Prognosis Of Carcinoma Research Articles

Prognostic significance of MRI features in patients with solitary large hepatocellular carcinoma following surgical resection.

To assess the prognostic impact of preoperative MRI features on outcomes for single large hepatocellular carcinoma (HCC) (≥ 8 cm) after surgical resection. This retrospective study included 151 patients (mean age: 59.2 years; 126 men) with a single large HCC who underwent gadoxetic acid-enhanced MRI and surgical resection between 2008 and 2020. Clinical variables, including tumor markers and MRI features (tumor size, tumor margin, and the proportion of hypovascular component on hepatic arterial phase (AP) (≥ 50% vs. < 50% tumor volume) were evaluated. Cox proportional hazards model analyzed overall survival (OS), recurrence-free survival (RFS), and associated factors. Among 151 HCCs, 37.8% and 62.2% HCCs were classified as ≥ 50% and < 50% AP hypovascular groups, respectively. The 5- and 10-year OS and RFS rates in all patients were 62.0%, 52.6% and 41.4%, 38.5%, respectively. Multivariable analysis revealed that ≥ 50% AP hypovascular group (hazard ratio [HR] 1.7, p = 0.048), tumor size (HR 1.1, p = 0.006), and alpha-fetoprotein ≥ 400 ng/mL (HR 2.6, p = 0.001) correlated with poorer OS. ≥ 50% AP hypovascular group (HR 1.9, p = 0.003), tumor size (HR 1.1, p = 0.023), and non-smooth tumor margin (HR 2.1, p = 0.009) were linked to poorer RFS. One-year RFS rates were lower in the ≥ 50% AP hypovascular group than in the < 50% AP hypovascular group (47.4% vs 66.9%, p = 0.019). MRI with ≥ 50% AP hypovascular component and larger tumor size were significant factors associated with poorer OS and RFS after resection of single large HCC (≥ 8 cm). These patients require careful multidisciplinary management to determine optimal treatment strategies. Preoperative MRI showing a ≥ 50% arterial phase hypovascular component and larger tumor size can predict worse outcomes after resection of single large hepatocellular carcinomas (≥ 8 cm), underscoring the need for tailored, multidisciplinary treatment strategies. MRI features offer insights into the postoperative prognosis for large hepatocellular carcinoma. Hypovascular component on arterial phase ≥ 50% and tumor size predicted poorer overall survival and recurrence-free survival. These findings can assist in prioritizing aggressive and multidisciplinary approaches for patients at risk for poor outcomes.

Effect of cytokines on advanced hepatocellular carcinoma prognosis receiving radiotherapy and tislelizumab plus anlotinib: a single-center phase II clinical trial

The purpose of this study was to investigate the relationship between circulating cytokines and liver function and prognosis of patients with advanced hepatocellular carcinoma (HCC) treated with radiotherapy combined with tislelizumab and anlotinib. The liver function indexes and pre-treatment levels of cytokines in 47 patients were measured by chemical method and flow cytometry. The median follow-up was 23.1 months. The objective response and the disease control rates were 46.8% and 68.1%, while overall survival (OS) and progression-free survival (PFS) were 12.6 and 11.4 months, respectively. Adverse events (2.1%) were grade 3–4. In addition to stage, intrahepatic metastasis and Child–Pugh score, pre-treatment interleukin-6 (IL-6) was the main cytokine affecting OS and PFS (p < 0.05). The OS (14.63 pg/mL as cutoff value) and PFS (9.85 pg/mL as cutoff value) of patients with low IL-6 levels exceeded those with high levels (21.0 and 6.9, 15.8 and 10.0 months, respectively). The risks of death and disease progression were reduced by 63.0% (HR = 0.37, 95% CI: 0.19–0.72) and 43.0% (HR = 0.57, 95% CI: 0.22–1.47), respectively. Pre-treatment IL-6 levels may be a simple and effective prognostic indicator for patients with advanced HCC treated with radiotherapy combined with immunotargeted therapy.

