Quantitative online survey of self-perceived knowledge and knowledge gaps of medicines research and development among Finnish general public

Objectives This study explored self-reported knowledge and interest to learn more about medicines research, development and health technology assessment among Finnish general public. It also aimed to define possible knowledge gaps and needs for public education regarding these topics. Design Online survey with 503 participants. The questionnaire was originally developed as a part of the Needs Assessment Work Package of the European Patients' Academy on Therapeutic Innovation Project. The survey was carried out in Finland in 2019. Methods The survey was conducted as an online survey by Kantar TNS Gallup Forum online panel. The data were analysed by using the freely available programming language R. Relationships between the demographic characteristics (such as age, gender and education level) of respondents and their knowledge or interest in medicines research and development were determined using Pearson's chi(2) tests. Statistically significant responses of demographic characteristics in the respondents' knowledge or interest in medicines research were determined by logistic regression. Results Of the 503 respondents (age 16-64) only 12% reported having good or very good knowledge of medicines research and development in general. Regarding health technology assessment, pharmacoeconomics and regulation, the percentage of respondents reporting good or very good knowledge was as low as 8%. Respondents were most interested in learning more about predictive and personalised medicine (47%) and least interested in medicines regulation (30%) and pharmacoeconomics (31%). Conclusions Self-reported knowledge about medicines research and development and health technology assessment appears to be very low in Finland. Patient and public participation is recognised as an important and essential element in up-to-date medical research and assessment of new treatments. In order to participate as an active and equal partner in these processes, the public needs more information and education in these topics.Peer reviewe

Prognostic significance of esterase gene expression in multiple myeloma

Background Esterase enzymes differ in substrate specificity and biological function and may display dysregulated expression in cancer. This study evaluated the biological significance of esterase expression in multiple myeloma (MM). Methods For gene expression profiling and evaluation of genomic variants in the Institute for Molecular Medicine Finland (FIMM) cohort, bone marrow aspirates were obtained from patients with newly diagnosed MM (NDMM) or relapsed/refractory MM (RRMM). CD138+ plasma cells were enriched and used for RNA sequencing and analysis, and to evaluate genomic variation. The Multiple Myeloma Research Foundation (MMRF) Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass) dataset was used for validation of the findings from FIMM. Results MM patients (NDMM, n = 56; RRMM, n = 78) provided 171 bone marrow aspirates (NDMM, n = 56; RRMM, n = 115). Specific esterases exhibited relatively high or low expression in MM, and expression of specific esterases (UCHL5, SIAE, ESD, PAFAH1B3, PNPLA4 and PON1) was significantly altered on progression from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, SIAE and USP4, and low expression of PCED1B, were identified as poor prognostic markers (P <0.05). The MMRF CoMMpass dataset provided validation that higher expression of PAFAH1B3 and SIAE, and lower expression of PCED1B, were associated with poor prognosis. Conclusions Esterase gene expression levels change as patients progress from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, USP4 and SIAE, and low expression of PCED1B, are poor prognostic markers in MM, suggesting a role for these esterases in myeloma biology.Peer reviewe

Drug combination sensitivity scoring facilitates the discovery of synergistic and efficacious drug combinations in cancer

High-throughput drug screening has facilitated the discovery of drug combinations in cancer. Many existing studies adopted a full matrix design, aiming for the characterization of drug pair effects for cancer cells. However, the full matrix design may be suboptimal as it requires a drug pair to be combined at multiple concentrations in a full factorial manner. Furthermore, many of the computational tools assess only the synergy but not the sensitivity of drug combinations, which might lead to false positive discoveries. We proposed a novel cross design to enable a more cost-effective and simultaneous testing of drug combination sensitivity and synergy. We developed a drug combination sensitivity score (CSS) to determine the sensitivity of a drug pair, and showed that the CSS is highly reproducible between the replicates and thus supported its usage as a robust metric. We further showed that CSS can be predicted using machine learning approaches which determined the top pharmaco-features to cluster cancer cell lines based on their drug combination sensitivity profiles. To assess the degree of drug interactions using the cross design, we developed an S synergy score based on the difference between the drug combination and the single drug dose-response curves. We showed that the S score is able to detect true synergistic and antagonistic drug combinations at an accuracy level comparable to that using the full matrix design. Taken together, we showed that the cross design coupled with the CSS sensitivity and S synergy scoring methods may provide a robust and accurate characterization of both drug combination sensitivity and synergy levels, with minimal experimental materials required. Our experimental-computational approach could be utilized as an efficient pipeline for improving the discovery rate in high-throughput drug combination screening, particularly for primary patient samples which are difficult to obtain.Peer reviewe

Perinnöllinen sairastumisalttius kiinnostaa kansalaisia

Vertaisarvioitu. English summaryJOHDANTO : Selvitimme kansalaisten asenteita ja odotuksia yksilön perimästä saatavan tiedon, genomitiedon, keräämisestä ja käytöstä lääketieteellisiin tutkimustarkoituksiin. MENETELMÄT : Valtakunnallinen kyselytutkimus toteutettiin tammikuussa 2019. TULOKSET : Kansalaiset suhtautuvat genomitiedon keräämiseen ja käyttöön myönteisesti ja haluaisivat tietää terveydentilaansa mahdollisesti vaikuttavista perinnöllisistä alttiuksista. Erityisesti naiset olisivat valmiita tekemään saamansa tiedon perusteella myös elintapamuutoksia. PÄÄTELMÄT : Tutkimus vahvistaa käsitystä siitä, että suomalaiset ovat tutkimusmyönteisiä ja valmiita luovuttamaan näytteensä biopankkiin. Toisaalta useat kyselytutkimuksen vastaajista eivät osanneet sanoa kantaansa heille esitettyihin kysymyksiin, mikä viittaa osaltaan siihen, että kansalaiset kaipaisivat lisää tietoa sekä genomitiedon käytöstä että siihen liittyvistä ongelmista ja mahdollisuuksista.Peer reviewe

Identification of precision treatment strategies for relapsed/refractory multiple myeloma by functional drug sensitivity testing

Novel agents have increased survival of multiple myeloma (MM) patients, however high-risk and relapsed/refractory patients remain challenging to treat and their outcome is poor. To identify novel therapies and aid treatment selection for MM, we assessed the ex vivo sensitivity of 50 MM patient samples to 308 approved and investigational drugs. With the results we i) classified patients based on their ex vivo drug response profile; ii) identified and matched potential drug candidates to recurrent cytogenetic alterations; and iii) correlated ex vivo drug sensitivity to patient outcome. Based on their drug sensitivity profiles, MM patients were stratified into four distinct subgroups with varied survival outcomes. Patients with progressive disease and poor survival clustered in a drug response group exhibiting high sensitivity to signal transduction inhibitors. Del(17p) positive samples were resistant to most drugs tested with the exception of histone deacetylase and BCL2 inhibitors. Samples positive for t(4; 14) were highly sensitive to immunomodulatory drugs, proteasome inhibitors and several targeted drugs. Three patients treated based on the ex vivo results showed good response to the selected treatments. Our results demonstrate that ex vivo drug testing may potentially be applied to optimize treatment selection and achieve therapeutic benefit for relapsed/refractory MM.Peer reviewe

S100 Calcium Binding Protein Family Members Associate With Poor Patient Outcome and Response to Proteasome Inhibition in Multiple Myeloma

Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients’ survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.Peer reviewe

HOX gene expression predicts response to BCL-2 inhibition in acute myeloid leukemia

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Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies

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