Dual effects of TGF-β on ERα-mediated estrogenic transcriptional activity in breast cancer

<p>Abstract</p> <p>Background</p> <p>TGF-β resistance often develops in breast cancer cells that in turn overproduce this cytokine to create a local immunosuppressive environment that fosters tumor growth and exacerbates the invasive and metastatic behavior of the tumor cells themselves. Smads-mediated cross-talk with the estrogen receptor has been implied to play an important role in development and/or progression of breast cancer. We investigated how TGF-β regulates ERα-induced gene transcription and potential mechanisms of frequent TGF-β resistance in breast cancer.</p> <p>Methods</p> <p>Effect of TGF-β on ERα-mediated gene transcription was investigated in breast cancer cell lines using transient transfection, real-time PCR, sequential DNA precipitation, and small interfering RNA assays. The expression of Smads on both human breast cancer cell lines and ERα-positive human breast cancer tissue was evaluated by immunofluorescence and immunohistochemical assays.</p> <p>Results</p> <p>A complex of Smad3/4 mediates TGF-β inhibition of ERα-mediated estrogenic activity of gene transcription in breast cancer cells, and Smad4 is essential and sufficient for such repression. Either overexpression of Smad3 or inhibition of Smad4 leads to the "switch" of TGF-β from a repressor to an activator. Down-regulation and abnormal cellular distribution of Smad4 were associated with some ERα-positive infiltrating human breast carcinoma. There appears a dynamic change of Smad4 expression from benign breast ductal tissue to infiltrating ductal carcinoma.</p> <p>Conclusion</p> <p>These results suggest that aberrant expression of Smad4 or disruption of Smad4 activity lead to the loss of TGF-β suppression of ERα transactivity in breast cancer cells.</p

2D, 3D-QSAR study and docking of vascular endothelial growth factor receptor 3 (VEGFR3) inhibitors for potential treatment of retinoblastoma

Background: Retinoblastoma is currently the most common malignant tumor seen in newborns and children’s eyes worldwide, posing a life-threatening hazard. Chemotherapy is an integral part of retinoblastoma treatment. However, the chemotherapeutic agents used in clinics often lead to drug resistance. Thus there is a need to investigate new chemotherapy-targeted agents. VEGFR3 inhibitors are anti-tumour-growth and could be used to develop novel retinoblastoma-targeted agents.Objective: To predict drug activity, discover influencing factors and design new drugs by building 2D, 3D-QSAR models.Method: First, linear and non-linear QSAR models were built using heuristic methods and gene expression programming (GEP). The comparative molecular similarity indices analysis (COMISA) was then used to construct 3D-QSAR models through the SYBYL software. New drugs were designed by changing drug activity factors in both models, and molecular docking experiments were performed.Result: The best linear model created using HM had an R2, S2, and R2cv of 0.82, 0.02, and 0.77, respectively. For the training and test sets, the best non-linear model created using GEP had correlation coefficients of 0.83 and 0.72 with mean errors of 0.02 and 0.04. The 3D model designed using SYBYL passed external validation due to its high Q2 (0.503), R2 (0.805), and F-value (76.52), as well as its low standard error of SEE value (0.172). This demonstrates the model’s reliability and excellent predictive ability. Based on the molecular descriptors of the 2D model and the contour plots of the 3D model, we designed 100 new compounds using the best active compound 14 as a template. We performed activity prediction and molecular docking experiments on them, in which compound 14.d performed best regarding combined drug activity and docking ability.Conclusion: The non-linear model created using GEP was more stable and had a more substantial predictive power than the linear model built using the heuristic technique (HM). The compound 14.d designed in this experiment has the potential for anti-retinoblastoma treatment, which provides new design ideas and directions for retinoblastoma-targeted drugs

Identification of loci affecting teat number by genome-wide association studies on three pig populations

Objective Three genome-wide association studies (GWAS) and a meta-analysis of GWAS were conducted to explore the genetic mechanisms underlying variation in pig teat number. Methods We performed three GWAS and a meta-analysis for teat number on three pig populations, including a White Duroc×Erhualian F2 resource population (n = 1,743), a Chinese Erhualian pig population (n = 320) and a Chinese Sutai pig population (n = 383). Results We detected 24 single nucleotide polymorphisms (SNPs) that surpassed the genome-wide significant level on Sus Scrofa chromosomes (SSC) 1, 7, and 12 in the F2 resource population, corresponding to four loci for pig teat number. We highlighted vertnin (VRTN) and lysine demethylase 6B (KDM6B) as two interesting candidate genes at the loci on SSC7 and SSC12. No significant associated SNPs were identified in the meta-analysis of GWAS. Conclusion The results verified the complex genetic architecture of pig teat number. The causative variants for teat number may be different in the three population

HTMC: hierarchical tolerance mask correspondence for human body point cloud registration

