Univariate Cox Regression Analysis Research Articles

Increased Risk of End-Stage Kidney Disease in Patients with Chronic Kidney Disease and Heart Failure with Reduced Ejection Fraction.

The prevalence of heart failure (HF) is more common in people with advanced non-dialysis chronic kidney disease (ND-CKD) compared to the general population. It is well known that HF with reduced ejection fraction (HFrEF) is associated with a higher risk of mortality in people with ND-CKD. However, the impact of HFrEF on progression into end-stage kidney disease (ESKD) is not well studied. Our study aimed to examine the independent association of HFrEF on progression to ESKD after correcting for confounding factors using two methods of propensity scoring. This study used data from the Salford Kidney Study, a longitudinal study which has recruited more than 3,000 patients with ND-CKD since 2002. Patients without a history of HF during the recruitment questionnaire were included in the control group. Patients with a reported history of HF and echo showing left ventricular ejection fraction <40% at enrolment were included in the HFrEF group. Two propensity score methods were used to attenuate the effects of confounding factors between the two groups - propensity score matching (PSM) and inverse probability weighting (IPW). Univariate and multivariate Cox-regression analyses were performed. A total of 2,383 patients were included in the analysis. Patients with HFrEF had significantly higher median age and a higher percentage of male gender compared to patients with no HF (72.5 vs. 66.6 years and 71.8 vs. 61.1%, respectively). Univariate and 5 models of multivariate Cox-regression analysis showed that HFrEF in people with CKD was a strong predictor for a higher incidence of ESKD (model 5: hazard ratio 1.38; 95% confidence interval = 1.01-1.90; p = 0.044). The association between HFrEF and the risk of ESKD remained significant after using the PSM and the IPW methods. Patients with concomitant advanced ND-CKD and prevalent HFrEF were found to have a higher risk of ESKD when compared to patients with no HF. This risk persists despite the adjustment of confounding factors using PSM and IPW.

Efficacy and safety of gemcitabine/nab-paclitaxel combined with anlotinib and PD-1 inhibitors as a first-line treatment for advanced pancreatic cancer

ObjectiveTo investigate the clinical efficacy and adverse reactions of gemcitabine/nab-paclitaxel (AG regimen) combined with anlotinib and PD-1 inhibitors as a first-line treatment for advanced pancreatic cancer (PC). MethodsData of 52 patients with advanced PC who were treated in the Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) between August 2019 and March 2023 were retrospectively analyzed. According to the treatment regimen, patients were divided into two groups, including 27 patients in the chemotherapy group (AG regimen) and 25 patients in the combined treatment group (AG regimen combined with anlotinib and PD-1 inhibitors). Overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and adverse reactions were compared between the two groups. The survival curves of the two groups were drawn using the Kaplan-Meier method, and the differences in PFS and OS between the two groups were compared by the log-rank test. Univariate and multivariate Cox regression analyses were performed to identify independent risk factors influencing prognosis. ResultsThe median OS and PFS in the combined treatment group were significantly longer than those in the chemotherapy group (OS, 12.8 vs. 7.9 months, P = 0.005; PFS, 5.6 vs. 4.4 months, P = 0.003). There was no significant difference in ORR between the two groups (32.0 % vs. 25.9 %, P = 0.629), and DCR in the combined treatment group was significantly better than that in the chemotherapy group (84.0 % vs. 59.3 %, P = 0.049). Grade 1–2 adverse reactions were predominant in both groups, and no adverse reaction-related deaths occurred. ConclusionCompared with chemotherapy alone, AG regimen combined with anlotinib and PD-1 inhibitors exhibited to have a higher efficacy for the first-line treatment of advanced PC, and the adverse reactions were also controllable.

Clinical features and prognosis of conjunctival melanoma in Japanese patients.

