Breast tumor copy number aberration phenotypes and genomic instability

Bayesianism from a philosophical perspective and its application to medicine

Bayesian philosophy and Bayesian statistics have diverged in recent years, because Bayesian philosophers have become more interested in philosophical problems other than the foundations of statistics and Bayesian statisticians have become less concerned with philosophical foundations. One way in which this divergence manifests itself is through the use of direct inference principles: Bayesian philosophers routinely advocate principles that require calibration of degrees of belief to available non-epistemic probabilities, while Bayesian statisticians rarely invoke such principles. As I explain, however, the standard Bayesian framework cannot coherently employ direct inference principles. Direct inference requires a shift towards a non-standard Bayesian framework, which further increases the gap between Bayesian philosophy and Bayesian statistics. This divergence does not preclude the application of Bayesian philosophical methods to real-world problems. Data consolidation is a key challenge for present-day systems medicine and other systems sciences. I show that data consolidation requires direct inference and that the non-standard Bayesian methods outlined here are well suited to this task.

Identification of BRIP1, NSMCE2, ANAPC7, RAD18 and TTL from chromosome segregation gene set associated with hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma is one of the most frequent cancers with high mortality rate worldwide.

METHODS

TCGA LIHC HTseq counts were analyzed. GSEA was performed with GO BP gene sets. GO analysis was performed with differentially expressed genes. The subset of genes contributing most of the enrichment result of GO_BP_CHROMOSOME_SEGREGATION of GSEA were identified. Five genes have been selected in this subset of genes for further analysis. A microarray data set, GSE112790, was analyzed as a validation data set. Survival analysis was performed.

RESULTS

According to GSEA and GO analysis several gene sets and processes related to chromosome segregation were enriched in LIHC. GO_BP_CHROMOSOME_SEGREGATION gene set from GSEA had the highest size of the genes contributing most of the enrichment. Five genes in this gene set; BRIP1, NSMCE2, ANAPC7, RAD18 and TTL, whose expressions and prognostic values have not been studied in hepatocellular carcinoma in detail, have been selected for further analyses. Expression of these five genes were identified as significantly upregulated in LIHC RNA-seq and HCC microarray data set. Survival analysis showed that high expression of the five genes was associated with poor overall survival in HCC patients.

CONCLUSION

Selected genes were upregulated and had prognostic value in HCC.

DNA methylation profiling identifies two distinct subgroups in breast cancers with low hormone receptor expression, mainly associated with HER2 amplification status

Background

Current clinical guidelines suggest that breast cancers with low hormone receptor expression (LowHR) in 1–10% of tumor cells should be regarded as hormone receptor positive. However, clinical data show that these patients have worse outcome compared to patients with hormone receptor expression above 10%. We performed DNA methylation profiling on 23 LowHR breast cancer specimens, including 13 samples with HER2 amplification and compared our results with a reference breast cancer cohort from The Cancer Genome Atlas to clarify the status for this infrequent but important patient subgroup.

Results

In unsupervised clustering and dimensionality reduction, breast cancers with low hormone receptor expression that lacked HER2 amplification usually clustered with triple negative breast cancer (TNBC) reference samples (8/10; “LowHR TNBC-like”). In contrast, most specimens with low hormone receptor expression and HER2 amplification grouped with hormone receptor positive cancers (11/13; “LowHR HRpos-like”). We observed highly similar DNA methylation patterns of LowHR TNBC-like samples and true TNBCs. Furthermore, the Ki67 proliferation index of LowHR TNBC-like samples and clinical outcome parameters were more similar to TNBCs and differed from LowHR HRpos-like cases.

Conclusions

We here demonstrate that LowHR breast cancer comprises two epigenetically distinct groups. Our data strongly suggest that LowHR TNBC-like samples are molecularly, histologically and clinically closely related to TNBC, while LowHR HRpos-like specimens are closely related to hormone receptor positive tumors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01176-5.

A potential role for metastasis-associated in colon cancer 1 (MACC1) as a pan-cancer prognostic and immunological biomarker

BACKGROUND

Metastasis-Associated in Colon Cancer 1(MACC1) is a validated biomarker for metastasis and is linked to survival. Although extensive experimental evidence indicates an association between MACC1 and diverse cancers, no pan-cancer analyses have yet been performed for this marker, and the role of MACC1 in immunology remains unknown.

MATERIAL AND METHODS

In our study, we performed the analysis of MACC1 expression and its influence on prognosis using multiple databases, including TIMER2, GEPIA2, Kaplan-Meier plotter. MACC1 promoter methylation levels were evaluated using the UALCAN database. Based on the TCGA database, we explored the relationship between MACC1 and tumor mutational burden (TMB), microsatellite instability (MSI), immune checkpoints using the R programming language. We evaluated the association between MACC1 and immune infiltration via TIMER and UALCAN.

RESULTS

Our results revealed that abnormal DNA methylation may be an important cause for the different expression of MACC1 across cancer types. Meanwhile, we explored the potential oncogenic roles of MACC1 and found significant prognostic value. MACC1 may be related to T-cell function and the polarization of tumor-associated macrophages, especially in STAD and LGG. Its expression was associated with immune infiltration and was found to be closely related to immune checkpoint-associated genes, especially CD274 and SIGLEC15, indicating that MACC1 may be a potential immune therapeutic target for several malignancies. Our paper reveals for the first time the relationship between MACC1 and cancer immunology.

CONCLUSIONS

MACC1 might act as a predictor for the immune response in cancer patients, and could also represent a new potential immunotherapeutic target.

Over-expression of SRD5A3 and its prognostic significance in breast cancer

Objective

The study aimed to compare the Steroid 5 alpha-reductase 3 (SRD5A3) expression levels in breast cancer (BC) and normal tissues, to investigate the prognostic value of SRD5A3 mRNA expression in BC patients and to identify the SRD5A3-related signaling pathways using bioinformatics approaches.

Methods

We evaluated the expression levels of SRD5A3 and survival data in BC patients using different bioinformatic databases. Further, Cox regression analysis was conducted to predict the independent prognostic factors for BC. Moreover, the association of SRD5A3 with clinicopathological factors was measured through LinkedOmics database. And the potential role of SRD5A3 was determined by Gene Ontology and KEGG pathway enrichment analysis. Finally, protein network of SRD5A3 was constructed and genetic alterations were analyzed.

Results

Bioinformatic data indicated that both mRNA and protein expression levels of SRD5A3 were higher in BC group than those in the normal group (P < 0.05). Besides, BC patients with higher SRD5A3 mRNA expression levels had a lower overall survival (all P < 0.05). Cox regression analysis further demonstrated the independent prognostic value of SRD5A3 in BC (P = 0.015). SRD5A3 mRNA expression was significantly associated with N stage (P < 0.001), age (P < 0.05), and histologic subtype (P < 0.001) but had no significant relationship with other clinical characteristics (all P > 0.05). Moreover, the functional enrichment analysis revealed that the SRD5A3 was involved in metabolism-related pathways (all P < 0.05).

Conclusions

SRD5A3 was highly expressed in BC tissues and high SRD5A3 expression was related to poorer prognosis. SRD5A3 serves as an oncogene and might function as a potential biomarker for prognosis and a therapeutic target for BC.

Short somatic alterations at the site of copy number variation in breast cancer

Copy number variation (CNV) is a polymorphism in the human genome involving DNA fragments larger than 1 kb. Copy number variation sites provide hotspots of somatic alterations in cancers. Herein, we examined somatic alterations at sites of CNV in DNA from 20 invasive breast cancers using a Comparative Genomic Hybridization array specifically designed to detect the genome-wide CNV status of approximately 412 000 sites. Somatic copy number alterations (CNAs) were detected in 39.9% of the CNV probes examined. The most frequently altered regions were gains of 1q21-22 (90%), 8q21-24 (85%), 1q44 (85%), and 3q11 (85%) or losses of 16q22-24 (80%). Gene ontology analyses of genes within the CNA fragments revealed that cascades related to transcription and RNA metabolism correlated significantly with human epidermal growth factor receptor 2 positivity and menopausal status. Thirteen of 20 tumors showed CNAs in more than 35% of sites examined and a high prevalence of CNAs correlated significantly with estrogen receptor (ER) negativity, higher nuclear grade (NG), and higher Ki-67 labeling index. Finally, when CNA fragments were categorized according to their size, CNAs smaller than 10 kb correlated significantly with ER positivity and lower NG, whereas CNAs exceeding 10 Mb correlated with higher NG, ER negativity, and a higher Ki-67 labeling index. Most of these findings were confirmed or supported by quantitative PCR of representative DNA fragments in 72 additional breast cancers. These results suggest that most CNAs are caused by gain or loss of large chromosomal fragments and correlate with NG and several malignant features, whereas solitary CNAs of less than 10 kb could be involved in ER-positive breast carcinogenesis.

CONY: A Bayesian procedure for detecting copy number variations from sequencing read depths

Copy number variations (CNVs) are genomic structural mutations consisting of abnormal numbers of fragment copies. Next-generation sequencing of read-depth signals mirrors these variants. Some tools used to predict CNVs by depth have been published, but most of these tools can be applied to only a specific data type due to modeling limitations. We develop a tool for copy number variation detection by a Bayesian procedure, i.e., CONY, that adopts a Bayesian hierarchical model and an efficient reversible-jump Markov chain Monte Carlo inference algorithm for whole genome sequencing of read-depth data. CONY can be applied not only to individual samples for estimating the absolute number of copies but also to case-control pairs for detecting patient-specific variations. We evaluate the performance of CONY and compare CONY with competing approaches through simulations and by using experimental data from the 1000 Genomes Project. CONY outperforms the other methods in terms of accuracy in both single-sample and paired-samples analyses. In addition, CONY performs well regardless of whether the data coverage is high or low. CONY is useful for detecting both absolute and relative CNVs from read-depth data sequences. The package is available at https://github.com/weiyuchung/CONY.

Novel insights into breast cancer copy number genetic heterogeneity revealed by single-cell genome sequencing

Copy number alterations (CNAs) play an important role in molding the genomes of breast cancers and have been shown to be clinically useful for prognostic and therapeutic purposes. However, our knowledge of intra-tumoral genetic heterogeneity of this important class of somatic alterations is limited. Here, using single-cell sequencing, we comprehensively map out the facets of copy number alteration heterogeneity in a cohort of breast cancer tumors. Ou/var/www/html/elife/12-05-2020/backup/r analyses reveal: genetic heterogeneity of non-tumor cells (i.e. stroma) within the tumor mass; the extent to which copy number heterogeneity impacts breast cancer genomes and the importance of both the genomic location and dosage of sub-clonal events; the pervasive nature of genetic heterogeneity of chromosomal amplifications; and the association of copy number heterogeneity with clinical and biological parameters such as polyploidy and estrogen receptor negative status. Our data highlight the power of single-cell genomics in dissecting, in its many forms, intra-tumoral genetic heterogeneity of CNAs, the magnitude with which CNA heterogeneity affects the genomes of breast cancers, and the potential importance of CNA heterogeneity in phenomena such as therapeutic resistance and disease relapse.

Clinical Implications of Chromosomal Instability (CIN) and Kinetochore Abnormalities in Breast Cancers

Genetic instability is a defining property of cancer cells and is the basis of various lesions including point mutations, copy number alterations and translocations. Chromosomal instability (CIN) is part of the genetic instability of cancer and consists of copy number alterations in whole or parts of cancer cell chromosomes. CIN is observed in differing degrees in most cancers. In breast cancer, CIN is commonly part of the genomic landscape of the disease and has a higher incidence in aggressive sub-types. Tumor suppressors that are commonly mutated or disabled in cancer, such as p53 and pRB, play roles in protection against CIN, and as a result, their dysfunction contributes to the establishment or tolerance of CIN. Several structural and regulatory proteins of the centromeres and kinetochore, the complex structure that is responsible for the correct distribution of genetic material in the daughter cells during mitosis, are direct or, mostly, indirect transcription targets of p53 and pRB. Thus, despite the absence of structural defects in genes encoding for centromere and kinetochore components, dysfunction of these tumor suppressors may have profound implications for the correct function of the mitotic apparatus contributing to CIN. CIN and its prognostic and therapeutic implications in breast cancer are discussed in this article.

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

Feline mammary carcinomas (FMCs) are highly malignant. As the disease-free survival (DFS) and overall survival (OS) are short, prognostication is crucial. Copy-number variations (CNVs) analysis by next-generation sequencing serves to identify critical cancer-related genomic regions. Thirty-three female cats with FMCs were followed during two years after surgery. Tumours represented tubulopapillary and solid carcinomas encompassing six molecular subtypes. Regardless of the histopathological diagnosis, molecular subtypes showed important differences in survival. Luminal A tumours exhibited the highest DFS (p = 0.002) and cancer-specific OS (p = 0.001), and the lowest amount of CNVs (p = 0.0001). In contrast, basal-like triple-negative FMCs had the worst outcome (DFS, p < 0.0001; and OS, p < 0.00001) and were the most aberrant (p = 0.05). In the multivariate analysis, copy-number losses (CNLs) in chromosome B1 (1-23 Mb) harbouring several tumour-repressors (e.g. CSMD1, MTUS1, MSR1, DBC2, and TUSC3) negatively influenced DFS. Whereas, copy-number gains (CNGs) in B4 (1-29 Mb) and F2 (64-82.3 Mb) comprising epithelial to mesenchymal transition genes and metastasis-promoting transcription factors (e.g. GATA3, VIM, ZEB1, and MYC) negatively influenced DFS and cancer-specific OS. These data evidence an association between specific CNVs in chromosomes B1, B4 and F2, and poor prognosis in FMCs.

ATM-dependent activation of SIM2s regulates homologous recombination and epithelial-mesenchymal transition

There is increasing evidence that genomic instability is a prerequisite for cancer progression. Here we show that SIM2s, a member of the bHLH/PAS family of transcription factors, regulates DNA damage repair through enhancement of homologous recombination (HR), and prevents epithelial-mesenchymal transitions (EMT) in an Ataxia-telangiectasia mutated (ATM)-dependent manner. Mechanistically, we found that SIM2s interacts with ATM and is stabilized through ATM-dependent phosphorylation in response to IR. Once stabilized, SIM2s interacts with BRCA1 and supports RAD51 recruitment to the site of DNA damage. Loss of SIM2s through the introduction of shSIM2 or the mutation of SIM2s at one of the predicted ATM phosphorylation sites (S115) reduces HR efficiency through disruption of RAD51 recruitment, resulting in genomic instability and induction of EMT. The EMT induced by the mutation of S115 is characterized by a decrease in E-cadherin and an induction of the basal marker, K14, resulting in increased invasion and metastasis. Together, these results identify a novel player in the DNA damage repair pathway and provides a link in ductal carcinoma in situ progression to invasive ductal carcinoma through loss of SIM2s, increased genomic instability, EMT, and metastasis.

Circulating Tumor Cells: Strategies for Capture, Analyses, and Propagation

Circulating tumor cells (CTCs) play a central role in tumor dissemination and metastases, which are ultimately responsible for most cancer deaths. Technologies that allow for identification and enumeration of rare CTC from cancer patients' blood have already established CTC as an important clinical biomarker for cancer diagnosis and prognosis. Indeed, current efforts to robustly characterize CTC as well as the associated cells of the tumor microenvironment such as circulating cancer associated fibroblasts (cCAF), are poised to unmask key insights into the metastatic process. Ultimately, the clinical utility of CTC will be fully realized once CTC can be reliably cultured and proliferated as a biospecimen for precision management of cancer patients, and for discovery of novel therapeutics. In this review, we highlight the latest CTC capture and analyses technologies, and discuss in vitro strategies for culturing and propagating CTC.

