Summary Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA -induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction. Video Abstract

Background: Pediatric high-grade gliomas (pHGGs) are facing a very dismal prognosis and representative pre-clinical models are needed for new treatment strategies. Here, we examined the relevance of collecting functional, genomic, and metabolomics data to validate patient-derived models in a hypoxic microenvironment. Methods: From our biobank of pediatric brain tumor-derived models, we selected 11 pHGGs driven by the histone H3.3K28M mutation. We compared the features of four patient tumors to their paired cell lines and mouse xenografts using NGS (next generation sequencing), aCGH (array comparative genomic hybridization), RNA sequencing, WES (whole exome sequencing), immunocytochemistry, and HRMAS (high resolution magic angle spinning) spectroscopy. We developed a multicellular in vitro model of cell migration to mimic the brain hypoxic microenvironment. The live cell technology Incucyte© was used to assess drug responsiveness in variable oxygen conditions. Results: The concurrent 2D and 3D cultures generated from the same tumor sample exhibited divergent but complementary features, recreating the patient intra-tumor complexity. Genomic and metabolomic data described the metabolic changes during pHGG progression and supported hypoxia as an important key to preserve the tumor metabolism in vitro and cell dissemination present in patients. The neurosphere features preserved tumor development and sensitivity to treatment. Conclusion: We proposed a novel multistep work for the development and validation of patient-derived models, considering the immature and differentiated content and the tumor microenvironment of pHGGs.

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Osteosarcoma is the first bone cancer diagnosed in adolescent and young adults. Multiple studies involved a deregulation of osteoblast, osteoclast, or microenvironment genes in their development and progression. Nevertheless, no focus was already done in the oxygen-modulated environment of those cancers. Our objectives in this study were to determine, first, the presence of hypoxia deregulation in a cohort of pediatric osteosarcomas (pOS at diagnosis) and in 4 PDCLs (patient-derived cell lines from diagnostic samples). For this purpose, we performed CGHarray for 67 samples and a validation by semiquantitative PCR in another cohort of 20 samples. We also explored by immunohistochemistry in 30 tumor specimens protein expressions of key biomarkers from the hypoxic signaling pathway. Those biomarkers were validated and assessed functionally by immunofluorescence and Western blotting in PDCLs and paired xenografts. All those results in the pOS collections were correlated to survivals and response to first-line therapies. Secondly, the role of hypoxia modulation in PDCLs was determined using variations of oxygen levels from 21% to 5% on cell proliferation characteristics and protein parameters. Finally, to understand how the process of hypoxia is a potential target for pOS treatment, we inhibited different targets of the mTor/HIF1alpha pathway in those PDCLs. As expected, the hypoxia signaling pathway was highly expressed in pOS (tumor samples and PDCLs). Several biomarkers (for example, ULK1, USP33, VEGFR2, CCL7, etc.) were overexpressed in specific groups, linking them significantly to prognosis and a response to chemotherapy. Most of them were involved in the metabolism, autophagy, or angiogenic processes. The PDCLs also expressed in vitro and in xenografts several proteins of this hypoxic pathway as in tumors themselves (pS6, phosphor-mTor, pAKT, HIF1alpha, HIF2alpha). The induction of HIF1alpha during oxygen decrease is early and constant in PDCLs. mTor and HIF2alpha were not induced by the variation of oxygen and were constantly expressed in the cells. Surprisingly, most of the PDCLs increase their proliferation rate in hypoxic conditions, but do not change their microscopic aspects. Finally, the inhibition of mTor and HIF1alpha with rapamycine and irinotecan, respectively, decreases the cell proliferation with a complete inhibition of the targets. In conclusion, hypoxia seems to be frequently involved in pOS through different downstream signaling processes and might be a new potential way of treatment. Citation Format: Marina Pierrevelcin, Audrey Grain, Aurelien Tripp, Adeline Obrecht, Benoit Lhermitte, Noelle Weingertner, Nathalie Gaspar, Pascal Villa, Isabelle Lelong-Rebel, Françoise Redini, Monique Dontenwill, Natacha Entz-Werlé. Hypoxia signaling pathway is frequently involved in pediatric osteosarcoma microenvironment, as diagnostic and prognostic biomarkers, but also as new therapeutic targets [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A34.

Introduction A multi-modal analysis approach using desorption electrospray ionization (DESI-MSI) and RNA-Seq can envision a complete metabolic and genetic information from clinical specimens revealing tumour heterogeneity. Coupled with laser capture microdissection (LCM) provides a compelling opportunity for molecular sub-characterizing of the tumour tissues. The envisioned combination analysis raises special requirements, including short LCM time, to prevent RNA degradation during microdissection at room temperature. The isolated RNA must have sufficient quality and quantity to carry out RNA seq for transcriptomics. Objectives The aim of this study was developing a multi-modal analysis protocol obtaining metabolic clusters to get a more in-depth knowledge for tumour-heterogeneity from Patient-derived Xenografts (PDXs) and clinical specimens. Methods PDXs and primary tissue biopsies from patients with Breast cancer were cryosectioned at ten μm and mounted on PEN membrane glass slides, which are unique slides for LASER Capture Microdissection (LDM). The DESI imaging analysis area was obtained line-by-line using the DEFFI sprayer. The analyzed tissue sections were stained with H&E and annotated by a histopathologist to allow the alignment of optical and MSI images. Next, the areas of interest in the same slide were microdissected by Laser Capture Microdissection for LC-MS and RNA-seq (Leica LDM 7000). RNA was isolated with a commercial kit (Qiagen RNeasy Micro Kit). Finally, standardization of RNA quality control was done by the Agilent 2100 Bioanalyzer System and followed by RNA Sequencing. Results Preliminary results showed that the extracted samples from microdissected sections using Laser Capture Microdissected for LC-MS could be used to validate the metabolites and lipids, which already had been imaged by DESI-MSI. These DESI-MSI and LC-MS results, which obtained from specific areas on the tissue sections can be attributed to identifying metabolically different sub-clones in the adjacent tumour sections. The next identification method for sub-cloning is a transcriptomic approach. For the transcriptomic study, the results of Agilent showed that the RNA quality of samples was sufficiently competent to carry out downstream analysis, including RNA seq. RNA seq can identify specific gene expression of the pathways, which are related to the identified metabolic profiling by DESI-MSI and LC-MS. Conclusion: We found that developing a multi-modal analysis protocol coupled to Laser capture microdissection is a promising approach for the identification of metabolic heterogeneity in the cancerous specimens. Citation Format: Emine Kazanc, Evi Karali, Vincen Wu, Paolo Inglese, James McKenzie, Aurelien Tripp, Nikos Koundouros, Thanasis Tsalikis, Hiromi Kudo, George Poulogiannis, Zoltan Takats. A multimodal analysis in breast cancer: Revealing metabolic heterogeneity using DESI-MS imaging with Laser-microdissection coupled transcriptome approach [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-042.