Identification of rare germline copy number variations over-represented in five human cancer types

Insights into the Clinical, Biological and Therapeutic Impact of Copy Number Alteration in Cancer

Copy number alterations (CNAs), resulting from the gain or loss of genetic material from as little as 50 base pairs or as big as entire chromosome(s), have been associated with many congenital diseases, de novo syndromes and cancer. It is established that CNAs disturb the dosage of genomic regions including enhancers/promoters, long non-coding RNA and gene(s) among others, ultimately leading to an altered balance of key cellular functions. In cancer, CNAs have been associated with almost all steps of the disease: predisposition, initiation, development, maintenance, response to treatment, resistance, and relapse. Therefore, understanding how specific CNAs contribute to tumourigenesis may provide prognostic insight and ultimately lead to the development of new therapeutic approaches to improve patient outcomes. In this review, we provide a snapshot of what is currently known about CNAs and cancer, incorporating topics regarding their detection, clinical impact, origin, and nature, and discuss the integration of innovative genetic engineering strategies, to highlight the potential for targeting CNAs using novel, dosage-sensitive and less toxic therapies for CNA-driven cancer.

Integrative Analysis of Germline Rare Variants in Clear and Non-clear Cell Renal Cell Carcinoma

Background and objective

Previous germline studies on renal cell carcinoma (RCC) have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification, which might have led to an inaccurate estimation of genetic risk. Here, we aim to analyze the major germline drivers of RCC risk and clinically relevant but underexplored germline variant types.

Methods

We first characterized germline pathogenic variants (PVs), cryptic splice variants, and copy number variants (CNVs) in 1436 unselected RCC patients. To evaluate the enrichment of PVs in RCC, we conducted a case-control study of 1356 RCC patients ancestry matched with 16 512 cancer-free controls using approaches accounting for population stratification and histological subtypes, followed by characterization of secondary somatic events.

Key findings and limitations

Clear cell RCC patients (n = 976) exhibited a significant burden of PVs in VHL compared with controls (odds ratio [OR]: 39.1, p = 4.95e-05). Non-clear cell RCC patients (n = 380) carried enrichment of PVs in FH (OR: 77.9, p = 1.55e-08) and MET (OR: 1.98e11, p = 2.07e-05). In a CHEK2-focused analysis with European participants, clear cell RCC (n = 906) harbored nominal enrichment of low-penetrance CHEK2 variants-p.Ile157Thr (OR: 1.84, p = 0.049) and p.Ser428Phe (OR: 5.20, p = 0.045), while non-clear cell RCC (n = 295) exhibited nominal enrichment of CHEK2 loss of function PVs (OR: 3.51, p = 0.033). Patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset than patients without germline PVs (mean: 46.0 vs 60.2 yr, p < 0.0001), and more than half had secondary somatic events affecting the same gene (n = 10/15, 66.7%). Conversely, CHEK2 PV carriers exhibited a similar age of onset to patients without germline PVs (mean: 60.1 vs 60.2 yr, p = 0.99), and only 30.4% carried somatic events in CHEK2 (n = 7/23). Finally, pathogenic germline cryptic splice variants were identified in SDHA and TSC1, and pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.

Conclusions and clinical implications

This analysis supports the existing link between several RCC risk genes and RCC risk manifesting in earlier age of onset. It calls for caution when assessing the role of CHEK2 due to the burden of founder variants with varying population frequency. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants.

Patient summary

In this study, we carefully compared the frequency of rare inherited mutations with a focus on patients' genetic ancestry. We discovered that subtle variations in genetic background may confound a case-control analysis, especially in evaluating the cancer risk associated with specific genes, such as CHEK2. We also identified previously less explored forms of rare inherited mutations, which could potentially increase the risk of kidney cancer.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Integrative Analysis of Germline Rare Variants in Clear and Non-Clear Cell Renal Cell Carcinoma

IMPORTANCE

RCC encompasses a set of histologically distinct cancers with a high estimated genetic heritability, of which only a portion is currently explained. Previous rare germline variant studies in RCC have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification that may significantly impact the interpretation and discovery of certain candidate risk genes.

OBJECTIVE

To evaluate the enrichment of germline PVs in established cancer-predisposing genes (CPGs) in clear cell and non-clear cell RCC patients compared to cancer-free controls using approaches that account for population stratification and to identify unconventional types of germline RCC risk variants that confer an increased risk of developing RCC.

DESIGN SETTING AND PARTICIPANTS

In 1,436 unselected RCC patients with sufficient data quality, we systematically identified rare germline PVs, cryptic splice variants, and copy number variants (CNVs). From this unselected cohort, 1,356 patients were ancestry-matched with 16,512 cancer-free controls, and gene-level enrichment of rare germline PVs were assessed in 143 CPGs, followed by an investigation of somatic events in matching tumor samples.

