Varying Mutational Classes Illuminate Differential Genetic Patterns Between Schizophrenia and Bipolar Disorder Schizophrenia (SCZ) and bipolar disorder (BPD) are two severe psychiatric disorders that share considerable comorbidities in both clinicals and genetics. In both diseases, the genetic susceptibility often arises from a combination of different types of variants, suggesting that they may contribute their effects to various biological pathways. Here, we compared susceptible risk factors in SCZ and BPD impacted by different types of variants, such as de novo mutations (DNM), single nucleotide polymorphisms (SNP), and copy number variants (CNV), to explore the shared and distinct biological pathways underlying the complex structure of disease genetics in SCZ and BPD. We found that genes carrying DNMs in SCZ and genes impacted by CNVs in BPD explain diseaserelevant functional enrichment patterns more than other types of variants. In addition, we evaluated the haploinsufficiency, mutation burden, and network degree of variants impacted genes. The results suggested that DNM affected genes contributed more to affected pathways than genes hit by CNVs in SCZ, not in BPD. As a whole, we investigated the impacts of various types of variants on biological pathways and provided insights on the convergent and divergent genetic patterns in SCZ and BPD.

Characterizing Mutually Exclusive Driver Mutations in PanCancer Efforts on cancer genomic study have revealed that mutations in cancerdriving oncogenes tend to mutually exclusive. To understand this tumorigenic mechanism and common cancer features, largescale genomic study and molecular analyses across many cancer types are essential. We compiled somatic mutation and transcriptome profiles for a pancancer dataset that contains tumor tissue samples from 32 cancer types for over 10,000 patients. The genomic and molecular analysis was applied to four pancancer subgroups including pangastrointestinal, pangynecological, pankidney and pansquamous, as well as the entire patient group. We identified seven genes, TP53, PIK3CA, PTEN, PIK3R1, LRP1B, CDH1, and TRRAP exhibited mutually exclusive mutation patterns across all cancer types (adjusted  mathrmp  ). The mutations in these genes occurred in 55.9% of all cancer patients and over 70% of patients with pangastrointestinal, pangynecological and pansquamous. Excepting LRP1B, the other six genes are included in the known cancer pathways. Notably, TP53, PIK3CA, and PIK3R1 are involved in over 20 cancerrelated pathways. The coexpression network analysis suggested that LRP1B was associated with multiple genes that showed significant enrichment in Wnt signal pathway (adjusted  mathrmp0.0023 ) and ERBB signal pathway (adjusted  mathrmp0.0097 ). We further constructed a regulatory network to infer novel regulations of LRP1B in cancer. In addition, based on the mutations in the seven genes, we divided the patients into different groups for survival analysis. We found that the survival rate of the patient group with TP53 mutations was significantly shorter than in other groups (log rank  mathrmp 5.88mathrme10 ) in pangynecological. Our analysis systematically revealed the mutually exclusive mutation patterns of seven cancer genes across 32 cancer types. It helps us to better understanding the relations among different cancer types and pancancer subgroups, providing new insights into common mechanisms underlying diverse cancer types.