The intratumoral microbiota biomarkers for predicting survival and efficacy of immunotherapy in patients with ovarian serous cystadenocarcinoma.

BACKGROUND: Ovarian serous cystadenocarcinoma, accounting for about 90% of ovarian cancers, is frequently diagnosed at advanced stages, leading to suboptimal treatment outcomes. Given the malignant nature of the disease, effective biomarkers for accurate prediction and personalized treatment remain an urgent clinical need. METHODS: In this study, we analyzed the microbial contents of 453 ovarian serous cystadenocarcinoma and 68 adjacent non-cancerous samples. A univariate Cox regression model was used to identify microorganisms significantly associated with survival and a prognostic risk score model constructed using LASSO Cox regression analysis. Patients were subsequently categorized into high-risk and low-risk groups based on their risk scores. RESULTS: Survival analysis revealed that patients in the low-risk group had a higher overall survival rate. A nomogram was constructed for easy visualization of the prognostic model. Analysis of immune cell infiltration and immune checkpoint gene expression in both groups showed that both parameters were positively correlated with the risk level, indicating an increased immune response in higher risk groups. CONCLUSION: Our findings suggest that microbial profiles in ovarian serous cystadenocarcinoma may serve as viable clinical prognostic indicators. This study provides novel insights into the potential impact of intratumoral microbial communities on disease prognosis and opens avenues for future therapeutic interventions targeting these microorganisms.

Bacterial outer membrane vesicle nanorobot.

Autonomous nanorobots represent an advanced tool for precision therapy to improve therapeutic efficacy. However, current nanorobotic designs primarily rely on inorganic materials with compromised biocompatibility and limited biological functions. Here, we introduce enzyme-powered bacterial outer membrane vesicle (OMV) nanorobots. The immobilized urease on the OMV membrane catalyzes the decomposition of bioavailable urea, generating effective propulsion for nanorobots. This OMV nanorobot preserves the unique features of OMVs, including intrinsic biocompatibility, immunogenicity, versatile surface bioengineering for desired biofunctionalities, capability of cargo loading and protection. We present OMV-based nanorobots designed for effective tumor therapy by leveraging the membrane properties of OMVs. These involve surface bioengineering of robotic body with cell-penetrating peptide for tumor targeting and penetration, which is further enhanced by active propulsion of nanorobots. Additionally, OMV nanorobots can effectively safeguard the loaded gene silencing tool, small interfering RNA (siRNA), from enzymatic degradation. Through systematic in vitro and in vivo studies using a rodent model, we demonstrate that these OMV nanorobots substantially enhanced siRNA delivery and immune stimulation, resulting in the utmost effectiveness in tumor suppression when juxtaposed with static groups, particularly evident in the orthotopic bladder tumor model. This OMV nanorobot opens an inspiring avenue to design advanced medical robots with expanded versatility and adaptability, broadening their operation scope in practical biomedical domains.

GWAS combined with QTL mapping reveals the genetic loci of leaf morphological characters in Nicotiana tabacum.

BACKGROUND: Leaf morphology plays a crucial role in photosynthetic efficiency and yield potential in crops. Cigar tobacco plants, which are derived from common tobacco (Nicotiana tabacum L.), possess special leaf characteristics including thin and delicate leaves with few visible veins, making it a good system for studying the genetic basis of leaf morphological characters. RESULTS: In this study, GWAS and QTL mapping were simultaneously performed using a natural population containing 185 accessions collected worldwide and an F2 population consisting of 240 individuals, respectively. A total of 26 QTLs related to leaf morphological traits were mapped in the F2 population at three different developmental stages, and some QTL intervals were repeatedly detected for different traits and at different developmental stages. Among the 206 significant SNPs identified in the natural population using GWAS, several associated with the leaf thickness phenotype were co-mapped via QTL mapping. By analyzing linkage disequilibrium and transcriptome data from different tissues combined with gene functional annotations, 7 candidate genes from the co-mapped region were identified as the potential causative genes associated with leaf thickness. CONCLUSIONS: These results presented a valuable cigar tobacco resource showing the genetic diversity regarding its leaf morphological traits at different developmental stages. It also provides valuable information for novel genes and molecular markers that will be useful for further functional verification and for molecular breeding of leaf morphological traits in crops in the future.

