Gynecologic perivascular epithelioid cell tumors (PEComas): a review of recent evidence.

Gynecologic perivascular epithelioid cell (PEC) tumors, or 'PEComas,' represent a rare and intriguing subset of tumors within the female reproductive tract. This systematic literature review aims to provide an updated understanding of gynecologic PEComas based on available literature and data. Although PEComa is rare, there are varied tumor-site presentations across gynecologic organs, with uterine PEComas being the most prevalent. There is scarce high-quality literature regarding gynecologic PEComa, and studies on malignant PEComa underscore the challenges in diagnosis. Among the diverse mutations, mTOR alterations are the most prominent. Survival analysis reveals a high rate of local recurrence and metastatic disease, which commonly affects the lungs. Treatment strategies are limited, however mTOR inhibitors have pivotal role when indicated and chemotherapy may also be used. with some cases demonstrating promising responses. The paucity of data underscores the need for multicentric studies, an international registry for PEComas, and standardized reporting in case series to enhance clinical and pathological data.

The value of multicenter collaboration in Gynecologic Oncology research.

INTRODUCTION: Canadian gynecological oncology (GYNONC) is constantly evolving. We aim to study the patterns in Canadian GYNONC research using a systematic search approach and bibliometric analysis. EVIDENCE ACQUISITION: We used Web of Science to identify all relevant publications in the field of GYNONC by Canadian. We analyzed bibliometric data obtained from the iCite database. Publications were evaluated for specific characteristics including the province of all co-authors. We compared bibliometric metrics among provinces. EVIDENCE SYNTHESIS: Overall, 1511 publications, published in 138 different journals during 1973-2022 were analyzed. Of those, 23.5% (N.=355) were of interprovincial origin. Interprovincial publications were constantly increasing, now reaching 34.1%. Publications of interprovincial setting had higher RCR, CPY, FCR and NIH percentile scores when compared to any single province (P=0.009, P>0.001, P<0.001, and P<0.001, respectively). The proportion of publications in high impact factor journals were higher in the interprovincial setting: 35 (9.9%) vs. 48 (4.2%), P<0.001. Excluding the interprovincial publications there were 1156 publications. Half of the publications were authored by authors from Ontario (N.=587, 50.6%), 278 (24.1%) by authors from Quebec, and 161 (14.0%) by authors from British Columbia. The mean FCR was higher in British Columbia as compared to Ontario, Quebec and Manitoba (6.0±2.1 vs. 5.3±2.1, 5.3±1.5, and 4.1±3.0 respectively; P=0.006, P=0.034, and 0.037, respectively). Only Ontario, Quebec, British Columbia and Alberta had publications in high impact factor journals, with similar rate (P=0.806). CONCLUSIONS: Interprovincial publications have the highest citation metrics in all domains. This underscores the importance of collaboration for the purpose of impactful research.

Machine learning for prediction of concurrent endometrial carcinoma in patients diagnosed with endometrial intraepithelial neoplasia.

OBJECTIVE: To identify predictive clinico-pathologic factors for concurrent endometrial carcinoma (EC) among patients with endometrial intraepithelial neoplasia (EIN) using machine learning. METHODS: a retrospective analysis of 160 patients with a biopsy proven EIN. We analyzed the performance of multiple machine learning models (n = 48) with different parameters to predict the diagnosis of postoperative EC. The prediction variables included: parity, gestations, sampling method, endometrial thickness, age, body mass index, diabetes, hypertension, serum CA-125, preoperative histology and preoperative hormonal therapy. Python 'sklearn' library was used to train and test the models. The model performance was evaluated by sensitivity, specificity, PPV, NPV and AUC. Five iterations of internal cross-validation were performed, and the mean values were used to compare between the models. RESULTS: Of the 160 women with a preoperative diagnosis of EIN, 37.5% (60) had a post-op diagnosis of EC. In univariable analysis, there were no significant predictors of EIN. For the five best machine learning models, all the models had a high specificity (71%-88%) and a low sensitivity (23%-51%). Logistic regression model had the highest specificity 88%, XG Boost had the highest sensitivity 51%, and the highest positive predictive value 62% and negative predictive value 73%. The highest area under the curve was achieved by the random forest model 0.646. CONCLUSIONS: Even using the most elaborate AI algorithms, it is not possible currently to predict concurrent EC in women with a preoperative diagnosis of EIN. As women with EIN have a high risk of concurrent EC, there may be a value of surgical staging including sentinel lymph node evaluation, to more precisely direct adjuvant treatment in the event EC is identified on final pathology.

