BRCA1/2 mutation carriers who have been treated with PS have a substantially reduced breast cancer incidence and mortality. Clin Cancer Res; 22(15); 3971-81. ©2016 AACR.

Purpose. About one-third of the world's total annual new cervical cancer cases are found in the People's Republic of China. We investigate the prevalence and clinical characteristics of cervical cancer cases in the People's Republic of China over the past decade. Method. A total of 10,012 hospitalized patients with cervical cancer from regions nationwide were enrolled from 2000 to 2009. Demographic and clinical characteristics, therapeutic strategies, and outcomes were analyzed. Results. The mean age at diagnosis of all cervical cancer patients was 44.7 Ϯ 9.5 years, which is 5-10 years younger than mean ages reported before 2000 in the People's Republic of China. The age distribution showed 16.0% of patients were Յ35 years old, 41.7% were 35-45 years old, and 41.7% were Ͼ45 years old. Early stage diagnoses were most prevalent: 57.3% were stage I, 33.9% were stage II, and 4.3% were stage III or IV. Most patients (83.9%) were treated with surgery, and only 9.5% had radiotherapy alone. Among 8,405 patients treated with surgery, 68.6% received adjuvant treatments, including chemotherapy (20.9%), radiotherapy (26.0%), and chemoradiotherapy (21.9%). Among stage IA patients, 16.0% were treated with corpus uteri preservation. The proportion of ovarian preservation was 42.0%. Conclusions. Cervical cancer cases in the People's Republic of China show increasing prevalence in young patients and at early stages. In the past 10 years, surgery has become the dominant treatment and is increasingly combined with adjuvant chemotherapy for patients with stages I and II. Conservative surgical approaches are reasonable options for genital organ preservation in selected patients. The Oncologist 2013;18:1101-1107 Implications for Practice: Cervical cancer morbidity and mortality have decreased steadily in recent decades; however, cervical cancer is still the third most common malignant disease in women worldwide, with an estimated 500,000 new cases diagnosed annually and more than 268,000 deaths per year. According to World Health Organization statistical data, about 75,000 of the annual new cervical cancer cases were estimated to be in the People's Republic of China, where cervical cancer was responsible for 33,000 deaths in 2008. Demographic and clinical characteristics, patterns of care, and long-term survival rates of patients with cervical cancer have been unclear because of limited published data and the absence of a Chinese cervical cancer database with considerable clinical parameters. A large-scale, multicenter database of cervical cancer cases was established to analyze the trends and clinical features of cervical cancer in the People's Republic of China. The present study was proposed to develop helpful suggestions for selecting suitable treatment strategies.

Background: Papillary thyroid carcinoma is a type of indolent tumor with a dramatically increasing incidence rate and stably high survival rate. Reducing the overdiagnosis and overtreatment of papillary thyroid carcinoma is clinically emergent and important. A radiomics model is proposed in this article to predict lymph node metastasis, the most important risk factor of papillary thyroid carcinoma, based on noninvasive routine preoperative ultrasound images. Methods: Four hundred fifty ultrasound manually segmented images of patients with papillary thyroid carcinoma with lymph node status obtained from pathology report were enrolled in our retrospective study. A radiomics evaluation of 614 high-throughput features were calculated, including size, shape, margin, boundary, orientation, position, echo pattern, posterior acoustic pattern, and calcification features. Then, combined feature selection strategy was used to select features with the greatest ability to discriminate lymph node status. A support vector machine classifier was employed to build and validate the prediction model. Another independent testing cohort was used to further evaluate the performance of the radiomics model. Results: Among 614 radiomics features, 50 selected features most reflecting echo pattern, posterior acoustic pattern, and calcification showed the superior lymph node status distinguishable performance with area under the receiver operating characteristic curve of 0.753, 0.740, and 0.743 separately when using each type of features predicting the lymph node status. The results of model based on all 50 final features predicting the lymph node status shown an area under the receiver operating characteristic curve of 0.782, and accuracy of 0.712. In the independent testing cohort, the proposed approach showed similar results, with area under the receiver operating characteristic curve of 0.727 and accuracy of 0.710. Conclusion: Papillary thyroid carcinoma with lymph node metastasis usually shows a complex echo pattern, posterior region homogeneity, and macrocalcification or multiple calcification. The radiomics model proposed in this article is a promising method for assessing the risk of papillary thyroid carcinoma metastasis noninvasively.

Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction. In the experiments of cross-validation and independent testing of the main cohort according to diagnostic time, machine, and operator, the TLR achieves an average area under the curve (AUC) of 0.90. In the other two independent cohorts, TLR also achieves 0.93 AUC, and this performance is statistically better than the other three methods according to Delong test. Decision curve analysis also proves that the TLR model brings more benefit to PTC patients than other methods.

