49 research outputs found
Changes in the immune landscape of TNBC after neoadjuvant chemotherapy: correlation with relapse
Introduction: Patients with high-risk, triple negative breast cancer (TNBC) often receive neoadjuvant chemotherapy (NAC) alone or with immunotherapy. Various single-cell and spatially resolved techniques have demonstrated heterogeneity in the phenotype and distribution of macrophages and T cells in this form of breast cancer. Furthermore, recent studies in mice have implicated immune cells in perivascular (PV) areas of tumors in the regulation of metastasis and anti-tumor immunity. However, little is known of how the latter change during NAC in human TNBC or their impact on subsequent relapse, or the likely efficacy of immunotherapy given with or after NAC.
Methods: We have used multiplex immunofluorescence and AI-based image analysis to compare the immune landscape in untreated and NAC-treated human TNBCs. We quantified changes in the phenotype, distribution and intercellular contacts of subsets of tumor-associated macrophages (TAMs), CD4+ and CD8+ T cells, and regulatory T cells (Tregs) in PV and non-PV various areas of the stroma and tumor cell islands. These were compared in tumors from patients who had either developed metastases or were disease-free (DF) after a three-year follow up period.
Results: In tumors from patients who remained DF after NAC, there was a marked increase in stromal CD163+ TAMs, especially those expressing the negative checkpoint regulator, T-cell immunoglobulin and mucin domain 3 (TIM-3). Whereas CD4+ T cells preferentially located to PV areas in the stroma of both untreated and NAC-treated tumors, specific subsets of TAMs and Tregs only did so only after NAC. Distinct subsets of CD4+ and CD8+ T cells formed PV clusters with CD163+ TAMs and Tregs. These were retained after NAC.
Discussion: Quantification of stromal TIM-3+CD163+ TAMs in tumor residues after NAC may represent a new way of identifying patients at high risk of relapse. PV clustering of immune cells is highly likely to regulate the activation and function of T cells, and thus the efficacy of T cell-based immunotherapies administered with or after NAC
Sequence-based feature prediction and annotation of proteins
The combination of prediction tools in complex workflows and pipelines facilitates prediction of protein features from sequence
Intraperitoneal adoptive transfer of mesenchymal stem cells enhances recovery from acid aspiration acute lung injury in mice
An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the commonest cause of chronic liver disease worldwide and represents an unmet precision medicine challenge. We established a retrospective national cohort of 940 histologically defined patients (55.4% men, 44.6% women; median body mass index 31.3; 32% with type 2 diabetes) covering the complete MASLD severity spectrum, and created a secure, searchable, open resource (SteatoSITE). In 668 cases and 39 controls, we generated hepatic bulk RNA sequencing data and performed differential gene expression and pathway analysis, including exploration of gender-specific differences. A web-based gene browser was also developed. We integrated histopathological assessments, transcriptomic data and 5.67 million days of time-stamped longitudinal electronic health record data to define disease-stage-specific gene expression signatures, pathogenic hepatic cell subpopulations and master regulator networks associated with adverse outcomes in MASLD. We constructed a 15-gene transcriptional risk score to predict future hepatic decompensation events (area under the receiver operating characteristic curve 0.86, 0.81 and 0.83 for 1-, 3- and 5-year risk, respectively). Additionally, thyroid hormone receptor beta regulon activity was identified as a critical suppressor of disease progression. SteatoSITE supports rational biomarker and drug development and facilitates precision medicine approaches for patients with MASLD
In vitro analysis of the effects on wound healing of high- and low-molecular weight chains of hyaluronan and their hybrid H-HA/L-HA complexes
Abstract
Background: Recent studies have reported the roles of Hyaluronic acid (HA) chains of diverse length in wound
repair, especially considering the simultaneous occurrence in vivo of both high- (H-HA) and low-molecular weight
(L-HA) hyaluronan at an injury site. It has been shown that HA fragments (5 ≤ MW ≤ 20 kDa) usually trigger an
inflammatory response that, on one hand, is the first signal in the activation of a repair mechanism but on the
other, when it’s overexpressed, it may promote unwanted side effects. The present experimental research has
aimed to investigate H-HA, L-HA and of a newly developed complex of the two (H-HA/L-HA) for stability (e.g.
hyaluronidases digestion), for their ability to promote wound healing of human keratinocytes in vitro and for their
effect on cellular biomarker expression trends.
Results: Time-lapse video microscopy studies proved that the diverse HA was capable of restoring the monolayer
integrity of HaCat. The H-HA/L-HA complex (0.1 and 1%w/v) proved faster in regeneration also in co-culture
scratch test where wound closure was achieved in half the time of H-HA stimulated cells and 2.5-fold faster than
the control. Gene expression was evaluated for transformation growth factor beta 1 (TGF-β1) proving that L-HA
alone increased its expression at 4 h followed by restoration of similar trends for all the stimuli. Depending on
the diverse stimulation (H-HA, L-HA or the complex), metalloproteinases (MMP-2, -9, -13) were also modulated differently.
Furthermore, type I collagen expression and production were evaluated. Compared to the others, persistence of a
significant higher expression level at 24 h for the H-HA/L-HA complex was found.
Conclusions: The outcomes of this research showed that, both at high and low concentrations, hybrid complexes
proved to perform better than HA alone thus suggesting their potential as medical devices in aesthetic and
regenerative medicine.
Keywords: Wound healing, Hyaluronan, MMPs, Hybrid complexe
Phenotypic Overlap between MMP-13 and the Plasminogen Activation System during Wound Healing in Mice
BACKGROUND: Proteolytic degradation of extracellular matrix is a crucial step in the healing of incisional skin wounds. Thus, healing of skin wounds is delayed by either plasminogen-deficiency or by treatment with the broad-spectrum metalloproteinase (MP) inhibitor Galardin alone, while the two perturbations combined completely prevent wound healing. Both urokinase-type plasminogen activator and several matrix metallo proteinases (MMPs), such as MMP-3, -9 and -13, are expressed in the leading-edge keratinocytes of skin wounds, which may account for this phenotypic overlap between these classes of proteases. METHODOLOGY: To further test that hypothesis we generated Mmp13;Plau and Mmp13;Plg double-deficient mice in a cross between Mmp13- and Plau-deficient mice as well as Mmp13- and Plg-deficient mice. These mice were examined for normal physiology in a large cohort study and in a well-characterized skin wound healing model, in which we made incisional 20 mm-long full-thickness skin wounds. PRINCIPAL FINDINGS: While mice that are deficient in Mmp13 have a mean healing time indistinguishable to wild-type mice, wound healing in both Plau- and Plg-deficient mice is significantly delayed. Histological analysis of healed wounds revealed a significant increase in keratin 10/14 immunoreactive layers of kerationcytes in the skin surface in Mmp13;Plau double-deficient mice. Furthermore, we observe, by immunohistological analysis, an aberrant angiogenic pattern during wound healing induced by Plau-deficiency, which has not previously been described. CONCLUSIONS: We demonstrate a phenotypic overlap, defined as an additional delay in wound healing in the double-deficient mice compared to the individual single-deficient mice, between MMP-13 and the plasminogen activation system in the process of wound healing, but not during gestation and in postnatal development. Thus, a dual targeting of uPA and MMP-13 might be a possible future strategy in designing therapies aimed at tissue repair or other pathological processes, such as cancer invasion, where proteolytic degradation is a hallmark
Predicting DNA-Binding Specificities of Eukaryotic Transcription Factors
Today, annotated amino acid sequences of more and more transcription factors (TFs) are readily available. Quantitative information about their DNA-binding specificities, however, are hard to obtain. Position frequency matrices (PFMs), the most widely used models to represent binding specificities, are experimentally characterized only for a small fraction of all TFs. Even for some of the most intensively studied eukaryotic organisms (i.e., human, rat and mouse), roughly one-sixth of all proteins with annotated DNA-binding domain have been characterized experimentally. Here, we present a new method based on support vector regression for predicting quantitative DNA-binding specificities of TFs in different eukaryotic species. This approach estimates a quantitative measure for the PFM similarity of two proteins, based on various features derived from their protein sequences. The method is trained and tested on a dataset containing 1 239 TFs with known DNA-binding specificity, and used to predict specific DNA target motifs for 645 TFs with high accuracy
Evidence for the Role of Horizontal Transfer in Generating pVT1, a Large Mosaic Conjugative Plasmid from the Clam Pathogen, Vibrio tapetis
The marine bacterium Vibrio tapetis is the causative agent of the brown ring disease, which affects the clam Ruditapes philippinarum and causes heavy economic losses in North of Europe and in Eastern Asia. Further characterization of V. tapetis isolates showed that all the investigated strains harbored at least one large plasmid. We determined the sequence of the 82,266 bp plasmid pVT1 from the CECT4600T reference strain and analyzed its genetic content. pVT1 is a mosaic plasmid closely related to several conjugative plasmids isolated from Vibrio vulnificus strains and was shown to be itself conjugative in Vibrios. In addition, it contains DNA regions that have similarity with several other plasmids from marine bacteria (Vibrio sp., Shewanella sp., Listonella anguillarum and Photobacterium profundum). pVT1 contains a number of mobile elements, including twelve Insertion Sequences or inactivated IS genes and an RS1 phage element related to the CTXphi phage of V. cholerae. The genetic organization of pVT1 underscores an important role of horizontal gene transfer through conjugative plasmid shuffling and transposition events in the acquisition of new genetic resources and in generating the pVT1 modular organization. In addition, pVT1 presents a copy number of 9, relatively high for a conjugative plasmid, and appears to belong to a new type of replicon, which may be specific to Vibrionaceae and Shewanelleacae
Deciphering Diseases and Biological Targets for Environmental Chemicals using Toxicogenomics Networks
Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types