Evaluation of HPV infection and smoking status impacts on cell proliferation in epithelial layers of cervical neoplasia.

Accurate cervical intra-epithelial neoplasia (CIN) lesion grading is needed for effective patient management. We applied computer-assisted scanning and analytic approaches to immuno-stained CIN lesion sections to more accurately delineate disease states and decipher cell proliferation impacts from HPV and smoking within individual epithelial layers. A patient cohort undergoing cervical screening was identified (n = 196) and biopsies of varying disease grades and with intact basement membranes and epithelial layers were obtained (n = 261). Specimens were sectioned, stained (Mib1), and scanned using a high-resolution imaging system. We achieved semi-automated delineation of proliferation status and epithelial cell layers using Otsu segmentation, manual image review, Voronoi tessellation, and immuno-staining. Data were interrogated against known status for HPV infection, smoking, and disease grade. We observed increased cell proliferation and decreased epithelial thickness with increased disease grade (when analyzing the epithelium at full thickness). Analysis within individual cell layers showed a ≥50% increase in cell proliferation for CIN2 vs. CIN1 lesions in higher epithelial layers (with minimal differences seen in basal/parabasal layers). Higher rates of proliferation for HPV-positive vs. -negative cases were seen in epithelial layers beyond the basal/parabasal layers in normal and CIN1 tissues. Comparing smokers vs. non-smokers, we observed increased cell proliferation in parabasal (low and high grade lesions) and basal layers (high grade only). In sum, we report CIN grade-specific differences in cell proliferation within individual epithelial layers. We also show HPV and smoking impacts on cell layer-specific proliferation. Our findings yield insight into CIN progression biology and demonstrate that rigorous, semi-automated imaging of histopathological specimens may be applied to improve disease grading accuracy

Average percentage of proliferating cells in the first layers of cervical epithelium.

<p>In all panels, layers 0 and 1 represent the basal and parabasal layers, respectively. A) Percentage of proliferating cells in the first seven layers of cervical epithelium as assessed for each pathology grade. B) Percentage of proliferating cells in the first seven layers of cervical epithelium for normal and CIN1 tissues based on high-risk HPV type infection status. C) Percentage of proliferating cells in the first six layers of epithelium of non-smokers, where LGSILs represent CIN1 lesions and HGSILs represent CIN2/3 lesions. D) Same representation as C), only results presented are for patients with smoking histories.</p

Percentage of proliferating cells in the full thickness of the epithelium for normal epithelium, LGSILs, and HGSILs for non-smokers and smokers.

<p>Factorial ANOVA/<i>post hoc</i> Fisher LSD testing revealed the following results when comparing results from non-smokers vs. smokers: for cases negative for disease, p = 0.75; for LGSILs, p = 0.94; and for HGSILs, p = 0.049.</p

Proportion of Mib1-positive cells (i.e. proliferating cells) in the four diagnostic groups.

<p>The mid-point represents the median value; boxes represent the 25th percentiles; and whiskers represent the 95^th percentiles. Once again, factorial ANOVA testing was followed by a <i>post hoc</i> Fisher LSD test for group-by-group comparisons, yielding: p = 0.0006 for a normal vs. CIN1 comparison; p = 0.017 for a normal CIN1 vs. CIN2 comparison; and p = 0.00001 for a CIN2 vs. CIN3 comparison.</p

Mean value of epithelial thickness (µm), number of layers, and percentage of proliferating cells according to histopathological diagnosis (with standard deviations represented in parentheses.

<p>Mean value of epithelial thickness (µm), number of layers, and percentage of proliferating cells according to histopathological diagnosis (with standard deviations represented in parentheses.</p

Percentage of proliferating cells – mean and (Standard Deviation) – in the first eight layers of cervical epithelium according to histopathology diagnosis.

<p>Detailed methods for delineating epithelial layers are found in Materials and Methods, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107088#pone-0107088-g001" target="_blank">Fig. 1</a>.</p><p>Percentage of proliferating cells – mean and (Standard Deviation) – in the first eight layers of cervical epithelium according to histopathology diagnosis.</p

Results for Mib1-stained biopsy specimens (including stratification based on histopathological review of an individual biopsy specimen [“Biopsy Diagnosis”]; worst disease grade observed amongst multiple biopsies from a single patient [i.e. “Worst Patient Diagnosis”]; and infection status for High Risk HPV types [i.e. the 13 high risk types defined within the Hybrid Capture II system]).

<p>Results for Mib1-stained biopsy specimens (including stratification based on histopathological review of an individual biopsy specimen [“Biopsy Diagnosis”]; worst disease grade observed amongst multiple biopsies from a single patient [i.e. “Worst Patient Diagnosis”]; and infection status for High Risk HPV types [i.e. the 13 high risk types defined within the Hybrid Capture II system]).</p

Spatial analysis of Mib1-stained cervical biopsies.

<p>We present: (A) an unprocessed, stained cervical biopsy cross section; (B) basal and superficial membranes that were first manually delineated by a technician through simple thresholding followed by automated segmentation of all nuclei, which generated candidate cell’s nuclear centers of gravity; (C) Mib1-positive nuclei that were identified manually by the technician (green dots) and Voronoi diagrams that were generated based on those centers of gravity; (D) the basal layer (bottom of panel) containing all nuclei whose associated Voronoi polygons intersected with the basal membrane; (E) layer 1 (the parabasal layer); and (F) successive layers that were incrementally calculated.</p