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http://dx.doi.org/10.1016/j.jbspin.2022.105386 | DOI Listing |
Cell Genom
December 2024
Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA. Electronic address:
Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity.
View Article and Find Full Text PDFComput Biol Med
December 2024
Baines Imaging Research Laboratory, London Regional Cancer Program, London Health Sciences Centre, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada; Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada. Electronic address:
Background: A growing body of research is using deep learning to explore the relationship between treatment biomarkers for lung cancer patients and cancer tissue morphology on digitized whole slide images (WSIs) of tumour resections. However, these WSIs typically contain non-cancer tissue, introducing noise during model training. As digital pathology models typically start with splitting WSIs into tiles, we propose a model that can be used to exclude non-cancer tiles from the WSIs of lung squamous cell carcinoma (SqCC) tumours.
View Article and Find Full Text PDFOncol Lett
January 2025
Department of Oncology, Yancheng Tinghu District People's Hospital, Yancheng, Jiangsu 224000, P.R. China.
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Despite continuous development of treatment methods, overall survival rate of liver cancer is low. Transcatheter arterial chemoembolization (TACE) is a first-choice treatment for advanced liver cancer.
View Article and Find Full Text PDFJ Immunother Cancer
November 2024
Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
Background: Neoadjuvant therapy with trastuzumab, pertuzumab and paclitaxel (THP) has significantly improved the prognosis of patients with human epidermal growth factor receptor 2 (HER2) breast cancer (BC). However, there remains a subset of non-responsive patients. Thus, this study sought to identify key regulators of THP neoadjuvant therapy resistance and potential targets to sensitize sensitivity.
View Article and Find Full Text PDFJ Immunother Cancer
November 2024
Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Background: While the prognostic role of tertiary lymphoid structures (TLS) has been well studied in solid cancers, the prevalence and impact of immature precursor lymphoid structures known as lymphoid aggregates (LA) remain unresolved in relation to the disease process. In this study, we examined characteristics and the prognostic utility of LA and TLS status in histological samples from patients with melanoma.
Methods: We assessed The Cancer Genomic Atlas-skin cutaneous melanoma digital slides and melanoma specimens from the University of Pittsburgh for the presence of LA and TLS using H&E staining, multiplex immunofluorescence (mIF) and transcriptomic analyses.
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