Genome-wide pathway analysis in neuroblastoma

The fellowship of the RING: BRCA1, its partner BARD1 and their liaison in DNA repair and cancer

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

An Overview of Long Non-Coding (lnc)RNAs in Neuroblastoma

Neuroblastoma (NB) is a heterogeneous developmental tumor occurring in childhood, which arises from the embryonic sympathoadrenal cells of the neural crest. Although the recent progress that has been done on this tumor, the mechanisms involved in NB are still partially unknown. Despite some genetic aberrations having been identified, the sporadic cases represent the majority. Due to its wide heterogeneity in clinical behavior and etiology, NB represents a challenge in terms of prevention and treatment. Since a definitive therapy is lacking so far, there is an urgent necessity to unveil the molecular mechanisms behind NB onset and progression to develop new therapeutic approaches. Long non-coding RNAs (lncRNAs) are a group of RNAs longer than 200 nucleotides. Whether lncRNAs are destined to become a protein or not, they exert multiple biological functions such as regulating gene expression and functions. In recent decades, different research has highlighted the possible role of lncRNAs in the pathogenesis of many diseases, including cancer. Moreover, lncRNAs may represent potential markers or targets for diagnosis and treatment of diseases. This mini-review aimed to briefly summarize the most recent findings on the involvement of some lncRNAs in NB disease by focusing on their mechanisms of action and possible role in unveiling NB onset and progression.

Typical numerical alterations in genome identified by array CGH analysis in neuroblastoma tumors

<abstract><sec> <title>Introduction</title> <p>The clinical variability in the course of neuroblastoma (NB) is closely linked to diverse genetic changes acquired by tumor cells. Rapid NB progression is associated with oncogene MYCN amplification (MNA) and segmental chromosomal aberrations (SCA). Alternatively, numerical chromosomal alterations (NCA) have positive impact on treatment. So far, no studies have been undertaken to identify NCA that may group NB patients. Therefore, the aim of the study was to identify NCA typical for NB.</p> </sec><sec> <title>Materials and methods</title> <p>Copy number alterations in NB tumor genome (fresh samples N = 94; formalin-fixed paraffin-embedded specimens N = 66) were analyzed with a pangenomic array CGH technique.</p> </sec><sec> <title>Results</title> <p>The profile with NCA was observed in 72 (45%) cases, NCA+SCA in 37 (23%), normal in 35 (22%) and MNA in 16 (10%). Samples with NCA were characterized by whole chromosome gains: 17, 7, 6 (78%, 65%, 51%, respectively) and copy loss of chromosome 14 (57%). Similarly to NCA, patients with a combined NCA and SCA profile were also characterized by gain of whole chromosome 17 and 7 (35% both) and loss of chromosome 14 (38%), but with lower frequency. In the combined NCA and SCA profiles, typical NB changes such as deletion 1p36 (27%) and gain 17q (41%) were observed, as well as deletion 11q (24%). The same alterations were detected in MNA samples (44%, 44%, 19%, respectively). A difference was found in spanning 11q deletion between MNA and NCA+SCA subgroup, which may suggest new prognostic markers in NB. In MNA subgroup specific NCA was not indicated.</p> </sec><sec> <title>Conclusions</title> <p>The hypothesis that NCA in NB tumors are more frequent in younger children with good prognosis was confirmed. To gain new insights into the pathogenesis of NB and to establish molecular targets for diagnosis and therapy, candidate genes in the altered chromosomal regions must be investigated.</p> </sec></abstract>

The Effects of Genetic and Epigenetic Alterations of BARD1 on the Development of Non-Breast and Non-Gynecological Cancers

