Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and distinguishing its subtypes holds significant value for diagnosis, treatment, and the prognosis. Unsupervised clustering analysis was conducted to classify HCC subtypes. Subtype signature genes were identified using LASSO, SVM, and logistic regression. Survival-related genes were identified using Cox regression, and their expression and function were validated via qPCR and gene interference. GO, KEGG, GSVA, and GSEA were used to determine enriched signaling pathways. ESTIMATE and CIBERSORT were used to calculate the stromal score, tumor purity, and immune cell infiltration. TIDE was employed to predict the patient response to immunotherapy. Finally, drug sensitivity was analyzed using the oncoPredict algorithm. Two HCC subtypes with different gene expression profiles were identified, where subtype S1 exhibited a significantly shorter survival time. A subtype scoring formula and a nomogram were constructed, both of which showed an excellent predictive performance. COL11A1 and ACTL8 were identified as survival-related genes among the signature genes, and the downregulation of COL11A1 could suppress the invasion and migration of HepG2 cells. Subtype S1 was characterized by the upregulation of pathways related to collagen and the extracellular matrix, as well as downregulation associated with the xenobiotic metabolic process and fatty acid degradation. Subtype S1 showed higher stromal scores, immune scores, and ESTIMATE scores and infiltration of macrophages M0 and plasma cells, as well as lower tumor purity and infiltration of NK cells (resting/activated) and resting mast cells. Subtype S2 was more likely to benefit from immunotherapy. Subtype S1 appeared to be more sensitive to BMS-754807, JQ1, and Axitinib, while subtype S2 was more sensitive to SB505124, Pevonedistat, and Tamoxifen. HCC patients can be classified into two subtypes based on their gene expression profiles, which exhibit distinctions in terms of signaling pathways, the immune microenvironment, and drug sensitivity.
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http://dx.doi.org/10.3390/biomedicines13010236 | DOI Listing |
J Plant Res
January 2025
College of Marine and Biological Engineering, Yancheng Institute of Technology, Yancheng, 224002, Jiangsu, China.
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MOE Key Laboratory of Laser Life Science and Institute of Laser Life Science, Guangdong Provincial Key Laboratory of Laser Life Science, Guangzhou Key Laboratory of Spectral Analysis and Functional Probes, College of Biophotonics, School of Optoelectronic Science and Engineering, South China Normal University, Guangzhou, 510631, China.
The three SDEs of CLas were expressed in citrus leaves by AuNPs-PEI mediated transient expression system, and promoted the proliferation of CLas and inhibited citrus immunity. Huanglongbing (HLB) is the most severe bacterial disease of citrus caused by Candidatus Liberibacter asiaticus (CLas). CLas suppress host immune responses and promote infection by sec-dependent effectors (SDEs), thus insight into HLB pathogenesis is urgently needed to develop effective management strategies.
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January 2025
Department of Oncology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, 210008, Jiangsu, China.
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State Key Laboratory of Crop Genetics and Germplasm Enhancement, Saya Institute of Nanjing Agricultural University, Nanjing Agricultural University, Nanjing, 211800, China.
This study indicated that the CCHC-type zinc finger protein PbrZFP719 involves into self-incompatibility by affecting the levels of reactive oxygen species and cellulose content at the tips of pollen tubes. S-RNase-based self-incompatibility (SI) facilitates cross-pollination and prevents self-pollination, which in turn increases the costs associated with artificial pollination in fruit crops. Self S-RNase exerts its inhibitory effects on pollen tube growth by altering cell structures and components, including reactive oxygen species (ROS) level and cellulose content.
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Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, United States; Department of Surgery, Indiana Center for Regenerative Medicine and Engineering, Indiana University School of Medicine, Indianapolis, IN 46202, United States. Electronic address:
Diabetic wounds are complicated by underlying peripheral vasculopathy. Reliance on vascular endothelial growth factor (VEGF) therapy to improve perfusion makes logical sense, yet clinical study outcomes on rescuing diabetic wound vascularization have yielded disappointing results. Our previous work has identified that low endothelial phospholipase Cγ2 (PLCγ2) expression hinders the therapeutic effect of VEGF on the diabetic ischemic limb.
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