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Proteomics: Application of next-generation proteomics in cancer research. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00016-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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2
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An oncogene addiction phosphorylation signature and its derived scores inform tumor responsiveness to targeted therapies. Cell Mol Life Sci 2022; 80:6. [PMID: 36494469 PMCID: PMC9734221 DOI: 10.1007/s00018-022-04634-2] [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: 02/18/2022] [Revised: 11/08/2022] [Accepted: 11/14/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE Oncogene addiction provides important therapeutic opportunities for precision oncology treatment strategies. To date the cellular circuitries associated with driving oncoproteins, which eventually establish the phenotypic manifestation of oncogene addiction, remain largely unexplored. Data suggest the DNA damage response (DDR) as a central signaling network that intersects with pathways associated with deregulated addicting oncoproteins with kinase activity in cancer cells. EXPERIMENTAL DESIGN: We employed a targeted mass spectrometry approach to systematically explore alterations in 116 phosphosites related to oncogene signaling and its intersection with the DDR following inhibition of the addicting oncogene alone or in combination with irradiation in MET-, EGFR-, ALK- or BRAF (V600)-positive cancer models. An NSCLC tissue pipeline combining patient-derived xenografts (PDXs) and ex vivo patient organotypic cultures has been established for treatment responsiveness assessment. RESULTS We identified an 'oncogene addiction phosphorylation signature' (OAPS) consisting of 8 protein phosphorylations (ACLY S455, IF4B S422, IF4G1 S1231, LIMA1 S490, MYCN S62, NCBP1 S22, P3C2A S259 and TERF2 S365) that are significantly suppressed upon targeted oncogene inhibition solely in addicted cell line models and patient tissues. We show that the OAPS is present in patient tissues and the OAPS-derived score strongly correlates with the ex vivo responses to targeted treatments. CONCLUSIONS We propose a score derived from OAPS as a quantitative measure to evaluate oncogene addiction of cancer cell samples. This work underlines the importance of protein phosphorylation assessment for patient stratification in precision oncology and corresponding identification of tumor subtypes sensitive to inhibition of a particular oncogene.
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Mo H, Breitling R, Francavilla C, Schwartz JM. Data integration and mechanistic modelling for breast cancer biology: Current state and future directions. CURRENT OPINION IN ENDOCRINE AND METABOLIC RESEARCH 2022; 24:None. [PMID: 36034741 PMCID: PMC9402443 DOI: 10.1016/j.coemr.2022.100350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Breast cancer is one of the most common cancers threatening women worldwide. A limited number of available treatment options, frequent recurrence, and drug resistance exacerbate the prognosis of breast cancer patients. Thus, there is an urgent need for methods to investigate novel treatment options, while taking into account the vast molecular heterogeneity of breast cancer. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics and metabolomics data, enable approaching breast cancer biology at multiple levels of omics interaction networks. Systems biology approaches, including computational inference of ‘big data’ and mechanistic modelling of specific pathways, are emerging to identify potential novel combinations of breast cancer subtype signatures and more diverse targeted therapies.
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Luo H, Ge H. Application of Proteomics in the Discovery of Radiosensitive Cancer Biomarkers. Front Oncol 2022; 12:852791. [PMID: 35280744 PMCID: PMC8904368 DOI: 10.3389/fonc.2022.852791] [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: 01/11/2022] [Accepted: 02/04/2022] [Indexed: 12/21/2022] Open
Abstract
Radiation therapy remains an important component of cancer treatment. Gene-encoded proteins were the actual executors of cellular functions. Proteomic was a novel technology that can systematically analysis protein composition and measure their levels of change, this was a high throughput method, and were the import tools in the post genomic era. In recent years, rapid progress of proteomic have been made in the study of cancer mechanism, diagnosis, and treatment. This article elaborates current advances and future directions of proteomics in the discovery of radiosensitive cancer biomarkers.
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Affiliation(s)
- Hui Luo
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Hong Ge
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
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5
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Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer. Cells 2022; 11:cells11060973. [PMID: 35326424 PMCID: PMC8946849 DOI: 10.3390/cells11060973] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 03/05/2022] [Accepted: 03/08/2022] [Indexed: 12/24/2022] Open
Abstract
Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.
