Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing

Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts

Resistance to androgen-deprivation therapies leads to metastatic castration-resistant prostate cancer (mCRPC) of adenocarcinoma (AdCa) origin that can transform into emergent aggressive variant prostate cancer (AVPC), which has neuroendocrine (NE)-like features. In this work, we used LuCaP patient-derived xenograft (PDX) tumors, clinically relevant models that reflect and retain key features of the tumor from advanced prostate cancer patients. Here we performed proteome and phosphoproteome characterization of 48 LuCaP PDX tumors and identified over 94,000 peptides and 9,700 phosphopeptides corresponding to 7,738 proteins. We compared 15 NE versus 33 AdCa samples, which included six different PDX tumors for each group in biological replicates, and identified 309 unique proteins and 476 unique phosphopeptides that were significantly altered and corresponded to proteins that are known to distinguish these two phenotypes. Assessment of concordance from PDX tumor-matched protein and mRNA revealed increased dissonance in transcriptionally regulated proteins in NE and metabolite interconversion enzymes in AdCa.

IMPLICATIONS

Overall, our study highlights the importance of protein-based identification when compared with RNA and provides a rich resource of new and feasible targets for clinical assay development and in understanding the underlying biology of these tumors.

ERBB3 Overexpression is Enriched in Diverse Patient Populations with Castration-sensitive Prostate Cancer and is Associated with a Unique AR Activity Signature

PURPOSE

Despite successful clinical management of castration-sensitive prostate cancer (CSPC), the 5-year survival rate for men with castration-resistant prostate cancer is only 32%. Combination treatment strategies to prevent disease recurrence are increasing, albeit in biomarker-unselected patients. Identifying a biomarker in CSPC to stratify patients who will progress on standard-of-care therapy could guide therapeutic strategies.

EXPERIMENTAL DESIGN

Targeted deep sequencing was performed for the University of Illinois (UI) cohort (n = 30), and immunostaining was performed on a patient tissue microarray (n = 149). Bioinformatic analyses identified pathways associated with biomarker overexpression (OE) in the UI cohort, consolidated RNA sequencing samples accessed from Database of Genotypes and Phenotypes (n = 664), and GSE209954 (n = 68). Neutralizing antibody patritumab and ectopic HER3 OE were utilized for functional mechanistic experiments.

RESULTS

We identified ERBB3 OE in diverse patient populations with CSPC, where it was associated with advanced disease at diagnosis. Bioinformatic analyses showed a positive correlation between ERBB3 expression and the androgen response pathway despite low dihydrotestosterone and stable expression of androgen receptor (AR) transcript in Black/African American men. At the protein level, HER3 expression was negatively correlated with intraprostatic androgen in Black/African American men. Mechanistically, HER3 promoted enzalutamide resistance in prostate cancer cell line models and HER3-targeted therapy resensitized therapy-resistant prostate cancer cell lines to enzalutamide.

CONCLUSIONS

In diverse patient populations with CSPC, ERBB3 OE was associated with high AR signaling despite low intraprostatic androgen. Mechanistic studies demonstrated a direct link between HER3 and enzalutamide resistance. ERBB3 OE as a biomarker could thus stratify patients for intensification of therapy in castration-sensitive disease, including targeting HER3 directly to improve sensitivity to AR-targeted therapies.

Glucocorticoid Receptor (GR) Activation Is Associated with Increased cAMP/PKA Signaling in Castration-Resistant Prostate Cancer

In castration-resistant prostate cancer (CRPC), increased glucocorticoid receptor (GR) expression and ensuing transcriptional activity have been proposed as an oncogenic "bypass" mechanism in response to androgen receptor (AR) signaling inhibition (ARSi). Here, we report that GR transcriptional activity acquired following ARSi is associated with the upregulation of cyclic adenosine monophosphate (cAMP)-associated gene expression pathways in both model systems and metastatic prostate cancer patient samples. In the context of ARSi, the expression of GR-mediated genes encoding cAMP signaling pathway-associated proteins can be inhibited by treatment with selective GR modulators (SGRMs). For example, in the context of ARSi, we found that GR activation resulted in upregulation of protein kinase inhibitor beta (PKIB) mRNA and protein levels, leading to nuclear accumulation of the cAMP-dependent protein kinase A catalytic subunit (PKA-c). Increased PKA-c, in turn, is associated with increased cAMP response element-binding protein phosphorylation and activity. Furthermore, enzalutamide and SGRM combination therapy in mice bearing CRPC xenografts delayed CRPC progression compared with enzalutamide therapy alone, and reduced tumor PKIB mRNA expression. Supporting the clinical importance of GR/PKA signaling activation in CRPC, we found a significant enrichment of both cAMP pathway signaling-associated gene expression and high NR3C1 (GR) activity in patient-derived xenograft models and metastatic human CRPC samples. These findings suggest a novel mechanism linking CRPC-induced GR transcriptional activity with increased cAMP signaling in AR-antagonized CRPC. Furthermore, our findings suggest that GR-specific modulation in addition to AR antagonism may delay GR+ CRPC time to recurrence, at least in part, by inhibiting tumor cAMP/PKA pathways.

Single-cell RNA sequencing of human prostate basal epithelial cells reveals zone-specific cellular populations and gene expression signatures

Despite evidence of genetic signatures in normal tissue correlating with disease risk, prospectively identifying genetic drivers and cell types that underlie subsequent pathologies has historically been challenging. The human prostate is an ideal model to investigate this phenomenon because it is anatomically segregated into three glandular zones (central, peripheral, and transition) that develop differential pathologies: prostate cancer in the peripheral zone (PZ) and benign prostatic hyperplasia (BPH) in the transition zone (TZ), with the central zone (CZ) rarely developing disease. More specifically, prostatic basal cells have been implicated in differentiation and proliferation during prostate development and regeneration; however, the contribution of zonal variation and the critical role of basal cells in prostatic disease etiology are not well understood. Using single-cell RNA sequencing of primary prostate epithelial cultures, we elucidated organ-specific, zone-specific, and cluster-specific gene expression differences in basal cells isolated from human prostate and seminal vesicle (SV). Aggregated analysis identified ten distinct basal clusters by Uniform Manifold Approximation and Projection. Organ specificity compared gene expression in SV with the prostate. As expected, SV cells were distinct from prostate cells by clustering, gene expression, and pathway analysis. For prostate zone specificity, we identified two CZ-specific clusters, while the TZ and PZ populations clustered together. Despite these similarities, differential gene expression was identified between PZ and TZ samples that correlated with gene expression profiles in prostate cancer and BPH, respectively. Zone-specific profiles and cell type-specific markers were validated using immunostaining and bioinformatic analyses of publicly available RNA-seq datasets. Understanding the baseline differences at the organ, zonal, and cellular level provides important insight into the potential drivers of prostatic disease and guides the investigation of novel preventive or curative treatments. Importantly, this study identifies multiple prostate basal cell populations and cell type-specific gene signatures within prostate basal epithelial cells that have potential critical roles in driving prostatic diseases. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts

Resistance to androgen deprivation therapies leads to metastatic castration-resistant prostate cancer (mCRPC) of adenocarcinoma (AdCa) origin that can transform to emergent aggressive variant prostate cancer (AVPC) which has neuroendocrine (NE)-like features. To this end, we used LuCaP patient-derived xenograft (PDX) tumors, clinically relevant models that reflects and retains key features of the tumor from advanced prostate cancer patients. Here we performed proteome and phosphoproteome characterization of 48 LuCaP PDX tumors and identified over 94,000 peptides and 9,700 phosphopeptides corresponding to 7,738 proteins. When we compared 15 NE versus 33 AdCa PDX samples, we identified 309 unique proteins and 476 unique phosphopeptides that were significantly altered and corresponded to proteins that are known to distinguish these two phenotypes. Assessment of protein and RNA concordance from these tumors revealed increased dissonance in transcriptionally regulated proteins in NE and metabolite interconversion enzymes in AdCa.

SOX2 expression in prostate cancer drives resistance to nuclear hormone receptor signaling inhibition through the WEE1/CDK1 signaling axis

The development of androgen receptor signaling inhibitor (ARSI) drug resistance in prostate cancer (PC) remains therapeutically challenging. Our group has described the role of sex determining region Y-box 2 (SOX2) overexpression in ARSI-resistant PC. Continuing this work, we report that NR3C1, the gene encoding glucocorticoid receptor (GR), is a novel SOX2 target in PC, positively regulating its expression. Similar to ARSI treatment, SOX2-positive PC cells are insensitive to GR signaling inhibition using a GR modulating therapy. To understand SOX2-mediated nuclear hormone receptor signaling inhibitor (NHRSI) insensitivity, we performed RNA-seq in SOX2-positive and -negative PC cells following NHRSI treatment. RNA-seq prioritized differentially regulated genes mediating the cell cycle, including G2 checkpoint WEE1 Kinase (WEE1) and cyclin-dependent kinase 1 (CDK1). Additionally, WEE1 and CDK1 were differentially expressed in PC patient tumors dichotomized by high vs low SOX2 gene expression. Importantly, pharmacological targeting of WEE1 (WEE1i) in combination with an ARSI or GR modulator re-sensitizes SOX2-positive PC cells to nuclear hormone receptor signaling inhibition in vitro, and WEE1i combined with ARSI significantly slowed tumor growth in vivo. Collectively, our data suggest SOX2 predicts NHRSI resistance, and simultaneously indicates the addition of WEE1i to improve therapeutic efficacy of NHRSIs in SOX2-positive PC.

iCancer-Pred: A tool for identifying cancer and its type using DNA methylation

DNA methylation is an important epigenetics, which occurs in the early stages of tumor formation. And it also is of great significance to find the relationship between DNA methylation and cancer. This paper proposes a novel model, iCancer-Pred, to identify cancer and classify its types further. The datasets of DNA methylation information of 7 cancer types have been collected from The Cancer Genome Atlas (TCGA). The coefficient of variation firstly is used to reduce the number of features, and then the elastic network is applied to select important features. Finally, a fully connected neural network is constructed with these selected features. In predicting seven types of cancers, iCancer-Pred has achieved an overall accuracy of over 97% accuracy with 5-fold cross-validation. For the convenience of the application, a user-friendly web server: http://bioinfo.jcu.edu.cn/cancer or http://121.36.221.79/cancer/ is available. And the source codes are freely available for download at https://github.com/Huerhu/iCancer-Pred.

Biological and Exploitable Crossroads for the Immune Response in Cancer and COVID-19

The outbreak of novel coronavirus disease 2019 (COVID-19) has exacted a disproportionate toll on cancer patients. The effects of anticancer treatments and cancer patients’ characteristics shared significant responsibilities for this dismal outcome; however, the underlying immunopathological mechanisms are far from being completely understood. Indeed, despite their different etiologies, SARS-CoV-2 infection and cancer unexpectedly share relevant immunobiological connections. In the pathogenesis and natural history of both conditions, there emerges the centrality of the immune response, orchestrating the timed appearance, functional and dysfunctional roles of multiple effectors in acute and chronic phases. A significant number (more than 600) of observational and interventional studies have explored the interconnections between COVID-19 and cancer, focusing on aspects as diverse as psychological implications and prognostic factors, with more than 4000 manuscripts published so far. In this review, we reported and discussed the dynamic behavior of the main cytokines and immune system signaling pathways involved in acute vs. early, and chronic vs. advanced stages of SARS-CoV-2 infection and cancer. We highlighted the biological similarities and active connections within these dynamic disease scenarios, exploring and speculating on possible therapeutic crossroads from one setting to the other.

Computational epigenetic landscape analysis reveals association of CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1 lncRNAs in prostate cancer progression through aberrant methylation

Aberrant expression of long non-coding RNAs (lncRNAs), caused by alterations in DNA methylation, is a driving factor in several cancers. Interplay between lncRNAs’ aberrant methylation and expression in prostate cancer (PC) progression still remains largely elusive. Therefore, this study characterized the genome-wide epigenetic landscape and expression profiles of lncRNAs and their clinical impact by integrating multi-omics data implementing bioinformatics approaches. We identified 62 differentially methylated CpG-sites (DMCs) and 199 differentially expressed lncRNAs (DElncRNAs), where 32 DElncRNAs contain 32 corresponding DMCs within promoter regions. Significant negative correlation was observed between 8 DElncRNAs-DMCs pairs. 3 (cg23614229, cg23957912, and cg11052780) DMCs and 4 (CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1) DElncRNAs were identified as high-risk factors for poor prognosis of PC patients. Overexpression of hypo-methylated CACNA1G-AS1, F11-AS1, and NNT-AS1 and down-regulation of hyper-methylated MSC-AS1 significantly lower the survival of PC patients and could be a potential prognostic and therapeutic biomarker. These DElncRNAs were found to be associated with several molecular functions whose deregulation can lead to cancer. Involvement of these epigenetically deregulated DElncRNAs in cancer-related biological processes was also noticed. These findings provide new insights into the understanding of lncRNA regulation by aberrant DNA methylation which will help to clarify the epigenetic mechanisms underlying PC.

O-GlcNAcylation and Its Role in Cancer-Associated Inflammation

Cancer cells, as well as surrounding stromal and inflammatory cells, form an inflammatory tumor microenvironment (TME) to promote all stages of carcinogenesis. As an emerging post-translational modification (PTM) of serine and threonine residues of proteins, O-linked-N-Acetylglucosaminylation (O-GlcNAcylation) regulates diverse cancer-relevant processes, such as signal transduction, transcription, cell division, metabolism and cytoskeletal regulation. Recent studies suggest that O-GlcNAcylation regulates the development, maturation and functions of immune cells. However, the role of protein O-GlcNAcylation in cancer-associated inflammation has been less explored. This review summarizes the current understanding of the influence of protein O-GlcNAcylation on cancer-associated inflammation and the mechanisms whereby O-GlcNAc-mediated inflammation regulates tumor progression. This will provide a theoretical basis for further development of anti-cancer therapies.

Analysis of a large prostate cancer family identifies novel and recurrent gene fusion events providing evidence for inherited predisposition

There is strong interest in the characterisation of gene fusions and their use to enhance clinical practices in prostate cancer (PrCa). Significantly, ~50% of prostate tumours harbour a gene fusion. Inherited factors are thought to predispose to these events but, to date, only one study has investigated gene fusions in a familial context. Here, we examined the prevalence and diversity of gene fusions in 14 tumours from a single large PrCa family, PcTas9, using the TruSight® RNA Fusion Panel and Sanger sequencing validation. These fusions were then explored in The Cancer Genome Atlas (TCGA) PrCa data set (n = 494). Overall, 64.3% of PcTas9 tumours harboured a gene fusion, including known erythroblast transformation-specific (ETS) fusions involving ERG and ETV1, and two novel gene fusions, C19orf48:ETV4 and RYBP:FOXP1. Although 3' ETS genes were overexpressed in PcTas9 and TCGA tumour samples, 3' fusion of FOXP1 did not appear to alter its expression. In addition, PcTas9 fusion carriers were more likely to have lower-grade disease than noncarriers (p = 0.02). Likewise, TCGA tumours with high-grade disease were less likely to harbour fusions (p = 0.03). Our study further implicates an inherited predisposition to PrCa gene fusion events, which are associated with less aggressive tumours. This knowledge could lead to clinical strategies to predict men at risk for fusion-positive PrCa and, thus, identify patients who are more or less at risk of aggressive disease and/or responsive to particular therapies.

