31 research outputs found

    A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility

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    <p>Abstract</p> <p>Background</p> <p>Microarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.</p> <p>Methods</p> <p>In this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.</p> <p>Results</p> <p>Supervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47–0.73).</p> <p>Conclusion</p> <p>The developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.</p

    Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease

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    Background: Patients with Estrogen Receptor α-positive (ER+) Inflammatory Breast Cancer (IBC) are less responsive to endocrine therapy compared with ER+ non-IBC (nIBC) patients. The study of ER+ IBC samples might reveal biomarkers for endocrine resistant breast cancer. Materials & methods: Gene expression profiles of ER+ samples from 201 patients were explored for genes that discriminated between IBC and nIBC. Classifier genes were applied onto clinically annotated expression data from 947 patients with ER+ breast cancer and validated with RT-qPCR for 231 patients treated with first-line tamoxifen. Relationships with metastasis-free survival (MFS) and progression-free survival (PFS) following adjuvant and first-line endocrine treatment, respectively, were investigated using Cox regression analysis. Results: A metagene of six genes including the genes encoding for 4-aminobutyrate aminotransferase (ABAT) and Stanniocalcin-2 (STC2) were identified to distinguish 22 ER+ IBC from 43 ER+ nIBC patients and remained discriminatory in an independent series of 136 patients. The metagene and two genes were not prognostic in 517 (neo)adjuvant untreated lymph node-negative ER+ nIBC breast cancer patients. Only ABAT was related to outcome in 250 patients treated with adjuvant tamoxifen. Three independent series of in total 411 patients with advanced disease showed increased metagene scores and decreased expression of ABAT and STC2 to be correlated with poor first-line endocrine therapy outcome. The biomarkers remained predictive for first-line tamoxifen treatment outcome in multivariate analysis including traditional factors or published signatures. In an exploratory analysis, ABAT and STC2 protein expression levels had no relation with PFS after first-line tamoxifen. Conclusions: This study utilized ER+ IBC to identify a metagene including ABAT and STC2 as predictive biomarkers for endocrine therapy resistance

    Patients with Rare Cancers in the Drug Rediscovery Protocol (DRUP) Benefit from Genomics-Guided Treatment

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    Purpose: Patients with rare cancers (incidence less than 6 cases per 100,000 persons per year) commonly have less treatment opportunities and are understudied at the level of genomic targets. We hypothesized that patients with rare cancer benefit from approved anticancer drugs outside their label similar to common cancers. Experimental Design: In the Drug Rediscovery Protocol (DRUP), patients with therapy-refractory metastatic cancers harboring an actionable molecular profile are matched to FDA/European Medicines Agency–approved targeted therapy or immunotherapy. Patients are enrolled in parallel cohorts based on the histologic tumor type, molecular profile and study drug. Primary endpoint is clinical benefit (complete response, partial response, stable disease ≥ 16 weeks). Results: Of 1,145 submitted cases, 500 patients, including 164 patients with rare cancers, started one of the 25 available drugs and were evaluable for treatment outcome. The overall clinical benefit rate was 33% in both the rare cancer and nonrare cancer subgroup. Inactivating alterations of CDKN2A and activating BRAF aberrations were overrepresented in patients with rare cancer compared with nonrare cancers, resulting in more matches to CDK4/6 inhibitors (14% vs. 4%; P ≤ 0.001) or BRAF inhibitors (9% vs. 1%; P ≤ 0.001). Patients with rare cancer treated with small-molecule inhibitors targeting BRAF experienced higher rates of clinical benefit (75%) than the nonrare cancer subgroup. Conclusions: Comprehensive molecular testing in patients with rare cancers may identify treatment opportunities and clinical benefit similar to patients with common cancers. Our findings highlight the importance of access to broad molecular diagnostics to ensure equal treatment opportunities for all patients with cancer

    Pan-cancer whole-genome analyses of metastatic solid tumours

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    Contains fulltext : 215492.pdf (publisher's version ) (Open Access)Metastatic cancer is a major cause of death and is associated with poor treatment efficacy. A better understanding of the characteristics of late-stage cancer is required to help adapt personalized treatments, reduce overtreatment and improve outcomes. Here we describe the largest, to our knowledge, pan-cancer study of metastatic solid tumour genomes, including whole-genome sequencing data for 2,520 pairs of tumour and normal tissue, analysed at median depths of 106x and 38x, respectively, and surveying more than 70 million somatic variants. The characteristic mutations of metastatic lesions varied widely, with mutations that reflect those of the primary tumour types, and with high rates of whole-genome duplication events (56%). Individual metastatic lesions were relatively homogeneous, with the vast majority (96%) of driver mutations being clonal and up to 80% of tumour-suppressor genes being inactivated bi-allelically by different mutational mechanisms. Although metastatic tumour genomes showed similar mutational landscape and driver genes to primary tumours, we find characteristics that could contribute to responsiveness to therapy or resistance in individual patients. We implement an approach for the review of clinically relevant associations and their potential for actionability. For 62% of patients, we identify genetic variants that may be used to stratify patients towards therapies that either have been approved or are in clinical trials. This demonstrates the importance of comprehensive genomic tumour profiling for precision medicine in cancer