TCL1A-expressing B cells are critical for tertiary lymphoid structure formation and the prognosis of oral squamous cell carcinoma

BackgroundOral squamous cell carcinoma (OSCC) is a malignant tumor with a poor prognosis. Traditional treatments have limited effectiveness. Regulation of the immune response represents a promising new approach for OSCC treatment. B cells are among the most abundant immune cells in OSCC. However, the role of B cells in OSCC treatment has not been fully elucidated.MethodsSingle-cell RNA sequencing analysis of 13 tissues and 8 adjacent normal tissues from OSCC patients was performed to explore differences in B-cell gene expression between OSCC tissues and normal tissues. We further investigated the relationship between differentially expressed genes and the immune response to OSCC. We utilized tissue microarray data for 146 OSCC clinical samples and RNA sequencing data of 359 OSCC samples from The Cancer Genome Atlas (TCGA) to investigate the role of T-cell leukemia 1 A (TCL1A) in OSCC prognosis. Multiplex immunohistochemistry (mIHC) was employed to investigate the spatial distribution of TCL1A in OSCC tissues. We then investigated the effect of TCL1A on B-cell proliferation and trogocytosis. Finally, lentiviral transduction was performed to induce TCL1A overexpression in B lymphoblastoid cell lines (BLCLs) to verify the function of TCL1A.ResultsOur findings revealed that TCL1A was predominantly expressed in B cells and was associated with a better prognosis in OSCC patients. Additionally, we found that TCL1A-expressing B cells are located at the periphery of lymphatic follicles and are associated with tertiary lymphoid structures (TLS) formation in OSCC. Mechanistically, upregulation of TCL1A promoted the trogocytosis of B cells on dendritic cells by mediating the upregulation of CR2, thereby improving antigen-presenting ability. Moreover, the upregulation of TCL1A expression promoted the proliferation of B cells.ConclusionThis study revealed the role of B-cell TCL1A expression in TLS formation and its effect on OSCC prognosis. These findings highlight TCL1A as a novel target for OSCC immunotherapy.

Predicting Survival Using Whole-Liver MRI Radiomics in Patients with Hepatocellular Carcinoma After TACE Refractoriness.

To develop a model based on whole-liver radiomics features of pre-treatment enhanced MRI for predicting the prognosis of hepatocellular carcinoma (HCC) patients undergoing continued transarterial chemoembolization (TACE) after TACE-resistance. Data from 111 TACE-resistant HCC patients between January2014 and March2018 were retrospectively collected. At a ratio of 7:3, patients were randomly assigned to developing and validation cohorts. The whole-liver were manually segmented, and the radiomics signature was extracted. The tumor and liver radiomics score (TLrad-score) was calculated. Models were trained by machine learning algorithms and their predictive efficacies were compared. Tumor stage, tumor burden, body mass index, alpha-fetoprotein, and vascular invasion were revealed as independent risk factors for survival. The model trained by Random Forest algorithms based on tumor burden, whole-liver radiomics signature, and clinical features had the highest predictive efficacy, with c-index values of 0.85 and 0.80 and areas under the ROC curve of 0.96 and 0.83 in the developing cohort and validation cohort, respectively. In the high-rad-score group (TLrad-score > - 0.34), the median overall survival (mOS) was significantly shorter than in the low-rad-score group (17m vs. 37m, p < 0.001). A shorter mOS was observed in patients with high tumor burden compared to those with low tumor burden (14m vs. 29m, p = 0.007). The combined radiomics model from whole-liver signatures may effectively predict survival for HCC patients continuing TACE after TACE refractoriness. The TLrad-score and tumor burden are potential prognostic markers for TACE therapy following TACE-resistance.

Systematic review of risk factors, prognosis, and management of colorectal signet-ring cell carcinoma.

