iRhom2 deficiency reduces sepsis-induced mortality associated with the attenuation of lung macrophages in mice.

Sepsis has a high mortality rate and leads to multi-organ failure, including lung injury. Inactive rhomboid protease family protein (iRhom2) has been identified as accountable for the release of TNF-α, a crucial mediator in the development of sepsis. This study aimed to evaluate the role of iRhom2 in sepsis and sepsis-induced acute lung injury (ALI). TNF-α and IL-6 secretion in vitro by peritoneal macrophages from wild-type (WT) and iRhom2 knoukout (KO) mice was assessed by enzyme-linked immunosorbent assay. Cecal ligation and puncture (CLP)-induced murine sepsis model was used for in vivo experiments. To evaluate the role of iRhom2 deficiency on survival during sepsis, both WT and iRhom2 KO mice were monitored for 8 consecutive days following the CLP. For histologic and biochemical examination, the mice were killed 18 h after CLP. iRhom2 deficiency improved the survival of mice after CLP. iRhom2 deficiency decreased CD68+ macrophage infiltration in lung tissues. Multiplex immunohistochemistry revealed that the proportion of Ki-67+ CD68+ macrophages was significantly lower in iRhom2 KO mice than that in WT mice after CLP. Moreover, CLP-induced release of TNF-α and IL-6 in the serum were significantly inhibited by iRhom2 deficiency. iRhom2 deficiency reduced NF-kB p65 and IκBα phosphorylation after CLP. iRhom2 deficiency reduces sepsis-related mortality associated with attenuated macrophage infiltration and proliferation in early lung injury. iRhom2 may play a pivotal role in the pathogenesis of sepsis and early stage of sepsis-induced ALI. Thus, iRhom2 may be a potential therapeutic target for the management of sepsis and sepsis-induced ALI.

Exploring macrophage heterogeneity in IgA nephropathy: Mechanisms of renal impairment and current therapeutic targets.

The lack of understanding of the mechanism of renal injury in IgA nephropathy (IgAN) hinders the development of personalized treatment plans and targeted therapies. Improved insight into the cause of renal dysfunction in IgAN is necessary to enhance the effectiveness of strategies for slowing the progression of the disease. This study examined single cell RNA sequencing (scRNA seq) and bulk-RNA seq data and found that the gene expression of renal intrinsic cells (RIC) was significantly changed in patients with renal impairment, with a primary focus on energy metabolism. We discovered a clear metabolic reprogramming of RIC during renal function impairment (RF) using the 'scMetabolism' package, which manifested as a weakening of oxidative phosphorylation, alterations in fatty acid metabolism, and changes in glycolysis. Cellular communication analysis revealed that communication between macrophages (Ma) and RIC became more active and impacted cell function through the ligand-receptor-transcription factor (L-R-TF) axis in patients with RF. Our studies showed a notable upsurge in the expression of gene CLU and the infiltration of CLU+ Ma in patients with RF. CLU is a multifunctional protein, extensively involved in processes such as cell apoptosis and immune responses. Data obtained from the Nephroseq V5 database and multiplex immunohistochemistry (mIHC) were used to validate the findings, which were found to be robustly correlated with estimated glomerular filtration rate (eGFR) of the IgAN patients, as demonstrated by linear regression (LR). This study provides new insights into the cellular and molecular changes that occur in IgAN during renal impairment, revealing that elevated expression of CLU and CLU+ Ma percolation are common features in patients with RF. These findings offer potential targets and strategies for personalized management and targeted therapy of IgAN.

Multiplexed immunohistochemical analysis of the immune microenvironment of biliary tract cancers pre- & post-neoadjuvant chemotherapy: case series.

