Performed Gene Set Enrichment Analysis Research Articles

Applying machine learning to screen for acute myocardial infarction‐related biomarkers and immune infiltration features and validate it clinically and experimentally

AbstractAcute myocardial infarction (AMI) has been responsible for 8.5 million deaths worldwide each year over the past decade and is the leading cause of death. It is a severe illness worldwide and can happen in multiple age categories. Despite the significant progress in fundamental and clinical studies of AMI, biomarkers for AMI development have not been adequately investigated. The present research aimed to characterize potential new biomarkers of AMI by comprehensive analysis and to explore the immune infiltration characteristics of this pathophysiological process. In this study, we identified 68 DEGs and performed gene set enrichment analysis, GO, disease oncology, and KEGG analysis, and the results suggested that several functional signaling pathways and essential genes were strongly related to the onset and progression of AMI. In addition, combining multiple algorithms, FCER1G, CLEC4D, SRGN, and SLC11A1 were determined to be prospective biomarkers of AMI and showed good diagnostic value. Immuno‐infiltration analysis suggested that neutrophils, CD8+ T cells, monocytes, and M0 macrophages might be involved in the onset and progress of AMI. In conclusion, a combined approach was employed to select biomarkers associated with AMI and to probe the critical function of immune cells in the progression of AMI. In addition, clinical studies were applied to analyze the correlation between the occurrence of AMI and lipid dysregulation.

Primary efficacy analyses of NeoRHEA, neoadjuvant biomarker research study of palbociclib combined with endocrine therapy in estrogen receptor positive/HER2 negative breast cancer.

522 Background: CDK4/6 inhibitors (CDK4/6i) and endocrine therapy (ET) are standard of care in the treatment of estrogen receptor (ER) positive, HER2-negative (ER+/HER2-) advanced breast cancer (BC). We tested palbociclib + ET as neoadjuvant therapy to identify baseline biomarkers of no response. Methods: NeoRHEA (NCT03065621) was a phase II, single arm trial evaluating 4 months of neoadjuvant palbociclib and ET in pre- or post-menopausal women with ER+/HER2- early BC. The primary objective was to identify biomarkers of no response by locally-assessed ultrasound (US) using RNA-seq on baseline (pretreatment) tumor biopsies. No response to treatment was defined as stable or progressive disease (SD or PD) at post-treatment US based on WHO criteria. Secondary endpoints included residual cancer burden (RCB) of 3 and absence of complete cell cycle arrest (CCCA) defined as Ki67 by immunohistochemistry (IHC) > 2.7% at surgery. We evaluated baseline clinicopathological characteristics, RNA-seq derived PAM50 subtypes and mRNA expression of ESR1, Ki67, CCNE1, RB1 and CDK6 single genes according to US response and CCCA. We also performed gene set enrichment analysis (GSEA) for 50 gene sets related to cancer hallmarks according to US response and CCCA. Results: 73 of 100 patients enrolled had baseline frozen tumors with enough cellularity and successful RNA-sequencing performed. Among the 73 patients, 70% were post-menopausal, 84% had cT2 and 70% cN0 tumors, 75% had invasive ductal carcinoma and 66% had histological grade 2 tumors. RNA-seq derived PAM50 subtypes were Luminal A, Luminal B, and non-Luminal in 56%, 36% and 8% of patients, respectively. Among the 73 patients, 31 (42%) had absence of US response (28 and 3 patients had stable and progressive disease by US, respectively) and 23 (31%) had RCB 3 tumors. Fifty-three of 73 patients had Ki67 by IHC available at surgery out of whom, 14 (26%) had absence of CCCA. Neither baseline clinicopathological characteristics nor PAM50 subtypes nor expression of ESR1, Ki67, CCNE1 and RB1 were associated with absence of US response or absence of CCCA. Interestingly, we observed higher baseline mRNA expression of CDK6 in patients with absence of US response (p = 0.039) or those with no CCCA (p = 0.004). We observed an enrichment in inflammatory / IFN-γ response and proliferation-related, G2M checkpoint gene sets in patients with US response (NES: 2.06, 2.30, 1.47; FDR: 7.04e-9, 5.48e-17, 0.0193 respectively) and an enrichment in early estrogen response gene set in patients with absence of US response (NES: -1.78, FDR: 0.0006). No signaling pathway was enriched in patients without CCCA. Conclusions: High pre-treatment mRNA expression of the CDK6 gene was associated with no US response or absence of CCCA in patients treated with neoadjuvant palbociclib and ET. Independent validation is needed. Clinical trial information: NCT03065621 .

