Breeze: an integrated quality control and data analysis application for high-throughput drug screening.

SUMMARY: High-throughput screening (HTS) enables systematic testing of thousands of chemical compounds for potential use as investigational and therapeutic agents. HTS experiments are often conducted in multi-well plates that inherently bear technical and experimental sources of error. Thus, HTS data processing requires the use of robust quality control procedures before analysis and interpretation. Here, we have implemented an open-source analysis application, Breeze, an integrated quality control and data analysis application for HTS data. Furthermore, Breeze enables a reliable way to identify individual drug sensitivity and resistance patterns in cell lines or patient-derived samples for functional precision medicine applications. The Breeze application provides a complete solution for data quality assessment, dose-response curve fitting and quantification of the drug responses along with interactive visualization of the results. AVAILABILITY AND IMPLEMENTATION: The Breeze application with video tutorial and technical documentation is accessible at https://breeze.fimm.fi; the R source code is publicly available at https://github.com/potdarswapnil/Breeze under GNU General Public License v3.0. CONTACT: swapnil.potdar@helsinki.fi. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical relevance of integrin alpha 4 in gastrointestinal stromal tumours.

The molecular mechanisms for the dissemination and metastasis of gastrointestinal stromal tumours (GIST) are incompletely understood. The purpose of the study was to investigate the clinical relevance of integrin alpha 4 (ITGA4) expression in GIST. GIST transcriptomes were first compared with transcriptomes of other types of cancer and histologically normal gastrointestinal tract tissue in the MediSapiens in silico database. ITGA4 was identified as an unusually highly expressed gene in GIST. Therefore, the effects of ITGA4 knock-down and selective integrin alpha 4 beta 1 (VLA-4) inhibitors on tumour cell proliferation and invasion were investigated in three GIST cell lines. In addition, the prognostic role of ITGA4 expression in cancer cells was investigated in a series of 147 GIST patients with immunohistochemistry. Inhibition of ITGA4-related signalling decreased GIST cell invasion in all investigated GIST cell lines. ITGA4 protein was expressed in 62 (42.2%) of the 147 GISTs examined, and expression was significantly associated with distant metastases during the course of the disease and several adverse prognostic features. Patients whose GIST expressed strongly ITGA4 had unfavourable GIST-specific survival and overall survival compared to patients with low or no ITGA4 expression. Taken together, ITGA4 is an important integrin in the molecular pathogenesis of GIST and may influence their clinical behaviour.

Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data.

MOTIVATION: Most data analysis tools for high-throughput screening (HTS) seek to uncover interesting hits for further analysis. They typically assume a low hit rate per plate. Hit rates can be dramatically higher in secondary screening, RNAi screening and in drug sensitivity testing using biologically active drugs. In particular, drug sensitivity testing on primary cells is often based on dose-response experiments, which pose a more stringent requirement for data quality and for intra- and inter-plate variation. Here, we compared common plate normalization and noise-reduction methods, including the B-score and the Loess a local polynomial fit method under high hit-rate scenarios of drug sensitivity testing. We generated simulated 384-well plate HTS datasets, each with 71 plates having a range of 20 (5%) to 160 (42%) hits per plate, with controls placed either at the edge of the plates or in a scattered configuration. RESULTS: We identified 20% (77/384) as the critical hit-rate after which the normalizations started to perform poorly. Results from real drug testing experiments supported this estimation. In particular, the B-score resulted in incorrect normalization of high hit-rate plates, leading to poor data quality, which could be attributed to its dependency on the median polish algorithm. We conclude that a combination of a scattered layout of controls per plate and normalization using a polynomial least squares fit method, such as Loess helps to reduce column, row and edge effects in HTS experiments with high hit-rates and is optimal for generating accurate dose-response curves. CONTACT: john.mpindi@helsinki.fi. AVAILABILITY AND IMPLEMENTATION: Supplementary information: R code and Supplementary data are available at Bioinformatics online.

Systematic drug screening reveals specific vulnerabilities and co-resistance patterns in endocrine-resistant breast cancer.

