Marker-free phenotyping of tumor cells by fractal analysis of reflection interference contrast microscopy images

Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy

Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm2) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient's slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist.

Morphological profiling by high-throughput single-cell biophysical fractometry

Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles a smaller part of itself. Although fractal variations in cells are proven to be closely associated with the disease-related phenotypes that are otherwise obscured in the standard cell-based assays, fractal analysis with single-cell precision remains largely unexplored. To close this gap, here we develop an image-based approach that quantifies a multitude of single-cell biophysical fractal-related properties at subcellular resolution. Taking together with its high-throughput single-cell imaging performance (~10,000 cells/sec), this technique, termed single-cell biophysical fractometry, offers sufficient statistical power for delineating the cellular heterogeneity, in the context of lung-cancer cell subtype classification, drug response assays and cell-cycle progression tracking. Further correlative fractal analysis shows that single-cell biophysical fractometry can enrich the standard morphological profiling depth and spearhead systematic fractal analysis of how cell morphology encodes cellular health and pathological conditions.

Subtle Immunoreactivity Differences in the Fractal Patterns of Membrane E-Cadherin in Gastric Adenocarcinoma

Gastric cancer continues to be a significant malignancy worldwide, accounting for approximately one million new cases in 2020. Scientists are focusing on the cancerous cells' plasma membrane (PM) as a potential therapeutic target in cancer because it functions as the cell's interface with its environment through a variety of mechanisms. The capacity of membrane shape and its structures to influence biological processes frequently occurs through the regulation of enzymes or preferential protein binding to membranes via membrane shape changes. We aimed here to assess the morphological irregularities of the cellular membranes in gastric adenocarcinoma tumors, and to find any putative differences from normal gastric mucosae epithelial cells. We analyzed the pattern of E-cadherin at the level of the cell membrane using the fractal dimension (FD) analysis on fluorescence immunohistochemistry samples labeled with E-cadherin in gastric well/moderate and solid gastric adenocarcinoma from patients without any associated chemotherapeutic treatment or radiotherapy. Images were binarized based on a fixed threshold of the E-cadherin fluorescence channel, and then the FD of the binarized image outlines has been calculated in order to assess the ruggedness of the cellular membranes. Overall assessment of the FD revealed that the subtle membrane variations were evident enough to deem a statistically significant difference and the complexity of the membrane roughness was clearly higher for adenocarcinoma cases. We intended to evaluate if separating adenocarcinoma cases as low grade (G1 and G2) and high grade (G3 and solid), FD analysis could still differentiate membrane patterns and check if the available clinical parameters like age, gender, tumor location, lymph ganglia involved might correlate with FD values for adenocarcinoma patients. Altogether, the morphological analysis of a simple marker for the cell membrane can identify and distinguish tumor cells. Although there was a limited correlation between this analysis and the main clinical and pathological indicators of the disease, it will be very useful in the future for automatic computer-assisted diagnosis on slides, as well as for evaluating cellular adhesion and inter-cellular trafficking in cancer cells.

An Online Pattern Recognition-Oriented Workshop to Promote Interest among Undergraduate Students in How Mathematical Principles Could Be Applied within Veterinary Science

Knowing the importance of mathematics and its relationship with veterinary medicine plays an important role for students. To promote interest in this relationship, we developed the workshop “Math in Nature” that utilizes the surrounding environment for stimulating pattern-recognition and observational skills. It consisted of four sections: A talk by a professional researcher, a question-and-answer section, a mathematical pattern identification session, and a discussion of the ideas proposed by students. The effectiveness of the program to raise interest in mathematics was evaluated using a questionnaire applied before and after the workshop. Following the course, a higher number of students agreed with the fact that biological phenomena can be explained and predicted by applying mathematics, and that it is possible to identify mathematical patterns in living beings. However, the students’ perspectives regarding the importance of mathematics in their careers, as well as their interest in deepening their mathematical knowledge, did not change. Arguably, “Math in Nature” could have exerted a positive effect on the students’ interest in mathematics. We thus recommend the application of similar workshops to improve interests and skills in relevant subjects among undergraduate students.

Bifurcation and chaos analysis of tumor growth

In this paper, a dynamic model given by three-dimensional ordinary differential equations is studied to determine how the dynamics of tumor growth is controlled by some key parameters. By varying the competition coefficient between healthy host cells and tumor cells, a Hopf bifurcation occurs in this system, leading to the creation of a stable limit cycle. Through numerical analysis of the continuity of this limit cycle, we find that the cascade of period-doubling bifurcations leads to the generation of a chaotic attractor. Moreover, the region of attractors is shown in the parameter space. Numerical simulations, bifurcation diagrams, Lyapunov exponent graph and phase portraits permit to highlight the rich and complex phenomena presented by the model.

The Effect of Geometry and TGF-β Signaling on Tumor Cell Migration from Free-Standing Microtissues

Recapitulation of 3D multicellular tissues in vitro is of great interest to the field of tumor biology to study the integrated effect of local biochemical and biophysical signals on tumor cell migration and invasion. However, most microengineered tissues and spheroids are unable to recapitulate in vitro the complexities of 3D geometries found in vivo. Here, lithographically defined degradable alginate microniches are presented to produce free-standing tumor microtissues, with precisely controlled geometry, high viability, and allowing for high cell proliferation. The role of microtissue geometry and TGF-β signaling in tumor cell migration is further investigated. TGF-β is found to induce the expression of p-myosin II, vimentin, and YAP/TAZ nuclear localization at the periphery of the microtissue, where enhanced nuclear stiffness and orientation are also observed. Upon embedding in a collagen matrix, microtissues treated with TGF-β maintain their geometric integrity, possibly due to the higher cell tension observed around the periphery. In contrast, cells in microtissues not treated with TGF-β are highly mobile and invade the surrounding matrix rapidly, with the initial migration strongly dependent on the local geometry. The microtissues presented here are promising model systems for studying the influence of biophysical properties and soluble factors on tumor cell migration.

Interferometric Scattering Microscopy: Seeing Single Nanoparticles and Molecules via Rayleigh Scattering

Fluorescence microscopy has been the workhorse for investigating optical phenomena at the nanometer scale but this approach confronts several fundamental limits. As a result, there have been a growing number of activities toward the development of fluorescent-free imaging methods. In this Mini Review, we demonstrate that elastic scattering, the most ubiquitous and oldest optical contrast mechanism, offers excellent opportunities for sensitive detection and imaging of nanoparticles and molecules at very high spatiotemporal resolution. We present interferometric scattering (iSCAT) microscopy as the method of choice, explain its theoretical foundation, discuss its experimental nuances, elaborate on its deep connection to bright-field imaging and other established microscopies, and discuss its promise as well as challenges. A showcase of numerous applications and avenues made possible by iSCAT demonstrates its rapidly growing impact on various disciplines concerned with nanoscopic phenomena.

Lamellipod Reconstruction by Three-Dimensional Reflection Interference Contrast Nanoscopy (3D-RICN)

There are very few techniques to reconstruct the shape of a cell at nanometric resolution, and those that exist are almost exclusively based on fluorescence, implying limitations due to staining constraints and artifacts. Reflection interference contrast microscopy (RICM), a label-free technique, permits the measurement of nanometric distances between refractive objects. However, its quantitative application to cells has been largely limited due to the complex interferometric pattern caused by multiple reflections on internal or thin structures like lamellipodia. Here we introduce 3D reflection interference contrast nanoscopy, 3D-RICN, which combines information from multiple illumination wavelengths and aperture angles to characterize the lamellipodial region of an adherent cell in terms of its distance from the surface and its thickness. We validate this new method by comparing data obtained on fixed cells imaged with atomic force microscopy and quantitative phase imaging. We show that as expected, cells adhering to micropatterns exhibit a radial symmetry for the lamellipodial thickness. We demonstrate that the substrate-lamellipod distance may be as high as 100 nm. We also show how the method applies to living cells, opening the way for label-free dynamical study of cell structures with nanometric resolution.

Label-Free Imaging of Melanoma with Confocal Photothermal Microscopy: Differentiation between Malignant and Benign Tissue

Label-free confocal photothermal (CPT) microscopy was utilized for the first time to investigate malignancy in mouse skin cells. Laser diodes (LDs) with 405 nm or 488 nm wavelengths were used as pumps, and a 638 nm LD was used as a probe for the CPT microscope. A Grey Level Cooccurrence Matrix (GLCM) for texture analysis was applied to the CPT images. Nine GLCM parameters were calculated with definite definitions for the intracellular super-resolved CPT images, and the parameters Entropy, Contrast, and Variance were found to be most suited among the nine parameters to discriminate clearly between healthy cells and malignant cells when a 405 nm pump was used. Prominence, Variance, and Shade were most suited when a pump wavelength of 488 nm was used.

Quantitative second harmonic generation microscopy for the structural characterization of capsular collagen in thyroid neoplasms

Quantitative second harmonic generation microscopy was used to investigate collagen organization in the fibrillar capsules of human benign and malignant thyroid nodules. We demonstrate that the combination of texture analysis and second harmonic generation images of collagen can be used to differentiate between capsules surrounding the thyroid follicular adenoma and papillary carcinoma nodules. Our findings indicate that second harmonic generation microscopy can provide quantitative information about the collagenous capsule surrounding both the thyroid and thyroid nodules, which may complement traditional histopathological examination.

Gray-level co-occurrence matrix analysis of several cell types in mouse brain using resolution-enhanced photothermal microscopy

Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.

Quantitative index imaging of coculture cells by scanning focused refractive index microscopy

We report the quantitative refractive index (RI) imaging of cocultured cells in their living environment by scanning focused refractive index microscopy (SFRIM). Mouse microglial cells and synovial cells are cocultured on the top surface of a trapezoid prism. The RI imaging of living cells is obtained in a reflection-type method. The RI information is deduced with the simple derivative total internal reflection method, where a complex retrieval algorithm or reconstruction process is unnecessary. The outline of each cell is determined according to the RI value compared with that of the immersion liquid. The cocultured cells can be discriminated in the RI image. The measurement is nondestructive and label-free. The experimental results prove that SFRIM is a promising tool in the field of biological optics.

