Identification of hub modules and therapeutic targets associated with CD8+T-cells in HF and their pan-cancer analysis

Mosterd, A. & Hoes, A. W. Clinical epidemiology of heart failure. Heart 93, 1137–1146 (2007).Article 

Google Scholar 
Tomasoni, D., Adamo, M., Lombardi, C. M. & Metra, M. Highlights in heart failure. ESC Heart Fail. 6, 1105–1127 (2020).Article 

Google Scholar 
Koene, R. J., Prizment, A. E., Blaes, A. & Konety, S. H. Shared risk factors in cardiovascular disease and cancer. Circulation 133, 1104–1114 (2016).Article 

Google Scholar 
de Wit, S., Glen, C., de Boer, R. A. & Lang, N. N. Mechanisms shared between cancer, heart failure, and targeted anti-cancer therapies. Cardiovasc. Res. 118, 3451–3466 (2022).Article 

Google Scholar 
Gröschel, C. et al. CD8+-T cells with specificity for a model antigen in cardiomyocytes can become activated after transverse aortic constriction but do not accelerate progression to heart failure. Front. Immunol. 9, 2665 (2018).Article 

Google Scholar 
Aghajanian, H. et al. Targeting cardiac fibrosis with engineered T cells. Nature 573, 430–433 (2019).Article 
ADS 
CAS 

Google Scholar 
Komai, K. et al. Single-cell analysis revealed the role of CD8+ effector T cells in preventing cardioprotective macrophage differentiation in the early phase of heart failure. Front. Immunol. 12, 763647 (2021).Article 
CAS 

Google Scholar 
Laroumanie, F. et al. CD4+T cells promote the transition from hypertrophy to heart failure during chronic pressure overload. Circulation 129, 2111–2124 (2014).Article 
CAS 

Google Scholar 
Zhao, S., Wu, Y., Wei, Y., Xu, X. & Zheng, J. Identification of biomarkers associated with CD8+ T cells in coronary artery disease and their pan-cancer analysis. Front. Immunol. 13, 876616 (2022).Article 
CAS 

Google Scholar 
Tsukumo, S. I. & Yasutomo, K. Regulation of CD8+ T cells and antitumor immunity by notch signaling. Front. Immunol. 30, 9 (2018).
Google Scholar 
Kersten, K. et al. Spatiotemporal co-dependency between macrophages and exhausted CD8+ T cells in cancer. Cancer Cell 40, 624–638 (2022).Article 
CAS 

Google Scholar 
Gutiérrez-Melo, N. & Baumjohann, D. T follicular helper cells in cancer. Trends Cancer 9, 309–325 (2023).Article 

Google Scholar 
Langfelder, P. & Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinf. 9, 559 (2008).Article 

Google Scholar 
Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).Article 
CAS 

Google Scholar 
Zhu, J., Meng, H., Zhang, L. & Li, Y. Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets. J. Transl. Med. 21, 372 (2023).Article 
CAS 

Google Scholar 
Wang, M. et al. Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways. Front. Immunol. 14, 1048195 (2023).Article 
CAS 

Google Scholar 
Obuchowski, N. A. & Bullen, J. A. Receiver operating characteristic (ROC) curves: review of methods with applications in diagnostic medicine. Phys. Med. Biol. 63, 07TR01 (2018).Article 

Google Scholar 
Sui, Q. et al. Inflammation promotes resistance to immune checkpoint inhibitors in high microsatellite instability colorectal cancer. Nat. Commun. 13, 7316 (2022).Article 
ADS 
CAS 

Google Scholar 
Sargent, D. J. et al. Defective mismatch repair as a predictive marker for lack of efficacy of fluorouracil-based adjuvant therapy in colon cancer. J. Clin. Oncol. 28, 3219–3226 (2010).Article 
CAS 

Google Scholar 
Goldman, M. J. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat. Biotechnol. 38, 675–678 (2020).Article 
CAS 

Google Scholar 
Thorsson, V. et al. The immune landscape of cancer. Immunity 48, 812-830.e814 (2018).Article 
CAS 

Google Scholar 
Hong, M., Clubb, J. D. & Chen, Y. Y. Engineering CAR-T Cells for next-generation cancer therapy. Cancer Cell 38, 473–488 (2020).Article 
CAS 

Google Scholar 
Balko, J. et al. T cells specific for α-myosin drive immunotherapy-related myocarditis. Nature 611, 818–826 (2022).Article 
ADS 

Google Scholar 
Läubli, H. et al. Acute heart failure due to autoimmune myocarditis under pembrolizumab treatment for metastatic melanoma. J. Immunother. Cancer 3, 11 (2015).Article 

Google Scholar 
Sur, M. et al. Transgenic mice expressing functional TCRs specific to cardiac Myhc-α 334–352 on both CD4 and CD8 T cells are resistant to the development of myocarditis on C57BL/6 genetic background. Cells 12, 2346 (2023).Article 
CAS 

Google Scholar 
Meijers, W. C. & de Boer, R. A. Common risk factors for heart failure and cancer. Cardiovasc. Res. 115, 844–853 (2019).Article 
CAS 

