Gwenael Ferron

Adjuvant treatment algorithm based on recent ESGO/ESTRO/ESP guidelines for early endometrial carcinoma according to prognostic risk groups

The incidence of endometrial cancer (EC) is unfortunately increasing. Often diagnosis is made at an early stage and surgery is the curative treatment. Nevertheless, adjuvant treatment is proposed to reduce the risk of relapse. This treatment is tailored based on the extent of the disease, such as the presence of distant metastasis, the extent of involvement of adjacent organs or lymph nodes. However, histological parameters such as myometrial invasion, substantial lymphovascular space invasion, invasion of the cervical stroma or tumor grade are also key to selecting adjuvant treatment. The Cancer Genome Atlas (TCGA) project has demonstrated the superiority of molecular classification over histological evaluation in EC to determine the prognosis. The International Federation of Gynecology and Obstetrics 2023 staging for EC is the first staging system that has incorporated molecular biomarkers on top of morpho-histological classification. Currently, all patients should have a molecular profile of their tumor and a lymph node assessment. The landmark treatment of stage I-III ECs is surgery followed by radiotherapy. The European guidelines updated in 2025 has divided EC in 4 risk categories with specific adjuvant treatment. For clinicians, it is seen as a complex landscape from surveillance to chemo-radiotherapy. Therefore, we propose here a practical pocket guideline for adjuvant treatment of early-stage EC patients based on a review of the different clinical trials in the adjuvant setting and on existing guidelines. This pocket guideline may also serve as a base for incorporation of new clinical trials under the RAINBO umbrella research program.

Pocket memo based on the ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma: definition of prognostic risk groups

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.

Intraepithelial tumor-infiltrating lymphocytes shape loco-regional PET/CT spread of locally advanced cervical cancer

Data suggest an association between positron emission tomography/CT (PET/CT) metabolic metrics and tumor microenvironment in several malignancies, and a potential role of PET/CT to monitor response to immunotherapy. To evaluate the correlation between tumor loco-regional extension and tumor-infiltrating lymphocyte infiltration in locally advanced cervical cancer prior to concurrent chemo-radiotherapy.The secondary objective was to assess the association between tumor-infiltrating lymphocytes and PET/CT metabolic metrics. Patients with locally advanced cervical cancer and negative para-aortic extensions on PET/CT were included. Two senior nuclear medicine physicians specializing in gynecologic oncology reviewed all PET/CT exams, and extracted tumor maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis, as well as pelvic lymph node involvement. One senior gynecologic oncology pathologist assessed intraepithelial tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes. Intraepithelial tumor-infiltrating lymphocytes were categorized following previous studies as 1%. The cut-off for stromal tumor-infiltrating lymphocytes was chosen empirically: intermediate 60%. 86 patients were included. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with tumor metabolic metrics. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with maximum standard uptake value (p=0.16), or metabolic tumor volume (p=0.19). Tumors with <1% intraepithelial tumor-infiltrating lymphocytes score were associated with a higher MRI tumor size (≥ median) (63.3% vs 39.3%, p=0.04). Patients with pelvic lymph node uptake were significantly more frequent in patients with high stromal tumor-infiltrating lymphocytes score (≥60%) (61.5% vs 31.7%, p=0.009). Poor or absent intraepithelial tumor-infiltrating lymphocytes were associated with more advanced disease at diagnosis and larger tumor size. Tumor-infiltrating lymphocytes were not associated with tumor metabolic activity. Intraepithelial and stroma tumor-infiltrating lymphocytes are not redundant and should be assessed separately. Further work is needed to evaluate the association between tumor metabolic profile and immune populations, including different T-cell subtypes for patient selection for immunotherapy strategies.

PD-1 blockade restores helper activity of tumor-infiltrating, exhausted PD-1hiCD39+ CD4 T cells

