Genomic imbalances in 5918 malignant epithelial tumors: an explorative meta-analysis of chromosomal CGH data

Selection forces underlying aneuploidy patterns in cancer

Aneuploidy, the presence of an aberrant number of chromosomes, has been associated with tumorigenesis for over a century. More recently, advances in karyotyping techniques have revealed its high prevalence in cancer: About 90% of solid tumors and 50-70% of hematopoietic cancers exhibit chromosome gains or losses. When analyzed at the level of specific chromosomes, there are strong patterns that are observed in cancer karyotypes both pan-cancer and for specific cancer types. These specific aneuploidy patterns correlate strongly with outcomes for tumor initiation, progression, metastasis formation, immune evasion and resistance to therapeutic treatment. Despite their prominence, understanding the basis underlying aneuploidy patterns in cancer has been challenging. Advances in genetic engineering and bioinformatic analyses now offer insights into the genetic determinants of aneuploidy pattern selection. Overall, there is substantial evidence that expression changes of particular genes can act as the positive selective forces for adaptation through aneuploidy. Recent findings suggest that multiple genes contribute to the selection of specific aneuploid chromosomes in cancer; however, further research is necessary to identify the most impactful driver genes. Determining the genetic basis and accompanying vulnerabilities of specific aneuploidy patterns is an essential step in selectively targeting these hallmarks of tumors.

Exploring the prognostic significance of arm-level copy number alterations in triple-negative breast cancer

Somatic copy number alterations (SCNAs) are prevalent in cancer and play a significant role in both tumorigenesis and therapeutic resistance. While focal SCNAs have been extensively studied, the impact of larger arm-level SCNAs remains poorly understood. Here, we investigated the association between arm-level SCNAs and overall survival in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer lacking targeted therapies. We identified frequent arm-level SCNAs, including 21q gain and 7p gain, which correlated with poor overall survival in TNBC patients. Further, we identified the expression of specific genes within these SCNAs associated with survival. Notably, we found that the expression of RIPK4, a gene located on 21q, exhibited a strong correlation with poor overall survival. In functional assays, we demonstrated that targeting Ripk4 in a murine lung metastatic TNBC model significantly reduced tumor burden, improved survival, and increased CD4+ and CD8+ T cell infiltration. RIPK4 enhanced the survival of triple-negative breast cancer cells at secondary sites, thereby facilitating the formation of metastatic lesions. Our findings highlight the significance of arm-level SCNAs in breast cancer progression and identify RIPK4 as a putative driver of TNBC metastasis and immunosuppression.

Advancements in minimal residual disease detection: a practical approach using single-cell droplet PCR for comprehensive monitoring in hematological malignancy

The identification of chromosomal abnormalities accompanied by copy number alterations is important for understanding tumor characteristics. Testing methodologies for copy number abnormality have limited sensitivity, resulting in their use only for the sample provided at the time of diagnosis or recurrence of malignancy, but not for the monitoring of minimal residual disease (MRD) during and after therapy. We developped the "DimShift" technology which enable to measure the copy number of target gene/chromosome in each cell, which is given by the single cell droplet PCR. Qualitative result of DimShift given by peripheral blood was perfectly concordant with that of bone marrow. These findings and performances are promising to be the new methodology for MRD detection in malignant diseases utilizing bone marrow as well as peripheral blood.

Data-driven information extraction and enrichment of molecular profiling data for cancer cell lines

Motivation

With the proliferation of research means and computational methodologies, published biomedical literature is growing exponentially in numbers and volume. Cancer cell lines are frequently used models in biological and medical research that are currently applied for a wide range of purposes, from studies of cellular mechanisms to drug development, which has led to a wealth of related data and publications. Sifting through large quantities of text to gather relevant information on cell lines of interest is tedious and extremely slow when performed by humans. Hence, novel computational information extraction and correlation mechanisms are required to boost meaningful knowledge extraction.

Results

In this work, we present the design, implementation, and application of a novel data extraction and exploration system. This system extracts deep semantic relations between textual entities from scientific literature to enrich existing structured clinical data concerning cancer cell lines. We introduce a new public data exploration portal, which enables automatic linking of genomic copy number variants plots with ranked, related entities such as affected genes. Each relation is accompanied by literature-derived evidences, allowing for deep, yet rapid, literature search, using existing structured data as a springboard.

Availability and implementation

Our system is publicly available on the web at https://cancercelllines.org.

Candidate targets of copy number deletion events across 17 cancer types

Genome variation is the direct cause of cancer and driver of its clonal evolution. While the impact of many point mutations can be evaluated through their modification of individual genomic elements, even a single copy number aberration (CNA) may encompass hundreds of genes and therefore pose challenges to untangle potentially complex functional effects. However, consistent, recurring and disease-specific patterns in the genome-wide CNA landscape imply that particular CNA may promote cancer-type-specific characteristics. Discerning essential cancer-promoting alterations from the inherent co-dependency in CNA would improve the understanding of mechanisms of CNA and provide new insights into cancer biology and potential therapeutic targets. Here we implement a model using segmental breakpoints to discover non-random gene coverage by copy number deletion (CND). With a diverse set of cancer types from multiple resources, this model identified common and cancer-type-specific oncogenes and tumor suppressor genes as well as cancer-promoting functional pathways. Confirmed by differential expression analysis of data from corresponding cancer types, the results show that for most cancer types, despite dissimilarity of their CND landscapes, similar canonical pathways are affected. In 25 analyses of 17 cancer types, we have identified 19 to 169 significant genes by copy deletion, including RB1, PTEN and CDKN2A as the most significantly deleted genes among all cancer types. We have also shown a shared dependence on core pathways for cancer progression in different cancers as well as cancer type separation by genome-wide significance scores. While this work provides a reference for gene specific significance in many cancers, it chiefly contributes a general framework to derive genome-wide significance and molecular insights in CND profiles with a potential for the analysis of rare cancer types as well as non-coding regions.

Modelling clinical DNA fragmentation in the development of universal PCR-based assays for bisulfite-converted, formalin-fixed and cell-free DNA sample analysis

In fragmented DNA, PCR-based methods quantify the number of intact regions at a specific amplicon length. However, the relationship between the population of DNA fragments within a sample and the likelihood they will amplify has not been fully described. To address this, we have derived a mathematical equation that relates the distribution profile of a stochastically fragmented DNA sample to the probability that a DNA fragment within that sample can be amplified by any PCR assay of arbitrary length. Two panels of multiplex PCR assays for quantifying fragmented DNA were then developed: a four-plex panel that can be applied to any human DNA sample and used to estimate the percentage of regions that are intact at any length; and a two-plex panel optimized for quantifying circulating cell-free DNA (cfDNA). For these assays, regions of the human genome least affected by copy number aberration were identified and selected; within these copy-neutral regions, each PCR assay was designed to amplify both genomic and bisulfite-converted DNA; and all assays were validated for use in both conventional qPCR and droplet-digital PCR. Finally, using the cfDNA-optimized assays we find evidence of universally conserved nucleosome positioning among individuals.

