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Cell Reports Medicine
All content is freely available to readers and supported through open access

Feb 16, 2021

Volume 2Issue 2
Open Access
On the cover: Aslostovar et al. (pp. 100202-1–100202-13) build on a phase I trial for acute myeloid leukemia and identify that enantiomer purification improves the efficacy:risk ratio of the trial drug, thioridazine, a dopamine receptor antagonist that targets leukemic stem/progenitor cells. In the cover image, the thioridazine enantiomer is symbolized by beach glass refined from jagged shards to a more valuable polished state similar to the enantiomer identified. This is achieved through iterations of waves crashing on the sand, representing iterative cycles of refinement between the clinic and the basic biomedical research at bench side....
On the cover: Aslostovar et al. (pp. 100202-1–100202-13) build on a phase I trial for acute myeloid leukemia and identify that enantiomer purification improves the efficacy:risk ratio of the trial drug, thioridazine, a dopamine receptor antagonist that targets leukemic stem/progenitor cells. In the cover image, the thioridazine enantiomer is symbolized by beach glass refined from jagged shards to a more valuable polished state similar to the enantiomer identified. This is achieved through iterations of waves crashing on the sand, representing iterative cycles of refinement between the clinic and the basic biomedical research at bench side.

Perspective

Commentary

  • The endangered physician-scientist and COVID-19

    • Rajesh C. Rao,
    • Brian J. Dlouhy,
    • Brian C. Capell,
    • Oluwaseun Akeju
    The COVID-19 pandemic has affected almost every stakeholder in healthcare, including the vulnerable population of clinician investigators known as physician-scientists. In this commentary, Rao et al. highlight the underappreciated challenges and opportunities, and present solutions, for physician-scientists vis-à-vis the uniquely disruptive event of the pandemic.

Report

  • Use of machine learning to identify a T cell response to SARS-CoV-2

    • M. Saad Shoukat,
    • Andrew D. Foers,
    • Stephen Woodmansey,
    • Shelley C. Evans,
    • Anna Fowler,
    • Elizabeth J. Soilleux
    To understand T cell responses to SARS-CoV-2, Shoukat et al. analyze TCR beta repertoire data from recovered COVID-19 patients and SARS-CoV-2 infection-naïve controls. Their machine learning approach can classify samples with up to 96.4% training accuracy and 92.9% testing accuracy. This method may detect T-cell responses acquired through natural infection or vaccination.

Articles

  • Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting

    • Julien Schmidt,
    • Angela R. Smith,
    • Morgane Magnin,
    • Julien Racle,
    • Jason R. Devlin,
    • Sara Bobisse,
    • Julien Cesbron,
    • Victor Bonnet,
    • Santiago J. Carmona,
    • Florian Huber,
    • Giovanni Ciriello,
    • Daniel E. Speiser,
    • Michal Bassani-Sternberg,
    • George Coukos,
    • Brian M. Baker,
    • Alexandre Harari,
    • David Gfeller
    Schmidt et al. develop a predictor of immunogenicity (PRIME) for CD8 T cell epitopes that captures antigen presentation on HLA molecules and TCR recognition. Their results reveal molecular determinants of TCR recognition and support immunoediting acting on recurrent cancer mutations.
  • Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

    • Alison Tarke,
    • John Sidney,
    • Conner K. Kidd,
    • Jennifer M. Dan,
    • Sydney I. Ramirez,
    • Esther Dawen Yu,
    • Jose Mateus,
    • Ricardo da Silva Antunes,
    • Erin Moore,
    • Paul Rubiro,
    • Nils Methot,
    • Elizabeth Phillips,
    • Simon Mallal,
    • April Frazier,
    • Stephen A. Rawlings,
    • Jason A. Greenbaum,
    • Bjoern Peters,
    • Davey M. Smith,
    • Shane Crotty,
    • Daniela Weiskopf,
    • Alba Grifoni,
    • Alessandro Sette
    Tarke et al. show a broad T cell repertoire, suggesting that viral escape of T cell immunity is unlikely. CD4 immunodominant regions correlate with HLA binding and not with high common cold coronavirus homology. RBD is poorly recognized by CD4s. Epitope pools can be used to optimize detection of T cell responses.
  • Sensitive detection of total anti-Spike antibodies and isotype switching in asymptomatic and symptomatic individuals with COVID-19

    • Yun Shan Goh,
    • Jean-Marc Chavatte,
    • Alicia Lim Jieling,
    • Bernett Lee,
    • Pei Xiang Hor,
    • Siti Naqiah Amrun,
    • Cheryl Yi-Pin Lee,
    • Rhonda Sin-Ling Chee,
    • Bei Wang,
    • Chia Yin Lee,
    • Eve Zhi Xian Ngoh,
    • Cheng-I Wang,
    • Barnaby Edward Young,
    • Paul A. Tambyah,
    • Shirin Kalimuddin,
    • Surinder Pada,
    • Seow-Yen Tan,
    • Louisa Jin Sun,
    • Mark I-Cheng Chen,
    • Yee-Sin Leo,
    • David C. Lye,
    • Lisa F.P. Ng,
    • Raymond Tzer Pin Lin,
    • Laurent Renia
    Using a flow cytometry-based assay, Goh et al. find specific antibodies in plasma samples from symptomatic individuals with COVID-19. IgG1 is the most dominant IgG subclass. Despite lower antibody levels, the assay detects 97% of asymptomatic infections, suggesting that the assay detects asymptomatic infections, which may otherwise remain undetected.
  • Abnormal dopamine receptor signaling allows selective therapeutic targeting of neoplastic progenitors in AML patients

