Identification of Prognostic and Chemopredictive microRNAs for Non-Small-Cell Lung Cancer by Integrating SEER-Medicare Data

This study developed a novel methodology to correlate genome-scale microRNA (miRNA) expression profiles in a lung squamous cell carcinoma (LUSC) cohort (n = 57) with Surveillance, Epidemiology, and End Results (SEER)-Medicare LUSC patients (n = 33,897) as a function of composite tumor progression indicators of T, N, and M cancer stage and tumor grade. The selected prognostic and chemopredictive miRNAs were extensively validated with miRNA expression profiles of non-small-cell lung cancer (NSCLC) patient samples collected from US hospitals (n = 156) and public consortia including NCI-60, The Cancer Genome Atlas (TCGA; n = 1016), and Cancer Cell Line Encyclopedia (CCLE; n = 117). Hsa-miR-142-3p was associated with good prognosis and chemosensitivity in all the studied datasets. Hsa-miRNA-142-3p target genes (NUP205, RAN, CSE1L, SNRPD1, RPS11, SF3B1, COPA, ARCN1, and SNRNP200) had a significant impact on proliferation in 100% of the tested NSCLC cell lines in CRISPR-Cas9 (n = 78) and RNA interference (RNAi) screening (n = 92). Hsa-miR-142-3p-mediated pathways and functional networks in NSCLC short-term survivors were elucidated. Overall, the approach integrating SEER-Medicare data with comprehensive external validation can identify miRNAs with consistent expression patterns in tumor progression, with potential implications for prognosis and prediction of chemoresponse in large NSCLC patient populations.     

Loss of ZNF677 Expression Is an Independent Predictor for Distant Metastasis in Middle Eastern Papillary Thyroid Carcinoma Patients

Thyroid cancer incidence has increased in recent decades. Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Approximately 30% of PTC patients develop recurrence or distant metastasis and tend to have poor prognosis. Therefore, the identification of targetable biomarkers in this subset of patients is of great importance. Accumulating evidence indicates that zinc finger protein 677 (ZNF677), which belongs to the zinc finger protein family, is an important effector during the progression of multiple malignancies. However, its role in Middle Eastern PTC patients has not been fully illustrated. Here, we uncovered the molecular mechanism and the clinical impact of ZNF677 expression in a large cohort of more than 1200 Middle Eastern PTC and 15 metastatic tissues. We demonstrated that ZNF677 is frequently downregulated in primary PTC (13.6%, 168/1235) and showed that complete loss of expression of ZNF677 is significantly associated with aggressive clinico-pathological markers such as extrathyroidal extension (p = 0.0008) and distant metastases (p < 0.0001). We also found a significantly higher incidence of ZNF677 loss in primary tumors with distant metastases (33.3%; p < 0.0001) as well as in distant metastatic tissues (46.7%; p = 0.0002) compared to the overall cohort (13.6%). More importantly, PTC with loss of ZNF677 expression showed significantly lower metastasis-free survival (p = 0.0090). Interestingly, on multivariate logistic regression analysis, ZNF677 loss was an independent predictor of distant metastasis in PTC (Odds ratio = 2.60, 95% Confidence interval = 1.20–5.62, p = 0.0155). In addition, we found a significant association between ZNF677 loss and phospho-AKT expression (p < 0.0001). Our functional molecular results suggest that ZNF677 acts as a tumor suppressor, mediating its effect by inhibiting AKT phosphorylation. Taken together, our results highlight the pivotal role played by ZNF677 during carcinogenesis and metastasis formation in Middle Eastern PTC patients.     

