Potential Biomarkers Research Articles

NMI, POLR3G and APIP are the key molecules connecting glaucoma with high intraocular pressure: a clue for early diagnostic biomarker candidates

AIM: To understand the molecular connectivity between the intraocular pressure (IOP) and glaucoma which will provide possible clues for biomarker candidates. METHODS: The current study uncovers the important genes connecting IOP with the core functional modules of glaucoma. An integrated analysis was performed using glaucoma and IOP microarray datasets to screen for differentially expressed genes (DEGs) in both conditions. To the selected DEGs, the protein interaction network was constructed and dissected to determine the core functional clusters of glaucoma. For the clusters, the connectivity of IOP DEGs was determined. Further, enrichment analyses were performed to assess the functional annotation and potential pathways of the crucial clusters. RESULTS: The gene expression analysis of glaucoma and IOP with normal control showed that 408 DEGs (277 glaucoma and 131 IOP genes) were discovered from two GEO datasets. The 290 DEGs of glaucoma were extended to form a network containing 1495 proteins with 9462 edges. Using ClusterONE, the network was dissected to have 12 clusters. Among them, three clusters were linked with three IOP DEGs [N-Myc and STAT Interactor (NMI), POLR3G (RNA Polymerase III Subunit G), and APAF1-interacting protein (APIP)]. In the clusters, ontology analysis revealed that RNA processing and transport, p53 class mediators resulting in cell cycle arrest, cellular response to cytokine stimulus, regulation of phosphorylation, regulation of type I interferon production, DNA deamination, and cellular response to hypoxia were significantly enriched to be implicated in the development of glaucoma. Finally, NMI, POLR3G, and APIP may have roles that were noticed altered in glaucoma and IOP conditions. CONCLUSION: Our findings could help to discover new potential biomarkers, elucidate the underlying pathophysiology, and identify new therapeutic targets for glaucoma.

BCL3, GBP1, IFI16, and CCR1 as potential brain-derived biomarkers for parietal grey matter lesions in multiple sclerosis

BCL3, GBP1, IFI16, and CCR1 as potential brain-derived biomarkers for parietal grey matter lesions in multiple sclerosis

Cerebrospinal fluid metabolites as potential biomarkers for epilepsy: Insights from genome‐wide association studies

AbstractObjectivesWhile metabolic imbalances have been observed in individuals with epilepsy, the direct involvement of specific metabolites in the development of the condition remains underexplored. A comprehensive analysis of the causality between cerebrospinal fluid metabolites (CSF) and epilepsy is pivotal in discovering innovative therapeutic interventions and prophylactic approaches.MethodsSummary data from genome‐wide association studies (GWAS) of CSF metabolites and epilepsy subtypes were obtained separately. A total of 338 CSF metabolites were investigated as exposures, and 11 epilepsy phenotypes were examined as the outcomes. A two sample Mendelian randomization (MR) approach was utilized to explore the causal influence of these metabolites on epilepsy. Causality was primarily estimated through inverse variance weighted (IVW) analysis, complemented by a range of sensitivity analyses to ensure result stability. Additionally, reverse MR analysis was performed to explore the possibility of bidirectional causality.ResultsThe IVW method, reinforced by sensitivity analyses, pinpointed 17 CSF metabolites with causal implications for six epilepsy phenotypes. After False Discovery Rate (FDR) multiple testing correction, two metabolites (Methylmalonate and Gamma‐glutamyl‐alpha‐lysine) were found to have robust causal links to epilepsy (p < 0.05 and FDR<0.05). The other 15 metabolites exhibited suggestive evidence of a causal association (p < 0.05 and FDR>0.05).SignificanceThis study highlights CSF metabolites that could serve as valuable biomarkers and may be critical in developing targeted treatments and preventing epilepsy.Plain Language SummaryThis study explores how certain chemicals in the brain fluid might influence the development of epilepsy, aiming to find new ways to treat or prevent it. Researchers looked at the relationship between 338 cerebrospinal fluid metabolites and 11 types of epilepsy using genetic data. They found that 17 of these chemicals could potentially cause six types of epilepsy. Two of these chemicals were strongly linked to epilepsy, suggesting they could be important for creating specific treatments or prevention strategies.

