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

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BACKGROUND

Most of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients.

METHODS

We collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC).

RESULTS

In predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556-0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction.

CONCLUSIONS

Our results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.

Collagen modifications predictive of lymph node metastasis in dogs with carcinoma in mixed tumours

Introduction

Mixed tumours in the canine mammary gland are the most common histological type in routine diagnosis. In general, these neoplasms have a favourable prognosis that does not evolve into metastatic disease. However, some cases develop into lymph node metastases and are associated with worse patient survival rates.

Methods

Here is a retrospective study of 46 samples of primary mixed tumours of the canine mammary gland: 15 cases of benign mixed tumours (BMT), 16 cases of carcinoma in mixed tumours without lymph node metastasis (CMT), and 15 cases of carcinomas in mixed tumours with lymph node metastasis (CMTM). In addition, we selected 23 cases of normal mammary glands (NMT) for comparison. The samples were collected from biopsies performed during nodulectomy, simple mastectomy, regional mastectomy, or unilateral/bilateral radical mastectomy. We used multiphoton microscopy, second harmonic generation, and two-photon excited fluorescence, to evaluate the characteristics of collagen fibres and cellular components in biopsies stained with haematoxylin and eosin. We performed Ki67, ER, PR, and HER-2 immunostaining to define the immunophenotype and COX-2. We showed that carcinomas that evolved into metastatic disease (CMTM) present shorter and wavier collagen fibres as compared to CMT.

Results and discussion

When compared to NMT and BMT the carcinomas present a smaller area of fibre coverage, a larger area of cellular coverage, and a larger number of individual fibres. Furthermore, we observed a correlation between the strong expression of COX-2 and a high rate of cell proliferation in carcinomas with a smaller area covered by cell fibres and a larger number of individual fibres. These findings highlight the fundamental role of collagen during tumour progression, especially in invasion and metastatic dissemination.

Tumor matrix stiffness provides fertile soil for cancer stem cells

Matrix stiffness is a mechanical characteristic of the extracellular matrix (ECM) that increases from the tumor core to the tumor periphery in a gradient pattern in a variety of solid tumors and can promote proliferation, invasion, metastasis, drug resistance, and recurrence. Cancer stem cells (CSCs) are a rare subpopulation of tumor cells with self-renewal, asymmetric cell division, and differentiation capabilities. CSCs are thought to be responsible for metastasis, tumor recurrence, chemotherapy resistance, and consequently poor clinical outcomes. Evidence suggests that matrix stiffness can activate receptors and mechanosensor/mechanoregulator proteins such as integrin, FAK, and YAP, modulating the characteristics of tumor cells as well as CSCs through different molecular signaling pathways. A deeper understanding of the effect of matrix stiffness on CSCs characteristics could lead to development of innovative cancer therapies. In this review, we discuss how the stiffness of the ECM is sensed by the cells and how the cells respond to this environmental change as well as the effect of matrix stiffness on CSCs characteristics and also the key malignant processes such as proliferation and EMT. Then, we specifically focus on how increased matrix stiffness affects CSCs in breast, lung, liver, pancreatic, and colorectal cancers. We also discuss how the molecules responsible for increased matrix stiffness and the signaling pathways activated by the enhanced stiffness can be manipulated as a therapeutic strategy for cancer.

Prostate cancer tissue classification by multiphoton imaging, automated image analysis and machine learning

Prostate carcinoma, a slow-growing and often indolent tumour, is the second most commonly diagnosed cancer among men worldwide. The prognosis is mainly based on the Gleason system through prostate biopsy analysis. However, new treatment and monitoring strategies depend on a more precise diagnosis. Here, we present results by multiphoton imaging for prostate tumour samples from 120 patients that allow to obtain quantitative parameters leading to specific tumour aggressiveness signatures. An automated image analysis was developed to recognise and quantify stromal fibre and neoplastic cell regions in each image. The set of metrics was able to distinguish between non-neoplastic tissue and carcinoma areas by linear discriminant analysis and random forest with accuracy of 89% ± 3%, but between Gleason groups of only 46% ± 6%. The reactive stroma analysis improved the accuracy to 65% ± 5%, clearly demonstrating that stromal parameters should be considered as additional criteria for a more accurate diagnosis.

Tumor-restrictive type III collagen in the breast cancer microenvironment: prognostic and therapeutic implications

Collagen plays a critical role in regulating breast cancer progression and therapeutic resistance. An improved understanding of both the features and drivers of tumor-permissive and -restrictive collagen matrices are critical to improve prognostication and develop more effective therapeutic strategies. In this study, using a combination of in vitro, in vivo and in silico experiments, we show that type III collagen (Col3) plays a tumor-restrictive role in human breast cancer. We demonstrate that Col3-deficient, human fibroblasts produce tumor-permissive collagen matrices that drive cell proliferation and suppress apoptosis in noninvasive and invasive breast cancer cell lines. In human TNBC biopsy samples, we demonstrate elevated deposition of Col3 relative to type I collagen (Col1) in noninvasive compared to invasive regions. Similarly, in silico analyses of over 1000 breast cancer patient biopsies from The Cancer Genome Atlas BRCA cohort revealed that patients with higher Col3:Col1 bulk tumor expression had improved overall, disease-free and progression-free survival relative to those with higher Col1:Col3 expression. Using an established 3D culture model, we show that Col3 increases spheroid formation and induces formation of lumen-like structures that resemble non-neoplastic mammary acini. Finally, our in vivo study shows co-injection of murine breast cancer cells (4T1) with rhCol3-supplemented hydrogels limits tumor growth and decreases pulmonary metastatic burden compared to controls. Taken together, these data collectively support a tumor-suppressive role for Col3 in human breast cancer and suggest that strategies that increase Col3 may provide a safe and effective modality to limit recurrence in breast cancer patients.

Transcriptomic Profile of Canine Mammary Ductal Carcinoma

Dogs can be excellent models for spontaneous studies about breast cancers, presenting similarities in clinical behavior and molecular pathways of the disease. Thus, analyses of the canine transcriptome can identify deregulated genes and pathways, contributing to the identification of biomarkers and new therapeutic targets, benefiting humans and animals. In this context, this study aimed to determine the transcriptional profile of canine mammary ductal carcinoma and contribute to the clarification of the importance of deregulated molecules in the molecular pathways involved in the disease. Therefore, we used mammary ductal carcinoma tissue samples and non-tumor mammary tissue from the radical mastectomy of six female dogs. Sequencing was performed on the NextSeq-500 System platform. A comparison of carcinoma tissue and normal tissue revealed 633 downregulated and 573 upregulated genes, which were able to differentiate the groups by principal component analysis. Gene ontology analysis indicated that inflammatory, cell differentiation and adhesion, and extracellular matrix maintenance pathways were mainly deregulated in this series. The main differentially expressed genes observed in this research can indicate greater disease aggressiveness and worse prognosis. Finally, the study of the canine transcriptome indicates that it is an excellent model to generate information relevant to oncology in both species.

The extracellular matrix protein pattern in the canine neoplastic mammary gland

Extracellular matrix (ECM) proteins in the mammary gland provide structure and regulate its development and homeostasis. Alterations in its structure can regulate and support pathogenesis, like breast tumors. Aiming to identify the health and tumoral canine mammary ECM scaffold protein profile by immunohistochemistry, the decellularization process was carried out to remove the cellular content. Additionally, it was verified the influence of health and tumoral ECM on the attachment of health and tumoral cells. The types I, III, IV, and V structural collagens were scarce in the mammary tumor, and ECM fibers were disorganized. Vimentin and CD44 were more common in mammary tumor stroma, suggesting a role in cell migration that results in tumor progression. Elastin, fibronectin, laminin, vitronectin, and osteopontin were similarly detected under healthy and tumor conditions, providing the attachment of normal cells in healthy ECM, while tumoral cells were able to attach in tumoral ECM. The protein pattern demonstrates ECM alteration in canine mammary tumorigenesis, presenting new knowledge on mammary tumor ECM microenvironment.

Strain and Shear-Wave Elastography and Their Relationship to Histopathological Features of Canine Mammary Nodular Lesions

Mammary gland tumours have a significant impact on the health of dogs, requiring diagnostic tools to support clinicians to develop appropriate therapeutic strategies. Sonoelastography is an emerging technology that is able to define the stiffness of the tissue and has promising applications in the evaluation of mammary gland lesions. In the present study, strain elastography (STE) and shear-wave (SWE) elastography were compared in 38 mammary nodular lesions for their ability to define the histopathological features of canine mammary lesions. Among the techniques, SWE showed better repeatability (intraclass correlation coefficient: 0.876), whereas STE was found to be only acceptable (intraclass correlation coefficient: 0.456). Mammary nodular lesions showed a wide range of tissue stiffening with a similar mean value for STE and SWE in benign (4 ± 0.3 and 115.4 ± 12.6 kPa, respectively) and malignant lesions (3.8 ± 0.1 and 115.5 ± 4.5 kPa, respectively). A significant correlation was found between lesion fibrosis and STE (STE-I: r = 0.513, p < 0.001; STE-R: r = 0.591, p < 0.001) or SWE-S (r = 0.769; p < 0.001). In conclusion, SWE was reliable and correlated with fibrosis and was similar for both benign and malignant lesions, suggesting that other collateral diagnostic techniques should be considered in conjunction with SWE to characterize mammary nodular lesions in dogs.

Remodelling of the fibre-aggregate structure of collagen gels by cancer-associated fibroblasts: A time-resolved grey-tone image analysis based on stochastic modelling

Introduction

Solid tumors consist of tumor cells associated with stromal and immune cells, secreted factors and extracellular matrix (ECM), which together constitute the tumor microenvironment. Among stromal cells, activated fibroblasts, known as cancer-associated fibroblasts (CAFs) are of particular interest. CAFs secrete a plethora of ECM components including collagen and modulate the architecture of the ECM, thereby influencing cancer cell migration. The characterization of the collagen fibre network and its space and time-dependent microstructural modifications is key to investigating the interactions between cells and the ECM. Developing image analysis tools for that purpose is still a challenge because the structural complexity of the collagen network calls for specific statistical descriptors. Moreover, the low signal-to-noise ratio of imaging techniques available for time-resolved studies rules out standard methods based on image segmentation.

Methods

In this work, we develop a novel approach based on the stochastic modelling of the gel structure and on grey-tone image analysis. The method is then used to study the remodelling of a collagen matrix by migrating breast cancer-derived CAFs in a three-dimensional spheroid model of cellular invasion imaged by time-lapse confocal microscopy.

Results

The structure of the collagen at the scale of a few microns consists in regions with high fibre density separated by depleted regions, which can be thought of as aggregates and pores. The approach developped captures this two-scale structure with a clipped Gaussian field model to describe the aggregates-and-pores large-scale structure, and a homogeneous Boolean model to describe the small-scale fibre network within the aggregates. The model parameters are identified by fitting the grey-tone histograms and correlation functions of the images. The method applies to unprocessed grey-tone images, and it can therefore be used with low magnification, noisy time-lapse reflectance images. When applied to the CAF spheroid time-resolved images, the method reveals different matrix densification mechanisms for the matrix in direct contact or far from the cells.

Conclusion

We developed a novel and multidisciplinary image analysis approach to investigate the remodelling of fibrillar collagen in a 3D spheroid model of cellular invasion. The specificity of the method is that it applies to the unprocessed grey-tone images, and it can therefore be used with noisy time-lapse reflectance images of non-fluorescent collagen. When applied to the CAF spheroid time-resolved images, the method reveals different matrix densification mechanisms for the matrix in direct contact or far from the cells.

Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer

BACKGROUND

Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.

METHODS

In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS).

RESULTS

TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts).

CONCLUSION

These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

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.

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.

Canine mammary cancer tumour behaviour and patient survival time are associated with collagen fibre characteristics

Precise diagnosis and prognosis are key in prevention and reduction of morbidity and mortality in all types of cancers. Here we show that changes in the collagen fibres in the main histological subtypes of canine mammary gland carcinomas are directly associated with the tumour behaviour and the animal survival time and could become a useful tool in helping with diagnosis. Imaging by second harmonic generation and multiphoton excited fluorescence microscopy were performed to evaluate the collagen and cellular segment parameters in cancer biopsies. We present a retrospective study of 45 cases of canine mammary cancer analysing 836 biopsies regions including normal mammary gland tissue, benign mixed tumours, carcinoma in mixed tumour, carcinosarcoma, micropapillary carcinoma and solid carcinoma. The image analyses and the comparison between the tumour types allowed to assess the collagen fibre changes during tumour progression. We demonstrate that the collagen parameters correlate with the clinical and pathological data, the results show that in neoplastic tissues, the collagen fibres are more aligned and shorter as compared to the normal tissues. There is a clear association of the mean fibre length with the dogs survival times, the carcinomas presenting shorter collagen fibres indicate a worse survival rate.

Expression of Periostin in Cancer-associated Fibroblasts in Mammary Cancer in Female Dogs

BACKGROUND/AIM

Mammary neoplasms, like breast neoplasms in women, are one of the most common tumours in female dogs. Cancer-associated fibroblasts (CAFs) found in the tumour stroma play a role in angiogenesis and increase cell migration, contributing to tumour growth and progression, as well as metastasis. The aim of our work was to determine the level of periostin (POSTN) expression in CAFs in mammary tumours of female dogs.

MATERIALS AND METHODS

The research material consisted of 77 carcinomas and 24 adenomas of the mammary ridge in female dogs. Immunohistochemistry tests were performed using antibodies directed against the antigens POSTN, Ki-67, ERB-B2 receptor tyrosine kinase 2 (HER2), vimentin, and alpha smooth muscle actin (αSMA). Expression of POSTN at the mRNA level was determined using real-time polymerase chain reaction methods in 20 cases of mammary neoplasms.

RESULTS

Expression of POSTN in CAFs was observed in 92% of mammary cancer samples and in 25% of mammary adenoma samples in female dogs. A statistically significant increase in POSNT expression in CAFs was found in the carcinomas compared with mammary adenomas in female dogs. Expression of POSTN in CAFs in mammary carcinomas in female dogs positively correlated with the histological malignancy grade of tumours and the expression of Ki-67 proliferative antigen.

CONCLUSION

Our results suggest a role of POSTN on the pathogenesis of mammary tumours in female dogs. Moreover, POSTN may prove to be a useful marker in the evaluation of cancerous stroma of mammary tumours in female dogs, and may have prognostic significance.

Regulation of extracellular matrix assembly and structure by hybrid M1/M2 macrophages

Aberrant extracellular matrix (ECM) assembly surrounding implanted biomaterials is the hallmark of the foreign body response, in which implants become encapsulated in thick fibrous tissue that prevents their proper function. While macrophages are known regulators of fibroblast behavior, how their phenotype influences ECM assembly and the progression of the foreign body response is poorly understood. In this study, we used in vitro models with physiologically relevant macrophage phenotypes, as well as controlled release of macrophage-modulating cytokines from gelatin hydrogels implanted subcutaneously in vivo to investigate the role of macrophages in ECM assembly. Primary human macrophages were polarized to four distinct phenotypes, which have each been associated with fibrosis, including pro-inflammatory M1, pro-healing M2, and a hybrid M1/M2, generated by exposing macrophages to M1-and M2-promoting stimuli simultaneously. Additionally, macrophages were first polarized to M1 and then to M2 (M1→M2) to generate a phenotype typically observed during normal wound healing. Human dermal fibroblasts that were cultured in macrophage-conditioned media upregulated numerous genes involved in regulation of ECM assembly, especially in M2-conditioned media. Hybrid M1/M2 macrophage-conditioned media caused fibroblasts to produce a matrix with thicker and less aligned fibers, while M2 macrophage-conditioned media caused the formation of a more aligned matrix with thinner fibers. Gelatin methacrylate hydrogels containing interleukin-4 (IL4) and IL13-loaded poly(lactic-co-glycolic acid) (PLGA) microparticles were designed to promote the M2 phenotype in a murine subcutaneous in vivo model. NanoString multiplex gene expression analysis of hydrogel explants showed that hydrogels without cytokines caused mostly M1 phenotype markers to be highly expressed at an early time point (3 days), but the release of IL4+IL13 promoted upregulation of M2 markers and genes associated with regulation of ECM assembly, such as Col5a1 and Col6a1. Biochemical analysis and second harmonic generation microscopy showed that the release of IL4+IL13 increased total sulfated glycosaminoglycan content and decreased fibril alignment, which is typically associated with less fibrotic tissue. Together, these results show that hybrid M1/M2 macrophages regulate ECM assembly, and that shifting the balance towards M2 may promote architectural and compositional changes in ECM with enhanced potential for downstream remodeling.

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

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

Canine mammary cancer diagnosis from quantitative properties of nonlinear optical images

We present nonlinear microscopy imaging results and analysis from canine mammary cancer biopsies. Second harmonic generation imaging allows information of the collagen structure in the extracellular matrix that together with the fluorescence of the cell regions of the biopsies form a base for comprehensive image analysis. We demonstrate an automated image analysis method to classify the histological type of canine mammary cancer using a range of parameters extracted from the images. The software developed for image processing and analysis allows for the extraction of the collagen fibre network and the cell regions of the images. Thus, the tissue properties are obtained after the segmentation of the image and the metrics are measured specifically for the collagen and the cell regions. A linear discriminant analysis including all the extracted metrics allowed to clearly separate between the healthy and cancerous tissue with a 91%-accuracy. Also, a 61%-accuracy was achieved for a comparison of healthy and three histological cancer subtypes studied.

Expression of EMT-Related Genes in Hybrid E/M Colorectal Cancer Cells Determines Fibroblast Activation and Collagen Remodeling

Collagen, the main non-cellular component of the extracellular matrix (ECM), is profoundly reorganized during tumorigenesis and has a strong impact on tumor behavior. The main source of collagen in tumors is cancer-associated fibroblasts. Cancer cells can also participate in the synthesis of ECM; however, the contribution of both types of cells to collagen rearrangements during the tumor progression is far from being clear. Here, we investigated the processes of collagen biosynthesis and remodeling in parallel with the transcriptome changes during cancer cells and fibroblasts interactions. Combining immunofluorescence, RNA sequencing, and second harmonic generation microscopy, we have explored the relationships between the ratio of epithelial (E) and mesenchymal (M) components of hybrid E/M cancer cells, their ability to activate fibroblasts, and the contributions of both cell types to collagen remodeling. To this end, we studied (i) co-cultures of colorectal cancer cells and normal fibroblasts in a collagen matrix, (ii) patient-derived cancer-associated fibroblasts, and (iii) mouse xenograft models. We found that the activation of normal fibroblasts that form dense collagen networks consisting of large, highly oriented fibers depends on the difference in E/M ratio in the cancer cells. The more-epithelial cells activate the fibroblasts more strongly, which correlates with a dense and highly ordered collagen structure in tumors in vivo. The more-mesenchymal cells activate the fibroblasts to a lesser degree; on the other hand, this cell line has a higher innate collagen remodeling capacity. Normal fibroblasts activated by cancer cells contribute to the organization of the extracellular matrix in a way that is favorable for migratory potency. At the same time, in co-culture with epithelial cancer cells, the contribution of fibroblasts to the reorganization of ECM is more pronounced. Therefore, one can expect that targeting the ability of epithelial cancer cells to activate normal fibroblasts may provide a new anticancer therapeutic strategy.

Force balancing ACT-IN the tumor microenvironment: Cytoskeletal modifications in cancer and stromal cells to promote malignancy

The tumor microenvironment is a complex milieu that dictates the growth, invasion, and metastasis of cancer cells. Both cancer and stromal cells in the tumor tissue encounter and adapt to a variety of extracellular factors, and subsequently contribute and drive the progression of the disease to more advanced stages. As the disease progresses, a small population of cancer cells becomes more invasive through a complex process known as epithelial-mesenchymal transition, and nearby stromal cells assume a carcinoma associated fibroblast phenotype characterized by enhanced migration, cell contractility, and matrix secretion with the ability to reorganize extracellular matrices. As cells transition into more malignant phenotypes their biophysical properties, controlled by the organization of cytoskeletal proteins, are altered. Actin and its associated proteins are essential modulators and facilitators of these changes. As the cells respond to the cues in the microenvironment, actin driven mechanical forces inside and outside the cells also evolve. Recent advances in biophysical techniques have enabled us to probe these actin driven changes in cancer and stromal cells and demarcate their role in driving changes in the microenvironment. Understanding the underlying biophysical mechanisms that drive cancer progression could provide critical insight on novel therapeutic approaches in the fight against cancer.

Intratumoral collagen signatures predict clinical outcomes in feline mammary carcinoma

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

Tumor-associated collagen signatures: pushing tumor boundaries

In 2006, a new model of invasive breast tumor emerged and, since 2011, is gaining recognition and research momentum. "Tumor-associated collagen signatures" describe 3 distinct layers of collagen which radiate outward in shells from the main body of the tumor. The outermost layer (TACS3) features branches of collagen radiating away from the tumor, 90° perpendicular to the tumor surface. TACS3 increases tumor span and correlates directly with metastasis, though presently difficult to detect in breast tissue. TACS is an emerging model but has been validated by multiple labs in vitro and in vivo, specifically for breast cancer prognostics. Newly recognized and accepted tumor borders will impact both R0 resections and downstream surgical reconstruction. This review aims to comprehensively introduce and connect the ranging literature on linearized collagen of invasive tumor borders. Using PubMed keyword searches containing "aligned," "linear," "oriented," and "organized," we have gathered the studies on TACS, integrated the concept into the clinic, and projected future platforms.

Oncogenic Linear Collagen VI of Invasive Breast Cancer Is Induced by CCL5

The triple-negative breast tumor boundary is made of aligned, linear collagen. The pro-oncogenic impact of linear collagen is well established; however, its mechanism of formation is unknown. An in vitro analogue of the tumor border is created by a co-culture of MDA-MB-231 cells, adipose derived stem cells, and dermal fibroblasts. Decellularization of this co-culture after seven days reveals an extracellular matrix that is linear in fashion, high in pro-oncogenic collagen type VI, and able to promote invasion of reseeded cells. Further investigation revealed linear collagen VI is produced by fibroblasts in response to a paracrine co-culture of adipose derived stem cells and MDA-MB-231, which together secrete high levels of the chemokine CCL5. The addition of monoclonal antibody against CCL5 to the co-culture results in an unorganized matrix with dramatically decreased collagen VI. Importantly, reseeded cells do not exhibit pro-oncogenic behavior. These data illustrate a cellular mechanism, which creates linear extracellular matrix (ECM) in vitro, and highlight a potential role of CCL5 for building striated tumor collagen in vivo.

Microstructural densification and alignment by aspiration-ejection influence cancer cell interactions with three-dimensional collagen networks

Extracellular matrix microstructure and mechanics are crucial to breast cancer progression and invasion into surrounding tissues. The peritumor collagen network is often dense and aligned, features which in vitro models lack. Aspiration of collagen hydrogels led to densification and alignment of microstructure surrounding embedded cancer cells. Two metastasis-derived breast cancer cell lines, MDA-MB-231 and MCF-7, were cultured in initially 4 mg/ml collagen gels for 3 days after aspiration, as well as in unaspirated control hydrogels. Videomicroscopy during aspiration, and at 0, 1, and 3 days after aspiration, epifluorescence microscopy of phalloidin-stained F-actin cytoskeleton, histological sections, and soluble metabolic byproducts from constructs were collected to characterize effects on the embedded cell morphology, the collagen network microstructure, and proliferation. Breast cancer cells remained viable after aspiration-ejection, proliferating slightly less than in unaspirated gels. Furthermore, MDA-MB-231 cells appear to partially relax the collagen network and lose alignment 3 days after aspiration. Aspiration-ejection generated aligned, compact collagen network microstructure with immediate cell co-orientation and higher cell number density apparently through purely physical means, though cell-collagen contact guidance and network remodeling influence cell organization and collagen network microstructure during subsequent culture. This study establishes a platform to determine the effects of collagen density and alignment on cancer cell behavior, with translational potential for anticancer drug screening in a biomimetic three-dimensional matrix microenvironment, or implantation in preclinical models.

Know Thy Model: Charting Molecular Homology in Stromal Reprogramming Between Canine and Human Mammary Tumors

Spontaneous canine simple mammary tumors (CMTs) are often viewed as models of human breast cancer. Cancer-associated stroma (CAS) is central for initiation and progression of human cancer, and is likely to play a key role in canine tumors as well. Until recently, however, canine CAS in general, and in CMT in particular, lacked detailed characterization and it remained unclear how canine and human CAS compare. This void in knowledge regarding canine CAS and the resulting lack of unbiased cross-species analysis of molecular homologies and differences undermined the validity of the canine model for human disease. To assess stromal reprogramming in canine breast tumors, we have recently established a protocol to specifically isolate and analyze CAS and matched normal stroma from archival, formalin-fixed paraffin embedded (FFPE) clinical tumor samples using laser-capture microdissection followed by next-generation RNA-sequencing. Using this approach, we have analyzed stromal reprogramming in both malignant canine mammary carcinomas (mCAs) as well as benign canine mammary adenomas in a series of studies. Our results demonstrate strong stromal reprogramming in CMTs and identify high-grade molecular homology between human and canine CAS. Here, I aim to give a short background on the value of comparative oncology in general, and spontaneous CMT in particular. This will be followed by a concise review of the current knowledge of stromal reprogramming in both malignant canine mCA and benign adenoma. Finally, I will conclude with insights on highly conserved aspects of stromal reprogramming between CMT and human breast cancer that accentuate the relevance of CAS in CMT as a model for the human disease.

Expression frequency of c-kit isoforms and its prognostic potential in canine mammary tumours

KIT is a tyrosine kinase receptor involved in carcinogenesis. Two alternatively spliced transcripts, differed from presence of four amino acids (GNSK) at exon 9 of c-kit, were identified in various human tumours and canine hemangiosarcoma (HSA). The biological function and clinical implications of these isoforms have not yet been elucidated in canine tumours. The current study aimed to validate the expression profile and ultimately to evaluate the correlation of c-kit isoform levels with clinicopathological factors of canine mammary tumours (CMTs). In total, the expression profiles of c-kit isoforms in 196 samples obtained from normal mammary glands (NMGs) of healthy controls and dogs with CMTs, benign and malignant CMTs, and HSAs were determined by polymerase chain reaction (PCR) and quantified via real-time PCR. Overall, the expression levels of the two isoforms were equivalent in NMGs, whereas the GNSK^- /GNSK⁺ ratio sharply increased to 7.44- and 8.33-fold, indicating abundant GNSK^- isoforms in benign and malignant CMTs, respectively. However, a significant decrease in GNSK^- expression was detected in dogs with high-grade malignant CMTs (mCMTs) and with metastatic CMTs compared with expression in those with a lower grade and non-metastatic CMTs. In addition, the median survival time was shorter in mCMT canines with a lower GNSK^- /GNSK⁺ ratio than that in mCMT canines with a higher ratio (899 days vs 1534 days). In conclusion, two c-kit isoforms are ubiquitously expressed with great variability in HSAs and CMTs with both benign and malignant status. The GNSK^- /GNSK⁺ ratio could serve as a prognostic indicator for dogs with mCMTs.

Comparative Approach to the Temporo-Spatial Organization of the Tumor Microenvironment

The complex ecosystem in which tumor cells reside and interact, termed the tumor microenvironment (TME), encompasses all cells and components associated with a neoplasm that are not transformed cells. Interactions between tumor cells and the TME are complex and fluid, with each facet coercing the other, largely, into promoting tumor progression. While the TME in humans is relatively well-described, a compilation and comparison of the TME in our canine counterparts has not yet been described. As is the case in humans, dog tumors exhibit greater heterogeneity than what is appreciated in laboratory animal models, although the current level of knowledge on similarities and differences in the TME between dogs and humans, and the practical implications of that information, require further investigation. This review summarizes some of the complexities of the human and mouse TME and interjects with what is known in the dog, relaying the information in the context of the temporo-spatial organization of the TME. To the authors' knowledge, the development of the TME over space and time has not been widely discussed, and a comprehensive review of the canine TME has not been done. The specific topics covered in this review include cellular invasion and interactions within the TME, metabolic derangements in the TME and vascular invasion, and the involvement of the TME in tumor spread and metastasis.

Regulation of migration of chemotactic tumor cells by the spatial distribution of collagen fiber orientation

Collagen fibers, an important component of the extracellular matrix (ECM), can both inhibit and promote cellular migration. In vitro studies have revealed that the fibers' orientations are crucial to cellular invasion, while in vivo investigations have led to the development of tumor-associated collagen signatures (TACS) as an important prognostic factor. Studying biophysical regulation of cell invasion and the effect of the fibers' orientation not only deepens our understanding of the phenomenon, but also helps classify the TACSs precisely, which is currently lacking. We present a stochastic model for random or chemotactic migration of cells in fibrous ECM, and study the role of the various factors in it. The model provides a framework for quantitative classification of the TACSs, and reproduces quantitatively recent experimental data for cell motility. It also indicates that the spatial distribution of the fibers' orientations and extended correlations between them, hitherto ignored, as well as dynamics of cellular motion all contribute to regulation of the cells' invasion length, which represents a measure of metastatic risk. Although the fibers' orientations trivially affect randomly moving cells, their effect on chemotactic cells is completely nontrivial and unexplored, which we study in this paper.

Characterization of Collagen Fibers (I, III, IV) and Elastin of Normal and Neoplastic Canine Prostatic Tissues

This study aimed to investigate collagen (Coll-I, III, IV) and elastin in canine normal prostate and prostate cancer (PC) using Picrosirius red (PSR) and Immunohistochemical (IHC) analysis. Eight normal prostates and 10 PC from formalin-fixed, paraffin-embedded samples were used. Collagen fibers area was analyzed with ImageJ software. The distribution of Coll-I and Coll-III was approximately 80% around prostatic ducts and acini, 15% among smooth muscle, and 5% surrounding blood vessels, in both normal prostate and PC. There was a higher median area of Coll-III in PC when compared to normal prostatic tissue (p = 0.001 for PSR and p = 0.05 for IHC). Immunostaining for Coll-IV was observed in the basal membrane of prostate acini, smooth muscle, blood vessels, and nerve fibers of normal and PC samples. Although there was no difference in Coll-IV area between normal tissue and PC, tumors with Gleason score 10 showed absence of Coll-IV, when compared to scores 6 and 8 (p = 0.0095). Elastic fibers were found in the septa dividing the lobules and around the prostatic acini of normal samples and were statistically higher in PC compared to normal tissue (p = 0.00229). Investigation of ECM components brings new information and should be correlated with prognosis in future studies.

Current biomarkers of canine mammary tumors

Mammary tumors are the second most common neoplasia in dogs. Due to the high similarity of canine mammary tumors (CMT) to human breast cancers (HBC), human biomarkers of HBC are also detectable in cases of CMT. The evaluation of biomarkers enables clinical diagnoses, treatment options and prognosis for bitches suffering from this disease. The aim of this article is to give a short summary of the biomarkers of CMT based on current literature. Very promising biomarkers are miRNAs, cancer stem cells, and circulating tumor cells, as well as mutations of the breast cancer 1 gene (BRCA1) and breast cancer 2 gene (BRCA2). Until now, the most studied and reliable biomarkers of CMT have remained antigen Ki-67 (Ki-67), endothelial growth factor receptor, human epidermal growth factor receptor 2 (HER-2), estrogen receptor, progesterone receptor and cyclooxygenase 1 (COX-2), which can be detected in both serum and tissue samples using different molecular methods. However, carcinoembryonic antigen and cancer antigen 15-3 (CA 15-3), while poorly studied, seem to be good biomarkers, especially for the early detection and prognosis of CMT. We will also mention the following: proliferative cell nuclear antigen, tumor protein p53 (p53), E-cadherin, vascular endothelial growth factor, microRNAs, cancer stem cells and circulating tumor cells, which can also be useful biomarkers. Although many studies have been conducted so far, the estimation of biomarkers in cases of CMT is still not a common practice, and more detailed research should be done.

Biophysics of Tumor Microenvironment and Cancer Metastasis - A Mini Review

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

Biomimetic tumor microenvironments based on collagen matrices

This review provides an overview of the current approaches to engineer defined 3D matrices for the investigation of tumor cell behaviorin vitro, with a focus on collagen-based fibrillar systems.