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Feng Y. An integrated machine learning-based model for joint diagnosis of ovarian cancer with multiple test indicators. J Ovarian Res 2024; 17:45. [PMID: 38378582 PMCID: PMC10877874 DOI: 10.1186/s13048-024-01365-9] [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: 08/31/2023] [Accepted: 02/01/2024] [Indexed: 02/22/2024] Open
Abstract
OBJECTIVE To construct a machine learning diagnostic model integrating feature dimensionality reduction techniques and artificial neural network classifiers to develop the value of clinical routine blood indexes for the auxiliary diagnosis of ovarian cancer. METHODS Patients with ovarian cancer clearly diagnosed in our hospital were collected as a case group (n = 185), and three groups of patients with other malignant otolaryngology tumors (n = 138), patients with benign otolaryngology diseases (n = 339) and those with normal physical examination (n = 92) were used as an overall control group. In this paper, a fully automated segmentation network for magnetic resonance images of ovarian cancer is proposed to improve the reproducibility of tumor segmentation results while effectively reducing the burden on radiologists. A pre-trained Res Net50 is used to the three edge output modules are fused to obtain the final segmentation results. The segmentation results of the proposed network architecture are compared with the segmentation results of the U-net based network architecture and the effect of different loss functions and region of interest sizes on the segmentation performance of the proposed network is analyzed. RESULTS The average Dice similarity coefficient, average sensitivity, average specificity (specificity) and average hausdorff distance of the proposed network segmentation results reached 83.62%, 89.11%, 96.37% and 8.50, respectively, which were better than the U-net based segmentation method. For ROIs containing tumor tissue, the smaller the size, the better the segmentation effect. Several loss functions do not differ much. The area under the ROC curve of the machine learning diagnostic model reached 0.948, with a sensitivity of 91.9% and a specificity of 86.9%, and its diagnostic efficacy was significantly better than that of the traditional way of detecting CA125 alone. The model was able to accurately diagnose ovarian cancer of different disease stages and showed certain discriminative ability for ovarian cancer in all three control subgroups. CONCLUSION Using machine learning to integrate multiple conventional test indicators can effectively improve the diagnostic efficacy of ovarian cancer, which provides a new idea for the intelligent auxiliary diagnosis of ovarian cancer.
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Affiliation(s)
- Yiwen Feng
- Departments of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200080, P.R. China.
- Jiuquan Hospital, Shanghai General Hospital, 200003, Shanghai, China.
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2
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Gnaiger E. Complex II ambiguities-FADH 2 in the electron transfer system. J Biol Chem 2024; 300:105470. [PMID: 38118236 PMCID: PMC10772739 DOI: 10.1016/j.jbc.2023.105470] [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: 07/03/2023] [Revised: 11/01/2023] [Accepted: 11/06/2023] [Indexed: 12/22/2023] Open
Abstract
The prevailing notion that reduced cofactors NADH and FADH2 transfer electrons from the tricarboxylic acid cycle to the mitochondrial electron transfer system creates ambiguities regarding respiratory Complex II (CII). CII is the only membrane-bound enzyme in the tricarboxylic acid cycle and is part of the electron transfer system of the mitochondrial inner membrane feeding electrons into the coenzyme Q-junction. The succinate dehydrogenase subunit SDHA of CII oxidizes succinate and reduces the covalently bound prosthetic group FAD to FADH2 in the canonical forward tricarboxylic acid cycle. However, several graphical representations of the electron transfer system depict FADH2 in the mitochondrial matrix as a substrate to be oxidized by CII. This leads to the false conclusion that FADH2 from the β-oxidation cycle in fatty acid oxidation feeds electrons into CII. In reality, dehydrogenases of fatty acid oxidation channel electrons to the Q-junction but not through CII. The ambiguities surrounding Complex II in the literature and educational resources call for quality control, to secure scientific standards in current communications of bioenergetics, and ultimately support adequate clinical applications. This review aims to raise awareness of the inherent ambiguity crisis, complementing efforts to address the well-acknowledged issues of credibility and reproducibility.