MAIN OUTCOMES AND MEASURES

Gene-level burden of rare germline PVs, identification of secondary somatic events accompanying the germline PVs, and characterization of less-explored types of rare germline PVs in RCC patients.

RESULTS

In clear cell RCC (n = 976 patients), patients exhibited significantly higher prevalence of PVs in VHL compared to controls (OR: 39.1, 95% CI: 7.01-218.07, p-value:4.95e-05, q-value:0.00584). In non-clear cell RCC (n = 380 patients), patients carried enriched burden of PVs in FH (OR: 77.9, 95% CI: 18.68-324.97, p-value:1.55e-08, q-value: 1.83e-06) and MET (OR: 1.98e11, 95% CI: 0-inf, p-value: 2.07e-05, q-value: 3.50e-07). In a CHEK2-focused analysis with European cases and controls, clear cell RCC patients (n=906 European patients) harbored nominal enrichment of the previously reported low-penetrance CHEK2 variants, p.Ile157Thr (OR:1.84, 95% CI: 1.00-3.36, p-value:0.049) and p.Ser428Phe (OR:5.20, 95% CI: 1.00-26.40, p-value:0.045) while non-clear cell RCC patients (n=295 European patients) exhibited nominal enrichment of CHEK2 LOF germline PVs (OR: 3.51, 95% CI: 1.10-11.10, p-value: 0.033). RCC patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset compared to patients without any germline PVs in CPGs (Mean: 46.0 vs 60.2 years old, Tukey adjusted p-value < 0.0001), and more than half had secondary somatic events affecting the same gene (n=10/15, 66.7%, 95% CI: 38.7-87.0%). Conversely, patients with rare germline PVs in CHEK2 exhibited a similar age of disease onset to patients without any identified germline PVs in CPGs (Mean: 60.1 vs 60.2 years old, Tukey adjusted p-value: 0.99), and only 30.4% of the patients carried secondary somatic events in CHEK2 (n=7/23, 95% CI: 14.1-53.0%). Finally, rare pathogenic germline cryptic splice variants underexplored in RCC were identified in SDHA and TSC1, and rare pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.

CONCLUSIONS AND RELEVANCE

This systematic analysis supports the existing link between several RCC risk genes and elevated RCC risk manifesting in earlier age of RCC onset. Our analysis calls for caution when assessing the role of germline PVs in CHEK2 due to the burden of founder variants with varying population frequency in different ancestry groups. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants, such as cryptic splice variants and CNVs.

Shallow Whole-Genome Sequencing of Cell-Free DNA (cfDNA) Detects Epithelial Ovarian Cancer and Predicts Patient Prognosis

Despite the progress in diagnostics and therapeutics, epithelial ovarian cancer (EOC) remains a fatal disease. Using shallow whole-genome sequencing of plasma cell-free DNA (cfDNA), we investigated biomarkers that could detect EOC and predict survival. Plasma cfDNA from 40 EOC patients and 20 healthy subjects were analyzed by shallow whole-genome sequencing (WGS) to identify copy number variations (CNVs) and determine the Z-scores of genes. In addition, we also calculated the genome-wide scores (Gi scores) to quantify chromosomal instability. We found that the Gi scores could distinguish EOC patients from healthy subjects and identify various EOC histological subtypes (e.g., high-grade serous carcinoma). In addition, we characterized EOC CNVs and demonstrated a relationship between RAB25 amplification (alone or with CA125), and disease-free survival and overall survival. This study identified RAB25 amplification as a predictor of EOC patient survival. Moreover, we showed that Gi scores could detect EOC. These data demonstrated that cfDNA, detected by shallow WGS, represented a potential tool for diagnosing EOC and predicting its prognosis.

Construction and validation of a prognostic signature using CNV-driven genes for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the major causes of cancer-related deaths worldwide. Copy number variations (CNVs) affect the expression of genes and play critical roles in carcinogenesis. We aimed to identify specific CNV-driven genes and establish a prognostic model for HCC.

Methods

Integrative analysis of CNVs difference data and differentially expressed genes (DEGs) data from The Cancer Genome Atlas (TCGA) were conducted to identify critical CNV-driven genes for HCC. A risk model was constructed based on univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. The associations between CNV-driven genes signature and infiltrating immune cells were explored. The International Cancer Genome Consortium (ICGC) dataset was utilized to validate this model.

Results

After integrative analysis of CNVs and corresponding mRNA expression profiles, 568 CNV-driven genes were identified. Sixty-three CNV-driven genes were found to be markedly associated with overall survival (OS) after univariate Cox regression analysis. Finally, eight CNV-driven genes were screened to generate a prognostic risk model. Compared with low-risk group, the OS of patients in the high-risk group was significantly shorter in both the TCGA [hazard ratio (HR) =6.14, 95% confidence interval (CI): 2.72-13.86, P<0.001] and ICGC (HR =3.23, 95% CI: 1.17-8.92, P<0.001) datasets. Further analysis revealed the infiltrating neutrophils were positively correlated with risk score. Meanwhile, the high-risk group was associated with higher expression of immune checkpoint genes.

