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.

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.

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.

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 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.

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.

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 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.

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.

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.

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.

Prognostic value of PD­L1 expression and CD68 macrophages in tumor nest of patients with primary gastric cancer.

The programmed death receptor 1/programmed death receptor ligand 1 axis (PD-1/PD-L1) is involved in tumor immune escape and is a potential prognostic biomarker and anti-tumor immunotherapy target in patients with gastric cancer (GC). However, the results of studies obtained in recent years have been inconsistent. The present study aimed to determine the possible predictive significance of PD-L1 in conjunction with three proteins linked with PD-L1 regulation in patients with primary GC. In the present study, the PD-L1, human epidermal growth factor receptor 2 (HER2), cluster of differentiation (CD)133 and microphage-associated CD68 expression levels were identified by multiplexed immunohistochemistry and assessed by automated pathological analysis system in 93 GC tumors and neighboring normal tissues arrayed on the same tissue microarray. All four proteins were statistically analyzed in relation to the clinicopathological characteristics. The expression levels of HER2, CD133 and CD68 were considerably higher in cancer tissues compared with neighboring normal tissues (P<0.05), however, the reverse trend was detected for PD-L1 expression (P=0.0577), particularly in tumor nest (TN; P<0.05). There was no significant correlation between the HER2 and CD133 expression levels and clinicopathological factors. However, significant relationships were found between PD-L1 expression and the TNM stage, pathological differentiation and survival status of patients (P<0.05). Moreover, survival time was prolonged in individuals with elevated PD-L1 expression in TN and GC tissues, but no significant correlation was identified (P=0.0881). The CD68 expression level in tumor stroma, but not in TN, was significantly correlated with poor pathological differentiation in patients with GC (P<0.05). However, PD-L1+CD68+ macrophages were strongly related to lower tumor size (diameter <5 cm), early TNM stage (stage I+II), good pathological differentiation and overall survival in TN (P<0.05). In conclusion, PD-L1+CD68+ macrophage infiltration in TN might be a potential indicator of prognosis in patients with primary GC and merits further investigation.

Unique characteristics of the tumor immune microenvironment in young patients with metastatic colorectal cancer.

Introduction: Metastatic colorectal cancer (mCRC) remains a common and highly morbid disease, with a recent increase in incidence in patients younger than 50 years. There is an acute need to better understand differences in tumor biology, molecular characteristics, and other age-related differences in the tumor microenvironment (TME). Methods: 111 patients undergoing curative-intent resection of colorectal liver metastases were stratified by age into those <50 years or >65 years old, and tumors were subjected to multiplex fluorescent immunohistochemistry (mfIHC) to characterize immune infiltration and cellular engagement. Results: There was no difference in infiltration or proportion of immune cells based upon age, but the younger cohort had a higher proportion of programmed death-ligand 1 (PD-L1)+ expressing antigen presenting cells (APCs) and demonstrated decreased intercellular distance and increased cellular engagement between tumor cells (TCs) and cytotoxic T lymphocytes (CTLs), and between TCs and APCs. These trends were independent of microsatellite instability in tumors. Discussion: Age-related differences in PD-L1 expression and cellular engagement in the tumor microenvironment of patients with mCRC, findings which were unrelated to microsatellite status, suggest a more active immune microenvironment in younger patients that may offer an opportunity for therapeutic intervention with immune based therapy.

EFHD1 expression is correlated with tumor-infiltrating neutrophils and predicts prognosis in gastric cancer.

Background: Gastric cancer (GC) ranks third in terms of mortality worldwide. The tumor microenvironment is critical for the progression of gastric cancer. This study investigated the association between EF-hand domain containing 1 (EFHD1) expression and its clinical significance in the tumor microenvironment (TME) of gastric cancer. Methods: We used bioinformatic analyses to assess the relevance of EFHD1 mRNA in the TME of gastric carcinoma tissues and its relationship with clinical features. Therefore, we performed multiplex immunohistochemistry analyses to determine the potential role of the EFHD1 protein in the TME of gastric cancer. Results: EFHD1 expression increased dramatically in gastric cancer tissues compared to levels in non-cancerous tissue samples (t = 6.246, P < 0.001). The EFHD1 protein presentation was associated with invasion depth (χ2 = 19.120, P < 0.001) and TNM stages (χ2 = 14.468, P = 0.002). Notably, EFHD1 protein expression was significantly related to CD66b + neutrophil infiltration of the intratumoral (r = 0.420, P < 0.001) and stromal (r = 0.367, P < 0.001) TME in gastric cancer. Additionally, Cox regression analysis revealed that EFHD1 was an independent prognostic predictor (hazard ratio [HR] = 2.262, P < 0.001) in patients with gastric cancer. Conclusions: Our study revealed the pattern of EFHD1 overexpression in the TME of patients with gastric cancer and demonstrated its utility as a biomarker for unfavorable clinical outcomes, thereby providing a potential immunotherapy target.

An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment.

We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Specifically, the same tumor sections were stained with the expensive multiplex immunofluorescence (mIF) assay first and then restained with cheaper multiplex immunohistochemistry (mIHC). This is a first public dataset that demonstrates the equivalence of these two staining methods which in turn allows several use cases; due to the equivalence, our cheaper mIHC staining protocol can offset the need for expensive mIF staining/scanning which requires highly-skilled lab technicians. As opposed to subjective and error-prone immune cell annotations from individual pathologists (disagreement > 50%) to drive SOTA deep learning approaches, this dataset provides objective immune and tumor cell annotations via mIF/mIHC restaining for more reproducible and accurate characterization of tumor immune microenvironment (e.g. for immunotherapy). We demonstrate the effectiveness of this dataset in three use cases: (1) IHC quantification of CD3/CD8 tumor-infiltrating lymphocytes via style transfer, (2) virtual translation of cheap mIHC stains to more expensive mIF stains, and (3) virtual tumor/immune cellular phenotyping on standard hematoxylin images. The dataset is available at https://github.com/nadeemlab/DeepLIIF.

Self-supervised deep learning for highly efficient spatial immunophenotyping.

BACKGROUND: Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently needed to reveal diverse cell distribution and spatial interactions in large-scale multiplex datasets. METHODS: This study proposed Self-supervised Learning for Antigen Detection (SANDI) for accurate cell phenotyping while mitigating the annotation burden. The model first learns intrinsic pairwise similarities in unlabelled cell images, followed by a classification step to map learnt features to cell labels using a small set of annotated references. We acquired four multiplex immunohistochemistry datasets and one imaging mass cytometry dataset, comprising 2825 to 15,258 single-cell images to train and test the model. FINDINGS: With 1% annotations (18-114 cells), SANDI achieved weighted F1-scores ranging from 0.82 to 0.98 across the five datasets, which was comparable to the fully supervised classifier trained on 1828-11,459 annotated cells (-0.002 to -0.053 of averaged weighted F1-score, Wilcoxon rank-sum test, P = 0.31). Leveraging the immune checkpoint markers stained in ovarian cancer slides, SANDI-based cell identification reveals spatial expulsion between PD1-expressing T helper cells and T regulatory cells, suggesting an interplay between PD1 expression and T regulatory cell-mediated immunosuppression. INTERPRETATION: By striking a fine balance between minimal expert guidance and the power of deep learning to learn similarity within abundant data, SANDI presents new opportunities for efficient, large-scale learning for histology multiplex imaging data. FUNDING: This study was funded by the Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre.