Analysis of heterogeneity in T2_2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma

$\textbf{Purpose}$ To develop an image analysis technique that distinguishes pseudoprogression from true progression by analyzing tumour heterogeneity in $T_2$-weighted images using topological descriptors of image heterogeneity called Minkowski functionals (MFs). $\textbf{Methods}$ Using a retrospective patient cohort ($n$ = 50), and blinded to treatment response outcome, unsupervised feature estimation was performed to investigate MFs for the presence of outliers, potential confounders, and sensitivity to treatment response. The progression and pseudoprogression groups were then unblinded and supervised feature selection was performed using MFs, size and signal intensity features. A support vector machine model was obtained and evaluated using a prospective test cohort. $\textbf{Results}$ The model gave a classification accuracy, using a combination of MFs and size features, of more than 85% in both retrospective and prospective datasets. A different feature selection method (Random Forest) and classifier (Lasso) gave the same results. Although not apparent to the reporting radiologist, the $T_2$-weighted hyperintensity phenotype of those patients with progression was heterogeneous, large and frond-like when compared to those with pseudoprogression. $\textbf{Conclusion}$ Analysis of heterogeneity, in $T_2$-weighted MR images, which are acquired routinely in the clinic, has the potential to detect an earlier treatment response allowing an early change in treatment strategy. Prospective validation of this technique in larger datasets is required.Funded by Medical Research Council/ Royal College of Radiologists (UK) Clinical Research Fellowship (G1000265); Cancer Research UK Clinical Research Fellowship; Addenbrookes Charitable Trust Award to TCB. Cancer Research UK Programme grant (C197/ A3514) to KMB

Somatically acquired hypomethylation of IGF2 in breast and colorectal cancer

The imprinted insulin-like growth factor 2 (IGF2) gene is expressed predominantly from the paternal allele. Loss of imprinting (LOI) associated with hypomethylation at the promoter proximal sequence (DMR0) of the IGF2 gene was proposed as a predisposing constitutive risk biomarker for colorectal cancer. We used pyrosequencing to assess whether IGF2 DMR0 methylation is either present constitutively prior to cancer or whether it is acquired tissue-specifically after the onset of cancer. DNA samples from tumour tissues and matched non-tumour tissues from 22 breast and 42 colorectal cancer patients as well as peripheral blood samples obtained from colorectal cancer patients [SEARCH (n=case 192, controls 96)], breast cancer patients [ABC (n=case 364, controls 96)] and the European Prospective Investigation of Cancer [EPIC-Norfolk (n=breast 228, colorectal 225, controls 895)] were analysed. The EPIC samples were collected 2–5 years prior to diagnosis of breast or colorectal cancer. IGF2 DMR0 methylation levels in tumours were lower than matched non-tumour tissue. Hypomethylation of DMR0 was detected in breast (33%) and colorectal (80%) tumour tissues with a higher frequency than LOI indicating that methylation levels are a better indicator of cancer than LOI. In the EPIC population, the prevalence of IGF2 DMR0 hypomethylation was 9.5% and this correlated with increased age not cancer risk. Thus, IGF2 DMR0 hypomethylation occurs as an acquired tissue-specific somatic event rather than a constitutive innate epimutation. These results indicate that IGF2 DMR0 hypomethylation has diagnostic potential for colon cancer rather than value as a surrogate biomarker for constitutive LOI

Choline kinase alpha as an androgen receptor chaperone and prostate cancer therapeutic target

Background: The androgen receptor (AR) is a major drug target in prostate cancer (PCa). We profiled the AR-regulated kinome to identify clinically relevant and druggable effectors of AR signaling. Methods: Using genome-wide approaches, we interrogated all AR regulated kinases. Among these, choline kinase alpha (CHKA) expression was evaluated in benign (n = 195), prostatic intraepithelial neoplasia (PIN) (n = 153) and prostate cancer (PCa) lesions (n = 359). We interrogated how CHKA regulates AR signaling using biochemical assays and investigated androgen regulation of CHKA expression in men with PCa, both untreated (n = 20) and treated with an androgen biosynthesis inhibitor degarelix (n = 27). We studied the effect of CHKA inhibition on the PCa transcriptome using RNA sequencing and tested the effect of CHKA inhibition on cell growth, clonogenic survival and invasion. Tumor xenografts (n = 6 per group) were generated in mice using genetically engineered prostate cancer cells with inducible CHKA knockdown. Data were analyzed with χ 2 tests, Cox regression analysis, and Kaplan-Meier methods. All statistical tests were two-sided. Results: CHKA expression was shown to be androgen regulated in cell lines, xenografts, and human tissue (log fold change from 6.75 to 6.59, P = .002) and was positively associated with tumor stage. CHKA binds directly to the ligand-binding domain (LBD) of AR, enhancing its stability. As such, CHKA is the first kinase identified as an AR chaperone. Inhibition of CHKA repressed the AR transcriptional program including pathways enriched for regulation of protein folding, decreased AR protein levels, and inhibited the growth of PCa cell lines, human PCa explants, and tumor xenografts. Conclusions: CHKA can act as an AR chaperone, providing, to our knowledge, the first evidence for kinases as molecular chaperones, making CHKA both a marker of tumor progression and a potential therapeutic target for PCa.Mohammad Asim ... Luke A. Selth ... Wayne D. Tilley et al

