Activation of a cGAS-STING-mediated immune response predicts response to neoadjuvant chemotherapy in early breast cancer.

BACKGROUND: The DNA-damage immune-response (DDIR) signature is an immune-driven gene expression signature retrospectively validated as predicting response to anthracycline-based therapy. This feasibility study prospectively evaluates the use of this assay to predict neoadjuvant chemotherapy response in early breast cancer. METHODS: This feasibility study assessed the integration of a novel biomarker into clinical workflows. Tumour samples were collected from patients receiving standard of care neoadjuvant chemotherapy (FEC + /-taxane and anti-HER2 therapy as appropriate) at baseline, mid- and post-chemotherapy. Baseline DDIR signature scores were correlated with pathological treatment response. RNA sequencing was used to assess chemotherapy/response-related changes in biologically linked gene signatures. RESULTS: DDIR signature reports were available within 14 days for 97.8% of 46 patients (13 TNBC, 16 HER2 + ve, 27 ER + HER2-ve). Positive scores predicted response to treatment (odds ratio 4.67 for RCB 0-1 disease (95% CI 1.13-15.09, P = 0.032)). DDIR positivity correlated with immune infiltration and upregulated immune-checkpoint gene expression. CONCLUSIONS: This study validates the DDIR signature as predictive of response to neoadjuvant chemotherapy which can be integrated into clinical workflows, potentially identifying a subgroup with high sensitivity to anthracycline chemotherapy. Transcriptomic data suggest induction with anthracycline-containing regimens in immune restricted, "cold" tumours may be effective for immune priming. TRIAL REGISTRATION: Not applicable (non-interventional study). CRUK Internal Database Number 14232.

Identifying mismatch repair-deficient colon cancer: near-perfect concordance between immunohistochemistry and microsatellite instability testing in a large, population-based series.

AIMS: Establishing the mismatch repair (MMR) status of colorectal cancers is important to enable the detection of underlying Lynch syndrome and inform prognosis and therapy. Current testing typically involves either polymerase chain reaction (PCR)-based microsatellite instability (MSI) testing or MMR protein immunohistochemistry (IHC). The aim of this study was to compare these two approaches in a large, population-based cohort of stage 2 and 3 colon cancer cases in Northern Ireland. METHODS AND RESULTS: The study used the Promega pentaplex assay to determine MSI status and a four-antibody MMR IHC panel. IHC was applied to tumour tissue microarrays with triplicate tumour sampling, and assessed manually. Of 593 cases with available MSI and MMR IHC results, 136 (22.9%) were MSI-high (MSI-H) and 135 (22.8%) showed abnormal MMR IHC. Concordance was extremely high, with 97.1% of MSI-H cases showing abnormal MMR IHC, and 97.8% of cases with abnormal IHC showing MSI-H status. Under-representation of tumour epithelial cells in samples from heavily inflamed tumours resulted in misclassification of several cases with abnormal MMR IHC as microsatellite-stable. MMR IHC revealed rare cases with unusual patterns of MMR protein expression, unusual combinations of expression loss, or secondary clonal loss of expression, as further illustrated by repeat immunostaining on whole tissue sections. CONCLUSIONS: MSI PCR testing and MMR IHC can be considered to be equally proficient tests for establishing MMR/MSI status, when there is awareness of the potential pitfalls of either method. The choice of methodology may depend on available services and expertise.

Immune status is prognostic for poor survival in colorectal cancer patients and is associated with tumour hypoxia.

