1
|
Liang R, Zhao A, Peng L, Xu X, Zhong J, Wu F, Yi F, Zhang S, Wu S, Hou J. Enhanced Artificial Intelligence Strategies in Renal Oncology: Iterative Optimization and Comparative Analysis of GPT 3.5 Versus 4.0. Ann Surg Oncol 2024; 31:3887-3893. [PMID: 38472675 DOI: 10.1245/s10434-024-15107-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND The rise of artificial intelligence (AI) in medicine has revealed the potential of ChatGPT as a pivotal tool in medical diagnosis and treatment. This study assesses the efficacy of ChatGPT versions 3.5 and 4.0 in addressing renal cell carcinoma (RCC) clinical inquiries. Notably, fine-tuning and iterative optimization of the model corrected ChatGPT's limitations in this area. METHODS In our study, 80 RCC-related clinical questions from urology experts were posed three times to both ChatGPT 3.5 and ChatGPT 4.0, seeking binary (yes/no) responses. We then statistically analyzed the answers. Finally, we fine-tuned the GPT-3.5 Turbo model using these questions, and assessed its training outcomes. RESULTS We found that the average accuracy rates of answers provided by ChatGPT versions 3.5 and 4.0 were 67.08% and 77.50%, respectively. ChatGPT 4.0 outperformed ChatGPT 3.5, with a higher accuracy rate in responses (p < 0.05). By counting the number of correct responses to the 80 questions, we then found that although ChatGPT 4.0 performed better (p < 0.05), both versions were subject to instability in answering. Finally, by fine-tuning the GPT-3.5 Turbo model, we found that the correct rate of responses to these questions could be stabilized at 93.75%. Iterative optimization of the model can result in 100% response accuracy. CONCLUSION We compared ChatGPT versions 3.5 and 4.0 in addressing clinical RCC questions, identifying their limitations. By applying the GPT-3.5 Turbo fine-tuned model iterative training method, we enhanced AI strategies in renal oncology. This approach is set to enhance ChatGPT's database and clinical guidance capabilities, optimizing AI in this field.
Collapse
Affiliation(s)
- Rui Liang
- Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China
- Department of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, Guangdong, China
| | - Anguo Zhao
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China
- Department of Urology, Medical Center of Soochow University, Suzhou Dushu Lake Hospital, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, China
| | - Lei Peng
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China
- Department of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, Guangdong, China
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, Gansu, China
- North Sichuan Medical College (University), Nanchong, Sichuan, China
| | - Xiaojian Xu
- Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Jianye Zhong
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China
| | - Fan Wu
- Faculty of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, China
| | - Fulin Yi
- North Sichuan Medical College (University), Nanchong, Sichuan, China
| | - Shaohua Zhang
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China.
- Department of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, Guangdong, China.
| | - Song Wu
- Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China.
- Department of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, Guangdong, China.
- Department of Urology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
| | - Jianquan Hou
- Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
- Department of Urology, Medical Center of Soochow University, Suzhou Dushu Lake Hospital, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, China.
| |
Collapse
|
2
|
Zieren RC, Zondervan PJ, Pienta KJ, Bex A, de Reijke TM, Bins AD. Diagnostic liquid biopsy biomarkers in renal cell cancer. Nat Rev Urol 2024; 21:133-157. [PMID: 37758847 DOI: 10.1038/s41585-023-00818-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2023] [Indexed: 09/29/2023]
Abstract
The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to also improve characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.
