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Wang S, Qi X, Liu D, Xie D, Jiang B, Wang J, Wang X, Wu G. The implications for urological malignancies of non-coding RNAs in the the tumor microenvironment. Comput Struct Biotechnol J 2024; 23:491-505. [PMID: 38249783 PMCID: PMC10796827 DOI: 10.1016/j.csbj.2023.12.016] [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: 10/03/2023] [Revised: 12/08/2023] [Accepted: 12/16/2023] [Indexed: 01/23/2024] Open
Abstract
Urological malignancies are a major global health issue because of their complexity and the wide range of ways they affect patients. There's a growing need for in-depth research into these cancers, especially at the molecular level. Recent studies have highlighted the importance of non-coding RNAs (ncRNAs) – these don't code for proteins but are crucial in controlling genes – and the tumor microenvironment (TME), which is no longer seen as just a background factor but as an active player in cancer progression. Understanding how ncRNAs and the TME interact is key for finding new ways to diagnose and predict outcomes in urological cancers, and for developing new treatments. This article reviews the basic features of ncRNAs and goes into detail about their various roles in the TME, focusing specifically on how different ncRNAs function and act in urological malignancies.
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Affiliation(s)
- Shijin Wang
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Xiaochen Qi
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Dequan Liu
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Deqian Xie
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Bowen Jiang
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Jin Wang
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Xiaoxi Wang
- Department of Clinical Laboratory Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
| | - Guangzhen Wu
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning, China
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Yu Y, Li Y, Zhou L, Cheng X, Gong Z. Hepatic stellate cells promote hepatocellular carcinoma development by regulating histone lactylation: Novel insights from single-cell RNA sequencing and spatial transcriptomics analyses. Cancer Lett 2024; 604:217243. [PMID: 39260669 DOI: 10.1016/j.canlet.2024.217243] [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: 04/25/2024] [Revised: 08/23/2024] [Accepted: 09/06/2024] [Indexed: 09/13/2024]
Abstract
This study evaluated the cellular heterogeneity and molecular mechanisms of hepatocellular carcinoma (HCC). Single cell RNA sequencing (scRNA-seq), transcriptomic data, histone lactylation-related genes were collected from public databases. Cell-cell interaction, trajectory, pathway, and spatial transcriptome analyses were executed. Differential expression and survival analyses were conducted. Western blot, Real-time reverse transcription PCR (qRT-PCR), and Cell Counting Kit 8 (CCK8) assay were used to detect the expression of αSMA, AKR1B10 and its target genes, and verify the roles of AKR1B10 in HCC cells. Hepatic stellate cell (HSC) subgroups strongly interacted with tumor cell subgroups, and their spatial distribution was heterogeneous. Two candidate prognostic genes (AKR1B10 and RMRP) were obtained. LONP1, NPIPB3, and ZSWIM6 were determined as AKR1B10 targets. Besides, the expression levels of AKR1B10 and αSMA were significantly increased in LX-2 + HepG2 and LX-2 + HuH7 groups compared to those in LX-2 group, respectively. sh-AKR1B10 significantly inhibited the HCC cell proliferation and change the expression of AKR1B10 target genes, Bcl-2, Bax, Pan Kla, and H3K18la at protein levels. Our findings unveil the pivotal role of HSCs in HCC pathogenesis through regulating histone lactylation.
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Affiliation(s)
- Yifan Yu
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China.
| | - Yongnan Li
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China.
| | - Long Zhou
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China.
| | - Xiaoli Cheng
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China.
| | - Zheng Gong
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China.
