Ask about this productRelated genes to: HIST1H1C antibody
- Gene:
- HIST1H1C NIH gene
- Name:
- histone cluster 1 H1 family member c
- Previous symbol:
- H1F2
- Synonyms:
- H1.2, H1s-1, H1c
- Chromosome:
- 6p22.2
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-22
- Date modifiied:
- 2016-10-05
Related products to: HIST1H1C antibody
Related articles to: HIST1H1C antibody
- Autoantibodies (AAbs) represent promising biomarkers in cancer. While most AAbs are elevated in cancer, a substantial subset is downregulated, and their diagnostic and prognostic potential remains largely unexplored. Here we used the HuProt protein microarray to identify downregulated AAbs in non-small cell lung cancer (NSCLC) serum. Indirect ELISA quantified serum levels in 781 samples. Ten machine learning algorithms were used to construct diagnostic models. An independent cohort of 353 NSCLC patients was used to assess prognostic value and develop a prognostic model. Six downregulated AAbs were identified, among which five AAbs (anti-HIST1H1B, anti-HIST1H1C, anti-DYDC2, anti-CAMKK2, and anti-GRPEL1) were significantly reduced in NSCLC. The gradient boosting machine (GBM) model showed the best performance for NSCLC and BPNs, with AUCs of 0.869 (95% CI: 0.833-0.905) in the training set and 0.813 (95% CI: 0.745-0.880) in the validation set. For early-stage NSCLC, the model achieved an AUC of 0.809 (95% CI: 0.729-0.890) in the validation set, with a sensitivity of 74.0% and specificity of 81.3%. Multivariate Cox regression identified four AAbs significantly associated with patient prognosis. A prognostic model integrating age and AAb levels demonstrated robust predictive performance for long-term survival (7-year AUC = 0.79). Bioinformatics analyses further supported the relevance of the corresponding genes/proteins of these AAbs to NSCLC outcomes. Overall, our findings demonstrate that downregulated AAbs possess significant diagnostic and prognostic value in NSCLC and may contribute to improved patient management and survival prediction. - Source: PubMed
Publication date: 2026/02/17
Liang YihaoMa HankeSun WenkeChen YingChen FengqiLi YutongOuyang SongyunDai Liping - Despite the high mortality associated with angiosarcoma, its low prevalence has limited sample sizes in prior studies. To address these gaps, we analyzed the AACR Project GENIE registry, a large, multi-institutional database. - Source: PubMed
Publication date: 2025/11/14
Leach EileenJafari AmirTorbenson ElijahHsia BeauTauseef Abubakar - Colorectal cancer (CRC) is among the most common and lethal cancers worldwide. Recent advances in tumor immunotherapy have highlighted the importance of T-cell subsets and the tumor microenvironment (TME) in CRC, both critical for mounting a successful anti-tumor immune response. Thus, there is an urgent need for comprehensive research in these areas to accelerate the development of personalized immunotherapeutic strategies for CRC patients. Therefore, this study aims to explore T-cell heterogeneity, identify characteristic genes, and develop a reliable prognostic model to predict patient outcomes and immunotherapy responses. - Source: PubMed
Publication date: 2025/10/29
Liu PingWang YizhouHuang ShuLuo RuiXie RuihengPeng JieyvWang RuiyuWang PingShi XiaominZhang WeiShi LeiZhou XianTang Xiaowei - Lactylation is increasingly recognized to play a crucial role in human health and diseases. However, its involvement in age-related macular degeneration (AMD) remains largely unclear. - Source: PubMed
Publication date: 2025/01/02
Gui ChenweiGao YanZhang RongZhou Guohong - Allergic rhinitis (AR) is an immunoglobulin E (IgE)-mediated inflammatory disorder. This study attempts to identify AR-related differential expressed genes (DEGs) and determine potential targets for AR. We employed bioinformatics analysis to screen for hub DEGs for AR, and their performances in distinguishing AR were assessed by receiver operating characteristic (ROC) curves. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Western blot was used to quantify Granzyme A (GZMA) in ovalbumin (OVA)-induced AR mice. TNF-α-induced cell model was utilized to assess the role of GZMA in AR, and the effect of GZMA silencing on the JAK2/STAT1 pathway was investigated in TNF-α-induced AR. We identified HIST1H2BD, RPS28, HIST1H1C, MAF, and GZMA as hub genes, all of which exhibited excellent performance in distinguishing between AR and controls (AUC > 0.800). GZMA was highly expressed in AR mice. Silencing GZMA reduced the levels of inflammatory cytokines (IL-6, IL-4 and IL-5), inhibited cell apoptosis and promoted cell proliferation in TNF-α-induced nasal mucosal epithelial cells (MIC-iCell-m024). Overexpression of GZMA exhibited the opposite effects by promoting inflammation and cell apoptosis but inhibiting proliferation. Mechanistically, silencing GZMA inhibited the phosphorylation of JAK2 and STAT1, indicating the suppression of JAK2/STAT1 pathway. This study might share new idea for AR management. - Source: PubMed
Li LinZhang YuhaoWang JingyuanZhang LixiaGao YingJi XiaolinWang TianZhao Fei