Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification.

Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-terminal truncated ß-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors. Of these, 126 genes were orthologous to protein-coding genes in the human genome (hereafter, human BC susceptibility genes, hBCSGs), 70% of which are previously reported cancer-associated genes, and ∼16% are known BC suppressor genes. Network analysis revealed a gene hub consisting of E1A binding protein P300 (EP300), CD44 molecule (CD44), neurofibromin (NF1) and phosphatase and tensin homolog (PTEN), which are linked to a significant number of mutated hBCSGs. From our survival prediction analysis of the expression of human BC genes in 2,333 BC cases, we isolated a six-gene-pair classifier that stratifies BC patients with high confidence into prognostically distinct low-, moderate-, and high-risk subgroups. Furthermore, we proposed prognostic classifiers identifying three basal and three claudin-low tumor subgroups. Intriguingly, our hBCSGs are mostly unrelated to cell cycle/mitosis genes and are distinct from the prognostic signatures currently used for stratifying BC patients. Our findings illustrate the strength and validity of integrating functional mutagenesis screens in mice with human cancer transcriptomic data to identify highly prognostic BC subtyping biomarkers.

Identification of common oncogenic and early developmental pathways in the ovarian carcinomas controlling by distinct prognostically significant microRNA subsets.

BACKGROUND: High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease aggressiveness and clinical outcomes. However, the functional relationships between microRNAs, the common pathways controlled by the microRNAs and their prognostic and therapeutic significance remain poorly understood. METHODS: We investigated the gene expression patterns of microRNAs in the tumors of 582 HG-SOC patients to identify prognosis signatures and pathways controlled by tumor miRNAs. We developed a variable selection and prognostic method, which performs a robust selection of small-sized subsets of the predictive features (e.g., expressed microRNAs) that collectively serves as the biomarkers of cancer risk and progression stratification system, interconnecting these features with common cancer-related pathways. RESULTS: Across different cohorts, our meta-analysis revealed two robust and unbiased miRNA-based prognostic classifiers. Each classifier reproducibly discriminates HG-SOC patients into high-confidence low-, intermediate- or high-prognostic risk subgroups with essentially different 5-year overall survival rates of 51.6-85%, 20-38.1%, and 0-10%, respectively. Significant correlations of the risk subgroup's stratification with chemotherapy treatment response were observed. We predicted specific target genes involved in nine cancer-related and two oocyte maturation pathways (neurotrophin and progesterone-mediated oocyte maturation), where each gene can be controlled by more than one miRNA species of the distinct miRNA HG-SOC prognostic classifiers. CONCLUSIONS: We identified robust and reproducible miRNA-based prognostic subsets of the of HG-SOC classifiers. The miRNAs of these classifiers could control nine oncogenic and two developmental pathways, highlighting common underlying pathologic mechanisms and perspective targets for the further development of a personalized prognosis assay(s) and the development of miRNA-interconnected pathway-centric and multi-agent therapeutic intervention.

Expression and clinical role of chemoresponse-associated genes in ovarian serous carcinoma.

OBJECTIVE: To validate our earlier observation that 11 chemoresistance-associated mRNAs are molecular markers of poor overall survival in ovarian serous carcinoma. METHODS: Ovarian serous carcinomas (n=112) and solid metastases (n=63; total=175) were analyzed for mRNA expression of APC, BAG3, EGFR, S100A10, ITGAE, MAPK3, TAP1, BNIP3, MMP9, FASLG and GPX3 using quantitative real-time PCR. mRNA expression was studied for association with clinicopathologic parameters and survival. Tumor heterogeneity was assessed in 20 cases with >1 specimen per patient. APC, BAG3, S100A10 and ERK1 protein expression by immunohistochemistry was analyzed in 58 specimens (38 primary carcinomas, 20 metastases). RESULTS: BAG3 (p=0.013), TAP1 (p=0.014), BNIP3 (p<0.001) and MMP9 (p=0.036) were overexpressed in primary tumors, whereas S100A10 (p=0.027) and FASLG (p=0.006) were overexpressed in metastases. Analysis of patient-matched primary carcinomas and metastases showed overexpression of APC (p=0.022), MAPK3 (p=0.002) and BNIP3 (p=0.004) in the former. In primary carcinomas, higher APC (p=0.003) and MAPK3 (p=0.005) levels were related to less favorable chemoresponse. Higher S100A10 (p=0.029) and MAPK3 (p=0.041) levels were related to primary chemoresistance. Higher BAG3 (p=0.026) and APC (p=0.046) levels in primary carcinomas were significantly related to poor overall survival in univariate, though not in multivariate survival analysis. S100A10 protein expression was related to poor chemoresponse (p=0.002) and shorter overall (p=0.005) and progression-free (p<0.001) survival, the latter finding retained in multivariate analysis (p=0.035). CONCLUSIONS: Our data provide evidence of heterogeneity in ovarian serous carcinoma and identify APC, MAPK3, BAG3 and S100A10 as potential biomarkers of poor chemotherapy response and/or poor outcome in this cancer.

Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma.

High-grade serous ovarian carcinoma (HG-SOC) is a heterogeneous, poorly classified, lethal disease that frequently exhibits altered expressions of microRNAs. Let-7 family members are often reported as tumor suppressors; nonetheless, clinicopathological functions and prognostic values of individual let-7 family members have not been addressed in HG-SOC. In our work, we performed an integrative study to investigate the potential roles, clinicopathological functions and prognostic values of let-7 miRNA family in HG-SOC. Using microarray and clinical data of 1,170 HG-SOC patients, we developed novel survival prediction and system biology methods to analyze prognostic values and functional associations of let-7 miRNAs with global transcriptome and clinicopathological factors. We demonstrated that individual let-7 members exhibit diverse evolutionary history and distinct regulatory characteristics. Statistical tests and network analysis suggest that let-7b could act as a global synergistic interactor and master regulator controlling hundreds of protein-coding genes. The elevated expression of let-7b is associated with poor survival rates, which suggests an unfavorable role of let-7b in treatment response for HG-SOC patients. A novel let-7b-defined 36-gene prognostic survival signature outperforms many clinicopathological parameters, and stratifies HG-SOC patients into three high-confidence, reproducible, clinical subclasses: low-, intermediate- and high-risk, with 5-year overall survival rates of 56-71%, 12-29% and 0-10%, respectively. Furthermore, the high-risk and low-risk subclasses exhibit strong mesenchymal and proliferative tumor phenotypes concordant with resistance and sensitivity to primary chemotherapy. Our results have led to identification of promising prognostic markers of HG-SOC, which could provide a rationale for genetic-based stratification of patients and optimization of treatment regimes.

KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer.

Stress-induced promoter-associated and antisense lncRNAs (si-paancRNAs) originate from a reservoir of oxidative stress (OS)-specific promoters via RNAPII pausing-mediated divergent antisense transcription. Several studies have shown that the KDM7A divergent transcript gene (KDM7A-DT), which encodes a si-paancRNA, is overexpressed in some cancer types. However, the mechanisms of this overexpression and its corresponding roles in oncogenesis and cancer progression are poorly understood. We found that KDM7A-DT expression is correlated with highly aggressive cancer types and specific inherently determined subtypes (such as ductal invasive breast carcinoma (BRCA) basal subtype). Its regulation is determined by missense TP53 mutations in a subtype-specific context. KDM7A-DT transcribes several intermediate-sized ncRNAs and a full-length transcript, exhibiting distinct expression and localization patterns. Overexpression of KDM7A-DT upregulates TP53 protein expression and H2AX phosphorylation in nonmalignant fibroblasts, while in semi-transformed fibroblasts, OS superinduces KDM7A-DT expression in a TP53-dependent manner. KDM7A-DT knockdown and gene expression profiling in TP53-missense mutated luminal A BRCA variant, where it is abundantly expressed, indicate its significant role in cancer pathways. Endogenous over-expression of KDM7A-DT inhibits DNA damage response/repair (DDR/R) via the TP53BP1-mediated pathway, reducing apoptosis and promoting G2/M checkpoint arrest. Higher KDM7A-DT expression in BRCA is associated with KDM7A-DT locus gain/amplification, higher histologic grade, aneuploidy, hypoxia, immune modulation scores, and activation of the c-myc pathway. Higher KDM7A-DT expression is associated with relatively poor survival outcomes in patients with luminal A or Basal subtypes. In contrast, it is associated with favorable outcomes in patients with HER2+ER- or luminal B subtypes. KDM7A-DT levels are coregulated with critical transcripts and proteins aberrantly expressed in BRCA, including those involved in DNA repair via non-homologous end joining and epithelial-to-mesenchymal transition pathway. In summary, KDM7A-DT and its si-lncRNA exhibit several intrinsic biological and clinical characteristics that suggest important roles in invasive BRCA and its subtypes. KDM7A-DT-defined mRNA and protein subnetworks offer resources for identifying clinically relevant RNA-based signatures and prospective targets for therapeutic intervention.

Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer.

Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression.

Genome and transcriptome delineation of two major oncogenic pathways governing invasive ductal breast cancer development.

Invasive ductal carcinoma (IDC) is a major histo-morphologic type of breast cancer. Histological grading (HG) of IDC is widely adopted by oncologists as a prognostic factor. However, HG evaluation is highly subjective with only 50%-85% inter-observer agreements. Specifically, the subjectivity in the assignment of the intermediate grade (histologic grade 2, HG2) breast cancers (comprising ~50% of IDC cases) results in uncertain disease outcome prediction and sub-optimal systemic therapy. Despite several attempts to identify the mechanisms underlying the HG classification, their molecular bases are poorly understood.We performed integrative bioinformatics analysis of TCGA and several other cohorts (total 1246 patients). We identified a 22-gene tumor aggressiveness grading classifier (22g-TAG) that reflects global bifurcation in the IDC transcriptomes and reclassified patients with HG2 tumors into two genetically and clinically distinct subclasses: histological grade 1-like (HG1-like) and histological grade 3-like (HG3-like). The expression profiles and clinical outcomes of these subclasses were similar to the HG1 and HG3 tumors, respectively. We further reclassified IDC into low genetic grade (LGG = HG1+HG1-like) and high genetic grade (HGG = HG3-like+HG3) subclasses. For the HG1-like and HG3-like IDCs we found subclass-specific DNA alterations, somatic mutations, oncogenic pathways, cell cycle/mitosis and stem cell-like expression signatures that discriminate between these tumors. We found similar molecular patterns in the LGG and HGG tumor classes respectively.Our results suggest the existence of two genetically-predefined IDC classes, LGG and HGG, driven by distinct oncogenic pathways. They provide novel prognostic and therapeutic biomarkers and could open unique opportunities for personalized systemic therapies of IDC patients.

Sense-antisense gene-pairs in breast cancer and associated pathological pathways.

More than 30% of human protein-coding genes form hereditary complex genome architectures composed of sense-antisense (SA) gene pairs (SAGPs) transcribing their RNAs from both strands of a given locus. Such architectures represent important novel components of genome complexity contributing to gene expression deregulation in cancer cells. Therefore, the architectures might be involved in cancer pathways and, in turn, be used for novel drug targets discovery. However, the global roles of SAGPs in cancer pathways has not been studied. Here we investigated SAGPs associated with breast cancer (BC)-related pathways using systems biology, prognostic survival and experimental methods. Gene expression analysis identified 73 BC-relevant SAGPs that are highly correlated in BC. Survival modelling and metadata analysis of the 1161 BC patients allowed us to develop a novel patient prognostic grouping method selecting the 12 survival-significant SAGPs. The qRT-PCR-validated 12-SAGP prognostic signature reproducibly stratified BC patients into low- and high-risk prognostic subgroups. The 1381 SAGP-defined differentially expressed genes common across three studied cohorts were identified. The functional enrichment analysis of these genes revealed the GABPA gene network, including BC-relevant SAGPs, specific gene sets involved in cell cycle, spliceosomal and proteasomal pathways. The co-regulatory function of GABPA in BC cells was supported using siRNA knockdown studies. Thus, we demonstrated SAGPs as the synergistically functional genome architectures interconnected with cancer-related pathways and associated with BC patient clinical outcomes. Taken together, SAGPs represent an important component of genome complexity which can be used to identify novel aspects of coordinated pathological gene networks in cancers.

