Functional genomic analysis of chromosomal aberrations in a compendium of 8000 cancer genomes

Chromosome 7 to the rescue: overcoming chromosome 10 loss in gliomas

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

Classification of tumor types using XGBoost machine learning model: a vector space transformation of genomic alterations

BACKGROUND

Machine learning (ML) represents a powerful tool to capture relationships between molecular alterations and cancer types and to extract biological information. Here, we developed a plain ML model aimed at distinguishing cancer types based on genetic lesions, providing an additional tool to improve cancer diagnosis, particularly for tumors of unknown origin.

METHODS

TCGA data from 9,927 samples spanning 32 different cancer types were downloaded from cBioportal. A vector space model type data transformation technique was designed to build consistently homogeneous new datasets containing, as predictive features, calls for somatic point mutations and copy number variations at chromosome arm-level, thus allowing the use of the XGBoost classifier models. Considering the imbalance in the dataset, due to large difference in the number of cases for each tumor, two preprocessing strategies were considered: i) setting a percentage cut-off threshold to remove less represented cancer types, ii) dividing cancer types into different groups based on biological criteria and training a specific XGBoost model for each of them. The performance of all trained models was mainly assessed by the out-of-sample balanced accuracy (BACC) and the AUC scores.

RESULTS

The XGBoost classifier achieved the best performance (BACC 77%; AUC 97%) on a dataset containing the 10 most represented tumor types. Moreover, dividing the 18 most represented cancers into three different groups (endocrine-related carcinomas, other carcinomas and other cancers),such analysis models achieved 78%, 71% and 86% BACC, respectively, with AUC scores greater than 96%. In addition, the model capable of linking each group to a specific cancer type reached 81% BACC and 94% AUC. Overall, the diagnostic potential of our model was comparable/higher with respect to others already described in literature and based on similar molecular data and ML approaches.

CONCLUSIONS

A boosted ML approach able to accurately discriminate different cancer types was developed. The methodology builds datasets simpler and more interpretable than the original data, while keeping enough information to accurately train standard ML models without resorting to sophisticated Deep Learning architectures. In combination with histopathological examinations, this approach could improve cancer diagnosis by using specific DNA alterations, processed by a replicable and easy-to-use automated technology. The study encourages new investigations which could further increase the classifier's performance, for example by considering more features and dividing tumors into their main molecular subtypes.

Centromere: A Trojan horse for genome stability

Centromeres play a key role in the maintenance of genome stability to prevent carcinogenesis and diseases. They are specialized chromosome loci essential to ensure faithful transmission of genomic information across cell generations by mediating the interaction with spindle microtubules. Nonetheless, while fulfilling these essential roles, their distinct repetitive composition and susceptibility to mechanical stresses during cell division render them susceptible to breakage events. In this review, we delve into the present understanding of the underlying causes of centromere fragility, from the mechanisms governing its DNA replication and repair, to the pathways acting to counteract potential challenges. We propose that the centromere represents a "Trojan horse" exerting vital functions that, at the same time, potentially threatens whole genome stability.

Condition-dependent fitness effects of large synthetic chromosome amplifications

Whole-chromosome aneuploidy and large segmental amplifications can have devastating effects in multicellular organisms, from developmental disorders and miscarriage to cancer. Aneuploidy in single-celled organisms such as yeast also results in proliferative defects and reduced viability. Yet, paradoxically, CNVs are routinely observed in laboratory evolution experiments with microbes grown in stressful conditions. The defects associated with aneuploidy are often attributed to the imbalance of many differentially expressed genes on the affected chromosomes, with many genes each contributing incremental effects. An alternate hypothesis is that a small number of individual genes are large effect 'drivers' of these fitness changes when present in an altered copy number. To test these two views, we have employed a collection of strains bearing large chromosomal amplifications that we previously assayed in nutrient-limited chemostat competitions. In this study, we focus on conditions known to be poorly tolerated by aneuploid yeast-high temperature, treatment with the Hsp90 inhibitor radicicol, and growth in extended stationary phase. To identify potential genes with a large impact on fitness, we fit a piecewise constant model to fitness data across chromosome arms, filtering breakpoints in this model by magnitude to focus on regions with a large impact on fitness in each condition. While fitness generally decreased as the length of the amplification increased, we were able to identify 91 candidate regions that disproportionately impacted fitness when amplified. Consistent with our previous work with this strain collection, nearly all candidate regions were condition specific, with only five regions impacting fitness in multiple conditions.

The Scarface Score: Deciphering Response to DNA Damage Agents in High-Grade Serous Ovarian Cancer-A GEICO Study

Genomic Instability (GI) is a transversal phenomenon shared by several tumor types that provide both prognostic and predictive information. In the context of high-grade serous ovarian cancer (HGSOC), response to DNA-damaging agents such as platinum-based and poly(ADP-ribose) polymerase inhibitors (PARPi) has been closely linked to deficiencies in the DNA repair machinery by homologous recombination repair (HRR) and GI. In this study, we have developed the Scarface score, an integrative algorithm based on genomic and transcriptomic data obtained from the NGS analysis of a prospective GEICO cohort of 190 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients diagnosed with HGSOC with a median follow up of 31.03 months (5.87-159.27 months). In the first step, three single-source models, including the SNP-based model (accuracy = 0.8077), analyzing 8 SNPs distributed along the genome; the GI-based model (accuracy = 0.9038) interrogating 28 parameters of GI; and the HTG-based model (accuracy = 0.8077), evaluating the expression of 7 genes related with tumor biology; were proved to predict response. Then, an ensemble model called the Scarface score was found to predict response to DNA-damaging agents with an accuracy of 0.9615 and a kappa index of 0.9128 (p < 0.0001). The Scarface Score approaches the routine establishment of GI in the clinical setting, enabling its incorporation as a predictive and prognostic tool in the management of HGSOC.

