Prognostic Biomarker Research Articles

High-Normal Serum Potassium, Calcium, and Magnesium Levels Are Associated With Decreased Risks of Adverse Outcomes After Ischemic Stroke.

High serum potassium, calcium, and magnesium levels have been reported to be associated with decreased risks of ischemic stroke, whereas their prognostic values in ischemic stroke remain unclear. We aimed to prospectively explore the associations of serum potassium, calcium, and magnesium levels with the prognosis of ischemic stroke. We measured serum potassium, calcium, and magnesium levels at baseline among 5469 patients with ischemic stroke from the Minhang Stroke Cohort study. The primary outcome was the composite outcome of death and major disability (modified Rankin Scale score ≥3) at 3 months after ischemic stroke. Secondary outcomes included major disability, death, and the ordered 7-level categorical score of the modified Rankin Scale. During 3-month follow-up, 1834 patients developed the primary outcome. After multivariate adjustment, the adjusted odds ratios of primary outcome for the highest versus the lowest quartile were 0.79 (95% CI, 0.68-0.93; Ptrend=0.007) for potassium, 0.69 (95% CI, 0.58-0.82; Ptrend<0.001) for calcium, and 0.83 (95% CI, 0.70-0.99; Ptrend=0.015) for magnesium. Multivariable-adjusted restricted cubic spline analyses showed linear dose-response relationships of serum potassium, calcium, and magnesium with the risk of primary outcome (all P for linearity<0.05). High-normal serum potassium, calcium, and magnesium levels were associated with decreased risks of adverse outcomes at 3 months after ischemic stroke, suggesting that serum potassium, calcium, and magnesium might be valuable prognostic biomarkers for ischemic stroke.

Liquid biopsy in diagnosis and monitoring of treatment efficacy in patients with small cell lung cancer.

Small-cell lung cancer (SCLC) remains one of the deadliest cancers worldwide. Patients' survival remains poor due to its rapid growth, high metastatic rate and limited possibilities of treatment. For many years, SCLC management has been based mostly on chemo and radiotherapy. However, new therapeutic approaches have been proposed in the past few years, including immunotherapy, which is currently implemented in clinical practice. Unfortunately, in many cases, response to therapy, especially chemotherapy, remains poor, or the patient becomes resistant to initially effective treatment. One of the crucial problems during SCLC patient care is a lack of appropriate predictive biomarkers for various therapeutic approaches. Another critical issue is the scarcity of collected tissue during biopsy, which may be insufficient or of too poor quality for analysis. A liquid biopsy might be the key to solving both of those problems as it is collected in a non-invasive way and enables the measurement of various biomarkers, including circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs). In this review, we discuss various approaches to potentially incorporating liquid biopsy into clinical application - as a companion to imaging during SCLC diagnostics, a new approach to molecular subtyping, and a material enabling predictive or prognostic biomarkers assessment. We also summarize ongoing clinical trials encompassing SCLC patients in which liquid biopsy is collected and examined.

Integrative analysis of the expression profile and prognostic values of SENP gene family in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) stands as the fourth leading cause of cancer-related deaths worldwide. SUMO-specific peptidases, known as SENPs, emerge as critical players, regulating tumorigenesis and progression of numerous cancer types. Despite this, the specific impact of SENPs in HCC remains unclear. Hence, our study aimed to reveal the immune and prognostic implications of SENPs in HCC. The gene expression of SENPin various cancers was examined using open-access databases including TCGA, GTEx, and CPTAC. In order to investigate the prognostic potential of the SENP family, Kaplan-Meier analysis was used. To clarify the underlying biological mechanisms, gene set enrichment analysis (GSEA) was carried out. cBioPortal database was used to evaluate genetic mutation profiles. For insight into the relationship between SENP genes and tumor immunity, various algorithms were used. Our findings showed that SENP1, SENP2, SENP3, SENP5, SENP6, and SENP7 expression levels were significantly higher in HCC tumor tissues compared to normal tissues. In HCC patients, elevated SENP1 and SENP5 expression has been associated with tumor development and poor outcomes. Our immune infiltration patterns results also showed significant correlations between SENP5 expression and neutrophil (cor = 0.346, p < 0.001), myeloid dendritic cell (cor = 0.491, p < 0.001), macrophage (cor = 0.465, p < 0.001), and memory B cell (cor = 0.336, p < 0.001) infiltration in HCC, whereas SENP1 expression was associated with none of these infiltrations. The prognostic and immunogenetic value of SENP1 and SENP5 in HCC was demonstrated in this study. Therefore, these two genes have the potential to function as separate prognostic biomarkers and offer promise as immunotherapeutic targets in the fight against HCC.

