Towards discovery-driven translational research in breast cancer

Discovery-driven translational research in breast cancer is moving steadily from the study of cell lines to the analysis of clinically relevant samples that, together with the ever increasing number of novel and powerful technologies available within genomics, proteomics and functional genomics, promise to have a major impact on the way breast cancer will be diagnosed, treated and monitored in the future. Here we present a brief report on long-term ongoing strategies at the Danish Centre for Translational Breast Cancer Research to search for markers for early detection and targets for therapeutic intervention, to identify signalling pathways affected in individual tumours, as well as to integrate multiplatform 'omic' data sets collected from tissue samples obtained from individual patients. The ultimate goal of this initiative is to coalesce knowledge-based complementary procedures into a systems biology approach to fight breast cancer.     

Quality control of human tissues-experience from the Indiana University Cancer Center-Lilly Research Labs human tissue bank

The success of molecular research and its applications in both the clinical and basic research arenas is strongly dependent on the collection, handling, storage, and quality control of fresh human tissue samples. This tissue bank was set up to bank fresh surgically obtained human tissue using a Clinical Annotated Tissue Database (CATD) in order to capture the associated patient clinical data and demographics using a one way patient encryption scheme to protect patient identification. In this study, we determined that high quality of tissue samples is imperative for both genomic and proteomic molecular research. This paper also contains a brief compilation of the literature involved in the patient ethics, patient informed consent, patient de-identification, tissue collection, processing, and storage as well as basic molecular research generated from the tissue bank using good clinical practices. The current applicable rules, regulations, and guidelines for handling human tissues are briefly discussed. More than 6,610 cancer patients have been consented (97% of those that were contacted by the consenter) and 16,800 tissue specimens have been banked from these patients in 9 years. All samples collected in the bank were QC’d by a pathologist. Approximately 1,550 tissue samples have been requested for use in basic, clinical, and/or biomarker cancer research studies. Each tissue aliquot removed from the bank for a research study were evaluated by a second H&E, if the samples passed the QC, they were submitted for genomic and proteomic molecular analysis/study. Approximately 75% of samples evaluated were of high histologic quality and used for research studies. Since 2003, we changed the patient informed consent to allow the tissue bank to gather more patient clinical follow-up information. Ninety two percent of the patients (1,865 patients) signed the new informed consent form and agreed to be re-contacted for follow-up information on their disease state. In addition, eighty five percent of patients (1,584) agreed to be re-contacted to provide a biological fluid sample to be used for biomarker research.     

Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.     

周期蛋白和周期蛋白依赖性激酶及相关激酶抑制剂在细胞周期进程中的调控机制研究进展

在细胞发育过程中,细胞周期起着至关重要的作用。细胞周期进程主要受细胞周期蛋白依赖性激酶(cyclin dependent kinase, CDK)、周期蛋白和内源性CDK抑制剂(cyclin-dependent kinase inhibitors,CKI)调控。其中,CDK是主要的细胞周期调节因子,可与周期蛋白结合形成周期蛋白-CDK复合物,从而使数百种底物磷酸化,调控分裂间期和有丝分裂进程。各类细胞周期蛋白的活性异常,可引起不受控制的癌细胞增殖,导致癌症的发生与发展。因此,了解CDK的活性变化情况、周期蛋白-CDK的组装以及CKI的作用,将有助于了解细胞周期进程中潜在的调控过程,为癌症与疾病的治疗和CKI治疗药物的研发提供基础。本文关注了CDK激活和灭活的关键事件,并总结了周期蛋白-CDK在特定时期及位置的调控过程,以及相关CKI治疗药物在癌症及疾病中的研究进展,最后简单阐述了细胞周期进程研究面临的问题和存在的挑战,以期为后续细胞周期进程的深入研究提供参考和思路。     

Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.     

Epidermal Growth Factor Receptor in Prostate Cancer Derived Exosomes

Exosomes proteins and microRNAs have gained much attention as diagnostic tools and biomarker potential in various malignancies including prostate cancer (PCa). However, the role of exosomes and membrane-associated receptors, particularly epidermal growth factor receptor (EGFR) as mediators of cell proliferation and invasion in PCa progression remains unexplored. EGFR is frequently overexpressed and has been associated with aggressive forms of PCa. While PCa cells and tissues express EGFR, it is unknown whether exosomes derived from PCa cells or PCa patient serum contains EGFR. The aim of this study was to detect and characterize EGFR in exosomes derived from PCa cells, LNCaP xenograft and PCa patient serum. Exosomes were isolated from conditioned media of different PCa cell lines; LNCaP xenograft serum as well as patient plasma/serum by differential centrifugation and ultracentrifugation on a sucrose density gradient. Exosomes were confirmed by electron microscopy, expression of exosomal markers and NanoSight^™ analysis. EGFR expression was determined by western blot analysis and ELISA. This study demonstrates that exosomes may easily be derived from PCa cell lines, serum obtained from PCa xenograft bearing mice and clinical samples derived from PCa patients. Presence of exosomal EGFR in PCa patient exosomes may present a novel approach for measuring of the disease state. Our work will allow to build on this finding for future understanding of PCa exosomes and their potential role in PCa progression and as minimal invasive biomarkers for PCa.     

