• Breast cancer
• CD8+ T cells
• PD-1
• draining lymph nodes
• exhaustion

• CD8-Positive T-Lymphocytes/immunology
• CD8-Positive T-Lymphocytes/metabolism
• Programmed Cell Death 1 Receptor/metabolism
• Breast Neoplasms/immunology
• Breast Neoplasms/pathology
• Breast Neoplasms/mortality
• Breast Neoplasms/metabolism
• Humans
• Female
• Lymph Nodes/immunology
• Lymph Nodes/pathology
• Lymph Nodes/metabolism
• Prognosis
• Lymphocytes, Tumor-Infiltrating/immunology
• Lymphocytes, Tumor-Infiltrating/metabolism

• Breast cancer
• CXCR4
• Checkpoint inhibitor immunotherapy
• Myeloid derived suppressor cells

• Animals
• Receptors, CXCR4/antagonists & inhibitors
• Female
• Mice
• Triple Negative Breast Neoplasms/immunology
• Triple Negative Breast Neoplasms/drug therapy
• Triple Negative Breast Neoplasms/therapy
• Triple Negative Breast Neoplasms/pathology
• Immunotherapy/methods
• Humans
• Cell Line, Tumor
• Peptides, Cyclic/pharmacology
• Myeloid-Derived Suppressor Cells/immunology
• Myeloid-Derived Suppressor Cells/drug effects
• Myeloid Cells/immunology
• Myeloid Cells/drug effects
• Programmed Cell Death 1 Receptor/antagonists & inhibitors
• Programmed Cell Death 1 Receptor/immunology
• Immune Checkpoint Inhibitors/pharmacology

• R50 CA221807 NCI NIH HHS
• R01 CA238023 NCI NIH HHS
• R33CA225549 National Cancer Institute,United States
• R35GM150509 NIGMS NIH HHS
• R33 CA225549 NCI NIH HHS
• U24 CA237683 NCI NIH HHS
• U24CA237683 National Cancer Institute, United States
• R37 CA222563 NCI NIH HHS
• R50CA221807 National Cancer Institute, United States
• R01 CA238042 NCI NIH HHS
• P50 CA272218 NCI NIH HHS
• R01CA238042 NCI NIH HHS
• P30 CA047904 NCI NIH HHS
• R35 GM150509 NIGMS NIH HHS
• P50CA272218 National Cancer Institute, United States
• National Institute of General Medical Sciences
• National Cancer Institute

• PD-1+CD8+ T cells
• cancer
• disease-free survival
• overall survival
• progression-free survival

• immunosuppression
• immunotherapy
• signaling pathway
• therapeutic target
• triple negative breast cancer
• tumor microenvironment

• Humans
• Triple Negative Breast Neoplasms/immunology
• Triple Negative Breast Neoplasms/drug therapy
• Female
• Immune Checkpoint Inhibitors/therapeutic use
• Immune Checkpoint Inhibitors/pharmacology
• Tumor Microenvironment/immunology
• Tumor Microenvironment/drug effects
• Tumor Escape/drug effects
• Lymphocytes, Tumor-Infiltrating/immunology
• Lymphocytes, Tumor-Infiltrating/drug effects
• Lymphocytes, Tumor-Infiltrating/metabolism
• Animals
• Molecular Targeted Therapy

• CD8(+) T-cell exhaustion
• Cancer immunotherapy
• Triple-negative breast cancer (TNBC)
• Tumor microenvironment (TME)

• Humans
• Triple Negative Breast Neoplasms/immunology
• Triple Negative Breast Neoplasms/drug therapy
• Triple Negative Breast Neoplasms/pathology
• CD8-Positive T-Lymphocytes/immunology
• CD8-Positive T-Lymphocytes/metabolism
• Immunotherapy/methods
• Tumor Microenvironment/immunology
• Female
• Tumor Escape
• Animals
• T-Cell Exhaustion

• cancer immunotherapy
• gastrointestinal cancers
• prognostic implications
• therapeutic strategies
• tissue-resident memory T cells

• 17cm0106414h0002, JP21lm0203007, 18KK0251, 19K22658, 20H00541, 21K19526, 22H03146, 22K19559, 23K19505 and 16H06279 (PAGS) MEXT
• 2024 Princess Takamatsu Cancer Research Fund.

