Validation of new cancer biomarkers: a position statement from the European group on tumor markers

Circulating tumor DNA (ctDNA): can it be used as a pan-cancer early detection test?

Circulating tumor DNA (ctDNA, DNA shed by cancer cells) is emerging as one of the most transformative cancer biomarkers discovered to-date. Although potentially useful at all the phases of cancer detection and patient management, one of its most exciting possibilities is as a relatively noninvasive pan-cancer screening test. Preliminary findings with ctDNA tests such as Galleri or CancerSEEK suggest that they have high specificity (> 99.0%) for malignancy. Their sensitivity varies depending on the type of cancer and stage of disease but it is generally low in patients with stage I disease. A major advantage of ctDNA over existing screening strategies is the potential ability to detect multiple cancer types in a single test. A limitation of most studies published to-date is that they are predominantly case-control investigations that were carried out in patients with a previous diagnosis of malignancy and that used apparently healthy subjects as controls. Consequently, the reported sensitivities, specificities and positive predictive values might be lower if the tests are used for screening in asymptomatic populations, that is, in the population where these tests are likely be employed. To demonstrate clinical utility in an asymptomatic population, these tests must be shown to reduce cancer mortality without causing excessive overdiagnosis in a large randomized prospective randomized trial. Such trials are currently ongoing for Galleri and CancerSEEK.

A preliminary study on the reference intervals of serum tumor marker in apparently healthy elderly population in southwestern China using real-world data

BACKGROUND

The aim is to establish and verify reference intervals (RIs) for serum tumor markers for an apparently healthy elderly population in Southwestern China using an indirect method.

METHODS

Data from 35,635 apparently healthy elderly individuals aged 60 years and above were obtained in West China Hospital from April 2020 to December 2021. We utilized the Box-Cox conversion combined with the Tukey method to normalize the data and eliminate outliers. Subgroups are divided according to gender and age to examine the division of RIs. The Z-test was used to compare differences between groups, and 95% distribution RIs were calculated using a nonparametric method.

RESULTS

In the study, we observed that the RIs for serum ferritin and Des-γ-carboxy prothrombin (DCP) were wider for men, ranging from 64.18 to 865.80 ng/ml and 14.00 to 33.00 mAU/ml, respectively, compared to women, whose ranges were 52.58 to 585.88 ng/ml and 13.00 to 29.00 mAU/ml. For other biomarkers, the overall RIs were established as follows: alpha-fetoprotein (AFP) 0-6.75 ng/ml, carcinoembryonic antigen (CEA) 0-4.85 ng/ml, carbohydrate antigen15-3 (CA15-3) for females 0-22.00 U/ml, carbohydrate antigen19-9 (CA19-9) 0-28.10 U/ml, carbohydrate antigen125 (CA125) 0-20.96 U/ml, cytokeratin 19 fragment (CYFRA21-1) 0-4.66 U/ml, neuron-specific enolase (NSE) 0-19.41 ng/ml, total and free prostate-specific antigens (tPSA and fPSA) for males 0-5.26 ng/ml and 0-1.09 ng/ml. The RIs for all these biomarkers have been validated through our rigorous processes.

CONCLUSION

This study preliminarily established 95% RIs for an apparently healthy elderly population in Southwestern China. Using real-world data and an indirect method, simple and reliable RIs for an elderly population can be both established and verified, which are suitable for application in various clinical laboratories.

Correlation between long non-coding RNA MAFG-AS1 and cancer prognosis: a meta-analysis

Background

MAF transcription factor G antisense RNA 1 (MAFG-AS1), a novel long non-coding RNA discovered recently, was proved to be useful in predicting malignancy prognosis. Nevertheless, its association with cancer prognosis has been inconsistent. Therefore, this meta-analysis aimed to explore the clinicopathological and prognostic significance of MAFG-AS1 in diverse carcinomas.

Methods

Studies focused on MAFG-AS1 expression as a prognostic role in cancers were thoroughly searched in six electronic databases. The value of MAFG-AS1 in malignancies was assessed by hazard ratios (HRs) or odds ratios (ORs). Additionally, the GEPIA database was utilized to further strengthen our conclusion.

Results

A total of 15 studies involving 1187 cases and nine types of cancers were recruited into this meta-analysis. High MAFG-AS1 expression was significantly related to advanced tumor stage (OR = 0.52, 95%CI [0.39, 0.69], P < 0.00001), earlier lymph node metastasis (OR = 3.62, 95%CI [2.19, 5.99], P < 0.00001), worse tumor differentiation (OR = 0.64, 95%CI [0.43, 0.95], P = 0.03), and poor overall survival (HR = 1.94, 95%CI [1.72, 2.19], P < 0.00001). No significant heterogeneity and publication bias was detected across studies. Meanwhile, MAFG-AS1 was significantly elevated in ten kinds of cancers based on the validation of the GEPIA database.

Conclusion

The results of this meta-analysis indicated that high MAFG-AS1 expression is dramatically correlated with unfavorable prognosis in cancers. MAFG-AS1 may be served as a promising biomarker for malignancies.

Targeting TRAIL Death Receptors in Triple-Negative Breast Cancers: Challenges and Strategies for Cancer Therapy

The tumor necrosis factor (TNF) superfamily member TNF-related apoptosis-inducing ligand (TRAIL) induces apoptosis in cancer cells via death receptor (DR) activation with little toxicity to normal cells or tissues. The selectivity for activating apoptosis in cancer cells confers an ideal therapeutic characteristic to TRAIL, which has led to the development and clinical testing of many DR agonists. However, TRAIL/DR targeting therapies have been widely ineffective in clinical trials of various malignancies for reasons that remain poorly understood. Triple negative breast cancer (TNBC) has the worst prognosis among breast cancers. Targeting the TRAIL DR pathway has shown notable efficacy in a subset of TNBC in preclinical models but again has not shown appreciable activity in clinical trials. In this review, we will discuss the signaling components and mechanisms governing TRAIL pathway activation and clinical trial findings discussed with a focus on TNBC. Challenges and potential solutions for using DR agonists in the clinic are also discussed, including consideration of the pharmacokinetic and pharmacodynamic properties of DR agonists, patient selection by predictive biomarkers, and potential combination therapies. Moreover, recent findings on the impact of TRAIL treatment on the immune response, as well as novel strategies to address those challenges, are discussed.

Robust Preanalytical Performance of Soluble PD-1, PD-L1 and PD-L2 Assessed by Sensitive ELISAs in Blood

The interaction between programmed death-1 receptor PD-1 and its ligands PD-L1 and PD-L2 is involved in self-tolerance, immune escape of cancer, cardiovascular diseases, and COVID-19. As blood-based protein markers they bear great potential to improve oncoimmunology research and monitoring of anti-cancer immunotherapy. A variety of preanalytical conditions were tested to assure high quality plasma sample measurements: (i) different time intervals and storage temperatures before and after blood centrifugation; (ii) fresh samples and repeated freeze–thaw-cycles; (iii) different conditions of sample preparation before measurement. Concerning short-term stability, acceptable recoveries for PD-1 between 80 and 120% were obtained when samples were kept up to 24 h at 4 and 25 °C before and after blood centrifugation. Similarly, recoveries for PD-L2 were acceptable for 24 h at 4 °C and 6 h at 25 °C before blood centrifugation and up to 24 h at 4 and 25 °C after centrifugation. Variations for PD-L1 were somewhat higher, however, at very low signal levels. Sample concentrations (ng/mL) were neither affected by the freezing process nor by repeated freeze–thaw cycles with coefficients of variation for PD-1: 9.1%, PD-L1 6.8%, and PD-L2 4.8%. All three biomarkers showed good stability regarding preanalytic conditions of sample handling enabling reliable and reproducible quantification in oncoimmunology research and clinical settings of anti-cancer immunotherapy.