Google Scholar 
Kachanova, O., Lobov, A. & Malashicheva, A. The role of the notch signaling pathway in recovery of cardiac function after myocardial infarction. Int. J. Mol. Sci. 23, 12509 (2022).Article 
CAS 

Google Scholar 
Aoyagi, T. & Matsui, T. Phosphoinositide-3 kinase signaling in cardiac hypertrophy and heart failure. Curr. Pharm. Des. 17, 1818–1824 (2011).Article 
CAS 

Google Scholar 
Zhong, S. et al. Apelin-13 alleviated cardiac fibrosis via inhibiting the PI3K/Akt pathway to attenuate oxidative stress in rats with myocardial infarction-induced heart failure. Biosci. Rep. 40(4), 20200040 (2020).Article 

Google Scholar 
Hoxhaj, G. & Manning, B. D. The PI3K–AKT network at the interface of oncogenic signalling and cancer metabolism. Nat. Rev. Cancer 20, 74–88 (2019).Article 

Google Scholar 
Ferreira, A. & Aster, J. C. Notch signaling in cancer: Complexity and challenges on the path to clinical translation. Semin. Cancer Biol. 85, 95–106 (2022).Article 
CAS 

Google Scholar 
Yu, T., Robotham, J. L. & Yoon, Y. Increased production of reactive oxygen species in hyperglycemic conditions requires dynamic change of mitochondrial morphology. Proc. Natl. Acad. Sci. 103(8), 2653–2658 (2006).Article 
ADS 
CAS 

Google Scholar 
Yu, H. et al. LARP7 protects against heart failure by enhancing mitochondrial biogenesis. Circulation 143, 2007–2022 (2021).Article 
CAS 

Google Scholar 
Vyas, S., Zaganjor, E. & Haigis, M. C. Mitochondria and cancer. Cell 166, 555–566 (2016).Article 
CAS 

Google Scholar 
Turman, M. A., Yabe, T., McSherry, C., Bach, F. H. & Houchins, J. P. Characterization of a novel gene (NKG7) on human chromosome 19 that is expressed in natural killer cells and T cells. Human Immunol. 36(1), 34–40 (1993).Article 
CAS 

Google Scholar 
Peña, S. V. & Krensky, A. M. Granulysin, a new human cytolytic granule-associated protein with possible involvement in cell-mediated cytotoxicity. Semin Immunol. 9, 117–125 (1997).Article 

Google Scholar 
Wen, T. et al. NKG7 Is a T-cell–intrinsic therapeutic target for improving antitumor cytotoxicity and cancer immunotherapy. Cancer Immunol. Res. 10, 162–181 (2022).Article 
CAS 

Google Scholar 
Martinez-Lostao, L., Miguel, D. D., Al-Wasaby, S., Gallego-Lleyda, A. & Anel, A. Death ligands and granulysin: mechanisms of tumor cell death induction and therapeutic opportunities. Immunotherapy 7(8), 883–882 (2015).Article 

Google Scholar 
Milovanović, J. et al. Can granulysin provide prognostic value in primary breast cancer?. Pathol. –Res. Pract. 237, 154039 (2022).Article 

Google Scholar 
Pilat, D. et al. The human Met-ase gene (GZMM): structure, sequence, and close physical linkage to the serine protease gene cluster on 19p13.3. Genomics 24(3), 445–450 (1994).Article 
CAS 

Google Scholar 
Susanto, O., Trapani, J. A. & Brasacchio, D. Controversies in granzyme biology. Tissue Antigens 80, 477–487 (2012).Article 
CAS 

Google Scholar 
Hu, D. et al. Cleavage of survivin by granzyme M triggers degradation of the survivin-X-linked Inhibitor of apoptosis protein (XIAP) complex to free caspase activity leading to cytolysis of target tumor cells. J. Biol. Chem. 285, 18326–18335 (2010).Article 
CAS 

Google Scholar 
Cullen, S. P. et al. Nucleophosmin is cleaved and inactivated by the cytotoxic granule protease granzyme M during natural killer cell-mediated Killing. J. Biol. Chem. 284, 5137–5147 (2009).Article 
CAS 

Google Scholar 
Rai, S. et al. Decreased expression of T-cell-associated immune markers predicts poor prognosis in patients with follicular lymphoma. Cancer Sci. 113, 660–673 (2021).Article 

Google Scholar 
Amin, S., Parker, A. & Mann, J. ZAP70 in chronic lymphocytic leukaemia. Int. J. Biochem. Cell Biol. 40, 1654–1658 (2008).Article 
CAS 

Google Scholar 
Au-Yeung, B. B. et al. The structure, regulation, and function of ZAP-70. Immunol. Rev. 228, 41–57 (2009).Article 
CAS 

Google Scholar 
Ashouri, J. F., Lo, W. L., Nguyen, T. T. T., Shen, L. & Weiss, A. ZAP70, too little, too much can lead to autoimmunity. Immunol. Rev. 307, 145–160 (2021).Article 

