Novel patterns of genome rearrangement and their association with survival in breast cancer

Molecular and functional profiling of chemotolerant cells unveils nucleoside metabolism-dependent vulnerabilities in medulloblastoma

Chemotherapy resistance is considered one of the main causes of tumor relapse, still challenging researchers for the identification of the molecular mechanisms sustaining its emergence. Here, we setup and characterized chemotherapy-resistant models of Medulloblastoma (MB), one of the most lethal pediatric brain tumors, to uncover targetable vulnerabilities associated to their resistant phenotype. Integration of proteomic, transcriptomic and kinomic data revealed a significant deregulation of several pathways in resistant MB cells, converging to cell metabolism, RNA/protein homeostasis, and immune response, eventually impacting on patient outcome. Moreover, resistant MB cell response to a large library of compounds through a high-throughput screening (HTS), highlighted nucleoside metabolism as a relevant vulnerability of chemotolerant cells, with peculiar antimetabolites demonstrating increased efficacy against them and even synergism with conventional chemotherapeutics. Our results suggest that drug-resistant cells significantly rewire multiple cellular processes, allowing their adaptation to a chemotoxic environment, nevertheless exposing alternative actionable susceptibilities for their specific targeting.

Deciphering complex breakage-fusion-bridge genome rearrangements with Ambigram

Breakage-fusion-bridge (BFB) is a complex rearrangement that leads to tumor malignancy. Existing models for detecting BFBs rely on the ideal BFB hypothesis, ruling out the possibility of BFBs entangled with other structural variations, that is, complex BFBs. We propose an algorithm Ambigram to identify complex BFB and reconstruct the rearranged structure of the local genome during the cancer subclone evolution process. Ambigram handles data from short, linked, long, and single-cell sequences, and optical mapping technologies. Ambigram successfully deciphers the gold- or silver-standard complex BFBs against the state-of-the-art in multiple cancers. Ambigram dissects the intratumor heterogeneity of complex BFB events with single-cell reads from melanoma and gastric cancer. Furthermore, applying Ambigram to liver and cervical cancer data suggests that the BFB mechanism may mediate oncovirus integrations. BFB also exists in noncancer genomics. Investigating the complete human genome reference with Ambigram suggests that the BFB mechanism may be involved in two genome reorganizations of Homo Sapiens during evolution. Moreover, Ambigram discovers the signals of recurrent foldback inversions and complex BFBs in whole genome data from the 1000 genome project, and congenital heart diseases, respectively.

Genomic landscapes of ovarian clear cell carcinoma from latin countries reveal aberrations linked to survival and progression

BACKGROUND

Ovarian clear cell carcinomas (OCCCs) are rare, aggressive and chemoresistant tumors. Geographical and ethnic differences in the incidence of OCCC have been reported with a higher incidence in Asiatic countries. There is a paucity of information regarding OCCC in Latin America (LA) and other countries.

METHODS

Here, we characterized two cohorts of 33 patients with OCCC from LA (24 from Brazil and 9 from Costa Rica) and a cohort of 27 patients from Spain. Genomic analysis was performed for 26 OCCC using the OncoScan platform. Tumors were classified according to their genomic landscapes into subgroups. Clinical parameters were related to the frequency of genomic aberrations.

RESULTS

The median overall survival (OS) was not significantly different between the cohorts. Genomic landscapes were characterized by different homologous recombination deficiency (HRD) levels. No difference in the distribution of genomic landscapes profiles was detected between patients from the different cohorts. OCCCs with MYC-amplified tumors harboring a concomitant loss of a region in chromosome 13q12-q13 that includes the BRCA2 gene had the longest OS. In contrast, patients carrying a high number (> 30) of total copy number (CN) aberrations with no concomitant alterations in MYC and BRCA2 genes presented the shortest OS. Furthermore, amplification of the ASH1L gene was also associated with a shorter OS. Initial-stage OCCCs with early progression were characterized by gains in the JNK1 and MKL1 genes.

CONCLUSIONS

Our results provide new data from understudied OCCC populations and reveal new potential markers for OCCCs.

ERα-associated translocations underlie oncogene amplifications in breast cancer

Focal copy-number amplification is an oncogenic event. Although recent studies have revealed the complex structure1-3 and the evolutionary trajectories4 of oncogene amplicons, their origin remains poorly understood. Here we show that focal amplifications in breast cancer frequently derive from a mechanism-which we term translocation-bridge amplification-involving inter-chromosomal translocations that lead to dicentric chromosome bridge formation and breakage. In 780 breast cancer genomes, we observe that focal amplifications are frequently connected to each other by inter-chromosomal translocations at their boundaries. Subsequent analysis indicates the following model: the oncogene neighbourhood is translocated in G1 creating a dicentric chromosome, the dicentric chromosome is replicated, and as dicentric sister chromosomes segregate during mitosis, a chromosome bridge is formed and then broken, with fragments often being circularized in extrachromosomal DNAs. This model explains the amplifications of key oncogenes, including ERBB2 and CCND1. Recurrent amplification boundaries and rearrangement hotspots correlate with oestrogen receptor binding in breast cancer cells. Experimentally, oestrogen treatment induces DNA double-strand breaks in the oestrogen receptor target regions that are repaired by translocations, suggesting a role of oestrogen in generating the initial translocations. A pan-cancer analysis reveals tissue-specific biases in mechanisms initiating focal amplifications, with the breakage-fusion-bridge cycle prevalent in some and the translocation-bridge amplification in others, probably owing to the different timing of DNA break repair. Our results identify a common mode of oncogene amplification and propose oestrogen as its mechanistic origin in breast cancer.

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications

As the field of translational ‘omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of ‘omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.

Loss of genes in chromosome arms 5q and 16q in breast cancer

INTRODUCTION

Losses of genetic material from chromosomes 5q and 16q commonly occur in sub-sets of breast cancer. Their significance from a pathophysiologic point of view is not well-defined.

METHODS

This study uses publicly available genomic data from extensive breast cancer datasets to define the landscape of losses in chromosomal arms 5q and 16q in the two sub-types of breast cancer they most commonly occur, basal-like and luminal A cancers, respectively.

RESULTS

It is shown that dozens of genes from these chromosomal arms are putatively hemi-deleted in few samples each. No individual gene from either 5q or 16q shows an incidence of deep deletion above 10% in the cohorts with basal-like and luminal A cancers or in the whole cohorts. A few tumor suppressor genes are deleted in a small number of samples, less than 5% in each cohort. Losses of 5q or 16q confer no survival advantage in either the basal-like or the luminal A cohorts from TCGA that harbor them.

CONCLUSION

Results suggest that there are no individual genes in chromosomes 5q and 16q whose loss can be implicated in a dominant pathophysiologic sequence of events in breast cancer or its sub-sets.

Cancer Genomic Rearrangements and Copy Number Alterations from Errors in Cell Division

Analysis of cancer genomes has shown that a large fraction of chromosomal changes originate from catastrophic events including whole-genome duplication, chromothripsis, breakage-fusion-bridge cycles, and chromoplexy. Through sophisticated computational analysis of cancer genomes and experimental recapitulation of these catastrophic alterations, we have gained significant insights into the origin, mechanism, and evolutionary dynamics of cancer genome complexity. In this review, we summarize this progress and survey the major unresolved questions, with particular emphasis on the relative contributions of chromosome fragmentation and DNA replication errors to complex chromosomal alterations.

