Compressive hyperspectral microscopy for cancer detection.

Significance: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs. Aim: We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution. Approach: The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images. Results: We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within ∼1 s. This means that a typical 1×1 cm2 biopsy can be measured in ∼10 min. The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm. Conclusions: CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics.

Cancer detection from stained biopsies using high-speed spectral imaging.

The escalating demand for diagnosing pathological biopsies requires the procedures to be expedited and automated. The existing imaging systems for measuring biopsies only measure color, and even though a lot of effort is invested in deep learning analysis, there are still serious challenges regarding the performance and validity of the data for the intended medical setting. We developed a system that rapidly acquires spectral images from biopsies, followed by spectral classification algorithms. The spectral information is remarkably more informative than the color information, and leads to very high accuracy in identifying cancer cells, as tested on tens of cancer cases. This was improved even more by using artificial intelligence algorithms that required a rather small training set, indicating the high level of information that exists in the spectral images. The most important spectral differences are observed in the nucleus and they are related to aneuploidy in tumor cells. Rapid spectral imaging measurement therefore can bridge the gap in the machine-aided diagnostics of whole biopsies, thus improving patient care, and expediting the treatment procedure.

Chromatin dynamics governed by a set of nuclear structural proteins.

During the past three decades, the study of nuclear and chromatin organization has become of great interest. The organization and dynamics of chromatin are directly responsible for many functions including gene regulation, genome replication, and maintenance. In order to better understand the details of these mechanisms, we need to understand the role of specific proteins that take part in these processes. The genome in the nucleus is organized in different length scales, ranging from the bead-like nucleosomes through topological associated domains up to chromosome territories. The mechanisms that maintain these structures, however, remain to be fully elucidated. Previous works highlighted the significance of lamin A, an important nucleoplasmic protein; however, there are other nuclear structural proteins that are also important for chromatin organization. Studying the organizational aspects of the nucleus is a complex task, and different methods have been developed and adopted for this purpose, including molecular and imaging methods. Here we describe the use of the live-cell imaging method and demonstrate that the dynamics of the nucleus is strongly related to its organizational mechanisms. We labeled different genomic sites in the nucleus and measured the effect of nuclear structural proteins on their dynamics. We studied lamin A, BAF, Emerin, lamin B, CTCF, and Cohesin and discuss how each of them affect chromatin dynamics. Our findings indicate that lamin A and BAF have a significant effect on chromosomes dynamics, while other proteins mildly affect the type of the diffusion while the volume of motion is not affected.

Genome organization in the nucleus: From dynamic measurements to a functional model.

A biological system is by definition a dynamic environment encompassing kinetic processes that occur at different length scales and time ranges. To explore this type of system, spatial information needs to be acquired at different time scales. This means overcoming significant hurdles, including the need for stable and precise labeling of the required probes and the use of state of the art optical methods. However, to interpret the acquired data, biophysical models that can account for these biological mechanisms need to be developed. The structure and function of a biological system are closely related to its dynamic properties, thus further emphasizing the importance of identifying the rules governing the dynamics that cannot be directly deduced from information on the structure itself. In eukaryotic cells, tens of thousands of genes are packed in the small volume of the nucleus. The genome itself is organized in chromosomes that occupy specific volumes referred to as chromosome territories. This organization is preserved throughout the cell cycle, even though there are no sub-compartments in the nucleus itself. This organization, which is still not fully understood, is crucial for a large number of cellular functions such as gene regulation, DNA breakage repair and error-free cell division. Various techniques are in use today, including imaging, live cell imaging and molecular methods such as chromosome conformation capture (3C) methods to better understand these mechanisms. Live cell imaging methods are becoming well established. These include methods such as Single Particle Tracking (SPT), Continuous Photobleaching (CP), Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS) that are currently used for studying proteins, RNA, DNA, gene loci and nuclear bodies. They provide crucial information on its mobility, reorganization, interactions and binding properties. Here we describe how these dynamic methods can be used to gather information on genome organization, its stabilization mechanisms and the proteins that take part in it.