Radiotherapy (RT) has been considered a local modality and outcomes have emphasized local and regional control of tumors. Recent data suggests that RT may activate the immune system and the combination of radiation therapy and immune therapies may have the potential to improve both local and distant control of tumor deposits. Below we review principals underlying the concepts of combining both modalities. The utility of radiotherapy (RT) as an anti-tumor agent is usually based on the fact that radiation can induce irreparable DNA damage, and eventually cell death through a variety of mechanisms including; mitotic catastrophe, apoptosis, senescence, and autophagy . ImproveThe principals of tumor immunology were originally established by pioneering work of Burnet and Thomas when they proposed that nascent tumors can be recognized and eliminated by the host immune system in a process they termed “cancer immunosurveillance”  viral proteins, (2) mutated versions of self-proteins that include point mutations and oncogenic fusion proteins generated by recombinatorial events, or (3) non-mutated self-proteins enriched in tumor cells but with shared expression on non-tumor tissue  radiation has been shown to directly upregulate the expression of some tumor antigens including tumor antigens associated with viral transformation , and CT The innate immune system is equipped with many molecular sensors that facilitate the recognition of unique molecular patterns found in the myriad pathogens present in the environment. These sensors are localized to subcellular locations including the plasma membrane, endosomes, and the cytoplasm poised to detect invading pathogens. Charles Janeway proposed a cellular recognition system, consisting of receptors that could exclusively recognize unique features of pathogens , that formed the central basis for “self” vs “non-self” discrimination. This pathogen recognition system was thought to explain why antigens derived from pathogens elicit potent adaptive immune responses, and self-antigens are “ignored.” A highly provocative amendment to this hypothesis was proposed by Polly Matzinger, who hypothesized that tissue injury in the absence of pathogens could elicit innate immune recognition through stress signals that she collectively termed “Danger Signals” . It is n+ T cells (T cell cross-priming). Since TLR4 binds ligands at the plasma membrane, HMGB1 must be released into the extracellular space in order to engage TLR4. Extracellular exposure could be mediated by direct necrotic cell death or secondary necrosis of lingering apoptotic bodies that are inefficiently cleared. Conceptually, apoptotic death of tumor cells is predicted to conceal HMGB1 from TLR4-mediated recognition (+ T cells (High mobility group box 1 (HMGB1) is a prototypical “alarmin” that was shown to be a central mediator in the immunogenicity of dying tumor cells following irradiation . Normallognition . Howeverognition . Radiatiognition . Importa T cells . The lig T cells . These c+ T cells following challenge with dying tumor cells  several days following treatment of established tumors with ablative single dose local RT . Our group demonstrated that treatment of tumors with local ablative RT could greatly enhance the cross-priming capacity of tumor-infiltrating DCs (TIDCs), and this effect was shown to be critically dependent on type I interferon (IFN) signaling in bone marrow-derived hematopoietic cells  accumulation depending on the dose and timing . TherefoAn accepted hypothesis is that anti-CTLA-4 blocking antibodies promote enhanced T cell activation and proliferation to promote effector cell priming . In precEnhancement of effector cell priming is a shared mechanism between anti-CTLA-4 and other targeted therapies employing agonistic antibodies against the costimulatory receptors OX40, 4-1BB (CD137), and CD27  and systemic IL-2 in melanoma and renal cell carcinoma demonstrated that this combination could result in impressive responses in both tumor types . Additio T cells . ImportaIn addition to the goal of improving T cell activation and effector cell generation, strategies that target immune suppressive mechanism in the tumor microenvironment are equally important. Local RT does have the ability to modify the tumor microenvironment, however, many tumors exploit natural immune regulatory mechanisms to subvert induced T cells responses. Expression of programmed death ligand-1 (PD-L1) in the tumor microenvironment can deliver an inhibitory signal through it’s receptor PD-1 that is expressed on a majority of activated effector T cells. PD-L1 expression has been observed across many tumor types  where itFrom the data discussed above it is clear that combination strategies employing high dose ablative RT and immunotherapy hold a lot of promise for improving anti-tumor immunity and mediating complete tumor regression. There are many important outstanding questions before RT and immunotherapy can reliably be combined in cancer therapy. Amongst the most important are what is (are) the optimal fractionation (dose delivery of radiation) schemes to increase anti-tumor immunity? Does daily fractionation continuously kill infiltrating T cells and/or reduce their function, or are tumor-infiltrating activated T cells functionally resistant to the low doses employed in traditional fractionation or hyperfractionated schedules? Does inclusion of the dLNs suppress or enhance the immunogenic effects of radiation, and does the timing of dLN irradiation change the response to treatment or therapeutic vaccination. What is the optimal “immune activating” strategy, e.g., high dose cytokines, vaccination, etc.? Answers to these and other questions may improve the local effects of RT and help to understand the basis of activating and improving the local tumor response to RT and the abscopal effect against distant metastasis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The relationship between the exact site of promoter methylation and its effect on gene silencing, and the patient's subsequent response to therapy, is still being defined. The aim of this study was to comprehensively characterize cytosine-guanine (CpG) dinucleotide methylation across the entire MGMT promoter and to correlate individual CpG site methylation patterns to mRNA expression, protein expression, and progression-free survival. To best identify the specific MGMT promoter region most predictive of gene silencing and response to therapy, we determined the methylation status of all 97 CpG sites in the MGMT promoter in tumor samples from 70 GBM patients using quantitative bisulfite sequencing. We next identified the CpG site specific and regional methylation patterns most predictive of gene silencing and improved progression-free survival. Using this data, we propose a new classification scheme utilizing methylation data from across the entire promoter and show that an analysis based on this approach, which we call 3R classification, is predictive of progression-free survival . To adapt this approach to the clinical setting, we used a methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) test based on the 3R classification and show that this test is both feasible in the clinical setting and predictive of progression free survival . We discuss the potential advantages of a test based on this promoter-wide analysis and compare it to the commonly used methylation-specific PCR test. Further prospective validation of these two methods in a large independent patient cohort will be needed to confirm the added value of promoter wide analysis of MGMT methylation in the clinical setting.O The current standard of care for patients diagnosed with glioblastoma multiforme (GBM) has evolved to include surgery with maximum feasible resection 6 position of guanine is a particularly cytotoxic lesion. Normal cells contain DNA repair proteins that remove these alkyl groups or alkylated nucleotides allowing for normal DNA replication. One of the DNA-repair proteins, O6-alkylguanine DNA alkyltransferase (AGT), removes alkyl adducts from the O6 position of guanine and the O4 position of thymine, effectively restoring these DNA bases and preventing TMZ-induced cell death. The DNA-repair protein AGT is encoded by the gene O6-Methlyguanine-DNA-methyltransferase (MGMT). Tumor cells expressing this gene have been shown to be resistant to alkylating agents, while those that lack the DNA-repair protein appear to be more susceptible TMZ damages DNA by introducing alkyl groups at multiple sites along the DNA backbone, impairing DNA replication, and triggering cell death. The alkylation of the OAlthough MGMT methylation status appears to be a predictive marker of response to TMZ in patients with newly diagnosed GBM Two significant issues need to be addressed in order to optimize MGMT methylation testing for use in clinical practice. First, the specific MGMT promoter regions most predictive of patient response to therapy need to be identified and validated. Second, the heterogeneity of methylation patterns across the promoter region and within individual tumors needs to be characterized in order to optimize probe design for PCR-based methods. To address these issues, we characterized MGMT promoter methylation patterns using bisulfite sequencing to obtain quantitative methylation results for all 97 CpG sites in 70 newly diagnosed GBM patients. Using a similar approach, Everhard et al. have previously shown a correlation between promoter-wide methylation patterns and MGMT mRNA expression This study was reviewed and approved by human subjects committees at the University of Iowa IRB (IRB199812055), and Western IRB (IRB00000533) in compliance with the ethical principles as set forth in the report of the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research entitled “Ethical Principles and Guidelines for the Protection of Human Subjects of Research (Belmont Report)”. The research protocol was also approved by the Swedish Neuroscience Institute research steering committee. All participants provided written informed consent according to IRB guidelines prior to participation in this study.Patient tissue samples were obtained from two institutions, the University of Iowa Hospital and Clinics, IA, USA (Iowa cohort) and Swedish Medical Center, WA, USA (Swedish cohort). All patients gave informed consent prior to collection of specimens according to institutional guidelines. Tissue samples were snap-frozen in the operating room immediately during surgery with an adjacent specimen sent to pathology for diagnosis by a board-certified neuropathologist. Each tumor specimen was archived at −80°C for further DNA, RNA and protein studies. All patients underwent surgery for tumor resection, had post-operative diagnosis of WHO grade IV glioblastoma multiforme (GBM), received radiation therapy with concurrent temozolomide chemotherapy and subsequent temozolomide adjuvant chemotherapy. For the Iowa cohort surgeries were performed between June 1999 to July 2008 and for the Swedish cohort surgeries were performed during the period of February 2007 to April 2010. All clinical data was collected prospectively according to institutional guidelines. Progression free survival (PFS) was calculated as the number of days between the date of surgery and the date of MRI scan that showed disease progression or recurrence.st round, F- AAA ACR AAA TCT AAA ACR AAA CRA AAC CRA AAA CCT AAA AAA AA, R- TAT TAT AGG TTT TGG AGG TTG TTT TTA CGG TTT TTT GAT, and for 2nd round, F- AAA CTA AAA CRA AAC CCR AAA AAA ACR AAA TAT TCC, R- TAG GGT TTT TGT TGG TTT GGG GGT TTT TGA T. To amplify the downstream region, the following primer pairs were used: for 1st round, F- CCA ATC CAC AAT CAC TAC AAC RCA ACC TAA TCC AAA, R- GAA GGG TTA TTY GGG TTA GGY GTA TAG GGT, and for 2nd round, F- CCC AAA CCC GAA AAA AAA CTA AAC AAC ACC TAA AAA A, R- GGY GTT TAG YGA GGA TGY GTA GAT TGT TTT AGG TT. The PCR products were cleaned using ChargeSwith PCR Clean-Up Kit  and cloned using the TOPO TA cloning kit. The bacterial colonies were inoculated in 96 well plates in 2YT media with appropriate antibiotic. Plasmid DNA were purified using Sprint Prep  on a Biomek FX(Beckman Coulter). DNA was sequenced using Big Dye Terminator v3.1  and the sequences were resolved on a 3730 XL DNA Analyzer (Applied Biosystems). Multiple clones were sequenced for each patient sample (median of 10 clones). The sequence data was then assembled using the phredPhrap program Genomic DNA was extracted from 25 mg of frozen GBM tissue using ChargeSwitch Genomic DNA mini tissue kit . Sodium bisulfite modification of 4 ug was carried out using the MethylEasy DNA bisulfite modification kit . The MGMT promoter associated CpG island was identified using the UCSC genome browser −.Total RNA was isolated from tissue samples with Triazol (Invitrogen), and then cleaned with RNeasy MinElute Cleanup Kit (Qiagen). 