Intratumor DNA methylation heterogeneity reflects clonal evolution in aggressive prostate cancer

The Proteogenomic Landscape of Curable Prostate Cancer

DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

The Genomics of Prostate Cancer: A Historic Perspective

The genomics of prostate cancer (PCA) has been difficult to study compared with some other cancer types for a multitude of reasons, despite significant efforts since the early 1980s. Overcoming some of these obstacles has paved the way for greater insight into the genomics of PCA. The advent of high-throughput technologies coming from the initial use of microsatellite and oligonucleotide probes gave rise to techniques like comparative genomic hybridization (CGH). With the introduction of massively parallel genomic sequencing, referred to as next-generation sequencing (NGS), a deeper understanding of cancer genomics in general has occurred. Along with these technologic advances, there has been the development of computational biology and statistical approaches to address novel large data sets characterized by single base resolution. This review will provide a historic perspective of PCA genomics with an emphasis on the cardinal mutations and alterations observed to be consistently seen in PCA for both hormone-naïve localized PCA and castration-resistant prostate cancer (CRPC). There will be a focus on alterations that have the greatest potential to play a role in disease progression and therapy management.

Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy

Background

Neoadjuvant chemotherapy (NAC) induces a pathological complete response (pCR) in ~ 30% of patients with breast cancer. However, aberrant DNA methylation alterations are frequent events during breast cancer progression and acquisition of chemoresistance. We aimed to characterize the inter- and intra-tumor methylation heterogeneity (MH) in breast cancer following NAC.

Methods

DNA methylation profiles of spatially separated regions of breast tumors before and after NAC treatment were investigated using high-density methylation microarray. Methylation levels of genes of interest were further examined using multiplexed MethyLight droplet digital PCR (ddPCR).

Results

We have discovered different levels of intra-tumor MH in breast cancer patients. Moreover, NAC dramatically altered the methylation profiles and such changes were highly heterogeneous between the patients. Despite the high inter-patient heterogeneity, we identified that stem cell quiescence-associated genes ALDH1L1, HOPX, WNT5A and SOX9 were convergently hypomethylated across all the samples after NAC treatment. Furthermore, by using MethyLight ddPCR, we verified that the methylation levels of these 4 genes were significantly lower in breast tumor samples after NAC than those before NAC.

Conclusions

Our study has revealed that NAC dramatically alters epigenetic heterogeneity in breast cancer and induces convergent hypomethylation of stem cell quiescence-associated genes, ALDH1L1, HOPX, WNT5A and SOX9, which can potentially be developed as therapeutic targets or biomarkers for chemoresistance.

Electronic supplementary material

The online version of this article (10.1186/s13578-019-0278-y) contains supplementary material, which is available to authorized users.

Genomic Evaluation of Multiparametric Magnetic Resonance Imaging-visible and -nonvisible Lesions in Clinically Localised Prostate Cancer

BACKGROUND

The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification.

OBJECTIVE

To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease.

DESIGN, SETTING, AND PARTICIPANTS

Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa.

INTERVENTION

Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients.

OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS

Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication.

RESULTS AND LIMITATIONS

A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up.

CONCLUSIONS

Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied.

PATIENT SUMMARY

Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed.

Prostate cancer-specific hallmarks of amino acids metabolism: Towards a paradigm of precision medicine

So far multiple differences in prostate cancer-specific amino acids metabolism have been discovered. Moreover, attempts to utilize these alterations for prostate cancer diagnosis and treatment have been made. The prostate cancer metabolism and biosynthesis of amino acids are particularly focused on anaplerosis more than on energy production. Other crucial requirements on amino acids pool come from the serine, one‑carbon cycle, glycine synthesis pathway and folate metabolism forming major sources of interproducts for synthesis of nucleobases necessary for rapidly proliferating cells. Considering the lack of some amino acids biosynthetic pathways and/or their extraordinary importance for prostate cancer cells, there is a widespread potential for targeted therapeutic applications with no effect on non-malignant cells. This review summarizes the up-to-date knowledge of the importance of amino acids for prostate cancer pathogenesis with a special emphasis on potential applications of metabolic variabilities in the new oncologic paradigm of precision medicine.

Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier

Background

BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other breast tumors, HR-deficient, BRCA1-like tumors exhibit worse prognosis but selective chemotherapeutic sensitivity. Presently, patients with triple negative breast cancer (TNBC) who do not respond to hormone endocrine-targeting therapy are given cytotoxic chemotherapy. However, more recent evidence showed a similar genomic profile between BRCA1-deficient TNBCs and hormone-receptor-positive tumors. Characterization of the somatic alterations of BRCA1-like hormone-receptor-positive breast tumors as a group, which is currently lacking, can potentially help develop biomarkers for identifying additional patients who might respond to chemotherapy.

Methods

We retrained and validated a copy-number-based support vector machine (SVM) classifier to identify HR-deficient, BRCA1-like breast tumors. We applied this classifier to The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast tumors. We assessed mutational profiles and proliferative capacity by covariate-adjusted linear models and identified differentially methylated regions using DMRcate in BRCA1-like hormone-receptor-positive tumors.

Results

Of the breast tumors in TCGA and METABRIC, 22% (651/2925) were BRCA1-like. Stratifying on hormone-receptor status, 13% (302/2405) receptor-positive and 69% (288/417) triple-negative tumors were BRCA1-like. Among the hormone-receptor-positive subgroup, BRCA1-like tumors showed significantly increased mutational burden and proliferative capacity (both P < 0.05). Genome-scale DNA methylation analysis of BRCA1-like tumors identified 202 differentially methylated gene regions, including hypermethylated BRCA1. Individually significant CpGs were enriched for enhancer regions (P < 0.05). The hypermethylated gene sets were enriched for DNA and chromatin conformation (all Bonferroni P < 0.05).

