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

Hematoxylin and Eosin Architecture Uncovers Clinically Divergent Niches in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) represents one of the only cancers with an increasing incidence rate and is often associated with intra- and peri-tumoral scarring, referred to as desmoplasia. This scarring is highly heterogeneous in extracellular matrix (ECM) architecture and plays complex roles in both tumor biology and clinical outcomes that are not yet fully understood. Using hematoxylin and eosin (H&E), a routine histological stain utilized in existing clinical workflows, we quantified ECM architecture in 85 patient samples to assess relationships between desmoplastic architecture and clinical outcomes such as survival time and disease recurrence. By utilizing unsupervised machine learning to summarize a latent space across 147 local (e.g., fiber length, solidity) and global (e.g., fiber branching, porosity) H&E-based features, we identified a continuum of histological architectures that were associated with differences in both survival and recurrence. Furthermore, we mapped H&E architectures to a CO-Detection by indEXing (CODEX) reference atlas, revealing localized cell- and protein-based niches associated with outcome-positive versus outcome-negative scarring in the tumor microenvironment. Overall, our study utilizes standard H&E staining to uncover clinically relevant associations between desmoplastic organization and PDAC outcomes, offering a translatable pipeline to support prognostic decision-making and a blueprint of spatial-biological factors for modeling by tissue engineering methods.

Thickness-Resolved Electrochemiluminescence Microscopy of Extracellular Matrix at Tumor Tissues for Rapid Cancer Diagnosis

The traditional recognition of extracellular matrix (ECM) at tissue sections relies on the time-consuming immunofluorescence that could not meet the demand of rapid diagnosis. Herein, we introduce a thickness-resolved electrochemiluminescence (ECL) microscopy to image thin-layer ECM at tissue sections for fast histopathological analysis. The unique surface-confined ECL mechanism enables to unveil the diversity and complexity of multiple tissue structures with varying thicknesses. Notably, the short lifetimes and the limited diffusion of electrogenerated coreactant radicals combined with their chemical reactivity result in a 2-fold increase in ECL intensity on ECM structures compared to the remaining tissue, enabling ECM visualization without specific labeling. The further quantitation of the ECM localization within tissue sections furnishes crucial insights into tumor progression and, more importantly, differentiates carcinoma and paracancerous tissues from patients in less than 30 min. Moreover, the reported electrochemistry-based microscopy is a dynamic approach allowing to investigate the transport, tortuosity, and trafficking properties through the tissues. This thickness-resolved recognition strategy not only opens new avenues for imaging complex samples but also holds promise for expediting tissue pathologic diagnosis, offering a more automated protocol with enhanced quantitative data compared to current intraoperative pathology methods.

Mechanoimmunology in the solid tumor microenvironment

The tumor microenvironment (TME) is a complex and dynamic ecosystem that adjoins the cancer cells within solid tumors and comprises distinct components such as extracellular matrix, stromal and immune cells, blood vessels, and an abundance of signaling molecules. In recent years, the mechanical properties of the TME have emerged as critical determinants of tumor progression and therapeutic response. Aberrant mechanical cues, including altered tissue architecture and stiffness, contribute to tumor progression, metastasis, and resistance to treatment. Moreover, burgeoning immunotherapies hold great promise for harnessing the immune system to target and eliminate solid malignancies; however, their success is hindered by the hostile mechanical landscape of the TME, which can impede immune cell infiltration, function, and persistence. Consequently, understanding TME mechanoimmunology - the interplay between mechanical forces and immune cell behavior - is essential for developing effective solid cancer therapies. Here, we review the role of TME mechanics in tumor immunology, focusing on recent therapeutic interventions aimed at modulating the mechanical properties of the TME to potentiate T cell immunotherapies, and innovative assays tailored to evaluate their clinical efficacy.

Biophysical perspectives to understanding cancer-associated fibroblasts

The understanding of cancer has evolved significantly, with the tumor microenvironment (TME) now recognized as a critical factor influencing the onset and progression of the disease. This broader perspective challenges the traditional view that cancer is primarily caused by mutations, instead emphasizing the dynamic interaction between different cell types and physicochemical factors within the TME. Among these factors, cancer-associated fibroblasts (CAFs) command attention for their profound influence on tumor behavior and patient prognoses. Despite their recognized importance, the biophysical and mechanical interactions of CAFs within the TME remain elusive. This review examines the distinctive physical characteristics of CAFs, their morphological attributes, and mechanical interactions within the TME. We discuss the impact of mechanotransduction on CAF function and highlight how these cells communicate mechanically with neighboring cancer cells, thereby shaping the path of tumor development and progression. By concentrating on the biomechanical regulation of CAFs, this review aims to deepen our understanding of their role in the TME and to illuminate new biomechanical-based therapeutic strategies.

Deposition of collagen III and alterations in basement membrane integrity as candidate prognostic markers in prostate cancer

The extracellular matrix surrounding the tumor undergoes changes in its organization during the metastasis process. The present study aims to quantify total collagen, collagen I (Col I) and collagen III (Col III), analyze the alignment of collagen fibers and assess the basement membrane integrity in samples from patients with metastatic and non-metastatic prostate cancer. Tissue samples from 60 patients were classified into groups based on prognostic parameters: better prognosis (n = 20), worse prognosis without metastasis (n = 23) and metastatic (n = 17). Picrosirius red with further analysis under polarizing microscope was used to quantify (with validation using immunohistochemistry) and analyze collagen alignment, and Periodic Acid Schiff staining was used to analyze the basement membrane integrity. The Col I/Col III ratio was found to be higher in the metastatic group than in the groups with better prognosis (p = 0.012) and worse prognosis without metastasis (p = 0.018). Basement membrane integrity constitution in malignant tumor tissue differed from that of adjacent non-tumor tissue (p < 0.001). Moreover, the worsening in the tumor tissue integrity was positively correlated with worse prognostic parameters. All in all, absence of Col III and basement membrane integrity might be indicators of poor prognosis in prostate cancer.

Prognostic significance of collagen signatures in pancreatic ductal adenocarcinoma obtained from second-harmonic generation imaging

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) ranks among the deadliest types of cancer, and it will be meaningful to search for new biomarkers with prognostic value to help clinicians tailor therapeutic strategies.

METHODS

Here we tried to use an advanced optical imaging technique, multiphoton microscopy (MPM) combining second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) imaging, for the label-free detection of PDAC tissues from a cohort of 149 patients. An automated image processing method was used to extract collagen features from SHG images and the Kaplan-Meier survival analysis and Cox proportional hazards regression were used to assess the prognostic value of collagen signatures.

RESULTS

SHG images clearly show the different characteristics of collagen fibers in tumor microenvironment. We gained eight collagen morphological features, and a Feature-score was derived for each patient by the combination of these features using ridge regression. Statistical analyses reveal that Feature-score is an independent factor, and can predict the overall survival of PDAC patients as well as provide well risk stratification.

CONCLUSIONS

SHG imaging technique can potentially be a tool for the accurate diagnosis of PDAC, and this optical biomarker (Feature-score) may help clinicians make more approximate treatment decisions.

Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues

Significance

Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagen's architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues.

Aim

To demonstrate a multimodal approach where a morphology-specific contrast mechanism guides a mid-infrared spectral imaging method to detect fibrillar collagen based on its chemical signatures.

Approach

We trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The remaining 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment.

Results

Compared to the SHG ground truth, the generated MIRSI collagen images achieved a high average boundary F-score (0.8 at 4 pixels threshold) in the collagen distribution, high correlation (Pearson's R 0.82) in the collagen orientation, and similarly high correlation (Pearson's R 0.66) in the collagen alignment.

