Mapping heterogeneous molecular subtypes of circadian misalignment underlying lung adenocarcinoma risk
DOI:
https://doi.org/10.71321/fy14v342Keywords:
Circadian Rhythm Disruption, Lung Adenocarcinoma, Molecular Subtype, Immunotherapy, Tumor Immune MicroenvironmentAbstract
Background: The circadian rhythm coordinates multiple physiological and behavioral processes. Substantial evidence illustrates that circadian rhythm disruption (CRD) dramatically influences tumor initiation, progression, and the tumor immune microenvironment remodeling. However, there is a dearth of exploration for CRD heterogeneity’s underlying clinical significance in lung adenocarcinoma (LUAD).
Methods: 2090 LUAD patients and 79 immunotherapy patients were enrolled from nine public independent datasets. The nonnegative matrix factorization (NMF) was applied to develop molecular classification after collecting CRD-related genes. Subsequently, the reliability and robustness of classification were evaluated through the nearest template prediction (NTP) method. Furthermore, clinical outcomes, functional characteristics, genomic alterations, and immune landscape were explored. The efficacy of clinical common treatment was detected for the specific classification.
Results: Three heterogeneous LUAD subtypes were identified based on the expression profile of CRD-related genes. Different expression characteristics and clinical outcomes of distinct subtypes were revealed. Relative similar clinical outcomes and proportion of each subtype were verified in multiple independent cohorts, which indicated the reliability of classification. Distinguish features of three subtypes were further explored: (i) C1, the poorest prognosis, significant cell proliferation, and highest genomic instability. (ii) C2, the best outcome, elevated lipid metabolic function, favorable regulation of circadian rhythm, and (iii) C3, copious immune infiltration, immunosuppressive microenvironment, and conspicuous intratumor heterogeneity. The evaluation of treatment strategies suggested that C1 patients might benefit from chemotherapeutics agents, including docetaxel and paclitaxel, patients in C2 were suitable for glucocorticoids, whereas C3 patients were recommended to accept immunotherapy.
Conclusions: We identified three CRD subtypes with distinct characteristics, including clinical outcomes, biological function, genomic alterations, and immune landscape. For individualized subtypes, befitting therapy approaches were proposed. Our study could provide more efficient and precise management to LUAD patients.
References
[1] He, Q., Qu, Shen, Xu, Y., Luo, J., & Tan, D. (2022). Suppression of VEGFD expression by S-nitrosylation promotes the development of lung adenocarcinoma. J Exp Clin Cancer Res, 41(1), 239. https://doi.org/10.1186/s13046-022-02454-7
[2] Garon, EB, Hellmann, MD, Rizvi, NA, Carcereny, E, Leighl, NB, Ahn, MJ, Eder, JP, Balmanoukian, AS, Aggarwal, C, Horn, L, Patnaik, A, Gubens, M, Ramalingam, SS, Felip, E, Goldman, JW, Scalzo, C, Jensen, E, Kush, DA, & Hui, R (2019). Five-Year Overall Survival for Patients With Advanced Non‒Small-Cell Lung Cancer Treated With Pembrolizumab: Results From the Phase I KEYNOTE-001 Study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 37(28), 2518-2527. https://doi.org/10.1200/JCO.19.00934
