- Methodology article
- Open Access
Investigation of nanoscale structural alterations of cell nucleus as an early sign of cancer
© Liu et al.; licensee BioMed Central Ltd. 2014
Received: 8 November 2013
Accepted: 5 February 2014
Published: 10 February 2014
The cell and tissue structural properties assessed with a conventional bright-field light microscope play a key role in cancer diagnosis, but they sometimes have limited accuracy in detecting early-stage cancers or predicting future risk of cancer progression for individual patients (i.e., prognosis) if no frank cancer is found. The recent development in optical microscopy techniques now permit the nanoscale structural imaging and quantitative structural analysis of tissue and cells, which offers a new opportunity to investigate the structural properties of cell and tissue below 200 – 250 nm as an early sign of carcinogenesis, prior to the presence of microscale morphological abnormalities. Identification of nanoscale structural signatures is significant for earlier and more accurate cancer detection and prognosis.
Our group has recently developed two simple spectral-domain optical microscopy techniques for assessing 3D nanoscale structural alterations – spectral-encoding of spatial frequency microscopy and spatial-domain low-coherence quantitative phase microscopy. These two techniques use the scattered light from biological cells and tissue and share a common experimental approach of assessing the Fourier space by various wavelengths to quantify the 3D structural information of the scattering object at the nanoscale sensitivity with a simple reflectance-mode light microscopy setup without the need for high-NA optics. This review paper discusses the physical principles and validation of these two techniques to interrogate nanoscale structural properties, as well as the use of these methods to probe nanoscale nuclear architectural alterations during carcinogenesis in cancer cell lines and well-annotated human tissue during carcinogenesis.
The analysis of nanoscale structural characteristics has shown promise in detecting cancer before the microscopically visible changes become evident and proof-of-concept studies have shown its feasibility as an earlier or more sensitive marker for cancer detection or diagnosis. Further biophysical investigation of specific 3D nanoscale structural characteristics in carcinogenesis, especially with well-annotated human cells and tissue, is much needed in cancer research.
Cancer develops through a series of genetic and epigenetic events that ultimately result in structural changes in the cell nucleus. As such, the structural abnormality of the cell nucleus (also known as nuclear morphology) is one of the hallmarks in cancer and remains the gold standard for cancer diagnosis and prognosis. Due to the diffraction-limited resolution (~250-500 nm) of conventional light microscopy, the characteristic morphological changes identified in cancerous or precancerous cells are limited to mostly micron-scale features, such as increased nuclear size, irregular nuclear shape and coarse chromatin texture. Many structural abnormalities observable at the micro-scale do not occur until an advanced stage, making it difficult to distinguish early-stage cancers from benign conditions. Further, in the era of personalized medicine, the detection of pre-cancer or early-stage cancer is not sufficient. As many pre-cancers or early-stage cancers will never progress into invasive cancer, such detection in fact may lead to unnecessary treatment in the absence of aggressive cancer that does more harm than good to the patient at a high cost. Therefore, it is crucial to not only identify pre-cancer or early-stage cancer, but also predict which pre-cancer or early-stage cancer is likely to develop into a more invasive form (i.e., prognosis). The conventional microscale nuclear morphology has some prognostic value, but its accuracy is somewhat limited in many clinical scenarios.
