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Triple-negative breast cancer (TNBC) is a type of breast cancer with poor prognosis, which is prone to distant metastasis and therapy resistance. The presence of neutrophil extracellular traps (NETs) contributes to the progression of breast cancer and is an efficient predictor of TNBC. We obtained the bulk and single-cell RNA sequencing data from public databases. Firstly, we identified five NET-related genes and constructed NET-related subgroups. Then, we constructed a risk index with three pivotal genes based on the differentially expressed genes between subgroups. Patients in the high-risk group had worse prognosis, clinicopathological features, and therapy response than low-risk group. Functional enrichment analysis revealed that the low-risk group was enriched in Wnt signaling pathway, and surprisingly, the drug sensitivity prediction showed that Wnt signaling pathway inhibitors had higher drug sensitivity in the low-risk group. Finally, verification experiments in vitro based on MDA-MB-231 and BT-549 cells showed that tumor cells with low-risk scores had less migration, invasion, and proliferative abilities and high drug sensitivity to Wnt signaling pathway inhibitors. In this study, multi-omics analysis revealed that genes associated with NETs may influence the occurrence, progression, and treatment of TNBC. Moreover, the bioinformatics analysis and cell experiments demonstrated that the risk index could predict the population of TNBC likely to benefit from treatment with Wnt signaling pathway inhibitors.

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

To explore the relationship between morphological and hemodynamic parameters, baseline characteristics, and long-term outcomes in patients with moyamoya disease (MMD) using a computational fluid dynamics model. We retrospectively reviewed 129 patients at Beijing Tiantan hospital between July 2020 and December 2021. Perioperative clinical variables and Suzuki stage were recorded. Logistic regression analysis was employed to identify the risk factors for unfavorable long-term outcomes. The association between morphological, CT perfusion parameters, hemodynamic parameters and the Suzuki stage, clinical variables of MMD was also analyzed. Patients with high relative Wall Shear Stress (rWSS) were older and had more cases with higher Suzuki stage and worse follow-up mRS scores (p < 0.05). High rWSS at the terminal ICA and diabetes mellitus were identified as independent predictors of unfavorable long-term outcomes [OR = 3.039(1.191–7.754), p = 0.020; OR = 3.164(1.141–8.723), p = 0.027, respectively]. ROC analysis demonstrated that predictive models incorporating rWSS improved AUC values, with the highest AUC in Model 2 (AUC = 0.889). High rWSS was significantly associated with future TIA and stroke events (p = 0.032). We speculated that high rWSS and diabetes mellitus were independent risk factors for unfavorable long-term outcomes in patients with MMD. rWSS and morphological parameters are crucial for predicting MMD progression and understanding its pathogenesis. [ABSTRACT FROM AUTHOR]

Pancreatic cancer exhibits a high degree of malignancy with a poor prognosis, lacking effective prognostic targets. Utilizing histopathological methodologies, this study endeavors to predict the expression of pathological features in pancreatic ductal adenocarcinoma (PAAD) and investigate their underlying molecular mechanisms. Pathological images, transcriptomic, and clinical data from TCGA-PAAD were collected for survival analysis. Image segmentation using unsupervised machine learning was employed to extract features, perform clustering, and establish models. The prognostic value of pathological features and associated clinical risk factors were evaluated; the correlation between pathological features and molecular mechanisms, gene mutations, and immune infiltration was analyzed. By clustering 45 effective pathological features, we divided PAAD patients into two groups: cluster 1 and cluster 2. Significant associations with poor prognosis were found for cluster 2 in both the training group (n = 113) and validation group (n = 75) (p = 0.006), with pathological stages II-IV identified as potential synergistic risk factors (HR = 2.421, 95% CI = 1.263–4.639, p = 0.008). Subsequently, through multi-omics correlation analysis, we further revealed a close association between cluster 2 and the oxidative phosphorylation mechanism. Within the cluster 2 group, 28 oxidative phosphorylation genes exhibited reduced expression, CDKN2A gene mutations were upregulated, and there was significant downregulation of Tregs infiltration and related immune gene expression. The pathomic model constructed using machine learning serves as a valuable prognostic target for PAAD. The histopathological features cluster 2 are closely associated with the downregulation of oxidative phosphorylation levels and Tregs immune infiltration. [ABSTRACT FROM AUTHOR]

RNA-dependent protein kinase (PKR) may have a positive regulatory role in controlling tumor growth and progression in hepatocellular carcinoma (HCC). However, the downstream substrates and the molecular mechanism of PKR in the growth and progression of HCC have not been clarified. In this study, mass spectrometry analysis was performed with immunoprecipitated samples, and 4.1R was identified as a protein that binds to PKR. In transfected COS7 cells, an immunoprecipitation experiment showed that 4.1R binds to wild-type PKR, but not to a kinase-deficient mutant PKR, suggesting that PKR binds to 4.1R in a kinase activity-dependent manner. In HCC cell lines, HuH7 and HepG2, the expression level of 4.1R protein was shown to be regulated by protein expression and activation of PKR. Interestingly, high expression of 4.1R, as well as PKR, is associated with a worse prognosis in HCC. PKR increased HCC cell growth in both anchorage-dependent and anchorage-independent manners, whereas 4.1R was involved in HCC cell growth only in an anchorage-independent manner, not in an anchorage-dependent manner. The rescue experiment indicated that increased anchorage-independent growth of HCC cells by PKR might be caused by 4.1R. In conclusion, PKR associates with 4.1R and promotes anchorage-independent growth of HCC. The PKR-4.1R axis might be a new therapeutic target in HCC. [ABSTRACT FROM AUTHOR]

Chronic kidney disease-mineral and bone disorder (CKD-MBD) are recognized as a systemic disease affecting the prognosis of patients with CKD. Proper management of CKD-MBD is important to improve the prognosis of patients with CKD. Although proteinuria is recognized as a poor prognostic factor in these patients, few reports have examined its association with CKD-MBD. We examined the association between proteinuria and CKD-MBD using data from the Japan Chronic Kidney Disease Database Extension (J-CKD-DB-Ex). Among the patients registered in the J-CKD-DB-Ex, 30,977 with CKD stages G2–G5 who had serum creatinine, albumin, calcium, and phosphate concentrations measured at least once and urinalysis performed were included. The patients were divided into four groups (negative, 1+, 2+, and 3+) according to the degree of proteinuria. The association between proteinuria and CKD-MBD was examined by a logistic regression analysis. In a model adjusted for age, sex, diabetes, and the estimated glomerular filtration rate (eGFR), the odds ratio of the 3 + group compared with the negative group significantly increased to 2.67 (95% confidence interval, 2.29–3.13) for hyperphosphatemia, 2.68 (1.94–3.71) for hypocalcemia, and 1.56 (1.24–1.98) for hypomagnesemia. Proteinuria is associated with hyperphosphatemia, hypocalcemia, and hypomagnesemia in patients with CKD independently of eGFR. [ABSTRACT FROM AUTHOR]

5-Methylcytosine (m5C) is closely associated with cancer. However, the role of m5C in breast cancer(BC)remains unclear. This study combined single-cell RNA sequencing (scRNA-Seq) and transcriptomics datasets to screen m5C regulators associated with BC progression and analyze their clinical values. Firstly, This study elucidates the mechanisms of the m5C landscape and the specific roles of m5C regulators in BC patients. we found that the dysregulation of m5C regulators with m5Cscore play the essential role of the carcinogenesis and progression in epithelial cells and myeloid cells of BC at single cell level. External validation was conducted using an independent scRNA-Seq datasets. Then, three distinct m5C modification patterns were identified by transcriptomics datasets. Based on the m5C differentially expressed regulators, the m5Cscore was constructed, and used to divide patients with BC into high and low m5Cscore groups. Patients with a high m5Cscore had more abundant immune cell infiltration, stronger antitumor immunity, and better prognoses. Finally, Quantitative real-time (PCR) and immunohistochemistry were used for the in vitro experimental validation, which had extensive prognostic value. In this study, we aimed to assess the expression of m5C regulators involved in BC and investigate their correlation with the tumor microenvironment, clinicopathological characteristics, and prognosis of BC. The m5C regulators could be used to effectively assess the cell specific regulation prognosis of patients with BC and develop more effective immunotherapy strategies. [ABSTRACT FROM AUTHOR]

The incidence of Early-Onset Colorectal Cancer (EOCRC) is increasing. However, the prognosis of EOCRC compared to Late-Onset Colorectal Cancer (LOCRC), and the ideal age for initial colorectal cancer (CRC) screening are not clear. In this study, we identified the pathological differences between the groups and determined the optimal screening age for CRC patients. We included 10,172 patients diagnosed with CRC from January 2011 to December 2021 in this study. Survival differences were compared by plotting Kaplan–Meier survival curves and conducting landmark analysis. Additionally, the diagnostic age of CRC patients was analyzed using age cumulative curves. Compared to LOCRC patients, EOCRC patients had a higher proportion of deficient mismatch repair (dMMR) and more advanced TNM staging (P < 0.05). The five-year survival of EOCRC patients was significantly better than that of LOCRC patients (P < 0.05). Laparoscopic surgery improved the long-term survival of EOCRC patients. Proficient mismatch repair (pMMR) favored the long-term survival of EOCRC patients. The survival rate of EOCRC patients at TNM stages I and II was higher than that of LOCRC patients at the same stages (P < 0.05). The age cumulative curve showed a substantial increase in the number of CRC patients at 40 years. The long-term prognosis of EOCRC patients is better than that of LOCRC patients, especially among those with pMMR, stages I–II, and who undergo laparoscopic surgery. For people with a high risk of cancer, such as a family history of cancer and poor lifestyle habits, the starting age for CRC screening should be 40 years. [ABSTRACT FROM AUTHOR]

