Microarray Analysis Of Gene Expression Research Articles

Alleviation of Angiotensin II-Induced Vascular Endothelial Cell Injury through Long Non-coding RNA TUG1 Inhibition.

Hypertension damages endothelial cells, causing vascular remodelling. It is caused by Ang II-induced endothelial cell (EC) destruction. The long noncoding RNA (lncRNAs) are emerging regulators of endothelium homeostasis. Injured endothelium expresses lncRNA taurine-upregulated gene 1 (TUG1), which may mediate endothelial cell damage, proliferation, apoptosis, and autophagy and contribute to cardiovascular disease. However, uncertainty surrounds the function of lncRNA TUG1, on arterial endothelium cell damage. This research aimed to investigate the role and mechanism of lncRNA TUG1 in vascular endothelial cell injury. A microarray analysis of lncRNA human gene expression was used to identify differentially expressed lncRNAs in human umbilical vein endothelial cell (HUVEC) cultures. The viability, apoptosis, and migration of Ang II-treated HUVECs were then evaluated. In order to investigate the role of lncRNA TUG1 in hypertension, qRT-PCR, western blotting, and RNA-FISH were used to examine the expression of TUG1 in SHR mice. Ang II-activated HUVECs and SHR rats' abdominal aortas highly express the lncRNA TUG1. LncRNA TUG1 knockdown in HUVECs could increase cell viability, reduce apoptosis, and produce inflammatory factors. In SHR rat abdominal aortas, lncRNA TUG1 knockdown promoted proliferation and inhibited apoptosis. HE spotting showed that lncRNA TUG1 knockdown improved SHR rats' abdominal aorta shape. lncRNA TUG1 knockdown promotes miR-9- 5p, which inhibits CXCR4 following transcription. The lncRNA TUG1/miR-9-5p/CXCR4 axis and vascular cell injury were also examined. MiR-9-5p silencing or CXCR4 overexpression lowered cell survival, apoptosis, and lncRNA TUG1-induced IL-6 and NO expression. lncRNA TUG1 suppression could reduce Ang II-induced endothelial cell damage by regulating and targeting miR-9-5p to limit CXCR4 expression and open new vascular disease research pathways.

Downregulation of Serum PTEN Expression in Mercury-Exposed Population and PI3K/AKT Pathway-Induced Inflammation

ObjectiveThis study investigated the impact of occupational mercury (Hg) exposure on human gene transcription and expression, and its potential biological mechanisms. MethodsDifferentially expressed genes related to Hg exposure were identified and validated using gene expression microarray analysis and extended validation. Hg-exposed cell models and PTEN low-expression models were established in vitro using 293T cells. PTEN gene expression was assessed using qRT-PCR, and Western blotting was used to measure PTEN, AKT, and PI3K protein levels. IL-6 expression was determined by ELISA. ResultsCombined findings from gene expression microarray analysis, bioinformatics, and population expansion validation indicated significant downregulation of the PTEN gene in the high-concentration Hg exposure group. In the Hg-exposed cell model (25 and 10 μmol/L), a significant decrease in PTEN expression was observed, accompanied by a significant increase in PI3K, AKT, and IL-6 expression. Similarly, a low-expression cell model demonstrated that PTEN gene knockdown led to a significant decrease in PTEN protein expression and a substantial increase in PI3K, AKT, and IL-6 levels. ConclusionThis is the first study to report that Hg exposure downregulates the PTEN gene, activates the PI3K/AKT regulatory pathway, and increases the expression of inflammatory factors, ultimately resulting in kidney inflammation.