Background: Neoadjuvant chemotherapy (NACT) is increasingly being used in the management of locally advanced biliary tract cancer (BTC). The evidence suggests a contributing role of tumor infiltrating immune cells in the prognosis and response. We set out to characterize immune modulation of tumor immune microenvironment in BTC following NACT. Case Description: Patients with BTC who underwent diagnostic biopsy, then NACT then resection between 2014-2018 were identified. Multiplexed immunohistochemical consecutive staining on single slide (MICSSS) analysis was performed with a series of immune markers to characterize T-cells, immune checkpoints etc. on pre- & post-NACT tumor tissue. Density was calculated for each marker. The final analysis included five patients. Median age was 48 (range, 41-56) years, with 4 female, 4 intrahepatic cholangiocarcinoma and 1 gallbladder. All patients received gemcitabine/cisplatin as NACT (median of 5 cycles). Median time from diagnosis to surgery was 4.3 (range, 1.4-7.8) months. All patients were mismatch repair proficient (pMMR). NACT on average produced a depletion of all immune markers. Given small sample size, each patient was considered their own control and changes in mean cell densities post-NACT were calculated. Patient #2 with a 40-fold increase in PD-L1 expression & 5-fold decrease in CD8:FOXP3 ratio after NACT notably had the shortest disease-free interval (DFI). Patient #3 with the longest DFI had the largest increase in CD8:FOXP3 by about 8-fold with a decrease in PD-L1. Conclusions: Preliminary results suggest NACT may differentially modulate various compartments of the immune tumor contexture despite overall cell depletion. Future studies should focus on strategies to expand immune modulation of tumor microenvironment, including immune-oncology agents to augment the effects of chemotherapy.

Digital quantification of PRAME for distinguishing melanoma from nevi compared to manual assessment.

AIMS: In this proof-of-concept study, we propose a new method for automated digital quantification of PRAME (PReferentially expressed Antigen of MElanoma) as a diagnostic aid to distinguish between benign and malignant melanocytic lesions. The proposed method utilizes immunohistochemical virtual double nuclear staining for PRAME and SOX10 to precisely identify the melanocytic cells of interest, which is combined with digital image analyse to quantify a PRAME-index. METHODS: Our study included 10 compound nevi, 3 halo nevi, and 10 melanomas. Tissue slides were stained with PRAME, scanned, the cover glass removed, stained with SOX10, scanned again, and finally analysed digitally. The digitally quantified PRAME-index was compared with a manual qualitative assessment by a dermatopathologist using the standard PRAME-scoring system. RESULTS: The digitally quantified PRAME-index showed a sensitivity of 70 % and a specificity of 100 % for separating melanomas from benign lesions. The manual qualitative PRAME-score showed a sensitivity of 60 % and a specificity of 100 %. Comparing the two methods using ROC-analyses, our digital quantitative method (AUC: 0.931, 95 % CI: 0.834;1.00, SD: 0.050) remains on par with the manual qualitative method (AUC: 0.877, 95 % CI: 0.725;1.00, SD: 0.078). CONCLUSION: We found our novel digital quantitative method was at least as precise at classifying lesions as benign or malignant as the current manual qualitative assessment. Our method has the advantages of being operator-independent, objective, and replicable. Furthermore, our method can easily be implemented in an already digitalized pathology department. Given the small cohort size, more studies are to be done to validate our findings.

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes for patients. The clinical challenge lies in identifying those patients at the highest risk of developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathological, histological, or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality in OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Biomarkers such as S100A7 demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Spatial distribution pattern of immune cells is associated with patient prognosis in colorectal cancer.

BACKGROUND: The spatial context of tumor-infiltrating immune cells (TIICs) is important in predicting colorectal cancer (CRC) patients' clinical outcomes. However, the prognostic value of the TIIC spatial distribution is unknown. Thus, we aimed to investigate the association between TIICs in situ and patient prognosis in a large CRC sample. METHODS: We implemented multiplex immunohistochemistry staining technology in 190 CRC samples to quantify 14 TIIC subgroups in situ. To delineate the spatial relationship of TIICs to tumor cells, tissue slides were segmented into tumor cell and microenvironment compartments based on image recognition technology, and the distance between immune and tumor cells was calculated by implementing the computational pipeline phenoptr. RESULTS: MPO+ neutrophils and CD68+IDO1+ tumor-associated macrophages (TAMs) were enriched in the epithelial compartment, and myeloid lineage cells were located nearest to tumor cells. Except for CD68+CD163+ TAMs, other cells were all positively associated with favorable prognosis. The prognostic predictive power of TIICs was highly related to their distance to tumor cells. Unsupervised clustering analysis divided colorectal cancer into three subtypes with distinct prognostic outcomes, and correlation analysis revealed the synergy among B cells, CD68+IDO1+TAMs, and T lineage cells in producing an effective immune response. CONCLUSIONS: Our study suggests that the integration of spatial localization with TIIC abundance is important for comprehensive prognostic assessment.

