Univariate Cox Regression Analysis Research Articles

Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer.

Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.

59 Risk Factors of Immune Related Adverse Events in Patients with Metastatic Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors

Abstract Background Immune checkpoint inhibitor (ICI) based combinations have become the standard of care for first-line treatment in patients with metastatic renal cell carcinoma (mRCC). However, ICI can be responsible for immune-related adverse events (irAEs). Herein, we aimed to identify risk factors of immune related adverse events (irAEs) in patients treated with current first line (1L) combination of ICIs (ICI+ICI) or ICI with vascular endothelial growth factor (VEGF) targeted therapy (ICI+VEGF). Methods Data was collected retrospectively from patients treated for mRCC at Dana-Farber Cancer Institute, either receiving dual ICI or ICI+VEGF as 1L treatment regimen. Patients were categorized into two groups: those who developed grade ≥ 2 irAEs and those with grade 1 or no AEs. Time to toxicity (TT) was defined as the primary outcome. Univariate Cox regression analysis was initially conducted to identify potential predictive factors associated with irAEs. Subsequently, significant variables related to treatment adverse events were included in a multivariate Cox regression analysis with adjustments for multiple baseline factors. Results Among the 158 patients included, 122 (77.2%) were male, and 36 (22.8%) were female. Median age of patients at the treatment start date of therapy was 61 years (Q1-Q3: 62-69). A total of 57 (36.1%) patients developed grade ≥ 2 irAEs. The median follow-up of patients was 25.7 months. Univariate analysis showed that diabetes, male sex, and ccRCC may indeed influence the development of irAEs with a trend towards significance. However, thrombocytosis could be a protective factor against developing irAEs (p <0.05, Table). Upon multivariate analysis, only ccRCC remained significant as a risk factor for irAEs compared to other subtypes, with a HR of 2.93 (95% CI:1.05-8.18, p = 0.04) (Table). Table: Cox regression analysis for assessment of risk factors associated with irAEs Conclusions In this real-world study, we investigated potential clinical risk factors at baseline related to irAEs in patients with mRCC undergoing ICI-combination therapy. ccRCC histology was significantly associated with a higher risk of developing irAEs compared to other RCC subtypes. The retrospective design and the number of patients could be potential limitations of our findings.

Identifying and validating the roles of the cuproptosis-related gene DKC1 in cancer with a focus on esophageal carcinoma

BackgroundEsophageal cancer is a common malignancy of the digestive tract. Despite remarkable advancements in its treatment, the overall prognosis for patients remains poor. Cuproptosis is a form of programmed cell death that affects the malignant progression of tumors. This study aimed to examine the impact of the cuproptosis-associated gene DKC1 on the malignant progression of esophageal cancer.MethodsClinical and RNA sequencing data of patients with esophageal cancer were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify the differentially expressed genes related to cuproptosis that are associated with prognosis. We then validated the difference in the expression of DKC1 between tumor and normal tissues via three-dimensional multiomics difference analysis. Subsequently, we investigated the association between DKC1 expression and the tumor microenvironment by employing the TIMER2.0 algorithm, which was further validated in 96 single-cell datasets obtained from the TISCH database. Additionally, the functional role of DKC1 in pancarcinoma was assessed through GSEA. Furthermore, a comprehensive pancancer survival map was constructed, and the expression of DKC1 was verified in various molecular subtypes. By utilizing the CellMiner, GDSC, and CTRP databases, we successfully established a connection between DKC1 and drug sensitivity. Finally, the involvement of DKC1 in the progression of esophageal cancer was investigated through in vivo and in vitro experiments.ResultsIn this study, we identified a copper death-related gene, DKC1, in esophageal cancer. Furthermore, we observed varying levels of DKC1 expression across different tumor types. Additionally, we conducted an analysis to determine the correlation between DKC1 expression and clinical features, revealing its association with common cell cycle pathways and multiple metabolic pathways. Notably, high DKC1 expression was found to indicate poor prognosis in patients with various tumors and to influence drug sensitivity. Moreover, our investigation revealed significant associations between DKC1 expression and the expression of molecules involved in immune regulation and infiltration of lymphocyte subtypes. Ultimately, the increased expression of DKC1 in esophageal cancer tissues was verified using clinical tissue samples. Furthermore, DKC1-mediated promotion of esophageal cancer cell proliferation and migration was confirmed through both in vitro and in vivo experiments. Additionally, it is plausible that DKC1 may play a role in the regulation of cuproptosis.ConclusionIn this study, we conducted a systematic analysis of DKC1 and its regulatory factors and experimentally validated its excellent diagnostic and prognostic abilities in various cancers. Further research indicated that DKC1 may reshape the tumor microenvironment (TME), highlighting the potential of DKC1-based cancer treatment and its usefulness in predicting the response to chemotherapy.

