Survivin-targeted immunotherapy drives robust polyfunctional T cell generation and differentiation in advanced ovarian cancer patients

DepoVax™ is an innovative and strongly immunogenic vaccine platform. Survivin is highly expressed in many tumor types and has reported prognostic value. To generate tumor-specific immune response, a novel cancer vaccine was formulated in DepoVax platform (DPX-Survivac) using survivin HLA class I peptides. Safety and immune potency of DPX-Survivac was tested in combination with immune-modulator metronomic cyclophosphamide in ovarian cancer patients. All the patients receiving the therapy produced antigen-specific immune responses; higher dose vaccine and cyclophosphamide treatment generating significantly higher magnitude responses. Strong T cell responses were associated with differentiation of naïve T cells into central/effector memory (CM/EM) and late differentiated (LD) polyfunctional antigen-specific CD4⁺ and CD8⁺ T cells. This approach enabled rapid de novo activation/expansion of vaccine antigen-specific CD8⁺ T cells and provided a strong rationale for further testing to determine clinical benefits associated with this immune activation. These data represent vaccine-induced T cell activation in a clinical setting to a self-tumor antigen previously described only in animal models.

Whole Cell Therapeutic Vaccine Modified With Hyper-IL6 for Combinational Treatment of Nonresected Advanced Melanoma

Active specific immunotherapy of cancer requires an efficient induction and effector phase. The induction covers potent activation of anti-tumor response, whereas effector breaks the immunosuppression. We report efficacy of therapeutic melanoma vaccine (AGI-101H) used alone in advanced disease as a candidate for further combined treatment. In adjuvant setting in patients with resected metastases AGI-101H combined with surgery of recurring disease demonstrated long-term survival. Seventy-seven patients with nonresectable melanoma (8% IIIB, 21% IIIC, 71% IV) were enrolled. AGI-101H was administered 8× every 2 weeks, and then every month. At progression, maintenance was continued or induction was repeated and followed by maintenance. Median follow-up was 139.3 months. The median overall survival (OS) was 17.3 months; in patients with WHO 0-1 was 20.3 months. Complete response (CR) and partial response (PR) were observed in 19.4% and 9% of pts. Disease control rate was 54.5% of pts. The median CR+PR duration was 32 months. Reinduction was performed in 36.3% patients following disease progression with 46.6% of CR+PR. No grade 3/4 adverse events were observed. Treatment with AGI-101H of melanoma patients is safe and effective. AGI-101H is a good candidate for combinatorial treatment with immune check-points inhibitors or tumor hypoxia normalizators.

TRIAL REGISTRATION

EudraCT Number 2008-003373-40.

Circulating tumor cell biomarker panel as an individual-level surrogate for survival in metastatic castration-resistant prostate cancer

PURPOSE

Trials in castration-resistant prostate cancer (CRPC) need new clinical end points that are valid surrogates for survival. We evaluated circulating tumor cell (CTC) enumeration as a surrogate outcome measure.

PATIENTS AND METHODS

Examining CTCs alone and in combination with other biomarkers as a surrogate for overall survival was a secondary objective of COU-AA-301, a multinational, randomized, double-blind phase III trial of abiraterone acetate plus prednisone versus prednisone alone in patients with metastatic CRPC previously treated with docetaxel. The biomarkers were measured at baseline and 4, 8, and 12 weeks, with 12 weeks being the primary measure of interest. The Prentice criteria were applied to test candidate biomarkers as surrogates for overall survival at the individual-patient level.

RESULTS

A biomarker panel using CTC count and lactate dehydrogenase (LDH) level was shown to satisfy the four Prentice criteria for individual-level surrogacy. Twelve-week surrogate biomarker data were available for 711 patients. The abiraterone acetate plus prednisone and prednisone-alone groups demonstrated a significant survival difference (P = .034); surrogate distribution at 12 weeks differed by treatment (P < .001); the discriminatory power of the surrogate to predict mortality was high (weighted c-index, 0.81); and adding the surrogate to the model eliminated the treatment effect on survival. Overall, 2-year survival of patients with CTCs < 5 (low risk) versus patients with CTCs ≥ 5 cells/7.5 mL of blood and LDH > 250 U/L (high risk) at 12 weeks was 46% and 2%, respectively.

