Identification of transcription factor co-regulators that drive prostate cancer progression

From metabolism to malignancy: the multifaceted role of PGC1α in cancer

PGC1α, a central player in mitochondrial biology, holds a complex role in the metabolic shifts seen in cancer cells. While its dysregulation is common across major cancers, its impact varies. In some cases, downregulation promotes aerobic glycolysis and progression, whereas in others, overexpression escalates respiration and aggression. PGC1α's interactions with distinct signaling pathways and transcription factors further diversify its roles, often in a tissue-specific manner. Understanding these multifaceted functions could unlock innovative therapeutic strategies. However, challenges exist in managing the metabolic adaptability of cancer cells and refining PGC1α-targeted approaches. This review aims to collate and present the current knowledge on the expression patterns, regulators, binding partners, and roles of PGC1α in diverse cancers. We examined PGC1α's tissue-specific functions and elucidated its dual nature as both a potential tumor suppressor and an oncogenic collaborator. In cancers where PGC1α is tumor-suppressive, reinstating its levels could halt cell proliferation and invasion, and make the cells more receptive to chemotherapy. In cancers where the opposite is true, halting PGC1α's upregulation can be beneficial as it promotes oxidative phosphorylation, allows cancer cells to adapt to stress, and promotes a more aggressive cancer phenotype. Thus, to target PGC1α effectively, understanding its nuanced role in each cancer subtype is indispensable. This can pave the way for significant strides in the field of oncology.

Deciphering the Transcription Factor Landscape in Neuroendocrine Prostate Cancer Progression: A Novel Approach to Understand NE Transdifferentiation

Background and Objective

Prostate cancer (PCa) is a leading cause of cancer mortality in men, with neuroendocrine prostate cancer (NEPC) representing a particularly resistant subtype. The role of transcription factors (TFs) in the progression from prostatic adenocarcinoma (PRAD) to NEPC is poorly understood. This study aims to identify and analyze lineage-specific TF profiles in PRAD and NEPC and illustrate their dynamic shifts during NE transdifferentiation.

Methods

A novel algorithmic approach was developed to evaluate the weighted expression of TFs within patient samples, enabling a nuanced understanding of TF landscapes in PCa progression and TF dynamic shifts during NE transdifferentiation.

Results

unveiled TF profiles for PRAD and NEPC, identifying 126 shared TFs, 46 adenocarcinoma-TFs, and 56 NEPC-TFs. Enrichment analysis across multiple clinical cohorts confirmed the lineage specificity and clinical relevance of these lineage-TFs signatures. Functional analysis revealed that lineage-TFs are implicated in pathways critical to cell development, differentiation, and lineage determination. Novel lineage-TF candidates were identified, offering potential targets for therapeutic intervention. Furthermore, our longitudinal study on NE transdifferentiation highlighted dynamic TF expression shifts and delineated a three-phase hypothesis for the process comprised of de-differentiation, dormancy, and re-differentiation. and proposing novel insights into the mechanisms of PCa progression.

Conclusion

The lineage-specific TF profiles in PRAD and NEPC reveal a dynamic shift in the TF landscape during PCa progression, highlighting three distinct phases of NE transdifferentiation.

Modeling gene expression cascades during cell state transitions

During cellular processes such as differentiation or response to external stimuli, cells exhibit dynamic changes in their gene expression profiles. Single-cell RNA sequencing (scRNA-seq) can be used to investigate these dynamic changes. To this end, cells are typically ordered along a pseudotemporal trajectory which recapitulates the progression of cells as they transition from one cell state to another. We infer transcriptional dynamics by modeling the gene expression profiles in pseudotemporally ordered cells using a Bayesian inference approach. This enables ordering genes along transcriptional cascades, estimating differences in the timing of gene expression dynamics, and deducing regulatory gene interactions. Here, we apply this approach to scRNA-seq datasets derived from mouse embryonic forebrain and pancreas samples. This analysis demonstrates the utility of the method to derive the ordering of gene dynamics and regulatory relationships critical for proper cellular differentiation and maturation across a variety of developmental contexts.

