PBAC: A pathway-based attention convolution neural network for predicting clinical drug treatment responses.

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. Although neural networks offer a new approach to improving drug strategies, their internal structure is difficult to interpret. Here, we propose PBAC (Pathway-Based Attention Convolution neural network), which integrates a deep learning framework and attention mechanism to address the complex biological pathway information, thereby provide a biology function-based robust drug responsiveness prediction model. PBAC has four layers: gene-pathway layer, attention layer, convolution layer and fully connected layer. PBAC improves the performance of predicting drug responsiveness by focusing on important pathways, helping us understand the mechanism of drug action in diseases. We validated the PBAC model using data from four chemotherapy drugs (Bortezomib, Cisplatin, Docetaxel and Paclitaxel) and 11 immunotherapy datasets. In the majority of datasets, PBAC exhibits superior performance compared to traditional machine learning methods and other research approaches (area under curve = 0.81, the area under the precision-recall curve = 0.73). Using PBAC attention layer output, we identified some pathways as potential core cancer regulators, providing good interpretability for drug treatment prediction. In summary, we presented PBAC, a powerful tool to predict drug responsiveness based on the biology pathway information and explore the potential cancer-driving pathways.

Characterization of the metabolic alteration-modulated tumor microenvironment mediated by TP53 mutation and hypoxia.

BACKGROUND: TP53 mutation and hypoxia play an essential role in cancer progression. However, the metabolic reprogramming and tumor microenvironment (TME) heterogeneity mediated by them are still not fully understood. METHODS: The multi-omics data of 32 cancer types and immunotherapy cohorts were acquired to comprehensively characterize the metabolic reprogramming pattern and the TME across cancer types and explore immunotherapy candidates. An assessment model for metabolic reprogramming was established by integration of multiple machine learning methods, including lasso regression, neural network, elastic network, and survival support vector machine (SVM). Pharmacogenomics analysis and in vitro assay were conducted to identify potential therapeutic drugs. RESULTS: First, we identified metabolic subtype A (hypoxia-TP53 mutation subtype) and metabolic subtype B (non-hypoxia-TP53 wildtype subtype) in hepatocellular carcinoma (HCC) and showed that metabolic subtype A had an "immune inflamed" microenvironment. Next, we established an assessment model for metabolic reprogramming, which was more effective compared to the traditional prognostic indicators. Then, we identified a potential targeting drug, teniposide. Finally, we performed the pan-cancer analysis to illustrate the role of metabolic reprogramming in cancer and found that the metabolic alteration (MA) score was positively correlated with tumor mutational burden (TMB), neoantigen load, and homologous recombination deficiency (HRD) across cancer types. Meanwhile, we demonstrated that metabolic reprogramming mediated a potential immunotherapy-sensitive microenvironment in bladder cancer and validated it in an immunotherapy cohort. CONCLUSION: Metabolic alteration mediated by hypoxia and TP53 mutation is associated with TME modulation and tumor progression across cancer types. In this study, we analyzed the role of metabolic alteration in cancer and propose a predictive model for cancer prognosis and immunotherapy responsiveness. We also explored a potential therapeutic drug, teniposide.

Construction of a TTN Mutation-Based Prognostic Model for Evaluating Immune Microenvironment, Cancer Stemness, and Outcomes of Colorectal Cancer Patients.

Background: Colorectal cancer (CRC) is one of the commonest cancers worldwide. As conventional biomarkers cannot clearly define the heterogeneity of CRC, it is essential to establish novel prognostic models. Methods: For the training set, data pertaining to mutations, gene expression profiles, and clinical parameters were obtained from the Cancer Genome Atlas. Consensus clustering analysis was used to identify the CRC immune subtypes. CIBERSORT was used to analyze the immune heterogeneity across different CRC subgroups. Least absolute shrinkage and selection operator regression was used to identify the genes for constructing the immune feature-based prognostic model and to determine their coefficients. Result: A gene prognostic model was then constructed to predict patient outcomes; the model was then externally validated using data from the Gene Expression Omnibus. As a high-frequency somatic mutation, the titin (TTN) mutation has been identified as a risk factor for CRC. Our results demonstrated that TTN mutations have the potential to modulate the tumor microenvironment, converting it into the immunosuppressive type. In this study, we identified the immune subtypes of CRC. Based on the identified subtypes, 25 genes were selected for prognostic model construction; a prediction model was also constructed, and its prediction accuracy was tested using the validation dataset. The potential of the model in predicting immunotherapy responsiveness was then explored. Conclusion: TTN-mutant and TTN-wild-type CRC demonstrated different microenvironment features and prognosis. Our model provides a robust immune-related gene prognostic tool and a series of gene signatures for evaluating the immune features, cancer stemness, and prognosis of CRC.