[Research progress on the differences between T and B cell responses to three different forms of human papilloma virus (HPV) vaccination].

One of the most prevalent malignancies in women is cervical cancer. Cervical cancer is mostly brought on by chronic high-risk human papillomavirus 16 (HPV16) and HPV18 infection. Currently, the widely used HPV vaccines are the bivalent Cervarix, the tetravalent Gardasil, and the 9-valent Gardasil-9.There are differences in T cell effector molecule changes, B cell antibody level, duration, age and the injection after vaccination of the three vaccines.

Hepatic artery infusion chemotherapy combined with camrelizumab plus rivoceranib for hepatocellular carcinoma with portal vein tumor thrombosis: a multicenter propensity score-matching analysis.

BACKGROUND: Portal vein tumor thrombosis (PVTT) signifies late-stage hepatocellular carcinoma (HCC) with high-risk progression and poor prognosis. As a standard treatment, sorafenib monotherapy has limited the efficacy in managing HCC with PVTT. Currently, both hepatic arterial infusion chemotherapy (HAIC) and the combination of camrelizumab and rivoceranib have shown favorable survival benefits for advanced HCC, surpassing the standard sorafenib treatment. In this study, we investigate the safety and efficacy of HAIC combined with camrelizumab and rivoceranib in treating HCC patients with PVTT. METHODS: From January 2020 to December 2021, HCC patients with PVTT, who received either a triple regime of HAIC combined with camrelizumab and rivoceranib or a dual regime of camrelizumab and rivoceranib as their first-line treatment, were reviewed for eligibility at four hospital centers in China. To balance any intergroup differences, propensity score matching (PSM) was applied. The aim of this study is to compare the efficacy of the dual and triple combination treatment regimens based on survival prognosis and tumor response and evaluate the safety based on the occurrence of adverse reactions. RESULT: In this study, a total of 411 patients who received either the triple treatment regime (HAIC combined with camrelizumab plus rivoceranib, referred to as the HAICCR group, n = 292) or the dual treatment regime (camrelizumab combined with rivoceranib, referred to as the CR group, n = 119) between January 2020 and December 2021 were included. The results showed that the HAICCR group exhibited significantly better overall survival (mOS: 19.60 months vs. 11.50 months, p < 0.0001) and progression-free survival (mPFS: 10.0 months vs. 5.6 months, p < 0.0001) compared to the CR group in the overall cohort. Moreover, the HAICCR group also had a significantly higher ORR (objective response rate, 55.5% vs. 42.0%, p = 0.013) and DCR (disease control rate, 89.0% vs. 79.0%) compared to the CR group. After PSM, a final matched cohort of 83 pairs was obtained, and the survival benefits were consistent in this cohort as well (mOS: 18.70 months vs. 11.0 months, p < 0.0001; mPFS: 10.0 months vs. 5.6 months, p < 0.0001). However, there was no significant difference in the ORR between the triple and dual combination regimes. Univariate and multivariate analysis showed that CTP (Child-Turcotte-Pugh) stage, ALBI (albumin-bilirubin index) grade, tumor number, and treatment regime were significant risk factors affecting overall survival, while AFP (α-fetoprotein) level, tumor number, metastasis, and treatment regime were significant risk factors affecting progression-free survival. As for safety, hypertension and hand-foot syndrome were the two most common adverse reactions in both groups, with no significant difference in the occurrence of adverse reactions between the two groups (p < 0.05). CONCLUSION: In the context of advanced HCC patients with PVTT, the combination regime of HAIC and camrelizumab plus rivoceranib demonstrates more excellent capacity for prolonging survival and offers a well-tolerated safety compared to the CR dual therapy approach. This triple regime represents a therapeutic modality of broad prospects and vast potential for HCC patients with PVTT.

[Establishment of a rapid detection method of colloidal gold immunochromatographic competition assay for organophosphorus pesticides].

