The mediator complex in genomic and non-genomic signaling in cancer

MediatorWeb: a protein-protein interaction network database for the RNA polymerase II Mediator complex

The protein-protein interaction (PPI) network of the Mediator complex is very tightly regulated and depends on different developmental and environmental cues. Here, we present an interactive platform for comparative analysis of the Mediator subunits from humans, baker's yeast Saccharomyces cerevisiae, and model plant Arabidopsis thaliana in a user-friendly web-interface database called MediatorWeb. MediatorWeb provides an interface to visualize and analyze the PPI network of Mediator subunits. The database facilitates downloading the untargeted and unweighted network of Mediator complex, its submodules, and individual Mediator subunits to better visualize the importance of individual Mediator subunits or their submodules. Further, MediatorWeb offers network visualization of the Mediator complex and interacting proteins that are functionally annotated. This feature provides clues to understand functions of Mediator subunits in different processes. In an additional tab, MediatorWeb provides quick access to secondary and tertiary structures, as well as residue-level contact information for Mediator subunits in each of the three model organisms. Another useful feature of MediatorWeb is detection of interologs based on orthologous analyses, which can provide clues to understand the functions of Mediator complex in less explored kingdoms. Thus, MediatorWeb and its features can help the user to understand the role of Mediator complex and its subunits in the transcription regulation of gene expression.

Characterization of Fusarium verticillioides Med1 LxxLL Motif Involved in Fumonisin Biosynthesis

The Med1 transcriptional coactivator is a crucial component of the Mediator middle complex, which regulates the expression of specific genes involved in cell development, differentiation, reproduction, and homeostasis. The Med1 LxxLL motif, a five-amino-acid peptide sequence, is essential for Med1-mediated gene expression. Our previous study revealed that the disruption of the Med1 subunit leads to a significant increase in fumonisin B1 (FB1) production in the maize pathogen Fusarium verticillioides. However, our understanding of how Med1 regulates FB1 biosynthesis in F. verticillioides, particularly through the Med1 LxxLL motifs, remains limited. To characterize the role of LxxLL motifs, we generated a series of Med1 LxxLL deletion and amino acid substitution mutants. These mutants exhibited impaired mycelial growth and conidia germination while demonstrating enhanced conidia production and virulence. Similar to the Med1 deletion mutant, Med1 LxxLL motif mutants also exhibited increased FB1 biosynthesis in F. verticillioides. Proteomic profiling revealed that the Med1 LxxLL motif regulated the biosynthesis of several key substances that affected FB1 production, including starch and carotenoid. Subsequent studies demonstrated that the production of amylopectin, which is strongly linked to FB1 biosynthesis, was significantly increased in Med1 LxxLL motif mutants. In addition, the disruption of carotenoid metabolic genes decreased carotenoid content, thus stimulating FB1 biosynthesis in F. verticillioides. Taken together, our results provide valuable insights into how the Med1 LxxLL motif regulates FB1 biosynthesis in the mycotoxigenic fungus F. verticillioides.

MED19 encodes two unique protein isoforms that confer prostate cancer growth under low androgen through distinct gene expression programs

MED19, a component of the mediator complex and a co-regulator of the androgen receptor (AR), is pivotal in prostate cancer cell proliferation. MED19 has two isoforms: a full-length "canonical" and a shorter "alternative" variant. Specific antibodies were developed to investigate these isoforms. Both exhibit similar expression in normal prostate development and adult prostate tissue, but the canonical isoform is elevated in prostate adenocarcinomas. Overexpression of canonical MED19 in LNCaP cells promotes growth under conditions of androgen deprivation in vitro and in vivo, mirroring earlier findings with alternative MED19-overexpressing LNCaP cells. Interestingly, alternative MED19 cells displayed strong colony formation in clonogenic assays under conditions of androgen deprivation, while canonical MED19 cells did not, suggesting distinct functional roles. These isoforms also modulated gene expression differently. Canonical MED19 triggered genes related to extracellular matrix remodeling while suppressing those involved in androgen-inactivating glucuronidation. In contrast, alternative MED19 elevated genes tied to cell movement and reduced those associated with cell adhesion and differentiation. The ratio of MED19 isoform expression in prostate cancers shifts with the disease stage. Early-stage cancers exhibit higher canonical MED19 expression than alternative MED19, consistent with canonical MED19's ability to promote cell proliferation under androgen deprivation. Conversely, alternative MED19 levels were higher in later-stage metastatic prostate cancer than in canonical MED19, reflecting alternative MED19's capability to enhance cell migration and autonomous cell growth. Our findings suggest that MED19 isoforms play unique roles in prostate cancer progression and highlights MED19 as a potential therapeutic target for both early and late-stage prostate cancer.

Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding

The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied "dark" members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the evolutionary and functional context encoded in knowledge graphs (KGs) to predict protein and pathway associations for understudied kinases. We propose a new scalable graph embedding approach, RegPattern2Vec, which employs regular pattern constrained random walks to sample diverse aspects of node context within a KG flexibly. RegPattern2Vec learns functional representations of kinases, interacting partners, post-translational modifications, pathways, cellular localization, and chemical interactions from a kinase-centric KG that integrates and conceptualizes data from curated heterogeneous data resources. By contextualizing information relevant to prediction, RegPattern2Vec improves accuracy and efficiency in comparison to other random walk-based graph embedding approaches. We show that the predictions produced by our model overlap with pathway enrichment data produced using experimentally validated Protein-Protein Interaction (PPI) data from both publicly available databases and experimental datasets not used in training. Our model also has the advantage of using the collected random walks as biological context to interpret the predicted protein-pathway associations. We provide high-confidence pathway predictions for 34 dark kinases and present three case studies in which analysis of meta-paths associated with the prediction enables biological interpretation. Overall, RegPattern2Vec efficiently samples multiple node types for link prediction on biological knowledge graphs and the predicted associations between understudied kinases, pseudokinases, and known pathways serve as a conceptual starting point for hypothesis generation and testing.

Assessing the Link between Diabetic Metabolic Dysregulation and Breast Cancer Progression

Diabetes mellitus is a burdensome disease that affects various cellular functions through altered glucose metabolism. Several reports have linked diabetes to cancer development; however, the exact molecular mechanism of how diabetes-related traits contribute to cancer progression is not fully understood. The current study aimed to explore the molecular mechanism underlying the potential effect of hyperglycemia combined with hyperinsulinemia on the progression of breast cancer cells. To this end, gene dysregulation induced by the exposure of MCF7 breast cancer cells to hyperglycemia (HG), or a combination of hyperglycemia and hyperinsulinemia (HGI), was analyzed using a microarray gene expression assay. Hyperglycemia combined with hyperinsulinemia induced differential expression of 45 genes (greater than or equal to two-fold), which were not shared by other treatments. On the other hand, in silico analysis performed using a publicly available dataset (GEO: GSE150586) revealed differential upregulation of 15 genes in the breast tumor tissues of diabetic patients with breast cancer when compared with breast cancer patients with no diabetes. SLC26A11, ALDH1A3, MED20, PABPC4 and SCP2 were among the top upregulated genes in both microarray data and the in silico analysis. In conclusion, hyperglycemia combined with hyperinsulinemia caused a likely unique signature that contributes to acquiring more carcinogenic traits. Indeed, these findings might potentially add emphasis on how monitoring diabetes-related metabolic alteration as an adjunct to diabetes therapy is important in improving breast cancer outcomes. However, further detailed studies are required to decipher the role of the highlighted genes, in this study, in the pathogenesis of breast cancer in patients with a different glycemic index.

Genetically Engineered Mice Unveil In Vivo Roles of the Mediator Complex

The Mediator complex is a multi-subunit protein complex which plays a significant role in the regulation of eukaryotic gene transcription. It provides a platform for the interaction of transcriptional factors and RNA polymerase II, thus coupling external and internal stimuli with transcriptional programs. Molecular mechanisms underlying Mediator functioning are intensively studied, although most often using simple models such as tumor cell lines and yeast. Transgenic mouse models are required to study the role of Mediator components in physiological processes, disease, and development. As constitutive knockouts of most of the Mediator protein coding genes are embryonically lethal, conditional knockouts and corresponding activator strains are needed for these studies. Recently, they have become more easily available with the development of modern genetic engineering techniques. Here, we review existing mouse models for studying the Mediator, and data obtained in corresponding experiments.

