Histone deacetylase (HDAC) inhibitors have demonstrated clinical benefits in subtypes of hematological malignancies. However, the efficacy of HDAC inhibitors in solid tumors remains uncertain. This study takes breast cancer as a model to understand mechanisms accounting for limited response of HDAC inhibitors in solid tumors and to seek combination solutions. We discover that feedback activation of leukemia inhibitory factor receptor (LIFR) signaling in breast cancer limits the response to HDAC inhibition. Mechanistically, HDAC inhibition increases histone acetylation at the LIFR gene promoter, which recruits bromodomain protein BRD4, upregulates LIFR expression, and activates JAK1-STAT3 signaling. Importantly, JAK1 or BRD4 inhibition sensitizes breast cancer to HDAC inhibitors, implicating combination inhibition of HDAC with JAK1 or BRD4 as potential therapies for breast cancer.
Activation of the stimulator of interferon gene (STING) pathway within the tumor microenvironment has been shown to generate a strong antitumor response. Although local administration of STING agonists has promise for cancer immunotherapy, the dosing regimen needed to achieve efficacy requires frequent intratumoral injections over months. Frequent dosing for cancer treatment is associated with poor patient adherence, with as high as 48% of patients failing to comply. Multiple intratumoral injections also disrupt the tumor microenvironment and vascular networks and therefore increase the risk of metastasis. Here, we developed microfabricated polylactic-co-glycolic acid (PLGA) particles that remain at the site of injection and release encapsulated STING agonist as a programmable sequence of pulses at predetermined time points that mimic multiple injections over days to weeks. A single intratumoral injection of STING agonist–loaded microparticles triggered potent local and systemic antitumor immune responses, inhibited tumor growth, and prolonged survival as effectively as multiple soluble doses, but with reduced metastasis in several mouse tumor models. STING agonist–loaded microparticles improved the response to immune checkpoint blockade therapy and substantially decreased the tumor recurrence rate from 100 to 25% in mouse models of melanoma when administered during surgical resection. In addition, we demonstrated the therapeutic efficacy of STING microparticles on an orthotopic pancreatic cancer model in mice that does not allow multiple intratumoral injections. These findings could directly benefit current STING agonist therapy by decreasing the number of injections, reducing risk of metastasis, and expanding its applicability to hard-to-reach cancers.
IntroductionLate-life depression (LLD) is a common and disabling disorder, which is typically defined as depression in individuals older than 60 years. Estimates of the prevalence of clinically relevant depressive symptoms in older adults typically range from 10% to 15%, and rates of major depression range from 1% to 5%.1-3 Late-life depression is characterized by diverse etiological factors that remain poorly understood.4,5 Successes in delineating the neurobiology of LLD have closely paralleled progress in neuroimaging and have provided evidence that LLD is associated with underlying brain anatomic and functional abnormalities. Structural neuroimaging findings have revealed grey matter volume reductions in multiple fronto-striatal-limbic regions of older depressed patients, including the anterior cingulate cortex (ACC), the prefrontal cortices, the striatum, the hippocampus and the amygdala, 4,6,7 and these regions are The aim of the present study was to conduct a meta-analysis that integrated the reported VBM studies, to determine consistent grey matter alterations in individuals with LLD. Methods: A systematic search was conducted to identify VBM studies that compared patients with LLD and healthy controls. We performed a meta-analysis using the effect size signed differential mapping method to quantitatively estimate regional grey matter abnormalities in patients with LLD. Results: We included 9 studies with 11 data sets comprising 292 patients with LLD and 278 healthy controls in our meta-analysis. The pooled and subgroup meta-analyses showed robust grey matter reductions in the right lentiform nucleus extending into the parahippocampus, the hippocampus and the amygdala, the bilateral medial frontal gyrus and the right subcallosal gyrus as well as a grey matter increase in the right lingual gyrus. Meta-regression analyses showed that mean age and the percentage of female patients with LLD were not significantly related to grey matter changes. Limitations: The analysis techniques, patient characteristics and clinical variables of the studies included were heterogeneous, and most participants were medicated. Conclusion: The present meta-analysis is, to our knowledge, the first to overcome previous inconsistencies in the VBM studies of LLD and provide robust evidence for grey matter alterations within fronto-striatal-limbic networks, thereby implicating them in the pathophysiology of LLD. The mean age and the percentage of female patients with LLD did not appear to have a measurable impact on grey matter changes, although we cannot rule out the contributory effects of medication.
Alterations in cortical thickness have been identified in major depressive disorder (MDD), but findings have been variable and inconsistent. To date, no reliable tools have been available for the meta-analysis of surface-based morphometric (SBM) studies to effectively characterize what has been learned in previous studies, and drug treatments may have differentially impacted findings. We conducted a comprehensive meta-analysis of magnetic resonance imaging (MRI) studies that explored cortical thickness in medication-free patients with MDD, using a newly developed meta-analytic mask compatible with seed-based d mapping (SDM) meta-analytic software. We performed the meta-regression to explore the effects of demographics and clinical characteristics on variation in cortical thickness in MDD. Fifteen studies describing 529 patients and 586 healthy controls (HCs) were included. Medication-free patients with MDD, relative to HCs, showed a complex pattern of increased cortical thickness in some areas (posterior cingulate cortex, ventromedial prefrontal cortex, and anterior cingulate cortex) and decreased cortical thickness in others (gyrus rectus, orbital segment of the superior frontal gyrus, and middle temporal gyrus). Most findings in the whole sample analysis were confirmed in a meta-analysis of studies recruiting medication-naive patients. Using the new mask specifically developed for SBM studies, this SDM meta-analysis provides evidence for regional cortical thickness alterations in MDD, mainly involving increased cortical thickness in the default mode network and decreased cortical thickness in the orbitofrontal and temporal cortex.
One of the biggest hurdles for the development of metabolism-targeted therapies is to identify the responsive tumor subsets. However, the metabolic vulnerabilities for most human cancers remain unclear. Establishing the link between metabolic signatures and the oncogenic alterations of receptor tyrosine kinases (RTK), the most well-defined cancer genotypes, may precisely direct metabolic intervention to a broad patient population. By integrating metabolomics and transcriptomics, we herein show that oncogenic RTK activation causes distinct metabolic preference. Specifically, EGFR activation branches glycolysis to the serine synthesis for nucleotide biosynthesis and redox homeostasis, whereas FGFR activation recycles lactate to fuel oxidative phosphorylation for energy generation. Genetic alterations of EGFR and FGFR stratify the responsive tumors to pharmacological inhibitors that target serine synthesis and lactate fluxes, respectively. Together, this study provides the molecular link between cancer genotypes and metabolic dependency, providing basis for patient stratification in metabolism-targeted therapies.
ParticipantsA total of 1,558 participants, including 782 patients with major depressive disorder (MDD) and 776 healthy controls (HCs), were recruited from 5 research centers in China (The Second Xiangya Hospital, ). The detailed inclusion and exclusion criteria for each center are listed below. CMU dataset:Four hundred thirty-one participants were recruited for participation in this study, including 155 patients with MDD and 276 HCs. All patients with MDD were recruited from the outpatient clinic at the Department of Psychiatry, First Affiliated Hospital of China Medical University and the Mental Health Center of Shenyang. Patients with MDD were diagnosed by two trained psychiatrists using the Structured Clinical Interview for DSM-IV Disorders. Participants with MDD met the DSM-IV diagnostic criteria for MDD but not for any other Axis I disorders. The severity of depression was rated using the 17-item HDRS (Williams, 1988) and the Clinical Global Impression of Severity Scale (Guy, 1976). The control group was recruited from the local community. HC participants did not have a current or lifetime history of Axis I disorders or a history of psychotic, mood, or other Axis I disorders in first-degree relatives as determined from the detailed family history. The participants were excluded for the following reasons: 1) a lifetime history of substance/alcohol abuse or dependence, 2) a concomitant major medical disorder, 3) any MRI contraindications, 4) a history of head trauma with loss of consciousness ≥5 minutes or any neurological disorder, and 5) suboptimal imaging data quality. The study was approved by the Institutional Review Board of China Medical University. Among these participants, 1 patient and 5 HCs were excluded because of duplicate data in the data transfer, 1 HC was excluded due to errors in raw DICOM data, 6 patients were excluded due to the use of different scanning parameters, 3 HCs were excluded due to abnormalities in anatomical brain images, 6 patients and 6 HCs were excluded for large head motion during the R-fMRI scan (exceeding 3 mm of translational movements or 3° of rotational movements), 13 patients and 8 HCs were excluded because the MRI scan did not cover the entire brain, 4 patients and 2 HCs were excluded due to a change in the diagnosis in follow-up interviews, 1 HC was excluded due to a lack of demographic information, and 1 HC was excluded because of his young age. Finally, data from the remaining 125 patients with MDD and 249 HCs were used in the present study. CSU dataset:Patients with MDD were recruited from inpatient or outpatient departments of the Psychiatry Hospital of Zhumadian, Henan Province, China. The diagnosis of MDD was confirmed by
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