Structural mutations in cancer: mechanistic and functional insights

The Spiral Model of Evolution: Stable Life Forms of Organisms and Unstable Life Forms of Cancers

If one must prioritize among the vast array of contributing factors to cancer evolution, environmental-stress-mediated chromosome instability (CIN) should easily surpass individual gene mutations. CIN leads to the emergence of genomically unstable life forms, enabling them to grow dominantly within the stable life form of the host. In contrast, stochastic gene mutations play a role in aiding the growth of the cancer population, with their importance depending on the initial emergence of the new system. Furthermore, many specific gene mutations among the many available can perform this function, decreasing the clinical value of any specific gene mutation. Since these unstable life forms can respond to treatment differently than stable ones, cancer often escapes from drug treatment by forming new systems, which leads to problems during the treatment for patients. To understand how diverse factors impact CIN-mediated macroevolution and genome integrity-ensured microevolution, the concept of two-phased cancer evolution is used to reconcile some major characteristics of cancer, such as bioenergetic, unicellular, and multicellular evolution. Specifically, the spiral of life function model is proposed, which integrates major historical evolutionary innovations and conservation with information management. Unlike normal organismal evolution in the microevolutionary phase, where a given species occupies a specific location within the spiral, cancer populations are highly heterogenous at multiple levels, including epigenetic levels. Individual cells occupy different levels and positions within the spiral, leading to supersystems of mixed cellular populations that exhibit both macro and microevolution. This analysis, utilizing karyotype to define the genetic networks of the cellular system and CIN to determine the instability of the system, as well as considering gene mutation and epigenetics as modifiers of the system for information amplification and usage, explores the high evolutionary potential of cancer. It provides a new, unified understanding of cancer as a supersystem, encouraging efforts to leverage the dynamics of CIN to develop improved treatment options. Moreover, it offers a historically contingent model for organismal evolution that reconciles the roles of both evolutionary innovation and conservation through macroevolution and microevolution, respectively.

DNA damage response and neoantigens: A favorable target for triple-negative breast cancer immunotherapy and vaccine development

Triple-negative breast cancer (TNBC) poses a significant clinical challenge due to its aggressive nature and limited therapeutic options. The interplay between DNA damage response (DDR) mechanisms and the emergence of neoantigens represents a promising avenue for developing targeted immunotherapeutic strategies and vaccines for TNBC. The DDR is a complex network of cellular mechanisms designed to maintain genomic integrity. In TNBC, where genetic instability is a hallmark, dysregulation of DDR components plays a pivotal role in tumorigenesis and progression. This review explores the intricate relationship between DDR and neoantigens, shedding light on the potential vulnerabilities of TNBC cells. Neoantigens, arising from somatic mutations in cancer cells, represent unique antigens that can be recognized by the immune system. TNBC's propensity for genomic instability leads to an increased mutational burden, consequently yielding a rich repertoire of neoantigens. The convergence of DDR and neoantigens in TNBC offers a distinctive opportunity for immunotherapeutic targeting. Immunotherapy has revolutionized cancer treatment by harnessing the immune system to selectively target cancer cells. The unique immunogenicity conferred by DDR-related neoantigens in TNBC positions them as ideal targets for immunotherapeutic interventions. This review also explores various immunotherapeutic modalities, including immune checkpoint inhibitors (ICIs), adoptive cell therapies, and cancer vaccines, that leverage the DDR and neoantigen interplay to enhance anti-tumor immune responses. Moreover, the potential for developing vaccines targeting DDR-related neoantigens opens new frontiers in preventive and therapeutic strategies for TNBC. The rational design of vaccines tailored to the individual mutational landscape of TNBC holds promise for precision medicine approaches. In conclusion, the convergence of DDR and neoantigens in TNBC presents a compelling rationale for the development of innovative immunotherapies and vaccines. Understanding and targeting these interconnected processes may pave the way for personalized and effective interventions, offering new hope for patients grappling with the challenges posed by TNBCs.

Tracking Karyotype Changes in Treatment-Induced Drug-Resistant Evolution

Karyotype coding, which encompasses the complete chromosome sets and their topological genomic relationships within a given species, encodes system-level information that organizes and preserves genes' function, and determines the macroevolution of cancer. This new recognition emphasizes the crucial role of karyotype characterization in cancer research. To advance this cancer cytogenetic/cytogenomic concept and its platforms, this study outlines protocols for monitoring the karyotype landscape during treatment-induced rapid drug resistance in cancer. It emphasizes four key perspectives: combinational analyses of phenotype and karyotype, a focus on the entire evolutionary process through longitudinal analysis, a comparison of whole landscape dynamics by including various types of NCCAs (including genome chaos), and the use of the same process to prioritize different genomic scales. This protocol holds promise for studying numerous evolutionary aspects of cancers, and it further enhances the power of karyotype analysis in cancer research.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis

BACKGROUND

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC.

METHODS

We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics.

RESULTS

In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively.

CONCLUSION

Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

Long-read sequencing identifies novel structural variations in colorectal cancer

Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.

Neoantigens: promising targets for cancer therapy

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Rates and spectra of de novo structural mutations in Chlamydomonas reinhardtii

Genetic variation originates from several types of spontaneous mutation, including single-nucleotide substitutions, short insertions and deletions (indels), and larger structural changes. Structural mutations (SMs) drive genome evolution and are thought to play major roles in evolutionary adaptation, speciation, and genetic disease, including cancers. Sequencing of mutation accumulation (MA) lines has provided estimates of rates and spectra of single-nucleotide and indel mutations in many species, yet the rate of new SMs is largely unknown. Here, we use long-read sequencing to determine the full mutation spectrum in MA lines derived from two strains (CC-1952 and CC-2931) of the green alga Chlamydomonas reinhardtii The SM rate is highly variable between strains and between MA lines, and SMs represent a substantial proportion of all mutations in both strains (CC-1952 6%; CC-2931 12%). The SM spectra differ considerably between the two strains, with almost all inversions and translocations occurring in CC-2931 MA lines. This variation is associated with heterogeneity in the number and type of active transposable elements (TEs), which comprise major proportions of SMs in both strains (CC-1952 22%; CC-2931 38%). In CC-2931, a Crypton and a previously undescribed type of DNA element have caused 71% of chromosomal rearrangements, whereas in CC-1952, a Dualen LINE is associated with 87% of duplications. Other SMs, notably large duplications in CC-2931, are likely products of various double-strand break repair pathways. Our results show that diverse types of SMs occur at substantial rates, and support prominent roles for SMs and TEs in evolution.

