OBJECTIVES:To determine if nutritional status effects response to immunotherapy in women with gynecologic malignancies. METHODS:A retrospective chart review was conducted on gynecologic cancer patients who received immunotherapy at a single institution between 2015 and 2022. Immunotherapy included checkpoint inhibitors and tumor vaccines. The prognostic nutritional index (PNI) was calculated from serum albumin levels and total lymphocyte count. PNI values were determined at the beginning of treatment for each patient and assessed for their association with immunotherapy response. Disease control response (DCR) as an outcome of immunotherapy was defined as complete response, partial response, or stable disease. RESULTS:One hundred and ninety-eight patients received immunotherapy (IT) between 2015 and 2022. The gynecological cancers treated were uterine (38%), cervix (32%), ovarian (25%), and vulvar or vaginal (4%) cancers. The mean PNI for responders was higher than the non-responder group (p < 0.05). The AUC value for PNI as a predictor of response was 49. A PNI value of 49 was 43% sensitive and 85% specific for predicting a DCR. In Cox proportional hazards analysis, after adjusting for ECOG score and the number of prior chemotherapy lines, severe malnutrition was associated with progression-free survival (PFS) (HR = 1.85, p = 0.08) and overall survival (OS) (HR = 3.82, p < 0.001). Patients with PNI < 49 were at a higher risk of IT failure (HR = 2.24, p = 0.0001) and subsequent death (HR = 2.84, p = 9 × 10-5). CONCLUSIONS:PNI can be a prognostic marker to predict response rates of patients with gynecologic cancers treated with immunotherapy. Additional studies needed to understand the mechanistic role of malnutrition in immunotherapy response.

Checkpoint inhibitors are increasingly used to treat patients with gynecologic malignancies and can cause rare and unusual side effects, also known as immunotoxicities, that are rarely observed in patients receiving traditional immunotherapy. If these are not identified and treated, they can cause disability and even death for patients undergoing treatment. This report describes the range of pembrolizumab-induced myasthenia gravis (MG) immunotoxicity through two cases. The first patient is an 85-year-old woman with recurrent vulvar carcinoma who completed two cycles of pembrolizumab. She had a severe presentation leading to respiratory failure. The second patient is an 80-year-old woman with recurrent serous endometrial carcinoma who developed isolated ocular myasthenia after her second cycle of pembrolizumab. The symptoms and physical examination findings described here illustrate the breadth of symptom severity associated with pembrolizumab-induced MG and importance of early identification and treatment to minimize symptoms and improve outcomes.

To investigate if inflammatory biomarkers can predict the prognosis of patients in remission with platinum-sensitive high-grade serous ovarian cancer.

To compare mutational targets in serous, carcinosarcoma, and clear cell uterine cancers. Genetic information was extracted from the Cancer Genome Atlas (TCGA) and AACR GENIE using CBioPortal of primary tumor specimens. The mutation status of the 64 genes corresponding to receiving the following targeted therapies: HER2/neu inhibitors, checkpoint inhibitors, PARP inhibitors, tyrosine kinase inhibitors (TKIs), CDK4/6 inhibitors, mTOR inhibitors, and BRAF inhibitors. Differences in mutations between histologies were analyzed using Fisher's exact test with adjustment for multiple comparisons. Of 995 endometrial cancers, 551 (55%) were serous, 358 (36%) carcinosarcoma, and 86 (9%) were clear cell. Overall, 232 (23.3%) had actionable mutations. Of these, 201 (87%) had 1 mutation, 27 (12%) had 2 mutations, and 4 (1%) had 3 mutations. Based on mutations, the most common targeted agents included trastuzumab (HER2/neu; 9.9%), PARP inhibitors (6.7%), TKIs (4.4%), CDK4/6 inhibitors (2.5%), mTOR inhibitors (1.8%), checkpoint inhibitors (1.0%), and BRAF inhibitors (0.4%). Based on histology, serous, carcinosarcoma, and clear cell cancers had comparable targetable mutations (22.9%, 22.9%, 27.9% P = 0.56). When considering serous histologies, 11.6% would qualify for HER2/neu inhibitors compared to 7.8% of carcinosarcoma and 8.1% of clear cell (P = 0.16). When considering clear cell cancers, 17.4% qualify for PARP inhibitors compared to 6% in serous and 5.3% in carcinosarcoma (P = 0.001). Clear cell histology also had slightly higher eligibility for checkpoint inhibitors (2.3%) compared to 0.7% in serous and 1.1% in carcinosarcoma (P = 0.27). Serous, carcinosarcoma, and clear cell cancers had comparable rates of mutations for TKIs, CDK4/6, mTOR, and BRAF (P = 0.37, 0.49, 0.158, 0.52, respectively). Over 20% of high-risk uterine cancers have targetable mutations, with HER2/neu inhibitors and PARP inhibitors being the most common. Unlike endometrioid histology, the role of immunotherapy may have limited utility. Future studies should further investigate the molecular landscape of these high-risk cancers.

