Altered liver metabolism post-wean abolishes efficacy of vitamin D for breast cancer prevention in a mouse model.

Young women have increased risk of vitamin D deficiency, which may increase breast cancer incidence. Here, we assessed the anti-cancer efficacy of vitamin D in mouse models of young-onset breast cancer. In never-pregnant mice, vitamin D supplementation increased serum 25(OH)D and hepatic 1,25(OH)2D3, reduced tumor size, and associated with anti-tumor immunity. These anti-tumor effects were not replicated in a mouse model of postpartum breast cancer, where hepatic metabolism of vitamin D was suppressed post-wean, which resulted in deficient serum 25(OH)D and reduced hepatic 1,25(OH)2D3. Treatment with active 1,25(OH)2D3 induced hypercalcemia exclusively in post-wean mice, highlighting metabolic imbalance post-wean. RNAseq revealed suppressed CYP450 expression postpartum. In sum, we provide evidence that vitamin D anti-tumor activity is mediated through immunomodulatory mechanisms and is ineffective in the post-wean window due to altered hepatic metabolism. These findings have implications for suppressed xenobiotic metabolism in postpartum women beyond vitamin D.

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.

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.

MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Alignment, segmentation and neighborhood analysis in cyclic immunohistochemistry data using CASSATT.

Cyclic immunohistochemistry (cycIHC) uses sequential rounds of colorimetric immunostaining and imaging for quantitative mapping of location and number of cells of interest. Additionally, cycIHC benefits from the speed and simplicity of brightfield microscopy, making the collection of entire tissue sections and slides possible at a trivial cost compared to other high dimensional imaging modalities. However, large cycIHC datasets currently require an expert data scientist to concatenate separate open-source tools for each step of image pre-processing, registration, and segmentation, or the use of proprietary software. Here, we present a unified and user-friendly pipeline for processing, aligning, and analyzing cycIHC data - Cyclic Analysis of Single-Cell Subsets and Tissue Territories (CASSATT). CASSATT registers scanned slide images across all rounds of staining, segments individual nuclei, and measures marker expression on each detected cell. Beyond straightforward single cell data analysis outputs, CASSATT explores the spatial relationships between cell populations. By calculating the log odds of interaction frequencies between cell populations within tissues and tissue regions, this pipeline helps users identify populations of cells that interact-or do not interact-at frequencies that are greater than those occurring by chance. It also identifies specific neighborhoods of cells based on the assortment of neighboring cell types that surround each cell in the sample. The presence and location of these neighborhoods can be compared across slides or within distinct regions within a tissue. CASSATT is a fully open source workflow tool developed to process cycIHC data and will allow greater utilization of this powerful staining technique.

Modulation of myeloid and T cells in vivo by Bruton's tyrosine kinase inhibitor ibrutinib in patients with metastatic pancreatic ductal adenocarcinoma.

