1
|
Gadwal A, Panigrahi P, Khokhar M, Sharma V, Setia P, Vishnoi JR, Elhence P, Purohit P. A critical appraisal of the role of metabolomics in breast cancer research and diagnostics. Clin Chim Acta 2024; 561:119836. [PMID: 38944408 DOI: 10.1016/j.cca.2024.119836] [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: 03/30/2024] [Revised: 06/24/2024] [Accepted: 06/24/2024] [Indexed: 07/01/2024]
Abstract
Breast cancer (BC) remains the most prevalent cancer among women worldwide, despite significant advancements in its prevention and treatment. The escalating incidence of BC globally necessitates continued research into novel diagnostic and therapeutic strategies. Metabolomics, a burgeoning field, offers a comprehensive analysis of all metabolites within a cell, tissue, system, or organism, providing crucial insights into the dynamic changes occurring during cancer development and progression. This review focuses on the metabolic alterations associated with BC, highlighting the potential of metabolomics in identifying biomarkers for early detection, diagnosis, treatment and prognosis. Metabolomics studies have revealed distinct metabolic signatures in BC, including alterations in lipid metabolism, amino acid metabolism, and energy metabolism. These metabolic changes not only support the rapid proliferation of cancer cells but also influence the tumour microenvironment and therapeutic response. Furthermore, metabolomics holds great promise in personalized medicine, facilitating the development of tailored treatment strategies based on an individual's metabolic profile. By providing a holistic view of the metabolic changes in BC, metabolomics has the potential to revolutionize our understanding of the disease and improve patient outcomes.
Collapse
Affiliation(s)
- Ashita Gadwal
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Pragyan Panigrahi
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Manoj Khokhar
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Vaishali Sharma
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Puneet Setia
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Jeewan Ram Vishnoi
- Department of Oncosurgery, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Poonam Elhence
- Department of Pathology, All India Institute of Medical Sciences, Jodhpur Rajasthan, 342005, India
| | - Purvi Purohit
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India.
| |
Collapse
|
2
|
Zhang N, Huang Y, Wang G, Xiang Y, Jing Z, Zeng J, Yu F, Pan X, Zhou W, Zeng X. Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer. Breast Cancer Res 2024; 26:64. [PMID: 38610016 PMCID: PMC11010353 DOI: 10.1186/s13058-024-01813-w] [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: 06/02/2023] [Accepted: 03/20/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre‑therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.
Collapse
Affiliation(s)
- Ningning Zhang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Yuxin Huang
- Department of Breast Cancer Center, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China
| | - Guanwen Wang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Yimei Xiang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Zhouhong Jing
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Junjie Zeng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Feng Yu
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xianjun Pan
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Wenqi Zhou
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiaohua Zeng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.
- Department of Breast Cancer Center, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China.
- Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, China.
| |
Collapse
|
3
|
Mehrotra S, Sharma S, Pandey RK. A journey from omics to clinicomics in solid cancers: Success stories and challenges. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:89-139. [PMID: 38448145 DOI: 10.1016/bs.apcsb.2023.11.008] [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: 03/08/2024]
Abstract
The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading cause of death worldwide, responsible for one in six deaths and hence imposes a significant burden on global healthcare systems. High-throughput omics technologies combined with advanced imaging tools, have revolutionized our ability to interrogate the molecular landscape of tumors and has provided unprecedented understanding of the disease. Yet, there is a gap between basic research discoveries and their translation into clinically meaningful therapies for improving patient care. To bridge this gap, there is a need to analyse the vast amounts of high dimensional datasets from multi-omics platforms. The integration of multi-omics data with clinical information like patient history, histological examination and imaging has led to the novel concept of clinicomics and may expedite the bench-to-bedside transition in cancer. The journey from omics to clinicomics has gained momentum with development of radiomics which involves extracting quantitative features from medical imaging data with the help of deep learning and artificial intelligence (AI) tools. These features capture detailed information about the tumor's shape, texture, intensity, and spatial distribution. Together, the related fields of multiomics, translational bioinformatics, radiomics and clinicomics may provide evidence-based recommendations tailored to the individual cancer patient's molecular profile and clinical characteristics. In this chapter, we summarize multiomics studies in solid cancers with a specific focus on breast cancer. We also review machine learning and AI based algorithms and their use in cancer diagnosis, subtyping, prognosis and predicting treatment resistance and relapse.
Collapse
|
4
|
Banerjee S, Hatimuria M, Sarkar K, Das J, Pabbathi A, Sil PC. Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer. Chem Res Toxicol 2024; 37:137-180. [PMID: 38011513 DOI: 10.1021/acs.chemrestox.3c00223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".
Collapse
Affiliation(s)
- Subhrajit Banerjee
- Department of Physiology, Surendranath College, University of Calcutta, Kolkata 700009, India
- Department of Microbiology, St. Xavier's College, Kolkata 700016, India
| | - Madushmita Hatimuria
- Department of Industrial Chemistry, School of Physical Sciences, Mizoram University, Aizawl 796004, Mizoram India
| | - Kasturi Sarkar
- Department of Microbiology, St. Xavier's College, Kolkata 700016, India
| | - Joydeep Das
- Department of Chemistry, School of Physical Sciences, Mizoram University, Aizawl 796004, Mizoram, India
| | - Ashok Pabbathi
- Department of Industrial Chemistry, School of Physical Sciences, Mizoram University, Aizawl 796004, Mizoram India
| | - Parames C Sil
- Department of Molecular Medicine Bose Institute, Kolkata 700054, India
| |
Collapse
|
5
|
Liu Q, Yan X, Li R, Yuan Y, Wang J, Zhao Y, Fu J, Su J. Polyamine Signal through HCC Microenvironment: A Key Regulator of Mitochondrial Preservation and Turnover in TAMs. Int J Mol Sci 2024; 25:996. [PMID: 38256070 PMCID: PMC10816144 DOI: 10.3390/ijms25020996] [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: 12/06/2023] [Revised: 01/06/2024] [Accepted: 01/11/2024] [Indexed: 01/24/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer, and, with increasing research on the tumor immune microenvironment (TIME), the immunosuppressive micro-environment of HCC hampers further application of immunotherapy, even though immunotherapy can provide survival benefits to patients with advanced liver cancer. Current studies suggest that polyamine metabolism is not only a key metabolic pathway for the formation of immunosuppressive phenotypes in tumor-associated macrophages (TAMs), but it is also profoundly involved in mitochondrial quality control signaling and the energy metabolism regulation process, so it is particularly important to further investigate the role of polyamine metabolism in the tumor microenvironment (TME). In this review, by summarizing the current research progress of key enzymes and substrates of the polyamine metabolic pathway in regulating TAMs and T cells, we propose that polyamine biosynthesis can intervene in the process of mitochondrial energy metabolism by affecting mitochondrial autophagy, which, in turn, regulates macrophage polarization and T cell differentiation. Polyamine metabolism may be a key target for the interactive dialog between HCC cells and immune cells such as TAMs, so interfering with polyamine metabolism may become an important entry point to break intercellular communication, providing new research space for developing polyamine metabolism-based therapy for HCC.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | - Jing Su
- Key Laboratory of Pathobiology, Department of Pathophysiology, Ministry of Education, College of Basical Medical Sciences, Jilin University, 126 Xinmin Street, Changchun 130012, China; (Q.L.); (X.Y.); (R.L.); (Y.Y.); (J.W.); (Y.Z.); (J.F.)
| |
Collapse
|
6
|
Jian J, He D, Gao S, Tao X, Dong X. Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication. Pharmaceuticals (Basel) 2023; 16:1568. [PMID: 38004434 PMCID: PMC10675232 DOI: 10.3390/ph16111568] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 10/19/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023] Open
Abstract
Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.
Collapse
Affiliation(s)
- Jingai Jian
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Donglin He
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Songyan Gao
- Institute of Translational Medicine, Shanghai University, Shanghai 200444, China;
| | - Xia Tao
- Department of Pharmacy, Changzheng Hospital, Second Military Medical University, Shanghai 200003, China
| | - Xin Dong
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| |
Collapse
|
7
|
Ye C, Dong C, Lin Y, Shi H, Zhou W. Interplay between the Human Microbiome and Biliary Tract Cancer: Implications for Pathogenesis and Therapy. Microorganisms 2023; 11:2598. [PMID: 37894256 PMCID: PMC10608879 DOI: 10.3390/microorganisms11102598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 10/29/2023] Open
Abstract
Biliary tract cancer, encompassing intrahepatic and extrahepatic cholangiocarcinoma as well as gallbladder carcinoma, stands as a prevalent malignancy characterized by escalating incidence rates and unfavorable prognoses. The onset of cholangiocarcinoma involves a multitude of risk factors and could potentially be influenced by microbial exposure. The human microbiome, encompassing the entirety of human microbial genetic information, assumes a pivotal role in regulating key aspects such as host digestion, absorption, immune responses, and metabolism. The widespread application of next-generation sequencing technology has notably propelled investigations into the intricate relationship between the microbiome and diseases. An accumulating body of evidence strongly suggests a profound interconnection between biliary tract cancer and the human microbiome. This article critically appraises the existing evidence pertaining to the microbiome milieu within patients afflicted by biliary tract cancer. Furthermore, it delves into potential mechanisms through which dysregulation of the human microbiome could contribute to the advancement of biliary tract cancer. Additionally, the article expounds on its role in the context of chemotherapy and immunotherapy for biliary tract cancer.
Collapse
Affiliation(s)
- Cheng Ye
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; (C.Y.); (C.D.); (Y.L.); (H.S.)
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Chunlu Dong
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; (C.Y.); (C.D.); (Y.L.); (H.S.)
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Yanyan Lin
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; (C.Y.); (C.D.); (Y.L.); (H.S.)
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Huaqing Shi
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; (C.Y.); (C.D.); (Y.L.); (H.S.)
