Immune predictors of response to immune checkpoint inhibitors in mismatch repair-deficient endometrial cancer.

BACKGROUND: Patients with mismatch repair-deficient (MMRd) endometrial cancer (EC) can derive great benefit from immune checkpoint inhibitors (ICI). However not all responses and predictors of primary resistance are lacking. METHODS: We compared the immune tumor microenvironment of MMRd EC ICI-responders (Rs) and ICI non-responders (NRs), using spatial multiplexed immune profiling and unsupervised hierarchical clustering analysis. RESULTS: Overall, NRs exhibited drastically lower CD8+, absent terminally differentiated T cells, lack of mature tertiary lymphoid structures and dendritic cells, as well as loss of human leukocyte antigen class I. However, no single marker could predict R versus NR with confidence. Clustering analysis identified a combination of four immune features that demonstrated that accurately predicted ICI response, with a discriminative power of 92%. Finally, 80% of NRs lacked programmed death-ligand 1, however, 60% exhibited another actionable immune checkpoint (T-cell immunoglobulin and mucin containing protein-3, indoleamine 2,3-dioxygenase 1, or lymphocyte activation gene 3). CONCLUSIONS: These findings underscore the potential of immune tumor microenvironment features for identifying patients with MMRd EC and primary resistance to ICI who should be oriented towards trials testing novel immunotherapeutic combinations.

Aberrant methylation and expression of TNXB promote chondrocyte apoptosis and extracullar matrix degradation in hemophilic arthropathy via AKT signaling.

Recurrent joint bleeding in hemophilia patients frequently causes hemophilic arthropathy (HA). Drastic degradation of cartilage is a major characteristic of HA, but its pathological mechanisms has not yet been clarified. In HA cartilages, we found server matrix degradation and increased expression of DNA methyltransferase proteins. We thus performed genome-wide DNA methylation analysis on human HA (N=5) and osteoarthritis (OA) (N=5) articular cartilages, and identified 1228 differentially methylated regions (DMRs) associated with HA. Functional enrichment analyses revealed the association between DMR genes (DMGs) and extracellular matrix (ECM) organization. Among these DMGs, Tenascin XB (TNXB) expression was down-regulated in human and mouse HA cartilages. The loss of Tnxb in F8-/- mouse cartilage provided a disease-promoting role in HA by augmenting cartilage degeneration and subchondral bone loss. Tnxb knockdown also promoted chondrocyte apoptosis and inhibited phosphorylation of AKT. Importantly, AKT agonist showed chondroprotective effects following Tnxb knockdown. Together, our findings indicate that exposure of cartilage to blood leads to alterations in DNA methylation, which is functionally related to ECM homeostasis, and further demonstrate a critical role of TNXB in HA cartilage degeneration by activating AKT signaling. These mechanistic insights allow development of potentially new strategies for HA cartilage protection.

Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy.

PURPOSE: This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes. EXPERIMENTAL DESIGN: Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322). RESULTS: Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent. CONCLUSIONS: Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1-resistant malignancy.

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions' correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.

Dnmt3b ablation affects fracture repair process by regulating apoptosis.

PURPOSE: Previous studies have shown that DNA methyltransferase 3b (Dnmt3b) is the only Dnmt responsive to fracture repair and Dnmt3b ablation in Prx1-positive stem cells and chondrocyte cells both delayed fracture repair. Our study aims to explore the influence of Dnmt3b ablation in Gli1-positive stem cells in fracture healing mice and the underlying mechanism. METHODS: We generated Gli1-CreERT2; Dnmt3bflox/flox (Dnmt3bGli1ER) mice to operated tibia fracture. Fracture callus tissues of Dnmt3bGli1ER mice and control mice were collected and analyzed by X-ray, micro-CT, biomechanical testing, histopathology and TUNEL assay. RESULTS: The cartilaginous callus significantly decrease in ablation of Dnmt3b in Gli1-positive stem cells during fracture repair. The chondrogenic and osteogenic indicators (Sox9 and Runx2) in the fracture healing tissues in Dnmt3bGli1ER mice much less than control mice. Dnmt3bGli1ER mice led to delayed bone callus remodeling and decreased biomechanical properties of the newly formed bone during fracture repair. Both the expressions of Caspase-3 and Caspase-8 were upregulated in Dnmt3bGli1ER mice as well as the expressions of BCL-2. CONCLUSIONS: Our study provides an evidence that Dnmt3b ablation Gli1-positive stem cells can affect fracture healing and lead to poor fracture healing by regulating apoptosis to decrease chondrocyte hypertrophic maturation.