1 ug of total RNA was used to generate 100 ul of cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Real-time PCR of MGMT was performed on the ABI PRISM 7900 HT detection system using a taqman probe  and taqman reagents under default conditions: 95°C for 10 minutes, 40 cycles of 95°C for 15 seconds, and 60°C for 1 minute with human beta-glucuronidase (hGUS) as endogenous control. All assays were done in triplicate. The expression level of MGMT for each tissue sample was calculated compared to the hGUS expression level using the formula 2Tissue sections were fixed in 10% buffered formalin and blocked in paraffin. Sections of 6 micron thickness were incubated with antibodies to O6-methylguanine-DNA methyltransferase (MGMT) from Santa Cruz Biotechnology (MT 3.1/sc-56157). Vizualization of the reaction product was accomplished using a biotinylated secondary antibody exposed to an avidin and biotinylated horseradish peroxidase macromolecular complex. A representative portion of the tumor containing less than 10% necrosis and without evidence of excessive macrophage infiltration was chosen for MGMT IHC studies. The entire immunoslide was reviewed along with the hematoxylin and eosin-stained slide and the percentage of tumor nuclei positive for MGMT was determined. GBM tissue with high MGMT protein expression was used as a positive control. Tissue samples were also assayed with no primary antibody as negative controls to rule out non-specific reaction. Staining of endothelial cells was used as positive internal control. As per Capper et al. see  section G TTC CCT AAG GGT TGG A, R- GTG CCA GCA AGA TCC AAT CTA GA primers were used. Three sets of primers were used for detecting methylation at CpG site 8 (MLPA-R1), 22 (MLPA-R2) and 80 (MLPA-R3). These CpG sites were chosen based on the presence of the methylation-sensitive HhaI recognition site. CpG 80 also correlated well with mRNA, protein expression and PFS whereas CpG 22 correlated well with mRNA expression and PFS . Additionally, the data were also checked by manual analysis.MLPA probes containing methylation-sensitive HhaI recognition site (GCGC) were annealed to genomic regions  was used for this analysis.The correlation of individual CpG site methylation with MGMT mRNA expression level was calculated using Spearman's rank correlation. Fractional methylation and mRNA expression level were both continuous variables. Fractional methylation of a promoter region was calculated by averaging methylation of all CpG sites in that region. For correlation of methylation with IHC staining, binary values were used for both methylation, cutoff set at 0.1 P to distinguish it from the commercially available qMSP P to the commercially-available qMSP on ten patient samples for which we found 100% concordant results (1).Results of the commercially-available qMSP test We obtained GBM tissue samples from 70 patients, 45 men (64%) and 25 women (36%) with a median age of 60 years . All were diagnosed with primary GBM with a single lesion, were treatment naïve, underwent surgery for maximal resection and received standard external-beam radiotherapy (59.4 gray) with concomitant TMZ (single daily dose 75 mg/m2) followed by monthly cycles of TMZ chemotherapy (daily dose 200 mg/m2 for five consecutive days)DNA for assessment of MGMT promoter methylation was available from all 70 patients. MGMT immunohistochemistry (IHC) was performed on 31 patients (Swedish cohort). RNA from 46 patients was available for assessment of MGMT gene expression. Progression-free survival (PFS) data was available for 44 patients out of which 39 patients had at least one year follow-up. Fourteen patients with less than 95% tumor resection were excluded from PFS analysis and twelve patients were lost to follow-up. The Venn diagram in Among the 44 patients with PFS data, the median PFS was 269 days . PFS was not associated with gender but did show a significant association with age where we observed a median PFS of 314 days in younger patients vs 197 days in older patients . Of note, for the 24 patients in this group for whom IHC results were available, patients with decreased MGMT protein expression  had significantly better PFS, 540 days vs 197 days, compared to patients with higher MGMT protein expression   . When paHigh resolution bisulfite sequencing of the entire CpG island in 70 GBM samples revealed highly heterogeneous methylation profiles . HierarcMethylation profile classification based on these three regions led to the identification of four methylation patterns: Group A, the unmethylated group, consisting of samples with all three regions unmethylated; Group B, the lightly methylated group, consisting of samples with only one region methylated; Group C, the moderately methylated group, consisting of samples with any two regions methylated; and Group D, consisting of samples that were densely methylated .Methylation of any of the three major CpG cluster regions was significantly correlated with mRNA expression (p<0.05). The methylation status of regions R2 and R3, but not R1, showed significant concordance with protein expression and PFS .When analyzed by groups, the largely unmethylated group A consisted of a subset of samples with high mRNA expression  and high protein expression (p = 0.02) when compared to Groups C and D. Twelve out of fourteen patients had disease progression before one year . In contrast, Group D, the highly methylated group in which all three regions are methylated compared to Groups A and B, had low mRNA expression  and negative protein expression (p = 0.001). Six out of the 10 patients in this group had PFS greater than one year .Group B, the lightly methylated group consisting of samples with one out of three regions methylated, was similar to Group A; consisting of a subset of samples with high protein expression (p = 0.04) and high mRNA expression approaching statistical significance . Nine out of nine patients had disease progression before one year . Group C, the moderately methylated group consisting of samples with any two regions methylated, was similar to Group D. The samples in this group compared to groups A and B had low mRNA expression  and negative protein expression (p = 0.006). Five out of six patients had over one year progression-free-survival . Subgroup analysis of Groups B and C did not reveal any significant difference in correlation with mRNA expression, protein expression or PFS within each subgroup compared with the parent group.We classified Group C and Group D samples as methylated and Group A and B samples as unmethylated. This classification of methylation patterns (3R classification) showed strong correlation with mRNA expression and protein expression . The metAnalysis of the entire MGMT promoter suggested that a test investigating methylation of individual CpG sites across the entire promoter might be more informative than methods focused on a single region. We recognize that bisulfite sequencing for 3R classification is not feasible in the clinical setting as it is an expensive and time consuming method that cannot be performed on paraffin-fixed or archived tissue. To overcome these limitations, we used an MS-MLPA based test Results of the commercially available qMSP test  In this study, we sought to further define the relationship between MGMT promoter methylation, mRNA expression, protein IHC and clinical response to therapy. We chose a uniform patient population who shared the same diagnosis and underwent similar treatment regimens. We used progression-free-survival as the clinical outcome measure in order to avoid differences between patients in response to post-progression treatment. This endpoint has been recently validated by a study which showed that six-month progression-free survival can be used as an alternative primary efficacy endpoint to overall survival in newly diagnosed glioblastoma patients receiving temozolomide In general, we observed that methylation profiles in GBM patients are heterogeneous across the promoter region and also within individual clones from the same tissue sample, most likely representing the heterogeneity of cell types within the tumor sample . MethylaOur findings with respect to the effect of MGMT methylation on MGMT transcription are consistent with those of an earlier study in cell lines P methylation status, although not significantly correlated with PFS, did show a lower frequency of disease progression in the methylated group (45% vs 75% at 1-year follow-up). We suspect that this would trend toward statistical significance with a larger patient population. Of note, when the methylation status was determined using our 3R method, the frequency of disease progression was 31% in the methylated group vs. 91% in the unmethylated group, which achieved statistical significance within the study cohort. These results show for the first time that the upstream region is potentially important in considering the design and development of a clinical test to measure MGMT methylation.MGMT methylation assessed by the qMSP test has been consistently shown to predict response to the alkylating agent TMZ, measured by either PFS or overall survival, in GBM patients The MGMT methylation patterns observed in this study confirm that the downstream region interrogated by the qMSP test is well chosen given the constraint that only one region is assessed. But our data also suggest that a semi-quantitative test that can measure methylation across the entire promoter and is not dependent on co-methylation of multiple sites may be more informative than qMSP and other MSP-based tests that measure methylation only at the single downstream region and appear to fail when the CpG sites spanning MSP primers are not densely methylated Click here for additional data file.Figure S2Clonal heterogeneity within an individual tumor sample. Each line represents a single clone sequenced from an individual patient's tumor sample. Each circle represents a single CpG site with the filled circles indicating that the site is methylated. For an individual tumor sample, the fractional methylation at a single CpG site is calculated by dividing the number of positive methylated clones by the total number of clones sequenced. In this patient, a total of 24 clones were sequenced.(DOC)Click here for additional data file.Figure S3Age and MGMT protein predict PFS in GBM. Kaplan-Meier estimation of PFS determined using: A) Age - The median PFS in younger patients was 314 days vs 197 days in older patients . B) Gender - The median PFS for the females was 224 days vs. 258 days for male patients , and C) MGMT protein (IHC) – The median PFS of patients with decreased MGMT protein expression  was significantly better, 540 days vs 197 days, compared to patients with higher MGMT protein expression  .(DOC)Click here for additional data file.Table S1Single site correlation.(DOC)Click here for additional data file.Table S2Correlation of MGMT promoter methylation patterns with MGMT mRNA expression, MGMT protein expression and PFS.(DOC)Click here for additional data file.