Mediator complex subunit 8 is a prognostic biomarker in hepatocellular carcinoma

BACKGROUND

Mediator complex subunit 8 (MED8) is known for its role in encoding a subunit of the mediator complex (MED), that is critical for transcription. MED8 is significantly expressed in various tumors and has been correlated with an unfavorable prognosis. Nevertheless, no relationships have been found between MED8 and the clinical characteristics of hepatocellular carcinoma (HCC).

METHODS

To conduct an evaluation of correlations between clinicopathologic characteristics and MED8 expression, the logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test were used. To perform analysis of factors contributing to prognosis, the Kaplan-Meier approach and the Cox regression analyses were used. A nomogram on the basis of a Cox multivariate analysis was employed to anticipate the influence of MED8 on patient prognosis. The receiver operating characteristic (ROC) curves were plotted and the areas under the curve (AUC) were calculated to assess the prognostic value of MED8. Both immune infiltration analysis and Gene Set Enrichment Analysis (GSEA) were applied to reveal significant enrichment differences among TCGA data. Quantitative RT-PCR (qRT-PCR) and western blotting were used to verify the difference in the expression of MED8 in normal and hepatocellular carcinoma cells. The immunohistochemical method was used to validate the MED8 expression in tumor and adjoining tissues of HCC patients.

RESULTS

A univariate analysis showed that high MED8 expression predicts poor disease-specific survival (DSS) (HR: 2.57; 95% confidence interval (CI) 1.62, 4.07; P<0.001). Multivariate regression analysis showed that high MED8 (adjusted HR: 3.032 (1.817, 5.060); P<0.001) expression and M stage (adjusted HR=4.075 (1.179-14.091) for M1 vs. M0, P=0.026) served as prognostic indicators of unfavorable overall survival in an independent manner in patients with HCC. The C-index for the nomogram was 0.732 (95% CI: 0.698, 0.766) and the AUC of MED8 was 0.817 (95% CI: 0.778, 0.857). Functional analysis showed that the cell cycle checkpoints, p53 dependent G1-DNA damage response, mitotic G1-G1-S phases, and mitotic G2-G2-M phases, were significantly enriched in DEGs associated with MED8 expression. Th2 cells were positively correlated with MED8 expression.

CONCLUSIONS

MED8 predicts poor prognosis in HCC, possibly through modulating the cell cycle and Th2 cells.

MED10 Drives the Oncogenicity and Refractory Phenotype of Bladder Urothelial Carcinoma Through the Upregulation of hsa-miR-590

Background

Dysfunctional transcription machinery with associated dysregulated transcription characterizes many malignancies. Components of the mediator complex, a principal modulator of transcription, are increasingly implicated in cancer. The mediator complex subunit 10 (MED10), a vital kinase module of the mediator, plays a critical role in bladder physiology and pathology. However, its role in the oncogenicity, metastasis, and disease recurrence in bladder cancer (BLCA) remains unclear.

Objective

Thus, we investigated the role of dysregulated or aberrantly expressed MED10 in the enhanced onco-aggression, disease progression, and recurrence of bladder urothelial carcinoma (UC), as well as the underlying molecular mechanism.

Methods

Using an array of multi-omics big data analyses of clinicopathological data, in vitro expression profiling and functional assays, and immunocytochemical staining, we assessed the probable roles of MED10 in the progression and prognosis of BLCA/UC.

Results

Our bioinformatics-aided gene expression profiling showed that MED10 is aberrantly expressed in patients with BLCA, is associated with high-grade disease, is positively correlated with tumor stage, and confers significant survival disadvantage. Reanalyzing the TCGA BLCA cohort (n = 454), we showed that aberrantly expressed MED10 expression is associated with metastatic and recurrent disease, disease progression, immune suppression, and therapy failure. Interestingly, we demonstrated that MED10 interacts with and is co-expressed with the microRNA, hsa-miR-590, and that CRISPR-mediated knockout of MED10 elicits the downregulation of miR-590 preferentially in metastatic UC cells, compared to their primary tumor peers. More so, silencing MED10 in SW1738 and JMSU1 UC cell lines significantly attenuates their cell proliferation, migration, invasion, clonogenicity, and tumorsphere formation (primary and secondary), with the associated downregulation of BCL-xL, MKI67, VIM, SNAI1, OCT4, and LIN28A but upregulated BAX protein expression. In addition, we showed that high MED10 expression is a non-inferior biomarker of urothelial recurrence compared with markers of cancer stemness; however, MED10 is a better biomarker of local recurrence than any of the stemness markers.