Tumor antigen-specific CD4 T cells accumulate at tumor sites, evoking their involvement in antitumor effector functions in situ. Contrary to CD8 cytotoxic T lymphocyte exhaustion, that of CD4 T cells remains poorly appreciated. Here, using phenotypic, transcriptomic, and functional approaches, we characterized CD4 T cell exhaustion in patients with head and neck, cervical, and ovarian cancer. We identified a CD4 tumor-infiltrating lymphocyte (TIL) population, defined by high PD-1 and CD39 expression, which contained high proportions of cytokine-producing cells, although the quantity of cytokines produced by these cells was low, evoking an exhausted state. Terminal exhaustion of CD4 TILs was instated regardless of TIM-3 expression, suggesting divergence with CD8 T cell exhaustion. scRNA-Seq and further phenotypic analyses uncovered similarities with the CD8 T cell exhaustion program. In particular, PD-1hiCD39+ CD4 TILs expressed the exhaustion transcription factor TOX and the chemokine CXCL13 and were tumor antigen specific. In vitro, PD-1 blockade enhanced CD4 TIL activation, as evidenced by increased CD154 expression and cytokine secretion, leading to improved dendritic cell maturation and consequently higher tumor-specific CD8 T cell proliferation. Our data identify exhausted CD4 TILs as players in responsiveness to immune checkpoint blockade.

CA-125 ELIMination Rate Constant K (KELIM) Is a Marker of Chemosensitivity in Patients with Ovarian Cancer: Results from the Phase II CHIVA Trial

Abstract Purpose: In patients with ovarian cancer receiving neoadjuvant chemotherapy, the first-line treatment success will depend on both the tumor-primary chemosensitivity and the completeness of interval debulking surgery (IDS). The modeled CA-125 ELIMination rate constant K (KELIM), calculated with the CA-125 longitudinal kinetics during the first 100 chemotherapy days, is a validated early marker of tumor chemosensitivity. The objective was to investigate the role of the chemosensitivity relative to the success of first-line medical–surgical treatment. Experimental Design: The CA-125 concentrations were prospectively measured in the randomized phase II trial CHIVA (NCT01583322, carboplatin–paclitaxel regimen ± nintedanib, and IDS, n = 188 patients). The KELIM predictive value regarding the tumor response rate, likelihood of complete IDS, risk of subsequent platinum-resistant relapse (PtRR), progression-free survival (PFS), and overall survival (OS) was assessed using univariate and multivariate tests. Results: The data from 134 patients were analyzed. KELIM was an independent and major predictor of subsequent PtRR risk, and of survivals. The final logistic regression model, including KELIM [OR = 0.13; 95% confidence interval (CI), 0.03–0.49] and complete IDS (no vs. yes, OR = 0.30; 95% CI, 0.11–0.76) highlights the preponderant role of chemosensitivity on the success of the first-line treatment. In patients with highly chemosensitive diseases, the patient prognosis was driven more by the chemotherapy-induced antitumor effects than by the surgery. Conclusions: The tumor-primary chemosensitivity, assessed by the modeled CA-125 KELIM calculated during neoadjuvant chemotherapy (http://www.biomarker-kinetics.org/CA-125-neo), may be a major parameter to consider for decision-making regarding IDS attempt, and selecting patients for treatments meant to reverse the primary chemoresistance. See related commentary by May and Oza, p. 4432

Peritoneal cancer index: laparoscopic evaluation of peritoneal carcinomatosis from gynecological origin

Vulvar and clitoral reconstruction using bilateral Singapore island perforator flap after anterior vulvectomy

The prognostic value of tumor-infiltrating lymphocytes in vulvovaginal melanoma

To assess the relation between immune microenvironment, survival, and clinicopathological characteristics. This study was a retrospective, single-center, observational study. Patients with a vulvovaginal melanoma and available archived material were included. All cases underwent pathology review, tumor-infiltrating lymphocyte quantification, and next-generation sequencing analysis, when feasible. Clinical data included demographic, treatment, and prognostic data. Forty-two patients were selected during the study period, but 13 were finally excluded owing to unavailable formalin-fixed, paraffin-embedded material or unknown follow-up data. Twelve of 19 cases (63.2%) had at least one genetic mutation, 3/18 (16.7%) had BRAF, 3/18 (16.7%) had c-KIT mutation, and 4/17 (23.5%) had NRAS mutations. High stromal tumor-infiltrating lymphocytes were identified in 13/28 patients (46.4%), and brisk tumor-infiltrating lymphocytes in 17/28 patients (60.7%). A density of stromal tumor-infiltrating lymphocytes >40% and brisk distribution were the single clinicopathologic factor associated with increased disease-free survival. The study showed that brisk tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes were a marker for disease progression, and for response to immunotherapy strategies. To validate these findings on a larger scale, further research is warranted through a multicenter study with a larger cohort and additional genetic and translational analysis.

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.