Conclusions

A novel signature based on CNV-driven genes was built to predict the survival of HCC patients and showed good performance. The results of our study may improve understanding of the mechanism that drives HCC, and provide an immunological perspective for individualized therapies.

All HPV-negative head and neck cancers are not the same: Analysis of the TCGA dataset reveals that anatomical sites have distinct mutation, transcriptome, hypoxia, and tumor microenvironment profiles

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) affects various anatomical sites, which often dictates whether the cancer is managed with primary surgery or radiation. This study aimed to assess differences in single nucleotide variation (SNV), copy number, mRNA abundance, methylation, and tumor microenvironment (TME) between HPV-negative oral cavity (OC), oropharyngeal (OPC), hypopharyngeal (HPC), and laryngeal (LC) cancers within The Cancer Genome Atlas (TCGA).

METHODS

We downloaded the clinical information and molecular data for the TCGA HNSCC cohort from the data portal and published literature. The TME was estimated using mRNA abundance data. We conducted our analyses within the Bioconductor statistical framework in the R environment. CNA and mRNA abundance results were correlated and grouped with SNV results for downstream pathway analysis.

RESULTS

LC had a higher mutational burden than OC and OPC (p <10^-4). LC tumors were enriched in CSMD3, NSD1, DCHS2 and ANK2 SNVs, while OC tumors were enriched in CASP8 SNVs (FDR < 0.1). LCs were enriched for neuronal and glycosylation pathways, while OCs were enriched for extracellular matrix pathways. B cells and endothelial cells were more abundant in LC while monocytes were more abundant in OC (FDR < 0.1). OPC was the most hypoxic, followed by OC then LC (FDR < 0.05). OC had greater methylation of Hox genes than LC. Subsite analysis revealed that oral tongue cancers had fewer CASP8 and FBN2 mutations and higher dendritic cell abundance than other oral cavity cancers.

CONCLUSIONS

We identified significant genomic, transcriptional, and microenvironmental differences between HPV-negative HNSCC. Further study is warranted to determine if these findings portend differential response to specific treatment modalities.

USP8 and TP53 Drivers are Associated with CNV in a Corticotroph Adenoma Cohort Enriched for Aggressive Tumors

CONTEXT

Pituitary corticotroph adenomas are rare tumors that can be associated with excess adrenocorticotropin (ACTH) and adrenal cortisol production, resulting in the clinically debilitating endocrine condition Cushing disease. A subset of corticotroph tumors behave aggressively, and genomic drivers behind the development of these tumors are largely unknown.

OBJECTIVE

To investigate genomic drivers of corticotroph tumors at risk for aggressive behavior.

DESIGN

Whole-exome sequencing of patient-matched corticotroph tumor and normal deoxyribonucleic acid (DNA) from a patient cohort enriched for tumors at risk for aggressive behavior.

SETTING

Tertiary care center.

PATIENTS

Twenty-seven corticotroph tumors from 22 patients were analyzed. Twelve tumors were macroadenomas, of which 6 were silent ACTH tumors, 2 were Crooke's cell tumors, and 1 was a corticotroph carcinoma.

INTERVENTION

Whole-exome sequencing.

MAIN OUTCOME MEASURE

Somatic mutation genomic biomarkers.

RESULTS

We found recurrent somatic mutations in USP8 and TP53 genes, both with higher allelic fractions than other somatic mutations. These mutations were mutually exclusive, with TP53 mutations occurring only in USP8 wildtype (WT) tumors, indicating they may be independent driver genes. USP8-WT tumors were characterized by extensive somatic copy number variation compared with USP8-mutated tumors. Independent of molecular driver status, we found an association between invasiveness, macroadenomas, and aneuploidy.

CONCLUSIONS

Our data suggest that corticotroph tumors may be categorized into a USP8-mutated, genome-stable subtype versus a USP8-WT, genome-disrupted subtype, the latter of which has a TP53-mutated subtype with high level of chromosome instability. These findings could help identify high risk corticotroph tumors, namely those with widespread CNV, that may need closer monitoring and more aggressive treatment.

Integrative analysis of genomic and epigenetic regulation of endometrial cancer

Endometrial carcinomas (EC) are characterized by high DNA copy numbers and DNA methylation aberrations. In this study, we sought to comprehensively explore the effect of these two factors on development and progression of EC by analyzing integrated genomic and epigenetic analysis to. We found high DNA copy number and DNA methylation abnormalities in EC, with 6308 copy-number variation genes (CNV-G) and 4376 methylation genes (MET-G). We used these CNV-G and MET-G to subcategorize the samples for prognostic analysis, and identified three molecular subtypes (iC1, iC2, iC3). Moreover, the subtypes exhibited different tumor immune microenvironment characteristics. A further analysis of their molecular characteristics revealed three potential prognostic markers (KIAA1324, nonexpresser of pathogenesis-related genes1 (NPR1) and idiopathic hypogonadotropic hypogonadism (IHH)). Notably, all three markers showed distinct CNV, DNA methylation, and gene expression profiles. Analysis of mutations among the three subtypes revealed that iC2 had fewer mutations than the other subtypes. Conversely, iC2 showed significantly higher CNV levels than other subtypes. This comprehensive analysis of genomic and epigenetic profiles identified three prognostic markers, therefore, provides new insights into the multi-layered pathology of EC. These can be utilized for accurate treatment of EC patients.