CONCLUSION

A biomarker panel containing CTC number and LDH level was shown to be a surrogate for survival at the individual-patient level in this trial of abiraterone acetate plus prednisone versus prednisone alone for patients with metastatic CRPC. Additional trials are ongoing to validate the findings.

PTEN Loss Is Associated with Worse Outcome in HER2-Amplified Breast Cancer Patients but Is Not Associated with Trastuzumab Resistance

PURPOSE

To investigate the clinical relevance of PTEN in HER2-amplified and HER2-nonamplified disease.

EXPERIMENTAL DESIGN

We assessed PTEN status in two large adjuvant breast cancer trials (BCIRG-006 and BCIRG-005) using a PTEN immunohistochemical (IHC) assay that was previously validated in a panel of 33 breast cancer cell lines and prostate cancer tissues with known PTEN gene deletion.

RESULTS

In the HER2-positive patient population, absence of tumor cell PTEN staining occurred at a rate of 5.4% and was independent of ER/PR status. In contrast, 15.9% of HER2-negative patients exhibited absence of PTEN staining with the highest frequency seen in triple-negative breast cancer (TNBC) subgroup versus ER/PR-positive patients (35.1% vs. 10.9%). Complete absence of PTEN staining in tumor cells was associated with poor clinical outcome in HER2-positive disease. Those patients whose cancers demonstrated absent PTEN staining had a significant decrease in disease-free survival (DFS) and overall survival (OS) compared with patients with tumors exhibiting any PTEN staining patterns (low, moderate, or high). Trastuzumab appeared to provide clinical benefit even for patients lacking PTEN staining. In the HER2-negative population, there were no statistically significant differences in clinical outcome based on PTEN status.

CONCLUSIONS

This study is the largest to date examining PTEN status in breast cancer and the data suggest that the rate and significance of PTEN status differ between HER2-positive and HER2-negative disease. Furthermore, the data clearly suggest that HER2-positive patients with PTEN loss still benefit from trastuzumab.

Radiographic progression-free survival as a response biomarker in metastatic castration-resistant prostate cancer: COU-AA-302 results

PURPOSE

Progression-free survival (PFS) in metastatic castration-resistant prostate cancer (mCRPC) trials has been inconsistently defined and poorly associated with overall survival (OS). A reproducible quantitative definition of radiographic PFS (rPFS) was tested for association with a coprimary end point of OS in a randomized trial of abiraterone in patients with mCRPC.

PATIENTS AND METHODS

rPFS was defined as ≥ two new lesions on an 8-week bone scan plus two additional lesions on a confirmatory scan, ≥ two new confirmed lesions on any scan ≥ 12 weeks after random assignment, and/or progression in nodes or viscera on cross-sectional imaging, or death. rPFS was assessed by independent review at 15% of deaths and by investigator review at 15% and 40% of deaths. rPFS and OS association was evaluated by Spearman's correlation.

RESULTS

A total of 1,088 patients were randomly assigned to abiraterone plus prednisone or prednisone alone. At first interim analysis, the hazard ratio (HR) by independent review was 0.43 (95% CI, 0.35 to 0.52; P < .001; abiraterone plus prednisone: median rPFS, not estimable; prednisone: median rPFS, 8.3 months). Similar HRs were obtained by investigator review at the first two interim analyses (HR, 0.49; 95% CI, 0.41 to 0.60; P < .001 and HR, 0.53; 95% CI, 0.45 to 0.62; P < .001, respectively), validating the imaging data assay used. Spearman's correlation coefficient between rPFS and OS was 0.72.

CONCLUSION

rPFS was highly consistent and highly associated with OS, providing initial prospective evidence on further developing rPFS as an intermediate end point in mCRPC trials.

