Potential Biomarker Candidates Research Articles

Serum and urine lipidomic profiles identify biomarkers diagnostic for seropositive and seronegative rheumatoid arthritis

ObjectiveSeronegative rheumatoid arthritis (RA) is defined as RA without circulating autoantibodies such as rheumatoid factor and anti-citrullinated protein antibodies; thus, early diagnosis of seronegative RA can be challenging. Here, we aimed to identify diagnostic biomarkers for seronegative RA by performing lipidomic analyses of sera and urine samples from patients with RA.MethodsWe performed untargeted lipidomic analysis of sera and urine samples from 111 RA patients, 45 osteoarthritis (OA) patients, and 25 healthy controls (HC). These samples were divided into a discovery cohort (n = 97) and a validation cohort (n = 84). Serum samples from 20 patients with systemic lupus erythematosus (SLE) were also used for validation.ResultsThe serum lipidome profile of RA was distinguishable from that of OA and HC. We identified a panel of ten serum lipids and three urine lipids in the discovery cohort that showed the most significant differences. These were deemed potential lipid biomarker candidates for RA. The serum lipid panel was tested using a validation cohort; the results revealed an accuracy of 79%, a sensitivity of 71%, and a specificity of 86%. Both seropositive and seronegative RA patients were differentiated from patients with OA, SLE, and HC. Three urinary lipids showing differential expression between RA from HC were identified with an accuracy of 84%, but they failed to differentiate RA from OA. There were five lipid pathways that differed between seronegative and seropositive RA.ConclusionHere, we identified a panel of ten serum lipids as potential biomarkers that can differentiate RA from OA and SLE, regardless of seropositivity. In addition, three urinary lipids had diagnostic utility for differentiating RA from HC.

Abstract PO4-24-02: Comprehensive Characterization of BCL2 Family Genes in Metaplastic Triple Negative Breast Cancer

Abstract Background: Metaplastic Breast Cancer (MBC) is rare (0.2-5%), aggressive form of BC characterized by chemotherapy resistance and has worse outcomes in comparison to other BC subtypes. Resistance to chemotherapeutic agents is related to defects in intact intrinsic apoptosis pathway and the BCL2 family of proteins are the central regulators of this pathway. Majority of MBC have triple-negative receptor status and have no standard therapeutic approach and validated prognostic markers. Here, we examine the association of BCL2 family pro-apoptotic and anti-apoptotic genes expression with metaplastic TNBC (MTNBC) patient survival. Methods: 13,036 BC samples (MTNBC, n=102; metaplastic non-TNBC, n=20) were analyzed by next-generation sequencing (592, NextSeq; WES, NovaSeq), Whole Transcriptome Sequencing (WTS; NovaSeq) (Caris Life Sciences, Phoenix, AZ). A total of 10 pro-apoptotic (BAX, BAK1, BID, BAD, BIK, BCL2L11, BMF, HRK, PMAIP1, BBC3) and 6 anti-apoptotic (BCL2, BCL2L1, BCL2L2, MCL1, BCL2A1, BCL2L10) BCL2 family genes were analyzed. MTNBC with PMAIP1-high(H) and -low(L) expression was classified by top and bottom quartile, respectively. Pathway enrichment was determined by GSEA (Broad Inst). Real world overall survival (OS) was extracted from insurance claims and calculated from tissue collection to last contact using Kaplan-Meier estimates. Statistical significance was determined using chi-square and Mann-Whitney U test with p-values adjusted for multiple comparisons (q < 0.05). Results: MTNBC had enrichment of apoptosis (NES: 1.4, FDR: 0.05), glycolysis (NES: 1.48, FDR: 0.03), PI3K/AKT/mTOR signaling (NES: 1.43, FDR: 0.05), P53 (NES: 1.51, FDR: 0.06), NOTCH signaling (NES: 1.39, FDR: 0.05), TGFβ signaling (NES: 1.41, FDR: 0.05), WNTβ catenin signaling (NES: 1.41, FDR: 0.05) and IL2/STAT5 signaling (NES: 1.33, FDR: 0.09) pathways compared to metaplastic non-TNBC. MTNBC had higher expression of BCL2 pro-apoptotic genes BAX (Fold Change (FC): 1.6), BAK1 (FC: 1.3), BID (FC: 2), BAD (FC: 1.6), BCL2L11 (FC: 2.5) and BBC3 (FC: 1.5), and anti-apoptotic genes BCL2L1 (FC: 1.6) and BCL2L2 (FC: 1.3) (all p < 0.05) compared to metaplastic non-TNBC. Higher PMAIP1 gene expression was associated with worse MTNBC patient survival (mOS: 14.3 month; HR: 0.37; 95% CI 0.19-1.41; p=0.002) (Table 1), but not in metaplastic non-TNBC (mOS: Inf; HR: 1.96; 95% CI 0.64-6.02; p=0.23). PMAIP1-H MTNBC had higher expression of immune checkpoint genes CD274 (FC: 2.8), PDCD1 (FC: 2.2), TIM3 (FC: 1.8), LAG3 (FC: 2.1) and IDO1 (FC: 5.7) (all p < 0.05), compared to PMAIP1-L MTNBC. PMAIP1-H MTNBC had higher frequency of IHC-PD-L1 positivity (68.4% vs 14.3%, p < 0.05). PMAIP1-H MTNBC had higher expression of stem cell related genes CD44 (FC: 1.7), ALDH1A2 (FC: 2.2), ALDH1A3 (FC: 2.6), SOX2 (FC: 5.21) and NANOG (FC: 2.13) (all p < 0.05) compared to PMAIP1-L MTNBC. Conclusion: This is the first comprehensive analysis of expression and prognostic role of BCL2 family proteins in MBC. Our data suggest a strong association of higher expression of PMAIP1 with worse MTNBC patient survival, potentially attributed to higher immune checkpoint, stem cell-related genes expression, and higher frequency of PD-L1 positivity in PMAIP1-H tumors. These findings indicate PMAIP1 as a potential prognostic biomarker candidate in MTNBC but needs further validation in large prospective studies Table 1. Overall survival of metaplastic TNBC patient based on BCL2 family gene expression. Citation Format: Pooja Advani, Sachin Deshmukh, Sharon Wu, Jacob Andring, Joanne Xiu, Alex Farrell, Milan Radovich, George Sledge Jr, Dario Trapani, Evanthia Roussos Torres, Stephanie Graff, Asher Chanan-Khan. Comprehensive Characterization of BCL2 Family Genes in Metaplastic Triple Negative Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-24-02.

Serum Levels of Long Non-coding RNAs NEAT1, GAS5, and GAPLINC Altered in Rheumatoid Arthritis.

Rheumatoid arthritis (RA), an autoimmune joint inflammatory disease, presents a significant challenge due to its prevalence, particularly among women, affecting around 6% of individuals over the age of 65. Novel insights into disease mechanisms are crucial for improved diagnostic and therapeutic approaches. Long non-coding RNAs (lncRNAs) have emerged as potential contributors to the pathogenesis of various autoimmune diseases, including RA. This study aims to investigate the unique roles of four lncRNAs-NEAT1, GAS5, TMEVPG1, and GAPLINC-in the etiology of RA. Leveraging isolated serum samples from RA patients and healthy controls, we comprehensively evaluated the expression profiles of these lncRNAs. Notably, our findings unveil a distinctive landscape of lncRNA expressions in RA. Among them, GAPLINC exhibited a significantly elevated average expression in the serum samples of RA patients, suggesting a potential biomarker candidate for disease stratification. Importantly, reduced expression of NEAT1 and GAS5 was observed in RA patients, highlighting their possible roles as diagnostic and prognostic markers. Conversely, TMEVPG1 displayed unaltered expression levels in RA samples. Our study introduces a novel dimension to RA research by identifying NEAT1, GAS5, and GAPLINC as promising serological biomarkers. These findings hold significant clinical implications, offering potential avenues for improved diagnosis, disease monitoring, and therapeutic interventions in RA.

Cervicovaginal metabolome and tumor characteristics for endometrial cancer detection and risk stratification.