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Wence Zhou
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; (C.Y.); (C.D.); (Y.L.); (H.S.)
- Department of General Surgery, The Second Hospital of Lanzhou University, Lanzhou 730000, China
| |
Collapse
|
8
|
Catanzaro E, Gringeri E, Burra P, Gambato M. Primary Sclerosing Cholangitis-Associated Cholangiocarcinoma: From Pathogenesis to Diagnostic and Surveillance Strategies. Cancers (Basel) 2023; 15:4947. [PMID: 37894314 PMCID: PMC10604939 DOI: 10.3390/cancers15204947] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Cholangiocarcinoma (CCA) is the most common malignancy in patients with primary sclerosing cholangitis (PSC), accounting for 2-8% of cases and being the leading cause of death in these patients. The majority of PSC-associated CCAs (PSC-CCA) develop within the first few years after PSC diagnosis. Older age and male sex, as well as concomitant inflammatory bowel disease (IBD) or high-grade biliary stenosis, are some of the most relevant risk factors. A complex combination of molecular mechanisms involving inflammatory pathways, direct cytopathic damage, and epigenetic and genetic alterations are involved in cholangiocytes carcinogenesis. The insidious clinical presentation makes early detection difficult, and the integration of biochemical, radiological, and histological features does not always lead to a definitive diagnosis of PSC-CCA. Surveillance is mandatory, but current guideline strategies failed to improve early detection and consequently a higher patient survival rate. MicroRNAs (miRNAs), gene methylation, proteomic and metabolomic profile, and extracellular vesicle components are some of the novel biomarkers recently applied in PSC-CCA detection with promising results. The integration of these new molecular approaches in PSC diagnosis and monitoring could contribute to new diagnostic and surveillance strategies.
Collapse
Affiliation(s)
- Elisa Catanzaro
- Gastroenterology, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
- Multivisceral Transplant Unit, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
| | - Enrico Gringeri
- Hepatobiliary Surgery and Liver Transplantation Center, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
| | - Patrizia Burra
- Gastroenterology, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
- Multivisceral Transplant Unit, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
| | - Martina Gambato
- Gastroenterology, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
- Multivisceral Transplant Unit, Department of Surgery, Oncology, and Gastroenterology, Padova University Hospital, 35128 Padova, Italy
| |
Collapse
|
9
|
Corona G, Di Gregorio E, Buonadonna A, Lombardi D, Scalone S, Steffan A, Miolo G. Pharmacometabolomics of trabectedin in metastatic soft tissue sarcoma patients. Front Pharmacol 2023; 14:1212634. [PMID: 37637412 PMCID: PMC10450632 DOI: 10.3389/fphar.2023.1212634] [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: 04/26/2023] [Accepted: 07/20/2023] [Indexed: 08/29/2023] Open
Abstract
Objective: Trabectedin is an anti-cancer drug commonly used for the treatment of patients with metastatic soft tissue sarcoma (mSTS). Despite its recognized efficacy, significant variability in pharmacological response has been observed among mSTS patients. To address this issue, this pharmacometabolomics study aimed to identify pre-dose plasma metabolomics signatures that can explain individual variations in trabectedin pharmacokinetics and overall clinical response to treatment. Methods: In this study, 40 mSTS patients treated with trabectedin administered by 24 h-intravenous infusion at a dose of 1.5 mg/m2 were enrolled. The patients' baseline plasma metabolomics profiles, which included derivatives of amino acids and bile acids, were analyzed using multiple reaction monitoring LC-MS/MS together with their pharmacokinetics profile of trabectedin. Multivariate Partial least squares regression and univariate statistical analyses were utilized to identify correlations between baseline metabolite concentrations and trabectedin pharmacokinetics, while Partial Least Squares-Discriminant Analysis was employed to evaluate associations with clinical response. Results: The multiple regression model, derived from the correlation between the AUC of trabectedin and pre-dose metabolomics, exhibited the best performance by incorporating cystathionine, hemoglobin, taurocholic acid, citrulline, and the phenylalanine/tyrosine ratio. This model demonstrated a bias of 4.6% and a precision of 17.4% in predicting drug AUC, effectively accounting for up to 70% of the inter-individual pharmacokinetic variability. Through the use of Partial least squares-Discriminant Analysis, cystathionine and hemoglobin were identified as specific metabolic signatures that effectively distinguish patients with stable disease from those with progressive disease. Conclusions: The findings from this study provide compelling evidence to support the utilization of pre-dose metabolomics in uncovering the underlying causes of pharmacokinetic variability of trabectedin, as well as facilitating the identification of patients who are most likely to benefit from this treatment.
Collapse
Affiliation(s)
- Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Emanuela Di Gregorio
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Angela Buonadonna
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Davide Lombardi
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Simona Scalone
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Gianmaria Miolo
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| |
Collapse
|
10
|
Fu J, Zhu F, Xu CJ, Li Y. Metabolomics meets systems immunology. EMBO Rep 2023; 24:e55747. [PMID: 36916532 PMCID: PMC10074123 DOI: 10.15252/embr.202255747] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/24/2022] [Accepted: 02/24/2023] [Indexed: 03/16/2023] Open
Abstract
Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.
Collapse
Affiliation(s)
- Jianbo Fu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| |
Collapse
|
11
|
Kannampuzha S, Mukherjee AG, Wanjari UR, Gopalakrishnan AV, Murali R, Namachivayam A, Renu K, Dey A, Vellingiri B, Madhyastha H, Ganesan R. A Systematic Role of Metabolomics, Metabolic Pathways, and Chemical Metabolism in Lung Cancer. Vaccines (Basel) 2023; 11:vaccines11020381. [PMID: 36851259 PMCID: PMC9960365 DOI: 10.3390/vaccines11020381] [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: 01/10/2023] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
Lung cancer (LC) is considered as one of the leading causes of cancer-associated mortalities. Cancer cells' reprogrammed metabolism results in changes in metabolite concentrations, which can be utilized to identify a distinct metabolic pattern or fingerprint for cancer detection or diagnosis. By detecting different metabolic variations in the expression levels of LC patients, this will help and enhance early diagnosis methods as well as new treatment strategies. The majority of patients are identified at advanced stages after undergoing a number of surgical procedures or diagnostic testing, including the invasive procedures. This could be overcome by understanding the mechanism and function of differently regulated metabolites. Significant variations in the metabolites present in the different samples can be analyzed and used as early biomarkers. They could also be used to analyze the specific progression and type as well as stages of cancer type making it easier for the treatment process. The main aim of this review article is to focus on rewired metabolic pathways and the associated metabolite alterations that can be used as diagnostic and therapeutic targets in lung cancer diagnosis as well as treatment strategies.
Collapse
Affiliation(s)
- Sandra Kannampuzha
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Anirban Goutam Mukherjee
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Uddesh Ramesh Wanjari
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Abilash Valsala Gopalakrishnan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
- Correspondence: (A.V.G.); (R.G.)
| | - Reshma Murali
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Arunraj Namachivayam
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Kaviyarasi Renu
- Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College & Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, India
| | - Abhijit Dey
- Department of Life Sciences, Presidency University, Kolkata 700073, India
| | - Balachandar Vellingiri
- Stem Cell and Regenerative Medicine/Translational Research, Department of Zoology, School of Basic Sciences, Central University of Punjab (CUPB), Bathinda 151401, India
| | - Harishkumar Madhyastha
- Department of Cardiovascular Physiology, Faculty of Medicine, University of Miyazaki, Miyazaki 889-1692, Japan
| | - Raja Ganesan
- Institute for Liver and Digestive Diseases, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea
- Correspondence: (A.V.G.); (R.G.)
| |
Collapse
|
12
|
Corsetto PA, Zava S, Rizzo AM, Colombo I. The Critical Impact of Sphingolipid Metabolism in Breast Cancer Progression and Drug Response. Int J Mol Sci 2023; 24:ijms24032107. [PMID: 36768427 PMCID: PMC9916652 DOI: 10.3390/ijms24032107] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/11/2023] [Accepted: 01/17/2023] [Indexed: 01/25/2023] Open
Abstract
Breast cancer is the second leading cause of cancer-related death in women in the world, and its management includes a combination of surgery, radiation therapy, chemotherapy, and immunotherapy, whose effectiveness depends largely, but not exclusively, on the molecular subtype (Luminal A, Luminal B, HER2+ and Triple Negative). All breast cancer subtypes are accompanied by peculiar and substantial changes in sphingolipid metabolism. Alterations in sphingolipid metabolite levels, such as ceramides, dihydroceramide, sphingosine, sphingosine-1-phosphate, and sphingomyelin, as well as in their biosynthetic and catabolic enzymatic pathways, have emerged as molecular mechanisms by which breast cancer cells grow, respond to or escape therapeutic interventions and could take on diagnostic and prognostic value. In this review, we summarize the current landscape around two main themes: 1. sphingolipid metabolites, enzymes and transport proteins that have been found dysregulated in human breast cancer cells and/or tissues; 2. sphingolipid-driven mechanisms that allow breast cancer cells to respond to or evade therapies. Having a complete picture of the impact of the sphingolipid metabolism in the development and progression of breast cancer may provide an effective means to improve and personalize treatments and reduce associated drug resistance.
Collapse
|
13
|
Bafiti V, Katsila T. Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:542-551. [PMID: 36149303 DOI: 10.1089/omi.2022.0097] [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: 06/16/2023]
Abstract
Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.
