ABSTRACT
Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of â¼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.
Subject(s)
Single-Cell Analysis , Transcriptome , Humans , Cell Nucleus/metabolism , Cell Nucleus/genetics , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/pathology , RNA/genetics , Sequence Analysis, RNA , Kidney Neoplasms/genetics , Kidney Neoplasms/pathology , High-Throughput Nucleotide SequencingABSTRACT
BACKGROUND: Identifying lymph node metastasis (LNM) relies mainly on indirect radiology. Current studies omitted the quantified associations with traits beyond cancer types, failing to provide generalisation performance across various tumour types. METHODS: 4400 whole slide images across 11 cancer types were collected for training, cross-verification, and external validation of the pan-cancer lymph node metastasis (PC-LNM) model. We proposed an attention-based weakly supervised neural network based on self-supervised cancer-invariant features for the prediction task. RESULTS: PC-LNM achieved a test area under the curve (AUC) of 0.732 (95% confidence interval: 0.717-0.746, P < 0.0001) in fivefold cross-validation of multiple cancer types, which also demonstrated good generalisation in the external validation cohort with AUC of 0.699 (95% confidence interval: 0.658-0.737, P < 0.0001). The interpretability results derived from PC-LNM revealed that the regions with the highest attention scores identified by the model generally correspond to tumours with poorly differentiated morphologies. PC-LNM achieved superior performance over previously reported methods and could also act as an independent prognostic factor for patients across multiple tumour types. DISCUSSION: We presented an automated pan-cancer model for predicting the LNM status from primary tumour histology, which could act as a novel prognostic marker across multiple cancer types.
Subject(s)
Deep Learning , Humans , Lymphatic Metastasis/pathology , Prognosis , Retrospective Studies , Lymph Nodes/pathologyABSTRACT
This study aimed to evaluate the effects of different vaccine regimens on mild and asymptomatic infections with SARS-CoV-2 Omicron BA.2 variant in Shanghai. All asymptomatic patients and those with mild symptoms of Omicron infections were recruited from three major Fangcang shelter hospitals between March 26, 2022 and May 20, 2022. Nucleic acid for SARS-CoV-2 by real-time reverse-transcription polymerase chain reaction methods in nasopharyngeal swabs was assessed every day during the hospitalization. The value of cycle threshold lower than 35 was considered as positive result of SARS-CoV-2. A total of 214 592 cases were included in this study. The proportion of the asymptomatic patients was 76.90% and 23.10% of the recruited patients had mild symptoms. The median (interquartile range [IQR]: 25-75) duration of viral shedding (DVS) was 7 (5-10) days among all participants. The DVS varied greatly among different age groups. Children and the elderly had longer DVS compared with the adults. The booster shot of inactivated vaccine contributed to the shorter DVS in patients aged ≥70 years compared with the unvaccinated patients (8 [6-11] vs. 9 [6-12] days, p = 0.002]. Full inactivated vaccine regimen contributed to the shorter DVS in patients aged 3-6 years (7 [5-9] vs. 8 [5-10] days, p = 0.001]. In conclusion, the full inactivated vaccine regimen on children aged 3-6 years and booster inactivated vaccine regimen on the elderly aged ≥70 years appeared to be effective in reducing DVS. The booster vaccine regimen should be rigorously promoted and implemented.
Subject(s)
Asymptomatic Infections , COVID-19 , Adult , Child , Aged , Humans , Asymptomatic Infections/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2/genetics , China/epidemiology , VaccinationABSTRACT
BACKGROUND: Traditional histopathology performed by pathologists through naked eyes is insufficient for accurate survival prediction of clear cell renal cell carcinoma (ccRCC). METHODS: A total of 483 whole slide images (WSIs) data from three patient cohorts were retrospectively analyzed. We performed machine learning algorithm to identify optimal digital pathological features and constructed machine learning-based pathomics signature (MLPS) for ccRCC patients. Prognostic performance of the prognostic model was also verified in two independent validation cohorts. RESULTS: MLPS could significantly distinguish ccRCC patients with high survival risk, with hazard ratio of 15.05, 4.49 and 1.65 in three independent cohorts, respectively. Cox regression analysis revealed that the MLPS could act as an independent prognostic factor for ccRCC patients. Integration nomogram based on MLPS, tumour stage system and tumour grade system improved the current survival prediction accuracy for ccRCC patients, with area under curve value of 89.5%, 90.0%, 88.5% and 85.9% for 1-, 3-, 5- and 10-year disease-free survival prediction. DISCUSSION: The machine learning-based pathomics signature could act as a novel prognostic marker for patients with ccRCC. Nevertheless, prospective studies with multicentric patient cohorts are still needed for further verifications.
Subject(s)
Carcinoma, Renal Cell/pathology , Image Interpretation, Computer-Assisted/methods , Kidney Neoplasms/pathology , Carcinoma, Renal Cell/mortality , Female , Humans , Kidney Neoplasms/mortality , Machine Learning , Male , Neoplasm Grading , Neoplasm Staging , Nomograms , Prognosis , Prospective Studies , Regression Analysis , Retrospective Studies , Survival AnalysisABSTRACT
BACKGROUND: It is of great urgency to explore useful prognostic markers for patients with clear cell renal cell carcinoma (ccRCC). Prognostic models based on ferroptosis-related gene (FRG) in ccRCC is poorly reported for now. METHODS: Comprehensive analysis of 22 FRGs were performed in 629 ccRCC samples from two independent patient cohorts. We carried out least absolute shrinkage and selection operator analysis to screen out prognosis-related FRGs and constructed prognosis model for patients with ccRCC. Weighted gene co-expression network analysis was also carried out for potential functional enrichment analysis. RESULTS: Based on the TCGA cohort, a total of 11 prognosis-associated FRGs were selected for the construction of the prognosis model. Significantly differential overall survival (hazard ratio = 3.61, 95% CI: 2.68-4.87, p < 0.0001) was observed between patients with high and low FRG score in the TCGA cohort, which was further verified in the CPTAC cohort with hazard ratio value of 5.13 (95% CI: 1.65-15.90, p = 0.019). Subgroup survival analysis revealed that our FRG score could significantly distinguish patients with high survival risk among different tumor stages and different tumor grades. Functional enrichment analysis illustrated that the process of cell cycle, including cell cycle-mitotic pathway, cytokinesis pathway and nuclear division pathway, might be involved in the regulation of ccRCC through ferroptosis. CONCLUSIONS: We developed and verified a FRG signature for the prognosis prediction of patients with ccRCC, which could act as a risk factor and help to update the tumor staging system when integrated with clinicopathological characteristics. Cell cycle-related pathways might be involved in the regulation of ccRCC through ferroptosis.
Subject(s)
Carcinoma, Renal Cell/genetics , Cell Cycle/genetics , Ferroptosis/genetics , Genetic Testing/statistics & numerical data , Kidney Neoplasms/genetics , Aged , Biomarkers, Tumor/genetics , Carcinoma, Renal Cell/mortality , Cohort Studies , Female , Gene Expression Regulation, Neoplastic , Humans , Kidney Neoplasms/mortality , Male , Middle Aged , Neoplasm Staging , Nomograms , Predictive Value of Tests , Prognosis , Proportional Hazards Models , Survival AnalysisABSTRACT
Hypoxia has been identified as a common contributor to tumor progression, including invasion and metastasis. However, the underlying mechanisms of enhanced invasion and metastasis under hypoxia remain unclear. A hypoxic microenvironment promotes invasion and metastasis of renal cell carcinoma (RCC) by upregulating expression of LOC100506178, which we named hypoxia-induced long non-coding RNA (lncRNA) associated with RCC (lncHILAR). Knockdown of lncHILAR inhibited cell invasion and migration, whereas overexpression of lncHILAR, conversely, facilitated cell invasion and migration of RCC cells. Notably, hypoxic RCC cells secreted exosomes packaged with lncHILAR, which were taken up by normoxic RCC cells and then drove normoxic cell invasion. Mechanistically, lncHILAR elevated RCC invasion and metastasis by acting as a competing endogenous RNA (ceRNA) for miR-613/206/1-1-3p, which led to the upregulation of Jagged-1 and the C-X-C motif chemokine receptor 4 (CXCR4). Activation of the Jagged-1/Notch/CXCR4 axis induced RCC metastasis. lncHILAR promotes RCC cell invasion and metastasis via ceRNA for the miR-613/206/1-1-3p/Jagged-1/Notch/CXCR4 axis. The novel lncHILAR may thus serve as a potential biomarker and therapeutic target in RCC.
