Systematic sequencing of cancer genomes has revealed prevalent heterogeneity, with patients harboring various combinatorial patterns of genetic alteration. In particular, a phenomenon that a group of genes exhibits mutually exclusive patterns has been widespread across cancers, covering a broad spectrum of crucial cancer pathways. Recently, there is considerable evidence showing that, mutual exclusivity reflects alternative functions in tumor initiation and progression, or suggests adverse effects of their concurrence. Given its importance, numerous computational approaches have been proposed to study mutual exclusivity using genomic profiles alone, or by integrating networks and phenotypes. Some of them have been routinely used to explore genetic associations, which lead to a deeper understanding of carcinogenic mechanisms and reveals unexpected tumor vulnerabilities. Here, we present an overview of mutual exclusivity from the perspective of cancer genome. We describe the common hypothesis underlying mutual exclusivity, summarize the strategies for the identification of significant mutually exclusive patterns, compare the performance of representative algorithms from simulated data sets and discuss their common confounders.

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

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.

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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