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The identification of phenotypic changes in breast cancer (BC) histopathology on account of corresponding molecular changes is of significant clinical importance in predicting disease outcome. One such example is the presence of lymphocytic infiltration (LI) in histopathology, which has been correlated with nodal metastasis and distant recurrence in HER2+ BC patients. In this paper, we present a computer-aided diagnosis (CADx) scheme to automatically detect and grade the extent of LI in digitized HER2+ BC histopathology. Lymphocytes are first automatically detected by a combination of region growing and Markov random field algorithms. Using the centers of individual detected lymphocytes as vertices, three graphs (Voronoi diagram, Delaunay triangulation, and minimum spanning tree) are constructed and a total of 50 image-derived features describing the arrangement of the lymphocytes are extracted from each sample. A nonlinear dimensionality reduction scheme, graph embedding (GE), is then used to project the high-dimensional feature vector into a reduced 3-D embedding space. A support vector machine classifier is used to discriminate samples with high and low LI in the reduced dimensional embedding space. A total of 41 HER2+ hematoxylin-and-eosin-stained images obtained from 12 patients were considered in this study. For more than 100 three-fold cross-validation trials, the architectural feature set successfully distinguished samples of high and low LI levels with a classification accuracy greater than 90%. The popular unsupervised Varma-Zisserman texton-based classification scheme was used for comparison and yielded a classification accuracy of only 60%. Additionally, the projection of the 50 image-derived features for all 41 tissue samples into a reduced dimensional space via GE allowed for the visualization of a smooth manifold that revealed a continuum between low, intermediate, and high levels of LI. Since it is known that extent of LI in BC biopsy specimens is a prognostic indicator, our CADx scheme will potentially help clinicians determine disease outcome and allow them to make better therapy recommendations for patients with HER2+ BC.
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http://dx.doi.org/10.1109/TBME.2009.2035305 | DOI Listing |
Otolaryngol Head Neck Surg
December 2024
Department of Otolaryngology-Head & Neck Surgery, Stanford University School of Medicine, Stanford, California, USA.
Intraepithelial type 1 innate lymphoid cells (ieILC1s) are tissue-resident lymphocytes in the microenvironment of head and neck squamous cell carcinoma. Here, we evaluate how these cells influence T-cell trafficking to tumors. We generated cytotoxic ieILC1-like cells from natural killer (NK) cells in vitro.
View Article and Find Full Text PDFFront Immunol
December 2024
The Catholic University Liver Research Center, Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Republic of Korea, Seoul, Republic of Korea.
Background: Programmed death-ligand 1 (PD-L1) expression is abundant not only in malignant cells but also in infiltrating cells within the tumor microenvironment (TME) of hepatocellular carcinoma (HCC). This study explored the association between PD-L1 expression in TME and outcomes in HCC patients treated with atezolizumab plus bevacizumab (AB), emphasizing the implications of PD-L1 expression in both malignant and tumor-infiltrating cells.
Methods: This study included 72 patients with HCC who underwent percutaneous core needle liver biopsy before AB treatment between September 2020 and December 2023.
J Pathol Inform
January 2025
U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD, United States of America.
Objective: With the increasing energy surrounding the development of artificial intelligence and machine learning (AI/ML) models, the use of the same external validation dataset by various developers allows for a direct comparison of model performance. Through our High Throughput Truthing project, we are creating a validation dataset for AI/ML models trained in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple negative breast cancer (TNBC).
Materials And Methods: We obtained clinical metadata for hematoxylin and eosin-stained glass slides and corresponding scanned whole slide images (WSIs) of TNBC core biopsies from two US academic medical centers.
Acta Biomater
December 2024
Department of Pharmaceutics, School of Pharmacy, Qingdao University, Qingdao 266021, China. Electronic address:
Platinum (Pt)-based anticancer agents exhibit a lack of selectivity in the treatment of osteosarcoma, resulting in significant toxicity. Furthermore, immune surveillance withinthe tumor microenvironment impedes the uptake of platinum drugs by osteosarcoma cells. To overcome these challenges, an oxaliplatin-based Pt prodrug amphiphile (Lipo-OXA-ALN) was designed and synthesized by incorporatingan osteosarcoma-targeting alendronate (ALN) alongside a lipid tail.
View Article and Find Full Text PDFElife
December 2024
UPMC Hillman Cancer Center, Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, United States.
Immune checkpoint inhibitors (ICIs) and their combination with other therapies such as chemotherapy, fail in most cancer patients. We previously identified the PDZ-LIM domain-containing protein 2 (PDLIM2) as a bona fide tumor suppressor that is repressed in lung cancer to drive cancer and its chemo and immunotherapy resistance, suggesting a new target for lung cancer therapy improvement. In this study, human clinical samples and data were used to investigate genetic and epigenetic changes in lung cancer.
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