Practical application of European biological variation combined with Westgard Sigma Rules in internal quality control

OBJECTIVES

Westgard Sigma Rules is a statistical tool available for quality control. Biological variation (BV) can be used to set analytical performance specifications (APS). The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) regularly updates BV data. However, few studies have used robust BV data to determine quality goals and design a quality control strategy for tumor markers. The aim of this study was to derive APS for tumor markers from EFLM BV data and apply Westgard Sigma Rules to establish internal quality control (IQC) rules.

METHODS

Precision was calculated from IQC data, and bias was obtained from the relative deviation of the External quality assurance scheme (EQAS) group mean values and laboratory-measured values. Total allowable error (TEa) was derived using EFLM BV data. After calculating sigma metrics, the IQC strategy for each tumor marker was determined according to Westgard Sigma Rules.

RESULTS

Sigma metrics achieved for each analyte varied with the level of TEa. Most of these tumor markers except neuron-specific enolase reached 3σ or better based on TEa_min. With TEa_des and TEa_opt set as the quality goals, almost all analytes had sigma values below 3. Set TEa_min as quality goal, each analyte matched IQC muti rules and numbers of control measurements according to sigma values.

CONCLUSIONS

Quality goals from the EFLM BV database and Westgard Sigma Rules can be used to develop IQC strategy for tumor markers.

Internal Standard Triggered-Parallel Reaction Monitoring Mass Spectrometry Enables Multiplexed Quantification of Candidate Biomarkers in Plasma

Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Previously, mass spectrometry-based approaches have been used to fill this gap but feature poor quantitative performance and were generally limited to hundreds of proteins. Here, we demonstrate the capability of an internal standard triggered-parallel reaction monitoring (IS-PRM) assay to greatly expand the numbers of candidates that can be tested with improved quantitative performance. The assay couples immunodepletion and fractionation with IS-PRM and was developed and implemented in human plasma to quantify 5176 peptides representing 1314 breast cancer biomarker candidates. Characterization of the IS-PRM assay demonstrated the precision (median % CV of 7.7%), linearity (median R² > 0.999 over 4 orders of magnitude), and sensitivity (median LLOQ < 1 fmol, approximately) to enable rank-ordering of candidate biomarkers for validation studies. Using three plasma pools from breast cancer patients and three control pools, 893 proteins were quantified, of which 162 candidate biomarkers were verified in at least one of the cancer pools and 22 were verified in all three cancer pools. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.

Tumour markers with clinically controlled cut-offs for suspected cancer

BACKGROUND

Due to insufficient scientific evidence, panels of tumour markers (TMs) are currently not recommended for use in suspected cancer. However, recent well-designed studies have revealed a potential clinical value in lung cancer. We analysed the diagnostic accuracy of a panel of 11 circulating TMs with clinically controlled thresholds in the differentiation of cancer from nonmalignant diseases.

METHODS

We prospectively recruited 4776 consecutive patients presenting with focal or nonspecific symptoms suggestive of cancer who underwent testing for 11 serum TMs before diagnosis was known. The study abided by 2015 STARD guidelines. Tumour markers included, among others, carbohydrate antigen 19-9, carcinoembryonic antigen, alpha-fetoprotein, squamous cell carcinoma-associated antigen, prostate-specific antigen (males), neuron-specific enolase, progastrin-releasing peptide and carbohydrate antigen 125. Thresholds were adjusted for the presence of kidney failure, liver disease, effusions and dermatological disorders. Results showing ≥1 TMs with concentrations above threshold were considered positive.

RESULTS

Benign diseases were diagnosed in 3281 (68.7%) patients and cancer in 1495 (31.3%), with epithelial cancers in 1214 (77% at stage IV). When applying criteria for controlled thresholds, overall specificity was 98%. Overall sensitivity of the panel in epithelial cancers was 72.2%, positive predictive value 93% and negative predictive value 90.5%. The area under the receiver operating characteristic curve was 0.920 (95% confidence interval, 0.902-0.924).

CONCLUSIONS

By using clinically controlled cut-offs, the combined panel demonstrated an excellent ability to discriminate epithelial cancers from nonmalignant diseases. However, its use in clinical practice would need formal validation through a multicentre controlled trial assessing a panel-guided strategy vs. standard diagnosis.

Serum lactate dehydrogenase activities as systems biomarkers for 48 types of human diseases

Most human diseases are systems diseases, and systems biomarkers are better fitted for diagnostic, prognostic, and treatment monitoring purposes. To search for systems biomarker candidates, lactate dehydrogenase (LDH), a housekeeping protein expressed in all living cells, was investigated. To this end, we analyzed the serum LDH activities from 172,933 patients with 48 clinically defined diseases and 9528 healthy individuals. Based on the median values, we found that 46 out of 48 diseases, leading by acute myocardial infarction, had significantly increased (p < 0.001), whereas gout and cerebral ischemia had significantly decreased (p < 0.001) serum LDH activities compared to the healthy control. Remarkably, hepatic encephalopathy and lung fibrosis had the highest AUCs (0.89, 0.80), sensitivities (0.73, 0.56), and specificities (0.90, 0.91) among 48 human diseases. Statistical analysis revealed that over-downregulation of serum LDH activities was associated with blood-related cancers and diseases. LDH activities were potential systems biomarker candidates (AUCs > 0.8) for hepatic encephalopathy and lung fibrosis.

MicroRNAs and Extracellular Vesicles as Distinctive Biomarkers of Precocious and Advanced Stages of Breast Cancer Brain Metastases Development

Triple negative breast cancer presents higher mortality and poorer survival rates than other breast cancer (BC) types, due to the proneness to brain metastases formation, which are usually diagnosed at advanced stages. Therefore, the discovery of BC brain metastases (BCBM) biomarkers appears pivotal for a timely intervention. With this work, we aimed to disclose microRNAs (miRNAs) and extracellular vesicles (EVs) in the circulation as biomarkers of BCBM formation. Using a BCBM animal model, we analyzed EVs in plasma by nanoparticle tracking analysis and ascertained their blood-brain barrier (BBB) origin by flow cytometry. We further evaluated circulating miRNAs by RT-qPCR and their brain expression by in situ hybridization. In parallel, a cellular model of BCBM formation, combining triple negative BC cells and BBB endothelial cells, was used to differentiate the origin of biomarkers. Established metastases were associated with an increased content of circulating EVs, particularly of BBB origin. Interestingly, deregulated miRNAs in the circulation were observed prior to BCBM detection, and their brain origin was suggested by matching alterations in brain parenchyma. In vitro studies indicated that miR-194-5p and miR-205-5p are expressed and released by BC cells, endothelial cells and during their interaction. These results highlight miRNAs and EVs as biomarkers of BCBM in early and advanced stages, respectively.

Within- and between-subject biological variation data for tumor markers based on the European Biological Variation Study

OBJECTIVES

Reliable biological variation (BV) data are required for the clinical use of tumor markers in the diagnosis and monitoring of treatment effects in cancer. The European Biological Variation Study (EuBIVAS) was established by the EFLM Biological Variation Working Group to deliver BV data for clinically important measurands. In this study, EuBIVAS-based BV estimates are provided for cancer antigen (CA) 125, CA 15-3, CA 19-9, carcinoembryonic antigen, cytokeratin-19 fragment, alpha-fetoprotein and human epididymis protein 4.