To evaluate the clinical features and prognosis of conjunctival melanoma in Japanese patients. Retrospective observational case series. Twenty patients (8 men and 12 women) diagnosed with conjunctival melanoma at a singlehospital between 2003 and 2017 were analyzed. Data on clinical presentation, sex, age, the affected eye, tumor location, tumor origin, tumor stage according to the American Joint Committee on Cancer staging system (eighth edition), treatment, outcomes, local recurrence, metastasis, and survival were extracted from the patients' medical records and reviewed. The mean age at diagnosis was 64.2 ± 14.8 years. Tumor locations at the first examination included the bulbar conjunctiva (n = 19), plica (n = 13), and fornix (n = 12). The tumor stage was T1 in 5 cases (25%), T2 in 12 cases (60%), T3 in 3 cases (15%), and T4 in none. The mean follow-up duration was 91.7 ± 46.0 months. The local recurrence rates at 1, 5, and 10 years were 5.0%, 18.8%, and 31.5%, respectively, whilst the metastasis rates were 5.0%, 25.6%, and 32.4%, respectively. Four of the 6 patients who experienced metastasis died; duration from metastasis to death was 17.5 months (range, 7-25). The 5-year survival rate for conjunctival melanoma was 78.8%. Tumor thickness was significantly associated with survival duration on univariate Cox regression analyses. The mortality rate for conjunctival melanoma in the Japanese population was lower and higher than that reported in the Chinese and United States populations, respectively. Tumor thickness was a prognostic factor for survival in patients with conjunctival melanoma.

A nomogram-based predictive model for tooth survival in Chinese patients with periodontitis: An 11-year retrospective cohort study.

To develop a nomogram-based predictive model of tooth survival by comprehensively analysing clinical and radiographic risk factors of tooth loss (TL). In this study, 3447 teeth of 131 subjects who underwent non-surgical periodontal treatment were examined retrospectively within a mean follow-up period of 11.6 years. The association of risk factors including clinical and radiographic parameters with TL was assessed using univariate and multivariate Cox regression analyses. A nomogram-based predictive model was developed, and its validation and discriminatory ability were analysed. In all, 313 teeth were lost in 94 patients in this study (overall tooth loss [OTL] 9.08%; 0.21 teeth/patient/year). Male, heavy smoking, molar teeth, probing depth (PD), attachment loss (AL), tooth mobility and radiographic bone loss were significantly associated with TL (p < .05). A gradient effect of tooth mobility on TL increased from degree I to III versus none (p < .0001). The area under the curve (AUC) of the model was 0.865. Calibration curve and decision curve analysis demonstrated good performance and high net benefit, respectively. Adopting a specific nomogram could facilitate the prediction of tooth survival and the development of tailored treatment plans in Chinese patients with advanced periodontitis.

T-Wave Alternans Measured by 24-Hour Ambulatory Recordings Rather Than Exercise Stress Tests as a Risk Stratification Marker in Patients With Long QT Syndrome.

Few small-sample studies have quantified the T-wave alternans (TWA) value by 24-hour ambulatory recordings or exercise stress tests in patients with long QT syndrome (LQTS). The cutoff point of TWA ≥47 μV was based on patients with myocardial infarction. In our study, we aimed to (1) evaluate the association of TWA with life-threatening arrhythmic events (LAEs); (2) compare the predictive model of LAEs according to the TWA value measured by 24-hour ambulatory recordings and exercise stress tests; and (3) propose a cutoff point for the high risk of LAEs in patients with LQTS. The study cohort included 110 patients with LQTS referred to our hospital, and the primary outcome was LAEs. Thirty-one patients with LQTS (31/110 [28.2%]) developed LAEs during the following 24 (12-47) months. Peak TWA value quantified from 12 leads by 24-hour ambulatory recordings in patients with LQTS with LAEs (LQTS-LAEs group) was significantly higher than LQTS without LAEs (LQTS-non-LAEs group) (64.0 [42.0-86.0] μV versus 43.0 [36.0-53.0] μV; P<0.01). There was no statistical difference in TWA value measured by exercise stress tests between the 2 groups (69.0 [54.5-127.5] μV versus 68.5 [53.3-99.8] μV; P=0.871). The new cutoff point of the peak TWA value measured by 24-hour ambulatory recordings was 55.5 μV, with a sensitivity of 75.0% and a specificity of 78.6%. A univariate Cox regression analysis revealed that TWA value ≥55.5 μV was a strong predictor of LAEs (hazard ratio [HR], 4.5 [2.1-9.6]; P<0.001]. A multivariate Cox regression analysis indicated that TWA value ≥55.5 μV remained significant (HR, 2.7 [1.1-6.8]; P=0.034). Peak TWA measured by 24-hour ambulatory recordings was a more favorable risk stratification marker than exercise stress tests for patients with LQTS.