Radiofrequency Ablation for the Treatment of Benign Thyroid Nodules: 10-Year Experience.

Background: Longer follow-up after radiofrequency ablation (RFA) of benign thyroid nodules is needed to understand regrowth and other causes of delayed surgery and long-term complications. Methods: This retrospective study included consecutive patients treated with RFA for symptomatic benign nonfunctioning thyroid nodules between March 2007 and December 2010. RFA was performed according to the standard protocol. We followed up patients at 1, 6, and 12 months, then yearly, until August 2022, and calculated the volume reduction ratio (VRR) at each follow-up. We assessed the incidence of regrowth according to three published criteria, delayed surgery, and complications. The Kaplan-Meier method was used to evaluate the cumulative incidence of regrowth, and univariable and multivariable Cox regression analyses were performed to identify risk factors for regrowth. Results: This study included 421 patients (mean age, 47 ± 13 years; 372 women) with 456 nodules (mean volume, 21 ± 23 mL). The median follow-up period was 90 months (interquartile range, 24-143 months). The mean VRR was 81% at 2 years, 90% at 5 years, and 94% at ≥10 years. Overall regrowth was noted in 12% (53/456) of nodules and was treated with repeat RFA (n = 33) or surgery (n = 4) or left under observation (n = 16). Thyroid nodules with ≥20 mL initial volume had significantly higher risk of regrowth compared with nodules with <10 mL initial volume (hazard ratio, 2.315 [95% confidence interval, 1.183-4.530]; p = 0.014 on multivariable Cox regression analysis). Delayed surgery was performed in 6% (26/421) of patients because of regrowth and/or persistent symptoms (n = 4) or newly detected thyroid tumors (n = 22), one benign and 21 malignant. The overall complication rate was 2.4% (10/421), with no procedure-related deaths or long-term complications. Conclusion: RFA is safe and effective for treating benign thyroid nodules, with a high VRR at long-term follow-up. Regular follow-up after initial success is warranted because of the possibility of regrowth of ablated nodules and the need for delayed surgery in some patients.

Unbalanced circulating Humanin levels and cardiovascular risk in chronic hemodialysis patients: a pilot, prospective study.

Mortality and cardiovascular (CV) risk prediction in individuals with end-stage kidney disease (ESKD) on chronic hemodialysis (HD) remains challenging due to the multitude of implicated factors. In a multicenter ESKD-HD cohort, we tested the prognostic yield of the assessment ofcirculating Humanin, a small mitochondrial-derived peptide involved in CV protection, on CV events and mortality. We conducted a prospective, observational, pilot study on 94 prevalent HD patients. The prognostic capacity of circulating Humanin levelswas tested on a primary composite (all-cause mortality + non-fatal CV events) and a secondary exploratory endpoint (all-cause mortality alone). Baseline Humanin levelwas comparable in patients reaching the primary or secondary endpoint as compared to others (p = 0.69 and 0.76, respectively). Unadjusted followed by multivariable Cox regression analyses adjusted for age, left ventricular mass index (LVMi), E/e', pulse pressure and diabetes mellitus indicated a non-linear relationship between Humanin levels and the composite outcome with the highest Hazard Ratio (HR) associated with very low (< 450.7pg/mL; HR ranging from 4.25 to 2.49) and very high (> 759.5pg/mL; HR ranging from 5.84 to 4.50) Humanin values. Restricted cubic splines fitting univariate and multivariate Cox regression analyses visually confirmed a curvilinear trend with an increasing risk observed for lower and higher Humanin values around the median, respectively. A similar, u-shaped association was also evidenced with the secondary endpoint. Altered Humanin levels may impart prognostic information in ESKD-HD patients at risk of death or CV events. Future investigations are needed to confirm whether Humanin measurement could improve CV and mortality risk prediction beyond traditional risk models.

