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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.

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. Diabetic foot ulcers (DFUs) remain a complication of diabetes that are difficult to heal and lead to disability. Here the authors use single-cell RNA-sequencing and spatial transcriptomics to characterize the DFU cellular landscape and identify a population of fibroblasts that is associated with successful wound closure.

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.

PGC1α protects against kidney injury by upregulating enzymes that enhance nicotinamide adenine dinucleotide (NAD) and driving local accumulation of the fatty acid breakdown product β-hydroxybutyrate, which leads to increased production of the renoprotective prostaglandin E 2 . Kidney protection by PGC1α Samir Parikh and colleagues show that the mitochondrial biogenesis regulator PGC1α protects against kidney injury by regulating NAD biosynthesis. In a mouse model, PGC1α upregulates NAMPT, an enzyme required form for NAD + biosynthesis, and drives local accumulation of the fatty acid breakdown product β-hydroxybutyrate. This, in turn, leads to increased production of the renoprotective prostaglandin PGE 2 . The authors further show that treatment with the NAD precursor nicotinamide (NAM) can reverse established ischaemic kidney injury. 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 1 , 2 . Here we show that the mitochondrial biogenesis regulator, PGC1α 3 , 4 , 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 PGE 2 (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.

Cancer therapy is a double-edged sword, as surgery and chemotherapy can induce an inflammatory/immunosuppressive injury response that promotes dormancy escape and tumor recurrence. We hypothesized that these events could be altered by early blockade of the inflammatory cascade and/or by accelerating the resolution of inflammation. Preoperative, but not postoperative, administration of the nonsteroidal antiinflammatory drug ketorolac and/or resolvins, a family of specialized proresolving autacoid mediators, eliminated micrometastases in multiple tumor-resection models, resulting in long-term survival. Ketorolac unleashed anticancer T cell immunity that was augmented by immune checkpoint blockade, negated by adjuvant chemotherapy, and dependent on inhibition of the COX-1/thromboxane A2 (TXA2) pathway. Preoperative stimulation of inflammation resolution via resolvins (RvD2, RvD3, and RvD4) inhibited metastases and induced T cell responses. Ketorolac and resolvins exhibited synergistic antitumor activity and prevented surgery- or chemotherapy-induced dormancy escape. Thus, simultaneously blocking the ensuing proinflammatory response and activating endogenous resolution programs before surgery may eliminate micrometastases and reduce tumor recurrence.

Acute myeloid leukemia (AML) microenvironment exhibits cellular and molecular differences among various subtypes. Here, we utilize single-cell RNA sequencing (scRNA-seq) to analyze pediatric AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse timepoints. Analysis of Dx, EOI scRNA-seq, and TARGET AML RNA-seq datasets reveals an AML blasts-associated 7-gene signature ( CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH ), which we validate on independent datasets. The analysis reveals distinct clusters of Dx relapse- and continuous complete remission (CCR)-associated AML-blasts with differential expression of genes associated with survival. At Dx, relapse-associated samples have more exhausted T cells while CCR-associated samples have more inflammatory M1 macrophages. Post-therapy EOI residual blasts overexpress fatty acid oxidation, tumor growth, and stemness genes. Also, a post-therapy T-cell cluster associated with relapse samples exhibits downregulation of MHC Class I and T-cell regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse- and CCR-associated samples to provide insights into the BM microenvironment landscape. Single-cell RNA-seq could help identify acute myeloid leukaemia (AML) patients at high risk of relapse after therapy. Here, the authors use single-cell RNA-seq from paediatric AML samples to construct a 7-gene signature that can identify malignant cells at diagnosis, which are distinctly associated with relapse or complete remission.

Different driver mutations and/or chromosomal aberrations and dysregulated signaling interactions between leukemia cells and the immune microenvironment have been implicated in the development of T-cell acute lymphoblastic leukemia (T-ALL). To better understand changes in the bone marrow microenvironment and signaling pathways in pediatric T-ALL, bone marrows collected at diagnosis (Dx) and end of induction therapy (EOI) from 11 patients at a single center were profiled by single cell transcriptomics (10 Dx, 5 paired EOI, 1 relapse). T-ALL blasts were identified by comparison with healthy bone marrow cells. T-ALL blast-associated gene signature included SOX4, STMN1, JUN, HES4, CDK6, ARMH1 among the most significantly overexpressed genes, some of which are associated with poor prognosis in children with T-ALL. Transcriptome profiles of the blast cells exhibited significant inter-patient heterogeneity. Post induction therapy expression profiles of the immune cells revealed significant changes. Residual blast cells in MRD+ EOI samples exhibited significant upregulation ( P  < 0.01) of PD-1 and RhoGDI signaling pathways. Differences in cellular communication were noted in the presence of residual disease in T cell and hematopoietic stem cell compartments in the bone marrow. Together, these studies generate new insights and expand our understanding of the bone marrow landscape in pediatric T-ALL.

Background 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. Methods 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. Results 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. Conclusions 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.

KDM3A is implicated in tumorigenesis; however, its biological role in multiple myeloma (MM) has not been elucidated. Here we identify KDM3A–KLF2–IRF4 axis dependence in MM. Knockdown of KDM3A is toxic to MM cells in vitro and in vivo . KDM3A maintains expression of KLF2 and IRF4 through H3K9 demethylation, and knockdown of KLF2 triggers apoptosis. Moreover, KLF2 directly activates IRF4 and IRF4 reciprocally upregulates KLF2 , forming a positive autoregulatory circuit. The interaction of MM cells with bone marrow milieu mediates survival of MM cells. Importantly, silencing of KDM3A , KLF2 or IRF4 both decreases MM cell adhesion to bone marrow stromal cells and reduces MM cell homing to the bone marrow, in association with decreased ITGB7 expression in MAF -translocated MM cell lines. Our results indicate that the KDM3A–KLF2–IRF4 pathway plays an essential role in MM cell survival and homing to the bone marrow, and therefore represents a therapeutic target. Several histone modifiers have been implicated in the survival of multiple myeloma cells. Here, the authors reveal a role for the histone demethylase KDM3A in the survival of this haematologic cancer, and show that mechanistically KDM3A removes H3K9 methylation from the promoters of KLF2 and IRF4 , genes essential for myeloma cell survival.