Conclusions

We showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

Netrin G1 Ligand is a new stromal immunomodulator that promotes pancreatic cancer

Understanding pancreatic cancer biology is fundamental for identifying new targets and for developing more effective therapies. In particular, the contribution of the stromal microenvironment to pancreatic cancer tumorigenesis requires further exploration. Here, we report the stromal roles of the synaptic protein Netrin G1 Ligand (NGL-1) in pancreatic cancer, uncovering its pro-tumor functions in cancer-associated fibroblasts and in immune cells. We observed that the stromal expression of NGL-1 inversely correlated with patients' overall survival. Moreover, germline knockout (KO) mice for NGL-1 presented decreased tumor burden, with a microenvironment that is less supportive of tumor growth. Of note, tumors from NGL-1 KO mice produced less immunosuppressive cytokines and displayed an increased percentage of CD8 + T cells than those from control mice, while preserving the physical structure of the tumor microenvironment. These effects were shown to be mediated by NGL-1 in both immune cells and in the local stroma, in a TGF-β-dependent manner. While myeloid cells lacking NGL-1 decreased the production of immunosuppressive cytokines, NGL-1 KO T cells showed increased proliferation rates and overall polyfunctionality compared to control T cells. CAFs lacking NGL-1 were less immunosuppressive than controls, with overall decreased production of pro-tumor cytokines and compromised ability to inhibit CD8 + T cells activation. Mechanistically, these CAFs downregulated components of the TGF-β pathway, AP-1 and NFAT transcription factor families, resulting in a less tumor-supportive phenotype. Finally, targeting NGL-1 genetically or using a functionally antagonistic small peptide phenocopied the effects of chemotherapy, while modulating the immunosuppressive tumor microenvironment (TME), rather than eliminating it. We propose NGL-1 as a new local stroma and immunomodulatory molecule, with pro-tumor roles in pancreatic cancer.

Statement of Significance

Here we uncovered the pro-tumor roles of the synaptic protein NGL-1 in the tumor microenvironment of pancreatic cancer, defining a new target that simultaneously modulates tumor cell, fibroblast, and immune cell functions. This study reports a new pathway where NGL-1 controls TGF-β, AP-1 transcription factor members and NFAT1, modulating the immunosuppressive microenvironment in pancreatic cancer. Our findings highlight NGL-1 as a new stromal immunomodulator in pancreatic cancer.

Small Extracellular Vesicles Promote Stiffness-mediated Metastasis

Tissue stiffness is a critical prognostic factor in breast cancer and is associated with metastatic progression. Here we show an alternative and complementary hypothesis of tumor progression whereby physiologic matrix stiffness affects the quantity and protein cargo of small extracellular vesicles (EV) produced by cancer cells, which in turn aid cancer cell dissemination. Primary patient breast tissue released by cancer cells on matrices that model human breast tumors (25 kPa; stiff EVs) feature increased adhesion molecule presentation (ITGα2β1, ITGα6β4, ITGα6β1, CD44) compared with EVs from softer normal tissue (0.5 kPa; soft EVs), which facilitates their binding to extracellular matrix proteins including collagen IV, and a 3-fold increase in homing ability to distant organs in mice. In a zebrafish xenograft model, stiff EVs aid cancer cell dissemination. Moreover, normal, resident lung fibroblasts treated with stiff and soft EVs change their gene expression profiles to adopt a cancer-associated fibroblast phenotype. These findings show that EV quantity, cargo, and function depend heavily on the mechanical properties of the extracellular microenvironment.

SIGNIFICANCE

Here we show that the quantity, cargo, and function of breast cancer-derived EVs vary with mechanical properties of the extracellular microenvironment.

Pirfenidone alleviates fibrosis by acting on tumour-stroma interplay in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with a 5-year survival rate of 12%. The abundant mesenchyme is partly responsible for the malignancy. The antifibrotic therapies have gained attention in recent research. However, the role of pirfenidone, an FDA-approved drug for idiopathic pulmonary fibrosis, remains unclear in PDAC.

METHODS

Data from RNA-seq of patient-derived xenograft (PDX) models treated with pirfenidone were integrated using bioinformatics tools to identify the target of cell types and genes. Using confocal microscopy, qRT-PCR and western blotting, we validated the signalling pathway in tumour cells to regulate the cytokine secretion. Further cocultured system demonstrated the interplay to regulate stroma fibrosis. Finally, mouse models demonstrated the potential of pirfenidone in PDAC.

RESULTS

Pirfenidone can remodulate multiple biological pathways, and exerts an antifibrotic effect through inhibiting the secretion of PDGF-bb from tumour cells by downregulating the TGM2/NF-kB/PDGFB pathway. Thus, leading to a subsequent reduction in collagen X and fibronectin secreted by CAFs. Moreover, the mice orthotopic pancreatic tumour models demonstrated the antifibrotic effect and potential to sensitise gemcitabine.

CONCLUSIONS

Pirfenidone may alter the pancreatic milieu and alleviate fibrosis through the regulation of tumour-stroma interactions via the TGM2/NF-kB/PDGFB signalling pathway, suggesting potential therapeutic benefits in PDAC management.

Tumor Stroma as a Therapeutic Target for Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis owing to its desmoplastic stroma. Therefore, therapeutic strategies targeting this tumor stroma should be developed. In this study, we describe the heterogeneity of cancer-associated fibroblasts (CAFs) and their diverse roles in the progression, immune evasion, and resistance to treatment of PDAC. We subclassified the spatial distribution and functional activity of CAFs to highlight their effects on prognosis and drug delivery. Extracellular matrix components such as collagen and hyaluronan are described for their roles in tumor behavior and treatment outcomes, implying their potential as therapeutic targets. We also discussed the roles of extracellular matrix (ECM) including matrix metalloproteinases and tissue inhibitors in PDAC progression. Finally, we explored the role of the adaptive and innate immune systems in shaping the PDAC microenvironment and potential therapeutic strategies, with a focus on immune cell subsets, cytokines, and immunosuppressive mechanisms. These insights provide a comprehensive understanding of PDAC and pave the way for the development of prognostic markers and therapeutic interventions.

A Perspective Review: Analyzing Collagen Alterations in Ovarian Cancer by High-Resolution Optical Microscopy

High-grade serous ovarian cancer (HGSOC) is the predominant subtype of ovarian cancer (OC), occurring in more than 80% of patients diagnosed with this malignancy. Histological and genetic analysis have confirmed the secretory epithelial of the fallopian tube (FT) as a major site of origin of HGSOC. Although there have been significant strides in our understanding of this disease, early stage detection and diagnosis are still rare. Current clinical imaging modalities lack the ability to detect early stage pathogenesis in the fallopian tubes and the ovaries. However, there are several microscopic imaging techniques used to analyze the structural modifications in the extracellular matrix (ECM) protein collagen in ex vivo FT and ovarian tissues that potentially can be modified to fit the clinical setting. In this perspective, we evaluate and compare the myriad of optical tools available to visualize these alterations and the invaluable insights these data provide on HGSOC initiation. We also discuss the clinical implications of these findings and how these data may help novel tools for early diagnosis of HGSOC.

Small extracellular vesicles promote stiffness-mediated metastasis

Tissue stiffness is a critical prognostic factor in breast cancer and is associated with metastatic progression. Here we show an alternative and complementary hypothesis of tumor progression whereby physiological matrix stiffness affects the quantity and protein cargo of small EVs produced by cancer cells, which in turn drive their metastasis. Primary patient breast tissue produces significantly more EVs from stiff tumor tissue than soft tumor adjacent tissue. EVs released by cancer cells on matrices that model human breast tumors (25 kPa; stiff EVs) feature increased adhesion molecule presentation (ITGα 2 β 1 , ITGα 6 β 4 , ITGα 6 β 1 , CD44) compared to EVs from softer normal tissue (0.5 kPa; soft EVs), which facilitates their binding to extracellular matrix (ECM) protein collagen IV, and a 3-fold increase in homing ability to distant organs in mice. In a zebrafish xenograft model, stiff EVs aid cancer cell dissemination through enhanced chemotaxis. Moreover, normal, resident lung fibroblasts treated with stiff and soft EVs change their gene expression profiles to adopt a cancer associated fibroblast (CAF) phenotype. These findings show that EV quantity, cargo, and function depend heavily on the mechanical properties of the extracellular microenvironment.

