PALB2/FANCN is mutated in breast and pancreatic cancers and Fanconi anemia (FA). It controls the intranuclear localization, stability, and DNA repair function of BRCA2 and links BRCA1 and BRCA2 in DNA homologous recombination repair and breast cancer suppression. Here, we show that PALB2 directly interacts with KEAP1, an oxidative stress sensor that binds and represses the master antioxidant transcription factor NRF2. PALB2 shares with NRF2 a highly conserved ETGE-type KEAP1 binding motif and can effectively compete with NRF2 for KEAP1 binding. PALB2 promotes NRF2 accumulation and function in the nucleus and lowers the cellular reactive oxygen species (ROS) level. In addition, PALB2 also regulates the rate of NRF2 export from the nucleus following induction. Our findings identify PALB2 as a regulator of cellular redox homeostasis and provide a new link between oxidative stress and the development of cancer and FA.

The Maasai are a pastoral people in Kenya and Tanzania, whose traditional diet of milk, blood and meat is rich in lactose, fat and cholesterol. In spite of this, they have low levels of blood cholesterol, and seldom suffer from gallstones or cardiac diseases. Field studies in the 1970s suggested that the Maasai have a genetic adaptation for cholesterol homeostasis. Analysis of HapMap 3 data using Fixation Index (Fst) and two metrics of haplotype diversity: the integrated Haplotype Score (iHS) and the Cross Population Extended Haplotype Homozygosity (XP-EHH), identified genomic regions and single nucleotide polymorphisms (SNPs) as strong candidates for recent selection for lactase persistence and cholesterol regulation in 143–156 founder individuals from the Maasai population in Kinyawa, Kenya (MKK). The non-synonmous SNP with the highest genome-wide Fst was the TC polymorphism at rs2241883 in Fatty Acid Binding Protein 1(FABP1), known to reduce low density lipoprotein and tri-glyceride levels in Europeans. The strongest signal identified by all three metrics was a 1.7 Mb region on Chr2q21. This region contains the genes LCT (Lactase) and MCM6 (Minichromosome Maintenance Complex Component) involved in lactase persistence, and the gene Rab3GAP1 (Rab3 GTPase-activating Protein Catalytic Subunit), which contains polymorphisms associated with total cholesterol levels in a genome-wide association study of >100,000 individuals of European ancestry. Sanger sequencing of DNA from six MKK samples showed that the GC-14010 polymorphism in the MCM6 gene, known to be associated with lactase persistence in Africans, is segregating in MKK at high frequency (∼58%). The Cytochrome P450 Family 3 Subfamily A (CYP3A) cluster of genes, involved in cholesterol metabolism, was identified by Fst and iHS as candidate loci under selection. Overall, our study identified several specific genomic regions under selection in the Maasai which contain polymorphisms in genes associated with lactase persistence and cholesterol regulation.

Ductal carcinoma in situ (DCIS) is a pre-invasive carcinoma of the breast that exhibits several distinct morphologies but the link between morphology and patient outcome is not clear. We hypothesize that different mechanisms of growth may still result in similar 2D morphologies, which may look different in 3D. To elucidate the connection between growth and 3D morphology, we reconstruct the 3D architecture of cribriform DCIS from resected patient material. We produce a fully automated algorithm that aligns, segments, and reconstructs 3D architectures from microscopy images of 2D serial sections from human specimens. The alignment algorithm is based on normalized cross correlation, the segmentation algorithm uses histogram equilization, Otsu's thresholding, and morphology techniques to segment the duct and cribra. The reconstruction method combines these images in 3D. We show that two distinct 3D architectures are indeed found in samples whose 2D histological sections are similarly identified as cribriform DCIS. These differences in architecture support the hypothesis that luminal spaces may form due to different mechanisms, either isolated cell death or merging fronds, leading to the different architectures. We find that out of 15 samples, 6 were found to have ‘bubble-like’ cribra, 6 were found to have ‘tube-like’ criba and 3 were ‘unknown.’ We propose that the 3D architectures found, ‘bubbles’ and ‘tubes’, account for some of the heterogeneity of the disease and may be prognostic indicators of different patient outcomes.

