Assessing the roles of collagen fiber morphology and matrix stiffness on ovarian cancer cell migration dynamics using multiphoton fabricated orthogonal image-based models

Multiphoton excited polymerized biomimetic models of collagen fiber morphology to study single cell and collective migration dynamics in pancreatic cancer

The respective roles of aligned collagen fiber morphology found in the extracellular matrix (ECM) of pancreatic cancer patients and cellular migration dynamics have been gaining attention because of their connection with increased aggressive phenotypes and poor prognosis. To better understand how collagen fiber morphology influences cell-matrix interactions associated with metastasis, we used Second Harmonic Generation (SHG) images from patient biopsies with Pancreatic ductal adenocarcinoma (PDAC) as models to fabricate collagen scaffolds to investigate processes associated with motility. Using the PDAC BxPC-3 metastatic cell line, we investigated single and collective cell dynamics on scaffolds of varying collagen alignment. Collective or clustered cells grown on the scaffolds with the highest collagen fiber alignment had increased E-cadherin expression and larger focal adhesion sites compared to single cells, consistent with metastatic behavior. Analysis of single cell motility revealed that the dynamics were characterized by random walk on all substrates. However, examining collective motility over different time points showed that the migration was super-diffusive and enhanced on highly aligned fibers, whereas it was hindered and sub-diffusive on un-patterned substrates. This was further supported by the more elongated morphology observed in collectively migrating cells on aligned collagen fibers. Overall, this approach allows the decoupling of single and collective cell behavior as a function of collagen alignment and shows the relative importance of collective cell behavior as well as fiber morphology in PDAC metastasis. We suggest these scaffolds can be used for further investigations of PDAC cell biology. STATEMENT OF SIGNIFICANCE: Pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate, where aligned collagen has been associated with poor prognosis. Biomimetic models representing this architecture are needed to understand complex cellular interactions. The SHG image-based models based on stromal collagen from human biopsies afford the measurements of cell morphology, cadherin and focal adhesion expression as well as detailed motility dynamics. Using a metastatic cell line, we decoupled the roles of single cell and collective cell behavior as well as that arising from aligned collagen. Our data suggests that metastatic characteristics are enhanced by increased collagen alignment and that collective cell behavior is more relevant to metastatic processes. These scaffolds provide new insight in this disease and can be a platform for further experiments such as testing drug efficacy.

Systemic low-dose anti-fibrotic treatment attenuates ovarian aging in the mouse

The female reproductive system is one of the first to age in humans, resulting in infertility and endocrine disruptions. The aging ovary assumes a fibro-inflammatory milieu which negatively impacts gamete quantity and quality as well as ovulation. Here, we tested whether the systemic delivery of anti-inflammatory (Etanercept) or anti-fibrotic (Pirfenidone) drugs attenuates ovarian aging in mice. We first evaluated the ability of these drugs to decrease the expression of fibro-inflammatory genes in primary ovarian stromal cells treated with a pro-fibrotic or a pro-inflammatory stimulus. Whereas Etanercept did not block Tnf expression in ovarian stromal cells, Pirfenidone significantly reduced Col1a1 expression. We then tested Pirfenidone in vivo where the drug was delivered systemically via mini-osmotic pumps for 6 weeks. Pirfenidone mitigated the age-dependent increase in ovarian fibrosis without impacting overall health parameters. Ovarian function was improved in Pirfenidone-treated mice as evidenced by increased follicle and corpora lutea number, AMH levels, and improved estrous cyclicity. Transcriptomic analysis revealed that Pirfenidone treatment resulted in an upregulation of reproductive function-related genes at 8.5 months and a downregulation of inflammatory genes at 12 months of age. These findings demonstrate that reducing the fibroinflammatory ovarian microenvironment improves ovarian function, thereby supporting modulating the ovarian environment as a therapeutic avenue to extend reproductive longevity.

Systemic low-dose anti-fibrotic treatment attenuates ovarian aging in the mouse

The female reproductive system is one of the first to age in humans, resulting in infertility and endocrine disruptions. The aging ovary assumes a fibro-inflammatory milieu which negatively impacts gamete quantity and quality as well as ovulation. Here we tested whether the systemic delivery of anti-inflammatory (Etanercept) or anti-fibrotic (Pirfenidone) drugs attenuates ovarian aging in mice. We first evaluated the ability of these drugs to decrease the expression of fibro-inflammatory genes in primary ovarian stromal cells. Whereas Etanercept did not block Tnf expression in ovarian stromal cells, Pirfenidone significantly reduced Col1a1 expression. We then tested Pirfenidone in vivo where the drug was delivered systemically via mini-osmotic pumps for 6-weeks. Pirfenidone mitigated the age-dependent increase in ovarian fibrosis without impacting overall health parameters. Ovarian function was improved in Pirfenidone-treated mice as evidenced by increased follicle and corpora lutea number, AMH levels, and improved estrous cyclicity. Transcriptomic analysis revealed that Pirfenidone treatment resulted in an upregulation of reproductive function-related genes at 8.5 months and a downregulation of inflammatory genes at 12 months of age. These findings demonstrate that reducing the fibroinflammatory ovarian microenvironment improves ovarian function, thereby supporting modulating the ovarian environment as a therapeutic avenue to extend reproductive longevity.

Shear wave elastography to assess stiffness of the human ovary and other reproductive tissues across the reproductive lifespan in health and disease†

The ovary is one of the first organs to show overt signs of aging in the human body, and ovarian aging is associated with a loss of gamete quality and quantity. The age-dependent decline in ovarian function contributes to infertility and an altered endocrine milieu, which has ramifications for overall health. The aging ovarian microenvironment becomes fibro-inflammatory and stiff with age, and this has implications for ovarian physiology and pathology, including follicle growth, gamete quality, ovulation dynamics, and ovarian cancer. Thus, developing a non-invasive tool to measure and monitor the stiffness of the human ovary would represent a major advance for female reproductive health and longevity. Shear wave elastography is a quantitative ultrasound imaging method for evaluation of soft tissue stiffness. Shear wave elastography has been used clinically in assessment of liver fibrosis and characterization of tendinopathies and various neoplasms in thyroid, breast, prostate, and lymph nodes as a non-invasive diagnostic and prognostic tool. In this study, we review the underlying principles of shear wave elastography and its current clinical uses outside the reproductive tract as well as its successful application of shear wave elastography to reproductive tissues, including the uterus and cervix. We also describe an emerging use of this technology in evaluation of human ovarian stiffness via transvaginal ultrasound. Establishing ovarian stiffness as a clinical biomarker of ovarian aging may have implications for predicting the ovarian reserve and outcomes of Assisted Reproductive Technologies as well as for the assessment of the efficacy of emerging therapeutics to extend reproductive longevity. This parameter may also have broad relevance in other conditions where ovarian stiffness and fibrosis may be implicated, such as polycystic ovarian syndrome, late off target effects of chemotherapy and radiation, premature ovarian insufficiency, conditions of differences of sexual development, and ovarian cancer. Summary sentence:  Shear Wave Elastography is a non-invasive technique to study human tissue stiffness, and here we review its clinical applications and implications for reproductive health and disease.

Nomograms integrating the collagen signature and systemic immune-inflammation index for predicting prognosis in rectal cancer patients

BACKGROUND

This study aimed to develop and validate a model based on the collagen signature and systemic immune-inflammation index to predict prognosis in rectal cancer patients who underwent neoadjuvant treatment.

METHODS

Patients with rectal cancer who had residual disease after neoadjuvant treatment at two Chinese institutions between 2010 and 2018 were selected, one used as a training cohort and the other as a validation cohort. In total, 142 fully quantitative collagen features were extracted using multiphoton imaging, and a collagen signature was generated by least absolute shrinkage and selection operator Cox regression. Nomograms were developed by multivariable Cox regression. The performance of the nomograms was assessed via calibration, discrimination and clinical usefulness. The outcomes of interest were overall survival and disease-free survival calculated at 1, 2 and 3 years.

RESULTS

Of 559 eligible patients, 421 were selected (238 for the training cohort and 183 for the validation cohort). The eight-collagen-features collagen signature was built and multivariable Cox analysis demonstrated that it was an independent prognostic factor of prognosis along with the systemic immune-inflammation index, lymph node status after neoadjuvant treatment stage and tumour regression grade. Then, two nomograms that included the four predictors were computed for disease-free survival and overall survival. The nomograms showed satisfactory discrimination and calibration with a C-index of 0.792 for disease-free survival and 0.788 for overall survival in the training cohort and 0.793 for disease-free survival and 0.802 for overall survival in the validation cohort. Decision curve analysis revealed that the nomograms could add more net benefit than the traditional clinical-pathological variables.

CONCLUSIONS

The study found that the collagen signature, systemic immune-inflammation index and nomograms were significantly associated with prognosis.

Thermally reversible hydrogels printing of customizable bio-channels with curvature

Replicating intricate bio-channels, akin to expansive vascular networks, offers numerous advantages including self-repair, replacing damaged bio-channels, testing drugs, and biomedical devices. But, crafting multi-sized, editable bio-channels with specific curvatures, particularly using natural polymer-based bio-inks, poses a significant challenge. To address this, this study introduces a temperature-driven indirect printing method, exemplified by the diploic vein. Here, K-carrageenan (kca)-silk fiber (SF)-hyaluronic acid (HA)/hFOB 1.19 (SV40 transfection of human osteoblasts) and kca-collagen-HA/HUVECs (human umbilical vein endothelial cells) are employed to fabricate vascular-like walls and lumens, utilizing their thermoreversible properties to create multi-stage bifurcated lumens. Precise spatial curvature was generated by heating the vascular network wrapped in poly(N-isopropyl acrylamide) (PNIPAAm)-poly(ethylene glycol) diacrylate (PEGDA). Since temperature is specific to the thermal material carrying the cells, the rheological properties of bioinks, modeling temperature parameters, and their impact on printing size was explored. Additionally, mechanical properties and curvature response were characterized to determine the necessary process parameters for achieving the desired size. Ultimately, in vitro bioprinting experiments involving HUVECs and hFOB 1.19 demonstrate cell viability, adhesion, proliferation, and migration within the intraluminal hydrogel scaffold. This approach allows for customizing bio-channel content and controlling curvature programming, providing new prospects for in vitro biochannel production, with potential benefits for pathology research.

Association of the pathomics-collagen signature with lymph node metastasis in colorectal cancer: a retrospective multicenter study

BACKGROUND

Lymph node metastasis (LNM) is a prognostic biomarker and affects therapeutic selection in colorectal cancer (CRC). Current evaluation methods are not adequate for estimating LNM in CRC. H&E images contain much pathological information, and collagen also affects the biological behavior of tumor cells. Hence, the objective of the study is to investigate whether a fully quantitative pathomics-collagen signature (PCS) in the tumor microenvironment can be used to predict LNM.

METHODS

Patients with histologically confirmed stage I-III CRC who underwent radical surgery were included in the training cohort (n = 329), the internal validation cohort (n = 329), and the external validation cohort (n = 315). Fully quantitative pathomics features and collagen features were extracted from digital H&E images and multiphoton images of specimens, respectively. LASSO regression was utilized to develop the PCS. Then, a PCS-nomogram was constructed incorporating the PCS and clinicopathological predictors for estimating LNM in the training cohort. The performance of the PCS-nomogram was evaluated via calibration, discrimination, and clinical usefulness. Furthermore, the PCS-nomogram was tested in internal and external validation cohorts.

RESULTS

By LASSO regression, the PCS was developed based on 11 pathomics and 9 collagen features. A significant association was found between the PCS and LNM in the three cohorts (P < 0.001). Then, the PCS-nomogram based on PCS, preoperative CEA level, lymphadenectasis on CT, venous emboli and/or lymphatic invasion and/or perineural invasion (VELIPI), and pT stage achieved AUROCs of 0.939, 0.895, and 0.893 in the three cohorts. The calibration curves identified good agreement between the nomogram-predicted and actual outcomes. Decision curve analysis indicated that the PCS-nomogram was clinically useful. Moreover, the PCS was still an independent predictor of LNM at station Nos. 1, 2, and 3. The PCS nomogram displayed AUROCs of 0.849-0.939 for the training cohort, 0.837-0.902 for the internal validation cohort, and 0.851-0.895 for the external validation cohorts in the three nodal stations.

CONCLUSIONS

This study proposed that PCS integrating pathomics and collagen features was significantly associated with LNM, and the PCS-nomogram has the potential to be a useful tool for predicting individual LNM in CRC patients.