Digital image analysis in pathologist-selected regions of interest predicts survival more accurately than whole-slide analysis: a direct comparison study in 153 gastric carcinomas

Histopathological analysis of tumor microenvironment in adrenocortical carcinoma: Possible effects of in situ disorganized glucocorticoid production on tumor immunity

Adrenocortical carcinoma (ACC) patients with glucocorticoid excess have been reported to be associated with decreased tumor-infiltrating immune cells, but the effects of in situ glucocorticoid production on tumor immunity have remained unknown. In addition, ACC was also known to harbor marked intra-tumoral heterogeneity of steroidogenesis or disorganized steroidogenesis. Therefore, in this study, we immune-profiled tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs) and pivotal steroidogenic enzymes of glucocorticoid biosynthesis (CYP17A and CYP11B1) to explore the potential effects of in situ glucocorticoid production and intra-tumoral heterogeneity/disorganized steroidogenesis on tumor immunity of ACC. We also studied the correlations of the status of tumor immunity with that of angiogenesis and tumor grade to further explore the tumor tissue microenvironment of ACC. TILs (CD3, CD4, CD8, and FOXP3), TAMs (CD68 and CD163), key steroidogenic enzymes of glucocorticoid (CYP17A and CYP11B1), angiogenesis (CD31 and vasohibin-1 (VASH-1)), tumor grade (Ki-67 and Weiss score) were immunohistochemically evaluated in 34 ACCs. Increased CYP17A immunoreactivity in the whole tumor area was significantly positively correlated with FOXP3-positive TILs (p = 0.021) and negatively with CD4/CD3 ratio (p = 0.001). Increased CYP11B1 immunoreactivity in the whole tumor area was significantly positively correlated with CD8/CD3 (p = 0.039) and CD163/CD68 ratios (p = 0.006) and negatively with CD4-positive TILs (p = 0.036) and CD4/CD3 ratio (p = 0.001). There were also significant positive correlations between CYP17A and CD8 (r = 0.334, p < 0.001) and FOXP3-positive TILs (r = 0.414, p < 0.001), CD8/CD3 ratio (r = 0.421, p < 0.001), and CD68-positive TAMs (r = 0.298, p < 0.001) in randomly selected areas. Significant positive correlations were also detected between CYP11B1 and CD8/CD3 ratio (r = 0.276, p = 0.001) and negative ones detected between CYP11B1 and CD3- (r = -0.259, p = 0.002) and CD4-positive TILs (r = -0.312, p < 0.001) in those areas above. Increased micro-vessel density (MVD) -VASH-1 was significantly positively correlated with CD68- (p = 0.015) and CD163-positive TAMs (p = 0.009) and CD163/CD68 ratio and the high VASH-1 with CD163-positive TAMs (p = 0.042). Ki-67 labeling index was significantly positively correlated with MAD-VASH-1 (p = 0.006) and VASH-1 (p = 0.006) status. Results of our present study indicated that in situ glucocorticoid production did influence the status of tumor immunity in ACC. In particular, increased levels of CYP17A and CYP11B1, both involved in glucocorticoid producing immunoreactivity played different effects on tumor immunity, i.e., reflecting the involvement of intra-tumoral heterogeneity and disorganized steroidogenesis of ACC, which also did indicate the importance of in situ approaches when analyzing tumor immunity of ACC.

Closing the loop - the role of pathologists in digital and computational pathology research

An increasing number of manuscripts related to digital and computational pathology are being submitted to The Journal of Pathology: Clinical Research as part of the continuous evolution from digital imaging and algorithm-based digital pathology to computational pathology and artificial intelligence. However, despite these technological advances, tissue analysis still relies heavily on pathologists' annotations. There are three crucial elements to the pathologist's role during annotation tasks: granularity, time constraints, and responsibility for the interpretation of computational results. Granularity involves detailed annotations, including case level, regional, and cellular features; and integration of attributions from different sources. Time constraints due to pathologist shortages have led to the development of techniques to expedite annotation tasks from cell-level attributions up to so-called unsupervised learning. The impact of pathologists may seem diminished, but their role is crucial in providing ground truth and connecting pathological knowledge generation with computational advancements. Measures to display results back to pathologists and reflections about correctly applied diagnostic criteria are mandatory to maintain fidelity during human-machine interactions. Collaboration and iterative processes, such as human-in-the-loop machine learning are key for continuous improvement, ensuring the pathologist's involvement in evaluating computational results and closing the loop for clinical applicability. The journal is interested particularly in the clinical diagnostic application of computational pathology and invites submissions that address the issues raised in this editorial.