Endometrial cancer is highly prevalent and lacking non-invasive diagnostic techniques. Diagnosis depends on histological investigation of biopsy samples. Serum biomarkers for endometrial cancer have lacked sensitivity and specificity. The objective of this study was to investigate the cervicovaginal environment to improve understanding of metabolic reprogramming related to endometrial cancer and identify potential biomarker candidates for non-invasive diagnostic and prognostic tests. Cervicovaginal lavages were collected from 192 participants with endometrial cancer (n=66) and non-malignant conditions (n=108), and global untargeted metabolomics was performed. Using the metabolite data (n=920), we completed a multivariate biomarker discovery analysis. We analyzed grade 1/2 endometrioid carcinoma (n=53) and other endometrial cancer subtypes (n=13) to identify shared and unique metabolic signatures between the subtypes. When compared to non-malignant conditions, downregulation of proline (p<0.0001), tryptophan (p<0.0001), and glutamate (p<0.0001) was found among both endometrial cancer groups, relating to key hallmarks of cancer including immune suppression and redox balance. Upregulation (q<0.05) of sphingolipids, fatty acids, and glycerophospholipids was observed in endometrial cancer in a type-specific manner. Furthermore, cervicovaginal metabolites related to tumor characteristics, including tumor size and myometrial invasion. Our findings provide insights into understanding the endometrial cancer metabolic landscape and improvement into diagnosis. The metabolic dysregulation described in this paper linked specific metabolites and pathophysiological mechanisms including cellular proliferation, energy supply, and invasion of neighbouring tissues. Furthermore, cervicovaginal metabolite levels related to tumor characteristics, which are used for risk stratification. Overall, development of non-invasive diagnostic can improve both the acceptability and accessibility of diagnosis.

The association between neighborhood deprivation and DNA methylation in an autopsy cohort.

Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimer's Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.

Candida albicans cDNA library screening reveals novel potential diagnostic targets for invasive candidiasis

The detection of patterns associated with the invasive form of Candida albicans, such as Candida albicans germ tube antibodies (CAGTA), is a useful complement to blood culture for Invasive Candidiasis (IC) diagnosis. As CAGTA are detected by a non-standardisable and non-automatable technique, a Candida albicans cDNA expression library was screened with CAGTA isolated from serum of an animal model of invasive candidiasis, and five protein targets were identified: hyphally regulated cell wall protein 1 (Hyr1), enolase 1 (Eno1), coatomer subunit gamma (Sec21), a metallo-aminopeptidase (Ape2) and cystathionine gamma-lyase (Cys3). Homology with proteins from other organisms rules out Cys3 as a good biomarker while Sec21 results suggest that it is not in the germ tubes surface but secreted to the external environment. Our analysis propose Ape2, Sec21 and a region of Hyr1 different from the one currently being studied for immunoprotection as potential biomarker candidates for the diagnosis of IC.

Serum proteomic profiling of patients with compensated advanced chronic liver disease with and without clinically significant portal hypertension.

Portal hypertension (PH) drives the progression of liver cirrhosis to decompensation and death. Hepatic venous pressure gradient (HVPG) measurement is the standard of PH quantification, and HVPG≥10 mmHg defines clinically significant PH (CSPH). We performed proteomics-based serum profiling to search for a proteomic signature of CSPH in patients with compensated advanced chronic liver disease (cACLD). Consecutive patients with histologically confirmed cACLD and results of HVPG measurements were prospectively included. Serum samples were pooled according to the presence/absence of CSPH and analysed by liquid chromatography-mass spectrometry. Gene set enrichment analysis was performed, followed by comprehensive literature review for proteins identified with the most striking difference between the groups. We included 48 patients (30 with, and 18 without CSPH). Protein CD44, involved in the inflammatory response, vascular endothelial growth factor C (VEGF-C) and lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), both involved in lymphangiogenesis were found solely in the CSPH group. Although identified in both groups, proteins involved in neutrophil extracellular traps (NET) formation, as well as tenascin C, autotaxin and nephronectin which mediate vascular contractility and lymphangiogenesis were more abundant in CSPH. We propose that altered inflammatory response, including NET formation, vascular contractility and formation of new lymph vessels are key steps in PH development. Proteins such as CD44, VEGF-C, LYVE-1, tenascin C, Plasminogen activator inhibitor 1, Nephronectin, Bactericidal permeability-increasing protein, Autotaxin, Myeloperoxidase and a disintegrin and metalloproteinase with thrombospondin motifs-like protein 4 might be considered for further validation as potential therapeutic targets and candidate biomarkers of CSPH in cACLD.

