Implementation of antibody-drug conjugates in HER2-positive solid cancers: Recent advances and future directions.

In recent decades, there has been a surge in the approval of monoclonal antibodies for treating a wide range of hematological and solid malignancies. These antibodies exhibit exceptional precision in targeting the surface antigens of tumors, heralding a groundbreaking approach to cancer therapy. Nevertheless, monoclonal antibodies alone do not show sufficient lethality against cancerous cells compared to chemotherapy. Consequently, a new class of anti-tumor medications, known as antibody-drug conjugates (ADCs), has been developed to bridge the divide between monoclonal antibodies and cytotoxic drugs, enhancing their therapeutic potential. ADCs are chemically synthesized by binding tumor-targeting monoclonal antibodies with cytotoxic payloads through linkers that are susceptible to cleavage by intracellular proteases. They combined the accurate targeting of monoclonal antibodies with the potent efficacy of cytotoxic chemotherapy drugs while circumventing systemic toxicity and boasting superior lethality over standalone targeted drugs. The human epidermal growth factor receptor (HER) family, which encompasses HER1 (also known as EGFR), HER2, HER3, and HER4, plays a key role in regulating cellular proliferation, survival, differentiation, and migration. HER2 overexpression in various tumors is one of the most frequently targeted antigens for ADC therapy in HER2-positive cancers. HER2-directed ADCs have emerged as highly promising treatment modalities for patients with HER2-positive cancers. This review focuses on three approved anti-HER2 ADCs (T-DM1, DS-8201a, and RC48) and reviews ongoing clinical trials and failed trials based on anti-HER2 ADCs. Finally, we address the notable challenges linked to ADC development and underscore potential future avenues for tackling these hurdles.

Novel agents and clinical trials in castration-resistant prostate cancer: latest updates from 2023 ASCO-GU Cancers Symposium.

Numerous novel and effective therapeutic agents and clinical trials addressing castration-resistant prostate cancer (CRPC) were reported during the 2023 American Society of Clinical Oncology-Genitourinary (ASCO-GU) Cancers Symposium. Notably, radionuclide drug conjugates (RDC), specifically 177Lu/111In-J591 and 225Ac-J591, exhibited enhanced therapeutic efficacy in treating patients with CRPC. Furthermore, promising treatment approaches for CRPC included dual anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and anti-programmed death-1 (PD-1) blockade in rare tumors (DART)-Lorigerlimab, prostate stem cell antigen (PSCA)-directed chimeric antigen receptor (CAR)-T cell immunotherapy-BPX-601, and protein kinase inhibitor (AKTi)-CAPltello-280. We have summarized the latest CRPC treatment strategies presented at the 2023 ASCO-GU Cancers Symposium, along with recent advances in CRPC clinical trials.

Novel ADCs and combination therapy in urothelial carcinoma: latest updates from the 2023 ASCO-GU Cancers Symposium.

Antibody-drug conjugates (ADCs) combine the cytotoxicity of small-molecule drugs with antibody targeting. Due to their precise and powerful effect, they have become a new hotspot and an important trend in the research and development of anti-tumor antibody drugs. Every year, exciting new developments and innovations in the treatment of urological tumors are introduced at the American Society of Clinical Oncology-Genitourinary (ASCO-GU) Cancers Symposium. In this article, we summarize some of the most impressive advances in new clinical trials and clinical data on ADCs in the 2023 ASCO-GU Cancers Symposium for the treatment of urothelial carcinoma.

High-Linearity Flexible Pressure Sensor Based on the Gaussian-Curve-Shaped Microstructure for Human Physiological Signal Monitoring.