BACKGROUND: The estrogen receptor (ER) inhibitor tamoxifen reduces breast cancer mortality by 31 % and has served as the standard treatment for ER-positive breast cancers for decades. However, 50 % of advanced ER-positive cancers display de novo resistance to tamoxifen, and acquired resistance evolves in 40 % of patients who initially respond. Mechanisms underlying resistance development remain poorly understood and new therapeutic opportunities are urgently needed. Here, we report the generation and characterization of seven tamoxifen-resistant breast cancer cell lines from four parental strains. METHODS: Using high throughput drug sensitivity and resistance testing (DSRT) with 279 approved and investigational oncology drugs, exome-sequencing and network analysis, we for the first time, systematically determine the drug response profiles specific to tamoxifen resistance. RESULTS: We discovered emerging vulnerabilities towards specific drugs, such as ERK1/2-, proteasome- and BCL-family inhibitors as the cells became tamoxifen-resistant. Co-resistance to other drugs such as the survivin inhibitor YM155 and the chemotherapeutic agent paclitaxel also occurred. CONCLUSION: This study indicates that multiple molecular mechanisms dictate endocrine resistance, resulting in unexpected vulnerabilities to initially ineffective drugs, as well as in emerging co-resistances. Thus, combatting drug-resistant tumors will require patient-tailored strategies in order to identify new drug vulnerabilities, and to understand the associated co-resistance patterns.

Androgen receptor-interacting protein HSPBAP1 facilitates growth of prostate cancer cells in androgen-deficient conditions.

Hormonal therapies targeting androgen receptor (AR) are effective in prostate cancer (PCa), but often the cancers progress to fatal castrate-resistant disease. Improved understanding of the cellular events during androgen deprivation would help to identify survival and stress pathways whose inhibition could synergize with androgen deprivation. Toward this aim, we performed an RNAi screen on 2,068 genes, including kinases, phosphatases, epigenetic enzymes and other druggable gene targets. High-content cell spot microarray (CSMA) screen was performed in VCaP cells in the presence and absence of androgens with detection of Ki67 and cleaved ADP-ribose polymerase (cPARP) as assays for cell proliferation and apoptosis. Thirty-nine candidate genes were identified, whose silencing inhibited proliferation or induced apoptosis of VCaP cells exclusively under androgen-deprived conditions. One of the candidates, HSPB (heat shock 27 kDa)-associated protein 1 (HSPBAP1), was confirmed to be highly expressed in tumor samples and its mRNA expression levels increased with the Gleason grade. We found that strong HSPBAP1 immunohistochemical staining (IHC) was associated with shorter disease-specific survival of PCa patients compared with negative to moderate staining. Furthermore, we demonstrate that HSPBAP1 interacts with AR in the nucleus of PCa cells specifically during androgen-deprived conditions, occupies chromatin at PSA/klk3 and TMPRSS2/tmprss2 enhancers and regulates their expression. In conclusion, we suggest that HSPBAP1 aids in sustaining cell viability by maintaining AR signaling during androgen-deprived conditions.

A functional genetic screen reveals new regulators of ß1-integrin activity.

ß1 integrins constitute a large group of widely distributed adhesion receptors, which regulate the ability of cells to interact with their surroundings. This regulation of the expression and activity of integrins is crucial for tissue homeostasis and development and contributes to inflammation and cancer. We report an RNA interference screen to uncover genes involved in the regulation of ß1-integrin activity using cell spot microarray technology in cancer cell lines. Altogether, ten cancer and two normal cell lines were used to identify regulators of ß1 integrin activity. Cell biological analysis of the identified ß1-integrin regulatory genes revealed that modulation of integrin activity can influence cell invasion in a three-dimensional matrix. We demonstrate with loss-of-function and rescue experiments that CD9 activates and MMP8 inactivates ß1 integrins and that both proteins associate with ß1 integrins in cells. Furthermore, CD9 and MMP8 regulate cancer cell extravasation in vivo. Our discovery of new regulators of ß1-integrin activity highlight the complexity of integrin activity regulation and provide a set of new genes involved in regulation of integrin function.