Objective To establish a colloidal gold immunochromatography and develop the corresponding test strip for detecting organophosphorus compounds including omethoate, phoxim, dipterex, and parathion in fruits, vegetables and drinking water. Methods Artificial antigen molecules of organophosphorus compounds were synthesized using N-hydroxysuccinimide esters. Acetylcholinesterase antigen was prepared and purified, and the serum containing the corresponding antibody was prepared, purified, and labeled. The working parameters of the test strip were optimized, and the performance evaluation of it was conducted. Results The titer of the antisera ranged from 1:32 to 1:64, with a protein content of approximately 2 mg/mL. The purified polyclonal antibodies displayed target bands at relative molecular masses (Mr) of 25 000 and 55 000, indicating satisfactory purity. The reaction time of the test strips was between 5 to 10 minutes, with a detection limit for samples at 200 ng/mL. Both specificity and accuracy were satisfactory, and the test strip remained valid for 6 months. Conclusion A simple and rapid colloidal gold immunochromatography is established successfully for detecting several organophosphorus compounds and may be useful for on-site preliminary screening of samples in large quantities.

Male breast cancer differs from female breast cancer in molecular features that affect prognoses and drug responses.

BACKGROUND: Male breast cancer (MBC) is a rare malignancy with a worse prognosis than female breast cancer (FBC). Current MBC treatment strategies are based on those for FBC. However, molecular differences between MBC and FBC with respect to prognosis and drug responses remain unclear. METHODS: After controlling for confounding factors with propensity score matching (PSM), differences between MBC and FBC were comprehensively analyzed using many types of data: survival, immune microenvironments, sex hormone responses, drug sensitivity, transcriptomes, genomes, epigenomes, and proteomes. RESULTS: Overall survival (OS) and cancer-specific survival (CSS) were both worse for MBC than for FBC. Differentially expressed mRNAs were enriched in numerous cancer-related functions and pathways, with SPAG16 and STOX1 being as the most important prognosis-related mRNAs for MBC. Competing endogenous RNA (ceRNA) and transcription factor (TF)-mRNA regulatory networks contain potential prognostic genes. Nine genes had higher mutation frequencies in MBC than in FBC. MBC shows a comparatively poor response to immunotherapy, with five proteins that promote breast cancer progression being highly expressed in MBC. MBC may be more responsive than FBC to estrogen. We detected six United States Food and Drug Administration (FDA)-approved therapeutic target genes as being differentially expressed between MBC and FBC. CONCLUSION: The poor prognosis of MBC compared to FBC is due to numerous molecular differences and resulting drug responses.

Screening, identification, and mechanism analysis of starch-degrading bacteria during curing process in tobacco leaf.

Tobacco, a vital economic crop, had its quality post-curing significantly influenced by starch content. Nonetheless, the existing process parameters during curing were inadequate to satisfy the starch degradation requirements. Microorganisms exhibit inherent advantages in starch degradation, offering significant potential in the tobacco curing process. Our study concentrated on the microbial populations on the surface of tobacco leaves and in the rhizosphere soil. A strain capable of starch degradation, designated as BS3, was successfully isolated and identified as Bacillus subtilis by phylogenetic tree analysis based on 16SrDNA sequence. The application of BS3 on tobacco significantly enhanced enzyme activity and accelerated starch degradation during the curing process. Furthermore, analyses of the metagenome, transcriptome, and metabolome indicated that the BS3 strain facilitated starch degradation by regulating surface microbiota composition and affecting genes related to starch hydrolyzed protein and key metabolites in tobacco leaves. This study offered new strategies for efficiently improving the quality of tobacco leaves.

Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer.

BACKGROUND: Accurate preoperative prediction of lymph node metastasis (LNM) in esophageal cancer (EC) patients is of crucial clinical significance for treatment planning and prognosis. AIM: To develop a clinical radiomics nomogram that can predict the preoperative lymph node (LN) status in EC patients. METHODS: A total of 32 EC patients confirmed by clinical pathology (who underwent surgical treatment) were included. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy, and its correlation with LNM was analyzed. Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python. Feature extraction, data dimensionality reduction, and feature selection were performed using XGBoost model and leave-one-out cross-validation. Multivariable logistic regression analysis was used to establish the prediction model, which included radiomics features, LN status from computed tomography (CT) reports, and B7-H3 mRNA expression, represented by a radiomics nomogram. Receiver operating characteristic area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical application value of the model. RESULTS: The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis, and the difference was statistically significant (P < 0.05). The AUC value in the receiver operating characteristic (ROC) curve was 0.718 (95%CI: 0.528-0.907), with a sensitivity of 0.733 and specificity of 0.706, indicating good diagnostic performance. The individualized clinical prediction nomogram included radiomics features, LN status from CT reports, and B7-H3 mRNA expression. The ROC curve demonstrated good diagnostic value, with an AUC value of 0.765 (95%CI: 0.598-0.931), sensitivity of 0.800, and specificity of 0.706. DCA indicated the practical value of the radiomics nomogram in clinical practice. CONCLUSION: This study developed a radiomics nomogram that includes radiomics features, LN status from CT reports, and B7-H3 mRNA expression, enabling convenient preoperative individualized prediction of LNM in EC patients.