The identification of gene fusions promises to play an important role in personalized cancer treatment decisions. Many rare gene fusion events have been identified in fresh frozen solid tumors from common cancers employing next-generation sequencing technology. However the ability to detect transcripts from gene fusions in RNA isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues, which exist in very large sample repositories for which disease outcome is known, is still limited due to the low complexity of FFPE libraries and the lack of appropriate bioinformatics methods. We sought to develop a bioinformatics method, named gFuse, to detect fusion transcripts in FFPE tumor tissues. An integrated, cohort based strategy has been used in gFuse to examine single-end 50 base pair (bp) reads generated from FFPE RNA-Sequencing (RNA-Seq) datasets employing two breast cancer cohorts of 136 and 76 patients. In total, 118 fusion events were detected transcriptome-wide at base-pair resolution across the 212 samples. We selected 77 candidate fusions based on their biological relevance to cancer and supported 61% of these using TaqMan assays. Direct sequencing of 19 of the fusion sequences identified by TaqMan confirmed them. Three unique fused gene pairs were recurrent across the 212 patients with 6, 3, 2 individuals harboring these fusions respectively. We show here that a high frequency of fusion transcripts detected at the whole transcriptome level correlates with poor outcome (P<0.0005) in human breast cancer patients. This study demonstrates the ability to detect fusion transcripts as biomarkers from archival FFPE tissues, and the potential prognostic value of the fusion transcripts detected. Oncogenesis is understood to be driven by ten distinctive and interactive capabilities that enable tumor growth and metastasis The detection of functional gene fusion events generated by chromosomal translocations has been facilitated by the application of RNA-Seq technologies. Numerous bioinformatics methods are available to detect fusion transcripts from RNA-Seq paired-end read data  method that was devised for analysis of microarray databases In this study, we detected fusion transcripts in two breast cancer cohorts, the Providence cohort of 136 patients and the Rush cohort of 76 patients with average FFPE block archive ages of 8.5 years and 13.4 years respectively One hundred thirty-six primary breast cancer FFPE tumor specimens with clinical outcomes were provided by Providence St. Joseph Medical Center , with institutional review board approval We define a fusion junction as a unique pair of donor and acceptor genomic positions such as “+chr17:5250220->+chr17:11532734”, and a fusion or fusion event as an occurrence of a particular fusion junction within a patient sample. The definition of symbols used to define each junction is: “->” indicates the splicing direction from donor to acceptor, “+” indicates the transcription direction on the top of chromosome strand, and “-” indicates the transcription direction on the bottom of the chromosome strand. The donor genomic position is the last base of the preserved side of the donor and the acceptor genomic position is the first base of the preserved side of the acceptor.The fusion transcript detection pipeline gFuse consists of two strategies, a sample-based strategy and a cohort-based strategy . The samRaw FASTQ sequencing data from the Providence and Rush cohorts were generated using CASAVA software. The FASTQ files were mapped to the human genome (version GHCh37/hg19) along with RefSeq splicing sites and dbSNP database (version 135) using the RNA-Seq aligner GSNAP Two filters were installed to remove low quality and unwanted reads. The quality filter retained reads with a minimum 15 bases at any position with a base quality score of 20 or above. To filter out the un-wanted reads, a number of abundant sequences including biological sequences , and sequences introduced during library prep  were removed from alignment (BAM) files. Only reads passing both filtering thresholds and uniquely mapped to human genome were retained to calculate the gene feature counts that provide expression values for exonic and intronic regions. The gene feature count is the number of aligned bases from reads mapped within the feature region. These gene feature counts are referred to as “gene tables” in In order to remove false positives, potential distant spliced reads in Step 1 were re-tested using GSNAP parameters that favor local alignment. Each alignment from the GSNAP re-run was examined, any reads meeting all of the following criteria were considered false positive distant splicing reads in the original GSNAP output, and removed from further analyses: the total matched length in the local alignment was at least 44 bp with a gap alignment tolerance of 1 bp. Reads that successfully passed through this step were considered to include a distant spliced junction.ftp://hgdownload.cse.ucsc.edu/goldenPath/hg19/database/refGene.txt.gz). During this annotation step, any junctions mapped to pseudo-genes, un-annotated gene regions, or multiply mapped RefSeq genes were removed. Also, gene rearrangements within the same gene or potential transcript read-throughs were also eliminated. At this stage, candidate fusions met at least one of the following criteria: (1) they mapped to different chromosomes, (2) they mapped to different RefSeq genes, (3) they were in opposite directions on same chromosome, or (4) they were at least 1 MB apart if on the same chromosome.The resulting distant splicing junctions were then annotated and candidate fusion transcripts were selected. Specifically, the alignments of reads that passed Step 2 were examined, and reads with any mismatches within 5 bp of the distant splicing junction site or mapped to the anti-sense strand of annotated genes were removed. Anti-sense reads were removed in this step since directional RNA-Seq libraries were constructed in the two cohorts analyzed here. The remaining reads were grouped according to the distant splicing junction sites, and each junction site was annotated based on the University of California, Santa Cruz RefSeq sequence annotation  was used to investigate the homology of the remaining candidate fusions. A separate collection of 300 bp template set was built for each of the fusion junction candidates with the same strategy as described above to provide sequence input to probe designs for qRT-PCR experiments. Homologies between the 300 bp donor template and the 300 bp acceptor template, as well as homologies between the 300 bp donor pre-mRNA template and the 300 bp acceptor pre-mRNA template were evaluated. Any candidate fusion satisfying the following criteria was removed from further analysis: (1) sequence identity of more than 14 bp  of 300 bp of the donor template and acceptor template; (2) sequence identity of more than 14 bp of 300 bp of the donor genomic template and acceptor genomic template; and (3) less than 50 bp exonic sequence on either side of fusion, donor, or acceptor template sequences.Donor and acceptor mRNA or pre-mRNA containing template sequences were used as controls. Since the DNA breakpoints were unknown in RNA-Seq data, a fusion pre-mRNA template could not be created. The genomic sequences were used to generate the pre-mRNA template sequences, and RefSeq sequences were used to generate mRNA template sequences. The sequence of each template in the five template set was retrieved and annotated for each candidate fusion transcript. Candidate fusion junctions were removed if any of their 100 bp templates had the identical sequence with any other template set. BLAST . When Primer3 failed, primer and probe sequences were optimized manually to ensure optimal performance of the TaqMan assay design for the chimeric transcripts. Reverse transcription reaction in the absence of RNA template  was always used as a negative control in all assays. The samples that were previously identified as positive or negative for a particular fusion junction served as controls when needed. Since the RT reaction was multiplexed by using a pooled gene specific primer set, the cDNA derived from a RNA sample was tested with all fusion gene qPCR assays within an assayed gene set. All RNA samples were assayed in triplicate qPCR reactions with 10 µl per well. Thermal cycling conditions were standard for all assays (A heat activation step of 95°C for 10 minutes followed by 40 cycles of 95°C for 20 seconds and 60°C for 45 seconds). All TaqMan assay results including primer and probe sequences are listed in Quantitative RT-PCR analysis using TaqMan RT-PCR was used to investigate the selected 60 fusion junctions. Reverse transcription was carried out using the Omniscript RT Kit (Qiagen) by incubating amplified RNA with random hexamers and gene-specific primers at 37°C for 1 hour. Primer, probe, and amplicon sequences are shown in Nineteen qPCR supported fusion transcripts were selected to be sequenced on the semi-conductor based Ion Torrent Personal Genome machine (PGM) to confirm the results from qPCR. The selection priority was given to those either recurred in multiple patients or appeared within a single patient as one of the multiple fusion transcripts.Eight replicate wells of PCR products were generated for each of the fusion targets  in 12 Providence/RUSH amplified RNA samples in order to prepare enough PCR product for PGM sequencing of the selected gene fusion candidates. Quantitative RT-PCR analysis using TaqMan RT PCR was used to confirm the presence of PCR product before proceeding to PGM sequencing. Reverse transcription was carried out as described in Step 8. The eight replicate wells of PCR product were pooled for each fusion target. Each PCR product was then purified using 1.8× volume of Agencourt AMPure XP beads (Beckman Coulter), and quality checked and quantitated using the Agilent High Sensitivity DNA Kit (Agilent Technologies). Fusion PCR products from the same patient samples were then pooled together. The Fusion PCR products were then prepared for sequencing using the Ion Plus Fragment Library Kit (Life Technologies) and barcoded using the Ion Xpress Barcode Adapters 1–16 (Life Technologies). The library was amplified with 7 cycles after adapter ligation and cleanup, as required by the protocol. The libraries were individually quantitated using the Agilent High Sensitivity DNA Kit (Agilent Technologies) and diluted to a target concentration of 26 pM. The libraries were pooled in equi-molar quantities prior to emulsion PCR on the Ion OneTouch 2 System (Life Technologies) and subsequently sequenced on a PGM 314 Chip Kit v2 (Life Technologies) using 260 flows.Ion Torrent Suite software was used to generate FASTQ files in which the barcode adaptors and 3′ end low quality sequences were removed as recommended. To recover read sequences longer than the desired 100 bp in a case of an expected amplicon of 126 bp, the 3′ end quality trimming was turned off for this design. All reads were mapped to the 5 template set sequence database containing the fusion templates. For each of expected fusion amplicons in a given sample, the most abundant reads mapped to the fusion template was selected as the PCR amplicon. The sequence of this read was compared to the sequence of the expected amplicon. If the PCR amplicon matches the expected fusion amplicon, the fusion junction sequence is considered as confirmed.Patients were stratified into different categories based on the fusion number detected. The time to disease recurrence as defined in the original studies http://doi.org/10.5061/dryad.98m0m).The read alignments which support the fusion