Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours

Simple and versatile molecular method of copy-number measurement using cloned competitors

Variations and alterations of copy numbers (CNVs and CNAs) carry disease susceptibility and drug responsiveness implications. Although there are many molecular methods to measure copy numbers, sensitivity, reproducibility, cost, and time issues remain. In the present study, we were able to solve those problems utilizing our modified real competitive PCR method with cloned competitors (mrcPCR). First, the mrcPCR for ERBB2 copy number was established, and the results were comparable to current standard methods but with a shorter assay time and a lower cost. Second, the mrcPCR assays for 24 drug-target genes were established, and the results in a panel of NCI-60 cells were comparable to those from real-time PCR and microarray. Third, the mrcPCR results for FCGR3A and the FCGR3B CNVs were comparable to those by the paralog ratio test (PRT), but without PRT's limitations. These results suggest that mrcPCR is comparable to the currently available standard or the most sensitive methods. In addition, mrcPCR would be invaluable for measurement of CNVs in genes with variants of similar structures, because combination of the other methods is not necessary, along with its other advantages such as short assay time, small sample amount requirement, and applicability to all sequences and genes.

Advances in molecular and clinical subtyping of breast cancer and their implications for therapy

The identification of the intrinsic molecular subtypes of breast cancer has enhanced our understanding of tumor biology, informing therapeutic targets, and clinical trial design. This article reviews the intrinsic classification system and the clinically defined subtypes of breast cancer. We review the molecular drivers of each subtype and discuss implications for prognosis, clinical management, and future directions.

REACTIN: regulatory activity inference of transcription factors underlying human diseases with application to breast cancer

BACKGROUND

Genetic alterations of transcription factors (TFs) have been implicated in the tumorigenesis of cancers. In many cancers, alteration of TFs results in aberrant activity of them without changing their gene expression level. Gene expression data from microarray or RNA-seq experiments can capture the expression change of genes, however, it is still challenge to reveal the activity change of TFs.

RESULTS

Here we propose a method, called REACTIN (REgulatory ACTivity INference), which integrates TF binding data with gene expression data to identify TFs with significantly differential activity between disease and normal samples. REACTIN successfully detect differential activity of estrogen receptor (ER) between ER+ and ER- samples in 10 breast cancer datasets. When applied to compare tumor and normal breast samples, it reveals TFs that are critical for carcinogenesis of breast cancer. Moreover, Reaction can be utilized to identify transcriptional programs that are predictive to patient survival time of breast cancer patients.

CONCLUSIONS

REACTIN provides a useful tool to investigate regulatory programs underlying a biological process providing the related case and control gene expression data. Considering the enormous amount of cancer gene expression data and the increasingly accumulating ChIP-seq data, we expect wide application of REACTIN for revealing the regulatory mechanisms of various diseases.

The PGC-1/ERR signaling axis in cancer

Proliferating cells need to produce a large amount of energy and, at the same time, need to maintain a constant supply of biosynthetic precursors of macromolecules that are used as building blocks for generating new cells. Indeed, many cancer cells undergo a switch from mitochondrial to glycolytic metabolism and display a truncated tricarboxylic acid cycle to match these specific metabolic requirements of proliferation. Understanding the mechanisms by which cancer cells reprogram various metabolic pathways to satisfy their unique bioenergetic requirements has become an active field of research. Concomitantly, it has emerged that members of a family of orphan nuclear receptors known as the estrogen-related receptors (ERRs), working in concert with members of the PPARγ coactivator (PGC)-1 family, act as central transcriptional regulators of metabolic gene networks involved in maintaining energy homeostasis in normal cells. Recent studies have suggested that the PGC-1/ERR transcriptional axis is also important in the metabolic reprogramming of cancer cells. This review focuses on the functional integration of the PGC-1/ERR axis with known oncogenes and the observation that modulation of the activity of this axis can have both pro- and anti-proliferative properties.

Deciphering and reversing tumor immune suppression

Generating an anti-tumor immune response is a multi-step process that is executed by effector T cells that can recognize and kill tumor targets. However, tumors employ multiple strategies to attenuate the effectiveness of T-cell-mediated attack. They achieve this by interfering with nearly every step required for effective immunity, from deregulation of antigen-presenting cells to establishment of a physical barrier at the vasculature that prevents homing of effector tumor-rejecting cells and the suppression of effector lymphocytes through the recruitment and activation of immunosuppressive cells such as myeloid-derived suppressor cells, tolerogenic monocytes, and T regulatory cells. Here, we review the ways in which tumors exert immune suppression and highlight the new therapies that seek to reverse this phenomenon and promote anti-tumor immunity. Understanding anti-tumor immunity, and how it becomes disabled by tumors, will ultimately lead to improved immune therapies and prolonged survival of patients.

[Triple-negative breast cancer: histoclinical and molecular features, therapeutic management and perspectives]

Triple-negative breast cancer (TNBC), as defined by the absence of estrogen and progesterone receptor expression, as well as the lack of HER2 overexpression/amplification, corresponds to 15% of breast cancer and represents an aggressive form of the disease. TNBC are frequently confounded with basal subtype in the molecular classification of breast cancer and also share some similarities with BRCA1-mutated tumors. Epidemiological and clinical characteristics are distinct from other subtypes, including a younger age at diagnosis, a higher risk of relapse in spite of increased chemosensitivity, and a higher incidence of lung and brain metastatic relapses. Conventional cytotoxics remain the mainstay of current systemic management but recent evaluation of more targeted therapeutics, including specific cytotoxics (such as the use of platinum salts), PARP and EGFR inhibition, and antiangiogenics have been performed, providing contrasted but rather disappointing results. Recent data indicate that TNBC represent a heterogeneous entity composed of multiple and distinct molecular subtypes, which should deserve specific targeted therapeutics.

Integrated analysis of genome-wide DNA methylation and gene expression profiles in molecular subtypes of breast cancer

Aberrant DNA methylation of CpG islands, CpG island shores and first exons is known to play a key role in the altered gene expression patterns in all human cancers. To date, a systematic study on the effect of DNA methylation on gene expression using high resolution data has not been reported. In this study, we conducted an integrated analysis of MethylCap-sequencing data and Affymetrix gene expression microarray data for 30 breast cancer cell lines representing different breast tumor phenotypes. As well-developed methods for the integrated analysis do not currently exist, we created a series of four different analysis methods. On the computational side, our goal is to develop methylome data analysis protocols for the integrated analysis of DNA methylation and gene expression data on the genome scale. On the cancer biology side, we present comprehensive genome-wide methylome analysis results for differentially methylated regions and their potential effect on gene expression in 30 breast cancer cell lines representing three molecular phenotypes, luminal, basal A and basal B. Our integrated analysis demonstrates that methylation status of different genomic regions may play a key role in establishing transcriptional patterns in molecular subtypes of human breast cancer.

Luminal breast cancer: from biology to treatment

Oestrogen receptor (ER)-positive--or luminal--tumours represent around two-thirds of all breast cancers. Luminal breast cancer is a highly heterogeneous disease comprising different histologies, gene-expression profiles and mutational patterns, with very varied clinical courses and responses to systemic treatment. Despite adjuvant endocrine therapy and chemotherapy treatment for patients at high risk of relapse, both early and late relapses still occur, a fact that highlights the unmet medical needs of these patients. Ongoing research aims to identify those patients who can be spared adjuvant chemotherapy and who will benefit from extended adjuvant hormone therapy. This research also aims to explore the role of adjuvant bisphosphonates, to interrogate new agents for targeting minimal residual disease, and to address endocrine resistance. Data from next-generation sequencing studies have given us new insight into the biology of luminal breast cancer and, together with advances in preclinical models and the availability of newer targeted agents, have led to the testing of rationally chosen combination treatments in clinical trials. However, a major challenge will be to make sense of the large amount of patient genomic data that is becoming increasingly available. This analysis will be critical to our understanding how intertumour and intratumour heterogeneity can influence treatment response and resistance.

Differential chemotherapeutic sensitivity for breast tumors with "BRCAness": a review

BRCA1 or BRCA2 mutations predispose to cancer development, primarily through their loss of role in the repair of DNA double-strand breaks. They play a key role in homologous recombination repair, which is a conservative, error-free DNA repair mechanism. When mutated, other alternative, error-prone mechanisms for DNA repair take over, leading to genomic instability. Somatic mutations are rare in sporadic breast tumors, but expression of BRCA1 and BRCA2 genes can be downregulated in other mechanistic ways. These tumors have similar features in terms of their phenotypic and genotypic profiles, which are normally regulated by these genes, and mutations lead to defective DNA repair capacity, called "BRCAness." Attempts have been made to exploit this differentially expressed feature between tumors and normal tissues by treatment with DNA-damaging chemotherapy agents. Cells with this functional BRCA deficiency should be selectively susceptible to DNA-damaging drugs. Preclinical and early clinical (primarily retrospective) evidence supports this approach. In contrast, there is emerging evidence of relative resistance of tumors containing BRCA1 or BRCA2 mutations (or BRCAness) to taxanes. In this review, we summarize the data supporting differential chemotherapeutic sensitivity on the basis of defective DNA repair. If confirmed with available, clinically applicable techniques, this differential chemosensitivity could lead to treatment choices in breast cancer that have a more individualized biologic basis.

Prolactin cooperates with loss of p53 to promote claudin-low mammary carcinomas

TP53 is one of the most commonly mutated genes in cancer. In breast cancer, it is mutated in about 40% of primary clinical tumors and is associated with poor survival. The mammotrophic hormone, prolactin (PRL), and/or its receptor are also expressed in many breast cancers, and accumulating epidemiologic data link PRL to breast cancer development and progression. Like TP53 mutations, evidence for PRL activity is evident across several molecular cancer subtypes, and elevated PRL expression and loss of p53 have been observed in some of the same clinical tumors. In order to examine the interaction of these factors, we used genetically modified mouse models of mammary-specific p53 loss and local overexpression of PRL. We demonstrated that mammary PRL decreased the latency of tumors in the absence of p53, and increased the proportion of triple-negative claudin-low carcinomas, which display similarities to human clinical metaplastic carcinomas. Moreover, PRL/p53(-/-) carcinomas displayed higher rates of proliferation and more aggressive behavior. Transcripts associated with cell cycle progression, invasion and stromal reactivity were differentially expressed in carcinomas that developed in the presence of elevated PRL. PRL/p53(-/-) carcinomas also exhibited selectively altered expression of activating protein-1 components, including higher levels of c-Jun and FosL1, which can drive transcription of many of these genes and the epithelial-mesenchymal transition. The ability of PRL to promote claudin-low carcinomas demonstrates that PRL can influence this subset of triple-negative breast cancers, which may have been obscured by the relative infrequency of this cancer subtype. Our findings suggest novel therapeutic approaches, and provide a preclinical model to develop possible agents.

SPARCL1 suppresses metastasis in prostate cancer

PURPOSE

Metastasis, the main cause of death from cancer, remains poorly understood at the molecular level.

EXPERIMENTAL DESIGN

Based on a pattern of reduced expression in human prostate cancer tissues and tumor cell lines, a candidate suppressor gene (SPARCL1) was identified. We used in vitro approaches to determine whether overexpression of SPARCL1 affects cell growth, migration, and invasiveness. We then employed xenograft mouse models to analyze the impact of SPARCL1 on prostate cancer cell growth and metastasis in vivo.

RESULTS

SPARCL1 expression did not inhibit tumor cell proliferation in vitro. By contrast, SPARCL1 did suppress tumor cell migration and invasiveness in vitro and tumor metastatic growth in vivo, conferring improved survival in xenograft mouse models.

CONCLUSIONS

We present the first in vivo data suggesting that SPARCL1 suppresses metastasis of prostate cancer.

