Univariate Cox Research Articles

P709 Role of NOD2 single nucleotide polymorphisms on ustekinumab drug durability in adult patients with Crohn’s disease

Abstract Background Ustekinumab (UST), a monoclonal antibody targeting the p19 subunit of the pro-inflammatory Interleukins 12 and 23, is a therapeutic option in patients with Crohn’s disease (CD) with high efficacy, although some patients will have to cease therapy with UST due to primary non-response, secondary loss of response, or adverse events. Single nucleotide polymorphisms (SNPs) in the Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) gene have been proposed as a prognostic factor in CD. Whether these NOD2 SNPs have an impact on UST drug durability among adult CD patients remains unclear. Methods CD patients were genotyped for the three most common NOD2 SNPs (rs2066844, rs2066845, and rs2066847). Hazard ratios (HR) for risk of NOD2 SNPs on UST durability were calculated using univariable and multivariable cox proportional hazard regression adjusting for age at first UST prescription, previous surgery, Montreal A, L, and B classification, present perianal disease, and previous anti-TNF exposure. Statistical analysis was conducted using SPSS. A two-tailed P value < 0.05 was considered statistically significant. All patients provided written informed consent. Results 92 CD patients were included in the analysis. Of those, 72 continued receiving UST until the end of the study. In univariable and multivariable analyses, NOD2 SNPs were not independent prognostic factors for UST drug durability (P>0.05 for all three NOD2 SNPs). However, age at first UST prescription (adjusted HR [aHR] 0.96, 95% confidence interval [CI] 0.93-1.00, P=0.028 for all tested NOD2 SNPs) and present perianal disease (aHR 2.65, 95% CI 1.11-6.31, P=0.028 for all tested NOD2 SNPs) were independent predictors of ustekinumab drug durability. Conclusion Among adult Crohn’s disease patients being treated with ustekinumab, the presence of NOD2 SNPs did not have a significant impact on ustekinumab drug durability.

Ferroptosis heterogeneity within the tumor microenvironment revealed a genetic blueprint of breast cancer.

The tumor microenvironment (TME) significantly influences disease progression through immune infiltration, while ferroptosis, a recently discovered cell death mechanism, plays a crucial role in tumor suppression. However, its role in breast cancer is not clear. In this study, we analyzed bulk RNA and single-cell RNA sequencing data from 1217 samples, including 1104 breast cancer patients and 113 controls, to identify ferroptosis-related genes (FRGs) and construct a prognostic model. Using univariate cox regression, LASSO regression, and multivariate cox regression analysis, we discovered 21 FRGs and 3 TME-related immune cell types with prognostic value. Dimensionality reduction clustering and visualization were performed using the UMAP method, while the immune infiltration process was calculated with the TIP online tool. We employed GSEA enrichment analysis, WGCNA clustering analysis, and correlation analysis to examine functional differences, and the mutation analysis of the best and worst prognosis groups was conducted using the maftools package. Our findings revealed that knocking down the expression of the hub gene SLC39A7 significantly impacted cancer cell apoptosis and combining ferroptosis and TME scores yielded high prognostic power. Epithelial cells and B cells exhibited higher ferroptosis scores, which were independently associated with immune checkpoint blockade (ICB) response and ICB gene expression. This study provides a foundation for further exploration of the relationship between ferroptosis and ICB response in breast cancer. In conclusion, we developed a prognostic model based on ferroptosis and infiltrated immune cells that effectively stratified breast cancer patients and demonstrated the role of SLC39A7 in breast cancer pathogenesis through the regulation of apoptosis.

Neoadjuvant chemotherapy vs upfront resection: A challenging choice in resectable pancreatic ductal adenocarcinoma.

