bims-ovdlit 2023-08-06 papers

Nat Genet. 2023 Jul 31.

Genome-wide mutation profiles from cell-free DNA for early cancer detection.

DOI: https://doi.org/10.1038/s41588-023-01448-1

Int J Gynecol Cancer. 2023 Aug 04. pii: ijgc-2023-004618. [Epub ahead of print]

Pathological findings and long-term prognosis in Korean BRCA1/2 mutation carriers undergoing risk-reducing salpingo-oophorectomy.

Ok-Ju Kang, Shin-Wha Lee, Ju-Hyun Kim, Jeong-Yeol Park, Dae-Shik Suh, Dae-Yeon Kim, Jong-Hyeok Kim, Yong-Man Kim, Young-Tak Kim.

OBJECTIVE: Our study aimed to evaluate the incidence of pathological findings in asymptomatic Korean patients with BRCA1/2 pathogenic variants who underwent risk-reducing salpingo-oophorectomy and to assess their long-term prognosis.
METHODS: We retrospectively analyzed the medical records of patients with a germinal BRCA1/2 pathologic variant who had undergone risk-reducing salpingo-oophorectomy at Asan Medical Center (Seoul, Korea) between January 2013 and December 2020. All pathologic reports were made based on the sectioning and extensively examining the fimbriated end of the fallopian tube (SEE/FIM) protocol.
RESULTS: Out of 243 patients who underwent risk-reducing salpingo-oophorectomy, 121 (49.8%) had a BRCA1 mutation, 119 (48.9%) had a BRCA2 mutation, and three (1.2%) had both mutations. During the procedure, four (3.3%) patients with a BRCA1 mutation were diagnosed with serous tubal intraepithelial carcinoma (STIC) or serous tubal intraepithelial lesion (STIL), and another four patients (3.3%) were diagnosed with occult cancer despite no evidence of malignancy on preoperative ultrasound. In the BRCA2 mutation group, we found one (0.8%) case of STIC, but no cases of STIL or occult cancer. During the median follow-up period of 98 months (range, 44-104) for STIC and 54 months (range, 52-56) for STIL, none of the patients diagnosed with these precursor lesions developed primary peritoneal carcinomatosis.
CONCLUSIONS: Risk-reducing salpingo-oophorectomy, in asymptomatic Korean patients with BRCA1/2 pathogenic variants, detected ovarian cancer and precursor lesions, including STIC or STIL. Furthermore, our follow-up period did not reveal any instances of primary peritoneal carcinomatosis, suggesting a limited body of evidence supporting the imperative need for adjuvant treatment in patients diagnosed with these precursor lesions during risk-reducing salpingo-oophorectomy.

Keywords: BRCA1 Protein; BRCA2 Protein; Fallopian Tube Neoplasms; Surgery

DOI: https://doi.org/10.1136/ijgc-2023-004618

Front Oncol. 2023 ;13 1181792

An explainable machine learning ensemble model to predict the risk of ovarian cancer in BRCA-mutated patients undergoing risk-reducing salpingo-oophorectomy.

Maria Colomba Comes, Francesca Arezzo, Gennaro Cormio, Samantha Bove, Angela Calabrese, Annarita Fanizzi, Anila Kardhashi, Daniele La Forgia, Francesco Legge, Isabella Romagno, Vera Loizzi, Raffaella Massafra.

Introduction: It has been estimated that 19,880 new cases of ovarian cancer had been diagnosed in 2022. Most epithelial ovarian cancer are sporadic, while in 15%-25% of cases, there is evidence of a familial or inherited component. Approximately 20%-25% of high-grade serous carcinoma cases are caused by germline mutations in the BRCA1 and BRCA2 genes. However, owing to a lack of effective early detection methods, women with BRCA mutations are recommended to undergo bilateral risk-reducing salpingo-oophorectomy (RRSO) after childbearing. Determining the right timing for this procedure is a difficult decision. It is crucial to find a clinical signature to identify high-risk BRCA-mutated patients and determine the appropriate timing for performing RRSO.
Methods: In this work, clinical data referred to a cohort of 184 patients, of whom 7.6% were affected by adnexal tumors including invasive carcinomas and intraepithelial lesions after RSSO has been analyzed. Thus, we proposed an explainable machine learning (ML) ensemble approach using clinical data commonly collected in clinical practice to early identify BRCA-mutated patients at high risk of ovarian cancer and consequentially establish the correct timing for RRSO.
Results: The ensemble model was able to handle imbalanced data achieving an accuracy value of 83.2%, a specificity value of 85.3%, a sensitivity value of 57.1%, a G-mean value of 69.8%, and an AUC value of 71.1%.
Discussion: In agreement with the promising results achieved, the application of suitable ML techniques could play a key role in the definition of a BRCA-mutated patient-centric clinical signature for ovarian cancer risk and consequently personalize the management of these patients. As far as we know, this is the first work addressing this task from an ML perspective.

Keywords: BRCA-mutation; early identification; machine learning; ovarian cancer; risk-reducing salpingo-oophorectomy

DOI: https://doi.org/10.3389/fonc.2023.1181792

Nat Biotechnol. 2023 Aug 03.

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

DOI: https://doi.org/10.1038/s41587-023-01881-x