Flexible pressure sensors with high-performance show broad application prospects in health monitoring, wearable electronic devices, intelligent robot sensing, and other fields. Although flexible pressure sensors have made significant progress in sensitivity and detection range, most of them still exhibit strong nonlinearity, which leads to significant troubles in signal acquisition and thus limits their popularity in practical applications. It remains a serious challenge for the flexible pressure sensor to achieve high linearity while maintaining high sensitivity. Herein, a doped sensing membrane with a uniformly distributed Gaussian-curve-shaped micropattern array was developed using the micro-electromechanical systems (MEMS) process, and a flexible sensor structure with the doped film as the core was designed and constructed. The prototype sensor has a high sensitivity of 1.77 kPa-1 and a linearity of 0.99 in the full detection range of 20 Pa to 30 kPa. In addition, its excellent performance also includes fast response/recovery times (∼25/50 ms) and long-term endurance (>10,000 cycles at 15 kPa). The prototype sensor has been successfully demonstrated in human pulse monitoring, speech recognition, and gesture recognition. The 2 × 6 sensor array can detect the spatial pressure distribution. Thus, such a microstructure shape design will open a new way to fabricate a high-linearity pressure sensor for potential applications in health monitoring, human-machine interaction, etc.

Risk factors and a predictive nomogram for hemodynamic instability during adrenalectomy for large pheochromocytomas and paragangliomas: A retrospective cohort study.

OBJECTIVE: This study aimed to investigate risk factors for intraoperative hemodynamic instability (HDI) and construct a clinical model for predicting intraoperative HDI for large pheochromocytomas and paragangliomas (PPGLs) patients. METHODS: A single-center retrospective study of the clinicopathological data of patients undergoing surgery for PPGLs larger than 5 cm in diameter was conducted. A total of 215 eligible patients were enrolled in the study. Three advanced statistical methods were used to select independent risk factors in the training cohort for constructing a nomogram for predicting intraoperative HDI. The predictive performance of the model was assessed by area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV), and calibration. Decision curve analysis (DCA) and clinical impact curves (CIC) were used to assess predictive accuracy and clinical utility. The performance of the nomogram of was further internally validated. RESULTS: Comorbid diabetes mellitus, anemia, hypoproteinemia, 24-h urine vanillylmandelic acid and intraoperative blood transfusion (P < 0.05) were identified as independent risk factors for constructing the nomogram. In the training cohort, the AUC, PPV and NPV of the nomogram were 0.846, 91.6% and 69.2%. In the validation cohort, the AUC, PPV and NPV were 0.842, 91.8% and 63.3%. These showed good predictive power of the model. The calibration curves demonstrated an optimal consistency between the nomogram-predicted and the actual observed survival probability. DCA and CIC examination showed superior clinical relevance. CONCLUSIONS: The nomogram can objectively and accurately predict intraoperative HDI in patients with large PPGLs, which can help in individualized pre-treatment decision-making.

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications.

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Knocking down NSUN5 inhibits the development of clear cell renal cell carcinoma by inhibiting the p53 pathway.

Clear cell renal cell carcinoma (ccRCC) is the most common solid renal tumor. NSUN5, a gene encoding cytosine-5 RNA methyltransferase, has rarely been reported associated with cancer. A bioinformatics analysis revealed that NSUN5 was overexpressed in ccRCC. Gene Ontology and gene set variation analyses showed that NSUN5 was associated with tumor immunity in ccRCC. The effect of immunosuppressive treatment was superior in the low-risk group compared to the high-risk group, and higher stromal score in the high-risk group relative to the low-risk group. A drug sensitivity analysis revealed that the high-risk group was more sensitive to 5-fluorouracil, mitomycin C, methotrexate, and 17-AAG, whereas the low-risk group was more sensitive to crizotinib, sorafenib, foretinib, and ivozanib. NSUN5 knockout decreased ccRCC cell proliferation. The migration speed and number of invasive cells further decreased. The percentage of apoptotic cells increased. In NSUN5-knockout cells, the levels of BAX, caspase-8, caspase-9, and p53 increased significantly, whereas those of Bcl2, CCND1, CCND3, and MMP9 decreased significantly. NSUN5 is highly expressed in ccRCC and inhibits cancer cell invasion, proliferation, and migration while promoting apoptosis by activating the p53 signaling pathway. This study provides insights into the mechanisms of action of NSUN5 in urological tumors and may contribute to improving ccRCC treatment options.