Google Scholar 
Ren, L., Li, P., Li, Z. & Chen, Q. AQP9 and ZAP70 as immune-related prognostic biomarkers suppress proliferation, migration and invasion of laryngeal cancer cells. BMC Cancer 22 (2022).Song, P. et al. Identification of important genes related to anoikis in acute myocardial infarction. J Cell Mol Med 28 (2024).Dunsmore, K. P. et al. Children’s oncology group AALL0434: A phase III randomized clinical trial testing nelarabine in newly diagnosed T-cell acute lymphoblastic leukemia. J. Clin. Oncol. 38, 3282–3293 (2020).Article 
CAS 

Google Scholar 
Baritussio, A., Gately, A., Pawade, J., Marks, D. I. & Bucciarelli-Ducci, C. Extensive cardiac infiltration in acute T-cell lymphoblastic leukemia: occult extra-medullary relapse and remission after salvage chemotherapy. Eur. Heart J. 38, 1933 (2016).
Google Scholar 
Robichaux, D. J., Harata, M., Murphy, E. & Karch, J. Mitochondrial permeability transition pore-dependent necrosis. J. Mol. Cell. Cardiol. 174, 47–55. https://doi.org/10.1016/j.yjmcc.2022.11.003 (2023).Article 
CAS 

Google Scholar 
Vagos Mata, A. et al. Chronic lymphocytic leukaemia/small lymphocytic lymphoma treatment with rituximab and high-dose methylprednisolone, revisited. Cancer Med. 10, 8768–8776 (2021).Article 
CAS 

Google Scholar 
Rovetto, M. J. Effect of hyaluronidase and methylprednisolone on myocardial function, glucose metabolism, and coronary flow in the isolated ischemic rat heart. Circ. Res. 41, 373–379 (1977).Article 
CAS 

Google Scholar 
Nayler, W. G., Yepez, C., Grau, A. & Slade, A. Protective effect of methylprednisolone sodium succinate on the ultrastructure and resting tension of hypoxic heart muscle. Cardiovasc. Res. 12, 91–98s (1978).Article 
CAS 

Google Scholar 
Greenberg, B. H. Emerging treatment approaches to improve outcomes in patients with heart failure. Cardiol. Discov. 4, 231–240 (2022).Article 

Google Scholar 
Huang, Y. et al. The protective role of Yin-Yang 1 in cardiac injury and remodeling after myocardial infarction. J. Am. Heart Assoc. 10, e021895 (2021).Article 
CAS 

Google Scholar 
Cho, A. A. & Bonavida, B. Targeting the overexpressed YY1 in cancer inhibits EMT and metastasis. Crit. Rev. Oncog. 22, 49–61 (2017).Article 

Google Scholar 
Chen, S. et al. YY1 complex in M2 macrophage promotes prostate cancer progression by upregulating IL-6. J Immunother Cancer 11, e006020 (2023).Article 

Google Scholar 
Thomassen, M., Tan, Q. & Kruse, T. A. Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer. BMC Cancer 8, 394 (2008).Article 

Google Scholar 
Krensky, A. M. & Clayberger, C. Granulysin: A novel host defense molecule. Am. J. Transpl. 5, 1789–1792 (2005).Article 
CAS 

Google Scholar 
Flam, E. et al. Integrated landscape of cardiac metabolism in end-stage human nonischemic dilated cardiomyopathy. Nat. Cardiovasc. Res. 1, 817–829 (2022).
Google Scholar 
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucl. Acids Res. 43, e47–e47 (2015).Article 

Google Scholar 
Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).Article 
CAS 

Google Scholar 
Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucl. Acids Res. 28, 27–30 (2000).Article 
CAS 

Google Scholar 
Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M. & Alizadeh, A. A. in Methods Mol Biol Methods in Molecular Biology Ch. Chapter 12, 243–259 (2018).Miao, Y. et al. Prognostic value and immunological role of PDCD1 gene in pan-cancer. Int. Immunopharmacol. 89, 107080 (2020).Article 
CAS 

Google Scholar 
Shankavaram, U. T. et al. Cell Miner: A relational database and query tool for the NCI-60 cancer cell lines. BMC Genomics 10, 277 (2009).Article 

Google Scholar 
Tang, Z., Kang, B., Li, C., Chen, T. & Zhang, Z. GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis. Nucl. Acids Res. 47, W556–W560 (2019).Article 
CAS 

Google Scholar 
Yoshihara, K. et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat. Commun. 4, 2612 (2013).Article 
ADS 

Google Scholar 
Liu, J. et al. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics. Cell 173, 400-416.e411 (2018).Article 
CAS 

Google Scholar 
Kumar, M., Kumar, R., Singhal, N. & Garg, A. mRNALoc: A novel machine-learning based in-silico tool to predict mRNA subcellular localization. Nucl. Acids Res. 48, W239–W243 (2020).Article 

Google Scholar 
Xia, J., Gill, E. E. & Hancock, R. E. W. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat. Protoc. 10, 823–844 (2015).Article 
CAS 

Google Scholar 
Subramanian, A. et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).Article 
ADS 
CAS 

Google Scholar 
Reinhold, W. C. et al. Cell miner: A web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set. Cancer Res. 72, 3499–3511 (2012).Article 
CAS 

Google Scholar 

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