Protective effects of Shensuitongzhi formula on intervertebral disc degeneration via downregulation of NF-κB signaling pathway and inflammatory response.

Low back pain (LBP) is a common orthopedic disease over the world. Lumbar intervertebral disc degeneration (IDD) is regarded as an important cause of LBP. Shensuitongzhi formula (SSTZF) is a drug used in clinical treatment for orthopedic diseases. It has been found that SSTZF can have a good treatment for IDD. But the exact mechanism has not been clarified. The results showed that SSTZF protects against LSI-induced degeneration of cartilage endplates and intervertebral discs. Meanwhile, SSTZF treatment dramatically reduces the expression of inflammatory factor as well as the expression of catabolism protein and upregulates the expression of anabolism protein in LSI-induced mice. In addition, SSTZF delayed the progression of LSI-induced IDD via downregulation the level of NF-κB signaling key gene RELA and phosphorylation of key protein P65 in endplate chondrocytes. Our study has illustrated the treatment as well as the latent mechanism of SSTZF in IDD.

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA.

Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab-bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study.

BACKGROUND: Clinical benefits of atezolizumab plus bevacizumab (atezolizumab-bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and the development of biomarkers is needed to improve therapeutic strategies. The atezolizumab-bevacizumab response signature (ABRS), assessed by molecular biology profiling techniques, has been shown to be associated with progression-free survival after treatment initiation. The primary objective of our study was to develop an artificial intelligence (AI) model able to estimate ABRS expression directly from histological slides, and to evaluate if model predictions were associated with progression-free survival. METHODS: In this multicentre retrospective study, we developed a model (ABRS-prediction; ABRS-P), which was derived from the previously published clustering-constrained attention multiple instance learning (or CLAM) pipeline. We trained the model fit for regression analysis using a multicentre dataset from The Cancer Genome Atlas (patients treated by surgical resection, n=336). The ABRS-P model was externally validated on two independent series of samples from patients with hepatocellular carcinoma (a surgical resection series, n=225; and a biopsy series, n=157). The predictive value of the model was further tested in a series of biopsy samples from a multicentre cohort of patients with hepatocellular carcinoma treated with atezolizumab-bevacizumab (n=122). All samples in the study were from adults (aged ≥18 years). The validation sets were sampled between Jan 1, 2008, to Jan 1, 2023. For the multicentre validation set, the primary objective was to assess the association of high versus low ABRS-P values, defined relative to cross-validation median split thresholds in the first biopsy series, with progression-free survival after treatment initiation. Finally, we performed spatial transcriptomics and matched prediction heatmaps with in situ expression profiles. FINDINGS: Of the 840 patients sampled, 641 (76%) were male and 199 (24%) were female. Across the development and validation datasets, hepatocellular carcinoma risk factors included alcohol intake, hepatitis B and C virus infections, and non-alcoholic steatohepatitis. Using cross-validation in the development series, the mean Pearson's correlation between ABRS-P values and ABRS score (mean expression of ABRS genes) was r=0·62 (SD 0·09; mean p<0·0001, SD<0·0001). The ABRS-P generalised well on the external validation series (surgical resection series, r=0·60 [95% CI 0·51-0·68], p<0·0001; biopsy series, r=0·53 [0·40-0·63], p<0·0001). In the 122 patients treated with atezolizumab-bevacizumab, those with ABRS-P-high tumours (n=74) showed significantly longer median progression-free survival than those with ABRS-P-low tumours (n=48) after treatment initiation (12 months [95% CI 7-not reached] vs 7 months [4-9]; p=0·014). Spatial transcriptomics showed significantly higher ABRS score, along with upregulation of various other immune effectors, in tumour areas with high ABRS-P values versus areas with low ABRS-P values. INTERPRETATION: Our study indicates that AI applied on hepatocellular carcinoma digital slides is able to serve as a biomarker for progression-free survival in patients treated with atezolizumab-bevacizumab. This approach could be used in the development of inexpensive and fast biomarkers for targeted therapies. The combination of AI heatmaps with spatial transcriptomics provides insight on the molecular features associated with predictions. This methodology could be applied to other cancers or diseases and improve understanding of the biological mechanisms that drive responses to treatments. FUNDING: Institut National du Cancer, Fondation ARC, China Scholarship Council, Ligue Contre le Cancer du Val de Marne, Fondation de l'Avenir, Ipsen, and Fondation Bristol Myers Squibb Pour la Recherche en Immuno-Oncologie.