Deciphering the multifaceted role of EXO1 in female-related cancers: implications for prognosis and therapeutic responsiveness

BackgroundAberrant function or overactivation of exonuclease 1 (EXO1) may be associated with cancer tumor development, drug resistance, and response to immunotherapy in female-related cancers.MethodsBy analyzing RNA-sequencing data from The Cancer Genome Atlas database, combined with validation through quantitative polymerase chain reaction experiments, we explored the expression levels of EXO1 in breast cancer (BRCA) cell lines and assessed its multidimensional roles in various female-related cancers.ResultsOur experiments revealed elevated expression of EXO1 in BRCA cell lines, consistent with the RNA-sequencing data. The high expression of EXO1 is associated with poor prognosis in various female-related cancers, especially in BRCA and UCEC. It significantly correlates with clinical and pathological characteristics. In specific cancer subtypes like the basal-like subtype of BRCA, high EXO1 expression is associated with a better prognosis. Genetic mutation analysis indicates a higher frequency of EXO1 gene mutations in uterine sarcoma and BRCA. DNA methylation levels may play a role in the regulation of EXO1 gene expression in some cancers. EXO1 expression is correlated with various factors within the tumor immune microenvironment and may be associated with the sensitivity to anticancer drugs.ConclusionEXO1 exhibits multidimensional roles in female-related cancers as a prognostic biomarker and potentially influences tumor immune therapy responses and drug sensitivities. Further studies are needed to fully understand the complex mechanisms underlying these associations and to explore potential therapeutic strategies targeting EXO1.

Novel Insights into the Phospholipase C Delta 3 and Its Implications in Neoplastic Diseases.

The phospholipase C (PLC) family plays a crucial role in the construction of biomembranes, cell growth, and signal transduction. PLC regulates multiple cellular processes by generating bioactive molecules such as inositol-1,4,5-triphosphate (IP3) and diacylglycerol (DAG). These products propagate and regulate cellular signaling via calcium (Ca2+) mobilization and activation of protein kinase C (PKC), other kinases, and ion channels. Recently, the function of PLC delta 3 (PLCδ3) has been arousing great interests in the basic research of neoplastic diseases. It is demonstrated to affect multiple parts of tumor progression and promote glycolysis reprogramming. However, currently there are no conclusive reports regarding the mechanism of PLCδ3-mediated tumor progression and its importance as a prognostic biomarker in specific neoplastic diseases. Therefore, the present article aimed to illustrate (1) the correlation between the function of phospholipases in PLC family and tumor progression; (2) the PLCδ3-mediated tumor progression, mainly focusing on the signal transduction and regulation; and (3) its potential mechanism and vital targets involved in multiple malignancies.

Revealing roles of PANoptosis-related genes in prognosis and molecular subtypes in lung squamous cell carcinoma by integrated bioinformatic analyses and experiments

The purpose of current study was to reveal the role of PANoptosis-associated genes in lung squamous cell carcinoma (LUSC) and their potential as prognostic biomarkers. We analyzed RNA-seq data from TCGA-LUSC and GEO datasets to identify differentially expressed genes (DEGs) between LUSC and normal samples, followed by VENN analysis to reveal PANoptosis-related DEGs. Functional enrichment analyses were performed by clusterProfiler package. Distinct LUSC subtypes were identified by consensus clustering based on PANoptosis-related DEGs. Univariate Cox and LASSO regression were utilized to identify key prognostic genes, and a prognostic model was developed based on selected genes. Immune infiltration status was evaluated by CIBERSORT and ESTIMATE algorithms. Expression of key prognostic genes was tested in three LUSC cell lines by RT-qPCR and Western blot. Roles of TLR3 in LUSC progression were determined by functional experiments. A total of 76 PANoptosis-related DEGs were identified, with significant enrichment in apoptosis pathways. The clustering analysis revealed four subtypes, in which survival and immune microenvironment were dramatically different. From the 76 genes, four key prognostic genes (CHEK2, PDK4, TLR3, and IL1B) were identified to establish prognostic risk model, which could reflect the survival status and immune cells composition variations for LUSC patients. Besides, these four genes showed significant correlations with infiltrating levels of various immune cells. TLR3 was identified as a more weighted prognostic risk gene in LUSC. Functional assays demonstrated that genes like TLR3 modulated cell proliferation, migration, and inflammatory responses in LUSC cells. This study highlighted the potential of the four key PANoptosis genes as biomarkers or targets in LUSC, and the risk model based on these four genes provided novel insights to develop personalized treatment strategy for patients with LUSC.Graphical