BACKGROUND: Immunohistochemical quantification of the immune response is prognostic for colorectal cancer (CRC). Here, we evaluate the suitability of alternative immune classifiers on prognosis and assess whether they relate to biological features amenable to targeted therapy. METHODS: Overall survival by immune (CD3, CD4, CD8, CD20 and FOXP3) and immune-checkpoint (ICOS, IDO-1 and PD-L1) biomarkers in independent CRC cohorts was evaluated. Matched mutational and transcriptomic data were interrogated to identify associated biology. RESULTS: Determination of immune-cold tumours by combined low-density cell counts of CD3, CD4 and CD8 immunohistochemistry constituted the best prognosticator across stage II-IV CRC, particularly in patients with stage IV disease (HR 1.98 [95% CI: 1.47-2.67]). These immune-cold CRCs were associated with tumour hypoxia, confirmed using CAIX immunohistochemistry (P = 0.0009), which may mediate disease progression through common biology (KRAS mutations, CRIS-B subtype and SPP1 mRNA overexpression). CONCLUSIONS: Given the significantly poorer survival of immune-cold CRC patients, these data illustrate that assessment of CD4-expressing cells complements low CD3 and CD8 immunohistochemical quantification in the tumour bulk, potentially facilitating immunophenotyping of patient biopsies to predict prognosis. In addition, we found immune-cold CRCs to associate with a difficult-to-treat, poor prognosis hypoxia signature, indicating that these patients may benefit from hypoxia-targeting clinical trials.

Alcohol intake, tobacco smoking, and esophageal adenocarcinoma survival: a molecular pathology epidemiology cohort study.

PURPOSE: To investigate the association between cigarette smoking, alcohol consumption, and esophageal adenocarcinoma survival, including stratified analysis by selected prognostic biomarkers. METHODS: A population-representative sample of 130 esophageal adenocarcinoma patients (n = 130) treated at the Northern Ireland Cancer Centre between 2004 and 2012. Cox proportional hazards models were applied to evaluate associations between smoking status, alcohol intake, and survival. Secondary analyses investigated these associations across categories of p53, HER2, CD8, and GLUT-1 biomarker expression. RESULTS: In esophageal adenocarcinoma patients, there was a significantly increased risk of cancer-specific mortality in ever, compared to never, alcohol drinkers in unadjusted (HR 1.96 95% CI 1.13-3.38) but not adjusted (HR 1.70 95% CI 0.95-3.04) analysis. This increased risk of death observed for alcohol consumers was more evident in patients with normal p53 expression, GLUT-1 positive or CD-8 positive tumors. There were no significant associations between survival and smoking status in esophageal adenocarcinoma patients. CONCLUSIONS: In esophageal adenocarcinoma patients, cigarette smoking or alcohol consumption was not associated with a significant difference in survival in comparison with never smokers and never drinkers in fully adjusted analysis. However, in some biomarker-selected subgroups, ever-alcohol consumption was associated with a worsened survival in comparison with never drinkers. Larger studies are needed to investigate these findings, as these lifestyle habits may not only be linked to cancer risk but also cancer survival.

Comparison of different anti-Ki67 antibody clones and hot-spot sizes for assessing proliferative index and grading in pancreatic neuroendocrine tumours using manual and image analysis.

AIMS: Ki67 proliferative index (PI) is essential for grading gastroenteric and pancreatic neuroendocrine tumours (GEP NETs). Analytical and preanalytical variables can affect Ki67 PI. In contrast to counting methodology, until now little attention has focused on the question of clone equivalence and the effect of hot-spot size on Ki67 PI in GEP NETs. Using manual counting and image analysis, this study compared the Ki67 PI achieved using MM1, K2 and 30-9 to MIB1, a clone which has been validated for, and is referenced in, guidelines relating to assessment of Ki67 PI in GEP NETs. METHODS AND RESULTS: Forty-two pancreatic NETs were each immunohistochemically stained for the anti-Ki67 clones MIB1, MM1, K2 and 30-9. Ki67 PI was calculated manually and by image analysis, the latter using three different hot-spot sizes. In manual comparisons using single hot-spot high-power fields, non-MIB1 clones overestimated Ki67 PI compared to MIB1, resulting in grading discordances. Image analysis shows good agreement with manual Ki67 PI but a tendency to overestimate absolute Ki67 PI. Increasing the size of tumour hot-spot from 500 to 2000 cells resulted in a decrease in Ki67 PI. CONCLUSION: Different anti-Ki67 clones do not produce equivalent PIs in GEP NETs, and clone selection may therefore affect patient care. Increasing the hot-spot size decreases the Ki67 PI. Greater standardisation in terms of antibody clone selection and hot-spot size is required for grading GEP NETs. Image analysis is an effective tool for assisting Ki67 assessment and allows easier standardisation of the size of the tumour hot-spot.

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.