Adjuvant hormonal therapy is administered to all early stage ER+ breast cancers, and has led to significantly improved survival. Unfortunately, a subset of ER+ breast cancers suffer early relapse despite hormonal therapy. To identify molecular markers associated with early relapse in ER+ breast cancer, an outlier analysis method was applied to a published gene expression dataset of 268 ER+ early-stage breast cancers treated with tamoxifen alone. Increased expression of sets of genes that clustered in chromosomal locations consistent with the presence of amplicons at 8q24.3, 8p11.2, 17q12 (HER2 locus) and 17q21.33-q25.1 were each found to be independent markers for early disease recurrence. Distant metastasis free survival (DMFS) after 10 years for cases with any amplicon (DMFS  = 56.1%, 95% CI  = 48.3–63.9%) was significantly lower (P  = 0.0016) than cases without any of the amplicons (DMFS  = 87%, 95% CI  = 76.3% –97.7%). The association between presence of chromosomal amplifications in these regions and poor outcome in ER+ breast cancers was independent of histologic grade and was confirmed in independent clinical datasets. A separate validation using a FISH-based assay to detect the amplicons at 8q24.3, 8p11.2, and 17q21.33-q25.1 in a set of 36 early stage ER+/HER2- breast cancers treated with tamoxifen suggests that the presence of these amplicons are indeed predictive of early recurrence. We conclude that these amplicons may serve as prognostic markers of early relapse in ER+ breast cancer, and may identify novel therapeutic targets for poor prognosis ER+ breast cancers.

Prostate cancer (PCa) is a major lethal malignancy in men, but the molecular events and their interplay underlying prostate carcinogenesis remain poorly understood. Epigenetic events and the upregulation of polycomb group silencing proteins including Bmi1 have been described to occur during PCa progression. Here, we found that conditional overexpression of Bmi1 in mice induced prostatic intraepithelial neoplasia, and elicited invasive adenocarcinoma when combined with PTEN haploinsufficiency. In addition, Bmi1 and the PI3K/Akt pathway were coactivated in a substantial fraction of human high-grade tumors. We found that Akt mediated Bmi1 phosphorylation, enhancing its oncogenic potential in an Ink4a/Arf-independent manner. This process also modulated the DNA damage response and affected genomic stability. Together, our findings demonstrate the etiological role of Bmi1 in PCa, unravel an oncogenic collaboration between Bmi1 and the PI3K/Akt pathway, and provide mechanistic insights into the modulation of Bmi1 function by phosphorylation during prostate carcinogenesis.

SYNOPSIS

Ubiquitin-like protein, containing PHD and RING finger domains-1 (UHRF1) is required for cell cycle progression and epigenetic regulation. In this study, we show that depleting cancer cells of UHRF1 causes activation of the DNA damage response pathway, cell cycle arrest in G2/M and apoptosis dependent on caspase-8. The DNA damage response in cells depleted of UHRF1 is illustrated by: phosphorylation of histone H2AX on serine 139, phosphorylation of CHK2 on threonine 68, phosphorylation of CDC25 on serine 216 and phosphorylation of CDK1 on tyrosine 15. Moreover, we find that UHRF1 accumulates at sites of DNA damage suggesting that the cell cycle block in UHRF1 depleted cells is due to an important role in damage repair. The consequence of UHRF1 depletion is apoptosis: cells undergo activation of caspases 8 and 3 and depletion of caspase-8 prevents cell death induced by UHRF1 knock-down. Interestingly, the cell cycle block and apoptosis occurs in p53 containing and deficient cells. From these studies we conclude that UHRF1 links epigenetic regulation with DNA replication.

BRCA1 plays a critical role in the regulation of homologous recombination (HR)-mediated DNA double-strand break repair. BRCA1-deficient cancers have evolved to tolerate loss of BRCA1 function. This renders them vulnerable to agents, such as PARP inhibitors, that are conditionally ‘synthetic lethal' with their underlying repair defect. Recent studies demonstrate that BRCA1-deficient cells may acquire resistance to these agents by partially correcting their defect in HR-mediated repair, either through reversion mutations in BRCA1 or through ‘synthetic viable' loss of 53BP1. These findings and their clinical implications will be reviewed in this article.