Glucocorticoid-induced activation of NOX/ROS/NF-κB signaling in MSCs contributes to the development of GONFH.

BACKGROUND: This study aimed to investigate the pathogenic factors of glucocorticoids (GCs)-induced osteonecrosis of the femoral head (GONFH) and its underlying pathogenesis in vivo and in vitro. METHODS: Radiographical (µCT) scanning, histopathological, immunohistochemical, reactive oxygen species (ROS) and tunel staining were conducted on GONFH patients and rats. ROS, tunel, flow cytometry, alkaline phosphatase, Oil red O staining, reverse transcription­quantitative PCR and western blotting were applied to elucidate the exact pathogenesis mechanism. RESULTS: Clinical and animal studies demonstrated increased levels of ROS, aggravated oxidative stress (OS) microenvironment, augmented apoptosis and imbalance in osteogenic/lipogenic in the GONFH group compared to the control group. The fate of mesenchymal stem cells (MSCs) directed by GCs is a crucial factor in determining GONFH. In vitro studies further revealed that GCs promote excessive ROS production through the expression of NOX family proteins, leading to a deterioration of the OS microenvironment in MSCs, ultimately resulting in apoptosis and imbalance in osteogenic/lipogenic differentiation. Furthermore, our results confirmed that the NOX inhibitor-diphenyleneiodonium chloride and the NF-κB inhibitor-BAY 11-7082 ameliorated apoptosis and osteogenic/lipogenic differentiation imbalance of MSCs induced by an excess of GCs. CONCLUSION: We demonstrated for the first time that the aggravation of the OS microenvironment in MSCs caused by high doses of GCs leading to apoptosis and differentiation imbalance is a crucial factor in the pathogenesis of GONFH, mediated through activating the NOX/ROS/NF-κB signaling pathway.

Glycyrrhizic acid alters the hyperoxidative stress-induced differentiation commitment of MSCs by activating the Wnt/ß-catenin pathway to prevent SONFH.

This study aimed to examine the in vivo and in vitro therapeutic effects of glycyrrhizic acid (GA) on steroid-induced osteonecrosis of the femoral head (SONFH), which is caused by the overuse of glucocorticoids (GCs). Clinically, we identified elevated oxidative stress (OS) levels and an imbalance in osteolipogenic homeostasis in SONFH patients compared to femoral neck fracture (FNF) patients. In vivo, we established experimental SONFH in rats via lipopolysaccharides (LPSs) combined with methylprednisolone (MPS). We showed that GA and Wnt agonist-S8320 alleviated SONFH, as evidenced by the reduced microstructural and histopathological alterations in the subchondral bone of the femoral head and the decreased levels of OS in rat models. In vitro, GA reduced dexamethasone (Dex)-induced excessive NOX4 and OS levels by activating the Wnt/ß-catenin pathway, thereby promoting the osteogenic differentiation of mesenchymal stem cells (MSCs) and inhibiting lipogenic differentiation. In addition, GA regulated the expression levels of the key transcription factors downstream of this pathway, Runx2 and PPARγ, thus maintaining osteolipogenic homeostasis. In summary, we demonstrated for the first time that GA modulates the osteolipogenic differentiation commitment of MSCs induced by excessive OS through activating the Wnt/ß-catenin pathway, thereby ameliorating SONFH.

18F-FDG PET as an imaging biomarker for the response to FGFR-targeted therapy of cancer cells via FGFR-initiated mTOR/HK2 axis.