The impact of body mass index on robotic surgery outcomes in endometrial cancer.

OBJECTIVES: To compare surgical outcomes of patients with endometrial cancer who underwent robotic surgery across different BMI categories. METHODS: A retrospective study including all consecutive patients with endometrial cancer who underwent robotic surgery at a tertiary cancer center between December 2007 and December 2022. The study analyzed outcome measures, including blood loss, surgical times, length of hospitalization, perioperative complications, and conversion rates with the Kruskal-Wallis test for BMI group differences and the Chi-squared test for associations between categorical variables. RESULTS: A total of 1329 patients with endometrial cancer were included in the study. Patients were stratified by BMI: <30.0 (n = 576; 43.3%), 30.0-39.9 (n = 449; 33.8%), and ≥ 40.0 (n = 304; 22.9%). There were no significant differences in post-anesthesia care unit (PACU) stay (p = 0.105) and hospital stay (p = 0.497) between the groups. The rate of post-op complications was similar across the groups, ranging from 8.0% to 9.5% (p = 0.761). The rate of conversion to laparotomy was also similar across the groups, ranging from 0.7% to 1.0% (p = 0.885). Women with a BMI ≥40.0 had a non-clinically relevant but greater median estimated blood loss (30 mL vs. 20 mL; p < 0.001) and longer median operating room (OR) time (288 min vs. 270 min; p < 0.001). Within the OR time, the median set-up time was longer for those with a higher BMI (58 min vs. 50 min; p < 0.001). However, skin-to-skin time (209 min vs. 203 min; p = 0.202) and post-op time (14 min vs. 13 min; p = 0.094) were comparable between groups. CONCLUSION: BMI does not affect the peri-operative outcome of patients undergoing robotic staging procedures for endometrial cancer.

The Impact of Intrauterine Manipulators on Outcome and Recurrence Patterns of Endometrial Cancer Patients Undergoing Minimally Invasive Surgery.

Objective: To evaluate the use of manipulators on the outcome of women who had minimally invasive surgery for endometrial cancer. Methods: Retrospective analysis of patients operated with or without an intrauterine manipulator. Results: Six hundred ninety-nine patients were included. The median follow-up was 44 months (range, 29-67). Nineteen (8.8%) patients had positive cytology in the manipulator group versus 21 (4.4%) in the comparison group (p = 0.02). Total recurrence rate was similar between the groups (12.3% vs. 11.9%; p = 0.8). Vaginal vault recurrence was the most common site of recurrence with higher incidence in the manipulator group (4.5% vs. 1.3%; p = 0.007). Subgroup analysis of low-risk patients who did not receive adjuvant treatment showed higher recurrence rate (8.3% vs. 3%; p = 0.023) and worse disease-free survival (p = 0.01) for the manipulator group. After controlling for other variables, the use of a manipulator did not affect the risk of recurrence for the whole cohort (hazard ratio [HR], 1.28; confidence interval [95% CI], 0.7-2.1, p = 0.3) and for the low-risk subgroup of patients who did not receive adjuvant treatment (HR, 2.47; 95% CI, 0.8-7, p = 0.08). Conclusion: The use of a manipulator increases the risk of positive cytology as well as vaginal vault recurrences, but it does not reduce the overall survival of patients.

GD2 and GD3 gangliosides as diagnostic biomarkers for all stages and subtypes of epithelial ovarian cancer.

