The identification of circulating biomarkers of early stage malignancy is a critical component of ongoing efforts aimed at reducing the overall public and personal impact of human cancer through early detection. The human immune system is capable of identifying and reporting the presence of tumor-derived factors appearing during the initial events of tumorigenesis with a sensitivity and specificity far beyond currently developed biochemical assays. Tapping into the process of immune surveillance through the identification and evaluation of autoantibodies against tumor-associated antigens (TAAs) represents a promising avenue of biomarker development. Here we review a diverse series of reports describing the use of TAA-specific autoantibodies for the discrimination of cancer from control groups. A description of the major technical platforms being utilized as well as specific innovations implemented for the detection of autoantibody biomarkers is included. This review provides an objective survey of results obtained using individual TAA-specific autoantibodies as well as multi-autoantibody panels in order to identify and assess emerging trends in this field of research. Such trends provide a basis for the discernment of the specific challenges currently facing autoantibody biomarker development, and lay the groundwork for future innovations aimed at overcoming those challenges.
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http://dx.doi.org/10.3233/CBM-2009-0137 | DOI Listing |
Sci Rep
December 2024
Division of Joint Surgery and Sports Medicine, Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
Lines of evidence have indicated that type 2 diabetes mellitus (T2DM) is an independent risk factor for osteoarthritis (OA) progression. However, the study focused on the relationship between T2DM and OA at the transcriptional level remains empty. We downloaded OA- and T2DM-related bulk RNA-sequencing and single-cell RNA sequencing data from the Gene Expression Omnibus (GEO) dataset.
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December 2024
Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, No. 16766, Jingshi Road, Jinan, 250014, Shandong, People's Republic of China.
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.
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December 2024
Department of Agronomy and Plant Breeding, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
Understanding the genetic basis of drought tolerance in safflower (Carthamus tinctorius L.) is essential for developing resilient varieties. In this study, we performed a genome-wide association study (GWAS) using DArTseq markers to identify marker-trait associations (MTAs) linked to drought tolerance across 90 globally diverse safflower genotypes.
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December 2024
Department of Radiology, the Affiliated Taian City Central Hospital of Qingdao University, Tai'an, 271099, China.
This study aimed to investigate the correlation between baseline MRI features and baseline carcinoembryonic antigen (CEA) expression status in rectal cancer patients. A training cohort of 168 rectal cancer patients from Center 1 and an external validation cohort of 75 rectal cancer patients from Center 2 were collected. A nomogram was constructed based on the training cohort and validated using the external validation cohort to predict high baseline CEA expression in rectal cancer patients.
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December 2024
Institute of Agriculture and Life Science, Gyeongsang National University, Jinju, 52828, Republic of Korea.
Heat stress (HS) is an impactful condition in ruminants that negatively affects their physiological and rumen microbial composition. However, a fundamental understanding of metabolomic and metataxonomic mechanisms in goats under HS conditions is lacking. Here, we analyzed the rumen metabolomics, metataxonomics, and serum metabolomics of goats (n = 10, body weight: 41.
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