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 Δ(4)-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 5ß-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 5ß-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.

Integrative analysis of the zinc finger transcription factor Lame duck in the Drosophila myogenic gene regulatory network.

Contemporary high-throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs, and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including ChIP sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF cooccupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous cooccupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide insights into the transcriptional codes regulating muscle gene expression and offer a generalizable approach for similar studies in other systems.

Determining risk and predictors of head and neck cancer treatment-related lymphedema: A clinicopathologic and dosimetric data mining approach using interpretable machine learning and ensemble feature selection.

Background and purpose: The ability to determine the risk and predictors of lymphedema is vital in improving the quality of life for head and neck (HN) cancer patients. However, selecting robust features is challenging due to the multicollinearity and high dimensionality of radiotherapy (RT) data. This study aims to overcome these challenges using an ensemble feature selection technique with machine learning (ML). Materials and methods: Thirty organs-at-risk, including bilateral cervical lymph node levels, were contoured, and dose-volume data were extracted from 76 HN treatment plans. Clinicopathologic data was collected. Ensemble feature selection was used to reduce the number of features. Using the reduced features as input to ML and competing risk models, internal and external lymphedema prediction capability was evaluated with the ML models, and time to lymphedema event and risk stratification were estimated using the risk models. Results: Two ML models, XGBoost and random forest, exhibited robust prediction performance. They achieved average F1-scores and AUCs of 84 ± 3.3 % and 79 ± 11.9 % (external lymphedema), and 64 ± 12 % and 78 ± 7.9 % (internal lymphedema). Predictive ML and risk models identified common predictors, including bulky node involvement, high dose to various lymph node levels, and lymph nodes removed during surgery. At 180 days, removing 0-25, 26-50, and > 50 lymph nodes increased external lymphedema risk to 72.1 %, 95.6 %, and 57.7 % respectively (p = 0.01). Conclusion: Our approach, involving the reduction of HN RT data dimensionality, resulted in effective ML models for HN lymphedema prediction. Predictive dosimetric features emerged from both predictive and competing risk models. Consistency with clinicopathologic features from other studies supports our methodology.

Multivalent state transitions shape the intratumoral composition of small cell lung carcinoma.

Studies to date have not resolved how diverse transcriptional programs contribute to the intratumoral heterogeneity of small cell lung carcinoma (SCLC), an aggressive tumor associated with a dismal prognosis. Here, we identify distinct and commutable transcriptional states that confer discrete functional attributes in individual SCLC tumors. We combine an integrative approach comprising the transcriptomes of 52,975 single cells, high-resolution measurement of cell state dynamics at the single-cell level, and functional and correlative studies using treatment naïve xenografts with associated clinical outcomes. We show that individual SCLC tumors contain distinctive proportions of stable cellular states that are governed by bidirectional cell state transitions. Using drugs that target the epigenome, we reconfigure tumor state composition in part by altering individual state transition rates. Our results reveal new insights into how single-cell transition behaviors promote cell state equilibrium in SCLC and suggest that facile plasticity underlies its resistance to therapy and lethality.

Investigation of brachial plexus dose that exceeds RTOG constraints for apical lung tumors treated with four- or five-fraction stereotactic body radiation therapy.