A nonhomogeneous hidden markov model for gene mapping based on next-generation sequencing data

The analysis of polygenetic characteristics for mapping quantitative trait loci (QTL) remains an important challenge. QTL analysis requires two or more strains of organisms that differ substantially in the (poly-)genetic trait of interest, resulting in a heterozygous offspring. The offspring with the trait of interest is selected and subsequently screened for molecular markers such as single-nucleotide polymorphisms (SNPs) with next-generation sequencing. Gene mapping relies on the co-segregation between genes and/or markers. Genes and/or markers that are linked to a QTL influencing the trait will segregate more frequently with this locus. For each identified marker, observed mismatch frequencies between the reads of the offspring and the parental reference strains can be modeled by a multinomial distribution with the probabilities depending on the state of an underlying, unobserved Markov process. The states indicate whether the SNP is located in a (vicinity of a) QTL or not. Consequently, genomic loci associated with the QTL can be discovered by analyzing hidden states along the genome. The aforementioned hidden Markov model assumes that the identified SNPs are equally distributed along the chromosome and does not take the distance between neighboring SNPs into account. The distance between the neighboring SNPs could influence the chance of co-segregation between genes and markers. To address this issue, we propose a nonhomogeneous hidden Markov model with a transition matrix that depends on a set of distance-varying observed covariates. The application of the model is illustrated on the data from a study of ethanol tolerance in yeast.

Trial-level association between response-based endpoints (RBEs) and progression-free (PFS)/overall survival (OS) in first-line therapy for metastatic colorectal cancer (mCRC) in the ARCAD database

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Background: Early tumor shrinkage (ETS; ≥20% decrease from baseline) and early objective tumor response (EOTR; CR/PR by RECIST) are associated with improved PFS/OS to a similar extent than best overall response (BOR), confirmed response (ConfR) and non-progression rate (NPR; CR/PR/SD by RECIST) at the individual level in first-line mCRC (ASCO 2014, abstr 3538/3578). We assessed these RBEs at the trial level. Methods: Data were available on 12,185 pts enrolled in a total of 17 randomized trials of chemotherapy (CT) alone or with targeted agents (TAs). ETS, EOTR and NPR were assessed at 6/8/9 and 12 weeks (wks), whereas BOR and ConfR were ascertained within 26 wks from randomization. Association between treatment effects on RBEs and on PFS/OS was assessed by coefficients of determination (R2, adjusted for estimation errors) using a copula model). Results: None of the RBEs had consistently strong correlations with PFS or OS (Table). The number of trials was insufficient to obtain reliable estimates for antiangiogenics and anti-EGFR separately. Conclusions: Despite their individual-level associations with PFS and OS, RBEs do not appear to be surrogate endpoints in first-line mCRC, given their poor predictive ability. [Table: see text]

On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints

The increasing cost of drug development has raised the demand for surrogate endpoints when evaluating new drugs in clinical trials. However, over the years, it has become clear that surrogate endpoints need to be statistically evaluated and deemed valid, before they can be used as substitutes of "true" endpoints in clinical studies. Nowadays, two paradigms, based on causal-inference and meta-analysis, dominate the scene. Nonetheless, although the literature emanating from these paradigms is wide, till now the relationship between them has largely been left unexplored. In the present work, we discuss the conceptual framework underlying both approaches and study the relationship between them using theoretical elements and the analysis of a real case study. Furthermore, we show that the meta-analytic approach can be embedded within a causal-inference framework on the one hand and that it can be heuristically justified why surrogate endpoints successfully evaluated using this approach will often be appealing from a causal-inference perspective as well, on the other. A newly developed and user friendly R package Surrogate is provided to carry out the evaluation exercise.

Comparison of the Mahalanobis distance and Pearson's χ² statistic as measures of similarity of isotope patterns

To extract a genuine peptide signal from a mass spectrum, an observed series of peaks at a particular mass can be compared with the isotope distribution expected for a peptide of that mass. To decide whether the observed series of peaks is similar to the isotope distribution, a similarity measure is needed. In this short communication, we investigate whether the Mahalanobis distance could be an alternative measure for the commonly employed Pearson's χ(2) statistic. We evaluate the performance of the two measures by using a controlled MALDI-TOF experiment. The results indicate that Pearson's χ(2) statistic has better discriminatory performance than the Mahalanobis distance and is a more robust measure.

