Antibody P504S _ AMACR α- polyclonal
- Known as:
- Antibody P504S _ AMACR α- pab
- Catalog number:
- AB04144
- Product Quantity:
- 3.0ml
- Category:
- -
- Supplier:
- Other suppliers
- Gene target:
- Antibody P504S _ AMACR α- polyclonal
Related genes to: Antibody P504S _ AMACR α- polyclonal
- Gene:
- AMACR NIH gene
- Name:
- alpha-methylacyl-CoA racemase
- Previous symbol:
- -
- Synonyms:
- RACE, P504S
- Chromosome:
- 5p13.2
- Locus Type:
- gene with protein product
- Date approved:
- 1999-10-19
- Date modifiied:
- 2016-12-13
Related products to: Antibody P504S _ AMACR α- polyclonal
Related articles to: Antibody P504S _ AMACR α- polyclonal
- Low-grade oncocytic tumor (LOT) of the kidney is a rare, indolent neoplasm within the spectrum of eosinophilic renal tumors. It typically presents as a small, solitary mass and is associated with molecular alterations in , , or . We describe a 72-year-old male with a history of pancreatic neuroendocrine tumor, gastrointestinal stromal tumor, and prostate cancer who presented with multiple bilateral renal masses. Partial nephrectomy revealed two distinct tumors: one consistent with LOT and the other with a sclerosing angiomyolipoma (AML). The LOT consisted of oncocytic cells with round to oval nuclei and delicate perinuclear halos, arranged predominantly in solid architecture, and immunoreactive for PAX8, EMA, and CK7, whereas negative for CD117 and AMACR. The AML was composed of spindle and epithelioid cells embedded in sclerotic stroma, positive for MiTF and SMA, and negative for conventional melanocytic markers, including HMB45 and Melan-A. Germline testing identified a intron 6, c.509-15G > A variant of uncertain significance. Somatic analysis showed increased allelic imbalance at the locus, suggesting loss of heterozygosity and a potential pathogenic role. This case adds to the limited reports of multifocal LOT and demonstrates the consistent association of germline alterations with this rare tumor presentation. - Source: PubMed
Publication date: 2026/07/16
Putra IlhamVashisht TanishqOrdobazari AtousaVosoughi Aram - The purpose of this study is to develop and validate a multimodal, multitask prediction framework for clear cell renal cell carcinoma (ccRCC) by integrating preoperative CT radiomics, pathology-derived biomarker data from preoperative biopsy specimens, and clinical variables. The model was built for pathologically confirmed ccRCC and excluded other RCC histologic subtypes (e.g., papillary and chromophobe). In this multicenter retrospective study, ccRCC patients were enrolled and data were collected from preoperative CT scans, AMACR/P504S immunohistochemistry results, pathology reports, and follow-up records. Patients were assigned by hospital site into a training cohort and an independent external test cohort. Radiomic features were extracted from CT tumor regions of interest (ROIs), while deep learning features were derived from pathology images. Clinical variables were incorporated as additional inputs. A post-feature fusion strategy enabled simultaneous prediction of tumor classification and postoperative survival. Model performance was assessed using AUC for diagnosis and C-index for survival, together with calibration curves, decision curve analysis, and bootstrap confidence intervals. SHAP analysis was applied to quantify feature contributions. In external validation, the integrated multimodal model achieved strong diagnostic discrimination for P504S/AMACR (AUC = 0.983) and demonstrated improved prognostic performance for postoperative outcomes (C-index = 0.804). Subgroup analyses by grade and stage further supported model robustness, while SHAP-based interpretation indicated complementary contributions from imaging, pathology, and clinical variables. Overall, the proposed multimodal, multitask fusion framework enables reliable preoperative P504S/AMACR-based classification and postoperative prognostic prediction in ccRCC, supporting more refined risk stratification and individualized postoperative management using noninvasive imaging and clinical information. Calibration and decision curve analyses further support its potential clinical utility. Larger prospective and external multicenter validations are still needed to confirm generalizability. - Source: PubMed