Collapse
Affiliation(s)
- Vivi Bafiti
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
| | - Theodora Katsila
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
| |
Collapse
|
14
|
Raggi C, Taddei ML, Rae C, Braconi C, Marra F. Metabolic reprogramming in cholangiocarcinoma. J Hepatol 2022; 77:849-864. [PMID: 35594992 DOI: 10.1016/j.jhep.2022.04.038] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/16/2022] [Accepted: 04/28/2022] [Indexed: 12/25/2022]
Abstract
Metabolic reprogramming is a hallmark of cancer and allows tumour cells to meet the increased energy demands required for rapid proliferation, invasion, and metastasis. Indeed, many tumour cells acquire distinctive metabolic and bioenergetic features that enable them to survive in resource-limited conditions, mainly by harnessing alternative nutrients. Several recent studies have explored the metabolic plasticity of cancer cells with the aim of identifying new druggable targets, while therapeutic strategies to limit the access to nutrients have been successfully applied to the treatment of some tumours. Cholangiocarcinoma (CCA), a highly heterogeneous tumour, is the second most common form of primary liver cancer. It is characterised by resistance to chemotherapy and poor prognosis, with 5-year survival rates of below 20%. Deregulation of metabolic pathways have been described during the onset and progression of CCA. Increased aerobic glycolysis and glutamine anaplerosis provide CCA cells with the ability to generate biosynthetic intermediates. Other metabolic alterations involving carbohydrates, amino acids and lipids have been shown to sustain cancer cell growth and dissemination. In this review, we discuss the complex metabolic rewiring that occurs during CCA development and leads to unique nutrient addiction. The possible role of therapeutic interventions based on metabolic changes is also thoroughly discussed.
Collapse
Affiliation(s)
- Chiara Raggi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
| | - Maria Letizia Taddei
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Colin Rae
- Institute of Cancer Sciences, The University of Glasgow, Glasgow, United Kingdom
| | - Chiara Braconi
- Institute of Cancer Sciences, The University of Glasgow, Glasgow, United Kingdom; Beatson West of Scotland Cancer Centre, Glasgow, United Kingdom
| | - Fabio Marra
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
| |
Collapse
|
15
|
Díaz C, González-Olmedo C, Díaz-Beltrán L, Camacho J, Mena García P, Martín-Blázquez A, Fernández-Navarro M, Ortega-Granados AL, Gálvez-Montosa F, Marchal JA, Vicente F, Pérez Del Palacio J, Sánchez-Rovira P. Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach. Mol Oncol 2022; 16:2658-2671. [PMID: 35338693 PMCID: PMC9297806 DOI: 10.1002/1878-0261.13216] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 02/17/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
Neoadjuvant chemotherapy (NACT) outcomes vary according to breast cancer (BC) subtype. Since pathologic complete response is one of the most important target endpoints of NACT, further investigation of NACT outcomes in BC is crucial. Thus, identifying sensitive and specific predictors of treatment response for each phenotype would enable early detection of chemoresistance and residual disease, decreasing exposures to ineffective therapies and enhancing overall survival rates. We used liquid chromatography−high‐resolution mass spectrometry (LC‐HRMS)‐based untargeted metabolomics to detect molecular changes in plasma of three different BC subtypes following the same NACT regimen, with the aim of searching for potential predictors of response. The metabolomics data set was analyzed by combining univariate and multivariate statistical strategies. By using ANOVA–simultaneous component analysis (ASCA), we were able to determine the prognostic value of potential biomarker candidates of response to NACT in the triple‐negative (TN) subtype. Higher concentrations of docosahexaenoic acid and secondary bile acids were found at basal and presurgery samples, respectively, in the responders group. In addition, the glycohyocholic and glycodeoxycholic acids were able to classify TN patients according to response to treatment and overall survival with an area under the curve model > 0.77. In relation to luminal B (LB) and HER2+ subjects, it should be noted that significant differences were related to time and individual factors. Specifically, tryptophan was identified to be decreased over time in HER2+ patients, whereas LysoPE (22:6) appeared to be increased, but could not be associated with response to NACT. Therefore, the combination of untargeted‐based metabolomics along with longitudinal statistical approaches may represent a very useful tool for the improvement of treatment and in administering a more personalized BC follow‐up in the clinical practice.
Collapse
Affiliation(s)
- Caridad Díaz
- Fundación MEDINA; Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain
| | | | | | - José Camacho
- Department of Signal Theory, Networking and Communications, University of Granada, 18071, Granada, Spain
| | - Patricia Mena García
- Fundación MEDINA; Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain
| | - Ariadna Martín-Blázquez
- Fundación MEDINA; Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain
| | | | | | | | - Juan Antonio Marchal
- Biopathology and Regenerative Medicine Institute (IBIMER), Centre for Biomedical Research, University of Granada, Granada, E-18100, Spain.,Instituto de Investigación Biosanitaria ibs.GRANADA, University of Granada, 18100, Granada, Spain.,Department of Human Anatomy and Embryology, Faculty of Medicine, University of Granada, Granada, E-18012, Spain.,Excellence Research Unit "Modeling Nature" (MNat), University of Granada, Spain
| | - Francisca Vicente
- Fundación MEDINA; Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain
| | - José Pérez Del Palacio
- Fundación MEDINA; Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain
| | | |
Collapse
|
16
|
Wajid S, Samad FA, Syed AS, Kazi F. Ki-67 and Its Relation With Complete Pathological Response in Patients With Breast Cancer. Cureus 2021; 13:e16788. [PMID: 34513395 PMCID: PMC8412210 DOI: 10.7759/cureus.16788] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/31/2021] [Indexed: 11/17/2022] Open
Abstract
Introduction Ki-67 is a nuclear antigen present in the synthesis phase of the cell cycle. Studies have shown that a high value of Ki-67 results in greater response to chemotherapy with higher incidence of complete pathological response, which ultimately results in improved overall survival. Methods and materials The objective of the study was to determine the frequency of high Ki-67 levels in breast cancer patients and to find the correlation of complete pathological response in breast cancer with Ki-67 levels. It is a descriptive case series with a correlational study design done at Fauji Foundation Hospital Rawalpindi. Eighty patients with locally advanced breast cancer who underwent neoadjuvant chemotherapy followed by surgery were recruited. Their Ki-67 levels were determined on trucut biopsy. Pathological response in the post-op sample was correlated with Ki-67 levels. Results The results showed 27 (33%) patients out of the 80 had high Ki-67 values. Among them 17 (63%) had complete pathological response, seven (26%) showed partial pathological response whereas three (11%) had disease progression. In contrast, out of the 53 patients having low Ki-67 values, only nine (17%) had complete pathological response, 31 (58%) showed partial pathological response and 13 (25%) had progressive disease. A Chi-square test was applied which showed significant correlation between Ki-67 and complete pathological response, with a p value of 0.00018. Conclusion Therefore high Ki-67 values in patients with breast cancer correlated well with attainment of complete pathological response. We can incorporate Ki-67 in the initial clinical assessment of breast cancer patients to help predict effectiveness as well as response to chemotherapy.
Collapse
Affiliation(s)
- Sana Wajid
- Oncology, Fauji Foundation Hospital, Rawalpindi, PAK
| | | | - Abdus S Syed
- Department of Radiation Oncology, Combined Military Hospital, Rawalpindi, PAK
| | - Faiza Kazi
- Pathology, Fauji Foundation Hospital, Rawalpindi, PAK
| |
Collapse
|
17
|
Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments. Cancers (Basel) 2021; 13:cancers13184544. [PMID: 34572770 PMCID: PMC8470181 DOI: 10.3390/cancers13184544] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/01/2021] [Accepted: 09/08/2021] [Indexed: 12/15/2022] Open
Abstract
Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.
Collapse
|
18
|
Pan X, Chen W, Nie M, Liu Y, Xiao Z, Zhang Y, Zhang W, Zou X. A Serum Metabolomic Study Reveals Changes in Metabolites During the Treatment of Lung Cancer-Bearing Mice with Anlotinib. Cancer Manag Res 2021; 13:6055-6063. [PMID: 34377024 PMCID: PMC8349534 DOI: 10.2147/cmar.s300897] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 07/23/2021] [Indexed: 12/24/2022] Open
Abstract
Background Anlotinib is a vascular endothelial growth factor receptor tyrosine kinase inhibitor recommended for the treatment of advanced lung cancer patients after at least two previous systemic chemotherapies. Currently, many patients with lung cancer do not respond well to anlotinib treatment. Therefore, the aim of this metabolomic study was to determine the internal mechanism of anlotinib action at the molecular level and to identify the potential biomarkers and pathways associated with the therapeutic effects of anlotinib. Methods A total of 20 male nude mice were randomly divided into 2 groups and treated with anlotinib or physiological saline. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was performed to analyze the serum samples and determine the differential metabolites and pathways between anlotinib and control groups. Results We observed significant differences between the anlotinib and control groups, and 13 endogenous differential metabolites and 5 potential metabolic pathways were identified. Glyoxylate and dicarboxylate metabolism, tryptophan metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism and valine, leucine and isoleucine biosynthesis were the most important pathways regulated by anlotinib in vivo. Notably, these 5 differential pathways were highly associated with the TCA cycle, which is important in the proliferation and apoptosis of cancer cells. Conclusion This serum metabolomic study revealed distinct metabolic profiles in lung cancer-bearing mice treated with anlotinib and identified differential metabolites and pathways between the anlotinib and control groups, which may provide new ideas for the clinical application of anlotinib.
