Vitamin D Deficiency in the Acute Phase of Stroke May Predict Post-stroke Depression: A Systematic Review and Meta-Analysis.

OBJECTIVE: To conduct the association between vitamin D levels in the acute phase of stroke and post-stroke depression (PSD) in stroke patients. METHODS: Five international databases (PubMed, Web of Science, Embase, Ovid MEDLINE(R), Cochrane Library) and one Chinese database (Wanfang Data) were searched for observational studies in any language reporting on PSD and vitamin D levels tested in the acute phase of stroke in stroke patients from inception to May 2024. Data extraction and study quality assessment were conducted by two authors independently. Qualitative and quantitative analyses of data were performed. The meta-analysis was registered in the PROSPERO database (CRD42023398581). RESULTS: We included 7 studies containing 3537 participants in the systematic review and meta-analysis. All studies that met the inclusion and exclusion criteria were conducted in China. Vitamin D levels in the acute phase of stroke were lower in PSD patients compared with non-PSD patients (weighted mean difference = -14.97 nmol/L; 95% confidence interval = -19.54, -10.40). Stroke patients with vitamin D deficiency (<50 nmol/L) had an increased risk of PSD compared with stroke patients with vitamin D sufficiency (≥75 nmol/L) (odds ratio = 3.59; 95% confidence interval = 2.05, 6.27). However, the association between vitamin D insufficiency (50-75 nmol/L) and PSD were not statistically significant (odds ratio = 4.15; 95% confidence interval = 0.87, 19.78). CONCLUSION: Vitamin D deficiency in the acute phase of stroke may be a risk factor for PSD.

The value of electroencephalography features in the prognostic evaluation of large hemispheric infarction patients at different time intervals.

BACKGROUND: Large Hemispheric Infarction (LHI) is a devastating disease with high mortality. This study aimed to use electroencephalography (EEG) to evaluate the death risk of LHI patients and identify suitable evaluation time. METHODS: This study retrospectively collected clinical and EEG data from 73 LHI patients, dividing them into death and survival group at discharge. EEG data was classified as 1-5 days and 6-14 days after onset according to the time intervals of cerebral edema. Regression and receiver operator characteristic curve (ROC) analysis were applied to explore the impact of temporal changes in various EEG and clinical features on death. RESULTS: The areas under ROC curve (AUC) of death prediction for non-α frequency on non-infarct side at 6-14 days after onset was significantly higher than that at 1-5 days (p = 0.004). And there was no significant difference between the AUC of seizure activity for death prediction at 1-5 days and 6-14 days (p = 0.418). Multivariate regression analysis revealed that non-α frequency on non-infarct side and seizure activity at 6-14 days after onset were the independent risk factors for the death of LHI patients. Additionally, above two EEG features significantly improved the death predictive efficacy of clinical features in LHI patients with the integrated discrimination improvement index (IDI) of 0.174 (p = 0.015) and the net reclassification improvement (NRI) of 1.314 (p<0.001). CONCLUSIONS: Non-α frequency on non-infarct side and seizure activity were reliable indicators for death prediction. 6-14 days after onset was the better time window for death evaluation of LHI patients through EEG.

The associations of serum valine with mild cognitive impairment and Alzheimer's disease.

BACKGROUND: The introduction of metabolomics makes it possible to study the characteristic changes of peripheral metabolism in Alzheimer's disease (AD). Recent studies have found that the levels of valine are related to mild cognitive impairment (MCI) and AD. AIMS: This study aimed to further clarify the characteristics of valine levels in MCI and AD. METHODS: A total of 786 participants from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) cohort were selected to evaluate the relationships between serum valine and cerebrospinal fluid (CSF) biomarkers, brain structure (magnetic resonance imaging, MRI), cerebral glucose metabolism (18F-fluorodeoxyglucose-positron emission tomography, FDG-PET), and cognitive declines, through different cognitive subgroups. RESULTS: Serum valine was decreased in patients with AD compared with cognitive normal (CN) and stable MCI (sMCI), and in progressive MCI (pMCI) compared with CN. Serum valine was negatively correlated with CSF total tau (t-tau) and phosphorylated tau (p-tau) in pMCI. Serum valine significantly predicted conversion from MCI to AD. In addition, serum valine was related to the rate of change of cerebral glucose metabolism during the follow-up period in pMCI. CONCLUSIONS: Serum valine may be a peripheral biomarker of pMCI and AD, and its level predicts the progression of MCI to AD. Our study may help to reveal the metabolic changes during AD disease trajectory and its relationship to clinical phenotype.