Subject(s)
Carcinoma, Renal Cell/pathology , Kidney Neoplasms/pathology , MicroRNAs/genetics , RNA, Long Noncoding/genetics , Receptors, CXCR4/genetics , Receptors, Notch/genetics , Animals , Carcinoma, Renal Cell/genetics , Cell Line, Tumor , Cell Movement , Cell Proliferation , Gene Expression Regulation, Neoplastic , Humans , Kidney Neoplasms/genetics , Mice , Neoplasm Metastasis , Neoplasm Transplantation , Tumor HypoxiaABSTRACT
BACKGROUND: Correct perioperative antibiotic strategies are crucial to prevent postoperative infections during percutaneous nephrolithotomy (PCNL). We aimed to compare the realistic antibiotic strategies applied in China with current urological guidelines. METHODS: Between April and May 2020, urologists from China were invited to finish an online cross-sectional survey. The questionnaire was designed according to the current urological guidelines and literatures. RESULTS: 3393 completed responses were received. 61.1% (2073/3393) respondents had urological experience of more than 10 years. 72.4% urologists chose multiple-dose antibiotics for patients with both negative urine culture (UC-) and negative urine microscopy (UM-) preoperatively. Respondents in central China (OR = 1.518; 95% CI 1.102-2.092; P = 0.011), east China (OR = 1.528; 95% CI 1.179-1.979; P = 0.001) and northeast China (OR = 1.904; 95% CI 1.298-2.792; P = 0.001) were more likely to prescribe multiple-dose antibiotic for UC-UM- patients. Notably, the respondents who finished PCNL exceeded 100 cases per year were in favor of single-dose administration (OR = 0.674; 95% CI 0.519-0.875; P = 0.003). There are only 8.3% urologists chose single-dose antibiotic for UC-UM+ patients, whereas 65.5% administered antibiotics for 1-3 days. Meanwhile, for UC+ patients, 59.0% of the urologists applied antibiotics shorter than 1 week, and only 26.3% of the urologists carried out routine re-examination of UC. Moreover, postoperative antibiotics were frequently prescribed for 3-6 days (1815; 53.5%). Finally, although 88.2% urologists considered stone culture important for management of postoperative antibiotics as the guideline recommended, only 18.5% performed it routinely. CONCLUSIONS: The antibiotic strategies are different between current practice in China and the urological guidelines. The dissimilarities suggested that further studies should be conducted to investigate the reasons of the differences and standardize the application of antibiotics.
Subject(s)
Kidney Calculi , Nephrolithotomy, Percutaneous , Urology , Anti-Bacterial Agents/therapeutic use , Cross-Sectional Studies , Humans , Kidney Calculi/surgery , Microscopy , UrinalysisABSTRACT
Due to the complicated histopathological characteristics of renal neoplasms, traditional distinguishing of clear cell renal cell carcinoma (ccRCC) by naked eyes of experienced pathologist remains labor intensive and time consuming. Here, we extracted quantitative features of hematoxylin-eosin-stained images using CellProfiler and performed machine learning method to develop and verify a novel computational recognition of digital pathology for diagnosis and prognosis of ccRCC patients in the training, test and external validation cohort. The diagnostic model based on digital pathology could accurately distinguish ccRCC from normal renal tissues, with area under the curve (AUC) of 96.0%, 94.5% and 87.6% in the training, test and external validation cohorts, respectively. It could also accurately distinguish ccRCC from other pathological types of renal cancer, with AUC values of 97.0% and 81.4% in the Cancer Genome Atlas (TCGA) cohort and General cohort. We next developed and verified a computational recognition prognosis model with risk score. There was a significant difference in disease-free survival comparing patients with high vs low risk score in training cohort (hazard ratio = 2.72, P < .0001) and validation cohort (hazard ratio = 9.50, P = .0091). The integrated nomogram based on our computational recognition risk score and clinicopathologic factors demonstrated excellent survival prediction for ccRCC patients, with increased accuracy by 6.6% in patients from Shanghai General Hospital and by 2.5% in patients from TCGA cohort when compared to current tumor stages/grade systems. These results indicate the potential clinical use of our machine learning histopathological image signature in diagnosis and survival prediction of ccRCC.
