Endocrine-Exocrine Signaling Drives Obesity-Associated Pancreatic Ductal Adenocarcinoma.

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Molecular analyses of human and murine samples define microenvironmental consequences of obesity that foster tumorigenesis rather than new driver gene mutations, including significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant beta cell expression of the peptide hormone cholecystokinin (Cck) in response to obesity and show that islet Cck promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment and implicate endocrine-exocrine signaling beyond insulin in PDAC development.

Immune cell profiles in the tumor microenvironment of early-onset, intermediate-onset, and later-onset colorectal cancer.

BACKGROUND: Despite heightened interest in early-onset colorectal cancer (CRC) diagnosed before age 50, little is known on immune cell profiles of early-onset CRC. It also remains to be studied whether CRCs diagnosed at or shortly after age 50 are similar to early-onset CRC. We therefore hypothesized that immune cell infiltrates in CRC tissue might show differential heterogeneity patterns between three age groups (< 50 "early onset," 50-54 "intermediate onset," ≥ 55 "later onset"). METHODS: We examined 1,518 incident CRC cases with available tissue data, including 35 early-onset and 73 intermediate-onset cases. To identify immune cells in tumor intraepithelial and stromal areas, we developed three multiplexed immunofluorescence assays combined with digital image analyses and machine learning algorithms, with the following markers: (1) CD3, CD4, CD8, CD45RO (PTPRC), and FOXP3 for T cells; (2) CD68, CD86, IRF5, MAF, and MRC1 (CD206) for macrophages; and (3) ARG1, CD14, CD15, CD33, and HLA-DR for myeloid cells. RESULTS: Although no comparisons between age groups showed statistically significant differences at the stringent two-sided α level of 0.005, compared to later-onset CRC, early-onset CRC tended to show lower levels of tumor-infiltrating lymphocytes (P = 0.013), intratumoral periglandular reaction (P = 0.025), and peritumoral lymphocytic reaction (P = 0.044). Compared to later-onset CRC, intermediate-onset CRC tended to show lower densities of overall macrophages (P = 0.050), M1-like macrophages (P = 0.062), CD14+HLA-DR+ cells (P = 0.015), and CD3+CD4+FOXP3+ cells (P = 0.039). CONCLUSIONS: This hypothesis-generating study suggests possible differences in histopathologic lymphocytic reaction patterns, macrophages, and regulatory T cells in the tumor microenvironment by age at diagnosis.

An integrated analysis of lymphocytic reaction, tumour molecular characteristics and patient survival in colorectal cancer.

BACKGROUND: Histological lymphocytic reaction is regarded as an independent prognostic marker in colorectal cancer. Considering the lack of adequate statistical power, adjustment for selection bias and comprehensive tumour molecular data in most previous studies, we investigated the strengths of the prognostic associations of lymphocytic reaction in colorectal carcinoma by utilising an integrative database of two prospective cohort studies. METHODS: We examined Crohn's-like reaction, intratumoural periglandular reaction, peritumoural reaction and tumour-infiltrating lymphocytes in 1465 colorectal carcinoma cases. Using covariate data of 4420 colorectal cancer cases in total, inverse probability-weighted Cox proportional hazard regression model was used to control for selection bias (due to tissue availability) and potential confounders, including stage, MSI status, LINE-1 methylation, PTGS2 and CTNNB1 expression, KRAS, BRAF and PIK3CA mutations, and tumour neoantigen load. RESULTS: Higher levels of each lymphocytic reaction component were associated with better colorectal cancer-specific survival (Ptrend < 0.002). Compared with cases with negative/low intratumoural periglandular reaction, multivariable-adjusted HRs were 0.55 (95% CI, 0.42-0.71) in cases with intermediate reaction and 0.20 (95% CI, 0.12-0.35) in cases with high reaction. These relationships were consistent in strata of MSI status or neoantigen loads (Pinteraction > 0.2). CONCLUSIONS: The four lymphocytic reaction components are prognostic biomarkers in colorectal carcinoma.

