Integrated High-Throughput Screening and Large-Scale Isobolographic Analysis to Accelerate the Discovery of Radiosensitizers With Greater Selectivity for Cancer Cells.

PURPOSE: High-throughput screening (HTS) platforms have been widely used to identify candidate anticancer drugs and drug-drug combinations; however, HTS-based identification of new drug-ionizing radiation (IR) combinations has rarely been reported. Herein, we developed an integrated approach including cell-based HTS and computational large-scale isobolographic analysis to accelerate the identification of radiosensitizing compounds acting strongly and more specifically on cancer cells. METHODS AND MATERIALS: In a 384-well plate format, 160 compounds likely to interfere with the cell response to radiation were screened on human glioblastoma (U251-MG) and cervix carcinoma (ME-180) cell lines, as well as on normal fibroblasts (CCD-19Lu). After drug exposure, cells were irradiated or not and short-term cell survival was assessed by high-throughput cell microscopy. Computational large-scale dose-response and isobolographic approach were used to identify promising synergistic drugs radiosensitizing cancer cells rather than normal cells. Synergy of a promising compound was confirmed on ME-180 cells by an independent 96-well assay protocol, and finally, by the gold-standard colony forming assay. RESULTS: We retained 4 compounds synergistic at 2 isoeffects in U251-MG and ME-180 cell lines and 11 compounds synergistically effective in only one cancer cell line. Among these 15 promising radiosensitizers, 5 compounds showed limited toxicity combined or not with IR on normal fibroblasts. CONCLUSIONS: Overall, this study demonstrated that HTS chemoradiation screening together with large-scale computational analysis is an efficient tool to identify synergistic drug-IR combinations, with concomitant assessment of unwanted toxicity on normal fibroblasts. It sparks expectations to accelerate the discovery of highly desired agents improving the therapeutic index of radiation therapy.

Homosalate boosts the release of tumour-derived extracellular vesicles with protection against anchorage-loss property.

Eukaryotic cells, including cancer cells, secrete highly heterogeneous populations of extracellular vesicles (EVs). EVs could have different subcellular origin, composition and functional properties, but tools to distinguish between EV subtypes are scarce. Here, we tagged CD63- or CD9-positive EVs secreted by triple negative breast cancer cells with Nanoluciferase enzyme, to set-up a miniaturized method to quantify secretion of these two EV subtypes directly in the supernatant of cells. We performed a cell-based high-content screening to identify clinically-approved drugs able to affect EV secretion. One of the identified hits is Homosalate, an anti-inflammatory drug found in sunscreens which robustly increased EVs' release. Comparing EVs induced by Homosalate with those induced by Bafilomycin A1, we demonstrate that: (1) the two drugs act on EVs generated in distinct subcellular compartments, and (2) EVs released by Homosalate-, but not by Bafilomycin A1-treated cells enhance resistance to anchorage loss in another recipient epithelial tumour cell line. In conclusion, we identified a new drug modifying EV release and demonstrated that under influence of different drugs, triple negative breast cancer cells release EV subpopulations from different subcellular origins harbouring distinct functional properties.

Targeting CCR5 trafficking to inhibit HIV-1 infection.

Using a cell-based assay monitoring differential protein transport in the secretory pathway coupled to high-content screening, we have identified three molecules that specifically reduce the delivery of the major co-receptor for HIV-1, CCR5, to the plasma membrane. They have no effect on the closely related receptors CCR1 and CXCR4. These molecules are also potent in primary macrophages as they markedly decrease HIV entry. At the molecular level, two of these molecules inhibit the critical palmitoylation of CCR5 and thereby block CCR5 in the early secretory pathway. Our results open a clear therapeutics avenue based on trafficking control and demonstrate that preventing HIV infection can be performed at the level of its receptor delivery.

High-Throughput Drug Screening Identifies Pazopanib and Clofilium Tosylate as Promising Treatments for Malignant Rhabdoid Tumors.

Rhabdoid tumors (RTs) are aggressive tumors of early childhood characterized by SMARCB1 inactivation. Their poor prognosis highlights an urgent need to develop new therapies. Here, we performed a high-throughput screening of approved drugs and identified broad inhibitors of tyrosine kinase receptors (RTKs), including pazopanib, and the potassium channel inhibitor clofilium tosylate (CfT), as SMARCB1-dependent candidates. Pazopanib targets were identified as PDGFRα/ß and FGFR2, which were the most highly expressed RTKs in a set of primary tumors. Combined genetic inhibition of both these RTKs only partially recapitulated the effect of pazopanib, emphasizing the requirement for broad inhibition. CfT perturbed protein metabolism and endoplasmic reticulum stress and, in combination with pazopanib, induced apoptosis of RT cells in vitro. In vivo, reduction of tumor growth by pazopanib was enhanced in combination with CfT, matching the efficiency of conventional chemotherapy. These results strongly support testing pazopanib/CfT combination therapy in future clinical trials for RTs.

Yeast cells reveal the misfolding and the cellular mislocalization of the human BRCA1 protein.

Understanding the effect of an ever-growing number of human variants detected by genome sequencing is a medical challenge. The yeast Saccharomyces cerevisiae model has held attention for its capacity to monitor the functional impact of missense mutations found in human genes, including the BRCA1 breast and ovarian cancer susceptibility gene. When expressed in yeast, the wild-type full-length BRCA1 protein forms a single nuclear aggregate and induces a growth inhibition. Both events are modified by pathogenic mutations of BRCA1. However, the biological processes behind these events in yeast remain to be determined. Here, we show that the BRCA1 nuclear aggregation and the growth inhibition are sensitive to misfolding effects induced by missense mutations. Moreover, misfolding mutations impair the nuclear targeting of BRCA1 in yeast cells and in a human cell line. In conclusion, we establish a connection between misfolding and nuclear transport impairment, and we illustrate that yeast is a suitable model to decipher the effect of misfolding mutations.

Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making.

Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening.

A kinome siRNA screen identifies HGS as a potential target for liver cancers with oncogenic mutations in CTNNB1.

BACKGROUND: Aberrant activation of the Wnt/ß-catenin pathway is a major and frequent event in liver cancer, but inhibition of oncogenic ß-catenin signaling has proven challenging. The identification of genes that are synthetically lethal in ß-catenin-activated cancer cells would provide new targets for therapeutic drug design. METHODS: We transfected the parental HuH6 hepatoblastoma cell line with a doxycycline-inducible shRNA against CTNNB1 (gene coding for ß-catenin) to obtain an isogenic cell line pair with or without aberrant ß-catenin signaling. Using this hepatoblastoma isogenic cell line pair, we performed a human kinome-wide siRNA screen to identify synthetic lethal interactions with oncogenic CTNNB1. The phenotypic readouts of the screen were cell proliferation, cell cycle arrest and apoptosis, which were assessed by image-based analysis. In addition, apoptosis was assessed by flow cytometric experiments and immunoblotting. The potential synthetic lethal relationship between candidates genes identified in the screen and oncogenic CTNNB1 was also investigated in a different cellular context, a colorectal HCT116 isogenic cell line pair. RESULTS: We first determined the experimental conditions that led to the efficient expression of shRNA against CTNNB1 and maximal reduction of ß-catenin signaling activity in response to doxycycline treatment. Following high throughput screening in which 687 genes coding for kinases and proteins related to kinases (such as pseudokinases and phosphatases) were targeted, we identified 52 genes required for HuH6 survival. The silencing of five of these genes selectively impaired the viability of HuH6 cells with high ß-catenin signaling: HGS, STRADA, FES, BRAF and PKMYT1. Among these candidates, HGS depletion had the strongest inhibitory effect on cell growth and led to apoptosis specifically in HuH6 with high ß-catenin activity, while HuH6 with low ß-catenin activity were spared. In addition, HGS was identified as a potential synthetic lethal partner of oncogenic CTNNB1 in the HCT116 colorectal isogenic cell line pair. CONCLUSIONS: These results demonstrate the existence of crosstalk between ß-catenin signaling and HGS. Importantly, HGS depletion specifically affected cells with uncontrolled ß-catenin signaling activity in two different types of cancer (Hepatoblastoma HuH6 and colorectal HCT116), and thus may represent a new potential target for novel therapeutic strategies in liver and colorectal cancer.

A siRNA screen identifies RAD21, EIF3H, CHRAC1 and TANC2 as driver genes within the 8q23, 8q24.3 and 17q23 amplicons in breast cancer with effects on cell growth, survival and transformation.

RNA interference has boosted the field of functional genomics, by making it possible to carry out 'loss-of-function' screens in cultured cells. Here, we performed a small interfering RNA screening, in three breast cancer cell lines, for 101 candidate driver genes overexpressed in amplified breast tumors and belonging to eight amplicons on chromosomes 8q and 17q, investigating their role in cell survival/proliferation. This screening identified eight driver genes that were amplified, overexpressed and critical for breast tumor cell proliferation or survival. They included the well-described oncogenic driver genes for the 17q12 amplicon, ERBB2 and GRB7. Four of six other candidate driver genes-RAD21 and EIF3H, both on chromosome 8q23, CHRAC1 on chromosome 8q24.3 and TANC2 on chromosome 17q23-were confirmed to be driver genes regulating the proliferation/survival of clonogenic breast cancer cells presenting an amplification of the corresponding region. Indeed, knockdown of the expression of these genes decreased cell viability, through both cell cycle arrest and apoptosis induction, and inhibited the formation of colonies in anchorage-independent conditions, in soft agar. Strategies for inhibiting the expression of these genes or the function of the proteins they encode are therefore of potential value for the treatment of breast cancers presenting amplifications of the corresponding genomic region.

A probabilistic model for cell population phenotyping using HCS data.

High Content Screening (HCS) platforms allow screening living cells under a wide range of experimental conditions and give access to a whole panel of cellular responses to a specific treatment. The outcome is a series of cell population images. Within these images, the heterogeneity of cellular response to the same treatment leads to a whole range of observed values for the recorded cellular features. Consequently, it is difficult to compare and interpret experiments. Moreover, the definition of phenotypic classes at a cell population level remains an open question, although this would ease experiments analyses. In the present work, we tackle these two questions. The input of the method is a series of cell population images for which segmentation and cellular phenotype classification has already been performed. We propose a probabilistic model to represent and later compare cell populations. The model is able to fully exploit the HCS-specific information: "dependence structure of population descriptors" and "within-population variability". The experiments we carried out illustrate how our model accounts for this specific information, as well as the fact that the model benefits from considering them. We underline that these features allow richer HCS data analysis than simpler methods based on single cellular feature values averaged over each well. We validate an HCS data analysis method based on control experiments. It accounts for HCS specificities that were not taken into account by previous methods but have a sound biological meaning. Biological validation of previously unknown outputs of the method constitutes a future line of work.