The Potential Role of DNA Methylation in Abdominal Aortic Aneurysms

Abdominal aortic aneurysm (AAA) is a complex disorder that has a significant impact on the aging population. While both genetic and environmental risk factors have been implicated in AAA formation, the precise genetic markers involved and the factors influencing their expression remain an area of ongoing investigation. DNA methylation has been previously used to study gene silencing in other inflammatory disorders and since AAA has an extensive inflammatory component, we sought to examine the genome-wide DNA methylation profiles in mononuclear blood cells of AAA cases and matched non-AAA controls. To this end, we collected blood samples and isolated mononuclear cells for DNA and RNA extraction from four all male groups: AAA smokers (n = 11), AAA non-smokers (n = 9), control smokers (n = 10) and control non-smokers (n = 11). Methylation data were obtained using the Illumina 450k Human Methylation Bead Chip and analyzed using the R language and multiple Bioconductor packages. Principal component analysis and linear analysis of CpG island subsets identified four regions with significant differences in methylation with respect to AAA: kelch-like family member 35 (KLHL35), calponin 2 (CNN2), serpin peptidase inhibitor clade B (ovalbumin) member 9 (SERPINB9), and adenylate cyclase 10 pseudogene 1 (ADCY10P1). Follow-up studies included RT-PCR and immunostaining for CNN2 and SERPINB9. These findings are novel and suggest DNA methylation may play a role in AAA pathobiology.     

Artificial neural network predictions of polycyclic aromatic hydrocarbon formation in premixed n-heptane flames

Polycyclic aromatic hydrocarbon formation in combustion systems has received considerable attention because of its health effects. The feed-forward, multi-layer perceptron type artificial neural networks with back-propagation learning were used to predict the total PAH amount in atmospheric pressure, premixed n-heptane and n-heptane/oxygenate flames. MTBE and ethanol were used as fuel oxygenates. The total fifty-four data sets were divided into three groups: training, cross-validation, and testing. The different network architectures were tested and the best predictions were obtained for a network of one hidden layer with five neurons. The transfer function was sigmoid function. The mean square and mean absolute errors were 10.52 and 2.60 ppm for the testing set, respectively. The correlation coefficient (R²) was 0.98. The results also showed that the total PAH amount was significantly influenced by the changes in equivalence ratio, presence of fuel oxygenates, and mole fractions of C₄ species.     

Prognostic Value of Tumor Markers,NSE, CA125 and SCC,in Operable NSCLC Patients

The aim of this study was to investigate the prognostic value of tumor markers in operable non-small cell lung cancer (NSCLC) patients. A total of 481 NSCLC patients were enrolled in the present study. High levels of neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125) and squamous cell carcinoma antigen (SCC) were detected in 306 (63.6%), 89 (18.5%) and 125 (26.0%) patients, respectively. Seventy-eight of 481 patients died of disease progression, and the median disease-free survival (DFS) and overall survival (OS) were 16.0 and 21.0 months, respectively. The three-year DFS rate was 56.7%, and the OS rate was 75.3%. For serum NSE, the three-year cumulative DFS rate for the normal and elevated group was 67.7% and 51.8% (p = 0.007). The OS in patients with high and normal levels of NSE was 34.0 months and 48.0 months, respectively. The median DFS was 46.0 months versus 32.0 months (p = 0.001), and the OS was 48.0 months versus 44.0 months (p = 0.001) in patients with normal and high levels of CA125. For patients with squamous cell carcinoma, the overall survival was significantly shorter in patients with elevated levels of SCC (p = 0.041). In the multivariate analysis high levels of NSE, CA125 and clinical stage were significantly correlated with worse prognosis (p < 0.05). Patients with all three tumor markers elevated presented the worst prognosis (p < 0.05). In our analysis, high levels of preoperative serum NSE and CA125 are correlated with worse survival in operable NSCLC patients.     

A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson’s Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson’s disease (PD) heterogeneity among individuals proves the existence of disease subtypes, so subgrouping patients is vital for better understanding disease mechanisms and designing precise treatment. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis. Two hundred and ten post mortem brain RNA-Seq samples from PD (n = 115) and normal controls (NCs, n = 95) were obtained with systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p < 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/β-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.     

