Candidate Prognostic Biomarker Research Articles

Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes

We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72 , 38 GRN , and 25 MAPT ) and 55 symptomatic (27 C9orf72 , 17 GRN , and 11 MAPT ) mutation carriers as well as 76 mutation-negative controls (“noncarriers”). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer’s disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.

Cyclin E Expression and p16 Loss Are Strong Prognostic Biomarkers in Primary Invasive Cutaneous Melanoma.

The traditional melanoma staging system is not ideal for predicting patients' individual risk of disease recurrence and death. Subsequently, suboptimal adjuvant treatment may be offered. Hence, identification of biomarkers to optimize risk stratification is warranted. Cyclins and cyclin-dependent kinase inhibitors, key players in the cell cycle regulation, are candidate prognostic biomarkers. Herein, their expression and prognostic value in melanoma are studied. The expression of Cyclin D1, Cyclin E, p16, p21, and p27 were assessed using immunohistochemistry in samples from 59 patients with melanoma and correlated with clinicopathological parameters, as well as relapse-free survival (RFS) and overall survival (OS). Cyclin E expression in the nucleus, observed in 19% of patients, was correlated with Breslow thickness (p=0.017), whereas p16 loss in the cytoplasm and nucleus, detected in 68% and 61% of patients respectively, was correlated with Breslow thickness (p=0.001) and ulceration (p=0.035). The high expression of Cyclin E in the nucleus (p<0.001) and the loss of p16 in the cytoplasm (p=0.012) and nucleus (p=0.002) were associated with shorter OS. Cyclin E in the nucleus was a prognostic factor for RFS and OS at least as strong as Breslow thickness. Expression of Cyclin E and loss of p16 appeared to be significant prognostic biomarkers, with Cyclin E being prognostically at least as strong as Breslow thickness regarding RFS and OS. Both biomarkers may potentially be used to improve stratification of individual patient's risk of recurrent disease and survival, and subsequently optimize adjuvant treatment.

KLRD1 (CD94): A Prognostic Biomarker and Therapeutic Candidate in Head and Neck Squamous Cell Carcinoma.

Background: Killer Cell Lectin Like Receptor D1 (KLRD1) plays a crucial role in antitumor immunity. However, its expression patterns across various cancers, its relationship with patient prognosis, and its potential as an immunotherapy target remain inadequately understood. Methods: We analyzed KLRD1 expression across various cancer types using multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, correlating it with patient prognosis. Single-cell RNA sequencing data were employed to further explore KLRD1 expression in natural killer (NK) cells and exhausted CD8+ T cells (CD8Tex). Functional enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) identified the biological processes and pathways associated with KLRD1. Immune infiltration analysis, conducted via CIBERSORT, assessed the relationship between KLRD1 expression and immune cell infiltration within the tumor microenvironment. Furthermore, the Tracking Tumor Immunophenotype (TIP) meta-server and Easier tool were employed to assess the role of KLRD1 in the cancer immunity cycle and to predict immunotherapy responses. Drug sensitivity was predicted using tools like CellMiner and the Genomics of Drug Sensitivity in Cancer (GDSC) database to explore the link between KLRD1 expression and responsiveness to various anticancer drugs. Results: KLRD1 exhibits significant differential expression and strong prognostic value across cancers, particularly as an independent prognostic factor in head and neck squamous cell carcinoma (HNSC). Single-cell analysis revealed high expression of KLRD1 in NK and CD8Tex cells, indicating its critical role in antitumor immune responses. Functional enrichment analyses showed that KLRD1 is involved in several immune-related signaling pathways, including NK cell-mediated cytotoxicity and T cell receptor pathways. Immune infiltration analysis further confirmed a positive correlation between KLRD1 expression and the infiltration of various immune cells. Moreover, higher KLRD1 expression in HNSC is associated with enhanced immune pathway activity, increased sensitivity to cell division inhibitors, and the identification of arachidonyltrifluoromethane as a potential compound to counteract its oncogenic effects. Conclusion: In HNSC, KLRD1 is a key prognostic marker and potential target for personalized immunotherapy.

