Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including , , , , , , , , and . The high-RS group had more inflamed immune features, including T and CD4 memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.
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http://dx.doi.org/10.1177/15330338241258570 | DOI Listing |
Curr Opin Crit Care
January 2025
Department of Critical Care Medicine.
Purpose Of Review: Neuroprognostication after acute brain injury (ABI) is complex. In this review, we examine the threats to accurate neuroprognostication, discuss strategies to mitigate the self-fulfilling prophecy, and how to approach the indeterminate prognosis.
Recent Findings: The goal of neuroprognostication is to provide a timely and accurate prediction of a patient's neurologic outcome so treatment can proceed in accordance with a patient's values and preferences.
Ann Hematol
January 2025
Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
In a previous preliminary study, radiomic features from the largest and the hottest lesion in baseline F-FDG PET/CT (bPET/CT) of classical Hodgkin's Lymphoma (cHL) predicted early response-to-treatment and prognosis. Aim of this large retrospectively-validated study is to evaluate the predictive role of two-lesions radiomics in comparison with other clinical and conventional PET/CT models. cHL patients with bPET/CT between 2010 and 2020 were retrospectively included and randomized into training-validation sets.
View Article and Find Full Text PDFBackground: Early identification of massive transfusion (MT) requirement in geriatric patients with severe trauma is challenging. Existing systems for predicting MT need in trauma patients have not been systematically evaluated for their relevance to the geriatric population. This study aimed to evaluate the predictive accuracy of initial vital signs and the Glasgow coma scale (GCS) in geriatric trauma patients for predicting MT.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, 130012 Changchun, China.
Accurate identification of causal genes for cancer prognosis is critical for estimating disease progression and guiding treatment interventions. In this study, we propose CPCG (Cancer Prognosis's Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression's impact on survival with parametric and semiparametric hazard models.
View Article and Find Full Text PDFRadiology
January 2025
From the Department of Radiology, Harbin Medical University Cancer Hospital, Harbin, China (Q.S., P.L., J.Z.); and Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029 (Q.S., P.L., R.Y., D.F.Y., C.I.H.).
Background Angiolymphatic invasion (ALI) is an important prognostic indicator in non-small cell lung cancer (NSCLC). However, few studies focus on radiologic features for predicting ALI in patients with early-stage NSCLCs 30 mm or smaller. Purpose To identify radiologic features for predicting ALI in NSCLCs 30 mm or smaller in maximum diameter.
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