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Schatten H. The Impact of Mitochondria in Ovarian Cancer Cell Metabolism, Proliferation, and Metastasis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1452:119-125. [PMID: 38805128 DOI: 10.1007/978-3-031-58311-7_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Mitochondrial dysfunctions are significantly implicated in cancer initiation, progression, and metastasis, which have been shown for several cancers including ovarian cancer.An increase in mitochondrial dysfunction is also associated with drug resistance along with cancer progression, which in part is related to its specific microenvironment that is characterized by ascites, low glucose levels, and hypoxia that causes ovarian cancer cells to switch to mitochondrial respiration to enable their survival. Peritoneal ascitic fluid accumulation is a specific feature of ovarian cancer, and it is a major cause of its metastatic spread that also presents challenges for effective treatment. Among the treatment difficulties for ovarian cancer is the mutation rate and frequency of mtDNA in ovarian cancer tissue that can affect the efficiency of chemotherapeutic drugs. The varied and multiple mutations of different types enable metabolic reprogramming, cancer cell proliferation, and drug resistance.New specific information on mechanisms underlying several of the mitochondrial dysfunctions has led to proposing various mitochondrial determinants as targets for ovarian cancer therapy, which include targeting specific mitochondrial proteins and phosphoproteins as well as reactive oxygen species (ROS) that accumulate abnormally in cancer cells. Because of the genetically and histologically heterogeneous nature of the disease, combination therapy approaches will be necessary to combat the disease and achieve progress in effective treatment of ovarian cancer. This chapter will address (1) mitochondrial vulnerabilities underlying dysfunction and disease; (2) mitochondrial dysfunction in ovarian cancer; (3) present treatment difficulties for ovarian cancer and new potential treatment strategies to target ovarian cancer mitochondrial metabolism; and (4) biobehavioral factors influencing ovarian cancer development.
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Affiliation(s)
- Heide Schatten
- Department of Veterinary Pathobiology, University of Missouri-Columbia, Columbia, MO, USA.
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4
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Rosenberg AM, Saggar M, Monzel AS, Devine J, Rogu P, Limoges A, Junker A, Sandi C, Mosharov EV, Dumitriu D, Anacker C, Picard M. Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice. Nat Commun 2023; 14:4726. [PMID: 37563104 PMCID: PMC10415311 DOI: 10.1038/s41467-023-39941-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 07/04/2023] [Indexed: 08/12/2023] Open
Abstract
The brain and behavior are under energetic constraints, limited by mitochondrial energy transformation capacity. However, the mitochondria-behavior relationship has not been systematically studied at a brain-wide scale. Here we examined the association between multiple features of mitochondrial respiratory chain capacity and stress-related behaviors in male mice with diverse behavioral phenotypes. Miniaturized assays of mitochondrial respiratory chain enzyme activities and mitochondrial DNA (mtDNA) content were deployed on 571 samples across 17 brain areas, defining specific patterns of mito-behavior associations. By applying multi-slice network analysis to our brain-wide mitochondrial dataset, we identified three large-scale networks of brain areas with shared mitochondrial signatures. A major network composed of cortico-striatal areas exhibited the strongest mitochondria-behavior correlations, accounting for up to 50% of animal-to-animal behavioral differences, suggesting that this mito-based network is functionally significant. The mito-based brain networks also overlapped with regional gene expression and structural connectivity, and exhibited distinct molecular mitochondrial phenotype signatures. This work provides convergent multimodal evidence anchored in enzyme activities, gene expression, and animal behavior that distinct, behaviorally-relevant mitochondrial phenotypes exist across the male mouse brain.
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Affiliation(s)
- Ayelet M Rosenberg
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Anna S Monzel
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Jack Devine
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Peter Rogu
- Columbia University Institute for Developmental Sciences, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Aaron Limoges
- Department of Biological Sciences, Columbia University, New York, NY, USA
- Division of Systems Neuroscience, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Alex Junker
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Carmen Sandi
- Brain Mind Institute, Ecole Polytechnique Federal de Lausanne (EPFL), Lausanne, Switzerland
| | - Eugene V Mosharov
- Division of Molecular Therapeutics, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Dani Dumitriu
- Columbia University Institute for Developmental Sciences, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
- Division of Developmental Neuroscience, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Christoph Anacker
- Columbia University Institute for Developmental Sciences, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Division of Systems Neuroscience, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Martin Picard
- Division of Behavioral Medicine, Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
- New York State Psychiatric Institute, New York, NY, USA.
