Prognostic Predictor Research Articles

A redox-related lncRNA signature in bladder cancer.

The redox status is intricately linked to the development and progression of cancer, a process that can be modulated by long non-coding RNAs (lncRNAs). Previous studies have demonstrated that redox regulation can be considered a potential therapeutic approach for cancer. However, the redox-related lncRNA predictive signature specific to bladder cancer (BCa) has yet to be fully elucidated. The purpose of our study is to establish a redox-related lncRNA signature to improve the prognostic prediction for BCa patients. To achieve this, we downloaded transcriptome and clinical data from the Cancer Genome Atlas (TCGA) database. Prognostic redox-related lncRNAs were identified through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis, resulting in the establishment of two risk groups. A comprehensive analysis corresponding to clinical features between high-risk and low-risk groups was conducted. Eight redox-related lncRNAs (AC018653.3, AC090229.1, AL357033.4, AL662844.4, AP003352.1, LINC00649, LINC01138, and MAFG-DT) were selected to construct the risk model. The overall survival (OS) in the high-risk group was worse than that in the low-risk group (p < 0.001). The redox-related lncRNA signature exhibits superior predictive accuracy compared to traditional clinicopathological characteristics. Gene Set Enrichment Analysis (GSEA) showed that the MAPK signaling pathway and Wnt signaling pathway were enriched in the high-risk group. Compared with the low-risk group, patients in the high-risk group demonstrated increased sensitivity to cisplatin, docetaxel, and paclitaxel. Furthermore, IGF2BP2, a potential target gene of MAFG-DT, was found to be overexpressed in tumor tissues and correlated with overall survival (OS). Our study demonstrated that the predictive signature based on eight redox-related lncRNAs can independently and accurately predict the prognosis of BCa patients.

BHLHE40-mediated transcriptional activation of GRIN2D in gastric cancer is involved in metabolic reprogramming.

Gastric cancer (GC) is the third leading cause of death in developed countries. The reprogramming of energy metabolism represents a hallmark of cancer, particularly amplified dependence on aerobic glycolysis. Here, we aimed to illustrate the functional role of glutamate ionotropic receptor N-methyl-D-aspartate type subunit 2D (GRIN2D) in the regulation of glycolysis in GC and the mechanisms involved. Differentially expressed genes were analyzed using the GEO and GEPIA databases, followed by prognostic value prediction using the Kaplan-Meier Plotter database. The effect of GRIN2D knockdown on the malignant behavior and glycolysis of GC cells was explored. GRIN2D expression was upregulated in GC cells and promoted the malignant behavior of GC cells by activating glycolysis. Class E basic helix-loop-helix protein 40 (BHLHE40) was overexpressed in GC cells and mediated transcriptional activation of GRIN2D. The anti-tumor effects of BHLHE40 knockdown on GC cells in vitro and in vivo were reversed by GRIN2D overexpression. Knockdown of GRIN2D or BHLHE40 downregulated the expression of mRNA of electron transport chain subunits and phosphorylation of p38 MARK and inhibited calcium efflux in GC cells. Overexpression of GRIN2D promoted calcium efflux, phosphorylation of p38 MARK protein, and proliferation of GES1 cells. Altogether, the findings derived from this study suggest that BHLHE40 knockdown suppresses the growth, mobility, and glycolysis of GC cells by inhibiting GRIN2D transcription and disrupting the BHLHE40/GRIN2D axis may be an attractive therapeutic strategy for GC.

Association of the Preoperative Controlling Nutritional Status (CONUT) Score with Clinicopathological Characteristics in Patients with Papillary Thyroid Carcinoma.

