Non-invasive Potential Circulating mRNA Markers for Colorectal Adenoma Using Targeted Sequencing

An investigation of plasma cell-free RNA for the detection of colorectal cancer: From transcriptome marker selection to targeted validation

Regular screening for colorectal cancer (CRC) is critical for early detection and long-term survival. Despite the current screening options available and advancements in therapies there will be around 53,000 CRC related deaths this year. There is great interest in non-invasive alternatives such as plasma cell-free RNA (cfRNA) for diagnostic, prognostic, and predictive applications. In the current study, our aim was to identify and validate potential cfRNA candidates to improve early CRC diagnosis. In phase 1 (n = 49; 25 controls, 24 cancers), discovery total RNA sequencing was performed. Select exons underwent validation in phase 2 (n = 73; 35 controls, 29 cancers, 9 adenomas) using targeted capture sequencing (n = 10,371 probes). In phase 3 (n = 57; 30 controls, 27 cancers), RT-qPCR was performed on previously identified candidates (n = 99). There were 895 exons that were differentially expressed (325 upregulated, 570 downregulated) among cancers versus controls. In phases 2 and 3, fewer markers were validated than expected in independent sets of patients, most of which were from previously published literature (FGA, FGB, GPR107, CDH3, and RP23AP7). In summary, we optimized laboratory processes and data analysis strategies which can serve as methodological framework for future plasma RNA studies beyond just the scope of CRC detection. Additionally, further exploration is needed in order to determine if the few cfRNA candidates identified in this study have clinical utility for early CRC detection. Over time, advancements in technologies, data analysis, and RNA preservation methods at time of collection may improve the biological and technical reproducibility of cfRNA biomarkers and enhance the feasibility of RNA-based liquid biopsies.

Current advances in detecting genetic and epigenetic biomarkers of colorectal cancer

Colorectal carcinoma (CRC) is the third most common cancer in terms of diagnosis and the second in terms of mortality. Recent studies have shown that various proteins, extracellular vesicles (i.e., exosomes), specific genetic variants, gene transcripts, cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and altered epigenetic patterns, can be used to detect, and assess the prognosis of CRC. Over the last decade, a plethora of conventional methodologies (e.g., polymerase chain reaction [PCR], direct sequencing, enzyme-linked immunosorbent assay [ELISA], microarray, in situ hybridization) as well as advanced analytical methodologies (e.g., microfluidics, electrochemical biosensors, surface-enhanced Raman spectroscopy [SERS]) have been developed for analyzing genetic and epigenetic biomarkers using both optical and non-optical tools. Despite these methodologies, no gold standard detection method has yet been implemented that can analyze CRC with high specificity and sensitivity in an inexpensive, simple, and time-efficient manner. Moreover, until now, no study has critically reviewed the advantages and limitations of these methodologies. Here, an overview of the most used genetic and epigenetic biomarkers for CRC and their detection methods are discussed. Furthermore, a summary of the major biological, technical, and clinical challenges and advantages/limitations of existing techniques is also presented.

The non-invasive diagnosis of colorectal cancer via a SOX9-based gene panel

Colorectal cancer (CRC) threatens human health seriously. Early diagnosis of CRC is critical to improving patient survival. Meanwhile, non-invasive detection through tumor-circulating markers can be an important auxiliary diagnosis. In this study, we performed targeted RNA sequencing in paired tumor and adjacent normal fresh frozen tissues from 68 patients, and we also measured circulating mRNA levels in 4 time-point plasma samples collected before and after operation or chemotherapy. Our results showed that SOX9 (6.73-fold with adjusted p value < 1 × 10-45), MYC (20.59-fold with adjusted p value < 1 × 10-57), and MMP7 (131.94-fold with adjusted p value < 1 × 10-78) highly expressed in tumor compared with adjacent normal tissues. Besides, the circulating mRNA of SOX9 (41.14-fold with adjusted p value < 1 × 10-13) in CRC was significantly higher than in the normal control as well. Moreover, a SOX9-based 9-gene panel (SOX9, GSK3A, FZD4, LEF1, DVL1, FZD7, NFATC1, KRT19, and RUVBL1) showed the non-invasive diagnostic value of CRC (AUC: 0.863 (0.766-0.960), TPR: 0.92, TNR: 0.87). In summary, SOX9 expression consistently increases in tumor and plasma samples from CRC patients, which indicates the important role of SOX9 in CRC progression and its potential in non-invasive diagnosis of CRC.

