The NEXT-1 (Next generation pErsonalized tX with mulTi-omics and preclinical model) trial: prospective molecular screening trial of metastatic solid cancer patients,a feasibility analysis

We conducted a prospective genomic screening trial with high throughput sequencing and copy number variation (CNV) assay, and immunohistochemistry array in metastatic solid cancer patients. We used Ion AmpliSeq Cancer Hotspot Panel v2 and nCounter Copy Number Variation Assay (21 genes) to identify molecular targets for potential matched therapy. Metastatic solid tumor patients were prospectively consented for molecular profiling tests. The primary outcome for this trial was the feasibility of molecular tests and response rate (matched vs non-matched treatment). Between November 2013 and August 2014, a total of 428 metastatic solid tumor patients were enrolled on to this study. The mutational profiles were obtained for 407 (95.1%) patients. CNV 21-gene assays were successfully performed in 281 (65.7%) of 428 patients. Of the 407 patients with molecular profiling results, 342 (84.0%) patients had one or more aberrations detected. Of the 342 patients, 103 patients were matched to molecularly targeted agents in the context of clinical trials or clinical practice. The response rate was significantly higher in the genome-matched treated group for gastrointestinal/hepatobiliary/rare tumors (matched vs non-matched treatment, 42.6% vs 24.3%, P = .009) and lung cancer cohort (matched vs non-matched treatment, 61.2% vs 28.6% < P = .001) when compared with the non-matched group. In this trial, we demonstrate that genome-matched treatment based on molecular profiling result in better treatment outcome in terms of response rate.     

Molecular biology of myeloma

Multiple myeloma (MM) is a B-cell malignancy characterised by the accumulation of clonal plasma cells (PC) in the bone marrow (BM). The molecular bases for this incurable disease have been widely investigated in the last years, and the development of modern genomic technologies has contributed to the understanding of the pathogenesis of MM. The molecular mechanisms that explain the cellular origin of myeloma cells, the cytogenetic abnormalities and their clinical implications, and the biological information provided by gene expression profiling analysis are reviewed in this paper. In addition, a molecular classification of MM in seven groups based on the relationship between gene expression profiling, chromosomal translocations and prognostic outcome is also presented. And finally, the recent hypothesis of a potential unifying event in the pathogenesis of MM, supported by cyclin D deregulation in virtually all MM tumours, will be summarised.     

外周血基因表达谱在肿瘤诊断中的应用

外周血基因表达谱代表了外周血细胞所有基因表达的格局.通过比较肿瘤患者与健康对照者以及不同种类肿瘤患者之间外周血基因表达的不同,可以得出差异表达基因,从而进一步分析其特征性基因表达谱进行辅助诊断和治疗.目前,外周血基因表达谱已在头颈部肿瘤、胸部肿瘤、腹腔肿瘤、泌尿及男生殖系肿瘤、妇科肿瘤等多种肿瘤领域研究成果显著,给未来临床应用奠定了基础.     

The prognostic significance of cytogenetics and molecular profiling in multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy characterized by very complex cytogenetic and molecular genetic aberrations. In newly diagnosed symptomatic patients, the modal chromosome number is usually either hyperdiploid with multiple trisomies or hypodiploid with one of several types of immunoglobulin heavy chain (Ig) translocations. The chromosome ploidy status and Ig rearrangements are two genetic criteria that are used to help stratify patients into prognostic groups based on the findings of conventional cytogenetics and fluorescence in situ hybridization (FISH). In general, the hypodiploid group with t(4;14)(p16;q32) or t(14;16)(q32;q23) is considered a high-risk group, while the hyperdiploid patients with t(11;14)(q13;q32) are considered a better prognostic group. As the disease progresses, it becomes more proliferative and develops a number of secondary chromosome aberrations. These secondary aberrations commonly involve MYC rearrangements, del(13q), del(17p), and the deletion of 1p and/or amplification of 1q. Of the secondary aberrations, del(17p) is consistently associated with poor prognosis. All of these cytogenetic aberrations and many additional ones are now identified by means of high resolution molecular profiling. Gene expression profiling (GEP), array comparative genomic hybridization (aCGH), and single-nucleotide polymorphism (SNP) arrays have been able to identify novel genetic aberration patterns that have previously gone unrecognized. With the integration of data from these profiling techniques, new subclassifications of MM have been proposed which define distinct molecular genetic subgroups. In this review, the findings from conventional cytogenetics, interphase FISH, GEP, aCGH, and SNP profiles are described to provide the conceptual framework for defining the emerging molecular genetic subgroups with prognostic significance.     

Clinical application of molecular profiling in breast cancer

Breast cancer is the leading type of cancer and second leading cause of cancer death in women. Breast cancer mortality has declined over the past 10 years largely due to early detection by mammographic screening, but also in part due to the increasing use of adjuvant hormonal therapy and chemotherapy. Indications for adjuvant chemotherapy have now expanded to include women who are at low risk of recurrence, resulting in overtreatment of most women to benefit a few, particularly those with favorable clinical features. New techniques have been evaluated that identify specific molecular signatures that may more accurately predict prognosis than clinical features, and that may also identify individuals who are more likely to benefit from endocrine therapy and/or chemotherapy. This review will focus on the clinical applications of these novel techniques reported to date, and how this may lead to the incorporation of molecular diagnostics into clinical practice. Two prospective, multicenter, multinational Phase III trials evaluating tumor genomic profiling in breast cancer are currently in development, and will be initiated within the forthcoming year. The completion of these important studies will represent the first step toward integrating molecular profiling into treatment selection for adjuvant therapy in breast cancer.     

基因表达谱技术在多发性骨髓瘤分子分型中的应用

多发性骨髓瘤（multiple myeloma,MM）是一种具有高度异质性的恶性浆细胞疾病。在过去的几年里,随着新药的出现患者的生存已得到极大的改善,但在分子分型及预后评估方面仍面临挑战。以基因表达谱（gene expression profiling,GEP）技术为基础的转录组学研究在很大程度上有助于破译MM的复杂性,为MM的分子分型提供新的视角。基因表达谱芯片可以检测编码和非编码基因的表达、突变和新的转录组修饰,提供更多不同骨髓瘤亚群治疗和预后的新信息。目前,已在多项临床试验中发现基因表达谱可以作为独立的预后因素评估不同队列患者的预后。尽管目前临床上尚未将基因表达谱整合到骨髓瘤的诊断和治疗中,但多个研究中心已开展针对骨髓瘤的表达谱数据研究。通过对公共数据库表达谱数据进行聚类分析,建立临床预后模型,在疾病的动态演变中识别高风险和低风险患者,预测治疗敏感性,找寻新的治疗靶点,使得从转录组水平上制定个体化治疗成为可能。本文就基因表达谱技术在骨髓瘤分子分型中的应用展开综述。      

Molecular markers predicting radiotherapy response: report and recommendations from an International Atomic Energy Agency technical meeting

PURPOSE: There is increasing interest in radiogenomics and the characterization of molecular profiles that predict normal tissue and tumor radioresponse. A meeting in Amsterdam was organized by the International Atomic Energy Agency to discuss this topic on an international basis. METHODS AND MATERIALS: This report is not completely exhaustive, but highlights some of the ongoing studies and new initiatives being carried out worldwide in the banking of tumor and normal tissue samples underpinning the development of molecular marker profiles for predicting patient response to radiotherapy. It is generally considered that these profiles will more accurately define individual or group radiosensitivities compared with the nondefinitive findings from the previous era of cellular-based techniques. However, so far there are only a few robust reports of molecular markers predicting normal tissue or tumor response. RESULTS: Many centers in different countries have initiated tissue and tumor banks to store samples from clinical trials for future molecular profiling analysis, to identify profiles that predict for radiotherapy response. The European Society for Therapeutic Radiology and Oncology GENEtic pathways for the Prediction of the effects of Irradiation (GENEPI) project, to store, document, and analyze sample characteristics vs. response, is the most comprehensive in this regard. CONCLUSIONS: The next 5-10 years are likely to see the results of these and other correlative studies, and promising associations of profiles with response should be validated in larger definitive trials.     

Implementation of a Molecular Tumor Board: The Impact on Treatment Decisions for 35 Patients Evaluated at Dartmouth‐Hitchcock Medical Center

Background.

Although genetic profiling of tumors is a potentially powerful tool to predict drug sensitivity and resistance, its routine use has been limited because clinicians are often unfamiliar with interpretation and incorporation of the information into practice. We established a Molecular Tumor Board (MTB) to interpret individual patients’ tumor genetic profiles and provide treatment recommendations.

