Canary Foundation

Abstract Existing predictive biomarkers for immune checkpoint blockade (ICB) therapies that rely on characterization of tumor genomics or immunohistological assessment of the tumor microenvironment have demonstrated mixed success, with no single biomarker proving to be universally predictive of ICB treatment outcome. To complement these existing approaches, we present a workflow that relies on high-resolution single-cell mass measurements curated with CNN-based image classification to characterize T cell activation and functional response to treatment with ICB therapies. As a highly integrative measure of cellular phenotype, cell mass can be used as a label-free biomarker for characterizing immune cell function. For instance, upon activation with anti-CD3/CD28, T cells isolated from human PBMC showed a rapid and significant increase in cell mass. However, in T cells that had been repeatedly stimulated in vitro to generate a PD-1+ exhausted-like phenotype, this mass response to activation was blunted. We hypothesized that this variability in activation-induced mass response was the result of an altered balance of stimulatory and inhibitory “signal two” cues seen by the T cells. Consistent with this hypothesis, purified T cells stimulated with anti-CD3 alone (no co-stimulation) demonstrated a significantly smaller increase in cell mass when compared with those stimulated with both anti-CD3 and anti-CD28. Furthermore, the T cell response measured when unpurified PBMC were activated with anti-CD3 demonstrated an intermediate mass increase, suggesting contributions of both stimulatory and inhibitory signaling from other cells in the milieu. To explore how ICB treatment disrupts this co-stimulatory/inhibitory signaling balance, we measured T cell mass responses for samples treated with anti-CD3 alone or in combination with pembrolizumab, atezolizumab, nivolumab, or dostarlimab. These samples included PBMC isolated from blood and tumor/immune cell milieus isolated from malignant fluids (pleural effusions or abdominal ascites) collected from patients with advanced cancer. We found that T cells isolated from samples treated with both anti-CD3 and an ICB drug often showed a significantly greater mass increase than the same samples treated with anti-CD3 alone. This mass response showed significant heterogeneity across patients, with many samples showing no significant treatment effect. Despite all four of these therapies targeting ostensibly the same PD-1/PD-L1 signaling axis, we also found significant response heterogeneity to these different treatments within individual samples.These results suggest that mass response measurements capture biological heterogeneity associated with ICB response and may serve as a valuable complementary readout to existing biomarkers. Citation Format: Robert Kimmerling, Mark Stevens, Selim Olcum, Anthony Minnah, Madeleine Vacha, Rachel LaBella, Katie Katsis, Audrey Guo, Juanita Fujii, Zayna Shaheen, Srividya Sundaresan, Anobel Tamrazi, Cliff Reid. A cell mass-based platform for characterizing immune cell function and response to checkpoint blockade in primary blood and malignant fluid samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2176.

Abstract Introduction. The Spanish Yale Food Addiction Scale for Children (S-YFAS-C) scale is the first tool adapted to Spanish to evaluate food addiction (FA) in the paediatric population. The aim of this study is to preliminarily evaluate the degree of FA in a non-clinical pilot paediatric population. Material and methods. A transversal observational study was performed on a convenience sample comprised of boys and girls aged 9 to 12 (4th to 6th year primary school). The main outcome measures were evaluation of FA (S-YFAS-C scale), child feeding attitudes (ChEAT scale) and evaluation of body image (CDRS scale). Moreover, sociodemographic and anthropometric data were collected. A descriptive and bivariate analysis of the main characteristics of subjects and outcome measures was performed. Results. A total of 21 boys and 24 girls were preliminarily evaluated and the minimum and maximum values obtained were for age (9.48 – 12.33), weight in kilograms (26.6 – 64.5), height in centimetres (131-163), BMI (14.2-27.9) and BMI Z-score (-1.36 – 2.66). The average number of FA symptoms measured with the S-YFAS-C scale is 1.67±1.45 (range 0 - 7). A total of 20% of the sample shows three or more symptoms for FA, risk of developing a food disorder and distortion of the body image. Moreover, statistically significant differences were observed between desired body image in boys and girls (P=0.001). Conclusions. The S-YFAS-C scale enables evaluating food addiction in Spanish-speaking boys and girls. The data obtained in regard to quantifying symptoms are similar compared to the original scale (S-YFAS-C: 1.67±1.45 vs. YFAS-C: 2±1.81). The option to score the counting of symptoms is the most sensitive measure to evaluate subclinical food behaviours.

Abstract Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. In current clinical practice, the microscopic architecture of the prostate glands is what forms the basis for prognostic grading by pathologists. Interpretation of these convoluted 3D glandular structures via visual inspection of a limited number of 2D histology sections is often unreliable, which contributes to the under- and over-treatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for non-destructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analog of standard H&E staining. Our analysis is based on interpretable glandular features, and is facilitated by the development of image-translation-assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep-learning-based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring real immunolabeling. To provide evidence of the translational value of a computational 3D pathology approach, we analyzed ex vivo biopsies (n = 300) extracted from archived radical-prostatectomy specimens (N = 50), and found that 3D glandular features are superior to corresponding 2D features for risk stratification of low-to intermediate-risk PCa patients based on their clinical biochemical recurrence (BCR) outcomes.SignificanceWe present an end-to-end pipeline for computational 3D pathology of whole prostate biopsies, showing that non-destructive pathology has the potential to enable superior prognostic stratification for guiding critical oncology decisions.

