Highly aligned stromal collagen is a negative prognostic factor following pancreatic ductal adenocarcinoma resection

Tertiary lymphoid structures accompanied by fibrillary matrix morphology impact anti-tumor immunity in basal cell carcinomas

Tertiary lymphoid structures (TLS) are specialized lymphoid formations that serve as local repertoire of T- and B-cells at sites of chronic inflammation, autoimmunity, and cancer. While presence of TLS has been associated with improved response to immune checkpoint blockade therapies and overall outcomes in several cancers, its prognostic value in basal cell carcinoma (BCC) has not been investigated. Herein, we determined the prognostic impact of TLS by relating its prevalence and maturation with outcome measures of anti-tumor immunity, namely tumor infiltrating lymphocytes (TILs) and tumor killing. In 30 distinct BCCs, we show the presence of TLS was significantly enriched in tumors harboring a nodular component and more mature primary TLS was associated with TIL counts. Moreover, assessment of the fibrillary matrix surrounding tumors showed discrete morphologies significantly associated with higher TIL counts, critically accounting for heterogeneity in TIL count distribution within TLS maturation stages. Specifically, increased length of fibers and lacunarity of the matrix with concomitant reduction in density and alignment of fibers were present surrounding tumors displaying high TIL counts. Given the interest in inducing TLS formation as a therapeutic intervention as well as its documented prognostic value, elucidating potential impediments to the ability of TLS in driving anti-tumor immunity within the tumor microenvironment warrants further investigation. These results begin to address and highlight the need to integrate stromal features which may present a hindrance to TLS formation and/or effective function as a mediator of immunotherapy response.

Multiscale anisotropy analysis of second-harmonic generation collagen imaging of human pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with a minority (< 10%) of patients surviving five years past diagnosis. This could be improved with the development of new imaging modalities for early differentiation of benign and cancerous fibrosis. This study intends to explore the application of a two-photon microscopy technique known as second harmonic generation to PDAC using the 2D Wavelet Transform Modulus Maxima (WTMM) Anisotropy method to quantify collagen organization in fibrotic pancreatic tissue. Forty slides from PDAC patients were obtained and eight images were captured per each tissue category on each slide. Brownian surface motion and white noise images were generated for calibration and testing of a new variable binning approach to the 2D WTMM Anisotropy method. The variable binning method had greater resistance to wavelet scaling effects and white noise images were found to have the lowest anisotropy factor. Cancer and fibrosis had greater anisotropy factors (Fa) at small wavelet scales than normal and normal adjacent tissue. At a larger scale of 21 μm this relationship changed with normal tissue having a higher Fa than all other tissue groups. White noise is the best representative image for isotropy and the 2D WTMM anisotropy method is sensitive to changes induced in collagen by PDAC.

Extracellular matrix mechanobiology in cancer cell migration

The extracellular matrix (ECM) is pivotal in modulating tumor progression. Besides chemically stimulating tumor cells, it also offers physical support that orchestrates the sequence of events in the metastatic cascade upon dynamically modulating cell mechanosensation. Understanding this translation between matrix biophysical cues and intracellular signaling has led to rapid growth in the interdisciplinary field of cancer mechanobiology in the last decade. Substantial efforts have been made to develop novel in vitro tumor mimicking platforms to visualize and quantify the mechanical forces within the tissue that dictate tumor cell invasion and metastatic growth. This review highlights recent findings on tumor matrix biophysical cues such as fibrillar arrangement, crosslinking density, confinement, rigidity, topography, and non-linear mechanics and their implications on tumor cell behavior. We also emphasize how perturbations in these cues alter cellular mechanisms of mechanotransduction, consequently enhancing malignancy. Finally, we elucidate engineering techniques to individually emulate the mechanical properties of tumors that could help serve as toolkits for developing and testing ECM-targeted therapeutics on novel bioengineered tumor platforms. STATEMENT OF SIGNIFICANCE: Disrupted ECM mechanics is a driving force for transitioning incipient cells to life-threatening malignant variants. Understanding these ECM changes can be crucial as they may aid in developing several efficacious drugs that not only focus on inducing cytotoxic effects but also target specific matrix mechanical cues that support and enhance tumor invasiveness. Designing and implementing an optimal tumor mimic can allow us to predictively map biophysical cue-modulated cell behaviors and facilitate the design of improved lab-grown tumor models with accurately controlled structural features. This review focuses on the abnormal changes within the ECM during tumorigenesis and its implications on tumor cell-matrix mechanoreciprocity. Additionally, it accentuates engineering approaches to produce ECM features of varying levels of complexity which is critical for improving the efficiency of current engineered tumor tissue models.

NetrinG1+ cancer-associated fibroblasts generate unique extracellular vesicles that support the survival of pancreatic cancer cells under nutritional stress

It is projected that in 5 years, pancreatic cancer will become the second deadliest cancer in the United States. A unique aspect of pancreatic ductal adenocarcinoma (PDAC) is its stroma; rich in cancer-associated fibroblasts (CAFs) and a dense CAF-generated extracellular matrix (ECM). These pathogenic stroma CAF/ECM units cause the collapse of local blood vessels rendering the tumor microenvironment nutrient-poor. PDAC cells are able to survive this state of nutrient stress via support from CAF-secreted material, which includes small extracellular vesicles (sEVs). The tumor-supportive CAFs possess a distinct phenotypic profile, compared to normal-like fibroblasts, expressing NetrinG1 (NetG1) at the plasma membrane, and active Integrin α₅β₁ localized to the multivesicular bodies; traits indicative of poor patient survival. We herein report that NetG1⁺ CAFs secrete sEVs that stimulate Akt-mediated survival in nutrient-deprived PDAC cells, protecting them from undergoing apoptosis. Further, we show that NetG1 expression in CAFs is required for the pro-survival properties of sEVs. Additionally, we report that the above-mentioned CAF markers are secreted in distinct subpopulations of EVs; with NetG1 being enriched in exomeres, and Integrin α₅β₁ being enriched in exosomes. Finally, we found that NetG1 and Integrin α₅β₁ were detected in sEVs collected from plasma of PDAC patients, while their levels were significantly lower in plasma-derived sEVs of sex/age-matched healthy donors. The discovery of these tumor-supporting CAF-EVs elucidates novel avenues in tumor-stroma interactions and pathogenic stroma detection.