Patients and Methods.

DNA from tumor specimens was sequenced in a Clinical Laboratory Improvement Amendments-certified laboratory to identify coding mutations in a 50-gene panel (n = 34) or a 255-gene panel (n = 1). Cases were evaluated by a multidisciplinary MTB that included pathologists, oncologists, hematologists, basic scientists, and genetic counselors.

Results.

During the first year, 35 cases were evaluated by the MTB, with 32 presented for recommendations on targeted therapies, and 3 referred for potential germline mutations. In 56.3% of cases, MTB recommended treatment with a targeted agent based on evaluation of tumor genetic profile and treatment history. Four patients (12.5%) were subsequently treated with a MTB-recommended targeted therapy; 3 of the 4 patients remain on therapy, 2 of whom experienced clinical benefit lasting >10 months.

Conclusion.

For the majority of cases evaluated, the MTB was able to provide treatment recommendations based on targetable genetic alterations. The most common reasons that MTB-recommended therapy was not administered stemmed from patient preferences and genetic profiling at either very early or very late stages of disease; lack of drug access was rarely encountered. Increasing awareness of molecular profiling and targeted therapies by both clinicians and patients will improve acceptance and adherence to treatments that could significantly improve outcomes.

Implications for Practice:

Case evaluation by a multidisciplinary Molecular Tumor Board (MTB) is critical to benefit from individualized genetic data and maximize clinical impact. MTB recommendations shaped treatment options for the majority of cases evaluated. In the few patients treated with MTB-recommended therapy, disease outcomes were positive and support genetically informed treatment.     

基于乳腺原发癌基因表达谱的预后分子分型研究

目的比较乳腺原发癌随访3年有远处转移病例与无远处转移病例的原发癌基因表达谱差异,筛选转移预后预测标志基因群,并探讨其用于乳腺癌患者预后分子分型的临床意义。方法以随访3年5例有远处转移和5例无远处转移的乳腺癌患者作为分析病例,采用含21329个人功能基因的Oligo芯片筛选预后不同的乳腺原发癌组织差异表达基因;基于差异表达基因分别对10例分析病例和另外20例验证病例进行k-mean聚类分析;利用逐一剔除法去除对聚类没有贡献的基因,得到可以预测乳腺癌患者转移和预后的标志基因群,用于乳腺癌患者预后的分子分型。结果利用10例不同预后的分析病例筛选得到的差异表达基因可以将30例乳腺癌患者分为预后良好和预后不良两个组;随访3年有远处转移的病例全部聚类在预后不良组,占该组的70．0％（7／10）,而预后良好组中不含有远处转移的病例（0／20）,两组3年内发生远处转移率的差异有统计学意义（P=0．03）。由104个基因组成的预后预测基因群中,5个与细胞黏附运动相关的基因在预后不良组较预后良好组均表达上调,2个与机体免疫应答相关的基因均下调,11个与细胞生长代谢相关的基因上调,14个与细胞生长代谢相关的基因下调,15个与细胞信号传导相关的基因表达量显著改变。结论通过乳腺癌有远处转移病例与无远处转移病例原发癌基因表达谱的比较研究,筛选得到可以预测乳腺癌患者转移和预后的基因群,且可反映高转移能力的乳腺原发癌中肿瘤细胞运动能力增强、机体免疫识别缺陷、细胞增殖活跃和信号传导异常的生物学特征,并能对乳腺癌患者进行预后分子分型,有望用于临床指导个体化治疗方案的选择。     

Current status of prognostic profiling in breast cancer

Breast cancer is a clinically heterogeneous disease that can affect individuals with seemingly identical clinicopathologic parameters differently. This clinical heterogeneity is driven to a large extent by abnormal gene expression within tumors. Investigators now have the ability to identify the gene-expression fingerprint of an individual's tumor. This information may be used to rationally design therapeutic targets in the future, and also to predict the clinical course of an individual's disease, including response to a specific treatment. Genetic profiles of tumors are now being correlated with clinical outcome, and several prognostic and predictive indicators have emerged based on this research. There are at least four commercially available predictive or prognostic tests, and several more are looming on the horizon. The data gathered from these tests augment standard diagnostic and prognostic information obtained from traditional clinical pathological variables. The advent of gene-profiling technologies started to change the conduct of clinical trials. In the not too distant future, prospective tissue collection for molecular analysis may become routine in order to stratify patients for treatment arms and to optimize treatment strategies based on molecular features of the cancer. Coordinated efforts among oncologists, pathologists, surgeons, laboratory scientists, statisticians, and regulators will be essential in the quest to incorporate genetic profiling and molecular hypotheses into clinical trial planning and conduct.     