Pan-cancer investigation of psoriasis-related BUB1B gene: genetical alteration and oncogenic immunology

Unknown factors contribute to psoriasis' hyperproliferative, chronic, inflammatory, and arthritic features. Psoriasis patients have been linked to an increased risk of cancer, though the underlying genetics remain unknown. Since our prior research indicated that BUB1B contributes to the development of psoriasis, we designed and carried out this investigation using bioinformatics analysis. Using the TCGA database, we investigated the oncogenic function of BUB1B in 33 tumor types. To sum up, our work sheds light on BUB1B's function in pan-cancer from various perspectives, including its pertinent signaling pathways, mutation locations, and connection to immune cell infiltration. BUB1B was shown to have a non-negligible role in pan-cancer, which is connected to immunology, cancer stemness, and genetic alterations in a variety of cancer types. BUB1B is highly expressed in a variety of cancers and may serve as a prognostic marker. This study is anticipated to offer molecular details on the elevated cancer risk that psoriasis sufferers experience.

TP53 Abnormalities Are Underlying the Poor Outcome Associated with Chromothripsis in Chronic Lymphocytic Leukemia Patients with Complex Karyotype

Chromothripsis (cth) has been associated with a dismal outcome and poor prognosis factors in patients with chronic lymphocytic leukemia (CLL). Despite being correlated with high genome instability, previous studies have not assessed the role of cth in the context of genomic complexity. Herein, we analyzed a cohort of 33 CLL patients with cth and compared them against a cohort of 129 non-cth cases with complex karyotypes. Nine cth cases were analyzed using optical genome mapping (OGM). Patterns detected by genomic microarrays were compared and the prognostic value of cth was analyzed. Cth was distributed throughout the genome, with chromosomes 3, 6 and 13 being those most frequently affected. OGM detected 88.1% of the previously known copy number alterations and several additional cth-related rearrangements (median: 9, range: 3-26). Two patterns were identified: one with rearrangements clustered in the region with cth (3/9) and the other involving both chromothriptic and non-chromothriptic chromosomes (6/9). Cases with cth showed a shorter time to first treatment (TTFT) than non-cth patients (median TTFT: 2 m vs. 15 m; p = 0.013). However, when stratifying patients based on TP53 status, cth did not affect TTFT. Only TP53 maintained its significance in the multivariate analysis for TTFT, including cth and genome complexity defined by genomic microarrays (HR: 1.60; p = 0.029). Our findings suggest that TP53 abnormalities, rather than cth itself, underlie the poor prognosis observed in this subset.

CONET: copy number event tree model of evolutionary tumor history for single-cell data

Copy number alterations constitute important phenomena in tumor evolution. Whole genome single-cell sequencing gives insight into copy number profiles of individual cells, but is highly noisy. Here, we propose CONET, a probabilistic model for joint inference of the evolutionary tree on copy number events and copy number calling. CONET employs an efficient, regularized MCMC procedure to search the space of possible model structures and parameters. We introduce a range of model priors and penalties for efficient regularization. CONET reveals copy number evolution in two breast cancer samples, and outperforms other methods in tree reconstruction, breakpoint identification and copy number calling.

Mechanistic origins of diverse genome rearrangements in cancer

Cancer genomes frequently harbor structural chromosomal rearrangements that disrupt the linear DNA sequence order and copy number. To date, diverse classes of structural variants have been identified across multiple cancer types. These aberrations span a wide spectrum of complexity, ranging from simple translocations to intricate patterns of rearrangements involving multiple chromosomes. Although most somatic rearrangements are acquired gradually throughout tumorigenesis, recent interrogation of cancer genomes have uncovered novel categories of complex rearrangements that arises rapidly through a one-off catastrophic event, including chromothripsis and chromoplexy. Here we review the cellular and molecular mechanisms contributing to the formation of diverse structural rearrangement classes during cancer development. Genotoxic stress from a myriad of extrinsic and intrinsic sources can trigger DNA double-strand breaks that are subjected to DNA repair with potentially mutagenic outcomes. We also highlight how aberrant nuclear structures generated through mitotic cell division errors, such as rupture-prone micronuclei and chromosome bridges, can instigate massive DNA damage and the formation of complex rearrangements in cancer genomes.

FPIA: A database for gene fusion profiling and interactive analyses

As one of the hallmarks of cancer, gene fusions play an important role in tumorigenesis, and have been established as biomarkers and therapeutic targets. Although recent years have witnessed the development of gene fusion databases, a tool with interactive analytic functions is still lacking. Here, we introduce FPIA (Fusion Profiling Interactive Analysis), a web server to perform interactive and customizable analysis on fusion genes. With this platform, researchers can easily explore fusion-associated biological and molecular differences including gene expression, tumor purity and ploidy, mutation, copy number variations, protein expression, immune cell infiltration, stemness, telomere length, microsatellite instability, survival, and novel peptides based on 33 cancer types from TCGA data. Currently, it contains 31 633 fusion events from 6910 patients. FPIA complements the existing gene fusion annotation databases with its multi-omics analytic capacity, integrated analysis features, customized analysis selection, and user-friendly design. The comprehensive data analyses by FPIA will greatly facilitate data mining, hypothesis generation, and therapeutic target discovery. FPIA is available at http://bioinfo-sysu.com/fpia.

Chromothripsis in Chronic Lymphocytic Leukemia: A Driving Force of Genome Instability

Chromothripsis represents a mechanism of massive chromosome shattering and reassembly leading to the formation of derivative chromosomes with abnormal functions and expression. It has been observed in many cancer types, importantly, including chronic lymphocytic leukemia (CLL). Due to the associated chromosomal rearrangements, it has a significant impact on the pathophysiology of the disease. Recent studies have suggested that chromothripsis may be more common than initially inferred, especially in CLL cases with adverse clinical outcome. Here, we review the main features of chromothripsis, the challenges of its assessment, and the potential benefit of its detection. We summarize recent findings of chromothripsis occurrence across hematological malignancies and address its causes and consequences in the context of CLL clinical features, as well as chromothripsis-related molecular abnormalities described in published CLL studies. Furthermore, we discuss the use of the current knowledge about genome functions associated with chromothripsis in the optimization of treatment strategies in CLL.

Gene Duplication and Gene Fusion Are Important Drivers of Tumourigenesis during Cancer Evolution

Chromosomal rearrangement and genome instability are common features of cancer cells in human. Consequently, gene duplication and gene fusion events are frequently observed in human malignancies and many of the products of these events are pathogenic, representing significant drivers of tumourigenesis and cancer evolution. In certain subsets of cancers duplicated and fused genes appear to be essential for initiation of tumour formation, and some even have the capability of transforming normal cells, highlighting the importance of understanding the events that result in their formation. The mechanisms that drive gene duplication and fusion are unregulated in cancer and they facilitate rapid evolution by selective forces akin to Darwinian survival of the fittest on a cellular level. In this review, we examine current knowledge of the landscape and prevalence of gene duplication and gene fusion in human cancers.