Exploring the Role of Circulating Cell-Free RNA in the Development of Colorectal Cancer

Circulating tumor RNA (ctRNA) has recently emerged as a novel and attractive liquid biomarker. CtRNA is capable of providing important information about the expression of a variety of target genes noninvasively, without the need for biopsies, through the use of circulating RNA sequencing. The overexpression of cancer-specific transcripts increases the tumor-derived RNA signal, which overcomes limitations due to low quantities of circulating tumor DNA (ctDNA). The purpose of this work is to present an up-to-date review of current knowledge regarding ctRNAs and their status as biomarkers to address the diagnosis, prognosis, prediction, and drug resistance of colorectal cancer. The final section of the article discusses the practical aspects involved in analyzing plasma ctRNA, including storage and isolation, detection technologies, and their limitations in clinical applications.

Cell-free circulating tumor RNAs in plasma as the potential prognostic biomarkers in colorectal cancer

Background

Cell free RNA (cfRNA) contains transcript fragments from multiple cell types, making it useful for cancer detection in clinical settings. However, the pathophysiological origins of cfRNAs in plasma from colorectal cancer (CRC) patients remain unclear.

Methods

To identify the tissue-specific contributions of cfRNAs transcriptomic profile, we used a published single-cell transcriptomics profile to deconvolute cell type abundance among paired plasma samples from CRC patients who underwent tumor-ablative surgery. We further validated the differentially expressed cfRNAs in 5 pairs of CRC tumor samples and adjacent tissue samples as well as 3 additional CRC tumor samples using RNA-sequencing.

Results

The transcriptomic component from intestinal secretory cells was significantly decreased in the in-house post-surgical cfRNA. The HPGD, PACS1, and TDP2 expression was consistent across cfRNA and tissue samples. Using the Cancer Genome Atlas (TCGA) CRC datasets, we were able to classify the patients into two groups with significantly different survival outcomes.

Conclusions

The three-gene signature holds promise in applying minimal residual disease (MRD) testing, which involves profiling remnants of cancer cells after or during treatment. Biomarkers identified in the present study need to be validated in a larger cohort of samples in order to ascertain their possible use in early diagnosis of CRC.

Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma

Background and rationale

Liver derived messenger ribonucleic acid (mRNA) transcripts were reported to be elevated in the circulation of hepatocellular carcinoma (HCC) patients. We now report the detection of high-risk mRNA variants exclusively in the circulation of HCC patients. Numerous genomic alleles such as single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), splicing variants in many genes, have been associated with elevated risk of cancer. Our findings potentially offer a novel non-invasive platform for HCC surveillance and early detection.

Approach

RNAseq analysis was carried out in the plasma of 14 individuals with a diagnosis of HCC, 8 with LC and no HCC, and 6 with no liver disease diagnosis. RNA from 6 matching tumors and 5 circulating extracellular vesicle (EV) samples from 14 of those with HCC was also analyzed. Specimens from two cholangiocarcinoma (CCA) patients were also included in our study. HCC specific SNPs and Indels referred as "variants" were identified using GATK HaplotypeCaller and annotated by SnpEff to filter out high risk variants.

