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Hasubek AL, Wang X, Zhang E, Kobus M, Chen J, Vandergrift LA, Kurreck A, Ehret F, Dinges S, Hohm A, Tilgner M, Buko A, Habbel P, Nowak J, Mercaldo ND, Gusev A, Feldman AS, Cheng LL. Differentiation of patients with and without prostate cancer using urine 1 H NMR metabolomics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:740-747. [PMID: 37654196 DOI: 10.1002/mrc.5391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/09/2023] [Accepted: 08/12/2023] [Indexed: 09/02/2023]
Abstract
Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate-specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)-based metabolomics has proven to be promising for advancing early-detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers. This retrospective study of urine-NMR samples, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate-key metabolites involved in cellular proliferation and microbiome effects, respectively-were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis.
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Affiliation(s)
- Anna-Laura Hasubek
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoyu Wang
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ella Zhang
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Marta Kobus
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jiashang Chen
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lindsey A Vandergrift
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Annika Kurreck
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Felix Ehret
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Sarah Dinges
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Annika Hohm
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Marlon Tilgner
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Buko
- Human Metabolome Technologies, Boston, Massachusetts, USA
| | - Piet Habbel
- Charite - Universitatsmedizin Berlin, Berlin, Germany
| | - Johannes Nowak
- SRH Poliklinik Gera GmbH, Radiology Gotha, Gotha, Germany
- SRH University of Applied Health Sciences, Gera, Germany
| | - Nathaniel D Mercaldo
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew Gusev
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Adam S Feldman
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Leo L Cheng
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
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Zhang Z, Pei Y, Hu W, Xue Y, Ning R, Guo X, Sun Y, Zhang Q. The metabolic repression effect of carbon-ion radiotherapy in synchronous hormone-sensitive oligometastatic prostate cancer. Front Endocrinol (Lausanne) 2023; 14:1291653. [PMID: 38027094 PMCID: PMC10680404 DOI: 10.3389/fendo.2023.1291653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023] Open
Abstract
Background Metastatic prostate cancer (PCa) poses a significant public health concern. While radiation therapy (RT) is commonly utilized in the treatment of synchronous oligometastatic hormone sensitive prostate cancer (OM-HSPC), the occurrence of biochemical recurrence still remains. To deepen our understanding and optimize the outcome of OM-HSPC, we conducted this study to investigate the characteristics of PCa progression and explore potential synergistic mechanisms involving carbon-ion radiotherapy (CIRT) and neoadjuvant androgen deprivation treatment (naADT) in OM-HSPC. Methods Metabolomic analysis was conducted with 72 urinary samples (at different timepoints) from 33 Patients (T2-3N0M0-1b) and 18 healthy volunteers by using liquid chromatography-tandem mass spectrometry (LC-MS/MS). MetaboAnalyst website and R software were employed for metabolomic analysis and visualization (using the criteria of p value < 0.05 and |FC|>1.5). The impact of CIRT on metabolism were further verified and explored through in vitro and in vivo experiments. Results We found that most metabolites (223 out of 233) were upregulated in treatment-naïve PCa samples compared to healthy samples. After naADT, 60 core risk metabolites were still significantly related to PCa's progression, and the glutamine level which was significantly higher in OM-HSPC compared to other groups. Remarkably, after CIRT treatment, the glutamine levels in OM-HSPC were significantly reduced to the level of healthy samples. Experiments further confirmed CIRT's ability to suppress glutamine levels in PCa tumors and its potential enhancement with glutamine deprivation intervention. Conclusion CIRT with naADT might synergistically inhibit HS-OMPC development, progression and even the ADT resistance through glutamine metabolism repression, moreover, the glutamine metabolism might be a novel target to further improved the efficacy of CIRT.
