Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression.

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis.

Increased frequency of CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression without inducing homologous recombination deficiency.

We analyzed genomic data derived from the prostate cancer of African and European American men in order to identify differences that may contribute to racial disparity of outcome and that could also define novel therapeutic strategies. In addition to analyzing patient derived next generation sequencing data, we performed FISH based confirmatory studies of Chromodomain helicase DNA-binding protein 1 () loss on prostate cancer tissue microarrays. We created CRISPR edited, deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis.

Nucleotide excision repair deficiency is a targetable therapeutic vulnerability in clear cell renal cell carcinoma.

Due to a demonstrated lack of DNA repair deficiencies, clear cell renal cell carcinoma (ccRCC) has not benefitted from targeted synthetic lethality-based therapies. We investigated whether nucleotide excision repair (NER) deficiency is present in an identifiable subset of ccRCC cases that would render those tumors sensitive to therapy targeting this specific DNA repair pathway aberration. We used functional assays that detect UV-induced 6-4 pyrimidine-pyrimidone photoproducts to quantify NER deficiency in ccRCC cell lines.

Nucleotide excision repair deficiency is a targetable therapeutic vulnerability in clear cell renal cell carcinoma.

Purpose: Due to a demonstrated lack of DNA repair deficiencies, clear cell renal cell carcinoma (ccRCC) has not benefitted from targeted synthetic lethality-based therapies. We investigated whether nucleotide excision repair (NER) deficiency is present in an identifiable subset of ccRCC cases that would render those tumors sensitive to therapy targeting this specific DNA repair pathway aberration.

Experimental Design: We used functional assays that detect UV-induced 6-4 pyrimidine-pyrimidone photoproducts to quantify NER deficiency in ccRCC cell lines.

Long-term treatment with the PARP inhibitor niraparib does not increase the mutation load in cell line models and tumour xenografts.

Background: Poly-ADP ribose polymerase (PARP) inhibitor-based cancer therapy selectively targets cells with deficient homologous recombination repair. Considering their long-term use in maintenance treatment, any potential mutagenic effect of PARP inhibitor treatment could accelerate the development of resistance or harm non-malignant somatic cells.

Methods: We tested the mutagenicity of long-term treatment with the PARP inhibitor niraparib using whole-genome sequencing of cultured cell clones and whole-exome sequencing of patient-derived breast cancer xenografts.

Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements.

Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets.

Assessing the significance of consistently mis-regulated genes in cancer associated gene expression matrices.

Motivation: The simplest level of statistical analysis of cancer associated gene expression matrices is aimed at finding consistently up- or down-regulated genes within a given set of tumor samples. Considering the high level of gene expression diversity detected in cancer, one needs to assess the probability that the consistent mis-regulation of a given gene is due to chance. Furthermore, it is important to determine the required sample number that will ensure the meaningful statistical analysis of massively parallel gene expression measurements.