Peroxisome proliferator-activated receptor gamma coactivator-1 (PGC-1) family in physiological and pathophysiological process and diseases

Peroxisome proliferator-activated receptor gamma coactivator-1 (PGC-1) family (PGC-1s), consisting of three members encompassing PGC-1α, PGC-1β, and PGC-1-related coactivator (PRC), was discovered more than a quarter-century ago. PGC-1s are essential coordinators of many vital cellular events, including mitochondrial functions, oxidative stress, endoplasmic reticulum homeostasis, and inflammation. Accumulating evidence has shown that PGC-1s are implicated in many diseases, such as cancers, cardiac diseases and cardiovascular diseases, neurological disorders, kidney diseases, motor system diseases, and metabolic disorders. Examining the upstream modulators and co-activated partners of PGC-1s and identifying critical biological events modulated by downstream effectors of PGC-1s contribute to the presentation of the elaborate network of PGC-1s. Furthermore, discussing the correlation between PGC-1s and diseases as well as summarizing the therapy targeting PGC-1s helps make individualized and precise intervention methods. In this review, we summarize basic knowledge regarding the PGC-1s family as well as the molecular regulatory network, discuss the physio-pathological roles of PGC-1s in human diseases, review the application of PGC-1s, including the diagnostic and prognostic value of PGC-1s and several therapies in pre-clinical studies, and suggest several directions for future investigations. This review presents the immense potential of targeting PGC-1s in the treatment of diseases and hopefully facilitates the promotion of PGC-1s as new therapeutic targets.

Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer

The current study in prostate cancer (PCa) focused on the genomic mechanisms at the cross-roads of pro-differentiation signals and the emergence of lineage plasticity. We explored an understudied cistromic mechanism involving RARγ's ability to govern AR cistrome-transcriptome relationships, including those associated with more aggressive PCa features. The RARγ complex in PCa cell models was enriched for canonical cofactors, as well as proteins involved in RNA processing and bookmarking. Identifying the repertoire of miR-96 bound and regulated gene targets, including those recognition elements marked by m6A, revealed their significant enrichment in the RARγ complex. RARγ significantly enhanced the AR cistrome, particularly in active enhancers and super-enhancers, and overlapped with the binding of bookmarking factors. Furthermore, RARγ expression led to nucleosome-free chromatin enriched with H3K27ac, and significantly enhanced the AR cistrome in G2/M cells. RARγ functions also antagonized the transcriptional actions of the lineage master regulator ONECUT2. Similarly, gene programs regulated by either miR-96 or antagonized by RARγ were enriched in alternative lineages and more aggressive PCa phenotypes. Together these findings reveal an under-investigated role for RARγ, modulated by miR-96, to bookmark enhancer sites during mitosis. These sites are required by the AR to promote transcriptional competence, and emphasize luminal differentiation, while antagonizing ONECUT2.

An in silico procedure for generating protein-mediated chromatin interaction data and comparison of significant interaction calling methods

The ability to simulate high-throughput data with high fidelity to real experimental data is fundamental for benchmarking methods used to detect true long-range chromatin interactions mediated by a specific protein. Yet, such tools are not currently available. To fill this gap, we develop an in silico experimental procedure, ChIA-Sim, which imitates the experimental procedures that produce real ChIA-PET, Hi-ChIP, or PLAC-seq data. We show the fidelity of ChIA-Sim to real data by using guiding characteristics of several real datasets to generate data using the simulation procedure. We also used ChIA-Sim data to demonstrate the use of our in silico procedure in benchmarking methods for significant interactions analysis by evaluating four methods for significant interaction calling (SIC). In particular, we assessed each method's performance in terms of correct identification of long-range interactions. We further analyzed four experimental datasets from publicly available databases and shew that the trend of the results are consistent with those seen in data generated from ChIA-Sim. This serves as additional evidence that ChIA-Sim closely resembles data produced from the experimental protocols it models after.

