Characterisation of new in vitro models and identification of potentially active drugs in angiosarcoma

Angiosarcoma is a rare soft tissue sarcoma originating from endothelial cells. Given that current treatments for advanced disease have shown limited efficacy, alternative therapies need to be identified. In rare diseases, patient-derived cell models are crucial for screening anti-tumour activity. In this study, cell line models were characterised in 2D and 3D cultures. The cell lines' growth, migration and invasion capabilities were explored, confirming them as useful tools for preclinical angiosarcoma studies. By screening a drug library, we identified potentially effective compounds: 8-amino adenosine impacted cell growth and inhibited migration and invasion at considerably low concentrations as a single agent. No synergistic effect was detected when combining with paclitaxel, gemcitabine or doxorubicin. These results suggest that this compound could be a potentially useful drug in the treatment of AGS.

Drug repurposing platform for deciphering the druggable SARS-CoV-2 interactome

The coronavirus disease 2019 (COVID-19) pandemic has heavily challenged the global healthcare system. Despite the vaccination programs, the new virus variants are circulating. Further research is required for understanding of the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and for discovery of therapeutic agents against the virus. Here, we took advantage of drug repurposing to identify if existing drugs could inhibit SARS-CoV-2 infection. We established an open high throughput platform for in vitro screening of drugs against SARS-CoV-2 infection. We screened ∼1000 drugs for their ability to inhibit SARS-CoV-2-induced cell death in the African green monkey kidney cell line (Vero-E6), analyzed how the hit compounds affect the viral N (nucleocapsid) protein expression in human cell lines using high-content microscopic imaging and analysis, determined the hit drug targets in silico, and assessed their ability to cause phospholipidosis, which can interfere with the viral replication. Duvelisib was found by in silico interaction assay as a potential drug targeting virus-host protein interactions. The predicted interaction between PARP1 and S protein, affected by Duvelisib, was further validated by immunoprecipitation. Our results represent a rapidly applicable platform for drug repurposing and evaluation of the new emerging viruses' responses to the drugs. Further in silico studies help us to discover the druggable host pathways involved in the infectious cycle of SARS-CoV-2.

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs' protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective combinations with the least toxicity and the best synergistic effect on blast cells. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment.

A novel SERPINA12 variant and first European patients with diffuse palmoplantar keratoderma

BACKGROUND

Hereditary palmoplantar keratodermas (hPPKs) comprise a heterogeneous group of skin disorders characterized by persistent palmoplantar hyperkeratosis. Loss-of-function variants in a serine peptidase inhibitor, SERPINA12, have recently been implicated in autosomal recessive diffuse hPPK. The disorder appears to share similarities with another hPPK associated with protease overactivity, namely Nagashima-type PPK (NPPK) caused by biallelic variants in SERPINB7.

OBJECTIVES

The aim of this study was to enhance the understanding of the clinical and genetic characteristics of serine protease-related hPPKs caused by variants in SERPINA12 and SERPINB7.

METHODS

Whole-exome sequencing (WES) was performed for hPPK patients. Haplotype analysis was completed for the patients with identified recessive SERPINA12 variants and their available family members. In addition, the current literature of SERPINA12- and SERPINB7-related hPPKs was summarized.

RESULTS

The phenotype of SERPINA12-related hPPK was confirmed by reporting three new SERPINA12 patients, the first of European origin. A novel SERPINA12 c.1100G>A p.(Gly367Glu) missense variant was identified confirming that the variant spectrum of SERPINA12 include both truncating and missense variants. The previously reported SERPINA12 c.631C>T p.(Arg211*) was indicated enriched in the Finnish population due to a plausible founder effect. In addition, SERPINA12 hPPK patients were shown to share a similar phenotype to patients with recessive variants in SERPINB7. The shared phenotype included diffuse transgradient PPK since birth or early childhood and frequent palmoplantar hyperhidrosis, aquagenic whitening and additional hyperkeratotic lesions in non-palmoplantar areas. SERPINA12 and SERPINB7 hPPK patients cannot be distinguished without genetic analysis.

CONCLUSIONS

Recessive variants in SERPINA12 and SERPINB7 leading to protease overactivity and hPPK produce a similar phenotype, indistinguishable without genetic analysis. SERPINA12 variants should be assessed also in non-Asian patients with diffuse transgradient PPK. Understanding the role of serine protease inhibitors will provide insights into the complex proteolytic network in epidermal homeostasis.

Robust scoring of selective drug responses for patient-tailored therapy selection

Most patients with advanced malignancies are treated with severely toxic, first-line chemotherapies. Personalized treatment strategies have led to improved patient outcomes and could replace one-size-fits-all therapies, yet they need to be tailored by testing of a range of targeted drugs in primary patient cells. Most functional precision medicine studies use simple drug-response metrics, which cannot quantify the selective effects of drugs (i.e., the differential responses of cancer cells and normal cells). We developed a computational method for selective drug-sensitivity scoring (DSS), which enables normalization of the individual patient's responses against normal cell responses. The selective response scoring uses the inhibition of noncancerous cells as a proxy for potential drug toxicity, which can in turn be used to identify effective and safer treatment options. Here, we explain how to apply the selective DSS calculation for guiding precision medicine in patients with leukemia treated across three cancer centers in Europe and the USA; the generic methods are also widely applicable to other malignancies that are amenable to drug testing. The open-source and extendable R-codes provide a robust means to tailor personalized treatment strategies on the basis of increasingly available ex vivo drug-testing data from patients in real-world and clinical trial settings. We also make available drug-response profiles to 527 anticancer compounds tested in 10 healthy bone marrow samples as reference data for selective scoring and de-prioritization of drugs that show broadly toxic effects. The procedure takes <60 min and requires basic skills in R.

Breeze 2.0: an interactive web-tool for visual analysis and comparison of drug response data

Functional precision medicine (fPM) offers an exciting, simplified approach to finding the right applications for existing molecules and enhancing therapeutic potential. Integrative and robust tools ensuring high accuracy and reliability of the results are critical. In response to this need, we previously developed Breeze, a drug screening data analysis pipeline, designed to facilitate quality control, dose-response curve fitting, and data visualization in a user-friendly manner. Here, we describe the latest version of Breeze (release 2.0), which implements an array of advanced data exploration capabilities, providing users with comprehensive post-analysis and interactive visualization options that are essential for minimizing false positive/negative outcomes and ensuring accurate interpretation of drug sensitivity and resistance data. The Breeze 2.0 web-tool also enables integrative analysis and cross-comparison of user-uploaded data with publicly available drug response datasets. The updated version incorporates new drug quantification metrics, supports analysis of both multi-dose and single-dose drug screening data and introduces a redesigned, intuitive user interface. With these enhancements, Breeze 2.0 is anticipated to substantially broaden its potential applications in diverse domains of fPM.