Colorectal signet-ring cell carcinoma (CSRCC) is a rare clinical entity which accounts for approximately 1% of all colorectal cancers. Although multiple studies concerning this specific topic have been published in the past decades, the pathogenesis, associated risk factors, and potential implications on treatment are still poorly understood. Besides the low incidence, historically confusing histological criteria have resulted in confusing data. Nevertheless, the rising incidence of CSRCC along with relatively young age at presentation and associated dismal prognosis, highlight the actual interest to synthesize the known literature regarding CSRCC. To provide an updated overview of risk factors, prognosis, and management of CSRCC. A literature search in the MEDLINE/PubMed database was conducted with the following search terms used: 'Signet ring cell carcinoma' and 'colorectal'. Studies in English language, published after January 1980, were included. Studies included in the qualitative synthesis were evaluated for content concerning epidemiology, risk factors, and clinical, diagnostic, histological, and molecular features, as well as metastatic pattern and therapeutic management. If possible, presented data was extracted in order to present a more detailed overview of the literature. In total, 67 articles were included for qualitative analysis, of which 54 were eligible for detailed data extraction. CSRCC has a reported incidence between 0.1%-2.4% and frequently presents with advanced disease stage at the time of diagnosis. CSRCC is associated with an impaired overall survival (5-year OS: 0%-46%) and a worse stage-corrected outcome compared to mucinous and not otherwise specified adenocarcinoma. The systematic use of exploratory laparoscopy to determine the presence of peritoneal metastases has been advised. Surgery is the mainstay of treatment, although the rates of curative resection in CSRCC (21%-82%) are lower compared to those in other histological types. In case of peritoneal metastasis, cytoreductive surgery with hyperthermic intraperitoneal chemotherapy should only be proposed in selected patients. CSRCC is a rare clinical entity most often characterized by young age and advanced disease at presentation. As such, diagnostic modalities and therapeutic approach should be tailored accordingly.

Albumin-bilirubin grade as a predictor of survival in hepatocellular carcinoma patients with thrombocytopenia.

The models for assessing liver function, mainly the Child-Pugh (CP), albuminbilirubin (ALBI), and platelet-ALBI (PALBI) classifications, have been validated for use in estimating the prognosis of hepatocellular carcinoma (HCC) patients. However, thrombocytopenia is a common finding and may influence the prognostic value of the three models in HCC. To investigate and compare the prognostic performance of the above three models in thrombocytopenic HCC patients. A total of 135 patients with thrombocytopenic HCC who underwent radical surgery were retrospectively analyzed. Preoperative scores on the CP, ALBI and PALBI classifications were estimated accordingly. Kaplan-Meier curves with log-rank tests and Cox regression models were used to explore the significant factors associated with overall survival (OS) and recurrence-free survival (RFS). The preoperative platelet counts were significantly different among the CP, ALBI and PALBI groups. After a median follow-up of 28 mo, 39.3% (53/135) of the patients experienced postoperative recurrence, and 36.3% (49/135) died. Univariate analysis suggested that α-fetoprotein levels, tumor size, vascular invasion, and ALBI grade were significant predictors of OS and RFS. According to the multivariate Cox regression model, ALBI was identified as an independent prognostic factor. However, CP and PALBI grades were not statistically significant prognostic indicators. The ALBI grade, rather than CP or PALBI grade, is a significant prognostic indicator for thrombocytopenic HCC patients.

Synergy of nodal factors in predicting recurrence after treatment of N1b papillary thyroid carcinoma.

Nodal factors are important predictors of prognosis for papillary thyroid carcinoma (PTC), but their synergy effect is not well understood. We aimed to explore their synergy effect in predicting recurrence of clinical N1b PTC. Patients who underwent surgery for cN1b PTC from 2013 to 2017 were enrolled. The association between nodal factors and recurrence was assessed using Cox proportional hazards regression models. Interaction and stratified analyses were conducted according to significant nodal factors. Of 1067 cN1b PTC patients included, all nodal factors (bilateral metastasis, largest dimension>3cm, micro and gross extranodal extension (mENE, gENE), No. of metastatic lymph nodes (MLN), lymph node yield (LNY) and ratio (LNR)) were significantly associated with all site and nodal recurrence in the univariate analysis (all P<0.05). Multivariate analyses revealed largest dimension>3cm, gENE and LNR>0.21 were associated with elevated both all site (HR [95%CI], 2.58 [1.67-4.00], 1.87[1.26-3.01], 1.68[1.11-2.42], all P<0.01) and nodal recurrences (HR[95%CI], 2.63[1.67-4.13], 1.90[1.15-3.12], 1.76[1.17-2.66], all P<0.01). LNR and gENE had interactive effect (all site recurrence: P for interaction = 0.009; nodal recurrence: P for interaction = 0.02). LNR was significantly associated with recurrence in patients without gENE (HR[95% CI], all site recurrence: 2.41[1.50-3.87]; nodal recurrence: 2.51[1.52-4.14], all P< 0.001), while when gENE appeared, LNR was no longer associated with recurrence (HR [95% CI], all site recurrence: 0.81[0.43-1.54], P=0.53; nodal recurrence: 0.85[0.43-1.67], P=0.64). Nodal factors have synergy effect in predicting recurrence in cN1b PTC patients. Increasing lymph nodes harvest may only decrease recurrence in patients without gENE, while not in gENE patients.