Simplifying stable CHO cell line generation with high probability of monoclonality by using microfluidic dispensing as an alternative to fluorescence activated cell sorting.

Single cell cloning is a critical step for cell line development (CLD) for therapeutic protein production, with proof of monoclonality being compulsorily sought in regulatory filings. Among the different single cell deposition technologies, we found that fluorescence activated cell sorting (FACS) offers high probability of monoclonality and can allow selective enrichment of the producer cells. However, FACS instruments are expensive and resource-intensive, have a large footprint, require highly skilled operators and take hours for setup, thereby complicating the cell line generation process. With the aim of finding an easy-to-use alternative to FACS, we identified a flow cytometry-based microfluidic cell dispenser, which presents a single cell sorting solution for biopharmaceutical CLD. The microfluidic cell dispenser is small, budget-friendly, easy-to-use, requires lower-cost consumables, permits flow cytometry-enabled multiparametric target cell enrichment and offers fast and gentle single cell dispensing into multiwell plates. Following comprehensive evaluation, we found that single cell deposition by the microfluidic cell dispenser resulted in >99% probability of monoclonality for production cell lines. Moreover, the clonally derived producer cell lines generated from the microfluidic cell dispenser demonstrated comparable or improved growth profiles and production capability compared to the FACS derived cell lines. Taken together, microfluidic cell dispensing can serve as a cost-effective, efficient and convenient alternative to FACS, simplifying the biopharmaceutical CLD platform with significant reductions in both scientist time and running costs.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile. RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides. CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

Integrative genomic, transcriptomic, and RNAi analysis indicates a potential oncogenic role for FAM110B in castration-resistant prostate cancer.

BACKGROUND: Castration-resistant prostate cancer (CRPC) represents a therapeutic challenge for current medications. METHODS: In order to explore the molecular mechanisms involved in CRPC progression and to identify new therapeutic targets, we analyzed a unique sample set of 11 CRPCs and 7 advanced tumors by array-CGH and gene expression microarrays. The genome-wide DNA and RNA data were integrated to identify genes whose overexpression was driven by their amplification. To assess the functional role of these genes, their expression was analyzed in a transcriptional data set of 329 clinical prostate cancers and the corresponding gene products were silenced using RNA interference in prostate cancer cells. RESULTS: Six recurrent genetic targets were identified in the CRPCs; ATP1B1, AR, FAM110B, LAS1L, MYC, and YIPF6. In addition to AR and MYC, FAM110B emerged as a potential key gene involved in CRPC progression in a subset of the tumors. FAM110B was able to regulate AR signaling in prostate cancer cells and FAM110B itself was regulated by androgens. FAM110B siRNA inhibited the growth of prostate cancer cells in vitro, and this effect was substantially enhanced in androgen deficient conditions. Ectopic FAM110B expression in non-cancerous epithelial prostate cells induced aneuploidy and impaired antigen presentation. CONCLUSIONS: The DNA/RNA gene outlier detection combined with siRNA cell proliferation assay identified FAM110B as a potential growth promoting key gene for CRPC. FAM110B appears to have a key role in the androgen signaling and progression of CRPC impacting multiple cancer hallmarks and therefore highlighting a potential therapeutic target.

Arachidonic acid pathway members PLA2G7, HPGD, EPHX2, and CYP4F8 identified as putative novel therapeutic targets in prostate cancer.

