Identification of the novel exhausted T cell CD8 + markers in breast cancer

Sonkin, D., Thomas, A. & Teicher, B. A. Cancer treatments: Past, present, and future. Cancer Genet. 286–287, 18–24. https://doi.org/10.1016/j.cancergen.2024.06.002 (2024).Article 
CAS 
PubMed 

Google Scholar 
Siegel, R. L., Giaquinto, A. N. & Jemal, A. Cancer statistics, 2024. CA Cancer J. Clin. 74, 12–49. https://doi.org/10.3322/caac.21820 (2024).Article 
PubMed 

Google Scholar 
Xia, C. et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin. Med. J. 135, 584–590. https://doi.org/10.1097/cm9.0000000000002108 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Britt, K. L., Cuzick, J. & Phillips, K. A. Key steps for effective breast cancer prevention. Nat. Rev. Cancer 20, 417–436. https://doi.org/10.1038/s41568-020-0266-x (2020).Article 
CAS 
PubMed 

Google Scholar 
Siegel, R. L., Miller, K. D., Fuchs, H. E. & Jemal, A. Cancer statistics, 2022. CA Cancer J. Clin. 72, 7–33. https://doi.org/10.3322/caac.21708 (2022).Article 
PubMed 

Google Scholar 
Lei, X. et al. Immune cells within the tumor microenvironment: Biological functions and roles in cancer immunotherapy. Cancer Lett. 470, 126–133. https://doi.org/10.1016/j.canlet.2019.11.009 (2020).Article 
CAS 
PubMed 

Google Scholar 
Dieci, M. V., Miglietta, F. & Guarneri, V. Immune infiltrates in breast cancer: Recent updates and clinical implications. Cells https://doi.org/10.3390/cells10020223 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Robert, C. et al. Durable complete response after discontinuation of pembrolizumab in patients with metastatic melanoma. J. Clin. Oncol. 36, 1668–1674 (2018).Article 
CAS 
PubMed 

Google Scholar 
Wang, J. et al. Role of immune checkpoint inhibitor-based therapies for metastatic renal cell carcinoma in the first-line setting: A Bayesian network analysis. EBioMedicine 47, 78–88 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Vonderheide, R. H., Domchek, S. M. & Clark, A. S. Immunotherapy for breast cancer: What are we missing?. Clin. Cancer Res. 23, 2640–2646 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Emens, L. A. et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer: biomarker evaluation of the IMpassion130 study. J. Natl. Cancer Inst. 113, 1005–1016. https://doi.org/10.1093/jnci/djab004 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Loi, S. et al. Tumor-infiltrating lymphocytes and prognosis: A pooled individual patient analysis of early-stage triple-negative breast cancers. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 37, 559–569. https://doi.org/10.1200/jco.18.01010 (2019).Article 
CAS 

Google Scholar 
Kwapisz, D. Pembrolizumab and atezolizumab in triple-negative breast cancer. Cancer Immunol Immunother 70, 607–617. https://doi.org/10.1007/s00262-020-02736-z (2021).Article 
CAS 
PubMed 

Google Scholar 
Latif, F. et al. Atezolizumab and pembrolizumab in triple-negative breast cancer: A meta-analysis. Exp. Rev. Anticancer Therapy 22, 229–235. https://doi.org/10.1080/14737140.2022.2023011 (2022).Article 
CAS 

Google Scholar 
Ruffell, B. et al. Leukocyte composition of human breast cancer. Proc. Natl. Acad. Sci. USA 109, 2796–2801. https://doi.org/10.1073/pnas.1104303108 (2012).Article 
ADS 
PubMed 

Google Scholar 
König, L. et al. Dissimilar patterns of tumor-infiltrating immune cells at the invasive tumor front and tumor center are associated with response to neoadjuvant chemotherapy in primary breast cancer. BMC Cancer 19, 120. https://doi.org/10.1186/s12885-019-5320-2 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Savas, P. et al. Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis. Nat. Med. 24, 986–993. https://doi.org/10.1038/s41591-018-0078-7 (2018).Article 
CAS 
PubMed 

Google Scholar 
Byrne, A. et al. Tissue-resident memory T cells in breast cancer control and immunotherapy responses. Nat. Rev. Clin. Oncol. 17, 341–348. https://doi.org/10.1038/s41571-020-0333-y (2020).Article 
PubMed 