Collapse
Affiliation(s)
- Xiaoting Pan
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Wenhao Chen
- No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China.,Jiangsu Cancer Hospital, Nanjing, Jiangsu, 210009, People's Republic of China
| | - Mengjun Nie
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Yuanjie Liu
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Zuopeng Xiao
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Ying Zhang
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China.,No.1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, People's Republic of China
| | - Wei Zhang
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China
| | - Xi Zou
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu, 210029, People's Republic of China
| |
Collapse
|
19
|
Pietkiewicz D, Klupczynska-Gabryszak A, Plewa S, Misiura M, Horala A, Miltyk W, Nowak-Markwitz E, Kokot ZJ, Matysiak J. Free Amino Acid Alterations in Patients with Gynecological and Breast Cancer: A Review. Pharmaceuticals (Basel) 2021; 14:ph14080731. [PMID: 34451829 PMCID: PMC8400482 DOI: 10.3390/ph14080731] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/15/2021] [Accepted: 07/21/2021] [Indexed: 02/06/2023] Open
Abstract
Gynecological and breast cancers still remain a significant health problem worldwide. Diagnostic methods are not sensitive and specific enough to detect the disease at an early stage. During carcinogenesis and tumor progression, the cellular need for DNA and protein synthesis increases leading to changes in the levels of amino acids. An important role of amino acids in many biological pathways, including biosynthesis of proteins, nucleic acids, enzymes, etc., which serve as an energy source and maintain redox balance, has been highlighted in many research articles. The aim of this review is a detailed analysis of the literature on metabolomic studies of gynecology and breast cancers with particular emphasis on alterations in free amino acid profiles. The work includes a brief overview of the metabolomic methodology and types of biological samples used in the studies. Special attention was paid to the possible role of selected amino acids in the carcinogenesis, especially proline and amino acids related to its metabolism. There is a clear need for further research and multiple external validation studies to establish the role of amino acid profiling in diagnosing gynecological and breast cancers.
Collapse
Affiliation(s)
- Dagmara Pietkiewicz
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Agnieszka Klupczynska-Gabryszak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
| | - Magdalena Misiura
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland; (M.M.); (W.M.)
| | - Agnieszka Horala
- Gynecologic Oncology Department, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (A.H.); (E.N.-M.)
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland; (M.M.); (W.M.)
| | - Ewa Nowak-Markwitz
- Gynecologic Oncology Department, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (A.H.); (E.N.-M.)
| | - Zenon J. Kokot
- Faculty of Health Sciences, Calisia University, 62-800 Kalisz, Poland;
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland; (D.P.); (A.K.-G.); (S.P.)
- Correspondence:
| |
Collapse
|
20
|
Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer. Toxins (Basel) 2021; 13:toxins13070461. [PMID: 34209281 PMCID: PMC8309959 DOI: 10.3390/toxins13070461] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 06/21/2021] [Accepted: 06/29/2021] [Indexed: 02/06/2023] Open
Abstract
Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.
Collapse
|
21
|
Vignoli A, Risi E, McCartney A, Migliaccio I, Moretti E, Malorni L, Luchinat C, Biganzoli L, Tenori L. Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer. Int J Mol Sci 2021; 22:ijms22094687. [PMID: 33925233 PMCID: PMC8124948 DOI: 10.3390/ijms22094687] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/22/2022] Open
Abstract
Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).
Collapse
Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Emanuela Risi
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Amelia McCartney
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
- School of Clinical Sciences, Monash University, Melbourne 3800, Australia
| | - Ilenia Migliaccio
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Erica Moretti
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Luca Malorni
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
- Correspondence: ; Tel.: +39-055-457-4296
| | - Laura Biganzoli
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
| |
Collapse
|
22
|
Fu J, Zhang Y, Liu J, Lian X, Tang J, Zhu F. Pharmacometabonomics: data processing and statistical analysis. Brief Bioinform 2021; 22:6236068. [PMID: 33866355 DOI: 10.1093/bib/bbab138] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 02/09/2021] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.
Collapse
Affiliation(s)
- Jianbo Fu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Ying Zhang
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jin Liu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Xichen Lian
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jing Tang
- Department of Bioinformatics in Chongqing Medical University, China
| | - Feng Zhu
- College of Pharmaceutical Sciences in Zhejiang University, China
| |
Collapse
|
23
|
Boguszewicz Ł, Bieleń A, Jarczewski JD, Ciszek M, Skorupa A, Składowski K, Sokół M. Molecular response to induction chemotherapy and its correlation with treatment outcome in head and neck cancer patients by means of NMR-based metabolomics. BMC Cancer 2021; 21:410. [PMID: 33858370 PMCID: PMC8048324 DOI: 10.1186/s12885-021-08137-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 04/02/2021] [Indexed: 12/16/2022] Open
Abstract
Background The aim of this prospective study is to identify the biomarkers associated with the effects of induction chemotherapy (iCHT) in terms of the favorable/weaker response to the treatment in locally advanced head and neck squamous cells carcinomas (LA-HNSCC). Methods The studied group consisted of 53 LA-HNSCC patients treated with iCHT. The treatment tolerance was measured by the Common Terminology Criteria for Adverse Events (CTCAE). The response to the treatment was evaluated by the clinical, fiberoptic and radiological examinations made before and after iCHT (the TNM Classification of Malignant Tumors was used for classifying the extent of cancer spread). Proton nuclear magnetic resonance (1H NMR) serum spectra of the samples collected before and after iCHT were acquired with a 400 MHz spectrometer and analyzed using the multivariate and univariate statistical methods. Results The molecular response to iCHT involves an increase of the serum lipids which is accompanied by the simultaneous decrease of alanine, glucose and N-acetyl-glycoprotein (NAG). Furthermore, in males, the iCHT induced changes in the lipid signals and NAG significantly correlate with the regression of the primary tumor. The OPLS-DA multivariate model identified two subgroups of the patients with a weaker metabolic and clinical response. The first one consisted of the patients with a significantly lower initial nodal stage, the second one showed no differences in the initial clinical and metabolic statuses. Conclusions The NMR-based metabolomic study of the serum spectra revealed that iCHT induces the marked changes in the LA-HNSCC patients’ metabolic profiles and makes it possible to stratify the patients according to their response to iCHT. These effects are sex dependent. Further studies on a larger scale accounting for sex and the clinical and metabolic factors are warranted. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08137-4.
Collapse
Affiliation(s)
- Łukasz Boguszewicz
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland.
| | - Agata Bieleń
- 1st Radiation and Clinical Oncology Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| | - Jarosław Dawid Jarczewski
- Radiology and Diagnostic Imaging Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| | - Mateusz Ciszek
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| | - Agnieszka Skorupa
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| | - Krzysztof Składowski
- 1st Radiation and Clinical Oncology Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| | - Maria Sokół
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Warszawa, Poland
| |
Collapse
|
24
|
Zidi O, Souai N, Raies H, Ben Ayed F, Mezlini A, Mezrioui S, Tranchida F, Sabatier JM, Mosbah A, Cherif A, Shintu L, Kouidhi S. Fecal Metabolic Profiling of Breast Cancer Patients during Neoadjuvant Chemotherapy Reveals Potential Biomarkers. Molecules 2021; 26:2266. [PMID: 33919750 PMCID: PMC8070723 DOI: 10.3390/molecules26082266] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 11/17/2022] Open
Abstract
Breast cancer (BC) is the most common form of cancer among women worldwide. Despite the huge advancements in its treatment, the exact etiology of breast cancer still remains unresolved. There is an increasing interest in the role of the gut microbiome in modulating the anti-cancer therapeutic response. It seems that alteration of the microbiome-derived metabolome potentially promotes carcinogenesis. Taken together, metabolomics has arisen as a fascinating new omics field to screen promising metabolic biomarkers. In this study, fecal metabolite profiling was performed using NMR spectroscopy, to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy (NAC) for breast cancer. Metabolic profiles of feces from patients (n = 8) following chemotherapy treatment cycles were studied. Interestingly, amino acids were found to be upregulated, while lactate and fumaric acid were downregulated in patients under the second and third cycles compared with patients before treatment. Furthermore, short-chain fatty acids (SCFAs) were significantly differentiated between the studied groups. These results strongly suggest that chemotherapy treatment plays a key role in modulating the fecal metabolomic profile of BC patients. In conclusion, we demonstrate the feasibility of identifying specific fecal metabolic profiles reflecting biochemical changes that occur during the chemotherapy treatment. These data give an interesting insight that may complement and improve clinical tools for BC monitoring.
Collapse
Affiliation(s)
- Oumaima Zidi
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Nessrine Souai
- Department of Biology, Faculty of Sciences of Tunis, Farhat Hachad Universitary Campus, University of Tunis El Manar, Rommana, Tunis 1068, Tunisia; (O.Z.); (N.S.)
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Henda Raies
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Farhat Ben Ayed
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Amel Mezlini
- Service d’Oncologie Médicale, Hôpital Salah-Azaïz, Tunis 1006, Tunisia; (H.R.); (A.M.)
| | - Sonia Mezrioui
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| | - Fabrice Tranchida
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Jean-Marc Sabatier
- Faculté de Pharmacie, Institute of NeuroPhysiopathology (INP), UMR 7051, 27, Boulevard Jean-Moulin, CEDEX, 13005 Marseille, France
| | - Amor Mosbah
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Ameur Cherif
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
| | - Laetitia Shintu
- Aix Marseille Univ, CNRS, Centrale Marseille, iSm2, 13284 Marseille, France; (F.T.); (L.S.)
| | - Soumaya Kouidhi
- Laboratory of Biotechnology and Valorisation of Bio-GeoRessources, Higher Institute of Biotechnology of Sidi Thabet, BiotechPole of Sidi Thabet, University of Manouba, Ariana 2020, Tunisia; (A.M.); (A.C.)
