PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer Res. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
PMCID: PMC2802178
NIHMSID: NIHMS162262

Nanoscale Cellular Changes in Field Carcinogenesis Detected by Partial Wave Spectroscopy

Abstract

Understanding alteration of cell morphology in disease has been hampered by the diffraction limited resolution of optical microscopy (>200nm). We recently developed an optical microscopy technique, partial wave spectroscopy (PWS), that is capable of quantifying statistical properties of cell structure at the nanoscale. Here we use PWS to show for the first time the increase in the disorder strength of the nanoscale architecture not only in tumor cells but also in the microscopically normal-appearing cells outside of the tumor. Although genetic and epigenetic alterations have been previously observed in the field of carcinogenesis, these cells were considered morphologically normal. Our data show organ-wide alteration in cell nanoarchitecture. This appears to be a general event in carcinogenesis, which is supported by our data in three types of cancer: colon, pancreatic and lung cancers. These results have important implications in that PWS can be used as a new methodology to identify patients harboring malignant or a premalignant tumors by interrogating easily accessible tissue sites distant from the location of the lesion.

Keywords: field carcinogenesis, light scattering, disorder, nanoscale alterations, microscopy

INTRODUCTION

Epithelial dysplasia (microscopic abnormalities associated with malignant transformation) and cancer is the culmination of a protracted process of genetic and epigenetic events. Thus, it is well established that in the microscopically normal mucosa undergoing neoplastic transformation, there are profound activation of proto-oncogenes (through mutation or increased copy number) or loss of tumor suppressor genes (via both mutations or through epigenetic silencing by promotor hypermethylation, microRNA or histone acetylation). Furthermore, it is being increasingly recognized that these genetic and epigenetic alterations not only occur at the neoplastic focus but more diffusely (field cancerization).

Neoplastic transformation of the colon is a prototypical example of field carcinogenesis. Indeed, the knowledge of field carcinogenesis has been used for clinical practice via the flexible sigmoidoscopy. This approach is based on the fact that endoscopic detection of adenomas in the distal colon portends a ~2.5 fold excess risk of proximal neoplasia (1). Numerous other biomarkers of colon carcinogenesis have been shown to correlate with the presence of neoplasia including morphological (aberrant crypt foci) (2), cellular (altered proliferation (3) and apoptosis (4)) and molecular (genomic, methylation and proteomic) (58). Many of these markers are detected in mucosa that is classified as normal by light microscopy. While one would anticipate that these genetic/epigenetic changes would result in structural changes, the diffraction limited resolution of light renders the conventional microscopy to be insensitive to structures < 200 nm, which would include ribosomes, macromolecular complexes, nucleosomes, membranes etc. These nanoscale structures are some of the most fundamental building blocks of a cell and are the most likely to be altered in early neoplastic transformation. Indeed, techniques such as karyometry have suggested that there are subtle ultrastructural alterations as markers of field cancerization (9, 10). However, the ability to sensitively and robustly detect these changes has been heretofore impossible. We posed a question if in early carcinogenesis microscopically normal- appearing cells do posses alterations in their morphology, although these changes occur at length scales not accessible by conventional microscopy, i.e. nanoarchitecture.

In order to assess the nanoscale we have utilized a fundamental principle of mesoscopic light transport theory (1115) that the signal in 1-dimension (1-D) arising due to multiple interferences of light waves reflected from weak refractive index fluctuations is sensitive to any length scale of refractive index fluctuations. Therefore, the spectrum of the 1-D scattering signals contain information regarding particles whose length scales are well below the wavelength (<< 200 nm)(1618). We recently reported a novel optical technique, partial wave spectroscopy (PWS), that is capable of extracting 1D-propagating waves (partial waves) from different parts of a scattering particle (19). We have also recently demonstrated that PWS was sensitive to subtle genetic/epigenetic alterations that occur in colonic carcinogenesis (20). Moreover, in the MIN (multiple intestinal neoplasia) model the abnormalities detected using PWS preceded development of microscopically evident neoplasia further supporting its role in field carcinogenesis detection. In this study, we demonstrate that these findings observed earlier in human colon cell lines and MIN mice model are translatable to the detection of human colorectal carcinogenesis. Our results also indicate that PWS may have the promise for detecting extended field carcinogenesis in the pancreas and lung.