A preliminary study of further attempt at the development, testing and application of an independent primary screening stool card.

Stool characteristics are of great value to assess diseases, but patients knew little. E-learning applied in health popularization and patient education is booming. In China, WeChat applets has advantages of abundant users, convenient access and low cost, which may be a great media in patient education on stool. This preliminary study aims to develop and evaluate a stool card WeChat applet. We collected stools images during 2020 to 2022 in the Department of Gastroenterology and Hepatology in the Second Affiliated Hospital of Harbin Medical University, constructed a stool card applet named the Doctor Friend Primary Screening Stool Card (DFPSSC) and evaluated it. Eligible participants were divided into the applet, traditional paper media and control group. We implement a series of tests to evaluate the effectiveness. 20 clinicians and participants using the DFPSSC completed a questionnaire to evaluate the usability. We developed the DFPSSC for an E-learning approach. Of 108 volunteers, 97 completed the DFPSSC learning. No significant pretest differences were found among the three groups (P = 0.303). Applet group had significantly higher posttest scores than pretest scores in intervention (P < 0.001, d = 1.68) and simulation (P = 0.006) test, and it had higher scores than other two group (P < 0.001). 63% participants and 59% clinicians strongly agree or agree to the usability of DFSSC. This preliminary study verified that the DFPSSC can effectively improve participants' knowledge of feces, making it an effective clinical tool for patient education and the avoidance of treatment delay.

Integration of cancer stemness and neoantigen load to predict responsiveness to anti-PD1/PDL1 therapy.

Background: Anti-programmed cell death 1/programmed cell death ligand 1 (PD1/PDL1) therapy is an important part of comprehensive cancer therapy. However, many patients suffer from non-response to therapy. Tumor neoantigen burden (TNB) and cancer stemness play essential roles in the responsiveness to therapy. Therefore, the identification of drug candidates for anti-PD1/PDL1 therapy remains an unmet need. Methods: Three anti-PD1/PDL1 therapy cohorts were obtained from GEO database and published literatures. Cancer immune characteristics were analyzed using CIBERSORTX, GSVA, and ESTIMATE. WGCNA was employed to identify the gene modules correlated with cancer TNB and stemness. A machine-learning method was used to construct the immunotherapy resistance score (TSIRS). Pharmacogenomic analysis was conducted to explore the potential alternative drugs for anti-PD1/PDL1 therapy resistant patients. CCK-8 assay, EdU assay and wound healing assay were used to validate the effect of the predicted drug on cancer cells. Results: The therapy response and non-response cancer groups have different microenvironment features. TSIRS was developed based on tumor neoantigen and stemness. TSIRS can effectively predict the outcomes of patients with anti-PD1/PDL1 therapy in training, validation and meta cohorts. Meanwhile, TSIRS can reflect the characteristics of tumor microenvironment during anti-PD1/PDL1 therapy. PF-4708671 is identified as a potential alternative drug for patients with resistance to anti-PD1/PDL1 therapy. It possesses significant inhibitive effect on the proliferation and migration of BGC-823 cells. Conclusion: TSIRS is an effective tool in the identification of candidate patients who will be benefit from anti-PD1/PDL1 therapy. Small molecule drug PF-4708671 has the potential to be used in anti-PD1/PDL1 therapy resistant patients.

Transplanted hair follicle mesenchymal stem cells alleviated small intestinal ischemia-reperfusion injury via intrinsic and paracrine mechanisms in a rat model.