Next generation analysis of breast cancer genomes for precision medicine

For many years breast cancer classification has been based on histology and immune-histochemistry. New techniques, more strictly related to cancer biology, partially succeeded in fractionating patients, correlated to survival and better predicted the patient response to therapy. Nowadays, great expectations arise from massive parallel or high throughput next generation sequencing. Cancer genomics has already revolutionized our knowledge of breast cancer molecular pathology, paving the way to the development of new and more effective clinical protocols. This review is focused on the most recent advances in the field of cancer genomics and epigenomics, including DNA alterations and driver gene mutations, gene fusions, DNA methylation and miRNA expression.

Comprehensive whole-genome sequencing of an early-stage primary myelofibrosis patient defines low mutational burden and non-recurrent candidate genes

In order to identify novel somatic mutations associated with classic BCR/ABL1-negative myeloproliferative neoplasms, we performed high-coverage genome sequencing of DNA from peripheral blood granulocytes and cultured skin fibroblasts from a patient with MPL W515K-positive primary myelofibrosis. The primary myelofibrosis genome had a low somatic mutation rate, consistent with that observed in similar hematopoietic tumor genomes. Interfacing of whole-genome DNA sequence data with RNA expression data identified three somatic mutations of potential functional significance: i) a nonsense mutation in CARD6, implicated in modulation of NF-kappaB activation; ii) a 19-base pair deletion involving a potential regulatory region in the 5'-untranslated region of BRD2, implicated in transcriptional regulation and cell cycle control; and iii) a non-synonymous point mutation in KIAA0355, an uncharacterized protein. Additional mutations in three genes (CAP2, SOX30, and MFRP) were also evident, albeit with no support for expression at the RNA level. Re-sequencing of these six genes in 178 patients with polycythemia vera, essential thrombocythemia, and myelofibrosis did not identify recurrent somatic mutations in these genes. Finally, we describe methods for reducing false-positive variant calls in the analysis of hematologic malignancies with a low somatic mutation rate. This trial is registered with ClinicalTrials.gov (NCT01108159).

Genes dysregulated to different extent or oppositely in estrogen receptor-positive and estrogen receptor-negative breast cancers

Background

Directly comparing gene expression profiles of estrogen receptor-positive (ER+) and estrogen receptor-negative (ER−) breast cancers cannot determine whether differentially expressed genes between these two subtypes result from dysregulated expression in ER+ cancer or ER− cancer versus normal controls, and thus would miss critical information for elucidating the transcriptomic difference between the two subtypes.

Principal Findings

Using microarray datasets from TCGA, we classified the genes dysregulated in both ER+ and ER− cancers versus normal controls into two classes: (i) genes dysregulated in the same direction but to a different extent, and (ii) genes dysregulated to opposite directions, and then validated the two classes in RNA-sequencing datasets of independent cohorts. We showed that the genes dysregulated to a larger extent in ER+ cancers than in ER− cancers enriched in glycerophospholipid and polysaccharide metabolic processes, while the genes dysregulated to a larger extent in ER− cancers than in ER+ cancers enriched in cell proliferation. Phosphorylase kinase and enzymes of glycosylphosphatidylinositol (GPI) anchor biosynthesis were upregulated to a larger extent in ER+ cancers than in ER− cancers, whereas glycogen synthase and phospholipase A2 were downregulated to a larger extent in ER+ cancers than in ER− cancers. We also found that the genes oppositely dysregulated in the two subtypes significantly enriched with known cancer genes and tended to closely collaborate with the cancer genes. Furthermore, we showed the possibility that these oppositely dysregulated genes could contribute to carcinogenesis of ER+ and ER− cancers through rewiring different subpathways.

Conclusions

GPI-anchor biosynthesis and glycogenolysis were elevated and hydrolysis of phospholipids was depleted to a larger extent in ER+ cancers than in ER− cancers. Our findings indicate that the genes oppositely dysregulated in the two subtypes are potential cancer genes which could contribute to carcinogenesis of both ER+ and ER− cancers through rewiring different subpathways.

miR-21 coordinates tumor growth and modulates KRIT1 levels

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miR-21 targets KRIT1.

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miR-21 and KRIT1 expression anticorrelate in human breast tumors.

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KRIT1 is involved in miR-21-mediated tumor cell growth.

miR-21 is overexpressed in tumors and it displays oncogenic activity. Here, we show that expression of miR-21 in primary tumors anticorrelates with KRIT1/CCM1, an interacting partner of the Ras-like GTPase Rap1, involved in Cerebral Cavernous Malformations (CCM). We present evidences that miR-21 silences KRIT1 by targeting its mRNA 3′UTR and that this interaction is involved in tumor growth control. In fact, miR-21 over-expression or KRIT1 knock-down promote anchorage independent tumor cell growth compared to controls, whereas the opposite is observed when anti-miR-21 or KRIT1 overexpression are employed. Our findings suggest that miR-21 promotes tumor cell growth, at least in part, by down-modulating the potential tumor suppressor KRIT1.

Evaluation of factors related to late recurrence--later than 10 years after the initial treatment--in primary breast cancer

BACKGROUND

Breast cancer is associated with a relatively good prognosis. Prognostic factors examined to date are related to early recurrence while those related to late recurrence and their countermeasures remain unclear. Therefore, we examined the factors related to late recurrence.

PATIENTS AND METHODS

From January 1980 to August 2012, 4,774 patients who underwent primary treatment and estrogen (ER) and progesterone receptor (PgR) assessment were enrolled in this study. The patients were divided into two groups, those with a follow-up period <10 years and those without any recurrence at 10 years but who continued follow-up examinations. Recurrence occurred in 711 patients followed up for <10 years and in 51 patients for ≥10 years.

RESULTS

The overall 10-year cumulative disease-free survival rate was 79.5%, and the recurrence rate at ≥10 years was 5.8%. A multivariate analysis revealed that the factors related to late recurrence were PgR positivity and positive nodes. This result differed from that for early recurrence in terms of ER/PgR, Ki-67 index and p53 overexpression.