• Breast cancer
• Diagnostic imaging
• Immunology
• Immunotherapy
• Oncology

• Triple Negative Breast Neoplasms/diagnostic imaging
• Triple Negative Breast Neoplasms/immunology
• Triple Negative Breast Neoplasms/drug therapy
• Triple Negative Breast Neoplasms/metabolism
• Triple Negative Breast Neoplasms/therapy
• Animals
• Mice
• Female
• Cholesterol/metabolism
• Immune Checkpoint Inhibitors/therapeutic use
• Immune Checkpoint Inhibitors/pharmacology
• Humans
• Immunotherapy/methods
• Tumor Microenvironment/immunology
• Positron-Emission Tomography/methods
• T-Lymphocytes/immunology
• T-Lymphocytes/metabolism
• Cell Line, Tumor
• Lymphocyte Activation

• P30 CA046592 NCI NIH HHS
• R01 CA238042 NCI NIH HHS
• R01 CA238023 NCI NIH HHS
• R33 CA225549 NCI NIH HHS
• U24 CA237683 NCI NIH HHS
• R37 CA222563 NCI NIH HHS

• Exhausted T cells
• STING
• Tumour microenvironment
• Tumour mutation burden

• Humans
• Female
• Mutation
• Prognosis
• Breast Neoplasms/genetics
• Breast Neoplasms/therapy
• Biomarkers, Tumor/genetics
• Antigens, Neoplasm/genetics

• P30 CA033572 NCI NIH HHS
• R01 CA240392 NCI NIH HHS
• R01 CA256989 NCI NIH HHS

• multiplex IHC
• prognosis
• subtype
• triple-negative breast cancer
• tumor immune microenvironment

• Humans
• Triple Negative Breast Neoplasms/pathology
• B7-H1 Antigen
• Retrospective Studies
• Prognosis
• Tumor Microenvironment
• Biomarkers, Tumor

• 82271957 The National Natural Science Foundation of China
• 82271940 The National Natural Science Foundation of China
• 82071878 The National Natural Science Foundation of China
• 22ZR1412500 Natural Science Foundation of Shanghai
• SACA-AX202109 Shanghai Anticancer Association SOAR PROJECT
• 320.6750.2021-06-37 Wu Jieping Medical Foundation
• Natural Science Foundation of Shanghai
• Wu Jieping Medical Foundation

• biomarkers
• breast cancer
• immune checkpoint inhibitors
• immunotherapy
• liquid biopsy

• Humans
• Female
• Breast Neoplasms/diagnosis
• Breast Neoplasms/therapy
• Breast Neoplasms/pathology
• B7-H1 Antigen/metabolism
• Biomarkers, Tumor/metabolism
• Liquid Biopsy
• Immunotherapy/methods

• Basal-like breast cancer
• Canine mammary tumor subtyping
• Dog–human comparison
• Estrogen receptor
• Interferon-γ response
• Machine learning
• PAM50 subtyping
• Progesterone receptor
• Prolactin receptor
• RNA-seq
• Wnt signaling

• Humans
• Dogs
• Animals
• Female
• Breast Neoplasms/pathology
• Biomarkers, Tumor/genetics
• Receptor, ErbB-2/metabolism
• Mammary Neoplasms, Animal/genetics
• Receptors, Progesterone/metabolism

• R01 CA182093 NCI NIH HHS
• R01 CA252713 NCI NIH HHS
• UL1 TR001070 NCATS NIH HHS
• P30 CA016058 NCI NIH HHS
• National Institutes of Health

• dog-human comparison
• canine mammary tumor subtyping
• rna-seq
• basal-like breast cancer
• estrogen receptor
• progesterone receptor
• wnt signaling
• interferon-γ response
• pam50 subtyping

• P30 CA016058 NCI NIH HHS
• R01 CA182093 NCI NIH HHS
• R01 CA252713 NCI NIH HHS
• UL1 TR001070 NCATS NIH HHS

• Breast Cancer
• Caloric Restriction
• Fasting Mimicking Diet
• Myeloid-derived suppressor cells
• metastasis

• Humans
• Female
• Mice
• Animals
• Myeloid-Derived Suppressor Cells/metabolism
• Myeloid-Derived Suppressor Cells/pathology
• Triple Negative Breast Neoplasms/metabolism
• Triple Negative Breast Neoplasms/pathology
• Caloric Restriction
• Disease Models, Animal
• Cell Line, Tumor

