Diagnostic Targets Research Articles

Enhancing the revelation of key genes and interaction networks in non-small cell lung cancer with major depressive disorder: A bioinformatics analysis.

Lung cancer is ranked as the second most prevalent form of cancer worldwide. Nonsmall cell lung cancer (NSCLC) represents the predominant histological subtype. Research suggests that one-third of lung cancer patients also experiencing depression. Antidepressants play an indispensable role in the management of NSCLC. Despite significant advancements in treatment, lung cancer patients still face a high mortality rate. Major depressive disorder (MDD) and related antidepressants involved in treatment efficacy and prognosis of NSCLC. However, there has been a lack of screening and analysis regarding genes and networks associated with both NSCLC and MDD. To investigate the correlation between MDD and NSCLC, our discovery and validation analysis included four datasets from the Gene Expression Omnibus database from NSCLC or MDD. Differential gene expression (DEGs) analysis, GO and KEGG Pathway, and protein-protein interaction network analyzes to identify hub genes, networks, and associated observations link between MDD and NSCLC. The analysis of two datasets yielded a total of 84 downregulated and 52 upregulated DEGs. Pathway enrichment analyzes indicated that co-upregulated genes were enriched in the regulation of positive regulation of cellular development, collagen-containing extracellular matrix (ECM), cytokine binding, and axon guidance. We identified 20 key genes, which were further analyzed using the MCODE plugin to identify two core subnetworks. The integration of functionally similar genes provided valuable insights into the potential involvement of these hub genes in diverse biological processes including angiogenesis humoral immune response regulation inflammatory response organization ECM network. We have identified a total of 136 DEGs that participate in multiple biological signaling pathways. A total of 20 hub genes have demonstrated robust associations, potentially indicating novel diagnostic and therapeutic targets for both diseases.

EPS3.06 Diagnostic target product profiles for managing infections and exacerbations in cystic fibrosis

EPS3.06 Diagnostic target product profiles for managing infections and exacerbations in cystic fibrosis

Hsa-miR-342-3p and hsa-miR-360 may be the key molecules that promote periodontitis in type 2 diabetes mellitus

BackgroundPeriodontitis (PD) has been acknowledged as a complication associated with type 2 diabetes mellitus (T2DM). However, the precise mechanism through which T2DM fosters the development of PD remains elusive. Our objective is to elucidate the connection between these two conditions by conducting bioinformatics analysis. MethodsIn this study, we analyzed miRNA datasets pertaining to T2DM and PD sourced from GEO. Through differential expression analysis, we identified common differentially expressed miRNAs (DE-miRNAs) and subsequently analyzed the functional enrichment of these common DE-miRNAs. We further leveraged the PD transcriptome database to select DE-miRNA-targeted mRNAs and examined their association with immune infiltration. Finally, machine learning was used to further screen hub DE-miRNA-targeted mRNAs and validate our data in external datasets. ResultsTwo common DE-miRNAs, namely hsa-miR-342-3p and hsa-miR-360, were identified from the miRNA datasets of PD and T2DM. Functional enrichment analysis indicated that these two common DE-miRNAs predominantly participate in Ras, PI3K-Akt, p53, and MAPK signaling pathways. Integration of the PD transcriptome dataset revealed a total of 21 DE-miRNA-targeted mRNAs in PD, with strong correlations observed with plasma cells and dendritic cells. Finally, three hub DE-miRNA-targeted mRNAs (hsa-miR-342-3p-/hsa-miR-360-RASAL2, hsa-miR-360-ENTPD1/PLXDC2) were identified. ENTPD1 exhibited a robust positive correlation with plasma cells and a negative correlation with resting dendritic cells. ConclusionsTherefore, hsa-miR-342-3p-/hsa-miR-360-RASAL2, as well as hsa-miR-360-ENTPD1/PLXDC2, may serve as diagnostic and therapeutic targets for T2DM-associated PD.

Systematic proteomics analysis revealed different expression of laminin interaction proteins in breast cancer: lower in luminal subtype and higher in claudin-low subtype.

Breast cancer is a major public health concern. Proteomics enables identification of proteins with aberrant properties. Here, we identified proteins with abnormal expression levels in breast cancer tissues and systematically analyzed and validated the data to locate potential diagnostic and therapeutic targets. Protein expression level in breast cancer tissues and para-carcinoma tissues were detected by Isobaric Tags for Relative and Absolute Quantification (iTRAQ) technology and further screened through Gene Expression Profiling Interactive Analysis (GEPIA) database. Cellular components, protein domain and Reactome pathway analysis were performed to screen functional targets. Abnormal expression levels of functional targets were validated by Oncomine database, quantitative real time polymerase chain reaction (qRT-PCR) and proteomics detection. Protein correlation analysis was performed to explain the abnormal expression levels of potential targets in breast cancer. Overall, 207 and 207 proteins were up- and down-regulated, respectively, in breast cancer tissues, and approximately 50% were also detected in the GEPIA database. The overlapping proteins were mainly extracellular proteins containing epidermal growth factor-like domain in leukocyte adhesion molecule (EGF-Lam) domain and enriched in laminin interaction pathway. Moreover, the downregulated laminin interaction proteins could be functional targets, which were also validated through Oncomine-Richardson and Oncomine-Curtis database. However, the lower expression level of laminin interaction proteins only fit for luminal breast cancer cells with no or low metastasis ability because the proteins achieved higher expression level in more invasive claudin-low breast cancer cells. In addition, when compared with corresponding in situ carcinoma tissues, above-mentioned proteins also showed higher expression levels in invasive carcinoma tissues. Finally, we have revealed the negative correlation between the laminin interaction proteins and the claudins. The laminin interaction protein, especially for laminins with β1 and γ1 subunits and their integrin receptors with α1 and α6 subunits, showed lower expression levels in luminal breast cancer with no or lower metastatic ability, but showed higher expression levels in claudin-low breast cancer with higher metastatic ability; and their higher expression could be related to the low claudin expression.

Gene expression and immune infiltration analysis comparing lesioned and preserved subchondral bone in osteoarthritis.

Osteoarthritis (OA) is a degenerative disease requiring additional research. This study compared gene expression and immune infiltration between lesioned and preserved subchondral bone. The results were validated using multiple tissue datasets and experiments. Differentially expressed genes (DEGs) between the lesioned and preserved tibial plateaus of OA patients were identified in the GSE51588 dataset. Moreover, functional annotation and protein-protein interaction (PPI) network analyses were performed on the lesioned and preserved sides to explore potential therapeutic targets in OA subchondral bones. In addition, multiple tissues were used to screen coexpressed genes, and the expression levels of identified candidate DEGs in OA were measured by quantitative real-time polymerase chain reaction. Finally, an immune infiltration analysis was conducted. A total of 1,010 DEGs were identified, 423 upregulated and 587 downregulated. The biological process (BP) terms enriched in the upregulated genes included "skeletal system development", "sister chromatid cohesion", and "ossification". Pathways were enriched in "Wnt signaling pathway" and "proteoglycans in cancer". The BP terms enriched in the downregulated genes included "inflammatory response", "xenobiotic metabolic process", and "positive regulation of inflammatory response". The enriched pathways included "neuroactive ligand-receptor interaction" and "AMP-activated protein kinase signaling". JUN, tumor necrosis factor α, and interleukin-1β were the hub genes in the PPI network. Collagen XI A1 and leucine-rich repeat-containing 15 were screened from multiple datasets and experimentally validated. Immune infiltration analyses showed fewer infiltrating adipocytes and endothelial cells in the lesioned versus preserved samples. Our findings provide valuable information for future studies on the pathogenic mechanism of OA and potential therapeutic and diagnostic targets.

Exploring the molecular mechanisms of ferroptosis-related genes in periodontitis: a multi-dataset analysis

