{"id":35428,"date":"2025-06-12T18:30:39","date_gmt":"2025-06-12T22:30:39","guid":{"rendered":"https:\/\/www.cancerresearch.org\/?post_type=cri_scientists&#038;p=35428"},"modified":"2025-06-12T18:30:40","modified_gmt":"2025-06-12T22:30:40","slug":"anusha-kalbasi-md","status":"publish","type":"cri_scientists","link":"https:\/\/www.cancerresearch.org\/es\/cri-funded-scientists\/anusha-kalbasi-md","title":{"rendered":"Anusha Kalbasi, MD"},"content":{"rendered":"\n<p>Dr. Anusha Kalbasi is creating a detailed map of how cytokines influence cancer-fighting T cells \u2013 information that is essential for designing next-generation immunotherapies that are both more effective and predictable. Cytokines are small protein messengers that help immune cells communicate and function, and Dr. Kalbasi has uncovered a promising new role for IL-9, a lesser-known cytokine with unique signaling properties that can supercharge T-cell function.<\/p>\n\n\n\n<p>While IL-2 has been the mainstay cytokine in cancer immunotherapy since 1992, IL-9 appears to drive T cells in a fundamentally different and potentially more effective way. Dr. Kalbasi\u2019s team will use techniques from protein and cell engineering, genomics, structural biology, and advanced T-cell biology to understand how IL-9 and other cytokines like it influence T-cell behavior at the molecular and cellular level, providing a blueprint for designing smarter cell- and protein-based therapies. Dr. Kalbasi is also working to bring these findings into the clinic by integrating IL-9 signaling into new T-cell therapies. This includes optimizing both conventional T-cell therapy and emerging approaches like <em>in vivo <\/em>T-cell engineering, which may especially benefit from cytokine-based control. His research aims to deliver more effective, durable treatments for patients, guided directly by the insights gained from clinical application.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Research Focus<\/h2>\n\n\n\n<p><strong>Sarcoma and other solid tumors, cytokines, T-cell therapy<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Projects and Grants<\/h2>\n\n\n\n<p><strong>Decoding the Cell-Intrinsic Language of Cytokines for Cancer Immunotherapy<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dr. Anusha Kalbasi is creating a detailed map of how cytokines influence cancer-fighting T cells \u2013 information that is essential for designing next-generation immunotherapies that are both more effective and predictable. Cytokines [&hellip;]<\/p>\n","protected":false},"featured_media":35417,"template":"","tax_cancer_type":[455],"tax_grant_type":[482],"tax_award_year":[742],"tax_institutions":[528],"tax_location_states":[501],"class_list":["post-35428","cri_scientists","type-cri_scientists","status-publish","has-post-thumbnail","hentry"],"acf":{"scientist_subhead":"Associate Professor of Radiation Oncology, Stanford University School of Medicine","quote":"We now have the tools to engineer almost any immune cell phenotype, but we still don\u2019t understand the rules that determine which cells will be most effective in patients. This support gives us the freedom to define those rules and translate them into smarter therapies.","scientist_last_name":"Kalbasi","show_on_landing":true,"scientist_publish_until":"20310612"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Anusha Kalbasi, MD - Cancer Research Institute<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.cancerresearch.org\/cri-funded-scientists\/anusha-kalbasi-md\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Anusha Kalbasi, MD - Cancer Research Institute\" \/>\n<meta property=\"og:description\" content=\"Dr. Anusha Kalbasi is creating a detailed map of how cytokines influence cancer-fighting T cells \u2013 information that is essential for designing next-generation immunotherapies that are both more effective and predictable. 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