NIR-II light therapy improves cognitive performance in MPTP induced Parkinson's disease rat models: A preliminary experimental study.

Cognitive impairment is an important component of non motor symptoms in Parkinson's disease (PD), and if not addressed in a timely manner, it can easily progress to dementia. However, no effective method currently exists to completely prevent or reverse cognitive impairment associated with PD. We therefore aimed to investigate the therapeutic effect of near-infrared region II light (NIR-II) region illumination on cognitive impairment in PD through behavioral experiments (water maze and rotary rod) and multiple fluorescence immunohistochemistry techniques. The 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP)-induced group was compared with the MPTP- untreated rat group, showing a significant reduction in escape latency and significant increase in the fall latency in the MPTP-treated group. The horizontal analysis results indicated that NIR-II phototherapy improved the learning and cognitive abilities as well as coordination and balance abilities of rats. Post-treatment, the MPTP rats showed significantly shortened, escape latency, prolonged target quadrant residence time, and prolonged fall latency compared with pre-treatment. The longitudinal analysis results reaffirmed that NIR-II phototherapy improved the learning and cognitive abilities as well as coordination and balance abilities of rats. The multiple fluorescence immunohistochemistry analysis trend plot showed that the activated microglia and astrocytes in the hippocampus were highest in MPTP-induced PD untreated group, moderate in MPTP-induced PD treatment group, and lowest in the control group. Our data indicates that NIR-II illumination improves learning and cognitive impairment as well as coordination and balance abilities in PD rats by downregulating the activation of microglia and astrocytes in the hippocampus.

The Comprehensive Characterization of B7-H3 Expression in the Tumor Microenvironment of Lung Squamous Cell Carcinoma: A Retrospective Study.

Lung squamous cell carcinoma (LSCC) is refractory to various therapies for non-small cell cancer; therefore, new therapeutic approaches are required to improve the prognosis of LSCC. Although immunotherapies targeting B7 family molecules were explored as treatments for several cancer types, the expression and significance of B7-H3 in the tumor microenvironment (TME) and its relationship with other immune checkpoint molecules have not yet been investigated in detail. We used high-throughput quantitative multiplex immunohistochemistry to examine B7-H3 expression in the TME. We investigated the relationship between B7-H3 expression and prognosis as well as changes in the TME with B7-H3 expression using 110 surgically resected pathological specimens retrospectively. We examined the correlation between B7-H3 and programmed cell death-ligand 1 (PD-L1) expression in single cells. High B7-H3 expression in tumor cells was associated with a better prognosis and a significant increase in the number of CD163+PD-L1+ macrophages. Quantitative analysis revealed that there is a positive correlation between B7-H3 and PD-L1 expression in tumor and stromal cells, as well as in intratumoral tumor-infiltrating lymphocytes and tumor-associated macrophages in the same cells. CD68+, CD163+, and CK+ cells with PD-L1+ phenotypes had higher B7-H3 expression compared to PD-L1- cells. Our findings demonstrate a correlation between B7-H3 and PD-L1 expression in the same cells, indicating that therapies targeting B7-H3 could provide additional efficacy in patients refractory to PD-L1-targeting therapies.

A novel risk scoring system predicts overall survival of hepatocellular carcinoma using cox proportional hazards machine learning method.