Cellular Senescence-Related Long Non-coding RNA Signatures Predict Prognosis in Juvenile Osteosarcoma

AbstractOsteosarcoma is the most common malignant bone tumor and is frequently diagnosed in juvenile. Cellular senescence is a fundamental hallmark of osteosarcoma and plays a vital role in the initiation and progression of aging and tumorigenesis. Long non-coding RNAs (lncRNAs) are implicated in tumorigenesis. In this study, six cellular senescence-related lncRNAs with independent prognostic significance in juvenile osteosarcoma patients were identified through univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis. Prognostic significance was further confirmed by Kaplan–Meier (KM) survival curves, co-expression interaction networks, and sankey diagrams. A prognostic model of cellular senescence-related genes in juvenile osteosarcoma patients was then constructed using multivariate Cox regression analysis based on these six genes. High- and low-risk groups were identified according to the median risk score calculated by the prognostic model. The favorable prognostic significance of this model was demonstrated through survival curves, receiver operating characteristic (ROC) curves, distribution scatter plots and lncRNA expression heatmaps. Furthermore, cellular senescence-related lncRNAs were validated by enrichment analysis, immunological correlation analysis, m6A correlation analysis, and drug sensitivity correlation analysis. These findings are important for improving the prognosis of juvenile osteosarcoma patients and understanding the mechanisms underlying cellular senescence in juvenile osteosarcoma development.

Cellular Senescence-Related Long Non-coding RNA Signatures Predict Prognosis in Juvenile Osteosarcoma

AbstractOsteosarcoma is the most common malignant bone tumor and is frequently diagnosed in juvenile. Cellular senescence is a fundamental hallmark of osteosarcoma and plays a vital role in the initiation and progression of aging and tumorigenesis. Long non-coding RNAs (lncRNAs) are implicated in tumorigenesis. In this study, six cellular senescence-related lncRNAs with independent prognostic significance in juvenile osteosarcoma patients were identified through univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis. Prognostic significance was further confirmed by Kaplan–Meier (KM) survival curves, co-expression interaction networks, and sankey diagrams. A prognostic model of cellular senescence-related genes in juvenile osteosarcoma patients was then constructed using multivariate Cox regression analysis based on these six genes. High- and low-risk groups were identified according to the median risk score calculated by the prognostic model. The favorable prognostic significance of this model was demonstrated through survival curves, receiver operating characteristic (ROC) curves, distribution scatter plots and lncRNA expression heatmaps. Furthermore, cellular senescence-related lncRNAs were validated by enrichment analysis, immunological correlation analysis, m6A correlation analysis, and drug sensitivity correlation analysis. These findings are important for improving the prognosis of juvenile osteosarcoma patients and understanding the mechanisms underlying cellular senescence in juvenile osteosarcoma development.

Risk factors for postoperative late deterioration in patients with spinal dural arteriovenous fistulas.