The arachidonic acid and prostaglandin pathway has been implicated in prostate carcinogenesis, but comprehensive studies of the individual members in this key pathway are lacking. Here, we first conducted a systematic bioinformatic study of the expression of 36 arachidonic acid pathway genes across 9783 human tissue samples. The results showed that the PLA2G7, HPGD, EPHX2, and CYP4F8 genes are highly expressed in prostate cancer. Functional studies using RNA interference in prostate cancer cells indicated that all four genes are also essential for cell growth and survival. Clinical validation confirmed high PLA2G7 expression, especially in ERG oncogene-positive prostate cancers, and its silencing sensitized ERG-positive prostate cancer cells to oxidative stress. HPGD was highly expressed in androgen receptor (AR)-overexpressing advanced tumors, as well as in metastatic prostate cancers. EPHX2 mRNA correlated with AR in primary prostate cancers, and its inhibition in vitro reduced AR signaling and potentiated the effect of antiandrogen flutamide in cultured prostate cancer cells. In summary, we identified four novel putative therapeutic targets with biomarker potential for different subtypes of prostate cancer. In addition, our results indicate that inhibition of these enzymes may be particularly powerful when combined with other treatments, such as androgen deprivation or induction of oxidative stress.

A cell spot microarray method for production of high density siRNA transfection microarrays.

BACKGROUND: High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. RESULTS: Here, we describe the optimization of a miniaturized cell spot microarray (CSMA) method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. CONCLUSIONS: The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

High miR-30 Expression Associates with Improved Breast Cancer Patient Survival and Treatment Outcome.

Deregulated miRNA expression has been suggested in several stages of breast cancer pathogenesis. We have studied the miR-30 family, in particular miR-30d, in relation to breast cancer patient survival and treatment outcomes. With tumor specimens from 1238 breast cancer patients, we analyzed the association of miR-30d expression with tumor characteristics with the 5-year occurrence of breast cancer-specific death or distant metastasis (BDDM), and with 10-year breast cancer survival (BCS). We conducted a two-stage drug-screen to investigate the impact of miR-30 family members (miR-30a-30e) on sensitivity to doxorubicin and lapatinib in six breast cancer cell lines HCC1937, HCC1954, MDA-MB-361, MCF7, MDA-MB-436 and CAL-120, using drug sensitivity scores (DSS) to compare the miR-30 family mimics to their specific inhibitors. The study was complemented with Ingenuity Pathway Analysis (IPA) with the METABRIC data. We found that while high miR-30d expression is typical for aggressive tumors, it predicts better metastasis-free (pBDDM = 0.035, HR = 0.63, 95% CI = 0.4-0.9) and breast cancer-specific survival (pBCS = 0.018, HR = 0.61, 95% CI = 0.4-0.9), especially in HER2-positive (pBDDM = 0.0009), ER-negative (pBDDM = 0.003), p53-positive (pBDDM = 0.011), and highly proliferating (pBDDM = 0.0004) subgroups, and after adjuvant chemotherapy (pBDDM = 0.035). MiR-30d predicted survival independently of standard prognostic markers (pBDDM = 0.0004). In the drug-screening test, the miR-30 family sensitized the HER2-positive HCC1954 cell line to lapatinib (p < 10-2) and HCC1937, MDA-MB-361, MDA-MB-436 and CAL120 to doxorubicin (p < 10-4) with an opposite impact on MCF7. According to the pathway analysis, the miR-30 family has a suppressive effect on cell motility and metastasis in breast cancer. Our results suggest prognostic and predictive potential for the miR-30 family, which warrants further investigation.

Anagrelide for Gastrointestinal Stromal Tumor.