Automated Detection of Arm-Level Alterations for Individual Cancer Patients in the Clinical Setting

Copy number alterations are genetic events that promote tumor initiation and progression and are used in clinical care as diagnostic, prognostic, and predictive biomarkers. Based on the length of the alteration, they are roughly classified as focal and arm-level alterations. Although genome-wide techniques to detect arm-level alterations are gaining momentum in hospital laboratories, the high precision and novelty of these techniques pose new challenges: there is no consensus on the definition of an arm-level alteration and a lack of tools to compute them for individual patients. Based on 376 clinical samples analyzed with the OncoScan formalin-fixed, paraffin-embedded assay, we observed a bimodal distribution of the percentage of bases with copy number alterations within a chromosomal arm, with the second peak starting at 90% of arm length. We tested two approaches for the definition of arm-level alterations: sum of altered segments (SoS) >90% or the longest segment (LS) >90%. The approaches were validated against expert annotation of 25 clinical cases. The SoS method outperformed the LS method with a higher concordance (SoS, 95.2%; LS, 79.9%). Some of the discordances ultimately were attributed to human error, highlighting the advantages of automation. The increase in reliability led to the development of publicly available software and its inclusion into routine clinical practice at Geneva University Hospitals.

driveR: a novel method for prioritizing cancer driver genes using somatic genomics data

Background

Cancer develops due to “driver” alterations. Numerous approaches exist for predicting cancer drivers from cohort-scale genomics data. However, methods for personalized analysis of driver genes are underdeveloped. In this study, we developed a novel personalized/batch analysis approach for driver gene prioritization utilizing somatic genomics data, called driveR.

Results

Combining genomics information and prior biological knowledge, driveR accurately prioritizes cancer driver genes via a multi-task learning model. Testing on 28 different datasets, this study demonstrates that driveR performs adequately, achieving a median AUC of 0.684 (range 0.651–0.861) on the 28 batch analysis test datasets, and a median AUC of 0.773 (range 0–1) on the 5157 personalized analysis test samples. Moreover, it outperforms existing approaches, achieving a significantly higher median AUC than all of MutSigCV (Wilcoxon rank-sum test p < 0.001), DriverNet (p < 0.001), OncodriveFML (p < 0.001) and MutPanning (p < 0.001) on batch analysis test datasets, and a significantly higher median AUC than DawnRank (p < 0.001) and PRODIGY (p < 0.001) on personalized analysis datasets.

Conclusions

This study demonstrates that the proposed method is an accurate and easy-to-utilize approach for prioritizing driver genes in cancer genomes in personalized or batch analyses. driveR is available on CRAN: https://cran.r-project.org/package=driveR.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04203-7.

Functional and Comparative Analysis of Centromeres Reveals Clade-Specific Genome Rearrangements in Candida auris and a Chromosome Number Change in Related Species

The thermotolerant multidrug-resistant ascomycete Candida auris rapidly emerged since 2009 causing systemic infections worldwide and simultaneously evolved in different geographical zones. The molecular events that orchestrated this sudden emergence of the killer fungus remain mostly elusive. Here, we identify centromeres in C. auris and related species, using a combined approach of chromatin immunoprecipitation and comparative genomic analyses. We find that C. auris and multiple other species in the Clavispora/Candida clade shared a conserved small regional GC-poor centromere landscape lacking pericentromeres or repeats. Further, a centromere inactivation event led to karyotypic alterations in this species complex. Interspecies genome analysis identified several structural chromosomal changes around centromeres. In addition, centromeres are found to be rapidly evolving loci among the different geographical clades of the same species of C. auris Finally, we reveal an evolutionary trajectory of the unique karyotype associated with clade 2 that consists of the drug-susceptible isolates of C. aurisIMPORTANCECandida auris, the killer fungus, emerged as different geographical clades, exhibiting multidrug resistance and high karyotype plasticity. Chromosomal rearrangements are known to play key roles in the emergence of new species, virulence, and drug resistance in pathogenic fungi. Centromeres, the genomic loci where microtubules attach to separate the sister chromatids during cell division, are known to be hot spots of breaks and downstream rearrangements. We identified the centromeres in C. auris and related species to study their involvement in the evolution and karyotype diversity reported in C. auris We report conserved centromere features in 10 related species and trace the events that occurred at the centromeres during evolution. We reveal a centromere inactivation-mediated chromosome number change in these closely related species. We also observe that one of the geographical clades, the East Asian clade, evolved along a unique trajectory, compared to the other clades and related species.

Amplifications of Stemness Gene Loci-New Markers for the Determination of the Need for Neoadjuvant Chemotherapy for Patients with Breast Cancer. A Prospective Study

In this prospective study, a new strategy for the prescription of neoadjuvant chemotherapy (NAC) was prospectively tested and depended on the presence of stemness gene amplifications in the tumor before treatment, which in our early studies showed a connection with metastasis. The study included 92 patients with grade IIA–IIIB luminal B breast cancer. Patients underwent a biopsy before treatment, and with the use of a CytoScan HD Array microarray (Affymetrix, Santa Clara, CA, USA), the presence of stemness gene amplifications (3q, 5p, 6p, 7q, 8q, 13q, 9p, 9q, 10p, 10q21.1, 16p, 18chr, 19p) in the tumor was determined. In group 1 (n = 41), in the presence of two or more amplifications, patients were prescribed a personalized NAC regimen. In group 2 (n = 21), if there was no amplification of stemness genes in the tumor, then patients were not prescribed NAC, and treatment began with surgery. Group 3 (n = 30) served as a historical control. The frequency of an objective response to NAC in groups 1 and 3 was 79%. Nonmetastatic survival was found in 100% of patients in group 2, who did not undergo NAC. In patients in group 1, the frequency of metastasis was 10% (4/41). At the same time, in patients in group 3, who received NAC, the rate of metastasis was 47% (14/30). The differences between group 1 and group 3 and between group 2 and group 3 were statistically significant, both by Fisher’s criterion and a log-rank test. The appointment of NAC was most feasible in patients with clones with stemness gene amplifications in the primary tumor, while in the absence of amplifications, preoperative chemotherapy led to a sharp decrease in metastasis-free survival. This strategy of NAC prescription allowed us to achieve 93% metastatic survival in patients with breast cancer.