Detection of Serum Protein Biomarkers for the Diagnosis and Staging of Hepatoblastoma

The present study aimed to identify serum biomarkers for the detection of hepatoblastoma (HB). Serum samples were collected from 71 HB patients (stage I, n = 19; stage II, n = 19, stage III, n = 19; and stage IV, n = 14) and 23 age- and sex-matched healthy children. Differential expression of serum protein markers were screened using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and the target proteins were isolated and purified using HPLC and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), SEQUEST, and bioinformatics analysis. Differential protein expression was confirmed by enzyme-linked immunosorbent analysis (ELISA). SELDI-TOF-MS screening identified a differentially expressed protein with an m/z of 9348 Da, which was subsequently identified as Apo A–I; its expression was significantly lower in the HB group as compared to the normal control group (1546.67 ± 757.81 vs. 3359.21 ± 999.36, respectively; p < 0.01). Although the expression level decreased with increasing disease stage, pair-wise comparison revealed significant differences in Apo A–I expression between the normal group and the HB subgroups (p < 0.01). ELISA verified the reduced expression of Apo A–I in the HB group. Taken together, these results suggest that Apo A–I may represent a serum protein biomarker of HB. Further studies will assess the value of using Apo A–I expression for HB diagnosis and staging.     

Characterization of the MicroRNA Cargo of Extracellular Vesicles Isolated from a Pulmonary Tumor-Draining Vein Identifies miR-203a-3p as a Relapse Biomarker for Resected Non-Small Cell Lung Cancer

In resected non-small cell lung cancer (NSCLC), post-surgical recurrence occurs in around 40% of patients, highlighting the necessity to identify relapse biomarkers. An analysis of the extracellular vesicle (EV) cargo from a pulmonary tumor-draining vein (TDV) can grant biomarker identification. We studied the pulmonary TDV EV-miRNAome to identify relapse biomarkers in a two-phase study (screening and validation). In the screening phase, a 17-miRNA relapse signature was identified in 18 selected patients by small RNAseq. The most expressed miRNA from the signature (EV-miR-203a-3p) was chosen for further validation. Pulmonary TDV EV-miR-203a-3p was studied by qRT-PCR in a validation cohort of 70 patients, where it was found to be upregulated in relapsed patients (p = 0.0194) and in patients with cancer spread to nearby lymph nodes (N+ patients) (p = 0.0396). The ROC curve analysis showed that TDV EV-miR-203a-3p was able to predict relapses with a sensitivity of 88% (AUC: 0.67; p = 0.022). Moreover, patients with high TDV EV-miR-203a-3p had a shorter time to relapse than patients with low levels (43.6 vs. 97.6 months; p = 0.00703). The multivariate analysis showed that EV-miR-203a-3p was an independent, predictive and prognostic post-surgical relapse biomarker. In conclusion, pulmonary TDV EV-miR-203a-3p is a promising new relapse biomarker for resected NSCLC patients.     

An Integrated Transcriptomic Approach to Identify Molecular Markers of Calcineurin Inhibitor Nephrotoxicity in Pediatric Kidney Transplant Recipients

Calcineurin inhibitors are highly efficacious immunosuppressive agents used in pediatric kidney transplantation. However, calcineurin inhibitor nephrotoxicity (CNIT) has been associated with the development of chronic renal allograft dysfunction and decreased graft survival. This study evaluated 37 formalin-fixed paraffin-embedded biopsies from pediatric kidney transplant recipients using gene expression profiling. Normal allograft samples (n = 12) served as negative controls and were compared to biopsies exhibiting CNIT (n = 11). The remaining samples served as positive controls to validate CNIT marker specificity and were characterized by other common causes of graft failure such as acute rejection (n = 7) and interstitial fibrosis/tubular atrophy (n = 7). MiRNA profiles served as the platform for data integration. Oxidative phosphorylation and mitochondrial dysfunction were the top molecular pathways associated with overexpressed genes in CNIT samples. Decreased ATP synthesis was identified as a significant biological function in CNIT, while key toxicology pathways included NRF2-mediated oxidative stress response and increased permeability transition of mitochondria. An integrative analysis demonstrated a panel of 13 significant miRNAs and their 33 CNIT-specific gene targets involved with mitochondrial activity and function. We also identified a candidate panel of miRNAs/genes, which may serve as future molecular markers for CNIT diagnosis as well as potential therapeutic targets.     

