Viruses as key modulators of the TGF‐β pathway; a double‐edged sword involved in cancer

Mirzaei, Habibollah; Faghihloo, Ebrahim

doi:10.1002/rmv.1967

Cited by 45 publications

(30 citation statements)

References 113 publications

(300 reference statements)

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“…Of these enriched GO terms, 2 biological processes, 5 cellular components, and 8 molecular functions had a dispensability value of 0 (see details in Table S6). Our results support previous findings that suggest that lysosomal transport and viral processes mediate cell proliferation and apoptosis in cancer cells 36,37 by targeting cellular components such as the focal adhesions or retromer complex 38,39 .…”

Section: Resultssupporting

confidence: 92%

Edgetic perturbation signatures represent known and novel cancer biomarkers

Kataka

Zaucha

Frishman

et al. 2020

Sci Rep

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isoform switching is a recently characterized hallmark of cancer, and often translates to the loss or gain of domains mediating protein interactions and thus, the re-wiring of the interactome. Recent computational tools leverage domain-domain interaction data to resolve the condition-specific interaction networks from RnA-Seq data accounting for the domain content of the primary transcripts expressed. Here, we used The Cancer Genome Atlas RNA-Seq datasets to generate 642 patient-specific pairs of interactomes corresponding to both the tumor and the healthy tissues across 13 cancer types. The comparison of these interactomes provided a list of patient-specific edgetic perturbations of the interactomes associated with the cancerous state. We found that among the identified perturbations, select sets are robustly shared between patients at the multi-cancer, cancer-specific and cancer subtype specific levels. Interestingly, the majority of the alterations do not directly involve significantly mutated genes, nevertheless, they strongly correlate with patient survival. The findings (available at edgeexplorer: "http://webclu.bio.wzw.tum.de/edgeexplorer") are a new source of potential biomarkers for classifying cancer types and the proteins we identified are potential anti-cancer therapy targets.Cancer involves the accumulation of somatic mutations 1 and epigenetic modifications 2 , which drive the cells into the malignant state. Recurrent mutations implicated in tumorigenesis affect highly connected proteins within the protein interaction network 3,4 and are enriched at the interaction interfaces 5,6 and phosphorylation sites 7 signifying their role in rewiring protein interactions 8 . For this reason, cancer has been described as the disease of the interactome 9 . Indeed, the network of protein-protein interactions (PPI) has repeatedly allowed for the extraction of molecular features predictive of various phenotypic traits relevant to cancer -the so-called disease biomarkers 10 . For example, Cui et al. have identified putative interaction-disrupting mutations occurring at the interfaces of protein complexes and demonstrated that their presence is prognostic of poor survival 11 . In another study, Li et al. 12 developed the "OncoPPI" network of protein-protein interactions (PPIN) relevant to lung cancer, identifying biomarkers that can inform therapeutic decisions according to the drug sensitivity in certain conditions 12 . Nevertheless, the physical disruption of interaction sites by somatic mutations is only one mode of perturbing the interactome. Another relevant cellular process is regulating the expression (and thereby the local molecular concentration) of the interacting proteins 13 ; this has been utilized in mining the network of protein-protein interactions to identify modules of differentially expressed genes serving as robust biomarkers indicative of breast cancer metastasis 14 or stratifying patients from several breast cancer subtypes 15 . Furthermore, the phenomenon of "isoform switching", i.e. altering t...

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Section: Resultssupporting

confidence: 92%

Edgetic perturbation signatures represent known and novel cancer biomarkers

Kataka

Zaucha

Frishman

et al. 2020

Sci Rep

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“…Frequently, cancer cells become resistant to the tumour suppressive effects of TGF-β, however functional TGF-β signalling often persists in these cells enabling TGF-β-induced tumour promoting phenotypes [ 13 , 14 , 15 , 16 ]. Accumulating evidence has revealed that the TGF-β signalling pathway is targeted by many oncogenic viruses, including Epstein-Barr virus (EBV), during the course of tumorigenesis [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Roles of TGF-β Signalling in EBV-Associated Cancers

Velapasamy

Dawson

et al. 2018

Cancers

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The transforming growth factor-β (TGF-β) signalling pathway plays a critical role in carcinogenesis. It has a biphasic action by initially suppressing tumorigenesis but promoting tumour progression in the later stages of disease. Consequently, the functional outcome of TGF-β signalling is strongly context-dependent and is influenced by various factors including cell, tissue and cancer type. Disruption of this pathway can be caused by various means, including genetic and environmental factors. A number of human viruses have been shown to modulate TGF-β signalling during tumorigenesis. In this review, we describe how this pathway is perturbed in Epstein-Barr virus (EBV)-associated cancers and how EBV interferes with TGF-β signal transduction. The role of TGF-β in regulating the EBV life cycle in tumour cells is also discussed.

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“…The Hippo signaling pathway regulates the proliferation, survival, and morphology of eukaryotic cells, and studies have shown that this pathway is involved in the process of ZIKV infection [37]. The MAPK signaling pathway also participates in the virushost interaction process by regulating various physiological processes, such as cell growth, differentiation, apoptosis and death [38,39].…”

Section: Analysis Of Signaling Pathwaysmentioning

confidence: 99%

Transcriptome Analysis of Aedes aegypti Aag2 Cells in Response to Dengue Virus-2 Infection

Lan

Gao

et al. 2020

Preprint

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Background: Dengue virus (DENV) is a flavivirus transmitted by mosquitoes that is prevalent in tropical and subtropical countries and has four serotypes (DENV1-4). Aedes aegypti, as the main transmission vector of DENV, exhibits strong infectivity and transmission. With the aim of obtaining a better understanding of the Ae. aegypti-DENV interaction, the transcriptome changes in DENV-2-infected Aag2 cells were studied to describe the immune responses of mosquitoes using the Ae. aegypti Aag2 cell line as a model.Methods: RNAseq technology was used to sequence the transcripts of the Ae. aegypti Aag2 cell line before and after infection with DENV-2. A bioinformatics analysis was then performed to assess the biological functions of the differentially expressed genes, and the sequencing data were verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).Results: The transcriptome analysis generated 8866 unigenes that were found in both groups, 225 unigenes that were only found in the infection group, and 683 unigenes that only existed in the control group. A total of 1199 differentially expressed genes, including 1014 upregulated and 185 downregulated genes, were identified. The bioinformatics analysis showed that the differentially expressed genes were mainly involved in the longevity regulating pathway, circadian rhythm, DNA replication, and peroxisome, purine, pyrimidine, and drug metabolism. The qRT-PCR verification results showed the same trend, which confirmed that the expression of the differentially expressed genes had changed and that the transcriptome sequencing data were reliable.Conclusions: This study investigated the changes in the transcriptome levels in the DENV-2-infected Ae. aegypti Aag2 cell line, which provides a faster and effective method for discovering genes related to Ae. aegypti pathogen susceptibility. The findings provide basic data and directions for further research on the complex mechanism underlying host-pathogen interactions.

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Viruses as key modulators of the TGF‐β pathway; a double‐edged sword involved in cancer

Cited by 45 publications

References 113 publications

Edgetic perturbation signatures represent known and novel cancer biomarkers

Edgetic perturbation signatures represent known and novel cancer biomarkers

The Dynamic Roles of TGF-β Signalling in EBV-Associated Cancers

Transcriptome Analysis of Aedes aegypti Aag2 Cells in Response to Dengue Virus-2 Infection

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