Early Breast Cancer Evolution by Autosomal Broad Copy Number Alterations

The availability of comprehensive genomic datasets across patient populations enables the application of novel methods for reconstructing tumor evolution within individual patients. To this end, we propose studying autosomal broad copy number alterations (CNAs) as a framework to better understand early tumor evolution. We compared the broad CNAs and somatic mutations of patients with 1 to 10 autosomal broad CNAs against the full set of patients, using data from The Cancer Genome Atlas breast cancer project. We reveal here that the frequency of a chromosome arm obtaining a broad CNA and a genome acquiring somatic mutations changes as autosomal broad CNAs accumulate. Therefore, we propose that the number of autosomal broad CNAs is an important characteristic of breast tumors that needs to be taken into consideration when studying breast tumors. To investigate this idea more in-depth, we next studied the frequency that specific chromosome arms acquire broad CNAs in patients with 1 to 10 broad CNAs. With this process, we identified the broad CNAs that exhibit the fastest rates of accumulation across all patients. This finding suggests a likely order of occurrence of these alterations in patients, which is apparent when we consider a subset of patients with few broad CNAs. Here, we lay the foundation for future studies to build upon our findings and use autosomal broad CNAs as a method to monitor breast tumor progression in vivo to further our understanding of how early tumor evolution unfolds.

Breast carcinomas with osteoclast-like giant cells: a comprehensive clinico-pathological and molecular portrait and evidence of RANK-L expression

Breast carcinomas (BC) with osteoclast-like giant cells (OGC) are rare. Despite their distinct stromal features, their molecular characteristics remain unknown. Here, we report comprehensive clinico-pathological and molecular findings for 27 patients diagnosed with BC-OGC at Institut Curie between 2000 and 2021. Seventeen (63%) cases were invasive carcinomas of no special type (IC NST) with OGC (OGC-IC NST), four (15%) were mixed or multifocal cases with and without OGC (OGC-Mixed), and six (22%) were metaplastic carcinomas with OGC (OGC-MC). All OGC-IC NST and OGC-Mixed cases were ER+ HER2- tumors (most being luminal A based on transcriptomic subtyping, when available), while all OGC-MC were triple-negative. The median age at diagnosis was 46, 45 and 62 years for OGC-IC NST, OGC-Mixed and OGC-MC, respectively. Three patients developed distant metastases (one OGC-IC NST, two OGC-Mixed), one of whom died of metastatic disease (OGC-Mixed), and one other patient died of locally advanced disease (OGC-MC). Histopathological evaluation comparing 13 OGC-IC NST and 19 control IC NST without OGC confirmed that OGC-IC NST showed significantly higher density of vessels (by CD34 immunohistochemistry (IHC)), iron deposits (Perls stain), and CD68 and CD163-positive cell infiltrates. Genomic findings for nine OGC-IC NST and four OGC-MC were consistent with the underlying histologic subtype, including activating alterations of the PI3K/AKT/mTOR pathway in 7/13 cases. Using RNA-seq data, differential gene expression analysis between OGC-IC NST (n = 7) and control IC NST without OGC (n = 7) revealed significant overexpression of TNFSF11 (RANK-L), TNFRSF11A (RANK), CSF1 (M-CSF), CSF1R, and genes encoding osteoclastic enzymes (MMP9, ACP5, CTSK, CTSB) in OGC-IC NST, while OPG (osteoprotegerin) was underexpressed. We also confirmed for the first time RANK-L expression in BC with OGC by IHC (seen in 15 out of 16 cases, and only in 2 of 16 controls without OGC). These findings could offer a rationale for further investigating RANK-L as a therapeutic target in BC with OGC.

Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. Using whole-genome sequencing data of the pediatric tumor neuroblastoma, we here identified a type of amplification, termed 'seismic amplification', that is characterized by multiple rearrangements and discontinuous copy number levels. Overall, seismic amplifications occurred in 9.9% (274 of 2,756) of cases across 38 cancer types, and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification showed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and overexpression in a substantial fraction of human malignancies.

Phenotypic Heterogeneity of Triple-Negative Breast Cancer Mediated by Epithelial-Mesenchymal Plasticity

Triple-negative breast cancer (TNBC) is a subtype of breast carcinoma known for its unusually aggressive behavior and poor clinical outcome. Besides the lack of molecular targets for therapy and profound intratumoral heterogeneity, the relatively quick overt metastatic spread remains a major obstacle in effective clinical management. The metastatic colonization of distant sites by primary tumor cells is affected by the microenvironment, epigenetic state of particular subclones, and numerous other factors. One of the most prominent processes contributing to the intratumoral heterogeneity is an epithelial-mesenchymal transition (EMT), an evolutionarily conserved developmental program frequently hijacked by tumor cells, strengthening their motile and invasive features. In response to various intrinsic and extrinsic stimuli, malignant cells can revert the EMT state through the mesenchymal-epithelial transition (MET), a process that is believed to be critical for the establishment of macrometastasis at secondary sites. Notably, cancer cells rarely undergo complete EMT and rather exist in a continuum of E/M intermediate states, preserving high levels of plasticity, as demonstrated in primary tumors and, ultimately, in circulating tumor cells, representing a simplified element of the metastatic cascade. In this review, we focus on cellular drivers underlying EMT/MET phenotypic plasticity and its detrimental consequences in the context of TNBC cancer.

The Genomic Landscape of Lobular Breast Cancer

Invasive lobular carcinoma (ILC) is the second most common breast cancer histologic subtype, accounting for approximately 15% of all breast cancers. It is only recently that its unique biology has been assessed in high resolution. Here, we present a meta-analysis of ILC sequencing datasets, to provide a long-awaited ILC-specific resource, and to confirm the prognostic value and strength of association between a number of clinico-pathology features and genomics in this special tumour type. We consider panel (n = 684), whole exome (n = 215) and whole genome sequencing data (n = 48), and review histology of The Cancer Genome Atlas cases to assign grades and determine whether the ILC is of classic type or a variant, such as pleomorphic, prior to performing statistical analyses. We demonstrate evidence of considerable genomic heterogeneity underlying a broadly homogeneous tumour type (typically grade 2, estrogen receptor (ER)-positive); with genomes exhibiting few somatic mutations or structural alterations, genomes with a hypermutator phenotype, and tumours with highly rearranged genomes. We show that while CDH1 (E-cadherin) and PIK3CA mutations do not significantly impact survival, overall survival is significantly poorer for patients with a higher tumour mutation burden; this is also true for grade 3 tumours, and those carrying a somatic TP53 mutation (and these cases were more likely to be ER-negative). Taken together, we have compiled a meta-dataset of ILC with molecular profiling, and our analyses show that the genomic landscape significantly impacts the tumour's variable natural history and overall survival of ILC patients.

Aberrations of Chromosomes 1 and 16 in Breast Cancer: A Framework for Cooperation of Transcriptionally Dysregulated Genes

Derivative chromosome der(1;16), isochromosome 1q, and deleted 16q-producing arm-level 1q-gain and/or 16q-loss-are recurrent cytogenetic abnormalities in breast cancer, but their exact role in determining the malignant phenotype is still largely unknown. We exploited The Cancer Genome Atlas (TCGA) data to generate and analyze groups of breast invasive carcinomas, called 1,16-chromogroups, that are characterized by a pattern of arm-level somatic copy number aberrations congruent with known cytogenetic aberrations of chromosome 1 and 16. Substantial differences were found among 1,16-chromogroups in terms of other chromosomal aberrations, aneuploidy scores, transcriptomic data, single-point mutations, histotypes, and molecular subtypes. Breast cancers with a co-occurrence of 1q-gain and 16q-loss can be distinguished in a "low aneuploidy score" group, congruent to der(1;16), and a "high aneuploidy score" group, congruent to the co-occurrence of isochromosome 1q and deleted 16q. Another three groups are formed by cancers showing separately 1q-gain or 16q-loss or no aberrations of 1q and 16q. Transcriptome comparisons among the 1,16-chromogroups, integrated with functional pathway analysis, suggested the cooperation of overexpressed 1q genes and underexpressed 16q genes in the genesis of both ductal and lobular carcinomas, thus highlighting the putative role of genes encoding gamma-secretase subunits (APH1A, PSEN2, and NCSTN) and Wnt enhanceosome components (BCL9 and PYGO2) in 1q, and the glycoprotein E-cadherin (CDH1), the E3 ubiquitin-protein ligase WWP2, the deubiquitinating enzyme CYLD, and the transcription factor CBFB in 16q. The analysis of 1,16-chromogroups is a strategy with far-reaching implications for the selection of cancer cell models and novel experimental therapies.

