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Biotech / Medical : Ciphergen Biosystems(CIPH): -- Ignore unavailable to you. Want to Upgrade?


To: tuck who wrote (295)1/4/2005 10:19:28 AM
From: tuck  Respond to of 510
 
[SELDI for diagnosing colorectal cancer]

>>Clin Cancer Res. 2004 Dec 15;10(24):8380-5.

Artificial neural networks analysis of surface-enhanced laser desorption/ionization mass spectra of serum protein pattern distinguishes colorectal cancer from healthy population.

Chen YD, Zheng S, Yu JK, Hu X.

Department of Oncology, Second Affiliated Hospital, Zhejiang University, HangZhou, Zhejiang, People's Republic of China.

PURPOSE: The low specificity and sensitivity of the carcinoembryonic antigen test makes it not an ideal biomarker for the detection of colorectal cancer. We developed and evaluated a proteomic approach for the simultaneous detection and analysis of multiple proteins for distinguishing individuals with colorectal cancer from healthy individuals. EXPERIMENTAL DESIGN: We subjected serum samples (including 55 colorectal cancer patients and 92 age- and sex-matched healthy individuals) from 147 individuals, for analysis by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. Peaks were detected with Ciphergen SELDI software version 3.0. Using a multilayer artificial neural network with a back propagation algorithm, we developed a classifier for separating the colorectal cancer groups from the healthy groups. RESULTS: The artificial neural network classifier separated the colorectal cancer from the healthy samples, with a sensitivity of 91% and specificity of 93%. Four top-scored peaks, at m/z of 5,911, 8,930, 8,817, and 4,476, were finally selected as the potential "fingerprints" for detection of colorectal cancer. CONCLUSIONS: The combination of SELDI-TOF mass spectrometry with the artificial neural networks in the analysis of serum protein yields significantly higher sensitivity and specificity values for the detection and diagnosis of colorectal cancer.<<

Cheers, Tuck



To: tuck who wrote (295)10/12/2006 12:55:15 PM
From: tuck  Respond to of 510
 
[Evaluation of Apolipoprotein A1 and Posttranslationally Modified Forms of Transthyretin as Biomarkers for Ovarian Cancer Detection in an Independent Study Population]

Ciphergen put out a PR about this, saying it validates results of the the study this post references. The difference being that this tests against disease controls, not those of healthy ones, which is good, but . . . Stock has been on a steady down trend ever since, and is below a buck this morning. All the studies in the world aren't going to help unless Quest says something about launching the blasted test.

>>Cancer Epidemiology Biomarkers & Prevention Vol. 15, 1641-1646, September 2006

Evaluation of Apolipoprotein A1 and Posttranslationally Modified Forms of Transthyretin as Biomarkers for Ovarian Cancer Detection in an Independent Study Population

Lee E. Moore1, Eric T. Fung2, Marielena McGuire2, Charles C. Rabkin1, Annette Molinaro1, Zheng Wang2, Fujun Zhang2, Jing Wang2, Christine Yip2, Xiao-Ying Meng2 and Ruth M. Pfeiffer1
1 Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, Maryland and 2 Ciphergen Biosystems, Inc., Fremont, California

Requests for reprints: Lee E. Moore, Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, 6120 Executive Boulevard, EPS 8118, Bethesda, MD 20852-7240. Phone: 301-496-6427; Fax: 301-402-1819. E-mail: moorele@mail.nih.gov

Background: Although overall 5-year survival rates for ovarian cancer are poor (10-30%), stage I/IIa patients have a 95% 5-year survival. New biomarkers that improve the diagnostic performance of existing tumor markers are critically needed. A previous study by Zhang et al. reported identification and validation of three biomarkers using proteomic profiling that together improved early-stage ovarian cancer detection.

Methods: To evaluate these markers in an independent study population, postdiagnostic/pretreatment serum samples were collected from women hospitalized at the Mayo Clinic from 1980 to 1989 as part of the National Cancer Institute Immunodiagnostic Serum Bank. Sera from 42 women with ovarian cancer, 65 with benign tumors, and 76 with digestive diseases were included in this study. Levels of various posttranslationally forms of transthyretin and apolipoprotein A1 were measured in addition to CA125.

Results: Mean levels of five of the six forms of transthyretin were significantly lower in cases than in controls. The specificity of a model including transthyretin and apolipoprotein A1 alone was high [96.5%; 95% confidence interval (95% CI), 91.9-98.8%] but sensitivity was low (52.4%; 95% CI, 36.4-68.0%). A class prediction algorithm using all seven markers, CA125, and age maintained high specificity (94.3%; 95% CI, 89.1-97.5%) but had higher sensitivity (78.6%; 95% CI, 63.2-89.7%).

Conclusions: We were able to replicate the findings reported by Zhang et al. in an independently conducted blinded study. These results provide some evidence that including age of patient and these markers in a model may improve specificity, especially when CA125 levels are 35 units/mL. Influences of sample handling, subject characteristics, and other covariates on biomarker levels require further consideration in discovery and replication or validation studies.<<

Cheers, Tuck