Explore the vast range of titles available.

Tumor-associated macrophages (TAMs) and abnormalities in cancer cells affect cancer progression and response to therapy. TAMs are a major component of the tumor microenvironment (TME) in breast cancer, with their invasion affecting clinical outcomes. Programmed death-ligand 1 (PD-L1), a target of immune checkpoint inhibitors, acts as a suppressive signal for the surrounding immune system; however, its expression and effect on TAMs and the clinical outcome in breast cancer are unknown. In this study, we used high-throughput multiple immunohistochemistry to spatially and quantitatively analyze TAMs. We subjected 81 breast cancer specimens to immunostaining for CD68, CD163, PD-1, PD-L1, CD20, and pan-CK. In both stromal and intratumoral areas, the triple-negative subtype had significantly more CD68/CD163, CD68/PD-L1, and CD163/PD-L1 double-positive cells than the estrogen receptor (ER)/progesterone receptor (PR) subtype. Interestingly, a higher number of CD68+/PD-L1+/CK-/CD163- TAMs in the intratumoral area was correlated with a favorable recurrence rate (p = 0.048). These findings indicated that the specific subpopulation and localization of TAMs in the TME affect clinical outcomes in breast cancer.

BackgroundCD8+ T cells differentiate into exhausted status within tumors, including hepatocellular carcinoma (HCC), which constitutes a solid barrier to effective anti-tumor immunity. A detailed characterization of exhausted T cells and their prognostic value in HCC is lacking.MethodsWe collected fresh tumor tissues with adjacent non-tumor liver tissues and blood specimens of 56 HCC patients, as well as archived samples from two independent cohorts of HCC patients (n = 358 and n = 254), who underwent surgical resection. Flow cytometry and multiplex immunostaining were used to characterize CD8+ T cells. Patient prognosis was evaluated by Kaplan-Meier analysis and Cox regression analysis.ResultsCD8+ T cells were classified into three distinct subpopulations: PD1Hi, PD1Int and PD1−. PD1Hi CD8+ T cells were significantly enriched in tumor compared to adjacent non-tumor liver tissues. PD1Hi CD8+ T cells highly expressed exhaustion-related inhibitory receptors (TIM3, CTLA-4, etc.) and transcription factors (Eomes, BATF, etc.). In addition, PD1Hi CD8+ T cells expressed low levels of cytotoxic molecules and displayed a compromised capacity to produce pro-inflammatory cytokines while the expression of anti-inflammatory IL-10 was up-regulated following mitotic stimulation. Furthermore, PD1Hi CD8+ T cells shared features with tissue resident memory T cells and were also characterized in an aberrantly activated status with an apoptosis-prone potential. In two independent cohorts of HCC patients (n = 358 and n = 254), we demonstrated that PD1Hi or TIM3+PD1Hi CD8+ T cells were significantly correlated with poor prognosis, and the latter was positioned in close proximity to PD-L1+ tumor associated macrophages.ConclusionThe current study unveils the unique features of PD1Hi CD8+ exhausted T cells in HCC, and also suggests that exhausted T cells could act as a biomarker to select the most care-demanding patients for tailored therapies.

The World Health Organization has defined long COVID-19 (LC) as a condition that occurs in individuals with a history of SARS-CoV-2 infection who exhibit persistent symptoms after its acute phase that last for at least two months and cannot be explained by an alternative diagnosis. Since we had previously reported residual viral antigens in tissues of convalescent patients, we aimed to assess the presence of such antigens in long COVID tissues. Here, we established the presence of the residual virus in the appendix, skin, and breast tissues of 2 patients who exhibited LC symptoms 163 and 426 days after symptom onset. With multiplex immunohistochemistry, we detected viral nucleocapsid protein in all three tissues. The nucleocapsid protein was further observed to colocalize with macrophage marker CD68, suggesting that immune cells were direct targets of SARS-CoV-2. Additionally, using RNAscope, the presence of viral RNA was also detected. Our positive finding in the breast tissue is corroborated by the recent reports of immunocompromised patients experiencing LC symptoms and persistent viral replication. Overall, our findings and emerging LC studies raise the possibility that the gastrointestinal tract may function as a reservoir for SARS-CoV-2.

