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[Display omitted] Eosinophilic esophagitis (EoE) is characterized by persistent or relapsing allergic inflammation, and both clinical and histologic features of esophageal inflammation persist over time in most individuals. Mechanisms contributing to EoE relapse are not understood, and chronic EoE-directed therapy is therefore required to prevent long-term sequelae. We investigated whether EoE patients in histologic remission have persistent dysregulation of esophageal gene expression. Esophageal biopsy samples from 51 pediatric and 52 adult subjects with EoE in histopathologic remission (<15 eosinophils per high-power field [eos/hpf]) and control (48 pediatric and 167 adult) subjects from multiple institutions were subjected to molecular profiling by the EoE diagnostic panel, which comprises a set of 94 esophageal transcripts differentially expressed in active EoE. Defining remission as <15 eos/hpf, we identified 51 and 32 differentially expressed genes in pediatric and adult EoE patients compared to control individuals, respectively (false discovery rate < 0.05). Using the stringent definition of remission (0 eos/hpf), the adult and pediatric cohorts continued to have 18 and 25 differentially expressed genes (false discovery rate < 0.05). Among 6 shared genes between adults and children, CDH26 was upregulated in both children and adults; immunohistochemistry demonstrated increased cadherin 26 staining in the epithelium of EoE patients in remission compared to non-EoE controls. In the adult cohort, POSTN expression correlated with the endoscopic reference system score (Spearman r = 0.35, P =.011), specifically correlating with the rings' endoscopic reference system subscore (r = 0.53, P =.004). We have identified persistent EoE-associated esophageal gene expression in patients with disease in deep remission. These data suggest potential inflammation-induced epigenetic mechanisms may influence gene expression during remission in EoE and provide insight into possible mechanisms that underlie relapse in EoE. [ABSTRACT FROM AUTHOR]

Bladder cancer (BCa) is a significant health issue and poses a healthcare burden on patients, highlighting the importance of an effective detection method. Here, we developed a urine DNA methylation diagnostic panel for distinguishing between BCa and non-BCa. In the discovery stage, an analysis of the TCGA database was conducted to identify BCa-specific DNA hypermethylation markers. In the validation phase, DNA methylation levels of urine samples were measured with real-time quantitative methylation-specific PCR (qMSP). Comparative analysis of the methylation levels between BCa and non-BCa, along with the receiver operating characteristic (ROC) analyses with machine learning algorithms (logistic regression and decision tree methods) were conducted to develop practical diagnostic panels. The performance evaluation of the panel shows that the individual biomarkers of ZNF671, OTX1, and IRF8 achieved AUCs of 0.86, 0.82, and 0.81, respectively, while the combined yielded an AUC of 0.91. The diagnostic panel using the decision tree algorithm attained an accuracy, sensitivity, and specificity of 82.6%, 75.0%, and 90.9%, respectively. Our results show that the urine-based DNA methylation diagnostic panel provides a sensitive and specific method for detecting and stratifying BCa, showing promise as a standard test that could enhance the diagnosis and prognosis of BCa in clinical settings. [ABSTRACT FROM AUTHOR]

Background: The “Bridge Project” is a Mexico in Alliance with St. Jude (MAS) initiative developed in 2019 to improve access, accuracy, and timeliness of specialized diagnostic studies for patients with suspected acute lymphoblastic leukemia (ALL). The project strategy relies on service centralization to improve service delivery, biological characterization, risk-group classification, and support proper treatment allocation. Methods: This is an ongoing prospective multisite intersectoral quality improvement (QI) project available to all patients 0-18 years of age presenting with suspected ALL to the 14 actively participating institutions in 12 Mexican states. Institutions send specimens to one centralized laboratory. From a clinical standpoint, the project secures access to a consensus-derived comprehensive diagnostic panel. From a service delivery standpoint, we assess equity, timeliness, effectiveness, and patient-centeredness. From an implementation science standpoint, we document feasibility, utility, and appropriateness of the diagnostic panel and centralized approach. This analysis spans from July 2019 to June 2023. Results: 612 patients have accessed the project. The median age was 6 years (IQR 3-11), and 53% were males. 94% of the specimens arrived within 48 hours, which documents the feasibility of the centralized model, and 100% of the patients received precise and timely diagnostic results, which documents the effectiveness of the approach. Of 505 (82.5%) patients with confirmed ALL, 463/505 (91.6%) had B-cell ALL, and 42/505 (8.3%) had T-cell ALL. High-hyperdiploidy was detected by DNA index in 36.6% and hypodiploidy in 1.6%. 76.6% of the patients had conclusive karyotype results. FISH studies showed t (12;21) in 15%, iAMP21 in 8.5%, t(1;19) in 7.5%, t(4;11) in 4.2%, t(9;22) in 3.2%, del (9)(p21) in 1.8%, and TRA/D (14)(q11.2) rearrangement in 2.4%. Among B-cell ALL patients, 344/403 (85.1%) had Day 15 MRD<1% and 261/305 (85.6%) Day 84 MRD<0.01. For T-cell ALL patients 20/28 (71.4%) had Day 29 MRD<0.01% and 19/22 (86.4%) Day 84 MRD<0.01%. Conclusions: By securing access to a standardized consensus-derived diagnostic panel, the Bridge Project has allowed better characterization of childhood ALL in Mexico while producing unprecedented service improvements and documenting key implementation outcomes. We are using these results to inform iterative changes to the diagnostic panel and an associated treatment guideline (MAS-ALL18). [ABSTRACT FROM AUTHOR]

BackgroundThe “Bridge Project” is a Mexico in Alliance with St. Jude (MAS) initiative developed in 2019 to improve access, accuracy, and timeliness of specialized diagnostic studies for patients with suspected acute lymphoblastic leukemia (ALL). The project strategy relies on service centralization to improve service delivery, biological characterization, risk-group classification, and support proper treatment allocation.MethodsThis is an ongoing prospective multisite intersectoral quality improvement (QI) project available to all patients 0-18 years of age presenting with suspected ALL to the 14 actively participating institutions in 12 Mexican states. Institutions send specimens to one centralized laboratory. From a clinical standpoint, the project secures access to a consensus-derived comprehensive diagnostic panel. From a service delivery standpoint, we assess equity, timeliness, effectiveness, and patient-centeredness. From an implementation science standpoint, we document feasibility, utility, and appropriateness of the diagnostic panel and centralized approach. This analysis spans from July 2019 to June 2023.Results612 patients have accessed the project. The median age was 6 years (IQR 3-11), and 53% were males. 94% of the specimens arrived within 48 hours, which documents the feasibility of the centralized model, and 100% of the patients received precise and timely diagnostic results, which documents the effectiveness of the approach. Of 505 (82.5%) patients with confirmed ALL, 463/505 (91.6%) had B-cell ALL, and 42/505 (8.3%) had T-cell ALL. High-hyperdiploidy was detected by DNA index in 36.6% and hypodiploidy in 1.6%. 76.6% of the patients had conclusive karyotype results. FISH studies showed t(12;21) in 15%, iAMP21 in 8.5%, t(1;19) in 7.5%, t(4;11) in 4.2%, t(9;22) in 3.2%, del(9)(p21) in 1.8%, and TRA/D (14)(q11.2) rearrangement in 2.4%. Among B-cell ALL patients, 344/403 (85.1%) had Day 15 MRD