Cross-platform gene expression profiling of breast cancer: Exploring the relationship between breast cancer grades and gene expression pattern

Gene expression profiling is a powerful tool that has been extensively used to investigate the underlying biology and etiology of diseases, including cancer. Microarray gene expression analysis enables simultaneous measurement of thousands of mRNA levels. Sophisticated computational approaches have evolved in parallel with the rapid progress in bioassay technologies, enabling more effective analysis of the large and complex datasets that these technologies produce.In this study, we utilized systems biology approaches to examine gene expression profiles across different grades of breast cancer progression. We conducted a meta-analysis of publicly available microarray data to elucidate the molecular mechanisms underlying breast cancer grade classification.Our results suggest that while grade index is commonly used for evaluating cancer progression status in the clinic, the complexity of molecular mechanisms, histological characteristics, and other factors related to patient outcomes raises doubts about the utility of breast cancer grades as a foundation for formulating treatment protocols.Our study underscores the importance of advancing personalized strategies for breast cancer classification and management. More research is crucial to refine diagnostic tools and treatment modalities, aiming for greater precision and tailored care in patient outcomes.

Enhancement of Classifier Performance with Adam and RanAdam Hyper-Parameter Tuning for Lung Cancer Detection from Microarray Data-In Pursuit of Precision.

Microarray gene expression analysis is a powerful technique used in cancer classification and research to identify and understand gene expression patterns that can differentiate between different cancer types, subtypes, and stages. However, microarray databases are highly redundant, inherently nonlinear, and noisy. Therefore, extracting meaningful information from such a huge database is a challenging one. The paper adopts the Fast Fourier Transform (FFT) and Mixture Model (MM) for dimensionality reduction and utilises the Dragonfly optimisation algorithm as the feature selection technique. The classifiers employed in this research are Nonlinear Regression, Naïve Bayes, Decision Tree, Random Forest and SVM (RBF). The classifiers' performances are analysed with and without feature selection methods. Finally, Adaptive Moment Estimation (Adam) and Random Adaptive Moment Estimation (RanAdam) hyper-parameter tuning techniques are used as improvisation techniques for classifiers. The SVM (RBF) classifier with the Fast Fourier Transform Dimensionality Reduction method and Dragonfly feature selection achieved the highest accuracy of 98.343% with RanAdam hyper-parameter tuning compared to other classifiers.

Abstract 6441: Discovery of ARID1A loss as a patient biomarker for NXP800 - A developmental activator of the integrated stress response (ISR) and inhibitor of the HSF1 pathway in ovarian cancer

Abstract Background. HSF1 helps cancer cells cope with multiple stresses caused by oncogene activation. Methods. See details below. Results. We discovered the bisamide NXP800 as an inhibitor of HSF1-mediated transcription through phenotypic screening and med chem optimization. Gene expression microarray analysis of human cancer cell lines and tumor xenografts treated with bisamide inhibitors indicated activation of the ATF4 axis of the ISR as a key mechanism of action. In SK-OV-3 ovarian cancer xenografts, NXP800 showed clear PK/PD relationships with increased expression of ATF4 transcriptional target genes alongside decreased expression of HSF1 transcriptional targets. NXP800 also caused tumor regressions in this model. Expanding in additional human ovarian cancer xenograft models, we observed efficacy in five and a complete lack of response in three others. The sensitive models all had homozygous deleterious mutations in the ARID1A gene, whereas the non-responding xenografts were all wild type (WT). ARID1A is a component of the SWI/SNF chromatin remodelling complex involved in repression and activation of target genes. Subsequent screening of the large Sanger human cancer cell line panel confirmed ARID1A as the most significant common disease-related alteration predicting sensitivity to NXP800 in ovarian cancer cell lines. This predictive relationship was confirmed in an ARID1A isogenic HCT-116 cell line pair; sensitivity was greater in the homozygous ARID1A mutant cells compared to WT, resulting in PARP cleavage in the mutant cells only. In vivo there was no effect in WT HCT-116 xenografts whereas growth inhibition was observed in the homozygous mutant cells, resulting in significantly smaller tumors. In addition, the induction of ATF4 target genes was stronger and more prolonged in the mutant cells. It is known that whereas short term ATF4 activation is adaptive, persistent activation can promote the induction of apoptosis. CHIP-seq analysis confirmed clear relationships between ARID1A status, ATF4 and HSF1 promoter occupancy, and the distribution of BRG1 and RNA pol II at target sites, although these were often gene-specific and complex. A relatively simple example is the regulation of the INHBE gene (expression of which is a PD biomarker). In untreated samples there is no binding of ATF4, BRG1 and RNA pol II at the INHBE promoter. NXP800 treatment results in the recruitment of BRG1, ATF4 and RNA pol II in ARID1A mutant TOV-21G cells but not in the RMGI WT cells, leading to increased expression in the mutant cells only. Conclusions. We propose that ARID1A loss alters the binding and recruitment of ATF4 and HSF1 leading to the altered and prolonged expression of ATF4 target genes and increased sensitivity to NXP800. NXP800 is currently in phase Ib for the treatment of ARID1A mutant platinum resistant ovarian cancer (NCT05226507). Citation Format: Robert H. te Poele, Marissa Powers, Swee Sharp, Emmanuel de Billy, Maria Taskinen, Loredana Pellegrino, Sharon Gowan, Asadh Miah, Angela Hayes, Matthew Cheeseman, Keith Jones, Suzanne Eccles, Florence Raynaud, Paul Clarke, Paul Workman. Discovery of ARID1A loss as a patient biomarker for NXP800 - A developmental activator of the integrated stress response (ISR) and inhibitor of the HSF1 pathway in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6441.