METHODS

Subjects from five European countries were enrolled in the study, and weekly samples were collected from 91 healthy individuals (53 females and 38 males; 21-69 years old) for 10 consecutive weeks. All samples were analyzed in duplicate within a single run. After excluding outliers and homogeneity analysis, the BVs of tumor markers were determined by CV-ANOVA on trend-corrected data, when relevant (Røraas method).

RESULTS

Marked individuality was found for all tumor markers. CYFRA 21-1 was the measurand with the highest index of individuality (II) at 0.67, whereas CA 19-9 had the lowest II at 0.07. The CV _I s of HE4, CYFRA 21-1, CA 19-9, CA 125 and CA 15-3 of pre- and postmenopausal females were significantly different from each other.

CONCLUSIONS

This study provides updated BV estimates for several tumor markers, and the findings indicate that marked individuality is characteristic. The use of reference change values should be considered when monitoring treatment of patients by means of tumor markers.

Whole blood GRHL2 expression as a prognostic biomarker in metastatic hormone-sensitive and castration-resistant prostate cancer

Background

As potent systemic therapies transition earlier in the prostate cancer disease course, molecular biomarkers are needed to guide optimal treatment selection for metastatic hormone-sensitive prostate cancer (mHSPC). The value of whole blood RNA to detect candidate biomarkers in mHSPC remains largely undefined.

Methods

In this cohort study, we used a previously optimised whole blood reverse transcription polymerase chain reaction assay to assess the prognostic utility [measured by seven-month undetectable prostate-specific antigen (PSA) and time to castration-resistance (TTCR)] of eight prostate cancer-associated gene transcripts in 43 mHSPC patients. Transcripts with statistically significant associations (P<0.05) were further investigated in a metastatic castration-resistant prostate cancer (mCRPC) cohort (n=119) receiving contemporary systemic therapy, exploring associations with PSA >50% response (PSA₅₀), progression-free survival (PFS) and overall survival (OS). Clinical outcomes were prospectively collected in a protected digital database. Kaplan-Meier estimates and multivariable Cox proportional-hazards models assessed associations between gene transcripts and clinical outcomes (mHSPC covariates: disease volume, docetaxel use and haemoglobin level; mCRPC covariates: prior exposure to chemotherapy or ARPIs, haemoglobin, performance status and presence of visceral disease). Follow-up was performed monthly during ARPI treatment, three-weekly during taxane chemotherapy, and three-monthly during androgen deprivation therapy (ADT) monotherapy. Serial PSA measurements were performed before each follow-up visit and repeat imaging was at the discretion of the investigator.

Results

Detection of circulating Grainyhead-like 2 (GRHL2) transcript was associated with poor outcomes in mHSPC and mCRPC patients. Detectable GRHL2 expression in mHSPC was associated with a lower rate of seven-month undetectable PSA levels (25% vs. 65%, P=0.059), and independently associated with shorter TTCR (HR 7.3, 95% CI: 1.5–36, P=0.01). In the mCRPC cohort, GRHL2 expression predicted significantly lower PSA₅₀ response rates (46% vs. 69%, P=0.01), and was independently associated with shorter PFS (HR 3.1, 95% CI: 1.8–5.2, P<0.001) and OS (HR 2.9, 95% CI: 1.6–5.1, P<0.001). Associations were most apparent in patients receiving ARPIs.

Conclusions

Detectable circulating GRHL2 was a negative prognostic biomarker in our mHSPC and mCRPC cohorts. These data support further investigation of GRHL2 as a candidate prognostic biomarker in metastatic prostate cancer, in addition to expanding efforts to better understand a putative role in therapeutic resistance to AR targeted therapies.

High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and has clinical potential as a prognostic biomarker. The objective of this work was to develop an artificial intelligence (AI) system for automated detection and localization of PTEN loss on immunohistochemically (IHC) stained sections. PTEN loss was assessed using IHC in two prostate tissue microarrays (TMA) (internal cohort, n = 272 and external cohort, n = 129 patients). TMA cores were visually scored for PTEN loss by pathologists and, if present, spatially annotated. Cores from each patient within the internal TMA cohort were split into 90% cross-validation (N = 2048) and 10% hold-out testing (N = 224) sets. ResNet-101 architecture was used to train core-based classification using a multi-resolution ensemble approach (×5, ×10, and ×20). For spatial annotations, single resolution pixel-based classification was trained from patches extracted at ×20 resolution, interpolated to ×40 resolution, and applied in a sliding-window fashion. A final AI-based prediction model was created from combining multi-resolution and pixel-based models. Performance was evaluated in 428 cores of external cohort. From both cohorts, a total of 2700 cores were studied, with a frequency of PTEN loss of 14.5% in internal (180/1239) and external 13.5% (43/319) cancer cores. The final AI-based prediction of PTEN status demonstrated 98.1% accuracy (95.0% sensitivity, 98.4% specificity; median dice score = 0.811) in internal cohort cross-validation set and 99.1% accuracy (100% sensitivity, 99.0% specificity; median dice score = 0.804) in internal cohort test set. Overall core-based classification in the external cohort was significantly improved in the external cohort (area under the curve = 0.964, 90.6% sensitivity, 95.7% specificity) when further trained (fine-tuned) using 15% of cohort data (19/124 patients). These results demonstrate a robust and fully automated method for detection and localization of PTEN loss in prostate cancer tissue samples. AI-based algorithms have potential to streamline sample assessment in research and clinical laboratories.

A Phenomic Perspective on Factors Influencing Breast Cancer Treatment: Integrating Aging and Lifestyle in Blood and Tissue Biomarker Profiling

Breast cancer is the most common malignancy among women worldwide. Over the last four decades, diagnostic and therapeutic procedures have improved substantially, giving patients with localized disease a better chance of cure, and those with more advanced cancer, longer periods of disease control and survival. However, understanding and managing heterogeneity in the clinical response exhibited by patients remains a challenge. For some treatments, biomarkers are available to inform therapeutic options, assess pathological response and predict clinical outcomes. Nevertheless, some measurements are not employed universally and lack sensitivity and specificity, which might be influenced by tissue-specific alterations associated with aging and lifestyle. The first part of this article summarizes available and emerging biomarkers for clinical use, such as measurements that can be made in tumor biopsies or blood samples, including so-called liquid biopsies. The second part of this article outlines underappreciated factors that could influence the interpretation of these clinical measurements and affect treatment outcomes. For example, it has been shown that both adiposity and physical activity can modify the characteristics of tumors and surrounding tissues. In addition, evidence shows that inflammaging and immunosenescence interact with treatment and clinical outcomes and could be considered prognostic and predictive factors independently. In summary, changes to blood and tissues that reflect aging and patient characteristics, including lifestyle, are not commonly considered clinically or in research, either for practical reasons or because the supporting evidence base is developing. Thus, an aim of this article is to encourage an integrative phenomic approach in oncology research and clinical management.

Development and Multiple Validation of the Protein Multi-marker Panel for Diagnosis of Pancreatic Cancer

PURPOSE

To develop and validate a protein-based, multi-marker panel that provides superior pancreatic ductal adenocarcinoma (PDAC) detection abilities with sufficient diagnostic performance.

EXPERIMENTAL DESIGN

A total of 959 plasma samples from patients at multiple medical centers were used. To construct an optimal, diagnostic, multi-marker panel, we applied data preprocessing procedure to biomarker candidates. The multi-marker panel was developed using a training set comprised of 261 PDAC cases and 290 controls. Subsequent evaluations were performed in a validation set comprised of 65 PDAC cases and 72 controls. Further validation was performed in an independent set comprised of 75 PDAC cases and 47 controls.

