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Background: Exposure to cigarette smoke, particularly in early life, is modestly associated with ovarian cancer risk and may impact systemic immunity and the tumor immune response. However, no studies have evaluated whether cigarette smoke exposure impacts the ovarian tumor immune microenvironment. Methods: Participants in the Nurses’ Health Study (NHS) and NHSII reported on early life exposure to cigarette smoke and personal smoking history on questionnaires (n = 165,760). Multiplex immunofluorescence assays were used to measure markers of T cells and immune checkpoints in tumor tissue from 385 incident ovarian cancer cases. We used Cox proportional hazards models to evaluate HRs and 95% confidence intervals (CI) for developing ovarian tumors with a low ( Results: Women exposed versus not to cigarette smoke early in life had a higher risk of developing ovarian cancer with low levels of T cells overall (CD3+: HR: 1.54, 95% CI: 1.08–2.20) and recently activated cytotoxic T cells (CD3+CD8+CD69+: HR: 1.45, 95% CI: 1.05–2.00). These findings were not statistically significant at the Bonferroni-corrected P value of 0.0083. Adult smoking was not significantly associated with tumor immune markers after Bonferroni correction. Conclusions: These results suggest early life cigarette smoke exposure may modestly increase risk of developing ovarian tumors with low abundance of total T cells and recently activated cytotoxic T cells. Impact: Future research should focus on understanding the impact of exposures throughout the life course on the ovarian tumor immune microenvironment.

Supplemental Table 1 shows the correlations of percentages of the markers in the tumor.

Supplemental Figure 1 provides representative images from the T cell panel for high-grade serous, endometrioid, clear cell, and mucinous tumors.

Supplemental Figure 2 provides representative images from the immune checkpoint panel for high-grade serous, endometrioid, clear cell, and mucinous tumors.

Supplemental Table 2 shows the distribution of presence/absence of percentage of the marker in the tumor, by age of sample for type I and type II tumors

Supplemental Table 3 shows case characteristics included on tissue microarrays in NHS and NHSII

Supplemental Table 4 shows beta binomial models, odds ratios and 95% confidence intervals for marker positivity in the tumor, by tumor and participant characteristics

Background:Despite the immunogenic nature of many ovarian tumors, treatment with immune checkpoint therapies has not led to substantial improvements in ovarian cancer survival. To advance population-level research on the ovarian tumor immune microenvironment, it is critical to understand methodologic issues related to measurement of immune cells on tissue microarrays (TMA) using multiplex immunofluorescence (mIF) assays.Methods:In two prospective cohorts, we collected formalin-fixed, paraffin-embedded ovarian tumors from 486 cases and created seven TMAs. We measured T cells, including several sub-populations, and immune checkpoint markers on the TMAs using two mIF panels. We used Spearman correlations, Fisher exact tests, and multivariable-adjusted beta-binomial models to evaluate factors related to immune cell measurements in TMA tumor cores.Results:Between-core correlations of intratumoral immune markers ranged from 0.52 to 0.72, with more common markers (e.g., CD3+, CD3+CD8+) having higher correlations. Correlations of immune cell markers between the whole core, tumor area, and stromal area were high (range 0.69–0.97). In multivariable-adjusted models, odds of T-cell positivity were lower in clear cell and mucinous versus type II tumors (ORs, 0.13–0.48) and, for several sub-populations, were lower in older tissue (sample age > 30 versus ≤ 10 years; OR, 0.11–0.32).Conclusions:Overall, high correlations between cores for immune markers measured via mIF support the use of TMAs in studying ovarian tumor immune infiltration, although very old samples may have reduced antigenicity.Impact:Future epidemiologic studies should evaluate differences in the tumor immune response by histotype and identify modifiable factors that may alter the tumor immune microenvironment.

