Development and external validation of a predictive multivariable model for last-weeks survival of advanced cancer patients in the palliative home care setting (PACS).

PURPOSE: Various prognostic indexes have been proposed to improve physicians' ability to predict survival time in advanced cancer patients, admitted to palliative care (PC) with a survival probably to a few weeks of life, but no optimal score has been identified. The study aims therefore to develop and externally validate a new multivariable predictive model in this setting. METHODS: We developed a model to predict short-term overall survival in cancer patients on the basis of clinical factors collected at PC admission. The model was developed on 1020 cancer patients prospectively enrolled to home palliative care at VIDAS Milan, Italy, between May 2018 and February 2020 and followed-up to June 2020, and validated in two separate samples of 544 home care and 247 hospice patients. RESULTS: Among 68 clinical factors considered, five predictors were included in the predictive model, i.e., rattle, heart rate, anorexia, liver failure, and the Karnofsky performance status. Patient's survival probability at 5, 15, 30 and 45 days was estimated. The predictive model showed a good calibration and moderate discrimination (area under the receiver operating characteristic curve between 0.72 and 0.79) in the home care validation set, but model calibration was suboptimal in hospice patients. CONCLUSIONS: The new multivariable predictive model for palliative cancer patients' survival (PACS model) includes clinical parameters routinely at patient's admission to PC and can be easily used to facilitate immediate and appropriate short-term clinical decisions for PC cancer patients in the home setting.

THE SPACE DIMENSION AT THE MICRO LEVEL: MASS SPECTROMETRY IMAGING OF DRUGS IN TISSUES.

Mass spectrometry imaging (MSI) has seen remarkable development in recent years. The possibility of getting quantitative or semiquantitative data, while maintaining the spatial component in the tissues has opened up unique study possibilities. Now with a spatial window of few tens of microns, we can characterize the events occurring in tissue subcompartments in physiological and pathological conditions. For example, in oncology-especially in preclinical models-we can quantitatively measure drug distribution within tumors, correlating it with pharmacological treatments intended to modify it. We can also study the local effects of the drug in the tissue, and their effects in relation to histology. This review focuses on the main results in the field of drug MSI in clinical pharmacology, looking at the literature on the distribution of drugs in human tissues, and also the first preclinical evidence of drug intratissue effects. The main instrumental techniques are discussed, looking at the different instrumentation, sample preparation protocols, and raw data management employed to obtain the sensitivity required for these studies. Finally, we review the applications that describe in situ metabolic events and pathways induced by the drug, in animal models, showing that MSI makes it possible to study effects that go beyond the simple concentration of the drug, maintaining the space dimension. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

ActivinA: a new leukemia-promoting factor conferring migratory advantage to B-cell precursor-acute lymphoblastic leukemic cells.

B-cell precursor-acute lymphoblastic leukemia modulates the bone marrow (BM) niche to become leukemia-supporting and chemo-protective by reprogramming the stromal microenvironment. New therapies targeting the interplay between leukemia and stroma can help improve disease outcome. We identified ActivinA, a TGF-ß family member with a well-described role in promoting several solid malignancies, as a factor favoring leukemia that could represent a new potential target for therapy. ActivinA resulted over-expressed in the leukemic BM and its production was strongly induced in mesenchymal stromal cells after culture with leukemic cells. Moreover, MSCs isolated from BM of leukemic patients showed an intrinsic ability to secrete higher amounts of ActivinA compared to their normal counterparts. The pro-inflammatory leukemic BM microenvironment synergized with leukemic cells to induce stromal-derived ActivinA. Gene expression analysis of ActivinA-treated leukemic cells showed that this protein was able to significantly influence motility-associated pathways. Interestingly, ActivinA promoted random motility and CXCL12-driven migration of leukemic cells, even at suboptimal chemokine concentrations, characterizing the leukemic niche. Conversely, ActivinA severely impaired CXCL12-induced migration of healthy CD34+ cells. This opposite effect can be explained by the ability of ActivinA to increase intracellular calcium only in leukemic cells, boosting cytoskeleton dynamics through a higher rate of actin polymerization. Moreover, by stimulating the invasiveness of the leukemic cells, ActivinA was found to be a leukemia-promoting factor. Importantly, the ability of ActivinA to enhance BM engraftment and the metastatic potential of leukemic cells was confirmed in a xenograft mouse model of the disease. Overall, ActivinA was seen to be a key factor in conferring a migratory advantage to leukemic cells over healthy hematopoiesis within the leukemic niche.