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.

PD-1 Blockade Induces Reactivation of Nonproductive T-Cell Responses Characterized by NF-κB Signaling in Patients with Pancreatic Cancer.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) trials have evaluated CTLA-4 and/or PD-(L)1 blockade in patients with advanced disease in which bulky tumor burden and limited time to develop antitumor T cells may have contributed to poor clinical efficacy. Here, we evaluated peripheral blood and tumor T cells from patients with PDAC receiving neoadjuvant chemoradiation plus anti-PD-1 (pembrolizumab) versus chemoradiation alone. We analyzed whether PD-1 blockade successfully reactivated T cells in the blood and/or tumor to determine whether lack of clinical benefit could be explained by lack of reactivated T cells versus other factors. EXPERIMENTAL DESIGN: We used single-cell transcriptional profiling and TCR clonotype tracking to identify TCR clonotypes from blood that match clonotypes in the tumor. RESULTS: PD-1 blockade increases the flux of TCR clonotypes entering cell cycle and induces an IFNγ signature like that seen in patients with other GI malignancies who respond to PD-1 blockade. However, these reactivated T cells have a robust signature of NF-κB signaling not seen in cases of PD-1 antibody response. Among paired samples between blood and tumor, several of the newly cycling clonotypes matched activated T-cell clonotypes observed in the tumor. CONCLUSIONS: Cytotoxic T cells in the blood of patients with PDAC remain sensitive to reinvigoration by PD-1 blockade, and some have tumor-recognizing potential. Although these T cells proliferate and have a signature of IFN exposure, they also upregulate NF-κB signaling, which potentially counteracts the beneficial effects of anti-PD-1 reinvigoration and marks these T cells as non-productive contributors to antitumor immunity. See related commentary by Lander and DeNardo, p. 474.

Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer.

Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (αCD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict αCD40 treatment status and disease-free survival (DFS) following αCD40 therapy based upon TME features. Through downstream interpretation of the machine learning models' predictions, we found αCD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following αCD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of αCD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for αCD40-treated patients with PDAC.

Bayesian risk prediction model for colorectal cancer mortality through integration of clinicopathologic and genomic data.

Routine tumor-node-metastasis (TNM) staging of colorectal cancer is imperfect in predicting survival due to tumor pathobiological heterogeneity and imprecise assessment of tumor spread. We leveraged Bayesian additive regression trees (BART), a statistical learning technique, to comprehensively analyze patient-specific tumor characteristics for the improvement of prognostic prediction. Of 75 clinicopathologic, immune, microbial, and genomic variables in 815 stage II-III patients within two U.S.-wide prospective cohort studies, the BART risk model identified seven stable survival predictors. Risk stratifications (low risk, intermediate risk, and high risk) based on model-predicted survival were statistically significant (hazard ratios 0.19-0.45, vs. higher risk; P < 0.0001) and could be externally validated using The Cancer Genome Atlas (TCGA) data (P = 0.0004). BART demonstrated model flexibility, interpretability, and comparable or superior performance to other machine-learning models. Integrated bioinformatic analyses using BART with tumor-specific factors can robustly stratify colorectal cancer patients into prognostic groups and be readily applied to clinical oncology practice.