Cutaneous T cell lymphoma atlas reveals malignant TH2 cells supported by a B cell-rich tumor microenvironment

AbstractCutaneous T cell lymphoma (CTCL) is a potentially fatal clonal malignancy of T cells primarily affecting the skin. The most common form of CTCL, mycosis fungoides, can be difficult to diagnose, resulting in treatment delay. We performed single-cell and spatial transcriptomics analysis of skin from patients with mycosis fungoides-type CTCL and an integrated comparative analysis with human skin cell atlas datasets from healthy and inflamed skin. We revealed the co-optation of T helper 2 (TH2) cell-immune gene programs by malignant CTCL cells and modeling of the tumor microenvironment to support their survival. We identified MHC-II+ fibroblasts and dendritic cells that can maintain TH2 cell-like tumor cells. CTCL tumor cells are spatially associated with B cells, forming tertiary lymphoid structure-like aggregates. Finally, we validated the enrichment of B cells in CTCL and its association with disease progression across three independent patient cohorts. Our findings provide diagnostic aids, potential biomarkers for disease staging and therapeutic strategies for CTCL.

Corneal subepithelial nerve fibers in type 2 diabetes: potential biomarker of diabetic neuropathy

AIM: To observe the changes in corneal subepithelial nerve fibers (CNFs) and Langerhans cells (LCs) in patients with type 2 diabetes using corneal laser confocal microscopy (CLCM). METHODS: A total of 60 patients (64 eyes), including 40 patients with type 2 diabetes (DM group) and 20 subjects without diabetes (control group) were included with CLCM. Neuron J plugin of Image J software were used for quantitative analysis of CNF length (CNFL), CNF density (CNFD), corneal nerve branch fiber density (CNBD), main branch length density, branch length density, corneal nerve fiber tortuosity (NT) score, and LCs density. An independent samples t-test to analyze the variability between the two groups was performed, and Pearson correlation analysis was used to analyze the relationships between CNF and multiple biochemical indicators in the DM group. The predictive power of CNF for type 2 diabetes was assessed using the receiver operating characteristic (ROC) curve. RESULTS: There were significant differences in the CNFL, CNFD, and main branch length density between two groups. The results of Pearson correlation analysis showed a significant negative correlation between CNFD and the duration of diabetes as well as triglyceride levels and total cholesterol, and a significant positive correlation between CNFD and serum albumin. In addition, the NT score showed a positive correlation and urea nitrogen, similar to the positive correlation observed between LC density and glycosylated hemoglobin (HbA1c) levels. CNFD showed the highest area under the curve (AUC of ROC) value, followed by main branch length density and CNFL. The AUC of the ROC curve under the logistic regression model also demonstrated good predictive values. The cut-off values of CNFD, CNFL, and main branch length density for diabetes showed 31.25, 18.85, and 12.56, respectively. CONCLUSION: In patients with type 2 diabetes, there is a notable reduction in both CNFL and CNFD. These measurements can be influenced by various blood biochemical factors. However, the compromised nerve fibers can serve as valuable indicators for predicting the onset of type 2 diabetes and also as biomarkers for detecting diabetic neuropathy and its related complications.

Serum microRNA qPCR profiling and validation indicate upregulation of circulating miR-145-5p and miR-26a-5p in migraineurs

Abstract Background In recent years, miRNAs found in biological fluids have gained interest as biomarkers of numerous conditions, including migraine. This study aimed to identify differences in the levels of circulating miRNAs in the serum of migraineurs as compared to healthy controls, as well as between patients with different types of migraine and during the ictal and nonictal phases of the condition. Methods The screening phase of the study included serum from 13 migraine patients and 13 sex and age matched controls. A panel of 179 miRNAs was analysed using locked nucleic acid SYBR based qPCR. Based on statistical analysis (U Mann-Whitney test) and data from existing literature, nine miRNAs were selected for validation by TaqMan qPCR in an independent cohort of 26 migraineurs and eleven healthy controls. For comparison between the study and control group, U Mann-Whitney test was performed. The differences between patients with chronic and episodic migraine, migraine with and without aura and in ictal and nonictal phases were analysed with Kruskal-Wallis test. The results were corrected for multiple comparisons using Benjamini-Hochberg method. In all analysis p value ≤ 0,05 was considered as significant. Results Two miRNAs, miR-145-5p and miR-26a-5p were significantly upregulated in serum of migraineurs compared to healthy controls. MiRNA-19a-3p was downregulated in patients currently experiencing migraine headache compared to those in the interictal period. No differences were found between patients with different migraine types. Conclusion The results of our study add to the growing body of evidence for dysregulation of the circulating miRNA profile by migraine. They are further supported by previous reports on differential expression of miR-145-5p, miR-26a-5p and miR-19a-3p in migraineurs. However, more research on larger populations is needed to validate these findings, as well as elucidate the role of circulating miRNAs in the condition. Moreover, to wholly explore the biomarker potential of miRNAs, migraine patients should not only be compared to healthy controls but also to populations with different headache disorders. Graphical Abstract

Role of gut microbiome in developing necrotizing enterocolitis.

Necrotizing enterocolitis (NEC) is one of the most devastating intestinal diseases observed in preterm in the first days of life. Researchers have recently focused on potential predictive biomarkers for early and concomitant diagnoses. Thus, we inquired about the linkage of intestinal dysbiosis, one of the most important factors in NEC development to the gut microbiota. In this study, the systematic differences in the bacterial composition between neonates affected by NEC and healthy newborns were highlighted by metagenomic analysis. The next-generation sequencing of the V3-V4 variable region of the 16S rRNA gene and gene-specific qPCR analyzed the untargeted gut microbiota. Total bacteria, total and fecal coliform loads in stool samples with NEC were higher than control. OTU-level relative abundances of NEC infant was characterized by Firmicutes and Bacteroidetes at phylum levels. At the genus level, NEC stool was identified by the lack of Klebsiella and the presence of Roseburia, Blautia, and Parasutterella. Finally, Clostridium fessum was the predominant species of Clostridium genus in disease and healthy specimens at the species level, whereas Clostridium jeddahitimonense was at NEC diagnosis. Despite a strong relationship between pathophysiology and characterization of gut microbiota at a clinical diagnosis of NEC, our results emphasize the broad difficulty in identifying potential biomarkers.

Multiomics biomarkers were not superior to clinical variables for pan-cancer screening

Abstract Background Cancer screening tests are considered pivotal for early diagnosis and survival. However, the efficacy of these tests for improving survival has recently been questioned. This study aims to test if cancer screening could be improved by biomarkers in peripheral blood based on multi-omics data. Methods We utilize multi-omics data from 500,000 participants in the UK Biobank. Machine learning is applied to search for proteins, metabolites, genetic variants, or clinical variables to diagnose cancers collectively and individually. Results Here we show that the overall performance of the potential blood biomarkers do not outperform clinical variables for collective diagnosis. However, we observe promising results for individual cancers in close proximity to peripheral blood, with an Area Under the Curve (AUC) greater than 0.8. Conclusions Our findings suggest that the identification of blood biomarkers for cancer might be complicated by variable overlap between molecular changes in tumor tissues and peripheral blood. This explanation is supported by local proteomics analyses of different tumors, which all show high AUCs, greater than 0.9. Thus, multi-omics biomarkers for the diagnosis of individual cancers may potentially be effective, but not for groups of cancers.

Abstract A024: Tissue biomarkers in the tumor microenvironment predicting the development of cachexia in pancreatic cancer patients

Abstract Pancreatic ductal adenocarcinoma (PDAC) poses significant challenges due to its aggressive nature and the limited efficacy of existing treatments. The complex interactions within the tumor microenvironment (TME) and tumor cell itself remain poorly understood, particularly in relation to cancer cachexia, which is characterized by weight loss, muscle wasting, systemic inflammation, and metabolic disturbances, and has a profound impact on PDAC outcomes. This study investigated the role of the TME in the development of cachexia in PDAC patients, focusing on the potential of cachexia-related proteins as tissue biomarkers in the TME. In this retrospective study, tissue samples from 13 PDAC patients obtained via Endoscopic Ultrasound-Guided Fine Needle Aspiration at the time of diagnosis were analyzed using immunofluorescence staining, supplemented by epidemiological data. The initial classification of cachexia based on epidemiological data, including patients body mass index and three-month weight changes, was further refined through body composition trend analysis during 180 days after the diagnosis with consecutive computed tomography images. These detailed classification criteria allowed for a more realistic classification of cachexia compared to the conventional classification of cachexia based on weight change, resulting in 5 patients being classified as cachexia and 8 as non-cachexia. We selected NAMPT (nicotinamide phosphoribosyl transferase) as a candidate tissue biomarker, a rate-limiting enzyme crucial in the NAD+ salvage pathway, due to its significant role in cellular metabolism, and the regulation of energy depletion and consumption in muscle cells. We hypothesized that NAMPT is closely linked to the mechanisms of cachexia because NAD+ is essential for muscle regeneration. Additionally, PTHLH (Parathyroid Hormone-Like Hormone), selected as another candidate marker, plays a critical role by being secreted from tumor cells, promoting cancer cell growth and metastasis. The overexpression of PTHLH can lead to malignant hypercalcemia, which may trigger severe systemic inflammatory responses in cancer patients, contributing to the development of cachexia. We utilized the coordinated expression of these two proteins as potential tissue biomarkers predicting cachexia at the time of diagnosis of PDAC. In our study, PTHLH expression was significantly elevated in the cachexia group, while NAMPT expression was higher in the non- cachexia group. Although both markers are known to be overexpressed in most metastatic pancreatic cancers, their correlations vary depending on the presence of cachexia. These findings suggest that even in metastatic pancreatic cancer, these markers can serve as precise biomarker signatures that determine the possibility of developing cachexia. To further validate our findings, we are currently testing a larger validation set (cachectic PDAC patients=100, non-cachectic PDAC patients=100) to determine whether the expression of these two markers can be utilized as biomarkers for the early detection of cachexia. Citation Format: Hyun Jung Kee, Jinhee Lee, Ju Young Bae, Hia Jung, Jeehoon Kim, Galam Leem, Hee Seung Lee, Jeong Youp Park, Seungmin Bang, Seung Woo Park, Moon Jae Chung. Tissue biomarkers in the tumor microenvironment predicting the development of cachexia in pancreatic cancer patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A024.