Tumor progression and metastatic dissemination in ovarian cancer after dose-dense or conventional paclitaxel and cisplatin plus bevacizumab.

The efficacy of therapeutic regimens incorporating weekly or every-3-weeks paclitaxel (PTX) for ovarian cancer is debated. We investigated the addition of bevacizumab in regimens of chemotherapy with different PTX doses and schedules in preclinical models. Treatments were cisplatin (DDP) with weekly PTX (conventional), or dose-dense-equi (every other day to the conventional cumulative dose), or dose-dense-high (total dose 1.5 times higher), with or without bevacizumab. Treatment efficacy was evaluated analyzing tumor growth in different time-windows in two patient-derived ovarian cancer xenografts with different sensitivity to cisplatin. Tumor progression, metastasis and survival were studied in ovarian cancer models growing orthotopically and disseminating in the mouse peritoneal cavity. Short-term effects on cell cycle, tumor cell proliferation/apoptosis and vasculature were evaluated by flow cytometry and immunohistochemistry. PTX dose-dense (with/without DDP) was superior to the conventional scheme in a dose-dependent manner; the high efficacy was confirmed by the lower ratio of tumor to normal cells. All schemes benefited from bevacizumab, which reduced tumor vessels. However, DDP/PTX dose-dense-high (only chemotherapy) was at least as active as DDP/PTX conventional plus bevacizumab. DDP/PTX dose-dense-high plus bevacizumab was the most effective in delaying tumor progression, though it did not prolong mouse survival and the continuous treatment with bevacizumab was associated with a malignant disease. These findings indicate that the effect of bevacizumab in combination with chemotherapy may depend on the schedule-dose of the treatment and help to explain the unclear benefits after bevacizumab.

Promising in vivo efficacy of the BET bromodomain inhibitor OTX015/MK-8628 in malignant pleural mesothelioma xenografts.

It has recently been reported that a large proportion of human malignant pleural mesothelioma (MPM) cell lines and patient tissue samples present high expression of the c-MYC oncogene. This gene drives several tumorigenic processes and is overexpressed in many cancers. Although c-MYC is a strategic target to restrain cancer processes, no drugs acting as c-MYC inhibitors are available. The novel thienotriazolodiazepine small-molecule bromodomain inhibitor OTX015/MK-8628 has shown potent antiproliferative activity accompanied by c-MYC downregulation in several tumor types. This study was designed to evaluate the growth inhibitory effect of OTX015 on patient-derived MPM473, MPM487 and MPM60 mesothelioma cell lines and its antitumor activity in three patient-derived xenograft models, MPM473, MPM487 and MPM484, comparing it with cisplatin, gemcitabine and pemetrexed, three agents which are currently used to treat MPM in the clinic. OTX015 caused a significant delay in cell growth both in vitro and in vivo. It was the most effective drug in MPM473 xenografts and showed a similar level of activity as the most efficient treatment in the other two MPM models (gemcitabine in MPM487 and cisplatin in MPM484). In vitro studies showed that OTX015 downregulated c-MYC protein levels in both MPM473 and MPM487 cell lines. Our findings represent the first evidence of promising therapeutic activity of OTX015 in mesothelioma.

PEGylated Nanoparticles Obtained through Emulsion Polymerization as Paclitaxel Carriers.