Distinct Gene Expression and Immune Features Between Different Neutrophil Extracellular Trap-Related Osteosarcoma Subtypes.

We sought to determine neutrophil extracellular trap (NET)-related genes' potential value in improving the efficacy of diagnosis and identifying novel therapeutic targets for osteosarcoma. Data were obtained from TARGET, GEO, and CCLE database. Differentially expressed genes were identified between the subtypes based on NET-related genes. PPI network was constructed using STRING, following by ClueGO enrichment analysis. Infiltration of immune cells was calculated by ssGSEA. Risk Score model was built by LASSO Cox regression analysis. Western blot and qRT-PCR were applied to validate the expression of genes used in the model. We identified 19 NET-related genes with prognostic potential in osteosarcoma using univariate Cox regression analysis. Patients from TARGET were clustered into two subtypes with distinct prognosis and immune features. 381 DEGs were identified between the two NET subtypes. Risk Score based on BST1, SELPLG, FPR1 and TNFRSF10C was reliable to predict the prognosis of osteosarcoma patients. The four genes expressed significantly lower in osteosarcoma than normal cells. Low Risk Score individuals only existed in C1 subtype with better prognosis. Osteosarcoma were clustered into two subtypes based on NET-related genes. Risk Score model constructed by four NET-related gene was able to independently predict the prognosis of osteosarcoma.

Incremental prognostic value of cardiovascular magnetic resonance imaging in patients with severe LV dysfunction undergoing coronary artery bypass grafting.

Coronary artery disease (CAD) remains a significant global health issue, particularly when complicated by left ventricular ejection fraction (LVEF) < 35%. Although coronary artery bypass grafting (CABG) is recommended for such cases, the unclear prognosis necessitates further investigation. This retrospective study aimed to determine whether cardiovascular magnetic resonance (CMR) imaging provides additional prognostic value in guiding effective clinical management. The study included patients with CAD and LVEF < 35% who underwent CABG surgery after enhanced CMR between March 2016 and March 2023. CMR was performed using a 3.0T scanner with steady-state free precession and phase-sensitive inversion recovery sequences. Prognostic analysis of clinical and CMR data was conducted, with the endpoint defined as cardiovascular death, revascularization, hospitalization for heart failure, or stroke. Statistical analysis included Student's t-test, chi-squared test, univariate and multivariate Cox regression analysis, receiver operating characteristic analysis, Harrell C statistical analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) analysis. The study included 152 patients (mean age 58.6 ± 9.7 years; 138 men). During a mean follow-up of 2.0 years, 8 patients experienced cardiovascular death, while 1 case had revascularization, 13 had hospitalization for heart failure, and 11 had a stroke. Left atrial diameter index (LADi) (hazard ratio [HR], 1.08 [95% confidence interval (CI): 1.02-1.15]; P = 0.04) and late gadolinium enhancement (LGE) mass (HR, 1.03 [95% CI: 1.01-1.06]; P < 0.001) were associated with the endpoint, even after adjusting for multiple clinical variables. Adding LADi and LGE mass improved risk prediction for adverse events, as indicated by the C-index (0.738, p < 0.01), IDI (0.36), and NRI (0.13). Left atrial diameter index (LADi) and scar burden are valuable prognostic indicators in patients with LVEF < 35% undergoing CABG. They offer enhanced risk stratification beyond traditional clinical factors, highlighting their importance in guiding clinical management.

