Periductal stromal collagen topology of pancreatic ductal adenocarcinoma differs from that of normal and chronic pancreatitis

Quantifying Breast Cancer-Driven Fiber Alignment and Collagen Deposition in Primary Human Breast Tissue

Solid tumor progression is significantly influenced by interactions between cancer cells and the surrounding extracellular matrix (ECM). Specifically, the cancer cell-driven changes to ECM fiber alignment and collagen deposition impact tumor growth and metastasis. Current methods of quantifying these processes are incomplete, require simple or artificial matrixes, rely on uncommon imaging techniques, preclude the use of biological and technical replicates, require destruction of the tissue, or are prone to segmentation errors. We present a set of methodological solutions to these shortcomings that were developed to quantify these processes in cultured, ex vivo human breast tissue under the influence of breast cancer cells and allow for the study of ECM in primary breast tumors. Herein, we describe a method of quantifying fiber alignment that can analyze complex native ECM from scanning electron micrographs that does not preclude the use of replicates and a high-throughput mechanism of quantifying collagen content that is non-destructive. The use of these methods accurately recapitulated cancer cell-driven changes in fiber alignment and collagen deposition observed by visual inspection. Additionally, these methods successfully identified increased fiber alignment in primary human breast tumors when compared to human breast tissue and increased collagen deposition in lobular breast cancer when compared to ductal breast cancer. The successful quantification of fiber alignment and collagen deposition using these methods encourages their use for future studies of ECM dysregulation in human solid tumors.

Optical biopsy of laryngeal lesions using femtosecond multiphoton microscopy

Laryngeal squamous cell carcinoma (LSCC) is one of the most prevalent malignancy of the upper aerodigestive tract. Detection of early lesions in vivo could improve the survival rate significantly. In this study, we demonstrated that femtosecond multiphoton microscopy (MPM) is an effective tool to visualize the microscopic features within fixed laryngeal tissues, without sectioning, staining, or labeling. Accurate detection of lesions and determination of the tumor grading can be achieved, with excellent consistency with conventional histological examination. These results suggest that MPM may represent a powerful tool for in-vivo or fast ex-vivo diagnosis of laryngeal lesions at the point of care.

Morphological Heterogeneity in Pancreatic Cancer Reflects Structural and Functional Divergence

Simple Summary

Pancreatic cancer has a poor prognosis, which is largely due to resistance to treatment. Tumor heterogeneity is a known cause for treatment failure and has been studied at the molecular level. Morphological heterogeneity is common but has not been investigated, despite the fact that pathology examination is an integral part of clinical diagnostics. This study assessed whether morphological heterogeneity reflects structural and functional diversity in key cancer biological processes. Using archival tissues from resected pancreatic cancer, we selected four common and distinct morphological phenotypes and demonstrated that these differed significantly for a panel of 26 structural and functional features of the cancer-cell and stromal compartments. The strong link between these features and morphological phenotypes allowed prediction of the latter based on the results for the panel of features. The findings of this study indicate that morphological heterogeneity reflects biological diversity and that its assessment may potentially provide clinically relevant information.

Abstract

Inter- and intratumor heterogeneity is an important cause of treatment failure. In human pancreatic cancer (PC), heterogeneity has been investigated almost exclusively at the genomic and transcriptional level. Morphological heterogeneity, though prominent and potentially easily assessable in clinical practice, remains unexplored. This proof-of-concept study aims at demonstrating that morphological heterogeneity reflects structural and functional divergence. From the wide morphological spectrum of conventional PC, four common and distinctive patterns were investigated in 233 foci from 39 surgical specimens. Twenty-six features involved in key biological processes in PC were analyzed (immuno-)histochemically and morphometrically: cancer cell proliferation (Ki67) and migration (collagen fiber alignment, MMP14), cancer stem cells (CD44, CD133, ALDH1), amount, composition and spatial arrangement of extracellular matrix (epithelial proximity, total collagen, collagen I and III, fibronectin, hyaluronan), cancer-associated fibroblasts (density, αSMA), and cancer-stroma interactions (integrins α2, α5, α1; caveolin-1). All features differed significantly between at least two of the patterns. Stromal and cancer-cell-related features co-varied with morphology and allowed prediction of the morphological pattern. In conclusion, morphological heterogeneity in the cancer-cell and stromal compartments of PC correlates with structural and functional diversity. As such, histopathology has the potential to inform on the operationality of key biological processes in individual tumors.

Recent Advancements in Optical Harmonic Generation Microscopy: Applications and Perspectives

Second harmonic generation (SHG) and third harmonic generation (THG) microscopies have emerged as powerful imaging modalities to examine structural properties of a wide range of biological tissues. Although SHG and THG arise from very different contrast mechanisms, the two are complimentary and can often be collected simultaneously using a modified multiphoton microscope. In this review, we discuss the needed instrumentation for these modalities as well as the underlying theoretical principles of SHG and THG in tissue and describe how these can be leveraged to extract unique structural information. We provide an overview of recent advances showing how SHG microscopy has been used to evaluate collagen alterations in the extracellular matrix and how this has been used to advance our knowledge of cancers, fibroses, and the cornea, as well as in tissue engineering applications. Specific examples using polarization-resolved approaches and machine learning algorithms are highlighted. Similarly, we review how THG has enabled developmental biology and skin cancer studies due to its sensitivity to changes in refractive index, which are ubiquitous in all cell and tissue assemblies. Lastly, we offer perspectives and outlooks on future directions of SHG and THG microscopies and present unresolved questions, especially in terms of overall miniaturization and the development of microendoscopy instrumentation.

Navigating the Collagen Jungle: The Biomedical Potential of Fiber Organization in Cancer

Recent research has highlighted the importance of key tumor microenvironment features, notably the collagen-rich extracellular matrix (ECM) in characterizing tumor invasion and progression. This led to great interest from both basic researchers and clinicians, including pathologists, to include collagen fiber evaluation as part of the investigation of cancer development and progression. Fibrillar collagen is the most abundant in the normal extracellular matrix, and was revealed to be upregulated in many cancers. Recent studies suggested an emerging theme across multiple cancer types in which specific collagen fiber organization patterns differ between benign and malignant tissue and also appear to be associated with disease stage, prognosis, treatment response, and other clinical features. There is great potential for developing image-based collagen fiber biomarkers for clinical applications, but its adoption in standard clinical practice is dependent on further translational and clinical evaluations. Here, we offer a comprehensive review of the current literature of fibrillar collagen structure and organization as a candidate cancer biomarker, and new perspectives on the challenges and next steps for researchers and clinicians seeking to exploit this information in biomedical research and clinical workflows.

Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization

High-quality whole slide scanners used for animal and human pathology scanning are expensive and can produce massive datasets, which limits the access to and adoption of this technique. As a potential solution to these challenges, we present a deep learning-based approach making use of single image super-resolution (SISR) to reconstruct high-resolution histology images from low-resolution inputs. Such low-resolution images can easily be shared, require less storage, and can be acquired quickly using widely available low-cost slide scanners. The network consists of multi-scale fully convolutional networks capable of capturing hierarchical features. Conditional generative adversarial loss is incorporated to penalize blurriness in the output images. The network is trained using a progressive strategy where the scaling factor is sampled from a normal distribution with an increasing mean. The results are evaluated with quantitative metrics and are used in a clinical histopathology diagnosis procedure which shows that the SISR framework can be used to reconstruct high-resolution images with clinical level quality. We further propose a self-supervised color normalization method that can remove staining variation artifacts. Quantitative evaluations show that the SISR framework can generalize well on unseen data collected from other patient tissue cohorts by incorporating the color normalization method.

