CDKN2A is not the principal target of deletions on the short arm of chromosome 9 in neuroendocrine (Merkel cell) carcinoma of the skin

The majority of small-cell lung cancers (SCLCs) express p16 but not pRb. Given our previous study showing loss of pRb in Merkel cell carcinoma (MCC)/neuroendocrine carcinoma of the skin and the clinicopathological similarities between SCLC and MCC, we wished to determine if this was also the case in MCC. Twenty-nine MCC specimens from 23 patients were examined for deletions at 10 loci on 9p and 1 on 9q. No loss of heterozygosity (LOH) was seen in 9 patients including 2 for which tumour and cell line DNAs were examined. Four patients had LOH for all informative loci on 9p. Ten tumours showed more limited regions of loss on 9p, and from these 2 common regions of deletion were determined. Half of all informative cases had LOH at D9S168, the most telomeric marker examined, and 3 specimens showed loss of only D9S168. A second region (IFNA-D9S126) showed LOH in 10 (44%) cases, and case MCC26 showed LOH for only D9S126, implicating genes centromeric of the CDKN2A locus. No mutations in the coding regions of p16 were seen in 7 cell lines tested, and reactivity to anti-p16 antibody was seen in all 11 tumour specimens examined and in 6 of 7 cell lines from 6 patients. Furthermore, all cell lines examined reacted with anti-p14(ARF) antibody. These results suggest that neither transcript of the CDKN2A locus is the target of deletions on 9p in MCC and imply the existence of tumour-suppressor genes mapping both centromeric and telomeric of this locus.

FGFR2 as a molecular target in endometrial cancer

Although molecularly targeted therapies have been effective in some cancer types, no targeted therapy is approved for use in endometrial cancer. The recent identification of activating mutations in fibroblast growth factor receptor 2 (FGFR2) in endometrial tumors has generated a new avenue for the development of targeted therapeutic agents. The majority of the mutations identified are identical to germline mutations in FGFR2 and FGFR3 that cause craniosynostosis and hypochondroplasia syndromes and result in both ligand-independent and ligand-dependent receptor activation. Mutations that predominantly occur in the endometrioid subtype of endometrial cancer, are mutually exclusive with KRAS mutation, but occur in the presence of PTEN abrogation. In vitro studies have shown that endometrial cancer cell lines with activating FGFR2 mutations are selectively sensitive to a pan-FGFR inhibitor, PD173074. Several agents with activity against FGFRs are currently in clinical trials. Investigation of these agents in endometrial cancer patients with activating FGFR2 mutations is warranted.

Detection versus false alarm characterisation of a vision-based airborne dim-target collision detection system

This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.