CONCLUSION

PgR positivity and lymph node metastases significantly correlated with late recurrence. Therefore, it is important to evaluate appropriate measures such as treatment period and treatment regimen for hormone-sensitive patients.

A gene signature for late distant metastasis in breast cancer identifies a potential mechanism of late recurrences

INTRODUCTION

Breast cancer risk of recurrence is known to span 20 years, yet existing prognostic signatures are best at predicting early recurrences (≤ 5 years). There is a critical need to identify those patients at risk of late-relapse (>5 years), in order to select potential candidates for further treatment and to identify molecular targets for such treatment.

METHODS

A total of 252 breast primary tumors were selected at the Netherlands Cancer Institute from a retrospective series of ER+, HER2- breast cancer patients with a follow-up of at least 10 years. Gene expression analysis was performed using Agilent 4x44K microarrays. Patients were classified in 3 groups: no relapse (M0); relapse before 5 years (M0-5) or after 5 years (M5-15). We assessed the correlation of clinico-pathological variables with late Distant Metastases (DM). We divided the patient series into a training set of untreated patients (n = 140) and a test set of treated patients (n = 112), to investigate whether a gene-signature or single genes could be identified for predicting late DM. Pathway level late DM correlates were identified using PARADIGM and DAVID.

RESULTS

Of the clinico-pathologic variables tested, only lymph node status associated with late DM. A 241-gene signature developed on the NKI training set was able to classify M5-15 patients in the test set with a sensitivity of 77% and a specificity of 33% (AUC 0.654). This signature showed enrichment in genes involved in immune response and extracellular matrix. An alternative analysis of individual genes identified CH25H as an independent predictor of distant metastasis in our patient series.

CONCLUSIONS

We identified a gene signature for late metastasis in breast cancer. Our data are consistent with a model in which suppressed anti-tumoral immunity enables dormant tumor cells to re-enter the cell cycle to form metastases in response to extrinsic events in the microenvironment.

BCL-2 hypermethylation is a potential biomarker of sensitivity to antimitotic chemotherapy in endocrine-resistant breast cancer

Overexpression of the antiapoptotic factor BCL-2 is a frequent feature of malignant disease and is commonly associated with poor prognosis and resistance to conventional chemotherapy. In breast cancer, however, high BCL-2 expression is associated with favorable prognosis, estrogen receptor (ER) positivity, and low tumor grade, whereas low expression is included in several molecular signatures associated with resistance to endocrine therapy. In the present study, we correlate BCL-2 expression and DNA methylation profiles in human breast cancer and in multiple cell models of acquired endocrine resistance to determine whether BCL-2 hypermethylation could provide a useful biomarker of response to cytotoxic therapy. In human disease, diminished expression of BCL-2 was associated with hypermethylation of the second exon, in a region that overlapped a CpG island and an ER-binding site. Hypermethylation of this region, which occurred in 10% of primary tumors, provided a stronger predictor of patient survival (P = 0.019) when compared with gene expression (n = 522). In multiple cell models of acquired endocrine resistance, BCL-2 expression was significantly reduced in parallel with increased DNA methylation of the exon 2 region. The reduction of BCL-2 expression in endocrine-resistant cells lowered their apoptotic threshold to antimitotic agents: nocodazole, paclitaxel, and the PLK1 inhibitor BI2536. This phenomenon could be reversed with ectopic expression of BCL-2, and rescued with the BCL-2 inhibitor ABT-737. Collectively, these data imply that BCL-2 hypermethylation provides a robust biomarker of response to current and next-generation cytotoxic agents in endocrine-resistant breast cancer, which may prove beneficial in directing therapeutic strategy for patients with nonresectable, metastatic disease.

Diverse mechanisms of somatic structural variations in human cancer genomes

Identification of somatic rearrangements in cancer genomes has accelerated through analysis of high-throughput sequencing data. However, characterization of complex structural alterations and their underlying mechanisms remains inadequate. Here, applying an algorithm to predict structural variations from short reads, we report a comprehensive catalog of somatic structural variations and the mechanisms generating them, using high-coverage whole-genome sequencing data from 140 patients across ten tumor types. We characterize the relative contributions of different types of rearrangements and their mutational mechanisms, find that ~20% of the somatic deletions are complex deletions formed by replication errors, and describe the differences between the mutational mechanisms in somatic and germline alterations. Importantly, we provide detailed reconstructions of the events responsible for loss of CDKN2A/B and gain of EGFR in glioblastoma, revealing that these alterations can result from multiple mechanisms even in a single genome and that both DNA double-strand breaks and replication errors drive somatic rearrangements.

An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers

Recent studies indicate that a subclass of APOBEC cytidine deaminases, which convert cytosine to uracil during RNA editing and retrovirus or retrotransposon restriction, may induce mutation clusters in human tumors. We show here that throughout cancer genomes APOBEC-mediated mutagenesis is pervasive and correlates with APOBEC mRNA levels. Mutation clusters in whole-genome and exome data sets conformed to the stringent criteria indicative of an APOBEC mutation pattern. Applying these criteria to 954,247 mutations in 2,680 exomes from 14 cancer types, mostly from The Cancer Genome Atlas (TCGA), showed a significant presence of the APOBEC mutation pattern in bladder, cervical, breast, head and neck, and lung cancers, reaching 68% of all mutations in some samples. Within breast cancer, the HER2-enriched subtype was clearly enriched for tumors with the APOBEC mutation pattern, suggesting that this type of mutagenesis is functionally linked with cancer development. The APOBEC mutation pattern also extended to cancer-associated genes, implying that ubiquitous APOBEC-mediated mutagenesis is carcinogenic.

Updates in the treatment of basal/triple-negative breast cancer

PURPOSE OF REVIEW

Triple-negative breast cancer (TNBC) is clinically characterized by the lack of expression of the estrogen receptor/progesterone receptor and the human epidermal growth factor receptor 2. It is highly heterogeneous and exhibits considerable overlap with basal-like and BRCA-related breast cancers. Constituting 15-20% of breast cancers, TNBC exhibits an aggressive phenotype with a poor prognosis. This review summarizes recent progress and studies in TNBC and discusses some of the ongoing clinical trials and emerging therapies for the treatment of TNBC.

