Ask about this productRelated genes to: SH2D2A antibody
- Gene:
- SH2D2A NIH gene
- Name:
- SH2 domain containing 2A
- Previous symbol:
- -
- Synonyms:
- TSAd, F2771
- Chromosome:
- 1q23.1
- Locus Type:
- gene with protein product
- Date approved:
- 1998-11-19
- Date modifiied:
- 2016-10-05
Related products to: SH2D2A antibody
Related articles to: SH2D2A antibody
- Effective CAR T cell infiltration into solid tumors remains a major barrier to therapy success. Despite their clinical potential, few studies have evaluated phenotypes of CAR T cells successfully invading the tumor mass following infusion. Phenotypic information would enrich our understanding of the mechanisms governing CAR T cell migration into solid tumors. Here we implemented an strategy to identify genes driving L1CAM-CAR T cell migration into a 3D tumor mass. - Source: PubMed
Publication date: 2025/11/27
Andersch LenaGrunewald LauraStecklum MariaKlironomos FilipposHaase KerstinHollek ViolaLam TobiasJung Beate AnahitaWinkler AnikaSchwiebert SilkeAstrahantseff KathyLaunspach MichaelJens MarvinHenssen AntonKloke LutzBlüthgen NilsEggert AngelikaSchulte Johannes HAnders KathleenKünkele Annette - Regulatory T cells (Tregs) have multiple roles in the tumor microenvironment (TME), which maintain a balance between autoimmunity and immunosuppression. This research aimed to investigate the interaction between cancer stemness and Regulatory T cells (Tregs) in the breast cancer tumor immune microenvironment. Breast cancer stemness was calculated using one-class logistic regression. Twelve main cell clusters were identified, and the subsequent three subsets of Regulatory T cells with different differentiation states were identified as being closely related to immune regulation and metabolic pathways. A prognostic risk model including , , , , , , and was generated through the intersection between Regulatory T cell differentiation-related genes and stemness-related genes using LASSO and univariate Cox regression. The patient's total survival times were predicted and validated with AUC of 0.96 and 0.831 in both training and validation sets, respectively; the immunotherapeutic predication efficacy of prognostic signature was confirmed in four ICI RNA-Seq cohorts. Seven drugs, including Ethinyl Estradiol, Epigallocatechin gallate, Cyclosporine, Gentamicin, Doxorubicin, Ivermectin, and Dronabinol for prognostic signature, were screened through molecular docking and found a synergistic effect among drugs with deep learning. Our prognostic signature potentially paves the way for overcoming immune resistance, and blocking the interaction between cancer stemness and Tregs may be a new approach in the treatment of breast cancer. - Source: PubMed
Publication date: 2025/07/21
Gul SaminaPang JianyuChen YongzhiQi QiTang YuhengSun YingjieWang HuiTang WenruZhou Xuhong - Multiple myeloma (MM) progression is driven by immune dysregulation within the tumor microenvironment (TME). However, myeloma-intrinsic mechanisms underlying immune dysfunction remain poorly defined, and current immunotherapies show limited efficacy. Using RNA-seq data from 859 MM patients (MMRF-CoMMpass), we integrated xCELL, CIBERSORT, and ESTIMATE algorithms to deconvolute immune-stromal dynamics. Consensus clustering identified immune subtypes, followed by differential gene analysis and LASSO-Cox regression to construct a prognostic model validated in an independent cohort (GSE19784, N = 328). Immune Subtype Classification: Two subgroups emerged: Multiple myeloma-associated immune-related cluster 1 (N = 482): Immune-dysfunctional TME with Th2 cell enrichment, preadipocyte accumulation, and CXCL family suppression, linked to poor survival (P < 0.001). Multiple myeloma-associated immune-related cluster 2 (N = 377): Immune-active TME with cytotoxic CD8 + T/NK cell infiltration and favorable outcomes. Prognostic Gene Signature: Ten immune-related genes (UBE2T, E2F2, EXO1, SH2D2A, DRP2, WNT9A, SHROOM3, TMC8, CDCA7, and GPR132) predicted survival (The One-year AUC = 0.682 and The Over 5-years AUC = 0.714). We define a myeloma-intrinsic immune classification system and a 10-gene prognostic index, offering a framework for risk-stratified immunotherapy. Integration with flow cytometry could optimize precision treatment in MM. - Source: PubMed
Publication date: 2025/05/05
Fang Chuan-FengLi YanYang ChunFang HuaLi Chen - The vascular endothelial growth factor VEGF drives excessive vascular permeability to cause tissue-damaging oedema in neovascular and inflammatory diseases across multiple organs. Several molecular pathways have been implicated in VEGF-induced hyperpermeability, including binding of the VEGF-activated tyrosine kinase receptor VEGFR2 by the T-cell specific adaptor (TSAd) to recruit a SRC family kinase to induce junction opening between vascular endothelial cells (ECs). Inconsistent with a universal role for TSAd in permeability signalling, immunostaining approaches previously reported TSAd only in dermal and kidney vasculature. To address this discrepancy, we have mined publicly available omics data for expression of TSAd and other permeability-relevant signal transducers in multiple organs affected by VEGF-induced vascular permeability. Unexpectedly, TSAd transcripts were largely absent from EC single cell RNAseq data, whereas transcripts for other permeability-relevant signal transducers were detected readily. TSAd transcripts were also lacking from half of the EC bulk RNAseq datasets examined, and in the remaining datasets appeared at low levels concordant with models of leaky transcription. Epigenomic EC data located the TSAd promoter to closed chromatin in ECs, and mass spectrometry-derived EC proteomes typically lacked TSAd. By suggesting that TSAd is not actively expressed in ECs, our findings imply that TSAd is likely not critical for linking VEGFR2 to downstream signal transducers for EC junction opening. - Source: PubMed
Publication date: 2025/03/13
Brash James TDiez-Pinel GuillermoRinaldi LucaCastellan Raphael F PFantin AlessandroRuhrberg Christiana - T cells are involved in every stage of tumor development and significantly influence the tumor microenvironment (TME). Our objective was to assess T-cell marker gene expression profiles, develop a predictive risk model for human papilloma virus (HPV)-negative oral squamous cell carcinoma (OSCC) utilizing these genes, and examine the correlation between the risk score and the immunotherapy response. - Source: PubMed
Publication date: 2025/01/23
Li ChunyanLv ZengboLi ChongxinYang ShixuanLiu FeinengZhang TengfeiWang LinZhang WenDeng RuoyuXu GuoyuLuo HuanZhao YinhongLv JialingZhang Chao