620 Background: Pancreatic ductal adenocarcinoma (PDAC) remains an immense challenge within oncology, with only 15-20% of cases initially qualifying as resectable. Based on National Cancer Database analyses there is an increase in neoadjuvant chemotherapy (NACT) use, with potential downstaging effects. Yet, a subset of neoadjuvant-treated patients fail to proceed with curative-intent surgery, leading to worse outcomes. This retrospective analysis aims to uncover factors that predict NACT use and the impact on survival outcomes. Methods: A cohort of 543 consecutive non-metastatic PDAC patients treated at an NCCN-designated comprehensive cancer center between 2015 and 2022 were prospectively enrolled into a REDCap database. Based on NCCN resectability criteria, initial CT staging placed 96 patients as upfront resectable. Survival outcomes were compared using univariate and multivariate cox regression analyses. Results: Within 96 resectable patients, 45 (47%) underwent upfront surgery, 36 (37%) received NACT followed by surgery and 15 (16%) only received chemotherapy. The majority were CA19-9 secretors (94%) with 54% lower values during chemotherapy. While 60% of patients experienced up to 35% tumor size reductions on NACT, 20% had stable disease, and 20% showed progressive disease. The patients who received NACT were significantly younger (p = 0.01), with higher baseline CA19-9 (p < 0.01) and more frequently underwent stent placement (p = 0.01), table 1. Median overall survival for the upfront surgery, NACT+surgery and chemotherapy groups were 32.8, 23.7 and 20.2 months (log-rank test p<0.01) subsequently. On univariate analysis initial presentation with weight loss (p = 0.02, HR = 2.08) and high baseline CA19-9 (log2-scaled, p = 0.01, HR = 1.13) were predictive of worse overall survival. After adjusting for potential confounding variables, patients in chemotherapy group had significantly worse survival compared to the upfront surgery group (P < 0.01, HR = 3.14). These 15 patients failed to undergo surgery due to diverse reasons, including distant progression (7), local progression (3), performance status decline or death during chemotherapy (2), refusal due to chemotherapy side effects (2), and indecision and loss to follow-up (1). Conclusions: These findings underscore the need for more robust selection criteria in resectable PDAC patients to undergo NACT. Leveraging real-world data helps identify predictive factors of treatment decision making and their impact on patient survival outcomes. [Table: see text]

MTFR2-dependent mitochondrial fission promotes HCC progression

BackgroundThe role of mitochondrial dynamics, encompassing fission, fusion, and mitophagy, in cancer progression has been extensively studied. However, the specific impact of mitochondrial dynamics on hepatocellular carcinoma (HCC) is still under investigation.MethodsIn this study, mitochondrial dynamic genes were obtained from the MitoCarta 3.0 database, and gene expression data were collected from The Cancer Genome Atlas (TCGA) database. Based on the expression of these dynamic genes and differentially expressed genes (DEGs), patients were stratified into two clusters. Subsequently, a prognostic model was constructed using univariate COX regression and the least absolute shrinkage and selection operator (LASSO) regression, and the prognostic signature was evaluated. We analyzed the interaction between these model genes and dynamic genes to identify hub genes and reveal mitochondrial status. Furthermore, we assessed immune infiltration, tumor mutational burden (TMB), tumor stemness indices (TSI), and the response to immune checkpoint block (ICB) therapy using the TIDE algorithm and risk scores. Additionally, transmission electron microscopy (TEM), hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC), western blotting (WB), and immunofluorescence (IF) were conducted to afford detailed visualization of the morphology of the mitochondria and the expression patterns of fission-associated proteins.ResultsPatients in Cluster 2 exhibited heightened mitochondrial fission and had a worse prognosis. The up-regulated dynamic genes in Cluster 2 were identified as fission genes. GO/KEGG analyses reconfirmed the connection of Cluster 2 to augmented mitochondrial fission activities. Subsequently, a ten-gene prognostic signature based on the differentially expressed genes between the two clusters was generated, with all ten genes being up-regulated in the high-risk group. Moreover, the potential links between these ten signature genes and mitochondrial dynamics were explored, suggesting their involvement in mediating mitochondrial fission through interaction with MTFR2. Further investigation revealed that the high-risk group had an unfavorable prognosis, with a higher mutation frequency of TP53, increased immune checkpoint expression, a higher TIS score, and a lower TIDE score. The mitochondrial imbalance characterized by increased fission and upregulated MTFR2 and DNM1L expression was substantiated in both HCC specimens and cell lines.ConclusionsIn conclusion, we developed a novel MTFR2-related prognostic signature comprising ten mitochondrial dynamics genes. These genes play crucial roles in mitochondrial fission and have the potential to serve as important predictors and therapeutic targets for HCC.

Development and validation of epigenetic modification-related signals for the diagnosis and prognosis of colorectal cancer

BackgroundColorectal cancer (CRC) is one of the world's most common malignancies. Epigenetics is the study of heritable changes in characteristics beyond the DNA sequence. Epigenetic information is essential for maintaining specific expression patterns of genes and the normal development of individuals, and disorders of epigenetic modifications may alter the expression of oncogenes and tumor suppressor genes and affect the development of cancer. This study elucidates the relationship between epigenetics and the prognosis of CRC patients by developing a predictive model to explore the potential value of epigenetics in the treatment of CRC.MethodsGene expression data of CRC patients’ tumor tissue and controls were downloaded from GEO database. Combined with the 720 epigenetic-related genes (ERGs) downloaded from EpiFactors database, prognosis-related epigenetic genes were selected by univariate cox and LASSO analyses. The Kaplan–Meier and ROC curve were used to analyze the accuracy of the model. Data of 238 CRC samples with survival data downloaded from the GSE17538 were used for validation. Finally, the risk model is combined with the clinical characteristics of CRC patients to perform univariate and multivariate cox regression analysis to obtain independent risk factors and draw nomogram. Then we evaluated the accuracy of its prediction by calibration curves.ResultsA total of 2906 differentially expressed genes (DEGs) were identified between CRC and control samples. After overlapping DEGs with 720 ERGs, 56 epigenetic-related DEGs (DEERGs) were identified. Combining univariate and LASSO regression analysis, the 8 epigenetic-related genes-based risk score model of CRC was established. The ROC curves and survival difference of high and low risk groups revealed the good performance of the risk score model based on prognostic biomarkers in both training and validation sets. A nomogram with good performance to predict the survival of CRC patients were established based on age, NM stage and risk score. The calibration curves showed that the prognostic model had good predictive performance.ConclusionIn this study, an epigenetically relevant 8-gene signature was constructed that can effectively predict the prognosis of CRC patients and provide potential directions for targeted therapies for CRC.