STEAP3 is a potential preliminary prognostic biomarker of glioblastoma

Six-transmembrane epithelial antigen of prostate 3 (STEAP3), a member of the iron regulation protein family, is characterized by a high recurrence rate and a short survival time. Nevertheless, studies investigating the role of STEAP3 in glioblastoma (GB) are scarce. In this study, the prognostic value of STEAP3 was evaluated utilizing mRNA expression profiles from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases as the validation and training cohorts, respectively. Moreover, differentially expressed genes were subjected to a functional enrichment analysis. The relationship between STEAP3 and the tumor microenvironment (TME) was examined. The immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) score were used to investigate response to immunotherapy. In all cohorts, GB patients with higher STEAP3 expression levels exhibited shorter overall survival (OS). Additionally, STEAP3-associated genes were primarily implicated in leukocyte migration, the JAK-STAT signaling pathway, and the cytokine-mediated signaling pathway. In the STEAP3 high-expression group, the ESTIMATEScore, ImmuneScore, StromalScore, and IPS were significantly higher. Overall, our results highlighted that STEAP3 might serve as a candidate prognostic biomarker for GB. Additionally, it might regulate the TME and influence GB metastasis.

A Comprehensive Proteomic and Bioinformatic Analysis of Human Spinal Cord Injury Plasma Identifies Proteins Associated with the Complement Cascade and Liver Function as Potential Prognostic Indicators of Neurological Outcome.

Spinal cord injury (SCI) is a major cause of disability, with complications postinjury often leading to lifelong health issues with the need for extensive treatment. Neurological outcome post-SCI can be variable and difficult to predict, particularly in incompletely injured patients. The identification of specific SCI biomarkers in blood may be able to improve prognostics in the field. This study has utilized proteomic and bioinformatic methodologies to investigate differentially expressed proteins in plasma samples across human SCI cohorts with the aim of identifying candidate prognostic biomarkers and biological pathway alterations that relate to neurological outcome. Blood samples were taken, following informed consent, from American Spinal Injury Association impairment scale (AIS) grade C "improvers" (those who experienced an AIS grade improvement) and "nonimprovers" (no AIS change) and AIS grade A and D at <2 weeks ("acute") and ∼3 months ("subacute") postinjury. The total protein concentration from each sample was extracted, with pooled samples being labeled and nonpooled samples treated with ProteoMiner™ beads. Samples were then analyzed using two 4-plex isobaric tag for relative and absolute quantification (iTRAQ) analyses and a label-free experiment for comparison before quantifying with mass spectrometry. Data are available via ProteomeXchange with identifiers PXD035025 and PXD035072 for the iTRAQ and label-free experiments, respectively. Proteomic datasets were analyzed using OpenMS (version 2.6.0). R (version 4.1.4) and, in particular, the R packages MSstats (version 4.0.1) and pathview (version 1.32.0) were used for downstream analysis. Proteins of interest identified from this analysis were further validated by enzyme-linked immunosorbent assay. The data demonstrated proteomic differences between the cohorts, with the results from the iTRAQ approach supporting those of the label-free analysis. A total of 79 and 87 differentially abundant proteins across AIS and longitudinal groups were identified from the iTRAQ and label-free analyses, respectively. Alpha-2-macroglobulin, retinol-binding protein 4 (RBP4), serum amyloid A1, peroxiredoxin 2 (PRX-2), apolipoprotein A1, and several immunoglobulins were identified as biologically relevant and differentially abundant, with potential as individual candidate prognostic biomarkers of neurological outcome. Bioinformatics analyses revealed that the majority of differentially abundant proteins were components of the complement cascade and most interacted directly with the liver. Many of the proteins of interest identified using proteomics were detected only in a single group and therefore have potential as binary (present or absent) biomarkers, RBP4 and PRX-2 in particular. Additional investigations into the chronology of these proteins and their levels in other tissues (cerebrospinal fluid in particular) are needed to better understand the underlying pathophysiology, including any potentially modifiable targets. Pathway analysis highlighted the complement cascade as being significant across groups of differential functional recovery.

