Ask about this productRelated genes to: CD171 antibody
- Gene:
- L1CAM NIH gene
- Name:
- L1 cell adhesion molecule
- Previous symbol:
- HSAS1, SPG1, HSAS, MASA, MIC5, S10
- Synonyms:
- CD171
- Chromosome:
- Xq28
- Locus Type:
- gene with protein product
- Date approved:
- 1989-06-30
- Date modifiied:
- 2019-04-23
Related products to: CD171 antibody
Related articles to: CD171 antibody
- Birt-Hogg-Dubé (BHD) syndrome is an autosomal dominant disorder caused by germline inactivation of the folliculin gene (FLCN). Approximately 25% of BHD syndrome patients are diagnosed with renal tumors, which can be multifocal and/or bilateral. These tumors have been reported to span a broad histologic spectrum; however, the majority exhibit a distinctive histology characterized by intermingled cytologic features similar to that seen in oncocytoma and chromophobe renal cell carcinoma. Accordingly, such tumors were previously termed 'hybrid oncocytic chromophobe tumor' (HOCT). To date, most studies have characterized tumors arising in BHD syndrome patients without molecular confirmation of FLCN biallelic inactivation; accordingly, the clinicopathologic characterization of molecularly confirmed FLCN biallelic inactivated tumors remains limited. This study evaluates a multi-institutional cohort of 18 renal tumors from different individuals, including integrated histologic, immunohistochemical, and targeted next-generation sequencing analyses. While all patients exhibited clinical characteristics raising suspicion for BHD syndrome, germline status was not available in 5 patients. Nevertheless, molecular analysis demonstrated findings supportive of FLCN biallelic inactivation in all patients, and there were no other candidate driver alterations or recurrent molecular findings. Histologically, most tumors showed 'conventional' histology consisting of solid or nested growth with a characteristic mosaic population of eosinophilic and clear cells and low-grade nuclear features, including frequent perinuclear halos and binucleation. Two cases showed 'non-conventional' histology including tubulocystic and tubulopapillary architecture. Immunohistochemistry revealed consistent GPNMB expression and a distinctive mosaic staining pattern for KRT7, L1CAM, and GATA3, aiding distinction from other eosinophilic renal neoplasms. Follow-up was available for 17 patients (median 37 months, range 1-110 months). Both patients with non-conventional morphology demonstrated advanced stage at presentation, including one with metastatic disease. Collectively, these findings define one of the largest molecularly-confirmed cohorts of FLCN biallelic inactivated tumors to date and support recognition of FLCN-driven tumors as a distinct, molecularly defined entity. - Source: PubMed
Publication date: 2026/05/21
Siegmund Stephanie EWobker Sara EHarik Lara RTretiakova MariaKandukuri ShivaniTrpkov KirilMaclean FionaOdintsov IgorAlchoueiry MichelAron ManjuPicken Maria MMahlow JonathonAdeniran Adebowale JHumphrey Peter AMoch HolgerTsai HarrisonHenske Elizabeth PHirsch Michelle S - Pathological α-synuclein aggregates are key finding of synucleinopathies, including Parkinson's disease (PD), dementia with Lewy bodies, and multiple system atrophy. The Real-Time Quaking-Induced Conversion (RT-QuIC) assay using cerebrospinal fluid (CSF) can sensitively detect pathological α-syn aggregates with strong biologic rationale. Because of limitation by the invasive nature of CSF collection, blood-based RT-QuIC assay is now attended with small evidence and showed good performance discriminating PD and control. This study investigated pathological α-syn aggregates using the neuronal extracellular vesicles (nEVs) from serum in patients with synucleinopathies, and healthy controls (HC). - Source: PubMed
Publication date: 2026/05/20
Choi Hye JoungKo Dong GyunYu JeKukThanh Nguyen Thi HaiMa Hyeo-IlKim Young Eun - Race, ethnicity, and geography can impact cancer management, genomics and outcomes. We aimed to determine the ethnic and geographic diversity of endometrial carcinoma (EC) patients in our province and their impact on molecular subtype and outcomes. - Source: PubMed
Publication date: 2026/05/15