Abstract B017: The double-edged sword of cystatin B in luminal-like and triple-negative breast cancers

Abstract The complex protease network of cathepsins and their inhibitors, cystatins, intricately regulates numerous cellular processes, and its dysregulation is frequently implicated in cancer pathogenesis. Abnormal cathepsin activity, subcellular localization, and a disrupted balance between cathepsins and cystatins have been identified in cancer. While diminished cystatin levels typically correlate with more aggressive cancer phenotypes, few findings challenge this paradigm. In this context, our latest study revealed elevated expression of cystatin B (CSTB) in luminal-like breast cancer (BC) patients experiencing relapse within five years post-surgery. Furthermore, computational analysis of publicly available datasets supports our idea of CSTB as a potential negative prognostic biomarker in luminal-like tumors. Intriguingly, a converse relationship is observed in basal-like/triple negative BC patients, where increased CSTB expression seems to be associated with improved prognosis. In addition, the cysteine/cathepsin network intricately intersects with immune functions, adding another layer of complexity. Cathepsins are indeed involved in the induction of an efficient anti-tumor immune response, being key in antigen processing and presentation by antigen-presenting cells and in the cytotoxic activities of NK and T cells. On the other hand, myeloid cells rely on cathepsins for the degradation of ECM proteins that may favor migration and invasion of tumor cells. All these pieces of evidence led to the hypothesis that the functional impact of CSTB may vary depending on the tumor intrinsic characteristics and on its microenvironment and therefore that CSTB might fulfill distinct functional roles in luminal-like and basal-like BC. To start addressing our hypothesis, we silenced CSTB expression in the 4T1 mouse cell line, a TNBC model spontaneously metastasizing to the lungs upon intra-mammary fat pad injection. Preliminary in vivo experiments to investigate the effect on primary tumor growth and metastatic dissemination showed that 4T1 shCSTB lines were indeed characterized by increased tumor growth and metastatic dissemination than the two sh-control lines. Interestingly, expression of stemness- related genes (Nanog, Sox2 and Oct4) were up-modulated upon CTSB silencing, in agreement with a more aggressive phenotype. On the other hand, preliminary in vitro assays with a luminal- like BC cell line support the hypothesis of an opposite effect of CSTB down-modulation in luminal BC subtype. Moreover, CSTB silencing in RAW264.7 macrophagic cell line, impaired M1 in vitro polarization, while it did not appear to affect M2 skewing. Overall, although preliminary, these data suggest that CSTB may affect BC aggressiveness by both interfering with tumor cell-intrinsic features and microenviroment-related traits. Citation Format: Anna Zaccaria, Chiara Ratti, Laura Botti, Sabina Sangaletti, Mario P. Colombo, Claudia Chiodoni. The double-edged sword of cystatin B in luminal-like and triple-negative breast cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B017.

Abstract B028: The Role of cDC1 Gene Signatures in gastric cancer prognosis and immune microenvironment modulation

