Literature DB >> 26555452

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

Viktor Martyanov1, Michael L Whitfield.   

Abstract

PURPOSE OF REVIEW: The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. RECENT
FINDINGS: Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes.
SUMMARY: Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

Entities:  

Mesh:

Year:  2016        PMID: 26555452      PMCID: PMC4722537          DOI: 10.1097/BOR.0000000000000237

Source DB:  PubMed          Journal:  Curr Opin Rheumatol        ISSN: 1040-8711            Impact factor:   5.006


  23 in total

1.  Growth differentiation factor 15, a marker of lung involvement in systemic sclerosis, is involved in fibrosis development but is not indispensable for fibrosis development.

Authors:  Stijn Lambrecht; Vanessa Smith; Katelijne De Wilde; Julie Coudenys; Saskia Decuman; Dieter Deforce; Filip De Keyser; Dirk Elewaut
Journal:  Arthritis Rheumatol       Date:  2014-02       Impact factor: 10.995

2.  A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis.

Authors:  G Farina; D Lafyatis; R Lemaire; R Lafyatis
Journal:  Arthritis Rheum       Date:  2010-02

3.  Proteomic analysis of plasma identifies the Toll-like receptor agonists S100A8/A9 as a novel possible marker for systemic sclerosis phenotype.

Authors:  L van Bon; M Cossu; A Loof; F Gohar; H Wittkowski; M Vonk; J Roth; W van den Berg; W van Heerde; J C A Broen; T R D J Radstake
Journal:  Ann Rheum Dis       Date:  2014-04-09       Impact factor: 19.103

4.  Fresolimumab treatment decreases biomarkers and improves clinical symptoms in systemic sclerosis patients.

Authors:  Lisa M Rice; Cristina M Padilla; Sarah R McLaughlin; Allison Mathes; Jessica Ziemek; Salma Goummih; Sashidhar Nakerakanti; Michael York; Giuseppina Farina; Michael L Whitfield; Robert F Spiera; Romy B Christmann; Jessica K Gordon; Janice Weinberg; Robert W Simms; Robert Lafyatis
Journal:  J Clin Invest       Date:  2015-06-22       Impact factor: 14.808

5.  Brief report: lysyl oxidase is a potential biomarker of fibrosis in systemic sclerosis.

Authors:  Doron Rimar; Itzhak Rosner; Yuval Nov; Gleb Slobodin; Michael Rozenbaum; Katy Halasz; Tharwat Haj; Nizar Jiries; Lisa Kaly; Nina Boulman; Rula Daood; Zahava Vadasz
Journal:  Arthritis Rheumatol       Date:  2014-03       Impact factor: 10.995

Review 6.  Gene expression profiling offers insights into the role of innate immune signaling in SSc.

Authors:  Michael E Johnson; Patricia A Pioli; Michael L Whitfield
Journal:  Semin Immunopathol       Date:  2015-07-30       Impact factor: 9.623

7.  A TGFbeta-responsive gene signature is associated with a subset of diffuse scleroderma with increased disease severity.

Authors:  Jennifer L Sargent; Ausra Milano; Swati Bhattacharyya; John Varga; M Kari Connolly; Howard Y Chang; Michael L Whitfield
Journal:  J Invest Dermatol       Date:  2009-10-08       Impact factor: 8.551

8.  Experimentally-derived fibroblast gene signatures identify molecular pathways associated with distinct subsets of systemic sclerosis patients in three independent cohorts.

Authors:  Michael E Johnson; J Matthew Mahoney; Jaclyn Taroni; Jennifer L Sargent; Eleni Marmarelis; Ming-Ru Wu; John Varga; Monique E Hinchcliff; Michael L Whitfield
Journal:  PLoS One       Date:  2015-01-21       Impact factor: 3.240

9.  Levels of target activation predict antifibrotic responses to tyrosine kinase inhibitors.

Authors:  Britta Maurer; Alfiya Distler; Clara Dees; Korsa Khan; Christopher P Denton; David Abraham; Renate E Gay; Beat A Michel; Steffen Gay; Jörg Hw Distler; Oliver Distler
Journal:  Ann Rheum Dis       Date:  2013-09-07       Impact factor: 19.103

10.  Molecular signatures in skin associated with clinical improvement during mycophenolate treatment in systemic sclerosis.