Conclusion

These data provide preclinical evidence that dysregulated MED10/MIR590 signaling drives onco-aggression, disease progression, and recurrence of bladder UC and that this oncogenic signal is therapeutically actionable for repressing the metastatic/recurrent phenotypes, enhancing therapy response, and shutting down stemness-driven disease progression and relapse in patients with BLCA/UC.

Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma

Lipid metabolism has been associated with progression of various cancers. However, the underlying mechanisms of the impact of lipid metabolism-associated genes (LMAGs) on the tumor immune microenvironment have not been well-elucidated. This study aimed to determine the effects of lipid metabolism on the progression and development of hepatocellular carcinoma (HCC). Expression profiles and clinical data of 371 and 231 patients with HCC were obtained from the TCGA and Internal Cancer Genome Consortium (ICGC) databases, respectively. Using Cox regression and LASSO regression analyses, a prognostic risk model was constructed based on the LMAG data. The tumor mutation burden (TMB), immune cell infiltration levels, and immune response checkpoints of the identified risk groups were determined and compared. A total of two clusters were identified based on the LMAG expression, showing significant differences in tumor stage and immune cell infiltration. A prognostic risk model based on four LMAGs was constructed and proven to have a significant prognostic value. The 1-, 3-, and 5-year survival rates in the high-risk group were 62.2%, 20.5%, and 8.1%, respectively, whereas those in the low-risk group were 78.9%, 28.1%, and 13.5%, respectively. The survival differences between the two risk groups were likely associated with TP53 mutation status, TMB score, degree of immunocyte infiltration, and immune checkpoint level. Likewise, the expression level of every LMAG included in the model had the same effect on the overall survival and immune cell infiltration levels. More importantly, the prognostic value of the signature was verified in an independent ICGC cohort. Thus, the expression levels of LMAGs are closely related to the tumor microenvironment in HCC and may serve as promising biological indicators for prognosis and immune therapy in patients with HCC.

Diverse role of androgen action in human breast cancer

Breast cancer is a hormone-dependent cancer, and sex steroids play a pivotal role in breast cancer progression. Estrogens are strongly associated with breast cancers, and the estrogen receptor (estrogen receptor α; ERα) is expressed in 70-80% of human breast carcinoma tissues. Although antiestrogen therapies (endocrine therapies) have significantly improved clinical outcomes in ERα-positive breast cancer patients, some patients experience recurrence after treatment. In addition, patients with breast carcinoma lacking ERα expression do not benefit from endocrine therapy. The androgen receptor (AR) is also expressed in >70% of breast carcinoma tissues. Growing evidence supports this novel therapeutic target for the treatment of triple-negative breast cancers that lack ERα, progesterone receptor, and human EGF receptor 2, and ERα-positive breast cancers, which are resistant to conventional endocrine therapy. However, the clinical significance of AR expression is still controversial and the biological function of androgens in breast cancers is unclear. In this review, we focus on the recent findings concerning androgen action in breast cancers and the contributions of androgens to improved breast cancer therapy.

HNRNPA2B1 regulates tamoxifen- and fulvestrant-sensitivity and hallmarks of endocrine resistance in breast cancer cells

