Nuclear receptor coregulator SNP discovery and impact on breast cancer risk

<p>Abstract</p> <p>Background</p> <p>Coregulator proteins are "master regulators", directing transcriptional and posttranscriptional regulation of many target genes, and are critical in many normal physiological processes, but also in hormone driven diseases, such as breast cancer. Little is known on how genetic changes in these genes impact disease development and progression. Thus, we set out to identify novel single nucleotide polymorphisms (SNPs) within SRC-1 (NCoA1), SRC-3 (NCoA3, AIB1), NCoR (NCoR1), and SMRT (NCoR2), and test the most promising SNPs for associations with breast cancer risk.</p> <p>Methods</p> <p>The identification of novel SNPs was accomplished by sequencing the coding regions of these genes in 96 apparently normal individuals (48 Caucasian Americans, 48 African Americans). To assess their association with breast cancer risk, five SNPs were genotyped in 1218 familial BRCA1/2-mutation negative breast cancer cases and 1509 controls (rs1804645, rs6094752, rs2230782, rs2076546, rs2229840).</p> <p>Results</p> <p>Through our resequencing effort, we identified 74 novel SNPs (30 in NCoR, 32 in SMRT, 10 in SRC-3, and 2 in SRC-1). Of these, 8 were found with minor allele frequency (MAF) >5% illustrating the large amount of genetic diversity yet to be discovered. The previously shown protective effect of rs2230782 in SRC-3 was strengthened (OR = 0.45 [0.21-0.98], p = 0.04). No significant associations were found with the other SNPs genotyped.</p> <p>Conclusions</p> <p>This data illustrates the importance of coregulators, especially SRC-3, in breast cancer development and suggests that more focused studies, including functional analyses, should be conducted.</p

Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. © 2012 Coronnello et al

Recurrent Loss of NFE2L2 Exon 2 Is a Mechanism for Nrf2 Pathway Activation in Human Cancers

The Nrf2 pathway is frequently activated in human cancers through mutations in Nrf2 or its negative regulator KEAP1. Using a cell-line-derived gene signature for Nrf2 pathway activation, we found that some tumors show high Nrf2 activity in the absence of known mutations in the pathway. An analysis of splice variants in oncogenes revealed that such tumors express abnormal transcript variants from the NFE2L2 gene (encoding Nrf2) that lack exon 2, or exons 2 and 3, and encode Nrf2 protein isoforms missing the KEAP1 interaction domain. The Nrf2 alterations result in the loss of interaction with KEAP1, Nrf2 stabilization, induction of a Nrf2 transcriptional response, and Nrf2 pathway dependence. In all analyzed cases, transcript variants were the result of heterozygous genomic microdeletions. Thus, we identify an alternative mechanism for Nrf2 pathway activation in human tumors and elucidate its functional consequences

Candidate mechanisms of acquired resistance to first-line osimertinib in EGFR-mutated advanced non-small cell lung cancer

Abstract Osimertinib, an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), potently and selectively inhibits EGFR-TKI-sensitizing and EGFR T790M resistance mutations. In the Phase III FLAURA study (NCT02296125), first-line osimertinib improved outcomes vs comparator EGFR-TKIs in EGFRm advanced non-small cell lung cancer. This analysis identifies acquired resistance mechanisms to first-line osimertinib. Next-generation sequencing assesses circulating-tumor DNA from paired plasma samples (baseline and disease progression/treatment discontinuation) in patients with baseline EGFRm. No EGFR T790M-mediated acquired resistance are observed; most frequent resistance mechanisms are MET amplification (n = 17; 16%) and EGFR C797S mutations (n = 7; 6%). Future research investigating non-genetic acquired resistance mechanisms is warranted

Targeted genomic analysis of 364 adrenocortical carcinomas.

Despite recent advances in elucidating molecular pathways underlying adrenocortical carcinoma (ACC), this orphan malignancy is associated with poor survival. Identification of targetable genomic alterations is critical to improve outcomes. The objective of this study was to characterize the genomic profile of a large cohort of patient ACC samples to identify actionable genomic alterations. Three hundred sixty-four individual patient ACC tumors were analyzed. The median age of the cohort was 52 years and 60.9% (n = 222) were female. ACC samples had common alterations in epigenetic pathways with 38% of tumors carrying alterations in genes involved in histone modification, 21% in telomere lengthening, and 21% in SWI/SNF complex. Tumor suppressor genes and WNT signaling pathway were each mutated in 51% of tumors. Fifty (13.7%) ACC tumors had a genomic alteration in genes involved in the DNA mismatch repair (MMR) pathway with many tumors also displaying an unusually high number of mutations and a corresponding MMR mutation signature. In addition, genomic alterations in several genes not previously associated with ACC were observed, including IL7R, LRP1B, FRS2 mutated in 6, 8 and 4% of tumors, respectively. In total, 58.5% of ACC (n = 213) had at least one potentially actionable genomic alteration in 46 different genes. As more than half of ACC have one or more potentially actionable genomic alterations, this highlights the value of targeted sequencing for this orphan cancer with a poor prognosis. In addition, significant incidence of MMR gene alterations suggests that immunotherapy is a promising therapeutic for a considerable subset of ACC patients