Polymer nanoparticles (NPs) represent a promising way to deliver poorly water-soluble anticancer drugs without the use of unwanted excipients, whose presence can be the cause of severe side effects. In this work, a Cremophor-free formulation for paclitaxel (PTX) has been developed by employing PEGylated polymer nanoparticles (NPs) as drug delivery carriers based on modified poly(ε-caprolactone) macromonomers and synthesized through free radical emulsion polymerization. Paclitaxel was loaded in the NPs in a postsynthesis process which allowed to obtain a drug concentration suitable for in vivo use. In vivo experiments on drug biodistribution and therapeutic efficacy show comparable behavior between the NPs and the Cremophor formulation, also showing good tolerability of the new formulation proposed.

Fate of PLA and PCL-Based Polymeric Nanocarriers in Cellular and Animal Models of Triple-Negative Breast Cancer.

An integrated platform to assess the interaction between nanocarriers and biological matrices has been developed by our group using poly methyl-methacrylate nanoparticles. In this study, we exploited this platform to evaluate the behavior of two biodegradable formulations, poly-ε-caprolactone (PCL3) and poly lactic-acid (PLA8), respectively, in cellular and animal models of triple-negative breast cancer (TNBC). Both NPs shared the main physicochemical parameters (size, shape, ζ-potential) and exclusively differentiated on the material on which they are composed. Our results showed that (1) PLA8 NPs, systemically injected in mice, underwent rapid degradation without penetration into tumors; (2) PLA8 NPs were not internalized in the human TNBC cell line (MDA-MB-231); (3) PCL3 NPs had a longer bioavailability, reached the tumor parenchyma, and efficiently penetrated in MDA-MB-231 cells. Our data highlight the relevance of the material selection to both improve bioavailability and target tropism, and make PCL3 NPs an interesting tool for the development of nanodrugs against TNBC.

Small interfering RNA delivery through positively charged polymer nanoparticles.

Small interfering RNA (siRNA) is receiving increasing attention with regard to the treatment of many genetic diseases, both acquired and hereditary, such as cancer and diabetes. Being a high molecular weight (MW) polyanion, siRNA is not able to cross a cell membrane, and in addition it is unstable in physiological conditions. Accordingly, a biocompatible nanocarrier able to deliver siRNA into cells is needed. In this work, we synthesized biocompatible positively charged nanoparticles (NPs) following a two-step process that involves ring opening polymerization (ROP) and emulsion free radical polymerization (EFRP). Firstly, we proved the possibility of fine tuning the NPs' characteristics (e.g. size and surface charge) by changing the synthetic process parameters. Then the capability in loading and delivering undamaged siRNA into a cancer cell cytoplasm has been shown. This latter process occurs through the biodegradation of the polymer constituting the NPs, whose kinetics can be tuned by adjusting the polymer's MW. Finally, the ability of NPs to carry siRNA inside the cells in order to inhibit their target gene has been demonstrated using green flourescent protein positive cells.

Dynamic rendering of the heterogeneous cell response to anticancer treatments.

The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dose-dependence of G1, S and G2M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario.

Integrated multiplatform method for in vitro quantitative assessment of cellular uptake for fluorescent polymer nanoparticles.

Studies of cellular internalization of nanoparticles (NPs) play a paramount role for the design of efficient drug delivery systems, but so far they lack a robust experimental technique able to quantify the NP uptake in terms of number of NPs internalized in each cell. In this work we propose a novel method which provides a quantitative evaluation of fluorescent NP uptake by combining flow cytometry and plate fluorimetry with measurements of number of cells. Single cell fluorescence signals measured by flow cytometry were associated with the number of internalized NPs, exploiting the observed linearity between average flow cytometric fluorescence and overall plate fluorimeter measures, and previous calibration of the microplate reader with serial dilutions of NPs. This precise calibration has been made possible by using biocompatible fluorescent NPs in the range of 20-300 nm with a narrow particle size distribution, functionalized with a covalently bonded dye, Rhodamine B, and synthesized via emulsion free-radical polymerization. We report the absolute number of NPs internalized in mouse mammary tumor cells (4T1) as a function of time for different NP dimensions and surface charges and at several exposure concentrations. The obtained results indicate that 4T1 cells incorporated 10(3)-10(4) polymer NPs in a short time, reaching an intracellular concentration 15 times higher than the external one.

Biocompatible fluorescent nanoparticles for in vivo stem cell tracking.