Targeting monocytic‐myeloid suppressor cells through CSF1R‐blockade enhances CD19‐CAR T‐cell response in DLBCL

Introduction: Adoptive immunotherapies such as chimeric antigen receptor (CAR) T cell therapy have strongly improved the outcome of patients with diffuse large cell lymphoma (DLBCL) that are relapsed or refractory after standard chemo-immunotherapy. However, approx. 50% of patients with DLBCL are not durably responding to CAR T cell therapy. CAR T cell expansion is associated with durable responses. However, the molecular mechanisms that mediate suppression of CAR T cells leading to resistance still remain elusive. Methods: We performed bulk RNA sequencing of DLBCL patients before CAR T cell therapy. We performed gene set enrichment analysis (GSEA) using signatures derived from published genes associated with an immunosuppressive lymphoma microenvironment. To investigate CAR T cell therapy in an immunocompetent autochthonous mouse model we established murine CD19-redirected CAR-T cells that were generated using splenic T cells isolated from mice harbouring a C57BL/6N background. We treated DLBCL derived from PPMBC (PRDM1-KO, Myd88 + BCL2 overexpression, CD19: Cre) mice with this murine CD19 CAR-T cells in combination with an anti-CSF1R targeted antibody compared to controls. Results: We found increased immunosuppressive metabolic characteristics in CD19 CAR T refractory DLBCL patients indicated by increased glycolysis, hypoxia and elevated reactive oxygen species (ROS) in GSEA analysis. This metabolic signature was associated with an enriched monocytic-myeloid cell signature and a lack of expansion of effector T cells in CD19 CAR T refractory DLBCL. CSF1-CSFR1 (CD115) signaling is one major pathway that mediates the differentiation of myeloid derived cells into immunosuppressive MSCs. CD115-positive MSCs are important immune regulators in the tumor microenvironment that mediate inhibition of T cells and induce the proliferation of Tregs. We therefore hypothesize that combined treatment with a CSFR1 inhibitor will enhance CAR T cell expansion and thus improve CAR T cell response. We show that CSF1R blockade shifts the immunosuppressive lymphoma microenvironment into an proinflammatory environment in CD19 CAR T cell treated mice with DLBCL and abrogation of the expansion of lymphoma associated myelo-monocytic suppressor cells (LAMMs). This shift into an immunosupportive lymphoma microenvironment was accompanied with an increase of T cell expansion within the tumor and expansion of CD19-CAR T cells. We next evaluated whether the combination of CD19-CAR T cell therapy with CSF1R inhibition improves therapeutic outcome PPMBC DLBCL mice. Strikingly, we show that CSF1R Inhibition displays synergistic efficacy in combination with CD19 CAR T cell therapy. Conclusions: Our data strongly indicates that CSF1R inhibition improves CD19-CAR T expansion, promotes an immunosupportive microenvironment and could enhance CD19-CAR T cell therapy efficacy in patients with DLBCL. Keywords: Aggressive B-cell non-Hodgkin lymphoma, Cellular therapies, Microenvironment No conflicts of interests pertinent to the abstract.

Identification of MiR-223 Associated with Diagnosis in Ectopic Pregnancy.

In this study, we conducted an integrated study of the diagnostic value of MiR-223 in ectopic pregnancy (EP). We used GSE44731 downloaded from GEO and GEO2R to identify differentially expressed miRNA. The hub genes corresponding to the differential miRNA were then identified by using the Xiantao academic tool, GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes). Afterward, we used the miEAA database to perform gene set enrichment analysis (GSEA) of differential miRNA, and used Xiantao academic tools again to conduct the ceRNA network based on the target genes. Protein-protein interaction (PPI) network construction and lncRNA of hub miRNA target genes were then predicted by the starbase database. For validation, the villus tissue from intrauterine pregnancy and tubal pregnancy was collected and assayed by qPCR. In total 19 differentially expressed miRNAs were screened out, of which MiR-223 had a relatively clear diagnostic significance. Hub genes were enriched and analyzed by GO, KEGG, and GSEA, and the results showed that regulation of NF-κB and other signaling pathways are primarily enriched in ectopic pregnancy. We also obtained 215 key genes from PPI analysis. Our ceRNA analysis indicated that LRRC75A-AS1 and PITPNA-AS1 were associated with MiR-223, and the expression of MiR-223 in qPCR was significantly high in tubal pregnancy group. We found that MiR-223 can be used in the diagnosis of EP. Our findings provide valuable information and direction for future research into novel targets for EP diagnosis.