Abstract Background and Aim: Gastric cancer (GC) continues to be a major global health burden, with a growing body of evidence highlighting the critical role of conventional type 1 dendritic cells (cDC1s) within the tumor microenvironment. This study aims to elucidate the prognostic significance of cDC1-associated genes—CD141, XCR1, CLEC9A, CADM1, and BTLA—in gastric cancer, as well as to explore the biological mechanisms that underpin their effects on patient outcomes. Materials and Methods: We conducted a comprehensive analysis of RNA- seq data from The Cancer Genome Atlas (TCGA-STAD) and Gene Expression Omnibus (GEO) datasets, focusing on the expression profiles of five cDC1-related genes. Patients were stratified into high and low expression groups based on a defined cDC1 gene signature. To assess the impact of these signatures, we utilized gene set variation analysis (GSVA) to examine relevant oncogenic pathways and performed Kaplan-Meier survival analysis along with Cox proportional hazards modeling to evaluate their prognostic value. Results: Our findings demonstrate that patients exhibiting a high cDC1-related gene signature had significantly worse overall and disease-free survival within the TCGA-STAD cohort. Further analysis revealed marked differences in CD8+ T cell infiltration and cytotoxic activity between the high and low cDC1 signature groups. Additionally, the high cDC1 signature group was strongly associated with upregulated expression of immune checkpoint proteins and the activation of oncogenic pathways, indicating a highly immunosuppressive tumor microenvironment. Conclusions: This study suggests that the cDC1-related gene signature may serve as a potent prognostic biomarker in gastric cancer, offering new insights into the complex interactions between the tumor and immune microenvironment. These results could pave the way for innovative therapeutic strategies that target the immune landscape in gastric cancer, potentially improving patient outcomes. Citation Format: Song-hee han. The Role of cDC1 Gene Signatures in gastric cancer prognosis and immune microenvironment modulation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B028.

Abstract B016: Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy

Abstract Background: Despite the success of anti-PD-1/PD-L1 immunotherapies, outcomes for lung cancer patients remain suboptimal. There is a critical need to incorporate multi-omics data focused on the tumor microenvironment (TME) to enhance patient selection and treatment individualization. This study aimed to identify predictive and prognostic biomarkers of immunotherapy response by characterizing transcriptional profiles of lung adenocarcinoma patients who underwent genomic profiling at diagnosis. Methods: RNA sequencing data were obtained from 68 lung adenocarcinoma patients who underwent next-generation sequencing with CARIS at our institution. We analyzed gene expression profiles (GEP) comprising 18 inflammatory genes associated with antigen presentation, chemokine expression, cytolytic activity, and adaptive immune resistance, identified as potential biomarkers for immune checkpoint inhibitor (ICI) response (Cristescu et al., 2018). The genes included were CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PD-L2), PSMB10, STAT1, and TIGIT. GEP scores were calculated, and hierarchical clustering identified tumor subsets with similar GEPs. Gene set variation analysis was conducted to assess enrichment of cell-cell interaction activities of specific ligand-receptor pairs of immune checkpoint genes, partially overlapping with the 18 GEP genes. Results: Hierarchical clustering identified four distinct GEP clusters: "T cell-inflamed GEP," "T cell-non-inflamed GEP high," "T cell-non-inflamed GEP medium," and "T cell-non-inflamed low GEP," with average scores of 0.18 (N=9, 13%), 0.11 (N=29, 43%), 0.08 (N=19, 28%), and 0.04 (N=11, 16%), respectively. The gene scores among these clusters showed significant differences (P = 3.3e-09). Additionally, analysis of specific ligand-receptor pairs of immune checkpoint genes (PD1/PD-L1, PD-L2; CTLA4/CD28, CD80, CD86; ICOS/ICOSLG; TIM3/GAL9; SIRP1/CD47) showed consistent positive enrichment in the “T cell-inflamed” cluster, with no or negative enrichment in the “T cell-non-inflamed” clusters. This suggests active immune checkpoint interactions in clusters with high GEP scores. Conclusion: We identified four different clusters among tissues from patients with NSCLC based on GEP scoring highlighting differences in immune activation and TME makeup, which may play a role in predicting response to immunotherapies. Our results suggest that GEP may provide information on identifying optimal immunotherapeutic approaches based on TME. Our findings underscore the importance of using biomarker-guided strategies to improve patient selection for precision immunotherapy approaches in lung cancer. Citation Format: Changde Cheng, Doug Welsch, Kayla F. Goliwas, Jessy Deshane, Sameer Deshmukh, Sanad Ahlushki, Yanis Boumber, Darshan Shimoga Chandrashekar, Alexander C. Mackinnon, Aakash Desai. Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B016.