Spatial Variability of Grape Berry Maturation Program at the Molecular Level

The application of sensors in viticulture is a fast and efficient method to monitor grapevine vegetative, yield, and quality parameters and determine spatial intra-vineyard variability. Molecular analysis at the gene expression level can further contribute to the understanding of the observed variability by elucidating how pathways contributing to different grape quality traits behave in zones diverging on any of these parameters. The intra-vineyard variability of a Cabernet Sauvignon vineyard was evaluated through a Normalized Difference Vegetation Index (NDVI) map calculated from a multispectral image and detailed ground-truthing (e.g., vegetative, yield, and berry ripening compositional parameters). The relationships between NDVI and ground measurements were explored by correlation analysis. Moreover, berries were investigated by microarray gene expression analysis performed at five time points from fruit set to full ripening. Comparison between the transcriptomes of samples taken from locations with the highest and lowest NDVI values identified 968 differentially expressed genes. Spatial variability maps of the expression level of key berry ripening genes showed consistent patterns aligned with the vineyard vigor map. These insights indicate that berries from different vigor zones present distinct molecular maturation programs and suggest that transcriptome analysis may be a valuable tool for the management of vineyard variability.

MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis.

The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.

Local Entropy Based Remora Optimization and Sparse Autoencoders for Cancer Diagnosis Through Microarray Gene Expression Analysis

Local Entropy Based Remora Optimization and Sparse Autoencoders for Cancer Diagnosis Through Microarray Gene Expression Analysis

Genetic Discrimination of Grade 3 and Grade 4 Gliomas by Artificial Neural Network.

Gliomas, including anaplastic gliomas (AG; grade 3) and glioblastomas (GBM; grade 4), are malignant brain tumors associated with poor prognosis and low survival rates. Current classification systems based on histopathology have limitations due to intratumoral heterogeneity. The treatment and prognosis are distinctly different between grade 3 and grade 4 gliomas patients. Therefore, there is a need for molecular markers to differentiate these tumors accurately. In this study, we aimed to identify a gene expression signature using an artificial neural network (ANN) in application to microarray and serial analysis of gene expression (SAGE) data for grade 3 (AG) and grade 4 (GBM) gliomas discrimination. We acquired gene expression data from publicly available datasets on glial tumors of grades 3 and 4-a total of 93 grade 3 gliomas and 224 grade 4 gliomas. To select genes for classification, we implemented an artificial neural network-based method using a combination of self-organized maps (SOM) and perceptron. In general, we implemented a multi-stage procedure that involved multiple runs of a genetic algorithm to identify genes that provided optimal clusterization on the SOM. We performed this procedure multiple times, resulting in different sets of genes each time. Eventually, we selected several genes that appeared most frequently in the reduced sets and performed classification using them. Our analysis identified a set of seven genes (BCAS4, GLUD2, KCNJ10, KCND2, AKR7A2, FOLR1, and KIAA0319). The classification accuracy using this gene set was 87.5%. These findings suggest the potential of this gene set as a molecular marker for distinguishing grade 3 (AG) from grade 4 (GBM) gliomas.

