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1
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Feliu J, Gámez-Pozo A, Martínez-Pérez D, Pérez-Wert P, Matamala-Luengo D, Viñal D, Kunz L, López-Vacas R, Dittmann A, Rodríguez-Salas N, Custodio A, Fresno Vara JÁ, Trilla-Fuertes L. Functional proteomics of colon cancer Consensus Molecular Subtypes. Br J Cancer 2024; 130:1670-1678. [PMID: 38486123 DOI: 10.1038/s41416-024-02650-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/26/2024] [Accepted: 03/01/2024] [Indexed: 05/15/2024] Open
Abstract
BACKGROUND The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, only MSI tumour patients have seen a change in their disease management in clinical practice. This study aims to characterise the proteome of colon cancer CMS and broaden CMS's clinical utility. METHODS One-hundred fifty-eight paraffin samples from stage II-III colon cancer patients treated with adjuvant chemotherapy were analysed through DIA-based mass-spectrometry proteomics. RESULTS CMS1 exhibited overexpression of immune-related proteins, specifically related to neutrophils, phagocytosis, antimicrobial response, and a glycolytic profile. These findings suggested potential therapeutic strategies involving immunotherapy and glycolytic inhibitors. CMS3 showed overexpression of metabolic proteins. CMS2 displayed a heterogeneous protein profile. Notably, two proteomics subtypes within CMS2, with different protein characteristics and prognoses, were identified. CMS4 emerged as the most distinct group, featuring overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. CMS4 showed a high metastatic profile and suggested possible chemoresistance that may explain its worse prognosis. CONCLUSIONS DIA proteomics revealed new features for each colon cancer CMS subtype. These findings provide valuable insights into potential therapeutic targets for colorectal cancer subtypes in the future.
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Affiliation(s)
- Jaime Feliu
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain.
- Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Madrid, Spain.
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.
| | - Angelo Gámez-Pozo
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Daniel Martínez-Pérez
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Pablo Pérez-Wert
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | | | - David Viñal
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Laura Kunz
- Functional Genomics Center Zurich, Zurich, Switzerland
| | - Rocío López-Vacas
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | | | - Nuria Rodríguez-Salas
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Ana Custodio
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
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2
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Trilla-Fuertes L, Gámez-Pozo A, Prado-Vázquez G, López-Vacas R, Soriano V, Garicano F, Lecumberri MJ, Rodríguez de la Borbolla M, Majem M, Pérez-Ruiz E, González-Cao M, Oramas J, Magdaleno A, Fra J, Martín-Carnicero A, Corral M, Puértolas T, Ramos-Ruiz R, Dittmann A, Nanni P, Fresno Vara JÁ, Espinosa E. Multi-omics Characterization of Response to PD-1 Inhibitors in Advanced Melanoma. Cancers (Basel) 2023; 15:4407. [PMID: 37686682 PMCID: PMC10486782 DOI: 10.3390/cancers15174407] [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: 07/25/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/10/2023] Open
Abstract
Immunotherapy improves the survival of patients with advanced melanoma, 40% of whom become long-term responders. However, not all patients respond to immunotherapy. Further knowledge of the processes involved in the response and resistance to immunotherapy is still needed. In this study, clinical paraffin samples from fifty-two advanced melanoma patients treated with anti-PD-1 inhibitors were assessed via high-throughput proteomics and RNA-seq. The obtained proteomics and transcriptomics data were analyzed using multi-omics network analyses based on probabilistic graphical models to identify those biological processes involved in the response to immunotherapy. Additionally, proteins related to overall survival were studied. The activity of the node formed by the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation machinery was higher in responders compared to non-responders; the activity of the immune and inflammatory response node was also higher in those with complete or partial responses. A predictor for overall survival based on two proteins (AMBP and PDSM5) was defined. In summary, the response to anti-PD-1 therapy in advanced melanoma is related to protein processing in the endoplasmic reticulum, and also to genes involved in the immune and inflammatory responses. Finally, a two-protein predictor can define survival in advanced disease. The molecular characterization of the mechanisms involved in the response and resistance to immunotherapy in melanoma leads the way to establishing therapeutic alternatives for patients who will not respond to this treatment.
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Affiliation(s)
- Lucía Trilla-Fuertes
- Molecular Oncology Laboratory, Hospital Universitario La Paz-IdiPAZ, 28046 Madrid, Spain; (L.T.-F.); (A.G.-P.); (G.P.-V.); (R.L.-V.); (J.Á.F.V.)
| | - Angelo Gámez-Pozo
- Molecular Oncology Laboratory, Hospital Universitario La Paz-IdiPAZ, 28046 Madrid, Spain; (L.T.-F.); (A.G.-P.); (G.P.-V.); (R.L.-V.); (J.Á.F.V.)
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain
| | - Guillermo Prado-Vázquez
- Molecular Oncology Laboratory, Hospital Universitario La Paz-IdiPAZ, 28046 Madrid, Spain; (L.T.-F.); (A.G.-P.); (G.P.-V.); (R.L.-V.); (J.Á.F.V.)
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain
| | - Rocío López-Vacas
- Molecular Oncology Laboratory, Hospital Universitario La Paz-IdiPAZ, 28046 Madrid, Spain; (L.T.-F.); (A.G.-P.); (G.P.-V.); (R.L.-V.); (J.Á.F.V.)
| | - Virtudes Soriano
- Instituto Valenciano de Oncología, 46009 Valencia, Spain;
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
| | - Fernando Garicano
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital de Galdakao, 48960 Galdakao, Spain
| | - M. José Lecumberri
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Complejo Hospitalario de Navarra, 31008 Pamplona, Spain
| | - María Rodríguez de la Borbolla
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital de Valme, 41014 Sevilla, Spain
| | - Margarita Majem
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital de la Santa Creu i Sant Pau, 08001 Barcelona, Spain
| | - Elisabeth Pérez-Ruiz
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Unidad de Gestión Clínica Intercentros (UGCI) de Oncología Médica, Hospitales Universitarios Regional y Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospitales Universitarios Regional y Virgen de la Victoria, 29010 Málaga, Spain
| | - María González-Cao
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Quirón Dexeus, 08028 Barcelona, Spain
| | - Juana Oramas
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Universitario de Canarias-San Cristóbal de la Laguna, 38320 Tenerife, Spain
| | - Alejandra Magdaleno
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Universitario de Elche y Vega Baja, 03203 Alicante, Spain
| | - Joaquín Fra
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Universitario Río Hortega, 47012 Valladolid, Spain
| | - Alfonso Martín-Carnicero
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital San Pedro, 27347 Logroño, Spain
| | - Mónica Corral
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Clínico Lozano Blesa, 50009 Zaragoza, Spain
| | - Teresa Puértolas
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain
| | | | - Antje Dittmann
- Functional Genomics Center Zurich, University/ETH Zurich, 8092 Zurich, Switzerland; (A.D.); (P.N.)
| | - Paolo Nanni
- Functional Genomics Center Zurich, University/ETH Zurich, 8092 Zurich, Switzerland; (A.D.); (P.N.)
| | - Juan Ángel Fresno Vara
- Molecular Oncology Laboratory, Hospital Universitario La Paz-IdiPAZ, 28046 Madrid, Spain; (L.T.-F.); (A.G.-P.); (G.P.-V.); (R.L.-V.); (J.Á.F.V.)