Supplemental Table 5 shows beta binomial models, odds ratios and 95% confidence intervals for marker positivity in the tumor, by population characteristics

Cutaneous T-cell lymphoma (CTCL) is a rare cancer of skin-homing T cells. A subgroup of patients develops large cell transformation with rapid progression to an aggressive lymphoma. Here, we investigated the transformed CTCL (tCTCL) tumor ecosystem using integrative multiomics spanning whole-exome sequencing (WES), single-cell RNA sequencing, and immune profiling in a unique cohort of 56 patients. WES of 70 skin biopsies showed high tumor mutation burden, UV signatures that are prognostic for survival, exome-based driver events, and most recurrently mutated pathways in tCTCL. Single-cell profiling of 16 tCTCL skin biopsies identified a core oncogenic program with metabolic reprogramming toward oxidative phosphorylation (OXPHOS), cellular plasticity, upregulation of MYC and E2F activities, and downregulation of MHC I suggestive of immune escape. Pharmacologic perturbation using OXPHOS and MYC inhibitors demonstrated potent antitumor activities, whereas immune profiling provided in situ evidence of intercellular communications between malignant T cells expressing macrophage migration inhibitory factor and macrophages and B cells expressing CD74.Significance:Our study contributes a key resource to the community with the largest collection of tCTCL biopsies that are difficult to obtain. The multiomics data herein provide the first comprehensive compendium of genomic alterations in tCTCL and identify potential prognostic signatures and novel therapeutic targets for an incurable T-cell lymphoma.This article is highlighted in the In This Issue feature, p. 1171

Supplementary Data from Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma

Supplementary Table from Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma

Supplementary Figure from Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma

Advances in the understanding of the tumor microenvironment have led to development of immunotherapeutic strategies, such as chimeric antigen receptor T cells (CAR-Ts). However, despite success in blood malignancies, CAR-T therapies in solid tumors have been hampered by their restricted infiltration. Here, we used our understanding of early cytotoxic lymphocyte infiltration of human lymphocytes in solid tumors in vivo to investigate the receptors in normal, adjacent, and tumor tissues of primary non-small-cell lung cancer specimens. We found that CX3CL1-CX3CR1 reduction restricts cytotoxic cells from the solid-tumor bed, contributing to tumor escape. Based on this, we designed a CAR-T construct using the well-established natural killer group 2, member D (NKG2D) CAR-T expression together with overexpression of CX3CR1 to promote their infiltration. These CAR-Ts infiltrate tumors at higher rates than control-activated T cells or IL-15-overexpressing NKG2D CAR-Ts. This construct also had similar functionality in a liver-cancer model, demonstrating potential efficacy in other solid malignancies.

Background: Tumor-infiltrating lymphocytes (TIL) confer a survival benefit among patients with ovarian cancer; however, little work has been conducted in racially diverse cohorts. Methods: The current study investigated racial differences in the tumor immune landscape and survival of age- and stage-matched non-Hispanic Black and non-Hispanic White women with high-grade serous ovarian carcinoma (HGSOC) enrolled in two population-based studies (n = 121 in each racial group). We measured TILs (CD3+), cytotoxic T cells (CD3+CD8+), regulatory T cells (CD3+FoxP3+), myeloid cells (CD11b+), and neutrophils (CD11b+CD15+) via multiplex immunofluorescence. Multivariable Cox proportional hazard regression was used to estimate the association between immune cell abundance and survival overall and by race. Results: Overall, higher levels of TILs, cytotoxic T cells, myeloid cells, and neutrophils were associated with better survival in the intratumoral and peritumoral region, irrespective of tissue compartment (tumor, stroma). Improved survival was noted for T-regulatory cells in the peritumoral region and in the stroma of the intratumoral region, but no association for intratumoral T-regulatory cells. Despite similar abundance of immune cells across racial groups, associations with survival among non-Hispanic White women were consistent with the overall findings, but among non-Hispanic Black women, most associations were attenuated and not statistically significant. Conclusions: Our results add to the existing evidence that a robust immune infiltrate confers a survival advantage among women with HGSOC; however, non-Hispanic Black women may not experience the same survival benefit as non-Hispanic White women with HGSOC. Impact: This study contributes to our understanding of the immunoepidemiology of HGSOC in diverse populations.