Conclusions

To provide insights into alternative classification and potential therapeutic targeting strategies of BRCA1-like hormone-receptor-positive tumors we developed and applied a novel copy number classifier to identify BRCA1-like hormone-receptor-positive tumors and their characteristic somatic alteration profiles.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1090-z) contains supplementary material, which is available to authorized users.

Prostate Cancer Genomic Subtypes

Over the last decade, advancements in massively-parallel DNA sequencing and computational biology have allowed for unprecedented insights into the fundamental mutational processes that underlie virtually every major cancer type. Two major cancer genomics consortia-The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC)-have produced rich databases of mutational, pathological, and clinical data that can be mined through web-based portals, allowing for correlative studies and testing of novel hypotheses on well-powered patient cohorts.In this chapter, we will review the impact of these technological developments on the understanding of molecular subtypes that promote prostate cancer initiation, progression, metastasis, and clinical aggression. In particular, we will focus on molecular subtypes that define clinically-relevant patient cohorts and assess how a better understanding of how these subtypes-in both somatic and germline genomes-may influence the clinical course for individual men diagnosed with prostate cancer.

Decoding transcriptomic intra-tumour heterogeneity to guide personalised medicine in ovarian cancer

The evaluation of intra-tumour heterogeneity (ITH) from a transcriptomic point of view is limited. Single-cell cancer studies reveal significant genomic and transcriptomic ITH within a tumour and it is no longer adequate to employ single-subtype assignment as this does not acknowledge the ITH that exists. Molecular assessment of subtype heterogeneity (MASH) was developed to comprehensively report on the composition of all transcriptomic subtypes within a tumour lesion. Using MASH on 3431 ovarian cancer samples, correlation and association analyses with survival, metastasis and clinical outcomes were performed to assess the impact of subtype composition as a surrogate for ITH. The association was validated on two independent cohorts. We identified that 30% of ovarian tumours consist of two or more subtypes. When biological features of the subtype constituents were examined, we identified significant impact on clinical outcomes with the presence of poor prognostic subtypes (Mes or Stem-A). Poorer outcomes correlated with having higher degrees of poor prognostic subtype populations within the tumour. Subtype prediction in several independent datasets reflected a similar prognostic trend. In addition, paired analysis of primary and recurrent/metastatic tumours demonstrated Mes and/or Stem-A subtypes predominated in recurrent and metastatic tumours regardless of the original primary subtype. Given the biological and prognostic value in delineating individual subtypes within a tumour, a clinically applicable MASH assay using NanoString^® technology was developed as a classification tool to comprehensively describe constituents of molecular subtypes. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.

ZNF350 promoter methylation accelerates colon cancer cell migration

Diversification of transcriptomic and epigenomic states may occur during the expansion of colorectal cancers. Certain cancer cells lose their epithelial characters and gain mesenchymal properties, known as epithelial-mesenchymal transition (EMT), and they aggressively migrate into the non-tumorigenic extracellular matrix. In this study, we isolated a subpopulation with accelerated baseline motility (MG cells) and an immotile one (non-MG cells) from a colon cancer cell line (HCT116). Gene expression signatures of the MG cells indicated that this subpopulation was likely an EMT hybrid. The MG cells substantially lost their migratory properties after treatment with a methyltransferase inhibitor, 5-azacytidine, suggesting a role of DNA methylation in this process. Global transcriptome assays of both types of cells with or without 5-azacytidine treatment identified 640 genes, whose expression might be methylation-dependently down-regulated in the MG cells. Global methylation analysis revealed that 35 out of the 640 genes were hyper-methylated in the MG cells. Among them, we focused on the anti-oncogene ZNF350, which encodes a zinc-finger and BRCA1-interacting protein. Notably, ZNF350 knockdown accelerated migration of the non-MG cells, while overexpression of ZNF350 in the MG cells significantly impaired their migration. Finally, pyrosequence analysis together with dual luciferase assays of serially truncated fragments of the ZNF350 promoter (-268 to +49 bp) indicated that three hyper-methylated sites were possibly responsible for the basal promoter activity of ZNF350. Taken together, our results suggest that hyper-methylation of the ZNF350 proximal promoter may be one of the crucial determinants for acquiring increased migratory capabilities in colon cancer cells.

Exploring the transcriptome of hormone-naive multifocal prostate cancer and matched lymph node metastases

Background

The current inability to predict whether a primary prostate cancer (PC) will progress to metastatic disease leads to overtreatment of indolent PCs as well as undertreatment of aggressive PCs. Here, we explored the transcriptional changes associated with metastatic progression of multifocal hormone-naive PC.

Methods

Using total RNA-sequencing, we analysed laser micro-dissected primary PC foci (n = 23), adjacent normal prostate tissue samples (n = 23) and lymph node metastases (n = 9) from ten hormone-naive PC patients. Genes important for PC progression were identified using differential gene expression and clustering analysis. From these, two multi-gene-based expression signatures (models) were developed, and their prognostic potential was evaluated using Cox-regression and Kaplan–Meier analyses in three independent radical prostatectomy (RP) cohorts (>650 patients).

Results

We identified several novel PC-associated transcripts deregulated during PC progression, and these transcripts were used to develop two novel gene-expression-based prognostic models. The models showed independent prognostic potential in three RP cohorts (n = 405, n = 107 and n = 91), using biochemical recurrence after RP as the primary clinical endpoint.

Conclusions

We identified several transcripts deregulated during PC progression and developed two new prognostic models for PC risk stratification, each of which showed independent prognostic value beyond routine clinicopathological factors in three independent RP cohorts.

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice.