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Sirven P, Faucheux L, Grandclaudon M, Michea P, Vincent-Salomon A, Mechta-Grigoriou F, Scholer-Dahirel A, Guillot-Delost M, Soumelis V. Definition of a novel breast tumor-specific classifier based on secretome analysis. Breast Cancer Res 2022; 24:94. [PMID: 36539890 PMCID: PMC9764559 DOI: 10.1186/s13058-022-01590-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND During cancer development, the normal tissue microenvironment is shaped by tumorigenic events. Inflammatory mediators and immune cells play a key role during this process. However, which molecular features most specifically characterize the malignant tissue remains poorly explored. METHODS Within our institutional tumor microenvironment global analysis (T-MEGA) program, we set a prospective cohort of 422 untreated breast cancer patients. We established a dedicated pipeline to generate supernatants from tumor and juxta-tumor tissue explants and quantify 55 soluble molecules using Luminex or MSD. Those analytes belonged to five molecular families: chemokines, cytokines, growth factors, metalloproteinases, and adipokines. RESULTS When looking at tissue specificity, our dataset revealed some breast tumor-specific characteristics, as IL-16, as well as some juxta-tumor-specific secreted molecules, as IL-33. Unsupervised clustering analysis identified groups of molecules that were specific to the breast tumor tissue and displayed a similar secretion behavior. We identified a tumor-specific cluster composed of nine molecules that were secreted fourteen times more in the tumor supernatants than the corresponding juxta-tumor supernatants. This cluster contained, among others, CCL17, CCL22, and CXCL9 and TGF-β1, 2, and 3. The systematic comparison of tumor and juxta-tumor secretome data allowed us to mathematically formalize a novel breast cancer signature composed of 14 molecules that segregated tumors from juxta-tumors, with a sensitivity of 96.8% and a specificity of 96%. CONCLUSIONS Our study provides the first breast tumor-specific classifier computed on breast tissue-derived secretome data. Moreover, our T-MEGA cohort dataset is a freely accessible resource to the biomedical community to help advancing scientific knowledge on breast cancer.
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Affiliation(s)
- Philémon Sirven
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France
| | - Lilith Faucheux
- INSERM U976, Université de Paris, IRSLHôpital Saint Louis, 75006 Paris, France ,INSERM UMR1153, Université de Paris, ECSTRRA Team, 75006 Paris, France
| | - Maximilien Grandclaudon
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France
| | - Paula Michea
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France
| | - Anne Vincent-Salomon
- grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,grid.418596.70000 0004 0639 6384Diagnostic and Theranostic Medicine Division, Institut Curie, Paris, France
| | - Fatima Mechta-Grigoriou
- grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,grid.418596.70000 0004 0639 6384Centre de Recherche, Stress and Cancer Laboratory, U830 Genetics and Biology of Cancers, INSERM, Institut Curie, Paris, France
| | - Alix Scholer-Dahirel
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France
| | - Maude Guillot-Delost
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France
| | - Vassili Soumelis
- grid.418596.70000 0004 0639 6384INSERM Unit U932, Immunity and Cancer, Institut Curie, Paris, France ,grid.440907.e0000 0004 1784 3645Paris Sciences Lettres (PSL) University, Paris, France ,Center of Clinical Investigation, CIC IGR-Curie 1428, Paris, France ,INSERM U976, Université de Paris, IRSLHôpital Saint Louis, 75006 Paris, France ,grid.413328.f0000 0001 2300 6614Department of Immunology-Histocompatibility, AP-HP, Hôpital Saint-Louis, 75010 Paris, France
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On-tissue polysulfide visualization by surface-enhanced Raman spectroscopy benefits patients with ovarian cancer to predict post-operative chemosensitivity. Redox Biol 2021; 41:101926. [PMID: 33752108 PMCID: PMC8010883 DOI: 10.1016/j.redox.2021.101926] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 02/23/2021] [Accepted: 02/26/2021] [Indexed: 12/14/2022] Open
Abstract
Chemosensitivity to cisplatin derivatives varies among individual patients with intractable malignancies including ovarian cancer, while how to unlock the resistance remain unknown. Ovarian cancer tissues were collected the debulking surgery in discovery- (n = 135) and validation- (n = 47) cohorts, to be analyzed with high-throughput automated immunohistochemistry which identified cystathionine γ-lyase (CSE) as an independent marker distinguishing non-responders from responders to post-operative platinum-based chemotherapy. We aimed to identify CSE-derived metabolites responsible for chemoresistant mechanisms: gold-nanoparticle (AuN)-based surface-enhanced Raman spectroscopy (SERS) was used to enhance electromagnetic fields which enabled to visualize multiple sulfur-containing metabolites through detecting scattering light from Au-S vibration two-dimensionally. Clear cell carcinoma (CCC) who turned out less sensitive to cisplatin than serous adenocarcinoma was classified into two groups by the intensities of SERS intensities at 480 cm-1; patients with greater intensities displayed the shorter overall survival after the debulking surgery. The SERS signals were eliminated by topically applied monobromobimane that breaks sulfane-sulfur bonds of polysulfides to result in formation of sulfodibimane which was detected at 580 cm-1, manifesting the presence of polysulfides in cancer tissues. CCC-derived cancer cell lines in culture were resistant against cisplatin, but treatment with ambroxol, an expectorant degrading polysulfides, renders the cells CDDP-susceptible. Co-administration of ambroxol with cisplatin significantly suppressed growth of cancer xenografts in nude mice. Furthermore, polysulfides, but neither glutathione nor hypotaurine, attenuated cisplatin-induced disturbance of DNA supercoiling. Polysulfide detection by on-tissue SERS thus enables to predict prognosis of cisplatin-based chemotherapy. The current findings suggest polysulfide degradation as a stratagem unlocking cisplatin chemoresistance.