IntroductionIn clear cell renal cell carcinoma (ccRCC), tumor-associated macrophage (TAM) induction of CD8+T cells into a terminally exhausted state has been implicated as a major mechanism of immunotherapy resistance, but a deeper biological understanding is necessary.MethodsPrimary ccRCC tumor samples were obtained from 97 patients between 2004 and 2018. Multiplex immunofluorescence using lymphoid and myeloid markers was performed in seven regions of interest per patient across three predefined zones, and geospatial analysis was performed using Ripley’s K analysis, a methodology adapted from ecology.ResultsClustering of CD163+M2 like TAMs into the stromal compartment at the tumor–stroma interface was associated with worse clinical stage (tumor/CD163+nK(75): stage I/II: 4.4 (IQR −0.5 to 5.1); stage III: 1.4 (IQR −0.3 to 3.5); stage IV: 0.6 (IQR −2.1 to 2.1); p=0.04 between stage I/II and stage IV), and worse overall survival (OS) and cancer-specific survival (CSS) (tumor/CD163+nK(75): median OS–hi=149 months, lo=86 months, false-discovery rate (FDR)-adj. Cox pConclusionsGeospatial clustering of CD163+M2 like TAMs into the stromal compartment at the tumor–stromal interface was associated with poor clinical outcomes and CD8+T cell terminal exhaustion.

Abstract Cutaneous T-cell lymphoma (CTCL) is a rare cancer of skin-homing T cells. A subgroup of patients develops large cell transformation with rapid progression to an aggressive lymphoma. Here, we investigated the transformed CTCL (tCTCL) tumor ecosystem using integrative multiomics spanning whole-exome sequencing (WES), single-cell RNA sequencing, and immune profiling in a unique cohort of 56 patients. WES of 70 skin biopsies showed high tumor mutation burden, UV signatures that are prognostic for survival, exome-based driver events, and most recurrently mutated pathways in tCTCL. Single-cell profiling of 16 tCTCL skin biopsies identified a core oncogenic program with metabolic reprogramming toward oxidative phosphorylation (OXPHOS), cellular plasticity, upregulation of MYC and E2F activities, and downregulation of MHC I suggestive of immune escape. Pharmacologic perturbation using OXPHOS and MYC inhibitors demonstrated potent antitumor activities, whereas immune profiling provided in situ evidence of intercellular communications between malignant T cells expressing macrophage migration inhibitory factor and macrophages and B cells expressing CD74. Significance: Our study contributes a key resource to the community with the largest collection of tCTCL biopsies that are difficult to obtain. The multiomics data herein provide the first comprehensive compendium of genomic alterations in tCTCL and identify potential prognostic signatures and novel therapeutic targets for an incurable T-cell lymphoma. This article is highlighted in the In This Issue feature, p. 1171

INTRODUCTION AND OBJECTIVE:Clear cell renal cell carcinoma (ccRCC) tumors harbor comparatively low frequencies of genetic alterations yet very high levels of immune cell infiltration. Identifying a...

INTRODUCTION AND OBJECTIVE:Immune infiltration is typically quantified using cellular density, not accounting for cellular clustering. Tumor-associated macrophages (TAM) activate oncogenic signalin...