Challenges in the Metabolomics-Based Biomarker Validation Pipeline.

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.

The plasma miRNome and venous thromboembolism in high-grade glioma: miRNA Sequencing of a nested case-control cohort.

Patients with high-grade gliomas are at high risk of venous thromboembolism (VTE). MicroRNAs (miRNAs) are small non-coding RNAs with multiple roles in tumour biology, haemostasis and platelet function. Their association with VTE risk in high-grade glioma has not been comprehensively mapped so far. We thus conducted a nested case-control study within 152 patients with WHO grade IV glioma that had been part of a prospective cohort study on VTE risk factors. At inclusion a single blood draw was taken, and patients were thereafter followed for a maximum of 2 years. During that time, 24 patients (16%) developed VTE. Of the other 128 patients, we randomly selected 24 age- and sex-matched controls. After quality control, the final group size was 21 patients with VTE during follow-up and 23 without VTE. Small RNA next-generation sequencing of plasma was performed. We observed that hsa-miR-451a was globally the most abundant miRNA. Notably, 51% of all miRNAs showed a correlation with platelet count. The analysis of miRNAs differentially regulated in VTE patients-with and without platelet adjustment-identified potential VTE biomarker candidates such as has-miR-221-3p. Therewith, we here provide one of the largest and deepest peripheral blood miRNA datasets of high-grade glioma patients so far, in which we identified first VTE biomarker candidates that can serve as the starting point for future research.

305 Extracellular Vesicular mRNA and miRNA Biomarkers in Patients With Glioblastoma

INTRODUCTION: Glioblastoma (GBM) is a highly lethal primary brain cancer that is resistant to conventional immunotherapies. However, currently, there is a lack of reliable biomarkers for clinical practice. Extracellular vesicles (EVs) present in biofluids are a potential biomarker for GBM diagnosis. METHODS: EVs from cell culture medium, healthy donor and GBM patient serum were purified using tangential flow filtration (TFF). Morphology, size, and numbers of EVs were characterized by TEM and qNano, respectively. EVs from healthy donor and GBM patient serum were compared against other cancer EV samples using bulk mRNA and miRNA sequencing analysis. Selected mRNA and miRNA name are not mentioned due to patents being drafted. mRNA and miRNA expression in EVs were quantified by a fluorescent nucleic acid detection method using a biochip platform at a single-EV level. Fluorescence images were recorded using high-resolution total internal reflection fluorescence (TIRF) microscopy. RESULTS: From bulk mRNA and miRNA sequencing and bioinformatics analysis, three miRNA and two mRNA were selected as potential candidate biomarkers for GBM. Subsequently, EVs from the serum of GBM patients (n = 39) were evaluated through our biochip platform. mRNA and miRNA expression of these biomarkers were positive in single EVs, for which we detected colocalization of protein/RNAs or multiple RNAs in subpopulations of EVs. Our platform was benchmarked with a standard PCR method showing 100X more sensitivity. Moreover, levels of expression of the different RNAs were compared to a cohort of serum from healthy donors (n=20), and showing significant differences between the two groups. CONCLUSIONS: Our non-invasive biochip assay outperformed qRT-PCR for EV RNA detection. Selected mRNAs and miRNAs in subpopulations of EVs could be used as potential GBM biomarkers.

