High Expression Patients Research Articles

Ustekinumab affects myofibroblast metabolism to alleviate intestinal fibrosis by targeting KDELC1 in Crohn's disease through multi-machine learning combined with single-cell sequencing analysis.

Ustekinumab (UST), a biologic against interleukin (IL)-12/23, is commonly used to treat Crohn's disease (CD). Myofibroblast (MF) is known as one of the most important factors causing intestinal fibrosis, and UST has been reported to alleviate this condition. However, the genetic mechanisms underlying UST's effects on CD remain unclear. This study uses bioinformatics tools to analyze the genes and potential pathways affected by UST in CD, with a focus on its anti-fibrosis effects, providing insights into new therapeutic targets. The data downloaded from the Gene Expression Omnibus (GEO) database were analyzed to screen for differentially expressed genes (DEGs). Various machine learning strategies, including the least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF), were employed to screen for key genes among the DEGs. Functional and pathway enrichment analyses were conducted, and key genes associated with myofibroblast (MF) activity were screened. Finally, endoscopic surgical specimens from CD patients and healthy participants were collected to assess the expression levels of collagen and key genes in intestinal tissues using hematoxylin-eosin (H&E), Masson staining, and immunohistochemistry. A total of 1,341 DEGs associated with CD were identified. Among them, 738 genes showed low expression in healthy populations but high expression in patients with CD, reduced expression after the treatment of UST. In contrast, 603 genes exhibited high expression in healthy individuals, showed low expression in CD patients, and increased expression after UST treatment. Functional and pathway analysis showed that DEGs were mainly concentrated in response to foreign biological stimuli and bacterial-derived molecules. DEGs are mainly enriched in chemokines, TNF, IL-17, and other signaling pathways. Seven key genes were identified: NCRNA00236, LOC730101, ORP3, XG, UBFD1, KDELC1, and RBP7. Single-cell analysis revealed that KDELC1 was closely related to MF activity. MFs with high KDELC1 expression were significantly enriched in biological functions, signaling pathways, and metabolic processes that promote fibrosis. The experiment showed that UST treatment helped maintain the integrity of intestinal tissue structure, reducing the expression levels of collagen I, KDELC1, and the severity of intestinal fibrosis. The functional and pathway analysis reiterated that DEGs were largely focused on responses to foreign biological stimuli and bacterial-derived molecules, as well as signaling pathways such as chemokines, TNF, and IL-17. Of the identified genes, KDELC1 showed a particularly strong correlation with MF activity in single-cell analysis (R = 0.33, p = 3.2e-07). MFs with high KDELC1 expression were closely linked to pathways promoting fibrosis progression, including TGF-β, epithelial-mesenchymal transformation, TNF/NF-κB, and related metabolic pathways such as vitamin B6 and arginine. KDELC1 plays a key role in regulating multiple biological functions, including signaling pathways related to MF. UST alleviates intestinal fibrosis by targeting KDELC1, thereby influencing intramuscular fat metabolism and intercellular communication.

Siglec-15 expression in diffuse gliomas and its correlation with MRI morphologic features and apparent diffusion coefficient.

Sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) enhances tumor immune escape and leads to tumor growth. To investigate the expression of Siglec-15 in diffuse gliomas and its correlation with tumor magnetic resonance imaging (MRI) features. This study included 57 patients with gliomas. Morphological MRI features, including the largest tumor diameter, enhancement category, location, calcification, cysts, and hemorrhage, were visually rated. Apparent diffusion coefficient (ADC) values were calculated in tumor region. MRI morphologic features and ADC were compared between patients with positive and negative Siglec-15 expression. Receiver operating characteristic (ROC) curves were further constructed to assess the diagnostic performance. Siglec-15 was expressed in immunocytes, such as macrophages in the peritumoral area. Siglec-15 expression was positive in 20/57 (35.09%) patients, with higher expression in patients with IDH-mutant gliomas and lower grade gliomas. The tumor diameter was significantly smaller in patients with positive Siglec-15 expression than in those with negative expression for all patients (P = 0.017) and for patients with IDH-mutant gliomas (P = 0.020). Moreover, ADC values of the tumor were significantly higher in patients with positive Siglec-15 expression than in those with negative expression for all patients (P = 0.027). The areas under the ROC curve (AUCs) of the diameter and ADC were 0.702 and 0.686, respectively. A combination of these two parameters generated an improved AUC of 0.762. Siglec-15 was expressed in immunocytes such as macrophages in the peritumoral area, with a positive rate of 35.09%. Positive Siglec-15 expression in diffuse gliomas was correlated with smaller tumor size and higher ADC values.

CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8+ T cells via JAK2/STAT3 pathway

Evidence from clinical trials suggests that CXCR4 antagonists enhance immunotherapy effectiveness in several cancers. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood. Here, we employed single-cell transcriptomic analysis and identified CXCR4 as a marker gene in Tcells, with CD8+PD-1high exhausted T (Tex) cells exhibiting high CXCR4 expression. By blocking CXCR4, the Tex phenotype was attenuated invivo. Mechanistically, CXCR4-blocking Tcells mitigated the Tex phenotype by regulating the JAK2-STAT3 pathway. Single-cell RNA/TCR/ATAC-seq confirmed that Cxcr4-deficient CD8+ Tcells epigenetically mitigated the transition from functional to exhausted phenotypes. Notably, clinical sample analysis revealed that CXCR4+CD8+ Tcells showed higher expression in patients with a non-complete pathological response. Collectively, these findings demonstrate the mechanism by which CXCR4 orchestrates CD8+ Tex cells and provide a rationale for combining CXCR4 antagonists with immunotherapy in clinical trials.

Association of overexpression of PLD6, CHRAC1 and PDCD5 with type 2 diabetes mellitus

<p><strong>Aim </strong>Diabetes type 2 (DT2) is a metabolic disease characterized by high blood sugar caused by insulin resistance and/or insufficient insulin production. The pathogenesis of DT2 is complicated by both genetic predisposition and environmental and lifestyle variables. At least 150 genetic variants have been linked to the probability of having DT2. The aim of this study was to determine the expression of PLD6, CHRAC1, and PDCD5 genes in type 2 diabetic patients. <br /><strong>Methods </strong>Information on 12 DT2 patients was obtained from the Gene Expression Omnibus (GEO) using the series identification (ID) (GSE34008). The analysis tools GEO2R, String Utils (STRING), University of Alabama at Birmingham Cancer data analysis (UAL-CAN), and the Cancer Genome Atlas (TCGA) were used. The human protein atlas provided details on gene cancer.<br /><strong>Results </strong>Only ten genes with expression differences ranging from low to high were selected. PLD6, CHRAC1, and PDCD5 were detected to have higher expression in patients compared to controls. The number of patients with primary pancreatic adenocarcinoma for SLC16A4, DERK2, and CHRAC1 was greater than that of healthy controls. Concerning the severity of cancer, all chosen genes demonstrated a greater proportion of affected individuals compared to the control group. <br /><strong>Conclusion </strong>There are multiple genes whose increased expression is linked to type 2 diabetes.</p>

Molecular Alterations Associated with Histologically Overt Stromal Response in Patients with Prostate Cancer.

Prostate cancer has substantial heterogeneity in clinical outcomes and therapeutic responses, posing challenges in predicting disease progression and tailoring treatment strategies. Recent studies have highlighted the potential prognostic value of evaluating the tumor microenvironment, including the presence of a histologically overt stromal response (HOST-response) characterized by peri-glandular stromal changes and architectural distortions. This retrospective study examined patient records from The Cancer Genome Atlas database to identify genomic alterations associated with the HOST-response in prostate cancer. Among 348 patients who underwent radical prostatectomy, 160 (45.98%) were identified as having a HOST-response. A gene expression analysis revealed 1263 genes with significantly higher expression in patients with a HOST-response. A protein-protein interaction network analysis identified seven hub genes (KIF2C, CENPA, CDC20, UBE2C, ESPL1, KIF23, and PLK1) highly interconnected in the network. A functional enrichment analysis revealed alterations in the cell division, cytoskeletal organization, cytokinesis, and interleukin-16 signaling pathways in patients with a HOST-response, suggesting dysregulated proliferation and inflammation. The distinct molecular signature associated with the HOST-response provides insights into the tumor-stroma interactions driving adverse outcomes and potential targets for tailored therapeutic interventions in this subset of patients with prostate cancer.

Anti-TCP1 Antibody Is a Potential Biomarker for Diagnosing Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a chronic inflammatory disease caused by autoantibodies. Serum samples from patients with SLE (n = 10) were compared with those from normal controls (NCs, n = 5) using 21K protein chip analysis to identify a biomarker for SLE, revealing 63 SLE-specific autoantibodies. The anti-chaperonin-containing t-complex polypeptide-1 (TCP1) antibody exhibited higher expression in patients with SLE than in NCs. To validate the specificity of the anti-TCP1 antibody in SLE, dot blot analysis was conducted using sera from patients with SLE (n = 100), rheumatoid arthritis (RA; n = 25), Behçet's disease (BD; n = 28), and systemic sclerosis (SSc; n = 30) and NCs (n = 50). The results confirmed the detection of anti-TCP1 antibodies in 79 of 100 patients with SLE, with substantially elevated expression compared to both NCs and patients with other autoimmune diseases. We performed an enzyme-linked immunosorbent assay to determine the relative amounts of anti-TCP1 antibodies; markedly elevated anti-TCP1 antibody levels were detected in the sera of patients with SLE (50.1 ± 17.3 arbitrary unit (AU), n = 251) compared to those in NCs (33.9 ± 9.3 AU), RA (35 ± 8.7 AU), BD (37.5 ± 11.6 AU), and SSc (43 ± 11.9 AU). These data suggest that the anti-TCP1 antibody is a potential diagnostic biomarker for SLE.

Correlation of IDH1 gene expression error in breast tumor biopsy in patients with invasive ductal carcinoma.

One of the most important cancers in terms of worldwide prevalence is breast tumors, which have been less investigated in correlation with the enzyme Isocitrate Dehydrogenase 1 (IDH1) gene. The aim of this study was that expression of this gene could have significant effects on the progression of metastasis and invasive disease in breast cancer patients. We used the molecular method of RT-PCR with SYBR-Green to analyze breast tumor tissue from patients with metastasis and non-metastasis, the latter confirmed by the pathology department of Shohada-e Tajrish Hospital (serving as a control group). Also, patients population and its relationship with the degree of tumor in the IDH1 gene was investigated. The IDH1 gene has shown high expression in patients with metastatic breast cancer rather than in patients with non-metastatic breast cancer. The metastatic samples were compared with non-metastatic samples for IDH1 mRNA expression. In this research work, 72.5% (29 samples) were up-regulated in comparison to 27.5% of samples (11 samples) that did not exhibit high expression (P=0.000). This study examined the IDH1 gene expression, suggesting that changes in this gene's expression could impact the prognosis of breast cancer. However, further research is needed to draw definitive conclusions.

Expression of ADAM17 and its clinical value for patients with pernicious placenta previa: A retrospective study of 148 PPP patients underwent cesarean section.

To explore the expression and the diagnostic value of ADAM17 in pernicious placenta previa (PPP) combined placental accreta. A total of 148 PPP patients were enrolled and divided into 2 groups: 62 patients with placenta accrete (PPP with PA group) and 86 patients without placenta accrete (PPP without PA group). In the same period, 74 pregnant women without PPP who had undergone cesarean section were selected as controls. The levels of ADAM17 were detected by qt-PCR. Diagnostic efficiency of ADAM17 were evaluated by receiver operating characteristics curve. ADAM17 was higher expression in PPP patients. Multivariate analysis showed that ADAM17 was related to gravida times (HR = 2.43 95% CI, 1.25-3.31), history of cesarean delivery (HR = 3.44, 95% CI = 2.24-4.28), history of abortions (HR = 2.22, 95% CI = 1.57-3.06) for PPP with PA patients and gravida times (HR = 2.01, 95% CI = 1.45-2.86), history of cesarean delivery (HR = 1.89, 95% CI = 1.33-2.48) for PPP patients without PA. Diagnostic efficiency of ADAM17 indicated that the sensitivity and specificity of ADAM17 detection for PPP with PA were 74.41% and 67.21% and for PPP without PA were 89.29% and 85.52%. Area under curve were 0.7876 (0.7090-0.8661) for PPP with PA and 0.9443 (0.9136-0.9750) for PPP without PA. Insummary, ADAM17 was higher expression in patients with PPP. ADAM17 was associated with gravida times, history of cesarean delivery, history of abortions. It also indicated a better diagnostic efficiency for patients with PPP. Further larger sample, multicenter studies should be conducted to confirm the conclusion from our study.

Abstract B016: Recapitulation of gene expression-based immune subtypes of breast cancer using immunohistochemical staining

Abstract Using gene expression profiling data, we previously identified three immune subtypes (low-TIL, high-TIL, high-ISG) of breast cancer (BC) among Chinese BC patients in Hong Kong (HK) (Zhu et al., Breast Cancer Res, 2017). To investigate if standard in situ immunohistochemical (IHC) staining could capture the BC immune landscape, we analyzed archival tissue sections from 148 HKBC patients who were previously characterized based on gene expression. Dual IHC staining for 8 immune markers (CD3, CD8, CD20, FOXP3, CD68, CD163, PDL1, and IDO1) and PanCK was performed. Digitized whole slide images for each marker were analyzed using high-accuracy machine learning algorithms trained to quantify the percentage of positively stained regions. Strong correlations were found between IHC immune markers and gene expression-based immune and intrinsic subtypes. Compared to patients with lower level of tumor-infiltrating lymphocytes (low-TIL) classified based on gene expression data, those in the high-TIL subtype (characterized by high T cell and immune checkpoint gene expression) showed higher proportions of CD3, CD8, CD20, FOXP3, CD68, and PDL1 IHC positively stained cells. Similarly, the high-ISG subtype (with increased interferon-stimulated gene expression and TP53 somatic mutations) had higher proportions of CD3, CD8, CD20, FOXP3, and CD68 stained cells than the low-TIL subtype and in particular exhibited high CD163 staining, indicative of a proinflammatory tumor microenvironment. CD8, CD20, CD163, PDL1, and IDO1 expression varied significantly by PAM50 subtypes, with luminal (A and B) subtypes showing lower staining than non-luminal (HER2 and Basal) subtypes. A distinctive feature, however, of luminal B tumors was the higher infiltration by CD163-expressing cells when compared with the luminal A subtype. Except for FOXP3, all examined IHC markers showed significantly higher expression in patients with somatic TP53 mutations (CD3: P= 0.003, CD8: P= 0.005, CD20: P= 0.003, CD68: P= 0.002, CD163: P= 0.002, PDL1: P= 0.003, and IDO1: P= 0.013). On the other hand, expression of these markers did not significantly vary by PIK3CA mutation or germline APOBEC3A/B deletion polymorphism, which is more prevalent among East Asians than other populations and was previously linked to BC risk and immune environment. Of the BC risk factors assessed, only body mass index (BMI) demonstrated associations with immune cell densities, with higher BMI associated with lower expression of CD3, CD8, and CD20. This study sheds further light on the in situ immune landscape of gene expression-based BC subtypes, suggesting that standard IHC assessment of immune markers could refine BC subtype classification for clinical and epidemiological use. Citation Format: Mustapha Abubakar, Hela Koka, Priscilla Lee, Scott Lawrence, Karun Mutreja, Difei Wang, Bin Zhu, Shelly Tse, Xiaohong R Yang. Recapitulation of gene expression-based immune subtypes of breast cancer using immunohistochemical staining [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B016.

