Comprehensive transcriptome, miRNA and kinome profiling identifies new treatment options for personalized lung cancer therapy

Abstract

Background: Basic research identified oncogenic driver mutations in lung cancer (LC). However, <10% of patients carry driver mutations. Thus, most patients are not recommended for first-line kinase inhibitor (KI)–based therapies. Through enabling technologies and bioinformatics, we gained deep insight into patient-specific signalling networks which permitted novel KI-based treatment options in LC.

Methods: We performed molecular pathology, transcriptomics and miRNA profiling across 95 well-characterized LC patients. We confirmed results based on cross-linked immunoprecipitation-sequencing data, and used N = 524 adeno- and 497 squamous cell carcinomas as validation sets. We employed the PamGene platform to identify aberrant kinases, validated the results by evaluating independent siRNA and CRISPR-mediated mRNA knockdown studies in human LC cell lines.

Results: Transcriptomics revealed 439, 1240, 383 and 320 significantly upregulated genes, respectively, for adeno-, squamous, neuroendocrine and metastatic cases, and there are 1092, 1477, 609 and 1267 downregulated DEGs. Based on gene enrichment analysis and experimentally validated miRNA–gene interactions, we constructed regulatory networks specific for adeno-, squamous, neuroendocrine and metastatic LC. Molecular profiling discovered 137 significantly upregulated kinases (range 2–26-fold) of which 65 and 72, respectively, are tyrosine and serine-threonine kinases while 6 kinases carry driver mutations. Meanwhile, there are 21 kinases commonly upregulated irrespective of the histological type of LC. Bioinformatics decoded networks in which kinases function as master regulators. Typically, the networks consisted of 14, 9, 16 and 19 highly regulated kinases in adeno-, squamous, neuroendocrine and metastatic LC. Inhibition of kinases which function as master regulators disrupted the signalling networks, and their gene knock-down studies confirmed inhibition of cell proliferation in a panel of human LC cell lines. Additionally, the proposed molecular profiling enables KI-based therapies in patients with acquired drug resistance.

Conclusions: Our study broadens the perspective of KI-based therapies in LC, and we propose a framework to overcome acquired drug resistance.

Keywords

kinase inhibitor / lung cancer / neoadjuvant therapy / precision medicine

References

[1] Casal-Mouriño A, Ruano-Ravina A, Lorenzo-González M, et al. Epidemiology of stage III lung cancer: frequency, diagnostic characteristics, and survival. Transl Lung Cancer Res. 2021;10(1):506-518.

[2] Godoy LA, Chen J, Ma W, et al. Emerging precision neoadjuvant systemic therapy for patients with resectable non-small cell lung cancer: current status and perspectives. Biomark Res. 2023;11(1):7.

[3] Bao Y, Gu C, Xie H, et al. Comprehensive study of neoadjuvant targeted therapy for resectable non-small cell lung cancer. Ann Transl Med. 2021;9(6):493-1134.

[4] Osmani L, Askin F, Gabrielson E, Li QK. Current WHO guidelines and the critical role of immunohistochemical markers in the subclassification of non-small cell lung carcinoma (NSCLC):moving from targeted therapy to immunotherapy. Semin Cancer Biol. 2018;52(pt 1):103-109.

[5] Chan BA, Hughes BGM. Targeted therapy for non-small cell lung cancer: current standards and the promise of the future. Transl Lung Cancer Res. 2015;4(1):36-54. doi:10.3978/j.issn.2218-6751.2014.05.01

[6] Skoulidis F, Heymach JV. Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat Rev Cancer. 2019;19(9):495-509.

[7] Kris MG, Johnson BE, Berry LD, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA. 2014;311(19):1998-2006.

[8] Bodor JN, Kasireddy V, Borghaei H. First-line therapies for metastatic lung adenocarcinoma without a driver mutation. J Oncol Pract. 2018;14(9):529-535.

