Entering edit mode
5.8 years ago
b.bearmi
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10
I've got a series of data for a certain tissue, a type of cancer). We suspect that when tissues were sampled (biopsy/surgery) we end up with a mixture of different tissues, so when we do the analysis, it is not just the target tissue + tumour cells, it will also have a significant proportion of fibroblasts swiped along. Surgeries are supposed to err on the safe side after all.
How do I approach this from the analysis point of view? For starters, I would like to know, based on the expression profiles of my samples, how big is the fibroblast component?
Unless you know of a fibroblast specific marker gene this does not sound feasible. Did a pathologist look at the tissue? Perhaps there was some indication there.
I can certainly find some fibroblast-specific markers, based on this ResearchGate https://tinyurl.com/y77hg4zs discussion, they would be FSP1, collagens (I, III) - COL1A2; COL3A1, Thymic stromal lymphopoietin (TSLP) and Vimentin - VIM. Data is mostly open source, not every expression data is published with a histology plate attached, so far I am looking from strictly bioinformatics point of view.
I am afraid that this is a wet-lab problem, not a bioinformatics problem. Maybe a strange comparison, but what if the wet-lab members design a poor PCR, do they go to the bioinformatician then with an empty gel image and ask to fix it? Better would be to design better primers.
Here I would suggest to do some gene enrichment analysis for set of genes expressed from your sample against expression profile of fibrobalst. May be that will give idea about the fibroblast component in your sample