RESULTS

A multi-marker panel containing 14 proteins was developed. The multi-marker panel achieved AUCs of 0.977 and 0.953 for the training set and validation set, respectively. In an independent validation set, the multi-marker panel yielded an AUC of 0.928. The diagnostic performance of the multi-marker panel showed significant improvements compared with carbohydrate antigen (CA) 19-9 alone (training set AUC = 0.977 vs. 0.872, P < 0.001; validation set AUC = 0.953 vs. 0.832, P < 0.01; independent validation set AUC = 0.928 vs. 0.771, P < 0.001). When the multi-marker panel and CA 19-9 were combined, the diagnostic performance of the combined panel was improved for all sets.

CONCLUSIONS

This multi-marker panel and the combined panel showed statistically significant improvements in diagnostic performance compared with CA 19-9 alone and has the potential to complement CA 19-9 as a diagnostic marker in clinical practice.

Patient-centered Weight Tracking as an Early Cancer Detection Strategy

Early detection is a valued strategy to decrease cancer mortality rates; however, new strategies are needed. Unintentional weight loss (UWL) is experienced by patients across the cancer spectrum, but often goes unnoticed. Patient-centered weight tracking may be a useful early detection marker. Fifty patients were enrolled in a prospective patient-centered weight tracking trial. Patients received a scale and monetary compensation to participate. A reminder to measure and record weight was texted to participants for 26 consecutive weeks. Most patients were black (86.0%) and female (68.0%). The median age was 47 years (range: 22-84 years). Many participants had Medicaid (42.0%) and the median household income by home zip code was $31,046. After 26 weeks, 90% of patients had recorded at least one weight. Among all patients, 73.7% of all possible weights were recorded and the median response rate per patient was 92.3% (24 of 26 weights). There was no difference in the response rates during the first and second halves of the study (77.7% vs. 69.7%, P = 0.53). The range of weight change over the study period was 16.1% loss to 25.0% gain, with 56% of patients maintaining stable weight. Seven patients (14.0%) lost more than 5% weight and 11 patients (22.0%) gained over 5%. Of the seven patients with weight loss, two (4.0% of the cohort) were determined to have UWL. Patient-centered weight tracking is feasible and inexpensive, and has potential as an early detector of UWL. Further studies are needed to apply this strategy to detect underlying malignancies.

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.

Diagnostic Value of Combinatorial Markers in Colorectal Carcinoma

Objectives: Blood-based tests have been shown to be an effective strategy for colorectal cancer (CRC) detection in screening programs. This study was aimed to test the performance of 20 blood markers including tumor antigens, inflammatory markers, and apolipoproteins as well as their combinations.

Methods: In total 203 healthy volunteers and 102 patients with CRC were enrolled into the study. Differences between healthy and cancer subjects were evaluated using Wilcoxon rank-sum test. Several multivariate classification algorithms were employed using information about different combinations of biomarkers altered in CRC patients as well as age and gender of the subjects; random sub-sampling cross-validation was done to overcome overfitting problem. Diagnostic performance of single biomarkers and multivariate classification models was evaluated by receiver operating characteristic (ROC) analysis.

Results: Of 20 biomarkers, 16 were significantly different between the groups (p-value ≤ 0.001); ApoA1, ApoA2 and ApoA4 levels were decreased, whereas levels of tumor antigens (e.g. carcinoembriogenic antigen) and inflammatory markers (e.g., C-reactive protein) were increased in CRC patients vs. healthy subjects. Combinatorial markers including information about all 16 significant analytes, age and gender of patients, demonstrated better performance over single biomarkers with average accuracy on test datasets ≥95% and area under ROC curve (AUROC) ≥98%.

Conclusions: Combinatorial approach was shown to be a valid strategy to improve performance of blood-based CRC diagnostics. Further evaluation of the proposed models in screening programs will be performed to gain a better understanding of their diagnostic value.

Biomarkers for Early Cancer Diagnosis: Prospects for Success through the Lens of Tumor Genetics

Thousands of candidate cancer biomarkers have been proposed, but so far, few are used in cancer screening. Failure to implement these biomarkers is attributed to technical and design flaws in the discovery and validation phases, but a major obstacle stems from cancer biology itself. Oncogenomics has revealed broad genetic heterogeneity among tumors of the same histology and same tissue (or organ) from different patients, while tumors of different tissue origins also share common genetic mutations. Moreover, there is wide intratumor genetic heterogeneity among cells within any single neoplasm. These findings seriously limit the prospects of finding a single biomarker with high specificity for early cancer detection. Current research focuses on developing biomarker panels, with data assessment by machine-learning algorithms. Whether such approaches will overcome the inherent limitations posed by tumor biology and lead to tests with true clinical value remains to be seen.

High FUT3 expression is a marker of lower overall survival of breast cancer patients

The complex enzyme network responsible for glycan synthesis suffers significant changes during the first steps of tumor development, leading to the early formation of tumor-associated glycan signatures. Among the glycosylation pathways, changes in fucosylation emerged as one of most important features in cancer. Αlpha-1,3/4-fucosyltransferase (FUT3) has been linked to pro-tumor and anti-tumor pathways depending on the cancer type. The present study aimed to understand the gene and protein expression profiles of FUT3 in three different and independent cohorts composed by invasive breast cancer patients: Local Brazilian population, METABRIC and TCGA. FUT3 transcripts and protein were measured in the Brazilian population by real-time PCR and Western blotting, respectively. Clinical records and FUT3 levels from public METABRIC and TCGA cohorts were accessed through CBioPortal database. FUT3 expression was analyzed in each cohort using the appropriated statistic tools. Survival meta-analysis in triple negative patients was performed using five independent cohorts including GSE41119, GSE47994 and GSE86945, data obtained from GEO repository available at NCBI database, and METABRIC and TCGA. Our analysis showed that high FUT3 levels were consistently associated to reduced invasive breast cancer patients overall survival. This finding is particularly significant in triple negative patients. These results together with the previously knowledge regarding the involvement of FUT3 in pro-tumor and anti-tumor mechanisms led us to purpose a model for FUT3 expression regulation throughout breast cancer establishment and progression.

Predicting immune checkpoint inhibitor response in urothelial carcinoma: another step in personalised medicine?

Prediction of treatment response is a crucial issue in individualised treatment for cancer patients. In this context, Nassar and colleagues in the accompanying study published in the British Journal of Cancer analysed retrospectively a cohort of 62 metastatic urothelial cancer patients treated with immune checkpoint inhibitors and of whom not only clinical but also genomic characteristics were available. Combining molecular and clinical factors in a multivariable analysis they identified lack of visceral metastases, neutrophil-to-lymphocyte ratio (NLR) <5, and high single nucleotide variant (SNV) count (≥10) as independent predictors of treatment response.

Biomarkers in Lung Cancer

Biomarkers that focus on lung cancer risk assessment, detection, prognosis, diagnosis, and personalized treatment are in various stages of development. This article provides an overview of lung cancer biomarker development, focusing on clinical utility and highlighting 2 unmet clinical needs: selection of high-risk patients for lung cancer screening and differentiation of early lung cancer from benign pulmonary nodules. The authors highlight biomarkers under development and those lung cancer screening and nodule management biomarkers post-clinical validation. Finally, trends in lung cancer biomarker development that may improve accuracy and accelerate implementation in practice are discussed.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for cancer.

