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Simple Summary: High-grade serous ovarian cancer (HGSOC) has a dismal prognosis, but its tumor microenvironment (TME), which impacts disease progression and prognosis, is inadequately mapped. A better understanding of the complexity of the TME requires its characterization with multidimensional approaches that allow for simultaneous identification and categorization of the various cell populations. Here, we have performed in-depth profiling of the cellular TME by merging two high-dimensional single-cell datasets generated by mass cytometry of dissociated tumors, to determine whether combining datasets by the CyTOFmerge algorithm can provide more information on the HGSOC TME than separate dataset analyses. The results confirmed high interpatient heterogeneity and that such merging had the potential for identifying novel combinations of markers expressed on cells of the TME. These hypothesis-generating findings could help identify new combinations of expressed antigens and lead to improved mapping of the HGSOC TME and enhanced response to therapy. The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer screening participation is suboptimal in most settings. We assessed whether human papillomavirus (HPV) self-sampling may increase screening participation among long-term non-attenders in Norway.Methods: A pragmatic randomised controlled trial with participation as the primary outcome was initiated in the national cervical screening programme in March 2019. A random sample of 6000 women aged 35-69 years who had not attended screening for at least 10 years were randomised 1:1:1 to receive either (i) a reminder to attend regular screening (control), (ii) an offer to order a self-sampling kit (opt-in) for HPV testing or (iii) a self-sampling kit unsolicited (send-to-all) for HPV testing.Results: Total participation was 4.8%, 17.0% and 27.7% among control, opt-in and send-to-all (P < 0.0001; participation difference (%) send-to-all vs. control: 22.9 (95%CI: 20.7, 25.2); opt-in vs. control: 12.3 (95%CI: 10.3, 14.2); send-to-all vs. opt-in: 10.7 (95% CI: 8.0, 13.3)). High-risk HPV was detected in 11.5% of self-samples and 9.2% of clinician-collected samples (P = 0.40). Most women (92.5%) who returned a positive self-sample attended the clinic for triage testing. Of the 933 women screened, 33 (3.5%) had CIN2 + (1.1%, 3.7%, 3.8% among control, opt-in, and send-to-all, respectively), and 11 (1.2%) had cervical cancer (0%, 1.2%, 1.3% among control, opt-in, send-to-all, respectively).Conclusion: Opt-in and send-to-all self-sampling increased screening participation among long-term, higher-risk non-attenders.Clinical Trial Registration: ClinicalTrials.gov NCT03873376. [ABSTRACT FROM AUTHOR]

Introduction: Gynecological cancer patients are routinely followed up for five years after primary treatment. However, the value of such follow up has been debated, as retrospective studies indicate that first recurrence is often symptomatic and occurs within two to three years of primary treatment. We prospectively investigated time to first recurrence, symptoms at recurrence, diagnostic procedures, and recurrence treatment in gynecological cancer patients after primary curative treatment.Material and Methods: Clinicians from 21 hospitals in Norway interviewed 680 patients with first recurrence of gynecological cancer (409 ovarian, 213 uterine, and 58 cervical cancer patients) between 2012 and 2016. A standardized questionnaire was used to collect information on self-reported and clinical variables.Results: Within two years of primary treatment, 72% of ovarian, 64% of uterine, and 66% of cervical cancer patients were diagnosed with first recurrence, and 54, 67, and 72%, respectively, had symptomatic recurrence. Of symptomatic patients, 25-50% failed to make an appointment before their next scheduled follow-up visit. Computer tomography was the most common diagnostic procedure (89% of ovarian, 76% of uterine, and 62% of cervical cancer patients), and recurrence treatment in terms of chemotherapy was most frequently planned (86% of ovarian, 46% of uterine, and 62% of cervical cancer patients).Conclusions: A majority of patients experienced symptomatic recurrence, but many patients failed to make an appointment earlier than scheduled. Most first recurrences occurred within two years of primary treatment; the mean annual incidence rate for years 3-5 after primary treatment was <7%. New models for follow up of gynecological cancer patients could be considered. [ABSTRACT FROM AUTHOR]