CT-based intratumoral and peritumoral deep transfer learning features prediction of lymph node metastasis in non-small cell lung cancer.

BACKGROUND: The main metastatic route for lung cancer is lymph node metastasis, and studies have shown that non-small cell lung cancer (NSCLC) has a high risk of lymph node infiltration. OBJECTIVE: This study aimed to compare the performance of handcrafted radiomics (HR) features and deep transfer learning (DTL) features in Computed Tomography (CT) of intratumoral and peritumoral regions in predicting the metastatic status of NSCLC lymph nodes in different machine learning classifier models. METHODS: We retrospectively collected data of 199 patients with pathologically confirmed NSCLC. All patients were divided into training (n = 159) and validation (n = 40) cohorts, respectively. The best HR and DTL features in the intratumoral and peritumoral regions were extracted and selected, respectively. Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Light Gradient Boosting Machine (Light GBM), Multilayer Perceptron (MLP), and Logistic Regression (LR) models were constructed, and the performance of the models was evaluated. RESULTS: Among the five models in the training and validation cohorts, the LR classifier model performed best in terms of HR and DTL features. The AUCs of the training cohort were 0.841 (95% CI: 0.776-0.907) and 0.955 (95% CI: 0.926-0.983), and the AUCs of the validation cohort were 0.812 (95% CI: 0.677-0.948) and 0.893 (95% CI: 0.795-0.991), respectively. The DTL signature was superior to the handcrafted radiomics signature. CONCLUSIONS: Compared with the radiomics signature, the DTL signature constructed based on intratumoral and peritumoral areas in CT can better predict NSCLC lymph node metastasis.

A Simple Scoring System for Predicting the Risk of Delayed Hyponatremia After Endoscopic Transsphenoidal Surgery for Pituitary Adenomas.

BACKGROUND: To identify high-risk patients for delayed postoperative hyponatremia (DPH) early, we constructed a simple and effective scoring system. METHODS: We retrospectively analyzed 141 consecutive patients who underwent endoscopic transsphenoidal surgery from January 2019 to December 2022. Patients were divided into DPH group and nondelayed postoperative hyponatremia group based on whether hyponatremia occurred after the third postoperative day. Multivariable logistic regression analysis was conducted to determine the predictive factors of DPH, and a simple scoring system was constructed based on these predictors. RESULTS: Among 141 patients, 36 (25.5%) developed DPH. Multivariable logistic regression analysis showed that age ≥48 years (odds ratio [OR], 3.74; 95% confidence interval [CI], 1.14-12.21; P = 0.029), Knosp grade ≥3 (OR, 5.17; 95% CI, 1.20-22.27; P = 0.027), postoperative hypokalemia within three days (OR, 3.13; 95% CI, 1.05-9.33; P = 0.040), a difference in blood sodium levels between the first and second day after surgery ≥1 mEq/L (OR, 3.65; 95% CI, 1.05-12.77; P = 0.043), and postoperative diabetes insipidus (OR, 3.57; 95% CI, 1.16-10.96; P = 0.026) were independent predictors of DPH. CONCLUSIONS: This scoring system for predicting DPH has an area under the receiver operating characteristic curve of 0.856 (95% CI, 0.787-0.925), indicating moderate to good predictive value for DPH in our cohort, but further prospective external validation is needed.

An Injectable Magnesium-Based Cement Stimulated with NIR for Drug-Controlled Release and Osteogenic Potential.