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Terkelsen T, Pernemalm M, Gromov P, Børresen-Dale AL, Krogh A, Haakensen VD, Lethiö J, Papaleo E, Gromova I. High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers. Mol Oncol 2021; 15:429-461. [PMID: 33176066 PMCID: PMC7858121 DOI: 10.1002/1878-0261.12850] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 08/13/2020] [Accepted: 11/09/2020] [Indexed: 12/24/2022] Open
Abstract
Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.
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Affiliation(s)
- Thilde Terkelsen
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Maria Pernemalm
- Cancer Proteomics Mass Spectrometry, Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Pavel Gromov
- Breast Cancer Biology Group, Genome Integrity Unit, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anna-Lise Børresen-Dale
- Department of Cancer Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Norway
| | - Anders Krogh
- Department of Computer Science, University of Copenhagen, Denmark.,Department of Biology, University of Copenhagen, Denmark
| | - Vilde D Haakensen
- Department of Cancer Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Norway
| | - Janne Lethiö
- Cancer Proteomics Mass Spectrometry, Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Elena Papaleo
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark.,Translational Disease System Biology, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Denmark
| | - Irina Gromova
- Breast Cancer Biology Group, Genome Integrity Unit, Danish Cancer Society Research Center, Copenhagen, Denmark
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Kang KW, Kim H, Hur W, Jung JH, Jeong SJ, Shin H, Seo D, Jeong H, Choi B, Hong S, Kim HK, Choi Y, Park JH, Lee KY, Kim KP, Park Y. A Proteomic Approach to Understand the Clinical Significance of Acute Myeloid Leukemia-Derived Extracellular Vesicles Reflecting Essential Characteristics of Leukemia. Mol Cell Proteomics 2020; 20:100017. [PMID: 33592500 PMCID: PMC7949255 DOI: 10.1074/mcp.ra120.002169] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 11/12/2020] [Accepted: 11/30/2020] [Indexed: 01/08/2023] Open
Abstract
Extracellular vesicle (EV) proteins from acute myeloid leukemia (AML) cell lines were analyzed using mass spectrometry. The analyses identified 2450 proteins, including 461 differentially expressed proteins (290 upregulated and 171 downregulated). CD53 and CD47 were upregulated and were selected as candidate biomarkers. The association between survival of patients with AML and the expression levels of CD53 and CD47 at diagnosis was analyzed using mRNA expression data from The Cancer Genome Atlas database. Patients with higher expression levels showed significantly inferior survival than those with lower expression levels. ELISA results of the expression levels of CD53 and CD47 from EVs in the bone marrow of patients with AML at diagnosis and at the time of complete remission with induction chemotherapy revealed that patients with downregulated CD53 and CD47 expression appeared to relapse less frequently. Network model analysis of EV proteins revealed several upregulated kinases, including LYN, CSNK2A1, SYK, CSK, and PTK2B. The potential cytotoxicity of several clinically applicable drugs that inhibit these kinases was tested in AML cell lines. The drugs lowered the viability of AML cells. The collective data suggest that AML cell-derived EVs could reflect essential leukemia biology.