Results

The variant calling on all RNA samples enabled the detection of 5.2 million SNPs, 0.91 million insertions and 0.81 million deletions. RNAseq analyses in tumors, normal liver tissue, plasma, and plasma derived EVs led to the detection of 5480 high-risk tumor specific mRNA variants in the circulation of HCC patients. These variants are concurrently detected in tumors and plasma samples or tumors and EVs from HCC patients, but none of these were detected in normal liver, plasma of LC patients or normal healthy individuals. Our results demonstrate selective detection of concordant high-risk HCC-specific mRNA variants in free plasma, plasma derived EVs and tumors of HCC patients. The variants comprise of splicing, frameshift, fusion and single nucleotide alterations and correspond to cancer and tumor metabolism pathways. Detection of these high-risk variants in matching specimens from same subjects with an enrichment in circulating EVs is remarkable. Validation of these HCC selective ctmRNA variants in larger patient cohorts is likely to identify a predictive set of ctmRNA with high diagnostic performance and thus offer a novel non-invasive serology-based biomarker for HCC.

Intravoxel incoherent motion DWI with different mathematical models in predicting rectal adenoma with and without canceration

PURPOSE

To evaluate the clinical value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) with mono-exponential (ME), bi-exponential (BE), and stretched-exponential (SE) models for predicting rectal adenomas with canceration.

MATERIAL AND METHODS

Sixty patients with postoperative pathology-confirmed rectal adenoma (n = 31) and adenoma with canceration (n = 29) were enrolled and underwent IVIM-DWI scanning. The ME-derived apparent diffusion coefficient (ADC), BE-derived true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), SE-derived distributed diffusion coefficient (DDC), and water molecular diffusion heterogeneity index (α) were measured. The differences in each parameter between adenoma and canceration were compared. Multivariate binary logistic regression analysis was used to establish models for predicting rectal adenomas with canceration. Receiver operating characteristic curve analysis was applied to evaluate diagnostic performances of each model in terms of sensitivity, specificity, accuracy, and area under the curve (AUC).

RESULTS

The AUCs of ADC, D, D*, f, DDC and α were 0.851 (95 % confidence interval, CI, 0.735-0.930), 0.895 (95 % CI, 0.789-0.960), 0.720 (95 % CI, 0.589-0.828), 0.791 (95 % CI, 0.667-0.886), 0.841 (95 % CI, 0.724-0.923) and 0.738 (95 % CI, 0.608-0.834), respectively. The AUCs of BE and SE models were 0.927 (95 % CI, 0.829-0.978) and 0.874 (95 % CI, 0.763-0.946), respectively. The AUC, sensitivity, specificity, and accuracy of the derived four values (ADC, D, f, and DDC) from the combination of three models were 0.950, 96.6 % (95 % CI, 95.3-97.6 %), 80.6 % (95 % CI, 78.0-82.9 %), and 88.3 % (95 % CI, 86.2-90.2 %), respectively.

CONCLUSION

ADC can easily and effectively predict rectal adenomas with canceration. The BE model has a better combination of sensitivity and specificity for the diagnosis of rectal adenoma canceration.

Extracellular Nucleic Acids in the Diagnosis and Progression of Colorectal Cancer

Simple Summary

Colorectal cancer (CRC) is a disease that usually shows no evident clinical symptoms in the early stages, often leading to late diagnosis. Over the past few years, a new approach based on liquid biopsy has gained far-reaching applications in less-invasive CRC diagnosis and management, allowing for the use of extracellular nucleic acids as promising biomarkers to detect CRC at an early stage and monitor disease recurrence. That is why an up-to-date review and discussion of in-depth liquid biopsy-derived DNA and RNA biomarkers is essential. We hereby offer an overview of known predisposing genetic factors for developing sporadic and hereditary CRC, and an extensive repertoire of available extracellular DNA/RNA molecules with their potential clinical applications and shortcomings. Our review may be of value to experts dealing with CRC at the molecular level as well as to clinical professionals aiming for a better understanding of state-of-the-art techniques in CRC diagnosis and management.

Abstract

Colorectal cancer (CRC) is the 3rd most common malignant neoplasm worldwide, with more than two million new cases diagnosed yearly. Despite increasing efforts in screening, many cases are still diagnosed at a late stage, when mortality is high. This paper briefly reviews known genetic causes of CRC (distinguishing between sporadic and familial forms) and discusses potential and confirmed nucleic acid biomarkers obtainable from liquid biopsies, classified by their molecular features, focusing on clinical relevance. We comment on advantageous aspects such as better patient compliance due to blood sampling being minimally invasive, the possibility to monitor mutation characteristics of sporadic and hereditary CRC in a disease showing genetic heterogeneity, and using up- or down-regulated circulating RNA markers to reveal metastasis or disease recurrence. Current difficulties and thoughts on some possible future directions are also discussed. We explore current evidence in the field pointing towards the introduction of personalized CRC management.

Diagnostic and prognostic biomarkers in colorectal cancer and the potential role of exosomes in drug delivery

Colorectal cancer (CRC) is third most common cancer with second most common cause of death worldwide. One fourth to one fifth of the CRC cases are detected at advance stage. Early detection of colorectal cancer might help in decreasing mortality and morbidity worldwide. CRC being a heterogeneous disease, new non-invasive approaches are needed to complement and improve the screening and management of CRC. Reliable and early detectable biomarkers would improve diagnosis, prognosis, therapeutic responses, and will enable the prediction of drug response and recurrence risk. Over the past decades molecular research has demonstrated the potentials of CTCs, ctDNAs, circulating mRNA, ncRNAs, and exosomes as tumor biomarkers. Non-invasive screening approaches using fecal samples for identification of altered gut microbes in CRC is also gaining attention. Exosomes can be potential candidates that can be employed in the drug delivery system. Further, the integration of in vitro, in vivo and in silico models that involve CRC biomarkers will help to understand the interactions occurring at the cellular level. This review summarizes recent update on CRC biomarkers and their application along with the nanoparticles followed by the application of organoid culture in CRC.

Irreversible alteration of extracellular vesicle and cell-free messenger RNA profiles in human plasma associated with blood processing and storage

The discovery and utility of clinically relevant circulating biomarkers depend on standardized methods that minimize preanalytical errors. Despite growing interest in studying extracellular vesicles (EVs) and cell-free messenger RNA (cf-mRNA) as potential biomarkers, how blood processing and freeze/thaw impacts the profiles of these analytes in plasma was not thoroughly understood. We utilized flow cytometric analysis to examine the effect of differential centrifugation and a freeze/thaw cycle on EV profiles. Utilizing flow cytometry postacquisition analysis software (FCMpass) to calibrate light scattering and fluorescence, we revealed how differential centrifugation and post-freeze/thaw processing removes and retains EV subpopulations. Additionally, cf-mRNA levels measured by RT-qPCR profiles from a panel of housekeeping, platelet, and tissue-specific genes were preferentially affected by differential centrifugation and post-freeze/thaw processing. Critically, freezing plasma containing residual platelets yielded irreversible ex vivo generation of EV subpopulations and cf-mRNA transcripts, which were not removable by additional processing after freeze/thaw. Our findings suggest the importance of minimizing confounding variation attributed to plasma processing and platelet contamination.

Integrated Analysis of Mutations, miRNA and mRNA Expression in Glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is a common, malignant brain tumor in adults, with a median survival of only 15-23 months. Organisms respond to disease stress through sophisticated mechanisms at the physiological, transcriptional and metabolic levels. However, the molecular regulatory networks responsible for occurrence, progression and recurrence of glioma have yet to be elucidated.

METHODS

In this study, we sought to determine the cause of gliomas by developing an RNA-seq technique that analyzes mRNA and small RNA (sRNA) with the aim of discovering potential methods for precisely blocking key signaling pathways in occurrence, progression, and recurrence. The explication of mechanisms leading to GBM formation has become a feasible and promising new therapeutic method.