Expressed prognostic biomarkers for primary prostate cancer independent of multifocality and transcriptome heterogeneity

The majority of prostate cancer patients are diagnosed with multiple primary malignant foci. The distinct foci are exceptionally heterogeneous with regard to DNA mutations, but whether this is recapitulated at the transcriptome level remains unknown. In this study, inter- and intrafocal heterogeneity has been assessed by whole-transcriptome sequencing of 87 tissue samples from 23 patients with localized prostate cancer treated with radical prostatectomy. From each patient, multiple samples were taken from one or more malignant foci, in addition to one sample from benign prostate tissue. Transcriptomic profiles of different malignant foci from the same patient showed a similar level of heterogeneity as tumors from different patients. This applies to expression of genes, fusion genes, and somatic mutations. Within-patient pair-wise analyses identified expression patterns linked to ETS status and extraprostatic extension. A set of 62 genes were found with low intrapatient heterogeneity and high interpatient heterogeneity, retaining stable expression profiles across foci within the same patient. Among these, 16 genes are associated with biochemical recurrence in a separately published study and are therefore nominated as biomarkers with prognostic value regardless of which malignant focus is sampled. In conclusion, an extensive heterogeneity in multifocal prostate cancer is confirmed at the gene expression level. Diagnostic biomarkers were identified for ETS positive samples and samples from extraprostatic extensions. Finally, prognostic biomarkers independent of multifocal heterogeneity were found.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads

BACKGROUND

The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.

RESULTS

We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.

CONCLUSIONS

Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

SOX2 mediates metabolic reprogramming of prostate cancer cells

New strategies are needed to predict and overcome metastatic progression and therapy resistance in prostate cancer. One potential clinical target is the stem cell transcription factor SOX2, which has a critical role in prostate development and cancer. We thus investigated the impact of SOX2 expression on patient outcomes and its function within prostate cancer cells. Analyses of SOX2 expression among a case-control cohort of 1028 annotated tumor specimens demonstrated that SOX2 expression confers a more rapid time to metastasis and decreased patient survival after biochemical recurrence. SOX2 ChIP-Seq analyses revealed SOX2-binding sites within prostate cancer cells which differ significantly from canonical embryonic SOX2 gene targets, and prostate-specific SOX2 gene targets are associated with multiple oncogenic pathways. Interestingly, phenotypic and gene expression analyses after CRISPR-mediated deletion of SOX2 in castration-resistant prostate cancer cells, as well as ectopic SOX2 expression in androgen-sensitive prostate cancer cells, demonstrated that SOX2 promotes changes in multiple metabolic pathways and metabolites. SOX2 expression in prostate cancer cell lines confers increased glycolysis and glycolytic capacity, as well as increased basal and maximal oxidative respiration and increased spare respiratory capacity. Further, SOX2 expression was associated with increased quantities of mitochondria, and metabolomic analyses revealed SOX2-associated changes in the metabolism of purines, pyrimidines, amino acids and sugars, and the pentose phosphate pathway. Analyses of SOX2 gene targets with central functions metabolism (CERK, ECHS1, HS6SDT1, LPCAT4, PFKP, SLC16A3, SLC46A1, and TST) document significant expression correlation with SOX2 among RNA-Seq datasets derived from patient tumors and metastases. These data support a key role for SOX2 in metabolic reprogramming of prostate cancer cells and reveal new mechanisms to understand how SOX2 enables metastatic progression, lineage plasticity, and therapy resistance. Further, our data suggest clinical opportunities to exploit SOX2 as a biomarker for staging and imaging, as well as a potential pharmacologic target.

NF-κB signaling in inflammation and cancer

Since nuclear factor of κ-light chain of enhancer-activated B cells (NF-κB) was discovered in 1986, extraordinary efforts have been made to understand the function and regulating mechanism of NF-κB for 35 years, which lead to significant progress. Meanwhile, the molecular mechanisms regulating NF-κB activation have also been illuminated, the cascades of signaling events leading to NF-κB activity and key components of the NF-κB pathway are also identified. It has been suggested NF-κB plays an important role in human diseases, especially inflammation-related diseases. These studies make the NF-κB an attractive target for disease treatment. This review aims to summarize the knowledge of the family members of NF-κB, as well as the basic mechanisms of NF-κB signaling pathway activation. We will also review the effects of dysregulated NF-κB on inflammation, tumorigenesis, and tumor microenvironment. The progression of the translational study and drug development targeting NF-κB for inflammatory diseases and cancer treatment and the potential obstacles will be discussed. Further investigations on the precise functions of NF-κB in the physiological and pathological settings and underlying mechanisms are in the urgent need to develop drugs targeting NF-κB for inflammatory diseases and cancer treatment, with minimal side effects.

Regulation of Nuclear Factor-kappaB Function by O-GlcNAcylation in Inflammation and Cancer

Nuclear factor-kappaB (NF-κB) is a pleiotropic, evolutionarily conserved transcription factor family that plays a central role in regulating immune responses, inflammation, cell survival, and apoptosis. Great strides have been made in the past three decades to understand the role of NF-κB in physiological and pathological conditions. Carcinogenesis is associated with constitutive activation of NF-κB that promotes tumor cell proliferation, angiogenesis, and apoptosis evasion. NF-κB is ubiquitously expressed, however, its activity is under tight regulation by inhibitors of the pathway and through multiple posttranslational modifications. O-GlcNAcylation is a dynamic posttranslational modification that controls NF-κB-dependent transactivation. O-GlcNAcylation acts as a nutrient-dependent rheostat of cellular signaling. Increased uptake of glucose and glutamine by cancer cells enhances NF-κB O-GlcNAcylation. Growing evidence indicates that O-GlcNAcylation of NF-κB is a key molecular mechanism that regulates cancer cell proliferation, survival and metastasis and acts as link between inflammation and cancer. In this review, we are attempting to summarize the current understanding of the cohesive role of NF-κB O-GlcNAcylation in inflammation and cancer.

NF-κB and Human Cancer: What Have We Learned over the Past 35 Years?

Transcription factor NF-κB has been extensively studied for its varied roles in cancer development since its initial characterization as a potent retroviral oncogene. It is now clear that NF-κB also plays a major role in a large variety of human cancers, including especially ones of immune cell origin. NF-κB is generally constitutively or aberrantly activated in human cancers where it is involved. These activations can occur due to mutations in the NF-κB transcription factors themselves, in upstream regulators of NF-κB, or in pathways that impact NF-κB. In addition, NF-κB can be activated by tumor-assisting processes such as inflammation, stromal effects, and genetic or epigenetic changes in chromatin. Aberrant NF-κB activity can affect many tumor-associated processes, including cell survival, cell cycle progression, inflammation, metastasis, angiogenesis, and regulatory T cell function. As such, inhibition of NF-κB has often been investigated as an anticancer strategy. Nevertheless, with a few exceptions, NF-κB inhibition has had limited success in human cancer treatment. This review covers general themes that have emerged regarding the biological roles and mechanisms by which NF-κB contributes to human cancers and new thoughts on how NF-κB may be targeted for cancer prognosis or therapy.