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Affiliation(s)
- Ka-Won Kang
- Division of Hematology-Oncology, Department of Internal Medicine, Korea University College of Medicine, Seoul, South Korea
| | - Hyoseon Kim
- Department of Applied Chemistry, Institute of Natural Science, Global Center for Pharmaceutical Ingredient Materials, Kyung Hee University, Yongin, South Korea; Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, Seoul, South Korea
| | - Woojune Hur
- Division of Hematology-Oncology, Department of Internal Medicine, Korea University College of Medicine, Seoul, South Korea
| | - Jik-Han Jung
- Department of Bio and Brain Bioengineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Su Jin Jeong
- Department of Statistics Support, Medical Science Research Institute, Kyung Hee University Hospital, Seoul, South Korea
| | - Hyunku Shin
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea
| | - Dongkwon Seo
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea
| | - Hyesun Jeong
- School of Biosystem and Biomedical Science, Korea University, Seoul, South Korea
| | - ByeongHyeon Choi
- Department of Thoracic and Cardiovascular Surgery, Korea University College of Medicine, Seoul, South Korea
| | - Sunghoi Hong
- School of Biosystem and Biomedical Science, Korea University, Seoul, South Korea
| | - Hyun Koo Kim
- Department of Thoracic and Cardiovascular Surgery, Korea University College of Medicine, Seoul, South Korea
| | - Yeonho Choi
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea
| | - Ji-Ho Park
- Department of Bio and Brain Bioengineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Kil Yeon Lee
- Department of Surgery, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Kwang Pyo Kim
- Department of Applied Chemistry, Institute of Natural Science, Global Center for Pharmaceutical Ingredient Materials, Kyung Hee University, Yongin, South Korea; Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, Seoul, South Korea.
| | - Yong Park
- Division of Hematology-Oncology, Department of Internal Medicine, Korea University College of Medicine, Seoul, South Korea.
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Hernandez-Valladares M, Bruserud Ø, Selheim F. The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives. Int J Mol Sci 2020; 21:ijms21186830. [PMID: 32957646 PMCID: PMC7556012 DOI: 10.3390/ijms21186830] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/10/2020] [Accepted: 09/15/2020] [Indexed: 02/08/2023] Open
Abstract
With the current reproducibility of proteome preparation workflows along with the speed and sensitivity of the mass spectrometers, the transition of the mass spectrometry (MS)-based proteomics technology from biomarker discovery to clinical implementation is under appraisal in the biomedicine community. Therefore, this technology might be implemented soon to detect well-known biomarkers in cancers and other diseases. Acute myeloid leukemia (AML) is an aggressive heterogeneous malignancy that requires intensive treatment to cure the patient. Leukemia relapse is still a major challenge even for patients who have favorable genetic abnormalities. MS-based proteomics could be of great help to both describe the proteome changes of individual patients and identify biomarkers that might encourage specific treatments or clinical strategies. Herein, we will review the advances and availability of the MS-based proteomics strategies that could already be used in clinical proteomics. However, the heterogeneity of complex diseases as AML requires consensus to recognize AML biomarkers and to establish MS-based workflows that allow their unbiased identification and quantification. Although our literature review appears promising towards the utilization of MS-based proteomics in clinical AML in a near future, major efforts are required to validate AML biomarkers and agree on clinically approved workflows.
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MESH Headings
- Biomarkers, Tumor/analysis
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Computational Biology
- Humans
- Leukemia, Myeloid, Acute/diagnosis
- Leukemia, Myeloid, Acute/genetics
- Leukemia, Myeloid, Acute/metabolism
- Leukemia, Myeloid, Acute/therapy
- Mass Spectrometry/methods
- Prognosis
- Proteome/analysis
- Proteome/metabolism
- Proteomics/methods
- Robotics/instrumentation
- Robotics/methods
- Workflow
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Affiliation(s)
- Maria Hernandez-Valladares
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- The Proteomics Facility of the University of Bergen (PROBE), Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
| | - Øystein Bruserud
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
| | - Frode Selheim
- The Proteomics Facility of the University of Bergen (PROBE), Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- The Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
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Doostparast Torshizi A, Duan J, Wang K. Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes. PATTERNS 2020; 1. [PMID: 32984858 PMCID: PMC7518509 DOI: 10.1016/j.patter.2020.100091] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Accumulation of diverse types of omics data on schizophrenia (SCZ) requires a systems approach to model the interplay between genome, transcriptome, and proteome. We introduce Markov affinity-based proteogenomic signal diffusion (MAPSD), a method to model intra-cellular protein trafficking paradigms and tissue-wise single-cell protein abundances. MAPSD integrates multi-omics data to amplify the signals at SCZ risk loci with small effect sizes, and reveal convergent disease-associated gene modules in the brain. We predicted a set of high-confidence SCZ risk loci followed by characterizing the subcellular localization of proteins encoded by candidate SCZ risk genes, and illustrated that most are enriched in neuronal cells in the cerebral cortex as well as Purkinje cells in the cerebellum. We demonstrated how the identified genes may be involved in neurodevelopment, how they may alter SCZ-related biological pathways, and how they facilitate drug repurposing. MAPSD is applicable in other polygenic diseases and can facilitate our understanding of disease mechanisms.