Approximately 86% of patients with spinal dural arteriovenous fistulas (SDVAFs) exhibit clinical improvement after surgery. However, 12%-55.8% of these patients experience late deterioration (LD) after an initial period of improvement. The risk factors for LD remain unclear. The aim of this study was to explore the risk factors for LD in SDVAF patients. The clinical data of patients who were admitted to two tertiary hospitals between June 2014 and May 2022 were reviewed. Patients were divided into two groups: the LD group and the no LD group. The severity of neurological dysfunction (NDF) was evaluated using the Modified Aminoff and Logue Scale. Univariable and multivariable Cox regression analyses were performed. A total of 105 eligible patients were enrolled, with a mean age of 57.55 ± 9.42 years. The LD group comprised 37 individuals, while the no LD group consisted of 68 individuals. According to the univariable analysis, preoperative NDF severity and treatment strategy were associated with the risk of LD. According to the multivariable analysis, patients who underwent microsurgery (MS) had a lower risk of LD than did those who underwent endovascular treatment (EVT; HR 0.197, 95% CI 0.085-0.457), and patients with severe NDF had a higher risk of LD than did those with mild NDF (HR 3.604, 95% CI 1.226-10.588), whereas the risk of LD in patients with moderate NDF was similar to that of patients with mild NDF (HR 1.352, 95% CI 0.519-3.524). EVT and severe preoperative NDF are independent risk factors for LD.

Long-term outcomes of CNS WHO grade 2 oligodendroglioma in adult patients: a single-institution experience

PurposeOligodendrogliomas (ODGs) are a subtype of diffuse lower-grade gliomas with overall survival of > 10 years. This study aims to analyze long-term outcomes and identify prognostic factors in patients with WHO grade 2 ODG.MethodsWe retrospectively reviewed 138 adult patients diagnosed with 1p/19q co-deleted ODG who underwent surgical resection or biopsy between 1994 and 2021, analyzing clinical data, treatment details, and outcomes. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier analysis. Univariate and multivariate Cox regression analyses were utilized to identify significant prognostic factors.ResultsIn the gross total resection (GTR) group, 63 (45.7%) underwent observation and 5 (3.6%) received postoperative treatment; in the non-GTR group, 37 (26.8%) were observed and 33 (23.9%) received postoperative treatment. The median PFS and OS were 6.8 and 18.4 years, respectively. Between adjuvant treatment and observation, there was no significant difference in PFS or OS. However, GTR or STR with less than 10% residual tumor exhibited significantly better PFS and OS compared to PR or biopsy (p = 0.022 and 0.032, respectively). Multivariate analysis revealed that contrast enhancement on MRI was associated with worse PFS (HR = 2.36, p < 0.001) and OS (HR = 5.89, p = 0.001). And the presence of seizures at presentation was associated with improved OS (HR = 0.28, p = 0.006).ConclusionThis study underscores favorable long-term outcomes for patients with 1p/19q co-deleted ODG WHO grade 2. Our findings indicate that the EOR plays a crucial role as a significant prognostic factor in enhancing PFS and OS outcomes in WHO grade 2 ODG.

Long-term outcomes of CNS WHO grade 2 oligodendroglioma in adult patients: a single-institution experience

PurposeOligodendrogliomas (ODGs) are a subtype of diffuse lower-grade gliomas with overall survival of > 10 years. This study aims to analyze long-term outcomes and identify prognostic factors in patients with WHO grade 2 ODG.MethodsWe retrospectively reviewed 138 adult patients diagnosed with 1p/19q co-deleted ODG who underwent surgical resection or biopsy between 1994 and 2021, analyzing clinical data, treatment details, and outcomes. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier analysis. Univariate and multivariate Cox regression analyses were utilized to identify significant prognostic factors.ResultsIn the gross total resection (GTR) group, 63 (45.7%) underwent observation and 5 (3.6%) received postoperative treatment; in the non-GTR group, 37 (26.8%) were observed and 33 (23.9%) received postoperative treatment. The median PFS and OS were 6.8 and 18.4 years, respectively. Between adjuvant treatment and observation, there was no significant difference in PFS or OS. However, GTR or STR with less than 10% residual tumor exhibited significantly better PFS and OS compared to PR or biopsy (p = 0.022 and 0.032, respectively). Multivariate analysis revealed that contrast enhancement on MRI was associated with worse PFS (HR = 2.36, p < 0.001) and OS (HR = 5.89, p = 0.001). And the presence of seizures at presentation was associated with improved OS (HR = 0.28, p = 0.006).ConclusionThis study underscores favorable long-term outcomes for patients with 1p/19q co-deleted ODG WHO grade 2. Our findings indicate that the EOR plays a crucial role as a significant prognostic factor in enhancing PFS and OS outcomes in WHO grade 2 ODG.

