ArticlePloS one2016
Systems Biology Approaches for the Prediction of Possible Role of Chlamydia pneumoniae Proteins in the Etiology of Lung Cancer.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Pathogenesis of various pulmonary diseases by tuning immune response: insight from host-microbial crosstalk.Current research in microbial sciences · 2026Review
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- scLTF: A self-training clustering framework for large-scale single-cell RNA-Seq data.PloS one · 2026Article
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- Contrastive hypergraph collaborative filtering for transfer RNA-disease association prediction.Briefings in bioinformatics · 2025Article
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- scATD: a high-throughput and interpretable framework for single-cell cancer drug resistance prediction and biomarker identification.Briefings in bioinformatics · 2025Article
- Curcumin-gold nanoshell mediated near-infrared irradiation on human ovarian cancer cell: in vitro study.Medical oncology (Northwood, London, England) · 2025Article
- PathSynergy: a deep learning model for predicting drug synergy in liver cancer.Briefings in bioinformatics · 2025Article
- Scaling up drug combination surface prediction.Briefings in bioinformatics · 2025Article
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Corrections and comments
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Authors and funding
5 authors.
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Abstract
Accumulating evidence has recently supported the association of bacterial infection with the growth and development of cancers, particularly in organs that are constantly exposed to bacteria such as the lungs, colon, cervical cancer etc. Our in silico study on the proteome of Chlamydia pneumoniae suggests an unprecedented idea of the etiology of lung cancer and have revealed that the infection of C. pneumoniae is associated with lung cancer development and growth. It is reasonable to assume that C. pneumoniae transports its proteins within host-intracellular organelles during infection, where they may work with host-cell proteome. The current study was performed for the prediction of nuclear targeting protein of C. pneumoniae in the host cell using bioinformatics predictors including ExPASy pI/Mw tool, nuclear localization signal (NLS) mapper, balanced sub cellular localization predictor (BaCeILo), and Hum-mPLoc 2.0. We predicted 47/1112 nuclear-targeting proteins of C. pneumoniae connected with several possible alterations in host replication and transcription during intracellular infection. These nuclear-targeting proteins may direct to competitive interactions of host and C. pneumoniae proteins with the availability of same substrate and may be involved as etiological agents in the growth and development of lung cancer. These novel findings are expected to access in better understanding of lung cancer etiology and identifying molecular targets for therapy.
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