Risk factors and prediction nomogram of local regeneration after ultrasound-guided microwave ablation of uterine fibroids

To explore the risk factors associated with uterine fibroids (UFs) local regeneration of the treated UFs after microwave ablation (MWA) and to develop a nomogram model for predicting the risk of local regeneration. Retrospective study. The Eighth Affiliated Hospital of Sun Yat-sen University. Patients with UFs who underwent MWA at our hospital between October 2020 and April 2023 were included. MWA was used for the treatment of UFs. A total of 47 patients with 68 fibroids were included into this study. Over a median follow-up of 13 months (interquartile range: 8 to 22 months), local regeneration occurred in 11 UFs. The clinical and imaging characteristics of these patients were recorded and compared. Risk factors for local regeneration were determined through univariate and multivariate Cox regression analysis. Multivariate analysis revealed that the fertility desires, larger size of UFs (≥95.3cm3) and hyper-enhancement of UFs on contrast-enhanced ultrasound (CEUS) were independent risk factors for local regeneration after MWA. A predictive nomogram was constructed to predict the local regeneration after MWA of UFs. The concordance index (C-index = 0.924, internal validation C-index = 0.895) and the 1-year and 2-year area under the curve (AUC) values (0.962, 0.927) all indicated that the nomogram had good predictive performance. Calibration and decision curve analysis (DCA) curves further confirmed the model's accuracy and clinical utility. Fertility desires, larger size of UFs and hyper-enhancement on CEUS were independent predictors of UFs local regeneration after MWA in our study. The nomogram constructed based on the above independent risk factors may help predict which UFs will develop local regeneration after MWA.

The clinicopathological significance and prognostic value of PD-L1 in oral squamous cell carcinoma.

To investigate the relationship between the expression of PD-L1 in OSCC and the clinicopathological features and prognosis of patients. We retrospectively analyzed the clinicopathological data and prognosis of 381 OSCC patients. Immunohistochemical staining was performed on OSCC tumor specimens, and the expression level of PD-L1 was evaluated according to the combined positive score (CPS). Kaplan-Meier analysis was used to identify the effect of PD-L1 expression and clinicopathological features on the prognosis of patients. Univariate and multivariate Cox regression analyses were conducted to determine the hazard factors affecting the prognosis of patients. PD-L1 overexpression was significantly associated with cervical lymph node metastasis (p = 0.018), worse clinical stage (p = 0.022), worse tumor differentiation (p = 0.046), and worse depth of invasion (DOI) (p = 0.003). Poorer clinical stage and degree of tumor differentiation were significantly associated with poorer OS and DSS in patients. PD-L1 expression was not associated with prognosis in patients with OSCC. High PD-L1 expression was significantly associated with higher tumor malignancy in OSCC patients. Poorer clinical stage and degree of tumor differentiation were associated with poor prognosis in OSCC patients. Our results may help clinicians develop more appropriate individualized treatment strategies for their patients, thus improving their outcomes.

Hypoxia-related signature to risk stratify patients for the benefit of immune checkpoint inhibitors therapy in head and neck squamous cell carcinoma: An experimental study.

Increasing evidence has shown that hypoxia is a biomarker of tumor proliferation and metastasis. This research aimed to identify a hypoxia-associated gene prognostic index (HAGPI) in head and neck squamous cell carcinoma (HNSCC) and based on HAGPI-defined subgroups to predict prognosis and response to immune checkpoint inhibitors therapy. RNA-sequencing transcriptomic data for patients with HNSCC were downloaded from The Cancer Genome Atlas (TCGA). Protein-protein interaction network analysis was performed to select hypoxia-related hub genes. Univariate and multivariate cox regression analyses were used to identify hub genes to develop the HAGPI. Afterward expression data were imported into CIBERSORT to evaluate the relative proportion of 22 immune cells and compared the relative proportions of immune cells between the 2 HAGPI subgroups. The relationship between immunopheno score (IPS) and HAGPI was validated for immune checkpoint inhibitors (ICIs) response in TCGA cohorts. The HAGPI was constructed based on HS3ST1, HK1, PGK1, STC2, SERPINE1, PKLR genes. In high-HAGPI patients, the primary and secondary endpoint events in TCGA and GEO cohorts were significantly lower than low-HAGPI groups (P < .05). HAGPI-high patients exhibited a poorer prognosis than HAGPI-low patients did. The abundance of M2 macrophages and NK cell were significantly enhanced in the high-HAGPI while T cells regulatory and T cells CD8, were markedly elevated in the low-HAGPI. Meanwhile, patients in the low-HAGPI patients had higher levels of immunosuppressant expression and less aggressive phenotypes. Furthermore, IPS analysis showed that the low-HAGPI group with higher IPS represented a more immunogenic phenotype. The current study developed and verified a HAPGI model that can be considered as an independent prognostic biomarker and elucidated the tumor immune microenvironment of HNSCC.