Multicenter randomized controlled trial of neoadjuvant chemoradiotherapy alone or in combination with pembrolizumab in patients with resectable or borderline resectable pancreatic adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a challenging target for immunotherapy because it has an immunosuppressive tumor microenvironment. Neoadjuvant chemoradiotherapy can increase tumor-infiltrating lymphocyte (TIL) density, which may predict overall survival (OS). We hypothesized that adding programmed cell death protein 1 (PD-1) blockade to chemoradiotherapy would be well tolerated and increase TILs among patients with localized PDAC. METHODS: Patients were randomized 2:1 to Arm A (receiving pembrolizumab plus chemoradiotherapy (capecitabine and external beam radiation)) or Arm B (receiving chemoradiotherapy alone) before anticipated pancreatectomy. Primary endpoints were (1) incidence and severity of adverse events during neoadjuvant therapy and (2) density of TILs in resected tumor specimens. TIL density was assessed using multiplexed immunofluorescence histologic examination. RESULTS: Thirty-seven patients were randomized to Arms A (n=24) and B (n=13). Grade ≥3 adverse events related to neoadjuvant treatment were experienced by 9 (38%) and 4 (31%) patients in Arms A and B, respectively, with one patient experiencing dose-limiting toxicity in Arm A. Seventeen (71%) and 7 (54%) patients in Arms A and B, respectively, underwent pancreatectomy. Median CD8+ T-cell densities in Arms A and B were 67.4 (IQR: 39.2-141.8) and 37.9 (IQR: 22.9-173.4) cells/mm2, respectively. Arms showed no noticeable differences in density of CD8+Ki67+, CD4+, or CD4+FOXP3+ regulatory T cells; M1-like and M2-like macrophages; or granulocytes. Median OS durations were 27.8 (95% CI: 17.1 to NR) and 24.3 (95% CI: 12.6 to NR) months for Arms A and B, respectively. CONCLUSIONS: Adding pembrolizumab to neoadjuvant chemoradiotherapy was safe. However, no convincing effect on CD8+ TILs was observed.

Spatially Resolved Single-Cell Assessment of Pancreatic Cancer Expression Subtypes Reveals Co-expressor Phenotypes and Extensive Intratumoral Heterogeneity.

Pancreatic ductal adenocarcinoma (PDAC) has been classified into classical and basal-like transcriptional subtypes by bulk RNA measurements. However, recent work has uncovered greater complexity to transcriptional subtypes than was initially appreciated using bulk RNA expression profiling. To provide a deeper understanding of PDAC subtypes, we developed a multiplex immunofluorescence (mIF) pipeline that quantifies protein expression of six PDAC subtype markers (CLDN18.2, TFF1, GATA6, KRT17, KRT5, and S100A2) and permits spatially resolved, single-cell interrogation of pancreatic tumors from resection specimens and core needle biopsies. Both primary and metastatic tumors displayed striking intratumoral subtype heterogeneity that was associated with patient outcomes, existed at the scale of individual glands, and was significantly reduced in patient-derived organoid cultures. Tumor cells co-expressing classical and basal markers were present in > 90% of tumors, existed on a basal-classical polarization continuum, and were enriched in tumors containing a greater admixture of basal and classical cell populations. Cell-cell neighbor analyses within tumor glands further suggested that co-expressor cells may represent an intermediate state between expression subtype poles. The extensive intratumoral heterogeneity identified through this clinically applicable mIF pipeline may inform prognosis and treatment selection for patients with PDAC. SIGNIFICANCE: A high-throughput pipeline using multiplex immunofluorescence in pancreatic cancer reveals striking expression subtype intratumoral heterogeneity with implications for therapy selection and identifies co-expressor cells that may serve as intermediates during subtype switching.

Smoking and Incidence of Colorectal Cancer Subclassified by Tumor-Associated Macrophage Infiltrates.