Google Scholar 
Zhu, Z., Jiang, L. & Ding, X. Advancing breast cancer heterogeneity analysis: insights from genomics, transcriptomics and proteomics at bulk and single-cell levels. Cancers https://doi.org/10.3390/cancers15164164 (2023).Article 
PubMed 
PubMed Central 

Google Scholar 
Yu, J., Guo, Z. & Wang, L. Progress and challenges of immunotherapy predictive biomarkers for triple negative breast cancer in the era of single-cell multi-omics. Life (Basel) https://doi.org/10.3390/life13051189 (2023).Article 
PubMed 
PubMed Central 

Google Scholar 
Nolan, E., Lindeman, G. J. & Visvader, J. E. Deciphering breast cancer: from biology to the clinic. Cell 186, 1708–1728. https://doi.org/10.1016/j.cell.2023.01.040 (2023).Article 
CAS 
PubMed 

Google Scholar 
Wang, Y. et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512, 155–160 (2014).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chung, W. et al. Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat. Commun. 8, 15081 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kim, J. J., Liang, W., Kang, C.-C., Pegram, M. D. & Herr, A. E. Single-cell immunoblotting resolves estrogen receptor-α isoforms in breast cancer. Plos one 16, e0254783 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Gerlinger, M. & Swanton, C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Br. J. Cancer 103, 1139–1143 (2010).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Satam, H. et al. Next-generation sequencing technology: Current trends and advancements. Biology (Basel) https://doi.org/10.3390/biology12070997 (2023).Article 
PubMed 

Google Scholar 
Shiovitz, S. & Korde, L. A. Genetics of breast cancer: A topic in evolution. Ann. Oncol. 26, 1291–1299 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Griseri, P. & Pagès, G. Regulation of the mRNA half-life in breast cancer. World J. Clin. Oncol. 5, 323 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Weng, J. A comprehensive bioinformatic analysis of cyclin-dependent kinase 2 (CDK2) in glioma. Gene https://doi.org/10.1016/j.gene.2022.146325 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Tao, T. Pan-cancer genetic analysis of cuproptosis and copper metabolism-related gene set. Front. Oncol. https://doi.org/10.3389/fonc.2022.952290 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. Pan-cancer profiles of the cuproptosis gene set. Am. J. Cancer Res. 12, 4074–4081 (2022).CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. Pan-cancer profiles of the cuproptosis gene set. Res. Square https://doi.org/10.21203/rs.3.rs-1716214/v1 (2022).Article 

Google Scholar 
Li, Y. & Liu, H. Clinical powers of aminoacyl tRNA synthetase complex interacting multifunctional protein 1 (AIMP1) for head-neck squamous cell carcinoma. Cancer Biomark. Sect. A Dis. Mark. https://doi.org/10.3233/cbm-210340 (2022).Article 

Google Scholar 
Li, Y., Liu, H. & Han, Y. Potential Roles of Cornichon Family AMPA Receptor Auxiliary Protein 4 (CNIH4) in Head and Neck Squamous Cell Carcinoma. Research Square (2021).Liu, H. & Tang, T. MAPK signaling pathway-based glioma subtypes, machine-learning risk model, and key hub proteins identification. Sci. Rep. 13, 19055. https://doi.org/10.1038/s41598-023-45774-0 (2023).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Tang, T. Pan-cancer genetic analysis of disulfidptosis-related gene set. Cancer Genet. 278–279, 91–103. https://doi.org/10.1016/j.cancergen.2023.10.001 (2023).Article 
CAS 
PubMed 

Google Scholar 
Liu, H. & Tang, T. A bioinformatic study of IGFBPs in glioma regarding their diagnostic, prognostic, and therapeutic prediction value. Am. J. Transl. Res. 15, 2140–2155 (2023).CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Tang, T. Pan-cancer genetic analysis of disulfidptosis-related gene set. bioRxiv, 2023.2002. 2025.529997 (2023).Hong, M. et al. RNA sequencing: New technologies and applications in cancer research. J. Hematol. Oncol. 13, 166. https://doi.org/10.1186/s13045-020-01005-x (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Li, X. & Wang, C. Y. From bulk, single-cell to spatial RNA sequencing. Int. J. Oral Sci. 13, 36. https://doi.org/10.1038/s41368-021-00146-0 (2021).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Puram, S. V. et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 171, 1611-1624.e1624. https://doi.org/10.1016/j.cell.2017.10.044 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lambrechts, D. et al. Phenotype molding of stromal cells in the lung tumor microenvironment. Nat. Med. 24, 1277–1289. https://doi.org/10.1038/s41591-018-0096-5 (2018).Article 
CAS 
PubMed 

Google Scholar 
Azizi, E. et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell 174, 1293-1308.e1236. https://doi.org/10.1016/j.cell.2018.05.060 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kim, C. et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell 173, 879-893.e813. https://doi.org/10.1016/j.cell.2018.03.041 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ali, H. R. et al. Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer. Nat. Cancer 1, 163–175. https://doi.org/10.1038/s43018-020-0026-6 (2020).Article 
CAS 
PubMed 

Google Scholar 
Wagner, J. et al. A single-cell atlas of the tumor and immune ecosystem of human breast cancer. Cell 177, 1330–1345. https://doi.org/10.1016/j.cell.2019.03.005 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, S. Q. et al. Single-cell and spatially resolved analysis uncovers cell heterogeneity of breast cancer. J. Hematol. Oncol. 15, 19. https://doi.org/10.1186/s13045-022-01236-0 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
McRitchie, B. R. & Akkaya, B. Exhaust the exhausters: Targeting regulatory T cells in the tumor microenvironment. Front. Immunol. 13, 940052. https://doi.org/10.3389/fimmu.2022.940052 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Han, Y. et al. TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment. Nucl. Acids Res. 51, D1425-d1431. https://doi.org/10.1093/nar/gkac959 (2023).Article 
PubMed 

Google Scholar 
Wang, C. et al. Integrative analyses of single-cell transcriptome and regulome using MAESTRO. Genome Biol. 21, 198. https://doi.org/10.1186/s13059-020-02116-x (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888-1902.e1821. https://doi.org/10.1016/j.cell.2019.05.031 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Xu, C. & Su, Z. Identification of cell types from single-cell transcriptomes using a novel clustering method. Bioinformatics 31, 1974–1980. https://doi.org/10.1093/bioinformatics/btv088 (2015).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Becht, E. et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat. Biotechnol. https://doi.org/10.1038/nbt.4314 (2018).Article 
PubMed 

Google Scholar 
Wu, S. Z. et al. A single-cell and spatially resolved atlas of human breast cancers. Nat. Genet. 53, 1334–1347. https://doi.org/10.1038/s41588-021-00911-1 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Qian, J. et al. A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling. Cell Res. 30, 745–762. https://doi.org/10.1038/s41422-020-0355-0 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zhang, L. et al. Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer. Cell 181, 442–459. https://doi.org/10.1016/j.cell.2020.03.048 (2020).Article 
CAS 
PubMed 

Google Scholar 
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420. https://doi.org/10.1038/nbt.4096 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Becht, E. et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat. Biotechnol. 37, 38–44 (2019).Article 
CAS 

Google Scholar 
Monti, S., Tamayo, P., Mesirov, J. & Golub, T. Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data. Mach. Learn. 52, 91–118 (2003).Article 

Google Scholar 
Liu, H. Expression and potential immune involvement of cuproptosis in kidney renal clear cell carcinoma. Cancer Genet. 274–275, 21–25. https://doi.org/10.1016/j.cancergen.2023.03.002 (2023).Article 
CAS 
PubMed 

Google Scholar 
Reich, M. et al. GenePattern 2.0. Nat. Genet. 38, 500–501. https://doi.org/10.1038/ng0506-500 (2006).Article 
CAS 
PubMed 

Google Scholar 
Li, T. et al. TIMER: A web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res. 77, e108–e110. https://doi.org/10.1158/0008-5472.Can-17-0307 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Aran, D., Hu, Z. & Butte, A. J. xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220. https://doi.org/10.1186/s13059-017-1349-1 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M. & Alizadeh, A. A. Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol. Biol. (Clifton, N.J.) 1711, 243–259. https://doi.org/10.1007/978-1-4939-7493-1_12 (2018).Article 
CAS 

