Dataset Information

Proteomic Manifestations of Genetic Defects in Autosomal Recessive Congenital Ichthyosis

ABSTRACT: Numerous genetic conditions give rise to a scaly skin phenotype as a result of impaired barrier function. Differences in appearance suggest the response of epidermal cells depends upon the basic defect. The present work characterizes the departure of afflicted corneocytes from normal as judged by their proteomic profiles in three types of autosomal recessive congenital ichthyosis arising from defects in the genes PNPLA1, SDR9C7 and TGM1. The results show that the profiles were distinctive, each displaying a set of altered protein levels, but with a subset of common alterations. Departure from the normal profile was examined at three different anatomic sites (forearm, forehead, leg). Reflecting that the normal protein profile differed at these sites, comparing profiles from afflicted subjects revealed that the alterations in profile were site-dependent. These results suggest proteomic profiling can provide a quantitative measure of departure from the normal state of epidermis. Further development may find application to diagnosis, including identification of new genetic defects, and may help understand signaling pathways perturbed by the basic defects, supplementing visual evaluation of treatment.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Robert H. Rice

PROVIDER: MSV000082828 | MassIVE | Fri Aug 17 17:12:00 BST 2018

SECONDARY ACCESSION(S): PXD010814

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:The success of targeted therapies creates a need to discriminate tumors accurately by their histological and genetic characteristics. Here, we used cDNA microarray analysis to identify gene expression profiles and single markers that recapitulate the pathological and genetic background (i.e., BRAF, EGFR, KRAS, LKB1, PIK3CA, and TP53 gene alterations) of non-small cell lung cancer (NSCLC). Gene expression profiles were determined for 6 normal lung tissues and 69 lung tumors from patients diagnosed with NSCLC. We performed an unsupervised hierarchical clustering with the most variably expressed transcript to investigate whether there was evidence for natural grouping samples based on similarity in gene expression profiles. We examined the relationship between the clusters of tumors and patient and tumor characteristics such as gender, smoking status, histological type, degree of differentiation, tumor size, lymph node involvement and genetic background. We used a supervised analysis to identify the genes that are important for distinguishing subgroups of tumors defined by histological type. Moreover, we used this supervised approach to search for markers that characterize those tumors carrying EGFR, KRAS, PIK3CA and TP53 alterations. We identify several genes with characteristic patterns of expression in each tumor histological type (adenocarcinoma and squamous cell carcinoma) and we found that the presence of EGFR mutations result in a particular expression profile. Keywords: Transciption profiling of tumors with different histological and genetic background. We analyzed 69 NSCLC tumors. All the samples were characterized by histological type and by the presence of alterations at genes that are known to be involved in lung carcinogenesis. Mutational analysis of BRAF, EGFR, KRAS, and LKB1 is provided only for adenocarcinomas and analysis of alterations at PIK3CA gene (mutational analysis or gene amplification by FISH analysis) is provided only for 47 of the tumors. We analyzed gene expression profiles to identify those genes that are differentially expressed between two subgroups by t-test: 1) adenocarcinomas vs. squamous cell carcinomas; 2) tumors with mutation at EGFR gene vs. wild type tumors; 3) tumors with mutation at KRAS gene vs. wild type tumors; 4) tumors with mutation at TP53 gene vs. wild type tumors; 5) tumors with alterations (mutation or gene amplification) at PIK3CA gene vs. wild type tumors.

Dataset Information

Proteomic Manifestations of Genetic Defects in Autosomal Recessive Congenital Ichthyosis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets