Reliable Prognostic Biomarkers Research Articles

Úloha imunoterapie pri liečbe hepatocelulárneho karcinómu

Hepatocellular carcinoma (HCC) represents the most common primary liver malignancy, accounting for approximately 75–80% of all liver cancer cases. The global incidence of hepatocellular carcinoma is increasing due to rising rates of underlying diseases, creating a significant cancer burden and a significant clinical challenge due to its often late presentation and limited effective treatment options. Immune checkpoint inhibitors have revolutionized the treatment approach in various malignancies. In the treatment of advanced hepatocellular carcinoma, immunotherapy has proven to be more effective than tyrosine kinase inhibitors, which have been a treatment option for a decade. Clinical trials such as the HIMALAYA and IMbrave150 have demonstrated significant survival benefits, showing superior efficacy compared to sorafenib. Despite these promising results, not all HCC patients respond to immunotherapy equally. There is a need to search for reliable prognostic and predictive biomarkers that can help predict which patients are most likely to benefit from immunotherapy, thereby personalizing treatment and improving outcomes. The purpose of this article is to provide a summary of clinical trials on immunotherapy for various stages of hepatocellular carcinoma.

Prognostic Value of Neutrophil-to-Eosinophil Ratio (NER) in Cancer: A Systematic Review and Meta-Analysis

Background: The identification of reliable prognostic biomarkers is crucial for optimizing cancer treatment strategies, especially in the era of personalized medicine. This systematic review and meta-analysis evaluate the prognostic significance of the neutrophil-to-eosinophil ratio (NER) in various cancer types, with a focus on its association with overall survival (OS) and progression-free survival (PFS). Methods: We conducted a systematic literature search across PubMed, Scopus, and Web of Science databases for studies published up to 28 July 2024. We performed the meta-analyses with the generic inverse variance method with a random effects model and reported hazard ratios (HR) with 95% confidence intervals (CI). Results: The comprehensive literature search identified 10 studies comprising 2351 patients. Pooled analyses demonstrated that elevated pretreatment NER levels were significantly correlated with poorer OS (HR: 1.74, 95% CI: 1.28–2.36, p < 0.001) and PFS (HR: 1.53, 95% CI: 1.21–1.95, p < 0.001). Subgroup analyses confirmed a consistent adverse association between high NER and OS across various tumor types and geographic locations, although results from studies conducted in the Far East did not reach statistical significance. Conclusions: This meta-analysis demonstrates that elevated NER is associated with poorer OS and PFS in cancer patients, suggesting its potential utility as a non-invasive prognostic marker. Further validation in large, prospective studies is warranted to establish NER’s role in guiding personalized treatment strategies across diverse oncologic contexts.

Deciphering the landscape of triple negative breast cancer from microenvironment dynamics and molecular insights to biomarker analysis and therapeutic modalities.

Triple negative breast cancer (TNBC) displays a notable challenge in clinical oncology due to its invasive nature which is attributed to the absence of progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor (HER-2). The heterogenous tumor microenvironment (TME) of TNBC is composed of diverse constituents that intricately interact to evade immune response and facilitate cancer progression and metastasis. Based on molecular gene expression, TNBC is classified into four molecular subtypes: basal-like (BL1 and BL2), luminal androgen receptor (LAR), immunomodulatory (IM), and mesenchymal. TNBC is an aggressive histological variant with adverse prognosis and poor therapeutic response. The lack of response in most of the TNBC patients could be attributed to the heterogeneity of the disease, highlighting the need for more effective treatments and reliable prognostic biomarkers. Targeting certain signaling pathways and their components has emerged as a promising therapeutic strategy for improving patient outcomes. In this review, we have summarized the interactions among various components of the dynamic TME in TNBC and discussed the classification of its molecular subtypes. Moreover, the purpose of this review is to compile and provide an overview of the most recent data about recently discovered novel TNBC biomarkers and targeted therapeutics that have proven successful in treating metastatic TNBC. The emergence of novel therapeutic strategies such as chemoimmunotherapy, chimeric antigen receptor (CAR)-T cells-based immunotherapy, phytometabolites-mediated natural therapy, photodynamic and photothermal approaches have made a significant positive impact and have paved the way for more effective interventions.

The role of NOP58 in prostate cancer progression through SUMOylation regulation and drug response.

Prostate cancer is one of the leading causes of cancer-related deaths in men. Its molecular pathogenesis is closely linked to various genetic and epigenetic alterations, including posttranslational modifications like SUMOylation. Identifying biomarkers that predict outcomes and specific therapeutic targets depends on a comprehensive understanding of these processes. With growing interest in SUMOylation as a mechanism affecting prostate cancer-related genes, this study aimed to investigate the central role of SUMOylation in prostate cancer prognostics, focusing on the significance of NOP58. We conducted a comprehensive bioinformatics analysis, integrating differential expression analysis, survival analysis, gene set enrichment analysis (GSEA), and single-cell transcriptomic analyses using data from The Cancer Genome Atlas (TCGA). Key genes were identified through intersections of Venn diagrams, Boralta algorithm signatures, and machine learning models. These signaling mechanisms were validated through experimental studies, including immunohistochemical staining and gene ontology analyses. The dual-gene molecular subtype analysis with SUMO1, SUMO2, and XPO1 genes revealed significant differences in survival outcomes across molecular subtypes, further emphasizing the potential impact of NOP58 on SUMOylation, a key post-translational modification, in prostate cancer. NOP58 overexpression was strongly associated with shorter overall survival (OS), progression-free interval (PFI), and disease-specific death in prostate cancer patients. Immunohistochemical analysis confirmed that NOP58 was significantly overexpressed in prostate cancer tissues compared to normal tissues. ROC curve analysis demonstrated that NOP58 could distinguish prostate cancer from control samples with high diagnostic accuracy. Gene Ontology analysis, along with GSVA and GSEA, suggested that NOP58 may be involved in cell cycle regulation and DNA repair pathways. Moreover, NOP58 knockdown led to increased BCL2 expression and decreased Ki67 levels, promoting apoptosis and inhibiting cell proliferation. Colony formation assays further showed that NOP58 knockdown inhibited, while its overexpression promoted, colony formation, highlighting the critical role of NOP58 in prostate cancer cell growth and survival. Additionally, NOP58 was linked to drug responses, including Methotrexate, Rapamycin, Sorafenib, and Vorinostat. NOP58 is a key regulator of prostate cancer progression through its mediation of the SUMOylation pathway. Its expression level serves as a reliable prognostic biomarker and an actionable therapeutic target, advancing precision medicine for prostate cancer. Targeting NOP58 may enhance therapeutic efficacy and improve outcomes in oncology.

Mitogen-activated protein kinase kinase kinase 1 facilitates the temozolomide resistance and migration of GBM via the MEK/ERK signalling.

Mitogen-Activated Protein Kinase Kinase Kinase 1 (MAP3K1) is overexpressed in gliomas; however, its clinical significance, biological functions, and underlying molecular mechanisms remain unclear. Abnormal overexpression of MAP3K1 in glioma is strongly associated with unfavourable clinicopathological characteristics and disease progression. MAP3K1 could potentially serve as a reliable diagnostic and prognostic biomarker for glioma. MAP3K1 silencing suppressed the migration but had no effect on the proliferation and cell death of Glioblastoma Multiforme (GBM) cells. MAP3K1 knockdown exacerbated the temozolomide (TMZ) induced inhibition of glioma cell proliferation and death of GBM cells. In addition, MAP3K1 knockdown combined with TMZ treatment significantly inhibited the growth and increased cell death in organoids derived from GBM patients. MAP3K1 knockdown reversed TMZ resistance of GBM in intracranial glioma model. In terms of molecular mechanisms, the phosphorylation level of ERK was significantly decreased by MAP3K1 silencing. No significant change in the JNK pathway was found in MAP3K1-silenced GBM cells. Inhibition of ERK phosphorylation suppressed the migration and enhanced the TMZ sensibility of GBM cells. MAP3K1 was correlated with the immune infiltration in glioma. MAP3K1 could facilitate the migration and TMZ resistance of GBM cells through MEK/ERK signalling.