- Department of Neurology, H. Houston Merritt Center, Columbia Translational Neuroscience Initiative, Columbia University Irving Medical Center, New York, NY, USA.
- Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA.
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Rickard BP, Overchuk M, Chappell VA, Kemal Ruhi M, Sinawang PD, Nguyen Hoang TT, Akin D, Demirci U, Franco W, Fenton SE, Santos JH, Rizvi I. Methods to Evaluate Changes in Mitochondrial Structure and Function in Cancer. Cancers (Basel) 2023; 15:2564. [PMID: 37174030 PMCID: PMC10177605 DOI: 10.3390/cancers15092564] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/15/2023] Open
Abstract
Mitochondria are regulators of key cellular processes, including energy production and redox homeostasis. Mitochondrial dysfunction is associated with various human diseases, including cancer. Importantly, both structural and functional changes can alter mitochondrial function. Morphologic and quantifiable changes in mitochondria can affect their function and contribute to disease. Structural mitochondrial changes include alterations in cristae morphology, mitochondrial DNA integrity and quantity, and dynamics, such as fission and fusion. Functional parameters related to mitochondrial biology include the production of reactive oxygen species, bioenergetic capacity, calcium retention, and membrane potential. Although these parameters can occur independently of one another, changes in mitochondrial structure and function are often interrelated. Thus, evaluating changes in both mitochondrial structure and function is crucial to understanding the molecular events involved in disease onset and progression. This review focuses on the relationship between alterations in mitochondrial structure and function and cancer, with a particular emphasis on gynecologic malignancies. Selecting methods with tractable parameters may be critical to identifying and targeting mitochondria-related therapeutic options. Methods to measure changes in mitochondrial structure and function, with the associated benefits and limitations, are summarized.
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Affiliation(s)
- Brittany P. Rickard
- Curriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Marta Overchuk
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, and North Carolina State University, Raleigh, NC 27695, USA
| | - Vesna A. Chappell
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Mustafa Kemal Ruhi
- Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey
| | - Prima Dewi Sinawang
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, School of Medicine, Palo Alto, CA 94304, USA
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Tina Thuy Nguyen Hoang
- Department of Biomedical Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| | - Demir Akin
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, School of Medicine, Palo Alto, CA 94304, USA
- Center for Cancer Nanotechnology Excellence for Translational Diagnostics (CCNE-TD), School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Utkan Demirci
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, School of Medicine, Palo Alto, CA 94304, USA
| | - Walfre Franco
- Department of Biomedical Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
| | - Suzanne E. Fenton
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Janine H. Santos
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Imran Rizvi
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, and North Carolina State University, Raleigh, NC 27695, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
- Center for Environmental Health and Susceptibility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Rickard BP, Overchuk M, Obaid G, Ruhi MK, Demirci U, Fenton SE, Santos JH, Kessel D, Rizvi I. Photochemical Targeting of Mitochondria to Overcome Chemoresistance in Ovarian Cancer †. Photochem Photobiol 2023; 99:448-468. [PMID: 36117466 PMCID: PMC10043796 DOI: 10.1111/php.13723] [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: 08/08/2022] [Accepted: 08/29/2022] [Indexed: 11/30/2022]
Abstract
Ovarian cancer is the most lethal gynecologic malignancy with a stubborn mortality rate of ~65%. The persistent failure of multiline chemotherapy, and significant tumor heterogeneity, has made it challenging to improve outcomes. A target of increasing interest is the mitochondrion because of its essential role in critical cellular functions, and the significance of metabolic adaptation in chemoresistance. This review describes mitochondrial processes, including metabolic reprogramming, mitochondrial transfer and mitochondrial dynamics in ovarian cancer progression and chemoresistance. The effect of malignant ascites, or excess peritoneal fluid, on mitochondrial function is discussed. The role of photodynamic therapy (PDT) in overcoming mitochondria-mediated resistance is presented. PDT, a photochemistry-based modality, involves the light-based activation of a photosensitizer leading to the production of short-lived reactive molecular species and spatiotemporally confined photodamage to nearby organelles and biological targets. The consequential effects range from subcytotoxic priming of target cells for increased sensitivity to subsequent treatments, such as chemotherapy, to direct cell killing. This review discusses how PDT-based approaches can address key limitations of current treatments. Specifically, an overview of the mechanisms by which PDT alters mitochondrial function, and a summary of preclinical advancements and clinical PDT experience in ovarian cancer are provided.
