OBJECTIVES: In this study, we are testing the hypothesis that human papillomavirus (HPV) positivity is correlated with chromatin texture in the cell. Interim analyses are important since this study involves 2000 patients and generates 6000 biopsy specimens that will be subjected to quantitative histopathological analysis and correlated to HPV positivity as measured by the Hybrid Capture II test (Digene; Gaithersberg, MD) and both HPV-DNA and mRNA by the polymerase chain reaction (PCR). The studies of optical technologies, from which we derive this sample, use the colposcopically directed and histopathologically classified cervical biopsy as the gold standard. In this report, we describe the results of an interim analysis of quantitative histopathology and chromatin texture as correlates of HPV infection using the cyto-savant system in cytologically and histopathologically negative specimens. METHODS: A group of 1544 patients entered the optical technology trials, generating 3275 biopsies and 1544 Papanicolaou readings. Two hundred forty-eight patients were cytologically and histopathologically negative. Study pathologists reviewed histologic samples 3 times in a blinded fashion. Non-overlapping, quantitatively stained nuclei were selected from the samples by the pathologists. HPV testing was done using the PCR method and the Hybrid Capture II test. Statistical analysis involved the creation of a classification matrix using a linear discriminant analysis. The matrix was trained on HPV-positive cells by PCR. The analysis included the random creation of both a training set and a validation set that were classified based on the discrimination score obtained by correlating nuclear texture with HPV positivity. RESULTS: The sensitivity of the classification was 52-54% and the specificity was 77-78%. Overall, a 68% predicted accuracy was achieved for both the training set and the test set. The agreement of a test and training set shows that the sets created randomly are indeed similar, and that the discrimination score worked equally well in both sets of cells. Once a cell-by-cell algorithm for HPV positivity was derived, HPV positivity was recalculated on the basis of cell-by-cell texture features. HPV positivity was then recalculated on both a per-biopsy basis and a per-patient basis. For HPV 16 and 18, the positivity rate was 70% on a per-biopsy basis and 73% on a per-patient basis. CONCLUSIONS: Although these results are preliminary, they suggest that texture features reflecting chromatin condensation may correlate with HPV positivity. The current sample is histologic, the analysis suggests that in a cytologic sample, HPV positivity could be detected or confirmed by texture features computed as part of an HPV-associated score. Additional biologic markers could be used as needed. While this study was performed on histologic samples, a study of cytologic samples would be more useful. Future studies will examine chromatin texture compared to HPV integration and mRNA HPV expression.
OBJECTIVES: In this study, we are testing the hypothesis that human papillomavirus (HPV) positivity is correlated with chromatin texture in the cell. Interim analyses are important since this study involves 2000 patients and generates 6000 biopsy specimens that will be subjected to quantitative histopathological analysis and correlated to HPV positivity as measured by the Hybrid Capture II test (Digene; Gaithersberg, MD) and both HPV-DNA and mRNA by the polymerase chain reaction (PCR). The studies of optical technologies, from which we derive this sample, use the colposcopically directed and histopathologically classified cervical biopsy as the gold standard. In this report, we describe the results of an interim analysis of quantitative histopathology and chromatin texture as correlates of HPV infection using the cyto-savant system in cytologically and histopathologically negative specimens. METHODS: A group of 1544 patients entered the optical technology trials, generating 3275 biopsies and 1544 Papanicolaou readings. Two hundred forty-eight patients were cytologically and histopathologically negative. Study pathologists reviewed histologic samples 3 times in a blinded fashion. Non-overlapping, quantitatively stained nuclei were selected from the samples by the pathologists. HPV testing was done using the PCR method and the Hybrid Capture II test. Statistical analysis involved the creation of a classification matrix using a linear discriminant analysis. The matrix was trained on HPV-positive cells by PCR. The analysis included the random creation of both a training set and a validation set that were classified based on the discrimination score obtained by correlating nuclear texture with HPV positivity. RESULTS: The sensitivity of the classification was 52-54% and the specificity was 77-78%. Overall, a 68% predicted accuracy was achieved for both the training set and the test set. The agreement of a test and training set shows that the sets created randomly are indeed similar, and that the discrimination score worked equally well in both sets of cells. Once a cell-by-cell algorithm for HPV positivity was derived, HPV positivity was recalculated on the basis of cell-by-cell texture features. HPV positivity was then recalculated on both a per-biopsy basis and a per-patient basis. For HPV 16 and 18, the positivity rate was 70% on a per-biopsy basis and 73% on a per-patient basis. CONCLUSIONS: Although these results are preliminary, they suggest that texture features reflecting chromatin condensation may correlate with HPV positivity. The current sample is histologic, the analysis suggests that in a cytologic sample, HPV positivity could be detected or confirmed by texture features computed as part of an HPV-associated score. Additional biologic markers could be used as needed. While this study was performed on histologic samples, a study of cytologic samples would be more useful. Future studies will examine chromatin texture compared to HPV integration and mRNA HPV expression.
Authors: Jon Whitney; German Corredor; Andrew Janowczyk; Shridar Ganesan; Scott Doyle; John Tomaszewski; Michael Feldman; Hannah Gilmore; Anant Madabhushi Journal: BMC Cancer Date: 2018-05-30 Impact factor: 4.430
Authors: Timon P H Buys; Scott B Cantor; Martial Guillaud; Karen Adler-Storthz; Dennis D Cox; Clement Okolo; Oyedunni Arulogon; Oladimeji Oladepo; Karen Basen-Engquist; Eileen Shinn; José-Miguel Yamal; J Robert Beck; Michael E Scheurer; Dirk van Niekerk; Anais Malpica; Jasenka Matisic; Gregg Staerkel; Edward Neely Atkinson; Luc Bidaut; Pierre Lane; J Lou Benedet; Dianne Miller; Tom Ehlen; Roderick Price; Isaac F Adewole; Calum MacAulay; Michele Follen Journal: Gend Med Date: 2011-09-22
Authors: Martial Guillaud; Qian Ye; Sam Leung; Anita Carraro; Alan Harrison; Malcolm Hayes; Alan Nichol; Mira Keyes Journal: Med Oncol Date: 2017-12-06 Impact factor: 3.064
Authors: Aparna Kumar; Arvind Rao; Santosh Bhavani; Justin Y Newberg; Robert F Murphy Journal: Proc Natl Acad Sci U S A Date: 2014-12-08 Impact factor: 11.205
Authors: Anne E Carpenter; Thouis R Jones; Michael R Lamprecht; Colin Clarke; In Han Kang; Ola Friman; David A Guertin; Joo Han Chang; Robert A Lindquist; Jason Moffat; Polina Golland; David M Sabatini Journal: Genome Biol Date: 2006-10-31 Impact factor: 13.583