Xilio Therapeutics Presents Promising Preclinical Tumor-Selective Efficacy and Safety Data for XTX201 (IL-2) and XTX101 (anti-CTLA-4) at SITC

On November 12, 2020 Xilio Therapeutics, a biotechnology company developing potent, tumor-selective immunotherapies for patients with cancer, reported the presentation of preclinical data of its lead investigational therapies: XTX201, a tumor-selective IL-2, and XTX101, a tumor-selective anti-CTLA-4 antibody (Press release, Xilio Therapeutics, NOV 12, 2020, View Source [SID1234570832]). The findings were presented at the 35th Annual Meeting of The Society for Immunotherapy of Cancer (SITC) (Free SITC Whitepaper) (SITC 2020).

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"This is a transformational moment for the company. These positive preclinical data showing tumor-selective activity with our most advanced therapeutic candidates, XTX201 and XTX101, support the evaluation of both molecules in clinical studies, bringing us one step closer to delivering transformative cancer treatments for patients. Based on these findings, we hope to submit Investigational New Drug applications for both molecules in 2021," said Rene Russo, Chief Executive Officer of Xilio Therapeutics.

XTX201 is a protein-engineered IL-2 agonist, and XTX101 is an Fc-engineered anti-CTLA4 monoclonal antibody. Both are novel molecules designed to bind their targets preferentially in tumors while minimizing activity in healthy non-tumor tissues. The new data demonstrate preclinical proof-of-concept for these molecules with significant anti-tumor effects and minimal peripheral effects in animal models, significantly widening the potential therapeutic index for these therapies vs. currently available treatments.

Abstracts and presentations at SITC (Free SITC Whitepaper) 2020

XTX201, a protein-engineered IL-2, exhibits tumor-selective activity in mice without peripheral toxicities in non-human primates (Poster Presentation, Abstract #568)
Tumor-activated Fc-engineered anti-CTLA-4 monoclonal antibody, XTX101, demonstrates tumor-selective PD and efficacy in preclinical models (Oral Presentation, Abstract #587)