Subject(s)
Carcinoma, Renal Cell/diagnosis , Image Interpretation, Computer-Assisted/methods , Kidney Neoplasms/diagnosis , Carcinoma, Renal Cell/pathology , China , Disease-Free Survival , Humans , Kidney Neoplasms/pathology , Machine Learning , Neoplasm Staging , Nomograms , PrognosisABSTRACT
Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TCGA). We constructed and cross-verified automatic diagnosis and prognosis models by performing a machine learning algorithm based on pathomics data. Our study indicated that high diagnostic efficiency of the machine learning-based diagnosis model was observed in patients with BCa, with area under the curve (AUC) values of 96.3%, 89.2%, and 94.1% in the training cohort, test cohort, and external validation cohort, respectively. Our diagnosis model also performed well in distinguishing patients with BCa from patients with glandular cystitis, with an AUC value of 93.4% in the General cohort. Significant differences were found in overall survival in TCGA cohort (hazard ratio (HR) = 2.09, 95% confidence interval (CI): 1.56-2.81, P < .0001) and the General cohort (HR = 5.32, 95% CI: 2.95-9.59, P < .0001) comparing patients with BCa of high risk vs low risk stratified by risk score, which was proved to be an independent prognostic factor for BCa. The integration nomogram based on our risk score and clinicopathologic characters displayed higher prediction accuracy than current tumor stage/grade systems, with AUC values of 77.7%, 83.8%, and 81.3% for 1-, 3-, and 5-y overall survival prediction of patients with BCa. However, prospective studies are still needed for further verifications.
Subject(s)
Machine Learning , Urinary Bladder Neoplasms/mortality , Urinary Bladder Neoplasms/pathology , Algorithms , Area Under Curve , Cystitis/diagnosis , Cystitis/pathology , Diagnosis, Differential , Humans , Kaplan-Meier Estimate , Neoplasm Grading , Neoplasm Staging , Nomograms , Proportional Hazards Models , Regression Analysis , Risk Factors , Urinary Bladder Neoplasms/diagnosisABSTRACT
BACKGROUND: The coronavirus disease 2019 (COVID-19) has induced a worldwide epidemiological event with a high infectivity and mortality. However, the predicting biomarkers and their potential mechanism in the progression of COVID-19 are not well known. OBJECTIVE: The aim of this study is to identify the candidate predictors of COVID-19 and investigate their underlying mechanism. METHODS: The retrospective study was conducted to identify the potential laboratory indicators with prognostic values of COVID-19 disease. Then, the prognostic nomogram was constructed to predict the overall survival of COVID-19 patients. Additionally, the scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of the most important prognostic indicators in lungs and peripherals, respectively. RESULTS: In total, 304 hospitalized adult COVID-19 patients in Wuhan Jinyintan Hospital were included in the retrospective study. CEA was the only laboratory indicator with significant difference in the univariate (P < 0.001) and multivariate analysis (P = 0.020). The scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of CEA in lungs and peripherals, respectively. The results revealed the potential roles of CEA were significantly distributed in type II pneumocytes of BALF and developing neutrophils of PBMCs, participating in the progression of COVID-19 by regulating the cell-cell communication. CONCLUSION: This study identifies the prognostic roles of CEA in COVID-19 patients and implies the potential roles of CEACAM8-CEACAM6 in the progression of COVID-19 by regulating the cell-cell communication of developing neutrophils and type II pneumocyte.