A snapshot neural ensemble method for cancer-type prediction based on copy number variations

An accurate diagnosis and prognosis for cancer are specific to patients with particular cancer types and molecular traits, which needs to address carefully. The discovery of important biomarkers is becoming an important step toward understanding the molecular mechanisms of carcinogenesis in which genomics data and clinical outcomes need to be analyzed before making any clinical decision. Copy number variations (CNVs) are found to be associated with the risk of individual cancers and hence can be used to reveal genetic predispositions before cancer develops. In this paper, we collect the CNVs data about 8000 cancer patients covering 14 different cancer types from The Cancer Genome Atlas. Then, two different sparse representations of CNVs based on 578 oncogenes and 20,308 protein-coding genes, including genomic deletions and duplication across the samples, are prepared. Then, we train Conv-LSTM and convolutional autoencoder (CAE) networks using both representations and create snapshot models. While the Conv-LSTM can capture locally and globally important features, CAE can utilize unsupervised pretraining to initialize the weights in the subsequent convolutional layers against the sparsity. Model averaging ensemble (MAE) is then applied to combine the snapshot models in order to make a single prediction. Finally, we identify most significant CNVs biomarkers using guided-gradient class activation map plus (GradCAM++) and rank top genes for different cancer types. Results covering several experiments show fairly high prediction accuracies for the majority of cancer types. In particular, using protein-coding genes, Conv-LSTM and CAE networks can predict cancer types correctly at least 72.96% and 76.77% of the cases, respectively. Contrarily, using oncogenes gives moderately higher accuracies of 74.25% and 78.32%, whereas the snapshot model based on MAE shows overall 2.5% of accuracy improvement.

Germline 16p11.2 Microdeletion Predisposes to Neuroblastoma

Neuroblastoma is a cancer of the developing sympathetic nervous system. It is diagnosed in 600-700 children per year in the United States and accounts for 12% of pediatric cancer deaths. Despite recent advances in our understanding of this malignancy's complex genetic architecture, the contribution of rare germline variants remains undefined. Here, we conducted a genome-wide analysis of large (>500 kb), rare (<1%) germline copy number variants (CNVs) in two independent, multi-ethnic cohorts totaling 5,585 children with neuroblastoma and 23,505 cancer-free control children. We identified a 550-kb deletion on chromosome 16p11.2 significantly enriched in neuroblastoma cases (0.39% of cases and 0.03% of controls; p = 3.34 × 10^-9). Notably, this CNV corresponds to a known microdeletion syndrome that affects approximately one in 3,000 children and confers risk for diverse developmental phenotypes including autism spectrum disorder and other neurodevelopmental disorders. The CNV had a substantial impact on neuroblastoma risk, with an odds ratio of 13.9 (95% confidence interval = 5.8-33.4). The association remained significant when we restricted our analysis to individuals of European ancestry in order to mitigate potential confounding by population stratification (0.42% of cases and 0.03% of controls; p = 4.10 × 10^-8). We used whole-genome sequencing (WGS) to validate the deletion in paired germline and tumor DNA from 12 cases. Finally, WGS of four parent-child trios revealed that the deletion primarily arose de novo without maternal or paternal bias. This finding expands the clinical phenotypes associated with 16p11.2 microdeletion syndrome to include cancer, and it suggests that disruption of the 16p11.2 region may dysregulate neurodevelopmental pathways that influence both neurological phenotypes and neuroblastoma.

A Propensity Score-adjusted Analysis of the Effects of Ubiquitin E3 Ligase Copy Number Variation in Peripheral Blood Leukocytes on Colorectal Cancer Risk

Background: The ubiquitin ligases E3 (E3s) plays a key role in the specific protein degradation in many carcinogenic biological processes. Colorectal cancer (CRC) development may be affected by the copy number variation (CNV) of E3s. Prior studies may have underestimated the impact of potential confounding factors' effects on the association between gene CNV and CRC risk, and CRC risk predictive model integrating gene CNV patterns is lacking. Our research sought to assess the genes CNVs of MDM2, SKP2, FBXW7, β-TRCP, and NEDD4-1 and CRC risk by using propensity score (PS) adjustment and developing models that integrate CNV patterns for CRC risk predictions.