Establishing a stable, repeatable platform for measuring changes in sperm DNA methylation

BACKGROUND

Several independent research groups have shown that alterations in human sperm methylation profiles correlate with decreased fecundity and an increased risk of poor embryo development. Moving these initial findings from the lab into a clinical setting where they can be used to measure male infertility though requires a platform that is stable and robust against batch effects that can occur between sample runs. Operating parameters must be established, performance characteristics determined, and guidelines set to ensure repeatability and accuracy. The standard for technical validation of a lab developed test (LDT) in the USA comes from the Clinical Laboratory Improvement Amendments (CLIA). However, CLIA was introduced in 1988, before the advent of genome-wide profiling and associated computational analysis. This, coupled with its intentionally general nature, makes its interpretation for epigenetic assays non-trivial.

RESULTS

Here, we present an interpretation of the CLIA technical validation requirements for profiling DNA methylation and calling aberrant methylation using the Illumina Infinium platform (e.g., the 450HM and MethylationEPIC). We describe an experimental design to meet these requirements, the experimental results obtained, and the operating parameters established.

CONCLUSIONS

The CLIA guidelines, although not intended for high-throughput assays, can be interpreted in a way that is consistent with modern epigenetic assays. Based on such an interoperation, Illumina's Infinium platform is quite amenable to usage in a clinical setting for diagnostic work.

Effect of Combined Use of Astragaloside IV (AsIV) and Atorvastatin (AV) on Expression of PPAR-γ and Inflammation-Associated Cytokines in Atherosclerosis Rats

BACKGROUND The aim of this study was to assess the effect of combined use of Astragaloside IV(AsIV) and atorvastatin (AV) on the expression of PPAR-γ and inflammation-associated cytokines in atherosclerosis rats. MATERIAL AND METHODS High-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) in plasma were detected through automatic biochemical analyzer and the histopathological analysis was performed via HE staining. The levels of oxidized low-density lipoprotein (oxLDL) and tumor necrosis factor-α (TNF-α), and interleukins (IL)-6 and IL-18 in serum were detected by ELISA. The expressions of proliferator-activated receptor-gamma (PPAR-γ), cluster of differentiation 36 (CD36), matrix metalloprotein-9 (MMP-9), intercellular cell adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1(VCAM-1), and p38 and P-p38 levels were detected by Western blot. RT-PCR was used to detect the mRNA expressions of nuclear factor-κB (NF-κB), PPAR-γ, CD36, MMP-9, ICAM-1, and VCAM-1. RESULTS Administration of AsIV and AV significantly decreased the lipid content and oxLDL in plasma. The levels of TNF-α, IL-6, and IL-18 were significantly decreased in AsIV, AV, and AsIV + AV groups, especially in the AsIV + AV group. Administration decreased the levels of NF-κB, CD36, MMP-9, ICAM-1, VCAM-1, and P-p38 expression and increased the expression of peroxisome PPAR-γ. Compared with the NC group, the atherosclerotic lesions significantly increased in the HD group, while the combined administration significantly inhibited the development of atherosclerotic disease. CONCLUSIONS Combined administration of AV and AsIV showed potent effects against atherosclerosis through the NF-κB/PPARγ pathway, which may be a new therapy for treatment of atherosclerosis in the future.

Sentinel node evaluation in prostate cancer

Sentinel lymph node (SLN) based pelvic lymph node dissection (PLND) in prostate cancer (PCa) is appealing over the time, cost and morbidity classically attributed to conventional PLND during radical prostatectomy. The initial report of feasibility of the SLN concept in prostate cancer was nearly 20 years ago. However, PLND based on the SLN concept, either SLN biopsy of a single node or targeted SLN dissection of multiple nodes, is still considered investigational in PCa. To better appreciate the challenges, and potential solutions, associated with SLN-based PLND in PCa, this review will discuss the rationale behind PLND in PCa and evaluate current SLN efforts in the most commonly diagnosed malignancy in men in the US.

Cancer evolution and heterogeneity

Undoubtedly, intratumor heterogeneity (ITH) is one of the causes of the intractability of cancers. Recently, technological innovation in genomics has promoted studies on ITH in solid tumors and on the pattern and level of diversity, which varies among malignancies. We profiled the genome in multiple regions of nine colorectal cancer (CRC) cases. The most impressive finding was that in the late phase, a parental clone branched into numerous subclones. We found that minor mutations were dominant in advanced CRC named neutral evolution; that is, driver gene aberrations were observed with high proportion in the early-acquired phase, but low in the late-acquired phase. Then, we validated that neutral evolution could cause ITH in advanced CRC by super-computational analysis. According to the clinical findings, we explored a branching evolutionary process model in cancer evolution, which assumes that each tumor cell has cellular automaton. According to the model, we verified factors to foster ITH with neutral evolution in advanced CRC. In this review, we introduce recent advances in the field of ITH including the general component of ITH, clonal selective factors that consolidate the evolutionary process, and a representative clinical application of ITH.

Intratumor heterogeneity in prostate cancer

Prostate cancer (PCa) has long been thought of as a disease with a heterogeneous phenotype. It can manifest in men as benign growths that can be safely watched or as more aggressive malignancies that can prove fatal. Recent investigations at the genomic, histopathological and molecular levels have identified tumor heterogeneity, the phenomenon of individual tumor cells presenting distinct genomic and phenotypic characteristics, as one of the most confounding and complex factors underlying PCa diagnosis, prognosis, and treatment. Despite tremendous progress made over the course of the last decade we still have an incomplete understanding of the extent and effect of intra- and inter-tumoral heterogeneity in the course of PCa progression. For example, a primary tumor can be classified into one of several molecular subgroups depending on whether the cancer has a particular gene fusion or a mutation which in turn might yield some patient-specific therapeutic regimen, but this same type of heterogeneous growth can be spatially or temporally restricted proving it difficult to detect during biopsy. We therefore present here a comprehensive review of the various studies addressing intra-tumor heterogeneity in PCa and in the context of that seen in other solid tumors. We discuss the impact of heterogeneity on clinical decision-making in treating both primary and metastatic lesions and how our understanding of this heterogeneity might help in developing better diagnostic tools and biomarkers and in guiding the selection of better therapeutic strategies.