Organ-on-a-Chip Systems for Modeling Pathological Tissue Morphogenesis Associated with Fibrosis and Cancer

Tissue building does not occur exclusively during development. Even after a whole body is built from a single cell, tissue building can occur to repair and regenerate tissues of the adult body. This confers resilience and enhanced survival to multicellular organisms. However, this resiliency comes at a cost, as the potential for misdirected tissue building creates vulnerability to organ deformation and dysfunction-the hallmarks of disease. Pathological tissue morphogenesis is associated with fibrosis and cancer, which are the leading causes of morbidity and mortality worldwide. Despite being the priority of research for decades, scientific understanding of these diseases is limited and existing therapies underdeliver the desired benefits to patient outcomes. This can largely be attributed to the use of two-dimensional cell culture and animal models that insufficiently recapitulate human disease. Through the synergistic union of biological principles and engineering technology, organ-on-a-chip systems represent a powerful new approach to modeling pathological tissue morphogenesis, one with the potential to yield better insights into disease mechanisms and improved therapies that offer better patient outcomes. This Review will discuss organ-on-a-chip systems that model pathological tissue morphogenesis associated with (1) fibrosis in the context of injury-induced tissue repair and aging and (2) cancer.

Intratumoral collagen signatures predict clinical outcomes in feline mammary carcinoma

Breast cancer is the most common cause of cancer-related deaths in women worldwide. Identification of reliable prognostic indicators and therapeutic targets is critical for improving patient outcome. Cancer in companion animals often strongly resembles human cancers and a comparative approach to identify prognostic markers can improve clinical care across species. Feline mammary tumors (FMT) serve as models for extremely aggressive triple negative breast cancer (TNBC) in humans, with high rates of local and distant recurrence after resection. Despite the aggressive clinical behavior of most FMT, current prognostic indicators are insufficient for accurately predicting outcome, similar to human patients. Given significant heterogeneity of mammary tumors, there has been a recent focus on identification of universal tumor-permissive stromal features that can predict biologic behavior and provide therapeutic targets to improve outcome. As in human and canine patients, collagen signatures appear to play a key role in directing mammary tumor behavior in feline patients. We find that patients bearing FMTs with denser collagen, as well as longer, thicker and straighter fibers and less identifiable tumor-stromal boundaries had poorer outcomes, independent of the clinical variables grade and surgical margins. Most importantly, including the collagen parameters increased the predictive power of the clinical model. Thus, our data suggest that similarities with respect to the stromal microenvironment between species may allow this model to predict outcome and develop novel therapeutic targets within the tumor stroma that would benefit both veterinary and human patients with aggressive mammary tumors.

Non-disruptive collagen characterization in clinical histopathology using cross-modality image synthesis

The importance of fibrillar collagen topology and organization in disease progression and prognostication in different types of cancer has been characterized extensively in many research studies. These explorations have either used specialized imaging approaches, such as specific stains (e.g., picrosirius red), or advanced and costly imaging modalities (e.g., second harmonic generation imaging (SHG)) that are not currently in the clinical workflow. To facilitate the analysis of stromal biomarkers in clinical workflows, it would be ideal to have technical approaches that can characterize fibrillar collagen on standard H&E stained slides produced during routine diagnostic work. Here, we present a machine learning-based stromal collagen image synthesis algorithm that can be incorporated into existing H&E-based histopathology workflow. Specifically, this solution applies a convolutional neural network (CNN) directly onto clinically standard H&E bright field images to extract information about collagen fiber arrangement and alignment, without requiring additional specialized imaging stains, systems or equipment.

Cancer associated fibroblast: Mediators of tumorigenesis

It is well accepted that the tumor microenvironment plays a pivotal role in cancer onset, development, and progression. The majority of clinical interventions are designed to target either cancer or stroma cells. These emphases have been directed by one of two prevailing theories in the field, the Somatic Mutation Theory and the Tissue Organization Field Theory, which represent two seemingly opposing concepts. This review proposes that the two theories are mutually inclusive and should be concurrently considered for cancer treatments. Specifically, this review discusses the dynamic and reciprocal processes between stromal cells and extracellular matrices, using pancreatic cancer as an example, to demonstrate the inclusivity of the theories. Furthermore, this review highlights the functions of cancer associated fibroblasts, which represent the major stromal cell type, as important mediators of the known cancer hallmarks that the two theories attempt to explain.

Matrix density drives 3D organotypic lymphatic vessel activation in a microfluidic model of the breast tumor microenvironment

Lymphatic vessels (LVs) have been suggested as a preferential conduit for metastatic progression in breast cancer, where a correlation between the occurrence of lymph node metastasis and an increased extracellular matrix (ECM) density has been reported. However, the effect of ECM density on LV function is largely unknown. To better understand these effects, we used a microfluidic device to recreate tubular LVs in a collagen type I matrix. The density of the matrix was tailored to mimic normal breast tissue using a low-density collagen (LD-3 mg mL-1) and cancerous breast tissue using a high-density collagen (HD-6 mg mL-1). We investigated the effect of ECM density on LV morphology, growth, cytokine secretion, and barrier function. LVs cultured in HD matrices showed morphological changes as compared to LVs cultured in a LD matrix. Specifically, LVs cultured in HD matrices had a 3-fold higher secretion of the pro-inflammatory cytokine, IL-6, and a leakier phenotype, suggesting LVs acquired characteristics of activated vessels. Interestingly, LV leakiness was mitigated by blocking the IL-6 receptor on the lymphatic ECs, maintaining endothelium permeability at similar levels of LV cultured in a LD matrix. To recreate a more in vivo microenvironment, we incorporated metastatic breast cancer cells (MDA-MB-231) into the LD and HD matrices. For HD matrices, co-culture with MDA-MB-231 cells exacerbated vessel leakiness and secretion of IL-6. In summary, our data suggest that (1) ECM density is an important microenvironmental cue that affects LV function in the breast tumor microenvironment (TME), (2) dense matrices condition LVs towards an activated phenotype and (3) blockade of IL-6 signaling may be a potential therapeutic target to mitigate LV dysfunction. Overall, modeling LVs and their interactions with the TME can help identify novel therapeutic targets and, in turn, advance therapeutic discovery.

Pancreatic Cancer and Its Microenvironment-Recent Advances and Current Controversies

Pancreatic ductal adenocarcinoma (PDAC) causes annually well over 400,000 deaths world-wide and remains one of the major unresolved health problems. This exocrine pancreatic cancer originates from the mutated epithelial cells: acinar and ductal cells. However, the epithelia-derived cancer component forms only a relatively small fraction of the tumor mass. The majority of the tumor consists of acellular fibrous stroma and diverse populations of the non-neoplastic cancer-associated cells. Importantly, the tumor microenvironment is maintained by dynamic cell-cell and cell-matrix interactions. In this article, we aim to review the most common drivers of PDAC. Then we summarize the current knowledge on PDAC microenvironment, particularly in relation to pancreatic cancer therapy. The focus is placed on the acellular stroma as well as cell populations that inhabit the matrix. We also describe the altered metabolism of PDAC and characterize cellular signaling in this cancer.

Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation. These new features include C++-based code optimization for fast individual fiber tracking, Java-based synthetic fiber generator module for method validation, automatic tumor boundary generation for fiber relative quantification, parallel computing for large-scale batch mode processing, region-of-interest analysis for user-specified quantification, and pre- and post-processing modules for individual fiber visualization. We present a validation of the tracking of individual fibers and fiber orientations by using synthesized fibers generated by the synthetic fiber generator. In addition, we provide a comparison of the fiber orientation calculation on pancreatic tissue images between our tool and three other quantitative approaches. Lastly, we demonstrate the use of our software tool for the automatic tumor boundary creation and the relative alignment quantification of collagen fibers in human breast cancer pathology images, as well as the alignment quantification of in vivo mouse xenograft breast cancer images.

