BRCA1 and BRCA2 Germline Mutations in Malaysian Women with Early-Onset Breast Cancer without a Family History

BACKGROUND: In Asia, breast cancer is characterised by an early age of onset: In Malaysia, approximately 50% of cases occur in women under the age of 50 years. A proportion of these cases may be attributable, at least in part, to genetic components, but to date, the contribution of genetic components to breast cancer in many of Malaysia's ethnic groups has not been well-characterised. METHODOLOGY: Given that hereditary breast carcinoma is primarily due to germline mutations in one of two breast cancer susceptibility genes, BRCA1 and BRCA2, we have characterised the spectrum of BRCA mutations in a cohort of 37 individuals with early-onset disease (<or=40 years) and no reported family history. Mutational analysis of BRCA1 and BRCA2 was conducted by full sequencing of all exons and intron-exon junctions. CONCLUSIONS: Here, we report a total of 14 BRCA1 and 17 BRCA2 sequence alterations, of which eight are novel (3 BRCA1 and 5 BRCA2). One deleterious BRCA1 mutation and 2 deleterious BRCA2 mutations, all of which are novel mutations, were identified in 3 of 37 individuals. This represents a prevalence of 2.7% and 5.4% respectively, which is consistent with other studies in other Asian ethnic groups (4-9%)

DNA Methylation Changes in Atypical Adenomatous Hyperplasia, Adenocarcinoma In Situ, and Lung Adenocarcinoma

BACKGROUND:Aberrant DNA methylation is common in lung adenocarcinoma, but its timing in the phases of tumor development is largely unknown. Delineating when abnormal DNA methylation arises may provide insight into the natural history of lung adenocarcinoma and the role that DNA methylation alterations play in tumor formation. METHODOLOGY/PRINCIPAL FINDINGS:We used MethyLight, a sensitive real-time PCR-based quantitative method, to analyze DNA methylation levels at 15 CpG islands that are frequently methylated in lung adenocarcinoma and that we had flagged as potential markers for non-invasive detection. We also used two repeat probes as indicators of global DNA hypomethylation. We examined DNA methylation in 249 tissue samples from 93 subjects, spanning the putative spectrum of peripheral lung adenocarcinoma development: histologically normal adjacent non-tumor lung, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS, formerly known as bronchioloalveolar carcinoma), and invasive lung adenocarcinoma. Comparison of DNA methylation levels between the lesion types suggests that DNA hypermethylation of distinct loci occurs at different time points during the development of lung adenocarcinoma. DNA methylation at CDKN2A ex2 and PTPRN2 is already significantly elevated in AAH, while CpG islands at 2C35, EYA4, HOXA1, HOXA11, NEUROD1, NEUROD2 and TMEFF2 are significantly hypermethylated in AIS. In contrast, hypermethylation at CDH13, CDX2, OPCML, RASSF1, SFRP1 and TWIST1 and global DNA hypomethylation appear to be present predominantly in invasive cancer. CONCLUSIONS/SIGNIFICANCE:The gradual increase in DNA methylation seen for numerous loci in progressively more transformed lesions supports the model in which AAH and AIS are sequential stages in the development of lung adenocarcinoma. The demarcation of DNA methylation changes characteristic for AAH, AIS and adenocarcinoma begins to lay out a possible roadmap for aberrant DNA methylation events in tumor development. In addition, it identifies which DNA methylation changes might be used as molecular markers for the detection of preinvasive lesions

The Sulfotransferase SULT1C2 Is Epigenetically Activated and Transcriptionally Induced by Tobacco Exposure and Is Associated with Patient Outcome in Lung Adenocarcinoma

Lung cancer is the leading cause of cancer-related death. Tobacco exposure is associated with 80&ndash;90% of lung cancer cases. The SULT1C2 sulfotransferase modifies xenobiotic compounds to enhance secretion but can also render these compounds carcinogenic. To determine if SULT1C2 contributes to tobacco-related carcinogenesis in the lung, we analyzed the expression and epigenetic state of SULT1C2 in human lung adenocarcinoma (LUAD) samples and in LUAD cell lines exposed to cigarette smoke condensate (CSC). SULT1C2 expression was significantly positively correlated to overall LUAD patient survival in smokers, was elevated in LUAD tumors compared to adjacent non-tumor lung, and was significantly correlated with levels of patient exposure to tobacco smoke. SULT1C2 promoter DNA methylation was inversely correlated with expression in LUAD, and hypomethylation of the SULT1C2 promoter was observed in Asian patients, as compared to Caucasians. In vitro analysis of LUAD cell lines indicates that CSC stimulates expression of SULT1C2 in a dose-dependent and cell-line-specific manner. In vitro methylation of the SULT1C2 promoter significantly decreased transcriptional activity of a reporter plasmid, and SULT1C2 expression was activated by the DNA demethylating agent 5-Aza-2&prime;-deoxycytidine in a cell line in which the SULT1C2 promoter was hypermethylated. An aryl hydrocarbon receptor (AHR) binding site was detected spanning critical methylation sites upstream of SULT1C2. CSC exposure significantly increased AHR binding to this predicted binding site in the SULT1C2 promoter in multiple lung cell lines. Our data suggest that CSC exposure leads to activation of the AHR transcription factor, increased binding to the SULT1C2 promoter, and upregulation of SULT1C2 expression and that this process is inhibited by DNA methylation at the SULT1C2 locus. Additionally, our results suggest that the level of SULT1C2 promoter methylation and gene expression in normal lung varies depending on the race of the patient, which could in part reflect the molecular mechanisms of racial disparities seen in lung cellular responses to cigarette smoke exposure