Mechanical Conditioning (MeCo) Score Progressively Increases Through the Metastatic Cascade in Breast Cancer via Circulating Tumor Cells

Background: The mechanical conditioning (MeCo) score is a multigene expression signature that is acquired by cancer cells in the primary breast tumor and is reflective of their responsiveness to ECM stiffness caused by tumor fibrosis. Chromatin remodeling downstream of mechanotransduction allows cancer cells to retain these acquired aggressive features even in the absence of mechanical stimulation from the primary tumor microenvironment, for instance, after dissemination through systemic circulation during metastasis. Importantly, patients who have high MeCo score tumors are at higher risk of developing metastatic breast cancer, compared to those with low MeCo scores. Moreover, circulating tumor cells (CTCs) are associated with a higher rate of metastatic dissemination, making CTC detection in the circulation of patients with breast cancer a significant prognostic biomarker for breast cancer metastasis. Beyond their enumeration per blood volume units, specific prognostic features of CTCs are not fully explored. We sought to determine whether MeCo scores increase stepwise along the metastatic cascade, from primary tumors to CTCs to distant metastatic colonization, using patient-matched biopsies. Methods: CTCs were isolated from the peripheral blood of two patient cohorts: patients with early-stage breast cancer using immunomagnetic enrichment/FACS methodology; and patients with late-stage breast cancer using the ANGLE Parsortix microfluidics system. Gene expression profiling using RNA-seq was performed on CTCs and matched primary tumors (PTs) in the early-stage cohort, and on CTCs and matched metastases (METs) for the late-stage cohorts. A quantile normalization approach was used to allow comparison across cohorts and MeCo scores were computed for all samples. The Wilcoxon matched-pairs signed rank test was performed for the comparison of MeCo scores from matching samples within each cohort; the Mann–Whitney unpaired test was used to compare MeCo scores of CTCs across cohorts. Results: In 12 pairs of patients with early-stage breast cancer, MeCo scores in CTCs were significantly higher than in their matched PTs (p = 0.026). Additionally, in 26 pairs of metastatic patient CTCs and METs, MeCo scores were significantly higher in METs compared to matched CTCs (p = 0.0004). MeCo scores of CTCs were similar between patients with early- and late-stage breast cancers, despite differing CTC isolation strategies (epitope-dependent and microfluidics size gradient). Notably, 98% of the genes in the MeCo score were present across evaluable CTC, MET, and PT samples. Conclusions: Our results show that the MeCo score is higher in CTCs than in PTs, and higher in METs compared to CTCs, in early- and late-stage breast cancer, respectively (i.e., PT &lt; CTC &lt; MET). Therefore, the MeCo score is progressively higher throughout the metastatic cascade in breast cancer. These findings demonstrate that mechanical conditioning from primary tumors is retained during metastatic progression, after mechanical induction by ECM stiffness is lost, as cancer cells disseminate through systemic circulation. Additionally, these findings support that cancer cells with higher MeCo scores are more competent with—and potentially selected for—metastatic progression. Importantly, these findings provide a novel feature of CTCs, mechanical conditioning (MeCo), which is associated with higher capacity for metastasis. Furthermore, since the CTC MeCo score is elevated even in early-stage breast cancer, it could provide, in addition to CTC enumeration, a potential prognostic indicator to improve metastatic risk assessment in early disease.

