Nuclear refractive index as a novel molecular marker for cancer

Article Title:
Nuclear nano-morphology markers of histologically normal cells detect the “field effect”
of breast cancer
Breast Cancer Research and Treatment
Rajan K. Bista*, Pin Wang*, Rohit Bhargava†, Shikhar Uttam*, Douglas J. Hartman‡,
Randall E. Brand*, and Yang Liu*,§
Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition,
University of Pittsburgh, Pittsburgh, PA 15232, USA
Department of Pathology, Magee-Womens Hospital, University of Pittsburgh Medical
Center, Pittsburgh, PA 15213, USA
Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA
15232, USA
Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15219, USA
Corresponding author:
Yang Liu, Ph.D.
Email: [email protected]
S1. Correction of stain variations
To account for the effect of variation in the stain-induced optical pathlength difference,
we have developed a correction model [1] based on the following equation:
OPDc ( x, y)  OPD( x, y)  OPDc , where OPDc is the corrected optical pathlength
difference (OPD), OPD is the measured OPD value before the correction, and OPDc is
the stain-induced OPD value. This correction model follows directly from the linear
relation between optical path length and change in cell dry mass concentration [2]. The
detailed description and validation of this model have been reported in our paper [1].
In brief, a technician in a clinical pathology laboratory at University of Pittsburgh
Medical Center (UPMC) prepared a calibration sample set using normal tissue with a
series of standard histology slides with different amounts of H&E stain, representing the
range of variation that could be encountered in routine clinical specimens. We then
measured the absorbance (A) of each histology slide through the transmission-mode
optics and established a relationship between the various A and OPDc , which shows a
linear dependence with a slope of  ( OPDc   A , where  is the modified specific
refraction increment [3,2]) and used as a constant calibration factor (Fig. S1).
Fig. S1 The effect of variation in the stain-induced nuclear optical pathlength difference
(OPD). The measured  OPD  as a function of the absorbance before and after applying
correction model in the validation set of histology specimens. The solid lines represent
the linear regression fits.
After the calibration factor  is determined from the calibration sample set, for
any given histology slide, we perform both the reflectance measurement to obtain OPD
values and the transmission measurement to obtain absorbance A, and the corrected OPD
is obtained through relation OPDc ( x, y)  OPD( x, y)   A . As shown in Fig. S1, before
correction, the  OPD  shows a strong dependence on the different stain levels and the
variation in  OPD  (quantified by the standard deviation of  OPD  ) is 2.6 nm. After
applying the correction model, the  OPD  remains nearly constant for varying stain
levels for the same sample set, as suggested by a clearly flat line in Fig. S1, and the
variation in  OPD  is 0.89 nm, which is within the system sensitivity level of 0.9 nm.
Therefore, the  OPD  after applying the correction model is nearly unaffected by
staining levels.
S2. Variation due to the thickness of tissue section
Although the tissue section thickness can be controlled by a microtome, sub-micron scale
variation is inevitable. Therefore, we investigated the effect of variation in section
thickness on the measured  OPD  . We first prepared histology slides sectioned at 4
µm setting with 3 different microtomes (10 slides from each microtome) in the clinical
pathology laboratory at UPMC that are routinely used for clinical specimen processing.
This setting represents a real clinical scenario that the tissue sectioning was often
performed with different microtomes which have variations in tissue section thickness.
As shown in Fig. S2(a), we found that our method to extract OPD is not sensitive to
variation in the tissue section thickness from different microtomes (no statistical
difference, P = 0.7) and that the  OPD  from histology slides prepared with 3 different
microtomes had a maximal variation of 0.5 nm, within the system sensitivity. Hence, we
confirm that the variation in the tissue section thickness among different microtomes does
not make a significant contribution to our results.