Rationale: The overall clinical response to FGFR inhibitor (FGFRi) is far from satisfactory in cancer patients stratified by FGFR aberration, the current biomarker in clinical practice. A novel biomarker to evaluate the therapeutic response to FGFRi in a non-invasive and dynamic manner is thus greatly desired. Methods: Six FGFR-aberrant cancer cell lines were used, including four FGFRi-sensitive ones (NCI-H1581, NCI-H716, RT112 and Hep3B) and two FGFRi-resistant ones (primary for NCI-H2444 and acquired for NCI-H1581/AR). Cell viability and tumor xenograft growth analyses were performed to evaluate FGFRi sensitivities, accompanied by corresponding 18F-fluorodeoxyglucose (18F-FDG) uptake assay. mTOR/PLCγ/MEK-ERK signaling blockade by specific inhibitors or siRNAs was applied to determine the regulation mechanism. Results: FGFR inhibition decreased the in vitro accumulation of 18F-FDG only in four FGFRi-sensitive cell lines, but in neither of FGFRi-resistant ones. We then demonstrated that FGFRi-induced transcriptional downregulation of hexokinase 2 (HK2), a key factor of glucose metabolism and FDG trapping, via mTOR pathway leading to this decrease. Moreover, 18F-FDG PET imaging successfully differentiated the FGFRi-sensitive tumor xenografts from primary or acquired resistant ones by the tumor 18F-FDG accumulation change upon FGFRi treatment. Of note, both 18F-FDG tumor accumulation and HK2 expression could respond the administration/withdrawal of FGFRi in NCI-H1581 xenografts correspondingly. Conclusion: The novel association between the molecular mechanism (FGFR/mTOR/HK2 axis) and radiological phenotype (18F-FDG PET uptake) of FGFR-targeted therapy was demonstrated in multiple preclinical models. The adoption of 18F-FDG PET biomarker-based imaging strategy to assess response/resistance to FGFR inhibition may benefit treatment selection for cancer patients.

Case Report: First Documented Hip Arthroplasty on Chinese Patient with Ochronotic Arthropathy.

Alkaptonuria (AKU) is a rare autosomal recessive disorder caused by homogentisc acid (HGA) accumulation, the deposition of which in the joints usually causes ochronotic arthropathy. With no specific therapy for AKU currently, total joint arthroplasty in ochronotic arthropathy is applied to relieve the symptoms. A 63-year-old female patient came to our Orthopedic Surgery Department in 2019, complaining of severe limitation of movement and pain in the right hip for more than one year. A right total hip arthroplasy (THA) was performed due to the ineffective conservative therapy. At a follow-up of more than 15 months, the woman had full mobility with no complaining of pains. Since there is no relevant case reported about THA therapy for Chinese AKU patients, this report provides a feasible scheme, which makes clinical data more comprehensive.

Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology.

BACKGROUND & AIMS: Patients with hepatocellular carcinoma (HCC) displaying overexpression of immune gene signatures are likely to be more sensitive to immunotherapy, however, the use of such signatures in clinical settings remains challenging. We thus aimed, using artificial intelligence (AI) on whole-slide digital histological images, to develop models able to predict the activation of 6 immune gene signatures. METHODS: AI models were trained and validated in 2 different series of patients with HCC treated by surgical resection. Gene expression was investigated using RNA sequencing or NanoString technology. Three deep learning approaches were investigated: patch-based, classic MIL and CLAM. Pathological reviewing of the most predictive tissue areas was performed for all gene signatures. RESULTS: The CLAM model showed the best overall performance in the discovery series. Its best-fold areas under the receiver operating characteristic curves (AUCs) for the prediction of tumors with upregulation of the immune gene signatures ranged from 0.78 to 0.91. The different models generalized well in the validation dataset with AUCs ranging from 0.81 to 0.92. Pathological analysis of highly predictive tissue areas showed enrichment in lymphocytes, plasma cells, and neutrophils. CONCLUSION: We have developed and validated AI-based pathology models able to predict the activation of several immune and inflammatory gene signatures. Our approach also provides insights into the morphological features that impact the model predictions. This proof-of-concept study shows that AI-based pathology could represent a novel type of biomarker that will ease the translation of our biological knowledge of HCC into clinical practice. LAY SUMMARY: Immune and inflammatory gene signatures may be associated with increased sensitivity to immunotherapy in patients with advanced hepatocellular carcinoma. In the present study, the use of artificial intelligence-based pathology enabled us to predict the activation of these signatures directly from histology.