Background: Small intestinal ischemia-reperfusion (IR) injury is a common intestinal disease with high morbidity and mortality. Mesenchymal stem cells (MSCs) have been increasingly used in various intestinal diseases. This study aimed to evaluate the therapeutic effect of hair follicle MSCs (HFMSCs) on small intestinal IR injury. Methods: We divided Sprague-Dawley rats into three groups: the sham group, IR group and IR + HFMSCs group. A small intestinal IR injury rat model was established by clamping of the superior mesenteric artery (SMA) for 30 min and reperfusion for 2 h. HFMSCs were cultured in vitro and injected into the rats through the tail vein. Seven days after treatment, the intrinsic homing and differentiation characteristics of the HFMSCs were observed by immunofluorescence and immunohistochemical staining, and the paracrine mechanism of HFMSCs was assessed by Western blotting and enzyme-linked immunosorbent assay (ELISA). Results: A small intestinal IR injury model was successfully established. HFMSCs could home to damaged sites, express proliferating cell nuclear antigen (PCNA) and intestinal stem cell (ISC) markers, and promote small intestinal ISC marker expression. The expression levels of angiopoietin-1 (ANG1), vascular endothelial growth factor (VEGF) and insulin growth factor-1 (IGF1) in the IR + HFMSCs group were higher than those in the IR group. HFMSCs could prevent IR-induced apoptosis by increasing B-cell lymphoma-2 (Bcl-2) expression and decreasing Bcl-2 homologous antagonist/killer (Bax) expression. Oxidative stress level detection showed that the malondialdehyde (MDA) content was decreased, while the superoxide dismutase (SOD) content was increased in the IR + HFMSCs group compared to the IR group. An elevated diamine oxidase (DAO) level reflected the potential protective effect of HFMSCs on the intestinal mucosal barrier. Conclusion: HFMSCs are beneficial to alleviate small intestinal IR injury through intrinsic homing to the small intestine and by differentiating into ISCs, via a paracrine mechanism to promote angiogenesis, reduce apoptosis, regulate the oxidative stress response, and protect intestinal mucosal function potentially. Therefore, this study suggests that HFMSCs serve as a new option for the treatment of small intestinal IR injury.

Fucosyltransferase 4 Predicts Patient Outcome in Rectal Cancer through an Immune Microenvironment-Mediated Multi-Mechanism.

Colorectal cancer is the most common type of gastrointestinal malignant tumors worldwide. Standardization of the strategy for the precise treatment of this cancer has been a major challenge. Enrichment analysis of six gene groups (colon cancer-specific genes (upregulated and downregulated); rectal cancer-specific genes (upregulated and downregulated); and common genes (upregulated and downregulated)) revealed the common and specific features of colon and rectal cancer, particularly a hyperactive immune response in rectal cancer. Key common genes exhibited a similar expression pattern, but were associated with distinct patient prognosis in colon and rectal cancer. FUT4 was a core regulatory gene in rectal cancer; it can decrease the level of infiltration by M2 macrophages in the tumor immune microenvironment and participate in the positive regulation of the immune system and glycoprotein biosynthetic process, thereby affecting the outcome of patients with rectal cancer. FUT4 co-expression genes can influence patient's survival time by regulating the cell cycle. Among the regulators of FUT4 co-expression genes, checkpoint kinase 2 (CHEK2) was linked to patient outcome.

Integrated Analysis Revealing the Senescence-Mediated Immune Heterogeneity of HCC and Construction of a Prognostic Model Based on Senescence-Related Non-Coding RNA Network.

Background: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. Non-coding RNAs play an important role in HCC. This study aims to identify a senescence-related non-coding RNA network-based prognostic model for individualized therapies for HCC. Methods: HCC subtypes with senescence status were identified on the basis of the senescence-related genes. Immune status of the subtypes was analyzed by CIBERSORT and ESTIMATE algorithm. The differentially expressed mRNAs, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) were identified between the two HCC subtypes. A senescence-based competing endogenous RNA (ceRNA) co-expression network in HCC was constructed. On the basis of the ceRNA network, Lasso Cox regression was used to construct the senescence-related prognostic model (S score). The prognosis potential of the S score was evaluated in the training dataset and four external validation datasets. Finally, the potential of the prognostic model in predicting immune features and response to immunotherapy was evaluated. Results: The HCC samples were classified into senescence active and inactivate subtypes. The senescence active group showed an immune suppressive microenvironment compared to the senescence inactive group. A total of 2,902 mRNAs, 19 miRNAs, and 308 lncRNAs were identified between the two subtypes. A ceRNA network was constructed using these differentially expressed genes. On the basis of the ceRNA network, S score was constructed to predict the prognosis of patients with HCC. The S score was correlated with immune features and can predict response to immunotherapy of cancer. Conclusion: The present study analyzed the biological heterogeneity across senescence-related subtypes and constructed a senescence-related ceRNA-network-based prognostic model for predicting prognosis and immunotherapy responsiveness.

From hair to liver: emerging application of hair follicle mesenchymal stem cell transplantation reverses liver cirrhosis by blocking the TGF-ß/Smad signaling pathway to inhibit pathological HSC activation.

