Peer-Reviewed Publication
J Immunother Cancer2026;14(6)June 24, 2026Journal Article
Artificial intelligence-guided analysis of the tumor microenvironment predicts response to pembrolizumab in rare tumors.
Mohamed H Derbala1, Bettzy Stephen1, Woochan Hwang2, Chan-Young Ock2, Soohyun Hwang2, Joud Hajjar3, Seungeun Lee2, Jianling Zhou4, Serdar A Gurses1, Mohamed A Gouda1, Kathryn E McGonagle1, Anas Alshawa1, Lilibeth Castillo1, Abdulrazzak Zarifa1, Siqing Fu1, Sarina A Piha-Paul1, Apostolia M Tsimberidou1, Funda Meric-Bernstam1, Luisa Maren Solis Soto5, Maria Gabriela Raso5, Siraj Ali2, Aung Naing6
1Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
2Lunit Inc, Gangnam-gu, Seoul, Korea (the Republic of).
3Division of Immunology, Allergy and Retrovirology, Baylor College of Medicine, Houston, Texas, USA.
4Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
5Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
6Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA anaing@mdanderson.org.
Abstract
BACKGROUND: Pathologic tumor response and changes in the tumor microenvironment (TME) predict outcomes to immune checkpoint inhibitors, but are understudied in rare tumors. We investigated whether artificial intelligence (AI)-powered analyses of pretreatment and on-treatment biopsies may inform treatment outcomes to pembrolizumab.
METHODS: We evaluated 256 baseline and 248 on-treatment biopsies f…
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