Spatially multiplexed RNA in situ hybridization to reveal tumor heterogeneity

The Expression Profiles of lncRNAs Are Associated with Neoadjuvant Chemotherapy Resistance in Locally Advanced, Luminal B-Type Breast Cancer

lncRNAs are noncoding transcripts with tissue and cancer specificity. Particularly, in breast cancer, lncRNAs exhibit subtype-specific expression; they are particularly upregulated in luminal tumors. However, no gene signature-based laboratory tests have been developed for luminal breast cancer identification or the differential diagnosis of luminal tumors, since no luminal A- or B-specific genes have been identified. Particularly, luminal B patients are of clinical interest, since they have the most variable response to neoadjuvant treatment; thus, it is necessary to develop diagnostic and predictive biomarkers for these patients to optimize treatment decision-making and improve treatment quality. In this study, we analyzed the lncRNA expression profiles of breast cancer cell lines and patient tumor samples from RNA-Seq data to identify an lncRNA signature specific for luminal phenotypes. We identified an lncRNA signature consisting of LINC01016, GATA3-AS1, MAPT-IT1, and DSCAM-AS1 that exhibits luminal subtype-specific expression; among these lncRNAs, GATA3-AS1 is associated with the presence of residual disease (Wilcoxon test, p < 0.05), which is related to neoadjuvant chemotherapy resistance in luminal B breast cancer patients. Furthermore, analysis of GATA3-AS1 expression using RNA in situ hybridization (RNA ISH) demonstrated that this lncRNA is detectable in histological slides. Similar to estrogen receptors and Ki67, both commonly detected biomarkers, GATA3-AS1 proves to be a suitable predictive biomarker for clinical application in breast cancer laboratory tests.

Current Landscape of Cancer Immunotherapy: Harnessing the Immune Arsenal to Overcome Immune Evasion

Cancer immune evasion represents a leading hallmark of cancer, posing a significant obstacle to the development of successful anticancer therapies. However, the landscape of cancer treatment has significantly evolved, transitioning into the era of immunotherapy from conventional methods such as surgical resection, radiotherapy, chemotherapy, and targeted drug therapy. Immunotherapy has emerged as a pivotal component in cancer treatment, harnessing the body's immune system to combat cancer and offering improved prognostic outcomes for numerous patients. The remarkable success of immunotherapy has spurred significant efforts to enhance the clinical efficacy of existing agents and strategies. Several immunotherapeutic approaches have received approval for targeted cancer treatments, while others are currently in preclinical and clinical trials. This review explores recent progress in unraveling the mechanisms of cancer immune evasion and evaluates the clinical effectiveness of diverse immunotherapy strategies, including cancer vaccines, adoptive cell therapy, and antibody-based treatments. It encompasses both established treatments and those currently under investigation, providing a comprehensive overview of efforts to combat cancer through immunological approaches. Additionally, the article emphasizes the current developments, limitations, and challenges in cancer immunotherapy. Furthermore, by integrating analyses of cancer immunotherapy resistance mechanisms and exploring combination strategies and personalized approaches, it offers valuable insights crucial for the development of novel anticancer immunotherapeutic strategies.

From complexity to clarity: unravelling tumor heterogeneity through the lens of tumor microenvironment for innovative cancer therapy

Despite the tremendous clinical successes recorded in the landscape of cancer therapy, tumor heterogeneity remains a formidable challenge to successful cancer treatment. In recent years, the emergence of high-throughput technologies has advanced our understanding of the variables influencing tumor heterogeneity beyond intrinsic tumor characteristics. Emerging knowledge shows that drivers of tumor heterogeneity are not only intrinsic to cancer cells but can also emanate from their microenvironment, which significantly favors tumor progression and impairs therapeutic response. Although much has been explored to understand the fundamentals of the influence of innate tumor factors on cancer diversity, the roles of the tumor microenvironment (TME) are often undervalued. It is therefore imperative that a clear understanding of the interactions between the TME and other tumor intrinsic factors underlying the plastic molecular behaviors of cancers be identified to develop patient-specific treatment strategies. This review highlights the roles of the TME as an emerging factor in tumor heterogeneity. More particularly, we discuss the role of the TME in the context of tumor heterogeneity and explore the cutting-edge diagnostic and therapeutic approaches that could be used to resolve this recurring clinical conundrum. We conclude by speculating on exciting research questions that can advance our understanding of tumor heterogeneity with the goal of developing customized therapeutic solutions.

