Hypoxia, an important component of the tumor microenvironment, plays a crucial role in the occurrence and progression of cancer. However, to the best of our knowledge, a systematic analysis of a hypoxia-related prognostic signature for breast cancer is lacking and is urgently required. Therefore, in the present study, RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and served as a discovery cohort. Cox proportional hazards regression analysis was performed to construct a 14-gene prognostic signature (PFKL, P4HA2, GRHPR, SDC3, PPP1R15A, SIAH2, NDRG1, BTG1, TPD52, MAFF, ISG20, LALBA, ERRFI1 and VHL). The hypoxia-related signature successfully predicted survival outcomes of the discovery cohort (P<0.001 for the TCGA dataset). Three independent Gene Expression Omnibus databases (GSE10886, GSE20685 and GSE96058) were used as validation cohorts to verify the value of the predictive signature (P=0.007 for GSE10886, P=0.021 for GSE20685, P<0.001 for GSE96058). In the present study, a robust predictive signature was developed for patients with breast cancer, and the findings revealed that the 14-gene hypoxia-related signature could serve as a potential prognostic biomarker for breast cancer.
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http://dx.doi.org/10.3892/ol.2020.11733 | DOI Listing |
Discov Oncol
January 2025
Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
Hematology
December 2025
Department of Hematology, XuChang Central Hospital, XuChang, People's Republic of China.
Introduction: Mitochondria and angiogenesis play key roles in multiple myeloma (MM) development, but their interrelated genes affecting MM prognosis are under-studied.
Methods: We analyzed TCGA_MMRF and GSE4581 datasets to identify four genes - CCNB1, CDC25C, HSP90AA1, and PARP1 - that significantly correlate with MM prognosis, with high expression indicating poor outcomes.
Results: A prognostic signature based on these genes stratified patients into high- and low-risk groups, with the latter showing better survival.
Front Pharmacol
January 2025
Department of Neurological Function Examination, Affiliated Hospital of Hebei University, Baoding, China.
Background: Lower-grade glioma (LGG) exhibits significant heterogeneity in clinical outcomes, and current prognostic markers have limited predictive value. Despite the growing recognition of histone modifications in tumor progression, their role in LGG remains poorly understood. This study aimed to develop a histone modification-based risk signature and investigate its relationship with drug sensitivity to guide personalized treatment strategies.
View Article and Find Full Text PDFEur J Endocrinol
January 2025
Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong, PR China.
Background: Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy with high recurrence rates and poor prognosis. Current prognostic models are inadequate, highlighting the need for innovative diagnostic tools. Pathomics, which utilizes computer algorithms to analyze whole-slide images, offers a promising approach to enhance prognostic models for ACC.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Background: The tumor microenvironment (TME) is integral to tumor progression. However, its prognostic implications and underlying mechanisms in clear cell renal cell carcinoma (ccRCC) are not yet fully elucidated. This study aims to examine the prognostic significance of genes associated with immune-stromal scores and to explore their underlying mechanisms in ccRCC.
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