One of the most fundamental questions in biology is what types of cells form different tissues and organs in a functionally coordinated fashion. Larger-scale single-cell sequencing and biology experiment studies are now rapidly opening up new ways to track this question by revealing substantial cell markers for distinguishing different cell types in tissues. Here, we developed the CellMarker database (http://biocc.hrbmu.edu.cn/CellMarker/ or http://bio-bigdata.hrbmu.edu.cn/CellMarker/), aiming to provide a comprehensive and accurate resource of cell markers for various cell types in tissues of human and mouse. By manually curating over 100 000 published papers, 4124 entries including the cell marker information, tissue type, cell type, cancer information and source, were recorded. At last, 13 605 cell markers of 467 cell types in 158 human tissues/sub-tissues and 9148 cell makers of 389 cell types in 81 mouse tissues/sub-tissues were collected and deposited in CellMarker. CellMarker provides a user-friendly interface for browsing, searching and downloading markers of diverse cell types of different tissues. Furthermore, a summarized marker prevalence in each cell type is graphically and intuitively presented through a vivid statistical graph. We believe that CellMarker is a comprehensive and valuable resource for cell researches in precisely identifying and characterizing cells, especially at the single-cell level.

Diffuse glioma, including low-grade glioma (LGG) and glioblastoma (GBM), is a common primary malignant intracranial tumor in adults. It accounts for almost 80% of malignant brain tumors and has high mortality, especially in GBM. According to previous studies, sex differences present in both incidence and outcome of glioma patients, with higher morbidity and mortality in men than women. 1,2 Although the obvious epidemiological disparity exists between male and female glioma patients, neither pathological diagnosis nor clinical treatment considers sex as an important variable. Sexual dimorphisms of glioma at the clinical phenotypic and molecular levels have been revealed by several researches. For example, in a retrospective study 201

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DGs are the most common primary malignant brain tumours in adults, with an age-adjusted mortality rate of 4.25/100,000 per year in the United States [1]. To understand gliomagenesis, molecular changes in large cohorts of DGs have been described previously [2,3]. These large-scale studies established the full spectrum of genomic alterations and revealed extensive molecular heterogeneity among individuals. Recent genomic studies have documented that individual cancer samples display genetic heterogeneity and contain subclonal populations [4]. The presence of multiple clones within a single tumour has been explained as a Darwinian evolutionary

Breast cancer (BRCA) is the most common cancer and a major cause of death in women. Long non-coding RNAs (lncRNAs) are emerging as key regulators and have been implicated in carcinogenesis and prognosis. In this study, we aimed to develop a lncRNA signature of BRCA patients to improve risk stratification. In the training cohort (GSE21653, n = 232), 17 lncRNAs were identified by univariate Cox proportional hazards regression, which were significantly associated with patients’ survival. The least absolute shrinkage and selection operator-penalized Cox proportional hazards regression analysis was used to identify a six-lncRNA signature. According to the median of the signature risk score, patients were divided into a high-risk group and a low-risk group with significant disease-free survival differences in the training cohort. A similar phenomenon was observed in validation cohorts (GSE42568, n = 101; GSE20711, n = 87). The six-lncRNA signature remained as independent prognostic factors after adjusting for clinical factors in these two cohorts. Furthermore, this signature significantly predicted the survival of grade III patients and estrogen receptor-positive patients. Furthermore, in another cohort (GSE19615, n = 115), the low-risk patients that were treated with tamoxifen therapy had longer disease-free survival than those who underwent no therapy. Overall, the six-lncRNA signature can be a potential prognostic tool used to predict disease-free survival of patients and to predict the benefits of tamoxifen treatment in BRCA, which will be helpful in guiding individualized treatments for BRCA patients.