Identification of tumour‐infiltrating myeloid subsets associated with overall survival in lung squamous cell carcinoma
Open accessAbstract
Lung squamous cell carcinoma (LUSC) is a primary subtype of lung cancer with limited therapeutic options and poor prognosis, and tumour‐infiltrating myeloid cells (TIMs) are key regulators of LUSC. However, the correlation between the abundance of TIM subtypes and clinical outcomes of LUSC remains unexplored. This study aimed to develop and validate a prognostic model for low‐ and high‐risk patients with LUSC based on myeloid cell microenvironments. TIM markers in the tumoural (T) and stromal (S) regions were quantified using immunohistochemistry for 502 LUSC patients. L1‐penalized Cox regression was used to develop a myeloid survival score (MSS) model based on the training cohort, followed by validation in distinct cohorts from multiple centres. RNA sequencing and immunostaining were used to examine the mechanisms of myeloid cells in LUSC progression and predict potential drug targets and therapeutic agents. Of the 12 myeloid markers, CD163T, CD163S, and S100A12T were highly associated with overall survival (OS) in LUSC patients. The MSS of the three myeloid signatures accurately categorized LUSC patients into risk categories, with an observable difference in OS between the training and validation cohorts. Tumours with high MSS were associated with enhanced antioxidative ability and hedgehog signalling and a shift to a more pro‐tumorigenic microenvironment, accompanied by a reduced tumour cell immunogenicity and increased CD8 + T cell exhaustion patterns. Additionally, in high‐risk patients, potential drug targets and compounds regulating hedgehog signalling were identified. Our study provides the first prognostic myeloid signature for LUSC, which may help advance precision medicine. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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The copper-complex radiosensitizes ALDH1-positive carcinoma cells by inhibiting ALDH1 and downregulating the PI3K/Akt pathway, particularly enhancing the radiosensitivity of tumor-initiating cells.
“In vitro and in vivo studies showed that the copper-complex radiosensitizes ALDH1-positive carcinoma cells by inhibiting ALDH1 and downregulating the phosphoinositide 3-kinase (PI3K)/Akt pathway, particularly enhancing the radiosensitivity of tumor-initiating cells.79”
From Off-label and repurposed use of disulfiram beyond alcohol dependence: A systematic review of clinical and preclinical evidence (2026) · cites this paper as [79]
The Discussion (page unavailable) says disulfiram inhibits GLI1 in a copper-dependent manner. The References list separate studies on disulfiram/copper targeting an ALDH-positive population through ALDH1A1 inhibition and on copper-related radiosensitization. Our copy does not report that a copper-complex radiosensitizes ALDH1-positive carcinoma cells by inhibiting ALDH1 and downregulating PI3K/Akt, or that it particularly sensitizes tumor-initiating cells. (LLM, conf=0.80)
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Cites
Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21660 · Cited by 108,699 · see citing works
Siegel, R. L., Miller, K. D., & Jemal, A. (2015) · CA A Cancer Journal for Clinicians · doi:10.3322/caac.21254 · Cited by 11,854 · see citing works
The future of immune checkpoint therapy
Sharma, P., & Allison, J. P. (2015) · Science · doi:10.1126/science.aaa8172 · Cited by 4,878 · see citing works
The Tumor Microenvironment Innately Modulates Cancer Progression
Hinshaw, D. C., & Shevde, L. A. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-3962 · Cited by 3,270 · see citing works
Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards
Bronte, V., Brandau, S., Chen, S.-H., Colombo, M. P., Frey, A. B., Greten, T. F., Mandruzzato, S., Murray, P. J., Ochoa, A., Ostrand-Rosenberg, S., et al. (2016) · Nature Communications · doi:10.1038/ncomms12150 · Cited by 2,751 · see citing works
Thai, A. A., Solomon, B., Sequist, L. V. D., Gainor, J. F., & Heist, R. S. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00312-3 · Cited by 2,629 · see citing works
Targeting macrophages: therapeutic approaches in cancer
Cassetta, L., & Pollard, J. W. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.169 · Cited by 2,057 · see citing works
Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity
Veglia, F., Sanseviero, E., & Gabrilovich, D. I. (2021) · Nature Reviews Immunology · doi:10.1038/s41577-020-00490-y · Cited by 1,940 · see citing works
Tumor-Associated Macrophages in Tumor Immunity
Pan, Y., Yu, Y., Wang, X., & Zhang, T. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.583084 · Cited by 1,884 · see citing works
Macrophages and metabolism in the tumor microenvironment
Vitale, I., Manic, G., Coussens, L. M., Kroemer, G., & Galluzzi, L. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.06.001 · Cited by 1,837 · cited 12× · see citing works
“The discrepant role and underlying regulatory mechanisms of M2 macrophages in the different interspaces of the TME during LUSC progression need to be further studied.”
