Validation of a whole slide image management system for metabolic-associated steatohepatitis for clinical trials.

The gold standard for enrollment and endpoint assessment in metabolic dysfunction-associated steatosis clinical trials is histologic assessment of a liver biopsy performed on glass slides. However, obtaining the evaluations from several expert pathologists on glass is challenging, as shipping the slides around the country or around the world is time-consuming and comes with the hazards of slide breakage. This study demonstrated that pathologic assessment of disease activity in steatohepatitis, performed using digital images on the AISight whole slide image management system, yields results that are comparable to those obtained using glass slides. The accuracy of scoring for steatohepatitis (nonalcoholic fatty liver disease activity score ≥4 with ≥1 for each feature and absence of atypical features suggestive of other liver disease) performed on the system was evaluated against scoring conducted on glass slides. Both methods were assessed for overall percent agreement with a consensus "ground truth" score (defined as the median score of a panel of three pathologists' glass slides). Each case was also read by three different pathologists, once on glass and once digitally with a minimum 2-week washout period between the modalities. It was demonstrated that the average agreement across three pathologists of digital scoring with ground truth was noninferior to the average agreement of glass scoring with ground truth [noninferiority margin: -0.05; difference: -0.001; 95% CI: (-0.027, 0.026); and p < 0.0001]. For each pathologist, there was a similar average agreement of digital and glass reads with glass ground truth (pathologist A, 0.843 and 0.849; pathologist B, 0.633 and 0.605; and pathologist C, 0.755 and 0.780). Here, we demonstrate that the accuracy of digital reads for steatohepatitis using digital images is equivalent to glass reads in the context of a clinical trial for scoring using the Clinical Research Network scoring system.

Whole slide image features predict pathologic complete response and poor clinical outcomes in triple-negative breast cancer.

INTRODUCTION: Breast cancers are complex ecosystem like networks of malignant cells and their associated microenvironment. Applications for machine intelligence and the tumoral microenvironment are expanding frontiers in pathology. Previously, computational approaches have been developed to quantify and spatially analyze immune cells, proportionate stroma, and detect tumor budding. Little work has been done to analyze different types of tumor-associated stromata both quantitatively and computationally in relation to clinical endpoints. METHODS: We aimed to quantify stromal features from whole slide images (WSI) including stromata (myxoid, collagenous, immune) and tumoral components and combined them with traditional clinical and pathologic parameters in 120 triple-negative breast cancer (TNBC) patients treated with neoadjuvant chemotherapy (NAC) to predict pathologic complete response (pCR) and poor clinical outcomes. RESULTS: High collagenous stroma on WSI was best associated with lower rates of pCR, while combined high proportionated stroma (myxoid, collagenous, and immune) most optimally predicted worse clinical survival outcomes. When combining clinical, pathologic, and WSI features, Receiver Operator Characteristics (ROC) curves for LASSO features was up to 0.67 for pCR and 0.77 for poor outcomes. CONCLUSION: The techniques demonstrated in the present study can be performed with appropriate quality assurance. Future trials are needed to demonstrate whether coupling applications for machine intelligence, inclusive of the tumor mesenchyme, can improve outcomes prediction for patients with breast cancer.

Stromal computational signatures predict upgrade to invasive carcinoma in mass-forming DCIS: A brief report of 44 cases.

Mass-forming ductal carcinoma in situ (DCIS) detected on core needle biopsy (CNB) is often a radiology-pathology discordance and thought to represent missed invasive carcinoma. This brief report applied supervised machine learning (ML) for image segmentation to investigate a series of 44 mass-forming DCIS cases, with the primary focus being stromal computational signatures. The area under the curve (AUC) for receiver operator curves (ROC) in relation to upgrade to invasive carcinoma from DCIS were as follows: high myxoid stromal ratio (MSR): 0.923, P = <0.001; low collagenous stromal percentage (CSP): 0.875, P = <0.001; and low proportionated stromal area (PSA): 0.682, P = 0.039. The use of ML in mass-forming DCIS could predict upgraded to invasive carcinoma with high sensitivity and specificity. The findings from this brief report are clinically useful and should be further validated by future studies.

A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH.

BACKGROUND AND AIMS: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but is limited by variability in interpretation and insensitivity to change. Thus, there is a critical need for improved tools to assess liver pathology in order to risk stratify NASH patients and monitor treatment response. APPROACH AND RESULTS: Here, we describe a machine learning (ML)-based approach to liver histology assessment, which accurately characterizes disease severity and heterogeneity, and sensitively quantifies treatment response in NASH. We use samples from three randomized controlled trials to build and then validate deep convolutional neural networks to measure key histological features in NASH, including steatosis, inflammation, hepatocellular ballooning, and fibrosis. The ML-based predictions showed strong correlations with expert pathologists and were prognostic of progression to cirrhosis and liver-related clinical events. We developed a heterogeneity-sensitive metric of fibrosis response, the Deep Learning Treatment Assessment Liver Fibrosis score, which measured antifibrotic treatment effects that went undetected by manual pathological staging and was concordant with histological disease progression. CONCLUSIONS: Our ML method has shown reproducibility and sensitivity and was prognostic for disease progression, demonstrating the power of ML to advance our understanding of disease heterogeneity in NASH, risk stratify affected patients, and facilitate the development of therapies.