Longitudinal clinical and proteomic diabetes signatures in women with a history of gestational diabetes.

We characterized the longitudinal serum protein signatures of women 6 and 10 years after having gestational diabetes mellitus (GDM) to identify factors associated with the development of type 2 diabetes mellitus (T2D) and prediabetes in this at-risk post-GDM population, aiming to discover potential biomarkers for early diagnosis and prevention of T2D. Our study identified 75 T2D-associated serum proteins and 23 prediabetes-associated proteins, some of which were validated in an independent T2D cohort. Machine learning (ML) performed on the longitudinal proteomics highlighted protein signatures associated with progression to post-GDM diabetes. We also proposed prognostic biomarker candidates that were differentially regulated in healthy participants at 6 years postpartum who later progressed to having T2D. Our longitudinal study revealed T2D risk factors for post-GDM populations who are relatively young and healthy, providing insights for clinical decisions and early lifestyle interventions.

Circulating Galectin-3: A Prognostic Biomarker in Hepatocellular Carcinoma.

Galectin-3 plays critical roles in the adhesion, proliferation, and differentiation of tumor cells. Recent data have suggested that galectin-3 plays a role in the development of hepatocellular carcinoma (HCC); however, its prognostic value has not been validated. The aim of our study was to evaluate the clinical and prognostic value of galectin-3 in patients with HCC. We prospectively enrolled and collected clinicopathologic data and serum samples from 767 patients with HCC between 2001 and 2014 at The University of Texas MD Anderson Cancer Center. Two hundred patients without HCC were also enrolled and had data collected. The Kaplan-Meier method was used to estimate overall survival (OS) distributions. The median OS in this cohort was 14.2 months (95% CI, 12-16.1). At the time of analysis, the 1-year OS rate was 45% (95% CI, 0.4-0.51) among patients with high galectin-3 levels and 59% (95% CI, 0.54-0.63) among patients with low galectin-3 levels. OS was significantly inferior in patients with high galectin-3 levels than in patients with lower galectin-3 levels (median OS: 10.12 vs. 16.49 months; p = 0.0022). Additionally, the multivariate model showed a significant association between high galectin-3 level and poor OS (hazard ratio [HR] = 1.249; 95% CI, 1.005-1.554). Comparison between low ( n = 464 patients) and high ( n = 302 patients) galectin-3 levels showed that mean serum galectin-3 levels were significantly higher in patients with HCC who had hepatitis C virus (HCV) infection ( p = 0.0001), higher Child-Pugh score (CPS) ( p = 0.0009), and higher Cancer of the Liver Italian Program (CLIP) score ( p = 0.0015). Our study shows that serum galectin-3 level is a valid prognostic biomarker candidate.

Urinary biomarkers for active Lupus Nephritis that have survived independent validation across cohorts

Most reported biomarkers for lupus nephritis (LN) have not been independently validated across cohorts. Moreover, many of the documented biomarker candidates have been reported to be elevated in LN compared to healthy controls. However, biomarkers that distinguish patients with active LN (ALN) from inactive systemic lupus erythematosus (iSLE) hold significant clinical utility. Hence, our review attempts to identify urine protein biomarkers for LN that have been independently validated across two or more cohorts and exhibit good diagnostic potential for distinguishing ALN from iSLE. PubMed and OVID were screened for studies assessing the diagnostic value of urinary biomarkers in patients with ALN compared to iSLE. Forty peer-reviewed articles were evaluated, encompassing urine biomarker data from 3,411 distinct patients. Of the 32 candidate biomarkers identified, fourteen were repeatedly reported/tested in four or more papers each, namely ALCAM, CCL2 (MCP1), CD163, HAVCR1 (KIM-1), HPGDS, ICAM-1 (CD54), ICAM-2 (CD102), IGFBP-2, LCN2, NCAM-1 (CD56), SELE (E-Selectin), SELL (L-Selectin), TNFSF12 (TWEAK), and VCAM-1, with most exhibiting C-statistics of 0.80 or more across multiple studies when discriminating patients with ALN from iSLE. The 32 reproducibly elevated biomarkers for active LN mapped to nine functional categories. The urinary proteins reported here promise to serve as a liquid biopsy for ALN. Besides representing potential candidates for diagnostic, monitoring, predictive, and prognostic biomarkers in LN, they also provide a window into potential molecular processes within the kidney that may be driving LN. Thus, ongoing advances in proteomics, which offer wider proteome coverage at increased sensitivity, are likely to further reshape our perspective of urinary biomarkers for LN.

