Showing papers on "Tumour heterogeneity published in 2012"

Intratumor heterogeneity and branched evolution revealed by multiregion sequencing.

Abstract: Background Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. Methods To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. Results Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. Conclusions Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.)

Intra-tumour heterogeneity: a looking glass for cancer?

Abstract: Populations of tumour cells display remarkable variability in almost every discernable phenotypic trait, including clinically important phenotypes such as ability to seed metastases and to survive therapy. This phenotypic diversity results from the integration of both genetic and non-genetic influences. Recent technological advances have improved the molecular understanding of cancers and the identification of targets for therapeutic interventions. However, it has become exceedingly apparent that the utility of profiles based on the analysis of tumours en masse is limited by intra-tumour genetic and epigenetic heterogeneity, as characteristics of the most abundant cell type might not necessarily predict the properties of mixed populations. In this Review, we discuss both genetic and non-genetic causes of phenotypic heterogeneity of tumour cells, with an emphasis on heritable phenotypes that serve as a substrate for clonal selection. We discuss the implications of intra-tumour heterogeneity in diagnostics and the development of therapeutic resistance.

Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival.

Abstract: To establish the potential for tumour heterogeneity in non-small cell lung cancer (NSCLC) as assessed by CT texture analysis (CTTA) to provide an independent marker of survival for patients with NSCLC. Tumour heterogeneity was assessed by CTTA of unenhanced images of primary pulmonary lesions from 54 patients undergoing 18F-fluorodeoxyglucose (FDG) PET-CT for staging of NSCLC. CTTA comprised image filtration to extract fine, medium and coarse features with quantification of the distribution of pixel values (uniformity) within the filtered images. Receiver operating characteristics identified thresholds for PET and CTTA parameters that were related to patient survival using Kaplan-Meier analysis. The median (range) survival was 29.5 (1–38) months. 24, 10, 14 and 6 patients had tumour stages I, II, III and IV respectively. PET stage and tumour heterogeneity assessed by CTTA were significant independent predictors of survival (PET stage: Odds ratio 3.85, 95% confidence limits 0.9–8.09, P = 0.002; CTTA: Odds ratio 56.4, 95% confidence limits 4.79–666, p = 0.001). SUV was not a significantly associated with survival. Assessment of tumour heterogeneity by CTTA of non-contrast enhanced images has the potential for to provide a novel, independent predictor of survival for patients with NSCLC. • Computed tomography is a routine staging procedure in non-small cell lung cancer • CT texture analysis (CTTA) can quantify heterogeneity within these lung tumours • CTTA seems to offer a novel independent predictor of survival for NSCLC • CTTA could contribute to disease risk-stratification for patients with NSCLC

Sox2 expression in breast tumours and activation in breast cancer stem cells.

Abstract: The cancer stem cell (CSC) model does not imply that tumours are generated from transformed tissue stem cells. The target of transformation could be a tissue stem cell, a progenitor cell, or a differentiated cell that acquires self-renewal ability. The observation that induced pluripotency reprogramming and cancer are related has lead to the speculation that CSCs may arise through a reprogramming-like mechanism. Expression of pluripotency genes (Oct4, Nanog and Sox2) was tested in breast tumours by immunohistochemistry and it was found that Sox2 is expressed in early stage breast tumours. However, expression of Oct4 or Nanog was not found. Mammosphere formation in culture was used to reveal stem cell properties, where expression of Sox2, but not Oct4 or Nanog, was induced. Over-expression of Sox2 increased mammosphere formation, effect dependent on continuous Sox2 expression; furthermore, Sox2 knockdown prevented mammosphere formation and delayed tumour formation in xenograft tumour initiation models. Induction of Sox2 expression was achieved through activation of the distal enhancer of Sox2 promoter upon sphere formation, the same element that controls Sox2 transcription in pluripotent stem cells. These findings suggest that reactivation of Sox2 represents an early step in breast tumour initiation, explaining tumour heterogeneity by placing the tumour-initiating event in any cell along the axis of mammary differentiation.