Chronic Stress Blocks the Endometriosis Immune Response by Metabolic Reprogramming.

Studies have shown that the occurrence and development of endometriosis are closely linked to long-term psychological stress. The specific contribution of chronic stress to the metabolic adaptations in patients with endometriosis is still unknown. Lesions were removed from ten endometriosis patients during an operation, and the participants were divided into two groups using a psychological questionnaire. An mRNA Human Gene Expression Microarray analysis was applied to compare the mRNA expression profiles between the chronic stress group and the control group. In addition, the reliability of the mRNA Human Gene Expression Microarray analysis was verified by using research on metabolites based on both the liquid chromatography (LC-MS/MS) technique and quantitative reverse transcription polymerase chain reaction (RT-PCR). A microarray analysis of significantly up-regulated, differentially expressed genes between the chronic stress and the control groups showed genes that were principally related to metabolism-related processes and immune-related processes, such as the immune response process, negative regulation of T cell proliferation, the leucine metabolic process, and the L-cysteine metabolic process (p < 0.05). LC-MS showed that the differential metabolites were primarily concerned with arginine and proline metabolism, D-glutamine and D-glutamate metabolism, aspartate metabolism, glycine, serine metabolism, and tyrosine metabolism (p < 0.05). The possibility of chronic stress blocks the endometriosis immune response through metabolic reprogramming. Chronic stress reduces the supply of energy substrates such as arginine and serine, down-regulates T immune cell activation, and affects the anti-tumor immune response, thereby promoting the migration and invasion of endometriosis lesions in patients with chronic stress.

Retracted: Microarray and Bioinformatics Analysis of Differential Gene and lncRNA Expression during Erythropoietin Treatment of Acute Spinal Cord Injury in Rats

Retracted: Microarray and Bioinformatics Analysis of Differential Gene and lncRNA Expression during Erythropoietin Treatment of Acute Spinal Cord Injury in Rats

DNA Methylation Aberrations in Dimethylarsinic Acid-Induced Bladder Carcinogenesis.

Arsenic is a known human urinary bladder carcinogen. While arsenic is known to cause aberrant DNA methylation, the mechanism of arsenic-triggered bladder carcinogenesis is not fully understood. The goal of this study was to identify aberrant DNA methylation in rat bladder urothelial carcinoma (UC) induced by dimethylarsinic acid (DMAV), a major organic metabolite of arsenic. We performed genome-wide DNA methylation and microarray gene expression analyses of DMAV-induced rat UCs and the urothelium of rats treated for 4 weeks with DMAV. We identified 40 genes that were both hypermethylated and downregulated in DMAV-induced rat UCs. Notably, four genes (CPXM1, OPCML, TBX20, and KCND3) also showed reduced expression in the bladder urothelium after 4 weeks of exposure to DMAV. We also found that CPXM1 is aberrantly methylated and downregulated in human bladder cancers and human bladder cancer cells. Genes with aberrant DNA methylation and downregulated expression in DMAV-exposed bladder urothelium and in DMAV-induced UCs in rats, suggest that these alterations occurred in the early stages of arsenic-induced bladder carcinogenesis. Further study to evaluate the functions of these genes will advance our understanding of the role of aberrant DNA methylation in arsenic bladder carcinogenesis, and will also facilitate the identification of new therapeutic targets for arsenic-related bladder cancers.