BACKGROUND: In preclinical studies of pancreatic ductal adenocarcinoma (PDAC), ibrutinib improved the antitumor efficacy of the standard of care chemotherapy. This led to a phase 1b clinical trial to determine the safety, tolerability, and immunologic effects of ibrutinib treatment in patients with advanced PDAC. METHODS: Previously untreated patients with PDAC were enrolled in a phase 1b clinical trial (ClinicalTrials.gov) to determine the safety, toxicity, and maximal tolerated dose of ibrutinib when administered with the standard regimen of gemcitabine and nab-paclitaxel. To study the immune response to ibrutinib alone, the trial included an immune response arm where patients were administered with ibrutinib daily for a week followed by ibrutinib combined with gemcitabine and nab-paclitaxel. Endoscopic ultrasonography-guided primary PDAC tumor biopsies and blood were collected before and after ibrutinib monotherapy. Changes in abundance and functional state of immune cells in the blood was evaluated by mass cytometry by time of flight and statistical scaffold analysis, while that in the local tumor microenvironment (TME) were assessed by multiplex immunohistochemistry. Changes in B-cell receptor and T-cell receptor repertoire were assessed by sequencing and analysis of clonality. RESULTS: In the blood, ibrutinib monotherapy significantly increased the frequencies of activated inducible T cell costimulator+(ICOS+) CD4+ T cells and monocytes. Within the TME, ibrutinib monotherapy led to a trend in decreased B-cell abundance but increased interleukin-10+ B-cell frequency. Monotherapy also led to a trend in increased mature CD208+dendritic cell density, increased late effector (programmed cell death protein 1 (PD-1-) eomesodermin (EOMES+)) CD8+ T-cell frequency, with a concomitantly decreased dysfunctional (PD-1+ EOMES+) CD8+ T-cell frequency. When ibrutinib was combined with chemotherapy, most of these immune changes were not observed. Patients with partial clinical responses had more diverse T and B cell receptor repertoires prior to therapy initiation. CONCLUSION: Ibrutinib monotherapy skewed the immune landscape both in the circulation and TME towards activated T cells, monocytes and DCs. These effects were not observed when combining ibrutinib with standard of care chemotherapy. Future studies may focus on other therapeutic combinations that augment the immunomodulatory effects of ibrutinib in solid tumors. TRIAL REGISTRATION NUMBER: NCT02562898.

Axatilimab for Chronic Graft-Versus-Host Disease After Failure of at Least Two Prior Systemic Therapies: Results of a Phase I/II Study.

PURPOSE: Chronic graft-versus-host disease (cGVHD) remains the major cause of late morbidity after allogeneic hematopoietic cell transplantation. Colony-stimulating factor 1 receptor (CSF-1R)-dependent macrophages promote cGVHD fibrosis, and their elimination in preclinical studies ameliorated cGVHD. Axatilimab is a humanized monoclonal antibody that inhibits CSF-1R signaling and restrains macrophage development. PATIENTS AND METHODS: This phase I (phI)/phase II (phII) open-label study (ClinicalTrials.gov identifier: NCT03604692) evaluated safety, tolerability, and efficacy of axatilimab in patients age ≥ 6 years with active cGVHD after ≥ 2 prior systemic therapy lines. Primary objectives in phI were to identify the optimal biologic and recommended phII dose and in phII to evaluate the overall (complete and partial) response rate (ORR) at the start of treatment cycle 7. RESULTS: Forty enrolled patients (17 phI; 23 phII) received at least one axatilimab dose. In phI, a dose of 3 mg/kg given once every 4 weeks met the optimal biologic dose definition. Two dose-limiting toxicities occurred at the 3 mg/kg dose given once every 2 weeks. At least one treatment-related adverse event (TRAE) was observed in 30 patients with grade ≥ 3 TRAEs in eight patients, the majority known on-target effects of CSF-1R inhibition. No cytomegalovirus reactivations occurred. With the 50% ORR at cycle 7 day 1, the phII cohort met the primary efficacy end point. Furthermore, the ORR in the first six cycles, an end point supporting regulatory approvals, was 82%. Responses were seen in all affected organs regardless of prior therapy. Fifty-eight percent of patients reported significant improvement in cGVHD-related symptoms using the Lee Symptom Scale. On-target activity of axatilimab was suggested by the decrease in skin CSF-1R-expressing macrophages. CONCLUSION: Targeting profibrotic macrophages with axatilimab is a therapeutically promising novel strategy with a favorable safety profile for refractory cGVHD.

Therapeutics That Promote Sympathetic Reinnervation Modulate the Inflammatory Response After Myocardial Infarction.

