Immunotherapeutic value of NUSAP1 associated with bladder cancer through a comprehensive analysis of 33 human cancer cases.

To investigate the correlation between nucleolar spindle-associated protein 1 (NUSAP1) and cancer immunotherapy across 33 different types of human cancers. We conducted an analysis of The Cancer Genome Atlas (TCGA) database to retrieve gene expression data and clinical characteristics for 33 different cancer types. The immunotherapy cohorts encompassed GSE67501, GSE78220, and IMvigor210. Relevant information was extracted from the gene expression repository. We assessed the prognostic significance of NUSAP1 by examining various clinical parameters. The single-sample gene-set enrichment analysis (ssGSEA) method was utilized to gauge NUSAP1 activity and to contrast NUSAP1 transcriptome and protein levels. We delved into the correlation between NUSAP1 and various immune processes and components to gain insights into NUSAP1's role. We also discussed coherent pathways associated with NUSAP1 signal transduction and its impact on immunotherapy biomarkers. To authenticate and validate the differential expression patterns of NUSAP1 in bladder tumor tissues versus normal bladder counterparts, we utilized Western blotting (WB), real-time quantitative polymerase chain reaction (RT-qPCR), and immunohistochemistry (IHC) techniques. NUSAP1 exhibits overexpression across a spectrum of malignancies, and its expression levels correlate with overall survival (OS), disease-specific survival, and tumor stage in specific cancer types. Furthermore, NUSAP1 expression is linked to mutations, methylation patterns, and immunotherapy responses in human cancers. Meanwhile, our experiments, involving WB, RT-qPCR, and IHC, consistently demonstrated significantly higher NUSAP1 expression in bladder tumor tissues compared to normal controls. Our study underscores the potential of NUSAP1 as a promising prognostic indicator and immunotherapeutic target for a range of malignant tumors.

TriFNet: A triple-branch feature fusion network for pH determination by surface-enhanced Raman spectroscopy.

Due to the acidic tumor microenvironment caused by metabolic changes in tumor cells, the accurate pH detection of extracellular fluid is helpful for doctors in precise tumor resection. The combination of Raman spectroscopy and deep learning provides a solution for pH detection. However, most existing studies use one-dimensional convolutional neural networks (1D-CNNs) for spectral analysis, which limits the performance due to insufficient feature extraction. In this work, we propose a 2D triple-branch feature fusion network (TriFNet) for accurate pH determination using surface-enhanced Raman spectra (SERS). Specifically, we design a triple-branch network structure by converting Raman spectra into three types of images to extensively extract complex patterns in spectra. In addition, an attention fusion module, which leverages the complementarity among features in both space and channel, is designed to obtain the valuable information, achieving further accurate pH determination. On our Raman spectral dataset containing 14,137 samples, we achieved mean absolute error (MAE) of 0.059, standard deviation of the absolute error (SD) of 0.07, root mean squared error (RMSE) of 0.092, and coefficient of determination (R2) of 0.991 on the test set. Compared with other published methods, the four metrics showed an average improvement of 47%, 39%, 43%, and 6%, respectively. In addition, visualization validates the diagnostic capability of our model to correlate with biomolecular signatures. Meanwhile, our model has robustness to different SERS chips. These results prove the potential of our method to develop an effective technology based on Raman spectroscopy for accurate pH determination to guide surgery.

Sophora flavescens alcohol extract ameliorates insomnia and promotes PI3K/AKT/BDNF signaling transduction in insomnia model rats.

Active ingredient of Sophora flavescens is reported to promote non-rapid eye movement (NREM) sleep. However, the role of Sophora flavescens alcohol extract in insomnia is elusive, which is addressed in this study, together with the exploration on its potential mechanism. An insomnia model of rats was established by para-chlorophenylalanine induction and further treated with SFAE or Zaoren Anshen capsule (ZRAS; positive control drug). Sleep quality and sleep architecture of rats were evaluated by the sleep test, electroencephalogram and electromyogram. The levels of monoamine neurotransmitters in rat hypothalamus were determined using ELISA, and the transduction of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/brain-derived neurotrophic factor (BDNF) signaling in the brain tissues of rats was examined by Western blot. SFAE and ZRAS increased the sleeping time and decreased the sleep latency of insomnia rats. SFAE reduced waking time and increased NREM and REM time, while changing power density of wakefulness, NREM sleep, and REM sleep in insomnia rats. SFAE and ZRAS upregulated levels of 5-hydroxytryptamine and 5-hydroxyindoleacetic acid, and downregulated those of norepinephrine and dopamine in insomnia rats. Besides, SFAE and ZRAS elevated BDNF expression as well as the ratios of phosphorylated (p)-PI3K/PI3K and p-AKT/AKT. The role of SFAE in insomnia model rats was similar with that of ZRAS. SFAE reduces insomnia and enhances the PI3K/AKT/BDNF signaling transduction in insomnia model rats, which can function as a drug candidate for insomnia.

Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning.

BACKGROUND: Molecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultrasound, this study developed a rapid intraoperative molecular diagnostic method based on ultrasound radio-frequency signals. METHODS: We built a brain tumor ultrasound bank with 169 cases enrolled since July 2020, of which 43483 RF signal patches from 67 cases with a pathological diagnosis of glioma were a retrospective cohort for model training and validation. IDH1 and TERT promoter (TERTp) mutations and 1p/19q co-deletion were detected by next-generation sequencing. We designed a spatial-temporal integration model (STIM) to diagnose the three molecular biomarkers, thus establishing a rapid intraoperative molecular diagnostic system for glioma, and further analysed its consistency with the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5). We tested STIM in 16-case prospective cohorts, which contained a total of 10384 RF signal patches. Two other RF-based classical models were used for comparison. Further, we included 20 cases additional prospective data for robustness test (ClinicalTrials.govNCT05656053). FINDINGS: In the retrospective cohort, STIM achieved a mean accuracy and AUC of 0.9190 and 0.9650 (95% CI, 0.94-0.99) respectively for the three molecular biomarkers, with a total time of 3 s and a 96% match to WHO CNS5. In the prospective cohort, the diagnostic accuracy of STIM is 0.85 ± 0.04 (mean ± SD) for IDH1, 0.84 ± 0.05 for TERTp, and 0.88 ± 0.04 for 1p/19q. The AUC is 0.89 ± 0.02 (95% CI, 0.84-0.94) for IDH1, 0.80 ± 0.04 (95% CI, 0.71-0.89) for TERTp, and 0.85 ± 0.06 (95% CI, 0.73-0.98) for 1p/19q. Compared to the second best available method based on RF signal, the diagnostic accuracy of STIM is improved by 16.70% and the AUC is improved by 19.23% on average. INTERPRETATION: STIM is a rapid, cost-effective, and easy-to-manipulate AI method to perform real-time intraoperative molecular diagnosis. In the future, it may help neurosurgeons designate personalized surgical plans and predict survival outcomes. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Study of radiochemotherapy decision-making for young high-risk low-grade glioma patients using a macroscopic and microscopic combined radiomics model.

OBJECTIVES: As a few types of glioma, young high-risk low-grade gliomas (HRLGGs) have higher requirements for postoperative quality of life. Although adjuvant chemotherapy with delayed radiotherapy is the first treatment strategy for HRLGGs, not all HRLGGs benefit from it. Accurate assessment of chemosensitivity in HRLGGs is vital for making treatment choices. This study developed a multimodal fusion radiomics (MFR) model to support radiochemotherapy decision-making for HRLGGs. METHODS: A MFR model combining macroscopic MRI and microscopic pathological images was proposed. Multiscale features including macroscopic tumor structure and microscopic histological layer and nuclear information were grabbed by unique paradigm, respectively. Then, these features were adaptively incorporated into the MFR model through attention mechanism to predict the chemosensitivity of temozolomide (TMZ) by means of objective response rate and progression free survival (PFS). RESULTS: Macroscopic tumor texture complexity and microscopic nuclear size showed significant statistical differences (p < 0.001) between sensitivity and insensitivity groups. The MFR model achieved stable prediction results, with an area under the curve of 0.950 (95% CI: 0.942-0.958), sensitivity of 0.833 (95% CI: 0.780-0.848), specificity of 0.929 (95% CI: 0.914-0.936), positive predictive value of 0.833 (95% CI: 0.811-0.860), and negative predictive value of 0.929 (95% CI: 0.914-0.934). The predictive efficacy of MFR was significantly higher than that of the reported molecular markers (p < 0.001). MFR was also demonstrated to be a predictor of PFS. CONCLUSIONS: A MFR model including radiomics and pathological features predicts accurately the response postoperative TMZ treatment. CLINICAL RELEVANCE STATEMENT: Our MFR model could identify young high-risk low-grade glioma patients who can have the most benefit from postoperative upfront temozolomide (TMZ) treatment. KEY POINTS: • Multimodal radiomics is proposed to support the radiochemotherapy of glioma. • Some macro and micro image markers related to tumor chemotherapy sensitivity are revealed. • The proposed model surpasses reported molecular markers, with a promising area under the curve (AUC) of 0.95.