The genomic landscape of cholangiocarcinoma reveals the disruption of post-transcriptional modifiers

Molecular variation between geographical populations and subtypes indicate potential genomic heterogeneity and novel genomic features within CCA. Here, we analyze exome-sequencing data of 87 perihilar cholangiocarcinoma (pCCA) and 261 intrahepatic cholangiocarcinoma (iCCA) cases from 3 Asian centers (including 43 pCCAs and 24 iCCAs from our center). iCCA tumours demonstrate a higher tumor mutation burden and copy number alteration burden (CNAB) than pCCA tumours, and high CNAB indicates a poorer pCCA prognosis. We identify 12 significantly mutated genes and 5 focal CNA regions, and demonstrate common mutations in post-transcriptional modification-related potential driver genes METTL14 and RBM10 in pCCA tumours. Finally we demonstrate the tumour-suppressive role of METTL14, a major RNA N6-adenosine methyltransferase (m6A), and illustrate that its loss-of-function mutation R298H may act through m6A modification on potential driver gene MACF1. Our results may be valuable for better understanding of how post-transcriptional modification can affect CCA development, and highlight both similarities and differences between pCCA and iCCA.

Cholangiocarcinoma is a heterogenous group of cancers, with large genetic variation seen within subtypes. Here, the authors find 12 significantly mutated genes and 5 focal CNA regions were found in perihilar cholangiocarcinoma, and identified METTL14 to have a potential tumour suppressive role.

The Progenetix oncogenomic resource in 2021

In cancer, copy number aberrations (CNAs) represent a type of nearly ubiquitous and frequently extensive structural genome variations. To disentangle the molecular mechanisms underlying tumorigenesis as well as identify and characterize molecular subtypes, the comparative and meta-analysis of large genomic variant collections can be of immense importance. Over the last decades, cancer genomic profiling projects have resulted in a large amount of somatic genome variation profiles, however segregated in a multitude of individual studies and datasets. The Progenetix project, initiated in 2001, curates individual cancer CNA profiles and associated metadata from published oncogenomic studies and data repositories with the aim to empower integrative analyses spanning all different cancer biologies. During the last few years, the fields of genomics and cancer research have seen significant advancement in terms of molecular genetics technology, disease concepts, data standard harmonization as well as data availability, in an increasingly structured and systematic manner. For the Progenetix resource, continuous data integration, curation and maintenance have resulted in the most comprehensive representation of cancer genome CNA profiling data with 138 663 (including 115 357 tumor) copy number variation (CNV) profiles. In this article, we report a 4.5-fold increase in sample number since 2013, improvements in data quality, ontology representation with a CNV landscape summary over 51 distinctive National Cancer Institute Thesaurus cancer terms as well as updates in database schemas, and data access including new web front-end and programmatic data access. Database URL: progenetix.org.

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma

Somatic copy-number alterations (SCNAs) are major contributors to cancer development that are pervasive and highly heterogeneous in human cancers. However, the driver roles of SCNAs in cancer are insufficiently characterized. We combined network propagation and linear regression models to design an integrative strategy to identify driver SCNAs and dissect the functional roles of SCNAs by integrating profiles of copy number and gene expression in lower-grade glioma (LGG). We applied our strategy to 511 LGG patients and identified 98 driver genes that dysregulated 29 cancer hallmark signatures, forming 143 active gene-hallmark pairs. We found that these active gene-hallmark pairs could stratify LGG patients into four subtypes with significantly different survival times. The two new subtypes with similar poorest prognoses were driven by two different gene sets (one including EGFR, CDKN2A, CDKN2B, INFA8, and INFA5, and the other including CDK4, AVIL, and DTX3), respectively. The SCNAs of the two gene sets could disorder the same cancer hallmark signature in a mutually exclusive manner (including E2F_TARGETS and G2M_CHECKPOINT). Compared with previous methods, our strategy could not only capture the known cancer genes and directly dissect the functional roles of their SCNAs in LGG, but also discover the functions of new driver genes in LGG, such as IFNA5, IFNA8, and DTX3. Additionally, our method can be applied to a variety of cancer types to explore the pathogenesis of driver SCNAs and improve the treatment and diagnosis of cancer.

Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes

Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements. In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification.

Prostate Carcinogenesis: Insights in Relation to Epigenetics and Inflammation

Prostate cancer is a multifactorial disease that mainly occurs due to the accumulation of somatic, genetic, and epigenetic changes, resulting in the inactivation of tumor-suppressor genes and activation of oncogenes. Mutations in genes, specifically those that control cell growth and division or the repair of damaged DNA, make the cells grow and divide uncontrollably to form a tumor. The risk of developing prostate cancer depends upon the gene that has undergone the mutation. Identifying such genetic risk factors for prostate cancer poses a challenge for the researchers. Besides genetic mutations, many epigenetic alterations, including DNA methylation, histone modifications (methylation, acetylation, ubiquitylation, sumoylation, and phosphorylation) nucleosomal remodeling, and chromosomal looping, have significantly contributed to the onset of prostate cancer as well as the prognosis, diagnosis, and treatment of prostate cancer. Chronic inflammation also plays a major role in the onset and progression of human cancer, via modifications in the tumor microenvironment by initiating epithelialmesenchymal transition and remodeling the extracellular matrix. In this article, the authors present a brief history of the mechanisms and potential links between the genetic aberrations, epigenetic changes, inflammation, and inflammasomes that are known to contribute to the prognosis of prostate cancer. Furthermore, the authors examine and discuss the clinical potential of prostate carcinogenesis in relation to epigenetics and inflammation for its diagnosis and treatment..

Systematic analysis of enhancer regulatory circuit perturbation driven by copy number variations in malignant glioma

Background: Enhancers are emerging regulatory regions controlling gene expression in diverse cancer types. However, the functions of enhancer regulatory circuit perturbations driven by copy number variations (CNVs) in malignant glioma are unclear. Therefore, we aimed to investigate the comprehensive enhancer regulatory perturbation and identify potential biomarkers in glioma.

Results: We performed a meta-analysis of the enhancer centered regulatory circuit perturbations in 683 gliomas by integrating CNVs, gene expression, and transcription factors (TFs) binding. We found widespread CNVs of enhancers during glioma progression, and CNVs were associated with the perturbations of enhancer activities. In particular, the degree of perturbations for amplified enhancers was much greater accompanied by the glioma malignant progression. In addition, CNVs and enhancers cooperatively regulated the expressions of cancer-related genes. Genome-wide TF binding profiles revealed that enhancers were pervasively regulated by TFs. A network-based analysis of TF-enhancer-gene regulatory circuits revealed a core TF-gene module (58 interactions including seven genes and 14 TFs) that was associated survival of patients with glioma (p < 0.001). Finally, we validated this prognosis-associated TF-gene regulatory module in an independent cohort. In summary, our analyses provided new molecular insights for enhancer-centered transcriptional perturbation in glioma therapy.

Conclusion: Integrative analysis revealed enhancer regulatory perturbations in glioma and also identified a network module that was associated with patient survival, thereby providing novel insights into enhancer-centered cancer therapy.

Molecular Mechanisms of Colon Cancer Progression and Metastasis: Recent Insights and Advancements

Colorectal cancer (CRC), the third most common type of cancer, is the second leading cause of cancer-related mortality rates worldwide. Although modern research was able to shed light on the pathogenesis of CRC and provide enhanced screening strategies, the prevalence of CRC is still on the rise. Studies showed several cellular signaling pathways dysregulated in CRC, leading to the onset of malignant phenotypes. Therefore, analyzing signaling pathways involved in CRC metastasis is necessary to elucidate the underlying mechanism of CRC progression and pharmacotherapy. This review focused on target genes as well as various cellular signaling pathways including Wnt/β-catenin, p53, TGF-β/SMAD, NF-κB, Notch, VEGF, and JAKs/STAT3, which are associated with CRC progression and metastasis. Additionally, alternations in methylation patterns in relation with signaling pathways involved in regulating various cellular mechanisms such as cell cycle, transcription, apoptosis, and angiogenesis as well as invasion and metastasis were also reviewed. To date, understanding the genomic and epigenomic instability has identified candidate biomarkers that are validated for routine clinical use in CRC management. Nevertheless, better understanding of the onset and progression of CRC can aid in the development of early detection molecular markers and risk stratification methods to improve the clinical care of CRC patients.