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Affiliation(s)
- Brittany P. Rickard
- Curriculum in Toxicology & Environmental Medicine, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Marta Overchuk
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; North Carolina State University, Raleigh, NC 27606, USA
| | - Girgis Obaid
- Department of Bioengineering, University of Texas at Dallas, Richardson TX 95080, USA
| | - Mustafa Kemal Ruhi
- Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey
| | - Utkan Demirci
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Suzanne E. Fenton
- Curriculum in Toxicology & Environmental Medicine, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Mechanistic Toxicology Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Janine H. Santos
- Mechanistic Toxicology Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - David Kessel
- Department of Pharmacology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - Imran Rizvi
- Curriculum in Toxicology & Environmental Medicine, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; North Carolina State University, Raleigh, NC 27606, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
- Center for Environmental Health and Susceptibility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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7
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Koc ZC, Sollars VE, Bou Zgheib N, Rankin GO, Koc EC. Evaluation of mitochondrial biogenesis and ROS generation in high-grade serous ovarian cancer. Front Oncol 2023; 13:1129352. [PMID: 36937395 PMCID: PMC10014927 DOI: 10.3389/fonc.2023.1129352] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 02/08/2023] [Indexed: 03/05/2023] Open
Abstract
Introduction Ovarian cancer is one of the leading causes of death for women with cancer worldwide. Energy requirements for tumor growth in epithelial high-grade serous ovarian cancer (HGSOC) are fulfilled by a combination of aerobic glycolysis and oxidative phosphorylation (OXPHOS). Although reduced OXPHOS activity has emerged as one of the significant contributors to tumor aggressiveness and chemoresistance, up-regulation of mitochondrial antioxidant capacity is required for matrix detachment and colonization into the peritoneal cavity to form malignant ascites in HGSOC patients. However, limited information is available about the mitochondrial biogenesis regulating OXPHOS capacity and generation of mitochondrial reactive oxygen species (mtROS) in HGSOC. Methods To evaluate the modulation of OXPHOS in HGSOC tumor samples and ovarian cancer cell lines, we performed proteomic analyses of proteins involved in mitochondrial energy metabolism and biogenesis and formation of mtROS by immunoblotting and flow cytometry, respectively. Results and discussion We determined that the increased steady-state expression levels of mitochondrial- and nuclear-encoded OXPHOS subunits were associated with increased mitochondrial biogenesis in HGSOC tumors and ovarian cancer cell lines. The more prominent increase in MT-COII expression was in agreement with significant increase in mitochondrial translation factors, TUFM and DARS2. On the other hand, the ovarian cancer cell lines with reduced OXPHOS subunit expression and mitochondrial translation generated the highest levels of mtROS and significantly reduced SOD2 expression. Evaluation of mitochondrial biogenesis suggested that therapies directed against mitochondrial targets, such as those involved in transcription and translation machineries, should be considered in addition to the conventional chemotherapies in HGSOC treatment.