Google Scholar 
Becht, E. et al. Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol. 17, 218. https://doi.org/10.1186/s13059-016-1070-5 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Finotello, F. et al. Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome Med. 11, 34. https://doi.org/10.1186/s13073-019-0638-6 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Racle, J. & Gfeller, D. EPIC: A tool to estimate the proportions of different cell types from bulk gene expression data. Methods Mol. Biol. (Clifton, N.J.) 2120, 233–248. https://doi.org/10.1007/978-1-0716-0327-7_17 (2020).Article 
CAS 

Google Scholar 
Fu, J. et al. Large-scale public data reuse to model immunotherapy response and resistance. Genome Med. 12, 21. https://doi.org/10.1186/s13073-020-0721-z (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Tibshirani, R. The lasso method for variable selection in the Cox model. Stat. Med. 16, 385–395. https://doi.org/10.1002/(sici)1097-0258(19970228)16:4%3c385::aid-sim380%3e3.0.co;2-3 (1997).Article 
CAS 
PubMed 

Google Scholar 
Chin, S. F. et al. High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer. Genome Biol. 8, R215. https://doi.org/10.1186/gb-2007-8-10-r215 (2007).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lin, C. Y. et al. Hubba: Hub objects analyzer–a framework of interactome hubs identification for network biology. Nucl. Acids Res. 36, W438-443. https://doi.org/10.1093/nar/gkn257 (2008).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Shannon, P. et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504. https://doi.org/10.1101/gr.1239303 (2003).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82. https://doi.org/10.1126/science.aaf2403 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Fan, Z., Chen, R. & Chen, X. SpatialDB: A database for spatially resolved transcriptomes. Nucl. Acids Res. 48, D233-d237. https://doi.org/10.1093/nar/gkz934 (2020).Article 
CAS 
PubMed 

Google Scholar 
Zeng, X. et al. Molecular subtyping and immune score system by a novel pyroptosis-based gene signature precisely predict immune infiltrating, survival and response to immune-checkpoint blockade in breast cancer. Cancer Genet. 276–277, 60–69. https://doi.org/10.1016/j.cancergen.2023.07.007 (2023).Article 
CAS 
PubMed 

Google Scholar 
Li, W., Wu, H. & Xu, J. Construction of a genomic instability-derived predictive prognostic signature for non-small cell lung cancer patients. Cancer Genet. 278–279, 24–37. https://doi.org/10.1016/j.cancergen.2023.07.008 (2023).Article 
CAS 
PubMed 

Google Scholar 
Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucl. Acids Res. 28, 27–30. https://doi.org/10.1093/nar/28.1.27 (2000).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kanehisa, M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. Publ. Soc. 28, 1947–1951. https://doi.org/10.1002/pro.3715 (2019).Article 
CAS 

Google Scholar 
Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M. & Ishiguro-Watanabe, M. KEGG for taxonomy-based analysis of pathways and genomes. Nucl. Acids Res. 51, D587-d592. https://doi.org/10.1093/nar/gkac963 (2023).Article 
CAS 
PubMed 

Google Scholar 
Eerola, A.-K., Soini, Y. & Pääkkö, P. A high number of tumor-infiltrating lymphocytes are associated with a small tumor size, low tumor stage, and a favorable prognosis in operated small cell lung carcinoma. Clin. Cancer Res. 6, 1875–1881 (2000).CAS 
PubMed 

Google Scholar 
Rye, I. H. et al. Breast cancer metastasis: immune profiling of lymph nodes reveals exhaustion of effector T cells and immunosuppression. Mol. Oncol. 16, 88–103 (2022).Article 
CAS 
PubMed 

Google Scholar 
Liu, H. & Weng, J. A pan-cancer bioinformatic analysis of RAD51 regarding the values for diagnosis, prognosis, and therapeutic prediction. Front. Oncol. https://doi.org/10.3389/fonc.2022.858756 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Tang, T. Pan-cancer genetic analysis of cuproptosis and copper metabolism-related gene set. Front. Oncol. 12, 952290. https://doi.org/10.3389/fonc.2022.952290 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, H. & Li, Y. Potential roles of cornichon family AMPA receptor auxiliary protein 4 (CNIH4) in head and neck squamous cell carcinoma. Cancer Biomark. Sect. A Dis. Mark. https://doi.org/10.3233/cbm-220143 (2022).Article 