DNA Copy Number Changes in Diffuse Large B Cell Lymphomas

Copy number aberrations (CNV/CNA) represent a major contribution to the somatic mutation landscapes in cancers, and their identification can lead to the discovery of oncogenetic targets as well as improved disease (sub-) classification. Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma in Western Countries and up to 40% of the affected individuals still succumb to the disease. DLBCL is an heterogenous group of disorders, and we call DLBCL today is not necessarily the same disease of a few years ago. This review focuses on types and frequencies of regional DNA CNVs in DLBCL, not otherwise specified, and in two particular conditions, the transformation from indolent lymphomas and the DLBCL in individuals with immunodeficiency.

The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While “High-Throughput” sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR’s recently established human CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

TOOme: A Novel Computational Framework to Infer Cancer Tissue-of-Origin by Integrating Both Gene Mutation and Expression

Metastatic cancers require further diagnosis to determine their primary tumor sites. However, the tissue-of-origin for around 5% tumors could not be identified by routine medical diagnosis according to a statistics in the United States. With the development of machine learning techniques and the accumulation of big cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), it is now feasible to predict cancer tissue-of-origin by computational tools. Metastatic tumor inherits characteristics from its tissue-of-origin, and both gene expression profile and somatic mutation have tissue specificity. Thus, we developed a computational framework to infer tumor tissue-of-origin by integrating both gene mutation and expression (TOOme). Specifically, we first perform feature selection on both gene expressions and mutations by a random forest method. The selected features are then used to build up a multi-label classification model to infer cancer tissue-of-origin. We adopt a few popular multiple-label classification methods, which are compared by the 10-fold cross validation process. We applied TOOme to the TCGA data containing 7,008 non-metastatic samples across 20 solid tumors. Seventy four genes by gene expression profile and six genes by gene mutation are selected by the random forest process, which can be divided into two categories: (1) cancer type specific genes and (2) those expressed or mutated in several cancers with different levels of expression or mutation rates. Function analysis indicates that the selected genes are significantly enriched in gland development, urogenital system development, hormone metabolic process, thyroid hormone generation prostate hormone generation and so on. According to the multiple-label classification method, random forest performs the best with a 10-fold cross-validation prediction accuracy of 96%. We also use the 19 metastatic samples from TCGA and 256 cancer samples downloaded from GEO as independent testing data, for which TOOme achieves a prediction accuracy of 89%. The cross-validation validation accuracy is better than those using gene expression (i.e., 95%) and gene mutation (53%) alone. In conclusion, TOOme provides a quick yet accurate alternative to traditional medical methods in inferring cancer tissue-of-origin. In addition, the methods combining somatic mutation and gene expressions outperform those using gene expression or mutation alone.

Minimum error calibration and normalization for genomic copy number analysis

BACKGROUND

Copy number variations (CNV) are regional deviations from the normal autosomal bi-allelic DNA content. While germline CNVs are a major contributor to genomic syndromes and inherited diseases, the majority of cancers accumulate extensive "somatic" CNV (sCNV or CNA) during the process of oncogenetic transformation and progression. While specific sCNV have closely been associated with tumorigenesis, intriguingly many neoplasias exhibit recurrent sCNV patterns beyond the involvement of a few cancer driver genes. Currently, CNV profiles of tumor samples are generated using genomic micro-arrays or high-throughput DNA sequencing. Regardless of the underlying technology, genomic copy number data is derived from the relative assessment and integration of multiple signals, with the data generation process being prone to contamination from several sources. Estimated copy number values have no absolute or strictly linear correlation to their corresponding DNA levels, and the extent of deviation differs between sample profiles, which poses a great challenge for data integration and comparison in large scale genome analysis.

RESULTS

In this study, we present a novel method named "Minimum Error Calibration and Normalization for Copy Numbers Analysis" (Mecan4CNA). It only requires CNV segmentation files as input, is platform independent, and has a high performance with limited hardware requirements. For a given multi-sample copy number dataset, Mecan4CNA can batch-normalize all samples to the corresponding true copy number levels of the main tumor clones. Experiments of Mecan4CNA on simulated data showed an overall accuracy of 93% and 91% in determining the normal level and single copy alteration (i.e. duplication or loss of one allele), respectively. Comparison of estimated normal levels and single copy alternations with existing methods and karyotyping data on the NCI-60 tumor cell line produced coherent results. To estimate the method's impact on downstream analyses, we performed GISTIC analyses on the original and Mecan4CNA normalized data from the Cancer Genome Atlas (TCGA) where the normalized data showed prominent improvements of both sensitivity and specificity in detecting focal regions.

CONCLUSIONS

Mecan4CNA provides an advanced method for CNA data normalization, especially in meta-analyses involving large profile numbers and heterogeneous source data quality. With its informative output and visualization options, Mecan4CNA also can improve the interpretation of individual CNA profiles. Mecan4CNA is freely available as a Python package and through its code repository on Github.

The Landscape of Somatic Copy Number Alterations in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide. Somatic copy number alterations (CNAs) play a significant role in the development of this lethal cancer. In this study, we present a meta-analysis of CNAs for a total of 1,395 HNSCC samples. Publicly available R packages and in-house scripts were used for genomic array data processing, including normalization, segmentation and CNA calling. We detected 125 regions of significant gains or losses using GISTIC algorithm and found several potential driver genes in these regions. The incidence of chromothripsis in HNSCC was estimated to be 6%, and the chromosome pulverization hotspot regions were detected. We determined 323 genomic locations significantly enriched for breakpoints, which indicate HNSCC-specific genomic instability regions. Unsupervised clustering of genome-wide CNA data revealed a sub-cluster predominantly composed of nasopharynx tumors and presented a large proportion of HPV-positive samples. These results will facilitate the discovery of therapeutic candidates and extend our molecular understanding of HNSCC.

Revisiting the Genomic and Transcriptomic Landscapes from Female Malignancies Could Provide Molecular Markers and Targets for Precision Medicine

AIMS

Gynaecological malignancies such as breast, ovarian and cervical cancers have become an important public health problem. Detection of molecular alterations in cancer research is fundamental since it can reveal specific pathogenic patterns and genes that could serve as markers. Our aim was to characterize common genomic and transcriptomic signatures for the three gynaecologic malignancies with the highest incidence and mortality to try to identify new molecular markers, therapeutic targets and molecular signatures.

METHODS

Here we analysed a total of 723 microarray libraries corresponding to equal number of breast, ovary and cervical cancer and non-cancer patient samples. Copy number variation (CNV) was carried out using 428 libraries and transcriptomic analysis using the 295 remaining samples.

RESULTS

Our results showed that breast, ovary and cervical malignancies are characterized by gain of 1q chromosome. At transcriptomic level, they share 351 coding and non-coding genes, which could represent core transcriptome of gynaecological malignancies. Pathway analysis from the resulting gene lists from CNV and expression showed participation in cell cycle, metabolism, and cell adhesion molecules among others.

CONCLUSIONS

Chromosome 1q characterize the gynaecological malignancies, which could harbour a richness of genetic repertoire to mine for molecular markers and targets, particular gynaecologic expression profile, containing FANCI, FH and MIR155HG among others, could represent part of the transcriptomic core for diagnostic test and attractive therapeutic targets. It may not be long before every human cancer sample is profiled for a detections test to ascertain a molecular diagnosis and prognosis and to define an optimal and precise treatment strategy.