Drug sensitivity profiling of 3D tumor tissue cultures in the pediatric precision oncology program INFORM

The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75-78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET, and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs.

A novel desmoplakin mutation causes dilated cardiomyopathy with palmoplantar keratoderma as an early clinical sign

Background

PPKs represent a heterogeneous group of disorders with hyperkeratosis of palmar and/or plantar skin. PPK, hair shaft abnormalities, cardiomyopathy and arrhythmias can be caused by mutations in desmosomal genes, e.g. desmoplakin (DSP). PPK should trigger genetic testing to reveal mutations with possible related cardiac disease.

Objectives

To report a large multigenerational family with a novel DSP mutation associated with early‐onset PPK and adult‐onset cardiomyopathy and arrhythmias.

Methods

A custom‐designed in‐house panel of 35 PPK related genes was used to screen mutations in the index patient with focal PPK. The identified DSP mutation was verified by Sanger sequencing. DNA samples from 20 members of the large multigenerational family were sequenced for the DSP mutation. Medical records were reviewed. Clinical dermatological evaluation was performed, including light microscopy of hair samples. Cardiac evaluation included clinical examination, echocardiography, cardiac magnetic resonance imaging (CMR), electrocardiogram (ECG), Holter monitoring and laboratory tests.

Results

We identified a novel autosomal dominant truncating DSP c.2493delA p.(Glu831Aspfs*33) mutation associated with dilated cardiomyopathy (DCM) with arrhythmia susceptibility and focal PPK as an early cutaneous sign. The mutation was found in nine affected family members, but not in any unaffected members. Onset of dermatological findings preceded cardiac symptoms which were variable and occurred at adult age.

Conclusions

We report a novel truncating DSP mutation causing focal PPK with varying severity and left ventricular dilatation and ventricular extrasystoles. This finding emphasizes the importance of genetic diagnosis in patients with PPK for clinical counselling and management of cardiomyopathies and arrhythmias.

Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia

We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.See related commentary by Letai, p. 290.This article is highlighted in the In This Issue feature, p. 275.

Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

Therapeutic targeting of KSP in preclinical models of high-risk neuroblastoma

Neuroblastoma is a childhood malignancy with often dismal prognosis; relapse is common despite intense treatment. Here, we used human tumor organoids representing multiple MYCN-amplified high-risk neuroblastomas to perform a high-throughput drug screen with approved or emerging oncology drugs. Tumor-selective effects were calculated using drug sensitivity scores. Several drugs with previously unreported anti-neuroblastoma effects were identified by stringent selection criteria. ARRY-520, an inhibitor of kinesin spindle protein (KSP), was among those causing reduced viability. High expression of the KSP-encoding gene KIF11 was associated with poor outcome in neuroblastoma. Genome-scale loss-of-function screens in hundreds of human cancer cell lines across 22 tumor types revealed that KIF11 is particularly important for neuroblastoma cell viability. KSP inhibition in neuroblastoma patient-derived xenograft (PDX) cells resulted in the formation of abnormal monoastral spindles, mitotic arrest, up-regulation of mitosis-associated genes, and apoptosis. In vivo, KSP inhibition caused regression of MYCN-amplified neuroblastoma PDX tumors. Furthermore, treatment of mice harboring orthotopic neuroblastoma PDX tumors resulted in increased survival. Our results suggested that KSP inhibition could be a promising treatment strategy in children with high-risk neuroblastoma.

Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

In Vitro Identification and In Vivo Confirmation of Inhibitors for Sweet Potato Chlorotic Stunt Virus RNA Silencing Suppressor, a Viral RNase III

Sweet potato virus disease (SPVD), caused by synergistic infection of Sweet potato chlorotic stunt virus (SPCSV) and Sweet potato feathery mottle virus (SPFMV), is responsible for substantial yield losses all over the world. However, there are currently no approved treatments for this severe disease. The crucial role played by RNase III of SPCSV (CSR3) as an RNA silencing suppressor during the viruses' synergistic interaction in sweetpotato makes it an ideal drug target for developing antiviral treatment. In this study, high-throughput screening (HTS) of small molecular libraries targeting CSR3 was initiated by a virtual screen using Glide docking, allowing the selection of 6,400 compounds out of 136,353. We subsequently developed and carried out kinetic-based HTS using fluorescence resonance energy transfer technology, which isolated 112 compounds. These compounds were validated with dose-response assays including kinetic-based HTS and binding affinity assays using surface plasmon resonance and microscale thermophoresis. Finally, the interference of the selected compounds with viral accumulation was verified in planta In summary, we identified five compounds belonging to two structural classes that inhibited CSR3 activity and reduced viral accumulation in plants. These results provide the foundation for developing antiviral agents targeting CSR3 to provide new strategies for controlling sweetpotato virus diseases.IMPORTANCE We report here a high-throughput inhibitor identification method that targets a severe sweetpotato virus disease caused by coinfection with two viruses (SPCSV and SPFMV). The disease is responsible for up to 90% yield losses. Specifically, we targeted the RNase III enzyme encoded by SPCSV, which plays an important role in suppressing the RNA silencing defense system of sweetpotato plants. Based on virtual screening, laboratory assays, and confirmation in planta, we identified five compounds that could be used to develop antiviral drugs to combat the most severe sweetpotato virus disease.

Hereditary palmoplantar keratoderma - phenotypes and mutations in 64 patients

BACKGROUND

Hereditary palmoplantar keratodermas (PPK) represent a heterogeneous group of rare skin disorders with epidermal hyperkeratosis of the palms and soles, with occasional additional manifestations in other tissues. Mutations in at least 69 genes have been implicated in PPK, but further novel candidate genes and mutations are still to be found.

OBJECTIVES

To identify mutations underlying PPK in a cohort of 64 patients.

METHODS

DNA of 48 patients was analysed on a custom-designed in-house panel for 35 PPK genes, and 16 patients were investigated by a diagnostic genetic laboratory either by whole-exome sequencing, gene panels or targeted single-gene sequencing.

