Augmentation of tumor expression of HLA-DR, CXCL9, and CXCL10 may improve olfactory neuroblastoma immunotherapeutic responses.

BACKGROUND: Olfactory neuroblastoma is a rare malignancy of the anterior skull base typically treated with surgery and adjuvant radiation. Although outcomes are fair for low-grade disease, patients with high-grade, recurrent, or metastatic disease oftentimes respond poorly to standard treatment methods. We hypothesized that an in-depth evaluation of the olfactory neuroblastoma tumor immune microenvironment would identify mechanisms of immune evasion in high-grade olfactory neuroblastoma as well as rational targetable mechanisms for future translational immunotherapeutic approaches. METHODS: Multispectral immunofluorescence and RNAScope evaluation of the tumor immune microenvironment was performed on forty-seven clinically annotated olfactory neuroblastoma samples. A retrospective chart review was performed and clinical correlations assessed. RESULTS: A significant T cell infiltration was noted in olfactory neuroblastoma samples with a stromal predilection, presence of myeloid-derived suppressor cells, and sparse natural killer cells. A striking decrease was observed in MHC-I expression in high-grade olfactory neuroblastoma compared to low-grade disease, representing a mechanism of immune evasion in high-grade disease. Mechanistically, the immune effector stromal predilection appears driven by low tumor cell MHC class II (HLA-DR), CXCL9, and CXCL10 expression as those tumors with increased tumor cell expression of each of these mediators correlated with significant increases in T cell infiltration. CONCLUSION: These data suggest that immunotherapeutic strategies that augment tumor cell expression of MHC class II, CXCL9, and CXCL10 may improve parenchymal trafficking of immune effector cells in olfactory neuroblastoma and augment immunotherapeutic responses.

Chordoma cancer stem cell subpopulation characterization may guide targeted immunotherapy approaches to reduce disease recurrence.

Introduction: Cancer stem cells (CSCs), a group of tumor-initiating and tumor-maintaining cells, may be major players in the treatment resistance and recurrence distinctive of chordoma. Characterizing CSCs is crucial to better targeting this subpopulation. Methods: Using flow cytometry, six chordoma cell lines were evaluated for CSC composition. In vitro, cell lines were stained for B7H6, HER2, MICA-B, ULBP1, EGFR, and PD-L1 surface markers. Eighteen resected chordomas were stained using a multispectral immunofluorescence (mIF) antibody panel to identify CSCs in vivo. HALO software was used for quantitative CSC density and spatial analysis. Results: In vitro, chordoma CSCs express more B7H6, MICA-B, and ULBP1, assessed by percent positivity and mean fluorescence intensity (MFI), as compared to non-CSCs in all cell lines. PD- L1 percent positivity is increased by >20% in CSCs compared to non-CSCs in all cell lines except CH22. In vivo, CSCs comprise 1.39% of chordoma cells and most are PD-L1+ (75.18%). A spatial analysis suggests that chordoma CSCs cluster at an average distance of 71.51 mm (SD 73.40 mm) from stroma. Discussion: To our knowledge, this study is the first to identify individual chordoma CSCs and describe their surface phenotypes using in vitro and in vivo methods. PD-L1 is overexpressed on CSCs in chordoma human cell lines and operative tumor samples. Similarly, potential immunotherapeutic targets on CSCs, including B7H6, MICA-B, ULBP1, EGFR, and HER2 are overexpressed across cell lines. Targeting these markers may have a preferential role in combating CSCs, an aggressive subpopulation likely consequential to chordoma's high recurrence rate.

Efficacy, safety, and biomarker analyses of bintrafusp alfa, a bifunctional fusion protein targeting TGF-ß and PD-L1, in patients with advanced non-small cell lung cancer.