BACKGROUND: Limited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification. METHODS: Three hundred twenty-nine EAC cases were available in Tissue Microarrays (TMA) format. A discovery cohort of 166 EAC cases were stained immunohistochemically for range of adaptive immune (CD3, CD4, CD8 and CD45RO) and immune checkpoint biomarkers (ICOS, IDO-1, PD-L1, PD-1). A validation cohort of 163 EAC cases was also accessed. A digital pathology analysis approach was used to quantify biomarker density. RESULTS: CD3, CD4, CD8, CD45RO, ICOS and PD-1 were individually predictive of better overall survival (OS) (Log rank p = < 0.001; p = 0.014; p = 0.001; p = < 0.001; p = 0.008 and p = 0.026 respectively). Correlation and multivariate analysis identified high CD45RO/ICOS patients with significantly improved OS which was independently prognostic (HR = 0.445, (0.223-0.886), p = 0.021). Assessment of CD45RO and ICOS high cases in the validation cohort revealed an associated with improved OS (HR = 0.601 (0.363-0.996), p = 0.048). Multiplex IHC identified cellular co-expression of high CD45RO/ICOS. High CD45RO/ICOS patients have significantly improved OS. CONCLUSIONS: Multiplexing identifies true cellular co-expression. These data demonstrate that co-expression of immune biomarkers are associated with better outcome in EAC and may provide evidence for immunotherapy treatment stratification.

Recommendations for determining HPV status in patients with oropharyngeal cancers under TNM8 guidelines: a two-tier approach.

BACKGROUND: TNM8 staging for oropharyngeal squamous cell carcinomas (OPSCC) surrogates p16 immunohistochemistry for HPV testing. Patients with p16+ OPSCC may lack HPV aetiology. Here, we evaluate the suitability of TNM8 staging for guiding prognosis in such patients. METHODS: HPV status was ascertained using p16 immunohistochemistry and high-risk HPV RNA and DNA in situ hybridisation. Survival by stage in a cohort of OPSCC patients was evaluated using TNM7/TNM8 staging. Survival of p16+/HPV- patients was compared to p16 status. RESULTS: TNM8 staging was found to improve on TNM7 (log rank p = 0·0190 for TNM8 compared with p = 0·0530 for TNM7) in p16+ patients. Patients who tested p16+ but were HPV- (n = 20) had significantly reduced five-year survival (33%) compared to p16+ patients (77%) but not p16- patients (35%). Cancer stage was reduced in 95% of p16+/HPV- patients despite having a mortality rate twice (HR 2.66 [95% CI: 1.37-5.15]) that of p16+/HPV+ patients under new TNM8 staging criteria. CONCLUSION: Given the significantly poorer survival of p16+/HPV- OPSCCs, these data provide compelling evidence for use of an HPV-specific test for staging classification. This has particular relevance in light of potential treatment de-escalation that could expose these patients to inappropriately reduced treatment intensity as treatment algorithms evolve.

High PTGS2 expression in post-neoadjuvant chemotherapy-treated oesophageal adenocarcinoma is associated with improved survival: a population-based cohort study.

AIMS: High prostaglandin endoperoxide synthase-2 (PTGS2) enzyme expression in oesophageal adenocarcinoma has been shown to independently predict poor prognosis; however, the evidence is inconsistent. The aim of this study was to investigated the association between PTGS2 expression and prognosis in patients with oesophageal adenocarcinoma. METHODS AND RESULTS: A cohort of 135 patients with oesophageal adenocarcinoma who received neoadjuvant chemotherapy and surgery from 2004 to 2012 was identified in the Northern Ireland Cancer Centre. Tissue microarrays were created in the Northern Ireland Biobank, with triplicate cores being sampled from each tumour. Immunohistochemical PTGS2 expression was scored by two independent assessors, with intensity and proportion of tumour staining being used to calculate H-scores for each patient. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for overall and cancer-specific survival, and recurrence-free survival by PTGS2 expression, with adjustment for potential confounders. Patients were followed up for a mean of 3.0 years (standard deviation 1.8 years). The PTGS2 expression cut-off value was determined from the median H-score of the cohort (270/300). High (n = 79), as compared with low (n = 56), PTGS2 expression was associated with improved cancer-specific survival (adjusted HR 0.56, 95% CI 0.33-0.94; P = 0.03). PTGS2 expression was not significantly associated with recurrence-free survival (adjusted HR 0.85, 95% CI 0.52-1.38; P = 0.51). CONCLUSIONS: High PTGS2 expression in oesophageal adenocarcinoma tissue was associated with improved overall and cancer-specific survival, in contrast to previous evidence. As this is the first study of its kind to include patients who had undergone neoadjuvant chemotherapy, further studies are needed to clarify these associations.