- Association Tunisienne de Lutte Contre le Cancer (ATCC), Tunis 1938, Tunisia; (F.B.A.); (S.M.)
| |
Collapse
|
25
|
Mussap M, Noto A, Piras C, Atzori L, Fanos V. Slotting metabolomics into routine precision medicine. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2021. [DOI: 10.1080/23808993.2021.1911639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Michele Mussap
- Department of Surgical Science, University of Cagliari, Monserrato, Italy
| | - Antonio Noto
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, Italy
| | - Cristina Piras
- Department of Surgical Science, University of Cagliari, Monserrato, Italy
- Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Luigi Atzori
- Department of Biomedical Sciences, University of Cagliari, Monserrato, Italy
| | - Vassilios Fanos
- Department of Surgical Science, University of Cagliari, Monserrato, Italy
| |
Collapse
|
26
|
Liang L, Sun F, Wang H, Hu Z. Metabolomics, metabolic flux analysis and cancer pharmacology. Pharmacol Ther 2021; 224:107827. [PMID: 33662451 DOI: 10.1016/j.pharmthera.2021.107827] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 02/19/2021] [Accepted: 02/23/2021] [Indexed: 02/07/2023]
Abstract
Metabolic reprogramming is a hallmark of cancer and increasing evidence suggests that reprogrammed cell metabolism supports tumor initiation, progression, metastasis and drug resistance. Understanding metabolic dysregulation may provide therapeutic targets and facilitate drug research and development for cancer therapy. Metabolomics enables the high-throughput characterization of a large scale of small molecule metabolites in cells, tissues and biofluids, while metabolic flux analysis (MFA) tracks dynamic metabolic activities using stable isotope tracer methods. Recent advances in metabolomics and MFA technologies make them powerful tools for metabolic profiling and characterizing metabolic activities in health and disease, especially in cancer research. In this review, we introduce recent advances in metabolomics and MFA analytical technologies, and provide the first comprehensive summary of the most commonly used isotope tracing methods. In addition, we highlight how metabolomics and MFA are applied in cancer pharmacology studies particularly for discovering targetable metabolic vulnerabilities, understanding the mechanisms of drug action and drug resistance, exploring potential strategies with dietary intervention, identifying cancer biomarkers, as well as enabling precision treatment with pharmacometabolomics.
Collapse
Affiliation(s)
- Lingfan Liang
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China
| | - Fei Sun
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China
| | - Hongbo Wang
- Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China.
| | - Zeping Hu
- School of Pharmaceutical Sciences; Tsinghua-Peking Joint Center for Life Sciences; Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing 100084, China.
| |
Collapse
|
27
|
Bar H, Bang S. A mixture model to detect edges in sparse co-expression graphs with an application for comparing breast cancer subtypes. PLoS One 2021; 16:e0246945. [PMID: 33571253 PMCID: PMC7877669 DOI: 10.1371/journal.pone.0246945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 01/28/2021] [Indexed: 11/19/2022] Open
Abstract
We develop a method to recover a gene network's structure from co-expression data, measured in terms of normalized Pearson's correlation coefficients between gene pairs. We treat these co-expression measurements as weights in the complete graph in which nodes correspond to genes. To decide which edges exist in the gene network, we fit a three-component mixture model such that the observed weights of 'null edges' follow a normal distribution with mean 0, and the non-null edges follow a mixture of two lognormal distributions, one for positively- and one for negatively-correlated pairs. We show that this so-called L2 N mixture model outperforms other methods in terms of power to detect edges, and it allows to control the false discovery rate. Importantly, our method makes no assumptions about the true network structure. We demonstrate our method, which is implemented in an R package called edgefinder, using a large dataset consisting of expression values of 12,750 genes obtained from 1,616 women. We infer the gene network structure by cancer subtype, and find insightful subtype characteristics. For example, we find thirteen pathways which are enriched in each of the cancer groups but not in the Normal group, with two of the pathways associated with autoimmune diseases and two other with graft rejection. We also find specific characteristics of different breast cancer subtypes. For example, the Luminal A network includes a single, highly connected cluster of genes, which is enriched in the human diseases category, and in the Her2 subtype network we find a distinct, and highly interconnected cluster which is uniquely enriched in drug metabolism pathways.
Collapse
Affiliation(s)
- Haim Bar
- Department of Statistics, University of Connecticut, Storrs, CT, United States of America
| | - Seojin Bang
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, United States of America
| |
Collapse
|
28
|
Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
Collapse
Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| |
Collapse
|
29
|
Monzen S, Tatara Y, Mariya Y, Chiba M, Wojcik A, Lundholm L. HER2-positive breast cancer that resists therapeutic drugs and ionizing radiation releases sphingomyelin-based molecules to circulating blood serum. Mol Clin Oncol 2020; 13:70. [PMID: 33005404 PMCID: PMC7523270 DOI: 10.3892/mco.2020.2140] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 06/16/2020] [Indexed: 12/24/2022] Open
Abstract
Breast cancer is the second most common cancer in the world based on incidence, reaching more than 2 million new cases in 2018, while continuing to increase. Invasive ductal carcinoma is the most common type of this cancer, making up approximately 70-80% of all breast cancer diagnoses. In particular, the type of breast cancer overexpressing human epidermal growth factor receptor 2 (HER2) has potential of strong proliferation, migration and invasion and early treatment is necessary. The authors identified and studied a single patient displaying complete therapeutic resistance to monoclonal anti-HER2 antibody therapy, chemotherapy and radiotherapy. A patient who exhibited resistance to postoperative adjuvant therapy after mastectomy was selected from HER2-positive breast cancer, and this patient had the grade of T4bN2aM0, Stage IIIB. The patient samples, blood serum and cancer tissue, were analyzed by metabolome and immunostaining technique, respectively. The characteristics of peripheral blood serum and solid tumor were investigated, aiming to find new serum biomarker(s) using the metabolomics technique. A correlation between the appearance of HER2-positive cancer tissue and serum concentration of the sphingomyelin family was found. In addition, HER2-positive tumor tissue in both the primary and recurrent cancer express the sphingomyelinase. These results suggest that sphingomyelins from this cancer tissue leads to therapy resistance, induction of invasion and strong proliferation.
Collapse
Affiliation(s)
- Satoru Monzen
- Department of Radiation Science, Hirosaki University Graduate School of Health Sciences, Hirosaki, Aomori 036-8564, Japan
| | - Yota Tatara
- Department of Glycotechnology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori 036-8562, Japan
| | - Yasushi Mariya
- Department of Radiology, Mutsu General Hospital, Mutsu, Aomori 035-0071, Japan
| | - Mitsuru Chiba
- Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences, Hirosaki, Aomori 036-8564, Japan
| | - Andrzej Wojcik
- Centre for Radiation Protection Research, Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, 114 18 Stockholm, Sweden
| | - Lovisa Lundholm
- Centre for Radiation Protection Research, Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, 114 18 Stockholm, Sweden
| |
Collapse
|
30
|
Lo C, Hsu YL, Cheng CN, Lin CH, Kuo HC, Huang CS, Kuo CH. Investigating the Association of the Biogenic Amine Profile in Urine with Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer Patients. J Proteome Res 2020; 19:4061-4070. [PMID: 32819094 DOI: 10.1021/acs.jproteome.0c00362] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Neoadjuvant treatment (NAT) can downstage breast cancer and can be utilized for different clinical applications. However, the response to NAT varies among individuals. Having effective biomarkers is important to optimize the treatment of breast cancer. Concentrations of biogenic amines have been found to show an association with cancer cell proliferation, but their clinical utility remains unclear. This study developed a postcolumn-infused internal standard (PCI-IS)-assisted liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) method for profiling biogenic amines in human urine. Putrescine-d8 was selected as the PCI-IS to calibrate the errors caused by matrix effects in the urine sample. The optimized method was applied to investigate the association between changes in 14 amines and the therapeutic response to NAT in breast cancer patients. Urine samples were collected before initiation of chemotherapy (n = 60). Our results indicated that the levels of N1-acetylspermine, spermidine, norepinephrine, and dopamine were significantly higher in the responder group than the nonresponder group. These metabolites were incorporated with clinical factors to identify NAT responders, and the prediction model showed an area under the curve value of 0.949. These observations provide remarkable insights for future studies in elucidating the roles of biogenic amines in breast cancer. Additionally, the PCI-IS-assisted amine profiling method can facilitate these studies.
Collapse
Affiliation(s)
- Chiao Lo
- Department of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei 100, Taiwan.,Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei 10002, Taiwan
| | - Ya-Lin Hsu
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei 10050, Taiwan
| | - Chih-Ning Cheng
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei 10050, Taiwan
| | - Ching-Hung Lin
- Department of Medical Oncology, National Taiwan University Cancer Center Hospital, Taipei 106, Taiwan
| | - Han-Chun Kuo
- The Metabolomics Core Laboratory, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Chiun-Sheng Huang
- Department of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei 10050, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei 10055, Taiwan.,Department of Pharmacy, National Taiwan University Hospital, Taipei 100, Taiwan
| |
Collapse
|
31
|
Oncology Therapeutics Targeting the Metabolism of Amino Acids. Cells 2020; 9:cells9081904. [PMID: 32824193 PMCID: PMC7463463 DOI: 10.3390/cells9081904] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 12/19/2022] Open
Abstract
Amino acid metabolism promotes cancer cell proliferation and survival by supporting building block synthesis, producing reducing agents to mitigate oxidative stress, and generating immunosuppressive metabolites for immune evasion. Malignant cells rewire amino acid metabolism to maximize their access to nutrients. Amino acid transporter expression is upregulated to acquire amino acids from the extracellular environment. Under nutrient depleted conditions, macropinocytosis can be activated where proteins from the extracellular environment are engulfed and degraded into the constituent amino acids. The demand for non-essential amino acids (NEAAs) can be met through de novo synthesis pathways. Cancer cells can alter various signaling pathways to boost amino acid usage for the generation of nucleotides, reactive oxygen species (ROS) scavenging molecules, and oncometabolites. The importance of amino acid metabolism in cancer proliferation makes it a potential target for therapeutic intervention, including via small molecules and antibodies. In this review, we will delineate the targets related to amino acid metabolism and promising therapeutic approaches.
Collapse
|
32
|
Tayanloo-Beik A, Sarvari M, Payab M, Gilany K, Alavi-Moghadam S, Gholami M, Goodarzi P, Larijani B, Arjmand B. OMICS insights into cancer histology; Metabolomics and proteomics approach. Clin Biochem 2020; 84:13-20. [PMID: 32589887 DOI: 10.1016/j.clinbiochem.2020.06.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/01/2020] [Accepted: 06/09/2020] [Indexed: 02/06/2023]
Abstract
Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.