Proteogenomic Characterization of Early Intrahepatic Recurrence after Curative-Intent Treatment of Colorectal Liver Metastases.

Clinical and pathological factors are insufficient to accurately identify patients at risk of early recurrence after curative-intent treatment of colorectal liver metastases (CRLM). This study aimed to identify candidate prognostic proteogenomic biomarkers for early intrahepatic recurrence after curative-intent resection of CRLM. Patients diagnosed with intrahepatic recurrence within 6 months of liver resection were categorized as the "early recurrence" group, while those who achieved a recurrence-free status for 10 years were designated as "durable remission". Comprehensive genomic and proteomic profiling of fresh frozen samples from these prognostically distinct groups was performed using the TruSight Oncology 500 assay and label-free data-dependent acquisition liquid chromatography-mass spectrometry. Genetic alterations were identified in 117 of the 523 profiled genes in patients with early recurrence. The most common somatic mutations linked to early recurrence were TP53 (88%), APC (71%), KRAS (38%), and SMAD4 (21%). SMAD4 alterations were absent in samples from patients with a durable remission. Calponin-2, versican core protein, glutathione peroxidase 3, fibulin-5, and amyloid-β precursor protein were upregulated more than 2-fold in early recurrence. Exploratory analysis of these proteogenomic biomarkers suggests that SMAD4, calponin-2, and glutathione peroxidase 3 may have the potential to predict early recurrence, enabling improved prognostication and precision oncology in CRLM.

Gamma-butyrobetaine hydroxylase (BBOX1) exerts suppressive effects on HepG2 hepatoblastoma cells.

Gamma-butyrobetaine hydroxylase (BBOX1) plays a pivotal role in catalyzing the final stage of L-carnitine biosynthesis. Recently, increasing number of studies have reported that BBOX1 is weakly expressed in tumor cells and exhibits antitumor activity. The role of BBOX1 in Hepatoblastoma (HB) has yet to be determined. To substantiate this, we have investigated BBOX1 expression and its clinical relevance in HB, and explored how BBOX1 might inhibit the occurrence and development of HB. The GSE104766 and GSE131329 datasets were used to screen for the core gene BBOX1 in HB and to analyze differences in expression between hepatoblastoma and normal tissues. Based on the clinicopathological features of the GSE131329 dataset, the connections between the expression of BBOX1 and the clinicopathological feature of HB patients were determined. After BBOX1 was overexpressed, CCK-8 and colony formation assays were employed to assess cell proliferation and wound healing experiments were utilized to assess cell migration. The presence of cell apoptosis, cell cycle changes, and reactive oxygen species (ROS) was assayed using flow cytometry. Compared with normal tissues, the expression of BBOX1 in hepatoblastoma tissues was notably decreased. Dysregulated expression of BBOX1 was indicated as a prognostic risk factor closely linked to clinical stag of patients with HB. Furthermore, following BBOX1 overexpression, cell proliferation and migration are decreased, the cell cycle is arrested, and ROS are attenuated. BBOX1 has suppressive effects on HepG2 cells, potentially through its ability to hinder cancer cell proliferation, arrest cell cycle progression, and decrease ROS levels, suggesting its potential as a novel prognostic biomarker and therapeutic candidate for hepatoblastoma.

Revealing alterations in heart rate fluctuations during the progression of Chagas disease.