CPT1A/HIF-1α positive feedback loop induced fatty acid oxidation metabolic pathway contributes to the L-ascorbic acid-driven angiogenesis in breast cancer

BackgroundIn tumors rich in adipose tissue, angiogenesis is a critical factor in promoting cancer cell metastasis. However, the connection between angiogenesis and the mechanisms driving adipose metabolic remodeling in breast cancer (BC) remains insufficiently understood. This research seeks to explore whether and how CPT1A, a crucial rate-limiting enzyme in fatty acid oxidation (FAO), supports angiogenesis through metabolic pathways in BC.MethodsFirst, cell functional assays and animal models were employed to elucidate the pro-carcinogenic effects of CPT1A on BC and its role in metabolic alterations. Following this, the reciprocal regulatory relationship between CPT1A and HIF-1α was elucidated using transcriptomic studies, ubiquitination analysis, and dual-luciferase assays. Matrigel tube formation assays, vasculogenic mimicry assays, and chick chorioallantoic membrane (CAM) assays were utilized to evaluate the effect of CPT1A on the pro-angiogenic properties of BC. Subsequently, untargeted metabolomics was employed to identify specific metabolic changes in supernatants with and without CPT1A expression and verified by functional recovery experiments. Finally, the prognostic significance of CPT1A and the vascular marker VEGF in BC tissues was evaluated using tissue microarrays and public databases.ResultsCPT1A overexpression significantly enhanced cell proliferation, motility, and angiogenesis via activating the FAO metabolic pathway, as demonstrated by both in vivo and in vitro experiments. Mechanistically, CPT1A regulates the ubiquitination level of hypoxia-inducible factor-1α (HIF-1α), which directly binds to the CPT1A promoter. Mutations at the 63–74 and 434–445 regions significantly reduced CPT1A promoter activity, indicating that these sites are critical for its transcriptional regulation. Ultimately, this interaction creates a reinforcing feedback loop between CPT1A and HIF-1α. Subsequently, this feedback loop alters changes in extracellular L-ascorbic acid (LAA) levels. Interestingly, LAA affects ROS homeostasis through the Nrf2/NQO1 pathway, specifically influencing angiogenesis in BC and HUVECs, while having no significant effect on their proliferation or EMT process. Moreover, increased expression levels of CPT1A and vascular endothelial growth factor (VEGF) were significantly associated with lymph node metastasis and adverse outcomes in BC patients.ConclusionThe CPT1A/HIF-1α positive feedback loop critically regulates angiogenesis through activation of the Nrf2/NQO1 pathway, modulated by LAA. These findings highlight CPT1A and VEGF as promising therapeutic targets and prognostic biomarkers for angiogenesis in BC.Graphical abstract

RACGAP1 and MKI67 are potential prognostic biomarker in hepatocellular carcinoma caused by HBV/HCV via lactylation

IntroductionHepatocellular carcinoma (HCC) is recognized as the prime and lethal form of liver cancer caused by the hepatitis B virus (HBV) and hepatitis C virus (HCV) globally. Lactate is an end product of glycolysis that influences epigenetic expression through histone lactylation. While MKI67 and RACGAP1 play crucial roles in HBV- and HCV-related HCC. However, the role of lactylation-related genes (LRGs) effects in this context remains unclear. This study innovatively explored the role of LRGs in HBV/HCV-associated HCC, identifying novel biomarkers for diagnosis and prognosis.MethodsThe present study used various online databases for analysis, and the findings were validated via immunohistochemical (IHC) analysis of HCC patient samples (n=60).ResultsWe identified six signature LRGs (ALB, G6PD, HMGA1, MKI67, RACGAP1, and RFC4) possess prognostic potential, correlation with immune infiltration, and lactylation-related pathways, providing novel insights into tumor microenvironment (TME) of HCC. Moreover, MKI67 and RACGAP1 were significantly associated with HBV- and HCV-related HCC. IHC confirmed these findings, with high expression of MKI67 and RACGAP1 was significantly linked with HBV/HCV-associated HCC compared to non-viral HCC. The expression is also significantly associated with key clinical variables.ConclusionOur results suggest that MKI67 and RACGAP1 could serve as promising biomarkers for detecting and predicting HCC caused by HBV/HCV via lactylation, opening a new direction for immune-targeted therapies.