Breast-cancer stem cells—beyond semantics

Abstract: Intratumoral heterogeneity in breast cancer is well documented. Although the mechanisms leading to this heterogeneity are not understood, a subpopulation of cancer cells, cancer stem cells (CSCs), that have some phenotypic similarities with adult tissue stem cells, has been suggested to contribute to tumour heterogeneity. It has been postulated that these CSCs are dormant, and by virtue of their low proliferative activity and ability to exclude intracellular toxins, are resistant to chemotherapy and radiation therapy. These cells were initially isolated based on the presence of markers such as CD44, CD24, and ALDH1, with further characterisation using mammosphere assay and transplantation into immunodeficient mice. The CSC hypothesis raises several theoretical and practical questions. Does cancer arise in normal mammary stem cells or do some malignant cells acquire a CSC phenotype through clonal evolution? Are CSCs in different molecular (intrinsic) subtypes of breast cancer similar, or do they have distinct properties based on the subtype? Does the CSC phenotype reflect plasticity or the dynamic nature of a few cancer cells? How do these cells acquire invasive behaviour, as they go through epithelial-to-mesenchymal transition and then revert to epithelial phenotype at sites of metastasis in response to tumour microenvironmental and metastasis site-specific cues? It is increasingly recognised that the methods and assays used for identifying CSCs have substantial limitations; does this negate the entire concept? In this Personal View, we argue that the CSC phenotype represents an aggressive clone that survives in an adverse environment through constant evolution and integration of various hallmarks of cancer. This evolution could involve acquiring mutations that permit asymmetric and symmetric division, converting the host immune attack to its own advantage, and plasticity to adapt to sites of metastasis through reversible change in adhesion molecules. We also argue that the cell-type origin of cancer could affect the rate at which CSCs develop in a tumour, with an eventual effect on disease outcome.

Overcoming implementation challenges of personalized cancer therapy

Abstract: Personalized cancer therapy is based on the precept that detailed molecular characterization of the patient's tumour and its microenvironment will enable tailored therapies to improve outcomes and decrease toxicity. The goal of personalized therapy is to target aberrations that drive tumour growth and survival, by administering the right drug combination for the right person. This is becoming increasingly achievable with advances in high-throughput technologies to characterize tumours and the expanding repertoire of molecularly targeted therapies. However, there are numerous challenges that need to be surpassed before delivering on the promise of personalized cancer therapy. These include tumour heterogeneity and molecular evolution, costs and potential morbidity of biopsies, lack of effective drugs against most genomic aberrations, technical limitations of molecular tests, and reimbursement and regulatory hurdles. Critically, the 'hype' surrounding personalized cancer therapy must be tempered with realistic expectations, which, today, encompass increased survival times for only a portion of patients.

Personalized medicine for lung cancer: new challenges for pathology

Abstract: Recent advances in non-small-cell lung cancer (NSCLC) therapy mean the relatively simple discrimination between small-cell and 'non-small-cell' carcinoma is insufficient to determine the best treatment for individual patients. Safety, efficacy and prescribing requirements mandate more specific subtyping of NSCLC for several new drugs: practice made difficult by the tumour heterogeneity combined with the paucity of tissue in most diagnostic samples. Immunohistochemical approaches have emerged as accurate predictors of probable tumour histotype. P63 and/or cytokeratins 5 and 6 and thyroid transcription factor 1 (TTF1) are among the best predictors, respectively, of squamous and adenocarcinoma histology. Molecular characteristics may predict response to both newer molecular targeted agents and traditional cytotoxic agents. Specific mutations in the epidermal growth factor receptor (EGFR) gene as predictors of response to EGFR tyrosine kinase inhibitors (erlotinib, gefitinib) is the first example of markers which predict response to targeted agents. Actual drug targets [e.g. thymidilate synthase (TS) - pemetrexed] or markers of the tumour's ability to repair cytotoxic drug-induced damage [e.g. excision repair cross-complementation group 1 (ERCC1) - cisplatin] may well also complement NSCLC diagnosis. This extended diagnostic requirement from increasingly limited material provided by minimally invasive biopsy techniques poses major challenges for pathology.