Background: Ovarian cancer (OC) is the deadliest gynecological cancer, often diagnosed at advanced stages. A fast and accurate diagnostic method for early-stage OC is needed. The tumor marker gangliosides, GD2 and GD3, exhibit properties that make them ideal potential diagnostic biomarkers, but they have never before been quantified in OC. We investigated the diagnostic utility of GD2 and GD3 for diagnosis of all subtypes and stages of OC. Methods: This retrospective study evaluated GD2 and GD3 expression in biobanked tissue and serum samples from patients with invasive epithelial OC, healthy donors, non-malignant gynecological conditions, and other cancers. GD2 and GD3 levels were evaluated in tissue samples by immunohistochemistry (n=299) and in two cohorts of serum samples by quantitative ELISA. A discovery cohort (n=379) showed feasibility of GD2 and GD3 quantitative ELISA for diagnosing OC, and a subsequent model cohort (n=200) was used to train and cross-validate a diagnostic model. Results: GD2 and GD3 were expressed in tissues of all OC subtypes and FIGO stages but not in surrounding healthy tissue or other controls. In serum, GD2 and GD3 were elevated in patients with OC. A diagnostic model that included serum levels of GD2+GD3+age was superior to the standard of care (CA125, p<0.001) in diagnosing OC and early-stage (I/II) OC. Conclusion: GD2 and GD3 expression was associated with high rates of selectivity and specificity for OC. A diagnostic model combining GD2 and GD3 quantification in serum had diagnostic power for all subtypes and all stages of OC, including early stage. Further research exploring the utility of GD2 and GD3 for diagnosis of OC is warranted.

Alcohol intake and the risk of epithelial ovarian cancer.

PURPOSE: To investigate the association between alcohol intake over the lifetime and the risk of overall, borderline, and invasive ovarian cancer. METHODS: In a population-based case-control study of 495 cases and 902 controls, conducted in Montreal, Canada, average alcohol intake over the lifetime and during specific age periods were computed from a detailed assessment of the intake of beer, red wine, white wine and spirits. Multivariable logistic regression was used to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for the association between alcohol intake and ovarian cancer risk. RESULTS: For each one drink/week increment in average alcohol intake over the lifetime, the adjusted OR (95% CI) was 1.06 (1.01-1.10) for ovarian cancer overall, 1.13 (1.06-1.20) for borderline ovarian cancers and 1.02 (0.97-1.08) for invasive ovarian cancers. This pattern of association was similarly observed for alcohol intake in early (15- < 25 years), mid (25- < 40 years) and late adulthood (≥ 40 years), as well as for the intake of specific alcohol beverages over the lifetime. CONCLUSIONS: Our results support the hypothesis that a higher alcohol intake modestly increases the risk of overall ovarian cancer, and more specifically, borderline tumours.

Endocervical sampling using brush versus curette: a single centre experience and literature review.

Endocervical sampling is performed traditionally with an endocervical curette (ECC). The current study objective is to compare the histopathological performance of endocervical brush (ECB) and endocervical curette (ECC). A retrospective review was performed including patients included that underwent colposcopy with endocervical sampling using either method. A total of 127 samples were obtained with ECC and 98 with ECB. Histopathological diagnosis was obtained in 124 (97.6%) ECC samples and in 94 (95.9%) ECB samples (p = 0.46). The incidence of benign results was similar between ECC and ECB (117 (92.1%) versus 88 (89.8%) respectively (p = 0.28)). When combining information from endocervical sampling with cervical biopsies, the detection rate of high-grade pathologies was similar between the groups with 14 cases (17.7%) for ECC and 8 cases (17.0%) for ECB (p = 0.43). A scope review of the topic was performed, illustrating that studies favour either method. In conclusion, ECB and ECC perform similarly for providing a histopathological diagnosis on endocervical samples.IMPACT STATEMENTWhat is already known on this subject? Endocervical samples in colposcopy were traditionally obtained using an endocervical curette. Similarly, a brush can be used for histological sampling of the endocervical canal. However, it is unclear how the ability to obtain a histopathological diagnosis compares between the two techniques.What do the results of this study add? This single-institution experience with using endocervical brush and curette for endocervical sampling finds that both methods are acceptable and have a high ability to provide a histopathological diagnosis. Precisely, 4.1% of brush and 2.4% of curette samples had insufficient tissue.What are the implications of these findings for clinical practice and further research? The endocervical brush is an adequate sampling method for colposcopy, and can be safely used instead of the curette, based on clinician preference. Further studies could investigate how these methods compare from a patient perspective.

Impact of robotic surgery on patient flow and resource use intensity in ovarian cancer.