transcripts for Providence and Rush cohorts are deposited into Dryad Digital Repository  and 34.86 (ECI) respectively, while other 39 samples tested were negative in the assay , consistent with findings of others On the other hand, in certain fusion cases we identified varied junctions between two identical fused partners within a single patient. One patient in the Providence cohort has three different ERBB2->IKZF3 junctions that only differ at the donor junction site, and one patient in the Rush cohort has two different TRIM37->BCAS3 junctions that only differ at the donor junction site . In thes−8) is 3.5 fold compared to all known RefSeq genes. Among them, ACACA, BCAS3, DDX5, FBXL20, IKZF3, RAF1, TFG and TRPS1 were fused to more than one partner in the database. These observations suggest fusion events are unlikely to be random although they appear to be rare in solid tumors.We searched the Mitelman fusion database with all 184 unique fusion partners including donors and acceptors from the final 118 fusion list, and 29 partners were found fused to various different partners in that database The identified fusion partners tend to be cancer-related: 82% of the total 83 fusion junctions  retains 8% of fusion candidates . GeneralTo tailor this method to the short insert size and low complexity of FFPE RNA-Seq data, the candidate fusion templates are extended across a cohort or from one cohort to another to maximize the probability of identifying recurrent fusions. The potential of the cohort-based approach was demonstrated by our identification of a total of 6 recurrent TFG->GPR128 fusions across two cohorts, which include 1 Tier-1 fusion, 3 Tier-2 fusions, and 2 Tier-3 fusions . The TieOur method also addresses intronic RNA sequences, in recognition of the large amount of intronic sequence information present in FFPE RNA. Both donor and acceptor pre-mRNAs are built into 5 template sets to filter out reads mapped to mRNA precursors. On the other hand, the introns are selectively included in the expression profiling analysis to take advantage of abundant intronic sequence information. The two different remapping steps by GSNAP  than what have been reported in many studies using fresh tissue RNA This study demonstrates the technical feasibility and potential biomedical value of being able to detect fusion transcripts in archival tumor specimens having attached clinical records. Although the average frequency of detected fusion transcripts is relatively low per patient, plausibly attributable to the low quality of FFPE RNA-Seq libraries, the frequency of fusion events found in our cohort nevertheless appears to have prognostic significance. Many of the identified fusion partner genes belong to the kinase, phosphatase and ubiquitin ligase families, which are attractive pharmaceutical targets in oncology. Both fusion frequency and tumor prognosis may be linked to cancer genome instability, which can generate chromosome rearrangements and fusion transcripts. In conclusion, this study significantly enriches the current understanding of breast tumor complexity by discovering a large number of novel fusion transcripts. It confirms one of the challenges of cancer therapeutics, namely that each cancer is different and personalized treatment is needed. In parallel we demonstrate a unique approach that reveals the genetic compositions of individual cancers employing short read sequencing methods and bioinformatics analysis adapted for FFPE tumor tissues.Figure S1www.uniprot.org). The red vertical line indicates the fusion position on the corresponding protein. The amino acid length and amino acid positions of each fusion position are labeled on the top of each protein. A. The protein domains of ESR1 protein P03372 (UniProt ID). B. The protein domains of AKAP12 protein Q02952 (UniProt ID). C. The protein domains of two predicted fusion protein isoforms ESR1->AKAP12. The one amino acid insertion generated from the fusion event is labeled on each fusion protein.Protein domains of fusion ESR1->AKAP12 are illustrated based on UniProt database ((EPS)Click here for additional data file.Figure S2Kaplan-Meier plots of patient subsets of Providence or Rush patients as a function of fusion numbers, segregated by block age. Either upper quartile or lower quartile based on block age is selected to examine the effect of the block ages on the disease outcome. The log-rank p-values are displayed.(EPS)Click here for additional data file.Table S1An excel file contains the complete information of all 118 fusion transcripts from Providence and Rush cohorts. All Tier-1 and Tier-2 fusions from (XLSX)Click here for additional data file.Table S2An excel file contains all TaqMan results.(XLSX)Click here for additional data file.Table S3An excel file contains the complete information of 19 fusion junction sequences confirmed by PGM.(XLSX)Click here for additional data file.Table S4TaqMan assays for examination of residual gDNA contamination of all Providence and Rush cohorts using beta-actin. Each sample from Providence has 6 TaqMan replicates, and each sample from Rush has 3 TaqMan replicates. Each TaqMan plate has Human Genomic DNA  triplicates as positive control, and no template triplicates as negative control. A second DNase I treatment was repeated on 2 Providence RNA samples which didn't pass the first residual gDNA contamination assays.(XLSX)Click here for additional data file.


Lung cancer diagnosis is usually achieved through a set of bronchoscopic techniques or computed tomography guided-transthoracic needle aspiration (CT-TTNA). However these procedures have a variable diagnostic yield and some patients remain without a definite diagnosis despite being submitted to an extensive workup. The aim of this study was to evaluate the efficacy and cost of linear endobronchial (EBUS) and endoscopic ultrasound (EUS) guided fine needle aspiration (FNA), performed with one echoendoscope, for the diagnosis of suspicious lung cancer lesions after failure of conventional procedures.One hundred and twenty three patients with an undiagnosed but suspected malignant lung lesion  or with a peripheral lesion and positron emission tomography positive mediastinal lymph nodes who had undergone at least one diagnostic flexible bronchoscopy or CT-TTNA attempt were submitted to EBUS and EUS-FNA. Patients with endobronchial lesions were excluded.Of the 123 patients, 88 had a pulmonary nodule/mass and 35 were selected based on mediastinal PET positive lymph nodes. Two patients were excluded because an endobronchial mass was detected at the time of the procedure. The target lesion could be visualized in 121 cases and FNA was performed in 118 cases. A definitive diagnosis was obtained in 106 cases (87.6%). Eighty-eight patients (72.7%) had non-small cell lung cancer, 15 (12.4%) had small cell lung cancer and metastatic disease was found in 3 patients (2.5%). The remaining 15 negative cases were subsequently diagnosed by surgical procedures. Twelve patients (9.9%) had a malignant tumor and in 3 (2.5%) a benign lesion was found. The overall sensitivity, specificity, positive and negative predictive values of EBUS and EUS-FNA to diagnose malignancy were 89.8%, 100%, 100% and 20.0% respectively. The diagnostic accuracy was 90.1% in a population with 97.5% prevalence of cancer. The ultrasonographic approach avoided expensive surgical procedures and significantly reduced costs (p < 0.001).Linear EBUS and EUS-FNA are able to improve the diagnostic yield of suspicious lung cancer lesions after non-diagnostic conventional techniques. These techniques, performed with one scope, can be offered to patients with accessible lesions as an intermediate step for diagnosis since they may avoid more invasive procedures and hence reduce costs. Lung cancer is a major health problem and the most common cause of cancer-related mortality worldwide . In patiThe accuracy and safety of TBNA has been increased by the development of endosonography. Linear real-time endobronchial (EBUS) and esophageal endoscopic ultrasound (EUS) are minimally invasive techniques that are able to image and sample, under direct vision, the intended structures in order to obtain specimens from pulmonary and mediastinal lesions. Both procedures have proven their value, individually or in combination, in mediastinal staging ,7 but thThe aim of this study was to evaluate the value of linear EBUS and EUS guided fine needle aspiration (FNA), performed with one echoendoscope, in patients with a suspicious lung lesion who failed diagnosis after conventional procedures.Individuals with an undiagnosed suspicious lung cancer lesion who had performed at least one diagnostic attempt with conventional techniques (FB or CT-TTNA) were prospectively enrolled in the study. Patients were eligible if a chest CT documented a tumor arising in an accessible area to EBUS or EUS  without direct endobronchial signs on a previous bronchoscopy; or if they had a peripheral pulmonary parenchymal lesion (that could not be assessed by linear EBUS and EUS-FNA) with fluorodeoxyglucose (FDG) positron emission tomography (PET) positive mediastinal/hilar lymph nodes (SUV > 3.5). Patients were excluded from the study if the tumor was not abutting the airways or the esophagus; if the primary peripheral lesion was not associated to PET positive mediastinal lymph nodes; or if they already had a confirmed diagnosis of lung cancer and were sent for mediastinal staging.Based on the described criteria, between June 2008 and June 2011, a total of 123 patients were referred from several institutions for EBUS and EUS-FNA diagnosis. The study was approved by the ethical committee of Centro Hospitalar Lisboa Norte, Hospital Pulido Valente and a written informed consent was obtained in all patients.All procedures were done in an outpatient setting. EBUS and EUS-FNA were performed under general anesthesia with a flexible ultrasound bronchoscope . The scope was first inserted through the tracheobronchial tree towards the area of the target lesion in a standard approach. In the same session, the linear echoendoscope was advanced to the stomach and then slowly withdrawn into the esophagus while making circular movements to localize anatomic landmarks and the intended lesion, according to the previously described technique . The tarThe estimated costs were based on the Portuguese National Health Service (NHS) according to the Health System Central Administration (ACSS) regulation prices for institutions and integrated services of the NHS (nº 132/2009). Costs were calculated in Euros (€) for patients submitted to conventional techniques and to EBUS/EUS-FNA, and estimated for avoided surgical procedures.The data was entered into a database and analyzed with the SPSS statistical software package . A descriptive analysis was carried out in which categorical variables were expressed as absolute and relative frequencies and continuous variables as means. Sensitivity, specificity, accuracy, and positive and negative predictive values were calculated using the standard formulas. T-Student tests were used to compare the cost of procedures.During the study period, a total of 123 patients met the inclusion criteria . Of these, 92 were males and 31 females, with a mean age of 63.1 years (range 38–88). Patients’ demographics are summarized in Table In 104 cases (84.5%) the patients had been initially submitted to a non-diagnostic FB with accessory sample techniques and in 19 (15.5%) to a CT-guided TTNA. These 19 CT-TTNA cases were all done in peripheral lung lesions. In the subgroup of 13 patients with central lesions, 11 were immediately sent for EBUS and EUS-FNA after the first