RECENT FINDINGS

Conventional cytotoxic chemotherapy and DNA damaging agents continue to be the mainstay for treatment of this disease. The use of targeted agents such as bevacizumab, epidermal growth factor receptor and polyadenosine diphosphate-ribose polymerase inhibitors have led to conflicting results. However, recent research has prompted evaluation of additional drugs targeting multiple signaling pathways and epigenetic modifications for the treatment of this disease.

SUMMARY

TNBC remains a challenging disease to treat with recent trials having demonstrated only modest improvements in outcomes. Increased understanding of the heterogeneity of this complex subtype may help tailor therapies to specific patient subgroups.

Carboxyl group footprinting mass spectrometry and molecular dynamics identify key interactions in the HER2-HER3 receptor tyrosine kinase interface

The HER2 receptor tyrosine kinase is a driver oncogene in many human cancers, including breast and gastric cancer. Under physiologic levels of expression, HER2 heterodimerizes with other members of the EGF receptor/HER/ErbB family, and the HER2-HER3 dimer forms one of the most potent oncogenic receptor pairs. Previous structural biology studies have individually crystallized the kinase domains of HER2 and HER3, but the HER2-HER3 kinase domain heterodimer structure has yet to be solved. Using a reconstituted membrane system to form HER2-HER3 kinase domain heterodimers and carboxyl group footprinting mass spectrometry, we observed that HER2 and HER3 kinase domains preferentially form asymmetric heterodimers with HER3 and HER2 monomers occupying the donor and acceptor kinase positions, respectively. Conformational changes in the HER2 activation loop, as measured by changes in carboxyl group labeling, required both dimerization and nucleotide binding but did not require activation loop phosphorylation at Tyr-877. Molecular dynamics simulations on HER2-HER3 kinase dimers identify specific inter- and intramolecular interactions and were in good agreement with MS measurements. Specifically, several intermolecular ionic interactions between HER2 Lys-716-HER3 Glu-909, HER2 Glu-717-HER3 Lys-907, and HER2 Asp-871-HER3 Arg-948 were identified by molecular dynamics. We also evaluated the effect of the cancer-associated mutations HER2 D769H/D769Y, HER3 E909G, and HER3 R948K (also numbered HER3 E928G and R967K) on kinase activity in the context of this new structural model. This study provides valuable insights into the EGF receptor/HER/ErbB kinase structure and interactions, which can guide the design of future therapies.

Individualised proteome profiling of human endometrial tumours improves detection of new prognostic markers

Background:

The individual features of tumours are often disregarded in cohort studies. As these features may represent a source for individualised cancer treatment, it is important to develop a novel approach for their assessment.

Methods:

We used proteomics, systems biology, and immunohistochemistry to explore protein expression in human endometrial tumours, to identify deregulated regulatory mechanisms, and to validate observed changes in protein expression using tissue microarrays.

Results:

Compared with the evaluation of common tumour features, the evaluation of individual tumour features gave a more comprehensive and detailed overview of the regulatory processes in endometrial tumours. Systemic analysis of the individual proteome profiles showed that endometrial tumours employed different proteins to regulate similar functions. Comparison of our data with publicly available data sets of molecular profiling of human endometrial tumours confirmed that individual tumour features are not simply irrelevant individual variations, but are indeed important in endometrial tumorigenesis. Validation through tissue microarray investigation of MST1 and PKN1 proteins confirmed the usefulness of this approach, and suggested that MST1 and PKN1 may be considered as predictive biomarkers of endometrial cancer.

Conclusion:

We show that individualised profiling of endometrial tumours may deliver better insights into a tumour's physiology, thereby giving a better prediction of tumour development. Individual tumour features may also be used to tailor cancer treatment.

A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer

To date, three molecular markers (ER, PR, and CYP2D6) have been used in clinical setting to predict the benefit of the anti-estrogen tamoxifen therapy. Our aim was to validate new biomarker candidates predicting response to tamoxifen treatment in breast cancer by evaluating these in a meta-analysis of available transcriptomic datasets with known treatment and follow-up. Biomarker candidates were identified in Pubmed and in the 2007-2012 ASCO and 2011-2012 SABCS abstracts. Breast cancer microarray datasets of endocrine therapy-treated patients were downloaded from GEO and EGA and RNAseq datasets from TCGA. Of the biomarker candidates, only those identified or already validated in a clinical cohort were included. Relapse-free survival (RFS) up to 5 years was used as endpoint in a ROC analysis in the GEO and RNAseq datasets. In the EGA dataset, Kaplan-Meier analysis was performed for overall survival. Statistical significance was set at p < 0.005. The transcriptomic datasets included 665 GEO-based and 1,208 EGA-based patient samples. All together 68 biomarker candidates were identified. Of these, the best performing genes were PGR (AUC = 0.64, p = 2.3E-07), MAPT (AUC = 0.62, p = 7.8E-05), and SLC7A5 (AUC = 0.62, p = 9.2E-05). Further genes significantly correlated to RFS include FOS, TP53, BTG2, HOXB7, DRG1, CXCL10, and TPM4. In the RNAseq dataset, only ERBB2, EDF1, and MAPK1 reached statistical significance. We evaluated tamoxifen-resistance genes in three independent platforms and identified PGR, MAPT, and SLC7A5 as the most promising prognostic biomarkers in tamoxifen treated patients.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026.