RESULTS

Of the 64 PPK patients, 32 had diffuse (50%), 19 focal (30%) and 13 punctate (20%) PPK. None had striate PPK. Pathogenic mutations in altogether five genes were identified in 31 of 64 (48%) patients, the majority (22/31) with diffuse PPK. Of them, 11 had a mutation in AQP5, five in SERPINB7, four in KRT9 and two in SLURP1. AAGAB mutations were found in nine punctate PPK patients. New mutations were identified in KRT9 and AAGAB. No pathogenic mutations were detected in focal PPK. Variants of uncertain significance (VUS) in PPK-associated and other genes were observed in 21 patients that might explain their PPK. No suggestive pathogenic variants were found for 12 patients.

CONCLUSIONS

Diffuse PPK was the most common (50%) and striate PPK was not observed. We identified pathogenic mutations in 48% of our PPK patients, mainly in five genes: AQP5, AAGAB, KRT9, SERPINB7 and SLURP1.

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.

High NRF2 Levels Correlate with Poor Prognosis in Colorectal Cancer Patients and with Sensitivity to the Kinase Inhibitor AT9283 In Vitro

Aberrant hyperactivation of nuclear factor erythroid 2 (NF-E2) p45-related factor 2 (NRF2) is a common event in many tumour types and associates with resistance to therapy and poor patient prognosis; however, its relevance in colorectal tumours is not well-established. Measuring the expression of surrogate genes for NRF2 activity in silico, in combination with validation in patients' samples, we show that the NRF2 pathway is upregulated in colorectal tumours and that high levels of nuclear NRF2 correlate with a poor patient prognosis. These results highlight the need to overcome the protection provided by NRF2 and present an opportunity to selectively kill cancer cells with hyperactive NRF2. Exploiting the CRISPR/Cas9 technology, we generated colorectal cancer cell lines with hyperactive NRF2 and used them to perform a drug screen. We identified AT9283, an Aurora kinase inhibitor, for its selectivity towards killing cancer cells with hyperactive NRF2 as a consequence to either genetic or pharmacological activation. Our results show that hyperactivation of NRF2 in colorectal cancer cells might present a vulnerability that could potentially be therapeutically exploited by using the Aurora kinase inhibitor AT9283.

Development of FRET-based high-throughput screening for viral RNase III inhibitors

The class 1 ribonuclease III (RNase III) encoded by Sweet potato chlorotic stunt virus (CSR3) suppresses RNA silencing in plant cells and thereby counters the host antiviral response by cleaving host small interfering RNAs, which are indispensable components of the plant RNA interference (RNAi) pathway. The synergy between sweet potato chlorotic stunt virus and sweet potato feathery mottle virus can reduce crop yields by 90%. Inhibitors of CSR3 might prove efficacious to counter this viral threat, yet no screen has been carried out to identify such inhibitors. Here, we report a novel high-throughput screening (HTS) assay based on fluorescence resonance energy transfer (FRET) for identifying inhibitors of CSR3. For monitoring CSR3 activity via HTS, we used a small interfering RNA substrate that was labelled with a FRET-compatible dye. The optimized HTS assay yielded 109 potential inhibitors of CSR3 out of 6,620 compounds tested from different small-molecule libraries. The three best inhibitor candidates were validated with a dose-response assay. In addition, a parallel screen of the selected candidates was carried out for a similar class 1 RNase III enzyme from Escherichia coli (EcR3), and this screen yielded a different set of inhibitors. Thus, our results show that the CSR3 and EcR3 enzymes were inhibited by distinct types of molecules, indicating that this HTS assay could be widely applied in drug discovery of class 1 RNase III enzymes.

Patient-Derived Organoids from Multiple Colorectal Cancer Liver Metastases Reveal Moderate Intra-patient Pharmacotranscriptomic Heterogeneity

PURPOSE

Molecular tumor heterogeneity may have important implications for the efficacy of targeted therapies in metastatic cancers. Inter-metastatic heterogeneity of sensitivity to anticancer agents has not been well explored in colorectal cancer.

EXPERIMENTAL DESIGN

We established a platform for ex vivo pharmacogenomic profiling of patient-derived organoids (PDO) from resected colorectal cancer liver metastases. Drug sensitivity testing (n = 40 clinically relevant agents) and gene expression profiling were performed on 39 metastases from 22 patients.

RESULTS

Three drug-response clusters were identified among the colorectal cancer metastases, based primarily on sensitivities to EGFR and/or MDM2 inhibition, and corresponding with RAS mutations and TP53 activity. Potentially effective therapies, including off-label use of drugs approved for other cancer types, could be nominated for eighteen patients (82%). Antimetabolites and targeted agents lacking a decisive genomic marker had stronger differential activity than most approved chemotherapies. We found limited intra-patient drug sensitivity heterogeneity between PDOs from multiple (2-5) liver metastases from each of ten patients. This was recapitulated at the gene expression level, with a highly proportional degree of transcriptomic and pharmacological variation. One PDO with a multi-drug resistance profile, including resistance to EGFR inhibition in a RAS-mutant background, showed sensitivity to MEK plus mTOR/AKT inhibition, corresponding with low-level PTEN expression.

CONCLUSIONS

Intra-patient inter-metastatic pharmacological heterogeneity was not pronounced and ex vivo drug screening may identify novel treatment options for metastatic colorectal cancer. Variation in drug sensitivities was reflected at the transcriptomic level, suggesting potential to develop gene expression-based predictive signatures to guide experimental therapies.

Prediction of drug combination effects with a minimal set of experiments

High-throughput drug combination screening provides a systematic strategy to discover unexpected combinatorial synergies in pre-clinical cell models. However, phenotypic combinatorial screening with multi-dose matrix assays is experimentally expensive, especially when the aim is to identify selective combination synergies across a large panel of cell lines or patient samples. Here we implemented DECREASE, an efficient machine learning model that requires only a limited set of pairwise dose-response measurements for accurate prediction of drug combination synergy and antagonism. Using a compendium of 23,595 drug combination matrices tested in various cancer cell lines, and malaria and Ebola infection models, we demonstrate how cost-effective experimental designs with DECREASE capture almost the same degree of information for synergy and antagonism detection as the fully-measured dose-response matrices. Measuring only the diagonal of the matrix provides an accurate and practical option for combinatorial screening. The open-source web-implementation enables applications of DECREASE to both pre-clinical and translational studies.

Effects of sickness absence on disability pension risk: Finnish register study of two native groups

Background

Sickness absence and disability pension have a close connection and both describe the health of working-aged populations. The aim of this paper was to study if Swedish and Finnish speakers differ in the risk of disability pension after first-time sickness absence. This may reveal new aspects how to support health and work ability promotion activities.