Key concepts in glioblastoma therapy

Abstract: Glioblastoma is the most common form of primary brain cancer and remains one of the most aggressive forms of human cancer. Current standard of care involves maximal surgical resection followed by concurrent therapy with radiation and the DNA alkylating agent temozolomide. Despite this aggressive regimen, the median survival remains approximately 14 months. Meaningful strategies for therapeutic intervention are desperately needed. Development of such strategies will require an understanding of the therapeutic concepts that have evolved over the past three decades. This article reviews the key principles that drive the formulation of therapeutic strategies in glioblastoma. Specifically, the concepts of tumour heterogeneity, oncogene addiction, non-oncogene addiction, tumour initiating cells, tumour microenvironment, non-coding sequences and DNA damage response will be reviewed.

Mate Pair Sequencing of Whole-Genome-Amplified DNA Following Laser Capture Microdissection of Prostate Cancer

Abstract: High-throughput next-generation sequencing provides a revolutionary platform to unravel the precise DNA aberrations concealed within subgroups of tumour cells. However, in many instances, the limited number of cells makes the application of this technology in tumour heterogeneity studies a challenge. In order to address these limitations, we present a novel methodology to partner laser capture microdissection (LCM) with sequencing platforms, through a whole-genome amplification (WGA) protocol performed in situ directly on LCM engrafted cells. We further adapted current Illumina mate pair (MP) sequencing protocols to the input of WGA DNA and used this technology to investigate large genomic rearrangements in adjacent Gleason Pattern 3 and 4 prostate tumours separately collected by LCM. Sequencing data predicted genome coverage and depths similar to unamplified genomic DNA, with limited repetition and bias predicted in WGA protocols. Mapping algorithms developed in our laboratory predicted high-confidence rearrangements and selected events each demonstrated the predicted fusion junctions upon validation. Rearrangements were additionally confirmed in unamplified tissue and evaluated in adjacent benign-appearing tissues. A detailed understanding of gene fusions that characterize cancer will be critical in the development of biomarkers to predict the clinical outcome. The described methodology provides a mechanism of efficiently defining these events in limited pure populations of tumour tissue, aiding in the derivation of genomic aberrations that initiate cancer and drive cancer progression.

Density-dependent quiescence in glioma invasion: instability in a simple reaction-diffusion model for the migration/proliferation dichotomy.

Abstract: Gliomas are very aggressive brain tumours, in which tumour cells gain the ability to penetrate the surrounding normal tissue. The invasion mechanisms of this type of tumour remain to be elucidated. Our work is motivated by the migration/proliferation dichotomy (go-or-grow) hypothesis, i.e. the antagonistic migratory and proliferating cellular behaviours in a cell population, which may play a central role in these tumours. In this paper, we formulate a simple go-or-grow model to investigate the dynamics of a population of glioma cells for which the switch from a migratory to a proliferating phenotype (and vice versa) depends on the local cell density. The model consists of two reaction-diffusion equations describing cell migration, proliferation and a phenotypic switch. We use a combination of numerical and analytical techniques to characterize the development of spatio-temporal instabilities and travelling wave solutions generated by our model. We demonstrate that the density-dependent go-or-grow mechanism can produce complex dynamics similar to those associated with tumour heterogeneity and invasion.