Despite being immunogenic, high-grade serous ovarian carcinomas (HGSC), the most common histotype, generally are not responsive to immune checkpoint inhibitors. To understand potential reasons for this, we examined associations of tumor-infiltrating B cells and T cells, including sub-populations defined by expression of immune checkpoints and T cell exhaustion markers, with survival in three epidemiologic studies. Analyses included participants in the Nurses’ Health Study (NHS), NHSII, and New England Case-control study who were diagnosed with stage 1-3 HGSC for whom tumor tissue was obtained. B cells (CD19, CD20, CD138), T cells (CD3), and T cell subpopulations (CD3 co-localized with CD8, CD4, PD1, PDL1, LAG3, TIM3) were measured using multiplex immunofluorescence assays performed on tissue microarray slides containing 3 cores per case. For each participant, we summed counts of immune cells infiltrating the tumor and total tumor cells across cores. Counts of immune cell subpopulations were adjusted for the parent cell count using residuals from beta-binomial models. Hazard ratios (HR) and 95% confidence intervals (CI) for overall mortality according to presence/absence or quantiles of immune cells were calculated using Cox proportional hazards regression models adjusting for age at diagnosis, diagnosis year, stage, study, and total tumor cell count. Among 389 women with HGSC, presence vs. absence of CD19+ B cells was suggestively associated with lower mortality (HR 0.79, 95%CI:0.61-1.01); similar associations were observed for CD19-adjusted CD20+ B cells and CD138+ plasma cells (HRs 0.75-0.78, quintile 5 vs. 1).Higher total T cells was associated with improved survival (HR 0.67, 95%CI:0.45-0.99, quintile 5vs. 1). Similar reduced risks were observed with high levels of both CD19+ B cells and CD3+ T cells (HR 0.66) or high levels of one cell type (HRs 0.65-0.75) compared with low levels of both. For the two primary T cell subfractions, lower risk was observed with higher CD3-adjustedCD3+CD8+ cytotoxic T cells (HRs 0.68, 0.73, 0.69, 0.59 for quintiles 2-5 vs. 1), but notCD3+CD4+ helper T cells (HR 0.97, 95%CI: 0.72-1.31, tertile 3 vs. 1). T cells with immune checkpoint markers (PD1, PDL1) and/or markers of T-cell exhaustion (LAG3, TIM3) generally were not associated with mortality or tended to be associated with lower mortality risk, with a significant inverse association observed for CD3-adjusted CD3+PD1+TIM3- cells (HR 0.61,95%CI:0.41-0.92, quintile 5 vs. 1).Overall, higher levels of B cells and CD3+CD8+ T cells in tumor were associated with improved outcomes, consistent with other studies. Congruent with the apparent ineffectiveness of immune checkpoint inhibitors in ovarian cancer, our results do not support that T cells expressing immune checkpoint and/or T cell exhaustion markers are related to worse outcome among women with HGSC. Future analyses will consider multiple cell types simultaneously and the stroma compartment. Citation Format: Shelley S. Tworoger, Mary K. Townsend, Jose Conejo-Garcia, Brooke L. Fridley, Carlos Moran Segura, Daryoush Saeed-Vafa, Naoko Sasamoto, Kathryn L. Terry. Association of ovarian tumor immune profiles with overall survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5887.

New technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations. However, there are currently few approaches to analyze the spatial context of the TIME. Therefore, we have developed a framework for the spatial analysis of the TIME using Ripley’s K, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness (CSR) as a measure of the interactions between immune cells. This approach was then applied to epithelial ovarian cancer (EOC) using mIF collected on intra-tumoral regions of interest (ROIs) and tissue microarrays (TMAs) from 160 high-grade serous ovarian carcinoma patients in the African American Cancer Epidemiology Study (AACES) (94 subjects on TMAs resulting in 263 tissue cores; 93 subjects with 260 ROIs; 27 subjects with both TMA and ROI data). Cox proportional hazard models were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes (CD3+), cytotoxic T-cells (CD8+CD3+), and regulatory T-cells (CD3+FoxP3+) with overall survival. Analysis was done on TMA and ROIs, treating the TMA data as validation of the findings from the ROIs. We found that EOC patients with high abundance and low spatial clustering of tumor-infiltrating lymphocytes and T-cell subsets in their tumors had the best overall survival. Additionally, patients with EOC tumors displaying high co-occurrence of cytotoxic T-cells and regulatory T-cells had the best overall survival. Grouping women with ovarian cancer based on both cell abundance and spatial contexture showed better discrimination for survival than grouping ovarian cancer cases only by cell abundance. These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the TIME. In conclusion, the application of this spatial analysis framework to the study of the TIME could lead to the identification of immune content and spatial architecture that could aid in the determination of patients that are likely to respond to immunotherapies.