Increased gene dosage and mRNA expression from chromosomal duplications in Caenorhabditis elegans

Isolation of copy number variations and chromosomal duplications at high frequency in the laboratory suggested that Caenorhabditis elegans tolerates increased gene dosage. Here, we addressed if a general dosage compensation mechanism acts at the level of mRNA expression in C. elegans. We characterized gene dosage and mRNA expression in 3 chromosomal duplications and a fosmid integration strain using DNA-seq and mRNA-seq. Our results show that on average, increased gene dosage leads to increased mRNA expression, pointing to a lack of genome-wide dosage compensation. Different genes within the same chromosomal duplication show variable levels of mRNA increase, suggesting feedback regulation of individual genes. Somatic dosage compensation and germline repression reduce the level of mRNA increase from X chromosomal duplications. Together, our results show a lack of genome-wide dosage compensation mechanism acting at the mRNA level in C. elegans and highlight the role of epigenetic and individual gene regulation contributing to the varied consequences of increased gene dosage.

The role of BCL9 genetic variation as a biomarker for hepatitis C-related hepatocellular carcinoma in Egyptian patients

BACKGROUND

Hepatocellular carcinoma (HCC) is considered one of the most common cancers related to mortality around the world, and susceptibility is related with genetic, lifestyle, and environmental factors. Copy number variation of the Bcell CLL/lymphoma 9 (BCL9) gene is a type of structural variation which can influence gene expression and can be related with specific phenotypes and diseases and has a role in hepatocarcinogenesis. Our aims were to assess the copy number variation (CNV) in the BCL9 gene and explore its role in HCV-related HCC Egyptian patients. A total of 50 HCV-related HCC patients were enrolled in the study (including 25 early HCC and 25 late HCC cases); the copy number of the BCL9 gene was detected using quantitative polymerase reaction.

RESULTS

There was a highly statistically significant difference between the two groups (early and late HCC patients) in gender, bilharziasis, performance status, child score class, child grade, focal lesion size, portal vein, and ascites. CNV was detected and represented by the gain in the BCL9 gene in 14% of patients, and all of them were males. Also, it was noticed that the ratio of gain in BCL9 copy number in late individuals was about 1.5 times than that in early HCC individuals. Moreover, our results showed that the distribution of performance status > 1, average and enlarged liver, focal lesion size, thrombosed portal vein, and AFP was higher in patients with BCL9 copy number gain.

CONCLUSION

We detected about 14% gain in BCL9 copy number in Egyptian HCC patients. But the variation in copy number of the BCL9 gene did not affect HCC development in our patients' cohort.

Genome Chaos, Information Creation, and Cancer Emergence: Searching for New Frameworks on the 50th Anniversary of the "War on Cancer"

The year 2021 marks the 50th anniversary of the National Cancer Act, signed by President Nixon, which declared a national “war on cancer.” Powered by enormous financial support, this past half-century has witnessed remarkable progress in understanding the individual molecular mechanisms of cancer, primarily through the characterization of cancer genes and the phenotypes associated with their pathways. Despite millions of publications and the overwhelming volume data generated from the Cancer Genome Project, clinical benefits are still lacking. In fact, the massive, diverse data also unexpectedly challenge the current somatic gene mutation theory of cancer, as well as the initial rationales behind sequencing so many cancer samples. Therefore, what should we do next? Should we continue to sequence more samples and push for further molecular characterizations, or should we take a moment to pause and think about the biological meaning of the data we have, integrating new ideas in cancer biology? On this special anniversary, we implore that it is time for the latter. We review the Genome Architecture Theory, an alternative conceptual framework that departs from gene-based theories. Specifically, we discuss the relationship between genes, genomes, and information-based platforms for future cancer research. This discussion will reinforce some newly proposed concepts that are essential for advancing cancer research, including two-phased cancer evolution (which reconciles evolutionary contributions from karyotypes and genes), stress-induced genome chaos (which creates new system information essential for macroevolution), the evolutionary mechanism of cancer (which unifies diverse molecular mechanisms to create new karyotype coding during evolution), and cellular adaptation and cancer emergence (which explains why cancer exists in the first place). We hope that these ideas will usher in new genomic and evolutionary conceptual frameworks and strategies for the next 50 years of cancer research.

Exploring the Modulatory Effects of Gut Microbiota in Anti-Cancer Therapy

In the recent decade, gut microbiota has received growing interest due to its role in human health and disease. On the one hand, by utilizing the signaling pathways of the host and interacting with the immune system, the gut microbiota is able to maintain the homeostasis in human body. This important role is mainly modulated by the composition of microbiota, as a normal microbiota composition is responsible for maintaining the homeostasis of human body, while an altered microbiota profile could contribute to several pathogenic conditions and may further lead to oncogenesis and tumor progression. Moreover, recent insights have especially focused on the important role of gut microbiota in current anticancer therapies, including chemotherapy, radiotherapy, immunotherapy and surgery. Research findings have indicated a bidirectional interplay between gut microbiota and these therapeutic methods, in which the implementation of different therapeutic methods could lead to different alterations in gut microbiota, and the presence of gut microbiota could in turn contribute to different therapeutic responses. As a result, manipulating the gut microbiota to reduce the therapy-induced toxicity may provide an adjuvant therapy to achieve a better therapeutic outcome. Given the complex role of gut microbiota in cancer treatment, this review summarizes the interactions between gut microbiota and anticancer therapies, and demonstrates the current strategies for reshaping gut microbiota community, aiming to provide possibilities for finding an alternative approach to lower the damage and improve the efficacy of cancer therapy.