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..

Copy Number Analysis Reveal Genetic Risks of Penile Cancer

Objectives

To evaluate copy number alterations (CNAs) in genes associated with penile cancer (PeC) and determine their correlation and prognostic ability with PeC.

Methods

Whole-exome sequencing was performed for tumor tissue and matched normal DNA of 35 patients diagnosed with penile squamous cell carcinoma from 2011 to 2016. Somatic CNAs were detected using the Genome Analysis Toolkit (GATK). Retrospective clinical data were collected and analyzed. All the data were statistically analyzed using SPSS 16.0 software. The cancer-specific survival rates were estimated by Kaplan-Meier curves and compared with the log-rank test.

Results

CNAs in the MYCN gene was detected in 19 (amplification: 54.29%) patients. Other CNAs gene targets were FAK (amplification: 45.72%, deletion: 8.57%), TP53 (amplification: 2.86%, deletion: 51.43%), TRKA (amplification: 34.29%, deletion: 2.86%), p75NTR (amplification: 5.71%, deletion: 42.86%), Miz-1 (amplification: 14.29%, deletion: 20.00%), Max (amplification: 17.14%, deletion: 2.86%), Bmi1 (amplification:14.29%, deletion: 48.57%), and MDM2 (amplification: 5.71%, deletion: 45.72%). The CNAs in MYCN and FAK correlated significantly with patient prognosis (P<0.05). The 3-year Recurrence-free survival rate was 87.10% among patients followed up. The 5-year survival rate of patients with MYCN amplification was 69.2%, compared to 94.4% in the non-amplification group. The 5-year survival rate of patients with FAK amplification was 65.6%, compared to 94.7% in the non-amplification group. The PPI network showed that TP53 and MYCN might play meaningful functional roles in PeC.

Conclusion

MYCN and FAK amplification and TP53 deletion were apparent in PeC. MYCN and TP53 were hub genes in PeC. MYCN and FAK amplification was also detected and analyzed, and the findings indicated that these two genes are predictors of poor prognosis in PeC.

RNA-sequencing of IDH-wild-type glioblastoma with chromothripsis identifies novel gene fusions with potential oncogenic properties

Glioblastoma (GBM) is the most frequent and most aggressive form of glioma. It is characterized by marked genomic instability, which suggests that chromothripsis (CT) might be involved in GBM initiation. Recently, CT has emerged as an alternative mechanism of cancer development, involving massive chromosome rearrangements in a one-step catastrophic event. The aim of the study was to detect CT in GBM and identify novel gene fusions in CT regions. One hundred and seventy IDH-wild-type GBM were screened for CT patterns using whole-genome single nucleotide polymorphism (SNP) arrays. RNA sequencing was performed in 52 GBM with CT features to identify gene fusions within CT regions. Forty tumors (40/52, 77%) harbored at least one gene fusion within CT regions. We identified 120 candidate gene fusions, 30 of which with potential oncogenic activities. We validated 11 gene fusions, which involved the most recurrent fusion partners (EGFR, SEPT14, VOPP1 and CPM), by RT-PCR and Sanger sequencing. The occurrence of CT points to underlying gene fusions in IDH-wild-type GBM. CT provides exciting new research avenues in this highly aggressive cancer.

Small but mighty: the causes and consequences of micronucleus rupture

Micronuclei are small DNA-containing nuclear structures that are spatially isolated from the main nucleus. They are frequently found in pathologies, including cancer. It was recently shown that these nuclear structures are not only biomarkers of disease but also play an active role in tumor biology. Many consequences of micronucleus formation on tumor biology are dependent on the frequent and irreversible rupture of their nuclear envelopes, which results in the exposure of their DNA contents to the cytoplasm. In this review, we discuss models of defective nuclear envelope deposition on missegregated chromosomes that lead to nuclear envelope rupture. Furthermore, we expound upon the various downstream consequences of micronucleus nuclear envelope rupture on cells. These consequences include a massive DNA rearrangement phenomenon called chromothripsis and activation of the cGAS-STING innate immune signaling pathway, which can be a double-edged sword with tumorigenesis and tumor prevention functions. Although micronuclei are small structures, the impact they have on cells and their microenvironment is quite large.

Micronuclei, which contain faulty chromosomes or chromosome fragments and occur outside the main cellular nucleus, are prone to rupturing, which leads to DNA changes that can drive tumor development. A team led by Mijung Kwon from Ewha Womans University in Seoul and Jae-Ho Lee of Ajou University School of Medicine in Suwon, both in South Korea, review how these micronuclei tend to burst, spilling their contents into the cell with devastating consequences. The chromosomes they contain break into tiny fragments and this broken DNA finds its way into the main nucleus, leading to chromosomal rearrangements that can permanently alter genomic function. The rupture of micronuclei also activates a part of the innate immune system that can promote cancer cell invasion and spread. Drugs targeting these processes could aid in the treatment of cancer.

Prognostic Impact of Somatic Copy Number Alterations in Childhood B-Lineage Acute Lymphoblastic Leukemia

PURPOSE OF REVIEW

The high prevalence of relapse in pediatric B-lineage acute lymphoblastic leukemia (B-ALL) despite the improvements achieved using current risk stratification schemes, demands more accurate methods for outcome prediction. Here, we provide a concise overview about the key advances that have expanded our knowledge regarding the somatic defects across B-ALL genomes, particularly focusing on copy number alterations (CNAs) and their prognostic impact.

RECENT FINDINGS

The identification of commonly altered genes in B-ALL has inspired the development of risk classifiers based on copy number states such as the IKZF1^plus and the United Kingdom (UK) ALL-CNA classifiers to improve outcome prediction in B-ALL. CNA-risk classifiers have emerged as effective tools to predict disease relapse; though, their clinical applications are yet to be transferred to routine practice.