Identifying and Validating an Angiogenesis-related Signature for the Prognosis of Head and Neck Squamous Cell Carcinoma.

The present study aimed todevelop a prognostic model for HNSCC treatment on the basis of angiogenesis-related signatures. Head and Neck Squamous Cell Carcinoma (HNSCC) is the most frequent malignancy with poor prognostic outcomes in the head and neck. Angiogenesis plays a critical role in tumorigenesis and is expected to be an effective therapeutic target. The RNA-seq dataset TCGA-HNSCC and the hallmark gene set were used for angiogenesis-related RiskScore model construction. The RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA), and the hallmark gene set was used to measure the angiogenesis score using the GSVA R package. Then, the optimal cutoff point for prognostic classification was calculated by the survminer package, and Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify angiogenesis gene modules . Multi/univariable and Lasso Cox analyses were performed to develop the RiskScore model, and the classifier efficiency was evaluated by the Receiver Operating Characteristic curve (ROC). Furthermore, a nomogram was designed for survival probability prediction, and the immune infiltration and immunotherapy differences among different risk patients were assessed. After calculating the angiogenesis score, we found that this indicator and patients' prognosis were closely correlated, especially when patients with a high angiogenesis score had a poor prognosis. Then, WGCNA identified a blue gene module positively correlated with angiogenesis. Multivariate and Lasso Cox analysis further identified 9 risk model genes for developing a RiskScore, which was used to divide low- and high- -risk groups of patients. Those with a high risk tended to show poor prognosis, immune infiltration, and higher immune escape. Finally, a nomogram was developed to optimize the risk model, and it exhibited excellent short- and long-term survival prediction performance. We constructed a reliable RiskScore model for the prognostic prediction of HNSCC patients, contributing to precise therapeutic intervention of the cancer.

Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging parameters and serum tumor markers in rectal carcinoma prognosis.

Rectal carcinoma (RC), one of the most common malignancies globally, presents an increasing incidence and mortality year by year, especially among young people, which seriously affects the prognosis and quality of life of patients. At present, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and serum carbohydrate antigen 19-9 (CA19-9) and CA125 Levels have been used in clinical practice to evaluate the T stage and differentiation of RC. However, the accuracy of these evaluation modalities still needs further research. This study explores the application and value of these methods in evaluating the T stage and differentiation degree of RC. To analyze the diagnostic performance of DCE-MRI parameters combined with serum tumor markers (TMs) in assessing pathological processes and prognosis of RC patients. A retrospective analysis was performed on 104 RC patients treated at Yantai Yuhuangding Hospital from May 2018 to January 2022. Patients were categorized into stages T1, T2, T3, and T4, depending on their T stage and differentiation degree. In addition, they were assigned to low (L group) and moderate-high differentiation (M + H group) groups based on their differentiation degree. The levels of DCE-MRI parameters and serum CA19-9 and CA125 in different groups of patients were compared. In addition, the value of DCE-MRI parameters [volume transfer constant (Ktrans), rate constant (Kep), and extravascular extracellular volume fraction (Ve) in assessing the differentiation and T staging of RC patients was discussed. Furthermore, the usefulness of DCE-MRI parameters combined with serum CA19-9 and CA125 Levels in the evaluation of RC differentiation and T staging was analyzed. Ktrans, Ve, CA19-9 and CA125 were higher in the high-stage group and L group than in the low-stage group and M + H Group, respectively (P < 0.05). The areas under the curve (AUCs) of the Ktran and Ve parameters were 0.638 and 0.694 in the diagnosis of high and low stages, respectively, and 0.672 and 0.725 in diagnosing moderate-high and low differentiation, respectively. The AUC of DCE-MRI parameters (Ktrans + Ve) in the diagnosis of high and low stages was 0.742, and the AUC in diagnosing moderate-high and low differentiation was 0.769. The AUCs of CA19-9 and CA-125 were 0.773 and 0.802 in the diagnosis of high and low stages, respectively, and 0.834 and 0.796 in diagnosing moderate-high and low differentiation, respectively. Then, we combined DCE-MRI (Ktrans + Ve) parameters with CA19-9 and CA-125 and found that the AUC of DCE-MRI parameters plus serum TMs was 0.836 in the diagnosis of high and low stages and 0.946 in the diagnosis of moderate-high and low differentiation. According to the Delong test, the AUC of DCE-MRI parameters plus serum TMs increased significantly compared with serum TMs alone in the diagnosis of T stage and differentiation degree (P < 0.001). The levels of the DCE-MRI parameters Ktrans and Ve and the serum TMs CA19-9 and CA125 all increase with increasing T stage and decreasing differentiation degree of RC and can be used as indices to evaluate the differentiation degree of RC in clinical practice. Moreover, the combined evaluation of the above indices has a better effect and more obvious clinical value, providing important guiding importance for clinical condition judgment and treatment selection.