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain
- CIBERONC, ISCIII, 28222 Madrid, Spain
| | - Enrique Espinosa
- Spanish Melanoma Group (GEM), 08024 Barcelona, Spain; (F.G.); (M.J.L.); (M.R.d.l.B.); (M.M.); (E.P.-R.); (M.G.-C.); (J.O.); (A.M.); (J.F.); (M.C.); (T.P.)
- CIBERONC, ISCIII, 28222 Madrid, Spain
- Medical Oncology Service, Hospital Universitario La Paz, 28046 Madrid, Spain
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Punetha A, Kotiya D. Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice. Proteomes 2023; 11:2. [PMID: 36648960 PMCID: PMC9844371 DOI: 10.3390/proteomes11010002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/12/2023] Open
Abstract
Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.
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Affiliation(s)
- Ankita Punetha
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Rutgers University, 225 Warren St., Newark, NJ 07103, USA
| | - Deepak Kotiya
- Department of Pharmacology and Nutritional Sciences, University of Kentucky, 900 South Limestone St., Lexington, KY 40536, USA
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4
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García-Adrián S, Trilla-Fuertes L, Gámez-Pozo A, Chiva C, López-Vacas R, López-Camacho E, Zapater-Moros A, Lumbreras-Herrera MI, Hardisson D, Yébenes L, Zamora P, Sabidó E, Fresno Vara JÁ, Espinosa E. Molecular characterization of triple negative breast cancer formaldehyde-fixed paraffin-embedded samples by data-independent acquisition proteomics. Proteomics 2021; 22:e2100110. [PMID: 34624180 DOI: 10.1002/pmic.202100110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 09/14/2021] [Accepted: 09/29/2021] [Indexed: 11/05/2022]
Abstract
Triple negative breast cancer accounts for 15%-20% of all breast carcinomas and is clinically characterized by an aggressive phenotype and poor prognosis. Triple negative tumors do not benefit from targeted therapies, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of 125 formalin-fixed paraffin-embedded samples from patients diagnosed with non-metastatic triple negative breast cancer were analyzed using data-independent acquisition + in a LTQ-Orbitrap Fusion Lumos mass spectrometer coupled to an EASY-nLC 1000. 1206 proteins were identified in at least 66% of the samples. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were combined to characterize proteomics-based molecular groups. Two molecular groups were defined with differences in biological processes such as glycolysis, translation and immune response. These two molecular groups showed also several differentially expressed proteins. This clinically homogenous dataset may serve to design new therapeutic strategies in the future.
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Affiliation(s)
| | | | - Angelo Gámez-Pozo
- Molecular Oncology and Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Cristina Chiva
- Proteomics Unit, Center for Genomics Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Proteomics Unit, Universitat Pompeu Fabra, Barcelona, Spain
| | - Rocío López-Vacas
- Molecular Oncology and Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | | | | | - María I Lumbreras-Herrera
- Molecular Oncology and Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - David Hardisson
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), Madrid, Spain.,Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.,Faculty of Medicine, Universidad Autónoma de Madrid, Madrid, Spain.,Department of Pathology, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Laura Yébenes
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), Madrid, Spain
| | - Pilar Zamora
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.,Medical Oncology Service, La Paz University Hospital-IdiPAZ, Madrid, Spain.,Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Madrid, Spain
| | - Eduard Sabidó
- Proteomics Unit, Center for Genomics Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Proteomics Unit, Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology and Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain.,Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
| | - Enrique Espinosa
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.,Medical Oncology Service, La Paz University Hospital-IdiPAZ, Madrid, Spain.,Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Madrid, Spain
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5
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Rossouw SC, Bendou H, Blignaut RJ, Bell L, Rigby J, Christoffels A. Evaluation of Protein Purification Techniques and Effects of Storage Duration on LC-MS/MS Analysis of Archived FFPE Human CRC Tissues. Pathol Oncol Res 2021; 27:622855. [PMID: 34257588 PMCID: PMC8262168 DOI: 10.3389/pore.2021.622855] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 03/01/2021] [Indexed: 12/17/2022]
Abstract
To elucidate cancer pathogenesis and its mechanisms at the molecular level, the collecting and characterization of large individual patient tissue cohorts are required. Since most pathology institutes routinely preserve biopsy tissues by standardized methods of formalin fixation and paraffin embedment, these archived FFPE tissues are important collections of pathology material that include patient metadata, such as medical history and treatments. FFPE blocks can be stored under ambient conditions for decades, while retaining cellular morphology, due to modifications induced by formalin. However, the effect of long-term storage, at resource-limited institutions in developing countries, on extractable protein quantity/quality has not yet been investigated. In addition, the optimal sample preparation techniques required for accurate and reproducible results from label-free LC-MS/MS analysis across block ages remains unclear. This study investigated protein extraction efficiency of 1, 5, and 10-year old human colorectal carcinoma resection tissue and assessed three different gel-free protein purification methods for label-free LC-MS/MS analysis. A sample size of n = 17 patients per experimental group (with experiment power = 0.7 and α = 0.05, resulting in 70% confidence level) was selected. Data were evaluated in terms of protein concentration extracted, peptide/protein identifications, method reproducibility and efficiency, sample proteome integrity (due to storage time), as well as protein/peptide distribution according to biological processes, cellular components, and physicochemical properties. Data are available via ProteomeXchange with identifier PXD017198. The results indicate that the amount of protein extracted is significantly dependent on block age (p < 0.0001), with older blocks yielding less protein than newer blocks. Detergent removal plates were the most efficient and overall reproducible protein purification method with regard to number of peptide and protein identifications, followed by the MagReSyn® SP3/HILIC method (with on-bead enzymatic digestion), and lastly the acetone precipitation and formic acid resolubilization method. Overall, the results indicate that long-term storage of FFPE tissues (as measured by methionine oxidation) does not considerably interfere with retrospective proteomic analysis (p > 0.1). Block age mainly affects initial protein extraction yields and does not extensively impact on subsequent label-free LC-MS/MS analysis results.
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Affiliation(s)
- Sophia C. Rossouw
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Hocine Bendou
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Renette J. Blignaut
- Department of Statistics and Population Studies, University of the Western Cape, Bellville, South Africa
| | - Liam Bell
- Centre for Proteomic and Genomic Research, Observatory, Cape Town, South Africa
| | - Jonathan Rigby
- Division of Anatomical Pathology, Department of Pathology, Faculty of Health Sciences, University of Stellenbosch, National Health Laboratory Service, Tygerberg Hospital, Cape Town, South Africa
| | - Alan Christoffels
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
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6
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Trilla-Fuertes L, Gámez-Pozo A, Arevalillo JM, López-Vacas R, López-Camacho E, Prado-Vázquez G, Zapater-Moros A, Díaz-Almirón M, Ferrer-Gómez M, Navarro H, Nanni P, Zamora P, Espinosa E, Maín P, Fresno Vara JÁ. Bayesian networks established functional differences between breast cancer subtypes. PLoS One 2020; 15:e0234752. [PMID: 32525929 PMCID: PMC7289386 DOI: 10.1371/journal.pone.0234752] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 06/01/2020] [Indexed: 12/15/2022] Open
Abstract
Breast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. In previous works, our group defined a new hormonal receptor positive subgroup, the TN-like subtype, which had a prognosis and a molecular profile more similar to triple negative tumors. In this study, proteomics and Bayesian networks were used to characterize protein relationships in 96 breast tumor samples. Components obtained by these methods had a clear functional structure. The analysis of these components suggested differences in processes such as mitochondrial function or extracellular matrix between breast cancer subtypes, including our new defined subtype TN-like. In addition, one of the components, mainly related with extracellular matrix processes, had prognostic value in this cohort. Functional approaches allow to build hypotheses about regulatory mechanisms and to establish new relationships among proteins in the breast cancer context.