Microengineering 3D Collagen Matrices with Tumor-Mimetic Gradients in Fiber Alignment

Collagen fibers in the 3D tumor microenvironment (TME) exhibit complex alignment landscapes that are critical in directing cell migration through a process called contact guidance. Previous in vitro work studying this phenomenon has focused on quantifying cell responses in uniformly aligned environments. However, the TME also features short-range gradients in fiber alignment that result from cell-induced traction forces. Although the influence of graded biophysical taxis cues is well established, cell responses to physiological alignment gradients remain largely unexplored. In this work, fiber alignment gradients in biopsy samples are characterized and recreated using a new microfluidic biofabrication technique to achieve tunable sub-millimeter to millimeter scale gradients. This study represents the first successful engineering of continuous alignment gradients in soft, natural biomaterials. Migration experiments on graded alignment show that HUVECs exhibit increased directionality, persistence, and speed compared to uniform and unaligned fiber architectures. Similarly, patterned MDA-MB-231 aggregates exhibit biased migration toward increasing fiber alignment, suggesting a role for alignment gradients as a taxis cue. This user-friendly approach, requiring no specialized equipment, is anticipated to offer new insights into the biophysical cues that cells interpret as they traverse the extracellular matrix, with broad applicability in healthy and diseased tissue environments.

Distribution of smooth muscle actin and collagen in superficial peritoneal endometriotic lesions varies from the surrounding microenvironment

RESEARCH QUESTION

Do different subtypes of superficial peritoneal endometriotic lesions exist, based on the presence and morphology of smooth muscle, collagen fibres and immune cell populations?

DESIGN

A retrospective cohort study of 24 patients, from across the menstrual cycle, with surgically and histologically confirmed endometriosis. Immunofluorescence was used to delineate the CD10 stromal area of lesions (n = 271 lesions from 67 endometriotic biopsies), and then smooth muscle actin (SMA) positive tissue and immune cell populations (CD45+ and CD68+) were quantified within and adjacent to these lesions. Second harmonic generation microscopy was used to evaluate the presence and morphology of type-1 collagen fibres within and surrounding lesions.

RESULTS

Overall, immune cell numbers and the area of SMA and collagen within endometriotic lesions tended to be low, but a spectrum of presentations significantly varied, particularly in the adjacent tissue microenvironment, based on lesion locations, the morphology of endometriotic gland profiles, or both. Lesions in which collagen fibres formed well aligned capsules around the CD10+ stromal border were identified compared with lesions in which collagen fibre distribution was random. Considerable inter- and intra-patient variability in the morphology of SMA and collagen was observed within and surrounding lesions.

CONCLUSION

These data demonstrate considerable diversity in the presence of immune cells and morphology of SMA and collagen within, but even more so, surrounding endometriotic lesions, even within individual patients. This heterogeneity, especially within individual patients, presents a challenge to incorporating these cell and tissue types into any new endometriosis classification systems or prognostic approaches.

Spatially Resolved Transcriptomes of CD30+-Transformed Mycosis Fungoides and Cutaneous Anaplastic Large-Cell Lymphoma

Mycosis fungoides with large-cell transformation (MF-LCT) occurs in a minor proportion of aggressive lesions, which express CD30 similar to primary cutaneous anaplastic large-cell lymphoma (pcALCL). We investigated the differences in spatially resolved transcriptome profiles of MF-LCT and pcALCL using CD30 morphology markers and 28 and 24 regions of interest (ROIs) in MF-LCT and pcALCL, respectively. Differentially expressed genes, pathway analysis, and immune-cell deconvolution by selective analysis of CD30-positive tumor cells and CD30-negative extratumoral areas were undertaken. In CD30-positive ROIs of MF-LCT, 190 differentially expressed genes were upregulated (29 were directly or indirectly associated with extracellular matrix remodeling), whereas 255 differentially expressed genes were downregulated, compared with those of pcALCL. Except for cornified envelope formation and keratinization, all six pathways enriched in CD30-positive ROIs of MF-LCT were associated with extracellular matrix remodeling. In CD30-positive ROIs in MF-LCT compared with those in pcALCL, immune-cell deconvolution revealed significantly increased fibroblasts and M2 macrophages (P = 0.012 and P = 0.023, respectively) but decreased M1 macrophages (P = 0.031). In CD30-negative ROIs in MF-LCT compared with those in pcALCL, memory B (P = 0.021), plasma (P = 0.023), and CD8 memory T (P = 0.001) cells significantly decreased, whereas regulatory T cells (P = 0.024) increased. Predomination of extracellular matrix remodeling pathways and immunosuppressive microenvironment in MF-LCT indicates pathophysiological differences between MF-LCT and pcALCL.

[Research Progress on the Influence of Tumor Extracellular Matrix Mechanic Properties on Nanodrug Delivery]

Nanodrugs are widely utilized in the biomedical fields, exhibiting immense potential in cancer therapy in particular. However, tumors exist in an extremely complicated microenvironment where substances like collagen are continuously deposited and remodeled, leading to significant alterations in the mechanical properties of the extracellular matrix (ECM) during tumor development. Previous research has primarily focused on the specific physicochemical properties of nanodrugs, such as particle size, electric charge, shape, surface chemistry, etc., and their effects on cellular uptake, cytotoxicity, and in vivo pharmacokinetics. Limited studies have been done to explore the impact of ECM mechanical properties on nanodrug delivery. In this review, we systematically summarized the relevant research findings on this topic from the perspective of the characteristics and testing methods of tumor ECM mechanics. Additionally, we made a thorough discussion of the potential mechanical and biological mechanisms involved in nanodrug delivery. We proposed several noteworthy research directions. Regarding the overall strategy, there is a need to emphasize targeted delivery that combines ECM mechanics and nanomechanics to achieve precise drug delivery. Regarding the spatial aspect, attention should be given to the nonlinear spatial mechanical heterogeneity within the interior of solid tumors and the construction of mechanic microenvironment-adaptive nanocarriers to improve the delivery efficiency. Regarding the temporal aspect, emphasis should be placed on the dynamic development and changes in the mechanical microenvironment during solid tumor growth and treatment processes. Based on the stromal mechanical characteristics of the tumor tissues of individual patients, personalized treatment strategies can be formulated, which will enhance treatment specificity and efficacy. In addition, issues such as mechanically targeted nanodrug delivery, degradation, and metabolism under dynamic ECM mechanical conditions warrant further investigation.