    • Lili Aslostovar,
    • Allison L. Boyd,
    • Yannick D. Benoit,
    • Justin Di Lu,
    • Juan Luis Garcia Rodriguez,
    • Mio Nakanishi,
    • Deanna P. Porras,
    • Jennifer C. Reid,
    • Ryan R. Mitchell,
    • Brian Leber,
    • Anargyros Xenocostas,
    • Ronan Foley,
    • Mickie Bhatia
    Aslostovar et al. establish reliable assays that predict clinical responsiveness to a dopamine receptor 2 (DRD2) antagonist using patient samples from a Phase I clinical study of acute myeloid leukemia. Using this platform, they identify biomarkers for patient stratification and develop an alternative drug formulation with an improved efficacy:risk ratio.
  • Single-cell analysis shows that adipose tissue of persons with both HIV and diabetes is enriched for clonal, cytotoxic, and CMV-specific CD4+ T cells

    • Celestine N. Wanjalla,
    • Wyatt J. McDonnell,
    • Ramesh Ram,
    • Abha Chopra,
    • Rama Gangula,
    • Shay Leary,
    • Mona Mashayekhi,
    • Joshua D. Simmons,
    • Christian M. Warren,
    • Samuel Bailin,
    • Curtis L. Gabriel,
    • Liang Guo,
    • Briana D. Furch,
    • Morgan C. Lima,
    • Beverly O. Woodward,
    • LaToya Hannah,
    • Mark A. Pilkinton,
    • Daniela T. Fuller,
    • Kenji Kawai,
    • Renu Virmani,
    • Aloke V. Finn,
    • Alyssa H. Hasty,
    • Simon A. Mallal,
    • Spyros A. Kalams,
    • John R. Koethe
    Wanjalla et al. demonstrate that adipose tissue in persons with HIV and diabetes includes a large proportion of clonally expanded, inflammatory, and frequently CMV-specific CX3CR1+ GPR56+ CD57+ (C-G-C+) CD4+ T cells. These cells may contribute to the altered adipocyte function and elevated risk of metabolic disease observed among persons with HIV.
  • A standard calculation methodology for human doubly labeled water studies

    • John R. Speakman,
    • Yosuke Yamada,
    • Hiroyuki Sagayama,
    • Elena S.F. Berman,
    • Philip N. Ainslie,
    • Lene F. Andersen,
    • Liam J. Anderson,
    • Lenore Arab,
    • Issaad Baddou,
    • Kweku Bedu-Addo,
    • Ellen E. Blaak,
    • Stephane Blanc,
    • Alberto G. Bonomi,
    • Carlijn V.C. Bouten,
    • Pascal Bovet,
    • Maciej S. Buchowski,
    • Nancy F. Butte,
    • Stefan G.J.A. Camps,
    • Graeme L. Close,
    • Jamie A. Cooper,
    • Seth A. Creasy,
    • Sai Krupa Das,
    • Richard Cooper,
    • Lara R. Dugas,
    • Cara B. Ebbeling,
    • Ulf Ekelund,
    • Sonja Entringer,
    • Terrence Forrester,
    • Barry W. Fudge,
    • Annelies H. Goris,
    • Michael Gurven,
    • Catherine Hambly,
    • Asmaa El Hamdouchi,
    • Marije B. Hoos,
    • Sumei Hu,
    • Noorjehan Joonas,
    • Annemiek M. Joosen,
    • Peter Katzmarzyk,
    • Kitty P. Kempen,
    • Misaka Kimura,
    • William E. Kraus,
    • Robert F. Kushner,
    • Estelle V. Lambert,
    • William R. Leonard,
    • Nader Lessan,
    • David S. Ludwig,
    • Corby K. Martin,
    • Anine C. Medin,
    • Erwin P. Meijer,
    • James C. Morehen,
    • James P. Morton,
    • Marian L. Neuhouser,
    • Theresa A. Nicklas,
    • Robert M. Ojiambo,
    • Kirsi H. Pietiläinen,
    • Yannis P. Pitsiladis,
    • Jacob Plange-Rhule,
    • Guy Plasqui,
    • Ross L. Prentice,
    • Roberto A. Rabinovich,
    • Susan B. Racette,
    • David A. Raichlen,
    • Eric Ravussin,
    • Rebecca M. Reynolds,
    • Susan B. Roberts,
    • Albertine J. Schuit,
    • Anders M. Sjödin,
    • Eric Stice,
    • Samuel S. Urlacher,
    • Giulio Valenti,
    • Ludo M. Van Etten,
    • Edgar A. Van Mil,
    • Jonathan C.K. Wells,
    • George Wilson,
    • Brian M. Wood,
    • Jack Yanovski,
    • Tsukasa Yoshida,
    • Xueying Zhang,
    • Alexia J. Murphy-Alford,
    • Cornelia U. Loechl,
    • Edward L. Melanson,
    • Amy H. Luke,
    • Herman Pontzer,
    • Jennifer Rood,
    • Dale A. Schoeller,
    • Klaas R. Westerterp,
    • William W. Wong
    • the IAEA DLW database group
    Speakman et al. use a large database of doubly labeled water measurements to show the choice of equation for the calculation of energy expenditure introduces significant variation into the final estimate. They then derive new equations that outperform previous equations in validation studies against chamber calorimetry.
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