Dickkopf-related protein 1 as a biomarker of local immune status and worse prognosis of Oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is an infiltrative malignancy characterized by a significantly elevated recurrence rate. Dickkopf-related protein 1 (DKK1), which plays an oncogene role in many cancers, acts as an inhibitor of the Wingless protein (Wnt) signaling pathway. Currently, there is a lack of consensus regarding the role of DKK1 in OSCC or its clinical significance. To examine the role and effect of DKK1 in OSCC. The identification of differentially expressed genes (DEGs) in OSCC was conducted by utilizing databases such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A comprehensive analysis of gene expression profile interactions (GEPIA) and Kaplan-Meier curve were conducted to investigate the associations among DEGs, patient survival and prognosis in individuals with OSCC. The biological function of DKK1 in OSCC was investigated by using molecular biology approaches. The expression of DKK1 was found to be upregulated in OSCC tissues at various stages. High levels of DKK1 expression exhibited a positive correlation with the overall survival (OS) and progression-free survival (PFS) rates among OSCC patients. DKK1 knockdown suppressed the proliferation and induced apoptotic response in OSCC cells. Moreover, DKK1 exerted a positive regulatory effect on HMGA2 expression, thereby modulating cell growth and apoptosis in OSCC. The expression of DKK1 was found to be positively correlated with the infiltration of immune cells in patients with OSCC. Additionally, higher levels of CD4 + T cells were associated with improved 5-year survival rates. DKK1 is a prognostic biomarker for patients with OSCC.

Identification and validation of a prognostic anoikis-related gene signature in papillary thyroid carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid carcinoma (PTC) prognosis may be deteriorated due to the metastases, and anoikis palys an essential role in the tumor metastasis. However, the potential effect of anoikis-related genes on the prognosis of PTC was unclear. The mRNA and clinical information were obtained from the cancer genome atlas database. Hub genes were identified and risk model was constructed using Cox regression analysis. Kaplan-Meier (K-M) curve was applied for the survival analysis. Immune infiltration and immune therapy response were calculated using CIBERSORT and TIDE. The identification of cell types and cell interaction was performed by Seurat, SingleR and CellChat packages. GO, KEGG, and GSVA were applied for the enrichment analysis. Protein-protein interaction network was constructed in STRING and Cytoscape. Drug sensitivity was assessed in GSCA. Based on bulk RNA data, we identified 4 anoikis-related risk signatures, which were oncogenes, and constructed a risk model. The enrichment analysis found high risk group was enriched in some immune-related pathways. High risk group had higher infiltration of Tregs, higher TIDE score and lower levels of monocytes and CD8 T cells. Based on scRNA data, we found that 4 hub genes were mainly expressed in monocytes and macrophages, and they interacted with T cells. Hub genes were significantly related to immune escape-related genes. Drug sensitivity analysis suggested that cyclin dependent kinase inhibitor 2A may be a better chemotherapy target. We constructed a risk model which could effectively and steadily predict the prognosis of PTC. We inferred that the immune escape may be involved in the development of PTC.

Retinol-binding protein 4 as a promising serum biomarker for the diagnosis and prognosis of hepatocellular Carcinoma

