Lihong Long

A prognostic gene expression signature in infratentorial ependymoma

Patients with ependymoma exhibit a wide range of clinical outcomes that are currently unexplained by clinical or histological factors. Little is known regarding molecular biomarkers that could predict clinical behavior. Since recent data suggest that these tumors display biological characteristics according to their location (cerebral vs. infratentorial vs. spinal cord), rather than explore a broad spectrum of ependymoma, we focused on molecular alterations in ependymomas arising in the infratentorial compartment. Unsupervised clustering of available gene expression microarray data revealed two major subgroups of infratentorial ependymoma. Group 1 tumors over expressed genes that were associated with mesenchyme, Group 2 tumors showed no distinct gene ontologies. To assess the prognostic significance of these gene expression subgroups, real-time reverse transcriptase polymerase chain reaction assays were performed on genes defining the subgroups in a training set. This resulted in a 10-gene prognostic signature. Multivariate analysis showed that the 10-gene signature was an independent predictor of recurrence-free survival after adjusting for clinical factors. Evaluation of an external dataset describing subgroups of infratentorial ependymomas showed concordance of subgroup definition, including validation of the mesenchymal subclass. Importantly, the 10-gene signature was validated as a predictor of recurrence-free survival in this dataset. Taken together, the results indicate a link between clinical outcome and biologically identified subsets of infratentorial ependymoma and offer the potential for prognostic testing to estimate clinical aggressiveness in these tumors.

Randomized, Double-Blind, Phase II Study of Temozolomide in Combination With Either Veliparib or Placebo in Patients With Relapsed-Sensitive or Refractory Small-Cell Lung Cancer

Purpose Both temozolomide (TMZ) and poly (ADP-ribose) polymerase (PARP) inhibitors are active in small-cell lung cancer (SCLC). This phase II, randomized, double-blind study evaluated whether addition of the PARP inhibitor veliparib to TMZ improves 4-month progression-free survival (PFS). Patients and Methods A total of 104 patients with recurrent SCLC were randomly assigned 1:1 to oral veliparib or placebo 40 mg twice daily, days 1 to 7, and oral TMZ 150 to 200 mg/m2/day, days 1 to 5, of a 28-day cycle until disease progression, unacceptable toxicity, or withdrawal of consent. Response was determined by imaging at weeks 4 and 8, and every 8 weeks thereafter. Improvement in PFS at 4 months was the primary end point. Secondary objectives included overall response rate (ORR), overall survival (OS), and safety and tolerability of veliparib with TMZ. Exploratory objectives included PARP-1 and SLFN11 immunohistochemical expression, MGMT promoter methylation, and circulating tumor cell quantification. Results No significant difference in 4-month PFS was noted between TMZ/veliparib (36%) and TMZ/placebo (27%; P = .19); median OS was also not improved significantly with TMZ/veliparib (8.2 months; 95% CI, 6.4 to 12.2 months; v 7.0 months; 95% CI, 5.3 to 9.5 months; P = .50). However, ORR was significantly higher in patients receiving TMZ/veliparib compared with TMZ/placebo (39% v 14%; P = .016). Grade 3/4 thrombocytopenia and neutropenia more commonly occurred with TMZ/veliparib: 50% versus 9% and 31% versus 7%, respectively. Significantly prolonged PFS (5.7 v 3.6 months; P = .009) and OS (12.2 v 7.5 months; P = .014) were observed in patients with SLFN11-positive tumors treated with TMZ/veliparib. Conclusion Four-month PFS and median OS did not differ between the two arms, whereas a significant improvement in ORR was observed with TMZ/veliparib. SLFN11 expression was associated with improved PFS and OS in patients receiving TMZ/veliparib, suggesting a promising biomarker of PARP-inhibitor sensitivity in SCLC.

A relative increase in circulating platelets following chemoradiation predicts for poor survival of patients with glioblastoma

Background Thrombocytosis is triggered by and promotes tumor growth. The relationship between the change in circulating platelets after chemoradiation therapy (CRT) or adjuvant temozolomide (TMZ) and survival in glioblastoma remains unclear. We hypothesized that an increase in platelets after these treatments would be predictive of a shorter survival. Methods We retrospectively reviewed data on 122 patients with newly diagnosed, pathologically proven glioblastoma who had been treated with surgery, followed by CRT and adjuvant TMZ, from 2007 to 2016. The association between the changes in blood count levels and survival was analyzed by the log-rank test. To adjust for confounding, we performed a multivariate analysis using known prognostic co-variates. Results Patients were dichotomized on the basis of the relative change in platelets after CRT from the baseline: ≤30% increase, low (n = 101) vs >30% increase, high (n = 12). The median survival for high vs. low platelets were 11 vs 28 months (p = 0.0062). No significant survival differences were observed on the basis of platelet changes during adjuvant TMZ. Similarly, changes in lymphocyte counts were not significantly prognostic. On multivariate analysis, MGMT, performance status, and an increase in platelets after CRT were significantly associated with survival (HR for platelets, 4.5; 95% confidence interval, 1.6-12.6). Conclusions Increased platelet counts after CRT are predictive of poor survival in glioblastoma. The effect is platelet specific and does not reflect bone marrow changes, as lymphocyte changes were not significantly prognostic. These results suggest an interaction between platelets and tumor aggressiveness. Thus, platelets serve as a novel, minimally invasive liquid biopsy for predicting outcome.

Abstract 3348: UniD: unified and integrated diagnostic pipeline for malignant gliomas based on DNA methylation data

Prognostic and predictive molecular diagnostics for patients with gliomas typically rely on multiple assays, requiring large amounts of tissue and high cost. DNA methylation has been utilized to identify prognostic subsets and high-throughput platforms exist that are suitable for archival tissue. Therefore, we developed a unified and integrated diagnostic pipeline that can assess multiple prognostic and predictive biomarkers using only the Illumina Infinium Methylation array. This pipeline includes two parts: data processing and diagnostic biomarkers. Data processing starts from the raw data and followed with quantitative sample, probe, and batch quality control. The diagnostic biomarkers include a glioma methylation assay that predicts radiation response (GaMA); tumor classification enriched for TCGA expression subclasses; copy number alterations including phosphatase and tensin homolog (PTEN) loss, epidermal growth factor receptor (EGFR) amplification, and chromosomes 1p/19q co-deletion; CpG island methylation phenotype (G-CIMP); isocitrate dehydrogenase (IDH) mutation, and O 6 -methylguanine-DNA methyltransferase (MGMT) promoter hypermethylation. WHO grade II-IV gliomas were analyzed in both publically available and institutional datasets. A signature was identified to effectively distinguished radiation resistant from radiation sensitive glioma stem-like cells (GSCs). Signature has been applied to 272 TCGA GBM samples from patients who received standard radiotherapy (RT). The survival analysis showed that the subgroup with RT-sensitive and RT-resistant have significant difference in survival time (log-rank test p-value = 0.0016). Gene expression subclasses prediction biomarker was build by using the revised TCGA gene expression subclasses as gold standard. The prediction accuracy in test data set was 83.5% in the homogeneous subgroup, 71.0% in the semi-heterogeneous subgroup, and 62.1% in the heterogeneous subgroup. The prediction accuracy decreased as tumor heterogeneity increased. Certain copy number alteration events were predicted by developing specific signatures. Revised methylation signatures were developed for IDH mutation and G-CIMP status respectively, which can identified 99% of those samples. 230 GBM samples with 450k data available were tested with MGMT methylation-specific real-time PCR for MGMT methylation status. The methylation-based MGMT prediction accuracy reached about 90%. In summary, we have developed a single, FFPE-based pipeline for unified and integrated determination of multiple biomarkers of malignant glioma. Citation Format: Jie Yang, Qianghu Wang, Lihong Long, Ravesanker Ezhilarasan, Erik Sulman. UniD: unified and integrated diagnostic pipeline for malignant gliomas based on DNA methylation data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3348. doi:10.1158/1538-7445.AM2017-3348