Establishing the Clinical Utility of ctDNA Analysis for Diagnosis, Prognosis, and Treatment Monitoring of Retinoblastoma: The Aqueous Humor Liquid Biopsy

Because direct tumor biopsy is prohibited for retinoblastoma (RB), eye-specific molecular biomarkers are not used in clinical practice for RB. Recently, we demonstrated that the aqueous humor (AH) is a rich liquid biopsy source of cell-free tumor DNA. Herein, we detail clinically-relevant molecular biomarkers from the first year of prospective validation data. Seven eyes from 6 RB patients who had AH sampled at diagnosis and throughout therapy with ≥12 months of follow-up were included. Cell-free DNA (cfDNA) from each sample was isolated and sequenced to assess genome-wide somatic copy number alterations (SCNAs), followed by targeted resequencing for pathogenic variants using a RB1 and MYCN custom hybridization panel. Tumoral genomic information was detected in 100% of diagnostic AH samples. Of the seven diagnostic AH samples, 5/7 were positive for RB SCNAs. Mutational analysis identified RB1 variants in 5/7 AH samples, including the 2 samples in which no SCNAs were detected. Two eyes failed therapy and required enucleation; both had poor prognostic biomarkers (chromosome 6p gain or MYCN amplification) present in the AH at the time of diagnosis. In the context of previously established pre-analytical, analytical, and clinical validity, this provides evidence for larger, prospective studies to further establish the clinical utility of the AH liquid biopsy and its applications to precision oncology for RB.

Palindromes in DNA-A Risk for Genome Stability and Implications in Cancer

A palindrome in DNA consists of two closely spaced or adjacent inverted repeats. Certain palindromes have important biological functions as parts of various cis-acting elements and protein binding sites. However, many palindromes are known as fragile sites in the genome, sites prone to chromosome breakage which can lead to various genetic rearrangements or even cell death. The ability of certain palindromes to initiate genetic recombination lies in their ability to form secondary structures in DNA which can cause replication stalling and double-strand breaks. Given their recombinogenic nature, it is not surprising that palindromes in the human genome are involved in genetic rearrangements in cancer cells as well as other known recurrent translocations and deletions associated with certain syndromes in humans. Here, we bring an overview of current understanding and knowledge on molecular mechanisms of palindrome recombinogenicity and discuss possible implications of DNA palindromes in carcinogenesis. Furthermore, we overview the data on known palindromic sequences in the human genome and efforts to estimate their number and distribution, as well as underlying mechanisms of genetic rearrangements specific palindromic sequences cause.

Reconstruction of clone- and haplotype-specific cancer genome karyotypes from bulk tumor samples

Many cancer genomes are extensively rearranged with aberrant chromosomal karyotypes. Deriving these karyotypes from high-throughput DNA sequencing of bulk tumor samples is complicated because most tumors are a heterogeneous mixture of normal cells and subpopulations of cancer cells, or clones, that harbor distinct somatic mutations. We introduce a new algorithm, Reconstructing Cancer Karyotypes (RCK), to reconstruct haplotype-specific karyotypes of one or more rearranged cancer genomes from DNA sequencing data from a bulk tumor sample. RCK leverages evolutionary constraints on the somatic mutational process in cancer to reduce ambiguity in the deconvolution of admixed sequencing data into multiple haplotype-specific cancer karyotypes. RCK models mixtures containing an arbitrary number of derived genomes and allows the incorporation of information both from short-read and long-read DNA sequencing technologies. We compare RCK to existing approaches on 17 primary and metastatic prostate cancer samples. We find that RCK infers cancer karyotypes that better explain the DNA sequencing data and conform to a reasonable evolutionary model. RCK's reconstructions of clone- and haplotype-specific karyotypes will aid further studies of the role of intra-tumor heterogeneity in cancer development and response to treatment. RCK is freely available as open source software.

Circulating MicroRNAs as Prognostic and Therapeutic Biomarkers in Breast Cancer Molecular Subtypes

Breast cancer (BC) is a common and heterogeneous disease, of which six molecular subtypes, characterized by different biological features and clinical outcomes, were described. The identification of additional biomarkers able to further connote and distinguish the different BC subtypes is essential to improve the diagnostic, prognostic and therapeutic strategies in BC patients. MicroRNAs (miRNAs) are short non-coding RNA involved in several physiological and pathological processes, including cancer development and progression. In particular, circulating miRNAs, which can be found in an adequately stable structure in serum/plasma of cancer patients, are emerging as very promising non-invasive biomarkers. Several studies have analyzed the potential role of circulating miRNAs as prognostic and therapeutic markers in BC. In the present review we describe circulating miRNAs, identified as putative biomarker in BC, with special reference to different BC molecular subtypes.

DNA copy number motifs are strong and independent predictors of survival in breast cancer

Somatic copy number alterations are a frequent sign of genome instability in cancer. A precise characterization of the genome architecture would reveal underlying instability mechanisms and provide an instrument for outcome prediction and treatment guidance. Here we show that the local spatial behavior of copy number profiles conveys important information about this architecture. Six filters were defined to characterize regional traits in copy number profiles, and the resulting Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to tumors in four breast cancer cohorts (n = 2919). The derived motifs represent a layer of information that complements established molecular classifications of breast cancer. A score reflecting presence or absence of motifs provided a highly significant independent prognostic predictor. Results were consistent between cohorts. The nonsite-specific occurrence of the detected patterns suggests that CARMA captures underlying replication and repair defects and could have a future potential in treatment stratification.

Translational genomics of ovarian clear cell carcinoma

Ovarian clear cell carcinomas (OCCC) are rare aggressive, chemo-resistant tumours comprising approximately 13% of all epithelial ovarian cancers, which have distinct clinical and molecular features, when compared to other gynaecological malignancies. At present, there are no specific licensed targeted therapies for OCCC, although a number of candidate targets have been identified. This review focuses on recent knowledge underpinning our understanding of the pathogenesis of OCCC including direct and synthetic-lethal therapeutic strategies in particular focussing on ARID1A deficiency. We also discuss current targeted clinical trials and immunotherapeutic approaches.

Morphologic and Genomic Heterogeneity in the Evolution and Progression of Breast Cancer

: Breast cancer is a remarkably complex and diverse disease. Subtyping based on morphology, genomics, biomarkers and/or clinical parameters seeks to stratify optimal approaches for management, but it is clear that every breast cancer is fundamentally unique. Intra-tumour heterogeneity adds further complexity and impacts a patient's response to neoadjuvant or adjuvant therapy. Here, we review some established and more recent evidence related to the complex nature of breast cancer evolution. We describe morphologic and genomic diversity as it arises spontaneously during the early stages of tumour evolution, and also in the context of treatment where the changing subclonal architecture of a tumour is driven by the inherent adaptability of tumour cells to evolve and resist the selective pressures of therapy.

HetRCNA: A Novel Method to Identify Recurrent Copy Number Alternations from Heterogeneous Tumor Samples Based on Matrix Decomposition Framework

A common strategy to discovering cancer associated copy number aberrations (CNAs) from a cohort of cancer samples is to detect recurrent CNAs (RCNAs). Although the previous methods can successfully identify communal RCNAs shared by nearly all tumor samples, detecting subgroup-specific RCNAs and their related subgroup samples from cancer samples with heterogeneity is still invalid for these existing approaches. In this paper, we introduce a novel integrated method called HetRCNA, which can identify statistically significant subgroup-specific RCNAs and their related subgroup samples. Based on matrix decomposition framework with weight constraint, HetRCNA can successfully measure the subgroup samples by coefficients of left vectors with weight constraint and subgroup-specific RCNAs by coefficients of the right vectors and significance test. When we evaluate HetRCNA on simulated dataset, the results show that HetRCNA gives the best performances among the competing methods and is robust to the noise factors of the simulated data. When HetRCNA is applied on a real breast cancer dataset, our approach successfully identifies a bunch of RCNA regions and the result is highly correlated with the results of the other two investigated approaches. Notably, the genomic regions identified by HetRCNA harbor many breast cancer related genes reported by previous researches.

