Genomic instability

Centrosome amplification drives chromosomal instability in breast tumor development. Lingle, W. L. et al. Proc. Natl Acad. Sci. USA 99, 1978–1983 (2002) [PubMed]

About 80% of invasive breast cancers have amplified centrosomes, so does this drive chromosomal instability? By determining chromosomal instability, and centrosome number, size and microtubule nucleation in normal and cancerous breast tissue, Lingle et al. now show that centrosome size and number correlate with chromosomal instability, so centrosome amplification might contribute to tumorigenesis.

Mouse models

Genetic analysis of Pten and Ink4a/Arf interactions in the suppression of tumorigenesis in mice. You, M. J. et al. Proc. Natl Acad. Sci. USA 99, 1455–1460 (2002) [PubMed]

CDKN2A — which encodes transcripts of the tumour-suppressor proteins INK4A and ARF — and PTEN are frequently mutated in human cancer, but do they cooperate in tumorigenesis? Cdkn2a−/− Pten+/− mouse embryonic fibroblasts that are grown in low serum show higher proliferation rates than Cdkn2a−/− Pten+/+ cells, and Cdkn2a−/− Pten+/– mice are also more tumour prone and succumb to an increased range of tumour types. The two tumour-suppressor genes therefore seem to cooperate to prevent tumour formation.

Genetics

Dominant negative ATM mutations in breast cancer families. Chenevix-Trench, G. et al. J. Natl Cancer Inst. 94, 205–215 (2002) [PubMed]

Do heterozygous mutations in the ataxia-telangiectasia mutated (ATM) tumour suppressor predispose to breast cancer? Studies that indicate that ATM heterozygotes have an increased risk have not been confirmed. But Chenevix-Trench and co-workers now find two ATM mutations that co-segregate with breast cancer in three multiple-case breast cancer families. Both mutations yield a dominant-negative inhibitor of ATM, explaining the dominant nature of these mutations.

Diagnostics

Use of proteomic patterns in serum to identify ovarian cancer. Petricoin, E. F. et al. Lancet 35, 572–577 (2002) [Contents Page]

There is no accurate means, at present, of detecting ovarian cancer in the early stages. This study used mass spectroscopy and algorithms designed to distinguish specific proteomic patterns to analyse blood samples from patients with and without cancer. The authors were able to correctly identify all 50 cases of ovarian cancer, including stage-I cases, and 95% of the non-cancer controls. This is a great improvement over the ovarian cancer detection technique that is used at present — identifying the tumour marker CA125 combined with ultrasound.