318 Profiling Long RNA Transcriptome From Circulating Extracellular Vesicles in Subarachnoid Hemorrhage for Biomarker Discovery

INTRODUCTION: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality rate and permanent neurological deficits following acute brain injury. Previous studies have aimed at investigating CNS specific biomarkers that can predict the outcomes following aSAH. Liquid biopsy represents a promising minimally invasive approach for biomarker discovery using biofluids (plasma, CSF). METHODS: CSF was collected from patients (n = 10) during in-hospital stay at multiple time points via the external ventricular drain and EV RNA was sequenced using Oxford Nanopore Technologies. RESULTS: We detected different biotypes in EV RNA with minimal rRNA contamination (protein coding; 58.4%, pseudogene; 23.1%, LncRNA; 10%, rRNA; 1.7%). This is the first study reporting presence of long (&gt;500 bp) RNA transcripts in CSF derived EVs. Approximately, 80% of the sequenced reads were up to 500 bp long and 20% reads 500-10,000 bp long. Principal Component Analysis demonstrated distinct clustering of samples based on location (anterior vs. posterior circulation) and type of aneurysm (saccular, dissecting, bilobed). A set of protein coding genes (S100A9, EEF1A1, SCARNA1, DMTN) were found to be differentially enriched in patients who developed cerebral vasospasm (n = 6). Furthermore, for each patient there was a unique population of biomarkers upregulated in acute (HBB, COX2) vs. chronic (SEPTIN7, PDK4) immune response following aSAH. Preliminary findings reveal potential candidate biomarkers providing insight into the pathogenesis and prognosis. CONCLUSIONS: There is an unmet need for inclusion of diagnostic and predictive biomarkers in clinical management of aSAH to decrease the overall mortality. In this study, we overcame challenges of analyzing low input RNA using a sensitive and optimized sequencing platform. Validation and testing in a larger study population offers new opportunities for biomarker discovery.

Abstract 4379: RING1, a novel E3 ubiquitin ligase for CIP2A, negatively regulates smoking-induced lung tumorigenesis

Abstract Lung cancer is the second incidence rate of all new cancer diagnoses and the leading cause of cancer-related deaths globally. To develop novel diagnostic and therapeutic targets for lung cancer, there are emerging needs for molecular biological research on the occurrence and progression. Among the targets, CIP2A has been studied for promoting various cancer types, but detailed underlying mechanisms are needed to be further investigated. In this study, it was verified that CIP2A is overexpressed in lung cancer tissues, particularly amongst those with a smoking history, compared to adjacent normal tissues. CIP2A knockdown in lung cancer cells efficiently reduced cell proliferation and migration capacity. Through the mass spectrometry analysis on A549 cells overexpressing CIP2A, RING1 was identified as a candidate for E3 ligase of CIP2A. The interaction of the two proteins and ubiquitin chain regulation by RING1 was verified by immunoprecipitation. RING1 knockdown enhanced proliferation and migration of lung cancer cells, and these effects result from the upregulation of CIP2A and its downstream molecules, c-Myc and cyclin B1. To further study a trigger for RING1 expression changes in lung tumorigenesis, cigarette smoke extract (CSE) was applied for the following experiments. CSE treatment depleted RING1 mRNA, including protein expression. Decreased RING1 level led to upregulation of CIP2A and c-MYC. Collectively, these results reveal novel roles of the RING1 and CIP2A in lung cancer progression caused by smoking and propose a potential biomarker candidate for the therapeutic and diagnostic targets. Citation Format: In-ho Jeong, Chang-Whan Peter Lee, Hwan Jung Lim, Seong Jun Park, Ji Young Hyun. RING1, a novel E3 ubiquitin ligase for CIP2A, negatively regulates smoking-induced lung tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4379.

Identification and prognostic analysis of candidate biomarkers for lung metastasis in colorectal cancer.

Colorectal cancer (CRC) is one of the most prevalent types of malignant tumors. It's vital to explore new biomarkers and potential therapeutic targets in CRC lung metastasis through adopting integrated bioinformatics tools. Multiple cohort datasets and databases were integrated to clarify and verify potential key candidate biomarkers and signal transduction pathways in CRC lung metastasis. DAVID, STRING, UALCAN, GEPIA, TIMER, cBioPortal, THE HUMAN PROTEIN ATLAS, GSEA 4.3.2, FUNRICH 3.1.3, and R 4.2.3 were utilized in this study. The enriched biological processes and pathways modulated by the differentially expressed genes (DEGs) were determined with Gene Ontology, Kyoto Encyclopedia of Genes and Genomes. The search tool Retrieval of Interacting Genes and Cytoscape were used to construct a protein-protein interaction network among DEGs. Four hundred fifty-nine colorectal primary cancer and lung metastatic gene expression profiles were screened from 3 gene expression profiles (GSE41258, GSE68468, and GSE41568). Forty-one upregulated genes and 8 downregulated genes were identified from these 3 gene expression profiles and verified by the transcriptional levels of hub genes in other GEO datasets and The Cancer Genome Atlas database. Two pathways (immune responses and chemokine receptors bind chemokines), 13 key DEGs, 6 hub genes (MMP3, SFTPD, ABCA3, CLU, APOE, and SPP1), and 2 biomarkers (APOE, SPP1) with significantly prognostic values were screened. Forty-nine DEGs were identified as potential candidate diagnostic biomarkers for patients with CRC lung metastasis in present study. Enrichment analysis indicated that immune responses and chemokine receptors bind chemokines may play a leading role in lung metastasis of CRC, and further studies are needed to validate these findings.