Dynamic changes in microbial community structure in farming pond water and their effect on the intestinal microbial community profile in juvenile common carp (Cyprinus carpio L.).

Water quality parameter dynamics, gut, sediment and water bacteria communities were studied to understand the environmental influence on the gut microbial community of a new strain of Huanghe common carp. A total of 3,384,078 raw tags and 5105 OTUs were obtained for the gut, water and sediment bacteria. The water quality had a stronger influence on the water bacteria community than gut and sediment bacteria communities. The ambient water quality parameters also significantly influenced the water and sediment bacteria communities. Comparing the gut, sediment, and water microbial communities, a relationship was found among them. However, gut bacteria were more closely related to sediment bacterial communities than to water bacteria communities. The results showed that the top three bacterial taxa were identical in gut and sediment samples in the early days of rearing. Interestingly, bacterial communities in the carp gut, water, and sediment had different adaptabilities to variations in environmental factors.

Precoder and Decoder Co-Designs for Radar and Communication Spectrum Sharing.

The coexistence of radar and communication systems is necessary to facilitate new wireless systems and services due to the shortage of the useful radio spectrum. Moreover, changes in spectrum regulation will be introduced in which the spectrum is allocated in larger chunks and different radio systems need to share the spectrum. For example, 5G NR, LTE and Wi-Fi systems have to share the spectrum with S-band radars. Managing interference is a key task in coexistence scenarios. Cognitive radio and radar technologies facilitate using the spectrum in a flexible manner and sharing channel awareness between the two subsystems. In this paper, we propose a nullspace-based joint precoder-decoder design for coexisting multicarrier radar and multiuser multicarrier communication systems. The maximizing signal interference noise ratio (max-SINR) criterion and interference alignment (IA) constraints are employed in finding the precoder and decoder. By taking advantage of IA theory, a maximum degree of freedom upper bound for the K+1-radar-communication-user interference channel can be achieved. Our simulation studies demonstrate that interference can be practically fully canceled in both communication and radar systems. This leads to improved detection performance in radar and a higher rate in communication subsystems. A significant performance gain over a nullspace-based precoder-only design is also obtained.

Device-Free Human Identification Using Behavior Signatures in WiFi Sensing.

Wireless sensing can be used for human identification by mining and quantifying individual behavior effects on wireless signal propagation. This work proposes a novel device-free biometric (DFB) system, WirelessID, that explores the joint human fine-grained behavior and body physical signatures embedded in channel state information (CSI) by extracting spatiotemporal features. In addition, the signal fluctuations corresponding to different parts of the body contribute differently to the identification performance. Inspired by the success of the attention mechanism in computer vision (CV), thus, to extract more robust features, we introduce the spatiotemporal attention function into our system. To evaluate the performance, commercial WiFi devices are used for prototyping WirelessID in a real laboratory environment with an average accuracy of 93.14% and a best accuracy of 97.72% for five individuals.

Therapeutic targeting of BET bromodomain proteins in castration-resistant prostate cancer.

