Recent advances in tissue imaging for cancer research

Research progress and perspectives on the application of tyramide signal amplification-based multiplex immunohistochemistry/immunofluorescence: a bibliometrics analysis

Background and aims

Multiplex immunohistochemistry/immunofluorescence (mIHC/IF), which uses the tyramide signal amplification (TSA) technique, enables sequential staining of multiple targets in formalin-fixed paraffin-embedded (FFPE) samples without worrying about cross-reactivity. This approach has received considerable attention from researchers over the past decades. This article aims to provide a bibliometric analysis of the research progress and perspectives on the application of TSA-based mIHC/IF.

Methods

We collected all the TSA-based mIHC/IF documents published between 2007 and 2023 from the Web of Science Core Collection (WoSCC) database. CiteSpace, VOSviewer and Bibliometrix R Package were used to perform the bibliometrics analysis, including details about annual publications, countries, institutions, authors, journals, and research topics and hotspots.

Results

A total of 873 relevant publications (811 articles and 62 reviews) with a time span of 17 years (2007-2023) were obtained. The number of annual publications started to increase rapidly since 2016. The United States (307, 35.17%) and the People's Republic of China (297, 34.02%) are the top two listed countries for both the number of articles produced and the citations. The University of Texas System (53, 6.07%) was the most productive institution. Integrating these results of hotspot and frontier analysis, TSA-based mIHC/IF provides significant benefits, particularly in neurology, cancer and immunology.

Conclusion

This study conducted a comprehensive bibliometric analysis for the use of TSA-based mIHC/IF. As TSA-based mIHC/IF and its associated imaging systems and analytic software progress, it will become the most promising tool for describing the variety of the whole tissue for a better understanding of pathological or physiological behavior.

Unexplained Recurrent Pregnancy Loss: Clinical Application of Immunophenotyping

PROBLEM

Recurrent pregnancy loss (RPL) is defined as the failure of two or more pregnancies and affects approximately 5% of couples, often without a clear cause. The etiologies of RPL include factors such as maternal age, endocrine dysfunction, uterine abnormalities, chromosomal abnormalities, thrombophilias, infections, and autoimmune disorders. However, these conditions account for only 50%-60% of RPL cases. Research has explored whether an altered immune system, compared to the physiological state, may be linked to RPL. This review aims to determine whether specific immunophenotypes are associated with unexplained Recurrent Pregnancy Loss (uRPL) and whether targeted therapies addressing specific immunophenotypic alterations can improve pregnancy outcomes.

METHODS

A literature review was conducted using Pubmed/Medline, Scopus, and Embase databases, analyzing data from 95 articles published between 2001 and 2023. The roles of various cells of the immune system (B lymphocytes, T lymphocytes, natural killer cells, macrophages) in different tissues (peripheral blood, menstrual blood) were specifically investigated in women with uRPL.

DISCUSSION AND CONCLUSION

Specific immunophenotypes have been demonstrated to be associated with this condition. However, there is a need to standardize immunophenotyping assays and conduct more trials to stratify RPL risk and improve potential therapeutic strategies.

FunSpace: A functional and spatial analytic approach to cell imaging data using entropy measures

Spatial heterogeneity in the tumor microenvironment (TME) plays a critical role in gaining insights into tumor development and progression. Conventional metrics typically capture the spatial differential between TME cellular patterns by either exploring the cell distributions in a pairwise fashion or aggregating the heterogeneity across multiple cell distributions without considering the spatial contribution. As such, none of the existing approaches has fully accounted for the simultaneous heterogeneity caused by both cellular diversity and spatial configurations of multiple cell categories. In this article, we propose an approach to leverage spatial entropy measures at multiple distance ranges to account for the spatial heterogeneity across different cellular organizations. Functional principal component analysis (FPCA) is applied to estimate FPC scores which are then served as predictors in a Cox regression model to investigate the impact of spatial heterogeneity in the TME on survival outcome, potentially adjusting for other confounders. Using a non-small cell lung cancer dataset (n = 153) as a case study, we found that the spatial heterogeneity in the TME cellular composition of CD14+ cells, CD19+ B cells, CD4+ and CD8+ T cells, and CK+ tumor cells, had a significant non-zero effect on the overall survival (p = 0.027). Furthermore, using a publicly available multiplexed ion beam imaging (MIBI) triple-negative breast cancer dataset (n = 33), our proposed method identified a significant impact of cellular interactions between tumor and immune cells on the overall survival (p = 0.046). In simulation studies under different spatial configurations, the proposed method demonstrated a high predictive power by accounting for both clinical effect and the impact of spatial heterogeneity.