Remediating Desmoplasia with EGFR-Targeted Photoactivable Multi-Inhibitor Liposomes Doubles Overall Survival in Pancreatic Cancer

Desmoplasia is characteristic of pancreatic ductal adenocarcinoma (PDAC), which exhibits 5-year survival rates of 3%. Desmoplasia presents physical and biochemical barriers that contribute to treatment resistance, yet depleting the stroma alone is unsuccessful and even detrimental to patient outcomes. This study is the first demonstration of targeted photoactivable multi-inhibitor liposomes (TPMILs) that induce both photodynamic and chemotherapeutic tumor insult, while simultaneously remediating desmoplasia in orthotopic PDAC. TPMILs targeted with cetuximab (anti-EGFR mAb) contain lipidated benzoporphyrin derivative (BPD-PC) photosensitizer and irinotecan. The desmoplastic tumors comprise human PDAC cells and patient-derived cancer-associated fibroblasts. Upon photoactivation, the TPMILs induce 90% tumor growth inhibition at only 8.1% of the patient equivalent dose of nanoliposomal irinotecan (nal-IRI). Without EGFR targeting, PMIL photoactivation is ineffective. TPMIL photoactivation is also sixfold more effective at inhibiting tumor growth than a cocktail of Visudyne-photodynamic therapy (PDT) and nal-IRI, and also doubles survival and extends progression-free survival by greater than fivefold. Second harmonic generation imaging reveals that TPMIL photoactivation reduces collagen density by >90% and increases collagen nonalignment by >103 -fold. Collagen nonalignment correlates with a reduction in tumor burden and survival. This single-construct phototoxic, chemotherapeutic, and desmoplasia-remediating regimen offers unprecedented opportunities to substantially extend survival in patients with otherwise dismal prognoses.

MALDI-MSI: A Powerful Approach to Understand Primary Pancreatic Ductal Adenocarcinoma and Metastases

Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.

Magnetically Driven Hierarchical Alignment in Biomimetic Fibrous Hydrogels

In vivo, natural biomaterials are frequently anisotropic, exhibiting directional microstructures and mechanical properties. It remains challenging to develop such anisotropy in synthetic materials. Here, a facile one-step approach for in situ fabrication of hydrogels with hierarchically anisotropic architectures and direction-dependent mechanical properties is proposed. The anisotropic hydrogels, composed of a fibrous gel network (0.1 wt%), cross-linked with magnetic nanoparticles (spheres, rods, and wires, <0.1 wt%) are readily formed in the presence of very low magnetic fields (<20 mT). The anisotropy of the nanoparticles is transduced to the polymer network, leading to macroscopic anisotropy, for instance, in mechanical properties. Electrostatic repulsion by the negatively charged nanoparticles induces an additional layer of order in the material, perpendicular to the magnetic field direction. The straightforward fabrication strategy allows for stepwise deposition of layers with different degrees or directions of anisotropy, which enables the formation of complex structures that are able to mimic some of the complex hierarchical architectures found in biology. It is anticipated that this approach of hydrogel alignment may serve as a guide for designing advanced biomaterials in tissue engineering.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

Targeting SOX10-deficient cells to reduce the dormant-invasive phenotype state in melanoma

Cellular plasticity contributes to intra-tumoral heterogeneity and phenotype switching, which enable adaptation to metastatic microenvironments and resistance to therapies. Mechanisms underlying tumor cell plasticity remain poorly understood. SOX10, a neural crest lineage transcription factor, is heterogeneously expressed in melanomas. Loss of SOX10 reduces proliferation, leads to invasive properties, including the expression of mesenchymal genes and extracellular matrix, and promotes tolerance to BRAF and/or MEK inhibitors. We identify the class of cellular inhibitor of apoptosis protein-1/2 (cIAP1/2) inhibitors as inducing cell death selectively in SOX10-deficient cells. Targeted therapy selects for SOX10 knockout cells underscoring their drug tolerant properties. Combining cIAP1/2 inhibitor with BRAF/MEK inhibitors delays the onset of acquired resistance in melanomas in vivo. These data suggest that SOX10 mediates phenotypic switching in cutaneous melanoma to produce a targeted inhibitor tolerant state that is likely a prelude to the acquisition of resistance. Furthermore, we provide a therapeutic strategy to selectively eliminate SOX10-deficient cells.

Tissue-reactive drugs enable materials-free local depots

Local, sustained drug delivery of potent therapeutics holds promise for the treatment of a myriad of localized diseases while eliminating systemic side effects. However, introduction of drug delivery depots such as viscous hydrogels or polymer-based implants is highly limited in stiff tissues such as desmoplastic tumors. Here, we present a method to create materials-free intratumoral drug depots through Tissue-Reactive Anchoring Pharmaceuticals (TRAPs). TRAPs diffuse into tissue and attach locally for sustained drug release. In TRAPs, potent drugs are modified with ECM-reactive groups and then locally injected to quickly react with accessible amines within the ECM, creating local drug depots. We demonstrate that locally injected TRAPs create dispersed, stable intratumoral depots deep within mouse and human pancreatic tumor tissues. TRAPs depots based on ECM-reactive paclitaxel (TRAP paclitaxel) had better solubility than free paclitaxel and enabled sustained in vitro and in vivo drug release. TRAP paclitaxel induced higher tumoral apoptosis and sustained better antitumor efficacy than the free drug. By providing continuous drug access to tumor cells, this material-free approach to sustained drug delivery of potent therapeutics has the potential in a wide variety of diseases where current injectable depots fall short.

Collagen Biomarkers Quantify Fibroblast Activity In Vitro and Predict Survival in Patients with Pancreatic Ductal Adenocarcinoma

The use of novel tools to understand tumour-fibrosis in pancreatic ductal adenocarcinoma (PDAC) and novel anti-fibrotic treatments are highly needed. We established a pseudo-3D in vitro model including humane pancreatic fibroblasts (PFs) and pancreatic cancer-associated fibroblasts (CAFs) in combination with clinical collagen biomarkers, as a translational anti-fibrotic drug screening tool. Furthermore, we investigated the prognostic potential of serum collagen biomarkers in 810 patients with PDAC. PFs and CAFs were cultured in Ficoll-media. Cells were treated w/wo TGF-ß1 and the anti-fibrotic compound ALK5i. Biomarkers measuring the formation of type III (PRO-C3) and VI (PRO-C6) collagens were measured by ELISA in supernatant at days 3, 6, 9, and 12. PRO-C3 and PRO-C6, and their association with overall survival (OS), were evaluated in serum with PDAC (n = 810). PRO-C3 and PRO-C6 were upregulated in CAFs compared to PFs (p < 0.0001.). TGF-ß1 increased PRO-C3 in both PFs and CAFs (p < 0.0001). The anti-fibrotic compound ALK5i inhibited both PRO-C3 and PRO-C6 (p < 0.0001). High serum levels of PRO-C3 and PRO-C6 in patients with PDAC were associated with short OS (PRO-C3: HR = 1.48, 95%CI: 1.29-1.71, p < 0.0001 and PRO-C6: HR = 1.31, 95%CI: 1.14-1.50, p = 0.0002). PRO-C3 and PRO-C6 have the potential to be used both pre-clinically and clinically as a measure of tumor fibrosis and CAF activity.

