Occupational exposure to pesticides and endometrial cancer in the Screenwide case-control study.

BACKGROUND: Endometrial cancer is the most common gynaecological tumour in developed countries and disease burden is expected to increase over the years. Identifying modifiable risk factors may help developing strategies to reduce the expected increasing incidence of these neoplasms. OBJECTIVE: This study evaluates the association between occupational exposure to pesticides and endometrial cancer using data from a recent case-control study in Spain. METHODS: The analyses included data from 174 consecutive incident endometrial cancer cases and 216 hospital controls frequency-matched by age. Data were collected through structured epidemiological questionnaires and exposure to pesticides was assessed using a Spanish job-exposure matrix (MatEmESp). RESULTS: Overall, 12% of controls and 18% of cases were occupationally exposed to pesticides. We observed a positive association between occupational exposure to pesticides and endometrial cancer (OR = 2.08; 95% CI = 1.13-3.88 compared to non-exposed). In general, exposures that occurred farther in the past were significantly associated with endometrial cancer. Exposure to insecticides, fungicides and herbicides were positively associated with endometrial cancer (OR = 2.08; 95% CI = 1.13-3.88, OR = 4.40; 95% CI = 1.65-13.33, and OR = 5.25; 95% CI = 1.84-17.67, respectively). The agricultural, poultry and livestock activities scenario was associated with endometrial cancer (OR = 4.16; 95% CI = 1.59-12.32), while the cleaning exposure scenario was not (OR = 1.22; 95% CI = 0.55-2.67). CONCLUSIONS: Assessment of occupational exposure to pesticides assessed using a Spanish job-exposure matrix revealed a positive association with endometrial cancer. The elucidation of the role of pesticide compounds on endometrial cancer should shed a light on the aetiology of this tumour.

Evaluation of Somatic Mutations in Urine Samples as a Noninvasive Method for the Detection and Molecular Classification of Endometrial Cancer.

PURPOSE: Current diagnostic methods for endometrial cancer lack specificity, leading to many women undergoing invasive procedures. The aim of this study was to evaluate somatic mutations in urine to accurately discriminate patients with endometrial cancer from controls. EXPERIMENTAL DESIGN: Overall, 72 samples were analyzed using next-generation sequencing (NGS) with molecular identifiers targeting 47 genes. We evaluated urine supernatant samples from women with endometrial cancer (n = 19) and age-matched controls (n = 20). Cell pellets from urine and plasma samples from seven cases were sequenced; further, we also evaluated paired tumor samples from all cases. Finally, immunohistochemical markers for molecular profiling were evaluated in all tumor samples. RESULTS: Overall, we were able to identify mutations in DNA from urine supernatant samples in 100% of endometrial cancers. In contrast, only one control (5%) showed variants at a variant allele frequency (VAF) ≥ 2% in the urine supernatant samples. The molecular classification obtained by using tumor samples and urine samples showed good agreement. Analyses in paired samples revealed a higher number of mutations and VAF in urine supernatants than in urine cell pellets and blood samples. CONCLUSIONS: Evaluation of somatic mutations using urine samples may offer a user-friendly and reliable tool for endometrial cancer detection and molecular classification. The diagnostic performance for endometrial cancer detection was very high, and cases could be molecularly classified using these noninvasive and self-collected samples. Additional multicenter evaluations using larger sample sizes are needed to validate the results and understand the potential of urine samples for the early detection and prognosis of endometrial cancer.

Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer.

BACKGROUND: The incidence of endometrial cancer is increasing worldwide. While delays in diagnosis reduce survival, case molecular misclassification might be associated with under- and over-treatment. The objective of this study was to evaluate genetic alterations to detect and molecularly classify cases of endometrial cancer using non-invasive samples. METHODS: Consecutive patients with incident endometrial cancer (N = 139) and controls (N = 107) from a recent Spanish case-control study were included in this analysis. Overall, 339 cervicovaginal samples (out of which 228 were clinician-collected and 111 were self-collected) were analysed using a test based on next-generation sequencing (NGS), which targets 47 genes. Immunohistochemical markers were evaluated in 133 tumour samples. A total of 159 samples were used to train the detection algorithm and 180 samples were used for validation. FINDINGS: Overall, 73% (N = 94 out of 129 clinician-collected samples, and N = 66 out of 90 self-collected samples) of endometrial cancer cases had detectable mutations in clinician-collected and self-collected samples, while the specificity was 80% (79/99) for clinician-collected samples and 90% (19/21) for self-collected samples. The molecular classifications obtained using tumour samples and non-invasive gynaecologic samples in our study showed moderate-to-good agreement. The molecular classification of cases of endometrial cancer into four groups using NGS of both clinician-collected and self-collected cervicovaginal samples yielded significant differences in disease-free survival. The cases with mutations in POLE had an excellent prognosis, whereas the cases with TP53 mutations had the poorest clinical outcome, which is consistent with the data on tumour samples. INTERPRETATION: This study classified endometrial cancer cases into four molecular groups based on the analysis of cervicovaginal samples that showed significant differences in disease-free survival. The molecular classification of endometrial cancer in non-invasive samples may improve patient care and survival by indicating the early need for aggressive surgery, as well as reducing referrals to highly specialized hospitals in cancers with good prognosis. Validation in independent sets will confirm the potential for molecular classification in non-invasive samples. FUNDING: This study was funded by a competitive grant from Instituto de Salud Carlos III through the projects PI19/01835, PI23/00790, and FI20/00031, CIBERESP CB06/02/0073 and CIBERONC CB16/12/00231, CB16/12/00234 (Co-funded by European Regional Development Fund. ERDF: A way to build Europe). Samples and data were provided by Biobank HUB-ICO-IDIBELL, integrated into the Spanish Biobank Network, and funded by the Instituto de Salud Carlos III (PT20/00171) and by Xarxa de Bancs de Tumors de Catalunya (XBTC) sponsored by Pla Director d'Oncologia de Catalunya. This work was supported in part by the AECC, Grupos estables (GCTRA18014MATI). It also counts with the support of the Secretariat for Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112.