Men who develop metastatic castration-resistant prostate cancer (CRPC) invariably succumb to the disease. Progression to CRPC after androgen ablation therapy is predominantly driven by deregulated androgen receptor (AR) signalling. Despite the success of recently approved therapies targeting AR signalling, such as abiraterone and second-generation anti-androgens including MDV3100 (also known as enzalutamide), durable responses are limited, presumably owing to acquired resistance. Recently, JQ1 and I-BET762 two selective small-molecule inhibitors that target the amino-terminal bromodomains of BRD4, have been shown to exhibit anti-proliferative effects in a range of malignancies. Here we show that AR-signalling-competent human CRPC cell lines are preferentially sensitive to bromodomain and extraterminal (BET) inhibition. BRD4 physically interacts with the N-terminal domain of AR and can be disrupted by JQ1 (refs 11, 13). Like the direct AR antagonist MDV3100, JQ1 disrupted AR recruitment to target gene loci. By contrast with MDV3100, JQ1 functions downstream of AR, and more potently abrogated BRD4 localization to AR target loci and AR-mediated gene transcription, including induction of the TMPRSS2-ERG gene fusion and its oncogenic activity. In vivo, BET bromodomain inhibition was more efficacious than direct AR antagonism in CRPC xenograft mouse models. Taken together, these studies provide a novel epigenetic approach for the concerted blockade of oncogenic drivers in advanced prostate cancer.

A Deep-Learning Method for Radar Micro-Doppler Spectrogram Restoration.

Radio frequency interference, which makes it difficult to produce high-quality radar spectrograms, is a major issue for micro-Doppler-based human activity recognition (HAR). In this paper, we propose a deep-learning-based method to detect and cut out the interference in spectrograms. Then, we restore the spectrograms in the cut-out region. First, a fully convolutional neural network (FCN) is employed to detect and remove the interference. Then, a coarse-to-fine generative adversarial network (GAN) is proposed to restore the part of the spectrogram that is affected by the interferences. The simulated motion capture (MOCAP) spectrograms and the measured radar spectrograms with interference are used to verify the proposed method. Experimental results from both qualitative and quantitative perspectives show that the proposed method can mitigate the interference and restore high-quality radar spectrograms. Furthermore, the comparison experiments also demonstrate the efficiency of the proposed approach.

Analysis of Quasi-Zenith Satellite System Signal Acquisition and Multiplexing Characteristics in China Area.

On the basis of realizing regional navigation, the Quasi-Zenith Satellite System (QZSS) has advanced navigation function, which leads to the broadcasting of more signals in a single frequency of QZSS signals. Current signal transmission technology cannot solve this problem, so it is necessary to design a signal multiplexing method. The current QZSS satellite interface document does not disclose the multiplexing modulation method of the signal transmission, which has a certain impact on the acquisition of high-precision observation data and further data processing. The iGMAS (International GNSS Monitoring & Assessment System) Monitoring and Evaluation Center of the 54th Research Institute of China Electronics Technology Group Corporation has used the low-distortion data acquisition and processing platform and refined signal software receiving processing algorithm of the iGMAS to complete the signal acquisition and analysis of QZSS satellites. Analysis of the multiplexing and modulation method and signal characteristics for the QZSS has been carried out, which can provide a reference for the design and data processing of high-precision receivers.

Analysis of the Multiplexing Method of New System Navigation Signals of GPS III First Star L1 Frequency in China's Regional.

Compared with the previous GPS satellites, the first GPS III satellite adds a new civil signal L1C to the signal components of the L1 frequency in addition to the improvement of positioning accuracy, anti-interference ability, and service life. The selection and combination of signal modulation and multiplexing methods will affect the power ratio and phase relationship in the process of signal transmission. In the distribution of constellation of different modulation modes, the signal amplitudes of different signal constellation points will be affected by the nonlinear amplifiers of satellites. The analysis can assess its impact on navigation performance. The iGMAS monitoring and evaluation center of the 54th Research Institute of China Electronics Technology Group Corporation uses the low-distortion data acquisition and processing platform and refined signal software receiving processing algorithm of the iGMAS monitoring and evaluation center to complete the signal acquisition of the first satellite of GPS III over China, and processes accordingly for its signal modulation mode. Compared with the previous generation GPS of old system signals, it is found that the GPS signal of the new system not only adds the L1C frequency, but also the constant envelope multiplexing mode of the L1 frequency signal, and the power ratio of the internal signal components are also adjusted.