failed diagnostic attempt (7 cases had been submitted to a blind TBNA). After the initial non-diagnostic exam a second diagnostic procedure has been performed in 48 patients (39.0%) (TTNA in 33 patients and FB in 15 patients) and a third in 10 of these patients (8.1%) (FB in 7 patients and TTNA in 3 patients), before they were sent for EBUS and EUS-FNA. In 64.6% of cases there was a shift between the first and second procedures, this means that patients who have been submitted to FB were afterwards submitted to CT-TTNA and vice versa.Mean procedure time was 35.5 minutes (range 21-65 minutes) and all patients were discharged home after the examination. There were no complications related to the procedure. Two patients were excluded from the study since they had direct tumor signs  when the endosonography was performed.In 121 cases the target lesion/lymph nodes could be visualized by EBUS/EUS although FNA could only be performed in 118 cases (97.5%). In three cases there was a major vessel interposition confirmed by Doppler mode that prevented a safe puncture. In 43 patients (36.4%) the target lesion could be assessed by EBUS and EUS-FNA, in 67 patients (56.8%) it could only be punctured by EBUS-TBNA and in 8 cases (6.8%) the lesion was inaccessible through an endobronchial approach and was sampled by EUS. The lesions were punctured 5.4 times (range 4–9 times). A total of sixty-nine lymph nodes were sampled in the 35 patients selected based on the presence of PET positive lymph nodes (1.97 per patient). These were punctured at the level of Mountain-Dressler stations 2R (n = 2), 2L (n = 3), 4R (n = 15), 4L (n = 9), 7 (n = 23), 8 (n = 2), 10R (n = 6), 10L (n = 7) and 11L (n = 2) (Table EBUS and EUS-FNA provided a definitive diagnosis in 106 cases (87.6%). Of these patients, there were 88 cases (72.7%) of non-small cell lung cancer and the tumor could be characterized as lung adenocarcinoma in 50 patients, squamous cell carcinoma in 23 patients, large cell carcinoma in one patient (14 patients had undifferentiated carcinoma). Small cell lung cancer was identified in 15 patients (12.4%). In three cases the pulmonary lesions were secondary to breast cancer, thyroid adenocarcinoma and renal cell carcinoma. In two cases, malignancy was suspected but could not be confirmed (inadequate sample) and in 10 cases the sample was negative for malignant cells.The fifteen undiagnosed cases were further submitted to mediastinoscopy (n = 2), video-assisted thoracoscopy (n = 5) and open thoracotomy (n = 8). The cytological inadequate samples proved to be lung adenocarcinoma (with extensive necrosis) and large cell neuroendocrine carcinoma on surgery. The negative cases were characterized as atypical carcinoid tumor (n = 2), lymphoma (n = 2), large cell lymphoepithelioma-like carcinoma n = 1), thoracic paraganglioma (n = 1), sarcomatoid carcinoma (n = 1), hamartoma (n = 1), inflammatory pseudotumor (n = 1) and benign granular cell tumor (n = 1)  and 20.0% (95% CI 7.0-45.2%) respectively. The overall diagnostic accuracy was 90.1% and there were no significant differences between the group of patients with centrally located lesions and PET positive mediastinal lymph nodes. The prevalence of cancer in the study population was 97.5%.The mean procedure cost for each patient submitted to the non-diagnostic conventional procedures was 273.73€. EBUS and EUS-FNA cost, done with a single scope under general anesthesia, was 740.2€ per patient. The cost of mediastinoscopy or video-assisted thoracoscopy was 2524.25€ per patient and thoracotomy was 5047.22€ per patient. The use of ultrasonography avoided more invasive procedures in 106 cases and led to estimated cost savings of 272382€  (p < 0.001). The EBUS and EUS-FNA approach cost saved approximately 2570€ per patient.The present study demonstrates that in selected patients with central lesions without an endobronchial component, EBUS and EUS-FNA, performed with one linear ultrasound bronchoscope, are accurate methods to diagnose lung cancer.The diagnosis of indeterminate pulmonary nodules and masses can constitute a considerable challenge in some cases. A broad range of factors must be considered when selecting a specific diagnostic modality to assess a suspicious lesion. These factors include the clinical and radiological information, sensitivity and specificity of the test, invasiveness of the procedure, safety profile, institutional availability of technology, presence of qualified clinicians and cost-effectiveness of the procedure .Several options are available for the diagnosis of indeterminate pulmonary lesions. Less invasive techniques include CT-TTNA and FB however these approaches have both advantages and limitations. FB with its attendant diagnostic modalities is extremely valuable for the diagnosis of a patient with suspected lung cancer but its yield is quite variable. A systematic review  reportedCT-TTNA is frequently used by pulmonologists and interventional radiologists because it provides a more accurate way of diagnosing peripheral pulmonary nodules and masses than FB although it has the potential to cause a non-negligible rate of iatrogenic complications, especially pneumothorax . Its senA small yet important number of patients with radiologically suspicious pulmonary lesions remain without a definitive diagnosis after extensive workup (7.9% in our study). Some patients are referred to other procedures such as mediastinoscopy, thoracoscopy or even thoracotomy ,10.Over the last few years, EBUS and EUS-FNA have been introduced to medical practice and numerous studies have evaluated their impact in lung cancer mediastinal staging.They have a high diagnostic yield and are simpler, less invasive, cost-effective and allow sampling of lymph node stations not accessible to mediastinoscopy . These tEUS-FNA has also been used to diagnose centrally located lung tumors abutting the esophagus ,15. The A further relevant point, demonstrated in our study, is that tissue may be acquired from highly suspicious metastatic central lymph nodes to diagnose lung cancer if the main peripheral lesion cannot be easily accessed. Since an important percentage of patients with lung cancer also have mediastinal lymph node enlargement at the time of clinical presentation, EBUS and EUS-FNA can play an important role in the diagnostic algorithm. However, it is important to distinguish patients with an established lung cancer diagnosis sent for mediastinal staging and those referred with enlarged lymph nodes without a definitive diagnosis since the described yield in this second group of patients is usually lower ,17,18. IAnother concern regarding the diagnostic procedures is safety. EBUS and EUS-FNA are usually associated with a very good safety profile with a low risk of adverse events. In this study they were also found to be safe since there were no complications associated with the procedures. The use of Doppler mode avoided vessels adjacent or within to the target lesion and in three cases dictated that the lesion could not be safely punctured.EBUS plus EUS-FNA had a significant influence on the diagnostic management of our patients since they were able to spare more invasive procedures such as surgical exploration in 87.6% of cases. This approach may constitute an important strategy for patients in whom surgery is not an option because of comorbid conditions or advanced metastatic disease.Regarding the economic impact, a study by Steinfort et al.  confirmeSome limitations in our study justify further discussion. It should be noted that it is not a randomized trial and while this is a prospective study, it included a selected population with peripheral and central lung lesions without endobronchial visible signs. Patients were excluded whenever the tumor was not abutting the airways or the esophagus; if there was aerated lung parenchyma surrounding the lesion; or if the primary peripheral lesion was not associated to PET positive enlarged central lymph nodes. Even though the population represented in this study embraces just a part of the suspected lung cancer patients that are frequently assess in the clinical practice we are aware that this particular group of patients usually causes a more challenging diagnosis. Further selection bias may exist since the work was carried out in a referral interventional pulmonology unit although this may be minimized by the fact that in our center CT-TTNA is executed by the authors in association with interventional radiologists. Nevertheless, our data must be confirmed in larger multicenter randomized trials.Finally, one can always argue that some of the included patients had a primary indication for EBUS or EUS-FNA instead of being submitted to the described conventional procedures. Previous work has shown that EBUS-TBNA can be performed as the first diagnostic procedure in patients with pulmonary masses and concomitant mediastinal lymph nodes . We cannIn conclusion, real-time EBUS and EUS-FNA are able to provide a high yield in lung cancer diagnosis after failure of conventional techniques. They may represent an additional step for diagnosing lung cancer since they seem able to replace more invasive diagnostic procedures in selected cases. Both techniques are extremely safe and cost-effective when they are performed by pulmonologists with a single linear ultrasound bronchoscope.CT-TTNA: Computed tomography-guided transthoracic needle; EBUS: Endobronchial ultrasound; EUS: Esophageal endoscopic ultrasound; FB: Flexible bronchoscopy; FDG: Fluorodeoxyglucose; FNA: Fine needle aspiration; NHS: National health system; PET: Positron emission tomography; SUV: Standardized uptake value; TBNA: Transbronchial needle aspirationAll authors declare that they do not have any competing interests related to this work.AB and DF conceived the study, participated in its design, collected the data and drafted the manuscript. RE was involved in the design, progression of the study and helped to draft the manuscript. SSD participated in the design of the study, data collection and statistical analysis. PAV, FJH and LC participated in the coordination of the study and revised the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/13/130/prepub


