Citations

Abstract Background: Understanding the spatial interactions between tumor and immune cells in the heterogeneous tumor microenvironment is pivotal to improve clinical outcomes of immunotherapy. Various multiplexed imaging platforms have been recently developed to visualize the different immune cell subtypes with various distribution patterns that can impact the antitumor immunity. However, the lack of tools that allow for the spatial pattern modeling remains a major barrier for systematic analysis of cellular interactions in the TME. Methods: We used multiplexed immunohistochemistry (mIHC) to understand the cellular interplays in metastatic melanoma TME using FFPE section. This platform allows in situ quantitative single cell analysis with high-level of multiplexing while preserving the tumor heterogeneity. Single cell spatial data (position and location) in the context of TME can be obtained during mIHC, enabling further spatial modeling to characterize the cellular interactions between tumor immune cells. Novel spatial analysis algorithms are developed taking advantages of these spatial data. Results: Using R programming language, we developed two novel analytical approaches to reveal the spatial distributions of various immune cell subtypes relative to tumor cells. The cell neighborhood analysis algorithm uses the “applynbd()” function to traverse through every cellular point on a two-dimensional plane and creates neighborhoods of 24um in diameter centered by a tumor cell. This algorithm captures the counts of a specific type of immune cells that are in direct contact with a tumor cell, allowing the visualization and statistical analysis of cellular attraction/repulsion patterns. The cell aggregate analysis algorithm uses a sliding-window based approach to capture cell aggregates with certain densities and the areas within the TME covered by specific cell aggregates. Combined with the Ripley K-function, the cell aggregate algorithm captures the aggregation vs. segregation pattern between different cell types, enabling the clustering and distance analysis of immune cells relative to tumor cells. Our algorithms demonstrate that tumor cells either attract CD3+ tumor-infiltrating T cells or favor the aggregation of CD20+ B cell in peri-tumor areas depends on the levels of tumor cell human leukocyte antigen-1 (HLA-1) expression. Conclusion: Our novel spatial analysis algorithms enable the modeling of different interaction patterns between tumor and immune cells (direct contact vs. aggregation) at both single cell and TME level. It demonstrates that tumor cells with heterogeneous properties can impact the immune cells’ distributions in the TME with various biological outcomes. It also establishes tools that are necessary for systematic analysis of the TME, allowing the elucidation of the “homogeneous patterns” within the heterogeneous TME. Citation Format: Yiyi Yan, Alberto Santamaria-Pang, Michael Gerdes, Fiona Ginty, Anup Sood, Svetomir N. Markovic, Alexey Leontovich. Novel algorithms for spatial modeling of cellular interactions in the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 547. doi:10.1158/1538-7445.AM2017-547

AbstractLaboratory professionals are in an ideal situation to identify CBC and peripheral blood smear findings that raise the possibility of a hematolymphoid neoplasm, and based on this information make recommendations for additional studies, such as flow cytometric immunophenotyping. In some circumstances a definitive diagnosis can be established from the combined peripheral blood morphologic and immunophenotypic findings obviating the need for bone marrow evaluation, such as for chronic lymphocytic leukemia. Occasionally flow cytometric studies are superior to morphologic assessment, such as in screening for hairy cell leukemia or identifying lymphocytic‐variant hypereosinophilia. However, there is increasing recognition of small immunophenotypically unusual or abnormal populations of peripheral blood cells, particularly in older patients, which are of uncertain clinical significance, such as monoclonal B lymphocytosis and T‐cell clonopathy. Therefore, it is important to integrate peripheral blood smear review findings with the clinical and other information before recommending flow cytometry. In addition, it is important to recognize situations where the results of peripheral blood smear review and flow cytometric immunophenotyping do not explain the clinical findings.