Publication date: 2026/07/13
Wang ChengYueJiang XinYingWu ChengShuaiZhang Liang - A 58-year-old woman on long-term hemodialysis underwent computed tomography for diabetic foot gangrene, which revealed a mass adjacent to the gallbladder, suggesting gallbladder carcinoma. Magnetic resonance imaging also suggested a gallbladder tumor. At laparotomy, the lesion was found to originate from the right kidney, and right nephrectomy was performed. Histopathological and immunohistochemical findings (AMACR+, CD10, CK7-) confirmed acquired cystic disease-associated renal cell carcinoma (ACD-RCC). ACD-RCC may present with atypical imaging findings and mimic adjacent organ malignancies in patients on dialysis. - Source: PubMed
Publication date: 2026/07/01
Kawaguchi YoshihiroMorokuma FutoshiMiyoshi AtsushiNonaka MaiMori Daisuke - Malignant tumor treatment still faces issues like insufficient targeting, drug resistance, and immunosuppression. Spherical nucleic acids (SNAs), with their three-dimensional core-shell structure and densely packed, radially oriented oligonucleotide shell, enable transfection-free cellular uptake and provide nuclease resistance and stability. This review examines SNA engineering strategies and their impact on precision oncology. Functionalization with antibodies, aptamers, or antisense oligonucleotides enables SNAs to target key molecules such as human epidermal growth factor receptor 2 (HER2), programmed death-ligand 1 (PD-L1), and toll-like receptors (TLRs). Advances in stimuli-responsive, self-assembled, liposomal, and peptide-based carrier systems facilitate controlled drug release and modulation of the tumor microenvironment (TME). Diagnostic applications of SNAs include electrochemical, fluorescent, and colorimetric sensing systems for detecting biomarkers such as exosomes, miRNAs, alpha-methylacyl-CoA racemase (AMACR), and telomerase. Therapeutically, SNAs co-deliver chemotherapeutics and immunoadjuvants, support cancer vaccines, and exert efficacy in various tumors, including the central nervous, reproductive, digestive, hematological, barrier, and respiratory systems. Early clinical studies indicate a favorable biosafety profile, but issues remain regarding delivery efficiency, target selectivity, scalability, and long-term safety. Progress toward biodegradable, machine-learning-guided SNA platforms may soon make this nanotechnology a fundamental part of personalized, precision cancer medicine. - Source: PubMed
Publication date: 2026/06/17
Wang YilinWu WenbingYao Fuli - Nephrogenic adenoma (NA) is a benign lesion of the genitourinary tract that may mimic malignancy both clinically and histologically. The fibromyxoid variant (FMNA), characterized by spindled cells in myxoid stroma, presents additional diagnostic challenges due to its rarity and overlapping features with renal cell carcinoma (RCC). A 72-year-old man with a history of nephrolithiasis and no prior urologic surgery was evaluated for a right renal mass. Fine-needle aspiration yielded cloudy red fluid with scant epithelial cells and a fibromyxoid background. Immunohistochemistry showed positivity for PAX8, AMACR, CK7, and CA-IX, leading to a pre-operative diagnosis of RCC. Partial nephrectomy revealed a unilocular cyst with a solid component. Histology demonstrated fibromyxoid stroma with embedded spindled cells and focal tubular NA features; therefore, a final diagnosis of fibromyxoid nephrogenic adenoma was rendered. Fibromyxoid nephrogenic adenoma is a benign entity that can closely mimic RCC on cytologic and immunohistochemical grounds. Our findings underscore the diagnostic pitfalls in small-volume cytologic samples. Awareness of the cytologic features of FMNA and cautious interpretation of immunostains are essential to avoid misdiagnosis and unnecessary treatment. - Source: PubMed
Publication date: 2026/06/28
Gedallovich JodiAdeniyi AdebolaSangoi Ankur RQian XiaohuaErnst Kelly