Anti-miRNA Oligonucleotide Therapy for Chondrosarcoma.

Chondrosarcoma is a highly aggressive primary malignant bone tumor mostly occurring in adults. There are no effective systemic treatments, and patients with this disease have poor survival. miR-181a is an oncomiR that is overexpressed in high-grade chondrosarcoma and promotes tumor progression. Regulator of G-protein signaling 16 (RGS16) is a target of miR-181a. Inhibition of RGS16 expression by miR-181a enhances CXC chemokine receptor 4 signaling, which in turn increases MMP1 and VEGF expression, angiogenesis, and metastasis. Here, we report the results of systemic treatment with anti-miRNA oligonucleotides (AMO) directed against miR-181a utilizing a nanopiece delivery platform (NPs). NPs were combined with a molecular beacon or anti-miR-181a oligonucleotides and are shown to transfect chondrosarcoma cells in vitro and in vivo Intratumoral injection and systemic delivery had similar effects on miR-181a expression in nude mice bearing chondrosarcoma xenografts. Systemic delivery of NPs carrying anti-miR-181a also restored RGS16 expression, decreased expression of VEGF and MMP1, MMP activity, and tumor volume by 32% at day 38, and prolonged survival from 23% to 45%. In conclusion, these data support that systemic delivery of AMO shows promise for chondrosarcoma treatment.

Role of immune microenvironment in gastrointestinal stromal tumours.

AIMS: The immune microenvironment is a prognostic factor for various malignancies. The significance of key players of this immune microenvironment, including tumour-infiltrating lymphocytes (TILs) and expression of programmed death-ligand 1 (PD-L1), indoleamine 2,3-dioxygenase (IDO) and tryptophanyl-tRNA synthetase (WARS) in gastrointestinal stromal tumours (GISTs) is largely unknown. METHODS AND RESULTS: Tissue microarrays were constructed from pathology files, 1996-2016. Immunohistochemistry for PD-L1, IDO and WARS was correlated with tumour size, mitoses and outcomes. TILs expressing CD3, CD4, CD8, FoxP3 and GBP5 were counted. A total of 129 GISTs were analysed. Mean patient age was 62.5 years; 52.0% were male. Tumour location included 89 stomach (69.0%), 33 small bowel (25.6%) and seven other (5.4%). Mean tumour size was 5.6 cm; mean mitoses were 7.2 per 50 high-power field. Nineteen patients (15.0%) developed disease progression, to abdominal wall (n = 8), liver (n = 6) and elsewhere (n = 5). Median progression-free survival was 56.6 months; five patients died of disease. PD-L1 was positive in 88 of 127 tumour samples (69.0%), 114 of 127 tumours were IDO-positive (89.8%) and 60 of 127 were positive for WARS (47.2%). PD-L1 was associated with increased size (P = 0.01), necrosis (P = 0.018) and mitoses (P = 0.006). Disease progression was not associated with PD-L1 (P = 0.44), IDO (P = 0.14) or WARS (P = 0.36) expression. PD-L1-positive GISTs with CD8+ or CD3+ TILs were significantly smaller than tumours with CD8+ or CD3+ TILs. CONCLUSIONS: PD-L1 expression was associated with increased size and mitoses. High CD8+ or CD3+ TIL counts were associated with decreased PD-L1/IDO+ GIST size. PD-L1 and IDO could be significant in GIST tumour biology, which invites consideration of immunotherapy as a potential treatment option.

A pilot study estimating liver fibrosis with ultrasound shear-wave elastography: does the cause of liver disease or location of measurement affect performance?