The Functional Role of Extracellular Matrix Proteins in Cancer

The extracellular matrix (ECM) is highly dynamic as it is constantly deposited, remodeled and degraded to maintain tissue homeostasis. ECM is a major structural component of the tumor microenvironment, and cancer development and progression require its extensive reorganization. Cancerized ECM is biochemically different in its composition and is stiffer compared to normal ECM. The abnormal ECM affects cancer progression by directly promoting cell proliferation, survival, migration and differentiation. The restructured extracellular matrix and its degradation fragments (matrikines) also modulate the signaling cascades mediated by the interaction with cell-surface receptors, deregulate the stromal cell behavior and lead to emergence of an oncogenic microenvironment. Here, we summarize the current state of understanding how the composition and structure of ECM changes during cancer progression. We also describe the functional role of key proteins, especially tenascin C and fibronectin, and signaling molecules involved in the formation of the tumor microenvironment, as well as the signaling pathways that they activate in cancer cells.

An integrated approach to investigate age-related modifications of morphological, mechanical and structural properties of type I collagen

The main propose of this study is to characterize the impact of chronological aging on mechanical, structural, biochemical, and morphological properties of type I collagen. We have developed an original approach combining a stress-strain measurement device with a portable Raman spectrometer to enable simultaneous measurement of Raman spectra during stress vs strain responses of young adult, adult and old rat tail tendon fascicles (RTTFs). Our data showed an increase in all mechanical properties such as Young's modulus, yield strength, and ultimate tensile strength with aging. At the molecular level, Raman data revealed that the most relevant frequency shift was observed at 938 cm^-1 in Old RTTFs, which is assigned to the C-C. This suggested a long axis deformation of the peptide chains in Old RTTFs during tensile stress. In addition, the intensity of the band at 872 cm^-1, corresponding to hydroxyproline decreased for young adult RTTFs and increased for the adult ones, while it remained unchanged for Old RTTFs during tensile stress. The amide III band (1242 and 1265 cm^-1) as well as the band ratios I₁₆₃₁/ I₁₆₆₃ and I₁₆₄₅ / I₁₆₆₃ responses to tensile stress were depending on mechanical phases (toe, elastic and plastic). The quantification of advanced glycation end-products by LC-MS/MS and spectrofluorometry showed an increase in their content with aging. This suggested that the accumulation of such products was correlated to the alterations observed in the mechanical and molecular properties of RTTFs. Analysis of the morphological properties of RTTFs by SHG combined with CT-FIRE software revealed an increase in length and straightness of collagen fibers, whereas their width and wavy fraction decreased. Our integrated study model could be useful to provide additional translational information to monitor progression of diseases related to collagen remodeling in musculoskeletal disorders. STATEMENT OF SIGNIFICANCE: Type I collagen is the major component of the extracellular matrix. Its architectural and structural organization plays an important role in the mechanical properties of many tissues at the physiological and pathological levels. The objective of this work is to develop an integrated approach to bring a new insight on the impact of chronological aging on the structural organization and mechanical properties of type I collagen. We combined a portable Raman spectrometer with a mechanical tensile testing device in order to monitor in real time the changes in the Raman fingerprint of type I collagen fibers during the mechanical stress. Raman spectroscopy allowed the identification of the type I collagen bonds that were affected by mechanical stress in a differential manner with aging.

Label-free 3D characterization of cardiac fibrosis in muscular dystrophy using SHG imaging of cleared tissue

BACKGROUND INFORMATION

Duchenne muscular dystrophy (DMD) is a neuromuscular disease caused by mutations in the gene encoding dystrophin. It leads to repeated cycles of muscle fiber necrosis and regeneration and progressive replacement of fibers by fibrotic and adipose tissue, with consequent muscle weakness and premature death. Fibrosis and, in particular, collagen accumulation are important pathological features of dystrophic muscle. A better understanding of the development of fibrosis is crucial to enable better management of DMD. Three-dimensional (3D) characterization of collagen organization by second harmonic generation (SHG) microscopy has already proven a highly informative means of studying the fibrotic network in tissue.

RESULTS

Here, we combine for the first-time tissue clearing with SHG microscopy to characterize in depth the 3D cardiac fibrosis network from DMD^mdx rat model. Heart sections (1-mm-thick) from 1-year-old wild-type (WT) and DMD^mdx rats were cleared using the CUBIC protocol. SHG microscopy revealed significantly greater collagen deposition in DMD^mdx versus WT sections. Analyses revealed a specific pattern of SHG⁺ segmented objects in DMD^mdx cardiac muscle, characterized by a less elongated shape and increased density. Compared with the observed alignment of SHG⁺ collagen fibers in WT rats, profound fiber disorganization was observed in DMD^mdx rats, in which we observed two distinct SHG⁺ collagen fiber profiles, which may reflect two distinct stages of the fibrotic process in DMD.

CONCLUSION AND SIGNIFICANCE

The current work highlights the interest to combine multiphoton SHG microscopy and tissue clearing for 3D fibrosis network characterization in label free organ. It could be a relevant tool to characterize the fibrotic tissue remodeling in relation to the disease progression and/or to evaluate the efficacy of therapeutic strategies in preclinical studies in DMD model or others fibrosis-related cardiomyopathies diseases. This article is protected by copyright. All rights reserved.

Immune Modulatory Properties of Collagen in Cancer

During tumor growth the extracellular matrix (ECM) undergoes dramatic remodeling. The normal ECM is degraded and substituted with a tumor-specific ECM, which is often of higher collagen density and increased stiffness. The structure and collagen density of the tumor-specific ECM has been associated with poor prognosis in several types of cancer. However, the reason for this association is still largely unknown. Collagen can promote cancer cell growth and migration, but recent studies have shown that collagens can also affect the function and phenotype of various types of tumor-infiltrating immune cells such as tumor-associated macrophages (TAMs) and T cells. This suggests that tumor-associated collagen could have important immune modulatory functions within the tumor microenvironment, affecting cancer progression as well as the efficacy of cancer immunotherapy. The effects of tumor-associated collagen on immune cells could help explain why a high collagen density in tumors is often correlated with a poor prognosis. Knowledge about immune modulatory functions of collagen could potentially identify targets for improving current cancer therapies or for development of new treatments. In this review, the current knowledge about the ability of collagen to influence T cell activity will be summarized. This includes direct interactions with T cells as well as induction of immune suppressive activity in other immune cells such as macrophages. Additionally, the potential effects of collagen on the efficacy of cancer immunotherapy will be discussed.

Tumor-Associated Extracellular Matrix: How to Be a Potential Aide to Anti-tumor Immunotherapy?

The development of cancer immunotherapy, particularly immune checkpoint blockade therapy, has made major breakthroughs in the therapy of cancers. However, less than one-third of the cancer patients obtain significant and long-lasting therapeutic effects by cancer immunotherapy. Over the past few decades, cancer-related inflammations have been gradually more familiar to us. It’s known that chronic inflammation in tumor microenvironment (TME) plays a predominant role in tumor immunosuppression. Tumor-associated extracellular matrix (ECM), as a core member of TME, has been a research hotspot recently. A growing number of studies indicate that tumor-associated ECM is one of the major obstacles to realizing more successful cases of cancer immunotherapy. In this review, we discussed the potential application of tumor-associated ECM in the cancer immunity and its aide potentialities to anti-tumor immunotherapy.