The concentration of the cleaved suPAR forms in pre- and postoperative plasma samples improves the prediction of survival in colorectal cancer: A nationwide multicenter validation and discovery study

BACKGROUND AND OBJECTIVES

The aim was to evaluate the prognostic biomarker potential of the soluble urokinase-type plasminogen activator receptor (suPAR) in plasma samples collected pre- and postoperatively from patients resected for colorectal cancer (CRC).

METHODS

Patients with CRC were recruited prospectively at six centers from 2006 to 2008. Preoperative plasma samples were available from 494 patients and from 328 of these patients at 6 months postoperatively. Determinations of intact soluble uPAR (suPAR) suPAR(I-III) and the cleaved forms suPAR(I-III) + (II-III) and uPAR(I) were performed. Clinical data were retrieved retrospectively.

RESULTS

In a multivariable model based on preoperative plasma samples suPAR(I-III) + (II-III) and uPAR(I) showed an independent statistically significant association to long term survival. When including the change in biomarker level between the pre- and postoperatively samples the hazard ratios were 3.06 (95% confidence interval [CI], 1.78-5.28; P < .0001) and 2.24 (95% CI, 1.59-3.16; P < .0001) for suPAR(I-III) + (II-III) and uPAR(I), respectively. A one-unit decrease in biomarker levels between the pre- and postoperative levels resulted in a 55% and 34% reduction in the risk estimate of death for suPAR(I-III) + (II-III) and uPAR(I), respectively.

CONCLUSION

This study validates previously findings regarding the prognostic significance of suPAR in preoperative samples. The inclusion of postoperative samples added further prognostic information.

Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer

PURPOSE

Most patients with early-stage breast cancer are treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) to prevent locoregional recurrence (LRR). However, no genomic tools are used currently to select the optimal RT strategy.

METHODS

We profiled the transcriptome of primary tumors on a clinical grade assay from the SweBCG91-RT trial, in which patients with node-negative breast cancer were randomly assigned to either whole-breast RT after BCS or no RT. We derived a new classifier, Adjuvant Radiotherapy Intensification Classifier (ARTIC), comprising 27 genes and patient age, in three publicly available cohorts, then independently validated ARTIC for LRR in 748 patients in SweBCG91-RT. We also compared previously published genomic signatures for ability to predict benefit from RT in SweBCG91-RT.

RESULTS

ARTIC was highly prognostic for LRR in patients treated with RT (hazard ratio [HR], 3.4; 95% CI, 2.0 to 5.9; P < .001) and predictive of RT benefit (P_interaction = .005). Patients with low ARTIC scores had a large benefit from RT (HR, 0.33 [95% CI, 0.21 to 0.52], P < .001; 10-year cumulative incidence of LRR, 6% v 21%), whereas those with high ARTIC scores benefited less from RT (HR, 0.73 [95% CI, 0.44 to 1.2], P = .23; 10-year cumulative incidence of LRR, 25% v 32%). In contrast, none of the eight previously published signatures were predictive of benefit from RT in SweBCG91-RT.

CONCLUSION

ARTIC identified women with a substantial benefit from RT as well as women with a particularly elevated LRR risk in whom whole-breast RT was not sufficiently effective and, thus, in whom intensified treatment strategies such as tumor-bed boost, and possibly regional nodal RT, should be considered. To our knowledge, ARTIC is the first classifier validated as predictive of benefit from RT in a phase III clinical trial with patients randomly assigned to receive or not receive RT.

Expressiveness of Bone Markers in Breast Cancer with Bone Metastases

INTRODUCTION

On a global scale, the malignant growth of mammary gland is the most common type of cancer in women. In the progress of mammary carcinoma, osseous metastatic invasion has a pivotal significance because it is a frequent complication occurring at an early stage of the disease.

BACKGROUND

Bone metastases in breast cancer patients lead to increased mortality and decreased health-related quality of life. Therefore, early diagnostic assessment and treatment is requested. Meanwhile the progress of the disease should be monitored closely. Regarding health-related quality of life and lifetime prolongation, osseous metastases should be early diagnosed, therapied, and monitored. Up to date the gold standard is the whole-body scintigraphy. This kind of bone imaging features has high sensitivity but shows loss of specificity.

AIM

This study aims to investigate the diagnostic versatility of bone markers in its resorption and formation function to detect bone metastases in patients with breast cancer.

PATIENTS, MATERIALS, AND METHODS

For this purpose, the concentration of competing bone processing tumor markers in serums of 78 patients was detected and analyzed. Two groups of women with mammary carcinoma with and without osseous metastases were built to examine the presence (or absence) of statistically significant disparity of tumor marker concentration. The tumor markers employed in this study were the carboxyterminal collagen type I telopeptid (CTX), known as beta-crosslaps (β-CTx), the alkaline phosphatase (AP), and its isoenzymes (especially the bone-specific AP [B-AP]). Additionally, the tumor markers for breast cancer (CA 15-3 and CEA) were analyzed in both groups.

RESULTS

Our results provide evidence that in both groups, tumor markers such as β-CTx and B-AP were a promising tool for the detection and exclusion of bone metastases in breast cancer. This comprehensive investigation shows both β-CTx and B-AP are able to fulfill the conditions of a competent appliance to detect osseous metastases of patients with mammary carcinoma.

CONCLUSION

Concerning the urgency of early and frequent detection, staging, and disease monitoring of mammary carcinoma with osseous metastases, this study renewed and underlined the importance of biochemical tumor markers - especially β-CTx and B-AP - and laid a clinical-based cornerstone to build up on a prospective research.

Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis

There is a great need for a noninvasive diagnosis for endometriosis. Several biomarkers and biomarker panels have been proposed. Biomarker models consisting of CA-125, VEGF, Annexin V, and glycodelin/sICAM-1 were previously developed by our group. The objective of our current study was to assess the impact of technical and biological variability on the performance of those previously developed prediction models in a technical verification and a validation setting. The technical verification cohort consisted of peripheral blood plasma samples from a subset of the patients included in the original study of Vodolazkaia et al. (99 women with and 37 women without endometriosis). The validation study was done in plasma samples of an independent patient cohort (170 women with and 86 women without endometriosis). Single immunoassays were used for CA-125, VEGF-A, sICAM-1, Annexin V, and glycodelin. Statistical analyses were done using univariate and multivariate (logistic regression) approaches. The previously reported prediction models for endometriosis had a low performance in both the technical verification and validation setting. New prediction models were developed, which included CA-125, Annexin V, and sICAM-1, but CA-125 was the only marker that was retained in the models across the technical verification and validation study. Overall, successful validation of a biomarker model depends on several factors such as patient selection, collection methods, assay selection/handling, stability of the marker, and statistical analysis and interpretation. There is a need for standardized studies in large, well-defined patient cohorts with robust assay methodologies.

Shortcomings in the evaluation of biomarkers in ovarian cancer: a systematic review

Background

Shortcomings in study design have been hinted at as one of the possible causes of failures in the translation of discovered biomarkers into the care of ovarian cancer patients, but systematic assessments of biomarker studies are scarce. We aimed to document study design features of recently reported evaluations of biomarkers in ovarian cancer.

Methods

We performed a systematic search in PubMed (MEDLINE) for reports of studies evaluating the clinical performance of putative biomarkers in ovarian cancer. We extracted data on study designs and characteristics.

Results

Our search resulted in 1026 studies; 329 (32%) were found eligible after screening, of which we evaluated the first 200. Of these, 93 (47%) were single center studies. Few studies reported eligibility criteria (17%), sampling methods (10%) or a sample size justification or power calculation (3%). Studies often used disjoint groups of patients, sometimes with extreme phenotypic contrasts; 46 studies included healthy controls (23%), but only five (3%) had exclusively included advanced stage cases.