Methods

The longitudinal register data used come from Statistics Finland. They consist of random samples of 5 % of all Finnish speakers and 20 % of all Swedish speakers, observed throughout the period 1989-2010. The analyses concerned non-retired individuals aged 16-60 years who were under risk of first-time sickness absence that extended 10 days. Discrete-time hazard models were estimated to both language groups to evaluate how first-time sickness absence, time since absence, length of absence, and various socio-economic control variables affected the disability pension risk.

Results

The disability pension risk was extremely high immediately after the sickness absence receipt and remained elevated thereafter approximately 20 times higher as compared to non-recipients. A strong interrelation between first-time sickness absence and the risk of subsequent disability pension was found for both language groups and the risk was persistent in the very long term. The risk pattern looked similar to both Swedish and Finnish speakers and we did not observe any differences between women and men.

Conclusions

Paid sickness absence is illustrative of strong health selection and a notable risk for reduced work ability even in the more distant future. The currently implemented policies in Finland, which require statements about rehabilitation plans soon after individuals have entered a sickness spell, can be considered beneficial for both the individual and society. Comparison of the language groups shows that the disability pension process after sickness absence is operating similarly to both groups.

Key messages

Sickness absence requiring medical certificate is an indicator of possible long-term work disability. Timing of rehabilitation process during the sickness absence is critical.

Network pharmacology modeling identifies synergistic Aurora B and ZAK interaction in triple-negative breast cancer

Cancer cells with heterogeneous mutation landscapes and extensive functional redundancy easily develop resistance to monotherapies by emerging activation of compensating or bypassing pathways. To achieve more effective and sustained clinical responses, synergistic interactions of multiple druggable targets that inhibit redundant cancer survival pathways are often required. Here, we report a systematic polypharmacology strategy to predict, test, and understand the selective drug combinations for MDA-MB-231 triple-negative breast cancer cells. We started by applying our network pharmacology model to predict synergistic drug combinations. Next, by utilizing kinome-wide drug-target profiles and gene expression data, we pinpointed a synergistic target interaction between Aurora B and ZAK kinase inhibition that led to enhanced growth inhibition and cytotoxicity, as validated by combinatorial siRNA, CRISPR/Cas9, and drug combination experiments. The mechanism of such a context-specific target interaction was elucidated using a dynamic simulation of MDA-MB-231 signaling network, suggesting a cross-talk between p53 and p38 pathways. Our results demonstrate the potential of polypharmacological modeling to systematically interrogate target interactions that may lead to clinically actionable and personalized treatment options.

Abstract 2153: Ex vivo drug sensitivity testing of primary cells for precision cancer medicine

Introduction/Purpose:

Cancer therapy is increasingly moving towards individualized care and therapy, but there are still gaps between what is known and described on the molecular level about cancers and what is applied in the clinic. In an attempt to bridge the knowledge gap, we at the Institute for Molecular Medicine Finland (FIMM) have set up an Individualized Systems Medicine program that integrates clinical information, molecular profiling and functional information about individual patients’ cancers (Pemovska et al, Cancer Discov, 2013). Central to this program is the Drug Sensitivity and Resistance Testing (DSRT) where we functionally profile the responses of primary cancer cells to a comprehensive clinical oncology and signal transduction inhibitor drug collection of 528 compounds.

Methods:

Acoustic dispensing platforms are integral to the success of this profiling activity. We have to date produced approximately 3000 drug sets as dose response assay ready plates. The acoustic dispensing allows for making pre-drugged single drug plate sets and/or drug combination plates within hours after sampling of the cells. The plates are also readily sent to researchers anywhere in the world for running comparable assays at other sites. The drugging reproducibility is excellent generating results with correlations of 0.98 or higher in replicate assays. We have developed in-house software solutions to aid these processes: a script for quick creation of transfer list for combination plates and automated analysis pipelines with web-based software interfaces to enable the screening biologists to analyze the screening results effectively.

Results:

The results of these assays are used to explore and understand cancer biology in terms of druggability, functional heterogeneity and mechanism of drug response and resistance. The profiling data can be used to stratify and position the relevance of specific drugs in different diseases and has been used to identify novel clinically relevant activities of existing and investigational drugs (see e.g. Pemovska et al, Nature, 2015). This information is further utilized to establish hypotheses on drug combinations selectively targeting individual cancers and their predictive biomarkers, which can be explored in the clinic by our clinical collaborators to guide the treatment of the individual patient.

Conclusions:

In summary, we describe our platform for a functional drug sensitivity testing within our individualized cancer systems medicine program, which generates consistent biological and clinically relevant data.

Citation Format: Sergey G. Kuznetsov, Alexander Ianevski, Evgeny Kulessky, Karoliina Laamanen, Elina Lehtinen, Maria Nurmi, Swapnil Potdar, Jani Saarela, Katja Suomi, Laura Turunen, Krister Wennerberg, Päivi Tammela. Ex vivo drug sensitivity testing of primary cells for precision cancer medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2153.

Abstract 458: Precision systems medicine in acute myeloid leukemia: real-time translation of tailored therapeutic opportunities arising from ex-vivo drug sensitivity testing and molecular profiling

Acute myeloid leukemia (AML) is an aggressive disease of clonal hematopoietic progenitor cells. Here, we applied ex-vivo drug sensitivity and resistance testing on AML patient cells with 362 emerging and 153 approved cancer drugs together with genomic and transcriptomic profiling to identify and tailor therapies for patients with advanced disease. Ex-vivo testing with freshly isolated patient cells revealed cancer-specific efficacies of approved drugs in 97% of the 164 patient cases, including 47% of the cases with no actionable driver mutations. We identified 142 statistically significant associations between drug responses and somatic mutations, including increased sensitivity to JAK inhibitors in patients with NPM1 mutations. Transcriptomic profiles predicted drug responses better than genomics and helped to identify additional response markers, especially beyond mutations. For example, overexpression of HOX family genes was associated with sensitivity to JAK inhibitors in patients with NPM1 mutation. In a prospective study, we translated the functional drug response and molecular profile data to the clinic and suggested tailored therapy with targeted drugs for 26 relapsed or refractory AML patients. In an observational intervention study, acting on these recommendations resulted in a temporary complete clinical remission or leukemia-free state in 39% of the cases. In summary, we conclude that ex-vivo testing of drugs on patient AML cells i) revealed clinically actionable drug efficacies in almost all AML patients, including patients with no actionable mutations, ii) predicted cases with actionable driver mutations with no pharmacological dependency on the target, and iii) enabled real-time tailoring of therapy with 39% clinical response rate in chemorefractory advanced AML. Taken together, we believe this real-time systems medicine approach could become a powerful strategy for tailoring therapies for individual patients in the future.