Patients with advanced and recurrent cervical cancer often lack satisfactory treatment outcomes. Thus, it is necessary to seek reliable biomarkers that provide the ability to identify the disease at an early stage and predict the patient prognosis, providing new strategies for the treatment of cervical cancer. The sequencing data of ITGA3 were retrieved from public datasets. Immune infiltration and sensitivity of potential immunotherapy and chemotherapy have been analyzed between two subgroups. Functional analysis was applied to excavate the related pathways of ITGA3 in cervical cancer. Furthermore, the impact of ITGA3 in tumor progression has been verified in vitro. The results revealed that the level of ITGA3 was upregulated in cervical cancer, and was positively correlated with worse prognosis. The tumor microenvironment of patients in the high-risk group was immunosuppressed. Patients in high-risk group may not benefit from immunotherapy, but be may be sensitive to several chemotherapy drugs. Notably, the angiogenesis, epithelial mesenchymal transition, and PI3K pathway were increased in high-risk group. Collectively, ITGA3 is a marker of poor prognosis and promotes tumor progression by regulating PI3K/AKT pathway in cervical cancer. Our results provide new insights for potential molecular targeted therapy and prognostic prediction of cervical cancer. [ABSTRACT FROM AUTHOR]

We propose a fully automatic multi-task Bayesian model, named Bayesian Sequential Network (BSN), for predicting high-grade (Gleason ≥ 8) prostate cancer (PCa) prognosis using pre-prostatectomy FDG-PET/CT images and clinical data. BSN performs one classification task and five survival tasks: predicting lymph node invasion (LNI), biochemical recurrence-free survival (BCR-FS), metastasis-free survival, definitive androgen deprivation therapy-free survival, castration-resistant PCa-free survival, and PCa-specific survival (PCSS). Experiments are conducted using a dataset of 295 patients. BSN outperforms widely used nomograms on all tasks except PCSS, leveraging multi-task learning and imaging data. BSN also provides automated prostate segmentation, uncertainty quantification, personalized feature-based explanations, and introduces dynamic predictions, a novel approach that relies on short-term outcomes to refine long-term prognosis. Overall, BSN shows great promise in its ability to exploit imaging and clinicopathological data to predict poor outcome patients that need treatment intensification with loco-regional or systemic adjuvant therapy for high-risk PCa. [ABSTRACT FROM AUTHOR]

A pan-cancer analysis summarizing the overall changes in mRNA and protein stability of ADM9, as well as its oncogenic function on immune cell line modulation and checkpoints within the tumor microenvironment (TME), is lacking, despite the fact that ADM9 up-regulation is correlated with the progression of many cancers. Therefore, in this study, we comprehensively analyzed the role of ADAM9 expression and its prognostic value in different cancers to fill this gap. Multiple bioinformatics databases such as Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to evaluate the ADAM9 genetic alternation, phosphorylation, and methylation, and indicated highly positive correlated genes that might play a critical interaction with ADAM9 and their molecular function with GO analysis. We also evaluate the effect of higher ADAM9 with prominent immune modulatory genes and immune infiltration especially in liver cancer pathogenesis stimulates lower NK cell effector functions based on its role in MICA shedding and increasing the Tregs infiltration. Immunohistochemistry (IHC) staining from 90 pathologically verified samples proved the positive correlation between ADAM9 and tumor stages and proved the higher expression of ADAM9 correlated genes (SNX9, APP, TNF, CDH1, ITGAV, MAD2L2) in HCC pathogenesis. In conclusion, this pan-cancer study provides a comprehensive understanding of the prognostic value of ADAM9 in various tumors emphasizing its importance to be considered as an innovative treatment approach, especially in tumor immunity shortly. [ABSTRACT FROM AUTHOR]

Disulfidptosis is a novel programmed cell death mode that has been reported to play a role in oncogenesis. Increasing evidences suggest that the long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of bladder cancer (BLCA). However, the role and prognostic value of disulfidptosis-related lncRNAs in BLCA remain unknown.The aim of this study was to construct and validate a disulfidptosis-related lncRNA risk model for predicting the prognosis of BLCA patients. A risk model consisting of 5 disulfidptosis-related lncRNAs was developed to predict the prognosis of BLCA patients. The overall survival (OS) of BLCA patients in the high-risk group was significantly shorter than that in the low-risk group (P < 0.05). The effectiveness of this model was validated using the receiver operating characteristic (ROC) curve analysis, and this model proved superior in prognostic accuracy compared with other clinical features. Furthermore, the tumor immune dysfunction and exclusion (TIDE) score in the high-risk group was significantly higher than that in the low-risk group, suggesting that the high-risk group had a less favorable response to immunotherapy. Simultaneously, patients in the low-risk group exhibited significantly higher sensitivity to CTLA-4 monoclonal antibody therapy compared to those in the high-risk group, suggesting potential benefits of immunotherapy for patients in the low-risk group. The combination of high risk and low tumor mutational burden (TMB) could further shortened the OS of BLCA patients. Lastly, the drug sensitivity analysis revealed that the BLCA cells in the high-risk group showed an increased sensitivity to cisplatin, sunitinib, cetuximab, axitinib, docetaxel, saracatinib, vinblastine and pazopanib compared with those in the low-risk group. According to the Quantitative real time PCR results, we found that five lncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line. The disulfidptosis-related lncRNA risk model has a valuable effect in assessing the prognosis of BLCA patients. [ABSTRACT FROM AUTHOR]

D-dimer is a biomarker of coagulation and fibrinolytic system activation in response to the hypercoagulable state of the body. The research aimed to analyze the value of D-dimer in the prognosis of patients with dilated cardiomyopathy (DCM). Patients admitted to our center for the first time with DCM were enrolled consecutively. The clinical characteristics variables were obtained from the electronic medical record system, and the prognostic information was obtained using telephone return visits and a review of repeated hospitalization records. Univariate and multivariate Cox regression was used to explore the association of D-dimer with all-cause mortality. Smooth curve fitting, threshold saturation effect analysis, and subgroup analysis were performed. Ultimately, 534 patients were included. After a follow-up of the enrolled patients, 485 patients obtained prognostic information, of which 159 died from all causes, and the main cause of death was heart failure (89/159), the sudden death accounted for about 17%. The independent positive association between D-dimer and all-cause mortality remained unchanged in both unadjusted and adjusted Cox regression models. In the fully adjusted model, each standard deviation increase in D-dimer was associated with a 14% increase in all-cause mortality (HR = 1.14; 95% CI: 1.02 ~ 1.27; P < 0.05). Curve fitting and threshold effect analysis showed an inflection point in the relationship between D-dimer and all-cause mortality (non-linear test: P = 0.03). When D-dimer was equal to 362ng/ml, HR = 1; and as the value increased, the risk of all-cause mortality increased by 34.7% for every 2-fold increase in D-dimer gradually (HR = 1.347; 95% CI: 1.069 ~ 1.697; P = 0.012). In subgroup analysis, D-dimer and BMI had a significant interaction on all-cause mortality, with a significantly increased risk of all-cause mortality in subjects with BMI ≥ 25 kg/m2 (HR = 1.99; 95% CI: 1.34 ~ 2.97; P < 0.01). The ROC curve showed that D-dimer was a good predictor of all-cause mortality, and the areas under the curve at 1-, 3-, and 5-year were 0.71, 0.64, and 0.59, respectively. In addition, D-dimer improved the predictive performance of the MAGGIC heart failure score in patients with DCM. D-dimer is not only independently associated with all-cause mortality in DCM patients, but also has good predictive value, suggesting that D-dimer may be an early and useful marker for improving the management of DCM patients. [ABSTRACT FROM AUTHOR]

