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Abstract Background: HER2-positive (HER2+) breast cancer accounts for 20–30% of all breast cancers. Although trastuzumab has significantly improved the survival of patients with HER2+ breast cancer, more than 70% of patients develop drug resistance within one year of treatment. Understanding the molecular mechanisms of trastuzumab resistance and identifying biomarkers that predict early trastuzumab resistance would greatly benefit patients receiving trastuzumab therapy. Methods: Differential-gene-expression analysis of trastuzumab-sensitive and resistant HER2+ breast cancer cell lines from GSE15043 was performed to identify the biomarkers associated with trastuzumab resistance. Differential biomarker expression was confirmed in FFPE tissues collected from clinical HER2+ breast cancer tumor samples that were sensitive or resistant to trastuzumab treatment. The function of the biomarkers associated with trastuzumab resistance was studied using western blotting, immunofluorescence, electron microscopy, and siRNA knockdown and overexpression to elucidate the role and mechanisms of the biomarker in affecting the trastuzumab response. Results: UGT1A7, a member of the uronic acid transferase family, was associated with trastuzumab resistance. UGT1A7 expression was downregulated in trastuzumab-resistant tumor tissues and in a cell line that developed trastuzumab resistance (BT474TR). Overexpressing UGT1A7 in BT474TR restored their sensitivity to trastuzumab treatment, whereas downregulating UGT1A7 expression in parental cells led to trastuzumab resistance. Importantly, UGT1A7 localized to the endoplasmic reticulum and altered stress responses. Furthermore, downregulating UGT1A7 expression promoted epithelial-to-mesenchymal transition (EMT) by affecting TWIST, SNAIL, and GRP78 expression and the AMP-activated protein kinase signaling pathway, thus contributing to trastuzumab resistance. Conclusions: This study demonstrated the important role and novel mechanisms of UGT1A7 in tumor responses to trastuzumab. Low UGT1A7 expression plays an important role in EMT and contributes to trastuzumab resistance. UGT1A7 has the potential to be developed as a biomarker for identifying patients who are resistant to trastuzumab treatment.

Abstract Accumulating evidence suggests that changes in the tumor microenvironment caused by radiotherapy are closely related to the recurrence of glioma. However, the mechanisms by which such radiation‐induced changes are involved in tumor regrowth have not yet been fully investigated. In the present study, how cranial irradiation‐induced senescence in non‐neoplastic brain cells contributes to glioma progression is explored. It is observed that senescent brain cells facilitated tumor regrowth by enhancing the peripheral recruitment of myeloid inflammatory cells in glioblastoma. Further, it is identified that astrocytes are one of the most susceptible senescent populations and that they promoted chemokine secretion in glioma cells via the senescence‐associated secretory phenotype. By using senolytic agents after radiotherapy to eliminate these senescent cells substantially prolonged survival time in preclinical models. The findings suggest the tumor‐promoting role of senescent astrocytes in the irradiated glioma microenvironment and emphasize the translational relevance of senolytic agents for enhancing the efficacy of radiotherapy in gliomas.

AbstractBackgroundWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use at the midway point of data collection of the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS). We compared amyloid‐positive early‐onset Alzheimer’s disease (EOAD) participants and amyloid‐negative early‐onset non‐Alzheimer’s disease [EOnonAD]) participants across NPS domains and psychotropic medication categories.Method282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid‐negative EOnonAD (n = 70). All participants were between ages 40 and 64 at baseline. NPS were measured with the Neuropsychiatric Inventory – Questionnaire (NPI‐Q) and Geriatric Depression Scale – Short Form (GDS‐SF). Medications were categorized into psychotropic category (e.g., antidepressants, antipsychotics, benzodiazepines). Groups were compared on NPI‐Q using binary logistic regression adjusting for sex and disease severity, on GDS‐SF using linear regression adjusting for sex and disease severity, and on psychotropic medication use using Chi square or Fisher’s exact test.ResultDemographic data are presented in Table 1. Average total NPI‐Q score was higher in EOnonAD than EOAD (p = .002, ŋp 2 = .03). Regardless of diagnostic group, informants endorsed Affective behaviors most frequently (76.2%). EOAD informants endorsed fewer Distress‐Tension behaviors (p = .02, OR = .498) and Impulse Control behaviors (p = .01, OR = .438). EOAD informants also endorsed apathy (p < .001, OR = .316), irritability (p = .02, OR = .498), and disinhibition (p = .04, OR = .476) at lower frequency than EOnonAD. GDS‐SF showed that the EOnonAD participants self‐reported more symptoms of depression than the EOAD group (p = .002, ŋp 2 = .03). (Table 2A). A minority of participants, regardless of diagnostic group, reported psychotropic medication use (35%). There was higher use in EOnonAD (38%) than EOAD (24%) (p = .03, Cohen W = .14) (Table 2B).ConclusionNPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants, despite EOnonAD being less severely impaired. LEADS continues to collect data. Future studies will examine etiologies that may be larger drivers of NPS than AD neuropathology, mediators (e.g., race, ethnicity) in the association between NPS and diagnostic group classication, compare NPS in EOAD vs. LOAD, and examine longitudinal changes in neuropsychiatric profiles.

AbstractBackgroundApproximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer’s Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns.MethodCognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume.ResultScree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration.

AbstractBackgroundAlzheimer’s Disease (AD) has no cure. We showed that partial inhibition of mitochondrial complex I (MCI) with small molecule CP2 induced adaptive stress response activating multiple neuroprotective mechanisms. Chronic treatment reduced inflammation, improved synaptic and mitochondrial functions, and blocked neurodegeneration in symptomatic APP/PS1 mice, a translational model of AD.MethodsAnalysis of mitochondrial morphology and mitochondria‐endoplasmic reticulum (ER) contacts (MERCS) was done in the hippocampal CA1 tissue from APP/PS1 mice treated with CP2 and compared to APP/PS1 and non‐transgenic mice treated with vehicle using serial block‐face scanning electron microscopy (SBFSEM) and three‐dimensional (3D) EM reconstructions combined with western blot analysis and next generation RNA sequencing.ResultsWe demonstrate that CP2 treatment restores mitochondrial morphology and mitochondria‐ ER communication, reducing ER stress in the APP/PS1 mouse brain. Using 3D EM reconstructions, we found that mitochondria in AD dendrites existed primarily as mitochondria‐on‐a‐string (MOAS), a morphological phenotype that is difficult to detect using conventional 2D EM or fluorescence spectroscopy. Compared to other morphological phenotypes, MOAS are extensively enveloped in the ER membranes forming multiple MERCS known to contribute to abnormal lipid and calcium homeostasis, and ER stress in AD. CP2 treatment specifically reduced MOAS formation, consistent with improved energy homeostasis in the brain, with concomitant reduction in MERCS, ER stress, and improved lipid homeostasis.ConclusionsThese data provide novel information on the role MOAS play in AD. Our data demonstrate that in response to energetic stress, mitochondria in dendrites acquire MOAS phenotype with increased interaction with the ER, which may synergistically contribute to the AD development. Since CP2 treatment alleviated the ER stress and improved mitochondrial dynamics and function, these data further support the development of partial MCI inhibitors as disease modifying strategy for AD.

AbstractBackgroundInter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, and maintenance of the blood‐brain‐barrier (BBB) properties. The breakdown of BBB in Alzheimer’s disease (AD) is well‐established, but precise underlying molecular changes remain unclear. Additionally, whether GVU molecular alterations observed in AD brains are also detected in blood from living patients is unknown. Further, these GVU molecular perturbations require further investigation in different model systems to identify both human brain‐specific and cross‐species conserved alterations. In this study, we investigated prioritized GVU molecules altered in AD brains for their conservation in blood and cross‐species model systems.MethodsWe performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in AD and control brains. We analyzed this data to detect cell‐specific GVU molecular perturbations and their interactions. We investigated molecular interactions between vascular and astrocyte clusters, the major cell types of the GVU of the BBB. To determine whether GVU transcriptional alterations detected in the brain are preserved in the blood, existing blood expression, genetic, and neuroimaging data from two longitudinal antemortem cohorts were analyzed. Using model systems, including mouse, drosophila, and zebrafish, we evaluated the cross‐species conservation of the top GVU alterations detected in AD brains.ResultsBrain snRNAseq revealed transcriptional profiles of 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as pericytes, endothelia and perivascular fibroblasts. We identified differentially expressed genes and their enriched pathways within these clusters and observed the highest levels of transcriptional changes within pericytes. Vascular targets that interact with astrocytic ligands have biological functions in cell signaling, angiogenesis, amyloid ß metabolism, and cytoskeletal architecture. We discovered that genetic variants influencing blood expression levels of some of the prioritized GVU genes were associated with neuroimaging burden of cerebrovascular disease in living human cohorts. Our ongoing studies in model systems revealed conservation of some of the top prioritized molecular perturbations across species.ConclusionOur findings prioritized by multiscale, cross‐tissue human data revealed GVU perturbations within interacting pericyte and astrocyte molecules, which are conserved across multiple cross‐species models. These results nominate new molecular targets and mechanistic insights for BBB disruptions in AD.