Constructing ferroptosis-related competing endogenous RNA networks and exploring potential biomarkers correlated with immune infiltration cells in asthma using combinative bioinformatics strategy

BackgroundAsthma is a common chronic respiratory disease worldwide. Recent studies have revealed the critical effects of the ceRNA network and ferroptosis on patients with asthma. Thus, this study aimed to explore the potential ferroptosis-related ceRNA network, investigate the immune cell infiltration level in asthma through integrated analysis of public asthma microarray datasets, and find suitable diagnostic biomarkers for asthma.MethodsFirst, three asthma-related datasets which were downloaded from the Gene Expression Omnibus (GEO) database were integrated into one pooled dataset after correcting for batch effects. Next, we screened differentially expressed lncRNAs (DElncRNAs) between patients and healthy subjects, constructed a ceRNA network using the StarBase database and screened ferroptosis–related genes from the predicted target mRNAs for Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also performed Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) on the batch effect-corrected mRNA expression profile. Then, Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen potential diagnostic biomarkers, and the diagnostic efficacy was assessed using a receiver operating characteristic (ROC) curve. Finally, we determined the proportion of 22 immune cells in patients with asthma using CIBERSORT and investigated the correlation between key RNAs and immune cells.ResultsWe obtained 19 DElncRNAs, of which only LUCAT1 and MIR222HG had corresponding target miRNAs. The differentially expressed ferroptosis-related genes were involved in multiple programmed cell death-related pathways. We also found that the mRNA expression profile was primarily enriched in innate immune system responses. We screened seven candidate diagnostic biomarkers for asthma using LASSO regression (namely, BCL10, CD300E, IER2, MMP13, OAF, TBC1D3, and TMEM151A), among which the area under the curve (AUC) value for CD300E and IER2 were 0.722 and 0.856, respectively. Finally, we revealed the infiltration ratio of different immune cells in asthma and found a correlation between LUCAT1, MIR222HG, CD300E, and IER2 with some immune cells.ConclusionThis study explored a potential lncRNA-miRNA-mRNA regulatory network and its underlying diagnostic biomarkers (CD300E and IER2) in asthma and identified the immune cells most associated with them, providing possible diagnostic markers and immunotherapeutic targets for asthma.

Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning.

Polycystic ovary syndrome (PCOS) is a complex endocrine metabolic disorder that affects 5-10% of women of reproductive age. The endometrium of women with PCOS has altered immune cells resulting in chronic low-grade inflammation, which attribute to recurrent implantation failure (RIF). In this study, we obtained three PCOS and RIF datasets respectively from the Gene Expression Omnibus (GEO) database. By analyzing differentially expressed genes (DEGs) and module genes using weighted gene co-expression networks (WGCNA), functional enrichment analysis, and three machine learning algorithms, we identified twelve diseases shared genes, and two diagnostic genes, including GLIPR1 and MAMLD1. PCOS and RIF validation datasets were assessed using the receiver operating characteristic (ROC) curve, and ideal area under the curve (AUC) values were obtained for each disease. Besides, we collected granulosa cells from healthy and PCOS infertile women, and endometrial tissues of healthy and RIF patients. RT-PCR was used to validate the reliability of GLIPR1 and MAMLD1. Furthermore, we performed gene set enrichment analysis (GSEA) and immune infiltration to explore the underlying mechanism of PCOS and RIF cooccurrence. Through the functional enrichment of twelve shared genes and two diagnostic genes, we found that both PCOS and RIF patients had disturbances in metabolites related to the TCA cycle, which eventually led to the massive activation of immune cells.

N6-methyladenosine (m6A)-connected lncRNAs is linked to survival and immune infiltration in glioma patients.

The connection between m6A-assiociateed lncRNAs and prognosis has been demonstrated in multiple types of tumors. However, potential roles of m6A-assiociateed lncRNAs in glioma is still rare. &#160;Methods: We implemented consensus cluster analysis to group the downloaded samples into two subtypes. The least absolute shrinkage and selection operator (LASSO) analysis was used to create a risk model. Additionally, the conjunction between m6A-related lncRNAs and immune cells infiltration was explored by conducting the R package. Ultimately, we inspected the underlying downstream pathways of the two subtypes by performing Gene Set Enrichment Analysis (GSEA). The expression level of m6A-connected lncRNAs in glioma were examined by conducting in vitro experiments.</p> &#160;Results: We ascertained two subtypes of glioma in line with the consensus clustering of m6A-associated lncRNAs. We confirmed that age, grade, and IDH are related to the two subtypes. Additionally, the immune cells infiltration and immune checkpoint molecules of the two clusters were discussed. A risk signature including AL359643.3, AL445524.1, AL162231.2, AL117332.1, AP001486.2, POLR2J4, AC120036.4, LINC00641, LINC00900, CRNDE, and AL158212.3, was identified using the Cox regression and LASSO analyses. We also verified the prognostic value and discussed the immune cells infiltration and immune checkpoint molecules of the risk signature. In Vitro experiments verified that the m6A-associated lncRNAs was abnormally expressed in glioma.</p> &#160;Conclusion: We elaborated the significant role of m6A-connected lncRNAs in glioma prognosis and immune infiltration and suggest that these key regulators may serve as underlying therapeutic targets to build up the efficacy of glioma immunotherapy.

