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Prognostic markers in routine clinical management of breast cancer are often assessed using RNA-based multi-gene panels that depend on fluctuating tumor purity. Multiplex fluorescence immunohistochemistry (mfIHC) holds the potential for an improved risk assessment. To enable automated prognosis marker detection (i.e., progesterone receptor [PR], estrogen receptor [ER], androgen receptor [AR], GATA3, TROP2, HER2, PD-L1, Ki67, TOP2A), a framework for automated breast cancer identification was developed and validated involving thirteen different artificial intelligence analysis steps and an algorithm for cell distance analysis using 11+1-marker-BLEACH&STAIN-mfIHC staining in 1404 invasive breast cancers of no special type (NST). The framework for automated breast cancer detection discriminated normal glands from malignant glands with an accuracy of 98.4%. This approach identified that five (PR, ER, AR, GATA3, PD-L1) of nine biomarkers were associated with prolonged overall survival (p ≤ 0.0095 each) and two of these (PR, AR) were found to be independent risk factors in multivariate analysis (p ≤ 0.0151 each). The combined assessment of PR-ER-AR-GATA3-PD-L1 as a five-marker prognosis score showed strong prognostic relevance (p < 0.0001) and was an independent risk factor in multivariate analysis (p = 0.0034). Automated breast cancer detection in combination with an artificial intelligence-based analysis of mfIHC enables a rapid and reliable analysis of multiple prognostic parameters. The strict limitation of the analysis to malignant cells excludes the impact of fluctuating tumor purity on assay precision. [ABSTRACT FROM AUTHOR]

The Ki‐67 labeling index (Ki‐67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification of Ki‐67 immunostaining in 200–500 tumor cells. To enable automated Ki‐67 LI assessment in routine clinical practice, a framework for automated Ki‐67 LI quantification, which comprises three different artificial intelligence analysis steps and an algorithm for cell‐distance analysis of multiplex fluorescence immunohistochemistry (mfIHC) staining, was developed and validated in a cohort of 12,475 prostate cancers. The prognostic impact of the Ki‐67 LI was tested on a tissue microarray (TMA) containing one 0.6 mm sample per patient. A 'heterogeneity TMA' containing three to six samples from different tumor areas in each patient was used to model Ki‐67 analysis of multiple different biopsies, and 30 prostate biopsies were analyzed to compare a 'classical' bright field‐based Ki‐67 analysis with the mfIHC‐based framework. The Ki‐67 LI provided strong and independent prognostic information in 11,845 analyzed prostate cancers (p < 0.001 each), and excellent agreement was found between the framework for automated Ki‐67 LI assessment and the manual quantification in prostate biopsies from routine clinical practice (intraclass correlation coefficient: 0.94 [95% confidence interval: 0.87–0.97]). The analysis of the heterogeneity TMA revealed that the Ki‐67 LI of the sample with the highest Gleason score (area under the curve [AUC]: 0.68) was as prognostic as the mean Ki‐67 LI of all six foci (AUC: 0.71 [p = 0.24]). The combined analysis of the Ki‐67 LI and Gleason score obtained on identical tissue spots showed that the Ki‐67 LI added significant additional prognostic information in case of classical International Society of Urological Pathology grades (AUC: 0.82 [p = 0.002]) and quantitative Gleason score (AUC: 0.83 [p = 0.018]). The Ki‐67 LI is a powerful prognostic parameter in prostate cancer that is now applicable in routine clinical practice. In the case of multiple cancer‐positive biopsies, the sole automated analysis of the worst biopsy was sufficient. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