MotifHub: Detection of trans-acting DNA motif group with probabilistic modeling algorithm

BACKGROUND

Trans-acting factors are of special importance in transcription regulation, which is a group of proteins that can directly or indirectly recognize or bind to the 8-12 bp core sequence of cis-acting elements and regulate the transcription efficiency of target genes. The progressive development in high-throughput chromatin capture technology (e.g., Hi-C) enables the identification of chromatin-interacting sequence groups where trans-acting DNA motif groups can be discovered. The problem difficulty lies in the combinatorial nature of DNA sequence pattern matching and its underlying sequence pattern search space.

METHOD

Here, we propose to develop MotifHub for trans-acting DNA motif group discovery on grouped sequences. Specifically, the main approach is to develop probabilistic modeling for accommodating the stochastic nature of DNA motif patterns.

RESULTS

Based on the modeling, we develop global sampling techniques based on EM and Gibbs sampling to address the global optimization challenge for model fitting with latent variables. The results reflect that our proposed approaches demonstrate promising performance with linear time complexities.

CONCLUSION

MotifHub is a novel algorithm considering the identification of both DNA co-binding motif groups and trans-acting TFs. Our study paves the way for identifying hub TFs of stem cell development (OCT4 and SOX2) and determining potential therapeutic targets of prostate cancer (FOXA1 and MYC). To ensure scientific reproducibility and long-term impact, its matrix-algebra-optimized source code is released at http://bioinfo.cs.cityu.edu.hk/MotifHub.

The MYC axis in advanced prostate cancer is impacted through concurrent targeting of ERβ and AR using a novel ERβ-selective ligand alongside Enzalutamide

We have dissected the role of Estrogen receptor beta (ERβ) in prostate cancer (PCa) with a novel ERβ ligand, OSU-ERb-12. Drug screens revealed additive interactions between OSU-ERB-12 and either epigenetic inhibitors or the androgen receptor antagonist, Enzalutamide (Enza). Clonogenic and cell biolody studies supported the potent additive effects of OSU-ERB-12 (100nM) and Enza (1μM). The cooperative behavior was in PCa cell lines treated with either OSU-ERB-12 plus Enza or combinations involving 17β-estradiol (E2). OSU-ERb-12 plus Enza uniquely impacted the transcriptiome, accessible chromatin, and the AR, MYC and H3K27ac cistromes. This included skewed transcriptional responses including suppression of the androgen and MYC transcriptomes, and repressed MYC protein. OSU-ERb-12 plus Enza uniquely impacted chromatin accessibility at approximately 3000 nucleosome-free sites, enriched at enhancers, enriched for basic Helix-Loop-Helix motifs. CUT&RUN experiments revealed combination treatment targeting of MYC, AR, and H3K27ac again shaping enhancer accessibility. Specifically, it repressed MYC interactions at enhancer regions enriched for bHLH motifs, and overlapped with publicly-available bHLH cistromes. Finally, cistrome-transcriptome analyses identified ~200 genes that distinguished advanced PCa tumors in the SU2C cohort with high androgen and low neuroendocrine scores.

Transcriptional co-activators: emerging roles in signaling pathways and potential therapeutic targets for diseases

Specific cell states in metazoans are established by the symphony of gene expression programs that necessitate intricate synergic interactions between transcription factors and the co-activators. Deregulation of these regulatory molecules is associated with cell state transitions, which in turn is accountable for diverse maladies, including developmental disorders, metabolic disorders, and most significantly, cancer. A decade back most transcription factors, the key enablers of disease development, were historically viewed as 'undruggable'; however, in the intervening years, a wealth of literature validated that they can be targeted indirectly through transcriptional co-activators, their confederates in various physiological and molecular processes. These co-activators, along with transcription factors, have the ability to initiate and modulate transcription of diverse genes necessary for normal physiological functions, whereby, deregulation of such interactions may foster tissue-specific disease phenotype. Hence, it is essential to analyze how these co-activators modulate specific multilateral processes in coordination with other factors. The proposed review attempts to elaborate an in-depth account of the transcription co-activators, their involvement in transcription regulation, and context-specific contributions to pathophysiological conditions. This review also addresses an issue that has not been dealt with in a comprehensive manner and hopes to direct attention towards future research that will encompass patient-friendly therapeutic strategies, where drugs targeting co-activators will have enhanced benefits and reduced side effects. Additional insights into currently available therapeutic interventions and the associated constraints will eventually reveal multitudes of advanced therapeutic targets aiming for disease amelioration and good patient prognosis.