Methods: This study comprising 1036 participants used traditional regression and different PS techniques to adjust the confounding factors to evaluate the relationships between five gene CNVs and CRC risk, and to establish a CRC risk predictive model. The AUC was applied to evaluate the effect of the model. The categorical net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) were analyzed to evaluate the discriminatory accuracy improvement among the models.

Results: Compared to variable adjustment, the odds ratios (ORs) tended to be conservative and accurate with narrow confidence intervals (CIs) after PS adjustment. After PS adjustment, MDM2 amplification was related to increased CRC risk (Amp-pattern: OR = 8.684, 95% CI: 1.213-62.155, P = 0.031), whereas SKP2 deletion and the (del+amp) genotype were associated with reduced CRC risk (Del-pattern: OR = 0.323, 95% CI: 0.106-0.979, P = 0.046; Var-pattern: OR = 0.339, 95% CI: 0.135-0.854, P = 0.024). The predictive model integrating the gene CNV pattern could correctly reclassify 1.7% of the subjects.

Conclusions: MDM2 amplification and SKP2 CNVs are associated with increased and decreased CRC risk, respectively; abnormal CNV-integrated model is more precise for predicting CRC risk. Further studies are needed to verify these encouraging outcomes.

MR imaging phenotype correlates with extent of genome-wide copy number abundance in IDH mutant gliomas

PURPOSE

There is variability in survival within IDH mutant gliomas determined by chromosomal events. Copy number variation (CNV) abundance associated with survival in low-grade and IDH mutant astrocytoma has been reported. Our purpose was to correlate the extent of genome-wide CNV abundance in IDH mutant astrocytomas with MRI features.

METHODS

Presurgical MRI and CNV plots derived from Illumina 850k EPIC DNA methylation arrays of 18 cases of WHO grade II-IV IDH mutant astrocytomas were reviewed. IDH mutant astrocytomas were divided into CNV stable group (CNV-S) with ≤ 3 chromosomal gains or losses and lack of focal gene amplifications and CNV unstable group (CNV-U) with > 3 large chromosomal gains/losses and/or focal amplifications. The associations between MR features, relative cerebral blood volume (rCBV), CNV abundance, and time to progression were assessed. Tumor rCBV estimates were obtained using DSC T2* perfusion analysis.

RESULTS

There were nine (50%) CNV-S and nine (50%) CNV-U IDH mutant astrocytomas. CNV-U tumors showed larger mean tumor size (P = 0.004) and maximum diameter on FLAIR (P = 0.004) and also demonstrated significantly higher median rCBV than CNV-S tumors (2.62 vs 0.78, P = 0.019). CNV-U tumors tended to have shorter time to progression although without statistical significance (P = 0.393).

CONCLUSIONS

Larger size/diameter and higher rCBVs were seen associated CNV-U astrocytomas, suggesting a correlation of aggressive imaging phenotype with unstable and aggressive genotype in IDH mutant astrocytomas.

Large Genomic Aberrations in Corticotropinomas Are Associated With Greater Aggressiveness

CONTEXT

Genomic losses/gains are associated with cancer progression and prognosis. In pituitary adenomas, analyses of copy number variations (CNVs) have shown that a subset of adenomas have higher genomic variability. However, whether CNVs are associated with tumor aggressiveness and prognosis has not been determined.

OBJECTIVE

We hypothesized that somatic CNVs of pituitary tumors may play a role in the progression and aggressiveness of pituitary corticotropinomas in children and adolescents.

SAMPLES AND DESIGN

Paired germline and tumor DNA samples from 27 pediatric patients with Cushing disease (CD), were subjected to whole exome sequencing. Somatic CNVs were identified using the ExomeDepth tool. Clinical, histological, and biochemical data from the patients were collected and correlated with the results of the CNV analysis.

RESULTS

Chromosomal instability, involving 23% to 59% of the tumor genome, was noted in 5 of the 27 samples (18.5%). The patients with tumors showing chromosomal instability had similar clinical and biochemical characteristics to the remaining patients, except for tumor size, which was larger (median size 18 mm vs 5.5 mm, P = 0.005). Tumors with chromosomal instability were also associated with a higher rate of invasion of the cavernous sinus (P = 0.029). There was insufficient information on persistence or recurrence of CD to determine whether the risk was higher in those with chromosomal instability.

CONCLUSIONS

A subgroup of corticotropinomas demonstrates chromosomal instability that is associated with markers of aggressiveness of these adenomas. It appears that more genomic gains/losses in a few, rare corticotropinomas may predict poorer prognosis for pediatric patients with CD.

