Diabetic foot ulceration (DFU) is a devastating complication of diabetes whose pathogenesis remains incompletely understood. Here, we profile 174,962 single cells from the foot, forearm, and ...peripheral blood mononuclear cells using single-cell RNA sequencing. Our analysis shows enrichment of a unique population of fibroblasts overexpressing MMP1, MMP3, MMP11, HIF1A, CHI3L1, and TNFAIP6 and increased M1 macrophage polarization in the DFU patients with healing wounds. Further, analysis of spatially separated samples from the same patient and spatial transcriptomics reveal preferential localization of these healing associated fibroblasts toward the wound bed as compared to the wound edge or unwounded skin. Spatial transcriptomics also validates our findings of higher abundance of M1 macrophages in healers and M2 macrophages in non-healers. Our analysis provides deep insights into the wound healing microenvironment, identifying cell types that could be critical in promoting DFU healing, and may inform novel therapeutic approaches for DFU treatment.
The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number ...of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ .
The relaxation response (RR) is the counterpart of the stress response. Millennia-old practices evoking the RR include meditation, yoga and repetitive prayer. Although RR elicitation is an effective ...therapeutic intervention that counteracts the adverse clinical effects of stress in disorders including hypertension, anxiety, insomnia and aging, the underlying molecular mechanisms that explain these clinical benefits remain undetermined. To assess rapid time-dependent (temporal) genomic changes during one session of RR practice among healthy practitioners with years of RR practice and also in novices before and after 8 weeks of RR training, we measured the transcriptome in peripheral blood prior to, immediately after, and 15 minutes after listening to an RR-eliciting or a health education CD. Both short-term and long-term practitioners evoked significant temporal gene expression changes with greater significance in the latter as compared to novices. RR practice enhanced expression of genes associated with energy metabolism, mitochondrial function, insulin secretion and telomere maintenance, and reduced expression of genes linked to inflammatory response and stress-related pathways. Interactive network analyses of RR-affected pathways identified mitochondrial ATP synthase and insulin (INS) as top upregulated critical molecules (focus hubs) and NF-κB pathway genes as top downregulated focus hubs. Our results for the first time indicate that RR elicitation, particularly after long-term practice, may evoke its downstream health benefits by improving mitochondrial energy production and utilization and thus promoting mitochondrial resiliency through upregulation of ATPase and insulin function. Mitochondrial resiliency might also be promoted by RR-induced downregulation of NF-κB-associated upstream and downstream targets that mitigates stress.
Objective
Chronic migraine (CM) is often associated with chronic tenderness of pericranial muscles. A distinct increase in muscle tenderness prior to onset of occipital headache that eventually ...progresses into a full‐blown migraine attack is common. This experience raises the possibility that some CM attacks originate outside the cranium. The objective of this study was to determine whether there are extracranial pathophysiologies in these headaches.
Methods
We biopsied and measured the expression of gene transcripts (mRNA) encoding proteins that play roles in immune and inflammatory responses in affected (ie, where the head hurts) calvarial periosteum of (1) patients whose CMs are associated with muscle tenderness and (2) patients with no history of headache.
Results
Expression of proinflammatory genes (eg, CCL8, TLR2) in the calvarial periosteum significantly increased in CM patients attesting to muscle tenderness, whereas expression of genes that suppress inflammation and immune cell differentiation (eg, IL10RA, CSF1R) decreased.
Interpretation
Because the upregulated genes were linked to activation of white blood cells, production of cytokines, and inhibition of NF‐κB, and the downregulated genes were linked to prevention of macrophage activation and cell lysis, we suggest that the molecular environment surrounding periosteal pain fibers is inflamed and in turn activates trigeminovascular nociceptors that reach the affected periosteum through suture branches of intracranial meningeal nociceptors and/or somatic branches of the occipital nerve. This study provides the first set of evidence for localized extracranial pathophysiology in CM. Ann Neurol 2016;79:1000–1013
Mesenchymal stem/stromal cells (MSCs) are progenitor cells shown to participate in breast tumor stroma formation and to promote metastasis. Despite expanding knowledge of their contributions to ...breast malignancy, the underlying molecular responses of breast cancer cells (BCCs) to MSC influences remain incompletely understood. Here, we show that MSCs cause aberrant expression of microRNAs, which, led by microRNA-199a, provide BCCs with enhanced cancer stem cell (CSC) properties. We demonstrate that such MSC-deregulated microRNAs constitute a network that converges on and represses the expression of FOXP2, a forkhead transcription factor tightly associated with speech and language development. FOXP2 knockdown in BCCs was sufficient in promoting CSC propagation, tumor initiation, and metastasis. Importantly, elevated microRNA-199a and depressed FOXP2 expression levels are prominent features of malignant clinical breast cancer and are associated significantly with poor survival. Our results identify molecular determinants of cancer progression of potential utility in the prognosis and therapy of breast cancer.
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•MSCs promote contact-dependent upregulation of miR-199a in breast cancer cells•MiR-199a represses the transcriptional regulator FOXP2•The miR-199a-FOXP2 axis propagates cancer stem cell traits and metastasis•Elevated miR-199a and depleted FOXP2 characterize malignant clinical breast cancer
Cuiffo et al. show that repression of the speech-associated gene FOXP2 by a network of mesenchymal-stem-cell-regulated microRNAs facilitates the acquisition of cancer stem cell and metastatic phenotypes by breast cancer cells.
The energetic burden of continuously concentrating solutes against gradients along the tubule may render the kidney especially vulnerable to ischaemia. Acute kidney injury (AKI) affects 3% of all ...hospitalized patients. Here we show that the mitochondrial biogenesis regulator, PGC1α, is a pivotal determinant of renal recovery from injury by regulating nicotinamide adenine dinucleotide (NAD) biosynthesis. Following renal ischaemia, Pgc1α(-/-) (also known as Ppargc1a(-/-)) mice develop local deficiency of the NAD precursor niacinamide (NAM, also known as nicotinamide), marked fat accumulation, and failure to re-establish normal function. Notably, exogenous NAM improves local NAD levels, fat accumulation, and renal function in post-ischaemic Pgc1α(-/-) mice. Inducible tubular transgenic mice (iNephPGC1α) recapitulate the effects of NAM supplementation, including more local NAD and less fat accumulation with better renal function after ischaemia. PGC1α coordinately upregulates the enzymes that synthesize NAD de novo from amino acids whereas PGC1α deficiency or AKI attenuates the de novo pathway. NAM enhances NAD via the enzyme NAMPT and augments production of the fat breakdown product β-hydroxybutyrate, leading to increased production of prostaglandin PGE2 (ref. 5), a secreted autacoid that maintains renal function. NAM treatment reverses established ischaemic AKI and also prevented AKI in an unrelated toxic model. Inhibition of β-hydroxybutyrate signalling or prostaglandin production similarly abolishes PGC1α-dependent renoprotection. Given the importance of mitochondrial health in ageing and the function of metabolically active organs, the results implicate NAM and NAD as key effectors for achieving PGC1α-dependent stress resistance.
A major cause of cancer recurrence following chemotherapy is cancer dormancy escape. Taxane-based chemotherapy is standard of care in breast cancer treatment aimed at killing proliferating cancer ...cells. Here, we demonstrate that docetaxel injures stromal cells, which release protumor cytokines, IL-6 and granulocyte colony stimulating factor (G-CSF), that in turn invoke dormant cancer outgrowth both in vitro and in vivo. Single-cell transcriptomics shows a reprogramming of awakened cancer cells including several survival cues such as stemness, chemoresistance in a tumor stromal organoid (TSO) model, as well as an altered tumor microenvironment (TME) with augmented protumor immune signaling in a syngeneic mouse breast cancer model. IL-6 plays a role in cancer cell proliferation, whereas G-CSF mediates tumor immunosuppression. Pathways and differential expression analyses confirmed MEK as the key regulatory molecule in cancer cell outgrowth and survival. Antibody targeting of protumor cytokines (IL-6, G-CSF) or inhibition of cytokine signaling via MEK/ERK pathway using selumetinib prior to docetaxel treatment prevented cancer dormancy outgrowth suggesting a novel therapeutic strategy to prevent cancer recurrence.
In 2021, 1 out of adults suffered from diabetes mellitus globally. A major complication resulting from this is diabetic foot ulcers (DFU) , which can lead to amputation if improperly managed. Current ...clinical approaches to DFU have significant limitations, such as the high cost involved in the diagnosis and time-consuming care. In light of this, we have developed DFUCare, a mobile app that uses the built-in camera and deep learning to diagnose and quantify patients' diabetic foot ulcers. DFUCare is trained on an extensive foot dataset containing over 5000 images of normal and infected DFU patients. For binary classification of infected and non-infected patients, we use a combination of transfer and ensemble learning. Using transfer learning, DFUCare uses the pretrained InceptionResNetV2 model for deep learning derived feature extraction. With an ensemble approach, we compare the deep learning derived feature extraction results to handcrafted color and textural feature extraction results to come up with a final prediction of infected vs. non-infected patients. In the end, we achieved top-level results with a binary accuracy of .9014, AUC of .9437, specificity of .9023, and precision of .8901. In addition, using standardized metrics and computer vision algorithms, DFUCare can determine the dimensions of the DFU to quantify the severity over time. With all of the information stored in the cloud, doctors and patients can use the share feature in the mobile app to send medical reports to anyone in the world. In the future, we are planning to add clinical, biological, and epidemiological features along with macroscopic image features to improve the performance of the tool in predicting infection and healing. This novel approach has the potential to deliver a paradigm shift in diabetic foot care among patients by being a cost-effective, remote, and convenient healthcare solution.
Disclosure
V.Sendilraj: None. W.C.Pilcher: None. M.K.Bhasin: None.
Pancreatic ductal adenocarcinoma (PDAC) is generally incurable due to the late diagnosis and absence of markers that are concordant with expression in several sample sources (i.e., tissue, blood, ...plasma) and platforms (i.e., Microarray, sequencing). We optimized meta-analysis of 19 PDAC (tissue and blood) transcriptome studies from multiple platforms. The key biomarkers for PDAC diagnosis with secretory potential were identified and validated in different cohorts. Machine learning approach i.e., support vector machine supported by leave-one-out cross-validation was used to build and test the classifier. We identified a 9-gene panel (IFI27, ITGB5, CTSD, EFNA4, GGH, PLBD1, HTATIP2, IL1R2, CTSA) that achieved ∼0.92 average sensitivity and ∼0.90 average specificity in distinguishing PDAC from healthy samples in five training sets using cross-validation. These markers were also validated in proteomics and single-cell transcriptomics studies suggesting their prognostic role in the diagnosis of PDAC. Our 9-gene classifier can not only clearly discriminate between better and poor survivors but can also precisely discriminate PDAC from chronic pancreatitis (AUC = 0.95), early stages of progression Stage I and II (AUC = 0.82), IPMA and IPMN (AUC = 1), and IPMC (AUC = 0.81). The 9-gene marker outperformed the previously known markers in blood studies particularly (AUC = 0.84). The discrimination of PDAC from early precursor lesions in non-malignant tissue (AUC > 0.81) and peripheral blood (AUC > 0.80) may assist in an early diagnosis of PDAC in blood samples and thus will also facilitate risk stratification upon validation in clinical trials.
Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker ...detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression.
Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis.
Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities.
It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression.
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