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Affiliation(s)
| | - Angelo Gámez-Pozo
- Biomedica Molecular Medicine SL, Madrid, Spain
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Jorge M. Arevalillo
- Operational Research and Numerical Analysis, National Distance Education University (UNED), Madrid, Spain
| | - Rocío López-Vacas
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | | | - Guillermo Prado-Vázquez
- Biomedica Molecular Medicine SL, Madrid, Spain
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Andrea Zapater-Moros
- Biomedica Molecular Medicine SL, Madrid, Spain
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | | | - María Ferrer-Gómez
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Hilario Navarro
- Operational Research and Numerical Analysis, National Distance Education University (UNED), Madrid, Spain
| | - Paolo Nanni
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | - Pilar Zamora
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Enrique Espinosa
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Madrid, Spain
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
| | - Paloma Maín
- Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Biomedica Molecular Medicine SL, Madrid, Spain
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
- * E-mail:
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7
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Trilla-Fuertes L, Ghanem I, Gámez-Pozo A, Maurel J, G-Pastrián L, Mendiola M, Peña C, López-Vacas R, Prado-Vázquez G, López-Camacho E, Zapater-Moros A, Heredia V, Cuatrecasas M, García-Alfonso P, Capdevila J, Conill C, García-Carbonero R, Ramos-Ruiz R, Fortes C, Llorens C, Nanni P, Fresno Vara JÁ, Feliu J. Genetic Profile and Functional Proteomics of Anal Squamous Cell Carcinoma: Proposal for a Molecular Classification. Mol Cell Proteomics 2020; 19:690-700. [PMID: 32107283 PMCID: PMC7124473 DOI: 10.1074/mcp.ra120.001954] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Indexed: 12/21/2022] Open
Abstract
Anal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed. High-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groups de novo Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level. A molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The functional analysis by the probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such as ATM, SLFN11 and DST Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy.
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Affiliation(s)
| | - Ismael Ghanem
- Medical Oncology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Angelo Gámez-Pozo
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Joan Maurel
- Medical Oncology Department, Hospital Clinic of Barcelona, Translational Genomics and Targeted Therapeutics in Solid Tumors Group, IDIBAPS, University of Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain
| | - Laura G-Pastrián
- Pathology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain; Molecular Pathology and Therapeutic Targets Group, Hospital Universitario La Paz-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Marta Mendiola
- Molecular Pathology and Therapeutic Targets Group, Hospital Universitario La Paz-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain; Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Cristina Peña
- Pathology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Rocío López-Vacas
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | | | - Elena López-Camacho
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Andrea Zapater-Moros
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Victoria Heredia
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Translational Oncology Lab, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Miriam Cuatrecasas
- Pathology Department, Hospital Clínic Universitari de Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain
| | - Pilar García-Alfonso
- Medical Oncology Department, Hospital General Universitario Gregorio Marañón, /Dr. Esquerdo 46, 28007, Madrid, Spain
| | - Jaume Capdevila
- Medical Oncology Service, Vall Hebron University Hospital. Vall Hebron Institute of Oncology (VHIO), Paseigg de la Vall d'Hebron 119, 08035, Barcelona, Spain
| | - Carles Conill
- Radiotherapy Oncology Department, Hospital Clínic Universitari de Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain
| | - Rocío García-Carbonero
- Medical Oncology Service, Hospital Universitario 12 de Ocubre, Av. de Córdoba s/n, 28041, Madrid, Spain
| | - Ricardo Ramos-Ruiz
- Genomics Unit Cantoblanco, Parque Científico de Madrid, C/ Faraday 7, 28049, Madrid, Spain
| | - Claudia Fortes
- Functional Genomics Center Zurich, University of Zurich/ETH Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Carlos Llorens
- Biotechvana SL, Parque Científico de Madrid, C/ Faraday 7, 28049, Madrid, Spain
| | - Paolo Nanni
- Functional Genomics Center Zurich, University of Zurich/ETH Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Juan Ángel Fresno Vara
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz -IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain; Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Jaime Feliu
- Medical Oncology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain; Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain.
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8
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Trilla-Fuertes L, Gámez-Pozo A, Díaz-Almirón M, Prado-Vázquez G, Zapater-Moros A, López-Vacas R, Nanni P, Zamora P, Espinosa E, Fresno Vara JÁ. Computational metabolism modeling predicts risk of distant relapse-free survival in breast cancer patients. Future Oncol 2019; 15:3483-3490. [PMID: 31580166 DOI: 10.2217/fon-2018-0698] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Aim: Differences in metabolism among breast cancer subtypes suggest that metabolism plays an important role in this disease. Flux balance analysis is used to explore these differences as well as drug response. Materials & methods: Proteomics data from breast tumors were obtained by mass-spectrometry. Flux balance analysis was performed to study metabolic networks. Flux activities from metabolic pathways were calculated and used to build prognostic models. Results: Flux activities of vitamin A, tetrahydrobiopterin and β-alanine metabolism pathways split our population into low- and high-risk patients. Additionally, flux activities of glycolysis and glutamate metabolism split triple negative tumors into low- and high-risk groups. Conclusion: Flux activities summarize flux balance analysis data and can be associated with prognosis in cancer.
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Affiliation(s)
| | - Angelo Gámez-Pozo
- Biomedica Molecular Medicine SL, C/ Faraday 7, Madrid 28049, Spain.,Molecular Oncology & Pathology Lab, Institute of Medical & Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain
| | - Mariana Díaz-Almirón
- Biostatistics Unit, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain
| | | | - Andrea Zapater-Moros
- Molecular Oncology & Pathology Lab, Institute of Medical & Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain
| | - Rocío López-Vacas
- Molecular Oncology & Pathology Lab, Institute of Medical & Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain
| | - Paolo Nanni
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Pilar Zamora
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain.,Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, Madrid 28049, Spain.,Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, C/ Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Enrique Espinosa
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain.,Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, Madrid 28049, Spain.,Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, C/ Melchor Fernández Almagro, 3, Madrid 28029, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology & Pathology Lab, Institute of Medical & Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, Madrid 28046, Spain.,Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, C/ Melchor Fernández Almagro, 3, Madrid 28029, Spain
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9
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Melanoma proteomics suggests functional differences related to mutational status. Sci Rep 2019; 9:7217. [PMID: 31076580 PMCID: PMC6510784 DOI: 10.1038/s41598-019-43512-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 04/23/2019] [Indexed: 12/13/2022] Open
Abstract
Melanoma is the most lethal cutaneous cancer. New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between melanoma tumor subtypes, based on BRAF and NRAS mutational status. Fourteen formalin-fixed, paraffin-embedded melanoma samples were analyzed using a high-throughput proteomics approach, combined with probabilistic graphical models and Flux Balance Analysis, to characterize these differences. Proteomics analyses showed differences in expression of proteins related with fatty acid metabolism, melanogenesis and extracellular space between BRAF mutated and BRAF non-mutated melanoma tumors. Additionally, probabilistic graphical models showed differences between melanoma subgroups at biological processes such as melanogenesis or metabolism. On the other hand, Flux Balance Analysis predicts a higher tumor growth rate in BRAF mutated melanoma samples. In conclusion, differential biological processes between melanomas showing a specific mutational status can be detected using combined proteomics and computational approaches.