Collapse
Affiliation(s)
- Richard C Zieren
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
- The Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
| | - Patricia J Zondervan
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Kenneth J Pienta
- The Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Axel Bex
- Specialist Centre for Kidney Cancer, Royal Free Hospital, London, United Kingdom
- Division of Surgery and Interventional Science, University College London, London, United Kingdom
- The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Theo M de Reijke
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Adriaan D Bins
- Department of Medical Oncology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
3
|
Wu Y, Qi T, Qin X, Zhao Z, Zheng J, Du Q, Yu N. A nomogram based on the preoperative neutrophil-to-lymphocyte ratio to distinguish sarcomatoid renal cell carcinoma from clear cell renal cell carcinoma. Front Oncol 2023; 13:1218280. [PMID: 37810969 PMCID: PMC10556675 DOI: 10.3389/fonc.2023.1218280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 09/04/2023] [Indexed: 10/10/2023] Open
Abstract
Objective Our study aimed to assess the predictive value of the preoperative neutrophil-to-lymphocyte ratio(NLR) in distinguishing sarcomatoid renal cell carcinoma (SRCC) from clear cell renal cell carcinoma(CCRCC) and to developing a nomogram based on the preoperative NLR and other factors to distinguish SRCC from CCRCC. Materials and methods The database involved 280 patients, including 46 SRCC and 234 CCRCC. logistic analysis was conducted to select the variables associated with identifying SRCC preoperatively, and subgroup analysis was used to further validate the ability of NLR with preoperative identification of SRCC.In addition, The data were randomly separated into a training cohort(n=195) and a validation cohort(n=85). And an NLR-based nomogram was plotted based on the logistic analysis results. The nomogram was evaluated according to its discrimination, consistency, and clinical benefits. Results Multivariate analysis indicated that NLR, flank pain, tumor size, and total cholesterol(TC) were independent risk factors for identifying SRCC. The results of subgroup analysis showed that higher NLR was associated with a higher probability of SRCC in most subgroups. The area under the curve(AUC) of the training and validation cohorts were 0.801 and 0.738, respectively. The results of the calibration curve show high consistency between predicted and actual results. Decision Curve Analysis(DCA) showed clinical intervention based on the model was beneficial over most of the threshold risk range. Conclusion NLR is a potential indicator for preoperative differentiation of SRCC and CCRCC, and the predictive model constructed based on NLR has a good predictive ability. The new model could provide suggestions for the early identification of SRCC.
Collapse
Affiliation(s)
- Yijian Wu
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Tienan Qi
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Xin Qin
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Zhongwei Zhao
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Jianguo Zheng
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qinglong Du
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Nengwang Yu
- Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China
| |
Collapse
|
4
|
Chen H, Zhang L, Zuo M, Lou X, Liu B, Fu T. Inhibition of apoptosis through AKT-mTOR pathway in ovarian cancer and renal cancer. Aging (Albany NY) 2023; 15:1210-1227. [PMID: 36849137 PMCID: PMC10008491 DOI: 10.18632/aging.204564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/11/2023] [Indexed: 03/01/2023]
Abstract
OBJECTIVE Ovarian cancer and renal cancer are malignant tumors; however, the relationship between TTK Protein Kinase (TTK), AKT-mTOR pathway and ovarian cancer, renal cancer remains unclear. METHODS Download GSE36668 and GSE69428 from Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed. Created protein-protein interaction (PPI) network. Used Gene Ontology analysis (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional enrichment analysis. Gene Set Enrichment Analysis (GSEA) analysis and survival analysis were performed. Created animal model for western blot analysis. Gene Expression Profiling Interactive Analysis (GEPIA) was performed to explore the role of TTK on the overall survival of renal cancer. RESULTS GO showed that DEGs were enriched in anion and small molecule binding, and DNA methylation. KEGG analysis presented that they mostly enriched in cholesterol metabolism, type 1 diabetes, sphingolipid metabolism, ABC transporters, etc., TTK, mTOR, p-mTOR, AKT, p-AKT, 4EBP1, p-4EBP1 and Bcl-2 are highly expressed in ovarian cancer, Bax, Caspase3 are lowly expressed in ovarian cancer, cell apoptosis is inhibited, leading to deterioration of ovarian cancer. Furthermore, the TTK was not only the hub biomarker of ovarian cancer, but also one significant hub gene of renal cancer, and its expression was up-regulated in the renal cancer. Compared with the renal cancer patients with low expression of TTK, the patients with high expression of TTK have the poor overall survival (P = 0.0021). CONCLUSION TTK inhibits apoptosis through AKT-mTOR pathway, worsening ovarian cancer. And TTK was also one significant hub biomarker of renal cancer.