Biased regulation of glucocorticoid receptors signaling

Glucocorticoids (GCs), steroid hormones that depend on glucocorticoid receptor (GR) binding for their action, are essential for regulating numerous homeostatic functions in the body.GR signals are biased, that is, GR signals are various in different tissue cells, disease states and ligands. This biased regulation of GR signaling appears to depend on ligand-induced metameric regulation, protein post-translational modifications, assembly at response elements, context-specific assembly (recruitment of co-regulators) and intercellular differences. Based on the bias regulation of GR, selective GR agonists and modulators (SEGRAMs) were developed to bias therapeutic outcomes toward expected outcomes (e.g., anti-inflammation and immunoregulation) by influencing GR-mediated gene expression. This paper provides a review of the bias regulation and mechanism of GR and the research progress of drugs.

African American Prostate Cancer Displays Quantitatively Distinct Vitamin D Receptor Cistrome-transcriptome Relationships Regulated by BAZ1A

African American (AA) prostate cancer associates with vitamin D3 deficiency, but vitamin D receptor (VDR) genomic actions have not been investigated in this context. We undertook VDR proteogenomic analyses in European American (EA) and AA prostate cell lines and four clinical cohorts. Rapid immunoprecipitation mass spectrometry of endogenous protein (RIME) analyses revealed that nonmalignant AA RC43N prostate cells displayed the greatest dynamic protein content in the VDR complex. Likewise, in AA cells, Assay for Transposase-Accessible Chromatin using sequencing established greater 1α,25(OH)2D3-regulated chromatin accessibility, chromatin immunoprecipitation sequencing revealed significant enhancer-enriched VDR cistrome, and RNA sequencing identified the largest 1α,25(OH)2D3-dependent transcriptome. These VDR functions were significantly corrupted in the isogenic AA RC43T prostate cancer cells, and significantly distinct from EA cell models. We identified reduced expression of the chromatin remodeler, BAZ1A, in three AA prostate cancer cohorts as well as RC43T compared with RC43N. Restored BAZ1A expression significantly increased 1α,25(OH)2D3-regulated VDR-dependent gene expression in RC43T, but not HPr1AR or LNCaP cells. The clinical impact of VDR cistrome-transcriptome relationships were tested in three different clinical prostate cancer cohorts. Strikingly, only in AA patients with prostate cancer, the genes bound by VDR and/or associated with 1α,25(OH)2D3-dependent open chromatin (i) predicted progression from high-grade prostatic intraepithelial neoplasia to prostate cancer; (ii) responded to vitamin D3 supplementation in prostate cancer tumors; (iii) differentially responded to 25(OH)D3 serum levels. Finally, partial correlation analyses established that BAZ1A and components of the VDR complex identified by RIME significantly strengthened the correlation between VDR and target genes in AA prostate cancer only. Therefore, VDR transcriptional control is most potent in AA prostate cells and distorted through a BAZ1A-dependent control of VDR function.

Significance

Our study identified that genomic ancestry drives the VDR complex composition, genomic distribution, and transcriptional function, and is disrupted by BAZ1A and illustrates a novel driver for AA prostate cancer.

Recent advances in prostate cancer: WNT signaling, chromatin regulation, and transcriptional coregulators

Prostate cancer is one of the most common diseases in men worldwide. Surgery, radiation therapy, and hormonal therapy are effective treatments for early-stage prostate cancer. However, the development of castration-resistant prostate cancer has increased the mortality rate of prostate cancer. To develop novel drugs for castration-resistant prostate cancer, the molecular mechanisms of prostate cancer progression must be elucidated. Among the signaling pathways regulating prostate cancer development, recent studies have revealed the importance of noncanonical wingless-type MMTV integration site family (WNT) signaling pathways, mainly that involving WNT5A, in prostate cancer progression and metastasis; however, its role remains controversial. Moreover, chromatin remodelers such as the switch/sucrose nonfermentable (SWI/SNF) complex and chromodomain helicase DNA-binding proteins 1 also play important roles in prostate cancer progression through genome-wide gene expression changes. Here, we review the roles of noncanonical WNT signaling pathways, chromatin remodelers, and epigenetic enzymes in the development and progression of prostate cancer.

Systematic Investigation of the Diagnostic and Prognostic Impact of LINC01087 in Human Cancers

(1) Background: Long non-coding RNAs may constitute epigenetic biomarkers for the diagnosis, prognosis, and therapeutic response of a variety of tumors. In this context, we aimed at assessing the diagnostic and prognostic value of the recently described long intergenic non-coding RNA 01087 (LINC01087) in human cancers. (2) Methods: We studied the expression of LINC01087 across 30 oncological indications by interrogating public resources. Data extracted from the TCGA and GTEx databases were exploited to plot receiver operating characteristic curves (ROC) and determine the diagnostic performance of LINC01087. Survival data from TCGA and KM-Plotter directories allowed us to graph Kaplan-Meier curves and evaluate the prognostic value of LINC01087. To investigate the function of LINC01087, gene ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed. Furthermore, interactions between LINC01087 and both miRNA and mRNA were studied by means of bioinformatics tools. (3) Results: LINC01087 was significantly deregulated in 7 out of 30 cancers, showing a predominant upregulation. Notably, it was overexpressed in breast (BC), esophageal (ESCA), and ovarian (OV) cancers, as well as lung squamous cell carcinoma (LUSC), stomach adenocarcinoma (STAD), and uterine carcinosarcoma (UCS). By contrast, LINC01087 displayed downregulation in testicular germ cell tumors (TGCT). ROC curve analyses identified LINC01087 as a potential diagnostic indicator in BC, ESCA, OV, STAD, and TGCT. Moreover, high and low expression of LINC01087 predicted a favorable prognosis in BC and papillary cell carcinoma, respectively. In silico analyses indicated that deregulation of LINC01087 in cancer was associated with a modulation of genes related to ion channel, transporter, and peptide receptor activity. (4) Conclusions: the quantification of an altered abundance of LINC01087 in tissue specimens might be clinically useful for the diagnosis and prognosis of some hormone-related tumors, including BC, OV, and TGCT, as well as other cancer types such as ESCA and STAD. Moreover, our study revealed the potential of LINC01087 (and perhaps other lncRNAs) to regulate neuroactive molecules in cancer.

Nuclear Receptor Coregulators in Hormone-Dependent Cancers

Nuclear receptors (NRs) function collectively as a transcriptional signaling network that mediates gene regulatory actions to either maintain cellular homeostasis in response to hormonal, dietary and other environmental factors, or act as orphan receptors with no known ligand. NR complexes are large and interact with multiple protein partners, collectively termed coregulators. Coregulators are essential for regulating NR activity and can dictate whether a target gene is activated or repressed by a variety of mechanisms including the regulation of chromatin accessibility. Altered expression of coregulators contributes to a variety of hormone-dependent cancers including breast and prostate cancers. Therefore, understanding the mechanisms by which coregulators interact with and modulate the activity of NRs provides opportunities to develop better prognostic and diagnostic approaches, as well as novel therapeutic targets. This review aims to gather and summarize recent studies, techniques and bioinformatics methods used to identify distorted NR coregulator interactions that contribute as cancer drivers in hormone-dependent cancers.