Age cutoff for Epstein-Barr virus-positive diffuse large B-cell lymphoma–is it necessary?

Epstein-Barr virus-positive diffuse large B-cell lymphoma of the elderly (EBV+ DLBCL-e) is a molecularly distinct variant of DLBCL, characterized by a monoclonal B-cell proliferation that occurs in patients >50 years of age without a history or clinicopathologic evidence of immunodeficiency. However, patients with EBV+ DLBCL younger than 50-years-old also exist in Western countries. We evaluated the clinicopathologic, immunophenotypic and genetic features in Cacausian patients with EBV+ DLBCL who are ≤50 years of age and compared this patient group to patients who are >50 years. In patients who are ≤50 years, less frequent expression of BCL6 and a trend of more frequent expression of CD30 and pSTAT3 were found in patients with EBV+ DLBCL. In patients who are >50 years, common expression of CD30, p50, pSTAT3 and less frequent expression of BCL6 were observed. Older patients also more commonly had a poor performance status (ECOG≥2). Comparing EBV+ DLBCL patients in ≤50 years versus >50 years, both groups had similar clinicopathologic, immunophenotypic and genetic features. Gene expression profiling, microRNA profiling and treatment outcome of the younger patients with EBV+ DLBCL was not distinctive from tumors in older patients. Based on our data, we suggest that the arbitrary age cutoff for EBV+ DLBCL is unnecessary and should be eliminated in the WHO lymphoma classification scheme.     

Clinical management of metastatic colorectal cancer in the era of precision medicine

Colorectal cancer (CRC) represents approximately 10% of all cancers and is the second most common cause of cancer deaths. Initial clinical presentation as metastatic CRC (mCRC) occurs in approximately 20% of patients. Moreover, up to 50% of patients with localized disease eventually develop metastases. Appropriate clinical management of these patients is still a challenging medical issue. Major efforts have been made to unveil the molecular landscape of mCRC. This has resulted in the identification of several druggable tumor molecular targets with the aim of developing personalized treatments for each patient. This review summarizes the improvements in the clinical management of patients with mCRC in the emerging era of precision medicine. In fact, molecular stratification, on which the current treatment algorithm for mCRC is based, although it does not completely represent the complexity of this disease, has been the first significant step toward clinically informative genetic profiling for implementing more effective therapeutic approaches. This has resulted in a clinically relevant increase in mCRC disease control and patient survival. The next steps in the clinical management of mCRC will be to integrate the comprehensive knowledge of tumor gene alterations, of tumor and microenvironment gene and protein expression profiling, of host immune competence as well as the application of the resulting dynamic changes to a precision medicine-based continuum of care for each patient. This approach could result in the identification of individual prognostic and predictive parameters, which could help the clinician in choosing the most appropriate therapeutic program(s) throughout the entire disease journey for each patient with mCRC. CA Cancer J Clin. 2022;72:000-000.     

High-throughput microRNA profiling of pediatric high-grade gliomas

Background

High-grade gliomas (HGGs) account for 15% of all pediatric brain tumors and are a leading cause of cancer-related mortality and morbidity. Pediatric HGGs (pHGGs) are histologically indistinguishable from their counterpart in adulthood. However, recent investigations indicate that differences occur at the molecular level, thus suggesting that the molecular path to gliomagenesis in childhood is distinct from that of adults. MicroRNAs (miRNAs) have been identified as key molecules in gene expression regulation, both in development and in cancer. miRNAs have been investigated in adult high-grade gliomas (aHGGs), but scant information is available for pHGGs.

Methods

We explored the differences in microRNAs between pHGG and aHGG, in both fresh-frozen and paraffin-embedded tissue, by high-throughput miRNA profiling. We also evaluated the biological effects of miR-17-92 cluster silencing on a pHGG cell line.