Collapse
Affiliation(s)
- Hongrun Chen
- Department of Urology, China Aerospace Science and Industry Corporation 731 Hospital, Beijing 100074, China
| | - Lianfeng Zhang
- Department of Urology, China Aerospace Science and Industry Corporation 731 Hospital, Beijing 100074, China
| | - Meini Zuo
- Department of Urology, China Aerospace Science and Industry Corporation 731 Hospital, Beijing 100074, China
| | - Xiaowen Lou
- Department of Social Work, The First People's Hospital of Fuyang District of Hangzhou, Hangzhou 311400, Zhejiang, China
| | - Bin Liu
- Department of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, Hebei, China
| | - Taozhu Fu
- Department of Urology, China Aerospace Science and Industry Corporation 731 Hospital, Beijing 100074, China
| |
Collapse
|
5
|
Li Q, Zhang Y, Liu M, Li H, Guan W, Meng X, Hu Z, Wang Z, Wang S, Li Z, Liu J, Liu Z. Identification of predictive factors for outcomes after robot-assisted partial nephrectomy based on three-dimensional reconstruction of preoperative enhanced computerized tomography. Front Oncol 2023; 13:927582. [PMID: 36925922 PMCID: PMC10011456 DOI: 10.3389/fonc.2023.927582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 02/07/2023] [Indexed: 03/08/2023] Open
Abstract
Background Information from the RENAL score is limited. This study aimed to identify new parameters based on three-dimensional (3D) reconstruction of preoperative enhanced computerized tomography (CT) for predicting outcomes after robot-assisted partial nephrectomy (RPN). Materials and methods The records of kidney cancer patients who underwent RPN at Tongji Hospital from March 2015 to July 2019 were reviewed. Demographic data, laboratory examinations, postoperative hospitalization time, and enhanced CT were retrospectively collected. Some tumor parameters were obtained from 3D reconstruction of CT data. The association between these predictive factors and outcomes after RPN was analyzed. Results A larger tumor bed area (TBA) was associated with a longer warm ischemia time (WIT) (P-value <0.001) and tumor resection time (P-value <0.001). Moreover, TBA was significantly associated with the elevation of postoperative creatinine (P-value = 0.005). TBA (P = 0.008), distance from the tumor to the first bifurcation of the renal artery (DTA) (P <0.034), and RENAL score (P = 0.005) were significantly associated with WIT in univariate logistic regression. In multivariate logistic regression, TBA (P = 0.026) and DTA (P = 0.048) were independent risk factors for prolonged WIT (over 25 min). The predictive effect of the combination of TBA, DTA, and RENAL score was higher than the predictive effect of RENAL score alone for WIT (area under curve: 0.786 versus 0.72). Conclusion TBA and DTA are independently associated with the WIT of RPN, which provides additional assessment value for the complexity of kidney cancer in RPN over the RENAL score.
Collapse
Affiliation(s)
- Qinyu Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yucong Zhang
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Man Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Guan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiquan Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhihua Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaogang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jihong Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
6
|
Couto-Cunha A, Jerónimo C, Henrique R. Circulating Tumor Cells as Biomarkers for Renal Cell Carcinoma: Ready for Prime Time? Cancers (Basel) 2022; 15:cancers15010287. [PMID: 36612281 PMCID: PMC9818240 DOI: 10.3390/cancers15010287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 12/19/2022] [Accepted: 12/28/2022] [Indexed: 01/03/2023] Open
Abstract
Renal cell carcinoma (RCC) is among the 15 most common cancers worldwide, with rising incidence. In most cases, this is a silent disease until it reaches advance stages, demanding new effective biomarkers in all domains, from detection to post-therapy monitoring. Circulating tumor cells (CTC) have the potential to provide minimally invasive information to guide assessment of the disease's aggressiveness and therapeutic strategy, representing a special pool of neoplastic cells which bear metastatic potential. In some tumor models, CTCs' enumeration has been associated with prognosis, but there is a largely unexplored potential for clinical applicability encompassing screening, diagnosis, early detection of metastases, prognosis, response to therapy and monitoring. Nonetheless, lack of standardization and high cost hinder the translation into clinical practice. Thus, new methods for collection and analysis (genomic, proteomic, transcriptomic, epigenomic and metabolomic) are needed to ascertain the role of CTC as a RCC biomarker. Herein, we provide a critical overview of the most recently published data on the role and clinical potential of CTCs in RCC, addressing their biology and the molecular characterization of this remarkable set of tumor cells. Furthermore, we highlight the existing and emerging techniques for CTC enrichment and detection, exploring clinical applications in RCC. Notwithstanding the notable progress in recent years, the use of CTCs in a routine clinical scenario of RCC patients requires further research and technological development, enabling multimodal analysis to take advantage of the wealth of information they provide.