Targeting Metabolic Deregulation Landscapes in Breast Cancer Subtypes

Metabolic deregulation is an emergent hallmark of cancer. Altered patterns of metabolic pathways result in exacerbated synthesis of macromolecules, increased proliferation, and resistance to treatment via alteration of drug processing. In addition, molecular heterogeneity creates a barrier to therapeutic options. In breast cancer, this broad variation in molecular metabolism constitutes, simultaneously, a source of prognostic and therapeutic challenges and a doorway to novel interventions. In this work, we investigated the metabolic deregulation landscapes in breast cancer molecular subtypes. Such landscapes are the regulatory signatures behind subtype-specific metabolic features. n = 735 breast cancer samples of the Luminal A, Luminal B, Her2+, and Basal subtypes, as well as n = 113 healthy breast tissue samples were analyzed. By means of a single-sample-based algorithm, deregulation for all metabolic pathways in every sample was determined. Deregulation levels match almost perfectly with the molecular classification, indicating that metabolic anomalies are closely associated with gene-expression signatures. Luminal B tumors are the most deregulated but are also the ones with higher within-subtype variance. We argued that this variation may underlie the fact that Luminal B tumors usually present the worst prognosis, a high rate of recurrence, and the lowest response to treatment in the long term. Finally, we designed a therapeutic scheme to regulate purine metabolism in breast cancer, independently of the molecular subtype. This scheme is founded on a computational tool that provides a set of FDA-approved drugs to target pathway-specific differentially expressed genes. By providing metabolic deregulation patterns at the single-sample level in breast cancer subtypes, we have been able to further characterize tumor behavior. This approach, together with targeted therapy, may open novel avenues for the design of personalized diagnostic, prognostic, and therapeutic strategies.

Current concepts in breast cancer genomics: An evidence based review by the CGC breast cancer working group

BACKGROUND

Genomic abnormalities in breast cancer have been described according to diverse conceptual frameworks, including histologic subtypes, clinical molecular subtypes, intrinsic DNA, RNA, and epigenetic profiles, and activated molecular pathways.

METHODS

The Cancer Genomics Consortium (CGC) Breast Cancer Workgroup performed an evidence based literature review to summarize current knowledge of clinically significant genomic alterations in breast cancer using CGC levels of evidence. Targetable or disease-defining alterations were prioritized.

RESULTS

We summarized genomic alterations in breast cancer within a framework of existing clinical tools for diagnosis, risk stratification, and therapeutic management. Using CGC levels of evidence, we catalog copy number profiles, gene expression profiles, and mutations in clinically significant genes. We also describe emerging molecular markers such as methylation profiling and immunotherapy biomarkers.

CONCLUSION

A summary of currently available information on breast cancer genomics will enhance precision medicine by serving as an interpretive resource for clinical laboratory geneticists, providing a foundation for future practice guidelines, and identifying knowledge gaps to address in future research.

Tumor propagating cells: drivers of tumor plasticity, heterogeneity, and recurrence

Tumorigenesis is associated with the development of a highly variable pattern of cellular diversity, consequence of genetic and epigenetic diversification, followed by clonal selection and expansion. This process is shaped by the microenvironment and leads to intratumoral heterogeneity, which is characterized by differences between cancer cells in terms of gene expression, phenotypic markers, growth dynamics, and resistance to treatment. Another relevant aspect in intratumor heterogeneity is cell plasticity-the ability of a cell to switch to new identities. In this review, we focus on the mechanisms that regulate cancer cell plasticity within a tumor, and explore the concept of tumor propagating cells, or TPCs, a cancer cell able to propagate/phenocopy the parental tumor and recapitulate tumor heterogeneity. We discuss the influence of the microenvironment and driver mutations on TPCs formation and function, the existence of phenotypically distinct TPC clones within a tumor, the evolution of TPCs with disease progression, and their implications for therapy.

Radiation-Induced Chromosomal Breaks may be DNA Repair Fragile Sites with Larger-scale Correlations to Eight Double-Strand-Break Related Data Sets over the Human Genome

In this work, we compared the genomic distribution of common radiation-induced chromosomal breaks to eight different data sets covering the whole human genome. Sites with a high probability of chromatid breakage after exposure to low and high ionization density radiations were often located inside common and rare fragile sites, indicating that they may be a new and more local type of DNA repair-related fragility. Breaks in specific chromosome bands after acute exposure to oil and benzene also showed strong correlation with these sites and fragile sites. In addition, close correlation was found with cytologically detected chiasma and MLH1 immunofluorescence sites and with the HapMap recombination density distributions. Also, of interest, copy number changes occurred predominantly at radiation-induced breaks and fragile sites, at least for breast cancers with poor prognosis, and they decreased weakly but significantly in regions with increasing recombination and CpG density. An increased CpG density is linked to regions of high gene density to secure high-fidelity reproduction and survival. To minimize cancer induction, cancer-related genes are often located in regions of decreased recombination density and/or higher-than-average CpG density. It is compelling that all these data sets were influenced by the cells' handling of double-strand breaks and, more generally, DNA damage on its genome. In fact, the DNA repair genes systematically avoid regions with a high recombination density, as they need to be intact to accurately handle repairable DNA lesions.

Clonality of circulating tumor cells in breast cancer brain metastasis patients

Background

The incidence of brain metastases in breast cancer (BCBM) patients is increasing. These patients have a very poor prognosis, and therefore, identification of blood-based biomarkers, such as circulating tumor cells (CTCs), and understanding the genomic heterogeneity could help to personalize treatment options.

Methods

Both EpCAM-dependent (CellSearch® System) and EpCAM-independent Ficoll-based density centrifugation methods were used to detect CTCs from 57 BCBM patients. DNA from individual CTCs and corresponding primary tumors and brain metastases were analyzed by next-generation sequencing (NGS) in order to evaluate copy number aberrations and single nucleotide variations (SNVs).

Results

CTCs were detected after EpCAM-dependent enrichment in 47.7% of the patients (≥ 5 CTCs/7.5 ml blood in 20.5%). The CTC count was associated with ERBB2 status (p = 0.029) of the primary tumor as well as with the prevalence of bone metastases (p = 0.021). EpCAM-independent enrichment revealed CTCs in 32.6% of the patients, especially among triple-negative breast cancer (TNBC) patients (70.0%). A positive CTC status after enrichment of either method was significantly associated with decreased overall survival time (p < 0.05). Combining the results of both enrichment methods, 63.6% of the patients were classified as CTC positive. In three patients, the matched tumor tissue and single CTCs were analyzed by NGS showing chromosomal aberrations with a high genomic clonality and mutations in pathways potentially important in brain metastasis formation.

Conclusion

The detection of CTCs, regardless of the enrichment method, is of prognostic relevance in BCBM patients and in combination with molecular analysis of CTCs can help defining patients with higher risk of early relapse and suitability for targeted treatment.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1184-2) contains supplementary material, which is available to authorized users.

SMURF-seq: efficient copy number profiling on long-read sequencers

We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up to 30 fragments per read, providing an average of 6.2 and up to 7.5 million mappable fragments per run, increasing information throughput for read-counting applications. We apply SMURF-seq on the MinION to generate copy number profiles. A comparison with profiles from Illumina sequencing reveals that SMURF-seq attains similar accuracy. More broadly, SMURF-seq expands the utility of long-read sequencers for read-counting applications.