Progression-free survival as a surrogate for overall survival in advanced/recurrent gastric cancer trials: a meta-analysis

The traditional endpoint for assessing efficacy of chemotherapies for advanced/recurrent gastric cancer is overall survival (OS), but OS requires prolonged follow-up. We investigated whether progression-free survival (PFS) is a valid surrogate for OS. Using individual patient data from the GASTRIC meta-analysis, surrogacy of PFS was assessed through the correlation between the endpoints and through the correlation between the treatment effects on the endpoints. External validation of the prediction based on PFS was also evaluated. Individual data from 4069 patients in 20 randomized trials were analyzed. The rank correlation coefficient between PFS and OS was 0.853 (95% confidence interval [CI] = 0.852 to 0.854). The R (2) between treatment effects on PFS and on OS was 0.61 (95% CI = 0.04 to 1.00). Treatment effects on PFS and on OS were only moderately correlated, and we could not confirm the validity of PFS as a surrogate endpoint for OS in advanced/recurrent gastric cancer.

Disease-free survival as a surrogate for overall survival in adjuvant trials of gastric cancer: a meta-analysis

BACKGROUND

In investigations of the effectiveness of surgery and adjuvant chemotherapy for gastric cancers, overall survival (OS) is considered the gold standard endpoint. However, the disadvantage of using OS as the endpoint is that it requires an extended follow-up period. We sought to investigate whether disease-free survival (DFS) is a valid surrogate for OS in trials of adjuvant chemotherapy for gastric cancer.

METHODS

The GASTRIC group initiated a meta-analysis of individual patient data collected in randomized clinical trials comparing adjuvant chemotherapy vs surgery alone for patients with curatively resected gastric cancer. Surrogacy of DFS was assessed through the correlation between the endpoints as well as through the correlation between the treatment effects on the endpoints. External validation of the prediction based on DFS was also evaluated.

RESULTS

Individual patient data from 14 randomized clinical trials that included a total of 3288 patients were analyzed. The rank correlation coefficient between DFS and OS was 0.974 (95% confidence interval [CI] = 0.971 to 0.976). The coefficient of determination between the treatment effects on DFS and on OS was as high as 0.964 (95% CI = 0.926 to 1.000), and the surrogate threshold effect based on adjusted regression analysis was 0.92. In external validation, the six hazard ratios for OS predicted according to DFS were in very good agreement with those actually observed for OS.

CONCLUSIONS

DFS is an acceptable surrogate for OS in trials of cytotoxic agents for gastric cancer in the adjuvant setting.

Evaluation of normalization methods to pave the way towards large-scale LC-MS-based metabolomics profiling experiments

Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approaches on LC-MS metabolomics experiments, which do not require the use of internal standards. According to variability measures, each normalization method performs relatively well, showing that the use of any normalization method will greatly improve data-analysis originating from multiple experimental runs. In the second part, we apply cyclic-Loess normalization to a Leishmania sample. This normalization method allows the removal of systematic variability between two measurement blocks over time and maintains the differential metabolites. In conclusion, normalization allows for pooling datasets from different measurement blocks over time and increases the statistical power of the analysis, hence paving the way to increase the scale of LC-MS metabolomics experiments. From our investigation, we recommend data-driven normalization methods over model-driven normalization methods, if only a few internal standards were used. Moreover, data-driven normalization methods are the best option to normalize datasets from untargeted LC-MS experiments.

Effect of oral cyclophosphamide on the immunogenicity of DPX-Survivac in ovarian cancer patients: Results of a phase I study