Structural Aberrations with Secondary Implications (SASIs): consensus recommendations for reporting of cancer susceptibility genes identified during analysis of Copy Number Variants (CNVs)

Clinical testing with chromosomal microarray (CMA) is most commonly undertaken for clinical indications such as intellectual disability, dysmorphic features and/or congenital abnormalities. Identification of a structural aberration (SA) involving a cancer susceptibility gene (CSG) constitutes a type of incidental or secondary finding. Laboratory reporting, risk communication and clinical management of these structural aberrations with secondary implications (SASIs) is currently inconsistent. We undertake meta-analysis of 18 622 instances of CMA performed for unrelated indications in which 106 SASIs are identified involving in total 40 different CSGs. Here we present the recommendations of a joint UK working group representing the British Society of Genomic Medicine, UK Cancer Genetics Group and UK Association for Clinical Genomic Science. SASIs are categorised into four groups, defined by the type of SA and the cancer risk. For each group, recommendations are provided regarding reflex parental testing and cancer risk management.

Identifying disease-associated copy number variations by a doubly penalized regression model

Copy number variation (CNV) of DNA plays an important role in the development of many diseases. However, due to the irregularity and sparsity of the CNVs, studying the association between CNVs and a disease outcome or a trait can be challenging. Up to now, not many methods have been proposed in the literature for this problem. Most of the current researchers reply on an ad hoc two-stage procedure by first identifying CNVs in each individual genome and then performing an association test using these identified CNVs. This potentially leads to information loss and as a result a lower power to identify disease associated CNVs. In this article, we describe a new method that combines the two steps into a single coherent model to identify the common CNV across patients that are associated with certain diseases. We use a double penalty model to capture CNVs' association with both the intensities and the disease trait. We validate its performance in simulated datasets and a data example on platinum resistance and CNV in ovarian cancer genome.

DNA copy number gain-mediated lncRNA LINC01061 upregulation predicts poor prognosis and promotes papillary thyroid cancer progression

Several DNA copy number amplifications (CNAs) have been reported in papillary thyroid cancer (PTC). However, the functional role of CNAs in PTC remains very unclear. And whether there is a correlation between long noncoding RNA (lncRNA) and CNA requires to be explored. Here, we identified a novel lncRNA LINC01061. The genomic copy number of LINC01061 is amplified, which leads to its elevated expression level in PTC tissues. Moreover, increased level of LINC01061 was correlated with aggressive clinicopathological characteristics. Functional study indicated that LINC01061 silence significantly inhibited the proliferation, cell-cycle and invasion of PTC cells in vitro and tumor growth in vivo. Mechanistically, we showed that LINC01061 interacted with miR-4316 to promote E2F6 expression. The expression of miR-4316 was downregulated in PTC tissues while that of E2F6 was upregulated. Through rescue assay, we demonstrated that LINC01061 promoted PTC cell proliferation, cell-cycle progression and invasion by regulating miR-4316/E2F6 signaling pathway. In conclusion, our research indicated that LINC01061 might be a target for PTC therapy.

Genetic susceptibility to neuroblastoma: current knowledge and future directions

Neuroblastoma, a malignancy of the developing peripheral nervous system that affects infants and young children, is a complex genetic disease. Over the past two decades, significant progress has been made toward understanding the genetic determinants that predispose to this often lethal childhood cancer. Approximately 1-2% of neuroblastomas are inherited in an autosomal dominant fashion and a combination of co-morbidity and linkage studies has led to the identification of germline mutations in PHOX2B and ALK as the major genetic contributors to this familial neuroblastoma subset. The genetic basis of "sporadic" neuroblastoma is being studied through a large genome-wide association study (GWAS). These efforts have led to the discovery of many common susceptibility alleles, each with modest effect size, associated with the development and progression of sporadic neuroblastoma. More recently, next-generation sequencing efforts have expanded the list of potential neuroblastoma-predisposing mutations to include rare germline variants with a predicted larger effect size. The evolving characterization of neuroblastoma's genetic basis has led to a deeper understanding of the molecular events driving tumorigenesis, more precise risk stratification and prognostics and novel therapeutic strategies. This review details the contemporary understanding of neuroblastoma's genetic predisposition, including recent advances and discusses ongoing efforts to address gaps in our knowledge regarding this malignancy's complex genetic underpinnings.

Long noncoding RNA CNALPTC1 promotes cell proliferation and migration of papillary thyroid cancer via sponging miR-30 family

Several somatic copy number variations (CNVs) have been identified in papillary thyroid cancer (PTC). However, the functional roles of CNVs and the genes responsible for the roles of CNVs are largely unknown. In this study, we identified a novel long noncoding RNA (lncRNA) CNALPTC1 (copy number amplified long noncoding RNA in papillary thyroid cancer 1). The genomic copy number of CNALPTC1 is amplified and CNALPTC1 expression level is up-regulated in PTC. Increased expression of CNALPTC1 is associated with aggressive clinicopathological characteristics. Gain-of-function and loss-of-function assays revealed that CNALPTC1 promotes proliferation and migration of PTC cells, and inhibits apoptosis of PTC cells. Mechanistically, we found that CNALPTC1 physically associates to miR-30 family and down-regulates miR-30 expression. Furthermore, CNALPTC1 up-regulates the expression of miR-30 targets, such as BCL9, SNAI1, and VIM. The mutation of miR-30 binding site on CNALPTC1 or overexpression of miR-30 abrogates the oncogenic roles of CNALPTC1 in PTC. Collectively, our results suggested that the copy number amplified lncRNA CNALPTC1 promotes PTC progression via sponging miR-30 family. Our data also implied that CNALPTC1 may be a novel therapeutic target for PTC.

