Prognostic Significance of TRAIL Signaling Molecules in Stage II and III Colorectal Cancer

Purpose: We previously found that cellular FLICE-inhibitory protein (c-FLIP), caspase 8, and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) receptor 2 (DR5) are major regulators of cell viability and chemotherapy-induced apoptosis in colorectal cancer. In this study, we determined the prognostic significance of c-FLIP, caspase 8, TRAIL and DR5 expression in tissues from patients with stage II and III colorectal cancer.

Experimental Design: Tissue microarrays were constructed from matched normal and tumor tissue derived from patients (n = 253) enrolled in a phase III trial of adjuvant 5-fluorouracil–based chemotherapy versus postoperative observation alone. TRAIL, DR5, caspase 8, and c-FLIP expression levels were determined by immunohistochemistry.

Results: Colorectal tumors displayed significantly higher expression levels of c-FLIP (P < 0.001), caspase 8 (P = 0.01), and DR5 (P < 0.001), but lower levels of TRAIL (P < 0.001) compared with matched normal tissue. In univariate analysis, higher TRAIL expression in the tumor was associated with worse overall survival (P = 0.026), with a trend to decreased relapse-free survival (RFS; P = 0.06), and higher tumor c-FLIP expression was associated with a significantly decreased RFS (P = 0.015). Using multivariate predictive modeling for RFS in all patients and including all biomarkers, age, treatment, and stage, we found that the model was significant when the mean tumor c-FLIP expression score and disease stage were included (P < 0.001). As regards overall survival, the overall model was predictive when both TRAIL expression and disease stage were included (P < 0.001).

Conclusions: High c-FLIP and TRAIL expression may be independent adverse prognostic markers in stage II and III colorectal cancer and might identify patients most at risk of relapse.

Biomarkers of fruit and vegetable intake in Human intervention studies a systematic review

Observational evidence consistently shows that consumption of a diet rich in fruit and vegetables may offer protection against diseases such as cardiovascular disease and cancer. Assessment of dietary intake is complex and prone to many sources of error. More objective biomarkers of fruit and vegetable intake are therefore of interest. The aim of this review is to examine the usefulness of the main biomarkers of fruit and vegetable intake to act as objective indicators of compliance in dietary intervention studies. A comprehensive search of the literature was conducted using six databases. Suitable papers were selected and relevant data extracted. The papers were categorized into 3 sub-groups: whole diet interventions; mixed fruit and vegetable interventions; and studies involving individual varieties of fruits or vegetables. Ninety-six studies were included in the review. Overall, the most commonly measured, and most consistently responsive, biomarkers were the carotenoids and vitamin C. Based on the results of this systematic review, it remains prudent to measure a panel of biomarkers in fruit and vegetable intervention studies. The only possible exception to this is “fruit only” intervention studies where assessment of vitamin C alone may suffice.

Progressive lung cancer determined by expression profiling and transcriptional regulation

Clinically, our ability to predict disease outcome for patients with early stage lung cancer is currently poor. To address this issue, tumour specimens were collected at surgery from non-small cell lung cancer (NSCLC) patients as part of the European Early Lung Cancer (EUELC) consortium. The patients were followed-up for three years post-surgery and patients who suffered progressive disease (PD, tumour recurrence, metastasis or a second primary) or remained disease-free (DF) during follow-up were identified. RNA from both tumour and adjacent-normal lung tissue was extracted from patients and subjected to microarray expression profiling. These samples included 36 adenocarcinomas and 23 squamous cell carcinomas from both PD and DF patients. The microarray data was subject to a series of systematic bioinformatics analyses at gene, network and transcription factor levels. The focus of these analyses was 2-fold: firstly to determine whether there were specific biomarkers capable of differentiating between PD and DF patients, and secondly, to identify molecular networks which may contribute to the progressive tumour phenotype. The experimental design and analyses performed permitted the clear differentiation between PD and DF patients using a set of biomarkers implicated in neuroendocrine signalling and allowed the inference of a set of transcription factors whose activity may differ according to disease outcome. Potential links between the biomarkers, the transcription factors and the genes p21/CDKN1A and Myc, which have previously been implicated in NSCLC development, were revealed by a combination of pathway analysis and microarray meta-analysis. These findings suggest that neuroendocrine-related genes, potentially driven through p21/CDKN1A and Myc, are closely linked to whether or not a NSCLC patient will have poor clinical outcome.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