[3] Zhang, L, Zhang, Y, Wang, C, Yang, Y, Ni, Y, Wang, Z, Song, T, Yao, M, Liu, Z, Chao, N, Yang, Y, Shao, J, Li, Z, Zhou, R, Chen, L, Zhang, D, Zhao, Y, Liu, W, Li, Y, ... Li, W (2022). Integrated single-cell RNA sequencing analysis reveals distinct cellular and transcriptional modules associated with survival in lung cancer. Signal transduction and targeted therapy, 7(1), 9. https://doi.org/10.1038/s41392-021-00824-9
[4] Yin, Z., Deng, J., Zhou, M., Li, M., Zhou, E., & Liu, J. (2022). Exploration of a Novel Circadian miRNA Pair Signature for Predicting Prognosis of Lung Adenocarcinoma. Cancers (Basel), 14(20). https://doi.org/10.3390/cancers14205070
[5] Bass, J, & Takahashi, JS (2010). Circadian integration of metabolism and energetics. Science (New York, N.Y.), 330(6009), 1349-54. https://doi.org/10.1126/science.1195027
[6] Lassi, M., Tomar, A., Comas-Armangue, G., Vogtmann, R., Dijkstra, D., & Corujo, D. (2021). Disruption of paternal circadian rhythm affects metabolic health in male offspring via nongerm cell factors. Sci Adv, 7(22). https://doi.org/10.1126/sciadv.abh1057
[7] Kinouchi, K, & Sassone-Corsi, P (2020). Metabolic rivalry: circadian homeostasis and tumorigenesis. Nature reviews. Cancer, 20(11), 645-661. https://doi.org/10.1038/s41568-020-0291-9
[8] Xuan, W, Khan, F, James, CD, Heimberger, AB, Lesniak, MS, & Chen, P (2021). Circadian regulation of cancer cell and tumor microenvironment crosstalk. Trends in cell biology, 31(11), 940-950. https://doi.org/10.1016/j.tcb.2021.06.008
[9] Aiello, I, Mul Fedele, ML, Román, F, Marpegan, L, Caldart, C, Chiesa, JJ, Golombek, DA, Finkielstein, CV, & Paladino, N (2020). Circadian disruption promotes tumor-immune microenvironment remodeling favoring tumor cell proliferation. Science advances, 6(42). https://doi.org/10.1126/sciadv.aaz4530
[10] Hadadi, E, Taylor, W, Li, XM, Aslan, Y, Villote, M, Rivière, J, Duvallet, G, Auriau, C, Dulong, S, Raymond-Letron, I, Provot, S, Bennaceur-Griscelli, A, & Acloque, H (2020). Chronic circadian disruption modulates breast cancer stemness and immune microenvironment to drive metastasis in mice. Nature communications, 11(1), 3193. https://doi.org/10.1038/s41467-020-16890-6
[11] Ruan, W, Yuan, X, & Eltzschig, HK (2021). Circadian rhythm as a therapeutic target. Nature reviews. Drug discovery, 20(4), 287-307. https://doi.org/10.1038/s41573-020-00109-w
[12] Partch, CL, Green, CB, & Takahashi, JS (2014). Molecular architecture of the mammalian circadian clock. Trends in cell biology, 24(2), 90-9. https://doi.org/10.1016/j.tcb.2013.07.002
[13] Takahashi, JS (2017). Transcriptional architecture of the mammalian circadian clock. Nature reviews. Genetics, 18(3), 164-179. https://doi.org/10.1038/nrg.2016.150
[14] Pauli, C, Hopkins, BD, Prandi, D, Shaw, R, Fedrizzi, T, Sboner, A, Sailer, V, Augello, M, Puca, L, Rosati, R, McNary, TJ, Churakova, Y, Cheung, C, Triscott, J, Pisapia, D, Rao, R, Mosquera, JM, Robinson, B, Faltas, BM, ... Rubin, MA (2017). Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine. Cancer discovery, 7(5), 462-477. https://doi.org/10.1158/2159-8290.CD-16-1154
[15] Jiang, F., Hu, Y., Liu, X., Wang, M., & Wu, C. (2022). Methylation Pattern Mediated by m(6)A Regulator and Tumor Microenvironment Invasion in Lung Adenocarcinoma. Oxid Med Cell Longev, 2022, 2930310. https://doi.org/10.1155/2022/2930310
