Glucocorticoids indirectly decrease colon cancer cell proliferation and invasion via effects on cancer-associated fibroblasts.

Cancer-associated fibroblasts (CAFs) support cancer growth, invasion, and metastasis. Glucocorticoids (GCs), drugs often administered together with chemotherapy, are steroidal ligands of the glucocorticoid receptor (GR), a transcription factor which upon activation regulates expression of multiple genes involved in suppression of inflammation. We have previously shown that in dexamethasone (Dex)-treated CAFs derived from colon cancer, production and secretion of several factors related to cancer progression, such as tenascin C (TNC) and hepatocyte growth factor (HGF), were strongly suppressed. In this study we show that GCs can neutralize the cancer cell-promoting properties of CAFs. Conditioned medium from solvent-treated CAFs (CMCTRL) stimulates proliferation, motility and stretched morphotype of GR-deficient HCT8/E11 colon cancer cells. Yet, HCT8/E11 proliferation and stretched morphotype are impaired upon treatment with conditioned medium from Dex-treated CAFs (CMDEX), but HCT8/E11 cell migration is slightly increased under these conditions. Moreover, expression and potential activity of MMP-2 is also reduced in CMDEX compared with CMCTRL. These combined in vitro results concur with the results from in vivo chick chorioallantoic membrane assays, where the co-cultures of CAFs with colon cancer cells displayed impaired tumor formation and cancer cell invasion due to Dex administration. Combined, GC treatment influences cancer cell behavior indirectly through effects on CAFs.

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

A global federated real-world data and analytics platform for research.

Objective: This article describes a scalable, performant, sustainable global network of electronic health record data for biomedical and clinical research. Materials and Methods: TriNetX has created a technology platform characterized by a conservative security and governance model that facilitates collaboration and cooperation between industry participants, such as pharmaceutical companies and contract research organizations, and academic and community-based healthcare organizations (HCOs). HCOs participate on the network in return for access to a suite of analytics capabilities, large networks of de-identified data, and more sponsored trial opportunities. Industry participants provide the financial resources to support, expand, and improve the technology platform in return for access to network data, which provides increased efficiencies in clinical trial design and deployment. Results: TriNetX is a growing global network, expanding from 55 HCOs and 7 countries in 2017 to over 220 HCOs and 30 countries in 2022. Over 19 000 sponsored clinical trial opportunities have been initiated through the TriNetX network. There have been over 350 peer-reviewed scientific publications based on the network's data. Conclusions: The continued growth of the TriNetX network and its yield of clinical trial collaborations and published studies indicates that this academic-industry structure is a safe, proven, sustainable path for building and maintaining research-centric data networks.

Exploring Breast Cancer Systemic Drug Therapy Patterns in Real-World Data.

PURPOSE: To explore medications and their administration patterns in real-world patients with breast cancer. METHODS: A retrospective study was performed using TriNetX, a federated network of deidentified, Health Insurance Portability and Accountability Act-compliant data from 21 health care organizations across North America. Patients diagnosed with breast cancer between January 1, 2013, and May 31, 2022, were included. We investigated a rule-based and unsupervised learning algorithm to extract medications and their administration patterns. To group similar administration patterns, we used three features in k-means clustering: total number of administrations, median number of days between administrations, and standard deviation of the days between administrations. We explored the first three lines of therapy for patients classified into six groups on the basis of their stage at diagnosis (early as stages I-III v late as stage IV) and the sensitivity of the tumor's receptors to targeted therapies: hormone receptor-positive/human epidermal growth factor 2-negative (HR+/ERBB2-), ERBB2-positive (ERBB2+/HR±), or triple-negative (TN; HR-/ERBB2-). To add credence to the derived regimens, we compared them to the National Comprehensive Cancer Network (NCCN): Breast Cancer (version 2.2023) recommendations. RESULTS: In early-stage HR+/ERBB2- and TN groups, the most common regimens were (1) cyclophosphamide and docetaxel, administered once every 3 weeks for three to six cycles and (2) cyclophosphamide and doxorubicin, administered once every 2 weeks for four cycles, followed by paclitaxel administered once every week for 12 cycles. In the early-stage ERBB2+/HR± group, most patients were administered carboplatin and docetaxel with or without pertuzumab and with trastuzumab (for six or more cycles). Medications most commonly administered in our data set (7,798 patients) agreed with recommendations from the NCCN in terms of medications (regimens), number of administrations (cycles), and days between administrations (cycle length). CONCLUSION: Although there is a general agreement with the NCCN Guidelines, real-world medication data exhibit variability in the medications and their administration patterns.

Glucocorticoid-mediated effects on angiogenesis in solid tumors.

Angiogenesis is essential in tumor development to maintain the oxygen and nutrient supply. Glucocorticoids have shown both direct and indirect angiostatic properties in various types of solid cancers. In most of the reported cases glucocorticoid-mediated actions involved suppression of multiple pro-angiogenic factors expression by cancer cells. The anti-angiogenic properties of glucocorticoids correlated with diminished tumor vasculature and reduced tumor growth in multiple in vivo studies. However, when glucocorticoid treatment is considered, possible adverse events should be taken into account. Additional research is needed to further test the use of these steroidal drugs in cancer therapy.

When Neighbors Talk: Colon Cancer Cell Invasion and Tumor Microenvironment Myofibroblasts.

Historically, the word cancer is derived from the Latin cancer, as the red swollen arteries near a tumor reminded the physician Galenus and his fellow Romans of a red crab. Currently, cancer remains the disease to beat as it remains a leading cause of death worldwide (WHO). Tumors do not simply consist of cancer cells, as they can recruit normal cells, which will form the tumor-associated stroma. These stromal cells together with the extracellular matrix, constitute the tumor microenvironment. Reciprocal communication between tumor-associated stromal cells and cancer cells is important for the induction of epithelial-to-mesenchymal transition and invasion. A detailed knowledge of this communication can spark the development of novel therapeutic strategies aimed at tackling yet unaddressed regulators of invasion and thus metastasis. Therefore, this review will focus not only on epithelial-to-mesenchymal transition and invasion, but also on communication between tumor cells, in particular colon cancer cells, and their stroma, with a primordial focus on cancer-associated fibroblasts, and lastly this review will discuss how this communication can affect the cancer cell's ability to invade its surroundings and form metastases.

Colon cancer-derived myofibroblasts increase endothelial cell migration by glucocorticoid-sensitive secretion of a pro-migratory factor.

Angiogenesis is important in cancer progression and can be influenced by tumor-associated myofibroblasts. We addressed the hypothesis that glucocorticoids indirectly affect angiogenesis by altering the release of pro-angiogenic factors from colon cancer-derived myofibroblasts. Our study shows that glucocorticoids reduced prostanoids, urokinase-type plasminogen activator (uPA) and angiopoietin-like protein-2 (ANGPTL2) levels, but increased angiogenin (ANG) in supernatant from human CT5.3hTERT colon cancer-derived myofibroblasts. Conditioned medium from solvent- (CMS) and dexamethasone (Dex)-treated (CMD) myofibroblasts increased human umbilical vein endothelial cell (HUVEC) proliferation, but did not affect expression of pro-angiogenic factors or tube-like structure formation (by HUVECs or human aortic ECs). In a HUVEC scratch assay CMS-induced acceleration of wound healing was blunted by CMD treatment. Moreover, CMS-induced neovessel growth in mouse aortic rings ex vivo was also blunted using CMD. The latter effect could be ascribed to both Dex-driven reduction of secreted factors and potential residual Dex present in CMD (indicated using a dexamethasone-spiked CMS control). A similar control in the scratch assay, however, revealed that altered levels of factors in the CMD, and not potential residual Dex, were responsible for decreased wound closure. In conclusion, our results suggest that glucocorticoids indirectly alter endothelial cell function during tumor development in vivo.

An integrated network of Arabidopsis growth regulators and its use for gene prioritization.

Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.

Glucocorticoids and the non-steroidal selective glucocorticoid receptor modulator, compound A, differentially affect colon cancer-derived myofibroblasts.

The glucocorticoid receptor functions as a ligand-dependent transcription factor that positively or negatively regulates the transcription of various specific target genes. Not only steroidal glucocorticoids can bind and activate the glucocorticoid receptor, but also the intensively examined non-steroidal selective glucocorticoid receptor modulators can do so, albeit with a select effector profile skewed to glucocorticoid receptor transrepression. Glucocorticoids are widely used to treat inflammatory afflictions, but also as anti-cancer therapies or adjuvants thereof. As the impact of glucocorticoids and selective glucocorticoid receptor modulators has scarcely been researched in this setting, we focused on colon cancer and its stromal environment, in particular the stromal myofibroblasts, which are known to influence cancer cells via paracrine signaling. In these myofibroblasts, the glucocorticoid dexamethasone is able to drive the glucocorticoid receptor into the nucleus and thus negatively regulates the expression of particular pro-inflammatory genes in TNFα-stimulated cells. The selective glucocorticoid receptor modulator compound A has an impaired ability to translocate GR, presumably underpinning its modest anti-inflammatory properties in these cells. Only dexamethasone, and not compound A, can upregulate the glucocorticoid receptor transactivation-dependent GILZ expression. Neither dexamethasone, nor compound A affects myofibroblast cell viability. However, compound A retards the growth of this myofibroblast cell line. Additionally, dexamethasone can inhibit the expression of Tenascin C, hepatocyte growth factor, and TGFß, which are all factors known for their impact on colon cancer cell invasion, in a glucocorticoid receptor-dependent manner. In contrast, compound A can only slightly diminish the expression of just hepatocyte growth factor, and not tenascin C or TGFß. Combined, our results expose new tumor microenvironment-modulating effects of glucocorticoids and the selective GR modulator compound A.

Compound A, a selective glucocorticoid receptor modulator, enhances heat shock protein Hsp70 gene promoter activation.

Compound A possesses glucocorticoid receptor (GR)-dependent anti-inflammatory properties. Just like classical GR ligands, Compound A can repress NF-κB-mediated gene expression. However, the monomeric Compound A-activated GR is unable to trigger glucocorticoid response element-regulated gene expression. The heat shock response potently activates heat shock factor 1 (HSF1), upregulates Hsp70, a known GR chaperone, and also modulates various aspects of inflammation. We found that the selective GR modulator Compound A and heat shock trigger similar cellular effects in A549 lung epithelial cells. With regard to their anti-inflammatory mechanism, heat shock and Compound A are both able to reduce TNF-stimulated IκBα degradation and NF-κB p65 nuclear translocation. We established an interaction between Compound A-activated GR and Hsp70, but remarkably, although the presence of the Hsp70 chaperone as such appears pivotal for the Compound A-mediated inflammatory gene repression, subsequent novel Hsp70 protein synthesis is uncoupled from an observed CpdA-induced Hsp70 mRNA upregulation and hence obsolete in mediating CpdA's anti-inflammatory effect. The lack of a Compound A-induced increase in Hsp70 protein levels in A549 cells is not mediated by a rapid proteasomal degradation of Hsp70 or by a Compound A-induced general block on translation. Similar to heat shock, Compound A can upregulate transcription of Hsp70 genes in various cell lines and BALB/c mice. Interestingly, whereas Compound A-dependent Hsp70 promoter activation is GR-dependent but HSF1-independent, heat shock-induced Hsp70 expression alternatively occurs in a GR-independent and HSF1-dependent manner in A549 lung epithelial cells.

Drug resistance mutations in drug-naive HIV type 1 subtype C-infected individuals from rural Malawi.

In this preliminary study we show that in 2008, 3 years after antiretroviral therapy was introduced into the Karonga District, Malawi, a greater than expected number of drug-naive individuals have been infected with HIV-1 subtype C virus harboring major and minor drug resistance mutations (DRMs). From a sample size of 40 reverse transcriptase (RT) consensus sequences from drug-naive individuals we found five showing NRTI and four showing NNRTI mutations with one individual showing both. From 29 protease consensus sequences, again from drug-naive individuals, we found evidence of minor DRMs in three. Additional major and minor DRMs were found in clonal sequences from a number of individuals that were not present in the original consensus sequences. This clearly illustrates the importance of sequencing multiple HIV-1 variants from individuals to fully assess drug resistance.