Molecular analysis of V617F mutation in Janus kinase 2 gene of breast cancer patients

BACKGROUND

Breast cancer is a multifactorial disease with the highest frequency in females. Genetic and environmental factors can cause mutation in several genes like tyrosine kinase, JAK2 gene which may initiate cancer. Molecular analysis of mutations in the JAK2 gene along with determination of environmental, clinical and haematological risk factors associated with breast cancer patients is need of hour to improve patient's healthcare. Somatic JAK2 valine-to-phenylalanine (617 codon) mutation is one of the widely prevalent mutations.

METHODS

Blood was collected from seventy breast cancer patients after their consent. The questionnaire included risk factors, age group, locality, number of children, tumor type, family history, time of initial diagnosis, no of cycles/month, water conditions and exposure to radiations. Molecular analysis were carried out from genomic DNA using Sanger sequencing and allele-specific PCR to check the V617F point mutation.

RESULTS

The breast cancer risk factors includes unfiltered water (68.57%), urban (58.57%), menopause (55.71%), family history of cancer (18.57%), tumor grades (II, 37.14% and III, 35.71%), consanguineous marriages (44.28%) and having more than 3-4 children (45.71%). Prevalence of breast cancer was higher after the age of 35 and maximum at 35-50. In allele-specific PCR of 70 patients, 25 patients were wild type (229 bp), 25 patients were with partially deleted gene (200 bp), and 20 patient had shown no or less than 40 bp size fragments. In Sanger's sequencing of 70 BC cases, 18% were found to be positive for V617F point mutation, including 6 homozygous (T/T) and 7 heterozygous (G/T) mutations at nucleotide position 1849 in exon 14 of the JAK2 gene.

CONCLUSIONS

Environmental and clinical risk factors were associated with breast cancer which can be overcome by improving awareness of associated risks, health facilities and reducing stress.

Highly Multiplexed Fluorescence in Situ Hybridization for in Situ Genomics

The quantification of changes in gene copy number is critical to our understanding of tumor biology and for the clinical management of cancer patients. DNA fluorescence in situ hybridization is the gold standard method to detect copy number alterations, but it is limited by the number of genes one can quantify simultaneously. To increase the throughput of this informative technique, a fluorescent bar-code system for the unique labeling of dozens of genes and an automated image analysis algorithm that enabled their simultaneous hybridization for the quantification of gene copy numbers were devised. We demonstrate the reliability of this multiplex approach on normal human lymphocytes, metaphase spreads of transformed cell lines, and cultured circulating tumor cells. It also opens the door to the development of gene panels for more comprehensive analysis of copy number changes in tissue, including the study of heterogeneity and of high-throughput clinical assays that could provide rapid quantification of gene copy numbers in samples with limited cellularity, such as circulating tumor cells.

Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival

The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient's overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients' age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker.

Cancer type prediction based on copy number aberration and chromatin 3D structure with convolutional neural networks

BACKGROUND

With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which further contributes to more accurate somatic mutation based cancer typing (SMCT). In existing SMCT methods however, the absence of high-level feature extraction is a major obstacle in improving the classification performance.

RESULTS

We propose DeepCNA, an advanced convolutional neural network (CNN) based classifier, which utilizes copy number aberrations (CNAs) and HiC data, to address this issue. DeepCNA first pre-process the CNA data by clipping, zero padding and reshaping. Then, the processed data is fed into a CNN classifier, which extracts high-level features for accurate classification. Experimental results on the COSMIC CNA dataset indicate that 2D CNN with both cell lines of HiC data lead to the best performance. We further compare DeepCNA with three widely adopted classifiers, and demonstrate that DeepCNA has at least 78% improvement of performance.

CONCLUSIONS

This paper demonstrates the advantages and potential of the proposed DeepCNA model for processing of somatic point mutation based gene data, and proposes that its usage may be extended to other complex genotype-phenotype association studies.

Speciation Theory of Carcinogenesis Explains Karyotypic Individuality and Long Latencies of Cancers

It has been known for over 100 years that cancers have individual karyotypes and arise only years to decades after initiating carcinogens. However, there is still no coherent theory to explain these definitive characteristics of cancer. The prevailing mutation theory holds that cancers are late because the primary cell must accumulate 3–8 causative mutations to become carcinogenic and that mutations, which induce chromosomal instability (CIN), generate the individual karyotypes of cancers. However, since there is still no proven set of mutations that transforms a normal to a cancer cell, we have recently advanced the theory that carcinogenesis is a form of speciation. This theory predicts carcinogens initiate cancer by inducing aneuploidy, which automatically unbalances thousands of genes and thus catalyzes chain-reactions of progressive aneuploidizations. Over time, these aneuploidizations have two endpoints, either non-viable karyotypes or very rarely karyotypes of new autonomous and immortal cancers. Cancer karyotypes are immortalized despite destabilizing congenital aneuploidy by clonal selections for autonomy—similar to those of conventional species. This theory predicts that the very low probability of converting the karyotype of a normal cell to that of a new autonomous cancer species by random aneuploidizations is the reason for the karyotypic individuality of new cancers and for the long latencies from carcinogens to cancers. In testing this theory, we observed: (1) Addition of mutagenic and non-mutagenic carcinogens to normal human and rat cells generated progressive aneuploidizations months before neoplastic transformation. (2) Sub-cloning of a neoplastic rat clone revealed heritable individual karyotypes, rather than the non-heritable karyotypes predicted by the CIN theory. (3) Analyses of neoplastic and preneoplastic karyotypes unexpectedly identified karyotypes with sets of 3–12 new marker chromosomes without detectable intermediates, consistent with single-step origins. We conclude that the speciation theory explains logically the long latencies from carcinogen exposure and the individuality of cancers. In addition, the theory supports the single-step origins of cancers, because karyotypic autonomy is all-or-nothing. Accordingly, we propose that preneoplastic aneuploidy and clonal neoplastic karyotypes provide more reliable therapeutic indications than current analyses of thousands of mutations.

Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer

Functional redundancy shared by paralog genes may afford protection against genetic perturbations, but it can also result in genetic vulnerabilities due to mutual interdependency1-5. Here, we surveyed genome-scale short hairpin RNA and CRISPR screening data on hundreds of cancer cell lines and identified MAGOH and MAGOHB, core members of the splicing-dependent exon junction complex, as top-ranked paralog dependencies6-8. MAGOHB is the top gene dependency in cells with hemizygous MAGOH deletion, a pervasive genetic event that frequently occurs due to chromosome 1p loss. Inhibition of MAGOHB in a MAGOH-deleted context compromises viability by globally perturbing alternative splicing and RNA surveillance. Dependency on IPO13, an importin-β receptor that mediates nuclear import of the MAGOH/B-Y14 heterodimer9, is highly correlated with dependency on both MAGOH and MAGOHB. Both MAGOHB and IPO13 represent dependencies in murine xenografts with hemizygous MAGOH deletion. Our results identify MAGOH and MAGOHB as reciprocal paralog dependencies across cancer types and suggest a rationale for targeting the MAGOHB-IPO13 axis in cancers with chromosome 1p deletion.