Molecular and cellular basis of mammary gland fibrosis and cancer risk

Mammary gland luminal cells are maintained by the proliferation of ER- luminal progenitor (LP) cells. Human breast LP cells exhibit telomere DNA damage, which is associated with mammographic density and increased cancer risk. Telomeric repeat factor 2 (TRF2) protects telomeres from DNA damage response. TRF2 expression is reduced in human breast cancers. We deleted TRF2 expression in mammary gland epithelium. Mammary glands lacking TRF2 expression exhibited increased telomere DNA damage response, histopathological and functional degeneration, and prominent ductal fibrosis. TRF2-deficient mammary tumors exhibited rapid onset and increased proliferation. Tumor derived LP cells failed to form tumors after transplantation. The MSC population was highly tumorigenic and maintained telomeres via the ALT mechanism. Telomere DNA damage response in mammary tumors resulted in p53 dependent ER+ cellular differentiation and sensitivity to anti-estrogen therapy. Our results provide a new in vivo model of mammographic density, stem cell differentiation, cancer risk, and therapeutic sensitivity.

CDK5 Functions as a Tumor Promoter in Human Lung Cancer

Cyclin-dependent kinase 5 (CDK5), an atypical member of the cyclin-dependent kinase family, plays an important role in the nervous system. Recent studies have shown that CDK5 is also associated with tumors. However, few studies have been done to investigate the mechanism underlying the connection between CDK5 and cancers. To explore the role of CDK5 in cancers by using an extensive bioinformatics data mining process. We mined the transcriptional, survival, functions and structure of CDK5 gene through databases and in vitro experiments. We found that higher CDK5 expression levels in most cancer cell lines while lower expression in liver and brain cancer cell lines. High expression of CDK5 was associated with shorter overall survival (OS) in lung cancer. In addition, high expression level of CDK5 promoted lung cancer cells proliferation and metastasis. Inhibited CDK5 decreases CAP1 phosphorylation. CDK5 may prove to be a valid target of anticancer therapies.

Systematic expression alteration analysis of master reprogramming factor OCT4 and its three pseudogenes in human cancer and their prognostic outcomes

OCT4 is a master transcription factor that regulates the pluripotency of pluripotent stem cells and cancer stem cells along with other factors, including SOX2, KLF4, and C-MYC. Three different transcripts, OCT4A, OCT4B, and OCT4B1, are known to be generated by alternative splicing and eight OCT4 pseudogenes have been found in the human genome. Among them, we examined OCT4 and three pseudogenes (POU5F1P1, POU5F1P3, and POU5F1P4) because of their high expression possibility in cancer. In addition, previous studies indicated that OCT4 expression is augmented in cervical cancer and associated with poor prognosis, whereas OCT4 is down-regulated and correlated with good clinical outcomes in breast cancer. Because of these conflicting reports, we systematically evaluated whether expression of OCT4 and its pseudogenes can serve as oncogenic markers in various human cancers using the Oncomine database. Moreover, copy number alterations and mutations in OCT4 gene and its pseudogenes were analyzed using cBioPortal and the relationship between expression of OCT4 and pseudogenes and survival probability of cancer patients were explored using Kaplan-Meier plotter, OncoLnc, PROGgeneV2, and PrognoScan databases. Multivariate survival analysis was further conducted to determine the risk of the expression of the occurrence of OCT4 and its pseudogenes on certain cancer types using data from the Kaplan-Meier plotter. Overall, an association between expression of OCT4 and pseudogenes and cancer prognosis were established, which may serve as a therapeutic target for various human cancers.

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.

Genetic alterations detected by comparative genomic hybridization in BRCAX breast and ovarian cancers of Brazilian population

Background

About 5–10% of breast/ovarian cancers are hereditary. However, for a large proportion of cases (around 50%), the genetic cause remains unknown. These cases are grouped in a separated BRCAX category. The aim of this study was to identify genomic alterations in BRCA1/BRCA2 wild-type tumor samples from women with family history strongly suggestive of hereditary breast/ovarian cancer.

Results

A cohort of 31 Brazilian women was included in the study. Using the GISTIC algorithm, we identified 20 regions with genomic gains and 31 with losses. The most frequent altered regions were 1q21.2, 6p22.1 and 8p23.3 in breast tumors and Xq26 and Xp22.32-22.31 among the ovarian cancer cases. An interesting association identified was the loss of 22q13.31-13.32 and the presence of ovarian cancer cases. Among the genes present in the frequently altered regions, we found FGFR1, NSMCE2, CTTN, CRLF2, ERBB2, STARD3, MIR3201 and several genes of RAET and ULBP family.

Conclusions

In conclusion, our results suggest that alterations on chromosomes 1, 6, 8 and X are common on BRCAX tumors and that the loss on 22q can be associated with the presence of ovarian cancer.

Methods

DNA copy number alterations were analyzed by 60K array comparative genomic hybridization in breast and ovarian FFPE tumors.

Expanded Genomic Profiling of Circulating Tumor Cells in Metastatic Breast Cancer Patients to Assess Biomarker Status and Biology Over Time (CALGB 40502 and CALGB 40503, Alliance)

Purpose: We profiled circulating tumor cells (CTCs) to study the biology of blood-borne metastasis and to monitor biomarker status in metastatic breast cancer (MBC).Methods: CTCs were isolated from 105 patients with MBC using EPCAM-based immunomagnetic enrichment and fluorescence-activated cells sorting (IE/FACS), 28 of whom had serial CTC analysis (74 samples, 2-5 time points). CTCs were subjected to microfluidic-based multiplex QPCR array of 64 cancer-related genes (n = 151) and genome-wide copy-number analysis by array comparative genomic hybridization (aCGH; n = 49).Results: Combined transcriptional and genomic profiling showed that CTCs were 26% ESR1-ERBB2-, 48% ESR1+ERBB2-, and 27% ERBB2+ Serial testing showed that ERBB2 status was more stable over time compared with ESR1 and proliferation (MKI67) status. While cell-to-cell heterogeneity was observed at the single-cell level, with increasingly stable expression in larger pools, patient-specific CTC expression "fingerprints" were also observed. CTC copy-number profiles clustered into three groups based on the extent of genomic aberrations and the presence of large chromosomal imbalances. Comparative analysis showed discordance in ESR1/ER (27%) and ERBB2/HER2 (23%) status between CTCs and matched primary tumors. CTCs in 65% of the patients were considered to have low proliferation potential. Patients who harbored CTCs with high proliferation (MKI67) status had significantly reduced progression-free survival (P = 0.0011) and overall survival (P = 0.0095) compared with patients with low proliferative CTCs.Conclusions: We demonstrate an approach for complete isolation of EPCAM-positive CTCs and downstream comprehensive transcriptional/genomic characterization to examine the biology and assess breast cancer biomarkers in these cells over time. Clin Cancer Res; 24(6); 1486-99. ©2018 AACR.

Systematic analysis of gene expression alterations and clinical outcomes of adenylate cyclase-associated protein in cancer

Adenylate Cyclase-associated protein (CAP) is an evolutionarily conserved protein that regulates actin dynamics. Our previous study indicates that CAP1 is overexpressed in NSCLC tissues and correlated with poor clinical outcomes, but CAP1 in HeLa cells actually inhibited migration and invasion, the role of CAP was discrepancy in different cancer types. The present study aims to determine whether CAP can serve as a prognostic marker in human cancers. The CAP expression was assessed using Oncomine database to determine the gene alteration during carcinogenesis, the copy number alteration, or mutations of CAP using cBioPortal, International Cancer Genome Consortium, and Tumorscape database investigated, and the association between CAP expression and the survival of cancer patient using Kaplan-Meier plotter and PrognoScan database evaluated. Therefore, the functional correlation between CAP expression and cancer phenotypes can be established; wherein CAP might serve as a diagnostic marker or therapeutic target for certain types of cancers.

