Genetic landscape of ultra-stable chronic lymphocytic leukemia patients

Background

Chronic lymphocytic leukemia (CLL) has a heterogeneous clinical course. Beside patients requiring immediate treatment, others show an initial indolent phase followed by progression and others do not progress for decades. The latter two subgroups usually display mutated IGHV genes and a favorable FISH profile.

Patients and methods

Patients with absence of disease progression for over 10 years (10-34) from diagnosis were defined as ultra-stable CLL (US-CLL). Forty US-CLL underwent extensive characterization including whole exome sequencing (WES), ultra-deep sequencing and copy number aberration (CNA) analysis to define their unexplored genetic landscape. Microarray analysis, comparing US-CLL with non-US-CLL with similar immunogenetic features (mutated IGHV/favorable FISH), was also carried out to recognize US-CLL at diagnosis.

Results

WES was carried out in 20 US-CLL and 84 non-silent somatic mutations in 78 genes were found. When re-tested in a validation cohort of 20 further US-CLL, no recurrent lesion was identified. No clonal mutations of NOTCH1, BIRC3, SF3B1 and TP53 were found, including ATM and other potential progression driving mutations. CNA analysis identified 31 lesions, none with known poor prognostic impact. No novel recurrent lesion was identified: most cases showed no lesions (38%) or an isolated del(13q) (31%). The expression of 6 genes, selected from a gene expression profile analysis by microarray and quantified by droplet digital PCR on a cohort of 79 CLL (58 US-CLL and 21 non-US-CLL), allowed to build a decision-tree capable of recognizing at diagnosis US-CLL patients.

Conclusions

The genetic landscape of US-CLL is characterized by the absence of known unfavorable driver mutations/CNA and of novel recurrent genetic lesions. Among CLL patients with favorable immunogenetics, a decision-tree based on the expression of 6 genes may identify at diagnosis patients who are likely to maintain an indolent disease for decades.

GAB2 induces tumor angiogenesis in NRAS-driven melanoma

GAB2 is a scaffold protein with diverse upstream and downstream effectors. MAPK and PI3K signaling pathways are known effectors of GAB2. It is amplified and overexpressed in a variety of human tumors including melanoma. Here we show a previously undescribed role for GAB2 in NRAS-driven melanoma. Specifically, we found that GAB2 is co-expressed with mutant NRAS in melanoma cell lines and tumor samples and its expression correlated with metastatic potential. Co-expression of GAB2(WT) and NRAS(G12D) in melanocytes and in melanoma cells increased anchorage-independent growth by providing GAB2-expressing cells a survival advantage through upregulation of BCL-2 family of anti-apoptotic factors. Of note, collaboration of GAB2 with mutant NRAS enhanced tumorigenesis in vivo and led to an increased vessel density with strong CD34 and VEGFR2 activity. We found that GAB2 facilitiated an angiogenic switch by upregulating HIF-1α and VEGF levels. This angiogenic response was significantly suppressed with the MEK inhibitor PD325901. These data suggest that GAB2-mediated signaling cascades collaborate with NRAS-driven downstream activation for conferring an aggressive phenotype in melanoma. Second, we show that GAB2/NRAS signaling axis is non-linear and non-redundant in melanocytes and melanoma, and thus are acting independent of each other. Finally, we establish a link between GAB2 and angiogenesis in melanoma for the first time. In conclusion, our findings provide evidence that GAB2 is a novel regulator of tumor angiogenesis in NRAS-driven melanoma through regulation of HIF-1α and VEGF expressions mediated by RAS-RAF-MEK-ERK signaling.

Biclustering of adverse drug events in the FDA's spontaneous reporting system

In this article, we present a new pharmacovigilance data mining technique based on the biclustering paradigm, which is designed to identify drug groups that share a common set of adverse events (AEs) in the spontaneous reporting system (SRS) of the US Food and Drug Administration (FDA). A taxonomy of biclusters is developed, revealing that a significant number of bona fide adverse drug event (ADE) biclusters have been identified. Statistical tests indicate that it is extremely unlikely that the bicluster structures thus discovered, as well as their content, could have arisen by mere chance. Some of the biclusters classified as indeterminate provide support for previously unrecognized and potentially novel ADEs. In addition, we demonstrate the potential importance of the proposed methodology in several important aspects of pharmacovigilance such as providing insight into the etiology of ADEs, facilitating the identification of novel ADEs, suggesting methods and a rationale for aggregating terminologies, highlighting areas of focus, and providing an exploratory tool for data mining.

Cluster analysis of the origins of the new influenza A(H1N1) virus

In March and April 2009, a new strain of influenza A(H1N1) virus has been isolated in Mexico and the United States. Since the initial reports more than 10,000 cases have been reported to the World Health Organization, all around the world. Several hundred isolates have already been sequenced and deposited in public databases. We have studied the genetics of the new strain and identified its closest relatives through a cluster analysis approach. We show that the new virus combines genetic information related to different swine influenza viruses. Segments PB2, PB1, PA, HA, NP and NS are related to swine H1N2 and H3N2 influenza viruses isolated in North America. Segments NA and M are related to swine influenza viruses isolated in Eurasia.

The origin of the recent swine influenza A(H1N1) virus infecting humans

Preliminary analysis of the genome of the new H1N1 influenza A virus responsible for the current pandemic indicates that all genetic segments are related closest to those of common swine influenza viruses.

The origin of the recent swine influenza A(H1N1) virus infecting humans

Preliminary analysis of the genome of the new H1N1 influenza A virus responsible for the current pandemic indicates that all genetic segments are related closest to those of common swine influenza viruses.