In:
PROTEOMICS, Wiley, Vol. 16, No. 11-12 ( 2016-06), p. 1613-1621
Abstract:
Intra‐tumor heterogeneity is a vivid problem of molecular oncology that could be addressed by imaging mass spectrometry. Here we aimed to assess molecular heterogeneity of oral squamous cell carcinoma and to detect signatures discriminating normal and cancerous epithelium. Tryptic peptides were analyzed by MALDI‐IMS in tissue specimens from five patients with oral cancer. Novel algorithm of IMS data analysis was developed and implemented, which included Gaussian mixture modeling for detection of spectral components and iterative k‐means algorithm for unsupervised spectra clustering performed in domain reduced to a subset of the most dispersed components. About 4% of the detected peptides showed significantly different abundances between normal epithelium and tumor, and could be considered as a molecular signature of oral cancer. Moreover, unsupervised clustering revealed two major sub‐regions within expert‐defined tumor areas. One of them showed molecular similarity with histologically normal epithelium. The other one showed similarity with connective tissue, yet was markedly different from normal epithelium. Pathologist's re‐inspection of tissue specimens confirmed distinct features in both tumor sub‐regions: foci of actual cancer cells or cancer microenvironment‐related cells prevailed in corresponding areas. Hence, molecular differences detected during automated segmentation of IMS data had an apparent reflection in real structures present in tumor.
Type of Medium:
Online Resource
ISSN:
1615-9853
,
1615-9861
DOI:
10.1002/pmic.v16.11-12
DOI:
10.1002/pmic.201500458
Language:
English
Publisher:
Wiley
Publication Date:
2016
detail.hit.zdb_id:
2037674-1
SSG:
12
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