Exploration and validation of key genes associated with early lymph node metastasis in thyroid carcinoma using weighted gene co-expression network analysis and machine learning.

Thyroid carcinoma (THCA), the most common endocrine neoplasm, typically exhibits an indolent behavior. However, in some instances, lymph node metastasis (LNM) may occur in the early stages, with the underlying mechanisms not yet fully understood. LNM potential was defined as the tumor's capability to metastasize to lymph nodes at an early stage, even when the tumor volume is small. We performed differential expression analysis using the 'Limma' R package and conducted enrichment analyses using the Metascape tool. Co-expression networks were established using the 'WGCNA' R package, with the soft threshold power determined by the 'pickSoftThreshold' algorithm. For unsupervised clustering, we utilized the 'ConsensusCluster Plus' R package. To determine the topological features and degree centralities of each node (protein) within the Protein-Protein Interaction (PPI) network, we used the CytoNCA plugin integrated with the Cytoscape tool. Immune cell infiltration was assessed using the Immune Cell Abundance Identifier (ImmuCellAI) database. We applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) algorithms individually, with the 'glmnet,' 'e1071,' and 'randomForest' R packages, respectively. Ridge regression was performed using the 'oncoPredict' algorithm, and all the predictions were based on data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. To ascertain the protein expression levels and subcellular localization of genes, we consulted the Human Protein Atlas (HPA) database. Molecular docking was carried out using the mcule 1-click Docking server online. Experimental validation of gene and protein expression levels was conducted through Real-Time Quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) assays. Through WGCNA and PPI network analysis, we identified twelve hub genes as the most relevant to LNM potential from these two modules. These 12 hub genes displayed differential expression in THCA and exhibited significant correlations with the downregulation of neutrophil infiltration, as well as the upregulation of dendritic cell and macrophage infiltration, along with activation of the EMT pathway in THCA. We propose a novel molecular classification approach and provide an online web-based nomogram for evaluating the LNM potential of THCA (http://www.empowerstats.net/pmodel/?m=17617_LNM). Machine learning algorithms have identified ERBB3 as the most critical gene associated with LNM potential in THCA. ERBB3 exhibits high expression in patients with THCA who have experienced LNM or have advanced-stage disease. The differential methylation levels partially explain this differential expression of ERBB3. ROC analysis has identified ERBB3 as a diagnostic marker for THCA (AUC=0.89), THCA with high LNM potential (AUC=0.75), and lymph nodes with tumor metastasis (AUC=0.86). We have presented a comprehensive review of endocrine disruptor chemical (EDC) exposures, environmental toxins, and pharmacological agents that may potentially impact LNM potential. Molecular docking revealed a docking score of -10.1 kcal/mol for Lapatinib and ERBB3, indicating a strong binding affinity. In conclusion, our study, utilizing bioinformatics analysis techniques, identified gene modules and hub genes influencing LNM potential in THCA patients. ERBB3 was identified as a key gene with therapeutic implications. We have also developed a novel molecular classification approach and a user-friendly web-based nomogram tool for assessing LNM potential. These findings pave the way for investigations into the mechanisms underlying differences in LNM potential and provide guidance for personalized clinical treatment plans.

Leveraging Custom CRISPR/Cas9 Screens to Identify AraC-Daunorubicin-Etoposide (ADE), Gemtuzumab Ozogamicin (GO), and Bortezomib Response Modulators Association with Clinical Outcomes in Pediatric AML