Identification of copy number variation and population analysis of the sacred lotus (Nelumbo nucifera)

The sacred lotus (Nelumbo nucifera) is widely cultured in East Asia for its horticultural, agricultural, and medicinal values. Although many molecular markers had been used to extrapolate population genetics of the sacred lotus, a study of large variations, such as copy number variation (CNV), are absent up to now. In this study, we applied whole-genome re-sequencing to 24 lotus accessions, and use read depth information to genotype and filter original CNV call. Totally 448 duplications and 4,267 deletions were identified in the final CNV set. Further analysis of population structure revealed that the population structure patterns revealed by CNV and SNP are largely consistent with each other. Our result indicated that deep sequencing followed by genotyping is a quick and straightforward way to mine out CNV from the population, and the CNV along with SNP could enable us to better comprehend the biology of the plant.

DINTD: Detection and Inference of Tandem Duplications From Short Sequencing Reads

Tandem duplication (TD) is an important type of structural variation (SV) in the human genome and has biological significance for human cancer evolution and tumor genesis. Accurate and reliable detection of TDs plays an important role in advancing early detection, diagnosis, and treatment of disease. The advent of next-generation sequencing technologies has made it possible for the study of TDs. However, detection is still challenging due to the uneven distribution of reads and the uncertain amplitude of TD regions. In this paper, we present a new method, DINTD (Detection and INference of Tandem Duplications), to detect and infer TDs using short sequencing reads. The major principle of the proposed method is that it first extracts read depth and mapping quality signals, then uses the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to find the possible TD regions. The total variation penalized least squares model is fitted with read depth and mapping quality signals to denoise signals. A 2D binary search tree is used to search the neighbor points effectively. To further identify the exact breakpoints of the TD regions, split-read signals are integrated into DINTD. The experimental results of DINTD on simulated data sets showed that DINTD can outperform other methods for sensitivity, precision, F1-score, and boundary bias. DINTD is further validated on real samples, and the experiment results indicate that it is consistent with other methods. This study indicates that DINTD can be used as an effective tool for detecting TDs.

Integrated analysis of optical mapping and whole-genome sequencing reveals intratumoral genetic heterogeneity in metastatic lung squamous cell carcinoma

Background

Intratumoral heterogeneity is a crucial factor to the outcome of patients and resistance to therapies, in which structural variants play an indispensable but undiscovered role.

Methods

We performed an integrated analysis of optical mapping and whole-genome sequencing on a primary tumor (PT) and matched metastases including lymph node metastasis (LNM) and tumor thrombus in the pulmonary vein (TPV). Single nucleotide variants, indels and structural variants were analyzed to reveal intratumoral genetic heterogeneity among tumor cells in different sites.

Results

Our results demonstrated there were less nonsynonymous somatic variants shared with PT in LNM than in TPV, while there were more structural variants shared with PT in LNM than in TPV. More private variants and its affected genes associated with tumorigenesis and progression were identified in TPV than in LNM. It should be noticed that optical mapping detected an average of 77.1% (74.5-78.5%) large structural variants (>5,000 bp) not detected by whole-genome sequencing and identified several structural variants private to metastases.

Conclusions

Our study does demonstrate structural variants, especially large structural variants play a crucial role in intratumoral genetic heterogeneity and optical mapping could make up for the deficiency of whole-genome sequencing to identify structural variants.

MACROD2 deficiency promotes hepatocellular carcinoma growth and metastasis by activating GSK-3β/β-catenin signaling

Structural variations (SVs) influence the development and progression of multiple types of cancer. The genes affected by SVs in hepatocellular carcinoma (HCC) and their contribution to tumor growth and metastasis remain unknown. In this study, through whole-genome sequencing (WGS), we identified MACROD2 as the gene most frequently affected by SVs, which were associated with low MACROD2 expression levels. Low MACROD2 expression was predictive of tumor recurrence and poor overall survival. MACROD2 expression was decreased in HCC cell lines, especially those with high metastatic potential. MACROD2 knockdown in HCC cells markedly enhanced proliferation and invasiveness in vitro and tumor progression in vivo and promoted epithelial–mesenchymal transition (EMT). By contrast, MACROD2 overexpression reversed EMT and inhibited HCC growth and metastasis. Mechanistically, MACROD2 deficiency suppressed glycogen synthase kinase-3β (GSK-3β) activity and activated β-catenin signaling, which mediated the effect of MACROD2 on HCC. In clinical HCC samples, decreased MACROD2 expression was correlated with the activation of GSK-3β/β-catenin signaling and the EMT phenotype. Overall, our results revealed that MACROD2 is frequently affected by SVs in HCC, and its deficiency promotes tumor growth and metastasis by activating GSK-3β/β-catenin signaling.

Digital PCR and the QuantStudio™ 3D Digital PCR System

The great promise of digital PCR is the potential for unparalleled precision enabling accurate measurements for detection and quantification of genetic material. This chapter walks the reader through the fundamentals of digital PCR technology including digital PCR modeling using Poisson statistics. It describes a highly successful implementation of digital PCR technology using the chip-based nanofluidic Applied Biosystems™ QuantStudio™ 3D digital PCR system. It reviews the large number of applications where digital PCR is poised to make significant impacts. These include applications where detection of rare genetic targets is prioritized such as liquid biopsy, rare mutation detection, confirmation of NGS variant detection, detection of fusion transcripts, detection of chimerism and GMO detection and monitoring. These further include applications where accurate quantification of genetic targets is prioritized such as generation of references and standards, copy number variation, and NGS Library quantification.