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Affiliation(s)
- Abolfazl Doostparast Torshizi
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, North Shore University Health System, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL 60637, USA
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Corresponding author
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Lastovickova M, Strouhalova D, Bobalova J. Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review. J Proteome Res 2020; 19:1885-1899. [PMID: 32181666 DOI: 10.1021/acs.jproteome.9b00818] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.
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Affiliation(s)
- Marketa Lastovickova
- Institute of Analytical Chemistry of the CAS, Veveří 97, 602 00 Brno, Czech Republic
| | - Dana Strouhalova
- Institute of Analytical Chemistry of the CAS, Veveří 97, 602 00 Brno, Czech Republic
| | - Janette Bobalova
- Institute of Analytical Chemistry of the CAS, Veveří 97, 602 00 Brno, Czech Republic
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13
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Borgmann-Winter KE, Wang K, Bandyopadhyay S, Torshizi AD, Hahn CG, Hahn CG. The proteome and its dynamics: A missing piece for integrative multi-omics in schizophrenia. Schizophr Res 2020; 217:148-161. [PMID: 31416743 PMCID: PMC7500806 DOI: 10.1016/j.schres.2019.07.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 07/10/2019] [Accepted: 07/13/2019] [Indexed: 01/08/2023]
Abstract
The complex and heterogeneous pathophysiology of schizophrenia can be deconstructed by integration of large-scale datasets encompassing genes through behavioral phenotypes. Genome-wide datasets are now available for genetic, epigenetic and transcriptomic variations in schizophrenia, which are then analyzed by newly devised systems biology algorithms. A missing piece, however, is the inclusion of information on the proteome and its dynamics in schizophrenia. Proteomics has lagged behind omics of the genome, transcriptome and epigenome since analytic platforms were relatively less robust for proteins. There has been remarkable progress, however, in the instrumentation of liquid chromatography (LC) and mass spectrometry (MS) (LCMS), experimental paradigms and bioinformatics of the proteome. Here, we present a summary of methodological innovations of recent years in MS based proteomics and the power of new generation proteomics, review proteomics studies that have been conducted in schizophrenia to date, and propose how such data can be analyzed and integrated with other omics results. The function of a protein is determined by multiple molecular properties, i.e., subcellular localization, posttranslational modification (PTMs) and protein-protein interactions (PPIs). Incorporation of these properties poses additional challenges in proteomics and their integration with other omics; yet is a critical next step to close the loop of multi-omics integration. In sum, the recent advent of high-throughput proteome characterization technologies and novel mathematical approaches enable us to incorporate functional properties of the proteome to offer a comprehensive multi-omics based understanding of schizophrenia pathophysiology.
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Affiliation(s)
- Karin E. Borgmann-Winter
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104-3403,Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, PA 19104
| | - Kai Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104,Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104
| | | | - Abolfazl Doostparast Torshizi
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104
| | - Chang-Gyu Hahn
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104-3403, United States of America.
| | - Chang-Gyu Hahn
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104-3403, United States of America.
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14
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Parsons J, Francavilla C. 'Omics Approaches to Explore the Breast Cancer Landscape. Front Cell Dev Biol 2020; 7:395. [PMID: 32039208 PMCID: PMC6987401 DOI: 10.3389/fcell.2019.00395] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 12/30/2019] [Indexed: 12/24/2022] Open
Abstract
Breast cancer incidence is increasing worldwide with more than 600,000 deaths reported in 2018 alone. In current practice treatment options for breast cancer patients consists of surgery, chemotherapy, radiotherapy or targeting of classical markers of breast cancer subtype: estrogen receptor (ER) and HER2. However, these treatments fail to prevent recurrence and metastasis. Improved understanding of breast cancer and metastasis biology will help uncover novel biomarkers and therapeutic opportunities to improve patient stratification and treatment. We will first provide an overview of current methods and models used to study breast cancer biology, focusing on 2D and 3D cell culture, including organoids, and on in vivo models such as the MMTV mouse model and patient-derived xenografts (PDX). Next, genomic, transcriptomic, and proteomic approaches and their integration will be considered in the context of breast cancer susceptibility, breast cancer drivers, and therapeutic response and resistance to treatment. Finally, we will discuss how 'Omics datasets in combination with traditional breast cancer models are useful for generating insights into breast cancer biology, for suggesting individual treatments in precision oncology, and for creating data repositories to undergo further meta-analysis. System biology has the potential to catalyze the next great leap forward in treatment options for breast cancer patients.