Jamieson AmyKwon JessicaGao TinaLee JessicaLeung SamuelChiu DerekTalhouk AlineCochrane Dawn RMcAlpine Jessica N - Current post-treatment surveillance strategies for endometrial cancer rely predominantly on clinical stage and histological grade, without integration of molecular tumor biology. Molecular classification has revealed profound biological heterogeneity across endometrial cancer subtypes, including differences in recurrence patterns, prognosis, and treatment responsiveness, yet surveillance strategies have not been systematically adapted to reflect this heterogeneity. To propose a biology-driven surveillance framework for endometrial cancer that integrates molecular subtype, clinicopathological risk factors, and recurrence phenotype. This narrative review and conceptual framework synthesizes evidence from cohort studies, molecular classification analyses, international guidelines, and the literature addressing recurrence patterns and treatment responsiveness across molecular subtypes of endometrial cancer. We propose a three-tier surveillance model stratifying patients into low-, intermediate-, and high-risk groups. The framework integrates molecular subtype with clinicopathological modifiers and expected recurrence phenotype. Within the no specific molecular profile (NSMP) subtype, CTNNB1 mutation status is incorporated as a primary modifier, assigning CTNNB1-mutated tumors to the intermediate-risk group regardless of estrogen receptor (ER) status. In CTNNB1 wild-type NSMP tumors, ER expression functions as a secondary modifier, allowing identification of a biologically low-risk subgroup. L1CAM expression is considered a high-risk modifier within NSMP. The framework also accounts for differences in the therapeutic modifiability of recurrence, including the role of immunotherapy in mismatch repair-deficient tumors. Uniform post-treatment surveillance does not reflect the biological diversity of endometrial cancer. The proposed framework provides a biologically grounded approach to surveillance that aligns follow-up intensity with recurrence phenotype and therapeutic opportunities. This model may serve as a conceptual basis for prospective studies evaluating personalized surveillance strategies in endometrial cancer. - Source: PubMed
Publication date: 2026/04/30
Szatkowski WiktorGlanowska-Nawrat Izabela - Neuro-cancer crosstalk plays an important role in the development and progression of Glioblastoma (GBM), but its specific mechanisms remain incompletely elucidated. This study aims to systematically identify key genes related to neuro-cancer crosstalk in GBM and construct a prognostic risk model through integrating single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and machine learning algorithms. The GSE273274 dataset was obtained from the GEO database for single-cell data analysis to investigate differences in intercellular communication. GBM transcriptomic data were obtained from TCGA and GTEx databases for differential expression analysis, and WGCNA was used to identify co-expressed gene modules. LASSO Cox regression was employed to screen out key prognostic genes and construct a prognostic risk model. Immune infiltration, drug sensitivity analysis and molecular docking validation were conducted. Finally, the expression of key genes was validated through immunohistochemistry experiments. Single-cell analysis identified 15 cell types and revealed significantly elevated proportions of CD44+ astrocytes and oligodendrocyte progenitor cells in the GC group. Intercellular communication analysis showed key COL6A2-GP6 and L1CAM-ERBB3 interactions between pericytes and mature excitatory neurons. Transcriptomic analysis identified 6680 differentially expressed genes and 8636 WGCNA hub genes. Integrated analysis identified 7 key neuro-cancer crosstalk genes, among which NGFR and L1CAM were further selected to construct the prognostic risk model. This model demonstrated good predictive performance in both training and validation sets. Immune infiltration analysis showed significantly elevated M0 macrophage proportions in the high-risk group. GSEA analysis revealed enrichment of axon guidance and RAS-ERK signaling pathways in the high-risk group. Drug sensitivity analysis identified betamethasone acetate as a potential therapeutic agent, and molecular docking showed good binding capacity with L1CAM and NGFR. Immunohistochemistry confirmed high NGFR expression and low L1CAM expression in GBM. This study identified NGFR and L1CAM as potential key genes associated with neuro-cancer crosstalk in GBM through multi-omics integrated analysis, and demonstrated that the constructed prognostic risk model has utility for medium- to long-term survival prediction. The research findings provide new perspectives for understanding the mechanisms of neuro-cancer crosstalk in GBM and offer important theoretical foundations and potential targets for developing personalized treatment strategies. - Source: PubMed
Publication date: 2026/05/12
Zeng LinLi DingjunDu MengyuWu TaoLiao YunHuang YuxingLiao Xingyu