Influence of unrecognized molecular heterogeneity on randomized clinical trials

Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence

Purpose

For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer.

Methods

199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported.

Results

Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation).

Conclusion

In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

Radial Data Mining to Identify Density-Dose Interactions That Predict Distant Failure Following SABR

Purpose

Lower dose outside the planned treatment area in lung stereotactic radiotherapy has been linked to increased risk of distant metastasis (DM) possibly due to underdosage of microscopic disease (MDE). Independently, tumour density on pretreatment computed tomography (CT) has been linked to risk of MDE. No studies have investigated the interaction between imaging biomarkers and incidental dose. The interaction would showcase whether the impact of dose on outcome is dependent on imaging and, hence, if imaging could inform which patients require dose escalation outside the gross tumour volume (GTV). We propose an image-based data mining methodology to investigate density-dose interactions radially from the GTV to predict DM with no a priori assumption on location.

Methods

Dose and density were quantified in 1-mm annuli around the GTV for 199 patients with early-stage lung cancer treated with 60 Gy in 5 fractions. Each annulus was summarised by three density and three dose parameters. For parameter combinations, Cox regressions were performed including a dose-density interaction in independent annuli. Heatmaps were created that described improvement in DM prediction due to the interaction. Regions of significant improvement were identified and studied in overall outcome models.

Results

Dose-density interactions were identified that significantly improved prediction for over 50% of bootstrap resamples. Dose and density parameters were not significant when the interaction was omitted. Tumour density variance and high peritumour density were associated with DM for patients with more cold spots (less than 30-Gy EQD2) and non-uniform dose about 3 cm outside of the GTV. Associations identified were independent of the mean GTV dose.

Conclusions

Patients with high tumour variance and peritumour density have increased risk of DM if there is a low and non-uniform dose outside the GTV. The dose regions are independent of tumour dose, suggesting that incidental dose may play an important role in controlling occult disease. Understanding such interactions is key to identifying patients who will benefit from dose-escalation. The methodology presented allowed spatial dose-density interactions to be studied at the exploratory stage for the first time. This could accelerate the clinical implementation of imaging biomarkers by demonstrating the impact of incidental dose for tumours of varying characteristics in routine data.

Treating non-responders: pitfalls and implications for cancer immunotherapy trial design

BACKGROUND

Conventional trial design and analysis strategies fail to address the typical challenge of immune-oncology (IO) studies: only a limited percentage of treated patients respond to the experimental treatment. Treating non-responders, we hypothesize, would in part drive non-proportional hazards (NPH) patterns in Kaplan-Meier curves that violates the proportional hazards (PH) assumption required by conventional strategies. Ignoring such violation incurred from treating non-responders in the design and analysis strategy may result in underpowered or even falsely negative studies. Hence, designing innovative IO trials to address such pitfall becomes essential.

METHODS

We empirically tested the hypothesis that treating non-responders in studies of inadequate size is sufficient to cause NPH patterns and thereby proposed a novel strategy, p-embedded, to incorporate the dichotomized response incurred from treating non-responders, as measured by the baseline proportion of responders among treated patients p%, into the design and analysis procedures, aiming to ensure an adequate study power when the PH assumption is violated.

RESULTS

Empirical studies confirmed the hypothetical cause contributes to the manifestation of NPH patterns. Further evaluations revealed a significant quantitative impact of p% on study efficiency. The p-embedded strategy incorporating the properly pre-specified p% ensures an adequate study power whereas the conventional design ignoring it leads to a severe power loss.

CONCLUSION

The p-embedded strategy allows us to quantify the impact of treating non-responders on study efficiency. Implicit in such strategy is the solution to mitigate the occurrence of NPH patterns and enhance the study efficiency for IO trials via enrolling more prospective responders.

A Review of Perspectives on the Use of Randomization in Phase II Oncology Trials

Historically, phase II oncology trials assessed a treatment's efficacy by examining its tumor response rate in a single-arm trial. Then, approximately 25 years ago, certain statistical and pharmacological considerations ignited a debate around whether randomized designs should be used instead. Here, based on an extensive literature review, we review the arguments on either side of this debate. In particular, we describe the numerous factors that relate to the reliance of single-arm trials on historical control data and detail the trial scenarios in which there was general agreement on preferential utilization of single-arm or randomized design frameworks, such as the use of single-arm designs when investigating treatments for rare cancers. We then summarize the latest figures on phase II oncology trial design, contrasting current design choices against historical recommendations on best practice. Ultimately, we find several ways in which the design of recently completed phase II trials does not appear to align with said recommendations. For example, despite advice to the contrary, only 66.2% of the assessed trials that employed progression-free survival as a primary or coprimary outcome used a randomized comparative design. In addition, we identify that just 28.2% of the considered randomized comparative trials came to a positive conclusion as opposed to 72.7% of the single-arm trials. We conclude by describing a selection of important issues influencing contemporary design, framing this discourse in light of current trends in phase II, such as the increased use of biomarkers and recent interest in novel adaptive designs.

A signature of hypoxia-related factors reveals functional dysregulation and robustly predicts clinical outcomes in stage I/II colorectal cancer patients

Background

The hypoxic tumor microenvironment accelerates the invasion and migration of colorectal cancer (CRC) cells. The aim of this study was to develop and validate a hypoxia gene signature for predicting the outcome in stage I/II CRC patients that have limited therapeutic options.

Methods

The hypoxic gene signature (HGS) was constructed using transcriptomic data of 309 CRC patients with complete clinical information from the CIT microarray dataset. A total of 1877 CRC patients with complete prognostic information in six independent datasets were divided into a training cohort and two validation cohorts. Univariate and multivariate analyses were conducted to evaluate the prognostic value of HGS.

Results

The HGS consisted of 14 genes, and demarcated the CRC patients into the high- and low-risk groups. In all three cohorts, patients in the high-risk group had significantly worse disease free survival (DFS) compared with those in the low risk group (training cohort—HR = 4.35, 95% CI 2.30–8.23, P < 0.001; TCGA cohort—HR = 2.14, 95% CI 1.09–4.21, P = 0.024; meta-validation cohort—HR = 1.91, 95% CI 1.08–3.39, P = 0.024). Compared to Oncotype DX, HGS showed superior predictive outcome in the training cohort (C-index, 0.80 vs 0.65) and the validation cohort (C-index, 0.70 vs 0.61). Pathway analysis of the high- and low-HGS groups showed significant differences in the expression of genes involved in mTROC1, G2-M, mitosis, oxidative phosphorylation, MYC and PI3K–AKT–mTOR pathways (P < 0.005).

