Encoding Phenotype in Bacteria with an Alternative Genetic Set

An unnatural base-pair architecture with base pairs 2.4 Å larger than the natural DNA-based genetic system (xDNA) is evaluated for its ability to function like DNA, encoding amino acids in the context of living cells. xDNA bases are structurally analogous to natural bases but homologated by the width of a benzene ring, increasing their sizes and resulting in a duplex that is wider than native B-DNA. Plasmids encoding green fluorescent protein were constructed to contain single and multiple xDNA bases (as many as eight) in both strands and were transformed into <i>Escherichia coli</i>. Although they yielded fewer colonies than the natural control plasmid, in <i>all</i> cases in which a modified plasmid (containing one, two, three, or four consecutive size-expanded base pairs) was used, the correct codon bases were substituted, yielding green colonies. All four xDNA bases (xA, xC, xG, and xT) were found to encode the correct partners in the replicated plasmid DNA, both alone and in longer segments of xDNA. Controls with mutant cell lines having repair functions deleted were found to express the gene correctly, ruling out repair of xDNA and confirming polymerase reading of the unnatural bases. Preliminary experiments with polymerase deletion mutants suggested combined roles of replicative and lesion-bypass polymerases in inserting correct bases opposite xDNA bases and in bypassing the xDNA segments. These experiments demonstrate a biologically functioning synthetic genetic set with larger-than-natural architecture

Genomic analysis of advanced breast cancer tumors from talazoparib-treated gBRCA1/2mut carriers in the ABRAZO study.

These analyses explore the impact of homologous recombination repair gene mutations, including BRCA1/2 mutations and homologous recombination deficiency (HRD), on the efficacy of the poly(ADP-ribose) polymerase (PARP) inhibitor talazoparib in the open-label, two-cohort, Phase 2 ABRAZO trial in germline BRCA1/2-mutation carriers. In the evaluable intent-to-treat population (N = 60), 58 (97%) patients harbor ≥1 BRCA1/2 mutation(s) in tumor sequencing, with 95% (53/56) concordance between germline and tumor mutations, and 85% (40/47) of evaluable patients have BRCA locus loss of heterozygosity indicating HRD. The most prevalent non-BRCA tumor mutations are TP53 in patients with BRCA1 mutations and PIK3CA in patients with BRCA2 mutations. BRCA1- or BRCA2-mutated tumors show comparable clinical benefit within cohorts. While low patient numbers preclude correlations between HRD and efficacy, germline BRCA1/2 mutation detection from tumor-only sequencing shows high sensitivity and non-BRCA genetic/genomic events do not appear to influence talazoparib sensitivity in the ABRAZO trial.ClinicalTrials.gov identifier: NCT02034916

Determinants of Response to Talazoparib in Patients with HER2-Negative, Germline BRCA1/2-Mutated Breast CancerTalazoparib in Germline BRCA1/2-Mutated Breast Cancer

PurposePARP inhibitors (PARPi) have demonstrated efficacy in tumors with germline breast cancer susceptibility genes (gBRCA) 1 and 2 mutations, but further factors influencing response to PARPi are poorly understood.Experimental designBreast cancer tumor tissue from patients with gBRCA1/2 mutations from the phase III EMBRACA trial of the PARPi talazoparib versus chemotherapy was sequenced using FoundationOne CDx.ResultsIn the evaluable intent-to-treat population, 96.1% (296/308) had ≥1 tumor BRCA (tBRCA) mutation and there was strong concordance (95.3%) between tBRCA and gBRCA mutational status. Genetic/genomic characteristics including BRCA loss of heterozygosity (LOH; identified in 82.6% of evaluable patients), DNA damage response (DDR) gene mutational burden, and tumor homologous recombination deficiency [assessed by genomic LOH (gLOH)] demonstrated no association with talazoparib efficacy.ConclusionsOverall, BRCA LOH status, DDR gene mutational burden, and gLOH were not associated with talazoparib efficacy; however, these conclusions are qualified by population heterogeneity and low patient numbers in some subgroups. Further investigation in larger patient populations is warranted

Genomic analysis of advanced breast cancer tumors from talazoparib-treated gBRCA1/2mut carriers in the ABRAZO study

Abstract These analyses explore the impact of homologous recombination repair gene mutations, including BRCA1/2 mutations and homologous recombination deficiency (HRD), on the efficacy of the poly(ADP-ribose) polymerase (PARP) inhibitor talazoparib in the open-label, two-cohort, Phase 2 ABRAZO trial in germline BRCA1/2-mutation carriers. In the evaluable intent-to-treat population (N = 60), 58 (97%) patients harbor ≥1 BRCA1/2 mutation(s) in tumor sequencing, with 95% (53/56) concordance between germline and tumor mutations, and 85% (40/47) of evaluable patients have BRCA locus loss of heterozygosity indicating HRD. The most prevalent non-BRCA tumor mutations are TP53 in patients with BRCA1 mutations and PIK3CA in patients with BRCA2 mutations. BRCA1- or BRCA2-mutated tumors show comparable clinical benefit within cohorts. While low patient numbers preclude correlations between HRD and efficacy, germline BRCA1/2 mutation detection from tumor-only sequencing shows high sensitivity and non-BRCA genetic/genomic events do not appear to influence talazoparib sensitivity in the ABRAZO trial. ClinicalTrials.gov identifier: NCT02034916