Leukemia inhibitory factor shortens primary cilia by upregulating C-C motif chemokine 2 in human neural stem/progenitor cells.

Primary cilia on neural stem/progenitor cells (NSPCs) play an important role in determining cell fate, although the regulatory mechanisms involved in the ciliogenesis remain largely unknown. In this study, we analyzed the effect of the leukemia inhibitory factor (LIF) for the primary cilia in immortalized human NSPCs. LIF withdrawal elongated the primary cilia length, whereas the addition of LIF shortened it. Microarray gene expression analysis revealed that differentially expressed genes (DEGs) associated with LIF treatment were related with the multiple cytokine signaling pathways. Among the DEGs, C-C motif chemokine 2 (CCL2) had the highest ranking and its increase in the protein concentration in the NSPCs-conditioned medium after the LIF treatment was confirmed by ELISA. Interestingly, we found that CCL2 was a negative regulator of cilium length, and LIF-induced shortening of primary cilia was antagonized by CCL2-specific antibody, suggesting that LIF could influence cilia length via upregulating CCL2. The shortening effect of LIF and CCL2 on primary cilia was also observed in SH-SY5Y cells. The results of the study suggested that the LIF-CCL2 axis may well be a regulator of NSPCs and its primary cilia length, which could affect multiple cellular processes, including NSPC proliferation and differentiation.

Parvalbumin expression changes with retinal ganglion cell degeneration.

Glaucoma is one of the main causes of irreversible visual field loss and blindness worldwide. Vision loss in this multifactorial neurodegenerative disease results from progressive degeneration of retinal ganglion cells (RGCs) and their axons. Identifying molecular markers that can be measured objectively and quantitatively may provide essential insights into glaucoma diagnosis and enhance pathophysiology understanding. The chronic, progressive DBA/2J glaucomatous mouse model of glaucoma and C57BL6/J optic nerve crush (ONC) mouse model were used in this study. Changes in PVALB expression with RGC and optic nerve degeneration were assessed via gene expression microarray analysis, quantitative real-time polymerase chain reaction (qRT-PCR), Western blot and immunohistochemistry. Microarray analysis of the retinal gene expression in the DBA/2J mice at different ages showed that the expression of PVALB was downregulated as the mice aged and developed glaucoma with retinal ganglion cell loss. Analysis of qRT-PCR results demonstrated PVALB at the mRNA level was reduced in the retinas and optic nerves of old DBA/2J mice and in those after ONC compared to baseline young DBA2/J mice. PVALB protein expression measured by Western blot was also significantly reduced signal in the retinas and optic nerves of old DBA/2J mice and those eyes with crushed nerves. Immunohistochemical staining results demonstrated that there were fewer PVALB-positive cells in the ganglion cell layer (GCL) of the retina and staining pattern changed in the optic nerve from old DBA/2J mice as well as in mice eyes following ONC. PVALB is abundantly expressed both by RGCs' soma in the retinas and RGCs' axons in the optic nerves of C57BL/6J. Furthermore, the expression level of PVALB decreases with RGC degeneration in the glaucomatous DBA/2J mice and after ONC injury of C57BL6/6J, indicating that PVALB is a reliable RGC molecular marker that can be used to study retinal and optic nerve degeneration.

Cross-Comparison Individual Patient Level Analysis of Three Gene Expression Signatures in Localized Prostate in over 50,000 Men

Risk stratification guides the management of localized prostate cancer. Multiple commercial gene expression biomarkers have been developed to improve estimates of prognosis, however the 22-gene Decipher genomic classifier (22-GC) is the only test with level 1 evidence supporting its use per NCCN guidelines. It is unknown whether other commercial signatures, Oncotype (GPS) or Prolaris (CCP), are sufficiently correlated to negate the differences in evidence supporting these commercial tests. Herein, we aim to perform a cross-comparison of these signatures in a large cohort of patients diagnosed with localized prostate cancer. Patients diagnosed with localized prostate cancer who underwent whole transcriptome gene expression microarray analysis on their primary tumor biopsy specimen were included. The 22-GC score was calculated by Veracyte using a commercially locked model. Individual genes in each of the GPS and CCP gene signatures were identified, and the gene weights in each signature were retrained for prediction of metastasis in a multi-institutional cohort of 1,574 men with long-term outcome data. This was performed to improve correlation performance of GPS and CCP given only the 22-GC was trained for prediction of metastasis. For each of the three signatures, both continuous and categorical scores were calculated. Linear regression and spearman correlations were calculated both on univariable and multivariable analyses adjusting for age, grade group, PSA, and T-stage. A total of 50,881 patients were included (15,379 (30.2%) NCCN low-risk, 14,773 (29.0%) favorable intermediate-risk, 15,544 (30.5%) unfavorable intermediate-risk, and 5,185 (10.2%) high/very high-risk) with a median age of 68 years, and a median PSA of 6.2 ng/mL. On linear regression, the GPS model had poor goodness-of-fit to the 22-GC with an R2 of 0.36, as did the CCP model to the 22-GC with an R2 of 0.32. For CCP, the linear sum of the 31-genes was also tested but had inferior performance (R2 0.28) compared to the reoptimized CCP model. Results were similar on multivariable analysis adjusting for age, PSA, clinical stage and grade group. Spearman correlation between the continuous GPS model scores and the 22-GC was moderate at 0.59, as was the correlation between CCP model and the 22-GC of 0.54. CCP is a measure of proliferation, but in 22-GC high-risk patients, the majority (64.1%) of patients had low-average proliferation and only 35.9% had high proliferation, potentially explaining the lack of strong correlation. There is minimal to moderate correlation between the 22-GC and GPS or CCP gene expression signatures tested. Therefore, these tests should not be viewed as interchangeable, and utilization should be based on the level of evidence supporting each gene expression biomarker.

BluePrint molecular subtypes predict response to neoadjuvant pertuzumab in HER2-positive breast cancer

BackgroundThe introduction of pertuzumab has greatly improved pathological complete response (pCR) rates in HER2-positive breast cancer, yet effects on long-term survival have been limited and it is uncertain which patients derive most benefit. In this study, we determine the prognostic value of BluePrint subtyping in HER2-positive breast cancer. Additionally, we evaluate its use as a biomarker for predicting response to trastuzumab-containing neoadjuvant chemotherapy with or without pertuzumab.MethodsFrom a cohort of patients with stage II-III HER2-positive breast cancer who were treated with neoadjuvant chemotherapy and trastuzumab with or without pertuzumab, 836 patients were selected for microarray gene expression analysis, followed by readout of BluePrint standard (HER2, Basal and Luminal) and dual subtypes (HER2-single, Basal-single, Luminal-single, HER2-Basal, Luminal-HER2, Luminal-HER2-Basal). The associations between subtypes and pathological complete response (pCR), overall survival (OS) and breast cancer-specific survival (BCSS) were assessed, and pertuzumab benefit was evaluated within the BluePrint subgroups.ResultsBluePrint results were available for 719 patients. In patients with HER2-type tumors, the pCR rate was 71.9% in patients who received pertuzumab versus 43.5% in patients who did not (adjusted Odds Ratio 3.43, 95% CI 2.36–4.96). Additionally, a significantly decreased hazard was observed for both OS (adjusted hazard ratio [aHR] 0.45, 95% CI 0.25–0.80) and BCSS (aHR 0.46, 95% CI 0.24–0.86) with pertuzumab treatment. Findings were similar in the HER2-single subgroup. No significant benefit of pertuzumab was seen in other subtypes.ConclusionsIn patients with HER2-type or HER2-single-type tumors, pertuzumab significantly improved the pCR rate and decreased the risk of breast cancer mortality, which was not observed in other subtypes. BluePrint subtyping may be valuable in future studies to identify patients that are likely to be highly sensitive to HER2-targeting agents.