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Affiliation(s)
- Zhenshan Zhang
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Yulei Pei
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Wei Hu
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Yushan Xue
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Renli Ning
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Xiaomao Guo
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Yun Sun
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
- Department of Research and Development, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Qing Zhang
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
- Shanghai Key Laboratory of Radiation Oncology, Shanghai, China
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
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Huang HP, Chen CH, Chang KH, Lee MS, Lee CF, Chao YH, Lu SY, Wu TF, Liang ST, Lin CY, Lin YC, Liu SP, Lu YC, Shun CT, Huang WJ, Lin TP, Ku MH, Chung HJ, Chang YH, Liao CH, Yu CC, Chung SD, Tsai YC, Wu CC, Chen KC, Ho CH, Hsiao PW, Pu YS. Prediction of clinically significant prostate cancer through urine metabolomic signatures: A large-scale validated study. J Transl Med 2023; 21:714. [PMID: 37821919 PMCID: PMC10566053 DOI: 10.1186/s12967-023-04424-9] [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: 04/27/2023] [Accepted: 08/07/2023] [Indexed: 10/13/2023] Open
Abstract
PURPOSE Currently, there are no accurate markers for predicting potentially lethal prostate cancer (PC) before biopsy. This study aimed to develop urine tests to predict clinically significant PC (sPC) in men at risk. METHODS Urine samples from 928 men, namely, 660 PC patients and 268 benign subjects, were analyzed by gas chromatography/quadrupole time-of-flight mass spectrophotometry (GC/Q-TOF MS) metabolomic profiling to construct four predictive models. Model I discriminated between PC and benign cases. Models II, III, and GS, respectively, predicted sPC in those classified as having favorable intermediate risk or higher, unfavorable intermediate risk or higher (according to the National Comprehensive Cancer Network risk groupings), and a Gleason sum (GS) of ≥ 7. Multivariable logistic regression was used to evaluate the area under the receiver operating characteristic curves (AUC). RESULTS In Models I, II, III, and GS, the best AUCs (0.94, 0.85, 0.82, and 0.80, respectively; training cohort, N = 603) involved 26, 24, 26, and 22 metabolites, respectively. The addition of five clinical risk factors (serum prostate-specific antigen, patient age, previous negative biopsy, digital rectal examination, and family history) significantly improved the AUCs of the models (0.95, 0.92, 0.92, and 0.87, respectively). At 90% sensitivity, 48%, 47%, 50%, and 36% of unnecessary biopsies could be avoided. These models were successfully validated against an independent validation cohort (N = 325). Decision curve analysis showed a significant clinical net benefit with each combined model at low threshold probabilities. Models II and III were more robust and clinically relevant than Model GS. CONCLUSION This urine test, which combines urine metabolic markers and clinical factors, may be used to predict sPC and thereby inform the necessity of biopsy in men with an elevated PC risk.
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Affiliation(s)
- Hsiang-Po Huang
- Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chung-Hsin Chen
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Kai-Hsiung Chang
- Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli, Taiwan
| | - Ming-Shyue Lee
- Department of Biochemistry and Molecular Biology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Cheng-Fan Lee
- Department of Biochemistry and Molecular Biology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yen-Hsiang Chao
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Shih-Yu Lu
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Tzu-Fan Wu
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Sung-Tzu Liang
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Chih-Yu Lin
- Agricultural Biotechnology Research Center, Academia Sinica, No. 128, Sec. 2, Academia Road, Nankang, Taipei, 11529, Taiwan
| | - Yuan Chi Lin
- Department of Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Shih-Ping Liu
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
| | - Yu-Chuan Lu
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China
- Department of Surgical Oncology, National Taiwan University Cancer Center, Taipei, Taiwan
| | - Chia-Tung Shun
- Department of Pathology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - William J Huang
- Department of Urology, Taipei Veterans General Hospital, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tzu-Ping Lin
- Department of Urology, Taipei Veterans General Hospital, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ming-Hsuan Ku
- Department of Urology, Taipei Veterans General Hospital, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Hsiao-Jen Chung
- Department of Urology, Taipei Veterans General Hospital, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Hwa Chang
- Department of Urology, Taipei Veterans General Hospital, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chun-Hou Liao
- Division of Urology, Department of Surgery, Cardinal Tien Hospital, New Taipei City, Taiwan
- School of Medicine, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Chih-Chin Yu
- Division of Urology, Department of Surgery, Taipei Tzu Chi Hospital, and the Buddhist Tzu Chi Medical Foundation, College of Medicine, Tzu Chi University, Hualien, Taiwan
| | - Shiu-Dong Chung
- Division of Urology, Department of Surgery, Far Eastern Memorial Hospital, and Department of Nursing, College of Healthcare & Management, Asia Eastern University of Science and Technology, New Taipei City, Taiwan
| | - Yao-Chou Tsai
- Department of Medicine & Division of Urology, Taipei Tzu Chi Hospital, New Taipei City, Taiwan
| | - Chia-Chang Wu
- Department of Urology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Department of Urology, Shuang-Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan
| | - Kuan-Chou Chen
- Department of Urology, Shuang-Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
- TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, Taipei Medical University, Taipei, Taiwan
| | - Chen-Hsun Ho
- School of Medicine, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
- Division of Urology, Department of Surgery, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
| | - Pei-Wen Hsiao
- Agricultural Biotechnology Research Center, Academia Sinica, No. 128, Sec. 2, Academia Road, Nankang, Taipei, 11529, Taiwan.
| | - Yeong-Shiau Pu
- Department of Urology, National Taiwan University College of Medicine and Hospital, 7 Zhongshan South Road, Taipei, 100225, Taiwan, Republic of China.