Targeting BCL-2 with the BH3 mimetic ABT-199 in estrogen receptor-positive breast cancer

The prosurvival protein BCL-2 is frequently overexpressed in estrogen receptor (ER)-positive breast cancer. We have generated ER-positive primary breast tumor xenografts that recapitulate the primary tumors and demonstrate that the BH3 mimetic ABT-737 markedly improves tumor response to the antiestrogen tamoxifen. Despite abundant BCL-XL expression, similar efficacy was observed with the BCL-2 selective inhibitor ABT-199, revealing that BCL-2 is a crucial target. Unexpectedly, BH3 mimetics were found to counteract the side effect of tamoxifen-induced endometrial hyperplasia. Moreover, BH3 mimetics synergized with phosphatidylinositol 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) inhibitors in eliciting apoptosis. Importantly, these two classes of inhibitor further enhanced tumor response in combination therapy with tamoxifen. Collectively, our findings provide a rationale for the clinical evaluation of BH3 mimetics in therapy for breast cancer.

A multiplexed luciferase-based screening platform for interrogating cancer-associated signal transduction in cultured cells

Genome-scale interrogation of gene function using RNA interference (RNAi) holds tremendous promise for the rapid identification of chemically tractable cancer cell vulnerabilities. Limiting the potential of this technology is the inability to rapidly delineate the mechanistic basis of phenotypic outcomes and thus inform the development of molecularly targeted therapeutic strategies. We outline here methods to deconstruct cellular phenotypes induced by RNAi-mediated gene targeting using multiplexed reporter systems that allow monitoring of key cancer cell-associated processes. This high-content screening methodology is versatile and can be readily adapted for the screening of other types of large molecular libraries.

Ductal carcinoma in situ: morphology-based knowledge and molecular advances

Ductal carcinoma in situ (DCIS) is an established precursor of invasive breast carcinoma. Immunoperoxidase stains for selected markers can assist pathologists in the diagnosis of challenging ductal epithelial proliferations, but they cannot replace morphologic evaluation as the primary and critical assessment of this disease. Molecular studies provide further insight into how DCIS progresses to invasive carcinoma and also confirm the heterogeneity of this lesion. Morphology-based knowledge, immunohistochemistry, and molecular advances in DCIS are the subjects of this review.

The FGF/FGFR axis as a therapeutic target in breast cancer

Fibroblast growth factor receptor (FGFR) signaling is a vital component of both embryonic and postnatal mammary gland development, which has prompted researchers to investigate both its relevance to breast cancer and its potential as a therapeutic target. Deregulated FGFR signaling during breast cancer occurs through various mechanisms, including amplification of the receptor genes, aberrant ligand expression, receptor mutations and translocations. Recent experimental outcomes involving both animal models and human breast cancer cell lines have led to the initiation of multiple early clinical trials investigating the safety and efficacy of small molecule FGFR inhibitors. In this article we review both the most recent discoveries and the need for further investigation of the mechanisms through which FGF/FGFR signaling has emerged as an oncogenic driver.

Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue

Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics.

Forkhead box proteins: tuning forks for transcriptional harmony

Forkhead box (FOX) proteins are multifaceted transcription factors that are responsible for fine-tuning the spatial and temporal expression of a broad range of genes both during development and in adult tissues. This function is engrained in their ability to integrate a multitude of cellular and environmental signals and to act with remarkable fidelity. Several key members of the FOXA, FOXC, FOXM, FOXO and FOXP subfamilies are strongly implicated in cancer, driving initiation, maintenance, progression and drug resistance. The functional complexities of FOX proteins are coming to light and have established these transcription factors as possible therapeutic targets and putative biomarkers for specific cancers.

Tumor growth dynamics: insights into evolutionary processes

Identifying the types of event that drive tumor evolution and progression is crucial for understanding cancer. We suggest that the analysis of tumor growth dynamics can provide a window into tumor biology and evolution by connecting them with the types of genetic change that have occurred. Although fundamentally important, the documentation of tumor growth kinetics is more sparse in the literature than is the molecular analysis of cells. Here, we provide a historical summary of tumor growth patterns and argue that they can be classified into five basic categories. We then illustrate how those categories can provide insights into events that drive tumor progression, by discussing a particular evolutionary model as an example and encouraging such analysis in a more general setting.

Signaling pathway switch in breast cancer

Next generation sequencing studies have drawn the general landscape of breast cancers and identified hundreds of new, actual therapeutic targets. Two major signaling pathways seem to be altered in a vast proportion of breast cancers. The PI3 kinase/AKT pathway is activated and the JUN/MAPK pathway is repressed. Via the regulation of the cell cycle this metabolic switch impacts on the balance between self-renewal, proliferation and differentiation of the tumor-initiating cells

Oncogenic Actions of the Nuclear Receptor Corepressor (NCOR1) in a Mouse Model of Thyroid Cancer

Studies have suggested that the nuclear receptor corepressor 1 (NCOR1) could play an important role in human cancers. However, the detailed molecular mechanisms by which it functions in vivo to affect cancer progression are not clear. The present study elucidated the in vivo actions of NCOR1 in carcinogenesis using a mouse model (Thrb^PV/PV mice) that spontaneously develops thyroid cancer. Thrb^PV/PV mice harbor a dominantly negative thyroid hormone receptor β (TRβ) mutant (denoted as PV). We adopted the loss-of-the function approach by crossing Thrb^PV mice with mice that globally express an NCOR1 mutant protein (NCOR1ΔID) in which the receptor interaction domains have been modified so that it cannot interact with the TRβ, or PV, in mice. Remarkably, expression of NCOR1ΔID protein reduced thyroid tumor growth, markedly delayed tumor progression, and prolonged survival of Thrb^PV/PVNcor1^ΔID/ΔID mice. Tumor cell proliferation was inhibited by increased expression of cyclin-dependent kinase inhibitor 1 (p21^waf1/cip1; Cdkn1A), and apoptosis was activated by elevated expression of pro-apoptotic BCL-Associated X (Bax). Further analyses showed that p53 was recruited to the p53-binding site on the proximal promoter of the Cdkn1A and the Bax gene as a co-repressor complex with PV/NCOR1/histone deacetylas-3 (HDAC-3), leading to repression of the Cdkn1A as well as the Bax gene in thyroids of Thrb^PV/PV mice. In thyroids of Thrb^PV/PVNcor1^ΔID/ΔID mice, the p53/PV complex could not recruit NCOR1ΔID and HDAC-3, leading to de-repression of both genes to inhibit cancer progression. The present studies provided direct evidence in vivo that NCOR1 could function as an oncogene via transcription regulation in a mouse model of thyroid cancer.

