Skin cutaneous melanoma (SKCM) is the most invasive form of skin cancer with poor prognosis. Growing evidence has demonstrated that tumor immune microenvironment plays a key contributing role in tumorigenesis and predicting clinical outcomes. The aim of this study was to recognize immune classification and a reliable prognostic signature for patients with SKCM. By using single-sample gene set enrichment (ssGSEA) and hierarchical clustering analyses, we evaluated the immune infiltration landscape of SKCM afflicted patients from The Cancer Genome Atlas (TCGA) dataset and named two SKCM subtypes: Immunity-high and Immunity-low. The Immunity-high subgroup was characterized by up-regulation of immune response and favorable survival probability. Seven candidate small molecule drugs which potentially reverse SKCM immune status were identified by using Connectivity map (CMap) database. A prognostic five-immune-associated gene (IAG) signature consisting IFITM1, TNFSF13B, APOBEC3G, CCL8 and KLRK1 with high predictive value was established using the LASSO Cox regression analysis in training set, and validated in testing set as well as Gene Expression Omnibus (GEO) external validation cohort (P < 0.05). Lower tumor purity and active immune-related signaling pathways were obviously presented in low-risk group. Furthermore, a novel composite nomogram based upon the five-IAG signature and other clinical parameters was built with excellent calibration curves. Collectively, comprehensively characterizing the SKCM subtypes based upon immune microenvironment landscape and development of a survival-related IAG signature may provide a promising avenue for improving individualized treatment design and prognosis prediction for patients with SKCM.
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http://dx.doi.org/10.1016/j.intimp.2020.107162 | DOI Listing |
Comb Chem High Throughput Screen
January 2025
Department of Gynecology, Affiliated Xingtai People Hospital of Hebei Medical University, China.
Introduction: Ovarian Cancer (OC) was known for its high mortality rate among gynecological malignancies, often resulting in a poor prognosis. This study sought to identify prognostic necroptosis-related long non-coding RNAs (lncRNAs) (NRlncRNAs) with prognostic potential and to construct a reliable risk prediction model for OC patients.
Method: The transcriptome and clinic data were sourced from TCGA and GTEx databases.
Comb Chem High Throughput Screen
January 2025
Department of Gastroenterology, First Affiliated Hospital of Air Force Medical University, Xi'an, China.
Background: Stomach adenocarcinoma (STAD) is the fifth most common tumor worldwide, imposing a significant disease burden on populations, particularly in Asia. Oxidative stress is well-known to play an essential role in the occurrence and progression of malignancies. Our study aimed to construct a prediction model by exploring the correlation between oxidative stress-related genes and the prognosis of patients with STAD.
View Article and Find Full Text PDFJ Cancer
January 2025
The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.
The ubiquitin-proteasome system influences cancer progression through multiple mechanisms. Due to the extensive proteasomal modifications observed in cancer tissues, ubiquitination is closely related to various biological functions with cancer. However, the roles of ubiquitin-related genes (UbRGs) in breast cancer (BC) have not been thoroughly investigated.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Immunology, Medical School of Nantong University, 19 Qixiu Road, Nantong, 226000, China.
Background: Recent advancements in contemporary therapeutic approaches have increased the survival rates of lung cancer patients; however, the long-term benefits remain constrained, underscoring the pressing need for novel biomarkers. Surfactant-associated 3 (SFTA3), a long non-coding RNA predominantly expressed in normal lung epithelial cells, plays a crucial role in lung development. Nevertheless, its function in lung adenocarcinoma (LUAD) remains inadequately understood.
View Article and Find Full Text PDFCommun Med (Lond)
January 2025
Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Background: Gene signatures derived from transcriptomic-causal networks offer potential for tailoring clinical care in cancer treatment by identifying predictive and prognostic biomarkers. This study aimed to uncover such signatures in metastatic colorectal cancer (CRC) patients to aid treatment decisions.
Methods: We constructed transcriptomic-causal networks and integrated gene interconnectivity into overall survival (OS) analysis to control for confounding genes.
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