In-silico identification of therapeutic targets in pancreatic ductal adenocarcinoma using WGCNA and Trader

Luo, W., Tao, J., Zheng, L. & Zhang, T. Current epidemiology of pancreatic cancer: Challenges and opportunities. Chin. J. Cancer Res. 32, 705 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Singhi, A. D. & Wood, L. D. Early detection of pancreatic cancer using DNA-based molecular approaches. Nat. Rev. Gastroenterol. Hepatol. 18, 457–468 (2021).Article 
CAS 
PubMed 

Google Scholar 
Mizrahi, J. D., Surana, R., Valle, J. W. & Shroff, R. T. Pancreatic cancer. Lancet 395, 2008–2020 (2020).Article 
CAS 
PubMed 

Google Scholar 
McGuigan, A. et al. Pancreatic cancer: A review of clinical diagnosis, epidemiology, treatment and outcomes. World J. Gastroenterol. 24, 4846 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Jagadeesan, B., Haran, P. H., Praveen, D., Chowdary, P. R. & Aanandhi, M. V. A comprehensive review on pancreatic cancer. Res. J. Pharm. Technol. 14, 552–554 (2021).Article 

Google Scholar 
Wood, L. D., Canto, M. I., Jaffee, E. M. & Simeone, D. M. Pancreatic cancer: Pathogenesis, screening, diagnosis and treatment. Gastroenterology (2022).Lanfredini, S., Thapa, A. & O’Neill, E. RAS in pancreatic cancer. Biochem. Soc. Trans. 47, 961–972 (2019).Article 
CAS 
PubMed 

Google Scholar 
Goral, V. Pancreatic cancer: Pathogenesis and diagnosis. Asian Pac. J. Cancer Prevent. 16, 5619–5624 (2015).Article 

Google Scholar 
Jin, C. & Bai, L. Pancreatic cancer—current situation and challenges. Gastroenterol. Hepatol. Lett. 2, 1–3 (2020).Article 

Google Scholar 
Hruban, R. H., Maitra, A. & Goggins, M. Update on pancreatic intraepithelial neoplasia. Int. J. Clin. Exp. Pathol. 1, 306 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
Hidalgo, M. Pancreatic cancer. N. Engl. J. Med. 362, 1605–1617 (2010).Article 
CAS 
PubMed 

Google Scholar 
Feldmann, G., Beaty, R., Hruban, R. H. & Maitra, A. Molecular genetics of pancreatic intraepithelial neoplasia. J. Hepato Biliary Pancreatic Surg. 14, 224–232 (2007).Article 

Google Scholar 
Zhao, Z. & Liu, W. Pancreatic cancer: A review of risk factors, diagnosis, and treatment. Technol. Cancer Res. Treat. 19, 1533033820962117 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Canto, M. I. et al. Surgical outcomes after pancreatic resection of screening-detected lesions in individuals at high risk for developing pancreatic cancer. J. Gastrointest. Surg. 24, 1101–1110 (2020).Article 
PubMed 

Google Scholar 
Gholaminejad, A., Ghaeidamini, M., Simal-Gandara, J. & Roointan, A. An integrative in silico study to discover key drivers in pathogenicity of focal and segmental glomerulosclerosis. Kidney Blood Press. Res. 1–13 (2022).Ajucarmelprecilla, A. et al. In silico identification of hub genes as observing biomarkers for gastric cancer metastasis. Evid. Based Complement. Altern. Med. 6316158. https://doi.org/10.1155/2022/6316158 (2022).Gholaminejad, A., Gheisari, Y., Jalali, S. & Roointan, A. Comprehensive analysis of IgA nephropathy expression profiles: Identification of potential biomarkers and therapeutic agents. BMC Nephrol. 22, 1–10 (2021).Article 

