Genomic epidemiology reveals the dominance of Hennepin County in the transmission of SARS-CoV-2 in Minnesota from 2020 to 2022.

IMPORTANCE: We analyzed over 22,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes of patient samples tested at Mayo Clinic Laboratories during a 2-year period in the COVID-19 pandemic, which included Alpha, Delta, and Omicron variants of concern to examine the roles and relationships of Minnesota virus transmission. We found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after an initial predicted introduction with the virus in early 2020 from an international source, while other counties acted as transmission "sinks." In addition, major policies, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.

Integration of multiomics data shows down regulation of mismatch repair and tubulin pathways in triple-negative chemotherapy-resistant breast tumors.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). The response to NAC is prognostic, with reductions in overall survival and disease-free survival rates in those patients who do not achieve a pathological complete response (pCR). Based on this premise, we hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence. METHODS AND RESULTS: We investigated 24 samples from 12 non-LAR TNBC patients with paired pre- and post-NAC data, including four patients with recurrence shortly after surgery (< 24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and nonrecurrent TNBC tumors; however, post-NAC samples demonstrated significant alterations in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the 9 paired non-LAR samples available in the NAC I-SPY1 trial confirmed 56 gene sets. Within these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n = 392) breast cancer dataset with relapse-free survival (RFS) data was used to refine our gene list to a 17-gene signature. A threefold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine-learning models. Due to the limited number of studies with pre- and post-NAC TNBC tumor data, further validation of the signature is needed. CONCLUSION: Analysis of multiomics data from post-NAC TNBC chemoresistant tumors showed down regulation of mismatch repair and tubulin pathways. Additionally, we identified a 17-gene signature in TNBC associated with post-NAC recurrence enriched with down-regulated immune genes.

Genomic epidemiology reveals the dominance of Hennepin County in transmission of SARS-CoV-2 in Minnesota from 2020-2022.

SARS-CoV-2 has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread, and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020-2022 and use Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest introduction into Minnesota was to Hennepin County from a domestic source around January 22, 2020; six weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota, and eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International (MSP) airport) totaling 45 (out of 107) over the two-year period. Southern Minnesota counties were most common for domestic introductions with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations (n=772) over the two-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases or major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have impact on virus diversity across each individual county.

Molecular Profile Changes in Patients with Castrate-Resistant Prostate Cancer Pre- and Post-Abiraterone/Prednisone Treatment.

We identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study.We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC).At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4-4.5) or long-term (median 29 months; range 23.5-41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders. IMPLICATIONS: Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K_AKT_MTOR pathways.

Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX).

The application of patient-derived xenografts (PDX) in drug screening and testing is a costly and time-consuming endeavor. While cell lines permit extensive mechanistic studies, many human breast cancer cell lines lack patient characteristics and clinical treatment information. Establishing cell lines that retain patient's genetic and drug response information would enable greater drug screening and mechanistic studies. Therefore, we utilized breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalized, genomically unique breast cancer cell lines. Through extensive genetic and therapeutic testing, the cell lines were found to retain the same clinical subtype, major somatic alterations, and drug response phenotypes as their corresponding PDX and patient tumor. Our findings demonstrate PDX can be utilized to develop immortalized breast cancer cell lines and provide a valuable tool for understanding the molecular mechanism of drug resistance and exploring novel treatment strategies.

COVID-19 Transmission, Current Treatment, and Future Therapeutic Strategies.