Google Scholar 
Liu, H., Dilger, J. P. & Lin, J. A pan-cancer-bioinformatic-based literature review of TRPM7 in cancers. Pharmacol. Ther. https://doi.org/10.1016/j.pharmthera.2022.108302 (2022).Article 
PubMed 

Google Scholar 
Zheng, S. et al. CRTAM promotes antitumor immune response in triple negative breast cancer by enhancing CD8+ T cell infiltration. Int. Immunopharmacol. 129, 111625. https://doi.org/10.1016/j.intimp.2024.111625 (2024).Article 
CAS 
PubMed 

Google Scholar 
Xiao, G. et al. Integrative multiomics analysis identifies a metastasis-related gene signature and the potential oncogenic role of EZR in breast cancer. Oncol. Res. 30, 35–51 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Aureli, A. et al. Breast cancer is associated with increased HLA-DRB1*11:01 and HLA-DRB1*10:01 allele frequency in a population of patients from central Italy. Immunol. Invest. 49, 489–497. https://doi.org/10.1080/08820139.2020.1737539 (2020).Article 
CAS 
PubMed 

Google Scholar 
Huang, R. et al. Targeting glutamine metabolic reprogramming of SLC7A5 enhances the efficacy of anti-PD-1 in triple-negative breast cancer. Front. Immunol. 14, 1251643. https://doi.org/10.3389/fimmu.2023.1251643 (2023).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, Y. et al. GBP2 is a prognostic biomarker and associated with immunotherapeutic responses in gastric cancer. BMC Cancer 23, 925. https://doi.org/10.1186/s12885-023-11308-0 (2023).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, X., Cui, Q. & Qin, N. Low expression of KLRB1 predicts poor survival outcomes and is associated with immune infiltration in breast cancer. Transl. Cancer Res. 13, 1225–1240 (2024).Article 
PubMed 
PubMed Central 

Google Scholar 
He, J. R. et al. Inhibiting KLRB1 expression is associated with impairing cancer immunity and leading to cancer progression and poor prognosis in breast invasive carcinoma patients. Aging 15, 13265–13286 (2023).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wu, C., Zhong, R., Sun, X. & Shi, J. PSME2 identifies immune-hot tumors in breast cancer and associates with well therapeutic response to immunotherapy. Front. Genet. 13, 1071270. https://doi.org/10.3389/fgene.2022.1071270 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Engelhard, V. et al. B cells and cancer. Cancer Cell 39, 1293–1296. https://doi.org/10.1016/j.ccell.2021.09.007 (2021).Article 
CAS 
PubMed 

Google Scholar 
Overgaard, N. H., Jung, J. W., Steptoe, R. J. & Wells, J. W. CD4+/CD8+ double-positive T cells: More than just a developmental stage?. J. Leukocyte Biol. 97, 31–38. https://doi.org/10.1189/jlb.1RU0814-382 (2015).Article 
CAS 
PubMed 

Google Scholar 
van der Leun, A. M., Thommen, D. S. & Schumacher, T. N. CD8(+) T cell states in human cancer: Insights from single-cell analysis. Nat. Rev. Cancer 20, 218–232. https://doi.org/10.1038/s41568-019-0235-4 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Farhood, B., Najafi, M. & Mortezaee, K. CD8(+) cytotoxic T lymphocytes in cancer immunotherapy: A review. J. Cell Physiol. 234, 8509–8521. https://doi.org/10.1002/jcp.27782 (2019).Article 
CAS 
PubMed 