    DNAAF1 links heart laterality with the AAA+ ATPase RUVBL1 and ciliary intraflagellar transport

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    DNAAF1 (LRRC50) is a cytoplasmic protein required for dynein heavy chain assembly and cilia motility, and DNAAF1 mutations cause primary ciliary dyskinesia (PCD; MIM 613193). We describe four families with DNAAF1 mutations and complex congenital heart disease (CHD). In three families, all affected individuals have typical PCD phenotypes. However, an additional family demonstrates isolated CHD (heterotaxy) in two affected siblings, but no clinical evidence of PCD. We identified a homozygous DNAAF1 missense mutation, p.Leu191Phe, as causative for heterotaxy in this family. Genetic complementation in dnaaf1-null zebrafish embryos demonstrated the rescue of normal heart looping with wild-type human DNAAF1, but not the p.Leu191Phe variant, supporting the conserved pathogenicity of this DNAAF1 missense mutation. This observation points to a phenotypic continuum between CHD and PCD, providing new insights into the pathogenesis of isolated CHD. In further investigations of the function of DNAAF1 in dynein arm assembly, we identified interactions with members of a putative dynein arm assembly complex. These include the ciliary intraflagellar transport protein IFT88 and the AAA+ (ATPases Associated with various cellular Activities) family proteins RUVBL1 (Pontin) and RUVBL2 (Reptin). Co-localization studies support these findings, with the loss of RUVBL1 perturbing the co-localization of DNAAF1 with IFT88. We show that RUVBL1 orthologues have an asymmetric left-sided distribution at both the mouse embryonic node and the Kupffer’s vesicle in zebrafish embryos, with the latter asymmetry dependent on DNAAF1. These results suggest that DNAAF1-RUVBL1 biochemical and genetic interactions have a novel functional role in symmetry breaking and cardiac development

    Integration of Gene Dosage and Gene Expression in Non-Small Cell Lung Cancer, Identification of HSP90 as Potential Target

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    BACKGROUND: Lung cancer causes approximately 1.2 million deaths per year worldwide, and non-small cell lung cancer (NSCLC) represents 85% of all lung cancers. Understanding the molecular events in non-small cell lung cancer (NSCLC) is essential to improve early diagnosis and treatment for this disease. METHODOLOGY AND PRINCIPAL FINDINGS: In an attempt to identify novel NSCLC related genes, we performed a genome-wide screening of chromosomal copy number changes affecting gene expression using microarray based comparative genomic hybridization and gene expression arrays on 32 radically resected tumor samples from stage I and II NSCLC patients. An integrative analysis tool was applied to determine whether chromosomal copy number affects gene expression. We identified a deletion on 14q32.2-33 as a common alteration in NSCLC (44%), which significantly influenced gene expression for HSP90, residing on 14q32. This deletion was correlated with better overall survival (P = 0.008), survival was also longer in patients whose tumors had low expression levels of HSP90. We extended the analysis to three independent validation sets of NSCLC patients, and confirmed low HSP90 expression to be related with longer overall survival (P = 0.003, P = 0.07 and P = 0.04). Furthermore, in vitro treatment with an HSP90 inhibitor had potent antiproliferative activity in NSCLC cell lines. CONCLUSIONS: We suggest that targeting HSP90 will have clinical impact for NSCLC patients

    Missense mutations in the WD40 domain of AHI1 cause non-syndromic retinitis pigmentosa