At the stroke of the New Year 2020, COVID-19, a zoonotic disease that would turn into a global pandemic, was identified in the Chinese city of Wuhan. Although unique in its transmission and virulence, COVID-19 is similar to zoonotic diseases, including other SARS variants (e.g., SARS-CoV) and MERS, in exhibiting severe flu-like symptoms and acute respiratory distress. Even at the molecular level, many parallels have been identified between SARS and COVID-19 so much so that the COVID-19 virus has been named SARS-CoV-2. These similarities have provided several opportunities to treat COVID-19 patients using clinical approaches that were proven to be effective against SARS. Importantly, the identification of similarities in how SARS-CoV and SARS-CoV-2 access the host, replicate, and trigger life-threatening pathological conditions have revealed opportunities to repurpose drugs that were proven to be effective against SARS. In this article, we first provided an overview of COVID-19 etiology vis-à-vis other zoonotic diseases, particularly SARS and MERS. Then, we summarized the characteristics of droplets/aerosols emitted by COVID-19 patients and how they aid in the transmission of the virus among people. Moreover, we discussed the molecular mechanisms that enable SARS-CoV-2 to access the host and become more contagious than other betacoronaviruses such as SARS-CoV. Further, we outlined various approaches that are currently being employed to diagnose and symptomatically treat COVID-19 in the clinic. Finally, we reviewed various approaches and technologies employed to develop vaccines against COVID-19 and summarized the attempts to repurpose various classes of drugs and novel therapeutic approaches.

Frequency of MicroRNA Response Elements Identifies Pathologically Relevant Signaling Pathways in Triple-Negative Breast Cancer.

Complex interactions between mRNAs and microRNAs influence cellular functions. The mRNA-microRNA interactions also determine the post-transcriptional availability of mRNAs and unbound microRNAs. MicroRNAs binds to one or more microRNA response elements (MREs) located on the 3'UTR of mRNAs. In this study, we leveraged MREs and their frequencies in cancer and matched normal tissues to obtain insights into disease-specific interactions between mRNAs and microRNAs. We developed a bioinformatics method "ReMIx" that utilizes RNA sequencing (RNA-Seq) data to quantify MRE frequencies across the transcriptome. We applied ReMIx to triple-negative (TN) breast cancer tumor-normal adjacent pairs and identified MREs specific to TN tumors. ReMIx identified candidate mRNAs and microRNAs in the MAPK signaling cascade. Further analysis of MAPK gene regulatory networks revealed microRNA partners that influence and modulate MAPK signaling. In conclusion, we demonstrate a novel method of using MREs in the identification of functionally relevant mRNA-microRNA interactions in TN breast cancer.

PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient.

PURPOSE: The majority of patients with cancer receive treatments that are minimally informed by omics data. We propose a precision medicine computational framework, PANOPLY (Precision Cancer Genomic Report: Single Sample Inventory), to identify and prioritize drug targets and cancer therapy regimens. MATERIALS AND METHODS: The PANOPLY approach integrates clinical data with germline and somatic features obtained from multiomics platforms and applies machine learning and network analysis approaches in the context of the individual patient and matched controls. The PANOPLY workflow uses the following four steps: selection of matched controls to the patient of interest; identification of patient-specific genomic events; identification of suitable drugs using the driver-gene network and random forest analyses; and provision of an integrated multiomics case report of the patient with prioritization of anticancer drugs. RESULTS: The PANOPLY workflow can be executed on a stand-alone virtual machine and is also available for download as an R package. We applied the method to an institutional breast cancer neoadjuvant chemotherapy study that collected clinical and genomic data as well as patient-derived xenografts to investigate the prioritization offered by PANOPLY. In a chemotherapy-resistant patient-derived xenograft model, we found that that the prioritized drug, olaparib, was more effective than placebo in treating the tumor ( P < .05). We also applied PANOPLY to in-house and publicly accessible multiomics tumor data sets with therapeutic response or survival data available. CONCLUSION: PANOPLY shows promise as a means to prioritize drugs on the basis of clinical and multiomics data for an individual patient with cancer. Additional studies are needed to confirm this approach.

TSPYL Family Regulates CYP17A1 and CYP3A4 Expression: Potential Mechanism Contributing to Abiraterone Response in Metastatic Castration-Resistant Prostate Cancer.