QuaDMutEx: quadratic driver mutation explorer

BACKGROUND

Somatic mutations accumulate in human cells throughout life. Some may have no adverse consequences, but some of them may lead to cancer. A cancer genome is typically unstable, and thus more mutations can accumulate in the DNA of cancer cells. An ongoing problem is to figure out which mutations are drivers - play a role in oncogenesis, and which are passengers - do not play a role. One way of addressing this question is through inspection of somatic mutations in DNA of cancer samples from a cohort of patients and detection of patterns that differentiate driver from passenger mutations.

RESULTS

We propose QuaDMutEx, a method that incorporates three novel elements: a new gene set penalty that includes non-linear penalization of multiple mutations in putative sets of driver genes, an ability to adjust the method to handle slow- and fast-evolving tumors, and a computationally efficient method for finding gene sets that minimize the penalty, through a combination of heuristic Monte Carlo optimization and exact binary quadratic programming. Compared to existing methods, the proposed algorithm finds sets of putative driver genes that show higher coverage and lower excess coverage in eight sets of cancer samples coming from brain, ovarian, lung, and breast tumors.

CONCLUSIONS

Superior ability to improve on both coverage and excess coverage on different types of cancer shows that QuaDMutEx is a tool that should be part of a state-of-the-art toolbox in the driver gene discovery pipeline. It can detect genes harboring rare driver mutations that may be missed by existing methods. QuaDMutEx is available for download from https://github.com/bokhariy/QuaDMutEx under the GNU GPLv3 license.

ExCNVSS: A Noise-Robust Method for Copy Number Variation Detection in Whole Exome Sequencing Data

Copy number variations (CNVs) are structural variants associated with human diseases. Recent studies verified that disease-related genes are based on the extraction of rare de novo and transmitted CNVs from exome sequencing data. The need for more efficient and accurate methods has increased, which still remains a challenging problem due to coverage biases, as well as the sparse, small-sized, and noncontinuous nature of exome sequencing. In this study, we developed a new CNV detection method, ExCNVSS, based on read coverage depth evaluation and scale-space filtering to resolve these problems. We also developed the method ExCNVSS_noRatio, which is a version of ExCNVSS, for applying to cases with an input of test data only without the need to consider the availability of a matched control. To evaluate the performance of our method, we tested it with 11 different simulated data sets and 10 real HapMap samples' data. The results demonstrated that ExCNVSS outperformed three other state-of-the-art methods and that our method corrected for coverage biases and detected all-sized CNVs even without matched control data.

BREAST CANCER HISTOPATHOLOGY IMAGE ANALYSIS PIPELINE FOR TUMOR PURITY ESTIMATION

The translation of genomic sequencing technology to the clinic has greatly advanced personalized medicine. However, the presence of normal cells in tumors is a confounding factor in genome sequence analysis. Tumor purity, or the percentage of cancerous cells in whole tissue section, is a correction factor that can be used to improve the clinical utility of genomic sequencing. Currently, tumor purity is estimated visually by expert pathologists; however, it has been shown that there exist vast inter-observer discrepancies in tumor purity scoring. In this paper, we propose a quantitative image analysis pipeline for tumor purity estimation and provide a systematic comparison between pathologists' scores and our image-based tumor purity estimation.

Next Generation Sequencing of Circulating Cell-Free DNA for Evaluating Mutations and Gene Amplification in Metastatic Breast Cancer

BACKGROUND

Breast cancer tissues are heterogeneous and show diverse somatic mutations and somatic copy number alterations (CNAs). We used a novel targeted next generation sequencing (NGS) panel to examine cell-free DNA (cfDNA) to detect somatic mutations and gene amplification in women with metastatic breast cancer (MBC).

METHODS

cfDNA from pretreated patients (n = 42) and 9 healthy controls were compared with matched lymphocyte DNA by NGS, using a custom 158 amplicon panel covering hot-spot mutations and CNAs in 16 genes, with further validation of results by droplet digital PCR.