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Bansal N, Kumar M, Sankhwar SN, Gupta A. Evaluation of prostate cancer tissue metabolomics: would clinics utilise it for diagnosis? Expert Rev Mol Med 2023; 25:e26. [PMID: 37548191 DOI: 10.1017/erm.2023.22] [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] [Indexed: 08/08/2023]
Abstract
The difficulty of diagnosing prostate cancer (PC) with the available biomarkers frequently leads to over-diagnosis and overtreatment of PC, underscoring the need for novel molecular signatures. The purpose of this review is to provide a summary of the currently available cellular metabolomics for PC molecular signatures. A comprehensive search on PubMed was conducted to find studies published between January 2004 and August 2022 that reported biomarkers for PC detection, development, aggressiveness, recurrence and treatment response. Although potential studies have reported the presence of distinguishing molecules that can distinguish between benign and cancerous prostate tissue. However, there are few studies looking into signature molecules linked to disease development, therapy response or tumour recurrence. The majority of these studies use high-dimensional datasets, and the number of potential metabolites investigated frequently exceeds the size of the available samples. In light of this, pre-analytical, statistical, methodological and confounding factors such as antiandrogen therapy (NAT) may also be linked to the identified chemometric multivariate differences between PC and relevant control samples in the datasets. Despite the methodological and procedural challenges, a range of methodological groups and processes have consistently identified a number of signature metabolites and pathways that appear to imply a substantial involvement in the cellular metabolomics of PC for tumour formation and recurrence.
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Affiliation(s)
- Navneeta Bansal
- Department of Urology, King George's Medical University, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George's Medical University, Lucknow, India
| | - Satya N Sankhwar
- Department of Urology, King George's Medical University, Lucknow, India
| | - Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
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5
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Liu Q, Fan Y, Zeng S, Zhao Y, Yu L, Zhao L, Gao J, Zhang X, Zhang Y. Volatile organic compounds for early detection of prostate cancer from urine. Heliyon 2023; 9:e16686. [PMID: 37303549 PMCID: PMC10250727 DOI: 10.1016/j.heliyon.2023.e16686] [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: 02/21/2023] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 06/13/2023] Open
Abstract
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Early diagnosis of PCa is extremely challenging due to the lack of effective diagnostic methods. The study presented here aims to evaluate whether urine volatile organic compounds (VOCs) can be used as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in urine samples from 66 patients with PCa and to comparatively analyze samples from 87 patients with non-cancerous controls (NCs). A total of 86 substance peak heights were detected in urine samples from all patients. Analysis using four machine learning algorithms suggested that the diagnosis of PCa could be effectively facilitated. Ultimately, diagnostic models were constructed based on the four VOCs selected. The AUC for the RF and SVM model were 0.955 and 0.981, respectively. Both the NN and DT diagnostic models also achieved an AUC of 0.8 or more, but their sensitivity or specificity was poor compared to the RF and SVM models.
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Affiliation(s)
- Qi Liu
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Yingjing Fan
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Shunjie Zeng
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Yuxiao Zhao
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Longchen Yu
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Liqiang Zhao
- Department of Research and Development, Hanon Advanced Technology Group Co., Ltd, Jinan, China
| | - Jingxian Gao
- Department of Research and Development, Hanon Advanced Technology Group Co., Ltd, Jinan, China
| | - Xin Zhang
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
| | - Yi Zhang
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China
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Shi F, Qi Y, Jiang S, Sun N, Deng C. Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy. Anal Chem 2023; 95:7312-7319. [PMID: 37121232 DOI: 10.1021/acs.analchem.3c00369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.