A deep imputation and inference framework for estimating personalized and race-specific causal effects of genomic alterations on PSA

Prostate Specific Antigen (PSA) level in the serum is one of the most widely used markers in monitoring prostate cancer (PCa) progression, treatment response, and disease relapse. Although significant efforts have been taken to analyze various socioeconomic and cultural factors that contribute to the racial disparities in PCa, limited research has been performed to quantitatively understand how and to what extent molecular alterations may impact differential PSA levels present at varied tumor status between African-American and European-American men. Moreover, missing values among patients add another layer of difficulty in precisely inferring their outcomes. In light of these issues, we propose a data-driven, deep learning-based imputation and inference framework (DIIF). DIIF seamlessly encapsulates two modules: an imputation module driven by a regularized deep autoencoder for imputing critical missing information and an inference module in which two deep variational autoencoders are coupled with a graphical inference model to quantify the personalized and race-specific causal effects. Large-scale empirical studies on the independent sub-cohorts of The Cancer Genome Atlas (TCGA) PCa patients demonstrate the effectiveness of DIIF. We further found that somatic mutations in TP53, ATM, PTEN, FOXA1, and PIK3CA are statistically significant genomic factors that may explain the racial disparities in different PCa features characterized by PSA.

HOX genes and the NF-κB pathway: A convergence of developmental biology, inflammation and cancer biology

The roles of HOX transcription factors as oncogenes and tumor suppressor genes, and the NF-KB pathway in chronic inflammation, both leading to cancer are well-established. HOX transcription factors are members of an evolutionarily conserved family of proteins required for anteroposterior body axis patterning during embryonic development, and are often dysregulated in cancer. The NF-KB pathway aids inflammation and immunity but it is also important during embryonic development. It is frequently activated in both solid and hematological malignancies. NF-KB and HOX proteins can influence each other through mutual transcriptional regulation, protein-protein interactions, and regulation of upstream and downstream interactors. These interactions have important implications both in homeostasis and in disease. In this review, we summarize the role of HOX proteins in regulating inflammation in homeostasis and disease- with a particular emphasis on cancer. We also describe the relationship between HOX genes and the NF-KB pathway, and discuss potential therapeutic strategies.

Application of Single-Cell Sequencing to Immunotherapy

Cancer is a highly complex and heterogeneous disease and immunotherapy has shown promise as a therapeutic approach. The increased resolution afforded by single-cell analysis offers the hope of finding and characterizing previously underappreciated populations of cells that could prove useful in understanding cancer progression and treatment. Urologic and prostate cancers are inherently heterogeneous diseases, and the potential for single-cell analysis to help understand and develop immunotherapeutic approaches to treat these diseases is very exciting. In this review, we view cancer immunotherapy through a single-cell lens and discuss the state-of-the-art technologies that enable advances in this field.

Imaging Fibroblast Activation Protein Alpha Improves Diagnosis of Metastatic Prostate Cancer with Positron Emission Tomography

PURPOSE

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal, heterogeneous disease with few therapeutic strategies that significantly prolong survival. Innovative therapies for mCRPC are needed; however, the development of new therapies relies on accurate imaging to assess metastasis and monitor response. Standard imaging modalities for prostate cancer require improvement and there remains a need for selective and sensitive imaging probes that can be widely used in patients with mCRPC.

EXPERIMENTAL DESIGN

We evaluated the transmembrane protease fibroblast activation protein alpha (FAP) as a targetable cell surface antigen for mCRPC. Genomic and IHC analyses were performed to investigate FAP expression in prostate cancer. Our FAP-targeted antibody imaging probe, [⁸⁹Zr]Zr-B12 IgG, was evaluated by PET/CT imaging in preclinical prostate cancer models.

RESULTS

Analysis of patient data documented FAP overexpression in metastatic disease across tumor subtypes. PET imaging with [⁸⁹Zr]Zr-B12 IgG demonstrated high tumor uptake and long-term retention of the probe in the preclinical models examined. FAP-positive stroma tumor uptake of [⁸⁹Zr]Zr-B12 IgG was 5-fold higher than the isotype control with mean %ID/cc of 34.13 ± 1.99 versus 6.12 ± 2.03 (n = 3/group; P = 0.0006) at 72 hours. Ex vivo biodistribution corroborated these results documenting rapid blood clearance by 24 hours and high tumor uptake of [⁸⁹Zr]Zr-B12 IgG by 72 hours.

CONCLUSIONS

Our study reveals FAP as a target for imaging the tumor microenvironment of prostate cancer. Validation of [⁸⁹Zr]Zr-B12 IgG as a selective imaging probe for FAP-expressing tumors presents a new approach for noninvasive PET/CT imaging of mCRPC.

MEIS-mediated suppression of human prostate cancer growth and metastasis through HOXB13-dependent regulation of proteoglycans

The molecular roles of HOX transcriptional activity in human prostate epithelial cells remain unclear, impeding the implementation of new treatment strategies for cancer prevention and therapy. MEIS proteins are transcription factors that bind and direct HOX protein activity. MEIS proteins are putative tumor suppressors that are frequently silenced in aggressive forms of prostate cancer. Here we show that MEIS1 expression is sufficient to decrease proliferation and metastasis of prostate cancer cells in vitro and in vivo murine xenograft models. HOXB13 deletion demonstrates that the tumor-suppressive activity of MEIS1 is dependent on HOXB13. Integration of ChIP-seq and RNA-seq data revealed direct and HOXB13-dependent regulation of proteoglycans including decorin (DCN) as a mechanism of MEIS1-driven tumor suppression. These results define and underscore the importance of MEIS1-HOXB13 transcriptional regulation in suppressing prostate cancer progression and provide a mechanistic framework for the investigation of HOXB13 mutants and oncogenic cofactors when MEIS1/2 are silenced.

Novel Gene Fusions in Glioblastoma Tumor Tissue and Matched Patient Plasma

Sequencing studies have provided novel insights into the heterogeneous molecular landscape of glioblastoma (GBM), unveiling a subset of patients with gene fusions. Tissue biopsy is highly invasive, limited by sampling frequency and incompletely representative of intra-tumor heterogeneity. Extracellular vesicle-based liquid biopsy provides a minimally invasive alternative to diagnose and monitor tumor-specific molecular aberrations in patient biofluids. Here, we used targeted RNA sequencing to screen GBM tissue and the matched plasma of patients (n = 9) for RNA fusion transcripts. We identified two novel fusion transcripts in GBM tissue and five novel fusions in the matched plasma of GBM patients. The fusion transcripts FGFR3-TACC3 and VTI1A-TCF7L2 were detected in both tissue and matched plasma. A longitudinal follow-up of a GBM patient with a FGFR3-TACC3 positive glioma revealed the potential of monitoring RNA fusions in plasma. In summary, we report a sensitive RNA-seq-based liquid biopsy strategy to detect RNA level fusion status in the plasma of GBM patients.

Tumor-infiltrating Leukocytes Suppress Local Inflammation Via Interleukin-1 Receptor Antagonist in a Syngeneic Prostate Cancer Model

BACKGROUND

Several lines of evidence have demonstrated the tumor-promoting function of inflammation. Since many chemokines are important in coordinating immune cells during inflammation, monitoring intratumoral chemokines provides a way to study the tumor microenvironment.