Citation Format: Disha Malani, Ashwni Kumar, Bhagwan Yadav, Mika Kontro, Swapnil Potdar, Oscar Bruck, Säri Kytölä, Jani Saarela, Samuli Eldfors, Riikka Karjalainen, Muntasir M. Majumder, Imre Västrik, Pekka Ellonen, Matti Kankainen, Minna Suvela, Siv Knappila, Alun Parson, Aino Palva, Pirkko Mattila, Evgeny Kulesskiy, Laura Turunen, Karoliina Laamanen, Elina Lehtinen, Maria Nurmi, Katja Suomi, Astrid Muruimägi, Bjorn T. Gjertsen, Satu Mustjoki, Simon Anders, Maija Wolf, Tero Aittokallio, Krister Wennerberg, Caroline Heckman, Kimmo Porkka, Olli Kallioniemi. Precision systems medicine in acute myeloid leukemia: real-time translation of tailored therapeutic opportunities arising from ex-vivo drug sensitivity testing and molecular profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 458.

Abstract 2684: Drug sensitivity profiling of BT-474 breast cancer cell line for identification of novel therapies targeting HER2-positive breast cancer

Developing targeted therapy for breast cancer expressing hormone receptors such as estrogen receptor (ER) and progesterone receptor (PR) as well as human epidermal growth factor receptor 2 (HER2) is essential. However, breast cancer has high susceptibility to spread despite the targeted therapies and metastases often turn resistant to the used treatment. Therefore, new therapies are needed especially at the stage when cancer becomes resistant to hormonal therapy. The aim of the study was to investigate drug sensitivity of BT-474 breast cancer cell line and to recognize possible vulnerabilities especially in HER2+ breast cancer.

BT-474 cell line (ER+, PR+, HER2+) is originally derived from human solid, invasive ductal carcinoma of the breast. Drug sensitivity of the cell line was assessed by screening of a large compound library consisting of many clinically available and emerging anti-cancer drugs including e.g. conventional chemotherapy, metabolic modifiers, kinesin inhibitors, apoptotic modulators, immunomodulators and kinase inhibitors such as HER2, pan-HER2 and EGFR-HER2 inhibitors. A panel of 525 compounds was tested in five concentrations covering a 10.000-fold drug-relevant concentration range in 384-well format. Cells were seeded to pre-drugged plates, followed by cell viability measurements (CellTiter-Glo) after 72 hours. Maximal and minimal responses to drugs were analyzed, the EC50 values were calculated and Drug Sensitivity Score (DSS) was calculated for each drug as a measure of reduced viability. A selective DSS (sDSS) was calculated to identify the selective drug response pattern.

DSS analysis of BT-474 cell line showed sensitivity to conventional chemotherapy including paclitaxel and docetaxel and to kinase inhibitors such as EGFR and HER2 inhibitors neratinib, afatinib, mubritinib, poziotinib, dacomitinib and lapatinib with nanomolar EC50 values. Moreover, BT-474 cells showed sensitivity to PI3K and mTOR inhibitors, such as copanlisib and omipalisib, and to HSP90 and HDAC inhibitors, such as tanespimycin and abexinostat.

Screening of large compound libraries combined with DSS and sDSS analysis enables drug sensitivity profiling of BT-474 breast cancer cells for discovery of novel therapies against HER+ breast cancer. Furthermore, drug sensitivity profiling enables repurposing of existing drugs to new indications and identification of vulnerabilities in different types of cancer cells.

Citation Format: Jenni H. Mäki-Jouppila, Tiina E. Kähkönen, Mari I. Suominen, Jussi M. Halleen, Jenni Bernoulli, Jani Saarela, Katja Fagerlund. Drug sensitivity profiling of BT-474 breast cancer cell line for identification of novel therapies targeting HER2-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2684.

Abstract 3899: Discovery and clinical implementation of individualized therapies in acute myeloid leukemia based on ex vivo drug sensitivity testing and multi-omics profiling

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by multiple molecular subtypes and lack of effective targeted therapies. Here, we performed extensive molecular profiling and ex vivo drug testing with 515 approved and emerging cancer drugs on 164 AML patient samples. The aim was to i) assign individualized treatment options to advanced AML patients in real time, ii) explore drug response patterns across the molecular subtypes of AML and iii) identify opportunities to repurpose existing and emerging cancer drugs.

Bone marrow samples (n=164) from 129 consecutive AML patients and 17 healthy donors were studied from the Helsinki University Hospital and the Haukeland University Hospital, Bergen. Mononuclear cells were resuspended either in mononuclear cell medium (MCM) or stroma conditioned medium (CM) and tested for drug sensitivity and resistance as previously described (PMID: 24056683) and studied by exome and transcriptome sequencing. The study protocol allowed us to return data to the clinician for consideration of novel treatment options. For the meta-analysis of associations between drug responses and molecular and clinical parameters, Wilcoxon signed ranked test and logistic regression were applied.

Clustering of all patient samples based on ex vivo drug response patterns in both media types identified 7 distinct functional groups of AML. For example, a subgroup of samples was highly resistant to chemotherapeutics and all targeted drugs except BCL-2 inhibitors. The differences in drug responses in the two media types highlighted the importance of assay conditions for ex vivo drug testing. Strong clustering of several drugs in the same drug classes was often observed as well as clustering across different classes, for example between BET (JQ1, I-BET151, birabresib) and MEK (trametinib, cobimetinib) inhibitors. About 24 percent of the FLT3 negative AML patients manifested strong ex vivo sensitivity to glucocorticoids, highlighting a potential drug repositioning opportunity in this subset of AML patients. Overall, we identified 320 significant associations between drugs and mutated driver genes including association between NPM1 mutation and sensitivity to JAK inhibitors.

Altogether, targeted treatment opportunities were clinically tested in 25 occasions in chemorefractory AML patients. The tailored clinical therapy led to transient complete remission or leukemia free state in 36% (9/25) of these cases.

In conclusion, we discovered and clinically implemented individualized therapeutic options for AML patients, which resulted in a 36% clinical responses in a non-randomized proof-of-concept study. The associations identified between ex-vivo drug response and driver mutations provided novel drug repositioning opportunities in specific molecular subtypes.

