High-resolution microscopy for imaging cancer pathobiology

Abstract

Purpose of review: Light microscopy plays an essential role in clinical diagnosis and understanding the pathogenesis of cancer. Conventional bright-field microscope is used to visualize abnormality in tissue architecture and nuclear morphology, but often suffers from many limitations. This review focuses on the potential of new imaging techniques to improve basic and clinical research in pathobiology.

Recent findings: Light microscopy has significantly expanded its ability in resolution, imaging volume, speed and contrast. It now allows 3D high-resolution volumetric imaging of tissue architecture from large tissue and molecular structures at nanometer resolution.

Summary: Pathologists and researchers now have access to various imaging tools to study cancer pathobiology in both breadth and depth. Although clinical adoption of a new technique is slow, the new imaging tools will provide significant new insights and open new avenues for improving early cancer detection, personalized risk assessment and identifying the best treatment strategies.

Keywords: 3D volumetric imaging; label-free imaging; light microscopy; super-resolution microscopy.

Figure 1.

(A) Full-field OCT images of (a) normal and (c) malignant ovary; corresponding histology images are shown in (b,d). The matching areas are indicated by red arrows. (B) The acridine orange stained confocal fluorescence microscopy images of basal cell carcinoma. The infiltrative BCC can be readily detected on a wide-field fluorescent confocal mosaic image (b) that correlates with H&E-stained image from a frozen tissue section (a). (c) A zoomed image of (b) that shows nuclear morphology. (C) The wide-field fluorescence image obtained by MUSE (a), converted virtual H&E image (b) and paired FFPE conventional histology (c). (D) (a) Stereo projection of confocal microscopy images of optically cleared mouse ileum with DiD-stained membranes (gray) and PI-stained nuclei (orange). (b) Stereo projection of the confocal “luminal scan” and “serosal scan” for the ileum. Arrows indicate the scan directions. (c) A full-depth, 3D projection of the ileum. Figures A-D are modified with permission from the following sources: [6, 63, 10, 19], respectively.

Figure 2.

(A) Comparison of H&E-stained (a) and the diffraction-limited immunofluorescence-stained confocal microscopy (b) images over a large area of a HER2-positive human rectal cancer tissue. (c) The magnified image of (b) from the area marked with white arrows. (d-e) The comparison of diffraction-limited confocal microscopy with STED super-resolution microscopy images. (B) (a) The workflow for Touch-prep samples for STORM-based super-resolution imaging. (b) Quantitative single-molecule localization microscopy is performed on the excised tumor tissue placed inside an imaging chamber, and H&E stained image of a touch prep sample. (c) STORM image of a HER2-positive cell in patient tissue. (d) The correlation between HER2 copy number from FISH and the average density of HER2 molecules from quantitative analysis of STORM image from three cell lines. (C) 3D-STORM images of HER2, TOM-20 and lamin-B1 on HER2+ tumor FFPE sections. Axial positions are color coded. (D) Comparison of H&E-stained image of human pancreatic tissue (a, c) and corresponding STORM-based super-resolution images (b, d) of facultative heterochromatin structure marked by H3K27me3. (E) Electron microscopy (a, c) and corresponding fluorescence microscopy images after expansion (b, d) on a clinical biopsy sample from a normal human kidney and a patient with a patient with minimal change disease (MCD). The intensity profile along the line cut of the inset is shown below each microscopic image. The expansion microscopy image clearly distinguished the features that are normally detected by electron microscopy. Figures A, B, C and E are modified with permission from the following sources: [33, 35, 34, 39], respectively. Figure D is the previously unpublished data from the authors of this paper.

Figure 3.

(A) The optical anisotropy image (a) calculated based on quantitative phase imaging of a prostate tissue, and the quantitative phase image (b) of a stromal tissue region in the prostate. (c) The histograms distribution of anisotropy values for 89 non-recurrent and 92 recurrent cases. (B) Bright-field microscope images and the corresponding disorder strength maps of the nuclei obtained from partial-wave spectroscopy in histologically normal buccal cells from a healthy patient (left) and a patient with lung cancer (right). (C) The quantitative phase images of unstained urothelial cells and corresponding pap-stained cytology images from patients with a cytologic diagnosis of (a) negative, (b) atypical, (c) suspicious, and (d) positive for urothelial carcinoma. The color bars are in radians. (D) The histology image and corresponding nanoNAM on normal colonic epithelial cells from a patient with ulcerative colitis (UC) who did not develop HGD or colorectal cancer (CRC) after 7 years of follow-up (a, low-risk) and from a UC patient who developed colon adenocarcinoma after 7 years (b, high-risk). Figures A-D are modified with permission from the following sources: [50, 54, 52, 48], respectively.