Whole genome sequencing for lung cancer

Abstract: Lung cancer is a leading cause of cancer related morbidity and mortality globally, and carries a dismal prognosis. Improved understanding of the biology of cancer is required to improve patient outcomes. Next-generation sequencing (NGS) is a powerful tool for whole genome characterisation, enabling comprehensive examination of somatic mutations that drive oncogenesis. Most NGS methods are based on polymerase chain reaction (PCR) amplification of platform-specific DNA fragment libraries, which are then sequenced. These techniques are well suited to high-throughput sequencing and are able to detect the full spectrum of genomic changes present in cancer. However, they require considerable investments in time, laboratory infrastructure, computational analysis and bioinformatic support. Next-generation sequencing has been applied to studies of the whole genome, exome, transcriptome and epigenome, and is changing the paradigm of lung cancer research and patient care. The results of this new technology will transform current knowledge of oncogenic pathways and provide molecular targets of use in the diagnosis and treatment of cancer. Somatic mutations in lung cancer have already been identified by NGS, and large scale genomic studies are underway. Personalised treatment strategies will improve care for those likely to benefit from available therapies, while sparing others the expense and morbidity of futile intervention. Organisational, computational and bioinformatic challenges of NGS are driving technological advances as well as raising ethical issues relating to informed consent and data release. Differentiation between driver and passenger mutations requires careful interpretation of sequencing data. Challenges in the interpretation of results arise from the types of specimens used for DNA extraction, sample processing techniques and tumour content. Tumour heterogeneity can reduce power to detect mutations implicated in oncogenesis. Next-generation sequencing will facilitate investigation of the biological and clinical implications of such variation. These techniques can now be applied to single cells and free circulating DNA, and possibly in the future to DNA obtained from body fluids and from subpopulations of tumour. As costs reduce, and speed and processing accuracy increase, NGS technology will become increasingly accessible to researchers and clinicians, with the ultimate goal of improving the care of patients with lung cancer.

Biomarkers: the next therapeutic hurdle in metastatic renal cell carcinoma.

Abstract: Despite recent advances, metastatic renal cell carcinoma remains largely an incurable disease. Vascular endothelial growth factor and mammalian target of rapamycin inhibitors have provided improvements in clinical outcomes. High-dose interleukin 2 remains an option for highly selected patients and is associated with durable remissions in a small minority of patients. The toxicity profiles of specific agents and patient characteristics and comorbidities and costs have an important role in the current choice of therapy. Major challenges encountered in developing molecular biomarkers to guide therapy are tumour heterogeneity and standardisation of tissue collection and analysis. Although biomarkers are in their infancy of development, they should be a priority in early preclinical and clinical development in order to guide rational tailored development of emerging agents.

Delivering preventive, predictive and personalised cancer medicine for renal cell carcinoma: the challenge of tumour heterogeneity

Abstract: Recent years have seen major advances in the management of metastatic renal cell carcinoma (mRCC). The tyrosine kinase and mammalian target of rapamycin inhibitors have resulted in disease control and improved survival for many patients with mRCC, but they have not led to preventive, predictive or personalised medicine (PPPM). Failure to achieve this rests ultimately with inadequate knowledge of tissue and molecular heterogeneity; discovery of these drugs was based upon identification of pathogenic molecular pathways in RCC, but research into molecular factors which underpin drug response, resistance and selection of therapy for individual patients has lagged well behind clinical trials of drug development. This review will provide an overview of the development of targeted drug therapies for mRCC, will discuss the challenges which currently impede the delivery of PPPM, including identification of biomarkers, drug resistance and molecular heterogeneity, and will propose research methodologies and technologies required to overcome these obstacles.

Multiparametric PET/CT in oncology

Abstract: The standardized uptake value (SUV) and other measurements of tumour uptake of fluorodeoxyglucose (FDG) on positron emission tomography (PET) can potentially be supplemented by additional imaging parameters derived either from the PET images or from the computed tomography (CT) component of integrated PET/CT examinations including tumour size, CT attenuation, texture (reflecting tumour heterogeneity) and blood flow. This article illustrates the emerging benefits of such a multiparametric approach. Example benefits include greater diagnostic accuracy in characterization of adrenal masses achieved by using both the SUV and measured CT attenuation. Tumour size combined with the SUV can potentially improve the prognostic information available from PET/CT in oesophageal and lung cancer. However, greater improvements may be realized through using CT measurements of texture instead of size. Studies in breast and lung cancer suggest that combined PET/CT measurements of glucose metabolism and blood flow provide correlates for tumour proliferation and angiogenesis, respectively. These combined measurements can be utilized to determine vascular-metabolic phenotypes, which vary with tumour type. Uncoupling of blood flow and metabolism suggests a poor prognosis for larger more advanced tumours, high-grade lesions and tumours responding poorly to treatment. Vascular-metabolic imaging also has the potential to subclassify tumour response to treatment. The additional biomarkers described can be readily incorporated in existing FDG-PET examinations thereby improving the ability of PET/CT to depict tumour biology, characterize potentially malignant lesions, and assess prognosis and therapeutic response.