On the other hand, the nanoscale structural properties, also referred to as “nano-morphology”, show the potential to become a new class of morphological markers for earlier and more accurate cancer diagnosis and prognosis. It is well recognized that cancer is a complex disease involving early changes in the genome and epigenome . The nucleus, as the storehouse of the genomic information, is not a homogeneous organelle with randomly organized DNA; instead, the DNAs are packed at various densities and spatially arranged in a certain manner in a 3D space that is associated with nuclear function [2–4]. Recent studies using super-resolution microscopy also confirm that histone octamers are not randomly distributed throughout the nucleus and that pronounced differences are seen in the compaction of chromatin with such fluctuation in histone density . The spatial organization of specific chromatin domains with a size in the hundred nanometer range also plays an essential role for gene regulation . During carcinogenesis, the 3D spatial arrangement of chromatin patterns experience translocation and alterations in the spatial density of chromatin at different loci of the nucleus. For example, the large-scale changes in 3D genomic architecture or the changes in spatial distribution of chromosome have been reported in cancer [6, 7]. Therefore, we hypothesize that the complex genomic and epigenomic changes in carcinogenesis result in nanoscale structural alterations arising from the changes in the 3D spatial arrangement and the chromatin density variation in the cell nucleus. In other words, investigating the nano-morphology characteristics as the downstream structural manifestation of complex genetic and epigenetic events regardless of which molecular pathways are involved in carcinogenesis is an important effort. As such physical characteristics can be detected easily with low-cost, high throughput and high sensitivity, yet independent of molecular heterogeneity, they have the potential to become a new class of cancer markers to make a significant clinical impact. For example, the analysis of cellular disorder strength has been reported to detect nano-architectural changes early in carcinogenesis that precede microscopically detectable cytological abnormalities  and show the ability to detect cancer from normal cells from a remote location in lung, colon and pancreas [9–11].
Elucidation of 3D nano-morphological changes in cancer requires tools that are able to interrogate nano-structures in the cell nucleus and other sub-cellular components. Thanks to the remarkable advances in optical microscopy techniques in recent years, the advanced light microscope now supports the detection of structural properties at a scale about an order of magnitude less than what conventional light microscope can detect. The nanoscale structural characteristics can be measured either using direct imaging with nanoscale resolution, or indirect analysis of optical signals from light-cell interaction. The direct nanoscopic imaging can be achieved by super-resolution fluorescence microscopy techniques, such as stochastic optical reconstruction microscopy (STORM) , photoactivatable localization microscopy (PALM) , stimulated emission depletion microscopy (STED)  and 3D structured illumination microscopy (3D-SIM) . These super-resolution microscopy techniques have the ability to directly image the nanoscale architecture of any labeled molecular component in live and fixed cells and even tissue at a spatial resolution down to 20–50 nm. The label-free nanoscopic imaging of biological cells at a resolution of 90 nm based on optical diffraction tomography has also been reported recently . A few investigators have pioneered the investigation of 3D nanoscopic imaging of nuclear architecture in cancer cells [5, 17]. As the super-resolution fluorescence microscopy becomes commercially available, it will play an essential role in elucidating how nanoscale structural arrangement in the nucleus is altered during carcinogenesis. While these are powerful basic research tools, the clinical translation of these techniques has several challenges to overcome. Due to the complex fluorescent staining process, high cost, sophisticated instrument operation and the very low throughput, they are not well suited as a routine clinical diagnostic tool at the current form.
An alternative to direct nanoscopic imaging is indirect measurement of nanoscale structural properties by probing optical properties via scattered light. Although it often does not directly visualize the structures at nanoscale resolution [as is the case of super-resolution imaging], the structural properties from a single cell or sub-cellular organelle can be indirectly quantified with nanoscale sensitivity and accuracy by light-scattering based microscopy techniques. Light scattering is an intrinsic optical signal caused by the spatial variation of intra-cellular macromolecular densities. This approach has the advantages of simple sample preparation (no molecular staining or labeling required), simple instrument and operation, low cost, high throughput and high sensitivity. Such advantages are crucial in translating these techniques into a real clinical setting to improve cancer diagnosis and prognosis.