Conclusion

Hypoxic gene signature is a satisfactory prognostic model for early stage CRC patients, and the exact biological mechanism needs to be validated further.

Spatially Resolved Transcriptomics Enables Dissection of Genetic Heterogeneity in Stage III Cutaneous Malignant Melanoma

Cutaneous malignant melanoma (melanoma) is characterized by a high mutational load, extensive intertumoral and intratumoral genetic heterogeneity, and complex tumor microenvironment (TME) interactions. Further insights into the mechanisms underlying melanoma are crucial for understanding tumor progression and responses to treatment. Here we adapted the technology of spatial transcriptomics (ST) to melanoma lymph node biopsies and successfully sequenced the transcriptomes of over 2,200 tissue domains. Deconvolution combined with traditional approaches for dimensional reduction of transcriptome-wide data enabled us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Our unsupervised analysis revealed a complex spatial intratumoral composition of melanoma metastases that was not evident through morphologic annotation. Each biopsy showed distinct gene expression profiles and included examples of the coexistence of multiple melanoma signatures within a single tumor region as well as shared profiles for lymphoid tissue characterized according to their spatial location and gene expression profiles. The lymphoid area in close proximity to the tumor region displayed a specific expression pattern, which may reflect the TME, a key component to fully understanding tumor progression. In conclusion, using the ST technology to generate gene expression profiles reveals a detailed landscape of melanoma metastases. This should inspire researchers to integrate spatial information into analyses aiming to identify the factors underlying tumor progression and therapy outcome.Significance: Applying ST technology to gene expression profiling in melanoma lymph node metastases reveals a complex transcriptional landscape in a spatial context, which is essential for understanding the multiple components of tumor progression and therapy outcome. Cancer Res; 78(20); 5970-9. ©2018 AACR.

Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design

Importance

The heterogeneity of rate of clinical progression among patients with Alzheimer disease leads to difficulty in providing clinical counseling and diminishes the power of clinical trials using disease-modifying agents.

Objective

To gain a better understanding of the factors that affect the natural history of progression in Alzheimer disease for the purpose of improving both clinical care and clinical trial design.

Design, Setting, and Participants

A longitudinal cohort study of aging from 2005 to 2014 in the National Alzheimer Coordinating Center. Clinical evaluation of the participants was conducted in 31 National Institute on Aging's Alzheimer Disease Centers. Nine hundred eighty-four participants in the National Alzheimer Coordinating Center cohort study who died and underwent autopsy and met inclusion and exclusion criteria.

Main Outcomes and Measures

We sought to model the possibility that knowledge of neurofibrillary tangle burden in the presence of moderate or frequent plaques would add to the ability to predict clinical rate of progression during the ensuing 2 to 3 years. We examined the National Alzheimer Coordinating Center autopsy data to evaluate the effect of different neurofibrillary tangle stages on the rates of progression on several standard clinical instruments: the Clinical Dementia Rating Scale sum of boxes, a verbal memory test (logical memory), and a controlled oral word association task (vegetable naming), implementing a reverse-time longitudinal modeling approach in conjunction with latent class estimation to adjust for unmeasured sources of heterogeneity.

Results

Several correlations between clinical variables and neurocognitive performance suggest a basis for heterogeneity: Higher education level was associated with lower Clinical Dementia Rating Scale sum of boxes (β = -0.19; P < .001), and frequent vs moderate neuritic plaques were associated with higher Clinical Dementia Rating Scale sum of boxes (β = 1.64; P < .001) and lower logical memory score (β = -1.07; P = .005). The rate of change of the clinical and cognitive scores varied depending on Braak stage, when adjusting for plaques, age of death, sex, education, and APOE genotype. For example, comparing high vs low Braak stage with other variables fixed, the logical memory score decreased a substantial 0.38 additional units per year (95% CI, -0.70 to -0.06; P = .02). Using these data, we estimate that a 300-participant clinical trial with end point of a 20% improvement in slope in rate of change of Clinical Dementia Rating Scale sum of boxes has 89% power when all participants in the trial are from the high Braak stage, compared with 29% power if Braak stage had not used for eligibility.

Conclusions and Relevance

We found that knowledge of neurofibrillary tangle stage, modeled as the sort of information that could be available from tau positron-emission tomography scans and its use to determine eligibility to a trial, could dramatically improve the power of clinical trials and equivalently reduce the required sample sizes of clinical trials.

Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces

Stratified medicine seeks to identify biomarkers or parsimonious gene signatures distinguishing patients that will benefit most from a targeted treatment. We evaluated 12 approaches in high-dimensional Cox models in randomized clinical trials: penalization of the biomarker main effects and biomarker-by-treatment interactions (full-lasso, three kinds of adaptive lasso, ridge+lasso and group-lasso); dimensionality reduction of the main effect matrix via linear combinations (PCA+lasso (where PCA is principal components analysis) or PLS+lasso (where PLS is partial least squares)); penalization of modified covariates or of the arm-specific biomarker effects (two-I model); gradient boosting; and univariate approach with control of multiple testing. We compared these methods via simulations, evaluating their selection abilities in null and alternative scenarios. We varied the number of biomarkers, of nonnull main effects and true biomarker-by-treatment interactions. We also proposed a novel measure evaluating the interaction strength of the developed gene signatures. In the null scenarios, the group-lasso, two-I model, and gradient boosting performed poorly in the presence of nonnull main effects, and performed well in alternative scenarios with also high interaction strength. The adaptive lasso with grouped weights was too conservative. The modified covariates, PCA+lasso, PLS+lasso, and ridge+lasso performed moderately. The full-lasso and adaptive lassos performed well, with the exception of the full-lasso in the presence of only nonnull main effects. The univariate approach performed poorly in alternative scenarios. We also illustrate the methods using gene expression data from 614 breast cancer patients treated with adjuvant chemotherapy.

Statistical controversies in clinical research: prognostic gene signatures are not (yet) useful in clinical practice

With the genomic revolution and the era of targeted therapy, prognostic and predictive gene signatures are becoming increasingly important in clinical research. They are expected to assist prognosis assessment and therapeutic decision making. Notwithstanding, an evidence-based approach is needed to bring gene signatures from the laboratory to clinical practice. In early breast cancer, multiple prognostic gene signatures are commercially available without having formally reached the highest levels of evidence-based criteria. We discuss specific concepts for developing and validating a prognostic signature and illustrate them with contemporary examples in breast cancer. When a prognostic signature has not been developed for predicting the magnitude of relative treatment benefit through an interaction effect, it may be wishful thinking to test its predictive value. We propose that new gene signatures be built specifically for predicting treatment effects for future patients and outline an approach for this using a cross-validation scheme in a standard phase III trial. Replication in an independent trial remains essential.

