Nuclear factor erythroid-2 related factor 2 (NRF2) is a redox-sensitive transcription factor that positively regulates the expression of genes encoding antioxidants, xenobiotic detoxification enzymes, and drug efflux pumps, and confers cytoprotection against oxidative stress and xenobiotics in normal cells. Kelch-like ECH-associated protein 1 (KEAP1) negatively regulates NRF2 activity by targeting it to proteasomal degradation. Increased expression of cellular antioxidants and xenobiotic detoxification enzymes has been implicated in resistance of tumor cells against chemotherapeutic drugs. Here we report a systematic analysis of the KEAP1 genomic locus in lung cancer patients and cell lines that revealed deletion, insertion, and missense mutations in functionally important domains of KEAP1 and a very high percentage of loss of heterozygosity at 19p13.2, suggesting that biallelic inactivation of KEAP1 in lung cancer is a common event. Sequencing of KEAP1 in 12 cell lines and 54 non-small-cell lung cancer (NSCLC) samples revealed somatic mutations in KEAP1 in a total of six cell lines and ten tumors at a frequency of 50% and 19%, respectively. All the mutations were within highly conserved amino acid residues located in the Kelch or intervening region domain of the KEAP1 protein, suggesting that these mutations would likely abolish KEAP1 repressor activity. Evaluation of loss of heterozygosity at 19p13.2 revealed allelic losses in 61% of the NSCLC cell lines and 41% of the tumor samples. Decreased KEAP1 activity in cancer cells induced greater nuclear accumulation of NRF2, causing enhanced transcriptional induction of antioxidants, xenobiotic metabolism enzymes, and drug efflux pumps. This is the first study to our knowledge to demonstrate that biallelic inactivation of KEAP1 is a frequent genetic alteration in NSCLC. Loss of KEAP1 function leading to constitutive activation of NRF2-mediated gene expression in cancer suggests that tumor cells manipulate the NRF2 pathway for their survival against chemotherapeutic agents.

While patient-derived xenografts (PDXs) offer a powerful modality for translational cancer research, a precise evaluation of how accurately patient responses correlate with matching PDXs in a large, heterogeneous population is needed for assessing the utility of this platform for preclinical drug-testing and personalized patient cancer treatment. Tumors obtained from surgical or biopsy procedures from 237 cancer patients with a variety of solid tumors were implanted into immunodeficient mice and whole-exome sequencing was carried out. For 92 patients, responses to anticancer therapies were compared with that of their corresponding PDX models. We compared whole-exome sequencing of 237 PDX models with equivalent information in The Cancer Genome Atlas database, demonstrating that tumorgrafts faithfully conserve genetic patterns of the primary tumors. We next screened PDXs established for 92 patients with various solid cancers against the same 129 treatments that were administered clinically and correlated patient outcomes with the responses in corresponding models. Our analysis demonstrates that PDXs accurately replicate patients’ clinical outcomes, even as patients undergo several additional cycles of therapy over time, indicating the capacity of these models to correctly guide an oncologist to treatments that are most likely to be of clinical benefit. Integration of PDX models as a preclinical platform for assessment of drug efficacy may allow a higher success-rate in critical end points of clinical benefit.

Background: The noninvasive identification of bladder tumors may improve disease control and prevent disease progression. Aberrant promoter methylation (i.e., hypermethylation) is a major mechanism for silencing tumor suppressor genes and other cancer-associated genes in many human cancers, including bladder cancer. Methods: A quantitative fluorogenic real-time polymerase chain reaction (PCR) assay was used to examine primary tumor DNA and urine sediment DNA from 15 patients with bladder cancer and 25 control subjects for promoter hypermethylation of nine genes (APC, ARF, CDH1, GSTP1, MGMT, CDKN2A, RARβ2, RASSF1A, and TIMP3) to identify potential biomarkers for bladder cancer. We then used these markers to examine urine sediment DNA samples from an additional 160 patients with bladder cancers of various stages and grades and from an additional 69 age-matched control subjects. Data were analyzed on the basis of a prediction model and were internally validated using a jacknife procedure. All statistical tests were two-sided. Results: For all 15 patients with paired DNA samples, the promoter methylation pattern in urine matched that in the primary tumors. Four genes displayed 100% specificity. Of the 175 bladder cancer patients, 121 (69%, 95% confidence interval [CI] = 62% to 76%) displayed promoter methylation in at least one of these genes (CDKN2A, ARF, MGMT, and GSTP1), whereas all control subjects were negative for such methylation (100% specificity, 95% CI = 96% to 100%). A logistic prediction model using the methylation levels of all remaining five genes was developed and internally validated for subjects who were negative on the four-gene panel. This combined, two-stage predictor produced an internally validated ROC curve with an overall sensitivity of 82% (95% CI = 75 % to 87%) and specificity of 96% (95% CI = 90% to 99%). Conclusion: Testing a small panel of genes with the quantitative methylation–specific PCR assay in urine sediment DNA is a powerful noninvasive approach for the detection of bladder cancer. Larger independent confirmatory cohorts with longitudinal follow-up will be required in future studies to define the impact of this technology on early detection, prognosis, and disease monitoring before clinical application.

Purpose: Promoter hypermethylation is an alternative pathway for gene silencing in neoplastic cells and a promising cancer detection marker. Although quantitative methylation-specific PCR (QMSP) of the GSTP1 promoter has demonstrated near perfect specificity for cancer detection in prostate biopsies, we postulated that identification and characterization of additional methylation markers might further improve its high (80–90%) sensitivity.

Somatic mitochondrial mutations are common in human cancers, and can be used as a tool for early detection of cancer. We have developed a mitochondrial Custom Reseq™ microarray as an array-based sequencing platform for rapid and high-throughput analysis of mitochondrial DNA. The MitoChip contains oligonucleotide probes synthesized using standard photolithography and solid-phase synthesis, and is able to sequence >29 kb of double-stranded DNA in a single assay. Both strands of the entire human mitochondrial coding sequence (15,451 bp) are arrayed on the MitoChip; both strands of an additional 12,935 bp (84% of coding DNA) are arrayed in duplicate. We used 300 ng of genomic DNA to amplify the mitochondrial coding sequence in three overlapping long PCR fragments. We then sequenced >2 million base pairs of mitochondrial DNA, and successfully assigned base calls at 96.0% of nucleotide positions. Replicate experiments demonstrated >99.99% reproducibility. In matched fluid samples (urine and pancreatic juice, respectively) obtained from five patients with bladder cancer and four with pancreatic cancer, the MitoChip detected at least one cancer-associated mitochondrial mutation in six (66%) of nine samples. The MitoChip is a high-throughput sequencing tool for the reliable identification of mitochondrial DNA mutations from primary tumors in clinical samples.