Contrasting expression patterns of coding and noncoding parts of the human genome upon oxidative stress.

Oxidative stress (OS) is caused by an imbalance between pro- and anti-oxidant reactions leading to accumulation of reactive oxygen species within cells. We here investigate the effect of OS on the transcriptome of human fibroblasts. OS causes a rapid and transient global induction of transcription characterized by pausing of RNA polymerase II (PolII) in both directions, at specific promoters, within 30 minutes of the OS response. In contrast to protein-coding genes, which are commonly down-regulated, this novel divergent, PolII pausing-phenomenon leads to the generation of thousands of long noncoding RNAs (lncRNAs) with promoter-associated antisense lncRNAs transcripts (si-paancRNAs) representing the major group of stress-induced transcripts. OS causes transient dynamics of si-lncRNAs in nucleus and cytosol, leading to their accumulation at polysomes, in contrast to mRNAs, which get depleted from polysomes. We propose that si-lncRNAs represent a novel component of the transcriptional stress that is known to determine the outcome of immediate-early and later cellular stress responses and we provide insights on the fate of those novel mature lncRNA transcripts by showing that their association with polysomal complexes is significantly increased in OS.

Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures.

High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5-13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known. We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors. We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature. Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations.

Mapping of genomic segments of influenza B virus strains by an oligonucleotide microarray method.

Similar to other segmented RNA viruses, influenza viruses can exchange genome segments and form a wide variety of reassortant strains upon coreplication within a host cell. Therefore, the mapping of genome segments of influenza viruses is essential for understanding their phenotypes. In this work, we have developed an oligonucleotide microarray hybridization method for simultaneous genotyping of all genomic segments of two highly homologous strains of influenza B virus. A few strain-specific oligonucleotide probes matching each of the eight segments of the viral genomes of the B/Beijing/184/93 and B/Shangdong/7/97 strains were hybridized with PCR-amplified fluorescently labeled single-stranded DNA. Even though there were a few mismatches among the genomes of the studied virus strains, microarray hybridization showed highly significant and reproducible discrimination ability and allowed us to determine the origins of individual genomic segments in a series of reassortant strains prepared as vaccine candidates. Additionally, we were able to detect the presence of at least 5% of mixed genotypes in virus stocks even when conventional sequencing methods failed, for example, for the NS segment. Thus, the proposed microarray method can be used for (i) rapid and reliable genome mapping of highly homologous influenza B viruses and (ii) extensive monitoring of influenza B virus reassortants and the mixed genotypes. The array can be expanded by adding new oligoprobes and using more quantitative assays to determine the origin of individual genomic segments in series of reassortant strains prepared as vaccine candidates or in mixed virus populations.

Evaluation of immunogenicity and protective properties of inactivated poliovirus vaccines: a new surrogate method for predicting vaccine efficacy.

An assay for the evaluation of protective properties of inactivated poliovirus vaccines (IPVs) in transgenic (Tg) mice susceptible to poliovirus has been developed and optimized for type 2 IPV. This method was used to compare the immunogenicity and protective properties of experimental IPV produced from the attenuated Sabin strain (sIPV) with those of conventional IPV (cIPV) produced from the wild-type (wt) poliovirus MEF-1 strain. Modified enzyme-linked immunosorbent assays (ELISAs) were used to measure immune response in serum and saliva samples from test mice. Tg mice were vaccinated and were challenged either with wt poliovirus or virulent poliovirus derived from the vaccine strain. Compared with cIPV, sIPV induced lower levels of antibodies and did not completely protect mice against challenge with wt virus but did protect mice against challenge with the virulent vaccine-derived strain. This may be due to an 18% nucleotide difference between the MEF-1 and Sabin 2 strains, resulting in 72 amino acid substitutions and leading to antigenic dissimilarity. Immunological properties of both strains, revealed by cross-neutralization tests and ELISAs, confirmed that MEF-1 possesses broader immunogenicity than does Sabin 2. This animal model may be used for the assessment of new IPVs and of combination vaccines containing an IPV component.