A real-world study of recombinant human endostatin combined with PD-1/PD-L1 blockade and chemotherapy for patients with advanced non-small cell lung cancer negative for actionable molecular biomarkers.

The ongoing ENPOWER study exploring the efficacy and safety of the recombinant human endostatin (endostar) combined with programmed cell death 1 antibody sintilimab and chemotherapy showed encouraging efficacy and safety in advanced non-squamous non-small cell lung cancer. To evaluate the real-world efficacy and safety of endostar combined with immune checkpoint inhibitor and chemotherapy (EIC) for advanced non-squamous non-small cell lung cancer patients negative for actionable molecular biomarkers (NSCLCnm), patients with advanced NSCLCnm hospitalized to Zhejiang Provincial People's Hospital from January 2020 to December 2022 were screened for eligibility. The included patients were analyzed for the objective response rate (ORR) and disease control rate (DCR). The pre- and posttreatment expression levels of serum tumor associated biomarkers, chemokines and subpopulations of immune cells in peripheral blood were compared. For the 31 patients with advanced NSCLCnm treated with EIC, the median follow-up and treatment cycles were 18.0 months and 4, respectively. The ORR and DCR were 38.7% and 90.3%, respectively. For those who received EIC as first-line treatment, the ORR and DCR were 63.2% and 94.7%, respectively. EIC significantly decreased expression levels of carcinoma antigen 125, carcinoma embryonic antigen and cytokeratin 19 (P<0.05) in patients who were partial remission or stable disease. Among the 31 patients, 27 (87.1%) experienced at least 1 treatment-related adverse events, and 13 (41.9%) had the treatment-related adverse events of grade 3 or higher. No antiangiogenesis-related adverse events were observed. The current study showed that EIC was potentially effective for patients with NSCLCnm, especially when used as first-line therapy, and well tolerated.

Case Report: Life-threatening pancytopenia with tislelizumab followed by cerebral infarction in a patient with lung adenocarcinoma.

Immune checkpoint inhibitors (ICIs) are an integral antitumor therapy for many malignancies. Most patients show very good tolerability to ICIs; however, serious immune-related adverse events (irAEs) with ICIs have been well documented and prevent some patients from continuing ICIs or even become the direct cause of patient death. Cytopenia is a rare irAE but can be life-threatening. Here, we present the case of a 66-year-old male patient with metastatic lung adenocarcinoma who received two doses of chemotherapy + PD-1 antibody tislelizumab and developed pancytopenia after each dose. Although the first episode of pancytopenia resolved with a treatment regimen of granulocyte colony-stimulating factor (G-CSF), thrombopoietin (TPO), and red blood cell and platelet transfusion, the second episode showed extreme resistance to these treatments and improved only after the administration of steroids. His second pancytopenia episode resolved after a long course of treatment with methylprednisolone, G-CSF, TPO, hetrombopag and multiple red blood cell and platelet transfusions. However, he suffered a cerebral infarction when his platelet count was in the normal range and gradually recovered 1 week later. This case highlights the importance of the early recognition and management of hematological irAEs.

OCIF: automatically learning the optimized clinical information fusion method for computer-aided diagnosis tasks.