Myocardial infarction (MI) triggers an inflammatory response that transitions from pro-inflammatory to reparative over time. Restoring sympathetic nerves in the heart after MI prevents arrhythmias. This study investigated if reinnervation altered the immune response after MI. This study used quantitative multiplex immunohistochemistry to identify the immune cells present in the heart 2 weeks after ischemia-reperfusion. Two therapeutics stimulated reinnervation, preventing arrhythmias and shifting the immune response from inflammatory to reparative, with fewer pro-inflammatory macrophages and more regulatory T cells and reparative macrophages. Treatments did not alter macrophage phenotype in vitro, which suggested reinnervation contributed to the altered immune response.

Quantitative Spatial Profiling of Immune Populations in Pancreatic Ductal Adenocarcinoma Reveals Tumor Microenvironment Heterogeneity and Prognostic Biomarkers.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with poor 5-year survival rates, necessitating identification of novel therapeutic targets. Elucidating the biology of the tumor immune microenvironment (TiME) can provide vital insights into mechanisms of tumor progression. In this study, we developed a quantitative image processing platform to analyze sequential multiplexed IHC data from archival PDAC tissue resection specimens. A 27-plex marker panel was employed to simultaneously phenotype cell populations and their functional states, followed by a computational workflow to interrogate the immune contextures of the TiME in search of potential biomarkers. The PDAC TiME reflected a low-immunogenic ecosystem with both high intratumoral and intertumoral heterogeneity. Spatial analysis revealed that the relative distance between IL10+ myelomonocytes, PD-1+ CD4+ T cells, and granzyme B+ CD8+ T cells correlated significantly with survival, from which a spatial proximity signature termed imRS was derived that correlated with PDAC patient survival. Furthermore, spatial enrichment of CD8+ T cells in lymphoid aggregates was also linked to improved survival. Altogether, these findings indicate that the PDAC TiME, generally considered immuno-dormant or immunosuppressive, is a spatially nuanced ecosystem orchestrated by ordered immune hierarchies. This new understanding of spatial complexity may guide novel treatment strategies for PDAC. SIGNIFICANCE: Quantitative image analysis of PDAC specimens reveals intertumoral and intratumoral heterogeneity of immune populations and identifies spatial immune architectures that are significantly associated with disease prognosis.

A Cancer Cell-Intrinsic GOT2-PPARδ Axis Suppresses Antitumor Immunity.

Despite significant recent advances in precision medicine, pancreatic ductal adenocarcinoma (PDAC) remains near uniformly lethal. Although immune-modulatory therapies hold promise to meaningfully improve outcomes for patients with PDAC, the development of such therapies requires an improved understanding of the immune evasion mechanisms that characterize the PDAC microenvironment. Here, we show that cancer cell-intrinsic glutamic-oxaloacetic transaminase 2 (GOT2) shapes the immune microenvironment to suppress antitumor immunity. Mechanistically, we find that GOT2 functions beyond its established role in the malate-aspartate shuttle and promotes the transcriptional activity of nuclear receptor peroxisome proliferator-activated receptor delta (PPARδ), facilitated by direct fatty acid binding. Although GOT2 is dispensable for cancer cell proliferation in vivo, the GOT2-PPARδ axis promotes spatial restriction of both CD4+ and CD8+ T cells from the tumor microenvironment. Our results demonstrate a noncanonical function for an established mitochondrial enzyme in transcriptional regulation of immune evasion, which may be exploitable to promote a productive antitumor immune response. SIGNIFICANCE: Prior studies demonstrate the important moonlighting functions of metabolic enzymes in cancer. We find that the mitochondrial transaminase GOT2 binds directly to fatty acid ligands that regulate the nuclear receptor PPARδ, and this functional interaction critically regulates the immune microenvironment of pancreatic cancer to promote tumor progression. See related commentary by Nwosu and di Magliano, p. 2237.. This article is highlighted in the In This Issue feature, p. 2221.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

Characterization of the tumor immune microenvironment of sinonasal squamous-cell carcinoma.

