232 results on '"Yokoyama, Seiya"'
Search Results
2. MALAT1 functions as a transcriptional promoter of MALAT1::GLI1 fusion for truncated GLI1 protein expression in cancer
3. “Surface epithelial slackening” pattern in endometrioid carcinoma: A morphological feature for differentiating the POLE mutation-subtype from the no specific molecular profile subtype
4. Gallbladder microbiota composition is associated with pancreaticobiliary and gallbladder cancer prognosis
5. An oncogenic splice variant of PDGFRα in adult glioblastoma as a therapeutic target for selective CDK4/6 inhibitors
6. Exercise Suppresses Head and Neck Squamous Cell Carcinoma Growth via Oncostatin M
7. One-hundred-nm-scale electronic structure and transport calculations of organic polymers on the K computer
8. PCP4/PEP19 downregulates neurite outgrowth via transcriptional regulation of Ascl1 and NeuroD1 expression in human neuroblastoma M17 cells
9. Cervical Cytology Preserves Histologically Detected Surface Epithelial Slackening, Unique to thePOLEMutation-subtype in Endometrial Cancer
10. Novel linear algebraic theory and one-hundred-million-atom quantum material simulations on the K computer
11. Aberrant Methylation of UC Promoters in Human Pancreatic Ductal Carcinomas
12. Characterization and treatment of gemcitabine‐ and cisplatin‐resistant bladder cancer cells with a pan‐RAS inhibitor
13. Assessment of tumor characteristics based on glycoform analysis of membrane-tethered MUC1
14. Next-generation sequencing analysis of endometrial screening liquid-based cytology specimens: a comparative study to tissue specimens
15. Data from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
16. Supplementary table 4 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
17. Supplementary table 1 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
18. Supplementary table 3 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
19. Supplementary table 2 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
20. Supplementary figure 3 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
21. Supplementary figure 1 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
22. Supplementary figure 2 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
23. Supplementary figure 4 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
24. Favorable prognostic impact of phosphatase and tensin homolog alterations in wild-type isocitrate dehydrogenase and telomerase reverse transcriptase promoter glioblastoma
25. Identification of Neck Lymph Node Metastasis-Specific microRNA—Implication for Use in Monitoring or Prediction of Neck Lymph Node Metastasis.
26. Genome Editing Using Cas9 Ribonucleoprotein Is Effective for Introducing PDGFRA Variant in Cultured Human Glioblastoma Cell Lines
27. Characterization and treatment of gemcitabine- and cisplatin-resistant bladder cancer cells with a Pan-RAS inhibitor
28. Molecular Genetic Profile of 300 Japanese Patients with Diffuse Gliomas Using a Glioma-tailored Gene Panel
29. Distribution and favorable prognostic implication of genomicEGFRalterations inIDH‐wildtype glioblastoma
30. Genome Editing Using Cas9 Ribonucleoprotein Is Effective for Introducing PDGFRA Variant in Cultured Human Glioblastoma Cell Lines.
31. Distribution and favorable prognostic implication of genomic EGFR alterations in IDH‐wildtype glioblastoma.
32. PDGFRA amplification is a significant prognostic marker in patients with IDH wild-type glioblastoma multiforme
33. Prognostic impact of PDGFRA gain/amplification and MGMT promoter methylation status in patients with IDH wild-type glioblastoma
34. Molecular Evaluation of Endometrial Dedifferentiated Carcinoma, Endometrioid Carcinoma, Carcinosarcoma, and Serous Carcinoma Using a Custom-Made Small Cancer Panel
35. Detection of EGFR Mutation Distribution and Transcriptional Variants in IDH-Wildtype High-Grade Gliomas Using a Next-Generation Sequencing Oncopanel
36. Two autopsy cases of severe fever with thrombocytopenia syndrome (SFTS) in Japan: A pathognomonic histological feature and unique complication of SFTS
37. A novel anti-MUC1 antibody against the MUC1 cytoplasmic tail domain: use in sensitive identification of poorly differentiated cells in adenocarcinoma of the stomach
38. Expression of MUC5AC, an early marker of pancreatobiliary cancer, is regulated by DNA methylation in the distal promoter region in cancer cells
39. Significance of mucin expression in pancreatobiliary neoplasms
40. Circulating microRNA Panel as a Potential Novel Biomarker for Oral Squamous Cell Carcinoma Diagnosis
41. Aberrant DNA Methylation of Tumor-Related Genes In Oral Rinse: A Noninvasive Method for Detection of Oral Squamous Cell Carcinoma
42. Mucins in human neoplasms: Clinical pathology, gene expression and diagnostic application
43. DNA methylation and histone H3-K9 modifications contribute to MUC17 expression
44. A tailored next‐generation sequencing panel identified distinct subtypes of wildtype IDH and TERT promoter glioblastomas
45. Next-Generation Sequencing Analysis of Endometrial Screening Liquid-Based Cytology Specimens A Comparative Study to Tissue Specimens
46. Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning
47. Analysis by Next-Generation Sequencing Panel Covered 60 Genes and 17 Microsatellite Foci in Endometrial Screening Liquid-Based Cytology Specimens A Comparative Study to Tissue Specimens
48. Purification, characterization, and sequencing of antimicrobial peptides, Cy-AMP1, Cy-AMP2, and Cy-AMP3, from the Cycad (Cycas revoluta) seeds
49. The application of methylation specific electrophoresis (MSE) to DNA methylation analysis of the 5' CpG island of mucin in cancer cells
50. Comprehensive validation of liquid-based cytology specimens for next-generation sequencing in cancer genome analysis
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