BACKGROUND: Bintrafusp alfa, a first-in-class bifunctional fusion protein targeting transforming growth factor-ß (TGF-ß) and programmed cell death ligand 1, has demonstrated encouraging efficacy as second-line treatment in patients with non-small cell lung cancer (NSCLC) in a dose expansion cohort of the phase 1, open-label clinical trial (NCT02517398). Here, we report the safety, efficacy, and biomarker analysis of bintrafusp alfa in a second expansion cohort of the same trial (biomarker cohort). METHODS: Patients with stage IIIb/IV NSCLC who were either immune checkpoint inhibitor (ICI)-naïve (n=18) or ICI-experienced (n=23) were enrolled. The primary endpoint was the best overall response. Paired biopsies (n=9/41) and peripheral blood (n=14/41) pretreatment and on-treatment were studied to determine the immunological effects of treatment and for associations with clinical activity. RESULTS: Per independent review committee assessment, objective responses were observed in the ICI-naïve group (overall response rate, 27.8%). No new or unexpected safety signals were identified. Circulating TGF-ß levels were reduced (>97%; p<0.001) 2 weeks after initiation of treatment with bintrafusp alfa and remained reduced up to 12 weeks. Increases in lymphocytes and tumor-associated macrophages (TAMs) were observed in on-treatment biospies, with an increase in the M2 (tumor trophic TAMs)/M1 (inflammatory TAMs) ratio associated with poor outcomes. Specific peripheral immune analytes at baseline and early changes after treatment were associated with clinical response. CONCLUSIONS: Bintrafusp alfa was observed to have modest clinical activity and manageable safety, and was associated with notable immunologic changes involving modulation of the tumor immune microenvironment in patients with advanced NSCLC.

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts.

Tumor cell HLA class I expression and pathologic response following neoadjuvant immunotherapy for newly diagnosed head and neck cancer.

OBJECTIVES: Biomarkers are needed to identify patients likely to respond to neoadjuvant immunotherapy (NIT) prior to receiving definitive treatment. MATERIALS AND METHODS: We hypothesized that expression of tumor cell HLA class I would correlate with pathologic response (PR) following NIT for primary untreated head and neck cancer. Multispectral immunofluorescence of pre- and post-treatment biopsy specimens from a neoadjuvant study of bintrafusp alfa, a dual TGF-ß and PD-L1 inhibitor, was performed. RESULTS: Discordant expression of tumor cell HLA class I and PD-L1 measured by multispectral immunofluorescence was observed with most positive tumor cells expressing HLA class I or PD-L1 but not both. Spatial analysis revealed colocalization between tumor parenchyma T cells and HLA class I positive tumors cells, but no clear colocalization between T cells and PD-L1 positive tumor cells. Greater pre-treatment tumor cell HLA class I expression, but not PD-L1 expression or tumor T cell infiltration, correlated with the development of a PR. Additionally, increased tumor cell HLA class I expression after NIT compared to before NIT correlated with development of a PR, whereas inconsistent changes in PD-L1 and T cell infiltration were observed after treatment in all patients. CONCLUSIONS: These data provide the rationale for the study of tumor cell HLA class I expression in larger prospective studies powered to determine the performance of biomarkers of PR in newly diagnosed HNSCC patients receiving NIT.

GNRH2 Polymorphism in Men With Prostate Cancer Treated With Androgen Deprivation Therapy.

BACKGROUND/AIM: Gonadotropin-releasing hormone 2 (GNRH2) is a poorly-studied peptide hormone that is widely distributed in the central nervous system and expressed in peripheral tissues of mammals. The non-synonymous rs6051545 variant in GNRH2 (A16V) has been linked to higher serum testosterone concentrations. This study investigated whether the A16V variant is associated with altered androgen-deprivation therapy (ADT) progression-free survival (PFS) and overall survival (OS). PATIENTS AND METHODS: We examined the expression of GNRH2 in prostate tissue microarrays comprising normal tissue, prostatic hyperplasia, and prostate cancer using immunofluorescence. We also evaluated the GNRH2 genotype in 131 patients with prostate cancer who received ADT and compared PFS and OS between the variant and wild-type genotypes. RESULTS: GNRH2 was detected in all prostate tissues, although expression did not vary with Gleason grade or disease stage (p=0.71). The GNRH2 A16V genotype was not associated with PFS or OS; however, univariate and multivariate analyses revealed Gleason score and definitive local therapy were each associated with PFS (p≤0.0074), whereas age and Gleason score were associated with OS (p≤0.0046). CONCLUSION: GNRH2 is expressed in normal, hyperplastic, and neoplastic prostate tissues; the A16V variant is not related to treatment outcome or survival.

Prediction of cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values. DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Our key contribution is showing that ENLIGHT-DeepPT successfully predicts true responders in five independent patients' cohorts involving four different treatments spanning six cancer types with an overall odds ratio of 2.44, increasing the baseline response rate by 43.47% among predicted responders, without the need for any treatment data for training. Furthermore, its prediction accuracy on these datasets is comparable to a supervised approach predicting the response directly from the images, which needs to be trained and tested on the same cohort. ENLIGHT-DeepPT future application could provide clinicians with rapid treatment recommendations to an array of different therapies and importantly, may contribute to advancing precision oncology in developing countries.