NUP98 - a novel predictor of response to anthracycline-based chemotherapy in triple negative breast cancer.

BACKGROUND: Triple Negative breast cancer (TNBC) is a poor outcome subgroup of breast cancer defined based on the absence of expression of ERα and PR and HER2 amplification. These hard to treat cancers lack targeted treatment options and are therefore treated with a standard of care (SoC) generic cocktail of DNA damaging chemotherapy, with a wide range of clinical responses. While a subset of TNBC patients respond very well to this treatment, others receive no clinical benefit and die from their disease within a short time period. We currently lack biomarkers to prospectively identify patients likely to relapse and we lack alternate treatment options. METHODS: NUP98 protein expression was investigated in patient samples using two independent tissue microarrays (TMAs), as well as a normal breast TMA. Correlation with pathological response to various chemotherapy regimens was investigated. RESULTS: We have shown that high NUP98 is significantly associated with poor outcome in TNBC patient samples both by gene expression and IHC-based protein analysis. While trends linking NUP98 expression with poorer outcomes were observed in breast cancer overall (and more specifically in the LuminalB Her2- subgroup), significant correlations were observed in TNBC. This appeared to be specific to anthracycline based regimens as the association between NUP98 and response was not observed in patients treated with taxane-based chemotherapy. CONCLUSIONS: We have identified a novel biomarker, NUP98, that can predict response to anthracycline based chemotherapy in TNBC. The ability to prospectively identify patients who are less likely to respond to SoC chemotherapy is a vital step in improving the overall survival of these patients.

Gremlin1 plays a key role in kidney development and renal fibrosis.

Gremlin1 (Grem1), an antagonist of bone morphogenetic proteins, plays a key role in embryogenesis. A highly specific temporospatial gradient of Grem1 and bone morphogenetic protein signaling is critical to normal lung, kidney, and limb development. Grem1 levels are increased in renal fibrotic conditions, including acute kidney injury, diabetic nephropathy, chronic allograft nephropathy, and immune glomerulonephritis. We demonstrate that a small number of grem1-/- whole body knockout mice on a mixed genetic background (8%) are viable, with a single, enlarged left kidney and grossly normal histology. The grem1-/- mice displayed mild renal dysfunction at 4 wk, which recovered by 16 wk. Tubular epithelial cell-specific targeted deletion of Grem1 (TEC-grem1-cKO) mice displayed a milder response in the acute injury and recovery phases of the folic acid model. Increases in indexes of kidney damage were smaller in TEC-grem1-cKO than wild-type mice. In the recovery phase of the folic acid model, associated with renal fibrosis, TEC-grem1-cKO mice displayed reduced histological damage and an attenuated fibrotic gene response compared with wild-type controls. Together, these data demonstrate that Grem1 expression in the tubular epithelial compartment plays a significant role in the fibrotic response to renal injury in vivo.

Statin use, candidate mevalonate pathway biomarkers, and colon cancer survival in a population-based cohort study.