Predictive value of platelet to lymphocyte ratio for in-hospital outcome of patients admitted with diagnosis of exacerbation of COPD with type II respiratory failure

Introduction: Exacerbations of COPD are often associated with increased local and systemic inflammation. They tend to worsen the quality of life of sufferers and increase hospital admissions and mortality. Reliable and readily available biomarkers to identify the high-risk patients are necessary to facilitate early implementation of appropriate treatment strategies. Methods: This prospective cohort study, conducted on 110 patients, aimed to study the predictive value of platelet to lymphocyte Ratio (P/L) at the time of admission for in-hospital outcome of patients admitted with a diagnosis of Exacerbation of COPD with Type II respiratory failure. Patients were followed up during their entire stay at the hospital and their blood tests, clinical course and outcome were recorded. The data obtained were recorded in an Excel sheet and analyzed using Statistical Package for Social Science (SPSS) version 25. The work has been reported in line with the STROCSS criteria. Results: Among 110 patients, 11 (10%) died during hospitalization. Mean P/L at the time of admission was 214.56 ± 84.13 among the patients who eventually died at hospital and 152.53 ± 121.19 among those who were discharged (p = 0.006). Conclusion: Our study shows that the mean P/L at the time of admission was significantly higher in COPD patients with type II respiratory failure who died during hospitalization compared to those who were discharged. These findings suggest that the P/L could serve as potential prognostic biomarker for in-hospital mortality risk in COPD exacerbations.

Unravelling lumbar disc herniation severity beyond MRI : integrated transcriptomic and metabolomic analyses highlight glycerophospholipid metabolism and inform a machine-learning diagnostic model: a pilot study.

While MRI serves as a tool for assessing the severity of lumbar disc herniation (LDH), it has been observed that imaging diagnoses do not always align with clinical symptoms in nearly half of patients. The absence of dependable prognostic biomarkers impedes the early and accurate diagnosis of LDH, which is critical for the development of further treatment approaches. Thus, the aim of this study was to elucidate the molecular mechanisms that determine pain and LDH severity. We conducted a pilot study with 55 patients, employing transcriptomic and metabolomic analyses on blood samples to identify potential biomarkers. A gene-metabolite interaction approach helped in identifying the pivotal pathway linked to disease severity. Moreover, a machine-learning model was designed to differentiate between patients based on the intensity of pain. Cholinergic-related glycerophospholipid metabolism emerged as the predominant enriched pathway in the severe symptom group via gene-metabolite interaction network analysis. Among various models, the gradient boosting machines (GBM) model stood out, achieving a commendable area under the curve (AUC) of 0.875 in distinguishing between the severe and mild symptom groups using combined RNA and metabolomics data. Integrated molecular profiling of blood biomarkers has highlighted a novel determining pathway for LDH severity. This machine-learning approach can serve as a valuable predictive tool when MRI findings are inconclusive. Future research will focus on validating these biomarkers and exploring their potential for personalized medicine approaches.

Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis

BackgroundCD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim of this study was to explore the potential role of CD8T cell-associated biomarkers in predicting prognosis and immunotherapy efficacy in ovarian cancer.MethodsThe single-cell sequencing data from the EMTAB8107 cohort were used to identify CD8 T-cell subtypes. The TCGA-OV cohort was involved in constructing a machine learning-based CD8T cell-associated index (CCAI). Additionally, independent ovarian cancer cohorts GSE26712 and GSE26193 were used to validate the predictive validity of CCAI. Multifactorial Cox regression and ROC analysis were applied to assess CCAI. The STRING database was used to clarify the interactions of CD8 T-cell-associated molecules. Furthermore, immune landscape analysis was performed using CIBERSORT, ssGSEA, TIMER, and ESTIMATE algorithms. Tumor mutation burden (TMB) analysis and drug sensitivity analysis were used to evaluate the potential predictive value of CCAI.ResultsThe CCAI, comprising LRP1, PLAUR, OGN, TAP1, ISG20, CXCR4, IL2RG, LCK, and CD3G, serves as a reliable prognostic marker for ovarian cancer patients, demonstrating robust predictive accuracy across various patient cohorts. Notably, individuals with low CCAI tend to exhibit immunoinflammatory tumor characteristics.ConclusionsThe developed CCAI serves as a promising prognostic biomarker for ovarian cancer, accurately predicting patient outcomes. Additionally, it differentiates between patients with distinct immune landscape profiles. This insight enables personalized treatment strategies and facilitates the exploration of underlying mechanisms involving CCAI-related molecules.