Altered organization of collagen fibers in the uninvolved human colon mucosa 10 cm and 20 cm away from the malignant tumor

Remodelling of collagen fibers has been described during every phase of cancer genesis and progression. Changes in morphology and organization of collagen fibers contribute to the formation of microenvironment that favors cancer progression and development of metastasis. However, there are only few data about remodelling of collagen fibers in healthy looking mucosa distant from the cancer. Using SHG imaging, electron microscopy and specialized softwares (CT-FIRE, CurveAlign and FiberFit), we objectively visualized and quantified changes in morphology and organization of collagen fibers and investigated possible causes of collagen remodelling (change in syntheses, degradation and collagen cross-linking) in the colon mucosa 10 cm and 20 cm away from the cancer in comparison with healthy mucosa. We showed that in the lamina propria this far from the colon cancer, there were changes in collagen architecture (width, straightness, alignment of collagen fibers and collagen molecules inside fibers), increased representation of myofibroblasts and increase expression of collagen-remodelling enzymes (LOX and MMP2). Thus, the changes in organization of collagen fibers, which were already described in the cancer microenvironment, also exist in the mucosa far from the cancer, but smaller in magnitude.

Molecular imaging of extracellular matrix proteins with targeted probes using magnetic resonance imaging

The extracellular matrix (ECM) consists of proteins and carbohydrates that supports different biological structures and processes such as tissue development, elasticity, and preservation of organ structure. Diseases involving inflammation, fibrosis, tumor invasion, and injury are all attributed to the transition of the ECM from homeostasis to remodeling, which can significantly change the biochemical and biomechanical features of ECM components. While contrast agents have played an indispensable role in facilitating clinical diagnosis of diseases using magnetic resonance imaging (MRI), there is a strong need to develop novel biomarker-targeted imaging probes for in vivo visualization of biological processes and pathological alterations at a cellular and molecular level, for both early diagnosis and monitoring drug treatment. Herein, we will first review the pathological accumulation and characterization of ECM proteins recognized as important molecular features of diseases. Developments in MRI probes targeting ECM proteins such as collagen, fibronectin, and elastin via conjugation of existing contrast agents to targeting moieties and their applications to various diseases, are also reviewed. We have also reviewed our progress in the development of collagen-targeted protein MRI contrast agent with significant improvement in relaxivity and metal binding specificity, and their applications in early detection of fibrosis and metastatic cancer. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Biology-Inspired Nanomaterials > Peptide-Based Structures Biology-Inspired Nanomaterials > Protein and Virus-Based Structures.

A Biomimetic Tumor Model of Heterogeneous Invasion in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a complex, heterogeneous, and genetically unstable disease. Its tumor microenvironment (TME) is complicated by heterogeneous cancer cell populations and strong desmoplastic stroma. This complex and heterogeneous environment makes it challenging to discover and validate unique therapeutic targets. Reliable and relevant in vitro PDAC tumor models can significantly advance the understanding of the PDAC TME and may enable the discovery and validation of novel drug targets. In this study, an engineered tumor model is developed to mimic the PDAC TME. This biomimetic model, named ductal tumor-microenvironment-on-chip (dT-MOC), permits analysis and experimentation on the epithelial-mesenchymal transition (EMT) and local invasion with intratumoral heterogeneity. This dT-MOC is a microfluidic platform where a duct of murine genetically engineered pancreatic cancer cells is embedded within a collagen matrix. The cancer cells used carry two of the three mutations of KRAS, CDKN2A, and TP53, which are key driver mutations of human PDAC. The intratumoral heterogeneity is mimicked by co-culturing these cancer cells. Using the dT-MOC model, heterogeneous invasion characteristics, and response to transforming growth factor-beta1 are studied. A mechanism of EMT and local invasion caused by the interaction between heterogeneous cancer cell populations is proposed.

Quantitative phase imaging of stromal prognostic markers in pancreatic ductal adenocarcinoma

New quantitative prognostic markers are needed for improved pancreatic ductal adenocarcinoma (PDAC) prognosis. Second harmonic generation microscopy has been used to show that collagen fiber alignment in PDAC is a negative prognostic factor. In this work, a series of PDAC and normal adjacent tissue (NAT) biopsies were imaged with spatial light interference microscopy (SLIM). Quantitative analysis performed on the biopsy SLIM images show that PDAC fiber structures have lower alignment per unit length, narrower width, and are longer than NAT controls. Importantly, fibrillar collagen in PDAC shows an inverse relationship between survival data and fiber width and length (p < 0.05).

Desmoplasia and Biophysics in Pancreatic Ductal Adenocarcinoma: Can We Learn From Breast Cancer?

Pancreatic ductal adenocarcinoma (PDAC) treatments have historically focused on targeting tumor cells directly. However, in pancreatic masses, the stroma encasing the malignant epithelial cells constitutes up to 80% to 90% of the tumor bulk. This extracellular matrix, which was previously neglected when designing cancer therapies, is now considered fundamental for tumor progression and drug delivery. Desmoplastic tissue is extensively cross-linked, resulting in tremendous tensile strength. This key pathological feature is procarcinogenic, linking PDAC and breast cancer (BC). Physical forces exerted onto cellular surfaces are detected intracellularly and transduced via biochemical messengers in a process called mechanotransduction. Mechanotransduction and tensional homeostasis are linked, with an integral role in influencing tumor growth, metastasis, and interactions with the immune system. It is essential to enhance our knowledge of these integral elements of parenchymal tumors. We aim to review the topic, with a special emphasis on desmoplastic processes and their importance in pancreatic and BC development and treatments, mindful that innovative diagnostic and therapeutic strategies cannot focus on biochemical pathways alone. We then focus on common therapeutic targets identified in both PDAC and BC models and/or patients, aiming to understand these treatments and draw similarities between the two tumors.

Spinal Cord Injury Results in Chronic Mechanical Stiffening

Gliosis and fibrosis after spinal cord injury (SCI) lead to formation of a scar that is thought to present both molecular and mechanical barriers to neuronal regeneration. The scar consists of a meshwork of reactive glia and deposited, cross-linked, extracellular matrix (ECM) that has long been assumed to present a mechanically "stiff" blockade. However, remarkably little quantitative information is available about the rheological properties of chronically injured spinal tissue. In this study we utilize atomic force microscopy microindentation to provide quantitative evidence of chronic mechanical stiffening after SCI. Using the results of this tissue characterization, we assessed the sensitivity of both mouse and human astrocytes in vitro and determined that they are exquisitely mechanosensitive within the relevant range of substrate stiffness observed in the injured/uninjured spinal cord. We then utilized a novel immune modifying nanoparticle (IMP) treatment as a tool to reveal fibrotic scarring as one of the key drivers of mechanical stiffening after SCI in vivo. We also demonstrate that glial scar-forming astrocytes form a highly aligned, anisotropic network of glial fibers after SCI, and that IMP treatment mitigates this pathological alignment. Taken together, our results identify chronic mechanical stiffening as a critically important aspect of the complex lesion milieu after SCI that must be considered when assessing and developing potential clinical interventions for SCI.