[16] Herbst, RS, Baas, P, Kim, DW, Felip, E, Pérez-Gracia, JL, Han, JY, Molina, J, Kim, JH, Arvis, CD, Ahn, MJ, Majem, M, Fidler, MJ, de Castro, G, Garrido, M, Lubiniecki, GM, Shentu, Y, Im, E, Dolled-Filhart, M, & Garon, EB (2016). Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet (London, England), 387(10027), 1540-1550. https://doi.org/10.1016/S0140-6736(15)01281-7
[17] Tan, CS, Kumarakulasinghe, NB, Huang, YQ, Ang, YLE, Choo, JR, Goh, BC, & Soo, RA (2018). Third generation EGFR TKIs: current data and future directions. Molecular cancer, 17(1), 29. https://doi.org/10.1186/s12943-018-0778-0
[18] He, L, Fan, Y, Zhang, Y, Tu, T, Zhang, Q, Yuan, F, & Cheng, C (2022). Single-cell transcriptomic analysis reveals circadian rhythm disruption associated with poor prognosis and drug-resistance in lung adenocarcinoma. Journal of pineal research, 73(1), e12803. https://doi.org/10.1111/jpi.12803
[19] Brunet, JP, Tamayo, P, Golub, TR, & Mesirov, JP (2004). Metagenes and molecular pattern discovery using matrix factorization. Proceedings of the National Academy of Sciences of the United States of America, 101(12), 4164-9. https://doi.org/10.1073/pnas.0308531101
[20] Hoshida, Y (2010). Nearest template prediction: a single-sample-based flexible class prediction with confidence assessment. PloS one, 5(11), e15543. https://doi.org/10.1371/journal.pone.0015543
[21] Zhang, G., Liu, Z., Deng, J., Liu, L., Li, Y., & Weng, S. (2022). Smooth muscle cell fate decisions decipher a high-resolution heterogeneity within atherosclerosis molecular subtypes. J Transl Med, 20(1), 568. https://doi.org/10.1186/s12967-022-03738-4
[22] Li, D, Zhang, G, Wang, Z, Guo, J, Liu, Y, Lu, Y, Qin, Z, Xu, Y, Cao, C, Wang, B, Guo, Q, Wang, Y, Liu, G, Cui, X, Zhang, J, & Tang, J (2023). Idebenone attenuates ferroptosis by inhibiting excessive autophagy via the ROS-AMPK-mTOR pathway to preserve cardiac function after myocardial infarction. European journal of pharmacology, 943, 175569. https://doi.org/10.1016/j.ejphar.2023.175569
[23] Shinohara, S, Takahashi, Y, Komuro, H, Matsui, T, Sugita, Y, Demachi-Okamura, A, Muraoka, D, Takahara, H, Nakada, T, Sakakura, N, Masago, K, Miyai, M, Nishida, R, Shomura, S, Shigematsu, Y, Hatooka, S, Sasano, H, Watanabe, F, Adachi, K, ... Matsushita, H (2022). New evaluation of the tumor immune microenvironment of non-small cell lung cancer and its association with prognosis. Journal for immunotherapy of cancer, 10(4). https://doi.org/10.1136/jitc-2021-003765
[24] Thorsson, V, Gibbs, DL, Brown, SD, Wolf, D, Bortone, DS, Ou Yang, TH, Porta-Pardo, E, Gao, GF, Plaisier, CL, Eddy, JA, Ziv, E, Culhane, AC, Paull, EO, Sivakumar, IKA, Gentles, AJ, Malhotra, R, Farshidfar, F, Colaprico, A, Parker, JS, ... Shmulevich, I (2019). The Immune Landscape of Cancer. Immunity, 51(2), 411-412. https://doi.org/10.1016/j.immuni.2019.08.004
[25] Liu, L, Liu, Z, Gao, J, Liu, X, Weng, S, Guo, C, Hu, B, Wang, Z, Zhang, J, Shi, J, Guo, W, & Zhang, S (2022). CD8+ T cell trajectory subtypes decode tumor heterogeneity and provide treatment recommendations for hepatocellular carcinoma. Frontiers in immunology, 13, 964190. https://doi.org/10.3389/fimmu.2022.964190
[26] Li, L, Li, M, & Wang, X (2020). Cancer type-dependent correlations between TP53 mutations and antitumor immunity. DNA repair, 88, 102785. https://doi.org/10.1016/j.dnarep.2020.102785
