Exhaustive in vitro evaluation of the 9-drug cocktail CUSP9 for treatment of glioblastoma.

The CUSP9 protocol is a polypharmaceutical strategy aiming at addressing the complexity of glioblastoma by targeting multiple pathways. Although the rationale for this 9-drug cocktail is well-supported by theoretical and in vitro data, its effectiveness compared to its 511 possible subsets has not been comprehensively evaluated. Such an analysis could reveal if fewer drugs could achieve similar or better outcomes. We conducted an exhaustive in vitro evaluation of the CUSP9 protocol using COMBImageDL, our specialized framework for testing higher-order drug combinations. This study assessed all 511 subsets of the CUSP9v3 protocol, in combination with temozolomide, on two clonal cultures of glioma-initiating cells derived from patient samples. The drugs were used at fixed, clinically relevant concentrations, and the experiment was performed in quadruplicate with endpoint cell viability and live-cell imaging readouts. Our results showed that several lower-order drug combinations produced effects equivalent to the full CUSP9 cocktail, indicating potential for simplified regimens in personalized therapy. Further validation through in vivo and precision medicine testing is required. Notably, a subset of four drugs (auranofin, disulfiram, itraconazole, sertraline) was particularly effective, reducing cell growth, altering cell morphology, increasing apoptotic-like cells within 4-28 h, and significantly decreasing cell viability after 68 h compared to untreated cells. This study underscores the importance and feasibility of comprehensive in vitro evaluations of complex drug combinations on patient-derived tumor cells, serving as a critical step toward (pre-)clinical development.

Comprehensive approach to national tire wear emissions: Challenges and implications.

The use of vehicle tires has been identified as a major source of microplastics in the environment and an increasing source of urban particulate air pollution. In light of increasing traffic volumes, increasingly heavier and more powerful vehicles due to trends and electrification, and the lack of tire wear regulation, methods to estimate and monitor changes in national emissions are needed as input for environmental impact assessments. Emission estimations of tire wear are made either based on the mileage approach or the sales approach. This study aims to investigate if and how the mileage approach can be improved by using emission factors for passenger cars and LDVs based on our own measurements and emission factors from the literature for HDVs and buses. An approach with emission factor adjustments based on weight and number of tires in combination with highly detailed mileage data has been evaluated. Sales approach calculations have been used to validate the method. A secondary aim was to use the new mileage approach framework to calculate the national tire wear emissions for Sweden. These calculations resulted in slightly lower total emissions than previous estimations provide, but with higher emissions for passenger cars and light-duty vehicles, and lower emissions for heavy-duty vehicles and motorcycles. Passenger cars constitute more than half of the total emissions. It is concluded that even though the framework offers greater detail, thus increasing the possibilities to adjust for changes in emission factors and mileages in specific vehicle categories, the challenges posed by such factors as the lack of measured emission factors for heavy-duty vehicles and uncertainties regarding the quality of mileage statistics makes the estimations uncertain. Important future suggestions for research include establishing reliable emission factors, especially for heavy-duty vehicles, and initiating research to better understand how climate, road networks, surface properties, and vehicle fleet characteristics affect emission factors.

Airway contraction and cytokine release in isolated rat lungs induced by wear particles from the road and tire interface and road vehicle brakes.

The dominant road traffic particle sources are wear particles from the road and tire interface, and from vehicle brake pads. The aim of this work was to investigate the effect of road and brake wear particles on pulmonary function and biomarkers in isolated perfused rat lungs. Particles were sampled from the studded tire wear of three road pavements containing different rock materials in a road simulator; and from the wear of two brake pad materials using a pin-on-disk machine. Isolated rat lungs inhaled the coarse and fine fractions of the sampled particles resulting in an estimated total particle lung dose of 50 µg. The tidal volume (TV) was measured during the particle exposure and the following 50 min. Perfusate and BALF were analyzed for the cytokines TNF, CXCL1 and CCL3. The TV of lungs exposed to rock materials was significantly reduced after 25 min of exposure compared to the controls, for quartzite already after 4 min. The particles of the heavy-duty brake pads had no effect on the TV. Brake particles resulted in a significant elevation of CXCL1 in the perfusate. Brake particles showed significant elevations of all three measured cytokines, and quartzite showed a significant elevation of TNF in BALF. The study shows that the toxic effect on lungs exposed to airborne particles can be investigated using measurements of tidal volume. Furthermore, the study shows that the choice of rock material in road pavements has the potential to affect the toxicity of road wear PM10.