The prognostic value of prostate-specific antigen (PSA) kinetics in primary high-volume metastatic hormone-sensitive prostate cancer (mHSPC) patients treated with novel hormonal therapy agents is still unclear. Here, we retrospectively reviewed the data of 102 patients with primary high-volume mHSPC who received novel hormonal therapy agents. The median follow-up was 32.25 ± 14.51 months and the median nadir PSA (nPSA) was 0.20 (0.06, 11.71) ng/mL after treatment. The mean time to nPSA was 10.82 ± 7.27 months and 55 patients (53.9%) had a PSA-density (PSA-D) ≤ 0.08 at 3-months. Univariate and multivariate Cox regression analyses showed that the absence of visceral metastases, nPSA ≤ 0.2 and PSA-D ≤ 0.08 were independent prognostic factors for better PFS and OS (all P < 0.05). Moreover, patients with nPSA ≤ 0.2 and PSA-D ≤ 0.08 had the best PFS and OS, and the combination of the nPSA and PSA-D had a better predictive accuracy for PFS and OS than nPSA and PSA-D alone. Thus, Visceral metastases, nPSA and PSA-D were independent prognostic factors for primary high-volume mHSPC patients treated with novel hormonal therapy agents. Patients with lower nPSA and PSA-D had a best survival outcome, and the combination of nPSA and PSA-D had a better effect on prognosis predicting. [ABSTRACT FROM AUTHOR]

Recurrent high-grade intracranial malignancies have a grim prognosis and uniform management guidelines are lacking. Re-irradiation is underused due to concerns about irreversible side effects. Pulsed-reduced dose rate radiotherapy (PRDR) aims to reduce toxicity while improving tumor control by exploiting dose-rate effects. We share our initial experience with temporally modulated pulsed proton re-irradiation (TMPPR), focusing on workflow, safety, feasibility, and outcomes for the first patient cohort. TMPPR was administered to patients with recurrent or progressive central nervous system malignancies using intensity modulated proton therapy with three fields. Patient and treatment data were collected, responses categorized using RANO assessment, and toxicities graded using CTCAE v5.0. Five patients received TMPPR between October 2022 and May 2023, with a median age of 54 years (Range: 32–72), and a median time from initial radiotherapy to re-RT of 23 months (Range 14–40). Treatment was completed without delay, with a median dose of 60 GyRBE in 30 fractions. Initial treatment response assessment showed complete (n = 1) or partial (n = 3) responses. Limited toxicity was observed, primarily grade 2 alopecia and one case of radiation necrosis graded at 2. This early experience demonstrates the feasibility of TMPPR delivery, highlighting the importance of prospective evaluations in the re-irradiation setting. [ABSTRACT FROM AUTHOR]

Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to obtain. We evaluated the potential of an artificial intelligence (AI)-generated electrocardiography score for LVGLS estimation (ECG-GLS score) to diagnose LV systolic dysfunction and predict prognosis of patients with heart failure (HF). A convolutional neural network-based deep-learning algorithm was trained to estimate the echocardiography-derived GLS (LVGLS). ECG-GLS score performance was evaluated using data from an acute HF registry at another tertiary hospital (n = 1186). In the validation cohort, the ECG-GLS score could identify patients with impaired LVGLS (≤ 12%) (area under the receiver-operating characteristic curve [AUROC], 0.82; sensitivity, 85%; specificity, 59%). The performance of ECG-GLS in identifying patients with an LV ejection fraction (LVEF) < 40% (AUROC, 0.85) was comparable to that of LVGLS (AUROC, 0.83) (p = 0.08). Five-year outcomes (all-cause death; composite of all-cause death and hospitalization for HF) occurred significantly more frequently in patients with low ECG-GLS scores. Low ECG-GLS score was a significant risk factor for these outcomes after adjustment for other clinical risk factors and LVEF. The ECG-GLS score demonstrated a meaningful correlation with the LVGLS and is effective in risk stratification for long-term prognosis after acute HF, possibly acting as a practical alternative to the LVGLS. [ABSTRACT FROM AUTHOR]

Non-small cell lung adenocarcinoma (LUAD) is the predominant form of lung cancer originating from lung epithelial cells, making it the most prevalent pathological type. Currently, reliable indicators for predicting treatment efficacy and disease prognosis are lacking. Despite extensive validation of autophagy-dependent cell death (ADCD) in solid tumor studies and its correlation with immunotherapy effectiveness and cancer prognosis, systematic research on ADCD-related genes in LUAD is limited. We utilized AddModuleScore, ssGSEA, and WGCNA to identify genes associated with ADCD across single-cell and bulk transcriptome datasets. The TCGA dataset, comprising 598 cases, was randomly divided into training and validation sets to develop an ADCD-related LUAD prediction model. Internal validation was performed using the TCGA validation set. For external validation, datasets GSE13213 (119 LUAD samples), GSE26939 (115 LUAD samples), GSE29016 (39 LUAD samples), and GSE30219 (86 LUAD samples) were employed. We evaluated the model's accuracy and effectiveness in predicting prognostic risk. Additionally, CIBERSORT, ESTIMATE, and ssGSEA techniques were used to explore immunological characteristics, drug response, and gene expression in LUAD. Real-time RT-PCR was conducted to assess variations in mRNA expression levels of the gene XCR1 between cancerous and normal tissues in 10 lung cancer patients. We identified 249 genes associated with autophagy-dependent cell death (ADCD) at both single-cell and bulk transcriptome levels. Univariate COX regression analysis revealed that 18 genes were significantly associated with overall survival (OS). Using LASSO-Cox analysis, we developed an ADCD signature based on five genes (BIRC3, TAP1, SLAMF1, XCR1, and HLA-DMB) and created the ADCD-related risk scoring system (ADCDRS). Validation of this model demonstrated its ability to predict disease prognosis and its correlation with clinical characteristics, immune cell infiltration, and the tumor microenvironment. To enhance clinical applicability, we integrated an ADCDRS nomogram. Furthermore, we identified potential drugs targeting specific risk subgroups. We successfully identified a model based on five ADCD genes to predict disease prognosis and treatment efficacy in LUAD, as well as to assess the tumor immune microenvironment. An efficient and practical ADCDRS nomogram was designed. [ABSTRACT FROM AUTHOR]

Pheochromocytoma and paraganglioma (PPGL) represent a group of rare neuroendocrine tumors known for their potential to metastasize. This study provides a comprehensive retrospective evaluation of 15 patients diagnosed with metastatic or recurrent PPGL at our institution over a two-decade span (2000–2020). Our primary objectives were to delineate the long-term clinical outcomes and pinpoint key prognostic determinants. Median duration from initial PPGL diagnosis to the onset of metastasis or recurrence stood at 5.8 years. Predominant sites for metastasis included the bone, lung, lymph nodes, and peritoneum. A salient finding was that surgical interventions targeting metastatic lesions significantly improved prognosis. Further analysis revealed that a Pheochromocytoma of the Adrenal Gland Scaled Score (PASS) exceeding 7 closely associated with unfavorable outcomes. These insights not only underscore the clinical variability of PPGL's progression but also highlight the pivotal role of surgical management for metastatic or recurrent cases. The value of the PASS score as an informative prognostic tool was evident, suggesting its utility in shaping future therapeutic approaches. Given the intricacies of PPGL, collaborative studies involving larger patient cohorts will be crucial to optimize management strategies and prognostication. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study investigates the role and mechanisms of ADAM9 as a biomarker and potential therapeutic target in HCC. Utilizing RNA-sequencing data and clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we conducted survival and meta-analyses, functional enrichment, and immune infiltration studies. Additionally, we evaluated the effects of ADAM9 silencing on HCC cell proliferation, migration, and invasion through in vitro experiments. Our results demonstrate that high ADAM9 expression is associated with poor prognosis and increased immune infiltration in HCC patients. Furthermore, ADAM9 knockdown significantly inhibited tumor cell proliferation and migration. These findings indicate that ADAM9 is a promising prognostic biomarker and potential therapeutic target in HCC. In conclusion, ADAM9 could offer avenues for developing strategies to inhibit tumor progression and improve patient outcomes. [ABSTRACT FROM AUTHOR]