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Liu X, Xiao W, Qiao J, Luo Q, Gao X, He F, Qin X. Prediction of Lymph Node Metastasis in Endometrial Cancer Based on Color Doppler Ultrasound Radiomics. Acad Radiol 2024:S1076-6332(24)00561-0. [PMID: 39232912 DOI: 10.1016/j.acra.2024.07.056] [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: 07/17/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/06/2024]
Abstract
RATIONALE AND OBJECTIVES To construct a model using radiomics features based on ultrasound images and evaluate the feasibility of noninvasive assessment of lymph node status in endometrial cancer (EC) patients. METHODS In this multicenter retrospective study, a total of 186 EC patients who underwent hysterectomy and lymph node dissection were included, Pathology confirmed the presence or absence of lymph node metastasis (LNM). The study encompassed patients from seven centers, spanning from September 2018 to November 2023, with 93 patients in each group (with or without LNM). Extracted ultrasound radiomics features from transvaginal ultrasound images, used five machine learning (ML) algorithms to establish US radiomics models, screened clinical features through univariate and multivariate logistic regression to establish a clinical model, and combined clinical and radiomics features to establish a nomogram model. The diagnostic ability of the three models for LNM with EC was compared, and the diagnostic performance and accuracy of the three models were evaluated using receiver operating characteristic curve analysis. RESULTS Among the five ML models, the XGBoost model performed the best, with AUC values of 0.900 (95% CI, 0.847-0.950) and 0.865 (95% CI, 0.763-0.950) for the training and testing sets, respectively. In the final model, the nomogram based on clinical features and the ultrasound radiomics showed good resolution, with AUC values of 0.919 (95% CI, 0.874-0.964) and 0.884 (0.801-0.967) in the training and testing sets, respectively. The decision curve analysis verified the clinical practicality of the nomogram. CONCLUSION The ML model based on ultrasound radiomics has potential value in the noninvasive differential diagnosis of LNM in patients with EC. The nomogram constructed by combining ultrasound radiomics and clinical features can provide clinical doctors with more comprehensive and personalized image information, which is highly important for selecting treatment strategies.
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Affiliation(s)
- Xiaoling Liu
- Department of Ultrasound, Beijing Anzhen Nanchong Hospital, Capital Medical University (Nanchong Central Hospital), Nanchong, Sichuan 637000, China
| | - Weihan Xiao
- North Sichuan Medical College, Nanchong 637000 China
| | - Jing Qiao
- Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, China
| | - Qi Luo
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Xiang Gao
- Department of Ultrasound, People's Hospital of Rizhao, Rizhao, Shandong 276827, China
| | - Fanding He
- Department of Medical Ultrasound, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Xiachuan Qin
- Department of Ultrasound, Chengdu Second People's Hospital, Chengdu 610000, China.
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Wu C, Zhang G, Wang L, Hu J, Ju Z, Tao H, Li Q, Li J, Zhang W, Sheng J, Hou X, Hu Y. Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma. Oncogene 2024; 43:2751-2767. [PMID: 39122893 DOI: 10.1038/s41388-024-03123-z] [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] [Received: 05/15/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 08/12/2024]
Abstract
Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.
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Affiliation(s)
- Chao Wu
- Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China
| | - Guoqing Zhang
- Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China
| | - Lin Wang
- College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Jinlong Hu
- Department of Oncology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhongjian Ju
- Department of Radiation Oncology, Chinese PLA General Hospital, The First Medical Center, Beijing, China
| | - Haitao Tao
- Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China
| | - Qing Li
- The Shapingba Affiliated Hospital, Chongqing University, Chongqing, China
| | - Jian Li
- Chengdu Medical College, Chengdu, China
| | - Wei Zhang
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
| | - Jianpeng Sheng
- College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
- Chinese Institutes for Medical Research, Beijing, China.
| | - Xiaobin Hou
- Department of Thoracic Surgery, Chinese PLA General Hospital, The First Medical Center, Beijing, China.
| | - Yi Hu
- Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing, China.