Managing communications activities for a multi-drug, multi-indication oncology portfolio

Objective: To describe an effective approach that addresses the challenges and needs associated with managing the communications activities for a multi-drug, multi-indication oncology portfolio. • Challenge/problem: Oncology agents hold a distinct position in the pantheon of therapeutics, as many of these agents can treat >1 type of cancer. Correspondingly, communication strategies surrounding these agents present a unique challenge in that information must simultaneously maintain a consistent scientific narrative for the drug itself while meeting the specific needs for the differing tumor types. This problem is further complicated when a franchise of agents is considered. • Solution: In collaboration with a medical communications consultancy partner, a multi-pronged strategy for aligning scientific messaging among key oncology brands was developed. Key components of this strategy included: (1) development of and achieving consensus on a core clinical narrative for each agent; (2) alignment of the scientific platforms to the consensus narratives; (3) development of medical objectives based on the communications needs; and (4) creation of a unified communication strategy that capitalizes on synergies within and between agents. Novel strategies for developing consensus and tracking metrics will be discussed. • Outcome: Consensus was reached quickly, informed by novel live and virtual interactions in 2016-2017. Communication plans were subsequently developed and actioned, and metrics were monitored over time. Plan revisions were minimal and consistent with natural expansions of brand strategy. • Benefit: A collaborative unified approach to a portfolio strategy for communicating key scientific messages for oncology assets proved to be an effective and efficient means of disseminating pertinent information

Sequence variants identified in the <i>BRCA1</i> gene.

<p>MS, missense; Syn, synonymous; FS, frameshift; VUS, variant of uncertain significance; BIC, Breast Information Core</p

Sequence variants identified in the <i>BRCA2</i> gene.

*<p>These sequence alterations are likely to be polymorphisms. They have been classified as benign as allelic frequency data from population studies are not currently available. MS, missense; Syn, synonymous; FS, frameshift; VUS, variant of uncertain significance; BIC, Breast Information Core</p

Chromatin changes during AEC differentiation.

<p>A) Manhattan plot of differential chromatin changes. X-axis = chromosomal location, Y-axis = number of cell type-specific chromatin changes within 2 MB region. Upper panel = H3K9/14^Ac changes, blue = AT2 cell-specific acetylation, purple = AT1 cell-specific acetylation. Lower panel = H3K27^me3 changes, orange = AT2 cell-specific methylation, grey = AT1 cell-specific methylation. B) 135 TFBS enrichment in domains of chromatin change from HOMER. X-axis = H3K9/14^Ac, Y-axis = H3K27^me3 enrichment. AT2 enrichment is shown as the log₁₀ TFBS p-value, AT1 enrichment is shown as the −log₁₀ TFBS p-value. C) Example of chromatin changes at an upregulated gene, <i>FZD2</i>, using IGV to visualize chromatin tracks. Blue = H3K9/14^Ac raw reads and SICER peaks called, green = predicted RXR binding site from HOMER analysis. D) Example of downregulated gene expression at the <i>PGC</i> gene locus. Lavender = predicted FOXA1 binding sites from HOMER analysis. AT2 = AEC chromatin signature (D0), AT1 = AEC chromatin signature (D8).</p

Transcriptomic profiling of human AEC differentiation.

<p>A) Heatmap of top 5% variant-VSN normalized gene expression probes. Blue = low expression, red = high expression. DAY = number of days AT2 cells were allowed to differentiate. “Prep” = donor lung origin by color (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003513#pgen.1003513.s001" target="_blank">Figure S1</a>). B) Principal component analysis of normalized hAEC samples. Samples color coded by donor lung as in (A). C) Significant changes in hAEC gene expression. Black line = BH-adjusted cutoff (FDR adjusted p≤0.05) calculated between D0 and D8. 20 genes show both significant up and downregulation for probes in different locations of the gene. D) Manhattan plot of differentially expressed genes. X-axis = chromosomal location, Y-axis = number of genes in each 2 MB region. E) qRT-PCR validation of microarray, data expressed in log₂-fold change of differences between D0 and D8. Circles = top 10 up- and down-regulated genes, triangles = known AT1 cell differentiation markers (<i>AQP5, PDPN, CAV1</i>). F) IPA of significantly up- or down-regulated genes. Bars expressed as log₁₀-BH corrected p-values of enrichment for pathway members in significant list against RefSeq db38 background. Whole figure: Red = upregulated, green = downregulated.</p