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Affiliation(s)
- Joseph Parsons
- Division of Molecular and Cellular Function, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Chiara Francavilla
- Division of Molecular and Cellular Function, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom
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15
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Scott DA, Drake RR. Glycosylation and its implications in breast cancer. Expert Rev Proteomics 2019; 16:665-680. [PMID: 31314995 PMCID: PMC6702063 DOI: 10.1080/14789450.2019.1645604] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 07/15/2019] [Indexed: 02/07/2023]
Abstract
Introduction: For decades, the role of glycans and glycoproteins in the progression of breast cancer and other cancers have been evaluated. Through extensive studies focused on elucidating the biological functions of glycosylation, researchers have been able to implicate alterations in these functions to tumor formation and metastasis. Areas covered: In this review, we summarize how changes in glycosylation are associated with tumorigenesis, with emphasis on breast cancers. An overview of the changes in N-linked and O-linked glycans associated with breast cancer tumors and biofluids are described. Recent advances in glycomics are emphasized in the context of continuing to decipher the glycosylation changes associated with breast cancer progression. Expert opinion: While changes in glycosylation have been studied in breast cancer for many years, the clinical relevance of these studies has been limited. This reflects the inherent biological and clinical heterogeneity of breast cancers. Glycomics analysis lags behind the advances in genomics and proteomics, but new approaches are emerging. A summary of known glycosylation changes associated with breast cancer is necessary to implement new findings in the context of clinical outcomes and therapeutic strategies. A better understanding of the dynamics of tumor and immune glycosylation is critical to improving emerging immunotherapeutic treatments.
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Affiliation(s)
- Danielle A Scott
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC, Proteomics Center, Medical University of South Carolina , Charleston , SC , USA
| | - Richard R Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics and MUSC, Proteomics Center, Medical University of South Carolina , Charleston , SC , USA
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16
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Leal MF, Haynes BP, MacNeill FA, Dodson A, Dowsett M. Comparison of protein expression between formalin-fixed core-cut biopsies and surgical excision specimens using a novel multiplex approach. Breast Cancer Res Treat 2019; 175:317-326. [PMID: 30796652 PMCID: PMC6533418 DOI: 10.1007/s10549-019-05163-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 02/06/2019] [Indexed: 01/03/2023]
Abstract
PURPOSE We evaluated whether multiplex protein quantification using antibody bar-coding with photocleavable oligonucleotides (NanoString) can be applied to evaluate protein expression in breast cancer FFPE specimens. We also assessed whether diagnostic core-cuts fixed immediately at time of procedures and surgical excision sections from routinely fixed breast cancers are affected by the same fixation related differences noted using immunohistochemistry (IHC). METHODS The expression of 26 proteins was analysed using NanoString technology in 16 pairs of FFPE breast cancer core-cuts and surgical excisions. The measurements yielded were compared with those by IHC on Ki67, PgR and HER2 biomarkers and pAKT and pERK1/2 phosphorylated proteins. RESULTS When considered irrespective of sample type, expression measured by the two methods was strongly correlated for all markers (p < 0.001; ρ = 0.69-0.88). When core-cuts and excisions were evaluated separately, the correlations between NanoString and IHC were weaker but significant except for pAKT in excisions. Surgical excisions showed lower levels of 8/12 phosphoproteins and higher levels of 4/13 non-phosphorylated proteins in comparison to core-cuts (p < 0.01). Reduced p4EBP1, pAMPKa, pRPS6 and pRAF1 immunogenicity in excisions was correlated with tumour size and mastectomy specimens showed lower p4EBP1 and pRPS6 expression than lumpectomy (p < 0.05). CONCLUSIONS Our study supports the validity of the new multiplex approach to protein analysis but indicates that, as with IHC, caution is necessary for the analysis in excisions particularly of phosphoproteins. The specimen type, tumour size and surgery type may lead to biases in the quantitative analysis of many proteins of biologic and clinical interest in excision specimens.
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Affiliation(s)
- Mariana Ferreira Leal
- Ralph Lauren Centre for Breast Cancer Research, Royal Marsden Hospital, The Royal Marsden NHS Foundation Trust, 4th Floor Wallace Wing, 203 Fulham Road, London, SW3 6JJ, UK.