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Ma T, Wang M, Wang S, Hu H, Zhang X, Wang H, Wang G, Jin Y. BMSC derived EVs inhibit colorectal Cancer progression by transporting MAGI2-AS3 or something similar. Cell Signal 2024; 121:111235. [PMID: 38806109 DOI: 10.1016/j.cellsig.2024.111235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 05/16/2024] [Accepted: 05/24/2024] [Indexed: 05/30/2024]
Abstract
In this study, we investigated the molecular mechanisms underlying the impact of extracellular vesicles (EVs) derived from bone marrow stromal cells (BMSCs) on colorectal cancer (CRC) development. The focus was on the role of MAGI2-AS3, delivered by BMSC-EVs, in regulating USP6NL DNA methylation-mediated MYC protein translation modification to promote CDK2 downregulation. Utilizing bioinformatics analysis, we identified significant enrichment of MAGI2-AS3 related to copper-induced cell death in CRC. In vitro experiments demonstrated the downregulation of MAGI2-AS3 in CRC cells, and BMSC-EVs were found to deliver MAGI2-AS3 to inhibit CRC cell proliferation, migration, and invasion. Further exploration revealed that MAGI2-AS3 suppressed MYC protein translation modification by regulating USP6NL DNA methylation, leading to CDK2 downregulation and prevention of colorectal cancer. Overexpression of MYC reversed the functional effects of BMSC-EVs-MAGI2-AS3. In vivo experiments validated the inhibitory impact of BMSC-EVs-MAGI2-AS3 on CRC tumorigenicity by promoting CDK2 downregulation through USP6NL DNA methylation-mediated MYC protein translation modification. Overall, BMSC-EVs-MAGI2-AS3 may serve as a potential intervention to prevent CRC occurrence by modulating key molecular pathways.
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Affiliation(s)
- Tianyi Ma
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China
| | - Meng Wang
- Department of Colorectal Surgery, Zhejiang Cancer Hospital (Affiliated Cancer Hospital of the Chinese Academy of Sciences), Hangzhou 310000, China
| | - Song Wang
- Department of Colorectal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China
| | - Hanqing Hu
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China
| | - Xin Zhang
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China
| | - Hufei Wang
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China
| | - Guiyu Wang
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China.
| | - Yinghu Jin
- Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150000, China.
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Corres-Mendizabal J, Zacchi F, Martín-Martín N, Mateo J, Carracedo A. Metastatic hormone-naïve prostate cancer: a distinct biological entity. Trends Cancer 2024; 10:825-841. [PMID: 39048488 PMCID: PMC11397905 DOI: 10.1016/j.trecan.2024.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 06/11/2024] [Accepted: 06/20/2024] [Indexed: 07/27/2024]
Abstract
Metastatic hormone-naïve prostate cancer (mHNPC) is often the initial form of presentation for metastatic prostate cancer and encompasses a heterogeneous patient population with high inter-patient heterogeneity in prognosis and response to therapy. A more precise treatment of mHNPC, guided by evidence-based biomarkers, remains an unmet medical need. In addition, the limited number of representative laboratory models of mHNPC hampers the translation of basic research into clinical applications. We provide a comprehensive overview of the clinical and biological features that characterize mHNPC, highlight molecular data that could explain the unique prognostic characteristics of mHNPC, and identify key open questions.
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Affiliation(s)
- Jon Corres-Mendizabal
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, 48160 Derio, Spain
| | - Francesca Zacchi
- Section of Innovation Biomedicine-Oncology Area, Department of Engineering for Innovation Medicine (DIMI), University of Verona and University and Hospital Trust (AOUI) of Verona, Verona, Italy; Vall Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Campus, Barcelona, Spain
| | - Natalia Martín-Martín
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, 48160 Derio, Spain; Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain; Translational Prostate Cancer Research Laboratory, CIC bioGUNE-Basurto, Biobizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain
| | - Joaquin Mateo
- Vall Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital Campus, Barcelona, Spain.
| | - Arkaitz Carracedo
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, 48160 Derio, Spain; Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain; Translational Prostate Cancer Research Laboratory, CIC bioGUNE-Basurto, Biobizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain; Biochemistry and Molecular Biology Department, University of the Basque Country (UPV/EHU), Bilbao, Spain.