Epigenetics, Nutrition, Disease and Drug Development

Epigenetic mechanisms comprising of DNA methylation, histone modifications and gene silencing by RNA interference have been strongly linked to the development and progression of various diseases. These findings have triggered research on epigenetic functions and signal pathways as targets for novel drug discovery. Dietary intake has also presented significant influence on human health and disease development and nutritional modifications have proven important in prevention, but also the treatment of disease. Moreover, a strong link between nutrition and epigenetic changes has been established. Therefore, in attempts to develop novel safer and more efficacious drugs, both nutritional requirements and epigenetic mechanisms need to be addressed.

Delineation of human prostate cancer evolution identifies chromothripsis as a polyclonal event and FKBP4 as a potential driver of castration resistance

Understanding the evolutionary mechanisms and genomic events leading to castration-resistant (CR) prostate cancer (PC) is key to improve the outcome of this otherwise deadly disease. Here, we delineated the tumour history of seven patients progressing to castration resistance by analysing matched prostate cancer tissues before and after castration. We performed genomic profiling of DNA content-based flow-sorted populations in order to define the different evolutionary patterns. In one patient, we discovered that a catastrophic genomic event, known as chromothripsis, resulted in multiple CRPC tumour populations with distinct, potentially advantageous copy number aberrations, including an amplification of FK506 binding protein 4 (FKBP4, also known as FKBP52), a protein enhancing the transcriptional activity of androgen receptor signalling. Analysis of FKBP4 protein expression in more than 500 prostate cancer samples revealed increased expression in CRPC in comparison to hormone-naïve (HN) PC. Moreover, elevated FKBP4 expression was associated with poor survival of patients with HNPC. We propose FKBP4 amplification and overexpression as a selective advantage in the process of tumour evolution and as a potential mechanism associated with the development of CRPC. Furthermore, FKBP4 interaction with androgen receptor may provide a potential therapeutic target in PC. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Diagnostic role of Wnt pathway gene promoter methylation in non small cell lung cancer

Wnt signal pathway genes are known to be involved with cancer development. Here we tested the hypothesis whether DNA methylation of genes part of the Wnt signaling pathway could help the diagnosis of non-small cell lung cancer (NSCLC). The methylation levels of SFRP1, SFRP2, WIF1 and PRKCB in 111 NSCLC patients were evaluated by quantitative methylation-specific PCR (qMSP). Promoter methylation levels of four candidate genes were significantly higher in tumor tissues compared with the adjacent tissues. SFRP1, SFRP2 and PRKCB genes were all shown to be good predictors of NSCLC risk (SFRP1: AUC = 0.711; SFRP2: AUC = 0.631; PRKCB: AUC = 0.650). The combined analysis showed that the methylation status of the four genes had a sensitivity of 70.3% and a specificity of 73.9% in the prediction of NSCLC risk for study cohort. A higher diagnostic value with an AUC of 0.945 (95% CI: 0.923–0.967, sensitivity: 90.6%, specificity: 93.0%) was found in TCGA cohort. In addition, SFRP1 and SFRP2 hypermethylation events were specific to male patients. Further TCGA data mining analysis suggested that SFRP1_cg15839448, SFRP2_cg05774801, and WIF1_cg21383810 were inversely associated with the host gene expression. Moreover, GEO database analysis showed that 5′-Aza-deoxycytidine was able to upregulate gene expression in several lung cancer cell lines. Subsequent dual-luciferase reporter assay showed a crucial regulatory function of PRKCB promoter. In summary, our study showed that a panel of Wnt signal pathway genes (SFRP1, SFRP2, WIF1 and PRKCB) had the potential as methylation biomarkers in the diagnosis of NSCLC.

Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling

Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle‐level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting.

Addressing intra-tumoral heterogeneity and therapy resistance

In the last several years, our appreciation of intra-tumoral heterogeneity has greatly increased due to accumulating evidence for the co-existence of genetically and epigenetically divergent cancer cells residing in different microenvironments within a tumor. Herein, we review recent literature discussing intra-tumoral heterogeneity in the context of therapy resistance mechanisms at the genetic, epigenetic and microenvironmental levels. We illustrate the influence of tumor microenvironment on therapy resistance and epigenetic states of cancer cells by highlighting the role of cancer stem cells in therapy resistance. We also summarize different strategies that have been employed to address various resistance mechanisms at genetic, epigenetic, and microenvironmental levels in preclinical and clinical studies. We propose that future personalized cancer therapy design needs to incorporate dynamic and comprehensive analyses of tumor heterogeneity landscape and multi-dimensional mechanisms of therapy resistance.

The role of TET-mediated DNA hydroxymethylation in prostate cancer

Ten-eleven translocation (TET) proteins are recently characterized dioxygenases that regulate demethylation by oxidizing 5-methylcytosine to 5-hydroxymethylcytosine and further derivatives. The recent finding that 5hmC is also a stable and independent epigenetic modification indicates that these proteins play an important role in diverse physiological and pathological processes such as neural and tumor development. Both the genomic distribution of (hydroxy)methylation and the expression and activity of TET proteins are dysregulated in a wide range of cancers including prostate cancer. Up to now it is still unknown how changes in TET and 5(h)mC profiles are related to the pathogenesis of prostate cancer. In this review, we explore recent advances in the current understanding of how TET expression and function are regulated in development and cancer. Furthermore, we look at the impact on 5hmC in prostate cancer and the potential underlying mechanisms. Finally, we tried to summarize the latest techniques for detecting and quantifying global and locus-specific 5hmC levels of genomic DNA.