Strain-dependent lung transcriptomic differences in cigarette smoke and LPS models of lung injury in mice.

Background Cigarette smoke exposure increases the risk of developing Acute Respiratory Distress Syndrome (ARDS) after a number of disparate insults 1-3. It is not known why some at risk individuals develop ARDS, while others do not. Based on our previous finding that smoke-exposed AKR mice were more susceptible to lipopolysaccharides (LPS)-induced Acute Lung Injury (ALI) than C57BL/6 mice4, we investigated strain-dependent lung transcriptomic responses to cigarette smoke exposure. Methods Eight week old male AKR and C57BL/6 mice were exposed to 3 weeks of room air (RA) or cigarette smoke (CS) for 6 hours per day, 4 days per week, followd by intra-tracheal instillation of LPS or normal saline (NS) and microarray analysis of lung homogenate gene expression. Other groups of AKR and C57 mice were similarly exposed to RA or CS for 6 weeks, followed by evaluation of lung mechanics, pathology, and gene expression. Results Transcriptomic analyses of lung homogenates show distinct strain dependent lung transcriptional responses to CS and LPS, with AKR mice having larger numbers of genes affected than similarly treated C57 mice, congruent with strain differences in physiologic and inflammatory parameters previously observed in LPS-induced ALI after CS priming. These results suggest that genetic differences may underlie differing susceptibility of smokers to ARDS and emphysema. Conclusions Strain-based differences in gene transcription contribute to CS and LPS induced lung injury. Implications There may be a genetic basis for smoking related susceptibility to lung injury. Clinicians should consider cigarette smoke exposure as a risk factor for ALI and ARDS.

Sox13 and M2-like leukemia-associated macrophages contribute to endogenous IL-34 caused accelerated progression of acute myeloid leukemia

Interleukin 34 (IL-34) mainly plays physiologic and pathologic roles through the sophisticated multi-ligand signaling system, macrophage colony-stimulating factor (M-CSF, CSF-1)/IL-34-CSF-1R axis, which exhibits functional redundancy, tissue-restriction and diversity. This axis is vital for the survival, differentiation and function of monocytic lineage cells and plays pathologic roles in a broad range of diseases. However, the role of IL-34 in leukemia has not been established. Here MLL-AF9 induced mouse acute myeloid leukemia (AML) model overexpressing IL-34 (MA9-IL-34) was used to explore its role in AML. MA9-IL-34 mice exhibited accelerated disease progression and short survival time with significant subcutaneous infiltration of AML cells. MA9-IL-34 cells showed increased proliferation. In vitro colony forming assays and limiting dilution transplantation experiments demonstrated that MA9-IL-34 cells had elevated leukemia stem cell (LSC) levels. Gene expression microarray analysis revealed a panel of differential expressed genes including Sex-determining region Y (SRY)-box 13 (Sox13). Furthermore, a positive correlation between the expressions of IL-34 and Sox13 was detected human datasets. Knockdown of Sox13 rescued the enhanced proliferation, high LSC level and subcutaneous infiltration in MA9-IL-34 cells. Moreover, more leukemia-associated macrophages (LAMs) were detected in MA9-IL-34 microenvironment. Additionally, those LAMs showed M2-like phenotype since they expressed high level of M2-associated genes and had attenuated phagocytic potential, suggesting that LAMs should also contribute to IL-34 caused adverse phenotypes. Therefore, our findings uncover the intrinsic and microenvironmental mechanisms of IL-34 in AML and broadens the knowledge of M-CSF/IL-34-CSF-1R axis in malignancies.

Milk protects against sarcopenic obesity due to increase in the genus Akkermansia in faeces of db/db mice.