The testis-specific Y-encoded-like protein (TSPYL) gene family includes TSPYL1 to TSPYL6. We previously reported that TSPYL5 regulates cytochrome P450 (CYP) 19A1 expression. Here we show that TSPYLs, especially TSPYL 1, 2, and 4, can regulate the expression of many CYP genes, including CYP17A1, a key enzyme in androgen biosynthesis, and CYP3A4, an enzyme that catalyzes the metabolism of abiraterone, a CYP17 inhibitor. Furthermore, a common TSPYL1 single nucleotide polymorphism (SNP), rs3828743 (G/A) (Pro62Ser), abolishes TSPYL1's ability to suppress CYP3A4 expression, resulting in reduced abiraterone concentrations and increased cell proliferation. Data from a prospective clinical trial of 87 metastatic castration-resistant prostate cancer patients treated with abiraterone acetate/prednisone showed that the variant SNP genotype (A) was significantly associated with worse response and progression-free survival. In summary, TSPYL genes are novel CYP gene transcription regulators, and genetic alteration within these genes significantly influences response to drug therapy through transcriptional regulation of CYP450 genes.

Androgen Receptor Variant AR-V9 Is Coexpressed with AR-V7 in Prostate Cancer Metastases and Predicts Abiraterone Resistance.

Purpose: Androgen receptor (AR) variant AR-V7 is a ligand-independent transcription factor that promotes prostate cancer resistance to AR-targeted therapies. Accordingly, efforts are under way to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC). The purpose of this study was to understand whether other AR variants may be coexpressed with AR-V7 and promote resistance to AR-targeted therapies.Experimental Design: We utilized complementary short- and long-read sequencing of intact AR mRNA isoforms to characterize AR expression in CRPC models. Coexpression of AR-V7 and AR-V9 mRNA in CRPC metastases and circulating tumor cells was assessed by RNA-seq and RT-PCR, respectively. Expression of AR-V9 protein in CRPC models was evaluated with polyclonal antisera. Multivariate analysis was performed to test whether AR variant mRNA expression in metastatic tissues was associated with a 12-week progression-free survival endpoint in a prospective clinical trial of 78 CRPC-stage patients initiating therapy with the androgen synthesis inhibitor, abiraterone acetate.Results: AR-V9 was frequently coexpressed with AR-V7. Both AR variant species were found to share a common 3' terminal cryptic exon, which rendered AR-V9 susceptible to experimental manipulations that were previously thought to target AR-V7 uniquely. AR-V9 promoted ligand-independent growth of prostate cancer cells. High AR-V9 mRNA expression in CRPC metastases was predictive of primary resistance to abiraterone acetate (HR = 4.0; 95% confidence interval, 1.31-12.2; P = 0.02).Conclusions: AR-V9 may be an important component of therapeutic resistance in CRPC. Clin Cancer Res; 23(16); 4704-15. ©2017 AACR.

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer.

Background: Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown. Methods: We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery. Results: Recurrent "targetable" alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance ( p53, AKT, and IKBKE ). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs. Conclusions: In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. "Targetable" alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

Custom Gene Capture and Next-Generation Sequencing to Resolve Discordant ALK Status by FISH and IHC in Lung Adenocarcinoma.