Subject(s)
COVID-19/metabolism , Carcinoembryonic Antigen/metabolism , Pneumonia, Viral/metabolism , Adult , Aged , Biomarkers/metabolism , Bronchoalveolar Lavage Fluid/chemistry , COVID-19/mortality , Cell Communication , China/epidemiology , Disease Progression , Hospitalization , Humans , Male , Middle Aged , Neutrophils/metabolism , Nomograms , Pneumonia, Viral/mortality , Pneumonia, Viral/virology , Predictive Value of Tests , Prognosis , Retrospective Studies , SARS-CoV-2 , Survival AnalysisABSTRACT
The rapid emergence of coronavirus disease 2019 (COVID-19) has necessitated the implementation of diverse pandemic control strategies throughout the world. To effectively control the spread of this disease, it is essential that it be diagnosed at an early stage so that patients can be reliably quarantined such that disease spread will be slowed. At present, the diagnosis of this infectious form of coronavirus pneumonia is largely dependent upon a combination of laboratory testing and imaging analyses of variable diagnostic efficacy. In the present report, we reviewed prior literature pertaining to the diagnosis of different forms of pneumonia caused by coronaviruses (severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, and SARS-CoV-2) and assessed two different potential diagnostic approaches. We ultimately found that computed tomography was associated with a higher rate of diagnostic accuracy than was a real-time quantitative polymerase chain reaction-based approach (P = .0041), and chest radiography (P = .0100). Even so, it is important that clinicians utilize a combination of laboratory and radiological testing where possible to ensure that this virus is reliably and quickly detected such that it may be treated and patients may be isolated in a timely fashion, thereby effectively curbing the further progression of this pandemic.
Subject(s)
COVID-19/diagnosis , COVID-19 Nucleic Acid Testing , COVID-19 Serological Testing , Data Accuracy , Humans , Thorax/diagnostic imaging , Tomography, X-Ray ComputedABSTRACT
Coronavirus disease 2019 (COVID-19) represents a significant global medical issue, with a growing number of cumulative confirmed cases. However, a large number of patients with COVID-19 have overcome the disease, meeting hospital discharge criteria, and are gradually returning to work and social life. Nonetheless, COVID-19 may cause further downstream issues in these patients, such as due to possible reactivation of the virus, long-term pulmonary defects, and posttraumatic stress disorder. In this study, we, therefore, queried relevant literature concerning severe acute respiratory syndrome, Middle East respiratory syndrome, and COVID-19 for reference to come to a consensus on follow-up strategies. We found that strategies, such as the implementation of polymerase chain reaction testing, imaging surveillance, and psychological assessments, starting at the time of discharge, were necessary for long-term follow-up. If close care is given to every aspect of coronavirus management, we expect that the pandemic outbreak will soon be overcome.
Subject(s)
COVID-19/epidemiology , Communicable Disease Control/methods , Patient Discharge/statistics & numerical data , COVID-19 Nucleic Acid Testing , Disease Management , Follow-Up Studies , HumansABSTRACT
BACKGROUND: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. METHODS: Data from reports released by the National Health Commission of the People's Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model. RESULTS: The optimistic scenario (non-Hubei model, daily increment rate of - 3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of - 2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of - 1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20 k in South Korea, 209 k in Italy, and 226 k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. CONCLUSION: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.
Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Models, Theoretical , Pneumonia, Viral/epidemiology , COVID-19 , China/epidemiology , Coronavirus Infections/virology , Forecasting/methods , Humans , Iran/epidemiology , Italy/epidemiology , Pandemics , Pneumonia, Viral/virology , Prognosis , Republic of Korea/epidemiology , SARS-CoV-2ABSTRACT
BACKGROUND: The impact of corticosteroid therapy on outcomes of patients with coronavirus disease 2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. METHODS: In this single-center retrospective observational study, patients with ARDS caused by COVID-19 between January 20, 2020, and February 24, 2020, were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. RESULTS: A total of 382 patients [60.7 ± 14.1 years old (mean ± SD), 61.3% males] were analyzed. The median of sequential organ failure assessment (SOFA) score was 2.0 (IQR 2.0-3.0). Of these cases, 94 (24.6%) patients had invasive mechanical ventilation. The number of patients received systemic corticosteroids was 226 (59.2%), and 156 (40.8%) received standard treatment. The maximum dose of corticosteroids was 80.0 (IQR 40.0-80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0-12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days after adjusting for age, sex, SOFA score at hospital admission, propensity score of corticosteroid treatment, comorbidities, antiviral treatment, and respiratory supports (HR 0.42; 95% CI 0.21, 0.85; p = 0.0160). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. CONCLUSION: In this clinical practice setting, low-dose corticosteroid treatment was associated with reduced risk of in-hospital death within 60 days in COVID-19 patients who developed ARDS.