RESULTS

GBM-associated genes were identified based on their expression during the disease stress response. Analysis of the inverse correlations between microRNAs (miRNAs) and target mRNAs revealed 43 mRNA-miRNA interactions during disease progression. BOC-SMO and BOC-RAS were found to promote the malignant progression of glioma. A total of 3088 differentially expressed genes were identified as involved in several biological processes, such as amino acid metabolism, protein transport associated with immune response, cell proliferation, and cell apoptosis. Fifteen miRNAs were also identified as being differentially expressed in GBM and control groups.

CONCLUSION

The results of this study provide an important foundation for understanding the pathogenesis of glioma and discovering new therapeutic targets.

Plasma circulating cell free messenger RNA as a potential biomarker of melanoma

BACKGROUND

Blood borne cell free nucleic acids are increasingly emerging as significant non-invasive adjuncts to current methods of disease status evaluation in cancer patients. In this study, we sought to examine whether significant differences exist in the plasma transcriptomic profile of advanced melanoma patients with a high disease burden compared to patients with a low disease burden or therapeutic response.

METHODS

Pathway focussed gene expression analysis was performed using cDNA derived from the plasma circulating cell free messenger ribonucleic acid (ccfmRNA) samples of twenty-two patients with advanced melanoma. Patients were assessed with paired blood sample collection and CT scan assessments at baseline and at 3 months follow up.

RESULTS

We identified several genes which were significantly over-expressed in patients with a low disease burden or therapeutic response; BCL2L1, CXCL9, IDO1, IL13, MIF, MYD88 and TLR4 (p ≤ 0.001, versus high disease burden). There was an increase in the magnitude of fold change (2^ (-dd CT)) of BCL2L1 (p = 0.031), CCL4 (p = 0.001), CCL5 (p = 0.043), CXCL9 (p = 0.012), GZMB (p = 0.023) and TNFSF10 (p = 0.039) genes in patients with therapeutic response at 3 months follow up assessment relative to baseline assessment. Moreover, in stage IV melanoma patients with brain metastases, CCL18, CCR1, CCR4, CD274, CSF2, EGF, and PTGS2 genes were significantly over-expressed (p < 0.001, versus patients without melanoma brain metastasis).

CONCLUSION

Significant differences were observed in the plasma transcriptomic profile between the various melanoma patient groups, and we postulate that these differences may be exploited to identify novel therapeutic targets or biomarkers relevant to melanoma.

Sensitive detection of colorectal cancer in peripheral blood by a novel methylation assay

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Early detection of CRC can significantly reduce its mortality rate. Current method of CRC diagnosis relies on the invasive endoscopy. Non-invasive assays including fecal occult blood testing (FOBT) and fecal immunological test (FIT) are compromised by low sensitivity and specificity, especially at early stages. Thus, a non-invasive and accurate approach for CRC screening would be highly desirable.

RESULTS

A new qPCR-based assay combining the simultaneous detection of the DNA methylation status of ten candidate genes was used to examine plasma samples from 56 normal controls, 6 hyperplastic polys, 9 non-advanced adenomas (NAAs), 22 advanced adenomas (AAs) and 175 CRC patients, using 10 ng of cfDNA. We further built a logistic regression model for CRC diagnosis. We tested ten candidate methylation markers including twist1, vav3-as1, fbn1, c9orf50, sfmbt2, kcnq5, fam72c, itga4, kcnj12 and znf132. All markers showed moderate diagnostic performance with AUCs ranging from 0.726 to 0.815. Moreover, a 4-marker model, comprised of two previously reported markers (c9orf50 and twist1) and two novel ones (kcnj12 and znf132), demonstrated high performance for detecting colorectal cancer in an independent validation set (N = 69) with an overall AUC of 0.911 [95% confidence interval (CI) 0.834-0.988], sensitivity of 0.800 [95% CI 0.667-0.933] and specificity of 0.971 [95% CI 0.914-1.000]. The stage-stratified sensitivity of the model was 0.455 [95% CI 0.227-0.682], 0.667 [95% CI 0.289-1.000], 0.800 [95% CI 0.449-1.000], 0.800 [95% CI 0.449-1.000] and 0.842 [95% CI 0.678-1.000] for advanced adenoma and CRC stage I-IV, respectively.

