Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

OBJECTIVE: Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch). METHODS: In order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools. RESULTS: Each platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically. CONCLUSIONS: Treatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.

Technical Evaluation of Commercial Mutation Analysis Platforms and Reference Materials for Liquid Biopsy Profiling.

Molecular profiling from liquid biopsy, in particular cell-free DNA (cfDNA), represents an attractive alternative to tissue biopsies for the detection of actionable targets and tumor monitoring. In addition to PCR-based assays, Next Generation Sequencing (NGS)-based cfDNA assays are now commercially available and are being increasingly adopted in clinical practice. However, the validity of these products as well as the clinical utility of cfDNA in the management of patients with cancer has yet to be proven. Within framework of the Innovative Medicines Initiative (IMI) program CANCER-ID we evaluated the use of commercially available reference materials designed for ctDNA testing and cfDNA derived from Diagnostic Leukaphereses (DLA) for inter- and intra-assay as well as intra- and inter-laboratory comparisons. In three experimental setups, a broad range of assays including ddPCR, MassARRAY and various NGS-based assays were tested. We demonstrate that both reference materials with predetermined VAFs and DLA samples are extremely useful for the performance assessment of mutation analysis platforms. Moreover, our data indicate a substantial variability of NGS assays with respect to sensitivity and specificity highlighting the importance of extensive validation of the test performance before offering these tests in clinical routine practice.

Publisher Correction: Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors.

BACKGROUND: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. METHODS: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. RESULTS: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. CONCLUSIONS: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches.

Cell-free DNA analysis reveals POLR1D-mediated resistance to bevacizumab in colorectal cancer.

BACKGROUND: Bevacizumab, a monoclonal antibody against soluble VEGFA, is an approved and commonly administered anti-angiogenic drug in patients with metastasized colorectal cancer (mCRC). The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months, and acquired resistance mechanisms are largely unknown. Here, we employed whole-genome sequencing of plasma DNA to evaluate the tumor genome of patients undergoing treatment with bevacizumab to determine novel aberrations associated with resistance. METHODS: Using longitudinal plasma analyses, we studied the evolution of tumor genomes in a mCRC cohort (n = 150) and conducted analyses of CRC cases from The Cancer Genome Atlas (TCGA) database (n = 619) to identify associations between genomic aberrations and clinical features. We employed whole-genome sequencing to identify the most frequently occurring focal somatic copy number alterations (SCNAs). Using the TCGA data as a comparative and supporting dataset, we defined the minimally amplified overlapping region and studied the mechanistic consequences of copy number gain of the involved genes in this segment. In addition, we established an in vitro cell model and conducted downstream gene expression and cell viability assays to confirm our findings from the patient dataset. RESULTS: We observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of CRC cases from the TCGA database suggested that this amplicon is associated with more advanced stages. We confirmed that this 13q12.2 amplicon frequently emerges later during the clinical course of disease. After defining the minimally amplified region, we observed that the amplification and expression of one gene, POLR1D, impacted cell proliferation and resulted in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab treatment. In fact, in several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with therapy resistance. CONCLUSIONS: Non-invasive analyses of cell-free DNA from patients undergoing treatment with bevacizumab enabled the tracking of evolving tumor genomes and helped identify a recurrent focal SCNA of clinical relevance. Here, we describe a novel resistance mechanism against a widely applied treatment in patients with mCRC which will impact the clinical management of patients.

Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection.

Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. Here we develop and validate a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyze whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

Genomic alterations in plasma DNA from patients with metastasized prostate cancer receiving abiraterone or enzalutamide.