Collapse
Affiliation(s)
- Akram Tayanloo-Beik
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Masoumeh Sarvari
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Moloud Payab
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Kambiz Gilany
- Reproductive Immunology Research Center, Avicenna Research Institute, ACECR, Tehran, Iran; Integrative Oncology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran.
| | - Sepideh Alavi-Moghadam
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Mahdi Gholami
- Department of Toxicology & Pharmacology, Faculty of Pharmacy; Toxicology and Poisoning Research Center, Tehran University of Medical Sciences, Tehran 1416753955, Iran.
| | - Parisa Goodarzi
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
33
|
Bannuscher A, Hellack B, Bahl A, Laloy J, Herman H, Stan MS, Dinischiotu A, Giusti A, Krause BC, Tentschert J, Roșu M, Balta C, Hermenean A, Wiemann M, Luch A, Haase A. Metabolomics profiling to investigate nanomaterial toxicity in vitro and in vivo. Nanotoxicology 2020; 14:807-826. [DOI: 10.1080/17435390.2020.1764123] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Anne Bannuscher
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
- Adolphe Merkle Institute (AMI), University of Fribourg, Fribourg, Switzerland
| | - Bryan Hellack
- Institute of Energy and Environmental Technology (IUTA) e.V, Duisburg, Germany
- German Environment Agency (UBA), Dessau, Germany
| | - Aileen Bahl
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Julie Laloy
- Department of Pharmacy, Namur Nanosafety Centre, NARILIS, University of Namur, Namur, Belgium
| | - Hildegard Herman
- Aurel Ardelean” Institute of Life Sciences, “Vasile Goldis” Western University of Arad, Arad, Romania
| | - Miruna S. Stan
- Department of Biochemistry and Molecular Biology, University of Bucharest, Bucharest, Romania
| | - Anca Dinischiotu
- Department of Biochemistry and Molecular Biology, University of Bucharest, Bucharest, Romania
| | - Anna Giusti
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Benjamin-Christoph Krause
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Jutta Tentschert
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Marcel Roșu
- Aurel Ardelean” Institute of Life Sciences, “Vasile Goldis” Western University of Arad, Arad, Romania
| | - Cornel Balta
- Aurel Ardelean” Institute of Life Sciences, “Vasile Goldis” Western University of Arad, Arad, Romania
| | - Anca Hermenean
- Aurel Ardelean” Institute of Life Sciences, “Vasile Goldis” Western University of Arad, Arad, Romania
- Department of Biochemistry and Molecular Biology, University of Bucharest, Bucharest, Romania
| | - Martin Wiemann
- IBE R&D Institute for Lung Health gGmbH, Münster, Germany
| | - Andreas Luch
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Andrea Haase
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| |
Collapse
|
34
|
Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine. Metabolites 2020; 10:metabo10040129. [PMID: 32230776 PMCID: PMC7241083 DOI: 10.3390/metabo10040129] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 03/19/2020] [Accepted: 03/20/2020] [Indexed: 02/07/2023] Open
Abstract
Pharmacometabolomics (PMx) studies use information contained in metabolic profiles (or metabolome) to inform about how a subject will respond to drug treatment. Genome, gut microbiome, sex, nutrition, age, stress, health status, and other factors can impact the metabolic profile of an individual. Some of these factors are known to influence the individual response to pharmaceutical compounds. An individual’s metabolic profile has been referred to as his or her “metabotype.” As such, metabolomic profiles obtained prior to, during, or after drug treatment could provide insights about drug mechanism of action and variation of response to treatment. Furthermore, there are several types of PMx studies that are used to discover and inform patterns associated with varied drug responses (i.e., responders vs. non-responders; slow or fast metabolizers). The PMx efforts could simultaneously provide information related to an individual’s pharmacokinetic response during clinical trials and be used to predict patient response to drugs making pharmacometabolomic clinical research valuable for precision medicine. PMx biomarkers can also be discovered and validated during FDA clinical trials. Using biomarkers during medical development is described in US Law under the 21st Century Cures Act. Information on how to submit biomarkers to the FDA and their context of use is defined herein.
Collapse
|
35
|
Wu D, Li X, Zhang X, Han F, Lu X, Liu L, Zhang J, Dong M, Yang H, Li H. Pharmacometabolomics Identifies 3-Hydroxyadipic Acid, d-Galactose, Lysophosphatidylcholine (P-16:0), and Tetradecenoyl-l-Carnitine as Potential Predictive Indicators of Gemcitabine Efficacy in Pancreatic Cancer Patients. Front Oncol 2020; 9:1524. [PMID: 32064236 PMCID: PMC7000527 DOI: 10.3389/fonc.2019.01524] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 12/18/2019] [Indexed: 12/28/2022] Open
Abstract
Gemcitabine (GEM)-based chemotherapy is the standard regimen for the treatment of pancreatic cancer (PC). However, chemoresistance is a major challenge in PC treatment. Reliable biomarkers are urgently needed to predict the response to GEM-based therapies. GEM-sensitive (GEM-S) and GEM-resistant (GEM-R) pancreatic carcinoma xenograft models were established, and GEM monotherapy and GEM plus nanoparticle albumin-bound paclitaxel (nab-PTX) doublet therapy were administered to GEM-S/R tumor-bearing mice. Metabolomic mass spectrometry (MS) analysis of serum, liver, and tumor samples was performed using an ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometer. The results showed that both GEM monotherapy and combination therapy significantly inhibited the tumor growth in GEM-S subgroup. However, in the GEM-R subgroup, tumor growth was not significantly inhibited by GEM monotherapy, but was significantly suppressed by GEM combination therapy. Metabolic profiling analysis by hierarchical cluster analysis and partial least squares discriminant analysis showed that the differences in metabolites were most significant in serum of three types of samples in the GEM-S/R subgroups, regardless of the administration of GEM monotherapy or combination therapy. The differential metabolite analysis of serum samples revealed 38 and 26 differential metabolites between the GEM-R and GEM-S subgroups treated with GEM monotherapy or combination therapy, and four common discriminating metabolites were investigated: 3-hydroxyadipic acid, d-galactose, lysophosphatidylcholine (LysoPC) (P-16:0), and tetradecenoyl-l-carnitine. The relative amounts of the four metabolites changed significantly and consistently after GEM monotherapy or combination therapy. The levels of these four metabolites were significantly different in the GEM-S and GEM-R pancreatic carcinoma xenograft models; thus, these metabolites could be effective predictive indicators of the efficacy of chemotherapy in PC patients, regardless of the administration of GEM alone or GEM plus nab-PTX.
Collapse
Affiliation(s)
- Dongyuan Wu
- Department of Biochemistry and Molecular Biology, Basic Medical Science College, Harbin Medical University, Harbin, China.,Department of Pharmacy, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xinyuan Li
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xiaohan Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Fang Han
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xin Lu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Lei Liu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junsheng Zhang
- College of Basic Medicine, Harbin Medical University, Harbin, China
| | - Mei Dong
- Department of Pharmacy, Harbin Medical University Cancer Hospital, Harbin, China
| | - Huanjie Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Hui Li
- Department of Biochemistry and Molecular Biology, Basic Medical Science College, Harbin Medical University, Harbin, China
| |
Collapse
|
36
|
Effect of Estrogen Receptor Status on Circulatory Immune and Metabolomics Profiles of HER2-Positive Breast Cancer Patients Enrolled for Neoadjuvant Targeted Chemotherapy. Cancers (Basel) 2020; 12:cancers12020314. [PMID: 32013102 PMCID: PMC7072610 DOI: 10.3390/cancers12020314] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Revised: 01/21/2020] [Accepted: 01/27/2020] [Indexed: 12/11/2022] Open
Abstract
HER2-positive breast cancer (BC) represents a heterogeneous cancer disease. In an attempt to identify new stratification models useful for prognosis and therapeutic strategy, we investigated the influence of estrogen receptor (ER) status on the host immune and metabolomics profile of HER2-positive BC patients enrolled for neoadjuvant targeted chemotherapy (NATC). The study enrolled 43 HER2-positive BC patients eligible for NATC based on the trastuzumab-paclitaxel combination. Baseline circulatory cytokines and 1H NMR plasma metabolomics profiles were investigated. Differences in the immune cytokines and metabolomics profile as a function of the ER status, and their association with clinical outcomes were studied by multivariate and univariate analysis. Baseline metabolomics profiles were found to discriminate HER2-positive ER(+) from ER(−) BC patients. Within the ER(+) group an immune-metabolomics model, based on TNF-α and valine, predicted pathological complete response to NATC with 90.9% accuracy (AUROC = 0.92, p = 0.004). Moreover, metabolomics information integrated with IL-2 and IL-10 cytokine levels were prognostic of relapse with an accuracy of 95.5%. The results indicate that in HER2-positive BC patients the ER status influences the host circulatory immune-metabolomics profile. The baseline immune-metabolomics assessment in combination with ER status could represent an independent stratification tool able to predict NATC response and disease relapse of HER2-positive patients.
Collapse
|
37
|
Mussap M, Loddo C, Fanni C, Fanos V. Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics. Expert Rev Clin Pharmacol 2020; 13:115-134. [PMID: 31958027 DOI: 10.1080/17512433.2020.1713750] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.
Collapse
Affiliation(s)
- Michele Mussap
- Laboratory Unit, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy
| | | | - Claudia Fanni
- Division of Pediatrics, Rovigo Hospital, Rovigo, Italy
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Neonatal Pathology and Neonatal Section, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy
| |
Collapse
|
38
|
Chen Z, Li Z, Li H, Jiang Y. Metabolomics: a promising diagnostic and therapeutic implement for breast cancer. Onco Targets Ther 2019; 12:6797-6811. [PMID: 31686838 PMCID: PMC6709037 DOI: 10.2147/ott.s215628] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 07/22/2019] [Indexed: 12/24/2022] Open
Abstract
Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.