• FI2 GM123963 NIGMS NIH HHS
• National Institute on Aging

The heterogeneity of exhausted T cells (Tex) is a critical determinant of immune checkpoint blockade therapy efficacy. However, few studies have explored exhausted T cell subpopulations in human cancers. In the present study, we examined samples from two cohorts of 175 patients with head and neck squamous cell cancer (HNSCC) by multiplex immunohistochemistry (mIHC) to investigate two subsets of Tex, CD8⁺PD1⁺TCF1⁺ progenitor exhausted T cells (TCF1⁺Tex^prog) and CD8⁺PD1⁺TCF1⁻ terminally exhausted T cells (TCF1⁻Tex^term). Moreover, fresh tumor samples from 34 patients with HNSCC were examined by flow cytometry and immunohistochemistry to further investigate their properties and cytotoxic capabilities and their correlation with regulatory T cells (Tregs) in the tumor immune microenvironment (TIME). mIHC and flow cytometry analysis showed that TCF1⁻Tex^term represented a greater proportion of CD8⁺PD1⁺Tex than TCF1⁺Tex^prog in most patients. TCF1⁺Tex^prog produced abundant TNFα, while TCF1⁻Tex^term expressed higher levels of CD103, TIM-3, CTLA-4, and TIGIT. TCF1⁻Tex^term exhibited a polyfunctional TNFα⁺GZMB⁺IFNγ⁺ phenotype; and were associated with better overall survival and recurrence-free survival. The results also indicated that larger proportions of TCF1⁻Tex^term were accompanied by an increase in the proportion of Tregs. Therefore, it was concluded that TCF1⁻Tex^term was the major CD8⁺PD1⁺Tex subset in the HNSCC TIME and that these cells favor patient survival. A high proportion of TCF1⁻Tex^term was associated with greater Treg abundance.

In the classification and typing of breast cancer, triple-negative breast cancer (TNBC) is one type of refractory breast cancer, while chemotherapy stays in the traditional treatment methods. However, the impact of chemotherapy is short-lived and may lead to recurrence due to incomplete killing of tumor cells. The occurrence, development, and relapse of breast cancer are relevant to T cell dysfunction, multiplied expression of related immune checkpoint molecules (ICIs) such as programmed death receptor 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) produce immunosuppressive effect. Immunotherapy (namely, immune checkpoint inhibitors, adoptive cellular immunotherapy, CAR-T immunotherapy and some potential treatments) provides new hope in TNBC. This review focuses on the new immune strategies of TNBC patients.

• CTLA-4
• PD1/PD-L1 pathway
• combination therapy
• immune checkpoint molecules
• immunotherapy
• triple-negative breast cancers

Stratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1^hiCD8⁺ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types.

We built a transcriptome signature of PD-1^hiCD8⁺ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined.

Signature scores could be used to identify the PD-1^hiCD8⁺ T subset and were correlated with the fraction of PD-1^hiCD8⁺ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1^hiCD8⁺ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package “PD1highCD8Tscore” (https://github.com/Liulab/PD1highCD8Tscore).

Through estimating the fraction of the PD-1^hiCD8⁺ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.

• CXCL13
• PD-1hiCD8+ T cell
• biomarker
• cancer
• immune checkpoint inhibitor

We sought to determine the clinicopathological significance of PD-1, LAG3, and TIM3 in gastric cancer (GC) by examining their expression and immune context. Immunohistochemistry (IHC) for PD-1, TIM3, LAG3, and tumor-infiltrating immune cell (TIIC) markers was performed in 385 stage II/III GCs. Epstein-Barr virus (EBV) and microsatellite stability (MSI) testing were performed for molecular classification. Chromogenic multiplex IHC (mIHC) for PD1, TIM3, LAG3, CD3, CD8, FOXP3, CD68, and cytokeratin was performed in 58 of the total samples. PD-1, LAG3, and TIM3 expression in TIICs was observed in 91 (23.6%), 193 (50.1%), and 257 (66.8%) GCs by single IHC, respectively. The expression was associated with EBV⁺ and MSI-H molecular subtypes (p ≤ 0.001). A positive expression of LAG3 in the invasive margin of the tumor was associated with better prognosis in univariate (p = .020) and multivariate (p = .026) survival analyses. The expression of different immune checkpoint receptors (ICRs) was significantly positively correlated. Dual or triple ICR expression was more frequent in high PD-1 and TIM3 density groups than in low-density groups by mIHC (all p ≤ 0.05). ICRs were mainly expressed in CD3⁺CD8⁺ and CD3⁺CD8⁻ T cells. Fifty-eight GCs were classified into three groups by clustering analysis based on mIHC, and the group with the highest ICR expression in TIICs showed significantly better outcomes in progression-free survival (p = .020). In GC, PD-1, LAG3, and TIM3 expression is positively correlated and associated with better prognosis. Our study provides information for the application of effective immune checkpoint inhibitors against GC.

• gastric cancer
• immune checkpoint receptor
• immune context
• immunohistochemistry

• tumour immunology
• breast cancer

• Single-cell transcriptome
• activated macrophages
• exhausted CD8+ T cells
• immune ecosystem
• immunosuppressive checkpoint
• triple-negative breast cancer

Recent studies in non-colorectal malignancy have associated T resident memory (T_RM) cells with improved patient survival. It is unknown if T_RM plays a role in colorectal cancer (CRC).