Array comparative genomic hybridization analysis discloses chromosome copy number alterations as indicators of patient outcome in lymph node-negative breast cancer

BACKGROUND

Patients with lymph node metastasis-negative (pN0) invasive breast cancer have favorable outcomes following initial treatment. However, false negatives which occur during routine histologic examination of lymph nodes are reported to underestimate the clinical stage of disease. To identify a high-risk group in pN0 invasive breast cancer, we examined copy number alterations (CNAs) of 800 cancer-related genes.

METHODS

Using array-based comparative genomic hybridization (CGH) in 51 pN0 cases (19 relapsed and 32 non-relapsed cases), the positivities of specific gene CNAs in the relapsed and non-relapsed groups were compared. An unsupervised hierarchical cluster analysis was then performed to identify case groups that were correlated with patient outcomes.

RESULTS

The cluster analysis identified three distinct clusters of cases: groups 1, 2, and 3. The major component was triple-negative cases (69%, 9 of 13) in group 1, luminal B-like (57%, 13 of 23) and HER2-overexpressing (26%, 6 of 23) subtypes in group 2, and luminal A-like subtype (60%, 9 of 15) in group 3. Among all 51 cases, those in group 1 showed significantly worse overall survival (OS) than group 2 (p = 0.014), and 5q15 loss was correlated with worse OS (p = 0.017). Among 19 relapsed cases, both OS and relapse-free survival (RFS) rates were significantly lower in group 1 than in group 2 (p = 0.0083 and 0.0018, respectively), and 5q15 loss, 12p13.31 gain, and absence of 16p13.3 gain were significantly correlated with worse OS and RFS (p = 0.019 and 0.0027, respectively).

CONCLUSIONS

As the target genes in these loci, NR2F1 (5q15), TNFRSF1A (12p13.31), and ABCA3 (16p13.3) were examined. 5q15 loss, 12p13.31 gain, and absence of 16q13.3 gain were potential indicators of high-risk recurrence and aggressive clinical behavior of pN0 invasive breast cancers.

High expression of RAB38 promotes malignant progression of pancreatic cancer

Ras-Related Protein Rab-38 (RAB38), which belongs to the RAB family, is involved in the biogenesis of lysosome-related organelles and defense against certain microbial infections. However, the clinical significance and potential function of RAB38 in pancreatic adenocarcinoma remain unclear. In the present study, an immunohistochemical assay was performed to analyze the expression of RAB38 in pancreatic adenocarcinoma tumor specimens from 82 patients, and the clinicopathological characteristics and survival rate of these patients were further examined. To validate the role of RAB38 in tumors, the effect of RAB38 on tumor cell proliferation, migration and invasion was assessed by establishing RAB38 knockdown cell lines. Reverse transcription-quantitative polymerase chain reaction and western blotting were used to examine the expression levels of proteins associated with the cancer cell behavior. In addition, the inhibitory effect of RAB38 silencing on pancreatic cancer was examined in mice. The immunohistochemistry results revealed that RAB38 was upregulated and positively correlated with the grade of progression in pancreatic adenocarcinoma patients. Further investigation indicated that RAB38 downregulation significantly suppressed the proliferation, migration and invasive capacity of pancreatic cancer cells, as well as decreased the expression levels of Ki67, proliferating cell nuclear antigen, and matrix metalloproteinases 2 and 9. RAB38 silencing also inhibited the development of pancreatic cancer in vivo. Taken together, a high level of RAB38 was significantly associated with the malignant phenotypes of pancreatic cancer, suggesting that RAB38 may serve as a novel biomarker and a potential therapeutic target for pancreatic cancer.

A low cost and input tailing method of quality control on multiple annealing, and looping-based amplification cycles-based whole-genome amplification products

BACKGROUND

Single-cell whole-genome sequencing provides novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, amplification of formalin-fixed tissues with low cell numbers is still problematic and multiple annealing, and looping-based amplification cycles (MALBAC) is a commonly used whole-genome amplification (WGA) method with low cell numbers.

METHODS

We developed a low-input tailing method to evaluate the MALBAC-based WGA from sub-nanogram or less quantities of input DNA. The tailing method uses 2100 BioAnalyzer to evaluate the size distribution of MALBAC products, and comparing the tailing with 10380 bp.

RESULTS

Compared with a 22 loci qPCR panel, the tailing method provided a similar WGA evaluation efficiency in 13 samples on one set of study, with lower input, cheaper cost, shorter manual time, and a clear filtering cut off. Later, we demonstrated a strong correlation between tailing size and coverage breadth in another 29 samples on two sets of assays. As a result, the tailing method showed that it could predict whether a sequence breadth achieved 70% or not with 100% accuracy on these three sets of assays. Although further studies are needed, this tailing method is expected to be used as an excellent tool to select high-quality WGA products before library construction.

CONCLUSIONS

Our tailing method can provide a new WGA quality test to evaluate the WGA efficiency with 100% accuracy (42/42). Compared with qPCR panel, our tailing method needs lower input, cheaper cost, shorter manual time, a clear filtering cut off, and extendable high throughput as well as the same sensitivity.

Clonal relatedness in tumour pairs of breast cancer patients

Background

Molecular classification of tumour clonality is currently not evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. There is no consensus about which type of data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours.

Methods

Thirty-seven invasive breast tumour pairs were stratified according to laterality and time interval between the diagnoses of the two tumours. In a multi-omics approach, tumour clonality was analysed by integrating clinical characteristics (n = 37), DNA copy number (n = 37), DNA methylation (n = 8), gene expression microarray (n = 7), RNA sequencing (n = 3), and SNP genotyping data (n = 3). Different statistical methods, e.g. the diagnostic similarity index (SI), were used to classify the tumours as clonally related recurrences or independent primary tumours.

Results

The SI and hierarchical clustering showed similar tendencies and the highest concordance with the other methods. Concordant evidence for tumour clonality was found in 46% (17/37) of patients. Notably, no association was found between the current clinical guidelines and molecular tumour features.

Conclusions

A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. Guidelines need to be defined with exact thresholds to standardise clonality testing in a routine diagnostic setting.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1022-y) contains supplementary material, which is available to authorized users.

Genomic cfDNA Analysis of Aqueous Humor in Retinoblastoma Predicts Eye Salvage: The Surrogate Tumor Biopsy for Retinoblastoma

Tumor-derived cell-free DNA (cfDNA) has biomarker potential; therefore, this study aimed to identify cfDNA in the aqueous humor (AH) of retinoblastoma eyes and correlate somatic chromosomal copy-number alterations (SCNA) with clinical outcomes, specifically eye salvage. AH was extracted via paracentesis during intravitreal injection of chemotherapy or enucleation. Shallow whole-genome sequencing was performed using isolated cfDNA to assess for highly recurrent SCNAs in retinoblastoma including gain of 1q, 2p, 6p, loss of 13q, 16q, and focal MYCN amplification. Sixty-three clinical specimens of AH from 29 eyes of 26 patients were evaluated; 13 eyes were enucleated and 16 were salvaged (e.g., saved). The presence of detectable SCNAs was 92% in enucleated eyes versus 38% in salvaged eyes (P = 0.006). Gain of chromosome 6p was the most common SCNA found in 77% of enucleated eyes, compared with 25% of salvaged eyes (P = 0.0092), and associated with a 10-fold increased odds of enucleation (OR, 10; 95% CI, 1.8-55.6). The median amplitude of 6p gain was 1.47 in enucleated versus 1.07 in salvaged eyes (P = 0.001). The presence of AH SCNAs was correlated retrospectively with eye salvage. The probability of ocular salvage was higher in eyes without detectable SCNAs in the AH (P = 0.0028), specifically 6p gain. This is the first study to correlate clinical outcomes with SCNAs in the AH from retinoblastoma eyes, as such these findings indicate that 6p gain in the aqueous humor is a potential prognostic biomarker for poor clinical response to therapy.Implications: The correlation of clinical outcomes and SCNAs in the AH identified in the current study requires prospective studies to validate these finding before SCNAs, like 6p gain, can be used to predict clinical outcomes at diagnosis. Mol Cancer Res; 16(11); 1701-12. ©2018 AACR.