Collapse
Affiliation(s)
- Zhanghan Chen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Zehuan Li
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Haoran Li
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| | - Ying Jiang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, People's Republic of China
| |
Collapse
|
39
|
Banales JM, Iñarrairaegui M, Arbelaiz A, Milkiewicz P, Muntané J, Muñoz‐Bellvis L, La Casta A, Gonzalez LM, Arretxe E, Alonso C, Martínez‐Arranz I, Lapitz A, Santos‐Laso A, Avila MA, Martínez‐Chantar ML, Bujanda L, Marin JJ, Sangro B, Macias RI. Serum Metabolites as Diagnostic Biomarkers for Cholangiocarcinoma, Hepatocellular Carcinoma, and Primary Sclerosing Cholangitis. Hepatology 2019; 70:547-562. [PMID: 30325540 PMCID: PMC6767196 DOI: 10.1002/hep.30319] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 10/06/2018] [Indexed: 12/12/2022]
Abstract
Early and differential diagnosis of intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) by noninvasive methods represents a current clinical challenge. The analysis of low-molecular-weight metabolites by new high-throughput techniques is a strategy for identifying biomarkers. Here, we have investigated whether serum metabolome can provide useful biomarkers in the diagnosis of iCCA and HCC and could discriminate iCCA from HCC. Because primary sclerosing cholangitis (PSC) is a risk factor for CCA, serum metabolic profiles of PSC and CCA have also been compared. The analysis of the levels of lipids and amino acids in the serum of patients with iCCA, HCC, and PSC and healthy individuals (n = 20/group) showed differential profiles. Several metabolites presented high diagnostic value for iCCA versus control, HCC versus control, and PSC versus control, with areas under the receiver operating characteristic curve (AUC) greater than those found in serum for the nonspecific tumor markers carbohydrate antigen 19-9 (CA 19-9) and alpha-fetoprotein (AFP), commonly used to help in the diagnosis of iCCA and HCC, respectively. The development of an algorithm combining glycine, aspartic acid, SM(42:3), and SM(43:2) permitted to accurately differentiate in the diagnosis of both types of tumors (biopsy-proven). The proposed model yielded 0.890 AUC, 75% sensitivity, and 90% specificity. Another algorithm by combination of PC(34:3) and histidine accurately permitted to differentiate PSC from iCCA, with an AUC of 0.990, 100% sensitivity, and 70% specificity. These results were validated in independent cohorts of 14-15 patients per group and compared with profiles found in patients with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Conclusion: Specific changes in serum concentrations of certain metabolites are useful to differentiate iCCA from HCC or PSC, and could help in the early diagnosis of these diseases.
Collapse
Affiliation(s)
- Jesus M. Banales
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain,National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,IKERBASQUEBasque Foundation for ScienceBilbaoSpain
| | - Mercedes Iñarrairaegui
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Liver UnitClínica Universidad de Navarra‐IDISNAPamplonaSpain
| | - Ander Arbelaiz
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain
| | - Piotr Milkiewicz
- Liver and Internal Medicine Unit, Department of General, Transplant and Liver SurgeryMedical University of WarsawWarsawPoland
| | - Jordi Muntané
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Department of General Surgery “Virgen del Rocío” University Hospital/IBiS/CSIC/University of SevilleSevilleSpain
| | - Luis Muñoz‐Bellvis
- Service of General and Gastrointestinal SurgeryUniversity Hospital of Salamanca, Biomedical Research Institute of Salamanca (IBSAL), CIBERONCSalamancaSpain
| | - Adelaida La Casta
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain
| | - Luis M. Gonzalez
- Service of General and Gastrointestinal SurgeryUniversity Hospital of Salamanca, Biomedical Research Institute of Salamanca (IBSAL), CIBERONCSalamancaSpain
| | | | | | | | - Ainhoa Lapitz
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain
| | - Alvaro Santos‐Laso
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain
| | - Matias A. Avila
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Program of Hepatology, Center for Applied Medical Research (CIMA)University of Navarra‐IDISNAPamplonaSpain
| | - Maria L. Martínez‐Chantar
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,CIC bioGUNEBizkaia Technology ParkDerioSpain
| | - Luis Bujanda
- Department of Liver and Gastrointestinal DiseasesBiodonostia Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EHU)San SebastianSpain,National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain
| | - Jose J.G. Marin
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Experimental Hepatology and Drug Targeting (HEVEFARM)University of Salamanca, Biomedical Research Institute of Salamanca (IBSAL)SalamancaSpain
| | - Bruno Sangro
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Liver UnitClínica Universidad de Navarra‐IDISNAPamplonaSpain
| | - Rocio I.R. Macias
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute)MadridSpain,Experimental Hepatology and Drug Targeting (HEVEFARM)University of Salamanca, Biomedical Research Institute of Salamanca (IBSAL)SalamancaSpain
| |
Collapse
|
40
|
Pang H, Jia W, Hu Z. Emerging Applications of Metabolomics in Clinical Pharmacology. Clin Pharmacol Ther 2019; 106:544-556. [DOI: 10.1002/cpt.1538] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 05/18/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Huanhuan Pang
- School of Pharmaceutical Sciences Tsinghua University Beijing China
| | - Wei Jia
- Cancer Biology Program University of Hawaii Cancer Center Honolulu Hawaii USA
| | - Zeping Hu
- School of Pharmaceutical Sciences Tsinghua University Beijing China
- Tsinghua‐Peking Joint Center for Life Sciences Tsinghua University Beijing China
- Beijing Frontier Research Center for Biological Structure Tsinghua University Beijing China
| |
Collapse
|
41
|
Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers? Int J Mol Sci 2019; 20:ijms20061385. [PMID: 30893889 PMCID: PMC6471292 DOI: 10.3390/ijms20061385] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/14/2019] [Accepted: 03/15/2019] [Indexed: 02/07/2023] Open
Abstract
Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.
Collapse
|
42
|
Wide spectrum targeted metabolomics identifies potential ovarian cancer biomarkers. Life Sci 2019; 222:235-244. [PMID: 30853626 DOI: 10.1016/j.lfs.2019.03.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 02/21/2019] [Accepted: 03/04/2019] [Indexed: 02/06/2023]
Abstract
AIMS Despite of almost a hundred years of research on cancer metabolism, the biological background of cancerogenesis and cancer-related reprogramming of metabolism remains not fully understood. In order to comprehensively and effectively diagnose and treat the deadliest diseases, the mechanisms underlying these diseases have to be discovered urgently. Among the gynecological malignancies, ovarian cancer is the most common cause of death. The aim of the study was to search for potential cancer-related differences in concentrations of metabolites and interactions between them in serum of women with ovarian cancer and benign ovarian tumor in comparison with healthy controls using targeted metabolomics. These metabolites might serve as biomarkers in the future. MAIN METHODS We used wide spectrum targeted metabolomics to evaluate serum concentrations of metabolites related to ovarian cancer and compared them against benign ovarian tumors and healthy controls. The measurements were performed using high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry technique in highly-selective multiple reaction monitoring mode. KEY FINDINGS In this study we confirmed our previous findings about the role of histidine and citrulline in ovarian cancer as well as we indicated new lipid compounds (lysoPC a C16:1, PC aa C32:2, PC aa C34:4 and PC aa C 36:6) potentially involved in cancer metabolism. SIGNIFICANCES We indicated interesting interactions between metabolites for further in-depth research which could potentially serve as clinically useful biomarkers in future. Moreover, the presented work attempts to visualize a possible 3D-network of relationships between the molecules found to be related to ovarian malignancy.
Collapse
|
43
|
Everett JR. Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling. Handb Exp Pharmacol 2019; 260:263-299. [PMID: 31823071 DOI: 10.1007/164_2019_316] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.
Collapse
Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich, Kent, UK.
| |
Collapse
|
44
|
Abstract
Advances in our understanding of the metabolism and molecular functions of polyamines and their alterations in cancer have led to resurgence in the interest of targeting polyamine metabolism as an anticancer strategy. Increasing knowledge of the interplay between polyamine metabolism and other cancer-driving pathways, including the PTEN-PI3K-mTOR complex 1 (mTORC1), WNT signalling and RAS pathways, suggests potential combination therapies that will have considerable clinical promise. Additionally, an expanding number of promising clinical trials with agents targeting polyamines for both therapy and prevention are ongoing. New insights into molecular mechanisms linking dysregulated polyamine catabolism and carcinogenesis suggest additional strategies that can be used for cancer prevention in at-risk individuals. In addition, polyamine blocking therapy, a strategy that combines the inhibition of polyamine biosynthesis with the simultaneous blockade of polyamine transport, can be more effective than therapies based on polyamine depletion alone and may involve an antitumour immune response. These findings open up new avenues of research into exploiting aberrant polyamine metabolism for anticancer therapy.