Developing mRNA-based biomarkers from formalin-fixed paraffin-embedded tissue

Cancer is a complex and heterogeneous disease which is one of the leading causes of death in Western civilisations. Thus, oncology is viewed as a primary focus for personalized medicine. It is recognised that cancer treatment needs to be better tailored in order to improve patient outcome. Patient tumor samples will be required to characterize cancer at a molecular level and identify where there may be disease subgroups that should be treated differently. The use of formalin-fixed paraffin-embedded tissue is important for enabling such studies. In this report, we focus on the challenges that have been faced to date along with the technological developments that have now made this possible. We also highlight the impact this may have on drug and diagnostic development.

Molecular mapping the presence of druggable targets in preinvasive and precursor breast lesions:a comprehensive review of biomarkers related to therapeutic interventions

The analysis of clinical breast samples using biomarkers is integral to current breast cancer management. Currently, a limited number of targeted therapies are standard of care in breast cancer treatment. However, these targeted therapies are only suitable for a subset of patients and resistance may occur. Strategies to prevent the occurrence of invasive lesions are required to reduce the morbidity and mortality associated with the development of cancer. In theory, application of targeted therapies to pre-invasive lesions will prevent their progression to invasive lesions with full malignant potential. The diagnostic challenge for pathologists is to make interpretative decisions on early detected pre-invasive lesions. Overall, only a small proportion of these pre-invasive lesions will progress to invasive carcinoma and morphological assessment is an imprecise and subjective means to differentiate histologically identical lesions with varying malignant potential. Therefore differential biomarker analysis in pre-invasive lesions may prevent overtreatment with surgery and provide a predictive indicator of response to therapy. There follows a review of established and emerging potential druggable targets in pre-invasive lesions and correlation with lesion morphology.

Impact of oncogenic driver mutations on feedback between the PI3K and MEK pathways in cancer cells

Inhibition of the PI3K (phosphoinositide 3-kinase)/Akt/mTORC1 (mammalian target of rapamycin complex 1) and Ras/MEK [MAPK (mitogen-activated protein kinase)/ERK (extracellular-signal-regulated kinase) kinase]/ERK pathways for cancer therapy has been pursued for over a decade with limited success. Emerging data have indicated that only discrete subsets of cancer patients have favourable responses to these inhibitors. This is due to genetic mutations that confer drug insensitivity and compensatory mechanisms. Therefore understanding of the feedback mechanisms that occur with respect to specific genetic mutations may aid identification of novel biomarkers that predict patient response. In the present paper, we show that feedback between the PI3K/Akt/mTORC1 and Ras/MEK/ERK pathways is cell-line-specific and highly dependent on the activating mutation of K-Ras or overexpression c-Met. We found that cell lines exhibited differential signalling and apoptotic responses to PD184352, a specific MEK inhibitor, and PI103, a second-generation class I PI3K inhibitor. We reveal that feedback from the PI3K/Akt/mTORC1 to the Ras/MEK/ERK pathway is present in cancer cells harbouring either K-Ras activating mutations or amplification of c-Met but not the wild-type counterparts. Moreover, we demonstrate that inhibition of protein phosphatase activity by OA (okadaic acid) restored PI103-mediated feedback in wild-type cells. Together, our results demonstrate a novel mechanism for feedback between the PI3K/Akt/mTORC1 and the Ras/MEK/ERK pathways that only occurs in K-Ras mutant and c-Met amplified cells but not the isogenic wild-type cells through a mechanism that may involve inhibition of a specific endogenous phosphatase(s) activity. We conclude that monitoring K-Ras and c-Met status are important biomarkers for determining the efficacy of PI103 and other PI3K/Akt inhibitors in cancer therapy.