Magnesium phosphate bone cement (MPC) has gained widespread usage in orthopedic implantation due to its fast-setting and high initial strength benefits. However, the simultaneous attainment of drug-controlled release and osteogenic potential in MPC remains a significant challenge. Herein, a strategy to create a smart injectable cement system using nanocontainers and chondroitin sulfate is proposed. It employs nanocontainers containing alendronate-loaded mesoporous silica nanoparticles, which are surface-modified with polypyrrole to control drug release in response to near-infrared (NIR) stimulation. The alendronate-incorporated cement (ACMPC) exhibits improved compressive strength (70.6 ± 5.9 MPa), prolonged setting time (913 s), and exceptional injectability (96.5% of injection rate and 242 s of injection time). It also shows the capability to prevent degradation, thus preserving mechanical properties. Under NIR irradiation, the cement shows good antibacterial properties due to the combined impact of hyperthermia, reactive oxygen species, and alendronate. Furthermore, the ACMPC (NIR) group displays good biocompatibility and osteogenesis capabilities, which also lead to an increase in alkaline phosphatase activity, extracellular matrix mineralization, and the upregulation of osteogenic genes. This research has significant implications for developing multifunctional biomaterials and clinical applications.

Exploring prognostic microbiota markers in patients with endometrial carcinoma: Intratumoral insights.

Endometrial cancer, a leading gynecological malignancy, is profoundly influenced by the uterine microbiota, a key factor in disease prognosis and treatment. Our study underscores the distinct microbial compositions in endometrial cancer compared to adjacent non-cancerous tissues, revealing a dominant presence of p_Actinobacteria in cancerous tissues as opposed to p_Firmicutes in surrounding areas. Through comprehensive analysis, we identified 485 unique microorganisms in cancer tissues, 26 of which correlate with patient prognosis. Employing univariate Cox regression and LASSO regression analyses, we devised a microbial risk scoring model, effectively stratifying patients into high and low-risk categories, thereby providing predictive insights into their overall survival. We further developed a nomogram that incorporates the microbial risk score along with age, grade, and clinical stage, significantly enhancing the accuracy of our clinical prediction model for endometrial cancer. Moreover, our study delves into the differential immune landscapes of high-risk and low-risk patients. The low-risk group displayed a higher prevalence of activated B cells and increased T cell co-stimulation, indicative of a robust immune response. Conversely, high-risk patients showed elevated tumor immune dysfunction and exclusion scores, suggesting less favorable outcomes in immunotherapy. Notably, the efficacy of IPS-CTLA4 and PD1/PD-L1/PD-L2 blockers was substantially higher in the low-risk group, pointing to a more responsive immunotherapeutic approach. In summary, our research elucidates the unique microbial patterns in endometrial cancer and adjacent tissues, and establishes both a microbial risk score model and a clinical prediction nomogram. These findings highlight the potential of uterine microbiota as a biomarker for customizing treatment strategies, enabling precise interventions for high-risk patients while preventing overtreatment in low-risk cases. This study emphasizes the microbiota's role in tailoring immunotherapy, offering a novel perspective in the treatment and prognosis of endometrial cancer. Significantly, our study's expansive sample analysis from the TCGA-UCEC cohort, employing linear discriminant analysis effect size methodology, not only validates but also enhances our understanding of the microbiota's role in endometrial cancer, paving the way for novel diagnostic and therapeutic approaches in its management.

Cathepsin B: The dawn of tumor therapy.

Cathepsin B (CTSB) is a key lysosomal protease that plays a crucial role in the development of cancer. This article elucidates the relationship between CTSB and cancer from the perspectives of its structure, function, and role in tumor growth, migration, invasion, metastasis, angiogenesis and autophagy. Further, we summarized the research progress of cancer treatment related drugs targeting CTSB, as well as the potential and advantages of Traditional Chinese medicine in treating tumors by regulating the expression of CTSB.

Insights into drought stress response mechanism of tobacco during seed germination by integrated analysis of transcriptome and metabolome.

