Su1754 - Pre-Clinical Performance of Stool RNA for Detection of Adenomas and Colorectal Cancer

Barnell, Erica K.; Kang, Yiming; Campbell, Katie M.; Barnell, Andrew; Wurtzler, Elizabeth M.

doi:10.1016/s0016-5085(18)32117-6

Cited by 2 publications

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“…The custom amplicons were associated with 408 transcripts, which were selected using previously conducted research (see Supplementary Methods). 21 Specifically, using microarray data (Affymetrix Human Transcriptome Array 2.0) from 265 individuals (177 patients with CRC or adenomas and 88 patients with no findings on a colonoscopy), 214 transcripts were identified as differentially expressed (p<0.03). Using molecular barcoding data (NanoString nCounter) from 85 individuals (59 with CRC or adenomas and 26 with no findings on a colonoscopy), an additional 123 transcripts were identified as differentially expressed.…”

Section: Custom Amplicon Panel Developmentmentioning

confidence: 99%

Stool-derived eukaryotic RNA biomarkers for detection of high-risk adenomas

Barnell

Kang

Barnell³

et al. 2019

Preprint

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Abbreviations AUC area under the curve ANOVA analysis of variance CRC colorectal cancer DE differentially expressed FC fold-change FIT fecal immunochemical test HRA high-risk adenoma LRA low-risk adenoma MRA medium-risk adenoma NPV negative predictive value PPV positive predictive value ROC receiver operating characteristic seRNA stool-derived eukaryotic RNA AbstractBackground and aims: Colorectal cancer (CRC) is the second leading cause of cancer related deaths in the United States. Mortality is largely attributable to low patient compliance with screening and a subsequent high frequency of late-stage diagnoses. Noninvasive methods, such as stool-or blood-based diagnostics could improve patient compliance, however, existing techniques cannot adequately detect high-risk adenomas (HRAs) and early-stage CRC. Methods: Here we apply cancer profiling using amplicon sequencing of stool-derived eukaryotic RNA for 275 patients undergoing prospective CRC screening. A training set of 154 samples was used to build a random forest model that included 4 feature types (differentially expressed amplicons, total RNA expression, demographic information, and fecal immunochemical test results). An independent hold out test set of 121 patients was used to assess model performance. Results: When applied to the 121-patient hold out test set, the model attained a receiver operating characteristic (ROC) area under the curve (AUC) of 0.94 for CRC and a ROC AUC of 0.87 for CRC and HRAs. In aggregate, the model achieved a 91% sensitivity for CRC and a 73% sensitivity for HRAs at an 89% specificity for all other findings (medium-risk adenomas, low-risk adenomas, benign polyps, and no findings on a colonoscopy). Conclusion: Collectively, these results indicate that in addition to early CRC detection, stool-derived biomarkers can accurately and noninvasively identify HRAs, which could be harnessed to prevent CRC development for asymptomatic, average-risk patients.

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Section: Custom Amplicon Panel Developmentmentioning

confidence: 99%