From gene editing to genome engineering: restructuring plant chromosomes via CRISPR/Cas

In the last years, tremendous progress has been achieved in the field of gene editing in plants. By the induction of single site-specific double-strand breaks (DSBs), the knockout of genes by non-homologous end joining has become routine in many plant species. Recently, the efficiency of inducing pre-planned mutations by homologous recombination has also been improved considerably. However, very little effort has been undertaken until now to achieve more complex changes in plant genomes by the simultaneous induction of several DSBs. Several reports have been published on the efficient induction of deletions. However, the induction of intrachromosomal inversions and interchromosomal recombination by the use of CRISPR/Cas has only recently been reported. In this review, we want to sum up these results and put them into context with regards to what is known about natural chromosome rearrangements in plants. Moreover, we review the recent progress in CRISPR/Cas-based mammalian chromosomal rearrangements, which might be inspiring for plant biologists. In the long run, the controlled restructuring of plant genomes should enable us to link or break linkage of traits at will, thus defining a new area of plant breeding.

Chromosomal rearrangements as a source of new gene formation in Drosophila yakuba

The origins of new genes are among the most fundamental questions in evolutionary biology. Our understanding of the ways that new genetic material appears and how that genetic material shapes population variation remains incomplete. De novo genes and duplicate genes are a key source of new genetic material on which selection acts. To better understand the origins of these new gene sequences, we explored the ways that structural variation might alter expression patterns and form novel transcripts. We provide evidence that chromosomal rearrangements are a source of novel genetic variation that facilitates the formation of de novo exons in Drosophila. We identify 51 cases of de novo exon formation created by chromosomal rearrangements in 14 strains of D. yakuba. These new genes inherit transcription start signals and open reading frames when the 5' end of existing genes are combined with previously untranscribed regions. Such new genes would appear with novel peptide sequences, without the necessity for secondary transitions from non-coding RNA to protein. This mechanism of new peptide formations contrasts with canonical theory of de novo gene progression requiring non-coding intermediaries that must acquire new mutations prior to loss via pseudogenization. Hence, these mutations offer a means to de novo gene creation and protein sequence formation in a single mutational step, answering a long standing open question concerning new gene formation. We further identify gene expression changes to 134 existing genes, indicating that these mutations can alter gene regulation. Population variability for chromosomal rearrangements is considerable, with 2368 rearrangements observed across 14 inbred lines. More rearrangements were identified on the X chromosome than any of the autosomes, suggesting the X is more susceptible to chromosome alterations. Together, these results suggest that chromosomal rearrangements are a source of variation in populations that is likely to be important to explain genetic and therefore phenotypic diversity.

Essential Saccharomyces cerevisiae genome instability suppressing genes identify potential human tumor suppressors

Gross Chromosomal Rearrangements (GCRs) play an important role in human diseases, including cancer. Although most of the nonessential Genome Instability Suppressing (GIS) genes in Saccharomyces cerevisiae are known, the essential genes in which mutations can cause increased GCR rates are not well understood. Here 2 S. cerevisiae GCR assays were used to screen a targeted collection of temperature-sensitive mutants to identify mutations that caused increased GCR rates. This identified 94 essential GIS (eGIS) genes in which mutations cause increased GCR rates and 38 candidate eGIS genes that encode eGIS1 protein-interacting or family member proteins. Analysis of TCGA data using the human genes predicted to encode the proteins and protein complexes implicated by the S. cerevisiae eGIS genes revealed a significant enrichment of mutations affecting predicted human eGIS genes in 10 of the 16 cancers analyzed.

Common fragile site instability in normal cells: Lessons and perspectives

Mechanisms and events related to common fragile site (CFS) instability are well known in cancer cells. Here, we argue that normal cells remain an important experimental model to address questions related to CFS instability in the absence of alterations in cell cycle and DNA damage repair pathways, which are common features acquired in cancer. Furthermore, a major gap of knowledge concerns the stability of CFSs during gametogenesis. CFS instability in meiotic or postmeiotic stages of the germ cell line could generate chromosome deletions or large rearrangements. This in turn can lead to the functional loss of the several CFS-associated genes with tumor suppressor function. Our hypothesis is that such mutations can potentially result in genetic predisposition to develop cancer. Indirect evidence for CFS instability in human germ cells has been provided by genomic investigations in family pedigrees associated with genetic disease. The issue of CFS instability in the germ cell line should represent one of the future efforts, and may take advantage of the existence of sequence and functional conservation of CFSs between rodents and humans.

Breaking point: the genesis and impact of structural variation in tumours

Somatic structural variants undoubtedly play important roles in driving tumourigenesis. This is evident despite the substantial technical challenges that remain in accurately detecting structural variants and their breakpoints in tumours and in spite of our incomplete understanding of the impact of structural variants on cellular function. Developments in these areas of research contribute to the ongoing discovery of structural variation with a clear impact on the evolution of the tumour and on the clinical importance to the patient. Recent large whole genome sequencing studies have reinforced our impression of each tumour as a unique combination of mutations but paradoxically have also discovered similar genome-wide patterns of single-nucleotide and structural variation between tumours. Statistical methods have been developed to deconvolute mutation patterns, or signatures, that recur across samples, providing information about the mutagens and repair processes that may be active in a given tumour. These signatures can guide treatment by, for example, highlighting vulnerabilities in a particular tumour to a particular chemotherapy. Thus, although the complete reconstruction of the full evolutionary trajectory of a tumour genome remains currently out of reach, valuable data are already emerging to improve the treatment of cancer.

Bleomycin-induced genome structural variations in normal, non-tumor cells

Many anticancer drugs are genotoxic agents inducing DNA breaks in actively proliferating cancer cells. However, these same drugs also induce mutations, mostly genome structural variations (GSVs). The detection of GSVs in normal cells and tissues is a major challenge due to the very low abundance of these mutations, which are essentially only detectable in clonal outgrowths, such as tumors. Previously we developed Structural Variant Search (SVS) – an NGS-based assay for the quantitative detection of somatic GSVs in normal cells. Using an improved version of SVS we now demonstrate that the same dose of the anti-cancer drug bleomycin induces about 5 times more somatic GSVs in quiescent primary human fibroblasts than in proliferating cells. GVS induction in non-dividing, normal cells was subsequently confirmed in vivo by demonstrating that a single dose of bleomycin leads to a significant increase of GSV frequency in mouse liver and heart, two postmitotic tissues. Our findings suggest that normal non-cycling differentiated cells may serve as a reservoir of iatrogenically induced mutations. These results provide more insight into the possible molecular mechanisms that underlie late-life morbidities in cancer survivors exposed to chemotherapy.