Efficient application of stem cells to the treatment of neurodegenerative diseases requires safe cell tracking to follow stem cell fate over time in the host environment after transplantation. In this work, for the first time, fluorescent and biocompatible methyl methacrylate (MMA)-based nanoparticles (fluoNPs) were synthesized through a free-radical co-polymerization process with a fluorescent macromonomer obtained by linking Rhodamine B and hydroxyethyl methacrylate. We demonstrate that the fluoNPs produced by polymerization of MMA-Rhodamine complexes (1) were efficient for the labeling and tracking of multipotent human amniotic fluid cells (hAFCs); (2) did not alter the main biological features of hAFCs (such as viability, cell growth and metabolic activity); (3) enabled us to determine the longitudinal bio-distribution of hAFCs in different brain areas after graft in the brain ventricles of healthy mice by a direct fluorescence-based technique. The reliability of our approach was furthermore confirmed by magnetic resonance imaging analyses, carried out by incubating hAFCs with both superparamagnetic iron oxide nanoparticles and fluoNPs. Our data suggest that these finely tunable and biocompatible fluoNPs can be exploited for the longitudinal tracking of stem cells.

Enhanced cell cycle perturbation and apoptosis mediate the synergistic effects of ST1926 and ATRA in neuroblastoma preclinical models.

Retinoic acid therapy is nowadays an important component of treatment for residual disease of stage IV neuroblastoma after multimodal therapy. Nevertheless, arising resistance and treatment toxicity could represent relevant limiting factors. In the present study, we show that retinoic acid enhances the cytostatic and apoptogenic properties of the novel adamantyl retinoid ST1926 in a panel of neuroblastoma cells with different p53 status and caspase 8 expression, resulting in synergistic effects as assessed by Combination Index and Isobologram analysis. Under conditions where the two drugs alone produced no toxic effects, their combination resulted in enhanced G2-M arrest and sub-G1 population as shown by BrdU pulse-chase and labeling experiments. PARP cleavage, caspase 3, 8 and 9 activation and modulation of DR4 and FAS were indicative of enhanced apoptosis triggered by the co-incubation of the two drugs whereas neither ST1926-mediated genotoxic damage nor ATRA-differentiating effects were affected by the combined treatment. Caspase-3 and 8-mediated apoptosis appeared to play an important role in the drugs synergism. In fact, the addition of a pan-caspase inhibitor ZVAD-FMK reverted this effect in SK-N-DZ cells, and synergism was confined to limited drugs doses in HTLA cells not expressing caspase-8. Although not modulated, p53 appeared to enhance cells responsiveness to retinoid/ATRA combination. In vivo studies in the most sensitive neuroblastoma model SK-N-DZ, confirmed enhanced activity of the drugs combination vs single treatments. The study provides important lines of evidence that such a drugs combination could represent a less toxic and more effective approach for maintenance treatment in children with neuroblastoma.

Interoperability of time series cytometric data: a cross platform approach for modeling tumor heterogeneity.

The cell cycle, with its highly conserved features, is a fundamental driver for the temporal control of cell proliferation-while abnormal control and modulation of the cell cycle are characteristic of tumor cells. The principal aim in cancer biology is to seek an understanding of the origin and nature of innate and acquired heterogeneity at the cellular level, driven principally by temporal and functional asynchrony. A major bottleneck when mathematically modeling these biological systems is the lack of interlinked structured experimental data. This often results in the in silico models failing to translate the specific hypothesis into parameterized terms that enable robust validation and hence would produce suitable prediction tools rather than just simulation tools. The focus has been on linking data originating from different cytometric platforms and cell-based event analysis to inform and constrain the input parameters of a compartmental cell cycle model, hence partly measuring and deconvolving cell cycle heterogeneity within a tumor population. Our work has addressed the concept that the interoperability of cytometric data, derived from different cytometry platforms, can complement as well as enhance cellular parameters space, thus providing a more broader and in-depth view of the cellular systems. The initial aim was to enable the cell cycle model to deliver an improved integrated simulation of the well-defined and constrained biological system. From a modeling perspective, such a cross platform approach has provided a paradigm shift from conventional cross-validation approaches, and from a bioinformatics perspective, novel computational methodology has been introduced for integrating and mapping continuous data with cross-sectional data. This establishes the foundation for developing predictive models and in silico tracking and prediction of tumor progression

L1CAM promotes ovarian cancer stemness and tumor initiation via FGFR1/SRC/STAT3 signaling.