Multiphoton Microscopy for Identifying Collagen Signatures Associated with Biochemical Recurrence in Prostate Cancer Patients

Prostate cancer is a heterogeneous disease that remains dormant for long periods or acts aggressively with poor clinical outcomes. Identifying aggressive prostate tumor behavior using current glandular-focused histopathological criteria is challenging. Recent evidence has implicated the stroma in modulating prostate tumor behavior and in predicting post-surgical outcomes. However, the emergence of stromal signatures has been limited, due in part to the lack of adoption of imaging modalities for stromal-specific profiling. Herein, label-free multiphoton microscopy (MPM), with its ability to image tissue with stromal-specific contrast, is used to identify prostate stromal features associated with aggressive tumor behavior and clinical outcome. MPM was performed on unstained prostatectomy specimens from 59 patients and on biopsy specimens from 17 patients with known post-surgery recurrence status. MPM-identified collagen content, organization, and morphological tumor signatures were extracted for each patient and screened for association with recurrent disease. Compared to tumors from patients whose disease did not recur, tumors from patients with recurrent disease exhibited higher MPM-identified collagen amount and collagen fiber intensity signal and width. Our study shows an association between MPM-identified stromal collagen features of prostate tumors and post-surgical disease recurrence, suggesting their potential for prostate cancer risk assessment.

Pancreatic Cancer Microenvironment and Cellular Composition: Current Understandings and Therapeutic Approaches

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human solid tumors, despite great efforts in improving therapeutics over the past few decades. In PDAC, the distinct characteristic of the tumor microenvironment (TME) is the main barrier for developing effective treatments. PDAC TME is characterized by a dense stroma, cancer-associated fibroblasts, and immune cells populations that crosstalk to the subpopulations of neoplastic cells that include cancer stem cells (CSCs). The heterogeneity in TME is also exhibited in the diversity and dynamics of acellular components, including the Extracellular matrix (ECM), cytokines, growth factors, and secreted ligands to signaling pathways. These contribute to drug resistance, metastasis, and relapse in PDAC. However, clinical trials targeting TME components have often reported unexpected results and still have not benefited patients. The failures in those trials and various efforts to understand the PDAC biology demonstrate the highly heterogeneous and multi-faceted TME compositions and the complexity of their interplay within TME. Hence, further functional and mechanistic insight is needed. In this review, we will present a current understanding of PDAC biology with a focus on the heterogeneity in TME and crosstalk among its components. We also discuss clinical challenges and the arising therapeutic opportunities in PDAC research.

Real-time polarization microscopy of fibrillar collagen in histopathology

Over the past two decades, fibrillar collagen reorganization parameters such as the amount of collagen deposition, fiber angle and alignment have been widely explored in numerous studies. These parameters are now widely accepted as stromal biomarkers and linked to disease progression and survival time in several cancer types. Despite all these advances, there has not been a significant effort to make it possible for clinicians to explore these biomarkers without adding steps to the clinical workflow or by requiring high-cost imaging systems. In this paper, we evaluate previously described polychromatic polarization microscope (PPM) to visualize collagen fibers with an optically generated color representation of fiber orientation and alignment when inspecting the sample by a regular microscope with minor modifications. This system does not require stained slides, but is compatible with histological stains such as H&E. Consequently, it can be easily accommodated as part of regular pathology review of tissue slides, while providing clinically useful insight into stromal composition.

Bioengineered 3D models of human pancreatic cancer recapitulate in vivo tumour biology

Patient-derived in vivo models of human cancer have become a reality, yet their turnaround time is inadequate for clinical applications. Therefore, tailored ex vivo models that faithfully recapitulate in vivo tumour biology are urgently needed. These may especially benefit the management of pancreatic ductal adenocarcinoma (PDAC), where therapy failure has been ascribed to its high cancer stem cell (CSC) content and high density of stromal cells and extracellular matrix (ECM). To date, these features are only partially reproduced ex vivo using organoid and sphere cultures. We have now developed a more comprehensive and highly tuneable ex vivo model of PDAC based on the 3D co-assembly of peptide amphiphiles (PAs) with custom ECM components (PA-ECM). These cultures maintain patient-specific transcriptional profiles and exhibit CSC functionality, including strong in vivo tumourigenicity. User-defined modification of the system enables control over niche-dependent phenotypes such as epithelial-to-mesenchymal transition and matrix deposition. Indeed, proteomic analysis of these cultures reveals improved matrisome recapitulation compared to organoids. Most importantly, patient-specific in vivo drug responses are better reproduced in self-assembled cultures than in other models. These findings support the use of tuneable self-assembling platforms in cancer research and pave the way for future precision medicine approaches.

Whence CRIPTO: The Reemergence of an Oncofetal Factor in 'Wounds' That Fail to Heal

There exists a set of factors termed oncofetal proteins that play key roles in ontogeny before they decline or disappear as the organism's tissues achieve homeostasis, only to then re-emerge in cancer. Although the unique therapeutic potential presented by such factors has been recognized for more than a century, their clinical utility has yet to be fully realized1. This review highlights the small signaling protein CRIPTO encoded by the tumor derived growth factor 1 (TDGF1/Tdgf1) gene, an oft cited oncofetal protein whose presence in the cancer literature as a tumor promoter, diagnostic marker and viable therapeutic target continues to grow. We touch lightly on features well established and well-reviewed since its discovery more than 30 years ago, including CRIPTO's early developmental roles and modulation of SMAD2/3 activation by a selected set of transforming growth factor β (TGF-β) family ligands. We predominantly focus instead on more recent and less well understood additions to the CRIPTO signaling repertoire, on its potential upstream regulators and on new conceptual ground for understanding its mode of action in the multicellular and often stressful contexts of neoplastic transformation and progression. We ask whence it re-emerges in cancer and where it 'hides' between the time of its fetal activity and its oncogenic reemergence. In this regard, we examine CRIPTO's restriction to rare cells in the adult, its potential for paracrine crosstalk, and its emerging role in inflammation and tissue regeneration-roles it may reprise in tumorigenesis, acting on subsets of tumor cells to foster cancer initiation and progression. We also consider critical gaps in knowledge and resources that stand between the recent, exciting momentum in the CRIPTO field and highly actionable CRIPTO manipulation for cancer therapy and beyond.