Conclusions

Our findings confirm the presence of suboptimal features in clinical evaluations of ovarian cancer biomarkers. This may lead to premature claims about the clinical value of these markers or, alternatively, the risk of discarding potential biomarkers that are urgently needed.

Extracellular vesicles as cancer liquid biopsies: from discovery, validation, to clinical application

Substantial research has been devoted to elucidate the roles that extracellular vesicles (EVs) play in the regulation of both normal and pathological processes, and multiple studies have demonstrated their potential as a source of cancer biomarkers. However, several factors have slowed the development of liquid biopsy EV biomarkers for cancer diagnosis, including logistical and technical difficulties associated with reproducibly obtaining highly purified EVs suitable for diagnostic analysis. Significant effort has focused on addressing these problems, and multiple groups have now reported EV analysis methods using liquid biopsies that have the potential for clinical translation. However, there are still important issues that must be addressed if these discoveries and technical advances are to be used for clinical translation of EV cancer biomarkers from liquid biopsies. To address these issues, this review focuses on the potential application of EV biomarkers for diagnosis of major cancer types, discussing approaches for EV biomarker discovery and verification, EV clinical assay development, analytical and clinical validation, clinical trials, regulatory submission, and end user utilization for the intended clinical application. This review also discusses key difficulties related to these steps, and recommendations for how to best accomplish steps in order to translate EV-based biomarkers into clinical settings.

The Possibility of Systematic Research Fraud Targeting Under-Studied Human Genes: Causes, Consequences, and Potential Solutions

A major reason for biomarker failure is the selection of candidate biomarkers based on inaccurate or incorrect published results. Incorrect research results leading to the selection of unproductive biomarker candidates are largely considered to stem from unintentional research errors. The additional possibility that biomarker research may be actively misdirected by research fraud has been given comparatively little consideration. This review discusses what we believe to be a new threat to biomarker research, namely, the possible systematic production of fraudulent gene knockdown studies that target under-studied human genes. We describe how fraudulent papers may be produced in series by paper mills using what we have described as a ‘theme and variations’ model, which could also be considered a form of salami slicing. We describe features of these single-gene knockdown publications that may allow them to evade detection by journal editors, peer reviewers, and readers. We then propose a number of approaches to facilitate their detection, including improved awareness of the features of publications constructed in series, broader requirements to post submitted manuscripts to preprint servers, and the use of semi-automated literature screening tools. These approaches may collectively improve the detection of fraudulent studies that might otherwise impede future biomarker research.

Mass Spectrometry-Based Biomarkers in Drug Development

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement and to confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drugs mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increases the efficiency of drug development. Here we will provide descriptions of the different classes of biomarkers that have utility in the drug development process as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

Optimizing cancer immunotherapy: Is it time for personalized predictive biomarkers?

Cancer immunotherapy, a treatment that selectively augments a patient's anti-tumor immune response, is a breakthrough advancement in personalized medicine. A subset of cancer patients undergoing immunotherapy have displayed robust and long-lasting therapeutic responses. Currently, the spotlight is on the use of blocking antibodies against the T-cell checkpoint molecules, cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programed cell death-1 (PD-1)/programed death-ligand 1 (PD-L1), which have been effectively used to combat many cancers types. Despite the overall enthusiasm, immune checkpoint blockade inhibitors suffer from significant limitations such as high cost, serious toxicity in a substantial proportion of patients, and a response rate as low as 10%-40% in some clinical trials. Consequently, there is an urgent and unmet medical need for companion biomarkers that could both predict the response of individual patients to these therapies, and provide the means for precise monitoring of their therapeutic outcome. In this era of precision medicine, predictive biomarkers are a hot commodity because they can effectively separate responders from non-responders, and spare non-responders from serious therapy-related toxicity. Emerging predictive biomarkers for immune checkpoint blockade are: PD-L1 expression, increased amounts of tumor-infiltrating lymphocytes, increased mutational load and mismatch repair deficiency. Other well-studied biomarkers include inflammatory infiltrate, absolute lymphocyte count and lactate dehydrogenase levels. We review recent progress on predictive cancer biomarkers in immunotherapy, with a special emphasis on serum autoantibodies that have the potential to be personalized for optimal clinical outcomes.

Asparaginase-like protein 1 expression in curettage independently predicts lymph node metastasis in endometrial carcinoma: a multicentre study

OBJECTIVE

Correct preoperative identification of high-risk patients is important to optimise surgical treatment and improve survival. We wanted to explore if asparaginase-like protein 1 (ASRGL1) expression in curettage could predict lymph node metastases and poor outcome, potentially improving preoperative risk stratification.

DESIGN

Multicentre study.

SETTING

Ten hospitals in Norway, Sweden and Belgium.

POPULATION

Women diagnosed with endometrial carcinoma.

METHODS

ASRGL1 expression in curettage specimens from 1144 women was determined by immunohistochemistry.

MAIN OUTCOME MEASURES

ASRGL1 status related to disease-specific survival, lymph node status, preoperative imaging parameters and clinicopathological data.

RESULTS

ASRGL1 expression had independent prognostic value in multivariate survival analyses, both in the whole patient population (hazard ratio (HR) 1.63, 95% CI 1.11-2.37, P = 0.012) and in the low-risk curettage histology subgroup (HR 2.54, 95% CI 1.44-4.47, P = 0.001). Lymph node metastases were more frequent in women with low expression of ASRGL1 compared with women with high ASRGL1 levels (23% versus 10%, P < 0.001), and low ASRGL1 level was found to independently predict lymph node metastases (odds ratio 2.07, 95% CI 1.27-3.38, P = 0.003).

CONCLUSIONS

Low expression of ASRGL1 in curettage independently predicts lymph node metastases and poor disease-specific survival.

TWEETABLE ABSTRACT

Low ASRGL1 expression in curettage predicts lymph node metastasis and poor survival in endometrial carcinoma.

Methods for the evaluation of biomarkers in patients with kidney and liver diseases: multicentre research programme including ELUCIDATE RCT

Background

Protein biomarkers with associations with the activity and outcomes of diseases are being identified by modern proteomic technologies. They may be simple, accessible, cheap and safe tests that can inform diagnosis, prognosis, treatment selection, monitoring of disease activity and therapy and may substitute for complex, invasive and expensive tests. However, their potential is not yet being realised.

Design and methods

The study consisted of three workstreams to create a framework for research: workstream 1, methodology – to define current practice and explore methodology innovations for biomarkers for monitoring disease; workstream 2, clinical translation – to create a framework of research practice, high-quality samples and related clinical data to evaluate the validity and clinical utility of protein biomarkers; and workstream 3, the ELF to Uncover Cirrhosis as an Indication for Diagnosis and Action for Treatable Event (ELUCIDATE) randomised controlled trial (RCT) – an exemplar RCT of an established test, the ADVIA Centaur® Enhanced Liver Fibrosis (ELF) test (Siemens Healthcare Diagnostics Ltd, Camberley, UK) [consisting of a panel of three markers – (1) serum hyaluronic acid, (2) amino-terminal propeptide of type III procollagen and (3) tissue inhibitor of metalloproteinase 1], for liver cirrhosis to determine its impact on diagnostic timing and the management of cirrhosis and the process of care and improving outcomes.