Abstract C040: Spatial transcriptomics unveils disparities in tumor microenvironment dynamics between breast cancer responders and non-responders

Abstract Spatial transcriptomics is revolutionizing our understanding of cellular dynamics and interactions in the tumor microenvironment (TME). By mapping distinct cellular populations and their interactions, we can gain valuable insights into tumor behavior. To investigate these dynamics in breast cancer, we conducted Xenium In-situ spatial transcriptomics on twenty formalin-fixed paraffin-embedded (FFPE) samples taken from eight patients undergoing neoadjuvant chemotherapy. These samples have been taken pre-treatment, mid-treatment and post-treatment from four cases with pathological complete response (pCR), and four cases with residual disease (RD) at time of surgery. Our analyses have found distinct cellular composition changes between pCR and RD cases. Patients with RD demonstrated an increase in endothelial, perivascular-like (PVL) and epithelial cells from pre- to post-treatment. This was accompanied by a decrease in myeloid and malignant epithelial cells at mid-treatment. In contrast, patients with pCR demonstrated increases in cancer-associated fibroblasts (CAFs) and myeloid cells, with reductions in plasmablasts and cancer epithelial cells at mid-treatment. This suggests that an increase in CAF and myeloid cells observed between pre-treatment and mid-treatment samples may be predictive of response. We performed ligand-receptor (LR) analyses, which demonstrated diverse myeloid interactions in RD cases and diverse CAF interactions in pCR cases in pre-treatment samples. Mid-treatment samples exhibited a decrease in interactions for CAFs, myeloid and T cells in pCR and RD cases. The most frequently identified CAF LR interactions, as senders, were between TGFB1/TGFB3 and TGFBR1/TGFBR2, while the most frequently identified myeloid LR interactions were between PDCD1LG2 - PDCD1 (encoding PDL2 & PD1), CCL8 - ACKR1 (encoding Atypical Chemokine Receptor 1) and CCL2 - ACKR1. Our findings indicate that the dynamic changes in cellular composition and interactions within the TME differs between responders and non-responders. To further explore these differences, we plan to perform spatially constrained analyses to identify unique cellular niches that may serve as potential biomarkers for informing novel therapeutic strategies. Citation Format: Jeremy Mo, Hanyun Zhang, Kate Harvey, Alexander Swarbrick. Spatial transcriptomics unveils disparities in tumor microenvironment dynamics between breast cancer responders and non-responders [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C040.

Cell-free pregnancy-associated microRNAs in blood plasma as potential biomarker in early diagnosis of ectopic pregnancy.

Ectopic pregnancy (EP) is one of the life-threatening disorders in early pregnancy and current strategies are inadequate in its clinical management. There is a need to identify more accurate biomarkers for early diagnosis of ectopic pregnancy. This case-control study was conducted in a group of 35 women diagnosed with ectopic pregnancy and 31 women with a normal singleton pregnancy. Patients' characteristics including the level of β-hCG, age, body mass index (BMI), and gestational age have been recorded. The plasma levels of cell-free hsa-miR-411, hsa-miR-433, and hsa-miR-524 were examined by qRT-PCR using specific primers. There was no statistically significant difference in maternal age, gestational age, and BMI between the two groups. β-hCG concentrations in EP were significantly lower than normal pregnancy group. Cell-free hsa-miR-411 and hsa-miR-433 had statistically significant differences in concentrations in women with EP and normal pregnancy. hsa-miR-411 and hsa-miR-433 had better diagnostic values for discriminating EP from normal pregnancy. Moreover, hsa-miR-411 and hsa-miR-433 showed a specificity of 61% and 53%, and a sensitivity of 72% and 79%, respectively. hsa-miR-411 and hsa-miR-433 microRNAs concentrations in plasma have potential as a predicting biomarker for early diagnosis of EP. However, further research is needed before using miRNAs in clinical practice for both diagnostic and therapeutic goals.

Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.

Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of CaOx crystals in renal tissues. Despite their prevalence, precise biomarkers for CaOx nephrolithiasis are lacking. With advances in high-throughput sequencing, we aimed to identify biomarkers of CaOx nephrolithiasis by combining twoCaOx nephrolithiasis datasets (GSE73680 and GSE117518). Utilizing weighted gene co-expression network analysis (WGCNA) and four machine learning, we identified six hub genes (DLK2, BHLHA15, C12orf5, ICMT, LOXHD1, and TP73) as potential biomarkers. Additionally, CIBERSORT immune infiltration analysis suggested that these core genes may influence immune cell recruitment and infiltration in CaOx nephrolithiasis. Then, TP73 emerged as a significant hub gene in CaOx nephrolithiasis via receiver operating characteristic (ROC) analysis (AUC = 0.885). Furthermore, the role of TP73 was validated in CaOx nephrolithiasis rat models induced by 1% ethylene glycol, as well as clinical samples and renal tubular epithelial cell models treated with 1mM oxalate. Immunohistochemistry, RNA-Sequencing, and RT-qPCR experiments demonstrated an increased expression of TP73 in CaOx nephrolithiasis rat models and clinical samples. After transfection with TP73 lentivirus, CCK-8 assays suggested that TP73 could inhibit the proliferation of HK-2 and NRK-52E cells. In oxalate-induced cell models, dihydroethidium staining and flow cytometry apoptosis assays indicated that TP73 could enhance ROS levels and cell apoptosis. In summary, our study preliminarily identified TP73 as a diagnostic biomarker and elucidated the promoting role of TP73 in CaOx nephrolithiasis, providing a deeper understanding of the clinical diagnosis and pathogenesis.