Introduction: Acute aortic dissection (AAD) often leads to the development of acute lung injury (ALI). However, the early detection and diagnosis of AAD in patients with ALI pose significant challenges. The objective of this study is to investigate distinct metabolic alterations in the plasma samples of AAD patients with ALI, AAD patients without ALI, and healthy individuals.Method: Between September 2019 and September 2022, we retrospectively collected data from 228 AAD patients who were diagnosed with ALI through post-surgery chest X-ray and PaO2/FiO2 assessments. Univariate analysis was employed to identify pre-surgery risk factors for ALI. Additionally, we conducted high-throughput target metabolic analysis on 90 plasma samples, comprising 30 samples from AAD patients with ALI, 30 from patients with AAD only, and 30 from healthy controls. After LC-MS spectral processing and metabolite quantification, the recursive feature elimination with cross-validation (RFECV) analysis based on the random forest was used to select the optimal metabolites as a diagnostic panel for the detection of AAD patients with ALI. The support vector machines (SVM) machine learning model was further applied to validate the diagnostic accuracy of the established biomarker panel.Results: In the univariate analysis, preoperative β-HB and TNF-α exhibited a significant association with lung injury (OR = 0.906, 95% CI 0.852–0.965, p = 0.002; OR = 1.007, 95% CI 1.003–1.011, p < 0.0001). The multiple-reaction monitoring analysis of 417 common metabolites identified significant changes in 145 metabolites (fold change >1.2 or

BackgroundEosinophilic gastritis (EG) is a clinicopathologic disorder with marked gastric eosinophilia and clinical symptoms. There is an unmet need among patients with EG for more precise diagnostic tools.ObjectiveWe aimed to develop tissue- and blood-based diagnostic platforms for EG.MethodsPatients with EG and control subjects without EG were enrolled across 9 Consortium of Eosinophilic Gastrointestinal Disease Researchers-associated sites. An EG Diagnostic Panel (EGDP; gastric transcript subset) and EG blood biomarker panel (protein multiplex array) were analyzed. EGDP18 scores were derived from the expression of 18 highly dysregulated genes, and blood EG scores were derived from dysregulated cytokine/chemokine levels.ResultsGastric biopsy specimens and blood samples from 185 subjects (patients with EG, n = 74; control subjects without EG, n = 111) were analyzed. The EGDP (1) identified patients with active EG (P < .0001, area under the curve ≥ 0.95), (2) effectively monitored disease activity in longitudinal samples (P = .0078), (3) highly correlated in same-patient samples (antrum vs body, r = 0.85, P < .0001), and (4) inversely correlated with gastric peak eosinophil levels (r = -0.83, P < .0001), periglandular circumferential collars (r = -0.73, P < .0001), and endoscopic nodularity (r = -0.45, P < .0001). For blood-based platforms, eotaxin-3, thymus and activation-regulated chemokine, IL-5, and thymic stromal lymphopoietin levels were significantly increased. Blood EG scores (1) distinguished patients with EG from control subjects without EG (P < .0001, area under the curve ≥ 0.91), (2) correlated with gastric eosinophil levels (plasma: r = 0.72, P = .0002; serum: r = 0.54, P = .0015), and (3) inversely correlated with EGDP18 scores (plasma: r = -0.64, P = .0015; serum: r = -0.46, P = .0084). Plasma eotaxin-3 levels strongly associated with gastric CCL26 expression (r = 0.81, P < .0001).ConclusionWe developed tissue- and blood-based platforms for assessment of EG and uncovered robust associations between specific gastric molecular profiles and histologic and endoscopic features, providing insight and clinical readiness tools for this emerging rare disease.

Introduction. World statistics indicate an increase in patients, including young people, suffering from dry eye disease (DED). Along with exogenous factors, the development of DED depends on a genetic predisposition. Changes in the expression of genes PTPN22, TRIM21, directly or indirectly affecting the T-cell link of immunity, leads to overproduction of cytokines and, as a consequence, damage to the ocular surface.This study aimed to design a diagnostic panel of genetic markers to determine the risk for DED of various etiologies development.Materials and methods. The study included 154 patients with autoimmune diseases with and without established DED. With a diagnosis of rheumatoid arthritis (RA) n = 79 and primary Sjogren’s syndrome (PSS) n = 75. The control group consisted of 100 people without ophthalmic diseases, 31 patients with exogenous DED. In this study, we use melting curve analysis to confirm the results of the association analysis for polymorphic markers in genes.Results. The prognostic value of the predisposing genotypes of the TRIM21 gene of the markers rs915956 and rs7947461 with the risk of DED in the presence of RA (p ≤ 0.001), the marker rs4144331 at the tendency level (p ≤ 0.1) was determined. The risk of developing DES against the background of PSS is associated with the presence of the predisposing genotypes of the TRIM21 genes, the rs4144331 marker, and the PTPN22 rs33996649 marker (p ≤ 0.001). The association of polymorphic markers of the TRIM21 rs7947461 gene and the PTPN22 gene of the rs33996649 marker (p ≤ 0.01) with the risk of developing exogenous DED was established.Conclusions. The predisposing genotypes were identified and the associations of polymorphic markers of the TRIM21, PTPN22 genes were established. A diagnostic panel of genetic markers has been created to predict DED of various etiologies.