The precision prevention and therapy of HPV-related cervical cancer: new concepts and clinical implications

Cervical cancer is the third most common cancer in women worldwide, with concepts and knowledge about its prevention and treatment evolving rapidly. Human papillomavirus (HPV) has been identified as a major factor that leads to cervical cancer, although HPV infection alone cannot cause the disease. In fact, HPV-driven cancer is a small probability event because most infections are transient and could be cleared spontaneously by host immune system. With persistent HPV infection, decades are required for progression to cervical cancer. Therefore, this long time window provides golden opportunity for clinical intervention, and the fundament here is to elucidate the carcinogenic pattern and applicable targets during HPV-host interaction. In this review, we discuss the key factors that contribute to the persistence of HPV and cervical carcinogenesis, emerging new concepts and technologies for cancer interventions, and more urgently, how these concepts and technologies might lead to clinical precision medicine which could provide prediction, prevention, and early treatment for patients.

Essential Role of BRCA2 in Ovarian Development and Function

The causes of ovarian dysgenesis remain incompletely understood. Two sisters with XX ovarian dysgenesis carried compound heterozygous truncating mutations in the BRCA2 gene that led to reduced BRCA2 protein levels and an impaired response to DNA damage, which resulted in chromosomal breakage and the failure of RAD51 to be recruited to double-stranded DNA breaks. The sisters also had microcephaly, and one sister was in long-term remission from leukemia, which had been diagnosed when she was 5 years old. Drosophila mutants that were null for an orthologue of BRCA2 were sterile, and gonadal dysgenesis was present in both sexes. These results revealed a new role for BRCA2 and highlight the importance to ovarian development of genes that are critical for recombination during meiosis. (Funded by the Israel Science Foundation and others.).

Somatic Mutagenesis in Mammals and Its Implications for Human Disease and Aging

DNA mutations as a consequence of errors during DNA damage repair, replication, or mitosis are the substrate for evolution. In multicellular organisms, mutations can occur in the germline and also in somatic tissues, where they are associated with cancer and other chronic diseases and possibly with aging. Recent advances in high-throughput sequencing have made it relatively easy to study germline de novo mutations, but in somatic cells, the vast majority of mutations are low-abundant and can be detected only in clonal lineages, such as tumors, or single cells. Here we review recent results on somatic mutations in normal human and animal tissues with a focus on their possible functional consequences.

The Swr1 chromatin-remodeling complex prevents genome instability induced by replication fork progression defects

Genome instability is associated with tumorigenesis. Here, we identify a role for the histone Htz1, which is deposited by the Swr1 chromatin-remodeling complex (SWR-C), in preventing genome instability in the absence of the replication fork/replication checkpoint proteins Mrc1, Csm3, or Tof1. When combined with deletion of SWR1 or HTZ1, deletion of MRC1, CSM3, or TOF1 or a replication-defective mrc1 mutation causes synergistic increases in gross chromosomal rearrangement (GCR) rates, accumulation of a broad spectrum of GCRs, and hypersensitivity to replication stress. The double mutants have severe replication defects and accumulate aberrant replication intermediates. None of the individual mutations cause large increases in GCR rates; however, defects in MRC1, CSM3 or TOF1 cause activation of the DNA damage checkpoint and replication defects. We propose a model in which Htz1 deposition and retention in chromatin prevents transiently stalled replication forks that occur in mrc1, tof1, or csm3 mutants from being converted to DNA double-strand breaks that trigger genome instability.

Experimental Induction of Genome Chaos

Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.

Pathways and Mechanisms that Prevent Genome Instability in Saccharomyces cerevisiae

Genome rearrangements result in mutations that underlie many human diseases, and ongoing genome instability likely contributes to the development of many cancers. The tools for studying genome instability in mammalian cells are limited, whereas model organisms such as Saccharomyces cerevisiae are more amenable to these studies. Here, we discuss the many genetic assays developed to measure the rate of occurrence of Gross Chromosomal Rearrangements (called GCRs) in S. cerevisiae. These genetic assays have been used to identify many types of GCRs, including translocations, interstitial deletions, and broken chromosomes healed by de novo telomere addition, and have identified genes that act in the suppression and formation of GCRs. Insights from these studies have contributed to the understanding of pathways and mechanisms that suppress genome instability and how these pathways cooperate with each other. Integrated models for the formation and suppression of GCRs are discussed.

The number of key carcinogenic events can be predicted from cancer incidence

The widely accepted multiple-hit hypothesis of carcinogenesis states that cancers arise after several successive events. However, no consensus has been reached on the quantity and nature of these events, although “driver” mutations or epimutations are considered the most probable candidates. By using the largest publicly available cancer incidence statistics (20 million cases), I show that incidence of 20 most prevalent cancer types in relation to patients’ age closely follows the Erlang probability distribution (R² = 0.9734–0.9999). The Erlang distribution describes the probability y of k independent random events occurring by the time x, but not earlier or later, with events happening on average every b time intervals. This fits well with the multiple-hit hypothesis and potentially allows to predict the number k of key carcinogenic events and the average time interval b between them, for each cancer type. Moreover, the amplitude parameter A likely predicts the maximal populational susceptibility to a given type of cancer. These parameters are estimated for 20 most common cancer types and provide numerical reference points for experimental research on cancer development.

Tandem duplications lead to novel expression patterns through exon shuffling in Drosophila yakuba

One common hypothesis to explain the impacts of tandem duplications is that whole gene duplications commonly produce additive changes in gene expression due to copy number changes. Here, we use genome wide RNA-seq data from a population sample of Drosophila yakuba to test this ‘gene dosage’ hypothesis. We observe little evidence of expression changes in response to whole transcript duplication capturing 5′ and 3′ UTRs. Among whole gene duplications, we observe evidence that dosage sharing across copies is likely to be common. The lack of expression changes after whole gene duplication suggests that the majority of genes are subject to tight regulatory control and therefore not sensitive to changes in gene copy number. Rather, we observe changes in expression level due to both shuffling of regulatory elements and the creation of chimeric structures via tandem duplication. Additionally, we observe 30 de novo gene structures arising from tandem duplications, 23 of which form with expression in the testes. Thus, the value of tandem duplications is likely to be more intricate than simple changes in gene dosage. The common regulatory effects from chimeric gene formation after tandem duplication may explain their contribution to genome evolution.