PLA2G4A and ACHE modulate lipid profiles via glycerophospholipid metabolism in platinum-resistant gastric cancer

BackgroundBioactive lipids involved in the progression of various diseases. Nevertheless, there is still a lack of biomarkers and relative regulatory targets. The lipidomic analysis of the samples from platinum-resistant in gastric cancer patients is expected to help us further improve our understanding of it.MethodsWe employed LC–MS based untargeted lipidomic analysis to search for potential candidate biomarkers for platinum resistance in GC patients. Partial least squares discriminant analysis (PLS-DA) and variable importance in projection (VIP) analysis were used to identify differential lipids. The possible molecular mechanisms and targets were obtained by metabolite set enrichment analysis and potential gene network screened. Finally, verified them by immunohistochemical of a tissue microarray.ResultsThere were 71 differential lipid metabolites identified in GC samples between the chemotherapy-sensitivity group and the chemotherapy resistance group. According to Foldchange (FC) value, VIP value, P values (FC > 2, VIP > 1.5, p < 0.05), a total of 15 potential biomarkers were obtained, including MGDG(43:11)-H, Cer(d18:1/24:0) + HCOO, PI(18:0/18:1)-H, PE(16:1/18:1)-H, PE(36:2) + H, PE(34:2p)-H, Cer(d18:1 + hO/24:0) + HCOO, Cer(d18:1/23:0) + HCOO, PC(34:2e) + H, SM(d34:0) + H, LPC(18:2) + HCOO, PI(18:1/22:5)-H, PG(18:1/18:1)-H, Cer(d18:1/24:0) + H and PC(35:2) + H. Furthermore, we obtained five potential key targets (PLA2G4A, PLA2G3, DGKA, ACHE, and CHKA), and a metabolite-reaction-enzyme-gene interaction network was built to reveal the biological process of how they could disorder the endogenous lipid profile of platinum resistance in GC patients through the glycerophospholipid metabolism pathway. Finally, we further identified PLA2G4A and ACHE as core targets of the process by correlation analysis and tissue microarray immunohistochemical verification.ConclusionPLA2G4A and ACHE regulated endogenous lipid profile in the platinum resistance in GC patients through the glycerophospholipid metabolism pathway. The screening of lipid biomarkers will facilitate earlier precision medicine interventions for chemotherapy-resistant gastric cancer. The development of therapies targeting PLA2G4A and ACHE could enhance platinum chemotherapy effectiveness.

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.

Utilizing Excitatory and Inhibitory Activity Derived from Interictal Intracranial Electroencephalography as Potential Biomarkers for Epileptogenicity.

Epileptogenic zones (EZs), where epileptic seizures cease after resection, are localized by assessing the seizure-onset zone using ictal electroencephalography (EEG). Owing to the difficulty in capturing unpredictable seizures, biomarkers capable of identifying EZs from interictal EEG are anticipated. Recent studies using intracranial EEG have identified several potential candidate biomarkers for epileptogenicity. High-frequency oscillation (HFO) was initially expected to be a robust biomarker of abnormal excitatory activity in the ictogenic region. However, HFO-guided resection failed to improve seizure prognosis. Meanwhile, the regularity of low-gamma oscillations (30-80 Hz) indicates inhibitory interneurons' hypersynchronization, which could be used to localize the EZ. Besides resting-state EEG assessments, evoked potentials elicited by single-pulse electrical stimulation, such as corticocortical evoked potentials (CCEP), became valuable tools for assessing epileptogenic regions. CCEP responses recorded in the cortex remote from the stimulation site indicate functional connectivity, revealing increased internal connectivity within the ictogenic region and elevated inhibitory input from the non-involved regions to the ictogenic region. Conversely, large responses close to the stimulation site reflect local excitability, manifesting as an increased N1 amplitude and overriding HFO. Further research is required to establish whether these novel electrophysiological methods, either individually or in combination, can function as robust biomarkers of epileptogenicity and hold promise for improving seizure prognosis.

