Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model.

Mechanistic models are essential to deepen the understanding of complex diseases at the molecular level. Nowadays, high-throughput molecular and phenotypic characterizations are possible, but the integration of such data with prior knowledge on signaling pathways is limited by the availability of scalable computational methods. Here, we present a computational framework for the parameterization of large-scale mechanistic models and its application to the prediction of drug response of cancer cell lines from exome and transcriptome sequencing data. This framework is over 104 times faster than state-of-the-art methods, which enables modeling at previously infeasible scales. By applying the framework to a model describing major cancer-associated pathways (>1,200 species and >2,600 reactions), we could predict the effect of drug combinations from single drug data. This is the first integration of high-throughput datasets using large-scale mechanistic models. We anticipate this to be the starting point for development of more comprehensive models allowing a deeper mechanistic insight.

Genotype-phenotype correlations in patients with retinoblastoma and interstitial 13q deletions.

Patients with an interstitial 13q deletion that contains the RB1 gene show retinoblastoma and variable clinical features. Relationship between phenotypic expression and loss of specific neighboring genes are unresolved, yet. We obtained clinical, cytogenetic and molecular data in 63 patients with an interstitial 13q deletion involving RB1. Whole-genome array analysis or customized high-resolution array analysis for 13q14.11q14.3 was performed in 38 patients, and cytogenetic analysis was performed in 54 patients. Deletion sizes ranged between 4.2 kb and more than 33.43 Mb; breakpoints were non-recurrent. Sequence analysis of deletion junctions in five patients revealed microhomology and insertion of 2-34 base pairs suggestive of non-homologous end joining. Milder phenotypic expression of retinoblastoma was observed in patients with deletions larger than 1 Mb, which contained the MED4 gene. Clinical features were compared between patients with small (within 13q14), medium (within 13q12.3q21.2) and large (within 13q12q31.2) deletions. Patients with a small deletion can show macrocephaly, tall stature, obesity, motor and/or speech delay. Patients with a medium deletion show characteristic facial features, mild to moderate psychomotor delay, short stature and microcephaly. Patients with a large deletion have characteristic craniofacial dysmorphism, short stature, microcephaly, mild to severe psychomotor delay, hypotonia, constipation and feeding problems. Additional features included deafness, seizures and brain and heart anomalies. We found no correlation between clinical features and parental origin of the deletion. Our data suggest that hemizygous loss of NUFIP1 and PCDH8 may contribute to psychomotor delay, deletion of MTLR1 to microcephaly and loss of EDNRB to feeding difficulties and deafness.

AML/MDS with 11q/MLL amplification show characteristic gene expression signature and interplay of DNA copy number changes.

AML/MDS patients carrying 11q amplifications involving the mixed lineage leukemia gene (MLL) locus are characterized by a complex aberrant karyotype (CAK) frequently including deletions within 5q, 17p, and 7q, older age and fast progression of the disease with extremely poor prognosis. MLL has been shown to be overexpressed in cases with 11q amplification. However, in most of the cases, the amplified region is not restricted to the MLL locus. In this study, we investigated 19 patients with AML/MDS and MLL gain/amplification. By means of array CGH performed in 12 patients, we were able to delineate the minimal deleted regions within 5q and 17p and identified three independent regions 11q/I-III that were amplified in all cases. Gene expression profiles established in 15 cases were used to identify candidate genes within these regions. Notably, analysis of our data suggests a correlation of loss of 5q and 17p and expression of genes present in 11q23-25. Furthermore, we demonstrate that the gene expression signature can be used to discriminate AML/MDS with MLL amplification from several other types of AML.

An integrative approach for analyzing the interplay of genetic and epigenetic changes in tumors.

The accumulation of chromosomal aberrations is a characteristic feature of tumor development. However, an understanding of tumorigenesis that assumes that changes in DNA copy number always cause equivalent changes in the corresponding RNA and protein levels is an oversimplification and completely ignores the individual genetic and epigenetic context in which an aberration has to be evaluated. We present a brief introduction to various techniques dedicated to the genome-wide analysis of genetic and epigenetic changes, and illustrate how complementary information derived from these various DNA array-based technologies can lead to a better understanding of the consequences of chromosomal aberrations.