M
Michael Barnes
Researcher at Hoffmann-La Roche
Publications - 22
Citations - 572
Michael Barnes is an academic researcher from Hoffmann-La Roche. The author has contributed to research in topics: Breast cancer & Tumor-infiltrating lymphocytes. The author has an hindex of 11, co-authored 22 publications receiving 405 citations. Previous affiliations of Michael Barnes include Howard Hughes Medical Institute & Ventana Medical Systems.
Papers
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Journal ArticleDOI
Ki67 Proliferation Index as a Tool for Chemotherapy Decisions During and After Neoadjuvant Aromatase Inhibitor Treatment of Breast Cancer: Results From the American College of Surgeons Oncology Group Z1031 Trial (Alliance).
Matthew J. Ellis,Vera J. Suman,Jeremy Hoog,Rodrigo Franco Gonçalves,Souzan Sanati,Chad J. Creighton,Katherine DeSchryver,Erika C. Crouch,Amy Brink,Mark A. Watson,Jingqin Luo,Yu Tao,Michael Barnes,Mitchell Dowsett,G. Thomas Budd,Eric P. Winer,Paula Silverman,Laura J. Esserman,Lisa A. Carey,Cynthia X. Ma,Gary Unzeitig,Timothy J. Pluard,Pat Whitworth,Gildy Babiera,J. Michael Guenther,Zoneddy Dayao,David M. Ota,Marilyn Leitch,John A. Olson,D. Craig Allred,Kelly K. Hunt +30 more
TL;DR: Chemotherapy efficacy was lower than expected in ER-positive tumors exhibiting AI-resistant proliferation, supporting the study of adjuvant endocrine monotherapy in this group.
Journal ArticleDOI
Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
Mohamed Amgad,Elisabeth Specht Stovgaard,Eva Balslev,Jeppe Thagaard,Weijie Chen,Sarah N Dudgeon,Ashish Sharma,Jennifer K. Kerner,Carsten Denkert,Carsten Denkert,Carsten Denkert,Yinyin Yuan,Khalid AbdulJabbar,Stephan Wienert,Peter Savas,Peter Savas,Leonie Voorwerk,Andrew H. Beck,Anant Madabhushi,Anant Madabhushi,Johan Hartman,Manu M. Sebastian,Hugo M. Horlings,Jan Hudecek,Francesco Ciompi,David Moore,Rajendra Singh,Elvire Roblin,Marcelo Luiz Balancin,Marie-Christine Mathieu,Jochen K. Lennerz,Pawan Kirtani,I-Chun Chen,Jeremy P Braybrooke,Jeremy P Braybrooke,Giancarlo Pruneri,Sandra Demaria,Sylvia Adams,Stuart J. Schnitt,Sunil R. Lakhani,Federico Rojo,Laura Comerma,Sunil S. Badve,Mehrnoush Khojasteh,W. Fraser Symmans,Christos Sotiriou,Paula I. Gonzalez-Ericsson,Katherine L. Pogue-Geile,Rim S. Kim,David L. Rimm,Giuseppe Viale,Stephen M. Hewitt,John M. S. Bartlett,John M. S. Bartlett,Frédérique Penault-Llorca,Shom Goel,Huang-Chun Lien,Sibylle Loibl,Zuzana Kos,Sherene Loi,Sherene Loi,Matthew G. Hanna,Stefan Michiels,Stefan Michiels,Marleen Kok,Torsten O. Nielsen,Alexander J. Lazar,Zsuzsanna Bago-Horvath,Loes F. S. Kooreman,Jeroen van der Laak,Jeroen van der Laak,Joel H. Saltz,Brandon D. Gallas,Uday Kurkure,Michael Barnes,Roberto Salgado,Lee Cooper +76 more
TL;DR: The benefits of computational TILs assessment, the readiness of Tils scoring for computational assessment, and considerations for overcoming key barriers to clinical translation in this arena are outlined.
Journal ArticleDOI
Intertumoral Heterogeneity of CD3+ and CD8+ T-Cell Densities in the Microenvironment of DNA Mismatch-Repair-Deficient Colon Cancers: Implications for Prognosis.
Harry H. Yoon,Qian Shi,Erica N. Heying,Andrea Muranyi,Joerg Bredno,Faith M. Ough,Azita Djalilvand,June Clements,Rebecca Bowermaster,Wen-Wei Liu,Michael Barnes,Steven R. Alberts,Kandavel Shanmugam,Frank A. Sinicrope +13 more
TL;DR: Tumor-infiltrating T-cell densities exhibited greater intertumoral heterogeneity among dMMR than pMMR colon cancers, with CD3+IM providing robust stratification of both dMMr and p MMR tumors for prognosis.
Patent
Informatics platform for integrated clinical care
Michael Barnes,Stephen Burnell,William Evans,Chi Lou Weng,Mark M. Morita,Oluwatosin Oyeniran,Joseph Perez-Rogers,Joachim Schmid +7 more
TL;DR: An informatics platform as mentioned in this paper provides an architecture to integrate information from relevant patient information systems, including a workflow tool that can be used to prepare and review information at multi-disciplinary board meetings.
Proceedings ArticleDOI
Joint Region and Nucleus Segmentation for Characterization of Tumor Infiltrating Lymphocytes in Breast Cancer.
Mohamed Amgad,Anindya Sarkar,Chukka Srinivas,Rachel Redman,Simrath Ratra,Charles J. Bechert,Benjamin C. Calhoun,Karen C. Mrazeck,Uday Kurkure,Lee Cooper,Lee Cooper,Michael Barnes +11 more
TL;DR: In this article, a deep learning-based method for joint region-level and nucleus-level segmentation and classification of breast cancer H&E tissue whole slide images is proposed, which simultaneously identifies tumor, fibroblast, and lymphocyte nuclei, along with key histologic region compartments including tumor and stroma.