M. Abazeed

Redirecting abiraterone metabolism to fine-tune prostate cancer anti-androgen therapy

Abiraterone blocks androgen synthesis and prolongs survival in patients with castration-resistant prostate cancer, which is otherwise driven by intratumoral androgen synthesis. Abiraterone is metabolized in patients to Δ4-abiraterone (D4A), which has even greater anti-tumour activity and is structurally similar to endogenous steroidal 5α-reductase substrates, such as testosterone. Here, we show that D4A is converted to at least three 5α-reduced and three 5β-reduced metabolites in human serum. The initial 5α-reduced metabolite, 3-keto-5α-abiraterone, is present at higher concentrations than D4A in patients with prostate cancer taking abiraterone, and is an androgen receptor agonist, which promotes prostate cancer progression. In a clinical trial of abiraterone alone, followed by abiraterone plus dutasteride (a 5α-reductase inhibitor), 3-keto-5α-abiraterone and downstream metabolites were depleted by the addition of dutasteride, while D4A concentrations rose, showing that dutasteride effectively blocks production of a tumour-promoting metabolite and permits D4A accumulation. Furthermore, dutasteride did not deplete the three 5β-reduced metabolites, which were also clinically detectable, demonstrating the specific biochemical effects of pharmacological 5α-reductase inhibition on abiraterone metabolism. Our findings suggest a previously unappreciated and biochemically specific method of clinically fine-tuning abiraterone metabolism to optimize therapy.

Characterizing genomic alterations in cancer by complementary functional associations

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.

A genetic basis for the variation in the vulnerability of cancer to DNA damage

Radiotherapy is not currently informed by the genetic composition of an individual patients tumour. To identify genetic features regulating survival after DNA damage, here we conduct large-scale profiling of cellular survival after exposure to radiation in a diverse collection of 533 genetically annotated human tumour cell lines. We show that sensitivity to radiation is characterized by significant variation across and within lineages. We combine results from our platform with genomic features to identify parameters that predict radiation sensitivity. We identify somatic copy number alterations, gene mutations and the basal expression of individual genes and gene sets that correlate with the radiation survival, revealing new insights into the genetic basis of tumour cellular response to DNA damage. These results demonstrate the diversity of tumour cellular response to ionizing radiation and establish multiple lines of evidence that new genetic features regulating cellular response after DNA damage can be identified.

A Histologic Basis for the Efficacy of SBRT to the lung

Purpose: Stereotactic body radiation therapy (SBRT) is the standard of care for medically inoperable patients with early‐stage NSCLC. However, NSCLC is composed of several histological subtypes and the impact of this heterogeneity on SBRT treatments has yet to be established. Methods: We analyzed 740 patients with early‐stage NSCLC treated definitively with SBRT from 2003 through 2015. We calculated cumulative incidence curves using the competing risk method and identified predictors of local failure using Fine and Gray regression. Results: Overall, 72 patients had a local failure, with a cumulative incidence of local failure at 3 years of 11.8%. On univariate analysis, squamous histological subtype, younger age, fewer medical comorbidities, higher body mass index, higher positron emission tomography standardized uptake value, central tumors, and lower radiation dose were associated with an increased risk for local failure. On multivariable analysis, squamous histological subtype (hazard ratio = 2.4 p = 0.008) was the strongest predictor of local failure. Patients with squamous cancers fail SBRT at a significantly higher rate than do those with adenocarcinomas or NSCLC not otherwise specified, with 3‐year cumulative rates of local failure of 18.9% (95% confidence interval [CI]: 12.7–25.1), 8.7% (95% CI: 4.6–12.8), and 4.1% (95% CI: 0–9.6), respectively. Conclusion: Our results demonstrate an increased rate of local failure in patients with squamous cell carcinoma. Standard approaches for radiotherapy that demonstrate efficacy for a population may not achieve optimal results for individual patients. Establishing the differential dose effect of SBRT across histological groups is likely to improve efficacy and inform ongoing and future studies that aim to expand indications for SBRT.

