A Molecular Predictor Reassesses Classification of Human Grade II/III Gliomas

Genomic characterization of IDH-mutant astrocytoma progression to grade 4 in the treatment setting

As the progression of low-grade diffuse astrocytomas into grade 4 tumors significantly impacts patient prognosis, a better understanding of this process is of paramount importance for improved patient care. In this project, we analyzed matched IDH-mutant astrocytomas before and after progression to grade 4 from six patients (discovery cohort) with genome-wide sequencing, 21 additional patients with targeted sequencing, and 33 patients from Glioma Longitudinal AnalySiS cohort for validation. The Cancer Genome Atlas data from 595 diffuse gliomas provided supportive information. All patients in our discovery cohort received radiation, all but one underwent chemotherapy, and no patient received temozolomide (TMZ) before progression to grade 4 disease. One case in the discovery cohort exhibited a hypermutation signature associated with the inactivation of the MSH2 and DNMT3A genes. In other patients, the number of chromosomal rearrangements and deletions increased in grade 4 tumors. The cell cycle checkpoint gene CDKN2A, or less frequently RB1, was most commonly inactivated after receiving both chemo- and radiotherapy when compared to other treatment groups. Concomitant activating PDGFRA/MET alterations were detected in tumors that acquired a homozygous CDKN2A deletion. NRG3 gene was significantly downregulated and recurrently altered in progressed tumors. Its decreased expression was associated with poorer overall survival in both univariate and multivariate analysis. We also detected progression-related alterations in RAD51B and other DNA repair pathway genes associated with the promotion of error-prone DNA repair, potentially facilitating tumor progression. In our retrospective analysis of patient treatment and survival timelines (n = 75), the combination of postoperative radiation and chemotherapy (mainly TMZ) outperformed radiation, especially in the grade 3 tumor cohort, in which it was typically given after primary surgery. Our results provide further insight into the contribution of treatment and genetic alterations in cell cycle, growth factor signaling, and DNA repair-related genes to tumor evolution and progression.

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass

OBJECTIVE

To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood.

METHODS

This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared.

RESULTS

A total of 183 evaluable patients were enrolled (average age 56 years, range 19-91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0-98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2-65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9-93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3-97.8%) for stage I-II and 98.9% (95% CI 96.7-100%) for stage III-IV patients with epithelial ovarian cancer.

CONCLUSION

Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT02781272.

FUNDING SOURCE

This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).

Multivariate Analysis of RNA Chemistry Marks Uncovers Epitranscriptomics-Based Biomarker Signature for Adult Diffuse Glioma Diagnostics

One of the main challenges in cancer management relates to the discovery of reliable biomarkers, which could guide decision-making and predict treatment outcome. In particular, the rise and democratization of high-throughput molecular profiling technologies bolstered the discovery of “biomarker signatures” that could maximize the prediction performance. Such an approach was largely employed from diverse OMICs data (i.e., genomics, transcriptomics, proteomics, metabolomics) but not from epitranscriptomics, which encompasses more than 100 biochemical modifications driving the post-transcriptional fate of RNA: stability, splicing, storage, and translation. We and others have studied chemical marks in isolation and associated them with cancer evolution, adaptation, as well as the response to conventional therapy. In this study, we have designed a unique pipeline combining multiplex analysis of the epitranscriptomic landscape by high-performance liquid chromatography coupled to tandem mass spectrometry with statistical multivariate analysis and machine learning approaches in order to identify biomarker signatures that could guide precision medicine and improve disease diagnosis. We applied this approach to analyze a cohort of adult diffuse glioma patients and demonstrate the existence of an “epitranscriptomics-based signature” that permits glioma grades to be discriminated and predicted with unmet accuracy. This study demonstrates that epitranscriptomics (co)evolves along cancer progression and opens new prospects in the field of omics molecular profiling and personalized medicine.

Ruta graveolens L. induces death of glioblastoma cells and neural progenitors, but not of neurons, via ERK 1/2 and AKT activation

Glioblastoma multiforme is a highly aggressive brain tumor whose prognosis is very poor. Due to early invasion of brain parenchyma, its complete surgical removal is nearly impossible, and even after aggressive combined treatment (association of surgery and chemo- and radio-therapy) five-year survival is only about 10%. Natural products are sources of novel compounds endowed with therapeutic properties in many human diseases, including cancer. Here, we report that the water extract of Ruta graveolens L., commonly known as rue, induces death in different glioblastoma cell lines (U87MG, C6 and U138) widely used to test novel drugs in preclinical studies. Ruta graveolens’ effect was mediated by ERK1/2 and AKT activation, and the inhibition of these pathways, via PD98058 and wortmannin, reverted its antiproliferative activity. Rue extract also affects survival of neural precursor cells (A1) obtained from embryonic mouse CNS. As in the case of glioma cells, rue stimulates the activation of ERK1/2 and AKT in A1 cells, whereas their blockade by pharmacological inhibitors prevents cell death. Interestingly, upon induction of differentiation and cell cycle exit, A1 cells become resistant to rue’s noxious effects but not to those of temozolomide and cisplatin, two alkylating agents widely used in glioblastoma therapy. Finally, rutin, a major component of the Ruta graveolens water extract, failed to cause cell death, suggesting that rutin by itself is not responsible for the observed effects. In conclusion, we report that rue extracts induce glioma cell death, discriminating between proliferating/undifferentiated and non-proliferating/differentiated neurons. Thus, it can be a promising tool to isolate novel drugs and also to discover targets for therapeutic intervention.