Commentary: Lifestyle factors and colorectal cancer microsatellite instability—molecular pathological epidemiology science, based on unique tumour principle

Abstract: Colorectal cancer encompasses fundamentally heterogeneous multifactorial diseases,1–3 as do breast, lung and other common cancers. Each tumour is unique in terms of the tumour microenvironment, interactome and intra-tumour heterogeneity, as well as host genomic variation and lifestyle and environmental exposures. There is likely a subtle difference in the local microenvironment even in a single organ system4,5 or within a single tumour. This unique tumour concept is supported by technologies that have enabled reading whole genome, epigenome, transcriptome, etc. in human tumour specimens. Essentially, each tumour follows its own unique pathway of tumour evolution and progression,6 and we classify tumours according to similarities in molecular signatures accumulated during the carcinogenesis process.6 Accumulating evidence suggests that aetiological factors influence the carcinogenesis process differentially according to tumour pathway (hence, tumour classification).2,3 Therefore, just as different tumours respond variably to therapy, causation appears to differ by tumour subtype. However, traditional cancer epidemiology approaches (including many genome-wide association studies) have not generally taken tumour heterogeneity into consideration or analysis. Recently, molecular pathological epidemiology (MPE) has been established as a transdisciplinary field,1–3 which examines a relationship between exposures and molecular signatures in tumour, as well as interactive influences of the exposures and molecular features on cancer progression.7,8 MPE is philosophically based on the concept of the uniqueness and heterogeneity of neoplastic diseases. Through MPE research, we can refine risk estimates for specific subtypes, and gain pathogenic insights on how potential aetiological factors influence different carcinogenesis pathways.1–3 MPE may uncover causal associations in tumour subtypes, which had been masked when all tumours in an anatomical site were pooled together.2,3 In this issue of IJE, utilizing the MPE approach, Hughes et al.9 prospectively examined the relationship between anthropometric measurements and risk of colorectal cancer according to status of BRAF mutation and microsatellite instability (MSI). Notably, this study represents the first MPE study to conduct a pooled prospective analysis using geographically and operationally distinct cohort studies. One substantial challenge in MPE research is limited statistical power, because MPE research is essentially a subset analysis using tumour classification.3 The strategy of pooling multiple cohorts may potentially alleviate this issue. Hughes et al.9 successfully demonstrated that an increase in body mass index (BMI) was associated with increased risk of microsatellite stable (MSS) cancer but not of MSI-high cancer, although the risk difference was not statistically significant. These data are generally in agreement with the previous case–control studies.10–12 Energetics and inflammation have been implicated in colorectal carcinogenesis. Obesity was associated with CpG island methylator phenotype (CIMP)-low/negative colon cancer in a case–control study,13 although in a case–cohort study, body size and physical activity were associated with colorectal cancer risk but not differentially by CIMP status.14 Of note, in colorectal cancer, MSI-high is associated with CIMP-high, which is associated with BRAF mutation.15–18 Thus, these molecular correlations can confound the apparent relationship between an exposure and a tumour variable. This ‘tumour molecular confounding’ is not typical confounding in an epidemiological sense because the nature of the relationships among molecular markers is not always understood. Recently, a prospective study of women showed that obesity was associated with colorectal cancer risk differentially by fatty acid synthase (FASN) expression.19 FASN has been known to be physiologically regulated by energy metabolic status. FASN is implicated in carcinogenesis, and its expression is associated with MSI-high colorectal cancer, independent of CIMP status.20 The apparent relationship between obesity and MSS cancer might be due to the link between obesity and FASN-negative tumour.19 Therefore, the interrelationship between energetics and tumour molecular features seems complex and more investigations are needed in this area. Hughes et al.9 also showed that body height was associated with increased MSI-high (or BRAF-mutated) cancer risk to a significantly greater degree than MSS (or BRAF-wild-type) cancer risk. Body height may reflect exposure to energy metabolic status and hormonal milieu in the growth period. Interestingly, in the Netherlands Cohort Study, calorie restriction in early life might be associated with a lower risk of CIMP-high colorectal cancer.21 Although confirmation by independent data sets is necessary, these data suggest that energy metabolic status in early life to adolescence may influence carcinogenesis pathway that involves epigenetic instability, whereas later in life, energy metabolism is more relevant to MSS or FASN-negative tumour development. Although MPE appears to be a promising science,2,3 as a largely observational endeavour it encompasses all limitations of observational epidemiology. In addition, there are specific caveats, which have been discussed in detail elsewhere.3 We believe that MPE research should be conducted in a rigorous manner, so that findings can be generalized and appropriate public health measures can be taken based on new knowledge. To that end, we need to develop international guidelines for MPE, an extension of the STROBE (STrengthening the Reporting of OBservational Studies in Epidemiology) guidelines, which can be termed ‘STROBE-MPE’.22 For centuries, organ-based cancer classification has been useful. However, we are now geared to enter an era towards more personalized treatment in medicine. Epidemiologists should also regard each tumour as unique, and use molecular classification to better design epidemiology studies. Eventually, population cancer registries worldwide should record classification based on molecular pathogenesis and disease heterogeneity, which will accelerate the advancement of population health science. To advance the integrated interdisciplinary field of MPE, there is great need to educate epidemiologists in molecular pathology, as well as great need to educate pathologists in epidemiology and biostatistics.22 We believe that MPE can serve as a successful platform for such an interdisciplinary integration of diverse fields. In summary, the study by Hughes et al.9 underscores the importance of the MPE approach in our quest for cancer aetiologies as well as the potential of a strategy of pooling multiple studies to overcome challenges and gain generalizable knowledge. In addition, to increase statistical power of individual population-based MPE studies, cooperation of all hospitals and pathology laboratories in provision of medical information and biospecimens is crucial. We genuinely call for collaboration and cooperation for the advancement of population science and public health.