Drought stress inhibits seed germination, plant growth and development of tobacco, and seriously affects the yield and quality of tobacco leaves. However, the molecular mechanism underlying tobacco drought stress response remains largely unknown. In this study, integrated analysis of transcriptome and metabolome was performed on the germinated seeds of a cultivated variety K326 and its EMS mutagenic mutant M28 with great drought tolerance. The result showed that drought stress inhibited seed germination of the both varieties, while the germination rate of M28 was faster than that of K326 under drought stress. Besides, the levels of phytohormone ABA, GA19, and zeatin were increased by drought stress in M28. Five vital pathways were identified through integrated transcriptomic and metabolomic analysis, including zeatin biosynthesis, aspartate and glutamate synthesis, phenylamine metabolism, glutathione metabolism, and phenylpropanoid synthesis. Furthermore, 20 key metabolites in the above pathways were selected for further analysis of gene modular-trait relationship, and then four highly correlated modules were found. Then analysis of gene expression network was carried out of Top30 hub gene of these four modules, and 9 key candidate genes were identified, including HSP70s, XTH16s, APX, PHI-1, 14-3-3, SCP, PPO. In conclusion, our study uncovered some key drought-responsive pathways and genes of tobacco during seeds germination, providing new insights into the regulatory mechanisms of tobacco drought stress response.

Comprehensive Analysis and Experimental Validation of the Parkinson's Disease Lysosomal Gene ACP2 and Pan-cancer.

The pivotal role of lysosomal function in preserving neuronal homeostasis is recognized, with its dysfunction being implicated in neurodegenerative processes, notably in Parkinson's disease (PD). Yet, the molecular underpinnings of lysosome-related genes (LRGs) in the context of PD remain partially elucidated. We collected RNA-seq data from the brain substantia nigra of 30 PD patients and 20 normal subjects from the GEO database. We obtained molecular classification clusters from the screened lysosomal expression patterns. The lysosome-related diagnostic model of Parkinson's disease was constructed by XGBoost and Random Forest. And we validated the expression patterns of signature LRGs in the diagnostic model by constructing a PD rat model. Finally, the linkage between PD and cancer through signature genes was explored. The expression patterns of the 33 LRGs screened can be divided into two groups of PD samples, enabling exploration of the variance in biological processes and immune elements. Cluster A had a higher disease severity. Subsequently, critical genes were sieved through the application of machine learning methodologies culminating in the identification of two intersecting feature genes (ACP2 and LRP2). A PD risk prediction model was constructed grounded on these signature genes. The model's validity was assessed through nomogram evaluation, which demonstrated robust confidence validity. Then we analyzed the correlation analysis, immune in-filtration, biological function, and rat expression validation of the two genes with common pathogenic genes in Parkinson's disease, indicating that these two genes play an important role in the pathogenesis of PD. We then selected ACP2, which had a significant immune infiltration correlation, as the entry gene for the pan-cancer analysis. The pan-cancer analysis revealed that ACP2 has profound associations with prognostic indicators, immune infiltration, and tumor-related regulatory processes across various neoplasms, suggesting its potential as a therapeutic target in a range of human diseases, including PD and cancers. Our study comprehensively analyzed the molecular grouping of LRGs expression patterns in Parkinson's disease, and the disease progression was more severe in cluster A. And the PD diagnosis model related to LRGs is constructed. Finally, ACP2 is a potential target for the relationship between Parkinson's disease and tumor.

Zirconium-rich magnetic polyoxometalate-based metal-organic framework: Tailored for phosphopeptide analysis from lung cancer A549 cells.

Polyoxometalate-based metal-organic frameworks (POMOFs) have become a promising affinity material for separation and enrichment. The analysis of protein phosphorylation represents a challenge for the development of efficient enrichment materials. Here, a novel zirconium-rich magnetic POMOF was successfully designed and prepared for the enrichment of phosphopeptides. The binding affinity of the nanomaterial partly came from Fe-O clusters in the MOF. The Lewis acid-base interactions between V-O clusters and zirconium ions in V10O28-Zr4+ and phosphate groups in phosphopeptides further strengthened the enrichment ability. The zirconium-rich magnetic POMOF was employed to capture phosphopeptides from non-fat milk, human saliva, and serum. Additionally, 748 unique phosphopeptide peaks were detected from the tryptic digests of lung cancer A549 cell proteins with a high specificity (86.9 %). POMOFs will become an active competitor for the design of protein affinity materials and will provide a new approach for phosphopeptide analysis.