[Display omitted] The Index of Severity for Eosinophilic Esophagitis (I-SEE) is a new expert-defined clinical tool that classifies disease severity of eosinophilic esophagitis (EoE). We aimed to determine whether I-SEE is associated with patient characteristics, molecular features of EoE, or both. We analyzed a prospective cohort of patients with EoE from the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR). Associations between I-SEE and clinical and molecular features (assessed by an EoE diagnostic panel [EDP]) were assessed. In 318 patients with chronic EoE (209 adults, 109 children), median total I-SEE score was 7.0, with a higher symptoms and complications score in children than adults (4.0 vs 1.0; P <.001) and higher inflammatory and fibrostenotic features scores in adults than children (3.0 vs 1.0 and 3.0 vs 0, respectively; both P <.001). Total I-SEE score had a bimodal distribution with the inactive to moderate categories and severe category. EDP score correlated with total I-SEE score (r = −0.352, P <.001) and both inflammatory and fibrostenotic features scores (r = −0.665, P <.001; r = −0.446, P <.001, respectively), but not with symptoms and complications scores (r = 0.047, P =.408). Molecular severity increased from inactive to mild and moderate, but not severe, categories. Longitudinal changes of modified I-SEE scores and inflammatory and fibrostenotic features scores reflected histologic and molecular activity. I-SEE score is associated with select clinical features across severity categories and with EoE molecular features for nonsevere categories, warranting further validation. [ABSTRACT FROM AUTHOR]

The metabolic differences between patients with calcium oxalate (CaOx) urolithiasis and the healthy population remain unclear. Currently there is no diagnostic panel for CaOx urolithiasis. This study aimed to identify the full-scale metabolic changes in the urine of CaOx urolithiasis patients and to establish a novel diagnostic panel as a noninvasive early prevention method. 240 urine samples were collected from 137 patients diagnosed with CaOx urolithiasis and 103 healthy controls. Electrospray ionization – mass spectrometry (ESI-MS) metabolomics and univariate, multivariate, and bioinformatic analyses were combined to identify the differential metabolites and related metabolic pathways between the groups. Integrated machine learning methods were adopted to discover potential biomarkers and establish a diagnostic panel. 79 differential metabolites were identified in the urine of patients compared with healthy controls. Pathways closely associated with these abnormal metabolites included metabolic pathways, amino acid biosynthesis, microbial metabolism in diverse environments, and protein digestion and absorption. Five potential metabolites, n-acetylputrescine, n-alpha-acetyl-L-arginine, ethyl 3-hydroxybutyrate, s-adenosylmethionine, and l-pyroglutamic acid, were selected as biomarkers by machine learning models, which included logistic regression (LR), random forest (RF), and support vector machine (SVM) models. The panel showed an excellent classification to differentiate patients from healthy controls with areas under the curve (AUC) of 0.998 in the training cohort and 0.993 in the validation cohort. The results revealed differential metabolites between the two groups. Furthermore, a panel of potential biomarkers was established for the first time and showed promising diagnostic value. [ABSTRACT FROM AUTHOR]

Abstract Cancer is one of the main health challenges and leading causes of deaths in the world. Various environmental and genetic risk factors are associated with tumorigenesis. Epigenetic deregulations are also important risk factors during tumor progression which are reversible transcriptional alterations without any genomic changes. Various mechanisms are involved in epigenetic regulations such as DNA methylation, chromatin modifications, and noncoding RNAs. Cancer incidence and mortality have a growing trend during last decades among Iranian population which are significantly related to the late diagnosis. Therefore, it is required to prepare efficient molecular diagnostic panels for the early detection of cancer in this population. Promoter hyper methylation is frequently observed as an inhibitory molecular mechanism in various genes associated with DNA repair, cell cycle regulation, and apoptosis during tumor progression. Since aberrant promoter methylations have critical roles in early stages of neoplastic transformations, in present review we have summarized all of the aberrant methylations which have been reported during tumor progression among Iranian cancer patients. Aberrant promoter methylations are targetable and prepare novel therapeutic options for the personalized medicine in cancer patients. This review paves the way to introduce a non-invasive methylation specific panel of diagnostic markers for the early detection of cancer among Iranians.

Yueting Tang,1 Yirong Li,1 Jiayu Sun,2 Huaqin Pan,3 Fen Yao,2 Xiaoyang Jiao2 1Department of Clinical Laboratory, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of China; 2Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 3Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of ChinaCorrespondence: Xiaoyang JiaoShantou University Medical College, Shantou, Guangdong, People’s Republic of ChinaTel +86-754-88900459Fax +86-754-88557562Email xyjiao@stu.edu.cnPurpose: It is difficult to predict the prognosis of COVID-19 patients at the disease onset. This study was designed to add new biomarkers into conventional inflammatory panels to build an optimal combination panel, to better triage patients and predict their outcomes.Patients and Methods: Biochemical parameters representing multi-organ functions, cytokines, acute-phase proteins, and other inflammatory markers were measured in COVID-19 patients on hospital admission. Receiver operating characteristic (ROC) curves, logistic regression, event-free survival (EFS), and Cox analyses were performed to screen and compare the predictive capabilities of the new panel in patients with different illness severity and outcome.Results: This study included 120 patients with COVID-19, consisting of 32 critical, 28 severe, and 60 mild/moderate patients. Initial levels of the selected biomarkers showed a significant difference in the three groups, all of which influenced patient outcome and EFS to varying degrees. Cox proportional hazard model revealed that procalcitonin (PCT) and interleukin 10 (IL-10) were independent risk factors, while superoxide dismutase (SOD) was an independent protective factor influencing EFS. In discriminating the critical and mild patients, a panel combining PCT, IL-6, and neutrophil (NEUT) yielded the best diagnostic performance with an AUC of 0.99, the sensitivity of 90.60% and specificity of 100%. In distinguishing between severe and mild patients, SOD’s AUC of 0.89 was higher than any other single biomarker. In differentiating the critical and severe patients, the combination of white blood cell count (WBC), PCT, IL-6, IL-10, and SOD achieved the highest AUC of 0.95 with a sensitivity of 75.00% and specificity of 100%.Conclusion: The optimal combination panel has a substantial potential to better triage COVID-19 patients on admission. Better triage of patients will benefit the rational use of medical resources.Keywords: COVID-19, diagnostic panel, cytokine, acute-phase protein

Abstract Background Cancer is associated with various genetic and environmental risk factors. Beside the mutations or aberrant expression of protein-coding genes, the genetic deregulation of non-coding RNAs has also an important role during tumor progression and metastasis. Long non-coding RNAs (lncRNAs) are a class of ncRNAs larger than 200 nucleotides that may function as tumor-suppressor or oncogene. Main body There is a raising trend of cancer incidence among Iranian population during the last decades. Therefore, it is required to prepare a general population specific panel of genetic markers for the early detection of cancer in this population. The tissue-specific expression characteristics and high stability in body fluids highlight the lncRNAs as efficient diagnostic and prognostic noninvasive biomarkers in cancer. In present review we summarized all of the lncRNAs which have been reported until now in different tumors among Iranian patients. Conclusions This review paves the way of introducing a population based noninvasive diagnostic panel of lncRNAs for the early detection of tumor cells among Iranian population.