Optimal treatment strategy and prognostic analysis for patients with non-metastatic pT4 colon adenocarcinoma.

This study endeavored to explore the optimal treatment strategy and conduct a prognostic analysis for patients diagnosed with pT4M0 (pathologic stage T4) colon adenocarcinoma (COAD). A total of 8,843 patients diagnosed with pT4M0 COAD between January 2010 and December 2015 were included in this study from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly divided into a training set and an internal validation set using a 7:3 ratio. Variables that demonstrated statistical significance (P<0.05) in univariate COX regression analysis or held clinical significance were incorporated into the multivariate COX regression model. Subsequently, this model was utilized to formulate a nomogram. The predictive accuracy and discriminability of the nomogram were assessed using the C-index, area under the curve (AUC), and calibration curves. Decision curve analysis (DCA) was conducted to confirm the clinical validity of the model. In the entire SEER cohort, the 3-year overall survival (OS) rate (74.22% vs. 63.20%, P<0.001) and the 3-year cancer-specific survival (CSS) rate (76.25% vs. 66.98%, P<0.001) in the surgery combined with postoperative adjuvant therapy (S+ADT) group surpassed those in the surgery (S) group. Multivariate COX regression analysis of the training set unveiled correlations between age, race, N stage, serum CEA (carcinoembryonic antigen), differentiation, number of resected lymph nodes, and treatment modalities with OS and CSS. Nomograms for OS and CSS were meticulously crafted based on these variables, achieving C-indexes of 0.692 and 0.690 in the training set, respectively. The robust predictive ability of the nomogram was further affirmed through receiver operating characteristic (ROC) and calibration curves in both the training and validation sets. In individuals diagnosed with pT4M0 COAD, the integration of surgery with adjuvant chemoradiotherapy demonstrated a substantial extension of long-term survival. The nomogram, which incorporated key factors such as age, race, differentiation, N stage, serum CEA level, tumor size, and the number of resected lymph nodes, stood as a dependable tool for predicting OS and CSS rates. This predictive model held promise in aiding clinicians by identifying high-risk patients and facilitating the development of personalized treatment plans.

EPYC functions as a novel prognostic biomarker for pancreatic cancer

Pancreatic cancer (PC) has become a worldwide challenge attributed to its difficult early diagnosis and rapid progression. Treatments continue to be limited besides surgical resection. Hence, we aimed to discover novel biological signatures as clinically effective therapeutic targets for PC via the mining of public tumor databases. We found that epiphycan (EPYC) could function as an independent risk factor to predict the poor prognosis in PC based on integrated bioinformatics analysis. We downloaded associated PC data profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) online websites, then applied the software Rstudio to filter out genes under the strict criteria. After the batch survival analysis using Log-rank test and univariate cox regression, we obtained 39 candidate genes. Subsequently, we narrowed the scope to 8 genes by establishing a Lasso regression model. Eventually, we focused on 2 genes (EPYC and MET) by further building a multivariate cox regression model. Given that the role of EPYC in PC remains obscure, we then performed a series of molecular functional experiments, including RT-qPCR, CCK8, EdU, colony formation, Transwell, western blot, cell live-dead staining, subcutaneous tumor formation, to enhance our insight into its underlying molecular mechanisms. The above results demonstrated that EPYC was highly expressed in PC cell lines and could promote the proliferation of PCs via PI3K-AKT signaling pathway in vivo and in vitro. We arrived at a conclusion that EPYC was expected to be a biological neo-biomarker for PC followed by being a potential therapeutic target.