CONCLUSION

kcnj12 and znf132 are two novel methylation biomarkers for CRC diagnosis. The 4-marker methylation model provides a new non-invasive choice for CRC screening and interception.

Multiparametric MRI-based machine learning models for preoperatively predicting rectal adenoma with canceration

OBJECTIVES

To propose multiparametric MRI-based machine learning models and assess their ability to preoperatively predict rectal adenoma with canceration.

MATERIALS AND METHODS

A total of 53 patients with postoperative pathology confirming rectal adenoma (n = 29) and adenoma with canceration (n = 24) were enrolled in this retrospective study. All patients were divided into a training cohort (n = 42) and a test cohort (n = 11). All patients underwent preoperative pelvic MR examination, including high-resolution T2-weighted imaging (HR-T2WI) and diffusion-weighted imaging (DWI). A total of 1396 radiomics features were extracted from the HR-T2WI and DWI sequences, respectively. The least absolute shrinkage and selection operator (LASSO) was utilized for feature selection from the radiomics feature sets from the HR-T2WI and DWI sequences and from the combined feature set with 2792 radiomics features incorporating two sequences. Five-fold cross-validation and two machine learning algorithms (logistic regression, LR; support vector machine, SVM) were utilized for model construction in the training cohort. The diagnostic performance of the models was evaluated by sensitivity, specificity and area under the curve (AUC) and compared with the Delong's test.

RESULTS

Ten, 8, and 25 optimal features were selected from 1396 HR-T2WI, 1396 DWI and 2792 combined features, respectively. Three group models were constructed using the selected features from HR-T2WI (Model_T2), DWI (Model_DWI) and the two sequences combined (Model_combined). Model_combined showed better prediction performance than Model_T2 and Model_DWI. In Model_combined, there was no significant difference between the LR and SVM algorithms (p = 0.4795), with AUCs in the test cohort of 0.867 and 0.900, respectively.

CONCLUSIONS

Multiparametric MRI-based machine learning models have the potential to predict rectal adenoma with canceration. Compared with Model_T2 and Model_DWI, Model_combined showed the best performance. Moreover, both LR and SVM have equal excellent performance for model construction.

Circulating RNA biomarkers in diffuse large B-cell lymphoma: a systematic review

Diffuse large B-cell lymphoma (DLBCL) is the most common histological subtype of non-Hodgkin's lymphomas (NHL). DLBCL is an aggressive malignancy that displays a great heterogeneity in terms of morphology, genetics and biological behavior. While a sustained complete remission is obtained in the majority of patients with standard immunochemotherapy, patients with refractory of relapsed disease after first-line treatment have a poor prognosis. This patient group represents an important unmet need in lymphoma treatment. In recent years, improved understanding of the underlying molecular pathogenesis had led to new classification and prognostication tools, including the development of cell-free biomarkers in liquid biopsies. Although the majority of studies have focused on the use of cell-free fragments of DNA (cfDNA), there has been an increased interest in circulating-free coding and non-coding RNA, including messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA) and circular RNA (circRNA), as well as RNA encapsulated in extracellular vesicles or tumor-educated platelets (TEPs). We performed a systematic search in PubMed to identify articles that evaluated circulating RNA as diagnostic, subtype, treatment response or prognostic biomarkers in a human DLBCL population. A total of 35 articles met the inclusion criteria. The aim of this systematic review is to present the current understanding of circulating RNA molecules as biomarker in DLBCL and to discuss their future potential.