Background Clear cell renal cell carcinoma (ccRCC) tumors have low frequencies of genetic alterations compared with other malignancies, but very high levels of immune cell infiltration and favorable response rates to immunotherapy. Currently, the interplay between specific ccRCC somatic mutations and immune infiltration pattern is unclear. Objective To analyze the associations between common ccRCC somatic mutations and immune cell infiltration patterns within the tumor immune microenvironment (TIME). Design, setting, and participants The study included tumor samples (24 primary and 24 metastatic) from 48 patients with stage IV ccRCC. Targeted sequencing was performed for well-characterized recurrent somatic mutations in ccRCC, with the analysis focusing on the six most common ones: VHL, BAP1, PBRM1, SETD2, TP53, and KDM5C. For each sample, multiplex immunofluorescence (IF) was performed in lymphoid and myeloid panels, for seven regions of interest in three zones (tumor core, stroma, and tumor-stroma interface). IF-derived cellular densities were compared across patients, stratified by their somatic mutation status, using a linear mixed-model analysis. External validation was pursued using RNA-seq enrichment scoring from three large external data sources. Results and limitations Tumors with SETD2 mutations demonstrated significantly decreased levels of FOXP3+ T cells in the tumor core, stroma, and tumor-stroma interface. PBRM1 mutations were associated with decreased FOXP3+ T cells in the tumor core. Primary KDM5C mutations were associated with significantly increased CD206+ macrophage tumor infiltration in the tumor core. A computational method estimating immune cell types in the TIME using bulk RNA-seq data, xCell scoring, failed to validate associations from the IF analysis in large external data sets. A major limitation of the study is the relatively small patient population studied. Conclusions This study provides evidence that common somatic mutations in ccRCC, such as SETD2, PBRM1, and KDM5C, are associated with distinct immune infiltration patterns within the TIME. Patient summary In this study, we analyzed tumor samples from patients with metastatic kidney cancer to determine whether common genetic mutations that arise from the cancer cells are associated with the density of immune cells found within those tumors. We found several distinct immune cell patterns that were associated with specific genetic mutations. These findings provide insight into the interaction between cancer genetics and the immune system in kidney cancer.

Immune infiltration is typically quantified using cellular density, not accounting for cellular clustering. Tumor-associated macrophages (TAM) activate oncogenic signaling through paracrine interactions with tumor cells, which may be better reflected by local cellular clustering than global density metrics. Using multiplex immunohistochemistry and digital pathologic analysis we quantified cellular density and cellular clustering for myeloid cell markers in 129 regions of interest from 55 samples from 35 patients with metastatic ccRCC. CD68+ cells were found to be clustered with tumor cells and dispersed from stromal cells, while CD163+ and CD206+ cells were found to be clustered with stromal cells and dispersed from tumor cells. CD68+ density was not associated with OS, while high tumor/CD68+ cell clustering was associated with significantly worse OS. These novel findings would not have been identified if immune infiltrate was assessed using cellular density alone, highlighting the importance of including spatial analysis in studies of immune cell infiltration of tumors.SIGNIFICANCEIncreased clustering of CD68+ TAMs and tumor cells was associated with worse overall survival for patients with metastatic ccRCC. This effect would not have been identified if immune infiltrate was assessed using cell density alone, highlighting the importance of including spatial analysis in studies of immune cell infiltration of tumors.

