Immune infiltrate analysis to reveal distinct immune classes for leiomyosarcomas.

person Alicia Gingrich The University of Texas MD Anderson Cancer Center, Houston, TX info_outline Alicia Gingrich, Hannah Beird, Rossana Lazcano Segura, Ryan Denu, Michael Nakazawa, Ravin Ratan, J. Andrew Livingston, Maria Alejandra Zarzour, Anthony Paul Conley, Neeta Somaiah, Dejka M. Araujo, S Shreyaskumar Patel, Christina Lynn Roland, Andrew Futreal, Alexander J. Lazar, Emily Zhi-Yun Keung, Elise F Nassif Haddad

Authors person Alicia Gingrich The University of Texas MD Anderson Cancer Center, Houston, TX info_outline Alicia Gingrich, Hannah Beird, Rossana Lazcano Segura, Ryan Denu, Michael Nakazawa, Ravin Ratan, J. Andrew Livingston, Maria Alejandra Zarzour, Anthony Paul Conley, Neeta Somaiah, Dejka M. Araujo, S Shreyaskumar Patel, Christina Lynn Roland, Andrew Futreal, Alexander J. Lazar, Emily Zhi-Yun Keung, Elise F Nassif Haddad Organizations The University of Texas MD Anderson Cancer Center, Houston, TX, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX Abstract Disclosures Research Funding No funding sources reported Background: Leiomyosarcomas (LMS) are aggressive malignancies of smooth-muscle origin. Few targeted molecular options exist and immunotherapy (IO) agents against T cells have been disappointing. In this study, we examine the immune infiltrate of LMS tumors by immunohistochemistry (IHC) and gene expression. Our objective was to identify actionable targets for immunotherapy in patients with LMS. Methods: Tumor samples from a series of LMS patients were prospectively collected and banked for DNA and RNA sequencing as part of the MD Anderson Patient Mosaic. Associated clinical data for the patients were collected and maintained. IHC was performed on available separate tissue microarrays. Differential gene expression (DGE) analysis was done using the DESeq2 package for R and the Benjamini-Hochberg procedure used to control for false discovery rate. Immune cell fractions were estimated using the MCPcounter package. All gene expression analyses were repeated on The Cancer Genome Atlas (TCGA) dataset as an independent dataset. Results: A total of 104 TCGA samples and 72 samples from Mosaic from 53 patients with uterine or soft tissue LMS were included in the analysis. Tumors in the TCGA group were treatment naive. Of the samples in the Mosaic group, 61 (85%) had been previously treated with chemotherapy, 8 (11%) had been radiated, and 5 (7.5%) had been previously treated with immunotherapy. Thirty-one (43%) tumors were metastatic. Fifty-one (70%) were soft tissue LMS and 21 (30%) were uterine LMS. Four distinct immune classes were seen in both the TGCA and Mosaic: a predominantly B-cell group, a monocyte/macrophage group, a mixed infiltrate group and a group with a neutrophil signature. DGE performed between the subgroups revealed a unique gene expression pattern for tumors in the B cell and monocyte/macrophage subgroups. Interrogation of specific immune-associated genes revealed low levels of expression in the neutrophil group, suggesting this may be the most immunologically “cold” subset. Some of these results were reproduced by IHC using a TMA: the presence of a cluster of samples with B-cells and higher expression of immune checkpoints, a macrophage driven cluster, and an immunologically cold cluster. Conclusions: Analyses of LMS samples across two large datasets demonstrate the existence of 4 distinct immune classes of tumors that persist despite variation in clinical and treatment conditions: B cell, monocytic/macrophage, mixed-infiltrate and neutrophil rich. The B cell and monocytic groups have increased expression of immune markers which may be amenable to targeted therapies.

Pre-clinical