Neoadjuvant Therapy Induces a Potent Immune Response to Sarcoma, Dominated by Myeloid and B Cells

Abstract

Purpose: To characterize changes in the soft-tissue sarcoma (STS) tumor immune microenvironment induced by standard neoadjuvant therapy with the goal of informing neoadjuvant immunotherapy trial design.

Experimental design: Paired pre- and postneoadjuvant therapy specimens were retrospectively identified for 32 patients with STSs and analyzed by three modalities: multiplexed IHC, NanoString, and RNA sequencing with ImmunoPrism analysis.

Results: All 32 patients, representing a variety of STS histologic subtypes, received neoadjuvant radiotherapy and 21 (66%) received chemotherapy prior to radiotherapy. The most prevalent immune cells in the tumor before neoadjuvant therapy were myeloid cells (45% of all immune cells) and B cells (37%), with T (13%) and natural killer (NK) cells (5%) also present. Neoadjuvant therapy significantly increased the total immune cells infiltrating the tumors across all histologic subtypes for patients receiving neoadjuvant radiotherapy with or without chemotherapy. An increase in the percentage of monocytes and macrophages, particularly M2 macrophages, B cells, and CD4+ T cells was observed postneoadjuvant therapy. Upregulation of genes and cytokines associated with antigen presentation was also observed, and a favorable pathologic response (≥90% necrosis postneoadjuvant therapy) was associated with an increase in monocytic infiltrate. Upregulation of the T-cell checkpoint TIM3 and downregulation of OX40 were observed posttreatment.

Conclusions: Standard neoadjuvant therapy induces both immunostimulatory and immunosuppressive effects within a complex sarcoma microenvironment dominated by myeloid and B cells. This work informs ongoing efforts to incorporate immune checkpoint inhibitors and novel immunotherapies into the neoadjuvant setting for STSs.

Trial registration: ClinicalTrials.gov NCT02923778 NCT03069378 NCT01803152 NCT02180698.

Conflict of interest statement

Conflicts of Interest: The authors have disclosed they have significant relationships with, or financial interest in, the following commercial companies pertaining to this article: PHG received research funding from Gilead Sciences, Inc. outside the submitted work. BL is a paid consultant from Cofactor Genomics, Inc., the company that developed and produces the ImmunoPrism® reagent kit and informatics tools used in this article. JE, KF, and NL are employed by Cofactor Genomics, Inc., which funded and performed the RNA sequencing and ImmunoPrism analysis herein but did not otherwise play a role in the conceptualization, analysis, or presentation of the work herein. LDC received research funding paid to the institution from Eli Lilly, AADi, BluePrint Medicine, Iterion, Gradalis, Philogen, Advenchen Laboratories, and CBA Pharma; LDC has received honoraria or has served on advisory boards for Daichi Sankyo, BluePrint Medicines and Regeneron. JC and RHP are employed by Sensei Biotherapeutics, Inc., which did not play any role in the conceptualization, analysis, or presentation of the work herein. EM, WMB, and TM are employed by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA which funded and performed NanoString nCounter gene expression analysis herein but did not otherwise play a role in the conceptualization, analysis, or presentation of the work herein. SMP reported research funding from Merck during the conduct of the study; research funding from EMD Serono, Incyte, Presage, Janssen, OncoSec, and Juno and consulting, honoraria, and advisory activity with Deciphera, Aadi, Epizyme, Springworks, GlaxoSmithKline, Obsidian, T-knife, Daiichi Sankyo, and Blueprint Medicine, outside the submitted work. MJW reports consulting, honoraria, and advisory activity from Epizyme, Adaptimmune, and Deciphera. The remaining authors declare no potential conflicts of interest.

©2022 American Association for Cancer Research.

Figures

Figure 1.

Experimental design. Multiplexed immunohistochemistry (mIHC), NanoString (800 Gene Immune Panel) and RNA sequencing with analysis by ImmunoPrism platform were performed on paired soft tissue sarcoma tissue samples before and after neoadjuvant therapy. Schema indicates the number of paired samples analyzed by each technology. Two mIHC panels were performed with the indicated markers above (in addition to VISTA which is not shown in Panel 1). Example mIHC of undifferentiated pleomorphic sarcoma tumors paired pre- (A-D) and post-neoadjuvant chemoradiation (E-H) at low (A, C, E, G) and high (B, D, F, H) magnification, with an example of the flow cytometric analysis shown below.

Figure 2.

Tumor infiltrating immune cells pre- and post- neoadjuvant therapy identified by RNA sequencing with analysis by Cofactor ImmunoPrism. (A) Percentage of immune infiltrating cells for all pooled sarcoma subtypes. Individual values, mean and standard deviations are shown. (B) Percentage of immune infiltrating cells by sarcoma subtype. UPS: Undifferentiated pleomorphic sarcoma (n=12); LMS: Leiomyosarcoma (n=2); MRCL: Myxoid/round cell liposarcoma (n=3); SS: Synovial Sarcoma (n=2); EW: Ewing sarcoma (n=2) and other (n=5). Comparisons for statistical differences in means were tested using two-tailed paired t-tests: * p-value

Figure 3.

Myeloid cells pre- and post- neoadjuvant therapy identified by multiplex immunohistochemistry (mIHC) (top row), NanoString quantile normalized mRNA expression (middle row), and RNA sequencing with analysis by ImmunoPrism (bottom row). mIHC: percentage of CD68+/CD163+ cells (A) and CD206+ as percentage of total cells (B). NanoString: quantile normalized expression values for CD163 (C) and CD206 (MRC1) (D) genes. ImmunoPrism: percentage of monocytes (E) and M2 macrophages (F). Individual values, mean and standard deviations are shown. mIHC and ImmunoPrism statistical differences were tested using two-tailed paired t-tests: * p-value

Figure 4.

Tumor infiltrating T cells pre- and post- neoadjuvant therapy identified by mIHC (top row), NanoString quantile normalized mRNA expression (middle row), and RNA sequencing with analysis by ImmunoPrism (bottom row). mIHC: percentage of CD3+ cells (A), CD4+ cells (B) and FOXP3+ T cells (C). NanoString: quantile normalized expression values for CD3G (D), CD4 (E) and FOXP3 (F) genes. ImmunoPrism: percentage of T cells (CD3) (G), CD4 cells (H) and T regulatory cells (Treg) (I). Individual values, mean and standard deviations are shown. mIHC and ImmunoPrism statistical differences were tested using two-tailed paired t-tests: * p-value

Figure 5.

Changes in gene expression pathways after neoadjuvant therapy. (A) Difference in the percentage of monocytes (post – pre neoadjuvant therapy) identified by ImmunoPrism in tumors with a favorable pathological response (≥90% necrosis) vs. 1.5 for upregulation, 3 genes identified are shown. (C) Percentage of HLA-DRHi + non-T cells (CD4- CD8- cells) pre- and post- neoadjuvant therapy identified by mIHC. (D) Percentage of B cells pre- and post- neoadjuvant therapy identified by ImmunoPrism. (E) Percentage of NK cells pre- and post- neoadjuvant therapy identified by ImmunoPrism. Testing for differences in mean levels was performed using two-tailed paired t-tests: * p-value <0.05, ** p-value <0.01.