MATERIALS AND METHODS

Partial Wave Spectroscopic Microscopy

The design of the PWS instrument is discussed in detail elsewhere (20). In brief, a nearly plane wave of white, low-spatially coherent light illuminates the sample and an image formed by the backscattered photons is acquired. The spectra of the backscattered light within the wavelength range from 400 to 700 nm are acquired from each pixel, normalized by the spectrum of the incident light, and filtered to remove spectral noise. This yields a data cube R(λ, x, y) (λ is the wavelength, x and y are pixel coordinates), which is referred to as the fluctuating part of the reflection coefficient. Hence, unlike conventional microscopy, in which an image is formed by integrating the reflected or transmitted intensity over a broad spectrum, PWS measures spectral fluctuations in the backscattering spectra. In essence, PWS decomposes a complex 3D weakly disordered medium such as a biological cell into many spatially independent parallel 1D channels each with diffraction-limited transverse size and acquires 1D-reflection spectra R(λ; x, y). These spectral fluctuations are analyzed by means of 1D mesoscopic light transport theory. This theory enables quantification of the statistical properties of the spatial refractive index variations at any length scale including those well below the wavelength (<< 200nm). The statistical parameter determined from the analysis is the disorder strength Ld = < Δn2 > lc, where < Δn2 > and lc are the variance and the spatial correlation length of the refractive index fluctuations. At a given point in a cell, Δn is proportional to the local concentration of intracellular solids and lc is related to the size of the intracellular structures within a cell. We had recently demonstrated using numerical simulations and model experiments that the minimum lc that can be probed by using PWS is below 20 nm (20, 21). Thus, using PWS, a two-dimensional map depicting the distribution of disorder strength Ld (x, y) can be obtained for a particular cell. From these 2D images several statistical parameters can be extracted, such as the mean intracellular disorder strength Ld(c) (the average Ld (x, y) over x and y) and the standard deviation of intracellular disorder strength, σ(c). The averages of Ld(c), σ(c) over a group of cells, such as cells sampled from a particular patient category, are termed the group means Ld(g) and σ(g).

The stability of the PWS instrument was established by calculating the statistical parameters Ld(c) and σ(c) from a cell sample at different time points on the same day. This technical reproducibility of the PWS instrument was measured to be ~ 1.5%. Also, the variability of the statistical parameters from the same sample measured over a period of 30 days was measured to be ~5%. This measure included both the variability of the system and the sample over a period of 30 days. The variability of disorder strength calculated from multiple cytological samples of the same patient was ~ 25% which probably reflects the 'patchiness' of the field effect (22, 23).

Human Studies

All studies were performed and the samples were collected with the approval of the institutional review board at Northshore University HealthSystem.

Colon

The patients undergoing screening or surveillance colonoscopy scheduled at Northshore University Health System were included in the study. The exclusion criteria included incomplete colonoscopy (failure to intubate cecum), poor colonic preparation, coagulopathy, prior history of pelvic radiation or systemic chemotherapy. The samples were collected as follows: colonoscopy to cecum was performed with standard techniques using Olympus 160 or 180 series colonoscopes. Upon withdrawal of the colonoscope to the rectum, a cytology brush was passed through the endoscope and gently applied to the visually normal rectum.

Pancreas

The controls are patients undergoing esophagogastroduodenoscopy for non-pancreatic reasons. The cancer patients are patients with histologically confirmed pancreatic cancer undergoing endoscopic ultrasound or endoscopic retrograde pacreatocholangiography. The patients with the history of systemic chemotherapy or radiation therapy, coagulopathy, failure to obtain histological confirmation of malignancy were excluded from the study. The samples were collected as follows: an Olympus 180 series upper endoscope was inserted under direct visualization to the second portion of the duodenum. The ampulla was identified and then an endoscopically compatible cytology brush was used to gently sample the endoscopically-normal peri-ampullary mucosa.