Hotspots of Human Mutation

Mutation of the human genome results in three classes of genomic variation: single nucleotide variants; short insertions or deletions; and large structural variants (SVs). Some mutations occur during normal processes, such as meiotic recombination or B cell development, and others result from DNA replication or aberrant repair of breaks in sequence-specific contexts. Regardless of mechanism, mutations are subject to selection, and some hotspots can manifest in disease. Here, we discuss genomic regions prone to mutation, mechanisms contributing to mutation susceptibility, and the processes leading to their accumulation in normal and somatic genomes. With further, more accurate human genome sequencing, additional mutation hotspots, mechanistic details of their formation, and the relevance of hotspots to evolution and disease are likely to be discovered.

Systematic investigation of promoter substitutions resulting from somatic intrachromosomal structural alterations in diverse human cancers

One of the ways in which genes can become activated in tumors is by somatic structural genomic rearrangements leading to promoter swapping events, typically in the context of gene fusions that cause a weak promoter to be substituted for a strong promoter. While identifiable by whole genome sequencing, limited availability of this type of data has prohibited comprehensive study of the phenomenon. Here, we leveraged the fact that copy number alterations (CNAs) arise as a result of structural alterations in DNA, and that they may therefore be informative of gene rearrangements, to pinpoint recurrent promoter swapping at a previously intractable scale. CNA data from nearly 9500 human tumors was combined with transcriptomic sequencing data to identify several cases of recurrent activating intrachromosomal promoter substitution events, either involving proper gene fusions or juxtaposition of strong promoters to gene upstream regions. Our computational screen demonstrates that a combination of CNA and expression data can be useful for identifying novel fusion events with potential driver roles in large cancer cohorts.

Multiple Chromoanasynthesis in a Rare Case of Sporadic Renal Leiomyosarcoma: A Case Report

We present the genetic profile of kidney giant leiomyosarcoma characterized by sequencing of 409 cancer related genes and chromosomal microarray analysis. Renal leiomyosarcomas are extremely rare neoplasms with aggressive behavior and poor survival prognosis. Most frequent somatic events in leiomyosarcomas are mutations in the TP53, RB1, ATRX, and PTEN genes, chromosomal instability (CIN) and chromoanagenesis. 67-year-old woman presented with a right kidney completely replaced by tumor. Immunohistochemical reaction on surgical material was positive to desmin and smooth muscle actin. Molecular genetic analysis revealed that tumor harbored monosomy of chromosomes 3 and 11, gain of Xp (ATRX) arm and three chromoanasynthesis regions (6q21-q27, 7p22.3-p12.1, and 12q13.11-q21.2), with MDM2 and CDK4 oncogenes copy number gains, whereas no copy number variations (CNVs) or tumor specific single nucleotide variants (SNVs) in TP53, RB1, and PTEN genes were present. We hypothesize that chromoanasynthesis in 12q13.11-q21.2 could be a trigger of observed CIN in this tumor.

Design and Development of a Fully Synthetic Multiplex Ligation-Dependent Probe Amplification-Based Probe Mix for Detection of Copy Number Alterations in Prostate Cancer Formalin-Fixed, Paraffin-Embedded Tissue Samples

DNA copy number alterations (CNAs) are promising biomarkers to predict prostate cancer (PCa) outcome. However, fluorescence in situ hybridization (FISH) cannot assess complex CNA signatures because of low multiplexing capabilities. Multiplex ligation-dependent probe amplification (MLPA) can detect multiple CNAs in a single PCR assay, but PCa-specific probe mixes available commercially are lacking. Synthetic MLPA probes were designed to target 10 CNAs relevant to PCa: 5q15-21.1 (CHD1), 6q15 (MAP3K7), 8p21.2 (NKX3-1), 8q24.21 (MYC), 10q23.31 (PTEN), 12p13.1 (CDKN1B), 13q14.2 (RB1), 16p13.3 (PDPK1), 16q23.1 (GABARAPL2), and 17p13.1 (TP53), with 9 control probes. In cell lines, CNAs were detected when the cancer genome was as low as 30%. Compared with FISH in radical prostatectomy formalin-fixed, paraffin-embedded samples (n = 18: 15 cancers and 3 matched benign), the MLPA assay showed median sensitivity and specificity of 80% and 93%, respectively, across all CNAs assessed. In the validation set (n = 40: 20 tumors sampled in two areas), the respective sensitivity and specificity of MLPA compared advantageously with FISH and TaqMan droplet digital PCR (ddPCR) when assessing PTEN deletion (FISH: 85% and 100%; ddPCR: 100% and 83%) and PDPK1 gain (FISH: 100% and 92%; ddPCR: 93% and 100%). This new PCa probe mix accurately identifies CNAs by MLPA across multiple genes using low quality and quantities (50 ng) of DNA extracted from clinical formalin-fixed, paraffin-embedded samples.

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.

Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.

Eleven grand challenges in single-cell data science

The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.

Chromosomal rearrangements and their neoantigenic potential in mesothelioma

Chromosomal rearrangements are a defining molecular feature of mesothelioma that are not readily detected by standard DNA sequencing approaches but could be detected by whole genome sequencing methods such as mate-pair sequencing. These chromosomal rearrangements result in novel, unique gene junctions that can be expressed and potentially result in the presentation of several neoantigens. These predicted neoantigens can be presented by tumors on major histocompatibility complex (MHC) proteins and are correlated with clonal expansion of tumor infiltrating T cells. T cells responsive to these neoantigens have been identified in the circulation of a patient. The predictive values of next generation sequencing-based tumor mutation burden measurements may be significantly enhanced by the addition of techniques such as mate-pair sequencing that can detect chromosomal rearrangements. Furthermore, rearrangement associated neo-antigens may also represent valuable targets for future anti-tumor vaccine strategies. Finally, chromosomal rearrangements are now recognized as a mutation signature in cancer and these events are likely to be important in the oncogenesis and immune recognition of not only in mesothelioma but multiple malignancies including non-small cell lung cancer.