Upper bounds on focusing efficiency.

Upper bounds on the focusing efficiency of aperture fields and lens systems are formulated using integral equation representations of Maxwell's equations and Lagrangian duality. Two forms of focusing efficiency are considered based on lens exit plane fields and optimal polarization currents within lens design regions of prescribed shape and available materials. Bounds are compared against the performance of classical prescriptions of ideal lens aperture fields, hyperbolic lens designs, and lenses produced by inverse design. Results demonstrate that, without regularization, focusing efficiency based solely on lens exit plane fields is unbounded, similar to the problem of unbounded antenna directivity. Additionally, results considering extruded two-dimensional dielectric geometries driven by out-of-plane electric fields for the calculation of bounds and inverse design demonstrate that aperture fields based on time-reversal do not necessarily yield optimal lens focusing efficiency, particularly in the case of near-field (high numerical aperture) focusing.

Concentrations of tire wear microplastics and other traffic-derived non-exhaust particles in the road environment.

Tire wear particles (TWP) are assumed to be one of the major sources of microplastic pollution to the environment. However, many of the previously published studies are based on theoretical estimations rather than field measurements. To increase the knowledge regarding actual environmental concentrations, samples were collected and analyzed from different matrices in a rural highway environment to characterize and quantify TWP and other traffic-derived non-exhaust particles. The sampled matrices included road dust (from kerb and in-between wheeltracks), runoff (water and sediment), and air. In addition, airborne deposition was determined in a transect with increasing distance from the road. Two sieved size fractions (2-20 µm and 20-125 µm) were analyzed by automated Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX) single particle analysis and classified with a machine learning algorithm into the following subclasses: TWP, bitumen wear particles (BiWP), road markings, reflecting glass beads, metals, minerals, and biogenic/organic particles. The relative particle number concentrations (%) showed that the runoff contained the highest proportion of TWP (up to 38 %). The share of TWP in kerb samples tended to be higher than BiWP. However, a seasonal increase of BiWP was observed in coarse (20-125 µm) kerb samples during winter, most likely reflecting studded tire use. The concentration of the particle subclasses within airborne PM80-1 decreases with increasing distance from the road, evidencing road traffic as the main emission source. The results confirm that road dust and the surrounding environment contain traffic-derived microplastics in both size fractions. The finer fraction (2-20 µm) dominated (by mass, volume, and number) in all sample matrices. These particles have a high potential to be transported in water and air far away from the source and can contribute to the inhalable particle fraction (PM10) in air. This highlights the importance of including also finer particle fractions in future investigations.

A Review of Road Traffic-Derived Non-Exhaust Particles: Emissions, Physicochemical Characteristics, Health Risks, and Mitigation Measures.

Implementation of regulatory standards has reduced exhaust emissions of particulate matter from road traffic substantially in the developed world. However, nonexhaust particle emissions arising from the wear of brakes, tires, and the road surface, together with the resuspension of road dust, are unregulated and exceed exhaust emissions in many jurisdictions. While knowledge of the sources of nonexhaust particles is fairly good, source-specific measurements of airborne concentrations are few, and studies of the toxicology and epidemiology do not give a clear picture of the health risk posed. This paper reviews the current state of knowledge, with a strong focus on health-related research, highlighting areas where further research is an essential prerequisite for developing focused policy responses to nonexhaust particles.

Fundamental bounds on the performance of monochromatic passive cloaks.

Fundamental bounds on the performance of monochromatic scattering-cancellation and field-zeroing cloaks made of prescribed linear passive materials occupying a predefined design region are formulated by projecting field quantities onto a sub-sectional basis and applying quadratically constrained quadratic programming. Formulations are numerically tested revealing key physical trends as well as advantages and disadvantages between the two classes of cloaks. Results show that the use of low-loss materials with high dielectric contrast affords the highest potential for effective cloaking.

Traffic-related microplastic particles, metals, and organic pollutants in an urban area under reconstruction.

