Identification of SPOP related metabolic pathways in prostate cancer

Genetic Profiling of African American Patients With Prostatic Adenocarcinoma Metastatic to the Lymph Nodes: A Pilot Study

CONTEXT.—

Genetic profiling data of prostatic adenocarcinoma are derived from predominantly White patients. In African Americans, prostatic adenocarcinoma has a poorer prognosis, raising the possibility of distinct genetic alterations.

OBJECTIVE.—

To investigate the genomic alterations of prostatic adenocarcinoma metastatic to regional lymph nodes in African American patients, with an emphasis on SPOP mutation.

DESIGN.—

We retrospectively reviewed African American patients with pN1 prostatic adenocarcinoma managed with radical prostatectomy and lymph node dissection. Comprehensive molecular profiling was performed, and androgen receptor signaling scores were calculated.

RESULTS.—

Nineteen patients were included. The most frequent genetic alteration was SPOP mutations (5 of 17; 29.4% [95% CI: 10.3-56.0]). While most alterations were associated with a high androgen receptor signaling score, mutant SPOP was exclusively associated with a low median and interquartile range (IQR) androgen receptor signaling score (0.788 [IQR 0.765-0.791] versus 0.835 [IQR 0.828-0.842], P = .003). In mutant SPOP, mRNA expression of SPOP inhibitor G3BP1 and SPOP substrates showed a significantly decreased expression of AR (33.40 [IQR 28.45-36.30] versus 59.53 [IQR 53.10-72.83], P = .01), TRIM24 (3.95 [IQR 3.28-5.03] versus 9.80 [IQR 7.39-11.70], P = .008), and NCOA3 (15.19 [IQR 10.59-15.93] versus 21.88 [IQR 18.41-28.33], P = .046).

CONCLUSIONS.—

African American patients with metastatic prostate adenocarcinoma might have a higher prevalence of mutant SPOP (30%), compared to ∼10% in unselected cohorts with lower expressions of SPOP substrates. In our study, in patients with mutant SPOP, the mutation was associated with decreased SPOP substrate expression and androgen receptor signaling, raising concern for suboptimal efficacy of androgen deprivation therapy in this subset of patients.

LRP5 competes for SPOP binding to enhance tumorigenesis mediated by Daxx and PD-L1 in prostate cancer

Genetic factors coordinate with environmental factors to drive the pathogenesis of prostate adenocarcinoma (PRAD). SPOP is one of the most mutated genes and LRP5 mediates lipid metabolism that is abnormally altered in PRAD. Here, we investigated the potential cross-talk between SPOP and LRP5 in PRAD. We find a negative correlation between SPOP and LRP5 proteins in PRAD. SPOP knockdown increased LRP5 protein while SPOP overexpression resulted in LRP5 reduction that was fully rescued by proteasome inhibitors. LRP5 intracellular tail has SPOP binding site and the direct interaction between LRP5 and SPOP was confirmed by Co-IP and GST-pulldown. Moreover, LRP5 competed with Daxx for SPOP-mediated degradation, establishing a dynamic balance among SPOP, LRP5 and Daxx. Overexpression of LRP5 tail could shift this balance to enhance Daxx-mediated transcriptional inhibition, and inhibit T cell activity in a co-culture system. Further, we generated human and mouse prostate cancer cell lines expressing SPOP variants (F133V, A227V, R368H). SPOP-F133V and SPOP-A227V have specific effects in up-regulating the protein levels of PD-1 and PD-L1. Consistently, SPOP-F133V and SPOP-A227V show robust inhibitory effects on T cells compared to WT SPOP in co-culture. This is further supported by the mouse syngeneic model showing that SPOP-F133V and SPOP-A227V enhance tumorigenesis of prostate cancer in in-vivo condition. Taken together, our study provides evidence that SPOP-LRP5 crosstalk plays an essential role, and the genetic variants of SPOP differentially modulate the expression and activity of immune checkpoints in prostate cancer.

The Mutational and Transcriptional Landscapes of Speckle-Type POZ Protein (SPOP) and Androgen Receptor (AR) in a Single-Center pT3 Prostatectomy Cohort