BackgroundInfluentialSingle-cell RNA sequencing to explore immune cell heterogeneity
Papalexi, E., & Satija, R. (2018) · Nature Reviews Immunology · doi:10.1038/nri.2017.76 · Cited by 1,806 · see citing works
Žilionis, R., Engblom, C., Pfirschke, C., Savova, V., Zemmour, D., Saatcioglu, H. D., Krishnan, I., Maroni, G., Meyerovitz, C. V., Kerwin, C. M., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.03.009 · Cited by 1,483 · see citing works
Type I interferons in anticancer immunity
Zitvogel, L., Galluzzi, L., Kepp, O., Smyth, M. J., & Kroemer, G. (2015) · Nature Reviews Immunology · doi:10.1038/nri3845 · Cited by 1,305 · see citing works
The cGAS–cGAMP–STING pathway connects DNA damage to inflammation, senescence, and cancer
Li, T., & Chen, Z. J. (2018) · Journal of Experimental Medicine · doi:10.1084/jem.20180139 · Cited by 1,293 · see citing works
Glutathione metabolism in cancer progression and treatment resistance
Bansal, A., & Simon, M. C. (2018) · The Journal of Cell Biology · doi:10.1083/jcb.201804161 · Cited by 1,234 · see citing works
Cassetta, L., Fragkogianni, S., Sims, A. H., Swierczak, A., Forrester, L. M., Zhang, H., Soong, D. Y. H., Cotechini, T., Anur, P., Lin, E. Y., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.02.009 · Cited by 918 · see citing works
Antitumour actions of interferons: implications for cancer therapy
Parker, B. S., Rautela, J., & Hertzog, P. J. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2016.14 · Cited by 897 · see citing works
Structures and Mechanisms in the cGAS-STING Innate Immunity Pathway
Zhang, X., Bai, X., & Chen, Z. J. (2020) · Immunity · doi:10.1016/j.immuni.2020.05.013 · Cited by 845 · see citing works
The role of myeloid cells in cancer therapies
Engblom, C., Pfirschke, C., & Pittet, M. J. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.54 · Cited by 788 · see citing works
Cancer immunotherapy: Pros, cons and beyond
Tan, S., Li, D., & Zhu, X. M. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.109821 · Cited by 694 · see citing works
Immune parameters affecting the efficacy of chemotherapeutic regimens
Zitvogel, L., Kepp, O., & Kroemer, G. (2011) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2010.223 · Cited by 665 · see citing works
Targeting macrophages in cancer immunotherapy
Duan, Z., & Luo, Y. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00506-6 · Cited by 634 · see citing works
Tumor-associated macrophages: Potential therapeutic targets for anti-cancer therapy
Komohara, Y., Fujiwara, Y., Ohnishi, K., & Takeya, M. (2015) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2015.11.009 · Cited by 613 · see citing works
Myeloid immunosuppression and immune checkpoints in the tumor microenvironment
Nakamura, K., & Smyth, M. J. (2019) · Cellular and Molecular Immunology · doi:10.1038/s41423-019-0306-1 · Cited by 521 · see citing works
Local mutational diversity drives intratumoral immune heterogeneity in non-small cell lung cancer
Jia, Q., Wu, W., Wang, Y., Alexander, P. B., Sun, C., Gong, Z., Cheng, J.-N., Sun, H., Guan, Y., Xia, X., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07767-w · Cited by 483 · see citing works