BACKGROUND: Programmed death ligand 1 (PD-L1) is the target of immune checkpoint inhibitor therapies in a growing number of tumor types, but a unanimous picture on PD-L1 expression across cancer types is lacking. MATERIALS AND METHODS: We analyzed immunohistochemical PD-L1 expression in 11,838 samples from 118 human tumor types and its relationship with tumor infiltrating CD8 positive lymphocytes. RESULTS: At a cut-off level of 10% positive tumor cells, PD-L1 positivity was seen in 85 of 118 (72%) tumor types, including thymoma (100% positive), Hodgkin's lymphoma (93%), anaplastic thyroid carcinoma (76%), Kaposi sarcoma (71%), sarcomatoid urothelial carcinoma (71%), and squamous cell carcinoma of the penis (67%), cervix (65%), floor of the mouth (61%), the lung (53%), and pharynx (50%). In immune cells, PD-L1 positivity was detectable in 103 (87%) tumor types, including tumors of haematopoetic and lymphoid tissues (75% to 100%), Warthin tumors of the parotid glands (95%) and Merkel cell carcinoma (82%). PD-L1 positivity in tumor cells was significantly correlated with the number of intratumoral CD8 positive lymphocytes across all tumor types as well as in individual tumor types, including serous carcinoma of the ovary, invasive breast carcinoma of no special type, intestinal gastric adenocarcinoma, and liposarcoma (p < 0.0001 each). CONCLUSIONS: PD-L1 expression in tumor and inflammatory cells is found in a wide range of human tumor types. Higher rates of tumor infiltrating CD8 positive lymphocytes in PD-L1 positive than in PD-L1 negative cancers suggest that the antitumor immune response may trigger tumoral PD-L1 expression. [ABSTRACT FROM AUTHOR]

Simple Summary: Quantification of tumor infiltrating lymphocytes (TILs) in the cancer microenvironment has become of increasing interest in immuno-oncology and has been therefore studied extensively in all "high prevalence" cancer entities. However, only little is known about TILs infiltration in rare cancer entities, such as vulvar cancer. Here, we have studied an exceptional large multicenter cohort of 530 vulvar squamous cell cancer specimens using immunohistochemistry. The study was conducted using large tissue section to quantitate the CD3+/CD8+ T-cell density along the invasive margin compared to the center of the tumor. The CD3+ T-cell density at the invasive margin showed the strongest prognostic value. Moreover, analysing the interplay between both T-cell densities—at different locations—enabled us to identify three major immune phenotypes that showed strong prognostic relevance. Accordingly, the sole analysis of CD3+ T-cells at the invasive margin—rather than a cumbersome immune score—predicts patient's outcome in vulvar cancer. Background: Although quantification of tumor infiltrating lymphocytes (TILs) has become of increasing interest in immuno-oncology, only little is known about TILs infiltration in the tumor microenvironment and its predictive value in vulvar cancer. Methods: Immunohistochemistry and automated digital image analysis was applied to measure the densities of CD3+ (DAKO, #IR503) and CD8+ (DAKO, #IR623) TILs at the invasive margin and in the center of 530 vulvar squamous cell cancers. Results: An elevated density of CD3+ T-cell at the invasive margin was significantly associated with low tumor stage (p = 0.0012) and prolonged survival (overall survival [OS] p = 0.0027, progression free survival [PFS] p = 0.024) and was independent from tumor stage, nodal stage, grade, and HPV-status in multivariate analysis (p < 0.05). The prognostic impact of CD3+ cells in the center of the tumor was weaker compared to the invasive margin (OS p = 0.046, PFS p = 0.031) and lacking for CD8+ T-cell densities at any location (p ≥ 0.14 each). Unsupervised clustering of CD3+ and CD8+ T-cell densities identified three major subgroups corresponding to the immune desert (137 patients), immune excluded (220 patients) and immune inflamed phenotypes (133 patients). Survival analysis revealed a particular poor prognosis for the immune desert phenotype for OS (p = 0.0071) and PFS (p = 0.0027). Conclusion: Our data demonstrate a high prognostic value of CD3+ T-cells at the invasive margin and immune phenotypes in vulvar squamous cell cancer. [ABSTRACT FROM AUTHOR]