Prediction Model for Therapeutic Responses in Ovarian Cancer Patients using Paclitaxel-resistant Immune-related lncRNAs.

Ovarian cancer (OC) is the deadliest malignant tumor in women with a poor prognosis due to drug resistance and lack of prediction tools for therapeutic responses to anti- cancer drugs. The objective of this study was to launch a prediction model for therapeutic responses in OC patients. The RNA-seq technique was used to identify differentially expressed paclitaxel (PTX)- resistant lncRNAs (DE-lncRNAs). The Cancer Genome Atlas (TCGA)-OV and ImmPort database were used to obtain immune-related lncRNAs (ir-lncRNAs). Univariate, multivariate, and LASSO Cox regression analyses were performed to construct the prediction model. Kaplan- meier plotter, Principal Component Analysis (PCA), nomogram, immune function analysis, and therapeutic response were applied with Genomics of Drug Sensitivity in Cancer (GDSC), CIBERSORT, and TCGA databases. The biological functions were evaluated in the CCLE database and OC cells. The RNA-seq defined 186 DE-lncRNAs between PTX-resistant A2780-PTX and PTXsensitive A2780 cells. Through the analysis of the TCGA-OV database, 225 ir-lncRNAs were identified. Analyzing 186 DE-lncRNAs and 225 ir-lncRNAs using univariate, multivariate, and LASSO Cox regression analyses, 9 PTX-resistant immune-related lncRNAs (DEir-lncRNAs) acted as biomarkers were discovered as potential biomarkers in the prediction model. Single-cell RNA sequencing (scRNA-seq) data of OC confirmed the relevance of DEir-lncRNAs in immune responsiveness. Patients with a low prediction score had a promising prognosis, whereas patients with a high prediction score were more prone to evade immunotherapy and chemotherapy and had poor prognosis. The novel prediction model with 9 DEir-lncRNAs is a valuable tool for predicting immunotherapeutic and chemotherapeutic responses and prognosis of patients with OC.

Serum inflammatory markers as prognostic marker for nasopharyngeal carcinoma with liver metastasis: a multi-center retrospective study.

This retrospective study investigated the prognostic value of serum inflammatory markers in nasopharyngeal carcinoma (NPC) patients, focusing on their association with overall survival (OS) and liver metastasis-free survival (LMFS). The study included 314 NPC patients treated between 2010 and 2020. Clinical characteristics, treatment methods, and serum inflammatory markers were assessed. Patients were categorized into two groups of with and without liver metastasis. Univariate and multivariate Cox regression and Kaplan-Meier survival analyses were performed to investigate the prognostic value of serum inflammatory markers in NPC patients with and without liver metastasis. In the whole cohort, univariate Cox regression analysis singled out tumor necrosis factor-α (TNF-α) (HR = 1.57, 95% CI 1.44-4.90, p = 0.004) and neutrophil-to-lymphocyte ratio (NLR) (HR = 2.13, 95% CI 1.33-3.99, p = 0.009), which were significantly associated with poorer OS. In patients with liver metastasis, TNF-α and NLR could not independently predict OS. However, high TNF-α levels were independently associated with worse OS in patients without liver metastasis (HR (95% CI) = 2.75 (1.67-8.68), p < 0.001). High NLR levels could independently predict poor OS in both groups with (HR (95% CI) = 1.94 (1.77-6.38), p = 0.010) and without liver metastasis (HR (95% CI) = 1.58 (1.19-7.54), p = 0.009). Ultimately, TNF-α and NLR could not significantly predict LMFS. This study highlights the prognostic significance of TNF-α and NLR in NPC patients, especially in those with liver metastasis. These inflammatory markers could serve as valuable indicators for assessing the prognosis of NPC patients. Further research is warranted to validate their clinical utility and explore potential therapeutic implications.

Integrated Single-cell and Bulk RNA Sequencing Analysis Cross Talk between Ferroptosis-related Genes and Prognosis in Oral Cavity Squamous Cell Carcinoma.

Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy. In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC). The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model's capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model's predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells. A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis. We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.

