In the present study, we cloned and sequenced the mRNAs of the Sod3 [extracellular Cu Zn SOD (superoxide dismutase)] gene in Drosophila and identified two mRNA products formed by alternative splicing. These products code for a long and short protein derived from the four transcripts found in global expression studies (Flybase numbers Dmel\CG9027, FBgn0033631). Both mRNA process variants contain an extracellular signalling sequence, a region of high homology to the Sod1 (cytoplasmic Cu Zn SOD) including a conserved AUG start, with the longer form also containing a hydrophobic tail. The two fully processed transcripts are homologous to Caenorhabditis elegans Sod3 mRNA showing the same processing pattern. Using an established KG p-element+ insertion line (KG06029), we demonstrate that the Sod3 codes for an active Cu Zn SOD. We found differing expression patterns across sex with higher levels of expression of Sod3 in females. There is a correlation of Sod1 and Sod3 gene expression and activity that can explain why Sod3 was not seen in earlier studies of Sod1. Finally, we found no effect on lifespan with the Sod3 hypomorph mutation (Sod3KG06029) but did observe a significant increase in resistance to paraquat and H2O2 (hydrogen peroxide).
Extracellular superoxide dismutase (SOD3) in Drosophila is characterized for mRNA splice variants and sex-specific expression. A SOD3 mutant reveals no effect on longevity, enhanced resistance to paraquat and H202, and provided evidence suggesting an interaction with other superoxide dismutases.
alternate RNA splicing; Drosophila; extracellular superoxide dismutase; hydrogen peroxide; oxygen free radical; reactive oxygen species; SOD; H2O2, hydrogen peroxide; NBT, Nitro Blue Tetrazolium; NO, nitric oxide; RNAi, RNA interference; ROS, reactive oxygen species; SOD, superoxide dismutase; Sod1, cytoplasmic Cu Zn superoxide dismutase; Sod2, mitochondrial Mn superoxide dismutase; Sod3, extracellular Cu Zn superoxide dismutase; SOD3v1, SOD3 variant 1; SOD3v2, SOD3 variant 2; TEMED, N,N,N′,N′-tetramethylethylenediamine
Genetic alterations in specific driver genes lead to disruption of cellular pathways and are critical events in the instigation and progression of hepatocellular carcinoma. As a prerequisite for individualized cancer treatment, we sought to characterize the landscape of recurrent somatic mutations in hepatocellular carcinoma. We performed whole exome sequencing on 87 hepatocellular carcinomas and matched normal adjacent tissues to anaverage coverage of 59x. The overall mutation rate was roughly 2 mutations per Mb, with a median of 45 non-synonymous mutations that altered the amino acid sequence (range 2 to 381). We found recurrent mutations in several genes with high transcript levels: TP53 (18%), CTNNB1 (10%), KEAP1 (8%), C16orf62 (8%), MLL4(7%) and RAC2 (5%). Significantly affected gene families include the nucleotide-binding domain and leucine rich repeat containing family, calcium channel subunits, and histone methyltransferases. In particular, the MLL family of methyltransferases for histone H3 lysine 4 were mutated in 20% of tumors.
The NFE2L2-KEAP1 and MLL pathways are recurrently mutated in multiple cohorts of hepatocellular carcinoma.
HCC; mutations; histone methyltransferases
The clinical impact of the biological heterogeneity within HER2-positive (HER2+) breast cancer is not fully understood. Here, we evaluated the molecular features and survival outcomes of the intrinsic subtypes within HER2+ breast cancer.
We interrogated The Cancer Genome Atlas (n = 495) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets (n = 1730) of primary breast cancers for molecular data derived from DNA, RNA and protein, and determined intrinsic subtype. Clinical HER2 status was defined according to American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines or DNA copy-number aberration by single nucleotide polymorphism arrays. Cox models tested the prognostic significance of each variable in patients not treated with trastuzumab (n = 1711).