Ability of a Genomic Classifier to Predict Metastasis and Prostate Cancer-specific Mortality after Radiation or Surgery based on Needle Biopsy Specimens

Decipher is a validated genomic classifier developed to determine the biological potential for metastasis after radical prostatectomy (RP). To evaluate the ability of biopsy Decipher to predict metastasis and Prostate cancer-specific mortality (PCSM) in primarily intermediate- to high-risk patients treated with RP or radiation therapy (RT). Two hundred and thirty-five patients treated with either RP (n=105) or RT±androgen deprivation therapy (n=130) with available genomic expression profiles generated from diagnostic biopsy specimens from seven tertiary referral centers. The highest-grade core was sampled and Decipher was calculated based on a locked random forest model. Metastasis and PCSM were the primary and secondary outcomes of the study, respectively. Cox analysis and c-index were used to evaluate the performance of Decipher. With a median follow-up of 6 yr among censored patients, 34 patients developed metastases and 11 died of prostate cancer. On multivariable analysis, biopsy Decipher remained a significant predictor of metastasis (hazard ratio: 1.37 per 10% increase in score, 95% confidence interval [CI]: 1.06–1.78, p=0.018) after adjusting for clinical variables. For predicting metastasis 5-yr post-biopsy, Cancer of the Prostate Risk Assessment score had a c-index of 0.60 (95% CI: 0.50–0.69), while Cancer of the Prostate Risk Assessment plus biopsy Decipher had a c-index of 0.71 (95% CI: 0.60–0.82). National Comprehensive Cancer Network risk group had a c-index of 0.66 (95% CI: 0.53–0.77), while National Comprehensive Cancer Network plus biopsy Decipher had a c-index of 0.74 (95% CI: 0.66–0.82). Biopsy Decipher was a significant predictor of PCSM (hazard ratio: 1.57 per 10% increase in score, 95% CI: 1.03–2.48, p=0.037), with a 5-yr PCSM rate of 0%, 0%, and 9.4% for Decipher low, intermediate, and high, respectively. Biopsy Decipher predicted metastasis and PCSM from diagnostic biopsy specimens of primarily intermediate- and high-risk men treated with first-line RT or RP. Biopsy Decipher predicted metastasis and prostate cancer-specific mortality risk from diagnostic biopsy specimens. Biopsy Decipher was able to predict metastasis and prostate cancer-specific mortality from diagnostic biopsy specimens in a cohort of primarily intermediate- and high-risk men regardless of type of first-line treatment

Development and Validation of a Novel Integrated Clinical-Genomic Risk Group Classification for Localized Prostate Cancer.

Purpose It is clinically challenging to integrate genomic-classifier results that report a numeric risk of recurrence into treatment recommendations for localized prostate cancer, which are founded in the framework of risk groups. We aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Materials and Methods Two multicenter cohorts (n = 991) were used for training and validation of the clinical-genomic risk groups, and two additional cohorts (n = 5,937) were used for reclassification analyses. Competing risks analysis was used to estimate the risk of distant metastasis. Time-dependent c-indices were constructed to compare clinicopathologic risk models with the clinical-genomic risk groups. Results With a median follow-up of 8 years for patients in the training cohort, 10-year distant metastasis rates for National Comprehensive Cancer Network (NCCN) low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.3%, 9.2%, 38.0%, and 39.5%, respectively. In contrast, the three-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.5%, 29.4%, and 54.6%, for low-, intermediate-, and high-risk, respectively, which were consistent in the validation cohort (0%, 25.9%, and 55.2%, respectively). C-indices for the clinical-genomic risk grouping system (0.84; 95% CI, 0.61 to 0.93) were improved over NCCN (0.73; 95% CI, 0.60 to 0.86) and Cancer of the Prostate Risk Assessment (0.74; 95% CI, 0.65 to 0.84), and 30% of patients using NCCN low/intermediate/high would be reclassified by the new three-tier system and 67% of patients would be reclassified from NCCN six-tier (very-low- to very-high-risk) by the new six-tier system. Conclusion A commercially available genomic classifier in combination with standard clinicopathologic variables can generate a simple-to-use clinical-genomic risk grouping that more accurately identifies patients at low, intermediate, and high risk for metastasis and can be easily incorporated into current guidelines to better risk-stratify patients