A wide variety of light-scattering microscopy techniques have been developed to analyze the nano-morphology characteristics, and can be generalized into the following four categories based on the underlying physical principles to achieve nanoscale structural assessment. Please note that these are broad categories that are not mutually exclusive, and in fact, can and do have overlap. The first form is to quantify the cell structure by measuring phase difference using interferometry-based approach, such as various versions of quantitative phase microscopy and digital holographic microscopy (DHM) . The light interference effect is well known to detect changes in optical path length even at sub-nanometer sensitivity. The second form is based on the analysis of Fourier space (or K-space, the conjugate of an object) of scattered light, such as optical scatter imaging  and spectral-encoding of spatial frequency (SESF) [20–22]. This approach is based on the concept that any scattering object’s structure can be described either by the spatial distribution of refractive index or its Fourier components in the far-field . Although the image resolution is still limited by diffraction, the 2D or 3D structural characteristics of a scattering object can be quantified with a nanoscale precision by directly assessing the spatial frequencies in K-space. The third form is to combine microscopic imaging with light scattering spectroscopy. In this case, the scattered light is collected as a function of scattering wavelength or/and angle. Assuming the scattering object as a spherical or spheroid shape, the structural parameters such as size distribution from a well-defined microscopic region are derived from a model-based interpretation (e.g., Mie-theory, T-matrix). For example, in confocal light absorption and scattering spectroscopic microscopy , the smallest scatterer is about 100 nm . The fourth form is referred to as partial-wave spectroscopy that characterizes the statistical properties of refractive index fluctuation by disorder strength  which is proportional to the amplitude and the length scale of the macromolecular density variations at the scale of ~20 nm.
In this paper, we will focus on reviewing the use of two spectral-domain optical microscopy techniques – spatial-domain low-coherence quantitative phase microscopy (SL-QPM) and spectral-encoding of spatial frequency (SESF) microscopy – from the first two-categories to interrogate the nanoscale structural information. First, we review the general theory behind SL-QPM and SESF microscopy and why the nanoscale structural alterations can be interrogated. Next, we discuss the technical implementation and how these techniques are designed to analyze the human cell and tissue samples. In the third section, we present the results of how nanoscale nuclear architecture is altered during carcinogenesis in cancer cell lines and well-annotated human tissue at different stages of cancer.
The SL-QPM and SESF microscopy are two optical microscopy systems that are able to assess the 3D nanoscale structural information with just simple reflection-mode optical microscopy setup, without high-NA immersion objectives or demanding nano-positioning mechanical scanning, well-suited for low-cost and high throughput clinical use. They share a common theory of light scattering by an inhomogeneous scattering object and first Born approximation . It does not assume any a priori information about the scattering object (e.g., shape, size) and the only assumption is that the scattering object is a weakly scattering object with relative refractive index between the scattering object and surrounding medium is close to 1, which can be broadly applied to live or fixed biological cells and tissue with easy sample preparation. Both methods also share a common experimental approach of assessing the Fourier space (i.e., K-space) by various wavelengths to quantify the structural information of the scattering object, which can be easily implemented with tunable light source or spectral device. Further, both techniques are capable of assessing 3D nanoscale structural information without the need for axial scanning.
General theory of light scattering by an inhomogeneous object
Therefore, the scattering amplitude of the scattering object under first Born approximation depends only on the vector K defined in Eq. (5), or Fourier components of the scattering potential [23, 26].
If the complex amplitudes of all of the possible 3D Fourier components (or spatial frequencies) are collected, the 3D scattering object (scattering potential) can be reconstructed via 3D inverse Fourier transform, which serves as the basis for optical diffraction tomography [23, 27]. However, the 3D structure in the reconstructed scattering object still has the diffraction-limited resolution due to the NA-limited accessible bandwidth of Fourier components and integration process of Fourier transform. A recent advance overcame this limitation by expanding the collected spatial frequencies of the scattering object using a high-NA oil immersion objective together with a deconvolution algorithm to achieve a resolution of 90 nm  in the reconstructed 3D scattering object.
Alternatively, based on the above theory, the nanoscale structural characteristics of the 3D scattering object can also be interrogated via two simple light microscopy systems using a moderate NA (NA ≤ 0.5): Fourier-filtering based SESF and a spectral interferometry based SL-QPM. These approaches do not directly image the scattering object at the nanoscale resolution, but quantify the nanoscale structural information by employing the spectral information of scattered light from the 3D scattering object. These approaches can be implemented with simple optical setup and are widely applicable to live or fixed biological cells, as well as clinically prepared fixed tissue.