BACKGROUND: Robust and practical prognosis prediction models for hepatocellular carcinoma (HCC) patients play crucial roles in personalized precision medicine. MATERIAL AND METHODS: We recruited two independent HCC cohorts (discovery cohort and validation cohort), totally consisting of 222 HCC patients undergone surgical resection. We quantified the expressions of immune-related proteins (CD8, CD68, CD163, PD-1 and PD-L1) in paired HCC tissues and non-tumor liver tissues from these HCC patients using immunohistochemistry (mIHC) assays. We constructed the HCC prognosis prediction model using five different machine learning methods based on the patients in the discovery cohort, such as Cox proportional hazards (CoxPH). RESULTS: We identified 19 features that were associated with overall survival of HCC patients in the discovery cohort (p < 0.1), such as immune-related features CD68+ and CD8+ cell infiltration. We constructed five HCC prognosis prediction models using five different machine learning methods. Among the five different machine learning models, the CoxPH model achieved the best performance (area under the curve [AUC], 0.839; C-index, 0.779). According to the risk score from CoxPH model, we divided HCC patients into high-risk group/low-risk group. In both discovery cohort and validation cohort, the patients in low-risk group showed longer overall survival compared with those in high-risk group (p = 1.8 × 10-7 and 3.4 × 10-5, respectively). Moreover, our novel scoring system efficiently predicted the 6, 12, and 18 months survival rate of HCC patients with AUC >0.75 in both discovery cohort and validation cohort. In addition, we found that the scoring system could also distinguish the patients with high/low risks of relapse in both discovery cohort and validation cohort (p = 0.00015 and 0.00012). CONCLUSION: The novel CoxPH-based risk scoring model on clinical, laboratory-testing and immune-related features showed high prediction efficiencies for overall survival and recurrence of HCCs undergone surgical resection. Our results may be helpful to optimize clinical follow-up or therapeutic interventions.

Tumor-stroma contact ratio - a novel predictive factor for tumor response to chemoradiotherapy in locally advanced oropharyngeal cancer.

The growth pattern of oropharyngeal squamous cell carcinomas (OPSCC) varies from compact tumor cell aggregates to diffusely infiltrating tumor cell-clusters. The influence of the growth pattern on local tumor control and survival has been studied mainly for surgically treated oral cavity carcinomas on a visual basis. In this study, we used multiplex immunofluorescence staining (mIF) to examine the antigens pan-cytokeratin, p16INK4a, Ki67, CD271, PD-L1, and CD8 in pretherapeutic biopsies from 86 OPSCC. We introduce Tumor-stroma contact ratio (TSC), a novel parameter, to quantify the relationship between tumor cells in contact with the stromal surface and the total number of epithelial tumor cells. mIF tumor cores were analyzed at the single-cell level, and tumor-stromal contact area was quantified using the R package "Spatstat". TSC was correlated with the visually assessed invasion pattern by two independent investigators. Furthermore, TSC was analyzed in relation to clinical parameters and patient survival data to evaluate its potential prognostic significance. Higher TSC correlated with poor response to (chemo-)radiotherapy (r = 0.3, p < 0.01), and shorter overall (OS) and progression-free (PFS) survival (median OS: 13 vs 136 months, p < 0.0001; median PFS: 5 vs 85 months, p < 0.0001). Visual categorization of growth pattern according to established criteria of tumor aggressiveness showed interobserver variability increasing with more nuanced categories (2 categories: k = 0.7, 95 %-CI: 0.55 - 0.85; 4 categories k = 0.48, 95 %-CI: 0.35 - 0.61). In conclusion, TSC is an objective and reproducible computer-based parameter to quantify tumor-stroma contact area. We demonstrate its relevance for the response of oropharyngeal carcinomas to primary (chemo-)radiotherapy.

A Multiplexed Approach to Assess Small Cell Lung Cancer Subtype Heterogeneity in Primary and Patient-Derived Tumor Samples.