Integrated bioinformatic analysis identifies GADD45B as an immune-related prognostic biomarker in skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) arises from melanocytes and is an aggressive form of skin cancer. If left untreated, most melanomas will metastasize, posing a major health risk. GADD45B, a member of the GADD45 family, is known to be involved in DNA damage repair; however, its specific role in SKCM remains largely unclear. In this study, we comprehensively investigated the function of GADD45B in SKCM. By integrating 26 SKCM-related datasets from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), cBioPortal for Cancer Genomics (cBioPortal), Gene Expression Omnibus (GEO), and other databases, we conducted functional enrichment, immune infiltration, and single-cell analyses using R. Additionally, transcriptome sequencing of 30 human SKCM cell lines, phenotype characterization of 29 SKCM lines in vitro, and macrophage polarization analysis were performed. We found that GADD45B expression was significantly downregulated in SKCM patients compared to normal controls (p < 0.001), and higher GADD45B levels correlated with better prognosis (p < 0.05). GADD45B also showed high diagnostic accuracy, with an area under the curve (AUC) of 0.986. GO and KEGG analyses revealed a strong association between GADD45B and immune-related pathways. Gene Set Variation Analysis (GSVA) and single-cell sequencing suggested that GADD45B may serve as a novel immune checkpoint, predominantly expressed in macrophages and promoting M1 polarization. In vitro, overexpression of GADD45B significantly inhibited SKCM cell proliferation, potentially via suppression of the PI3K/Akt signaling pathway, and also reduced chemotherapy resistance. Furthermore, in vivo experiments using a xenograft mouse model demonstrated that GADD45B overexpression significantly suppressed tumor growth. Mice injected with GADD45B-overexpressing tumor cells exhibited smaller tumor volumes from day 15 onwards compared to controls, with markedly reduced tumor volume and weight at the endpoint. These results underscore the potential of GADD45B as an effective tumor suppressor in SKCM. In conclusion, our findings highlight GADD45B as a key regulator in SKCM progression, capable of restraining tumor cell proliferation and enhancing apoptosis. GADD45B holds promise as a novel diagnostic and prognostic biomarker and a potential target for SKCM immunotherapy.

Prognostic impact of tumor-infiltrating lymphocytes in HER2+ metastatic breast cancer receiving first-line treatment

Breast cancer (BC) is a leading cause of death among women, with approximately 30% HER2−positive (HER2+). Although HER2-targeted therapies have improved outcomes for patients with HER2+ metastatic breast cancer (mBC), clinical challenges and prognostic variability remain. Tumor-infiltrating lymphocytes (TILs) have emerged as prognostic and predictive biomarkers in various tumors, including BC, but their role in HER2+ mBC is poorly understood. This multicentric retrospective cohort study evaluated the prognostic significance of TILs in 110 patients with HER2+ mBC treated with pertuzumab, trastuzumab, and taxane-based chemotherapy at two Italian institutes from June 2013 to May 2024. TILs were assessed on metastatic or primary tumor samples. High TILs levels (>5%) were independently associated with longer PFS and OS. TILs levels were higher in primary tumours than in metastases (p = 0.009), with significant variation by metastatic site. These findings underscore the potential of TILs as prognostic biomarkers in HER2+ mBC, necessitating further prospective studies.

STAT3-mediated upregulation of TRIM6 promotes hepatocellular carcinoma invasion through the DDX58-Snail1 axis

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy with poor prognosis, driven by complex molecular mechanisms that remain inadequately understood. Among these, the ubiquitin–proteasome system plays a crucial role in regulating protein stability and function, with E3 ubiquitin ligases emerging as key players in cancer progression. Here, we identify Tripartite Motif-containing 6 (TRIM6), an E3 ubiquitin ligase, as a critical regulator of HCC metastasis. We demonstrate that TRIM6 is significantly upregulated in HCC tissues and correlates with poor overall survival. Mechanistically, we uncover that STAT3 directly regulates TRIM6 by binding to its promoter and enhancing its transcription. Functionally, TRIM6 promotes epithelial-mesenchymal transition (EMT) and cell invasion by upregulating the key EMT transcription factor Snail1. Importantly, we reveal that TRIM6 interacts with and ubiquitinates DDX58 (RIG-I), leading to its proteasomal degradation. The degradation of DDX58 by TRIM6 alleviates its inhibitory effects on Snail1, thereby facilitating EMT and enhancing the invasive potential of HCC cells. These findings establish the STAT3-TRIM6-DDX58-Snail1 axis as a pivotal pathway in HCC progression, offering novel insights into the molecular underpinnings of HCC metastasis and highlighting TRIM6 as a potential therapeutic target and prognostic biomarker in HCC.