Polygenic risk scores point toward potential genetic mechanisms of type 2 myocardial infarction in people with HIV

BackgroundPeople with human immunodeficiency virus (HIV) infection (PWH) are at higher risk of myocardial infarction (MI) than those without HIV. About half of MIs in PWH are type 2 (T2MI), resulting from mismatch between myocardial oxygen supply and demand, in contrast to type 1 MI (T1MI), which is due to primary plaque rupture or coronary thrombosis. Despite worse survival and rising incidence in the general population, evidence-based treatment recommendations for T2MI are lacking. We used polygenic risk scores (PRS) to explore genetic mechanisms of T2MI compared to T1MI in PWH. MethodsWe derived 115 PRS for MI-related traits in 9541 PWH enrolled in the Centers for AIDS Research Network of Integrated Clinical Systems cohort with adjudicated T1MI and T2MI. We applied multivariate logistic regression analyses to determine the association with T1MI and T2MI. Based on initial findings, we performed gene set enrichment analysis of the top variants composing PRS associated with T2MI. ResultsWe found that T1MI was strongly associated with PRS for cardiovascular disease, lipid profiles, and metabolic traits. In contrast, PRS for alcohol dependence and cholecystitis, significantly enriched in energy metabolism pathways, were predictive of T2MI risk. The association remained after the adjustment for actual alcohol consumption. ConclusionsWe demonstrate distinct genetic traits associated with T1MI and T2MI among PWH further highlighting their etiological differences and supporting the role of energy regulation in T2MI pathogenesis.

TLSEA: a tool for lncRNA set enrichment analysis based on multi-source heterogeneous information fusion.

Long non-coding RNAs (lncRNAs) play an important regulatory role in gene transcription and post-transcriptional modification, and lncRNA regulatory dysfunction leads to a variety of complex human diseases. Hence, it might be beneficial to detect the underlying biological pathways and functional categories of genes that encode lncRNA. This can be carried out by using gene set enrichment analysis, which is a pervasive bioinformatic technique that has been widely used. However, accurately performing gene set enrichment analysis of lncRNAs remains a challenge. Most conventional enrichment analysis methods have not exhaustively included the rich association information among genes, which usually affects the regulatory functions of genes. Here, we developed a novel tool for lncRNA set enrichment analysis (TLSEA) to improve the accuracy of the gene functional enrichment analysis, which extracted the low-dimensional vectors of lncRNAs in two functional annotation networks with the graph representation learning method. A novel lncRNA-lncRNA association network was constructed by merging lncRNA-related heterogeneous information obtained from multiple sources with the different lncRNA-related similarity networks. In addition, the random walk with restart method was adopted to effectively expand the lncRNAs submitted by users according to the lncRNA-lncRNA association network of TLSEA. In addition, a case study of breast cancer was performed, which demonstrated that TLSEA could detect breast cancer more accurately than conventional tools. The TLSEA can be accessed freely at http://www.lirmed.com:5003/tlsea.

Transcriptional factor MAZ promotes cisplatin-induced DNA damage repair in lung adenocarcinoma by regulating NEIL3

BackgroundCisplatin remains a common chemotherapy drug for lung adenocarcinoma (LUAD) in clinical treatment. Long-term use of cisplatin in patients may lead to acquired drug resistance, resulting in poor prognoses of patients. NEIL3 was a glycosylase-encoding gene highly expressed in LUAD. NEIL3 can repair telomerase DNA damage in the S phase. Nevertheless, there are few reports on whether NEIL3 is involved in cisplatin resistance and its related mechanisms in LUAD. MethodsThe expression of NEIL3 in LUAD patients was analyzed by bioinformatics. The regulator upstream of NEIL3 was predicted via hTFtarget. The possibly involved pathways of NEIL3 were obtained by performing Gene Set Enrichment Analysis. qRT-PCR and western blot were applied to test the expression level of genes and protein LUAD cells. Dual-luciferase assay and chromatin immunoprecipitation (ChIP) assay were conducted to validate the binding relationship between MAZ and NEIL3. Cell function assays were performed to test the DNA damage, cell viability, cell migration and invasion, and cell cycle of LUAD cells in the treatment group. ResultsNEIL3 and its upstream regulatory factor MAZ were highly expressed in LUAD tissue, and NEIL3 was enriched in cell cycle and mismatch repair pathways. Dual-luciferase assay and ChIP assay proved that MAZ could target NEIL3. Cell experiments identified that MAZ/NEIL3 axis could repress DNA damage to advance cisplatin resistance of cancer cells, and foster cell migration and invasion in LUAD. ConclusionMAZ-activated NEIL3 could propel the cisplatin resistance in LUAD by repressing DNA damage.