- Breast Cancer Now Research Centre, The Institute of Cancer Research, Fulham Road, London, SW3 6JB, UK.
| | - Ben P Haynes
- Ralph Lauren Centre for Breast Cancer Research, Royal Marsden Hospital, The Royal Marsden NHS Foundation Trust, 4th Floor Wallace Wing, 203 Fulham Road, London, SW3 6JJ, UK
| | - Fiona A MacNeill
- Breast Unit, The Royal Marsden NHS Foundation Trust, Fulham Road, London, SW3 6JJ, UK
| | - Andrew Dodson
- Ralph Lauren Centre for Breast Cancer Research, Royal Marsden Hospital, The Royal Marsden NHS Foundation Trust, 4th Floor Wallace Wing, 203 Fulham Road, London, SW3 6JJ, UK
| | - Mitch Dowsett
- Ralph Lauren Centre for Breast Cancer Research, Royal Marsden Hospital, The Royal Marsden NHS Foundation Trust, 4th Floor Wallace Wing, 203 Fulham Road, London, SW3 6JJ, UK
- Breast Cancer Now Research Centre, The Institute of Cancer Research, Fulham Road, London, SW3 6JB, UK
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17
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Barnabas GD, Bahar-Shany K, Sapoznik S, Helpman L, Kadan Y, Beiner M, Weitzner O, Arbib N, Korach J, Perri T, Katz G, Blecher A, Brandt B, Friedman E, Stockheim D, Jakobson-Setton A, Eitan R, Armon S, Brand H, Zadok O, Aviel-Ronen S, Harel M, Geiger T, Levanon K. Microvesicle Proteomic Profiling of Uterine Liquid Biopsy for Ovarian Cancer Early Detection. Mol Cell Proteomics 2019; 18:865-875. [PMID: 30760538 DOI: 10.1074/mcp.ra119.001362] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Indexed: 12/28/2022] Open
Abstract
High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.
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Affiliation(s)
- Georgina D Barnabas
- From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Keren Bahar-Shany
- §Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel;; From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Stav Sapoznik
- §Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Limor Helpman
- ¶Division of Gynecologic Oncology, Meir Medical Center, Kfar Saba, Israel;; ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Yfat Kadan
- ¶Division of Gynecologic Oncology, Meir Medical Center, Kfar Saba, Israel
| | - Mario Beiner
- ¶Division of Gynecologic Oncology, Meir Medical Center, Kfar Saba, Israel
| | - Omer Weitzner
- **Department of Obstetrics and Gynecology, Meir Medical Center, Kfar Saba, Israel
| | - Nissim Arbib
- **Department of Obstetrics and Gynecology, Meir Medical Center, Kfar Saba, Israel
| | - Jacob Korach
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ‡‡Department of Gynecologic Oncology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Tamar Perri
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ‡‡Department of Gynecologic Oncology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Guy Katz
- ‡‡Department of Gynecologic Oncology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Anna Blecher
- ‡‡Department of Gynecologic Oncology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Benny Brandt
- ‡‡Department of Gynecologic Oncology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Eitan Friedman
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; §§The Susanne-Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - David Stockheim
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ¶¶Department of Gynecology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Ariella Jakobson-Setton
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ‖‖Department of Gynecologic Oncology, Rabin Medical Center, Petah Tikva, Israel
| | - Ram Eitan
- ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ‖‖Department of Gynecologic Oncology, Rabin Medical Center, Petah Tikva, Israel
| | - Shunit Armon
- ‡‡‡Department of Obstetrics & Gynecology, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Hadar Brand
- §Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel;; ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Oranit Zadok
- §§§Department of Pathology, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Sarit Aviel-Ronen
- §§§Department of Pathology, Chaim Sheba Medical Center, Ramat Gan, Israel;; ¶¶¶The Talpiot Medical Leadership Program, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Michal Harel
- From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Tamar Geiger
- From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;.
| | - Keren Levanon
- §Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel;; ‖Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;; ¶¶¶The Talpiot Medical Leadership Program, Chaim Sheba Medical Center, Ramat Gan, Israel; From the ‡Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel;.
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18
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Orlando E, Aebersold R. On the contribution of mass spectrometry-based platforms to the field of personalized oncology. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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19
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Pinker K, Chin J, Melsaether AN, Morris EA, Moy L. Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment. Radiology 2018; 287:732-747. [PMID: 29782246 DOI: 10.1148/radiol.2018172171] [Citation(s) in RCA: 168] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer. © RSNA, 2018.