Biological factors driving colorectal cancer metastasis.

Approximately 20% of colorectal cancer (CRC) patients present with metastasis at diagnosis. Among Stage I-III CRC patients who undergo surgical resection, 18% typically suffer from distal metastasis within the first three years following initial treatment. The median survival duration after the diagnosis of metastatic CRC (mCRC) is only 9 mo. mCRC is traditionally considered to be an advanced stage malignancy or is thought to be caused by incomplete resection of tumor tissue, allowing cancer cells to spread from primary to distant organs; however, increasing evidence suggests that the mCRC process can begin early in tumor development. CRC patients present with high heterogeneity and diverse cancer phenotypes that are classified on the basis of molecular and morphological alterations. Different genomic and nongenomic events can induce subclone diversity, which leads to cancer and metastasis. Throughout the course of mCRC, metastatic cascades are associated with invasive cancer cell migration through the circulatory system, extravasation, distal seeding, dormancy, and reactivation, with each step requiring specific molecular functions. However, cancer cells presenting neoantigens can be recognized and eliminated by the immune system. In this review, we explain the biological factors that drive CRC metastasis, namely, genomic instability, epigenetic instability, the metastatic cascade, the cancer-immunity cycle, and external lifestyle factors. Despite remarkable progress in CRC research, the role of molecular classification in therapeutic intervention remains unclear. This review shows the driving factors of mCRC which may help in identifying potential candidate biomarkers that can improve the diagnosis and early detection of mCRC cases.

Introducing Pain-Related Molecular Pathways in Painful Diabetic Neuropathy Via Protein Interaction Networks

Background: Painful diabetic neuropathy (PDN) is one of the most drastic complications of diabetes. Patients with PDN always reveal spontaneous and stimulus‑evoked pain. However, the pathogenesis mechanisms of PDN are not entirely distinct. Objectives: In the present study protein-protein interaction (PPI) network for PDN was constructed and analyzed to identify key proteins as potential biomarker candidates. Methods: The transcriptomic (genes) and proteomic (proteins) data in articles that focused on PDN with differential expressions were collected. Protein networks were constructed and analyzed using STRING and Cytoscape software, respectively. Further PPI network analysis, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis were performed using MCODE and DAVID tools. Results: A total of 147 differentially regulated proteins/genes were identified in painful diabetic neuropathy, including 91 up-regulated and 56 down-regulated proteins/genes. A network analysis of genes/proteins related to PDN identified COX4I1, NDUFS8, UQCRC1, COX7C, and some other NADH dehydrogenases, including NDUFB7, NDUFS7, NDUFS3, NDUFB5, NDUFA2, and NDUFB4 as hub-bottleneck proteins. With functional enrichment analysis of network clustering, COX7C, HP, RPS12, KCNIP2, and CoL4A1 were established as distinct seed proteins in the obtained modules, which could lead to the discovery of biomarker candidates. Conclusions: These results could provide new insights into pathology and molecular mechanisms, as well as the identification of pathways and proteins/genes involved in causing PDN in diabetic patients. COX7C, HP, RPS12, KCNIP2, and CoL4A1 are the top 5 seed nodes (hub proteins) and can serve as potential biomarker candidates and targets for PDN management. However, further investigations are needed to evaluate these proteins in detail.

Exploration of Diagnostic Deubiquitinating Enzymes in Endometriosis and Its Immune Infiltration.