BACKGROUND: Biological evidence indicates that smoking can influence macrophage functions and polarization, thereby promoting tumor evolution. We hypothesized that the association of smoking with colorectal cancer incidence might differ by macrophage infiltrates. METHODS: Using the Nurses' Health Study and the Health Professionals Follow-up Study, we examined the association of smoking with incidence of colorectal cancer subclassified by macrophage counts. Multiplexed immunofluorescence (for CD68, CD86, IRF5, MAF, and MRC1 [CD206]) combined with digital image analysis and machine learning was used to identify overall, M1-polarized, and M2-polarized macrophages in tumor. We used inverse-probability-weighted multivariable Cox proportional hazards regression models to control for potential confounders and selection bias because of tissue data availability. All statistical tests were 2-sided. RESULTS: During follow-up of 131 144 participants (3 648 370 person-years), we documented 3092 incident colorectal cancer cases, including 871 cases with available macrophage data. The association of pack-years smoked with colorectal cancer incidence differed by stromal macrophage densities (Pheterogeneity = .003). Compared with never smoking, multivariable-adjusted hazard ratios (95% confidence interval) for tumors with low macrophage densities were 1.32 (0.97 to 1.79) for 1-19 pack-years, 1.31 (0.92 to 1.85) for 20-39 pack-years, and 1.74 (1.26 to 2.41) for 40 or more pack-years (Ptrend = .004). In contrast, pack-years smoked was not statistically significantly associated with the incidence of tumors having intermediate or high macrophage densities (Ptrend > .009, with an α level of .005). No statistically significant differential association was found for colorectal cancer subclassified by M1-like or M2-like macrophages. CONCLUSIONS: The association of smoking with colorectal cancer incidence is stronger for tumors with lower stromal macrophage counts. Our findings suggest an interplay of smoking and macrophages in colorectal carcinogenesis.

Spatial Organization and Prognostic Significance of NK and NKT-like Cells via Multimarker Analysis of the Colorectal Cancer Microenvironment.

Although tumor-infiltrating T cells hold a beneficial prognostic role in colorectal cancer, other lymphocytic populations are less characterized. We developed a multiplexed immunofluorescence assay coupled with digital image analysis and machine learning to identify natural killer (NK) cells (NCAM1+CD3-), natural killer T-like (NKT-like) cells (NCAM1+CD3+), and T cells (NCAM1-CD3+) within the PTPRC+ (CD45+) cell population and to measure their granzyme B (GZMB; cytotoxicity marker) and FCGR3A (CD16a; NK-cell maturity marker) expression. We evaluated immune cell densities and spatial configuration in 907 incident colorectal carcinoma cases within two prospective cohort studies. We found that T cells were approximately 100 times more abundant than NK and NKT-like cells. Overall, NK cells showed high GZMB expression and were located closer to tumor cells than T and NKT-like cells. In T and NKT-like cells, GZMB expression was enriched in cells in closer proximity to tumor cells. Higher densities of both T and NKT-like cells associated with longer cancer-specific survival, independent of potential confounders (P trend < 0.0007). Higher stromal GZMB+ and FCGR3A+ NK-cell densities associated with longer cancer-specific survival (P trend < 0.003). For T and NKT-like cells, greater proximity to tumor cells associated with longer cancer-specific survival (P trend < 0.0001). These findings indicate that cytotoxic NCAM1+CD3-GZMB+ NK cells and NCAM1+CD3+ NKT-like cells are relatively rare lymphocytic populations within the colorectal cancer microenvironment and show distinct spatial configuration and associations with patient outcome. The results highlight the utility of a quantitative multimarker assay for in situ, single-cell immune biomarker evaluation and underscore the importance of spatial context for tumor microenvironment characterization.

Neoadjuvant Chemotherapy Is Associated with Altered Immune Cell Infiltration and an Anti-Tumorigenic Microenvironment in Resected Pancreatic Cancer.

PURPOSE: Neoadjuvant chemotherapy is increasingly administered to patients with resectable or borderline resectable pancreatic ductal adenocarcinoma (PDAC), yet its impact on the tumor immune microenvironment is incompletely understood. DESIGN: We employed quantitative, spatially resolved multiplex immunofluorescence and digital image analysis to identify T-cell subpopulations, macrophage polarization states, and myeloid cell subpopulations in a multi-institution cohort of up-front resected primary tumors (n = 299) and in a comparative set of resected tumors after FOLFIRINOX-based neoadjuvant therapy (n = 36) or up-front surgery (n = 30). Multivariable-adjusted Cox proportional hazards models were used to evaluate associations between the immune microenvironment and patient outcomes. RESULTS: In the multi-institutional resection cohort, immune cells exhibited substantial heterogeneity across patient tumors and were located predominantly in stromal regions. Unsupervised clustering using immune cell densities identified four main patterns of immune cell infiltration. One pattern, seen in 20% of tumors and characterized by abundant T cells (T cell-rich) and a paucity of immunosuppressive granulocytes and macrophages, was associated with improved patient survival. Neoadjuvant chemotherapy was associated with a higher CD8:CD4 ratio, greater M1:M2-polarized macrophage ratio, and reduced CD15+ARG1+ immunosuppressive granulocyte density. Within neoadjuvant-treated tumors, 72% showed a T cell-rich pattern with low immunosuppressive granulocytes and macrophages. M1-polarized macrophages were located closer to tumor cells after neoadjuvant chemotherapy, and colocalization of M1-polarized macrophages and tumor cells was associated with greater tumor pathologic response and improved patient survival. CONCLUSIONS: Neoadjuvant chemotherapy with FOLFIRINOX shifts the PDAC immune microenvironment toward an anti-tumorigenic state associated with improved patient survival.