Normalized, Segmented or Called aCGH Data?

Array comparative genomic hybridization (aCGH) is a high-throughput lab technique to measure genome-wide chromosomal copy numbers. Data from aCGH experiments require extensive pre-processing, which consists of three steps: normalization, segmentation and calling. Each of these pre-processing steps yields a different data set: normalized data, segmented data, and called data. Publications using aCGH base their findings on data from all stages of the pre-processing. Hence, there is no consensus on which should be used for further down-stream analysis. This consensus is however important for correct reporting of findings, and comparison of results from different studies. We discuss several issues that should be taken into account when deciding on which data are to be used. We express the believe that called data are best used, but would welcome opposing views.

Statistical Contributions to Bioinformatics: Design, Modeling, Structure Learning, and Integration

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologiees yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to effectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, focusing on four areas: (1) experimental design and reproducibility, (2) preprocessing and feature extraction, (3) unified modeling, and (4) structure learning and integration. In each of these areas, we highlight some key contributions and try to elucidate the key statistical principles underlying these methods and approaches. Our goals are to demonstrate major ways in which statisticians have contributed to bioinformatics, encourage statisticians to get involved early in methods development as new technologies emerge, and to stimulate future methodological work based on the statistical principles elucidated in this article and utilizing all availble information to uncover new biological insights.

Inherent variability of cancer-specific aneuploidy generates metastases

Background

The genetic basis of metastasis is still unclear because metastases carry individual karyotypes and phenotypes, rather than consistent mutations, and are rare compared to conventional mutation. There is however correlative evidence that metastasis depends on cancer-specific aneuploidy, and that metastases are karyotypically related to parental cancers. Accordingly we propose that metastasis is a speciation event. This theory holds that cancer-specific aneuploidy varies the clonal karyotypes of cancers automatically by unbalancing thousands of genes, and that rare variants form new autonomous subspecies with metastatic or other non-parental phenotypes like drug-resistance – similar to conventional subspeciation.

Results

To test this theory, we analyzed the karyotypic and morphological relationships between seven cancers and corresponding metastases. We found (1) that the cellular phenotypes of metastases were closely related to those of parental cancers, (2) that metastases shared 29 to 96% of their clonal karyotypic elements or aneusomies with the clonal karyotypes of parental cancers and (3) that, unexpectedly, the karyotypic complexity of metastases was very similar to that of the parental cancer. This suggests that metastases derive cancer-specific autonomy by conserving the overall complexity of the parental karyotype. We deduced from these results that cancers cause metastases by karyotypic variations and selection for rare metastatic subspecies. Further we asked whether metastases with multiple metastasis-specific aneusomies are assembled in one or multiple, sequential steps. Since (1) no stable karyotypic intermediates of metastases were observed in cancers here and previously by others, and (2) the karyotypic complexities of cancers are conserved in metastases, we concluded that metastases are generated from cancers in one step – like subspecies in conventional speciation.

Conclusions

We conclude that the risk of cancers to metastasize is proportional to the degree of cancer-specific aneuploidy, because aneuploidy catalyzes the generation of subspecies, including metastases, at aneuploidy-dependent rates. Since speciation by random chromosomal rearrangements and selection is unpredictable, the theory that metastases are karyotypic subspecies of cancers also explains Foulds’ rules, which hold that the origins of metastases are “abrupt” and that their phenotypes are “unpredictable.”

Sequencing Structural Variants in Cancer for Precision Therapeutics

The identification of mutations that guide therapy selection for patients with cancer is now routine in many clinical centres. The majority of assays used for solid tumour profiling use DNA sequencing to interrogate somatic point mutations because they are relatively easy to identify and interpret. Many cancers, however, including high-grade serous ovarian, oesophageal, and small-cell lung cancer, are driven by somatic structural variants that are not measured by these assays. Therefore, there is currently an unmet need for clinical assays that can cheaply and rapidly profile structural variants in solid tumours. In this review we survey the landscape of 'actionable' structural variants in cancer and identify promising detection strategies based on massively-parallel sequencing.

Amplification of TLK2 Induces Genomic Instability via Impairing the G2-M Checkpoint

Managing aggressive breast cancers with enhanced chromosomal instability (CIN) is a significant challenge in clinics. Previously, we described that a cell cycle-associated kinase called Tousled-like kinase 2 (TLK2) is frequently deregulated by genomic amplifications in aggressive estrogen receptor-positive (ER⁺) breast cancers. In this study, it was discovered that TLK2 amplification and overexpression mechanistically impair Chk1/2-induced DNA damage checkpoint signaling, leading to a G₂-M checkpoint defect, delayed DNA repair process, and increased CIN. In addition, TLK2 overexpression modestly sensitizes breast cancer cells to DNA-damaging agents, such as irradiation or doxorubicin. To our knowledge, this is the first report linking TLK2 function to CIN, in contrast to the function of its paralog TLK1 as a guardian of genome stability. This finding yields new insight into the deregulated DNA damage pathway and increased genomic instability in aggressive ER⁺ breast cancers.

IMPLICATIONS

Targeting TLK2 presents an attractive therapeutic strategy for the TLK2-amplified breast cancers that possess enhanced genomic instability and aggressiveness. Mol Cancer Res; 14(10); 920-7. ©2016 AACR.

Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types

The identification of good targets is a critical step for the development of targeted therapies for cancer treatment. Here, we used a multi-omics approach to delineate potential targets on chromosome 20q, which frequently shows a complex pattern of DNA copy number amplification in many human cancers suggesting the presence of multiple driver genes. By comparing the amounts of individual mRNAs in cancer from 11 different human tissues with those in their corresponding normal tissues, we identified 18 genes that were robustly elevated across human cancers. Moreover, we found that higher expression levels of a majority of these genes were associated with poor prognosis in many human cancer types. Using DNA copy number and expression data for all 18 genes obtained from The Cancer Genome Atlas project, we discovered that amplification is a major mechanism driving overexpression of these 18 genes in the majority of human cancers. Our integrated analysis suggests that 18 genes on chromosome 20q might serve as novel potential molecular targets for targeted cancer therapy.

Different Array CGH profiles within hereditary breast cancer tumors associated to BRCA1 expression and overall survival

Background

Array CGH analysis of breast tumors has contributed to the identification of different genomic profiles in these tumors. Loss of DNA repair by BRCA1 functional deficiency in breast cancer has been proposed as a relevant contribution to breast cancer progression for tumors with no germline mutation. Identifying the genomic alterations taking place in BRCA1 not expressing tumors will lead us to a better understanding of the cellular functions affected in this heterogeneous disease. Moreover, specific genomic alterations may contribute to the identification of potential therapeutic targets and offer a more personalized treatment to breast cancer patients.

Methods

Forty seven tumors from hereditary breast cancer cases, previously analyzed for BRCA1 expression, and screened for germline BRCA1 and 2 mutations, were analyzed by Array based Comparative Genomic Hybridization (aCGH) using Agilent 4x44K arrays. Overall survival was established for tumors in different clusters using Log-rank (Mantel-Cox) Test. Gene lists obtained from aCGH analysis were analyzed for Gene Ontology enrichment using GOrilla and DAVID tools.