Cytarabine, daunorubicin, and etoposide (ADE) remain the standard backbone chemotherapy for pediatric AML. In addition to ADE, gemtuzumab ozogamicin (GO) and bortezomib have been evaluated in the COG's AAML0531 and AAML1031 clinical trials, respectively. Nonetheless, when these experimental agents were combined with ADE, ADE+GO had shown to improve EFS but not OS, while ADE+bortezomib displayed no additional benefit over ADE alone. Thus, treatment options for pediatric AML are still limited, and development of resistance is a major concern, resulting in poor clinical outcomes. To overcome treatment resistance, it is crucial to understand the underlying molecular mechanisms of ADE±GO or bortezomib. Herein, we conducted custom CRISPR/Cas9 synthetic-lethal screens targeting 2440 genes (including AML-relevant genes, pharmacologically relevant genes, and druggable genes), in six AML cell lines with exposure to ara-C, daunorubicin, etoposide, GO and bortezomib followed by integration of the results with outcome data from multiple clinical trials where induction treatment was either standard ADE chemotherapy, ADE+GO or ADE+bortezomib. Six AML cell lines were transduced with a custom library and puromycin selected. Then pool transduced cell populations were then treated with DMSO, the IC30-IC50 levels of cytarabine, daunorubicin, etoposide, GO, or bortezomib for 7-doubling-times at 500x coverage. All samples were processed with genomic DNA extraction, sgRNAs were amplified by PCR, and were subjected to Illumina NovaSeq 6000 SP 100SR sequencing. The abundance of sgRNA was analyzed using MAGeCK-RRA to estimate the RRA drug response score (drug vs. control conditions at 7-doubling times). Genes with an average RRA score of < -1 across six AML cell lines were defined as drug-resistant genes (negative selection), whereas genes with an average RRA score of > 1 were categorized as sensitive genes (positive selection). Next, we investigated leukemic cell gene expression levels of the drug-resistant and drug-sensitive genes with clinical outcomes. At the average RRA score cutoff from CRISPR screens, 459 genes met the significance as resistant or sensitive genes to at least one drug from ADE's screens as ADE genes, 244 genes were significant from ADE genes and GO's screen as ADE+GO genes, and 166 genes were significant from ADE genes and bortezomib'screen as ADE+bortezomib genes ( Fig 1a). ADE genes were evaluated with clinical outcomes with patients treated with ADE AML02 (n=163), ADE arm of AAML0531 (n=201) and AAML1031 (n=411); while ADE+GO genes were evaluated in ADE+GO arm of AAML0531 (n=205) and ADE+bortezomib genes were evaluated in ADE+bortezomib arm of AAML1031 (n=436). Genes showing drug resistance in CRISPR screens and associated with detrimental outcomes (EFS, OS, or MRD1) at high expression were deemed clinically and biologically important drug genes and vice versa. Our preliminary results showed 21 met the criteria as clinically and biologically important drug-resistant or drug-sensitive genes, where genes were significant in multiple CRISPR screens and multiple pediatric AML cohorts ( Fig 1b). Six genes were determined to resist multiple drugs, with higher expression associated with worse outcomes across multiple cohorts. Particularly, ABCC1 encodes the ATP Binding Cassette C1-mediated drug efflux transporter; therefore, knocking out the efflux transporter causing drug resistance, would increase the lethality of AML cells, resulting in poor outcomes in multiple cohorts in patients treated with ADE alone and ADE with GO or bortezomib. Five genesshowed significant as sensitive genes for multiple drugs in our CRISPR screens with high expression association with favorable outcomes in multiple cohorts. Interestingly, two genes were identified as bortezomib-sensitive genes with high expression in patients treated with ADE+bortezemib in AAML1031 cohort had better outcomes. Other genes were revealed to be sensitive to one drug but resistant to another, indicating that antagonistic pleiotropy effects between genes and drugs may affect clinical outcomes. Current research focuses on developing a pipeline to predict different drug combination outcomes for prioritizing drug treatments and identifying novel drug targets to overcome drug resistance to ADE+GO or bortezomib.

Genome Sequencing to Discover Drivers of Clonal Expansion in Smoldering Multiple Myeloma