Necroptosis-related lncRNAs: establishment of a gene module and distinction between the cold and hot tumors in glioma.

Gliomas are the most common primary tumors of the central nervous system and portend a poor prognosis. The efficacy of emerging and promising immunotherapies varies significantly among individuals. Distinction and transformation of cold and hot tumors may improve the antitumor efficacy of immunotherapy. In this study, we constructed a necroptosis-related lncRNA module based on public databases. The association of this module with survival was assessed using the Cox regression, Kaplan-Meier survival analysis, and nomogram, external validation was also conducted in another public database. Furthermore, we performed gene set enrichment analysis (GSEA), immune checkpoint and tumor microenvironment analysis, and in vitro qRT-PCR validation. Finally, we clustered all samples into 2 clusters based on the expression of model lncRNAs and identified cluster 1 as cold tumors with fewer infiltrating T cells. Identifying cold and hot tumors by necroptosis-related lncRNAs can help available immunotherapeutic strategies to achieve efficacy in the precise treatment of individuals. Prior treatment failure can be overcome by targeting necroptosis-related lncRNAs.

Skeletal muscle transcriptomics dissects the pathogenesis of Friedreich's ataxia.

In Friedreich's ataxia (FRDA), the most affected tissues are not accessible to sampling and available transcriptomic findings originate from blood-derived cells and animal models. Herein, we aimed at dissecting for the first time the pathophysiology of FRDA by means of RNA-sequencing in an affected tissue sampled in vivo. Skeletal muscle biopsies were collected from seven FRDA patients before and after treatment with recombinant human Erythropoietin (rhuEPO) within a clinical trial. Total RNA extraction, 3'-mRNA library preparation and sequencing were performed according to standard procedures. We tested for differential gene expression with DESeq2 and performed gene set enrichment analysis with respect to control subjects. FRDA transcriptomes showed 1873 genes differentially expressed from controls. Two main signatures emerged: (1) a global downregulation of the mitochondrial transcriptome as well as of ribosome/translational machinery and (2) an upregulation of genes related to transcription and chromatin regulation, especially of repressor terms. Downregulation of the mitochondrial transcriptome was more profound than previously shown in other cellular systems. Furthermore, we observed in FRDA patients a marked upregulation of leptin, the master regulator of energy homeostasis. RhuEPO treatment further enhanced leptin expression. Our findings reflect a double hit in the pathophysiology of FRDA: a transcriptional/translational issue and a profound mitochondrial failure downstream. Leptin upregulation in the skeletal muscle in FRDA may represent a compensatory mechanism of mitochondrial dysfunction, which is amenable to pharmacological boosting. Skeletal muscle transcriptomics is a valuable biomarker to monitor therapeutic interventions in FRDA.

Abstract NG07: Targeting polyamines metabolism in acute myeloid leukemia stem cells

Abstract NG07: Targeting polyamines metabolism in acute myeloid leukemia stem cells

Abstract 6504: Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas

Abstract High body mass index (BMI) is a causal risk factor for endometrial cancer but the molecular mechanisms underlying this association remain elusive. Here we sought to characterize the tumor genomic landscape of endometrial cancers that have developed on a germline genetic background of predisposition to elevated BMI. We built a polygenic score (PGS) for adult BMI in women using effect size estimates and allele information on 242 independent (r2&amp;lt;0.05) variants associated with BMI at genome-wide significance (P&amp;lt;5x10-9) in 379,501 women of European ancestry. We performed sample and germline (blood) genotype quality control and imputation into the 1000 Genomes reference panel on data from 354 endometrial cancer cases of genetically inferred European ancestry from The Cancer Genome Atlas (TCGA). We assigned each woman in this TCGA cohort her genetically predicted life-course BMI based on the BMI PGS and found this to be modestly correlated with BMI at the point of diagnosis (r2=0.23; P=2.1x10-5). Multivariable linear (default) and quasi-Poisson (for zero-inflated counts) regression models were used to test for associations between the BMI germline PGS and endometrial cancer tumor genomic, transcriptomic, proteomic, and immune traits in TCGA. All analyses were adjusted for age, stage, microsatellite status and 10 genetic principal components. Mutational signature models were also adjusted for signature accuracy. We ranked 18,458 genes based on the association between their tumor expression and the BMI PGS and performed gene set enrichment analysis to identify associations between the BMI PGS and upregulation of genes in the IL6-JAK-STAT3 signaling (false discovery rate (FDR)=8.50x10-7), inflammatory response (FDR=7.03x10-6), interferon gamma response (FDR=5.49x10-5) and glycolysis (FDR=3.28x10-4) pathways. High BMI PGS had an inverse association with endometrial tumor EGFR (FDR=0.07) protein levels of the 131 tumor proteins profiled by reverse phase protein array. Endometrial tumors that had developed on a germline background predictive of high BMI were also associated with increased infiltration of activated mast cells (FDR=9.55x10-3) in our evaluation of 22 tumor immune cell infiltrates quantified by the CIBERSORT algorithm, as well as the mitotic and aging clock-like single base substitution (SBS) signatures 1 (FDR=0.01) and 5 (FDR=0.04). The two SBS signature associations and the activated mast cell association with the BMI PGS were substantially more pronounced in the subgroup of endometrial cancers with microsatellite instability. Thus, we combined germline and somatic data using a novel approach to identify endometrial cancer tumor molecular features associated with genetically predicted higher BMI, providing precision multi-omic portraits of endometrial cancers that develop on a background of adiposity. Citation Format: George Richenberg, Victoria Gray, Carina Owen, Tom Gaunt, Caroline Relton, Emma Vincent, Siddhartha Kar. Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas [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 6504.