Associations between lumbar bone mineral density, serum 25-hydroxyvitamin D and history of kidney stones in adults aged 30-69 years in the USA (NHANES 2011-2018).

OBJECTIVES: Most kidney stones contain calcium, which is closely associated with human bone health. Therefore, we aimed to determine the relationship between the history of kidney stones and human bone health. This study examined the associations between lumbar bone mineral density (BMD), serum 25-hydroxyvitamin D (25-OHD) and a history of kidney stones in individuals aged between 30 years and 69 years. DESIGN AND DATA ANALYSIS: A multivariate logistic regression model was used to estimate the relationship between lumbar BMD, serum 25-OHD levels and kidney stones in this cross-sectional study. All models incorporated survey sample weights and were adjusted for covariates. SETTING: National Health and Nutrition Examination Survey (NHANES) 2011-2018. The exposure and outcomes of this study included the lumbar BMD and presence of kidney stones. PARTICIPANTS: All the 7500 participants for this cross-sectional survey were selected from the NHANES between 2011 and 2018. MAIN OUTCOME MEASURES: The main outcome of this study was the presence of kidney stones. The interviewers asked the questions on kidney stones while the respondents were at home, using a computer-assisted personal interview system. RESULTS: Lumbar BMD was negatively correlated with a history of kidney stones in all three multivariate linear regression models; the negative association existed in all genders after adjusting for all confounding factors. In the multiple regression analysis, there was an interaction between serum 25-OHD and lumbar BMD (p<0.05) regarding the influence on kidney stones; the negative association between lumbar BMD and kidney stones was more obvious in the higher 25-OHD group (≥50 nmol/L). CONCLUSION: The study results suggest that maintaining a high lumbar BMD may reduce the incidence of kidney stone formation. Simultaneously, maintaining a high serum 25-OHD level may be more beneficial in preventing the occurrence or recurrence of stones while ensuring a high lumbar BMD.

Protozoa as Hotspots for Potential Pathogens in the Drinking Water of a Subtropical Megacity: Diversity, Treatment, and Health Risk.

Drinking water systems host a wide range of microorganisms essential for biosafety. However, one major group of waterborne pathogens, protozoa, is relatively neglected compared to bacteria and other microorganisms. Until now, little is known about the growth and fate of protozoa and their associated bacteria in drinking water systems. In this study, we aim to investigate how drinking water treatment affects the growth and fate of protozoa and their associated bacteria in a subtropical megacity. The results showed that viable protozoa were prevalent in the city's tap water, and amoebae were the major component of tap water protozoa. In addition, protozoan-associated bacteria contained many potential pathogens and were primarily enriched in amoeba hosts. Furthermore, this study showed that current drinking water disinfection methods have little effect on protozoa and their associated bacteria. Besides, ultrafiltration membranes unexpectedly served as an ideal growth surface for amoebae in drinking water systems, and they could significantly promote the growth of amoeba-associated bacteria. In conclusion, this study shows that viable protozoa and their associated bacteria are prevalent in tap water, which may present an emerging health risk in drinking water biosafety.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer.

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Research on Wind Environment and Morphological Effects of High-Rise Buildings in Macau: An Example from the New Reclamation Area around Areia Preta.

The Macau peninsula is close to the tropical ocean, with a high population density and a large number of high-rise buildings, which require a windy environment with good ventilation and heat dissipation. Based on residential samples and the degree of agglomeration, the high-rise residential area in Areia Preta was selected as the focus of this study. Meanwhile, summer typhoons pose serious safety risks to high-rise buildings. Therefore, it is necessary to study the connection between spatial form and the wind environment. First of all, this research is based on relevant concepts and the wind environment evaluation system of high-rise buildings and conducts research on high-rise residential areas in Areia Preta. PHOENICS software is used to simulate the prevailing monsoon in winter and summer, as well as a typhoon in an extreme wind environment, and summarize the wind environment's characteristics. Secondly, by comparing the parameter calculation and simulation results, the possible relationship between the causes of each wind field is studied. Finally, conclusions are drawn about the urban form and wind environment of the site, and corresponding control strategies are proposed to reduce the shielding effect between buildings and typhoon damage. It can be used as a theoretical basis and reference point for urban construction and high-rise building planning and layout.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application.