The mutational landscape of lethal castration-resistant prostate cancer.

Characterization of the prostate cancer transcriptome and genome has identified chromosomal rearrangements and copy number gains and losses, including ETS gene family fusions, PTEN loss and androgen receptor (AR) amplification, which drive prostate cancer development and progression to lethal, metastatic castration-resistant prostate cancer (CRPC). However, less is known about the role of mutations. Here we sequenced the exomes of 50 lethal, heavily pre-treated metastatic CRPCs obtained at rapid autopsy (including three different foci from the same patient) and 11 treatment-naive, high-grade localized prostate cancers. We identified low overall mutation rates even in heavily treated CRPCs (2.00 per megabase) and confirmed the monoclonal origin of lethal CRPC. Integrating exome copy number analysis identified disruptions of CHD1 that define a subtype of ETS gene family fusion-negative prostate cancer. Similarly, we demonstrate that ETS2, which is deleted in approximately one-third of CRPCs (commonly through TMPRSS2:ERG fusions), is also deregulated through mutation. Furthermore, we identified recurrent mutations in multiple chromatin- and histone-modifying genes, including MLL2 (mutated in 8.6% of prostate cancers), and demonstrate interaction of the MLL complex with the AR, which is required for AR-mediated signalling. We also identified novel recurrent mutations in the AR collaborating factor FOXA1, which is mutated in 5 of 147 (3.4%) prostate cancers (both untreated localized prostate cancer and CRPC), and showed that mutated FOXA1 represses androgen signalling and increases tumour growth. Proteins that physically interact with the AR, such as the ERG gene fusion product, FOXA1, MLL2, UTX (also known as KDM6A) and ASXL1 were found to be mutated in CRPC. In summary, we describe the mutational landscape of a heavily treated metastatic cancer, identify novel mechanisms of AR signalling deregulated in prostate cancer, and prioritize candidates for future study.

Fourier transform infrared spectroscopy microscopic imaging classification based on multifractal methods.

Multifractal analysis (MFA) based on generalized concepts of fractals has been applied to biological tissues composed of complex structures. In this paper, a new MFA methodology based on the neighborhood spatial correlation (NSC) is proposed for an extracting texture feature. NSC is used to extract spatial features, and the obtained spatial features are combined with spectral features of characteristic absorption peaks (CAPs) to promote more feature information. This spatial-spectral structure is used as a feature to differentiate cholesterol from Fourier transform infrared spectroscopy microscopic imaging of a rabbit artery by a support vector machine classifier. The dataset was collected between 4000 and 720 cm-1 on rabbit arteries as research objects. The experimental results show that the accuracy of the proposed spatial-spectral structure is higher than that of other multivariate analysis methods (PCA and 2DPCA). The NSC method, compared to the bottom interface method, new bottom interface method, variance method multi-weight method, and neighborhood spatial correlation method, could effectively reduce the influence of speckle noise, and the convergence rate of the weight factor q is not increased.

Transcriptome sequencing to detect gene fusions in cancer.

Recurrent gene fusions, typically associated with haematological malignancies and rare bone and soft-tissue tumours, have recently been described in common solid tumours. Here we use an integrative analysis of high-throughput long- and short-read transcriptome sequencing of cancer cells to discover novel gene fusions. As a proof of concept, we successfully used integrative transcriptome sequencing to 're-discover' the BCR-ABL1 (ref. 10) gene fusion in a chronic myelogenous leukaemia cell line and the TMPRSS2-ERG gene fusion in a prostate cancer cell line and tissues. Additionally, we nominated, and experimentally validated, novel gene fusions resulting in chimaeric transcripts in cancer cell lines and tumours. Taken together, this study establishes a robust pipeline for the discovery of novel gene chimaeras using high-throughput sequencing, opening up an important class of cancer-related mutations for comprehensive characterization.

Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 × 10(-16)). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.

Associations of Serum Isoleucine with Mild Cognitive Impairment and Alzheimer's Disease.

BACKGROUND: Advances in blood biomarker discovery have enabled the improved diagnosis and prognosis of Alzheimer's disease (AD). Most branched-chain amino acids, except isoleucine (Ile), are correlated with both mild cognitive impairment (MCI) and AD. Therefore, this study investigated the association between serum Ile levels and MCI/AD. METHODS: This study stratified 700 participants from the Alzheimer's Disease Neuroimaging Initiative database into four diagnostic groups: cognitively normal, stable MCI, progressive MCI, and AD. Analysis of covariance and chi-square analyses were used to test the demographic data. Receiver operating curve analyses were used to calculate the diagnostic accuracy of different biomarkers and were compared by MedCalc 20. Additionally, Cox proportional hazards models were used to measure the ability of serum Ile levels to predict disease conversion. Finally, a linear mixed-effects model was used to evaluate the associations between serum Ile levels and cognition, brain structure, and metabolism. RESULTS: Serum Ile concentration was decreased in AD and demonstrated significant diagnostic efficacy. The combination of serum Ile and cerebrospinal fluid (CSF) phosphorylated tau (P-tau) improved the diagnostic accuracy in AD compared to total tau (T-tau) alone. Serum Ile levels significantly predicted the conversion from MCI to AD (cutoff value of 78.3 µM). Finally, the results of this study also revealed a correlation between serum Ile levels and the Alzheimer's Disease Assessment Scale cognitive subscale Q4. CONCLUSIONS: Serum Ile may be a potential biomarker of AD. Ile had independent diagnostic efficacy and significantly improved the diagnostic accuracy of CSF P-tau in AD. MCI patients with a lower serum Ile level had a higher risk of progression to AD and a worse cognition assessment.

Frequency-Aware Divide-and-Conquer for Efficient Real Noise Removal.

Deep-learning-based approaches have achieved remarkable progress for complex real scenario denoising, yet their accuracy-efficiency tradeoff is still understudied, particularly critical for mobile devices. As real noise is unevenly distributed relative to underlay signals in different frequency bands, we introduce a frequency-aware divide-and-conquer strategy to develop a frequency-aware denoising network (FADN). FADN is materialized by stacking frequency-aware denoising blocks (FADBs), in which a denoised image is progressively predicted by a series of frequency-aware noise dividing and conquering operations. For noise dividing, FADBs decompose the noisy and clean image pairs into low-and high-frequency representations via a wavelet transform (WT) followed by an invertible network and recover the final denoised image by integrating the denoised information from different frequency bands. For noise conquering, the separated low-frequency representation of the noisy image is kept as clean as possible by the supervision of the clean counterpart, while the high-frequency representation combining the estimated residual from the successive FADB is purified under the corresponding accompanied supervision for residual compensation. Since our FADN progressively and pertinently denoises from frequency bands, the accuracy-efficiency tradeoff can be controlled as a requirement by the number of FADBs. Experimental results on the SIDD, DND, and NAM datasets show that our FADN outperforms the state-of-the-art methods by improving the peak signal-to-noise ratio (PSNR) and decreasing the model parameters. The code is released at https://github.com/NekoDaiSiki/FADN.

Genetic diversity of the common carp black strain population based on mtDNA (D-loop and cytb).