AI-powered genomic mutation signature for predicting immune checkpoint inhibitor therapy outcomes in gastroesophageal cancer: a multi-cohort analysis

BackgroundImmune checkpoint inhibitors (ICIs) have significantly transformed the treatment of gastroesophageal cancer (GEC). However, the lack of reliable prognostic biomarkers hinders the ability to predict patient response to ICI therapy.MethodsIn this study, we engineered and validated a genomic mutation signature (GMS) utilizing an innovative artificial intelligence (AI) algorithm to forecast ICI therapy outcomes in GEC patients. We further explored immune profiles across subtypes through comprehensive multiomics analysis. Our investigation of drug sensitivity data from the Genomics of Drug Sensitivity in Cancer (GDSC) database led to the identification of trametinib as a potential therapeutic agent. We subsequently evaluated trametinib’s efficacy in AGS and MKN45 cell lines using Cell Counting Kit-8 (CCK8) assays and clonogenic experiments.ResultsWe developed a GMS by integrating 297 algorithms, enabling autonomous prognosis prediction for GEC patients. The GMS demonstrated consistent performance across three public cohorts, exhibiting high sensitivity and specificity for overall survival (OS) at 6, 12, and 18 months, as shown by Receiver Operator Characteristic Curve (ROC) analysis. Notably, the GMS surpassed traditional clinical and molecular features, including tumor mutational burden (TMB), programmed death-ligand 1 (PD-L1) expression, and microsatellite instability (MSI), in predictive accuracy. Low-risk samples exhibited elevated levels of cytolytic immune cells and heightened immunogenic potential compared to high-risk samples. Our investigation identified trametinib as a potential therapeutic agent. An inverse correlation was observed between GMS and trametinib IC50. Moreover, the high-risk-derived AGS cell line showed increased sensitivity to trametinib compared to the low-risk-derived MKN45 cell line.ConclusionThe GMS utilized in this study successfully demonstrated the ability to reliably predict the survival advantage for patients with GECs undergoing ICI therapy.

Potential Prognostic Role of Protein Kinase D Isoforms in Head and Neck Cancers.

Head and neck squamous cell carcinomas (HNSCC) are among the most common malignancies in men worldwide. Nevertheless, their clinical management is hampered by the limited availability of reliable predictive and prognostic biomarkers. Protein kinase D (PKD) isoforms contribute to major cellular processes. However, their potential role in HNSCC has not been studied systematically, which is the focus of this study. A total of 63 therapy-naive patients with squamous cell carcinoma were consecutively enrolled. Tissue microarray duplicate cores from each case were tested in situ for PKD1, PKD2, and PKD3 expression using immunohistochemistry, and the results were correlated with clinicopathological parameters. We found a high frequency of PKD1/PKD2 positive cases in oropharyngeal and PKD2 positive cases in laryngeal localizations. Only high PKD2 levels were statistically linked to elevated tumor grades, more advanced TNM (3-4) tumor stages, and p16INK4a expression, while elevated PKD3 levels were associated with favorable disease-specific survival. Both PKD2 and PKD3 have been proposed to promote tumor cell proliferation, migration/invasion, and angiogenesis. However, the role of PKD3 was elusive in some cancers. Our findings suggest that testing for PKD isotypes with immunohistochemistry may support the diagnostic estimation of tumor progression and prognosis in HNSCC with a potential therapeutic relevance.

GNAS, not a Highly Mutated Gene, Has Prognostic Significance and Carcinogenic Effects in Osteosarcoma.

Osteosarcoma is a prevalent and aggressive primary malignant bone tumor affecting children and adolescents. Despite advancements in sequencing technologies, there remains a lack of reliable prognostic biomarkers and effective targeted therapies for osteosarcoma. This study focuses on identifying key prognostic genes, particularly the role of GNAS, in osteosarcoma progression. Bioinformatics analyses were performed on osteosarcoma datasets from the Gene Expression Omnibus (GEO). Differential gene expression analysis, weighted correlation network analysis (WGCNA), and survival analysis identified potential prognostic hub genes. The expression and function of these genes were validated through immunohistochemistry and animal experiments. Specifically, the role of GNAS was investigated through siRNA-mediated knockdown in osteosarcoma cell lines and nude mice models. Five hub genes (PROP1, GNAS, CYP4F2, LHX3, CNGB1) were identified as significantly related to osteosarcoma prognosis. Among these, GNAS was found to be highly expressed in osteosarcoma tissues compared to normal tissues. Immunohistochemical analysis confirmed the elevated expression of GNAS in osteosarcoma samples. GNAS mutation analysis revealed a low mutation rate in osteosarcoma, suggesting its oncogenic role is independent of mutational status. Animal experiments demonstrated that knocking down GNAS significantly inhibited tumor growth and induced apoptosis in osteosarcoma cells. GNAS is highly expressed in osteosarcoma and associated with poor prognosis, acting as an oncogene in osteosarcoma progression. Targeting GNAS could be a potential therapeutic strategy for osteosarcoma. Further studies on GNAS-related signaling pathways may provide deeper insights into the molecular mechanisms driving osteosarcoma malignancy.

Prognostic Values of Ferroptosis-Related Proteins ACSL4, SLC7A11, and CHAC1 in Cholangiocarcinoma.

The epithelial malignant tumor known as cholangiocarcinoma (CCA) is most commonly found in Southeast Asia, particularly in northeastern Thailand. Previous research has indicated that the overexpression of acyl-CoA synthetase long-chain family member 4 (ACSL4), solute carrier family 7 member 11 (SLC7A11), and ChaC glutathione-specific γ-glutamylcyclotransferase (CHAC1) as ferroptosis-related proteins is associated with poorer prognosis in several cancers. The role of these three proteins in CCA is still unclear. The present study aimed to investigate the expression levels of ACSL4, SLC7A11, and CHAC1, all potential ferroptosis biomarkers, in CCA. The ACSL4, SLC7A11, and CHAC1 protein expression levels in 137 CCA tissues were examined using immunohistochemistry, while 61 CCA serum samples were evaluated using indirect ELISA. The associations between the expression levels of ACSL4, SLC7A11, and CHAC1 and patient clinicopathological data were evaluated to determine the clinical significance of these proteins. The expression levels of ACSL4, SLC7A11, and CHAC1 were assessed in CCA tissues. A significant association was observed between high ACSL4 levels and extrahepatic CCA, tumor growth type, and elevated alanine transferase (ALT). There was also a positive association between elevated SLC7A11 levels and tumor growth type. Additionally, the upregulation of CHAC1 was significantly associated with a shorter survival time in patients. High levels of ACSL4 and SLC7A11 in CCA sera were both significantly associated with advanced tumor stages and abnormal liver function test results, indicating that they could be used as a reliable prognostic biomarker panel in patients with CCA. The results of the present study demonstrated that the upregulation of ACSL4, SLC7A11, and CHAC1 could be used as a valuable biomarker panel for predicting prognosis parameters in CCA. Furthermore, ACSL4 and SLC7A11 could potentially serve as complementary markers for improving the accuracy of prognosis prediction when CCA sera is used. These less invasive biomarkers could facilitate effective treatment planning.

Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy

AimThe availability of disease-modifying therapies and newborn screening programs for spinal muscular atrophy (SMA) has generated an urgent need for reliable prognostic biomarkers to classify patients according to disease severity. We aim to identify cerebrospinal fluid (CSF) prognostic protein biomarkers in CSF samples of SMA patients collected at baseline (T0), and to describe proteomic profile changes and biological pathways influenced by nusinersen before the sixth nusinersen infusion (T302).MethodsIn this multicenter retrospective longitudinal study, we employed an untargeted liquid chromatography mass spectrometry (LC-MS)-based proteomic approach on CSF samples collected from 61 SMA patients treated with nusinersen (SMA1 n=19, SMA2 n=19, SMA3 n=23) at T0 at T302. The Random Forest (RF) machine learning algorithm and pathway enrichment analysis were applied for analysis.ResultsThe RF algorithm, applied to the protein expression profile of naïve patients, revealed several proteins that could classify the different types of SMA according to their differential abundance at T0. Analysis of changes in proteomic profiles identified a total of 147 differentially expressed proteins after nusinersen treatment in SMA1, 135 in SMA2, and 289 in SMA3.Overall, nusinersen-induced changes on proteomic profile were consistent with i) common effects observed in allSMA types (i.e. regulation of axonogenesis), and ii) disease severity-specific changes, namely regulation of glucose metabolism in SMA1, of coagulation processes in SMA2, and of complement cascade in SMA3.ConclusionsThis untargeted LC-MS proteomic profiling in the CSF of SMA patients revealed differences in protein expression in naïve patients and showed nusinersen-related modulation in several biological processes after 10 months of treatment. Further confirmatory studies are needed to validate these results in larger number of patients and over abroader timeframe.

Exploring the Prognostic Role of D-dimer Levels in Pancreatic Cancer: A Comprehensive Review of Clinicopathological Associations.

Pancreatic cancer is known for its dismal prognosis and high mortality rate, primarily due to late-stage diagnosis and aggressive disease progression. Finding reliable prognostic biomarkers is crucial in improving patient outcomes and guiding treatment strategies. D-dimer, a fibrin degradation product, has emerged as a potential biomarker of interest in various cancers due to its association with coagulation abnormalities. This comprehensive review investigates the prognostic role of D-dimer levels in pancreatic cancer by synthesizing current research and exploring its clinicopathological associations. Elevated D-dimer levels in pancreatic cancer patients have been linked to poorer clinical outcomes, including reduced overall survival and increased disease progression. The review examines how D-dimer levels correlate with tumor characteristics such as stage, grade, and metastatic spread, highlighting its potential utility as a prognostic marker. Additionally, the review addresses the methodological challenges in D-dimer measurement and the need for standardized protocols to enhance the reliability and applicability of results. Future research directions are identified, focusing on validating D-dimer's clinical utility and integrating it into routine practice for risk stratification and personalized treatment planning. By providing a comprehensive overview of D-dimer's prognostic value, this review aims to contribute to developing more effective management strategies for pancreatic cancer, ultimately improving patient care and outcomes.

Diagnostic Values of Ki67, Cox2, CD31, E-cadherin, VEGF, MMP2, and MMP9 Protein Expression in Human Melanoma

Background: Cutaneous melanoma, the most severe form of skin cancer, has an unpredictable behavior and a high mortality rate. Recent research has identified new biomarkers and their associations with certain histopathological features, offering essential insights into diagnosis, prognosis, and therapeutic strategies. Material and method: In this meticulously designed and executed study, we analyzed 85 formalin-fixed, paraffin-embedded (FFPE) tissue samples using the gold standard technique of immunohistochemistry (IHC) to characterize the protein expression profiles. We used a comprehensive panel of Ki67, Cox2, CD31, VEGF, MMP2, MMP9, and E-cadherin antibodies. Clinical stages were meticulously determined according to TNM classification, the thickness of the Breslow depth, and Clark levels. We employed robust statistical methods such as one-way ANOVA and curve estimation regression to analyze the data. The STRING database, a trusted resource, was used to identify protein-protein interactions and related pathways. Results: The results of our study unveiled novel pairwise positive correlations between CD31 and Ki67 (r = 0.72), and between VEGF and Ki67 protein expression (r = 0.63). We also found a significant inverse relationship between the expression of E-cadherin and some biomarkers, such as Ki67, CD31, and VEGF (p < 0.001 for all). Additionally, our findings revealed a strong positive association between the extent of tumor invasion and the expression levels of Ki67, CD31, and VEGF. The overexpression of these proteins was significantly correlated with advanced clinical stages (p < 0.001 for all). Conclusion: Our study suggests that the biomarkers we examined could be reliable potential diagnostic and prognostic biomarkers for cutaneous melanoma. These findings have the potential to significantly impact the diagnosis, prognosis, and treatment of this deadly disease, offering new avenues for improved patient care.