Despite new combination therapies improving survival of breast cancer patients with estrogen receptor α (ER+) tumors, the molecular mechanisms for endocrine-resistant disease remain unresolved. Previously we demonstrated that expression of the RNA binding protein and N6-methyladenosine (m6A) reader HNRNPA2B1 (A2B1) is higher in LCC9 and LY2 tamoxifen (TAM)-resistant ERα breast cancer cells relative to parental TAM-sensitive MCF-7 cells. Here we report that A2B1 protein expression is higher in breast tumors than paired normal breast tissue. Modest stable overexpression of A2B1 in MCF-7 cells (MCF-7-A2B1 cells) resulted in TAM- and fulvestrant- resistance whereas knockdown of A2B1 in LCC9 and LY2 cells restored TAM and fulvestrant, endocrine-sensitivity. MCF-7-A2B1 cells gained hallmarks of TAM-resistant metastatic behavior: increased migration and invasion, clonogenicity, and soft agar colony size, which were attenuated by A2B1 knockdown in MCF-7-A2B1 and the TAM-resistant LCC9 and LY2 cells. MCF-7-A2B1, LCC9, and LY2 cells have a higher proportion of CD44+/CD24-/low cancer stem cells (CSC) compared to MCF-7 cells. MCF-7-A2B1 cells have increased ERα and reduced miR-222-3p that targets ERα. Like LCC9 cells, MCF-7-A2B1 have activated AKT and MAPK that depend on A2B1 expression and are growth inhibited by inhibitors of these pathways. These data support that targeting A2B1 could provide a complimentary therapeutic approach to reduce acquired endocrine resistance.

MedProDB: A database of Mediator proteins

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Mediator complex is a key component of transcriptional regulation in eukaryotes.

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Identification of Mediator subunits was done by using computational approaches.

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Different physicochemical properties, and functions of Mediators were discussed.

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We have developed first database of Mediator proteins e.g. MedProDB.

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MedProDB contains different types of search and browse options, and various tools.

In the last three decades, the multi-subunit Mediator complex has emerged as the key component of transcriptional regulation of eukaryotic gene expression. Although there were initial hiccups, recent advancements in bioinformatics tools contributed significantly to in-silico prediction and characterization of Mediator subunits from several organisms belonging to different eukaryotic kingdoms. In this study, we have developed the first database of Mediator proteins named MedProDB with 33,971 Mediator protein entries. Out of those, 12531, 11545, and 9895 sequences belong to metazoans, plants, and fungi, respectively. Apart from the core information consisting of sequence, length, position, organism, molecular weight, and taxonomic lineage, additional information of each Mediator sequence like aromaticity, hydropathy, instability index, isoelectric point, functions, interactions, repeat regions, diseases, sequence alignment to Mediator subunit family, Intrinsically Disordered Regions (IDRs), Post-translation modifications (PTMs), and Molecular Recognition Features (MoRFs) may be of high utility to the users. Furthermore, different types of search and browse options with four different tools namely BLAST, Smith-Waterman Align, IUPred, and MoRF-Chibi_Light are provided at MedProDB to perform different types of analysis. Being a critical component of the transcriptional machinery and regulating almost all the aspects of transcription, it generated lots of interest in structural and functional studies of Mediator functioning. So, we think that the MedProDB database will be very useful for researchers studying the process of transcription. This database is freely available at www.nipgr.ac.in/MedProDB.

Loss of Mediator complex subunit 13 (MED13) promotes resistance to alkylation through cyclin D1 upregulation

Alkylating drugs are among the most often used chemotherapeutics. While cancer cells frequently develop resistance to alkylation treatments, detailed understanding of mechanisms that lead to the resistance is limited. Here, by using genome-wide CRISPR-Cas9 based screen, we identify transcriptional Mediator complex subunit 13 (MED13) as a novel modulator of alkylation response. The alkylation exposure causes significant MED13 downregulation, while complete loss of MED13 results in reduced apoptosis and resistance to alkylating agents. Transcriptome analysis identified cyclin D1 (CCND1) as one of the highly overexpressed genes in MED13 knock-out (KO) cells, characterized by shorter G1 phase. MED13 is able to bind to CCND1 regulatory elements thus influencing the expression. The resistance of MED13 KO cells is directly dependent on the cyclin D1 overexpression, and its down-regulation is sufficient to re-sensitize the cells to alkylating agents. We further demonstrate the therapeutic potential of MED13-mediated response, by applying combinatory treatment with CDK8/19 inhibitor Senexin A. Importantly, the treatment with Senexin A stabilizes MED13, and in combination with alkylating agents significantly reduces viability of cancer cells. In summary, our findings identify novel alkylation stress response mechanism dependent on MED13 and cyclin D1 that can serve as basis for development of innovative therapeutic strategies.