PURPOSE: In computer-aided diagnosis, the fusion of image features extracted from neural networks and clinical information is crucial to improve diagnostic accuracy. How to integrate low-dimensional clinical information (LDCF) with high-dimensional network features (HDNF) is an urgent problem to be solved. We offer a new network search framework to address this problem, which can provide optimized LDCF fusion and efficient dimensionality reduction in HDNF. METHODS: OCIF innovatively uses Gaussian process optimization to explore the search space for the number of fully connected (FC) layers, the number of neurons in each FC layer, the activation function, the dropout factor, and whether to add clinical information to each FC layer. Moreover, OCIF employs transfer learning to reduce the training parameter space and improve search efficiency. To evaluate the effectiveness of the proposed OCIF, we utilized three popular end-to-end overall survival (OS) time prediction models to predict the three classes. RESULTS: Our experimental results show that applying OCIF to a classical computer-aided diagnosis neural network can improve classification accuracy. Experiments on the 2020 BRATS dataset prove that OCIF achieves satisfactory performance, with an accuracy of 0.684, precision of 0.735, recall of 0.684, and F1-score of 0.675 on the OS time prediction task. CONCLUSION: OCIF effectively and creatively combines clinical information and network features, leveraging both clinical information and image features to enhance the accuracy of the final diagnosis. Our experiments demonstrate that the use of OCIF can significantly improve computer-aided diagnosis accuracy, and the approach has the potential to be extended to other medical classification tasks as well.

Intra-Operative Definition of Glioma Infiltrative Margins by Visualizing Immunosuppressive Tumor-Associated Macrophages.

Accurate delineation of glioma infiltrative margins remains a challenge due to the low density of cancer cells in these regions. Here, a hierarchical imaging strategy to define glioma margins by locating the immunosuppressive tumor-associated macrophages (TAMs) is proposed. A pH ratiometric fluorescent probe CP2-M that targets immunosuppressive TAMs by binding to mannose receptor (CD206) is developed, and it subsequently senses the acidic phagosomal lumen, resulting in a remarkable fluorescence enhancement. With assistance of CP2-M, glioma xenografts in mouse models with a tumor-to-background ratio exceeding 3.0 for up to 6 h are successfully visualized. Furthermore, by intra-operatively mapping the pH distribution of exposed tissue after craniotomy, the glioma allograft in rat models is precisely excised. The overall survival of rat models significantly surpasses that achieved using clinically employed fluorescent probes. This work presents a novel strategy for locating glioma margins, thereby improving surgical outcomes for tumors with infiltrative characteristics.

Dietary Methionine Restriction Improves Gastrocnemius Muscle Glucose Metabolism through Improved Insulin Secretion and H19/IRS-1/Akt Pathway in Middle-Aged Mice.

Methionine restriction (MR) improves glucose metabolism. In skeletal muscle, H19 is a key regulator of insulin sensitivity and glucose metabolism. Therefore, this study aims to reveal the underlying mechanism of H19 upon MR on glucose metabolism in skeletal muscle. Middle-aged mice were fed MR diet for 25 weeks. Mouse islets ß cell line ß-TC6 cells and mouse myoblast cell line C2C12 cells were used to establish the apoptosis or insulin resistance model. Our findings showed that MR increased B-cell lymphoma-2 (Bcl-2) expression, deceased Bcl-2 associated X protein (Bax), cleaved cysteinyl aspartate-specific proteinase-3 (Caspase-3) expression in pancreas, and promoted insulin secretion of ß-TC6 cells. Meanwhile, MR increased H19 expression, insulin Receptor Substrate-1/insulin Receptor Substrate-2 (IRS-1/IRS-2) value, protein Kinase B (Akt) phosphorylation, glycogen synthase kinase-3ß (GSK3ß) phosphorylation, and hexokinase 2 (HK2) expression in gastrocnemius muscle and promoted glucose uptake in C2C12 cells. But these results were reversed after H19 knockdown in C2C12 cells. In conclusion, MR alleviates pancreatic apoptosis and promotes insulin secretion. And MR enhances gastrocnemius muscle insulin-dependent glucose uptake and utilization via the H19/IRS-1/Akt pathway, thereby ameliorating blood glucose disorders and insulin resistance in high-fat-diet (HFD) middle-aged mice.

Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.