Background: Eosinophilic esophagitis (EoE) is considered to be an immunoglobulin E (IgE)-mediated allergic disorder. Our goal was to examine IgE-mediated allergic sensitization patterns in patients with esophageal eosinophilia (EE).Methods: We enrolled subjects with EE who underwent evaluation with a diagnostic panel to document multiple allergen-specific IgEs. Statistically significant groups were identified by cluster analysis. We also defined allergens based on their characteristics including outdoor, indoor, plant, and animal allergens.Results: We classified patients with EE into 3 distinct groups, including cluster 1 (n = 62) who were minimally sensitized to most allergens except pollen and house dust, cluster 2 (n = 30) who were hypersensitized to outdoor and plant allergens, and cluster 3 (n = 15) who were hypersensitized to most allergens, most notably to indoor and animal allergens. Dysphagia reported among those in clusters 1, 2, and 3 at 35.5%, 46.7%, and 73.3%, respectively, (p = 0.028) and EoE endoscopic reference scores (EREFS) at 3.0, 6.0, and 8.0, respectively, (p < 0.001) differed significantly between the 3 clusters. Those in cluster 3 had a significantly higher prevalence of dysphagia (35.5% vs. 73.3%, p = 0.030), and higher EREFS with respect to rings (0.3 vs. 0.9, p = 0.003) and strictures (0.0 vs. 0.13, p = 0.011) compared to those in cluster 1.Conclusions: IgE-mediated allergic sensitization patterns are associated with clinical features of patients with EE. Use of a diagnostic panel that detects multiple allergen-specific IgEs can help to explain the heterogeneous phenotype of this patient cohort. [ABSTRACT FROM AUTHOR]

Cancer is one of the main health challenges and leading causes of deaths in the world. Various environmental and genetic risk factors are associated with tumorigenesis. Epigenetic deregulations are also important risk factors during tumor progression which are reversible transcriptional alterations without any genomic changes. Various mechanisms are involved in epigenetic regulations such as DNA methylation, chromatin modifications, and noncoding RNAs. Cancer incidence and mortality have a growing trend during last decades among Iranian population which are significantly related to the late diagnosis. Therefore, it is required to prepare efficient molecular diagnostic panels for the early detection of cancer in this population. Promoter hyper methylation is frequently observed as an inhibitory molecular mechanism in various genes associated with DNA repair, cell cycle regulation, and apoptosis during tumor progression. Since aberrant promoter methylations have critical roles in early stages of neoplastic transformations, in present review we have summarized all of the aberrant methylations which have been reported during tumor progression among Iranian cancer patients. Aberrant promoter methylations are targetable and prepare novel therapeutic options for the personalized medicine in cancer patients. This review paves the way to introduce a non-invasive methylation specific panel of diagnostic markers for the early detection of cancer among Iranians. [ABSTRACT FROM AUTHOR]

Serum microRNAs (miRNAs), with their noticeable stability and unique expression pattern in patients with various diseases, are robust novel non-invasive biomarkers for cancer detection. The objective of this study was to identify specific serum miRNAs as potential biomarkers for screening lung adenocarcinoma. The study was divided into a screening phase, training phase, and validation phase. The expression of 46 serum miRNAs from lung adenocarcinoma (LUAD) patients and healthy controls (HCs) were examined in the screening phase. The expression of the most dysregulated miRNAs was further verified in training (30 LUAD vs. 30 HCs) and validation (82 LUAD vs. 90 HCs) phases. Seven serum miRNAs (miR-142-5p, miR-203a-5p, miR-409-3p, miR-223-3p, miR-150-5p, miR-486-5p and miR-146a-5p) in LUAD patients were significantly dysregulated compared to those in HCs. Their ability to diagnose lung cancer was also significant, with miR-142-5p (AUC = 0.743), miR-409-3p (AUC = 0.755), miR-223-3p (AUC = 0.828) and miR-146a-5p (AUC = 0.745) being more prominent. The combined use of these four could enhance diagnostic value (AUC = 0.933). Our findings define a distinct miRNA expression profile in the serum of LUAD patients. The four-miRNA panel (miR-142-5p, miR-409-3p, miR-223-3p and 146a-5p) may be considered as a novel, non-invasive biomarker for LUAD early detection. [ABSTRACT FROM AUTHOR]

Objectives: Although low-dose computed tomography has been confirmed to have meaningful diagnostic utility, lung cancer is still the leading cause of cancer-related deaths for both genders worldwide. Thus, a novel panel with a stronger diagnostic performance for lung cancer is needed. This study aimed to investigate the efficacy of a new panel in lung cancer diagnosis. Materials and Methods: The serum levels of carcinoembryonic antigen (CEA), cancer antigen 125 (CA125) and seven autoantibodies were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. The 316 candidates enrolled in this study were randomly assigned into two groups for the training and validation of a diagnostic panel. Results: An optimal panel with four biomarkers (CEA, CA125, Annexin A1-Ab, and Alpha enolase-Ab) was established, with an area under the receiver operator characteristic (ROC) curve (AUC) of 0.897, a sensitivity of 86.5%, a specificity of 82.3%, a positive predictive value (PPV) of 88.3%, a negative predictive value (NPV) of 79.7%, and a diagnostic accuracy of 84.8% for the training group. The panel was validated, with an AUC of 0.856 and a sensitivity of 87.5% for the validation group. Furthermore, the new panel performed significantly better in lung cancer screening than did CEA and CA125 in all of the cohorts (p< .05). Conclusion: The diagnostic performance of CEA and CA125 was significantly enhanced through their combination with two autoantibodies (Annexin A1-Ab, and Alpha enolase-Ab). Optimization of the measured autoantibodies is critical for generating a panel to detect lung cancer in patients.