DNA nanotechnology-based nucleic acid delivery systems for bioimaging and disease treatment

Nucleic acids, including DNA and RNA, have been considered as powerful and functional biomaterials owing to their programmable structure, good biocompatibility, and ease of synthesis. However, traditional nucleic acid-based probes have always suffered from inherent limitations, including restricted cell internalization efficiency and structural instability. In recent years, DNA nanotechnology has shown great promise for the applications of bioimaging and drug delivery. The attractive superiorities of DNA nanostructures, such as precise geometries, spatial addressability, and improved biostability, have enabled them to be a novel category of nucleic acid delivery systems for biomedical applications. In this review, we introduce the development of DNA nanotechnology, and highlight recent advances of DNA nanostructure-based delivery systems for cellular imaging and therapeutic applications. Finally, we propose the challenges as well as opportunities for the future development of DNA nanotechnology in biomedical research.

Microfluidic Aqueous Two-Phase Focusing of Chemical Species for In Situ Subcellular Stimulation

Confinement of chemical species in a controllable micrometer-level (several to a dozen micrometers) space in an aqueous environment is essential for precisely manipulating chemical events in subcellular regions. However, rapid diffusion and hard-to-control micrometer-level fluids make it a tough challenge. Here, a versatile open microfluidic method based on an aqueous two-phase system (ATPS) is developed to restrict species inside an open space with micron-level width. Unequal standard chemical potentials of the chemical species in two phases and space-time correspondence in the microfluidic system prevent outward diffusion across the phase interface, retaining the target species inside its preferred phase flow and creating a sharp boundary with a dramatic concentration change. Then, the chemical flow (the preferred phase with target chemical species) is precisely manipulated by a microfluidic probe, which can be compressed to a micron-level width and aimed at an arbitrary position of the sample. As a demonstration of the feasibility and versatility of the strategy, chemical flow is successfully applied to subcellular regions of various kinds of living single cells. Subcellular regions are successfully labeled (cytomembrane and mitochondria) and damaged. Healing-regeneration behaviors of living single cells are triggered by subcellular damage and analyzed. The method is relatively general regarding the species of chemicals and biosamples, which could promote deeper cell research.

Recent Advances in High-sensitivity In Situ Hybridization and Costs and Benefits to Consider When Employing These Methods

In situ hybridization (ISH), which visualizes nucleic acids in tissues and cells, is a powerful tool in histology and pathology. Over 50 years since its invention, multiple attempts have been made to increase the sensitivity and simplicity of these methods. Therefore, several highly sensitive in situ hybridization methods have been developed that offer researchers a wide range of options. When selecting these in situ hybridization variants, their signal-amplification principles and characteristics must be understood. In addition, from a practical point of view, a method with good monetary and time-cost performance must be chosen. This review introduces recent high-sensitivity in situ hybridization variants and presents their principles, characteristics, and costs.

Cruciate DNA probes for amplified multiplexed imaging of microRNAs in living cells

The real-time imaging of low-abundance tumor-related microRNAs (miRNAs) in living cells holds great potential for early clinical diagnosis of cancers. However, the relatively low detection sensitivity and possible false-positive signals of a probe in complex cellular matrices remain critical challenges for accurate RNA detection. Herein, we developed a novel aptamer-functionalized cruciate DNA probe that enabled amplified multiple miRNA imaging in living cells via catalytic hairpin assembly (CHA). The cross-shaped design of the cruciate DNA probe improved the stability against nucleases and acted as a modular scaffold for CHA circuits for efficient delivery into tumor cells. The cruciate DNA probe allowed self-assembly through thermal annealing and displayed excellent performance for sensitive miRNA detection in vitro. The cruciate DNA probe could be internalized into nucleolin-overexpressed cells specifically via cell-targeting of the AS1411 aptamer, achieving amplified fluorescence imaging and quantitative evaluation of the expression of miRNAs in living cells. Through the simultaneous detection of intracellular multiple miRNAs, the developed cruciate DNA probe could provide more accurate information and reduce the chances of false positive signals for cancer diagnosis. This approach offers a new opportunity for promoting the development of miRNA-related biomedical research and tumor diagnostic applications.

A review of spatial profiling technologies for characterizing the tumor microenvironment in immuno-oncology

Interpreting the mechanisms and principles that govern gene activity and how these genes work according to -their cellular distribution in organisms has profound implications for cancer research. The latest technological advancements, such as imaging-based approaches and next-generation single-cell sequencing technologies, have established a platform for spatial transcriptomics to systematically quantify the expression of all or most genes in the entire tumor microenvironment and explore an array of disease milieus, particularly in tumors. Spatial profiling technologies permit the study of transcriptional activity at the spatial or single-cell level. This multidimensional classification of the transcriptomic and proteomic signatures of tumors, especially the associated immune and stromal cells, facilitates evaluation of tumor heterogeneity, details of the evolutionary trajectory of each tumor, and multifaceted interactions between each tumor cell and its microenvironment. Therefore, spatial profiling technologies may provide abundant and high-resolution information required for the description of clinical-related features in immuno-oncology. From this perspective, the present review will highlight the importance of spatial transcriptomic and spatial proteomics analysis along with the joint use of other sequencing technologies and their implications in cancers and immune-oncology. In the near future, advances in spatial profiling technologies will undoubtedly expand our understanding of tumor biology and highlight possible precision therapeutic targets for cancer patients.