The enclosed work shows that whole gene duplications rarely affect gene expression, in contrast to widely held views that the adaptive value of duplicate genes is related to additive changes in gene expression due to gene copy number. We further explain how tandem duplications that create shuffled gene structures can force upregulation of gene sequences, de novo gene creation, and multifold changes in transcript levels. These results show that tandem duplications can produce new genes that are a source of immediate novelty associated with more extreme expression changes than previously suggested by theory. Further, these gene expression changes are a potential source of both beneficial and pathogenic mutations, immediately relevant to clinical and medical genetics in humans and other metazoans.

Order from clutter: selective interactions at mammalian replication origins

Mammalian chromosome duplication progresses in a precise order and is subject to constraints that are often relaxed in developmental disorders and malignancies. Molecular information about the regulation of DNA replication at the chromatin level is lacking because protein complexes that initiate replication seem to bind chromatin indiscriminately. High-throughput sequencing and mathematical modelling have yielded detailed genome-wide replication initiation maps. Combining these maps and models with functional genetic analyses suggests that distinct DNA-protein interactions at subgroups of replication initiation sites (replication origins) modulate the ubiquitous replication machinery and supports an emerging model that delineates how indiscriminate DNA-binding patterns translate into a consistent, organized replication programme.

GeneBreak: detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes

Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. 'GeneBreak' is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, 'GeneBreak' collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, 'GeneBreak', is implemented in R ( www.cran.r-project.org) and is available from Bioconductor ( www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).

GeneBreak: detection of recurrent DNA copy number aberration-associated chromosomal breakpoints within genes

Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. 'GeneBreak' is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, 'GeneBreak' collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, 'GeneBreak', is implemented in R ( www.cran.r-project.org) and is available from Bioconductor ( www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).

Novel Somatic Copy Number Alteration Identified for Cervical Cancer in the Mexican American Population

Cervical cancer affects millions of Americans, but the rate for cervical cancer in the Mexican American is approximately twice that for non-Mexican Americans. The etiologies of cervical cancer are still not fully understood. A number of somatic mutations, including several copy number alterations (CNAs), have been identified in the pathogenesis of cervical carcinomas in non-Mexican Americans. Thus, the purpose of this study was to investigate CNAs in association with cervical cancer in the Mexican American population. We conducted a pilot study of genome-wide CNA analysis using 2.5 million markers in four diagnostic groups: reference (n = 125), low grade dysplasia (cervical intraepithelial neoplasia (CIN)-I, n = 4), high grade dysplasia (CIN-II and -III, n = 5) and invasive carcinoma (squamous cell carcinoma (SCC), n = 5) followed by data analyses using Partek. We observed a statistically-significant difference of CNA burden between case and reference groups of different sizes (>100 kb, 10-100 kb and 1-10 kb) of CNAs that included deletions and amplifications, e.g., a statistically-significant difference of >100 kb deletions was observed between the reference (6.6%) and pre-cancer and cancer (91.3%) groups. Recurrent aberrations of 98 CNA regions were also identified in cases only. However, none of the CNAs have an impact on cancer progression. A total of 32 CNA regions identified contained tumor suppressor genes and oncogenes. Moreover, the pathway analysis revealed endometrial cancer and estrogen signaling pathways associated with this cancer (p < 0.05) using Kyoto Encyclopedia of Genes and Genomes (KEGG). This is the first report of CNAs identified for cervical cancer in the U.S. Latino population using high density markers. We are aware of the small sample size in the study. Thus, additional studies with a larger sample are needed to confirm the current findings.

A genetic network that suppresses genome rearrangements in Saccharomyces cerevisiae and contains defects in cancers

Gross chromosomal rearrangements (GCRs) play an important role in human diseases, including cancer. The identity of all Genome Instability Suppressing (GIS) genes is not currently known. Here multiple Saccharomyces cerevisiae GCR assays and query mutations were crossed into arrays of mutants to identify progeny with increased GCR rates. One hundred eighty two GIS genes were identified that suppressed GCR formation. Another 438 cooperatively acting GIS genes were identified that were not GIS genes, but suppressed the increased genome instability caused by individual query mutations. Analysis of TCGA data using the human genes predicted to act in GIS pathways revealed that a minimum of 93% of ovarian and 66% of colorectal cancer cases had defects affecting one or more predicted GIS gene. These defects included loss-of-function mutations, copy-number changes associated with reduced expression, and silencing. In contrast, acute myeloid leukaemia cases did not appear to have defects affecting the predicted GIS genes.

Here, Richard Kolodner and colleagues use assays in Saccharomyces cerevisiae to identify 182 genetic modifiers of gross chromosomal rearrangements (GCRs). They also compared these Genome Instability Suppressing (GIS) genes and pathways in human cancer genome, and found many ovarian and colorectal cancer cases have alterations to GIS pathways.

Genome Editing of Structural Variations: Modeling and Gene Correction

The analysis of chromosomal structural variations (SVs), such as inversions and translocations, was made possible by the completion of the human genome project and the development of genome-wide sequencing technologies. SVs contribute to genetic diversity and evolution, although some SVs can cause diseases such as hemophilia A in humans. Genome engineering technology using programmable nucleases (e.g., ZFNs, TALENs, and CRISPR/Cas9) has been rapidly developed, enabling precise and efficient genome editing for SV research. Here, we review advances in modeling and gene correction of SVs, focusing on inversion, translocation, and nucleotide repeat expansion.

Whole-Genome Sequencing Reveals Diverse Models of Structural Variations in Esophageal Squamous Cell Carcinoma

Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs.

Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach

Cancer, like many common disorders, has a complex etiology, often with a strong genetic component and with multiple environmental factors contributing to susceptibility. A considerable number of genomic variants have been previously reported to be causative of, or associated with, an increased risk for various types of cancer. Here, we adopted a next-generation sequencing approach in 11 members of two families of Greek descent to identify all genomic variants with the potential to predispose family members to cancer. Cross-comparison with data from the Human Gene Mutation Database identified a total of 571 variants, from which 47 % were disease-associated polymorphisms, 26 % disease-associated polymorphisms with additional supporting functional evidence, 19 % functional polymorphisms with in vitro/laboratory or in vivo supporting evidence but no known disease association, 4 % putative disease-causing mutations but with some residual doubt as to their pathological significance, and 3 % disease-causing mutations. Subsequent analysis, focused on the latter variant class most likely to be involved in cancer predisposition, revealed two variants of prime interest, namely MSH2 c.2732T>A (p.L911R) and BRCA1 c.2955delC, the first of which is novel. KMT2D c.13895delC and c.1940C>A variants are additionally reported as incidental findings. The next-generation sequencing-based family genomics approach described herein has the potential to be applied to other types of complex genetic disorder in order to identify variants of potential pathological significance.

High-throughput sequencing in mutation detection: A new generation of genotoxicity tests?

The advent of next generation sequencing (NGS) technology has provided the means to directly analyze the genetic material in primary cells or tissues of any species in a high throughput manner for mutagenic effects of potential genotoxic agents. In principle, direct, genome-wide sequencing of human primary cells and/or tissue biopsies would open up opportunities to identify individuals possibly exposed to mutagenic agents, thereby replacing current risk assessment procedures based on surrogate markers and extrapolations from animal studies. NGS-based tests can also precisely characterize the mutation spectra induced by genotoxic agents, improving our knowledge of their mechanism of action. Thus far, NGS has not been widely employed in genetic toxicology due to the difficulties in measuring low-abundant somatic mutations. Here, we review different strategies to employ NGS for the detection of somatic mutations in a cost-effective manner and discuss the potential applicability of these methods in testing the mutagenicity of genotoxic agents.

Lymphovascular invasion and histologic grade are associated with specific genomic profiles in invasive carcinomas of the breast

Lymphovascular invasion (LVI) and histologic grade are clinical parameters of high prognostic value in breast cancer and indicate the level of tumor aggressiveness. Many studies have focused on the association of breast cancer subtypes with gene expression and chromosomal profiles, but considerably less genomic information is available regarding traditional prognostic factors such as histologic grade and LVI. We studied by array-CGH a group of 57 invasive ductal carcinomas of the breast to outline the DNA copy number aberration (CNA) profile linked to high histologic grades and LVI. Selected CNAs were validated using real-time quantitative PCR (qPCR). Furthermore, gene expression analysis was performed in a subset of 32 of these tumors, and findings were integrated with array-CGH data. Our findings indicated an accumulation of genomic alterations in high-grade breast tumors compared to low-grade samples. Grade III tumors showed higher number of CNAs and larger aberrations than low-grade tumors and displayed a wide range of chromosomal aberrations, which were mainly 5p, 8q, 10p, 17q12, and 19 gains, and 3p, 4, 5q proximal, 9p, 11p, 18q, and 21 losses. The presence of LVI, a well-established prognostic marker, was not significantly associated with increased genomic instability in comparison to breast tumors negative for LVI, considering the total number of chromosomal alterations. However, a slightly increase in the frequency of specific alterations could be detected in LVI-positive group, such as gains at 5p, 16p, 17q12, and 19, and losses at 8p, 11q, 18q, and 21. Three newly reported small-scale rearrangements were detected in high-risk tumors (LVI-positive grade III) harboring putative breast cancer genes (amplicons at 4q13.3 and 11p11.2, and a deletion at 12p12.3). Furthermore, gene expression analysis uncovered networks highlighting S100A8, MMP1, and MED1 as promising candidate genes involved in high-grade and LVI-positive tumors. In summary, a group of genomic regions could be associated with high-risk tumors, and expression analysis pinpointed candidate genes deserving further investigation. The data has shed some light on the molecular players involved in two highly relevant prognostic factors and may further add to the understanding of the mechanisms of breast cancer aggressiveness.

Functional chromatin features are associated with structural mutations in cancer

BACKGROUND

Structural mutations (SMs) play a major role in cancer development. In some cancers, such as breast and ovarian, DNA double-strand breaks (DSBs) occur more frequently in transcribed regions, while in other cancer types such as prostate, there is a consistent depletion of breakpoints in transcribed regions. Despite such regularity, little is understood about the mechanisms driving these effects. A few works have suggested that protein binding may be relevant, e.g. in studies of androgen receptor binding and active chromatin in specific cell types. We hypothesized that this behavior might be general, i.e. that correlation between protein-DNA binding (and open chromatin) and breakpoint locations is common across divergent cancers.

RESULTS

We investigated this hypothesis by comprehensively analyzing the relationship among 457 ENCODE protein binding ChIP-seq experiments, 125 DnaseI and 24 FAIRE experiments, and 14,600 SMs from 8 diverse cancer datasets covering 147 samples. In most cancers, including breast and ovarian, we found enrichment of protein binding and open chromatin in the vicinity of SM breakpoints at distances up to 200 kb. Furthermore, for all cancer types we observed an enhanced enrichment in regions distant from genes when compared to regions proximal to genes, suggesting that the SM-induction mechanism is independent from the bias of DSBs to occur near transcribed regions. We also observed a stronger effect for sites with more than one protein bound.

CONCLUSIONS

Protein binding and open chromatin state are associated with nearby SM breakpoints in many cancer datasets. These observations suggest a consistent mechanism underlying SM locations across different cancers.

