Noninvasive Detection Of Colorectal Cancer Research Articles

Selection of optimal extraction and RT-PCR protocols for stool RNA detection of colorectal cancer associated immune genes

There is a growing interest in using fecal mRNA transcripts as biomarkers for non-invasive detection of colorectal cancer (CRC). The following study compares different RNA extraction and reverse transcription PCR (RT-PCR) methods for mRNA detection in stool and identifies a robust and sensitive protocol. A combination of the Stool total RNA purification kit (Norgen) and the Superscript III one-step RT-PCR kit (Invitrogen) provided high RNA purity and sensitive and consistent mRNA detection, making them well-suited candidates for large-scale studies. We tested the protocol by detecting the mRNA of several immune genes (CXCL1, IL8, IL1B, IL6, PTGS2, and SPP1) in 22 CRCs, 24 adenomatous polyps, and 22 control stool samples. All these inflammatory markers, except for CXCL1, showed a strong association with CRC. Cancer stool samples showed increased levels of IL1B, IL8, and PTGS2 transcripts compared to polyp and control groups. Thus, this work supports the potential use of fecal mRNA as biomarkers for CRC detection.

Non-invasive colorectal cancer detection using multimodal deep learning ensemble classifier.

3066 Background: The demand for alternative, non-invasive methods for colorectal cancer (CRC) screening is substantial. Cell-free DNA (cfDNA) whole genome sequencing (WGS) offers a promising avenue, utilizing diverse fragmentomic data. We aimed to develop a new approach: integrating fragment end motif by size (FEMS) with genomic coverage (COV) of cfDNA to enhance CRC screening. Methods: Participants were comprised of 1,506 colonoscopy verified normal samples, 130 advanced adenoma (AA) patients, 302 CRC patients (stage I: 28.5%, stage II: 25.5%, stage III: 31.1%, stage IV: 14.2%, unknown: 0.7%). We generated low depth cfDNA-WGS data (a minimum 40 million reads per sample) using the Novaseq 6000 sequencer. We minimized batch bias by normalizing with the same samples for each experimental batch. The development set comprised 1,332 samples (1,023 normal, 103 AA, and 206 CRC), while the validation set consisted of 606 samples (483 normal, 27 AA, and 96 CRC). Results: Our new algorithm achieved 84.0% sensitivity (95% CI: 81%-86%) for CRC and 69.9% (95% CI: 66%-81%) for AA in the development set, with a specificity of 90.0%. These findings were consistent in the external set with 84.9% specificity (95% CI: 82%-88%) and sensitivities of 80.2% (95% CI: 72%-88%) and 63.0% (95% CI: 44%-82%) for CRC and AA, respectively. The sensitivities across stages (Stage I: 80%, Stage II: 86.8%, Stage III: 78.8%, Stage IV: 96.7%) were similarly reflected in the validation sets (Stage I: 74%, Stage II: 83%, Stage III: 79%, Stage IV: 92%). Conclusions: Our multimodal deep learning model shows promise for accurate non-invasive colon cancer and AA detection using low-coverage cfDNA WGS. Its strong performance in detecting not only CRC but also AA lesions suggests its potential for early intervention and improved patient outcomes. The use of colonoscopy-verified normal samples strengthens the study's credibility and paves the way for future clinical translation.

Identification and validation of the surface proteins FIBG, PDGF-β, and TGF-β on serum extracellular vesicles for non-invasive detection of colorectal cancer: experimental study.

The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and the absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multi-centre study comprising 404 individuals. In the application phase, the authors evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. Through 4D-DIA proteomic analysis, the authors identified seven potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of three EVs surface proteins, FIBG, PDGF-β and TGF-β, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an area under the curve (AUC) of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-β, and TGF-β as novel diagnostic biomarkers for CRC. The development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Abstract 1063: IsomiR relative proportion (IRP) within miRNA family as an efficient biomarker for noninvasive colorectal cancer detection