Lung

The patients with radiographic confirmation of COPD or histological confirmation of lung malignancy were included in the study while the patients with history of systemic chemotherapy or radiation therapy, coagulopathy, failure to obtain histological confirmation of malignancy were excluded from the study. The samples were collected by gently brushing the visually normal buccal mucosa of the patients using a cytological brush.

The cytology brush obtained from above studies was then applied to a sterile glass slide. The slides were then fixed in an alcohol bath containing 90% ethylalcohol. Though the cytological slide contained different types of cells including epithelial and inflammatory cells, we note that all the measurements mentioned in this manuscript were taken from epithelial cells. This was made possible by directly visualizing the cells before taking the PWS measurements (PWS system contains a flipper mirror that directs the image of a cell into a digital camera for quick visualization).

Statistical methods

All p-values were calculated using Studentized t-tests. Leave-one-out cross validation (LOOCV) was performed with logistic regression in Matlab (Mathworks, Natick, MA) by determining values for each patient without including that patient in the fitting model. Contributions of demographic factors towards the PWS parameters (Ld(g) and σ(g)) were evaluated by performing an Analysis of Variance and Covariance test in STATA (Stata Corp, College Station, TX).

RESULTS AND DISCUSSION

We first confirmed that PWS could distinguish morphologically normal and abnormal cells by examining cytological preparations of brushings from colorectal cancer patients (n=10) and normal patients (n=20). The normal patients had an average age of 59±9 years (mean ± SD) with 40% being males. Similarly, the cancer population had an average age of 71±13 years with 60% being males. First, we noted that both Ld(c) and σ(c) showed no significant difference (P > 0.2, ANOVA) among cancer cells obtained from tumors located at different parts of the colon. Figure 1(a) plots Ld(c) vs. σ(c) for all cells for the normal and cancer groups with each cell being represented by a point:( Ld(c) σ(c)). Clearly, both Ld(c) and σ(c) are increased in cancer cells. This is further illustrated in Figs. 1(b–c) which show that both Ld(g) and σ(g) were highly elevated ((P < 0.001) in the tumor cells when compared to the cells obtained from normal patients. These results agree well with the conventional cytology in that cancer cells show a significant difference in their morphology compared to the normal cells.

Figure 1
(a) Cells at a distance from a colon tumor undergo changes in their internal nanoarchitecture similar to tumor cells. The values of Ld and its intracellular standard deviation σLd averaged over a cell, that is Ld(c) and σ(c), for control ...

We next study the changes in the internal architecture of the cells outside of the spatial extent of tumors in the field of carcinogenesis. The cells were obtained from the patients with colorectal cancer (n = 10), this time from locations greater than 4cm away from the tumor. All cells were cytologically normal. The question we asked was as follows: although appearing normal by the criteria of microscopic histopathology, do these colonocytes possess alterations in their nanoarchitecture? Figures 1(b–c) show that both Ld(g) and σ(g) are highly significantly (p-value<0.001) increased in the cells obtained from outside the tumor boundary compared to those from normal patients. Interestingly, these cells only had a slightly decreased Ld(g) and σ(g) compared to cancer cells. That is, the effect size between controls (no neoplasia) and field carcinogenesis (histologically normal mucosa of patient harbouring neoplasia) was much greater than those between the field carcinogenesis and frankly malignant tissue. This would imply that nanoscale changes are a relatively early event in carcinogenesis. This is further supported by our recent report in the MIN mouse model of colon carcinogenesis (20). This model contains a germline mutation in the adenomatous polyposis coli tumor suppressor gene which results in spontaneous polyp formation at ~10 weeks. We noted profound changes in Ld(g) and σ(g) at 5 weeks that preceded even microadenoma formation indicating that the genetic alterations in the field carcinogenesis results in structural variations at the nanoscale level that is in turn translated into an increase in disorder strength.