Changes in choroidal thickness quantified by Optical Coherence Tomography across cognitive impairment: data from the NORFACE cohort.

Optical coherence tomography (OCT) enables high-resolution imaging of ocular structures in health and disease. Choroid thickness (CT) is a key vascular retinal parameter that can be assessed by OCT and might be relevant in the evaluation of the vascular component of cognitive decline. We aimed to investigate CT changes in a large cohort of individuals cognitive unimpaired (CU), with mild cognitive impairment due to Alzheimer's (MCI-AD), mild cognitive impairment due to cerebrovascular disease (MCI-Va), Alzheimer's disease dementia (ADD), and vascular dementia (VaD). Clinical, demographical, ophthalmological and OCT data from the Neuro-ophthalmological Research at Fundació ACE (NORFACE) project were analyzed. CT was assessed in the macula across nine Early Treatment Diabetic Retinopathy Study (ETDRS) quadrants, average thickness, total volume, and subfoveal choroidal thickness. Differences of CT among the five diagnostic groups were assessed in a multivariate regression model, adjusting for demographic and cardiovascular risk factors and OCT image quality. A comparison between manual and automatic CT measurements in a subset of participants was also performed. The study cohort comprised 1,280 participants: 301 CU, 196 MCI-AD, 112 MCI-Va, 578 ADD, and 93 VaD. CT was significantly increased in individuals with cognitive impairment compared to those CU, particularly in the VaD and MCI-Va groups and in the peripheral ETDRS regions. No significant differences were found in inner superior, center and subfoveal choroidal thickness. The interaction of sex and diagnosis had no effect in differentiating CT. Mini-Mental State Examination (MMSE) scores were not correlated to CT. Manual and automated CT measurements showed good reliability. Our findings indicated that peripheral choroidal thickening, especially in patients with cerebrovascular disease, may serve as a potential choroidal biomarker for cognitive decline and suggest different pathogenic pathways in AD and VaD. Further research is required to explore CT as a reliable ocular biomarker for cognitive impairment.

Alterations of gray matter asymmetry in internet gaming disorder.

Structural asymmetry is a subtle but pervasive property of the human brain, which has been found altered in various psychiatric and neurocognitive disorders. However, little is known regarding potential alterations of structural asymmetry underlying internet gaming disorder (IGD). Therefore, this study aimed to investigate the structural features of gray matter asymmetry in IGD. High-resolution structural magnetic resonance imaging data were collected from 104 individuals with IGD and 104 recreational game users (RGUs). We applied a whole-brain voxel-based asymmetry (VBA) approach to determine the asymmetrical aberrations of gray matter in relation to IGD. Furthermore, the local abnormalities of structural asymmetry were employed as features to examine the effect of classification using a support vector machine (SVM). The results indicated that individuals with IGD as compared to RGUs showed asymmetrical alterations of gray matter in the medial prefrontal cortex (mPFC), orbitofrontal cortex, precuneus, middle temporal gyrus, superior parietal lobule and inferior temporal gyrus, regions implicated in hedonic motivation, self-reflection, information integration and visuospatial attention processing. Moreover, these atypical asymmetrical features can distinguish IGD subjects from RGUs with high accuracy. These results suggested that disrupted structural asymmetry of motivational reward, visuospatial and default mode circuits might be potential biomarkers for identifying pathological gaming dependence. These findings extended our understanding of structural underpinnings of IGD and provided new insights for developing effective interventions to alleviate compulsive gaming usage.

Bioinformatics combined with network pharmacology and experimental validation to identify key biomarkers of hepatocellular carcinoma and corresponding compounds in Radix Astragali and Pueraria Mirifica.