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Xin S, Liu X, Li Z, Sun X, Wang R, Zhang Z, Feng X, Jin L, Li W, Tang C, Mei W, Cao Q, Wang H, Zhang J, Feng L, Ye L. Correction: ScRNA-seq revealed an immunosuppression state and tumor microenvironment heterogeneity related to lymph node metastasis in prostate cancer. Exp Hematol Oncol 2024; 13:54. [PMID: 38769580 PMCID: PMC11103884 DOI: 10.1186/s40164-024-00517-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024] Open
Affiliation(s)
- Shiyong Xin
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
- Department of Urology, The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, China
| | - Xiang Liu
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
- Department of Urology, Putuo People's Hospital, School of Medicine, Shanghai, China
| | - Ziyao Li
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Xianchao Sun
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Rong Wang
- School of Pharmacy, Inner Mongolia Medical University, Hohhot, 010000, China
| | - Zhenhua Zhang
- School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Xinwei Feng
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-Sen University, Shenzhen, 518107, China
| | - Liang Jin
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Weiyi Li
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Chaozhi Tang
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Wangli Mei
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China
| | - Qiong Cao
- Department of Pathology, The Third Affiliated Hospital of Henan University of Science and Technology, Henan, 471003, China
| | - Haojie Wang
- Department of Central Laboratory, Zhengzhou University, Luoyang Central Hospital, Luoyang, 471003, China
| | - Jianguo Zhang
- Department of Urology, The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, China
| | - Lijin Feng
- Department of Pathology, Jing'an District Zhabei Central Hospital, No.619, Zhonghuaxin Road, Shanghai, 200070, China.
| | - Lin Ye
- Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, No.150, Ji-mo Rd, Pu-Dong New District, Shanghai, 200120, China.
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Sun L, Tuo Z, Chen X, Wang H, Lyu Z, Li G. Identification of cell differentiation trajectory-related gene signature to reveal the prognostic significance and immune landscape in prostate cancer based on multiomics analysis. Heliyon 2024; 10:e27628. [PMID: 38510027 PMCID: PMC10950568 DOI: 10.1016/j.heliyon.2024.e27628] [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] [Received: 01/02/2024] [Revised: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 03/22/2024] Open
Abstract
Background In the context of prostate cancer (PCa), the occurrence of biochemical recurrence (BCR) stands out as a pivotal factor significantly impacting prognosis, potentially leading to metastasis and mortality. However, the early detection of BCR poses a substantial challenge for PCa patients. There is an urgent need to pinpoint hub genes that can serve as predictive indicators for BCR in PCa patients. Methods Our primary goal was to identify cell differentiation trajectory-related gene signature in PCa patients by pseudo-time trajectory analysis. We further explored the functional enrichment of overlapped marker genes and probed clinically relevant modules and BCR-related genes using Weighted Gene Co-expression Network Analysis (WGCNA) in PCa patients. Key genes predicting recurrence-free survival were meticulously identified through univariate and multivariate Cox regression analyses. Subsequently, these genes were utilized to construct a prognostic gene signature, the expression, predictive efficacy, putative functions, and immunological landscape of which were thoroughly validated. Additionally, we employed immunohistochemistry (IHC) and a western blotting assay to quantify the expression of PYCR1 in clinical samples. Results Our single-cell RNA (scRNA) sequencing analysis unveiled three subgroups characterized by distinct differentiation trajectories, and the marker genes associated with these groups were extracted from PCa patients. These marker genes successfully classified the PCa sample into two molecular subtypes, demonstrating a robust correlation with clinical characteristics and recurrence-free survival. Through WGCNA and Lasso analysis, we identified four hub genes (KLK3, CD38, FASN, and PYCR1) to construct a risk profile of prognostic genes linked to BCR. Notably, the high-risk patient group exhibited elevated levels of B cell naive, Macrophage M0, and Macrophage M2 infiltration, while the low-risk group displayed higher levels of T cells CD4 memory activated and monocyte infiltration. Furthermore, IHC and western blotting assays confirmed the heightened expression of PYCR1 in PCa tissues. Conclusion This study leveraged the differentiation trajectory and genetic variability of the microenvironment to uncover crucial prognostic genes associated with BCR in PCa patients. These findings present novel perspectives for tailoring treatment strategies for PCa patients on an individualized basis.