Results

The methodology workstream evaluated the quality of recommendations for using prostate-specific antigen to monitor patients, systematically reviewed RCTs of monitoring strategies and reviewed the monitoring biomarker literature and how monitoring can have an impact on outcomes. Simulation studies were conducted to evaluate monitoring and improve the merits of health care. The monitoring biomarker literature is modest and robust conclusions are infrequent. We recommend improvements in research practice. Patients strongly endorsed the need for robust and conclusive research in this area. The clinical translation workstream focused on analytical and clinical validity. Cohorts were established for renal cell carcinoma (RCC) and renal transplantation (RT), with samples and patient data from multiple centres, as a rapid-access resource to evaluate the validity of biomarkers. Candidate biomarkers for RCC and RT were identified from the literature and their quality was evaluated and selected biomarkers were prioritised. The duration of follow-up was a limitation but biomarkers were identified that may be taken forward for clinical utility. In the third workstream, the ELUCIDATE trial registered 1303 patients and randomised 878 patients out of a target of 1000. The trial started late and recruited slowly initially but ultimately recruited with good statistical power to answer the key questions. ELF monitoring altered the patient process of care and may show benefits from the early introduction of interventions with further follow-up. The ELUCIDATE trial was an ‘exemplar’ trial that has demonstrated the challenges of evaluating biomarker strategies in ‘end-to-end’ RCTs and will inform future study designs.

Conclusions

The limitations in the programme were principally that, during the collection and curation of the cohorts of patients with RCC and RT, the pace of discovery of new biomarkers in commercial and non-commercial research was slower than anticipated and so conclusive evaluations using the cohorts are few; however, access to the cohorts will be sustained for future new biomarkers. The ELUCIDATE trial was slow to start and recruit to, with a late surge of recruitment, and so final conclusions about the impact of the ELF test on long-term outcomes await further follow-up. The findings from the three workstreams were used to synthesise a strategy and framework for future biomarker evaluations incorporating innovations in study design, health economics and health informatics.

Trial registration

Current Controlled Trials ISRCTN74815110, UKCRN ID 9954 and UKCRN ID 11930.

Funding

This project was funded by the NIHR Programme Grants for Applied Research programme and will be published in full inProgramme Grants for Applied Research; Vol. 6, No. 3. See the NIHR Journals Library website for further project information.

Impact of pathological features of brain metastases in prognosis

AIM

To evaluate the prognostic value of tumor-infiltrating lymphocytes (TILs) and Ki67 in brain metastasis lesions, and the effect of adding them to variables of graded prognostic assessment score.

PATIENTS & METHODS

Clinicopathological information from 111 medical charts of brain metastasis patients was obtained, and TIL distribution (n = 84), Ki67 index (n = 79) and CD3 TIL (n = 64) were prospectively evaluated.

RESULTS

Most frequent TIL pattern was perivascular (67.8%), and median Ki67 and CD3 TIL percents were 30 and 4.8%, respectively. Ki67 ≥15 was associated with shorter survival (p = 0.018) but CD3 TIL was not (p = 0.870). The highest graded prognostic assessment score was not associated with survival (p = 0.648), however, those with low Ki67 and high score was associated with better outcome (p = 0.007).

CONCLUSION

High Ki67 index in brain metastasis carries a worse prognosis.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

- In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

- To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

- The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

- Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

- The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes ( ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes (ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology

CONTEXT

In 2013, an evidence-based guideline was published by the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology to set standards for the molecular analysis of lung cancers to guide treatment decisions with targeted inhibitors. New evidence has prompted an evaluation of additional laboratory technologies, targetable genes, patient populations, and tumor types for testing.

OBJECTIVE

To systematically review and update the 2013 guideline to affirm its validity; to assess the evidence of new genetic discoveries, technologies, and therapies; and to issue an evidence-based update.

DESIGN

The College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology convened an expert panel to develop an evidence-based guideline to help define the key questions and literature search terms, review abstracts and full articles, and draft recommendations.

RESULTS

Eighteen new recommendations were drafted. The panel also updated 3 recommendations from the 2013 guideline.

CONCLUSIONS

The 2013 guideline was largely reaffirmed with updated recommendations to allow testing of cytology samples, require improved assay sensitivity, and recommend against the use of immunohistochemistry for EGFR testing. Key new recommendations include ROS1 testing for all adenocarcinoma patients; the inclusion of additional genes (ERBB2, MET, BRAF, KRAS, and RET) for laboratories that perform next-generation sequencing panels; immunohistochemistry as an alternative to fluorescence in situ hybridization for ALK and/or ROS1 testing; use of 5% sensitivity assays for EGFR T790M mutations in patients with secondary resistance to EGFR inhibitors; and the use of cell-free DNA to "rule in" targetable mutations when tissue is limited or hard to obtain.

Prognostic significance of preoperative serum CA125, CA19-9 and CEA in gastric carcinoma

The prognostic significance of preoperative serum CA125, CA19-9 and CEA in gastric carcinoma (GC) has been widely reported and is still under debate. Here, we evaluated the prognostic significance of preoperative serum CA125, CA19-9 and CEA in patients with GC. 1692 patients with GC who underwent gastrectomy were divided into the training (from January 2005 to December 2011, n = 1024) and the validation (from January 2012 to December 2013, n = 668) cohorts. Positive groups of CA125 (> 13.72 U/ml), CA19-9 (> 23.36 U/ml) and CEA (> 4.28 ng/ml) were significantly associated with more advanced clinicopathological traits and worse outcomes than that of negative groups (all P < 0.01). In Cox regression analysis, tumor size (P < 0.001, P = 0.005), pTNM stage (P < 0.001, P < 0.001) and CA125 (P = 0.026, P = 0.005) were independent prognostic factors both in two cohorts. Nomograms of these two cohorts based on the number of positive serum tumor markers (NPTM) were more accurate in prognostic prediction than TNM stage alone. Our findings suggested that elevated preoperative serum CA125, CA19-9 and CEA were associated with more advanced clinicopathological traits and less favorable outcomes. In addition, CA125 as an independent prognostic factor should be further investigated. Nomogram based on NPTM could accurately predict the prognosis of GC patients.

A Comprehensive Assessment of the Role of miRNAs as Biomarkers in Gastroenteropancreatic Neuroendocrine Tumors

BACKGROUND/AIMS

A key issue in neuroendocrine neoplasia management is the identification of blood signatures that specifically define the activity of a cancer or local tumor microenvironment. MicroRNAs (miRNAs) may represent such a candidate. To evaluate their clinical utility as biomarkers in gastroenteropancreatic neuroendocrine tumors (GEP-NETs), we assessed their expression in tissue and blood.

METHODS

A systematic review of PubMed was undertaken to identify studies investigating miRNAs in GEP-NETs and their utility as blood or tissue biomarkers.

RESULTS

Twenty-two studies using a range of methodologies with different normalization protocols were identified: tumor - gastric NET type 1 (n = 1 study: MiR-222, regulates p27KIP1), pancreatic (n = 6: MiR-21 [inflammatory marker, oncogene] and MiR-144 [PI3K/AKT signaling], both up- and downregulated depending on the method), small intestinal (n = 7: no consistent signature), and colorectal (n = 3: no consistent signature); blood - gastric NET type 1 (n = 1: MiR-222), pancreatic (n = 3: MiR-21), and small intestinal (n = 3: no consistent signature). The studies all included heterogeneous cohorts, were insufficiently powered, and utilized different methodologies, and age- and gender-matched controls were not used. Different miRNA isolation methods and detection protocols resulted in inconsistent expression comparing tumor and blood. A scientific discrepancy was the downregulated expression of some circulating candidates compared to tissue levels, suggesting methodological issues or physiological responses to the tumor. Both are of concern in defining the biometrics of a marker.