Results

Genomic profiling of the tumors showed specific alterations associated to BRCA1 or 2 mutation status, and BRCA1 expression in the tumors, affecting relevant cellular processes. Similar cellular functions were found affected in BRCA1 not expressing and BRCA1 or 2 mutated tumors. Hierarchical clustering classified hereditary breast tumors in four major, groups according to the type and amount of genomic alterations, showing one group with a significantly poor overall survival (p = 0.0221). Within this cluster, deletion of PLEKHO1, GDF11, DARC, DAG1 and CD63 may be associated to the worse outcome of the patients.

Conclusions

These results support the fact that BRCA1 lack of expression in tumors should be used as a marker for BRCAness and to select these patients for synthetic lethality approaches such as treatment with PARP inhibitors. In addition, the identification of specific alterations in breast tumors associated with poor survival, immune response or with a BRCAness phenotype will allow the use of a more personalized treatment in these patients.

Laminin-binding integrin gene copy number alterations in distinct epithelial-type cancers

BACKGROUND

The laminin-binding integrin (LBI) family are cell adhesion molecules that are essential for invasion and metastasis of human epithelial cancers and cell adhesion mediated drug resistance. We investigated whether copy number alteration (CNA) or mutations of a five-gene signature (ITGB4, ITGA3, LAMB3, PLEC, and SYNE3), representing essential genes for LBI adhesion, would correlate with patient outcomes within human epithelial-type tumor data sets currently available in an open access format.

METHODS

We investigated the relative alteration frequency of an LBI signature panel (integrin β4 (ITGB4), integrin α3 (ITGA3), laminin β3 chain (LAMB3), plectin (PLEC), and nesprin 3 (SYNE3)), independent of the epithelial cancer type, within publically available and published data using cBioPortal and Oncomine software. We rank ordered the results using a 20% alteration frequency cut-off and limited the analysis to studies containing at least 100 samples. Kaplan-Meier survival curves were analyzed to determine if alterations in the LBI signature correlated with patient survival. The Oncomine data mining tool was used to compare the heat map expression of the LBI signature without SYNE3 (as this was not included in the Oncomine database) to drug resistance patterns.

RESULTS

Twelve different cancer types, representing 5,647 samples, contained at least a 20% alteration frequency of the five-gene LBI signature. The frequency of alteration ranged from 38.3% to 19.8%. Within the LBI signature, PLEC was the most commonly altered followed by LAMB3, ITGB4, ITGA3, and SYNE3 across all twelve cancer types. Within cancer types, there was little overlap of the individual amplified genes from each sample, suggesting different specific amplicons may alter the LBI adhesion structures. Of the twelve cancer types, overall survival was altered by CNA presence in bladder urothelial carcinoma (p=0.0143*) and cervical squamous cell carcinoma and endocervical adenocarcinoma (p=0.0432*). Querying the in vitro drug resistance profiles with the LBI signature demonstrated a positive correlation with cells resistant to inhibitors of HDAC (Vorinostat, Panobinostat) and topoisomerase II (Irinotecan). No correlation was found with the following agents: Bleomycin, Doxorubicin, Methotrexate, Gemcitabine, Docetaxel, Bortezomib, and Shikonen.

CONCLUSIONS

Our work has identified epithelial-types of human cancer that have significant CNA in our selected five-gene signature, which was based on the essential and genetically-defined functions of the protein product networks (in this case, the LBI axis). CNA of the gene signature not only predicted overall survival in bladder, cervical, and endocervical adenocarcinoma but also response to chemotherapy. This work suggests that future studies designed to optimize the gene signature are warranted.

GENERAL SIGNIFICANCE

The copy number alteration of structural components of the LBI axis in epithelial-type tumors may be promising biomarkers and rational targets for personalized therapy in preventing or arresting metastatic spread.

Patterns of Chromosomal Aberrations in Solid Tumors

Chromosomal abnormalities are a defining feature of solid tumors. Such cytogenetic alterations are mainly classified into structural chromosomal aberrations and copy number alterations, giving rise to aneuploid karyotypes. The increasing detection of these genetic changes allowed the description of specific tumor entities and the associated patterns of gene expression. In fact, tumor-specific landscapes of gross genomic copy number changes, including aneuploidies of entire chromosome arms and chromosomes result in a global deregulation of the transcriptome of cancer cells. Furthermore, the molecular characterization of cytogenetic abnormalities has provided insights into the mechanisms of tumorigenesis and has, in a few instances, led to the clinical implementation of effective diagnostic and prognostic tools, as well as treatment strategies that target a specific genetic abnormality.

Estrogen receptor mutations and functional consequences for breast cancer

A significant number of estrogen receptor α (ERα)-positive breast tumors develop resistance to endocrine therapy and recur with metastatic disease. Several mechanisms of endocrine resistance have been proposed, including genetic alterations that lead to ERs with altered protein sequence. By altering the conformation of the protein and increasing the interaction with coactivators, point mutations in ESR1, the gene encoding ERα, promote an active form of the receptor in the absence of hormone that assists tumor cells to evade hormonal treatments. Recent studies have confirmed that ESR1 point mutations frequently occur in metastatic breast tumors that are refractory to endocrine therapy, and suggest the development of novel strategies that may be more effective in controlling ER signaling and benefit patients with recurrent and metastatic disease.

Identification of Copy Number Aberrations in Breast Cancer Subtypes Using Persistence Topology

DNA copy number aberrations (CNAs) are of biological and medical interest because they help identify regulatory mechanisms underlying tumor initiation and evolution. Identification of tumor-driving CNAs (driver CNAs) however remains a challenging task, because they are frequently hidden by CNAs that are the product of random events that take place during tumor evolution. Experimental detection of CNAs is commonly accomplished through array comparative genomic hybridization (aCGH) assays followed by supervised and/or unsupervised statistical methods that combine the segmented profiles of all patients to identify driver CNAs. Here, we extend a previously-presented supervised algorithm for the identification of CNAs that is based on a topological representation of the data. Our method associates a two-dimensional (2D) point cloud with each aCGH profile and generates a sequence of simplicial complexes, mathematical objects that generalize the concept of a graph. This representation of the data permits segmenting the data at different resolutions and identifying CNAs by interrogating the topological properties of these simplicial complexes. We tested our approach on a published dataset with the goal of identifying specific breast cancer CNAs associated with specific molecular subtypes. Identification of CNAs associated with each subtype was performed by analyzing each subtype separately from the others and by taking the rest of the subtypes as the control. Our results found a new amplification in 11q at the location of the progesterone receptor in the Luminal A subtype. Aberrations in the Luminal B subtype were found only upon removal of the basal-like subtype from the control set. Under those conditions, all regions found in the original publication, except for 17q, were confirmed; all aberrations, except those in chromosome arms 8q and 12q were confirmed in the basal-like subtype. These two chromosome arms, however, were detected only upon removal of three patients with exceedingly large copy number values. More importantly, we detected 10 and 21 additional regions in the Luminal B and basal-like subtypes, respectively. Most of the additional regions were either validated on an independent dataset and/or using GISTIC. Furthermore, we found three new CNAs in the basal-like subtype: a combination of gains and losses in 1p, a gain in 2p and a loss in 14q. Based on these results, we suggest that topological approaches that incorporate multiresolution analyses and that interrogate topological properties of the data can help in the identification of copy number changes in cancer.

Appraisal of the technologies and review of the genomic landscape of ductal carcinoma in situ of the breast

Ductal carcinoma in situ is a biologically diverse entity. Whereas some lesions are cured by local surgical excision, others recur as in situ disease or progress to invasive carcinoma with subsequent potential for metastatic spread. Reliable prognostic biomarkers are therefore desirable for appropriate clinical management but remain elusive. In common with invasive breast cancer, ductal carcinoma in situ exhibits many genomic changes, predominantly copy number alterations. Although studies have revealed the genomic heterogeneity within individual ductal carcinoma in situ lesions and the association of certain copy number alterations with nuclear grade, none of the genomic changes defined so far is consistently associated with invasive transformation or recurrence risk in pure ductal carcinoma in situ. This article will review the current landscape of genomic alterations in ductal carcinoma in situ and their potential as prognostic biomarkers together with the technologies used to define these.