TRAIL receptors are expressed in both malignant and stromal cells in pancreatic ductal adenocarcinoma

This study assesses the expression of all TNF-related apoptosis-inducing ligand (TRAIL) receptors in pancreatic ductal adenocarcinoma (PDAC) tumor tissue. We aimed to include TRAIL receptor expression as an inclusion parameter in a future clinical study using a TRAIL-based therapy approach for PDAC patients. Considering the emerging influence of PDAC desmoplastic stroma on the efficacy of anti-PDAC therapies, this analysis was extended to tumor stromal cells. Additionally, we performed PDAC stroma characterization. Our retrospective cohort study (N=50) included patients with histologically confirmed PDAC who underwent surgery. The expression of TRAIL receptors (DR4, DR5, DcR1, DcR2, and OPG) in tumor and stromal cells was evaluated by immunohistochemistry (IHC). The amount of tumor stroma was assessed by anti-vimentin IHC and Mallory's trichrome staining. The prognostic impact was determined by the univariate Cox proportional hazards regression model. An extensive expression of functional receptors DR4 and DR5 and a variable expression of decoy receptors were detected in PDAC tumor and stromal cells. Functional receptors were detected also in metastatic tumor and stromal cells. A poor prognosis was associated with low or absent expression of decoy receptors in tumor cells of primary PDAC. After assessing that almost 80% of tumor mass was composed of stroma, we correlated a cellular-dense stroma in primary PDAC with reduced relapse-free survival. We demonstrated that TRAIL functional receptors are widely expressed in PDAC, representing a promising target for TRAIL-based therapies. Further, we demonstrated that a low expression of DcR1 and the absence of OPG in tumor cells, as well as a cellular-dense tumor stroma, could negatively impact the prognosis of PDAC patients.

3D Cancer Models: Depicting Cellular Crosstalk within the Tumour Microenvironment

The tumour microenvironment plays a critical role in tumour progression and drug resistance processes. Non-malignant cell players, such as fibroblasts, endothelial cells, immune cells and others, interact with each other and with the tumour cells, shaping the disease. Though the role of each cell type and cell communication mechanisms have been progressively studied, the complexity of this cellular network and its role in disease mechanism and therapeutic response are still being unveiled. Animal models have been mainly used, as they can represent systemic interactions and conditions, though they face recognized limitations in translational potential due to interspecies differences. In vitro 3D cancer models can surpass these limitations, by incorporating human cells, including patient-derived ones, and allowing a range of experimental designs with precise control of each tumour microenvironment element. We summarize the role of each tumour microenvironment component and review studies proposing 3D co-culture strategies of tumour cells and non-malignant cell components. Moreover, we discuss the potential of these modelling approaches to uncover potential therapeutic targets in the tumour microenvironment and assess therapeutic efficacy, current bottlenecks and perspectives.

Going your own way: Self-guidance mechanisms in cell migration

How cells and tissues migrate from one location to another is a question of significant biological and medical relevance. Migration is generally thought to be controlled by external hardwired guidance cues, which cells follow by polarizing their internal locomotory machinery in the imposed direction. However, a number of recently discovered 'self-guidance' mechanisms have revealed that migrating cells have more control over the path they follow than previously thought. Here, directional information is generated by the migrating cells themselves via a dynamic interplay of cell-intrinsic and -extrinsic regulators. In this review, we discuss how self-guidance can emerge from mechanisms acting at different levels of scale and how these enable cells to rapidly adapt to environmental challenges.

Tumor collagen framework from bright-field histology images predicts overall survival of breast carcinoma patients

Within the tumor microenvironment, specifically aligned collagen has been shown to stimulate tumor progression by directing the migration of metastatic cells along its structural framework. Tumor-associated collagen signatures (TACS) have been linked to breast cancer patient outcome. Robust and affordable methods for assessing biological information contained in collagen architecture need to be developed. We have developed a novel artificial neural network (ANN) based approach for tumor collagen segmentation from bright-field histology images and have tested it on a set of tissue microarray sections from early hormone receptor-positive invasive ductal breast carcinoma stained with Sirius Red (1 core per patient, n = 92). We designed and trained ANNs on sets of differently annotated image patches to segment collagen fibers and extracted 37 features of collagen fiber morphometry, density, orientation, texture, and fractal characteristics in the entire cohort. Independent instances of ANN models trained on highly differing annotations produced reasonably concordant collagen segmentation masks and allowed reliable prognostic Cox regression models (with likelihood ratios 14.11-22.99, at p-value < 0.05) superior to conventional clinical parameters (size of the primary tumor (T), regional lymph node status (N), histological grade (G), and patient age). Additionally, we noted statistically significant differences of collagen features between tumor grade groups, and the factor analysis revealed features resembling the TACS concept. Our proposed method offers collagen framework segmentation from bright-field histology images and provides novel image-based features for better breast cancer patient prognostication.

Collagen Organization Does Not Influence T-Cell Distribution in Stroma of Human Pancreatic Cancer

Simple Summary

The excessive desmoplasia is the hallmark of human pancreatic cancer that influences the local T-cell-based immune response. In the present work, the stromal collagen organization in normal and malignant pancreatic tissues as well as its relationsship to T-cell distribution in pancreatic cancer were studied. It was found that differences in collagen organization do not change the spatial orientation of T-cell migration and do not influence the availability of tumor cells for T-cells. The results of the study do not support the concept of use of stroma collagen organization for improvement of spatial T-cell distribution in the tumor.

Abstract

The dominant intrastromal T-cell infiltration in pancreatic cancer is mainly caused by the contact guidance through the excessive desmoplastic reaction and could represent one of the obstacles to an effective immune response in this tumor type. This study analyzed the collagen organization in normal and malignant pancreatic tissues as well as its influence on T-cell distribution in pancreatic cancer. Human pancreatic tissue was analyzed using immunofluorescence staining and multiphoton and SHG microscopy supported by multistep image processing. The influence of collagen alignment on activated T-cells was studied using 3D matrices and time-lapse microscopy. It was found that the stroma of malignant and normal pancreatic tissues was characterized by complex individual organization. T-cells were heterogeneously distributed in pancreatic cancer and there was no relationship between T-cell distribution and collagen organization. There was a difference in the angular orientation of collagen alignment in the peritumoral and tumor-cell-distant stroma regions in the pancreatic ductal adenocarcinoma tissue, but there was no correlation in the T-cell densities between these regions. The grade of collagen alignment did not influence the directionality of T-cell migration in the 3D collagen matrix. It can be concluded that differences in collagen organization do not change the spatial orientation of T-cell migration or influence stromal T-cell distribution in human pancreatic cancer. The results of the present study do not support the rationale of remodeling of stroma collagen organization for improvement of T-cell–tumor cell contact in pancreatic ductal adenocarcinoma.

Collagenase-Expressing Salmonella Targets Major Collagens in Pancreatic Cancer Leading to Reductions in Immunosuppressive Subsets and Tumor Growth

Therapeutic resistance in pancreatic ductal adenocarcinoma (PDAC) can be attributed, in part, to a dense extracellular matrix containing excessive collagen deposition. Here, we describe a novel Salmonella typhimurium (ST) vector expressing the bacterial collagenase Streptomyces omiyaensis trypsin (SOT), a serine protease known to hydrolyze collagens I and IV, which are predominantly found in PDAC. Utilizing aggressive models of PDAC, we show that ST-SOT selectively degrades intratumoral collagen leading to decreases in immunosuppressive subsets, tumor proliferation and viability. Ultimately, we found that ST-SOT treatment significantly modifies the intratumoral immune landscape to generate a microenvironment that may be more conducive to immunotherapy.