Point cloud registration can be solved by searching for correspondence pairs. Searching for correspondence pairs in human body point clouds poses some challenges, including: (1) the similar geometrical shapes of the human body are difficult to distinguish. (2) The symmetry of the human body confuses the correspondence pairs searching. To resolve the above issues, this article proposes a Hierarchical Tolerance Mask Correspondence (HTMC) method to achieve better alignment by tolerating obfuscation. First, we define various levels of correspondence pairs and assign different similarity scores for each level. Second, HTMC designs a tolerance loss function to tolerate the obfuscation of correspondence pairs. Third, HTMC uses a differentiable mask to diminish the influence of non-overlapping regions and enhance the influence of overlapping regions. In conclusion, HTMC acknowledges the presence of similar local geometry in human body point clouds. On one hand, it avoids overfitting caused by forcibly distinguishing similar geometries, and on the other hand, it prevents genuine correspondence relationships from being masked by similar geometries. The codes are available at https://github.com/ChenPointCloud/HTMC

Dual effects of TGF-beta on ERalpha-mediated estrogenic transcriptional activity in breast cancer

Abstract Background TGF-β resistance often develops in breast cancer cells that in turn overproduce this cytokine to create a local immunosuppressive environment that fosters tumor growth and exacerbates the invasive and metastatic behavior of the tumor cells themselves. Smads-mediated cross-talk with the estrogen receptor has been implied to play an important role in development and/or progression of breast cancer. We investigated how TGF-β regulates ERα-induced gene transcription and potential mechanisms of frequent TGF-β resistance in breast cancer. Methods Effect of TGF-β on ERα-mediated gene transcription was investigated in breast cancer cell lines using transient transfection, real-time PCR, sequential DNA precipitation, and small interfering RNA assays. The expression of Smads on both human breast cancer cell lines and ERα-positive human breast cancer tissue was evaluated by immunofluorescence and immunohistochemical assays. Results A complex of Smad3/4 mediates TGF-β inhibition of ERα-mediated estrogenic activity of gene transcription in breast cancer cells, and Smad4 is essential and sufficient for such repression. Either overexpression of Smad3 or inhibition of Smad4 leads to the "switch" of TGF-β from a repressor to an activator. Down-regulation and abnormal cellular distribution of Smad4 were associated with some ERα-positive infiltrating human breast carcinoma. There appears a dynamic change of Smad4 expression from benign breast ductal tissue to infiltrating ductal carcinoma. Conclusion These results suggest that aberrant expression of Smad4 or disruption of Smad4 activity lead to the loss of TGF-β suppression of ERα transactivity in breast cancer cells

Global Investigation of Cytochrome P450 Genes in the Chicken Genome

Cytochrome P450 (CYP) superfamily enzymes are broadly involved in a variety of physiological and toxicological processes. However, genome-wide analysis of this superfamily has never been investigated in the chicken genome. In this study, genome-wide analyses identified 45 chicken CYPs (cCYPs) from the chicken genome, and their classification and evolutionary relationships were investigated by phylogenetic, conserved protein motif, and gene structure analyses. The comprehensive evolutionary data revealed several remarkable characteristics of cCYPs, including the highly divergent and rapid evolution of the cCYPs, and the loss of cCYP2AF in the chicken genome. Furthermore, the cCYP expression profile was investigated by RNA-sequencing. The differential expression of cCYPs in developing embryos revealed the involvement of cCYPs in embryonic development. The significantly regulated cCYPs suggested its potential role in hepatic metabolism. Additionally, 11 cCYPs, including cCYP2AC1, cCYP2C23a, and cCYP2C23b, were identified as estrogen-responsive genes, which indicates that these cCYPs are involved in the estrogen-signaling pathway. Meanwhile, an expression profile analysis highlights the divergent role of different cCYPs. These data expand our view of the phylogeny and evolution of cCYPs, provide evolutionary insight, and can help elucidate the roles of cCYPs in physiological and toxicological processes in chicken

Altered effective connectivity patterns of the default mode network in Alzheimer's disease: An fMRI study

The aim of this work is to investigate the differences of effective connectivity of the default mode network (DMN) in Alzheimer's disease (AD) patients and normal controls (NC). The technique of independent component analysis (ICA) was applied to identify DMN components and multivariate Granger causality analysis (mGCA) was used to explore an effective connectivity pattern. We found that: (i) connections in AD were decreased than those in NC, in terms of intensity and quantity. Posterior cingulated cortex (PCC) exhibited significant activity in NC as it connected with most of the other regions within the DMN. Besides, the PCC was the convergence center which only received interactions from other regions; (ii) right inferior temporal cortex (rITC) in the NC exhibited stronger interactions with other regions within the DMN compared with AD patients; and (iii) interactions between medial prefrontal cortex (MPFC) and bilateral inferior parietal cortex (IPC) in the NC were weaker than those in AD patients. These findings may implicate a brain dysfunction in AD patients and reveal more pathophysiological characteristics of AD