The heart rate variability (HRV) continually evolves throughout life, reflecting modifications in the architecture of the sinoatrial node (SAN) and in the regulation of heart rate by the autonomic nervous system (ANS). Both can be considerably affected by Chagas disease, causing important changes in the complex nature of HRV. We aim to evaluate the ability of an index based on the false nearest neighbors method (FN10) to reflect these changes during disease progression. We perform a retrospective, descriptive, and cross-sectional study analyzing HRV time series of participants with Chagas disease. We determine the dependence of FN10 on age and sex in a healthy population, and then evaluate FN10 in individuals with Chagas disease. In the healthy population, FN10 has a scaling behavior with age, which is independent of sex. In Chagas disease, some individuals show FN10 values significantly above those seen in the healthy population. We relate the findings to the pathophysiological mechanisms that determine the progression of the disease. The results indicate that FN10 may be a candidate prognostic biomarker for heart disease.

RGS4 inhibits glioma cells sensitivity to radiotherapy and temozolomide by regulating ferroptosis

Background Chemoradiotherapy is the major means in the treatment of gliomas followed by surgery. Ferroptosis has been shown to play an important role in carcinogenesis by many studies. However, its underlying effect on chemoradiotherapy sensitivity in gliomas remains unclear. Methods The genetic and clinical information and ferroptosis-related genes were downloaded from The Cancer Genome Atlas (TCGA) database. Gene Expression Profiling Interactive Analysis (GEPIA) was used to perform hub gene expression and survival analysis. Cell Counting Kit 8 (CCK-8), colony formation, 5-Ethynyl-2′-Deoxyuridine (EdU), Transwell and chemoradiotherapy sensitivity experiments were performed to confirm the biological function of RGS4 in glioma cells. The molecular mechanism of RGS4 on ferroptosis in gliomas was explored in vitro. Results 385 ferroptosis-related genes were identified via bioinformatics analysis. 16 differential expressed genes (DEGs) were identified as radiation-related genes. Among them, RGS4, HSPA5, and SLC40A1 had prognostic values in further analysis. The calculated risk score could significantly distinguish the high-risk population. Moreover, RGS4 expression was closely related with immune infiltration and regulators. RGS4 knockdown could inhibit the proliferation and migration of glioma cells. Down-regulation of RGS4 expression induced ferroptosis to promote cancer sensitivity to chemoradiotherapy. Conclusions A three-gene signature was developed in a risk-score model, which could be used to predict the prognosis of glioma patients. RGS4 is dysregulated in many types of cancers, and is a candidate prognostic biomarker for many types of cancers. Moreover, RGS4 may be a target for predicting and enhancing the chemoradiotherapy sensitivity of gliomas.

NFS1 as a Candidate Prognostic Biomarker for Gastric Cancer Correlated with Immune Infiltrates.

Cysteine desulfurase (NFS1) is closely associated with the occurrence and development of human tumors, but its relationship with the prognosis and immunity of gastric cancer (GC) patients remains unclear. To study the relationship between NFS1 and GC, GC-related data of TCGA were downloaded and analyzed. At the same time, Tumor Immune Estimation Resource (TIMER) and Kaplan‒Meier Plotter were used for relevant online analysis. Clinical samples were collected for immunohistochemical testing to validate the results. The mRNA and protein levels of NFS1 in GC tissues were significantly higher than those in normal tissues. In terms of the operating characteristic curve (ROC), the area under the curve (AUC) was 0.793, indicating that NFS1 had a high diagnostic value for GC. Further analysis showed that NFS1 expression was highly correlated with the depth of tumor invasion, lymph node metastasis, and tumor stage. Survival analysis showed that patients with high expression of NFS1 had a poorer prognosis, and NFS1 was an independent risk factor. Enrichment analysis by GO, KEGG, and GSEA showed that NFS1 was enriched in immune-related pathways. The expression of NFS1 was significantly positively correlated with the proportion of macrophages M0 and plasma cells but negatively correlated with the proportion of B cells memory, monocytes, and mast cells resting. In addition, NFS1 expression was significantly correlated with TMB levels and responses to immunotherapy. Our results suggest that NFS1 may be a potential biomarker for the diagnosis and prediction of prognosis and immunotherapy efficacy in GC.