Abstract Background: Cell free miRNA has been widely used for disease diagnosis, particularly in cancers. The latest research has also demonstrated that isomiRs (isoform miRNAs) can serve as superior markers, displaying enhanced diagnostic performance in cancer diagnosis. However, the low detection sensitivities of miRNA/isomiRs in previous methods in plasma have limited their broad implementations for screening purpose. In this study, we propose a new isomiRs feature of isomiR relative proportion (IRP), which was validated with high performance in Colorectal Cancer (CRC) early diagnosis. Methods: A total of 1036 participants were enrolled from the National Colorectal Cancer Cohort (NCRCC), and 836 participants were eligible for plasma collection, including 238 controls, 373 CRC patients, 41 inflammatory bowel disease (IBD), 5 intramucosal carcinoma (Tis) and 179 advanced precancerous lesions (APL). Total circulating small RNA was extracted, followed by library preparation using UMI-based approach. Subsequently, small RNA sequencing was conducted using DNB-seq, and bioinformatic analysis was performed thereafter. The samples were randomly assigned into training (49%), test (30%) and validation (21%) sets. Models based on isomiR relative proportion (IRP), isomiR relative expression (IRE) or both features were constructed by beam search and random forest algorithms in training and test sets, and results were verified in validation set. Results: Differential IRP or IRE features were identified between cancer and controls. IRP identified 132 specific differential expressed isomiRs. Models constructed using either IRP or IRE features showed high performance (both AUC > 0.9). However, there was improvement in IRP feature model in the validation set (sensitivity of IRP: 0.923, sensitivity of IRE: 0.859) compared with IRE model. We then found that there may be complementarities between IRP and IRE features, and the combination model (34 IRP+IRE features) improved cancer detection performance (AUC: 0.953). Finally, the risk scores predicted by this combination model increased gradually across CRC progression (R=0.921), and the sensitivity of APL was 0.626. Conclusion: We improved the small-RNA sequencing method and developed an IRP method, and present that IRP as a new feature not only demonstrate the ability of CRC early detection, but also revealed the CRC progressing process. Besides, the combination of IRP and IRE improved the performance of diagnosis. These results highlight the potential value of the IRP feature in early cancer detection. Citation Format: Yeting Hu, Wei Lu, Chengcheng Liu, Xiaozhuan Dai, Jiasheng Xu, Xiangxing Kong, Yunfeng Zhu, Yao Ye, Lihao Chen, Xiaolong An, Fan Wu, Shiqing Ma, Nana Wang, Qian Xiao, Jun Liu, Kefeng Ding. IsomiR relative proportion (IRP) within miRNA family as an efficient biomarker for noninvasive colorectal cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1063.

Multimodal epigenetic sequencing analysis (MESA) of cell-free DNA for non-invasive colorectal cancer detection

BackgroundDetecting human cancers through cell-free DNA (cfDNA) in blood is a sensitive and non-invasive option. However, capturing multiple forms of epigenetic information remains a technical and financial challenge.MethodsTo address this, we developed multimodal epigenetic sequencing analysis (MESA), a flexible and sensitive approach to capturing and integrating a diverse range of epigenetic features in cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq. MESA enables simultaneous inference of four epigenetic modalities: cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and windowed protection score for regions surrounding gene promoters and polyadenylation sites.ResultsWhen applied to 690 cfDNA samples from 3 colorectal cancer clinical cohorts, MESA’s novel modalities, which include nucleosome fuzziness, and genomic features, including polyadenylation sites, improve cancer detection beyond the traditional epigenetic markers of promoter DNA methylation.ConclusionsTogether, MESA stands as a major advancement in the field by utilizing comprehensive and complementary epigenetic profiles of cfDNA for effective non-invasive cancer detection.

Pioneering noninvasive colorectal cancer detection with an AI-enhanced breath volatilomics platform.