Authors:  Monique Hinchcliff; Chiang-Ching Huang; Tammara A Wood; J Matthew Mahoney; Viktor Martyanov; Swati Bhattacharyya; Zenshiro Tamaki; Jungwha Lee; Mary Carns; Sofia Podlusky; Arlene Sirajuddin; Sanjiv J Shah; Rowland W Chang; Robert Lafyatis; John Varga; Michael L Whitfield
Journal:  J Invest Dermatol       Date:  2013-03-14       Impact factor: 8.551

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  13 in total

1.  Current and Future Outlook on Disease Modification and Defining Low Disease Activity in Systemic Sclerosis.

Authors:  Vivek Nagaraja; Marco Matucci-Cerinic; Daniel E Furst; Masataka Kuwana; Yannick Allanore; Christopher P Denton; Ganesh Raghu; Vallerie Mclaughlin; Panduranga S Rao; James R Seibold; John D Pauling; Michael L Whitfield; Dinesh Khanna
Journal:  Arthritis Rheumatol       Date:  2020-05-18       Impact factor: 10.995

2.  Recent advances steer the future of systemic sclerosis toward precision medicine.

Authors:  Gemma Lepri; Michael Hughes; Cosimo Bruni; Marco Matucci Cerinic; Silvia Bellando Randone
Journal:  Clin Rheumatol       Date:  2019-11-23       Impact factor: 2.980

3.  The mechanistic implications of gene expression studies in SSc: Insights from Systems Biology.

Authors:  Jaclyn N Taroni; J Matthew Mahoney; Michael L Whitfield
Journal:  Curr Treatm Opt Rheumatol       Date:  2017-07-29

Review 4.  Evolving insights into the cellular and molecular pathogenesis of fibrosis in systemic sclerosis.

Authors:  Benjamin Korman
Journal:  Transl Res       Date:  2019-02-23       Impact factor: 7.012

Review 5.  Biomarkers in systemic sclerosis.

Authors:  Brian Skaug; Shervin Assassi
Journal:  Curr Opin Rheumatol       Date:  2019-11       Impact factor: 5.006

6.  The JAK/STAT pathway is activated in systemic sclerosis and is effectively targeted by tofacitinib.

Authors:  Wenxia Wang; Swati Bhattacharyya; Roberta Goncalves Marangoni; Mary Carns; Kathleen Dennis-Aren; Anjana Yeldandi; Jun Wei; John Varga
Journal:  J Scleroderma Relat Disord       Date:  2019-08-07

7.  Global skin gene expression analysis of early diffuse cutaneous systemic sclerosis shows a prominent innate and adaptive inflammatory profile.

Authors:  Brian Skaug; Dinesh Khanna; William R Swindell; Monique E Hinchcliff; Tracy M Frech; Virginia D Steen; Faye N Hant; Jessica K Gordon; Ami A Shah; Lisha Zhu; W Jim Zheng; Jeffrey L Browning; Alexander M S Barron; Minghua Wu; Sudha Visvanathan; Patrick Baum; Jennifer M Franks; Michael L Whitfield; Victoria K Shanmugam; Robyn T Domsic; Flavia V Castelino; Elana J Bernstein; Nancy Wareing; Marka A Lyons; Jun Ying; Julio Charles; Maureen D Mayes; Shervin Assassi
Journal:  Ann Rheum Dis       Date:  2019-11-25       Impact factor: 19.103

8.  A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets.

Authors:  Jennifer M Franks; Viktor Martyanov; Guoshuai Cai; Yue Wang; Zhenghui Li; Tammara A Wood; Michael L Whitfield
Journal:  Arthritis Rheumatol       Date:  2019-09-02       Impact factor: 15.483

Review 9.  Shared and distinct mechanisms of fibrosis.

Authors:  Jörg H W Distler; Andrea-Hermina Györfi; Meera Ramanujam; Michael L Whitfield; Melanie Königshoff; Robert Lafyatis
Journal:  Nat Rev Rheumatol       Date:  2019-11-11       Impact factor: 20.543

10.  Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.

Authors:  Dana E Orange; Jessica K Gordon; Kimberly Showalter; Robert Spiera; Cynthia Magro; Phaedra Agius; Viktor Martyanov; Jennifer M Franks; Roshan Sharma; Heather Geiger; Tammara A Wood; Yaxia Zhang; Caryn R Hale; Jackie Finik; Michael L Whitfield
Journal:  Ann Rheum Dis       Date:  2020-10-07       Impact factor: 19.103

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