BACKGROUND: Statin use after colorectal cancer diagnosis may improve survival but evidence from observational studies is conflicting. The anti-cancer effect of statins may be restricted to certain molecular subgroups. In this population-based cohort study, the interaction between p53 and 3-hydroxy-3-methylglutaryl coenzyme-A reductase (HMGCR) expression, KRAS mutations, and the association between statin use and colon cancer survival was assessed. METHODS: The cohort consisted of 740 stage II and III colon cancer patients diagnosed between 2004 and 2008. Statin use was determined through clinical note review. Tissue blocks were retrieved to determine immunohistochemical expression of p53 and HMGCR in tissue microarrays and the presence of KRAS mutations in extracted DNA. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for colorectal cancer-specific and overall survival. RESULTS: Statin use was not associated with improved cancer-specific survival in this cohort (HR=0.91, 95% CI 0.64-1.28). Statin use was also not associated with improved survival when the analyses were stratified by tumour p53 (wild-type HR=1.31, 95% CI 0.67-2.56 vs aberrant HR=0.80, 95% CI 0.52-1.24), HMGCR (HMGCR-high HR=0.69, 95% CI 0.40-1.18 vs HMGCR-low HR=1.10, 95% CI 0.66-1.84), and KRAS (wild-type HR=0.73, 95% CI 0.44-1.19 vs mutant HR=1.21, 95% CI 0.70-2.21) status. CONCLUSIONS: Statin use was not associated with improved survival either independently or when stratified by potential mevalonate pathway biomarkers in this population-based cohort of colon cancer patients.

Molecular profiling of signet ring cell colorectal cancer provides a strong rationale for genomic targeted and immune checkpoint inhibitor therapies.

BACKGROUND: Signet ring cell colorectal cancer (SRCCa) has a bleak prognosis. Employing molecular pathology techniques we investigated the potential of precision medicine in this disease. METHODS: Using test (n=26) and validation (n=18) cohorts, analysis of mutations, DNA methylation and transcriptome was carried out. Microsatellite instability (MSI) status was established and immunohistochemistry (IHC) was used to test for adaptive immunity (CD3) and the immune checkpoint PDL1. RESULTS: DNA methylation data split the cohorts into hypermethylated (n=18, 41%) and hypomethylated groups (n=26, 59%). The hypermethylated group predominant in the proximal colon was enriched for CpG island methylator phenotype (CIMP), BRAF V600E mutation and MSI (P<0.001). These cases also had a high CD3+ immune infiltrate (P<0.001) and expressed PDL1 (P=0.03 in intra-tumoural lymphoid cells). The hypomethylated group predominant in the distal colon did not show any characteristic molecular features. We also detected a common targetable KIT mutation (c.1621A>C) across both groups. No statistically significant difference in outcome was observed between the two groups. CONCLUSIONS: Our data show that SRCCa phenotype comprises two distinct genotypes. The MSI+/CIMP+/BRAF V600E+/CD3+/PDL1+ hypermethylated genotype is an ideal candidate for immune checkpoint inhibitor therapy. In addition, one fourth of SRCCa cases can potentially be targeted by KIT inhibitors.

Topographic analysis of pancreatic cancer by TMA and digital spatial profiling reveals biological complexity with potential therapeutic implications.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-ß axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

Exploring the immune microenvironment in small bowel adenocarcinoma using digital image analysis.

BACKGROUND: Small bowel adenocarcinoma (SBA) is a rare malignancy of the small intestine associated with late stage diagnosis and poor survival outcome. High expression of immune cells and immune checkpoint biomarkers especially programmed cell death ligand-1 (PD-L1) have been shown to significantly impact disease progression. We have analysed the expression of a subset of immune cell and immune checkpoint biomarkers in a cohort of SBA patients and assessed their impact on progression-free survival (PFS) and overall survival (OS). METHODS: 25 patient samples in the form of formalin fixed, paraffin embedded (FFPE) tissue were obtained in tissue microarray (TMAs) format. Automated immunohistochemistry (IHC) staining was performed using validated antibodies for CD3, CD4, CD8, CD68, PD-L1, ICOS, IDO1 and LAG3. Slides were scanned digitally and assessed in QuPath, an open source image analysis software, for biomarker density and percentage positivity. Survival analyses were carried out using the Kaplan Meier method. RESULTS: Varying expressions of biomarkers were recorded. High expressions of CD3, CD4 and IDO1 were significant for PFS (p = 0.043, 0.020 and 0.018 respectively). High expression of ICOS was significant for both PFS (p = 0.040) and OS (p = 0.041), while high PD-L1 expression in tumour cells was significant for OS (p = 0.033). High correlation was observed between PD-L1 and IDO1 expressions (Pearson correlation co-efficient = 1) and subsequently high IDO1 expression in tumour cells was found to be significant for PFS (p = 0.006) and OS (p = 0.034). CONCLUSIONS: High levels of immune cells and immune checkpoint proteins have a significant impact on patient survival in SBA. These data could provide an insight into the immunotherapeutic management of patients with SBA.