Re-purposing clinical kinase inhibitors to enhance chemosensitivity by overriding checkpoints

Inhibitors of the DNA damage checkpoint kinase, Chk1, are highly effective as chemo- and radio-sensitizers in preclinical studies but are not well-tolerated by patients. We exploited the promiscuous nature of kinase inhibitors to screen 9 clinically relevant kinase inhibitors for their ability to sensitize pancreatic cancer cells to a sub-lethal concentration of gemcitabine. Bosutinib, dovitinib, and BEZ-235 were identified as sensitizers that abrogated the DNA damage checkpoint. We further characterized bosutinib, an FDA-approved Src/Abl inhibitor approved for chronic myelogenous leukemia. Unbeknownst to us, we used an isomer (Bos-I) that was unknowingly synthesized and sold to the research community as “authentic” bosutinib. In vitro and cell-based assays showed that both the authentic bosutinib and Bos-I inhibited DNA damage checkpoint kinases Chk1 and Wee1, with Bos-I showing greater potency. Imaging data showed that Bos-I forced cells to override gemcitabine-induced DNA damage checkpoint arrest and destabilized stalled replication forks. These inhibitors enhanced sensitivity to the DNA damaging agents’ gemcitabine, cisplatin, and doxorubicin in pancreatic cancer cell lines. The in vivo efficacy of Bos-I was validated using cells derived directly from a pancreatic cancer patient’s tumor. Notably, the xenograft studies showed that the combination of gemcitabine and Bos-I was significantly more effective in suppressing tumor growth than either agent alone. Finally, we show that the gatekeeper residue in Wee1 dictates its sensitivity to the 2 compounds. Our strategy to screen clinically relevant kinase inhibitors for off-target effects on cell cycle checkpoints is a promising approach to re-purpose drugs as chemosensitizers.     

Current perspectives in cancer proteomics

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.     

Proteomic analysis of tissue samples in translational breast cancer research

In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis, and both prognosis and prediction of outcome of chemotherapy. The purpose of this review is to critically appraise what has been achieved to date using proteomic technologies and to bring forward novel strategies – based on the analysis of clinically relevant samples – that promise to accelerate the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens.     

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.     

A functional glycoproteomics approach identifies CD13 as a novel E-selectin ligand in breast cancer

Background

The glycan moieties sialyl-Lewis-X and/or -A (sLe^X/A) are the primary ligands for E-selectin, regulating subsequent tumor cell extravasation into distant organs. However, the nature of the glycoprotein scaffolds displaying these glycans in breast cancer remains unclear and constitutes the focus of the present investigation.

Tumour Biological Aspects of CD24, A Mucin-Like Adhesion Molecule

CD24 is a molecule that recently has raised considerable attention in tumour biology. It is involved in cell adhesion and metastatic tumour spread. It has also been described as a new diagnostic marker of tumours, of neuroendocrine differentiation and, possibly most intriguing of all, of patient prognosis. High rates of CD24 expression detected by immunohistochemistry have been found in epithelial ovarian cancer (83%), breast cancer (85%), non-small cell lung cancer (45%), prostate cancer (48%) and pancreatic cancer (72%). With the exception of pancreatic cancer, high rates of CD24 are significantly associated with a more aggressive course of the disease, a finding that remains significant in a multivariate analysis. The aim of this review is to summarize relevant work covering these aspects of CD24.     

