An Orthotopic Model of Glioblastoma Is Resistant to Radiodynamic Therapy with 5-AminoLevulinic Acid

Radiosensitization of glioblastoma is a major ambition to increase the survival of this incurable cancer. The 5-aminolevulinic acid (5-ALA) is metabolized by the heme biosynthesis pathway. 5-ALA overload leads to the accumulation of the intermediate fluorescent metabolite protoporphyrin IX (PpIX) with a radiosensitization potential, never tested in a relevant model of glioblastoma. We used a patient-derived tumor cell line grafted orthotopically to create a brain tumor model. We evaluated tumor growth and tumor burden after different regimens of encephalic multifractionated radiation therapy with or without 5-ALA. A fractionation scheme of 5 × 2 Gy three times a week resulted in intermediate survival [48-62 days] compared to 0 Gy (15-24 days), 3 × 2 Gy (41-47 days) and, 5 × 3 Gy (73-83 days). Survival was correlated to tumor growth. Tumor growth and survival were similar after 5 × 2 Gy irradiations, regardless of 5-ALA treatment (RT group (53-67 days), RT+5-ALA group (40-74 days), HR = 1.57, p = 0.24). Spheroid growth and survival were diminished by radiotherapy in vitro, unchanged by 5-ALA pre-treatment, confirming the in vivo results. The analysis of two additional stem-like patient-derived cell lines confirmed the absence of radiosensitization by 5-ALA. Our study shows for the first time that in a preclinical tumor model relevant to human glioblastoma, treated as in clinical routine, 5-ALA administration, although leading to important accumulation of PpIX, does not potentiate radiotherapy

Lactate dehydrogenases promote glioblastoma growth and invasion via a metabolic symbiosis

Lactate is a central metabolite in brain physiology but also contributes to tumor development. Glioblastoma (GB) is the most common and malignant primary brain tumor in adults, recognized by angiogenic and invasive growth, in addition to its altered metabolism. We show herein that lactate fuels GB anaplerosis by replenishing the tricarboxylic acid (TCA) cycle in absence of glucose. Lactate dehydrogenases (LDHA and LDHB), which we found spatially expressed in GB tissues, catalyze the interconversion of pyruvate and lactate. However, ablation of both LDH isoforms, but not only one, led to a reduction in tumor growth and an increase in mouse survival. Comparative transcriptomics and metabolomics revealed metabolic rewiring involving high oxidative phosphorylation (OXPHOS) in the LDHA/B KO group which sensitized tumors to cranial irradiation, thus improving mouse survival. When mice were treated with the antiepileptic drug stiripentol, which targets LDH activity, tumor growth decreased. Our findings unveil the complex metabolic network in which both LDHA and LDHB are integrated and show that the combined inhibition of LDHA and LDHB strongly sensitizes GB to therapy.publishedVersio

Combined targeting of MDM2 and CDK4 is synergistic in dedifferentiated liposarcomas

Abstract Purpose MDM2 and CDK4 are frequently co-amplified in well-differentiated/dedifferentiated liposarcoma (WDLPS/DDLPS). We aimed to determine whether combined MDM2/CDK4 targeting is associated with higher antitumour activity than a single agent in preclinical models of DDLPS. Experimental design DDLPS cells were exposed to RG7388 (MDM2 antagonist) and palbociclib (CDK4 inhibitor), and apoptosis and signalling/survival pathway perturbations were monitored by flow cytometry and Western blotting. Xenograft mouse models were used to assess tumour growth and survival. Treatment efficacy was assessed by Western blotting, histopathology and tumour volume. Results RG7388 and palbociclib together exerted a greater antitumour effect than either drug alone, with significant differences in cell viability after a 72-h treatment with RG7388 and/or palbociclib. The combination treatment significantly increased apoptosis compared to the single agents. We then analysed the in vivo antitumour activity of RG7388 and palbociclib in a xenograft model of DDLPS. The combination regimen reduced the tumour growth rate compared with a single agent alone and significantly increased the median progression-free survival. Conclusions Our results provide a strong rationale for evaluating the therapeutic potential of CDK4 inhibitors as potentiators of MDM2 antagonists in DDLPS and justify clinical trials in this setting

RNA-mediated paternal heredity of diet-induced obesity and metabolic disorders

International audienceThe paternal heredity of obesity and diabetes induced by a high-fat and/or high-sugar diet (Western-like diet) has been demonstrated through epidemiological analysis of human cohorts and experimental analysis, but the nature of the hereditary vector inducing this newly acquired phenotype is not yet well defined. Here, we show that microinjection of either testis or sperm RNA of male mice fed a Western-like diet into naive one-cell embryos leads to the establishment of the Western-like diet-induced metabolic phenotype in the resulting progenies, whereas RNAs prepared from healthy controls did not. Among multiple sequence differences between the testis transcriptomes of the sick and healthy fathers, we noted that several microRNAs had increased expression, which was of interest because this class of noncoding RNA is known to be involved in epigenetic control of gene expression. When microinjected into naive one-cell embryos, one of these small RNA, i.e., the microRNA miR19b, induced metabolic alterations that are similar to the diet-induced phenotype. Furthermore, this pathological phenotype was inherited by the offspring after crosses with healthy partners. Our results indicate that acquired food-induced trait inheritance might be enacted by RNA signalling

Deep learning model for automatic segmentation of lungs and pulmonary metastasis in small animal MR images