Collapse
Affiliation(s)
- Anabela Couto-Cunha
- Integrated Master in Medicine, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
| | - Carmen Jerónimo
- Department of Pathology and Molecular Immunology, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
- Department of Pathology & Cancer Biology & Epigenetics Group—Research Center of IPO Porto (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Centre Raquel Seruca (P.CCC Raquel Seruca), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
| | - Rui Henrique
- Department of Pathology and Molecular Immunology, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
- Department of Pathology & Cancer Biology & Epigenetics Group—Research Center of IPO Porto (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Centre Raquel Seruca (P.CCC Raquel Seruca), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Correspondence: or
| |
Collapse
|
7
|
Beyer K, Widdershoven C, Wintner LM, Dabestani S, Marconi L, Moss C, Kinsella N, Yuan Y, Giles RH, Barod R, Van Hemelrijck M, Bex A, Zondervan P, MacLennan S. A Systematic Review of Heterogeneity in Outcome Definition and Reporting in Localised Renal Cancer. EUR UROL SUPPL 2022; 48:1-11. [PMID: 36578462 PMCID: PMC9791121 DOI: 10.1016/j.euros.2022.11.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2022] [Indexed: 12/23/2022] Open
Abstract
Context Outcomes in renal cell carcinoma (RCC) are reported inconsistently, with variability in definitions and measurement. Hence, it is difficult to compare intervention effectiveness and synthesise outcomes for systematic reviews and to create clinical practice guidelines. This uncertainty in the evidence makes it difficult to guide patient-clinician decision-making. One solution is a core outcome set (COS): an agreed minimum set of outcomes. Objective To describe outcome reporting, definitions, and measurement heterogeneity as the first stage in co-creating a COS for localised renal cancer. Evidence acquisition We systematically reviewed outcome reporting heterogeneity in effectiveness trials and observational studies in localised RCC. In total, 2822 studies (randomised controlled trials, cohort studies, case-control studies, systematic reviews) up to June 2020 meeting our inclusion criteria were identified. Abstracts and full texts were screened independently by two reviewers; in cases of disagreement, a third reviewer arbitrated. Data extractions were double-checked. Evidence synthesis We included 149 studies and found that there was inconsistency in which outcomes were reported across studies and variability in the definitions used for outcomes that were conceptually the same. We structured our analysis using the outcome classification taxonomy proposed by Dodd et al. Outcomes linked to adverse events (eg, bleeding, outcomes linked to surgery) and renal injury outcomes (reduced renal function) were reported most commonly. Outcomes related to deaths from any cause and from cancer were reported in 44% and 25% of studies, respectively, although the time point for measurement and the analysis methods were inconsistent. Outcomes linked to life impact (eg, global quality of life) were reported least often. Clinician-reported outcomes are more frequently reported than patient-reported outcomes in the renal cancer literature. Conclusions This systematic review underscores the heterogeneity of outcome reporting, definitions, and measurement in research on localised renal cancer. It catalogues the variety of outcomes and serves as a first step towards the development of a COS for localised renal cancer. Patient summary We reviewed studies on localised kidney cancer and found that multiple terms and definitions have been used to describe outcomes. These are not defined consistently, and often not defined at all. Our review is the first phase in developing a core outcome set to allow better comparisons of studies to improve medical care.
Collapse
Affiliation(s)
- Katharina Beyer
- Translational Oncology and Urology Research, King’s College London, London, UK
- Corresponding author. Translational Oncology and Urology Research, School of Cancer and Pharmaceutical Studies, Guy’s Hospital, Great Maze Pond, London SE1 9RT, UK. Tel. +44 207 188 5594.