From a biological perspective, these studies do not provide definitive information as to the molecular determinants of the disorder strength. However, some insight can be gleaned by our observation that the alterations seem to occur at lc~50 nm (Δn~0.1 (24)). This length scale is well below the diffraction limited resolution of the conventional microscopy, which explains why these cellular changes are not identifiable by conventional histopathology. Also, the length scale corresponds to the size of some of the most fundamental building blocks of the cell, such as ribosomes, components of cytoskeleton and membranes etc. Each of these molecular candidate categories have been implicated in the initiation/progression of carcinogenesis. For instance, ribosome dysregulation has long been thought to play a role in carcinogenesis providing the machinery to increase protein synthesis (25). Many critical proto-oncogenes have been shown to impact upon ribosomal biogenesis including c-Myc (26). With regards to cytoskeleton, the role is well established in neoplastic transformation including processes such as epithelial-mesenchymal transition (27). While less is known about early events in colon carcinogenesis, it bears emphasis that APC, the initiating mutation in most colorectal cancers, interacts with microtubule structure and has important impact on processes such as chromosomal instability, RNA targeting etc (28, 29). Finally, alterations in membrane proteins and fluidity are well established in early neoplastic transformation of the colon (30). Thus, at the length scale of ~50 nm, there are numerous plausible molecular events and some or all may be involved in the alterations in disorder strength. Future studies will aim to elucidate the molecular determinants of these changes in nanoscale architecture.

From a clinical perspective, in order to take the advantage of the field effect detection capabilities of PWS to identify patients at risk for colon carcinogenesis, analysis would need to be performed from a readily accessible site. In the colon, this would be the rectum which is commonly interrogated during physical examination (digital rectal exam). Moreover, it is well established that examination of the rectal mucosa can aid in the prediction of proximal neoplasia. The typical biomarkers to date (aberrant crypt foci, proliferation, apoptosis rates, etc.) have been shown to correlate with proximal neoplasia although the performance characteristics have been inadequate (6, 7, 31). We therefore performed PWS analysis on patients undergoing colonoscopy. Brushings were taken from the endoscopically normal rectal mucosa from 35 patients undergoing complete colonoscopy. In this dataset, 20 patients had no neoplasia detected on colonoscopy, 11 patients harboured non-advanced and 4 patients had advanced adenomas (defined as adenoma ≥1 cm or >25% villous features or presence of high grade dysplasia). The demographic information such as age, smoking, race and gender is shown in Table 1. Figures 2(a–c) show that both Ld(g) and σ(g) are highly significantly elevated in patients with adenoma compared to the control group (P < 0.001). Interestingly, the patients with advanced adenoma (adenoma >10 mm) had the highest Ld(g) and σ(g). Thus a gradient in the increase of Ld(g) and σ(g) in microscopically normal rectal cells parallels the significance of neoplasia. Moreover, if one were to combine the colonic resection and colonoscopy data, the progressive nature is quite striking. Indeed, the Ld(g) of controls (both rectal brushings and benign surgical resections) was 0.3*10−5 µm, patients with non-advanced adenomas were at 0.45*10−5 µm, 0.68*10−5 µm from those with advanced adenomas, 3.0*10−5 µm from uninvolved mucosa of cancer patients and 3.8*10−5 µm for frankly malignant tissue. This is consistent with other field carcinogenesis literature suggesting that the effect size of rectal biomarkers (e.g. ACF) appeared to be greater in patients with more biologically significant lesions.

Figure 2
Cells obtained from histologically normal colonic mucosa have increased disorder strength due to the presence of premalignant tumors anywhere else in colon.
Table 1
Demographic information of the subjects involved in the rectal study and the effect of the patient characteristics on PWS parameters. The table indicates that both Ld(g) and σ(g) are not confounded by the patient demographic factors.

