Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

Prevalence and functional consequence of TP53 mutations in pediatric adrenocortical carcinoma: a children's oncology group study.

PURPOSE: Adrenocortical carcinoma (ACC) is a rare pediatric malignancy. It occurs in excess among individuals with the Li-Fraumeni syndrome, which results primarily from germline mutations in the TP53 gene. Prior series exploring frequencies of germline TP53 mutation among children with ACC have been small, geographically limited, or subject to referral bias. The functional consequence of mutations has not been related to phenotype. We provide a genotype-phenotype analysis of TP53 mutations in pediatric ACC and propose a model for tissue-specific effects based on adrenocortical ontogeny. PATIENTS AND METHODS: Eighty-eight consecutive, unrelated children with ACC, unselected for family history, underwent germline TP53 sequencing. Rate and distribution of mutations were identified. Functional analysis was performed for novel TP53 variants. Correlation with the International Agency for Research on Cancer p53 database further delineated mutational distribution, association with family history, and risk for multiple primary malignancies (MPMs). RESULTS: Germline mutations were present in 50% of children. These mutations did not correspond to the conventional hotspot mutations. There was a wide range of mutant protein function. Patients bearing alleles encoding protein with higher functionality were less likely to have a strong family cancer history, whereas those with greater loss of function had MPMs and/or positive family history. In patients with MPMs, ACC was the most frequent initial malignancy. Finally, we demonstrated age-dependent rates of TP53 mutation positivity. CONCLUSION: TP53 mutations are prevalent in children with ACC but decline with age. Mutations result in a broad spectrum of functional loss. Effect of individual mutations may predict carrier and familial disease penetrance with potentially broad implications for clinical surveillance and counseling.

Vascular endothelial growth factor acts in an autocrine manner in rhabdomyosarcoma cell lines and can be inhibited with all-trans-retinoic acid.

Vascular endothelial growth factor (VEGF) is a potent signalling molecule that acts through two tyrosine kinase receptors, VEGFR1 and VEGFR2. The upregulation of VEGF and its receptors is important in tumour-associated angiogenesis; however, recent studies suggest that several tumour cells express VEGF receptors and may be influenced by autocrine VEGF signalling. Rhabdomyosarcoma (RMS) is the most common paediatric soft-tissue sarcoma, and is dependent on autocrine signalling for its growth. The alveolar subtype of RMS is often characterized by the presence of a PAX3-FKHR translocation, and when introduced into non-RMS cells, the resultant fusion protein induces expression of VEGFR1. In our study, we examined the expression of VEGF and its receptors in RMS, and autocrine effects of VEGF on cell growth. VEGF and receptor mRNA and protein were found to be expressed in RMS cells. Exogenous VEGF addition resulted in extracellular signal-regulated kinase-1/2 phosphorylation and cell proliferation, and both were reduced by VEGFR1 blockade. Growth was also slowed by VEGFR1 inhibitor alone. Treatment of RMS cells with all-trans-retinoic acid decreased VEGF secretion and slowed cell growth, which was rescued by VEGF. These data suggest that autocrine VEGF signalling likely influences RMS growth and its inhibition may be an effective treatment for RMS.

Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors.

We present a computational model that offers an integrated quantitative, dynamic, and topological representation of intracellular signal networks, based on known components of epidermal growth factor (EGF) receptor signal pathways. The model provides insight into signal-response relationships between the binding of EGF to its receptor at the cell surface and the activation of downstream proteins in the signaling cascade. It shows that EGF-induced responses are remarkably stable over a 100-fold range of ligand concentration and that the critical parameter in determining signal efficacy is the initial velocity of receptor activation. The predictions of the model agree well with experimental analysis of the effect of EGF on two downstream responses, phosphorylation of ERK-1/2 and expression of the target gene, c-fos.