Epigenetic SMAD3 Repression in Tumor-Associated Fibroblasts Impairs Fibrosis and Response to the Antifibrotic Drug Nintedanib in Lung Squamous Cell Carcinoma

The tumor-promoting fibrotic stroma rich in tumor-associated fibroblasts (TAF) is drawing increased therapeutic attention. Intriguingly, a trial with the antifibrotic drug nintedanib in non-small cell lung cancer reported clinical benefits in adenocarcinoma (ADC) but not squamous cell carcinoma (SCC), even though the stroma is fibrotic in both histotypes. Likewise, we reported that nintedanib inhibited the tumor-promoting fibrotic phenotype of TAFs selectively in ADC. Here we show that tumor fibrosis is actually higher in ADC-TAFs than SCC-TAFs in vitro and patient samples. Mechanistically, the reduced fibrosis and nintedanib response of SCC-TAFs was associated with increased promoter methylation of the profibrotic TGFβ transcription factor SMAD3 compared with ADC-TAFs, which elicited a compensatory increase in TGFβ1/SMAD2 activation. Consistently, forcing global DNA demethylation of SCC-TAFs with 5-AZA rescued TGFβ1/SMAD3 activation, whereas genetic downregulation of SMAD3 in ADC-TAFs and control fibroblasts increased TGFβ1/SMAD2 activation, and reduced their fibrotic phenotype and antitumor responses to nintedanib in vitro and in vivo. Our results also support that smoking and/or the anatomic location of SCC in the proximal airways, which are more exposed to cigarette smoke particles, may prime SCC-TAFs to stronger SMAD3 epigenetic repression, because cigarette smoke condensate selectively increased SMAD3 promoter methylation. Our results unveil that the histotype-specific regulation of tumor fibrosis in lung cancer is mediated through differential SMAD3 promoter methylation in TAFs and provide new mechanistic insights on the selective poor response of SCC-TAFs to nintedanib. Moreover, our findings support that patients with ADC may be more responsive to antifibrotic drugs targeting their stromal TGFβ1/SMAD3 activation. SIGNIFICANCE: This study implicates the selective epigenetic repression of SMAD3 in SCC-TAFs in the clinical failure of nintedanib in SCC and supports that patients with ADC may benefit from antifibrotic drugs targeting stromal TGFβ1/SMAD3.

Geometric characteristics of collagen have independent prognostic significance in breast ductal carcinoma in situ: an image analysis study

Collagen plays a key role in normal and malignant tissue homeostasis. While the prognostic significance of collagen fiber remodeling in invasive breast cancer has been studied, its role in ductal carcinoma in situ (DCIS) remains poorly defined. Using image analysis, we aimed to evaluate the prognostic significance of the geometric characteristics of collagen surrounding DCIS. A large well-characterized cohort of DCIS comprising pure DCIS (n = 610) and DCIS coexisting with invasive carcinoma (n = 180) were histochemically stained for collagen using picrosirius red. ImageJ software was used to assess collagen density, degree of collagen fiber dispersion and directionality in relation to DCIS ducts' boundary. We developed a collagen prognostic index and evaluated its prognostic significance. A poor index was observed in 24% of the pure DCIS and was associated with determinants of high-risk DCIS including higher nuclear grade, comedo type necrosis, hormonal receptor negativity, HER2 positivity and high proliferation index. High collagen prognostic index was associated with the collagen remodeling protein prolyl-4-hydroxlase alpha subunit 2 and the hypoxia-related protein hypoxia inducible factor 1α. DCIS coexisting with invasive breast cancer had a higher collagen prognostic index than pure DCIS ( p < 0.0001). High index was an independent poor prognostic factor for DCIS recurrence for all recurrences (HR = 2.3, p = 0.005) and just invasive recurrences (HR = 3.4, p = 0.003). Interaction between collagen prognostic index and radiotherapy showed that the index was associated with poor outcome even with adjuvant radiotherapy ( p = 0.0001). Collagen reorganization around DCIS is associated with poor outcome and provides a potential predictor for disease progression and resistance to radiotherapy. Mechanistic studies are warranted to decipher the underlying mechanisms.

Rigidity controls human desmoplastic matrix anisotropy to enable pancreatic cancer cell spread via extracellular signal-regulated kinase 2

It is predicted that pancreatic ductal adenocarcinoma (PDAC) will become the second most lethal cancer in the US by 2030. PDAC includes a fibrous-like stroma, desmoplasia, encompassing most of the tumor mass, which is produced by cancer-associated fibroblasts (CAFs) and includes their cell-derived extracellular matrices (CDMs). Since elimination of desmoplasia has proven detrimental to patients, CDM reprogramming, as opposed to stromal ablation, is therapeutically desirable. Hence, efforts are being made to harness desmoplasia's anti-tumor functions. We conducted biomechanical manipulations, using variations of pathological and physiological substrates in vitro, to culture patient-harvested CAFs and generate CDMs that restrict PDAC growth and spread. We posited that extrinsic modulation of the environment, via substrate rigidity, influences CAF's cell-intrinsic forces affecting CDM production. Substrates used were polyacrylamide gels of physiological (~1.5 kPa) or pathological (~7 kPa) stiffnesses. Results showed that physiological substrates influenced CAFs to generate CDMs similar to normal/control fibroblasts. We found CDMs to be softer than the corresponding underlying substrates, and CDM fiber anisotropy (i.e., alignment) to be biphasic and informed via substrate-imparted morphological CAF aspect ratios. The biphasic nature of CDM fiber anisotropy was mathematically modeled and proposed a correlation between CAF aspect ratios and CDM alignment; regulated by extrinsic and intrinsic forces to conserve minimal free energy. Biomechanical manipulation of CDMs, generated on physiologically soft substrates, leads to reduction in nuclear translocation of pERK1/2 in KRAS mutated pancreatic cells. ERK2 was found essential for CDM-regulated tumor cell spread. In vitro findings correlated with in vivo observations; nuclear pERK1/2 is significantly high in human PDAC samples. The study suggests that altering underlying substrates enable CAFs to remodel CDMs and restrict pancreatic cancer cell spread in an ERK2 dependent manner.

Collagen organization of renal cell carcinoma differs between low and high grade tumors

Background

The traditional pathologic grading for human renal cell carcinoma (RCC) has low concordance between biopsy and surgical specimen. There is a need to investigate adjunctive pathology technique that does not rely on the nuclear morphology that defines the traditional grading. Changes in collagen organization in the extracellular matrix have been linked to prognosis or grade in breast, ovarian, and pancreatic cancers, but collagen organization has never been correlated with RCC grade. In this study, we used Second Harmonic Generation (SHG) based imaging to quantify possible differences in collagen organization between high and low grades of human RCC.

Methods

A tissue microarray (TMA) was constructed from RCC tumor specimens. Each TMA core represents an individual patient. A 5 μm section from the TMA tissue was stained with standard hematoxylin and eosin (H&E). Bright field images of the H&E stained TMA were used to annotate representative RCC regions. In this study, 70 grade 1 cores and 51 grade 4 cores were imaged on a custom-built forward SHG microscope, and images were analyzed using established software tools to automatically extract and quantify collagen fibers for alignment and density assessment. A linear mixed-effects model with random intercepts to account for the within-patient correlation was created to compare grade 1 vs. grade 4 measurements and the statistical tests were two-sided.

Results

Both collagen density and alignment differed significantly between RCC grade 1 and RCC grade 4. Specifically, collagen fiber density was greater in grade 4 than in grade 1 RCC (p < 0.001). Collagen fibers were also more aligned in grade 4 compared to grade 1 (p < 0.001).

Conclusions

Collagen density and alignment were shown to be significantly higher in RCC grade 4 vs. grade 1. This technique of biopsy sampling by SHG could complement classical tumor grading approaches. Furthermore it might allow biopsies to be more clinically relevant by informing diagnostics. Future studies are required to investigate the functional role of collagen organization in RCC.

