A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types

Cancer research continues to highlight the extensive genetic diversity that exists both between and within tumors. This intrinsic heterogeneity poses one of the central challenges to predicting patient clinical outcome and the personalization of treatments. Despite progress in some individual tumor types, it is not yet possible to prospectively, accurately classify patients by expected survival. One hypothesis proposed to explain this is that the prognostic classifiers developed to date are insufficiently sensitive and specific; however it is also possible that patients are not equally easy to classify by any given biomarker. We demonstrate in a cohort of 45 AJCC stage III melanoma patients that clinico-pathologic biomarkers can identify those patients that are most likely to be misclassified by a molecular biomarker. The process of modelling the classifiability of patients was then replicated in a cohort of 49 stage II breast cancer patients and 53 stage III colon cancer patients. A multi-step procedure incorporating this information not only improved classification accuracy but also indicated the specific clinical attributes that had made classification problematic in each cohort. These findings show that, even when cohorts are of moderate size, including features that explain the patient-specific performance of a prognostic biomarker in a classification framework can improve the modelling and estimation of survival.

Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-detection algorithms for human melanoma genomes

Whole genome sequencing (WGS) of cancer patients' tumours offers the most comprehensive method of identifying both novel and known clinically-actionable genomic targets. However, the practicalities of performing WGS on clinical samples are poorly defined.This study was designed to test sample preparation, sequencing specifications and bioinformatic algorithms for their effect on accuracy and cost-efficiency in a large WGS analysis of human melanoma samples.WGS was performed on melanoma cell lines (n = 15) and melanoma fresh frozen tumours (n = 222). The appropriate level of coverage and the optimal mutation detection algorithm for the project pipeline were determined.An incremental increase in sequencing coverage from 36X to 132X in melanoma tissue samples and 30X to 103X for cell lines only resulted in a small increase (1-2%) in the number of mutations detected, and the quality scores of the additional mutations indicated a low probability that the mutations were real. The results suggest that 60X coverage for melanoma tissue and 40X for melanoma cell lines empower the detection of 98-99% of informative single nucleotide variants (SNVs), a sensitivity level at which clinical decision making or landscape research projects can be carried out with a high degree of confidence in the results. Likewise the bioinformatic mutation analysis methodology strongly influenced the number and quality of SNVs detected. Detecting mutations in the blood genomes separate to the tumour genomes generated 41% more SNVs than if the blood and melanoma tissue genomes were analysed simultaneously. Therefore, simultaneous analysis should be employed on matched melanoma tissue and blood genomes to reduce errors in mutation detection.This study provided valuable insights into the accuracy of SNV with WGS at various coverage levels in human clinical cancer specimens. Additionally, we investigated the accuracy of the publicly available mutation detection algorithms to detect cancer specific SNVs which will aid researchers and clinicians in study design and implementation of WGS for the identification of somatic mutations in other cancers.

Identification, Review, and Systematic Cross-Validation of microRNA Prognostic Signatures in Metastatic Melanoma

In metastatic melanoma, it is vital to identify and validate biomarkers of prognosis. Previous studies have systematically evaluated protein biomarkers or mRNA-based expression signatures. No such analyses have been applied to microRNA (miRNA)-based prognostic signatures. As a first step, we identified two prognostic miRNA signatures from publicly available data sets (Gene Expression Omnibus/The Cancer Genome Atlas) of global miRNA expression profiling information. A 12-miRNA signature predicted longer survival after surgery for resection of American Joint Committee on Cancer stage III disease (>4 years, no sign of relapse) and outperformed American Joint Committee on Cancer standard-of-care prognostic markers in leave-one-out cross-validation analysis (error rates 34% and 38%, respectively). A similar 15-miRNA biomarker derived from The Cancer Genome Atlas miRNA-seq data performed slightly worse (39%) than these current biomarkers. Both signatures were then assessed for replication in two independent data sets and subjected to systematic cross-validation together with the three other miRNA-based prognostic signatures proposed in the literature to date. Five miRNAs (miR-142-5p, miR-150-5p, miR-342-3p, miR-155-5p, and miR-146b-5p) were reproducibly associated with patient outcome and have the greatest potential for application in the clinic. Our extensive validation approach highlighted among multiple independent cohorts the translational potential and limitations of miRNA signatures, and pointed to future directions in the analysis of this emerging class of markers.

Comparison of whole-exome sequencing of matched fresh and formalin fixed paraffin embedded melanoma tumours: implications for clinical decision making

The identification of recurrent driver mutations by whole-exome sequencing (WES) of fresh-frozen human cancers and the subsequent development of novel targeted therapies have recently transformed the treatment of many cancers including melanoma. In routine clinical practice, fresh-frozen tissue is rarely available and mutation testing usually needs to be carried out on archival formalin fixed, paraffin embedded (FFPE) tissue, from which DNA is typically fragmented, cross-linked and of lower quality. In this study we aimed to determine whether WES data generated from genomic DNA (gDNA) extracted from FFPE tissues can be produced reliably and of clinically-actionable standard. In this study of ten melanoma patients, we compared WES data produced from analysis of gDNA isolated from FFPE tumour tissue with that isolated from fresh-frozen tumour tissue from the same specimen. FFPE samples were sequenced using both Illumina's Nextera and NimbleGen SeqCap exome capture kits. To examine mutations between the two tissue sources and platforms, somatic mutations in the FFPE exomes were called using the matched fresh tissue sequence as a reference. Of the 10 FFPE DNA samples, seven Nextera and four SeqCap samples passed library preparation. On average, there were 5341 and 2246 variants lost in FFPE compared to matched fresh tissue utilising Nextera and SeqCap kits, respectively. In order to explore the feasibility of future clinical implementation of WES, FFPE variants in 27 genes of important clinical relevance in melanoma were assessed. The average concordance rate was 43.2% over a total of 1299 calls for the chosen genes in the FFPE DNA. For the current clinically most important melanoma mutations, 0/3 BRAF and 6/8 (75%) NRAS FFPE calls were concordant with the fresh tissue result, which was confirmed using a Sequenom OncoCarta Panel. The poor performance of FFPE WES indicates that specialised library construction to account for low quality DNA and further refinements will be necessary before this approach could be used for routine clinical decision making over currently preferred techniques.