Lungs are the most frequent site of metastases growth. The amount and size of pulmonary metastases acquired from MRI imaging data are the important criteria to assess the efficacy of new drugs in preclinical models. While efficient solutions both for MR imaging and the downstream automatic segmentation have been proposed for human patients, both MRI lung imaging and segmentation in preclinical animal models remains challenging due to the physiological motion (respiratory and cardiac movements), to the low amount of protons in this organ and to the particular challenge of precise segmentation of metastases. As a consequence post-mortem analysis is currently required to obtain information on metastatic volume. In this work, we have developed a complete methodological pipeline for automated analysis of lungs and metastases in mice, consisting of an MR sequence for image acquisition and a deep learning method for automatic segmentation of both lungs and metastases. On one hand, we optimized an MR sequence for mouse lung imaging with high contrast for high detection sensitivity. On the other hand we developed DeepMeta, a multiclass U-Net 3+ deep learning model to automatically segment the images. To assess if the proposed deep learning pipeline is able to provide an accurate segmentation of both lungs and pulmonary metastases, we have longitudinally imaged mice with fast- and slow-growing metastasis. Fifty-five balb/c mice were injected with two different derivatives of renal carcinoma cells. Mice were imaged with a SG-bSSFP (self-gated balanced steady state free precession) sequence at different time points after the injection of cancer cells. Both lung and metastases segmentations were manually performed by experts. DeepMeta was trained to perform lung and metastases segmentation based on the resulting ground truth annotations. Volumes of lungs and of pulmonary metastases as well as the number of metastases per mouse were measured on a separate test dataset of MR images. Thanks to the SG method, the 3D bSSFP images of lungs were artifact-free, enabling the downstream detection and serial follow-up of metastases. Moreover, both lungs and metastases segmentation was accurately performed by DeepMeta as soon as they reached the volume of ∼ 0.02 m m 3 . Thus we were able to distinguish two groups of mice in terms of number and volume of pulmonary metastases as well as in terms of the slow versus fast patterns of growth of metastases. We have shown that our methodology combining SG-bSSFP with deep learning, enables processing of the whole animal lungs and is thus a viable alternative to histology alone

Antiangiogenic Compound Axitinib Demonstrates Low Toxicity and Antitumoral Effects against Medulloblastoma

International audienceBackground: Despite the improvement of medulloblastoma (MB) treatments, survivors face severe long-term adverse effects and associated morbidity following multimodal treatments. Moreover, relapses are fatal within a few months. Therefore, chemotherapies inducing fewer adverse effects and/or improving survival at relapse are key for MB patients. Our purpose was to evaluate the last-generation antiangiogenic drugs for their relevance in the therapeutic arsenal of MB. Methods: We screened three EMA- and FDA-approved antiangiogenic compounds (axitinib, cabozantinib and sunitinib) for their ability to reduce cell viability of five MB cell lines and their low toxicity towards two normal cell lines in vitro. Based on this screening, single-agent and combination therapies were designed for in vivo validation. Results: Axitinib, cabozantinib and sunitinib decreased viability of all the tested tumor cells. Although sunitinib was the most efficient in tumor cells, it also impacted normal cells. Therefore, axitinib showed the highest selectivity index for MB cells as compared to normal cells. The compound did not lead to acute toxicity in juvenile rats and crossed the blood–brain barrier. Moreover, axitinib efficiently reduced the growth rate of experimental brain tumors. Analysis of public databases showed that high expression of axitinib targets correlates with poor prognosis. Conclusion: Our results suggest that axitinib is a compelling candidate for MB treatment

Refining the Role of Pyruvate Dehydrogenase Kinases in Glioblastoma Development

International audienceGlioblastoma (GB) are the most frequent brain cancers. Aggressive growth and limited treatment options induce a median survival of 12-15 months. In addition to highly proliferative and invasive properties, GB cells show cancer-associated metabolic characteristics such as increased aerobic glycolysis. Pyruvate dehydrogenase (PDH) is a key enzyme complex at the crossroads between lactic fermentation and oxidative pathways, finely regulated by PDH kinases (PDHKs). PDHKs are often overexpressed in cancer cells to facilitate high glycolytic flux. We hypothesized that targeting PDHKs, by disturbing cancer metabolic homeostasis, would alter GB progression and render cells vulnerable to additional cancer treatment. Using patient databases, distinct expression patterns of PDHK1 and PDHK2 in GB tissues were obvious. To disturb protumoral glycolysis, we modulated PDH activity through the genetic or pharmacological inhibition of PDHK in patient-derived stem-like spheroids. Striking effects of PDHKs inhibition using dichloroacetate were observed in vitro on cell morphology and metabolism, resulting in increased intracellular ROS levels and decreased proliferation and invasion. In vivo findings confirmed a reduction in tumor size and better survival of mice implanted with PDHK1 and PDHK2 knockout cells. Adding a radiotherapeutic protocol further resulted in a reduction in tumor size and improved mouse survival in our model

THBS1+ myeloid cells expand in SLD hepatocellular carcinoma and contribute to immunosuppression and unfavorable prognosis through TREM1

Summary: Hepatocellular carcinoma (HCC) is an inflammation-associated cancer arising from viral or non-viral etiologies including steatotic liver diseases (SLDs). Expansion of immunosuppressive myeloid cells is a hallmark of inflammation and cancer, but their heterogeneity in HCC is not fully resolved and might underlie immunotherapy resistance. Here, we present a high-resolution atlas of innate immune cells from patients with HCC that unravels an SLD-associated contexture characterized by influx of inflammatory and immunosuppressive myeloid cells, including a discrete population of THBS1+ regulatory myeloid (Mreg) cells expressing monocyte- and neutrophil-affiliated genes. THBS1+ Mreg cells expand in SLD-associated HCC, populate fibrotic lesions, and are associated with poor prognosis. THBS1+ Mreg cells are CD163+ but distinguished from macrophages by high expression of triggering receptor expressed on myeloid cells 1 (TREM1), which contributes to their immunosuppressive activity and promotes HCC tumor growth in vivo. Our data support myeloid subset-targeted immunotherapies to treat HCC