Research grants in cancer research

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Laureates 2021 - 2022

Olivia LE SAUX


Title of the project: Targeting CD7 loss in T-cell lymphomas with inhibitory chimeric antigen receptor.

Current location: Laboratoire « Molecular mechanisms of hematological disorders and therapeutic implications » du Pr Olivier Hermine, unité Inserm U1163 – Institut Imagine, Paris, France.

Fellowship location: The Michel Sadelain Lab, Immunology Program – Center for Cell Engineering, Memorial Sloan Kettering Cancer Center, New York, USA.

Summary of the project: T-cell lymphomas are rare malignancies, accounting for approximately 15% of the non-Hodgkin lymphomas, that arise from mature T-cells. It is a heterogenous group of distinct entities with regards to their histological pattern, clinical presentation, but most of them share a very aggressive clinical outcome. To date, few therapeutic options have demonstrated their efficacy and innovative strategies are very scarce. Recently, promising results of chimeric antigen receptor (CAR) T-cells for the treatment of B-cell lymphomas have raised tremendous interest, and several studies are now conducted in others hematological malignancies, including T-cell lymphomas. However, development of these adoptive cellular therapies in T-cell lymphomas faces numerous challenges, including CAR-T cell fratricide and T-cell aplasia when targeting a pan-T cell antigen, and one of the main challenges is to narrow T cell specificity against tumor cell only. As many CD4+ T-cell lymphomas exhibit lost expression of the pan-T cell CD7 antigen (approximately 50% of the most frequent T-cell lymphoma sub types), we thought to use this atypical phenotype to distinguish normal T cells (CD4+CD7+) from tumor T cells (CD4+CD7-) through a dual CAR approach in order to mitigate “on target, off tumor” toxicity. We will genetically modify normal T cells to express two CAR receptors, including an activating CD4-directed CD28z CAR that will mediate the anti-tumor activity, and an inhibitory CD7-specific PD-1-based iCAR targeting CD7, that will selectively limit T-cell responsiveness upon CD7 recognition on normal T cells. We will evaluate dual CD4-CD7 CAR-T cells anti-tumor efficacy and selectivity in vitro, using target cell lines, and then in vivo with immunocompromised mice. This innovative strategy might offer a novel curative approach for CD4+CD7- T-cell lymphoma, and regardless of the target, may find broader indications among hematological malignancies and solid tumors.

Olivia LE SAUX

Title of the project: Characterisation of macrophage phenotypic heterogeneity in ovarian carcinoma

Current location: C. Caux Team - CISTAR « Cancer Immune Surveillance and Therapeutic tARgeting » Cancer Research Center Lyon (CRCL), Centre Léon Bérard – Cheney D 3ème étage, 28 rue Laennec - 69373 LYON Cedex 08, France

Fellowship location: Division of Cancer, Department of Surgery and Cancer, Imperial College London, IRDB, Hammersmith Hospital, Du Cane Rd, LONDON W12 ONN

Summary of the project: Tumour-associated macrophages (TAM) are one of the most abundant immune cell type in ovarian carcinoma (OC). It has recently been shown that the peritoneal cavity harbour populations of resident macrophages contrary to what was once believed. These recent advances highlight that TAM require further analysis. The McNeish lab has recently demonstrated that peritoneal resident macrophages are the source of most macrophages within omental metastases in mouse models. Single cell RNAseq analysis of these omental macrophages detected five separate subpopulations with significant differences between genotypes. In this context, the objectives of our project will be to:
- Validate the presence of discrete subpopulations in human OC. I will use imaging mass cytometry to co-stain sections of the BriTROC-1 for approximately 30 proteins, using a combination of Hyperion-validated antibodies and a custom panel of macrophage subtype-specific antibodies.
-Investigate the association of macrophage heterogeneity with tumour genomics and clinical prognosis. In order to do so, I will correlate macrophage phenotype clusters with loss of PTEN, BRCA1/2 mutations, copy number signatures, and overall survival in BriTROC-1 (training cohort) and ICON-8 (validation cohort).
As efficacy of immunotherapy in OC is still modest, a clear understanding of TAM heterogeneity may help identify new therapeutic targets.


Title of the project: Comparaison et prédiction de la radionécrose cérébrale survenant après une réirradiation en photon ou en proton chez des patients atteints d'une récidive locale d'un cancer des voies aérodigestives supérieures ou de la base du crâne

Current location:
Senior Physician – Institut Curie – Centre de Protonthérapie d’Orsay – Head : Prof. Gilles Crehange
PhD Student – Laboratoire d’Imagerie Translationnelle en Oncologie (LITO) – Institut Curie/Inserm UMR 1288 – Head : Dr Irène Buvat

Host laboratory in the USA: Gordon Center for Medical Imaging in Boston (MGH-Harvard Medical School) – Head : Prof. Georges El Fakhri