The molecular characteristics of colorectal cancer: Implications for diagnosis and therapy

Colorectal cancer (CRC) results from the progressive accumulation of multiple genetic and epigenetic aberrations within cells. The progression from colorectal adenoma to carcinoma is caused by three major pathways: Microsatellite instability, chromosomal instability and CpG island methylator phenotype. A growing body of scientific evidences suggests that CRC is a heterogeneous disease, and genetic characteristics of the tumors determine their prognostic outcome and response to targeted therapies. Early diagnosis and effective targeted therapies based on a current knowledge of the molecular characteristics of CRC are essential to the successful treatment of CRC. Therefore, the present review summarized the current understanding of the molecular characteristics of CRC, and discussed its implications for diagnosis and targeted therapy.

Identification of copy number alterations in colon cancer from analysis of amplicon-based next generation sequencing data

The objective of this study was to determine the feasibility to detect copy number alterations in colon cancer samples using Next Generation Sequencing data and to elucidate the association between copy number alterations in specific genes and the development of cancer in different colon segments. We report the successful detection of somatic changes in gene copy number in 37 colon cancer patients by analysis of sequencing data through Amplicon CNA Algorithm. Overall, we have found a total of 748 significant copy number alterations in 230 significant genes, of which 143 showed CN losses and 87 showed CN gains. Validation of results was performed on 20 representative genes by quantitative qPCR and/or immunostaining. By this analysis, we have identified 4 genes that were subjected to copy number alterations in tumors arising in all colon segments (defined "common genes") and the presence of copy number alterations in 14 genes that were significantly associated to one specific site (defined "site-associated genes"). Finally, copy number alterations in ASXL1, TSC1 and IL7R turned out to be clinically relevant since the loss of TSC1 and IL7R was associated with advanced stages and/or reduced survival whereas copy number gain of ASXL1 was associated with good prognosis.

Somatic DNA Copy-Number Alterations Detection for Esophageal Adenocarcinoma Using Digital Polymerase Chain Reaction

Somatic copy-number alterations are commonly found in cancer and play key roles in activating oncogenes and deactivating tumor suppressor genes. Digital polymerase chain reaction is an effective way to detect the changes in copy number. In esophageal adenocarcinoma, detection of somatic copy-number alterations could predict the prognosis of patients as well as the response to therapy. This chapter will review the methods involved in digital polymerase chain reaction for the research or potential clinical applications in esophageal adenocarcinoma.

Evidence for a pre-malignant cell line in a skin biopsy from a patient with Nijmegen breakage syndrome

Background

Nijmegen breakage syndrome is an autosomal recessive disorder characterized by microcephaly, immunodeficiency, hypersensitivity to X-irradiation, and a high predisposition to cancer. Nibrin, the product of the NBN gene, is part of the MRE11/RAD50 (MRN) complex that is involved in the repair of DNA double strand breaks (DSBs), and plays a critical role in the processing of DSBs in immune gene rearrangements, telomere maintenance, and meiotic recombination. NBS skin fibroblasts grow slowly in culture and enter early into senescence.

Case presentation

Here we present an incidental finding. Skin fibroblasts, derived from a 9 year old NBS patient, showed a mosaic of normal diploid cells (46,XY) and those with a complex, unbalanced translocation. The aberrant karyotype was analysed by G-banding, comparative genomic hybridization, and whole chromosome painting. The exact breakpoints of the derivative chromosome were mapped by whole genome sequencing: 45,XY,der(6)(6pter → 6q11.1::13q11 → 13q21.33::20q11.22 → 20qter),-13. The deleted region of chromosomes 6 harbors almost 1.400 and that of chromosome 13 more than 500 genes, the duplicated region of chromosome 20 contains about 700 genes. Such unbalanced translocations are regularly incompatible with cellular survival, except in malignant cells. The aberrant cells, however, showed a high proliferation potential and could even be clonally expanded. Telomere length was significantly reduced, hTERT was not expressed. The cells underwent about 50 population doublings until they entered into senescence. The chromosomal preparation performed shortly before senescence showed telomere fusions, premature centromere divisions, endoreduplications and tetraploid cells, isochromatid breaks and a variety of marker chromosomes. Inspection of the site of skin biopsy 18 years later, presented no evidence for abnormal growth.

Conclusions

The aberrant cells had a significant selective advantage in vitro. It is therefore tempting to speculate that this highly unbalanced translocation could be a primary driver of cancer cell growth.

Electronic supplementary material

The online version of this article (10.1186/s13039-018-0364-6) contains supplementary material, which is available to authorized users.

Recurrent copy number alterations in young women with breast cancer

Breast cancer diagnosis in young women has emerged as an independent prognostic factor with higher recurrence risk and death than their older counterparts. We aim to find recurrent somatic copy number alteration (CNA) regions identified from breast cancer microarray data and associate the CNA status of the genes harbored in the regions to the survival of young women with breast cancer.

By using the interval graph-based algorithm we developed, and the CNA data consisting of a Discovery set with 130 young women and a Validation set with 125 young women, we identified 38 validated recurrent CNAs containing 39 protein encoding genes. CNA gain regions encompassing genes CAPN2, CDC73 and ASB13 are the top 3 with the highest occurring frequencies in both the Discovery and Validation dataset, while gene SGCZ ranked top for the recurrent CNA loss regions. The mutation status of 9 of the 39 genes shows significant associations with breast cancer specific survival. Interestingly, the expression level of 2 of the 9 genes, ASB13 and SGCZ, shows significant association with survival outcome. Patients with CNA mutations in both of these genes had a worse survival outcome when compared to patients without the gene mutations. The mutated CNA status in gene ASB13 was associated with a higher gene expression, which predicted patient survival outcome. Together, identification of the CNA events with prognostic significance in young women with breast cancer may be used in genomic-guided treatment.

Breast Cancer Molecular Stratification: From Intrinsic Subtypes to Integrative Clusters

Breast carcinomas can be stratified into different entities based on clinical behavior, histologic features, and/or by biological properties. A classification of breast cancer should be based on underlying biology, which we know must be determined by the somatic genomic landscape of mutations. Moreover, because the latest generations of anticancer agents are founded on biological mechanisms, a detailed molecular stratification is a requirement for appropriate clinical management. Such stratification, based on genomic drivers, will be important for selecting patients for clinical trials. It will also facilitate the discovery of novel drivers, the study of tumor evolution, and the identification of mechanisms of treatment resistance. Assays for risk stratification have focused mainly on response prediction to existing treatment regimens. Molecular stratification based on gene expression profiling revealed that breast cancers could be classified in so-called intrinsic subtypes (luminal A and B, HER2-enriched, basal-like, and normal-like), which mostly corresponded to hormone receptor and HER2 status, and further stratified luminal tumors based on proliferation. The realization that a significant proportion of the gene expression landscape is determined by the somatic copy number alterations that drive expression in cis led to the newer classification of breast cancers into integrative clusters. This stratification of breast cancers into integrative clusters reveals prototypical patterns of single-nucleotide variants and is associated with distinct clinical courses and response to therapy.

DNA copy number changes define spatial patterns of heterogeneity in colorectal cancer

Genetic heterogeneity between and within tumours is a major factor determining cancer progression and therapy response. Here we examined DNA sequence and DNA copy-number heterogeneity in colorectal cancer (CRC) by targeted high-depth sequencing of 100 most frequently altered genes. In 97 samples, with primary tumours and matched metastases from 27 patients, we observe inter-tumour concordance for coding mutations; in contrast, gene copy numbers are highly discordant between primary tumours and metastases as validated by fluorescent in situ hybridization. To further investigate intra-tumour heterogeneity, we dissected a single tumour into 68 spatially defined samples and sequenced them separately. We identify evenly distributed coding mutations in APC and TP53 in all tumour areas, yet highly variable gene copy numbers in numerous genes. 3D morpho-molecular reconstruction reveals two clusters with divergent copy number aberrations along the proximal-distal axis indicating that DNA copy number variations are a major source of tumour heterogeneity in CRC.