Subject(s)
Adrenal Cortex Hormones/administration & dosage , Betacoronavirus , Coronavirus Infections/drug therapy , Coronavirus Infections/mortality , Pneumonia, Viral/drug therapy , Pneumonia, Viral/mortality , Propensity Score , Respiratory Distress Syndrome/drug therapy , Respiratory Distress Syndrome/mortality , Aged , COVID-19 , Cohort Studies , Dexamethasone/administration & dosage , Female , Hospitalization/trends , Humans , Male , Methylprednisolone/administration & dosage , Middle Aged , Pandemics , Retrospective Studies , SARS-CoV-2 , Survival Rate/trendsABSTRACT
Colorectal cancer (CRC) affects people globally, and lymph node metastasis (LNM) is an important indicator of poor clinical outcome in CRC. The current study aims to evaluate the role of microRNA-448 (miR-488) and claudin-2 (CLDN2) in epithelial-mesenchymal transition (EMT) and LNM of CRC through the MAPK signaling pathway. First, microarray analysis indicated that miR-488 was poorly expressed in CRC, whereas CLDN2 was highly expressed. Additionally, the bioinformatics website MicroRNA.org and the dual luciferase reporter gene assay found that CLDN2 was a target gene of miR-488. Next, the results for the correlations between expression of miR-488 and clinicopathological characteristics of CRC indicated that the expression of miR-488 was closely associated with differentiation degree, LNM, and Dukes stages in CRC patients. Moreover, overexpression of miR-488 inhibited the activation of the MAPK signal transduction pathway. Notably, loss- and gain-of-function experiments demonstrated that upregulation of miR-488 suppressed SW480 cell viability, invasion, and migration and promoted apoptosis in SW480 cells. Finally, overexpression of miR-488 inhibited LNM, microlymphatic vessel density, and tumor growth in nude mice. We conclude that overexpression of miR-488 could suppress the cell proliferation, EMT, and LNM of CRC cells via inhibition of the CLDN2-mediated MAPK signaling pathway, which could be a new molecular therapy target for CRC.
Subject(s)
Claudin-2/biosynthesis , Colorectal Neoplasms/metabolism , Disease Progression , MicroRNAs/biosynthesis , Mitogen-Activated Protein Kinases/metabolism , Adult , Aged , Animals , Claudin-2/antagonists & inhibitors , Colorectal Neoplasms/pathology , Colorectal Neoplasms/prevention & control , Drug Delivery Systems/methods , Female , HCT116 Cells , HT29 Cells , Humans , Male , Mice , Mice, Inbred BALB C , Mice, Nude , Middle Aged , Mitogen-Activated Protein Kinases/antagonists & inhibitors , Xenograft Model Antitumor Assays/methodsABSTRACT
BACKGROUND: The aberrant expression of long noncoding RNAs (lncRNAs) has recently emerged as key molecules in human cancers; however, whether lncRNAs are implicated in the progression of clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: Candidate lncRNAs were selected using microarray analysis and quantitative real-time PCR (qRT-PCR) was performed to detect lncRNAs expression in human ccRCC tissues. Overexpression and knocking down experiments in vivo and in vitro were performed to uncover the biological roles of lncRNA-URRCC on ccRCC cell proliferation and invasion. Microarray, chromatin immunoprecipitation, Luciferase reporter assay and western blot were constructed to investigate the molecular mechanisms underlying the functions of lncRNA-URRCC. RESULTS: The microarray analysis and qRT-PCR identified a new lncRNA, URRCC, whose expression is upregulated in RCC samples and associated with poor prognosis, leading to promote ccRCC cell proliferation and invasion. Mechanistically, URRCC enhances the expression of EGFL7 via mediating histone H3 acetylation of EGFL7 promoter, activation of P-AKT signaling, and suppressing P-AKT downstream gene, FOXO3. In return, FOXO3 could inhibit the transcription of URRCC via binding to the special region on the promoter of URRCC. CONCLUSIONS: Our data suggests that targeting this newly identified feed-back loop between LncRNA-URRCC and EGFL7/P-AKT/FOXO3 signaling may enhance the efficacy of existing therapy and potentially imparts a new avenue to develop more potent therapeutic approaches to suppress RCC progression.
