CD66c antibody
- Known as:
- CD66c (anti-)
- Catalog number:
- orb100511
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Biorbyt biorb
- Gene target:
- CD66c antibody
Related genes to: CD66c antibody
- Gene:
- CEACAM6 NIH gene
- Name:
- carcinoembryonic antigen related cell adhesion molecule 6
- Previous symbol:
- NCA
- Synonyms:
- CD66c
- Chromosome:
- 19q13.2
- Locus Type:
- gene with protein product
- Date approved:
- 1989-06-30
- Date modifiied:
- 2016-10-05
Related products to: CD66c antibody
Related articles to: CD66c antibody
- Systemic administration of bispecific T‑cell engagers (BiTEs) targeting CEACAM6 has shown therapeutic potential but is limited by on‑target/off‑tumor toxicity and short serum half‑life. To overcome these challenges, we engineered an oncolytic herpes simplex virus (oHSV) that delivers and locally produces anti‑CEACAM6/CD3 BiTE directly within the tumor microenvironment (oHSV‑anti‑CEA6/CD3). In immunocompetent mouse models of colon (CT26) and breast (4T1) cancer, a single intratumoral injection of oHSV‑anti‑CEA6/CD3 promoted tumor regression, increased infiltration of CD8⁺CD44⁺ T cells both locally and systemically, and induced durable antitumor immunity. When combined with PD‑1 blockade, this localized BiTE‑arming strategy synergistically enhanced therapeutic efficacy, leading to superior tumor control and long‑term immunological memory without additional toxicity. Mechanistically, the virus exerts a dual action: direct oncolysis and sustained in situ BiTE production, enabling targeted T‑cell activation and tumor elimination while avoiding systemic BiTE exposure. Unlike previous reports of BiTE‑armed oncolytic viruses or simple combinations with immune checkpoint inhibitors, our approach leverages the oHSV platform to achieve spatiotemporally controlled T‑cell redirection coupled with virus‑mediated innate immune stimulation. This work provides a safe, effective, and readily translatable strategy for solid tumor immunotherapy. - Source: PubMed
Publication date: 2026/08/13
Zhang WeiweiDai ShuangFan HaohanYang NianXu LongLiu ZheranMin YuJiang ZhengZhou LiangxueYang HuiTong AipingPeng Xingchen - Lung cancer continues to be the leading cause of cancer-related deaths worldwide, primarily due to persistent challenges in early detection and the limited effectiveness of precision medicine. Although low-dose computed tomography (CT) has been widely implemented for lung cancer screening and has contributed to a measurable reduction in disease-specific mortality, its diagnostic accuracy is limited by its inability to reliably distinguish benign from malignant pulmonary nodules. Furthermore, the clinical standard for metabolic imagingF-fluorodeoxyglucose (F-FDG) positron emission tomography (PET)is significantly constrained by a high incidence of false-positive findings in patients with inflammatory conditions and frequent false-negative results in tumors exhibiting low glycolytic activity. To overcome these critical limitations, highly specific PET radiotracers have been developed to target immune checkpoints, cell surface receptors, and distinct features of the tumor microenvironment. These molecularly targeted probes offer improved biological specificity, enabling more precise visualization of tumor pathophysiology and supporting applications in early diagnosis, real-time treatment monitoring, and prognostic stratification. This review summarizes recent advances in targeted PET imaging and critically evaluates the potential of integrating these approaches with multimodal imaging, liquid biopsy, and artificial intelligence (AI)-driven radiomics to enhance diagnostic accuracy and inform therapeutic decision-making. By synthesizing key developments from both preclinical studies and clinical trials, we highlight the translational significance and future directions of target-specific PET tracers. Despite existing challenges related to tracer development, regulatory approval, and methodological standardization, the integration of next-generation whole-body PET systems with advanced artificial intelligence algorithms holds considerable promise for establishing molecular-targeted PET as a cornerstone of precision oncology in lung cancer management. - Source: PubMed
Publication date: 2026/02/13
Chen ChongyangPan DonghuiWang XinyuXu YupingYan JunjieWang LizhenYang Min - Background Estrogen receptor-positive (ER+) breast cancer is the most prevalent breast cancer subtype, and tamoxifen remains the cornerstone of adjuvant endocrine therapy. However, a significant proportion of patients eventually develop acquired tamoxifen resistance, leading to disease recurrence and progression. Methodology To characterize the cellular and molecular mechanisms underlying this resistance at single-cell resolution, we performed an integrative analysis of publicly available single-cell RNA sequencing data from 16 ER+ breast cancer specimens, comprising 13 treatment-naive primary tumors and three tamoxifen-resistant recurrent tumors. Following rigorous quality control, batch correction, and dimensionality reduction, we identified 11 major cell populations in the tumor microenvironment. Copy number variation inference using InferCNV was utilized to confirm the malignant identity of the epithelial cells. Results Gene Ontology Biological Process enrichment analysis revealed that recurrent malignant cells were significantly enriched for pathways associated with translation, chromatin remodeling, and cell division compared with primary tumor cells. Sub-clustering of malignant epithelial cells resolved nine distinct subpopulations, among which a GAS5+ (growth arrest-specific 5-positive) subpopulation was markedly expanded in