Development and validation of a novel lysosome-related LncRNA signature for predicting prognosis and the immune landscape features in colon cancer

Lysosomes are essential components for managing tumor microenvironment and regulating tumor growth. Moreover, recent studies have also demonstrated that long non-coding RNAs could be used as a clinical biomarker for diagnosis and treatment of colorectal cancer. However, the influence of lysosome-related lncRNA (LRLs) on the progression of colon cancer is still unclear. This study aimed to identify a prognostic LRL signature in colon cancer and elucidated potential biological function. Herein, 10 differential expressed lysosome-related genes were obtained by the TCGA database and ultimately 4 prognostic LRLs for conducting a risk model were identified by the co-expression, univariate cox, least absolute shrinkage and selection operator analyses. Kaplan–Meier analysis, principal-component analysis, functional enrichment annotation, and nomogram were used to verify the risk model. Besides, the association between the prognostic model and immune infiltration, chemotherapeutic drugs sensitivity were also discussed in this study. This risk model based on the LRLs may be promising for potential clinical prognosis and immunotherapeutic responses related indicator in colon cancer patients.

Screening of coexpression genes of immune cells in breast cancer tissues.

This study aimed to investigate immune cell infiltration (ICI) in breast cancer tissues and its impact on the prognosis of patients. The whole transcriptome sequencing data sets of breast tissue (GSE126125, GSE190275 and GSE45498) were downloaded from Gene Expression Omnibus database. Data sets, including 281 breast cancer tissue samples and 59 normal breast tissue samples. In this study, the CIBERSORT algorithm was used to calculate the infiltration content of 22 immune cells subtypes in breast cancer tissues and normal breast tissues. The ICI between normal and breast cancer tissue samples was examined through the Rank-sum test. Furthermore, Kaplan-Meier and the log-rank test were used for survival analysis. Univariate and multivariate COX analysis was used to screen the prognostic risk factors of breast cancer based on ICI. The correlation between 22 kinds of immune cells was analyzed by the Pearson test. The results of univariate COX analysis indicated that resting dendritic cells, eosinophils, resting mast cells, monocytes, and memory CD4 T cells resting were protective factors for the prognosis of breast cancer patients (hazard ratio [HR] < 1, P < .05). The activation of macrophage M0 and mast cells were also prognostic risk factors for breast cancer patients (HR > 1, P < .05). Besides, multivariate COX analysis showed that resting mast cells were independent protective factors for the prognosis of breast cancer patients (HR < 1, P < .05). Macrophage M0 and mast cell activation were independent risk factors for the prognosis of breast cancer patients (HR > 1, P < .05). High infiltration of macrophage M0 and activated mast cells is associated with poor prognosis. Meanwhile, macrophage M0 and activated mast cells promote breast cancer progression. Low infiltration of resting mast cells is associated with poor prognosis, which inhibits breast cancer progression.

Development and Validation of Anoiki-Related Lncrna Signature Prediction Model for KIRC Prognosis.

Various cancer types have been studied and understood using long noncoding RNA (lncRNA). Despite this, only a few studies have examined anoikis-related lncRNAs in kidney renal clear cell carcinoma (KIRC). As a result, this study evaluated a powerful prognostic model for KIRC patients based on anoikis-lncRNAs and identified potential biological targets. Anoikis-related lncRNAs associated with patient prognosis were identified using Pearson correlation, variance, and univariate Cox regression analyses. A predictive model that incorporated 4 anoikis-related lncRNAs has been constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm. The prognostic performance of the proposed model has also been assessed utilizing Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analyses. An ESTIMATE analysis was carried out on the low- as well as high-risk subtypes to evaluate immune cell infiltration status. Furthermore, CIBERSORT, TIMER, and QUANTISEQ along with other algorithms were applied for determining the infiltration status of numerous immune cells across both groups. In addition, immune checkpoint gene expression in both groups was also determined. Finally, drug sensitivity assays and in vitro experiments were performed to validate the results. A total of sixty-three lncRNAs associated with anoikis and KIRC prognosis were identified via univariate cox analysis, and four lncRNAs (Z99289.2, AC084876.1, LINC00460, and AC090337.2.) were selected as hub lncRNAs. A prognostic signature has been developed based on the expression levels and coefficiency of these four lncRNAs while establishing its efficacy in part and whole TCGA KIRC cohort. Furthermore, by using this risk signature, high- as well as low-risk KIRC patients could be distinguished more precisely it can predict patient outcomes as well. The survival predictions by the nomogram exhibited an absolute degree of concordance with actual situations. In vitro experiments verified that LINC00460 downregulation contributed to the growth inhibition of KIRC cell lines and promoted apoptosis of cancer cells. This study suggests that anoikis-related lncRNAs could serve as valuable prognostic markers for KIRC. Additionally, they may provide insight into future KIRC treatment options by reflecting on the situation of the kidney immune microenvironment.