Development of a novel lipid metabolism-based risk score model in hepatocellular carcinoma patients

Background

Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75–85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis.

Methods

We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model.

Results

We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis.

Conclusions

We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.

Molecular determinants of MED1 interaction with the DNA bound VDR-RXR heterodimer

The MED1 subunit of the Mediator complex is an essential coactivator of nuclear receptor-mediated transcriptional activation. While structural requirements for ligand-dependent binding of classical coactivator motifs of MED1 to numerous nuclear receptor ligand-binding domains have been fully elucidated, the recognition of the full-length or truncated coactivator by full nuclear receptor complexes remain unknown. Here we present structural details of the interaction between a large part of MED1 comprising its structured N-terminal and the flexible receptor-interacting domains and the mutual heterodimer of the vitamin D receptor (VDR) and the retinoid X receptor (RXR) bound to their cognate DNA response element. Using a combination of structural and biophysical methods we show that the ligand-dependent interaction between VDR and the second coactivator motif of MED1 is crucial for complex formation and we identify additional, previously unseen, interaction details. In particular, we identified RXR regions involved in the interaction with the structured N-terminal domain of MED1, as well as VDR regions outside the classical coactivator binding cleft affected by coactivator recruitment. These findings highlight important roles of each receptor within the heterodimer in selective recognition of MED1 and contribute to our understanding of the nuclear receptor-coregulator complexes.

HIF1α and p53 Regulated MED30, a Mediator Complex Subunit, is Involved in Regulation of Glioblastoma Pathogenesis and Temozolomide Resistance

Glioblastoma (GBM) is the most common, malignant, and aggressive form of glial cell cancer with unfavorable clinical outcomes. It is believed that a better understanding of the mechanisms of gene deregulation may lead to novel therapeutic approaches for this yet incurable cancer. Mediator complex is a crucial component of enhancer-based gene expression and works as a transcriptional co-activator. Many of the mediator complex subunits are found to be deregulated/mutated in various malignancies; however, their status and role in GBM remains little studied. We report that MED30, a core subunit of the head module, is overexpressed in GBM tissues and cell lines. MED30 was found to be induced by conditions present in the tumor microenvironment such as hypoxia, serum, and glucose deprivation. MED30 harbors hypoxia response elements (HREs) and p53 binding site in its promoter and is induced in a HIF1α and p53 dependent manner. Further, MED30 levels also significantly positively correlated with p53 and HIF1α levels in GBM tissues. Using both MED30 overexpression and knockdown approach, we show that MED30 promotes cell proliferation while reduces the migration capabilities in GBM cell lines. Notably, MED30 was also found to confer sensitivity to chemodrug, temozolomide, in GBM cells and modulate the level of p53 in vitro. Overall, this is the first report showing MED30 overexpression in GBM and its involvement in GBM pathogenesis suggesting its diagnostic and therapeutic potential urging the need for further systematic exploration of MED30 interactome and target networks.

Understanding Obesity as a Risk Factor for Uterine Tumors Using Drosophila

Multiple large-scale epidemiological studies have identified obesity as an important risk factor for a variety of human cancers, particularly cancers of the uterus, gallbladder, kidney, liver, colon, and ovary, but there is much uncertainty regarding how obesity increases the cancer risks. Given that obesity has been consistently identified as a major risk factor for uterine tumors, the most common malignancies of the female reproductive system, we use uterine tumors as a pathological context to survey the relevant literature and propose a novel hypothesis: chronic downregulation of the cyclin-dependent kinase 8 (CDK8) module, composed of CDK8 (or its paralog CDK19), Cyclin C, MED12 (or MED12L), and MED13 (or MED13L), by elevated insulin or insulin-like growth factor signaling in obese women may increase the chances to dysregulate the activities of transcription factors regulated by the CDK8 module, thereby increasing the risk of uterine tumors. Although we focus on endometrial cancer and uterine leiomyomas (or fibroids), two major forms of uterine tumors, our model may offer additional insights into how obesity increases the risk of other types of cancers and diseases. To illustrate the power of model organisms for studying human diseases, here we place more emphasis on the findings obtained from Drosophila melanogaster.