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10
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Rojas L K, Trilla-Fuertes L, Gámez-Pozo A, Chiva C, Sepúlveda J, Manso L, Prado-Vázquez G, Zapater-Moros A, López-Vacas R, Ferrer-Gómez M, Mendiola C, Espinosa E, Sabidó E, Ciruelos E, Vara JÁF. Proteomics characterisation of central nervous system metastasis biomarkers in triple negative breast cancer. Ecancermedicalscience 2019; 13:891. [PMID: 30792808 PMCID: PMC6369972 DOI: 10.3332/ecancer.2019.891] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Indexed: 01/05/2023] Open
Abstract
Background Breast cancer (BC) is the most frequent tumour in women. Triple negative tumours (TNBC)-which are associated with minor survival rates-lack markers predictive of response to anticancer drugs. Triple negative tumours frequently metastasise to the central nervous system (CNS). Objective The main objective of this study was to study differences in tumour protein expression between patients with CNS metastases and those without this kind of spread, and propose new biomarkers. Methods A retrospective study was performed. Targeted proteomics and statistical analyses were used to identify possible biomarkers. Results Proteins were quantified by a targeted proteomics approach and protein expression data were successfully obtained from 51 triple negative formalin-fixed paraffin-embedded samples. ISG15, THBS1 and AP1M1 were identified as possible biomarkers related with CNS metastasis development. Conclusions Three possible biomarkers associated with CNS metastases in TNBC tumours were identified: ISG15, THBS1 and AP1M1. They may become markers predicting the appearance of CNS infiltration in triple negative BC.
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Affiliation(s)
- Katerin Rojas L
- Department of Medical Oncology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain.,Katerin L Rojas and Lucía Trilla-Fuertes contributed equally to this work
| | - Lucía Trilla-Fuertes
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain.,Katerin L Rojas and Lucía Trilla-Fuertes contributed equally to this work
| | - Angelo Gámez-Pozo
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain.,Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain
| | - Cristina Chiva
- Proteomics Unit, Center of Genomics Regulation, Barcelona Institute of Science and Technology, 08036 Barcelona, Spain.,Proteomics Unit, Universitat Pompeu Fabra, 08002 Barcelona, Spain
| | - Juan Sepúlveda
- Department of Medical Oncology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain
| | - Luis Manso
- Department of Medical Oncology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain
| | - Guillermo Prado-Vázquez
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain.,Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain
| | - Andrea Zapater-Moros
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain.,Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain
| | - Rocío López-Vacas
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain
| | - María Ferrer-Gómez
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain
| | - César Mendiola
- Department of Medical Oncology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain
| | - Enrique Espinosa
- Medical Oncology Service, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain.,CIBERONC, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Eduard Sabidó
- Proteomics Unit, Center of Genomics Regulation, Barcelona Institute of Science and Technology, 08036 Barcelona, Spain.,Proteomics Unit, Universitat Pompeu Fabra, 08002 Barcelona, Spain
| | - Eva Ciruelos
- Department of Medical Oncology, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain
| | - Juan Ángel Fresno Vara
- Biomedica Molecular Medicine SL, 28049 Madrid, Spain.,Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, 28029 Madrid, Spain.,CIBERONC, Instituto de Salud Carlos III, 28029 Madrid, Spain
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11
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de Velasco G, Trilla-Fuertes L, Gamez-Pozo A, Urbanowicz M, Ruiz-Ares G, Sepúlveda JM, Prado-Vazquez G, Arevalillo JM, Zapater-Moros A, Navarro H, Lopez-Vacas R, Manneh R, Otero I, Villacampa F, Paramio JM, Vara JAF, Castellano D. Urothelial cancer proteomics provides both prognostic and functional information. Sci Rep 2017; 7:15819. [PMID: 29150671 PMCID: PMC5694001 DOI: 10.1038/s41598-017-15920-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Accepted: 11/01/2017] [Indexed: 11/24/2022] Open
Abstract
Traditionally, bladder cancer has been classified based on histology features. Recently, some works have proposed a molecular classification of invasive bladder tumors. To determine whether proteomics can define molecular subtypes of muscle invasive urothelial cancer (MIUC) and allow evaluating the status of biological processes and its clinical value. 58 MIUC patients who underwent curative surgical resection at our institution between 2006 and 2012 were included. Proteome was evaluated by high-throughput proteomics in routinely archive FFPE tumor tissue. New molecular subgroups were defined. Functional structure and individual proteins prognostic value were evaluated and correlated with clinicopathologic parameters. 1,453 proteins were quantified, leading to two MIUC molecular subgroups. A protein-based functional structure was defined, including several nodes with specific biological activity. The functional structure showed differences between subtypes in metabolism, focal adhesion, RNA and splicing nodes. Focal adhesion node has prognostic value in the whole population. A 6-protein prognostic signature, associated with higher risk of relapse (5 year DFS 70% versus 20%) was defined. Additionally, we identified two MIUC subtypes groups. Prognostic information provided by pathologic characteristics is not enough to understand MIUC behavior. Proteomics analysis may enhance our understanding of prognostic and classification. These findings can lead to improving diagnosis and treatment selection in these patients.
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Affiliation(s)
- Guillermo de Velasco
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain.