The common strain black carp (Cyprinus carpio var. baisenensis) is a culturally important carp strain that is raised and cultured in Guangxi Province, China. Its color reflects the interactions between the Burau people and their surrounding environment. The population of the common carp black strain was isolated and cultured in a rice-fish integration system. To explore the genetic diversity and protection of germplasm resources, we analyzed mitochondrial DNA (mtDNA) sequences, specifically the displacement loop (D-loop) and cytochrome b (Cytb), using single-nucleotide polymorphisms (SNP). We compared these sequences with those from four other local common carp populations. The study included a total of 136 adult common carps from five strain populations: the common black carp strain (HJ = 31), Jian (F = 30), Heilongjiang (H = 10), Songpu (S = 31), and Saijiang (SJ = 34). The results of the Cytb and D-loop analyses showed that the Heilongjiang carp (H) and Saijiang (SJ) populations had the highest levels of haplotype diversity (0.867 ± 0.034785) and nucleotide diversity (π = 0.0063 ± 0.000137 and 0.0093 ± 0.000411), respectively. On the other hand, the Common carp black strain population (HJ) exhibited the lowest haplotype diversity in both Cytb and D-loop, with haplotype 2 being the most commonly observed among the populations. Private haplotypes dominated the five common carp populations, which were significantly different at P<0.001. Furthermore, analyzing the coefficient of genetic differentiation (Fst), the highest genetic difference was observed between Saijiang (SJ) and Heilongjiang (H) (Fst = 0.963), whereas the lowest was observed between Songpu (S) and the Common carp black strain population (HJ) (Fst = 0.019) for the Cytb gene sequences. For the D-loop, the Common carp black strain population (HJ) and Songpu (S) (Fst = 0.7) had the highest values, and Heilongjiang (H) and Common black carp strain (HJ) had an Fst of 0.125. Additionally, the AMOVA analysis revealed a higher level of variance for the Cytb and D-loop genes, indicating lower genetic diversity within the local carp community. On the other hand, the phylogenetic tree analysis showed that the five carp populations were closely related and formed a distinct cluster. The distinct cluster of populations suggests a common ancestor or recent gene flow, possibly due to geographic proximity or migration history, and unique genetic characteristics, possibly due to adaptations or selective pressures. The results of this study provide valuable insights into the genetic diversity of the common strain black carp, which can have implications for conservation, breeding programs, evolutionary studies, and fisheries management.

Comprehensive proteogenomic characterization of rare kidney tumors.

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.

Distinct classes of chromosomal rearrangements create oncogenic ETS gene fusions in prostate cancer.

Recently, we identified recurrent gene fusions involving the 5' untranslated region of the androgen-regulated gene TMPRSS2 and the ETS (E26 transformation-specific) family genes ERG, ETV1 or ETV4 in most prostate cancers. Whereas TMPRSS2-ERG fusions are predominant, fewer TMPRSS2-ETV1 cases have been identified than expected on the basis of the frequency of high (outlier) expression of ETV1 (refs 3-13). Here we explore the mechanism of ETV1 outlier expression in human prostate tumours and prostate cancer cell lines. We identified previously unknown 5' fusion partners in prostate tumours with ETV1 outlier expression, including untranslated regions from a prostate-specific androgen-induced gene (SLC45A3) and an endogenous retroviral element (HERV-K_22q11.23), a prostate-specific androgen-repressed gene (C15orf21), and a strongly expressed housekeeping gene (HNRPA2B1). To study aberrant activation of ETV1, we identified two prostate cancer cell lines, LNCaP and MDA-PCa 2B, that had ETV1 outlier expression. Through distinct mechanisms, the entire ETV1 locus (7p21) is rearranged to a 1.5-megabase prostate-specific region at 14q13.3-14q21.1 in both LNCaP cells (cryptic insertion) and MDA-PCa 2B cells (balanced translocation). Because the common factor of these rearrangements is aberrant ETV1 overexpression, we recapitulated this event in vitro and in vivo, demonstrating that ETV1 overexpression in benign prostate cells and in the mouse prostate confers neoplastic phenotypes. Identification of distinct classes of ETS gene rearrangements demonstrates that dormant oncogenes can be activated in prostate cancer by juxtaposition to tissue-specific or ubiquitously active genomic loci. Subversion of active genomic regulatory elements may serve as a more generalized mechanism for carcinoma development. Furthermore, the identification of androgen-repressed and insensitive 5' fusion partners may have implications for the anti-androgen treatment of advanced prostate cancer.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.