Analysis of gene copy number changes in tumor phylogenetics

BACKGOUND

Evolution of cancer cells is characterized by large scale and rapid changes in the chromosomal  landscape. The fluorescence in situ hybridization (FISH) technique provides a way to measure the copy numbers of preselected genes in a group of cells and has been found to be a reliable source of data to model the evolution of tumor cells. Chowdhury et al. (Bioinformatics 29(13):189-98, 23; PLoS Comput Biol 10(7):1003740, 24) recently develop a computational model for tumor progression driven by gains and losses in cell count patterns obtained by FISH probes. Their model aims to find the rectilinear Steiner minimum tree (RSMT) (Chowdhury et al. in Bioinformatics 29(13):189-98, 23) and the duplication Steiner minimum tree (DSMT) (Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) that describe the progression of FISH cell count patterns over its branches in a parsimonious manner. Both the RSMT and DSMT problems are NP-hard and heuristics are required to solve the problems efficiently.

METHODS

In this paper we propose two approaches to solve the RSMT problem, one inspired by iterative methods to address the "small phylogeny" problem (Sankoff et al. in J Mol Evol 7(2):133-49, 27; Blanchette et al. in Genome Inform 8:25-34, 28), and the other based on maximum parsimony phylogeny inference. We further show how to extend these heuristics to obtain solutions to the DSMT problem, that models large scale duplication events.

RESULTS

Experimental results from both simulated and real tumor data show that our methods outperform previous heuristics (Chowdhury et al. in Bioinformatics 29(13):189-98, 23; Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) in obtaining solutions to both RSMT and DSMT problems.

CONCLUSION

The methods introduced here are able to provide more parsimony phylogenies compared to earlier ones which are consider better choices.

ABO blood groups in relation to breast carcinoma incidence and associated prognostic factors in Moroccan women

The association between blood groups ABO and different types of diseases was established in several previous studies. Our aim was to seek the possible association between the ABO blood group and breast cancer-associated prognostic factors. The Chi-squared analytic test was used to compare phenotypic ABO distribution among Moroccan blood donors and 442 cases of women suffering from breast carcinoma with archived files in Maternity Ward of University Hospital C.H.U Ibn Rochd between 2008 and 2011. High incidence of breast carcinoma was observed in blood type B patients (p < 0.05). Blood type B was associated with breast carcinomas overexpressing human epidermal growth factor receptor HER2 (p < 0.05) and high risk of cancer at age over 70 years (p < 0.001). Blood type A was associated with high risk of cancer among women younger than 35 years old. Blood type A and AB were associated with high incidence of lymph node metastasis (p < 0.05). Multivariate analysis has shown correlation between O blood type and estrogen receptor-positive tumor. Patients with blood group A, B, and AB were more likely to develop aggressive breast carcinoma. Further follow-up studies are necessary to clarify the role of ABH antigens in the progression of breast carcinoma.

Integrated Genomics for Pinpointing Survival Loci within Arm-Level Somatic Copy Number Alterations

The identification of driver loci underlying arm-level somatic copy number alterations (SCNAs) in cancer has remained challenging and incomplete. Here, we assess the relative impact and present a detailed landscape of arm-level SCNAs in 10,985 patient samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Furthermore, using chromosome 9p loss in lower grade glioma (LGG) as a model, we employ a unique multi-tiered genomic dissection strategy using 540 patients from three independent LGG datasets to identify genetic loci that govern tumor aggressiveness and poor survival. This comprehensive approach uncovered several 9p loss-specific prognostic markers, validated existing ones, and redefined the impact of CDKN2A loss in LGG.

Molecular classification of gastric cancer

Gastric cancer (GC), a heterogeneous disease characterized by epidemiologic and histopathologic differences across countries, is a leading cause of cancer-related death. Treatment of GC patients is currently suboptimal due to patients being commonly treated in a uniform fashion irrespective of disease subtype. With the advent of next-generation sequencing and other genomic technologies, GCs are now being investigated in great detail at the molecular level. High-throughput technologies now allow a comprehensive study of genomic and epigenomic alterations associated with GC. Gene mutations, chromosomal aberrations, differential gene expression and epigenetic alterations are some of the genetic/epigenetic influences on GC pathogenesis. In addition, integrative analyses of molecular profiling data have led to the identification of key dysregulated pathways and importantly, the establishment of GC molecular classifiers. Recently, The Cancer Genome Atlas (TCGA) network proposed a four subtype classification scheme for GC based on the underlying tumor molecular biology of each subtype. This landmark study, together with other studies, has expanded our understanding on the characteristics of GC at the molecular level. Such knowledge may improve the medical management of GC in the future.

Abundant copy-number loss of CYCLOPS and STOP genes in gastric adenocarcinoma

BACKGROUND

Gastric cancer, a leading cause of cancer death worldwide, has been little studied compared with other cancers that impose similar health burdens. Our goal is to assess genomic copy-number loss and the possible functional consequences and therapeutic implications thereof across a large series of gastric adenocarcinomas.

METHODS

We used high-density single-nucleotide polymorphism microarrays to determine patterns of copy-number loss and allelic imbalance in 74 gastric adenocarcinomas. We investigated whether suppressor of tumorigenesis and/or proliferation (STOP) genes are associated with genomic copy-number loss. We also analyzed the extent to which copy-number loss affects Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS (CYCLOPS) genes-genes that may be attractive targets for therapeutic inhibition when partially deleted.

RESULTS

The proportion of the genome subject to copy-number loss varies considerably from tumor to tumor, with a median of 5.5 %, and a mean of 12 % (range 0-58.5 %). On average, 91 STOP genes were subject to copy-number loss per tumor (median 35, range 0-452), and STOP genes tended to have lower copy-number compared with the rest of the genes. Furthermore, on average, 1.6 CYCLOPS genes per tumor were both subject to copy-number loss and downregulated, and 51.4 % of the tumors had at least one such gene.

CONCLUSIONS

The enrichment of STOP genes in regions of copy-number loss indicates that their deletion may contribute to gastric carcinogenesis. Furthermore, the presence of several deleted and downregulated CYCLOPS genes in some tumors suggests potential therapeutic targets in these tumors.

TumorTracer: a method to identify the tissue of origin from the somatic mutations of a tumor specimen

BACKGROUND

A substantial proportion of cancer cases present with a metastatic tumor and require further testing to determine the primary site; many of these are never fully diagnosed and remain cancer of unknown primary origin (CUP). It has been previously demonstrated that the somatic point mutations detected in a tumor can be used to identify its site of origin with limited accuracy. We hypothesized that higher accuracy could be achieved by a classification algorithm based on the following feature sets: 1) the number of nonsynonymous point mutations in a set of 232 specific cancer-associated genes, 2) frequencies of the 96 classes of single-nucleotide substitution determined by the flanking bases, and 3) copy number profiles, if available.

METHODS

We used publicly available somatic mutation data from the COSMIC database to train random forest classifiers to distinguish among those tissues of origin for which sufficient data was available. We selected feature sets using cross-validation and then derived two final classifiers (with or without copy number profiles) using 80 % of the available tumors. We evaluated the accuracy using the remaining 20 %. For further validation, we assessed accuracy of the without-copy-number classifier on three independent data sets: 1669 newly available public tumors of various types, a cohort of 91 breast metastases, and a set of 24 specimens from 9 lung cancer patients subjected to multiregion sequencing.

