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

DNA Origami-Cyanine Nanocomplex for Precision Imaging of KRAS-Mutant Pancreatic Cancer Cells

Selective delivery of imaging agents to pancreatic cancer cells (PCCs) within the highly desmoplastic tumors of pancreatic ductal adenocarcinoma (PDAC) represents a significant advancement. This approach allows for precise labeling of PCCs while excluding cancer-associated fibroblasts (CAFs), thereby enhancing both research and diagnostic capabilities. Additionally, it holds the potential to target and eliminate PCCs precisely without harming the surrounding stromal cells in the PDAC tumor microenvironment (TME). In this study, DNA origami-cyanine (Do-Cy) nanocomplexes are synthesized to image KRAS-mutant PCCs selectively in the PDAC TME. These Do-Cy nanocomplexes are hypothesized to be internalized preferentially to KRAS-mutant PCCs over CAFs via elevated macropinocytosis. Several designs of Do-Cy nanocomplexes are synthesized and characterized their cellular uptake using both engineered in vitro and xenograft pancreatic cancer models. The results are further discussed for the implication of precision delivery of therapeutic and imaging agents to KRAS-mutant cancers.

Intelligent Diagnosis of Pancreatic Biopsy From Endoscopic Ultrasound-Guided Fine-Needle Aspiration Via Stimulated Raman Histopathology

Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) has become one of the most important preoperative diagnostic methods for pancreatic tumors, but it often faces challenges of redundant sampling from patients and complex tissue processing that hinders timely diagnosis. Intraoperative rapid on-site evaluation is an auxiliary diagnostic technique that helps assess sample quality in real time, but it heavily depends on pathologists and involves subjectivity and complex procedures. Here, we developed a rapid and label-free approach for intraoperative histology on EUS-FNA specimen via deep learning-based stimulated Raman scattering microscopy, aimed at replacing rapid on-site evaluation and providing a more efficient and objective diagnostic approach. Fresh pancreatic EUS-FNA tissues were imaged with stimulated Raman scattering and compared with hematoxylin and eosin staining to identify key histologic features. Using images from 76 patients, a convolutional neural network model was established to identify benign, malignant, and nondiagnostic areas, achieving a validation accuracy >96% on an external test set of 33 cases. Furthermore, gradient-weighted class activation mapping was able to highlight histologic profiles within individual biopsy. Our approach has potential application in efficient intraoperative assessment of pancreatic biopsy through EUS-FNA.

Development and validation of a CT-based radiomics model to predict survival-graded fibrosis in pancreatic ductal adenocarcinoma

BACKGROUND

Tumor fibrosis plays an important role in chemotherapy resistance in pancreatic ductal adenocarcinoma (PDAC); however, there remains a contradiction in the prognostic value of fibrosis. The authors aimed to investigate the relationship between tumor fibrosis and survival in patients with PDAC, classify patients into high- and low-fibrosis groups, and develop and validate a CT-based radiomics model to non-invasively predict fibrosis before treatment.

MATERIALS AND METHODS

This retrospective, bicentric study included 295 patients with PDAC without any treatments before surgery. Tumor fibrosis was assessed using the collagen fraction (CF). Cox regression analysis was used to evaluate the associations of CF with overall survival (OS) and disease-free survival (DFS). Receiver operating characteristic (ROC) analyses were used to determine the rounded threshold of CF. An integrated model (IM) was developed by incorporating selected radiomic features and clinical-radiological characteristics. The predictive performance was validated in the test cohort (Center 2).

RESULTS

The CFs were 38.22±6.89% and 38.44±8.66% in center 1 (131 patients, 83 males) and center 2 (164 patients, 100 males), respectively ( P =0.814). Multivariable Cox regression revealed that CF was an independent risk factor in the OS and DFS analyses at both centers. ROCs revealed that 40% was the rounded cut-off value of CF. IM predicted CF with areas under the curves (AUCs) of 0.829 (95% CI: 0.753-0.889) and 0.751 (95% CI: 0.677-0.815) in the training and test cohorts, respectively. Decision curve analyses revealed that IM outperformed radiomics model and clinical-radiological model for CF prediction in both cohorts.

CONCLUSIONS

Tumor fibrosis was an independent risk factor for survival of patients with PDAC, and a rounded cut-off value of 40% provided a good differentiation of patient prognosis. The model combining CT-based radiomics and clinical-radiological features can satisfactorily predict survival-grade fibrosis in patients with PDAC.

Understanding the interplay between extracellular matrix topology and tumor-immune interactions: Challenges and opportunities

Modern cancer management comprises a variety of treatment strategies. Immunotherapy, while successful at treating many cancer subtypes, is often hindered by tumor immune evasion and T cell exhaustion as a result of an immunosuppressive tumor microenvironment (TME). In solid malignancies, the extracellular matrix (ECM) embedded within the TME plays a central role in T cell recognition and cancer growth by providing structural support and regulating cell behavior. Relative to healthy tissues, tumor associated ECM signatures include increased fiber density and alignment. These and other differentiating features contributed to variation in clinically observed tumor-specific ECM configurations, collectively referred to as Tumor-Associated Collagen Signatures (TACS) 1-3. TACS is associated with disease progression and immune evasion. This review explores our current understanding of how ECM geometry influences the behaviors of both immune cells and tumor cells, which in turn impacts treatment efficacy and cancer evolutionary progression. We discuss the effects of ECM remodeling on cancer cells and T cell behavior and review recent in silico models of cancer-immune interactions.