Elastography ultrasound (EUS) imaging is a vital ultrasound imaging modality. The current use of EUS faces many challenges, such as vulnerability to subjective manipulation, echo signal attenuation, and unknown risks of elastic pressure in certain delicate tissues. The hardware requirement of EUS also hinders the trend of miniaturization of ultrasound equipment. Here we show a cost-efficient solution by designing a deep neural network to synthesize virtual EUS (V-EUS) from conventional B-mode images. A total of 4580 breast tumor cases were collected from 15 medical centers, including a main cohort with 2501 cases for model establishment, an external dataset with 1730 cases and a portable dataset with 349 cases for testing. In the task of differentiating benign and malignant breast tumors, there is no significant difference between V-EUS and real EUS on high-end ultrasound, while the diagnostic performance of pocket-sized ultrasound can be improved by about 5% after V-EUS is equipped.

Mechanisms and strategies to enhance penetration during intravesical drug therapy for bladder cancer.

Bladder cancer (BCa) is one of the most prevalent cancers worldwide. The effectiveness of intravesical therapy for bladder cancer, however, is limited due to the short dwell time and the presence of permeation barriers. Considering the histopathological features of BCa, the permeation barriers for drugs to transport across consist of a mucus layer and a nether tumor physiological barrier. Mucoadhesive delivery systems or mucus-penetrating delivery systems are developed to enhance their retention in or penetration across the mucus layer, but delivery systems that are capable of mucoadhesion-to-mucopenetration transition are more efficient to deliver drugs across the mucus layer. For the tumor physiological barrier, delivery systems mainly rely on four types of penetration mechanisms to cross it. This review summarizes the classical and latest approaches to intravesical drug delivery systems to penetrate BCa.

Methionine-Restricted Diet: A Feasible Strategy Against Chronic or Aging-Related Diseases.

Dietary methionine restriction (MR) has been associated with multifaceted health-promoting effects. MR is conducive to prevention of several chronic diseases and cancer, and extension of lifespan. A growing number of studies on new phenotypes and mechanisms of MR have become available in the past five years, especially in angiogenesis, neurodegenerative diseases, intestinal microbiota, and intestinal barrier function. In this review, we summarize the characteristics and advantages of MR, and current knowledge on the physiological responses and effects of MR on chronic diseases and aging-associated pathologies. Potential mechanisms, in which hydrogen sulfide, fibroblast growth factor 21, gut microbiota, short-chain fatty acids, and so on are involved, are discussed. Moreover, directions for epigenetics and gut microbiota in an MR diet are presented in future perspectives. This review comprehensively summarizes the novel roles and interpretations of the mechanisms underlying MR in the prevention of chronic diseases and aging.

CD3 high and FoxP3 - tumor-infiltrating lymphocytes in the invasive margin as a favorable prognostic marker in patients with invasive urothelial carcinoma of the bladder.

Tumor-infiltrating lymphocytes (TILs) have been extensively explored as prognostic biomarkers and cellular immunotherapy methods in cancer patients. However, the prognostic significance of TILs in bladder cancer remains unresolved. We evaluated the prognostic effect of TILs in bladder cancer patients. Sixty-four bladder cancer patients who underwent surgical resection between 2018 and 2020 in Zhejiang Provincial People's Hospital were analyzed in this study. Immunohistochemistry was used to evaluate CD3, CD4, CD8, and FoxP3 expression on TILs in the invasive margin of tumor tissue, and the presence of TIL subsets was correlated with the disease-free survival (DFS) of bladder cancer patients. The relationship between clinical-pathological features and DFS were analyzed. A high level of CD3 + TILs (CD3 high TILs) ( P = 0.027) or negative expression of FoxP3 TILs (FoxP3 - TILs) ( P = 0.016) was significantly related to better DFS in bladder cancer patients. Those with CD3 high FoxP3 - TILs had the best prognosis compared to those with CD3 high FoxP3 + TILs or CD3 low FoxP3 - TILs ( P = 0.0035). Advanced age [HR 4.57, (1.86-11.25); P = 0.001], CD3 low TILs [HR 0.21, (0.06-0.71); P = 0.012], CD8 low TILs [HR 0.34, (0.12-0.94); P = 0.039], and FoxP3 + TILs [HR 10.11 (1.96-52.27); P = 0.006] in the invasive margin were associated with a worse prognosis (DFS) by multivariate analysis. In conclusion, we demonstrated that CD3 high , FoxP3 - , and CD3 high FoxP3 - TILs in the invasive margin were significantly associated with better DFS. CD8 high and CD4 high TILs in the invasive margin tended to predict better DFS in bladder cancer. Patients with CD4 high CD8 high TILs in the invasive margin were likely to have a better prognosis.