Identification of immune- and oxidative stress-related signature genes as potential targets for mRNA vaccines for pancreatic cancer patients.

Adenocarcinoma of the pancreas (PAAD) is one of the deadliest malignant tumors, and messenger ribonucleic acid vaccines, which constitute the latest generation of vaccine technology, are expected to lead to new ideas for the treatment of pancreatic cancer. The Cancer Genome Atlas-PAAD and Genotype-Tissue Expression data were merged and analyzed. Weighted gene coexpression network analysis was used to identify gene modules associated with tumor mutational burden among the genes related to both immunity and oxidative stress. Differentially expressed immune-related oxidative stress genes were screened via univariate Cox regression analysis, and these genes were analyzed via nonnegative matrix factorization. After immune infiltration analysis, least absolute shrinkage and selection operator regression combined with Cox regression was used to construct the model, and the usefulness of the model was predicted based on the receiver operating characteristic curve and decision curve analysis curves after model construction. Finally, metabolic pathway enrichment was analyzed using gene set enrichment analysis combined with Kyoto Encyclopedia of Genes and Genomes and gene ontology biological process analyses. This model consisting of the ERAP2, mesenchymal-epithelial transition factor (MET), CXCL9, and angiotensinogen (AGT) genes can be used to help predict the prognosis of pancreatic cancer patients more accurately than existing models. ERAP2 is involved in immune activation and is important in cancer immune evasion. MET binds to hepatocyte growth factor, leading to the dimerization and phosphorylation of c-MET. This activates various signaling pathways, including MAPK and PI3K, to regulate the proliferation, invasion, and migration of cancer cells. CXCL9 overexpression is associated with a poor patient prognosis and reduces the number of CD8 + cytotoxic T lymphocytes in the PAAD tumor microenvironment. AGT is cleaved by the renin enzyme to produce angiotensin 1, and AGT-converting enzyme cleaves angiotensin 1 to produce angiotensin 2. Exposure to AGT-converting enzyme inhibitors after pancreatic cancer diagnosis is associated with improved survival. The 4 genes identified in the present study - ERAP2, MET, CXCL9, and AGT - are expected to serve as targets for messenger ribonucleic acid vaccine development and need to be further investigated in depth.

A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells

Leukemia stem cells (LSCs) are recognized as the root cause of leukemia initiation, relapse, and drug resistance. Lipid species are highly abundant and essential component of human cells, which often changed in tumor microenvironment. LSCs remodel lipid metabolism to sustain the stemness. However, there is no useful lipid related biomarker has been approved for clinical practice in AML prediction and treatment. Here, we constructed and verified fatty acid metabolism-related risk score (LFMRS) model based on TCGA database via a series of bioinformatics analysis, univariate COX regression analysis, and multivariate COX regression analysis, and found that the LFMRS model could be an independent risk factor and predict the survival time of AML patients combined with age. Moreover, we revealed that Galectin-1 (LGALS1, the key gene of LFMRS) was highly expressed in LSCs and associated with poor prognosis of AML patients, and LGALS1 repression inhibited AML cell and LSC proliferation, enhanced cell apoptosis, and decreased lipid accumulation in vitro. LGALS1 repression curbed AML progression, lipid accumulation, and CD8+ T and NK cell counts in vivo. Our study sheds light on the roles of LFMRS (especially LGALS1) model in AML, and provides information that may help clinicians improve patient prognosis and develop personalized treatment regimens for AML.

Preoperative MRI-based nomogram to predict survival after curative resection in patients with gallbladder cancer: a retrospective multicenter analysis.

To use preoperative MRI data to construct a nomogram to predict survival in patients who have undergone R0 resection for gallbladder cancer. The present retrospective study included 143 patients (M:F, 76:67; 67.15years) with gallbladder cancer who underwent preoperative MRI and subsequent R0 resection between 2013 and 2021 at two tertiary institutions. Clinical and radiological features were analyzed using univariate and multivariate Cox regression analysis to identify independent prognostic factors. Based on the multivariate analysis, we developed an MRI-based nomogram for determining prognoses after curative resections of gallbladder cancer. We also obtained calibration curves for 1-,3-, and 5-year survival probabilities. The multivariate model consisted of the following independent predictors of poor overall survival (OS), which were used for constructing the nomogram: age (years; hazard ratio [HR] = 1.04; 95% confidence interval [CI], 1.04-1.07; p = 0.033); tumor size (cm; HR = 1.40; 95% CI, 1.09-1.79; p = 0.008); bile duct invasion (HR = 3.54; 95% CI, 1.66-7.58; p = 0.001); regional lymph node metastasis (HR = 2.47; 95% CI, 1.10-5.57; p = 0.029); and hepatic artery invasion (HR = 2.66; 95% CI, 1.04-6.83; p = 0.042). The nomogram showed good probabilities of survival on the calibration curves, and the concordance index of the model for predicting overall survival (OS) was 0.779. Preoperative MRI findings could be used to determine the prognosis of gallbladder cancer, and the MRI-based nomogram accurately predicted OS in patients with gallbladder cancer who underwent curative resection.

Analysis of glutathione Stransferase mu class 5 gene methylation as a prognostic indicator in low-grade gliomas

BACKGROUND: Low-grade gliomas (LGG) are a variety of brain tumors that show different clinical outcomes. The methylation of the GSTM5 gene has been noted in the development of LGG, however, its prognostic importance remains uncertain. OBJECTIVE: The objective of this study was to examine the correlation between GSTM5 DNA methylation and clinical outcomes in individuals diagnosed with LGG. METHODS: Analysis of GSTM5 methylation levels in LGG samples was conducted using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The overall survival based on GSTM5 methylation status was evaluated using Kaplan-Meier curves. The DNA methylation heatmap for particular CpG sites in the GSTM5 gene was visualized using the “pheatmap” R package. RESULTS: The study analyzed that LGG tumors had higher levels of GSTM5 methylation than normal tissues. There was an inverse relationship discovered between GSTM5 expression and methylation. LGG patients with hypermethylation of GSTM5 promoter experienced a positive outcome. Age, grade, and GSTM5 methylation were determined as independent prognostic factors in LGG through both univariate and multivariate Cox regression analyses. CONCLUSION: Methylation of GSTM5 DNA, specifically at certain CpG sites, is linked to a positive outlook in patients with LGG. Utilizing the “pheatmap” R package to visualize GSTM5 methylation patterns offers important information for identifying prognostic markers and therapeutic targets in low-grade gliomas.

Establishment of a nomogram to predict the overall survival of patients with collecting duct renal cell carcinoma

BackgroundCollecting duct carcinoma (CDC) is a rare histological type of renal cell carcinoma that lacks a prognostic prediction model. In this study, we developed a nomogram to predict the prognosis of CDC patients.MethodsData for patients (n = 247) diagnosed with CDC from 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were randomized into training (n = 165) and validation (n = 82) cohorts. Survival outcomes were evaluated by the Kaplan–Meier method. Significant variables determined by univariate and multivariate Cox regression analyses were used to construct the nomogram. C-indexes and calibration plots were applied to evaluate the performance of the nomogram.ResultsCDC patients had a median overall survival (OS) of 18.0 months (95% confidence interval: 13.7–22.3); 1-year, 3-year, and 5-year OS rates were 58.7%, 34.2%, and 29.4%, respectively. Independent prognostic factors, including age at diagnosis, tumor size, tumor grade, T stage, N stage, M stage, and surgery information, were identified by multivariate analysis. The nomogram was constructed based on significant factors in the training cohort. The C-indexes were 0.769 (training cohort) and 0.767 (validation cohort). The calibration curves for survival rates showed that the predicted and observed values were consistent.ConclusionsThis study constructed a nomogram to predict prognosis in patients with CDC. The nomogram performed well in predicting the 1-year, 3-year, and 5-year OS, which can help doctors actively monitor and follow up patients.