RESULTS

The cross-validation accuracy was highest when all three types of information were used. On the left-out COSMIC data not used for training, we achieved a classification accuracy of 85 % across 6 primary sites (with copy numbers), and 69 % across 10 primary sites (without copy numbers). Importantly, a derived confidence score could distinguish tumors that could be identified with 95 % accuracy (32 %/75 % of tumors with/without copy numbers) from those that were less certain. Accuracy in the independent data sets was 46 %, 53 % and 89 % respectively, similar to the accuracy expected from the training data.

CONCLUSIONS

Identification of primary site from point mutation and/or copy number data may be accurate enough to aid clinical diagnosis of cancers of unknown primary origin.

Duplex Ratio Tests as Diagnostic Biomarkers in Malignant Melanoma

Chromosomal instability is a well-described feature of malignant tumors. Melanomas have typical patterns of chromosomal instability compared with benign nevi, which have minimal DNA copy number change. A few malignant melanomas and their benign counterparts, nevi, prove difficult to diagnose on histopathologic analysis alone, which is currently the gold standard. Quantitative PCR-based assays called duplex ratio tests (DRTs) have been developed by our laboratory for application using DNA from FFPE samples of melanomas and nevi. The reproducibility and accuracy of the DRTs were demonstrated and appropriate correction factors for DNA quality calculated for each assay, based on the results of 108 diploid samples. As a panel, seven DRTs were able to differentiate unambiguous cases of melanoma and nevi with a sensitivity of 87% (95% CI, 83%-91%) and a specificity of 88% (95% CI, 84%-92%) in a series of 145 melanomas and 123 nevi. The DRT scores for 20 nonmetastasizing primary melanomas and 20 metastasizing primary melanomas revealed that DRTs had a marginal benefit as prognostic markers. DRTs have early potential to act as molecular biomarkers of melanoma on FFPE specimens pending validation, and DRTs may have applicability as prognostic markers in melanoma or other tumor types if new DRTs to relevant loci are developed.

Genotype and Haplotype Analyses of TP53 Gene in Breast Cancer Patients: Association with Risk and Clinical Outcomes

Variations in the TP53 gene have been suggested to play a role in many cancers, including breast. We previously observed an association between TP53 haplotypes based on four polymorphisms (rs17878362, rs1042522, rs12947788, and rs17884306) and the risk of colorectal and pancreatic cancer. Based on these results, in the present study, we have investigated the same polymorphisms and their haplotypes in 705 breast cancer cases and 611 healthy controls in relation to the disease risk, histopathological features of the tumor and clinical outcomes. In comparison to the most common haplotype A₁-G-C-G, all the other identified haplotypes were globally associated with a significantly decreased breast cancer risk (P = 0.006). In particular, the A₂-G-C-G haplotype was associated with a marked decreased risk of breast cancer when compared with the common haplotype (P = 0.0001). Moreover, rs1042522 in patients carrying the GC genotype and receiving only the anthracycline-based chemotherapy was associated with both overall and disease-free survival (recessive model for overall survival HR = 0.30 95% CI 0.11–0.80, P = 0.02 and for disease-free survival HR = 0.42 95% CI 0.21–0.84, P = 0.01). Present results suggest common genetic features in the susceptibility to breast and gastrointestinal cancers in respect to TP53 variations. In fact, similar haplotype distributions were observed for breast, colorectal, and pancreatic patients in associations with cancer risk. Rs1042522 polymorphism (even after applying the Dunn-Bonferroni correction for multiple testing) appears to be an independent prognostic marker in breast cancer patients.

Comparison of structural genetics of non-schistosoma-associated squamous cell carcinoma of the urinary bladder

Little is known about genetic changes in squamous differentiation of non-schistosomiasis-associated bladder cancer. Therefore, we investigated pure squamous cell carcinomas (SqCC), squamous parts of mixed urothelial carcinomas with squamous differentiation (MIX) and mere urothelial cancers (UC) for structural genetic differences. Tissue microarray slides (n = 29 SqCC, n = 35 MIX and n = 23 UC) were analyzed by ZytoLight SPEC p16/CEN3/7/17 Quadruple Color Probe fluorescence-in-situ-hybridization (FISH) and DNA was investigated by comparative genomic hybridization (CGH) (n = 35 SqCCs, n = 40 MIX and n = 36 UC). By FISH the mean number of polysomic cells was lowest in SqCC (CEN3 P = 0.0498, CEN17 P = 0.0009). A slight tendency of lower copy numbers of chromosomes 3, 7 and 17 and higher numbers of the p16-locus in SqCC (P = 0.45) indicated less aneuploid tumor cells in SqCC compared to MIX and UC. In CGH SqCC showed the lowest mean number of aberrations per tumor (SqCC 5.37 changes, MIX 6.75 and UC 7.64; P = 0.1754). Significant differences between the three groups were found for loss of chromosome 3p (P = 0.004), 6q (P = 0.028), 11p (P = 0.024) and gains of 5p (P = 0.020). Loss of 3p was more frequent in SqCC (51.4%) than in MIX (37.5%) or UC (13.9%). To conclude, SqCCs show less polysomy and genetic alterations than MIX and UC. Loss of 3p is more frequent in SqCC but there are no absolute specific alterations for each tumor group. Squamous parts of mixed tumors show similar alterations than UC and should be considered as further development of UC, while pure SqCC seem to be a separate tumor group.

The fitness consequences of aneuploidy are driven by condition-dependent gene effects

Aneuploidy is a hallmark of tumor cells, and yet the precise relationship between aneuploidy and a cell's proliferative ability, or cellular fitness, has remained elusive. In this study, we have combined a detailed analysis of aneuploid clones isolated from laboratory-evolved populations of Saccharomyces cerevisiae with a systematic, genome-wide screen for the fitness effects of telomeric amplifications to address the relationship between aneuploidy and cellular fitness. We found that aneuploid clones rise to high population frequencies in nutrient-limited evolution experiments and show increased fitness relative to wild type. Direct competition experiments confirmed that three out of four aneuploid events isolated from evolved populations were themselves sufficient to improve fitness. To expand the scope beyond this small number of exemplars, we created a genome-wide collection of >1,800 diploid yeast strains, each containing a different telomeric amplicon (Tamp), ranging in size from 0.4 to 1,000 kb. Using pooled competition experiments in nutrient-limited chemostats followed by high-throughput sequencing of strain-identifying barcodes, we determined the fitness effects of these >1,800 Tamps under three different conditions. Our data revealed that the fitness landscape explored by telomeric amplifications is much broader than that explored by single-gene amplifications. As also observed in the evolved clones, we found the fitness effects of most Tamps to be condition specific, with a minority showing common effects in all three conditions. By integrating our data with previous work that examined the fitness effects of single-gene amplifications genome-wide, we found that a small number of genes within each Tamp are centrally responsible for each Tamp's fitness effects. Our genome-wide Tamp screen confirmed that telomeric amplifications identified in laboratory-evolved populations generally increased fitness. Our results show that Tamps are mutations that produce large, typically condition-dependent changes in fitness that are important drivers of increased fitness in asexually evolving populations.