Google Scholar 
Roointan, A., Gheisari, Y., Hudkins, K. L. & Gholaminejad, A. Non-invasive metabolic biomarkers for early diagnosis of diabetic nephropathy: Meta-analysis of profiling metabolomics studies. Nutr. Metab. Cardiovasc. Dis. 31, 2253–2272 (2021).Article 
CAS 
PubMed 

Google Scholar 
Zhou, W. et al. Identification of key genes involved in pancreatic ductal adenocarcinoma with diabetes mellitus based on gene expression profiling analysis. Pathol. Oncol. Res. 27, 604730 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Ullah, M. A., Sarkar, B. & Akter, F. Prediction of biomarker signatures and therapeutic agents from blood sample against pancreatic ductal adenocarcinoma (PDAC): A network-based study. Inform. Medi. Unlocked 19, 100346. https://doi.org/10.1016/j.imu.2020.100346 (2020).Article 

Google Scholar 
Masoudi-Sobhanzadeh, Y., Gholaminejad, A., Gheisari, Y. & Roointan, A. Discovering driver nodes in chronic kidney disease-related networks using Trader as a newly developed algorithm. Comput. Biol. Med. 148, 105892 (2022).Article 
PubMed 

Google Scholar 
Masoudi-Sobhanzadeh, Y., Omidi, Y., Amanlou, M. & Masoudi-Nejad, A. Trader as a new optimization algorithm predicts drug-target interactions efficiently. Sci. Rep. 9, 9348 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Xie, Y.-G. et al. FYN promotes breast cancer progression through epithelial-mesenchymal transition. Oncol. Rep. 36, 1000–1006 (2016).Article 
CAS 
PubMed 

Google Scholar 
Comba, A. et al. Fyn tyrosine kinase, a downstream target of receptor tyrosine kinases, modulates antiglioma immune responses. Neuro-oncology 22, 806–818 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Du, Y. et al. MicroRNA-143 targets MAPK3 to regulate the proliferation and bone metastasis of human breast cancer cells. Amb. Express 10, 1–8 (2020).Article 

Google Scholar 
Pandey, K. et al. Combined CDK2 and CDK4/6 inhibition overcomes palbociclib resistance in breast cancer by enhancing senescence. Cancers 12, 3566 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lan, Y. et al. Downregulation of SNRPG induces cell cycle arrest and sensitizes human glioblastoma cells to temozolomide by targeting Myc through a p53-dependent signaling pathway. Cancer Biol. Med. 17, 112 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lai, J., Zeng, X., Yu, X. & Ye, J. GNAQ affects the occurrence and development of gastric cancer through the P53/P21 and MEK/ERK pathways. Acta Med. Mediterr. 35, 2139–2143 (2019).
Google Scholar 
Wang, K. et al. Inhibition of PAK1 suppresses pancreatic cancer by stimulation of anti-tumour immunity through down-regulation of PD-L1. Cancer Lett. 472, 8–18 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Butler, L. M. et al. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention. Adv. Drug Deliv. Rev. 159, 245–293 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zhao, H. et al. High expression of LC3B is associated with progression and poor outcome in triple-negative breast cancer. Med. Oncol. 30, 1–8 (2013).
Google Scholar 
Lazova, R. et al. Punctate LC3B expression is a common feature of solid tumors and associated with proliferation, metastasis, and poor outcome autophagy in solid malignancies. Clin. Cancer Res. 18, 370–379 (2012).Article 
CAS 
PubMed 

Google Scholar 
Ma, X. et al. Mir-486-5p inhibits cell growth of papillary thyroid carcinoma by targeting fibrillin-1. Biomed. Pharmacother. 80, 220–226 (2016).Article 
CAS 
PubMed 

Google Scholar 
Wang, Z. et al. Fibrillin-1, induced by Aurora-A but inhibited by BRCA2, promotes ovarian cancer metastasis. Oncotarget 6, 6670 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Kroes, R. A. et al. The identification of novel therapeutic targets for the treatment of malignant brain tumors. Cancer Lett. 156, 191–198 (2000).Article 
CAS 
PubMed 