Imaging approaches for monitoring three-dimensional cell and tissue culture systems

The past decade has seen an increasing demand for more complex, reproducible and physiologically relevant tissue cultures that can mimic the structural and biological features of living tissues. Monitoring the viability, development and responses of such tissues in real-time are challenging due to the complexities of cell culture physical characteristics and the environments in which these cultures need to be maintained in. Significant developments in optics, such as optical manipulation, improved detection and data analysis, have made optical imaging a preferred choice for many three-dimensional (3D) cell culture monitoring applications. The aim of this review is to discuss the challenges associated with imaging and monitoring 3D tissues and cell culture, and highlight topical label-free imaging tools that enable bioengineers and biophysicists to non-invasively characterise engineered living tissues.

SPF: A spatial and functional data analytic approach to cell imaging data

The tumor microenvironment (TME), which characterizes the tumor and its surroundings, plays a critical role in understanding cancer development and progression. Recent advances in imaging techniques enable researchers to study spatial structure of the TME at a single-cell level. Investigating spatial patterns and interactions of cell subtypes within the TME provides useful insights into how cells with different biological purposes behave, which may consequentially impact a subject's clinical outcomes. We utilize a class of well-known spatial summary statistics, the K-function and its variants, to explore inter-cell dependence as a function of distances between cells. Using techniques from functional data analysis, we introduce an approach to model the association between these summary spatial functions and subject-level outcomes, while controlling for other clinical scalar predictors such as age and disease stage. In particular, we leverage the additive functional Cox regression model (AFCM) to study the nonlinear impact of spatial interaction between tumor and stromal cells on overall survival in patients with non-small cell lung cancer, using multiplex immunohistochemistry (mIHC) data. The applicability of our approach is further validated using a publicly available multiplexed ion beam imaging (MIBI) triple-negative breast cancer dataset.

Super-Resolution Fluorescence Microscopy Methods for Assessing Mouse Biology

Super-resolution (diffraction unlimited) microscopy was developed 15 years ago; the developers were awarded the Nobel Prize in Chemistry in recognition of their work in 2014. Super-resolution microscopy is increasingly being applied to diverse scientific fields, from single molecules to cell organelles, viruses, bacteria, plants, and animals, especially the mammalian model organism Mus musculus. In this review, we explain how super-resolution microscopy, along with fluorescence microscopy from which it grew, has aided the renaissance of the light microscope. We cover experiment planning and specimen preparation and explain structured illumination microscopy, super-resolution radial fluctuations, stimulated emission depletion microscopy, single-molecule localization microscopy, and super-resolution imaging by pixel reassignment. The final section of this review discusses the strengths and weaknesses of each super-resolution technique and how to choose the best approach for your research. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.

Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP

Spatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts.

Hybrid Hierarchical Heterostructures of Nanoceramic Phosphors as Imaging Agents for Multiplexing and Living Cancer Cells Translocation

Existing fluorescent labels used in life sciences are based on organic compounds with limited lifetime or on quantum dots which are either expensive or toxic and have low kinetic stability in biological environments. To address these challenges, luminescent nanomaterials have been conceived as hierarchical, core–shell structures with spherical morphology and highly controlled dimensions. These tailor-made nanophosphors incorporate Ln:YVO₄ nanoparticles (Ln = Eu(III) and Er(III)) as 50 nm cores and display intense and narrow emission maxima centered at ∼565 nm. These cores can be encapsulated in silica shells with highly controlled dimensions as well as functionalized with chitosan or PEG5000 to reduce nonspecific interactions with biomolecules in living cells. Confocal fluorescence microscopy in living prostate cancer cells confirmed the potential of these platforms to overcome the disadvantages of commercial fluorophores and their feasibility as labels for multiplexing, biosensing, and imaging in life science assays.