We hypothesized that males reared by dams of the more aggressive DBA strain would attack intruders faster than those reared by B6 dams. Surprisingly, we found that both methods of fostering enhanced aggressive behavior, but only in B6 mice. Since all the B6 offspring are genetically identical, we asked if maternal behavior of B6 dams was affected by the relatedness of their pups. In fact, B6 dams caring for foster B6 pups displayed significantly reduced maternal behaviors. Finally, we measured vasopressin and corticotrophin releasing hormone mRNA in the amygdalae of adult B6 males reared by foster or biological dams. Both genes correlated with aggressive behavior in within-strain fostered B6 mice, but not in mice reared by their biological dams. In sum, we have demonstrated in inbred laboratory mice, that dams behave differently when rearing their own newborn pups versus pups from another dam of the same strain. These differences in maternal care affect aggression in the male offspring and transcription of Avp and Crh in the brain. It is likely that rearing by foster dams has additional effects and implications for other species.It is well known that genes and environment interact to produce behavioral phenotypes. One environmental factor with long-term effects on gene transcription and behavior is maternal care. A classic paradigm for examining maternal care and genetic interactions is to foster pups of one genetic strain to dams of a different strain ("between-strain fostering"). In addition, fostering to a dam of the same strain ("within-strain fostering") is used to reduce indirect effects, via behavioral changes in the dams, of gestation treatments on offspring. Using within-and between-strain fostering we examined the contributions of genetics/prenatal environment, maternal care, and the effects of fostering  The last two decades have witnessed an increased interest in the field of maternal behavior, as we now know that natural variation in the amount of maternal care provided to infants dictates many of their adult behaviors Because the maternal environment can have powerful actions on offspring, it should be treated as a dependent variable in experiments where the behavior of the dam may be influenced by treatment. "Within-strain" fostering, whereby pups are removed from their dam at birth and reared by dams with the same genetic background, is a common method for providing consistent maternal care per se, on adult aggressive behavior in the C57BL/6J (B6) and DBA/2J (DBA) inbred mouse strains. These strains differ from each other in a variety of behavioral and physiological measures Here we used both between-strain fostering and within-strain fostering to assess the contributions of genetics/prenatal environment, the postnatal maternal environment, and the effects of fostering Peromyscus), male offspring from an aggressive species  reared by dams of a less aggressive species (P. leucopus) exhibited reduced adult agonistic behaviors There is an extensive literature on the genetic basis strain differences in aggression All animal care and treatment was in compliance with, and all experiments approved by, the University of Virginia Animal Care and Use Committee.ad libitum. To generate offspring for adult aggression experiments, DBA/2J (DBA) and C57BL/6J (B6) male and female mice (10 pairs of each strain) were purchased from Jackson Laboratories. To give all dams maternal experience, males and females were paired, mated, and males were removed prior to parturition . Only females that successfully raised a litter to weaning were included in the study. Adult male (n = 15) and female (n = 15) B6 mice from our mouse colony were used as stimulus animals for social exposure tests. Intruders for aggression tests were age and size-matched A/J strain (an inbred line noted for its passivity) male mice, also from our mouse colony (n = 61). For maternal behavior experiments, adult male and multiparous female (n = 19) B6 mice from our breeding colony were paired to produce litters.Animals were maintained on a 12:12 light/dark cycle . Food (Harlan Teklad #7912) and water were provided Experienced dams were paired with males, mating plugs were verified and, after 1–2 wks, males were removed. On the day of birth (PN0), pups were separated briefly (less than 5 minutes) from their dams, litters were culled to 2 males and 2 females, then pups were either returned to their biological dam  or fostered to another dam . BetweenBecause adult B6 males have lower levels of testosterone than DBA males To enhance territorial behavior, cages were not changed for at least 5 days prior to aggression testing. Social exposure was conducted as described previously Biological (n = 9) and within-strain fostered (n = 10) litters were prepared as in Experiment 1. After culling litters, pups were scattered on the opposite side of the nest in the home-cage and dams were observed for 5 mins. Latencies to sniff the first pup, and to return each of the four pups to the nest were recorded. On the next day (PN1), dams were observed (by NLS) for two 60-minute periods in their home-cages. One observation was conducted during the light portion (at least 3 hrs before lights off) and one was conducted during the dark portion (at least 1 hr after lights off) of the light cycle. Within each 60-minute period, maternal behavior was scored every 20 seconds, resulting in a total of 360 observations for each dam. The following behavioral categories were recorded: (1) dam nursing pups in either high crouch or low crouch posture (2) dam licking and grooming pups, (3) dam building or rearranging nest, (4) dam on nest without nursing, licking and grooming, or nest-building, and (5) dam off nest.Approximately 48 hours after the final aggression test, adult B6 male offspring (n = 5–6 per group), from the biological and within-strain fostered groups were rapidly decapitated under isoflurane anesthesia, and brains were removed and frozen on dry ice. Using a cryostat, brains were then cut in coronal sections (120μm) onto slides. A tissue punch (1 mm) was used to dissect out the amygdala and the medial preoptic area (mPOA) following anatomical guidelines established by visually comparing slices to figures in the Mouse Brain Atlas Avp, Avpr1a, Crh, Nr3c1, Ar and B2m, while Taqman® probes were used for Esr1 and B2m (B2m) as an endogenous control.Total RNA was isolated using a Qiagen RNeasy® Lipid Tissue Mini Kit. cDNA templates were generated with an ABI High Capacity cDNA Reverse Transcriptase Kit. An ABI StepOnePlus real-time PCR system was used to perform qPCR analysis with SYBR® Green or Taqman® reagents. Oligonucleotide primers were designed for  and B2m . All genAggression latencies were analyzed via repeated measures ANOVA as previously described Using both within-strain and between-strain fostering , we testTo ask if maternal behavior was affected by within-strain fostering, we fostered B6 pups to same-strain dams and measured maternal behavior of biological versus fostered dams. Intriguingly, pups reared by their own mothers were treated differently than foster pups. There was a significant effect of fostering on latency to retrieve pups, with foster dams taking longer to retrieve pups back to the nest  = 4.58, p<0.05; Avp and Crh mRNA levels may respond acutely to aggressive encounters, studies on short-term responses of AVP release Crh mRNA Lastly, we examined whether differences in maternal environment had effects on gene transcription in offspring. We also determined if these differences in gene transcription correlated with individual aggressive behavior. We examined gene transcription in the amygdalae of within-strain fostered and biologically reared B6 male mice collected approximately 48 hours after the final aggression test. While Crh gene transcription  while there was no significant correlation with Avp gene expression  in the amygdala. However, longer attack latencies in the third and final aggression test were significantly correlated with both increased Crh gene transcription , and a significant positive correlation with Crh gene transcription . Attack latencies in the final aggression test followed the same pattern (Avp and Crh). We speculate that changes in aggressive behavior in fostered males were mediated through these genes. None of the other candidate genes examined showed significant differences between groups or correlations with aggressive behavior in biological or fostered offspring  correlated with increased ffspring .Peromyscus mice, Bester-Meredith and colleagues (2001) found that aggression in fostered males matched levels in foster parents, indicating that maternal-infant interactions play a role in determining adult aggressive behavior. In contrast, a within-strain fostering experiment using outbred CD-1 mice showed no effect of fostering on aggressive behavior These studies show that rearing by a non-biological dam, whether it is by a female of the same inbred strain or another strain, increases aggressive behavior in B6 male mice. Our data brings to the foreground the impact of within-strain fostering on social behavior, as fostered B6 males, regardless of the strain of the foster dam, displayed increased aggressive behavior as compared to mice reared by biological dams. To our knowledge, only one set of studies has tested the effects of fostering on aggression using inbred laboratory mouse strains  and arginine vasopressin (Avp) in the amygdalae of male mice correlated with their attack latencies. However, only fostered males showed this correlation, suggesting that fostering may increase aggression by acting on brain circuits involving Crh and Avp production in the amygdala. Although genes involved in aggressive behavior have not been studied within in the context of variations in maternal care, maternal separation, a form of early post-natal stress, enhances the display of aggression in male rats Avp mRNA transcription in the anterior hypothalamus Avp mRNA transcription correlates with higher level of aggression in fostered B6 males in the amygdala, a region in which local synthesis and release of vasopressin are important for aggressive behavior Avp enhancer Avp mRNA can become elevated in adult offspring subjected to maternal separation. Therefore, our finding that decreased maternal behavior led to altered vasopressin in the amygdala and increased aggression in fostered offspring, while correlational, fits within the framework of what is understood about maternal influences on vasopressin, and may be mediated by altered methylation of the Avp gene.Maternal care is able to influence offspring behaviors via modulation of gene transcription (reviewed in Crh mRNA in the hypothalamus Crh mRNA transcription the amygdala, a region important for behavioral responses to stress and anxiety-related behavior Crh mRNA was altered in fostered B6 male offspring and that fostering led to higher levels of aggression, it would be worthwhile to examine the effect of fostering on the relationship between anxiety-related behavior and aggression in future studies. Interestingly, rats selectively bred for low anxiety behavior exhibit significantly higher aggression than non-selectively bred rats Previous studies have shown that variations in the early-life environment can also affect HPA-mediated neuroendocrine and behavioral responses through altering components of the glucocorticoid feedback mechanism and Avp and Crh mRNA in the amygdala, a brain region important for aggressive behavior. Moreover, we show that these effects are likely mediated by differences in maternal behavior in B6 mouse dams towards fostered and biological pups. These findings have broader implications for experimental design and interpretation of results in studies using fostering protocols. While, at times, fostering is necessary to prevent off-target effects of drugs or other independent variables, it may also be necessary to include a biologically-reared group in these studies and/or evaluate maternal behavior to assess the contributions of the maternal environment to measured phenotypes.In summary, this is the first study to find effects of within-strain and between-strain fostering on aggressive behavior in an inbred mouse strain, while also showing that within-strain fostering has a long-lasting impact on