PURPOSE/OBJECTIVESS: We sought to determine the rate of brachial plexopathy (BPX) in patients exceeding RTOG dose constraints for treatment of apical lung tumors. MATERIALS/METHODS: Patients with apical lung tumors treated with four- or five-fraction SBRT were identified from a prospective registry. Dosimetric data were obtained for ipsilateral subclavian vein (SCV) and anatomic BP (ABP) contours. Cumulative equivalent dose in 2 Gy equivalents (EQD2) was calculated for the SCV contour in patients with a history of prior ipsilateral RT. Five-fraction SBRT RTOG constraints of D0.03cc ≤32.0 Gy and D3cc ≤30.0 Gy were used. BPX was graded according to Common Terminology Criteria for Adverse Events 3.0. RESULTS: A total of 64 patients met inclusion criteria. Median follow-up was 21 months. Six patients (9.4%) had prior ipsilateral conventional fractionated RT with varying degrees of overlap with subsequent SBRT field. Eleven patients without prior ipsilateral RT exceeded D0.03cc ≤32.0 Gy to SCV (mean 43.8 Gy ± 5.8). No BPX was observed in these patients. Out of the six patients who had prior ipsilateral RT, three patients exceeded D0.03cc ≤32.0 Gy to SCV (44.2 Gy ± 11.3), with two of these patients developing Grade 2 BPX within one year of SBRT. The EQD2 cumulative maximum point dose to BP was 122.6 Gy and 184.7 Gy for the two patients who developed Grade 2 BPX. The D0.03cc was >10 Gy higher to the ABP contour than the SCV contour in 14 patients. CONCLUSION: Without a history of prior ipsilateral RT, no BPX was observed at 21 month follow-up in 11 patients who exceeded the RTOG five-fraction BP constraint. This observation is hypothesis generating and more experience with longer follow-up is necessary to validate these findings. For tumors located in close proximity to apical structures, there was substantial variation in dose between the ABP and SCV contours.

Intensity modulated radiation therapy with pulsed reduced dose rate as a reirradiation strategy for recurrent central nervous system tumors: An institutional series and literature review.

BACKGROUND: Pulsed reduced dose rate (PRDR) is a reirradiation technique that potentially overcomes volume and dose limitations in the setting of previous radiation therapy for recurrent central nervous system (CNS) tumors. Intensity modulated radiation therapy (IMRT) has not yet been reported as a PRDR delivery technique. We reviewed our IMRT PRDR outcomes and toxicity and reviewed the literature of available PRDR series for CNS reirradiation. METHODS AND MATERIALS: A total of 24 patients with recurrent brain tumors received PRDR reirradiation between August 2012 and December 2014. Twenty-two patients were planned with IMRT. Linear accelerators delivered an effective dose rate of 0.0667 Gy/minute. Data collected included number of prior interventions, diagnosis, tumor grade, radiation therapy dose and fractionation, normal tissue dose, radiation therapy planning parameters, time to progression, overall survival, and adverse events. RESULTS: The median time to PRDR from completion of initial radiation therapy was 47.8 months (range, 11-389.1 months). The median PRDR dose was 54 Gy (range, 38-60 Gy). The mean planning target volume was 369.1 ± 177.9 cm3. The median progression-free survival and 6-month progression-free survival after PRDR treatment was 3.1 months and 31%, respectively. The median overall survival and 6-month overall survival after PRDR treatment was 8.7 months and 71%, respectively. Fifty percent of patients had ≥4 chemotherapy regimens before PRDR. Toxicity was similar to initial treatment, including no cases of radiation necrosis. CONCLUSION: IMRT PRDR reirradiation is a feasible and appropriate treatment strategy for large volume recurrent CNS tumors resulting in acceptable overall survival with reasonable toxicity in our patients who were heavily pretreated. Prospective studies are necessary to determine the optimal timing of PRDR reirradiation, the role of concurrent systemic agents, and the ideal patient population who would receive the maximal benefit from this treatment approach. SUMMARY: Intensity modulated radiation therapy (IMRT) has not yet been reported as a pulsed reduced dose rate (PRDR) delivery technique for recurrent brain tumors and may allow for safe and comprehensive reirradiation for large volume tumors. We reviewed our IMRT PRDR outcomes and toxicity and reviewed the literature of available PRDR series for recurrent central nervous system tumors. We conclude that IMRT PRDR reirradiation is a feasible and appropriate treatment strategy for large volume recurrent brain tumors resulting in acceptable overall survival with reasonable toxicity in our patients who were heavily pretreated.

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 patient's 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.