Factors and a model to predict three-month mortality in patients with acute fatty liver of pregnancy from two medical centers

BackgroundAcute fatty liver of pregnancy (AFLP) is an uncommon but potentially life-threatening complication. Lacking of prognostic factors and models renders prediction of outcomes difficult. This study aims to explore factors and develop a prognostic model to predict three-month mortality of AFLP.MethodsThis retrospective study included 78 consecutive patients fulfilling both clinical and laboratory criteria and Swansea criteria for diagnosis of AFLP. Univariate and multivariate cox regression analyses were used to identify predictive factors of mortality. Predictive efficacy of prognostic index for AFLP (PI-AFLP) was compared with the other four liver disease models using receiver operating characteristic (ROC) curve.ResultsAFLP-related three-month mortality of two medical centers was 14.10% (11/78). International normalised ratio (INR, hazard ratio [HR] = 3.446; 95% confidence interval [CI], 1.324–8.970), total bilirubin (TBIL, HR = 1.005; 95% CI, 1.000-1.010), creatine (Scr, HR = 1.007; 95% CI, 1.001–1.013), low platelet (PLT, HR = 0.964; 95% CI, 0.931–0.997) at 72 h postpartum were confirmed as significant predictors of mortality. Artificial liver support (ALS, HR = 0.123; 95% CI, 0.012–1.254) was confirmed as an effective measure to improve severe patients’ prognosis. Predictive accuracy of PI-AFLP was 0.874. Area under the receiver operating characteristic curves (AUCs) of liver disease models for end-stage liver disease (MELD), MELD-Na, integrated MELD (iMELD) and pregnancy-specific liver disease (PSLD) were 0.781, 0.774, 0.744 and 0.643, respectively.ConclusionTBIL, INR, Scr and PLT at 72 h postpartum are significant predictors of three-month mortality in AFLP patients. ALS is an effective measure to improve severe patients’ prognosis. PI-AFLP calculated by TBIL, INR, Scr, PLT and ALS was a sensitive and specific model to predict mortality of AFLP.

Left Ventricular-Arterial Coupling as an Independent Predictor of Adverse Events in Young Patients with ST Elevation Myocardial Infarction-A 3D Echocardiographic Study.

Left ventricular-arterial coupling (VAC) is a key determinant of global cardiovascular performance, calculated as the ratio between arterial elastance (EA) and left ventricular end-systolic elastance (EES). Over the years, acute myocardial infarction (STEMI) has remained an important cause of morbidity and mortality worldwide. Although, until recently, it was considered a disease occurring mostly in older patients, its prevalence in the young population is continuously rising. In this study, we aimed to investigate the role of 3D VAC and its derived indices in predicting adverse outcomes in young patients with STEMI. We prospectively enrolled 84 young patients (18-51 years) with STEMI who underwent primary PCI and 28 healthy age and sex-matched controls. A 3D echocardiography was used for non-invasive measurements of end-systolic elastance (EES), arterial elastance (EA), and VAC (EA/EES). The occurrence of major adverse cardiac events (MACE) was assessed one year after the index STEMI. Out of 84 patients, 15.4% had adverse events at 12 months follow-up. Patients were divided into two groups according to the presence or absence of MACE. There were no significant differences in arterial elastance between the two groups. EA was higher in the MACE group but without statistical significance (2.65 vs. 2.33; p = 0.09). EES was significantly lower in the MACE group (1.25 ± 0.34 vs. 1.91 ± 0.56. p < 0.0001) and VAC was higher (2.2 ± 0.62 vs. 1.24 ± 0.29, p < 0.0001). ROC analysis showed that VAC has a better predictive value for MACE (AUC 0.927) compared with EA or EEA but also compared with a classical determinant of LV function (LVEF and LVGLS). A VAC value over 1.71 predicts unfavourable outcome with 83.3% sensitivity and 97.1% specificity. In both univariate and multivariate COX regression analysis, VAC remained an independent predictor for MACE and demonstrated incremental prognostic value over LVEF and LVGLS in the proposed statistical models. In conclusion, 3D VAC is an independent predictor of adverse events in young patients with STEMI at a 12 month follow-ups and could be used for a more accurate risk stratification in the acute phase.

Evaluation of the clinical efficacy of Ru'ai Shuhou recipe for the prevention of lung metastases from breast cancer: a retrospective study based on propensity score matching.