Genome-wide somatic copy number alteration analysis and database construction for cervical cancer

Cervical cancer is a common gynecological malignancy with high incidence and mortality. Somatic copy number alterations (CNAs) play an important role in identifying tumor suppressor genes and oncogenes and are a useful diagnostic indicator for many cancer types. However, the genomic landscape of CNAs in cervical cancer has not yet been comprehensively characterized. In the present study, we collected 974 cervical cancer samples from different data sources. All samples were analyzed by genomic arrays to obtain high-resolution CNAs. Focal genomic regions with CNA events and potential cancer driver genes were identified by GISTIC2.0. Meanwhile, we constructed a comprehensive cervical cancer database by PHP and self-written Perl and R scripts. In total, 54 recurrent regions of amplification and deletion were detected. Frequently altered tumor suppressor genes were found in these regions, including PIK3CA, ERBB2, EP300 and FBXW7. CNA hotspots and related enriched functional categories were also identified. The incidence of chromothripsis in cervical cancer was estimated to be 6.06%, and the chromosome pulverization hotspot regions were detected. Based on the curated data, we developed CNAdbCC (http://cailab.labshare.cn/CNAdbCC/), a comprehensive database for copy number alterations in cervical cancer. We provide a user-friendly Web interface for data mining and visualization. It is the most comprehensive public database devoted exclusively to genomic alterations in cervical cancer. These results extend our molecular understanding of cervical cancer. The database will enable researchers to explore specific CNA patterns in this lethal cancer and facilitate the discovery of therapeutic candidates.

Adrenocortical tumors have a distinct, long, non-coding RNA expression profile and LINC00271 is downregulated in malignancy

BACKGROUND

Adrenocortical carcinoma is an aggressive malignancy with a low but variable overall survival rate. The role of in adrenocortical carcinoma is poorly understood. Thus, in this study we performed long noncoding RNA expression profiling in adrenocortical carcinomas, adrenocortical adenomas, and normal adrenal cortex.

METHODS

Long noncoding RNA expression profile using Human LncRNA/mRNA Expression Microarray V3.0 (Arraystar, Inc, Rockville, MD) was analyzed in samples from 11 adrenocortical adenomas, 9 adrenocortical carcinomas, and 5 normal adrenal cortex. Differentially expressed long noncoding RNAs were validated using TaqMan, real-time quantitative polymerase chain reaction with additional samples. The dataset from the adrenocortical carcinoma Cancer Genome Atlas Programproject was used to evaluate the prognostic utility of long noncoding RNAs.

RESULTS

Unsupervised hierarchical clustering showed distinct clustering of adrenocortical carcinoma samples compared with normal adrenal cortex and adrenocortical adenoma samples by long noncoding RNA expression profiles. A total of 874 long noncoding RNAs were differentially expressed between adrenocortical carcinoma and normal adrenal cortex. LINC00271 expression level was associated with prognosis, patients with low LINC00271 expression survived a shorter time than patients with high LINC00271 expression. Low LINC00271 expression was positively associated with WNT signaling, cell cycle, and chromosome segregation pathways.

CONCLUSION

Adrenocortical carcinoma has a distinct long noncoding RNA expression profile. LINC00271 is downregulated in adrenocortical carcinoma and appears to be involved in biologic pathways commonly dysregulated in adrenocortical carcinoma.

Comprehensive identification and characterization of somatic copy number alterations in triple‑negative breast cancer

Triple‑negative breast cancer (TNBC) accounts for ~15% of all breast cancer diagnoses each year. Patients with TNBC tend to have a higher risk for early relapse and a worse prognosis. TNBC is characterized by extensive somatic copy number alterations (CNAs). However, the DNA CNA profile of TNBC remains to be extensively investigated. The present study assessed the genomic profile of CNAs in 201 TNBC samples, aiming to identify recurrent CNAs that may drive the pathogenesis of TNBC. In total, 123 regions of significant amplification and deletion were detected using the Genomic Identification of Significant Targets in Cancer algorithm, and potential driver genes for TNBC were identified. A total of 31 samples exhibited signs of chromothripsis and revealed chromosome pulverization hotspot regions. The present study further determined 199 genomic locations that were significantly enriched for breakpoints, which indicated TNBC‑specific genomic instability regions. Unsupervised hierarchical clustering of tumors resulted in three main subgroups that exhibited distinct CNA profiles, which may reveal the heterogeneity of molecular mechanisms in TNBC subgroups. These results will extend the molecular understanding of TNBC and will facilitate the discovery of therapeutic and diagnostic target candidates.

Roles for Non-coding RNAs in Spatial Genome Organization

Genetic loci are non-randomly arranged in the nucleus of the cell. This order, which is important to overall genome expression and stability, is maintained by a growing number of factors including the nuclear envelope, various genetic elements and dedicated protein complexes. Here, we review evidence supporting roles for non-coding RNAs (ncRNAs) in the regulation of spatial genome organization and its impact on gene expression and cell survival. Specifically, we discuss how ncRNAs from single-copy and repetitive DNA loci contribute to spatial genome organization by impacting perinuclear chromosome tethering, major nuclear compartments, chromatin looping, and various chromosomal structures. Overall, our analysis of the literature highlights central functions for ncRNAs and their transcription in the modulation of spatial genome organization with connections to human health and disease.

Defining Signatures of Arm-Wise Copy Number Change and Their Associated Drivers in Kidney Cancers

Using pan-cancer data from The Cancer Genome Atlas (TCGA), we investigated how patterns in copy number alterations in cancer cells vary both by tissue type and as a function of genetic alteration. We find that patterns in both chromosomal ploidy and individual arm copy number are dependent on tumour type. We highlight for example, the significant losses in chromosome arm 3p and the gain of ploidy in 5q in kidney clear cell renal cell carcinoma tissue samples. We find that specific gene mutations are associated with genome-wide copy number changes. Using signatures derived from non-negative factorisation, we also find gene mutations that are associated with particular patterns of ploidy change. Finally, utilising a set of machine learning classifiers, we successfully predicted the presence of mutated genes in a sample using arm-wise copy number patterns as features. This demonstrates that mutations in specific genes are correlated and may lead to specific patterns of ploidy loss and gain across chromosome arms. Using these same classifiers, we highlight which arms are most predictive of commonly mutated genes in kidney renal clear cell carcinoma (KIRC).

Clinical use of SNP-microarrays for the detection of genome-wide changes in haematological malignancies

Single nucleotide polymorphism (SNP) microarrays are commonly used for the clinical investigation of constitutional genomic disorders; however, their adoption for investigating somatic changes is being recognised. With increasing importance being placed on defining the cancer genome, a shift in technology is imperative at a clinical level. Microarray platforms have the potential to become frontline testing, replacing or complementing standard investigations such as FISH or karyotype. This 'molecular karyotype approach' exemplified by SNP-microarrays has distinct advantages in the investigation of several haematological malignancies. A growing body of literature, including guidelines, has shown support for the use of SNP-microarrays in the clinical laboratory to aid in a more accurate definition of the cancer genome. Understanding the benefits of this technology along with discussing the barriers to its implementation is necessary for the development and incorporation of SNP-microarrays in a clinical laboratory for the investigation of haematological malignancies.