This study aimed to determine and compare the survival of patients having targetable mutations in endometrial cancer. The mutation status of 64 genes corresponding to targeted treatments and their associated survival information was extracted from the Cancer Genome Atlas (TCGA) using CBioPortal. These genes correspond to treatment with Parp inhibitors, Checkpoint inhibitors, BRAF inhibitors, CDK4/6 inhibitors, HER2/neu inhibitors, and Kinase inhibitors. Progression-free survival (PFS) was assessed using Cox proportional hazards and Kaplan Meier curves. P-values for individual genes were after adjustment for multiple comparisons. Of 534 endometrial cancer tumors, 399 (75.0%) were endometrioid, 128 (20%) were serous (20%), and 27 (5%) were carcinosarcoma. Of these patients, 248 (46.4%) had a targetable mutation. Compared to those without a targetable mutation, those with molecular mutations had an improved progression-free survival (PFS) (HR: 0.65, 95% CI: 0.45–0.93, P = 0.02). When considering targets for individual agents, those qualifying for PARP inhibitors (HR: 0.29, 95% CI: 0.13–0.63, P < 0.001) or checkpoint inhibitors (HR: 0.27, 95% CI: 0.25–0.78, P = 0.01) had improved PFS compared to those without a qualifying mutation in the respective targets. Mutations in genes associated with eligibility for BRAF, CDK 4/6, Her2/neu, or Kinase inhibitors were not associated with prognosis. When considering individual genes, a mutation in RFC4 (n = 17) was associated with a 5-yr PFS of 100% compared to 66% if no mutation was present. In a separate analysis of mutations of unknown significance, there was a PFS benefit if a mutation was present in 11 different genes: ATM, ATR, BRCA2, KIT, MET, MSH2, MTOR, POLD1, POLE, RAF1, and RFC4 (P adjusted all <0.05). In patients with high-grade endometrioid, serous, or carcinosarcoma histologies, ATM (HR: 0.27), BRCA2 (HR: 0.17), KIT (HR: 0.10), MET (HR: 0.12), MSH2 (HR: 0.15), MTOR (HR: 0.11), and POLE (HR: 0.28) mutations remained associated with PFS (p adjusted all <0.05). There were no recurrences in patients who had a RAF1 or RFC4 mutation (5-year PFS 100%, HR: <0.001) in this high-risk population. Endometrial cancers with genetic mutations targetable for PARP inhibitors and checkpoint inhibitors have an improved PFS. Mutations of unknown significance may provide additional targets in these cancers.