Compared with clinically HER2 (cHER2)-negative breast cancer, cHER2+ breast cancer had a higher frequency of the HER2-enriched (HER2E) subtype (47.0% vs 7.1%) and a lower frequency of Luminal A (10.7% vs 39.0%) and Basal-like (14.1% vs 23.4%) subtypes. The likelihood of cHER2-positivity in HER2E, Luminal B, Basal-like and Luminal A subtypes was 64.6%, 20.0%, 14.4% and 7.3%, respectively. Within each subtype, only 0.3% to 3.9% of genes were found differentially expressed between cHER2+ and cHER2-negative tumors. Within cHER2+ tumors, HER2 gene and protein expression was statistically significantly higher in the HER2E and Basal-like subtypes than either luminal subtype. Neither cHER2 status nor the new 10-subtype copy number-based classification system (IntClust) added independent prognostic value to intrinsic subtype.
When the intrinsic subtypes are taken into account, cHER2-positivity does not translate into large changes in the expression of downstream signaling pathways, nor does it affect patient survival in the absence of HER2 targeting.
Nearly half of patients with advanced triple negative breast cancer (TNBC) develop brain metastases (BM) and most will also have uncontrolled extracranial disease. This study evaluated the safety and efficacy of iniparib, a small molecule anti-cancer agent that alters reactive oxygen species tumor metabolism and penetrates the blood brain barrier, with the topoisomerase I inhibitor irinotecan in patients with TNBC-BM. Eligible patients had TNBC with new or progressive BM and received irinotecan and iniparib every 3 weeks. Time to progression (TTP) was the primary end point; secondary endpoints were response rate (RR), clinical benefit rate (CBR), overall survival (OS), toxicity, and health-related quality of life. Correlative endpoints included molecular subtyping and gene expression studies on pre-treatment archival tissues, and determination of germline BRCA1/2 status. Thirty-seven patients began treatment; 34 were evaluable for efficacy. Five of 24 patients were known to carry a BRCA germline mutation (4 BRCA1, 1 BRCA2). Median TTP was 2.14 months and median OS was 7.8 months. Intracranial RR was 12 %, while intracranial CBR was 27 %. Treatment was well-tolerated; the most common grade 3/4 adverse events were neutropenia and fatigue. Grade 3/4 diarrhea was rare (3 %). Intrinsic subtyping revealed 19 of 21 tumors (79 %) were basal-like, and intracranial response was associated with high expression of proliferation-related genes. This study suggests a modest benefit of irinotecan plus iniparib in progressive TNBC-BM. More importantly, this trial design is feasible and lays the foundation for additional studies for this treatment-refractory disease.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-014-3039-y) contains supplementary material, which is available to authorized users.
Irinotecan; Iniparib; Brain metastases; Breast cancer; Phase II; Triple negative
Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors.
Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative.
Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation.
Availability and implementation: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra.
Supplementary data are available at Bioinformatics online.
RNA sequencing (RNA-Seq) is often used for transcriptome profiling as well as the identification of novel transcripts and alternative splicing events. Typically, RNA-Seq libraries are prepared from total RNA using poly(A) enrichment of the mRNA (mRNA-Seq) to remove ribosomal RNA (rRNA), however, this method fails to capture non-poly(A) transcripts or partially degraded mRNAs. Hence, a mRNA-Seq protocol will not be compatible for use with RNAs coming from Formalin-Fixed and Paraffin-Embedded (FFPE) samples.
To address the desire to perform RNA-Seq on FFPE materials, we evaluated two different library preparation protocols that could be compatible for use with small RNA fragments. We obtained paired Fresh Frozen (FF) and FFPE RNAs from multiple tumors and subjected these to different gene expression profiling methods. We tested 11 human breast tumor samples using: (a) FF RNAs by microarray, mRNA-Seq, Ribo-Zero-Seq and DSN-Seq (Duplex-Specific Nuclease) and (b) FFPE RNAs by Ribo-Zero-Seq and DSN-Seq. We also performed these different RNA-Seq protocols using 10 TCGA tumors as a validation set.