One question that comes up in the above field carcinogenesis study is whether the PWS signatures (i.e., Ld(g) and σ(g)) are sensing the presence of neoplasia or simply confounding factors. For instance, age is one of the key risk factors for colonic neoplasia and there are a variety of age-related changes in the colonic mucosa including methylation effects that are unrelated to neoplasia. We therefore looked at 4 of the key demographic risk factors: age, gender, race and smoking history. As outlined in table 1, there was no significant difference among age or race. Smoking was increased in patients with advanced adenomas as may be expected since smoking is an established risk factor (portending a ~2–3 fold increase risk). We therefore performed an ANCOVA analysis and noted no significant confounding with smoking history (p=0.50 and 0.77 for Ld(g) and σ(g) respectively). Similarly, male gender is a well established risk factor for colonic neoplasia and was slightly over-represented among the advanced adenoma patients. However, ANCOVA analysis supported the assertion that there was no significant confounding (p=0.89 and 0.88 for Ld(g) and σ(g) respectively). The correlation analysis further validated the non significant association between the demographic factors and disorder strength parameters. Taken together, this data supports the robustness of the association between rectal PWS signatures and colonic neoplasia.

Although the dataset is far too small to make any claims regarding the diagnostic ability, we calculated the performance characteristics to further quantify the robustness of the PWS analysis. The preliminary estimate of the area under the receiver operator characteristic curve (AUROC) for PWS analysis of rectal brushings was 0.86 for advanced adenoma and 0.76 for all adenomas. For carcinomas (resection studies), the field carcinogenesis effect was 0.90. These estimates do not seem to be over fitted since the AUROC for all adenomas with leave-one-out cross validation was only minimally decreased to 0.71. We note that the AUROC curves reported were obtained using a single disorder strength parameter of Ld(g) and were not due to the combination of different markers.

Therefore, our data suggests that rectal PWS evaluation may be a powerful means of detecting colonic risk through the identification of field carcinogenesis. We were interested in understanding whether this could potentially be a common theme for many GI cancers. In general, GI neoplasia is a hallmark of field carcinogenesis. There have been numerous elegant studies on esophageal adenocarcinoma with genetically determined clones detectable (32, 33). Recently, a group reported that a microarray signature from non-malignant hepatocytes could predict recurrence in patients who underwent resection with hepatocellular carcinoma underscoring the role of field carcinogenesis (34). In order to assess the utility of our paradigm to other GI cancers, we chose pancreatic cancer given its lethality (fourth leading cause of cancer deaths among Americans) and lack of a robust screening test. Clinically, the major issue is that instrumenting the pancreatic duct to screen for cancer is not only expensive and uncomfortable but has a significant incidence of complications (~5% risk of pancreatitis which sometimes can be fatal). Our approach was to use the concept of extended field carcinogenesis which was espoused by Kopelovich et al (35). They noted that for many cancer types, the fingerprint of neoplastic transformation could be detected outside the organ. This may be related to a diffuse field of injury, shared hormonal milieu, or tumor elaborated factors. For the pancreas, the duodenal mucosa represents a promising target given it is relatively easy and safe to interrogate (via the commonly utilized tests such as esophagogastroduodenoscopy). The biological plausibility is underscored by a report by Matsubayashi and colleagues who demonstrated that evaluating the endoscopically-normal duodenal mucosa for methylation of important tumor suppressor genes allowed discrimination between patients with pancreatic cancer and chronic pancreatitis (36). Therefore, we performed brushings on patients with pancreatic cancer (n=9) and those undergoing upper endoscopy with malignancy (n=26) and obtained brushings from the endoscopically-normal peri-ampullary duodenal mucosa (the demographic information of the patients and their effect on the disorder strength parameters is shown in Table 2). As demonstrated in Figure 3 (a), the scatter plot shows a marked elevation in both Ld(c) and σ(c) of patients with pancreatic cancer when compared to controls (P < 0.0001). This supports the proposition that PWS analysis of field carcinogenesis may be useful for a number of gastrointestinal malignancies.