Unlocking the heterogeneity of cancers is crucial for developing therapeutic approaches that effectively eradicate disease. As our understanding of markers specific to cancer subclones or subtypes expands, there is a growing demand for advanced technologies that enable the simultaneous investigation of multiple targets within an individual tumor sample. Indeed, multiplex approaches offer distinct benefits, particularly when tumor specimens are small and scarce. Here we describe the utility of two fluorescence-based multiplex approaches; fluorescent Western blots, and multiplex immunohistochemistry (Opal™) staining to interrogate heterogeneity, using small cell lung cancer as an example. Critically, the coupling of Opal™ staining with advanced image quantitation, permits the dissection of cancer cell phenotypes at a single cell level. These approaches can be applied to patient biopsies and/or patient-derived xenograft (PDX) models and serve as powerful methodologies for assessing tumor cell heterogeneity in response to therapy or between metastatic lesions across diverse tissue sites.

Nucleic acid-sensing-related gene signature in predicting prognosis and treatment efficiency of small cell lung cancer patients.

Introduction: Nucleic acid-sensing (NAS) pathways could induce innate and adaptive immune responses. However, rare evidence exhibited how the core genes of the NAS pathways affected the immune response and prognosis of small cell lung cancer (SCLC) patients. Methods: We conducted a comprehensive bioinformatic analysis based on the RNA profiles of 114 SCLC patients, including 79 from cBioPortal, 21 from GSE30219, and 14 from our sequencing data. The multiplex immunohistochemistry (mIHC) was used to characterize the role of NAS related genes in the tumor microenvironment (TME) of SCLC. Results: A prognostic model (7NAS risk model) was constructed based on 7 NAS-related genes which was demonstrated as an independent prognostic index. The low-risk group was identified to have a better prognosis and an immune-activated microenvironment in both the public datasets and our dataset. Intriguingly, mIHC data showed that CD45+ immune cells, CD8+ T lymphocytes, and CD68+ macrophages were prevalently enriched in low-risk SCLC patients and positively correlated with IRF1 expression. Additionally, Patients in the low-risk group might have superior responses to chemotherapy and immunotherapy. Conclusion: Conclusively, this study created a new risk model based on genes associated with NAS pathways which could predict the prognosis and response of treatment in patients with SCLC.

Association between ascites Gustave Roussy immune score and the intratumoural microbiome in malignant ascites secondary to hepatocellular carcinoma.

BACKGROUNDS: The Gustave Roussy Immune (GRIm) score predicts survival outcomes in several cancers. However, the prognostic significance of the GRIm score in patients with malignant ascites has not yet been investigated. METHODS: Clinical samples were collected from a cohort of patients with malignant ascites secondary to hepatocellular carcinoma (HCC). We calculated serum GRIm (sGRIm) and ascites GRIm (aGRIm) scores and divided the samples into low and high GRIm score groups. Survival analysis was used to compare the prognostic significance of the sGRIm and aGRIm scores. 16S rRNA sequencing was performed to determine the profiles of the intratumoral microbiota in the groups. A fluorescent multiplex immunohistochemistry (mIHC) assay was used to detect the expression of different immune cells by labeling seven markers of malignant ascites. RESULTS: 155 patients with HCC and malignant ascites were enrolled in this study. Survival analysis revealed that the aGRIm score showed a superior prognostic significance compared to the sGRIm score. Microbial analysis demonstrated that the bacterial richness and diversity were higher in the low aGRIm score group than in the high aGRIm score group. LefSe analysis revealed that certain bacteria were correlated with high aGRIm scores. Fluorescent mIHC displayed the tumor microenvironment of malignant ascites and found that the density of CD8 + T cells was significantly higher in the low aGRIm score group than in the high aGRIm score group. CONCLUSIONS: Our present study identified a novel scoring system (aGRIm score) that can predict the survival outcome of patients with malignant ascites secondary to HCC.

Association of preoperative aspartate aminotransferase to platelet ratio index with outcomes and tumour microenvironment among colorectal cancer with liver metastases.