WTAP/CCND1 axis accelerates esophageal squamous cell carcinoma progression by MAPK signaling pathway.

N6-methyladenosine (m6A) methylation, as a new regulatory mechanism, has been reported to be involved in diverse biological processes in recent years. Wilms tumor 1-associated protein (WTAP), as the key member of m6A methylation, has been proven to participate in tumorigenesis. Here, we studied the expression of WTAP and its potential mechanism involved in the development of esophageal squamous cell carcinoma (ESCC). We detected the expression of WTAP and its correlation with clinicopathological features, and we determined the function of WTAP on ESCC cells by MTS assay, colony formation, scratch wound healing assay, Transwell assay, and subcutaneous xenograft assay. We used mRNA sequencing technology to screen candidate downstream targets for WTAP and investigated the underlying mechanism of CCND1 in ESCC promotion through a series of rescue assays. An elevated expression of WTAP in ESCC malignancy indicated a worse prognosis. WTAP promoted the proliferation and metastasis of ESCC cells, and CCND1 was identified as the potential downstream effecter of WTAP. Moreover, WTAP modulated ESCC progression through a MAPK pathway-dependent pattern. Our research suggested that WTAP promoted both proliferation and metastasis of ESCC by accelerating the expression of CCND1 via the MAPK signaling pathway, indicating that WTAP may be a candidate prognostic biomarker for ESCC and also will be a promising strategy for ESCC cancer therapy.

Multi-Omics Profiles of Chronic Low Back Pain and Fibromyalgia - Study Protocol.

Chronic low back pain (CLBP) and fibromyalgia (FM) are leading causes of suffering, disability, and social costs. Current pharmacological treatments do not target molecular mechanisms driving CLBP and FM, and no validated biomarkers are available, hampering the development of effective therapeutics. Omics research has the potential to substantially advance our ability to develop mechanism-specific therapeutics by identifying pathways involved in the pathophysiology of CLBP and FM, and facilitate the development of diagnostic, predictive, and prognostic biomarkers. We will conduct a blood and urine multi-omics study in comprehensively phenotyped and clinically characterized patients with CLBP and FM. Our aims are to identify molecular pathways potentially involved in the pathophysiology of CLBP and FM that would shift the focus of research to the development of target-specific therapeutics, and identify candidate diagnostic, predictive, and prognostic biomarkers. We are conducting a prospective cohort study of adults ≥18 years of age with CLBP (n=100) and FM (n=100), and pain-free controls (n=200). Phenotyping measures include demographics, medication use, pain-related clinical characteristics, physical function, neuropathiccomponents (quantitative sensory tests and DN4 questionnaire), pain facilitation (temporal summation), and psychosocial function as moderator. Blood and urine samples are collected to analyze metabolomics, lipidomics and proteomics. We will integrate the overall omics data to identify common mechanisms and pathways, and associate multi-omics profiles to pain-related clinical characteristics, physical function, indicators of neuropathic pain, and pain facilitation, with psychosocial variables as moderators. Our study addresses the need for a better understanding of the molecular mechanisms underlying chronic low back pain and fibromyalgia. Using a multi-omics approach, we hope to identify converging evidence for potential targets of future therapeutic developments, as well as promising candidate biomarkers for further investigation by biomarker validation studies. We believe that accurate patient phenotyping will be essential for the discovery process, as both conditions are characterized by high heterogeneity and complexity, likely rendering molecular mechanisms phenotype specific.

Prognostic and Potential Therapeutic Roles of PRKDC Expression in Lung Cancer.

PRKDC is a key factor involved in the ligation step of the non-homologous end joining pathway. Its dysfunction has proven to be a biomarker for radiosensitivity of cancer cells. However, the prognostic value of PRKDC and its underlying mechanisms have not been clarified yet. In this study, we found that PRKDC overexpressed in lung adenocarcinoma (LUAD) and is significantly related to unfavorable survival, while downregulation of PRKDC is link to inflamed tumor immune signature. Our further in vitro results also showed a potent antitumor efficacy of PRKDC inhibitors alone or combined with cisplatin in human lung cancer cells. This study demonstrated that PRKDC is a potential prognostic biomarker, immunotherapy target, and promising combination candidate for chemotherapy for lung cancer, and highlighted the potential of PRKDC-targeted inhibitors for the treatment of lung cancer.