PURPOSE: Gastrointestinal stromal tumor (GIST) is a common type of soft-tissue sarcoma. Imatinib, an inhibitor of KIT, platelet-derived growth factor receptor alpha (PDGFRA), and a few other tyrosine kinases, is highly effective for GIST, but advanced GISTs frequently progress on imatinib and other approved tyrosine kinase inhibitors. We investigated phosphodiesterase 3 (PDE3) as a potential therapeutic target in GIST cell lines and xenograft models. EXPERIMENTAL DESIGN: The GIST gene expression profile was interrogated in the MediSapiens IST Online transcriptome database comprising human tissue and cancer samples, and PDE3A and PDE3B expression was studied using IHC on tissue microarrays (TMA) consisting of 630 formalin-fixed human tissue samples. GIST cell lines were screened for sensitivity to 217 anticancer compounds, and the efficacy of PDE inhibitors on GIST was further studied in GIST cell lines and patient-derived mouse xenograft models. RESULTS: GISTs expressed PDE3A and PDE3B frequently compared with other human normal or cancerous tissues both in the in silico database and the TMAs. Anagrelide was identified as the most potent of the PDE3 modulators evaluated. It reduced cell viability, promoted cell death, and influenced cell signaling in GIST cell lines. Anagrelide inhibited tumor growth in GIST xenograft mouse models. Anagrelide was also effective in a GIST xenograft mouse model with KIT exon 9 mutation that may pose a therapeutic challenge, as these GISTs require a high daily dose of imatinib. CONCLUSIONS: PDE3A and PDE3B are frequently expressed in GIST. Anagrelide had anticancer efficacy in GIST xenograft models and warrants further testing in clinical trials.

ITGB1-dependent upregulation of Caveolin-1 switches TGFß signalling from tumour-suppressive to oncogenic in prostate cancer.

Caveolin-1 (CAV1) is over-expressed in prostate cancer (PCa) and is associated with adverse prognosis, but the molecular mechanisms linking CAV1 expression to disease progression are poorly understood. Extensive gene expression correlation analysis, quantitative multiplex imaging of clinical samples, and analysis of the CAV1-dependent transcriptome, supported that CAV1 re-programmes TGFß signalling from tumour suppressive to oncogenic (i.e. induction of SLUG, PAI-1 and suppression of CDH1, DSP, CDKN1A). Supporting such a role, CAV1 knockdown led to growth arrest and inhibition of cell invasion in prostate cancer cell lines. Rationalized RNAi screening and high-content microscopy in search for CAV1 upstream regulators revealed integrin beta1 (ITGB1) and integrin associated proteins as CAV1 regulators. Our work suggests TGFß signalling and beta1 integrins as potential therapeutic targets in PCa over-expressing CAV1, and contributes to better understand the paradoxical dual role of TGFß in tumour biology.

Comprehensive Drug Testing of Patient-derived Conditionally Reprogrammed Cells from Castration-resistant Prostate Cancer.

BACKGROUND: Technology development to enable the culture of human prostate cancer (PCa) progenitor cells is required for the identification of new, potentially curative therapies for PCa. OBJECTIVE: We established and characterized patient-derived conditionally reprogrammed cells (CRCs) to assess their biological properties and to apply these to test the efficacies of drugs. DESIGN, SETTING, AND PARTICIPANTS: CRCs were established from seven patient samples with disease ranging from primary PCa to advanced castration-resistant PCa (CRPC). The CRCs were characterized by genomic, transcriptomic, protein expression, and drug profiling. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The phenotypic quantification of the CRCs was done based on immunostaining followed by image analysis with Advanced Cell Classifier using Random Forest supervised machine learning. Copy number aberrations (CNAs) were called from whole-exome sequencing and transcriptomics using in-house pipelines. Dose-response measurements were used to generate multiparameter drug sensitivity scores using R-statistical language. RESULTS AND LIMITATIONS: We generated six benign CRC cultures which all had an androgen receptor-negative, basal/transit-amplifying phenotype with few CNAs. In three-dimensional cell culture, these cells could re-express the androgen receptor. The CRCs from a CRPC patient (HUB.5) displayed multiple CNAs, many of which were shared with the parental tumor. We carried out high-throughput drug-response studies with 306 emerging and clinical cancer drugs. Using the benign CRCs as controls, we identified the Bcl-2 family inhibitor navitoclax as the most potent cancer-specific drug for the CRCs from a CRPC patient. Other drug efficacies included taxanes, mepacrine, and retinoids. CONCLUSIONS: Comprehensive cancer pharmacopeia-wide drug testing of CRCs from a CRPC patient highlighted both known and novel drug sensitivities in PCa, including navitoclax, which is currently being tested in clinical trials of CRPC. PATIENT SUMMARY: We describe an approach to generate patient-derived cancer cells from advanced prostate cancer and apply such cells to discover drugs that could be applied in clinical trials for castration-resistant prostate cancer.