Derivation of the King’s College London human embryonic stem cell lines

Since the derivation of the first human embryonic stem cell (hESC) line in 1998, there has been substantial interest in the potential of these cells for regenerative medicine and cell therapy and in the use of hESCs carrying clinically relevant genetic mutations as models for disease research and therapeutic target identification. There is still a need to improve derivation efficiency and further the understanding of the basic biology of these cells and to develop clinical grade culture systems with the aim of producing cell lines suitable for subsequent manipulation for therapy. The derivation of initial hESC lines at King’s College London is discussed here, with focus on derivation methodology. Each of the derivations was distinctive. Although the stage and morphology of each blastocyst were generally similar in each attempt, the behaviour of the colonies was unpredictable; colony morphology and development was different with each attempt. Days 5, 6 and 7 blastocysts were used successfully, and the number of days until appearance of stem-like cells varied from 4 to 14 d. Routine characterisation analyses were performed on three lines, all of which displayed appropriate marker expression and survived cryopreservation—thaw cycles. From the lines discussed, four are at various stages of the deposition process with the UKSCB, one is pending submission and two are unsuitable for banking. Continued open and transparent reporting of results and collaborations will maximise the efficiency of derivation and facilitate the development of standardised protocols for the derivation and early culture of hESC lines.     

Microarrays of tumor cell derived proteins uncover a distinct pattern of prostate cancer serum immunoreactivity

The broad characterization of the immune responses elicited by tumors has valuable applications in diagnostics and basic research. We present here the use of microarrays of tumor-derived proteins to profile the antibody repertoire in the sera of prostate cancer patients and controls. Two-dimensional liquid chromatography was used to separate proteins from the prostate cancer cell line LNCaP into 1760 fractions. These fractions were spotted in microarrays on coated microscope slides, and the microarrays were incubated individually with serum samples from 25 men with prostate cancer and 25 male controls. The amount of immunoglobulin bound to each fraction by each serum sample was quantified. Statistical analysis revealed that 38 of the fractions had significantly higher levels of immunoglobulin binding in the prostate cancer samples compared to the controls. Two fractions showed higher binding in the control samples. The significantly higher immunoglobulin reactivity from the prostate cancer samples may reflect a strong immune response to the tumors in the prostate cancer patients. We used multivariate analysis to classify the samples as either prostate cancer or control. In a cross-validation study, recursive partitioning classified the samples with 84% accuracy. A decision tree with two levels of partitioning classified the samples with 98% accuracy. Additional studies will allow further characterization of tumor antigens in prostate cancer and their significance for diagnosis. These results suggest that microarrays of fractionated proteins could be a powerful tool for tumor antigen discovery and cancer diagnosis.     

Protein phosphorylation analysis in archival clinical cancer samples by shotgun and targeted proteomics approaches

Protein phosphorylation affects most eukaryotic cellular processes and its deregulation is considered a hallmark of cancer and other diseases. Phosphoproteomics may enable monitoring of altered signaling pathways as a means of stratifying tumors and facilitating the discovery of new drugs. Unfortunately, the development of molecular tests for clinical use is constrained by the limited availability of fresh frozen, clinically annotated samples. Here we report phosphopeptide analysis in human archival formalin-fixed, paraffin-embedded (FFPE) cancer samples based on immobilized metal affinity chromatography followed by liquid chromatography coupled with tandem mass spectrometry and selected reaction monitoring techniques. Our results indicate the equivalence of detectable phosphorylation rates in archival FFPE and fresh frozen tissues. Moreover, we demonstrate the applicability of targeted assays for phosphopeptide analysis in clinical archival FFPE samples, using an experimental workflow suitable for processing and analyzing large sample series. This work paves the way for the application of shotgun and targeted phosphoproteomics approaches in clinically relevant studies using archival clinical samples.     

Optimizing Size Exclusion Chromatography for Extracellular Vesicle Enrichment and Proteomic Analysis from Clinically Relevant Samples

The field of extracellular vesicle (EV) research has rapidly expanded in recent years, with particular interest in their potential as circulating biomarkers. Proteomic analysis of EVs from clinical samples is complicated by the low abundance of EV proteins relative to highly abundant circulating proteins such as albumin and apolipoproteins. To overcome this, size exclusion chromatography (SEC) has been proposed as a method to enrich EVs whilst depleting protein contaminants; however, the optimal SEC parameters for EV proteomics have not been thoroughly investigated. Here, quantitative evaluation and optimization of SEC are reported for separating EVs from contaminating proteins. Using a synthetic model system followed by cell line‐derived EVs, it is found that a 10 mL Sepharose 4B column in PBS produces optimal resolution of EVs from background protein. By spiking‐in cancer cell‐derived EVs to healthy plasma, it is shown that some cancer EV‐associated proteins are detectable by nano‐LC‐MS/MS when as little as 1% of the total plasma EV number are derived from a cancer cell line. These results suggest that an optimized SEC and nanoLC‐MS/MS workflow may be sufficiently sensitive for disease EV protein biomarker discovery from patient‐derived clinical samples.