PurposeThis study aims to elucidate the biological functions of ferroptosis-related genes in periodontitis, along with their correlation to tumor microenvironment (TME) features such as immune infiltration. It aims to provide potential diagnostic markers of ferroptosis for clinical management of periodontitis.MethodsUtilizing the periodontitis-related microarray dataset GSE16134 from the Gene Expression Omnibus (GEO) and a set of 528 ferroptosis-related genes identified in prior studies, this research unveils differentially expressed ferroptosis-related genes in periodontitis. Subsequently, a protein–protein interaction network was constructed. Subtyping of periodontitis was explored, followed by validation through immune cell infiltration and gene set enrichment analyses. Two algorithms, randomForest and SVM(Support Vector Machine), were employed to reveal potential ferroptosis diagnostic markers for periodontitis. The diagnostic efficacy, immune correlation, and potential transcriptional regulatory networks of these markers were further assessed. Finally, potential targeted drugs for differentially expressed ferroptosis markers in periodontitis were predicted.ResultsA total of 36 ferroptosis-related genes (30 upregulated, 6 downregulated) were identified from 829 differentially expressed genes between 9 periodontitis samples and the control group. Subsequent machine learning algorithm screening highlighted 4 key genes: SLC1A5(Solute Carrier Family 1 Member 5), SLC2A14(Solute Carrier Family 1 Member 14), LURAP1L(Leucine Rich Adaptor Protein 1 Like), and HERPUD1(Homocysteine Inducible ER Protein With Ubiquitin Like Domain 1). Exploration of these 4 key genes, supported by time-correlated ROC analysis, demonstrated reliability, while immune infiltration results indicated a strong correlation between key genes and immune factors. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted for the four key genes, revealing enrichment in GO/KEGG pathways that have a significant impact on periodontitis. Finally, the study predicted potential transcriptional regulatory networks and targeted drugs associated with these key genes in periodontitis.ConclusionsThe ferroptosis-related genes identified in this study, including SLC1A5, SLC2A14, LURAP1L, and HERPUD1, may serve as novel diagnostic and therapeutic targets for periodontitis. They are likely involved in the occurrence and development of periodontitis through mechanisms such as immune infiltration, cellular metabolism, and inflammatory chemotaxis, potentially linking the ferroptosis pathway to the progression of periodontitis. Targeted drugs such as flurofamide, L-733060, memantine, tetrabenazine, and WAY-213613 hold promise for potential therapeutic interventions in periodontitis associated with these ferroptosis-related genes.

The Future of TCR-like Antibodies in Diagnosis and Potential Application Targets.

The human leukocyte antigen (HLA, also known as the major histocompatibility complex or MHC) system, is responsible for immune monitoring of the intracellular proteome of all nucleated cells. The presentation of antigen peptides separates malignant or infected cells from their healthy counterparts and forms aberrant cells tagged as the foundation for identification. Therefore, peptide-MHC molecules can give potential diagnostic targets for cancer or infection. TCR-like antibodies recognize specific peptides that bind to MHC molecules, allowing them to target Such inaccessible cytoplasmic or nuclear tumors or virus-associated antigens. It binds to MHC, presenting peptides found on the surface of target cells. These antibodies have shown promising clinical applications in diagnosing and imaging cancer and infected cells. This review presents the current situation of TCR-like antibodies and its prospects for application in the field of intracellular antigen diagnostics. It also lists the potential application targets of TCR, like antibodies in various disease diagnoses, providing valuable information for developing diagnostic reagents and selecting targets in the future.

Arterial Adventitial Vasa Vasorum Hyperplasia involved in Atherosclerotic Plaque Formation in a Rabbit Model

ObjectiveIt was previously believed that atherosclerotic (AS) plaque starts to develop from the intima and that intraplaque vasa vasorum (VV) hyperplasia promotes adventitial VV (AVV) hyperplasia. However, recent studies have shown that arterial AVV hyperplasia precedes early intimal thickening, suggesting its possible role as an initiating factor of AS. To provide further insight into this process, in this study, we examine the evolution of AAV and VV development in a preclinical model of early AS with longitudinal ultrasound imaging. MethodsModels of early AS were established. Duplex ultrasound scanning and contrast-enhanced ultrasound were performed for diagnosis. Pearson correlation tests were used to analyze the relationships between AVV hyperplasia and VV hyperplasia, or between AVV hyperplasia and intima-media thickness (IMT). ResultsDuring 0–12 wk of high-fat feeding, AVV gradually increased and intima-media thickened gradually in the observation area; in the 2nd wk of high-fat feeding, the observation area showed obvious AVV proliferation; at the 4th wk, the intima-media membrane became thicker; at the 12th wk, early plaque formation and intraplaque VV proliferation were observed. There was a strong positive correlation between AVV proliferation and IMT thickening and a strong negative correlation between AVV proliferation and the change rate of vessel diameter. ConclusionThis study demonstrated that AVV proliferation in the arteries occurred earlier than IMT thickening and was positively correlated with IMT. At present, the indicators of ultrasonic diagnosis of AS, such as IMT, Intraplaque VV, Echo property, all appear in the advanced stage of AS. The AVV may be an innovative diagnostic target for the early stage of AS plaque.

Hepatitis B Virus X Protein Represses Expression of Tumor Suppressor PTPN18 in Hepatocellular Carcinoma.