BACKGROUND: Treatment and prognosis of sinonasal squamous-cell carcinoma (SNSCC) have not significantly improved despite improvements in radical therapy. Characterization of the tumor immune microenvironment (TiME) may identify patient subgroups associated with disease recurrence, and provide new biomarkers for improved patient stratification and treatment. METHODS: The TiME was quantitatively evaluated by multiplex immunohistochemistry (mIHC) in archived tissue sections from 38 patients with SNSCC, and were assessed for differences between recurrent (n = 20) and nonrecurrent (n = 18) groups. Hierarchical clustering analyses were performed to identify phenotypic TiME subgroups within the cohort and were used to compare survival outcomes. RESULTS: Our mIHC analysis revealed increased T-cell populations and decreased myeloid-cell populations in SNSCC patients without recurrent disease, as compared with patients with recurrent disease. Within T-cell subsets, there was a significantly higher percentage of granzyme B+ , T-bet+ , Eomes+ T cells, as well as higher proliferation of CD8+ T cells within the nonrecurrent group relative to the recurrent group. Furthermore, immune-cell complexity profiles of SNSCC revealed hyper- and hypo-T-cell-inflamed, myeloid-inflamed, B-cell-inflamed, and broadly hypoinflamed subtypes not previously identified by gene expression analyses. Our study revealed that presence of either hyper- or hypo-T-cell-inflamed TiME subtypes were associated with increased survival outcomes as compared with broadly hypoinflamed TiME subtypes (p = 0.035 and 0.0376, respectively). CONCLUSIONS: The TiME of SNSCC reveals distinct subtypes, which may correlate with recurrence and survival outcomes.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging.

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

Safety and Efficacy of Pembrolizumab in Combination with Acalabrutinib in Advanced Head and Neck Squamous Cell Carcinoma: Phase 2 Proof-of-Concept Study.

PURPOSE: Programmed cell death-1 (PD-1) receptor inhibitors have shown efficacy in head and neck squamous cell carcinoma (HNSCC), but treatment failure or secondary resistance occurs in most patients. In preclinical murine carcinoma models, inhibition of Bruton's tyrosine kinase (BTK) induces myeloid cell reprogramming that subsequently bolsters CD8+ T cell responses, resulting in enhanced antitumor activity. This phase 2, multicenter, open-label, randomized study evaluated pembrolizumab (anti-PD-1 monoclonal antibody) plus acalabrutinib (BTK inhibitor) in recurrent or metastatic HNSCC. PATIENTS AND METHODS: Patients received pembrolizumab 200 mg intravenously every 3 weeks, alone or in combination with acalabrutinib 100 mg orally twice daily. Safety and overall response rate (ORR) were co-primary objectives. The secondary objectives were progression-free survival (PFS) and overall survival. RESULTS: Seventy-six patients were evaluated (pembrolizumab, n = 39; pembrolizumab + acalabrutinib, n = 37). Higher frequencies of grade 3-4 treatment-emergent adverse events (AE; 65% vs. 39%) and serious AEs (68% vs. 31%) were observed with combination therapy versus monotherapy. ORR was 18% with monotherapy versus 14% with combination therapy. Median PFS was 2.7 [95% confidence interval (CI), 1.4-6.8] months in the combination arm and 1.7 (95% CI, 1.4-4.0) months in the monotherapy arm. The study was terminated due to lack of clinical benefit with combination treatment. To assess how tumor immune contexture was affected by therapy in patients with pre- and post-treatment biopsies, spatial proteomic analyses were conducted that revealed a trend toward increased CD45+ leukocyte infiltration of tumors from baseline at day 43 with pembrolizumab (monotherapy, n = 5; combination, n = 2), which appeared to be higher in combination-treated patients; however, definitive conclusions could not be drawn due to limited sample size. CONCLUSIONS: Despite lack of clinical efficacy, immune subset analyses suggest that there are additive effects of this combination; however, the associated toxicity limits the feasibility of combination treatment with pembrolizumab and acalabrutinib in patients with recurrent or metastatic HNSCC.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies.

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

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.

Beyond Programmed Death-Ligand 1: B7-H6 Emerges as a Potential Immunotherapy Target in SCLC.

INTRODUCTION: The programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors, atezolizumab and durvalumab, have received regulatory approval for the first-line treatment of patients with extensive-stage SCLC. Nevertheless, when used in combination with platinum-based chemotherapy, these PD-L1 inhibitors only improve overall survival by 2 to 3 months. This may be due to the observation that less than 20% of SCLC tumors express PD-L1 at greater than 1%. Evaluating the composition and abundance of checkpoint molecules in SCLC may identify molecules beyond PD-L1 that are amenable to therapeutic targeting. METHODS: We analyzed RNA-sequencing data from SCLC cell lines (n = 108) and primary tumor specimens (n = 81) for expression of 39 functionally validated inhibitory checkpoint ligands. Furthermore, we generated tissue microarrays containing SCLC cell lines and patient with SCLC specimens to confirm expression of these molecules by immunohistochemistry. We annotated patient outcomes data, including treatment response and overall survival. RESULTS: The checkpoint protein B7-H6 (NCR3LG1) exhibited increased protein expression relative to PD-L1 in cell lines and tumors (p < 0.05). Higher B7-H6 protein expression correlated with longer progression-free survival (p = 0.0368) and increased total immune infiltrates (CD45+) in patients. Furthermore, increased B7-H6 gene expression in SCLC tumors correlated with a decreased activated natural killer cell gene signature, suggesting a complex interplay between B7-H6 expression and immune signature in SCLC. CONCLUSIONS: We investigated 39 inhibitory checkpoint molecules in SCLC and found that B7-H6 is highly expressed and associated with progression-free survival. In addition, 26 of 39 immune checkpoint proteins in SCLC tumors were more abundantly expressed than PD-L1, indicating an urgent need to investigate additional checkpoint targets for therapy in addition to PD-L1.

High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer.

BACKGROUND: Characterization of breast cancer (BC) through the determination of conventional markers such as ER, PR, HER2, and Ki67 has been useful as a predictive and therapeutic tool. Also, assessment of tumor-infiltrating lymphocytes has been proposed as an important prognostic aspect to be considered in certain BC subtypes. However, there is still a need to identify additional biomarkers that could add precision in distinguishing therapeutic response of individual patients. To this end, we focused in the expression of interferon regulatory factor 8 (IRF8) in BC cells. IRF8 is a transcription factor which plays a well-determined role in myeloid cells and that seems to have multiple antitumoral roles: it has tumor suppressor functions; it acts downstream IFN/STAT1, required for the success of some therapeutic regimes, and its expression in neoplastic cells seems to depend on a cross talk between the immune contexture and the tumor cells. The goal of the present study was to examine the relationship between IRF8 with the therapeutic response and the immune contexture in BC, since its clinical significance in this type of cancer has not been thoroughly addressed. METHODS: We identified the relationship between IRF8 expression and the clinical outcome of BC patients and validated IRF8 as predictive biomarker by using public databases and then performed in silico analysis. To correlate the expression of IRF8 with the immune infiltrate in BC samples, we performed quantitative multiplex immunohistochemistry. RESULTS: IRF8 expression can precisely predict the complete pathological response to monoclonal antibody therapy or to select combinations of chemotherapy such as FAC (fluorouracil, adriamycin, and cytoxan) in ER-negative BC subtypes. Analysis of immune cell infiltration indicates there is a strong correlation between activated and effector CD8+ T cell infiltration and tumoral IRF8 expression. CONCLUSIONS: We propose IRF8 expression as a potent biomarker not only for prognosis, but also for predicting therapy response in ER-negative BC phenotypes. Its expression in neoplastic cells also correlates with CD8+ T cell activation and infiltration. Therefore, our results justify new efforts towards understanding mechanisms regulating IRF8 expression and how they can be therapeutically manipulated.