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma

BackgroundIn the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD).MethodsTranscriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies.ResultsA novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways.ConclusionsThis prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient’s disease.

Identification of a novel lactylation-related gene signature predicts the prognosis of multiple myeloma and experiment verification

Multiple myeloma (MM) is an incurable hematological malignancy with poor survival. Accumulating evidence reveals that lactylation modification plays a vital role in tumorigenesis. However, research on lactylation-related genes (LRGs) in predicting the prognosis of MM remains limited. Differentially expressed LRGs (DELRGs) between MM and normal samples were investigated from the Gene Expression Omnibus database. Univariate Cox regression and LASSO Cox regression analysis were applied to construct gene signature associated with overall survival. The signature was validated in two external datasets. A nomogram was further constructed and evaluated. Additionally, Enrichment analysis, immune analysis, and drug chemosensitivity analysis between the two groups were investigated. qPCR and immunofluorescence staining were performed to validate the expression and localization of PFN1. CCK-8 and flow cytometry were performed to validate biological function. A total of 9 LRGs (TRIM28, PPIA, SOD1, RRP1B, IARS2, RB1, PFN1, PRCC, and FABP5) were selected to establish the prognostic signature. Kaplan–Meier survival curves showed that high-risk group patients had a remarkably worse prognosis in the training and validation cohorts. A nomogram was constructed based on LRGs signature and clinical characteristics, and showed excellent predictive power by calibration curve and C-index. Moreover, biological pathways, immunologic status, as well as sensitivity to chemotherapy drugs were different between high- and low-risk groups. Additionally, the hub gene PFN1 is highly expressed in MM, knocking down PFN1 induces cell cycle arrest, suppresses cell proliferation and promotes cell apoptosis. In conclusion, our study revealed that LRGs signature is a promising biomarker for MM that can effectively early distinguish high-risk patients and predict prognosis.

Incidence and predictors of 2-year mortality following percutaneous left atrial appendage occlusion in the EWOLUTION trial.

Sufficient survival time following left atrial appendage occlusion (LAAO) is essential for ensuring the efficacy and cost-effectiveness of this strategy for stroke prevention. Understanding prognostic factors for early mortality after LAAO could optimize patient selection. In the current study, we perform an in-depth analysis of 2-year mortality after LAAO, focusing particularly on potential predictors. The EWOLUTION registry is a real-world cohort comprising 1020 patients that underwent LAAO. Endpoint definitions were pre-specified, and death was categorized as cardiovascular, non-cardiovascular, or unknown origin. Mortality rates were calculated from Kaplan-Meier estimates. Baseline characteristics significantly associated with death in univariate Cox regression analysis were incorporated into the multivariate analysis. All multivariate predictors were included in a risk model. Two-year mortality rate was 16.4% [confidence interval (CI): 14.0-18.7%], with 50% of patients dying from a non-cardiovascular cause. Multivariate baseline predictors of 2-year mortality included age [hazard ratio (HR) 1.05, CI: 1.03-1.08, per year increase], heart failure (HR 1.73, CI: 1.24-2.41), vascular disease (HR 1.47, CI: 1.05-2.05), valvular disease (HR 1.63, CI: 1.15-2.33), abnormal liver function (HR 1.80, CI: 1.02-3.17), and abnormal renal function (HR 1.58, CI: 1.10-2.27). Mortality rate exhibited a gradual rise as the number of risk factors increased, reaching 46.1% in patients presenting with five or six risk factors. One in six patients died within 2 years after LAAO. We identified six independent predictors of mortality. When combined, this model showed a gradual increase in mortality rate with a growing number of risk factors, which may guide appropriate patient selection for LAAO. The original EWOLUTION registry was registered at clinicaltrials.gov under identifier NCT01972282.

Identification and characterization of RAC1-related immune and prognostic subtypes of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with significant variability in prognosis among patients. Ras-related C3 botulinum toxin substrate 1 (RAC1) is a key focus in the area of cancer research. However, the molecular mechanisms of RAC1 in HCC remain incompletely elucidated. In this study, bioinformatics analysis was used, and public databases were used to obtain information about HCC cases. The samples were categorized into two groups of high and low expression based on the expression level of RAC1 gene. The limma package was used to calculate the differentially expressed genes between the two groups, and univariate Cox regression analysis was used to screen the prognostic related factors. Consensus clustering analysis was performed using the ConsensusClusterPlus package to identify molecular subtypes of HCC patients. Immune cell infiltration and ESTIMATE scores were assessed using the single sample gene set enrichment analysis and ESTIMATE algorithms. The sensitivity of different isoforms to chemotherapeutic agents was predicted by the oncoPredict package. Finally, we also performed cell function experiments to validate the biological role of RAC1 in vitro. Initially, we classified patients into high and low expression groups based on RAC1 gene expression levels and identified 195 up-regulated genes and 107 down-regulated genes. Through univariate Cox regression analysis, we screened out 169 prognosis-related factors. Furthermore, HCC patients were categorized into two subtypes. Subsequently, Kaplan-Meier survival curves showed that there was a significant difference in prognosis between the two molecular subtypes. Further analysis indicated substantial differences in gene expression levels and TIDE scores between two molecular subtypes. Moreover, these two subtypes exhibited varying sensitivity to chemotherapy drugs, as evidenced by differences in IC50 values. In addition, we found that the silence of RAC1 could effectively inhibit the migration and invasion of HCC cells in vitro. This study sheds light on the molecular intricacies of RAC1 in HCC and identifies patient populations that may benefit from immunotherapeutic interventions, with potential implications for tailored treatment strategies.

A Novel Amino Acid-Related Gene Signature Predicts Overall Survival in Patients With Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is an extremely harmful malignant tumor in the world. Since the energy metabolism and biosynthesis of HCC cells are closely related to amino acids, it is necessary to further explore the relationship between amino acid-related genes and the prognosis of HCC to achieve individualized treatment. We herein aimed to develop a prognostic model for HCC based on amino acid genes. In this study, RNA-sequencing data of HCC patients were downloaded from the TCGA-LIHC cohort as the training cohort and the GSE14520 cohort as the validation cohort. Amino acid-related genes were derived from the Molecular Signatures Database. Univariate Cox and Lasso regression analysis were used to construct an amino acid-related signature (AARS). The predictive value of this risk score was evaluated by Kaplan-Meier (K-M) curve, receiver operating characteristic (ROC) curve, univariate and multivariate Cox regression analysis. Gene set variation analysis (GSVA) and immune characteristics evaluation were used to explore the underlying mechanisms. Finally, a nomogram was established to help the personalized prognosis assessment of patients with HCC. The AARS comprises 14 amino acid-related genes to predict overall survival (OS) in HCC patients. HCC patients were divided into AARS-high group and AARS-low group according to the AARS scores. The K-M curve, ROC curve, and univariate and multivariate Cox regression analysis verified the good prediction efficiency of the risk score. Using GSVA, we found that AARS variants were concentrated in four pathways, including cholesterol metabolism, delayed estrogen response, fatty acid metabolism, and myogenesis metabolism. Our results suggest that the AARS as a prognostic model based on amino acid-related genes is of great value in the prediction of survival of HCC, and can help improve the individualized treatment of patients with HCC.