Developing an institutional cancer biorepository for personalized medicine

High quality human biospecimens, such as tissue, blood, cell derivatives, and associated patient clinical information, are key elements of a scientific infrastructure that supports discovery and identification of molecular biomarkers and diagnostic agents. The goal of most biorepositories is to collect, process, store, and distribute human biospecimen for use in basic, translational and clinical research. A biorepository serving as the central hub provides investigators with an invaluable resource with appropriately examined and characterized biospecimens with associated patient clinical information. Expertise in standardization, quality control, and information technology, and awareness of cutting edge research developments are generally required for biorepository development and management. The availability of low cost whole genome profiles of individual tumors has opened up new possibilities for personalized medicine to deliver the most appropriate treatments to individual patients with minimal toxicity. A biorepository in support of personalized medicine thus requires the highest standards of operation and adequate funding, training and certification. This review provides an overview of the development of an institutional cancer biorepository for clinical research and personalized medicine advancement.

Data set for pathology reporting of cutaneous invasive melanoma: recommendations from the international collaboration on cancer reporting (ICCR)

An accurate and complete pathology report is critical for the optimal management of cutaneous melanoma patients. Protocols for the pathologic reporting of melanoma have been independently developed by the Royal College of Pathologists of Australasia (RCPA), Royal College of Pathologists (United Kingdom) (RCPath), and College of American Pathologists (CAP). In this study, data sets, checklists, and structured reporting protocols for pathologic examination and reporting of cutaneous melanoma were analyzed by an international panel of melanoma pathologists and clinicians with the aim of developing a common, internationally agreed upon, evidence-based data set. The International Collaboration on Cancer Reporting cutaneous melanoma expert review panel analyzed the existing RCPA, RCPath, and CAP data sets to develop a protocol containing "required" (mandatory/core) and "recommended" (nonmandatory/noncore) elements. Required elements were defined as those that had agreed evidentiary support at National Health and Medical Research Council level III-2 level of evidence or above and that were unanimously agreed upon by the review panel to be essential for the clinical management, staging, or assessment of the prognosis of melanoma or fundamental for pathologic diagnosis. Recommended elements were those considered to be clinically important and recommended for good practice but with lesser degrees of supportive evidence. Sixteen core/required data elements for cutaneous melanoma pathology reports were defined (with an additional 4 core/required elements for specimens received with lymph nodes). Eighteen additional data elements with a lesser level of evidentiary support were included in the recommended data set. Consensus response values (permitted responses) were formulated for each data item. Development and agreement of this evidence-based protocol at an international level was accomplished in a timely and efficient manner, and the processes described herein may facilitate the development of protocols for other tumor types. Widespread utilization of an internationally agreed upon, structured pathology data set for melanoma will lead not only to improved patient management but is a prerequisite for research and for international benchmarking in health care.

BRAF/NRAS wild-type melanomas have a high mutation load correlating with histologic and molecular signatures of UV damage

PURPOSE

The mutation load in melanoma is generally high compared with other tumor types due to extensive UV damage. Translation of exome sequencing data into clinically relevant information is therefore challenging. This study sought to characterize mutations identified in primary cutaneous melanomas and correlate these with clinicopathologic features.

EXPERIMENTAL DESIGN

DNA was extracted from 34 fresh-frozen primary cutaneous melanomas and matched peripheral blood. Tumor histopathology was reviewed by two dermatopathologists. Exome sequencing was conducted and mutation rates were correlated with age, sex, tumor site, and histopathologic variables. Differences in mutations between categories of solar elastosis, pigmentation, and BRAF/NRAS mutational status were investigated.

RESULTS

The average mutation rate was 12 per megabase, similar to published results in metastases. The average mutation rate in severely sun damaged (SSD) skin was 21 per Mb compared with 3.8 per Mb in non-SSD skin (P=0.001). BRAF/NRAS wild-type (WT) tumors had a higher average mutation rate compared with BRAF/NRAS-mutant tumors (27 vs. 5.6 mutations per Mb; P=0.0001). Tandem CC>TT/GG>AA mutations comprised 70% of all dinucleotide substitutions and were more common in tumors arising in SSD skin (P=0.0008) and in BRAF/NRAS WT tumors (P=0.0007). Targetable and potentially targetable mutations in WT tumors, including NF1, KIT, and NOTCH1, were spread over various signaling pathways.

CONCLUSION

Melanomas arising in SSD skin have higher mutation loads and contain a spectrum of molecular subtypes compared with BRAF- and NRAS-mutant tumors indicating multigene screening approaches and combination therapies may be required for management of these patients.