The data from paired RNA samples showed high concordance in transcript quantification across all protocols and between FF and FFPE RNAs. In both FF and FFPE, Ribo-Zero-Seq removed rRNA with comparable efficiency as mRNA-Seq, and it provided an equivalent or less biased coverage on gene 3′ ends. Compared to mRNA-Seq where 69% of bases were mapped to the transcriptome, DSN-Seq and Ribo-Zero-Seq contained significantly fewer reads mapping to the transcriptome (20-30%); in these RNA-Seq protocols, many if not most reads mapped to intronic regions. Approximately 14 million reads in mRNA-Seq and 45–65 million reads in Ribo-Zero-Seq or DSN-Seq were required to achieve the same gene detection levels as a standard Agilent DNA microarray.
Our results demonstrate that compared to mRNA-Seq and microarrays, Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts. Moreover, Ribo-Zero-Seq and DSN-Seq have consistent transcript quantification using FFPE RNAs, suggesting that RNA-Seq can be used with FFPE-derived RNAs for gene expression profiling.
Electronic supplementary material
The online version of this article (doi: 10.1186/1471-2164-15-419) contains supplementary material, which is available to authorized users.
RNA sequencing; FFPE; RNA depletion; Ribo-zero; Gene expression; Microarray
The Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico was recently established to better understand the impacts of prenatal exposure to inorganic arsenic (iAs). In the present study, we examined a subset (n=40) of newborn cord blood samples for microRNA (miRNA) expression changes associated with in utero arsenic exposure. Levels of iAs in maternal drinking water (DW-iAs) and maternal urine were assessed. Levels of DW-iAs ranged from below detectable values to 236 μg/L (mean=51.7 μg/L). Total arsenic in maternal urine (U-tAs) was defined as the sum of iAs and its monomethylated and dimethylated metabolites (MMAs and DMAs, respectively) and ranged from 6.2 to 319.7 μg/L (mean=64.5 μg/L). Genome-wide miRNA expression analysis of cord blood revealed 12 miRNAs with increasing expression associated with U-tAs. Transcriptional targets of the miRNAs were computationally predicted and subsequently assessed using transcriptional profiling. Pathway analysis demonstrated that the U-tAs-associated miRNAs are involved in signaling pathways related to known health outcomes of iAs exposure including cancer and diabetes mellitus. Immune response-related mRNAs were also identified with decreased expression levels associated with U-tAs, and predicted to be mediated in part by the arsenic-responsive miRNAs. Results of this study highlight miRNAs as novel responders to prenatal arsenic exposure that may contribute to associated immune response perturbations.
arsenic; prenatal; epigenetics; microRNAs; gene expression
We demonstrate that the androgen receptor (AR) regulates a transcriptional program of DNA repair genes that promotes prostate cancer radioresistance, providing a potential mechanism by which androgen deprivation therapy (ADT) synergizes with ionizing radiation (IR). Using a model of castration-resistant prostate cancer, we show that second-generation antiandrogen therapy results in downregulation of DNA repair genes. Next, we demonstrate that primary prostate cancers display a significant spectrum of AR transcriptional output which correlates with expression of a set of DNA repair genes. Employing RNA-seq and ChIP-seq, we define which of these DNA repair genes are both induced by androgen and represent direct AR targets. We establish that prostate cancer cells treated with IR plus androgen demonstrate enhanced DNA repair and decreased DNA damage and furthermore that antiandrogen treatment causes increased DNA damage and decreased clonogenic survival. Finally, we demonstrate that antiandrogen treatment results in decreased classical non-homologous end joining.
Topoisomerases are expressed throughout the developing and adult brain and are mutated in some individuals with autism spectrum disorder (ASD). However, how topoisomerases are mechanistically connected to ASD is unknown. Here we found that topotecan, a Topoisomerase 1 (TOP1) inhibitor, dose-dependently reduced the expression of extremely long genes in mouse and human neurons, including nearly all genes >200 kb. Expression of long genes was also reduced following knockdown of Top1 or Top2b in neurons, highlighting that each enzyme was required for full expression of long genes. By mapping RNA polymerase II density genome-wide in neurons, we found that this length-dependent effect on gene expression was due to impaired transcription elongation. Interestingly, many high confidence ASD candidate genes are exceptionally long and were reduced in expression following TOP1 inhibition. Our findings suggest that chemicals and genetic mutations that impair topoisomerases could commonly contribute to ASD and other neurodevelopmental disorders.
Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes.
Patients and Methods
Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) –positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance.
Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, human epidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) –positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa.
Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.
MEK1/2 inhibitors such as AZD6244 are in clinical trials for the treatment of multiple cancers, including breast cancer. Targeted kinase inhibition can induce compensatory kinome changes, rendering single therapeutic agents ineffective. To identify target proteins to be used in a combinatorial approach to inhibit tumor cell growth, we used a novel strategy that identified microRNAs (miRNAs) that synergized with AZD6244 to inhibit the viability of the claudin-low breast cancer cell line MDA-MB-231. Screening of a miRNA mimic library revealed the ability of miR-9-3p to significantly enhance AZD6244-induced extracellular signal-regulated kinase inhibition and growth arrest, while miR-9-3p had little effect on growth alone. Promoter methylation of mir-9 genes correlated with low expression of miR-9-3p in different breast cancer cell lines. Consistent with miR-9-3p having synthetic enhancer tumor suppressor characteristics, miR-9-3p expression in combination with MEK inhibitor caused a sustained loss of c-MYC expression and growth inhibition. The β1 integrin gene (ITGB1) was identified as a new miR-9-3p target, and the growth inhibition seen with small interfering RNA knockdown or antibody blocking of ITGB1 in combination with MEK inhibitor phenocopied the growth inhibition seen with miR-9-3p plus AZD6244. The miRNA screen led to identification of a druggable protein, ITGB1, whose functional inhibition synergizes with MEK inhibitor.
Due to the heterogeneous nature of breast cancer and the widespread use of single-gene studies, there is limited knowledge of multi-gene, locus-specific DNA methylation patterns in relation to molecular subtype and clinical features. We, therefore, quantified DNA methylation of 70 candidate gene loci in 140 breast tumors and matched normal tissues and determined associations with gene expression and tumor subtype. Using Sequenom’s EpiTYPER platform, approximately 1,200 CpGs were interrogated and revealed six DNA methylation patterns in breast tumors relative to matched normal tissue. Differential methylation of several gene loci was observed within all molecular subtypes, while other patterns were subtype-dependent. Methylation of numerous gene loci was inversely correlated with gene expression, and in some cases, this correlation was only observed within specific breast tumor subtypes. Our findings were validated on a larger set of tumors and matched adjacent normal tissue from The Cancer Genome Atlas dataset, which utilized methylation data derived from both Illumina Infinium 27 and 450 k arrays. These findings highlight the need to control for subtype when interpreting DNA methylation results, and the importance of interrogating multiple CpGs across varied gene regions.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-013-2738-0) contains supplementary material, which is available to authorized users.
Epigenetic; Methylation; Breast cancer; Illumina; BRCA1; Basal-like
Five molecular subtypes (luminal A, luminal B, HER2-enriched, basal-like, and claudin-low) with clinical implications exist in breast cancer. Here, we evaluated the molecular and phenotypic relationships of (1) a large in vitro panel of human breast cancer cell lines (BCCLs), human mammary fibroblasts (HMFs), and human mammary epithelial cells (HMECs); (2) in vivo breast tumors; (3) normal breast cell subpopulations; (4) human embryonic stem cells (hESCs); and (5) bone marrow-derived mesenchymal stem cells (hMSC). First, by integrating genomic data of 337 breast tumor samples with 93 cell lines we were able to identify all the intrinsic tumor subtypes in the cell lines, except for luminal A. Secondly, we observed that the cell lines recapitulate the differentiation hierarchy detected in the normal mammary gland, with claudin-low BCCLs and HMFs cells showing a stromal phenotype, HMECs showing a mammary stem cell/bipotent progenitor phenotype, basal-like cells showing a luminal progenitor phenotype, and luminal B cell lines showing a mature luminal phenotype. Thirdly, we identified basal-like and highly migratory claudin-low subpopulations of cells within a subset of triple-negative BCCLs (SUM149PT, HCC1143, and HCC38). Interestingly, both subpopulations within SUM149PT were enriched for tumor-initiating cells, but the basal-like subpopulation grew tumors faster than the claudin-low subpopulation. Finally, claudin-low BCCLs resembled the phenotype of hMSCs, whereas hESCs cells showed an epithelial phenotype without basal or luminal differentiation. The results presented here help to improve our understanding of the wide range of breast cancer cell line models through the appropriate pairing of cell lines with relevant in vivo tumor and normal cell counterparts.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-013-2743-3) contains supplementary material, which is available to authorized users.