Summary of the project: Background: The risk of brain radionecrosis (BN) after curative reirradiation (reRT) for a recurrence of head and neck carcinoma (HNC) is frequent and can result in an alteration of patients’ quality of life. The objective of our study is to determine if multimodal imaging, including in room PET-CT, could predict the risk of BN after reRT with X-rays (intensity modulated radiation therapy [IMRT]) or proton therapy (PT). Methods: Ninety patients reirradiated in the department of radiation oncology of the Massachusetts General Hospital (Boston) with IMRT (60) or PT (30) will be including. First, the occurrence, the time of onset, and the precise location of BN assessed on brain MRIs within two years after reRT will be compared between IMRT and PT groups. Second, radiomic analysis of pre-reRT PET and/or MRI will be performed to determine if BN can be predicted before reRT. Finally, a dose-response relationship between the effective dose to the temporal lobe, assessed with in-room PET, and the risk of cerebral RN after PT re-irradiation will be investigated. Expected results: The radiation-induced brain toxicities are expected to be different, for the same deposited dose, between patients treated with proton and photon. It is also expected that radiomics features from multimodal imaging will predict these toxicities. These results are attempted to help the physician to select the best technique for reRT.


Title of the project: PolARI, A synthetic lethality model of Polo-like kinase inhibitor in the treatment of patients with advanced gynecological tumors with ARID1A loss.

Current location: Institut Gustave Roussy, 114 rue Edouard Vaillant, 94800 Villejuif

Fellowship location: National Cancer Institute of Singapore

Summary of the project: Clear-cell carcinomas (CC) are a rare form of endometrial and ovarian cancers in Europe accounting for around 10% of the cases, but surprinsigly, they are one of the most frequent subtype in South-East Asia. They are characterized by an aggressive behavior and chemotherapy resistance, therefore represent an unmet medical need globally. ARID1A is frequently mutated across all tumor type, but, above all, is altered in more than 50% of CC cases and effective strategies targeting this gene are eagerly awaited. The team has recently observed that oxygen consumption of ARID1A-mutated cells is abnormally high making them exquisitely sensitive to PLK1 inhibitors. Based on these observations, we designed a translational research program testing a PLK1 inhibitor in different models of clear-cell carcinomas. Using multiple approaches at a molecular and proteomic levels, this project aims to confirm previous early observations and also characterize potential predictive biomarkers of response and treatment resistance in order to better leverage this drug in treating patients. These efforts may represent the basis for building a clinical trial testing this personalized treatment strategy in CC patients and these results could even be extended to all patients with ARID1A-mutated tumors.


Title of the project: Immune-regulation of castration resistant prostate cancer.

Current location: Laboratoire du Dr Daniel Metzger, Département de génomique fonctionnelle et cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France

Fellowship location: Laboratoire du Pr Mikaël Pittet, Département de pathologie et d’immunologie, AGORA Cancer Center, Swiss Cancer Center Léman, Lausanne, Suisse

Summary of the project: Prostate cancer is the second cause of cancer-related death in men worldwide. Systemic prostate cancer treatment is based on androgen signaling blockade via surgical or chemical castration. However, after a period of sensitivity to the treatment, some tumors develop mechanisms of resistance. For these patients, therapeutic options are limited and the prognosis is poor. Using genetically-engineered mice models that recapitulate many of the features of the human disease, we determined that a transcription factor, plays a key role in the development of castration resistant prostate cancer. Moreover, we discovered that inactivation of this gene in tumoral cells allowsthe activation of immune components with anti-tumoral properties. In collaboration with the Pittet lab, I will determine whether that immune components are directly implicated in the control of the tumor growth. This study should open new avenues to treat castration-resistant prostate cancer.


Title of the project: In vitro modeling and genotype-specific therapeutic targeting of homologous recombination deficiency in human prostate cancer

Current location:
Department of Medical Oncology, University Hospital of Bern , Bern, Switzerland
Department for BioMedical Research, University of Bern, Bern, Switzerland

Fellowship location: Department for BioMedical Research, University of Bern, Bern, Switzerland

Summary of the project: Prostate cancer (PCa) affects 1 out of 8 men and is a leading cause of morbidity and mortality. Alterations in the DNA homologous recombination repair (HRR) pathway are a common molecular feature of metastatic PCa, and many distinct genomic alterations constitute this heterogeneous group of homologous repair deficient tumors. While inhibitors of poly-ADP-ribose polymerase (PARPis) have shown efficacy in BRCA1-, BRCA2-, and a subset of ATM- and PALB2-altered PCas, effective therapeutic strategies for the “non-canonical” HRR genotypes are still lacking. Within this project, we aim to study the consequences of loss of BRIP1, RAD51C, RAD51D, FANCA and CDK12, five “non-canonical” HRR-related genes recurrently altered in PCa. Exploiting CRISPR/Cas9-mediated genome editing, we will individually delete these genes from PCa cell lines and established patient-derived organoids. We will characterize these isogenic HRR-knockout cell lines and organoids by analyzing phenotype, DNA repair strategies, oncogenic signaling, and in vitro growth and invasiveness. To establish novel treatment strategies for these phenotypes, we will perform combination drug testing with established and experimental agents targeting homologous recombination deficiency and associated oncogenic signaling pathways.