CD8A is a Promising Biomarker Associated with Immunocytes Infiltration in Hyperoxia-Induced Bronchopulmonary Dysplasia.

Bronchopulmonary dysplasia (BPD) refers to a chronic lung disease which is commonly observed in preterm infants. It can usually be caused by several pathological processes that endanger the long-term lung development, such as inflammation and immune dysfunction. In this study, a bioinformatics approach was applied to identify the differentially expressed immune-related genes (DEIRGs). We downloaded the transcriptional profiles (GSE32472 dataset) from the Gene Expression Omnibus (GEO) database and performed gene set enrichment analysis (GSEA). Cell type Identification By Estimating Relative Subsets of RNA Transcripts (CIBERSORT), microenvironment cell populations counter (MCPcounter), and Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) were used for the analysis of the immune cell infiltration landscape of BPD. A weighted co-expression network was subsequently constructed using weighted gene co-expression network analysis (WGCNA) to screen candidate differentially expressed immune related genes (DEIRGs). GSEA results indicated that immune-related pathways were mainly involved in BPD. Ten significantly different immune cell types were observed between BPD and normal groups. A total of 228 DEGs in the turquoise module were identified, and 31 DEIRGs were further identified. Cluster of the differentiation 8 alpha (CD8A) expression was down-regulated in BPD, and its expression was validated by the GSE25286, GSE25293, GSE99633 datasets and qRT-PCR. In addition, CD8A expression was closely associated with immune cells infiltration, especially T cells CD8 and neutrophil. A distinct immune cell infiltration landscape was found between BPD and normal group. CD8A can be a novel candidate biomarker for BPD, which plays an essential role in the onset and progress of hyperoxia-related BPD via the disruption of immune cell functions.

In silico analysis to identify miR-1271-5p/PLCB4 (phospholipase C Beta 4) axis mediated oxaliplatin resistance in metastatic colorectal cancer

Oxaliplatin (OXA) is the first-line chemotherapy drug for metastatic colorectal cancer (mCRC), and the emergence of drug resistance is a major clinical challenge. Although there have been numerous studies on OXA resistance, but its underlying molecular mechanisms are still unclear. This study aims to identify key regulatory genes and pathways associated with OXA resistance. The Gene Expression Omnibus (GEO) GSE42387 dataset containing gene expression profiles of parental and OXA-resistant LoVo cells was applied to explore potential targets. GEO2R, STRING, CytoNCA (a plug-in of Cytoscape), and DAVID were used to analyze differentially expressed genes (DEGs), protein–protein interactions (PPIs), hub genes in PPIs, and gene ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. R2 online platform was used to run a survival analysis of validated hub genes enriched in KEGG pathways. The ENCORI database predicted microRNAs for candidate genes. A survival analysis of those genes was performed, and validated using the OncoLnc database. In addition, the 'clusterProfiler' package in R was used to perform gene set enrichment analysis (GSEA). We identified 395 DEGs, among which 155 were upregulated and 240 were downregulated. In total, 95 DEGs were screened as hub genes after constructing the PPI networks. Twelve GO terms and three KEGG pathways (steroid hormone biosynthesis, malaria, and pathways in cancer) were identified as being significant in the enrichment analysis of hub genes. Twenty-one hub genes enriched in KEGG pathways were defined as key genes. Among them AKT3, phospholipase C Beta 4 (PLCB4), and TGFB1 were identified as OXA-resistance genes through the survival analysis. High expressions of AKT3 and TGFB1 were each associated with a poor prognosis, and lower expression of PLCB4 was correlated with worse survival. Further, high levels of hsa-miR-1271-5p, which potentially targets PLCB4, were associated with poor overall survival in patients with CRC. Finally, we found that PLCB4 low expression was associated with MAPK signaling pathway and VEGF signaling pathway in CRC. Our results demonstrated that hsa-miR-1271-5p/PLCB4 in the pathway in cancer could be a new potential therapeutic target for mCRC with OXA resistance.