Background Better prediction models are required to identify patients with high-risk smoldering multiple myeloma (SMM) who can benefit from early intervention therapy before progression. Several studies have reported heterogeneity of genetic abnormalities found at the SMM stage, but whether any mutations are sufficient to cause, or instead prevent progression, remains an important open question. We leveraged whole-genome sequencing (WGS) in a large cohort of precursor patients, including repeated assessment over time, to discover drivers of disease growth and monitor malignant transformation to multiple myeloma (MM). Methods WGS was performed on tumor and normal cells from 141 untreated patients with SMM or Monoclonal Gammopathy of Undetermined Significance (MGUS) from the PCROWD study. Moreover, this dataset was combined with genomic data from the literature totaling 1,034 patients with WGS and/or exomes sampled across MM stages for comparative analysis and biomarker discovery. MutSig2CV, GISTIC2, and a novel method for structural variants were used to establish the list of candidate drivers across disease stages, with statistical power to detect myeloma drivers from points mutations found in ≥2% of patients. Longitudinal WGS data were analyzed with the PhylogicNDT suite of tools to characterize clonal competition in treated and untreated patients. Results Patients were followed for a median time of 20 months from the sample date (range: 3 to 78 months), during which 11 progressed. Patients evenly distributed across 20/2/20 stages: 44 Low-Risk (37%), 29 Intermediate-Risk (24%), 47 High-Risk (39%) SMM were combined with 20 MGUS, showing our method is reliable to perform WGS in lower disease burden settings. A validation cohort comprising 61 SMM with a median follow-up time of 36 months (range: 5 to 121), with 22 progressions was used to corroborate our findings. As significant drivers could be specifically enriched among indolent disease (i.e., protective alleles), we ran de novo driver mutation discovery across MM stages. In addition to well-characterized MM drivers ( KRAS, NRAS, etc.), 16 new candidate genes were found significantly mutated, including IKFZ3 (Aiolos), a transcription factor and direct target of degradation with lenalidomide therapy, harboring frameshift and stop-gain mutations in the protein dimerization domain which could affect complete differentiation of plasma cells. Mutants in KRAS found primarily at codons Q61, G12, G13, and A146, were found in all disease risk groups and associated with progression to overt myeloma (Odds Ratio: 6.1, CI95%: [1.4, 27], p=0.01, q<0.1). Next, we investigated genes targeted by copy-number abnormalities and found candidates in four regions with focal gains, including on chr(1q21), chr(8q24)( MYC), chr(3q26), and chr(16p13) encompassing BCMA. These genes have higher expression in patients with broad gain (e.g. BCMA: P=8.8E-3) or focal amplification (e.g. BCMA: P=6.2E-5), and therefore are likely to be underlying targets of the rearrangements driving cancer growth. Of note, BCMA antigen point mutations remained undetected in SMM, therefore patients with gain(16p) represent an attractive population for targeted therapy with anti-BCMA agents, in particular when the gain is clonal (n=3/8, 38%). In 15 patients, serial sampling of tumor cells allowed longitudinal WGS analyses and reconstruction of phylogenetic trees of disease clones (2 to 3 timepoints, 4 progressors, median 14 months). Maintenance of the major clone with subclonal structure evolving over time was confirmed in all patients, and we observed a steady increase in the cancer cell fraction of known MM mutations (del(13q), KRAS, DIS3 loss of function) in untreated patients. In one patient receiving early interventional treatment, a 70% reduction of M-spike concentration was achieved after four cycles of therapy; however, partial response was found in tandem with the selection of a high-risk del(1p) and of a KRAS activating G12S mutation, before increase and clinical progression to MM. Conclusion These results highlight the power of genomic profiling in MM for early detection, discovery of novel drivers, monitoring of clonal selection and transformation to malignant disease. We show SMM is not a simple genomically-mature disorder, but rather a dynamic state with competing subclones, which could be leveraged for therapeutic interventions.

Inhibitory Effects of Urolithins, Bioactive Gut Metabolites from Natural Polyphenols, against Glioblastoma Progression

We previously reported that proinflammatory cytokines, particularly tumor necrosis factor (TNF)-α, promoted tumor migration, invasion, and proliferation, thus worsening the prognosis of glioblastoma (GBM). Urolithins, the potent metabolites produced by the gut from pomegranate polyphenols, have anticancer properties. To develop an effective therapy for GBM, this study aimed to study the effects of urolithins against GBM. Urolithin A and B significantly reduced GBM migration, reduced epithelial–mesenchymal transition, and inhibited tumor growth. Moreover, urolithin A and B inhibited TNF-α-induced vascular cell adhesion molecule (VCAM)-1 and programmed death ligand 1 (PD-L1) expression, thereby reducing human monocyte (HM) binding to GBM cells. Aryl hydrocarbon receptor (AhR) level had higher expression in patients with glioma than in healthy individuals. Urolithins are considered pharmacological antagonists of AhR. We demonstrated that the inhibition of AhR reduced TNF-α-stimulated VCAM-1 and PD-L1 expression. Furthermore, human macrophage condition medium enhanced expression of PD-L1 in human GBM cells. Administration of the AhR antagonist attenuated the enhancement of PD-L1, indicating the AhR modulation in GBM progression. The modulatory effects of urolithins in GBM involve inhibiting the Akt and epidermal growth factor receptor pathways. The present study suggests that urolithins can inhibit GBM progression and provide valuable information for anti-GBM strategy.

The frequency of peripheral PD-1+ TCD4+ cells is reversely associated with serum creatinine levels in recipients of kidney allografts

The long-term survival of solid organ allografts remains a challenge for organ transplantation systems worldwide. T-cell exhaustion has been supposed to be associated with immunologic tolerance in transplantation and might reflect the immunologic status in recipients. The aim of the present study was to compare the TCD4+ cells of kidney transplant recipients with high and low serum creatinine levels for their expressions of PD-1 and TIGIT as two well-known exhaustion markers.Blood samples were taken from 20 kidney allograft recipients with serum creatinine levels above 2 mg/dL and 20 recipients with creatinine levels below 2 mg/dL. The percentages of PD-1+ CD4+ and TIGIT+ CD4+ cells were analyzed along with the evaluation of TNF-α, IFN-γ, and IL-10 release from peripheral blood mononuclear cells (PBMCs).The patients with serum creatinine levels below 2 mg/dL demonstrated a higher frequency of PD-1+ CD4+ T-cells (p = 0.003) along with lower TNF-α secretion from PBMCs (p = 0.028). The frequency of PD-1 + CD4+ T-cells was reversely correlated with the serum creatinine levels in recipients of kidney allografts (r = 0.59, p < 0.001). Besides, the MFI of TIGIT on TCD4+ cells demonstrated a trend for higher expression in patients with serum creatinine levels below 2 mg/dL (p = 0.070).The expression of PD-1+ on CD4+ T-cells demonstrated a potential for estimation of the immunologic status of the host in interaction with alloantigens. The exhaustion markers could be regarded as potential diagnostic indicators for the evaluation of immunologic tolerance in renal transplantation.

