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At least 307 records · Page 17Linked to original sources
PubMed2004

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.

MOTIVATION: Cancer diagnosis is one of the most important emerging clinical applications of gene expression microarray technology. We are seeking to develop a computer system for powerful and reliable cancer diagnostic model creation based on microarray data. To keep a realistic perspective on clinical applications we focus on multicategory diagnosis. To equip the system with the optimum combination of classifier, gene selection and cross-validation methods, we performed a systematic and comprehensive evaluation of several major algorithms for multicategory classification, several gene selection methods, multiple ensemble classifier methods and two cross-validation designs using 11 datasets spanning 74 diagnostic categories and 41 cancer types and 12 normal tissue types. RESULTS: Multicategory support vector machines (MC-SVMs) are the most effective classifiers in performing accurate cancer diagnosis from gene expression data. The MC-SVM techniques by Crammer and Singer, Weston and Watkins and one-versus-rest were found to be the best methods in this domain. MC-SVMs outperform other popular machine learning algorithms, such as k-nearest neighbors, backpropagation and probabilistic neural networks, often to a remarkable degree. Gene selection techniques can significantly improve the classification performance of both MC-SVMs and other non-SVM learning algorithms. Ensemble classifiers do not generally improve performance of the best non-ensemble models. These results guided the construction of a software system GEMS (Gene Expression Model Selector) that automates high-quality model construction and enforces sound optimization and performance estimation procedures. This is the first such system to be informed by a rigorous comparative analysis of the available algorithms and datasets. AVAILABILITY: The software system GEMS is available for download from http://www.gems-system.org for non-commercial use. CONTACT: alexander.statnikov@vanderbilt.edu.

Algorithms↗
PubMed2005

CDC2/CDK1 expression in esophageal adenocarcinoma and precursor lesions serves as a diagnostic and cancer progression marker and potential novel drug target.

Esophageal adenocarcinoma arises through well-defined precursor lesions (Barrett esophagus), although only a subset of these lesions advances to invasive adenocarcinoma. The lack of markers predicting progression in Barrett esophagus, typical presentation at advanced stage, and limitations of conventional chemotherapy result in >90% mortality for Barrett-associated adenocarcinomas. To identify potential prognostic markers and therapeutic targets, we compared gene expression profiles from Barrett-associated esophageal adenocarcinoma cell lines (BIC1, SEG1, KYAE, OE33) and normal esophageal epithelial scrapings utilizing the Affymetrix U133_A gene expression platform. We identified 560 transcripts with >3-fold up-regulation in the adenocarcinoma cell lines compared with normal epithelium. Utilizing tissue microarrays composed of normal esophageal squamous mucosa (n = 20), Barrett esophagus (n = 10), low-grade dysplasia (n = 14), high-grade dysplasia (n = 27), adenocarcinoma (n = 59), and node metastases (n = 27), we confirmed differential up-regulation of three proteins (Cdc2/Cdk1, Cdc5, and Igfbp3) in adenocarcinomas and Barrett lesions. Protein expression mirrored histologic progression; thus, 87% of low-grade dysplasias had at least focal surface Cdc2/Cdk1 and 20% had >5% surface staining; 96% of high-grade dysplasias expressed abundant surface Cdc2/Cdk1, while invasive adenocarcinoma and metastases demonstrated ubiquitous expression. Esophageal adenocarcinoma cell lines treated with the novel CDC2/CDK1 transcriptional inhibitor, tetra-O-methyl nordihydroguaiaretic acid (EM-1421, formerly named M4N) demonstrated a dose-dependent reduction in cell proliferation, paralleling down-regulation of CDC2/CDK1 transcript and protein levels. These findings suggest a role for CDC2/CDK1 in esophageal adenocarcinogenesis, both as a potential histopathologic marker of dysplasia and a putative treatment target.

Adenocarcinoma↗
PubMed2002

Simultaneously presenting head and neck and lung cancer: a diagnostic and treatment dilemma.

OBJECTIVES/HYPOTHESIS: Synchronous tumors are defined as malignancies presenting within 6 months of the index tumors. A significant subset of patients present at initial evaluation with malignant tumors of both the head and neck (head and neck squamous cell carcinoma) and the lung, which are termed simultaneous primaries. The management and treatment outcomes in this cohort of patients have not been clearly defined and are the subject of the present review. STUDY DESIGN: Retrospective chart review of previously untreated patients. METHODS: From January 1974 to December 1997, a total of 2964 patients were treated for mucosal squamous cell carcinoma of the head and neck. Forty-two patients fulfilled the criteria for synchronous head and neck and lung malignancy. Of these, 27 patients had simultaneous tumors of the head and neck and the lung. This cohort of patients (n = 27) was stratified into three treatment groups. Patients in group A (n = 10) had resectable head and neck and lung primaries treated with curative intent. Group B (n = 8) was composed of patients who could have been treated with curative intent but declined and were given only palliative therapy. Patients in group C (n = 9) were candidates for only palliative treatment. RESULTS: The estimated 5-year disease-specific survival in group A was 47%, whereas patients in group B had a 5-year disease-specific survival of only 13% (P =.05). There were no survivors beyond 1 year in group C. The presence of mediastinal adenopathy in patients in group A portended poor clinical outcome. There was an estimated 5-year disease-specific survival of 51% in patients with no preoperative evidence of mediastinal adenopathy (n = 7), whereas 67% of patients with radiological evidence of mediastinal adenopathy died (two of three patients). CONCLUSION: The presence of simultaneous head and neck squamous cell carcinoma and pulmonary malignancies should not be a deterrent to aggressive surgical therapy because a potentially satisfactory outcome can be expected in these patients.

Aged↗
PubMed1979

Early detection of ductal breast cancer: the diagnostic procedure for grouped microcalcifications.

Mammography and xeroradiography for grouped microcalcifications are considered the most effective diagnostic methods to detect occult breast carcinoma. Radiography must direct the surgeon to excise the nonpalpable area. The removal of the tissue with grouped microcalcifications must be confirmed by intraoperative radiological control. The histologic preparation must be guided by radiographic controls. Tissue with calcific deposits is examined by step sections. The diagnostic success depends upon the cooperation between the radiologist, the surgeon, and the pathologist. Our results from 1964 to 1977 have shown a frequency of 14.4% of occult carcinoma. Ductal or lobular carcinomata in situ have been diagnosed in 8.9%. In 9.9% of the patients, cystic disease with severe and atypical proliferations has been encountered.

Biopsy↗
PubMed2006

Multicolor quantum dots for molecular diagnostics of cancer.

In the pursuit of sensitive and quantitative methods to detect and diagnose cancer, nanotechnology has been identified as a field of great promise. Semiconductor quantum dots are nanoparticles with intense, stable fluorescence, and could enable the detection of tens to hundreds of cancer biomarkers in blood assays, on cancer tissue biopsies, or as contrast agents for medical imaging. With the emergence of gene and protein profiling and microarray technology, high-throughput screening of biomarkers has generated databases of genomic and expression data for certain cancer types, and has identified new cancer-specific markers. Quantum dots have the potential to expand this in vitro analysis, and extend it to cellular, tissue and whole-body multiplexed cancer biomarker imaging.

Animals↗