This study develops a prognostic model to predict metastasis and prognosis in colorectal cancer liver metastases by identifying distinct macrophage subsets. Using scRNA-seq data from primary colorectal cancer and liver metastases, we dissected the cellular landscape to find unique macrophage subpopulations, particularly EEF1G + macrophages, which were prevalent in liver metastases. The study leveraged data from GSE231559, TCGA, and GEO databases to construct an 8-gene risk model named EMGS, based on the EEF1G + macrophage gene signature. Patients were divided into high-risk and low-risk groups using the median EMGS score, with the high-risk group showing significantly worse survival. This group also demonstrated upregulated pathways associated with tumor progression, such as epithelial-mesenchymal transition and angiogenesis, and downregulated metabolic pathways. Moreover, the high-risk group presented an immunosuppressive microenvironment, with a higher TIDE score indicating lower effectiveness of immunotherapy. The study identifies potential drugs targeting the high-risk group, suggesting therapeutic avenues to improve survival. Conclusively, the EMGS score identifies colorectal cancer patients at high risk of liver metastases, highlighting the role of specific macrophage subsets in tumor progression and providing a basis for personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Immunotherapy research focuses on reshaping the tumor microenvironment (TME) to enhance its antitumor immune responses, with an emphasis on understanding the impact of RNA methylation in triple-negative breast cancer (TNBC) TME regulation. This study explored the influence of various RNA methyltransferases on TME cells in TNBC and their correlation with prognosis and immunotherapy response. Using non-negative matrix factorization on single-cell RNA-sequencing data, distinct TME cell clusters were identified based on the expression of 30 RNA methyltransferases. Various analyses, including pseudotime, cell communication, transcription factor regulatory network, and gene enrichment, were conducted on these clusters. The roles of RNA methyltransferase-mediated TME clusters in prognosis and immunotherapy response were determined using TNBC bulk RNA-Seq data, and the findings were validated through immunofluorescence analysis of a tissue microarray comprising 87 samples. Spatial transcriptomic analysis further revealed the distribution of TME cell clusters. Different methyltransferase-mediated cell clusters exhibited unique metabolic, immune, transcriptional, and intercellular communication patterns. Survival analysis indicated prognostic significance in specific TME cell clusters, and immunofluorescence analysis confirmed the prognostic value of m6A_WTAP + CD8T + cells. In conclusion, our study illustrated the involvement of these cell subgroups in tumor growth and antitumor immunity modulation, providing insights into the enhancement of TNBC immunotherapy. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignancy within the digestive system, characterized by high incidence and mortality rates. The biological role of REEP5 in ESCC progression remains poorly understood, despite its associations with various diseases, potentially accelerating tumor malignancy. We retrieved RNA-seq data and clinical information from 179 ESCC patients from the Gene Expression Omnibus (GEO) and 93 patients from The Cancer Genome Atlas (TCGA) databases. Bioinformatics analyses were conducted to explore the biological functions of REEP5 in ESCC, its role in the tumor microenvironment, and its prognostic value. Additionally, utilizing single-cell RNA-seq (scRNA-seq) data from 3 ESCC patients in the GEO database, we performed cluster analyses to investigate cell-specific expression differences of REEP5 between cancerous and adjacent non-cancerous tissues. Molecular biology experiments were also conducted to validate REEP5 expression disparities between tumor and non-tumor tissues. Compared to normal tissues, REEP5 was significantly enriched in ESCC tissues. High REEP5 expression was closely associated with poor prognosis in ESCC patients. Gene Ontology (GO) analysis revealed strong correlations between REEP5 and processes such as mRNA splicing and protein stabilization. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) indicated positive correlations between REEP5 and mRNA spliceosome assembly and disassembly. Pearson correlation analysis demonstrated positive associations between REEP5 and cancer-inhibitory immune checkpoints CTLA-4, TIM-3, and HVEM. Single-cell clustering and CIBERSORT analysis showed that REEP5 expression was closely related to T-cell infiltration in ESCC, with significant enrichment effects observed in CD8+ T-cell infiltration. REEP5 expression is closely correlated with the pathological and molecular pathology of ESCC, potentially playing a crucial role in Mast cell or T-cell-mediated immune responses in ESCC. Therefore, REEP5 holds promise as a novel therapeutic target for ESCC. [ABSTRACT FROM AUTHOR]

This study aimed to explore the association between inflammation-based prognostic markers and outcomes in non-small cell lung cancer (NSCLC) patients undergoing therapy with immune checkpoint inhibitors (ICIs). We conducted a comprehensive search of the Embase, PubMed, and Cochrane databases for studies that reported on the impact of inflammation-based prognostic factors, such as C-reactive protein (CRP), on the prognosis of NSCLC patients treated with ICIs. The primary outcomes of interest were overall survival (OS) and progression-free survival (PFS). Statistical analyses were performed using Stata 14 software, with assessments of publication bias and heterogeneity conducted as necessary. Our meta-analysis included 27 studies encompassing 5,174 patients, evaluating factors such as CRP, the modified Glasgow Prognostic Score (mGPS), and the CRP-albumin ratio (CAR). The analysis revealed that elevated levels of CRP were significantly correlated with both reduced PFS (I2 = 0%, P = 0.72; HR = 1.50, 95%CI: 1.33–1.67, P < 0.01) and shorter OS (I2 = 0%, P = 0.55; HR = 1.90, 95%CI: 1.50–2.30, P < 0.01). Similarly, elevated levels of mGPS values were associated with worse PFS (I2 = 0%, P = 0.75; HR = 1.28, 95%CI: 1.10–1.46, P < 0.05) and OS (I2 = 0%, P = 0.94; HR = 1.56, 95%CI: 1.31–1.81, P < 0.05). However, the relationship between elevated levels of CAR and worse outcomes for PFS (I2 = 59.6%, P = 0.94; HR = 1.42, 95%CI: 0.74–2.11, P > 0.05) and OS (I2 = 45.3%, P = 0.16; HR = 1.41, 95%CI: 0.70–2.13, P > 0.05) was not statistically significant. Our findings suggest that CRP and mGPS may serve as potential prognostic markers in NSCLC patients receiving immunotherapy. Nonetheless, further research with more homogeneous study populations is necessary to valid these observations. [ABSTRACT FROM AUTHOR]

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC. [ABSTRACT FROM AUTHOR]

Through their involvement in cancer metabolism, alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), γ-glutamyltransferase (GGT) and lactate dehydrogenase (LDH) reflect the tumor burden and thus could have a prognostic potential for patients treated with immune checkpoint inhibitors (CPI). Therefore, this study investigated the prognostic potential of these parameters in a real-world cohort of patients with metastatic renal cell cancer (mRCC) under first-line CPI-based therapy. The retrospective study cohort included 82 mRCC patients treated with CPI-based first-line therapy between 2019 and 2023. Progression-free survival (PFS), overall survival (OS) and response rates were evaluated according to baseline levels and early dynamic changes of ALAT, ASAT, GGT and LDH. Multivariate Cox proportional hazard regression models were generated to identify independent prognosticators for PFS and OS. High baseline levels and non-normalized kinetics of ALAT, ASAT, GGT and LDH were significantly associated with shorter PFS and OS (p < 0.05), which was also reflected by lower response rates. Combining the four parameters at baseline into a 4-Risk-Score resulted in an enhanced prognostic power, as indicated by a higher C-index of 0.693 for OS compared to the individual parameters (≤ 0.663). Patients with all four risk factors present showed the worst PFS and OS. Overall, baseline levels and early kinetics of the four parameters as well as the 4-Risk-Score were identified as independent prognosticators for PFS and OS by multivariate analysis. As standard laboratory parameters, ALAT, ASAT, GGT and LDH are cost-effective and could be easily used either alone or in combination for therapy monitoring of CPI-treated mRCC patients. [ABSTRACT FROM AUTHOR]

This study investigates the prevalence and evaluates the prognostic implications of acute kidney injury (AKI) in COVID-19 patients, with a novel emphasis on the evaluation of serum uromodulin (sUmod) as a potential kidney-specific biomarker. A cohort of hospitalised COVID-19 patients (n = 378) was examined for AKI using standard criteria. In addition to traditional urinary biomarkers, sUmod levels were analysed. Univariable and multivariable regression models were employed to evaluate the association of sUmod and AKI and in-hospital mortality. Levels of sUmod were significantly lower in patients with CKD (91.8 ± 60.7 ng/ml) compared to patients with normal kidney function (204.7 ± 91.7 ng/ml; p < 0.001). 151 patients (40.0%) presented with AKI at the time of hospital admission or developed an AKI during hospitalization. 116 patients (76.8%) had an AKI already at the time of hospital admission. COVID-19 patients with AKI had significantly lower levels of sUmod compared to patients without AKI during hospitalisation (124.8 ± 79.5 ng/ml) vs 214.6 ± 92.3 ng/ml; p < 0.001). The in-hospital mortality rate in this cohort of COVID-19 patients was 15.3%. Patients with AKI had a higher probability for in-hospital death (OR 5.6, CI 1.76 to 17.881, p = 0.004). Patients who died during hospital stay, had significantly lower sUmod levels (129.14 ± 89.56 ng/ml) compared to patients surviving hospitalisation (187.71 ± 96,64 ng/ml; p < 0.001). AKI is frequently associated with COVID-19 in hospitalized patients. Serum uromodulin may emerge as a promising biomarker for AKI in COVID-19 patients. Further research is warranted to explore its clinical application and refine risk stratification in this patient population. [ABSTRACT FROM AUTHOR]

Studies have underscored the pivotal role of metastasis-associated protein 3 (MTA3) as a cancer regulator, yet its potential as a drug target across cancers necessitates comprehensive evaluation. In this study, we analyzed MTA3 expression profiles to ascertain its diagnostic and prognostic value in pan-cancers, probing associations with genetic variations and immunological characteristics. Notably, liver hepatocellular carcinoma (LIHC) exhibited the most significant correlation with MTA3. By transfection of siRNA, interference of MTA3 affected HepG2 and Hepa1-6 cell viability and migration. Through drug screening and drug-likeness evaluation among marine-derived natural products, Jaspamycin was identified as a potential hepatocellular carcinoma treatment by targeting MTA3. By applying in vitro and in vivo experiment, the inhibitory effects of Jaspamycin on hepatocellular carcinoma viability, migration, and tumor progression were observed. To assess the potential of MTA3 as an anticancer drug target, MTA3 overexpression plasmid was transfected together with Jaspamycin treatment, and observed that MTA3 upregulation counteracted the inhibitory effects of Jaspamycin on hepatocarcinoma cell proliferation and migration, underscoring the efficacy of MTA3 as a drug target in hepatocellular carcinoma drug screening. This study highlights the clinical significance of MTA3 in pan-cancer, particularly in hepatocellular carcinoma. Additionally, it identifies Jaspamycin, a marine-derived compound with promising pharmacological properties, as an effective inhibitor of MTA3 activity, suggesting its potential for hepatocellular carcinoma treatment. [ABSTRACT FROM AUTHOR]

