Identification of GIMAP7 and Rabl3 as Putative Biomarkers for Oral Squamous Cell Carcinoma Through Comparative Proteomic Approach.
Muhammad UsmanAmber IlyasZehra HashimShamshad ZarinaPublished in: Pathology oncology research : POR (2019)
Oral squamous cell carcinoma (OSCC) accounts for more than 90% of all oral cancers and has been listed as sixth most common human cancer. Due to late diagnosis and insufficient therapeutic response among patients, the survival rate remains very low accentuating the importance of early diagnostic markers. The study aimed to identify differentially expressed proteins in search for putative serum biomarkers and drug targets. Serum samples (n = 45) were depleted and resolved on two dimensional gel electrophoresis. Among differentially expressed proteins, two were identified using MALDI-TOF mass spectrometry. Gene expression levels of identified proteins were quantified in malignant and normal tissue using RT-qPCR. To validate serum Rabl3 expression, sandwich ELISA was performed. Proteomics analysis revealed two proteins which were found to be associated with oral cancer. The expression of GIMAP7 was found to be down regulated in serum of patients suffering from oral cancer while the expression of Rabl3 was found to be up-regulated. Gene expression analysis in malignant tissue and adjacent normal tissue revealed the same pattern. Quantitative ELISA was used to validate expression of Rabl3 in serum from oral cancer patients and healthy subjects which demonstrated significant up-regulation in cancer patients. Findings in current study demonstrate differential expression of novel putative biomarkers GIMAP7 and Rabl3 in oral cancer which suggests their potential role in oral cancer pathology and can be considered as predictive biomarkers.
Keyphrases
- mass spectrometry
- poor prognosis
- gene expression
- newly diagnosed
- high resolution
- transcription factor
- binding protein
- liquid chromatography
- dna methylation
- ms ms
- long non coding rna
- young adults
- genome wide
- drug induced
- induced pluripotent stem cells
- data analysis
- hyaluronic acid
- bioinformatics analysis
- tandem mass spectrometry