Spatial and Compositional Biomarkers in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options, which warrants identification of novel therapeutic targets. Deciphering nuances in the tumor microenvironment (TME) may unveil insightful links between anti-tumor immunity and clinical outcomes, yet such connections remain underexplored. Here we employed a dataset derived from imaging mass cytometry of 58 TNBC patient specimens at single-cell resolution and performed in-depth quantifications with a suite of multi-scale computational algorithms. We detected distinct cell distribution patterns among clinical subgroups, potentially stemming from different infiltration related to tumor vasculature and fibroblast heterogeneity. Spatial analysis also identified ten recurrent cellular neighborhoods (CNs) - a collection of local TME characteristics with unique cell components. Coupling of the prevalence of pan-immune and perivasculature immune hotspot CNs, enrichment of inter-CN interactions was associated with improved survival. Using a deep learning model trained on engineered spatial data, we can with high accuracy (mean AUC of 5-fold cross-validation = 0.71) how a separate cohort of patients in the NeoTRIP clinical trial will respond to treatment based on baseline TME features. These data reinforce that the TME architecture is structured in cellular compositions, spatial organizations, vasculature biology, and molecular profiles, and suggest novel imaging-based biomarkers for treatment development in the context of TNBC.

Clinical importance of high-mannose, fucosylated, and complex N-glycans in breast cancer metastasis.

BACKGROUND: Although aberrant glycosylation is recognized as a hallmark of cancer, glycosylation in clinical breast cancer (BC) metastasis has not yet been studied. While preclinical studies show that the glycocalyx coating of cancer cells is involved in adhesion, migration, and metastasis, glycosylation changes from primary tumor (PT) to various metastatic sites remain unknown in patients. METHODS: We investigated N-glycosylation profiles in 17 metastatic BC patients from our rapid autopsy program. Primary breast tumor, lymph node metastases, multiple systemic metastases, and various normal tissue cores from each patient were arranged on unique single-patient tissue microarrays (TMAs). We performed mass spectrometry imaging (MSI) combined with extensive pathology annotation of these TMAs, and this process enabled spatially differentiated cell-based analysis of N-glycosylation patterns in metastatic BC. RESULTS: N-glycan abundance increased during metastatic progression independently of BC subtype and treatment regimen, with high-mannose glycans most frequently elevated in BC metastases, followed by fucosylated and complex glycans. Bone metastasis, however, displayed increased core-fucosylation and decreased high-mannose glycans. Consistently, N-glycosylated proteins and N-glycan biosynthesis genes were differentially expressed during metastatic BC progression, with reduced expression of mannose-trimming enzymes and with elevated EpCAM, N-glycan branching, and sialyation enzymes in BC metastases versus PT. CONCLUSION: We show in patients that N-glycosylation of breast cancer cells undergoing metastasis occurs in a metastatic site-specific manner, supporting the clinical importance of high-mannose, fucosylated, and complex N-glycans as future diagnostic markers and therapeutic targets in metastatic BC. FUNDING: NIH grants R01CA213428, R01CA213492, R01CA264901, T32CA193145, Dutch Province Limburg "LINK", European Union ERA-NET TRANSCAN2-643638.

Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in Triple-Negative Breast Cancer.

Overwhelming evidence has shown the significant role of the tumor microenvironment (TME) in governing the triple-negative breast cancer (TNBC) progression. Digital pathology can provide key information about the spatial heterogeneity within the TME using image analysis and spatial statistics. These analyses have been applied to CD8+ T cells, but quantitative analyses of other important markers and their correlations are limited. In this study, a digital pathology computational workflow is formulated for characterizing the spatial distributions of five immune markers (CD3, CD4, CD8, CD20, and FoxP3) and then the functionality is tested on whole slide images from patients with TNBC. The workflow is initiated by digital image processing to extract and colocalize immune marker-labeled cells and then convert this information to point patterns. Afterward invasive front (IF), central tumor (CT), and normal tissue (N) are characterized. For each region, we examine the intra-tumoral heterogeneity. The workflow is then repeated for all specimens to capture inter-tumoral heterogeneity. In this study, both intra- and inter-tumoral heterogeneities are observed for all five markers across all specimens. Among all regions, IF tends to have higher densities of immune cells and overall larger variations in spatial model fitting parameters and higher density in cell clusters and hotspots compared to CT and N. Results suggest a distinct role of IF in the tumor immuno-architecture. Though the sample size is limited in the study, the computational workflow could be readily reproduced and scaled due to its automatic nature. Importantly, the value of the workflow also lies in its potential to be linked to treatment outcomes and identification of predictive biomarkers for responders/non-responders, and its application to parameterization and validation of computational immuno-oncology models.

Immunohistochemical Differentiation of Plasmacytoid Urothelial Carcinoma From Secondary Carcinoma Involvement of the Bladder.

Plasmacytoid urothelial carcinoma (UC) is a rare variant of UC that can histologically mimic metastatic cancer involving the urinary bladder. A total of 45 cases of plasmacytoid UC were collected and reviewed histologically. The following immunohistochemical markers were performed: CDX2; polyclonal carcinoembryonic antigen (p-CEA); gross cystic disease fluid protein 15 (GCDFP-15); mammaglobin; estrogen receptor (ER); progesterone receptor (PR); GATA 3 and uroplakin II. In all cases, the plasmacytoid variant of UC lacked expression of ER and mammaglobin. In contrast, GCPDFP-15, PR, CDX2 and p-CEA showed positive staining in 11 (24.4%), 6 (13.3%), 8 (17.7%), and 22 (48.8%) cases, respectively. GCPDFP-15 was expressed in 4/8 female cases with 1 concurrently focally (+2) expressing PR. GATA 3 and uroplakin II was positive in 37/45 cases (82.2%) and 15/45 (33.3%) cases, respectively. A tissue microarray with 40 cases of infiltrating lobular carcinoma of the breast was stained for uroplakin II, and was negative in all cases. Tissue microarrays with 46 cases of gastric signet ring cell adenocarcinomas were all negative for GCDFP-15, ER, PR, GATA3, uroplakin II, and mammaglobin. A panel of stains including mammaglobin, ER, and uroplakin II is recommended to exclude metastatic lobular breast carcinoma to the bladder in cases where a conventional UC component is not present. Immunohistochemistry for CDX2 and p-CEA cannot be utilized to differentiate signet ring cell adenocarcinoma of the gastrointestinal tract from plasmacytoid UC; GATA3 or uroplakin II immunoreactivity can rule out a gastric primary given their negativity in signet ring cell adenocarcinoma of the stomach.

Peripheral Nerve Sheath Tumors.

This article presents an overview of the diagnostic categories of benign and malignant nerve sheath tumors, including neuroma, neurofibroma, nerve sheath myxoma, perineurioma, schwannoma, and malignant peripheral nerve sheath tumor. The discussion emphasizes histologic patterns; ancillary studies, such as immunohistochemistry; and differential diagnoses. The information is of value to practicing pathologists in both community and academic settings.