HBV-associated hepatocellular carcinoma (HCC) represents the prevalent form of HCC, with HBx protein being a crucial oncoprotein. Numerous members of the protein tyrosine phosphatase nonreceptor (PTPN) family have been confirmed to be significantly associated with the occurrence and progression of malignant tumors. Our group previously identified the involvement of PTPN13 in HCC. However, the roles of other PTPNs in HCC require further investigation. In this study, we found that PTPN18 expression was significantly downregulated within HCC tissues compared with adjacent nontumor and reference liver tissues. Functionally, PTPN18 exerted inhibitory effects on the proliferation, migration, invasion, and sphere-forming capability of HCC cells while concurrently promoting apoptotic processes. Through phospho-protein microarray screening followed by subsequent validation experiments, we identified that PTPN18 could activate the p53 signaling pathway and suppress the AKT/FOXO1 signaling cascade in HCC cells. Moreover, the HBx protein mediated the repression of PTPN18 expression by upregulating miR-128-3p. Collectively, our study unveiled the role of PTPN18 as a tumor suppressor in HBV-related HCC. Implications: Our findings revealed that PTPN18 might be a potential diagnostic and therapeutic target for HBV-related HCC.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness.

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Region-Specific CD16+ Neutrophils Promote Colorectal Cancer Progression by Inhibiting Natural Killer Cells.

The colon is the largest compartment of the immune system, with innate immune cells exposed to antigens in the environment. However, the mechanisms by which the innate immune system is instigated are poorly defined in colorectal cancer (CRC). Here, a population of CD16+ neutrophils that specifically accumulate in CRC tumor tissues by imaging mass cytometry (IMC), immune fluorescence, and flow cytometry, which demonstrated pro-tumor activity by disturbing natural killer (NK) cells are identified. It is found that these CD16+ neutrophils possess abnormal cholesterol accumulation due to activation of the CD16/TAK1/NF-κB axis, which upregulates scavenger receptors for cholesterol intake including CD36 and LRP1. Consequently, these region-specific CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, which interrupts NK lipid raft formation and blocks their antitumor signaling but also release neutrophil extracellular traps (NETs) to induce the death of NK cells. Furthermore, CD16-knockout reverses the pro-tumor activity of neutrophils and restored NK cell cytotoxicity. Collectively, the findings suggest that CRC region-specific CD16+ neutrophils can be a diagnostic marker and potential therapeutic target for CRC.

Identification of plasma protein markers of allergic disease risk: a mendelian randomization approach to proteomic analysis

BackgroundWhile numerous allergy-related biomarkers and targeted treatment strategies have been developed and employed, there are still signifcant limitations and challenges in the early diagnosis and targeted treatment for allegic diseases. Our study aims to identify circulating proteins causally associated with allergic disease-related traits through Mendelian randomization (MR)-based analytical framework.MethodsLarge-scale cis-MR was employed to estimate the effects of thousands of plasma proteins on five main allergic diseases. Additional analyses including MR Steiger analyzing and Bayesian colocalisation, were performed to test the robustness of the associations; These findings were further validated utilizing meta-analytical methods in the replication analysis. Both proteome- and transcriptome-wide association studies approach was applied, and then, a protein-protein interaction was conducted to examine the interplay between the identified proteins and the targets of existing medications.ResultsEleven plasma proteins were identified with links to atopic asthma (AA), atopic dermatitis (AD), and allergic rhinitis (AR). Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. MR analysis and extra validation revealed STAT6 and TNFRSF6B to be Tier 1 and IL1RL2 and IL6R to be Tier 2 proteins with the potential for AA treatment. Two Tier 1 proteins, CRAT and TNFRSF6B, and five Tier 2 proteins, ERBB3, IL6R, MMP12, ICAM1, and IL1RL2, were linked to AD, and three Tier 2 proteins, MANF, STAT6, and TNFSF8, to AR.ConclusionEleven Tier 1 and 2 protein targets that are promising drug target candidates were identified for AA, AD, and AR, which influence the development of allergic diseases and expose new diagnostic and therapeutic targets.