Association of GATA3 expression in triple-positive breast cancer with overall survival and immune cell infiltration

Breast cancer remains a leading cause of cancer-related mortality among women, with triple-positive breast cancer (TPBC) being a particularly aggressive subtype. GATA binding protein 3 (GATA3) plays a crucial role in the luminal differentiation of breast epithelium and T-cell differentiation. However, the relationship between GATA3 and immune infiltration in TPBC remains unclear. This study collected and analyzed TPBC data from The Cancer Genome Atlas (TCGA), METABRIC, and GSE123845 databases. Univariate and multivariate Cox regression analyses, along with Kaplan–Meier survival analyses, were employed to assess the prognostic value of GATA3 and other clinical features. Subsequently, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and regulatory mechanisms of GATA3 in TPBC. Additionally, ssGSEA analysis revealed the connection between GATA3 and immune infiltration. And the effects of neoadjuvant chemotherapy and immunotherapy on GATA3 expression were also explored. Finally, clinical samples were used to detect the relationship between GATA3 expression and tumor infiltrating lymphocyte (TIL) levels. Our results demonstrated that GATA3 was significantly overexpressed in TPBC tissues compared to normal tissues (P < 0.05). A positive correlation between GATA3 mRNA and protein levels was observed (R = 0.55, P < 0.05). Notably, high GATA3 expression was associated with poor overall survival (HR = 1.24, 95% confidence interval (CI) 1.25–11.76, P < 0.05). GSEA indicated significant enrichment of immune-related gene sets in low GATA3 expression groups. Furthermore, pathologic complete response (pCR) patients exhibited significantly lower GATA3 expression compared to residual disease (RD) patients. Mutation analysis revealed higher PIK3CA and TP53 mutation rates in high GATA3 expression groups. Finally, clinical validation data showed that the degree of TILs was significantly higher in the low GATA3 expression group. In conclusion, this study suggests that high GATA3 expression may be associated with poor prognosis and may reduce immune infiltration in TPBC.

Nomograms established for predicting microvascular invasion and early recurrence in patients with small hepatocellular carcinoma

BackgroundIn this study, we aimed to establish nomograms to predict the microvascular invasion (MVI) and early recurrence in patients with small hepatocellular carcinoma (SHCC), thereby guiding individualized treatment strategies for prognosis improvement.MethodsThis study retrospectively analyzed 326 SHCC patients who underwent radical resection at Wuhan Union Hospital between April 2017 and January 2022. They were randomly divided into a training set and a validation set at a 7:3 ratio. The preoperative nomogram for MVI was constructed based on univariate and multivariate logistic regression analysis, and the prognostic nomogram for early recurrence was constructed based on univariate and multivariate Cox regression analysis. We used the receiver operating characteristic (ROC) curves, area under the curves (AUCs), and calibration curves to estimate the predictive accuracy and discriminability of nomograms. Decision curve analysis (DCA) and Kaplan-Meier survival curves were employed to further confirm the clinical effectiveness of nomograms.ResultsThe AUCs of the preoperative nomogram for MVI on the training set and validation set were 0.749 (95%CI: 0.684–0.813) and 0.856 (95%CI: 0.805–0.906), respectively. For the prognostic nomogram, the AUCs of 1-year and 2-year RFS respectively reached 0.839 (95%CI: 0.775–0.903) and 0.856 (95%CI: 0.806–0.905) in the training set, and 0.808 (95%CI: 0.719–0.896) and 0.874 (95%CI: 0.804–0.943) in the validation set. Subsequent calibration curves, DCA analysis and Kaplan-Meier survival curves demonstrated the high accuracy and efficacy of the nomograms for clinical application.ConclusionsThe nomograms we constructed could effectively predict MVI and early recurrence in SHCC patients, providing a basis for clinical decision-making.

Stereotactic radiotherapy for managing ovarian cancer oligoprogression under poly (ADP-ribose) polymerase inhibitors (PARPi)

ObjectivePoly (ADP-ribose) polymerase inhibitors (PARPi) have become a new standard of care for the maintenance treatment of advanced epithelial ovarian cancer. This study aims to evaluate the efficacy and safety...

