Fig. 1: Measurement of the cancer distribution of driver mutations with network diversity (network diversity).
From: Diversity spectrum analysis identifies mutation-specific effects of cancer driver genes
a Driver mutations identified from patients of 33 cancer types are used to construct a patient–mutation bipartite network. The 33 cancer types include adrenocortical carcinoma (ACC), bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cervical squamous cell carcinoma, and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), acute myeloid leukemia (LAML), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), mesothelioma (MESO), ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), sarcoma (SARC), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD), testicular germ cell tumors (TGCT), thyroid carcinoma (THCA), thymoma (THYM), uterine corpus endometrial carcinoma (UCEC), uterine carcinosarcoma (UCS), and uveal melanoma (UVM). Based on this network, the network diversity (ND) value of each mutation is calculated and mapped onto the cancer diversity spectrum. According to the spectrum, driver mutations are classified into specific, relatively specific and pancancer mutations. b The overall composition of cancer types in the patient–mutation network related to 1570 analyzed driver mutations in the study. c The genes that harbor the 1570 mutations and their relative contributions.