Technical note on the exploration of COVID-19 in autopsy material.

Interrogation of immune response in autopsy material from patients with SARS-CoV-2 is potentially significant. We aim to describe a validated protocol for the exploration of the molecular physiopathology of SARS-CoV-2 pulmonary disease using multiplex immunofluorescence (mIF).The application of validated assays for the detection of SARS-CoV-2 in tissues, originally developed in our laboratory in the context of oncology, was used to map the topography and complexity of the adaptive immune response at protein and mRNA levels.SARS-CoV-2 is detectable in situ by protein or mRNA, with a sensitivity that could be in part related to disease stage. In formalin-fixed, paraffin-embedded pneumonia material, multiplex immunofluorescent panels are robust, reliable and quantifiable and can detect topographic variations in inflammation related to pathological processes.Clinical autopsies have relevance in understanding diseases of unknown/complex pathophysiology. In particular, autopsy materials are suitable for the detection of SARS-CoV-2 and for the topographic description of the complex tissue-based immune response using mIF.

Orthogonal MET analysis in a population-representative stage II-III colon cancer cohort: prognostic and potential therapeutic implications.

Clinical trials for MET inhibitors have demonstrated limited success for their use in colon cancer (CC). However, clinical efficacy may be obscured by a lack of standardisation in MET assessment for patient stratification. In this study, we aimed to determine the molecular context in which MET is deregulated in CC using a series of genomic and proteomic tests to define MET expression and identify patient subgroups that should be considered in future studies with MET-targeted agents. To this aim, orthogonal expression analysis of MET was conducted in a population-representative cohort of stage II/III CC patients (n = 240) diagnosed in Northern Ireland from 2004 to 2008. Targeted sequencing was used to determine the relative incidence of MET R970C and MET T992I mutations within the cohort. MET amplification was assessed using dual-colour dual-hapten brightfield in situ hybridisation (DDISH). Expression of transcribed MET and c-MET protein within the cohort was assessed using digital image analysis on MET RNA in situ hybridisation (ISH) and c-MET immunohistochemistry (IHC) stained slides. We found that less than 2% of the stage II/III CC patient population assessed demonstrated a genetic MET aberration. Determination of a high MET RNA-ISH/low c-MET IHC protein subgroup was found to be associated with poor 5-year cancer-specific outcomes compared to patients with concordant MET RNA-ISH and c-MET IHC protein expression (HR 2.12 [95%CI: 1.27-3.68]). The MET RNA-ISH/c-MET IHC protein biomarker paradigm identified in this study demonstrates that subtyping of MET expression may be required to identify MET-addicted malignancies in CC patients who will truly benefit from MET inhibition.

HistoClean: Open-source software for histological image pre-processing and augmentation to improve development of robust convolutional neural networks.

The growth of digital pathology over the past decade has opened new research pathways and insights in cancer prediction and prognosis. In particular, there has been a surge in deep learning and computer vision techniques to analyse digital images. Common practice in this area is to use image pre-processing and augmentation to prevent bias and overfitting, creating a more robust deep learning model. This generally requires consultation of documentation for multiple coding libraries, as well as trial and error to ensure that the techniques used on the images are appropriate. Herein we introduce HistoClean; a user-friendly, graphical user interface that brings together multiple image processing modules into one easy to use toolkit. HistoClean is an application that aims to help bridge the knowledge gap between pathologists, biomedical scientists and computer scientists by providing transparent image augmentation and pre-processing techniques which can be applied without prior coding knowledge. In this study, we utilise HistoClean to pre-process images for a simple convolutional neural network used to detect stromal maturity, improving the accuracy of the model at a tile, region of interest, and patient level. This study demonstrates how HistoClean can be used to improve a standard deep learning workflow via classical image augmentation and pre-processing techniques, even with a relatively simple convolutional neural network architecture. HistoClean is free and open-source and can be downloaded from the Github repository here: https://github.com/HistoCleanQUB/HistoClean.