tamoxifen-resistant recurrent tumors. This subpopulation exhibited distinctive metabolic reprogramming characterized by enhanced aerobic respiration and energy metabolism. Monocle2-based pseudotemporal trajectory analysis positioned GAS5+ cells at a terminally differentiated state, likely derived from CLDN3+ and CEACAM6+ tumor progenitor cells. Single-cell regulatory network inference using SCENIC identified SPDEF (SAM pointed domain-containing ETS transcription factor) as a putative key transcription factor specifically active in GAS5+ tumor cells, and SPDEF expression was highly enriched in this subcluster. Validation in The Cancer Genome Atlas breast cancer cohort demonstrated that high SPDEF expression was significantly associated with worse overall survival (log-rank p = 0.011). Conclusions These findings implicate the SPDEF-GAS5+ regulatory axis as a potential driver of tamoxifen resistance and a compelling candidate for future therapeutic targeting in ER+ breast cancer. - Source: PubMed
Publication date: 2026/06/28
Jin WenChen ClaireZhou YanlingWang JingHou RenShi Wen-Jie - Protein glycosylation is a major post-translational modification that regulates tumor initiation and progression; however, its dynamic modeling during multistep evolution of lung adenocarcinoma (LUAD) remains poorly understood, particularly in clinically archived tissues. Here, we established an integrated multi-omics workflow combining global proteomes, N-glycans, and site-specific intact N-glycopeptides to comprehensively characterize glycosylation in formalin-fixed paraffin-embedded (FFPE) specimens spanning four pathological stages of LUAD progression: inflammatory nodules (IN), atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC). Using optimized protein extraction, hydrophilic interaction liquid chromatography (HILIC)-based glycopeptide enrichment, and high-resolution LC-MS/MS, we achieved large-scale identification of proteins, N-glycans, and intact glycopeptides from archival clinical samples. Integrated analyses revealed progressive remodeling of site-specific N-glycosylation during malignant transformation, characterized by increased glycan branching, fucosylation, and sialylation during the transition from premalignant lesions to invasive cancer. Sialylated glycans reached their highest abundance in the premalignant AAH stage, whereas highly branched and fucosylated complex N-glycans predominated in invasive adenocarcinoma, indicating stage-dependent glycan remodeling throughout disease progression. Functional enrichment analyses linked these glycosylation alterations to extracellular matrix organization, neutrophil degranulation, and immune-associated pathways, while representative glycoproteins, including CEACAM6 and FGB, exhibited coordinated changes in protein abundance and site-specific glycoform micro-heterogeneity across pathological stages. Collectively, this study demonstrates the feasibility of deep glycoproteomic profiling using archived FFPE tissues and provides a comprehensive molecular atlas of glycosylation remodeling during LUAD progression. These findings establish a valuable resource for elucidating disease mechanisms and identifying stage-specific glycosylation biomarkers and potential glycan-targeted therapeutic candidates for early lung adenocarcinoma. - Source: PubMed
Publication date: 2026/07/27
Cui JinggangChen YanYue ShuangDeng JianboZhang WenqiWen ShengyeZhao LingboZhang RumengYang ShuangJiang Junhong - Air pollution, such as particulate matter with a diameter of ≤2.5 μm (PM) is a major contributor to lung cancer in the never-smoking population. Anthracotic pigments (black deposits in the lungs) are physical evidence of environmental exposures. While links between anthracosis and lung disease have been established, anthracosis has not been routinely used as a measure of environmental exposure in research, because there is neither a standard quantitative measure of anthracosis nor an efficient method for quantifying it. We developed 'Slide-based methods for High-throughput Anthracosis Detection and Estimation' (SHADE). SHADE is an automated workflow that quantifies anthracotic pigments on scanned images of whole H&E slides. SHADE was optimized to identify anthracosis while avoiding detection of artefacts in images. SHADE scores and manual pathologist rankings of 10-image patches demonstrated high concordance (R = 0.864). Application of SHADE to background lung sections from 140 never-smoking lung cancer patients demonstrated significant associations between high anthracosis and older age, male sex, 30-year residential PM estimates, and birthplace in Asia (p < 0.05). Low anthracosis was associated with less aggressive adenocarcinomas (p = 0.052). No significant relationship was identified between anthracosis and 3-year residential PM estimates, lobe sampled, ethnicity, EGFR mutation status or pathologic tumor stage. Anthracosis levels in the never-smoking cohort were similar to that of background lung sections from 59 ever-smoking patients. Exploratory analysis of background lung sections of 15 individuals who had bronchoalveolar lavage specimen gene expression data available, SHADE scores were associated with the expression of several immunoregulatory genes (CEACAM6, CXCL6, IL5RA, LCN2, SPA17), the activation of inflammatory response and cytokine gene sets, and suppression of the antigen processing and presentation gene set (false discovery rate < 0.1). SHADE provides an automated workflow for anthracosis quantification and has demonstrated utility in uncovering insight into anthracosis-associated molecular changes in lung cancer. - Source: PubMed
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