Second, we prepared histology slides using different settings of tissue section
thickness (4 µm and 5 µm) on the same microtome. As shown in Fig. S2(b), the extracted
 OPD  is independent of tissue section’s thickness (no statistical difference, P = 0.8),
with a difference of 0.3 nm between 4 µm and 5 µm, also within the system sensitivity.
This result also justifies that the measured  OPD  is due to the changes in internal
structural properties of the cell nucleus, rather than the sample thickness difference.
Fig. S2 Statistical analysis to investigate the effect of the variations in tissue sectioning
thickness: (a) for three different microtomes with the same setting of section thickness at
4µm (ANOVA test, two-sided P-value = 0.67); (b) for different settings of section
thickness at 4µm and 5µm, respectively (student t-test, two-sided P-value = 0.8). Error
bar represents the standard error.
Here we provide a preliminary theoretical interpretation why our method to
extract OPD is minimally affected by the thickness variation. In clinical histology
specimens, there is no strong reflection interface due to the closely matched refractive
index between the mounting medium and the sample. We obtain the optical path length
(OPL) profile based on spectral signals from the interfaces and scatterers within the
sample. In our method, we select a constant point (the same OPL value of interest for all
samples) on the OPL profile plot, where the phase-related information is derived. This
selected OPL value of interest must be within the sample, and the light beam should pass
through most of the cell nucleus to capture the required phase information. By selecting
the same OPL value of interest on OPL profile for each sample, we exclude sample
thickness variation from our measurements and produces reliable results in which only
phase variations due to internal structure occur.
S3. Quantification of stain absorbance
To confirm the result that the nano-morphology markers detect the “field effect” in breast
carcinogenesis that is not due to the artifact of staining variations in cell nuclei, we
quantified the absorbance from the cell nuclei. Specifically, we measured the light
intensity in the transmission configuration from the background ( I 0 ) and from the same
cell nuclei ( I nu ) as we used for nano-morphology marker analysis, from patients with
normal cells (Cat 1), ‘malignant-adjacent’ normal cells (Cat 5) and malignant cells (Cat
6). We calculated the absorbance based on the standard Beer’s law: A  log10 ( I 0 / I nu ) for
each cell nucleus, and obtained the characteristic value of average absorbance for an
individual patient by taking the average value of 40-60 cell nuclei from each patient. As
shown in Fig. S3, the absorbance does not show any similar correlation to our nanomorphology markers (as shown in Fig. 2 in the manuscript). Evidently, the stain
absorbance from the cell nuclei cannot distinguish normal and “malignant-adjacent”
normal groups (P = 0.58), but distinguish “malignant-adjacent” normal from malignant
groups (P = 4.1E-6). While the statistical analysis shows that the nano-morphology
markers from ‘malignant-adjacent’ normal cells (Cat 5) are distinct from normal tissue
from healthy patients (Cat 1), with a great similarity to malignant cells (Cat 6) (P < 0.001
between Cat 1 and Cat 5, and P > 0.05 between Cat 5 and Cat 6). Hence, we confirmed
that the “field-effect” detected by the nano-morphology markers is not due to the artifact
of staining variations.
P = 0.0006
P = 0.58
P = 4.1E-6
'Malignantadjacent' normal
Fig. S3: Statistical analysis of the stain absorbance from the cell nuclei in patients with
normal cells (Cat 1), ‘malignant-adjacent’ normal cells (Cat 5) and malignant cells (Cat
5). The statistical comparison between two patient groups was obtained using
Wilcoxon’s rank-sum test at 95% confidence interval, and two-sided P-values were used.
The error bar represents the standard error.
1. Uttam S, Bista RK, Hartman DJ, Brand RE, Liu Y (2011) Correction of stain
variations in nuclear refractive index of clinical histology specimens. J Biomed Opt 16
(11):116013. doi:10.1117/1.3650306
2. Barer R (1957) Refractometry and interferometry of living cells. J Opt Soc Am 47
3. Barer R (1952) Interference microscopy and mass determination. Nature 169:366-367