Microscale hydrodynamic confinements: shaping liquids across length scales as a toolbox in life sciences

Hydrodynamic phenomena can be leveraged to confine a range of biological and chemical species without needing physical walls. In this review, we list methods for the generation and manipulation of microfluidic hydrodynamic confinements in free-flowing liquids and near surfaces, and elucidate the associated underlying theory and discuss their utility in the emerging area of open space microfluidics applied to life-sciences. Microscale hydrodynamic confinements are already starting to transform approaches in fundamental and applied life-sciences research from precise separation and sorting of individual cells, allowing localized bio-printing to multiplexing for clinical diagnosis. Through the choice of specific flow regimes and geometrical boundary conditions, hydrodynamic confinements can confine species across different length scales from small molecules to large cells, and thus be applied to a wide range of functionalities. We here provide practical examples and implementations for the formation of these confinements in different boundary conditions - within closed channels, in between parallel plates and in an open liquid volume. Further, to enable non-microfluidics researchers to apply hydrodynamic flow confinements in their work, we provide simplified instructions pertaining to their design and modelling, as well as to the formation of hydrodynamic flow confinements in the form of step-by-step tutorials and analytical toolbox software. This review is written with the idea to lower the barrier towards the use of hydrodynamic flow confinements in life sciences research.

Multitarget Reaction Programmable Automatic Diagnosis and Treatment Logic Device

Accurate diagnosis and precise and effective treatment are currently the two magic weapons for dealing with cancer. However, a single marker is often associated with multiple cellular events, which is not conducive to accurate diagnosis, and overly mild treatment methods often make the treatment effect unsatisfactory. In this paper, we construct a Au/Pd octopus nanoparticle-DNA nanomachine (Au/Pd ONP-DNA nanomachine) as a fully automatic diagnosis and treatment logic system. In this system, multiple DNA components are targeting detection units, Au/Pd ONPs act as carriers, and Au/Pd ONPs with an 808 nm laser is the treatment unit. In order to achieve the purpose of precise treatment, we will detect two secondary markers under the premise of detecting one major tumor marker. When all of the designated targets are detected (the logic system input is (1, 1, 1), and the output is (1, 1)), the 808 nm laser can be programmed to automatically radiate tumors and perform photothermal therapy and photodynamic therapy. In vivo and in vitro experiments show that this logic system not only can accurately identify tumor cells but also has considerable therapeutic effects.

Spatial protein heterogeneity analysis in frozen tissues to evaluate tumor heterogeneity

A new workflow for protein-based tumor heterogeneity probing in tissues is here presented. Tumor heterogeneity is believed to be key for therapy failure and differences in prognosis in cancer patients. Comprehending tumor heterogeneity, especially at the protein level, is critical for tracking tumor evolution, and showing the presence of different phenotypical variants and their location with respect to tissue architecture. Although a variety of techniques is available for quantifying protein expression, the heterogeneity observed in the tissue is rarely addressed. The proposed method is validated in breast cancer fresh-frozen tissues derived from five patients. Protein expression is quantified on the tissue regions of interest (ROI) with a resolution of up to 100 μm in diameter. High heterogeneity values across the analyzed patients in proteins such as cytokeratin 7, β-actin and epidermal growth factor receptor (EGFR) using a Shannon entropy analysis are observed. Additionally, ROIs are clustered according to their expression levels, showing their location in the tissue section, and highlighting that similar phenotypical variants are not always located in neighboring regions. Interestingly, a patient with a phenotype related to increased aggressiveness of the tumor presents a unique protein expression pattern. In summary, a workflow for the localized extraction and protein analysis of regions of interest from frozen tissues, enabling the evaluation of tumor heterogeneity at the protein level is presented.