Stratifying Cumulus Cell Samples Based on Molecular Profiling to Help Resolve Biomarker Discrepancies and to Predict Oocyte Developmental Competence

To increase the efficiency of assisted reproductive techniques (ART), molecular studies have been performed to identify the best predictive biomarkers for selecting the most suitable germ cells for fertilization and the best embryo for intra-uterine transfer. However, across different studies, no universal markers have been found. In this study, we addressed this issue by generating gene expression and CpG methylation profiles of outer cumulus cells obtained during intra-cytoplasmic sperm injection (ICSI). We also studied the association of the generated genomic data with the clinical parameters (spindle presence, zona pellucida birefringence, pronuclear pattern, estrogen level, endometrium size and lead follicle size) and the pregnancy result. Our data highlighted the presence of several parameters that affect analysis, such as inter-individual differences, inter-treatment differences, and, above all, specific treatment protocol differences. When comparing the pregnancy outcome following the long protocol (GnRH agonist) of ovarian stimulation, we identified the single gene markers (NME6 and ASAP1, FDR < 5%) which were also correlated with endometrium size, upstream regulators (e.g., EIF2AK3, FSH, ATF4, MKNK1, and TP53) and several bio-functions related to cell death (apoptosis) and cellular growth and proliferation. In conclusion, our study highlighted the need to stratify samples that are very heterogeneous and to use pathway analysis as a more reliable and universal method for identifying markers that can predict oocyte development potential.     

The G-Protein-Coupled Estrogen Receptor (GPER/GPR30) in Ovarian Granulosa Cell Tumors

Ovarian granulosa cell tumors (GCTs) are thought to arise from cells of the ovarian follicle and comprise a rare entity of ovarian masses. We recently identified the G-protein-coupled estrogen receptor (GPER/GPR30) to be present in granulosa cells, to be regulated by gonadotropins in epithelial ovarian cancer and to be differentially expressed throughout folliculogenesis. Thus, supposing a possible role of GPER in GCTs, this study aimed to analyze GPER in GCTs. GPER immunoreactivity in GCTs (n = 26; n (primary diagnosis) = 15, n (recurrence) = 11) was studied and correlated with the main clinicopathological variables. Positive GPER staining was identified in 53.8% (14/26) of GCTs and there was no significant relation of GPER with tumor size or lymph node status. Those cases presenting with strong GPER intensity at primary diagnosis showed a significant reduced overall survival (p = 0.002). Due to the fact that GPER is regulated by estrogens, as well as gonadotropins, GPER may also be affected by endocrine therapies applied to GCT patients. Moreover, with our data supposing GPER to be associated with GCT prognosis, GPER might be considered as a possible confounder when assessing the efficacy of hormone-based therapeutic approaches in GCTs.     

Influence of Preoperative Serum Aspartate Aminotransferase (AST) Level on the Prognosis of Patients with Non-Small Cell Lung Cancer

The purpose of this work is to analyze preoperative serum aspartate aminotransferase (AST) levels and their effect on the prognosis of patients with non-small cell lung cancer (NSCLC) after surgical operation. These analyses were performed retrospectively in patients with NSCLC followed by surgery; participants were recruited between January 2004 and January 2008. All clinical information and laboratory results were collected from medical records. We explored the association between preoperative serum AST and recurrence-free survival (RFS), and the overall survival (OS) of NSCLC patients. Kaplan–Meier analysis and Cox multivariate analysis, stratified by the AST median value, were used to evaluate the prognostic effect. A chi-squared test was performed to compare clinical characteristics in different subgroups. A p-value of ≤0.05 was considered to be statistically significant. A total of 231 patients were enrolled. The median RFS and OS were 22 and 59 months, respectively. The AST levels were divided into two groups, using a cut-off value of 19 U/L: High AST (>19 U/L), n = 113 vs. low AST (≤19 U/L), n = 118. Multivariate analysis indicated that preoperative serum AST > 19 U/L (hazard ratio (HR) = 0.685, 95% confidence interval (CI): 0.493–0.994, p = 0.046 for RFS, HR = 0.646, 95% CI: 0.438–0.954, p = 0.028 for OS) was an independent prognostic factor for both RFS and OS. High preoperative serum AST levels may serve as a valuable marker to predict the prognosis of NSCLC after operation.     