[9] Roberts TJ, Kehl KL, Brooks GA, et al. Practice-level variation in molecular testing and use of targeted therapy for patients with non-small cell lung cancer and colorectal cancer. JAMA Netw Open. 2023;6(4):e2310809.

[10] Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. 2022;12(1):31-46.

[11] Roskoski RJ. Properties of FDA-approved small molecule protein kinase inhibitors: a 2023 update. Pharmacol Res. 2023;187:106552.

[12] Zhong S, Golpon H, Zardo P, Borlak J. miRNAs in lung cancer. A systematic review identifies predictive and prognostic miRNA candidates for precision medicine in lung cancer. Transl Res. 2021;230:164-196.

[13] Pradhan M, Chocry M, Gibbons DL, Sepesi B, Cascone T. Emerging biomarkers for neoadjuvant immune checkpoint inhibitors in operable non-small cell lung cancer. Transl Lung Cancer Res. 2021;10(1):590-606.

[14] Chirumamilla CS, Fazil MHUT, Perez-Novo C, et al. Profiling activity of cellular kinases in migrating T-cells. Methods Mol Biol. 2019;1930:99-113.

[15] Colaprico A, Silva TC, Olsen C, et al. TCGAbiolinks: an R/bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 2016;44(8):e71.

[16] Ritchie ME, Phipson B, Wu D, et al. LIMMA powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.

[17] R Core Team. R: a language and environment for statistical computing. 2022. https://www.R-project.org/

[18] Chang L, Zhou G, Soufan O, Xia J. miRNet 2.0:network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Res. 2020;48:W244-W251.

[19] Otasek D, Morris JH, Bouças J, Pico AR, Demchak B. Cytoscape automation: empowering workflow-based network analysis. Genome Biol. 2019;20(1):185.

[20] Kel A, Voss N, Jauregui R, Kel-Margoulis O, Wingender E. Beyond microarrays: find key transcription factors controlling signal transduction pathways. BMC Bioinformatics. 2006;7(suppl 2):S13.

[21] Krull M, Pistor S, Voss N, et al. TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations. Nucleic Acids Res. 2006;34(Database issue):546.

[22] Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.

[23] Humphreys JM, Piala AT, Akella R, He H, Goldsmith EJ. Precisely ordered phosphorylation reactions in the p38 mitogen-activated protein (MAP) kinase cascade. J Biol Chem. 2013;288(32):23322-23330.

[24] Shah K, Al-Haidari A, Sun J, Kazi JU. T cell receptor (TCR) signaling in health and disease. Signal Transduct Target Ther. 2021;6(1):412.

[25] Wu W, Zhou Q, Masubuchi T, et al. Multiple signaling roles of CD3ϵ and its application in CAR-T cell therapy. Cell. 2020;182(4):855-871.e23.

[26] Lorenz U. SHP-1 and SHP-2 in T cells: two phosphatases functioning at many levels. Immunol Rev. 2009;228(1):342-359.

[27] Zhang SQ, Yang W, Kontaridis MI, et al. Shp2 regulates SRC family kinase activity and RAS/ERK activation by controlling CSK recruitment. Mol Cell. 2004;13(3):341-355.

[28] Kim YJ, Sekiya F, Poulin B, Bae YS, Rhee SG. Mechanism of B-cell receptor-induced phosphorylation and activation of phospholipase C-gamma2. Mol Cell Biol. 2004;24(22):9986-9999.

[29] Yang WC, Ghiotto M, Barbarat B, Olive D. The role of tec protein-tyrosine kinase in T cell signaling. J Biol Chem. 1999;274(2):607-617.

[30] Fresno Vara JA, Casado E, de Castro J, Cejas P, Belda-Iniesta C, González-Barón M. PI3K/Akt signalling pathway and cancer. Cancer Treat Rev. 2004;30(2):193-204.

[31] Deneka A, Korobeynikov V, Golemis EA. Embryonal Fyn-associated substrate (EFS) and CASS4:the lesser-known CAS protein family members. Gene. 2015;570(1):25-35.