Ononin promotes radiosensitivity in lung cancer by inhibiting HIF-1α/VEGF pathway.

BACKGROUND: In our previous study, we provided evidence that Astragalus mongholicus Bunge(AM) and its extracts possess a protective capability against radiation-induced damage, potentially mediated through the reduction of reactive oxygen species (ROS) and nitric oxide (NO). However, we were pleasantly surprised to discover during our experimentation that AM not only offers protection against radiation damage but also exhibits a radiation sensitization effect. This effect may be attributed to a specific small molecule present in AM known as ononin. Currently, radiation sensitizers are predominantly found in nitrazole drugs and nanomaterials, with no existing reports on the radiation sensitization properties of ononin, nor its underlying mechanism. PURPOSE: This study aims to investigate the sensitization effect of the small molecule ononin derived from AM on lung cancer radiotherapy, elucidating its specific molecular mechanism of action. Additionally, the safety profile of combining astragalus small molecule ononin with radiation therapy will be evaluated. METHODS: The effective concentration of ononin was determined through cell survival experiments, and the impact of ononin combined with varying doses of radiation on lung cancer cells was observed using CCK-8 and cell cloning experiments. The apoptotic effect of ononin combined with radiation on lung cancer cells was assessed using Hochester staining, flow cytometry, and WB assay. Additionally, WB and immunofluorescence analysis were conducted to investigate the influence of ononin on HIF-1α/VEGF pathway. Furthermore, Molecular Dynamics Simulation was employed to validate the targeted binding ability of ononin and HIF-1α. A lung cancer cell line was established to investigate the effects of knockdown and overexpression of HIF-1α. Subsequently, the experiment was repeated using tumor bearing nude mice and C57BL/6 mouse models in an in vivo study. Tumor volume was measured using a vernier caliper, while HE, immunohistochemistry, and immunofluorescence techniques were employed to observe the effects of ononin combined with radiation on tumor morphology, proliferation, and apoptosis. Additionally, Immunofluorescence was employed to examine the impact of ononin on HIF-1α/VEGF pathway in vivo, and its effect on liver function in mice was assessed through biochemistry analysis. RESULTS: At a concentration of 25 µM, ononin did not affect the proliferation of lung epithelial cells but inhibited the survival of lung cancer cells. In vitro experiments demonstrated that the combination of ononin and radiation could effectively inhibit the growth of lung cancer cells, induce apoptosis, and suppress the excessive activation of the Hypoxia inducible factor 1 alpha/Vascular endothelial growth factor pathway. In vivo experiments showed that the combination of ononin and radiation reduced the size and proliferation of lung cancer tumors, promoted cancer cell apoptosis, mitigated abnormal activation of the Hypoxia inducible factor 1 alpha pathway, and protected against liver function damage. CONCLUSION: This study provides evidence that the combination of AM and its small molecule ononin can enhance the sensitivity of lung cancer to radiation. Additionally, it has been observed that this combination can specifically target HIF-1α and exert its effects. Notably, ononin exhibits the unique ability to protect liver function from damage while simultaneously enhancing the tumor-killing effects of radiation, thereby demonstrating a synergistic and detoxifying role in tumor radiotherapy. These findings contribute to the establishment of a solid basis for the development of novel radiation sensitizers derived from traditional Chinese medicine.

Prognosis prediction and risk stratification of transarterial chemoembolization or intraarterial chemotherapy for unresectable hepatocellular carcinoma based on machine learning.