Epithelial ovarian carcinoma (EOC) is the most fatal among female reproductive system tumors. The immune tumor microenvironment and ubiquitin-proteasome pathway are closely related to the proliferation, invasion, and response to chemotherapy in EOC. However, their specific roles in EOC have not been fully elucidated. Therefore, we aimed to recognize potential prognostic markers and novel therapeutic targets for EOC. We constructed the ubiquitin-related signature risk model comprising HSP90AB1, FBXO9, SIGMAR1, STAT1, SH3KBP1, EPB41L2, DNAJB6, VPS18, PPM1G, AKAP12, FRK, and PYGB, specifically for patients with EOC. The high-risk model presented a worse prognosis, primarily associated with the B-cell receptor signaling pathway, ECM receptor interaction, focal adhesion, and actin cytoskeleton regulations. Analysis of the immune landscape revealed a higher abundance of B cells, M2 macrophages, neutrophil CD4 T cells, cancer-associated fibroblasts, macrophage neutrophils, and fibroblasts in the high-risk group. It also exhibited lower tumor mutation burden, mRNAsi, and EREG-mRNAsi and reduced sensitivity to other chemotherapy drugs, except dasatinib. These findings serve as a valuable indicator for personalized treatment strategies and clinical stratification in managing patients with EOC. Additionally, our study will serve as a foundation for future mechanistic research to explore the association between the ubiquitin-proteasome pathway and EOC. [ABSTRACT FROM AUTHOR]

PI3K/AKT/mTOR pathway is implicated in breast cancer progression and recurrence. The identification of PIK3CA and AKT1 mutations and loss of PTEN serve as selection criterion for targeted therapies involving selective inhibitors. However, they do not consistently align with pathway activation, and high-cost determinations limit their routine application. PI3K-downstream epigenetic regulatory mechanisms broaden the alterations that amplify pathway activity and, consequently, sensitivity to selective inhibitors. In this retrospective observational study, conducted within a cohort of early-stage breast cancer patients, we determined phosphorylated ribosomal protein S6 (pS6) at Ser240/244 by immunohistochemistry as an indicator of PI3K pathway activation. Log-Rank test and Cox proportional hazards regression were used to analyze the clinical relevance of pS6, alone and together with clinicopathological variables, regarding recurrence-free survival. ROC curves and the area under the curves were used to evaluate the calibration and discrimination properties of uni- and multivariate models. Our results show that a high percentage of pS6 positive tumor cells was associated with an unfavorable prognosis in a cohort of 129 hormone receptor positive/HER2 negative breast cancer patients (Hazard Ratio = 5.92; Log-Rank p = 9.5e-08; median follow-up = 53 months). When assessed in combination with lymph node status, the predictive capacity was higher compared to both univariate models individually. In conclusion, pS6 could represent a novel independent marker for predicting recurrence risk in luminal breast cancer. [ABSTRACT FROM AUTHOR]

Glioblastomas (GBMs) are the most aggressive types of central nervous system tumors. Although certain genomic alterations have been identified as prognostic biomarkers of GBMs, the histomorphological features that predict their prognosis remain elusive. In this study, following an integrative diagnosis of 227 GBMs based on the 2021 World Health Organization classification system, the cases were histologically fractionated by cellular variations and abundance to evaluate the relationship between cellular heterogeneity and prognosis in combination with O-6-methylguanine-DNA methyltransferase gene promoter methylation (mMGMTp) status. GBMs comprised four major cell types: astrocytic, pleomorphic, gemistocytic, and rhabdoid cells. t-distributed stochastic neighbor embedding analysis using the histological abundance of heterogeneous cell types identified two distinct groups with significantly different prognoses. In individual cell component analysis, the abundance of gemistocytes showed a significantly favorable prognosis but confounding to mMGMTp status. Conversely, the abundance of epithelioid cells was correlated with the unfavorable prognosis. Linear model analysis showed the favorable prognostic utility of quantifying gemistocytic and epithelioid cells, independent of mMGMTp. The evaluation of GBM cell histomorphological heterogeneity is more effective for prognosis prediction in combination with mMGMTp analysis, indicating that histomorphological analysis is a practical and useful prognostication tool in an integrative diagnosis of GBMs. [ABSTRACT FROM AUTHOR]

To evaluate the prognosis and influencing factors of retinal vein occlusion (RVO) in patients with concomitant carotid artery disease receiving anti-vascular endothelial growth factor (VEGF) treatment. Patients diagnosed with RVO and receiving anti-VEGF treatment were included. Eye and clinical data were collected. The patients were divided into a group with concomitant carotid artery disease (Group A) and a group without concomitant carotid artery disease (Group B). The risk factors affecting the visual prognosis of RVO patients with concomitant carotid artery disease were analyzed. Among 177 eligible patients with RVO, 101 had concomitant carotid artery disease (Group A), while 76 did not (Group B). Group A had a significantly lower treatment effectiveness rate than Group B (P < 0.001). The age and platelet distribution width of Group A were significantly higher than Group B (P < 0.001). Multivariate logistic regression analysis showed that baseline best-corrected visual acuity (BCVA), disorganization of retinal inner layers (DRIL), external limiting membrane (ELM) disruption, and red blood cell distribution width (RDW) were significantly associated with the posttreatment visual prognosis of RVO patients with concomitant carotid artery disease(P < 0.05). RVO patients with concomitant carotid artery disease had a significantly lower treatment effectiveness rate than RVO patients without carotid artery disease. The poor baseline BCVA, DRIL, ELM disruption, and a greater RDW are risk factors for low anti-VEGF treatment efficacy among RVO patients with concomitant carotid artery disease. [ABSTRACT FROM AUTHOR]

Globally, CRC ranks as a principal cause of mortality, with projections indicating a substantial rise in both incidence and mortality by the year 2040. The immunological responses to cancer heavily rely on the function of CD4Tconv. Despite this critical role, prognostic studies on CRC-related CD4Tconv remain insufficient. In this investigation, transcriptomic and clinical data were sourced from TCGA and GEO. Initially, we pinpointed CD4TGs using single-cell datasets. Prognostic genes were then isolated through univariate Cox regression analysis. Building upon this, 101 machine learning algorithms were employed to devise a novel risk assessment framework, which underwent rigorous validation using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent ROC curves, nomograms, and calibration plots. Furthermore, GSEA facilitated the examination of these genes' potential roles. The RS derived from this model was also analyzed for its implications in the TME, and its potential utility in immunotherapy and chemotherapy contexts. A novel prognostic model was developed, utilizing eight CD4TGs that are significantly linked to the outcomes of patients with CRC. This model's RS showcased remarkable predictive reliability for the overall survival rates of CRC patients and strongly correlated with malignancy levels. RS serves as an autonomous prognostic indicator, capable of accurately forecasting patient prognoses. Based on the median value of RS, patients were categorized into subgroups of high and low risk. The subgroup with higher risk demonstrated increased immune infiltration and heightened activity of genes associated with immunity. This investigation's establishment of a CD4TGs risk model introduces novel biomarkers for the clinical evaluation of CRC risks. These biomarkers may enhance therapeutic approaches and, in turn, elevate the clinical outcomes for patients with CRC by facilitating an integrated treatment strategy. [ABSTRACT FROM AUTHOR]

ER+/HER2- breast cancer is a common subtype of breast cancer. This study aimed to evaluate the prognostic value of ER-to-PR difference (EPD) in ER+/HER2- early breast cancer (EBC). A retrospective cohort study was conducted, including 3,340 ER+/HER2- EBC patients, divided into a training cohort of 2,873 patients and a validation cohort of 467 patients. The optimal EPD cutoff value for stratifying patients was determined using X-tile. Additionally, the prognostic value of EPD, when combined with other clinicopathological factors, was assessed using the Cox proportional hazards model and five traditional machine learning methods. The optimal cutoff value for EPD was determined as 10%, categorizing patients into EPD-low (ER-PR ≤ 10%) and EPD-high (ER-PR > 10%) expression groups. Patients with EPD-high tumors exhibited a poorer prognosis compared to those with EPD-low tumors. In the multivariate Cox model, EPD was identified as an independent prognostic factor for disease-free survival (DFS) (HR: 1.496, P = 0.004). Integrating EPD with clinicopathological parameters into a predictive model effectively predicts DFS in ER+/HER2- EBC patients. In the most effective CoxPH model, the area under the curve (AUC) values for predicting 3-year, 5-year, and 7-year DFS were 0.718, 0.702, and 0.701, respectively, in the WCH cohort, and 0.770, 0.739, and 0.743, respectively, in the FUSCC cohort. EPD may serve as a novel prognostic marker, allowing for the identification of a population with a poor prognosis in ER+/HER2- EBC, thereby aiding clinical decision-making. [ABSTRACT FROM AUTHOR]

