A multi-ancestry cerebral cortex transcriptome-wide association study identifies genes associated with smoking behaviors.

Transcriptome-wide association studies (TWAS) have provided valuable insight in identifying genes that may impact cigarette smoking. Most of previous studies, however, mainly focused on European ancestry. Limited TWAS studies have been conducted across multiple ancestries to explore genes that may impact smoking behaviors. In this study, we used cis-eQTL data of cerebral cortex from multiple ancestries in MetaBrain, including European, East Asian, and African samples, as reference panels to perform multi-ancestry TWAS analyses on ancestry-matched GWASs of four smoking behaviors including smoking initiation, smoking cessation, age of smoking initiation, and number of cigarettes per day in GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Multiple-ancestry fine-mapping approach was conducted to identify credible gene sets associated with these four traits. Enrichment and module network analyses were further performed to explore the potential roles of these identified gene sets. A total of 719 unique genes were identified to be associated with at least one of the four smoking traits across ancestries. Among those, 249 genes were further prioritized as putative causal genes in multiple ancestry-based fine-mapping approach. Several well-known smoking-related genes, including PSMA4, IREB2, and CHRNA3, showed high confidence across ancestries. Some novel genes, e.g., TSPAN3 and ANK2, were also identified in the credible sets. The enrichment analysis identified a series of critical pathways related to smoking such as synaptic transmission and glutamate receptor activity. Leveraging the power of the latest multi-ancestry GWAS and eQTL data sources, this study revealed hundreds of genes and relevant biological processes related to smoking behaviors. These findings provide new insights for future functional studies on smoking behaviors.

Ring geometric effect on the performance of AlGaN-based deep-ultraviolet light-emitting diodes.

In this study, we fabricated and characterized various parallel flip-chip AlGaN-based deep-ultraviolet (DUV) micro-ring LEDs, including changes in ring dimensions as well as the p-GaN-removed region widths at the outer micro-ring, respectively (PRM LEDs). It is revealed that the LED chips with smaller mesa withstand higher current density and deliver considerably higher light output power density (LOPD), under the same proportion of the hole to the entire mesa column (before it is etched into ring) within the limits of dimensions. However, as the ring-shaped mesa decreases, the LOPD begins to decline because of etching damage. Subsequently, at the same external diameter, the optical performance of micro-ring LEDs with varied internal diameters is studied. Meanwhile, the influence of different structures on light extraction efficiency (LEE) is studied by employing a two-dimensional (2D)-finite-difference time-domain (FDTD) method. In addition, the expand of the p-GaN-removed region at the outer micro-ring as well as the corresponding effective light emission region have some influence to LOPD. The PRM-23 LED (with an external diameter of 90 µm, an internal diameter of 22 µm, and a p-GaN-removed region width of 8 µm) has an LOPD of 53.36 W/cm2 with a current density of 650 A/cm2, and an external quantum efficiency (EQE) of 6.17% at 5 A/cm2. These experimental observations provide a comprehensive understanding of the optical and electrical performance of DUV micro-LEDs for future applications.

Meal timing of dietary total antioxidant capacity and its association with all-cause, CVD and cancer mortality: the US national health and nutrition examination survey, 1999-2018.

BACKGROUND: The association of the meal timing of dietary total antioxidant capacity (DAC) with mortality is unclear. We aimed to investigate the association between the meal timing of DAC and all-cause, cardiovascular disease (CVD), and cancer mortality in general adult populations. METHODS: A total of 56,066 adults who participated in the US National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 were recruited for this study. Dietary intake (quantity and timing) was evaluated by nonconsecutive 24-h dietary recalls. The main exposure variables were the DAC across three meals (total, breakfast, lunch, and dinner; without coffee) and the difference between dinner and breakfast DAC (Δ = dinner-breakfast; without coffee). The outcomes were all-cause, CVD, and cancer mortality. The adjusted hazard ratios [aHRs] and 95% confidence intervals [CI] were imputed by Cox proportional hazards regression. RESULTS: Among the 56,066 participants, there were 8566 deaths from any cause, including 2196 from CVD and 1984 from cancer causes. Compared to participants in the lowest quintiles of the total DAC, those in the highest quintiles had 34% and 27% decreased risks of all-cause and CVD mortality, respectively (all-cause mortality: aHRs 0.66 [95% CI 0.57-0.76]; CVD mortality: aHRs 0.73 [95% CI 0.57-0.94]). More importantly, participants in the highest quintiles of the dinner DAC, but not those in that of breakfast or lunch, had a 24% decrease in all-cause mortality (aHRs 0.76 [95% CI 0.67-0.87]) compared with those in the lowest quintiles. Inverse associations were further confirmed for Δ DAC (aHRs 0.84 [95% CI 0.74-0.96]). Above associations did not change when including DAC from snacks or tea. Mediation analysis showed that the total associations of total, dinner or Δ DACs with reduced all-cause mortality were 24%, 13% and 6%, respectively, mediated by serum CRP. Additionally, all-cause mortality was decreased by 7% in models replacing 10% breakfast DAC (aHRs 0.93 [95% CI 0.9-0.97]) with an equivalent proportion of dinner DAC. For cancer mortality, no statistical significance was detected in the adjusted models. CONCLUSIONS: The findings emphasize the putative beneficial relationship of a diet rich in antioxidants and meal timing on serum CRP and all-cause mortality.