Single nucleotide polymorphism array profiling identifies distinct chromosomal aberration patterns across colorectal adenomas and carcinomas

The progression of benign colorectal adenomas into cancer is associated with the accumulation of chromosomal aberrations. Even though patterns and frequencies of chromosomal aberrations have been well established in colorectal carcinomas, corresponding patterns of aberrations in adenomas are less well documented. The aim of this study was to profile chromosomal aberrations across colorectal adenomas and carcinomas to provide a better insight into key changes during tumor initiation and progression. Single nucleotide polymorphism array analysis was performed on 216 colorectal tumor/normal matched pairs, comprising 60 adenomas and 156 carcinomas. While many chromosomal aberrations were specific to carcinomas, those with the highest frequency in carcinomas (amplification of chromosome 7, 13q, and 20q; deletion of 17p and chromosome 18; LOH of 1p, chromosome 4, 5q, 8p, 17p, chromosome 18, and 20p) were also identified in adenomas. Hierarchical clustering using chromosomal aberrations revealed three distinct subtypes. Interestingly, these subtypes were only partially dependent on tumor staging. A cluster of colorectal cancer patients with frequent chromosomal deletions had the least favorable prognosis, and a number of adenomas (n = 9) were also present in the cluster suggesting that, at least in some tumors, the chromosomal aberration pattern is determined at a very early stage of tumor formation. Finally, analysis of LOH events revealed that copy-neutral/gain LOH (CN/G-LOH) is frequent (>10%) in carcinomas at 5q, 11q, 15q, 17p, chromosome 18, 20p, and 22q. Deletion of the corresponding region is sometimes present in adenomas, suggesting that LOH at these loci may play an important role in tumor initiation.

Computational characterisation of cancer molecular profiles derived using next generation sequencing

Our current understanding of cancer genetics is grounded on the principle that cancer arises from a clone that has accumulated the requisite somatically acquired genetic aberrations, leading to the malignant transformation. It also results in aberrent of gene and protein expression. Next generation sequencing (NGS) or deep sequencing platforms are being used to create large catalogues of changes in copy numbers, mutations, structural variations, gene fusions, gene expression, and other types of information for cancer patients. However, inferring different types of biological changes from raw reads generated using the sequencing experiments is algorithmically and computationally challenging. In this article, we outline common steps for the quality control and processing of NGS data. We highlight the importance of accurate and application-specific alignment of these reads and the methodological steps and challenges in obtaining different types of information. We comment on the importance of integrating these data and building infrastructure to analyse it. We also provide exhaustive lists of available software to obtain information and point the readers to articles comparing software for deeper insight in specialised areas. We hope that the article will guide readers in choosing the right tools for analysing oncogenomic datasets.

arrayMap 2014: an updated cancer genome resource

Somatic copy number aberrations (CNA) represent a mutation type encountered in the majority of cancer genomes. Here, we present the 2014 edition of arrayMap (http://www.arraymap.org), a publicly accessible collection of pre-processed oncogenomic array data sets and CNA profiles, representing a vast range of human malignancies. Since the initial release, we have enhanced this resource both in content and especially with regard to data mining support. The 2014 release of arrayMap contains more than 64 000 genomic array data sets, representing about 250 tumor diagnoses. Data sets included in arrayMap have been assembled from public repositories as well as additional resources, and integrated by applying custom processing pipelines. Online tools have been upgraded for a more flexible array data visualization, including options for processing user provided, non-public data sets. Data integration has been improved by mapping to multiple editions of the human reference genome, with the majority of the data now being available for the UCSC hg18 as well as GRCh37 versions. The large amount of tumor CNA data in arrayMap can be freely downloaded by users to promote data mining projects, and to explore special events such as chromothripsis-like genome patterns.

CLPTM1L promotes growth and enhances aneuploidy in pancreatic cancer cells

Genome-wide association studies (GWAS) of 10 different cancers have identified pleiotropic cancer predisposition loci across a region of chromosome 5p15.33 that includes the TERT and CLPTM1L genes. Of these, susceptibility alleles for pancreatic cancer have mapped to the CLPTM1L gene, thus prompting an investigation of the function of CLPTM1L in the pancreas. Immunofluorescence analysis indicated that CLPTM1L localized to the endoplasmic reticulum where it is likely embedded in the membrane, in accord with multiple predicted transmembrane domains. Overexpression of CLPTM1L enhanced growth of pancreatic cancer cells in vitro (1.3-1.5-fold; PDAY7 < 0.003) and in vivo (3.46-fold; PDAY68 = 0.039), suggesting a role in tumor growth; this effect was abrogated by deletion of two hydrophilic domains. Affinity purification followed by mass spectrometry identified an interaction between CLPTM1L and non-muscle myosin II (NMM-II), a protein involved in maintaining cell shape, migration, and cytokinesis. The two proteins colocalized in the cytoplasm and, after treatment with a DNA-damaging agent, at the centrosomes. Overexpression of CLPTM1L and depletion of NMM-II induced aneuploidy, indicating that CLPTM1L may interfere with normal NMM-II function in regulating cytokinesis. Immunohistochemical analysis revealed enhanced staining of CLPTM1L in human pancreatic ductal adenocarcinoma (n = 378) as compared with normal pancreatic tissue samples (n = 17; P = 1.7 × 10(-4)). Our results suggest that CLPTM1L functions as a growth-promoting gene in the pancreas and that overexpression may lead to an abrogation of normal cytokinesis, indicating that it should be considered as a plausible candidate gene that could explain the effect of pancreatic cancer susceptibility alleles on chr5p15.33.

Classification of non-small cell lung cancer based on copy number alterations

Lung cancer is one of the leading causes of cancer mortality worldwide and non–small cell lung cancer (NSCLC) accounts for the most part. NSCLC can be further divided into adenocarcinoma (ACA) and squamous cell carcinoma (SCC). It is of great value to distinguish these two subgroups clinically. In this study, we compared the genome-wide copy number alterations (CNAs) patterns of 208 early stage ACA and 93 early stage SCC tumor samples. As a result, 266 CNA probes stood out for better discrimination of ACA and SCC. It was revealed that the genes corresponding to these 266 probes were enriched in lung cancer related pathways and enriched in the chromosome regions where CNA usually occur in lung cancer. This study sheds lights on the CNA study of NSCLC and provides some insights on the epigenetic of NSCLC.

Chromothripsis-like patterns are recurring but heterogeneously distributed features in a survey of 22,347 cancer genome screens

Background

Chromothripsis is a recently discovered phenomenon of genomic rearrangement, possibly arising during a single genome-shattering event. This could provide an alternative paradigm in cancer development, replacing the gradual accumulation of genomic changes with a “one-off” catastrophic event. However, the term has been used with varying operational definitions, with the minimal consensus being a large number of locally clustered copy number aberrations. The mechanisms underlying these chromothripsis-like patterns (CTLP) and their specific impact on tumorigenesis are still poorly understood.

Results

Here, we identified CTLP in 918 cancer samples, from a dataset of more than 22,000 oncogenomic arrays covering 132 cancer types. Fragmentation hotspots were found to be located on chromosome 8, 11, 12 and 17. Among the various cancer types, soft-tissue tumors exhibited particularly high CTLP frequencies. Genomic context analysis revealed that CTLP rearrangements frequently occurred in genomes that additionally harbored multiple copy number aberrations (CNAs). An investigation into the affected chromosomal regions showed a large proportion of arm-level pulverization and telomere related events, which would be compatible to a number of underlying mechanisms. We also report evidence that these genomic events may be correlated with patient age, stage and survival rate.

Conclusions

Through a large-scale analysis of oncogenomic array data sets, this study characterized features associated with genomic aberrations patterns, compatible to the spectrum of “chromothripsis”-definitions as previously used. While quantifying clustered genomic copy number aberrations in cancer samples, our data indicates an underlying biological heterogeneity behind these chromothripsis-like patterns, beyond a well defined “chromthripsis” phenomenon.