In urban environments, particularly areas under reconstruction, metals, organic pollutants (OP), and microplastics (MP), are released in large amounts due to heavy traffic. Road runoff, a major transport route for urban pollutants, contributes significantly to a deteriorated water quality in receiving waters. This study was conducted in Gothenburg, Sweden, and is unique because it simultaneously investigates the occurrence of OP, metals, and MP on roads and in stormwater from an urban area under reconstruction. Correlations between the various pollutants were also explored. The study was carried out by collecting washwater and sweepsand generated from street sweeping, road surface sampling, and flow-proportional stormwater sampling on several occasions. The liquid and solid samples were analyzed for metals, polycyclic aromatic hydrocarbons (PAH), oxy-PAH, aliphatics, aromatics, phthalates, and MP. The occurrence of OP was also analyzed with a non-target screening method of selected samples. Microplastics, i.e. plastic fragments/fibers, paint fragments, tire wear particles (TWP) and bitumen, were analyzed with a method based on density separation with sodium iodide and identification with a stereo microscope, melt-tests, and tactile identification. MP concentrations amounted to 1500 particles/L in stormwater, 51,000 particles/L in washwater, and 2.6 × 106 particles/kg dw in sweepsand. In stormwater, washwater and sweepsand, MP ≥20 µm were found to be dominated by TWP (38%, 83% and 78%, respectively). The results confirm traffic as an important source to MP, OP, and metal emissions. Concentrations exceeding water and sediment quality guidelines for metals (e.g. Cu and Zn), PAH, phthalates, and aliphatic hydrocarbons in the C16-C35 fraction were found in most samples. The results show that the street sweeper collects large amounts of polluted materials and thereby prevents further spread of the pollutants to the receiving stormwater.

Trade-offs in absorption and scattering by nanophotonic structures.

Trade-offs between absorption and scattering cross sections of lossy obstacles confined to an arbitrarily shaped volume are formulated as a multi-objective optimization problem solvable by Lagrangian-dual methods. Solutions to this optimization problem yield a Pareto-optimal set, the shape of which reveals the feasibility of achieving simultaneously extremal absorption and scattering. Two forms of the trade-off problems are considered involving both pre-assigned loss and reactive material parameters. Numerical comparisons between the derived multi-objective bounds and several classes of realized structures are made. Additionally, low-frequency (electrically small, long wavelength) limits are examined for certain special cases.

Occurrence of tire and bitumen wear microplastics on urban streets and in sweepsand and washwater.

Tire and road wear particles have been identified as a potential major source of microplastics in the environment. However, more knowledge of the emissions and their further fate in the environment is needed, and the effectiveness and benefits of potential measures must be investigated to support future risk management efforts. Here the concentrations of tire and bitumen microplastic particles (TBMP) on roads and in nearby in stormwater, sweepsand and washwater were measured for the first time within the same area and time period. The analysis also included plastic, paint and fiber particles. Road dust was sampled on the road surface using a wet dust sampler, before and after street sweeping on two occasions. On each of these occasions, and several occasions during a four-month period with frequent street sweeping, sweepsand and washwater, as well as flow-weighted sampling of stormwater, were collected. TBMP concentrations were operationally defined, using density separation for some samples, followed by analysis by stereo microscopy. Sodium iodide (NaI) was found to be effective for density separation of TBMP. The largest proportion of anthropogenic microplastics detected consisted of tire tread wear and bitumen. The number of TBMP ≥100 µm in the WDS samples was up to 2561 particles/L. Sweepsand and washwater contained high amounts of TBMP ≥100 µm, up to 2170 particles/kg dw and 4500 particles/L, respectively. The results show that the sweeper collects considerable amounts of TBMP, and thus weekly sweeping might prevent further transport of TBMP to the receiving stormwater. In stormwater the number of particles ≥100 µm was up to 3 particles/L and ≥ 20 µm was up to 5900 particles/L showing the importance of analysing smaller microparticle sizes than 100 µm in all samples in future studies. This study also confirms that there is a substantial volume of TBMP generated from traffic that enters the environment.

COMBSecretomics: A pragmatic methodological framework for higher-order drug combination analysis using secretomics.

Multi drug treatments are increasingly used in the clinic to combat complex and co-occurring diseases. However, most drug combination discovery efforts today are mainly focused on anticancer therapy and rarely examine the potential of using more than two drugs simultaneously. Moreover, there is currently no reported methodology for performing second- and higher-order drug combination analysis of secretomic patterns, meaning protein concentration profiles released by the cells. Here, we introduce COMBSecretomics (https://github.com/EffieChantzi/COMBSecretomics.git), the first pragmatic methodological framework designed to search exhaustively for second- and higher-order mixtures of candidate treatments that can modify, or even reverse malfunctioning secretomic patterns of human cells. This framework comes with two novel model-free combination analysis methods; a tailor-made generalization of the highest single agent principle and a data mining approach based on top-down hierarchical clustering. Quality control procedures to eliminate outliers and non-parametric statistics to quantify uncertainty in the results obtained are also included. COMBSecretomics is based on a standardized reproducible format and could be employed with any experimental platform that provides the required protein release data. Its practical use and functionality are demonstrated by means of a proof-of-principle pharmacological study related to cartilage degradation. COMBSecretomics is the first methodological framework reported to enable secretome-related second- and higher-order drug combination analysis. It could be used in drug discovery and development projects, clinical practice, as well as basic biological understanding of the largely unexplored changes in cell-cell communication that occurs due to disease and/or associated pharmacological treatment conditions.