Neoadjuvant Selicrelumab, an Agonist CD40 Antibody, Induces Changes in the Tumor Microenvironment in Patients with Resectable Pancreatic Cancer.

PURPOSE: CD40 activation is a novel clinical opportunity for cancer immunotherapy. Despite numerous active clinical trials with agonistic CD40 monoclonal antibodies (mAb), biological effects and treatment-related modulation of the tumor microenvironment (TME) remain poorly understood. PATIENTS AND METHODS: Here, we performed a neoadjuvant clinical trial of agonistic CD40 mAb (selicrelumab) administered intravenously with or without chemotherapy to 16 patients with resectable pancreatic ductal adenocarcinoma (PDAC) before surgery followed by adjuvant chemotherapy and CD40 mAb. RESULTS: The toxicity profile was acceptable, and overall survival was 23.4 months (95% confidence interval, 18.0-28.8 months). Based on a novel multiplexed immunohistochemistry platform, we report evidence that neoadjuvant selicrelumab leads to major differences in the TME compared with resection specimens from treatment-naïve PDAC patients or patients given neoadjuvant chemotherapy/chemoradiotherapy only. For selicrelumab-treated tumors, 82% were T-cell enriched, compared with 37% of untreated tumors (P = 0.004) and 23% of chemotherapy/chemoradiation-treated tumors (P = 0.012). T cells in both the TME and circulation were more active and proliferative after selicrelumab. Tumor fibrosis was reduced, M2-like tumor-associated macrophages were fewer, and intratumoral dendritic cells were more mature. Inflammatory cytokines/sec CXCL10 and CCL22 increased systemically after selicrelumab. CONCLUSIONS: This unparalleled examination of CD40 mAb therapeutic mechanisms in patients provides insights for design of subsequent clinical trials targeting CD40 in cancer.

Leukocyte Heterogeneity in Pancreatic Ductal Adenocarcinoma: Phenotypic and Spatial Features Associated with Clinical Outcome.

Immunotherapies targeting aspects of T cell functionality are efficacious in many solid tumors, but pancreatic ductal adenocarcinoma (PDAC) remains refractory to these treatments. Deeper understanding of the PDAC immune ecosystem is needed to identify additional therapeutic targets and predictive biomarkers for therapeutic response and resistance monitoring. To address these needs, we quantitatively evaluated leukocyte contexture in 135 human PDACs at single-cell resolution by profiling density and spatial distribution of myeloid and lymphoid cells within histopathologically defined regions of surgical resections from treatment-naive and presurgically (neoadjuvant)-treated patients and biopsy specimens from metastatic PDAC. Resultant data establish an immune atlas of PDAC heterogeneity, identify leukocyte features correlating with clinical outcomes, and, through an in silico study, provide guidance for use of PDAC tissue microarrays to optimally measure intratumoral immune heterogeneity. Atlas data have direct applicability as a reference for evaluating immune responses to investigational neoadjuvant PDAC therapeutics where pretherapy baseline specimens are not available. SIGNIFICANCE: We provide a phenotypic and spatial immune atlas of human PDAC identifying leukocyte composition at steady state and following standard neoadjuvant therapies. These data have broad utility as a resource that can inform on leukocyte responses to emerging therapies where baseline tissues were not acquired.This article is highlighted in the In This Issue feature, p. 1861.