Immunohistochemical estimation of cell cycle phase in laryngeal neoplasia

We previously developed an immunohistochemical method for estimating cell cycle state and phase in tissue samples, including biopsies that are too small for flow cytometry. We have used our technique to examine whether primary abnormalities of the cell cycle exist in laryngeal neoplasia. Antibodies against the markers of cell cycle entry, minichromosome maintenance protein-2 (Mcm-2) and Ki67, and putative markers of cell cycle phase, cyclin D1 (G1-phase), cyclin A (S-phase), cyclin B1 (G2-phase) and phosphohistone H3 (Mitosis) were applied to paraffin-embedded sections of normal larynx (n=8), laryngeal dysplasia (n=10) and laryngeal squamous cell carcinoma (n=10). Cells expressing each marker were determined as a percentage of total cells, termed the labelling index (LI), and as a percentage of Mcm-2-positive cells, termed the labelling fraction (LF). The frequency of coexpression of each putative phase marker was investigated by confocal microscopy. There was a correlation between Mcm-2 and Ki67 LIs (ρ=0.93) but Mcm-2 LIs were consistently higher. All cells expressing a phase marker coexpressed Mcm-2, whereas Ki67 was not expressed in a proportion of these cells. The putative phase markers showed little coexpression. Labelling index values increased on progression from normal larynx through laryngeal dysplasia to squamous cell carcinoma for Mcm-2 (P=0.001), Ki67 (P=0.0002), cyclin D1 (P=0.015), cyclin A (P=0.0001) and cyclin B1 (P=0.0004). There was no evidence of an increase in the LF for any phase marker. Immunohistochemistry can be used to estimate cell cycle state and phase in laryngeal biopsies. Our data argues against primary cell cycle phase abnormalities in laryngeal neoplasia

Bcl-2 and β1-integrin predict survival in a tissue microarray of small cell lung cancer.

INTRODUCTION: Survival in small cell lung cancer (SCLC) is limited by the development of chemoresistance. Factors associated with chemoresistance in vitro have been difficult to validate in vivo. Both Bcl-2 and β(1)-integrin have been identified as in vitro chemoresistance factors in SCLC but their importance in patients remains uncertain. Tissue microarrays (TMAs) are useful to validate biomarkers but no large TMA exists for SCLC. We designed an SCLC TMA to study potential biomarkers of prognosis and then used it to clarify the role of both Bcl-2 and β(1)-integrin in SCLC. METHODS: A TMA was constructed consisting of 184 cases of SCLC and stained for expression of Bcl-2 and β(1)-integrin. The slides were scored and the role of the proteins in survival was determined using Cox regression analysis. A meta-analysis of the role of Bcl-2 expression in SCLC prognosis was performed based on published results. RESULTS: Both proteins were expressed at high levels in the SCLC cases. For Bcl-2 (n=140), the hazard ratio for death if the staining was weak in intensity was 0.55 (0.33-0.94, P=0.03) and for β(1)-integrin (n=151) was 0.60 (0.39-0.92, P=0.02). The meta-analysis showed an overall hazard ratio for low expression of Bcl-2 of 0.91(0.74-1.09). CONCLUSIONS: Both Bcl-2 and β(1)-integrin are independent prognostic factors in SCLC in this cohort although further validation is required to confirm their importance. A TMA of SCLC cases is feasible but challenging and an important tool for biomarker validation

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01

Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).Background : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Publisher PDFPeer reviewe