Han, C., Jin, J., Xu, S., Liu, H., Li, N., & Cao, X. (2010) · Nature Immunology · doi:10.1038/ni.1908 · Cited by 458 · see citing works
Tumor-Infiltrating Dendritic Cells in Cancer Pathogenesis
Janco, J. M. T., Lamichhane, P., Karyampudi, L., & Knutson, K. L. (2015) · The Journal of Immunology · doi:10.4049/jimmunol.1403134 · Cited by 440 · see citing works
Spatial Heterogeneity in the Tumor Microenvironment
Yuan, Y. (2016) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a026583 · Cited by 342 · see citing works
DNA Damage and Cancer Immunotherapy: A STING in the Tale
Reisländer, T., Groelly, F. J., & Tarsounas, M. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.07.026 · Cited by 318 · see citing works
Jensen, T. Ø., Schmidt, H., Møller, H. J., Høyer, M., Maniecki, M. B., Sjoegren, P., Christensen, I. J., & Steiniche, T. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2008.19.9919 · Cited by 299 · see citing works
Yang, C. G., Huang, X., Yan, L., Chen, J., Lv, Y., & Dai, S. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa164 · Cited by 268 · see citing works
Tumor-infiltrating dendritic cell states are conserved across solid human cancers
Gerhard, G. M., Bill, R., Messemaker, M., Klein, A. M., & Pittet, M. J. (2020) · The Journal of Experimental Medicine · doi:10.1084/jem.20200264 · Cited by 240 · see citing works
Nagorsen, D., Voigt, S., Berg, E. G., Stein, H., Thiel, E., & Loddenkemper, C. (2007) · Journal of Translational Medicine · doi:10.1186/1479-5876-5-62 · Cited by 228 · see citing works
Kasper, M., Schnidar, H., Neill, G. W., Hanneder, M., Klingler, S., Blaas, L., Schmid, C., Hauser‐Kronberger, C., Regl, G., Philpott, M. P., et al. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.02317-05 · Cited by 219 · see citing works
Zheng, X., Weigert, A., Reu, S., Günther, S., Mansouri, S., Bassaly, B., Gattenlöhner, S., Grimminger, F., Pullamsetti, S. S., Seeger, W., et al. (2020) · Cancer Research · doi:10.1158/0008-5472.can-20-0069 · Cited by 218 · see citing works
Human Tumor-Infiltrating Myeloid Cells: Phenotypic and Functional Diversity
Elliott, L., Doherty, G. A., Sheahan, K. D., & Ryan, E. J. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.00086 · Cited by 208 · see citing works
Nechushtan, H., Hamamreh, Y., Nidal, S., Gotfried, M., Baron, A., Shalev, Y. I., Nisman, B., Peretz, T., & Peylan‐Ramu, N. (2015) · The Oncologist · doi:10.1634/theoncologist.2014-0424 · Cited by 204 · see citing works
Agonism of CD11b reprograms innate immunity to sensitize pancreatic cancer to immunotherapies
Panni, R. Z., Herndon, J. M., Zuo, C., Hegde, S., Hogg, G. D., Knolhoff, B. L., Breden, M. A., Li, X., Krisnawan, V. E., Khan, S. Q., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aau9240 · Cited by 203 · see citing works
Catching a Gli-mpse of Hedgehog
Altaba, A. R. I. (1997) · Cell · doi:10.1016/s0092-8674(00)80325-6 · Cited by 199 · see citing works
Mei, J., Xiao, Z., Guo, C., Pu, Q., Ma, L., Liu, C., Lin, F., Liao, H., You, Z., & Liu, L. (2016) · Oncotarget · doi:10.18632/oncotarget.9079 · Cited by 198 · see citing works
The sonic hedgehog factor GLI1 imparts drug resistance through inducible glucuronidation