BACKGROUND: Cancer stem cells (CSC) have been implicated in tumor progression. In ovarian carcinoma (OC), CSC drive tumor formation, dissemination and recurrence, as well as drug resistance, thus contributing to the high death-to-incidence ratio of this disease. However, the molecular basis of such a pathogenic role of ovarian CSC (OCSC) has been elucidated only to a limited extent. In this context, the functional contribution of the L1 cell adhesion molecule (L1CAM) to OC stemness remains elusive. METHODS: The expression of L1CAM was investigated in patient-derived OCSC. The genetic manipulation of L1CAM in OC cells provided gain and loss-of-function models that were then employed in cell biological assays as well as in vivo tumorigenesis experiments to assess the role of L1CAM in OC cell stemness and in OCSC-driven tumor initiation. We applied antibody-mediated neutralization to investigate L1CAM druggability. Biochemical approaches were then combined with functional in vitro assays to study the molecular mechanisms underlying the functional role of L1CAM in OCSC. RESULTS: We report that L1CAM is upregulated in patient-derived OCSC. Functional studies showed that L1CAM promotes several stemness-related properties in OC cells, including sphere formation, tumor initiation and chemoresistance. These activities were repressed by an L1CAM-neutralizing antibody, pointing to L1CAM as a druggable target. Mechanistically, L1CAM interacted with and activated fibroblast growth factor receptor-1 (FGFR1), which in turn induced the SRC-mediated activation of STAT3. The inhibition of STAT3 prevented L1CAM-dependent OC stemness and tumor initiation. CONCLUSIONS: Our study implicate L1CAM in the tumorigenic function of OCSC and point to the L1CAM/FGFR1/SRC/STAT3 signaling pathway as a novel driver of OC stemness. We also provide evidence that targeting this pathway can contribute to OC eradication.

PEGylated recombinant human hyaluronidase (PEGPH20) pre-treatment improves intra-tumour distribution and efficacy of paclitaxel in preclinical models.

BACKGROUND: Scarce drug penetration in solid tumours is one of the possible causes of the limited efficacy of chemotherapy and is related to the altered tumour microenvironment. The abnormal tumour extracellular matrix (ECM) together with abnormal blood and lymphatic vessels, reactive stroma and inflammation all affect the uptake, distribution and efficacy of anticancer drugs. METHODS: We investigated the effect of PEGylated recombinant human hyaluronidase PH20 (PEGPH20) pre-treatment in degrading hyaluronan (hyaluronic acid; HA), one of the main components of the ECM, to improve the delivery of antitumor drugs and increase their therapeutic efficacy. The antitumor activity of paclitaxel (PTX) in HA synthase 3-overexpressing and wild-type SKOV3 ovarian cancer model and in the BxPC3 pancreas xenograft tumour model, was evaluated by monitoring tumour growth with or without PEGPH20 pre-treatment. Pharmacokinetics and tumour penetration of PTX were assessed by HPLC and mass spectrometry imaging analysis in the same tumour models. Tumour tissue architecture and HA deposition were analysed by histochemistry. RESULTS: Pre-treatment with PEGPH20 modified tumour tissue architecture and improved the antitumor activity of paclitaxel in the SKOV3/HAS3 tumour model, favouring its accumulation and more homogeneous intra-tumour distribution, as assessed by quantitative and qualitative analysis. PEGPH20 also reduced HA content influencing, though less markedly, PTX distribution and antitumor activity in the BxPC3 tumour model. CONCLUSION: Remodelling the stroma of HA-rich tumours by depletion of HA with PEGPH20 pre-treatment, is a potentially successful strategy to improve the intra-tumour distribution of anticancer drugs, increasing their therapeutic efficacy, without increasing toxicity.