Expression of P16INK4a in Uveal Melanoma: New Perspectives

Uveal melanoma (UM) is the most common intraocular tumor in adults. Despite sharing the name and similar morphological features with cutaneous melanoma (CM), it is an entirely different neoplasia with a particular genetic background and clinical behavior. CDKN2A is a gene located at chromosome 9p21, encoding for P16INK4a and P14(ARF) proteins, whose role as a tumor suppressor has been clearly defined in many malignant tumors. CDKN2A frequently presents germline mutations in familial CM and epigenetic downregulation in a considerable percentage of sporadic CM. It has been hypothesized that CDKN2A alterations are early events in CM development, playing a central role in the malignant transformation of melanocytes. Alterations of the CDKN2A gene reduce the expression of P16INK4a in most CM subtypes. Immunohistochemical evaluation of P16INK4a is currently used, in association with Ki67 and HMB45, in pathology practice to discriminate between dysplastic nevi and melanoma. On the other hand, CKDN2A is rarely mutated in UM, and the immunohistochemical expression of P16INK4a has only been reported in small case series. We tested P16INK4a expression on paraffin-embedded tissue sections from 9 tissue microarrays (TMAs), built with 2 mm cores derived from 133 uveal melanoma FFPE blocks, collected from 1990 to 2018, and from selected paraffin-blocks of 3 UM liver metastases. The immunohistochemical expression of P16INK4a was assessed with a visual evaluation by light microscopy and then with a digital approach. Both approaches, with an acceptable concordance rate, revealed P16INK4a expression in a large proportion of UM cases and all liver metastases, opening new possibilities of using it in the differential diagnosis between cutaneous and uveal melanoma metastases in cases of unknown primary tumor or patients with two different primary melanomas.

A robust multiplex immunofluorescence and digital pathology workflow for the characterisation of the tumour immune microenvironment

Multiplex immunofluorescence is a powerful tool for the simultaneous detection of tissue-based biomarkers, revolutionising traditional immunohistochemistry. The Opal methodology allows up to eight biomarkers to be measured concomitantly without cross-reactivity, permitting identification of different cell populations within the tumour microenvironment. In this study, we aimed to validate a multiplex immunofluorescence workflow in two complementary multiplex panels and evaluate the tumour immune microenvironment in colorectal cancer (CRC) formalin-fixed paraffin-embedded tissue. We stained CRC and tonsil samples using Opal multiplex immunofluorescence on a Leica BOND RX immunostainer. We then acquired images on an Akoya Vectra Polaris and performed multispectral unmixing using inform. Antibody panels were validated on tissue microarray sections containing cores from six normal tissue types, using qupath for image analysis. Comparisons between chromogenic immunohistochemistry and multiplex immunofluorescence on consecutive sections from the same tissue microarray showed significant correlation (rs  > 0.9, P-value < 0.0001), validating both panels. We identified many factors that influenced the quality of the acquired fluorescent images, including biomarker co-expression, staining order, Opal-antibody pairing, sample thickness, multispectral unmixing and biomarker detection order during image analysis. Overall, we report the optimisation and validation of a multiplex immunofluorescence process, from staining to image analysis, ensuring assay robustness. Our multiplex immunofluorescence protocols permit the accurate detection of multiple immune markers in various tissue types, using a workflow that enables rapid processing of samples, above and beyond previous workflows.

In situ Metabolic Profiling of Ovarian Cancer Tumor Xenografts: A Digital Pathology Approach

Metabolic profiling of cancer is a rising interest in the field of biomarker development. One bottleneck of its clinical exploitation, however, is the lack of simple and quantitative techniques that enable to capture the key metabolic traits of tumor from archival samples. In fact, liquid chromatography associated with mass spectrometry is the gold-standard technique for the study of tumor metabolism because it has high levels of accuracy and precision. However, it requires freshly frozen samples, which are difficult to collect in large multi-centric clinical studies. For this reason, we propose here to investigate a set of established metabolism-associated protein markers by exploiting immunohistochemistry coupled with digital pathology. As case study, we quantified expression of MCT1, MCT4, GLS, PHGDH, FAS, and ACC in 17 patient-derived ovarian cancer xenografts and correlated it with survival. Among these markers, the glycolysis-associated marker MCT4 was negatively associated with survival of mice. The algorithm enabling a quantitative analysis of these metabolism-associated markers is an innovative research tool that can be exported to large sets of clinical samples and can remove the variability of individual interpretation of immunohistochemistry results.