In non-cancerous cells, phosphorylated proteins exist transiently, becoming de-phosphorylated by specific phosphatases that terminate propagation of signaling pathways. In cancers, compromised phosphatase activity and/or expression occur and contribute to tumor phenotype. The non-receptor phosphatase, PTPN13, has recently been dubbed a putative tumor suppressor. It decreased expression in breast cancer correlates with decreased overall survival. Here we show that PTPN13 regulates a new signaling complex in breast cancer consisting of ErbB2, Src, and EphrinB1. To our knowledge, this signaling complex has not been previously described. Co-immunoprecipitation and localization studies demonstrate that EphrinB1, a PTPN13 substrate, interacts with ErbB2. In addition, the oncogenic V660E ErbB2 mutation enhances this interaction, while Src kinase mediates EphrinB1 phosphorylation and subsequent MAP Kinase signaling. Decreased PTPN13 function further enhances signaling. The association of oncogene kinases (ErbB2, Src), a signaling transmembrane ligand (EphrinB1) and a phosphatase tumor suppressor (PTPN13) suggest that EphrinB1 may be a relevant therapeutic target in breast cancers harboring ErbB2-activating mutations and decreased PTPN13 expression.

DNA damage activates signaling pathways that lead to modification of local chromatin and recruitment of DNA repair proteins. Multiple DNA repair proteins having ubiquitin ligase activity are recruited to sites of DNA damage, where they ubiquitinate histones and other substrates. This DNA damage-induced histone ubiquitination is thought to play a critical role in mediating the DNA damage response. We now report that the polycomb protein BMI1 is rapidly recruited to sites of DNA damage, where it persists for more than 8 h. The sustained localization of BMI1 to damage sites is dependent on intact ATM and ATR and requires H2AX phosphorylation and recruitment of RNF8. BMI1 is required for DNA damage-induced ubiquitination of histone H2A at lysine 119. Loss of BMI1 leads to impaired repair of DNA double-strand breaks by homologous recombination and the accumulation of cells in G2/M. These data support a crucial role for BMI1 in the cellular response to DNA damage.

Ductal carcinoma in situ (DCIS) of the breast is a non-invasive tumor in which cells proliferate abnormally, but remain confined within a duct. Although four distinguishable DCIS morphologies are recognized, the mechanisms that generate these different morphological classes remain unclear, and consequently the prognostic strength of DCIS classification is not strong. To improve the understanding of the relation between morphology and time course, we have developed a 2D in silico particle model of the growth of DCIS within a single breast duct. This model considers mechanical effects such as cellular adhesion and intra-ductal pressure, and biological features including proliferation, apoptosis, necrosis, and cell polarity. Using this model, we find that different regions of parameter space generate distinct morphological subtypes of DCIS, so elucidating the relation between morphology and time course. Furthermore, we find that tumors with similar architectures may in fact be produced through different mechanisms, and we propose future work to further disentangle the mechanisms involved in DCIS progression.

Purpose

Cisplatin is a chemotherapeutic agent not used routinely for breast cancer treatment. As a DNA cross-linking agent, cisplatin may be effective treatment for hereditary BRCA1-mutated breast cancers. Because sporadic triple-negative breast cancer (TNBC) and BRCA1-associated breast cancer share features suggesting common pathogenesis, we conducted a neoadjuvant trial of cisplatin in TNBC and explored specific biomarkers to identify predictors of response.

Patients and Methods

Twenty-eight women with stage II or III breast cancers lacking estrogen and progesterone receptors and HER2/Neu (TNBC) were enrolled and treated with four cycles of cisplatin at 75 mg/m2 every 21 days. After definitive surgery, patients received standard adjuvant chemotherapy and radiation therapy per their treating physicians. Clinical and pathologic treatment response were assessed, and pretreatment tumor samples were evaluated for selected biomarkers.

