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Szadai L, Bartha A, Parada IP, Lakatos A, Pál D, Lengyel AS, de Almeida NP, Jánosi ÁJ, Nogueira F, Szeitz B, Doma V, Woldmar N, Guedes J, Ujfaludi Z, Pahi ZG, Pankotai T, Kim Y, Győrffy B, Baldetorp B, Welinder C, Szasz AM, Betancourt L, Gil J, Appelqvist R, Kwon HJ, Kárpáti S, Kuras M, Murillo JR, Németh IB, Malm J, Fenyö D, Pawłowski K, Horvatovich P, Wieslander E, Kemény LV, Domont G, MarkoVarga G, Sanchez A. Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts. bioRxiv 2024:2024.05.01.592032. [PMID: 38746333 PMCID: PMC11092593 DOI: 10.1101/2024.05.01.592032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making. Abstract Figure
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Giwercman A, Sahlin KB, Pla Parada I, Pawlowski K, Fehninger C, Lundberg Giwercman Y, Leijonhufvud I, Appelqvist R, Marko-Varga G, Sanchez A, Malm J. Novel protein markers of androgen activity in humans: proteomic study of plasma from young chemically castrated men. eLife 2022; 11:74638. [PMID: 35230239 PMCID: PMC8993215 DOI: 10.7554/elife.74638] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Background Reliable biomarkers of androgen activity in humans are lacking. The aim of this study was, therefore, to identify new protein markers of biological androgen activity and test their predictive value in relation to low vs. normal testosterone values and some androgen deficiency linked pathologies. Methods Blood samples from 30 healthy GnRH-antagonist treated males were collected at three time points: a) before GnRH antagonist administration; b) 3 weeks later, just before testosterone undecanoate injection, and c) after additional 2 weeks. Subsequently they were analysed by mass spectrometry to identify potential protein biomarkers of testosterone activity. Levels of proteins most significantly associated with testosterone fluctuations were further tested in a cohort of 75 hypo- and eugonadal males suffering from infertility. Associations between levels of those markers and cardio-metabolic parameters, bone mineral density as well as androgen receptor CAG repeat lengths, were explored. Results Using ROC analysis, 4-hydroxyphenylpyruvate dioxygenase (4HPPD), insulin-like growth factor-binding protein 6 (IGFBP6) and fructose-bisphosphate aldolase (ALDOB), as well as a Multi Marker Algorithm, based on levels of 4HPPD and IGFBP6, were shown to be best predictors of low (< 8 nmol/L) vs. normal (> 12 nmol/L) testosterone. They were also more strongly associated with metabolic syndrome and diabetes than testosterone levels. Levels of ALDOB and 4HPPD levels also showed association with AR CAG-repeat lengths. Conclusions We identified potential new protein biomarkers of testosterone action. Further investigations to elucidate their clinical potential are warranted. Funding The work was supported by ReproUnion 2.0 (grant no 20201846), which is funded by the Interreg V EU program.
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Affiliation(s)
| | - K Barbara Sahlin
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | | | - Krzysztof Pawlowski
- Department of Experimental Design and Bioinformatics, Warsaw University of Life Sciences, Warszawa, Poland
| | - Carl Fehninger
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | | | | | - Roger Appelqvist
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | | | - Aniel Sanchez
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Johan Malm
- Department of Translational Medicine, Lund University, Malmo, Sweden
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Almeida N, Rodriguez J, Pla Parada I, Perez-Riverol Y, Woldmar N, Kim Y, Oskolas H, Betancourt L, Valdés JG, Sahlin KB, Pizzatti L, Szasz AM, Kárpáti S, Appelqvist R, Malm J, B. Domont G, C. S. Nogueira F, Marko-Varga G, Sanchez A. Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database. Cancers (Basel) 2021; 13:6224. [PMID: 34944842 PMCID: PMC8699267 DOI: 10.3390/cancers13246224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 11/30/2021] [Accepted: 12/08/2021] [Indexed: 12/26/2022] Open
Abstract
Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.
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Affiliation(s)
- Natália Almeida
- Laboratory of Proteomics/LADETEC, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-598, Brazil;
- Proteomics Unit, Institute of Chemistry, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil;
- Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden; (N.W.); (K.B.S.); (G.M.-V.)
| | - Jimmy Rodriguez
- Division of Chemistry I, Department of Biochemistry and Biophysics, Karolinska Institute, 17165 Stockholm, Sweden;
| | - Indira Pla Parada
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden; (I.P.P.); (J.M.)
| | - Yasset Perez-Riverol
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK;
| | - Nicole Woldmar
- Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden; (N.W.); (K.B.S.); (G.M.-V.)