Systematic Identification of MicroRNAs That Impact on Proliferation of Prostate Cancer Cells and Display Changed Expression in Tumor Tissue.

BACKGROUND: Systematic approaches to functionally identify key players in microRNA (miRNA)-target networks regulating prostate cancer (PCa) proliferation are still missing. OBJECTIVE: To comprehensively map miRNA regulation of genes relevant for PCa proliferation through phenotypic screening and tumor expression data. DESIGN, SETTING, AND PARTICIPANTS: Gain-of-function screening with 1129 miRNA molecules was performed in five PCa cell lines, measuring proliferation, viability, and apoptosis. These results were integrated with changes in miRNA expression from two cohorts of human PCa (188 tumors in total). For resulting miRNAs, the predicted targets were collected and analyzed for patterns with gene set enrichment analysis, and for their association with biochemical recurrence free survival. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Rank product statistical analysis was used to evaluate miRNA effects in phenotypic screening and for expression differences in the prostate tumor cohorts. Expression data were analyzed using the significance analysis of microarrays (SAM) method and the patient material was subjected to Kaplan-Meier statistics. RESULTS AND LIMITATIONS: Functional screening identified 25 miRNAs increasing and 48 miRNAs decreasing cell viability. Data integration resulted in 14 miRNAs, with aberrant expression and effect on proliferation. These miRNAs are predicted to regulate >3700 genes, of which 28 were found up-regulated and 127 down-regulated in PCa compared with benign tissue. Seven genes, FLNC, MSRB3, PARVA, PCDH7, PRNP, RAB34, and SORBS1, showed an inverse association to their predicted miRNA, and were identified to significantly correlate with biochemical recurrence free survival in PCa patients. CONCLUSIONS: A systematic in vitro screening approach combined with in vivo expression and gene set enrichment analysis provide unbiased means for revealing novel miRNA-target links, possibly driving the oncogenic processes in PCa. PATIENT SUMMARY: This study identified novel regulatory molecules, which impact on PCa proliferation and are aberrantly expressed in clinical tumors. Thus, our study reveals regulatory nodes with potential for therapy.

REG4 Is Highly Expressed in Mucinous Ovarian Cancer: A Potential Novel Serum Biomarker.

Preoperative diagnostics of ovarian neoplasms rely on ultrasound imaging and the serum biomarkers CA125 and HE4. However, these markers may be elevated in non-neoplastic conditions and may fail to identify most non-serous epithelial cancer subtypes. The objective of this study was to identify histotype-specific serum biomarkers for mucinous ovarian cancer. The candidate genes with mucinous histotype specific expression profile were identified from publicly available gene-expression databases and further in silico data mining was performed utilizing the MediSapiens database. Candidate biomarker validation was done using qRT-PCR, western blotting and immunohistochemical staining of tumor tissue microarrays. The expression level of the candidate gene in serum was compared to the serum CA125 and HE4 levels in a patient cohort of prospectively collected advanced ovarian cancer. Database searches identified REG4 as a potential biomarker with specificity for the mucinous ovarian cancer subtype. The specific expression within epithelial ovarian tumors was further confirmed by mRNA analysis. Immunohistochemical staining of ovarian tumor tissue arrays showed distinctive cytoplasmic expression pattern only in mucinous carcinomas and suggested differential expression between benign and malignant mucinous neoplasms. Finally, an ELISA based serum biomarker assay demonstrated increased expression only in patients with mucinous ovarian cancer. This study identifies REG4 as a potential serum biomarker for histotype-specific detection of mucinous ovarian cancer and suggests serum REG4 measurement as a non-invasive diagnostic tool for postoperative follow-up of patients with mucinous ovarian cancer.

The impact of low-frequency and rare variants on lipid levels.

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.

A community effort to assess and improve drug sensitivity prediction algorithms.

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.