Results

Six (22%) of 28 patients achieved pathologic complete responses, including both patients with BRCA1 germline mutations;18 (64%) patients had a clinical complete or partial response. Fourteen (50%) patients showed good pathologic responses (Miller-Payne score of 3, 4, or 5), 10 had minor responses (Miller-Payne score of 1 or 2), and four (14%) progressed. All TNBCs clustered with reference basal-like tumors by hierarchical clustering. Factors associated with good cisplatin response include young age (P = .001), low BRCA1 mRNA expression (P = .03), BRCA1 promoter methylation (P = .04), p53 nonsense or frameshift mutations (P = .01), and a gene expression signature of E2F3 activation (P = .03).

Conclusion

Single-agent cisplatin induced response in a subset of patients with TNBC. Decreased BRCA1 expression may identify subsets of TNBCs that are cisplatin sensitive. Other biomarkers show promise in predicting cisplatin response.

In this paper, we attempt to quantify the prognostic information embedded in multi-parametric histologic biopsy images to predict disease aggressiveness in estrogen receptor-positive (ER+) breast cancers (BCa). The novel methodological contribution is in the use of a multi-field-of-view (multi-FOV) framework for integrating image-based information from differently stained histopathology slides. The multi-FOV approach involves a fixed image resolution while simultaneously integrating image descriptors from many FOVs corresponding to different sizes. For each study, the corresponding risk score (high scores reflecting aggressive disease and vice versa), predicted by a molecular assay (Oncotype DX), is available and serves as the surrogate ground truth for long-term patient outcome. Using the risk scores, a trained classifier is used to identify disease aggressiveness for each FOV size. The predictions for each FOV are then combined to yield the final prediction of disease aggressiveness (good, intermediate, or poor outcome). Independent multi-FOV classifiers are constructed for (1) 50 image features describing the spatial arrangement of cancer nuclei (via Voronoi diagram, Delaunay triangulation, and minimum spanning tree graphs) in H and E stained histopathology and (2) one image feature describing the vascular density in CD34 IHC stained histopathology. In a cohort of 29 patients, the multi-FOV classifiers obtained by combining information from the H and E and CD34 IHC stained channels were able to distinguish low- and high-risk patients with an accuracy of 0.91 ± 0.02 and a positive predictive value of 0.94 ± 0.10, suggesting that a purely image-based assay could potentially replace more expensive molecular assays for making disease prognostic predictions.

Germ-line mutations in BRCA1 predispose to breast and ovarian cancer. BRCA1-mutated tumors show genomic instability, mainly as a consequence of impaired recombinatorial DNA repair. Here we identify 53BP1 as an essential factor for sustaining the growth arrest induced by Brca1 deletion. Depletion of 53BP1 abrogates the ATM-dependent checkpoint response and G2 cell cycle arrest triggered by the accumulation of DNA breaks in Brca1-deleted cells. This effect of 53BP1 is specific to BRCA1 function, as 53BP1 depletion did not alleviate proliferation arrest or checkpoint responses in Brca2-deleted cells. Importantly, loss of 53BP1 partially restores the homologous recombination defect of Brca1-deleted cells and reverts their hypersensitivity to DNA-damaging agents. We find reduced 53BP1 expression in subsets of sporadic triple-negative and BRCA-associated breast cancers, indicating the potential clinical implications of our findings.

Within healthy human somatic cells, retrotransposition by long interspersed nuclear element-1 (also known as LINE-1 or L1) is thought to be held in check by a variety of mechanisms, including DNA methylation and RNAi. The expression of L1-ORF1 protein, which is rarely found in normal tissue, was assayed using antibodies with a variety of clinical cancer specimens and cancer cell lines. L1-ORF1p expression was detected in nearly all breast tumors that the authors examined, and the protein was also present in a high percentage of ileal carcinoids, bladder, and pancreatic neuroendocrine tumors, as well as in a smaller percentage of prostate and colorectal tumors. Tumors generally demonstrated cytoplasmic L1-ORF1p; however, in several breast cancers, L1-ORF1p was nuclear. Patients with breast tumors displaying nuclear L1-ORF1p had a greater incidence of both local recurrence and distal metastases and also showed poorer overall survival when compared with patients with tumors displaying cytoplasmic L1-ORF1p. These data suggest that expression of L1-ORF1p is widespread in many cancers and that redistribution from cytoplasm to nucleus could be a poor prognostic indicator during breast cancer. High expression and nuclear localization of L1-ORF1p may result in a higher rate of L1 retrotransposition, which could increase genomic instability.