Diagnostic SOX10 gene signatures in salivary adenoid cystic and breast basal-like carcinomas

BACKGROUND

Salivary adenoid cystic carcinoma (ACC) is an insidious slow-growing cancer with the propensity to recur and metastasise to distant sites. Basal-like breast carcinoma (BBC) is a molecular subtype that constitutes 15-20% of breast cancers, shares histological similarities and basal cell markers with ACC, lacks expression of ER (oestrogen receptor), PR (progesterone receptor), and HER2 (human epidermal growth factor receptor 2), and, similar to ACC, metastasises predominantly to the lung and brain. Both cancers lack targeted therapies owing to poor understanding of their molecular drivers.

METHODS

Gene expression profiling, immunohistochemical staining, western blot, RT-PCR, and in silico analysis of massive cancer data sets were used to identify novel markers and potential therapeutic targets for ACC and BBC. For the detection and comparison of gene signatures, we performed co-expression analysis using a recently developed web-based multi-experiment matrix tool for visualisation and rank aggregation.

RESULTS

In ACC and BBC we identified characteristic and overlapping SOX10 gene signatures that contained a large set of novel potential molecular markers. SOX10 was validated as a sensitive diagnostic marker for both cancers and its expression was linked to normal and malignant myoepithelial/basal cells. In ACC, BBC, and melanoma (MEL), SOX10 expression strongly co-segregated with the expression of ROPN1B, GPM6B, COL9A3, and MIA. In ACC and breast cancers, SOX10 expression negatively correlated with FOXA1, a cell identity marker and major regulator of the luminal breast subtype. Diagnostic significance of several conserved elements of the SOX10 signature (MIA, TRIM2, ROPN1, and ROPN1B) was validated on BBC cell lines.

CONCLUSION

SOX10 expression in ACC and BBC appears to be a part of a highly coordinated transcriptional programme characteristic for cancers with basal/myoepithelial features. Comparison between ACC/BBC and other cancers, such as neuroblastomaand MEL, reveals potential molecular markers specific for these cancers that are likely linked to their cell identity. SOX10 as a novel diagnostic marker for ACC and BBC provides important molecular insight into their molecular aetiology and cell origin. Given that SOX10 was recently described as a principal driver of MEL, identification of conserved elements of the SOX10 signatures may help in better understanding of SOX10-related signalling and development of novel diagnostic and therapeutic tools.

Biopsies: next-generation biospecimens for tailoring therapy

The majority of samples in existing tumour biobanks are surgical specimens of primary tumours. Insights into tumour biology, such as intratumoural heterogeneity, tumour-host crosstalk, and the evolution of the disease during therapy, require biospecimens from the primary tumour and those that reflect the patient's disease in specific contexts. Next-generation 'omics' technologies facilitate deep interrogation of tumours, but the characteristics of the samples can determine the ultimate accuracy of the results. The challenge is to biopsy tumours, in some cases serially over time, ensuring that the samples are representative, viable, and adequate both in quantity and quality for subsequent molecular applications. The collection of next-generation biospecimens, tumours, and blood samples at defined time points during the disease trajectory--either for discovery research or to guide clinical decisions--presents additional challenges and opportunities. From an organizational perspective, it also requires new additions to the multidisciplinary therapeutic team, notably interventional radiologists, molecular pathologists, and bioinformaticians. In this Review, we describe the existing procedures for sample procurement and processing of next-generation biospecimens, and highlight the issues involved in this endeavour, including the ethical, logistical, scientific, informational, and financial challenges accompanying next-generation biobanking.

Integrated genomic characterization of endometrial carcinoma

We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

An integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes.

This paper from The Cancer Genome Atlas Research Network presents an in-depth genome-wide analysis of endometrial (uterine) carcinomas from more than 350 patients. Based on a series of genomic features including newly identified hotspot mutations in the DNA polymerase gene POLE, and novel mutations in the ARID5B DNA-binding protein, the authors propose a reclassification of endometrial tumours into four distinct types. This might have clinical relevance for post-surgical adjuvant treatment of women with aggressive tumours.

Synthetic genetic targeting of genome instability in cancer

Cancer is a leading cause of death throughout the World. A limitation of many current chemotherapeutic approaches is that their cytotoxic effects are not restricted to cancer cells, and adverse side effects can occur within normal tissues. Consequently, novel strategies are urgently needed to better target cancer cells. As we approach the era of personalized medicine, targeting the specific molecular defect(s) within a given patient's tumor will become a more effective treatment strategy than traditional approaches that often target a given cancer type or sub-type. Synthetic genetic interactions are now being examined for their therapeutic potential and are designed to target the specific genetic and epigenetic phenomena associated with tumor formation, and thus are predicted to be highly selective. In general, two complementary approaches have been employed, including synthetic lethality and synthetic dosage lethality, to target aberrant expression and/or function associated with tumor suppressor genes and oncogenes, respectively. Here we discuss the concepts of synthetic lethality and synthetic dosage lethality, and explain three general experimental approaches designed to identify novel genetic interactors. We present examples and discuss the merits and caveats of each approach. Finally, we provide insight into the subsequent pre-clinical work required to validate novel candidate drug targets.

TACE-dependent TGFα shedding drives triple-negative breast cancer cell invasion

The epidermal growth factor receptor (EGFR) is frequently expressed in triple-negative breast cancer (TNBC) and is a marker of poor prognosis in this patient population. Because activating mutations in this kinase are very rare events in breast cancer, we screened breast tumor gene expression profiles to examine the distribution of EGFR ligand expression. Of the six known EGFR ligands, transforming growth factor alpha (TGFα) was expressed more highly in triple-negative breast tumors than in tumors of other subtypes. TGFα is synthesized as a transmembrane precursor requiring tumor necrosis factor alpha converting enzyme (TACE)/ADAM17-dependent proteolytic release to activate its receptor. In our study, we show that an inhibitor of this proteolytic release blocks invasion, migration and colony formation by several TNBC cell lines. Each of the effects of the drug was reversed upon expression of a soluble TGFα mutant that does not require TACE activity, implicating this growth factor as a key metalloproteinase substrate for these phenotypes. Together, these data demonstrate that TACE-dependent TGFα shedding is a key process driving EGFR activation and subsequent proliferation and invasion in TNBC cell lines.