Google Scholar 
Mehla, K. & Singh, P. K. Metabolic regulation of macrophage polarization in cancer. Trends Cancer 5, 822–834. https://doi.org/10.1016/j.trecan.2019.10.007 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chen, Y. et al. Type I collagen deletion in αSMA(+) myofibroblasts augments immune suppression and accelerates progression of pancreatic cancer. Cancer Cell 39, 548-565.e546. https://doi.org/10.1016/j.ccell.2021.02.007 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Golby, S. J., Chinyama, C. & Spencer, J. Proliferation of T-cell subsets that contact tumour cells in colorectal cancer. Clin. Exp. Immunol. 127, 85–91. https://doi.org/10.1046/j.1365-2249.2002.01730.x (2002).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Dolina, J. S., Van Braeckel-Budimir, N., Thomas, G. D. & Salek-Ardakani, S. CD8(+) T cell exhaustion in cancer. Front. Immunol. 12, 715234. https://doi.org/10.3389/fimmu.2021.715234 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Thommen, D. S. & Schumacher, T. N. T cell dysfunction in cancer. Cancer Cell 33, 547–562. https://doi.org/10.1016/j.ccell.2018.03.012 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Buller, C. W., Mathew, P. A. & Mathew, S. O. Roles of NK Cell Receptors 2B4 (CD244), CS1 (CD319), and LLT1 (CLEC2D) in Cancer. Cancers https://doi.org/10.3390/cancers12071755 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Takeuchi, A. et al. CRTAM determines the CD4+ cytotoxic T lymphocyte lineage. J. Exp. Med. 213, 123–138. https://doi.org/10.1084/jem.20150519 (2016).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zhou, X. et al. A pan-cancer analysis of CD161, a potential new immune checkpoint. Front. Immunol. 12, 688215. https://doi.org/10.3389/fimmu.2021.688215 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Li, R. et al. Effects of local anesthetics on breast cancer cell viability and migration. BMC Cancer 18, 666 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Ou, L. et al. 1,3,6-Trigalloylglucose: A novel potent anti-helicobacter pylori adhesion agent derived from aqueous extracts of Terminalia chebula Retz. Molecules (Basel, Switzerland) 29, 1161 (2024).Article 
CAS 
PubMed 

Google Scholar 
Ou, L. et al. Terminalia chebula Retz. aqueous extract inhibits the Helicobacter pylori-induced inflammatory response by regulating the inflammasome signaling and ER-stress pathway. J. Ethnopharmacol. 320, 117428. https://doi.org/10.1016/j.jep.2023.117428 (2024).Article 
CAS 
PubMed 

Google Scholar 
Peng, C. et al. Syzygium aromaticum enhances innate immunity by triggering macrophage M1 polarization and alleviates Helicobacter pylori-induced inflammation. J. Funct. Foods 107, 105626 (2023).Article 
CAS 

Google Scholar 
Hengrui, L. An example of toxic medicine used in Traditional Chinese Medicine for cancer treatment. J. Tradit. Chin. Med. 43, 209–210 (2023).PubMed 

Google Scholar 
Liu, H. et al. Exploring the mechanism underlying hyperuricemia using comprehensive research on multi-omics. Sci. Rep. 13, 7161. https://doi.org/10.1038/s41598-023-34426-y (2023).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Berkel, C. & Cacan, E. Half of most frequently mutated genes in breast cancer are expressed differentially between premenopausal and postmenopausal breast cancer patients. Cancer Genet. 286–287, 11–17. https://doi.org/10.1016/j.cancergen.2024.06.001 (2024).Article 
CAS 
PubMed 

Google Scholar 
Glaviano, A. et al. Mechanisms of sensitivity and resistance to CDK4/CDK6 inhibitors in hormone receptor-positive breast cancer treatment. Drug Resist. Updat. 76, 101103. https://doi.org/10.1016/j.drup.2024.101103 (2024).Article 
CAS 
PubMed 

Google Scholar 
Mundt, E. et al. Breast and colorectal cancer risks among over 6,000 CHEK2 pathogenic variant carriers: A comparison of missense versus truncating variants. Cancer Genet. 278–279, 84–90. https://doi.org/10.1016/j.cancergen.2023.10.002 (2023).Article 
CAS 
PubMed 

Google Scholar 
Ward, A. et al. Clinical management of TP53 mosaic variants found on germline genetic testing. Cancer Genet. 284–285, 43–47. https://doi.org/10.1016/j.cancergen.2024.04.002 (2024).Article 
CAS 
PubMed 

Google Scholar 
Gonzalez, T., Nie, Q., Chaudhary, L. N., Basel, D. & Reddi, H. V. Methylation signatures as biomarkers for non-invasive early detection of breast cancer: A systematic review of the literature. Cancer Genet. 282–283, 1–8. https://doi.org/10.1016/j.cancergen.2023.12.003 (2024).Article 
CAS 
PubMed 

Google Scholar 

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