In patients with metastatic castrate-resistant prostate cancer (mCRPC), circulating tumor DNA (ctDNA) analysis offers novel opportunities for the development of non-invasive biomarkers informative of treatment response with novel agents targeting the androgen-receptor (AR) pathway, such as abiraterone or enzalutamide. However, the relationship between ctDNA abundance, detectable somatic genomic alterations and clinical progression of mCRPC remains unexplored. Our study aimed to investigate changes in plasma DNA during disease progression and their associations with clinical variables in mCRPC patients. We analyzed ctDNA in two cohorts including 94 plasma samples from 25 treatment courses (23 patients) and 334 plasma samples from 125 patients, respectively. We conducted whole-genome sequencing (plasma-Seq) for genome-wide profiling of somatic copy number alterations and targeted sequencing of 31 prostate cancer-associated genes. The combination of plasma-Seq with targeted AR analyses identified prostate cancer-related genomic alterations in 16 of 25 (64%) treatment courses in the first cohort, in which we demonstrated that AR amplification does not always correlate with poor abiraterone and enzalutamide therapy outcome. As we observed a wide variability of ctDNA levels, we evaluated ctDNA levels and their association with clinical parameters and included the second, larger cohort for these analyses. Employing altogether 428 longitudinal plasma samples from 148 patients, we identified the presence of bone metastases, increased lactate dehydrogenase and prostate-specific antigen (PSA) as having the strongest association with high ctDNA levels. In summary, ctDNA alterations are observable in the majority of patients with mCRPC and may eventually be useful to guide clinical decision-making in this setting.

Advances in Circulating Tumor DNA Analysis.

The analysis of cell-free circulating tumor DNA (ctDNA) is a very promising tool and might revolutionize cancer care with respect to early detection, identification of minimal residual disease, assessment of treatment response, and monitoring tumor evolution. ctDNA analysis, often referred to as "liquid biopsy" offers what tissue biopsies cannot-a continuous monitoring of tumor-specific changes during the entire course of the disease. Owing to technological improvements, efforts for the establishment of preanalytical and analytical benchmark, and the inclusion of ctDNA analyses in clinical trial, an actual clinical implementation has come within easy reach. In this chapter, recent advances of the analysis of ctDNA are summarized starting from the discovery of cell-free DNA, to methodological approaches and the clinical applicability.

Emerging concepts in liquid biopsies.

Characterizing and monitoring tumor genomes with blood samples could achieve significant improvements in precision medicine. As tumors shed parts of themselves into the circulation, analyses of circulating tumor cells, circulating tumor DNA, and tumor-derived exosomes, often referred to as "liquid biopsies", may enable tumor genome characterization by minimally invasive means. Indeed, multiple studies have described how molecular information about parent tumors can be extracted from these components. Here, we briefly summarize current technologies and then elaborate on emerging novel concepts that may further propel the field. We address normal and detectable mutation levels in the context of our current knowledge regarding the gradual accumulation of mutations during aging and in light of technological limitations. Finally, we discuss whether liquid biopsies are ready to be used in routine clinical practice.

The potential of liquid biopsies for the early detection of cancer.

Precision medicine refers to the choosing of targeted therapies based on genetic data. Due to the increasing availability of data from large-scale tumor genome sequencing projects, genome-driven oncology may have enormous potential to change the clinical management of patients with cancer. To this end, components of tumors, which are shed into the circulation, i.e., circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), or extracellular vesicles, are increasingly being used for monitoring tumor genomes. A growing number of publications have documented that these "liquid biopsies" are informative regarding response to given therapies, are capable of detecting relapse with lead time compared to standard measures, and reveal mechanisms of resistance. However, the majority of published studies relate to advanced tumor stages and the use of liquid biopsies for detection of very early malignant disease stages is less well documented. In early disease stages, strategies for analysis are in principle relatively similar to advanced stages. However, at these early stages, several factors pose particular difficulties and challenges, including the lower frequency and volume of aberrations, potentially confounding phenomena such as clonal expansions of non-tumorous tissues or the accumulation of cancer-associated mutations with age, and the incomplete insight into driver alterations. Here we discuss biology, technical complexities and clinical significance for early cancer detection and their impact on precision oncology.

Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients.