CONCLUSIONS

A potential biomarker for GEP-NETs included MiR-21 (small bowel and pancreas), but this epithelial tumor marker requires prospective validation. Overall, significant scientific investigation remains to identify and demonstrate neuroendocrine specificity and to validate candidate miRNA biomarkers.

Asparaginase-like protein 1 is an independent prognostic marker in primary endometrial cancer, and is frequently lost in metastatic lesions

OBJECTIVE

Loss of Asparaginase-like protein 1 (ASRGL1) has been suggested as a prognostic biomarker in endometrial carcinoma. Our objective was to validate this in a prospectively collected, independent patient cohort, and evaluate ASRGL1 expression in endometrial carcinoma precursor lesion and metastases.

METHODS

782 primary endometrial carcinomas, 90 precursor lesions (complex atypical hyperplasia), and 179 metastases (from 87 patients) were evaluated for ASRGL1 expression by immunohistochemistry in relation to clinical and histopathological data. ASRGL1 mRNA level was investigated in 237 primary tumors and related to survival and ASRGL1 protein expression.

RESULTS

Low expression of ASRGL1 protein and ASRGL1 mRNA predicted poor disease specific survival (P<0.001). In multivariate survival analyses ASRGL1 had independent prognostic value both in the whole patient cohort (Hazard ratio (HR): 1.53, 95% confidence interval (CI): 1.04-2.26, P=0.031) and within the endometrioid subgroup (HR: 2.64, CI: 1.47-4.74, P=0.001). Low ASRGL1 expression was less frequent in patients with low grade endometrioid primary tumors compared to high grade endometrioid and non-endometrioid primary tumors, and ASRGL1 was lost in the majority of metastatic lesions.

CONCLUSIONS

In a prospective setting ASRGL1 validates as a strong prognostic biomarker in endometrial carcinoma. Loss of ASRGL1 is associated with aggressive disease and poor survival, and is demonstrated for the first time to have independent prognostic value in the entire endometrial carcinoma patient population.

Evaluating Molecular Biomarkers for the Early Detection of Lung Cancer: When Is a Biomarker Ready for Clinical Use? An Official American Thoracic Society Policy Statement

BACKGROUND

Molecular biomarkers have the potential to improve the current state of early lung cancer detection. The goal of this project was to develop a policy statement that provides guidance about the level of evidence required to determine that a molecular biomarker, used to support early lung cancer detection, is appropriate for clinical use.

METHODS

An ad hoc project steering committee was formed, to include individuals with expertise in the early detection of lung cancer and molecular biomarker development, from inside and outside of the Assembly on Thoracic Oncology. Key questions, generated from the results of a survey of the project steering committee, were discussed at an in-person meeting. Results of the discussion were summarized in a policy statement that was circulated to the steering committee and revised multiple times to achieve consensus.

RESULTS

With a focus on the clinical applications of lung cancer screening and lung nodule evaluation, the policy statement outlines categories of results that should be reported in the early phases of molecular biomarker development, discusses the level of evidence that would support study of the clinical utility, describes the outcomes that should be proven to consider a molecular biomarker clinically useful, and suggests study designs capable of assessing these outcomes.

CONCLUSIONS

The application of molecular biomarkers to assist with the early detection of lung cancer has the potential to substantially improve our ability to select patients for lung cancer screening, and to assist with the characterization of indeterminate lung nodules. We have described relevant considerations and have suggested standards to apply when determining whether a molecular biomarker for the early detection of lung cancer is ready for clinical use.

Revisiting biomarker discovery by plasma proteomics

Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a "rectangular" plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision-making, and we discuss some first steps in this direction.

Performance of seven criteria to assess CA125 increments among ovarian cancer patients monitored during first-line chemotherapy and the post-therapy follow-up period

Aim:

To investigate seven CA125 criteria to monitor progressive ovarian cancer among patients with stage IC–IV disease.

Materials & methods:

Four criteria were used to asses CA125 increments starting from concentrations ≥35 U/ml and three criteria to asses increments starting from concentrations <35 U/ml.

Results:

A total of 231 patients were allocated to CA125 monitoring. The performances of the CA125 criteria were similar with sensitivities of 30–55%, negative predictive values of 28–46%, positive predictive values of 90–100% and median lead times of 26–87 days.

Conclusion:

The criteria showed low sensitivity and inability to exclude progressive ovarian cancer. The study suggests that CA125 information cannot stand alone but should be considered used in conjunction with other investigative procedures.

Few have validated the CA125 progression criteria proposed by Rustin et al. in 1996 and in 2001. These two criteria were officially recommended by the Gynecological Cancer Intergroup to be incorporated into clinical trials in 2010. Among other criteria, we validated the Gynecological Cancer Intergroup CA125 progression criteria in an ovarian cancer population regarding sensitivity, specificity, positive predictive value and negative predictive value. We found that the criteria had low sensitivity and ability to exclude tumor growth. We believe that the clinical utility of CA125 may be questioned, and there is a need for supplementary markers and alternative assessment criteria.

Does biomarker information impact breast cancer patients' preferences and physician recommendation for adjuvant chemotherapy?

PURPOSE

This study aimed to examine how biomarker information would impact patients' preferences and physicians' recommendations for adjuvant breast cancer therapy.

METHODS

At the 18-month follow-up, participants in a large, double-blind randomized controlled trial of adjuvant chemotherapy with bevacizumab or placebo (E5103) were surveyed about their preferred treatment (either chemotherapy A alone or chemotherapy A+B) in two hypothetical scenarios: (1) without biomarker information; and (2) after learning that they tested positive for a "B-receptor" which modestly increased both the benefit and toxicity expected with chemotherapy A+B. We performed a cross-sectional analysis of the prospectively collected survey data and used the McNemar's test to examine changes in treatment preferences. A one-time survey of clinical investigators who enrolled patients on the trial evaluated physician recommendations in response to the same biomarker information.

RESULTS

439 patients completed both scenarios on 18-month survey. Most participants preferred A+B in both scenario 1 and 2 (77 and 76% respectively). The increase in benefit and toxicity associated with the positive biomarker information in scenario 2 led 60/439 (14%) of patients to switch their treatment preference. The corresponding physician survey revealed that most physicians chose regimen A+B in scenario 1 (77%), and moreso after the biomarker information was available in scenario 2 (84%).

CONCLUSIONS

Information about a positive biomarker indicating increased benefit and toxicity from additional chemotherapy did not change many participants' preferred treatment. The majority preferred the most effective course in both scenarios. Similarly, most investigators discounted increased toxicity and valued increased benefit. Parent Trial Registration: NCT00433511.

Clinical research in small genomically stratified patient populations

The paradigm of early drug development in cancer is shifting from 'histology-oriented' to 'molecularly oriented' clinical trials. This change can be attributed to the vast amount of tumour biology knowledge generated by large international research initiatives such as The Cancer Genome Atlas (TCGA) and the use of next generation sequencing (NGS) techniques developed in recent years. However, targeting infrequent molecular alterations entails a series of special challenges. The optimal molecular profiling method, the lack of standardised biological thresholds, inter- and intra-tumor heterogeneity, availability of enough tumour material, correct clinical trials design, attrition rate, logistics or costs are only some of the issues that need to be taken into consideration in clinical research in small genomically stratified patient populations. This article examines the most relevant challenges inherent to clinical research in these populations. Moreover, perspectives from the Academia point of view are reviewed as well as initiatives to be taken in forthcoming years.