Comorbidities and Mortality Risk in COVID-19 Patients with Congestive Heart Failure: A Comprehensive Analysis

The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, resulting in alarming incidence and mortality rates among patients with comorbidities, including heart failure. Understanding the characteristics of heart failure and other comorbidities during the COVID-19 pandemic is crucial for effective prevention and treatment. However, the current understanding of these characteristics among different racial groups remains incomplete. In this study, we investigated a cohort of 4,711 patients, classifying them into congestive heart failure (CHF) and non-CHF groups. Biomarker analysis revealed noteworthy variations in blood urea nitrogen, aspartate aminotransferase, and white blood cell levels based on the presence or absence of CHF. Stratified by three racial groups, univariate logistic regression analysis identified significant differences in multiple variables, including CHF. Subsequent univariate Cox regression and Kaplan-Meier analysis demonstrated variations in mortality factors among distinct populations, with age and comorbidity playing prominent roles. This study utilized a large-scale database to investigate the characteristics of heart failure and related variables during the COVID-19 pandemic. The findings revealed distinctive mortality risk factors among various racial groups, emphasizing the significance of customized risk assessment and management approaches for diverse populations. These findings also provide a valuable resource for the development of targeted interventions and the promotion of equitable healthcare outcomes in the context of the COVID-19 pandemic.

Occult coronary microvascular dysfunction and ischaemic heart disease in patients with diabetes and heart failure

BackgroundPatients with diabetes (DM) and heart failure (HF) have worse outcomes than normoglycaemic HF patients. Cardiovascular magnetic resonance (CMR) can identify ischaemic heart disease (IHD) and quantify coronary microvascular dysfunction (CMD) using myocardial perfusion reserve (MPR). We aimed to quantify extent of silent IHD and CMD in patients with DM presenting with HF. MethodsProspectively recruited outpatients undergoing assessment into the aetiology of HF underwent inline quantitative perfusion CMR for calculation of stress and rest myocardial blood flow (MBF) and MPR. Exclusions included angina or history of IHD. Patients were followed up (median 3.0 years) for major adverse cardiovascular events (MACE). ResultsFinal analysis included 343 patients (176 normoglycaemic, 84 with pre-diabetes and 83 with DM). Prevalence of silent IHD was highest in DM (31%), then pre-diabetes (20%) then normoglycaemia (17%). Stress MBF was lowest in DM (1.53±0.52), then pre-diabetes (1.59±0.54) then normoglycaemia (1.83±0.62). MPR was lowest in DM (2.37±0.85) then pre-diabetes (2.41±0.88) then normoglycaemia (2.61±0.90). During follow up 45 patients experienced at least one MACE. On univariate Cox regression analysis MPR and presence of silent IHD were both associated with MACE. However, after correction for HbA1c, age and left ventricular ejection fraction the associations were no longer significant. ConclusionsPatients with DM and HF had higher prevalence of silent IHD, more evidence of CMD and worse cardiovascular outcomes than their non-diabetic counterparts. These findings highlight the potential value of CMR for assessment of silent IHD and CMD in patients with DM presenting with HF.

Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment

BackgroundHepatocellular carcinoma (HCC) is the most common type of primary liver cancer and second leading cause of cancer-related deaths worldwide. The heightened mortality associated with HCC is largely attributed to its propensity for metastasis, which cannot be achieved without remodeling or loss of the basement membrane (BM). Despite advancements in targeted therapies and immunotherapies, resistance and limited efficacy in late-stage HCC underscore the urgent need for better therapeutic options and early diagnostic biomarkers. Our study aimed to address these gaps by investigating and evaluating potential biomarkers to improve survival outcomes and treatment efficacy in patients with HCC.MethodIn this study, we collected the transcriptome sequencing, clinical, and mutation data of 424 patients with HCC from The Cancer Genome Atlas (TCGA) and 240 from the International Cancer Genome Consortium (ICGC) databases. We then constructed and validated a prognostic model based on metastasis and basement membrane-related genes (MBRGs) using univariate and multivariate Cox regression analyses. Five immune-related algorithms (CIBERSORT, QUANTISEQ, MCP counter, ssGSEA, and TIMER) were then utilized to examine the immune landscape and activity across high- and low-risk groups. We also analyzed Tumor Mutation Burden (TMB) values, Tumor Immune Dysfunction and Exclusion (TIDE) scores, mutation frequency, and immune checkpoint gene expression to evaluate immune treatment sensitivity. We analyzed integrin subunit alpha 3 (ITGA3) expression in HCC by performing single-cell RNA sequencing (scRNA-seq) analysis using the TISCH 2.0 database. Lastly, wound healing and transwell assays were conducted to elucidate the role of ITGA3 in tumor metastasis.ResultsPatients with HCC were categorized into high- and low-risk groups based on the median values, with higher risk scores indicating worse overall survival. Five immune-related algorithms revealed that the abundance of immune cells, particularly T cells, was greater in the high-risk group than in the low-risk group. The high-risk group also exhibited a higher TMB value, mutation frequency, and immune checkpoint gene expression and a lower tumor TIDE score, suggesting the potential for better immunotherapy outcomes. Additionally, scRNA-seq analysis revealed higher ITGA3 expression in tumor cells compared with normal hepatocytes. Wound healing scratch and transwell cell migration assays revealed that overexpression of the MBRG ITGA3 enhanced migration of HCC HepG2 cells.ConclusionThis study established a direct molecular correlation between metastasis and BM, encompassing clinical features, tumor microenvironment, and immune response, thereby offering valuable insights for predicting clinical outcomes and immunotherapy responses in HCC.

Predictive value of inflammation and nutritional index in immunotherapy for stage IV non-small cell lung cancer and model construction

Identifying individuals poised to gain from immune checkpoint inhibitor (ICI) therapies is a pivotal element in the realm of tailored healthcare. The expression level of Programmed Death Ligand 1 (PD-L1) has been linked to the response to ICI therapy, but its assessment typically requires substantial tumor tissue, which can be challenging to obtain. In contrast, blood samples are more feasible for clinical application. A number of promising peripheral biomarkers have been proposed to overcome this hurdle. This research aims to evaluate the prognostic utility of the albumin-to-lactate dehydrogenase ratio (LAR), the Pan-immune-inflammation Value (PIV), and the Prognostic Nutritional Index (PNI) in predicting the response to ICI therapy in individuals with advanced non-small cell lung cancer (NSCLC). Furthermore, the study seeks to construct a predictive nomogram that includes these markers to facilitate the selection of patients with a higher likelihood of benefiting from ICI therapy. A research initiative scrutinized the treatment records of 157 advanced NSCLC patients who received ICI therapy across two Jiangxi medical centers. The cohort from Jiangxi Provincial People’s Hospital (comprising 108 patients) was utilized for the training dataset, while the contingent from Jiangxi Cancer Hospital (49 patients) served for validation purposes. Stratification was based on established LAR, PIV, and PNI benchmarks to explore associations with DCR and ORR metrics. Factorial influences on ICI treatment success were discerned through univariate and multivariate Cox regression analysis. Subsequently, a Nomogram was devised to forecast outcomes, its precision gauged by ROC and calibration curves, DCA analysis, and cross-institutional validation. In the training group, the optimal threshold values for LAR, PIV, and PNI were identified as 5.205, 297.49, and 44.6, respectively. Based on these thresholds, LAR, PIV, and PNI were categorized into high (≥ Cut-off) and low (< Cut-off) groups. Patients with low LAR (L-LAR), low PIV (L-PIV), and high PNI (H-PNI) exhibited a higher disease control rate (DCR) (P < 0.05) and longer median progression-free survival (PFS) (P < 0.05). Cox multivariate analysis indicated that PS, malignant pleural effusion, liver metastasis, high PIV (H-PIV), and low PNI (L-PNI) were risk factors adversely affecting the efficacy of immunotherapy (P < 0.05). The Nomogram model predicted a concordance index (C-index) of 0.78 (95% CI: 0.73–0.84). The areas under the ROC curve (AUC) for the training group at 6, 9, and 12 months were 0.900, 0.869, and 0.866, respectively, while the AUCs for the external validation group at the same time points were 0.800, 0.886, and 0.801, respectively. Throughout immunotherapy, PIV and PNI could act as prospective indicators for forecasting treatment success in NSCLC patients, while the devised Nomogram model exhibits strong predictive performance for patient prognoses.