Background: To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer.Methods: We used a brand-new immuno-inflammatory index—pan-immune-inflammation value (PIV)—to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated.Results: A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715–0.802); the calibration plot showed good calibration.Conclusions: We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

Thymosin beta 10 (TMSB10) has been demonstrated to be involved in the malignant process of many cancers. The purpose of this study was to determine the biological roles and clinical significance of TMSB10 in breast cancer and to identify whether TMSB10 might be used as a serum marker for the diagnosis of breast cancer. TMSB10 expression was evaluated by immunohistochemical analysis (IHC) of 253 breast tumors and ELISA of serum from 80 patients with breast cancer. Statistical analysis was performed to explore the correlation between TMSB10 expression and clinicopathological features in breast cancer. Univariate and multivariate Cox regression analysis were performed to examine the association between TMSB10 expression and overall survival and metastatic status. In vitro and in vivo assays were performed to assess the biological roles of TMSB10 in breast cancer. Western blotting and luciferase assays were examined to identify the underlying pathway involved in the tumor-promoting role of TMSB10. We found TMSB10 was upregulated in breast cancer cells and tissues. Univariate and multivariate analysis demonstrated that high TMSB10 expression significantly correlated with clinicopathological features, poor prognosis and distant metastases in patients with breast cancer. Overexpression of TMSB10 promotes, while silencing of TMSB10 inhibits, proliferation, invasion and migration of breast cancer cells in vitro and in vivo. Our results further reveal that TMSB10 promotes the proliferation, invasion and migration of breast cancer cells via AKT/FOXO signaling, which is antagonized by the AKT kinase inhibitor perifosine. Importantly, the expression of TMSB10 is significantly elevated in the serum of patients with breast cancer and is positively associated with clinical stages of breast cancer. TMSB10 may hold promise as a minimally invasive serum cancer biomarker for the diagnosis of breast cancer and a potential therapeutic target which will facilitate the development of a novel therapeutic strategy against breast cancer.

Purpose: Whether or not skeletal muscle mass (SMM) depletion, known as sarcopenia, has significant negative effects on the prognosis of patients with head and neck cancer (HNC) is both new and controversial. In this meta-analysis, we aimed to determine the prognostic significance of sarcopenia in HNC. Methods: We searched PubMed, the Cochrane Library, Embase, and Web of Science, which contain trial registries and meeting proceedings, to identify related published or unpublished studies. We used the Newcastle–Ottawa Scale (NOS) to appraise the risk of bias of the included retrospective studies. Pooled hazard ratios (HR) and the I² statistic were estimated for the impact of sarcopenia on overall survival (OS) and relapse-free survival (RFS). Results: We analyzed data from 11 studies involving 2,483 patients (39.4% on average of whom had sarcopenia). Based on the univariate analysis data, the sarcopenia group had significantly poorer OS compared to the non-sarcopenia group [HR = 1.97, 95% confidence interval (CI): 1.71–2.26, I² = 0%]. In the cutoff value subgroup, group 1, defined as skeletal muscle index (SMI) of 38.5 cm²/m² for women and 52.4 cm²/m² for men (HR = 2.41, 95% CI: 1.72–3.38, I² = 0%), had much poorer OS. In the race subgroup, the results were consistent between the Asia (HR = 2.11, 95% CI: 1.59–2.81) and non-Asia group (HR = 1.92, 95% CI: 1.64–2.25). The sarcopenia group also had significantly poorer RFS (HR = 1.74, 95% CI: 1.43–2.12, I² = 0%). Conclusions: Presence of pre-treatment sarcopenia has a significant negative impact on OS and RFS in HNC compared with its absence. Further well-conducted studies with detailed stratification are needed to complement our findings.

Background: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning. Methods: An endoscopic images‐based nasopharyngeal malignancy detection model (eNPM‐DM) consisting of a fully convolutional network based on the inception architecture was developed and fine‐tuned using separate training and validation sets for both classification and segmentation. Briefly, a total of 28,966 qualified images were collected. Among these images, 27,536 biopsy‐proven images from 7951 individuals obtained from January 1st, 2008, to December 31st, 2016, were split into the training, validation and test sets at a ratio of 7:1:2 using simple randomization. Additionally, 1430 images obtained from January 1st, 2017, to March 31st, 2017, were used as a prospective test set to compare the performance of the established model against oncologist evaluation. The dice similarity coefficient (DSC) was used to evaluate the efficiency of eNPM‐DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images, by comparing automatic segmentation with manual segmentation performed by the experts. Results: All images were histopathologically confirmed, and included 5713 (19.7%) normal control, 19,107 (66.0%) nasopharyngeal carcinoma (NPC), 335 (1.2%) NPC and 3811 (13.2%) benign diseases. The eNPM‐DM attained an overall accuracy of 88.7% (95% confidence interval (CI) 87.8%–89.5%) in detecting malignancies in the test set. In the prospective comparison phase, eNPM‐DM outperformed the experts: the overall accuracy was 88.0% (95% CI 86.1%–89.6%) vs. 80.5% (95% CI 77.0%–84.0%). The eNPM‐DM required less time (40 s vs. 110.0 ± 5.8 min) and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background, with an average DSC of 0.78 ± 0.24 and 0.75 ± 0.26 in the test and prospective test sets, respectively. Conclusions: The eNPM‐DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant, and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.

Background: Oct4 and Sox2 are two major transcription factors related to the stem cell self-renewal and differentiation. The aim of this study was to examine the association between Oct4 and Sox2 expression levels with both the clinicopathological characteristics and prognoses of patients with hypopharyngeal squamous cell carcinoma. Method: Tumor tissue samples from 85 patients with hypopharyngeal squamous cell carcinoma were collected, and the clinical follow-up data of these patients were recorded, and expression status of Oct4 and Sox2 were examined in these tissue samples by immunohistochemistry (IHC). Results: Oct4 expression was found to be an independent predictive factor for overall survival (p = 0.004) in patients with hypopharyngeal squamous cell carcinoma and was independently related to loco-regional control (p = 0.001). Although Sox2 expression status showed no significant association with overall survival (p = 0.166), disease-free survival (p = 0.680) or loco-regional control (p = 0.383), when using a subgroup analysis, the subgroup with both high Oct4 and Sox2 expression had the best prognosis (p = 0.000). Sox2 expression could be a potential prognostic predictor for patients with hypopharyngeal squamous cell carcinoma. Simultaneous analyses of Oct4 and Sox2 expression could be more effective in evaluating the prognoses of patients with hypopharyngeal squamous cell carcinoma. Conclusion: Oct4 expression is an independent predictive factor for patients with hypopharyngeal squamous cell carcinoma, suggesting that Oct4 expression may be a useful indicator for predicting the prognosis of hypopharyngeal squamous cell carcinoma.