Extracellular Matrices and Cancer-Associated Fibroblasts: Targets for Cancer Diagnosis and Therapy?

Solid cancer progression is dictated by neoplastic cell features and pro-tumoral crosstalks with their microenvironment. Stroma modifications, such as fibroblast activation into cancer-associated fibroblasts (CAFs) and extracellular matrix (ECM) remodeling, are now recognized as critical events for cancer progression and as potential therapeutic or diagnostic targets. The recent appreciation of the key, complex and multiple roles of the ECM in cancer and of the CAF diversity, has revolutionized the field and raised innovative but challenging questions. Here, we rapidly present CAF heterogeneity in link with their specific ECM remodeling features observed in cancer, before developing each of the impacts of such ECM modifications on tumor progression (survival, angiogenesis, pre-metastatic niche, chemoresistance, etc.), and on patient prognosis. Finally, based on preclinical studies and recent results obtained from clinical trials, we highlight key mechanisms or proteins that are, or may be, used as potential therapeutic or diagnostic targets, and we report and discuss benefits, disappointments, or even failures, of recently reported stroma-targeting strategies.

IL17A critically shapes the transcriptional program of fibroblasts in pancreatic cancer and switches on their protumorigenic functions

A hallmark of cancer, including pancreatic ductal adenocarcinoma (PDA), is a massive stromal and inflammatory reaction. Many efforts have been made to identify the anti- or protumoral role of cytokines and immune subpopulations within the stroma. Here, we investigated the role of interleukin-17A (IL17A) and its effect on tumor fibroblasts and the tumor microenvironment. We used a spontaneous PDA mouse model (KPC) crossed to IL17A knockout mice to show an extensive desmoplastic reaction, without impaired immune infiltration. Macrophages, especially CD80⁺ and T cells, were more abundant at the earlier time point. In T cells, a decrease in FoxP3⁺ cells and an increase in CD8⁺ T cells were observed in KPC/IL17A^-/- mice. Fibroblasts isolated from IL17A^+/+ and IL17A^-/- KPC mice revealed very different messenger RNA (mRNA) and protein profiles. IL17A^-/- fibroblasts displayed the ability to restrain tumor cell invasion by producing factors involved in extracellular matrix remodeling, increasing T cell recruitment, and producing higher levels of cytokines and chemokines favoring T helper 1 cell recruitment and activation and lower levels of those recruiting myeloid/granulocytic immune cells. Single-cell quantitative PCR on isolated fibroblasts confirmed a very divergent profile of IL17A-proficient and -deficient cells. All these features can be ascribed to increased levels of IL17F observed in the sera of IL17A^-/- mice, and to the higher expression of its cognate receptor (IL17RC) specifically in IL17A^-/- cancer-associated fibroblasts (CAFs). In addition to the known effects on neoplastic cell transformation, the IL17 cytokine family uniquely affects fibroblasts, representing a suitable candidate target for combinatorial immune-based therapies in PDA.

Pancreatic Ductal Adenocarcinoma: Relating Biomechanics and Prognosis

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer and carries a dismal prognosis. Resectable patients are treated predominantly with surgery while borderline resectable patients may receive neoadjuvant treatment (NAT) to downstage their disease prior to possible resection. PDAC tissue is stiffer than healthy pancreas, and tissue stiffness is associated with cancer progression. Another feature of PDAC is increased tissue heterogeneity. We postulate that tumour stiffness and heterogeneity may be used alongside currently employed diagnostics to better predict prognosis and response to treatment. In this review we summarise the biomechanical changes observed in PDAC, explore the factors behind these changes and describe the clinical consequences. We identify methods available for assessing PDAC biomechanics ex vivo and in vivo, outlining the relative merits of each. Finally, we discuss the potential use of radiological imaging for prognostic use.

Immune Cell Modulation of the Extracellular Matrix Contributes to the Pathogenesis of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a five-year survival rate of only 9%. PDAC is characterized by a dense, fibrotic stroma composed of extracellular matrix (ECM) proteins. This desmoplastic stroma is a hallmark of PDAC, representing a significant physical barrier that is immunosuppressive and obstructs penetration of cytotoxic chemotherapy agents into the tumor microenvironment (TME). Additionally, dense ECM promotes hypoxia, making tumor cells refractive to radiation therapy and alters their metabolism, thereby supporting proliferation and survival. In this review, we outline the significant contribution of fibrosis to the pathogenesis of pancreatic cancer, with a focus on the cross talk between immune cells and pancreatic stellate cells that contribute to ECM deposition. We emphasize the cellular mechanisms by which neutrophils and macrophages, specifically, modulate the ECM in favor of PDAC-progression. Furthermore, we investigate how activated stellate cells and ECM influence immune cells and promote immunosuppression in PDAC. Finally, we summarize therapeutic strategies that target the stroma and hinder immune cell promotion of fibrogenesis, which have unfortunately led to mixed results. An enhanced understanding of the complex interactions between the pancreatic tumor ECM and immune cells may uncover novel treatment strategies that are desperately needed for this devastating disease.

Multiscale anisotropy analysis of second-harmonic generation collagen imaging of mouse skin

SIGNIFICANCE

Morphological collagen signatures are important for tissue function, particularly in the tumor microenvironment. A single algorithmic framework with quantitative, multiscale morphological collagen feature extraction may further the use of collagen signatures in understanding fundamental tumor progression.

AIM

A modification of the 2D wavelet transform modulus maxima (WTMM) anisotropy method was applied to both digitally simulated collagen fibers and second-harmonic-generation imaged collagen fibers of mouse skin to calculate a multiscale anisotropy factor to detect collagen fiber organization.

APPROACH

The modified 2D WTMM anisotropy method was initially validated on synthetic calibration images to establish the robustness and sensitivity of the multiscale fiber organization tool. Upon validation, the algorithm was applied to collagen fiber organization in normal wild-type skin, melanoma stimulated skin, and integrin α10KO skin.

RESULTS

Normal wild-type skin collagen fibers have an increased anisotropy factor at all sizes scales. Interestingly, the multiscale anisotropy differences highlight important dissimilarities between collagen fiber organization in normal wild-type skin, melanoma stimulated, and integrin α10KO skin. At small scales (∼2 to 3  μm), the integrin α10KO skin was vastly different than normal skin (p-value  ∼  10  -  8), whereas the melanoma stimulated skin was vastly different than normal at large scales (∼30 to 40  μm, p-value  ∼  10  -  15).