Collateral sensitivity networks reveal evolutionary instability and novel treatment strategies in ALK mutated non-small cell lung cancer

Drug resistance remains an elusive problem in cancer therapy, particularly for novel targeted therapies. Much work is focused upon the development of an arsenal of targeted therapies, towards oncogenic driver genes such as ALK-EML4, to overcome the inevitable resistance that develops over time. Currently, after failure of first line ALK TKI therapy, another ALK TKI is administered, though collateral sensitivity is not considered. To address this, we evolved resistance in an ALK rearranged non-small cell lung cancer line (H3122) to a panel of 4 ALK TKIs, and performed a collateral sensitivity analysis. All ALK inhibitor resistant cell lines displayed significant cross-resistance to all other ALK inhibitors. We then evaluated ALK-inhibitor sensitivities after drug holidays of varying length (1–21 days), and observed dynamic patterns of resistance. This unpredictability led us to an expanded search for treatment options, where we tested 6 further anti-cancer agents for collateral sensitivity among resistant cells, uncovering possibilities for further treatment, including cross-sensitivity to standard cytotoxic therapies, as well as Hsp90 inhibitors. Taken together, these results imply that resistance to targeted therapy in non-small cell lung cancer is highly dynamic, and also one where there are many opportunities to re-establish sensitivities where there was once resistance. Drug resistance in cancer inevitably emerges during treatment; particularly with novel targeted therapies, designed to inhibit specific molecules. A clinically-relevant example of this phenomenon occurs in ALK-positive non-small cell lung cancer, where targeted therapies are used to inhibit the ALK-EML4 fusion protein. A potential solution to this may lie in finding drug sensitivities in the resistant population, termed collateral sensitivities, and then using these as second-line agents. This study shows how the evolution of resistance in ALK-positive lung cancer is a dynamic process through time, one in which patterns of drug resistance and collateral sensitivity change substantially, and therefore one where temporal regimens, such as drug cycling and drug holidays may have great benefit.

Radiotherapy in the Era of Precision Medicine

Current predictors of radiation response are largely limited to clinical and histopathologic parameters, and extensive systematic analyses of the correlation between radiation sensitivity and genomic parameters remain lacking. In the era of precision medicine, the lack of -omic determinants of radiation response has hindered the personalization of radiation delivery to the unique characteristics of each patient׳s cancer and impeded the discovery of new therapies that can be administered concurrently with radiation therapy. The cataloging of the -omic determinants of radiation sensitivity of cancer has great potential in enhancing efficacy and limiting toxicity in the context of a new approach to precision radiotherapy. Herein, we review concepts and data that contribute to the delineation of the radiogenomic landscape of cancer.

Case study: patient-derived clear cell adenocarcinoma xenograft model longitudinally predicts treatment response

There has been little progress in the use of patient-derived xenografts (PDX) to guide individual therapeutic strategies. In part, this can be attributed to the operational challenges of effecting successful engraftment and testing multiple candidate drugs in a clinically workable timeframe. It also remains unclear whether the ancestral tumor will evolve along similar evolutionary trajectories in its human and rodent hosts in response to similar selective pressures (i.e., drugs). Herein, we combine a metastatic clear cell adenocarcinoma PDX with a timely 3 mouse x 1 drug experimental design, followed by a co-clinical trial to longitudinally guide a patient’s care. Using this approach, we accurately predict response to first- and second-line therapies in so far as tumor response in mice correlated with the patient’s clinical response to first-line therapy (gemcitabine/nivolumab), development of resistance and response to second-line therapy (paclitaxel/neratinib) before these events were observed in the patient. Treatment resistance to first-line therapy in the PDX is coincident with biologically relevant changes in gene and gene set expression, including upregulation of phase I/II drug metabolism (CYP2C18, UGT2A, and ATP2A1) and DNA interstrand cross-link repair (i.e., XPA, FANCE, FANCG, and FANCL) genes. A total of 5.3% of our engrafted PDX collection is established within 2 weeks of implantation, suggesting our experimental designs can be broadened to other cancers. These findings could have significant implications for PDX-based avatars of aggressive human cancers.