| | - Lucia Trilla-Fuertes
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain.,Biomedica Molecular Medicine, Madrid, Spain
| | - Angelo Gamez-Pozo
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain.,Biomedica Molecular Medicine, Madrid, Spain
| | - Maria Urbanowicz
- Department of Pathology, University Hospital 12 de Octubre, Madrid, Spain
| | - Gustavo Ruiz-Ares
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain
| | - Juan M Sepúlveda
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain
| | - Guillermo Prado-Vazquez
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain
| | - Jorge M Arevalillo
- Department of Statistics, Operational Research and Numerical Analysis, University Nacional Educacion a Distancia (UNED), Madrid, Spain
| | - Andrea Zapater-Moros
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain
| | - Hilario Navarro
- Department of Statistics, Operational Research and Numerical Analysis, University Nacional Educacion a Distancia (UNED), Madrid, Spain
| | - Rocio Lopez-Vacas
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain
| | - Ray Manneh
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain
| | - Irene Otero
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain
| | - Felipe Villacampa
- Department of Urology, University Hospital 12 de Octubre, Madrid, Spain.,CIBERONC, Madrid, Spain
| | - Jesus M Paramio
- Molecular and Cell Oncology Group, Biomedical research Institute, University Hospital 12 de Octubre, i + 12, and Molecular Oncology Unit, CIEMAT, Madrid, Spain.,CIBERONC, Madrid, Spain
| | - Juan Angel Fresno Vara
- Molecular Oncology & Pathology Lab, INGEMM, Instituto de Investigación Hospital La Paz-IdiPAZ, Madrid, Spain.,Biomedica Molecular Medicine, Madrid, Spain.,CIBERONC, Madrid, Spain
| | - Daniel Castellano
- Department of Medical Oncology, University Hospital 12 de Octubre, i + 12, Madrid, Spain.,CIBERONC, Madrid, Spain
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12
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Gianazza E, Miller I, Guerrini U, Palazzolo L, Parravicini C, Eberini I. Gender proteomics II. Which proteins in sexual organs. J Proteomics 2017; 178:18-30. [PMID: 28988880 DOI: 10.1016/j.jprot.2017.10.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 09/26/2017] [Accepted: 10/04/2017] [Indexed: 02/08/2023]
Abstract
In continuity with the review dealing with differences by gender in non-sexual organs [1], this review collects data on the proteomes of the sexual organs as involved in human reproduction, under both physiological and pathological conditions. It also collects data on the tissue structures and biological fluids typical of pregnancy, such as placenta and amniotic fluid, as well as what may be tested on preimplantation embryos during medically assisted reproduction. The review includes as well mention to all fluids and secretions connected with sex organs and/or reproduction, including sperm and milk, to exemplify two distinctive items in male and female physiology. SIGNIFICANCE The causes of infertility are only incompletely understood; the same holds for the causes, and even the early markers, of the most frequent complications of pregnancy. To these established medical challenges, present day practice adds new issues connected with medically assisted reproduction. Omics approaches, including proteomics, are building the database for basic knowledge to possibly translate into clinical testing and eventually into medical routine in this critical branch of health care.
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Affiliation(s)
- Elisabetta Gianazza
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via Balzaretti 9, I-20133 Milano, Italy.
| | - Ingrid Miller
- Institut für Medizinische Biochemie, Veterinärmedizinische Universität Wien, Veterinärplatz 1, A-1210 Wien, Austria
| | - Uliano Guerrini
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via Balzaretti 9, I-20133 Milano, Italy
| | - Luca Palazzolo
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via Balzaretti 9, I-20133 Milano, Italy
| | - Chiara Parravicini
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via Balzaretti 9, I-20133 Milano, Italy
| | - Ivano Eberini
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via Balzaretti 9, I-20133 Milano, Italy
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13
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Next-Generation Proteomics and Its Application to Clinical Breast Cancer Research. THE AMERICAN JOURNAL OF PATHOLOGY 2017; 187:2175-2184. [DOI: 10.1016/j.ajpath.2017.07.003] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2017] [Revised: 07/05/2017] [Accepted: 07/06/2017] [Indexed: 12/17/2022]
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14
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Functional proteomics outlines the complexity of breast cancer molecular subtypes. Sci Rep 2017; 7:10100. [PMID: 28855612 PMCID: PMC5577137 DOI: 10.1038/s41598-017-10493-w] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 08/10/2017] [Indexed: 12/30/2022] Open
Abstract
Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.
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15
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Gámez-Pozo A, Trilla-Fuertes L, Prado-Vázquez G, Chiva C, López-Vacas R, Nanni P, Berges-Soria J, Grossmann J, Díaz-Almirón M, Ciruelos E, Sabidó E, Espinosa E, Fresno Vara JÁ. Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics. PLoS One 2017; 12:e0178296. [PMID: 28594844 PMCID: PMC5464546 DOI: 10.1371/journal.pone.0178296] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 05/10/2017] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives. METHODS We analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data. RESULTS Using univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients. CONCLUSIONS This study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.
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Affiliation(s)
- Angelo Gámez-Pozo
- Molecular Oncology & Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
- Biomedica Molecular Medicine SL, Madrid, Spain
| | | | - Guillermo Prado-Vázquez
- Molecular Oncology & Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Cristina Chiva
- Proteomics Unit, Center of Genomics Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Proteomics Unit, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Rocío López-Vacas
- Molecular Oncology & Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Paolo Nanni
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | - Julia Berges-Soria
- Molecular Oncology & Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Jonas Grossmann
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | | | - Eva Ciruelos
- Medical Oncology Service, Instituto de Investigación Hospital Universitario Doce de Octubre-i+12, Madrid, Spain
| | - Eduard Sabidó
- Proteomics Unit, Center of Genomics Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Proteomics Unit, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Enrique Espinosa
- Medical Oncology Service, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
- CIBERONC. Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology & Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
- Biomedica Molecular Medicine SL, Madrid, Spain
- CIBERONC. Instituto de Salud Carlos III, Madrid, Spain
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16
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Luebker SA, Wojtkiewicz M, Koepsell SA. Two methods for proteomic analysis of formalin-fixed, paraffin embedded tissue result in differential protein identification, data quality, and cost. Proteomics 2016; 15:3744-53. [PMID: 26306679 DOI: 10.1002/pmic.201500147] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 07/06/2015] [Accepted: 08/19/2015] [Indexed: 12/18/2022]
Abstract
Formalin-fixed paraffin-embedded (FFPE) tissue is a rich source of clinically relevant material that can yield important translational biomarker discovery using proteomic analysis. Protocols for analyzing FFPE tissue by LC-MS/MS exist, but standardization of procedures and critical analysis of data quality is limited. This study compared and characterized data obtained from FFPE tissue using two methods: a urea in-solution digestion method (UISD) versus a commercially available Qproteome FFPE Tissue Kit method (Qkit). Each method was performed independently three times on serial sections of homogenous FFPE tissue to minimize pre-analytical variations and analyzed with three technical replicates by LC-MS/MS. Data were evaluated for reproducibility and physiochemical distribution, which highlighted differences in the ability of each method to identify proteins of different molecular weights and isoelectric points. Each method replicate resulted in a significant number of new protein identifications, and both methods identified significantly more proteins using three technical replicates as compared to only two. UISD was cheaper, required less time, and introduced significant protein modifications as compared to the Qkit method, which provided more precise and higher protein yields. These data highlight significant variability among method replicates and type of method used, despite minimizing pre-analytical variability. Utilization of only one method or too few replicates (both method and technical) may limit the subset of proteomic information obtained.
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Affiliation(s)
- Stephen A Luebker
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Nebraska Medical Center, Omaha, NE, USA
| | - Melinda Wojtkiewicz
- Mass Spectrometry and Proteomics Core Facility, University of Nebraska Medical Center, Nebraska Medical Center, Omaha, NE, USA
| | - Scott A Koepsell
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Nebraska Medical Center, Omaha, NE, USA
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Analysis of formalin-fixed, paraffin-embedded (FFPE) tissue via proteomic techniques and misconceptions of antigen retrieval. Biotechniques 2016; 60:229-38. [DOI: 10.2144/000114414] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 02/20/2016] [Indexed: 11/23/2022] Open
Abstract
Since emerging in the late 19th century, formaldehyde fixation has become a standard method for preservation of tissues from clinical samples. The advantage of formaldehyde fixation is that fixed tissues can be stored at room temperature for decades without concern for degradation. This has led to the generation of huge tissue banks containing thousands of clinically significant samples. Here we review techniques for proteomic analysis of formalin-fixed, paraffin-embedded (FFPE) tissue samples with a specific focus on the methods used to extract and break formaldehyde crosslinks. We also discuss an error-of-interpretation associated with the technique known as “antigen retrieval.” We have discovered that this term has been mistakenly applied to two disparate molecular techniques; therefore, we argue that a terminology change is needed to ensure accurate reporting of experimental results. Finally, we suggest that more investigation is required to fully understand the process of formaldehyde fixation and its subsequent reversal.