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Affiliation(s)
- Zeynep C. Koc
- Department of Obstetrics, Gynecology and Reproductive Sciences, Temple University, Philadelphia, PA, United States
| | - Vincent E. Sollars
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
| | - Nadim Bou Zgheib
- Edwards Comprehensive Cancer Center, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
| | - Gary O. Rankin
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
| | - Emine C. Koc
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
- *Correspondence: Emine C. Koc,
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Achreja A, Yu T, Mittal A, Choppara S, Animasahun O, Nenwani M, Wuchu F, Meurs N, Mohan A, Jeon JH, Sarangi I, Jayaraman A, Owen S, Kulkarni R, Cusato M, Weinberg F, Kweon HK, Subramanian C, Wicha MS, Merajver SD, Nagrath S, Cho KR, DiFeo A, Lu X, Nagrath D. Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer. Nat Metab 2022; 4:1119-1137. [PMID: 36131208 DOI: 10.1038/s42255-022-00636-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 08/09/2022] [Indexed: 11/08/2022]
Abstract
Recurrent loss-of-function deletions cause frequent inactivation of tumour suppressor genes but often also involve the collateral deletion of essential genes in chromosomal proximity, engendering dependence on paralogues that maintain similar function. Although these paralogues are attractive anticancer targets, no methodology exists to uncover such collateral lethal genes. Here we report a framework for collateral lethal gene identification via metabolic fluxes, CLIM, and use it to reveal MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours. We show that MTHFD2 has a non-canonical oxidative function to provide mitochondrial NAD+, and demonstrate the regulation of systemic metabolic activity by the paralogue metabolic pathway maintaining metabolic flux compensation. This UQCR11-MTHFD2 collateral lethality is confirmed in vivo, with MTHFD2 inhibition leading to complete remission of UQCR11-deleted ovarian tumours. Using CLIM's machine learning and genome-scale metabolic flux analysis, we elucidate the broad efficacy of targeting MTHFD2 despite distinct cancer genetic profiles co-occurring with UQCR11 deletion and irrespective of stromal compositions of tumours.
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Affiliation(s)
- Abhinav Achreja
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Tao Yu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Anjali Mittal
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Srinadh Choppara
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Olamide Animasahun
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Minal Nenwani
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Fulei Wuchu
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Noah Meurs
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Aradhana Mohan
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Jin Heon Jeon
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Itisam Sarangi
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Anusha Jayaraman
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Sarah Owen
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Reva Kulkarni
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Michele Cusato
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Frank Weinberg
- Hematology and Oncology, University of Illinois, Chicago, IL, USA
| | - Hye Kyong Kweon
- Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA
| | - Chitra Subramanian
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Max S Wicha
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sofia D Merajver
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sunitha Nagrath
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Kathleen R Cho
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA
| | - Analisa DiFeo
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA
| | - Xiongbin Lu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
- Melvin & Bren Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Deepak Nagrath
- Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA.
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
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9
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Berkel C, Cacan E. Copy number and expression of CEP89, a protein required for ciliogenesis, are increased and predict poor prognosis in patients with ovarian cancer. Cell Biochem Funct 2022; 40:298-309. [PMID: 35285957 DOI: 10.1002/cbf.3694] [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: 12/29/2021] [Revised: 02/12/2022] [Accepted: 02/21/2022] [Indexed: 11/10/2022]
Abstract
CEP89 (centrosomal protein 89) is required for ciliogenesis and mitochondrial metabolism, but its role in cancer has yet to be clarified. We report that CEP89 is overexpressed in ovarian cancer (OC) compared to normal ovaries. Likewise, its expression is higher in malignant ovarian tumors than in borderline ovarian tumors with low malignant potential. More than a quarter of patients with OC have copy number gains in the CEP89 gene, and patients with high expression have more than a year shorter overall survival compared to those with low expression. Moreover, we found that CEP89 can be considered as a prognostic marker for poor overall survival in patients with OC, after adjusting for tumor stage and residual tumor. Nine out of the top 10 protein interactors of CEP89 have the highest percentage of total copy number variation (CNV) events in OC among all other cancer types. Furthermore, CEP89 messenger RNA (mRNA) levels are higher in OC patients with disease recurrence compared to those with no recurrence. We also analyzed CEP89 levels in OC cell lines in terms of CNV, mRNA, and protein levels; and observed that the FUOV-1 cell line has the highest levels among cell lines that originated from primary sites. Our study suggests that CEP89 may be a valuable prognostic predictor for the overall survival of patients with OC, and it could also be a novel therapeutic target in this malignancy.