Flying enhances viewing from above bias on ambiguous visual stimuli.

The human spatial orientation system is well designed on the ground but is imperfect in the aeronautical three-dimensional (3D) environment. However, human perception systems perform Bayesian statistics based on encountered environments and form shortcuts to improve perceptual efficiency. It is unknown whether our perception of spatial orientation is modified by flying experience and forms perceptual biases. The current study tested pilot perceptual biases on ambiguous visual stimuli, the bistable point-light walkers, and found that flying experiences increased the pilot's tendency to perceive himself as higher than the target and the target as farther away from them. Such perceptual effects due to flight are likely to be attributed to experience of variable vestibular state in a higher position in 3D space, rather than the experience of a higher viewpoint. Our findings suggest that flying experience will modifies our visual perceptual biases, and that more attention should be paid to the enhanced viewing from above bias when flying to avoid overestimating altitude or viewing angle when the visual conditions are ambiguous.

Inverse computational ghost imaging for image encryption.

Computer-generated random patterns and bucket detection are two key characteristics of computational ghost imaging (GI), which offer it a potential application in optical encryption. Here, we propose an inverse computational GI scheme, in which bucket signals are firstly selected and then random patterns are calculated correspondingly. Different GI reconstruction algorithms are used to test the inverse computational GI, and the relationship between imaging quality and error ratio factor is discussed as well. Compared with computational GI, our inverse one not only has disguised bucket signals but also provides an opportunity to combine with other cryptographies, both of which enrich the GI-based encryption process and enhance the security simultaneously.

Polarization-Controlled Plasmonic Structured Illumination.

Structured light in the subwavelength scale is important for a broad range of applications ranging from lithography to imaging. Of particular importance is the ability to dynamically shift the pattern of the fields, which has led to the development of structured illumination microscopy. Further extension of structured illumination to plasmonic systems has enabled imaging beyond diffraction limit. However, structured illumination usually requires complicated optical setups entailing moving mechanical parts. Here a polarization tunable structured plasmonic field (SPF) is proposed and experimentally demonstrated. The SPF is formed by surface plasmon interference (SPI) generated by a fishbone-shaped metasurface on a thin gold film. Importantly, the SPF can be continuously shifted by merely varying the linear polarization state of an incident beam. The precise control of the fringes of structured illumination and elimination of mechanical control will have great potential in subdiffractional imaging for practical applications.

Identification immunophenotyping of lung adenocarcinomas based on the tumor microenvironment.

The tumor immune microenvironment is heterogeneous, and its impact on treatment responses is not well understood. It is still a challenge to analyze the interaction between malignant cells and the tumor microenvironment to apply suitable immunotherapy in lung adenocarcinoma. We performed the nonnegative matrix factorization method to 513 messenger RNA expression profiles of lung adenocarcinomas (LUADs) from The Cancer Genome Atlas (TCGA) to obtain an immune-related expression pattern. Subsequently, we characterized the immune-related gene signatures and clinical and survival characteristics. We used 576 patients from Gene Expression Omnibus to confirm our findings. Of the patients in the training cohort, 51% had a high immune enrichment score, high expression of immune cell signaling, cytolytic activity, and interferon (IFN)-related signatures (all P < .05). We denoted these as the Immune Class. We further subdivided the Immune Class into two subclasses based on the tumor microenvironment. These were denoted the Active Immune Class and Exhausted Immune Class. The former showed significant IFN, T-cells, M1 macrophage signatures, and better prognosis (all P < .05), while the latter presented an exhausted immune response with activated stromal enrichment, M2 macrophage signatures, and immunosuppressive factors such as WNT/transforming growth factor-ß (all P < .05). Furthermore, we predicted the response of our immunophenotypes to immunological checkpoint inhibitors (P < .05). Our findings provide a novel insight into the immune-related state of LUAD and can identify the patients who will be receptive to suitable immunotherapeutic treatments.

NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data.

Untargeted metabolomics based on liquid chromatography-mass spectrometry is affected by nonlinear batch effects, which cover up biological effects, result in nonreproducibility, and are difficult to be calibrate. In this study, we propose a novel deep learning model, called Normalization Autoencoder (NormAE), which is based on nonlinear autoencoders (AEs) and adversarial learning. An additional classifier and ranker are trained to provide adversarial regularization during the training of the AE model, latent representations are extracted by the encoder, and then the decoder reconstructs the data without batch effects. The NormAE method was tested on two real metabolomics data sets. After calibration by NormAE, the quality control samples (QCs) for both data sets gathered most closely in a PCA score plot (average distances decreased from 56.550 and 52.476 to 7.383 and 14.075, respectively) and obtained the highest average correlation coefficients (from 0.873 and 0.907 to 0.997 for both). Additionally, NormAE significantly improved biomarker discovery (median number of differential peaks increased from 322 and 466 to 1140 and 1622, respectively). NormAE was compared with four commonly used batch effect removal methods. The results demonstrated that using NormAE produces the best calibration results.

Dual-channel sensing by combining geometric and dynamic phases with an ultrathin metasurface.

Ultrathin metasurfaces consisting of subwavelength anisotropic plasmonic resonators with spatially variant orientations are capable of generating local geometric phase profiles for circular polarizations (CP) and can be used for multiplexing of electromagnetic waves. As the geometric phase solely depends on the orientation of dipole antennas, the phase profiles cannot be changed dynamically with external environment once the structure is fabricated. Here, by incorporating geometric phase and resonance-induced dynamic phase in a monolayer of nano gold antennas, we show that phase profiles of different spin components can vary independently through modification of the external environment. Specifically, the intensities of the + 1 and -1 order diffracted waves vary asymmetrically with the refractive index of surrounding media, forming a dual-channel sensing system. Our dual-channel sensing method exhibits very high signal-to-noise ratio and stability for sensing of liquid, monomolecular layer and even nanoscale motion, which will have potential applications in various fields, including biosensing, precision manufacturing, monitoring of environment, and logic operations.

Integrated dual-channel sensing utilizing polarized dissimilation based on photonic spin-orbit interaction.

An integrated dual-channel sensing method utilizing polarized dissimilation is investigated with an appropriately designed plasmonic metasurface. By assembling two different kinds of nano-gold antennas to constitute a periodic array, the phase of diffraction fields contains both spin-dependent geometric phase and resonance-dependent dynamic phase components. Accurate control over the superposition of orthogonal spin components utilizing strong photonic spin-orbit interaction of metasurface leads to dissimilar response of different diffraction orders. The simulation shows that the linear polarization of ±1 diffraction orders rotate in the reverse direction (±19°) with the refractive index variation (1.3-1.5). The sensing method exhibits an extremely high signal-to-noise ratio and stability.

Sites of distant metastases and overall survival in ovarian cancer: A study of 1481 patients.

OBJECTIVE: To assess the association between patterns of distant metastases and overall survival in metastatic ovarian cancer and identify prognostic factors for site-specific distant metastases. METHODS: Data was obtained from the SEER database between 2010 and 2014. Univariate and multivariate Cox proportional hazard models were used to identify variables associated with overall survival. Survival times between different groups were compared using Kaplan-Meier analysis and log-rank tests. RESULTS: We analyzed 1481 patients. The most common distant metastatic site was liver, followed by distant lymph nodes, lung, bone, and brain. The site of distant metastases was an independent prognostic factor for overall survival. Using liver metastases as reference, overall survival was lower for lung metastases (p = 0.0297) and higher for distant lymph node metastases (p = 0.0006). Using distant lymph nodes as reference, distant metastases to the liver (p = 0.0006), lung (p < 0.0001), brain (p = 0.0455), and bone (p = 0.0138) were all associated with worse overall survival. The number of metastatic sites did not affect overall survival. We also found that surgery and chemotherapy affected overall survival for patients with distant lymph node metastases only; age, histological subtype, surgery, and chemotherapy affected overall survival for patients with liver metastases only, while histological subtype and chemotherapy affected overall survival for patients with lung metastases only. CONCLUSIONS: The site of distant metastases affected overall survival in metastatic ovarian cancer. Patients with specific distant metastatic sites should receive special treatment and management. The identified prognostic factors can help clinician evaluate the prognosis for ovarian cancer patients with distant metastases.