Activation of transcription and retrotransposition of a novel retroelement, Steamer, in neoplastic hemocytes of the mollusk Mya arenaria

Bivalve mollusks of the North Atlantic, most prominently the soft shell clam Mya arenaria, are afflicted with an epidemic transmissible disease of the circulatory system closely resembling leukemia. The disease is characterized by a dramatic expansion of blast-like cells in the hemolymph with high mitotic index. Examination of hemolymph of diseased clams revealed high levels of reverse transcriptase activity, the hallmark of retroviruses and retroelements. By deep sequencing of RNAs from hemolymph, we identified transcripts of a novel retroelement, here named Steamer. The DNA of the element is marked by long terminal repeats and encodes a single large protein with similarity to mammalian retroviral Gag-Pol proteins. Steamer mRNA levels were specifically elevated in diseased hemocytes, and high expression was correlated with disease status. DNA copy number per genome was present at enormously high levels in diseased hemocytes, indicative of extensive reverse transcription and retrotransposition. Steamer activation in M. arenaria is an example of a catastrophic induction of genetic instability that may initiate or advance the course of leukemia.

Systems consequences of amplicon formation in human breast cancer

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.

RAG2 mutants alter DSB repair pathway choice in vivo and illuminate the nature of 'alternative NHEJ'

DNA double-stranded breaks (DSBs) can be repaired by several mechanisms, including classical NHEJ (c-NHEJ) and a poorly defined, error-prone process termed alternative NHEJ (a-NHEJ). How cells choose between these alternatives to join physiologic DSBs remains unknown. Here, we show that deletion of RAG2's C-terminus allows a-NHEJ to repair RAG-mediated DSBs in developing lymphocytes from both c-NHEJ-proficient and c-NHEJ-deficient mice, demonstrating that the V(D)J recombinase influences repair pathway choice in vivo. Analysis of V(D)J junctions revealed that, contrary to expectation, junctional characteristics alone do not reliably distinguish between a-NHEJ and c-NHEJ. These data suggest that a-NHEJ is not necessarily mutagenic, and may be more prevalent than previously appreciated. Whole genome sequencing of a lymphoma arising in a p53^−/− mouse bearing a C-terminal RAG2 truncation reveals evidence of a-NHEJ and also of aberrant recognition of DNA sequences resembling RAG recognition sites.

Landscape of standing variation for tandem duplications in Drosophila yakuba and Drosophila simulans

We have used whole genome paired-end Illumina sequence data to identify tandem duplications in 20 isofemale lines of Drosophila yakuba and 20 isofemale lines of D. simulans and performed genome wide validation with PacBio long molecule sequencing. We identify 1,415 tandem duplications that are segregating in D. yakuba as well as 975 duplications in D. simulans, indicating greater variation in D. yakuba. Additionally, we observe high rates of secondary deletions at duplicated sites, with 8% of duplicated sites in D. simulans and 17% of sites in D. yakuba modified with deletions. These secondary deletions are consistent with the action of the large loop mismatch repair system acting to remove polymorphic tandem duplication, resulting in rapid dynamics of gain and loss in duplicated alleles and a richer substrate of genetic novelty than has been previously reported. Most duplications are present in only single strains, suggesting that deleterious impacts are common. Drosophila simulans shows larger numbers of whole gene duplications in comparison to larger proportions of gene fragments in D. yakuba. Drosophila simulans displays an excess of high-frequency variants on the X chromosome, consistent with adaptive evolution through duplications on the D. simulans X or demographic forces driving duplicates to high frequency. We identify 78 chimeric genes in D. yakuba and 38 chimeric genes in D. simulans, as well as 143 cases of recruited noncoding sequence in D. yakuba and 96 in D. simulans, in agreement with rates of chimeric gene origination in D. melanogaster. Together, these results suggest that tandem duplications often result in complex variation beyond whole gene duplications that offers a rich substrate of standing variation that is likely to contribute both to detrimental phenotypes and disease, as well as to adaptive evolutionary change.

Feasibility of whole RNA sequencing from single-cell mRNA amplification

Single-cell sampling with RNA-seq analysis plays an important role in reference laboratory; cytogenomic diagnosis for specimens on glass-slides or rare cells in circulating blood for tumor and genetic diseases; measurement of sensitivity and specificity in tumor-tissue genomic analysis with mixed-cells; mechanism analysis of differentiation and proliferation of cancer stem cell for academic purpose. Our single- cell RNA-seq technique shows that fragments were 250-450 bp after fragmentation, amplification, and adapter addition. There were 11.6 million reads mapped in raw sequencing reads (19.6 million). The numbers of mapped genes, mapped transcripts, and mapped exons were 31,332, 41,210, and 85,786, respectively. All QC results demonstrated that RNA-seq techniques could be used for single-cell genomic performance. Analysis of the mapped genes showed that the number of genes mapped by RNA-seq (6767 genes) was much higher than that of differential display (288 libraries) among similar specimens which we have developed and published. The single-cell RNA-seq can detect gene splicing using different subtype TGF-beta analysis. The results from using Q-rtPCR tests demonstrated that sensitivity is 76% and specificity is 55% from single-cell RNA-seq technique with some gene expression missing (2/8 genes). However, it will be feasible to use RNA-seq techniques to contribute to genomic medicine at single-cell level.

Detection of candidate tumor driver genes using a fully integrated Bayesian approach

DNA copy number alterations (CNAs), including amplifications and deletions, can result in significant changes in gene expression and are closely related to the development and progression of many diseases, especially cancer. For example, CNA-associated expression changes in certain genes (called candidate tumor driver genes) can alter the expression levels of many downstream genes through transcription regulation and cause cancer. Identification of such candidate tumor driver genes leads to discovery of novel therapeutic targets for personalized treatment of cancers. Several approaches have been developed for this purpose by using both copy number and gene expression data. In this study, we propose a Bayesian approach to identify candidate tumor driver genes, in which the copy number and gene expression data are modeled together, and the dependency between the two data types is modeled through conditional probabilities. The proposed joint modeling approach can identify CNA and differentially expressed genes simultaneously, leading to improved detection of candidate tumor driver genes and comprehensive understanding of underlying biological processes. We evaluated the proposed method in simulation studies, and then applied to a head and neck squamous cell carcinoma data set. Both simulation studies and data application show that the joint modeling approach can significantly improve the performance in identifying candidate tumor driver genes, when compared with other existing approaches.