Genomics

Dataset Information

0

Specific genomic aberrations in squamous cell lung carcinoma with lymph node or distant metastasis


ABSTRACT: The majority of patients with squamous cell lung cancer (SCC) die because of metastatic disease. The genomic mechanisms underlying this metastatic behaviour are underexposed. We analyzed a cohort of patients with primary squamous cell carcinoma (SCC) using array-based comparative genomic hybridization (aCGH) to identify which genomic aberrations were related metastatic behaviour. The cohort consisted of 34 patients with a follow-up of at least 5 years, including 15 without any metastases, 8 with metastases in regional lymph nodes only, and 11 with metastases exclusively in distant organs within two years after surgery. Common alterations observed in at least 40% of all SCC were gains at 3q13-q29, 5p11-p15, 8q24, 19q13, 20p12-p13, 22q11-q13, and losses at 3p12-p14, 3p24, 4p15, 4q33-q35, 5q14-q23, 5q31-q35, 8p21-p22, 9p21-p24. Amplifications were observed at 2p15-p16, 3q24-q29, 8p11-p12, 8q23-q24, and 12p12, containing candidate oncogenes such as BCL11A, REL, ECT2, PIK3CA, ADAM9, MYC, and KRAS. Gains at 7q36, 8p12, 10q22, 12p12, loss at 4p14 and homozygous deletions at 4q33-q34.1 occurred significantly more frequent in SCC from patients with lymph node metastases. SCC from patients with distant metastases showed a significantly higher frequency of gain at 8q22-q24 and loss of 8p23 and 13q21, and a significantly lower frequency of gain at 2p12 and 2p16 and loss at 11q25 as compared to SCC from patients without metastases. In conclusion, we identified specific genomic aberrations in primary SCC that are related to lymph node or distant metastases. These loci can be further explored for their potential use as predictive or prognostic markers.

ORGANISM(S): Homo sapiens

PROVIDER: GSE12280 | GEO | 2008/10/01

SECONDARY ACCESSION(S): PRJNA113669

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2014-02-10 | E-GEOD-38479 | biostudies-arrayexpress
2023-11-17 | MODEL2310150001 | BioModels
2017-12-01 | E-MTAB-4003 | biostudies-arrayexpress
2011-12-23 | E-GEOD-34666 | biostudies-arrayexpress
2011-08-30 | E-GEOD-29827 | biostudies-arrayexpress
2011-12-23 | GSE34666 | GEO
2014-07-01 | E-GEOD-43934 | biostudies-arrayexpress
2014-02-10 | GSE38479 | GEO
2010-07-08 | E-GEOD-21581 | biostudies-arrayexpress
2021-04-26 | ST001755 | MetabolomicsWorkbench