Breast cancer lung metastasis occurs at a high rate and at an early stage, and is the leading cause of death in breast cancer patients. The aim of this study was to investigate the effect of Ru'ai Shuhou Recipe (RSR) intervention on the occurrence of recurrent metastases, especially lung metastases, in postoperative patients with breast cancer. A retrospective cohort study was implemented at Shuguang Hospital of Shanghai University of Traditional Chinese Medicine in China between January 2014 to January 2019. Female patients were included according to the propensity score matching (PSM) method and balanced on the basis of general and clinical information such as age, body mass index, neo-adjuvant therapy, and surgical approach. Patients with pathological diagnosis of breast cancer were included in this study. Breast cancer patients were divided into exposed and non-exposed groups according to whether they took RSR-based botanical drugs after surgery. Kaplan-Meier survival analysis and Cox survival analysis to explore the relationship between RSR and 5-year disease-free survival and incidence of lung metastases in breast cancer patients after surgery. 360 female patients were assessed and 190 patients were included in the study after PSM (95 in each of the exposed and non-exposed groups). Of the 190 patients after PSM, 55.79% were over 50years of age. The mean follow-up time was 60.55 ± 14.82months in the exposed group and 57.12 ± 16.37months in the non-exposed group. There was no significant baseline characteristics difference between two groups. Kaplan-Meier analysis showed that the 5-year incidence of lung metastases was significantly lower in the exposed group, and the disease-free survival of patients was significantly longer. Cox univariate and multivariate analysis showed that neoadjuvant chemotherapy and lymph node metastasis were independent risk factors for the development of breast cancer lung metastasis, with risk ratios of 17.188 and 5.812, while RSR treatment was an independent protective factor against the development of breast cancer lung metastasis, with a risk ratio of 0.290. Standard biomedical treatment combined with RSR intervention can better prevent breast cancer recurrence and metastasis, reduce the incidence of lung metastasis in patients, and improve long-term prognosis.

Analysis of Correlation between Blood Inflammation Indicators in Peripheral Blood and Prognosis of Patients with Multiple Myeloma.

This study aimed to investigate the value of the peripheral blood neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) in the prognosis of patients with multiple myeloma (MM). Before treatment, the NLR and LMR and all clinical indicators of 168 patients, diagnosed with MM at the Affiliated Hospital of Southwest Medical University from April 2013 to April 2022, were retrospectively analyzed, and the patients were grouped according to their median NLR counts and median LMR counts. Differences between the groups were compared by using the chi-squared (χ²) test, the Kaplan-Meier survival curve and Log-rank test were used for survival analysis and difference comparison, and the COX proportional risk model was constructed to analyze the factors affecting the prognosis of the MM patients. The test level was α = 0.05. The groups were divided into high NLR group (> 2.19) and low NLR group (≤ 2.19) and high LMR group (> 3.45) and low LMR group (≤ 3.45), according to the median NLR and LMR values. The clinical stage, blood β2 microglobulin, and serum creatinine levels in the high NLR group were higher than in the low NLR group, and the differences between the groups were statistically significant (p < 0.05). The clinical stage and blood β2 microglobulin in the low LMR group were higher than in the high LMR group, and the differences between the groups were statistically significant (p < 0.05). The Cox univariate and multivariate analyses showed that peripheral blood NLR < 2.19 and LMR ≤ 3.45 were independent risk factors for the prognosis in patients with MM (p < 0.05). High NLR and low LMR counts of peripheral blood suggest a poor prognosis; NLR and LMR may be prognostic indicators in MM patients.

The Potential of Lipid Droplet-associated Genes as Diagnostic and Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma.

The role of lipid droplets (LDs) and lipid droplet-associated genes (LD-AGs) remains unclear in head and neck squamous cell carcinoma (HNSCC). This study aimed to investigate LDs in HNSCC and identify LD-AGs essential for the diagnosis and prognosis of HNSCC patients. The LDs in the HNSCC and normal cell lines were stained with oil red O. Bioinformatic analysis was used to find LD-AGs in HNSCC that had diagnostic and prognostic significance. LDs accumulation was increased in HNSCC cell lines compared with normal cell lines (P<0.05). Fifty-three differentially expressed genes, including 34 upregulated and 19 downregulated, were found in HNSCC based on the TCGA platform (P<0.05). Then, 53 genes were proved to be functionally enriched in lipid metabolism and LDs. Among them, with an AUC value > 0.7, 34 genes demonstrated a high predictive power. Six genes (AUP1, CAV1, CAV2, CAVIN1, HILPDA, and SQLE) out of 34 diagnostic genes were linked to overall survival in patients with HNSCC (P<0.05). The significant prognostic factors AUP1, CAV1, CAV2, and SQLE were further identified using the univariate and multivariate cox proportional hazard models (P<0.05). The protein expression of CAV2 and SQLE was significantly increased in the HNSCC tissue compared to normal tissues (P<0.05). Finally, the knockdown of the four LD-AGs decreased LDs accumulation, respectively. Increased LDs accumulation was a hallmark of HNSCC, and AUP1, CAV1, CAV2, and SQLE were discovered as differentially expressed LD-AGs with diagnostic and prognostic potential in HNSCC.