A Novel Multiplex Based Platform for Osteoarthritis Drug Candidate Evaluation.

Osteoarthritis (OA) is characterized by irreversible cartilage degradation with very limited therapeutic interventions. Drug candidates targeted at prototypic players had limited success until now and systems based approaches might be necessary. Consequently, drug evaluation platforms should consider the biological complexity looking beyond well-known contributors of OA. In this study an ex vivo model of cartilage degradation, combined with measuring releases of 27 proteins, was utilized to study 9 drug candidates. After an initial single drug evaluation step the 3 most promising compounds were selected and employed in an exhaustive combinatorial experiment. The resulting most and least promising treatment candidates were selected and validated in an independent study. This included estimation of mechanical properties via finite element modelling (FEM) and quantification of cartilage degradation as glycosaminoglycan (GAG) release. The most promising candidate showed increase of Young's modulus, decrease of hydraulic permeability and decrease of GAG release. The least promising candidate exhibited the opposite behaviour. The study shows the potential of a novel drug evaluation platform in identifying treatments that might reduce cartilage degradation. It also demonstrates the promise of exhaustive combination experiments and a connection between chondrocyte responses at the molecular level with changes of biomechanical properties at the tissue level.

Organic pollutants, nano- and microparticles in street sweeping road dust and washwater.

Road areas are pollution hotspots where many metals, organic pollutants (OPs) and nano/microparticles accumulate before being transported to receiving waters. Particles on roads originate from e.g. road, tyre and vehicle wear, winter road maintenance, soil erosion, and deposition. Street sweeping has the potential to be an effective and affordable practice to reduce the occurrence of road dust, and thereby the subsequent spreading of pollutants, but there is currently little knowledge regarding its effectiveness. In this paper we investigate the potential of street sweeping to reduce the amounts of OPs and nano/microparticles reaching stormwater, in a case study sampling road dust and washwater from a street sweeping machine, road dust before and after sweeping, and stormwater. The compound groups generally found in the highest concentrations in all matrices were aliphatics C5-C35 > phthalates > aromatics C8-C35 > PAH-16. The concentrations of aliphatics C16-C35 and PAHs in washwater were extremely high at ≤ 53,000 µg/L and ≤ 120 µg/L, respectively, and the highest concentrations were found after a 3-month winter break in sweeping. In general, fewer aliphatic and aromatic petroleum hydrocarbons and PAHs were detected in road dust samples than in washwater. The relative composition of the specific PAH-16 suggests tyre wear, vehicle exhausts, brake linings, motor oils and road surface wear as possible sources. The study indicates that many of the hydrophobic compounds quantified in washwater are attached to small particles or truly dissolved. The washwater contains a wide range of small particles, including nanoparticles in sizes from just below 1 nm up to 300 nm, with nanoparticles in the size range 25-300 nm present in the highest concentrations. The results also indicated agglomeration of nanoparticles in the washwater. The street sweeping collected a large amount of fine particles and associated pollutants, leading to the conclusion that washwater from street sweeping needs to be treated before disposal.

Optical theorems and physical bounds on absorption in lossy media.

Two different versions of an optical theorem for a scattering body embedded inside a lossy background medium are derived in this paper. The corresponding fundamental upper bounds on absorption are then obtained in closed form by elementary optimization techniques. The first version is formulated in terms of polarization currents (or equivalent currents) inside the scatterer and generalizes previous results given for a lossless medium. The corresponding bound is referred to here as a variational bound and is valid for an arbitrary geometry with a given material property. The second version is formulated in terms of the T-matrix parameters of an arbitrary linear scatterer circumscribed by a spherical volume and gives a new fundamental upper bound on the total absorption of an inclusion with an arbitrary material property (including general bianisotropic materials). The two bounds are fundamentally different as they are based on different assumptions regarding the structure and the material property. Numerical examples including homogeneous and layered (core-shell) spheres are given to demonstrate that the two bounds provide complimentary information in a given scattering problem.

An ex vivo tissue model of cartilage degradation suggests that cartilage state can be determined from secreted key protein patterns.