METHODS

To identify tumorigenic chemokines, we compared two syngeneic mouse prostate cancer cell lines by an antibody array and quantitative reverse-transcription polymerase chain reaction (RT-PCR). The tumor microenvironment was analyzed by monitoring gene expressions in mouse tumor tissues, primary cells, and tumor-infiltrating leukocytes (TILs).

RESULT

We identified a group of pro-inflammatory chemokines associated with a tumorigenic transgenic adenocarcinoma mouse prostate (TRAMP)-C1 cell line. In the tumor microenvironment, the TILs secrete a natural anti-inflammatory factor, interleukin-1 receptor antagonist (IL1RN), which inhibits the functions of pro-inflammatory molecules and likely accounts for tumor type-specific anti-inflammation functions.

CONCLUSION

Our results support that tumor cells recruit TILs by pro-inflammatory chemokines to establish an IL1RN-mediated anti-inflammatory environment in the syngeneic prostate cancer model.

Inferring Personalized and Race-Specific Causal Effects of Genomic Aberrations on Gleason Scores: A Deep Latent Variable Model

Extensive research has examined socioeconomic factors influencing prostate cancer (PCa) disparities. However, to what extent molecular and genetic mechanisms may also contribute to these inequalities still remains elusive. Although various in vitro, in vivo, and population studies have originated to address this issue, they are often very costly and time-consuming by nature. In this work, we attempt to explore this problem by a preliminary study, where a joint deep latent variable model (DLVM) is proposed to in silico quantify the personalized and race-specific effects that a genomic aberration may exert on the Gleason Score (GS) of each individual PCa patient. The core of the proposed model is a deep variational autoencoder (VAE) framework, which follows the causal structure of inference with proxies. Extensive experimental results on The Cancer Genome Atlas (TCGA) 270 European-American (EA) and 43 African-American (AA) PCa patients demonstrate that ERG fusions, somatic mutations in SPOP and ATM, and copy number alterations (CNAs) in ERG are the statistically significant genomic factors across all low-, intermediate-, and high-grade PCa that may explain the disparities between these two groups. Moreover, compared to a state-of-the-art deep inference method, our proposed method achieves much higher precision in causal effect inference in terms of the impact of a studied genomic aberration on GS. Further validation on an independent set and the assessment of the genomic-risk scores along with corresponding confidence intervals not only validate our results but also provide valuable insight to the observed racial disparity between these two groups regarding PCa metastasis. The pinpointed significant genomic factors may shed light on the molecular mechanism of cancer disparities in PCa and warrant further investigation.

Prediction of tumor location in prostate cancer tissue using a machine learning system on gene expression data

BACKGROUND

Finding the tumor location in the prostate is an essential pathological step for prostate cancer diagnosis and treatment. The location of the tumor - the laterality - can be unilateral (the tumor is affecting one side of the prostate), or bilateral on both sides. Nevertheless, the tumor can be overestimated or underestimated by standard screening methods. In this work, a combination of efficient machine learning methods for feature selection and classification are proposed to analyze gene activity and select them as relevant biomarkers for different laterality samples.

RESULTS

A data set that consists of 450 samples was used in this study. The samples were divided into three laterality classes (left, right, bilateral). The aim of this work is to understand the genomic activity in each class and find relevant genes as indicators for each class with nearly 99% accuracy. The system identified groups of differentially expressed genes (RTN1, HLA-DMB, MRI1) that are able to differentiate samples among the three classes.

CONCLUSION

The proposed method was able to detect sets of genes that can identify different laterality classes. The resulting genes are found to be strongly correlated with disease progression. HLA-DMB and EIF4G2, which are detected in the set of genes can detect the left laterality, were reported earlier to be in the same pathway called Allograft rejection SuperPath.

Structural variation and fusion detection using targeted sequencing data from circulating cell free DNA

MOTIVATION

Cancer is a complex disease that involves rapidly evolving cells, often forming multiple distinct clones. In order to effectively understand progression of a patient-specific tumor, one needs to comprehensively sample tumor DNA at multiple time points, ideally obtained through inexpensive and minimally invasive techniques. Current sequencing technologies make the 'liquid biopsy' possible, which involves sampling a patient's blood or urine and sequencing the circulating cell free DNA (cfDNA). A certain percentage of this DNA originates from the tumor, known as circulating tumor DNA (ctDNA). The ratio of ctDNA may be extremely low in the sample, and the ctDNA may originate from multiple tumors or clones. These factors present unique challenges for applying existing tools and workflows to the analysis of ctDNA, especially in the detection of structural variations which rely on sufficient read coverage to be detectable.

RESULTS

Here we introduce SViCT , a structural variation (SV) detection tool designed to handle the challenges associated with cfDNA analysis. SViCT can detect breakpoints and sequences of various structural variations including deletions, insertions, inversions, duplications and translocations. SViCT extracts discordant read pairs, one-end anchors and soft-clipped/split reads, assembles them into contigs, and re-maps contig intervals to a reference genome using an efficient k-mer indexing approach. The intervals are then joined using a combination of graph and greedy algorithms to identify specific structural variant signatures. We assessed the performance of SViCT and compared it to state-of-the-art tools using simulated cfDNA datasets with properties matching those of real cfDNA samples. The positive predictive value and sensitivity of our tool was superior to all the tested tools and reasonable performance was maintained down to the lowest dilution of 0.01% tumor DNA in simulated datasets. Additionally, SViCT was able to detect all known SVs in two real cfDNA reference datasets (at 0.6-5% ctDNA) and predict a novel structural variant in a prostate cancer cohort.

AVAILABILITY

SViCT is available at https://github.com/vpc-ccg/svict. Contact:faraz.hach@ubc.ca.

The role of WNT10B in normal prostate gland development and prostate cancer

BACKGROUND

WNT signaling is implicated in embryonic development, and in adult tissue homeostasis, while its deregulation is evident in disease. This study investigates the unique roles of canonical WNT10B in both normal prostate development and prostate cancer (PCa) progression.

METHODS

Organ culture and rat ventral prostates (VPs) were used to study Wnt10b ontogeny and growth effect of WNT10B protein. PB-SV40 LTag rat VPs were utilized for Wnt expression polymerase chain reaction (PCR) array and immunohistochemistry. Human localized PCa tissue microarrays (TMAs) were investigated for differential WNT10B expression. Human RNA-seq data sets were queried for differential expression of WNT10B in metastatic and localized PCa. Knockdown of WNT10B in PC3 cells was utilized to study its effects on proliferation, stemness, epithelial to mesenchymal transition (EMT), and xenograft propagation.

RESULTS

Wnt10b expression was highest at birth and rapidly declined in the postnatal rat VP. Exogenous WNT10B addition to culture developing VPs decreased growth suggesting an antiproliferative role. VPs from PB-SV40 LTag rats with localized PCa showed a 25-fold reduction in Wnt10b messenger RNA (mRNA) expession, confirmed at the protein level. Human PCa TMAs revealed elevated WNT10B protein in prostate intraepithelial neoplasia compared with normal prostates but reduced levels in localized PCa specimens. In contrast, RNA-seq data set of annotated human PCa metastasis found a significant increase in WNT10B mRNA expression compared with localized tumors suggesting stage-specific functions of WNT10B. Similarly, WNT10B mRNA levels were increased in metastatic cell lines PC3, PC3M, as well as in HuSLC, a PCa stem-like cell line, as compared with disease-free primary prostate epithelial cells. WNT10B knockdown in PC3 cells reduced expression of EMT genes, MMP9 and stemness genes NANOG and SOX2 and markedly reduced the stem cell-like side population. Furthermore, loss of WNT10B abrogated the ability of PC3 cells to propagate tumors via serial transplantation.

CONCLUSIONS

Taken together, these results suggest a dual role for WNT10B in normal development and in PCa progression with opposing functions depending on disease stage. We propose that decreased WNT10B levels in localized cancer allow for a hyperproliferative state, whereas increased levels in advanced disease confer a stemness and malignant propensity which is mitigated by knocking down WNT10B levels. This raises the potential for WNT10B as a novel target for therapeutic intervention in metastatic PCa.

PEG10 Promoter-Driven Expression of Reporter Genes Enables Molecular Imaging of Lethal Prostate Cancer

The retrotransposon-derived paternally expressed gene 10 (PEG10) protein is ordinarily expressed at high levels in the placenta. Recently, it was discovered that PEG10 isoforms promote the progression of prostate cancer to a highly lethal androgen receptor (AR)-negative phenotype. The presence of PEG10 in other subtypes of prostate cancer has not been explored and a utility for PEG10 overexpression has not been developed. Here, we found that in addition to AR-null disease, PEG10 was also expressed in prostate cancer with constitutively active AR-splice variants. A molecular genetic imaging strategy for noninvasive imaging of AR-splice variant prostate cancer was developed by utilizing the cancer specificity of the PEG10 promoter to drive the expression of reporter genes. Plasmid insertion of a PEG10 promoter sequence optimized for enhanced output upstream of a reporter gene allowed detection of prostate cancer by near-infrared and positron emission tomography imaging after systemic administration of the plasmid in vivo. PEG10 expressing subcutaneous xenograft and intratibial tumor models were imaged by both modalities using this molecular genetic imaging strategy. This study demonstrates a preclinical proof-of-concept that the PEG10 promoter is a powerful and specific tool that can be utilized for noninvasive detection of aggressive prostate cancer subtypes. SIGNIFICANCE: PEG10 is expressed by prostate cancer with constitutively active AR-splice variants that can be exploited for noninvasive molecular imaging of this aggressive prostate cancer subytpe.

Comparative RNA-seq analysis reveals dys-regulation of major canonical pathways in ERG-inducible LNCaP cell progression model of prostate cancer

Prostate Cancer (CaP) is the second leading cause of cancer related death in USA. In human CaP, gene fusion between androgen responsive regulatory elements at the 5'-untranslated region of TMPRSS2 and ETS-related genes (ERG) is present in at least 50% of prostate tumors. Here we have investigated the unique cellular transcriptome associated with over-expression of ERG in ERG-inducible LNCaP cell model system of human CaP. Comprehensive transcriptome analyses reveal a distinct signature that distinguishes ERG dependent and independent CaP in LNCaP cells. Our data highlight a significant heterogeneity among the transcripts. Out of the 526 statistically significant differentially expressed genes, 232 genes are up-regulated and 294 genes are down-regulated in response to ERG. These ERG-associated genes are linked to several major cellular pathways, cell cycle regulation being the most significant. Consistently our data indicate that ERG plays a key role in modulating the expression of genes required for G1 to S phase transition, particularly those that affect cell cycle arrest at G1 phase. Moreover, cell cycle arrest in response to ERG appears to be promoted by induction of p21 in a p53 independent manner. These findings may provide new insights into mechanisms that promote growth and progression of CaP.

RSRC1 suppresses gastric cancer cell proliferation and migration by regulating PTEN expression

Arginine/serine-rich coiled coil 1 (RSRC1) is a gene which plays a significant role in the constitutive and alternative splicing of mRNA and transcriptional regulation. It has been implicated in various neurological disorders, as well as in cancer. However, its role in gastric cancer (GC) remains unknown. Thus, the present study aimed to investigate the role of RSRC1 in GC. RSRC1 expression in GC tissues was determined by RT-qPCR and immunohistochemical staining. The effects of RSRC1 on cell proliferation and migration were detected using a Cell Counting Kit-8 assay, 5-ethynyl-2′-deoxyuridine (EdU) incorporation assay and a Transwell migration assay. Western blot analysis and RT-qPCR were used to explore the molecular mechanisms of of action of RSRC1 in GC. The results indicated that RSRC1 expression was downregulated in GC tissues compared to paired normal tissues and the reduced expression of RSRC1 was shown to contribute to a poor prognosis of patients with GC. RSRC1 knockdown promoted the proliferation and migration of GC cells. In addition, the knockdown of RSRC1 decreased the expression of phosphatase and tensin homolog deleted on chromosome 10 (PTEN), a potent tumor suppressor gene controlling cellular growth and viability. On the whole, the findings of the present study indicate that RSRC1 functions as a tumor suppressor gene in GC and that it may exert its effects by regulating PTEN expression.

Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. We have isolated transcripts that have the potential to serve as prognostic indicators and may have tremendous value in guiding treatment decisions. Analysis of normal versus malignant prostate cancer data sets indicates differential expression of the genes HEATR5B, DDC, and GABPB1-AS1 as potential prostate cancer biomarkers. Our study also supports PTGFR, NREP, SCARNA22, DOCK9, FLVCR2, IK2F3, USP13, and CLASP1 as potential biomarkers to predict prostate cancer progression, especially between stage II and subsequent stages of the disease.

The Identification of Potential Biomarkers and Biological Pathways in Prostate Cancer

Purpose: The present study aims to explore the potential mechanisms contributing to prostate cancer (PCa), screen the hub genes, and identify potential biomarkers and correlated pathways of PCa progression.

Methods: The PCa gene expression profile GSE3325 was operated to analyze the differentially expressed genes (DEGs). DAVID was used to evaluate Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was constructed to visualize interactions of the hub genes. The prognostic and diagnostic analysis of these hub genes was carried out to evaluate their potential effects on PCa.

Results: A total of 847 DEGs were identified (427 upregulated genes and 420 downregulated genes). Meanwhile, top15 hub genes were showed. GO analysis displayed that the DEGs were mainly enriched in cell cycle, DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest and proteinaceous extracellular matrix. KEGG analysis indicated the DEGs were enriched in the p53 signaling pathway and cell cycle pathway. The GO and KEGG enrichment analyses for the DEGs disclosed important biological features of PCa. PPI network showed the interaction of top 15 hub genes. Gene Set Enrichment Analysis (GSEA) revealed that some of the hub genes were associated with biochemical recurrence (BCR) and metastasis of PCa. Some top hub genes were distinctive and new discoveries compared with that of the existing associated researches.

Conclusions: Our analysis revealed that the changes of cell cycle and p53 signaling pathway are two major signatures of PCa. CENPA, KIF20A and CDCA8 might promote the tumorigenesis and progression of PCa, especially in BCR and metastasis, which could be novel therapeutic targets and biomarkers for diagnosis, prognosis of PCa.

An AR-ERG transcriptional signature defined by long-range chromatin interactomes in prostate cancer cells

The aberrant activities of transcription factors such as the androgen receptor (AR) underpin prostate cancer development. While the AR cis-regulation has been extensively studied in prostate cancer, information pertaining to the spatial architecture of the AR transcriptional circuitry remains limited. In this paper, we propose a novel framework to profile long-range chromatin interactions associated with AR and its collaborative transcription factor, erythroblast transformation-specific related gene (ERG), using chromatin interaction analysis by paired-end tag (ChIA-PET). We identified ERG-associated long-range chromatin interactions as a cooperative component in the AR-associated chromatin interactome, acting in concert to achieve coordinated regulation of a subset of AR target genes. Through multifaceted functional data analysis, we found that AR-ERG interaction hub regions are characterized by distinct functional signatures, including bidirectional transcription and cotranscription factor binding. In addition, cancer-associated long noncoding RNAs were found to be connected near protein-coding genes through AR-ERG looping. Finally, we found strong enrichment of prostate cancer genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) at AR-ERG co-binding sites participating in chromatin interactions and gene regulation, suggesting GWAS target genes identified from chromatin looping data provide more biologically relevant findings than using the nearest gene approach. Taken together, our results revealed an AR-ERG-centric higher-order chromatin structure that drives coordinated gene expression in prostate cancer progression and the identification of potential target genes for therapeutic intervention.

Identification and characterization of novel fusion genes in prostate cancer by targeted RNA capture and next-generation sequencing

Gene fusions play critical roles in the development and progression of prostate cancer, and have been used as molecular biomarkers for diagnosis of the malignant disease. To further explore the novel fusions in prostate cancer, we performed targeted RNA capture and next-generation sequencing in a cohort of 52 prostate cancer patients, identified and validated 14 fusion events (7 types of fusion genes) in 12 cases, including three novel fusion genes. We characterized a chromosome rearrangement-induced trigenic KLK2-DGKB-ETV1 fusion, which may function as a non-coding RNA to upregulate the expression of the wild-type ETV1 protein in the tumor tissue. Additionally, we detected two novel fusion forms of HNRNPA2B1-ETV1 and SLC45A2-AMACR fusions, respectively. Interestingly, fusion events participated by kinase genes, which frequently occurred in other human cancers, were not present in these prostate cancer cases, suggesting discrepant gene fusion patterns in different cancers. These findings expand the genetic spectrum of prostate cancer and provide insight into diagnosis of this prevalent disease.

ERG alterations and mTOR pathway activation in primary prostate carcinomas developing castration-resistance

INTRODUCTION

One of the most common sites of distant metastasization of prostate cancer is bone, but to date reliable biomarkers able to predict the risk and timing of bone metastasization are still lacking.

PATIENTS AND METHODS

Surgically resected paraffin embedded samples from 12 primary prostate cancers that developed metachronous bone metastasis at different time points were studied (six cases within 2 years, six cases after 5 years from surgery). A targeted next-generation DNA and RNA sequencing able to assess simultaneously mutations, copy number alterations and fusion events of multiple genes was used. Immunohistochemistry was used to assess mTOR pathway activation.

RESULTS

Rearrangements of ETS family genes, molecular alterations in PTEN and TP53 genes were detected in 10, 6 and 5 cancers, respectively. Nine samples showed TMPRSS2-ERG fusions, which were associated with increased ERG expression at immunohistochemistry. mTOR pathway activation was documented in 6 patients, with a clear trend of prevalence in late-metastatic patients (p = 0.08).

CONCLUSIONS

A simultaneous next-generation targeted DNA and RNA sequencing is applicable on routine formalin-fixed paraffin-embedded tissues to assess the multigene molecular asset of individual prostate cancers. This approach, coupled with immunohistochemistry for ERG and mTOR pathway proteins, may help to better characterize prostate cancer molecular features with a potential impact on clinical decisions.

Targeting IKKβ in Cancer: Challenges and Opportunities for the Therapeutic Utilisation of IKKβ Inhibitors

Deregulated NF-κB signalling is implicated in the pathogenesis of numerous human inflammatory disorders and malignancies. Consequently, the NF-κB pathway has attracted attention as an attractive therapeutic target for drug discovery. As the primary, druggable mediator of canonical NF-κB signalling the IKKβ protein kinase has been the historical focus of drug development pipelines. Thousands of compounds with activity against IKKβ have been characterised, with many demonstrating promising efficacy in pre-clinical models of cancer and inflammatory disease. However, severe on-target toxicities and other safety concerns associated with systemic IKKβ inhibition have thus far prevented the clinical approval of any IKKβ inhibitors. This review will discuss the potential reasons for the lack of clinical success of IKKβ inhibitors to date, the challenges associated with their therapeutic use, realistic opportunities for their future utilisation, and the alternative strategies to inhibit NF-κB signalling that may overcome some of the limitations associated with IKKβ inhibition.

MEIS1 and MEIS2 Expression and Prostate Cancer Progression: A Role For HOXB13 Binding Partners in Metastatic Disease

Purpose: Germline mutations within the MEIS-interaction domain of HOXB13 have implicated a critical function for MEIS-HOX interactions in prostate cancer etiology and progression. The functional and predictive role of changes in MEIS expression within prostate tumor progression, however, remain largely unexplored.Experimental Design: Here we utilize RNA expression datasets, annotated tissue microarrays, and cell-based functional assays to investigate the role of MEIS1 and MEIS2 in prostate cancer and metastatic progression.Results: These analyses demonstrate a stepwise decrease in the expression of both MEIS1 and MEIS2 from benign epithelia, to primary tumor, to metastatic tissues. Positive expression of MEIS proteins in primary tumors, however, is associated with a lower hazard of clinical metastasis (HR = 0.28) after multivariable analysis. Pathway and gene set enrichment analyses identified MEIS-associated networks involved in cMYC signaling, cellular proliferation, motility, and local tumor environment. Depletion of MEIS1 and MEIS2 resulted in increased tumor growth over time in vivo, and decreased MEIS expression in both patient-derived tumors and MEIS-depleted cell lines was associated with increased expression of the protumorigenic genes cMYC and CD142, and decreased expression of AXIN2, FN1, ROCK1, SERPINE2, SNAI2, and TGFβ2.Conclusions: These data implicate a functional role for MEIS proteins in regulating cancer progression, and support a hypothesis whereby tumor expression of MEIS1 and MEIS2 expression confers a more indolent prostate cancer phenotype, with a decreased propensity for metastatic progression. Clin Cancer Res; 24(15); 3668-80. ©2018 AACR.

Isolation and genome sequencing of individual circulating tumor cells using hydrogel encapsulation and laser capture microdissection

Circulating tumor cells (CTCs) are malignant cells released into the bloodstream with the potential to form metastases in secondary sites. These cells, acquired non-invasively, represent a sample of highly relevant tumor tissue that is an alternative to difficult and low-yield tumor biopsies. In recent years, there has been growing interest in genomic profiling of CTCs to enable longitudinal monitoring of the tumor's adaptive response to therapy. However, due to their extreme rarity, genotyping CTCs has proved challenging. Relevant mutations can be masked by leukocyte contamination in isolates. Heterogeneity between subpopulations of tumor cells poses an additional obstacle. Recent advances in single-cell sequencing can overcome these limitations but isolation of single CTCs is prone to cell loss and is prohibitively difficult and time consuming. To address these limitations, we developed a single cell sample preparation and genome sequencing pipeline that combines biophysical enrichment and single cell isolation using laser capture microdissection (LCM). A key component of this process is the encapsulation of enriched CTC sample in a hydrogel matrix, which enhances the efficiency of single-cell isolation by LCM, and is compatible with downstream sequencing. We validated this process by sequencing of single CTCs and cell free DNA (cfDNA) from a single patient with castration resistant prostate cancer. Identical mutations were observed in prostate cancer driver genes (TP53, PTEN, FOXA1) in both single CTCs and cfDNA. However, two independently isolated CTCs also had identical missense mutations in the genes for ATR serine/threonine kinase, KMT2C histone methyltransferase, and FANCC DNA damage repair gene. These mutations may be missed by bulk sequencing libraries, whereas single cell sequencing could potentially enable the characterization of key CTC subpopulations that arise during metastasis.