Multi-spectral immunofluorescence evaluation of the myeloid, T cell, and natural killer cell tumor immune microenvironment in chordoma may guide immunotherapeutic strategies.

Background: Chordoma is a rare, invasive, and devastating bone malignancy of residual notochord tissue that arises at the skull base, sacrum, or spine. In order to maximize immunotherapeutic approaches as a potential treatment strategy in chordoma it is important to fully characterize the tumor immune microenvironment (TIME). Multispectral immunofluorescence (MIF) allows for comprehensive evaluation of tumor compartments, molecular co-expression, and immune cell spatial relationships. Here we implement MIF to define the myeloid, T cell, and natural killer (NK) cell compartments in an effort to guide rational design of immunotherapeutic strategies for chordoma. Methods: Chordoma tumor tissue from 57 patients was evaluated using MIF. Three panels were validated to assess myeloid cell, T cell, and NK cell populations. Slides were stained using an automated system and HALO software objective analysis was utilized for quantitative immune cell density and spatial comparisons between tumor and stroma compartments. Results: Chordoma TIME analysis revealed macrophage infiltration of the tumor parenchyma at a significantly higher density than stroma. In contrast, helper T cells, cytotoxic T cells, and T regulatory cells were significantly more abundant in stroma versus tumor. T cell compartment infiltration more commonly demonstrated a tumor parenchymal exclusion pattern, most markedly among cytotoxic T cells. NK cells were sparsely found within the chordoma TIME and few were in an activated state. No immune composition differences were seen in chordomas originating from diverse anatomic sites or between those resected at primary versus advanced disease stage. Conclusion: This is the first comprehensive evaluation of the chordoma TIME including myeloid, T cell, and NK cell appraisal using MIF. Our findings demonstrate that myeloid cells significantly infiltrate chordoma tumor parenchyma while T cells tend to be tumor parenchymal excluded with high stromal infiltration. On average, myeloid cells are found nearer to target tumor cells than T cells, potentially resulting in restriction of T effector cell function. This study suggests that future immunotherapy combinations for chordoma should be aimed at decreasing myeloid cell suppressive function while enhancing cytotoxic T cell and NK cell killing.

Enhanced neoepitope-specific immunity following neoadjuvant PD-L1 and TGF-ß blockade in HPV-unrelated head and neck cancer.

BACKGROUNDHead and neck squamous cell carcinoma not associated with HPV (HPV-unrelated HNSCC) is associated with a high rate of recurrence and poor survival.METHODSWe conducted a clinical trial in 14 patients with newly diagnosed HPV-unrelated HNSCC to evaluate the safety and efficacy of neoadjuvant bintrafusp alfa, a bifunctional fusion protein that blocks programmed death ligand 1 (PD-L1) and neutralizes TGF-ß.RESULTSBintrafusp alfa was well tolerated, and no treatment-associated surgical delays or complications occurred. Objective pathologic responses (PRs) were observed, and 12 of the 14 (86%) patients were alive and disease free at 1 year. Alterations in Treg infiltration and spatial distribution relative to proliferating CD8+ T cells indicated a reversal of Treg immunosuppression in the primary tumor. Detection of neoepitope-specific tumor T cell responses, but not virus-specific responses, correlated with the development of a PR. Detection of neoepitope-specific responses and PRs in tumors was not correlated with genomic features or tumor antigenicity but was associated with reduced pretreatment myeloid cell tumor infiltration. These results indicate that dual PD-L1 and TGF-ß blockade can safely enhance tumor antigen-specific immunity and highlight the feasibility of multimechanism neoadjuvant immunotherapy for patients with HPV-unrelated HNSCC.CONCLUSIONOur studies provide insight into the ability of neoadjuvant immunotherapy to induce polyclonal neoadjuvant-specific T cell responses in tumors and suggest that features of the tumor microenvironment, such as myeloid cell infiltration, may be a major determinant of enhanced antitumor immunity following such treatment.TRIAL REGISTRATIONClinicalTrials.gov NCT04247282.FUNDINGThis work was funded by the Center for Cancer Research, the NCI, and the Intramural Research Program of the NIDCD, NIH. Bintrafusp alfa was provided by the health care business of Merck KGaA (Darmstadt, Germany), through a Cooperative Research and Development Agreement with the NCI. Additional funding was provided by ImmunityBio through a Cooperative Research and Development Agreement with the NIDCD.

