Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302–0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299–0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.     

Phyllodes tumour: cytologic and histologic presentation of 22 cases, and immunohistochemical demonstration of p53

A retrospective study of 22 cases of phyllodes tumour (PT) was undertaken to evaluate the potential value of fine needle aspiration (FNA) cytology in the diagnosis of benign and borderline PT. Histological material was available from 12 patients with typical benign PT (group 1), six patients with less typical changes (group 2) and four cases of borderline PT (group 3). Cytological presentation of PT in these cases was similar to that described by other cytologists, although abundant cellular material was obtained in only eight FNAs, naked nuclei were present in nine cases only, and atypical or suspicious cytological features were found in seven cases. Comparative analysis of p53 was made in nine patients with PT, five cases with other benign breast lesions and five with malignant lesions. p53 reaction was positive in five of nine patients with PT (all cases from groups 2 and 3), compared with two of five cases of carcinoma. p53 was negative in all patients with PT from group 1 and the five other benign cases. We suggest that cytopathologists should be careful when a myxoid stromal component is present in cytological smears.     

Identification of immune-enhanced molecular subtype associated with BRCA1 mutations,immune checkpoints and clinical outcome in ovarian carcinoma

Ovarian carcinoma has the highest mortality among the malignant tumours in gynaecology, and new treatment strategies are urgently needed to improve the clinical status of ovarian carcinoma patients. The Cancer Genome Atlas (TCGA) cohort were performed to explore the immune function of the internal environment of tumours and its clinical correlation with ovarian carcinoma. Finally, four molecular subtypes were obtained based on the global immune-related genes. The correlation analysis and clinical characteristics showed that four subtypes were all significantly related to clinical stage; the immune scoring results indicated that most immune signatures were upregulated in C3 subtype, and the majority of tumour-infiltrating immune cells were upregulated in both C3 and C4 subtypes. Compared with other subtypes, C3 subtype had a higher BRCA1 mutation, higher expression of immune checkpoints, and optimal survival prognosis. These findings of the immunological microenvironment in tumours may provide new ideas for developing immunotherapeutic strategies for ovarian carcinoma.     

Identification of cancer hallmark‐associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits (“hallmarks”) that govern the transformation of normal cells into cancer cells. Long non‐coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark‐associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC‐specific cancer hallmark‐associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co‐expression and co‐occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self‐sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark‐associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark‐associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA‐based targeted therapy in OSCC.     

TGFβ2 is a prognostic‐related biomarker and correlated with immune infiltrates in gastric cancer

TGFβ2 is an essential regulator of immune cell functionality, but the mechanisms whereby it drives immune infiltration in gastric cancer remain uncertain. The Oncomine and Tumor Immunoassay Resource (TIMER) databases were used for assessing the expression of TGFβ2, after which TIMER was used to explore the relationship between TGFβ2 and tumour immune infiltration. Finally, we assessed how TGFβ2 expression correlated with the expression of a set of marker genes associated with immune infiltration using TIMER and GEPIA. We determined TGFβ2 expression to be significantly correlated with outcome in multiple types of cancer in the Cancer Genome Atlas (TCGA), with the effect being particularly pronounced in gastric cancer. Furthermore, elevated TGFβ2 expression was found to be significantly correlated with gastric cancer N staging, and with the expression of a variety of immune markers associated with particular immune cell subsets. These results indicate that TGFΒ2 is associated with patient outcome and tumour immune cell infiltration in multiple cancer types. This suggests that TGFβ2 is a key factor which governs immune cell recruitment to gastric cancer tumours, potentially playing a vital role in governing immune cell infiltration and thus representing a valuable prognostic biomarker in gastric cancer patients.     

A stroma-related lncRNA panel for predicting recurrence and adjuvant chemotherapy benefit in patients with early-stage colon cancer

The heterogeneity in prognoses and chemotherapeutic responses of colon cancer patients with similar clinical features emphasized the necessity for new biomarkers that help to improve the survival prediction and tailor therapies more rationally and precisely. In the present study, we established a s troma-related l ncRNA s ignature (SLS) based on 52 lncRNAs to comprehensively predict clinical outcome. The SLS model could not only distinguish patients with different recurrence and mortality risks through univariate analysis, but also served as an independent factor for relapse-free and overall survival. Compared with the conventionally used TNM stage system, the SLS model clearly possessed higher predictive accuracy. Moreover, the SLS model also effectively screened chemotherapy-responsive patients, as only patients in the low-SLS group could benefit from adjuvant chemotherapy. The following cell infiltration and competing endogenous RNA (ceRNA) network functional analyses further confirmed the association between the SLS model and stromal activation-related biological processes. Additionally, this study also identified three phenotypically distinct colon cancer subtypes that varied in clinical outcome and chemotherapy benefits. In conclusion, our SLS model may be a significant determinant of survival and chemotherapeutic decision-making in colon cancer and may have a strong clinical transformation value.     

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co‐expression network analysis

The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan‐cancer validation and time‐dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed. Eight genes were eventually screened out as progression‐related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E‐MTAB‐4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time‐dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan‐cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision‐making.     

E-cadherin deregulation in breast cancer

E-cadherin protein (CDH1 gene) integrity is fundamental to the process of epithelial polarization and differentiation. Deregulation of the E-cadherin function plays a crucial role in breast cancer metastases, with worse prognosis and shorter overall survival. In this narrative review, we describe the inactivating mechanisms underlying CDH1 gene activity and its possible translation to clinical practice as a prognostic biomarker and as a potential targeted therapy.