- Laboratory of Molecular Biology and Blood Proteomics—LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil;
| | - Yonghyo Kim
- Data Convergence Drug Research Center, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea;
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden; (H.O.); (L.B.); (J.G.V.); (R.A.)
| | - Henriett Oskolas
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden; (H.O.); (L.B.); (J.G.V.); (R.A.)
| | - Lazaro Betancourt
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden; (H.O.); (L.B.); (J.G.V.); (R.A.)
| | - Jeovanis Gil Valdés
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden; (H.O.); (L.B.); (J.G.V.); (R.A.)
| | - K. Barbara Sahlin
- Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden; (N.W.); (K.B.S.); (G.M.-V.)
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden; (I.P.P.); (J.M.)
| | - Luciana Pizzatti
- Laboratory of Molecular Biology and Blood Proteomics—LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil;
| | | | - Sarolta Kárpáti
- Department of Dermatology, Venereology and Dermatooncology, Semmelweis University, 1085 Budapest, Hungary;
| | - Roger Appelqvist
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden; (H.O.); (L.B.); (J.G.V.); (R.A.)
| | - Johan Malm
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden; (I.P.P.); (J.M.)
| | - Gilberto B. Domont
- Proteomics Unit, Institute of Chemistry, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil;
| | - Fábio C. S. Nogueira
- Laboratory of Proteomics/LADETEC, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-598, Brazil;
- Proteomics Unit, Institute of Chemistry, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil;
| | - György Marko-Varga
- Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden; (N.W.); (K.B.S.); (G.M.-V.)
- Chemical Genomics Global Research Lab, Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea
- Department of Surgery, Tokyo Medical University, 6-7-1 Nishishinjiku Shinjiku-ku, Tokyo 160-0023, Japan
| | - Aniel Sanchez
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden; (I.P.P.); (J.M.)
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Betancourt LH, Gil J, Sanchez A, Doma V, Kuras M, Murillo JR, Velasquez E, Çakır U, Kim Y, Sugihara Y, Parada IP, Szeitz B, Appelqvist R, Wieslander E, Welinder C, de Almeida NP, Woldmar N, Marko‐Varga M, Eriksson J, Pawłowski K, Baldetorp B, Ingvar C, Olsson H, Lundgren L, Lindberg H, Oskolas H, Lee B, Berge E, Sjögren M, Eriksson C, Kim D, Kwon HJ, Knudsen B, Rezeli M, Malm J, Hong R, Horvath P, Szász AM, Tímár J, Kárpáti S, Horvatovich P, Miliotis T, Nishimura T, Kato H, Steinfelder E, Oppermann M, Miller K, Florindi F, Zhou Q, Domont GB, Pizzatti L, Nogueira FCS, Szadai L, Németh IB, Ekedahl H, Fenyö D, Marko‐Varga G. The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome. Clin Transl Med 2021; 11:e451. [PMID: 34323402 PMCID: PMC8299047 DOI: 10.1002/ctm2.451] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 12/12/2022] Open
Abstract
The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.
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Betancourt LH, Gil J, Kim Y, Doma V, Çakır U, Sanchez A, Murillo JR, Kuras M, Parada IP, Sugihara Y, Appelqvist R, Wieslander E, Welinder C, Velasquez E, de Almeida NP, Woldmar N, Marko‐Varga M, Pawłowski K, Eriksson J, Szeitz B, Baldetorp B, Ingvar C, Olsson H, Lundgren L, Lindberg H, Oskolas H, Lee B, Berge E, Sjögren M, Eriksson C, Kim D, Kwon HJ, Knudsen B, Rezeli M, Hong R, Horvatovich P, Miliotis T, Nishimura T, Kato H, Steinfelder E, Oppermann M, Miller K, Florindi F, Zhou Q, Domont GB, Pizzatti L, Nogueira FCS, Horvath P, Szadai L, Tímár J, Kárpáti S, Szász AM, Malm J, Fenyö D, Ekedahl H, Németh IB, Marko‐Varga G. The human melanoma proteome atlas-Defining the molecular pathology. Clin Transl Med 2021; 11:e473. [PMID: 34323403 PMCID: PMC8255060 DOI: 10.1002/ctm2.473] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 01/19/2023] Open
Abstract
The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.
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