Genome-wide copy number alteration and VEGFA amplification of circulating cell-free DNA as a biomarker in advanced hepatocellular carcinoma patients treated with Sorafenib

Background

Although sorafenib is the global standard first-line systemic treatment for unresectable hepatocellular carcinoma (HCC), it does not have reliable predictive or prognostic biomarkers. Circulating cell-free DNA (cfDNA) has shown promise as a biomarker for various cancers. We investigated the use of cfDNA to predict clinical outcomes in HCC patients treated with sorafenib.

Methods

This prospective biomarker study analyzed plasma cfDNA from 151 HCC patients who received first-line sorafenib and 14 healthy controls. The concentration and VEGFA-to-EIF2C1 ratios (the VEGFA ratio) of cfDNA were measured. Low depth whole-genome sequencing of cfDNA was used to identify genome-wide copy number alteration (CNA), and the I-score was developed to express genomic instability. The I-score was defined as the sum of absolute Z-scores of sequenced reads on each chromosome. The primary aim of this study was to develop cfDNA biomarkers predicting treatment outcomes of sorafenib, and the primary study outcome was the association between biomarkers with treatment efficacy including disease control rate (DCR), time to progression (TTP) and overall survival (OS) in these patients.

Results

The cfDNA concentrations were significantly higher in HCC patients than in healthy controls (0.71 vs. 0.34 ng/μL; P < 0.0001). Patients who did not achieve disease control with sorafenib had significantly higher cfDNA levels (0.82 vs. 0.63 ng/μL; P = 0.006) and I-scores (3405 vs. 1024; P = 0.0017) than those achieving disease control. The cfDNA-high group had significantly worse TTP (2.2 vs. 4.1 months; HR = 1.71; P = 0.002) and OS (4.1 vs. 14.8 months; HR = 3.50; P < 0.0001) than the cfDNA-low group. The I-score-high group had poorer TTP (2.2 vs. 4.1 months; HR = 2.09; P < 0.0001) and OS (4.6 vs. 14.8 months; HR = 3.35; P < 0.0001). In the multivariable analyses, the cfDNA remained an independent prognostic factor for OS (P < 0.0001), and the I-score for both TTP (P = 0.011) and OS (P = 0.010). The VEGFA ratio was not significantly associated with treatment outcomes.

Conclusion

Pretreatment cfDNA concentration and genome-wide CNA in cfDNA are potential biomarkers predicting outcomes in advanced HCC patients receiving first-line sorafenib.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5483-x) contains supplementary material, which is available to authorized users.

Chromoanagenesis: cataclysms behind complex chromosomal rearrangements

Background

During the last decade, genome sequencing projects in cancer genomes as well as in patients with congenital diseases and healthy individuals have led to the identification of new types of massive chromosomal rearrangements arising during single chaotic cellular events. These unanticipated catastrophic phenomenon are termed chromothripsis, chromoanasynthesis and chromoplexis., and are grouped under the name of “chromoanagenesis”.

Results

For each process, several specific features have been described, allowing each phenomenon to be distinguished from each other and to understand its mechanism of formation and to better understand its aetiology. Thus, chromothripsis derives from chromosome shattering followed by the random restitching of chromosomal fragments with low copy-number change whereas chromoanasynthesis results from erroneous DNA replication of a chromosome through serial fork stalling and template switching with variable copy-number gains, and chromoplexy refers to the occurrence of multiple inter-and intra-chromosomal translocations and deletions with little or no copy-number alterations in prostate cancer. Cumulating data and experimental models have shown that chromothripsis and chromoanasynthesis may essentially result from lagging chromosome encapsulated in micronuclei or telomere attrition and end-to-end telomere fusion.

Conclusion

The concept of chromanagenesis has provided new insight into the aetiology of complex structural rearrangements, the connection between defective cell cycle progression and genomic instability, and the complexity of cancer evolution. Increasing reported chromoanagenesis events suggest that these chaotic mechanisms are probably much more frequent than anticipated.

Identification of cancer prognosis-associated lncRNAs based on the miRNA-TF co-regulatory motifs and dosage sensitivity

By integrating dosage sensitivity and motif regulation data, we established a framework and identified a total of 33 cancer prognosis-associated lncRNAs.

Repetitive Fragile Sites: Centromere Satellite DNA As a Source of Genome Instability in Human Diseases

Maintenance of an intact genome is essential for cellular and organismal homeostasis. The centromere is a specialized chromosomal locus required for faithful genome inheritance at each round of cell division. Human centromeres are composed of large tandem arrays of repetitive alpha-satellite DNA, which are often sites of aberrant rearrangements that may lead to chromosome fusions and genetic abnormalities. While the centromere has an essential role in chromosome segregation during mitosis, the long and repetitive nature of the highly identical repeats has greatly hindered in-depth genetic studies, and complete annotation of all human centromeres is still lacking. Here, we review our current understanding of human centromere genetics and epigenetics as well as recent investigations into the role of centromere DNA in disease, with a special focus on cancer, aging, and human immunodeficiency⁻centromeric instability⁻facial anomalies (ICF) syndrome. We also highlight the causes and consequences of genomic instability at these large repetitive arrays and describe the possible sources of centromere fragility. The novel connection between alpha-satellite DNA instability and human pathological conditions emphasizes the importance of obtaining a truly complete human genome assembly and accelerating our understanding of centromere repeats' role in physiology and beyond.

The dark side of centromeres: types, causes and consequences of structural abnormalities implicating centromeric DNA

Centromeres are the chromosomal domains required to ensure faithful transmission of the genome during cell division. They have a central role in preventing aneuploidy, by orchestrating the assembly of several components required for chromosome separation. However, centromeres also adopt a complex structure that makes them susceptible to being sites of chromosome rearrangements. Therefore, preservation of centromere integrity is a difficult, but important task for the cell. In this review, we discuss how centromeres could potentially be a source of genome instability and how centromere aberrations and rearrangements are linked with human diseases such as cancer.