Citation Format: Disha Malani, Ashwini Kumar, Bhagwan Yadav, Mika Kontro, Swapnil Potdar, Oscar Brück, Sari Kytölä, Jani Saarela, Samuli Eldfors, Poojitha Ojamies, Karjalainen Riikka, Muntasir Mamun Majumder, Imre Västrik, Pekka Ellonen, Matti Kankainen, Minna Suvela, Siv Knappila, Alun Parson, Aino Palva, Pirkko Mattila, Evgeny Kulesskiy1, Laura Turunen, Karoliina Laamanen, Elina Lehtinen, Piia Mikkonen, Maria Nurmi, Sanna Timonen, Astrid Murumägi, Bjorn Tore Gjersten, Satu Mustjoki, Tero Aittokallio, Krister Wennerberg, Simon Anders, Maija Wolf, Caroline Heckman, Kimmo Porkka, Olli Kallioniemi. Discovery and clinical implementation of individualized therapies in acute myeloid leukemia based on ex vivo drug sensitivity testing and multi-omics profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3899.

Abstract A151: Drug sensitivity profiling of BT-474 breast cancer cell line for identification of novel therapies against HER2-positive breast cancer

Introduction: Targeted therapy for breast cancer expressing hormone receptors such as estrogen receptor (ER) and progesterone receptor (PR), as well as human epidermal growth factor receptor (HER2), is essential. In spite of current targeted therapies, breast cancer has high susceptibility to spread and metastases often turn resistant to the used treatment. Therefore, new therapies are needed, especially when cancer becomes resistant to hormonal therapy. The aim of the study was to investigate drug sensitivity and resistance of BT-474 breast cancer cell line and to recognize possible vulnerabilities, especially in hormone therapy resistant HER2+ breast cancer. Materials and Methods: BT-474 cell line (ER+, PR+, HER2+) is originally derived from human solid, invasive ductal carcinoma of the breast. The drug sensitivity of the cell line was assessed by applying a large panel of drugs covering cancer chemotherapeutics and clinically available and emerging drugs including, e.g., conventional chemotherapy and kinase inhibitors such as HER2, pan-HER2, and EGFR-HER2 inhibitors. Altogether a panel of 525 compounds was tested in five concentrations covering a 10,000-fold drug-relevant concentration range in 384-well format. Cells were seeded to predrugged plates, followed by cell viability measurements (CellTiter-Glo) after 72 hours. Maximal and minimal responses to drugs were analyzed, the EC50 values were calculated, and Drug Sensitivity Score (DSS) was calculated for each drug as a measure of reduced viability. A selective Drug Sensitivity Score (sDSS) was calculated to identify the selective drug response pattern. Results: DSS analysis of BT-474 cell line showed sensitivity to conventional chemotherapy including paclitaxel and docetaxel and to kinase inhibitors such as EGFR inhibitors neratinib and afatinib. In the absence of supplemented estradiol, the cell line was not sensitive to hormonal therapies, including antiestrogens and selective estrogen receptor modulators. However, BT-474 cells were sensitive to HER2, pan-HER2, and EGFR-HER2 inhibitors including mubritinib, poziotinib, dacomitinib, and lapatinib with EC50 range from 2 to 98 nM. The BT-474 cells also showed sensitivity against PI3K and mTOR inhibitors, such as copanlisib and omipalisib. Conclusions: Screening of large compound libraries combined with DSS and sDSS analysis enables drug sensitivity profiling of HER2+ BT-474 breast cancer cells for identification of novel anticancer compounds against breast cancer, especially for the hormonal-resistant stage of the disease. Moreover, the assay enables repurposing of existing drugs to new indications, identification of vulnerabilities in different types of cancer cells, and functional investigation of cellular pathways behind drug sensitivity or resistance.

Citation Format: Jenni Mäki-Jouppila, Tiina Kähkönen, Mari I. Suominen, Katja M. Fagerlund, Jussi M. Halleen, Jani Saarela, Jenni Bernoulli. Drug sensitivity profiling of BT-474 breast cancer cell line for identification of novel therapies against HER2-positive breast cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A151.

Methods for High-throughput Drug Combination Screening and Synergy Scoring

Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

Abstract 3838: Drug sensitivity profile of 5TGM1 murine multiple myeloma cell line emphasizes the translational potential of the syngeneic in vivo model

Multiple myeloma (MM) is the second most common hematologic malignancy that originates from B-cells (plasma cells) and causes 2% of cancer-related deaths. Symptoms of MM include bone pain caused by multiple osteolytic lesions, pathologic fractures, and hypercalcemia. Typically, MM has a low growth fraction and it is highly dependent on the microenvironment. These properties have made it hard to target by conventional chemotherapy, but could now be exploited by novel stroma-targeting drugs and immunotherapy. These new approaches underline the need for well characterized models with functional immune system and appropriate tumor microenvironment. To gain additional information supporting the use of the syngeneic 5TGM1 murine multiple myeloma model in drug development, we tested drug sensitivity of 5TGM1 cells by screening an extensive panel of drugs.

The compound library consisting of 460 compounds included conventional chemotherapy, kinase inhibitors, metabolic modifiers, rapalogs, differentiating/epigenetic modifiers, kinesin inhibitors, apoptotic modulators, NSAIDs, hormone therapy, immunomodulators and HSP inhibitors. The compounds were tested in five concentrations covering a 10.000-fold drug-relevant concentration range in 384-well format. Cells were seeded to plates with a compound library, followed by cell viability measurements (CellTiter-Glo) after 72 hours. Maximal and minimal responses to drugs were analyzed, and the EC50 values were calculated. Drug Sensitivity Score (DSS) was calculated for each drug as a measure of reduced viability.

According to DSS analysis, 5TGM1 cells showed sensitivity to conventional chemotherapy, such as antimitotic drugs, and kinase inhibitors, such as MEK1/2 inhibitors. In addition, the cells showed particular sensitivity to several HSP90 inhibitors currently in phase I/II clinical development for MM. Lenalidomide and pomalidomide, efficient in treating multiple myeloma in humans, both gave low DSS value indicating that 5TGM1 cells are not sensitive to these drugs, which is expected because they do not bind to murine form of the target cereblon. In contrast, 5TGM1 cells were highly sensitive to the proteasome inhibitor bortezomib (DSS 32.2), which is currently in clinical use.

In conclusion, the murine 5TGM1 cells show sensitivity to various MM drugs used in the clinic and under development. Evaluating the effects of the microenvironment on the growth and drug sensitivity of 5TGM1 cells in vitro and in vivo will be essential. Furthermore, the cell-based compound screening combined with DSS analysis provides a possibility to profile cellular responses to an extensive collection of anti-cancer compounds enabling identification of vulnerabilities in cancer cells and functional investigation of cellular pathways behind drug sensitivity or resistance.