The Heterogeneity of Prostate Cancer: A Practical Approach

Prostate cancer is a paradigm tumor model for heterogeneity in almost every sense. Its clinical, spatial, and morphological heterogeneity divided by the high-level molecular genetic diversity outline the complexity of this disease in the clinical and research settings. In this review, we summarize the main aspects of prostate cancer heterogeneity at different levels, with special attention given to the spatial heterogeneity within the prostate, and to the standard morphological heterogeneity, with respect to tumor grading and modern classifications. We also cover the complex issue of molecular genetic heterogeneity, discussing it in the context of the current evidence of the genetic characterization of prostate carcinoma; the interpatient, intertumoral (multifocal disease), and intratumoral heterogeneity; tumor clonality; and metastatic disease. Clinical and research implications are summarized and serve to address the most pertinent problems stemming from the extreme heterogeneity of prostate cancer.

Intratumor heterogeneity in epigenetic patterns

Analogous to life on earth, tumor cells evolve through space and time and adapt to different micro-environmental conditions. As a result, tumors are composed of millions of genetically diversified cells at the time of diagnosis. Profiling these variants contributes to understanding tumors' clonal origins and might help to better understand response to therapy. However, even genetically homogenous cell populations show remarkable diversity in their response to different environmental stimuli, suggesting that genetic heterogeneity does not explain the full spectrum of tumor plasticity. Understanding epigenetic diversity across cancer cells provides important additional information about the functional state of subclones and therefore allows better understanding of tumor evolution and resistance to current therapies.

MethyMer: Design of combinations of specific primers for bisulfite sequencing of complete CpG islands

We present MethyMer, a Python-based tool aimed at selecting primers for amplification of complete CpG islands. These regions are difficult in terms of selecting appropriate primers because of their low-complexity, high GC content. Moreover, bisulfite treatment, in fact, leads to the reduction of the 4-letter alphabet (ATGC) to 3-letter one (ATG, except for methylated cytosines), and this also reduces region complexity and increases mispriming potential. MethyMer has a flexible scoring system, which optimizes the balance between various characteristics such as nucleotide composition, thermodynamic features (melting temperature, dimers [Formula: see text]G, etc.), the presence of CpG sites and polyN tracts, and primer specificity, which is assessed with aligning primers to the bisulfite-treated genome using bowtie (up to three mismatches are allowed). Users are able to customize desired or limit ranges of various parameters as well as penalties for non-desired values. Moreover, MethyMer allows picking up the optimal combination of PCR primer pairs to perform the amplification of a large genomic locus, e.g. CpG island or other hard-to-study region, with minimal overlap of the individual amplicons. MethyMer incorporates ENCODE genome annotation records (promoter/enhancer/insulator), The Cancer Genome Atlas (TCGA) CpG methylation data derived with Illumina Infinium 450K microarrays, and records on correlations between TCGA RNA-Seq and CpG methylation data for 20 cancer types. These databases are included in the MethyMer release. Our tool is available at https://sourceforge.net/projects/methymer/ .

MHC Intratumoral Heterogeneity May Predict Cancer Progression and Response to Immunotherapy

An individual tumor can present intratumoral phenotypic heterogeneity, containing tumor cells with different phenotypes that do not present irreversible genetic alterations. We have developed a mouse cancer model, named GR9, derived from a methylcholanthrene-induced fibrosarcoma that was adapted to tissue culture and cloned into different tumor cell lines. The clones showed diverse MHC-I phenotypes, ranging from highly positive to weakly positive MHC-I expression. These MHC-I alterations are due to reversible molecular mechanisms, because surface MHC-I could be recovered by IFN-γ treatment. Cell clones with high MHC-I expression demonstrated low local oncogenicity and high spontaneous metastatic capacity, whereas MHC-I-low clones showed high local oncogenicity and no spontaneous metastatic capacity. Although MHC-I-low clones did not metastasize, they produced MHC-I-positive dormant micrometastases controlled by the host immune system, i.e., in a state of immunodormancy. The metastatic capacity of each clone was directly correlated with the host T-cell subpopulations; thus, a strong decrease in cytotoxic and helper T lymphocytes was observed in mice with numerous metastases derived from MHC-I positive tumor clones but a strong increase was observed in those with dormant micrometastases. Immunotherapy was administered to the hosts after excision of the primary tumor, producing a recovery in their immune status and leading to the complete eradication of overt spontaneous metastases or their decrease. According to these findings, the combination of MHC-I surface expression in primary tumor and metastases with host T-cell subsets may be a decisive indicator of the clinical outcome and response to immunotherapy in metastatic disease, allowing the identification of responders to this approach.

Development of a Method to Implement Whole-Genome Bisulfite Sequencing of cfDNA from Cancer Patients and a Mouse Tumor Model

The goal of this study was to develop a method for whole genome cell-free DNA (cfDNA) methylation analysis in humans and mice with the ultimate goal to facilitate the identification of tumor derived DNA methylation changes in the blood. Plasma or serum from patients with pancreatic neuroendocrine tumors or lung cancer, and plasma from a murine model of pancreatic adenocarcinoma was used to develop a protocol for cfDNA isolation, library preparation and whole-genome bisulfite sequencing of ultra low quantities of cfDNA, including tumor-specific DNA. The protocol developed produced high quality libraries consistently generating a conversion rate >98% that will be applicable for the analysis of human and mouse plasma or serum to detect tumor-derived changes in DNA methylation.

The Genomics of Prostate Cancer: emerging understanding with technologic advances

With the advent of next-generation sequencing technologies and large whole-exome and genome studies in prostate and other cancers, our understanding of the landscape of genomic alterations has dramatically been refined. In additional to well-known alterations in genomic regions involving 8p, 8q, 10q23, common ETS translocations and androgen receptor amplifications, newer technology have uncovered recurrent mutations in SPOP, FOXA1, MED12, IDH and complex large scale genomic alterations (eg, chromoplexy). This review surveys the enhanced landscape of genomic alterations in clinically localized and advanced prostate cancer.

A Summary of the Biological Processes, Disease-Associated Changes, and Clinical Applications of DNA Methylation

DNA methylation at cytosines followed by guanines, CpGs, forms one of the multiple layers of epigenetic mechanisms controlling and modulating gene expression through chromatin structure. It closely interacts with histone modifications and chromatin remodeling complexes to form the local genomic and higher-order chromatin landscape. DNA methylation is essential for proper mammalian development, crucial for imprinting and plays a role in maintaining genomic stability. DNA methylation patterns are susceptible to change in response to environmental stimuli such as diet or toxins, whereby the epigenome seems to be most vulnerable during early life. Changes of DNA methylation levels and patterns have been widely studied in several diseases, especially cancer, where interest has focused on biomarkers for early detection of cancer development, accurate diagnosis, and response to treatment, but have also been shown to occur in many other complex diseases. Recent advances in epigenome engineering technologies allow now for the large-scale assessment of the functional relevance of DNA methylation. As a stable nucleic acid-based modification that is technically easy to handle and which can be analyzed with great reproducibility and accuracy by different laboratories, DNA methylation is a promising biomarker for many applications.

Detailed longitudinal sampling of glioma stem cells in situ reveals Chr7 gain and Chr10 loss as repeated events in primary tumor formation and recurrence

Intratumoral heterogeneity at the genetic, epigenetic, transcriptomic, and morphologic levels is a commonly observed phenomenon in many aggressive cancer types. Clonal evolution during tumor formation and in response to therapeutic intervention can be predicted utilizing reverse engineering approaches on detailed genomic snapshots of heterogeneous patient tumor samples. In this study, we developed an extensive dataset for a GBM case via the generation of polyclonal and monoclonal glioma stem cell lines from initial diagnosis, and from multiple sections of distant tumor locations of the deceased patient's brain following tumor recurrence. Our analyses revealed the tissue-wide expansion of a new clone in the recurrent tumor and chromosome 7 gain and chromosome 10 loss as repeated genomic events in primary and recurrent disease. Moreover, chromosome 7 gain and chromosome 10 loss produced similar alterations in mRNA expression profiles in primary and recurrent tumors despite possessing other highly heterogeneous and divergent genomic alterations between the tumors. We identified ETV1 and CDK6 as putative candidate genes, and NFKB (complex), IL1B, IL6, Akt and VEGF as potential signaling regulators, as potentially central downstream effectors of chr7 gain and chr10 loss. Finally, the differences caused by the transcriptomic shift following gain of chromosome 7 and loss of chromosome 10 were consistent with those generally seen in GBM samples compared to normal brain in large-scale patient-tumor data sets.

DNA methylation intratumor heterogeneity in localized lung adenocarcinomas

Cancers are composed of cells with distinct molecular and phenotypic features within a given tumor, a phenomenon termed intratumor heterogeneity (ITH). Previously, we have demonstrated genomic ITH in localized lung adenocarcinomas; however, the nature of methylation ITH in lung cancers has not been well investigated. In this study, we generated methylation profiles of 48 spatially separated tumor regions from 11 localized lung adenocarcinomas and their matched normal lung tissues using Illumina Infinium Human Methylation 450K BeadChip array. We observed methylation ITH within the same tumors, but to a much less extent compared to inter-individual heterogeneity. On average, 25% of all differentially methylated probes compared to matched normal lung tissues were shared by all regions from the same tumors. This is in contrast to somatic mutations, of which approximately 77% were shared events amongst all regions of individual tumors, suggesting that while the majority of somatic mutations were early clonal events, the tumor-specific DNA methylation might be associated with later branched evolution of these 11 tumors. Furthermore, our data showed that a higher extent of DNA methylation ITH was associated with larger tumor size (average Euclidean distance of 35.64 (> 3cm, median size) versus 27.24 (<= 3cm), p = 0.014), advanced age (average Euclidean distance of 34.95 (above 65) verse 28.06 (below 65), p = 0.046) and increased risk of postsurgical recurrence (average Euclidean distance of 35.65 (relapsed patients) versus 29.03 (patients without relapsed), p = 0.039).

Impact of DNA methylation programming on normal and pre-leukemic hematopoiesis

Epigenome regulation is a critical mechanism that governs cell identity, lineage specification and developmental cell fates. With the advent of low-input and single-cell technologies as well as sophisticated cell labeling techniques, our understanding of transcriptional and epigenetic regulation of hematopoiesis is currently undergoing dramatic changes. Increasingly, evidence suggests that the epigenome conformation acts as a critical decision-making mechanism that instructs self-renewal, differentiation and developmental fates of hematopoietic progenitor cells. When dysregulated, this leads to the evolution of disease states such as leukemia. Indeed, aberrations in DNA methylation, histone modifications and genome architecture are characteristic features of many hematopoietic neoplasms in which epigenetic enzymes are frequently mutated. Sequencing studies and characterization of the epigenetic landscape in lymphomas, leukemias and in aged healthy individuals with clonal hematopoiesis have been indispensible to identify epigenetic regulators that play a role in transformation or pre-disposition to hematopoietic malignancies. In this review, we outline the current view of the hematopoietic system and the epigenetic mechanisms regulating hematopoiesis under homeostatic conditions, with a particular focus on the role of DNA methylation in this process. We will also summarize the current knowledge on the mechanisms underlying dysregulated DNA methylation in hematologic malignancies and how this contributes to our understanding of the physiological functions of epigenetic regulators in hematopoiesis.

Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.