The pathophysiology of osteoarthritis (OA) involves dysregulation of anabolic and catabolic processes associated with a broad panel of proteins that ultimately lead to cartilage degradation. An increased understanding about these protein interactions with systematic in vitro analyses may give new ideas regarding candidates for treatment of OA related cartilage degradation. Therefore, an ex vivo tissue model of cartilage degradation was established by culturing tissue explants with bacterial collagenase II. Responses of healthy and degrading cartilage were analyzed through protein abundance in tissue supernatant with a 26-multiplex protein profiling assay, after exposing the samples to a panel of 55 protein stimulations present in synovial joints of OA patients. Multivariate data analysis including exhaustive pairwise variable subset selection identified the most outstanding changes in measured protein secretions. MMP9 response to stimulation was outstandingly low in degrading cartilage and there were several protein pairs like IFNG and MMP9 that can be used for successful discrimination between degrading and healthy samples. The discovered changes in protein responses seem promising for accurate detection of degrading cartilage. The ex vivo model seems interesting for drug discovery projects related to cartilage degradation, for example when trying to uncover the unknown interactions between secreted proteins in healthy and degrading tissues.

COMBImage2: a parallel computational framework for higher-order drug combination analysis that includes automated plate design, matched filter based object counting and temporal data mining.

BACKGROUND: Pharmacological treatment of complex diseases using more than two drugs is commonplace in the clinic due to better efficacy, decreased toxicity and reduced risk for developing resistance. However, many of these higher-order treatments have not undergone any detailed preceding in vitro evaluation that could support their therapeutic potential and reveal disease related insights. Despite the increased medical need for discovery and development of higher-order drug combinations, very few reports from systematic large-scale studies along this direction exist. A major reason is lack of computational tools that enable automated design and analysis of exhaustive drug combination experiments, where all possible subsets among a panel of pre-selected drugs have to be evaluated. RESULTS: Motivated by this, we developed COMBImage2, a parallel computational framework for higher-order drug combination analysis. COMBImage2 goes far beyond its predecessor COMBImage in many different ways. In particular, it offers automated 384-well plate design, as well as quality control that involves resampling statistics and inter-plate analyses. Moreover, it is equipped with a generic matched filter based object counting method that is currently designed for apoptotic-like cells. Furthermore, apart from higher-order synergy analyses, COMBImage2 introduces a novel data mining approach for identifying interesting temporal response patterns and disentangling higher- from lower- and single-drug effects. COMBImage2 was employed in the context of a small pilot study focused on the CUSP9v4 protocol, which is currently used in the clinic for treatment of recurrent glioblastoma. For the first time, all 246 possible combinations of order 4 or lower of the 9 single drugs consisting the CUSP9v4 cocktail, were evaluated on an in vitro clonal culture of glioma initiating cells. CONCLUSIONS: COMBImage2 is able to automatically design and robustly analyze exhaustive and in general higher-order drug combination experiments. Such a versatile video microscopy oriented framework is likely to enable, guide and accelerate systematic large-scale drug combination studies not only for cancer but also other diseases.

COMBImage: a modular parallel processing framework for pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies.

BACKGROUND: Large-scale pairwise drug combination analysis has lately gained momentum in drug discovery and development projects, mainly due to the employment of advanced experimental-computational pipelines. This is fortunate as drug combinations are often required for successful treatment of complex diseases. Furthermore, most new drugs cannot totally replace the current standard-of-care medication, but rather have to enter clinical use as add-on treatment. However, there is a clear deficiency of computational tools for label-free and temporal image-based drug combination analysis that go beyond the conventional but relatively uninformative end point measurements. RESULTS: COMBImage is a fast, modular and instrument independent computational framework for in vitro pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies. Jointly with automated analyses of temporal changes in cell morphology and confluence, it performs and displays conventional cell viability and synergy end point analyses. The image processing algorithms are parallelized using Google's MapReduce programming model and optimized with respect to method-specific tuning parameters. COMBImage is shown to process time-lapse microscopy movies from 384-well plates within minutes on a single quad core personal computer. This framework was employed in the context of an ongoing drug discovery and development project focused on glioblastoma multiforme; the most deadly form of brain cancer. Interesting add-on effects of two investigational cytotoxic compounds when combined with vorinostat were revealed on recently established clonal cultures of glioma-initiating cells from patient tumor samples. Therapeutic synergies, when normal astrocytes were used as a toxicity cell model, reinforced the pharmacological interest regarding their potential clinical use. CONCLUSIONS: COMBImage enables, for the first time, fast and optimized pairwise drug combination analyses of temporal changes in label-free video microscopy movies. Providing this jointly with conventional cell viability based end point analyses, it could help accelerating and guiding any drug discovery and development project, without use of cell labeling and the need to employ a particular live cell imaging instrument.