The Controlling Nutritional Status (CONUT) score is an immunonutritional test tool based on serum albumin, total cholesterol, and lymphocyte counts. It has been studied as a simple prognostic predictor for various carcinomas. This study aimed to investigate the association between preoperative CONUT scores and the clinicopathological characteristics in papillary thyroid carcinoma (PTC) patients. This study included 2,403 PTC patients who underwent total thyroidectomy between 2012 and 2016 at a single tertiary medical center. The CONUT scores were calculated based on preoperative blood tests. The clinicopathological characteristics were retrospectively reviewed. The patients were categorized by the CONUT score (relatively low, 0-2; relatively high, 3-5). Among the 2,997 PTC patients who underwent total thyroidectomy at Pusan National University Hospital between 2012 and 2016, those without preoperative blood test were excluded (n=149). Finally 2,403 patients were analyzed after excluding 439 patients taking lipid-lowering drugs and six patients without available T stage data after surgery. Based on the CONUT score, the relatively high score group had a lower body mass index (23.7±3.3 kg/m2 vs. 21.9±2.9 kg/m2, P<0.001), more advanced T stage (T stage 3/4, 5.9% vs. 11.4%, P=0.045), and higher extrathyroidal extension (2.1% vs. 7.6%, P=0.005). Patients included in this large, single-center study all had a preoperative CONUT score of 0-5, but this study demonstrated that higher preoperative CONUT scores were significantly associated with advanced T stage and extrathyroidal extension. The CONUT score, which can be easily used in clinical practice, is thought to be helpful in predicting the aggressiveness of PTC.

Textbook oncological outcome of locally advanced gastric cancer patients with preoperative sarcopenia: a multicenter clinical study.

The impact of postoperative sarcopenia on the Textbook Oncological Outcome (TOO) in locally advanced gastric cancer (LAGC) remains uncertain. This study investigates the relationship between sarcopenia and TOO, explores its long-term prognostic value, and develops a prognostic model incorporating sarcopenia and TOO for survival prediction. We performed a retrospective analysis of clinical and pathological data from patients with LAGC who underwent radical surgery at two Chinese tertiary referral hospitals. Sarcopenia was defined as an SMI < 36.4 cm2/m2 in males and < 28.4 cm2/m2 in females. TOO was defined as the addition of perioperative chemotherapy to the textbook outcomes (TO). A nomogram was developed to predict postoperative overall survival (OS) and recurrence-free survival (RFS) in LAGC patients. The study included 972 patients with LAGC. The overall TOO achievement rate was 67.1%. The TOO achievement rate was significantly higher in patients non-sarcopenia compared to those with sarcopenia (68.9% vs. 61.1%, P = 0.031). Logistic regression revealed that age ≥ 65, high ASA score, and sarcopenia were independent risk factors for TOO failure. Cox regression analysis identified TOO, sarcopenia, tumor size, differentiation, vascular invasion, pT stage, and pN stage as independent predictors of OS and RFS. Nomogram models based on sarcopenia and TOO accurately predicted the 3-year and 5-year OS and RFS. Preoperative sarcopenia was an independent predictor of TOO implementation. A prognostic prediction model that integrates preoperative sarcopenia and TOO, which outperforms the current staging system, can aid clinicians in effectively assessing the prognosis of patients with LAGC.

Large-scale genome-wide association studies identified causal relationship between multiple blood biomarkers and risk of acute pancreatitis.

Observational studies have shown that there is a connection between blood biomarkers and the occurrence of acute pancreatitis (AP). Nevertheless, the causal relationships are still not clear. The purpose of this study was to evaluate causal association between biomarkers and AP. A bidirectional two-sample Mendelian randomization (MR) analysis was applied to investigate the causal association between blood biomarkers and AP. Summary statistics obtained from genome-wide association studies were utilized for this analysis. The primary statistical approach employed was the inverse variance weighted (IVW) method, complemented by sensitivity analyses aimed at assessing heterogeneity and pleiotropy. Furthermore, a multivariable MR (MVMR) analysis was performed to adjust for confounders. A total of 11 red blood cell (RBC) traits, 6 white blood cell traits, platelet count, and 30 blood biomarkers were analyzed in this study. Genetically predicted RBC count (IVW odds ratio [OR]=1.144, P=0.004), the high light scatter reticulocyte count (HLSR) (OR=1.127, P=0.022), blood glucose (BG) (OR=1.480, P=0.019), and leptin (OR=1.234, P=0.050) were suggestively associated with an increased risk of AP. Reverse MR analysis showed no causal effect of AP on RBC, HLSR, BG, and leptin (IVW P>0.05). Sensitivity analyses and MVMR analysis still supported the earlier causality. Our findings provide evidence of a suggestive association between RBC count, HLSR, BG, and leptin with an increased susceptibility to AP. These findings aid in our comprehension of the cause of AP and may be used as potential prognostic markers or predictors of severity with AP.

Predicting the prognosis of Wilms tumor by peripheral blood cells: a real-world study of more than 30years.