Prognostic significance of myeloid immune cells and their spatial distribution in the colorectal cancer microenvironment.

BACKGROUND: Myeloid cells represent an abundant yet heterogeneous cell population in the colorectal cancer microenvironment, and their roles remain poorly understood. METHODS: We used multiplexed immunofluorescence combined with digital image analysis to identify CD14+ monocytic and CD15+ granulocytic cells and to evaluate their maturity (HLA-DR and CD33), immunosuppressive potential (ARG1) and proximity to cytokeratin (KRT)-positive tumor cells in 913 colorectal carcinomas. Using covariate data of 4465 incident colorectal cancers in two prospective cohort studies, the inverse probability weighting method was used with multivariable-adjusted Cox proportional hazards models to assess cancer-specific mortality according to ordinal quartiles (Q1-Q4) of myeloid cell densities. Immune cell-tumor cell proximity was measured with the nearest neighbor method and the G-cross function, which determines the likelihood of any tumor cell having at least one immune cell of the specified type within a certain radius. RESULTS: Higher intraepithelial (Ptrend=0.0002; HR for Q4 (vs Q1), 0.48, 95% CI 0.31 to 0.76) and stromal (Ptrend <0.0001; HR for Q4 (vs Q1), 0.42, 95% CI 0.29 to 0.63) densities of CD14+HLA-DR+ cells were associated with lower colorectal cancer-specific mortality while, conversely, higher intraepithelial densities of CD14+HLA-DR- cells were associated with higher colorectal cancer-specific mortality (Ptrend=0.0003; HR for Q4 (vs Q1), 1.78, 95% CI 1.25 to 2.55). Spatial analyses indicated that CD15+ cells were located closer to tumor cells than CD14+ cells, and CD14+HLA-DR+ cells were closer to tumor than CD14+HLA-DR- cells (p<0.0001). The G-cross proximity measurement, evaluating the difference in the likelihood of any tumor cell being colocated with at least one CD14+HLA-DR+ cell versus CD14+HLA-DR- cell within a 20 µm radius, was associated with lower colorectal cancer-specific mortality (Ptrend <0.0001; HR for Q4 (vs Q1), 0.37, 95% CI 0.24 to 0.57). CONCLUSIONS: Myeloid cell populations occur in spatially distinct distributions and exhibit divergent, subset-specific prognostic significance in colorectal cancer, with mature CD14+HLA-DR+ and immature CD14+HLA-DR- monocytic phenotypes most notably showing opposite associations. These results highlight the prognostic utility of multimarker evaluation of myeloid cell infiltrates and reveal a previously unrecognized degree of spatial organization for myeloid cells in the immune microenvironment.

Composition, Spatial Characteristics, and Prognostic Significance of Myeloid Cell Infiltration in Pancreatic Cancer.

PURPOSE: Although abundant myeloid cell populations in the pancreatic ductal adenocarcinoma (PDAC) microenvironment have been postulated to suppress antitumor immunity, the composition of these populations, their spatial locations, and how they relate to patient outcomes are poorly understood. EXPERIMENTAL DESIGN: To generate spatially resolved tumor and immune cell data at single-cell resolution, we developed two quantitative multiplex immunofluorescence assays to interrogate myeloid cells (CD15, CD14, ARG1, CD33, HLA-DR) and macrophages [CD68, CD163, CD86, IFN regulatory factor 5, MRC1 (CD206)] in the PDAC tumor microenvironment. Spatial point pattern analyses were conducted to assess the degree of colocalization between tumor cells and immune cells. Multivariable-adjusted Cox proportional hazards regression was used to assess associations with patient outcomes. RESULTS: In a multi-institutional cohort of 305 primary PDAC resection specimens, myeloid cells were abundant, enriched within stromal regions, highly heterogeneous across tumors, and differed by somatic genotype. High densities of CD15+ARG1+ immunosuppressive granulocytic cells and M2-polarized macrophages were associated with worse patient survival. Moreover, beyond cell density, closer proximity of M2-polarized macrophages to tumor cells was strongly associated with disease-free survival, revealing the clinical significance and biologic importance of immune cell localization within tumor areas. CONCLUSIONS: A diverse set of myeloid cells are present within the PDAC tumor microenvironment and are distributed heterogeneously across patient tumors. Not only the densities but also the spatial locations of myeloid immune cells are associated with patient outcomes, highlighting the potential role of spatially resolved myeloid cell subtypes as quantitative biomarkers for PDAC prognosis and therapy.