A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.

Exome-wide analysis identifies three low-frequency missense variants associated with pancreatic cancer risk in Chinese populations

Germline coding variants have not been systematically investigated for pancreatic ductal adenocarcinoma (PDAC). Here we report an exome-wide investigation using the Illumina Human Exome Beadchip with 943 PDAC cases and 3908 controls in the Chinese population, followed by two independent replicate samples including 2142 cases and 4697 controls. We identify three low-frequency missense variants associated with the PDAC risk: rs34309238 in PKN1 (OR = 1.77, 95% CI: 1.48–2.12, P = 5.35 × 10⁻¹⁰), rs2242241 in DOK2 (OR = 1.85, 95% CI: 1.50–2.27, P = 4.34 × 10⁻⁹), and rs183117027 in APOB (OR = 2.34, 95% CI: 1.72–3.16, P = 4.21 × 10⁻⁸). Functional analyses show that the PKN1 rs34309238 variant significantly increases the level of phosphorylated PKN1 and thus enhances PDAC cells' proliferation by phosphorylating and activating the FAK/PI3K/AKT pathway. These findings highlight the significance of coding variants in the development of PDAC and provide more insights into the prevention of this disease.

Pancreatic ductal adenocarcinoma is a lethal human cancer with a poor 5-year overall survival rate. Here the authors perform an exome-wide analysis in a cohort of PDAC patients to identify three novel missense variants in PKN1, DOK2, and APOB genes, that are associated with PDAC risk.

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.

Cross-talk between Lysine-Modifying Enzymes Controls Site-Specific DNA Amplifications

Acquired chromosomal DNA amplifications are features of many tumors. Although overexpression and stabilization of the histone H3 lysine 9/36 (H3K9/36) tri-demethylase KDM4A generates transient site-specific copy number gains (TSSGs), additional mechanisms directly controlling site-specific DNA copy gains are not well defined. In this study, we uncover a collection of H3K4-modifying chromatin regulators that function with H3K9 and H3K36 regulators to orchestrate TSSGs. Specifically, the H3K4 tri-demethylase KDM5A and specific COMPASS/KMT2 H3K4 methyltransferases modulate different TSSG loci through H3K4 methylation states and KDM4A recruitment. Furthermore, a distinct chromatin modifier network, MLL1-KDM4B-KDM5B, controls copy number regulation at a specific genomic locus in a KDM4A-independent manner. These pathways comprise an epigenetic addressing system for defining site-specific DNA rereplication and amplifications.

Losses of cytokines and chemokines are common genetic features of human cancers: the somatic copy number alterations are correlated with patient prognoses and therapeutic resistance

Intricate relationships among cytokines (including chemokines) shape the tumor microenvironment (TME) and reflect cell-cell interactions between malignant cells and other cells from the TME. Although our previous study indicated the transcriptional landscape of cytokines in 19 cancer types, the global pattern somatic copy number (SCN) alterations and the clinical relevance of cytokines have not been systematically investigated. Here, we reported a significant negative selection on cytokine genes. We also linked the SCN losses of cytokine genes to the abundance of immune infiltrates which affects cancer progression and patient prognoses. We also demonstrated and validated the correlations between SCN alterations of cytokine-containing loci and drug sensitivity. The results indicated the genomic loss of cytokines in malignant cells as a crucial theme for interrogating cancer progression, malignant cell-TME interactions, and therapeutics.

Mutational game changer: Chromothripsis and its emerging relevance to cancer

In recent years, the paradigm that genomic abnormalities in cancer cells arise through progressive accumulation of mutational events has been challenged by the discovery of single catastrophic events. One such phenomenon termed chromothripsis, involving massive chromosomal rearrangements arising all at once, has emerged as a major mutational game changer. The strong interest in this process stems from its widespread association with a range of cancer types and its potential as a mutational driver. In this review, we first describe chromothripsis detection and incidence in cancers. We then explore recently proposed underlying mechanistic origins, which explain the curious observations of the highly localised nature of the rearrangements on chromothriptic chromosomes. Detection of chromothriptic patterns following incorporation of single chromosomes into micronuclei or following telomere attrition have greatly contributed to our understanding of the reasons behind this chromosomal restriction. These underlying cellular events have been found to be participants in the tumourigenic process, strongly suggesting a potential role for chromothripsis in cancer development. Thus, we discuss potential implications of chromothripsis for cancer progression and therapy.

Implementing precision cancer medicine in the genomic era

The utilization of genomic data to direct treatment for cancer patients represents the central tenet in precision oncology, in which a patient is matched to a specific drug or therapy based on the genetic drivers detected in his or her tumor rather than the tumor's histologic classification. The expected but not always realized outcomes of molecularly matched therapies include increased response rates, more durable responses, deeper responses, and decreased number of therapy-related side effects. In this review, we will discuss different facets of utilizing genomic data to direct the increasingly complex care of cancer patients. We discuss the enlarging compendium of actionable genomic alterations and the development of novel molecular diagnostic assays for clinical application. Finally, we present an overview of the growing number of genomics-driven clinical trials and conclude with a discussion of future challenges in the implementation of precision oncology.

Telomere Maintenance Mechanisms in Cancer

Tumour cells can adopt telomere maintenance mechanisms (TMMs) to avoid telomere shortening, an inevitable process due to successive cell divisions. In most tumour cells, telomere length (TL) is maintained by reactivation of telomerase, while a small part acquires immortality through the telomerase-independent alternative lengthening of telomeres (ALT) mechanism. In the last years, a great amount of data was generated, and different TMMs were reported and explained in detail, benefiting from genome-scale studies of major importance. In this review, we address seven different TMMs in tumour cells: mutations of the TERT promoter (TERTp), amplification of the genes TERT and TERC, polymorphic variants of the TERT gene and of its promoter, rearrangements of the TERT gene, epigenetic changes, ALT, and non-defined TMM (NDTMM). We gathered information from over fifty thousand patients reported in 288 papers in the last years. This wide data collection enabled us to portray, by organ/system and histotypes, the prevalence of TERTp mutations, TERT and TERC amplifications, and ALT in human tumours. Based on this information, we discuss the putative future clinical impact of the aforementioned mechanisms on the malignant transformation process in different setups, and provide insights for screening, prognosis, and patient management stratification.

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.