Malignant germ cell tumours of childhood: new associations of genomic imbalance

Malignant germ cell tumours (MGCTs) of childhood are a rare group of neoplasms that comprise many histological subtypes and arise at numerous different sites. Genomic imbalances have been described in these tumours but, largely because of the paucity of cases reported in the literature, it is unclear how they relate to abnormalities in adult MGCTs and impact on potential systems for classifying GCTs. We have used metaphase-based comparative genomic hybridisation to analyse the largest series of paediatric MGCTs reported to date, representing 34 primary tumours (22 yolk sac tumours (YSTs), 11 germinomatous tumours and one metastatic embryonal carcinoma) occurring in children from birth to age 16, including 17 ovarian MGCTs. The large dataset enabled us to undertake statistical analysis, with the aim of identifying associations worthy of further investigation between patterns of genomic imbalance and clinicopathological parameters. The YSTs showed an increased frequency of 1p- (P=0.003), 3p+ (P=0.02), 4q− (P=0.07) and 6q− (P=0.004) compared to germinomatous tumours. Gain of 12p, which is invariably seen in adult MGCTs, was present in 53% of primary MGCTs of children aged 5–16 and was also observed in four of 14 YSTs affecting children less than 5. Two of these cases (14% of MGCTs in children less than 5) showed gain of the 12p11 locus considered to be particularly relevant in adult MGCTs. Gain of 12p showed a significant association with gain of 12q. Conversely, MGCTs without 12p gain displayed a significantly increased frequency of loss on 16p (P=0.04), suggesting that this imbalance may contribute to tumour development in such cases. This data provides new insight into the biology of this under-investigated tumour group and will direct future studies on the significance of specific genetic abnormalities

Choline Kinase Alpha as an Androgen Receptor Chaperone and Prostate Cancer Therapeutic Target.

BACKGROUND: The androgen receptor (AR) is a major drug target in prostate cancer (PCa). We profiled the AR-regulated kinome to identify clinically relevant and druggable effectors of AR signaling. METHODS: Using genome-wide approaches, we interrogated all AR regulated kinases. Among these, choline kinase alpha (CHKA) expression was evaluated in benign (n = 195), prostatic intraepithelial neoplasia (PIN) (n = 153) and prostate cancer (PCa) lesions (n = 359). We interrogated how CHKA regulates AR signaling using biochemical assays and investigated androgen regulation of CHKA expression in men with PCa, both untreated (n = 20) and treated with an androgen biosynthesis inhibitor degarelix (n = 27). We studied the effect of CHKA inhibition on the PCa transcriptome using RNA sequencing and tested the effect of CHKA inhibition on cell growth, clonogenic survival and invasion. Tumor xenografts (n = 6 per group) were generated in mice using genetically engineered prostate cancer cells with inducible CHKA knockdown. Data were analyzed with χ(2) tests, Cox regression analysis, and Kaplan-Meier methods. All statistical tests were two-sided. RESULTS: CHKA expression was shown to be androgen regulated in cell lines, xenografts, and human tissue (log fold change from 6.75 to 6.59, P = .002) and was positively associated with tumor stage. CHKA binds directly to the ligand-binding domain (LBD) of AR, enhancing its stability. As such, CHKA is the first kinase identified as an AR chaperone. Inhibition of CHKA repressed the AR transcriptional program including pathways enriched for regulation of protein folding, decreased AR protein levels, and inhibited the growth of PCa cell lines, human PCa explants, and tumor xenografts. CONCLUSIONS: CHKA can act as an AR chaperone, providing, to our knowledge, the first evidence for kinases as molecular chaperones, making CHKA both a marker of tumor progression and a potential therapeutic target for PCa.This work was supported by a Cancer Research UK program grant (to DEN) and also by the US Department of Defense (Prostate Cancer Research Program Transformative Impact Award, grant ID W81XWH-13-2-0093; WDT and SMD), PCFA/Cancer Australia/Movember (grant IDs 1012337 and 1043482; WDT and LAS), Cancer Australia (grant ID 1043497; WDT and JC) and The Ray and Shirl Norman Cancer Research Trust (WDT and LAS). The Dame Roma Mitchell Cancer Research Laboratories were supported by an establishment grant from the PCFA (ID 2011/0452). FO was supported by a PhD project grant from Prostate Cancer UK (S10-10). LAS is supported by a Young Investigator Award from the Prostate Cancer Foundation (the Foundation 14 award)