Prognostic value of blood GRHL2 in patients with non-small-cell lung cancer after radiotherapy and chemotherapy.

Aim: We aimed to investigate the predictive value of the Grainyhead-like 2 (GRHL2) expression from circulating blood for recurrence, metastasis and overall death on patients with non-small-cell lung cancer (NSCLC).Materials & Methods: We collected blood samples from 122 patients who were admitted to our hospital for NSCLC.Results: Multivariable Cox proportional-hazards analysis in adjusted Model II showed that compared with GRHL2-negative expression, positive expression in patients with NSCLC was associated with increased death risk (HR=7.0, 95% CI: 2.1-20.9, p=0.03) and risk for composite end point (HR=8.2, 95% CI: 4.0-27.1, p <0.01).Conclusion: This study supported that elevated circulating GRHL2 expression might be considered as a candidate prognostic biomarker for poor prognosis among these NSCLC patients.

Immune checkpoint expression as prognostic biomarker candidates in non-small cell lung carcinoma patients.

Cancer immunotherapy has had an important role in oncologic therapeutics for patients with non-small cell lung cancer (NSCLC) using checkpoint inhibitors. We will explore the possible prognosis biomarker candidates such as: soluble OX40 (sOX40), OX40L (sOX40L), Glucocorticoid-induced tumor necrosis factor receptor family-related receptor (GITR), and their ligand (GITRL), 4-1BB or tumor necrosis factor receptor superfamily 9 (TNFRS9) and inducible T cell co-stimulator (ICOS) in peripheral blood of NSCLC patients. Fifty-eight patients were diagnosed with advanced NSCLC between January 2019 and March 2020. High sOX40 and low s4-1BB levels in smokers compared non-smoker NSCLC patients. Lower sOX40L levels were found in the male than female (p < 0.05). High sOX40 and sGITRL in stage III compared to the stage IV (p < 0.05). With follow-up at 21.4 months, 44.1% and 91.1% were alive in the sGITRhigh and sGITRlow groups, respectively (p = 0.02), and 73.3% and 27.7% were alive in the sGITRLhigh and sGITRLlow groups, respectively (p = 0.02). At 22 months, 38.7% and 92.3% were alive in the sOX40Lhigh and sOX40Llow groups, respectively (p = 0.01). sGITR, sGITRL, and sOX40L levels were potential prognostic biomarkers and could have an important role as new targets of immunotherapy in NSCLC patients. sGITR, sGITRL, sOX40L, and sOX40 levels were associated with smoking, sex, stage, and age in NSCLC.

Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics

High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SignificanceOC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate.

Exosomal noncoding RNAs: decoding their role in thyroid cancer progression.

Exosomes, as pivotal entities within the tumor microenvironment, orchestrate intercellular communication through the transfer of diverse molecules, among which non-coding RNAs (ncRNAs) such as miRNAs, lncRNAs, and circRNAs play a crucial role. These ncRNAs, endowed with regulatory functions, are selectively incorporated into exosomes. Emerging evidence underscores the significance of exosomal ncRNAs in modulating key oncogenic processes in thyroid cancer (TC), including proliferation, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunoediting. The unique composition of exosomes shields their cargo from enzymatic and chemical degradation, ensuring their integrity and facilitating their specific expression in plasma. This positions exosomal ncRNAs as promising candidates for novel diagnostic and prognostic biomarkers in TC. Moreover, the potential of exosomes in the therapeutic landscape of TC is increasingly recognized. This review aims to elucidate the intricate relationship between exosomal ncRNAs and TC, fostering a deeper comprehension of their mechanistic involvement. By doing so, it endeavors to propel forward the exploration of exosomal ncRNAs in TC, ultimately paving the way for innovative diagnostic and therapeutic strategies predicated on exosomes and their ncRNA content.