Peroxisome Proliferator Activated Receptor Gamma Coactivator-1 Alpha: A Double-Edged Sword in Prostate Cancer

Peroxisome proliferator activated receptor gamma coactivator-1 alpha (PGC-1α/PPARGC1A) is a pivotal transcriptional coactivator involved in the regulation of mitochondrial metabolism, including biogenesis and oxidative metabolism. PGC-1α is finely regulated by AMP-activated protein kinases (AMPKs), the role of which in tumors remains controversial to date. In recent years, a growing amount of research on PGC-1α and tumor metabolism has emphasized its importance in a variety of tumors, including prostate cancer (PCA). Compelling evidence has shown that PGC-1α may play dual roles in promoting and inhibiting tumor development under certain conditions. Therefore, a better understanding of the critical role of PGC-1α in PCA pathogenesis will provide new insights into targeting PGC-1α for the treatment of this disease. In this review, we highlight the procancer and anticancer effects of PGC-1α in PCA and aim to provide a theoretical basis for targeting AMPK/PGC-1α to inhibit the development of PCA. In addition, our recent findings provide a candidate drug target and theoretical basis for targeting PGC-1α to regulate lipid metabolism in PCA.

Side effect prediction based on drug-induced gene expression profiles and random forest with iterative feature selection

One in every ten drug candidates fail in clinical trials mainly due to efficacy and safety related issues, despite in-depth preclinical testing. Even some of the approved drugs such as chemotherapeutics are notorious for their side effects that are burdensome on patients. In order to pave the way for new therapeutics with more tolerable side effects, the mechanisms underlying side effects need to be fully elucidated. In this work, we addressed the common side effects of chemotherapeutics, namely alopecia, diarrhea and edema. A strategy based on Random Forest algorithm unveiled an expression signature involving 40 genes that predicted these side effects with an accuracy of 89%. We further characterized the resulting signature and its association with the side effects using functional enrichment analysis and protein-protein interaction networks. This work contributes to the ongoing efforts in drug development for early identification of side effects to use the resources more effectively.

MiR-16-5p suppresses breast cancer proliferation by targeting ANLN

BACKGROUND

In recent years, gene expression-based analysis has been used for disease biomarker discovery, providing ways for better diagnosis, leading to improvement of clinical treatment efficacy. This study aimed to explore the role of miR-16-5p and ANLN in breast cancer (BC).

METHODS

Cohort datasets of BC were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) and analyzed by bioinformatics tools. qRT-PCR and western blotting were applied to validate ANLN and its protein expression. A dual-luciferase reporter assay was used to prove the regulatory relationship of miR-16-5p and ANLN. Finally, MTT, wound healing, Transwell invasion and flow cytometry analyses of the cell cycle and apoptosis were performed to assess cell proliferation, migration, invasion, cell cycle and apoptosis, respectively.

RESULTS

A total of 195 differentially expressed genes (DEGs) and 50 overlapping microRNAs (miRNAs) were identified. Among these DEGs and miRNAs, ANLN, associated with poor overall survival in BC, overlapped in the GSE29431, GSE42568, TCGA and GEPIA2 databases. Moreover, ANLN was highly expressed, while miR-16-5p was lower in BC cells than in breast epithelial cells. Then, we confirmed that ANLN was directly targeted by miR-16-5p in BC cells. Over-expression of miR-16-5p and knock-down of ANLN remarkably inhibited cell proliferation and migration as well as cell invasion, arrested the cells in G2/M phase and induced apoptosis in BC cells.

CONCLUSIONS

These findings suggest that miR-16-5p restrains proliferation, migration and invasion while affecting cell cycle and promotes apoptosis by regulating ANLN, thereby providing novel candidate biomarkers for the diagnosis and treatment of BC.

The Etiology and Pathophysiology Genesis of Benign Prostatic Hyperplasia and Prostate Cancer: A New Perspective

Background: The etiology of benign prostatic hyperplasia and prostate cancer are unknown, with ageing being the greatness risk factor. Methods: This new perspective evaluates the available interdisciplinary evidence regarding prostate ageing in terms of the cell biology of regulation and homeostasis, which could explain the timeline of evolutionary cancer biology as degenerative, inflammatory and neoplasm progressions in these multifactorial and heterogeneous prostatic diseases. Results: This prostate ageing degeneration hypothesis encompasses the testosterone-vascular-inflamm-ageing triad, along with the cell biology regulation of amyloidosis and autophagy within an evolutionary tumorigenesis microenvironment. Conclusions: An understanding of these biological processes of prostate ageing can provide potential strategies for early prevention and could contribute to maintaining quality of life for the ageing individual along with substantial medical cost savings.