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Affiliation(s)
- Caglar Berkel
- Department of Molecular Biology and Genetics, Tokat Gaziosmanpasa University, Tokat, Turkey
| | - Ercan Cacan
- Department of Molecular Biology and Genetics, Tokat Gaziosmanpasa University, Tokat, Turkey
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10
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Xu Z, Lin S, Tong Z, Chen S, Cao Y, Li Q, Jiang Y, Cai W, Tong Y, Zahra BS, Wang P. Crocetin ameliorates non-alcoholic fatty liver disease by modulating mitochondrial dysfunction in L02 cells and zebrafish model. JOURNAL OF ETHNOPHARMACOLOGY 2022; 285:114873. [PMID: 34848360 DOI: 10.1016/j.jep.2021.114873] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 06/13/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Traditional Chinese medicine considers that the etiology and pathogenesis of non-alcoholic fatty liver disease (NAFLD) are related to liver depression and qi stagnation. Saffron and its active ingredient, crocetin (CCT), are used for the treatment of metabolic diseases owing to their "Liver deobstruent" and "Liver tonic" effects. However, the effect of CCT on NAFLD has not been fully elucidated. In the present study, the effect and potential molecular mechanism of CCT were explored in both in vivo and in vitro models of NAFLD. MATERIALS AND METHODS CCT was isolated from saffron and purity and structure characterization were performed using HPLC, MS, 1H-NMR, and 13C-NMR. The effect of CCT on the viability of L02 cells and its maximum tolerable concentration (MTC) in zebrafish were investigated. Free fatty acids (FFA) and thioacetamide (TAA) were used to induce lipid accumulation in L02 cells and steatosis in zebrafish, respectively. The effects of CCT on indexes related to lipid metabolism, oxidative stress, and mitochondrial function in NAFLD models were explored using biochemical assay kits, Western blot analysis, Reverse Transcription-Polymerase Chain Reaction (RT-PCR), histopathology analysis, and determination of mitochondrial membrane potential (ΔΨm). Morphological analysis of mitochondria was performed using transmission electron microscopy (TEM). RESULTS The levels of triglyceride (TG), total cholesterol (TC), malondialdehyde (MDA), and alanine/aspartate aminotransferases (ALT/AST) activities in FFA treated L02 cells were significantly reduced after CCT treatment. CCT treatment significantly increased ATP concentration, ΔΨm, and activities of superoxide dismutase (SOD), catalase (CAT), and cytochrome c oxidase (COX IV) in FFA treated L02 cells. TEM images showed restoration of mitochondrial morphology. CCT decreased ATP concentration and upregulated expression of B-cell lymphoma-2 (Bcl-2) and COX IV, whereas, CCT downregulated expression of BCL2-Associated X (Bax) and cleaved caspase-3 in TAA treated zebrafish. These findings indicated that mitochondrial dysfunction was alleviated after CCT treatment. Oil Red O staining of L02 cells and zebrafish showed that CCT treatment reversed the accumulation of lipid droplets. CONCLUSION In summary, CCT treatment effectively alleviated the symptoms of NAFLD and restored mitochondrial function in L02 cells and zebrafish NAFLD model.
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Affiliation(s)
- Zijin Xu
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Susu Lin
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Zheren Tong
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Suhong Chen
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Yifeng Cao
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Qiaoqiao Li
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Yuli Jiang
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China
| | - Weijie Cai
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang University of Technology, Hangzhou, Zhejiang, 310014, People's Republic of China
| | - Yingpeng Tong
- School of Life Sciences, Taizhou University, Taizhou, 318000, People's Republic of China
| | - Bathaie S Zahra
- Department of Clinical Biochemistry, Faculty of Medical Sciences, Tarbiat Modares University, P.O. Box. 14115-133, Tehran, Islamic Republic of Iran
| | - Ping Wang
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, People's Republic of China.
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11
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Vera DB, Fredes AN, Garrido MP, Romero C. Role of Mitochondria in Interplay between NGF/TRKA, miR-145 and Possible Therapeutic Strategies for Epithelial Ovarian Cancer. LIFE (BASEL, SWITZERLAND) 2021; 12:life12010008. [PMID: 35054401 PMCID: PMC8779980 DOI: 10.3390/life12010008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/24/2021] [Accepted: 11/29/2021] [Indexed: 12/20/2022]
Abstract
Ovarian cancer is the most lethal gynecological neoplasm, and epithelial ovarian cancer (EOC) accounts for 90% of ovarian malignancies. The 5-year survival is less than 45%, and, unlike other types of cancer, the proportion of women who die from this disease has not improved in recent decades. Nerve growth factor (NGF) and tropomyosin kinase A (TRKA), its high-affinity receptor, play a crucial role in pathogenesis through cell proliferation, angiogenesis, invasion, and migration. NGF/TRKA increase their expression during the progression of EOC by upregulation of oncogenic proteins as vascular endothelial growth factor (VEGF) and c-Myc. Otherwise, the expression of most oncoproteins is regulated by microRNAs (miRs). Our laboratory group reported that the tumoral effect of NGF/TRKA depends on the regulation of miR-145 levels in EOC. Currently, mitochondria have been proposed as new therapeutic targets to activate the apoptotic pathway in the cancer cell. The mitochondria are involved in a myriad of functions as energy production, redox control, homeostasis of Ca+2, and cell death. We demonstrated that NGF stimulation produces an augment in the Bcl-2/BAX ratio, which supports the anti-apoptotic effects of NGF in EOC cells. The review aimed to discuss the role of mitochondria in the interplay between NGF/TRKA and miR-145 and possible therapeutic strategies that may decrease mortality due to EOC.
