Project description:<p>The earliest genetic abnormalities in cancer represent a unique opportunity for timely clinical diagnosis. Classic deep sequencing of tumors identifies many aberrations acquired later in cancer progression. In this study, data regarding simple mutation and chromosomal aberration were integrated to trace the evolution of cutaneous squamous cell carcinomas and ovarian adenocarcinomas. Only after the second allele of TP53 was lost did the genome enter a window of extreme genomic vulnerability, in both cancer types, eventually acquiring more than 100,000 mutations in skin cancers. Inactivating Notch mutations were also identified as prevalent secondary changes. These results add context to the idea of TP53 mutation as dominant negative and occurring later in tumorigenesis.</p>
Project description:<p>The earliest genetic abnormalities in cancer represent a unique opportunity for timely clinical diagnosis. Classic deep sequencing of tumors identifies many aberrations acquired later in cancer progression. In this study, data regarding simple mutation and chromosomal aberration were integrated to trace the evolution of cutaneous squamous cell carcinomas and ovarian adenocarcinomas. Only after the second allele of TP53 was lost did the genome enter a window of extreme genomic vulnerability, in both cancer types, eventually acquiring more than 100,000 mutations in skin cancers. Inactivating Notch mutations were also identified as prevalent secondary changes. These results add context to the idea of TP53 mutation as dominant negative and occurring later in tumorigenesis.</p>
Project description:Timely intervention for cancer requires knowledge of its earliest genetic aberrations. Sequencing of tumors and their metastases reveals numerous abnormalities occurring late in progression. A means to temporally order aberrations in a single cancer, rather than inferring them from serially acquired samples, would define changes preceding even clinically evident disease. We integrate DNA sequence and copy number information to reconstruct the order of abnormalities as individual tumors evolve for 2 separate cancer types. We detect vast, unreported expansion of simple mutations sharply demarcated by recombinative loss of the second copy of TP53 in cutaneous squamous cell carcinomas (cSCC) and serous ovarian adenocarcinomas, in the former surpassing 50 mutations per megabase. In cSCCs, we also report diverse secondary mutations in known and novel oncogenic pathways, illustrating how such expanded mutagenesis directly promotes malignant progression. These results reframe paradigms in which TP53 mutation is required later, to bypass senescence induced by driver oncogenes.
Project description:Stanford type A aortic dissection (STAAD) is an aortic degenerative remodeling disease carrying an exceedingly high mortality worldwide. The irreversible weakening, dilatation and dissection of the ascending aorta contributes to circulatory failure and premature death. Dissections manifest distinct patterns in both clinical presentations and histophathological features during disease temporal transition. Therefore, we delineate a full repertoire of cellular landscape and dynamic interplay in distinct temporal patterns of STAAD using single-cell transcriptomics for comprehensively understanding of disease features and temporal evolution. We performed single-cell RNA sequencing with ascending aortic tissues from 14 participants, including 9 patients with STAAD (4 acute, 3 subacute, and 2 chronic) and 5 control subjects. Unsupervised clustering was performed based on transcriptional profiles of highly variable genes. Single T cell analysis by RNA sequencing and TCR tracking (STARTRACT) was performed to quantitatively delineate the developmental trajectory of aortic T lymphocytes. On the basis of molecular signatures and distinct disease patterns, we draw a spatiotemporal map of disease subtype-specific alterations and complex interplay among cell types. The transcriptional profiles of 93,397 individual cells enable us to identify 12 major cell types and 37 subtypes in human ascending aorta. Comparisons of transcriptomes of disease subtypes reveal striking stage-specific cellular diversity and transcriptional dynamics in phenotypic switch, vascular inflammation, cell death and survival, extracellular matrix remodeling, and cell-cell interactions during disease temporal transition. Modeling of developmental trajectory revealed that the defects in mitochondrial OXPHOS drives phenotypic switch of contractile smooth muscle cells to synthetic myofibroblasts through AP-1 transcriptional complex. STARTRACT analysis revealed that CD8+ HSP are preferentially enriched and potentially clonally expanded in acute AD. Intersection of disease risk genes with our dataset reveals distinct gene panel in discriminating temporal-specifc AD. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the cellular diversity and heterogeneity in human aorta. The distinct alterations of cell type- and disease subtype-specific spatiotemporal features will ultimately facilitate the design of more precisely tailored anti-AD therapies.