A Associação de Pressão Arterial Definida pelas Diretrizes ACC/AHA de 2017 e Risco de Doença Cardiovascular para Pessoas de Meia-Idade e Idosas na China: Um Estudo de Coorte

Abstract Background Cardiovascular disease (CVD) is a series of diseases affecting the heart or blood vessels. Objectives To assess the relationship between blood pressure (BP) levels defined by the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline and CVD/atherosclerotic cardiovascular disease (ASCVD) risk for middle-aged and elderly people in China. Methods A total of 6,644 middle-aged and elderly people from the China Health and Retirement Longitudinal Study (CHARLS) were finally included. According to the 2017 ACC/AHA guideline, all subjects were divided into four groups: normal BP, elevated BP, stage 1 hypertension, and stage 2 hypertension. The outcome of this study was considered as the risk of CVD and ASCVD. Univariate and multivariate COX regression models were adopted to examine the relationship of the 2017 ACC/AHA BP classification with the risk of CVD. Univariate and multivariate logistic regression models were used to investigate the association between BP levels and ASCVD risk. Subgroup analyses based on age, gender, and use of antihypertensive drugs were performed. P&lt;0.05 was accepted as statistically significant. Results After adjusting all covariates, compared to middle-aged and elderly patients with normal BP, we found that patients with stage 1/2 hypertension were associated with a higher risk of CVD, separately. Simultaneously, we also observed a positive association between individuals with elevated BP, stage 1 hypertension, stage 2 hypertension, and higher ASCVD risk in the fully adjusted model. The result of subgroup analyses implied that the relationship between stage 1/2 hypertension and CVD/ high ASCVD was robust in different ages and genders, and participants without using antihypertensive drugs. Conclusion BP classification under the 2017 ACC/AHA BP guidelines may apply to the Chinese population.

Albumin corrected anion gap for predicting in-hospital death among patients with acute myocardial infarction: A retrospective cohort study

ObjectiveTo explore the relationship between Anion Gap (AG), Albumin Corrected AG (ACAG), and in-hospital mortality of Acute Myocardial Infarction (AMI) patients and develop a prediction model for predicting the mortality in AMI patients. MethodsThis was a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-Ⅲ, MIMIC-IV, and eICU Collaborative Study Database (eICU). A total of 9767 AMI patients who were admitted to the intensive care unit were included. The authors employed univariate and multivariable cox proportional hazards analyses to investigate the association between AG, ACAG, and in-hospital mortality; p < 0.05 was considered statistically significant. A nomogram incorporating ACAG and clinical indicators was developed and validated for predicting mortality among AMI patients. ResultsBoth ACAG and AG exhibited a significant association with an elevated risk of in-hospital mortality in AMI patients. The C-index of ACAG (C-index = 0.606) was significantly higher than AG (C-index = 0.589). A nomogram (ACAG combined model) was developed to predict the in-hospital mortality for AMI patients. The nomogram demonstrated a good predictive performance by Area Under the Curve (AUC) of 0.763 in the training set, 0.744 and 0.681 in the external validation cohort. The C-index of the nomogram was 0.759 in the training set, 0.756 and 0.762 in the validation cohorts. Additionally, the C-index of the nomogram was obviously higher than the ACAG and age shock index in three databases. ConclusionACAG was related to in-hospital mortality among AMI patients. The authors developed a nomogram incorporating ACAG and clinical indicators, demonstrating good performance for predicting in-hospital mortality of AMI patients.

Elevated Fibrinogen-to-Albumin Ratio Correlates with Incident Stroke in Cerebral Small Vessel Disease.

We aimed to explore the association between fibrinogen-to-albumin ratio (FAR) and the risk of incident stroke (IS) in a cohort of cerebral small vessel disease (CSVD) patients. Participants were screened from a prospective CSVD database. Clinical data, hematologic measures and imaging findings were collected. The primary outcome was IS during follow-up, with a secondary outcome of composite vascular events (CVE) including IS, myocardial infarction (MI), and vascular deaths. Univariate and multivariate COX proportional risk models, along with competing risk models, were employed to identify factors associated with outcomes. Restricted cubic spline (RCS) and subgroup analyses were conducted to assess the association between FAR and the risk of IS and CVE in CSVD patients. In the final analysis of 682 CSVD patients over a median observation period of 34.0 [24.0-53.0] months, there were 33 cases of IS (4.84%, 1.55/100 person-years), 4 incidents of MI (0.59%, 0.19/100 person-years), 15 non-vascular deaths (2.20%, 0.70/100 person-years), and 37 occurrences of CVE (5.43%, 1.74/100 person-years). Multivariate Cox regression analysis revealed a significant positive correlation between elevated FAR and both IS (HR 1.146; 95% CI 1.043-1.259; P=0.004) and CVE (HR 1.156; 95% CI 1.063-1.257; P=0.001) in CSVD patients. Multivariate competing risk model showed the similar results (IS: HR 1.16; 95% CI 1.06-1.27; P=0.001, CVE: HR 1.15; 95% CI 1.05-1.26; P=0.003). RCS analysis indicated a linear relationship between FAR and the risks of both IS (P for non-linearity =0.7016) and CVE (P for non-linearity =0.6475), with an optimal cutoff value of 8.69, particularly in individuals over 60 years of age. Elevated FAR demonstrated an independent and linear association with IS and the development of CVE in CSVD patients.