Liver cirrhosis (LC) involves multiple systems throughout the body, and patients with LC often die of multiple organ failure. However, few drugs are useful to treat LC. Hair follicle mesenchymal stem cells (HF-MSCs) are derived from the dermal papilla and the bulge area of hair follicles and are pluripotent stem cells in the mesoderm with broad prospects in regenerative medicine. As an emerging seed cell type widely used in skin wound healing and plastic surgery, HF-MSCs show considerable prospects in the treatment of LC due to their proliferation and multidirectional differentiation capabilities. We established an LC model in C57BL/6J mice by administering carbon tetrachloride (CCl4) and injected HF-MSCs through the tail vein to explore the therapeutic effects and potential mechanisms of HF-MSCs on LC. Here, we found that HF-MSCs improved liver function and ameliorated the liver pathology of LC. Notably, PKH67-labeled HF-MSCs were detected in the injured liver and expressed the hepatocyte-specific markers cytokeratin 18 (CK18) and albumin (ALB). In addition, in contrast to that in the LC group, the α-SMA expression showed a decreasing trend in the treatment group in vitro and in vivo, indicating that the pathological activation of hepatic stellate cells (HSCs) was inhibited by HF-MSC treatment. Moreover, the levels of transforming growth factor ß (TGF-ß1) and p-Smad3, a signaling molecule downstream of TGF-ß1, were increased in mice with LC, while HF-MSC treatment reversed these changes in vivo and in vitro. Based on these findings, HF-MSCs may reverse LC by blocking the TGF-ß/Smad pathway and inhibiting the pathological activation of HSCs, which may provide evidence for the application of HF-MSCs to treat LC.

Development and Assessment of a Gastroscopy Electronic Learning System for Primary Learners: Randomized Controlled Trial.

BACKGROUND: Endoscopic examination is a popular and routine procedure for the diagnosis and treatment of gastrointestinal (GI) diseases. Skilled endoscopists are in great demand in clinical practice, but the training process for beginners to become endoscopy specialists is fairly long. Convenience and a self-paced, learner-centered approach make electronic learning (e-learning) an excellent instructional prospect. OBJECTIVE: This study aimed to develop and apply an e-learning system in gastroscopy teaching and learning and to evaluate its effectiveness and user satisfaction. METHODS: The e-learning software Gastroscope Roaming System was developed for primary learners. The system simulates the real structure of the upper gastrointestinal (UGI) tract to teach the main characteristics of gastroscopy under both normal conditions and conditions of common UGI tract diseases. A randomized controlled trial was conducted. Participants were randomly allocated to an e-learning group (EG)or a non-e-learning control group after a pretest. On completing the training, participants undertook a posttest and gastroscopy examination. In addition, the EG completed a satisfaction questionnaire. RESULTS: Of the 44 volunteers, 41 (93%) completed the gastroscopy learning and testing components. No significant pretest differences were found between the intervention and control groups (mean 50.86, SD 6.12 vs mean 50.76, SD 6.88; P=.96). After 1 month of learning, the EG's posttest scores were higher (mean 83.70, SD 5.99 vs mean 78.76, SD 7.58; P=.03) and improved more (P=.01) than those of the control group, with better performance in the gastroscopy examination (mean 91.05, SD 4.58 vs mean 84.38, SD 5.19; P<.001). Overall, 85% (17/20) of the participants were satisfied with the e-learning system, and 95% (19/20) of the participants considered it successful. CONCLUSIONS: E-learning is an effective educational strategy for primary learners to acquire skills in gastroscopy examination and endoscopic imaging of the GI tract. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-IOR-17013091; http://www.chictr.org.cn/showproj.aspx?proj=22142.

5-(3-Chloro-phen-ylsulfan-yl)-1-methyl-3-trifluoro-methyl-1H-pyrazole-4-carbaldehyde O-[(2-chloro-1,3-thia-zol-5-yl)meth-yl]oxime.

In the title compound, C(16)H(11)Cl(2)F(3)N(4)OS(2), the benzene ring and the thia-zole ring make dihedral angles of 83.2 (3) and 78.3 (3)°, respectively, with the pyrazole ring. The crystal packing shows S⋯N contacts of 3.309 (2) Å.

1-Methyl-3-trifluoro-methyl-5-[(3-chloro-phen-yl)sulfanyl]-1H-pyrazole-4-carbaldehyde O-(4-chloro-benzo-yl)oxime.

In the title compound, C(19)H(12)Cl(2)F(3)N(3)O(2)S, the 3-chloro-phenyl and 4-chloro-phenyl rings form dihedral angles 89.5 (2) and 11.4 (2)°, respectively, with the pyrazole ring. In the crystal, mol-ecules related by translation along the a axis are linked into chains via C-H⋯N hydrogen bonds.