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Background: Survivin, a protein involved in regulation of apoptosis, is highly expressed in many tumor types and has reported prognostic value. DPX-Survivac is a cocktail of survivin HLA class I peptides (A1, A2, A3, A24 and B7) formulated in the novel adjuvanting vaccine platform DepoVax. A phase I study examined the safety and immune potency of DPX-Survivac in combination with cyclophosphamide in ovarian cancer patients. Methods: 18 of 19 advanced ovarian cancer patients treated with platinum chemotherapy and showing no disease progression completed their vaccine therapy. Cohort A (6 pts) received three 0.5 mL vaccine injections 3 weeks apart; cohorts B and C (6 pts each) received three 0.1 mL or 0.5 mL vaccine injections in combination with metronomic low dose oral cyclophosphamide. Adverse events were assessed using CTCAE v4.0. Blood was collected to study immune function (MDSCs, T regs and B cells) and vaccine-induced T cell immunity (ELISpot, tetramer analysis and multi-parametric intracellular cytokine staining). Repeated measures of immunity at baseline and after 1, 2 and 3 injections were analyzed using a general linear model. Results: DPX-Survivac was well tolerated with no significant systemic AEs. Local injection AEs occured in all patients. Grade 3 local reactions occured in 3 patients (1 pt in B and 2 pts in C). 11 of 12 patients receiving the combination therapy produced immune responses by at least 2 assays, generally established with one or two vaccinations and increased or maintained with boosters. A dose response was observed, with cohort C patients producing significantly higher magnitude responses (C vs B, P=.013). Low dose cyclophosphamide significantly enhanced the 0.5 ml dose (C vs A, P=.015). Notably, antigen specific CD8 T cells were detected ex vivoi n PBL’s using tetramers and further characterized as polyfunctional by multi-parametric ICS, suggesting a robust immune response. Conclusions: DPX-Survivac is well tolerated and immunogenic. Immune modulation with low dose oral cyclophosphamide can dramatically enhance the immunogenicity of this vaccine. The efficacy of the proposed DPX-Survivac vaccine therapy needs to be tested in a randomized phase II study. Clinical trial information: NCT01416038.

Simultaneous mapping of multiple gene loci with pooled segregants

The analysis of polygenic, phenotypic characteristics such as quantitative traits or inheritable diseases remains an important challenge. It requires reliable scoring of many genetic markers covering the entire genome. The advent of high-throughput sequencing technologies provides a new way to evaluate large numbers of single nucleotide polymorphisms (SNPs) as genetic markers. Combining the technologies with pooling of segregants, as performed in bulked segregant analysis (BSA), should, in principle, allow the simultaneous mapping of multiple genetic loci present throughout the genome. The gene mapping process, applied here, consists of three steps: First, a controlled crossing of parents with and without a trait. Second, selection based on phenotypic screening of the offspring, followed by the mapping of short offspring sequences against the parental reference. The final step aims at detecting genetic markers such as SNPs, insertions and deletions with next generation sequencing (NGS). Markers in close proximity of genomic loci that are associated to the trait have a higher probability to be inherited together. Hence, these markers are very useful for discovering the loci and the genetic mechanism underlying the characteristic of interest. Within this context, NGS produces binomial counts along the genome, i.e., the number of sequenced reads that matches with the SNP of the parental reference strain, which is a proxy for the number of individuals in the offspring that share the SNP with the parent. Genomic loci associated with the trait can thus be discovered by analyzing trends in the counts along the genome. We exploit the link between smoothing splines and generalized mixed models for estimating the underlying structure present in the SNP scatterplots.

BRAIN: a universal tool for high-throughput calculations of the isotopic distribution for mass spectrometry

This Letter presents the R-package implementation of the recently introduced polynomial method for calculating the aggregated isotopic distribution called BRAIN (Baffling Recursive Algorithm for Isotopic distributioN calculations). The algorithm is simple, easy to understand, highly accurate, fast, and memory-efficient. The method is based on the application of the Newton-Girard theorem and Viète's formulae to the polynomial coding of different aggregated isotopic variants. As a result, an elegant recursive equation is obtained for computing the occurrence probabilities of consecutive aggregated isotopic peaks. Additionally, the algorithm also allows calculating the center-masses of the aggregated isotopic variants. We propose an implementation which is suitable for high-throughput processing and easily customizable for application in different areas of mass spectral data analyses. A case study demonstrates how the R-package can be applied in the context of protein research, but the software can be also used for calculating the isotopic distribution in the context of lipidomics, metabolomics, glycoscience, or even space exploration. More materials, i.e., reference manual, vignette, and the package itself are available at Bioconductor online (http://www.bioconductor.org/packages/release/bioc/html/BRAIN.html).