Characterization of Pancreatic Cancer Tissue Using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy

Thin tissue sections of normal and tumorous pancreatic tissues stained with hematoxylin and eosin were investigated using multiphoton excitation fluorescence (MPF), second harmonic generation (SHG), and third harmonic generation (THG) microscopies. The cytoplasm, connective tissue, collagen and extracellular structures are visualized with MPF due to the eosin stain, whereas collagen is imaged with endogenous SHG contrast that does not require staining. Cellular structures, including membranous interfaces and nuclear components, are seen with THG due to the aggregation of hematoxylin dye. Changes in the collagen ultrastructure in pancreatic cancer were investigated by a polarization-sensitive SHG microscopy technique, polarization-in, polarization-out (PIPO) SHG. This involves measuring the orientation of the linear polarization of the SHG signal as a function of the linear polarization orientation of the incident laser radiation. From the PIPO SHG data, the second-order non-linear optical susceptibility ratio, χ(2) zzz '/χ(2) zxx ', was obtained that serves as a structural parameter for characterizing the tissue. Furthermore, by assuming C6 symmetry, an additional second-order non-linear optical susceptibility ratio, χ(2) xyz '/χ(2) zxx ', was obtained, which is a measure of the chirality of the collagen fibers. Statistically-significant differences in the χ(2) zzz '/χ(2) zxx ' values were found between tumor and normal pancreatic tissues in periductal, lobular, and parenchymal regions, whereas statistically-significant differences in the full width at half maximum (FWHM) of χ(2) xyz '/χ(2) zxx ' occurrence histograms were found between tumor and normal pancreatic tissues in periductal and parenchymal regions. Additionally, the PIPO SHG data were used to determine the degree of linear polarization (DOLP) of the SHG signal, which indicates the relative linear depolarization of the signal. Statistically-significant differences in DOLP values were found between tumor and normal pancreatic tissues in periductal and parenchymal regions. Hence, the differences observed in the χ(2) zzz '/χ(2) zxx ' values, the FWHM of χ(2) xyz '/χ(2) zxx ' values and the DOLP values could potentially be used to aid pathologists in diagnosing pancreatic cancer.

Actomyosin contractility-dependent matrix stretch and recoil induces rapid cell migration

Cells select from a diverse repertoire of migration strategies. Recent developments in tunable biomaterials have helped identify how extracellular matrix properties influence migration, however, many settings lack the fibrous architecture characteristic of native tissues. To investigate migration in fibrous contexts, we independently varied the alignment and stiffness of synthetic 3D fiber matrices and identified two phenotypically distinct migration modes. In contrast to stiff matrices where cells migrated continuously in a traditional mesenchymal fashion, cells in deformable matrices stretched matrix fibers to store elastic energy; subsequent adhesion failure triggered sudden matrix recoil and rapid cell translocation. Across a variety of cell types, traction force measurements revealed a relationship between cell contractility and the matrix stiffness where this migration mode occurred optimally. Given the prevalence of fibrous tissues, an understanding of how matrix structure and mechanics influences migration could improve strategies to recruit repair cells to wound sites or inhibit cancer metastasis.

Computer-aided assessment of the extra-cellular matrix during pancreatic carcinogenesis: a pilot study

BACKGROUND

A hallmark of pancreatic ductal adenocarcinoma is the desmoplastic reaction, but its impact on the tumor behavior remains controversial. Our aim was to introduce a computer -aided method to precisely quantify the amount of pancreatic collagenic extra-cellular matrix, its spatial distribution pattern, and the degradation process.

METHODS

A series of normal, inflammatory and neoplastic pancreatic ductal adenocarcinoma formalin-fixed and paraffin-embedded Sirius red stained sections were automatically digitized and analyzed using a computer-aided method.

RESULTS

We found a progressive increase of pancreatic collagenic extra-cellular matrix from normal to the inflammatory and pancreatic ductal adenocarcinoma. The two-dimensional fractal dimension showed a significant difference in the collagenic extra-cellular matrix spatial complexity between normal versus inflammatory and pancreatic ductal adenocarcinoma. A significant difference when comparing the number of cycles necessary to degrade the pancreatic collagenic extra-cellular matrix in normal versus inflammatory and pancreatic ductal adenocarcinoma was also found. The difference between inflammatory and pancreatic ductal adenocarcinoma was also significant. Furthermore, the mean velocity of collagenic extra-cellular matrix degradation was found to be faster in inflammatory and pancreatic ductal adenocarcinoma than in normal.

CONCLUSION

These findings demonstrate that inflammatory and pancreatic ductal adenocarcinomas are characterized by an increased amount of pancreatic collagenic extra-cellular matrix and by changes in their spatial complexity and degradation. Our study defines new features about the pancreatic collagenic extra-cellular matrix, and represents a basis for further investigations into the clinical behavior of pancreatic ductal adenocarcinoma and the development of therapeutic strategies.

ColXα1 is a stromal component that colocalizes with elastin in the breast tumor extracellular matrix

The tumor microenvironment regulates tissue development and homeostasis, and its dysregulation contributes to neoplastic progression. Increased expression of type X collagen α-1 (ColXα1) in tumor-associated stroma correlates with poor pathologic response to neoadjuvant chemotherapy in estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2)-positive breast cancers. Evaluation of ColXα1 expression patterns suggests a potential connection with elastin fibers. To investigate the possible interaction between ColXα1 and elastin, we evaluated the expression of ColXα1 in relation to elastin fibers in normal breast tissue, ductal carcinoma in situ, and invasive breast carcinomas at cellular and subcellular levels. Our findings demonstrate that ColXα1 colocalizes with elastin in invasive breast cancer-associated stroma by immunohistochemistry, immunofluorescence, and electron microscopy. In 212 invasive breast carcinomas, this complex was aberrantly and selectively expressed in tumor extracellular matrix in 79% of ER+/HER2-, 80% of ER+/HER2+, 76% of ER-/HER2+, and 58% of triple negative breast cancers. In contrast, ColXα1 was generally absent, while elastin was present perivascularly in normal breast tissue. ColXα1 and elastin were coexpressed in 58% of ductal carcinoma in situ (DCIS) in periductal areas. In mass-forming DCIS with desmoplastic stroma, the complex was intensely expressed in periductal areas as well as within the tumor-associated stroma in all cases. Our data suggest that the breast carcinoma neoplastic process may involve aberrant expression of ColXα1 and elastin in the tumor microenvironment emerging early at the DCIS stage. Enrichment of these complexes in tumor-associated stroma may represent a stromal signature indicative of intrinsic differences between breast cancers. These findings shed light on investigation into the role of aberrant collagen complex expression in tumorigenesis and tumor progression which may be leveraged in therapeutic and theranostic applications.

The use of magnetic resonance elastography in differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma: A preliminary study

PURPOSE

To assess the value of magnetic resonance elastography (MRE) in patients with autoimmune pancreatitis (AIP) and in the differentiation of AIP from pancreatic ductal adenocarcinoma (PDAC).

METHOD AND MATERIALS

This prospective study included 14 AIP patients, 26 PDAC patients, and 14 healthy volunteers. All participants underwent pancreatic MRE (40-Hz; 3 T scanner) at enrollment, and 7 AIP patients underwent a second MRE after initiation of steroid therapy. Pancreatic stiffness values were obtained by MRE and a new logistic regression model (the calculated Rad score) was used to combine pancreatic stiffness and the distribution and shape of high-stiffness areas for differentiation of AIP and PDAC. The area under the curve (AUC) was calculated for all parameters using receiver operating characteristic (ROC) analysis.

RESULTS

Pancreatic stiffness was significantly higher (2.67 kPa [interquartile range, 2.24-3.56 kPa]) in AIP than in healthy pancreas (1.24 kPa [1.18-1.24 kPa]) and significantly lower in AIP than in PDAC (3.78 kPa [3.22-5.11 kPa]; both P < 0.05). Diffuse (n = 4 vs 1; P = 0.043) and multiple (n = 3 vs 0; P = 0.037) lesions were more common in AIP, while solitary (n = 25 vs 7; P = 0.001) and nodular lesions (n = 18 vs 2; P =  0.002) were more frequent in PDAC. Rad scores outperformed individual imaging parameters in distinguishing AIP from PDAC (AUC, 0.948 vs 0.607 to 0.782; all P < 0.05), with 84.6% specificity and 92.9% sensitivity. Pancreatic stiffness in AIP decreased significantly, from 2.66 kPa [2.29 to 3.05 kPa] to 1.55 kPa [1.43 to 1.67 kPa] (P = 0.016), during treatment.