Novel transcription-induced fusion RNAs in prostate cancer

Prostate cancer is a clinically and pathologically heterogeneous disease with a broad spectrum of molecular abnormalities in the genome and transcriptome. One key feature is the involvement of chromosomal rearrangements creating fusion genes. Recent RNA-sequencing technology has uncovered that fusions which are not caused by chromosomal rearrangements, but rather meditated at transcription level, are common in both healthy and diseased cells. Such fusion transcripts have been proven highly associated with prostate cancer development and progression. To discover novel fusion transcripts, we analyzed RNA sequencing data from 44 primary prostate tumors and matched benign tissues from The Cancer Genome Atlas. Twenty-one high-confident candidates were significantly enriched in malignant vs. benign samples. Thirteen of the candidates have not previously been described in prostate cancer, and among them, five long intergenic non-coding RNAs are involved as fusion partners. Their expressions were validated in 50 additional prostate tumor samples and seven prostate cancer cell lines. For four fusion transcripts, we found a positive correlation between their expression and the expression of the 3′ partner gene. Among these, differential exon usage and qRT-PCR analyses in particular support that SLC45A3-ELK4 is mediated by an RNA polymerase read-through mechanism.

Decreased expression of SFRP2 promotes development of the pituitary corticotroph adenoma by upregulating Wnt signaling

Cushing's disease is primarily caused by pituitary adrenocorticotropin‑secreting adenoma. However, its pathogenesis has remained obscure. In the present study, whole transcriptome analysis was performed by RNA sequencing (RNA‑Seq) and expression of secreted frizzled‑related protein 2 (SFRP2) was decreased in corticotroph tumors compared with normal pituitary glands. Furthermore, the RNA‑Seq results were validated and the expression of SFRP2 in tumor tissues was analyzed by comparing another cohort of 23 patients with Cushing's disease and 3 normal human pituitary samples using reverse transcription‑quantitative polymerase chain reaction, western blot and immunohistochemistry staining. Clinically, there was an association between lower SFRP2 expression and aggressive adenoma characteristics, including larger size and invasiveness. Conversely, SFRP2 overexpression reduced the ability of AtT20 cells to proliferate and migrate, and reduced production of the adrenocorticotrophic hormone in vitro. Mechanistically, overexpressed SFRP2 reduced the level of β‑catenin in the cytoplasm and nucleus, and decreased Wnt signaling activity in AtT20 cells. Therefore, SFRP2 appears to act as a tumor suppressor in Cushing's disease by regulating the activity of the Wnt signaling pathway.

Gene Fusion in Malignant Glioma: An Emerging Target for Next-Generation Personalized Treatment

Malignant gliomas are heterogeneous diseases in genetic basis. The development of sequencing techniques has identified many gene rearrangements encoding novel oncogenic fusions in malignant glioma to date. Understanding the gene fusions and how they regulate cellular processes in different subtypes of glioma will shed light on genomic diagnostic approaches for personalized treatment. By now, studies of gene fusions in glioma remain limited, and no medication has been approved for treating the malignancy harboring gene fusions. This review will discuss the current characterization of gene fusions occurring in both adult and pediatric malignant gliomas, their roles in oncogenesis, and the potential clinical implication as therapeutic targets.

Molecular alterations associated with prostate cancer

Introduction

The amount of information and knowledge about pathways and genetic alterations regarding prostate cancer, including the tools available for its study has been recently increasing. Additionally, a variety of molecular signaling pathways control cell proliferation, however, this incompletely understood process is disturbed in cancer cells.

Materials and methods

A literature review was made using the MEDLINE, Embase and LILACS databases searching for the following keywords: prostate neoplasms, prostate cancer, molecular medicine, genomics, pathways, and cell cycle.

Results

Different biological mechanisms have been associated with the development of prostate cancer, such as alterations in tumor suppressor genes, oncogenes (TP53, RB1, among others) and CDKIs; DNA methylation; chromosomal alterations and rearrangements; changes in PTEN and PI3K / mTOR; global defects in apoptosis; alterations in the androgen receptor (AR); and epigenetic mechanisms.

Conclusions

Good clinical practice and a practical approach have to be based on basic knowledge, thus, in this article, the main genetic alterations, mutations and pathways involved in prostate cancer development were reviewed.

A streamlined workflow for single-cells genome-wide copy-number profiling by low-pass sequencing of LM-PCR whole-genome amplification products

Chromosomal instability and associated chromosomal aberrations are hallmarks of cancer and play a critical role in disease progression and development of resistance to drugs. Single-cell genome analysis has gained interest in latest years as a source of biomarkers for targeted-therapy selection and drug resistance, and several methods have been developed to amplify the genomic DNA and to produce libraries suitable for Whole Genome Sequencing (WGS). However, most protocols require several enzymatic and cleanup steps, thus increasing the complexity and length of protocols, while robustness and speed are key factors for clinical applications. To tackle this issue, we developed a single-tube, single-step, streamlined protocol, exploiting ligation mediated PCR (LM-PCR) Whole Genome Amplification (WGA) method, for low-pass genome sequencing with the Ion Torrent^™ platform and copy number alterations (CNAs) calling from single cells. The method was evaluated on single cells isolated from 6 aberrant cell lines of the NCI-H series. In addition, to demonstrate the feasibility of the workflow on clinical samples, we analyzed single circulating tumor cells (CTCs) and white blood cells (WBCs) isolated from the blood of patients affected by prostate cancer or lung adenocarcinoma. The results obtained show that the developed workflow generates data accurately representing whole genome absolute copy number profiles of single cell and allows alterations calling at resolutions down to 100 Kbp with as few as 200,000 reads. The presented data demonstrate the feasibility of the Ampli1^™ WGA-based low-pass workflow for detection of CNAs in single tumor cells which would be of particular interest for genome-driven targeted therapy selection and for monitoring of disease progression.

Identification of potential key genes and high-frequency mutant genes in prostate cancer by using RNA-Seq data

The aim of the present study was to identify potential key genes and single nucleotide variations (SNVs) in prostate cancer. RNA sequencing (RNA-seq) data, GSE22260, were downloaded from the Gene Expression Omnibus database, including 4 prostate cancer samples and 4 normal tissues samples. RNA-Seq reads were processed using Tophat and differentially-expressed genes (DEGs) were identified using the Cufflinks package. Gene Ontology enrichment analysis of DEGs was performed. Subsequently, Seqpos was used to identify the potential upstream regulatory elements of DEGs. SNV was analyzed using Genome Analysis Toolkit. In addition, the frequency and risk-level of mutant genes were calculated using VarioWatch. A total of 150 upregulated and 211 downregulated DEGs were selected and 25 upregulated and 17 downregulated potential upstream regulatory elements were identified, respectively. The SNV annotations of somatic mutations revealed that 65% were base transition and 35% were base transversion. At frequencies ≥2, a total of 17 mutation sites were identified. The mutation site with the highest frequency was located in the folate hydrolase 1B (FOLH1B) gene. Furthermore, 20 high-risk mutant genes with high frequency were identified using VarioWatch, including ribosomal protein S4 Y-linked 2 (RPS4Y2), polycystin 1 transient receptor potential channel interacting (PKD1) and FOLH1B. In addition, kallikrein 1 (KLK1) and PKD1 are known tumor suppressor genes. The potential regulatory elements and high-frequency mutant genes (RPS4Y2, KLK1, PKD1 and FOLH1B) may have key functions in prostate cancer. The results of the present study may provide novel information for the understanding of prostate cancer development.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.