Colorectal cancer (CRC) is a heterogeneous disease and current treatment options for patients are associated with a wide range of outcomes and tumor responses. Although the traditional TNM staging system continues to serve as a crucial tool for estimating CRC prognosis and for stratification of treatment choices and long-term survival, it remains limited as it relies on macroscopic features and cases of surgical resection, fails to incorporate new molecular data and information, and cannot perfectly predict the variety of outcomes and responses to treatment associated with tumors of the same stage. Although additional histopathologic features have recently been applied in order to better classify individual tumors, the future might incorporate the use of novel molecular and genetic markers in order to maximize therapeutic outcome and to provide accurate prognosis. Such novel biomarkers, in addition to individual patient tumor phenotyping and other validated genetic markers, could facilitate the prediction of risk of progression in CRC patients and help assess overall survival. Recent findings point to the emerging role of non-protein-coding regions of the genome in their contribution to the progression of cancer and tumor formation. Two major subclasses of non-coding RNAs (ncRNAs), microRNAs and long non-coding RNAs, are often dysregulated in CRC and have demonstrated their diagnostic and prognostic potential as biomarkers. These ncRNAs are promising molecular classifiers and could assist in the stratification of patients into appropriate risk groups to guide therapeutic decisions and their expression patterns could help determine prognosis and predict therapeutic options in CRC.

Current Insights into Long Non-Coding RNAs in Renal Cell Carcinoma.

Renal cell carcinoma (RCC) represents a deadly disease with rising mortality despite intensive therapeutic efforts. It comprises several subtypes in terms of distinct histopathological features and different clinical presentations. Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts in the genome which vary in expression levels and length and perform diverse functions. They are involved in the inititation, evolution and progression of primary cancer, as well as in the development and spread of metastases. Recently, several lncRNAs were described in RCC. This review emphasises the rising importance of lncRNAs in RCC. Moreover, it provides an outlook on their therapeutic potential in the future.

microRNAs and Colorectal Cancer.

Colorectal cancer (CRC) is one of the most common types of human cancer with high cancer-related morbidity and mortality rates. The development and clinical validation of novel therapeutic avenues have improved the clinical outcome, but metastatic CRC still remains an incurable disease in most cases. The interest in discovering novel pathophysiological drivers in CRC is intensively ongoing and the search for novel biomarkers for early diagnosis, for patient's stratification for prognostic purposes or for predicting treatment response are warranted. microRNAs are small RNA molecules that regulate the expression of larger messenger RNA species by different mechanisms with the final consequence to provide a fine tuning tool for global gene expression patterns. First discovered in worms, around 15 years ago it became clear that microRNAs are also existing in humans and that they are widely involved in human carcinogenesis. Within the last years, tremendous progress in the understanding of microRNAs and their role in CRC carcinogenesis has been developed. In this book chapter, several examples of previously identified microRNAs and how they influence colorectal carcinogenesis will be discussed. The information starting at the underlying molecular mechanisms towards clinical applications will be depicted and an overview what great potential these small molecules might carry in future colorectal cancer medicine, will be discussed.

Spinophilin expression determines cellular growth, cancer stemness and 5-flourouracil resistance in colorectal cancer.

The putative tumor suppressor gene spinophilin has been involved in cancer progression in several types of cancer. In this study, we explored the prognostic value of spinophilin expression in 162 colon adenocarcinoma patients. In addition, we generated stably expressing spinophilin-directed shRNA CRC cell lines and studied the influence of spinophilin expression on cellular phenotypes and molecular interactions. We independently confirmed that low spinophilin expression levels are associated with poor prognosis in CRC patients (p = 0.038). A reduction of spinophilin levels in p53 wild-type HCT116 and p53-mutated Caco-2 cells led to increased cellular growth rates and anchorage-independent growth (p<0.05). At molecular level, reduced spinophilin levels increased the expression of the transcription factor E2F-1. In addition, we observed an increased formation of tumor spheres, increased number of CD133 positive cells and an increased resistance to 5-flourouracil (p<0.05). Finally, treatment with the de-methylating agent 5-aza-dC increased spinophilin expression in CRC cells (p<0.05), corroborated by a correlation of spinophilin expression and extent of methylated CpG sites in the gene promoter region (p<0.001). In conclusion, gain of aggressive biological properties of CRC cells including cellular growth, cancer stem cell features and 5-flourouracil resistance partly explains the role of spinophilin in CRC.

MicroRNAs as novel predictive biomarkers and therapeutic targets in colorectal cancer.

