Genomic instability-derived plasma extracellular vesicle-microRNA signature as a minimally invasive predictor of risk and unfavorable prognosis in breast cancer. Bao Siqi,Hu Ting,Liu Jiaqi,Su Jianzhong,Sun Jie,Ming Yue,Li Jiaxin,Wu Nan,Chen Hongyan,Zhou Meng Journal of nanobiotechnology BACKGROUND:Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-associated deaths in women. Recent studies have indicated that microRNA (miRNA) regulation in genomic instability (GI) is associated with disease risk and clinical outcome. Herein, we aimed to identify the GI-derived miRNA signature in extracellular vesicles (EVs) as a minimally invasive biomarker for early diagnosis and prognostic risk stratification. EXPERIMENTAL DESIGN:Integrative analysis of miRNA expression and somatic mutation profiles was performed to identify GI-associated miRNAs. Then, we constructed a discovery and validation study with multicenter prospective cohorts. The GI-derived miRNA signature (miGISig) was developed in the TCGA discovery cohort (n = 261), and was subsequently independently validated in internal TCGA validation (n = 261) and GSE22220 (n = 210) cohorts for prognosis prediction, and in GSE73002 (n = 3966), GSE41922 (n = 54), and in-house clinical exosome (n = 30) cohorts for diagnostic performance. RESULTS:We identified a GI-derived three miRNA signature (MIR421, MIR128-1 and MIR128-2) in the serum extracellular vesicles of BC patients, which was significantly associated with poor prognosis in all the cohorts tested and remained as an independent prognostic factor using multivariate analyses. When integrated with the clinical characteristics, the composite miRNA-clinical prognostic indicator showed improved prognostic performance. The miGISig also showed high accuracy in differentiating BC from healthy controls with the area under the receiver operating characteristics curve (ROC) with 0.915, 0.794 and 0.772 in GSE73002, GSE41922 and TCGA cohorts, respectively. Furthermore, circulating EVs from BC patients in the in-house cohort harbored elevated levels of miGISig, with effective diagnostic accuracy. CONCLUSIONS:We report a novel GI-derived three miRNA signature in EVs, as an excellent minimally invasive biomarker for the early diagnosis and unfavorable prognosis in BC. 10.1186/s12951-020-00767-3

The prognostic value of circular RNA regulatory genes in competitive endogenous RNA network in gastric cancer. Cancer gene therapy Accumulating evidence shows that circular RNA (circRNA) is an important regulator of many diseases, especially cancer. Gastric cancer (GC) is a malignant tumor of the digestive system. The regulatory role and potential mechanism of circRNAs in GC remain unknown. This study aims to explore the function and regulatory mechanism of circRNA-related competitive endogenous RNA (ceRNA) in GC. The circRNA expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The RNA expression profile and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Difference analysis was conducted after quality control. Based on CircInteractome, TargetScan, and miRDB databases, a circRNA-related ceRNA network was constructed. R package "clusterProfiler" was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Then, a univariate and multivariate Cox regression was used to construct a prognostic-related gene model to predict survival models. Finally, a gene set enrichment analysis (GSEA) analysis was performed to elucidate the function of genes related to prognosis. Altogether, 23 DEcircRNAs, 319 DEmiRNAs, and 14,541 DEmRNAs were identified. Based on ceRNA trends, the ceRNA network included 15 DEcircRNAs, 25 DEmiRNAs, and 1099 DEmRNAs in GC. Univariate and multivariate Cox proportional hazards regression analysis was used to establish a survival model with 11 prognosis-related genes and its AUC was 0.741, indicating good sensitivity and specificity in the prediction of GC prognosis. Finally, three prognostic-related genes were selected randomly to verify expression levels, which were consistent with the analysis result. The prognostic genes were significantly enriched in cancer-related biological processes, suggesting their roles in the onset and progression of GC. Our study constructs a prognostic model of GC, deepens our understanding of circRNA-related ceRNA networks in GC biology, and provided further implications for the diagnosis and treatment of GC. 10.1038/s41417-020-00270-9

30-day mortality after systemic anticancer treatment for breast and lung cancer in England: a population-based, observational study. Wallington Michael,Saxon Emma B,Bomb Martine,Smittenaar Rebecca,Wickenden Matthew,McPhail Sean,Rashbass Jem,Chao David,Dewar John,Talbot Denis,Peake Michael,Perren Timothy,Wilson Charles,Dodwell David The Lancet. Oncology BACKGROUND:30-day mortality might be a useful indicator of avoidable harm to patients from systemic anticancer treatments, but data for this indicator are limited. The Systemic Anti-Cancer Therapy (SACT) dataset collated by Public Health England allows the assessment of factors affecting 30-day mortality in a national patient population. The aim of this first study based on the SACT dataset was to establish national 30-day mortality benchmarks for breast and lung cancer patients receiving SACT in England, and to start to identify where patient care could be improved. METHODS:In this population-based study, we included all women with breast cancer and all men and women with lung cancer residing in England, who were 24 years or older and who started a cycle of SACT in 2014 irrespective of the number of previous treatment cycles or programmes, and irrespective of their position within the disease trajectory. We calculated 30-day mortality after the most recent cycle of SACT for those patients. We did logistic regression analyses, adjusting for relevant factors, to examine whether patient, tumour, or treatment-related factors were associated with the risk of 30-day mortality. For each cancer type and intent, we calculated 30-day mortality rates and patient volume at the hospital trust level, and contrasted these in a funnel plot. FINDINGS:Between Jan 1, and Dec, 31, 2014, we included 23 228 patients with breast cancer and 9634 patients with non-small cell lung cancer (NSCLC) in our regression and trust-level analyses. 30-day mortality increased with age for both patients with breast cancer and patients with NSCLC treated with curative intent, and decreased with age for patients receiving palliative SACT (breast curative: odds ratio [OR] 1·085, 99% CI 1·040-1·132; p<0·0001; NSCLC curative: 1·045, 1·013-1·079; p=0·00033; breast palliative: 0·987, 0·977-0·996; p=0·00034; NSCLC palliative: 0·987, 0·976-0·998; p=0·0015). 30-day mortality was also significantly higher for patients receiving their first reported curative or palliative SACT versus those who received SACT previously (breast palliative: OR 2·326 99% CI 1·634-3·312; p<0·0001; NSCLC curative: 3·371, 1·554-7·316; p<0·0001; NSCLC palliative: 2·667, 2·109-3·373; p<0·0001), and for patients with worse general wellbeing (performance status 2-4) versus those who were generally well (breast curative: 6·057, 1·333-27·513; p=0·0021; breast palliative: 6·241, 4·180-9·319; p<0·0001; NSCLC palliative: 3·384, 2·276-5·032; p<0·0001). We identified trusts with mortality rates in excess of the 95% control limits; this included seven for curative breast cancer, four for palliative breast cancer, five for curative NSCLC, and seven for palliative NSCLC. INTERPRETATION:Our findings show that several factors affect the risk of early mortality of breast and lung cancer patients in England and that some groups are at a substantially increased risk of 30-day mortality. The identification of hospitals with significantly higher 30-day mortality rates should promote review of clinical decision making in these hospitals. Furthermore, our results highlight the importance of collecting routine data beyond clinical trials to better understand the factors placing patients at higher risk of 30-day mortality, and ultimately improve clinical decision making. Our insights into the factors affecting risk of 30-day mortality will help treating clinicians and their patients predict the balance of harms and benefits associated with SACT. FUNDING:Public Health England. 10.1016/S1470-2045(16)30383-7