Zahreddine, H. A., Čuljković, B., Assouline, S. E., Gendron, P., Romeo, A. A., Morris, S. J., Cormack, G., Jaquith, J. B., Cerchietti, L. C. A., Cocolakis, E., et al. (2014) · Nature · doi:10.1038/nature13283 · Cited by 180 · see citing works
Schreck, K. C., Taylor, P. H., Marchionni, L., Gopalakrishnan, V., Bar, E. E., Gaiano, N., & Eberhart, C. G. (2010) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-10-1624 · Cited by 166 · see citing works
M2 tumor‑associated macrophages promote tumor progression in non‑small‑cell lung cancer
Sumitomo, R., Hirai, T., Fujita, M., Murakami, H., Otake, Y., & Huang, C. (2019) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2019.8068 · Cited by 161 · see citing works
Applications of single-cell and bulk RNA sequencing in onco-immunology
Kuksin, M., Morel, D., Aglave, M., Danlos, F., Marabelle, A., Zinovyev, A. Y., Gautheret, D., & Verlingue, L. (2021) · European Journal of Cancer · doi:10.1016/j.ejca.2021.03.005 · Cited by 158 · see citing works
Meding, S., Balluff, B., Elsner, M., Schöne, C., Rauser, S., Nitsche, U., Maak, M., Schäfer, A., Hauck, S. M., Ueffing, M., et al. (2012) · The Journal of Pathology · doi:10.1002/path.4021 · Cited by 136 · see citing works
Rakaee, M., Busund, L., Jamaly, S., Paulsen, E., Richardsen, E., Andersen, S., Al-Saad, S., Bremnes, R., Donnem, T., & Kilvaer, T. (2019) · Neoplasia · doi:10.1016/j.neo.2019.01.005 · Cited by 133 · see citing works
Neutrophils in the era of immune checkpoint blockade
Faget, J., Peters, S., Quantin, X., Meylan, E., & Bonnefoy, N. (2021) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-002242 · Cited by 117 · see citing works
Generation of a Concise Gene Panel for Outcome Prediction in Urinary Bladder Cancer
Mitra, A. P., Pagliarulo, V., Yang, D., Waldman, F. M., Datar, R. H., Skinner, D. G., Groshen, S. G., & Côté, R. J. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2008.18.5744 · Cited by 104 · see citing works
Zhou, J., Zhu, G., Huang, J. X., Li, L., Du, Y., Gao, Y., Wu, D., Wang, X., Hsieh, J., He, D., et al. (2015) · Cancer Letters · doi:10.1016/j.canlet.2015.11.006 · Cited by 104 · see citing works
Myeloid Suppressor Cells and Immune Modulation in Lung Cancer
Srivastava, M. K., Andersson, Å., Zhu, L. X., Harris‐White, M. E., Lee, J. M., Dubinett, S. M., & Sharma, S. P. (2012) · Immunotherapy · doi:10.2217/imt.11.178 · Cited by 95 · see citing works
Weerasinghe, P., Garcia, G., Zhu, Q., Yuan, P., Feng, L., Mao, L., & Jing, N. (2007) · International Journal of Oncology · doi:10.3892/ijo.31.1.129 · Cited by 95 · see citing works
The Role of Myeloid-Derived Cells in the Progression of Liver Disease
Weston, C. J., Zimmermann, H. W., & Adams, D. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00893 · Cited by 91 · see citing works
Wu, P., Wu, D., Zhao, L., Huang, L., Chen, G., Shen, G., Huang, J., & Chai, Y. (2016) · Oncotarget · doi:10.18632/oncotarget.9625 · Cited by 91 · see citing works
Fortis, S. P., Sofopoulos, M., Sotiriadou, N. N., Haritos, C., Vaxevanis, C., Anastasopoulou, E. A., Janssen, N., Arnogiannaki, N., Ardavanis, A. S., Pawelec, G., et al. (2017) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-017-0240-7 · Cited by 89 · see citing works