Prognostic Value of T-Cell Density in the Tumor Center and Outer Margins in Gastric Cancer

Tumor-infiltrating lymphocytes are associated with the survival of gastric cancer patients. T-cell densities in the tumor and its periphery were previously identified as prognostic T-cell markers for resectable gastric cancer. Immunohistochemistry for 5 T-cell markers, CD3, CD45RO, CD8, FOXP3, and granzyme B was performed on serial sections of N = 251 surgical resection specimens of patients treated with surgery only in the D1/D2 trial. Positive T cells were digitally quantified into tiles of 0.25 mm2 across 3 regions: the tumor center (TC), the inner invasive margin, and the outer invasive margin (OIM). A classification and regression tree model was employed to identify the optimal combination of median T-cell densities per region with cancer-specific survival (CSS) as the outcome. All statistical tests were 2-sided. CD8OIM was identified as the most dominant prognostic factor, followed by FOXP3TC, resulting in a decision tree containing 3 prognostically distinct subgroups with high (Hi) or low (Lo) density of the markers: CD8OIMHi, CD8OIMLo/FOXP3TCHi, and CD8OIMLo/FOXP3TCLo. In a multivariable Cox regression analysis, which included pathological T and N stages, Lauren histologic types, EBV status, microsatellite instability, and type of surgery, the immune subgroups were independent predictors for CSS. CSS was lower for CD8OIMLo/FOXP3TCHi (HR: 5.02; 95% CI: 2.03-12.42) and for CD8OIMLo/FOXP3TCLo (HR: 7.99; 95% CI: 3.22-19.86), compared with CD8OIMHi (P < .0001). The location and density of both CD8+ and FOXP3+ T cells in resectable gastric cancer are independently associated with survival. The combination of CD8OIM and FOXP3TC T-cell densities is a promising stratification factor that should be validated in independent studies.

Visible- and near-infrared hyperspectral imaging for the quantitative analysis of PD-L1+ cells in human lymphomas: Comparison with fluorescent multiplex immunohistochemistry

INTRODUCTION

We analyzed the expression of PD-L1 in human lymphomas using hyperspectral imaging (HSI) compared to visual assessment (VA) and conventional digital image analysis (DIA) to strengthen further the value of HSI as a tool for the evaluation of brightfield-based immunohistochemistry (IHC). In addition, fluorescent multiplex immunohistochemistry (mIHC) was used as a second detection method to analyze the impact of a different detection method.

MATERIAL AND METHODS

18 cases (6 follicular lymphomas and 12 diffuse large B-cell lymphomas) were stained for PD-L1 by IHC and for PD-L1, CD3, and CD8 by fluorescent mIHC. The percentage of positively stained cells was evaluated with VA, HSI, and DIA for IHC and VA and DIA for mIHC. Results were compared between the different methods of detection and analysis.

RESULTS

An overall high concordance was found between VA, HSI, and DIA in IHC (Cohens Kappa = 0.810^VA/HSI, 0.710 ^VA/DIA, and 0.516 ^HSI/DIA) and for VA^mIHCversus DIA^mIHC (Cohens Kappa = 0.894). Comparing IHC and mIHC general agreement differed depending on the methods compared but reached at most a moderate agreement (Coheńs Kappa between 0.250 and 0.483). This is reflected by the significantly higher percentage of PD-L1+ cells found with mIHC (p^Friedman = 0.014).

CONCLUSION

Our study shows a good concordance for the different analysis methods. Compared to VA and DIA, HSI proved to be a reliable tool for assessing IHC. Understanding the regulation of PD-L1 expression will further enlighten the role of PD-L1 as a biomarker. Therefore it is necessary to develop an instrument, such as HSI, which can offer a reliable and objective evaluation of PD-L1 expression.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Gastric Carcinomas with Stromal B7-H3 Expression Have Lower Intratumoural CD8+ T Cell Density

CD8+ T cells are the main effector cells of anti-cancer immune response that can be regulated by various costimulatory and coinhibitory molecules, including members of the B7 family. B7 homolog 3 (B7-H3) appears as a promising marker for immunotherapy; however, its significance in gastric cancer (GC) is unclear yet. We evaluated the spatial distribution of CD8+ T cells in relation to the expression of B7-H3 by double immunohistochemical staining. The level of B7-H3 intensity was scored manually (0–3) and dichotomized into B7-H3-low and B7-H3-high groups. The distribution and density of CD8+ T cells was analysed using whole slide digital imaging. B7-H3 was expressed mainly in the stromal compartment of GC (n = 73, 76% of all cases). Tumours with high expression of B7-H3 showed larger spatial differences of CD8+ T cells (86.4/mm² in tumour centre vs. 414.9/mm² in invasive front) when compared to B7-H3-low group (157.7/mm² vs. 218.7/mm², respectively) (p < 0.001). This study provides insight into the expression pattern of B7-H3 in GC of Western origin. In GCs with higher level of B7-H3 expression, CD8+ T cells were spatially suppressed in the tumour centre suggesting that B7-H3 might be involved in tumour escape mechanisms from the immune response.