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Affiliation(s)
- Daniela B. Vera
- Laboratory of Endocrinology and Reproductive Biology, Clinical Hospital University of Chile, Santiago 8380456, Chile; (D.B.V.); (A.N.F.)
| | - Allison N. Fredes
- Laboratory of Endocrinology and Reproductive Biology, Clinical Hospital University of Chile, Santiago 8380456, Chile; (D.B.V.); (A.N.F.)
| | - Maritza P. Garrido
- Laboratory of Endocrinology and Reproductive Biology, Clinical Hospital University of Chile, Santiago 8380456, Chile; (D.B.V.); (A.N.F.)
- Obstetrics and Gynecology Departament, Faculty of Medicine, University of Chile, Santiago 8380453, Chile
- Correspondence: (M.P.G.); (C.R.)
| | - Carmen Romero
- Laboratory of Endocrinology and Reproductive Biology, Clinical Hospital University of Chile, Santiago 8380456, Chile; (D.B.V.); (A.N.F.)
- Obstetrics and Gynecology Departament, Faculty of Medicine, University of Chile, Santiago 8380453, Chile
- Correspondence: (M.P.G.); (C.R.)
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12
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Rausser S, Trumpff C, McGill MA, Junker A, Wang W, Ho SH, Mitchell A, Karan KR, Monk C, Segerstrom SC, Reed RG, Picard M. Mitochondrial phenotypes in purified human immune cell subtypes and cell mixtures. eLife 2021; 10:70899. [PMID: 34698636 PMCID: PMC8612706 DOI: 10.7554/elife.70899] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 10/26/2021] [Indexed: 12/20/2022] Open
Abstract
Using a high-throughput mitochondrial phenotyping platform to quantify multiple mitochondrial features among molecularly defined immune cell subtypes, we quantify the natural variation in mitochondrial DNA copy number (mtDNAcn), citrate synthase, and respiratory chain enzymatic activities in human neutrophils, monocytes, B cells, and naïve and memory T lymphocyte subtypes. In mixed peripheral blood mononuclear cells (PBMCs) from the same individuals, we show to what extent mitochondrial measures are confounded by both cell type distributions and contaminating platelets. Cell subtype-specific measures among women and men spanning four decades of life indicate potential age- and sex-related differences, including an age-related elevation in mtDNAcn, which are masked or blunted in mixed PBMCs. Finally, a proof-of-concept, repeated-measures study in a single individual validates cell type differences and also reveals week-to-week changes in mitochondrial activities. Larger studies are required to validate and mechanistically extend these findings. These mitochondrial phenotyping data build upon established immunometabolic differences among leukocyte subpopulations, and provide foundational quantitative knowledge to develop interpretable blood-based assays of mitochondrial health.
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Affiliation(s)
- Shannon Rausser
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Caroline Trumpff
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Marlon A McGill
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Alex Junker
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Wei Wang
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, United States
| | - Siu-Hong Ho
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, United States
| | - Anika Mitchell
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Kalpita R Karan
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States
| | - Catherine Monk
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States.,Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, United States.,New York State Psychiatric Institute, New York, United States
| | | | - Rebecca G Reed
- Department of Psychology, University of Pittsburgh, Pittsburgh, United States
| | - Martin Picard
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, United States.,New York State Psychiatric Institute, New York, United States.,Department of Neurology, Merritt Center and Columbia Translational Neuroscience Initiative, Columbia University Irving Medical Center, New York, United States
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