Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.
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http://dx.doi.org/10.3390/ijms25158044 | DOI Listing |
World J Urol
January 2025
Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Propose: This study aimed to evaluate the efficacy and safety of neoadjuvant treatment of darolutamide, a next-generation androgen receptor inhibitor, plus androgen deprivation therapy (ADT) for patients with locally advanced prostate cancer (LAPC).
Methods: This single-arm, multicenter, open-label phase II trial (ClinicalTrials.gov: NCT05249712, 2022-01-01), recruited 30 localized high-risk/very high-risk prostate cancer (HRPCa/VHRPCa) patients from three centers in China between 2021 and 2023.
Mikrochim Acta
January 2025
Department of Pulmonary and Critical Care Medicine, Quzhou People's Hospital, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, 324000, China.
A smartphone-integrated colorimetric sensor is introduced for the rapid detection of phenolic compounds, including 8-hydroquinone (HQ), p-nitrophenol (NP), and catechol (CC). This sensor relies on the peroxidase-mimicking activity of aspartate-based metal-organic frameworks (MOFs) such as Cu-Asp, Ce-Asp, and Cu/Ce-Asp. These MOFs facilitate the oxidation of a colorless substrate, 3,3',5,5'-tetramethylbenzidine (TMB), by reactive oxygen species (ROS) derived from hydrogen peroxide (HO), resulting in the formation of blue-colored oxidized TMB (ox-TMB).
View Article and Find Full Text PDFArch Toxicol
January 2025
School of Chemistry and Chemical Engineering, Guangxi University, Nanning, Guangxi, 530004, People's Republic of China.
Over the past decade, fentanyl-type new psychoactive substances (F-NPS) have emerged as the most representative synthetic opioids in third-generation drugs. These substances are characterized by their "low" fatal dose and parent drug levels in biological matrices, "fast" rates of derivatization and metabolism, and "many" derivatization sites and analogs. The low levels of parent fentanyl NPS in biological matrices complicate their detection, necessitating the use of characteristic metabolites as biomarkers for forensic analysis.
View Article and Find Full Text PDFTech Coloproctol
January 2025
Department of Surgical Sciences, University of Turin, Turin, Italy.
Introduction: Anorectal melanoma (ARM) is rare and highly lethal neoplasm. It has a poorer prognosis compared with cutaneous ones. Sentinel lymph node biopsy (SLNB) has become the preferred method of nodal staging method for cutaneous melanoma.
View Article and Find Full Text PDFEpilepsia
January 2025
Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.
Objective: Somatic variants causing epilepsy are challenging to detect, as they are only present in a subset of brain cells (e.g., mosaic), resulting in low variant allele frequencies.
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