Normal cellular behavior can be described as a complex, regulated network of interaction between genes and proteins. Targeted cancer therapies aim to neutralize specific proteins that are necessary for the cancer cell to remain viable in vivo. Ideally, the proteins targeted should be such that their downregulation has a major impact on the survival/fitness of the tumor cells and, at the same time, has a smaller effect on normal cells. It is difficult to use standard analysis methods on gene or protein expression levels to identify these targets because the level thresholds for tumorigenic behavior are different for different genes/proteins. We have developed a novel methodology to identify therapeutic targets by using a new paradigm called “gene centrality.” The main idea is that, in addition to being overexpressed, good therapeutic targets should have a high degree of connectivity in the tumor network because one expects that suppression of its expression would affect many other genes. We propose a mathematical quantity called “centrality,” which measures the degree of connectivity of genes in a network in which each edge is weighted by the expression level of the target gene. Using our method, we found that several SRC proto-oncogenes LYN, YES1, HCK, FYN, and LCK have high centrality in identifiable subsets of basal-like and HER2+ breast cancers. To experimentally validate the clinical value of this finding, we evaluated the effect of YES1 knockdown in basal-like breast cancer cell lines that overexpress this gene. We found that YES1 downregulation has a significant effect on the survival of these cell lines. Our results identify YES1 as a target for therapeutics in a subset of basal-like breast cancers.

Clear cell renal cell carcinoma (ccRCC) is the predominant RCC subtype, but even within this classification, the natural history is heterogeneous and difficult to predict. A sophisticated understanding of the molecular features most discriminatory for the underlying tumor heterogeneity should be predicated on identifiable and biologically meaningful patterns of gene expression. Gene expression microarray data were analyzed using software that implements iterative unsupervised consensus clustering algorithms to identify the optimal molecular subclasses, without clinical or other classifying information. ConsensusCluster analysis identified two distinct subtypes of ccRCC within the training set, designated clear cell type A (ccA) and B (ccB). Based on the core tumors, or most well-defined arrays, in each subtype, logical analysis of data (LAD) defined a small, highly predictive gene set that could then be used to classify additional tumors individually. The subclasses were corroborated in a validation data set of 177 tumors and analyzed for clinical outcome. Based on individual tumor assignment, tumors designated ccA have markedly improved disease-specific survival compared to ccB (median survival of 8.6 vs 2.0 years, P = 0.002). Analyzed by both univariate and multivariate analysis, the classification schema was independently associated with survival. Using patterns of gene expression based on a defined gene set, ccRCC was classified into two robust subclasses based on inherent molecular features that ultimately correspond to marked differences in clinical outcome. This classification schema thus provides a molecular stratification applicable to individual tumors that has implications to influence treatment decisions, define biological mechanisms involved in ccRCC tumor progression, and direct future drug discovery.

Apoptosis resistance is a hallmark of cancer linked to disease progression and treatment resistance, which has led to the development of anticancer therapeutics that restore apoptotic function. Antiapoptotic Bcl-2 is frequently overexpressed in refractory prostate cancer and increased following standard hormonal therapy and chemotherapy; however, the rationally designed Bcl-2 antagonist, ABT-737, has not shown single agent apoptosis-promoting activity against human prostate cancer cell lines. This is likely due to the coordinate expression of antiapoptotic, Bcl-2–related Mcl-1 that is not targeted by ABT-737. We developed a mouse model for prostate cancer in which apoptosis resistance and tumorigenesis were conferred by Bcl-2 expression. Combining ABT-737 with agents that target Mcl-1 sensitized prostate cancer cell lines with an apoptotic block to cell death in vitro. In mice in vivo, ABT-737 showed single agent efficacy in prostate tumor allografts in which tumor cells are under hypoxic stress. In human prostate cancer tissue, examined using a novel tumor explant system designated Tumor Tissue Assessment for Response to Chemotherapy, combination chemotherapy promoted efficient apoptosis. Thus, rational targeting of both the Bcl-2 and Mcl-1 mechanisms of apoptosis resistance may be therapeutically advantageous for advanced prostate cancer.