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Predicting the distribution of COVID-19 through CGAN-Taking Macau as an example.

Machine learning (ML) is an innovative method that is widely used in data prediction. Predicting the COVID-19 distribution using ML is essential for urban security risk assessment and governance. This study uses conditional generative adversarial network (CGAN) to construct a method to predict the COVID-19 hotspot distribution through urban texture and business formats and establishes a relationship between urban elements and COVID-19 so that machines can automatically predict the epidemic hotspots in cities. Taking Macau as an example, this method is used to determine the correlation between the urban texture and business hotspots of Macau and the new epidemic hotspot clusters. Different types of samples afforded different epidemic prediction accuracies. The results show the following: (1) CGAN can accurately predict the distribution area of COVID-19, and the accuracy can exceed 70%. (2) The results of predicting the COVID-19 distribution through urban texture and POI data of hospitals and stations are the best, with an accuracy of more than 60% in experiments in different regions of Macau. (3) The proposed method can also predict other areas in the city that may be at risk of COVID-19 and help urban epidemic prevention and control.

Nomograms for predicting overall and cancer-specific survival of patients with chromophobe renal cell carcinoma after nephrectomy: a retrospective SEER-based study.

OBJECTIVE: We aimed to construct and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with chromophobe renal cell carcinoma (chRCC) after nephrectomy. DESIGN: This study is a retrospective cohort study. SETTING AND PARTICIPANTS: There were 2810 patients with chRCC from Surveillance, Epidemiology and End Results database diagnosed between 2010 and 2015 included in the study who were randomly divided into a training cohort (n=1970) and a validation cohort (n=840). Another single-centre external validation cohort containing 124 patients from our hospital was also involved in our study. PRIMARY AND SECONDARY OUTCOME MEASURES: OS and CSS. RESULTS: Nomograms for OS and CSS include four and five variables, respectively, from the result of least absolute shrinkage and selection operator regression analyses. Nomograms reveal the accurate discrimination by the area under the curve of receiver operating characteristic (ROC) curves and C-indexes, with a C-index value of 0.777 (95% CI 0.728 to 0.826), 0.810 (95% CI 0.747 to 0.873) and 0.863 (95% CI 0.773 to 0.953) for the training cohort, the internal validation cohort and the external validation cohort in the nomogram for OS; and a C-index value of 0.884 (95% CI 0.829 to 0.939), 0.868 (95% CI 0.772 to 0.964) and 0.862 (95% CI 0.760 to 0.964) for the training cohort, the internal validation cohort and the external validation cohort in the nomogram for CSS. It was also proven that there was a high degree of conformance between the predicted and observation results by calibration plots. In addition, the comparison of ROC curves and C-indexes between nomograms and seventh tumour, node and metastasis stage demonstrated that nomograms were better in accuracy and efficacy ability. CONCLUSIONS: We successfully constructed two accurate and effective nomograms to predict OS and CSS for patients with chRCC after nephrectomy, which can help clinical doctors choose individual treatment strategies for chRCC patients.

Enhanced microbial nitrification-denitrification processes in a subtropical metropolitan river network.