BackgroundThe prognosis of hepatocellular carcinoma (HCC) is universally poor. Early diagnosis plays a pivotal role in determining the outcome of HCC. MethodsWe employed a comparative proteomics approach to identify potential biomarkers and validated the application of retinol-binding protein 4 (RBP4) as a biomarker for HCC. RBP4 protein expression was examined in liver tissues from 80 HCC patients through immunohistochemical analysis. Serum RBP4 concentrations were measured by ELISA in a cohort comprising 290 HCC patients, matched 202 chronic hepatitis B patients and 269 healthy controls. Survival data were collected from HCC patients. The diagnostic and prognostic values of RBP4 were evaluated using receiver operating curve (ROC) analysis. ResultsThe validation results demonstrated a significant reduction in RBP4 levels in both liver tissues and serum samples from HCC patients. ROC analysis of the diagnostic value of RBP4 revealed an AUC of 0.879 (95 % CI: 0.854∼0.903) for HCC. When combined with AFP, the AUC increased to 0.919, with a sensitivity of 87.9 % and specificity of 80 %. Survival analysis revealed significantly reduced overall survival time in individuals with low-expression of RBP4 compared to those with high-expression. The joint prognostic model exhibited an AUC of 0.926 (95 % CI: 0.888∼0.964), which was significantly higher than that of AFP alone (AUC=0.809; P <0.0001). ConclusionsRBP4 shows a great potential as a biomarker with appreciable diagnostic value, complementing the AFP in HCC diagnosis. Additionally, it holds promise as a prognostic biomarker that, when integrated into a combined prognostic model, could greatly improve HCC prognosis efficiency.

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20%-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. To construct and evaluate a preoperative diagnostic method to predict occult lymph node metastasis (OCLNM) in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA) and survival analysis. Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927) and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1 and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. The proposed MRI-based Resnet50 deep learning model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

CSChighE-cadherinlow immunohistochemistry panel predicts poor prognosis in oral squamous cell carcinoma

Identifying marker combinations for robust prognostic validation in primary tumour compartments remains challenging. We aimed to assess the prognostic significance of CSC markers (ALDH1, CD44, p75NTR, BMI-1) and E-cadherin biomarkers in OSCC. We analysed 94 primary OSCC and 67 metastatic lymph node samples, including central and invasive tumour fronts (ITF), along with clinicopathological data. We observed an increase in ALDH1+/CD44+/BMI-1- tumour cells in metastatic lesions compared to primary tumours. Multivariate analysis highlighted that elevated p75NTR levels (at ITF) and reduced E-cadherin expression (at the tumour centre) independently predicted metastasis, whilst ALDH1high exhibited independent predictive lower survival at the ITF, surpassing the efficacy of traditional tumour staging. Then, specifically at the ITF, profiles characterized by CSChighE-cadherinlow (ALDH1highp75NTRhighE-cadherinlow) and CSCintermediateE-cadherinlow (ALDH1 or p75NTRhighE-cadherinlow) were significantly associated with worsened overall survival and increased likelihood of metastasis in OSCC patients. In summary, our study revealed diverse tumour cell profiles in OSCC tissues, with varying CSC and E-cadherin marker patterns across primary tumours and metastatic sites. Given the pivotal role of reduced survival rates as an indicator of unfavourable prognosis, the immunohistochemistry profile identified as CSChighE-cadherinlow at the ITF of primary tumours, emerges as a preferred prognostic marker closely linked to adverse outcomes in OSCC.

Exploring genes within the glutathione peroxidase family as potential predictors of prognosis in papillary renal cell carcinoma

Abstract Objectives This research aims to explore the relationship between glutathione peroxidase (GPX) expression variations in papillary renal cell carcinoma (pRCC) and patient survival, while also developing and evaluating a customized survival prediction model based on GPX. Methods The transcriptomic dataset, including clinical parameters and GPX expression levels, is sourced from The Cancer Genome Atlas (TCGA) database, comprising 290 individuals diagnosed with pRCC. We utilized a univariate Cox regression model to select differentially expressed genes. Subsequently, we calculated risk scores through the least absolute shrinkage and selection operator (LASSO) regression. Based on the median risk score, patients were categorized into high and low-risk groups, establishing a prognostic risk model. Following this, the relationship between the risk model and the survival of pRCC patients was revealed through Kaplan–Meier survival curve analysis. The sensitivity and specificity of the predictive model were evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, chemotherapy drug sensitivity analysis was conducted on patients in the high and low-risk groups. Results A risk-scoring model was built by selecting GPX7 and GPX8. Compared to the low-risk group, individuals in the high-risk category showed significantly reduced overall survival rates (p=0.018). Additionally, validation results demonstrated the model’s good predictive accuracy. Conclusions The risk-scoring model constructed based on GPX family genes provides an innovative biomarker for forecasting the prognosis of pRCC and serves as a reference for individualized therapy in pRCC.