CONCLUSIONS

This objective computational collagen fiber organization algorithm is sensitive to collagen fiber organization across multiple scales for effective exploration of collagen morphological alterations associated with melanoma and the lack of α10 integrin binding.

Tumor extracellular matrix: lessons from the second-harmonic generation microscopy

Extracellular matrix (ECM) represents more than a mere intercellular cement. It is physiologically active in cell communication, adhesion and proliferation. Collagen is the most abundant protein, making up to 90% of ECM, and 30% of total protein weight in humans. Second-harmonic generation (SHG) microscopy represents an important tool to study collagen organization of ECM in freshly unfixed tissues and paraffin-embedded tissue samples. This manuscript aims to review some of the applications of SHG microscopy in Oncologic Pathology, mainly in the study of ECM of epithelial tumors. It is shown how collagen parameters measured by this technique can aid in the differential diagnosis and in prognostic stratification. There is a tendency to associate higher amount, lower organization and higher linearity of collagen fibers with tumor progression and metastasizing. These represent complex processes, in which matrix remodeling plays a central role, together with cancer cell genetic modifications. Integration of studies on cancer cell biology and ECM are highly advantageous to give us a more complete picture of these processes. As microscopic techniques provide topographic information allied with biologic characteristics of tissue components, they represent important tools for a more complete understanding of cancer progression. In this context, SHG has provided significant insights in human tumor specimens, readily available for Pathologists.

Exosomal integrins and their influence on pancreatic cancer progression and metastasis

As one of the most lethal and untreatable types of cancer so far, pancreatic cancer is not benefitting from advancements in research. Despite all the efforts, this malignancy is still very difficult to diagnose in time, resistant to treatments, and prone to relapses. The appearance of metastasis-notoriously difficult to fight and a signal of unfortunate prognosis-is the event most dreaded by every cancer patient, especially by those with pancreatic cancer. Strategies for early detection and treatment of metastases are limited, and new action plans are desperately awaited. Recently, the importance of cell-secreted vesicles, or exosomes, in cell-cell communication and, particularly, their key role in promoting pathological conditions, such as infectious diseases and cancer, have attracted the attention of the scientific community. The discovery of some exosome membrane components, such as adhesion receptors and integrins, and their ability to influence cancer cell functions and metastasis progression, has added some important understanding of the metastatic process and will hopefully open the door to the development of new tools for identifying and targeting metastases. The aim of this review is to discuss the role played by integrins in exosomal-mediated pancreatic cancer progression and metastasis.

A FIJI macro for quantifying pattern in extracellular matrix

Diverse extracellular matrix patterns are observed in both normal and pathological tissue. However, most current tools for quantitative analysis focus on a single aspect of matrix patterning. Thus, an automated pipeline that simultaneously quantifies a broad range of metrics and enables a comprehensive description of varied matrix patterns is needed. To this end, we have developed an ImageJ plugin called TWOMBLI, which stands for The Workflow Of Matrix BioLogy Informatics. This pipeline includes metrics of matrix alignment, length, branching, end points, gaps, fractal dimension, curvature, and the distribution of fibre thickness. TWOMBLI is designed to be quick, versatile and easy-to-use particularly for non-computational scientists. TWOMBLI can be downloaded from https://github.com/wershofe/TWOMBLI together with detailed documentation and tutorial video. Although developed with the extracellular matrix in mind, TWOMBLI is versatile and can be applied to vascular and cytoskeletal networks. Here we present an overview of the pipeline together with examples from a wide range of contexts where matrix patterns are generated.

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.

Palladin isoforms 3 and 4 regulate cancer-associated fibroblast pro-tumor functions in pancreatic ductal adenocarcinoma

Pancreatic Ductal Adenocarcinoma (PDAC) has a five-year survival under 10%. Treatment is compromised due to a fibrotic-like stromal remodeling process, known as desmoplasia, which limits therapeutic perfusion, supports tumor progression, and establishes an immunosuppressive microenvironment. These processes are driven by cancer-associated fibroblasts (CAFs), functionally activated through transforming growth factor beta1 (TGFβ1). CAFs produce a topographically aligned extracellular matrix (ECM) that correlates with reduced overall survival. Paradoxically, ablation of CAF populations results in a more aggressive disease, suggesting CAFs can also restrain PDAC progression. Thus, unraveling the mechanism(s) underlying CAF functions could lead to therapies that reinstate the tumor-suppressive features of the pancreatic stroma. CAF activation involves the f-actin organizing protein palladin. CAFs express two palladin isoforms (iso3 and iso4) which are up-regulated in response to TGFβ1. However, the roles of iso3 and iso4 in CAF functions remain elusive. Using a CAF-derived ECM model, we uncovered that iso3/iso4 are required to sustain TGFβ1-dependent CAF activation, secrete immunosuppressive cytokines, and produce a pro-tumoral ECM. Findings demonstrate a novel role for CAF palladin and suggest that iso3/iso4 regulate both redundant and specific tumor-supportive desmoplastic functions. This study highlights the therapeutic potential of targeting CAFs to restore fibroblastic anti-tumor activity in the pancreatic microenvironment.

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.

Large-scale tumor-associated collagen signatures identify high-risk breast cancer patients

The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort (n= 431) and an internal validation cohort (n = 300) collected from one clinical center, and in an external validation cohort (n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.

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.

Engineering of biomaterials for tumor modeling

Development of biomaterials mimicking tumor and its microenvironment has recently emerged for the use of drug discovery, precision medicine, and cancer biology. These biomimetic models have developed by reconstituting tumor and stroma cells within the 3D extracellular matrix. The models are recently extended to recapitulate the in vivo tumor microenvironment, including biological, chemical, and mechanical conditions tailored for specific cancer type and its microenvironment. In spite of the recent emergence of various innovative engineered tumor models, many of these models are still early stage to be adapted for cancer research. In this article, we review the current status of biomaterials engineering for tumor models considering three main aspects - cellular engineering, matrix engineering, and engineering for microenvironmental conditions. Considering cancer-specific variability in these aspects, our discussion is focused on pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC). In addition, we further discussed the current challenges and future opportunities to create reliable and relevant tumor models.

Neoplastic-Stromal Cell Cross-talk Regulates Matrisome Expression in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a highly desmoplastic reaction, warranting intense cancer-stroma communication. In this study, we interrogated the contribution of the BET family of chromatin adaptors to the cross-talk between PDAC cells and the tumor stroma. Short-term treatment of orthotopic xenograft tumors with CPI203, a small-molecule inhibitor of BET proteins, resulted in broad changes in the expression of genes encoding components of the extracellular matrix (matrisome) in both cancer and stromal cells. Remarkably, more than half of matrisome genes were expressed by cancer cells. In vitro cocultures of PDAC cells and cancer-associated fibroblasts (CAF) demonstrated that matrisome expression was regulated by BET-dependent cancer-CAF cross-talk. Disrupting this cross-talk in vivo resulted in diminished growth of orthotopic patient-derived xenograft tumors, reduced proliferation of cancer cells, and changes in collagen structure consistent with that of patients who experienced better survival. Examination of matrisome gene expression in publicly available data sets of 573 PDAC tumors identified a 65-gene signature that was able to distinguish long- and short-term PDAC survivors. Importantly, the expression of genes predictive of short-term survival was diminished in the cancer cells of orthotopic xenograft tumors of mice treated with CPI203. Taken together, these results demonstrate that inhibiting the activity BET proteins results in transcriptional and structural differences in the matrisome are associated with better patient survival. IMPLICATIONS: These studies highlight the biological relevance of the matrisome program in PDAC and suggest targeting of epigenetically driven tumor-stroma cross-talk as a potential therapeutic avenue.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.