Urban rivers are hotspots of regional nitrogen (N) pollution and N transformations. Previous studies have reported that the microbial community of urban rivers was different from that of natural rivers. However, how microbial community affects N transformations in the urban rivers is still unclear. In this study, we employed N nutrients-related isotope technology (includes natural-abundance isotopes survey and isotope-labeling method) and bioinformatics methods (includes 16S rRNA high-throughput sequencing and quantitative PCR analysis) to investigate the major N transformations, microbial communities as well as functional gene abundances in a metropolitan river network. Our results suggested that the bacterial community structure in the highly urbanized rivers was characterized by higher richness, less complexity and increased abundances of nitrification and denitrifying bacterium compared to those in the suburban rivers. These differences were mainly caused by high sewage discharge and N loadings. In addition, the abundances of nitrifier gene (amoA) and denitrifier genes (nirK and nirS) were significantly higher in the highly urbanized rivers (2.36 × 103, 7.43 × 107 and 2.28 × 107 copies·mL-1) than that in the suburban rivers (0.43 × 103, 2.18 × 107 and 0.99 × 107 copies·mL-1). These changes in microbes have accelerated nitrification-denitrification processes in the highly urbanized rivers as compared to those in the suburban rivers, which was evidenced by environmental isotopes and the rates of nitrification (10.52 vs. 0.03 nmol·L-1·h-1) and denitrification (83.31 vs. 22.49 nmol·g-1·h-1). Overall, this study concluded that the excess exogenous N has significantly shaped the specific aquatic bacterial communities, which had a potential for enhancing nitrification-denitrification processes in the highly urbanized river network. This study provides a further understanding of microbial N cycling in urban river ecosystems and expands the combined application of isotopic technology and bioinformatics methods in studying biogeochemical cycling.

Angle prediction model when the imaging plane is tilted about z-axis.

Computer Tomography (CT) is a complicated imaging system, requiring highly geometric positioning. We found a special artifact caused by detection plane tilted around z-axis. In short scan cone-beam reconstruction, this kind of geometric deviation result in half circle shaped fuzzy around highlighted particles in reconstructed slices. This artifact is distinct near the slice periphery, but deficient around the slice center. We generated mathematical models, and InceptionV3-R deep network to study the slice artifact features to estimate the detector z-axis tilt angle. The testing results are: mean absolute error of 0.08819 degree, the Root mean square error of 0.15221 degree and R-square of 0.99944. A geometric deviation recover formula was deduced, which can eliminate this artifact efficiently. This research enlarges the CT artifact knowledge hierarchy, and verifies the capability of machine learning in CT geometric deviation artifact recoveries.

Reduced Preoperative Glomerular Filtration Rate Is Associated With Adverse Postoperative Oncological Prognosis in Patients Undergoing Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma: A Retrospective Cohort Study.

Objective: To evaluate the association between perioperative estimated glomerular filtration rate (eGFR) and postoperative oncological outcomes in patients with upper tract urothelial carcinoma (UTUC) treated with radical nephroureterectomy (RNU),and to evaluate the effect of sex on this association. Methods: The medical records of patients with UTUC who underwent RNU between January 2012 and December 2017 at our hospital were retrospectively reviewed. Patients were divided into three groups based on preoperative eGFRs: normal eGFR (>60 mL/min/1.73 m2; n = 179), moderately reduced eGFR (45-60 mL/min/1.73 m2; n = 45), and severely reduced eGFR (≤ 45 mL/min/1.73 m2; n = 36). Statistical analyses were performed to evaluate the prognostic impact of preoperative eGFR on prognosis. Results: Patient mean age was 66.7 ± 9.6 years, and 47.9% were female. Multivariate regression analysis based on Cox proportional risk models and Kaplan-Meier survival rates showed that lower preoperative eGFR was associated with decreased OS, PFS, and CSS. In the adjusted Cox regression model, patients with normal and moderately reduced eGFRs had a decreased hazard for mortality, with adjusted hazard ratios of 0.13 [95% confidence interval (CI): 0.07-0.26] and 0.36 (95% CI: 0.18-0.73), respectively (P < 0.001). The smooth fitting curve suggested a linear relationship between eGFR and prognostic survival. Additionally, sensitivity subgroup analyses verified an inverse relationship between the reduced eGFR and OS. Women had a lower eGFR and worse oncological outcomes than men. A nomogram for OS was developed based on multivariate analysis with a C-index of 0.754 (95% CI: 0.728-0.779). Conclusion: Preoperative renal insufficiency is strongly associated with a higher risk of cancer progression and a lower survival probability. It is important to identify preoperative renal insufficiency in patients with UTUC, particularly female patients.