Genes involved in development and differentiation are commonly methylated in cancers derived from multiple organs: a single-institutional methylome analysis using 1007 tissue specimens

The aim of this study was to clarify the significance of DNA methylation alterations shared by cancers derived from multiple organs. We analyzed single-institutional methylome data by single-CpG-resolution Infinium assay for 1007 samples of non-cancerous tissue (N) and corresponding cancerous tissue (T) obtained from lung, stomach, kidney, breast and liver. Principal component analysis revealed that N samples of each organ showed distinct DNA methylation profiles, DNA methylation profiles of N samples of each organ being inherited by the corresponding T samples and DNA methylation profiles of T samples being more similar to those of N samples in the same organ than those of T samples in other organs. In contrast to such organ and/or carcinogenetic factor-specificity of DNA methylation profiles, when compared with the corresponding N samples, 231 genes commonly showed DNA hypermethylation in T samples in four or more organs. Gene ontology enrichment analysis showed that such commonly methylated genes were enriched among “transcriptional factors” participating in development and/or differentiation, which reportedly show bivalent histone modification in embryonic stem cells. Pyrosequencing and quantitative reverse transcription-PCR revealed an inverse correlation between DNA methylation levels and mRNA expression levels of representative commonly methylated genes, such as ALX1, ATP8A2, CR1 and EFCAB1, in tissue samples. These data suggest that disruption of the differentiated state of precancerous cells via alterations of expression, independent of differences in organs and/or carcinogenetic factors, may be a common feature of DNA methylation alterations during carcinogenesis in multiple organs.

Epigenetic drivers of tumourigenesis and cancer metastasis

Since the completion of the first human genome sequence and the advent of next generation sequencing technologies, remarkable progress has been made in understanding the genetic basis of cancer. These studies have mainly defined genetic changes as either causal, providing a selective advantage to the cancer cell (a driver mutation) or consequential with no selective advantage (not directly causal, a passenger mutation). A vast unresolved question is how a primary cancer cell becomes metastatic and what are the molecular events that underpin this process. However, extensive sequencing efforts indicate that mutation may not be a causal factor for primary to metastatic transition. On the other hand, epigenetic changes are dynamic in nature and therefore potentially play an important role in determining metastatic phenotypes and this area of research is just starting to be appreciated. Unlike genetic studies, current limitations in studying epigenetic events in cancer metastasis include a lack of conceptual understanding and an analytical framework for identifying putative driver and passenger epigenetic changes. In this review, we discuss the key concepts involved in understanding the role of epigenetic alterations in the metastatic cascade. We particularly focus on driver epigenetic events, and we describe analytical approaches and biological frameworks for distinguishing between "epi-driver" and "epi-passenger" events in metastasis. Finally, we suggest potential directions for future research in this important area of cancer research.

Genetic Mutations and Epigenetic Modifications: Driving Cancer and Informing Precision Medicine

Cancer treatment is undergoing a significant revolution from "one-size-fits-all" cytotoxic therapies to tailored approaches that precisely target molecular alterations. Precision strategies for drug development and patient stratification, based on the molecular features of tumors, are the next logical step in a long history of approaches to cancer therapy. In this review, we discuss the history of cancer treatment from generic natural extracts and radical surgical procedures to site-specific and combinatorial treatment regimens, which have incrementally improved patient outcomes. We discuss the related contributions of genetics and epigenetics to cancer progression and the response to targeted therapies and identify challenges and opportunities for the success of precision medicine. The identification of patients who will benefit from targeted therapies is more complex than simply identifying patients whose tumors harbour the targeted aberration, and intratumoral heterogeneity makes it difficult to determine if a precision therapy is successful during treatment. This heterogeneity enables tumors to develop resistance to targeted approaches; therefore, the rational combination of therapeutic agents will limit the threat of acquired resistance to therapeutic success. By incorporating the view of malignant transformation modulated by networks of genetic and epigenetic interactions, molecular strategies will enable precision medicine for effective treatment across cancer subtypes.

Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. SaGA was used on collectively invading 3D cancer cell packs to create purified leader and follower cell lines. The leader cell cultures are phenotypically stable and highly invasive in contrast to follower cultures, which show phenotypic plasticity over time and minimally invade in a sheet-like pattern. Genomic and molecular interrogation reveals an atypical VEGF-based vasculogenesis signalling that facilitates recruitment of follower cells but not for leader cell motility itself, which instead utilizes focal adhesion kinase-fibronectin signalling. While leader cells provide an escape mechanism for followers, follower cells in turn provide leaders with increased growth and survival. These data support a symbiotic model of collective invasion where phenotypically distinct cell types cooperate to promote their escape.

The mechanisms linking phenotypic heterogeneity to collective cancer invasion are unclear. Here the authors develop an image-guided genomic technique to select and amplify leader and follower cells from in vitro invading cell packs and find a cooperative symbiotic relationship between these two cell populations.

Exploiting Epigenetic Alterations in Prostate Cancer

Prostate cancer affects an increasing number of men worldwide and is a leading cause of cancer-associated deaths. Beside genetic mutations, many epigenetic alterations including DNA and histone modifications have been identified in clinical prostate tumor samples. They have been linked to aberrant activity of enzymes and reader proteins involved in these epigenetic processes, leading to the search for dedicated inhibitory compounds. In the wake of encouraging anti-tumor efficacy results in preclinical models, epigenetic modulators addressing different targets are now being tested in prostate cancer patients. In addition, the assessment of microRNAs as stratification biomarkers, and early clinical trials evaluating suppressor microRNAs as potential prostate cancer treatment are being discussed.

Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma

Understanding the intratumoral heterogeneity of hepatocellular carcinoma is instructive for developing personalized therapy and identifying molecular biomarkers. Here we applied whole-exome sequencing to 69 samples from 11 patients to resolve the genetic architecture of subclonal diversification. Spatial genomic diversity was found in all 11 hepatocellular carcinoma cases, with 29% of driver mutations being heterogeneous, including TERT, ARID1A, NOTCH2, and STAG2. Similar with other cancer types, TP53 mutations were always shared between all tumor regions, that is, located on the "trunk" of the evolutionary tree. In addition, we found that variants within several drug targets such as KIT, SYK, and PIK3CA were mutated in a fully clonal manner, indicating their therapeutic potentials for hepatocellular carcinoma. Temporal dissection of mutational signatures suggested that mutagenic processes associated with exposure to aristolochic acid and aflatoxin might play a more important role in early, as opposed to late, stages of hepatocellular carcinoma development. Moreover, we observed extensive intratumoral epigenetic heterogeneity in hepatocellular carcinoma based on multiple independent analytical methods and showed that intratumoral methylation heterogeneity might play important roles in the biology of hepatocellular carcinoma cells. Our results also demonstrated prominent heterogeneity of intratumoral methylation even in a stable hepatocellular carcinoma genome. Together, these findings highlight widespread intratumoral heterogeneity at both the genomic and epigenomic levels in hepatocellular carcinoma and provide an important molecular foundation for better understanding the pathogenesis of this malignancy. Cancer Res; 77(9); 2255-65. ©2017 AACR.