CONCLUSIONS

MRE shows promise as a quantitative imaging method for differentiating AIP from PDAC and for monitoring the treatment response in AIP.

The clinical usefulness of optical coherence tomography during cancer interventions

INTRODUCTION

Tumor detection and visualization plays a key role in the clinical workflow of a patient with suspected cancer, both in the diagnosis and treatment. Several optical imaging techniques have been evaluated for guidance during oncological interventions. Optical coherence tomography (OCT) is a technique which has been widely evaluated during the past decades. This review aims to determine the clinical usefulness of OCT during cancer interventions focussing on qualitative features, quantitative features and the diagnostic value of OCT.

METHODS

A systematic literature search was performed for articles published before May 2018 using OCT in the field of surgical oncology. Based on these articles, an overview of the clinical usefulness of OCT was provided per tumor type.

RESULTS

A total of 785 articles were revealed by our search, of which a total of 136 original articles were available for analysis, which formed the basis of this review. OCT is currently utilised for both preoperative diagnosis and intraoperative detection of skin, oral, lung, breast, hepatobiliary, gastrointestinal, urological, and gynaecological malignancies. It showed promising results in tumor detection on a microscopic level, especially using higher resolution imaging techniques, such as high-definition OCT and full-field OCT.

CONCLUSION

In the near future, OCT could be used as an additional tool during bronchoscopic or endoscopic interventions and could also be implemented in margin assessment during (laparoscopic) cancer surgery if a laparoscopic or handheld OCT device will be further developed to make routine clinical use possible.

Biophysics of Tumor Microenvironment and Cancer Metastasis - A Mini Review

The role of tumor microenvironment in cancer progression is gaining significant attention. It is realized that cancer cells and the corresponding stroma co-evolve with time. Cancer cells recruit and transform the stromal cells, which in turn remodel the extra cellular matrix of the stroma. This complex interaction between the stroma and the cancer cells results in a dynamic feed-forward/feed-back loop with biochemical and biophysical cues that assist metastatic transition of the cancer cells. Although biochemistry has long been studied for the understanding of cancer progression, biophysical signaling is emerging as a critical paradigm determining cancer metastasis. In this mini review, we discuss the role of one of the biophysical cues, mostly the mechanical stiffness of tumor microenvironment, in cancer progression and its clinical implications.

The hepatic pre-metastatic niche in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive malignancies to date, largely because it is associated with high metastatic risk. Pancreatic tumors have a characteristic tendency to metastasize preferentially to the liver. Over the past two decades, it has become evident that the otherwise hostile milieu of the liver is selectively preconditioned at an early stage to render it more conducive to the engraftment and growth of disseminated cancer cells, a concept defined as pre-metastatic niche (PMN) formation. Pancreatic cancer cells exploit components of the tumor microenvironment to facilitate their migration out of the primary tumor, which often involves conversion of pancreatic cancer cells from an epithelial to a mesenchymal phenotype via the epithelial-to-mesenchymal transition. Pancreatic stellate cells and matrix stiffness have been put forward as major drivers of invasiveness in PDAC. Even before the onset of pancreatic cancer cell dissemination, soluble factors and extracellular vesicles secreted by the primary tumor, and possibly even premalignant lesions, help shape a supportive niche in the liver by providing vascular docking sites for circulating tumor cells, enhancing vascular permeability, remodeling the extracellular matrix and recruiting immunosuppressive inflammatory cells. Emerging evidence suggests that some of these tumor-derived factors may represent powerful diagnostic or prognostic biomarkers. Though our understanding of the mechanisms driving PMN formation in PDAC has expanded considerably, many outstanding questions and challenges remain. Further studies dissecting the molecular and cellular events involved in hepatic PMN formation in PDAC will likely improve diagnosis and open new avenues from a therapeutic standpoint.

Methods for Quantifying Fibrillar Collagen Alignment

Recent evidence has implicated collagen, particularly fibrillar collagen, in a number of diseases ranging from osteogenesis imperfecta and asthma to breast and ovarian cancer. A key property of collagen that has been correlated with disease has been the alignment of collagen fibers. Collagen can be visualized using a variety of imaging techniques including second-harmonic generation (SHG) microscopy, polarized light microscopy, and staining with dyes or antibodies. However, there exists a great need to easily and robustly quantify images from these modalities for individual fibers in specified regions of interest and with respect to relevant boundaries. Most currently available computational tools rely on calculation of pixel-wise orientation or global window-wise orientation that do not directly calculate or give visible fiber-wise information and do not provide relative orientation against boundaries. We describe and detail how to use a freely available, open-source MATLAB software framework that includes two separate but linked packages "CurveAlign" and "CT-FIRE" that can address this need by either directly extracting individual fibers using an improved fiber tracking algorithm or directly finding optimal representation of fiber edges using the curvelet transform. This curvelet-based framework allows the user to measure fiber alignment on a global, region of interest, and fiber basis. Additionally, users can measure fiber angle relative to manually or automatically segmented boundaries. This tool does not require prior experience of programming or image processing and can handle multiple files, enabling efficient quantification of collagen organization from biological datasets.

Dynamics of 3D carcinoma cell invasion into aligned collagen

Carcinoma cells frequently expand and invade from a confined lesion, or multicellular clusters, into and through the stroma on the path to metastasis, often with an efficiency dictated by the architecture and composition of the microenvironment. Specifically, in desmoplastic carcinomas such as those of the breast, aligned collagen tracks provide contact guidance cues for directed cancer cell invasion. Yet, the evolving dynamics of this process of invasion remains poorly understood, in part due to difficulties in continuously capturing both spatial and temporal heterogeneity and progression to invasion in experimental systems. Therefore, to study the local invasion process from cell dense clusters into aligned collagen architectures found in solid tumors, we developed a novel engineered 3D invasion platform that integrates an aligned collagen matrix with a cell dense tumor-like plug. Using multiphoton microscopy and quantitative analysis of cell motility, we track the invasion of cancer cells from cell-dense bulk clusters into the pre-aligned 3D matrix, and define the temporal evolution of the advancing invasion fronts over several days. This enables us to identify and probe cell dynamics in key regions of interest: behind, at, and beyond the edge of the invading lesion at distinct time points. Analysis of single cell migration identifies significant spatial heterogeneity in migration behavior between cells in the highly cell-dense region behind the leading edge of the invasion front and cells at and beyond the leading edge. Moreover, temporal variations in motility and directionality are also observed between cells within the cell-dense tumor-like plug and the leading invasive edge as its boundary extends into the anisotropic collagen over time. Furthermore, experimental results combined with mathematical modeling demonstrate that in addition to contact guidance, physical crowding of cells is a key regulating factor orchestrating variability in single cell migration during invasion into anisotropic ECM. Thus, our novel platform enables us to capture spatio-temporal dynamics of cell behavior behind, at, and beyond the invasive front and reveals heterogeneous, local interactions that lead to the emergence and maintenance of the advancing front.

3D collagen architecture induces a conserved migratory and transcriptional response linked to vasculogenic mimicry

The topographical organization of collagen within the tumor microenvironment has been implicated in modulating cancer cell migration and independently predicts progression to metastasis. Here, we show that collagen matrices with small pores and short fibers, but not Matrigel, trigger a conserved transcriptional response and subsequent motility switch in cancer cells resulting in the formation of multicellular network structures. The response is not mediated by hypoxia, matrix stiffness, or bulk matrix density, but rather by matrix architecture-induced β1-integrin upregulation. The transcriptional module associated with network formation is enriched for migration and vasculogenesis-associated genes that predict survival in patient data across nine distinct tumor types. Evidence of this gene module at the protein level is found in patient tumor slices displaying a vasculogenic mimicry (VM) phenotype. Our findings link a collagen-induced migration program to VM and suggest that this process may be broadly relevant to metastatic progression in solid human cancers.