Recent advances in preclinical models for lung squamous cell carcinoma
Pan, Y., Han, H., Labbe, K. E., Zhang, H., & Wong, K. (2021) · Oncogene · doi:10.1038/s41388-021-01723-7 · Cited by 66 · see citing works
Drivers of dynamic intratumor heterogeneity and phenotypic plasticity
Biswas, A., & De, S. (2021) · American Journal of Physiology-Cell Physiology · doi:10.1152/ajpcell.00575.2020 · Cited by 59 · see citing works
Ni, Y., Soliman, A. S. A., Joehlin-Price, A. S., Rose, P. G., Vlad, A., Edwards, R. P., & Mahdi, H. (2021) · npj Precision Oncology · doi:10.1038/s41698-021-00242-8 · Cited by 57 · see citing works
Role and inhibition of GLI1 protein in cancer
Mastrangelo, E., & Milani, M. (2018) · Lung Cancer Targets and Therapy · doi:10.2147/lctt.s124483 · Cited by 55 · see citing works
Jin, N., Zhu, X., Cheng, F., & Zhang, L. (2018) · Journal of Cellular Biochemistry · doi:10.1002/jcb.26885 · Cited by 53 · see citing works
GSTM3 and GSTP1: novel players driving tumor progression in cervical cancer
Checa, A., Delgadillo-Silva, L. F., Velasco‐Herrera, M. D. C., Andrade-Domínguez, A., Gil, J., Santillán, O., Lozano, L., Toledo‐Leyva, A., Ramírez-Torres, A., Talamás‐Rohana, P., et al. (2018) · Oncotarget · doi:10.18632/oncotarget.24796 · Cited by 48 · see citing works
Falls-Hubert, K. C., Butler, A. L., Gui, K., Anderson, M., Li, M., Stolwijk, J. M., Rodman, S. N., Solst, S. R., Tomanek‐Chalkley, A., Searby, C. C., et al. (2020) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2020.01.186 · Cited by 42 · see citing works
Advanced basal cell carcinoma: What dermatologists need to know about treatment
Wilson, M., Johnson, R. P., Senft, S. C., Pan, E. Y., & Krakowski, A. C. (2022) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2022.03.022 · Cited by 31 · see citing works
Myeloid cell heterogeneity in lung cancer: implication for immunotherapy
Sangaletti, S., Ferrara, R., Tripodo, C., Garassino, M. C., & Colombo, M. P. (2021) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-021-02916-5 · Cited by 22 · see citing works
Yang, X., Chen, R., Chen, Y., Zhou, Y., Wu, C., Li, Q., Wu, J., Hu, W., Zhao, W., Wei, W., et al. (2022) · Cancer Science · doi:10.1111/cas.15299 · Cited by 22 · see citing works
Wu, X., Peng, H., He, M., Zhong, R., Liu, J., Wen, Y., Li, C., Li, J., Xiong, S., Tao, Y., et al. (2022) · Translational Lung Cancer Research · doi:10.21037/tlcr-21-916 · Cited by 17 · see citing works
S100 family members: potential therapeutic target in patients with hepatocellular carcinoma
Zhang, C., Yao, R., Chen, J., Zou, Q., & Zeng, L. (2021) · Medicine · doi:10.1097/md.0000000000024135 · Cited by 17 · see citing works
Zhang, Y., Vagiannis, D., Budagaga, Y., Sabet, Z., Hanke, I., Rozkoš, T., & Hofman, J. (2022) · Biochemical Pharmacology · doi:10.1016/j.bcp.2022.115009 · Cited by 17 · see citing works
Chen, P., Zhu, K., Zhang, D.-Y., Yan, H., Liu, H., Liu, Y., Cao, S., Zhou, G., Zeng, H., Chen, S., et al. (2018) · Journal of Translational Medicine · doi:10.1186/s12967-018-1579-3 · Cited by 16 · see citing works
Young, P., Ardestani, S., & Li, B. (2010) · Cancer Microenvironment · doi:10.1007/s12307-010-0045-4 · Cited by 14 · see citing works