Abstract P6-01-05: Platelet-derived growth factor-CC expression in primary triple-negative breast cancer is associated with the basal-like molecular subtype and increased immune infiltrate

Abstract Around 10-15% of all breast cancers are categorized clinically as triple-negative breast cancer (TNBC). TNBC is defined by lack of protein expression or over expression of treatment targets such as the Estrogen Receptor α (ER) and Human Epidermal Growth Factor Receptor-2 (HER2), and the prognostic factor PR (Progesterone Receptor). The negative definition of TNBC results in a heterogeneous mix of tumors with variable molecular characteristics and prognosis. Defining TNBC molecular subtypes in detail is of importance to improve prognostication and find new treatment options. Expression of Platelet-derived growth factor-CC (PDGF-CC) has previously been correlated with the TNBC subtype, and paracrine PDGF-CC signaling has been reported to be of importance for maintaining TNBC tumor cell phenotype. We aimed to characterize PDGF-CC expression within the TNBC patient population by combining studies of PDGF-CC in tissue microarrays (TMAs) with matching RNAseq data and clinical follow-up; all variables originating from the SCAN-B (Sweden Cancerome Analysis Network – Breast) clinical study (ClinicalTrials.gov: NCT02306096). TMAs constructed of primary TNBC patient samples were stained for PDGF-CC using the Dako PT Autostainer system. Tumor cell-specific expression of PDGF-CC intensity was scored as either absent (N=11), weak (N=86), intermediate (N=81) or strong (N=70), and the scores were used to create corresponding TNBC PDGF-CC subgroups. We then explored associations of these subgroups with clinicopathological variables and time-to-event outcomes. Intermediate and strong PDGF-CC scores were associated with Nottingham Histological Grade 3 (p=0.001), increased proliferation (p&amp;lt; 0.001) and younger patient age at diagnosis (p=0.002). RNAseq data corresponding to tumors included in the TMAs was then retrieved, and differentially expressed genes were identified and used to perform Gene Set Enrichment Analysis (GSEA) comparing the TMA-derived PDGF-CC subgroups. Immune-related signatures were found to be enriched in the strong PDGF-CC subgroup vs. intermediate. Interestingly, strong PDGF-CC intensity was associated with a decreased risk of recurrence in the chemotherapy treated patient group (HR 0.28, 95% CI 0.10-0.80, p=0.017). Finally, patient samples were assigned a PAM50 subtype and a TNBC molecular subtype by the TNBCtype algorithm. Ninety-four percent of tumors in the strong PDGF-CC subgroup were classified as basal-like, whereas the corresponding number in the weak and intermediate PDGF-CC subgroups were 51% and 84%, respectively. The TNBC molecular subtype termed ‘Immunomodulatory’ was more frequently represented in the strong PDGF-CC subgroup compared to weak and intermediate (33% vs. 13% and 16%, respectively). In conclusion, strong PDGF-CC protein expression identified basal-like TNBCs, with an increase in immune cell infiltrate shown by RNAseq analysis. Whether or not PDGF-CC has a direct effect on influx of immune cells into tumors remains to be investigated. Analyses are currently ongoing to better understand the improved outcome associated with strong PDGF-CC intensity and on the contrary, the worse outcome associated with weak and intermediate PDGF-CC intensity, and if paracrine PDGF-CC signaling may explain the discrepancy observed. Citation Format: Sophie Lehn, Gyula Pekar, Paulina Bolivar Balbas, Johan Staaf, Christina Möller, Kristina Lövgren, Anna Ehinger, Ana Bosch Campos, Åke Borg, Kristian Pietras. Platelet-derived growth factor-CC expression in primary triple-negative breast cancer is associated with the basal-like molecular subtype and increased immune infiltrate [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-05.

Mapping Immune Correlates and Surfaceome Genes in BRAF Mutated Colorectal Cancers.