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.

Prognostic value of tumor stromal collagen features in patients with hepatocellular carcinoma revealed by second-harmonic generation microscopy

INTRODUCTION

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide. The search for new biomarkers that predict the outcome of HCC patients is ongoing. We propose the second harmonic generation-based quantitative assessment approach to evaluate the prognostic value of tumor stromal collagen in HCC.

MATERIALS AND METHODS

We evaluated tumor stromal collagen in paraffin-embedded specimens from 109 HCC patients by second-harmonic generation imaging. The parameters and quantitative assessment of collagen were obtained using a fiber network extraction algorithm. The relationships between collagen features and clinical pathological features and overall survival were statistically analyzed.

RESULT

Among the collagen features, some parameters of aggregated collagen correlated well with clinical pathological features, especially the aggregated collagen cross-linked density. Cross-linked collagen fibers form a fiber network in moderately and poor differentiated HCCs. Kaplan-Meier analyses and the multivariate Cox proportional hazard model showed that high aggregated collagen cross-linked density was associated with poor overall survival. The chi-squared test showed that aggregated cross-link density was significantly associated with histological grade and tumor recurrence.

CONCLUSION

Our results indicate the prognostic value of the quantitative evaluation of tumor stromal collagen using second harmonic generation imaging of patients with HCC.

Collagen Density Modulates the Immunosuppressive Functions of Macrophages

Tumor-associated macrophages (TAMs) support tumor growth by suppressing the activity of tumor-infiltrating T cells. Consistently, TAMs are considered a major limitation for the efficacy of cancer immunotherapy. However, the molecular reason behind the acquisition of an immunosuppressive TAM phenotype is not fully clarified. During tumor growth, the extracellular matrix (ECM) is degraded and substituted with a tumor-specific collagen-rich ECM. The collagen density of this tumor ECM has been associated with poor patient prognosis but the reason for this is not well understood. In this study, we investigated whether the collagen density could modulate the immunosuppressive activity of TAMs. The murine macrophage cell line RAW 264.7 was three-dimensionally cultured in collagen matrices of low and high collagen densities mimicking healthy and tumor tissue, respectively. Collagen density did not affect proliferation or viability of the macrophages. However, whole-transcriptome analysis revealed a striking response to the surrounding collagen density, including the regulation of immune regulatory genes and genes encoding chemokines. These transcriptional changes were shown to be similar in murine bone marrow-derived macrophages and TAMs isolated from murine tumors. Strikingly, coculture assays with primary T cells showed that macrophages cultured in high-density collagen were less efficient at attracting cytotoxic T cells and capable of inhibiting T cell proliferation more than macrophages cultured in low-density collagen. Our study demonstrates that a high collagen density can instruct macrophages to acquire an immunosuppressive phenotype. This mechanism could reduce the efficacy of immunotherapy and explain the link between high collagen density and poor prognosis.

Alignment of stroma fibers, microvessel density and immune cell populations determine overall survival in pancreatic cancer-An analysis of stromal morphology

Introduction

The aim of this study was to define histo-morphological stroma characteristics by analyzing stromal components, and to evaluate their impact on local and systemic tumor spread and overall survival in pancreatic ductal adenocarcinoma (PDAC).

Methods and materials

Patients who underwent oncologic resections with curative intent for PDAC were identified from a prospectively maintained database. Histological specimens were re-evaluated for morphological stroma features as stromal fibers, fibroblast morphology, stroma matrix density, microvessel density and distribution of immune cell populations.

Results

A total of 108 patients were identified undergoing curative resection for PDAC in the period from 2011–2016. 33 (30.6%) patients showed parallel alignment of stroma fibers while 75 (69.4%) had randomly oriented stroma fibers. As compared to parallel alignment, random orientation of stroma fibers was associated with larger tumor size (median 3.62 cm vs. median 2.87cm, p = 0.037), nodal positive disease (76.0% vs. 54.5%, p = 0.040), higher margin positive resection rates (41.9% vs. 15.2%, p = 0.008) and a trend for higher rates of T3/4 tumors (33.3% vs. 15.2%, p = 0.064). In univariate analysis, patients with parallel alignment of stroma fibers had improved overall survival rates as compared to patients with random orientation of stroma fibers (42 months vs. 22 months, p = 0.046). The combination of random orientation of stroma fibers and low microvessel density was associated with impaired overall survival rates (16 months vs. 36 months, p = 0.019). A high CD4/CD3 ratio (16 months vs. 33 months, p = 0.040) and high stromal density of CD163 positive cells were associated with reduced overall survival (27 months vs. 34 months, p = 0.039). In multivariable analysis, the combination of random orientation of stroma fibers and low microvessel density (HR 1.592, 95%CI 1.098–2.733, p = 0.029), high CD4/CD3 ratio (HR 2.044, 95%CI 1.203–3.508, p = 0.028) and high density of CD163 positive cells (HR 1.596, 95%CI 1.367–1.968, p = 0.036) remained independent prognostic factors.

Conclusion

Alignment of stroma fibers and microvessel density are simple histomorphological features serving as surrogate markers of local tumor progression dissemination and surgical resectability and determine prognosis in PDAC patients. High CD4/CD3 ratio and CD163 positive cell counts determine poor prognosis.

The Physical Microenvironment of Tumors: Characterization and Clinical Impact

The tumor microenvironment plays a critical role in tumorigenesis and metastasis. As tightly controlled extracellular matrix homeostasis is lost during tumor progression, a dysregulated extracellular matrix can significantly alter cellular phenotype and drive malignancy. Altered physical properties of the tumor microenvironment alter cancer cell behavior, limit delivery and efficacy of therapies, and correlate with tumorigenesis and patient prognosis. The physical features of the extracellular matrix during tumor progression have been characterized; however, a wide range of methods have been used between studies and cancer types resulting in a large range of reported values. Here, we discuss the significant mechanical and structural properties of the tumor microenvironment, summarizing their reported values and clinical impact across cancer type and grade. We attempt to integrate the values in the literature to identify sources of reported differences and commonalities to better understand how aberrant extracellular matrix dynamics contribute to cancer progression. An intimate understanding of altered matrix properties during malignant transformation will be crucial in effectively detecting, monitoring, and treating cancer.