PTGS2 (Cyclooxygenase-2) expression and survival among colorectal cancer patients: A systematic review

Background: Studies have examined whether tumor expression of PTGS2 (also known as COX-2), an enzyme inhibited by nonsteroidal anti-inflammatory drugs such as aspirin, is associated with prognosis in patients with colorectal cancer. However, results to date have been mixed. Methods: Using terms for PTGS2 and colorectal cancer, the Medline, Embase, and Web of Science databases were systematically searched for studies published, in any language, until December 2011. Random effects meta-analyses were used to calculate pooled HRs [95% confidence intervals (CI)] for the association between PTGS2 expression and tumor recurrence, colorectal cancer-specific survival, and overall survival. Results: In total, 29 studies, which had prognostic data on 5,648 patients, met the inclusion criteria. PTGS2- positive patients were at an increased risk of tumor recurrence (n = 9 studies; HR, 2.79; 95% CI, 1.76-4.41; P <0.001) and had poorer colorectal cancer-specific survival (n = 7; HR, 1.36; 95% CI, 1.02-1.82; P = 0.04). However, there was funnel plot asymmetry, possibly due to publication bias, for the association with cancerspecific survival but less so for recurrence. PTGS2 expression was not associated with overall survival [(n= 16; pooled unadjusted HR, 1.30; 95% CI, 0.94-1.79; P=0.11) and (n=9; pooled adjusted HR, 1.02; 95% CI, 0.72-1.45; P = 0.91)]. Conclusions: PTGS2 expression was associated with an increased risk of tumor recurrence and poorer colorectal cancer-specific survival but not overall survival among patients with colorectal cancer. However, confounding by tumor characteristics such as tumor stage seems likely. Impact: There is insufficient evidence to recommend PTGS2 expression as a prognostic marker in patients with colorectal cancer. Furthermore, studies providing adjusted results are required. © 2013 AACR.

Evaluating Many Treatments and Biomarkers in Oncology: A New Design

There is a pressing need for more-efficient trial designs for biomarker-stratified clinical trials. We suggest a new approach to trial design that links novel treatment evaluation with the concurrent evaluation of a biomarker within a confirmatory phase II/III trial setting. We describe a new protocol using this approach in advanced colorectal cancer called FOCUS4. The protocol will ultimately answer three research questions for a number of treatments and biomarkers: (1) After a period of first-line chemotherapy, do targeted novel therapies provide signals of activity in different biomarker-defined populations? (2) If so, do these definitively improve outcomes? (3) Is evidence of activity restricted to the biomarker-defined groups? The protocol randomizes novel agents against placebo concurrently across a number of different biomarker-defined population-enriched cohorts: BRAF mutation; activated AKT pathway: PI3K mutation/absolute PTEN loss tumors; KRAS and NRAS mutations; and wild type at all the mentioned genes. Within each biomarker-defined population, the trial uses a multistaged approach with flexibility to adapt in response to planned interim analyses for lack of activity. FOCUS4 is the first test of a protocol that assigns all patients with metastatic colorectal cancer to one of a number of parallel population-enriched, biomarker-stratified randomized trials. Using this approach allows questions regarding efficacy and safety of multiple novel therapies to be answered in a relatively quick and efficient manner, while also allowing for the assessment of biomarkers to help target treatment.

Cancer drug resistance:an evolving paradigm

Resistance to chemotherapy and molecularly targeted therapies is a major problem facing current cancer research. The mechanisms of resistance to 'classical' cytotoxic chemotherapeutics and to therapies that are designed to be selective for specific molecular targets share many features, such as alterations in the drug target, activation of prosurvival pathways and ineffective induction of cell death. With the increasing arsenal of anticancer agents, improving preclinical models and the advent of powerful high-throughput screening techniques, there are now unprecedented opportunities to understand and overcome drug resistance through the clinical assessment of rational therapeutic drug combinations and the use of predictive biomarkers to enable patient stratification.

A feasibility study testing four hypotheses with phase II outcomes in advanced colorectal cancer (MRC FOCUS3): a model for randomised controlled trials in the era of personalised medicine?

Background: Molecular characteristics of cancer vary between individuals. In future, most trials will require assessment of biomarkers to allocate patients into enriched populations in which targeted therapies are more likely to be effective. The MRC FOCUS3 trial is a feasibility study to assess key elements in the planning of such studies.

Patients and methods: Patients with advanced colorectal cancer were registered from 24 centres between February 2010 and April 2011. With their consent, patients' tumour samples were analysed for KRAS/BRAF oncogene mutation status and topoisomerase 1 (topo-1) immunohistochemistry. Patients were then classified into one of four molecular strata; within each strata patients were randomised to one of two hypothesis-driven experimental therapies or a common control arm (FOLFIRI chemotherapy). A 4-stage suite of patient information sheets (PISs) was developed to avoid patient overload.