Allelic imbalance at the HER2/TOP2A locus in breast cancer

BACKGROUND

Breast cancer is a heterogeneous disease with various histological features and molecular markers. These are utilized for the prediction of clinical outcome and therapeutic decision making. In addition to well established markers such as HER2 overexpression and estrogen and progesterone receptor (ER and PR) status, chromosomal instability is evolving as an important hallmark of cancers. The HER2/TOP2A locus is of great importance in breast cancer. The copy number variability at this locus has been proposed to be a marker for the degree of chromosomal instability. We therefore developed a Single Nucleotide Polymorphism (SNP) assay to evaluate allelic imbalance at the HER2/TOP2A locus in three different entities of primary breast tumors.

METHODS

Eleven SNPs were carefully selected and detected by real time PCR using DNA extracted from paired (histologically normal and tumor) paraffin-embedded tissues. Primary breast tumors of 44 patients were included, 15 tumors with HER2 overexpression, 16 triple negative tumors, defined by the absence of HER2 overexpression and a negative ER and PR status and 13 ER and PR positive tumors without HER2 overexpression. As controls, histologically normal breast tissues from 10 patients with no breast tumor were included.

RESULTS

Allelic imbalance was observed in 13/15 (87 %) HER2 positive tumors, the remaining 2 being inconclusive. Of the 16 triple negative tumors, 12 (75 %) displayed instability, 3 (19 %) displayed no instability, and 1 was inconclusive. Of the 13 hormone receptor positive tumors, 5 (38 %) displayed allelic imbalance, while 8 did not.

CONCLUSIONS

We conclude that the SNP assay is suitable for rapid testing of allelic (im)balance at the HER2/TOP2A locus using paraffin-embedded tissues. Based on allelic imbalance at this locus, both triple negative and ER and PR positive breast tumors can be subcategorized. The clinical relevance of the allelic (im)balance status at the HER2/TOP2A locus in breast cancer is subject of future study.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2086062232155220.

Enriched transcription factor signatures in triple negative breast cancer indicates possible targeted therapies with existing drugs

PURPOSE

Triple negative (TN) breast cancers which lack expression of the estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER2) receptors convey a poor prognosis due in part to a lack of targeted therapies.

METHODS

To identify viable targets for the treatment of TN disease, we have conducted a gene set enrichment analysis (GSEA) on seven different breast cancer whole genome gene expression cohorts comparing TN vs. ER + HER2 - to identify consistently enriched genes that share a common promoter motif. The seven cohorts were profiled on three different genome expression platforms (Affymetrix, Illumina and RNAseq) consisting in total of 2088 samples with IHC metadata.

RESULTS

GSEA identified enriched gene expression patterns in TN samples that share common promoter motifs associated with SOX9, E2F1, HIF1A, HMGA1, MYC BACH2, CEBPB, and GCNF/NR6A1. Unexpectedly, NR6A1 an orphan nuclear receptor normally expressed in germ cells of gonads is highly expressed in TN and ER + HER2 - samples making it an ideal drug target.

CONCLUSION

With the increasing number of large sample size breast cancer cohorts, an exploratory analysis of genes that are consistently enriched in TN sharing common promoter motifs allows for the identification of possible therapeutic targets with extensive validation in patient derived data sets.

Bioinformatics analysis of circulating cell-free DNA sequencing data

The discovery of cell-free DNA molecules in plasma has opened up numerous opportunities in noninvasive diagnosis. Cell-free DNA molecules have become increasingly recognized as promising biomarkers for detection and management of many diseases. The advent of next generation sequencing has provided unprecedented opportunities to scrutinize the characteristics of cell-free DNA molecules in plasma in a genome-wide fashion and at single-base resolution. Consequently, clinical applications of circulating cell-free DNA analysis have not only revolutionized noninvasive prenatal diagnosis but also facilitated cancer detection and monitoring toward an era of blood-based personalized medicine. With the remarkably increasing throughput and lowering cost of next generation sequencing, bioinformatics analysis becomes increasingly demanding to understand the large amount of data generated by these sequencing platforms. In this Review, we highlight the major bioinformatics algorithms involved in the analysis of cell-free DNA sequencing data. Firstly, we briefly describe the biological properties of these molecules and provide an overview of the general bioinformatics approach for the analysis of cell-free DNA. Then, we discuss the specific upstream bioinformatics considerations concerning the analysis of sequencing data of circulating cell-free DNA, followed by further detailed elaboration on each key clinical situation in noninvasive prenatal diagnosis and cancer management where downstream bioinformatics analysis is heavily involved. We also discuss bioinformatics analysis as well as clinical applications of the newly developed massively parallel bisulfite sequencing of cell-free DNA. Finally, we offer our perspectives on the future development of bioinformatics in noninvasive diagnosis.

Characterization of genomic alterations in radiation-associated breast cancer among childhood cancer survivors, using comparative genomic hybridization (CGH) arrays

Ionizing radiation is an established risk factor for breast cancer. Epidemiologic studies of radiation-exposed cohorts have been primarily descriptive; molecular events responsible for the development of radiation-associated breast cancer have not been elucidated. In this study, we used array comparative genomic hybridization (array-CGH) to characterize genome-wide copy number changes in breast tumors collected in the Childhood Cancer Survivor Study (CCSS). Array-CGH data were obtained from 32 cases who developed a second primary breast cancer following chest irradiation at early ages for the treatment of their first cancers, mostly Hodgkin lymphoma. The majority of these cases developed breast cancer before age 45 (91%, n = 29), had invasive ductal tumors (81%, n = 26), estrogen receptor (ER)-positive staining (68%, n = 19 out of 28), and high proliferation as indicated by high Ki-67 staining (77%, n = 17 out of 22). Genomic regions with low-copy number gains and losses and high-level amplifications were similar to what has been reported in sporadic breast tumors, however, the frequency of amplifications of the 17q12 region containing human epidermal growth factor receptor 2 (HER2) was much higher among CCSS cases (38%, n = 12). Our findings suggest that second primary breast cancers in CCSS were enriched for an “amplifier” genomic subgroup with highly proliferative breast tumors. Future investigation in a larger irradiated cohort will be needed to confirm our findings.

FAM83D promotes cell proliferation and motility by downregulating tumor suppressor gene FBXW7

Abstract Amplification of chromosome 20q is frequently found in various types of human cancers, including breast cancer. The list of candidate oncogenes in 20q has expanded over the past decade. Here, we investigate whether FAM83D (family with sequence similarity 83, member D) on chromosome 20q plays any role in breast cancer development. The expression level of FAM83D is significantly elevated in breast cancer cell lines and primary human breast cancers. High expression levels of FAM83D are significantly associated with poor clinical outcome and distant metastasis in breast cancer patients. We show that ectopic expression of FAM83D in human mammary epithelial cells promotes cell proliferation, migration and invasion along with epithelial-mesenchymal transition (EMT). Ablation of FAM83D in breast cancer cells induces apoptosis and consequently inhibits cell proliferation and colony formation. Mechanistic studies reveal that overexpression of FAM83D downregulates FBXW7 expression levels through a physical interaction, which results in elevated protein levels of oncogenic substrates downstream to FBXW7, such as mTOR, whose inhibition by rapamycin can suppress FAM83D-induced cell migration and invasion. The results demonstrate that FAM83D has prognostic value for breast cancer patients and is a novel oncogene in breast cancer development that at least in part acts through mTOR hyper-activation by inhibiting FBXW7.