Discovery of Potent and Selective CDK9 Degraders for Targeting Transcription Regulation in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is highly aggressive with very limited treatment options due to the lack of efficient targeted therapies and thus still remains clinically challenging. Targeting transcription-associated cyclin-dependent kinases to remodel transcriptional regulation shows great promise in cancer therapy. Herein, we report the synthesis, optimization, and evaluation of new series of heterobifunctional molecules as highly selective and efficacious CDK9 degraders, enabling potent inhibition of TNBC cell growth and rapidly targeted degradation of CDK9. Moreover, the most potent CDK9 degrader (compound 45) induces cell apoptosis in vitro and inhibits tumor growth in the MDA-MB-231 TNBC model. Furthermore, the RNA-seq, immunohistochemistry assays demonstrate that the CDK9 degrader downregulates the downstream targets, such as MYC, at the transcriptional level, resulting apoptosis in TNBC cells. Our work establishes that 45 is a highly potent and efficacious CDK9 degrader for targeting transcription regulation, which represents an effective strategy and great potential as a new targeted therapy for TNBC.

Real-Time Structural Monitoring of the Multi-Point Hoisting of a Long-Span Converter Station Steel Structure.

In the process of using a long-span converter station steel structure, engineering disasters can easily occur. Structural monitoring is an important method to reduce hoisting risk. In previous engineering cases, the structural monitoring of long-span converter station steel structure hoisting is rare. Thus, no relevant hoisting experience can be referenced. Traditional monitoring methods have a small scope of application, making it difficult to coordinate monitoring and construction control. In the monitoring process, many problems arise, such as complicated installation processes, large-scale data processing, and large-scale installation errors. With a real-time structural monitoring system, the mechanical changes in the long-span converter station steel structure during the hoisting process can be monitored in real-time in order to achieve real-time warning of engineering disasters, timely identification of engineering issues, and allow for rapid decision-making, thus avoiding the occurrence of engineering disasters. Based on this concept, automatic monitoring and manual measurement of the mechanical changes in the longest long-span converter station steel structure in the world is carried out, and the monitoring results were compared with the corresponding numerical simulation results in order to develop a real-time structural monitoring system for the whole long-span converter station steel structure's multi-point lifting process. This approach collects the monitoring data and outputs the deflection, stress, strain, wind force, and temperature of the long-span converter station steel structure in real-time, enabling real-time monitoring to ensure the safety of the lifting process. This research offers a new method and basis for the structural monitoring of the multi-point hoisting of a long-span converter station steel structure.

Artificial intelligence for solid tumour diagnosis in digital pathology.

Tumour diagnosis relies on the visual examination of histological slides by pathologists through a microscope eyepiece. Digital pathology, the digitalization of histological slides at high magnification with slides scanners, has raised the opportunity to extract quantitative information due to image analysis. In the last decade, medical image analysis has made exceptional progress due to the development of artificial intelligence (AI) algorithms. AI has been successfully used in the field of medical imaging and more recently in digital pathology. The feasibility and usefulness of AI assisted pathology tasks have been demonstrated in the very last years and we can expect those developments to be applied to routine histopathology in the future. In this review, we will describe and illustrate this technique and present the most recent applications in the field of tumour histopathology. LINKED ARTICLES: This article is part of a themed issue on Molecular imaging - visual themed issue. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.21/issuetoc.

Integrated Strategy of Network Pharmacological Prediction and Experimental Validation Elucidate Possible Mechanism of Bu-Yang Herbs in Treating Postmenopausal Osteoporosis via ESR1.

Postmenopausal osteoporosis (PMOP) is a type of bone metabolism disease-related to estrogen deficiency with an increasing incidence. Traditional Chinese (TCM) has always been used and showed effectiveness in treating PMOP. In the current study, Bu-Yang herbs were considered to be the most frequently used and efficient TCM herbs in PMOP treatment. However, chemical and pharmacological profiles were not elucidated. Network pharmacology was conducted on representative Bu-Yang herbs (Yin-Yang-Huo. Du-Zhong, Bu-Gu-Zhi, Tu-Si-Zi) to investigate the mechanism of Bu-Yang herbs on PMOP. Chemical compounds, potential targets, and disease related genes were available from the corresponding database. Results showed that Bu-Yang herbs could interact with ESR1 and estrogen signaling pathways. For further validation, the Bu-Yang decoction (BYD), formula consisted of the above-mentioned 4 Bu-Yang herbs was presented for experimental validation. In vivo, BYD significantly reversed ovariectomy (OVX)-induced osteoporosis progress in a dose-dependent manner by up-regulation of bone mineral density and amelioration of bone microarchitecture. In vitro, BYD dramatically improved the proliferation and mineral nodules formation of osteoblasts. Both in vitro and in vivo results illustrated that the phenotype change induced by BYD is correlated with up-regulated of ESR1 and activation of the ß-catenin pathway. Meanwhile, inhibition of ESR1 by ICI182, 780 blocked the osteogenic phenotype and ß-catenin pathway activation induced by BYD. In conclusion, the current study suggested that Bu-Yang herbs are the most useful TCM herbs in treating PMOP. Furthermore, the integrated strategy of network pharmacology prediction with experimental validation suggested that BYD exerted its anti-PMOP via ESR1 and the downstream mechanism might be activation of the ß-catenin signaling pathway.