Prognostic Characteristics and Immune Effects of N6-Methyladenosine and 5-Methylcytosine-Related Regulatory Factors in Clear Cell Renal Cell Carcinoma.

In recent years, methylation modification regulators have been found to have essential roles in various tumor mechanisms. However, the relationships between N6-methyladenosine (m6A) and 5-methylcytosine (m5C) regulators and clear cell renal cell carcinoma (ccRCC) remain unknown. This study investigated these relationships using the data from The Cancer Genome Atlas database. We calculated risk scores using a Lasso regression analysis and divided the patient samples into two risk groups (tumor vs. normal tissues). Furthermore, we used univariate and multivariate Cox analyses to determine independent prognostic indicators and explore correlations between the regulatory factors and immune infiltrating cell characteristics. Finally, quantitative reverse transcriptase-polymerase chain reaction (PCR) and The Human Protein Atlas were used to verify signature-related gene expression in clinical samples. We identified expression differences in 35 regulatory factors between the tumor and normal tissue groups. Next, we constructed a five-gene risk score signature (NOP2 nucleolar protein [NOP2], methyltransferase 14, N6-adenosine-methyltransferase subunit [METTL14], NOP2/Sun RNA methyltransferase 5 [NSUN5], heterogeneous nuclear ribonucleoprotein A2/B1 [HNRNPA2B1], and zinc finger CCCH-type containing 13 [ZC3H13]) using the screening criteria (p < 0.01), and then divided the cases into high- and low-risk groups based on their median risk score. We also screened for independent prognostic factors related to age, tumor grade, and risk score. Furthermore, we constructed a Norman diagram prognostic model by combining two clinicopathological characteristics, which demonstrated good prediction efficiency with prognostic markers. Then, we used a single-sample gene set enrichment analysis and the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method to evaluate the tumor microenvironment of the regulatory factor prognostic characteristics. Moreover, we evaluated five risk subgroups with different genetic signatures for personalized prognoses. Finally, we analyzed the immunotherapy and immune infiltration response and demonstrated that the high-risk group was more sensitive to immunotherapy than the low-risk group. The PCR results showed that NSUN5 and HNRNPA2B1 expression was higher in tumor tissues than in normal tissues. In conclusion, we identified five m6A and m5C regulatory factors that might be promising biomarkers for future research.

5-methylcytosine RNA methyltransferases and their potential roles in cancer.

In recent years, 5-methylcytosine (m5C) RNA modification has emerged as a key player in regulating RNA metabolism and function through coding as well as non-coding RNAs. Accumulating evidence has shown that m5C modulates the stability, translation, transcription, nuclear export, and cleavage of RNAs to mediate cell proliferation, differentiation, apoptosis, stress responses, and other biological functions. In humans, m5C RNA modification is catalyzed by the NOL1/NOP2/sun (NSUN) family and DNA methyltransferase 2 (DNMT2). These RNA modifiers regulate the expression of multiple oncogenes such as fizzy-related-1, forkhead box protein C2, Grb associated-binding protein 2, and TEA domain transcription factor 1, facilitating the pathogenesis and progression of cancers. Furthermore, the aberrant expression of methyltransferases have been identified in various cancers and used to predict the prognosis of patients. In this review, we present a comprehensive overview of m5C RNA methyltransferases. We specifically highlight the potential mechanism of action of m5C in cancer. Finally, we discuss the prospect of m5C-relative studies.

Predicting biochemical-recurrence-free survival using a three-metabolic-gene risk score model in prostate cancer patients.

BACKGROUND: Biochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival. METHODS: We analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings. RESULTS: A total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model. CONCLUSION: We constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.