Colorectal cancer screening and diagnosis: omics-based technologies for development of a non-invasive blood-based method

Introduction: Colorectal cancer (CRC) is one of the most important health problems in the Western world. In order to reduce the burden of the disease, two strategies are proposed: screening and prompt detection in symptomatic patients. Although diagnosis and prevention are mainly based on colonoscopy, fecal hemoglobin detection has been widely implemented as a noninvasive strategy. Various studies aiming to discover blood-based biomarkers have recently emerged.Areas covered: The burgeoning omics field provides diverse high-throughput approaches for CRC blood-based biomarker discovery. In this review, we appraise the most robust and commonly used technologies within the fields of genomics, transcriptomics, epigenomics, proteomics, and metabolomics, together with their targeted validation approaches. We summarize the transference process from the discovery phase until clinical translation. Finally, we review the best candidate biomarkers and their potential clinical applicability.Expert opinion: Some available biomarkers are promising, especially in the field of epigenomics: DNA methylation and microRNA. Transference requires the joint collaboration of basic researchers, intellectual property experts, technology transfer officers and clinicians. Blood-based biomarkers will be selected not only based on their diagnostic accuracy and cost but also on their reliability, applicability to clinical analysis laboratories and their acceptance by the population.

Circulating Cell-Free Nucleic Acids: Main Characteristics and Clinical Application

Liquid biopsy recently became a very promising diagnostic method that has several advantages over conventional invasive methods. Liquid biopsy may serve as a source of several important biomarkers including cell-free nucleic acids (cf-NAs). Cf-DNA is widely used in prenatal testing in order to characterize fetal genetic disorders. Analysis of cf-DNA may provide information about the mutation profile of tumor cells, while cell-free non-coding RNAs are promising biomarker candidates in the diagnosis and prognosis of cancer. Many of these markers have the potential to help clinicians in therapy selection and in the follow-up of patients. Thus, cf-NA-based diagnostics represent a new path in personalized medicine. Although several reviews are available in the field, most of them focus on a limited number of cf-NA types. In this review, we give an overview about all known cf-NAs including cf-DNA, cf-mtDNA and cell-free non-coding RNA (miRNA, lncRNA, circRNA, piRNA, YRNA, and vtRNA) by discussing their biogenesis, biological function and potential as biomarker candidates in liquid biopsy. We also outline possible future directions in the field.

A novel mesenchymal-associated transcriptomic signature for risk-stratification and therapeutic response prediction in colorectal cancer

Risk stratification in Stage II and III colorectal cancer (CRC) patients is critical, as it allows patient selection for adjuvant chemotherapy. In view of the inadequacy of current clinicopathological features for risk-stratification, we undertook a systematic and comprehensive biomarker discovery effort to develop a risk-assessment signature in CRC patients. The biomarker discovery phase examined 853 CRC patients, and identified a gene signature for predicting recurrence-free survival (RFS). This signature was validated in a meta-analysis of 1212 patients from nine independent datasets, and its performance was compared against established prognostic signatures and consensus molecular subtypes (CMS). In addition, a risk-prediction model was trained (n = 142), and subsequently validated in an independent clinical cohort (n = 286). As a result, this mesenchymal-associated transcriptomic signature (MATS) identified high-risk CRC patients with poor RFS in the discovery (hazard ratio [HR]: 1.79), and nine validation cohorts (HR: 1.86). In multivariate analysis, MATS was the most significant predictor of RFS compared to established prognostic signatures and CMS subtypes. Intriguingly, MATS robustly identified CMS4-subtype in multiple CRC cohorts (AUC = 0.92-0.99). In the two clinical cohorts, MATS stratified low and high-risk groups with a 5-year RFS in the training (HR: 4.11) and validation cohorts (HR: 2.55), as well as predicted response to adjuvant therapy in Stage II and III CRC patients. We report a novel prognostic and predictive biomarker signature in CRC, which is superior to currently used approaches and have the potential for clinical translation in near future.