The mechanism involved in the pathogenesis of endometriosis is poorly understood. The purpose of this study is to identify key deubiquitinating enzymes (DUBs) for endometriosis diagnosis and elucidate the possible mechanism, offering novel insights for noninvasive early diagnosis and treatment. Four gene expression datasets were employed from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between endometriosis and normal controls. GO and KEGG pathways were performed for enrichment analysis. Calibration curves, ROC, DCA, and clinical impact curves verified the clinical usefulness of the nomogram model. In addition, the ssGSEA method was conducted to estimate 23 types of immune cells. A specific DUB gene signature was constructed with Lasso regression, univariate logistic regression, and SVM analysis. RT-qPCR validated the expression of biomarkers. A total of 85 endometriosis-related DUBs were identified in the eutopic endometrium. Among them, 20 DUBs were found to be correlated with the severity of endometriosis. A diagnostic risk model based on five DUB-related genes (USP21, USP48, ZRANB1, COPS5, and EIF3F) was developed using lasso-cox regression analysis. The nomogram model exhibited a strong predictive ability to diagnose endometriosis. KEGG analysis revealed that ubiquitin-mediated proteolysis was activated in patients suffering from severe symptoms. Analysis of immune cell infiltration revealed a positive correlation between USP21 and multiple immune cells in the eutopic endometrium. However, EIF3F showed an opposite relationship. Dysregulation of DUBs was related to the immune microenvironment in endometriosis. Results from RT-qPCR confirmed the expression of DEGs in clinical samples. In summary, the diagnostic model for endometriosis constructed using five differentially expressed DUB genes demonstrates strong diagnostic capability, suggesting that these genes could serve as potential candidate biomarkers and therapeutic targets.

MicroRNAs as potential diagnostic biomarkers for bipolar disorder

Abstract Abnormal expression of microRNAs is connected to brain development and disease and could provide novel biomarkers for the diagnosis and prognosis of bipolar disorder. We performed a PubMed search for microRNA biomarkers in bipolar disorder and found 18 original research articles on studies performed with human patients and published from January 2011 to June 2023. These studies included microRNA profiling in blood-and brain-based materials. From the studies that had validated the preliminary findings, potential candidate biomarkers for bipolar disorder in adults could be miR-140-3p, -30d- 5p, -330-5p, -378a-5p, -21-3p, -330-3p, -345-5p in whole blood, miR-19b-3p, -1180-3p, -125a-5p, let-7e-5p in blood plasma, and miR-7-5p, -23b-5p, -142-3p, -221-5p, -370-3p in the blood serum. Two of the studies had investigated the changes in microRNA expression of patients with bipolar disorder receiving treatment. One showed a significant increase in plasma miR-134 compared to baseline after 4 weeks of treatment which included typical antipsychotics, atypical antipsychotics, and benzodiazepines. The other study had assessed the effects of prescribed medications which included neurotransmitter receptor-site binders (drug class B) and sedatives, hypnotics, anticonvulsants, and analgesics (drug class C) on microRNA results. The combined effects of the two drug classes increased the significance of the results for miR-219 and -29c with miR-30e-3p and -526b* acquiring significance. MicroRNAs were tested to see if they could serve as biomarkers of bipolar disorder at different clinical states of mania, depression, and euthymia. One study showed that upregulation in whole blood of miR-9-5p, -29a-3p, -106a-5p, -106b-5p, -107, -125a-3p, -125b-5p and of miR-107, -125a-3p occurred in manic and euthymic patients compared to controls, respectively, and that upregulation of miR-106a-5p, -107 was found for manic compared to euthymic patients. In two other studies using blood plasma, downregulation of miR-134 was observed in manic patients compared to controls, and dysregulation of miR-134, -152, -607, -633, -652. -155 occurred in euthymic patients compared to controls. Finally, microRNAs such as miR-34a, -34b, -34c, -137 and -140- 3p, -21-3p, -30d-5p, -330-5p, -378a-5p, -134, -19b-3p were shown to have diagnostic potential in distinguishing bipolar disorder patients from schizophrenia or major depressive disorder patients, respectively. Further studies are warranted with adolescents and young adults having bipolar disorder and consideration should be given to using animal models of the disorder to investigate the effects of suppressing or overexpressing specific microRNAs.