Systemic treatment of hepatocellular carcinoma: why so many failures in the development of new drugs?

INTRODUCTION

The increasing knowledge of the genomic landscape of hepatocellular carcinoma (HCC) and the development of molecular targeted therapies are a promising background for increasing the number of effective drugs for HCC patients. In recent years, many new drugs have been tested as an alternative to sorafenib or after sorafenib failure.

AREAS COVERED

In this review, our aim is to describe the randomized trials recently conducted in HCC patients, in order to understand the main reasons potentially related to the failures of many drugs. In addition, we briefly describe the main ongoing trials, that could potentially change the scenario of HCC treatment in the next years. Expert commentary: Heterogeneity of study populations, lack of understanding of critical drivers of tumor progression, risk of liver toxicity associated with experimental agents, flaws in trial design and marginal antitumoral potency can be considered the main reasons for failure of phase III clinical trials in HCC. Most ongoing trials are conducted without any molecular selection criteria, although many drugs could be probably better tested in a molecularly selected population. The knowledge of potential predictive factors for drug efficacy in patients with advanced HCC could improve the chance of obtaining positive results in clinical trials.

Heterogeneity of Metastatic Melanoma: Correlation of MITF With Its Transcriptional Targets MLSN1, PEDF, HMB-45, and MART-1

OBJECTIVES

Histologic and molecular heterogeneity is well recognized in malignant melanoma; however, the diversity of expression of new and classic melanoma markers has not been correlated in serial sections of metastases.

METHODS

We examined and correlated the expression of microphthalmia transcription factor (MITF) with its transcriptional targets, including melastatin (MLSN1/TRPM1), pigment epithelium-derived factor (SERPINF1/PEDF), SILV/PMEL17/GP100 (human melanoma black 45 [HMB-45]), and melanoma antigen recognized by T cells 1 (MART-1)/MLANA, in 13 melanoma metastases in lymph nodes of 13 patients. The expression levels and patterns of marker expression were recorded by a semiquantitative, 4-point ordinal reactivity method.

RESULTS

Our results showed a consistently robust and diffuse expression of MITF protein in 12 (92%) of 13 metastatic tumors compared with variable expression of MLSN1 (46%) messenger RNA or PEDF (75%), HMB-45 (54%), and MART-1 (46%) proteins.

CONCLUSIONS

Overall, in melanoma lymph node metastases, MITF protein expression was not tightly correlated with its gene targets. Moreover, the immunoreactivity for MITF, compared with MART-1 and HMB-45, was retained, supporting immunohistochemical detection of MITF as a more sensitive method of detecting metastatic melanoma.

Tests for equivalence of two survival functions: Alternative to the tests under proportional hazards

For either the equivalence trial or the non-inferiority trial with survivor outcomes from two treatment groups, the most popular testing procedure is the extension (e.g., Wellek, A log-rank test for equivalence of two survivor functions, Biometrics, 1993; 49: 877-881) of log-rank based test under proportional hazards model. We show that the actual type I error rate for the popular procedure of Wellek is higher than the intended nominal rate when survival responses from two treatment arms satisfy the proportional odds survival model. When the true model is proportional odds survival model, we show that the hypothesis of equivalence of two survival functions can be formulated as a statistical hypothesis involving only the survival odds ratio parameter. We further show that our new equivalence test, formulation, and related procedures are applicable even in the presence of additional covariates beyond treatment arms, and the associated equivalence test procedures have correct type I error rates under the proportional hazards model as well as the proportional odds survival model. These results show that use of our test will be a safer statistical practice for equivalence trials of survival responses than the commonly used log-rank based tests.

Unobserved Heterogeneity of Frailty in the Analysis of Socioeconomic Differences in Health and Mortality

The concepts of unobserved frailty and selection have been extensively analyzed with respect to phenomena like mortality deceleration at old ages and mortality convergence or cross overs between populations (for example American black and white populations, men and women). Despite the long-time observation of converging mortality risks in differential socioeconomic mortality research, the interest in the connection between frailty, selection, and health and mortality inequalities over a life course approach has increased only recently. This overview of the literature summarizes the main concepts of unobserved frailty and socioeconomic differences in mortality and how frailty and selection relate to these differences at old ages. It then reviews the evidence coming from the existing studies. Although the number of studies is still limited, the body of research on unobserved frailty and socioeconomic inequalities in health and mortality in a life course approach is growing. The results, however, are contradictory, and whether selection plays a major role in shaping the observed socioeconomic mortality patterns at old ages is still controversial.

The clinical importance of assessing tumor hypoxia: relationship of tumor hypoxia to prognosis and therapeutic opportunities

Tumor hypoxia is a well-established biological phenomenon that affects the curability of solid tumors, regardless of treatment modality. Especially for head and neck cancer patients, tumor hypoxia is linked to poor patient outcomes. Given the biological problems associated with tumor hypoxia, the goal for clinicians has been to identify moderately to severely hypoxic tumors for differential treatment strategies. The "gold standard" for detecting and characterizing of tumor hypoxia are the invasive polarographic electrodes. Several less invasive hypoxia assessment techniques have also shown promise for hypoxia assessment. The widespread incorporation of hypoxia information in clinical tumor assessment is severely impeded by several factors, including regulatory hurdles and unclear correlation with potential treatment decisions. There is now an acute need for approved diagnostic technologies for determining the hypoxia status of cancer lesions, as it would enable clinical development of personalized, hypoxia-based therapies, which will ultimately improve outcomes. A number of different techniques for assessing tumor hypoxia have evolved to replace polarographic pO2 measurements for assessing tumor hypoxia. Several of these modalities, either individually or in combination with other imaging techniques, provide functional and physiological information of tumor hypoxia that can significantly improve the course of treatment. The assessment of tumor hypoxia will be valuable to radiation oncologists, surgeons, and biotechnology and pharmaceutical companies who are engaged in developing hypoxia-based therapies or treatment strategies.

Advances in diagnostic and treatment modalities for intracranial tumors

Intracranial neoplasia is a common clinical condition in domestic companion animals, particularly in dogs. Application of advances in standard diagnostic and therapeutic modalities together with a broad interest in the development of novel translational therapeutic strategies in dogs has resulted in clinically relevant improvements in outcome for many canine patients. This review highlights the status of current diagnostic and therapeutic approaches to intracranial neoplasia and areas of novel treatment currently in development.

Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease

Effective treatment options for advanced colorectal cancer (CRC) are limited, survival rates are poor and this disease continues to be a leading cause of cancer-related deaths worldwide. Despite being a highly heterogeneous disease, a large subset of individuals with sporadic CRC typically harbor relatively few established 'driver' lesions. Here, we describe a collection of genetically engineered mouse models (GEMMs) of sporadic CRC that combine lesions frequently altered in human patients, including well-characterized tumor suppressors and activators of MAPK signaling. Primary tumors from these models were profiled, and individual GEMM tumors segregated into groups based on their genotypes. Unique allelic and genotypic expression signatures were generated from these GEMMs and applied to clinically annotated human CRC patient samples. We provide evidence that a Kras signature derived from these GEMMs is capable of distinguishing human tumors harboring KRAS mutation, and tracks with poor prognosis in two independent human patient cohorts. Furthermore, the analysis of a panel of human CRC cell lines suggests that high expression of the GEMM Kras signature correlates with sensitivity to targeted pathway inhibitors. Together, these findings implicate GEMMs as powerful preclinical tools with the capacity to recapitulate relevant human disease biology, and support the use of genetic signatures generated in these models to facilitate future drug discovery and validation efforts.

Miniaturized nuclear magnetic resonance platform for detection and profiling of circulating tumor cells

Accurate detection and profiling of circulating tumor cells (CTCs) is a highly sought after technology to improve cancer management. Such "liquid biopsies" could offer a non-invasive, repeatable window into each patient's tumor, facilitating early cancer diagnosis and treatment monitoring. The rarity of CTCs, approximated at 1 CTC for every billion peripheral blood cells, however, poses significant challenges to sensitive and reliable detection. We have recently developed a new micro-nuclear magnetic resonance (μNMR) platform for biosensing. Through the synergistic integration of microfabrication, nanosensors, and novel chemistries, the μNMR platform offers high detection sensitivity and point-of-care operation, overcoming technical barriers in CTC research. We herein review the μNMR technology with emphasis on its application to CTC detection. Recent advances in the sensing technology will be summarized, followed by the description of the dynamic interplay between our preclinical and clinical CTC studies.

IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection

BACKGROUND

IDH1 gene mutations identify gliomas with a distinct molecular evolutionary origin. We sought to determine the impact of surgical resection on survival after controlling for IDH1 status in malignant astrocytomas-World Health Organization grade III anaplastic astrocytomas and grade IV glioblastoma.

METHODS

Clinical parameters including volumetric assessment of preoperative and postoperative MRI were recorded prospectively on 335 malignant astrocytoma patients: n = 128 anaplastic astrocytomas and n = 207 glioblastoma. IDH1 status was assessed by sequencing and immunohistochemistry.

RESULTS

IDH1 mutation was independently associated with complete resection of enhancing disease (93% complete resections among mutants vs 67% among wild-type, P < .001), indicating IDH1 mutant gliomas were more amenable to resection. The impact of residual tumor on survival differed between IDH1 wild-type and mutant tumors. Complete resection of enhancing disease among IDH1 wild-type tumors was associated with a median survival of 19.6 months versus 10.7 months for incomplete resection; however, no survival benefit was observed in association with further resection of nonenhancing disease (minimization of total tumor volume). In contrast, IDH1 mutants displayed an additional survival benefit associated with maximal resection of total tumor volume (median survival 9.75 y for >5 cc residual vs not reached for <5 cc, P = .025).

CONCLUSIONS

The survival benefit associated with surgical resection differs based on IDH1 genotype in malignant astrocytic gliomas. Therapeutic benefit from maximal surgical resection, including both enhancing and nonenhancing tumor, may contribute to the better prognosis observed in the IDH1 mutant subgroup. Thus, individualized surgical strategies for malignant astrocytoma may be considered based on IDH1 status.

Success at last: a molecular factor that informs treatment

Anaplastic oligodendrogliomas are rare primary brain tumors. However, they respond more effectively to treatment and have a better prognosis than commoner varieties. About 25 year ago, reports emerged that oligodendrogliomas can respond robustly and durably to chemotherapy with procarbazine, lomustine (CCNU), and vincristine (PCV). It was also discovered that co-deletion of chromosome arms 1p and 19q is more commonly observed in oligodendrogliomas (rather than astrocytomas). Early results of phase III trials confirmed that 1p/19q co-deletion was a favorable prognostic marker. Mature results now conclusively demonstrate that co-deletion also predicts longer survival from the addition of PCV chemotherapy to radiotherapy for newly diagnosed disease. However, changes in the treatment landscape, including a preference for deferred radiotherapy, the emergence of temozolomide as a better tolerated chemotherapy regimen, and the discovery of other biomarkers (e.g. IDH mutation and MGMT promoter methylation) that occurred in the interim emphasize the need for earlier, validated, and acceptable trial end points.

Identification of prognostic gene signatures of glioblastoma: a study based on TCGA data analysis

BACKGROUND

The Cancer Genome Atlas (TCGA) project is a large-scale effort with the goal of identifying novel molecular aberrations in glioblastoma (GBM).

METHODS

Here, we describe an in-depth analysis of gene expression data and copy number aberration (CNA) data to classify GBMs into prognostic groups to determine correlates of subtypes that may be biologically significant.

RESULTS

To identify predictive survival models, we searched TCGA in 173 patients and identified 42 probe sets (P = .0005) that could be used to divide the tumor samples into 3 groups and showed a significantly (P = .0006) improved overall survival. Kaplan-Meier plots showed that the median survival of group 3 was markedly longer (127 weeks) than that of groups 1 and 2 (47 and 52 weeks, respectively). We then validated the 42 probe sets to stratify the patients according to survival in other public GBM gene expression datasets (eg, GSE4290 dataset). An overall analysis of the gene expression and copy number aberration using a multivariate Cox regression model showed that the 42 probe sets had a significant (P < .018) prognostic value independent of other variables.

CONCLUSIONS

By integrating multidimensional genomic data from TCGA, we identified a specific survival model in a new prognostic group of GBM and suggest that molecular stratification of patients with GBM into homogeneous subgroups may provide opportunities for the development of new treatment modalities.

Multidomain patient-reported outcomes of irritable bowel syndrome: exploring person-centered perspectives to better understand symptom severity scores

OBJECTIVES

Patient-reported outcomes assessing multiple gastrointestinal symptoms are central to characterizing the therapeutic benefit of novel agents for irritable bowel syndrome (IBS). Common approaches that sum or average responses across different illness components must be unidimensional and have small unique variances to avoid aggregation bias and misinterpretation of clinical data. This study sought to evaluate the unidimensionality of the IBS Symptom Severity Scale (IBS-SSS) and to explore person-centered cluster analytic methods for characterizing multivariate-based patient profiles.