Background: Cancer is associated with various genetic and environmental risk factors. Beside the mutations or aberrant expression of protein-coding genes, the genetic deregulation of non-coding RNAs has also an important role during tumor progression and metastasis. Long non-coding RNAs (lncRNAs) are a class of ncRNAs larger than 200 nucleotides that may function as tumor-suppressor or oncogene. Main body: There is a raising trend of cancer incidence among Iranian population during the last decades. Therefore, it is required to prepare a general population specific panel of genetic markers for the early detection of cancer in this population. The tissue-specific expression characteristics and high stability in body fluids highlight the lncRNAs as efficient diagnostic and prognostic noninvasive biomarkers in cancer. In present review we summarized all of the lncRNAs which have been reported until now in different tumors among Iranian patients. Conclusions: This review paves the way of introducing a population based noninvasive diagnostic panel of lncRNAs for the early detection of tumor cells among Iranian population. [ABSTRACT FROM AUTHOR]

Objectives: Although low-dose computed tomography has been confirmed to have meaningful diagnostic utility, lung cancer is still the leading cause of cancer-related deaths for both genders worldwide. Thus, a novel panel with a stronger diagnostic performance for lung cancer is needed. This study aimed to investigate the efficacy of a new panel in lung cancer diagnosis. Materials and Methods: The serum levels of carcinoembryonic antigen (CEA), cancer antigen 125 (CA125) and seven autoantibodies were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. The 316 candidates enrolled in this study were randomly assigned into two groups for the training and validation of a diagnostic panel. Results: An optimal panel with four biomarkers (CEA, CA125, Annexin A1-Ab, and Alpha enolase-Ab) was established, with an area under the receiver operator characteristic (ROC) curve (AUC) of 0.897, a sensitivity of 86.5%, a specificity of 82.3%, a positive predictive value (PPV) of 88.3%, a negative predictive value (NPV) of 79.7%, and a diagnostic accuracy of 84.8% for the training group. The panel was validated, with an AUC of 0.856 and a sensitivity of 87.5% for the validation group. Furthermore, the new panel performed significantly better in lung cancer screening than did CEA and CA125 in all of the cohorts (p<.05). Conclusion: The diagnostic performance of CEA and CA125 was significantly enhanced through their combination with two autoantibodies (Annexin A1-Ab, and Alpha enolase-Ab). Optimization of the measured autoantibodies is critical for generating a panel to detect lung cancer in patients. [ABSTRACT FROM AUTHOR]

Abstract Background Clinicians are confronted with an increasing number of patients with thyroid nodules. Reliable preoperative diagnosis of thyroid nodules remains a challenge because of inconclusive cytological examination of fine-needle aspiration biopsies. Although molecular analysis of thyroid tissue has shown promise as a diagnostic tool in recent years, it has not been successfully applied in routine clinical use, particularly in Chinese patients. Methods Whole-transcriptome sequencing of 19 primary papillary thyroid cancer (PTC) samples and matched adjacent normal thyroid tissue (NT) samples were performed. Bioinformatics analysis was carried out to identify candidate diagnostic genes. Then, RT-qPCR was performed to evaluate these candidate genes, and four genes were finally selected. Based on these four genes, diagnostic algorithm was developed (training set: 100 thyroid cancer (TC) and 65 benign thyroid lesions (BTL)) and validated (independent set: 123 TC and 81 BTL) using the support vector machine (SVM) approach. Results We discovered four genes, namely fibronectin 1 (FN1), gamma-aminobutyric acid type A receptor beta 2 subunit (GABRB2), neuronal guanine nucleotide exchange factor (NGEF) and high-mobility group AT-hook 2 (HMGA2). A SVM model with these four genes performed with 97.0 % sensitivity, 93.8 % specificity, 96.0 % positive predictive value (PPV), and 95.3 % negative predictive value (NPV) in training set. For additional independent validation, it also showed good performance (92.7 % sensitivity, 90.1 % specificity, 93.4 % PPV, and 89.0 % NPV). Conclusions Our diagnostic panel can accurately distinguish benign from malignant thyroid nodules using a simple and affordable method, which may have daily clinical application in the near future.

Peripheral blood from 77 cases of B-CLL was analyzed to evaluate the diagnostic value of SIg clonality and fluorescence intensity, mouse rosettes (MR), and CD5. Monoclonal SIg (L-chain restriction or H-chain restriction or both) was detected in 69 cases (89.61%), with weak fluorescence (mean channel number on flow cytometry

Abstract Background Canine vector-borne diseases (CVBD) are caused by a diverse array of pathogens with varying biological behaviors that result in a wide spectrum of clinical presentations and laboratory abnormalities. For many reasons, the diagnosis of canine vector-borne infectious diseases can be challenging for clinicians. The aim of the present study was to compare CVBD serological and molecular testing as the two most common methodologies used for screening healthy dogs or diagnosing sick dogs in which a vector-borne disease is suspected. Methods We used serological (Anaplasma species, Babesia canis, Bartonella henselae, Bartonella vinsonii subspecies berkhoffii, Borrelia burgdorferi, Ehrlichia canis, and SFG Rickettsia) and molecular assays to assess for exposure to, or infection with, 10 genera of organisms that cause CVBDs (Anaplasma, Babesia, Bartonella, Borrelia, Ehrlichia, Francisella, hemotropic Mycoplasma, Neorickettsia, Rickettsia, and Dirofilaria). Paired serum and EDTA blood samples from 30 clinically healthy dogs (Group I) and from 69 sick dogs suspected of having one or more canine vector-borne diseases (Groups II-IV), were tested in parallel to establish exposure to or infection with the specific CVBDs targeted in this study. Results Among all dogs tested (Groups I-IV), the molecular prevalences for individual CVBD pathogens ranged between 23.3 and 39.1%. Similarly, pathogen-specific seroprevalences ranged from 43.3% to 59.4% among healthy and sick dogs (Groups I-IV). Among these representative sample groupings, a panel combining serological and molecular assays run in parallel resulted in a 4-58% increase in the recognition of exposure to or infection with CVBD. Conclusions We conclude that serological and PCR assays should be used in parallel to maximize CVBD diagnosis.

• Plasma proteomic analyses were used to compare patients with MDD and healthy controls. • Patients with MDD and healthy controls have a differential expression of proteins. • L-selectin and an isoform of the Ras oncogene family have diagnostic value in MDD. • Biomarker panels may help develop a diagnostic approach for MDD. Major depressive disorder (MDD) is a major international public health issue; thus, investigating its underlying mechanisms and identifying suitable biomarkers to enable its early detection are imperative. Using data-independent acquisition-mass spectrometry-based proteomics, the plasma of 44 patients with MDD and 25 healthy controls was studied to detect differentially expressed proteins. Bioinformatics analyses, such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, Protein-Protein Interaction network, and weighted gene co-expression network analysis were employed. Moreover, an ensemble learning technique was used to build a prediction model. A panel of two biomarkers, L-selectin and an isoform of the Ras oncogene family was identified. With an area under the receiver operating characteristic curve of 0.925 and 0.901 for the training and test sets, respectively, the panel was able to distinguish MDD from the controls. Our investigation revealed numerous potential biomarkers and a diagnostic panel based on several algorithms, which may contribute to the future development of a plasma-based diagnostic approach and better understanding of the molecular mechanisms of MDD. [ABSTRACT FROM AUTHOR]