This study aims to investigate applicable robust biomarkers that can improve prognostic predictions for colorectal liver metastasis (CRLM) patients receiving simultaneous resection. A total of 1323 CRLM patients from multiple centres were included. The preoperative aspartate aminotransferase to platelet ratio index (APRI) level from blood of patients were obtained. Patients were stratified into a high APRI group and a low APRI group, and comparisons were conducted by analyzing progression-free survival (PFS), overall survival (OS) and postoperative early recurrence. Tumour samples of CRLM were collected to perform single-cell RNA sequencing and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) to investigate the association of APRI levels and the tumour microenvironment of CRLM. Compared with APRI <0.33, PFS disadvantage (IPTW-adjusted HR = 1.240, P = 0.015) and OS disadvantage (IPTW- adjusted HR = 1.507, P = 0.002) of APRI ≥0.33 were preserved in the IPTW-adjusted Cox hazards regression analyses. An APRI ≥0.25 was associated with a significantly increased risk of postoperative early recurrence after adjustment (IPTW-adjusted OR = 1.486, P = 0.001). The external validation showed consistent results with the training cohort. In the high APRI group, the single-cell RNA sequencing results revealed a heightened malignancy of epithelial cells, the enrichment of inflammatory-like cancer-associated fibroblasts and SPP1+ macrophages associated with activation of malignant cells and fibrotic microenvironment, and a more suppressed-function T cells; mIHC/IF showed that PD1+ CD4+ T cells, FOXP3+ CD4+ T cells, PD1+ CD8+ T cells, FOXP3+ CD8+ T cells, SPP1+ macrophages and iCAFs were significantly increased in the intratumoral region and peritumoral region. This study contributed valuable evidence regarding preoperative APRI for predicting prognoses among CRLM patients receiving simultaneous resection and provided underlying clues supporting the association between APRI and clinical outcomes by single-cell sequencing bioinformatics analysis and mIHC/IF.

Immunohistochemical double nuclear staining for cell-specific automated quantification of the proliferation index - A promising diagnostic aid for melanocytic lesions.

AIMS: Pathologists often use immunohistochemical staining of the proliferation marker Ki67 in their diagnostic assessment of melanocytic lesions. However, the interpretation of Ki67 can be challenging. We propose a new workflow to improve the diagnostic utility of the Ki67-index. In this workflow, Ki67 is combined with the melanocytic tumour-cell marker SOX10 in a Ki67/SOX10 double nuclear stain. The Ki67-index is then quantified automatically using digital image analysis (DIA). The aim of this study was to optimise and test three different multiplexing methods for Ki67/SOX10 double nuclear staining. METHODS: Multiplex immunofluorescence (mIF), multiplex immunohistochemistry (mIHC), and multiplexed immunohistochemical consecutive staining on single slide (MICSSS) were optimised for Ki67/SOX10 double nuclear staining. DIA applications were designed for automated quantification of the Ki67-index. The methods were tested on a pilot case-control cohort of benign and malignant melanocytic lesions (n = 23). RESULTS: Using the Ki67/SOX10 double nuclear stain, malignant melanocytic lesions could be completely distinguished from benign lesions by the Ki67-index. The Ki67-index cut-offs were 1.8% (mIF) and 1.5% (mIHC and MICSSS). The AUC of the automatically quantified Ki67-index based on double nuclear staining was 1.0 (95% CI: 1.0;1.0), whereas the AUC of conventional Ki67 single-stains was 0.87 (95% CI: 0.71;1.00). CONCLUSIONS: The novel Ki67/SOX10 double nuclear stain highly improved the diagnostic precision of Ki67 interpretation. Both mIHC and mIF were useful methods for Ki67/SOX10 double nuclear staining, whereas the MICSSS method had challenges in the current setting. The Ki67/SOX10 double nuclear stain shows potential as a valuable diagnostic aid for melanocytic lesions.

Quantitative Multiplexed Analysis of Indoleamine 2,3-Dioxygenase (IDO) and Arginase-1 (ARG1) Expression and Myeloid Cell Infiltration in Colorectal Cancer.