Histologic grading remains the gold standard for prognosis in prostate cancer, and assessment of Gleason score plays a critical role in active surveillance management. We sought to optimize the prognostic stratification of grading and developed a method of recording and studying individual architectural patterns by light microscopic evaluation that is independent of standard Gleason grade. Some of the evaluated patterns are not assessed by current Gleason grading (eg, reactive stromal response). Individual histologic patterns were correlated with recurrence-free survival in a retrospective postradical prostatectomy cohort of 1275 patients represented by the highest-grade foci of carcinoma in tissue microarrays. In univariable analysis, fibromucinous rupture with varied epithelial complexity had a significantly lower relative risk of recurrence-free survival in cases graded as 3+4=7. Cases having focal "poorly formed glands," which could be designated as pattern 3+4=7, had lower risk than cribriform patterns with either small cribriform glands or expansile cribriform growth. In separate multivariable Cox proportional hazard analyses of both Gleason score 3+3=6 and 3+4=7 carcinomas, reactive stromal patterns were associated with worse recurrence-free survival. Decision tree models demonstrate potential regrouping of architectural patterns into categories with similar risk. In summary, we argue that Gleason score assignment by current consensus guidelines are not entirely optimized for clinical use, including active surveillance. Our data suggest that focal poorly formed gland and cribriform patterns, currently classified as Gleason pattern 4, should be in separate prognostic groups, as the latter is associated with worse outcome. Patterns with extravasated mucin are likely overgraded in a subset of cases with more complex epithelial bridges, whereas stromogenic cancers have a worse outcome than conveyed by Gleason grade alone. These findings serve as a foundation to facilitate optimization of histologic grading and strongly support incorporating reactive stroma into routine assessment.

Given the uncertainties inherent in clinical measures of prostate cancer aggressiveness, clinically validated tissue biomarkers are needed. We tested whether Alpha-2-Glycoprotein 1, Zinc-Binding (AZGP1) protein levels, measured by immunohistochemistry, and RNA expression, by RNA in situ hybridization (RISH), predict recurrence after radical prostatectomy independent of clinical and pathological parameters. AZGP1 IHC and RISH were performed on a large multi-institutional tissue microarray resource including 1,275 men with 5 year median follow-up. The relationship between IHC and RISH expression levels was assessed using the Kappa analysis. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazards models and the Log-rank test. Absent or weak expression of AZGP1 protein was associated with worse recurrence free survival (RFS), disease specific survival, and overall survival after radical prostatectomy in univariable analysis. AZGP1 protein expression, along with pre-operative serum PSA levels, surgical margin status, seminal vesicle invasion, extracapsular extension, and Gleason score predicted RFS on multivariable analysis. Similarly, absent or low AZGP1 RNA expression by RISH predicted worse RFS after prostatectomy in univariable and multivariable analysis. In our large, rigorously designed validation cohort, loss of AZGP1 expression predicts RFS after radical prostatectomy independent of clinical and pathological variables. Prostate 76:1409-1419, 2016. © 2016 Wiley Periodicals, Inc.

BackgroundEpithelial ovarian carcinoma is a significant cause of cancer mortality in women worldwide and in the United States. Epithelial ovarian cancer comprises several histological subtypes, each with distinct clinical and molecular characteristics. The natural history of this heterogeneous disease, including the cell types of origin, is poorly understood. This study applied recently developed methods for high-throughput DNA methylation profiling to characterize ovarian cancer cell lines and tumors, including representatives of three major histologies.Methodology/Principal FindingsWe obtained DNA methylation profiles of 1,505 CpG sites (808 genes) in 27 primary epithelial ovarian tumors and 15 ovarian cancer cell lines. We found that the DNA methylation profiles of ovarian cancer cell lines were markedly different from those of primary ovarian tumors. Aggregate DNA methylation levels of the assayed CpG sites tended to be higher in ovarian cancer cell lines relative to ovarian tumors. Within the primary tumors, those of the same histological type were more alike in their methylation profiles than those of different subtypes. Supervised analyses identified 90 CpG sites (68 genes) that exhibited ‘subtype-specific’ DNA methylation patterns (FDR<1%) among the tumors. In ovarian cancer cell lines, we estimated that for at least 27% of analyzed autosomal CpG sites, increases in methylation were accompanied by decreases in transcription of the associated gene.SignificanceThe significant difference in DNA methylation profiles between ovarian cancer cell lines and tumors underscores the need to be cautious in using cell lines as tumor models for molecular studies of ovarian cancer and other cancers. Similarly, the distinct methylation profiles of the different histological types of ovarian tumors reinforces the need to treat the different histologies of ovarian cancer as different diseases, both clinically and in biomarker studies. These data provide a useful resource for future studies, including those of potential tumor progenitor cells, which may help illuminate the etiology and natural history of these cancers.

Proteoglycans, a complex group of extracellular matrix (ECM) molecules, are elevated in benign prostatic hyperplasia (BPH). Versican is a stromal proteoglycan present in prostate tissue. Versican expression is elevated in tissues with increased proliferation. Based on these observations, we determined the extent and distribution of versican expression in prostates with BPH. The involvement of versican in BPH nodules was compared with levels in non-nodular transition (TZ) and peripheral zone (PZ) tissues from 18 human prostate glands using immunohistochemistry, Northern blots and/or QRTPCR to localize versican and quantify versican mRNA transcript levels, and Western blots to assess gene product levels. Increased versican immunoreactivity was observed in the stroma of BPH nodules. Higher steady state levels of versican variants V0, V1, and V3 mRNA transcript and gene product were detected in the nodular tissues than in the non-nodular TZ or PZ parenchyma. These results suggest that versican may play a role in nodule formation in BPH.