Google Scholar 
Li, T. et al. S100A16 induces epithelial-mesenchymal transition in human PDAC cells and is a new therapeutic target for pancreatic cancer treatment that synergizes with gemcitabine. Biochem. Pharmacol. 189, 114396 (2021).Article 
CAS 
PubMed 

Google Scholar 
Lee, Y. T., Tan, Y. J. & Oon, C. E. Molecular targeted therapy: Treating cancer with specificity. Eur. J. Pharmacol. 834, 188–196 (2018).Article 
CAS 
PubMed 

Google Scholar 
Yan, J., Risacher, S. L., Shen, L. & Saykin, A. J. Network approaches to systems biology analysis of complex disease: Integrative methods for multi-omics data. Briefings Bioinform. 19, 1370–1381 (2018).CAS 

Google Scholar 
Veenstra, T. D. Omics in systems biology: Current progress and future outlook. Proteomics 21, 2000235 (2021).Article 
CAS 

Google Scholar 
Liu, C. et al. Computational network biology: Data, models, and applications. Phys. Rep. 846, 1–66 (2020).Article 
ADS 
MathSciNet 

Google Scholar 
Green, S. et al. Network analyses in systems biology: New strategies for dealing with biological complexity. Synthese 195, 1751–1777 (2018).Article 
MathSciNet 

Google Scholar 
Tomkins, J. E. & Manzoni, C. Advances in protein-protein interaction network analysis for Parkinson’s disease. Neurobiol. Dis. 155, 105395 (2021).Article 
CAS 
PubMed 

Google Scholar 
Buphamalai, P., Kokotovic, T., Nagy, V. & Menche, J. Network analysis reveals rare disease signatures across multiple levels of biological organization. Nat. Commun. 12, 1–15 (2021).Article 

Google Scholar 
Prasad, K., AlOmar, S. Y., Alqahtani, S. A. M., Malik, M. & Kumar, V. Brain disease network analysis to elucidate the neurological manifestations of COVID-19. Mol. Neurobiol. 58, 1875–1893 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Das, M., Alphonse, P. & Kamalanathan, S. In 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 855–860 (IEEE, 2021).Dilmaghani, S. et al. From communities to protein complexes: A local community detection algorithm on PPI networks. Plos One 17, e0260484 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hu, L., Zhang, J., Pan, X., Luo, X. & Yuan, H. An effective link-based clustering algorithm for detecting overlapping protein complexes in protein-protein interaction networks. IEEE Trans. Netw. Sci. Eng. 8, 3275–3289 (2021).Article 

Google Scholar 
Langfelder, P. & Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinform. 9, 1–13 (2008).Article 

Google Scholar 
Giulietti, M., Righetti, A., Principato, G. & Piva, F. LncRNA co-expression network analysis reveals novel biomarkers for pancreatic cancer. Carcinogenesis 39, 1016–1025 (2018).Article 
CAS 
PubMed 

Google Scholar 
Gholaminejad, A., Fathalipour, M. & Roointan, A. Comprehensive analysis of diabetic nephropathy expression profile based on weighted gene co-expression network analysis algorithm. BMC Nephrol. 22, 1–13 (2021).Article 

Google Scholar 
Gholaminejad, A., Roointan, A. & Gheisari, Y. Transmembrane signaling molecules play a key role in the pathogenesis of IgA nephropathy: A weighted gene co-expression network analysis study. BMC Immunol. 22, 1–17 (2021).Article 

Google Scholar 
Yin, X. et al. Identification of key modules and genes associated with breast cancer prognosis using WGCNA and ceRNA network analysis. Aging (Albany NY) 13, 2519 (2021).Article 
CAS 

Google Scholar 
Ding, M., Li, F., Wang, B., Chi, G. & Liu, H. A comprehensive analysis of WGCNA and serum metabolomics manifests the lung cancer-associated disordered glucose metabolism. J. Cell. Biochem. 120, 10855–10863 (2019).Article 
CAS 
PubMed 