The epidermal growth factor receptor (EGFR) is a member of the receptor tyrosine kinase family that plays a role in multiple cellular processes. Activation of EGFR requires binding of a ligand on the extracellular domain to promote conformational changes leading to dimerization and transphosphorylation of intracellular kinase domains. Seven ligands are known to bind EGFR with affinities ranging from sub-nanomolar to near micromolar dissociation constants. In the case of EGFR, distinct conformational states assumed upon binding a ligand is thought to be a determining factor in activation of a downstream signaling network. Previous biochemical studies suggest the existence of both low affinity and high affinity EGFR ligands. While these studies have identified functional effects of ligand binding, high-resolution structural data are lacking. To gain a better understanding of the molecular basis of EGFR binding affinities, we docked each EGFR ligand to the putative active state extracellular domain dimer and 25.0 ns molecular dynamics simulations were performed. MM-PBSA/GBSA are efficient computational approaches to approximate free energies of protein-protein interactions and decompose the free energy at the amino acid level. We applied these methods to the last 6.0 ns of each ligand-receptor simulation. MM-PBSA calculations were able to successfully rank all seven of the EGFR ligands based on the two affinity classes: EGF>HB-EGF>TGF-α>BTC>EPR>EPG>AR.  Receptor tyrosine kinases (RTK) play essential roles in numerous cellular processes. Activation of an RTK by a particular ligand(s) enables transduction of a biological signal from the membrane surface to intracellular signaling pathways As with all RTKs, activating ligands bind to the extracellular domain of EGFR. The mechanism of ligand-dependent activation of EGFR has been studied in great detail Seven different ligands are known to bind to EGFR: epidermal growth factor (EGF), betacellulin (BTC), heparin-binding EGF-like growth factor (HB-EGF), amphiregulin (AR), epiregulin (EPR), transforming growth factor-α (TGF-α), and epigen (EPG) d) between 1 and 100 nM, while low affinity ligands  show a Kd greater than 100 nM While much attention has been paid to the biochemical and physiological roles of EGFR ligands, little is known about the protein-protein interactions that determine the binding affinity of a given ErbB ligand. EGFR ligands generally fall into two classes: high affinity or low affinity. High affinity ligands  bind with a dissociation constant  simulations provide atom-by-atom resolution and dynamical behavior on a nanosecond timescale. Previous modeling studies of EGFR have illustrated the asymmetric nature of dimer formation and kinase function. Using theoretical free energy methods combined with conventional MD simulations, we sought to determine residue-residue interactions that give rise to binding affinities for each EGFR ligand.To explore the differences in binding affinity of an EGFR ligand to the receptor, we chose to use computational methods to dock each ligand to the extracellular domain of EGFR (sEGFR) and compute the relative free energies. Accurate free energy prediction of protein-protein interactions is one of the long standing goals of computational biology The crystal structures for the sEGFR dimer structure bound to two EGF molecules (PDB code: 1IVO) were used as a starting model for the docking of each ligand. In this structure, electron densities for the ligand binding domains (DI and DIII) and the domain containing the dimerization arm (DII) were well resolved. Domain IV, however, was more disordered and initially could not be fit to the density maps. Therefore we chose to model the fourth domain DIV using the inactivated structure of EGFR bound to EGF (PDB code 1NQL) as a reference in vitroTo determine if each ligand causes different structural alterations in the EGFR dimer, we compared conformations of each ligand-protein complex at the end of the production simulations to the TGF-α-EGFR and EGF-EGFR complexes. A recent structural study of an ErbB4-neuregulin-1β complex highlighted two different types of interactions between ligand-ErbB complexes Each EGFR ligand shares a common EGF-like motif (or fold). This fold is characterized by three intramolecular disulfide bonds constraining three solvent-accessible loops While molecular dynamics simulations can provide us with a qualitative assessment of intramolecular interactions, knowledge of the energetic contributions from individual atoms or residues can provide a quantitative analysis of the binding mode of a ligand to a protein. Molecular mechanics Poison-Boltzmann Surface Area (MM-PBSA) calculations are a computationally efficient method to compute relative binding affinities Hydrogen bond lifetimes and salt bridges are indicators of stable non-covalent interactions during the course of a MD simulation. To investigate the interactions between EGFR and a given ligand at the molecular level, we analyzed the last 6.0 ns of each simulation using hydrogen bond and salt bridge analysis. We chose to analyze only the last 6.0 ns as we want to ensure the stability of each system. High occupancy hydrogen bonds were observed for all ligands bound to EGFR . The resBinding hotspots on protein interfaces can dictate the experimentally observed binding affinity. While alanine scanning mutagenesis can provide some insight, it must be interpreted with caution as exact knowledge of structural perturbations must be considered The results of the residue decomposition analysis revealed several amino acids that contribute to the overall binding energy from the MM-PBSA/GBSA calculations . Six conProtein-protein interactions drive biological processes Drosophila homolog of EGFR bound to the EGF-homolog Spitz has also been determined Drosophila EGFR, but those properties cannot be captured with static structures. EGFR forms multiple intramolecular interactions with a ligand by binding in a clamp-like fashion on domains I and III Theoretical free energy methods allow prediction of both relative and absolute binding energies from molecular dynamics simulations d value measured for EPR was done using the mouse homolog which contains several mutations in loop 2 and a mutation in loop 3 that have negative PBSA/GBSA decomposition energies. This could explain why the original binding affinity constant is significantly lower than our predicted binding energy. Overall, hydrophobic interactions along with electrostatic and van der Waals interactions were the energetic driving forces for binding of all seven ligands. The binding modes were similar in all cases; domains I and III formed multiple hydrogen bond networks and salt bridges with each ligand. Analysis of hydrogen bond lifetimes showed that several hydrogen bonds formed, but specific networks were not conserved across all ligands  . FurtherIn summary, we have performed molecular dynamics simulations of EGFR bound to each of its endogenous ligands. This study provides for the first time, to our knowledge, a detailed view of binding of all known EGFR ligands. We observed a similar binding mode during the course of our simulations and our MM-PBSA relative free energies were in agreement with previous experimental data. GBSA results produced similar results but failed to accurately rank EPR. We acknowledge that our studies were done on only the extracellular domain and that the absence of intracellular domains may affect our binding energies due to conformational restraints. The accurate ranking of all seven ligands suggests that binding is not affected by the intracellular domains, though cooperative effects observed in full length receptors cannot be ignored. Using residue level energy decomposition analysis, we found several conserved and non-conserved residues that the contributed to the overall binding energy. We identified several conserved residues that contribute favorably to the binding energy. We were also able to identify residues that were position conserved in the structure of each ligand that contributed to our predicted binding energies. The knowledge of both sequence and structural information in regards to binding may be applied to development of therapies targeting over-expression of a particular set of EGFR ligands.Seven systems were constructed to model the binding of the extracellular domain of EGFR to its endogenous ligands. The initial extracellular dimer crystal structure bound to two EGF molecules (PDB id 1IVO) was used X-ray structures have been solved for complexes with only two EGFR ligands bound: EGFR and TGF-α. Three ligand structures have been solved using NMR  and one x-ray bound to the diphtheria toxin  scheme. Langevin dynamics with a collision frequency of 2.0 were used for temperature regulation, the SHAKE algorithm was used for all hydrogen atoms, and the particle mesh Ewald (PME) method was employed to treat long-range electrostatics and van der Waals forces (cutoff of 8 Å) with an integration step of 2.0 fs. All Amber equilibration and production runs were performed using dual precision. All production simulations were repeated in triplicate and extended to 25.0 ns. Visualization of trajectories was performed in VMD All simulations and system equilibrations were performed using Amber 11 software. The leap module of AMBER11 was used to create parameter and topology files for the MD simulations using the AMBERff03.r1 force field complex), protein (ΔGprotein) and ligand (ΔGligand):MM), the polar solvation free energy (ΔGsolv), the nonpolar solvation free energy (ΔGnp) and the entropic contribution (ΔS):solv is solved using the Poisson Boltzmann (PB) equation. The nonpolar term ΔGnp is solved using the Generalized Born (GB) method and is assumed to be proportional to the SASA 2. β is an offset value used to correct for the nonpolar contribution to the solvation free energy term and is dependent on the GB model used The binding energies between EGFR and each ligand were calculated using the MM-PBSA/MM-GBSA method in Amber11 For each EGFR-ligand system, MM-PBSA and MM-GBSA calculations were performed using 600 snapshots over the last 6.0 ns of the simulation with 100 ps intervals. All energy values, including decomposition values, represent at least two independent MD simulation runs for each ligand-protein complex. All calculations were performed with the MMPBSA.py.MPI module in Amber 11 with an ionic strength equal to 0.1 M. For MM-PBSA calculations the PB equation is solved numerically by the PBSA program included with AmberTools. The hydrophobic contribution is approximated by the LCPO method implemented within sander in silico alanine mutagenesis is usually performed, yielding a ΔΔGala. A major drawback to this method is that mutations in macromolecular structures may cause perturbations that transcend the binding interface solvi and qj are atomic partial charges, κ is the Debye-Huckel screening parameter and εω is the solvent dielectric constant, which is set to 80.0 for water. GBf is defined as:i,j is the distance between the ith and jth atom, αi and αj are the effective Born radii.To determine the energetic contribution of an individual residue to ΔG, The ith atom contribution to the electrostatic free energy is obtained by solving:Hydrogen bonding analysis was performed in the Hydrogen Bond module of VMD Figure S1SASA fluctuations for each EGFR-ligand complex. The trace for EGF is colored blue, AR is colored purple, BTC cyan, EPG brown, EPR green, HB-EGF yellow and TGF-α orange.(TIF)Click here for additional data file.Figure S2Modeling domain IV for EGFR dimers. a-b) The x-ray structure of the EGF-EGFR dimer containing the first three domains of EGFR(colored blue) and the monomeric EGFR-EGF complex(colored magenta) containing domains I–IV were aligned using domain III as a reference.(TIF)Click here for additional data file.Figure S3Dimerization domain interface of EGFR-ligand structures. A) Structural alignment of EGFR-EGF model (colored cyan) and TGF-α-EGFR x-ray structure (colored magenta) (PDB ID 1MOX) complexes. B) Top down view of the dimerization domains.(TIF)Click here for additional data file.Figure S4Decomposition values for position for 43. GBSA values are depicted as solid black bars and PBSA values as shaded gray bars.(TIF)Click here for additional data file.Table S1Free energy results for MM-GBSA calculations of last 6.0 ns of each ligand-protein complex.(DOC)Click here for additional data file.