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Affiliation(s)
- Fangying Shi
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai 200433, China
| | - Yu Qi
- Department of Urology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Shuai Jiang
- Department of Urology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Department of Urology, Zhongshan Hospital Wusong Branch, Fudan University, Shanghai 200940, China
| | - Nianrong Sun
- Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chunhui Deng
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai 200433, China
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Gonzales LISA, Qiao JW, Buffier AW, Rogers LJ, Suchowerska N, McKenzie DR, Kwan AH. An omics approach to delineating the molecular mechanisms that underlie the biological effects of physical plasma. BIOPHYSICS REVIEWS 2023; 4:011312. [PMID: 38510160 PMCID: PMC10903421 DOI: 10.1063/5.0089831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 02/24/2023] [Indexed: 03/22/2024]
Abstract
The use of physical plasma to treat cancer is an emerging field, and interest in its applications in oncology is increasing rapidly. Physical plasma can be used directly by aiming the plasma jet onto cells or tissue, or indirectly, where a plasma-treated solution is applied. A key scientific question is the mechanism by which physical plasma achieves selective killing of cancer over normal cells. Many studies have focused on specific pathways and mechanisms, such as apoptosis and oxidative stress, and the role of redox biology. However, over the past two decades, there has been a rise in omics, the systematic analysis of entire collections of molecules in a biological entity, enabling the discovery of the so-called "unknown unknowns." For example, transcriptomics, epigenomics, proteomics, and metabolomics have helped to uncover molecular mechanisms behind the action of physical plasma, revealing critical pathways beyond those traditionally associated with cancer treatments. This review showcases a selection of omics and then summarizes the insights gained from these studies toward understanding the biological pathways and molecular mechanisms implicated in physical plasma treatment. Omics studies have revealed how reactive species generated by plasma treatment preferentially affect several critical cellular pathways in cancer cells, resulting in epigenetic, transcriptional, and post-translational changes that promote cell death. Finally, this review considers the outlook for omics in uncovering both synergies and antagonisms with other common cancer therapies, as well as in overcoming challenges in the clinical translation of physical plasma.
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Affiliation(s)
- Lou I. S. A. Gonzales
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Jessica W. Qiao
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Aston W. Buffier
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | | | | | | | - Ann H. Kwan
- Author to whom correspondence should be addressed:
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Nevedomskaya E, Haendler B. From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer. Int J Mol Sci 2022; 23:ijms23116281. [PMID: 35682963 PMCID: PMC9181488 DOI: 10.3390/ijms23116281] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/24/2022] [Accepted: 06/01/2022] [Indexed: 02/01/2023] Open
Abstract
Cancer arises following alterations at different cellular levels, including genetic and epigenetic modifications, transcription and translation dysregulation, as well as metabolic variations. High-throughput omics technologies that allow one to identify and quantify processes involved in these changes are now available and have been instrumental in generating a wealth of steadily increasing data from patient tumors, liquid biopsies, and from tumor models. Extensive investigation and integration of these data have led to new biological insights into the origin and development of multiple cancer types and helped to unravel the molecular networks underlying this complex pathology. The comprehensive and quantitative analysis of a molecule class in a biological sample is named omics and large-scale omics studies addressing different prostate cancer stages have been performed in recent years. Prostate tumors represent the second leading cancer type and a prevalent cause of cancer death in men worldwide. It is a very heterogenous disease so that evaluating inter- and intra-tumor differences will be essential for a precise insight into disease development and plasticity, but also for the development of personalized therapies. There is ample evidence for the key role of the androgen receptor, a steroid hormone-activated transcription factor, in driving early and late stages of the disease, and this led to the development and approval of drugs addressing diverse targets along this pathway. Early genomic and transcriptomic studies have allowed one to determine the genes involved in prostate cancer and regulated by androgen signaling or other tumor-relevant signaling pathways. More recently, they have been supplemented by epigenomic, cistromic, proteomic and metabolomic analyses, thus, increasing our knowledge on the intricate mechanisms involved, the various levels of regulation and their interplay. The comprehensive investigation of these omics approaches and their integration into multi-omics analyses have led to a much deeper understanding of the molecular pathways involved in prostate cancer progression, and in response and resistance to therapies. This brings the hope that novel vulnerabilities will be identified, that existing therapies will be more beneficial by targeting the patient population likely to respond best, and that bespoke treatments with increased efficacy will be available soon.
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Affiliation(s)
| | - Bernard Haendler
- Correspondence: ; Tel.: +49-30-2215-41198; Fax: +49-30-468-18069
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