Quantitative tissue analysis and role of myeloid cells in non-small cell lung cancer
Henick, B. S., Villarroel‐Espíndola, F., Datar, I. J., Sanmamed, M. F., Yu, J., Desai, S., Li, A., Aguirre, A., Syrigos, K., Rimm, D. L., et al. (2022) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2022-005025 · Cited by 12 · see citing works
Fortis, S. P., Sofopoulos, M., Sotiriadou, N. N., Haritos, C., Vaxevanis, C., Anastasopoulou, E. A., Janssen, N., Arnogiannaki, N., Ardavanis, A. S., Pawelec, G., et al. (2017) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-017-0248-z · Cited by 4 · see citing works
Flagged first, then by citations
1 of the 72 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- [3]Thai AA, Solomon BJ, Sequist LV, et al. Lung cancer. Lancet 2021; 398: 535– 554. 34273294
Cited by
Sorted by citations
Prognostic value of CD163+ macrophages in solid tumor malignancies: A scoping review
Mathiesen, H., Juul‐Madsen, K., Tramm, T., Vorup‐Jensen, T., Møller, H. J., Etzerodt, A., & Andersen, M. N. (2025) · Immunology Letters · doi:10.1016/j.imlet.2025.106970 · Cited by 23 · see citing works
Varnamkhasti, K. K., Moghanibashi, M., & Naeimi, S. (2023) · Scientific Reports · doi:10.1038/s41598-023-33897-3 · Cited by 15 · see citing works
Lin, H., Wang, J., Shi, Q., & Wu, M. (2024) · PeerJ · doi:10.7717/peerj.17338 · Cited by 2 · see citing works
Benkő, B.-M., De Brito Parreirinha, N. S., Sebe, I., & Zelkó, R. (2026) · iScience · doi:10.1016/j.isci.2026.115441 · Cited by 2 · see citing works
Wan, H., Li, A., Jiang, H., Ling, Z., Su, R., Hao, X., Pei, J., & Yang, X. (2025) · Clinical and Experimental Medicine · doi:10.1007/s10238-025-01888-5 · Cited by 1 · see citing works
Wang, Y., Gong, S., Shen, J., Liu, G., & Chen, M. (2026) · Biology Direct · doi:10.1186/s13062-026-00785-5
- Authors
- Lu, J., Duan, Y., Liu, P., He, X., Yang, Y., Zhang, R., & Weng, L.
- Affiliations
- Central South University (CN)
- Department of Oncology, Xiangya Cancer Center, Xiangya Hospital Central South University Changsha PR China
- Hunan Normal University (CN)
- Corresponding author
- Weng, Liang
- Venue
- The Journal of Pathology
- Publisher
- Wiley
- Published
- 2022-11-16
- Volume
- 259
- Issue
- 1
- Pages
- 21-34
- ISSN
- 0022-3417 (ISSN-L)
- 1096-9896
- PMC
- PMC10100161
- OpenAlex
- W4298086517
- Cited by
- 6
- References
- 72
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 1 · 2023: 1
- FWCI
- 0.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Journal of Pathology (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- Huxiang Youth Talent Support Program (2019RS1009)
- National Natural Science Foundation of China (81900199, 81974465)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Oncology › Lung Cancer Research Studies
- Keywords
- lung squamous cell carcinoma, prognostic signature, overall survival, CD163, S100A12, tumor microenvironment, Hedgehog signaling, antioxidant capacity, CD8+ T cell exhaustion, tumor immunogenicity, therapeutic target
- MeSH terms
- Carcinoma, Non-Small-Cell Lung, Carcinoma, Squamous Cell, Humans, Lung, Lung Neoplasms, Prognosis, Biomarkers, Tumor, Hedgehog Proteins, Tumor Microenvironment
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