To examine the potential role of T_RM cells in providing immunogenicity in CRC stratified by microsatellite instability (MSI) and BRAF status.

Patients with known MSI and BRAF mutation status were eligible for inclusion in this study. CRC tumour sections stained with haematoxylin and eosin were microscopically reviewed and the images scanned prior to assessment for location of invading edge and core of tumour. Sequential sections were prepared for quantitative multiplex immunohistochemistry (IHC) staining. Opal Multiplex IHC staining was performed with appropriate positive and negative controls and imaged using a standard fluorescent microscope fitted with a spectral scanning camera (Mantra) in conjunction with Mantra snap software. Images were unmixed and annotated in inForm 2.2.0. Statistical analysis was performed using Graphpad Prism Version 7 and Stata Version 15.

Seventy-two patients with known MSI and BRAF status were included in the study. All patients were assessed for MSI by IHC and high resolution capillary electrophoresis testing and 44 of these patients successfully underwent quantitative multiplex IHC staining. Overall, there was a statistically significant increase in CD8+ T_RM cells in the MSI (BRAF mutant and wild type) group over the microsatellite stable (MSS) group. There was a statistically significant difference in CD8+ T_RM between high level MSI (MSI-H):BRAF mutant [22.57, 95% confidence interval (CI): 14.31-30.84] vs MSS [8.031 (95%CI: 4.698-11.36)], P = 0.0076 andMSI-H:BRAF wild type [16.18 (95%CI: 10.44-21.93)] vs MSS [8.031 (95%CI: 4.698-11.36)], P = 0.0279. There was no statistically significant difference in CD8 T cells (both CD8+CD103- and CD8+CD103+T_RM) between MSI-H: BRAF mutant and wild type CRC.

This study has shown that CD8+ T_RM are found in greater abundance in MSI-H CRC, both BRAF mutant and MSI-H:BRAF wild type, when compared with their MSS counterpart. CD8+ T_RM may play a role in the immunogenicity in MSI-H CRC (BRAF mutant and BRAF wild type). Further studies should focus on the potential immunogenic qualities of T_RM cells and investigate potential immunotherapeutic approaches to improve treatment and survival associated with CRC.

• Tissue resident memory cells
• Resident memory T cells
• Colorectal cancer
• Microsatellite instability
• BRAF
• DNA mismatch repair
• Immunotherapy
• Prognosis

• Humans
• Immune System
• Immunotherapy
• Lab-On-A-Chip Devices
• Neoplasms/therapy
• Tumor Microenvironment

• Drug delivery
• Immune checkpoint blockade
• Lymph nodes
• T cell priming
• Triple-negative breast cancer
• Tumor dissemination

• FRAS1-Related Extracellular Matrix 1 (FREM1)
• biomarker
• breast cancer
• immune infiltration
• prognosis

• Breast cancer
• Gynecological cancer
• Immune checkpoint inhibitors
• Immune checkpoints
• Immuno-oncology
• Immunotherapy
• Liquid biopsy

The tumor microenvironment (TME) is a complex system that plays an important role in tumor development and progression, but the current knowledge about its effect on bladder cancer (BC) is scarce. In this study, we performed a comprehensive analysis of the relationship between the TME and gene expression profiles to identify prognostic biomarkers for BC. The ESTIMATE algorithm was used to calculate immune and stromal scores of BC patients who were obtained from the Gene Expression Omnibus database. We found that the immune and stromal scores were associated with clinical characteristics and the prognosis of BC patients. Based on these scores, 104 immune-related differentially expressed genes were identified. Further, functional enrichment analysis revealed that these genes were mainly involved in the immune-related biological processes and signaling pathways. Three prognostic genes were then identified and used to establish a risk prediction model using Cox regression analyses. Kaplan–Meier survival analysis showed that the expression levels of COL1A1, COMP, and SERPINE2 significantly correlated with cancer-specific survival and overall survival of BC patients. Additionally, we validated the prognostic values of these genes using two independent cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases. Finally, the relationships between the three prognostic genes and several immune cells were evaluated using Tumor Immune Estimation Resource, indicating that the expression levels of COL1A1, COMP, and SERPINE2 correlated positively with the tumor infiltration levels of CD4⁺ T cells and macrophages. In conclusion, the current study comprehensively analyzed the TME and presented immune-related prognostic genes for BC, providing new insights into immunotherapeutic strategies for BC patients.

• bladder cancer
• cancer-specific survival
• immune score
• overall survival
• prognosis
• stromal score
• tumor microenvironment