Cell-based quantification of molecular biomarkers in histopathology specimens.

AIMS: To investigate the use of a computer-assisted technology for objective, cell-based quantification of molecular biomarkers in specified cell types in histopathology specimens, with the aim of advancing current visual estimation and pixel-level (rather than cell-based) quantification methods. METHODS AND RESULTS: Tissue specimens were multiplex-immunostained to reveal cell structures, cell type markers, and analytes, and imaged with multispectral microscopy. The image data were processed with novel software that automatically delineates and types each cell in the field, measures morphological features, and quantifies analytes in different subcellular compartments of specified cells.The methodology was validated with the use of cell blocks composed of differentially labelled cultured cells mixed in known proportions, and evaluated on human breast carcinoma specimens for quantifying human epidermal growth factor receptor 2, estrogen receptor, progesterone receptor, Ki67, phospho-extracellular signal-related kinase, and phospho-S6. Automated cell-level analyses closely matched human assessments, but, predictably, differed from pixel-level analyses of the same images. CONCLUSIONS: Our method reveals the type, distribution, morphology and biomarker state of each cell in the field, and allows multiple biomarkers to be quantified over specified cell types, regardless of their abundance. It is ideal for studying specimens from patients in clinical trials of targeted therapeutic agents, for investigating minority stromal cell subpopulations, and for phenotypic characterization to personalize therapy and prognosis.

Improved automatic detection and segmentation of cell nuclei in histopathology images.

Automatic segmentation of cell nuclei is an essential step in image cytometry and histometry. Despite substantial progress, there is a need to improve accuracy, speed, level of automation, and adaptability to new applications. This paper presents a robust and accurate novel method for segmenting cell nuclei using a combination of ideas. The image foreground is extracted automatically using a graph-cuts-based binarization. Next, nuclear seed points are detected by a novel method combining multiscale Laplacian-of-Gaussian filtering constrained by distance-map-based adaptive scale selection. These points are used to perform an initial segmentation that is refined using a second graph-cuts-based algorithm incorporating the method of alpha expansions and graph coloring to reduce computational complexity. Nuclear segmentation results were manually validated over 25 representative images (15 in vitro images and 10 in vivo images, containing more than 7400 nuclei) drawn from diverse cancer histopathology studies, and four types of segmentation errors were investigated. The overall accuracy of the proposed segmentation algorithm exceeded 86%. The accuracy was found to exceed 94% when only over- and undersegmentation errors were considered. The confounding image characteristics that led to most detection/segmentation errors were high cell density, high degree of clustering, poor image contrast and noisy background, damaged/irregular nuclei, and poor edge information. We present an efficient semiautomated approach to editing automated segmentation results that requires two mouse clicks per operation.

Effect of VEGF and VEGF Trap on vascular endothelial cell signaling in tumors.

Vascular endothelial growth factor (VEGF) A is a major promoter of tumor angiogenesis and a prime target of antiangiogenic cancer therapy. To examine whether endothelial cell signaling might provide histological biomarkers of angiogenesis and VEGF activity in vivo, normal mouse organs and multiple tumor models were studied immunohistochemically for endothelial expression of activated ERK, STAT3, and AKT. Phospho(p)-ERK and p-STAT3 expression was negligible in the endothelia of normal organs but was significantly elevated in tumor endothelium. p-AKT was present at significant and comparable levels in both tumor and normal endothelia. In K1735 tumors induced to express more VEGF, endothelial p-ERK, p-STAT3 and p-AKT increased accompanied by signs of accelerated angiogenesis. Treatment of K1735 and Colo-205 tumors with the VEGF inhibitor, VEGF Trap (aflibercept), decreased tumor endothelial p-ERK, p-STAT3 and p-AKT expression accompanied by signs of antiangiogenic effect. These results show that endothelial p-ERK and p-STAT3 (but not p-AKT) distinguish tumor from normal vessels and that the presence of these two signaling intermediates may be useful indicators of tumor angiogenic activity and angiogenesis inhibition by VEGF antagonist.

Interferon-gamma-dependent infiltration of human T cells into neuroblastoma tumors in vivo.