[27] Chen, H, Carrot-Zhang, J, Zhao, Y, Hu, H, Freeman, SS, Yu, S, Ha, G, Taylor, AM, Berger, AC, Westlake, L, Zheng, Y, Zhang, J, Ramachandran, A, Zheng, Q, Pan, Y, Zheng, D, Zheng, S, Cheng, C, Kuang, M, ... Meyerson, M (2019). Genomic and immune profiling of pre-invasive lung adenocarcinoma. Nature communications, 10(1), 5472. https://doi.org/10.1038/s41467-019-13460-3
[28] Chen, Y, Chen, G, Li, J, Huang, YY, Li, Y, Lin, J, Chen, LZ, Lu, JP, Wang, YQ, Wang, CX, Pan, LK, Xia, XF, Yi, X, Chen, CB, Zheng, XW, Guo, ZQ, & Pan, JJ (2019). Association of Tumor Protein p53 and Ataxia-Telangiectasia Mutated Comutation With Response to Immune Checkpoint Inhibitors and Mortality in Patients With Non-Small Cell Lung Cancer. JAMA network open, 2(9), e1911895. https://doi.org/10.1001/jamanetworkopen.2019.11895
[29] Davoli, T, Uno, H, Wooten, EC, & Elledge, SJ (2017). Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy. Science (New York, N.Y.), 355(6322). https://doi.org/10.1126/science.aaf8399
[30] Chen, E., Zhang, J., Xu, S., Zhu, X., & Hu, H. (2017). Long non-coding RNA DGCR5 is involved in the regulation of proliferation, migration and invasion of lung cancer by targeting miR-1180. Am J Cancer Res, 7(7), 1463-75. https://doi.org/10.7150/jca.34585
[31] Ma, B, Geng, Y, Meng, F, Yan, G, & Song, F (2020). Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method. Journal of Cancer, 11(5), 1288-1298. https://doi.org/10.7150/jca.34585
[32] He, D, Wang, D, Lu, P, Yang, N, Xue, Z, Zhu, X, Zhang, P, & Fan, G (2021). Single-cell RNA sequencing reveals heterogeneous tumor and immune cell populations in early-stage lung adenocarcinomas harboring EGFR mutations. Oncogene, 40(2), 355-368. https://doi.org/10.1038/s41388-020-01528-0
[33] Malik, S., Stokes Iii, J., Manne, U., Singh, R., & Mishra, M. (2022). Understanding the significance of biological clock and its impact on cancer incidence. Cancer Lett, 527, 80-94. https://doi.org/10.1016/j.canlet.2021.12.013
[34] Liu, Y, Wang, X, Wang, G, Yang, Y, Yuan, Y, & Ouyang, L (2019). The past, present and future of potential small-molecule drugs targeting p53-MDM2/MDMX for cancer therapy. European journal of medicinal chemistry, 176, 92-104. https://doi.org/10.1016/j.ejmech.2019.05.018
[35] Liu, Z., Weng, S., Xu, H., Wang, L., Liu, L., & Zhang, Y. (2021). Computational Recognition and Clinical Verification of TGF-beta-Derived miRNA Signature With Potential Implications in Prognosis and Immunotherapy of Intrahepatic Cholangiocarcinoma. Front Oncol, 11, 757919. https://doi.org/10.3389/fonc.2021.757919
[36] Long, J, Wang, A, Bai, Y, Lin, J, Yang, X, Wang, D, Yang, X, Jiang, Y, & Zhao, H (2019). Development and validation of a TP53-associated immune prognostic model for hepatocellular carcinoma. EBioMedicine, 42, 363-374. https://doi.org/10.1016/j.ebiom.2019.03.022
[37] Rowshanravan, B, Halliday, N, & Sansom, DM (2018). CTLA-4: a moving target in immunotherapy. Blood, 131(1), 58-67. https://doi.org/10.1182/blood-2017-06-741033
[38] Han, Y., Liu, D., & Li, L. (2020). PD-1/PD-L1 pathway: current researches in cancer. Am J Cancer Res, 10(3), 727-42. https://doi.org/10.1001/jamanetworkopen.2019.11895
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The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.
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