Automated annotations of epithelial cells and stroma in hematoxylin-eosin-stained whole-slide images using cytokeratin re-staining

The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Carcinomas consist of malignant epithelial cells arranged in more or less cohesive clusters of variable size and shape, together with stromal cells, extracellular matrix, and blood vessels. Distinguishing stroma from epithelium is a critical component of artificial intelligence (AI) methods developed to detect and analyze carcinomas. In this paper, we propose a novel automated workflow that enables large‐scale guidance of AI methods to identify the epithelial component. The workflow is based on re‐staining existing hematoxylin and eosin (H&E) formalin‐fixed paraffin‐embedded sections by immunohistochemistry for cytokeratins, cytoskeletal components specific to epithelial cells. Compared to existing methods, clinically available H&E sections are reused and no additional material, such as consecutive slides, is needed. We developed a simple and reliable method for automatic alignment to generate masks denoting cytokeratin‐rich regions, using cell nuclei positions that are visible in both the original and the re‐stained slide. The registration method has been compared to state‐of‐the‐art methods for alignment of consecutive slides and shows that, despite being simpler, it provides similar accuracy and is more robust. We also demonstrate how the automatically generated masks can be used to train modern AI image segmentation based on U‐Net, resulting in reliable detection of epithelial regions in previously unseen H&E slides. Through training on real‐world material available in clinical laboratories, this approach therefore has widespread applications toward achieving AI‐assisted tumor assessment directly from scanned H&E sections. In addition, the re‐staining method will facilitate additional automated quantitative studies of tumor cell and stromal cell phenotypes.

Single-Cell RNA Sequencing Reveals Endothelial Cell Transcriptome Heterogeneity Under Homeostatic Laminar Flow

Supplemental Digital Content is available in the text.

Endothelial cells (ECs) that form the innermost layer of all vessels exhibit heterogeneous cell behaviors and responses to pro-angiogenic signals that are critical for vascular sprouting and angiogenesis. Once vessels form, remodeling and blood flow lead to EC quiescence, and homogeneity in cell behaviors and signaling responses. These changes are important for the function of mature vessels, but whether and at what level ECs regulate overall expression heterogeneity during this transition is poorly understood. Here, we profiled EC transcriptomic heterogeneity, and expression heterogeneity of selected proteins, under homeostatic laminar flow.

Biopatterning: The Art of Patterning Biomolecules on Surfaces

Patterning biomolecules on surfaces provides numerous opportunities for miniaturizing biological assays; biosensing; studying proteins, cells, and tissue sections; and engineering surfaces that include biological components. In this Feature Article, we summarize the themes presented in our recent Langmuir Lecture on patterning biomolecules on surfaces, miniaturizing surface assays, and interacting with biointerfaces using three key technologies: microcontact printing, microfluidic networks, and microfluidic probes.

Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into Genomic Workflows

In cancer research, genomic profiles are often extracted from homogenized macrodissections of tissues, with the histological context lost and a large fraction of material underutilized. Pertinently, the spatial genomic landscape provides critical complementary information in deciphering disease heterogeneity and progression. Microscale sampling methods such as microdissection to obtain such information are often destructive to a sizeable fraction of the biopsy sample, thus showing limited multiplexability and adaptability to different assays. A modular microfluidic technology is here implemented to recover cells at the microscale from tumor tissue sections, with minimal disruption of unsampled areas and tailored to interface with genome profiling workflows, which is directed here toward evaluating intratumoral genomic heterogeneity. The integrated workflow-GeneScape-is used to evaluate heterogeneity in a metastatic mammary carcinoma, showing distinct single nucleotide variants and copy number variations in different tumor tissue regions, suggesting the polyclonal origin of the metastasis as well as development driven by multiple location-specific drivers.

Next-Generation Digital Histopathology of the Tumor Microenvironment

Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology-which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning.

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.

Loss of CDKN1A mRNA and Protein Expression Are Independent Predictors of Poor Outcome in Chromophobe Renal Cell Carcinoma Patients

Chromophobe renal cell carcinoma (chRCC) patients have good prognosis. Only 5%-10% patients die of metastatic disease after tumorectomy, but tumor progression cannot be predicted by histopathological parameters alone. chRCC are characterized by losses of many chromosomes, whereas gene mutations are rare. In this study, we aim at identifying genes indicating chRCC progression. A bioinformatic approach was used to correlate chromosomal loss and mRNA expression from 15287 genes from The Cancer Genome Atlas (TCGA) database. All genes in TCGA chromophobe renal cancer dataset (KICH) for which a significant correlation between chromosomal loss and mRNA expression was shown, were identified and their associations with outcome was assessed. Genome-wide DNA copy-number alterations were analyzed by Affymetrix OncoScan^® CNV FFPE Microarrays in a second cohort of Swiss chRCC. In both cohorts, tumors with loss of chromosomes 2, 6, 10, 13, 17 and 21 had signs of tumor progression. There were 4654 genes located on these chromosomes, and 13 of these genes had reduced mRNA levels, which was associated with poor outcome in chRCC. Decreased CDKN1A expression at mRNA (p = 0.02) and protein levels (p = 0.02) were associated with short overall survival and were independent predictors of prognosis (p <0.01 and <0.05 respectively). CDKN1A expression status is a prognostic biomarker independent of tumor stage. CDKN1A immunohistochemistry may be used to identify chRCC patients at greater risk of disease progression.