Subject(s)
Carcinoma, Renal Cell/pathology , Kidney Neoplasms/pathology , RNA, Long Noncoding/genetics , Signal Transduction , Animals , Calcium-Binding Proteins , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/metabolism , Cell Line, Tumor , Cell Movement , Cell Proliferation , EGF Family of Proteins , Endothelial Growth Factors/metabolism , Forkhead Box Protein O3/metabolism , Gene Expression Profiling , Humans , Kidney Neoplasms/genetics , Kidney Neoplasms/metabolism , Mice , Neoplasm Metastasis , Neoplasm Staging , Neoplasm Transplantation , Oligonucleotide Array Sequence Analysis , Phosphorylation , Proto-Oncogene Proteins c-akt/metabolism , Up-RegulationABSTRACT
OBJECTIVE: The tumor susceptibility gene 101 (TSG101) is closely associated with various tumor types, but its role in the pathogenesis of renal cell carcinoma (RCC) is still unknown. This study used RNA interference to silence the expression of TSG101 in RCC cell lines and explore the role of TSG101 in RCC. METHODS: Immunohistochemistry and western blot were performed to detect the expression of TSG101 in 15 paired renal tumor samples. A small interfering RNA (siRNA) targeting TSG101 was transfected into A498 and 786-O cell lines. The Cell Counting Kit-8 (CCK-8) assay and colony formation assay were used to observe the changes in cell proliferation after transfection. Flow cytometry was used to detect the effect on the cell cycle. Western blot was conducted to study the changes of related functional proteins. RESULTS: The expression of TSG101 was higher in RCC tissues than in adjacent normal tissues. The CCK-8 assay showed that the proliferation and colony formation of the A498 and 786-O cell lines were attenuated after suppression of TSG101. Flow cytometry showed that silencing of TSG101 induced G0/G1 arrest. The western blot results revealed that the levels of cell cycle-related proteins (c-myc, cyclin E1 and cyclin-dependent kinase 2 (CDK2)) were markedly decreased in the siRNA groups. CONCLUSIONS: TSG101 promotes proliferation of RCC cells. This positive effect on tumor growth involves activation of c-myc and cyclin E1/CDK2 and their effect on cell cycle distribution.
Subject(s)
Carcinoma, Renal Cell/genetics , Cell Proliferation , DNA-Binding Proteins/genetics , Endosomal Sorting Complexes Required for Transport/genetics , G1 Phase Cell Cycle Checkpoints , Kidney Neoplasms/genetics , Transcription Factors/genetics , Carcinoma, Renal Cell/metabolism , Carcinoma, Renal Cell/physiopathology , Cell Line, Tumor , Gene Expression Regulation, Neoplastic , Humans , Kidney Neoplasms/metabolism , Kidney Neoplasms/physiopathologyABSTRACT
Background: Vitamin E has anti-cancer properties, which was demonstrated mainly due to its antioxidant effect. Several epidemiological studies have investigated the association between vitamin E consumption and the risk of bladder cancer. However, the results were inconsistent. The meta-analysis study aimed to evaluate the association of vitamin E consumption and the risk of bladder cancer. METHODS: We conducted a systematic literature search in the electronic databases, which included MEDLINE, EMBASE and the Cochrane Library till 1 January 2016. The pooled relative risk ratios (RRs) with 95% confidence intervals (CIs) were calculated depending on the heterogeneity among studies. Subgroup analysis and sensitivity analysis were also performed. Publication bias was assessed using Begg's test and Egger's test. RESULTS: A total of 11 prospective studies (3 randomized clinical trials and 8 cohort studies) including 575601 participants were identified to be eligible for our present meta-analysis. The pooled RRs with 95% CI for highest versus lowest vitamin E consumption was 0.89 (0.78-1.00). An inverse linear association between vitamin E consumption and bladder cancer risk was detected in the dose response analysis. The results were also stable in the subgroup analysis and sensitivity analysis. Meanwhile, no obvious publication bias was observed. CONCLUSIONS: Our study indicates that vitamin E consumption was inversely associated with the risk of bladder cancer.