Results: A total of 332 patients were registered, 244 randomised. Among randomised patients, biomarker results were provided within 10 working days (w.d.) in 71%, 15 w.d. in 91% and 20 w.d. in 99%. DNA mutation analysis was 100% concordant between two laboratories. Over 90% of participants reported excellent understanding of all aspects of the trial. In this randomised phase II setting, omission of irinotecan in the low topo-1 group was associated with increased response rate and addition of cetuximab in the KRAS, BRAF wild-type cohort was associated with longer progression-free survival.

Conclusions: Patient samples can be collected and analysed within workable time frames and with reproducible mutation results. Complex multi-arm designs are acceptable to patients with good PIS. Randomisation within each cohort provides outcome data that can inform clinical practice.

Multiple mycotoxin exposure determined by urinary biomarkers in rural subsistence farmers in the former Transkei, South Africa

Subsistence farmers are exposed to a range of mycotoxins. This study applied novel urinary multi-mycotoxin LC-MS/MS methods to determine multiple exposure biomarkers in the high oesophageal cancer region, Transkei, South Africa. Fifty-three female participants donated part of their maize-based evening meal and first void morning urine, which was analysed both with sample clean-up (single and multi-biomarker) and by a 'dilute-and-shoot' multi-biomarker method. Results were corrected for recovery with LOD for not detected. A single biomarker method detected fumonisin B1 (FB1) (87% incidence; mean±standard deviation 0.342±0.466 ng/mg creatinine) and deoxynivalenol (100%; mean 20.4±49.4 ng/mg creatinine) after hydrolysis with β-glucuronidase. The multi-biomarker 'dilute-and-shoot' method indicated deoxynivalenol-15-glucuronide was predominantly present. A multi-biomarker method with β-glucuronidase and immunoaffinity clean-up determined zearalenone (100%; 0.529±1.60 ng/mg creatinine), FB1 (96%; 1.52±2.17 ng/mg creatinine), α-zearalenol (92%; 0.614±1.91 ng/mg creatinine), deoxynivalenol (87%; 11.3±27.1 ng/mg creatinine), β-zearalenol (75%; 0.702±2.95 ng/mg creatinine) and ochratoxin A (98%; 0.041±0.086 ng/mg creatinine). These demonstrate the value of multi-biomarker methods in measuring exposures in populations exposed to multiple mycotoxins. This is the first finding of urinary deoxynivalenol, zearalenone, their conjugates, ochratoxin A and zearalenols in Transkei.

Statin Use and Survival from Lung Cancer: A Population-Based Cohort Study

Background: Preclinical evidence from lung cancer cell lines and animal models suggest that statins could have anticancer properties. We investigated whether statin users had reduced risk of cancer-specific mortality in a population based cohort of lung cancer patients.
Methods: Newly diagnosed lung cancer patients, from 1998 to 2009, were identified from English cancer registry data and linked to the UK Clinical Practice Research Datalink, providing prescription records, and to Office of National Statistics mortality data up to 2012. Cox regression models were used to calculate hazard ratios (HR) for cancer-specific mortality and 95% confidence intervals (CIs) by statin use before and after diagnosis and to adjust these HRs for potential confounders.
Results: In 3,638 lung cancer patients, there was some evidence that statin use after diagnosis was associated with reduced lung cancer-specific mortality (adjusted HR=0.89, 95% CI 0.78, 1.02; P=0.09). Associations were more marked after 12 prescriptions (adjusted HR=0.81, 95% CI 0.67, 0.98; P=0.03) and when lipophilic statins were investigated (adjusted HR=0.81, 95% CI 0.70, 0.94; P=0.01) but were attenuated in some sensitivity analyses. Furthermore, in 11,051 lung cancer patients, statin use before diagnosis was associated with reduced lung cancer-specific mortality (adjusted HR=0.88, 95% CI, 0.83, 0.93; P<0.001).
Conclusions: There was some evidence that lung cancer patients who used statins, and particularly simvastatin, had reduced rates of cancer-specific mortality.
 Impact: These findings should first be confirmed in observational studies, but provide some support for conducting randomized controlled trials of simvastatin as adjuvant cancer therapy in lung cancer patients.