Proteomics coupled transcriptomics reveals Slc34a1 and Slc34a3 downregulation as potential features of nephrotoxin-induced acute kidney injury

Acute kidney injury (AKI) stands as a prevalent and economically burdensome condition worldwide, yet its complex molecular mechanisms remain incompletely understood. To address this gap, our study employs a multifaceted approach, combining mass spectrometry and RNA sequencing technologies, to elucidate the intricate molecular landscape underlying nephrotoxin-induced AKI in mice by cisplatin- and LPS-induced. By examining the protein and RNA expression profiles, we aimed to uncover novel insights into the pathogenesis of AKI and identify potential diagnostic and therapeutic targets. Our results demonstrate significant down-regulation of Slc34a1 and Slc34a3, shedding light on their crucial roles in AKI pathology and highlighting their promise as actionable targets for diagnosis and treatment. This comprehensive analysis not only enhances our understanding of AKI pathophysiology but also offers valuable avenues for the development of targeted interventions to mitigate its clinical impact. SignificanceNephrotoxicity acute kidney injury (AKI) is a common clinical condition whose pathogenesis is the process by which some drugs, chemicals or other factors cause damage to the kidneys, resulting in impaired kidney function. Although it has been proved that different nephrotoxic substances can affect the kidney through different pathways, whether they have a commonality has not been registered. Here, we combined transcriptomics and proteomics to study the molecular mechanism of LPS and cisplatin-induced nephrotoxic acute kidney injury finding that the down-regulation of Slc34a1 and Slc34a3 may be a critical link in nephrotoxic acute kidney injury, which can be used as a marker for its early diagnosis.

Screening of drug targets for tuberculosis on the basis of transcription factor regulatory network and mRNA sequencing technology.

Tuberculosis is a worldwide epidemic disease, posing a serious threat to human health. To find effective drug action targets for Mycobacterium tuberculosis, differentially expressed genes in tuberculosis patients and healthy people were screened by mRNA sequencing in this study. A total of 556 differentially expressed genes in tuberculosis patients and healthy people were screened out by mRNA sequencing technology. 26 transcription factors and 66 corresponding target genes were screened out in the AnimalTFDB 3.0 database, and a transcription factor regulatory network was constructed. Three key transcription factors (TP53, KLF5 and GATA2) and one key gene (AKT1) were screened as new potential drug targets and diagnostic targets for tuberculosis by MCODE cluster analysis, and the key genes and key transcription factors were verified by RT-PCR. Finally, we constructed the and a key factor and KEGG signaling pathway regulatory network to clarify the possible molecular pathogenesis of tuberculosis. This study suggested M. tuberculosis may activate the AKT1 gene expression by regulating transcription factors TP53, KLF5, and GATA2, thus activating the B cell receptor signaling pathway to induce the infection and invasion of M. tuberculosis. AKT1, TP53, KLF5, and GATA2 can be used as new potential drug targets for tuberculosis.

Comprehensive analysis of KLF family reveals KLF6 as a promising prognostic and immune biomarker in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive.MethodsWe systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer.ResultsThe KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis.ConclusionThis study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC.

Identification of NR3C2 as a functional diagnostic and prognostic biomarker and potential therapeutic target in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required. The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms. NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC. NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.

Identification of ion channel-related genes as diagnostic markers and potential therapeutic targets for osteoarthritis through bioinformatics and machine learning-based approaches

Background Osteoarthritis (OA) is a debilitating joint disorder characterized by the progressive degeneration of articular cartilage. Although the role of ion channels in OA pathogenesis is increasingly recognized, diagnostic markers and targeted therapies remain limited. Methods In this study, we analyzed the GSE48556 dataset to identify differentially expressed ion channel-related genes (DEGs) in OA and normal controls. We employed machine learning algorithms, least absolute shrinkage and selection operator(LASSO), and support vector machine recursive feature elimination(SVM-RFE) to select potential diagnostic markers. Then the gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential diagnostic markers’ involvement in biological pathways. Finally, weighted gene co-expression network analysis (WGCNA) was used to identify key genes associated with OA. Results We identified a total of 47 DEGs, with the majority involved in transient receptor potential (TRP) pathways. Seven genes (CHRNA4, GABRE, HTR3B, KCNG2, KCNJ2, LRRC8C, and TRPM5) were identified as the best characteristic genes for distinguishing OA from healthy samples. We performed clustering analysis and identified two distinct subtypes of OA, C1, and C2, with differential gene expression and immune cell infiltration profiles. Then we identified three key genes (PPP1R3D, ZNF101, and LOC651309) associated with OA. We constructed a prediction model using these genes and validated it using the GSE46750 dataset, demonstrating reasonable accuracy and specificity. Conclusions Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer potential diagnostic markers and therapeutic targets for the treatment of OA.

Exploring Ferroptosis-Associated Gene Signatures as Diagnostic and Therapeutic Targets for Sepsis-Induced Cardiomyopathy.