Comparison of methods to detect copy number alterations in cancer using simulated and real genotyping data

Abstract: Background The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable.

Flow cytometric techniques for detection of candidate cancer stem cell subpopulations in canine tumour models.

Abstract: The cancer stem cell (CSC) hypothesis proposes that tumour growth is maintained by a distinct subpopulation of 'CSC'. This study applied flow cytometric methods, reported to detect CSC in both primary and cultured cancer cells of other species, to identify candidate canine subpopulations. Cell lines representing diverse canine malignancies, and cells derived from spontaneous canine tumours, were evaluated for expression of stem cell-associated surface markers (CD34, CD44, CD117 and CD133) and functional properties [Hoecsht 33342 efflux, aldehyde dehydrogenase (ALDH) activity]. No discrete marker-defined subsets were identified within established cell lines; cells derived directly from spontaneous tumours demonstrated more heterogeneity, although this diminished upon in vitro culture. Functional assays produced variable results, suggesting context-dependency. Flow cytometric methods may be adopted to identify putative canine CSC. Whilst cell lines are valuable in assay development, primary cells may provide a more rewarding model for studying tumour heterogeneity in the context of CSC. However, it will be essential to fully characterize any candidate subpopulations to ensure that they meet CSC criteria.

Genetics: Personalized medicine and tumour heterogeneity

Abstract: A team of what Cancer Research UK have described as “some of the UK's most exciting young researchers” have performed a careful genetic analysis of tumours and shown that “no two samples from the same patient were genetically identical.” This finding has obvious implications for personalized medicine.

In silico modelling of tumour margin diffusion and infiltration: review of current status.

Abstract: As a result of advanced treatment techniques, requiring precise target definitions, a need for more accurate delineation of the Clinical Target Volume (CTV) has arisen. Mathematical modelling is found to be a powerful tool to provide fairly accurate predictions for the Microscopic Extension (ME) of a tumour to be incorporated in a CTV. In general terms, biomathematical models based on a sequence of observations or development of a hypothesis assume some links between biological mechanisms involved in cancer development and progression to provide quantitative or qualitative measures of tumour behaviour as well as tumour response to treatment. Generally, two approaches are taken: deterministic and stochastic modelling. In this paper, recent mathematical models, including deterministic and stochastic methods, are reviewed and critically compared. It is concluded that stochastic models are more promising to provide a realistic description of cancer tumour behaviour due to being intrinsically probabilistic as well as discrete, which enables incorporation of patient-specific biomedical data such as tumour heterogeneity and anatomical boundaries.