Results

Comparison of miRNA expression patterns in formalin versus frozen specimens resulted in high correlation between both types of samples. The analysis of miRNA profiling revealed a specific microRNA pattern in pHGG with an overexpression and a proliferative role of the miR-17-92 cluster. Moreover, we highlighted a possible quenching function of miR-17-92 cluster on its target gene PTEN, together with an activation of tumorigenic signaling such as sonic hedgehog in pHGG.

Conclusions

Our results suggest that microRNA profiling represents a tool to distinguishing pediatric from adult HGG and that miR-17-92 cluster sustains pHGG.     

Comprehensive Genomic Profiling of Advanced Penile Carcinoma Suggests a High Frequency of Clinically Relevant Genomic Alterations

Background.

Advanced penile squamous cell carcinoma (PSCC) is associated with poor survival due to the aggressiveness of the disease and lack of effective systemic therapies. Comprehensive genomic profiling (CGP) was performed to identify clinically relevant genomic alterations (CRGAs).

Materials and Methods.

DNA was extracted from 40 μm of formalin-fixed, paraffin-embedded sections in patients with advanced PSCC. CGP was performed on hybridization-captured, adaptor ligation-based libraries to a mean coverage depth of 692× for 3,769 exons of 236 cancer-related genes plus 47 introns from 19 genes frequently rearranged in cancer. CRGAs were defined as genomic alterations (GAs) linked to targeted therapies on the market or under evaluation in mechanism-driven clinical trials.

Results.

Twenty male patients with a median age of 60 years (range, 46–87 years) were assessed. Seventeen (85%) cases were stage IV and three cases (15%) were stage III. CGP revealed 109 GAs (5.45 per tumor), 44 of which were CRGAs (2.2 per tumor). At least one CRGA was detected in 19 (95%) cases, and the most common CRGAs were CDKN2A point mutations and homozygous deletion (40%), NOTCH1 point mutations and rearrangements (25%), PIK3CA point mutations and amplification (25%), EGFR amplification (20%), CCND1 amplification (20%), BRCA2 insertions/deletions (10%), RICTOR amplifications (10%), and FBXW7 point mutations (10%).

Conclusion.

CGP identified CRGAs in patients with advanced PSCC, including EGFR amplification and PIK3CA alterations, which can lead to the rational administration of targeted therapy and subsequent benefit for these patients.

Implications for Practice:

Few treatment options exist for patients with advanced penile squamous cell carcinoma (PSCC). Outcomes are dismal with platinum-based chemotherapy, with median survival estimated at 1 year or less across multiple series. Biological studies of patients with PSCC to date have principally focused on human papillomavirus status, but few studies have elucidated molecular drivers of the disease. To this end, comprehensive genomic profiling was performed in a cohort of 20 patients with advanced PSCC. Findings of frequent mutations in CDKN2A, NOTCH1, PIK3CA, and EGFR (all in excess of 20%) point to potential therapeutic avenues. Trials of targeted therapies directed toward these mutations should be explored.     

miRNA expression profiling divides follicular dendritic cell sarcomas into two groups,related to fibroblasts and myopericytomas or Castleman's disease

Follicular dendritic cell (FDC) sarcomas are rare mesenchymal tumours, which are fatal in 20% of the patients and usually occur in secondary lymphoid organs or extranodal localizations. Due to the rareness of these tumours, only few studies have been conducted on molecular level. In the present study, we performed microRNA (miRNA) profiling of 31 FDC sarcomas and identified two subgroups, one with high miRNA expression and the other group with low miRNA expression levels. The first group showed a strong similarity to fibroblasts and myopericytomas, whereas the second group was more closely related to FDCs from Castleman's disease. Both groups showed important differences compared with myeloid-derived dendritic cells, confirming mesenchymal origin of FDCs and their derived sarcomas. The two FDC sarcoma groups did not differ on morphological grounds, mitotic activity or BRAF mutation status. However, patients of group I presented a tendency to a shorter overall survival and more frequent podoplanin expression by immunohistochemistry. The importance of these newly recognized FDC sarcoma subgroups in terms of clinical behaviour and therapeutic implications should be assessed in a larger cohort in future studies.     