Collapse
Affiliation(s)
- Robert A Casero
- Department of Oncology, Johns Hopkins University School of Medicine and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.
| | - Tracy Murray Stewart
- Department of Oncology, Johns Hopkins University School of Medicine and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Anthony E Pegg
- Department of Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| |
Collapse
|
45
|
Lipid profiling of pre-treatment plasma reveals biomarker candidates associated with response rates and hand-foot skin reactions in sorafenib-treated patients. Cancer Chemother Pharmacol 2018; 82:677-684. [PMID: 30062555 DOI: 10.1007/s00280-018-3655-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 07/23/2018] [Indexed: 12/17/2022]
Abstract
Sorafenib is a multi-kinase inhibitor for treatment of advanced hepatocellular carcinoma (HCC). Beyond its clinical benefit against advanced HCC, the efficacy and safety of sorafenib chemotherapy are critical concerns. In this study, we addressed the lipid profiles associated with the efficacy and safety of sorafenib chemotherapy. Plasma samples from HCC patients before sorafenib chemotherapy (N = 44) were collected and subjected to lipidomic analysis. We measured the levels of 176 lipids belonging to 8 classes of phosphoglycerolipids, 2 classes of sphingolipids, 3 classes of neutral lipids, and 4 other classes of lipids. To characterize lipids associated with efficacy, we compared the responder group (N = 21; partial response and stable disease) with non-responder group (N = 22; progressive disease). To characterize lipids associated with hand-foot skin reaction (HFSR), we compared the susceptible group (N = 12; grade 2 and 3) with non-susceptible group (N = 32; grade 0 and 1). The levels of 8 lipids, including phosphatidylcholine (PC)[34:2], PC[34:3]a, PC[35:2], PC[36:4]a, PC[34:3e], acylcarnitine (Car)[18:0], cholesterol ester[20:2], and diacylglycerol (DG)[34:2], were significantly lower in the responder group, and 6 out of 8 these lipids contained FA(18:2). In addition, the levels of 7 lipids (Car[12:0], Car[18:0], Car[18:1], Car[20:1] and fatty acid amides (FAA[16:0], FAA[18:0], and FAA[18:1]b)) were significantly lower in the group susceptible to HFSR. Our comprehensive lipidomics study using samples from sorafenib-treated patients with HCC revealed that significant differences in the lipid profiles of pre-treatment plasma were associated with sorafenib efficacy and sorafenib-induced HFSR. Validation using another set of patient plasma samples and elucidating the molecular basis of these changes will lead to better treatment with sorafenib chemotherapy.
Collapse
|
46
|
McCartney A, Vignoli A, Biganzoli L, Love R, Tenori L, Luchinat C, Di Leo A. Metabolomics in breast cancer: A decade in review. Cancer Treat Rev 2018; 67:88-96. [PMID: 29775779 DOI: 10.1016/j.ctrv.2018.04.012] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 04/09/2018] [Accepted: 04/10/2018] [Indexed: 12/27/2022]
Abstract
Breast cancer (BC) is a heterogeneous disease which has been characterised and stratified by many platforms such as clinicopathological risk factors, genomic assays, computer generated models, and various "-omic" technologies. Genomic, proteomic and transcriptomic analysis in breast cancer research is well established, and metabolomics, which can be considered a downstream manifestation of the former disciplines, is of growing interest. The past decade has seen significant progress made within the field of clinical metabolomic BC research, with several groups demonstrating results with significant promise in the setting of BC screening and biological characterisation, as well as future potential for prognostic metabolomic biomarkers.
Collapse
Affiliation(s)
- Amelia McCartney
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy
| | - Alessia Vignoli
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy
| | - Laura Biganzoli
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy
| | - Richard Love
- Department of Mathematics, Statistics and Computer Science, Marquette University, Milawaukee, WI, USA
| | - Leonardo Tenori
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy; Department of Clinical and Experimental Medicine, University of Florence, Largo Brambilla 3, Florence 50100, Italy
| | - Claudio Luchinat
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy; Department of Chemistry, University of Florence, Via della Lastruccia 3, Sesto Fiorentino 50019, Italy
| | - Angelo Di Leo
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy.
| |
Collapse
|
47
|
Niedzwiecki M, Samant P, Walker DI, Tran V, Jones DP, Prausnitz MR, Miller GW. Human Suction Blister Fluid Composition Determined Using High-Resolution Metabolomics. Anal Chem 2018; 90:3786-3792. [PMID: 29425024 PMCID: PMC5863097 DOI: 10.1021/acs.analchem.7b04073] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 02/09/2018] [Indexed: 12/22/2022]
Abstract
Interstitial fluid (ISF) surrounds the cells and tissues of the body. Since ISF has molecular components similar to plasma, as well as compounds produced locally in tissues, it may be a valuable source of biomarkers for diagnostics and monitoring. However, there has not been a comprehensive study to determine the metabolite composition of ISF and to compare it to plasma. In this study, the metabolome of suction blister fluid (SBF), which largely consists of ISF, collected from 10 human volunteers was analyzed using untargeted high-resolution metabolomics (HRM). A wide range of metabolites were detected in SBF, including amino acids, lipids, nucleotides, and compounds of exogenous origin. Various systemic and skin-derived metabolite biomarkers were elevated or found uniquely in SBF, and many other metabolites of clinical and physiological significance were well correlated between SBF and plasma. In sum, using untargeted HRM profiling, this study shows that SBF can be a valuable source of information about metabolites relevant to human health.
Collapse
Affiliation(s)
- Megan
M. Niedzwiecki
- Department
of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Pradnya Samant
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Douglas I. Walker
- Clinical
Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical
Care Medicine, Emory University School of
Medicine, Atlanta, Georgia 30322, United
States
| | - ViLinh Tran
- Clinical
Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical
Care Medicine, Emory University School of
Medicine, Atlanta, Georgia 30322, United
States
| | - Dean P. Jones
- Clinical
Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical
Care Medicine, Emory University School of
Medicine, Atlanta, Georgia 30322, United
States
| | - Mark R. Prausnitz
- School
of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Gary W. Miller
- Department
of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| |
Collapse
|
48
|
Zeng F, Fu J, Hu F, Tang Y, Fang X, Zeng F, Chu Y. Identification of key pathways and genes in response to trastuzumab treatment in breast cancer using bioinformatics analysis. Oncotarget 2018; 9:32149-32160. [PMID: 30181805 PMCID: PMC6114942 DOI: 10.18632/oncotarget.24605] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 02/25/2018] [Indexed: 01/06/2023] Open
Abstract
Breast cancer (BC) is one of the leading causes of death among women worldwide. The gene expression profile GSE22358 was downloaded from the Gene Expression Omnibus (GEO) database, which included 154 operable early-stage breast cancer samples treated with neoadjuvant capecitabine plus docetaxel, with (34) or without trastuzumab (120), to identify gene signatures during trastuzumab treatment and uncover their potential mechanisms. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and a protein–protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. There were 2284 DEGs, including 1231 up-regulated genes enriched in DNA replication, protein N-linked glycosylation via asparagine, and response to toxic substances, while 1053 down-regulated genes were enriched in axon guidance, protein localization to plasma membrane, protein stabilization, and protein glycosylation. Eight hub genes were identified from the PPI network, including GSK3B, RAC1, PXN, ERBB2, HSP90AA1, FGF2, PIK3R1 and RAC2. Our experimental results showed that GSK3B was also highly expressed in breast cancer tissues and was associated with poor survival, as was β-catenin. In conclusion, the present study indicated that the identified DEGs and hub genes further our understanding of the molecular mechanisms underlying trastuzumab treatment in BC and highlighted GSK3B, which might be used as a molecular target for the treatment of BC.
Collapse
Affiliation(s)
- Fanxin Zeng
- Institute of Molecular Medicine, Peking University, Beijing, China.,Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China.,Department of Oncology, Dazhou Central Hospital, Dazhou, Sichuan, China
| | - Jiangping Fu
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China.,Department of Oncology, Dazhou Central Hospital, Dazhou, Sichuan, China
| | - Fang Hu
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China.,Department of Oncology, Dazhou Central Hospital, Dazhou, Sichuan, China
| | - Yani Tang
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China
| | - Xiangdong Fang
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China.,Department of Oncology, Dazhou Central Hospital, Dazhou, Sichuan, China
| | - Fanwei Zeng
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China
| | - Yanpeng Chu
- Dazhou Central Hospital Clinic Medical Center, Dazhou, Sichuan, China
| |
Collapse
|
49
|
Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach. J Pharm Biomed Anal 2018; 154:95-101. [PMID: 29544107 DOI: 10.1016/j.jpba.2018.02.051] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 02/18/2018] [Accepted: 02/22/2018] [Indexed: 01/05/2023]
Abstract
Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment.
Collapse
|
50
|
Cardoso MR, Santos JC, Ribeiro ML, Talarico MCR, Viana LR, Derchain SFM. A Metabolomic Approach to Predict Breast Cancer Behavior and Chemotherapy Response. Int J Mol Sci 2018; 19:ijms19020617. [PMID: 29466297 PMCID: PMC5855839 DOI: 10.3390/ijms19020617] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 01/29/2018] [Accepted: 01/31/2018] [Indexed: 12/20/2022] Open
Abstract
Although the classification of breast carcinomas into molecular or immunohistochemical subtypes has contributed to a better categorization of women into different therapeutic regimens, breast cancer nevertheless still progresses or recurs in a remarkable number of patients. Identifying women who would benefit from chemotherapy could potentially increase treatment effectiveness, which has important implications for long-term survival. Metabolomic analyses of fluids and tissues from cancer patients improve our knowledge of the reprogramming of metabolic pathways involved in resistance to chemotherapy. This review evaluates how recent metabolomic approaches have contributed to understanding the relationship between breast cancer and the acquisition of resistance. We focus on the advantages and challenges of cancer treatment and the use of new strategies in clinical care, which helps us comprehend drug resistance and predict responses to treatment.
Collapse
Affiliation(s)
- Marcella Regina Cardoso
- Hospital da Mulher Prof. Dr. José Aristodemo Pinotti-Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil.
| | - Juliana Carvalho Santos
- Hospital da Mulher Prof. Dr. José Aristodemo Pinotti-Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil.
| | - Marcelo Lima Ribeiro
- Clinical Pharmacology and Gastroenterology Unit, São Francisco University, Bragança Paulista, São Paulo 13083-881, Brazil.
| | - Maria Cecília Ramiro Talarico
- Hospital da Mulher Prof. Dr. José Aristodemo Pinotti-Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil.
| | - Lais Rosa Viana
- Hospital da Mulher Prof. Dr. José Aristodemo Pinotti-Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil.
| | - Sophie Françoise Mauricette Derchain
- Hospital da Mulher Prof. Dr. José Aristodemo Pinotti-Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil.
| |
Collapse
|