Breast cancer; Cell lines; Intrinsic subtype; Stem cell; Tumor-initiating cell
Recent studies suggest that intrinsic breast cancer subtypes may differ in their responsiveness to specific chemotherapy regimens. We examined this hypothesis on NCIC.CTG MA.5, a clinical trial randomizing premenopausal women with node-positive breast cancer to adjuvant CMF (cyclophosphamide-methotrexate-fluorouracil) versus CEF (cyclophosphamide-epirubicin-fluorouracil) chemotherapy.
Intrinsic subtype was determined for 476 tumors using the quantitative reverse transcriptase PCR PAM50 gene expression test. Luminal A, luminal B, HER2-enriched (HER2-E), and basal-like subtypes were correlated with relapse-free survival (RFS) and overall survival (OS), estimated using Kaplan-Meier plots and log-rank testing. Multivariable Cox regression analyses determined significance of interaction between treatment and intrinsic subtypes.
Intrinsic subtypes were associated with RFS (P = 0005) and OS (P < 0.0001) on the combined cohort. The HER2-E showed the greatest benefit from CEF versus CMF, with absolute 5-year RFS and OS differences exceeding 20%, whereas there was a less than 2% difference for non-HER2-E tumors (interaction test P = 0.03 for RFS and 0.03 for OS). Within clinically defined Her2+ tumors, 79% (72 of 91) were classified as the HER2-E subtype by gene expression and this subset was strongly associated with better response to CEF versus CMF (62% vs. 22%, P = 0.0006). There was no significant difference in benefit between CEF and CMF in basal-like tumors [n = 94; HR, 1.1; 95% confidence interval (CI), 0.6−.1 for RFS and HR, 1.3; 95% CI, 0.7−2.5 for OS].
HER2-E strongly predicted anthracycline sensitivity. The chemotherapy-sensitive basal- like tumors showed no added benefit for CEF over CMF, suggesting that nonanthracycline regimens may be adequate in this subtype although further investigation is required.
Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry.
Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes.
Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease.
In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen.
Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, for a given sample, are expected to be almost completely false positives. We show that these blacklist positions are specific to the alignment algorithm and read length used, and BlackOPs allows users to generate a blacklist specific to their experimental setup. We queried the dbSNP and COSMIC variant databases and found numerous variants indistinguishable from mapping errors. We demonstrate how filtering against blacklist positions reduces the number of potential false variants using an RNA-seq glioblastoma cell line data set. In summary, accounting for mapping-caused variants tuned to experimental setups reduces false positives and, therefore, improves genome characterization by high-throughput sequencing.
Human lung adenocarcinomas with activating mutations in EGFR (epidermal growth factor receptor) often respond to treatment with EGFRtyrosine kinase inhibitors(TKIs),butthe magnitude of tumour regression is variable and transient1,2. This heterogeneity in treatment response could result from genetic modifiers that regulate the degree to which tumour cells are dependent on mutant EGFR. Through a pooled RNA interference screen, we show that knockdown of FAS and several components of the NF-κB pathway specifically enhanced cell death induced by the EGFR TKI erlotinib in EGFR-mutant lung cancer cells. Activation of NF-κB through overexpression of c-FLIP or IKK (also known as CFLAR and IKBKB, respectively), or silencing of IκB (also known as NFKBIA), rescued EGFR-mutant lung cancer cells from EGFR TKI treatment. Genetic or pharmacologic inhibition of NF-κB enhanced erlotinib-induced apoptosis in erlotinib-sensitive and erlotinib-resistant EGFR-mutant lung cancer models. Increased expression of the NF-κB inhibitor IκB predicted for improved response and survival in EGFR-mutant lung cancer patients treated with EGFR TKI. These data identify NF-κB as a potential companion drug target, together with EGFR, in EGFR-mutant lung cancers and provide insight into the mechanisms by which tumour cells escape from oncogene dependence.
