Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs

New Endeavors of (Micro)Tissue Engineering: Cells Tissues Organs on-Chip and Communication Thereof

The development of new therapies is tremendously hampered by the insufficient availability of human model systems suitable for preclinical research on disease target identification, drug efficacy, and toxicity. Thus, drug failures in clinical trials are too common and too costly. Animal models or standard 2D in vitro tissue cultures, regardless of whether they are human based, are regularly not representative of specific human responses. Approaching near human tissues and organs test systems is the key goal of organs-on-chips (OoC) technology. This technology is currently showing its potential to reduce both drug development costs and time-to-market, while critically lessening animal testing. OoC are based on human (stem) cells, potentially derived from healthy or disease-affected patients, thereby amenable to personalized therapy development. It is noteworthy that the OoC market potential goes beyond pharma, with the possibility to test cosmetics, food additives, or environmental contaminants. This (micro)tissue engineering-based technology is highly multidisciplinary, combining fields such as (developmental) biology, (bio)materials, microfluidics, sensors, and imaging. The enormous potential of OoC is currently facing an exciting new challenge: emulating cross-communication between tissues and organs, to simulate more complex systemic responses, such as in cancer, or restricted to confined environments, as occurs in osteoarthritis. This review describes key examples of multiorgan/tissue-on-chip approaches, or linked organs/tissues-on-chip, focusing on challenges and promising new avenues of this advanced model system. Additionally, major emphasis is given to the translation of established tissue engineering approaches, bottom up and top down, towards the development of more complex, robust, and representative (multi)organ/tissue-on-chip approaches

Skeletal tissue regeneration: where can hydrogels play a role?

The emerging field of tissue engineering reveals promising approaches for the repair and regeneration of skeletal tissues including the articular cartilage, bone, and the entire joint. Amongst the myriad of biomaterials available to support this strategy, hydrogels are highly tissue mimicking substitutes and thus of great potential for the regeneration of functional tissues. This review comprises an overview of the novel and most promising hydrogels for articular cartilage, osteochondral and bone defect repair. Chondro- and osteo-conductive and -instructive hydrogels are presented, highlighting successful combinations with inductive signals and cell sources. Moreover, advantages, drawbacks, and future perspectives of the role of hydrogels in skeletal regeneration are addressed, pointing out the current state of this rising approach.status: publishe

Hypoxia inhibits hypertrophic differentiation and endochondral ossification in explanted tibiae.

Hypertrophic differentiation of growth plate chondrocytes induces angiogenesis which alleviates hypoxia normally present in cartilage. In the current study, we aim to determine whether alleviation of hypoxia is merely a downstream effect of hypertrophic differentiation as previously described or whether alleviation of hypoxia and consequent changes in oxygen tension mediated signaling events also plays an active role in regulating the hypertrophic differentiation process itself.Fetal mouse tibiae (E17.5) explants were cultured up to 21 days under normoxic or hypoxic conditions (21% and 2.5% oxygen respectively). Tibiae were analyzed on growth kinetics, histology, gene expression and protein secretion.The oxygen level had a strong influence on the development of explanted fetal tibiae. Compared to hypoxia, normoxia increased the length of the tibiae, length of the hypertrophic zone, calcification of the cartilage and mRNA levels of hypertrophic differentiation-related genes e.g. MMP9, MMP13, RUNX2, COL10A1 and ALPL. Compared to normoxia, hypoxia increased the size of the cartilaginous epiphysis, length of the resting zone, calcification of the bone and mRNA levels of hyaline cartilage-related genes e.g. ACAN, COL2A1 and SOX9. Additionally, hypoxia enhanced the mRNA and protein expression of the secreted articular cartilage markers GREM1, FRZB and DKK1, which are able to inhibit hypertrophic differentiation.Collectively our data suggests that oxygen levels play an active role in the regulation of hypertrophic differentiation of hyaline chondrocytes. Normoxia stimulates hypertrophic differentiation evidenced by the expression of hypertrophic differentiation related genes. In contrast, hypoxia suppresses hypertrophic differentiation of chondrocytes, which might be at least partially explained by the induction of GREM1, FRZB and DKK1 expression

Self-attaching and cell-attracting in-situ forming dextran-tyramine conjugates hydrogels for arthroscopic cartilage repair

Small cartilage defects are frequently treated with debridement or left untreated, predisposing to early onset osteoarthritis. We propose to fill these defects with a cell-free injectable hydrogel comprising dextran-tyramine conjugates (Dex-TA) that can be applied during arthroscopic procedures. In this study, we report on the adhesion mechanism between cartilage and Dex-TA hydrogels and enhancement of cell ingrowth by incorporation of Heparin-tyramine (Hep-TA) conjugates. The enzyme-catalyzed crosslinking reaction of Dex-TA and Hep-TA hydrogels is based on covalent bonding of hydroxyphenyl residues. We hypothesized that this reaction results in covalent bonding of the hydroxyphenyl residues in Dex-TA and Hep-TA to tyrosine residues in cartilage matrix proteins. The involvement of TA residues was confirmed by modelling the enzymatic reaction occurring during gelation. The mechanical analysis indicated that higher tyramine content led to stronger binding. Interfacial cartilage-hydrogel morphology and Raman spectroscopy demonstrated collagens’ reorganization and evidenced the coupling of TA to tyrosine residues in collagen. Moreover, the addition of Hep-TA induced cell recruitment. Collectively, in vitro and ex vivo functional studies evidenced the covalent bonding of TA-containing hydrogels to tyrosine residues in cartilaginous matrix proteins. Moreover, the cell-attracting ability of these hydrogels could be explored to guide tissue repair in focal cartilage defects, preventing or delaying the onset osteoarthritis

Chitosan/Poly(ɛ-caprolactone) blend scaffolds for cartilage repair

Chitosan (CHT)/poly(ɛ-caprolactone) (PCL) blend 3D fiber-mesh scaffolds were studied as possible support structures for articular cartilage tissue (ACT) repair. Micro-fibers were obtained by wet-spinning of three different polymeric solutions: 100:0 (100CHT), 75:25 (75CHT) and 50:50 (50CHT) wt.% CHT/PCL, using a common solvent solution of 100 vol.% of formic acid. Scanning electron microscopy (SEM) analysis showed a homogeneous surface distribution of PCL. PCL was well dispersed throughout the CHT phase as analyzed by differential scanning calorimetry and Fourier transform infrared spectroscopy. The fibers were folded into cylindrical moulds and underwent a thermal treatment to obtain the scaffolds. μCT analysis revealed an adequate porosity, pore size and interconnectivity for tissue engineering applications. The PCL component led to a higher fiber surface roughness, decreased the scaffolds swelling ratio and increased their compressive mechanical properties. Biological assays were performed after culturing bovine articular chondrocytes up to 21 days. SEM analysis, live-dead and metabolic activity assays showed that cells attached, proliferated, and were metabolically active over all scaffolds formulations. Cartilaginous extracellular matrix (ECM) formation was observed in all formulations. The 75CHT scaffolds supported the most neo-cartilage formation, as demonstrated by an increase in glycosaminoglycan production. In contrast to 100CHT scaffolds, ECM was homogenously deposited on the 75CHT and 50CHT scaffolds. Although mechanical properties of the 50CHT scaffold were better, the 75CHT scaffold facilitated better neo-cartilage formation

Histological analysis of calcification in explanted tibiae.

<p>(A) Midsagittal sections of tibiae were stained with Alizarin red after explantation or cultured seven days under hypoxic or normoxic conditions. (B) Image analysis was used to determine the length of the intensely calcified tissue, which was taken as the broken line indicated in ‘A’. (C) The area of calcification was used to determine relative calcification of the samples. (D) Higher magnification microphotographs were used to investigate the calcification of the hypertrophic cartilage that resides on top of the intensely stained bone. The dashed line represents the osteochondral interface. (N = 15). * = P<0.05 compared to freshly isolated tibiae. # = P<0.05 compared to normoxic condition of the same time point.</p

Explanted tibiae cultured 21 days under hypoxic or normoxic conditions.

<p>(A) Microphotographs of representative tibiae at different points in time. (B) Using image analysis the average tibiae lengths were calculated. (N = 18). * = P<0.05. ** = P<0.01.</p