Background Tumor associated macrophages (TAM) stimulate tumor proliferation and facilitate immune escape via production of immunosuppressive cytokines. We hypothesize that non-random spatial clustering of TAMs within the tumor are associated with poor survival in ccRCC patients. Methods Tumor specimens were obtained from 41 patients with metastatic ccRCC who received immunotherapy (IT). Sections from the tumor core underwent multiplex immunofluorescence staining for CD68, CD163, and CD206. Digital pathologic analysis was used to convert the digital images to spatial point pattern plots (PPP). Ripley’s K function, the current standard metric for spatial heterogeneity, was utilized. Novel metrics were developed using a probability density function (PDF) for distances between cells, assuming that cells can be located anywhere with equal probability. Empirical histograms were generated from the PPPs. Deviation from the PDF demonstrates a non-random distribution. Deviations were quantified with the Kolmogorov-Smirnov (KS) test and Cramer-von Mises (CVM) criterion. Overall survival (OS) was assessed between groups stratified by the median value for each metric using Kaplan-Meier and log-rank analysis. Figure 1A. Results 75 slides were analyzed from the 41 patients. The three metrics for measuring spatial heterogeneity had moderate and statistically significant correlation with each other (Spearman’s R: Ripley/KS=0.68, p Conclusions We describe CVM and KS as novel metrics for measuring spatial heterogeneity of immune cells. Increased spatial heterogeneity of CD68+ TAMs and tumor cells was associated with worse OS in patients with metastatic ccRCC who received IT. These findings corroborate prior reports of TAMs eliciting an immunosuppressive effect on the tumor-immune microenvironment, and demonstrate the novel finding of a clinically significant effect of TAM spatial clustering on OS.

Summary A clearer understanding of the tumor immune microenvironment (TIME) in metastatic clear cell renal cell carcinoma (ccRCC) may help to inform precision treatment strategies. We sought to identify clinically meaningful TIME signatures in ccRCC. We studied tumors from 39 patients with metastatic ccRCC using quantitative multiplexed immunofluorescence and relevant immune marker panels. Cell densities were analyzed in three regions of interest (ROIs): tumor core, tumor–stroma interface and stroma. Patients were stratified into low- and high-marker density groups using median values as thresholds. Log-rank and Cox regression analyses while controlling for clinical variables were used to compare survival outcomes to patterns of immune cell distributions. There were significant associations with increased macrophage (CD68+CD163+CD206+) density and poor outcomes across multiple ROIs in primary and metastatic tumors. In primary tumors, T-bet+ T helper type 1 (Th1) cell density was highest at the tumor–stromal interface (P = 0·0021), and increased co-expression of CD3 and T-bet was associated with improved overall survival (P = 0·015) and survival after immunotherapy (P = 0·014). In metastatic tumor samples, decreased forkhead box protein 3 (FoxP3)+ T regulatory cell density correlated with improved survival after immunotherapy (P = 0·016). Increased macrophage markers and decreased Th1 T cell markers within the TIME correlated with poor overall survival and treatment outcomes. Immune markers such as FoxP3 showed consistent levels across the TIME, whereas others, such as T-bet, demonstrated significant variance across the distinct ROIs. These findings suggest that TIME profiling outside the tumor core may identify clinically relevant associations for patients with metastatic ccRCC.