Figure 3
(a) Histologically normal duodenal mucosa cells have increased disorder strength due to the presence of pancreatic cancer. The Ld(c) and σ(c) obtained from histologically normal duodenal mucosa from patients with pancreatic cancer and with no ...
Table 2
Demographic information of the subjects involved in the pancreatic cancer study and the effect of the patient characteristics on PWS parameters. The table indicates that both Ld(g) and σ(g) are not confounded by the patient demographic factors. ...

Finally we wanted to evaluate whether this concept would translate to malignancies outside the GI track. There would be numerous promising candidates (e.g. urogenetic or gynecological malignancies) but we chose the aerodigestive track since many feel it epitomizes field carcinogenesis (37). In particular, lung cancer serves as a nice marker because of the diffuse field of injury from tobacco use. Recent reports from Spira and colleagues suggest genetic alterations in the endoscopically normal right mainstem bronchial epithelium (38). While the right mainstem bronchus sampling could be viewed as somewhat intrusive, this “field of injury” extends to the buccal (cheek) mucosa (39). Indeed, emerging evidence has suggested that the buccal mucosa may serve as “molecular mirror” for the lung (40). Given that smoking is the most important risk factor for lung cancer and may alter the oral epithelium, we compared buccal cells from lung cancer patients (n=18) with those who were cancer free but had smoked an equivalent amount and thus developed chronic obstructive pulmonary disease, COPD (n=17). The demographic information of the patients and their effect on Ld(g) and σ(g) is given in Table 3. COPD patients were used as a control in order to avoid confounding by smoking and age. As can be seen from the scatter plot (Figure 3 (b)) there is a clear separation between patients with and without lung cancer (P < 0.0001). Thus, this very preliminary data underscores the promise of this approach in the aerodigestive track.

Table 3
Demographic information of the subjects involved in the lung cancer study and their effect on PWS parameters. The table indicates that both Ld(g) and σ(g) are not confounded by the patient demographic factors.

These results demonstrate that despite being cytologically-normal, epithelial cells in the “field” of a tumor have nanoarchitectural changes. Thus, PWS analysis could serve as a marker of field carcinogenesis and hence a novel platform for screening for a variety of cancers. The clinical imperative for this “pre-screen” is that current clinical practice for cancer screening is inadequate and thus many patients refuse to undergo recommended screening. For instance, colonoscopy is expensive, intrusive and has discomfort risks. This is juxtaposed with the observation that the detection rate of significant lesions (advanced adenomas and carcinomas) is only ~5% meaning that 95% of colonoscopies do not have any cancer preventive implications. For lung cancer, no effective population screening option exists with the best candidate, low-dose computerized tomography, hampered by the low prevalence of cancer and high rate of false positives. For pancreatic cancer, CT scans or endoscopic ultrasound are prohibitively cost ineffective with poor sensitivity to early lesions. Thus, we would envision that assessing field carcinogenesis could serve as an inexpensive, minimally intrusive risk-stratification test analogous to the pap smear–colposcopy approach that has been so successful in the management of cervical cancer.

In summary, we demonstrate herein that utilizing a powerful new light scattering technology PWS we are accurately able to detect the nanoscale correlates of field cancerization. In the colon, we demonstrate that the effect is not confined to the proximity of the lesion, but can be detected remotely in readily assessable areas such as the rectum. Moreover, the effect size seemed to be proportional to the severity of the neoplastic lesions. Furthermore, this approach has potential applications for other cancers including GI and aerodigestive track cancers. Thus, PWS analysis of field carcinogenesis (both confined to the organ and extended) may serve as a platform for screening for numerous malignancies. Future studies are planned to ascertain the clinical potential of this novel cancer screening paradigm.

Acknowledgments

Supported in grants from the NIH (R01 EB003682, R01 CA112315, R01 CA128641), NSF (CBET-0733868) and the V Foundation.

Footnotes

Disclosure: Drs. Backman, Roy and Goldberg have patent/license interest in partial wave spectroscopy.