The occurrence and death rates of primary hepatocellular carcinoma (HCC) are increasing, and there remains a shortage of effective oral medications with minimal side effects. We aim to identify potential biomarkers and compounds from Radix Astragali (RA) and Pueraria Mirifica (PM) to treat liver cancer and improve prognosis. Differentially expressed genes (DEGs) associated with HCC were identified by bioinformatics analysis of three datasets, GSE112791, GSE101685, and GSE45114. Using public databases to predict the bioactive components and possible targets of RA and PM. Target crossover from Gene Expression Omnibus (GEO) and public databases were used to identify potential biomarkers for HCC. Subsequently, validation and prognostic value analyses were performed using the Gene Expression Profile Interaction Analysis (GEPIA) platform. The Cytoscape software created a network of "compound targets" to pinpoint compounds linked to the biomarkers. Molecular docking techniques were utilized to validate the connection between these compounds and the identified biomarkers. Ultimately, the HepG2 liver cancer cell line was chosen to assess the inhibitory effect of Hederagenin (HDG) and to confirm the expression of ADH1B through Western blot analysis. In this study, four key biomarkers (NR1I2, ADH1B, NQO1, GHR) were identified. Molecular docking showed that these four core targets could form stable conformations with the corresponding compounds. As the drug concentration decreases, the inhibitory effect on HepG2 diminishes, and the survival rate of HepG2 cells significantly declines following the administration of 100 µmol/L HDG. Compared to the control, the expression of ADH1B protein is significantly increased in HepG2 cells treated with 100 µmol/L HDG. The study identified four key biomarkers (ADH1B, GHR, NQO1, NR1I2) that have prognostic ability for HCC. This study provides biomarkers and potential targeted monomeric medicines for treating HCC.

Diagnostic Value of lncRNA FGD5-AS1 Sponge miR-223-3p in Infantile Pneumonia and Its Prognostic Effect on Rehabilitation

Abstract Objective This study aimed to uncover the value of long noncoding RNA FGD5-AS1 (lncRNA FGD5-AS1) in the diagnosis of infantile pneumonia and explore its pathological mechanism in lung fibroblasts. This research may provide a potential biomarker for diagnosing patients and predicting their rehabilitation outcomes. Methods This study included 92 children with infantile pneumonia as the research object, and an equal number of healthy children were introduced as controls. The FGD5-AS1 content was detected using real-time quantitative polymerase chain reaction (RT-qPCR) assay. The diagnostic value of FGD5-AS1 was evaluated by receiver operating characteristic (ROC) and logistic analysis. The molecular mechanism of FGD5-AS1 and miR-223-3p was studied by luciferase activity assays. The impact of abnormal FGD5-AS1 expression on the proliferation and apoptosis of lung fibroblasts was analyzed using the cell counting kit-8 (CCK-8) and flow cytometry. Results FGD5-AS1 expression was decreased in the serum of infantile pneumonia patients, which may be a diagnostic marker for children with pneumonia. Furthermore, FGD5-AS1 has the ability to predict patient outcomes. FGD5-AS1 levels in lung fibroblasts (WI-38) decreased when induced by lipopolysaccharide (LPS). This decline resulted in reduced cell proliferation ability, increased apoptosis rate, and elevated inflammatory factor content. However, upregulated FGD5-AS1 counteracted the effects of LPS on WI-38 cells activity and inflammatory factors. Conclusion FGD5-AS1 may act as a potential marker in infantile pneumonia, and regulate the biological activity and inflammation level of lung fibroblasts by targeting miR-223-3p.

Altered expression of Csnk1a1p in Autism Spectrum Disorder in Iranian population: case-control study.

Over the past decade, substantial scientific evidence has showed that long non-coding RNAs (lncRNAs) are extensively expressed and play a crucial role in gene modulation through a diverse range of transcriptional, and post-transcriptional mechanisms. Recent discoveries have emphasized the involvement of lncRNAs in maintaining cellular homeostasis and neurogenesis in the brain. Accumulating reports identified dysregulated lncRNAs associated with psychiatric disorders, including autism. In this study, we examined the expression levels of DISC2, Linc00945, Foxg1-as1, Csnk1a1p, and Evf2 lncRNAs in blood samples from 21 clinically diagnosed autistic patients based on the Diagnostic and Statistical Manual of Mental Disorders criteria-5th edition (DSM-5), compared to age, sex, and ethnically-matched 25 healthy individuals. RNA extraction and cDNA synthesis were performed, followed by real-time PCR for quantification of lncRNAs expression levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate biomarker potential. Additionally, we investigated the correlation between gene expression levels and autism comorbidities. Our results showed a significant decrease in Csnk1a1p expression in patients with autism spectrum disorder (ASD) compared to healthy children (P value = 0.0008). ROC curve analysis indicated that Csnk1a1p expression levels could effectively discriminate patients from healthy controls (AUC = 0.837, P value = 0.000284). No significant differences were observed between Csnk1a1p expression levels and comorbidity with ADHD or intellectual disability (p-value > 0.05). Based on these findings, Csnk1a1p may play a significant role in autistic patients and could serve as a potential biomarker for diagnostic and predictive purposes, as well as a therapeutic target.