Genomic Variation Affecting MPV and PLT Count in Association with Development of Ischemic Stroke and Its Subtypes.

Platelets play a significant role in the pathophysiology of ischemic stroke since they are involved in the formation of intravascular thrombus after erosion or rupture of the atherosclerotic plaques. Platelet (PLT) count and mean platelet volume (MPV) are the two significant parameters that affect the functions of platelets. In the current study, MPV and PLT count was evaluated using flow cytometry and a cell counter. SonoClot analysis was carried out to evaluate activated clot timing (ACT), clot rate (CR), and platelet function (PF). Genotyping was carried out using GSA and Sanger sequencing, and expression analysis was performed using RT-PCR. In silico analysis was carried out using the GROMACS tool and UNAFold. The interaction of significant proteins with other proteins was predicted using the STRING database. Ninety-six genes were analyzed, and a significant association of THPO (rs6141) and ARHGEF3 (rs1354034) was observed with the disease and its subtypes. Altered genotypes were associated significantly with increased MPV, decreased PLT count, and CR. Expression analysis revealed a higher expression in patients bearing the variant genotypes of both genes. In silico analysis revealed that mutation in the THPO gene leads to the reduced compactness of protein structure. mRNA encoded by mutated ARHGEF3 gene increases the half-life of mRNA. The two significant proteins interact with many other proteins, especially the ones involved in platelet activation, aggregation, erythropoiesis, megakaryocyte maturation, and cytoskeleton rearrangements, suggesting that they could be important players in the determination of MPV values. In conclusion, the current study demonstrated the role of higher MPV affected by genetic variation in the development of IS and its subtypes. The results of the current study also indicate that higher MPV can be used as a biomarker for the disease and altered genotypes, and higher MPV can be targeted for better therapeutic outcomes.

Platelet miRNAs: differential expression in coronary artery disease and associations with course of left ventricular systolic function

BackgroundMicroRNAs are paramount in post transcriptional gene regulation. We investigated platelet miRNAs in patients with CAD and examined potential associations with course of left ventricular ejection fraction (LVEF%).Materials and methodsIn a first cohort, 62 MiRNAs were measured in platelets of 100 patients suffering from CAD. Expression profiles of individuals with chronic coronary syndrome (CCS) and MI were compared (CCS n = 67, MI n = 33). Also, associations between miRNA profiles and change in left ventricular ejection fraction (LVEF%) were investigated. In a second cohort of patients suffering from CCS (n = 10), MI (n = 11) or no CAD (n = 13), we measured miRNA expression in platelets, platelet supernatant and serum. This was carried out before and after in vitro platelet activation with CRP.ResultsPlatelet miRNAs 103a-3p and 155-5p demonstrated higher expression in patients with CCS then in individuals with MI. Furthermore, multiple miRNAs were significantly higher expressed in matched controls compared to MI patients. 8 miRNAs showed higher expression in patients with improving LVEF% after a 1-year follow-up. In our second cohort, we found higher concentrations of 6 miRNAs in the platelet supernatant of patients with CCS, MI and no CAD after in vitro platelet activation. Most of these miRNAs showed a higher abundance in serum of MI patients as compared to CCS.ConclusionSeveral miRNAs show higher expression in platelets of CCS compared to MI. After in vitro platelet activation, a release of multiple miRNAs out of the thrombocyte was observed. Furthermore, upregulation of serum miRNAs was found in MI patients when compared to CCS patients and individuals without CAD. Hence, platelets could present a source of upregulated circulating miRNAs in MI and additionally affect course of LVEF%.

Cell-Free RNA from Plasma in Patients with Neuroblastoma: Exploring the Technical and Clinical Potential

Neuroblastoma affects mostly young children, bearing a high morbidity and mortality. Liquid biopsies, e.g., molecular analysis of circulating tumor-derived nucleic acids in blood, offer a minimally invasive diagnostic modality. Cell-free RNA (cfRNA) is released by all cells, especially cancer. It circulates in blood packed in extracellular vesicles (EV) or attached to proteins. We studied the feasibility of analyzing cfRNA and EV, isolated by size exclusion chromatography (SEC), from platelet-poor plasma from healthy controls (n = 40) and neuroblastoma patients with localized (n = 10) and metastatic disease (n = 30). The mRNA content was determined using several multiplex droplet digital PCR (ddPCR) assays for a neuroblastoma-specific gene panel (PHOX2B, TH, CHRNA3) and a cell cycle regulation panel (E2F1, CDC6, ATAD2, H2AFZ, MCM2, DHFR). We applied corrections for the presence of platelets. We demonstrated that neuroblastoma-specific markers were present in plasma from 14/30 patients with metastatic disease and not in healthy controls and patients with localized disease. Most cell cycle markers had a higher expression in patients. The mRNA markers were mostly present in the EV-enriched SEC fractions. In conclusion, cfRNA can be isolated from plasma and EV and analyzed using multiplex ddPCR. cfRNA is an interesting novel liquid biopsy-based target to explore further.