Background

Topors is a nuclear protein that co-localizes with promyelocytic leukemia bodies and has both ubiquitin and SUMO E3 ligase activity. Expression studies implicated Topors as a tumor suppressor in various malignancies. To gain insight into the function of Topors, we generated a Topors-deficient mouse strain.

Results

Mice homozygous for a mutant Topors allele exhibited a high rate of perinatal mortality and decreased lifespan. In addition, heterozygotes were found to have an increased incidence of malignancy, involving a variety of tissues. Consistent with this finding, primary embryonic fibroblasts lacking Topors exhibited an increased rate of malignant transformation, associated with aneuploidy and defective chromosomal segregation. While loss of Topors did not alter sensitivity to DNA-damaging or microtubule-targeting agents, cells lacking Topors exhibited altered pericentric heterochromatin, manifested by mislocalization of HP1α and an increase in transcription from pericentric major satellite DNA. Topors-deficient cells exhibited a transcriptional profile similar to that of cells treated with histone deacetylase inhibitors, and were resistant to the anti-proliferative effects of the histone deacetylase inhibitor trichostatin A.

Conclusion

These results indicate a unique role for Topors in the maintenance of genomic stability and pericentric heterochromatin, as well as in cellular sensitivity to histone deacetylase inhibitors.

Background

MicroRNA regulate mRNA levels in a tissue specific way, either by inducing degradation of the transcript or by inhibiting translation or transcription. Putative mRNA targets of microRNA identified from seed sequence matches are available in many databases. However, such matches have a high false positive rate and cannot identify tissue specificity of regulation.

Results

We describe a simple method to identify direct mRNA targets of microRNA dysregulated in cancers from expression level measurements in patient matched tumor/normal samples. The word "direct" is used here in a strict sense to: a) represent mRNA which have an exact seed sequence match to the microRNA in their 3'UTR, b) the seed sequence match is strictly conserved across mouse, human, rat and dog genomes, c) the mRNA and microRNA expression levels can distinguish tumor from normal with high significance and d) the microRNA/mRNA expression levels are strongly and significantly anti-correlated in tumor and/or normal samples. We apply and validate the method using clear cell Renal Cell Carcinoma (ccRCC) and matched normal kidney samples, limiting our analysis to mRNA targets which undergo degradation of the mRNA transcript because of a perfect seed sequence match. Dysregulated microRNA and mRNA are first identified by comparing their expression levels in tumor vs normal samples. Putative dysregulated microRNA/mRNA pairs are identified from these using seed sequence matches, requiring that the seed sequence be conserved in human/dog/rat/mouse genomes. These are further pruned by requiring a strong anti-correlation signature in tumor and/or normal samples. The method revealed many new regulations in ccRCC. For instance, loss of miR-149, miR-200c and mir-141 causes gain of function of oncogenes (KCNMA1, LOX), VEGFA and SEMA6A respectively and increased levels of miR-142-3p, miR-185, mir-34a, miR-224, miR-21 cause loss of function of tumor suppressors LRRC2, PTPN13, SFRP1, ERBB4, and (SLC12A1, TCF21) respectively. We also found strong anti-correlation between VEGFA and the miR-200 family of microRNA: miR-200a*, 200b, 200c and miR-141. Several identified microRNA/mRNA pairs were validated on an independent set of matched ccRCC/normal samples. The regulation of SEMA6A by miR-141 was verified by a transfection assay.