Citation Format: Jenni Mäki-Jouppila, Jenni Bernoulli, Mari I. Suominen, Tiina Kähkönen, Jussi M. Halleen, Sanna Timonen, Elina Huovari, Katja Suomi, Swapnil Potdar, Maria Nurmi, Päivi Östling, Jani Saarela, Katja M. Fagerlund. Drug sensitivity profile of 5TGM1 murine multiple myeloma cell line emphasizes the translational potential of the syngeneic in vivo model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3838. doi:10.1158/1538-7445.AM2017-3838

Abstract 4207: Selective drug sensitivity score (DSS) for indolent and aggressive prostate cancer cell lines

Prostate cancer (PC) is the most common malignancy in men and the second leading cause of cancer-related deaths. The majority of the PCs are classified as adenocarcinomas characterized by the expression of androgen receptor (AR) and prostate-specific antigen (PSA). Two of the most commonly used cell lines are LNCaP and PC-3 cells, derived from lymph node and bone metastases, respectively. Also VCaP cells, derived from vertebral metastases, are widely used in prostate cancer research. It has been well established that LNCaP and VCaP cells represent the conventional indolent form of PC expressing AR and PSA and are androgen-dependent. PC-3 cells, on the other hand, do not express AR and PSA, are androgen-independent, and represent the highly aggressive form.

The drug sensitivity of the cell lines was assessed by applying a large panel of drugs covering cancer chemotherapeutics and clinically available and emerging drugs including conventional chemotherapy, kinase inhibitors, metabolic modifiers, rapalogs, differentiating/epigenetic modifiers, kinesin inhibitors, apoptotic modulators, NSAIDs, hormone therapy, immunomodulators and HSP inhibitors. A panel of 460 compounds was tested in five concentrations covering a 10.000-fold drug-relevant concentration range in 384-well format. Cells were seeded to pre-drugged plates, followed by cell viability measurements (CellTiter-Glo) after 72 hours. Maximal and minimal responses to drugs were analyzed, the EC50 values were calculated and Drug Sensitivity Score (DSS) was calculated for each drug as a measure of reduced viability. A selective Drug Sensitivity Score (sDSS) was calculated to identify the selective drug response pattern of each three cancer cell lines.

As expected, the results indicate that LNCaP and VCaP cells in general were more sensitive to drugs of different categories than PC-3 cells. According to DSS analysis, all three cell lines showed sensitivity to conventional chemotherapy and kinase inhibitors. However, PC-3 cells were more sensitive to kinase inhibitors than conventional chemotherapy. Determining sDSS revealed specific sensitivities of each cell line. LNCaP cells were sensitive to kinase inhibitors, such as mTOR and AKT inhibitors. Also VCaP cells showed selective sensitivity to kinase inhibitors, especially Aurora kinase and IGF1R inhibitors. In addition to kinase inhibitors, VCaP cells were selectively sensitive to HDAC inhibitors. Furthermore, PC-3 cells were sensitive to e.g. CDK inhibitors.

We conclude that the cell-based compound screening combined with DSS and sDSS analysis provides a possibility to profile cellular responses to an extensive collection of anti-cancer compounds enabling repurposing of existing drugs to new indications, identification of vulnerabilities in different types of cancer cells and functional investigation of cellular pathways behind drug sensitivity or resistance.

Citation Format: Jenni Mäki-Jouppila, Jenni Bernoulli, Johanna Tuomela, Mari I. Suominen, Jussi M. Halleen, Sanna Timonen, Elina Huovari, Katja Suomi, Swapnil Potdar, Päivi Östling, Jani Saarela, Katja M. Fagerlund. Selective drug sensitivity score (DSS) for indolent and aggressive prostate cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4207. doi:10.1158/1538-7445.AM2017-4207

TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer

TP53 overexpression is indicative of somatic TP53 mutations and associates with aggressive tumors and poor prognosis in breast cancer. We utilized a two-stage SNP association study to detect variants associated with breast cancer survival in a TP53-dependent manner. Initially, a genome-wide study (n = 575 cases) was conducted to discover candidate SNPs for genotyping and validation in the Breast Cancer Association Consortium (BCAC). The SNPs were then tested for interaction with tumor TP53 status (n = 4,610) and anthracycline treatment (n = 17,828). For SNPs interacting with anthracycline treatment, siRNA knockdown experiments were carried out to validate candidate genes.In the test for interaction between SNP genotype and TP53 status, we identified one locus, represented by rs10916264 (p(interaction) = 3.44 × 10-5; FDR-adjusted p = 0.0011) in estrogen receptor (ER) positive cases. The rs10916264 AA genotype associated with worse survival among cases with ER-positive, TP53-positive tumors (hazard ratio [HR] 2.36, 95% confidence interval [C.I] 1.45 - 3.82). This is a cis-eQTL locus for FBXO28 and TP53BP2; expression levels of these genes were associated with patient survival specifically in ER-positive, TP53-mutated tumors. Additionally, the SNP rs798755 was associated with survival in interaction with anthracycline treatment (p(interaction) = 9.57 × 10-5, FDR-adjusted p = 0.0130). RNAi-based depletion of a predicted regulatory target gene, FAM53A, indicated that this gene can modulate doxorubicin sensitivity in breast cancer cell lines.If confirmed in independent data sets, these results may be of clinical relevance in the development of prognostic and predictive marker panels for breast cancer.

BRCA1-deficient breast cancer cell lines are resistant to MEK inhibitors and show distinct sensitivities to 6-thioguanine

Germ-line or somatic inactivation of BRCA1 is a defining feature for a portion of human breast cancers. Here we evaluated the anti-proliferative activity of 198 FDA-approved and experimental drugs against four BRCA1-mutant (HCC1937, MDA-MB-436, SUM1315MO2, and SUM149PT) and four BRCA1-wild-type (MDA-MB-231, SUM229PE, MCF10A, and MCF7) breast cancer cell lines. We found that all BRCA1-mutant cell lines were insensitive to inhibitors of mitogen-activated protein kinase kinase 1 and 2 (MEK1/2) Selumetinib and Pimasertib in contrast to BRCA1-wildtype control cell lines. However, unexpectedly, only two BRCA1-mutant cell lines, HCC1937 and MDA-MB-436, were hypersensitive to a nucleotide analogue 6-thioguanine (6-TG). SUM149PT cells readily formed radiation-induced RAD51-positive nuclear foci indicating a functional homologous recombination, which may explain their resistance to 6-TG. However, the reason underlying 6-TG resistance of SUM1315MO2 cells remains unclear. Our data reveal a remarkable heterogeneity among BRCA1-mutant cell lines and provide a reference for future studies.