Prostate cancer (PCa) is a heterogeneous disease both clinically and genetically. According to The Cancer Genome Atlas (TCGA), the speckle‑type POZ protein (SPOP) mutant form is one of the significant core subtypes of PCa. However, the prognostic value of SPOP variations remains unknown. As a critical PCa driver and an SPOP-targeted protein, androgen receptor (AR) also plays a role in PCa initiation and progression. Thus, we aimed to analyze the mutational status of SPOP and AR with their transcriptional levels in a pathological stage 3 (pT3) prostatectomy cohort consisting of 89 Turkish PCa patients. Targeted sequence analysis and RT-qPCR were performed for SPOP and AR in the benign and malign prostate tissue samples. Our results introduced the two novel pathogenic SPOP variations, C203Y and S236R, in the BTB/POZ domain and a novel pathogenic variant in the ligand-binding domain of AR, R789W. Their predicted pathogenicities and effects on protein features were evaluated by web-based in silico analysis. The overall frequency of SPOP and AR variations for pT3 patients in our population was 3.4% (3/89) and 4.5% (4/89), respectively. The mutational results represented a possible subgroup characterized by carrying the novel variants in SPOP and AR in pT3 PCa patients. In addition to the significant clinicopathological parameters, the mutational results provide a better understanding of the molecular structure of pathologically advanced PCa in the SPOP and AR aspects.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

SPOP and cancer: a systematic review

The initiation and progression of cancer is dependent on the acquisition of mutations in oncogenes or tumor suppressor genes that ultimately leads to the dysregulation of key regulatory pathways. Though these mutations often occur in direct regulators of such pathways, some may confer tumorigenic potential by indirectly targeting several pathways congruently thereby exerting pleiotropic effects. In recent years, the tumor suppressor gene Speckle Type POZ Protein (SPOP) has gained a lot of attention as it has been found to be altered in a variety of different cancers. SPOP appears to exert pleiotropic tumorigenic effects as multiple different regulatory pathways become dysregulated upon SPOP alterations. SPOP has been identified as an E3 ubiquitin ligase substrate binding subunit of the proteasome complex. Since protein degradation is critical in regulating proper cellular function it is not surprising that the proteasome pathway is often found to be disrupted in cancer. Many studies have now indicated that mutations or changes in the expression of SPOP are one of several underlying reasons of proteasome pathway disruption in different cancers. Ultimately, either SPOP downregulation or mutation promotes stabilization of direct SPOP targets which subsequently promotes cancer through the dysregulation of key regulatory pathways. In this review, we will discuss the current literature on cancer-specific SPOP alterations as well the SPOP targets that are stabilized, and the pathways that are dysregulated, as a result.

MYCN and PRC1 cooperatively repress docosahexaenoic acid synthesis in neuroblastoma via ELOVL2

Background

The MYCN amplification is a defining hallmark of high-risk neuroblastoma. Due to irregular oncogenes orchestration, tumor cells exhibit distinct fatty acid metabolic features from non-tumor cells. However, the function of MYCN in neuroblastoma fatty acid metabolism reprogramming remains unknown.

Methods

Gas Chromatography-Mass Spectrometer (GC-MS) was used to find the potential target fatty acid metabolites of MYCN. Real-time PCR (RT-PCR) and clinical bioinformatics analysis was used to find the related target genes. The function of the identified target gene ELOVL2 on cell growth was detected through CCK-8 assay, Soft agar colony formation assay, flow Cytometry assay and mouse xenograft. Chromatin immunoprecipitation (ChIP) and Immunoprecipitation-Mass Spectrometer (IP-MS) further identified the target gene and the co-repressor of MYCN.

Results

The fatty acid profile of MYCN-depleted neuroblastoma cells identified docosahexaenoic acid (DHA), an omega-3 polyunsaturated fatty acid with anti-tumor activity, significantly increased after MYCN depletion. Compared with MYCN single-copy neuroblastoma cells, DHA level was significantly lower in MYCN-amplified neuroblastoma cells. RT-PCR and clinical bioinformatics analysis discovered that MYCN interfered DHA accumulation via ELOVL fatty acid elongase 2 (ELOVL2) which is a rate-limiting enzyme of cellular DHA synthesis. Enforced ELOVL2 expression in MYCN-amplified neuroblastoma cells led to decreased cell growth and counteracted the growth-promoting effect of MYCN overexpression both in vitro and vivo. ELOVL2 Knockdown showed the opposite effect in MYCN single-copy neuroblastoma cells. In primary neuroblastoma, high ELOVL2 transcription correlated with favorable clinical tumor biology and patient survival. The mechanism of MYCN-mediated ELOVL2 inhibition contributed to epigenetic regulation. MYCN recruited PRC1 (Polycomb repressive complex 1), catalysed H2AK119ub (histone 2A lysine 119 monoubiquitination) and inhibited subsequent ELOVL2 transcription.

Conclusions

The tumor suppressive properties of DHA and ELOVL2 are repressed by the MYCN and PRC1 jointly, which suggests a new epigenetic mechanism of MYCN-mediated fatty acid regulation and indicates PRC1 inhibition as a potential novel strategy to activate ELOVL2 suppressive functions.

Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells

Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lacking. We analyzed public single cell RNA-sequencing data from glioblastoma surgical resections, which offer the closest available view of tumor cell heterogeneity as encountered at the time of patients’ diagnosis. Unsupervised analyses revealed that information dispersed throughout the cell transcript repertoires encoded the identity of each tumor and masked information related to cell functioning states. Data reduction based on an experimentally-defined signature of transcription factors overcame this hurdle. It allowed cell grouping according to their tumorigenic potential, regardless of their tumor of origin. The approach relevance was validated using independent datasets of glioblastoma cell and tissue transcriptomes, patient-derived cell lines and orthotopic xenografts. Overexpression of genes coding for amino acid and lipid metabolism enzymes involved in anti-oxidative, energetic and cell membrane processes characterized cells with high tumorigenic potential. Modeling of their expression network highlighted the very long chain polyunsaturated fatty acid synthesis pathway at the core of the network. Expression of its most downstream enzymatic component, ELOVL2, was associated with worsened patient survival, and required for cell tumorigenic properties in vivo. Our results demonstrate the power of signature-driven analyses of single cell transcriptomes to obtain an integrated view of metabolic pathways at play within the heterogeneous cell landscape of patient tumors.

PTEN deletion drives acute myeloid leukemia resistance to MEK inhibitors

Kinases such as MEK are attractive targets for novel therapy in cancer, including acute myeloid leukaemia (AML). Acquired and inherent resistance to kinase inhibitors, however, is becoming an increasingly important challenge for the clinical success of such therapeutics, and often arises from mutations in the drug-binding domain of the target kinase. To identify possible causes of resistance to MEK inhibition, we generated a model of resistance by long-term treatment of AML cells with AZD6244 (selumetinib). Remarkably, resistance to MEK inhibition was due to acquired PTEN haploinsufficiency, rather than mutation of MEK. Resistance via this mechanism was confirmed using CRISPR/Cas9 technology targeting exon 5 of PTEN. While PTEN loss has been previously implicated in resistance to a number of other therapeutic agents, this is the first time that it has been shown directly and in AML.

[Study on the Metabolic Reprogramming of Lung Cancer Cells Regulated by Docetaxel Based on Metabolomics]

背景与目的

多西他赛是一种临床常用的抗肿瘤药物，是晚期非小细胞肺癌（non-small cell lung cancer, NSCLC）的一线用药。然而，多西他赛抗NSCLC作用的分子机制尚不明确。研究表明肿瘤细胞的代谢重编程在肿瘤发生发展过程中发挥重要作用。本研究旨在通过结合代谢组学分析及生物学手段来探讨多西他赛所影响的NSCLC细胞代谢通路。

方法

首先，通过CCK-8实验分析多西他赛对NSCLC细胞活力的影响，筛选合适药物浓度。接下来，通过基于气相色谱质谱联用（gas chromatography-mass spectrometry, GC-MS）的代谢组学技术分析多西他赛处理和未处理的A549和H1299细胞。并通过统计学计算得到处理组和未处理组间的差异代谢物。最后，通过蛋白质免疫印迹分析（Western blot）多西他赛对其所调控的相关代谢途径中关键酶蛋白质表达水平的影响。

结果

多西他赛可时间依赖和浓度依赖地抑制A549和H1299细胞活力。随着多西他赛处理时间延长，凋亡敏感蛋白质多聚二磷酸腺苷核糖聚合酶[Poly(ADP-)Polymerase, PARP]逐渐被激活裂解形成P89片段。代谢组学分析发现，药物处理后的A549和H1299细胞内，8种代谢物均发生显著变化，主要集中于三羧酸（tricarboxylic acid, TCA）循环代谢通路。同时，药物处理后，TCA循环关键调控酶异柠檬酸脱氢酶蛋白质表达水平显著下降。

结论

多西他赛诱导NSCLC增殖抑制及凋亡的效应可能与下调异柠檬酸脱氢酶，进而抑制三羧酸循环代谢途径有关。

Current and future perspectives of functional metabolomics in disease studies-A review

Functional metabolomics is a new concept, which studies the functions of metabolites and related enzymes focused on metabolomics. It overcomes the shortcomings of traditional discovery metabolomics of mainly relying on literatures for biological interpretation. Functional metabolomics has many advantages. Firstly, the functional roles of metabolites and related metabolic enzymes are focused. Secondly, the in vivo and in vitro experiments are conducted to validate the metabolomics findings, therefore, increasing the reliability of metabolomics study and producing the new knowledge. Thirdly, functional metabolomics can be used by biologists to investigate functions of metabolites, and related genes and proteins. In this review, we summarize the analytical, biological and clinical platforms used in functional metabolomics studies. Recent progresses of functional metabolomics in cancer, metabolic diseases and biological phenotyping are reviewed, and future development is also predicted. Because of the tremendous advantages of functional metabolomics, it will have a bright future.