The detection of prostate cancer based on ultrasound RF signal.

Objective: The diagnosis of prostate cancer has been a challenging task. Compared with traditional diagnosis methods, the radiofrequency (RF) signal is not only non-invasive but also rich in microscopic lesion information. This paper proposes a novel and accurate method for detecting prostate cancer based on the ultrasound RF signal. Method: Our approach is based on low-dimensional features in the frequency domain and high-throughput features in the spatial domain. The whole process could be divided into two parts: first, we calculate three feature maps from the ultrasound original RF signal, and 1,050 radiomics features are extracted from the three feature maps; second, we extracted 37 spectral features from the normalized frequency spectrum after Fourier transform. Results: We use LASSO regression as the method for feature selection; moreover, we use support vector machine (SVM) for classification 10-fold cross-validation for examining the classification performance of the SVM. An AUC (area under the receiver operating characteristic curve) of 0.84 was obtained on 71 subjects. Conclusions: Our method is feasible to detect prostate cancer based on the ultrasound RF signal with superior classification performance.

A novel T-cell proliferation-associated regulator signature pre-operatively predicted the prognostic of bladder cancer.

Background: Bladder cancer (BCa) is a remarkably malignant and heterogeneous neoplastic disease, and its prognosis prediction is still challenging. Even with the mounting researches on the mechanisms of tumor immunotherapy, the prognostic value of T-cell proliferation regulators in bladder cancer remains elusive. Methods: Herein, we collected mRNA expression profiles and relevant clinical information of bladder cancer sufferers from a publicly available data base. Then, the LASSO Cox regression model was utilized to establish a multi-gene signature for the TCGA cohort to predict the prognosis and staging of bladder cancer. Eventually, the predictive power of the model was validated by randomized grouping. Results: The outcomes revealed that most genes related to T-cell proliferation in the TCGA cohort exhibited different expressions between BCa cells and neighboring healthy tissues. Univariable Cox regressive analyses showed that four DEGs were related to OS in bladder cancer patients (p<0.05). We constructed a histogram containing four clinical characteristics and separated sufferers into high- and low-risk groups. High-risk sufferers had remarkably lower OS compared with low-risk sufferers (P<0.001). Eventually, the predictive power of the signature was verified by ROC curve analyses, and similar results were obtained in the validation cohort. Functional analyses were also completed, which showed the enrichment of immune-related pathways and different immune status in the two groups. Moreover, by single-cell sequencing, our team verified that CXCL12, a T-lymphocyte proliferation regulator, influenced bladder oncogenesis and progression by depleting T-lymphocyte proliferation in the tumor microenvironment, thus promoting tumor immune evasion. Conclusion: This study establishes a novel T cell proliferation-associated regulator signature which can be used for the prognostic prediction of bladder cancer. The outcomes herein facilitate the studies on T-cell proliferation and its immune micro-environment to ameliorate prognoses and immunotherapeutic responses.

A novel marker based on necroptosis-related long non-coding RNA for forecasting prognostic in patients with clear cell renal cell carcinoma.

Background: The incidence of clear cell renal cell carcinoma (ccRCC) is high and has increased gradually in recent years. At present, due to the lack of effective prognostic indicators, the prognosis of ccRCC patients is greatly affected.Necroptosis is a type of cell death, and along with cell necrosis is considered a new cancer treatment strategy. The aim of this study was to construct a new marker for predicting the prognosis of ccRCC patients based on long non-coding RNA (nrlncRNAs) associated with necroptosis. Methods: RNA sequence data and clinical information of ccRCC patients from the Cancer Genome Atlas database (TCGA) were downloaded. NrlncRNA was identified by Pearson correlation study. The differentially expressed nrlncRNA and nrlncRNA pairs were identified by univariate Cox regression and Lasso-Cox regression. Finally, a Kaplan-Meier survival study, Cox regression, clinicopathological features correlation study, and receiver operating characteristic (ROC) spectrum were used to evaluate the prediction ability of 25-nrlncrnas for markers. In addition, correlations between the risk values and sensitivity to tumor-infiltrating immune cells, immune checkpoint inhibitors, and targeted drugs were also investigated. Results: In the current research, a novel marker of 25-nrlncRNAs pairs was developed to improve prognostic prediction in patients with ccRCC. Compared with clinicopathological features, nrlncRNAs had a higher diagnostic validity for markers, with the 1-year, 3-years, and 5-years operating characteristic regions being 0.902, 0.835, and 0.856, respectively, and compared with the stage of 0.868, an increase of 0.034. Cox regression and stratified survival studies showed that this marker could be an independent predictor of ccRCC patients. In addition, patients with different risk scores had significant differences in tumor-infiltrating immune cells, immune checkpoint, and semi-inhibitory concentration of targeted drugs. The feature could be used to evaluate the clinical efficacy of immunotherapy and targeted drug therapy. Conclusion: 25-nrlncRNAs pair markers may help to evaluate the prognosis and molecular characteristics of ccRCC patients, which improve treatment methods and can be more used in clinical practice.