Night eating in timing, frequency, and food quality and risks of all-cause, cancer, and diabetes mortality: findings from national health and nutrition examination survey.

OBJECTIVE: To investigate the association of timing, frequency, and food quality of night eating with all-cause, cancer, and diabetes mortality. METHODS: This study included 41,744 participants from the US National Health and Nutrition Examination Survey (2002-2018). Night eating information was collected by 24-h dietary recall and the exposures were timing, frequency, and food quality of night eating. Food quality was assessed by latent class analysis. The outcomes were all-cause, cancer, and diabetes mortality, which were identified by the National Death Index and the International Classification of Diseases 10th Revision. Adjusted hazard ratios [aHR] with 95% confidence intervals [CI] were computed by Cox regression. RESULTS: During a median follow-up of 8.7 years, 6066 deaths were documented, including 1381 from cancer and 206 from diabetes. Compared with no night eating (eating before 22:00), the later timing of night eating was associated with higher risk of all-cause and diabetes mortality (each P-trend <0.05) rather than cancer mortality, with the highest risk of eating being 00:00-1:00 (aHR 1.38, 95% CI 1.02-1.88) and being 23:00-00:00 (aHR 2.31, 95% CI 1.21-4.40), respectively. However, the increased risks were not observed for 22:00-23:00. Likewise, one time or over frequency of night eating was associated with higher all-cause and diabetes mortality (each P < 0.05). That risks were further observed in high-dietary-energy-density group of night eating (all-cause mortality: aHR 1.21 [95% CI 1.06-1.38]; diabetes mortality: aHR 1.97 [95% CI 1.13-3.45]), but not in low-dietary-energy-density group. Finally, correlation analysis found positive associations of night eating with glycohemoglobin, fasting glucose, and OGTT. CONCLUSIONS: Night eating was associated with increased all-cause, cancer and diabetes mortality; however, reduction of excess mortality risk was observed when eating before 23:00 or low-dietary-energy-density foods.

Investigation on the Epidemic Situation of Epidemic Hemorrhagic Fever in an Island Industrial Park in Zhoushan, China.

Objective: To investigate the epidemic factors of hemorrhagic fever with renal syndrome (HFRS) and compare the S and M gene sequences of hantavirus (HV) between rodents and the infected cases. Methods: Detailed epidemiological investigations were conducted on the cases' working and living areas. Captured rodents were classified by night trapping method, and their lungs and blood were collected for virus carriage detection after aseptic dissection. Viral S and M fragments of HV RNA were amplified and sequenced from positive samples of cases and mice, and their homology was analyzed. Results: After reconstruction, the geographic and living environment changed significantly, altering rodent behaviors. The industrial park, characterized by high population density, poor living conditions, and frequent contact of rodent (feces) and humans, had a high rodent density and HV virus infection ratio. Four workers infected with HV were positive for anti-HV immunoglobulin G (IgG) and IgM. Among the positive samples, HV RNA was detected in all two cases, and four Rattus norvegicus specimens were Seoul type HV S3 subtype. The virus had the closest relationship with Rod/2012/QHD/4/Gc (Hebei, China) and RuianRn180 (Zhejiang, China), with the 100% homology of M gene segment. The homology of viral S gene segment exhibited the closest relationship with the Jiangxi isolated JiangxiXinjianRn-09-2011, ranging from 99.6% to 99.8%. Conclusion: The HV sequencing showed a strong epidemiological relationship between the cases and host rodents. Improving living environmental health conditions, administering HFRS vaccine, and reducing rodent density and human-rodent contact can mitigate the risk of HFRS.

Multi-omics and single cell characterization of cancer immunosenescence landscape.