Abstract The variable clinical success with immune checkpoint inhibitors in the treatment of solid tumors challenges us to further understand the regulatory mechanisms of immune cells infiltration – a critical step of tumor elimination – in a highly heterogenous tumor microenvironment (TME). Systemic analyses of the tumor-immune cell interface and interactions are of particular significance with direct clinical impact. We employed a multiplexed immunofluorescence (MxIF) method, a novel technology that allows in situ quantitative single cell characterization with high order protein multiplexing on whole tumor sections, to elucidate the key components in TME governing the immune cells' composition and function in metastatic melanoma lymph node metastases. Here, we show that the expression of tumor cell Human Leukocyte Antigen 1 (HLA-1) is highly heterogeneous both within the TME and between patients. The level of tumor HLA-1 expression directly correlates with the magnitude of cytotoxic T lymphocytes (CTLs) infiltration in the TME. In addition, decreased tumor HLA-1 expression is associated with accumulation of CD20+ cells at the edge of the tumor as well as an increased population of CD4+FOXP3+ cells. The association between tumor HLA-1 expression and immune cell distribution is highly consistent yet heterogenous across the entire tumor mass. Moreover, using quantitative single cell data, we developed algorithms for computational and spatial modeling of tumor-immune cell interfaces, allowing statistical comparison of cellular interactions in the context of tumor heterogeneity. Spatial analysis demonstrates that tumor HLA-1 expression favors CTL invasion, while lack of tumor HLA-1 expression results in CTL evasion. Furthermore, in a cohort of 166 Stage III melanoma patients, we confirm that CTLs infiltration is only present in regions with high tumor HLA-1 expressions, and that patients with tumors high in both tumor HLA-1 and CTLs have significantly improved progression free survival (PFS) compared with those with tumors low in HLA-1 and/or CTLs. Our study demonstrates that the heterogeneous tumor HLA-1 expression results in various immune cell distribution patterns in the TME, directly contributing to the varied antitumor immunities and ultimately influencing tumor outcomes. As part of the antigen presentation machinery, HLA-1 expression on tumors is necessary for CTLs infiltration and is indispensable for T cell mediated tumor elimination with direct clinical benefits. We also establish a novel platform for visualization and spatial representation of the cellular heterogeneity within the TME, providing data processing and modeling algorithms necessary for understanding the cellular interplay mediating tumor surveillance, which will ultimately improve therapeutic efficacy and clinical outcomes. Citation Format: Yiyi Yan, Alexey Leontovich, Thomas Flotte, Michael Gerdes, Fiona Ginty, Alberto Santamaria-Pang, Anup Sood, Keyur Desai, Chrystal Chadwick, Rong Zhang, Svetomir N. Markovic. Tumor HLA Class I expression influences immune cells infiltration in metastatic melanoma tumor microenvironment. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A71.

Objective Oncolytic viruses (OVs) represent promising, proinflammatory cancer treatments. Here, we explored whether OV-induced innate immune responses could simultaneously inhibit HCV while suppressing hepatocellular carcinoma (HCC). Furthermore, we extended this exemplar to other models of virus-associated cancer. Design and results Clinical grade oncolytic orthoreovirus (Reo) elicited innate immune activation within primary human liver tissue in the absence of cytotoxicity and independently of viral genome replication. As well as achieving therapy in preclinical models of HCC through the activation of innate degranulating immune cells, Reo-induced cytokine responses efficiently suppressed HCV replication both in vitro and in vivo. Furthermore, Reo-induced innate responses were also effective against models of HBV-associated HCC, as well as an alternative endogenous model of Epstein–Barr virus-associated lymphoma. Interestingly, Reo appeared superior to the majority of OVs in its ability to elicit innate inflammatory responses from primary liver tissue. Conclusions We propose that Reo and other select proinflammatory OV may be used in the treatment of multiple cancers associated with oncogenic virus infections, simultaneously reducing both virus-associated oncogenic drive and tumour burden. In the case of HCV-associated HCC (HCV-HCC), Reo should be considered as an alternative agent to supplement and support current HCV-HCC therapies, particularly in those countries where access to new HCV antiviral treatments may be limited.

Abstract Previous preclinical studies and a phase I clinical trial suggested that myo-inositol may be a safe and effective lung cancer chemopreventive agent. We conducted a randomized, double blind, placebo-controlled phase IIb study to determine the chemopreventive effects of myo-inositol in smokers with bronchial dysplasia. Smokers with ≥1 site of dysplasia identified by autofluorescence bronchoscopy-directed biopsy were randomly assigned to receive oral placebo or myo-inositol, 9 g once a day for 2 weeks, and then twice a day for 6 months. The primary endpoint was change in dysplasia rate after 6 months of intervention on a per-participant basis. Other trial endpoints reported herein include Ki-67 labeling index, blood and bronchoalveolar lavage fluid (BAL) levels of proinflammatory, oxidant/antioxidant biomarkers, and an airway epithelial gene expression signature for PI3K activity. Seventy-four (n = 38 myo-inositol and n = 36 placebo) participants with a baseline and 6-month bronchoscopy were included in all efficacy analyses. The complete response and the progressive disease rates were 26.3% versus 13.9% and 47.4% versus 33.3%, respectively, in the myo-inositol and placebo arms (P = 0.76). Compared with placebo, myo-inositol intervention significantly reduced IL6 levels in BAL over 6 months (P = 0.03). Among those with a complete response in the myo-inositol arm, there was a significant decrease in a gene expression signature reflective of PI3K activation within the cytologically normal bronchial airway epithelium (P = 0.002). The heterogeneous response to myo-inositol suggests a targeted therapy approach based on molecular alterations is needed in future clinical trials to determine the efficacy of myo-inositol as a chemopreventive agent. Cancer Prev Res; 9(12); 906–14. ©2016 AACR.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932