There is an emerging focus on the role of robotic surgery in ovarian cancer. To date, the operational and cost implications of the procedure remain unknown. The objective of the current study was to evaluate the impact of integrating minimally invasive robotic surgery on patient flow, resource utilization, and hospital costs associated with the treatment of ovarian cancer during the in-hospital and post-discharge processes. 261 patients operated for the primary treatment of ovarian cancer between January 2006 and November 2014 at a university-affiliated tertiary hospital were included in this study. Outcomes were compared by surgical approach (robotic vs. open surgery) as well as pre- and post-implementation of the robotics platform for use in ovarian cancer. The in-hospital patient flow and number of emergency room visits within 3 months of surgery were evaluated using multi-state Markov models and generalized linear regression models, respectively. Robotic surgery cases were associated with lower rates of postoperative complications, resulted in a more expedited postoperative patient flow (e.g., shorter time in the recovery room, ICU, and inpatient ward), and were between $10,376 and $7,421 less expensive than the average laparotomy, depending on whether or not depreciation and amortization of the robotic platform were included. After discharge, patients who underwent robotic surgery were less likely to return to the ER (IRR 0.42, p = 0.02, and IRR 0.47, p = 0.055, in the univariate and multivariable models, respectively). With appropriate use of the technology, the addition of robotics to the medical armamentarium for the management of ovarian cancer, when clinically feasible, can bring about operational efficiencies and entails cost savings.

Is sentinel lymph node assessment useful in patients with a preoperative diagnosis of endometrial intraepithelial neoplasia?

OBJECTIVE: To determine the prevalence of underlying high-intermediate (high-IM) and high-risk endometrial cancer (EC) in patients with preoperative diagnosis of Endometrial intraepithelial neoplasia (EIN) and to assess the impact of the information retrieved from the sentinel lymph node (SLN) on adjuvant therapy. METHODS: Retrospective cohort study of women undergoing hysterectomy, optional bilateral salpingo-oophorectomy (BSO) and lymph nodes assessment for EIN between December 2007 and August 2021. RESULTS: One hundred and sixty two (162) eligible patients were included, of whom 101 (62.3%) had a final diagnosis of EIN, while 61 (37.7%) were ultimately diagnosed with carcinoma. Out of 15 patients with high-IM to high-risk disease (9.25% of all EIN), 12 had grade 2-3 EC including 8 with >50% myometrial invasion, 2 with serous subtype, 1 with cervical invasion and 2 with pelvic lymph nodes involvement. Of the 3 patients with grade 1 EC, one patient had disease involving the adnexa and 2 patients had tumor invading >50% of the myometrium and with lymphovascular space invasion (LVSI). Ten patients received vaginal brachytherapy after surgery, 3 patients with extrauterine spread were treated with systemic chemotherapy followed by vaginal brachytherapy and pelvic external-beam radiotherapy and 2 patients with early-stage serous carcinoma received chemotherapy followed by vaginal brachytherapy. CONCLUSIONS: Information from SLN, even when negative, can be helpful in the management of patients with EC after preoperative EIN, as some patients are found to have high-IM to high-risk disease on final pathology. These patients would require either re-staging surgery or adjuvant external beam radiotherapy, both could be avoided by proper staging.

Predicting recurrence and recurrence-free survival in high-grade endometrial cancer using machine learning.

OBJECTIVE: To develop machine-learning models to predict recurrence and time-to-recurrence in high-grade endometrial cancer (HGEC) following surgery and tailored adjuvant treatment. METHODS: Data were retrospectively collected across eight Canadian centers including 1237 patients. Four models were trained to predict recurrence: random forests, boosted trees, and two neural networks. Receiver operating characteristic curves were used to select the best model based on the highest area under the curve (AUC). For time to recurrence, we compared random forests and Least Absolute Shrinkage and Selection Operator (LASSO) model to Cox proportional hazards. RESULTS: The random forest was the best model to predict recurrence in HGEC; the AUCs were 85.2%, 74.1%, and 71.8% in the training, validation, and test sets, respectively. The top five predictors were: stage, uterus height, specimen weight, adjuvant chemotherapy, and preoperative histology. Performance increased to 77% and 80% when stratified by Stage III and IV, respectively. For time to recurrence, there was no difference between the LASSO and Cox proportional hazards models (c-index 71%). The random forest had a c-index of 60.5%. CONCLUSIONS: A bootstrap random forest model may be a more accurate technique to predict recurrence in HGEC using multiple clinicopathologic factors. For time to recurrence, machine-learning methods performed similarly to the Cox proportional hazards model.

Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.