Indoleamine 2,3-dioxygenase (IDO) and arginase-1 (ARG1) are amino acid-metabolizing enzymes, frequently highly expressed in cancer. Their expression may deplete essential amino acids, lead to immunosuppression, and promote cancer growth. Still, their expression patterns, prognostic significance, and spatial localization in the colorectal cancer microenvironment are incompletely understood. Using a custom 10-plex immunohistochemistry assay and supervised machine learning-based digital image analysis, we characterized IDO and ARG1 expression in monocytic cells, granulocytes, mast cells, and tumor cells in 833 colorectal cancer patients. We evaluated the prognostic value and spatial arrangement of IDO- and ARG1-expressing myeloid and tumor cells. IDO was mainly expressed not only by monocytic cells but also by some tumor cells, whereas ARG1 was predominantly expressed by granulocytes. Higher density of IDO+ monocytic cells was an independent prognostic factor for improved cancer-specific survival both in the tumor center (Ptrend = .0002; hazard ratio [HR] for the highest ordinal category Q4 [vs Q1], 0.51; 95% CI, 0.33-0.79) and the invasive margin (Ptrend = .0015). Higher density of granulocytes was associated with prolonged cancer-specific survival in univariable models, and higher FCGR3+ARG1+ neutrophil density in the tumor center also in multivariable analysis (Ptrend = .0020). Granulocytes were, on average, located closer to tumor cells than monocytic cells. Furthermore, IDO+ monocytic cells and ARG1- granulocytes were closer than IDO- monocytic cells and ARG1+ granulocytes, respectively. The mRNA expression of the IDO1 gene was assessed in myeloid and tumor cells using publicly available single-cell RNA sequencing data for 62 colorectal cancers. IDO1 was mainly expressed in monocytes and dendritic cells, and high IDO1 activity in monocytes was associated with enriched immunostimulatory pathways. Our findings provided in-depth information about the infiltration patterns and prognostic value of cells expressing IDO and/or ARG1 in the colorectal cancer microenvironment, highlighting the significance of host immune response in tumor progression.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry.

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Clinical Outcomes of Small Cell Carcinoma of the Genitourinary Tract and the Prognostic Significance of the Tumor Immune Microenvironment.

PURPOSE: Small cell carcinoma of the genitourinary tract (GU SCC) is a rare disease with a poor prognosis. There are only limited treatment options due to insufficient understanding of the disease. In this study, we analyzed the clinical outcomes of patients with GU SCC and their association with the tumor immune phenotype. MATERIALS AND METHODS: Patients diagnosed with GU SCC were included. Survival outcomes according to the primary location (prostate and non-prostate) and stages (limited disease [LD] and extensive disease [ED]) were analyzed. We performed multiplex immunohistochemistry (IHC) in non-prostate SCC patients and analyzed the immune cell population. RESULTS: A total of 77 patients were included in this study. Their median age was 71 years, 67 patients (87.0%) were male, and 48 patients (62.3%) had non-prostate SCC. All patients with ED (n=31, 40.3%) received etoposide plus platinum (EP) as initial treatment and median overall survival (OS) was 9.7 months (95% confidence interval [CI], 7.1 to 18.6). Patients with LD (n=46, 59.7%) received EP followed by radiotherapy or surgery, and 24-months OS rate was 63.6% (95% CI, 49.9 to 81.0). The multiplex IHC analysis of 21 patients with non-prostate SCC showed that patients with a higher density of programmed death-ligand 1-expressing CD68+CD206+ M2-like macrophages had significantly worse OS outcomes with an adjusted hazards ratio of 4.17 (95% CI, 1.25 to 14.29; adjusted p=0.02). CONCLUSION: Patients with GU SCC had a poor prognosis, even those with localized disease. The tumor immune phenotypes were significantly associated with survival. This finding provides new insights for treating GU SCC.

High-Throughput Multiplex Immunohistochemistry of Glioma Organoids.

The invasive capacity and progression of glioblastoma cells and neoplastic cells in other are dependent on interactions with the surrounding tumor microenvironment. In particular, cancer cells form a reciprocal relationship with noncellular dysregulated extracellular matrix in the tumors. Here, we describe a protocol that can be used to model the functional relationship between tumor cells and extracellular matrix. We demonstrate how 3D organoids, including glioma tumor organoids, can be processed, embedded, and sectioned in a high-throughput setup that enables investigation of the organoids by histopathological methods, multiplex immunohistochemistry, and spatial analysis within the same section.