A survival benefit has been consistently observed for tumor infiltrating lymphocytes (TILs) among ovarian cancer patients; however, prior studies consist of predominantly white women and little work has been conducted in racially diverse cohorts. Here, we investigate racial differences in the tumor immune landscape and survival among African-American (AA) and white women with high-grade serous ovarian carcinoma (HGSOC), the most common histotype of ovarian cancer. Leveraging two population-based case-control studies of ovarian cancer, the African-American Cancer Epidemiology Study and the North Carolina Ovarian Cancer Study, treatment-naïve AA women with HGSOC were matched to white women with HGSOC by stage and age. Multiplex immunofluorescence staining was performed on formalin-fixed paraffin-embedded whole tissue sections to measure TILs (CD3+) and T-cell subsets, cytotoxic (CD3+CD8+) and regulatory (CD3+FoxP3+) T-cells. Image analysis was completed on three regions of interest (ROI) selected from the intratumoral region. We categorized immune cell abundance within the tumor, stroma, and overall as Citation Format: Lauren C Peres, Christelle Colin-Leitzinger, Sweta Sinha, Jeffrey R. Marks, Jose R. Conejo-Garcia, Anthony J. Alberg, Elisa V. Bandera, Andrew Berchuck, Melissa L. Bondy, Brock C. Christensen, Michele L. Cote, Jennifer A. Doherty, Patricia G. Moorman, Carlos Moran Segura, Jonathan V. Nguyen, Edward S. Peters, Ann G. Schwartz, Paul D. Terry, Christopher M. Wilson, Brooke L. Fridley, Joellen M. Schildkraut. Racial differences in the tumor immune landscape and survival of high-grade serous ovarian carcinoma [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-232.

Simple Summary Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME. Abstract Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.

INTRODUCTION Tumor associated macrophages (TAM) stimulate tumor proliferation and facilitate immune escape via production of immunosuppressive cytokines. We hypothesize that non-random spatial clustering of TAMs within the tumor is associated with poor survival in RCC patients. METHODS Primary and metastatic tumor specimens were obtained from 39 patients with metastatic RCC who received immunotherapy (IT). 29 patients (74.3%) also received targeted therapy (TT) at some point during their disease course. Sections from the tumor compartment underwent immunohistochemical (IHC) staining for pan-macrophage marker CD68, and M2 markers CD163 and CD206. Digital pathologic analysis was used to convert the digital images to spatial point pattern plots (PPP). A probability density function (PDF) for the distance between cells was calculated under the assumption that cells can be located anywhere in the slide with equal probability. The PDF was then compared to empirical histograms of cells derived from the PPP. Deviations from the PDF, the expected random distribution, reveal evidence of cell clustering or dispersion. We assessed deviations with the Kolmogorov-Smirnov (KS) test. Patients were stratified by the median value into high and low KS groups, and survival outcomes were compared between the two groups using a Cox regression. A high KS statistic indicates a good fit between the two curves (in this case, randomness), and a low KS statistic indicates a poor fit (in this case, dispersion or clustering). RESULTS Among primary tumor specimens, spatial clustering of CD68+ cells was associated with worse overall survival (OS) (HR -1.7, p=0.015), worse OS from IT initiation (HR -1.5, p=0.025), and no difference in OS from TT initiation (HR -0.4, p=0.48). Among metastatic tumor specimens, spatial clustering of CD68+ cells was not associated with any of the three survival outcomes (OS: HR 0.9, p=0.11; OS from IT: HR 0.7, p=0.20; OS from TT: HR 0.0, p=0.97). Spatial clustering of CD163+ cells was not associated with any of the three survival outcomes for either primary and metastatic sites. Spatial clustering of CD206+ cells was not associated with any of the three survival outcomes for either primary and metastatic sites. CONCLUSION Non-random spatial clustering of CD68+ TAMs in the primary tumor specimen was associated with worse survival, driven primarily by worse survival from initiation of immunotherapy. These findings corroborate prior reports of TAMs eliciting an immunosuppressive effect on the tumor-immune microenvironment, introduce novel methodology for quantifying spatial heterogeneity, and demonstrate the novel finding of a clinically significant effect of TAM spatial clustering on overall survival. Citation Format: Gregory J. Kimmel, Nicholas H. Chakiryan, Youngchul Kim, Ali J. Hajiran, Ahmet M. Aydin, Jonathan V. Nguyen, Carlos M. Moran-Segura, Jasreman Dhillon, Philipp Altrock, Brandon J. Manley. Non-random spatial clustering of tumor associated macrophages is associated with poor survival in metastatic RCC patients receiving immunotherapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-034.