DNA repair by homologous recombination (HR) is critical for the maintenance of genome stability. Germline and somatic mutations in HR genes have been associated with an increased risk of developing breast (BC) and ovarian cancers (OvC). However, the extent of factors and pathways that are functionally linked to HR with clinical relevance for BC and OvC remains unclear. To gain a broader understanding of this pathway, we used multi-omics datasets coupled with machine learning to identify genes that are associated with HR and to predict their sub-function. Specifically, we integrated our phylogenetic-based co-evolution approach (CladePP) with 23 distinct genetic and proteomic screens that monitored, directly or indirectly, DNA repair by HR. This omics data integration analysis yielded a new database (HRbase) that contains a list of 464 predictions, including 76 gold standard HR genes. Interestingly, the spliceosome machinery emerged as one major pathway with significant cross-platform interactions with the HR pathway. We functionally validated 6 spliceosome factors, including the RNA helicase SNRNP200 and its co-factor SNW1. Importantly, their RNA expression correlated with BC/OvC patient outcome. Altogether, we identified novel clinically relevant DNA repair factors and delineated their specific sub-function by machine learning. Our results, supported by evolutionary and multi-omics analyses, suggest that the spliceosome machinery plays an important role during the repair of DNA double-strand breaks (DSBs).

Lifetime caffeine intake and the risk of epithelial ovarian cancer.

BACKGROUND: Caffeine intake has been inconsistently associated with the risk of ovarian cancer in previous studies. The measure of caffeine in these studies has not always distinguished between caffeinated and decaffeinated sources, and the time for which intake was assessed was often for late adulthood and thus may have excluded the etiologic window. We investigated lifetime caffeine intake from caffeinated coffee, black tea, green tea and cola sodas in relation to ovarian cancer risk. METHODS: Among 497 cases and 904 controls in a population-based case-control study in Montreal, Canada, lifetime intake of caffeinated coffee, black tea, green tea and cola sodas was assessed and used to calculate lifetime total intake of caffeine. Unconditional multivariable logistic regression was used to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for the association between caffeine intake and ovarian cancer risk overall, as well as by menopausal status. Multivariable polytomous logistic regression was used to estimate the associations for invasive and borderline ovarian cancers separately. RESULTS: Almost all participants (98.4% of cases and 97.5% of controls) had consumed caffeine in their lifetime. The mean (standard deviation) daily consumption of caffeine over the lifetime was of 117 (89) mg/day among cases and 120 (118) mg/day among controls. The OR (95% CI) of ovarian cancer for the highest versus lowest quartile of lifetime caffeine intake was 1.17 (0.83-1.64). According to menopausal status, the OR (95% CI) was 1.56 (0.85-2.86) for premenopausal women and 0.94 (0.66-1.34) for postmenopausal women, comparing the highest to lowest tertiles of intake. Associations for invasive and borderline ovarian cancers separately were similar to that observed for ovarian cancer overall. CONCLUSION: Lifetime caffeine intake was not strongly associated with ovarian cancer risk. A difference in relationship by menopausal status is possible.

Inhibition of Poly ADP-Ribose Glycohydrolase Sensitizes Ovarian Cancer Cells to Poly ADP-Ribose Polymerase Inhibitors and Platinum Agents.

BACKGROUND: Poly ADP-ribose glycohydrolase (PARG) is responsible for the catabolism of PARP-synthesized PAR to free ADP-ribose. Inhibition of PARG leads to DNA repair interruption and consequently induces cell death. This study aims to evaluate the effect of a PARG inhibitor (PARGi) on epithelial ovarian cancer (OC) cell lines, alone and in combination with a PARP inhibitor (PARPi) and/or Cisplatin. METHODS: PARG mRNA levels were studied in three different OC datasets: TCGA, Hendrix, and Meyniel. PARG protein levels were assessed in 100 OC specimens from our bio-bank. The therapeutic efficacy of PARGi was assessed using cell migration and clonogenic formation assays. Flow cytometry was used to evaluate the cell apoptosis rate and the changes in the cell cycle. RESULTS: PARG protein was highly expressed in 34% of the OC tumors and low expression was found in another 9%. Similarly, Hendrix, Meyneil and TCGA databases showed a significant up-regulation in PARG mRNA expression in OC samples as compared to normal tissue (P=0.001, P=0.005, P=0.005, respectively). The use of PARGi leads to decreased cell migration. PARGi in combination with PARPi or Cisplatin induced decreased survival of cells as compared to each drug alone. In the presence of PARPi and Cisplatin, PARG knockdown cell lines showed significant G2/M cell cycle arrest and cell death induction. CONCLUSIONS: PARG inhibition appears as a complementary strategy to PARP inhibition in the treatment of ovarian cancer, especially in the presence of homologous recombination defects.

