Tracing cancer evolution and heterogeneity using Hi-C.

Chromosomal rearrangements can initiate and drive cancer progression, yet it has been challenging to evaluate their impact, especially in genetically heterogeneous solid cancers. To address this problem we developed HiDENSEC, a new computational framework for analyzing chromatin conformation capture in heterogeneous samples that can infer somatic copy number alterations, characterize large-scale chromosomal rearrangements, and estimate cancer cell fractions. After validating HiDENSEC with in silico and in vitro controls, we used it to characterize chromosome-scale evolution during melanoma progression in formalin-fixed tumor samples from three patients. The resulting comprehensive annotation of the genomic events includes copy number neutral translocations that disrupt tumor suppressor genes such as NF1, whole chromosome arm exchanges that result in loss of CDKN2A, and whole-arm copy-number neutral loss of homozygosity involving PTEN. These findings show that large-scale chromosomal rearrangements occur throughout cancer evolution and that characterizing these events yields insights into drivers of melanoma progression.

Large-scale cytological profiling for functional analysis of bioactive compounds.

Cytological profiling (CP) is an unbiased image-based screening technique that uses automated microscopy and image analysis to profile compounds based on numerous quantifiable phenotypic features. We used CP to evaluate a library of nearly 500 compounds with documented mechanisms of action (MOAs) spanning a wide range of biological pathways. We developed informatics techniques for generating dosage-independent phenotypic "fingerprints" for each compound, and for quantifying the likelihood that a compound's CP fingerprint corresponds to its annotated MOA. We identified groups of features that distinguish classes with closely related phenotypes, such as microtubule poisons vs. HSP90 inhibitors, and DNA synthesis vs. proteasome inhibitors. We tested several cases in which cytological profiles indicated novel mechanisms, including a tyrphostin kinase inhibitor involved in mitochondrial uncoupling, novel microtubule poisons, and a nominal PPAR-gamma ligand that acts as a proteasome inhibitor, using independent biochemical assays to confirm the MOAs predicted by the CP signatures. We also applied maximal-information statistics to identify correlations between cytological features and kinase inhibitory activities by combining the CP fingerprints of 24 kinase inhibitors with published data on their specificities against a diverse panel of kinases. The resulting analysis suggests a strategy for probing the biological functions of specific kinases by compiling cytological data from inhibitors of varying specificities.