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Weißer J, Lai ZW, Bronsert P, Kuehs M, Drendel V, Timme S, Kuesters S, Jilg CA, Wellner UF, Lassmann S, Werner M, Biniossek ML, Schilling O. Quantitative proteomic analysis of formalin-fixed, paraffin-embedded clear cell renal cell carcinoma tissue using stable isotopic dimethylation of primary amines. BMC Genomics 2015. [PMID: 26220445 PMCID: PMC4518706 DOI: 10.1186/s12864-015-1768-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most abundant resource of archived human specimens in pathology. Such tissue specimens are emerging as a highly valuable resource for translational proteomic studies. In quantitative proteomic analysis, reductive di-methylation of primary amines using stable isotopic formaldehyde variants is increasingly used due to its robustness and cost-effectiveness. Results In the present study we show for the first time that isotopic amine dimethylation can be used in a straightforward manner for the quantitative proteomic analysis of FFPE specimens without interference from formalin employed in the FFPE process. Isotopic amine dimethylation of FFPE specimens showed equal labeling efficiency as for cryopreserved specimens. For both FFPE and cryopreserved specimens, differential labeling of identical samples yielded highly similar ratio distributions within the expected range for dimethyl labeling. In an initial application, we profiled proteome changes in clear cell renal cell carcinoma (ccRCC) FFPE tissue specimens compared to adjacent non–malignant renal tissue. Our findings highlight increased levels of glyocolytic enzymes, annexins as well as ribosomal and proteasomal proteins. Conclusion Our study establishes isotopic amine dimethylation as a versatile tool for quantitative proteomic analysis of FFPE specimens and underlines proteome alterations in ccRCC. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1768-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- J Weißer
- Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany. .,Present address: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, A-1090, Vienna, Austria.
| | - Z W Lai
- Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany.
| | - P Bronsert
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany. .,Comprehensive Cancer Center Freiburg, Freiburg, Germany. .,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - M Kuehs
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany.
| | - V Drendel
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany.
| | - S Timme
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany.
| | - S Kuesters
- Clinic for General and Visceral Surgery, University Medical Center Freiburg, Freiburg, Germany.
| | - C A Jilg
- Urologische Klinik und Zentrale Klinische Forschung, Klinikum der Universität Freiburg, Freiburg, 79106, Germany.
| | - U F Wellner
- Clinic for General and Visceral Surgery, University Medical Center Freiburg, Freiburg, Germany. .,Present address: Clinic for Surgery, University Clinic of Schleswig-Holstein Campus Lübeck, Lübeck, Germany.
| | - S Lassmann
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany. .,BIOSS Centre for Biological Signaling Studies, University of Freiburg, D-79104, Freiburg, Germany. .,Comprehensive Cancer Center Freiburg, Freiburg, Germany. .,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - M Werner
- Department of Pathology, University Medical Center Freiburg, Freiburg, Germany. .,Comprehensive Cancer Center Freiburg, Freiburg, Germany. .,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - M L Biniossek
- Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany.
| | - O Schilling
- Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany. .,BIOSS Centre for Biological Signaling Studies, University of Freiburg, D-79104, Freiburg, Germany. .,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Campone M, Valo I, Jézéquel P, Moreau M, Boissard A, Campion L, Loussouarn D, Verriele V, Coqueret O, Guette C. Prediction of Recurrence and Survival for Triple-Negative Breast Cancer (TNBC) by a Protein Signature in Tissue Samples. Mol Cell Proteomics 2015. [PMID: 26209610 DOI: 10.1074/mcp.m115.048967] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
To date, there is no available targeted therapy for patients who are diagnosed with triple-negative breast cancers (TNBC). The aim of this study was to identify a new specific target for specific treatments. Frozen primary tumors were collected from 83 adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling by iTRAQ-OFFGEL-LC-MS/MS approach in two series: a training cohort (n = 42) and a test set (n = 41). Patients who remains free of local or distant metastasis for a minimum of 5 years after surgery were classified in the no-relapse group; the others were in the relapse group. OPLS and Kaplan-Meier analyses were performed to select candidate markers, which were validated by immunohistochemistry. Three proteins were identified in the training set and validated in the test set by Kaplan-Meier method and immunohistochemistry (IHC): TrpRS as a good prognostic markers and DP and TSP1 as bad prognostic markers. We propose the establishment of an IHC test to calculate the score of TrpRS, DP, and TSP1 in TNBC tumors to evaluate the degree of aggressiveness of the tumors. Finally, we propose that DP and TSP1 could provide therapeutic targets for specific treatments.
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Affiliation(s)
- Mario Campone
- ‡René Gauducheau ICO Cancer Center, Inserm U892, CNRS 6299, Bd J. Monod, 44805 Saint Herblain Cedex, France; §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France
| | - Isabelle Valo
- §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France
| | - Pascal Jézéquel
- ‡René Gauducheau ICO Cancer Center, Inserm U892, CNRS 6299, Bd J. Monod, 44805 Saint Herblain Cedex, France
| | - Marie Moreau
- ¶Angers University, 4 Boulevard de Lavoisier, Angers, 49000, France
| | - Alice Boissard
- §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France
| | - Loic Campion
- ‡René Gauducheau ICO Cancer Center, Inserm U892, CNRS 6299, Bd J. Monod, 44805 Saint Herblain Cedex, France
| | - Delphine Loussouarn
- ‖INSERM U892, CNRS 6299, IRT-UN, 8 quai Moncousu, 44007 Nantes Cedex, France
| | - Véronique Verriele
- §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France
| | - Olivier Coqueret
- §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France; ¶Angers University, 4 Boulevard de Lavoisier, Angers, 49000, France
| | - Catherine Guette
- §Paul Papin ICO Cancer Center, Inserm U892, CNRS 6299, 2 rue Moll, 49933 Angers Cedex 9, France;
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Gámez-Pozo A, Berges-Soria J, Arevalillo JM, Nanni P, López-Vacas R, Navarro H, Grossmann J, Castaneda CA, Main P, Díaz-Almirón M, Espinosa E, Ciruelos E, Fresno Vara JÁ. Combined Label-Free Quantitative Proteomics and microRNA Expression Analysis of Breast Cancer Unravel Molecular Differences with Clinical Implications. Cancer Res 2015; 75:2243-53. [PMID: 25883093 DOI: 10.1158/0008-5472.can-14-1937] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Accepted: 03/12/2015] [Indexed: 11/16/2022]
Abstract
Better knowledge of the biology of breast cancer has allowed the use of new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different levels of information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor-positive (ER(+)) and 25 triple-negative breast cancer (TNBC) samples. RNA and proteins obtained from formalin-fixed, paraffin-embedded tumors were analyzed by RT-qPCR and LC/MS-MS, respectively. We applied probabilistic graphical models representing complex biologic systems as networks, confirming that ER(+) and TNBC subtypes are distinct biologic entities. The integration of miRNA and protein expression data unravels molecular processes that can be related to differences in the genesis and clinical evolution of these types of breast cancer. Our results confirm that TNBC has a unique metabolic profile that may be exploited for therapeutic intervention.