Despite the impressive results obtained with immunotherapy in several cancer types, a significant fraction of patients remains unresponsive to these treatments. In colorectal cancer (CRC), B-RafV600 mutations have been identified in 8-15% of the patients. In this work we interrogated a public dataset to explore the surfaceome of these tumors and found that several genes, such as GP2, CLDN18, AQP5, TM4SF4, NTSR1, VNN1, and CD109, were upregulated. By performing gene set enrichment analysis, we also identified a striking upregulation of genes (CD74, LAG3, HLA-DQB1, HLA-DRB5, HLA-DMA, HLA-DMB, HLA-DPB1, HLA-DRA, HLA-DOA, FCGR2B, HLA-DQA1, HLA-DRB1, and HLA-DPA1) associated with antigen processing and presentation via MHC class II. Likewise, we found a strong correlation between PD1 and PD(L)1 expression and the presence of genes encoding for proteins involved in antigen presentation such as CD74, HLA-DPA1, and LAG3. Furthermore, a similar association was observed for the presence of dendritic cells and macrophages. Finally, a low but positive relationship was observed between tumor mutational burden and neoantigen load. Our findings support the idea that a therapeutic strategy based on the targeting of PD(L)1 together with other receptors also involved in immuno-modulation, such as LAG3, could help to improve current treatments against BRAF-mutated CRC tumors.

IDO1 Activity Predicts Lung Toxicity in Patients with Unresectable Stage III NSCLC and Chemoradiotherapy.

Indoleamine 2,3-dioxygenase 1 (IDO1) acts as the key rate-limiting enzyme that converts tryptophan (Trp) to kynurenine (Kyn). Its activity was primarily induced by interferon-γ (IFN-γ), which was reported to play a role in the development of acute radiation-induced pneumonitis. In this study, we aimed to investigate the correlation between IDO1 activity and radiation-induced lung toxicity (RILT) in stage III nonsmall cell lung cancer (NSCLC) patients who were treated with chemoradiotherapy (CRT). Systemic IDO1 activity was reflected by Kyn : Trp ratio. Plasma levels of Kyn and Trp in 113 stage III NSCLC patients were measured by high-performance liquid chromatography (HPLC) before the initiation of radiotherapy. Dynamic change of IDO1 activity was followed in 23 patients before, during, and after radiotherapy. We also used RNA sequencing (RNA-seq) data from the Cancer Genome Atlas Program (TCGA) database and performed gene set enrichment analysis (GSEA) to explore how IDO1 was involved in the development of RILT. 9.7% (11/113) of the whole group developed G3+ (greater than or equal to Grade 3) RILT. Preradiation IDO1 activity was significantly higher in patients who developed G3 + RILT than in nonG3 + RILT patients. (P = 0.029, AUC = 0.70). Univariate and multivariate analyses showed that high IDO1 activity was independently associated with the risk of G3 + RILT (P = 0.034). A predictive model combining both IDO1 activity and FEV1 was established for severe RILT and displayed a moderate predictive value (AUC = 0.83, P < 0.001). The incidence of G3 + RILT was 2.6% (1/38) in patients with an IDO activity ≤0.069 and FEV1 > 59.4%, and 50.0% (6/12) in those with an IDO activity >0.069 and FEV1 ≤ 59.4%. Of 23 patients with dynamic tracking, the IDO1 activity of postradiation was significantly lower than midradiation (P = 0.021), though no significant differences among the three time points were observed (P = 0.070). Bioinformatic analysis using RNA-seq data from 1014 NSCLC patients revealed that IDO mainly functioned in the inflammatory response instead of the late fibrosis process in NSCLC patients. High baseline IDO1 activity combined with unfavorable baseline FEV1 was predictive of severe RILT in unresectable stage III NSCLC patients. IDO1 might play a role in the acute inflammatory response. Finding effective interventions to alleviate RILT using IDO inhibitors is warranted in the future.

Gene expression profiles in Hispanic patients with early-onset gastric cancer.

464 Background: A larger proportion of Hispanic gastric cancer patients are diagnosed at a young age than patients of other ethnicities. Despite diagnosis at an early age, young Hispanic patients also present more frequently with advanced disease. Whether there are molecular differences between tumors from young and old Hispanic gastric cancer patients is unknown. Methods: We performed RNA-sequencing on pre-treatment tumor samples of gastric cancer patients of self-identified Hispanic ethnicity. We stratified patients into two groups: &lt;50 years and ≥50 years. Differentially expressed genes between groups were detected using the DESeq2 package (RStudio). We performed Gene Set Enrichment Analysis (GSEA) to identify pathways that were uniquely overexpressed in each age group. Results: 57 patients were included in our study. 23 patients were &lt;50 years and 33 patients were ≥50 years. Comparison of the top 10% most differentially expressed genes showed no clustering based on age. However, visual inspection of the top 40 most differentially expressed genes revealed 2 distinct patterns of gene expression between age groups. GSEA revealed upregulation of DNA replication, cell cycle, and DNA repair pathways in the younger patients The tumors in younger patients also had upregulation of multiple immune activation pathways. Cancers from older patients had upregulation of programmed cell death pathways. Conclusions: Early-onset gastric cancer in Hispanic patients may represent a distinct biologic process.