Spectral-encoding of Spatial Frequency (SESF)
General description of SESF
Spectral-encoding of spatial frequency (SESF) is a simple way to quantify the nanoscale structure of a 3D scattering object by encoding each spectral wavelength with a structure-characterizing axial spatial frequency [20, 21]. According to the Fourier theory of image formation, the structural components of a complex object can be quantified by a distribution of spatial frequencies in the Fourier space, describing its various spatial scales from large (i.e., low spatial frequency) to small (i.e., high spatial frequency). Thus, each pixel in the microscopic image is represented by a distribution of spectral colors characteristic of the corresponding axial structure at that image point. The 3D axial structure at each pixel can thus be quantified at nanoscale accuracy with a simple reflection-configuration optical microscope setup. It also provides a unique structure-color based image contrast and real-time structural characterization.
Furthermore, if the complex amplitude of the backscattered light in the Fourier space can be collected, when applying the SESF principle, the simultaneous reconstruction of 3D tomographic image and the quantitative characterization of 3D structural information at the nanoscale accuracy from any volume of interest within the 3D object can also be realized .
For example, for a normal incidence (θ = 0°) and the light collection NA of 0.5 (α = 30°), the estimated uncertainty for axial spatial period is ΔH z = 20 nm with the corresponding maximum possible error of ±10 nm. A smaller NA results in a smaller error, however, there is an inherent trade-off between the image resolution and the accuracy in axial structural characterization.
Experimental demonstration using a model system
Depth-resolved spatial-domain low-coherence quantitative phase microscopy (SL-QPM)
Along with assessing the nanoscale structural information in K-space, the 3D nanoscale structure of a scattering object can also be quantified using the quantitative phase information derived from a modified spectral interferometry approach. As discussed above, the scattered wave from an inhomogeous weakly scattered object can be depicted by the Ewald’s sphere [23, 30], and the 3D spatial frequency, after being scattered from the scattering object, is given by K = k s – k i .
Compared to other spectral-domain interferometry setups, the unique aspect of the SL-QPM is that it takes advantage of the small refractive index mismatch between the sample and the mounting medium in the clinically prepared biological sample and implicit coherent gating inherent in the spectral interferometry to detect the sub-resolution internal structural change in a depth-resolved manner, rather than the sample thickness difference (further discussion below).
where zopl is the fixed optical depth location, Im and Re denote the imaginary and real parts of the complex convolution p(z opl ) respectively, and δp(zopl) is the optical path length difference (OPD) at a specific optical depth location zopl, which is not limited by the resolution of optical system and can be used to probe the nanoscale structural changes of the biological cell.
The structural sensitivity, which is defined as the ability of this system to detect the smallest OPD change, is not limited by the resolution of light microscopy, but limited by the system stability. We investigated the temporal stability of the depth-resolved values at the fixed optical depth locations of 1.5 μm, 3 μm, 4.5 μm, and 6 μm, respectively. The depth-resolved values are relatively stable with a mean standard deviation around 1 nm due to temporal fluctuations, which is 0.76 nm, 0.78 nm, 0.86 nm and 1.2 nm at the optical depth locations of 1.5 μm, 3 μm, 4.5 μm, and 6 μm respectively. This standard deviation of mean OPD value of ~1 nm determines the nanoscale sensitivity. Please note that the nanoscale sensitivity is not nanoscale resolution. It does not directly image an object at the nanoscale resolution, but detect the structural changes at the sensitivity of ~ 1 nm. So the experimental interpretation of OPD value is only meaningful in the context of comparing the relative structural changes.
Analysis of SL-QPM internal nanoscale structural changes
Our goal is to use SL-QPM to probe the nanoscale structural changes associated with the biological processes. However, in most spectral interferometry setup, the nanoscale change in OPL comes from the structural changes at a distinct physical interface with a strong refractive-index mismatch. In most cell or tissue preparation, the biological cells have a strongest refractive index mismatch at the interface of cell and mounting medium. As a result, such measurement often reflects the surface variation of the cell rather than the internal structural changes. The cell surface variation is sometimes non-specific and subject to the cell preparation artifact.