| | | | - Lisa M. Wintner
- University Hospital of Psychiatry II, Medical University of Innsbruck, Innsbruck, Austria
| | - Saeed Dabestani
- Department of Translational Medicine, Division of Urological Cancers, Lund University, Kristianstad Central Hospital, Lund, Sweden
| | - Lorenzo Marconi
- Department of Urology, Coimbra University Hospital, Coimbra, Portugal
| | - Charlotte Moss
- Translational Oncology and Urology Research, King’s College London, London, UK
| | - Netty Kinsella
- Translational Oncology and Urology Research, King’s College London, London, UK
- Department of Urology, Royal Marsden Hospital, London, UK
| | - Yuhong Yuan
- Department of Medicine, McMaster University, Hamilton, Canada
| | - Rachel H. Giles
- International Kidney Cancer Coalition, Duivendrecht, The Netherlands
| | - Ravi Barod
- Specialist Centre for Kidney Cancer, Royal Free Hospital, London, UK
| | | | - Axel Bex
- University Hospital of Psychiatry II, Medical University of Innsbruck, Innsbruck, Austria
- Specialist Centre for Kidney Cancer, Royal Free Hospital, London, UK
| | - Patricia Zondervan
- University Hospital of Psychiatry II, Medical University of Innsbruck, Innsbruck, Austria
| | - Steven MacLennan
- Academic Urology Unit, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| |
Collapse
|
8
|
Hong P, Huang W, Du H, Hu D, Cao Q, Wang Y, Zhang H, Tong S, Li Z, Tong M. Prognostic value and immunological characteristics of a novel cuproptosis-related long noncoding RNAs risk signature in kidney renal clear cell carcinoma. Front Genet 2022; 13:1009555. [PMID: 36406128 PMCID: PMC9669974 DOI: 10.3389/fgene.2022.1009555] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 10/21/2022] [Indexed: 09/29/2023] Open
Abstract
Background: Cuproptosis has been found as a novel cell death mode significantly associated with mitochondrial metabolism, which may be significantly associated with the occurrence and growth of tumors. LncRNAs take on critical significance in regulating the development of kidney renal clear cell carcinoma (KIRC), whereas the correlation between cuproptosis-related LncRNAs (CRLs) and KIRC is not clear at present. Therefore, this study built a prognosis signature based on CRLs, which can achieve accurate prediction of the outcome of KIRC patients. Methods: The TCGA database provided the expression profile information and relevant clinical information of KIRC patients. Univariate Cox, Lasso, and multivariate Cox were employed for building a risk signature based on CRLs. Kaplan-Meier (K-M) survival analysis and time-dependent receiver operating characteristic (ROC) curve were employed for the verification and evaluation of the reliability and accuracy of risk signature. Then, qRT-PCR analysis of risk LncRNAs was conducted. Finally, the possible effect of the developed risk signature on the microenvironment for tumor immunization was speculated in accordance with ssGSEA and ESTIMATE algorithms. Results: A prognosis signature composed of APCDD1L-DT, MINCR, AL161782.1, and AC026401.3 was built based on CRLs. As revealed by the results of the K-M survival study, the OS rate and progression-free survival rate of highrisk KIRC patients were lower than those of lowrisk KIRC patients, and the areas under ROC curves of 1, 3, and 5 years were 0.828, 0.780, and 0.794, separately. The results of the immune analysis showed that there were significant differences in the status of immunization and the microenvironment of tumor between groups at low-risk and at high-risk. The qRT-PCR results showed that the relative expression level of MINCR and APCDD1L-DT were higher in 786-O and 769-P tumor cells than in HK-2 cells, which were normal renal tubular epithelial cells. Conclusion: The developed risk signature takes on critical significance in the prediction of the prognosis of patients with KIRC, and it can bring a novel direction for immunotherapy and clinical drug treatment of KIRC. In addition, 4 identified risk LncRNAs (especially APCDD1L-DT and MINCR) can be novel targets for immunotherapy of KIRC patients.
