EEF1D modulates proliferation and epithelial–mesenchymal transition in oral squamous cell carcinoma

Flores, Isadora Luana; Kawahara, Rebeca; Miguel, Márcia Cristina da Costa; Granato, Daniela Campos; Domingues, Romênia R.; Macedo, Carolina Carneiro Soares; Carnielli, Carolina Moretto; Yokoo, Sami; Rodrigues, Priscila Campioni; Monteiro, Bárbara Vanessa de Brito; Oliveira, Carine Ervolino de; Salmon, Cristiane R.; Nociti, Francisco Humberto; Lopes, Márcio Ajudarte; Santos‐Silva, Alan Roger; Winck, Flávia Vischi; Coletta, Ricardo D.; Leme, Adriana Franco Paes

doi:10.1042/cs20150646

Cited by 38 publications

(48 citation statements)

References 32 publications

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“…Histological sections with a thickness of 5 μm were stained with H&E to guide the LMD. The other three sections of 10 μm thickness were prepared using specific membrane slides (PEN Arcturus ® Membrane, Life Technologies, Foster City, CA, USA) for LMD, which were deparaffinized in xylol, hydrated with decreasing concentrations (100, 90, 70, and 50%) of ethanol, washed in water and stained with hematoxylin blue for 8 min prior to drying for LMD 62 .…”

Section: Methodsmentioning

confidence: 99%

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

et al. 2018

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Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

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Section: Methodsmentioning

confidence: 99%

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

et al. 2018

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“…The levels of mRNA and a protein coded by this mRNA do not often correlate (Liu et al, 2016) which is valid for eEF1B subunits as well (Veremieva et al, 2011(Veremieva et al, , 2014Flores et al, 2016). This mini-review is focused on eEF1B proteins, therefore cancer-related changes in the levels of corresponding mRNAs are not considered here, although such changes may be of marker/prognostic importance (Hassan et al, 2018;Biterge-Sut, 2019).…”

Section: Eef1b Proteins In Cancermentioning

confidence: 99%

“…Recently, eEF1Bβ was proposed as a blood marker for cadmium exposure (Lu et al, 2013). This protein was upregulated in the metastatic canine mammary carcinoma (Klopfleisch et al, 2010) and human oral squamous cell carcinoma (Flores et al, 2016) tissues, as well as in 5-fluorouracil-resistant human breast cancer cells (Zheng et al, 2010). Interestingly, knocking down of eEF1Bβ mRNA was accompanied by the opposite effects on the proliferation and epithelial mesenchymal transition (EMT)/invasion capabilities of squamous cell carcinoma cells (Flores et al, 2016).…”

Section: Eef1b Proteins In Cancermentioning

confidence: 99%

Non-translational Connections of eEF1B in the Cytoplasm and Nucleus of Cancer Cells

Negrutskii

2020

Front. Mol. Biosci.

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The human translation machinery includes three types of supramolecular complexes involved in elongation of the polypeptide chain: the ribosome, complex of elongation factors eEF1B and multienzyme aminoacyl-tRNA synthetase complex. Of the above, eEF1B is the least investigated assembly. Recently, a number of studies provided some insights into the structure of different eEF1B subunits and changes in their expression in cancer and other diseases. There is increasing agreement that possible disease-related functions of eEF1B are not necessarily related to its role in translation. This mini-review focuses on structural and functional features of the eEF1B complex while paying special attention to possible non-canonical functions of its subunits in cancer cells.

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“…According to cBioPortal (Gao et al, 2013), analysis of TCGA provisional Liver Hepatocellular Carcinoma dataset which included 442 samples, 12 of 32 highly expressed genes with more than 3-folds activation in HCC identified by PE100_2MI but not by SE100_SAM and SE50_SAM read count sets were overexpressed or amplified in more than 10% of HCC cases. These genes encode EEF1D elongation factor deregulated in multiple cancers and modulating proliferation and epithelial-mesenchymal transition in oral squamous cell carcinoma; Glo1 glyoxalase required for HCC cells proliferation and survival which is upregulated or amplified in 48% of HCC samples; liver-specific target of WNT signaling pathway glutamine synthetase GLUL; PRKAR1A regulatory subunit of cAMP-dependent protein kinase encoded by TSE1 locus associated with regulation of hepatic differentiation, and some others (Flores et al, 2016; Zhang et al, 2014; Zucman-Rossi et al, 2007; Boshart et al, 1991). …”

Section: Resultsmentioning

confidence: 99%

Effect of method of deduplication on estimation of differential gene expression using RNA-seq

Klepikova

Kasianov

Chesnokov

et al. 2017

PeerJ

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BackgroundRNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads.ResultsTo infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC) and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in SAMtools, and deduplication based on one or two molecular indices (MI). We also analyzed the influence of sequencing layout (single read or paired end) and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes.ConclusionThe use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

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EEF1D modulates proliferation and epithelial–mesenchymal transition in oral squamous cell carcinoma

Cited by 38 publications

References 32 publications

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Non-translational Connections of eEF1B in the Cytoplasm and Nucleus of Cancer Cells

Effect of method of deduplication on estimation of differential gene expression using RNA-seq

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