Despite established excellent treatment strategies for Wilms tumor (WT), effective prognostic evaluation methods were lacking. This study aims to examine prognostic factors for WT through real-world peripheral blood cell profiling. Basic data and pre-treatment laboratory indices from WT and non-WT children underwent Wilcoxon test analysis. Chi-square tests assessed the correlation between blood cells and the overall survival (OS) and event-free survival (EFS) of WT. Further the Log-rank test and multivariate Cox were used to identify independent prognostic factors for OS. Traditional accepted factors were included in multi-Cox and the nomogram was constructed to further validate the outcome. Blood cells significantly differed between WT and non-WT groups (P < 0.05). Univariate analysis revealed that NLR above 1.380, stage IV, M below 0.325 × 103/μL were linked with lower OS, and PLR below 94.632, LB above 3.570 × 103/μL, stage IV, M above 0.325 × 103/μL,age ≤ 3years were meaningful for higher EFS (P < 0.05). While in the multifactorial COX, only M (HR:0.220, HR95%CI: 0.080 ~ 0.620, P = 0.004 and HR: 0.437, HR95%CI: 0.202 ~ 0.947, P = 0.036, respectively) and stage IV (HR: 7.890, HR95%CI: 1.650 ~ 37.770, P = 0.010 and HR: 3.720, HR95%CI: 1.330 ~ 10.408, P = 0.012, respectively) were independent prognostic factors for OS and EFS. These two variables also were significant after including recognized risk factors, and were demonstrated the predictability via nomogram. OS and EFS were poorer in WT children with M below 0.325 × 103/μL, suggesting the potential as a prognostic predictor for WT.

Comparing gastrointestinal dysfunction score and acute gastrointestinal injury grade for predicting short-term mortality in critically ill patients

BACKGROUND The prognosis of critically ill patients is closely linked to their gastrointestinal (GI) function. The acute GI injury (AGI) grading system, established in 2012, is extensively utilized to evaluate GI dysfunction and forecast outcomes in clinical settings. In 2021, the GI dysfunction score (GIDS) was developed, building on the AGI grading system, to enhance the accuracy of GI dysfunction severity assessment, improve prognostic predictions, reduce subjectivity, and increase reproducibility. AIM To compare the predictive capabilities of GIDS and the AGI grading system for 28-day mortality in critically ill patients. METHODS A retrospective study was conducted at the general intensive care unit (ICU) of a regional university hospital. All data were collected during the first week of ICU admission. The primary outcome was 28-day mortality. Multivariable logistic regression analyzed whether GIDS and AGI grade were independent risk factors for 28-day mortality. The predictive abilities of GIDS and AGI grade were compared using the receiver operating characteristic curve, with DeLong’s test assessing differences between the curves’ areas. RESULTS The incidence of AGI in the first week of ICU admission was 92.13%. There were 85 deaths (47.75%) within 28 days of ICU admission. There was no initial 24-hour difference in GIDS between the non-survival and survival groups. Both GIDS (OR 2.01, 95%CI: 1.25-3.24; P = 0.004) and AGI grade (OR 1.94, 95%CI: 1.12-3.38; P = 0.019) were independent predictors of 28-day mortality. No significant difference was found between the predictive accuracy of GIDS and AGI grade for 28-day mortality during the first week of ICU admission (Z = -0.26, P = 0.794). CONCLUSION GIDS within the first 24 hours was an unreliable predictor of 28-day mortality. The predictive accuracy for 28-day mortality from both systems during the first week was comparable.

Identification of Molecular Subtypes and Prognostic Traits Based on Chromosomal Instability Phenotype-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) exhibits significant molecular heterogeneity; however, previous studies have not fully explored its classification into distinct molecular subtypes. Here, we identified LUAD-significant chromosomal instability (CIN) phenotype genes (n = 24) using a TCGA-LUAD cohort (n = 592) and evaluated their ability to predict pathologic grade. Unsupervised clustering and principal component analysis revealed that LUAD patients could be classified into CIN phenotype-related subtypes (GroupLow, GroupModerate, and GroupHigh), each exhibiting distinct transcriptomic patterns. Notably, the GroupHigh showed significantly poor overall survival [OS; hazard ratio (HR) = 1.43, p-value &lt; 10−3] and disease-free survival (DFS; HR = 1.27, p-value &lt; 10−3). Univariate and multivariate analysis confirmed that its expression status was an independent prognostic predictor (p-value &lt; 10−3, HR = 2.18, 95% C.I = 1.26–3.76) of the clinical outcomes, outperforming pathologic grade (p-value &lt; 10−3, HR = 1.2, 95% C.I = 1.08–1.33). Moreover, analysis of surfactant metabolism-related genes revealed higher expression in the GroupLow, which was associated with a favorable prognosis. By integrating multiple independent cohorts (n = 779), we validated these findings and confirmed that CIN phenotype gene status serves as a critical prognostic marker in LUAD. Furthermore, genomic profiling showed that the GroupHigh exhibited frequent mutations in key genes such as KEAP1, LYST, SETD2, and TP53, with oncogenes in this group preferentially showing copy number gains. Our study highlights the significance of CIN phenotype gene status as a predictor of LUAD prognosis and its association with transcriptomic and genomic alterations, paving the way for further clinical validation and potential therapeutic interventions.

Comprehensive analysis of single-cell and bulk RNA sequencing reveals postoperative progression markers for non-muscle invasive bladder cancer and predicts responses to immunotherapy.

Non-muscle-invasive bladder cancer (NMIBC) is renowned for its high recurrence, invasiveness, and poor prognosis. Consequently, developing new biomarkers for risk assessment and investigating innovative therapeutic targets postoperative in NMIBC patients are crucial to aid in treatment planning. Differential gene expression analysis was performed using multiple Gene Expression Omnibus (GEO) datasets to identify differentially expressed genes (DEGs) between NMIBC and normal tissue, as well as between NMIBC and muscle-invasive bladder cancer (MIBC). Functional enrichment analysis was conducted based on the DEGs identified. Subsequently, prognosis-related genes were selected using Kaplan-Meier (KM) analysis and Cox regression analysis. The Boruta algorithm was utilized to further screen for core DEGs related to postoperative progression in NMIBC based on the aforementioned prognosis-related genes. Single-cell and clinical correlation studies were performed to verify their expression across various stages of bladder cancer. To investigate the link between core genes and the immune microenvironment, single-sample gene set enrichment analysis (ssGSEA) was utilized, and Receiver Operating Characteristic (ROC) and KM analyses were performed to confirm predictive power for immune therapy outcomes. Machine learning (ML) models were constructed using the DepMap dataset to predict the efficacy of core gene inhibitors in treating bladder cancers. The prognostic performance of the core genes was evaluated using ROC curve analysis. An online prediction tool was developed based on the core genes to provide prognostic predictions. Finally, RT-qPCR, CCK-8, and Transwell assays were used to verify the pro-tumor effects of the GINS2 in bladder cancer. A total of 70 DEGs were identified, among which 11 prognostic genes were obtained through KM analysis, and an additional 8 prognostic genes were obtained through COX analysis. The Boruta algorithm selected AURKB, GINS2, and UHRF1 as the three core DEGs. Single-cell and clinical variable correlation analyses indicated that the core genes promoted the progression of bladder cancer. The analysis of immune infiltration revealed a strong positive association between the core genes and both activated CD4 T cells and Type 2 helper T cells. Two random forest (RF) models were constructed to effectively predict the treatment effect of bladder cancer after targeted inhibition of AURKB and GINS2. In addition, an online nomogram tool was developed to effectively predict the risk of postoperative progression in NMIBC patients undergoing TURBT. Finally, RT-qPCR, CCK8, and Transwell assays showed that GINS2 promoted the growth and progression of bladder cancer. AURKB, GINS2, and UHRF1 have the potential to enhance postoperative management of NMIBC patients undergoing transurethral resection of bladder tumor (TURBT) and can predict immunotherapy response, establishing them as promising therapeutic targets.

Inflammatory markers correlate with lymphocytes infiltrating and predict immunotherapy prognosis for esophageal cancer.