Collapse
Affiliation(s)
- Peng Hong
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Weichao Huang
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Huifang Du
- Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ding Hu
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Qingfei Cao
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Yinjie Wang
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Huashan Zhang
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Siqiao Tong
- The First Clinical College of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Zizhi Li
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| | - Ming Tong
- Department of Urology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China
| |
Collapse
|
9
|
Ma M, Zhang Z, Liu Y, Li Z, Fu S, Chen Q, Wang S. Preliminary study on the role of the C5orf46 gene in renal cancer. Transl Oncol 2022; 21:101442. [PMID: 35504177 PMCID: PMC9079122 DOI: 10.1016/j.tranon.2022.101442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/15/2022] [Accepted: 04/24/2022] [Indexed: 11/25/2022] Open
Abstract
The C5orf46 gene was first studied in tumors. C5orf46 gene is involved in tumor immunity. C5orf46 gene as a possible target for immunotherapy in renal cancer
Background C5orf46 has been found to have antibacterial and anti-inflammatory effects via sequencing and microarray technologies, but its effects on cancer are unclear. Methods C5orf46 expression in renal cancer patients and cell lines was measured by quantitative polymerase chain reaction (qPCR). RNA sequencing data and clinicopathological information from renal cancer patients extracted from The Tumor Genome Atlas (TCGA) were analyzed to evaluate the prognostic value of C5orf46. The role of C5orf46 in vitro was verified by migration, proliferation and apoptosis experiments in renal cancer cell lines. Furthermore, the transcriptome of renal cancer cell lines with C5orf46 knocked down was sequenced to analyze potential signaling network pathways. Finally, the possible mechanisms of C5orf46 involvement in renal cancer development were analyzed by evaluating the immune microenvironment, mutation status and methylation levels. Results C5orf46 was highly expressed in renal cancer and was an independent prognostic factor. In vitro cell experiments showed that inhibition of C5orf46 expression could reduce renal cancer cell proliferation and migration and increase apoptosis. Transcriptomic sequencing after knockdown of C5orf46 in renal cancer cells revealed that it is involved in the malignant phenotype and immune microenvironment regulation of renal cancer. Finally, public databases suggest that C5orf46-related immune cell infiltration, mutational potential, and low methylation levels may contribute to poor prognosis in renal cancer. Conclusion These findings suggest that C5orf46 is associated with renal cancer progression and could be a potential target for improving renal cancer prognosis.
Collapse
|
10
|
Guevara M, Molinuevo A, Salmerón D, Marcos-Gragera R, Carulla M, Chirlaque MD, Rodríguez Camblor M, Alemán A, Rojas D, Vizcaíno Batllés A, Chico M, Jiménez Chillarón R, López de Munain A, de Castro V, Sánchez MJ, Ramalle-Gómara E, Franch P, Galceran J, Ardanaz E. Cancer Survival in Adults in Spain: A Population-Based Study of the Spanish Network of Cancer Registries (REDECAN). Cancers (Basel) 2022; 14:cancers14102441. [PMID: 35626046 PMCID: PMC9139549 DOI: 10.3390/cancers14102441] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/11/2022] [Accepted: 05/13/2022] [Indexed: 02/06/2023] Open
Abstract
Simple Summary We studied cancer survival and its trends in adult patients in Spain. We included more than 600,000 patients with primary cancer diagnosed during 2002–2013 and followed them up to 2015. The study provides cancer survival estimates up to five years after diagnosis by sex and age for 29 cancer groups. We found survival improvements for most cancer groups from 2002–2007 to 2008–2013, although with differences by age, being greater for patients younger than 75 years than for older patients. The persistent poor prognosis for some cancers emphasizes the need to reinforce actions along the cancer continuum, from primary prevention to early diagnosis, optimal treatment, and supportive care. Further examination of possible sociodemographic inequalities is warranted. Abstract The assessment of cancer survival at the population level is essential for monitoring progress in cancer control. We aimed to assess cancer survival and its trends in adults in Spain. Individual records of 601,250 adults with primary cancer diagnosed during 2002–2013 and followed up to 2015 were included from 13 population-based cancer registries. We estimated net survival up to five years after diagnosis and analyzed absolute changes between 2002–2007 and 2008–2013. Estimates were age-standardized. Analyses were performed for 29 cancer groups, by age and sex. Overall, age-standardized five-year net survival was higher in women (61.7%, 95% CI 61.4–62.1%) than in men (55.3%, 95% CI 55.0–55.6%), and ranged by cancer from 7.2% (pancreas) to 89.6% (prostate) in men, and from 10.0% (pancreas) to 93.1% (thyroid) in women in the last period. Survival declined with age, showing different patterns by cancer. Between both periods, age-standardized five-year net survival increased overall by 3.3% (95% CI 3.0–3.7%) in men and 2.5% (95% CI 2.0–3.0%) in women, and for most cancer groups. Improvements were greater in patients younger than 75 years than in older patients. Chronic myeloid leukemia and myeloma showed the largest increases. Among the most common malignancies, the greatest absolute increases in survival were observed for colon (5.0%, 95% CI 4.0–6.0%) and rectal cancers (4.5%, 95% CI 3.2–5.9%). Survival improved even for some cancers with poor prognosis (pancreas, esophagus, lung, liver, and brain cancer). Further investigation of possible sociodemographic inequalities is warranted. This study contributes to the evaluation of cancer control and health services’ effectiveness.