METHODS

Ninety-eight Rome-diagnosed patients with IBS completed the IBS-SSS and a single, global item of symptom severity (UCLA Symptom Severity Scale) at pretreatment baseline of a clinical trial funded by the National Institutes of Health. k-means cluster analyses were performed on participants' symptom severity scores.

RESULTS

The IBS-SSS was not unidimensional. Exploratory cluster analyses revealed four common symptom profiles across five items of the IBS-SSS. One cluster of patients (25%) had elevated scores on pain frequency and bowel dissatisfaction, with less elevated but still high scores on life interference and low pain severity ratings. A second cluster (19%) was characterized by intermediate scores on both pain dimensions but more elevated scores on bowel dissatisfaction. A third cluster (18%) had elevated scores across all IBS-SSS subcomponents. The fourth and the most common cluster (37%) had relatively low scores on all dimensions except bowel dissatisfaction and life interference due to IBS symptoms.

CONCLUSIONS

Patient-reported outcome end points and research on IBS more generally relying on multicomponent assessments of symptom severity should take into account the multidimensional structure of symptoms to avoid aggregation bias and to optimize the sensitivity of detecting treatment effects.

Phase III trial of chemoradiotherapy for anaplastic oligodendroglioma: long-term results of RTOG 9402

PURPOSE

Anaplastic oligodendrogliomas, pure (AO) and mixed (anaplastic oligoastrocytoma [AOA]), are chemosensitive, especially if codeleted for 1p/19q, but whether patients live longer after chemoradiotherapy is unknown.

PATIENTS AND METHODS

Eligible patients with AO/AOA were randomly assigned to procarbazine, lomustine, and vincristine (PCV) plus radiotherapy (RT) versus RT alone. The primary end point was overall survival (OS).

RESULTS

Two hundred ninety-one eligible patients were randomly assigned: 148 to PCV plus RT and 143 to RT. For the entire cohort, there was no difference in median survival by treatment (4.6 years for PCV plus RT v 4.7 years for RT; hazard ratio [HR] = 0.79; 95% CI, 0.60 to 1.04; P = .1). Patients with codeleted tumors lived longer than those with noncodeleted tumors (PCV plus RT: 14.7 v 2.6 years, HR = 0.36, 95% CI, 0.23 to 0.57, P < .001; RT: 7.3 v 2.7 years, HR = 0.40, 95% CI, 0.27 to 0.60, P < .001), and the median survival of those with codeleted tumors treated with PCV plus RT was twice that of patients receiving RT (14.7 v 7.3 years; HR = 0.59; 95% CI, 0.37 to 0.95; P = .03). For those with noncodeleted tumors, there was no difference in median survival by treatment arm (2.6 v 2.7 years; HR = 0.85; 95% CI, 0.58 to 1.23; P = .39). In Cox models that included codeletion status, the adjusted OS for all patients was prolonged by PCV plus RT (HR = 0.67; 95% CI, 0.50 to 0.91; P = .01).

CONCLUSION

For the subset of patients with 1p/19q codeleted AO/AOA, PCV plus RT may be an especially effective treatment, although this observation was derived from an unplanned analysis.

Cetuximab in non-small-cell lung cancer

Cetuximab is a chimeric human-mouse anti-EGF receptor monoclonal antibody. In Phase I studies, no dose-limiting toxicities were observed with cetuximab as a single agent or combined with chemotherapy; pharmacokinetic and pharmacodynamic analyses supported 250 mg/m(2) weekly administration. Skin toxicity, diarrhea and fatigue were the most common toxicities. The positive results obtained in Phase II trials in patients with advanced non-small-cell lung cancer prompted two randomized Phase III trials evaluating cetuximab in addition to first-line chemotherapy. Both trials showed a small benefit in overall survival for the experimental treatment, which was considered insufficient by the EMA for marketing approval. However, a subgroup analysis of the FLEX Phase III trial recently demonstrated a larger survival benefit from the experimental treatment in patients with high immunohistochemical EGF receptor expression. This finding, if confirmed prospectively, could represent a new opportunity for positioning cetuximab into the standard treatment of advanced non-small-cell lung carcinoma.

Molecular biology in breast cancer: should molecular classifiers be assessed by conventional tools or by gene expression arrays?

Breast cancer is a complex disease, with heterogeneous presentations and clinical courses. Standard clinico-pathological parameters, relying on single gene or protein characterization determined with sometimes poorly-reproducible technologies, have shown limitations in the classification of the disease and in the prediction of individual patient outcomes and responses to therapy. Gene-expression profiling has revealed great potential to accurately classify breast cancer and define patient prognosis and prediction to anti-cancer therapy. Nevertheless, the performance of molecular classifiers remains sub-optimal, and both technical and conceptual improvements are needed. It is likely that determining the ideal strategy for tailoring treatment of breast cancer will require a more systematic, structured and multi-dimensional approach than in the past. Besides implementing cutting-edge technologies to detect genetic and epigenetic cancer alterations, the future of breast cancer research will in all probability rely on the innovative and multilevel integration of molecular profiles with clinical parameters of the disease and patient-related factors.

The insulin receptor/insulin-like growth factor receptor family as a therapeutic target in oncology

Over the past decade, encouraging preclinical and early clinical data concerning the relevance of the insulin receptor/insulin-like growth factor (IGF) receptor family to neoplasia led to ambitious clinical trial programs of more than a dozen drug candidates that target these receptors. These candidates include antireceptor antibodies, antiligand antibodies, receptor-specific tyrosine kinase inhibitors, and agents such as picropodophyllin and metformin that have novel mechanisms of action. Several recently reported phase III clinical trials of anti-IGF-I receptor antibodies have been disappointing and are sufficient to disprove the hypothesis that the antibodies tested have large favorable impacts on unselected patients with cancer. However, many of these trials were designed prior to recent insights concerning pathophysiology and predictive biomarkers. Future studies are required, but it will be important to optimize their design rather than simply repeat the approaches taken to date.

Prognostic and predictive significance of plasma HGF and IL-8 in a phase III trial of chemoradiation with or without tirapazamine in locoregionally advanced head and neck cancer

PURPOSE

Hepatocyte growth factor (HGF) is a hypoxia-induced secreted protein that binds to cMet and regulates interleukin (IL)-8 expression. We evaluated the role of circulating HGF and IL-8 as prognostic and predictive factors for efficacy of tirapazamine (TPZ), a hypoxic cell cytotoxin.

EXPERIMENTAL DESIGN

Patients with stages III to IV head and neck cancer were randomized to receive radiotherapy with cisplatin (CIS) or CIS plus TPZ (TPZ/CIS). Eligibility for the substudy included plasma sample availability for HGF and IL-8 assay by ELISA and no major radiation deviations (N = 498). Analyses included adjustment for major prognostic factors. p16(INK4A) staining (human papillomavirus surrogate) was carried out on available tumors. Thirty-nine patients had hypoxia imaging with (18)F-fluoroazomycin arabinoside ((18)FAZA)-positron emission tomography.