Modeling cellular response in large-scale radiogenomic databases to advance precision radiotherapy

Radiotherapy is integral to the care of a majority of cancer patients. Despite differences in tumor responses to radiation (radioresponse), dose prescriptions are not currently tailored to individual patients. Recent large-scale cancer cell line databases hold the promise of unravelling the complex molecular arrangements underlying cellular response to radiation, which is critical to novel predictive biomarker discovery. Here, we present RadioGx, a computational platform for integrative analyses of radioresponse using radiogenomic databases. We first used RadioGx to investigate the robustness of radioresponse assays and indicators. We then combined radioresponse and genome-wide molecular data with established radiobiological models to predict molecular pathways that are relevant for individual tissue types and conditions. We also applied RadioGx to pharmacogenomic data to identify several classes of drugs whose effects correlate with radioresponse. RadioGx provides a unique computational toolbox to advance preclinical research for radiation oncology and precision medicine.

Consequences of mutant TET2 on clonality and subclonal hierarchy

Somatic mutations in TET2 are common in myelodysplastic syndromes (MDS), myeloproliferative, and overlap syndromes. TET2 mutant (TET2MT) clones are also found in asymptomatic elderly individuals, a condition referred to as clonal hematopoiesis of indeterminate potential (CHIP). In various entities of TET2MT neoplasia, we examined the phenotype in relation to the strata of TET2 hits within the clonal hierarchy. Using deep sequencing, 1781 mutations were found in 1205 of 4930 patients; 40% of mutant cases were biallelic. Hierarchical analysis revealed that of TET2MT cases >40% were ancestral, e.g., representing 8% of MDS. Higher (earlier) TET2 lesion rank within the clonal hierarchy (greater clonal burden) was associated with impaired survival. Moreover, MDS driven by ancestral TET2MT is likely derived from TET2MT CHIP with a penetrance of ~1%. Following ancestral TET2 mutations, individual disease course is determined by secondary hits. Using multidimensional analyses, we demonstrate how hits following the TET2 founder defect induces phenotypic shifts toward dysplasia, myeloproliferation, or progression to AML. In summary, TET2MT CHIP-derived MDS is a subclass of MDS that is distinct from de novo disease.

Transcriptomic and protein analysis of small cell bladder cancer (SCBC) identifies prognostic biomarkers and DLL3 as a relevant therapeutic target

Purpose: Transcriptomic profiling can shed light on the biology of small-cell bladder cancer (SCBC), nominating biomarkers, and novel therapeutic targets. Experimental Design: Sixty-three patients with SCBC had small-cell histology confirmed and quantified by a genitourinary pathologist. Gene expression profiling was performed for 39 primary tumor samples, 1 metastatic sample, and 6 adjacent normal urothelium samples (46 total) from the same cohort. Protein levels of differentially expressed therapeutic targets, DLL3 and PDL1, and also CD56 and ASCL1, were confirmed by IHC. A SCBC PDX model was utilized to assess in vivo efficacy of DLL3-targeting antibody–drug conjugate (ADC). Results: Unsupervised hierarchical clustering of 46 samples produced 4 clusters that correlated with clinical phenotypes. Patients whose tumors had the most “normal-like” pattern of gene expression had longer overall survival (OS) compared with the other 3 clusters while patients with the most “metastasis-like” pattern had the shortest OS (P = 0.047). Expression of DLL3, PDL1, ASCL1, and CD56 was confirmed by IHC in 68%, 30%, 52%, and 81% of tissue samples, respectively. In a multivariate analysis, DLL3 protein expression on >10% and CD56 expression on >30% of tumor cells were both prognostic of shorter OS (P = 0.03 each). A DLL3-targeting ADC showed durable antitumor efficacy in a SCBC PDX model. Conclusions: Gene expression patterns in SCBC are associated with distinct clinical phenotypes ranging from more indolent to aggressive disease. Overexpression of DLL3 mRNA and protein is common in SCBC and correlates with shorter OS. A DLL3-targeted ADC demonstrated in vivo efficacy superior to chemotherapy in a PDX model of SCBC.