Vascular endothelial growth factor (VEGF), matrix metalloproteinase-9, and tissue inhibitor of metalloproteinase-1 may play a role in the pathogenesis of cancer disease. We investigated their levels and utility in comparison to cancer antigen (CA) 15-3 in patients with breast cancer (BC) and in relation to the control groups. The study included 100 women with BC, 50 patients with benign breast tumor, and 50 healthy women. The plasma levels of the tested parameters were determined using enzyme-linked immunosorbent assay, while CA 15-3 with chemiluminescent microparticle immunoassay. The results demonstrated significant differences in the concentration of the tested parameters and CA 15-3 between groups of patients with BC and healthy patients or patients with benign breast tumor. The plasma levels of VEGF and tissue inhibitor of metalloproteinase-1 were significantly higher in advanced tumor stages. The tested parameters were comparable to CA 15-3 values of the diagnostic sensitivity, specificity, the predictive values of positive and negative test results, and the area under the receiver-operating characteristic curve. The combined use of the tested parameters with CA 15-3 resulted in the increase in sensitivity, negative predictive value, and area under the receiver-operating characteristic curve, especially in the combination of VEGF with tumor marker (84%, 73%, 0.888, respectively). These findings suggest the usefulness of the tested parameters in the diagnosis of BC. VEGF, especially in combination with CA 15-3, showed the highest usefulness in the diagnosis of early BC. [ABSTRACT FROM AUTHOR]

The article discusses the role of microRNA (miRNA)-based biomarkers in the diagnosis of Alzheimer's disease (AD). Topics discussed include the significant variation in the miRNA-34a-mediated triggering receptor expressed in myeloid/microglial cells-2 (TREM-2) down-regulation in an African-American population and the three main genes involved in early-onset AD (EOAD), including presenilin 1 and presenilin 2. Also mentioned is the involvement of Aβ42 peptides production in the AD process.

Reliable preoperative diagnosis of malignant thyroid tumors remains challenging because of the inconclusive cytological examination of fine-needle aspiration biopsies. Although numerous studies have successfully demonstrated the use of high-throughput molecular diagnostics in cancer prediction, the application of microarrays in routine clinical use remains limited. Our aim was, therefore, to identify a small subset of genes to develop a practical and inexpensive diagnostic tool for clinical use. We developed a two-step feature selection method composed of a linear models for microarray data (LIMMA) linear model and an iterative Bayesian model averaging model to identify a suitable gene set signature. Using one public dataset for training, we discovered a three-gene signature dipeptidyl-peptidase 4 (DPP4), secretogranin V (SCG5) and carbonic anhydrase XII (CA12). We then evaluated the robustness of our gene set using three other independent public datasets. The gene signature accuracy was 85.7, 78.8 and 85.7%, respectively. For experimental validation, we collected 70 thyroid samples from surgery and our three-gene signature method achieved an accuracy of 94.3% by quantitative polymerase chain reaction (QPCR) experiment. Furthermore, immunohistochemistry in 29 samples showed proteins expressed by these three genes are also differentially expressed in thyroid samples. Our protocol discovered a robust three-gene signature that can distinguish benign from malignant thyroid tumors, which will have daily clinical application. [ABSTRACT FROM AUTHOR]

Sphingolipids (SPLs) are bioactive lipids that manifest structural diversity and complexity in eukaryotes. However, the distributions and functions of these molecules in mammalian tissues/cells have not been systematically investigated. Herein, we integrated shotgun lipidomics with targeted LC-MRM/MS approach to comprehensively analyze SPL species in various biological samples with high accuracy. Preliminarily, 1311 SPL molecules were identified in 18 kinds of mammalian samples, including 3 groups of human sera, 10 mouse tissues and 5 cell lines via 26 sphingoid long-chain bases scanning. The sphingolipidome compositions and distributions were systematically characterized and distinct qualitative and quantitative profiles were clearly exhibited in various samples, indicating unique biological functions of the sphingolipidomes. Next, targeted SPLs analysis by LC-MRM/MS with critical criteria monitoring two characteristic fragments of one precursor was applied to human serum samples from 24 coronary artery disease (CAD) patients and 12 healthy controls, which successfully quantified 170 SPL molecules. Ten novel SPL molecules were discovered as a potential diagnostic panel for CAD patients via multivariate exploratory receiver operating characteristic curve-based biomarker analysis. The diagnostic panel with the 10 SPL molecules achieved 97.2% accuracy, with a favorable auxiliary diagnostic value (AUC = 1.000), for the detection of CAD. These results clearly support the sphingolipidomic approach in application to discovering disease biomarker panel as well as deep investigation of biological functions of complex SPLs in mammalian samples. We integrated direct infusion shotgun lipidomics with targeted LC-MRM/MS to comprehensively profile and quantify sphingolipid species in various biological samples, enabling to discovery a potential diagnostic panel for CAD. [Display omitted] • A shotgun method comprehensively targeting 26 sphingoid bases enabled the identification of 1311 SPL molecules from various mammalian samples, expanding the existing mammalian sphingolipidome database and demonstrating the tissue-specificity and heterogeneity of sphingolipidomes. • A LC/MRM-MS method with critical criteria by monitoring two characteristic fragments of one precursor successfully validated and quantified 170 of 207 serum SPLs from the human serum samples of 24 CAD patients and 12 healthy controls. • A diagnostic biomarker panel of 10 SPL molecules for CAD achieved 97.2% accuracy, and a favorable auxiliary diagnostic value (AUC = 1.000). [ABSTRACT FROM AUTHOR]

Background: Canine vector-borne diseases (CVBD) are caused by a diverse array of pathogens with varying biological behaviors that result in a wide spectrum of clinical presentations and laboratory abnormalities. For many reasons, the diagnosis of canine vector-borne infectious diseases can be challenging for clinicians. The aim of the present study was to compare CVBD serological and molecular testing as the two most common methodologies used for screening healthy dogs or diagnosing sick dogs in which a vector-borne disease is suspected. Methods: We used serological (Anaplasma species, Babesia canis, Bartonella henselae, Bartonella vinsonii subspecies berkhoffii, Borrelia burgdorferi, Ehrlichia canis, and SFG Rickettsia) and molecular assays to assess for exposure to, or infection with, 10 genera of organisms that cause CVBDs (Anaplasma, Babesia, Bartonella, Borrelia, Ehrlichia, Francisella, hemotropic Mycoplasma, Neorickettsia, Rickettsia, and Dirofilaria). Paired serum and EDTA blood samples from 30 clinically healthy dogs (Group I) and from 69 sick dogs suspected of having one or more canine vector-borne diseases (Groups II-IV), were tested in parallel to establish exposure to or infection with the specific CVBDs targeted in this study. Results: Among all dogs tested (Groups I-IV), the molecular prevalences for individual CVBD pathogens ranged between 23.3 and 39.1%. Similarly, pathogen-specific seroprevalences ranged from 43.3% to 59.4% among healthy and sick dogs (Groups I-IV). Among these representative sample groupings, a panel combining serological and molecular assays run in parallel resulted in a 4-58% increase in the recognition of exposure to or infection with CVBD. Conclusions: We conclude that serological and PCR assays should be used in parallel to maximize CVBD diagnosis. [ABSTRACT FROM AUTHOR]