Miniaturizing bromodeoxyuridine incorporation enables the usage of flow cytometry for cell cycle analysis of adherent tissue culture cells for high throughput screening.

Analysis of cell cycle progression by 5-bromo-2'-deoxyuridine (BrdU) incorporation is commonly used for evaluating the mode of action of anticancer drugs, but usually requires a high number of cells and large amounts of monoclonal antibodies. In addition, manual sample handling is not suitable for high throughput. To circumvent these limitations, we have developed a miniaturized method to measure BrdU incorporation into DNA directly in 96-wells plates. Adherent cells were grown in 96-well plates in the absence or presence of compounds of interest. After BrdU pulse labeling or pulse chase, cells were harvested, transferred to polymerase chain reaction (PCR) V-bottom plates, and fixed by adding methanol. DNA denaturation was performed directly in the plates by heat using a PCR thermocycler. BrdU incorporation was detected by indirect immunocytochemical staining, and cellular DNA was counterstained using propidium iodide. Samples were acquired by a BD FACSCalibur with BD Multiwells Auto sampler or BD HTS. We defined a dynamic range of the optimal cell number, for which cells maintained exponential growth up to 72 h. The assay was robust up to 30,000 cells per well. BrdU dot plots of cell cycle phases showed an excellent separation of cell populations, and DNA histograms showed a low coefficient of variation. Thermal denaturation was suitable for 96-well plates to detect BrdU incorporation with a good signal-to-noise ratio, and cluster analysis allowed fingerprint readouts for drug sensitivity and mechanism of action as exemplified for paclitaxel and doxorubicin. This method provided rapid high-throughput BrdU/DNA content analysis with high accuracy and reproducibility, accompanied by a reduction in reagent consumption. A critical step was identified as the standardization of DNA denaturation using a PCR thermocycler. Here,we show some applications of this method for cell cycle studies in drug discovery.

Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging.

Rationale: Optimal intratumor distribution of an anticancer drug is fundamental to reach an active concentration in neoplastic cells, ensuring the therapeutic effect. Determination of drug concentration in tumor homogenates by LC-MS/MS gives important information about this issue but the spatial information gets lost. Targeted mass spectrometry imaging (MSI) has great potential to visualize drug distribution in the different areas of tumor sections, with good spatial resolution and superior specificity. MSI is rapidly evolving as a quantitative technique to measure the absolute drug concentration in each single pixel. Methods: Different inorganic nanoparticles were tested as matrices to visualize the PARP inhibitors (PARPi) niraparib and olaparib. Normalization by deuterated internal standard and a custom preprocessing pipeline were applied to achieve a reliable single pixel quantification of the two drugs in human ovarian tumors from treated mice. Results: A quantitative method to visualize niraparib and olaparib in tumor tissue of treated mice was set up and validated regarding precision, accuracy, linearity, repeatability and limit of detection. The different tumor penetration of the two drugs was visualized by MSI and confirmed by LC-MS/MS, indicating the homogeneous distribution and higher tumor exposure reached by niraparib compared to olaparib. On the other hand, niraparib distribution was heterogeneous in an ovarian tumor model overexpressing the multidrug resistance protein P-gp, a possible cause of resistance to PARPi. Conclusions: The current work highlights for the first time quantitative distribution of PAPRi in tumor tissue. The different tumor distribution of niraparib and olaparib could have important clinical implications. These data confirm the validity of MSI for spatial quantitative measurement of drug distribution providing fundamental information for pharmacokinetic studies, drug discovery and the study of resistance mechanisms.

Retinoic Acid Sensitivity of Triple-Negative Breast Cancer Cells Characterized by Constitutive Activation of the notch1 Pathway: The Role of Rarß.