The Prognostic Role of Macrophage Polarization in the Colorectal Cancer Microenvironment.

Macrophages are among the most common cells in the colorectal cancer microenvironment, but their prognostic significance is incompletely understood. Using multiplexed immunofluorescence for CD68, CD86, IRF5, MAF, MRC1 (CD206), and KRT (cytokeratins) combined with digital image analysis and machine learning, we assessed the polarization spectrum of tumor-associated macrophages in 931 colorectal carcinomas. We then applied Cox proportional hazards regression to assess prognostic survival associations of intraepithelial and stromal densities of M1-like and M2-like macrophages while controlling for potential confounders, including stage and microsatellite instability status. We found that high tumor stromal density of M2-like macrophages was associated with worse cancer-specific survival, whereas tumor stromal density of M1-like macrophages was not significantly associated with better cancer-specific survival. High M1:M2 density ratio in tumor stroma was associated with better cancer-specific survival. Overall macrophage densities in tumor intraepithelial or stromal regions were not prognostic. These findings suggested that macrophage polarization state, rather than their overall density, was associated with cancer-specific survival, with M1- and M2-like macrophage phenotypes exhibiting distinct prognostic roles. These results highlight the utility of a multimarker strategy to assess the macrophage polarization at single-cell resolution within the tumor microenvironment.

Association of Fusobacterium nucleatum with Specific T-cell Subsets in the Colorectal Carcinoma Microenvironment.

PURPOSE: While evidence indicates that Fusobacterium nucleatum (F. nucleatum) may promote colorectal carcinogenesis through its suppressive effect on T-cell-mediated antitumor immunity, the specific T-cell subsets involved remain uncertain. EXPERIMENTAL DESIGN: We measured F. nucleatum DNA within tumor tissue by quantitative PCR on 933 cases (including 128 F. nucleatum-positive cases) among 4,465 incident colorectal carcinoma cases in two prospective cohorts. Multiplex immunofluorescence combined with digital image analysis and machine learning algorithms for CD3, CD4, CD8, CD45RO (PTPRC isoform), and FOXP3 measured various T-cell subsets. We leveraged data on Bifidobacterium, microsatellite instability (MSI), tumor whole-exome sequencing, and M1/M2-type tumor-associated macrophages [TAM; by CD68, CD86, IRF5, MAF, and MRC1 (CD206) multimarker assay]. Using the 4,465 cancer cases and inverse probability weighting method to control for selection bias due to tissue availability, multivariable-adjusted logistic regression analysis assessed the association between F. nucleatum and T-cell subsets. RESULTS: The amount of F. nucleatum was inversely associated with tumor stromal CD3+ lymphocytes [multivariable OR, 0.47; 95% confidence interval (CI), 0.28-0.79, for F. nucleatum-high vs. -negative category; P trend = 0.0004] and specifically stromal CD3+CD4+CD45RO+ cells (corresponding multivariable OR, 0.52; 95% CI, 0.32-0.85; P trend = 0.003). These relationships did not substantially differ by MSI status, neoantigen load, or exome-wide tumor mutational burden. F. nucleatum was not significantly associated with tumor intraepithelial T cells or with M1 or M2 TAMs. CONCLUSIONS: The amount of tissue F. nucleatum is associated with lower density of stromal memory helper T cells. Our findings provide evidence for the interactive pathogenic roles of microbiota and specific immune cells.