Aim: To investigate the prognostic value of inflammatory markers in esophageal squamous cell carcinoma (ESCC) patients treated with immune checkpoint inhibitors (ICIs).Materials & methods: The infiltration of CD3+ and CD8+ T cells in tissue microarraysfrom 180 patients who underwent radical esophagectomy was detected using immunohistochemistry. A separate cohort of 351 patients with metastatic/recurrent or unresectable ESCC treated with ICIs was enrolled for further investigation. The overall survivaldifference among groups was assessed using Kaplan-Meier analysis. Cox proportional hazards models were employed to investigate the prognostic impact of the inflammatory markers, along with other factors.Results: Decreased inflammation was found to be associated with increased CD3+ and CD8+ T-cell infiltration and a better prognosis. Then, the value of inflammatory markers in predicting survival in 351 ESCC patients receiving immunotherapy was validated. Ultimately, the systemic immune-inflammation index was identified as an independent prognostic factor for overall survival. Additionally, the patients with no distant organ metastasis, or treated by first-line immunotherapy combined with concurrent chemoradiotherapy can considerably prolong survival.Conclusion: Inflammation is associated with the level of tumor infiltrating lymphocytes and that the systemic immune-inflammation index is an effective prognostic predictor for ESCC patients treated with ICIs.

Neutrophil-albumin ratio serves as a superior prognostic biomarker for traumatic brain injury.

Traumatic brain injury (TBI) represents a common and severe medical condition necessitating prompt risk stratification to enhance patient outcomes. Although substantial research has been conducted on the prognostic utility of various biomarkers for TBI, no single biomarker has been definitively recognized as the most precise predictor of disease outcomes. In comparison to other markers, the neutrophil-albumin ratio (NAR) has emerged as a cost-effective and reproducible inflammatory biomarker, demonstrating potential in evaluating the severity of inflammation and prognosticating outcomes in infections and cerebrovascular diseases. This study evaluated the prognostic significance of the NAR in comparison to two other readily accessible and cost-effective composite indices: the Neutrophil-Lymphocyte Ratio (NLR) and the Platelet-Lymphocyte Ratio (PLR) in individuals with TBI. We conducted a retrospective cohort analysis involving 297 hospitalized TBI patients, gathering comprehensive demographic, anthropometric, medical, clinical, laboratory, and imaging data to assess the expression changes of these biomarkers. Our findings suggest that both the NAR and the NLR possess predictive value regarding prognosis following TBI. However, receiver operating characteristic (ROC) curve analysis revealed that NAR outperformed NLR as a prognostic predictor. In conclusion, our examination of blood biochemistry composite indicators indicates that, while both NAR and NLR serve as significant prognostic markers, NAR is a more effective predictor of outcomes in patients with TBI.

Personalized MRD Assessment in Peri-surgical ctDNA for Prognostic Prediction in Hepatocellular Carcinoma.

Detecting residual disease is a critical clinical requirement in the peri-surgical management of patients with resectable hepatocellular carcinoma (HCC). Previous studies focused on specific genomic regions exhibiting limited sensitivity and failed to meet the minimal residual disease (MRD) testing threshold. We introduce a next-generation sequencing (NGS) based assay, informed by baseline samples, facilitating MRD detection in hepatectomized HCC patients and offering prognostic predictions. This study involved 88 HCC patients who underwent surgical resections January 2016 to May 2016 in Zhongshan Hospital Fudan University. Tumor and normal tissue samples were collected during surgery, while plasma samples were obtained both before surgery and up to seven days post-surgery. Using an NGS-based personalized circulating tumor DNA assay, we analyzed MRD in both pre-surgical and post-surgical blood samples and the correlation with prognosis. With a median follow-up period of 80.7 months, our findings demonstrated significant correlations between pre-surgical ctDNA tumor fractions, post-surgical plasma MRD status, and both recurrence-free survival (RFS) and overall survival (OS). Post-surgical MRD status emerged as the most significant risk factor for cancer recurrence (HR=2.17, 95% CI: 1.09-4.30, p=0.027) compared to other clinical characteristics in multivariate Cox regression analysis. Notably, MRD status showed potential as a prognostic indicator among clinically low-recurrent-risk patients, such as those with BCLC stage 0-A, CNLC stage I-II. Evaluating personalized MRD provided crucial prognostic insights into RFS and OS. It efficiently identified patients at high risk of recurrence, even among those initially perceived as low-risk cases.

BIOM-26. ROLE OF EXTRA-DOMAIN B FIBRONECTIN IN MODULATING GLIOBLASTOMA CELL INVASIVE PROPERTIES

Abstract Glioblastoma (GBM) is a highly malignant tumor characterized by its resistance to current treatment modalities and high recurrence rates. Extra-domain B Fibronectin (EDB-FN), a glycoprotein not found in normal tissues but selectively expressed in the tumor microenvironment, was previously identified by our team as a promising molecular marker for brain tumors, offering potential for both prognostic prediction and therapeutic targeting. However, the specific role and mechanism of action of EDB-FN in GBM cells remain unclear. In this study, we sought to elucidate the potential role of EDB-FN and the underlying mechanisms contributing to GBM malignancy through in vitro investigations. Our findings reveal that silencing EDB-FN in GBM cells leads to a decrease in cell migration, invasiveness, extracellular matrix adhesion ability, and stem cell-like properties. Furthermore, we discovered that FAK and ERK signaling pathways play a crucial role in GBM cell progression in response to EDB-FN. This study underscores the potential of EDB-FN as a specific biomarker for GBM treatment, paving the way for future research in this area.

CK19 is associated with poor survival in patients with dual-phenotype hepatocellular carcinoma

Objective: To study the role of CK19 in the survival of patients diagnosed with DPHCC in Fujian, China, which has a high incidence of hepatocellular carcinoma (HCC). Methods: Patients with DPHCC (n=84) who had undergone surgical interventions at the 900th Hospital of Joint Logistic Support Force between 2013 and 2019 were retrospectively analyzed using the log-rank test and Kaplan-Meier method. Univariate and multivariate Cox model analyses were also conducted to further understand the correlation between CK19 and patient survival. Results: (1)Tumor size, differentiation, peripheral hepatic fibrosis, liver capsule invasion, microvascular invasion (MVI) and serum CA-199 level showed a correlation with CK19, as per the outcomes of Chi-squared tests. (2)According to the univariate analysis, the expression of CK19, MVI, the number of tumor lesions, necrosis, differentiation, peripheral hepatic fibrosis, and serum levels of both alpha-fetoprotein (AFP) and CA-199 showed a strong correlation with overall survival. (3)Necrosis and serum AFP levels were strongly related to an increased risk of death, according to the multivariate analysis. Conclusions: The expression of CK19 may correlate with the survival of patients with DPHCC and could potentially serve as a prognostic predictor of survival.

Postoperative Karnofsky performance status prediction in patients with IDH wild-type glioblastoma: A multimodal approach integrating clinical and deep imaging features.

Glioblastoma is a highly aggressive brain tumor with limited survival that poses challenges in predicting patient outcomes. The Karnofsky Performance Status (KPS) score is a valuable tool for assessing patient functionality and contributes to the stratification of patients with poor prognoses. This study aimed to develop a 6-month postoperative KPS prediction model by combining clinical data with deep learning-based image features from pre- and postoperative MRI scans, offering enhanced personalized care for glioblastoma patients. Using 1,476 MRI datasets from the Brain Tumor Segmentation Challenge 2020 public database, we pretrained two variational autoencoders (VAEs). Imaging features from the latent spaces of the VAEs were used for KPS prediction. Neural network-based KPS prediction models were developed to predict scores below 70 at 6 months postoperatively. In this retrospective single-center analysis, we incorporated clinical parameters and pre- and postoperative MRI images from 150 newly diagnosed IDH wild-type glioblastoma, divided into training (100 patients) and test (50 patients) sets. In training set, the performance of these models was evaluated using the area under the curve (AUC), calculated through fivefold cross-validation repeated 10 times. The final evaluation of the developed models assessed in the test set. Among the 150 patients, 61 had 6-month postoperative KPS scores below 70 and 89 scored 70 or higher. We developed three models: a clinical-based model, an MRI-based model, and a multimodal model that incorporated both clinical parameters and MRI features. In the training set, the mean AUC was 0.785±0.051 for the multimodal model, which was significantly higher than the AUCs of the clinical-based model (0.716±0.059, P = 0.038) using only clinical parameters and the MRI-based model (0.651±0.028, P<0.001) using only MRI features. In the test set, the multimodal model achieved an AUC of 0.810, outperforming the clinical-based (0.670) and MRI-based (0.650) models. The integration of MRI features extracted from VAEs with clinical parameters in the multimodal model substantially enhanced KPS prediction performance. This approach has the potential to improve prognostic prediction, paving the way for more personalized and effective treatments for patients with glioblastoma.

Systematic review of risk prediction tools for primary cutaneous melanoma outcomes and validation of sentinel lymph node positivity prediction in a UK tertiary cohort.

It is difficult for clinicians to make predictions for cancer progression or outcomes based on AJCC staging for individual patients. Models individualising risk prediction for clinical outcomes are developed using patient level data, advanced statistical techniques, and artificial intelligence. A systematic search identified cutaneous melanoma prognostic prediction tools published between January 1985-March 2023. Population comparisons of key clinico-pathological variables, external prediction of receiver operating characteristics and calibration analysis are applied to an unselected group of patients undergoing sentinel lymph node biopsy in a UK University hospital setting (n = 1564). Twenty-nine models were identified which predicted survival, disease recurrence or sentinel lymph node positivity (Internal validation n = 19 and external validation n = 14). 3 out of 7 tools for sentinel node positivity were contemporaneous with available characteristics for external validation. External validation of models by Lo et al. Friedman et al. & Bertolli et al. highlighted good discriminative performance (AUC 68.1% (64.5-71.8%), 77.1% (66.8-85.7%) & 68.6% (63.3-74.1%) respectively) but were sub-optimally calibrated for the UK patient cohort (Calibration intercept & slope Friedman: -4.01 & 32.92, Lo: -1.17 & 0.44, Bertolli: -2.75 & 4.88). This work highlights the complexity of predictive modelling and the rigorous validation process necessary to ensure accurate predictions. Our search highlights a tendency to focus on discriminative performance over calibration, and the possibility for inconsistent predictions when tools are applied to populations with differing characteristics.

Effects of Sodium–Glucose Co-Transporter 2 Inhibitors on Serum Chloride Concentrations in Patients with Heart Failure

Background and aims: In the past few years, some reports have shown that serum chloride concentration is a more powerful prognostic predictor than serum sodium levels in heart failure (HF). Elevated Na/Cl ratio has shown to be independently associated with all-cause death in acute HF. We evaluated changes in serum chloride concentrations and Na/Cl ratio in correlation with various clinical factors during 12 months of follow-up in patients in whom SGLT2is were initiated as part of HF therapy. Patients and methods: This was a prospective observational study conducted at University Hospital Dubrava and involving patients with HF. We included 241 participants between May 2021 and April 2023. All data were obtained before the introduction of SGLT2is, and the same parameters were obtained at 6 and 12 months of follow-up as well. Results: The results show that higher chloride concentration at both 6 and 12 months is an independent predictor of lower NT-proBNP levels. The chloride concentrations did not differ significantly between these groups in the follow-up period. There were no statistically significant differences in the Na/Cl ratio at different timepoints. The presence of cardiovascular risk factors did not significantly affect the increase in chloride concentration. Conclusions: Our results suggest that hypochloremia could be a potentially modifiable risk factor, given the influence of SGLT2is on chloride concentration, but also an ominous sign of a poor outcome in patients with HF. We believe that the determination of chloride concentrations should become routine in the monitoring of patients with HF.

Histone-acetyl epigenome regulates TGF-β pathway-associated chemoresistance in colorectal cancer

TGF-β signaling pathway has been demonstrated to be closely related to chemoresistance, which is the major cause of recurrence and poor outcome in colorectal cancer (CRC), however, the comprehensive epigenetic landscape that functionally implicates in the regulation of TGF-β pathway-associated chemoresistance has not yet well established in CRC. In our study, chromatin immunoprecipitation sequencing (ChIP-seq) and Western blot were employed to investigate epigenetic modifications for histones in response to TGF-β1 intervene. We found that the activation of the TGF-β pathway was characterized by genome-wide high levels of H3K9ac and H3K18ac. Mechanistically, the activation of the TGF-β signaling pathway leads to the downregulation of the deacetylase HDAC4, resulting in the upregulation of H3K9ac and H3K18ac. Consequently, this cascade induces oxaliplatin chemoresistance in CRC by triggering the anti-apoptotic PI3K/AKT signaling pathway. Our in vivo experiment results confirmed that overexpression of HDAC4 significantly enhances the sensitivity of CRC to oxaliplatin chemotherapy. Moreover, the expression level of HDAC4 was positively correlated with patients’ prognosis in CRC. Our data suggest that histone-acetyl modification demonstrates a crucial role in modulating TGF-β pathway-associated chemoresistance in CRC, and HDAC4 would be a biomarker for prognostic prediction and potential therapeutic target for treatment in CRC.

Novel miRNA markers and their mechanism of esophageal squamous cell carcinoma (ESCC) based on TCGA

MicroRNAs(miRNAs) are promising biomarkers for early esophageal squamous cell carcinoma (ESCC) detection and prognostic prediction. This study aimed to explore the potential biomarkers and molecular pathogenesis in the early diagnosis of ESCC. Firstly, 48 differentially expressed miRNAs (DEMs) and 1319 differentially expressed genes (DEGs) were identified between 94 ESCC tissues and 13 normal esophageal tissues in TCGA. From miRNA–mRNA regulatory network, there are 6558 target genes of the 48 DEMs, where 400 target genes are also among 1319 DEGs. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicate that the 400 DEGs significantly enriched in cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis. And there are 66 DEGs among these six biological pathways, which we called GO-DEGs. From miRNA–mRNA regulatory network, 32 DEMs regulated the 66 GO-DEGs, where 22 DEMs were verified by different types of experiments in ESCC tissues, cells, or serum from the literature. For the other novel 10 DEMs, single-factor Cox regression analysis show that only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients. Finally, we obtained the novel 9 ESCC-related DEMs, where three are down-regulated, and six are up-regulated. We analyzed the expression trends of target genes for five miRNAs and identified three significantly different miRNAs (hsa-miR-205-3p, hsa-miR-452-3p, and hsa-miR-6499-3p) confirmed by qPCR. Moreover, the stage-specific miRNAs were also suggested. These three qPCR validated miRNAs are also specific to the early stages of ESCC: hsa-miR-452-3p is specific to Stage I, II and III; hsa-miR-205-3p is specific in Stage II and III; and hsa-miR-6499-3p is Stage II specific. They might be the potential biomarkers for ESCC stage diagnosis. This study identified three novel miRNA markers potentially related to the diagnosis of ESCC and participated in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway for oocyte meiosis.

SPP1 is a plasma biomarker associated with the dia gnosis and prediction of prognosis in sepsis

In this study, peripheral whole blood samples from 22 hospitalized patients and 10 healthy individuals were analyzed using a combination of Data Independent Acquisition (DIA) and Enzyme-Linked Immunosorbent Assay (ELISA) techniques to identify differentially expressed proteins (DEPs) in sepsis patients’ plasma. The aim was to provide accurate and detailed biomarkers, such as SPP1, for determining the pathological stages of sepsis. SPP1, known as osteopontin1 is a pleiotropic protein with a wide distribution and multifunctional effects. Its protein expression is associated with inflammatory changes, including variations in expression levels in infectious diseases, allergic diseases, and situations involving tissue damage. The registration number was ChiCTR1900021261.The full date of first registration year is 2018. In the affiliated hospital of southwest medical university, 22 sepsis patients were hospitalized from January 2019 to September 2020 and 10 normal healthy individuals were selected for DIA-based quantitative proteomics analysis. In addition to gene ontology analysis and Kyoto Encyclopedia of genes and genomes analysis, enrichment analysis of data was performed and target protein network was screened through joint protein–protein interaction and visualization techniques. The selected protein targets were then validated by Elisa kit. The software was used to analyze the differences comparing the control group to the sepsis group and the sepsis group, as well as between sepsis survivals and non-survivals, and a ROC curve was drawn to evaluate the diagnostic value and prognostic effect of the method of the corresponding target proteins. A total of 174 DEPs were screened by bioinformatics analysis. An analysis of go pathway enrichment revealed the following: These proteins were mainly involved in biological processes among them are the inflammation response, the metabolism of extracellular matrix, the secretion of cell secretions, the activation of cells, and the immune response. According to the Kegg pathway analysis, they were mainly involved in complement cascade polymerization, extracellular protease and glycosylase activation, protein synthesis process, biotin metabolism, leukocyte transmembrane migration, bacterial infection and phagosome formation. SPP1 was identified as a possible plasma biomarker and was therefore further validated using Elisa. As a result of experiments, it has been demonstrated that level in sepsis patients is significantly compared to the normal control group and the level is also higher in non-survivals of sepsis. The ROC curve can be used to see that it can diagnose sepsis more accurately and improve prognostic ability prediction. Cell experiments confirm that SPP1 is highly expressed in sepsis. There is a significant difference in the levels of SPP1 protein between the normal group and the sepsis group; it not only has good diagnostic significance for sepsis, but also provides corresponding reference value for patient prognosis; Therefore, it is more likely to become a biological marker of sepsis over time.