INTRODUCTION: We performed a genomic study in lung adenocarcinoma cases with discordant anaplastic lymphoma receptor tyrosine kinase gene (ALK) status by fluorescent in situ hybridization (FISH) and immunohistochemical (IHC) analysis. METHODS: DNA from formalin-fixed paraffin-embedded tissues of 16 discordant (four FISH-positive/IHC-negative and 12 FISH-negative/IHC-positive) cases by Vysis ALK Break Apart FISH and ALK IHC testing (ALK1 clone) were subjected to whole gene capture and next-generation sequencing (NGS) of nine genes, including ALK, echinoderm microtubule associated protein like 4 gene (EML4), kinesin family member 5B gene (KIF5B), staphylococcal nuclease and tudor domain containing 1 gene (SND1), BRAF, ret proto-oncogene (RET), ezrin gene (EZR), ROS1, and telomerase reverse transcriptase (TERT). All discordant cases (except one FISH-negative/IHC-positive case without sufficient tissue) were analyzed by IHC with D5F3 antibody. In one case with fresh frozen tissue, whole transcriptome sequencing was also performed. Twenty-six concordant (16 FISH-positive/IHC-positive and 10 FISH-negative/IHC-negative) cases were included as controls. RESULTS: In four ALK FISH-positive/IHC-negative cases, no EML4-ALK fusion gene was observed by NGS, but in one case using fresh frozen tissue, we identified EML4-baculoviral AIP repeat containing 6 gene (BIRC6) and AP2 associated kinase 1 gene (AAK1)-ALK fusion genes. Whole transcriptome sequencing revealed a highly expressed EML4-BIRC6 fusion transcript and a minimally expressed AAK1 transcript. Among the 12 FISH-negative/IHC-positive cases, no evidence of ALK gene rearrangement was detected by NGS. Eleven of 12 FISH-negative/IHC-positive cases detected by ALK1 clone were concordant by repeat ALK IHC with D5F3 antibody (i.e., FISH-negative/IHC-negative by D5F3 clone). Among the 16 ALK FISH-positive/IHC-positive positive controls, whole gene capture identified ALK gene fusion in 15 cases, including in one case with Huntington interacting protein 1 gene (HIP1)-ALK. No ALK fusion gene was observed in any of the 10 FISH-negative/IHC-negative cases. Other fusion genes involving ROS1, EZR, BRAF, and SND1 were also found. CONCLUSIONS: ALK FISH results appeared to be false-positive in three of four FISH-positive/IHC-negative cases, whereas no false-negative ALK FISH case was identified among 12 ALK FISH-negative/IHC-positive cases by ALK1 clone, which was in keeping with the concordant FISH-negative/IHC-negative status by D5F3 clone. Our targeted whole gene capture approach using formalin-fixed paraffin embedded samples was effective for detecting rearrangements involving ALK and other actionable oncogenes.

Determining the frequency of pathogenic germline variants from exome sequencing in patients with castrate-resistant prostate cancer.

OBJECTIVES: To determine the frequency of pathogenic inherited mutations in 157 select genes from patients with metastatic castrate-resistant prostate cancer (mCRPC). DESIGN: Observational. SETTING: Multisite US-based cohort. PARTICIPANTS: Seventy-one adult male patients with histological confirmation of prostate cancer, and had progressive disease while on androgen deprivation therapy. RESULTS: Twelve patients (17.4%) showed evidence of carrying pathogenic or likely pathogenic germline variants in the ATM, ATR, BRCA2, FANCL, MSR1, MUTYH, RB1, TSHR and WRN genes. All but one patient opted in to receive clinically actionable results at the time of study initiation. We also found that pathogenic germline BRCA2 variants appear to be enriched in mCRPC compared to familial prostate cancers. CONCLUSIONS: Pathogenic variants in cancer-susceptibility genes are frequently observed in patients with mCRPC. A substantial proportion of patients with mCRPC or their family members would derive clinical utility from mutation screening. TRIAL REGISTRATION NUMBER: NCT01953640; Results.

Measure transcript integrity using RNA-seq data.

BACKGROUND: Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling. RESULT: We developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86). CONCLUSION: TIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.

Mutational Landscapes of Sequential Prostate Metastases and Matched Patient Derived Xenografts during Enzalutamide Therapy.