KDM6B promotes gastric carcinogenesis and metastasis via upregulation of CXCR4 expression

KDM6B (Lysine-specific demethylase 6B) is a histone lysine demethyltransferase that plays a key role in many types of cancers. However, its potential role in gastric cancer (GC) remains unclear. Here, we focused on the clinical significance and potential role of KDM6B in GC. We found that the KDM6B expression is upregulated in GC tissues and that its high expression in patients is related to poor prognosis. KDM6B ectopic expression promotes GC cells’ proliferation and metastasis, while its inhibition has opposite effects in vitro and in vivo. Mechanistically, KDM6B promotes GC cells proliferation and metastasis through its enzymatic activity through the induction of H3K27me3 demethylation near the CXCR4 (C-X-C chemokine receptor type 4) promoter region, resulting in the upregulation of CXCR4 expression. Furthermore, H. pylori was found to induce KDM6B expression. In conclusion, our results suggest that KDM6B is aberrantly expressed in GC and plays a key role in gastric carcinogenesis and metastasis through CXCR4 upregulation. Our work also suggests that KDM6B may be a potential oncogenic factor and a therapeutic target for GC.

The identification of liver metastasis- and prognosis-associated genes in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is an often fatal malignancy with an extremely low survival rate. Liver metastasis, which causes high mortality, is the most common recurring metastasis for PDAC. However, the mechanisms underlying this liver metastasis and associated candidate biomarkers are unknown.MethodsWe performed mRNA profiling comparisons in 8 primary tumors (T) and 12 liver metastases (M) samples using the Gene Expression Omnibus (GEO) database. After determining differentially expressed genes (DEG), gene ontology (GO), pathway enrichment and protein–protein interaction (PPI) network analyses were performed to determine DEG functions. Then, Cytoscape was used to screen out significant hub genes, after which their clinical relevance was investigated using The Cancer Genome Atlas (TCGA) resources. Furthermore, prognosis-associated gene expression was validated using Oncomine and TCGA database. Lastly, associations between prognosis-associated genes, immune cells and immunological checkpoint genes were evaluated using the Tumor Immune Estimation Resource (TIMER).ResultsIn total, 102 genes were related to liver metastasis and predominantly involved in cell migration, motility, and adhesion. Using Cytoscape, this number was narrowed down to 16 hub genes. Elevated mRNA expression levels for two of these genes, SPARC (P = 0.019) and TPM1 (P = 0.037) were significantly correlated with poor disease prognosis. For the remaining 14, expression was not related to overall patient survival. SPARC had higher expression in patients with metastatic PDAC than those with non-metastatic PDAC in TCGA dataset. SPARC and TPM1 levels were also positively correlated with the immune infiltration of specific cell types. Additionally, both genes exhibited strong co-expression associations with immune checkpoint genes.ConclusionsCombined, we suggest SPARC has high potential as biomarker to predict liver metastasis during PDAC. Additionally, both SPARC and TPM1 appeared to recruit and regulate immune-infiltrating cells during these pathophysiological processes.

Hsa_circ_0005729 enhances accuracy in diagnosing parathyroid carcinoma.

BackgroundParathyroid carcinoma (PC), often misdiagnosed as a parathyroid adenoma (PA), is prone to local relapse due to the initial surgery being restricted to parathyroid lesions instead of en bloc resection of parathyroid lesions with negative incision margins. However, it is very challenging to distinguish PC from PA preoperatively; hence, this study investigated an effective biomarker for increasing accuracy in PC diagnosis.MethodFirst, the differentially expressed circular RNAs between three PC tissues and three PA tissues were screened by high-throughput circular RNA sequencing, and the expression of hsa_circ_0005729 was verified by qRT-PCR in 14 patients with PC and 40 patients with PA. Secondly, the receiver operating characteristic curve and the area under the curve (AUC) were used to analyze the diagnostic efficiency of hsa_circ_0005729 in PC by combining with laboratory data. Thirdly, RNF138mRNA, the corresponding linear transcript of hsa_circ_0005729, was measured, and the relationship between hsa_circ_0005729 and RNF138 mRNA was analyzed in patients with PA and patients with PC.ResultsHsa_circ_0005729 expression was significantly higher in patients with PC than in patients with PA. Serum calcium (P = 0.045), alkaline phosphatase (ALP) (P = 0.048), and creatinine levels (P = 0.036) were significantly higher in patients with PC than in patients with PA. The AUC increased to 0.86 when hsa_circ_0005729 combined with serum calcium, creatinine, and ALP. In addition, hsa_circ_0005729 was positively correlated with RNF138 mRNA in patients with PA but not in patients with PC.ConclusionThe novel circular RNA hsa_circ_0005729 was found to have a higher expression in patients with PC, indicating its usefulness for distinguishing PC from PA.