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Proteomics Clin Appl. 2017 Mar;11(3-4). doi: 10.1002/prca.201600100. Epub 2016 Nov 28.

Sample preparation method considerations for integrated transcriptomic and proteomic analysis of tumors.

Author information

1
Strand Life Sciences, Bangalore, India.
2
Institute of Bioinformatics, International Tech Park, Bangalore, India.
3
Manipal University, Madhav Nagar, Manipal, India.
4
Ganit Labs, Bio-IT Centre, Institute of Bioinformatics and Applied Biotechnology, Bangalore, India.
5
Head and Neck Oncology, Mazumdar Shaw Medical Centre, Narayana Health, Bangalore, India.
6
Mazumdar Shaw Center for Translational Research, Mazumdar Shaw Medical Foundation, Narayana Health, Bangalore, India.

Abstract

Sample processing protocols that enable compatible recovery of differentially expressed transcripts and proteins are necessary for integration of the multiomics data applied in the analysis of tumors. In this pilot study, we compared two different isolation methods for extracting RNA and protein from laryngopharyngeal tumor tissues and the corresponding adjacent normal sections. In Method 1, RNA and protein were isolated from a single tissue section sequentially and in Method 2, the extraction was carried out using two different sections and two independent and parallel protocols for RNA and protein. RNA and protein from both methods were subjected to RNA-seq and iTRAQ-based LC-MS/MS analysis, respectively. Analysis of data revealed that a higher number of differentially expressed transcripts and proteins were concordant in their regulation trends in Method 1 as compared to Method 2. Cross-method comparison of concordant entities revealed that RNA and protein extraction from the same tissue section (Method 1) recovered more concordant entities that are missed in the other extraction method (Method 2) indicating heterogeneity in distribution of these entities in different tissue sections. Method 1 could thus be the method of choice for integrated analysis of transcriptome and proteome data.

KEYWORDS:

Head and neck cancer; Multiomics data integration; Proteomics; Transcriptomics; Tumor heterogeneity

PMID:
27801551
DOI:
10.1002/prca.201600100
[Indexed for MEDLINE]

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