Chromosome 17 centromere duplication and responsiveness to anthracycline-based neoadjuvant chemotherapy in breast cancer

Human epidermal growth factor receptor 2 (HER2) and topoisomerase II alpha (TOP2A) genes have been proposed as predictive biomarkers of sensitivity to anthracycline chemotherapy. Recently, chromosome 17 centromere enumeration probe (CEP17) duplication has also been associated with increased responsiveness to anthracyclines. However, reports are conflicting and none of these tumor markers can yet be considered a clinically reliable predictor of response to anthracyclines. We studied the association of TOP2A gene alterations, HER2 gene amplification, and CEP17 duplication with response to anthracycline-based neoadjuvant chemotherapy in 140 patients with operable or locally advanced breast cancer. HER2 was tested by fluorescence in situ hybridization and TOP2A and CEP17 by chromogenic in situ hybridization. Thirteen patients (9.3%) achieved pathologic complete response (pCR). HER2 amplification was present in 24 (17.5%) of the tumors. TOP2A amplification occurred in seven tumors (5.1%). CEP17 duplication was detected in 13 patients (9.5%). CEP17 duplication correlated with a higher rate of pCR [odds ratio (OR) 6.55, 95% confidence interval (95% CI) 1.25-34.29, P = .026], and analysis of TOP2A amplification showed a trend bordering on statistical significance (OR 6.97, 95% CI 0.96-50.12, P = .054). TOP2A amplification and CEP17 duplication combined were strongly associated with pCR (OR 6.71, 95% CI 1.66-27.01, P = .007). HER2 amplification did not correlate with pCR. Our results suggest that CEP17 duplication predicts pCR to primary anthracycline-based chemotherapy. CEP17 duplication, TOP2A amplifications, and HER2 amplifications were not associated with prognosis.

Integration of mRNA expression profile, copy number alterations, and microRNA expression levels in breast cancer to improve grade definition

Defining the aggressiveness and growth rate of a malignant cell population is a key step in the clinical approach to treating tumor disease. The correct grading of breast cancer (BC) is a fundamental part in determining the appropriate treatment. Biological variables can make it difficult to elucidate the mechanisms underlying BC development. To identify potential markers that can be used for BC classification, we analyzed mRNAs expression profiles, gene copy numbers, microRNAs expression and their association with tumor grade in BC microarray-derived datasets. From mRNA expression results, we found that grade 2 BC is most likely a mixture of grade 1 and grade 3 that have been misclassified, being described by the gene signature of either grade 1 or grade 3. We assessed the potential of the new approach of integrating mRNA expression profile, copy number alterations, and microRNA expression levels to select a limited number of genomic BC biomarkers. The combination of mRNA profile analysis and copy number data with microRNA expression levels led to the identification of two gene signatures of 42 and 4 altered genes (FOXM1, KPNA4, H2AFV and DDX19A) respectively, the latter obtained through a meta-analytical procedure. The 42-based gene signature identifies 4 classes of up- or down-regulated microRNAs (17 microRNAs) and of their 17 target mRNA, and the 4-based genes signature identified 4 microRNAs (Hsa-miR-320d, Hsa-miR-139-5p, Hsa-miR-567 and Hsa-let-7c). These results are discussed from a biological point of view with respect to pathological features of BC. Our identified mRNAs and microRNAs were validated as prognostic factors of BC disease progression, and could potentially facilitate the implementation of assays for laboratory validation, due to their reduced number.

Molecular profiling of male breast cancer - lost in translation?

Breast cancer is the most common cancer form in women and it has been extensively studied on the molecular level. Male breast cancer (MBC), on the other hand, is rare and has not been thoroughly investigated in terms of transcriptional profiles or genomic aberrations. Most of our understanding of MBC has therefore been extrapolated from knowledge of female breast cancer. Although differences in addition to similarities with female breast cancer have been reported, the same prognostic and predictive markers are used to determine optimal management strategies for both men and women diagnosed with breast cancer. This review is focused on prognosis for MBC patients, prognostic and predictive factors and molecular subgrouping; comparisons are made with female breast cancer. Information was collected from relevant literature on both male and female breast cancer from the MEDLINE database between 1992 and 2014. MBC is a heterogeneous disease, and on the molecular level many differences compared to female breast cancer have recently been revealed. Two distinct subgroups of MBC, luminal M1 and luminal M2, have been identified which differ from the well-established intrinsic subtypes of breast cancer in women. These novel subgroups of breast cancer therefore appear unique to MBC. Furthermore, several studies report inferior survival for men diagnosed with breast cancer compared to women. New promising prognostic biomarkers for MBC (e.g. NAT1) deserving further attention are reviewed. Further prospective studies aimed at validating the novel subgroups and recently proposed biomarkers for MBC are warranted to provide the basis for optimal patient management in this era of personalized medicine. This article is part of a Directed Issue entitled: Rare Cancers.

Genome-wide copy number analysis of cerebrospinal fluid tumor cells and their corresponding archival primary tumors

A debilitating complication of breast cancer is the metastatic spread of tumor cells to the leptomeninges or cerebrospinal fluid (CSF). Patients diagnosed with this aggressive clinical syndrome, known as leptomeningeal carcinomatosis, have very poor prognosis. Despite improvements in detecting cerebrospinal fluid tumor cells (CSFTCs), information regarding their molecular biology is extremely limited. In our recent work, we utilized a protocol previously used for circulating tumor cell isolation to purify tumor cells from the CSF. We then performed genomic characterization of CSFTCs as well as archival tumors from the same patient. Here, we describe the microarray data and quality controls associated with our study published in the Cancer Research journal in 2013 [1]. We also provide an R script containing code for quality control of microarray data and assessment of copy number calls. The microarray data has been deposited into Gene Expression Omnibus under accession # GSE46068.

Evaluation of a large library of (thiazol-2-yl)hydrazones and analogues as histone acetyltransferase inhibitors: enzyme and cellular studies

Recently we described some (thiazol-2-yl)hydrazones as antiprotozoal, antifungal and anti-MAO agents as well as Gcn5 HAT inhibitors. Among these last compounds, CPTH2 and CPTH6 showed HAT inhibition in cells and broad anticancer properties. With the aim to identify HAT inhibitors more potent than the two prototypes, we synthesized several new (thiazol-2-yl)hydrazones including some related thiazolidines and pyrimidin-4(3H)-ones, and we tested the whole library existing in our lab against human p300 and PCAF HAT enzymes. Some compounds (1x, 1c', 1d', 1i' and 2m) were more efficient than CPTH2 and CPTH6 in inhibiting the p300 HAT enzyme. When tested in human leukemia U937 and colon carcinoma HCT116 cells (100 μM, 30 h), 1x, 1i' and 2m gave higher (U937 cells) or similar (HCT116 cells) apoptosis than CPTH6, and were more potent than CPTH6 in inducing cytodifferentiation (U937 cells).

Fluorescence in situ hybridization (FISH): an increasingly demanded tool for biomarker research and personalized medicine

Extensive studies of the genetic aberrations related to human diseases conducted over the last two decades have identified recurrent genomic abnormalities as potential driving factors underlying a variety of cancers. Over the time, a series of cutting-edge high-throughput genetic tests, such as microarrays and next-generation sequencing, have been developed and incorporated into routine clinical practice. Although it is a classical low-throughput cytogenetic test, fluorescence in situ hybridization (FISH) does not show signs of fading; on the contrary, it plays an increasingly important role in detecting specific biomarkers in solid and hematologic neoplasms and has therefore become an indispensable part of the rapidly developing field of personalized medicine. In this article, we have summarized the recent advances in FISH application for both de novo discovery and routine detection of chromosomal rearrangements, amplifications, and deletions that are associated with the pathogenesis of various hematopoietic and non-hematopoietic malignancies. In addition, we have reviewed the recent developments in FISH methodology as well.

