Patent Application from Liotta and colleagues:
appft1.uspto.gov
#20030004402
Detailed discussion of multiple biomarker approach for prostate and ovarian cancer in particular, including the ability to find ovarian cancer in stage I. Here's an excerpt:
>>[0068] A set of randomly chosen sera (50 from the control cohort and 50 sera from the disease cohort) within the ovarian cancer study set of 200 specimens was selected for SELDI-TOF mass spectrometry analysis and subsequent training of the bioinformatics method. A pattern of mass intensities at 5 independent molecular weight regions of 534, 989, 2111, 2251, and 2465 Da discovered from a starting set of 15,000.sup.5 pattern permutations correctly segregated 98% (49/50) of the ovarian cancer samples and 94% of the controls (47/50) in the training set. The optimal proteomic pattern, challenged with 100 SELDI-TOF data streams from diagnosis-blinded cases was able to accurately predict the presence of ovarian cancer in all 50 cancer specimens contained within the 100 unknown test samples (50/50, 95% confidence interval 93% to 100%). This included the correct classification of 18/18 stage I cancers (95% confidence interval 82% to 100%) while maintaining specificity for the blinded cancer-free samples (47/50, 95% confidence interval 84% to 99%, overall p<10.sup.-10 by chi-squared test). These results support the hypothesis that low molecular weight proteomic patterns in sera reflect changes in the pathology of tissue within an organ at a distant site. Moreover, such patterns may be sensitive indicators of early pathological changes, since they correctly classified all 18 sera from organ-confined stage I ovarian cancer specimens. <<
This is dated January 2, 2003. Behind some of the recent rise, perhaps?
Cheers, Tuck |