Dissecting tumor microenvironment heterogeneity in syngeneic mouse models: insights on cancer-associated fibroblast phenotypes shaped by infiltrating T cells

Murine syngeneic tumor models have been used extensively for cancer research for several decades and have been instrumental in driving the discovery and development of cancer immunotherapies. These tumor models are very simplistic cancer models, but recent reports have, however, indicated that the different inoculated cancer cell lines can lead to the formation of unique tumor microenvironments (TMEs). To gain more knowledge from studies based on syngeneic tumor models, it is essential to obtain an in-depth understanding of the cellular and molecular composition of the TME in the different models. Additionally, other parameters that are important for cancer progression, such as collagen content and mechanical tissue stiffness across syngeneic tumor models have not previously been reported. Here, we compare the TME of tumors derived from six common syngeneic tumor models. Using flow cytometry and transcriptomic analyses, we show that strikingly unique TMEs are formed by the different cancer cell lines. The differences are reflected as changes in abundance and phenotype of myeloid, lymphoid, and stromal cells in the tumors. Gene expression analyses support the different cellular composition of the TMEs and indicate that distinct immunosuppressive mechanisms are employed depending on the tumor model. Cancer-associated fibroblasts (CAFs) also acquire very different phenotypes across the tumor models. These differences include differential expression of genes encoding extracellular matrix (ECM) proteins, matrix metalloproteinases (MMPs), and immunosuppressive factors. The gene expression profiles suggest that CAFs can contribute to the formation of an immunosuppressive TME, and flow cytometry analyses show increased PD-L1 expression by CAFs in the immunogenic tumor models, MC38 and CT26. Comparison with CAF subsets identified in other studies shows that CAFs are skewed towards specific subsets depending on the model. In athymic mice lacking tumor-infiltrating cytotoxic T cells, CAFs express lower levels of PD-L1 and lower levels of fibroblast activation markers. Our data underscores that CAFs can be involved in the formation of an immunosuppressive TME.

Immunofluorescence profiling of collagen subtypes is a predictor of treatment outcomes in pancreatic cancer

Desmoplasia in pancreatic ductal adenocarcinoma (PDAC) is characterized by elevated levels of tumor collagen. Desmoplasia restricts drug delivery in PDAC, contributes to treatment resistance, and is associated with poor survival outcomes. We have previously shown that photodynamic therapy (PDT)-based treatment remediates desmoplasia in orthotopic PDAC tumors by reducing second harmonic generation signals from collagen by >90% and by reducing collagen alignment by >103-fold [19]. Remediating desmoplasia correlated with improved survival outcomes in mice. To understand this phenomenon at a fundamental level, it is important to dissect the impact of therapy on collagen subtypes. In this study, we demonstrate that immunofluorescence profiling of collagen subtypes I, II, III and IV in PDAC tumors 72 h following multiple treatment regimens is predictive of long-term outcomes. Treatment regimens include nanoliposomal irinotecan chemotherapy (nal-IRI; akin to ONIVYDE™), a combination of nal-IRI chemotherapy with PDT encapsulated in a single photoactivable multi-inhibitor liposome (PMIL) and an EGFR-targeted PMIL construct (TPMIL). Results show that the relative tumor content of collagen I, II and III was inversely correlated with overall survival (P ≤ 0.0013, P ≤ 0.0001, P ≤ 0.0011, respectively), while, surprisingly, the relative tumor content of collagen IV was directly correlated with overall survival (P ≤ 0.0001). Similar relationships were observed between the relative tumor content of collagen subtypes and the residual tumor volume at day 88 following treatment. Considering that the relationship between collagen subtypes and treatment outcomes is observed across multiple treatment regimens, immunofluorescence profiling at 72 h following treatment appears to be predictive of tumor growth inhibition and survival in PDAC. Early immunofluorescence collagen subtype profiling may therefore aid in treatment personalization and may inform the dosimetry and scheduling of combination regimens for PDAC, such as chemotherapy and emerging PDT-based combinations, to maximize patient survival benefit.

Benign and malignant prostate neoplasms show different spatial organization of collagen

AIM

To compare the indicators of the spatial organization of collagen and its regulating factors between benign and malignant prostate neoplasms.

METHODS

The study involved tumor tissue samples from 40 patients with stage II-III prostate cancer (PCa) and 20 patients with benign prostatic hyperplasia (BPH). The localization of collagen was determined with a Masson trichrome stain. To establish quantitative indicators of the spatial organization of collagen, morphometric studies were carried out with the CurveAlign and ImageJ programs.

RESULTS

PCa tissue had two times lower collagen density (P<0.0001) and 1.3 times lower levels of collagen alignment (P=0.018) compared with BPH tissue. In PCa tissue, collagen fibers were shorter (by 24.2%; P<0.001) and thicker (by 15.5%; P<0.001). PCa tissue samples showed significantly higher levels of metalloproteinase (MMP)-2 (by 2.4 times; P=0.001), MMP-8 (by 2.3 times; P=0.007), and MMP-13 (by 1.9 times; P=0.004).

CONCLUSIONS

Collagen matrix spatial organization features, as well as its regulatory factors, could be potential biomarkers of malignant prostate neoplasms.

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts ranging from cancers to chronic inflammations, as evidenced by many studies. Quantifying fibrillar collagen organization has become a powerful approach for characterizing the topology of collagen fibers and studying the role of collagen fibers in disease progression. We present a deep learning-based pipeline to quantify collagen fibers' topological properties in microscopy-based collagen images from pathological tissue samples. Our method leverages deep neural networks to extract collagen fiber centerlines and deep generative models to create synthetic training data, addressing the current shortage of large-scale annotations. As a part of this effort, we have created and annotated a collagen fiber centerline dataset, with the hope of facilitating further research in this field. Quantitative measurements such as fiber orientation, alignment, density, and length can be derived based on the centerline extraction results. Our pipeline comprises three stages. Initially, a variational autoencoder is trained to generate synthetic centerlines possessing controllable topological properties. Subsequently, a conditional generative adversarial network synthesizes realistic collagen fiber images from the synthetic centerlines, yielding a synthetic training set of image-centerline pairs. Finally, we train a collagen fiber centerline extraction network using both the original and synthetic data. Evaluation using collagen fiber images from pancreas, liver, and breast cancer samples collected via second-harmonic generation microscopy demonstrates our pipeline's superiority over several popular fiber centerline extraction tools. Incorporating synthetic data into training further enhances the network's generalizability. Our code is available at https://github.com/uw-loci/collagen-fiber-metrics.

Desmoplastic stromal signatures predict patient outcomes in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second leading cause of cancer-related death. Hallmarks include desmoplasia with variable extracellular matrix (ECM) architecture and a complex microenvironment with spatially defined tumor, stromal, and immune populations. Nevertheless, the role of desmoplastic spatial organization in patient/tumor variability remains underexplored, which we elucidate using two technologies. First, we quantify ECM patterning in 437 patients, revealing architectures associated with disease-free and overall survival. Second, we spatially profile the cellular milieu of 78 specimens using codetection by indexing, identifying an axis of pro-inflammatory cell interactions predictive of poorer outcomes. We discover that clinical characteristics, including neoadjuvant chemotherapy status, tumor stage, and ECM architecture, correlate with differential stromal-immune organization, including fibroblast subtypes with distinct niches. Lastly, we define unified signatures that predict survival with areas under the receiver operating characteristic curve (AUCs) of 0.872-0.903, differentiating survivorship by 655 days. Overall, our findings establish matrix ultrastructural and cellular organizations of fibrosis linked to poorer outcomes.

Quantifying in vivo collagen reorganization during immunotherapy in murine melanoma with second harmonic generation imaging

Significance

Increased collagen linearization and deposition during tumorigenesis can impede immune cell infiltration and lead to tumor metastasis. Although melanoma is well studied in immunotherapy research, studies that quantify collagen changes during melanoma progression and treatment are lacking.

Aim

Image in vivo collagen in preclinical melanoma models during immunotherapy and quantify the collagen phenotype in treated and control mice.

Approach

Second harmonic generation imaging of collagen was performed in mouse melanoma tumors in vivo over a treatment time-course. Animals were treated with a curative radiation and immunotherapy combination. Collagen morphology was quantified over time at an image and single fiber level using CurveAlign and CT-FIRE software.

Results

In immunotherapy-treated mice, collagen reorganized toward a healthy phenotype, including shorter, wider, curlier collagen fibers, with modestly higher collagen density. Temporally, collagen fiber straightness and length changed late in treatment (Day 9 and 12) while width and density changed early (Day 6) compared to control mice. Single fiber level collagen analysis was most sensitive to the changes between treatment groups compared to image level analysis.

Conclusions

Quantitative second harmonic generation imaging can provide insight into collagen dynamics in vivo during immunotherapy, with key implications in improving immunotherapy response in melanoma and other cancers.

In vivo label-free optical signatures of chemotherapy response in human pancreatic ductal adenocarcinoma patient-derived xenografts

Pancreatic cancer is a devastating disease often detected at later stages, necessitating swift and effective chemotherapy treatment. However, chemoresistance is common and its mechanisms are poorly understood. Here, label-free multi-modal nonlinear optical microscopy was applied to study microstructural and functional features of pancreatic tumors in vivo to monitor inter- and intra-tumor heterogeneity and treatment response. Patient-derived xenografts with human pancreatic ductal adenocarcinoma were implanted into mice and characterized over five weeks of intraperitoneal chemotherapy (FIRINOX or Gem/NabP) with known responsiveness/resistance. Resistant and responsive tumors exhibited a similar initial metabolic response, but by week 5 the resistant tumor deviated significantly from the responsive tumor, indicating that a representative response may take up to five weeks to appear. This biphasic metabolic response in a chemoresistant tumor reveals the possibility of intra-tumor spatiotemporal heterogeneity of drug responsiveness. These results, though limited by small sample size, suggest the possibility for further work characterizing chemoresistance mechanisms using nonlinear optical microscopy.

Fibroblast-derived matrix models desmoplastic properties and forms a prognostic signature in cancer progression

The desmoplastic reaction observed in many cancers is a hallmark of disease progression and prognosis, particularly in breast and pancreatic cancer. Stromal-derived extracellular matrix (ECM) is significantly altered in desmoplasia, and as such plays a critical role in driving cancer progression. Using fibroblast-derived matrices (FDMs), we show that cancer cells have increased growth on cancer associated FDMs, when compared to FDMs derived from non-malignant tissue (normal) fibroblasts. We assess the changes in ECM characteristics from normal to cancer-associated stroma at the primary tumor site. Compositional, structural, and mechanical analyses reveal significant differences, with an increase in abundance of core ECM proteins, coupled with an increase in stiffness and density in cancer-associated FDMs. From compositional changes of FDM, we derived a 36-ECM protein signature, which we show matches in large part with the changes in pancreatic ductal adenocarcinoma (PDAC) tumor and metastases progression. Additionally, this signature also matches at the transcriptomic level in multiple cancer types in patients, prognostic of their survival. Together, our results show relevance of FDMs for cancer modelling and identification of desmoplastic ECM components for further mechanistic studies.

Microengineering 3D Collagen Matrices with Tumor-Mimetic Gradients in Fiber Alignment

In the tumor microenvironment (TME), collagen fibers facilitate tumor cell migration through the extracellular matrix. Previous studies have focused on studying the responses of cells on uniformly aligned or randomly aligned collagen fibers. However, the in vivo environment also features spatial gradients in alignment, which arise from the local reorganization of the matrix architecture due to cell-induced traction forces. Although there has been extensive research on how cells respond to graded biophysical cues, such as stiffness, porosity, and ligand density, the cellular responses to physiological fiber alignment gradients have been largely unexplored. This is due, in part, to a lack of robust experimental techniques to create controlled alignment gradients in natural materials. In this study, we image tumor biopsy samples and characterize the alignment gradients present in the TME. To replicate physiological gradients, we introduce a first-of-its-kind biofabrication technique that utilizes a microfluidic channel with constricting and expanding geometry to engineer 3D collagen hydrogels with tunable fiber alignment gradients that range from sub-millimeter to millimeter length scales. Our modular approach allows easy access to the microengineered gradient gels, and we demonstrate that HUVECs migrate in response to the fiber architecture. We provide preliminary evidence suggesting that MDA-MB-231 cell aggregates, patterned onto a specific location on the alignment gradient, exhibit preferential migration towards increasing alignment. This finding suggests that alignment gradients could serve as an additional taxis cue in the ECM. Importantly, our study represents the first successful engineering of continuous gradients of fiber alignment in soft, natural materials. We anticipate that our user-friendly platform, which needs no specialized equipment, will offer new experimental capabilities to study the impact of fiber-based contact guidance on directed cell migration.

Quantitative intravital imaging for real-time monitoring of pancreatic tumor cell hypoxia and stroma in an orthotopic mouse model

Pancreatic cancer is a lethal disease with few successful treatment options. Recent evidence demonstrates that tumor hypoxia promotes pancreatic tumor invasion, metastasis, and therapy resistance. However, little is known about the complex relationship between hypoxia and the pancreatic tumor microenvironment (TME). In this study, we developed a novel intravital fluorescence microscopy platform with an orthotopic mouse model of pancreatic cancer to study tumor cell hypoxia within the TME in vivo, at cellular resolution, over time. Using a fluorescent BxPC3-DsRed tumor cell line with a hypoxia-response element (HRE)/green fluorescent protein (GFP) reporter, we showed that HRE/GFP is a reliable biomarker of pancreatic tumor hypoxia, responding dynamically and reversibly to changing oxygen concentrations within the TME. We also characterized the spatial relationships between tumor hypoxia, microvasculature, and tumor-associated collagen structures using in vivo second harmonic generation microscopy. This quantitative multimodal imaging platform enables the unprecedented study of hypoxia within the pancreatic TME in vivo.

The Extracellular Matrix: Its Composition, Function, Remodeling, and Role in Tumorigenesis

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissue and organ integrity. Initially thought to be a bystander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM's composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM constantly undergoes degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, ECM synthesis, remodeling, and degradation is dysregulated, causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in the progression of various diseases such as cancers. Advances in 'omics' technologies have seen an increase in studies focusing on bidirectional cell-matrix interactions, and here, we highlight the emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted therapies that can modify ECM tumors to overcome drug resistance and better cancer treatment.

Soft topographical patterns trigger a stiffness-dependent cellular response to contact guidance

Topographical patterns are a powerful tool to study directional migration. Grooved substrates have been extensively used as in vitro models of aligned extracellular matrix fibers because they induce cell elongation, alignment, and migration through a phenomenon known as contact guidance. This process, which involves the orientation of focal adhesions, F-actin, and microtubule cytoskeleton along the direction of the grooves, has been primarily studied on hard materials of non-physiological stiffness. But how it unfolds when the stiffness of the grooves varies within the physiological range is less known. Here we show that substrate stiffness modulates the cellular response to topographical contact guidance. We find that for fibroblasts, while focal adhesions and actin respond to topography independently of the stiffness, microtubules show a stiffness-dependent response that regulates contact guidance. On the other hand, both clusters and single breast carcinoma epithelial cells display stiffness-dependent contact guidance, leading to more directional and efficient migration when increasing substrate stiffness. These results suggest that both matrix stiffening and alignment of extracellular matrix fibers cooperate during directional cell migration, and that the outcome differs between cell types depending on how they organize their cytoskeletons.

Quantitative collagen analysis using second harmonic generation images for the detection of basal cell carcinoma with ex vivo multiphoton microscopy

Basal cell carcinoma (BCC) is the most common skin cancer, and its incidence is rising. Millions of benign biopsies are performed annually for BCC diagnosis, increasing morbidity, and healthcare costs. Non-invasive in vivo technologies such as multiphoton microscopy (MPM) can aid in diagnosing BCC, reducing the need for biopsies. Furthermore, the second harmonic generation (SHG) signal generated from MPM can classify and prognosticate cancers based on extracellular matrix changes, especially collagen type I. We explored the potential of MPM to differentiate collagen changes associated with different BCC subtypes compared to normal skin structures and benign lesions. Quantitative analysis such as frequency band energy analysis in Fourier domain, CurveAlign and CT-FIRE fibre analysis was performed on SHG images from 52 BCC and 12 benign lesions samples. Our results showed that collagen distribution is more aligned surrounding BCCs nests compared to the skin's normal structures (p < 0.001) and benign lesions (p < 0.001). Also, collagen was orientated more parallelly surrounding indolent BCC subtypes (superficial and nodular) versus those with more aggressive behaviour (infiltrative BCC) (p = 0.021). In conclusion, SHG signal from type I collagen can aid not only in the diagnosis of BCC but could be useful for prognosticating these tumors. Our initial results are limited to a small number of samples, requiring large-scale studies to validate them. These findings represent the groundwork for future in vivo MPM for diagnosis and prognosis of BCC.

Clustering and machine learning-based integration identify cancer associated fibroblasts genes’ signature in head and neck squamous cell carcinoma

Background: A hallmark signature of the tumor microenvironment in head and neck squamous cell carcinoma (HNSCC) is abundantly infiltration of cancer-associated fibroblasts (CAFs), which facilitate HNSCC progression. However, some clinical trials showed targeted CAFs ended in failure, even accelerated cancer progression. Therefore, comprehensive exploration of CAFs should solve the shortcoming and facilitate the CAFs targeted therapies for HNSCC.

Methods: In this study, we identified two CAFs gene expression patterns and performed the single‐sample gene set enrichment analysis (ssGSEA) to quantify the expression and construct score system. We used multi-methods to reveal the potential mechanisms of CAFs carcinogenesis progression. Finally, we integrated 10 machine learning algorithms and 107 algorithm combinations to construct most accurate and stable risk model. The machine learning algorithms contained random survival forest (RSF), elastic network (Enet), Lasso, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox (plsRcox), supervised principal components (SuperPC), generalised boosted regression modelling (GBM), and survival support vector machine (survival-SVM).

Results: There are two clusters present with distinct CAFs genes pattern. Compared to the low CafS group, the high CafS group was associated with significant immunosuppression, poor prognosis, and increased prospect of HPV negative. Patients with high CafS also underwent the abundant enrichment of carcinogenic signaling pathways such as angiogenesis, epithelial mesenchymal transition, and coagulation. The MDK and NAMPT ligand–receptor cellular crosstalk between the cancer associated fibroblasts and other cell clusters may mechanistically cause immune escape. Moreover, the random survival forest prognostic model that was developed from 107 machine learning algorithm combinations could most accurately classify HNSCC patients.

Conclusion: We revealed that CAFs would cause the activation of some carcinogenesis pathways such as angiogenesis, epithelial mesenchymal transition, and coagulation and revealed unique possibilities to target glycolysis pathways to enhance CAFs targeted therapy. We developed an unprecedentedly stable and powerful risk score for assessing the prognosis. Our study contributes to the understanding of the CAFs microenvironment complexity in patients with head and neck squamous cell carcinoma and serves as a basis for future in-depth CAFs gene clinical exploration.

Crosstalk between tumor acidosis, p53 and extracellular matrix regulates pancreatic cancer aggressiveness

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy with minimal treatment options and a global rise in prevalence. PDAC is characterized by frequent driver mutations including KRAS and TP53 (p53), and a dense, acidic tumor microenvironment (TME). The relation between genotype and TME in PDAC development is unknown. Strikingly, when wild type (WT) Panc02 PDAC cells were adapted to growth in an acidic TME and returned to normal pH to mimic invasive cells escaping acidic regions, they displayed a strong increase of aggressive traits such as increased growth in 3-dimensional (3D) culture, adhesion-independent colony formation and invasive outgrowth. This pattern of acidosis-induced aggressiveness was observed in 3D spheroid culture as well as upon organotypic growth in matrigel, collagen-I and combination thereof, mimicking early and later stages of PDAC development. Acid-adaptation-induced gain of cancerous traits was further increased by p53 knockout (KO), but only in specific extracellular matrix (ECM) compositions. Akt- and Transforming growth factor-β (TGFβ) signaling, as well as expression of the Na⁺ /H⁺ exchanger NHE1, were increased by acid adaptation. Whereas Akt inhibition decreased spheroid growth regardless of treatment and genotype, stimulation with TGFβI increased growth of WT control spheroids, and inhibition of TGFβ signaling tended to limit growth under acidic conditions only. Our results indicate that a complex crosstalk between tumor acidosis, ECM composition and genotype contributes to PDAC development. The findings may guide future strategies for acidosis-targeted therapies.

High serum levels of the C-propetide of type V collagen (PRO-C5) are prognostic for short overall survival in patients with pancreatic ductal adenocarcinoma

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a pronounced fibrotic tumor microenvironment, which impairs treatment response. Type I and V collagens are responsible for the densely packed fibrils in the tumor fibrosis environment. While the role of the major type I collagen in cancer is well described, less is known about the minor type V collagen. Quantifying collagen propeptides in serum has been shown to have prognostic and predictive value. In this study, we evaluated the clinical utility of measuring the propeptide of type V collagen (PRO-C5) in serum from a discovery cohort and a validation cohort of patients with PDAC as well as in non-pancreatic solid tumor types to explore the relevance of the PRO-C5 biomarker in cancer.

Methods: Serum PRO-C5 was measured in three cohorts: a discovery cohort (19 healthy controls, 12 patients with chronic pancreatitis and 33 patients with PDAC (stage I-IV)), a validation cohort (800 patients with PDAC (stage I-IV)), and a non-pancreatic solid tumor type cohort of 33 healthy controls and 200 patients with 10 different non-pancreatic solid tumor types. The levels of serum PRO-C5 in patients with cancer were compared to levels in healthy controls. The association between PRO-C5 levels and overall survival (OS) was evaluated in patients with PDAC after adjusting for established prognostic factors.

Results: PRO-C5 was significantly increased in serum from patients with PDAC compared to healthy controls (p &lt; 0.001). High PRO-C5 levels were significantly associated with short OS in both the discovery- and the validation cohort, especially in early stages of PDAC (validation cohort stage II, HR = 2.0, 95%CI1.2-3.4). The association was independent of other prognostic parameters including stage, performance status and CA19-9. Furthermore, serum levels of PRO-C5 were significantly increased in serum from patients with other non-pancreatic solid tumor types compared to healthy controls.

Conclusion: High levels of serum PRO-C5 is prognostic for short OS in patients with PDAC and may provide clinical value in many other tumor types beyond PDAC. This underlines the importance of type V collagen in tumor fibrosis. PRO-C5 could have the potential to be used in several aspects within drug discovery, patient stratification and drug efficacy.

Click chemistry functionalization of self-assembling peptide hydrogels

Self-assembling peptide (SAP) hydrogels provide a fibrous microenvironment to cells while also giving users control of biochemical and mechanical cues. Previously, biochemical cues were introduced by physically mixing them with SAPs prior to hydrogel assembly, or by incorporating them into the SAP sequence during peptide synthesis, which limited flexibility and increased costs. To circumvent these limitations, we developed "Click SAPs," a novel formulation that can be easily functionalized via click chemistry thiol-ene reaction. Due to its high cytocompatibility, the thiol-ene click reaction is currently used to crosslink and functionalize other types of polymeric hydrogels. In this study, we developed a click chemistry compatible SAP platform by addition of a modified lysine (lysine-alloc) to the SAP sequence, enabling effective coupling of thiol-containing molecules to the SAP hydrogel network. We demonstrate the flexibility of this approach by incorporating a fluorescent dye, a cellular adhesion peptide, and a matrix metalloproteinase-sensitive biosensor using the thiol-ene reaction in 3D Click SAPs. Using atomic force microscopy, we demonstrate that Click SAPs retain the ability to self-assemble into fibers, similar to previous systems. Additionally, a range of physiologically relevant stiffnesses can be achieved by adjusting SAP concentration. Encapsulated cells maintain high viability in Click SAPs and can interact with adhesion peptides and a matrix metalloproteinase biosensor, demonstrating that incorporated molecules retain their biological activity. The Click SAP platform supports easier functionalization with a wider array of bioactive molecules and enables new investigations with temporal and spatial control of the cellular microenvironment.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Cancer-associated fibroblasts: The chief architect in the tumor microenvironment

Stromal heterogeneity of tumor microenvironment (TME) plays a crucial role in malignancy and therapeutic resistance. Cancer-associated fibroblasts (CAFs) are one of the major players in tumor stroma. The heterogeneous sources of origin and subsequent impacts of crosstalk with breast cancer cells flaunt serious challenges before current therapies to cure triple-negative breast cancer (TNBC) and other cancers. The positive and reciprocal feedback of CAFs to induce cancer cells dictates their mutual synergy in establishing malignancy. Their substantial role in creating a tumor-promoting niche has reduced the efficacy of several anti-cancer treatments, including radiation, chemotherapy, immunotherapy, and endocrine therapy. Over the years, there has been an emphasis on understanding CAF-induced therapeutic resistance in order to enhance cancer therapy results. CAFs, in the majority of cases, employ crosstalk, stromal management, and other strategies to generate resilience in surrounding tumor cells. This emphasizes the significance of developing novel strategies that target particular tumor-promoting CAF subpopulations, which will improve treatment sensitivity and impede tumor growth. In this review, we discuss the current understanding of the origin and heterogeneity of CAFs, their role in tumor progression, and altering the tumor response to therapeutic agents in breast cancer. In addition, we also discuss the potential and possible approaches for CAF-mediated therapies.

Therapeutic Strategies to Overcome Fibrotic Barriers to Nanomedicine in the Pancreatic Tumor Microenvironment

Pancreatic cancer is notorious for its dismal prognosis. The enhanced permeability and retention (EPR) effect theory posits that nanomedicines (therapeutics in the size range of approximately 10-200 nm) selectively accumulate in tumors. Nanomedicine has thus been suggested to be the "magic bullet"-both effective and safe-to treat pancreatic cancer. However, the densely fibrotic tumor microenvironment of pancreatic cancer impedes nanomedicine delivery. The EPR effect is thus insufficient to achieve a significant therapeutic effect. Intratumoral fibrosis is chiefly driven by aberrantly activated fibroblasts and the extracellular matrix (ECM) components secreted. Fibroblast and ECM abnormalities offer various potential targets for therapeutic intervention. In this review, we detail the diverse strategies being tested to overcome the fibrotic barriers to nanomedicine in pancreatic cancer. Strategies that target the fibrotic tissue/process are discussed first, which are followed by strategies to optimize nanomedicine design. We provide an overview of how a deeper understanding, increasingly at single-cell resolution, of fibroblast biology is revealing the complex role of the fibrotic stroma in pancreatic cancer pathogenesis and consider the therapeutic implications. Finally, we discuss critical gaps in our understanding and how we might better formulate strategies to successfully overcome the fibrotic barriers in pancreatic cancer.

Multimodal Techniques to Study Tumor Growth, Basement Membrane Breaching, and Invasion in 3D Matrices

Cancer-derived organoids and three-dimensional (3D) extracellular matrix (ECM) are taking center stage as in vitro models to study neoplastic cell behavior, since they recapitulate the heterogeneous cellular composition of tumors and their extracellular environment. In combination with imaging and molecular/biochemical techniques, 3D organoid models have contributed substantially to our knowledge about the cellular and molecular mechanisms that regulate the growth of tumors and invasion into the surrounding tissue. We here outline a set of protocols that describe culturing of cancer-derived organoids in 3D matrices and various strategies that allow modeling of tumor growth, tumor cell penetration into basement membranes, and invasion into Collagen I-rich ECM. Furthermore, we specify protocols for subsequent handling of organoids cultured in 3D ECM for confocal microscopy and analysis of gene expression at the protein and mRNA level. Although we here use breast cancer-derived organoids, these protocols can be directly applied or adapted for organoids derived from other cancer types or healthy tissues. Thus, in addition to investigating cell behavior of multiple cancer types, the combination of protocols described here may be used to study processes such as cell differentiation and migration during homeostasis and normal development.

Challenges and Opportunities Modeling the Dynamic Tumor Matrisome

We need novel strategies to target the complexity of cancer and, particularly, of metastatic disease. As an example of this complexity, certain tissues are particularly hospitable environments for metastases, whereas others do not contain fertile microenvironments to support cancer cell growth. Continuing evidence that the extracellular matrix (ECM) of tissues is one of a host of factors necessary to support cancer cell growth at both primary and secondary tissue sites is emerging. Research on cancer metastasis has largely been focused on the molecular adaptations of tumor cells in various cytokine and growth factor environments on 2-dimensional tissue culture polystyrene plates. Intravital imaging, conversely, has transformed our ability to watch, in real time, tumor cell invasion, intravasation, extravasation, and growth. Because the interstitial ECM that supports all cells in the tumor microenvironment changes over time scales outside the possible window of typical intravital imaging, bioengineers are continuously developing both simple and sophisticated in vitro controlled environments to study tumor (and other) cell interactions with this matrix. In this perspective, we focus on the cellular unit responsible for upholding the pathologic homeostasis of tumor-bearing organs, cancer-associated fibroblasts (CAFs), and their self-generated ECM. The latter, together with tumoral and other cell secreted factors, constitute the "tumor matrisome". We share the challenges and opportunities for modeling this dynamic CAF/ECM unit, the tools and techniques available, and how the tumor matrisome is remodeled (e.g., via ECM proteases). We posit that increasing information on tumor matrisome dynamics may lead the field to alternative strategies for personalized medicine outside genomics.

Targeting the secreted RGDKGE collagen fragment reduces PD‑L1 by a proteasome‑dependent mechanism and inhibits tumor growth

Structural alterations of collagen impact signaling that helps control tumor progression and the responses to therapeutic intervention. Integrins represent a class of receptors that include members that mediate collagen signaling. However, a strategy of directly targeting integrins to control tumor growth has demonstrated limited activity in the clinical setting. New molecular understanding of integrins have revealed that these receptors can regulate both pro‑ and anti‑tumorigenic functions in a cell type‑dependent manner. Therefore, designing strategies that block pro‑tumorigenic signaling, without impeding anti‑tumorigenic functions, may lead to development of more effective therapies. In the present study, evidence was provided for a novel signaling cascade in which β3‑integrin‑mediated binding to a secreted RGDKGE‑containing collagen fragment stimulates an autocrine‑like signaling pathway that differentially governs the activity of both YAP and (protein kinase‑A) PKA, ultimately leading to alterations in the levels of immune checkpoint molecule PD‑L1 by a proteasome dependent mechanism. Selectively targeting this collagen fragment, reduced nuclear YAP levels, and enhanced PKA and proteasome activity, while also exhibiting significant antitumor activity in vivo. The present findings not only provided new mechanistic insight into a previously unknown autocrine‑like signaling pathway that may provide tumor cells with the ability to regulate PD‑L1, but our findings may also help in the development of more effective strategies to control pro‑tumorigenic β3‑integrin signaling without disrupting its tumor suppressive functions in other cellular compartments.

Multiscale Label-Free Imaging of Fibrillar Collagen in the Tumor Microenvironment

With recent advances in cancer therapeutics, there is a great need for improved imaging methods for characterizing cancer onset and progression in a quantitative and actionable way. Collagen, the most abundant extracellular matrix protein in the tumor microenvironment (and the body in general), plays a multifaceted role, both hindering and promoting cancer invasion and progression. Collagen deposition can defend the tumor with immunosuppressive effects, while aligned collagen fiber structures can enable tumor cell migration, aiding invasion and metastasis. Given the complex role of collagen fiber organization and topology, imaging has been a tool of choice to characterize these changes on multiple spatial scales, from the organ and tumor scale to cellular and subcellular level. Macroscale density already aids in the detection and diagnosis of solid cancers, but progress is being made to integrate finer microscale features into the process. Here we review imaging modalities ranging from optical methods of second harmonic generation (SHG), polarized light microscopy (PLM), and optical coherence tomography (OCT) to the medical imaging approaches of ultrasound and magnetic resonance imaging (MRI). These methods have enabled scientists and clinicians to better understand the impact collagen structure has on the tumor environment, at both the bulk scale (density) and microscale (fibrillar structure) levels. We focus on imaging methods with the potential to both examine the collagen structure in as natural a state as possible and still be clinically amenable, with an emphasis on label-free strategies, exploiting intrinsic optical properties of collagen fibers.

Extracellular matrix physical properties govern the diffusion of nanoparticles in tumor microenvironment

Nanoparticles (NPs) are confronted with limited and disappointing delivery efficiency in tumors clinically. The tumor extracellular matrix (ECM), whose physical traits have recently been recognized as new hallmarks of cancer, forms a main steric obstacle for NP diffusion, yet the role of tumor ECM physical traits in NP diffusion remains largely unexplored. Here, we characterized the physical properties of clinical gastric tumor samples and observed limited distribution of NPs in decellularized tumor tissues. We also performed molecular dynamics simulations and in vitro hydrogel experiments through single-particle tracking to investigate the diffusion mechanism of NPs and understand the influence of tumor ECM physical properties on NP diffusion both individually and collectively. Furthermore, we developed an estimation matrix model with evaluation scores of NP diffusion efficiency through comprehensive analyses of the data. Thus, beyond finding that loose and soft ECM with aligned structure contribute to efficient diffusion, we now have a systemic model to predict NP diffusion efficiency based on ECM physical traits and provide critical guidance for personalized tumor diagnosis and treatment.

Differentiation of pancreatic ductal adenocarcinoma and chronic pancreatitis using graph neural networks on histopathology and collagen fiber features

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. However, the symptoms and radiographic appearance of chronic pancreatitis (CP) mimics that of PDAC, and sometimes the 2 entities can also be difficult to differentiate microscopically. The need for accurate differentiation of PDAC and CP has become a major topic in pancreatic pathology. These 2 diseases can present similar histomorphological features, such as excessive deposition of fibrotic stroma in the tissue microenvironment and inflammatory cell infiltration. In this paper, we present a quantitative analysis pipeline empowered by graph neural networks (GNN) capable of automatic detection and differentiation of PDAC and CP in human histological specimens. Modeling histological images as graphs and deploying graph convolutions can enable the capture of histomorphological features at different scales, ranging from nuclear size to the organization of ducts. The analysis pipeline combines image features computed from co-registered hematoxylin and eosin (H&E) images and Second-Harmonic Generation (SHG) microscopy images, with the SHG images enabling the extraction of collagen fiber morphological features. Evaluating the analysis pipeline on a human tissue micro-array dataset consisting of 786 cores and a tissue region dataset consisting of 268 images, it attained 86.4% accuracy with an average area under the curve (AUC) of 0.954 and 88.9% accuracy with an average AUC of 0.957, respectively. Moreover, incorporating topological features of collagen fibers computed from SHG images into the model further increases the classification accuracy on the tissue region dataset to 91.3% with an average AUC of 0.962, suggesting that collagen characteristics are diagnostic features in PDAC and CP detection and differentiation.

Multiomic analysis reveals conservation of cancer-associated fibroblast phenotypes across species and tissue of origin

Cancer-associated fibroblasts (CAFs) are integral to the solid tumor microenvironment. CAFs were once thought to be a relatively uniform population of matrix-producing cells, but single-cell RNA sequencing has revealed diverse CAF phenotypes. Here, we further probed CAF heterogeneity with a comprehensive multiomics approach. Using paired, same-cell chromatin accessibility and transcriptome analysis, we provided an integrated analysis of CAF subpopulations over a complex spatial transcriptomic and proteomic landscape to identify three superclusters: steady state-like (SSL), mechanoresponsive (MR), and immunomodulatory (IM) CAFs. These superclusters are recapitulated across multiple tissue types and species. Selective disruption of underlying mechanical force or immune checkpoint inhibition therapy results in shifts in CAF subpopulation distributions and affected tumor growth. As such, the balance among CAF superclusters may have considerable translational implications. Collectively, this research expands our understanding of CAF biology, identifying regulatory pathways in CAF differentiation and elucidating therapeutic targets in a species- and tumor-agnostic manner.

STAT3 in tumor fibroblasts promotes an immunosuppressive microenvironment in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is associated with an incredibly dense stroma, which contributes to its recalcitrance to therapy. Cancer-associated fibroblasts (CAFs) are one of the most abundant cell types within the PDAC stroma and have context-dependent regulation of tumor progression in the tumor microenvironment (TME). Therefore, understanding tumor-promoting pathways in CAFs is essential for developing better stromal targeting therapies. Here, we show that disruption of the STAT3 signaling axis via genetic ablation of Stat3 in stromal fibroblasts in a Kras G12D PDAC mouse model not only slows tumor progression and increases survival, but re-shapes the characteristic immune-suppressive TME by decreasing M2 macrophages (F480+CD206+) and increasing CD8+ T cells. Mechanistically, we show that loss of the tumor suppressor PTEN in pancreatic CAFs leads to an increase in STAT3 phosphorylation. In addition, increased STAT3 phosphorylation in pancreatic CAFs promotes secretion of CXCL1. Inhibition of CXCL1 signaling inhibits M2 polarization in vitro. The results provide a potential mechanism by which CAFs promote an immune-suppressive TME and promote tumor progression in a spontaneous model of PDAC.

A miniaturized screening platform to identify novel regulators of extracellular matrix alignment

Extracellular matrix alignment contributes to metastasis in a number of cancers and is a known prognostic stromal factor; however, the mechanisms controlling matrix organization remain unclear. Cancer-associated fibroblasts (CAF) play a critical role in this process, particularly via matrix production and modulation of key signaling pathways controlling cell adhesion and contractility. Stroma normalization, as opposed to elimination, is a highly sought strategy, and screening for drugs that effectively alter extracellular matrix (ECM) alignment is a practical way to identify novel CAF-normalizing targets that modulate ECM organization. To meet this need, we developed a novel high-throughput screening platform in which fibroblast-derived matrices were produced in 384-well plates, imaged with automated confocal microscopy, and analyzed using a customized MATLAB script. This platform is a technical advance because it miniaturizes the assay, eliminates costly and time-consuming experimental steps, and streamlines data acquisition and analysis to enable high-throughput screening applications. As a proof of concept, this platform was used to screen a kinase inhibitor library to identify modulators of matrix alignment. A number of novel potential regulators were identified, including several receptor tyrosine kinases (c-MET, tropomyosin receptor kinase 1 (NTRK1), HER2/ERBB2) and the serine/threonine kinases protein kinase A, C, and G (PKA, PKC, and PKG). The expression of these regulators was analyzed in publicly available patient datasets to examine the association between stromal gene expression and patient outcomes.

CODA: quantitative 3D reconstruction of large tissues at cellular resolution

A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA's ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.

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.