Multidirectional Strategies for Targeted Delivery of Oncolytic Viruses by Tumor Infiltrating Immune Cells

Oncolytic virus (OV) immunotherapy has demonstrated to be a promising approach in cancer treatment due to tumor-specific oncolysis. However, their clinical use so far has been largely limited due to the lack of suitable delivery strategies with high efficacy. Direct 'intratumoral' injection is the way to cross the hurdles of systemic toxicity, while providing local effects. Progress in this field has enabled the development of alternative way using 'systemic' oncolytic virotherapy for producing better results. One major potential roadblock to systemic OV delivery is the low virus persistence in the face of hostile immune system. The delivery challenge is even greater when attempting to target the oncolytic viruses into the entire tumor mass, where not all tumor cells are equally exposed to exactly the same microenvironment. The microenvironment of many tumors is known to be massively infiltrated with various types of leucocytes in both primary and metastatic sites. Interestingly, this intratumoral immune cell heterogeneity exhibits a degree of organized distribution inside the tumor bed as evidenced, for example, by the hypoxic tumor microenviroment where predominantly recruits tumor-associated macrophages. Although in vivo OV delivery seems complicated and challenging, recent results are encouraging for decreasing the limitations of systemically administered oncolytic viruses and an improved efficiency of oncolytic viral therapy in targeting cancerous tissues in vitro. Here, we review the latest developments of carrier cell-based oncolytic virus delivery using tumor-infiltrating immune cells with a focus on the main features of each cellular vehicle.

Profiling Tumor Infiltrating Immune Cells with CIBERSORT

Tumor infiltrating leukocytes (TILs) are an integral component of the tumor microenvironment and have been found to correlate with prognosis and response to therapy. Methods to enumerate immune subsets such as immunohistochemistry or flow cytometry suffer from limitations in phenotypic markers and can be challenging to practically implement and standardize. An alternative approach is to acquire aggregative high dimensional data from cellular mixtures and to subsequently infer the cellular components computationally. We recently described CIBERSORT, a versatile computational method for quantifying cell fractions from bulk tissue gene expression profiles (GEPs). Combining support vector regression with prior knowledge of expression profiles from purified leukocyte subsets, CIBERSORT can accurately estimate the immune composition of a tumor biopsy. In this chapter, we provide a primer on the CIBERSORT method and illustrate its use for characterizing TILs in tumor samples profiled by microarray or RNA-Seq.

Tumor infiltrating leukocyte density is independent of tumor grade and molecular subtype in aggressive breast cancer of Western Kenya

Background

Tumors commonly are infiltrated by leukocytes, or tumor infiltrating leukocytes (TILs). It remains unclear, however, if the density and type of individual TILs has a direct or simply correlative role in promoting poor prognosis in breast cancer patients. Breast cancer in Kenyan women is aggressive with presentation at a young age, with advanced grade (grade III), large tumor size (>2.0 cm), and poor prognosis. We previously observed that the tumors were predominantly estrogen receptor positive (ER+) but also included both a high percentage of triple negative tumors and also increased immune cell infiltration within the tumors. We used breast tumor tissues from each patient to make tissue microarrays that were then stained for leukocyte and myeloid markers including CD4, CD8, CD20, CD25, CD68, and CD163 using immunohistochemical techniques. The immune cell infiltration into the cancer tissue included increased numbers of macrophages (CD68+), helper T cells (CD4+), and CD25+ lymphocytes compared to benign tissue.

Results

This study characterized the grade, molecular subtypes, and proliferation index of these tumors and determined if TIL density was enriched across any of these factors. We analyzed 49 malignant patient tissue samples for this study. The patient population had a mean age of 51.9 years. The tumors analyzed were heterogeneous by grade: grade I (6%), grade II (47%), and grade III (39%). Most patients presented with large tumors (>2.0 cm) (69%). We classified the tumors into molecular subtypes based on clinical marker expression. Based on this analysis, the molecular subtype distribution was heterogeneous with luminal B (41%), basal/triple negative (TN) (37%), luminal A (14%) and HER2 (8%) breast cancer subtypes. While the basal/TN subtype had a much higher proliferative index (Ki-67+) than did the other molecular subtypes, we did not see a significant correlation between TIL density and either subtype or tumor grade. Therefore, TIL density is independent of molecular subtype and grade.

Conclusion

This study identified a Kenyan patient cohort that develops large, high-grade tumors primarily of the luminal B and basal molecular subtypes. After analyzing the TILs within these tumors, we found that immune cell infiltration of these tumors correlated with increased proliferation but not grade or molecular subtype. Future research is required to determine if the aberrant recruitment of TILs to tumors contributes to cancer progression and response to cancer treatments.