Extracellular matrix plays a central role in driving cancer development. Here the authors using an in vitro approach show that confining collagen architectures induce fast and persistent cell migration and the formation of multicellular network structures linked to vascular mimicry observed in tumours from patients.

Human pancreatic stellate cells modulate 3D collagen alignment to promote the migration of pancreatic ductal adenocarcinoma cells

A hallmark of pancreatic ductal adenocarcinoma (PDAC) is the ability for cancer cells to aggressively infiltrate and navigate through a dense stroma during the metastatic process. Key features of the PDAC stroma include an abundant population of activated pancreatic stellate cells (PSCs) and highly aligned collagen fibers; however, important questions remain regarding how collagen becomes aligned and what the biological manifestations are. To better understand how PSCs, aligned collagen, and PDAC cells might cooperate during the transition to invasion, we utilized a microchannel-based in vitro tumor model and advanced imaging technologies to recreate and examine in vivo-like heterotypic interactions. We found that PSCs participate in a collaborative process with cancer cells by orchestrating the alignment of collagen fibers that, in turn, are permissive to enhanced cell migration. Additionally, direct contact between PSCs, collagen, and PDAC cells is critical to invasion and co-migration of both cell types. This suggests PSCs may accompany and assist in navigating PDAC cells through the stromal terrain. Together, our data provides a new role for PSCs in stimulating the metastatic process and underscores the importance of collagen alignment in cancer progression.

Quantification of collagen organization in histopathology samples using liquid crystal based polarization microscopy

A number of histopathology studies have utilized the label free microscopy method of Second Harmonic Generation (SHG) to investigate collagen organization in disease onset and progression. Here we explored an alternative label free imaging approach, LC-PolScope that is based on liquid crystal based polarized light imaging. We demonstrated that this more accessible technology has the ability to visualize all fibers of interest and has a good to excellent correlation between SHG and LC-PolScope measurements in fibrillar collagen orientation and alignment. This study supports that LC-PolScope is a viable alternative to SHG for label free collagen organization measurements in thin histology sections.

Fluorescence of Picrosirius Red Multiplexed With Immunohistochemistry for the Quantitative Assessment of Collagen in Tissue Sections

The low cost and simplicity of picrosirius red (PSR) staining have driven its popularity for collagen detection in tissue sections. We extended the versatility of this method by using fluorescent imaging to detect the PSR signal and applying automated quantification tools. We also developed the first PSR protocol that is fully compatible with multiplex immunostaining, making it possible to test whether collagen structure differs across immunohistochemically labeled regions of the tissue landscape. We compared our imaging method with two gold standards in collagen imaging, linear polarized light microscopy and second harmonic generation imaging, and found that it is at least as sensitive and robust to changes in sample orientation. As proof of principle, we used a genetic approach to overexpress beta catenin in a patchy subset of mouse prostate epithelial cells distinguished only by immunolabeling. We showed that collagen fiber length is significantly greater near beta catenin overexpressing cells than near control cells. Our fluorescent PSR imaging method is sensitive, reproducible, and offers a new way to guide region of interest selection for quantifying collagen in tissue sections.

Identification of prognostic collagen signatures and potential therapeutic stromal targets in canine mammary gland carcinoma

Increasing evidence indicates that the tumor microenvironment plays a critical role in regulating the biologic behavior of breast cancer. In veterinary oncology, there is a need for improved prognostic markers to accurately identify dogs at risk for local and distant (metastatic) recurrence of mammary gland carcinoma and therefore would benefit from adjuvant therapy. Collagen density and fiber organization have been shown to regulate tumor progression in both mouse and human mammary tumors, with certain collagen signatures predicting poor outcomes in women with breast cancer. We hypothesized that collagen signatures in canine mammary tumor biopsies can serve as prognostic biomarkers and potential targets for treatment. We used second harmonic generation imaging to evaluate fibrillar collagen density, the presence of a tumor-stromal boundary, tumor associated collagen signatures (TACS) and individual collagen fiber characteristics (width, length and straightness) in grade I/II and grade III canine mammary tumors. Collagen density, as well as fiber width, length and straightness, were inversely correlated with patient overall survival time. Notably, grade III cases were less likely to have a tumor-stromal boundary and the lack of a boundary predicted poor outcome. Importantly, a lack of a defined tumor-stromal boundary and an increased collagen fiber width were associated with decreased survival even when tumor grade, patient stage, ovariohysterectomy status at the time of mammary tumor excision, and histologic evidence of lymphovascular invasion were considered in a multivariable model, indicating that these parameters could augment current methods to identify patients at high risk for local or metastatic progression/recurrence. Furthermore, these data, which identify for the first time, prognostic collagen biomarkers in naturally occurring mammary gland neoplasia in the dog, support the use of the dog as a translational model for tumor-stromal interactions in breast cancer.

Matrix stiffness induces epithelial-mesenchymal transition and promotes chemoresistance in pancreatic cancer cells

Increased matrix rigidity associated with the fibrotic reaction is documented to stimulate intracellular signalling pathways that promote cancer cell survival and tumour growth. Pancreatic cancer is one of the stiffest of all human solid carcinomas and is characterised by a remarkable desmoplastic reaction. Here we use mouse models, genetically engineered to recapitulate human pancreatic cancer, and several pancreatic cancer cell lines as a model to investigate the effect of matrix stiffness in epithelial-mesenchymal transition (EMT) and resistance to chemotherapeutics. We found that recapitulation of the fibrotic rigidities found in pancreatic cancer tissues promote elements of EMT, including increases in vimentin expression, decreases in E-cadherin expression, nuclear localisation of β-catenin, YAP and TAZ and changes in cell shape towards a mesenchymal phenotype. We also report that stiffness induces chemoresistance to paclitaxel, but not to gemcitabine, both commonly used therapeutics, suggesting that environmental rigidity underlies an aspect of chemoresistance.

Reorganized Collagen in the Tumor Microenvironment of Gastric Cancer and Its Association with Prognosis

Collagen components in the tumor microenvironment substantially influence cancer pathogenesis and progression. Nevertheless, in gastric cancer, collagen status and its prognostic role remain unclear. Using picrosirius red staining and immunohistochemistry, we found that collagen deposition was significantly increased in gastric cancer when compared with non-neoplastic tissues, and in cancer stroma, more immature collagen components were present, suggesting a qualitative change. Furthermore, the morphology of collagen fibers could be weakly, moderately or strongly changed in gastric cancer; when weakly or moderately changed, they appeared similar to normal collagen fibers, except for a higher linearization and density; when strongly changed, they were thicker and less eosinophilic, sharply differently from their normal counterparts. In addition, we found abundant myofibroblasts and elevated expression of lysyl oxidase-like 2 (the enzyme that mediates crosslinking of collagen molecules) in cancer stroma, which might contribute to the increased collagen deposition and crosslinking. Last, five collagen architectural parameters (alignment, density, width, length and straightness) were analyzed with second harmonic generation imaging, a highly specific technology for detection of collagen fibers, and our data indicated that all the parameters were significantly increased in the tumor microenvironment. Of the five parameters, collagen width was the most powerful parameter in predicting 5-year overall survival, and increased collagen width was associated with reduced survival. The prognostic value of collagen width was superior to traditional clinicopathological parameters, and this was validated in two unrelated gastric cancer cohorts that contained 225 and 151 patients. Collectively, the collagen status (content, maturity, morphology and architecture) was profoundly reorganized in the tumor microenvironment of gastric cancer, and collagen width could serve as a valuable prognostic indicator.

The prognostic value and pathobiological significance of Glasgow microenvironment score in gastric cancer

PURPOSE

To evaluate the prognostic value and pathobiological significance of Glasgow microenvironment score (GMS), a parameter based on tumor stroma percentage and inflammatory cell infiltration, in gastric cancer.