DNA methylation: an epigenetic mark of cellular memory

DNA methylation is a stable epigenetic mark that can be inherited through multiple cell divisions. During development and cell differentiation, DNA methylation is dynamic, but some DNA methylation patterns may be retained as a form of epigenetic memory. DNA methylation profiles can be useful for the lineage classification and quality control of stem cells such as embryonic stem cells, induced pluripotent cells and mesenchymal stem cells. During cancer initiation and progression, genome-wide and gene-specific DNA methylation changes occur as a consequence of mutated or deregulated chromatin regulators. Early aberrant DNA methylation states occurring during transformation appear to be retained during tumor evolution. Similarly, DNA methylation differences among different regions of a tumor reflect the history of cancer cells and their response to the tumor microenvironment. Therefore, DNA methylation can be a useful molecular marker for cancer diagnosis and drug treatment.

The evolution of tumour phylogenetics: principles and practice

Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.

Global DNA Methylation Analysis Identifies Two Discrete clusters of Pheochromocytoma with Distinct Genomic and Genetic Alterations

Pheochromocytomas and paragangliomas (PPGLs) are rare and frequently heritable neural-crest derived tumours arising from the adrenal medulla or extra-adrenal chromaffin cells respectively. The majority of PPGL tumours are benign and do not recur with distant metastases. However, a sizeable fraction of these tumours secrete vasoactive catecholamines into the circulation causing a variety of symptoms including hypertension, palpitations and diaphoresis. The genetic landscape of PPGL has been well characterized and more than a dozen genes have been described as recurrently mutated. Recent studies of DNA-methylation have revealed distinct clusters of PPGL that share DNA methylation patterns and driver mutations, as well as identified potential biomarkers for malignancy. However, these findings have not been adequately validated in independent cohorts. In this study we use an array-based genome-wide approach to study the methylome of 39 PPGL and 4 normal adrenal medullae. We identified two distinct clusters of tumours characterized by different methylation patterns and different driver mutations. Moreover, we identify genes that are differentially methylated between tumour subcategories, and between tumours and normal tissue.

Combinatorial Ranking of Gene Sets to Predict Disease Relapse: The Retinoic Acid Pathway in Early Prostate Cancer

Background

Quantitative high-throughput data deposited in consortia such as International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) present opportunities and challenges for computational analyses.

Methods

We present a computational strategy to systematically rank and investigate a large number (2¹⁰–2²⁰) of clinically testable gene sets, using combinatorial gene subset generation and disease-free survival (DFS) analyses. This approach integrates protein–protein interaction networks, gene expression, DNA methylation, and copy number data, in association with DFS profiles from patient clinical records.

Results

As a case study, we applied this pipeline to systematically analyze the role of ALDH1A2 in prostate cancer (PCa). We have previously found this gene to have multiple roles in disease and homeostasis, and here we investigate the role of the associated ALDH1A2 gene/protein networks in PCa, using our methodology in combination with PCa patient clinical profiles from ICGC and TCGA databases. Relationships between gene signatures and relapse were analyzed using Kaplan–Meier (KM) log-rank analysis and multivariable Cox regression. Relative expression versus pooled mean from diploid population was used for z-statistics calculation. Gene/protein interaction network analyses generated 11 core genes associated with ALDH1A2; combinatorial ranking of the power set of these core genes identified two gene sets (out of 2¹¹ − 1 = 2,047 combinations) with significant correlation with disease relapse (KM log rank p < 0.05). For the more significant of these two sets, referred to as the optimal gene set (OGS), patients have median survival 62.7 months with OGS alterations compared to >150 months without OGS alterations (p = 0.0248, hazard ratio = 2.213, 95% confidence interval = 1.1–4.098). Two genes comprising OGS (CYP26A1 and RDH10) are strongly associated with ALDH1A2 in the retinoic acid (RA) pathways, suggesting a major role of RA signaling in early PCa progression. Our pipeline complements human expertise in the search for prognostic biomarkers in large-scale datasets.

PLMET: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalilzed Exponential Tilt Mixture Models

Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic data. We propose a pseudolikelihood based expectation-maximization test, and show the proposed test follows a simple chi-squared limiting distribution. Simulation studies show that the proposed test controls Type I errors well and has better power compared to several current tests. In particular, the proposed test outperforms the commonly used tests under all simulation settings considered, especially when there are variance differences between two groups. The proposed test is applied to a real data set to identify differentially methylated sites between ovarian cancer subjects and normal subjects.

Constraints in cancer evolution

Next-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.

The importance of DNA methylation in prostate cancer development

After briefly reviewing the nature of DNA methylation, its general role in cancer and the tools available to interrogate it, we consider the literature surrounding DNA methylation as relating to prostate cancer. Specific consideration is given to recurrent alterations. A list of frequently reported genes is synthesized from 17 studies that have reported on methylation changes in malignant prostate tissue, and we chart the timing of those changes in the diseases history through amalgamation of several previously published data sets. We also review associations with genetic alterations and hormone signalling, before the practicalities of investigating prostate cancer methylation using cell lines are assessed. We conclude by outlining the interplay between DNA methylation and prostate cancer metabolism and their regulation by androgen receptor, with a specific discussion of the mitochondria and their associations with DNA methylation.