Nicotine is a known risk factor for cancer development and has been shown to alter gene expression in cells and tissue upon exposure. We used Illumina® Next Generation Sequencing (NGS) technology to gain unbiased biological insight into the transcriptome of normal epithelial cells (MCF-10A) to nicotine exposure. We generated expression data from 54,699 transcripts using triplicates of control and nicotine stressed cells. As a result, we identified 138 differentially expressed transcripts, including 39 uncharacterized genes. Additionally, 173 transcripts that are primarily associated with DNA replication, recombination, and repair showed evidence for alternative splicing. We discovered the greatest nicotine stress response by HPCAL4 (up-regulated by 4.71 fold) and NPAS3 (down-regulated by -2.73 fold); both are genes that have not been previously implicated in nicotine exposure but are linked to cancer. We also discovered significant down-regulation (-2.3 fold) and alternative splicing of NEAT1 (lncRNA) that may have an important, yet undiscovered regulatory role. Gene ontology analysis revealed nicotine exposure influenced genes involved in cellular and metabolic processes. This study reveals previously unknown consequences of nicotine stress on the transcriptome of normal breast epithelial cells and provides insight into the underlying biological influence of nicotine on normal cells, marking the foundation for future studies. Worldwide, more than 1 million women are diagnosed with breast cancer every year and more than 410,000 die of the disease 50 dose because it is standardized and is established as an accurate means of measuring the effects We hypothesize the missing link between nicotine stress and cancer will be found by using an unbiased sequencing approach rather than a targeted array based approach. Next-generation sequencing (NGS) techniques, in contrast with cDNA microarrays used previously, enables systematic examination of known, uncharacterized transcript expression over a wide dynamic range, and alternative and novel splicing events without any technological and/or biological bias. This all-inclusive approach may provide better clues to complex pathways, understanding of uncharacterized transcripts and provide missing information on gene regulation under nicotine stress that were previously not possible with microarrays. Moreover, we selected a LDNicotine was purchased from Sigma . MCF-10A, normal breast epithelial cell-line, was obtained from American Type Culture Collection . MCF-10A cells were cultured in DMEM/F12 medium , supplemented with horse serum , antibiotics- Pen/Strep , growth factor- EGF , hydrocortisone , cholera toxin , and insulin  at 37°C in a humidified atmosphere containing 5% carbon dioxide.5 cells/well in six-well plates or 5×107/500 cm2 square cell culture dishes (Corning). Nicotine was diluted in complete culture medium at the required final serial concentrations. Nicotine dosage experiments were carried out in six well plates for 72 hours and at the end; the number of live cells were calculated using TC10 BioRad® cell counter. These dosage experiments were further analyzed and compared for the nicotine LD50 dose (5 mM/811 ng/mL) in 500 cm2 plates for 72 hours. After the exposure period, attached cells were harvested for RNA extraction using a Qiagen’s RNeasy® kit following the manufacturer’s protocol. RNA was properly tested for quality on Nano-drop® and Bioanalyzer® before transcriptome sequencing was conducted using Illumina HiSeq®.Twenty–four hours before the experiments, MCF-10A cells were seeded at a density of approximately 3×10RNA libraries were prepared according to the TruSeq® RNA sample preparation guide as per the manufacturer’s recommended protocol . Total RNA for the three biological replicates from control and nicotine stressed cell populations were transcribed to cDNA. Complimentary DNA samples were then sheared by nebulization . Duplexes were blunt-ended  and a single 3′adenosine moiety was added using Klenow exo− and dATP. Illumina adapters, containing primer sites for flow cell surface annealing, amplification and sequencing, were ligated onto the repaired ends of the cDNA. Gel electrophoresis was used to select for DNA constructs 200–250 base pairs in size, which were subsequently amplified by 18 cycles of PCR with Phusion polymerase (NEB). These libraries were then denatured with sodium hydroxide and diluted to 3.5 pM in a hybridization buffer for loading onto a single lane of an Illumina HiSeq® flow cell. Cluster formation, primer hybridization and sequencing reactions were according to the manufacturer’s protocol. High throughput sequencing was performed using paired-end, 100 base pair reads. One flow lane was used for cDNA sequencing, yielding an average of 45.26 million reads per sample with mean quality score of >36.3.http://www.ingenuity.com). Sequence reads are available in NIH Short Read Archive under the experiment accession number SRX254950.RNASeq data were analyzed according to the method described by Trapnell et al., For each sample, 1 µg of total RNA was reverse transcribed using the Qiagen QuantiTect Reverse Transcription Kit  according to the manufacturer’s standard protocol. For Taqman real-time PCR, 1.0 µl of diluted cDNA was used for 20 µl real-time PCR using Taqman Gene Expression Master Mix according to the manufacturer’s standard protocol. Applied Biosystem’s Taqman assays used were as follow: HPCAL4 (Hs04188853_g1), NEAT1 (Hs01008264_s1), Actin (Hs01060665_g1) and 18S rRNA (Hs03928985_g1). Quantitative RT-PCR was carried out in a StepOnePlus real-time PCR system .This is the first transcriptome sequencing study of nicotine stressed normal breast epithelial cells. Expression analysis via direct transcriptome sequencing (RNAseq) probes the rarest and most cell- and context-specific transcripts. Furthermore, RNAseq methods are not biased by prior knowledge of splicing and allow the analysis to determine the full repertoire of alternatively spliced isoforms. Finally, RNAseq as a method has been shown to be more quantitative as the number of reads produced from an RNA transcript is a function of that transcript and gene expression rather than a chemical property of probe hybridization that changes with the composition of the sample To identify differentially expressed genes and transcripts, we first confirmed the RNAseq data was free of sequencing bias and displayed a uniform coverage across samples . We thenCancer is a multifactorial disease, linked to the number of underlying biological events such as inflammatory response, tumor suppressor genes, oncogenes and transcription factors. An unbiased, all inclusive approach with next-generation sequencing can therefore provide more complete details and help us better understand the missing links. Our results indicated that HPCAL4, TREM1, EFNA2, SPATA22 and KRT85 are the top five upregulated genes and NPAS3, DEFB129, NEAT1, WDR96 and VRK2 are the top five downregulated genes upon nicotine exposure. Hippocalcin like 4 (HPCAL4) and triggering receptor expressed on myeloid cells 1 (TREM1) were highly upregulated genes with greater than four-fold change upon nicotine stress. HPCAL4 is a relatively under-studied gene and has unknown function, but it is reported to be overexpressed in lung carcinoma A distinct down-regulated gene is NEAT1, which is a long non-coding RNA (lncRNA) known to be an essential structural determinant of paraspeckles Jensen-Shannon divergence >0.8 are shown in Defects in mRNA splicing are an important cause of disease and several studies have reported cancer-specific alternative splicing even in the absence of genomic mutations To gain insight into the nature of the genes regulated and alternatively spliced upon nicotine stress, we performed gene ontology analysis using the PANTHER classification system analyzed using binomial test statistics and the Bonferroni correction. Significantly enriched biological processes and gene functions are shown in To identify which transcription regulators regulate the differential expression of those genes described in these experiments, the up- and down regulated genes were reimported into IPA and were analyzed for the enrichment of transcription regulators associated to promoters of differentially expressed genes. There were five up regulator genes  from the list. Their target molecules, including MMP2 and PROX1, were also up regulated in the study indicating a tight correlation . All of Interestingly, transcription regulator HEY1 is located at cytogenetic band 8q21. Amplification of 8q21 is associated with poor patient prognosis in breast cancer and is independent of MYC While this pilot study attempts to utilize standardized concentration of nicotine to document physiological and genotoxic effects, lower concentration of nicotine identical to those found in the plasma after smoking may be utilized in the future to further evaluate the effects.In conclusion, this study reveals that nicotine stress triggers responses from a number of understudied and uncharacterized genes and causes aberrant splicing events that could cumulatively contribute towards the development of cancer and altered immune system activity in smokers. Additionally, genes located at chromosome 12, 17, and 19 show biased sensitivity to nicotine stress indicating unknown biological significance. This implies that nicotine would be an additive in cancer propagation by modulating immune activity and ovarian cancer signalling pathways. This study has wide implications as we present new possible links between genes such as HPCAL4 (up-regulated), NPAS3 (down-regulated) and NEAT1  that could be targeted or monitored to reduce or assess the risk of cancer development in smokers (in particular) and cancer patients. Observations from this transcriptome study thus provide fresh biological insight into nicotine stress on normal breast epithelial cells that can be utilized in clinical settings to assess the harmful effects of nicotine in smokers.Figure S1Density graph and scatter plot. (1A) CummeRbund was used to generate a density graph of the densities of the FPKM values across all genes. The Control and Nicotine samples were very similar, indicating no bias in the sequencing coverage between the samples. (1B) The FPKM values for all genes were plotted for the Control and Nicotine samples, following averaging across replicates and normalization. Each dot represents a gene.(JPG)Click here for additional data file.Figure S2Validation of top two genes by Taqman real-time RT-PCR. Taqman real-time RT-PCR validation assessment of HPCAL4 (up regulated) and NEAT1 (down regulated) indicates the general agreement of RNASeq finding and quantitative PCR. Fold changes were relative to the control and normalized to the multiplexed housekeeping genes (Actin and 18S rRNA). Error bars represent standard errors.(JPG)Click here for additional data file.Figure S3Ingenuity pathway analysis of differentially expressed genes. Top network from the Ingenuity pathway analysis indicates that DE genes have important role in Cancer. Those shown in red are up-regulated, green are down-regulated and those in white serve to make the indirect connection between the DE genes.(JPG)Click here for additional data file.Figure S4Ingenuity pathway analysis of alternatively spliced genes. Top network from the Ingenuity pathway analysis indicates that alternatively spliced genes have association with DNA replication, recombination, and repair.(JPG)Click here for additional data file.Figure S5Differentially expressed and alternatively spliced transcripts per chromosome and their relative percentages. (4A) Radar graph indicates relative percentages of DE transcripts per chromosome. (4B) Radar graph demonstrates relative percentages of alternatively spliced transcripts per chromosome. (4C) Table illustrating the total number of differentially expressed and alternatively spliced transcripts per chromosome.(JPG)Click here for additional data file.Table S1List of all differentially expressed genes and uncharacterized transcripts (q<0.05).(XLS)Click here for additional data file.Table S2Transcripts which showed evidence of alternative splicing.(XLS)Click here for additional data file.Table S3Overlapping genes that showed differential expression and evidence of alternative splicing.(XLS)Click here for additional data file.Table S4IPA transcription factor enrichment analysis presenting all transcription factors that may have influenced differentially regulated genes.(XLS)Click here for additional data file.