To evaluate the new FIGO 2021 vulvar staging system reliability estimating prognosis for patients with advanced-stage vulvar cancer. An examination of the National Cancer Database (NCDB) identified patients from 2000 to 2019 with stage III and IV squamous cell carcinoma, basal cell carcinoma, and carcinoma NOS. Patients were assigned a stage based on both FIGO 2009 and FIGO 2021 staging systems. The NCDB database included both FIGO 2009 and AJCC/TNM staging methods. Patients were categorized using the FIGO 2021 system, including the AJCC/TNM components. Overall survival (OS) was the primary endpoint. Secondary endpoints included an analysis of stage migration between the 2009 and 2021 FIGO staging systems. Kaplan-Meier estimates were used to generate survival probabilities. Log-rank analysis was used to test differences between groups with stage migration. The analysis identified 2506 patients with stage III and IV vulvar cancer. The mean age of the cohort was 67 years old, with 89% White, 7.5% Black, and the remainder of others. Squamous cell carcinoma comprised 98% of the cases, with 38% grade 2, 27% positive for LVSI, and an average tumor size was 4.8 cm. Chemotherapy was administered to 45% of patients, and 67% received radiation. Immunotherapy was received by <1% of patients. Stage migration was identified between stages IIIA to IIIB, IIIB to IIIA, and IVA to IIIA (FIGO 2009 to 2021, respectively). There was no difference in stage assignment for patients with stage IIIB and stage IVB vulvar cancer. Restaging did occur in 335 (16%) patients; 327 patients changed from stage IVA to IIIA, and 40 patients migrated from stage IIIB to IIIA between the 2009 and 2021 staging criteria, respectively. Median OS for patients restaged from stage IVA to IIIA increased from 40 to 150 months (P < 0.001). Reassignment of patients from stage IVA to stage IIIA vulvar cancer, based on the FIGO 2021 staging system, indicate significant improvement in predicting OS in patients with advanced-stage vulvar cancer. These results support the change in stage assignment using the 2021 FIGO vulvar staging system.

OBJECTIVE:To determine if inflammatory biomarkers can predict the long-term outcome of platinum therapy in patients with high-grade serous ovarian cancer. METHODS:Women diagnosed with high-grade serous epithelial ovarian cancer (n = 70) at a single institution were enrolled in a prospective serum collection study between 2005 and 2020. Seventeen markers of inflammation and oxidative stress were measured in serum samples on a chemistry analyzer. Association was tested for serum levels with progression-free survival (PFS), time to recurrence (TTR), overall survival (OS), and time to death (TTD) using Cox proportional hazards and Kaplan-Meier curves. Patient survival was censored at 10 years. RESULTS:Higher serum levels of LDH were associated with worse PFS (HR 2.57, p = 0.028). High serum levels of BAP (HR 0.38, p = 0.025), GSP (HR 0.40, p = 0.040), HDL-c (HR 0.27, p = 0.002), and MG (HR 0.36, p = 0.017) were associated with improved PFS. Higher expression of LDH was associated with worse OS (HR 2.16, p = 0.023). Higher levels of CK.nac (HR 0.39, p = 0.033) and HDL-c (HR 0.35, p = 0.029) were associated with improved OS. Similar outcomes were found with TTR and TTD analyses. CONCLUSION:General inflammatory biomarkers may serve as a guide for prognosis and treatment benefit. Future studies needed to further define their role in predicting prognosis or how these markers may affect response to therapy.

In ovarian cancer, there is no current method to accurately predict recurrence after a complete response to chemotherapy. Here, we develop a machine learning risk score using serum proteomics for the prediction of early recurrence of ovarian cancer after initial treatment. The developed risk score was validated in an independent cohort with serum collected prospectively during the remission period. In the discovery cohort, patients scored as low-risk had a median time to recurrence (TTR) that was not reached at 10 years compared to 10.5 months (HR 4.66, p < 0.001) in high-risk patients. In the validation cohort, low-risk patients had a median TTR which was not reached compared to 4.7 months in high-risk patients (HR 4.67, p = 0.009). In advanced-stage patients with a CA125 < 10, low-risk patients had a median TTR of 68 months compared to 6 months in high-risk patients (HR 2.91, p = 0.02). The developed risk score was capable of distinguishing the duration of remission in ovarian cancer patients. This score may help guide maintenance therapy and develop innovative treatments in patients at risk at high-risk of recurrence.