Google Scholar 
Huang, C., Tong, Q., Zhang, W., Chen, X. & Pan, Z. WGCNA Reveal Potential Diagnosis Biomarkers and Therapeutic Targets for COVID-19 Infection in Patients with Sepsis (2022).Theodosiou, T. et al. The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks. BMC Res. Notes 10, 1–9 (2017).Article 

Google Scholar 
Nowakowska, A. W. & Kotulska, M. Topological analysis as a tool for detection of abnormalities in protein–protein interaction data. Bioinformatics 38, 3968–3975 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sanchez, R. & Mackenzie, S. A. Integrative network analysis of differentially methylated and expressed genes for biomarker identification in leukemia. Sci. Rep. 10, 1–16 (2020).Article 

Google Scholar 
Sharma, P., Bhattacharyya, D. K. & Kalita, J. K. In 2016 International Conference on Accessibility to Digital World (ICADW) 135–140 (IEEE).Ren, J., Wang, J., Li, M. & Wu, F. Discovering essential proteins based on PPI network and protein complex. Int. J. Data Min. Bioinform. 12, 24–43 (2015).Article 
PubMed 

Google Scholar 
Li, Y., Zeng, M., Zhang, F., Wu, F.-X. & Li, M. DeepCellEss: Cell line-specific essential protein prediction with attention-based interpretable deep learning. Bioinformatics (2022).Elebo, N., Fru, P., Omoshoro–Jones, J., Candy, Patrick & Nweke, E. E. Role of different immune cells and metabolic pathways in modulating the immune response in pancreatic cancer. Mol. Med. Rep. 22, 4981–4991 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Tjomsland, V. et al. Pancreatic adenocarcinoma exerts systemic effects on the peripheral blood myeloid and plasmacytoid dendritic cells: An indicator of disease severity?. BMC Cancer 10, 1–14 (2010).Article 

Google Scholar 
Karamitopoulou, E. Tumour microenvironment of pancreatic cancer: Immune landscape is dictated by molecular and histopathological features. Br. J. Cancer 121, 5–14 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Haqq, J. et al. Pancreatic stellate cells and pancreas cancer: Current perspectives and future strategies. Eur. J. Cancer 50, 2570–2582 (2014).Article 
PubMed 

Google Scholar 
Spranger, S. & Gajewski, T. F. Impact of oncogenic pathways on evasion of antitumour immune responses. Nat. Rev. Cancer 18, 139–147 (2018).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Deng, Y. et al. Glucocorticoid receptor regulates PD-L1 and MHC-I in pancreatic cancer cells to promote immune evasion and immunotherapy resistance. Nat. Commun. 12, 7041. https://doi.org/10.1038/s41467-021-27349-7 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Zubor, P. et al. Rho GTPases in gynecologic cancers: In-depth analysis toward the paradigm change from reactive to predictive, preventive, and personalized medical approach benefiting the patient and healthcare. Cancers 12, 1292 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Rodenburg, W. S. & van Buul, J. D. Rho GTPase signalling networks in cancer cell transendothelial migration. Vasc. Biol. 3, R77–R95 (2021).PubMed 
PubMed Central 

Google Scholar 
Ryan, D. P., Hong, T. S. & Bardeesy, N. Pancreatic adenocarcinoma. N. Engl. J. Med. 371, 1039–1049 (2014).Article 
CAS 
PubMed 

Google Scholar 
Kimmelman, A. C. et al. Genomic alterations link Rho family of GTPases to the highly invasive phenotype of pancreas cancer. Proc. Natl. Acad. Sci. 105, 19372–19377 (2008).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Melzer, C., Hass, R., von der Ohe, J., Lehnert, H. & Ungefroren, H. The role of TGF-β and its crosstalk with RAC1/RAC1b signaling in breast and pancreas carcinoma. Cell Commun. Signal. 15, 1–11 (2017).Article 