This study aimed to establish and validate an ultrasound radiomics nomogram for the preoperative prediction of central lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC). Patients and Methods: The prediction model was developed in 609 patients with clinicopathologically confirmed unifocal PTC who received ultrasonography between Jan 2018 and June 2018. Radiomic features were extracted after the ultrasonography of PTC. Lasso regression model was used for data dimensionality reduction, feature selection, and radiomics signature building. The predicting model was established based on the multivariable logistic regression analysis in which the radiomics signature, ultrasonography-reported LN status, and independent clinicopathologic risk factors were incorporated, and finally a radiomics nomogram was established. The performance of the nomogram was assessed with respect to the discrimination and consistence. An independent validation was performed in 326 consecutive patients from July 2018 to Sep 2018. Results: The radiomics signature consisted of 23 selected features and was significantly associated with LN status in both primary and validation cohorts. The independent predictors in the radiomics nomogram included the radiomics signature, age, TG level, TPOAB level, and ultrasonography-reported LN status. The model showed good discrimination and consistence in both cohorts: C-index of 0.816 (95% CI, 0.808-0.824) in the primary cohort and 0.858 (95% CI, 0.849-0.867) in the validation cohort. The area under receiver operating curve was 0.858. In the validation cohort, the accuracy, sensitivity, specificity and AUC of this model were 0.812, 0.816, 0.810, and 0.858 (95% CI, 0.785-0.930), respectively. Decision curve analysis indicated the radiomics nomogram was clinically useful. Conclusion: This study presents a convenient, clinically useful ultrasound radiomics nomogram that can be used for the pre-operative individualized prediction of central LN metastasis in patients with PTC.

There is a scarcity of reports addressing patients with multiple primary malignancies (MPM), especially for Chinese cses. The aim of this study was to present a detailed analysis of Chinese patients presenting with at least two primary malignancies. Particularly, the clinical characteristics and survival between synchronous and metachronous MPM were compared. Out of 6,545 cases, 72 patients (1.1%) including 39 males (54.2%) and 33 females (45.8%) were diagnosed as MPM, giving a male: female sex ratio of 1.2:1. Of these, there were 16 (22.2%) cases of synchronous MPM (7 males, 9 females), 55(76.4%) metachronous (31 males, 24 females), and 1 "mixed form". For first tumor diagnosis time, synchronous MPM patients generally presented later than the metachronous cases. The top three sites for malignancies with metachronous MPM were colorectum, head and neck, and lung, while for synchronous they were lung, colorectum and breast. Among MPM patients, the median survival time was 15.7 years and the 5-year survival was 56%, and there was statistical difference in MPM categories (P < 0.05). The median survival time was 17.3 years and 3.8 years for metachronous and synchronous MPM patients, respectively. In comparison with synchronous MPM patients, those metachronous had a longer survival. This studies increase understanding of the clinical features of Chinese MPM patients and suggest that those presenting with metachronous cancers have a higher incidence and a better prognosis.

Metformin is one of the extensively and most commonly used oral antihyperglycemic agents, but it has been shown to exert antineoplastic effects in many cancer cells. Recent studies have confirmed that metformin has an antitumor effect on hepatocellular carcinoma (HCC). However, the molecular mechanism underlying this effect needs to be further studied.Materials and methodsCDK1 and miR-378 expression was analyzed by western blotting and real-time PCR assays. We confirmed the association between miR-378 and CDK1 by dual luciferase reporter assay. The role of the miR-378/CDK1 pathway in proliferation, cell cycle and apoptosis was examined in vitro. The effect of miR-378 on HCC tumor growth was evaluated in nude xenograft mouse model.ResultsOur study found that metformin significantly inhibited the HCC cell proliferation via inducing G2/M arrest. At the same time, metformin efficiently decreased CDK1 expression and elevated miR-378 level. Moreover, the upregulation of miR-378 also repressed HCC cell proliferation by causing G2/M arrest and inhibited tumor growth. Additionally, we demonstrated that miR-378 directly targeted CDK1 3′UTR and downregulated CDK1 mRNA and protein levels. Furthermore, metformin treatment could not decrease CDK1 expression, suppress HCC cell proliferation, and induce G2/M cell cycle arrest.DiscussionMetformin-suppressed HCC cell proliferation was dependent on the inhibitory effect of miR-378 on CDK1 expression. Taken together, we concluded that metformin inhibited HCC cell proliferation via modulating miR-378/CDK1 axis.ConclusionCollectively, the current results provide the first evidence, to our knowledge, that miR-378/CDK1 axis is involved in metformin modulating the proliferation of HCC cells, which suggests a novel molecular mechanism underlying the thera peutic effect of metformin on HCC.

Rationale and Objectives: Accurate preoperative identification of lateral cervical lymph node metastasis (LNM) is important for decisionmaking and clinical management of patients with papillary thyroid carcinoma (PTC). The aim of this study was to develop an ultrasound (US)-based radiomic nomogram to preoperatively predict the lateral LNM in PTC patients. Methods: In this retrospective study, a total of 886 patients were enrolled and randomly divided into 2 groups. Radiomic features were extracted from the preoperative US images. A radiomic signature was constructed using the least absolute shrinkage and selection operator algorithm in the training set. Multivariate logistic regression was performed to develop the radiomic nomogram, which incorporating the radiomic signature and the selected clinical characteristics. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness in both the training and validation sets. Results: The radiomic signature was significantly associated with the lateral LNM in both cohorts (p< 0.001). The nomogram that consisted of radiomic signature, US-reported cervical lymph node (CLN) status, and CT-reported CLN status demonstrated good discrimination and calibration in the training and validation sets with an AUC of 0.946 and 0.914, respectively. The decision curve analysis indicated that the radiomic nomogram was worthy of clinical application. Conclusion: The radiomic nomogram proposed here has good performance for noninvasively predicting the lateral LNM and might be used to facilitate clinical decision-making and potentially improve the survival outcome in selected patients.