Serum miR-30c serves as potential biomarkers for the diagnosis and prognosis of gastric cancer

ABSTRACT Gastric cancer (GC)，the fourth leading cause of cancer-related deaths globally and thus early detection, is considered critical for diagnosis and treatment of this disease. It is well known that measurement of microRNA (miRNA) may serve as diagnostic and prognostic biomarker for GC. The aim of this study was to determine whether miR-30c was present in patients with gastric cancer and to correlate relative expression with patient survival. A total of 162 GC patients and 150 healthy controls were recruited. miR-30c levels were quantified in serum using quantitative real-time PCR(QRT-PCR). The sensitivity and specificity of circulating miR-30c was compared to carbohydrate antigen (CA) CA72–4, CA19–9, and carcinoembryonic antigen (CEA), 3 known markers associated with GC. QRT-PCR demonstrated downregulation of gene expression of miR-30c in GC patients. Downregulation of miR-30c gene expression was significantly correlated with stage of cancer, lymphatic metastasis, and distal metastasis. The sensitivity to detect GC of miR-30c, CA72–4, CA19–9, and CEA in serum of GC was 80%, 43%, 21%, and 42%, respectively, while specificity was 89%, 57%, 30%, and 78% respectively. Kaplan-Meier survival analysis showed that the presence of low gene expression of miR-30c was effective in predicting poor prognosis in GC patients. Our data suggest that circulating serum miR-30c concentrations may serve as a reliable biomarker for GC occurrence. (212words)

Serum peroxiredoxin 2 emerges as a predictive biomarker of poor neurological outcome and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a prospective cohort study.

Peroxiredoxin 2 (Prdx2), an oxidative mediator, participates in acute brain injury. Here, serum Prdx2 levels were measured in order to assess its prognostic significance in aneurysmal subarachnoid hemorrhage (aSAH). In this prospective cohort study, serum Prdx2 levels were detected in 100 controls and 161 patients with aSAH. The modified Fisher scale (mFisher) and World Federation of Neurological Surgeons Scale (WFNS) were selected as two severity metrics. Post-aSAH 6-month Glasgow outcome scale (GOS) score of 1-3 was termed as poor prognosis. Poor prognosis and delayed cerebral ischemia (DCI) were chosen as two outcome variables of interest. Severity correlation and prognosis association with serum Prdx2 levels were investigated using multiple factorial approaches. Patients had markedly higher serum Prdx2 levels than controls. Serum Prdx2 levels, in independent correlation with WFNS scores and mFisher scores, were independently associated with DCI, poor prognosis, continuous GOS scores and ordinal GOS scores. Serum Prdx2 levels and two other independent predictors, that is WFNS scores and mFisher scores, were merged to form two models for predicting DCI and poor prognosis respectively. The two models were visually represented via the nomogram, and occupied satisfactory validity, stability and discrimination efficiency under decision curve, calibration curve and receiver operating characteristic curve. Serum Prdx2 levels of substantial promotion after aSAH are firmly linked to severity, DCI and bad 6-month prognosis of patients, strengthening serum Prdx2 as a useful prognostic biomarker of aSAH.

DNA glycosylase (NEIL3) overexpression associated with low tumor immune infiltration and poor overall patient survival in endometrial cancer

Endometrial cancer (EC) is the most common gynecological malignancy. Although prognosis is favorable for patients with an early-stage disease, those with recurrent or more advanced disease have low response rates to chemotherapy and poor clinical outcomes. Previously, we have shown that DNA repair gene (NEIL3) is required for retaining replication fork integrity during replication stress. Here, we examined whether the overexpression of NEIL3 in endometrial cancer associated with altered genomic instability, tumor immunogenicity and anti-tumor immunity in endometrial tumor. In this study, we show that endometrial cancer patients with tumors that a have high NEIL3 expression associated with worse overall survival (OS) outcomes in patients. In addition, tumor with high NEIL3 expression is associated with high number of mutation and chromosomal instability. Furthermore, NEIL3 expression in EC tumors positively correlated with mutation of DNA polymerase eta (POLE) and TP53 as well as high expression of replicative polymerases genes (POLE, POLD1 and POLA1). In contrast, tumor with high NEIL3 expression exhibit low tumor immunogenicity and poor anti-tumor immune cell infiltration. Our findings may have important clinical implications for utilizing NEIL3 as a potential prognostic biomarker to stratify EC patients and as a target to enhance immunotherapy response in endometrial cancer. However, our NEIL3 overexpression associated observation still requires further experimental-based scientific validation studies.