Background & Aims: Gene expression profiling provides an opportunity for definitive diagnosis but has not yet been well applied to inflammatory diseases. Here we describe an approach for diagnosis of an emerging form of esophagitis, eosinophilic esophagitis (EoE), which is currently diagnosed by histology and clinical symptoms. Methods: We developed an EoE diagnostic panel (EDP) comprising a 96-gene quantitative polymerase chain reaction array and an associated dual-algorithm that uses cluster analysis and dimensionality reduction using a cohort of randomly selected esophageal biopsy samples from pediatric patients with EoE (n = 15) or without EoE (non-EoE controls, n = 14) and subsequently vetted the EDP using a separate cohort of 194 pediatric and adult patient samples derived from both fresh or formalin-fixed, paraffin-embedded tissue: active EoE (n = 91), control (non-EoE and EoE remission, n = 57), histologically ambiguous (n = 34), and reflux (n = 12) samples. Results: The EDP identified adult and pediatric patients with EoE with approximately 96% sensitivity and approximately 98% specificity, and distinguished patients with EoE in remission from controls, as well as identified patients exposed to swallowed glucorticoids. The EDP could be used with formalin-fixed, paraffin-embedded tissue RNA and distinguished patients with EoE from those with reflux esophagitis, identified by pH-impedance testing. Preliminary evidence showed that the EDP could identify patients likely to have disease relapse after treatment. Conclusions: We developed a molecular diagnostic test (referred to as the EDP) that identifies patients with esophagitis in a fast, objective, and mechanistic manner, offering an opportunity to improve diagnosis and treatment, and a platform approach for other inflammatory diseases. [Copyright &y& Elsevier]

Abstract: Background: Although liver biopsy remains the best diagnostic standard for nonalcoholic steatohepatitis (NASH), non-invasive tests are eagerly awaited. In this study, we sought to develop a support vector machine (SVM) algorithm to discriminate with high accuracy between subjects with NASH and controls using a blood-based biomarker panel. Methods: A total of 17 biomarkers were measured by commercially available enzyme-linked immunosorbent assays in 136 serum samples from patients with biopsy-proven NASH (n=60) and subjects with normal ALT and no evidence of fatty liver on ultrasound (n=76). The database was randomly divided (1:1 fashion) into a discovery set for classification training and in a validation set of the chosen biomarkers in blinded samples. Multivariate analysis was performed by means of SVM. Results: After the identification of a group of three most discriminative biomarkers (osteoprotegerin, fibroblast growth factor 21, and M30) in the discovery set, the application of SVM to the validation test resulted in a 92.5% sensitivity and 84.1% specificity for distinguishing subjects with NASH from controls. Conclusions: A targeted biomarker profiling combined with a SVM-based pattern identification approach may allow the identification of patients with NASH with clinically relevant accuracy and validity. [Copyright &y& Elsevier]

In contrast with the traditional methods applied to assessment of population diversity, high-throughput sequencing technologies have a wider application in clinical practice with greater potential to find novel disease-causing variants for multifactorial disorders. Widely used test panels may not meet their goal to diagnose the patient's condition with a full reliability since this method often does not take into account the population frequencies of analyzed genetic markers. Here, we analyzed 57 male individuals of five ethnic groups from Russia and Tajikistan using the whole exome sequencing technique (Ion AmpliSeq Exome), which resulted in detecting more than 299,000 single nucleotide polymorphisms. Samples formed clusters on the PCA plot according to the geographical location of the corresponding populations. Thereby, the methodology of whole-exome sequencing, in general, and the Ion AmpliSeq Exome panel, in particular, could be positively applied for the purposes of population genetics and for detection of the novel clinically relevant variants. [ABSTRACT FROM AUTHOR]

Eosinophilic esophagitis (EoE) is a histologically "patchy" disease with uneven eosinophil distribution along the esophagus, posing a dilemma for histologically analyzing endoscopic biopsy samples, especially when biopsy samples are limited to only the distal esophagus. We investigated whether molecular mRNA profiling of a distal esophageal biopsy sample predicts eosinophilia in the proximal esophagus. Esophageal biopsy samples (n = 507) from subjects with EoE were collected from multiple institutions, spanning adults and pediatric patients. Subjects were grouped on the basis of distinct distal (D) and proximal (P) eosinophil counts (D+P+, D+P–, D-P+, and D–P–, with + and – defined as ≥15 or <15 eosinophils/hpf, respectively). Molecular profiles were assessed by using the EoE Diagnostic Panel (EDP), a set of 96 esophageal transcripts used to derive the EDP score. The distal EDP score was correlated with proximal eosinophil levels (r = –0.73; P <.0001). EDP analysis of a histologically negative distal biopsy sample predicted the presence of proximal esophagitis with high sensitivity (85%). In a 2-year follow-up focusing on the cases with discordant histologic and EDP results, histologically negative patients (D–P–) had higher rates of EoE relapse when the EDP was positive than when the EDP was negative (odds ratio = 11; P =.003), indicating predictive medicine capacity. EDP analysis of a single distal esophageal biopsy sample predicts remote inflammation in patients with spatially heterogeneous eosinophilia and disease relapse in patients with histologic remission, providing diagnostic merit and predictive medicine capacity for molecular diagnosis of EoE. [ABSTRACT FROM AUTHOR]