Bliss and Loewe interaction analyses of clinically relevant drug combinations in human colon cancer cell lines reveal complex patterns of synergy and antagonism.

We analyzed survival effects for 15 different pairs of clinically relevant anti-cancer drugs in three iso-genic pairs of human colorectal cancer carcinoma cell lines, by applying for the first time our novel software (R package) called COMBIA. In our experiments iso-genic pairs of cell lines were used, differing only with respect to a single clinically important KRAS or BRAF mutation. Frequently, concentration dependent but mutation independent joint Bliss and Loewe synergy/antagonism was found statistically significant. Four combinations were found synergistic/antagonistic specifically to the parental (harboring KRAS or BRAF mutation) cell line of the corresponding iso-genic cell lines pair. COMBIA offers considerable improvements over established software for synergy analysis such as MacSynergy™ II as it includes both Bliss (independence) and Loewe (additivity) analyses, together with a tailored non-parametric statistical analysis employing heteroscedasticity, controlled resampling, and global (omnibus) testing. In many cases Loewe analyses found significant synergistic as well as antagonistic effects in a cell line at different concentrations of a tested drug combination. By contrast, Bliss analysis found only one type of significant effect per cell line. In conclusion, the integrated Bliss and Loewe interaction analysis based on non-parametric statistics may provide more robust interaction analyses and reveal complex patterns of synergy and antagonism.

Towards repositioning of quinacrine for treatment of acute myeloid leukemia - Promising synergies and in vivo effects.

We previously reported that the anti-malarial drug quinacrine has potential to be repositioned for treatment of acute myeloid leukemia (AML). As a next step towards clinical use, we assessed the efficacy of quinacrine in an AML-PS mouse model and investigated possible synergistic effects when combining quinacrine with nine other antileukemic compounds in two AML cell lines. Furthermore, we explored the in vivo activity of quinacrine in combination with the widely used AML agent cytarabine. The in vivo use of quinacrine (100mg/kg three times per week for two consecutive weeks) significantly suppressed circulating blast cells at days 30/31 and increased the median survival time (MST). The in vitro drug combination analysis yielded promising synergistic interactions when combining quinacrine with cytarabine, azacitidine and geldanamycin. Finally, combining quinacrine with cytarabine in vivo showed a significant decrease in circulating leukemic blast cells and increased MST compared to the effect of either drug used alone, thus supporting the findings from the in vitro combination experiments. Taken together, the repositioning potential of quinacrine for treatment of AML is reinforced by demonstrating significant in vivo activity and promising synergies when quinacrine is combined with different agents, including cytarabine, the hypomethylating agent azacitidine and HSP-90 inhibitor geldanamycin.

Targeting tumor cells based on Phosphodiesterase 3A expression.

We and others have previously reported a correlation between high phosphodiesterase 3A (PDE3A) expression and selective sensitivity to phosphodiesterase (PDE) inhibitors. This indicates that PDE3A could serve both as a drug target and a biomarker of sensitivity to PDE3 inhibition. In this report, we explored publicly available mRNA gene expression data to identify cell lines with different PDE3A expression. Cell lines with high PDE3A expression showed marked in vitro sensitivity to PDE inhibitors zardaverine and quazinone, when compared with those having low PDE3A expression. Immunofluorescence and immunohistochemical stainings were in agreement with PDE3A mRNA expression, providing suitable alternatives for biomarker analysis of clinical tissue specimens. Moreover, we here demonstrate that tumor cells from patients with ovarian carcinoma show great variability in PDE3A protein expression and that level of PDE3A expression is correlated with sensitivity to PDE inhibition. Finally, we demonstrate that PDE3A is highly expressed in subsets of patient tumor cell samples from different solid cancer diagnoses and expressed at exceptional levels in gastrointestinal stromal tumor (GIST) specimens. Importantly, vulnerability to PDE3 inhibitors has recently been associated with co-expression of PDE3A and Schlafen family member 12 (SLFN12). We here demonstrate that high expression of PDE3A in clinical specimens, at least on the mRNA level, seems to be frequently associated with high SLFN12 expression. In conclusion, PDE3A seems to be both a promising biomarker and drug target for individualized drug treatment of various cancers.