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Affiliation(s)
- Katja Pinker
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P., J.C., E.A.M.); and Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York University of Medicine, 160 E 34th St, New York, NY 10016 (A.N.M., L.M.)
| | - Joanne Chin
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P., J.C., E.A.M.); and Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York University of Medicine, 160 E 34th St, New York, NY 10016 (A.N.M., L.M.)
| | - Amy N Melsaether
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P., J.C., E.A.M.); and Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York University of Medicine, 160 E 34th St, New York, NY 10016 (A.N.M., L.M.)
| | - Elizabeth A Morris
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P., J.C., E.A.M.); and Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York University of Medicine, 160 E 34th St, New York, NY 10016 (A.N.M., L.M.)
| | - Linda Moy
- From the Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY (K.P., J.C., E.A.M.); and Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York University of Medicine, 160 E 34th St, New York, NY 10016 (A.N.M., L.M.)
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20
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Henry KE, Ulaner GA, Lewis JS. Clinical Potential of Human Epidermal Growth Factor Receptor 2 and Human Epidermal Growth Factor Receptor 3 Imaging in Breast Cancer. PET Clin 2018; 13:423-435. [PMID: 30100080 PMCID: PMC6092024 DOI: 10.1016/j.cpet.2018.02.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Increased expression of the human epidermal growth factor receptor (HER) protein family are targets in breast cancer for imaging and therapy. Imaging modalities targeting HER2 and HER3 can diagnose breast cancer with a specific, biologically relevant target. Repeat biopsies do not address heterogeneity intratumorally or between primary disease and metastasis. HER2- and HER3-targeted PET is an important tool to diagnose disease in breast cancer and evaluate response to targeted therapies. PET and single photon emission computed tomography with radiolabeled biomolecules can be used to detect and quantify specific targets, conferring a better understanding of the behavior and effectiveness of treatments.
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Affiliation(s)
- Kelly E Henry
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - Gary A Ulaner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Radiology, Weill Cornell Medical College, 1275 York Avenue, New York, NY 10065, USA
| | - Jason S Lewis
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Radiology, Weill Cornell Medical College, 1275 York Avenue, New York, NY 10065, USA; Program in Molecular Pharmacology and Chemistry, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Pharmacology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA; Radiochemistry and Molecular Imaging Probes Core, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
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21
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Abundant plasma protein depletion using ammonium sulfate precipitation and Protein A affinity chromatography. J Chromatogr B Analyt Technol Biomed Life Sci 2018; 1089:43-59. [PMID: 29758408 DOI: 10.1016/j.jchromb.2018.04.045] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 04/10/2018] [Accepted: 04/26/2018] [Indexed: 11/23/2022]
Abstract
Plasma is a highly valuable resource for biomarker research since it is easy obtainable and contains a high amount of information on patient health status. Although advancements in the field of proteomics enabled analysis of the plasma proteome, identification of low abundant proteins remains challenging due to high complexity and large dynamic range. In order to reduce the dynamic range of protein concentrations, a tandem depletion technique consisting of ammonium sulfate precipitation and Protein A affinity chromatography was developed. Using this method, 50% of albumin, together with other high abundant proteins such as alpha-1-antitrypsin, was depleted from the plasma sample at 20% to 40% ammonium sulfate saturation levels. In combination with immunoglobulin removal using a Protein A column, this technique delivered up to 40 new low- to medium abundance protein identifications when performing a shotgun mass spectrometry analysis. Compared to non-depleted plasma, 270 additional protein spots were observed during 2D-PAGE analysis. These results illustrate that this tandem depletion method is equivalent to commercial kits which are based on immune-affinity chromatography. Moreover, this method using Protein A immunoglobulin depletion was shown to be highly reproducible and a minimal amount of non-target proteins was depleted. The combination of ammonium sulfate precipitation and Protein A affinity chromatography offers a low cost, efficient, straightforward and reproducible alternative to commercial kits, with proteins remaining in native conformation, allowing protein activity and protein interaction studies.
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22
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Coleman WB. Next-Generation Breast Cancer Omics. THE AMERICAN JOURNAL OF PATHOLOGY 2017; 187:2130-2132. [PMID: 28822804 DOI: 10.1016/j.ajpath.2017.07.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 07/21/2017] [Accepted: 07/27/2017] [Indexed: 12/20/2022]
Abstract
This Editorial highlights the reviews in the Breast Cancer Theme Issue that features topics related to next-generation breast cancer omics.
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Affiliation(s)
- William B Coleman
- Department of Pathology and Laboratory Medicine, UNC Program in Translational Medicine, UNC Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
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