The significance of HAUS1 and its relationship with immune microenvironment in hepatocellular carcinoma.

Background: HAUS Augmin-like complex subunit 1(HAUS1), as a controlling gene, which affected the production of spindle was firstly discovered in Drosophila cells. Although HAUS1 has been intensively studied, but its significance and relationship with the immune microenvironment in Hepatocellular carcinoma (HCC) remain unclear. Materials and Methods: All data of HCC in this paper were obtained from The Cancer Genome Atlas(TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and the Human Protein Atlas(HPA) database. The role and potential value of HAUS1 in the tumorigenesis and development of HCC were studied by applying plenty of bioinformatics analysis methods. Knocked down the expression of HAUS1 through siRNA and further investigated the function of HAUS1 in HCC Results: HAUS1 was highly expressed in HCC, which led to a poor prognosis. ROC curve analysis showed that HAUS1 had a excellent diagnostic value. It was also associated with clinical stage, pathological grade and AFP of HCC. Univariate and multivariate COX regression analysis showed that HAUS1 was an independent prognostic factor for HCC patients. HAUS1 was associated with immune cells infiltrate and immune checkpoints in HCC, and it could generate significative therapeutic results when combined with anti-CTLA4 and anti-CD274 treatment. In vitro experiments, HAUS1 was found to promote the proliferation, invasion and metastasis, participated in cell cycle regulation and inhibited apoptosis of HCC. Conclusion: These results suggested that HAUS1 might serve as a potential therapeutic target, as well as a diagnostic, prognostic, and survival biomarker for HCC.

ASB6 as an Independent Prognostic Biomarker for Colorectal Cancer Progression Involves Lymphatic Invasion and Immune Infiltration.

Background: ASB6, an E3 ubiquitin ligase, mediates the proteasomal degradation of its substrate proteins via the ubiquitin-proteasome pathway. ASB6 has been reported to play significant roles in several biological processes, including tumor stemness and endoplasmic reticulum stress. However, the underlying role and mechanism of ASB6 in colorectal cancer, particularly its association with immune infiltration levels and its prognostic significance, remain to be fully elucidated. Methods: We identified key prognostic genes in CRC patients through LASSO-penalized Cox regression, Univariate and Multivariate Cox regression analyses. Subsequently, we comprehensively analyzed the prognostic value of hub genes and constructed a prognostic nomogram. Finally, we identified ASB6 interacting proteins through immunoprecipitation-mass spectrometry (IP-MS) and constructed protein-protein interaction (PPI) networks and performed pathway enrichment analysis to explore the potential mechanisms of ASB6. Meanwhile, we evaluated the functions of ASB6 in CRC cells through in vitro cell experiments. Results: We identified ASB6 as a hub gene in CRC. ASB6 was highly expressed in CRC, and patients with high ASB6 expression had worse Disease-Free Interval (DFI), Disease-Specific Survival (DSS), Overall Survival (OS), and Progression-Free Interval (PFI). Correlation analysis showed that ASB6 expression were positively correlated with lymph node invasion and distal metastasis. Overexpression of ASB6 enhanced the migration ability of CRC cells. Multivariate Cox regression analysis revealed that ASB6 was an independent prognostic factor for OS and DSS in CRC. The nomogram model constructed based on multivariate analysis results had good predictive effects, with C-indexes of 0.811 and 0.934 for OS and DSS, respectively. Furthermore, analysis of immune infiltration levels showed that ASB6 expression were positively correlated with M2-type macrophage infiltration levels in CRC, and patients with high levels of both ASB6 and M2-type macrophages had a worse prognosis. Furthermore, pathway enrichment analysis of ASB6 interacting proteins identified by IP-MS suggested that ASB6 may play a crucial role through the response to unfolded protein pathway and protein processing in the endoplasmic reticulum pathway. Conclusions: ASB6 is significantly upregulated in CRC tissues and is a risk factor for prognosis in CRC patients. ASB6 enhances the migration ability of CRC cells. Therefore, ASB6 may be an independent prognostic biomarker and potential therapeutic target for CRC patients.