Investigator

Dominique Berton-Rigaud

Institut De Cancrologie De Louest

DBDominique Berton-…
Papers(3)
Dissecting the Origin…Neoadjuvant and adjuv…Spatial Profiling of …
Collaborators(10)
Isabelle Ray-CoquardFlorence JolyGwenael FerronEmilie ThomasEmmanuelle MalaurieEric Pujade LauraineEtienne RouleauFabien CalvoFélix Blanc-DurandFrédéric Selle
Institutions(10)
Institut De Cancrolog…Centre Leon BErardCentre François Bacle…Institut National Pol…Hpital Intercommunal …Arcagy GinecoInstitut Gustave Rous…Centre De Recherche D…Institut Gustave Rous…Groupe Hospitalier Di…

Papers

Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas

Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance: We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.

Neoadjuvant and adjuvant pembrolizumab in advanced high-grade serous carcinoma: the randomized phase II NeoPembrOV clinical trial

AbstractThis open-label, non-comparative, 2:1 randomized, phase II trial (NCT03275506) in women with stage IIIC/IV high-grade serous carcinoma (HGSC) for whom upfront complete resection was unachievable assessed whether adding pembrolizumab (200 mg every 3 weeks) to standard-of-care carboplatin plus paclitaxel yielded a complete resection rate (CRR) of at least 50%. Postoperatively patients continued assigned treatment for a maximum of 2 years. Postoperative bevacizumab was optional. The primary endpoint was independently assessed CRR at interval debulking surgery. Secondary endpoints were Completeness of Cytoreduction Index (CCI) and peritoneal cancer index (PCI) scores, objective and best response rates, progression-free survival, overall survival, safety, postoperative morbidity, and pathological complete response. The CRR in 61 pembrolizumab-treated patients was 74% (one-sided 95% CI = 63%), exceeding the prespecified ≥50% threshold and meeting the primary objective. The CRR without pembrolizumab was 70% (one-sided 95% CI = 54%). In the remaining patients CCI scores were ≥3 in 27% of the standard-of-care group and 18% of the investigational group and CC1 in 3% of the investigational group. PCI score decreased by a mean of 9.6 in the standard-of-care group and 10.2 in the investigational group. Objective response rates were 60% and 72%, respectively, and best overall response rates were 83% and 90%, respectively. Progression-free survival was similar with the two regimens (median 20.8 versus 19.4 months in the standard-of-care versus investigational arms, respectively) but overall survival favored pembrolizumab-containing therapy (median 35.3 versus 49.8 months, respectively). The most common grade ≥3 adverse events with pembrolizumab-containing therapy were anemia during neoadjuvant therapy and infection/fever postoperatively. Pembrolizumab was discontinued prematurely because of adverse events in 23% of pembrolizumab-treated patients. Combining pembrolizumab with neoadjuvant chemotherapy is feasible for HGSC considered not completely resectable; observed activity in some subgroups justifies further evaluation to improve understanding of the role of immunotherapy in HGSC.

Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy

Abstract Purpose: This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes. Experimental Design: Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322). Results: Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent. Conclusions: Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1–resistant malignancy.

3Papers
55Collaborators
Ovarian NeoplasmsNeoplasm StagingTumor MicroenvironmentLymphocytes, Tumor-InfiltratingBiomarkers, TumorHepatitis A Virus Cellular Receptor 2