To probe the nanoscale changes in the internal structure of the cell or tissue, we prepared the biological samples with a small refractive index mismatch between the sample and the mounting medium. Thus the sample wave predominately comes from backscattered waves from inside the scattering sample, not the reflection from the sample-mounting medium interface.
Validation of SL-QPM to probe internal nanoscale structural changes
Results and discussion
In this section, we will show some examples of using SESF and SL-QPM based methods to detect nanoscale structural changes in a fundamental biological process important in cancer, as well as to demonstrate the ability to detect pre-cancerous changes in clinical samples beyond what conventional light microscopy can detect.
Nanoscale structural changes in abnormal cell growth
Nanoscale structural changes in pre-cancerous cervical cells
Nanoscale structural changes in breast tissue
We also conducted a proof-of-concept study using archived breast tissue to investigate how nuclear nano-architecture changes in breast tumorigenesis with SL-QPM . We analyzed the OPD values in the cell nucleus from well-annotated archived histology specimens processed according to standard clinical protocol. The specimens came from a total of 154 women: 24 healthy patients undergoing reduction mammoplasty; 14 patients with benign lesions; 25 patients with proliferative lesions (10 without atypia, 15 with atypia without co-existing IBC); and 32 patients with IBC whose histologically normal cells adjacent to tumor (‘malignant-adjacent’ normal) were analyzed; and 59 IBC patients whose malignant cells were analyzed. Among these lesions, normal, non-proliferative benign and proliferative lesions without atypia are considered as low-risk lesions (relative risk of 1–1.88 ) and patients with these lesions are not treated; while proliferative lesions with atypia has a significantly increased risk for breast cancer (relative risk of 4.24) and patients with this lesion are typically treated by both surgery and chemopreventive drug. The malignant-adjacent normal cells are no longer “normal”, because although these cells appear microscopically “normal” to pathologists, malignant tumor is already present in adjacent locations. Those malignant cells present microscopically detectable features characteristic of cancer cells. Therefore, this sequence of normal to benign, to proliferative without atypia to with atypia, to malignant-adjacent normal, to malignant cells represents a progressively increased severity in breast tumorigenesis.
This proof-of-concept study demonstrates that nuclear nano-morphology markers, derived from SL-QPM, show great promise to detect breast cancer with a high accuracy beyond conventional pathology. These nuclear nano-morphology markers are based on the detection of nanoscale structural characteristics, which otherwise cannot be appreciated using light microscopy or digital image analysis.
The analysis of nanoscale structural characteristics has shown some promise in detecting cancer before the microscopically visible changes become evident and several proof-of-concept studies using clinical patient samples have also shown its feasibility as an earlier or more sensitive marker for cancer detection or diagnosis in a clinical setting. From a basic science perspective, we will need further understanding and validation to identify specific 3D nanoscale structural characteristics as a downstream manifestation of complex molecular changes in carcinogenesis via direct super-resolution imaging of the 3D nuclear architecture in carcinogenesis using well-annotated human tissue from different tumor types. It remains an important biophysical question to be addressed. For example, what are specific 3D high-order chromatin structural alterations at the nanoscale in the development of cancer? How are they affected by molecular heterogeneity of the tumor? How do they change as a response to anti-cancer treatment? Ultimately, the elucidation of specific nanoscale structural characteristics together with the development of cost-effective and clinically applicable tools to accurately interrogate these nanoscale structural features in a high-throughput manner will have a significant potential clinical impact in bringing a new class of cancer markers for “personalized” cancer detection, diagnosis, prognosis, or monitoring of drug response or tumor recurrence.
All research was performed with the approval of the institutional review board at University of Pittsburgh.
We acknowledge the significant support from Drs. Rohit Bhargava, Douglas Hartman and Randall Brand who contributed the clinical samples and clinical expertise to generate the results discussed in this article.
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