Breast cancer intratumour heterogeneity: current status and clinical implications

Breast cancer (BC) is a heterogeneous disease that varies in presentation, morphological features, behaviour, and response to therapy. High-throughput molecular profiling studies have revolutionised our understanding of BC heterogeneity, and have demonstrated that molecular profiles of tumours are variable not only between tumours, but also within individual tumours. Current evidence indicates that spatial and temporal intratumour heterogeneity of BC exists at levels beyond what are commonly expected. Intratumour heterogeneity poses critical challenges in the diagnosis, prediction of behaviour and management of BC. For instance, heterogeneous expression of oestrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 can be seen not only in primary tumours between different regions, but also between primary tumours and their corresponding metastatic/recurrent lesions. The demonstration of molecularly distinct subclones within individual tumours may explain, at least in part, the mechanisms controlling the variable behaviour of BC, and may change our approach to BC sampling and treatment. In this review, BC intratumour heterogeneity is highlighted, with a special emphasis on the current knowledge pertaining to the relationship between intratumour heterogeneity and BC pathogenesis, evolution, and progression, with consideration of its impact on disease diagnosis, management, and the emergence of novel therapeutic targets. The key role of high-throughput molecular and imaging techniques is also addressed.

Long non-coding RNAs: implications in targeted diagnoses, prognosis, and improved therapeutic strategies in human non- and triple-negative breast cancer

Triple-negative breast cancer (TNBC) has been clinically difficult to manage because of tumor aggressiveness, cellular and histological heterogeneity, and molecular mechanisms’ complexity. All this in turn leads us to evaluate that tumor biological behavior is not yet fully understood. Additionally, the heterogeneity of tumor cells represents a great biomedicine challenge in terms of the complex molecular—genetical-transcriptional and epigenetical—mechanisms, which have not been fully elucidated on human solid tumors.

Recently, human breast cancer, but specifically TNBC is under basic and clinical-oncology research in the discovery of new molecular biomarkers and/or therapeutic targets to improve treatment responses, as well as for seeking algorithms for patient stratification, seeking a positive impact in clinical-oncology outcomes and life quality on breast cancer patients.

In this sense, important knowledge is emerging regarding several cancer molecular aberrations, including higher genetic mutational rates, LOH, CNV, chromosomal, and epigenetic alterations, as well as transcriptome aberrations in terms of the total gene-coding ribonucleic acids (RNAs), known as mRNAs, as well as non-coding RNA (ncRNA) sequences. In this regard, novel investigation fields have included microRNAs (miRNAs), as well as long ncRNAs (lncRNAs), which have been importantly related and are likely involved in the induction, promotion, progression, and/or clinical therapeutic response trackers of TNBC. Based on this, in general terms according with the five functional archetype classification, the lncRNAs may be involved in the regulation of several molecular mechanisms which include genetic expression, epigenetic, transcriptional, and/or post-transcriptional mechanisms, which are nowadays not totally understood.

Here, we have reviewed the main dis-regulated and functionally non- and well-characterized lncRNAs and their likely involvement, from a molecular enrichment and mechanistic point of view, as tumor biomarkers for breast cancer and its specific histological subtype, TNBC. In reference to the abovementioned, it has been described that some lncRNA expression profiles correspond or are associated with the TNBC histological subtype, potentially granting their use for TNBC malignant progression, diagnosis, tumor clinical stage, and likely therapy. Based on this, lncRNAs have been proposed as potential biomarkers which might represent potential predictive tools in the differentiated breast carcinomas versus TNBC malignant disease. Finally, elucidation of the specific or multi-functional archetypal of lncRNAs in breast cancer and TNBC could be fundamental, as these molecular intermediary-regulator “lncRNAs” are widely involved in the genome expression, epigenome regulation, and transcriptional and post-transcriptional tumor biology, which in turn will probably represent a new prospect in clinical and/or therapeutic molecular targets for the oncological management of breast carcinomas in general and also for TNBC patients.

Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer

Genomic rearrangements are common in cancer, with demonstrated links to disease progression and treatment response. These rearrangements can be complex, resulting in fusions of multiple chromosomal fragments and generation of derivative chromosomes. Although methods exist for detecting individual fusions, they are generally unable to reconstruct complex chained events. To overcome these limitations, we adopted a new optical mapping approach, allowing megabase-length genome maps to be reconstructed and rearranged genomes to be visualized without loss of integrity. Whole-genome mapping (Bionano Genomics) of a well-studied highly rearranged liposarcoma cell line resulted in 3338 assembled consensus genome maps, including 72 fusion maps. These fusion maps represent 112.3 Mb of highly rearranged genomic regions, illuminating the complex architecture of chained fusions, including content, order, orientation, and size. Spanning the junction of 147 chromosomal translocations, we found a total of 28 Mb of interspersed sequences that could not be aligned to the reference genome. Traversing these interspersed sequences using short-read sequencing breakpoint calls, we were able to identify and place 399 sequencing fragments within the optical mapping gaps, thus illustrating the complementary nature of optical mapping and short-read sequencing. We demonstrate that optical mapping provides a powerful new approach for capturing a higher level of complex genomic architecture, creating a scaffold for renewed interpretation of sequencing data of particular relevance to human cancer.

Whole genome sequencing of matched tumor, adjacent non-tumor tissues and corresponding normal blood samples of hepatocellular carcinoma patients revealed dynamic changes of the mutations profiles during hepatocarcinogenesis

Hepatocellular carcinoma (HCC) has become the third most deadly disease worldwide and HBV is the major factor in Asia and Africa. We conducted 9 WGS (whole genome sequencing) analyses for matched samples of tumor, adjacent non-tumor tissues and normal blood samples of HCC patients from three HBV positive patients. We then validated the mutations identified in a larger cohort of 177 HCC patients. We found that the number of the unique somatic mutations (average of 59,136) in tumor samples is significantly less than that in adjacent non-tumor tissues (average 83, 633). We discovered that the TP53 R249S mutation occurred in 7.7% of the HCC patients, and it was significantly associated with poor diagnosis. In addition, we found that the L104P mutation in the VCX gene (Variable charge, X-linked) was absent in white blood cell samples, but present at 11.1% frequency in the adjacent tissues and increased to 14.6% in HCC tissues, suggesting that this mutation might be a tumor driver gene driving HCC carcinogenesis. Finally, we identified a TK1-RNU7 fusion, which would result in a deletion of 103 amino acids from its C-terminal. The frequencies of this fusion event decreased from the adjacent tissues (29.2%) to the tumors (16.7%), suggesting that a truncated thymidine Kinase1 (TK1) caused by the fusion event might be deleterious and be selected against during tumor progression. The three-way comparisons allow the identification of potential driver mutations of carcinogenesis. Furthermore, our dataset provides the research community a valuable dataset for identifying dynamic changes of mutation profiles and driver mutations for HCC.

HER2 is not a cancer subtype but rather a pan-cancer event and is highly enriched in AR-driven breast tumors

BACKGROUND

Approximately one in five breast cancers are driven by amplification and overexpression of the human epidermal growth factor receptor 2 (HER2) receptor kinase, and HER2-enriched (HER2E) is one of four major transcriptional subtypes of breast cancer. We set out to understand the genomics of HER2 amplification independent of subtype, and the underlying drivers and biology of HER2E tumors.

METHODS

We investigated published genomic data from 3155 breast tumors and 5391 non-breast tumors.

RESULTS

HER2 amplification is a distinct driver event seen in all breast cancer subtypes, rather than a subtype marker, with major characteristics restricted to amplification and overexpression of HER2 and neighboring genes. The HER2E subtype has a distinctive transcriptional landscape independent of HER2A that reflects androgen receptor signaling as replacement for estrogen receptor (ER)-driven tumorigenesis. HER2 amplification is also an event in 1.8% of non-breast tumors.