Colorectal cancer (CRC) is the third most common cancer in western countries. Despite significant improvement in available treatment options, CRC still remains the second leading cause of cancer-related death. Traditionally, 5-fluorouracil has been used as the main chemotherapy drug for treatment of metastatic CRC (mCRC). However, during the last two decades more effective chemotherapeutic agents such as oxaliplatin, irinotecan and the monoclonal antibodies cetuximab, panitumumab and bevacizumab have been used in clinical practice. More recently, the therapeutic armamentarium has been supplemented by the monoclonal antibodies bevacizumab, cetuximab and panitumumab as well as the protein-trap aflibercept and the small molecule multi-kinase inhibitor regorafenib. One of the major problems for the management of CRC is the inherent or acquired resistance to therapeutic approaches. The discovery of microRNAs (miRNAs), a class of small, endogenous, non-coding, single-stranded RNAs that play a role as post-transcriptional regulators, has added new dimensions to the diagnosis and treatment of cancer. Because miRNAs are important regulators of carcinogenesis, progression, invasion, angiogenesis and metastases in CRC, they might serve as potential predictive and prognostic factors and even as therapeutic targets themselves. Several miRNAs are already known to be dysregulated in CRCs and have been linked to biological processes involved in tumor progression and response to anti-cancer therapies. This review summarizes current therapeutic approaches for treating CRC and highlights the role of miRNAs as novel predictive biomarkers and potential drug targets in CRC patients.

Tumor endothelial inflammation predicts clinical outcome in diverse human cancers.

BACKGROUND: Vascular endothelial cells contribute to the pathogenesis of numerous human diseases by actively regulating the stromal inflammatory response; however, little is known regarding the role of endothelial inflammation in the growth of human tumors and its influence on the prognosis of human cancers. METHODS: Using an experimental model of tumor necrosis factor-alpha (TNF-α)-mediated inflammation, we characterized inflammatory gene expression in immunopurified tumor-associated endothelial cells. These genes formed the basis of a multivariate molecular predictor of overall survival that was trained and validated in four types of human cancer. RESULTS: We report that expression of experimentally derived tumor endothelial genes distinguished pathologic tissue specimens from normal controls in several human diseases associated with chronic inflammation. We trained these genes in human cancer datasets and defined a six-gene inflammatory signature that predicted significantly reduced overall survival in breast cancer, colon cancer, lung cancer, and glioma. This endothelial-derived signature predicted outcome independently of, but cooperatively with, standard clinical and pathological prognostic factors. Consistent with these findings, conditioned culture media from human endothelial cells stimulated by pro-inflammatory cytokines accelerated the growth of human colon and breast tumors in immunodeficient mice as compared with conditioned media from untreated endothelial cells. CONCLUSIONS: This study provides the first prognostic cancer gene signature derived from an experimental model of tumor-associated endothelial inflammation. These findings support the notion that activation of inflammatory pathways in non-malignant tumor-infiltrating endothelial cells contributes to tumor growth and progression in multiple human cancers. Importantly, these results identify endothelial-derived factors that could serve as potential targets for therapy in diverse human cancers.

MicroRNA expression characterizes oligometastasis(es).

BACKGROUND: Cancer staging and treatment presumes a division into localized or metastatic disease. We proposed an intermediate state defined by ≤ 5 cumulative metastasis(es), termed oligometastases. In contrast to widespread polymetastases, oligometastatic patients may benefit from metastasis-directed local treatments. However, many patients who initially present with oligometastases progress to polymetastases. Predictors of progression could improve patient selection for metastasis-directed therapy. METHODS: Here, we identified patterns of microRNA expression of tumor samples from oligometastatic patients treated with high-dose radiotherapy. RESULTS: Patients who failed to develop polymetastases are characterized by unique prioritized features of a microRNA classifier that includes the microRNA-200 family. We created an oligometastatic-polymetastatic xenograft model in which the patient-derived microRNAs discriminated between the two metastatic outcomes. MicroRNA-200c enhancement in an oligometastatic cell line resulted in polymetastatic progression. CONCLUSIONS: These results demonstrate a biological basis for oligometastases and a potential for using microRNA expression to identify patients most likely to remain oligometastatic after metastasis-directed treatment.