AbstractBackgroundContext‐specific networks can capture functionally important genes that may not be differentially expressed. Leveraging seven different gene expression datasets of Alzheimer’s disease (AD) and healthy control brains, we constructed a novel pipeline that includes such network analysis, augmented by in vivo validations and in silico drug repurposing to facilitate prioritization of AD therapeutic targets.MethodWe utilized publicly available gene expression data from 733 AD and 454 control brains across 7 datasets and the NetDecoder (PMID: 26975659) network biology platform to build context‐specific networks. Based on the known protein‐protein interaction and gene expression correlations, information flow from the top differentially expressed genes (DEG) to transcriptional regulator genes was calculated using a process‐guided flow algorithm. Genes with the greatest informational flow changes across AD cohorts were systematically prioritized. We next validated these genes in a medium‐throughput screen of a tau‐transgenic Drosophila model (PMID: 11408621). Further, we identified existing small‐molecule drugs to target the candidate genes utilizing curated databases.ResultsA total of 14 context‐specific networks were constructed across 7 datasets. We found AD‐related genes, such as APP, to have high flow differences between AD and control networks and high connectivity. Notably, many such genes were not DEGs between AD and control, suggesting that the information flow captures novel aspects of AD pathophysiology. We nominated 224 unique genes with the greatest flow differences for functional validation. We screened 111 of the 224 candidate genes with readily available, high‐confidence orthologs in Drosophila. We identified genes that suppress (N = 68) or enhance (N = 27) tau‐related neurodegeneration in this model. We confirmed the effects of previously nominated genes, such as HDAC1, which enhances tau‐neurodegeneration if overexpressed and suppresses it if knocked down. We also identified and validated additional therapeutic targets. Lastly, we applied a network‐proximity‐based algorithm and identified small molecule drugs for the candidate genes.ConclusionWe present a novel pipeline that integrates analytic approaches, experimental validation, and drug repurposing to facilitate therapeutic discovery in AD. We applied this pipeline and nominated previously known and novel genes implicated in AD pathogenesis. Our pipeline demonstrates a cross‐species, systems‐level approach to therapeutic nomination in AD and related neurodegenerative diseases.

AbstractUnesbulin is being investigated in combination with dacarbazine (DTIC) as a potential therapeutic agent in patients with advanced leiomyosarcoma (LMS). This paper reports the pharmacokinetics (PK) of unesbulin, DTIC, and its unreactive surrogate metabolite 5‐aminoimidazole‐4‐carboxamide (AIC) in 29 patients with advanced LMS. Drug interactions between DTIC (and AIC) and unesbulin were evaluated. DTIC (1000 mg/m2) was administered to patients with LMS via 1‐h intravenous (i.v.) infusion on day 1 of every 21‐day (q21d) cycle. Unesbulin dispersible tablets were administered orally twice weekly (b.i.w.), starting on day 2 of every cycle, except for cycle 2 (C2), where unesbulin was dosed either on day 1 together with DTIC or on day 2, 1 day after DTIC administration. The PK of DTIC, AIC, and unesbulin in cycle 1 (C1) and C2 were estimated using noncompartmental analysis. DTIC and AIC were measurable immediately after the start of infusion and reached maximum plasma concentration (Cmax) immediately or shortly after end of infusion at 1.0 and 1.4 h (time to Cmax), respectively. Co‐administration of unesbulin orally at 200 mg or above with DTIC inhibited cytochrome P450 (CYP)1A2‐mediated DTIC metabolism, resulting in 66.7% reduction of AIC exposures. Such inhibition could be mitigated when unesbulin was dosed the day following DTIC infusion. Repeated unesbulin dosing demonstrated evidence of clinical CYP1A2 induction and increased AIC Cmax by 69.4% and area under concentration‐time curve to infinity by 57.9%. No meaningful difference in unesbulin PK was observed between C2 and C1. The combination therapy of 1000 mg/m2 i.v. DTIC q21d and 300 mg unesbulin b.i.w. in a staggered regimen is well‐tolerated in patients with LMS.