REFERENCES

1. Lewis JD, Ng K, Hung KE, et al. Detection of proximal adenomatous polyps with screening sigmoidoscopy: a systematic review and meta-analysis of screening colonoscopy. Arch Intern Med. 2003;163:413–420. [PubMed]
2. Takayama T, Katsuki S, Takahashi Y, et al. Aberrant crypt foci of the colon as precursors of adenoma and cancer. N Engl J Med. 1998;339:1277–1284. [PubMed]
3. Anti M, Marra G, Armelao F, et al. Rectal epithelial cell proliferation patterns as predictors of adenomatous colorectal polyp recurrence. Gut. 1993;34:525–530. [PMC free article] [PubMed]
4. Bernstein C, Bernstein H, Garewal H, et al. A bile acid-induced apoptosis assay for colon cancer risk and associated quality control studies. Cancer Res. 1999;59:2353–2357. [PubMed]
5. Chen L, Hao C, Chiu Y, et al. Alteration of Gene Expression in Normal-Appearing Colon Mucosa of APCmin Mice and Human Cancer Patients. Cancer Research. 2004;64:3694–3700. [PubMed]
6. Hao CY, Moore DH, Chiu YS, et al. Altered gene expression in normal colonic mucosa of individuals with polyps of the colon. Dis Colon Rectum. 2005;48:2329–2335. [PubMed]
7. Polley AC, Mulholland F, Pin C, et al. Proteomic analysis reveals field-wide changes in protein expression in the morphologically normal mucosa of patients with colorectal neoplasia. Cancer Res. 2006;66:6553–6562. [PubMed]
8. Ushijima T. Epigenetic field for cancerization. J Biochem Mol Biol. 2007;40:142–150. [PubMed]
9. Alberts DS, Einspahr JG, Krouse RS, et al. Karyometry of the colonic mucosa. Cancer Epidemiol Biomarkers Prev. 2007;16:2704–2716. [PubMed]
10. Ranger-Moore J, Frank D, Lance P, et al. Karyometry in rectal mucosa of patients with previous colorectal adenomas. Anal Quant Cytol Histol. 2005;27:134–142. [PubMed]
11. Anderson PW, Thouless DJ, Abrahams E, Fisher DS. New method for a scaling theory of localization. Physical Review B. 1980;22:3519–3526.
12. Kumar N. Resistance fluctuation in a one-dimensional conductor with static disorder. Physical Review B. 1985;31:5513–5515. [PubMed]
13. Rammal R, Doucot B. Invariant imbedding approach to localization. 1. General framework and basic equations. J Phys-Paris. 1987;48:509–526.
14. Pradhan P, Kumar N. Localization of light in coherently amplifying random-media. Phys Rev B. 1994;50:9644–9647. [PubMed]
15. Haley SB, Erdos P. Wave-propagation in one-dimensional disordered structures. Phys Rev B. 1992;45:8572–8584. [PubMed]
16. Anderson PW. Absence of diffusion in certain random lattices. Physical Review. 1958;109:1492–1505.
17. Abrahams E, Anderson PW, Licciardello DC, Ramakrishnan TV. Scaling theory of localization - absence of quantum diffusion in 2 dimensions. Physical Review Letters. 1979;42:673–676.
18. Kramer B, Mackinnon A. Localization - theory and experiment. Reports on Progress in Physics. 1993;56:1469–1564.
19. Liu Y, Li X, Kim YL, Backman V. Elastic backscattering spectroscopic microscopy. Opt Lett. 2005;30:2445–2447. [PubMed]
20. Subramanian H, Pradhan P, Liu Y, et al. Optical methodology for detecting histologically unapparent nanoscale consequences of genetic alterations in biological cells. Proc Natl Acad Sci U S A. 2008;105:20118–20123. [PubMed]
21. Subramanian H, Pradhan P, Liu Y, et al. Partial-wave microscopic spectroscopy detects subwavelength refractive index fluctuations: an application to cancer diagnosis. Opt Lett. 2009;34:518–520. [PMC free article] [PubMed]
