M
Marc Wadsworth
Researcher at Massachusetts Institute of Technology
Publications - 3
Citations - 52
Marc Wadsworth is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Cell type & Tumor microenvironment. The author has an hindex of 2, co-authored 3 publications receiving 18 citations. Previous affiliations of Marc Wadsworth include Ragon Institute of MGH, MIT and Harvard.
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Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states
Hanbing Song,Weinstein Hn,Allegakoen P,Marc Wadsworth,Jin Xie,Hongbo Yang,Felix Feng,Peter R. Carroll,Biao Wang,Matthew R. Cooperberg,Alex K. Shalek,Huang Fw +11 more
TL;DR: A population of tumor-associated club cells that may act as progenitor cells and uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer are identified.
Posted ContentDOI
Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease
Kevin Baßler,Wataru Fujii,Theodoros Kapellos,Arik Horne,Benedikt Reiz,Erika Dudkin,Lücken M,Nico Reusch,Osei-Sarpong C,Stefanie Warnat-Herresthal,Allon Wagner,Lorenzo Bonaguro,Patrick Günther,Carmen Pizarro,Schreiber T,Matthias Becker,Kristian Händler,Wohnhaas Ct,Baumgartner F,Köhler M,Heidi Theis,Michael Kraut,Marc Wadsworth,Marc Wadsworth,Travis K. Hughes,Travis K. Hughes,Ferreira Hjg,Jonas Schulte-Schrepping,Emily R. Hinkley,Kaltheuner Ih,Matthias Geyer,Christoph Thiele,Alex K. Shalek,Alex K. Shalek,Feißt A,Daniel Thomas,Henning Dickten,Marc Beyer,Baum P,Nir Yosef,Anna C. Aschenbrenner,Anna C. Aschenbrenner,Thomas Ulas,Jan Hasenauer,Fabian J. Theis,Dirk Skowasch,Joachim L. Schultze,Joachim L. Schultze +47 more
TL;DR: This work characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort.
Proceedings ArticleDOI
Abstract 4380: Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing
Benjamin Izar,Itay Tirsh,Sanjay Prakadan,Marc Wadsworth,Daniel J. Treacy,John J. Trombetta,Asaf Rotem,Christine G. Lian,George F. Murphy,Mohammad Fallahi-Sichani,Ken Dutton-Regester,Jia-Ren Lin,Judit Jané-Valbuena,Orit Rozenblatt-Rosen,Charles H. Yoon,Alex K. Shalek,Aviv Regev,Levi A. Garraway +17 more
TL;DR: This study represents the most comprehensive single-cell genomics analysis in humans to date and begins to unravel the cellular ecosystem of tumors.