PURPOSE: To investigate the impact of interferon-gamma-mediated upregulation of major histocompatibility complex class I expression on tumor-specific T-cell cytotoxicity and T-cell trafficking into neuroblastoma tumors in vivo. EXPERIMENTAL DESIGN: Restoration of major histocompatibility complex class I expression by interferon-gamma treatment enhances killing of neuroblastoma cells. To understand the potential of this approach in vivo, we developed a novel model of neuroblastoma in which NOD/scid/IL2R gamma(null) immunodeficient mice are engrafted with both human T cells and tumor cells. RESULTS: Here, we show enhanced killing of neuroblastoma cells by patient-derived, tumor-specific T cells in vitro. In addition, interferon-gamma treatment in vivo induces efficient upregulation of major histocompatibility complex class I expression on neuroblastoma tumor cells, and this is accompanied by significantly enhanced infiltration of T cells into the tumor. In a pilot clinical trial in patients with high-risk neuroblastoma, we similarly observed augmented T-cell trafficking into neuroblastoma nests in tumor biopsy specimens obtained from patients after 5 days of systemic interferon-gamma therapy. CONCLUSIONS: Interferon-gamma overcomes critical obstacles to the killing of human neuroblastoma cells by specific T cells. Together, these findings provide a rationale for the further testing of interferon-gamma as an approach for improving the efficacy of T cell-based therapies for neuroblastoma and other major histocompatibility complex class I-deficient malignancies. In addition, we describe a model that may expedite the preclinical screening of approaches aimed at augmenting T-cell trafficking into human tumors.

Activated STAT3 is a mediator and biomarker of VEGF endothelial activation.

STAT3 plays important roles in cell proliferation and survival signaling and is often constitutively activated in transformed cells. In this study, we examined STAT3 activation in endothelial cells (EC) during angiogenic activation and therapeutic angiogenesis inhibition. VEGF stimulation of cultured EC induced STAT3 phosphorylation by a VEGFR2- and Src-dependent mechanism. FGF2 but not PlGF also induced EC STAT3 activation in vitro. Activated STAT3 mediated VEGF induction of EC Bcl-2 and contributed to VEGF protection of EC from apoptosis. In vivo, p-STAT3 was absent by immunohistological staining in the vascular EC of most normal mouse organs but was present in the vessels of mouse and human tumors. Tumor vascular p-STAT3 increased as tumors were induced to overexpress VEGF, indicating that VEGF is an activator of EC p-STAT3 in vivo. Tumor vascular p-STAT3 decreased during angiogenesis inhibition by antagonists of VEGF-VEGFR signaling, VEGF Trap and SU5416, indicating that VEGF contributed to the EC STAT3 activation seen in the tumors prior to treatment and that p-STAT3 may be used to monitor therapy. These studies show that p-STAT3 is a mediator and biomarker of endothelial activation that reports VEGF-VEGFR2 activity and may be useful for studying the pharmacodynamics of targeted angiogenesis inhibitors.

Inhibition of tumor endothelial ERK activation, angiogenesis, and tumor growth by sorafenib (BAY43-9006).

Activation of the Raf-MEK-ERK signal transduction pathway in endothelial cells is required for angiogenesis. Raf is the kinase most efficiently inhibited by the multikinase inhibitor sorafenib, which has shown activity against certain human cancers in clinical trials. To understand the mechanisms underlying this activity, we studied how it controlled growth of K1735 murine melanomas. Therapy caused massive regional tumor cell death accompanied by severe tumor hypoxia, decreased microvessel density, increased percentage of pericyte-covered vessels, and increased caliber and decreased arborization of vessels. These signs of K1735 angiogenesis inhibition, along with its ability to inhibit Matrigel neovascularization, showed that sorafenib is an effective anti-angiogenic agent. Extracellular signal-regulated kinase (ERK) activation in tumor endothelial cells, revealed by immunostaining for phospho-ERK and CD34, was inhibited, whereas AKT activation, revealed by phospho-AKT immunostaining, was not inhibited in K1735 and two other tumor types treated with sorafenib. Treatment decreased endothelial but not tumor cell proliferation and increased both endothelial cell and tumor cell apoptosis. These data indicate that sorafenib's anti-tumor efficacy may be primarily attributable to angiogenesis inhibition resulting from its inhibition of Raf-MEK-ERK signaling in endothelial cells. Assessing endothelial cell ERK activation in tumor bio-psies may provide mechanistic insights into and allow monitoring of sorafenib's activity in patients in clinical trials.