Conclusions

We describe a simple and reliable method to identify direct gene targets of microRNA in any cancer. The constraints we impose (strong dysregulation signature for microRNA and mRNA levels between tumor/normal samples, evolutionary conservation of seed sequence and strong anti-correlation of expression levels) remove spurious matches and identify a subset of robust, tissue specific, functional mRNA targets of dysregulated microRNA.

Clear cell renal cell carcinoma (ccRCC) is the predominant RCC subtype, but even within this classification, the natural history is heterogeneous and difficult to predict. A sophisticated understanding of the molecular features most discriminatory for the underlying tumor heterogeneity should be predicated on identifiable and biologically meaningful patterns of gene expression. Gene expression microarray data were analyzed using software that implements iterative unsupervised consensus clustering algorithms to identify the optimal molecular subclasses, without clinical or other classifying information. ConsensusCluster analysis identified two distinct subtypes of ccRCC within the training set, designated clear cell type A (ccA) and B (ccB). Based on the core tumors, or most well-defined arrays, in each subtype, logical analysis of data (LAD) defined a small, highly predictive gene set that could then be used to classify additional tumors individually. The subclasses were corroborated in a validation data set of 177 tumors and analyzed for clinical outcome. Based on individual tumor assignment, tumors designated ccA have markedly improved disease-specific survival compared to ccB (median survival of 8.6 vs 2.0 years, P = 0.002). Analyzed by both univariate and multivariate analysis, the classification schema was independently associated with survival. Using patterns of gene expression based on a defined gene set, ccRCC was classified into two robust subclasses based on inherent molecular features that ultimately correspond to marked differences in clinical outcome. This classification schema thus provides a molecular stratification applicable to individual tumors that has implications to influence treatment decisions, define biological mechanisms involved in ccRCC tumor progression, and direct future drug discovery.

Within healthy human somatic cells, retrotransposition by long interspersed nuclear element-1 (also known as LINE-1 or L1) is thought to be held in check by a variety of mechanisms, including DNA methylation and RNAi. The expression of L1-ORF1 protein, which is rarely found in normal tissue, was assayed using antibodies with a variety of clinical cancer specimens and cancer cell lines. L1-ORF1p expression was detected in nearly all breast tumors that the authors examined, and the protein was also present in a high percentage of ileal carcinoids, bladder, and pancreatic neuroendocrine tumors, as well as in a smaller percentage of prostate and colorectal tumors. Tumors generally demonstrated cytoplasmic L1-ORF1p; however, in several breast cancers, L1-ORF1p was nuclear. Patients with breast tumors displaying nuclear L1-ORF1p had a greater incidence of both local recurrence and distal metastases and also showed poorer overall survival when compared with patients with tumors displaying cytoplasmic L1-ORF1p. These data suggest that expression of L1-ORF1p is widespread in many cancers and that redistribution from cytoplasm to nucleus could be a poor prognostic indicator during breast cancer. High expression and nuclear localization of L1-ORF1p may result in a higher rate of L1 retrotransposition, which could increase genomic instability.

Background

Breast cancers that overexpress the human epidermal growth factor receptor 2 (HER2) are eligible for effective biologically targeted therapies, such as trastuzumab. However, accurately determining HER2 overexpression, especially in immunohistochemically equivocal cases, remains a challenge. Manual analysis of HER2 expression is dependent on the assessment of membrane staining as well as comparisons with positive controls. In spite of the strides that have been made to standardize the assessment process, intra- and inter-observer discrepancies in scoring is not uncommon. In this manuscript we describe a pathologist assisted, computer-based continuous scoring approach for increasing the precision and reproducibility of assessing imaged breast tissue specimens.

Methods

Computer-assisted analysis on HER2 IHC is compared with manual scoring and fluorescence in situ hybridization results on a test set of 99 digitally imaged breast cancer cases enriched with equivocally scored (2+) cases. Image features are generated based on the staining profile of the positive control tissue and pixels delineated by a newly developed Membrane Isolation Algorithm. Evaluation of results was performed using Receiver Operator Characteristic (ROC) analysis.