CONCLUSIONS

These discoveries reveal therapeutic opportunities for combining anti-HER2 therapy with anti-androgen agents in breast cancer, and highlight the potential for broader therapeutic use of HER2 inhibitors.

Breast Cancer Molecular Stratification: From Intrinsic Subtypes to Integrative Clusters

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

Cancer heterogeneity: converting a limitation into a source of biologic information

Analysis of spatial and temporal genetic heterogeneity in human cancers has revealed that somatic cancer evolution in most cancers is not a simple linear process composed of a few sequential steps of mutation acquisitions and clonal expansions. Parallel evolution has been observed in many early human cancers resulting in genetic heterogeneity as well as multilineage progression. Moreover, aneuploidy as well as structural chromosomal aberrations seems to be acquired in a non-linear, punctuated mode where most aberrations occur at early stages of somatic cancer evolution. At later stages, the cancer genomes seem to get stabilized and acquire only few additional rearrangements. While parallel evolution suggests positive selection of driver mutations at early stages of somatic cancer evolution, stabilization of structural aberrations at later stages suggests that negative selection takes effect when cancer cells progressively lose their tolerance towards additional mutation acquisition. Mixing of genetically heterogeneous subclones in cancer samples reduces sensitivity of mutation detection. Moreover, driver mutations present only in a fraction of cancer cells are more likely to be mistaken for passenger mutations. Therefore, genetic heterogeneity may be considered a limitation negatively affecting detection sensitivity of driver mutations. On the other hand, identification of subclones and subclone lineages in human cancers may lead to a more profound understanding of the selective forces which shape somatic cancer evolution in human cancers. Identification of parallel evolution by analyzing spatial heterogeneity may hint to driver mutations which might represent additional therapeutic targets besides driver mutations present in a monoclonal state. Likewise, stabilization of cancer genomes which can be identified by analyzing temporal genetic heterogeneity might hint to genes and pathways which have become essential for survival of cancer cell lineages at later stages of cancer evolution. These genes and pathways might also constitute patient specific therapeutic targets.

Data-driven analysis of immune infiltrate in a large cohort of breast cancer and its association with disease progression, ER activity, and genomic complexity

The tumor microenvironment is now widely recognized for its role in tumor progression, treatment response, and clinical outcome. The intratumoral immunological landscape, in particular, has been shown to exert both pro-tumorigenic and anti-tumorigenic effects. Identifying immunologically active or silent tumors may be an important indication for administration of therapy, and detecting early infiltration patterns may uncover factors that contribute to early risk. Thus far, direct detailed studies of the cell composition of tumor infiltration have been limited; with some studies giving approximate quantifications using immunohistochemistry and other small studies obtaining detailed measurements by isolating cells from excised tumors and sorting them using flow cytometry. Herein we utilize a machine learning based approach to identify lymphocyte markers with which we can quantify the presence of B cells, cytotoxic T-lymphocytes, T-helper 1, and T-helper 2 cells in any gene expression data set and apply it to studies of breast tissue. By leveraging over 2,100 samples from existing large scale studies, we are able to find an inherent cell heterogeneity in clinically characterized immune infiltrates, a strong link between estrogen receptor activity and infiltration in normal and tumor tissues, changes with genomic complexity, and identify characteristic differences in lymphocyte expression among molecular groupings. With our extendable methodology for capturing cell type specific signal we systematically studied immune infiltration in breast cancer, finding an inverse correlation between beneficial lymphocyte infiltration and estrogen receptor activity in normal breast tissue and reduced infiltration in estrogen receptor negative tumors with high genomic complexity.

Amplification and overexpression of PSCA at 8q24 in invasive micropapillary carcinoma of breast

PURPOSE

Invasive micropapillary carcinoma (IMPC) of the breast has distinct histological features and molecular genetic profiles. Gains/amplifications of 8q24 are found associated with IMPC. Although the prostate stem cell antigen (PSCA) gene is located at chromosome 8q24, and found over-expressed in prior studies, its prognostic values and biological significance in IMPC have not been well studied.

METHODS

Fluorescence in situ hybridization (FISH) was used to assess the frequencies of PSCA copy number gains in IMPC, invasive ductal carcinoma of no special type (IDC-NST), and invasive lobular carcinoma (ILC) samples. The protein expression levels of PSCA were examined in 56 IMPC, 72 IDC-NST, and 56 ILC samples using immunohistochemical analysis.

RESULTS

PSCA gene amplification was detected in 45.2% (14/31) of the IMPC, 28.1% (9/32) of the IDC-NST, and none (0/25) of the ILC. PSCA protein expression was observed in 58.9% (33/56), 40.3% (29/72), and 3.6% (2/56) of IMPC, IDC-NST, and ILC samples, respectively. The concordant rate of the immunohistochemistry and FISH data was 85.2%. PSCA gene amplification highly correlated with its protein overexpression (rs = 0.687, P < 0.001), suggesting that gene amplification is an important mechanism involved in PSCA overexpression. Our univariate analysis showed that the patients with PSCA-positive IMPC had a decreased disease-free survival (DFS) compared to PSCA-negative IMPC patients (P = 0.003). Our multivariate analysis confirmed the worse DFS in PSCA-positive IMPC patients (P = 0.022).

CONCLUSIONS

Our results indicate that PSCA may be an attractive target in the 8q24 amplicon and that it may serve as a molecular marker of metastasis and recurrence in IMPC. The differential expression of PSCA may be associated with cell adhesion. Detection of PSCA protein and gene amplification may help manage and predict the prognosis of IMPC patients.

Integrative analysis of copy number and gene expression in breast cancer using formalin-fixed paraffin-embedded core biopsy tissue: a feasibility study

BACKGROUND

An absence of reliable molecular markers has hampered individualised breast cancer treatments, and a major limitation for translational research is the lack of fresh tissue. There are, however, abundant banks of formalin-fixed paraffin-embedded (FFPE) tissue. This study evaluated two platforms available for the analysis of DNA copy number and gene expression using FFPE samples.

METHODS

The cDNA-mediated annealing, selection, extension, and ligation assay (DASL™) has been developed for gene expression analysis and the Molecular Inversion Probes assay (Oncoscan™), were used for copy number analysis using FFPE tissues. Gene expression and copy number were evaluated in core-biopsy samples from patients with breast cancer undergoing neoadjuvant chemotherapy (NAC).

RESULTS

Forty-three core-biopsies were evaluated and characteristic copy number changes in breast cancers, gains in 1q, 8q, 11q, 17q and 20q and losses in 6q, 8p, 13q and 16q, were confirmed. Regions that frequently exhibited gains in tumours showing a pathological complete response (pCR) to NAC were 1q (55%), 8q (40%) and 17q (40%), whereas 11q11 (37%) gain was the most frequent change in non-pCR tumours. Gains associated with poor survival were 11q13 (62%), 8q24 (54%) and 20q (47%). Gene expression assessed by DASL correlated with immunohistochemistry (IHC) analysis for oestrogen receptor (ER) [area under the curve (AUC) = 0.95], progesterone receptor (PR)(AUC = 0.90) and human epidermal growth factor type-2 receptor (HER-2) (AUC = 0.96). Differential expression analysis between ER+ and ER- cancers identified over-expression of TTF1, LAF-4 and C-MYB (p ≤ 0.05), and between pCR vs non-pCRs, over-expression of CXCL9, AREG, B-MYB and under-expression of ABCG2.

CONCLUSION

This study was an integrative analysis of copy number and gene expression using FFPE core biopsies and showed that molecular marker data from FFPE tissues were consistent with those in previous studies using fresh-frozen samples. FFPE tissue can provide reliable information and will be a useful tool in molecular marker studies.

TRIAL REGISTRATION

Trial registration number ISRCTN09184069 and registered retrospectively on 02/06/2010.