Developing patient derived models from individual tumors that capture the biological heterogeneity and mutation landscape in advanced prostate cancer is challenging, but essential for understanding tumor progression and delivery of personalized therapy in metastatic castrate resistant prostate cancer stage. To demonstrate the feasibility of developing patient derived xenograft models in this stage, we present a case study wherein xenografts were derived from cancer metastases in a patient progressing on androgen deprivation therapy and prior to initiating pre-chemotherapy enzalutamide treatment. Tissue biopsies from a metastatic rib lesion were obtained for sequencing before and after initiating enzalutamide treatment over a twelve-week period and also implanted subcutaneously as well as under the renal capsule in immuno-deficient mice. The genome and transcriptome landscapes of xenografts and the original patient tumor tissues were compared by performing whole exome and transcriptome sequencing of the metastatic tumor tissues and the xenografts at both time points. After comparing the somatic mutations, copy number variations, gene fusions and gene expression we found that the patient's genomic and transcriptomic alterations were preserved in the patient derived xenografts with high fidelity. These xenograft models provide an opportunity for predicting efficacy of existing and potentially novel drugs that is based on individual metastatic tumor expression signature and molecular pharmacology for delivery of precision medicine.

Exome sequencing reveals frequent deleterious germline variants in cancer susceptibility genes in women with invasive breast cancer undergoing neoadjuvant chemotherapy.

When sequencing blood and tumor samples to identify targetable somatic variants for cancer therapy, clinically relevant germline variants may be uncovered. We evaluated the prevalence of deleterious germline variants in cancer susceptibility genes in women with breast cancer referred for neoadjuvant chemotherapy and returned clinically actionable results to patients. Exome sequencing was performed on blood samples from women with invasive breast cancer referred for neoadjuvant chemotherapy. Germline variants within 142 hereditary cancer susceptibility genes were filtered and reviewed for pathogenicity. Return of results was offered to patients with deleterious variants in actionable genes if they were not aware of their result through clinical testing. 124 patients were enrolled (median age 51) with the following subtypes: triple negative (n = 43, 34.7%), HER2+ (n = 37, 29.8%), luminal B (n = 31, 25%), and luminal A (n = 13, 10.5%). Twenty-eight deleterious variants were identified in 26/124 (21.0%) patients in the following genes: ATM (n = 3), BLM (n = 1), BRCA1 (n = 4), BRCA2 (n = 8), CHEK2 (n = 2), FANCA (n = 1), FANCI (n = 1), FANCL (n = 1), FANCM (n = 1), FH (n = 1), MLH3 (n = 1), MUTYH (n = 2), PALB2 (n = 1), and WRN (n = 1). 121/124 (97.6%) patients consented to return of research results. Thirteen (10.5%) had actionable variants, including four that were returned to patients and led to changes in medical management. Deleterious variants in cancer susceptibility genes are highly prevalent in patients with invasive breast cancer referred for neoadjuvant chemotherapy undergoing exome sequencing. Detection of these variants impacts medical management.

PatternCNV: a versatile tool for detecting copy number changes from exome sequencing data.

MOTIVATION: Exome sequencing (exome-seq) data, which are typically used for calling exonic mutations, have also been utilized in detecting DNA copy number variations (CNVs). Despite the existence of several CNV detection tools, there is still a great need for a sensitive and an accurate CNV-calling algorithm with built-in QC steps, and does not require a paired reference for each sample. RESULTS: We developed a novel method named PatternCNV, which (i) accounts for the read coverage variations between exons while leveraging the consistencies of this variability across different samples; (ii) reduces alignment BAM files to WIG format and therefore greatly accelerates computation; (iii) incorporates multiple QC measures designed to identify outlier samples and batch effects; and (iv) provides a variety of visualization options including chromosome, gene and exon-level views of CNVs, along with a tabular summarization of the exon-level CNVs. Compared with other CNV-calling algorithms using data from a lymphoma exome-seq study, PatternCNV has higher sensitivity and specificity. AVAILABILITY AND IMPLEMENTATION: The software for PatternCNV is implemented using Perl and R, and can be used in Mac or Linux environments. Software and user manual are available at http://bioinformaticstools.mayo.edu/research/patterncnv/, and R package at https://github.com/topsoil/patternCNV/.

Concordant effects of aromatase inhibitors on gene expression in ER+ Rat and human mammary cancers and modulation of the proteins coded by these genes.

