated that high expression of GATA2 is correlated with worse survival outcomes in KRAS mutant CRC patients, suggesting that GATA2 may serve as a novel biomarker for the survival of CRC patients harboring KRAS mutation.

A Five-Gene Signature Predicts Prognosis in Patients with Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers with high mortality all over the world. Many studies have proposed that genes could be used to predict prognosis in KIRC. In this study, RNA expression data from next-generation sequencing and clinical information of 523 patients downloaded from The Cancer Genome Atlas (TCGA) dataset were analyzed in order to identify the relationship between gene expression level and the prognosis of KIRC patients. A set of five genes that significantly associated with overall survival time was identified and a model containing these five genes was constructed by Cox regression analysis. By Kaplan-Meier and Receiver Operating Characteristic (ROC) analysis, we confirmed that the model had good sensitivity and specificity. In summary, expression of the five-gene model is associated with the prognosis outcomes of KIRC patients, and it may have an important clinical significance.