A Keratin 7 and E-Cadherin Signature Is Highly Predictive of Tubo-Ovarian High-Grade Serous Carcinoma Prognosis

During tubo-ovarian high-grade serous carcinoma (HGSC) progression, tumoral cells undergo phenotypic changes in their epithelial marker profiles, which are essential for dissemination processes. Here, we set out to determine whether standard epithelial markers can predict HGSC patient prognosis. Levels of E-CADH, KRT7, KRT18, KRT19 were quantified in 18 HGSC cell lines by Western blot and in a Discovery cohort tissue microarray (TMA) (n = 101 patients) using immunofluorescence. E-CADH and KRT7 levels were subsequently analyzed in the TMA of the Canadian Ovarian Experimental Unified Resource cohort (COEUR, n = 1158 patients) and in public datasets. Epithelial marker expression was highly variable in HGSC cell lines and tissues. In the Discovery cohort, high levels of KRT7 and KRT19 were associated with an unfavorable prognosis, whereas high E-CADH expression indicated a better outcome. Expression of KRT7 and E-CADH gave a robust combination to predict overall survival (OS, p = 0.004) and progression free survival (PFS, p = 5.5 × 10⁻⁴) by Kaplan–Meier analysis. In the COEUR cohort, the E-CADH-KRT7 signature was a strong independent prognostic biomarker (OS, HR = 1.6, p = 2.9 × 10⁻⁴; PFS, HR = 1.3, p = 0.008) and predicted a poor patient response to chemotherapy (p = 1.3 × 10⁻⁴). Our results identify a combination of two epithelial markers as highly significant indicators of HGSC patient prognosis and treatment response.     

Polymorphisms in EGFR Gene Predict Clinical Outcome in Unresectable Non-Small Cell Lung Cancer Treated with Radiotherapy and Platinum-Based Chemoradiotherapy

For non-small cell lung cancer (NSCLC), radiotherapy (RT) and platinum-based chemotherapy (CHT) are among the main treatment options. On the other hand, radioresistance and cytotoxic drug resistance are common causes of failure. The epidermal growth factor receptor (EGFR) plays an important role in radioresponse and therapy resistance. We hypothesized that single nucleotide polymorphisms (SNPs) in the EGFR gene might affect individual sensitivity to these treatments, and thus, therapy outcome and prognosis. The association between functional EGFR SNPs and overall (OS), locoregional recurrence-free (LFRS), and metastasis-free (MFS) survival was examined in 436 patients with unresectable NSCLC receiving RT and platinum-based CHTRT. In a multivariate analysis, the rs712830 CC homozygotes showed reduced OS in the whole group (p = 0.039) and in the curative treatment subset (p = 0.047). The rs712829 TT genotype was strongly associated with decreased LRFS (p = 0.006), and the T-C haplotype was a risk factor for locoregional recurrence in our patients (p = 0.003). The rs2227983 GG alone and in combination with rs712829 T was an indicator of unfavorable LRFS (p = 0.028 and 0.002, respectively). Moreover, significant independent effects of these SNPs on OS, LRFS, and MFS were observed. Our results demonstrate that inherited EGFR gene variants may predict clinical outcomes in NSCLC treated with DNA damage-inducing therapy.     