Title of the project: Prediction by artificial intelligence of molecular prognostic and theranostic factors in intrahepatic cholangiocarcinoma from histological sections

Current location: Pathology Department, Beaujon Hospital, 100 boulevard du Général Leclerc, 92110, Clichy, France

Fellowship location: Centre for Computational Biology - MINES ParisTech, 60 boulevard Saint-Michel, 75006 Paris, France

Summary of the project: Molecular studies of intrahepatic cholangiocarcinoma (iCCA), a tumour with a poor prognosis, have identified genetic alterations targetable by therapeutics, but this identification currently relies on complex molecular biology techniques. The aim of this project is to use artificial intelligence (AI) to predict the presence of targetable molecular alterations in iCCA from histological sections. We will conduct a two-centre retrospective study comprising a test cohort of 270 samples and a validation cohort of 100 biopsies. Targetable molecular abnormalities will be determined by a targeted NGS approach. AI models will be trained on the test cohort to predict molecular alterations and then validated in the validation cohort. We hope to generate a robust predictive model using an AI approach for targetable molecular alterations from routine histological slides.


Title of the project: Personalized in situ immunotherapy to prevent progression of head and neck cancer

Current location: Service d’ORL et de chirurgie cervico-faciale, Hôpitaux universitaires de Genève, Rue Gabriel Perret-Gentil 4, 1205 Genève

Fellowship location: Laboratoire du Professeur Nicolas Mach, Centre de Recherche Translationnelle en Onco-Hématologie, Centre Médical Universitaire, Rue Michel-Servet 1, 1206 Genève

Summary of the project: Recurrent head and neck squamous cell carcinoma (HNSCC) is a major cause of morbidity, preventing long-term survival of HNSCC patients. Currently, surgery and adjuvant chemo-radiation is the gold standard treatment for advanced HNSCC and is followed by tumor recurrence in more than 50% of the cases. Once tumor has recurred, check-point inhibitors have only a 16 to 22% tumor response rate. We postulate that pre-surgical in situ immunotherapy, delivered through a combination of a single intermediate dose of radiotherapy and peri-tumoral delivery of GM-CSF by myoblasts contained in macro-capsules implanted next to the tumor, will protect patients from cancer recurrences after surgical treatment, through the induction of a loco-regional and systemic immune response. We plan the following in vitro and in vivo steps in our immunocompetent mouse model of head and neck cancer : 1) Engineering of encapsulated myoblasts releasing local and sustained low-doses of GM-CSF 2) Evaluation of the treatment on primary and distant tumor growth in the flank mouse model 3) Evaluation of the effect on post-surgical recurrences in the orthotopic mouse model 4) Characterization of the immune response 5) Molecular characterization of the immune response 5) Functional validation with T cells depleting treatments, immunodeficient mice and antibodies targeting putative molecular targets unveiled by molecular analysis. We expect our findings to provide a “proof of concept” that neoadjuvant in situ immunotherapy can reduce post-surgical loco-regional tumor recurrence and distant metastasis progression. This would offer the opportunity to translate this innovative approach into clinical trials.


Title of the project: Artificial intelligence-based biomarker to predict clinical response to immunotherapy in non-small cell lung carcinoma by combining clinical, radiomics, genomics and immune features.

Current location: Centre Oscar Lambert, Lille, France.

Fellowship location: Laboratoire du Docteur Bertrand Routy, Centre de Recherche du Centre Hospitalier Universitaire de Montréal, Canada

Summary of the project: Lung cancer is the most lethal malignancy in the World. Unfortunately, most patients are initially diagnosed with advanced disease, which makes them not amenable to a curative approach, and only eligible for systemic treatments. In the past few years, treatments targeting the immune system have drastically modified the therapeutic landscape of advanced non-small lung cancer (NSCLC), notably with the use of immune checkpoint inhibitors. These drugs facilitate the recognition of tumor cells by the immune system, enabling immune cells to eliminate them more effectively. However, only 20 to 30% of patients will benefit from this type of treatment: it is therefore critical to accurately identify those who will be susceptible to respond to these expensive treatments. This project aims to develop and validate a clinical tool relying on artificial intelligence technology to generate a model integrating clinical, radiological and molecular data of a patient and his tumor in order to predict the likelihood of treatment response. We have first fully characterized the tumor and the clinical profile of patients treated with ICI after a diagnosis of advanced NSCLC. Parameters from radiologic features, tumor immune microenvironment as well as molecular profile in relation to response to treatment will be analyzed to generate a predictive biomarker algorithm based on artificial intelligence. In the era of precision medicine, this research will allow us not only to improve patient’s management but also to optimize the costs related to these expensive treatments.