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    Background: Recent findings suggesting that Abelson helper integration site 1 (AHI1) is involved in non-syndromic retinal disease have been debated, as the functional significance of identified missense variants was uncertain. We assessed whether AHI1 variants cause non-syndromic retinitis pigmentosa (RP). Methods: Exome sequencing was performed in three probands with RP. The effects of the identified missense variants in AHI1 were predicted by three-dimensional structure homology modelling. Ciliary parameters were evaluated in patient's fibroblasts, and recombinant mutant proteins were expressed in ciliated retinal pigmented epithelium cells. Results: In the three patients with RP, three sets of compound heterozygous variants were detected in AHI1 (c.2174G>A; p.Trp725* and c.2258A>T; p.Asp753Val, c.660delC; p.Ser221Glnfs*10 and c.2090C>T; p.Pro697Leu, c.2087A>G; p.His696Arg and c.2429C>T; p.Pro810Leu). All four missense variants were present in the conserved WD40 domain of Jouberin, the ciliary protein encoded by AHI1, with variable predicted implications for the domain structure. No significant changes in the percentage of ciliated cells, nor in cilium length or intraflagellar transport were detected. However, expression of mutant recombinant Jouberin in ciliated cells showed a significantly decreased enrichment at the ciliary base. Conclusions: This report confirms that mutations in AHI1 can underlie autosomal recessive RP. Moreover, it structurally and functionally validates the effect of the RP-associated AHI1 variants on protein function, thus proposing a new genotype-phenotype correlation for AHI1 mutation associated retinal ciliopathies

    The Consensus Molecular Subtypes of Colorectal Cancer

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    Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use -- https://www.nature.com/authors/policies/license.html#termsColorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC - with clear biological interpretability - and the basis for future clinical stratification and subtype-based targeted interventions

    Personalised selection of experimental treatment in patients with advanced solid cancer is feasible using whole-genome sequencing

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    Background: Biomarker-guided therapy in an experimental setting has been suggested to improve patient outcomes. However, trial-specific pre-screening tests are time and tissue consuming and complicate the personalised treatment of patients eligible for early-phase clinical trials. In this study the feasibility of whole-genome sequencing (WGS) as a one-test-for-all for guided inclusion in early-phase trials was investigated. Methods: Phase I Molecular Tumor Board (MTB) at the Erasmus MC Cancer Institute reviewed patients with advanced cancer without standard-of-care treatment (SOC) options for a ‘fresh-frozen’ (FF) tumour biopsy for WGS based on clinical-pathological features. Clinical grade WGS was performed by Hartwig Medical Foundation. MTB matched the patient with a trial, if available. Results: From September 2019–March 2021, 31 patients with highly diverse tumour types underwent a tumour biopsy for WGS. The median turnaround time (TAT) was 15 days [10–42 days]. At least one actionable event was found in 84% of the patients (26/31). One-third of the patients (11/31) received matched experimental treatment. Conclusions: WGS on fresh FF biopsies is a feasible tool for the selection of personalised experimental therapy in patients with advanced cancer without SOC options. WGS is now possible in an acceptable TAT and thus could fulfil the role of a universal genomic pre-screening test

    Early Cost Effectiveness of Whole-Genome Sequencing as a Clinical Diagnostic Test for Patients with Inoperable Stage IIIB,C/IV Non-squamous Non-small-Cell Lung Cancer

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    Background Advanced non-small-cell lung cancer (NSCLC) harbours many genetic aberrations that can be targeted with systemic treatments. Whole-genome sequencing (WGS) can simultaneously detect these (and possibly new) molecular targets. However, the exact added clinical value of WGS is unknown. Objective The objective of this study was to determine the early cost effectiveness of using WGS in diagnostic strategies compared with currently used molecular diagnostics for patients with inoperable stage IIIB,C/IV non-squamous NSCLC from a Dutch healthcare perspective. Methods A decision tree represented the diagnostic pathway, and a cohort state transition model represented disease progression. Three diagnostic strategies were modelled: standard of care (SoC) alone, WGS as a diagnostic test, and SoC followed by WGS. Treatment effectiveness was based on a systematic review. Probabilistic cost-effectiveness analyses were performed, and threshold analyses (using euro80,000 per quality-adjusted life-year [QALY]) was used to explore the early cost effectiveness of WGS. Results WGS as a diagnostic test resulted in more QALYs (0.002) and costs (euro1534 [incremental net monetary benefit -euro1349]), and SoC followed by WGS resulted in fewer QALYs (-0.002) and more costs (euro1059 [-euro1194]) compared with SoC alone. WGS as a diagnostic test was only cost effective if it was priced at euro2000 per patient and identified 2.7% more actionable patients than SoC alone. Treating these additional identified patients with new treatments costing >euro4069 per month decreased the probability of cost effectiveness. Conclusions Our analysis suggests that providing WGS as a diagnostic test is cost effective compared with SoC followed by WGS and SoC alone if costs for WGS decrease and additional patients with actionable targets are identified. This cost-effectiveness model can be used to incorporate new findings iteratively and to support ongoing decision making regarding the use of WGS in this rapidly evolving field
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