Sources of Variation in Cuticular Hydrocarbons in the Ant Formica exsecta

Phenotypic variation arises from interactions between genotype and environment, although how variation is produced and then maintained remains unclear. The discovery of the nest-mate recognition system in Formica exsecta ants has allowed phenotypic variation in chemical profiles to be quantified across a natural population of 83 colonies. We investigated if this variation was correlated or not with intrinsic (genetic relatedness), extrinsic (location, light, temperature), or social (queen number) factors. (Z)-9-Alkenes and n-alkanes showed different patterns of variance: island (location) explained only 0.2 % of the variation in (Z)-9-alkenes, but 21–29 % in n-alkanes, whereas colony of origin explained 96 % and 45–49 % of the variation in (Z)-9-alkenes and n-alkanes, respectively. By contrast, within-colony variance of (Z)-9-alkenes was 4 %, and 23–34 % in n-alkanes, supporting the function of the former as recognition cues. (Z)-9-Alkene and n-alkane profiles were correlated with the genetic distance between colonies. Only n-alkane profiles diverged with increasing spatial distance. Sampling year explained a small (5 %), but significant, amount of the variation in the (Z)-9-alkenes, but there was no consistent directional trend. Polygynous colonies and populous monogynous colonies were dominated by a rich C_23:1 profile. We found no associations between worker size, mound exposure, or humidity, although effect sizes for the latter two factors were considerable. The results support the conjecture that genetic factors are the most likely source of between-colony variation in cuticular hydrocarbons.     

Multi-omics differential gene regulatory network inference for lung adenocarcinoma tumor progression biomarker discovery

A systematic method was proposed to infer differential gene regulatory networks (GRNs) among lung adenocarcinoma (LUAD) samples at different stages by integrating multi-omics data to uncover significant network features and to identify tumor progression (TP) biomarker genes. The mRNA expressions, copy number variations, and DNA methylations of two independent LUAD cohorts (TCGA and SPORE) at stages I, II, and III were used, respectively. As results, the transition from normal to early onset was showed to be critical to reveal the pathogenesis of LUAD; 61 genes were identified as TP-related biomarkers, including two types of microRNAs of ABLIM2 and ZFAS1. These identified biomarkers may set light on the underlying mechanism of LUAD TP and may serve as potential drug targets for new treatments. Moreover, our study provides a general framework for TP biomarker identification for other types of cancer, which may improve the mechanism research for cancer development.     

Network structure of spontaneously forming physically cross-link hydrogel composed of two-water soluble phospholipid polymers

Hydrogels containing 2-methacryloyloxyethyl phosphorylcholine (MPC) moieties were prepared from aqueous solutions with water-soluble poly[MPC-co-methacrylic acid (MA)] (PMA) and poly[MPC-co-n-butyl methacrylate (BMA)] (PMB). We had found that the hydrogel would swell under acidic pH and dissociate under neutral and alkaline conditions. Investigating these properties together with the complex modulus and the calculating cross-link molecular weight, we tried to determine how the network is constructed. The hydrogel showed a low swelling and a low elastic modulus E as the PMA feed ratio increases. However, a slow dissociation behavior was shown at the same time. This is due to the formation of the intramolecular cross-links caused by hydrogen bonds provided by carboxyl groups inside the hydrogel, which does not contribute to the swelling or elastic property. However, they had affected the ionization of the carboxyl groups. The average cross-link molecular weight decreased with the higher PMA feed ratio, indicating that the network is actually denser. The calculated cross-link molecular weight for the high PMA feed ratio is low, but the number of cross-links is also low, indicating that there are many intramolecular cross-link networks, but fewer valid entanglements for high mechanical strength. Therefore, denser networks are formed for higher the PMA feed ratio, but they do not function as cross-link junctions. This could be confirmed by Fourier transform infrared spectroscopy (FTIR). When the release behavior of the loaded drugs was tested, it showed that the drugs with molecular weights higher than the cross-link molecular weight would be slower than that of drugs with lower molecular weights.