Aromatase inhibitors are effective in therapy/prevention of estrogen receptor-positive (ER⁺) breast cancers. Rats bearing methylnitrosourea (MNU)-induced ER⁺ mammary cancers were treated with the aromatase inhibitor vorozole (1.25 mg/kg BW/day) for five days. RNA expression showed 162 downregulated and 180 upregulated (P < 0.05 and fold change >1.5) genes. Genes modulated by vorozole were compared with published data from four clinical neoadjuvant trials using aromatase inhibitors (anastrozole or letrozole). More than 30 genes and multiple pathways exhibited synchronous changes in animal and human datasets. Cell-cycle genes related to chromosome condensation in prometaphase [anaphase-prometaphase complex (APC) pathway, including Aurora-A kinase, BUBR1B, TOP2, cyclin A, cyclin B CDC2, and TPX-2)] were downregulated in animal and human studies reflecting the strong antiproliferative effects of aromatase inhibitors. Comparisons of rat arrays with a cell culture study where estrogen was removed from MCF-7 cells showed decreased expression of E2F1-modulated genes as a major altered pathway. Alterations of the cell cycle and E2F-related genes were confirmed in a large independent set of human samples (81 pairs baseline and two weeks anastrozole treatment). Decreases in proliferation-related genes were confirmed at the protein level for cyclin A2, BuRB1, cdc2, Pttg, and TPX-2. Interestingly, the proteins downregulated in tumors were similarly downregulated in vorozole-treated normal rat mammary epithelium. Finally, decreased expression of known estrogen-responsive genes (including TFF, 1,3, progesterone receptor, etc.) were decreased in the animal model. These studies demonstrate that gene expression changes (pathways and individual genes) are similar in humans and the rat model.

Effects on gene expression in rat liver after administration of RXR agonists: UAB30, 4-methyl-UAB30, and Targretin (Bexarotene).

Examination of three retinoid X receptor (RXR) agonists [Targretin (TRG), UAB30, and 4-methyl-UAB30 (4-Me-UAB30)] showed that all inhibited mammary cancer in rodents and two (TRG and 4-Me-UAB30) strikingly increased serum triglyceride levels. Agents were administered in diets to female Sprague-Dawley rats. Liver RNA was isolated and microarrayed on the Affymetrix GeneChip Rat Exon 1.0 ST array. Statistical tests identified genes that exhibited differential expression and fell into groups, or modules, with differential expression among agonists. Genes in specific modules were changed by one, two, or all three agonists. An interactome analysis assessed the effects on genes that heterodimerize with known nuclear receptors. For proliferator-activated receptor α/RXR-activated genes, the strongest response was TRG > 4-Me-UAB30 > UAB30. Many liver X receptor/RXR-related genes (e.g., Scd-1 and Srebf1, which are associated with increased triglycerides) were highly expressed in TRG and 4-Me-UAB30- but not UAB30-treated livers. Minimal expression changes were associated with retinoic acid receptor or vitamin D receptor heterodimers by any of the agonists. UAB30 unexpectedly and uniquely activated genes associated with the aryl hydrocarbon hydroxylase (Ah) receptor (Cyp1a1, Cyp1a2, Cyp1b1, and Nqo1). Based on the Ah receptor activation, UAB30 was tested for its ability to prevent dimethylbenzanthracene (DMBA)-induced mammary cancers, presumably by inhibiting DMBA activation, and was highly effective. Gene expression changes were determined by reverse transcriptase-polymerase chain reaction in rat livers treated with Targretin for 2.3, 7, and 21 days. These showed similar gene expression changes at all three time points, arguing some steady-state effect. Different patterns of gene expression among the agonists provided insight into molecular differences and allowed one to predict certain physiologic consequences of agonist treatment.

Stochastic variation of transcript abundance in C57BL/6J mice.

BACKGROUND: Transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. We have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice and to partition variation into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript abundance between genetically identical mice. RESULTS: The nature and extent of transcript variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variance. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues. CONCLUSIONS: Genetically identical mice can experience different individual outcomes for medically important traits. Variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. The extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences.