Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set

BACKGROUND: While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements. METHODS: We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan–Meier method. RESULTS: PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R(2) = 0.73 and R(2) = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts). CONCLUSIONS: The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0705-4) contains supplementary material, which is available to authorized users

Differential expression of 12 histone deacetylase (HDAC) genes in astrocytomas and normal brain tissue: class II and IV are hypoexpressed in glioblastomas

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is the most lethal primary malignant brain tumor. Although considerable progress has been made in the treatment of this aggressive tumor, the clinical outcome for patients remains poor. Histone deacetylases (HDACs) are recognized as promising targets for cancer treatment. In the past several years, HDAC inhibitors (HDACis) have been used as radiosensitizers in glioblastoma treatment. However, no study has demonstrated the status of global <it>HDAC </it>expression in gliomas and its possible correlation to the use of HDACis. The purpose of this study was to evaluate and compare mRNA and protein levels of class I, II and IV of HDACs in low grade and high grade astrocytomas and normal brain tissue and to correlate the findings with the malignancy in astrocytomas.</p> <p>Methods</p> <p>Forty-three microdissected patient tumor samples were evaluated. The histopathologic diagnoses were 20 low-grade gliomas (13 grade I and 7 grade II) and 23 high-grade gliomas (5 grade III and 18 glioblastomas). Eleven normal cerebral tissue samples were also analyzed (54 total samples analyzed). mRNA expression of class I, II, and IV <it>HDACs </it>was studied by quantitative real-time polymerase chain reaction and normalized to the housekeeping gene <it>β-glucuronidase</it>. Protein levels were evaluated by western blotting.</p> <p>Results</p> <p>We found that mRNA levels of class II and IV <it>HDACs </it>were downregulated in glioblastomas compared to low-grade astrocytomas and normal brain tissue (7 in 8 genes, <it>p </it>< 0.05). The protein levels of class II HDAC9 were also lower in high-grade astrocytomas than in low-grade astrocytomas and normal brain tissue. Additionally, we found that histone H3 (but not histone H4) was more acetylated in glioblastomas than normal brain tissue.</p> <p>Conclusion</p> <p>Our study establishes a negative correlation between <it>HDAC </it>gene expression and the glioma grade suggesting that class II and IV <it>HDACs </it>might play an important role in glioma malignancy. Evaluation of histone acetylation levels showed that histone H3 is more acetylated in glioblastomas than normal brain tissue confirming the downregulation of <it>HDAC </it>mRNA in glioblastomas.</p

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

BackgroundTargeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing.ResultsAll panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden.ConclusionThis comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.Peer reviewe

Phase II trial of AKT inhibitor MK-2206 in patients with advanced breast cancer who have tumors with PIK3CA or AKT mutations, and/or PTEN loss/PTEN mutation

Background The PI3K/AKT pathway is activated through PIK3CA or AKT1 mutations and PTEN loss in breast cancer. We conducted a phase II trial with an allosteric AKT inhibitor MK-2206 in patients with advanced breast cancer who had tumors with PIK3CA/AKT1 mutations and/or PTEN loss/mutation. Methods The primary endpoint was objective response rate (ORR). Secondary endpoints were 6-month progression-free survival (6 m PFS), predictive and pharmacodynamic markers, safety, and tolerability. Patients had pre-treatment and on-treatment biopsies as well as collection of peripheral blood mononuclear cells (PBMC) and platelet-rich plasma (PRP). Next-generation sequencing, immunohistochemistry, and reverse phase protein arrays (RPPA) were performed. Results Twenty-seven patients received MK-2206. Eighteen patients were enrolled into the PIK3CA/AKT1 mutation arm (cohort A): 13 had PIK3CA mutations, four had AKT1 mutations, and one had a PIK3CA mutation as well as PTEN loss. ORR and 6 m PFS were both 5.6% (1/18), with one patient with HR+ breast cancer and a PIK3CA E542K mutation experiencing a partial response (on treatment for 36 weeks). Nine patients were enrolled on the PTEN loss/mutation arm (cohort B). ORR was 0% and 6 m PFS was 11% (1/9), observed in a patient with triple-negative breast cancer and PTEN loss. The study was stopped early due to futility. The most common adverse events were fatigue (48%) and rash (44%). On pre-treatment biopsy, PIK3CA and AKT1 mutation status was concordant with archival tissue testing. However, two patients with PTEN loss based on archival testing had PTEN expression on the pre-treatment biopsy. MK-2206 treatment was associated with a significant decline in pAKT S473 and pAKT T308 and PI3K activation score in PBMC and PRPs, but not in tumor biopsies. By IHC, there was no significant decrease in median pAKT S473 or Ki-67 staining, but a drop was observed in both responders. Conclusions MK-2206 monotherapy had limited clinical activity in advanced breast cancer patients selected for PIK3CA/AKT1 or PTEN mutations or PTEN loss. This may, in part, be due to inadequate target inhibition at tolerable doses in heavily pre-treated patients with pathway activation, as well as tumor heterogeneity and evolution in markers such as PTEN conferring challenges in patient selection. Trial registration ClinicalTrials.gov, NCT01277757 . Registered 13 January 2011

A simplified interventional mapping system (SIMS) for the selection of combinations of targeted treatments in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a leading cause of death worldwide. Targeted monotherapies produce high regression rates, albeit for limited patient subgroups, who inevitably succumb. We present a novel strategy for identifying customized combinations of triplets of targeted agents, utilizing a simplified interventional mapping system (SIMS) that merges knowledge about existent drugs and their impact on the hallmarks of cancer. Based on interrogation of matched lung tumor and normal tissue using targeted genomic sequencing, copy number variation, transcriptomics, and miRNA expression, the activation status of 24 interventional nodes was elucidated. An algorithm was developed to create a scoring system that enables ranking of the activated interventional nodes for each patient. Based on the trends of co-activation at interventional points, combinations of drug triplets were defined in order to overcome resistance. This methodology will inform a prospective trial to be conducted by the WIN consortium, aiming to significantly impact survival in metastatic NSCLC and other malignancies