RESULTS

No mutations were identified in cfDNA of healthy controls, whereas exactly half the patients with metastatic breast cancer had at least one mutation or amplification in cfDNA (mean 2, range 1-6) across a total of 13 genes. Longitudinal follow up showed dynamic changes to mutations and gene amplification in cfDNA indicating clonal and subclonal response to treatment that was more dynamic than cancer antigen 15-3 (CA15-3). Interestingly, at the time of blood sampling disease progression was occurring in 7 patients with erb-b2 receptor tyrosine kinase 2 (ERBB2) gene amplification in their cfDNA and 3 of these patients were human epidermal growth factor receptor 2 (HER2) negative at diagnosis, suggesting clonal evolution to a more aggressive phenotype. Lastly, 6 patients harbored estrogen receptor 1 (ESR1) mutations in cfDNA, suggesting resistance to endocrine therapy. Overall 9 of 42 patients (21%) had alterations in cfDNA that could herald a change in treatment.

CONCLUSIONS

Targeted NGS of cfDNA has potential for monitoring response to targeted therapies through both mutations and gene amplification, for analysis of dynamic tumor heterogeneity and stratification to targeted therapy.

A Genome-Wide Association Study to Identify Potential Germline Copy Number Variants for Sporadic Breast Cancer Susceptibility

Breast cancer (BC) predisposition in populations arises from both genetic and nongenetic risk factors. Structural variations such as copy number variations (CNVs) are heritable determinants for disease susceptibility. The primary objectives of this study are (1) to identify CNVs associated with sporadic BC using a genome-wide association study (GWAS) design; (2) to utilize 2 distinct CNV calling algorithms to identify concordant CNVs as a strategy to reduce false positive associations in the hypothesis-generating GWAS discovery phase, and (3) to identify potential candidate CNVs for follow-up replication studies. We used Affymetrix SNP Array 6.0 data profiled on Caucasian subjects (422 cases/348 controls) to call CNVs using algorithms implemented in Nexus Copy Number and Partek Genomics Suite software. Nexus algorithm identified CNVs associated with BC (731 autosomal CNVs with >5% frequency in the total sample and Q < 0.05). Thirteen CNVs were identified when Partek algorithm-called CNVs were overlapped with Nexus-identified CNVs; these CNVs showed concordances for frequency, effect size, and direction. Coding genes present within BC-associated CNVs were known to play a role in disease etiology and prognosis. Long noncoding RNAs identified within CNVs showed tissue-specific expression, indicating potential functional relevance of the findings. The identified candidate CNVs warrant independent replication.

Comprehensive Screening of Gene Copy Number Aberrations in Formalin-Fixed, Paraffin-Embedded Solid Tumors Using Molecular Inversion Probe-Based Single-Nucleotide Polymorphism Array

Gene copy number aberrations (CNAs) represent a major class of cancer-related genomic alterations that drive solid tumors. Comprehensive and sensitive detection of CNAs is challenging because of often low quality and quantity of DNA isolated from the formalin-fixed, paraffin-embedded (FFPE) solid tumor samples. Here, in a clinical molecular diagnostic laboratory, we tested the utility and validated a molecular inversion probe-based (MIP) array to routinely screen for CNAs in solid tumors. Using low-input FFPE DNA, the array detects genome-wide CNAs with a special focus on 900 cancer-related genes. A cohort of 76 solid tumors of various types and tumor cellularity (20% to 100%), and four cancer cell lines were used. These harbored CNAs in clinically important genes (ERBB2, EGFR, FGFR1, KRAS, MYC) as detected by orthogonal techniques like next-generation sequencing or fluorescence in situ hybridization. Results of the MIP array were concordant with results from orthogonal techniques, and also provided additional information regarding the allelic nature of the CNAs. Limit-of-detection and assay reproducibility studies showed a high degree of sensitivity and reproducibility of detection, respectively. FFPE compatibility, ability to detect CNAs with high sensitivity, accuracy, and provide valuable information such as loss of heterozygosity along with relatively short turnaround times makes the MIP array a desirable clinical platform for routine screening of solid tumors in a clinical laboratory.

Molecular and pathophysiological aspects of metal ion uptake by the zinc transporter ZIP8 (SLC39A8)

Zinc ion (Zn2+) is essential for life; its deficiency in the human body could cause stunted growth, anemia and susceptibility to infection. The Zn transporter ZIP8 (also known as SLC39A8) is an important Zn2+ importer; aberrant Zn2+ influx mediated by ZIP8 can lead to the pathogenesis of osteoarthritis and inflammatory diseases. ZIP8 also mediates the cellular uptake of divalent metal ions including iron, manganese, and the toxic heavy metal cadmium. Individuals with SLC39A8 mutations and transgenic mouse models are starting to reveal the critical role that this gene plays in embryonic development and the metabolism of essential metal ions. Here we summarize our current understanding of ZIP8's function and regulation, at both the molecular and biological levels. We also review the association of ZIP8 with various diseases and its linkage with complex disorders like obesity, hypertension, and schizophrenia as revealed by several large genome-wide association studies.

Genome-wide copy number variation (CNV) detection in Nelore cattle reveals highly frequent variants in genome regions harboring QTLs affecting production traits

Background

Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance.

Results

Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively.

Conclusions

Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2752-9) contains supplementary material, which is available to authorized users.