METHODS

A total of 225 cases of gastric cancer were histologically reviewed, and GMS was evaluated for each case. The association between GMS and patients' survival was investigated. Then the relationship between GMS and mismatch repair (MMR) status, Epstein-Barr virus (EBV) infection were determined using immunohistochemistry (IHC) and in situ hybridization, and the expression of PD1/PD-L1 was examined. Furthermore, the amount of cancer-associated fibroblasts (CAFs), the content and maturity of collagen components were detected using IHC, Picrosirius Red staining and second harmonic generation imaging.

RESULTS

GMS was significantly associated with clinical outcomes of gastric cancer, and multivariate analysis indicated that GMS was an independent factor (HR 1.725, P = 0.002). Low GMS was a manifestation of better prognosis and inflammatory tumor microenvironment, which was related to MMR deficiency (P = 0.042) and EBV infection (P = 0.032), and within this microenvironment, expression of PD-L1 in carcinoma cells (P = 0.030) or in inflammatory cells (P = 0.029) was significantly higher. In contrast, high GMS linked to a poorer survival and desmoplastic stroma, in which there existed markedly increased CAFs and collagen deposition.

CONCLUSION

GMS can serve as a useful prognostic factor for gastric cancer, and according to GMS, the tumor microenvironment in this cancer type may be partially classified as inflammatory or desmoplastic microenvironment that possesses different pathobiological features.

Validation of full-field optical coherence tomography in distinguishing malignant and benign tissue in resected pancreatic cancer specimens

Background

Pancreatic cancer is the fourth leading cause of cancer-related mortality in the United States. The minority of patients can undergo curative-intended surgical therapy due to progressive disease stage at time of diagnosis. Nonetheless, tumor involvement of surgical margins is seen in up to 70% of resections, being a strong negative prognostic factor. Real-time intraoperative imaging modalities may aid surgeons to obtain tumor-free resection margins. Full-field optical coherence tomography (FF-OCT) is a promising diagnostic tool using high-resolution white-light interference microscopy without tissue processing. Therefore, we composed an atlas of FF-OCT images of malignant and benign pancreatic tissue, and investigated the accuracy with which the pathologists could distinguish these.

Materials and methods

One hundred FF-OCT images were collected from specimens of 29 patients who underwent pancreatic resection for various indications between 2014 and 2016. One experienced gastrointestinal pathologist and one pathologist in training scored independently the FF-OCT images as malignant or benign blinded to the final pathology conclusion. Results were compared to those obtained with standard hematoxylin and eosin (H&E) slides.

Results

Overall, combined test characteristics of both pathologists showed a sensitivity of 72%, specificity of 74%, positive predictive value of 69%, negative predictive value of 79% and an overall accuracy of 73%. In the subset of pancreatic ductal adenocarcinoma patients, 97% of the FF-OCT images (n = 35) were interpreted as tumor by at least one pathologist. Moreover, normal pancreatic tissue was recognised in all cases by at least one pathologist. However, atrophy and fibrosis, serous cystadenoma and neuroendocrine tumors were more often wrongly scored, in 63%, 100% and 25% respectively.

Conclusion

FF-OCT could distinguish normal pancreatic tissue from pathologic pancreatic tissue in both processed as non-processed specimens using architectural features. The accuracy in pancreatic ductal adenocarcinoma is promising and warrants further evaluation using improved assessment criteria.

Anisotropic forces from spatially constrained focal adhesions mediate contact guidance directed cell migration

Directed migration by contact guidance is a poorly understood yet vital phenomenon, particularly for carcinoma cell invasion on aligned collagen fibres. We demonstrate that for single cells, aligned architectures providing contact guidance cues induce constrained focal adhesion maturation and associated F-actin alignment, consequently orchestrating anisotropic traction stresses that drive cell orientation and directional migration. Consistent with this understanding, relaxing spatial constraints to adhesion maturation either through reduction in substrate alignment density or reduction in adhesion size diminishes the contact guidance response. While such interactions allow single mesenchymal-like cells to spontaneously 'sense' and follow topographic alignment, intercellular interactions within epithelial clusters temper anisotropic cell-substratum forces, resulting in substantially lower directional response. Overall, these results point to the control of contact guidance by a balance of cell-substratum and cell-cell interactions, modulated by cell phenotype-specific cytoskeletal arrangements. Thus, our findings elucidate how phenotypically diverse cells perceive ECM alignment at the molecular level.

Imaging in pancreatic disease

Pancreatic diseases, chronic pancreatitis, pancreatic cancer and diabetes mellitus, taken together, occur in >10% of the world population. Pancreatic diseases, as with other diseases, benefit from early intervention and appropriate diagnosis. Although imaging technologies have given clinicians an unprecedented toolbox to aid in clinical decision-making, advances in these technologies and development of molecular-based diagnostic tools could enable physicians to identify diseases at an even earlier stage and, thereby, improve patient outcomes. In this Review, we discuss and identify gaps in the use of imaging techniques for the early detection and appropriate treatment stratification of various pancreatic diseases, including diabetes mellitus, acute and chronic pancreatitis and pancreatic cancer. Imaging techniques discussed are MRI, CT, PET and ultrasonography. Additionally, the identification of new molecular targets for imaging and the development of contrast agents that are able to give molecular information in noninvasive radionuclear imaging and ultrasonography are emerging areas of innovation that could lead to increased diagnostic accuracy and improved patient outcomes.

Characterization of the Tumor Microenvironment and Tumor-Stroma Interaction by Non-invasive Preclinical Imaging

Tumors are often characterized by hypoxia, vascular abnormalities, low extracellular pH, increased interstitial fluid pressure, altered choline-phospholipid metabolism, and aerobic glycolysis (Warburg effect). The impact of these tumor characteristics has been investigated extensively in the context of tumor development, progression, and treatment response, resulting in a number of non-invasive imaging biomarkers. More recent evidence suggests that cancer cells undergo metabolic reprograming, beyond aerobic glycolysis, in the course of tumor development and progression. The resulting altered metabolic content in tumors has the ability to affect cell signaling and block cellular differentiation. Additional emerging evidence reveals that the interaction between tumor and stroma cells can alter tumor metabolism (leading to metabolic reprograming) as well as tumor growth and vascular features. This review will summarize previous and current preclinical, non-invasive, multimodal imaging efforts to characterize the tumor microenvironment, including its stromal components and understand tumor-stroma interaction in cancer development, progression, and treatment response.

Induction of fibroblast senescence generates a non-fibrogenic myofibroblast phenotype that differentially impacts on cancer prognosis

Cancer-associated fibroblasts (CAF) remain a poorly characterized, heterogeneous cell population. Here we characterized two previously described tumor-promoting CAF sub-types, smooth muscle actin (SMA)-positive myofibroblasts and senescent fibroblasts, identifying a novel link between the two. Analysis of CAF cultured ex vivo, showed that senescent CAF are predominantly SMA-positive; this was confirmed by immunochemistry in head & neck (HNSCC) and esophageal (EAC) cancers. In vitro, we found that fibroblasts induced to senesce develop molecular, ultrastructural and contractile features typical of myofibroblasts and this is dependent on canonical TGF-β signaling. Similar to TGF-β1-generated myofibroblasts, these cells secrete soluble factors that promote tumor cell motility. However, RNA-sequencing revealed significant transcriptomic differences between the two SMA-positive CAF groups, particularly in genes associated with extracellular matrix (ECM) deposition and organization, which differentially promote tumor cell invasion. Notably, second harmonic generation imaging and bioinformatic analysis of SMA-positive human HNSCC and EAC showed that collagen fiber organization correlates with poor prognosis, indicating that heterogeneity within the SMA-positive CAF population differentially impacts on survival. These results show that non-fibrogenic, SMA-positive myofibroblasts can be directly generated through induction of fibroblast senescence and suggest that senescence and myofibroblast differentiation are closely linked processes.