Identification of glycogene-type and validation of ST3GAL6 as a biomarker predicts clinical outcome and cancer cell invasion in urinary bladder cancer.

Background: Urinary bladder cancer (UBC) is one of the most common causes of morbidity and mortality worldwide characterized by a high risk of invasion and metastasis; however, the molecular classification biomarkers and underlying molecular mechanisms for UBC patient stratification on clinical outcome need to be investigated. Methods: A systematic transcriptomic analysis of 185 glycogenes in the public UBC datasets with survival information and clinicopathological parameters were performed using unsupervised hierarchical clustering. The gene signature for glycogene-type classification was identified using Limma package in R language, and correlated to 8 known molecular features by Gene Set Variation Analysis (GSVA). The clinical relevance and function of a glycogene was characterized by immunohistochemistry in UBC patient samples, and quantitative RT-PCR, Western blotting, promoter activity, MAL II blotting, immunofluorescence staining, wound healing, and transwell assays in UBC cells. Results: A 14-glycogene signature for glycogene-type classification was identified. Among them, ST3GAL6, a glycotransferase to transfer sialic acid to 3'-hydroxyl group of a galactose residue, showed a significant negative association with the subtype with luminal feature in UBC patients (n=2,130 in total). Increased ST3GAL6 was positively correlated to tumor stage, grade, and survival in UBCs from public datasets or our cohort (n=52). Transcription factor GATA3, a luminal-specific marker for UBC, was further identified as a direct upstream regulator of ST3GAL6 to negatively regulate its transactivation. ST3GAL6 depletion decreased MAL II level, cell invasion and migration in 5637 and J82 UBC cells. ST3GAL6 could reverse the effects of GATA3 on global sialylation and cell invasion in SW780 cells. Conclusions: Herein, we successfully identified a novel 14-gene signature for glycogene-type classification of UBC patients. ST3GAL6 gene, from this signature, was demonstrated as a potential biomarker for poor outcomes and cell invasion in UBCs.

Pao Pereira Extract Attenuates Testosterone-Induced Benign Prostatic Hyperplasia in Rats by inhibiting 5α-Reductase.

Benign prostatic hyperplasia (BPH) is one of the most common diseases in the urinary system of elderly men. Pao extract is an herbal preparation of the bark of the Amazon rainforest tree Pao Pereira (Geissospermum vellosii), which was reported to inhibit prostate cancer cell proliferation. Herein we investigated the therapeutic potential of Pao extract against BPH development in a testosterone-induced BPH rat model. The administration of testosterone induced the prostate enlargement, compared with the sham operated group with vehicle treatment. The BPH/Pao group showed reduced prostate weight comparable with BPH/finasteride group. Notably, Pao treatment did not significantly reduce body weights and sperm number of rats, compared with the control group. Furthermore, Pao extract treatment reduced the proliferative index in prostate glands and testosterone-induced expression levels of AR, as well as androgen-associated proteins such as SRD5A1 and PSA. Moreover, Pao extract and its active component, flavopereirine, induced cytotoxicity on human prostate epithelial RWPE-1 cells in a dose- and time- dependent manner with G2/M arrest. Consistently, Pao extract and flavopereirine suppressed the expression levels of SRD5A1, AR and PSA, respectively. Together, these data demonstrated that Pao extract suppresses testosterone-induced BPH development through inhibiting AR activity and expression, and suggested that Pao extract may be a promising and relative safe agent for BPH.