MicroRNA-30c inhibits human breast tumour chemotherapy resistance by regulating TWF1 and IL-11

Chemotherapy resistance frequently drives tumour progression. However, the underlying molecular mechanisms are poorly characterized. Epithelial-to-mesenchymal transition has been shown to correlate with therapy resistance, but the functional link and signalling pathways remain to be elucidated. Here we report that microRNA-30c, a human breast tumour prognostic marker, has a pivotal role in chemoresistance by a direct targeting of the actin-binding protein twinfilin 1, which promotes epithelial-to-mesenchymal transition. An interleukin-6 family member, interleukin-11 is identified as a secondary target of twinfilin 1 in the microRNA-30c signalling pathway. Expression of microRNA-30c inversely correlates with interleukin-11 expression in primary breast tumours and low interleukin-11 correlates with relapse-free survival in breast cancer patients. Our study demonstrates that microRNA-30c is transcriptionally regulated by GATA3 in breast tumours. Identification of a novel microRNA-mediated pathway that regulates chemoresistance in breast cancer will facilitate the development of novel therapeutic strategies.

Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer

Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and multi-level deep sequencing data. To answer this need we introduce here a data-driven algorithm, SPINLONG, which is designed to search for genes that match the user-defined hypotheses or models. SPINLONG is applicable to various experimental setups measuring several molecular markers in parallel. To demonstrate the SPINLONG approach, we analyzed ChIP-seq data reporting PolII, estrogen receptor (), H3K4me3 and H2A.Z occupancy at five time points in the MCF-7 breast cancer cell line after estradiol stimulus. We obtained 777 early responsive genes and compared the biological functions of the genes having binding within 20 kb of the transcription start site (TSS) to genes without such binding site. Our results show that the non-genomic action of via the MAPK pathway, instead of direct binding, may be responsible for early cell responses to activation. Our results also indicate that the responsive genes triggered by the genomic pathway are transcribed faster than those without binding sites. The survival analysis of the 777 responsive genes with 150 primary breast cancer tumors and in two independent validation cohorts indicated the ATAD3B gene, which does not have binding site within 20 kb of its TSS, to be significantly associated with poor patient survival.

Cellular processes in mammalian cells are tightly regulated to ensure that the cells function properly as a part of an organism. Dysregulation of some of these processes, such as apoptosis, cell proliferation and growth, can lead to cancer. One of the most important regulation mechanisms for cellular processes is via activation of membrane receptors by extra-cellular stimulus. Such cues trigger signal cascades that lead to altered expression of a number of genes in the cell nucleus; a key challenge in biomedicine is to identify which genes respond to a specific stimulus. These so called response genes can be investigated on a whole-genome scale with genomic sequencing, which is a technology that can quantify protein binding to DNA or gene activation. Analysis of such whole-genome data, however, is challenging due to billions of data points measured in the experiments. Here we introduce a novel computational method, SPINLONG, which is a widely applicable novel computational method that integrates multiple levels of deep sequencing data to produce experimentally testable hypotheses. We applied SPINLONG to breast cancer data and found early responsive genes for estrogen receptor and analyzed their regulation. These analyses resulted in a gene whose high activity is associated with decreased breast cancer patient survival.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones.

Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance

A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor recurs. Genome sequencing and computational analysis allows to computational dissection of clones from tumors, while singe-cell genome sequencing including RNA-Seq allows profiling of these clones. This opens a new window for treating a tumor as a system in which clones are evolving. Future cancer systems biology studies should consider a tumor as an evolving system with multiple clones. Therefore, topics discussed in Part 2 of this review include evolutionary dynamics of clonal networks, early-warning signals (e.g., genome duplication events) for formation of fast-growing clones, dissecting tumor heterogeneity, and modeling of clone-clone-stroma interactions for drug resistance. The ultimate goal of the future systems biology analysis is to obtain a 'whole-system' understanding of a tumor and therefore provides a more efficient and personalized management strategies for cancer patients.

Video Q&A: molecular profiling of breast cancer

In this video Q&A, we talk to Professor Carlos Caldas about the identification of breast cancer subtypes through molecular profiling, and the clinical implications for diagnosis and treatment.

Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology

The progressive introduction of high-throughput molecular techniques in the clinic allows for the extensive and systematic exploration of multiple biologic layers of tumors. Molecular profiles and classifiers generated from these assays represent the foundation of what the National Academy describes as the future of "precision medicine". However, the analysis of such complex data requires the implementation of sophisticated bioinformatic and statistical procedures. It is critical that oncology practitioners be aware of the advantages and limitations of the methods used to generate classifiers to usher them into the clinic. This article uses publicly available expression data from patients with non-small cell lung cancer to first illustrate the challenges of experimental design and preprocessing of data before clinical application and highlights the challenges of high-dimensional statistical analysis. It provides a roadmap for the translation of such classifiers to clinical practice and makes key recommendations for good practice.

Genetic heterogeneity in breast cancer: the road to personalized medicine?

More women die from breast cancer across the world today than from any other type of malignancy. The clinical course of breast cancer varies tremendously between patients. While some of this variability is explained by traditional clinico-pathological factors (including patient age, tumor stage, histological grade and estrogen receptor status), molecular profiling studies have defined breast cancer subtypes with distinct clinical outcomes. This mini-review considers recent studies which have used genomics technologies in an attempt to identify new biomarkers of prognosis and treatment response. These studies highlight the genetic heterogeneity that exists within breast cancers in space and time.