Immunotherapeutic Value of Transcription Factor 19 (TCF19) Associated with Renal Clear Cell Carcinoma: A Comprehensive Analysis of 33 Human Cancer Cases.

Background: We aimed to study the relationship between transcription factor 19 (TCF19) and cancer immunotherapy in the 33 types of human cancers. Methods: The Cancer Genome Atlas database was analyzed to obtain the gene expression data and clinical characteristics for the cases of 33 types of cancers. GSE67501, GSE78220, and IMvigor 210 were included in the immunotherapy cohorts. Relevant data were obtained by analyzing the gene expression database. The prognostic value of TCF19 was determined by analyzing various clinical parameters, such as survival duration, age, the stage of the tumor, and sex of the patients. The single-sample gene set enrichment analysis method was used to determine the activity of TCF19 and the method was also used to assess the differences between the TCF19 transcriptome and protein levels. The correlation between TCF19 and various immune processes and elements such as immunosuppressants, stimulants, and major histocompatibility complexes were analyzed to gain insights into the role of TCF19. The coherent paths associated with the process of TCF19 signal transduction and the influence of TCF19 on immunotherapy biomarkers have also been discussed herein. Finally, three independent immunotherapy methods were used to understand the relationship between TCF19 and immunotherapy response. Results: It was observed that TCF19 was not significantly influenced by the age (5/33), sex (3/33), or tumor stage (3/21) of cancer patients. But the results revealed that TCF19 exhibited a potential prognostic value and could predict the survival rate of the patients. In some cases of this study, the activity and expression of TCF19 were taken at the same level (7/33). Conclusion: TCF19 is strongly related to immune cell infiltration, immunomodulators, and immunotherapy markers. Our study demonstrated that high expression levels of TCF19 are strongly linked with the immune-related pathways. Nevertheless, it is noteworthy that TCF19 is not significantly associated with immunotherapy response.

A comprehensive review of traditional uses, phytochemistry and pharmacology of Reynoutria genus.

OBJECTIVES: The genus Reynoutria belonging to the family Polygonaceae is widely distributed in the north temperate zone and used in folk medicine. It is administered as a sedative, tonic and digestive, also as a treatment for canities and alopecia. Herein, we reported a review on traditional uses, phytochemistry and pharmacology reported from 1985 up to early 2022. All the information and studies concerning Reynoutria plants were summarized from the library and digital databases (e.g. ScienceDirect, SciFinder, Medline PubMed, Google Scholar, and CNKI). KEY FINDINGS: A total of 185 articles on the genus Reynoutria have been collected. The phytochemical investigations of Reynoutria species revealed the presence of more than 277 chemical components, including stilbenoids, quinones, flavonoids, phenylpropanoids, phospholipids, lactones, phenolics and phenolic acids. Moreover, the compounds isolated from the genus Reynoutria possess a wide spectrum of pharmacology such as anti-atherosclerosis, anti-inflammatory, antioxidative, anticancer, neuroprotective, anti-virus and heart protection. SUMMARY: In this paper, the traditional uses, phytochemistry and pharmacology of genus Reynoutria were reviewed. As a source of traditional folk medicine, the Reynoutria genus have high medicinal value and they are widely used in medicine. Therefore, we hope our review can help genus Reynoutria get better development and utilization.

A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma.

Objective: Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration. Methods: Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression. Results: We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate. Conclusion: We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses.