ELUCIDATING THE ROLE OF CD44 EXPRESSION ON MESENCHYMAL STEM CELLS WITHIN THE TUMOR MICROENVIRONMENT

The tumor microenvironment is comprised of a vast array of heterogeneous cells including both normal and neoplastic cells. The tumor stroma recruitment process has been exploited for an effective gene delivery technique using bone marrow derived MSC. Targeted migration of the MSC toward the tumor microenvironment, while successful, is not yet fully understood. This study was designed to assess the role of CD44 in the migration of MSC toward the tumor microenvironment and to determine the implications of CD44-deficient MSC within the tumor stroma. Inhibition of MSC migration was evaluated through a variety of methods in vitro and in vivo including CD44 receptor knockdown, CD44 antagonists, CD44 neutralizing antibodies and small molecule inhibitor of matrix metalloproteinases. Blocking CD44 signaling through MMP inhibition was characterized by lack of intracellular domain cleavage and lead to the decrease in Twist gene expression. A functional relationship between CD44 and Twist expression was confirmed by chromatin immunoprecipitation. Next, a series of murine tumor models were used to examine the role of CD44 deficient stroma within the tumor microenvironment. Labeled transgenic CD44 knockout (KO) MSC or wild type (WT) C57/B6 MSC were used to analyze the stromal incorporation within murine breast carcinomas (EO771 and 4T1). Subsequent tumors were analyzed for vessel formation (CD31), and the presence of tumor associated fibroblast (TAF) markers, α-smooth muscle actin (α-SMA), fibroblast activation protein (FAP), and fibroblast specific protein (FSP). The tumors with CD44KO MSC cells had less vessel formation than the tumors with WT MSC. The lack of fibroblastic TAF population as defined by FAP/FSP expression by the CD44KO MSC admixed tumors suggest that the bone marrow derived population of MSC were unable to contribute to the fibroblastic stromal population. Subsequently, a bone marrow transplantation experiment confirmed the endogenous migratory deficiencies of the CD44KO bone marrow derived stromal cells toward the tumor microenvironment in vivo. WT mice with CD44KO bone marrow had less CD44KOderived tumor stroma compared to mice with WT bone marrow. These results indicate that CD44 is crucial to stromal cell migration and incorporation to the tumor microenvironment as TAF

Validation of a clinical and genetic model for predicting severe COVID-19

Using nested case-control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P < 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions

Origins of the Tumor Microenvironment: Quantitative Assessment of Adipose-Derived and Bone Marrow–Derived Stroma

To meet the requirements for rapid tumor growth, a complex array of non-neoplastic cells are recruited to the tumor microenvironment. These cells facilitate tumor development by providing matrices, cytokines, growth factors, as well as vascular networks for nutrient and waste exchange, however their precise origins remain unclear. Through multicolored tissue transplant procedures; we have quantitatively determined the contribution of bone marrow-derived and adipose-derived cells to stromal populations within syngeneic ovarian and breast murine tumors. Our results indicate that subpopulations of tumor-associated fibroblasts (TAFs) are recruited from two distinct sources. The majority of fibroblast specific protein (FSP) positive and fibroblast activation protein (FAP) positive TAFs originate from mesenchymal stem/stromal cells (MSC) located in bone marrow sources, whereas most vascular and fibrovascular stroma (pericytes, α-SMA+ myofibroblasts, and endothelial cells) originates from neighboring adipose tissue. These results highlight the capacity for tumors to utilize multiple sources of structural cells in a systematic and discriminative manner

Mesenchymal Stem Cell Transition to Tumor-Associated Fibroblasts Contributes to Fibrovascular Network Expansion and Tumor Progression

Tumor associated fibroblasts (TAF), are essential for tumor progression providing both a functional and structural supportive environment. TAF, known as activated fibroblasts, have an established biological impact on tumorigenesis as matrix synthesizing or matrix degrading cells, contractile cells, and even blood vessel associated cells. The production of growth factors, cytokines, chemokines, matrix-degrading enzymes, and immunomodulatory mechanisms by these cells augment tumor progression by providing a suitable environment. There are several suggested origins of the TAF including tissue-resident, circulating, and epithelial-to-mesenchymal-transitioned cells.We provide evidence that TAF are derived from mesenchymal stem cells (MSC) that acquire a TAF phenotype following exposure to or systemic recruitment into adenocarcinoma xenograft models including breast, pancreatic, and ovarian. We define the MSC derived TAF in a xenograft ovarian carcinoma model by the immunohistochemical presence of 1) fibroblast specific protein and fibroblast activated protein; 2) markers phenotypically associated with aggressiveness, including tenascin-c, thrombospondin-1, and stromelysin-1; 3) production of pro-tumorigenic growth factors including hepatocyte growth factor, epidermal growth factor, and interleukin-6; and 4) factors indicative of vascularization, including alpha-smooth muscle actin, desmin, and vascular endothelial growth factor. We demonstrate that under long-term tumor conditioning in vitro, MSC express TAF-like proteins. Additionally, human MSC but not murine MSC stimulated tumor growth primarily through the paracrine production of secreted IL6.Our results suggest the dependence of in vitro Skov-3 tumor cell proliferation is due to the presence of tumor-stimulated MSC secreted IL6. The subsequent TAF phenotype arises from the MSC which ultimately promotes tumor growth through the contribution of microvascularization, stromal networks, and the production of tumor-stimulating paracrine factors

Mesenchymal Stem Cells Promote Mammosphere Formation and Decrease E-Cadherin in Normal and Malignant Breast Cells

Normal and malignant breast tissue contains a rare population of multi-potent cells with the capacity to self-renew, referred to as stem cells, or tumor initiating cells (TIC). These cells can be enriched by growth as "mammospheres" in three-dimensional cultures.We tested the hypothesis that human bone-marrow derived mesenchymal stem cells (MSC), which are known to support tumor growth and metastasis, increase mammosphere formation.We found that MSC increased human mammary epithelial cell (HMEC) mammosphere formation in a dose-dependent manner. A similar increase in sphere formation was seen in human inflammatory (SUM149) and non-inflammatory breast cancer cell lines (MCF-7) but not in primary inflammatory breast cancer cells (MDA-IBC-3). We determined that increased mammosphere formation can be mediated by secreted factors as MSC conditioned media from MSC spheroids significantly increased HMEC, MCF-7 and SUM149 mammosphere formation by 6.4 to 21-fold. Mammospheres grown in MSC conditioned media had lower levels of the cell adhesion protein, E-cadherin, and increased expression of N-cadherin in SUM149 and HMEC cells, characteristic of a pro-invasive mesenchymal phenotype. Co-injection with MSC in vivo resulted in a reduced latency time to develop detectable MCF-7 and MDA-IBC-3 tumors and increased the growth of MDA-IBC-3 tumors. Furthermore, E-cadherin expression was decreased in MDA-IBC-3 xenografts with co-injection of MSC.MSC increase the efficiency of primary mammosphere formation in normal and malignant breast cells and decrease E-cadherin expression, a biologic event associated with breast cancer progression and resistance to therapy

Role of neoplastic monocyte-derived fibrocytes in primary myelofibrosis

Primary myelofibrosis (PMF) is a fatal neoplastic disease characterized by clonal myeloproliferation and progressive bone marrow (BM) fibrosis thought to be induced by mesenchymal stromal cells stimulated by overproduced growth factors. However, tissue fibrosis in other diseases is associated with monocyte-derived fibrocytes. Therefore, we sought to determine whether fibrocytes play a role in the induction of BM fibrosis in PMF. In this study, we show that BM from patients with PMF harbors an abundance of clonal, neoplastic collagen- and fibronectin-producing fibrocytes. Immunodeficient mice transplanted with myelofibrosis patients’ BM cells developed a lethal myelofibrosis-like phenotype. Treatment of the xenograft mice with the fibrocyte inhibitor serum amyloid P (SAP; pentraxin-2) significantly prolonged survival and slowed the development of BM fibrosis. Collectively, our data suggest that neoplastic fibrocytes contribute to the induction of BM fibrosis in PMF, and inhibiting fibrocyte differentiation with SAP may interfere with this process

Validation of a clinical and genetic model for predicting severe COVID-19

Using nested case-control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P &lt; 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions. </p

Predicting 10-Year Risk of Pancreatic Cancer Using a Combined Genetic and Clinical Model

Background and Aims: Pancreatic cancer has the poorest 5-year survival rate of any major solid tumor, but when diagnosed at an early stage, survival rates improve. Population screening is impractical because pancreatic cancer is rare with a lifetime risk of 1.7%, but accurate risk stratification in the general population could enable health care providers to focus early detection strategies to at-risk individuals. Here, we validate a combined risk prediction model that integrates a polygenic risk score and a clinical risk model. Methods: Using the UK Biobank, we conducted a prospective cohort study assessing 10-year pancreatic cancer risks based on a polygenic risk score, a clinical risk score, and a combined risk score. We assessed the association, discrimination, calibration, cumulative hazards, and standardized incidence ratios compared to population incidence rates for the risk scores. We also conducted net reclassification analyses. Results: While all of the risk scores discriminated well between affected and unaffected participants, the combined risk score – with a Harrell’s C-index of 0.714 (95% confidence interval [CI] = 0.698, 0.730) – discriminated better than both the polygenic risk score (P = .001) and the clinical risk score (P = .02). In terms of calibration, there was no problem with dispersion for the combined risk score (β = 0.952, 95% CI = 0.865–1.039, P = .3) and overall there was a small overestimation of risk (α = −0.089, 95% CI = −0.156 to −0.021, P = .009). Participants in the top decile of 10-year risk were at 1.413 (95% CI = 1.242–1.607) times population risk. Conclusion: The combined risk score was able to identify individuals at substantially increased risk of pancreatic cancer and to whom targeted screening could be useful