Invasive Mucinous Adenocarcinomas With Spatially Separate Lung Lesions: Analysis of Clonal Relationship by Comparative Molecular Profiling

IntroductionPulmonary invasive mucinous adenocarcinomas (IMAs) often present with spatially separate lung lesions. Clonal relationship between such lesions, particularly those involving contralateral lobes, is not well established. Here, we used comparative genomic profiling to address this question.MethodsPatients with genomic analysis performed on two IMAs located in different lung regions were identified. Molecular assays included DNA-based next-generation sequencing (NGS) for 410 to 468 genes (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets), RNA-based NGS for 62 genes (Memorial Sloan Kettering-Fusion), or non-NGS assays.ResultsComparative genomic profiling was performed on two separate IMAs in 24 patients, of whom 19 had contralateral lesions. Tumors from all but one patient shared matching driver alterations, including KRAS (n = 19), NRG1 (n = 2), ERBB2 (n = 1) or BRAF (n = 1). In addition, in patients with paired tumors profiled by NGS (n = 12), shared driver alterations were accompanied by up to 4 (average 2.6) other identical mutations, further supporting the clonal relationship between the tumors. Only in a single patient separate IMAs harbored entirely nonoverlapping mutation profiles, supporting clonally unrelated, distinct primary tumors. Notably, in a subset of patients (n = 3), molecular testing confirmed a clonal relationship between the original resected IMAs and subsequent contralateral IMA presenting after an extremely long latency (8.1–11.7 y).ConclusionsComparative molecular profiling supports that nearly all separate pulmonary IMA lesions represent intrapulmonary spread arising from a single tumor and documents a subset with a remarkably protracted course of intrapulmonary progression. This study reinforces the unique biology and clinical behavior of IMAs while further highlighting the value of genomic testing for clarifying the clonal relationship between multiple lung carcinomas.     

Fuzzy Neural Network Applied to Gene Expression Profiling for Predicting the Prognosis of Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the largest category of aggressive lymphomas. Less than 50% of patients can be cured by combination chemotherapy. Microarray technologies have recently shown that the response to chemotherapy reflects the molecular heterogeneity in DLBCL. On the basis of published microarray data, we attempted to develop a long-overdue method for the precise and simple prediction of survival of DLBCL patients. We developed a fuzzy neural network (FNN) model to analyze gene expression profiling data for DLBCL. From data on 5857 genes, this model identified four genes ( CD10, AA807551, AA805611 and IRF-4 ) that could be used to predict prognosis with 93% accuracy. FNNs are powerful tools for extracting significant biological markers affecting prognosis, and are applicable to various kinds of expression profiling data for any malignancy.     

Gene expression profiles of gliomas in formalin-fixed paraffin-embedded material

Background:

We have recently demonstrated that expression profiling is a more accurate and objective method to classify gliomas than histology. Similar to most expression profiling studies, our experiments were performed using fresh frozen (FF) glioma samples whereas most archival samples are fixed in formalin and embedded in paraffin (FFPE). Identification of the same, expression-based intrinsic subtypes in FFPE-stored samples would enable validation of the prognostic value of these subtypes on these archival samples. In this study, we have therefore determined whether the intrinsic subtypes identified using FF material can be reproduced in FFPE-stored samples.

Methods:

We have performed expression profiling on 55 paired FF-FFPE glioma samples using HU133 plus 2.0 arrays (FF) and Exon 1.0 ST arrays (FFPE). The median time in paraffin of the FFPE samples was 14.1 years (range 6.6–26.4 years).

Results:

In general, the correlation between FF and FFPE expression in a single sample was poor. We then selected the most variable probe sets per gene (n=17 583), and of these, the 5000 most variable probe sets on FFPE expression profiles. This unsupervised selection resulted in a better concordance (R²=0.54) between expression of FF and FFPE samples. Importantly, this probe set selection resulted in a correct assignment of 87% of FFPE samples into one of seven intrinsic subtypes identified using FF samples. Assignment to the same molecular cluster as the paired FF tissue was not correlated to time in paraffin.

Conclusion:

We are the first to examine a large cohort of paired FF and FFPE samples. We show that expression data from FFPE material can be used to assign samples to intrinsic molecular subtypes identified using FF material. This assignment allows the use of archival material, including material derived from large-randomised clinical trials, to determine the predictive and/or prognostic value of ‘intrinsic glioma subtypes'' on Exon arrays. This would enable clinicians to provide patients with an objective and accurate diagnosis and prognosis, and a personalised treatment strategy.