OBJECTIVE: To develop and validate a risk scoring scale model (RSSM) for stratifying prognostic risk after intra-arterial therapies (IATs) for hepatocellular carcinoma (HCC). METHODS: Between February 2014 and October 2022, 2338 patients with HCC who underwent initial IATs were consecutively enrolled. These patients were divided into training datasets (TD, n = 1700), internal validation datasets (ITD, n = 428), and external validation datasets (ETD, n = 200). Five-years death was used to predict outcome. Thirty-four clinical information were input and five supervised machine learning (ML) algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBT), and Random Forest (RF), were compared using the areas under the receiver operating characteristic (AUC) with DeLong test. The variables with top important ML scores were used to build the RSSM by stepwise Cox regression. RESULTS: The CatBoost model achieved the best discrimination when 12 top variables were input, with the AUC of 0.851 (95% confidence intervals (CI), 0.833-0.868) for TD, 0.817 (95%CI, 0.759-0.857) for ITD, and 0.791 (95%CI, 0.748-0.834) for ETD. The RSSM was developed based on the immune checkpoint inhibitors (ICI) (hazard ratios (HR), 0.678; 95%CI 0.549, 0.837), tyrosine kinase inhibitors (TKI) (HR, 0.702; 95%CI 0.605, 0.814), local therapy (HR, 0.104; 95%CI 0.014, 0.747), response to the first IAT (HR, 4.221; 95%CI 2.229, 7.994), tumor size (HR, 1.054; 95%CI 1.038, 1.070), and BCLC grade (HR, 2.375; 95%CI 1.950, 2.894). Kaplan-Meier analysis confirmed the role of RSSM in risk stratification (p < 0.001). CONCLUSIONS: The RSSM can stratify accurately prognostic risk for HCC patients received IAT. On the basis, an online calculator permits easy implementation of this model. CLINICAL RELEVANCE STATEMENT: The risk scoring scale model could be easily implemented for physicians to stratify risk and predict prognosis quickly and accurately, thereby serving as a more favorable tool to strengthen individualized intra-arterial therapies and management in patients with unresectable hepatocellular carcinoma. KEY POINTS: • The Categorical Gradient Boosting (CatBoost) algorithm achieved the optimal and robust predictive ability (AUC, 0.851 (95%CI, 0.833-0.868) in training datasets, 0.817 (95%CI, 0.759-0.857) in internal validation datasets, and 0.791 (95%CI, 0.748-0.834) in external validation datasets) for prediction of 5-years death of hepatocellular carcinoma (HCC) after intra-arterial therapies (IATs) among five machine learning models. • We used the SHapley Additive exPlanations algorithms to explain the CatBoost model so as to resolve the black boxes of machine learning principles. • A simpler restricted variable, risk scoring scale model (RSSM), derived by stepwise Cox regression for risk stratification after intra-arterial therapies for hepatocellular carcinoma, provides the potential forewarning to adopt combination strategies for high-risk patients.

Efficiency and safety of hepatic arterial infusion chemotherapy (HAIC) combined with anti-PD1 therapy versus HAIC monotherapy for advanced hepatocellular carcinoma: A multicenter propensity score matching analysis.

PURPOSE: To investigate the clinical efficacy and safety of combination therapy of hepatic arterial infusion chemotherapy (HAIC) and anti-programmed cell death protein-1 (PD-1) therapy in the treatment of advanced hepatocellular carcinoma (HCC). METHODS: In this retrospective clinical research, from March 2018 to December 2019, 1158 HCC patients categorized as BCLC stage C were reviewed for eligibility. We utilized propensity score matching (PSM) to mitigate initial disparities between the groups. The evaluation of the best tumor response was conducted in accordance with mRECIST 1.1 criteria. The difference in survival outcomes including overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) between groups were compared. RESULTS: Following the eligibility review, 453 patients underwent a combined treatment of HAIC with PD1 inhibitors (HAIC-PD1 group), while 221 patients received HAIC monotherapy (HAIC group) met the inclusion criteria and were finally enrolled in this study. In the entire cohort, the HAIC-PD1 group exhibited significantly prolonged overall survival (median overall survival: 40.4 months vs. 9.7 months, p < 0.001) and progression-free survival (median progression-free survival: 22.1 months vs. 5.8 months, p < 0.001). By propensity score, patients were matched according to baseline differences, resulting in all 442 patients in group HAIC-PD1 (n = 221) and group HAIC (n = 221). After PSM adjustment, as well, the survival of the HAIC-PD1 group was still distinctly longer than the HAIC group (median overall survival time, 40.4 months vs 9.7 months, p < 0.001; median progression-free survival, 22.1 months vs 5.7 months, p < 0.001). Univariate and multivariable analysis demonstrated that AFP level, metastasis, and therapeutic schedule were independent predictive factors for overall survival. CONCLUSION: The combination therapy of HAIC and PD1 inhibitors successfully extended OS to advanced HCC patients and could be a better choice than HAIC monotherapy.