Triple-negative breast cancer (TNBC) is a heterogeneous disease that lacks effective therapeutic options. In this study, we profile eighteen TNBC cell lines for their sensitivity to the anti-proliferative action of all-trans retinoic acid (ATRA). The only three cell lines (HCC-1599, MB-157 and MDA-MB-157) endowed with ATRA-sensitivity are characterized by genetic aberrations of the NOTCH1-gene, causing constitutive activation of the NOTCH1 γ-secretase product, N1ICD. N1ICD renders HCC-1599, MB-157 and MDA-MB-157 cells sensitive not only to ATRA, but also to γ-secretase inhibitors (DAPT; PF-03084014). Combinations of ATRA and γ-secretase inhibitors produce additive/synergistic effects in vitro and in vivo. RNA-sequencing studies of HCC-1599 and MB-157 cells exposed to ATRA and DAPT and ATRA+DAPT demonstrate that the two compounds act on common gene sets, some of which belong to the NOTCH1 pathway. ATRA inhibits the growth of HCC-1599, MB-157 and MDA-MB-157 cells via RARα, which up-regulates several retinoid target-genes, including RARß. RARß is a key determinant of ATRA anti-proliferative activity, as its silencing suppresses the effects exerted by the retinoid. In conclusion, we demonstrate that ATRA exerts a significant anti-tumor action only in TNBC cells showing constitutive NOTCH1 activation. Our results support the design of clinical trials involving combinations between ATRA and γ-secretase inhibitors for the treatment of this TNBC subtype.

Beyond The T/C Ratio: Old And New Anticancer Activity Scores In Vivo.

Assessing the efficacy of anticancer agents in animal models remains a necessary step in the development of new treatment options and plays an important role in their optimization and comparison. Often, however, interpretation of the results is flawed by excessive trust in scores traditionally handed down, but whose origin and limitations have been lost. Here I examine the theories and assumptions underlying the most common rating scales, suggesting improvements to the old scores and proposing the adoption of multi-parameter analysis and interpretation of the results, considering different time-windows. I examined case examples of different scenarios of antiproliferative effects induced by treatment, demonstrating that common scores fail to distinguish between completely different responses to treatment or, in other circumstances, indicate a different outcome when the response is the same. I found that a combination of parameters, including the percent tumor growth between the start and end of treatment, the relative tumor burden at nadir and the absolute growth delay, may distinguish among the different cases and support a correct interpretation of the antitumor response. All these parameters can be derived from individual tumor growth curves in a simple way, without any change to common experimental procedures.

HER2-positive breast-cancer cell lines are sensitive to KDM5 inhibition: definition of a gene-expression model for the selection of sensitive cases.

Targeting of histone methylation has therapeutic potential in oncology. Here, we provide proof-of-principle that pharmacological inhibition of KDM5 histone-demethylases is a new strategy for the personalized treatment of HER2+ breast cancer. The anti-proliferative effects of the prototype of a new class of selective KDM5-inhibitors (KDM5-inh1) are evaluated in 40 cell lines, recapitulating the heterogeneity of breast cancer. This analysis demonstrates that HER2+ cells are particularly sensitive to KDM5 inhibition. The results are confirmed in an appropriate in vivo model with a close structural analog (KDM5-inh1A). RNA-seq data obtained in HER2+ BT-474 cells exposed to KDM5-Inh1 indicate that the compound alters expression of numerous genes downstream of the ERBB2 gene-product, HER2. In selected HER2-positive breast-cancer cells, we demonstrate synergistic interactions between KDM5-inh1 and HER2-targeting agents (trastuzumab and lapatinib). In addition, HER2+ cell lines with innate and acquired resistance to trastuzumab show sensitivity to KDM5-inh1. The levels of KDM5A/B/C proteins, which are selectively targeted by the agent, have no significant association with KDM5-inh1 responsiveness across our panel of breast-cancer cell lines, suggesting the existence of other determinants of sensitivity. Using RNA-seq data of the breast-cancer cell lines we generate a gene-expression model that is a robust predictor of KDM5-inh1 sensitivity. In a test set of breast cancers, this model predicts sensitivity to the compound in a large fraction of HER2+ tumors. In conclusion, KDM5 inhibition has potential in the treatment of HER2+ breast cancer and our gene-expression model can be developed into a diagnostic tool for the selection of patients.