In recent years, CD9 has been extensively studied as a potential biomarker for cancer. However, the biological role of CD9 in gliomas remains unclear. This study investigates the function of CD9 in gliomas and its molecular mechanisms. Utilizing pan-cancer analysis with TCGA, CGGA, and GEO databases, differential expression of CD9 was observed in 11 tumor types within the TCGA cohort, and it was associated with patient survival rates. Analysis of the CGGA glioma database revealed that patients with high CD9 expression had lower survival rates. The area under the ROC curve (AUC) for GSE16011 was greater than 0.7, indicating a high discriminative ability. Through gene set enrichment analysis (GSEA), immune-related analysis, and CD9 mutation detection, CD9 was found to have the strongest correlation with neutrophil involvement (cor = 0.30, P < 0.05), and the high CD9 expression group exhibited higher rejection responses and TIDE scores, suggesting a lower likelihood of successful immunotherapy. The high CD9 expression group was more sensitive to 81 drugs, indicating potential therapeutic effects for gliomas. Furthermore, overexpression of CD9 in gliomas may be associated with gene mutations. Down-regulation or up-regulation of CD9 expression in the glioblastoma cell line LN229 showed that CD9 could positively regulate the migratory ability of LN229 cells. Further, several marker genes, such as VEGFR-2, TGF-β1, CASP1 and PI3K, were down regulated in CD9 knockdown cell lines and up regulated in CD9 overexpression cell lines, compared with control cell line. This study preliminarily explores the role of CD9 in gliomas and its prognostic value, providing new insights for personalized treatment strategies in glioma therapy. [ABSTRACT FROM AUTHOR]

Studies have shown that the cachexia index (CXI) is a useful predictor of cachexia in patients with colorectal cancer. However, the application of the CXI is limited stemming from the intricacy and additional cost of radiographic examinations. This study aimed to develop an easy-to-use and practical CXI based on fat-free mass index (FFMI-CXI) to evaluate the prognostic value of FFMI-CXI in CRC. A total of 656 patients with CRC were enrolled in the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. The FFMI-CXI was calculated as [FFMI (kg)/height (m)2 × serum albumin (g/L)]/neutrophil-lymphocyte ratio. The cutoff value for FFMI-CXI was determined through the analysis of ROC curves and Youden's index for both male and female cohorts. Kaplan–Meier survival curves with log-rank tests were conducted to compare time–event relationships between different groups. Cox proportional hazards regression models incorporating both univariate and multivariate variables were employed to explore the independent prognostic factors associated with OS. Logistic regression analysis was performed to assess the association of the FFMI-CXI with secondary outcomes. The major outcome was 5-year overall survival (OS). Based on the cutoff values, 331 patients had low FFMI-CXI, and 325 patients had high FFMI-CXI. Patients in the low FFMI-CXI subgroup were significantly older and had advanced TNM stage, malnutrition, high systemic inflammation, long hospitalizations, high hospitalization costs, adverse short-term outcomes, and all-cause mortality. Multivariate Cox regression analyses revealed that FFMI-CXI (HR 0.47, 95% CI 0.33–0.66; p < 0.001) and TNM stage (HR 3.38, 95% CI 2.63–4.35; p < 0.001) were independently associated with OS in CRC patients. K-M survival curves revealed that the CRC patients with a high FFMI-CXI had significantly more favorable OS than those with low FFMI-CXI (62.84% vs. 84.31%; log-rank p < 0.001). Furthermore, the FFMI-CXI was valuable for predicting 90-day outcomes, malnutrition, cancer cachexia, length of hospitalization, and hospitalization expenses. This study revealed that the FFMI-CXI can be used as a prognostic indicator in patients with CRC. Patients with low FFMI-CXI should receive more attention. [ABSTRACT FROM AUTHOR]

Lymphocyte activating gene-3 (LAG3) is a distinctive T cell co-receptor that is expressed on the surface of lymphocytes. It plays a special inhibitory immune checkpoint role due to its unique domain and signaling pattern. Our aim is to explore the correlation between LAG3 in cancers and physiological processes related to a range of cancers, as well as build LAG3-related immunity and prognostic models. By comprehensively using of datasets and methods from TCGA, GTE-x and GEO databases, cBioPortal, HPA, Kaplan-Meier Plotter, Spearman, CellMinerTM, we delved deeper into the potential impact of the LAG3 in cancer development. These include expression differences, Localization of tumor cell subsets, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways and prognosis. Furthermore, we explored LAG3 interactions with different drugs. LAG3 is highly expressed in ACC (p < 0.001), BRCA (p < 0.001), DLBC (p < 0.001), ESCA (p < 0.001), GBM (p < 0.001), HNSC (p < 0.001), KIRC (p < 0.001), LGG (p < 0.001), LUAD (p < 0.01), LUSC (p < 0.001), PAAD (p < 0.001), PCPG (p < 0.01), SKCM (p < 0.001), STAD (p < 0.001), TGCT (p < 0.001) and THCA (p < 0.05), while lowly expressed in COAD (p < 0.001), LIHC (p < 0.05), OV (p < 0.001), PRAD (p < 0.001), READ (p < 0.001), UCEC (p < 0.001) and UCS (p < 0.001). High expression of LAG3 correlates with longer overall survival (OS) in BLCA (HR = 0.67, p < 0.05), CESC (HR = 0.3, p < 0.001), HNSC (HR = 0.67, p < 0.01), LUSC (HR = 0.71, p < 0.05), OV (HR = 0.65, p < 0.01), STAD (HR = 0.68, p < 0.05), and UCEC (HR = 0.57, p < 0.01). Conversely, in KIRC (HR = 1.85, p < 0.001), KIRP (HR = 2.81, p < 0.001), and THYM (HR = 8.92, p < 0.001), high LAG3 expression corresponds to shorter OS. Comprehensive results for recurrence-free survival (RFS) indicate that LAG3 acts as a protective factor in BLCA, CESC, OV, and UCEC. Moreover, LAG3 is widely expressed in tumor-associated lymphocytes, positively correlating with tumor immune scores and stromal scores, and significantly present in the C2 immune subtype across various tumors. High LAG3 expression correlates with increased immune infiltration. LAG3 shows associations with MSI, TMB, and the MMR system, participating in multiple signaling pathways including the T cell receptor pathway. It also demonstrates positive correlations with sensitivity to eleven different drugs. Unlike traditional inhibitory immune checkpoints, LAG3 exhibits dual roles in clinical and immune prognostication across pan-cancers, making it a significant predictive factor. In some cancers, LAG3 serves as a risk factor, indicating adverse clinical outcomes. Conversely, in BLCA, CESC, OV, and UCEC, LAG3 acts as a protective factor associated with longer patient survival. LAG3 demonstrates strong associations within tumor immunity, participating in a range of immune and inflammatory signaling pathways. Elevated levels of LAG3 are linked not only to T cell exhaustion but also to increased immune infiltration and polarization towards M1 macrophages. [ABSTRACT FROM AUTHOR]

Globally, the prevalence of multidrug-resistant tuberculosis (MDR-TB) has been increasing recently. This is a major public health concern, as MDR-TB is more difficult to treat and has poorer outcomes compared to drug-sensitive tuberculosis. The main objective of the study was to identify risk factors for recurrent multidrug-resistant tuberculosis, at Alert Specialized Hospital, Addis Ababa, by using different parametric shared frailty models. From January 2016 to December 2021, a retrospective study was conducted on MDR-TB patients at Alert Specialized Hospital in Addis Ababa. The data for the study were collected from the medical records of MDR-TB patients at the hospital during this time period. Gamma and inverse-Gaussian shared frailty models were used to analyze the dataset, with the exponential, Weibull, and lognormal distributions included as baseline hazard functions. The data were analyzed using R statistical software. The median recurrence time of the patients was 12 months, and 149 (34.3%) had recurrences. The clustering effect was statistically significant for multiple drug-resistant tuberculosis patients' recurrence. According to the Weibull-Inverse-Gaussian model, factors that reduced time to MDR-TB recurrence included lower weight (ɸ = 0.944), smoking (ɸ = 0.045), alcohol use (ɸ = 0.631), hemoptysis (ɸ = 0.041), pneumonia (ɸ = 0.564), previous anti-TB treatment (ɸ = 0.106), rural residence (ɸ = 0.163), and chronic diseases like diabetes (ɸ = 0.442) were associated with faster recurrence. While, higher education (ɸ = 3.525) and age (ɸ = 1.021) extended time to recurrence. For weight increment, smokers and alcohol users, clinical complications of hemoptysis and pneumonia, patients with pulmonary disease who had a history of previous anti-TB treatment, and being rural residents are prognostic factors. There was a significant clustering effect at the Alert Specialized Hospital in Addis Ababa, Ethiopia. The Weibull-Inverse Gaussian Shared Frailty Model was chosen as the best model for predicting the time to recurrence of MDR-TB. [ABSTRACT FROM AUTHOR]