RESULTS

Elevated IL-8 level was associated with worse overall survival (OS) irrespective of treatment. There was an interaction between HGF and treatment arm (P = 0.053); elevated HGF was associated with worse OS in the control but not in the TPZ/CIS arm. Similar trends were observed in analyses restricted to p16(INK4A)-negative patients. Four subgroups defined by high and low HGF/IL-8 levels were examined for TPZ effect; the test for interaction with arm was P = 0.099. TPZ/CIS seemed to be beneficial for patients with high HGF and IL-8 but adverse for low HGF and high IL-8. Only HGF correlated with (18)FAZA tumor standard uptake value.

CONCLUSIONS

IL-8 is an independent prognostic factor irrespective of treatment. There is an interaction between HGF and treatment arm. Certain subgroups based on IL-8/HGF levels seemed to do better with TPZ/CIS while others did worse, highlighting the complexity of hypoxia targeting in unselected patients.

The insulin and insulin-like growth factor receptor family in neoplasia: an update

Although several early phase clinical trials raised enthusiasm for the use of insulin-like growth factor I receptor (IGF1R)-specific antibodies for cancer treatment, initial Phase III results in unselected patients have been disappointing. Further clinical studies may benefit from the use of predictive biomarkers to identify probable responders, the use of rational combination therapies and the consideration of alternative targeting strategies, such as ligand-specific antibodies and receptor-specific tyrosine kinase inhibitors. Targeting insulin and IGF signalling also needs to be considered in the broader context of the pathophysiology that relates obesity and diabetes to neoplasia, and the effects of anti-diabetic drugs, including metformin, on cancer risk and prognosis. The insulin and IGFI receptor family is also relevant to the development of PI3K-AKT pathway inhibitors.

The effect of heterogeneity on HIV prevention trials

BACKGROUND

Randomized controlled trials (RCTs) for the prevention of HIV heterosexual acquisition are usually conducted among adult African populations with high heterogeneity in individual risk of infection.

PURPOSE

The objectives were to (a) review how this heterogeneity has been considered when designing and interpreting such RCTs, (b) evaluate its effect on the findings and the statistical power of these trials, and (c) assess the potential advantages of using the crossover design with single failure-time endpoint.

METHODS

Individual-level HIV prevention RCTs conducted in Africa and published in the period 1998-2008 were reviewed. Using Monte Carlo simulations and statistical calculations, we assessed the effect of heterogeneity on the findings and the statistical power of HIV prevention RCTs.

RESULTS

All reviewed RCTs used the parallel design. The heterogeneity in individual risk of infection within study sites was not used for stratification nor generally considered in the design and interpretation of RCTs. Simulations showed that in the context of high HIV incidence, high heterogeneity can lead to a substantial underestimation of the impact of an intervention and reduced statistical power. Calculations demonstrated that the crossover design allowed for similar or better estimation and statistical power. The crossover design has the ethical advantage of sharing the potential benefits and risks of the intervention between participants.

LIMITATIONS

Only trials with two treatment arms and two follow-up periods were modeled. The baseline risk of infection of each participant was assumed to be constant over time and HIV status was assessed at the end of each follow-up period.

CONCLUSIONS

The heterogeneity in individual risk of HIV infection is an underestimated problem which should be taken into account when designing and interpreting RCTs that test prevention methods of HIV heterosexual acquisition in adult African populations with high HIV incidence. When the effects of tested interventions are rapidly reversible, the use of the crossover design should be considered.

Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint

The recent revolution in genomics and the advent of targeted therapies have increased interest in biomarker-defined subgroups of patients who respond to therapy or exhibit specific toxicities. Such biomarker-defined subgroups are also being investigated for non-targeted therapies (e.g. chemotherapy and statins). However, even when the targeting pathway has been identified, a broadly available test to identify the appropriate subgroup will rarely exist prior to the launch of the pivotal phase III trial. Our aim in this paper is to provide guidance for the analysis of a phase III clinical trial with a survival endpoint, in order to ascertain whether a therapy is more effective in the biomarker-positive patients as compared with biomarker-negative patients, when the trial is conducted on the entire population and when there are multiple candidate biomarkers. We studied treatment-by-biomarker interactions in a Weibull regression model. Different permutation procedures, using single-biomarker statistics and novel composite statistics, are proposed in order to control the family-wise error rate accounting for dependence structures among the biomarkers. A simulation study was performed to compare the operational characteristics of the permutation tests under different scenarios. The tests were applied to a phase III trial of adjuvant chemotherapy in early breast cancer, for which 10 biomarkers were measured in tumor samples from 798 patients. These permutation tests can be applied to retrospective biomarker studies and to prospective phase III trials of new drugs for which a few clues are known about the targeting pathway at the start of the trial.

Micro-NMR for rapid molecular analysis of human tumor samples

Although tumor cells obtained from human patients by image-guided intervention are a valuable source for diagnosing cancer, conventional means of analysis are limited. Here, we report the development of a quantitative micro-NMR (nuclear magnetic resonance) system for rapid, multiplexed analysis of human tumors. We implemented the technology in a clinical setting to analyze cells obtained by fine-needle aspirates from suspected lesions in 50 patients and validated the results in an independent cohort of another 20 patients. Single fine-needle aspirates yielded sufficient numbers of cells to enable quantification of multiple protein markers in all patients within 60 min. Moreover, using a four-protein signature, we report a 96% accuracy for establishing a cancer diagnosis, surpassing conventional clinical analyses by immunohistochemistry. Our results also show that protein expression patterns decay with time, underscoring the need for rapid sampling and diagnosis close to the patient bedside. We also observed a surprising degree of heterogeneity in protein expression both across the different patient samples and even within the same tumor, which has important implications for molecular diagnostics and therapeutic drug targeting. Our quantitative point-of-care micro-NMR technique shows potential for cancer diagnosis in the clinic.

Gefitinib in non small cell lung cancer

Gefitinib is an oral, reversible, tyrosine kinase inhibitor of epidermal growth factor receptor (EGFR) that plays a key role in the biology of non small cell lung cancer (NSCLC). Phase I studies indicated that the recommended dose of gefitinib was 250 mg/day. Rash, diarrhea, and nausea were the most common adverse events. The positive results obtained in early phase 2 clinical trials with gefitinib were not confirmed in large phase 3 trials in unselected patients with advanced NSCLC. The subsequent discovery that the presence of somatic mutations in the kinase domain of EGFR strongly correlates with increased responsiveness to EGFR tyrosine kinase inhibitors prompted phase 2 and 3 trials with gefitinib in the first line-treatment of EGFR-mutated NSCLC. The results of these trials have demonstrated the efficacy of gefitinib that can be now considered as the standard first-line treatment of patients with advanced NSCLC harbouring activating EGFR mutations.

ERK phosphorylation predicts synergism between gemcitabine and the epidermal growth factor receptor inhibitor AG1478

BACKGROUND

Clinical trials combining epidermal growth factor receptor (EGFR) inhibitors with gemcitabine-based chemotherapy in non-small cell lung cancer (NSCLC) have not produced a survival advantage. This may be caused by antagonism between the two drugs or mutations that promote such, possibly RAS mutation. Furthermore, ERK, a critical growth regulator downstream of RAS, may play a role. This study aimed to explore the relationship between ERK, synergy/antagonism and cell cycle arrest in combination treatment.

METHODS

A549 (mutant KRAS), H322 (wildtype KRAS) and siRNA-mediated KRAS knockdown A549 were treated with gemcitabine and/or the EGFR inhibitor AG1478 and analyzed with median effect analysis. Cell cycle distribution and ERK phosphorylation were assessed using flow cytometry and ELISA, respectively. Effect on cytotoxicity after ERK inhibition by U0126 was also assessed.

RESULTS

Cytotoxic interaction was dose dependent with antagonism at high dose AG1478. G1 arrest was observed with both high dose AG1478 and high dose gemcitabine and therefore was inconsistently associated with antagonism. Furthermore, ERK phosphorylation was increased by gemcitabine and its suppression by AG1478 was related to antagonism particularly in H322. ERK's effect in antagonism was further confirmed by using U0126. Greater antagonism was observed in the KRAS mutant cell line and KRAS knockdown by siRNA resulted in increased sensitivity to AG1478 as well as combination treatment.

CONCLUSION

Our findings are consistent with a model in which ERK phosphorylation favors synergy and the outcome depends on the balance between gemcitabine-induced and AG1478-inhibited ERK phosphorylation. KRAS mutation confers resistance to AG1478 as well as combination treatment.

Classification and Regression Trees on Aggregate Data Modeling: An Application in Acute Myocardial Infarction

Cardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival. The study objective was to determine whether accounting for hospital pathways in the selection of prognostic factors of one-year survival after acute myocardial infarction (AMI) provided a more informative analysis than that obtained by the use of a standard regression tree analysis (CART method). Information on AMI was collected for 1095 hospitalized patients over an 18-month period. The construction of pathways followed by patients produced symbolic-valued observations requiring a symbolic regression tree analysis. This analysis was compared with the standard CART analysis using patients as statistical units described by standard data selected TIMI score as the primary predictor variable. For the 1011 (84, resp.) patients with a lower (higher) TIMI score, the pathway variable did not appear as a diagnostic variable until the third (second) stage of the tree construction. For an ecological analysis, again TIMI score was the first predictor variable. However, in a symbolic regression tree analysis using hospital pathways as statistical units, the type of pathway followed was the key predictor variable, showing in particular that pathways involving early admission to cardiology units produced high one-year survival rates.

Translating cancer research into targeted therapeutics

The emphasis in cancer drug development has shifted from cytotoxic, non-specific chemotherapies to molecularly targeted, rationally designed drugs promising greater efficacy and less side effects. Nevertheless, despite some successes drug development remains painfully slow. Here, we highlight the issues involved and suggest ways in which this process can be improved and expedited. We envision an increasing shift to integrated cancer research and biomarker-driven adaptive and hypothesis testing clinical trials. The goal is the development of specific cancer medicines to treat the individual patient, with treatment selection being driven by a detailed understanding of the genetics and biology of the patient and their cancer.

Development of a validated immunofluorescence assay for γH2AX as a pharmacodynamic marker of topoisomerase I inhibitor activity

PURPOSE

Phosphorylated histone H2AX (γH2AX) serves as a biomarker for formation of DNA double-strand break repair complexes. A quantitative pharmacodynamic immunofluorescence assay for γH2AX was developed, validated, and tested in human tumor xenograft models with the use of clinically relevant procedures.

EXPERIMENTAL DESIGN

The γH2AX immunofluorescence assay uses a novel data quantitation and image processing algorithm to determine the extent of nuclear-specific γH2AX staining in tumor needle biopsies and hair follicles collected from mice bearing topotecan-responsive A375 xenografts. After method validation with the topoisomerase I (Top1) inhibitor topotecan, the assay was used to compare pharmacodynamic properties of three structurally related indenoisoquinoline Top1 inhibitors.

RESULTS

γH2AX response to topotecan was quantified over a 60-fold dose range (0.016-1.0 times the murine single-dose maximum tolerated dose), and significant pharmacodynamic response was measured at the mouse equivalent of the 1.5 mg/m(2) clinical dose as well as the lowest dose tested. Responses were within a time window amenable for biopsy collection in clinical trials. These studies enabled characterization of dose and time responses for three indenoisoquinolines, resulting in selection of two for clinical evaluation. γH2AX response to Top1 inhibitors in hair follicles was also observable above a minimal dose threshold.

CONCLUSIONS

Our γH2AX assay is sufficiently accurate and sensitive to quantify γH2AX in tumor samples and will be used in correlative studies of two indenoisoquinolines in a phase I clinical trial at the National Cancer Institute. Data suggest that hair follicles may potentially serve as a surrogate tissue to evaluate tumor γH2AX response to Top1 inhibitors.

A microfluidic platform for systems pathology: multiparameter single-cell signaling measurements of clinical brain tumor specimens

The clinical practice of oncology is being transformed by molecular diagnostics that will enable predictive and personalized medicine. Current technologies for quantitation of the cancer proteome are either qualitative (e.g., immunohistochemistry) or require large sample sizes (e.g., flow cytometry). Here, we report a microfluidic platform-microfluidic image cytometry (MIC)-capable of quantitative, single-cell proteomic analysis of multiple signaling molecules using only 1,000 to 2,800 cells. Using cultured cell lines, we show simultaneous measurement of four critical signaling proteins (EGFR, PTEN, phospho-Akt, and phospho-S6) within the oncogenic phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway. To show the clinical application of the MIC platform to solid tumors, we analyzed a panel of 19 human brain tumor biopsies, including glioblastomas. Our MIC measurements were validated by clinical immunohistochemistry and confirmed the striking intertumoral and intratumoral heterogeneity characteristic of glioblastoma. To interpret the multiparameter, single-cell MIC measurements, we adapted bioinformatic methods including self-organizing maps that stratify patients into clusters that predict tumor progression and patient survival. Together with bioinformatic analysis, the MIC platform represents a robust, enabling in vitro molecular diagnostic technology for systems pathology analysis and personalized medicine.