Precision Cancer Medicine in the Acoustic Dispensing Era: Ex Vivo Primary Cell Drug Sensitivity Testing

Cancer therapy is increasingly becoming individualized, but there are also big gaps between the molecular knowledge of individual cancers we can generate today and what can be applied in the clinic. In an attempt to bridge this knowledge gap between cancer genetic and molecular profiling and clinically useful information, an individualized systems medicine program has been established at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, and the Helsinki University Hospital. Central to this program is drug sensitivity and resistance testing (DSRT), in which responses of primary cancer cells to a comprehensive clinical oncology and signal transduction drug collection are monitored. The drug sensitivity information is used with molecular profiling to establish hypotheses on individual cancer-selective targeting drug combinations and their predictive biomarkers, which can be explored in the clinic. Here, we describe how acoustic droplet ejection is enabling DSRT in our cancer individualized systems medicine program to (1) generate consistent but configurable assay-ready plates and determine how this affects data quality, (2) flexibly prepare drug combination testing plates, (3) dispense reagents and cells to the assay plates, and (4) perform ultra-miniaturized follow-up assays on the cells from DSRT plates.

Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data

High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection.

Discovery of MINC1, a GTPase-activating protein small molecule inhibitor, targeting MgcRacGAP

The Rho family of Ras superfamily small GTPases regulates a broad range of biological processes such as migration, differentiation, cell growth and cell survival. Therefore, the availability of small molecule modulators as tool compounds could greatly enhance research on these proteins and their biological function. To this end, we designed a biochemical, high throughput screening assay with complementary follow-up assays to identify small molecule compounds inhibiting MgcRacGAP, a Rho family GTPase activating protein involved in cytokinesis and transcriptionally upregulated in many cancers. We first performed an in-house screen of 20,480 compounds, and later we tested the assay against 342,046 compounds from the NIH Molecular Libraries Small Molecule Repository. Primary screening hit rates were about 1% with the majority of those affecting the primary readout, an enzyme-coupled GDP detection assay. After orthogonal and counter screens, we identified two hits with high selectivity towards MgcRacGAP, compared with other RhoGAPs, and potencies in the low micromolar range. The most promising hit, termed MINC1, was then examined with cell-based testing where it was observed to induce an increased rate of cytokinetic failure and multinucleation in addition to other cell division defects, suggesting that it may act as an MgcRacGAP inhibitor also in cells.

Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles

Chemical perturbation screens offer the possibility to identify actionable sets of cancer-specific vulnerabilities. However, most inhibitors of kinases or other cancer targets result in polypharmacological effects, which complicate the identification of target dependencies directly from the drug-response phenotypes. In this study, we developed a chemical systems biology approach that integrates comprehensive drug sensitivity and selectivity profiling to provide functional insights into both single and multi-target oncogenic signal addictions. When applied to 21 breast cancer cell lines, perturbed with 40 kinase inhibitors, the subtype-specific addiction patterns clustered in agreement with patient-derived subtypes, while showing considerable variability between the heterogeneous breast cancers. Experimental validation of the top predictions revealed a number of co-dependencies between kinase targets that led to unexpected synergistic combinations between their inhibitors, such as dasatinib and axitinib in the triple-negative basal-like HCC1937 cell line.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

Systematic review of genome-wide expression studies in multiple sclerosis

Background Although recent genome-wide association studies have identified several genetic variants contributing to the complex aetiology of multiple sclerosis (MS), expression and functional studies are required to further understand its molecular basis. Objectives To identify genes and pathways with differential expression in MS. Design The authors conducted a systematic review of seven microarray studies, in which expression in immune cells was compared between MS patients and controls. These studies include a previously unpublished study, which is described here in detail. Results and conclusion Although in general the overlap between studies was poor, 229 genes were found to be differentially expressed in MS in at least two studies, of which 11 were in three studies and HSPA1A in four studies. After excluding the authors' unpublished experiment which may have been affected by certain confounding factors and inclusion of treated subjects, 135 genes were identified in at least two studies. The differentially expressed genes were significantly associated with several immunological pathways, including interleukin (IL)-4, IL-6, IL-17 and glucocorticoid receptor signalling pathways. 15 of the 229 loci have shown some association with MS in published genome-wide association studies (p<0.0001), including three loci with confirmed MS risk variants.

Papermill industrial waste as a sustainable source for high efficiency absorbent production

Papermill sludge (PMS) is generated during the wastewater treatment process of paper production. Its handling and disposal techniques are of great concern for the environment. It can be landfilled as a waste, or it can be recycled and converted into useful products of high value. It has a very promising application as an absorbing agent for the cleaning of water surfaces polluted with hydrophobic substances (vegetable, synthetic and mineral oils, animal fats, fuels, organic chemicals and even coal dust). Here, we present the pretreatment procedure (hydrophobation, mechanical and thermal treatments) of PMS that produces a lightweight absorbent material (HAWSC - high efficiency absorbent for water surface cleaning), which floats on the water surface and binds hydrophobic pollutants with considerably higher efficiency than commercially available mineral and synthetic absorbents. After its application, it can be incinerated, due to its high caloric value, to produce energy. The incineration residues can then be formed into granules that can be used as an efficient absorbent for fluids spilled onto solid surfaces.

Avian phospholipid transfer protein causes HDL conversion without affecting cholesterol efflux from macrophages

Circulatory phospholipid transfer protein (PLTP) has two major functions: 1) transfer of phospholipids towards HDL particles; and 2) modulation of HDL size and composition via the HDL conversion process. In the laying hen (Gallus gallus), the massive oocyte-targeted lipid flow is achieved through the concerted actions of lipases, lipid transfer proteins, and relatives of the LDL receptor family. The aim of the study was to gain insights into the structure and functions of chicken PLTP. The results demonstrate that PLTP is highly conserved from chicken to mammals, as (i) chicken PLTP is associated with plasma HDL; (ii) it clearly possesses phospholipid transfer activity; (iii) it is inactivated at +58 degrees C; and (iv) it mediates conversion of avian and human HDL into small prebeta-mobile HDL and large fused alpha-mobile HDL particles. Our data show that HDL from different chicken models is similar in chemical and physical properties to that of man based on PLTP activity, cholesterol efflux, and HDL conversion assays. In contrast to mammals, PLTP-facilitated HDL remodeling did not enhance cholesterol efflux efficiency of chicken HDL particles.