Cellular senescence (CS) is closely related to tumor progression. However, the studies about CS genes across human cancers have not explored the relationship between cancer senescence signature and telomere length. Additionally, single-cell analyses have not revealed the evolutionary trends of malignant cells and immune cells at the CS level. We defined a CS-associated signature, called "senescence signature", and found that patients with higher senescence signature had worse prognosis. Higher senescence signature was related to older age, higher genomic instability, longer telomeres, increased lymphocytic infiltration, higher pro-tumor immune infiltrates (Treg cells and MDSCs), and could predict responses to immune checkpoint inhibitor therapy. Single-cell analysis further reveals malignant cells and immune cells share a consistent evolutionary trend at the CS level. MAPK signaling pathway and apoptotic processes may play a key role in CS, and senescence signature may effectively predict sensitivity of MEK1/2 inhibitors, ERK1/2 inhibitors and BCL-2 family inhibitors. We also developed a new CS prediction model of cancer survival and established a portal website to apply this model ( https://bio-pub.shinyapps.io/cs_nomo/ ).

Circulating insulin-like growth factor-1 and brain health: Evidence from 369,711 participants in the UK Biobank.

BACKGROUND: The effects of insulin-like growth factor-1 (IGF-1) deficiency on cognitive decline have been consistently reported in animal studies, but the relationship between IGF-1 and human brain health remains controversial. Our study aimed to investigate the associations of serum IGF-1 concentrations with some brain-related disorders and neuroimaging features. METHODS: This prospective study included 369,711 participants (55.8 ± 8.1 years) from the UK biobank who had serum IGF-1 measured and were free from brain-related disorders of interest - dementia, stroke, and Parkinson's disease (PD) - at enrollment (2006-2010). Restricted cubic splines and Cox proportional hazards models were used to detect the associations between IGF-1 concentrations and brain-related diseases. In addition, general linear regressions were applied to explore the relationship between IGF-1 concentrations and neuroimaging features (volumes of white matter, grey matter, and hippocampus and white matter hyperintensity) among a sub-sample of 36,458 participants with magnetic resonance imaging data collected since 2014. RESULTS: During a median follow-up of 12.6 years, a total of 4,857 dementia, 6,240 stroke, and 2,116 PD cases were documented. The dose-response analyses yielded U-shaped relationships between IGF-1 concentrations and risks of dementia and stroke (P < 0.001 for non-linearity), with the lowest risks at 18 nmol/L and 26 nmol/L, respectively. A positive linear relationship was observed between IGF-1 concentrations and risk of PD (P = 0.163 for non-linearity). Moreover, neuroimaging analyses showed that higher IGF-1 concentrations were associated with greater volumes of white matter (ß = 2.98 × 10-4, P < 0.001) and hippocampus (ß = 3.37 × 10-4, P = 0.002) and smaller white matter hyperintensity (ß = -3.12 × 10-3, P < 0.001). CONCLUSIONS: Apart from the diverse associations with neuroimaging features, both low and high IGF-1 concentrations are associated with increased risks of dementia and stroke and higher IGF-1 concentrations are linked to a higher risk of PD, highlighting the potential of IGF-1 as a biomarker for risk stratification of brain health.

Association of dietary total antioxidant capacity and its distribution across three meals with all-cause, cancer, and non-cancer mortality among cancer survivors: the US National Health and Nutrition Examination Survey, 1999-2018.

The effect of the antioxidant capacity of diet and its distribution across three meals on mortality risk among cancer patients remains unexplored. We aimed to prospectively investigate the association of dietary total antioxidant capacity (DAC) and its distribution across three meals with all-cause, cancer, and noncancer mortality among cancer survivors. We included 5,009 patients with cancer from the National Health and Nutrition Examination Survey conducted between 1999 and 2018. The adjusted hazard ratio (aHR) was estimated using the survey-weighted Cox proportional hazards model. During a median follow-up of 7.9 years, 1811 deaths, including 575 cancer-related deaths, were recorded. Among cancer survivors, compared with participants in the lowest quartile of total DAC from three meals, those in the highest quartile had a 24% decreased risk of noncancer mortality (aHR = 0.76, 95% confidence interval [CI]: 0.60-0.92), but not of all-cause and cancer mortality (each p trend >0.1). However, this association became insignificant for total DAC after excluding dinner DAC. In addition, higher dinner DAC rather than breakfast or lunch DAC was associated with a 21% lower risk of all-cause mortality (aHR = 0.79, 95% CI: 0.65-0.98) and 28% lower risk of noncancer mortality (aHR = 0.72, 95% CI: 0.57-0.90). Similar associations were found for ΔDAC (dinner DAC - breakfast DAC) with noncancer mortality (aHR = 0.56, 95% CI: 0.38-0.83), but DAC was not associated with cancer mortality (p trend >0.3). Among cancer survivors, total DAC from three meals was associated with reduced noncancer mortality, with the primary effect attributable to increased DAC intake from dinner. Our findings emphasize that DAC consumption from dinner should be advocated to reduce mortality risk in cancer survivors.