Sarcopenic obesity, a combination of sarcopenia and obesity, is a pathological feature of type 2 diabetes. Several human studies have shown that milk is useful in the prevention of sarcopenia. This study was aimed at clarifying the effect of milk on the prevention of sarcopenic obesity in db/db mice. A randomized and investigator-blinded study was conducted using male db/db mice. Eight-week-old db/db mice were housed for 8weeks and fed milk (100μL/day) using a sonde. The faecal microbiota transplantation (FMT) group received antibiotics for 2weeks, starting at 6weeks of age, followed by FMT twice a week until 16weeks of age. Milk administration to db/db mice increased grip strength (Milk-: 164.2±4.7g, Milk+: 230.2±56.0g, P=0.017), muscle mass (soleus muscle, Milk-: 164.2±4.7mg, Milk+: 230.2±56.0mg, P<0.001; plantaris muscle, Milk-: 13.3±1.2mg, Milk+: 16.0±1.7mg, P<0.001) and decreased visceral fat mass (Milk-: 2.39±0.08g, Milk+: 1.98±0.04mg, P<0.001), resulting in a significant increase in physical activity (light: P=0.013, dark: P=0.034). FMT from mice fed milk not only improved sarcopenic obesity but also significantly improved glucose intolerance. Microarray analysis of gene expression in the small intestine revealed that the expression of amino acid absorption transporter genes, namely, SIc7a5 (P=0.010), SIc7a1 (P=0.015), Ppp1r15a (P=0.041) and SIc7a11 (P=0.029), was elevated in mice fed milk. In 16S rRNA sequencing of gut microbiota, the genus Akkermansia was increased in both the mice fed milk and the FMT group from the mice fed milk. The findings of this study suggest that besides increasing the intake of nutrients, such as amino acids, milk consumption also changes the intestinal environment, which might contribute to the mechanism of milk-induced improvement of sarcopenic obesity.

Abstract 1684: Plasminogen activator inhibitor-1 (PAI-1) promotes cisplatin resistance in ovarian cancer cells by inhibiting ROS-mediated apoptosis and ferroptosis

Abstract Resistance to platinum-based chemotherapy is one of major causes of therapy failure and tumor recurrence in ovarian cancer patients. However, the molecular mechanism of platinum resistance is not fully understood. Here, we compared gene expression between cisplatin-sensitive and -resistant ovarian cancer cells using gene expression microarray analysis and found the significantly up-regulated expression of SERPINE1 encoding plasminogen activator inhibitor-1 (PAI-1), a serine protease regulating the fibrinolysis and extracelluar matrix, in cisplatin-resistant ovarian cancer cells. The correlation of high PAI-1 expression with low cisplatin sensitivity was confirmed in ovarian cancer cells. PAI-1 overexpression in ovarian cancer cells significantly decreased the sensitivity to cisplatin, whereas PAI-1 down-regulation by SERPINE1 siRNA or PAI-1 inhibitor increased cisplatin sensitivity. PAI-1 inhibited cisplatin-induced apoptosis in ovarian cancer cells by suppressing reactive oxygen species (ROS) production and DNA damage. PAI-1 also decreased cisplatin-induced ferroptosis through the upregulation of GPX4 levels. Furthermore, Kaplan-Meier survival analysis using TGGA data demonstrated that high PAI-1 expression was significantly associated with shorter platinum-free survival of patients with ovarian cancer. Collectively, these results illustrate that PAI-1 promotes cisplatin resistance in ovarian cancer cells by inhibiting ROS-mediated apoptosis and ferroptosis, suggesting that targeting PAI-1 increases the sensitivity to cisplatin in ovarian cancer. Citation Format: Mi Jeong Kwon, Ha Yeong Chae, So Young Lee, Shin Ung Kang, Tae Woong Jung, Soo Youn Cho, Jinil Han, Hyojin Jeong, Chang Ohk Sung, Young Kee Shin. Plasminogen activator inhibitor-1 (PAI-1) promotes cisplatin resistance in ovarian cancer cells by inhibiting ROS-mediated apoptosis and ferroptosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1684.