Sepsis-induced cardiomyopathy (SICM) is a severe complication of sepsis associated with high mortality rates. Despite its significance, the molecular mechanisms underlying SICM remain poorly understood, particularly the role of ferroptosis - a form of iron-dependent programmed cell death. This study analyzed the GSE79962 dataset from the Gene Expression Omnibus, containing cardiac gene expression profiles from SICM patients and controls. A list of ferroptosis-related genes (FRGs) was retrieved from the FerrDb. We used the limmapackage in R for differential expression analysis, setting an adjusted P-value cutoff of <0.05 and a log2-fold change threshold of ±1 to identify differentially expressed ferroptosis-related genes (DE-FRGs). We applied machine learning algorithmsfor biomarker identification, including least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine with recursive feature elimination (SVM-RFE), implemented via the glmnetand e1071packages in R, respectively. Gene set enrichment analysis (GSEA) was conducted using the GSEApackage to investigate the biological pathways related to key DE-FRGs. After differential expression analysis, we identified 145 DE-FRGs. Functional enrichment analyses underscored the involvement of these genes in critical biological processes and pathways, such as lipid metabolism and insulin resistance. Machine learning approaches pinpointed five key DE-FRGs (NCOA4, GABARAPL1, GJA1, CISD1, CP), with strong predictive potential for SICM. Further analyses, including the construction of a ceRNA network, revealed intricate post-transcriptional regulatory mechanisms that may influence the expression of these key genes. Our findings highlight the central role of ferroptosis in SICM and identify potential biomarkers and therapeutic targets that could help refine diagnostic and treatment strategies. This study advances our understanding of the molecular underpinnings of SICM and sets the stage for future research aimed at mitigating this severe sepsis complication.

Dysregulation of lncRNA MALAT1 Contributes to Lung Cancer in African Americans by Modulating the Tumor Immune Microenvironment.

African American (AA) populations present with notably higher incidence and mortality rates from lung cancer in comparison to other racial groups. Here, we elucidated the contribution of long non-coding RNAs (lncRNAs) in the racial disparities and their potential clinical applications in both diagnosis and therapeutic strategies. AA patients had elevated plasma levels of MALAT1 and PVT1 compared with cancer-free smokers. Incorporating these lncRNAs as plasma biomarkers, along with smoking history, achieved 81% accuracy in diagnosis of lung cancer in AA patients. We observed a rise in MALAT1 expression, correlating with increased levels of monocyte chemoattractant protein-1 (MCP-1) and CD68, CD163, CD206, indicative of tumor-associated macrophages in lung tumors of AA patients. Forced MALAT1 expression led to enhanced growth and invasiveness of lung cancer cells, both in vitro and in vivo, accompanied by elevated levels of MCP-1, CD68, CD163, CD206, and KI67. Mechanistically, MALAT1 acted as a competing endogenous RNA to directly interact with miR-206, subsequently affecting MCP-1 expression and macrophage activity, and enhanced the tumorigenesis. Targeting MALAT1 significantly reduced tumor sizes in animal models. Therefore, dysregulated MALAT1 contributes to lung cancer disparities in AAs by modulating the tumor immune microenvironment through its interaction with miR-206, thereby presenting novel diagnostic and therapeutic targets.

Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer.

HER2-positive breast cancer (BC) accounts for 20-30% of all BC subtypes and is linked to poor prognosis. Trastuzumab (Tz), a humanized anti-HER2 monoclonal antibody, is a first-line treatment for HER2-positive breast cancer which faces resistance challenges. This study aimed to identify the biomarkers driving trastuzumab resistance. Differential expression analysis of genes and proteins between trastuzumab-sensitive (TS) and trastuzumab-resistant (TR) cells was conducted using RNA-seq and iTRAQ. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to study their functions. The prognostic significance and protein levels of ARFIP2 and MSN were evaluated using online tools and immunohistochemistry. Sensitivity of MSN and ARFIP2 to other therapies was assessed using public pharmacogenomics databases and the R language. Five genes were up-regulated, and nine genes were down-regulated in TR cells at both transcriptional and protein levels. Low ARFIP2 and high MSN expression linked to poor BC prognosis. MSN increased and ARFIP2 decreased in TR patients, correlating with shorter OS. MSN negatively impacted fulvestrant and immunotherapy sensitivity, while ARFIP2 had a positive impact. Our findings suggest that MSN and ARFIP2 could serve as promising biomarkers for predicting response to Tz, offering valuable insights for future research in the identification of diagnostic and therapeutic targets for BC patients with Tz resistance.