In recent years, the incidence of tibial plateau fractures (TPF) has been on the rise. Deep vein thrombosis (DVT) may lead to poor prognosis in patients. The systemic immune-inflammation index(SII) are novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model. This study used binary logistic regression analysis to predict the predictive effect of SII on the occurrence of DVT in tibial plateau fracture patients. And use R studio to construct nomogram model. The results showed that Age (1.03 [1, 1.06], p = 0.032), SII (3.57 [1.68, 7.61], p = 0.04), and NC (7.22 [3.21, 16.26], p < 0.001) were independent predictive factors for DVT. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them. The nomogram constructed based on SII can assist clinicians in early assessment of the probability of DVT occurrence. [ABSTRACT FROM AUTHOR]

The study aimed to develop and validate a preoperative scoring system to predict the risk of lymph node metastasis (LNM) in cervical cancer (CC). A total of 426 stage IB1–IIA1 CC patients were randomly divided into two sets. A logistic regression model was used to determine independent factors that contribute to LNM. A preoperative scoring system was developed based on beta (β) coefficients. An area under the receiver operating curve (AUC) was used to test for model discrimination. Five-year overall survival (OS) rate was 91.7%. Multivariable logistic regression analysis showed that FIGO stage, tumor size, depth of invasion on MRI, and squamous cell carcinoma antigen levels were independent risk factors in the development set (all P < 0.05). The AUCs of the scoring system for the development and validation sets were 0.833 (95% CI = 0.757–0.909) and 0.767 (95% CI = 0.634–0.891), respectively. Patients who scored 0–2, 3–5, and 6–8 were classified into low-risk, medium-risk, and high-risk groups. Predicted rates were in accord with observed rates in both sets. The 5-year OS rates of the new groups were also significantly different for the entire group, development set, and validation set (all P < 0.05). LNM affects the prognosis of CC patients. The scoring system can be used to assist in evaluating the risk of LNM in CC patients preoperatively. It is easy to obtain and can provide reference for clinical treatment decision-making. [ABSTRACT FROM AUTHOR]

Patients with traumatic brain injury (TBI) frequently exhibit concomitant immunosuppression. In this study, we evaluated the predictive values of soluble programmed death-1 (sPD-1) and soluble programmed death ligand-1 (sPD-L1) in patients with severe TBI. Peripheral blood sPD-1 and sPD-L1 levels were measured within 48 h of patient admission. A total of 20 healthy volunteers and 82 patients were enrolled in this study. The levels of sPD-1 and sPD-L1 were upregulated in patients with severe TBI (P < 0.001). They were significantly increased in the post-TBI severe pneumonia group and among non-survivors (P < 0.001). The area under the curves (AUCs) for sPD-1 and sPD-L1 levels to predict severe pneumonia were 0.714 and 0.696, respectively, and the AUCs to predict mortality were 0.758 and 0.735. The levels of sPD-1 and sPD-L1 are correlated with the GCS scores at admission, APACHE II scores, length of MV, and time elapsed to mortality. The levels of sPD-1 and sPD-L1 emerged as independent predictive factors for severe pneumonia and mortality. This study demonstrates that upregulation of sPD-1 and sPD-L1 in severe TBI patients is significantly associated with severe pneumonia and mortality, suggesting their potential as predictive biomarkers for these outcomes. [ABSTRACT FROM AUTHOR]

As the global prevalence of chronic liver disease continues to rise, the need to determine which patients will develop end-stage liver disease and require liver transplantation is increasingly important. However, current prognostic models perform sub-optimally. We aim to determine microRNA profiles associated with clinical decompensation and mortality/transplantation within 1 year. We examined microRNA expression profiles in plasma samples from patients across the spectrum of cirrhosis (n = 154), acute liver failure (ALF) (n = 22), sepsis (n = 20) and healthy controls (HC) (n = 20). We demonstrated that a microRNA-based model (miR-24 and -27a) associated with systemic inflammation differentiated decompensated cirrhosis states from compensated cirrhosis and HC (AUC 0.77 (95% CI 0.69–0.85)). 6 patients within the compensated cirrhosis group decompensated the subsequent year and their exclusion improved model performance (AUC 0.81 (95% CI 0.71–0.89)). miR-191 (associated with liver injury) predicted risk of mortality across the cohort when acutely decompensated and acute-on-chronic-liver failure patients were included. When they were excluded miR-24 (associated with systemic inflammation) predicted risk of mortality. Our findings demonstrate that microRNA associated with systemic inflammation and liver injury predict adverse outcomes in cirrhosis. miR-24 and -191 require further investigation as prognostic biomarkers and therapeutic targets for patients with liver disease. [ABSTRACT FROM AUTHOR]

Lower-grade gliomas (LGGs) exhibit diverse clinical behaviors and varying immune infiltration levels. Mitochondria have been implicated in numerous cancer pathogenesis and development, including LGGs. However, the precise biological functions of mitochondrial genes in shaping the immune landscape and the prognostic significance of LGGs remain elusive. Utilizing the Mito-Carta3.0 database, we curated a total of 1136 genes implicated in mitochondrial functions. By leveraging the expression profiles of 1136 genes related to mitochondria, we successfully categorized LGGs into four distinctive mitochondria-related transcriptome (MRT) subtypes. Our thorough analysis conclusively demonstrated that these subtypes exhibited marked disparities. To enable a personalized and integrated evaluation of LGG patients, we developed a prognostic signature known as MRT-related prognostic signature (MTRS). MTRS demonstrated correlation with mitochondria-related transcriptome (MRT) subtypes, allowing the assessment of patients' prognosis and immune microenvironment. We conducted a detailed exploration of the single-cell distribution of MTRS in lower-grade gliomas and verified the core genes of MTRS within the spatial transcriptome of these tumors. Furthermore, our study pinpointed MGME1 as the pivotal gene in the model, functioning as an oncogene that exerts influence on cell proliferation and migration capabilities. Our research highlights the importance of mitochondrial transcriptomic features in LGGs, offering paths for tailored therapies. [ABSTRACT FROM AUTHOR]

Breast cancer remains a significant public health issue, often resulting in severe side effects such as neutropenia, highlighting the need for reliable predictors of clinical outcomes. This study aimed to evaluate the predictive value of body composition measures for mortality, recurrence, and chemotherapy-induced neutropenia in patients with breast cancer following surgery and chemotherapy. We retrospectively analyzed 85 breast cancer patients who underwent surgery and chemotherapy between 2006 and 2016. Body composition was assessed using computed tomography (CT) or positron emission tomography (PET) at diagnosis and three years and five years post-diagnosis. Metrics included skeletal muscle area (SMA), skeletal muscle index (SMI), subcutaneous adipose tissue area (SAT), and visceral adipose tissue area (VAT). Longitudinal analysis revealed a decrease in muscle mass (P < 0.001 for both SMA and SMI) and nonsignificant changes in fat mass (P = 0.449 for SAT and P = 0.798 for VAT). A lower SMI at diagnosis was significantly associated with increased mortality (P = 0.019) and a higher incidence of grade 4 neutropenia (P = 0.008). There was no significant association between SMI at diagnosis and recurrence (P = 0.691). No associations were found between body composition measurements during the follow-up period and the clinical outcomes. Lower skeletal muscle mass at diagnosis is strongly associated with higher mortality and chemotherapy-induced complications in patients with breast cancer, highlighting the potential of readily available imaging techniques as valuable predictors of clinical outcomes. [ABSTRACT FROM AUTHOR]

Gremlin 1 (GREM1) can regulate the development of many cancers. However, a few studies have revealed the role of GREM1 in bladder cancer (BC). To evaluate the expression and potential function of GREM1 in bladder cancer, we used R version 3.6.3 and related packages to analyze the data from common databases. Samples from our institution were assessed by immunohistochemical staining (IHC), which was approved by the Institutional Ethics Committee (K20220830). GREM1 was highly expressed in BC tissues according to the TCGA and IHC data. Data from TCGA, GSE31684, GSE32894, and IHC showed that GREM1 has significant prognostic value for BC patients. GREM1 is involved in immune and metabolism-related pathways. According to the TIDE algorithm, 61.0% of patients with low GREM1 expression responded well to immunotherapy, compared to only 13.3% in the high GREM1 expression group. High GREM1 expression was associated with sensitivity to cisplatin, docetaxel, gemcitabine, and vinblastine. Thus, GREM1 can predict prognosis and responses to immunotherapy and chemotherapy in BC patients, making it a potential biomarker and therapeutic target. [ABSTRACT FROM AUTHOR]