Subject(s)
Urinary Bladder Neoplasms , Vitamin E , Humans , Odds Ratio , Prospective StudiesABSTRACT
Recently, increasing studies showed that long noncoding RNAs (lncRNAs) play critical roles in tumor progression. However, the function and underlying mechanism of HOMEOBOX A11 antisense RNA (HOXA11-AS) on renal cancer remain unclear. In the current study, our data showed that the expression of HOXA11-AS was significantly upregulated in clear cell renal cell carcinoma (ccRCC) tissues and cell lines. High HOXA11-AS expression was associated with the advanced clinical stage, tumor stage, and lymph node metastasis. Function assays showed that HOXA11-AS inhibition significantly suppressed renal cancer cells growth, invasion, and ETM phenotype. In addition, underlying mechanism revealed that HOXA11-AS could act as a competing endogenous RNA (ceRNA) that repressed miR-146b-5p expression, which regulated its downstream target MMP16 in renal cancer. Taken together, our findings suggested that HOXA11-AS could promote renal cancer cells growth and invasion by modulating miR-146b-5p-MMP16 axis. Thus, our findings suggested that HOXA11-AS could serve as potential therapeutic target for the treatment of renal cancer.
Subject(s)
Gene Expression Regulation, Neoplastic , Kidney Neoplasms/genetics , Kidney Neoplasms/pathology , Matrix Metalloproteinase 16/genetics , MicroRNAs/metabolism , RNA, Long Noncoding/metabolism , Aged , Animals , Base Sequence , Carcinoma, Renal Cell/enzymology , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/pathology , Cell Line, Tumor , Cell Proliferation/genetics , Disease Progression , Female , Gene Knockdown Techniques , Humans , Kidney Neoplasms/enzymology , Male , Matrix Metalloproteinase 16/metabolism , Mice, Nude , MicroRNAs/genetics , Middle Aged , Neoplasm Invasiveness , RNA, Long Noncoding/genetics , Up-Regulation/geneticsABSTRACT
This study aimed to investigate the effects of microRNA-184 (miR-184) on the proliferation and apoptosis of human colon cancer cells through the regulation of C-MYC and BCL-2. Human colon cancer tissues were selected as case group, and adjacent normal tissues were as control group. Human colon cancer SW480 and HCT116 cells were allocated into blank, miR-184 mimic negative control (mimic-NC), miR-184 inhibitor NC (inhibitor-NC), miR-184 mimic, and miR-184 inhibitor groups. Flow cytometry, Annexin V/PI and MTT assay were used to examine the cell cycle, apoptosis and viability. The expressions of C-MYC, BCL-2 and miR-184 were detected via immunohistochemistry, Western blotting and reverse transcription quantitative polymerase chain reaction (RT-qPCR). C-MYC and BCL-2 were direct targets to miR-184. The growth of colon cancer cells in the miR-184 mimic group was inhibited and exhibited an increase in apoptosis. Cell growth in the miR-184 mimic group was increased in addition to the inhibition of apoptosis. Compared with miR-184 mimic group, the expressions of C-MYC and BCL-2 in miR-184 inhibitor group were increased. The expressions of C-MYC and BCL-2 in colon cancer tissues exhibited high levels of expression, while miR-184 displayed relatively low levels in comparison to the adjacent normal tissues. An association was detected regarding the expressions of miR-184, C-MYC and BCL-2 with the differentiation, invasion depth and lymph node metastasis. MiR-184 expression was negatively related to C-MYC and BCL-2 expressions. Our study suggested that miR-184 could inhibit proliferation and promote apoptosis of colon cancer cells by down-regulating expressions of C-MYC and BCL-2.