OBJECTIVE: The purpose of this study was to evaluate the diagnostic accuracy of real-time shear-wave elastography for assessment of liver fibrosis in an unselected patient population, comparing shear-wave elastography measurements obtained at and remote from the site of random liver biopsy. SUBJECTS AND METHODS: In a prospective study of 50 patients (21 with and 29 without hepatitis C) referred for clinically indicated random liver biopsy for diffuse liver disease, shear-wave elastography measurements were taken from four locations before biopsy: one at the left lobe, two at the right lobe, and one at the biopsy location. The mean, minimum, maximum, and SD of shear-wave elastography were compared with pathologic grading. Steatosis and serum markers were analyzed using multiple logistic regression. Optimized shear-wave elastography thresholds were calculated using AUC analysis. RESULTS: The AUC (95% CI) at the biopsy site, ipsilateral lobe, and contralateral lobe were 0.82 (0.63-1.0), 0.84 (0.67-1.0), and 0.59 (0.19-0.99) in hepatitis C patients; 0.89 (0.75-1.0), 0.88 (0.73-1.0), and 0.93 (0.80-1.0) in nonhepatitis C patients; and 0.85 (0.74-0.96), 0.89 (0.79-0.99), and 0.80 (0.67-0.93) in all patients, respectively. Optimized biopsy site shear-wave elastography values for detecting Metavir score F2 or greater were 1.87 m/s (75% sensitivity and specificity), 2.00 m/s (80% sensitivity and specificity), and 1.89 m/s (76% sensitivity and specificity) in hepatitis C, nonhepatitis C, and all patients, respectively. Steatosis and serum markers were not significant. CONCLUSION: Real-time shear-wave elastography accurately predicted significant fibrosis (stage ≥ 2) in an unselected patient population with diffuse disease, including patients with and without hepatitis C. Shear-wave elastography best predicts pathologic grading when taken at the biopsy site or ipsilateral lobe in hepatitis C patients. Percentage steatosis was not predictive of shear-wave elastography results.

Calretinin expression in high-grade invasive ductal carcinoma of the breast is associated with basal-like subtype and unfavorable prognosis.

Calretinin, a calcium-binding protein, is a widely used marker for mesothelial differentiation. There is accumulating evidence of calretinin expression in epithelial and mesenchymal malignancies, as well. The objectives of this study were to (1) further delineate the expression of calretinin in grade 3 breast carcinomas in the context of molecular subtypes and (2) identify the impact of calretinin expression on overall and disease-free survival. On the basis of immunohistochemical expression of estrogen receptor, progesterone receptor, human epidermal growth factor receptor-2 (HER2), cytokeratin 5/6, and epidermal growth factor receptor, 214 grade 3 invasive ductal carcinomas were stratified into 36 luminal A, 63 luminal B, 24 HER2 positive, 81 basal-like (including 13 metaplastic carcinomas), and 10 unclassified. Tissue microarrays were analyzed for immunohistochemical expression of calretinin. High-level calretinin expression was identified in a significant proportion of basal-like (54.3%), HER2 (33.3%), and unclassified (30%) tumors. In contrast, luminal A and B subtypes demonstrated high-level calretinin expression in only 11.1% and 12.7%, respectively (P < .0001). Within the basal-like group, 38.5% of the metaplastic carcinomas demonstrated high-level expression, associated predominantly with the epithelial component and squamous metaplasia. High-level calretinin expression was strongly associated with decreased overall survival in the entire cohort of grade 3 cancer (P = .0096) and in the basal-like group (P = .039). Multivariate analysis revealed that both tumor stage and high-level calretinin expression were independent predictors of overall survival (P = .0002 and P = .0023, respectively). In conclusion, high-level calretinin expression is most common in grade 3 tumors with a basal-like phenotype and is associated with poor overall survival.

Immunohistochemistry of colorectal carcinoma: current practice and evolving applications.

The relatively high incidence of adenocarcinoma of the colon and rectum (colorectal carcinoma) in the general population makes its pathologic diagnosis one of the more frequent exercises in anatomical pathology. Although typically mundane in the primary setting, the correct identification of metastatic colorectal carcinoma or exclusion of metastatic disease from carcinoma arising in other anatomical foci can be problematic. The advent of targeted therapies and refinement of more traditional cytotoxic chemotherapeutic regimens mandates not only a more confident appraisal of site of origin but also assessment of those tumor-specific features that may alter therapeutic decisions. Despite the exponential increase in our understanding of the molecular pathogenesis of colorectal carcinoma, immunohistochemistry remains the foundation for resolution of these problematic cases and the number of antibodies available to the practicing pathologist continues to expand at a steady rate. In some cases, immunohistochemistry may also provide valuable prognostic information, either independently or as a surrogate marker for a specific route of carcinogenesis such as microsatellite instability. This review will focus on the use of new and more established immunohistochemistry markers in the diagnosis of colorectal carcinoma, with an emphasis on aberrant staining patterns of the various colorectal carcinoma subtypes as well as the utility of these markers in specific differential diagnostic settings.

Application of molecular techniques in the diagnosis, prognosis and management of patients with colorectal cancer: a practical approach.

There has been an increasing role for molecular diagnostics in the diagnosis and management of cancer, and colorectal carcinoma is no exception. Recent molecular advances have elucidated 3 broad molecular subtypes of colorectal cancer, including chromosomal instability, microsatellite instability, and cytosine-phosphoguanine island methylator phenotype, which will be discussed. Also, the common syndromes associated with colorectal carcinoma will be reviewed with a focus on the differentiation between Lynch syndrome and microsatellite unstable tumors. Molecular biomarkers for predictive and prognostic markers are also becoming widely used, and due to the clinical use of monoclonal antibodies to the epidermal growth factor receptor, an emphasis is placed on that pathway.