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Phosphatidylinositol-3-kinase α catalytic subunit gene somatic mutations in bronchopulmonary neuroendocrine tumours.

Oncology reports | 2012

Bronchopulmonary neuroendocrine tumours (BP-NETs) comprise a large spectrum of tumours including typical carcinoids (TCs), atypical carcinoids (ACs), large-cell neuroendocrine carcinomas (LCNECs) and small-cell lung carcinomas (SCLCs) that exhibit considerably different biological aggressiveness and clinical behaviours. The phosphatidylinositol-3-kinase α catalytic subunit (PIK3CA) gene is known to be involved in the pathogenesis of several types of human cancers through gene amplification, deletions or somatic missense mutations within the helical and catalytic domains. However, the PIK3CA gene status in BP-NETs has yet to be explored. This study aimed to investigate the PIK3CA gene status in a large series of BP-NETs by direct gene sequencing and to analyse its correlation with the main clinicopathological parameters. To the best of our knowledge, we demonstrated for the first time a high frequency of somatic missense mutations (23.2%) in the PIK3CA gene in a series of 190 BP-NETs, including 75 TCs, 23 ACs, 17 LCNECs and 75 SCLCs. The frequency of the PIK3CA gene mutation in the kinase domain was higher (17.9%) than that in the helical domain (5.3%). When the mutational status of the PIK3CA gene was compared with the main clinical and pathological characteristics of the BP-NET patients, we found a significant association between PIK3CA gene mutations and BP-NET histology (p=0.011). Interestingly, the frequency of PIK3CA gene mutations increased with the biological aggressiveness of all BP-NETs, except LCNECs. In conclusion, our results suggest that PIK3CA gene mutations may play a key role in tumourigenesis and aggressiveness of BP-NETs. The PIK3CA gene may represent a favourable candidate for an effective therapeutic strategy in the treatment of patients with BP-NETs.

Pubmed ID: 22949056 RIS Download

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Primer3 (tool)

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Tool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.

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