Chronic lymphocytic leukaemia (CLL) is the most common clonal B-cell disorder characterized by clonal diversity, a relapsing and remitting course, and in its aggressive forms remains largely incurable. Current front-line regimes include agents such as fludarabine, which act primarily via the DNA damage response pathway. Key to this is the transcription factor p53. Mutations in the TP53 gene, altering p53 functionality, are associated with genetic instability, and are present in aggressive CLL. Furthermore, the emergence of clonal TP53 mutations in relapsed CLL, refractory to DNA-damaging therapy, suggests that accurate detection of sub-clonal TP53 mutations prior to and during treatment may be indicative of early relapse. In this study, we describe a novel deep sequencing workflow using multiple polymerases to generate sequencing libraries (MuPol-Seq), facilitating accurate detection of TP53 mutations at a frequency as low as 0.3%, in presentation CLL cases tested. As these mutations were mostly clustered within the regions of TP53 encoding DNA-binding domains, essential for DNA contact and structural architecture, they are likely to be of prognostic relevance in disease progression. The workflow described here has the potential to be implemented routinely to identify rare mutations across a range of diseases.
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http://dx.doi.org/10.1038/onc.2016.73 | DOI Listing |
Target Oncol
January 2025
Hematology-Oncology Service, Department of Medicine, Centre hospitalier de l'Université de Montréal (CHUM), 1000, rue Saint-Denis, Montreal, QC, Canada.
Background: BERIL-1 was a randomized phase 2 study that studied paclitaxel with either buparlisib, a pan-class I PIK3 inhibitor, or placebo in patients with recurrent or metastatic (R/M) head and neck squamous cell cancer (HNSCC). Considering the therapeutic paradigm shift with immune checkpoint inhibitors (ICIs) now approved in the first-line setting, we present an updated immunogenomic analysis of patients enrolled in BERIL-1, including patients with immune-infiltrated tumors.
Objective: The objective of this study was to identify biomarkers predictive of treatment efficacy in the context of the post-ICI therapeutic landscape.
Oncol Lett
March 2025
Department of Obstetrics and Gynecology, Mie University School of Medicine, Tsu, Mie 514-8507, Japan.
Ovarian cancer has a poor prognosis, and screening methods have not been established. Biomarkers based on molecular genetic characteristics must be identified to develop diagnostic and therapeutic strategies for all cancer types, particularly ovarian cancer. The present study aimed to evaluate the usefulness of genetic analysis of cervical and endometrial liquid-based cytology (LBC) specimens for detecting somatic mutations in patients with ovarian cancer.
View Article and Find Full Text PDFBlood Res
January 2025
Department of Internal Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan, Korea.
Cancer Med
January 2025
Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT Alliance, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: The 2021 WHO Classification of Central Nervous System Tumors introduces more molecular markers for glioma reclassification, including TERT promoter (TERTp) mutation as a key feature in glioblastoma diagnosis.
Aims: Given the changes in the entities included in each subtype under the new classification, this research investigated the distribution, prognostic value, and correlations with other molecular alterations of TERTp mutation in different subgroups under this latest classification.
Methods: All glioma patients admitted to Peking Union Medical College Hospital for surgical resection or biopsy from 2011 to 2022 were included.
J Surg Oncol
January 2025
Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, USA.
Background: Biliary tract cancers (BTCs) represent distinct biological and genomic entities. Anatomic and geographic heterogeneity in genomic profiling of BTC subtypes, genomic co-alterations, and their impact on long-term outcomes are not well defined.
Methods: Genomic data to characterize alterations among patients with BTCs were derived from the AACR GENIE registry (v15.
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