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Affiliation(s)
- Liangxue Sun
- Department of Urology, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, China
- Department of Urology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Zhouting Tuo
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xin Chen
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Huming Wang
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Urology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Zhaojie Lyu
- Department of Urology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Guangyuan Li
- Department of Urology, The First Affiliated Hospital of Anhui Medical University, Anhui Public Health Clinical Center, Hefei, China
- The Lu’ an Hospital Affiliated to Anhui Medical University, Lu’ an, China
- The Lu’ an People’s Hospital, Lu’ an, China
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Monteran L, Zait Y, Erez N. It's all about the base: stromal cells are central orchestrators of metastasis. Trends Cancer 2024; 10:208-229. [PMID: 38072691 DOI: 10.1016/j.trecan.2023.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 03/16/2024]
Abstract
The tumor microenvironment (TME) is an integral part of tumors and plays a central role in all stages of carcinogenesis and progression. Each organ has a unique and heterogeneous microenvironment, which affects the ability of disseminated cells to grow in the new and sometimes hostile metastatic niche. Resident stromal cells, such as fibroblasts, osteoblasts, and astrocytes, are essential culprits in the modulation of metastatic progression: they transition from being sentinels of tissue integrity to being dysfunctional perpetrators that support metastatic outgrowth. Therefore, better understanding of the complexity of their reciprocal interactions with cancer cells and with other components of the TME is essential to enable the design of novel therapeutic approaches to prevent metastatic relapse.
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Affiliation(s)
- Lea Monteran
- Department of Pathology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yael Zait
- Department of Pathology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Neta Erez
- Department of Pathology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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10
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Dong G, Gao H, Chen Y, Yang H. Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis. Front Genet 2023; 14:1238407. [PMID: 37779906 PMCID: PMC10533932 DOI: 10.3389/fgene.2023.1238407] [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: 06/11/2023] [Accepted: 08/31/2023] [Indexed: 10/03/2023] Open
Abstract
Background: Although rheumatoid arthritis (RA) is a common autoimmune disease, the precise pathogenesis of the disease remains unclear. Recent research has unraveled the role of autophagy in the development of RA. This research aims to explore autophagy-related diagnostic biomarkers in the peripheral blood of RA patients. Methods: The gene expression profiles of GSE17755 were retrieved from the gene expression ontology (GEO) database. Differentially expressed autophagy-related genes (DE-ARGs) were identified for the subsequent research by inserting autophagy-related genes and differentially expressed genes (DEGs). Three machine learning algorithms, including random forest, support vector machine recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO), were employed to identify diagnostic biomarkers. A nomogram model was constructed to assess the diagnostic value of the biomarkers. The CIBERSORT algorithm was performed to investigate the correlation of the diagnostic biomarkers with immune cells and immune factors. Finally, the diagnostic efficacy and differential expression trend of diagnostic biomarkers were validated in multiple cohorts containing different tissues and diseases. Results: In this study, 25 DE-ARGs were identified between RA and healthy individuals. In addition to "macroautophagy" and "autophagy-animal," DE-ARGs were also associated with several types of programmed cell death and immune-related pathways according to GO and KEGG analysis. Three diagnostic biomarkers, EEF2, HSP90AB1 and TNFSF10, were identified by the random forest, SVM-RFE, and LASSO. The nomogram model demonstrated excellent diagnostic value in GSE17755 (AUC = 0.995, 95% CI: 0.988-0.999). Furthermore, immune infiltration analysis showed a remarkable association between EEF2, HSP90AB1, and TNFSF10 expression with various immune cells and immune factors. The three diagnostic biomarkers also exhibited good diagnostic efficacy and demonstrated the same trend of differential expression in multiple validation cohorts. Conclusion: This study identified autophagy-related diagnostic biomarkers based on three machine learning algorithms, providing promising targets for the diagnosis and treatment of RA.
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Affiliation(s)
| | | | | | - Huayuan Yang
- School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Huang D, Ma N, Li X, Gou Y, Duan Y, Liu B, Xia J, Zhao X, Wang X, Li Q, Rao J, Zhang X. Advances in single-cell RNA sequencing and its applications in cancer research. J Hematol Oncol 2023; 16:98. [PMID: 37612741 PMCID: PMC10463514 DOI: 10.1186/s13045-023-01494-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023] Open
Abstract
Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.
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Affiliation(s)
- Dezhi Huang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Naya Ma
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xinlei Li
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Yang Gou
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Yishuo Duan
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Bangdong Liu
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Jing Xia
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xianlan Zhao
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xiaoqi Wang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Qiong Li
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
| | - Jun Rao
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
| | - Xi Zhang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
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