Collapse
Affiliation(s)
- Marcela Guevara
- Navarra Public Health Institute, 31003 Pamplona, Spain;
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
- Correspondence:
| | - Amaia Molinuevo
- Biodonostia Health Research Institute, 20014 San Sebastian, Spain;
| | - Diego Salmerón
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Departamento de Ciencias Sociosanitarias, IMIB-Arrixaca, Universidad de Murcia, 30100 Murcia, Spain
| | - Rafael Marcos-Gragera
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Epidemiology Unit and Girona Cancer Registry, Oncology Coordination Plan, Catalan Institute of Oncology, Department of Health, Government of Catalonia, 17007 Girona, Spain
- Descriptive Epidemiology, Genetics and Cancer Prevention Research Group, Girona Biomedical Research Institute (IdiBGi), 17190 Girona, Spain
- Faculty of Medicine, University of Girona, 17071 Girona, Spain
- Josep Carreras Leukemia Research Institute, 17003 Girona, Spain
| | - Marià Carulla
- Tarragona Cancer Registry, Cancer Epidemiology and Prevention Service, Hospital Universitari Sant Joan de Reus, CatSalut, 43204 Reus, Spain; (M.C.); (J.G.)
- Pere Virgili Health Research Institute (IISPV), 43204 Reus, Spain
- Faculty of Medicine and Health Sciences, Rovira i Virgili University, 43204 Reus, Spain
| | - María-Dolores Chirlaque
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Departamento de Ciencias Sociosanitarias, IMIB-Arrixaca, Universidad de Murcia, 30100 Murcia, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, 30008 Murcia, Spain
| | | | - Araceli Alemán
- Canary Islands Cancer Registry, Public Health Directorate, Canary Health Service, 35003 Las Palmas de Gran Canaria, Spain; (A.A.); (D.R.)
| | - Dolores Rojas
- Canary Islands Cancer Registry, Public Health Directorate, Canary Health Service, 35003 Las Palmas de Gran Canaria, Spain; (A.A.); (D.R.)
| | - Ana Vizcaíno Batllés
- Castellón Cancer Registry, Public Health Directorate, General Health Department, Generalitat Valenciana, 46020 Valencia, Spain;
| | - Matilde Chico
- Ciudad Real Cancer Registry, Health and Social Welfare Authority, Castile-La Mancha, 13071 Ciudad Real, Spain;
| | - Rosario Jiménez Chillarón
- Cuenca Cancer Registry, Health and Social Welfare Authority, Castile-La Mancha, 16071 Cuenca, Spain;
| | - Arantza López de Munain
- Basque Country Cancer Registry, Health Department, 01010 Vitoria, Spain; (A.L.d.M.); (V.d.C.)
| | - Visitación de Castro
- Basque Country Cancer Registry, Health Department, 01010 Vitoria, Spain; (A.L.d.M.); (V.d.C.)
| | - Maria-José Sánchez
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
- Department of Preventive Medicine and Public Health, University of Granada, 18071 Granada, Spain
| | - Enrique Ramalle-Gómara
- Department of Epidemiology and Prevention, La Rioja Regional Health Authority, 26071 Logroño, Spain;
| | - Paula Franch
- Balearic Islands Health Research Institute (IdISBa), Illes Balears, 07120 Palma, Spain;
- Mallorca Cancer Registry, Balearic Islands Public Health Department, 07010 Palma, Spain
| | - Jaume Galceran
- Tarragona Cancer Registry, Cancer Epidemiology and Prevention Service, Hospital Universitari Sant Joan de Reus, CatSalut, 43204 Reus, Spain; (M.C.); (J.G.)
- Pere Virgili Health Research Institute (IISPV), 43204 Reus, Spain
- Faculty of Medicine and Health Sciences, Rovira i Virgili University, 43204 Reus, Spain
| | - Eva Ardanaz
- Navarra Public Health Institute, 31003 Pamplona, Spain;
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain; (D.S.); (R.M.-G.); (M.-D.C.); (M.-J.S.)
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
| |
Collapse
|