Breast Cancer 1 (BRCA1) gene is a well-characterized tumor suppressor gene, mutations of which are primarily found in women with breast and ovarian cancers. BRCA1-associated RING domain 1 (BARD1) gene has also been identified as an important tumor suppressor gene in breast, ovarian, and uterine cancers. Underscoring the functional significance of the BRCA1 and BARD1 interactions, prevalent mutations in the BRCA1 gene are found in its RING domain, through which it binds the RING domain of BARD1. BARD1-BRCA1 heterodimer plays a crucial role in a variety of DNA damage response (DDR) pathways, including DNA damage checkpoint and homologous recombination (HR). However, many mutations in both BARD1 and BRCA1 also exist in other domains that significantly affect their biological functions. Intriguingly, recent genome-wide studies have identified various single nucleotide polymorphisms (SNPs), genetic alterations, and epigenetic modifications in or near the BARD1 gene that manifested profound effects on tumorigenesis in a variety of non-breast and non-gynecological cancers. In this review, we will briefly discuss the molecular functions of BARD1, including its BRCA1-dependent as well as BRCA1-independent functions. We will then focus on evaluating the common BARD1 related SNPs as well as genetic and epigenetic changes that occur in the non-BRCA1-dominant cancers, including neuroblastoma, lung, and gastrointestinal cancers. Furthermore, the pro- and anti-tumorigenic functions of different SNPs and BARD1 variants will also be discussed.

Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival

Background

Modern experimental techniques deliver data sets containing profiles of tens of thousands of potential molecular and genetic markers that can be used to improve medical diagnostics. Previous studies performed with three different experimental methods for the same set of neuroblastoma patients create opportunity to examine whether augmenting gene expression profiles with information on copy number variation can lead to improved predictions of patients survival. We propose methodology based on comprehensive cross-validation protocol, that includes feature selection within cross-validation loop and classification using machine learning. We also test dependence of results on the feature selection process using four different feature selection methods.

Results

The models utilising features selected based on information entropy are slightly, but significantly, better than those using features obtained with t-test. The synergy between data on genetic variation and gene expression is possible, but not confirmed. A slight, but statistically significant, increase of the predictive power of machine learning models has been observed for models built on combined data sets. It was found while using both out of bag estimate and in cross-validation performed on a single set of variables. However, the improvement was smaller and non-significant when models were built within full cross-validation procedure that included feature selection within cross-validation loop. Good correlation between performance of the models in the internal and external cross-validation was observed, confirming the robustness of the proposed protocol and results.

Conclusions

We have developed a protocol for building predictive machine learning models. The protocol can provide robust estimates of the model performance on unseen data. It is particularly well-suited for small data sets. We have applied this protocol to develop prognostic models for neuroblastoma, using data on copy number variation and gene expression. We have shown that combining these two sources of information may increase the quality of the models. Nevertheless, the increase is small and larger samples are required to reduce noise and bias arising due to overfitting.

Reviewers

This article was reviewed by Lan Hu, Tim Beissbarth and Dimitar Vassilev.

Patient-Derived Xenograft Models Reveal Intratumor Heterogeneity and Temporal Stability in Neuroblastoma

Patient-derived xenografts (PDX) and the Avatar, a single PDX mirroring an individual patient, are emerging tools in preclinical cancer research. However, the consequences of intratumor heterogeneity for PDX modeling of biomarkers, target identification, and treatment decisions remain underexplored. In this study, we undertook serial passaging and comprehensive molecular analysis of neuroblastoma orthotopic PDXs, which revealed strong intrinsic genetic, transcriptional, and phenotypic stability for more than 2 years. The PDXs showed preserved neuroblastoma-associated gene signatures that correlated with poor clinical outcome in a large cohort of patients with neuroblastoma. Furthermore, we captured spatial intratumor heterogeneity using ten PDXs from a single high-risk patient tumor. We observed diverse growth rates, transcriptional, proteomic, and phosphoproteomic profiles. PDX-derived transcriptional profiles were associated with diverse clinical characteristics in patients with high-risk neuroblastoma. These data suggest that high-risk neuroblastoma contains elements of both temporal stability and spatial intratumor heterogeneity, the latter of which complicates clinical translation of personalized PDX-Avatar studies into preclinical cancer research.Significance: These findings underpin the complexity of PDX modeling as a means to advance translational applications against neuroblastoma. Cancer Res; 78(20); 5958-69. ©2018 AACR.

A highly malignant case of neuroblastoma with substantial increase of single-nucleotide variants and normal mismatch repair system: A case report

RATIONALE

Neuroblastoma is a common abdominal malignancy in children. The chemoresistant and relapsed cases have poor prognosis. The genetic background and the mechanism of resistance remain unelucidated. Next-generation sequence (NGS) is becoming a popular tool to unravel the genetic background and to guide precision medicine in oncology studies as well as in clinical practice.