Temporal lobe epilepsy (TLE) is one of the most common forms of focal epilepsy in children and adults. TLE is characterized by variable onset and seizures. Moreover, this form of epilepsy is often resistant to pharmacotherapy. The search for new mechanisms for the development of TLE may provide us with a key to the development of new diagnostic methods and a personalized approach to the treatment. In recent years, the role of non-coding ribonucleic acids (RNA) has been actively studied, among which microRNA (miR) is of the greatest interest. (1) Background: The purpose of the systematic review is to analyze the studies carried out on the role of miRs in the development of mesial TLE (mTLE) and update the existing knowledge about the biomarkers of this disease. (2) Methods: The search for publications was carried out in the databases PubMed, Springer, Web of Science, Clinicalkeys, Scopus, OxfordPress, Cochrane. The search was carried out using keywords and combinations. We analyzed publications for 2016–2021, including original studies in an animal model of TLE and with the participation of patients with TLE, thematic and systemic reviews, and Cochrane reviews. (3) Results: this thematic review showed that miR‒155, miR‒153, miR‒361‒5p, miR‒4668‒5p, miR‒8071, miR‒197‒5p, miR‒145, miR‒181, miR‒199a, miR‒1183, miR‒129‒2‒3p, miR‒143‒3p (upregulation), miR–134, miR‒0067835, and miR‒153 (downregulation) can be considered as biomarkers of mTLE. However, the roles of miR‒146a, miR‒142, miR‒106b, and miR‒223 are questionable and need further study. (4) Conclusion: In the future, it will be possible to consider previously studied miRs, which have high specificity and sensitivity in mTLE, as prognostic biomarkers (predictors) of the risk of developing this disease in patients with potentially epileptogenic structural damage to the mesial regions of the temporal lobe of the brain (congenital disorders of the neuronal migration and neurogenesis, brain injury, neuro-inflammation, tumor, impaired blood supply, neurodegeneration, etc.). [ABSTRACT FROM AUTHOR]

Background: Stroke is a devastating complication of tuberculous meningitis (TBM) and is an important determinant of its outcome. We propose a model which would help to predict development of infarction or cerebrovascular events in patients of TBM.Methods: A prospective study with n=129 patients of TBM were evaluated for predictors and outcomes of stroke. A diagnostic grid was formulated with clinical, laboratory and radiology as parameters to predict the vascular outcomes. All patients were followed up for mortality and disability on the basis of modified rankin score (mRS). MRI & CSF cytokines TNF-alpha, IFN- gamma & IL-6,8, 10 were measured at baseline and 3 months. The diagnosis of TBM included definite, probable & possible types and stage I & II with early and late onset of symptoms respectively.Results: The mortality was 16.2% and 19.4% of all patients developed stroke. The mean GCS, barthel index and mRS at admission was 57.03± 9.5,10.2±2.3 & 3.3±0.03 respectively mild to moderate infection and functional limitation. Barthel index (BI) happened to be a strong predictor [F=32.6, p=0.001, t=15.5, βeta coefficient =0.002] followed by biomarker TNF-α [F=18.9, p=0.02, t= -2.07, βeta coefficient=-0.04]. N=25 patients developed stroke with TNF-α, IL-6, IFN -γ showing statistically significant increase in all the stroke affected TBM (95% CI; 4.5 to 1.2; p=0.003). At 3 months, it was observed that mRS was statistically significant between stage I & II (95% CI; 5.4 to 2.1; p=0.04).Conclusions: Our data revealed that 19.4% patients developed vascular events during the hospital stay or follow up. We recruited late onset TBM as compared to early onset. BI, TNF-α, IL6 are most potent predictors of stroke post TBM. [ABSTRACT FROM AUTHOR]

Lung Adenocarcinoma is one of the most leading causes of death worldwide. Early detection of this cancer could enhance the survival chance of patients and even lead to better and more effective treatment. One of the approaches to find out more about biological malfunctions is using "omics" data. Among diverse computational procedures, data integration is becoming a striking tool to deal with complicated diseases such as cancer, considering the defective and informative nature of each kind of "omics" data. Data integration as relates to lung adenocarcinoma can lead to finding molecular biomarkers that could solve early-stage detection and progression prediction alongside other screening technologies like low-dose spiral computed tomography. In the present study, we hypothesized that genes with multiple variations are essential to provoke lung adenocarcinoma and one may use them to predict tumor formation or even cancer development. We integrated the genomic, epigenomic, transcriptomic and proteomic data. Consequently, five genes were introduced and validated by different analyses including classification of patients and survival analysis. Furthermore, we constructed a bipartite mRNA-miRNA network to identify a set of miRNAs for further experimental analyses. Finally, a sensitive and specific diagnostic panel comprising CDKN2A, CX3CR1, COX4I2, SLC15A2 and TFRC genes were identified for early detection of Lung Adenocarcinoma. • By detecting cancer early, molecular biomarkers could increase the survival rate in complex diseases like cancer. • Genes with multiple variations in different biological levels (e.g. genomic, transcriptomic) could be possible biomarkers. • We found 5 genes as a possible diagnostic panel via integrating and validated them by different analyses. • The prognostic value of our panel was validated through survival analysis in an independent data set. • We created a bipartite mRNA-miRNA network and proposed novel miRNAs as probable lung cancer adenocarcinoma biomarkers. [ABSTRACT FROM AUTHOR]

Rationale: The invasive behavior of non-functioning pituitary neuroendocrine tumors (NF-PitNEts) presents obstacles for complete surgical resection and is indicative of poor prognosis. Therefore, developing reliable diagnostic tools for identifying invasive PitNEts would be helpful in guiding surgical decisions and, in particular, the follow-up treatment. Methods: We analyzed differential gene expression profiles between 39 non-invasive and 22 invasive NF-PitNEts by high-throughput sequencing, gene co-expression, and functional annotation. Twenty-one transcripts were further validated by Taqman-qPCR in another 143 NF-PitNEt samples. The histological expression and serum-exosomal mRNA of three candidate genes were examined by tissue microarray and droplet digital PCR. Results: Non-invasive and invasive NF-PitNEts were clustered into distinct groups with a few outliers because of their gonadotroph, corticotroph, or null cell lineages. The gene signature with strong invasive potential was enriched in 'Pathways in cancers' and 'MAPK pathway', with significantly higher in situ INSM1 and HSPA2 protein expression in invasive NF-PitNEts. Further integration of the 20 qPCR-validated differentially expressed genes and pituitary cell lineages provided a gene-subtype panel that performed 80.00-90.24% diagnostic accuracy for the invasiveness of NF-PitNEts. Conclusion: Our approach defined new characteristics in the core molecular network for patients at risk for invasive NF-PitNEt, representing a significant clinical advance in invasive PitNEt diagnostics., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The diagnostic odyssey refers to the struggle to achieve a diagnosis for a medical condition in the face of significant implications if a diagnosis is not made. It is a common experience for people living with a rare disease. Western Australia has led the way in Australia in being the first State to establish a rare disease policy framework and an Undiagnosed Diseases Program (UDP). The UDP includes an expert panel made up of various specialists brought together with the aim of arriving at a diagnosis through collaboration. This article looks at the possibility of enhancing initiatives such as the UDP through a legislative framework. Relieving the medical, financial and emotional implications of the diagnostic odyssey is particularly important when one considers that taken together, rare diseases affect millions of people globally., Competing Interests: None.