Stage-specific dynamics of macular pigment optical density as a prognostic biomarker in epiretinal membrane surgery.

To explore macular pigment optical density (MPOD) dynamics in stage 2 and stage 3 epiretinal membranes (ERMs) and to evaluate its pre and postoperative modifications. Furthermore, the study assessed the potential of MPOD as a prognostic biomarker in ERM management. A cohort of stage 2 (n=21) and 3 (n=20) ERM patients, matched for age and gender, underwent clinical evaluation at baseline and postoperative follow-up. Correlations between MPOD and optical coherence tomography parameters were analysed within each group. Postoperative MPOD levels significantly differed between stage 2 and 3 ERM patients (p=0.027). Changes in MPOD over time (ΔMPOD) were significantly greater in stage 3 compared with stage 2 participants (p=0.018). In stage 2, ΔMPOD correlated with changes in best-corrected visual acuity (ΔBCVA) (r=0.398, p=0.074) and demonstrated a strong correlation with changes in outer nuclear layer thickness (r=0.672, p<0.001). In stage 3, ΔMPOD exhibited a significant negative correlation with changes in central foveal thickness (r=-0.547, p=0.013) and a positive correlation with ΔBCVA (r=0.510, p=0.022). MPOD exhibited stage-specific dynamics and significant postoperative changes. Correlation between ΔMPOD and ΔBCVA in both stages highlights its potential role as a prognostic functional biomarker.

Uncovering key regulatory pathways and prognostic biomarkers in the tumor microenvironment of high-grade serous ovarian cancer through single-cell RNA sequencing and experimental validation

BackgroundHigh-grade serous ovarian cancer (HGSOC) is a leading cause of cancer-related deaths among women globally. This study aims to identify novel regulatory targets and signaling pathways that modulate the tumor microenvironment (TME) in HGSOC, focusing on the pleiotrophin (PTN) signaling pathway and syndecan 4 (SDC4) expression as potential biomarkers for prognosis.MethodsBioinformatics analysis was conducted on single-cell RNA sequencing (scRNA-seq) data (GSE146026) of HGSOC to investigate the TME. The data were subjected to unsupervised clustering to classify cell types within the TME, revealing eight distinct clusters representing various cell types. Cell-cell interactions were analyzed using the CellChat tool. Additionally, TCGA datasets were used to validate the expression of SDC4 and its association with clinical outcomes. The functional enrichment of differentially expressed genes (DEGs) between high and low SDC4 expression groups was performed to uncover associated pathways. Experimental validation was carried out using quantitative real-time PCR (qRT-PCR) and Western blotting on ovarian cancer cell lines (OVCAR3 and SKOV3).ResultsThe unsupervised clustering analysis revealed eight major cell types: macrophages, fibroblasts, ovarian cancer cells, B cells, T cells, dendritic cells, and erythrocytes. CellChat analysis highlighted significant interactions between these cell types, suggesting a complex TME. Further exploration identified PTN signaling as a key regulator within the HGSOC TME. Validation using TCGA datasets revealed upregulation of SDC4 in ovarian cancer tissues, with high SDC4 expression correlating with shorter overall survival. DEGs between high and low SDC4 expression groups were linked to the PI3K-Akt and MAPK signaling pathways, cell junction organization, and focal adhesion. qRT-PCR validation confirmed a significant upregulation of SDC4 in OVCAR3 and SKOV3 ovarian cancer cell lines, with expression levels 3.8- to 4.2-fold higher than control cells (p&amp;lt;0.01), supporting the computational predictions.ConclusionThis study highlights the PTN signaling pathway as a potential therapeutic target in HGSOC and identifies SDC4 as a prognostic biomarker for poor patient outcomes. Our findings offer new insights into the molecular mechanisms governing the TME of HGSOC, although further investigation is needed to fully elucidate the functional role of SDC4 in ovarian cancer progression.