Subdivision of molecularly-classified groups by new gene signatures in breast cancer patients.

Abstract: Gene expression patterns as well as gene interactions are under investigation for their involvement in tumour heterogeneity. The molecular classification of breast cancer based on hormone receptor ...

Oestrogen-related tumour phenotype: positron emission tomography characterisation with 18F-FDG and 18F-FES

Abstract: This article outlines the role of 16α-[18F]fluoro-17β-oestradiol (18F-FES) positron emission tomography (PET) combined with 2-[18F]fluoro-2-deoxy-D-glucose (18F-FDG) in patients with oestrogen-related tumours for evaluating tumour phenotype. 18F-FES-PET combined with 18F-FDG is helpful in characterising the distinct phenotypic features of oestrogen-related tumours; that is, inter- and intrapatient tumour heterogeneity, which indicates its great potential as a determinant of individualised treatment and a prognostic predictor for patients with oestrogen-related tumours.

Proteomic analysis of pre- and post-sunitinib treated renal cancer tissue to assess tumor heterogeneity and differential protein expression.

Abstract: 388 Background: To investigate acquired resistance of clear cell renal cell cancer (ccRCC) patients to sunitinib and develop personalised treatment strategies, sequential tissue after a specific period of targeted therapy is required. This approach has proven successful with targeted therapy in chronic myeloid leukaemia; however, we are concerned that extensive tumour heterogeneity occurs in ccRCC. In this study we evaluated heterogeneity and differential protein expression in sunitinib treated and untreated ccRCC samples using high-throughput proteomics. Methods: Fresh frozen tissue was obtained from 27 sunitinib naive ccRCC specimens and 27 nephrectomy samples from patients treated with neoadjuvant sunitinib (18 weeks) as part of the SuMR trial. From each tumour frozen sections were performed and up to 5 protein lysates obtained from each morphologically differing region of each tumour as well as matched normal kidney. Reverse phase protein arrays (RPPA) were performed to assess the levels of multiple p...

What drives breast cancer heterogeneity: oncogenic events or cell of origin?

Abstract: Breast cancer is known to show considerable inter-tumoural heterogeneity. It is widely accepted that combinations of oncogenic events have a major role in determining tumour phenotype. However, accumulating evidence suggests that the identity of the cell that acquires the first oncogenic event, the so-called cell of origin, may define the molecular subtype of the resulting tumour. Recent work published in the Journal of Pathology by Natrajan and colleagues questions the origin of breast cancer heterogeneity. After studying BRCA1 tumours, they suggest that genomic alterations are not sufficient to determine tumour behaviour. These and other recent observations underscore the importance of defining what is causing tumour heterogeneity, so that appropriate therapy can be given. Copyright © 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Tumour heterogeneity: Darwin's finches.

Abstract: The extent of tumour heterogeneity has been explored in a paper recently published in the New England Journal of Medicine

Tumour heterogeneity: All mixed up

Abstract: Clinical trials of inhibitors against individual receptor tyrosine kinases (RTKs) in glioblastoma have not yielded promising results. By analysing DNA copy number data sets, Szerlip et al. determined that 36 of 583 glioblastoma cases had amplification of two or more RTKs in separate cell populations within a tumour. Fluorescence in situ hybridization analysis of epidermal growth factor receptor (EGFR) and platelet-derived growth factor receptor-α (PDGFRA), the most commonly amplified RTKs, showed distinct cells expressing each RTK. Furthermore, DNA sequencing revealed a common clonal origin of these cells. Cell lines derived from these tumours contained cells with either EGFR or PDGFRA amplification. Inhibition of both RTKs was required to block PI3K signalling in these cells, and this may be required to achieve therapeutic benefit in patients with co-amplified RTKs.