bims-ovdlit 2024-12-22 papers

J Surg Oncol. 2024 Dec 17.

Patient and Surgeon Attitudes Toward Opportunistic Salpingectomy During Nongynecological Surgeries for the Prevention of Ovarian Cancer: A Qualitative Study.

Carly C Tymm, Reena M Vattakalam, David R Flum, Jason D Wright, Katherine N Fischkoff.

BACKGROUND AND OBJECTIVES: Opportunity salpingectomy (OS), or prophylactic removal of the fallopian tubes during an operation for another indication, is broadly accepted as a risk-reduction strategy for ovarian cancer during gynecological operations. However, OS during nongynecological abdominal surgery is rare in the United States. A better understanding of surgeon and patient attitudes and perceived barriers to OS during nongynecological surgeries may facilitate implementation in the United States.
STUDY DESIGN: Qualitative interviews were conducted with general surgeons (n = 10), gynecologic surgeons (n = 10), and patients (n = 20) to assess perspectives and barriers towards OS during nongynecological surgeries. Interviews were transcribed and inductive analysis was carried out to identify themes and categorize responses using NVivo data analysis software.
RESULTS: OS during nongynecological surgery was viewed favorably by most patients and surgeons interviewed. While patients emphasized the importance of raising awareness of OS, both subsets of surgeons highlighted coordination, counseling, and billing barriers that would need to be overcome for efficient implementation.
CONCLUSION: OS was positively accepted by both patients and surgeons in our cohort. Improved attention to the shared barriers to implementation from our study may facilitate OS implementation during nongynecological surgery in the United States.

Keywords: cancer risk reduction; opportunistic salpingectomy; ovarian cancer

DOI: https://doi.org/10.1002/jso.28050

Cancer Discov. 2024 Dec 20.

Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma.

High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer.

DOI: https://doi.org/10.1158/2159-8290.CD-24-1366

Genome Med. 2024 Dec 18. 16(1): 145

Patterns of genomic instability in > 2000 patients with ovarian cancer across six clinical trials evaluating olaparib.

BACKGROUND: The introduction of poly(ADP-ribose) polymerase (PARP) inhibitors represented a paradigm shift in the treatment of ovarian cancer. Genomic data from patients with high-grade ovarian cancer in six phase II/III trials involving the PARP inhibitor olaparib were analyzed to better understand patterns and potential causes of genomic instability.
PATIENTS AND METHODS: Homologous recombination deficiency (HRD) was assessed in 2147 tumor samples from SOLO1, PAOLA-1, Study 19, SOLO2, OPINION, and LIGHT using next-generation sequencing technology. Genomic instability scores (GIS) were assessed in BRCA1 and/or BRCA2 (BRCA)-mutated (BRCAm), non-BRCA homologous recombination repair-mutated (non-BRCA HRRm), and non-HRRm tumors.
RESULTS: BRCAm was identified in 1021/2147 (47.6%) tumors. BRCAm tumors had significantly higher GIS than non-BRCAm tumors (P < 0.001) and high biallelic loss (815/838; 97.3%) regardless of germline (658/672; 97.9%) or somatic (101/108; 93.5%) BRCAm status. In non-BRCA HRRm tumors (n = 121) a similar proportion were HRD-positive (GIS ≥ 42: 55/121; 45.5%) relative to HRD-negative (GIS < 42: 52/121; 43.0%). GIS was highly variable in non-BRCA HRRm (median 42 [interquartile range (IQR) 29-58]) and non-HRRm (n = 1005; median 32 [IQR 20-55]) tumors. Gene mutations with high GIS included HRR genes BRIP1 (median 46 [IQR 41-58]), RAD51C (median 58 [IQR 48-66]), RAD51D (median 62 [IQR 54-69]), and PALB2 (median 64 [IQR 58-74]), and non-HRR genes NF1 (median 49 [IQR 25-60]) and RB1 (median 55 [IQR 30-71]). CCNE1-amplified and PIK3CA-mutated tumors had low GIS (CCNE1-amplified: median 24 [IQR 18-29]; PIK3CA-mutated: median 32 [IQR 14-52]) and were predominantly non-BRCAm.
CONCLUSIONS: These analyses provide valuable insight into patterns of genomic instability and potential drivers of HRD, besides BRCAm, in ovarian cancer and will help guide future research into the potential clinical effectiveness of anti-cancer treatments in ovarian cancer, including PARP inhibitors as well as other precision oncology agents.
TRIAL REGISTRATION: The SOLO1 trial was registered at ClinicalTrials.gov (NCT01844986) on April 30, 2013; the PAOLA-1 trial was registered at ClinicalTrials.gov (NCT02477644) on June 18, 2015 (retrospectively registered); Study 19 was registered at ClinicalTrials.gov (NCT00753545) on September 12, 2008 (retrospectively registered); the SOLO2 trial was registered at ClinicalTrials.gov (NCT01874353) on June 7, 2013; the OPINION trial was registered at ClinicalTrials.gov (NCT03402841) on January 3, 2018; the LIGHT trial was registered at ClinicalTrials.gov (NCT02983799) on November 4, 2016.

Keywords: Genomic instability; Olaparib; Ovarian cancer; Translational research

DOI: https://doi.org/10.1186/s13073-024-01413-5

Gigascience. 2024 Jan 02. pii: giae102. [Epub ahead of print]13

cfDNA UniFlow: a unified preprocessing pipeline for cell-free DNA data from liquid biopsies.

Sebastian Röner, Lea Burkard, Michael R Speicher, Martin Kircher.

BACKGROUND: Cell-free DNA (cfDNA), a broadly applicable biomarker commonly sourced from urine or blood, is extensively used for research and diagnostic applications. In various settings, genetic and epigenetic information is derived from cfDNA. However, a unified framework for its processing is lacking, limiting the universal application of innovative analysis strategies and the joining of data sets.
FINDINGS: Here, we describe cfDNA UniFlow, a unified, standardized, and ready-to-use workflow for processing cfDNA samples. The workflow is written in Snakemake and can be scaled from stand-alone computers to cluster environments. It includes methods for processing raw genome sequencing data as well as specialized approaches for correcting sequencing errors, filtering, and quality control. Sophisticated methods for detecting copy number alterations and estimating and correcting GC-related biases are readily incorporated. Furthermore, it includes methods for extracting, normalizing, and visualizing coverage signals around user-defined regions in case-control settings. Ultimately, all results and metrics are aggregated in a unified report, enabling easy access to a wide variety of information for further research and downstream analysis.
CONCLUSIONS: We provide an automated pipeline for processing cell-free DNA sampled from liquid biopsies, including a wide variety of additional functionalities like bias correction and signal extraction. With our focus on scalability and extensibility, we provide a foundation for future cfDNA research and faster clinical applications. The source code and extensive documentation are available on our GitHub repository (https://github.com/kircherlab/cfDNA-UniFlow).

Keywords: cancer detection; cell-free DNA; liquid biopsies; sequence analysis; workflow

DOI: https://doi.org/10.1093/gigascience/giae102

Nat Cancer. 2024 Dec 17.

The 2024 generation.

Shruthy Suresh Aggarwal, Cristina Andreani, Zihou Deng, Julia Frede, Polina Kameneva, Marta Kovatcheva, Goran Micevic, Fay Nicolson, Jens Puschhof, Morgan Roberts, Gang Wang, Dionysios C Watson.

DOI: https://doi.org/10.1038/s43018-024-00866-2