PubMed · 11556534
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E de Alava. 2001. Transcripts, transcripts, everywhere.. https://doi.org/10.1097/00125480-200109000-00003
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Next-generation sequencing data is fundamentally changing the clinical management of patients with cancer. The most frequent genomic alterations in malignancy are mutations and amplifications, with a subset of tumors having multiple amplifications - "amplificators". We sought to understand the molecular correlates of high tumor amplification burden in a pan-cancer context. Using both national registries and a single-institution dataset, our results demonstrate that cancers with TP53 mutations (as compared to those with wild-type TP53) exhibited significantly higher tumor amplification burden across all datasets. Amplifications, generally associated with overexpression, may be potentially actionable secondary consequences of TP53 mutations.
BACKGROUND: While 2-4% of lung cancers possess alterations in BRAF, little is known about the immune responsiveness of these tumours. METHODS: Clinical and genomic data were collected from 5945 patients with lung cancers whose tumours underwent next-generation sequencing between 2015 and 2018. Patients were followed through 2020. RESULTS: In total, 127 patients with metastatic BRAF-altered lung cancers were identified: 29 tumours had Class I mutations, 59 had Class II/III alterations, and 39 had variants of unknown significance (VUS). Tumour mutation burden was higher in Class II/III than Class I-altered tumours (8.8 mutations/Mb versus 4.9, P < 0.001), but this difference was diminished when stratified by smoking status. The overall response rate to immune checkpoint inhibitors (ICI) was 9% in Class I-altered tumours and 26% in Class II/III (P = 0.25), with median time on treatment of 1.9 months in both groups. Among patients with Class I-III-altered tumours, 36-month HR for death in those who ever versus never received ICI was 1.82 (1.17-6.11). Nine patients were on ICI for >2 years (two with Class I mutations, two with Class II/III alterations, and five with VUS). CONCLUSIONS: A subset of patients with BRAF-altered lung cancers achieved durable disease control on ICI. However, collectively no significant clinical benefit was seen.
Although DNA microarray analysis is presented as a revolution in gene expression studies, it is in fact based on the classic technique of Southern DNA hybridisation where a labelled DNA probe is hybridised to single stranded DNA that is bound to a solid support matrix. The truly revolutionary aspect of microarray analysis lies in the fact that, within a given cell population, the expression of tens of thousands of genes, and ultimately the entire genome, can be assayed simultaneously. This capability, when coupled with powerful data analysis software, allows researchers to rapidly compare gene expression between two cell populations. In the cancer field, this enables researchers to compare gene expression between normal and malignant cells and to identify genes that are differentially regulated during cancer development. Microarray data can also be used to categorize tumours on the basis of their molecular profile, which may provide important biological, diagnostic and prognostic information. As little as 5 years ago identifying even a few differentially expressed genes may have taken several years and cost tens of thousands of dollars. Today microarrays can identify ten times the number of candidate genes in just a few months and at a tenth of the cost. Even so, microarray analysis is still in its infancy and the technology is advancing rapidly. There is little doubt that microarrays will revolutionize our ability to quantify the complex changes that occur in gene expression during cancer development. The greatest challenge that lies ahead is how to translate this knowledge into clinically useful diagnostic and therapeutic tools. In this review, we describe the technical aspects of DNA microarray analysis and some of the current and future applications of this technology for analysing gene expression in ovarian cancer.