Molecular signatures in breast cancer

The use of molecular signatures to add value to standard clinical and pathological parameters has impacted clinical practice in many cancer types, but perhaps most notably in the breast cancer field. This is, in part, due to the considerable complexity of the disease at the clinical, morphological and molecular levels. The adoption of molecular profiling of DNA, RNA and protein continues to reveal important differences in the intrinsic biology between molecular subtypes and has begun to impact the way patients are managed. Several bioinformatic tools have been developed using DNA or RNA-based signatures to stratify the disease into biologically and/or clinically meaningful subgroups. Here, we review the approaches that have been used to develop gene expression signatures into currently available diagnostic assays (e.g., OncotypeDX® and Mammaprint®), plus we describe the latest work on genome sequencing, the methodologies used in the discovery process of mutational signatures, and the potential of these signatures to impact the clinic.

Early Detection of Cancer in Blood Using Single-Cell Analysis: A Proposal

Here, we explore the potential of single-cell genomic analysis in blood for early detection of cancer; we consider a method that screens the presence of recurrent patterns of copy number (CN) alterations using sparse single-cell sequencing. We argue for feasibility, based on in silico analysis of existing single-cell data and cancer CN profiles. Sampling procedures from existing diploid single cells can render data for a cell with any given profile. Sampling from multiple published tumor profiles can interrogate cancer clonality via an algorithm that tests the multiplicity of close pairwise similarities among single-cell cancer genomes. The majority of common solid cancers would be detectable in this manner. As any early detection method must be verifiable and actionable, we describe how further analysis of suspect cells can aid in determining risk and anatomic origin. Future affordability rests on currently available procedures for tumor cell enrichment and inexpensive methods for single-cell analysis.

Mutational Signatures in Breast Cancer: The Problem at the DNA Level

A breast cancer genome is a record of the historic mutagenic activity that has occurred throughout the development of the tumor. Indeed, every mutation may be informative. Although driver mutations were the main focus of cancer research for a long time, passenger mutational signatures, the imprints of DNA damage and DNA repair processes that have been operative during tumorigenesis, are also biologically illuminating. This review is a chronicle of how the concept of mutational signatures arose and brings the reader up-to-date on this field, particularly in breast cancer. Mutational signatures have now been advanced to include mutational processes that involve rearrangements, and novel cancer biological insights have been gained through studying these in great detail. Furthermore, there are efforts to take this field into the clinical sphere. If validated, mutational signatures could thus form an additional weapon in the arsenal of cancer precision diagnostics and therapeutic stratification in the modern war against cancer. Clin Cancer Res; 23(11); 2617-29. ©2017 AACRSee all articles in this CCR Focus section, "Breast Cancer Research: From Base Pairs to Populations."

CLImAT-HET: detecting subclonal copy number alterations and loss of heterozygosity in heterogeneous tumor samples from whole-genome sequencing data

Background

Copy number alterations (CNA) and loss of heterozygosity (LOH) represent a large proportion of genetic structural variations of cancer genomes. These aberrations are continuously accumulated during the procedure of clonal evolution and patterned by phylogenetic branching. This invariably results in the emergence of multiple cell populations with distinct complement of mutational landscapes in tumor sample. With the advent of next-generation sequencing technology, inference of subclonal populations has become one of the focused interests in cancer-associated studies, and is usually based on the assessment of combinations of somatic single-nucleotide variations (SNV), CNA and LOH. However, cancer samples often have several inherent issues, such as contamination of normal stroma, tumor aneuploidy and intra-tumor heterogeneity. Addressing these critical issues is imperative for accurate profiling of clonal architecture.

Methods

We present CLImAT-HET, a computational method designed for capturing clonal diversity in the CNA/LOH dimensions by taking into account the intra-tumor heterogeneity issue, in the case where a reference or matched normal sample is absent. The algorithm quantitatively represents the clonal identification problem using a factorial hidden Markov model, and takes an integrated analysis of read counts and allele frequency data. It is able to infer subclonal CNA and LOH events as well as the fraction of cells harboring each event.

Results

The results on simulated datasets indicate that CLImAT-HET has high power to identify CNA/LOH segments, it achieves an average accuracy of 0.87. It can also accurately infer proportion of each clonal population with an overall Pearson correlation coefficient of 0.99 and a mean absolute error of 0.02. CLImAT-HET shows significant advantages when compared with other existing methods. Application of CLImAT-HET to 5 primary triple negative breast cancer samples demonstrates its ability to capture clonal diversity in the CAN/LOH dimensions. It detects two clonal populations in one sample, and three clonal populations in one other sample.

Conclusions

CLImAT-HET, a novel algorithm is introduced to infer CNA/LOH segments from heterogeneous tumor samples. We demonstrate CLImAT-HET’s ability to accurately recover clonal compositions using tumor WGS data without a match normal sample.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-017-0255-4) contains supplementary material, which is available to authorized users.

Alterations of biomarker profiles after neoadjuvant chemotherapy in breast cancer: tumor heterogeneity should be taken into consideration

Tumor biomarkers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 are routinely tested in breast cancer patients and their status guides clinical management and predicts prognosis. A few retrospective studies have suggested that neoadjuvant chemotherapy (NAC) in breast cancer may change the status of biomarker expression, which in turn will affect further management of these patients. In this study we take advantage of a relatively large cohort and aim to study the effect of NAC on biomarker expression and explore the impact of tumor size and lymph node involvement on biomarker status changes. We collected 107 patients with invasive breast cancer who received at least three cycles of NAC. We retrospectively performed and scored the immunohistochemistry (IHC) of ER, PR, HER2 and Ki-67 using both the diagnostic core biopsies before NAC and excisional specimens following NAC. HER2 gene status was assessed by fluorescence in situ hybridization for cases with IHC result of 2+. We demonstrated that there was a significant decrease in expression of PR (P = 0.013) and Ki-67 (P = 0.000) in post-NAC specimens compared to pre-NAC core biopsies. In addition, cases with large tumor size (≥2cm) and cases with lymph node metastasis were more frequently to have biomarker changes. Finally we studied cases with HER2 status changes after NAC treatments in detail and emphasized the nature of tumor heterogeneity.

Genome-wide copy number aberrations and HER2 and FGFR1 alterations in primary breast cancer by molecular inversion probe microarray

Breast cancer remains the second leading cause of cancer-related death in women despite stratification based on standard hormonal receptor (HR) and HER2 testing. Additional prognostic markers are needed to improve breast cancer treatment. Chromothripsis, a catastrophic genome rearrangement, has been described recently in various cancer genomes and affects cancer progression and prognosis. However, little is known about chromothripsis in breast cancer. To identify novel prognostic biomarkers in breast cancer, we used molecular inversion probe (MIP) microarray to explore genome-wide copy number aberrations (CNA) and breast cancer-related gene alterations in DNA extracted from formalin-fixed paraffin-embedded tissue. We examined 42 primary breast cancers with known HR and HER2 status assessed via immunohistochemistry and FISH and analyzed MIP microarray results for correlation with standard tests and survival outcomes. Global genome-wide CNA ranged from 0.2% to 65.7%. Chromothripsis-like patterns were observed in 23/38 (61%) cases and were more prevalent in cases with ≥10% CNA (20/26, 77%) than in cases with <10% CNA (3/12, 25%; p<0.01). Most frequently involved chromosomal segment was 17q12-q21, the HER2 locus. Chromothripsis-like patterns involving 17q12 were observed in 8/19 (42%) of HER2-amplified tumors but not in any of the tumors without HER2 amplification (0/19; p<0.01). HER2 amplification detected by MIP microarray was 95% concordant with conventional testing (39/41). Interestingly, 21% of patients (9/42) had fibroblast growth factor receptor 1 (FGFR1)amplification and had a 460% higher risk for mortality than those without FGFR1 amplification (p<0.01). In summary, MIP microarray provided a robust assessment of genomic CNA of breast cancer.