Google Scholar 
Taniuchi, K. et al. Overexpressed P-cadherin/CDH3 promotes motility of pancreatic cancer cells by interacting with p120ctn and activating rho-family GTPases. Cancer Res. 65, 3092–3099 (2005).Article 
CAS 
PubMed 

Google Scholar 
Rane, C. K. & Minden, A. In Seminars in Cancer Biology 40–49 (Elsevier).Kalli, M., Li, R., Mills, G. B., Stylianopoulos, T. & Zervantonakis, I. K. Mechanical stress signaling in pancreatic Cancer cells triggers p38 MAPK-and JNK-dependent cytoskeleton remodeling and promotes cell migration via Rac1/cdc42/Myosin IIMechanical stress–induced adaptation in pancreatic cancer cells. Mol. Cancer Res. OF1-OF13 (2022).Crosas-Molist, E. et al. Rho GTPase signaling in cancer progression and dissemination. Physiol. Rev. 102, 455–510 (2022).Article 
CAS 
PubMed 

Google Scholar 
Chetty, A. K., Ha, B. H. & Boggon, T. J. Rho family GTPase signaling through type II p21-activated kinases. Cell. Mol. Life Sci. 79, 1–16 (2022).Article 

Google Scholar 
Manser, E., Leung, T., Salihuddin, H., Zhao, Z.-s & Lim, L. A brain serine/threonine protein kinase activated by Cdc42 and Rac1. Nature 367, 40–46 (1994).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Mira, J.-P., Benard, V., Groffen, J., Sanders, L. C. & Knaus, U. G. Endogenous, hyperactive Rac3 controls proliferation of breast cancer cells by a p21-activated kinase-dependent pathway. Proc. Natl. Acad. Sci. 97, 185–189 (2000).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Yao, D. et al. P21-Activated kinase 1: Emerging biological functions and potential therapeutic targets in Cancer. Theranostics 10, 9741 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Guo, P. et al. p21-activated kinase 1 (PAK1) as a therapeutic target for cardiotoxicity. Arch. Toxicol. 1–20 (2022).Nickols, N. G. et al. MEK-ERK signaling is a therapeutic target in metastatic castration resistant prostate cancer. Prostate Cancer Prostatic Dis. 22, 531–538 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Adamia, S. et al. Combination therapy targeting Erk1/2 and CDK4/6i in relapsed refractory multiple myeloma. Leukemia 36, 1088–1101 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ku, M.-C. et al. ERK1 as a therapeutic target for dendritic cell vaccination against high-grade gliomastargeting ERK1 in DC vaccines for glioma. Mol. Cancer Therap. 15, 1975–1987 (2016).Article 
CAS 

Google Scholar 
Huang, L. et al. Correlation of tumor-infiltrating immune cells of melanoma with overall survival by immunogenomic analysis. Cancer Med. 9, 8444–8456 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Niu, J. et al. Identification of potential therapeutic targets and immune cell infiltration characteristics in osteosarcoma using bioinformatics strategy. Front. Oncol. 10, 1628 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Szklarczyk, D. et al. STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613 (2019).Article 
PubMed 

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

Google Scholar 
Bindea, G. et al. ClueGO: A cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25, 1091–1093 (2009).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Uhlen, M. et al. Towards a knowledge-based human protein atlas. Nat. Biotechnol. 28, 1248–1250 (2010).Article 
CAS 
PubMed 

Google Scholar 
Chandrashekar, D. S. et al. An update to the integrated cancer data analysis platform. Neoplasia 25, 18–27 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Li, T. et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucl. Acids Res. 48, W509–W514 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Freshour, S. L. et al. Integration of the drug–gene Interaction Database (DGIdb 4.0) with open crowdsource efforts. Nucl. Acids Res. 49, D1144–D1151 (2021).Article 
PubMed 

Google Scholar