22. Bernstein C, Bernstein H, Payne CM, Dvorak K, Garewal H. Field defects in progression to gastrointestinal tract cancers. Cancer Lett. 2008;260:1–10. [PMC free article] [PubMed]
23. Payne CM, Holubec H, Bernstein C, et al. Crypt-restricted loss and decreased protein expression of cytochrome C oxidase subunit I as potential hypothesis-driven biomarkers of colon cancer risk. Cancer Epidemiol Biomarkers Prev. 2005;14:2066–2075. [PubMed]
24. Wilson JD, Cottrell WJ, Foster TH. Index-of-refraction-dependent subcellular light scattering observed with organelle-specific dyes. J Biomed Opt. 2007;12:014010. [PubMed]
25. Ruggero D, Pandolfi PP. Does the ribosome translate cancer? Nat Rev Cancer. 2003;3:179–192. [PubMed]
26. Dai MS, Lu H. Crosstalk between c-Myc and ribosome in ribosomal biogenesis and cancer. J Cell Biochem. 2008;105:670–677. [PMC free article] [PubMed]
27. Bazile F, Pascal A, Arnal I, Le Clainche C, Chesnel F, Kubiak JZ. Complex relationship between TCTP, microtubules and actin microfilaments regulates cell shape in normal and cancer cells. Carcinogenesis. 2009 [PMC free article] [PubMed]
28. McCartney BM, Nathke IS. Cell regulation by the Apc protein Apc as master regulator of epithelia. Curr Opin Cell Biol. 2008;20:186–193. [PubMed]
29. Mili S, Moissoglu K, Macara IG. Genome-wide screen reveals APC-associated RNAs enriched in cell protrusions. Nature. 2008;453:115–119. [PMC free article] [PubMed]
30. Brasitus TA, Dudeja PK, Dahiya R, Brown MD. 1,2-Dimethylhydrazine-induced alterations in colonic plasma membrane fluidity: restriction to the luminal region. Biochim Biophys Acta. 1987;896:311–317. [PubMed]
31. Anti M, Marra G, Armelao F, et al. Rectal epithelial cell proliferation patterns as predictors of adenomatous colorectal polyp recurrence. Gut. 1993;34:525–530. [PMC free article] [PubMed]
32. Brabender J, Marjoram P, Lord RV, et al. The molecular signature of normal squamous esophageal epithelium identifies the presence of a field effect and can discriminate between patients with Barrett's esophagus and patients with Barrett's-associated adenocarcinoma. Cancer Epidemiol Biomarkers Prev. 2005;14:2113–2117. [PubMed]
33. Maley CC, Galipeau PC, Finley JC, et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat Genet. 2006;38:468–473. [PubMed]
34. Hoshida Y, Villanueva A, Kobayashi M, et al. Gene expression in fixed tissues and outcome in hepatocellular carcinoma. N Engl J Med. 2008;359:1995–2004. [PMC free article] [PubMed]
35. Kopelovich L, Henson DE, Gazdar AF, et al. Surrogate anatomic/functional sites for evaluating cancer risk: An extension of the field effect. Clinical Cancer Research. 1999;5:3899–3905. [PubMed]
36. Matsubayashi H, Sato N, Brune K, et al. Age- and disease-related methylation of multiple genes in nonneoplastic duodenum and in duodenal juice. Clin Cancer Res. 2005;11:573–583. [PubMed]
37. Steiling K, Ryan J, Brody JS, Spira A. The Field of Tissue Injury in the Lung and Airway. Cancer Prev Res. 2008;1:396–403. [PMC free article] [PubMed]
38. Spira A, Beane JE, Shah V, et al. Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med. 2007;13:361–366. [PubMed]
39. Sridhar S, Schembri F, Zeskind J, et al. Smoking-induced gene expression changes in the bronchial airway are reflected in nasal and buccal epithelium. BMC Genomics. 2008;9:259. [PMC free article] [PubMed]
40. Kemp RA, Turic B. Can Early Lung Cancer Be Detected From Buccal Mucosal Scrapings? Chest. 2005;128:154S.