Omics data-driven analysis identifies laminin-integrin-mediated signaling pathway as a determinant for cell differentiation in oral squamous cell carcinoma.


Journal

Indian journal of pathology & microbiology
ISSN: 0974-5130
Titre abrégé: Indian J Pathol Microbiol
Pays: India
ID NLM: 7605904

Informations de publication

Date de publication:
Historique:
entrez: 16 10 2019
pubmed: 16 10 2019
medline: 23 2 2020
Statut: ppublish

Résumé

In recent years, high-throughput omics technologies have been widely used globally to identify potential biomarkers and therapeutic targets in various cancers. However, apart from large consortiums such as The Cancer Genome Atlas, limited attempts have been made to mine existing datasets pertaining to cancers. In the current study, we used an omics data analysis approach wherein publicly available protein expression data were integrated to identify functionally important proteins that revealed consistent dysregulated expression in head and neck squamous cell carcinomas. Our analysis revealed members of the integrin family of proteins to be consistently altered in expression across disparate datasets. Additionally, through association evidence and network analysis, we also identified members of the laminin family to be significantly altered in head and neck cancers. Members of both integrin and laminin families are known to be involved in cell-extracellular matrix adhesion and have been implicated in tumor metastatic processes in several cancers. To this end, we carried out immunohistochemical analyses to validate the findings in a cohort (n = 50) of oral cancer cases. Laminin-111 expression (composed of LAMA1, LAMB1, and LAMC1) was found to correlate with cell differentiation in oral cancer, showing a gradual decrease from well differentiated to poorly differentiated cases. This study serves as a proof-of-principle for the mining of multiple omics datasets coupled with selection of functionally important group of molecules to provide novel insights into tumorigenesis and cancer progression.

Sections du résumé

BACKGROUND BACKGROUND
In recent years, high-throughput omics technologies have been widely used globally to identify potential biomarkers and therapeutic targets in various cancers. However, apart from large consortiums such as The Cancer Genome Atlas, limited attempts have been made to mine existing datasets pertaining to cancers.
METHODS AND RESULTS RESULTS
In the current study, we used an omics data analysis approach wherein publicly available protein expression data were integrated to identify functionally important proteins that revealed consistent dysregulated expression in head and neck squamous cell carcinomas. Our analysis revealed members of the integrin family of proteins to be consistently altered in expression across disparate datasets. Additionally, through association evidence and network analysis, we also identified members of the laminin family to be significantly altered in head and neck cancers. Members of both integrin and laminin families are known to be involved in cell-extracellular matrix adhesion and have been implicated in tumor metastatic processes in several cancers. To this end, we carried out immunohistochemical analyses to validate the findings in a cohort (n = 50) of oral cancer cases. Laminin-111 expression (composed of LAMA1, LAMB1, and LAMC1) was found to correlate with cell differentiation in oral cancer, showing a gradual decrease from well differentiated to poorly differentiated cases.
CONCLUSION CONCLUSIONS
This study serves as a proof-of-principle for the mining of multiple omics datasets coupled with selection of functionally important group of molecules to provide novel insights into tumorigenesis and cancer progression.

Identifiants

pubmed: 31611435
pii: IndianJPatholMicrobiol_2019_62_4_529_269055
doi: 10.4103/IJPM.IJPM_1_19
doi:

Substances chimiques

Biomarkers, Tumor 0
Integrins 0
Laminin 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

529-536

Auteurs

Spoorti Kulkarni (S)

Department of Oral Pathology and Microbiology, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, India.

Riaz Abdulla (R)

Department of Oral Pathology and Microbiology, Yenepoya Dental College, Yenepoya (Deemed to be University), Mangalore, India.

Maji Jose (M)

Department of Oral Pathology and Microbiology, Yenepoya Dental College, Yenepoya (Deemed to be University), Mangalore, India.

Soniya Adyanthaya (S)

Department of Oral Pathology and Microbiology, Yenepoya Dental College, Yenepoya (Deemed to be University), Mangalore, India.

D A B Rex (DA)

Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore, India.

Arun H Patil (AH)

Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore, India.

Sneha M Pinto (SM)

Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore, India.

Yashwanth Subbannayya (Y)

Center for Systems Biology and Molecular Medicine Yenepoya (Deemed to be University), Mangalore, India.

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Classifications MeSH