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Affiliation(s)
- Angelo Gámez-Pozo
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Julia Berges-Soria
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Jorge M Arevalillo
- Department of Statistics, Operational Research and Numerical Analysis, University Nacional Educacion a Distancia (UNED), Madrid, Spain
| | - Paolo Nanni
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | - Rocío López-Vacas
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Hilario Navarro
- Department of Statistics, Operational Research and Numerical Analysis, University Nacional Educacion a Distancia (UNED), Madrid, Spain
| | - Jonas Grossmann
- Functional Genomics Centre Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | - Carlos A Castaneda
- Departamento de Investigación, Instituto Nacional de Enfermedades Neoplásicas, Lima, Surquillo-Lima, Peru
| | - Paloma Main
- Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain
| | - Mariana Díaz-Almirón
- Biostatistics Unit, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Enrique Espinosa
- Medical Oncology Service, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Eva Ciruelos
- Medical Oncology Service, Instituto de Investigación Hospital Universitario Doce de Octubre-i+12, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology and Pathology Lab, Instituto de Genética Médica y Molecular-INGEMM, Instituto de Investigación Hospital Universitario La Paz-IdiPAZ, Madrid, Spain.
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Combined phosphoproteomics and bioinformatics strategy in deciphering drug resistant related pathways in triple negative breast cancer. INTERNATIONAL JOURNAL OF PROTEOMICS 2014; 2014:390781. [PMID: 25478227 PMCID: PMC4247952 DOI: 10.1155/2014/390781] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Revised: 10/21/2014] [Accepted: 10/22/2014] [Indexed: 11/17/2022]
Abstract
Because of the absence of a clear therapeutic target for triple negative breast cancer (TNBC), conventional chemotherapy is the only available systemic treatment option for these patients. Despite chemotherapy treatment, TNBC patients still have worse prognosis when compared with other breast cancer patients. The study is to investigate unique phosphorylated proteins expressed in chemoresistant TNBC cell lines. In the current study, twelve TNBC cell lines were subjected to drug sensitivity assays against chemotherapy drugs docetaxel, doxorubicin, gemcitabine, and cisplatin. Based on their half maximal inhibitory concentrations, four resistant and two sensitive cell lines were selected for further analysis. The phosphopeptides from these cells were enriched with TiO2 beads and fractionated using strong cation exchange. 1,645 phosphoprotein groups and 9,585 unique phosphopeptides were identified by a high throughput LC-MS/MS system LTQ-Orbitrap. The phosphopeptides were further filtered with Ascore system and 1,340 phosphoprotein groups, 2,760 unique phosphopeptides, and 4,549 unique phosphosites were identified. Our study suggested that differentially phosphorylated Cdk5, PML, AP-1, and HSF-1 might work together to promote vimentin induced epithelial to mesenchymal transition (EMT) in the drug resistant cells. EGFR and HGF were also shown to be involved in this process.
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22
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Lai X, Schneider BP. Integrated and convenient procedure for protein extraction from formalin-fixed, paraffin-embedded tissues for LC-MS/MS analysis. Proteomics 2014; 14:2623-7. [DOI: 10.1002/pmic.201400110] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Revised: 07/09/2014] [Accepted: 07/31/2014] [Indexed: 11/10/2022]
Affiliation(s)
- Xianyin Lai
- Department of Biochemistry and Molecular Biology; Indiana University School of Medicine; Indianapolis IN USA
- Department of Cellular and Integrative Physiology; Indiana University School of Medicine; Indianapolis IN USA
| | - Bryan P. Schneider
- Department of Medicine; Indiana University School of Medicine; Indianapolis IN USA
- Department of Medical & Molecular Genetics; Indiana University School of Medicine; Indianapolis IN USA
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Bronsert P, Weißer J, Biniossek ML, Kuehs M, Mayer B, Drendel V, Timme S, Shahinian H, Küsters S, Wellner UF, Lassmann S, Werner M, Schilling O. Impact of routinely employed procedures for tissue processing on the proteomic analysis of formalin-fixed paraffin-embedded tissue. Proteomics Clin Appl 2014; 8:796-804. [PMID: 24888792 DOI: 10.1002/prca.201300082] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Revised: 05/08/2014] [Accepted: 05/26/2014] [Indexed: 12/20/2022]
Abstract
PURPOSE FFPE (formalin fixed, paraffin embedded) tissue cohorts represent an enduring archive of clinical specimens. Proteomic analysis of FFPE tissues is gaining interest for the in-depth analysis of aberrant proteome composition. Procedures for FFPE tissue processing are standardized but there is diversity regarding the different processing systems. This work focuses on three different processing methods commonly used in large European pathology institutes. EXPERIMENTAL DESIGN Formalin fixed tissue specimens of different tumors were serially sliced and processed with three different processing systems (xylene, ethanol/vacuum or microwave based). After paraffin embedding, they were subjected to MS-based proteomic analysis to investigate the impact of tissue processing techniques on the quality of proteomic analysis. Results were compared with proteomic analysis of corresponding cryopreserved tissue specimens. RESULTS All processing techniques achieved very good proteome coverage similar to the cryopreserved counterpart. Gene ontology profiles, relative protein abundances, and peptide modifications such as methionine oxidation or proteolytic truncation were highly similar for all techniques as well as for the cryopreserved samples. CONCLUSIONS AND CLINICAL RELEVANCE The results show that different processing procedures do not impede proteomic analysis as a robust and powerful approach for the identification of protein determinants and markers of disease processes and highlights the general robustness of FFPE-tissue based proteomics.
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Affiliation(s)
- Peter Bronsert
- Institute of Pathology, University Medical Center, Freiburg, Germany; Comprehensive Cancer Center, Freiburg, Germany
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Tanca A, Abbondio M, Pisanu S, Pagnozzi D, Uzzau S, Addis MF. Critical comparison of sample preparation strategies for shotgun proteomic analysis of formalin-fixed, paraffin-embedded samples: insights from liver tissue. Clin Proteomics 2014; 11:28. [PMID: 25097466 PMCID: PMC4115481 DOI: 10.1186/1559-0275-11-28] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 07/03/2014] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND The growing field of formalin-fixed paraffin-embedded (FFPE) tissue proteomics holds promise for improving translational research. Direct tissue trypsinization (DT) and protein extraction followed by in solution digestion (ISD) or filter-aided sample preparation (FASP) are the most common workflows for shotgun analysis of FFPE samples, but a critical comparison of the different methods is currently lacking. EXPERIMENTAL DESIGN DT, FASP and ISD workflows were compared by subjecting to the same label-free quantitative approach three independent technical replicates of each method applied to FFPE liver tissue. Data were evaluated in terms of method reproducibility and protein/peptide distribution according to localization, MW, pI and hydrophobicity. RESULTS DT showed lower reproducibility, good preservation of high-MW proteins, a general bias towards hydrophilic and acidic proteins, much lower keratin contamination, as well as higher abundance of non-tryptic peptides. Conversely, FASP and ISD proteomes were depleted in high-MW proteins and enriched in hydrophobic and membrane proteins; FASP provided higher identification yields, while ISD exhibited higher reproducibility. CONCLUSIONS These results highlight that diverse sample preparation strategies provide significantly different proteomic information, and present typical biases that should be taken into account when dealing with FFPE samples. When a sufficient amount of tissue is available, the complementary use of different methods is suggested to increase proteome coverage and depth.
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Affiliation(s)
- Alessandro Tanca
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy
| | - Marcello Abbondio
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy
| | - Salvatore Pisanu
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy
| | - Daniela Pagnozzi
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy
| | - Sergio Uzzau
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy ; Dipartimento di Scienze Biomediche, Università di Sassari, Viale San Pietro 43/B, 07100, Sassari, Italy
| | - Maria Filippa Addis
- Porto Conte Ricerche, S.P. 55 Porto Conte/Capo Caccia Km 8.400, Tramariglio, 07041 Alghero, Italy
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Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 2014; 13:2513-26. [PMID: 24942700 PMCID: PMC4159666 DOI: 10.1074/mcp.m113.031591] [Citation(s) in RCA: 3531] [Impact Index Per Article: 321.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS signals, given that the presence of quantifiable peptides varies from sample to sample. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button.
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Affiliation(s)
- Jürgen Cox
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Marco Y Hein
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Christian A Luber
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Igor Paron
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Nagarjuna Nagaraj
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Matthias Mann
- From the ‡Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
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Muñiz Lino MA, Palacios-Rodríguez Y, Rodríguez-Cuevas S, Bautista-Piña V, Marchat LA, Ruíz-García E, Astudillo-de la Vega H, González-Santiago AE, Flores-Pérez A, Díaz-Chávez J, Carlos-Reyes Á, Álvarez-Sánchez E, López-Camarillo C. Comparative proteomic profiling of triple-negative breast cancer reveals that up-regulation of RhoGDI-2 is associated to the inhibition of caspase 3 and caspase 9. J Proteomics 2014; 111:198-211. [PMID: 24768906 DOI: 10.1016/j.jprot.2014.04.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2014] [Revised: 03/20/2014] [Accepted: 04/07/2014] [Indexed: 10/25/2022]
Abstract
UNLABELLED There are no targeted therapeutic modalities for triple-negative breast cancer (TNBC), thus it is associated with poor prognosis and worst clinical outcome. Here, our aim was to identify deregulated proteins in TNBC with potential therapeutic applications. Proteomics profiling of TNBC and normal breast tissues through two-dimensional electrophoresis and ESI-MS/MS mass spectrometry revealed the existence of 16 proteins (RhoGDI-2, HSP27, SOD1, DJ1, UBE2N, PSME1, FTL, SH3BGRL, and eIF5A-1) with increased abundance in carcinomas. We also evidenced for the first time the deregulation of COX5, MTPN and DB1 proteins in TNBC that may represent novel tumor markers. Particularly, we confirmed the overexpression of the Rho-GDP dissociation inhibitor 2 (RhoGDI-2) in distinct breast cancer subtypes, as well as in metastatic cell lines derived from lung, prostate, and breast cancer. Remarkably, targeted disruption of RhoGDI-2 by RNA interference induced mitochondrial dysfunction, and facilitated caspase-3 and -9 activation in two breast cancer cell lines. Moreover, suppression of RhoGDI-2 resulted in a robust sensitization of breast cancer cells to cisplatin therapy. In conclusion, we identified novel proteins deregulated in TNBC, and confirmed the overexpression of RhoGDI-2. We propose that RhoGDI-2 inhibition may be exploited as a potential therapeutic strategy along cisplatin-based chemotherapy in breast cancer. BIOLOGICAL SIGNIFICANCE There are no useful biomarkers neither targeted therapeutic modalities for triple-negative breast cancer, which highly contributes to the poor prognosis of this breast cancer subtype. In this work, we used two-dimensional electrophoresis and ESI-MS/MS spectrometry to identify novel deregulated proteins in breast cancer tissues. Particularly, our results showed that RhoGDI-2, a protein that has been associated to metastasis and poor survival in human cancers, is overexpressed in different subtypes of breast tumors, as well as in metastatic cell lines derived from lung, prostate, and breast cancer. Our data also provided novel insights about the role of RhoGDI-2 in apoptosis through intrinsic pathway inhibition. Importantly, they suggested that targeted modulation of RhoGDI-2 levels might be a useful strategy for breast cancer therapy.
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Affiliation(s)
- Marcos A Muñiz Lino
- Oncogenomics and Cancer Proteomics Laboratory, Autonomous University of Mexico City, Mexico
| | | | | | | | - Laurence A Marchat
- Molecular Biomedicine Program and Biotechnology Network, National School of Medicine and Homeopathy, National Polytechnic Institute, Mexico City, Mexico
| | - Erika Ruíz-García
- Translational Medicine Laboratory, National Institute of Cancerology, Mexico City, Mexico
| | - Horacio Astudillo-de la Vega
- Laboratory of Translational Cancer Research and Cellular Therapy, Oncology Hospital, Medical Center Siglo XXI, Mexico City, Mexico
| | | | - Ali Flores-Pérez
- Oncogenomics and Cancer Proteomics Laboratory, Autonomous University of Mexico City, Mexico
| | - José Díaz-Chávez
- Carcinogenesis Laboratory, National Institute of Cancerology, Mexico City, Mexico
| | - Ángeles Carlos-Reyes
- Lung Cancer Laboratory, National Institute of Respiratory Diseases, Mexico City, Mexico
| | | | - César López-Camarillo
- Oncogenomics and Cancer Proteomics Laboratory, Autonomous University of Mexico City, Mexico.
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Theis JD, Dasari S, Vrana JA, Kurtin PJ, Dogan A. Shotgun-proteomics-based clinical testing for diagnosis and classification of amyloidosis. JOURNAL OF MASS SPECTROMETRY : JMS 2013; 48:1067-1077. [PMID: 24130009 DOI: 10.1002/jms.3264] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2013] [Revised: 08/01/2013] [Accepted: 08/16/2013] [Indexed: 06/02/2023]
Abstract
Shotgun proteomics technology has matured in the research laboratories and is poised to enter clinical laboratories. However, the road to this transition is sprinkled with major technical unknowns such as long-term stability of the platform, reproducibility of the technology and clinical utility over traditional antibody-based platforms. Further, regulatory bodies that oversee the clinical laboratory operations are unfamiliar with this new technology. As a result, diagnostic laboratories have avoided using shotgun proteomics for routine diagnostics. In this perspectives article, we describe the clinical implementation of a shotgun proteomics assay for amyloid subtyping, with a special emphasis on standardizing the platform for better quality control and earning clinical acceptance. This assay is the first shotgun proteomics assay to receive regulatory approval for patient diagnosis. The blueprint of this assay can be utilized to develop novel proteomics assays for detecting numerous other disease pathologies.
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Affiliation(s)
- Jason D Theis
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
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