PATIENT CONCERNS

Here we report a neuroblastoma case of a boy aged 2 years and 8 months when first diagnosed, with multiple metastatic sites found in both lungs. The metastatic tumors were resistant to chemotherapy and the patient suffered from severe bone marrow suppression. NGS of the whole exon revealed somatic mutations including 9666 single-nucleotide variants (SNVs) from 5148 genes, 55 copy number variations (CNVs), and 140 insertion-deletion variations. The high frequency of SNVs makes it distinguished case. However, no mutation of key tumor driver genes with functional significance was identified. No abnormality was found in nucleic acid synthesis enzymes. No amplification of c-Myc and n-Myc was found by fluorescence in situ hybridization (FISH). Both NGS and immunohistochemistry (IHC) analysis indicated that DNA mismatch repair (MMR) system was intact.

INTERVENTIONS

After initial diagnosis, the patient received combinational chemotherapy, which includes vindesine, an analogue of adriamycin suggested by NGS data, for 4 months. Radical section of the tumor together with the left kidney and the left adrenal gland was performed 5 months after diagnosis. Postsurgical chemotherapy protocols was similar with the previous.

OUTCOMES

The patient died 2 years after initial diagnosis after 8 relapses following combinational chemotherapy.

LESSONS

This case of neuroblastoma is with pronounced somatic mutations but unidentified driver gene and therapeutic target. Although NGS is a potentially powerful tool to guide precision medicine, at current stage, its application in the clinic certainly has its limits. The underlying mechanism of the substantially increased SNV number, as well as the malignant behaviors of the tumor, is yet to be revealed.

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path.

Genome-wide association pathway analysis to identify candidate single nucleotide polymorphisms and molecular pathways for gastric adenocarcinoma

To demonstrate candidate single nucleotide polymorphisms that might affect susceptibility to gastric adenocarcinoma as well as their potential mechanisms and pathway hypotheses, we performed a genome-wide association study dataset of gastric adenocarcinoma. Our study included 472,342 single nucleotide polymorphisms from 2766 cases of gastric cardia adenocarcinoma cases and 11,013 subjects from north central China as control groups. The identify candidate causal SNPs and pathways (ICSNPathway) analysis was employed to identify 13 candidate single nucleotide polymorphisms, nine genes, and 15 pathways. The top three candidate SNPs were rs3765524 (-log10(p) = 8.556), rs2274223 (-log10(p) = 8.633), and rs2076472 (-log10(p) = 3.205). The strongest mechanism involved the modulation of rs4745 and rs12904, thereby affecting their regulatory roles in ephrin receptor binding (p = 0.001; FDR = 0.005). The second strongest hypothetical biological mechanism was that rs932972 and rs1052177 alters the regulatory role of the glycolysis pathway (p < 0.001; FDR = 0.013). The most significant pathway was the regulation of the ephrin receptor binding pathway, which involved EFNA1, TIAM1, EFNA5, EFNB2, and EFNB3.

Genetic variants and risk of esophageal squamous cell carcinoma: a GWAS-based pathway analysis

This study was designed to identify candidate single-nucleotide polymorphisms (SNPs) that may affect the susceptibility to esophageal squamous cell carcinoma (ESCC) and elucidate their potential mechanisms to generate SNP-to-gene-to-pathway hypotheses. A genome-wide association study (GWAS) dataset for ESCC, which included 453,852 SNPs from 1898 ESCC patients and 2100 control subjects of Chinese population, was reviewed. The identify candidate causal SNPs and pathways (ICSNPathway) analysis identified seven candidate SNPs, five genes, and seven pathways, which together revealed seven hypothetical biological mechanisms. The three strongest hypothetical biological mechanisms were as follows: rs4135113→TDG→BASE EXCISION REPAIR; rs1800450→MBL2→MONOSACCHARIDE BINDING; and rs3769823→CASP8→d4gdiPathway. The GWAS dataset was evaluated using the ICSNPathway, which showed seven candidate SNPs, five genes, and seven pathways that may contribute to the susceptibility of patients to ESCC.