Gene aberrations of RRM1 and RRM2B and outcome of advanced breast cancer after treatment with docetaxel with or without gemcitabine

Background

The purpose of the present study was to retrospectively evaluate whether copy number changes of the genes encoding the ribonucleotide reductase subunit M1 (RRM1) and/or subunit M2B (RRM2B) predict sensitivity to gemcitabine administered in combination with docetaxel compared to single agent docetaxel in advanced breast cancer patients.

Methods

Primary tumor samples from patients randomly assigned to gemcitabine plus docetaxel or docetaxel alone were analyzed for RRM1 and RRM2B copy number changes using Fluorescence In Situ Hybridization (FISH) technology with probes covering respectively RRM1 at 11p15.5 and a reference probe covering the centromere of chromosome 11 (CEN-11), and RRM2B at 8q22.3 and a reference probe covering the centromere of chromosome 8 (CEN-8). The assays were validated in a material of 60 normal breast samples. Time to progression (TTP) was the primary endpoint. Overall survival (OS) and response rate (RR) were secondary endpoints. Associations between RRM1/CEN-11 and/or RRM2B/CEN-8 ratios and time-to-event endpoints were analyzed by unadjusted and adjusted Cox proportional hazards regression models. Heterogeneity of treatment effects on TTP and OS according to gene status were investigated by subgroup analyses, and the Wald test was applied. All statistical tests were two-sided.

Results

FISH analysis for both RRM1 and RRM2B was successful in 251 patients. RRM1 and RRM2B aberrations (deletions and amplifications) were observed in 15.9% and 13.6% of patients, respectively. RRM1 aberrations were associated with a decreased OS in the time interval 1.5-7.4 years (hazard ratio = 1.72, 95% confidence interval = 1.05-2.79, P = 0.03). RRM2B aberrations alone or in combination with RRM1 aberrations had no prognostic impact in terms of TTP or OS. RR was not different by gene status. No significant differences were detected in TTP or OS within subgroups according to gene status and chemotherapy regimen.

Conclusions

This study demonstrated the presence of RRM1 and RRM2B copy number changes in primary breast tumor specimens. Nevertheless, we found no support of the hypothesis that aberrations of RRM1 or RRM2B, neither individually nor in combination, are associated with an altered clinical outcome following chemotherapy with gemcitabine in combination with docetaxel compared to docetaxel alone in advanced breast cancer patients.

Molecular profiling of tumor cells in cerebrospinal fluid and matched primary tumors from metastatic breast cancer patients with leptomeningeal carcinomatosis

Although leptomeningeal carcinomatosis is a well-established clinical syndrome, virtually nothing is known about the tumor cells responsible for this particularly aggressive metastatic process. To isolate cerebrospinal fluid-derived tumor cells (CSFTC) from 15 patients with metastatic breast cancer diagnosed with leptomeningeal carcinomatosis, CSF samples were subjected to a two-step method involving immunomagnetic enrichment and fluorescence-activated cell sorting (IE/FACS), a technique previously used for isolating circulating tumor cells (CTC) from blood. CSFTCs were subjected to genome-wide copy number analysis by array comparative genomic hybridization. Genomic profiling was successfully performed for 13 of 15 patients (87%). Copy number analysis in CSFTCs revealed genomic alterations commonly observed in primary breast cancer and CTCs, indicating their malignant origin. Interestingly, 12 (92%) harbored high-level gains on the 8q24 locus, which includes the MYC oncogene. Comparison of CSFTCs against corresponding archival primary tumors in six patients revealed clonal relationships with some divergence. Good concordance among serial samples attested to the reproducibility of the assay. Our approach for isolation and molecular analysis of CSFTCs yielded new insights into the molecular nature of these cells. Further genomic and functional analyses may help elucidate mechanisms by which tumor cells metastasize to the central nervous system.

Mycosis fungoides and Sézary syndrome

The development of array comparative genomic hybridization (aCGH) techniques has allowed to characterize more precisely several human neoplasms with the aim of providing prognostic markers and targets for directed therapeutic intervention. Recently, several studies applying aCGH technique have been reported in which an exhaustive genetic characterization of mycosis fungoides (MF) and Sézary syndrome (SS) has been performed. Regarding MF, a genomic profile characterized by the gains of 7q, 17q, and 8q and losses in 9p, 13q, 17p, and 10q has been described. In SS, the most common abnormalities are gains in 8q and 17q and losses at 17p and 10q. One of the main contributions of the aCGH studies in MF and SS has been the description of genetic markers associated with a poor prognosis. In MF, three specific chromosomal regions, 9p21.3 (CDKN2A, CDKN2B, and MTAP), 8q24.21 (MYC), and 10q26qter (MGMT and EBF3) have been defined as prognostic markers exhibiting a significant correlation with overall survival (P = 0.042, P = 0.017, and P = 0.022, respectively). Moreover, two MF genomic subgroups have been described, distinguishing a stable group (0-5 DNA aberrations) and an unstable group (>5 DNA aberrations), showing that the genomic unstable group had a shorter overall survival (P = 0.05).

A novel measure of chromosome instability can account for prognostic difference in multiple myeloma

Multiple myeloma (MM) is characterized by complex genetic abnormalities whose complexity signifies varying degree of chromosomal instability (CIN). In this study, we introduced a novel CIN measure, chromosome instability genome event count (CINGEC), which considered both copy number aberrations and interstitial breakpoints from high-resolution genome-wide assays. When assessed in two aCGH MM datasets, higher CINGEC was associated with poor survival. We then derived a CINGEC-associated gene expression profile (GEP) signature, CINGECS, using a dataset that has both aCGH and GEP. Genes in CINGECS were mainly involved in DNA damage responses besides in aneuploidy and other generic oncogenic processes contrary to other CIN associated GEP signatures. Finally, we confirmed its survival association in three GEP datasets that encompassed newly diagnosed patients treated with transplant-based protocol with or without novel agents for induction as well as relapsed patients treated with bortezomib. Furthermore, CINGECS was independent of many GEP-based prognostic signatures. In conclusion, our novel CIN measure has definite biological and clinical significance in myeloma.

Lack of genomic rearrangements involving the aromatase gene CYP19A1 in breast cancer

Increased intratumoral expression of aromatase, the key enzyme for estrogen biosynthesis, is predicted to be of critical importance in the development of breast cancer. Recently, several germline rearrangements at 15q21 have been shown to cause overexpression of the aromatase gene CYP19A1 and resulting aromatase excess syndrome. To determine whether submicroscopic genomic rearrangements at 15q21 are involved in aromatase overexpression in breast cancer tissues, we investigated copy-number alterations in genomic DNA obtained from 44 tumor samples. Comparative genomic hybridization analysis identified no deletion or duplication at 15q21 in the 44 samples. These results, in conjunction with previous data, indicate that aromatase overexpression in breast cancer tissues is likely to result from a promoter switch of CYP19A1 and/or accumulation of CYP19A1-expressing cells, rather than from cryptic transactivation of CYP19A1 because of genomic rearrangements at 15q21.

The complex genetic landscape of familial breast cancer

Familial breast cancer represents a minor percentage of all human breast cancers. Mutations in two high susceptibility genes BRCA1 and BRCA2 explain around 25 % of familial breast cancers, while other high, moderate and low susceptibility genes explain up to 20 % more of breast cancer families. Thus, it is important to decipher the genetic architecture of families that show no mutations to improve genetic counselling. The comprehensive description of familial breast cancer using different techniques and platforms has shown to be very valuable for better patient diagnosis, tumour surveillance, and ultimately patient treatment. This review focuses on the complex landscape of pathological, protein, genetic and genomic features associated with BRCA1-, BRCA2-, and non-BRCA1/BRCA2-related cancers described up to date. Special emphasis deserves the coexistence of distinct molecular breast cancer subtypes, the development of tumour classifiers to predict BRCA1/2 mutations, and the last insights from recent whole genome sequencing studies and miRNA profiling.