Glycometabolism and lipid metabolism related genes predict the prognosis of endometrial carcinoma and their effects on tumor cells

BackgroundGlycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC).MethodsData on gene expression and clinical details were obtained from publicly accessible databases. GLRGs were obtained from the Genecards database. Through nonnegative matrix factorization (NMF) clustering, molecular groupings with various GLRG expression patterns were identified. LASSO Cox regression analysis was employed to create a prognostic model. Use rich algorithms such as GSEA, GSVA, xCELL ssGSEA, EPIC,CIBERSORT, MCPcounter, ESTIMATE, TIMER, TIDE, and Oncoppredict to analyze functional pathway characteristics of the forecast signal, immune status, anti-tumor therapy, etc. The expression was assessed using Western blot and quantitative real-time PCR techniques. A total of 113 algorithm combinations were combined to screen out the most significant GLRGs in the signature for in vitro experimental verification, such as colony formation, EdU cell proliferation, wound healing, apoptosis, and Transwell assays.ResultsA total of 714 GLRGs were found, and 227 of them were identified as prognostic-related genes. And ten GLRGs (AUP1, ESR1, ERLIN2, ASS1, OGDH, BCKDHB, SLC16A1, HK2, LPCAT1 and PGR-AS1) were identified to construct the prognostic model of patients with EC. Based on GLRGs, the risk model’s prognosis and independent prognostic value were established. The signature of GLRGs exhibited a robust correlation with the infiltration of immune cells and the sensitivity to drugs. In cytological experiments, we selected HK2 as candidate gene to verify its value in the occurrence and development of EC. Western blot and qRT-PCR revealed that HK2 was substantially expressed in EC cells. According to in vitro experiments, HK2 knockdown can increase EC cell apoptosis while suppressing EC cell migration, invasion, and proliferation.ConclusionThe GLRGs signature constructed in this study demonstrated significant prognostic value for patients with endometrial carcinoma, thereby providing valuable guidance for treatment decisions.

Construction and validation of a mutation-related model in papillary renal cell carcinoma and associated immune infiltration.

To improve the clinical evaluation of the prognosis of papillary renal cell carcinoma (PRCC), we screened a model to predict the survival of patients with mutations in related genes. We downloaded RNA sequencing information from all patients with PRCC in TCGA. We first analyzed the differences in genes and the enrichment of these differences. Then, by selecting mutant genes, constructing a protein-protein interaction network, lasso regression, and multivariable Cox regression, a prognosis model was constructed. Additionally, the model was validated using external data sets. We analyzed the immune infiltration of PRCC and the correlation between the model and popular targets. Finally, we performed tissue microarray analysis and immunohistochemistry to verify the expression levels of the three genes. We constructed a three-gene (NEK2, CENPA, and GINS2) model. The verification results indicated that the model had a good prediction effect. We also developed a visual nomogram. Enrichment analysis revealed the major pathways involved in muscle system processes. Immunoassays showed that the expression level of CENPA was positively correlated with PD-1 and CTLA4 expression levels. Immunohistochemical and tissue microarray results showed that these three genes were highly expressed in PRCC, which was consistent with the predicted results in the database. We constructed and verified a three-gene model to predict the patient survival. The results show that the model has a good prediction effect.

Efficacy and safety of hepatic arterial infusion chemotherapy combined with lenvatinib and PD-1 inhibitors for advanced hepatocellular carcinoma with macrovascular invasion