SEMA7A as a Novel Prognostic Biomarker and Its Correlation with Immune Infiltrates in Breast Cancer.

The role of Semaphorin 7a (SEMA7A) in the initiation and progression of different types of cancerous lesions has been extensively studied. However, the prognostic significance of SEMA7A, specifically in breast cancer (BC), lacks clarity. We conducted an evaluation on the relationship between SEMA7A and the prognosis, immune invasion and tumor mutation burden in different types of cancer by analyzing data from The Cancer Genome Atlas database. The present study focused on investigating the expression level, mutation, immune correlation and coexpression of SEMA7A in BC, utilizing various databases such as the University of Alabama at Birmingham Cancer data analysis portal, cBioPortal and tumor immune estimation resource. Survival analysis was carried out using the Kaplan-Meier Plotter. Furthermore, we employed the R software package to generate receiver operating characteristic (ROC) curves and nomograms. Notably, P<0.05 was considered to indicate statistical significance. Using pancancer analysis, it has been observed that the expression of SEMA7A is elevated in various types of cancer and is strongly correlated with the prognosis of different cancer types. SEMA7A also exhibits a significant association with the tumor mutation burden of diverse types of cancer. Moreover, SEMA7A displays a notable increase in BC cases, and was indicated to have a substantial association with the abundance of immune infiltration. In-depth survival analysis demonstrated that elevated levels of SEMA7A expression are notably linked to shorter overall survival and distant metastasis-free survival among patients with BC. The efficiency of SEMA7A as a reliable prognostic biomarker for BC has been substantiated by the validation of ROC curves and nomograms. SEMA7A has the potential to function as a prognostic indicator for BC, and its correlation with immune infiltration in BC is significant.

Identification of costimulatory molecule signatures for evaluating prognostic risk in non-small cell lung cancer

BackgroundNon-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality worldwide. Despite advances in treatment, prognosis remains poor, necessitating the identification of reliable prognostic biomarkers. Costimulatory molecules (CMs) have shown to enhance antitumor immune responses. We aimed to explore their prognostic signals in NSCLC. MethodsThis study is a combination of bioinformatics analysis and laboratory validation. Gene expression profiles from The Cancer Genome Atlas (TCGA), GSE120622, and GSE131907 datasets were collected. NSCLC samples in TCGA were clustered based on CMs using consensus clustering. We used LASSO regression to identify CMs-related signatures and constructed nomogram and risk models. Differences in immune cells and checkpoint expressions between risk models were evaluated. Enrichment analysis was performed for differentially expressed CMs between NSCLC and controls. Key results were validated using qRT-PCR and flow cytometry. ResultsNSCLC samples in TCGA were divided into two clusters based on CMs, with cluster 1 showing poor overall survival. Ten CMs-related signatures were identified using LASSO regression. NSCLC samples in TCGA were stratified into high- and low-risk groups based on the median risk score of these signatures, revealing differences in survival probability, drug sensitivity, immune cell infiltration and checkpoints expression. The area under the ROC curve values (AUC) for EDA, ICOS, PDCD1LG2, and VTCN1 exceeded 0.7 in both datasets and considered as hub genes. Expression of these hub genes was significance in GSE131907 and validated by qRT-PCR. Macrophage M1 and T cell follicular helper showed high correlation with hub genes and were lower in NSCLC than controls detected by flow cytometry. ConclusionThe identified hub genes can serve as prognostic biomarkers for NSCLC, aiding in treatment decisions and highlighting potential targets for immunotherapy. This study provides new insights into the role of CMs in NSCLC prognosis and suggests future directions for clinical research and therapeutic strategies.

Unraveling the obesity paradox in small cell lung cancer immunotherapy: unveiling prognostic insights through body composition analysis.

The advent of immunotherapy has changed the landscape of SCLC treatment, although the identification of reliable prognostic biomarkers remains a formidable challenge. Our objective was to investigate the prognostic implications of obesity and body composition in SCLC immunotherapy while seeking a straightforward anthropometric measure. This retrospective study analyzed data from patients with SCLC who underwent immunotherapy between 2019 and 2023. Body composition and waist circumference (WC) were analyzed using 3D slicer software on baseline CT images. Quantitative measures, including skeletal muscle index (SMI), total adipose tissue index (TATI), and other indicators at the L3 level, along with body shape index (BSI) and additional indicators based on WC, were obtained. The relationships between these indicators, response, PFS, OS, and their interconnections were examined. A total of 145 SCLC patients who received immunotherapy were identified, of whom 133 met the inclusion criteria. In univariate analysis, a BMI≥28 kg/m2 was associated with a PFS advantage (HR 0.42, p=0.04), but this trend vanished in multivariate analysis. Body measurements exhibited stronger correlations with adipose tissue content, with BSI showing the highest correlation with muscle. In multivariate analysis, lower BSI was associated with poorer OS (HR 1.79, p=0.02). The association between muscle composition and prognosis was robust in univariate analysis but dissipated in multivariate analysis. However, accounting for a high TATI background significantly heightened the adverse effect of SMI on prognosis in the multivariate model. No clear association between BMI and SCLC immunotherapy prognosis was observed. However, high adiposity exacerbated the adverse effects of sarcopenia in SCLC immunotherapy, and BSI demonstrated potential as a straightforward prognostic measure.

FN1, a reliable prognostic biomarker for thyroid cancer, is associated with tumor immunity and an unfavorable prognosis.

Thyroid cancer (THCA) is a malignant tumor that affects the endocrine system. At present, an effective treatment for THCA remains elusive, particularly for medullary carcinoma and undifferentiated carcinoma, due to the lack of suitable medications and prognostic markers. Patient RNA-sequencing and clinical data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Protein-protein interaction analyses were performed for differentially expressed genes related to THCA. Moreover, the associations between fibronectin 1 (FN1), clinical data, immune checkpoint genes and immune cell infiltration was assessed. The potential functional role of the FN1 gene was evaluated through gene set enrichment analysis. Immunohistochemistry was used to assess FN1 expression in 103 cases of THCA, comprising 32 with papillary carcinoma, 30 with follicular carcinoma, 35 with medullary carcinoma and 6 with undifferentiated carcinoma. Finally, 11 co-expression modules were constructed and the expression of five identified hub genes (FN1, mucin-1, keratin 19, intracellular adhesion molecule 1 and neural cell adhesion molecule) were evaluated. The results demonstrated that higher FN1 gene expression levels were strongly associated with a higher pathologic stage and tumor stage, and were significantly associated with immune cell infiltration in THCA. Significant increases in FN1 protein expression levels were noted among patients diagnosed with four types of THCA, comprising papillary carcinoma, follicular carcinoma, medullary carcinoma and undifferentiated carcinoma. Patients diagnosed with medullary carcinoma and undifferentiated carcinoma, and with low FN1 expression levels, exhibited a significant survival advantage compared with those with high FN1 expression levels. In conclusion, the present study identified five hub genes involved in the onset and progression of THCA. Furthermore, FN1 could serve as a candidate biomarker and a therapeutic target for THCA and may be a key gene mediating THCA immune infiltration.

Human Liver Organoids to Predict the Outcome of Kasai Portoenterostomy

BackgroundKasai portoenterostomy (KPE) remains the primary intervention for biliary atresia (BA), but its outcomes are highly variable. Reliable prognostic biomarkers remain elusive, complicating the management and prediction of postoperative progression. MethodLiver biopsies from BA patients taken at and after KPE (post-KPE) were used to generate organoids for RNA-sequencing analysis. Control organoids were derived from non-BA livers. Differential gene expression and enrichment analyses were performed to assess post-KPE transcriptomic changes between native liver survivors (NLS) and patients who eventually became liver transplant recipients (LTR). ResultsOrganoid datasets: 70 from liver biopsies at KPE (10 patients), 112 from post-KPE livers (13 livers; 12 patients), and 47 from control livers (9 patients). At KPE, BA organoids displayed mainly hepatocyte expression, a trait notably reduced in control organoids. Similarly, post-KPE organoids from NLS revealed a significant decrease in hepatocyte expression features and an overall increase in cholangiocyte expression features. A similar hepatocyte-to-cholangiocyte expression transition was evidenced in paired liver organoids (at- and post-KPE) generated from an NLS. In contrast, post-KPE organoids from LTR maintained a high level of hepatocyte expression features. ConclusionOur study demonstrated that an elevated expression of hepatocyte features in KPE organoids may indicate aberrant cholangiocyte development in BA livers. In contrast, a post-KPE hepatocyte-to-cholangiocyte expression transition in NLS may imply effective biliary recovery. The lack of this transition in LTR organoids indicates ongoing disease progression, highlighting the potential for organoid-based transcriptomic profiling to inform KPE success and guide BA management. Level of EvidenceLevel III.

Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.

Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs). In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR). Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m6A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated. Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.

Immune landscape of hepatocellular carcinoma: The central role of TP53-inducible glycolysis and apoptosis regulator.

This study aims to address the substantive issue of lacking reliable prognostic biomarkers in hepatocellular carcinoma (HCC) by investigating the relationship between TP53-inducible glycolysis and apoptosis regulator (TIGAR) and HCC prognosis using The Cancer Genome Atlas database. (1) Integrated statistical analyses, including logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test, were conducted to explore the association between TIGAR expression and clinical-pathological features of HCC. (2) The Kaplan-Meier method combined with univariate and multivariate Cox regression models underscored TIGAR as a prognostic factor in HCC. (3) Gene set enrichment analysis (GSEA) revealed key pathways associated with TIGAR, while single-sample gene set enrichment analysis (ssGSEA) determined its relevance to cancer immune infiltration. (1) Elevated TIGAR expression was significantly correlated with decreased survival outcomes in HCC patients. (2) GSEA highlighted the significant link between TIGAR and humoral immunity. (3) ssGSEA revealed a positive correlation between TIGAR expression and infiltration of Th1 and Th2 cells and a negative correlation with Th17 cell infiltration. TIGAR, as a potential prognostic biomarker for HCC, holds significant value in immune infiltration. Understanding the role of TIGAR could contribute to improved prognostic predictions and personalized treatment strategies for HCC patients.

Prognostic Significance of Phenylalanine in Heart Failure: Clinical Insights and Inter-Organ Crosstalk Snapshot.

Background: Heart failure (HF) remains a leading cause of morbidity and mortality globally, necessitating the identification of reliable prognostic biomarkers to guide therapeutic interventions. Recent clinical observations have underscored phenylalanine (PHE) as a prognostic marker in HF, although the mechanisms involving inter-organ crosstalk remain understood. Methods: This study adopted a dull approach, with a retrospective analysis of 550 HF patients to establish the prognostic value of pre-discharge PHE levels and a study on the inter-organ crosstalk of PHE among 24 patients. We analyzed the correlations between PHE concentrations and clinical outcomes, alongside a comprehensive examination of PHE metabolism across the skeletal muscle, liver, heart, kidney, and lung. Results: In the clinical prognostic analysis of 550 patients hospitalized for acute decompensated HF, elevated PHE levels (≥65.6 μM) were significantly and independently associated with increased all-cause mortality during a median follow-up of 4.5 years (log rank = 36.7, p < 0.001), underscoring its value as a prognostic marker in HF. The inter-organic crosstalk study elucidated the mechanism associated with PHE elevation in patients with HF, characterized by an increase in PHE output in skeletal muscle and a decrease in hepatic and cardiac PHE uptakes. Notably, PHE concentration gradients across these organs were correlated with HF severity, such as the NYHA functional class, B-type natriuretic peptide levels, and the presence of acute HF. Conclusions: Our findings confirm the prognostic significance of PHE in patients with HF and unveil the complex metabolic interplay among key organs that contribute to PHE dysregulation. These insights not only reinforce the importance of metabolic monitoring in HF management but also open avenues for therapeutic targets.