This study explored the role of radioiodine therapy (RAI) in low-risk thyroid cancer patients and examined the disease-specific survival (DSS) rates in a large cohort of differentiated thyroid cancer patients (DTC). We obtained patient data from SEER database. Patients who underwent total thyroidectomy were included and categorized into three groups based on histology: classical papillary thyroid carcinoma (C-PTC), follicular type variant carcinoma (FV-PTC), and follicular thyroid cancer (FTC). Patients with distant metastasis, tumor size ≥ 200 mm, chemotherapy, or any type of radiation other than RAI were also excluded. A nomogram was developed and tested for discrimination and calibration. In total, 96,532 thyroid cancer cases were examined, including 59,460 C-PTC, 31,583 FV-PTC, and 5,489 FTC cases. Age > 65 years and male sex were correlated with lower survival rates across the subtypes. In addition, extrathyroidal extension had a worse survival effect in patients with FTC. DSS rates were compared between patients who received RAI and those who did not, with a 3% difference in C-PTC (94% vs. 91%, p < 0.001), 2% in FV-PTC (92% vs. 90%, p < 0.001), and 1% in FTC (89% vs. 88%, p = 0.084) at 15 years. The nomograms for long-term DSS showed high discriminatory abilities with C-indices of 0.815, 0.805, and 0.781 for C-PTC, FV-PTC, and FTC, respectively. The developed nomogram can be used in the treatment plan for patients with DTC. Our study emphasizes the prognostic factors for DTC and highlights the need for personalized treatment plans based on individual risk profiles. [ABSTRACT FROM AUTHOR]

SHP-1, a nonreceptor protein tyrosine phosphatase encoded by ptpn6, has been regarded as a regulatory protein of hematopoietic cell biology for years. However, there is now increasing evidence to support its role in tumors. Thus, the role of ptpn6 for prognosis and immune regulation across 33 tumors was investigated, aiming to explore its functional heterogeneity and clinical significance in pan-cancer. Differential expression of ptpn6 was found between cancer and adjacent normal tissues, and its expression was significantly correlated with the prognosis of tumor patients. In most cancers, ptpn6 expression was significantly associated with immune infiltration. This was further confirmed by ptpn6-related genes/proteins enrichment analysis. Additionally, genetic alterations in ptpn6 was observed in most cancers. As for epigenetic changes, it's phosphorylation levels significantly altered in 6 tumors, while methylation levels significantly altered in 12 tumors. Notably, the methylation levels of ptpn6 were significantly decreased in 11 tumors, accompanied by its increased expression in 8 of them, suggesting that the hypomethylation may be related to its increased expression. Our results show that ptpn6 plays a specific role in tumor immunity and exerts a pleiotropic effect in a variety of tumors. It can serve as a prognostic factor for some cancers. Especially in LGG, KIRC, UCS and TGCT, the increased expression of ptpn6 is associated with poor prognosis and high immune infiltration. This aids in understanding the role of ptpn6 in tumor biology, and can provide insight into presenting a potential biomarker for poor prognosis and immune infiltration in cancers. [ABSTRACT FROM AUTHOR]

Liposarcoma (LPS) is the second most common kind of soft tissue sarcoma, and a heterogeneous malignant tumor derived from adipose tissue. Up to now, the prognostic value of BAG1 or BAG2 in LPS has not been defined yet. Expression profiling data of LPS patients were collected from TCGA and GEO database. Survival curves were plotted to verify the outcome differences of patients based on BAG1 or BAG2 expression. Univariate and multivariate Cox regression models were used to analyze the prognostic ability of BAG1 or BAG2. Chaperone's regulators BAG1 and BAG2 were identified as prognostic biomarkers for LPS patients, which exhibited distinct expression patterns and survival outcome prediction performances. Patients with high BAG2 expression and/or low BAG1 expression had worse prognosis. Enrichment analysis showed that BAG1 was involved in negative regulation of TGF-β signaling. Low expression of BAG1 was associated with high abundance of regulatory T cells (Tregs). The 2-gene signature model further confirmed the improved risk assessment performance of BAG1 and BAG2: high risk patients displayed poor prognosis. BAG1 and BAG2 are supposed to be potential prognostic biomarkers for LPS and have impacts on liposarcomagenesis and immune infiltration in distinctive manners, which may function as potential therapy targets (BAG1 agonists/BAG2 inhibitors) for LPS. [ABSTRACT FROM AUTHOR]

Melanoma is a highly malignant form of skin cancer that typically originates from abnormal melanocytes. Despite significant advances in treating metastatic melanoma with immune checkpoint blockade (ICB) therapy, a substantial number of patients do not respond to this treatment and face risks of recurrence and metastasis. This study collected data from multiple datasets, including cohorts from Riaz et al., Gide et al., MGH, and Abril-Rodriguez et al., focusing on on-treatment samples during ICB therapy. We used the single-sample gene set enrichment analysis (ssGSEA) method to calculate immunogenic cell death scores (ICDS) and employed an elastic network algorithm to construct a model predicting ICB efficacy. By analyzing 18 ICD gene signatures, we identified 9 key ICD gene signatures that effectively predict ICB treatment response for on-treatment metastatic melanoma specimens. Results showed that patients with high ICD scores had significantly higher response rates to ICB therapy compared to those with low ICD scores. ROC analysis demonstrated that the AUC values for both the training and validation sets were around 0.8, indicating good predictive performance. Additionally, survival analysis revealed that patients with high ICD scores had longer progression-free survival (PFS). This study used an elastic network algorithm to identify 9 ICD gene signatures related to the immune response in metastatic melanoma. These gene features can not only predict the efficacy of ICB therapy but also provide references for clinical decision-making. The results indicate that ICD plays an important role in metastatic melanoma immunotherapy and that expressing ICD signatures can more accurately predict ICB treatment response and prognosis for on-treatment metastatic melanoma specimens, thus providing a basis for personalized treatment. [ABSTRACT FROM AUTHOR]

Necroptosis is intimately associated with the initiation and progression of colon adenocarcinoma (COAD). However, studies on necroptosis-related genes (NRGs) and the regulating long non-coding RNAs (NRGlncRNAs) in the context of COAD are limited. We retrieved the cancer genome atlas (TCGA) to collect datasets of NRGs and NRGlncRNAs on COAD patients. The risk model constructed using Cox and least absolute shrinkage and selection operator (LASSO) regression was then employed to identify NRGs and NRGlncRNAs with prognostic significance. Subsequently, we validated the results using gene expression omnibus (GEO) datasets from different populations, conducted Mendelian randomization (MR) analysis to explore the potential causal relationships between prognostic NRGs and COAD, and conducted cell experiments to verify the expression of prognostic NRGlncRNAs in COAD. Furthermore, we explored potential pathways and regulatory mechanisms of these prognostic NRGlncRNAs and NRGs in COAD through enrichment analysis, immune cell correlation analysis, tumor microenvironment analysis, immune checkpoint analysis, tumor sample clustering, and so on. We identified eight NRGlncRNAs (AC245100.5, AP001619.1, LINC01614, AC010463.3, AL162595.1, ITGB1-DT, LINC01857, and LINC00513) used for constructing the prognostic model and nine prognostic NRGs (AXL, BACH2, CFLAR, CYLD, IPMK, MAP3K7, ATRX, BRAF, and OTULIN) with regulatory relationships with them, and their validation was performed using GEO and GWAS datasets, as well as cell experiments, which showed largely consistent results. These prognostic NRGlncRNAs and NRGs modulate various biological functions, including immune inflammatory response, oxidative stress, immune escape, telomere regulation, and cytokine response, influencing the development of COAD. Additionally, stratified analysis of the high-risk and low-risk groups based on the prognostic model revealed elevated expression of immune cells, increased expression of tumor microenvironment cells, and upregulation of immune checkpoint gene expression in the high-risk group. Finally, through cluster analysis, we identified tumor subtypes, and the results of cluster analysis were essentially consistent with the analysis between risk groups. The prognostic NGRlncRNAs and NRGs identified in our study serve as prognostic indicators and potential therapeutic targets for COAD, providing a theoretical basis for the clinical diagnosis and treatment of COAD and offering guidance for further research. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality, and the role of family cancer history in disease progression and treatment response remains underexplored. This study aims to investigate the influence of family tumor history on disease-free survival, tumor metabolism, and treatment response in NSCLC patients. A retrospective, single-center study of 414 NSCLC patients was conducted, with 101 patients having a family history of cancer (FHC). Disease-free survival (DFS), tumor glucose metabolism assessed by 18F-FDG PET/CT, and treatment response to chemoradiotherapy, targeted therapy, and immunotherapy were analyzed. Multivariate modeling was performed to improve prognostic prediction. Patients with FHC exhibited higher TNM staging, increased susceptibility to lymph node invasion, and elevated tumor glucose metabolism levels. Family history of cancer, particularly colorectal and lung cancer, was a significant risk factor for disease-free survival. Targeted therapy and immunotherapy significantly improved patient prognosis, while family history of cancer affected the efficacy of chemoradiotherapy but not targeted therapy or immunotherapy. Multivariate modeling combining FHC, treatment, and tumor metabolism levels yielded improved predictive performance. Our study highlights the importance of considering a patient’s family history when assessing risk profiles and formulating treatment decisions for NSCLC patients. Further research is needed to understand the molecular mechanisms underlying these observed associations and to develop more effective treatment strategies for NSCLC patients with a cancer family history. [ABSTRACT FROM AUTHOR]