Background Immunotherapy has demonstrated a limited clinical efficacy in approximately 5% of cholangiocarcinoma. The main challenges for an effective immunotherapy response in cholangiocarcinoma arise from the tumor microenvironment, which is poorly understood. Methods For a comprehensive analysis of the tumor microenvironment in cholangiocarcinoma, we performed multiplex immunohistochemistry with two 15-marker immune panels and Nanostring assays for a comprehensive analysis of 104 surgically resected cholangiocarcinomas including intrahepatic, hilar, and distal cholangiocarcinoma. We also validated some key findings with a batch integration analysis of published single cell RNA sequencing data. Results This study found that natural killer cells occupy the largest immune cell compartment in cholangiocarcinoma. Granzyme-B + CD8 + effector T cells are significantly associated with better overall survival in both intrahepatic and distal cholangiocarcinoma. Above 85% of intrahepatic cholangiocarcinomas with higher density of PD-1 − EOMES − CD8 + effector T cells are associated with long-term survival. However, only the density of PD-1 − EOMES − CD8 + T cells in the tumor areas, but not in the peripheries of the tumors, is prognostic. In all three cholangiocarcinoma subtypes, T regulator cells are significantly associated with a poor prognosis; however, M1 and M2 tumor-associated macrophages or PD-L1 + tumor-associated macrophage demonstrate different prognostic values. Combining PD-L1 + M1 or M2, PD-L1 − M1 or M2 tumor-associated macrophages, and T regulator cells to subgroup intrahepatic and distal cholangiocarcinoma, the prognosis is significantly better distinguished. Moreover, PD-L1 − M2 tumor-associated macrophages is associated with a good prognosis in intrahepatic and distal cholangiocarcinoma, suggesting this subtype of M2 tumor-associated macrophages may be antitumoral. Interestingly, lower densities of various types of immunosuppressive cells are associated with decreased infiltration of effector T cells in distal and hilar cholangiocarcinoma, but not in intrahepatic cholangiocarcinoma. In intrahepatic cholangiocarcinoma, PD-L1 + tumor-associated macrophages exert their immunosuppressive function likely through promoting T cell exhaustion. Conclusions This study suggests that the densities of Granzyme-B + CD8 + effector T cells and non-exhausted PD-1 − EOMES − CD8 + T cells and the PD-L1 status in the tumor-associated macrophages are prognostic makers in cholangiocarcinomas. The study also supports targeting PD-L1 + tumor-associated macrophages as the immunotherapy for cholangiocarcinoma.

[This corrects the article DOI: 10.3389/fimmu.2022.939989.].[This corrects the article DOI: 10.3389/fimmu.2022.939989.].

The association between the tumor microenvironment (TME) and treatment response or survival has been a recent focus in several types of cancer. However, most study materials are resected specimens that were completely modified by prior chemotherapy; therefore, the unmodified host immune condition has not yet been clarified. The aim of the present study was to evaluate the relationship between TME assessed in pre–therapeutic biopsy samples and chemoresistance in esophageal cancer (EC). A total of 86 endoscopic biopsy samples from EC patients who received neoadjuvant chemotherapy (NAC) prior to surgery were evaluated for the number of intratumoral CD4+ lymphocytes (with/without Foxp3 expression), CD8+ lymphocytes (with/without PD‐1 expression), monocytes (CD14+) and macrophages (CD86+, CD163+ and CD206+) by multiplex immunohistochemistry (IHC). The number of tumor‐infiltrating CD206+ macrophages I significantly correlated with cT, cM, cStage and neutrophil/lymphocyte ratio (NLR), whereas the number of lymphocytes (including expression of Foxp3 and PD‐1) was not associated with clinico‐pathological features. The high infiltration of CD163+ or CD206+ macrophages was significantly associated with poor pathological response to NAC (P = 0.0057 and 0.0196, respectively). Expression of arginase‐1 in CD163+ macrophages tended to be higher in non–responders (29.4% vs 18.2%, P = 0.17). In addition, patients with high infiltration of M2 macrophages exhibited unfavorable overall survival compared to those without high infiltration of M2 macrophages (5‐year overall survival 57.2% vs 71.0%, P = 0.0498). Thus, a comprehensive analysis of TME using multiplex IHC revealed that M2 macrophage infiltration would be useful in predicting the response to NAC and long‐term survival in EC patients. The present study confirmed that pre–therapeutic M2 macrophage infiltration would be a useful biomarker in predicting the response to NAC and unfavorable survival among a variety of immune cells in EC patients. Our results support the possibility of using immunotherapy, targeting M2 macrophages, alongside conventional neoadjuvant chemotherapy.

Immune checkpoint blockade (ICB) is a systemic therapeutic option for advanced hepatocellular carcinoma (HCC). However, low patient response rates necessitate the development of robust predictive biomarkers that identify individuals who will benefit from ICB. A 4-gene inflammatory signature, comprising , , , and , was recently shown to be associated with a better overall response to ICB in various cancer types. Here, we examined whether tissue protein expression of CD8, PD-L1, LAG-3, and STAT1 predicts response to ICB in HCC. HCC samples from 191 Asian patients, comprising resection specimens from 124 patients (ICB-naïve) and pre-treatment specimens from 67 advanced HCC patients treated with ICB (ICB-treated), were analyzed for CD8, PD-L1, LAG-3, and STAT1 tissue expression using multiplex immunohistochemistry followed by statistical and survival analyses. Immunohistochemical and survival analyses of ICB-naïve samples showed that high LAG-3 expression was associated with shorter median progression-free survival (mPFS) and overall survival (mOS). Analysis of ICB-treated samples revealed that high proportions of LAG-3 and LAG-3 CD8 cells pre-treatment were most closely associated with longer mPFS and mOS. Using a log-likelihood model, adding the total LAG-3 cell proportion to the total CD8 cell proportion significantly increased the predictive values for mPFS and mOS, compared with the total CD8 cell proportion alone. Moreover, levels of CD8 and STAT1, but not PD-L1, were significantly correlated with better responses to ICB. After analyzing viral-related and non-viral HCC samples separately, only the LAG3 CD8 cell proportion was significantly associated with responses to ICB regardless of viral status. Immunohistochemical scoring of pre-treatment levels of LAG-3 and CD8 in the tumor microenvironment may help predict ICB benefits in HCC patients. Furthermore, immunohistochemistry-based techniques offer the advantage of being readily translatable in the clinical setting.