A blood-based, metabolite and demographic characteristic markers panel for the diagnosis of Alzheimer's disease.

Aims: This work was designed to provide early diagnosis strategies for Alzheimer's disease (AD) based on the identification of blood metabolic biomarkers. Patients & methods: A total of 90 subjects aged 60 years or older were included in this study; 45 patients were assigned to the case group and control group, respectively. A total of 31 target metabolites were quantitatively analyzed by parallel reaction monitoring between the two groups. Results & conclusion: Three metabolites were screened out, including cystine, serine and alanine/sarcosine. Logistic regression and random forest analysis were used to establish AD diagnosis models, and the model combining metabolic biomarkers and demographic variables had higher detection efficiency (area under the curve = 0.869). A combination diagnostic model to provide a scientific reference for early screening and diagnosis of AD was constructed.

Active DHEA uptake in the prostate gland correlates with aggressive prostate cancer.

Strategies for patient stratification and early intervention are required to improve clinical benefits for patients with prostate cancer. Here, we found that active DHEA utilization in the prostate gland correlated with tumor aggressiveness at early disease stages, and 3ßHSD1 inhibitors were promising for early intervention. [3H]-labeled DHEA consumption was traced in fresh prostatic biopsies ex vivo. Active DHEA utilization was more frequently found in patients with metastatic disease or therapy-resistant disease. Genetic and transcriptomic features associated with the potency of prostatic DHEA utilization were analyzed to generate clinically accessible approaches for patient stratification. UBE3D, by regulating 3ßHSD1 homeostasis, was discovered to be a regulator of patient metabolic heterogeneity. Equilin suppressed DHEA utilization and inhibited tumor growth as a potent 3ßHSD1 antagonist, providing a promising strategy for the early treatment of aggressive prostate cancer. Overall, our findings indicate that patients with active prostatic DHEA utilization might benefit from 3ßHSD1 inhibitors as early intervention.

Celastrol recruits UBE3A to recognize and degrade the DNA binding domain of steroid receptors.

Strategies to degrade steroid receptors and their alternative splicing isoforms are critical for disease management. Here we report that celastrol recruited the ubiquitin ligase UBE3A and degraded androgen receptor (AR), AR-v7, and glucocorticoid receptor (GR) to suppress prostate cancer development. UBE3A was not an optimal endogenous AR ubiquitin ligase in mice and patients, but celastrol promoted the interaction between UBE3A and AR. Multiple domains of AR, including the DNA binding domain (DBD), were implicated into the UBE3A-AR interaction. Sharing a conserved DBD, GR, AR-v7, and other steroid receptors were recognized and degraded by UBE3A after celastrol treatment. Thus, celastrol suppressed prostate cancer cell proliferation more potently than enzalutamide. Modifying the carboxyl group of celastrol improved its anti-tumor activity. Together, our findings revealed that celastrol might be a potential molecular glue to enhance the interaction between UBE3A and steroid receptors to degrade multiple steroid receptors and splicing isoforms in prostate cancer, paving a way for further drug optimization and disease treatment.

Management of prostate cancer by targeting 3ßHSD1 after enzalutamide and abiraterone treatment.

Novel strategies for prostate cancer therapy are required to overcome resistance to abiraterone and enzalutamide. Here, we show that increasing 3ßHSD1 after abiraterone and enzalutamide treatment is essential for drug resistance, and biochanin A (BCA), as an inhibitor of 3ßHSD1, overcomes drug resistance. 3ßHSD1 activity increases in cell lines, biopsy samples, and patients after long-term treatment with enzalutamide or abiraterone. Enhanced steroidogenesis, mediated by 3ßHSD1, is sufficient to impair enzalutamide function. In patients, accelerated abiraterone metabolism results in a decline of plasma abiraterone as disease progresses. BCA inhibits 3ßHSD1 and suppresses prostate cancer development alone or together with abiraterone and enzalutamide. Daidzein, a BCA analog of dietary origin, is associated with higher plasma abiraterone concentrations and prevented prostate-specific antigen (PSA) increases in abiraterone-resistant patients. Overall, our results show that 3ßHSD1 is a promising target to overcome drug resistance, and BCA suppresses disease progression as a 3ßHSD1 inhibitor even after abiraterone and enzalutamide resistance.