The Potential of Digital Image Analysis to Determine Tumor Cell Content in Biobanked Formalin-Fixed, Paraffin-Embedded Tissue Samples.

Introduction: Best practices dictate that biobanks ensure accurate determination of tumor content before supplying formalin-fixed, paraffin-embedded (FFPE) tissue samples to researchers for nucleic acid extraction and downstream molecular testing. It is advisable that trained and competent individuals, who understand the requirements of the downstream molecular tests, perform the microscopic morphological examination. However, the special skills, time, and costs associated with these assessments can be prohibitive, especially in large case cohorts requiring extensive pathological review. Determination of tumor content reliably by digital image analysis (DIA) could represent a significant advantage if validated, utilized, and deployed by biobanks. Materials and Methods: Whole slide digital scanned images of colorectal, lung, and breast cancer specimens were created. The scanned images were imported into the DIA software QuPath and digital annotations were completed by biobank technicians, under the direction of trained histopathology senior scientists. Automated cell detection was conducted and tumor epithelial cells were classified and quantified. Results: DIA scores were highly concordant with the manual assessment for 376 of 435 samples (86%). A detailed review of discordant cases indicated digital scores had a higher accuracy than the manual estimation. Conclusion: Automated digital quantification has the potential to replace visual estimations with reduced subjectivity and increased reliability compared with manual tumor estimations. We recommend the use of DIA by biobanks involved in provision of FFPE tissue samples, especially in large research studies requiring high volumes of cases to be analyzed.

The clinical and molecular significance associated with STING signaling in breast cancer.

STING signaling in cancer is a crucial component of response to immunotherapy and other anti-cancer treatments. Currently, there is no robust method of measuring STING activation in cancer. Here, we describe an immunohistochemistry-based assay with digital pathology assessment of STING in tumor cells. Using this novel approach in estrogen receptor-positive (ER+) and ER- breast cancer, we identify perinuclear-localized expression of STING (pnSTING) in ER+ cases as an independent predictor of good prognosis, associated with immune cell infiltration and upregulation of immune checkpoints. Tumors with low pnSTING are immunosuppressed with increased infiltration of "M2"-polarized macrophages. In ER- disease, pnSTING does not appear to have a significant prognostic role with STING uncoupled from interferon responses. Importantly, a gene signature defining low pnSTING expression is predictive of poor prognosis in independent ER+ datasets. Low pnSTING is associated with chromosomal instability, MYC amplification and mTOR signaling, suggesting novel therapeutic approaches for this subgroup.

Evolutionary genetic algorithm identifies IL2RB as a potential predictive biomarker for immune-checkpoint therapy in colorectal cancer.

Identifying robust predictive biomarkers to stratify colorectal cancer (CRC) patients based on their response to immune-checkpoint therapy is an area of unmet clinical need. Our evolutionary algorithm Atlas Correlation Explorer (ACE) represents a novel approach for mining The Cancer Genome Atlas (TCGA) data for clinically relevant associations. We deployed ACE to identify candidate predictive biomarkers of response to immune-checkpoint therapy in CRC. We interrogated the colon adenocarcinoma (COAD) gene expression data across nine immune-checkpoints (PDL1, PDCD1, CTLA4, LAG3, TIM3, TIGIT, ICOS, IDO1 and BTLA). IL2RB was identified as the most common gene associated with immune-checkpoint genes in CRC. Using human/murine single-cell RNA-seq data, we demonstrated that IL2RB was expressed predominantly in a subset of T-cells associated with increased immune-checkpoint expression (P < 0.0001). Confirmatory IL2RB immunohistochemistry (IHC) analysis in a large MSI-H colon cancer tissue microarray (TMA; n = 115) revealed sensitive, specific staining of a subset of lymphocytes and a strong association with FOXP3+ lymphocytes (P < 0.0001). IL2RB mRNA positively correlated with three previously-published gene signatures of response to immune-checkpoint therapy (P < 0.0001). Our evolutionary algorithm has identified IL2RB to be extensively linked to immune-checkpoints in CRC; its expression should be investigated for clinical utility as a potential predictive biomarker for CRC patients receiving immune-checkpoint blockade.