Unique fractal evaluation and therapeutic implications of mitochondrial morphology in malignant mesothelioma

Malignant mesothelioma (MM), is an intractable disease with limited therapeutic options and grim survival rates. Altered metabolic and mitochondrial functions are hallmarks of MM and most other cancers. Mitochondria exist as a dynamic network, playing a central role in cellular metabolism. MM cell lines display a spectrum of altered mitochondrial morphologies and function compared to control mesothelial cells. Fractal dimension and lacunarity measurements are a sensitive and objective method to quantify mitochondrial morphology and most importantly are a promising predictor of response to mitochondrial inhibition. Control cells have high fractal dimension and low lacunarity and are relatively insensitive to mitochondrial inhibition. MM cells exhibit a spectrum of sensitivities to mitochondrial inhibitors. Low mitochondrial fractal dimension and high lacunarity correlates with increased sensitivity to the mitochondrial inhibitor metformin. Lacunarity also correlates with sensitivity to Mdivi-1, a mitochondrial fission inhibitor. MM and control cells have similar sensitivities to cisplatin, a chemotherapeutic agent used in the treatment of MM. Neither oxidative phosphorylation nor glycolytic activity, correlated with sensitivity to either metformin or mdivi-1. Our results suggest that mitochondrial inhibition may be an effective and selective therapeutic strategy in mesothelioma, and identifies mitochondrial morphology as a possible predictor of response to targeted mitochondrial inhibition.

Quantitative Evaluation of Cancer Cell Adhesion to Self-Assembled Monolayer-Patterned Substrates by Reflection Interference Contrast Microscopy

Adhesion of cancer cells with different metastatic potential and anticancer drug resistance has been quantitatively evaluated by using self-assembled monolayer (SAM)-patterned substrates and reflection interference contrast microscopy (RICM). Cell-adhesive SAM spots with optimized diameter could prevent cell-cell adhesion and thus allowed the systematic evaluation of statistically reliable numbers of contact area between single cancer cells and substrates by RICM. The statistical image analysis revealed that highly metastatic mouse melanoma cells showed larger contact area than lowly metastatic cells. We also found that both cancer cell types exhibited distinct transition from the "strong" to "weak" adhesion states with increase in the concentration of (-)-epigallocatechin gallate (EGCG), which is known to exhibit cancer preventive activity. Mathematical analysis of the adhesion transition revealed that adhesion of the highly metastatic mouse melanoma cells showed more EGCG tolerance than that of lowly metastatic cells. Moreover, time-lapse RICM observation revealed that EGCG weakened cancer cell adhesion in a stepwise manner, probably via focal adhesion complex. These results clearly indicate that contact area can be used as a quantitative measure for the determination of cancer phenotypes and their drug resistance, which will provide physical insights into the mechanism of cancer metastasis and cancer prevention.

In vitro cancer cell-ECM interactions inform in vivo cancer treatment

The general progression of cancer drug development involves in vitro testing followed by safety and efficacy evaluation in clinical trials. Due to the expense of bringing candidate drugs to trials, in vitro models of cancer cells and tumor biology are required to screen drugs. There are many examples of drugs exhibiting cytotoxic behavior in cancer cells in vitro but losing efficacy in vivo, and in many cases, this is the result of poorly understood chemoresistant effects conferred by the cancer microenvironment. To address this, improved methods for culturing cancer cells in biomimetic scaffolds have been developed; along the way, a great deal about the nature of cancer cell-extracellular matrix (ECM) interactions has been discovered. These discoveries will continue to be leveraged both in the development of novel drugs targeting these interactions and in the fabrication of biomimetic substrates for efficient cancer drug screening in vitro.

Models for Allee effect based on physical principles

We propose some models of single species with Allee effect based on physical principles. A method is used to obtain the expression for the per capita growth rate (a macroscopic information) starting from the characteristics of interactions between the individuals (a microscopic information). We assume that the agents in a model of a single species interact according to the distance between them. Moreover these agents must (i) cooperate with their nearest neighbors, (ii) compete with neighbors at an intermediate distance, and (iii) being indifferent to those who are far away. Using these assumptions and based on fundamental physical principles, we find what appears to be a new way of establishing models of single species with Allee effect.

Elasto-plasticity in wrinkled polymerized lipid membranes

Biomembranes shown to behave like elastic sheets, can also suffer plastic deformations. Neutron scattering experiments on partially polymerised wrinkled membranes revealed that when a critical degree of polymerisation is crossed, the wrinkled membranes do not resume their spherical shapes. Instead they remain wrinkled and rigid while their non-polymerised counterparts resume their spherical floppy shapes. The yield stress of these membranes, measured for the first time via the fractal dimension, is intimately related to the degree of polymerisation probably through a 2D disorder that quenches the lateral diffusion of the lipid molecules. This work might shed light on the physical reason behind the irreversible deformation of echinocytes, acanthocytes and malaria infected red blood cells.