Background and aimsThe prognosis of hepatocellular carcinoma (HCC) with macrovascular invasion(MaVI)is poor, and the treatment is limited. This study aims to explore the efficacy and safety of hepatic arterial infusion chemotherapy (HAIC), combined with lenvatinib and programmed cell death-1(PD-1) inhibitor in the first-line treatment of HCC with MaVI.MethodsFrom July 2020 to February 2022, we retrospectively analyzed consecutive patients with HCC with MaVI who received hepatic arterial infusion FOLFOX(oxaliplatin, 5-fluorouracil, and leucovorin)combined with lenvatinib and PD-1 inhibitor. The efficacy was evaluated by RECIST 1.1. Kaplan-Meier was used to explore the overall survival and progression-free survival (PFS), and the COX regression model was used to analyze the risk factors of PFS. Adverse events (AEs) were evaluated according to CTCAE5.0.ResultsThirty-two patients with HCC complicated with MaVI were recruited from the Second Affiliated Hospital of Nanchang University. Among the patients treated with HAIC combined with lenvatinib and PD-1 inhibitor, ten patients (31.25%) got partial response, eighteen patients (56.25%) maintained stable disease and four patients (12.50%) suffered progressive disease during follow-up; and objective response rate was 31.25%, and disease control rate was 87.5%. The median PFS was 179 days. Univariate and multivariate Cox analysis showed that the extrahepatic metastases and Child-Pugh score were independent prognostic factors of PFS. Twenty-two (68.75%) patients suffered adverse reactions. The main AEs were elevated transaminase (46.87%), thrombocytopenia (40.63%), hypoalbuminemia (28.13%), nausea and vomiting (21.88%), leukopenia (18.76%), abdominal pain (15.63%), hypertension (15.63%) and fever (15.63%). There were seven cases (21.88%) that had grade 3 or above AEs; Among them, two cases with elevated transaminase (6.25%), leukopenia, thrombocytopenia, nausea and vomiting, abdominal pain, and diarrhea occurred in one case respectively. Moreover, no treatment-related death was observed.ConclusionsHepatic arterial infusion of FOLFOX combined with lenvatinib and PD-1 inhibitor as the first-line treatment for HCC complicated with MaVI is effective, and adverse reactions are tolerable.

Ribosome-binding protein-1 (RRBP1) expression in prostate carcinomas and its relationship with clinicopathological prognostic factors.

Studies in recent years have shown that ribosome-binding protein-1 (RRBP1) is expressed at high rates in many cancers and that it may be a potential prognostic biomarker. The objective of the present study is to determine the RRBP1 expression level in prostatic carcinoma and neighboring non-neoplastic prostate tissue, the relationship between its expression level with prognostic factors, and the role of RRBP1 in the development of prostate cancer. The study included 45 patients who were diagnosed with prostatic carcinoma and underwent radical prostatectomy in our center between the years 2010 and 2021. Pathology reports were reviewed. Mann-Whitney U test was used for the comparison of RRBP1 and GADPH values of the cases (control and tumoral tissue) between the primary tumor stage (pT) and Gleason score (GS) groups. Hierarchical regression analysis was used to explain the effective variables in explaining the RRBP1 value of the research cases. According to the Mann-Whitney U test, mean and median RRBP1-T values of the cases with GS ≥ 8 were detected to be statistically significantly higher than the mean and median RRBP1-T values of the cases with GS < 8. We found out that RRBP1 was expressed at higher rates in patients with high GS and advanced-stage patients. This result indicated that RRBP1 expression may be important in predicting the prognosis of prostate carcinoma.

Impact of anesthesia-related genes on prognosis and tumor microenvironment in hepatocellular carcinoma: A comprehensive analysis.

Hepatocellular carcinoma (HCC), renowned for its bleak prognosis and high recurrence rates, necessitates innovative strategies for prognosis assessment and therapeutic intervention. In this pursuit, we systematically investigated the influence of anesthesia-related genes (ANARGs) on HCC outcomes. Leveraging data from The Cancer Genome Atlas (TCGA), our study scrutinized RNA sequencing data and clinical profiles from 374 HCC patients alongside 50 non-tumor liver samples to unravel ANARG expression patterns and their clinical relevance. Employing consensus clustering, we segregated HCC samples into two distinct subtypes based on ANARG profiles, unveiling significant survival disparities between them. Further differential expression analysis pinpointed pivotal genes and pathways distinguishing these subtypes, notably implicating lipid metabolism and the MTOR signaling pathway in HCC pathogenesis. A prognostic model, comprising five key ANARGs (DAGLA, CYP26B, HAVCR, G6PD and AKR1B), exhibited robust predictive capability for patient outcomes, validated across independent patient cohorts. Furthermore, immune infiltration analysis uncovered a nuanced interplay between ANARG expression and the tumor immune microenvironment, spotlighting variations in immune cell infiltration and function across the identified HCC subtypes. This comprehensive analysis underscores not only the prognostic significance of ANARGs in HCC but also their potential to modulate the tumor microenvironment, providing novel insights for tailoring anesthetic management and therapeutic strategies in HCC care. Our findings advocate for a more integrative approach to HCC management, amalgamating molecular profiling with traditional clinical parameters to refine patient stratification and personalize treatment strategies.