bims-ovdlit 2023-12-10 papers

Issue of 2023‒12‒10
seven papers selected by
Lara Paracchini, Humanitas Research

Sci Transl Med. 2023 Dec 06. 15(725): eadi2556

Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer.

TOWARDS group

Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic TP53 mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.

DOI: https://doi.org/10.1126/scitranslmed.adi2556

medRxiv. 2023 Nov 23. pii: 2023.11.22.23298470. [Epub ahead of print]

A Cellular atlas of the human fallopian tube reveals the metamorphosis of secretory epithelial cells during the menstrual cycle and menopause.

M Weigert, Y Li, L Zhu, H Eckart, P Bajwa, R Krishnan, S Ackroyd, R R Lastra, A Bilecz, A Basu, E Lengyel, M Chen.

The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.Graphical summary: Graphical summary of results. During the proliferative phase (estrogen high ) of the menstrual cycle, SE2 cells (OVGP1 + ) dominate the fallopian tube (FT) epithelium, while SE1 cells (OVGP1 - ) dominate the epithelium during the secretory phase. Though estrogen levels decrease during menopause, SE post-cells (OVGP1 + , CXCL2 + ) make up most of the FT epithelium.

DOI: https://doi.org/10.1101/2023.11.22.23298470

Clin Cancer Res. 2023 Dec 01.

Aneuploidy Landscape in Precursors of Ovarian Cancer.

Yeh Wang, Christopher Douville, Yen-Wei Chien, Brant G Wang, Chi-Long Chen, Andre Pinto, Saron Ann Smith, Ronny Drapkin, M Herman Chui, Tricia Numan, Russell Vang, Nickolas Papadopoulos, Tian-Li Wang, Ie-Ming Shih.

PURPOSE: Serous tubal intraepithelial carcinoma(STIC) is now recognized as the main precursor of ovarian high-grade serous carcinoma(HGSC). Other potential tubal lesions include p53 signatures and tubal intraepithelial lesions. We aimed to investigate the extent and pattern of aneuploidy in these epithelial lesions and HGSC to define the features that characterize stages of tumor initiation and progression.EXPERIMENTAL DESIGN: We applied RealSeqS to compare genome-wide aneuploidy patterns among the precursors, HGSC(cases, n=85), and histologically unremarkable fallopian tube epithelium(HU-FTE, control, n=65). Based on a discovery set(n=67), we developed an aneuploidy-based algorithm, REAL-FAST, to correlate the molecular data with pathology diagnoses. We validated the result in an independent validation set(n=83) to determine its performance. We correlated the molecularly defined precursor subgroups with proliferative activity and histology.
RESULTS: We found nearly all p53 signatures lost the entire Chr17, offering a "two-hit" mechanism involving both TP53 and BRCA1 in BRCA1 germline mutation carriers. Proliferatively active STICs harbor gains of 19q12(CCNE1), 19q13.2, 8q24(MYC), or 8q arm, while proliferatively dormant STICs show 22q loss. REAL-FAST classified HU-FTE and STICs into 5 clusters and identified a STIC subgroup harboring unique aneuploidy that is associated with increased proliferation and discohesive growth. Based on a validation set, REAL-FAST showed 95.8% sensitivity and 97.1% specificity in detecting STIC/HGSC.
CONCLUSIONS: Morphologically similar STICs are molecularly distinct. The REAL-FAST assay identifies a potentially "aggressive" STIC subgroup harboring unique DNA aneuploidy that is associated with increased cellular proliferation and discohesive growth. REAL-FAST offers a highly reproducible adjunct technique to assist the diagnosis of STICs.

DOI: https://doi.org/10.1158/1078-0432.CCR-23-0932

Fertil Steril. 2023 Dec 01. pii: S0015-0282(23)02027-7. [Epub ahead of print]

Complications following Opportunistic Salpingectomy compared to Tubal Ligation at cesarean delivery: A retrospective cohort study.

Khaye Gerazel A Rufin, Helena Abreu do Valle, Jessica N McAlpine, Chelsea Elwood, Gillian E Hanley.

OBJECTIVE: To compare peri- and post-operative complications in people undergoing opportunistic salpingectomy (the removal of fallopian tubes for ovarian cancer risk reduction during another surgery; herein referred to as salpingectomy) at time of cesarean delivery to those undergoing tubal ligation.DESIGN: A retrospective population-based cohort study.
SUBJECTS: 18,184 patients were included of which 8,440 underwent salpingectomy and 9,744 had tubal ligation.
EXPOSURE: Patients undergoing salpingectomy during a cesarean delivery were compared to patients undergoing tubal ligation during a cesarean delivery.
MAIN OUTCOME MEASURES: We examined 1) perioperative outcomes, including operating time, length of hospital stay, surgical complications such as infections, anemia, incision complications, injury to a pelvic organ, or operating room return, 2) post-operative complications, including physician visits for a post-operative infection, or visits that resulted in ultrasounds or labs, and hospital readmissions in the 6 weeks post-discharge, and 3) the likelihood to fill a prescription for antibiotics or prescription analgesics.
RESULTS: The salpingectomy group had decreased odds of perioperative complications versus tubal ligation patients (adjusted odds ratio, 0.77; 95% confidence interval 0.61-0.99). There were no increased risks for physician visits for surgical infection, surgical complication, or hospital readmissions in the 6 weeks after hospital discharge among those who had a salpingectomy. People who had a salpingectomy had 18% increased odds of filling a nonsteroidal anti-inflammatory and 23% increased odds of filling opioids prescriptions (adjusted odds ratio, 1.18; 95% confidence interval 1.07-1.28, and adjusted odds ratio, 1.23%; 95% confidence interval 1.12-1.35, respectively).
CONCLUSION: In this population-based, real-world study of salpingectomy at cesarean section, we report decreased perioperative complications and no difference in post-operative complications between people who underwent salpingectomy and people who underwent tubal ligation. Salpingectomy patients had an increased likelihood of filling a prescription for nonsteroidal anti-inflammatory and opioids in the 6 weeks following hospital discharge. This result should be interpreted with caution as we do not have data on over the counter medication use, and thus not all prescription analgesics were captured in our data. Our data suggest that salpingectomy following cesarean delivery is a safe way to provide effective contraception and ovarian cancer risk-reduction.

Keywords: ovarian cancer; permanent contraception; population-based; safety outcomes; sterilization

DOI: https://doi.org/10.1016/j.fertnstert.2023.11.031

Eur Radiol Exp. 2023 Dec 07. 7(1): 77

Deep learning-based segmentation of multisite disease in ovarian cancer.

PURPOSE: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.METHODS: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.
RESULTS: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10-7, 3 × 10-4, 4 × 10-2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10-3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.
CONCLUSION: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.
RELEVANCE STATEMENT: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.
KEY POINTS: • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines.

Keywords: Deep learning; Omentum; Ovarian Neoplasms; Pelvis; Tomography (x-ray computed)

DOI: https://doi.org/10.1186/s41747-023-00388-z

Nat Methods. 2023 Dec 04.

Modeling fragment counts improves single-cell ATAC-seq analysis.

Laura D Martens, David S Fischer, Vicente A Yépez, Fabian J Theis, Julien Gagneur.

Single-cell ATAC sequencing coverage in regulatory regions is typically binarized as an indicator of open chromatin. Here we show that binarization is an unnecessary step that neither improves goodness of fit, clustering, cell type identification nor batch integration. Fragment counts, but not read counts, should instead be modeled, which preserves quantitative regulatory information. These results have immediate implications for single-cell ATAC sequencing analysis.

DOI: https://doi.org/10.1038/s41592-023-02112-6