Molecular characterisation of ERG, ETV1 and PTEN gene loci identifies patients at low and high risk of death from prostate cancer

BACKGROUND

The discovery of ERG/ETV1 gene rearrangements and PTEN gene loss warrants investigation in a mechanism-based prognostic classification of prostate cancer (PCa). The study objective was to evaluate the potential clinical significance and natural history of different disease categories by combining ERG/ETV1 gene rearrangements and PTEN gene loss status.

METHODS

We utilised fluorescence in situ hybridisation (FISH) assays to detect PTEN gene loss and ERG/ETV1 gene rearrangements in 308 conservatively managed PCa patients with survival outcome data.

RESULTS

ERG/ETV1 gene rearrangements alone and PTEN gene loss alone both failed to show a link to survival in multivariate analyses. However, there was a strong interaction between ERG/ETV1 gene rearrangements and PTEN gene loss (P<0.001). The largest subgroup of patients (54%), lacking both PTEN gene loss and ERG/ETV1 gene rearrangements comprised a 'good prognosis' population exhibiting favourable cancer-specific survival (85.5% alive at 11 years). The presence of PTEN gene loss in the absence of ERG/ETV1 gene rearrangements identified a patient population (6%) with poorer cancer-specific survival that was highly significant (HR=4.87, P<0.001 in multivariate analysis, 13.7% survival at 11 years) when compared with the 'good prognosis' group. ERG/ETV1 gene rearrangements and PTEN gene loss status should now prospectively be incorporated into a predictive model to establish whether predictive performance is improved.

CONCLUSIONS

Our data suggest that FISH studies of PTEN gene loss and ERG/ETV1 gene rearrangements could be pursued for patient stratification, selection and hypothesis-generating subgroup analyses in future PCa clinical trials and potentially in patient management.

The macrophage colony-stimulating factor 1 response signature in breast carcinoma

PURPOSE

Macrophages play an important role in breast carcinogenesis. The pathways that mediate the macrophage contribution to breast cancer and the heterogeneity that exists within macrophages are incompletely understood. Macrophage colony-stimulating factor 1 (CSF1) is the primary regulator of tissue macrophages. The purpose of this study was to define a novel CSF1 response signature and to evaluate its clinical and biological significance in breast cancer.

EXPERIMENTAL DESIGN

We defined the CSF1 response signature by identifying genes overexpressed in tenosynovial giant cell tumor and pigmented villonodular synovitis (tumors composed predominantly of macrophages recruited in response to the overexpression of CSF1) compared with desmoid-type fibromatosis and solitary fibrous tumor. To characterize the CSF1 response signature in breast cancer, we analyzed the expression of CSF1 response signature genes in eight published breast cancer gene expression data sets (n = 982) and did immunohistochemistry and in situ hybridization for CSF1 response genes on a breast cancer tissue microarray (n = 283).

RESULTS

In both the gene microarray and tissue microarray analyses, a consistent subset (17-25%) of breast cancers shows the CSF1 response signature. The signature is associated with higher tumor grade, decreased expression of estrogen receptor, decreased expression of progesterone receptor, and increased TP53 mutations (P < 0.001).

CONCLUSIONS

Our data show that the CSF1 response signature is consistently seen in a subset of breast carcinomas and correlates with biological features of the tumor. Our findings provide insight into macrophage biology and may facilitate the development of personalized therapy for patients most likely to benefit from CSF1-targeted treatments.

Targeting targeted agents: open issues for clinical trial design

Molecularly targeted agents for the treatment of solid tumors had entered the market in the last 5 years, with a great impact upon both the scientific community and the society. Many randomized phase III trials conducted in recent years with new targeted agents, despite previous data coming from preclinical research and from phase II trials were often promising, have produced disappointingly negative results. Some other trials have actually met their primary endpoint, demonstrating a statistically significant result favouring the experimental treatment. Unfortunately, with a few relevant exceptions, this advantage is often small, if not negligible, in absolute terms. The difference between statistical significance and clinical relevance should always be considered when translating clinical trials' results in the practice. The reason why this 'revolution' did not significantly impact on cancer treatment to displace chemotherapy from the patient' bedside is in part due to complicated, and in many cases, unknown, mechanisms of action of such drugs; indeed, the traditional way the clinical investigators were used to test the efficacy of 'older' chemotherapeutics, has become 'out of date' from the methodological perspective. As these drugs should be theoretically tailored upon featured bio-markers expressed by the patients, the clinical trial design should follow new rules based upon stronger hypotheses than those developed so far. Indeed, the early phases of basic and clinical drug development are crucial in the correct process which is able to correctly identify the target (when present). Targeted trial designs can result in easier studies, with less, better selected, and supported by stronger proofs of response evidences, patients, in order to not waste time and resources.

Effective incorporation of biomarkers into phase II trials

The incorporation of biomarkers into the drug development process will improve understanding of how new therapeutics work and allow for more accurate identification of patients who will benefit from those therapies. Strategically planned biomarker evaluations in phase II studies may allow for the design of more efficient phase III trials and better screening of therapeutics for entry into phase III development, hopefully leading to increased chances of positive phase III trial results. Some examples of roles that a biomarker can play in a phase II trial include predictor of response or resistance to specific therapies, patient enrichment, correlative endpoint, or surrogate endpoint. Considerations for using biomarkers most effectively in these roles are discussed in the context of several examples. The substantial technical, logistic, and ethical challenges that can be faced when trying to incorporate biomarkers into phase II trials are also addressed. A rational and coordinated approach to the inclusion of biomarker studies throughout the drug development process will be the key to attaining the goal of personalized medicine.

Phase 0 clinical trials: recommendations from the Task Force on Methodology for the Development of Innovative Cancer Therapies

The Methodology for the Development of Innovative Cancer Therapies (MDICT) task force has been established as an expert forum to develop practical guidance on the development of innovative anticancer agents, in particular targeted agents. The task force recently addressed the utility, design and application of Phase 0 clinical trials in anticancer drug development. It was concluded that the role of non-therapeutic Phase 0 trials is controversial for several reasons, including the lack of clinical benefit for participating patients. However, it was recognised that Phase 0 trials provide an opportunity to generate essential human pharmacokinetic and pharmacodynamic data earlier in the drug development process, which could be a major advantage in the design and decision making concerning further clinical development of an agent. Construction of a 'decision chart' was highly recommended to assist investigators and sponsors in determining whether an agent is suitable for evaluation in a Phase 0 trial.