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 an MIRSI 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 other 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 with the SHG ground truth, the generated RF-MIRSI collagen images achieved a high average boundary F -score (0.8 at 4-pixel thresholds) 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.

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.

CCK Receptor Inhibition Reduces Pancreatic Tumor Fibrosis and Promotes Nanoparticle Delivery

The poor prognosis for pancreatic ductal adenocarcinoma (PDAC) patients is due in part to the highly fibrotic nature of the tumors that impedes delivery of therapeutics, including nanoparticles (NPs). Our prior studies demonstrated that proglumide, a cholecystokinin receptor (CCKR) antagonist, reduced fibrosis pervading PanIN lesions in mice. Here, we further detail how the reduced fibrosis elicited by proglumide achieves the normalization of the desmoplastic tumor microenvironment (TME) and improves nanoparticle uptake. One week following the orthotopic injection of PDAC cells, mice were randomized to normal or proglumide-treated water for 3-6 weeks. Tumors were analyzed ex vivo for fibrosis, vascularity, stellate cell activation, vascular patency, and nanoparticle distribution. The histological staining and three-dimensional imaging of tumors each indicated a reduction in stromal collagen in proglumide-treated mice. Proglumide treatment increased tumor vascularity and decreased the activation of cancer-associated fibroblasts (CAFs). Additionally, PANC-1 cells with the shRNA-mediated knockdown of the CCK2 receptor showed an even greater reduction in collagen, indicating the CCK2 receptors on tumor cells contribute to the desmoplastic TME. Proglumide-mediated reduction in fibrosis also led to functional changes in the TME as evidenced by the enhanced intra-tumoral distribution of small (<12 nm) Rhodamine-loaded nanoparticles. The documented in vivo, tumor cell-intrinsic anti-fibrotic effects of CCK2R blockade in both an immunocompetent syngeneic murine PDAC model as well as a human PDAC xenograft model demonstrates that CCK2R antagonists, such as proglumide, can improve the delivery of nano-encapsulated therapeutics or imaging agents to pancreatic tumors.

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

We aim to 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 was 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 (days 9 and 12), while width and density changed early (day 6) compared with control mice. Single-fiber collagen features calculated in CT-FIRE were the most sensitive to the changes among treatment groups compared with bulk collagen features.

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.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

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.

Nuclear deformation regulates YAP dynamics in cancer associated fibroblasts

Cells cultured on stiff 2D substrates exert high intracellular force, resulting in mechanical deformation of their nuclei. This nuclear deformation (ND) plays a crucial role in the transport of Yes Associated Protein (YAP) from the cytoplasm to the nucleus. However, cells in vivo are in soft 3D environment with potentially much lower intracellular forces. Whether and how cells may deform their nuclei in 3D for YAP localization remains unclear. Here, by culturing human colon cancer associated fibroblasts (CAFs) on 2D, 2.5D, and 3D substrates, we differentiated the effects of stiffness, force, and ND on YAP localization. We found that nuclear translocation of YAP depends on the degree of ND irrespective of dimensionality, stiffness and total force. ND induced by the perinuclear force, not the total force, and nuclear membrane curvature correlate strongly with YAP activation. Immunostained slices of human tumors further supported the association between ND and YAP nuclear localization, suggesting ND as a potential biomarker for YAP activation in tumors. Additionally, we conducted quantitative analysis of the force dynamics of CAFs on 2D substrates to construct a stochastic model of YAP kinetics. This model revealed that the probability of YAP nuclear translocation, as well as the residence time in the nucleus follow a power law. This study provides valuable insights into the regulatory mechanisms governing YAP dynamics and highlights the significance of threshold activation in YAP localization. STATEMENT OF SIGNIFICANCE: Yes Associated Protein (YAP), a transcription cofactor, has been identified as one of the drivers of cancer progression. High tumor stiffness is attributed to driving YAP to the nucleus, wherein it activates pro-metastatic genes. Here we show, using cancer associated fibroblasts, that YAP translocation to the nucleus depends on the degree of nuclear deformation, irrespective of stiffness. We also identified that perinuclear force induced membrane curvature correlates strongly with YAP nuclear transport. A novel stochastic model of YAP kinetics unveiled a power law relationship between the activation threshold and persistence time of YAP in the nucleus. Overall, this study provides novel insights into the regulatory mechanisms governing YAP dynamics and the probability of activation that is of immense clinical significance.

Microphysiological systems as reliable drug discovery and evaluation tools: Evolution from innovation to maturity

Microphysiological systems (MPSs), also known as organ-on-chip or disease-on-chip, have recently emerged to reconstitute the in vivo cellular microenvironment of various organs and diseases on in vitro platforms. These microfluidics-based platforms are developed to provide reliable drug discovery and regulatory evaluation testbeds. Despite recent emergences and advances of various MPS platforms, their adoption of drug discovery and evaluation processes still lags. This delay is mainly due to a lack of rigorous standards with reproducibility and reliability, and practical difficulties to be adopted in pharmaceutical research and industry settings. This review discusses the current and potential use of MPS platforms in drug discovery processes while considering the context of several key steps during drug discovery processes, including target identification and validation, preclinical evaluation, and clinical trials. Opportunities and challenges are also discussed for the broader dissemination and adoption of MPSs in various drug discovery and regulatory evaluation steps. Addressing these challenges will transform long and expensive drug discovery and evaluation processes into more efficient discovery, screening, and approval of innovative drugs.

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.

A niche-mimicking polymer hydrogel-based approach to identify molecular targets for tackling human pancreatic cancer stem cells

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is one of the most fatal human cancers, but effective therapies remain to be established. Cancer stem cells (CSCs) are highly resistant to anti-cancer drugs and a deeper understanding of their microenvironmental niche has been considered important to provide understanding and solutions to cancer eradication. However, as the CSC niche is composed of a wide variety of biological and physicochemical factors, the development of multidisciplinary tools that recapitulate their complex features is indispensable. Synthetic polymers have been studied as attractive biomaterials due to their tunable biofunctionalities, while hydrogelation technique further renders upon them a diversity of physical properties, making them an attractive tool for analysis of the CSC niche.

METHODS

To develop innovative materials that recapitulate the CSC niche in pancreatic cancers, we performed polymer microarray analysis to identify niche-mimicking scaffolds that preferentially supported the growth of CSCs. The niche-mimicking activity of the identified polymers was further optimized by polyethylene glycol (PEG)-based hydrogelation. To reveal the biological mechanisms behind the activity of the optimized hydrogels towards CSCs, proteins binding onto the hydrogel were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS), and the potential therapeutic targets were validated by looking at gene expression and patients' outcome in the TCGA database.

RESULTS

PA531, a heteropolymer composed of 2-methoxyethyl methacrylate (MEMA) and 2-(diethylamino)ethyl methacrylate (DEAEMA) (5.5:4.5) that specifically supports the growth and maintenance of CSCs was identified by polymer microarray screening using the human PAAD cell line KLM1. The polymer PA531 was converted into five hydrogels (PA531-HG1 to HG5) and developed to give an optimized scaffold with the highest CSC niche-mimicking activities. From this polymer that recapitulated CSC binding and control, the proteins fetuin-B and angiotensinogen were identified as candidate target molecules with clinical significance due to the correlation between gene expression levels and prognosis in PAAD patients and the proteins associated with the niche-mimicking polymer.

CONCLUSION

This study screened for biofunctional polymers suitable for recapitulation of the pancreatic CSC niche and one hydrogel with high niche-mimicking abilities was successfully fabricated. Two soluble factors with clinical significance were identified as potential candidates for biomarkers and therapeutic targets in pancreatic cancers. Such a biomaterial-based approach could be a new platform in drug discovery and therapy development against CSCs, via targeting of their niche.

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.

Quantitative Image Analysis of Fibrillar Collagens Reveals Novel Diagnostic and Prognostic Biomarkers and Histotype-dependent Aberrant Mechanobiology in Lung Cancer

Fibrillar collagens are the most abundant extracellular matrix components in non-small cell lung cancer (NSCLC). Yet, the potential of collagen fiber descriptors as a source of clinically-relevant biomarkers in NSCLC is mainly unknown. Likewise, our understanding of the aberrant collagen organization and associated tumor-promoting effects needs to be better defined. To address these limitations, we identified a digital pathology approach that can be easily implemented in pathology units based on the Curvelet Transform filtering and single Fiber Reconstruction (CT-FIRE) software analysis of picrosirius (PSR) stains of fibrillar collagens imaged with polarized light (PL). CT-FIRE settings were pre-optimized to assess a panel of collagen fiber descriptors in PSR-PL images of tissue microarrays from surgical NSCLC patients (106 adenocarcinomas (ADC), 89 squamous cell carcinomas (SCC)). Using this approach, we identified straightness as the single high-accuracy diagnostic collagen fiber descriptor (average area under the curve AUC = 0.92) and fiber density as the single descriptor consistently associated with poor prognosis in both ADC and SCC independently of the gold standard based on tumor size, lymph node involvement and metastasis (TNM) staging (Hazard ratio HR = 2.69 (1.55-4.66), p < 0.001). Moreover, we found that collagen fibers were markedly straighter, longer, and more aligned in tumors compared to paired samples from uninvolved pulmonary tissue, particularly in ADC, which is indicative of increased tumor stiffening. Consistently, we observed an increase in a panel of stiffness-associated processes in the high collagen fiber density patient group selectively in ADC, including venous/lymphatic invasion, fibroblast activation (alpha-smooth muscle actin (α-SMA)), and immune evasion (programmed death-ligand 1 (PD-L1)). Likewise, transcriptional correlation analysis supported the potential involvement of the major Yes-associated protein 1 (YAP)/TAZ mechanobiology pathway in ADC. Our results provide a proof-of-principle to use CT-FIRE analysis of PSR-PL images to assess new collagen fiber-based diagnostic and prognostic biomarkers in pathology units, which may improve the clinical management of surgical NSCLC patients. Our findings also unveil an aberrant stiff microenvironment in lung ADC that may foster immune evasion and dissemination, encouraging future work to identify therapeutic opportunities.

Extracellular matrix remodeling in tumor progression and immune escape: from mechanisms to treatments

The malignant tumor is a multi-etiological, systemic and complex disease characterized by uncontrolled cell proliferation and distant metastasis. Anticancer treatments including adjuvant therapies and targeted therapies are effective in eliminating cancer cells but in a limited number of patients. Increasing evidence suggests that the extracellular matrix (ECM) plays an important role in tumor development through changes in macromolecule components, degradation enzymes and stiffness. These variations are under the control of cellular components in tumor tissue via the aberrant activation of signaling pathways, the interaction of the ECM components to multiple surface receptors, and mechanical impact. Additionally, the ECM shaped by cancer regulates immune cells which results in an immune suppressive microenvironment and hinders the efficacy of immunotherapies. Thus, the ECM acts as a barrier to protect cancer from treatments and supports tumor progression. Nevertheless, the profound regulatory network of the ECM remodeling hampers the design of individualized antitumor treatment. Here, we elaborate on the composition of the malignant ECM, and discuss the specific mechanisms of the ECM remodeling. Precisely, we highlight the impact of the ECM remodeling on tumor development, including proliferation, anoikis, metastasis, angiogenesis, lymphangiogenesis, and immune escape. Finally, we emphasize ECM "normalization" as a potential strategy for anti-malignant treatment.

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.

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.

Variabilities in global DNA methylation and β-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer

PURPOSE

Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue.

METHODS

Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues.

RESULTS

The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of β-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies.

CONCLUSIONS

Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and β-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing.

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.

Advances in Tumor Organoids for the Evaluation of Drugs: A Bibliographic Review

Tumor organoids are defined as self-organized three-dimensional assemblies of heterogeneous cell types derived from patient samples that mimic the key histopathological, genetic, and phenotypic characteristics of the original tumor. This technology is proposed as an ideal candidate for the evaluation of possible therapies against cancer, presenting advantages over other models which are currently used. However, there are no reports in the literature that relate the techniques and material development of tumor organoids or that emphasize in the physicochemical and biological properties of materials that intent to biomimicry the tumor extracellular matrix. There is also little information regarding the tools to identify the correspondence of native tumors and tumoral organoids (tumoroids). Moreover, this paper relates the advantages of organoids compared to other models for drug evaluation. A growing interest in tumoral organoids has arisen from 2009 to the present, aimed at standardizing the process of obtaining organoids, which more accurately resemble patient-derived tumor tissue. Likewise, it was found that the characteristics to consider for the development of organoids, and therapeutic responses of them, are cell morphology, physiology, the interaction between cells, the composition of the cellular matrix, and the genetic, phenotypic, and epigenetic characteristics. Currently, organoids have been used for the evaluation of drugs for brain, lung, and colon tumors, among others. In the future, tumor organoids will become closer to being considered a better model for studying cancer in clinical practice, as they can accurately mimic the characteristics of tumors, in turn ensuring that the therapeutic response aligns with the clinical response of patients.

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.

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.

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.

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.

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.

Polarization Sensitive Photothermal Mid-Infrared Spectroscopic Imaging of Human Bone Marrow Tissue

Collagen quantity and integrity play an important role in understanding diseases such as myelofibrosis (MF). Label-free mid-infrared spectroscopic imaging (MIRSI) has the potential to quantify collagen while minimizing the subjective variance observed with conventional histopathology. Infrared (IR) spectroscopy with polarization sensitivity provides chemical information while also estimating tissue dichroism. This can potentially aid MF grading by revealing the structure and orientation of collagen fibers. Simultaneous measurement of collagen structure and biochemical properties can translate clinically into improved diagnosis and enhance our understanding of disease progression. In this paper, we present the first report of polarization-dependent spectroscopic variations in collagen from human bone marrow samples. We build on prior work with animal models and extend it to human clinical biopsies with a practical method for high-resolution chemical and structural imaging of bone marrow on clinical glass slides. This is done using a new polarization-sensitive photothermal mid-infrared spectroscopic imaging scheme that enables sample and source independent polarization control. This technology provides 0.5 µm spatial resolution, enabling the identification of thin (≈1 µm) collagen fibers that were not separable using Fourier Transform Infrared (FT-IR) imaging in the fingerprint region at diffraction-limited resolution ( ≈ 5 µm). Finally, we propose quantitative metrics to identify fiber orientation from discrete band images (amide I and amide II) measured under three polarizations. Previous studies have used a pair of orthogonal polarization measurements, which is insufficient for clinical samples since human bone biopsies contain collagen fibers with multiple orientations. Here, we address this challenge and demonstrate that three polarization measurements are necessary to resolve orientation ambiguity in clinical bone marrow samples. This is also the first study to demonstrate the ability to spectroscopically identify thin collagen fibers (≈1 µm diameter) and their orientations, which is critical for accurate grading of human bone marrow fibrosis.

Multiple roles for basement membrane proteins in cancer progression and EMT

Metastasis or the progression of malignancy poses a major challenge in cancer therapy and is the principal reason for increased mortality. The epithelial-Mesenchymal transition (EMT) of the Basement Membrane (BM) allows cells of epithelial phenotype to transform into a mesenchymal-like (quasi-mesenchymal) phenotype and metastasize via the lymphovascular system through a metastatic cascade by intravasation and extravasation. This helps in the progression of carcinoma from the primary site to distant organs. Collagen, laminin, and integrin are the prime components of BM and help in tumor cell metastasis, which makes them ideal cancer drug targets. Further, recent studies have shown that collagen, laminin, and integrin can be used as a biomarker for metastatic cells. In this review, we have summarized the current knowledge of such therapeutics, which are either currently in preclinical or clinical stages and could be promising cancer therapeutics. DATA AVAILABILITY: Not applicable.

Diaphragm muscle fibrosis involves changes in collagen organization with mechanical implications in Duchenne muscular dystrophy

In Duchenne muscular dystrophy (DMD), diaphragm muscle dysfunction results in respiratory insufficiency, a leading cause of death in patients. Increased muscle stiffness occurs with buildup of fibrotic tissue, characterized by excessive accumulation of extracellular matrix (ECM) components such as collagen, and prevents the diaphragm from achieving the excursion lengths required for respiration. However, changes in mechanical properties are not explained by collagen amount alone and we must consider the complex structure and mechanics of fibrotic tissue. The goals of our study were to 1) determine if and how collagen organization changes with the progression of DMD in diaphragm muscle tissue and 2) predict how collagen organization influences the mechanical properties of the ECM. We first visualized collagen structure with scanning electron microscopy (SEM) images and then developed an analysis framework to quantify collagen organization and generate image-based finite-element models. Image analysis revealed increased collagen fiber straightness and alignment in mdx over wild type (WT) at 3 mo (straightness: mdx = 0.976 ± 0.0108, WT = 0.887 ± 0.0309, alignment: mdx = 0.876 ± 0.0333, WT = 0.759 ± 0.0416) and 6 mo (straightness: mdx = 0.942 ± 0.0182, WT = 0.881 ± 0.0163, alignment: mdx = 0.840 ± 0.0315, WT = 0.759 ± 0.0368). Collagen fibers retained a transverse orientation relative to muscle fibers (70°-90°) in all groups. Mechanical models predicted an increase in the transverse relative to longitudinal (muscle fiber direction) stiffness, with stiffness ratio (transverse/longitudinal) increased in mdx over WT at 3 mo (mdx = 5.45 ± 2.04, WT = 1.97 ± 0.670) and 6 mo (mdx = 4.05 ± 0.985, WT = 1.96 ± 0.506). This study revealed changes in diaphragm ECM structure and mechanics during disease progression in the mdx muscular dystrophy mouse phenotype, highlighting the need to consider the role of collagen organization on diaphragm muscle function.NEW & NOTEWORTHY Scanning electron microscopy images of decellularized diaphragm muscle from WT and mdx, Duchenne muscular dystrophy model, mice revealed that collagen fibers in the epimysium are oriented transverse to muscle fibers, with age- and disease-dependent changes in collagen arrangement. Finite-element models generated from these images predicted that changes in collagen arrangement during disease progression influence the mechanical properties of the extracellular matrix. Thus, changes in collagen fiber-level structure are implicated on tissue-level properties during fibrosis.

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.

Osteocytes Influence on Bone Matrix Integrity Affects Biomechanical Competence at Bone-Implant Interface of Bioactive-Coated Titanium Implants in Rat Tibiae

Osseointegration is a prerequisite for the long-term success of implants. Titanium implants are preferred for their biocompatibility and mechanical properties. Nonetheless, the need for early and immediate loading requires enhancing these properties by adding bioactive coatings. In this preclinical study, extracellular matrix properties and cellular balance at the implant/bone interface was examined. Polyelectrolyte multilayers of chitosan and gelatin or with chitosan and Hyaluronic acid fabricated on titanium alloy using a layer-by-layer self-assembly process were compared with native titanium alloy. The study aimed to histologically evaluate bone parameters that correlate to the biomechanical anchorage enhancement resulted from bioactive coatings of titanium implants in a rat animal model. Superior collagen fiber arrangements and an increased number of active osteocytes reflected a significant improvement of bone matrix quality at the bone interface of the chitosan/gelatin-coated titan implants over chitosan/hyaluronic acid-coated and native implants. Furthermore, the numbers and localization of osteoblasts and osteoclasts in the reparative and remodeling phases suggested a better cellular balance in the chitosan/Gel-coated group over the other two groups. Investigating the micro-mechanical properties of bone tissue at the interface can elucidate detailed discrepancies between different promising bioactive coatings of titanium alloys to maximize their benefit in future medical applications.

Stromal architecture directs early dissemination in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDA) is an extremely metastatic and lethal disease. Here, in both murine and human PDA, we demonstrate that extracellular matrix architecture regulates cell extrusion and subsequent invasion from intact ductal structures through tumor-associated collagen signatures (TACS). This results in early dissemination from histologically premalignant lesions and continual invasion from well-differentiated disease, and it suggests TACS as a biomarker to aid in the pathologic assessment of early disease. Furthermore, we show that pancreatitis results in invasion-conducive architectures, thus priming the stroma prior to malignant disease. Analysis in potentially novel microfluidic-derived microtissues and in vivo demonstrates decreased extrusion and invasion following focal adhesion kinase (FAK) inhibition, consistent with decreased metastasis. Thus, data suggest that targeting FAK or strategies to reengineer and normalize tumor microenvironments may have roles not only in very early disease, but also for limiting continued dissemination from unresectable disease. Likewise, it may be beneficial to employ stroma-targeting strategies to resolve precursor diseases such as pancreatitis in order to remove stromal architectures that increase risk for early dissemination.

Alpha Smooth Muscle Actin (αSMA) Immunohistochemistry Use in the Differentiation of Pancreatic Cancer from Chronic Pancreatitis

Aim: Fibrosis is observed both in pancreatic cancer (PDAC) and chronic pancreatitis (CP). The main cells involved in fibrosis are pancreatic stellate cells (PSCs), which activate alpha smooth muscle actin (αSMA), which is considered to be the best-known fibrosis marker. The aim of the study was to evaluate the expression of the αSMA in patients with PDAC and CP as the possible differentiation marker. Methods: We enrolled 114 patients undergoing pancreatic resection: 83 with PDAC and 31 with CP. Normal fragments of resected specimen from 21 patients represented the control tissue. The immunoexpressions of αSMA were detected in tissue specimens with immunohistochemistry (Abcam antibodies, GB). Results: Mean cytoplasmatic expression of αSMA protein in PDAC stromal cells was significantly higher compared to CP: 2.42 ± 0.37 vs 1.95 ± 0.45 (p < 0.01) and control group 0.61 ± 0.45 (p < 0.01). Strong immunoexpression of the αSMA protein was found in the vast majority (80.7%) of patients with PDAC, in about half (58%) of patients with CP, and not at all in healthy tissue. The expression of αSMA of different intensity was found in all patients with PDAC and CP, while in healthy tissue was minimal or absent. In PDAC patients, αSMA expression was significantly higher in tumors of diameter higher than 3 cm compared to smaller ones (p = 0.017). Conclusions: Presented findings confirm the significant role of fibrosis in both PDAC and CP; however, they do not confirm the role of αSMA as a marker of differentiation.

Targeting Tumor-Stromal Interactions in Pancreatic Cancer: Impact of Collagens and Mechanical Traits

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst outcomes among cancers with a 5-years survival rate of below 10%. This is a result of late diagnosis and the lack of effective treatments. The tumor is characterized by a highly fibrotic stroma containing distinct cellular components, embedded within an extracellular matrix (ECM). This ECM-abundant tumor microenvironment (TME) in PDAC plays a pivotal role in tumor progression and resistance to treatment. Cancer-associated fibroblasts (CAFs), being a dominant cell type of the stroma, are in fact functionally heterogeneous populations of cells within the TME. Certain subtypes of CAFs are the main producer of the ECM components of the stroma, with the most abundant one being the collagen family of proteins. Collagens are large macromolecules that upon deposition into the ECM form supramolecular fibrillar structures which provide a mechanical framework to the TME. They not only bring structure to the tissue by being the main structural proteins but also contain binding domains that interact with surface receptors on the cancer cells. These interactions can induce various responses in the cancer cells and activate signaling pathways leading to epithelial-to-mesenchymal transition (EMT) and ultimately metastasis. In addition, collagens are one of the main contributors to building up mechanical forces in the tumor. These forces influence the signaling pathways that are involved in cell motility and tumor progression and affect tumor microstructure and tissue stiffness by exerting solid stress and interstitial fluid pressure on the cells. Taken together, the TME is subjected to various types of mechanical forces and interactions that affect tumor progression, metastasis, and drug response. In this review article, we aim to summarize and contextualize the recent knowledge of components of the PDAC stroma, especially the role of different collagens and mechanical traits on tumor progression. We furthermore discuss different experimental models available for studying tumor-stromal interactions and finally discuss potential therapeutic targets within the stroma.

Cold exposure and capsaicin promote 1,2-dimethylhyrazine-induced colon carcinogenesis in rats correlates with extracellular matrix remodeling

BACKGROUND

Extracellular matrix (ECM) remodeling and stiffening, which are correlated with tumor malignancy, drives tumor development. However, the relationship between ECM remodeling and rat experimental model of 1,2-dimethylhyrazine (DMH)-induced colorectal cancer (CRC) imposed by cold and capsaicin exposure remains unclear.

AIM

To explore the effects of cold exposure and capsaicin on ECM remodeling and ECM enzymes in DMH-induced CRC.

METHODS

For histopathological analysis, the sections of colon tissues were stained with hematoxylin and eosin, Masson’s trichrome, Picrosirius red, and Weigert’s Resorcin-Fuchsin to observe the remodeling of collagen and elastin. Additionally, the protein expression level of type I collagen (COL I), type 3 collagen (COL III0, elastin, matrix metalloproteinase (MMP) 1, MMP2, MMP9, and tissue-specific matrix metalloproteinase 1 (TIMP1) was assessed by immunohistochemistry. The messenger RNA (mRNA) levels of COL I, COL III, elastin, and lysyl oxidase-like-2 (LOXL2) in the colon tissues of rats was measured by reverse-transcriptase quantitative polymerase chain reaction.

RESULTS

Although no differences were observed in the proportion of adenomas, a trend towards the increase of invasive tumors was observed in the cold and capsaicin group. The cold exposure group had a metastasis rate compared with the other groups. Additionally, abnormal accumulation of both collagen and elastin was observed in the cold exposure and capsaicin group. Specifically, collagen quantitative analysis showed increased length, width, angle, and straightness compared with the DMH group. Collagen deposition and straightness were significantly increased in the cold exposure group compared with the capsaicin group. Cold exposure and capsaicin significantly increased the protein levels of COL I, elastin, and LOXL2 along with increases in their mRNA levels in the colon tissues compared with the DMH group, while COL III did not show a significant difference. Furthermore, in immunohistochemical evaluations, MMP1, MMP2, MMP9, and TIMP1 staining increased in the cold exposure and capsaicin group compared with the DMH group.

CONCLUSION

These results suggest that chronic cold and capsaicin exposure further increased the deposition of collagen and elastin in the colonic tissue. Increased COL I and elastin mRNA and protein levels expression may account for the enhanced ECM remodel and stiffness variations of colon tissue. The upregulated expression of the LOXL2 and physiological imbalance between MMP/TIMP activation and deactivation could contribute to the progression of the CRC resulting from cold and capsaicin exposure.

Aligned forces: Origins and mechanisms of cancer dissemination guided by extracellular matrix architecture

Organized extracellular matrix (ECM), in the form of aligned architectures, is a critical mediator of directed cancer cell migration by contact guidance, leading to metastasis in solid tumors. Current models suggest anisotropic force generation through the engagement of key adhesion and cytoskeletal complexes drives contact-guided migration. Likewise, disrupting the balance between cell-cell and cell-ECM forces, driven by ECM engagement for cells at the tumor-stromal interface, initiates and drives local invasion. Furthermore, processes such as traction forces exerted by cancer and stromal cells, spontaneous reorientation of matrix-producing fibroblasts, and direct binding of ECM modifying proteins lead to the emergence of collagen alignment in tumors. Thus, as we obtain a deeper understanding of the origins of ECM alignment and the mechanisms by which it is maintained to direct invasion, we are poised to use the new paradigm of stroma-targeted therapies to disrupt this vital axis of disease progression in solid tumors.

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.

Role of mechanosensitive ion channel Piezo1 in tumors

A better understanding of mechanotransduction mechanisms is the key to exploring biomechanical signal-regulated tumor malignant characteristics, and it is also the theoretical and practical basis for effective intervention from the upstream of mechanical cues. The discovery of the novel mechanosensitive ion channel protein Piezo1 (piezo type mechanosensitive ion channel component 1) provides a new perspective for the study of mechanotransduction mechanism in tumors. This article summarizes some of the latest research progress of Piezo1 in modulating tumor progression, including inducing cell carcinogenesis; regulating cell cycle, proliferation, invasion, and metastasis; influencing tumor stemness and angiogenesis; as well as reprogramming tumor immune microenvironment, etc.

The functional cross talk between cancer cells and cancer associated fibroblasts from a cancer mechanics perspective

The function of biological tissues in health and disease is regulated at cellular level and is highly influenced by the physical microenvironment, through the interaction of forces between cells and ECM, which are perceived through mechanosensing pathways. In cancer, both chemical and physical signaling cascades and their interactions are involved during cell-cell and cell-ECM communications to meet requirements of tumor growth. Among stroma cells, cancer associated fibroblasts (CAFs) play key role in tumor growth and pave the way for cancer cells to initiate metastasis and invasion to other tissues, and without recruitment of CAFs, the process of cancer invasion is dysfunctional. This is through an intense chemical and physical cross talks with tumor cells, and interactive remodeling of ECM. During such interaction CAFs apply traction forces and depending on the mechanical properties, deform ECM and in return receive physical signals from the micromechanical environment. Such interaction leads to ECM remodeling by manipulating ECM structure and its mechanical properties. The results are in form of deposition of extra fibers, stiffening, rearrangement and reorganization of fibrous structure, and degradation which are due to a complex secretion and expression of different markers triggered by mechanosensing of tumor cells, specially CAFs. Such events define cancer progress and invasion of cancer cells. A systemic knowledge of chemical and physical factors provides a holistic view of how cancer process and enhances the current treatment methods to provide more diversity among targets that involves tumor cells and ECM structure.

Analysis of Colorectal Carcinogenesis Paradigm between Cold Constitution and Heat Constitution: Earlier ECM Collagen Deposition

Colorectal cancer (CRC) is a common malignant tumor around the world. Studying the unique constitution of CRC patients is conducive to the application of personalized medical treatment for CRC. The most common types of constitution in CRC are cold and heat constitution. A previous study has suggested that the malignant progression in cold and heat constitution CRC are different; however, the mechanism remains unclear. The tumor microenvironment (TME) is likely to vary with each individual constitution, which may affect the tumor growth in different constitutions. The extracellular matrix (ECM), the most important component of TME, plays a critical role in disease progression and outcome in patients with CRC. Moreover, collagen, the major component of the ECM, determines the main functional characteristics of ECM and tissue fibrosis caused by collagen deposition, which is one of the signs of CRC malignant progression. This study aimed to explore the mechanisms leading to different colorectal carcinogenesis paradigms between the cold constitution and heat constitution within the context of ECM collagen deposition. We established the CRC rat models and enrolled 30 CRC patients with cold and heat constitution. The collagen-related parameters were detected by using Sirius red staining combined with polarized light microscope, and expressions of collagen (COL I and COL III) and lysyl oxidase (LOX and LOXL2) were determined using immunohistochemistry, while the mRNA levels of COL1A1, COL3A1, LOX, and LOXL2 were measured by qRT-PCR. We found that a higher degree of collagen deposition in the cold-constitution group. The results suggest cold and heat constitution may affect the colorectal carcinogenesis paradigm by influencing the early collagen deposition in colon tissue. The study may provide an effective idea for clinicians to improve the prognosis of CRC patients with different constitutions.

Emerging technologies provide insights on cancer extracellular matrix biology and therapeutics

Recent engineering technologies have transformed traditional perspectives of cancer to include the important role of the extracellular matrix (ECM) in recapitulating the malignant behaviors of cancer cells. Novel biomaterials and imaging technologies have advanced our understanding of the role of ECM density, structure, mechanics, and remodeling in tumor cell-ECM interactions in cancer biology and have provided new approaches in the development of cancer therapeutics. Here, we review emerging technologies in cancer ECM biology and recent advances in engineered systems for evaluating cancer therapeutics and provide new perspectives on how engineering tools present an opportunity for advancing the modeling and treatment of cancer. This review offers the cell biology and cancer cell biology communities insight into how engineering tools can improve our understanding of cancer ECM biology and therapeutic development.

Engineered ECM models: Opportunities to advance understanding of tumor heterogeneity

Intratumoral heterogeneity is a negative prognostic factor for cancer and commonly attributed to microenvironment-driven genetic mutations and/or the emergence of cancer stem-like cells. How aberrant extracellular matrix (ECM) remodeling regulates the phenotypic diversity of tumor cells, however, remains poorly understood due in part to a lack of model systems that allow isolating the physicochemical heterogeneity of malignancy-associated ECM for mechanistic studies. Here, we review the compositional, microarchitectural, and mechanical hallmarks of cancer-associated ECM and highlight biomaterials and engineering approaches to recapitulate these properties for in vitro and in vivo studies. Subsequently, we describe how such engineered platforms may be explored to define the spatiotemporal dynamics through which cancer-associated ECM remodeling regulates intratumoral heterogeneity and the cancer stem-like cell phenotype. Finally, we highlight future opportunities and technological advances to further elucidate the relationship between tumor-associated ECM dynamics and intratumoral heterogeneity.

Multiphoton tomography in differentiation of morphological and molecular subtypes of breast cancer: A quantitative analysis

In this study multiphoton tomography, based on second harmonic generation (SHG), and two-photon-excited fluorescence (TPEF) was used to visualize both the extracellular matrix and tumor cells in different morphological and molecular subtypes of human breast cancer. It was shown, that quantified assessment of the SHG based imaging data has great potential to reveal differences of collagen quantity, organization and uniformity in both low- and highly- aggressive invasive breast cancers. The values of quantity and uniformity of the collagen fibers distribution were significantly higher in low-aggressive breast cancer compared to the highly-aggressive subtypes, while the value representing collagen organization was lower in the former type. Additionally, it was shown, that TPEF detection of elastin fibers and amyloid protein may be used as a biomarker of detection the low-aggressive breast cancer subtype. Thus, TPEF/SHG imaging offers the possibility of becoming a useful tool for the rapid diagnosis of various subtypes of breast cancer during biopsy as well as for the intraoperative determinination of tumor-positive resection margins.

Collagen molecular phenotypic switch between non-neoplastic and neoplastic canine mammary tissues

In spite of major advances over the past several decades in diagnosis and treatment, breast cancer remains a global cause of morbidity and premature death for both human and veterinary patients. Due to multiple shared clinicopathological features, dogs provide an excellent model of human breast cancer, thus, a comparative oncology approach may advance our understanding of breast cancer biology and improve patient outcomes. Despite an increasing awareness of the critical role of fibrillar collagens in breast cancer biology, tumor-permissive collagen features are still ill-defined. Here, we characterize the molecular and morphological phenotypes of type I collagen in canine mammary gland tumors. Canine mammary carcinoma samples contained longer collagen fibers as well as a greater population of wider fibers compared to non-neoplastic and adenoma samples. Furthermore, the total number of collagen cross-links enriched in the stable hydroxylysine-aldehyde derived cross-links was significantly increased in neoplastic mammary gland samples compared to non-neoplastic mammary gland tissue. The mass spectrometric analyses of type I collagen revealed that in malignant mammary tumor samples, lysine residues, in particular those in the telopeptides, were markedly over-hydroxylated in comparison to non-neoplastic mammary tissue. The extent of glycosylation of hydroxylysine residues was comparable among the groups. Consistent with these data, expression levels of genes encoding lysyl hydroxylase 2 (LH2) and its molecular chaperone FK506-binding protein 65 were both significantly increased in neoplastic samples. These alterations likely lead to an increase in the LH2-mediated stable collagen cross-links in mammary carcinoma that may promote tumor cell metastasis in these patients.

Nanofibrillar Hydrogel Recapitulates Changes Occurring in the Fibrotic Extracellular Matrix

Fibrosis is a pathological condition that leads to excessive deposition of collagen and increased tissue stiffness. Understanding the mechanobiology of fibrotic tissue necessitates the development of effective in vitro models that recapitulate its properties and structure; however, hydrogels that are currently used for this purpose fail to mimic the filamentous structure and mechanical properties of the fibrotic extracellular matrix (ECM). Here, we report a nanofibrillar hydrogel composed of cellulose nanocrystals and gelatin, which addresses this challenge. By altering the composition of the hydrogel, we mimicked the changes in structure, mechanical properties, and chemistry of fibrotic ECM. Furthermore, we decoupled the variations in hydrogel structure, properties, and ligand concentration. We demonstrate that this biocompatible hydrogel supports the three-dimensional culture of cells relevant to fibrotic diseases. This versatile hydrogel can be used for in vitro studies of fibrosis of different tissues, thus enabling the development of novel treatments for fibrotic diseases.

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.

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

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