Prognostic Significance of Immune Cell Populations Identified by Machine Learning in Colorectal Cancer Using Routine Hematoxylin and Eosin-Stained Sections.

PURPOSE: Although high T-cell density is a well-established favorable prognostic factor in colorectal cancer, the prognostic significance of tumor-associated plasma cells, neutrophils, and eosinophils is less well-defined. EXPERIMENTAL DESIGN: We computationally processed digital images of hematoxylin and eosin (H&E)-stained sections to identify lymphocytes, plasma cells, neutrophils, and eosinophils in tumor intraepithelial and stromal areas of 934 colorectal cancers in two prospective cohort studies. Multivariable Cox proportional hazards regression was used to compute mortality HR according to cell density quartiles. The spatial patterns of immune cell infiltration were studied using the GTumor:Immune cell function, which estimates the likelihood of any tumor cell in a sample having at least one neighboring immune cell of the specified type within a certain radius. Validation studies were performed on an independent cohort of 570 colorectal cancers. RESULTS: Immune cell densities measured by the automated classifier demonstrated high correlation with densities both from manual counts and those obtained from an independently trained automated classifier (Spearman's ρ 0.71-0.96). High densities of stromal lymphocytes and eosinophils were associated with better cancer-specific survival [P trend < 0.001; multivariable HR (4th vs 1st quartile of eosinophils), 0.49; 95% confidence interval, 0.34-0.71]. High GTumor:Lymphocyte area under the curve (AUC0,20µm; P trend = 0.002) and high GTumor:Eosinophil AUC0,20µm (P trend < 0.001) also showed associations with better cancer-specific survival. High stromal eosinophil density was also associated with better cancer-specific survival in the validation cohort (P trend < 0.001). CONCLUSIONS: These findings highlight the potential for machine learning assessment of H&E-stained sections to provide robust, quantitative tumor-immune biomarkers for precision medicine.

Insulin-Like Growth Factor-1 Receptor Expression and Disease Recurrence and Survival in Patients with Resected Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Insulin-like growth factor-1 receptor (IGF1R) signaling is important in pancreatic ductal adenocarcinoma (PDAC) biology, but little is known regarding IGF1R expression and patient characteristics and outcomes. METHODS: In 365 patients with resected PDAC, we evaluated IGF1R protein expression using IHC on whole-slide sections and IGF1R genomic status using next-generation sequencing. Associations of IGF1R expression, measured by H-scores incorporating staining intensity and proportion of positive tumor cells, with disease-free survival (DFS) and overall survival (OS) were evaluated in 317 and 321 patients, respectively, using Cox regression adjusting for known prognostic factors. RESULTS: Higher IGF1R expression in tumor cells was associated with worse DFS comparing highest versus lowest expression tertiles [median DFS, 10.8 vs. 16.1 months; adjusted hazard ratio (HR), 1.73; 95% confidence interval (CI), 1.24-2.44; P trend = 0.002] and worse OS (median OS, 17.4 vs. 25.8 months; HR, 1.39; 95% CI, 1.00-1.92; P trend = 0.046). The association between high IGF1R expression and reduced DFS was identified primarily among patients with a preoperative body mass index ≥25 kg/m2 (HR, 4.27; 95% CI, 2.03-8.96, comparing extreme tertiles; P interaction = 0.032). KRAS-mutant tumors had greater IGF1R expression, and IGF1R expression in tumor epithelium was inversely correlated with that in stromal cells. Mutations in IGF1R were infrequent, and no overt loss-of-function alterations were identified. Higher IGF1R expression was modestly associated with higher gene copy number (Pearson correlation coefficient = 0.26, P < 0.001). CONCLUSIONS: Higher IGF1R protein expression was associated with worse patient outcomes in resected PDAC. IMPACT: IGF1R expression in PDAC represents a potential biomarker to guide patient selection for more aggressive, multidrug regimens in the adjuvant setting.