SMARCA4/2 loss inhibits chemotherapy-induced apoptosis by restricting IP3R3-mediated Ca2+ flux to mitochondria.

Inactivating mutations in SMARCA4 and concurrent epigenetic silencing of SMARCA2 characterize subsets of ovarian and lung cancers. Concomitant loss of these key subunits of SWI/SNF chromatin remodeling complexes in both cancers is associated with chemotherapy resistance and poor prognosis. Here, we discover that SMARCA4/2 loss inhibits chemotherapy-induced apoptosis through disrupting intracellular organelle calcium ion (Ca2+) release in these cancers. By restricting chromatin accessibility to ITPR3, encoding Ca2+ channel IP3R3, SMARCA4/2 deficiency causes reduced IP3R3 expression leading to impaired Ca2+ transfer from the endoplasmic reticulum to mitochondria required for apoptosis induction. Reactivation of SMARCA2 by a histone deacetylase inhibitor rescues IP3R3 expression and enhances cisplatin response in SMARCA4/2-deficient cancer cells both in vitro and in vivo. Our findings elucidate the contribution of SMARCA4/2 to Ca2+-dependent apoptosis induction, which may be exploited to enhance chemotherapy response in SMARCA4/2-deficient cancers.

Scalp cooling for reducing alopecia in gynecology oncology patients treated with dose-dense chemotherapy: A pilot project.

OBJECTIVE: Determine the efficacy of scalp cooling for the prevention of chemotherapy-induced alopecia in gynecology oncology patients. METHODS: This prospective pilot study included patients diagnosed with a gynecological malignancy that received DigniCap™ scalp cooling. Patients were divided into two groups based on chemotherapy regimen: Carboplatin with area under the curve (AUC) 5-6 every three weeks and (1) conventional Paclitaxel 175 mg/m2 every three weeks or (2) Paclitaxel 80 mg/m2 weekly. A 1-10 visual analogue scale (1 no hair loss, 10 - complete hair loss) was used to assess degree of hair loss by patients themselves and by a certified dermatologist using photographs. Changes in quality of life and body image were measured using the European Organization for Research and Treatment of Cancer quality of life questionnaire version 3 (EORTC QLQ-C30) and the Body Image Scale (BIS) for cancer patients. RESULTS: Hair preservation occurred with use of a scalp cooling device for patients receiving weekly Paclitaxel (n = 20), but not conventional every three weeks Paclitaxel (n = 8). Ten of 15 patients (66.7%) in the dose-dense group lost less than 50% of their hair based on self-assessment and 14 of 16 (87.5%) based on dermatologist assessment. No patient in this group acquired a cranial prosthesis (wig). There was no difference between groups in terms of quality of life (QoL) and BIS scores. CONCLUSION: Scalp cooling may allow for hair preservation in gynecology oncology patients receiving Carboplatin AUC 5-6 and weekly Paclitaxel 80 mg/m2 combination chemotherapy.

Identification of Predictive Biomarkers for Lymph Node Involvement in Obese Women With Endometrial Cancer.

Obesity, an established risk factor for endometrial cancer (EC), is also associated to increased risks of intraoperative and postoperative complications. A reliable tool to identify patients at low risk for lymph node (LN) metastasis may allow minimizing the surgical staging and omit lymphadenectomy in obese patients. To identify molecular biomarkers that could predict LN involvement in obese patients with EC we performed gene expression analysis in 549 EC patients using publicly available transcriptomic datasets. Patients were filtrated according to cancer subtype, weight (>30 kg/m2) and LN status. While in the LN+ group, NEB, ANK1, AMIGO2, LZTS1, FKBP5, CHGA, USP32P1, CLIC6, CEMIP, HMCN1 and TNFRSF10C genes were highly expressed; in the LN- group CXCL14, FCN1, EPHX3, DDX11L2, TMEM254, RNF207, LTK, RPL36A, HGAL, B4GALNT4, KLRG1 genes were up-regulated. As a second step, we investigated these genes in our patient cohort of 35 patients (15 LN+ and 20 LN-) and found the same correlation with the in-silico analysis. In addition, immunohistochemical expression was confirmed in the tumor tissue. Altogether, our findings propose a novel panel of genes able to predict LN involvement in obese patients with endometrial cancer.