[32] Huang Y, Clarke F, Karimi M, et al. CRK proteins selectively regulate T cell migration into inflamed tissues. J Clin Invest. 2015;125(3):1019-1032.

[33] Niu Z, Jin R, Zhang Y, Li H. Signaling pathways and targeted therapies in lung squamous cell carcinoma: mechanisms and clinical trials. Signal Transduct Target Ther. 2022;7(1):353.

[34] Campbell J, Ryan CJ, Brough R, et al. Large-scale profiling of kinase dependencies in cancer cell lines. Cell Rep. 2016;14(10):2490-2501.

[35] Tsherniak A, Vazquez F, Montgomery PG, et al. Defining a cancer dependency map. Cell. 2017;170(3):564-576.e16.

[36] Qin A, Reddy HG, Weinberg FD, Kalemkerian GP. Cyclin-dependent kinase inhibitors for the treatment of lung cancer. Expert Opin Pharmacother. 2020;21(8):941-952.

[37] Vansteenkiste J, Wauters E. Tyrosine kinase inhibition of EGFR: a successful history of targeted therapy for NSCLC since 20 years. Ann Oncol 2018;29(suppl_1):i1-i2.

[38] Bhullar KS, Lagarón NO, McGowan EM, et al. Kinase-targeted cancer therapies: progress, challenges and future directions. Mol Cancer. 2018;17(1):48-42.

[39] Lindeman NI, Cagle PT, Aisner DL, et al. Updated molecular testing guideline for the selection of lung cancer patients for treatment with targeted tyrosine kinase inhibitors: guideline from the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology. J Mol Diagn. 2018;20(2):129-159.

[40] Cucurull M, Notario L, Sanchez-Cespedes M, et al. Targeting KRAS in lung cancer beyond KRAS G12C inhibitors: the immune regulatory role of KRAS and novel therapeutic strategies. Front Oncol. 2022;11:793121.

[41] Fu K, Xie F, Wang F, Fu L. Therapeutic strategies for EGFR-mutated non-small cell lung cancer patients with osimertinib resistance. J Hematol Oncol. 2022;15(1):173-174.

[42] Riudavets M, Sullivan I, Abdayem P, Planchard D. Targeting HER2 in non-small-cell lung cancer (NSCLC): a glimpse of hope? An updated review on therapeutic strategies in NSCLC harbouring HER2 alterations. ESMO Open. 2021;6(5):100260.

[43] Sforza V, Palumbo G, Cascetta P, et al. BRAF inhibitors in non-small cell lung cancer. Cancers. 2022;14(19):4863.

[44] Wolf J, Seto T, Han J, et al. Capmatinib in MET exon 14-mutated or MET-amplified non-small-cell lung cancer. N Engl J Med. 2020;383(10):944-957.

[45] Li B, Jin J, Guo D, Tao Z, Hu X. Immune checkpoint inhibitors combined with targeted therapy: the recent advances and future potentials. Cancers. 2023;15(10):2858.

[46] Yang JC, Gadgeel SM, Sequist LV, et al. Pembrolizumab in combination with erlotinib or gefitinib as first-line therapy for advanced NSCLC with sensitizing EGFR mutation. J Thorac Oncol. 2019;14(3):553-559.

[47] Chang W, Lin H, Chang T, Lin S, Li Y. Assessment of tyrosine kinase inhibitors and survival and cardiovascular outcomes of patients with non-small cell lung cancer in Taiwan. JAMA Netw Open. 2023;6(5):e2313824.

[48] Shyam Sunder S, Sharma UC, Pokharel S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management. Signal Transduct Target Ther. 2023;8(1):262.

[49] Pakkala S, Ramalingam SS. Personalized therapy for lung cancer: striking a moving target. JCI Insight. 2018;3(15):e120858.

[50] Rosenzweig SA. Acquired resistance to drugs targeting tyrosine kinases. Adv Cancer Res. 2018;138:71-98.

RIGHTS & PERMISSIONS

2025 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.