A Web-based Prediction Model for Early Death in Patients With Metastatic Triple-negative Breast Cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2. This subtype of breast cancer is known for its high aggressiveness, high metastatic potential, tendency for recurrence, and poor prognosis. Patients with metastatic TNBC (mTNBC) have a poorer prognosis and a higher likelihood of early death (survival time ≤3 months). Therefore, the development of effective individualized survival prediction tools, such as prediction nomograms and web-based survival calculators, is of great importance for predicting the probability of early death in patients with metastatic TNBC. METHODS: Patients diagnosed with mTNBC in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were included in the model construction. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with early death in patients with mTNBC and predictive prognostic nomograms were constructed. The accuracy of the nomograms was verified using receiver operating characteristic curves, and GiViTi Calibration belt plots were used to evaluate the model consistency. The clinical applicability of the nomograms was evaluated using decision curve analysis. On the basis of the predictive prognostic nomograms, a network survival rate calculator was developed for individualized survival prediction in patients with mTNBC. RESULTS: A total of 2230 patients diagnosed with mTNBC were included in the Surveillance, Epidemiology, and End Results database for this study. After strict exclusion criteria, 1428 patients were found to be eligible for the study. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. Independent risk factors for mTNBC, including age, tumor size, brain metastasis, liver metastasis, surgery, and chemotherapy, were identified and integrated to construct the prediction nomogram and survival calculator. Results of receiver operating characteristic curves, calibration curves, and decision curve analysis curves from the training and validation cohort confirmed that the developed nomogram and web-based survival calculator in this study could accurately predict the probability of early death in patients with mTNBC. CONCLUSIONS: In this study, we developed a reliable prediction nomogram and web-based survival calculator for predicting the probability of early death in patients with mTNBC. These tools can assist clinical physicians in identifying high-risk patients and developing personalized treatment plans as early as possible.

Upregulated expression of long noncoding RNA SNHG15 promotes cell proliferation and invasion through regulates MMP2/MMP9 in patients with GC.

Accumulation of data indicates that misregulated long noncoding RNAs (lncRNAs) are implicated in cancer tumorigenesis and progression and might be served as diagnosis and prognosis biomarker or potential therapeutic targets. Identification of cancer-associated lncRNAs and investigation of their biological functions and molecular mechanisms are significant for understanding the development and progression of cancer. In this study, we identified a novel lncRNA SNHG15, whose expression was upregulated in tumor tissues in 106 patients with gastric cancer (GC) compared with those in the adjacent normal tissues (P < 0.001). Furthermore, increased SNHG15 expression was positively correlated with invasion depth (P < 0.001), advanced tumor node metastasis (TNM) stage (P = 0.001), and lymph node metastasis (P = 0.019). SNHG15 levels were robust in differentiating GC tissues from controls (area under the curve (AUC) = 0.722; 95 % confidence interval (CI) = 0.657-0.782, P < 0.01). Kaplan-Meier analysis demonstrated that elevated SNHG15 expression contributed to poor overall survival (P < 0.01) and disease-free survival (P < 0.01) of patients. A multivariate survival analysis also indicated that SNHG15 could be an independent prognostic marker. Furthermore, knockdown of SNHG15 expression by siRNA could inhibit cell proliferation and invasion and induce apoptosis, while ectopic expression of SNHG15 promoted cell proliferation and invasion in GC cells partly via regulating MMP2 and MMP9 protein expression. Our findings present that elevated lncRNA SNHG15 could be identified as a poor prognostic biomarker in GC and regulate cell invasion.

Preoperative elevation of serum C-reactive protein as an indicator of poor prognosis for early-stage esophageal squamous cell carcinoma.

Preoperative elevation of serum C-reactive protein (CRP) is reportedly associated with poor prognosis in several types of cancer. This study investigated the role of serum CRP as a prognostic factor in early-stage esophageal squamous cell carcinoma (ESCC). The preoperative serum CRP levels were measured in 156 newly diagnosed pT1-2N0M0 patients using an enzyme-linked immunosorbent assay. Correlations between serum CRP levels and other clinical parameters were analyzed. Multivariate analyses were performed to find prognostic markers using Cox's proportional hazards model. CRP concentrations were within the normal range in 117 (75%) individuals, but were elevated in 39 (25%) patients. Serum CRP levels were significantly correlated with the tumor length (p = 0.032), depth (T classification, p = 0.0157), or histologic grade (p = 0.034). The overall 5-year survival rates were 76.3% and 50.2% in the low- and high-CRP groups, respectively (p = 0.005). By multivariate analyses, the elevated serum CRP level was found to be an independent prognostic factor for poor survival (hazard ratio = 2.131; p = 0.007), regardless of tumor classification or other prognostic factors. In conclusion, preoperative, high serum CRP is an independent determinant of poor prognosis in early-stage ESCC.