Results

A computer-aided diagnostic approach has been developed using a membrane isolation algorithm and quantitative use of positive immunostaining controls. By incorporating internal positive controls into feature analysis a greater Area Under the Curve (AUC) in ROC analysis was achieved than feature analysis without positive controls. Evaluation of HER2 immunostaining that utilized membrane pixels, controls, and percent area stained showed significantly greater AUC than manual scoring, and significantly less false positive rate when used to evaluate immunohistochemically equivocal cases.

Conclusion

It has been shown that by incorporating both a membrane isolation algorithm and analysis of known positive controls a computer-assisted diagnostic algorithm was developed that can reproducibly score HER2 status in IHC stained clinical breast cancer specimens. For equivocal scoring cases, this approach performed better than standard manual evaluation as assessed by ROC analysis in our test samples. Finally, there exists potential for utilizing image-analysis techniques for improving HER2 scoring at the immunohistochemically equivocal range.

Background

Clustering analysis of microarray data is often criticized for giving ambiguous results because of sensitivity to data perturbation or clustering techniques used. In this paper, we describe a new method based on principal component analysis and ensemble consensus clustering that avoids these problems.

Results

We illustrate the method on a public microarray dataset from 36 breast cancer patients of whom 31 were diagnosed with at least two of three pathological stages of disease (atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Our method identifies an optimum set of genes and divides the samples into stable clusters which correlate with clinical classification into Luminal, Basal-like and Her2+ subtypes. Our analysis reveals a hierarchical portrait of breast cancer progression and identifies genes and pathways for each stage, grade and subtype. An intriguing observation is that the disease phenotype is distinguishable in ADH and progresses along distinct pathways for each subtype. The genetic signature for disease heterogeneity across subtypes is greater than the heterogeneity of progression from DCIS to IDC within a subtype, suggesting that the disease subtypes have distinct progression pathways.

Our method identifies six disease subtype and one normal clusters. The first split separates the normal samples from the cancer samples. Next, the cancer cluster splits into low grade (pathological grades 1 and 2) and high grade (pathological grades 2 and 3) while the normal cluster is unchanged. Further, the low grade cluster splits into two subclusters and the high grade cluster into four. The final six disease clusters are mapped into one Luminal A, three Luminal B, one Basal-like and one Her2+.

Conclusion

We confirm that the cancer phenotype can be identified in early stage because the genes altered in this stage progressively alter further as the disease progresses through DCIS into IDC. We identify six subtypes of disease which have distinct genetic signatures and remain separated in the clustering hierarchy. Our findings suggest that the heterogeneity of disease across subtypes is higher than the heterogeneity of the disease progression within a subtype, indicating that the subtypes are in fact distinct diseases.

Breast cancer, early onset 1 (BRCA1) encodes a nuclear protein that participates in breast and ovarian cancer suppression. The molecular basis for the gender and tissue specificity of the BRCA1 cancer syndrome is unknown. Recently, we observed that a fraction of BRCA1 in female cells is localized on the inactive X chromosome (Xi). Chromatin immunoprecipitation (ChIP) experiments have demonstrated that BRCA1 physically associates with Xi-specific transcript (XIST) RNA, a non-coding RNA known to coat Xi and to participate in the initiation of its inactivation during early embryogenesis. Cells lacking wild-type BRCA1 show abnormalities in Xi, including lack of proper XIST RNA localization. Reintroduction of wild-type, but not mutant, BRCA1 can correct this defect in XIST localization in these cells. Depletion of BRCA1 in female diploid cells led to a defect in proper XIST localization on Xi and in the development of normal Xi heterchromatic superstructure. Moreover, depletion of BRCA1 led to an increased likelihood of re-expression of a green fluorescent protein (GFP) reporter gene embedded on Xi. Taken together, these findings are consistent with a model in which BRCA1 function contributes to the maintenance of proper Xi heterochromatin superstructure. Although the data imply a novel gender-specific consequence of BRCA1 loss, the relevance of the BRCA1/Xi function to the tumour suppressor activity of BRCA1 remains unclear and needs to be tested.