Background Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of uniquely colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel. Methods Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and (3) ensemble methods that employ both ColorAE and U-Net , collectively referred to as ColorAE:U-Net . We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor). Results We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect six different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net in ensemble methods outperform ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). Summary We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also utilized the ColorAE:U-Net ensemble method to analyze 3 mIHC WSIs with nearest neighbor spatial analysis. We demonstrate a proof of concept that these methods can be employed to quantitatively describe the spatial distribution of immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.

There is increasing evidence that tertiary lymphoid structures (TLS) control not only local adaptive B cell responses at melanoma tumor sites but also the cellular composition and function of other immune cells. In human melanoma, however, a comprehensive analysis of TLS phenotypes, density and spatial distribution at different disease stages is lacking. Here we used 7-color multiplex immunostaining of whole tissue sections from 103 human melanoma samples to characterize TLS phenotypes along the expression of established TLS-defining molecular and cellular components. TLS density and spatial distribution were determined by referring TLS counts to the tissue area within defined intra- and extratumoral perimeters around the invasive tumor front. We show that only a subgroup of primary human melanomas contains TLS. These TLS rarely formed germinal centers and mostly located intratumorally within 1 mm distance to the invasive tumor front. In contrast, melanoma metastases had a significantly increased density of secondary follicular TLS. They appeared preferentially in stromal areas within an extratumoral 1 mm distance to the invasive tumor front and their density varied over time and site of metastasis. Interestingly, secondary follicular TLS in melanoma often lacked BCL6 + lymphatic cells and canonical germinal center polarity with the formation of dark and light zone areas. Our work provides an integrated qualitative, quantitative and spatial analysis of TLS in human melanoma and shows disease progression- and site-associated changes in TLS phenotypes, density and spatial distribution. The frequent absence of canonical germinal center polarity in melanoma TLS highlights the induction of TLS maturation as a potential additive to future immunotherapy studies. Given the variable evaluation strategies used in previous TLS studies of human tumors, an important asset of this study is the standardized quantitative evaluation approach that provides a high degree of reproducibility.

BackgroundThyroid tissue has a special immune microenvironment that is not well characterized. Whether immune cells have a prognostic value in the recurrence of papillary thyroid cancer (PTC) needs further investigation.MethodsMultinodular non-toxic goiter (MNG) was taken as normal tissue for the difficulty in obtaining completely normal thyroid tissue (normal thyroid function, no thyroiditis, and no nodules). We compared the composition of mononuclear cells (MNCs) in peripheral blood and thyroid tissues from MNG and PTC patients by high-dimensional flow cytometry profiling and verified the results by multiplex immunohistochemistry. The recurrence rates of PTC patients with different CD8+T cell subset signatures were compared using TCGA database.ResultsWe observed that the immune cell composition of MNG was different from that in peripheral blood. Thyroid tissue contains higher percentages of T cells and NK cells. Moreover, the percentages of memory T cells and Treg cells were higher in thyroid than in peripheral blood and increased in PTC tumors. We further focused on the antitumoral CD8+T cells and found that the expression patterns of PD-1, CD39, and CD103 on CD8+T cells were different between MNG and PTC. Importantly, we found higher percentages of PD-1+CD39+CD103+CD8+T and PD-1+CD39+CD103-CD8+T cells in PTC tumor tissues from recurrent patients than non-recurrent patients. By analyzing PTC data from TCGA database, we found that the expression patterns of these molecules were associated with different pathologic types and genders among PTC patients. Moreover, patients with PD-1hiCD39loCD103hiCD8hi, PD-1hiCD39hiCD103loCD8hi, and PD-1loCD39hiCD103hiCD8hi expression patterns have a higher 10-year recurrence-free survival.ConclusionThe immune microenvironment in MNG tissue is distinct from that in peripheral blood and paratumor tissue. More memory CD8+T cells were detected in PTC, and expression patterns of PD-1, CD39, and CD103 on CD8+T cells were significantly different in physiology and gender and associated with the recurrence rate of PTC. These observations indicate that CD8+T cell signatures may be useful prognostic markers for PTC recurrence.