In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.
We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).
Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.
Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.
Next-generation sequencing technologies have become important tools for genome-wide studies. However, the quality scores that are assigned to each base have been shown to be inaccurate. If the quality scores are used in downstream analyses, these inaccuracies can have a significant impact on the results.
Here we present ReQON, a tool that recalibrates the base quality scores from an input BAM file of aligned sequencing data using logistic regression. ReQON also generates diagnostic plots showing the effectiveness of the recalibration. We show that ReQON produces quality scores that are both more accurate, in the sense that they more closely correspond to the probability of a sequencing error, and do a better job of discriminating between sequencing errors and non-errors than the original quality scores. We also compare ReQON to other available recalibration tools and show that ReQON is less biased and performs favorably in terms of quality score accuracy.
ReQON is an open source software package, written in R and available through Bioconductor, for recalibrating base quality scores for next-generation sequencing data. ReQON produces a new BAM file with more accurate quality scores, which can improve the results of downstream analysis, and produces several diagnostic plots showing the effectiveness of the recalibration.
Next-generation sequencing; Quality score; Recalibration; Bioinformatics; Bioconductor
Preoperative aromatase inhibitor (AI) treatment promotes breast-conserving surgery (BCS) for estrogen receptor (ER) –positive breast cancer. To study this treatment option, responses to three AIs were compared in a randomized phase II neoadjuvant trial designed to select agents for phase III investigations.
Patients and Methods
Three hundred seventy-seven postmenopausal women with clinical stage II to III ER-positive (Allred score 6-8) breast cancer were randomly assigned to receive neoadjuvant exemestane, letrozole, or anastrozole. The primary end point was clinical response. Secondary end points included BCS, Ki67 proliferation marker changes, the Preoperative Endocrine Prognostic Index (PEPI), and PAM50-based intrinsic subtype analysis.
On the basis of clinical response rates, letrozole and anastrozole were selected for further investigation; however, no other differences in surgical outcome, PEPI score, or Ki67 suppression were detected. The BCS rate for mastectomy-only patients at presentation was 51%. PAM50 analysis identified AI-unresponsive nonluminal subtypes (human epidermal growth factor receptor 2 enriched or basal-like) in 3.3% of patients. Clinical response and surgical outcomes were similar in luminal A (LumA) versus luminal B tumors; however, a PEPI of 0 (best prognostic group) was highest in the LumA subset (27.1% v 10.7%; P = .004).
Neoadjuvant AI treatment markedly improved surgical outcomes. Ki67 and PEPI data demonstrated that the three agents tested are biologically equivalent and therefore likely to have similar adjuvant activities. LumA tumors were more likely to have favorable biomarker characteristics after treatment; however, occasional paradoxical increases in Ki67 (12% of tumors with > 5% increase after therapy) suggest treatment-resistant cells, present in some LumA tumors, can be detected by post-treatment profiling.
There is significant need to identify novel prostate cancer drug targets because current hormone therapies eventually fail, leading to a drug-resistant and fatal disease termed castration-resistant prostate cancer. To functionally identify genes that, when silenced, decrease prostate cancer cell proliferation or induce cell death in combination with antiandrogens, we employed an RNA interference-based short hairpin RNA barcode screen in LNCaP human prostate cancer cells. We identified and validated four candidate genes (AKT1, PSMC1, STRADA, and TTK) that impaired growth when silenced in androgen receptor positive prostate cancer cells and enhanced the antiproliferative effects of antiandrogens. Inhibition of AKT with a pharmacologic inhibitor also induced apoptosis when combined with antiandrogens, consistent with recent evidence for PI3K and AR pathway crosstalk in prostate cancer cells. Recovery of hairpins targeting a known prostate cancer pathway validates the utility of shRNA library screening in prostate cancer as a broad strategy to identify new candidate drug targets.