Background: The sensitivity and specificity of current breath biomarkers are often inadequate for effective cancer screening, particularly in colorectal cancer (CRC). While a few exhaled biomarkers in CRC exhibit high specificity, they lack the requisite sensitivity for early-stage detection, thereby limiting improvements in patient survival rates. Methods: In this study, we developed an advanced Mass Spectrometry-based volatilomics platform, complemented by an enhanced breath sampler. The platform integrates artificial intelligence (AI)-assisted algorithms to detect multiple volatile organic compounds (VOCs) biomarkers in human breath. Subsequently, we applied this platform to analyze 364 clinical CRC and normal exhaled samples. Results: The diagnostic signatures, including 2-methyl, octane, and butyric acid, generated by the platform effectively discriminated CRC patients from normal controls with high sensitivity (89.7%), specificity (86.8%), and accuracy (AUC = 0.91). Furthermore, the metastatic signature correctly identified over 50% of metastatic patients who tested negative for carcinoembryonic antigen (CEA). Fecal validation indicated that elevated breath biomarkers correlated with an inflammatory response guided by Bacteroides fragilis in CRC. Conclusion: This study introduces a sophisticated AI-aided Mass Spectrometry-based platform capable of identifying novel and feasible breath biomarkers for early-stage CRC detection. The promising results position the platform as an efficient noninvasive screening test for clinical applications, offering potential advancements in early detection and improved survival rates for CRC patients.

Potential of Fecal Carcinoembryonic Antigen for Noninvasive Detection of Colorectal Cancer: A Systematic Review

Carcinoembryonic antigen (CEA) is more abundant in feces than in serum; however, evidence for the role of fecal CEA (FCEA) in the detection of colorectal cancer (CRC) is limited. We conducted a systematic review of studies that evaluated FCEA for the noninvasive detection and diagnosis of CRC. PubMed and Web of Science were searched for relevant studies published until 18 January 2023. Information on publication year, study design, country, study population characteristics, FCEA and serum CEA (SCEA) concentrations, and diagnostic performance was summarized. Two authors independently extracted data and assessed the risk of bias and applicability of each included study. Seven studies published between 1979 and 2021, all conducted in clinical settings and together involving 399 CRC patients and 889 controls, were identified. Significant differences in FCEA concentrations were observed between CRC and control groups in all studies. Methods for detecting FCEA varied, with the electronic chemiluminescence immunoassay (ECLIA) being used in the most recent studies. Reported sensitivities, specificities, and area under the curves of FCEA ranged from 50.0% to 85.7%, 73.0% to 100.0%, and 0.704 to 0.831, respectively. In direct comparisons, the diagnostic performance of FCEA was better than that of SCEA. The potential role of FCEA as a novel, noninvasive, easily measurable biomarker for the diagnosis of CRC requires further evaluation in screening settings.

Identification of a 5-Hydroxymethylation Signature in Circulating Cell-Free DNA for the Noninvasive Detection of Colorectal Cancer.

Background As a crucial epigenetic modification, DNA 5-hydroxymethylcytosine (5-hmC) plays a key role during colorectal cancer (CRC) carcinogenesis. Nevertheless, the levels of 5-hmC-related genes in the circulating DNA of CRC remain largely unknown. Methods and Results The GSE81314 dataset from the Gene Expression Omnibus (GEO), which was generated by chemical marking-based low-input shotgun sequencing to detect 5-hmC in circulating cell-free DNA (cfDNA) was used in the present study. The GSE81314 dataset includes data for 8 plasma samples from healthy individuals and 4 plasma samples from CRC patients. The difference in the 5-hmC levels in cfDNA between the CRC group and healthy individuals was analyzed by the differentially expressed genes (DEG) package. Weighted gene coexpression network analysis (WGCNA) was conducted to analyze gene coexpression modules associated with sample characteristics. DEG analysis identified 19 upregulated and 9 downregulated 5-hmC-related genes. WGCNA showed that the pink, purple, and brown modules, which contain 531 genes in total, were significantly correlated with CRC (0.66, 0.61, and -0.59, respectively). We used gene set enrichment analysis (GSEA) software to compare 5-hmC-related genes and pathways between CRC patients and healthy controls. We further performed a protein–protein interaction (PPI) analysis and identified 4 nodes (LCN2, LRG1, S100P, and TACSTD2) that played key roles in the network, and we analyzed the expression of these nodes S100P in the GEPIA database. Consistent with the 5-hmC levels in CRC patient plasma, our external validation results from the GEPIA and UALCAN databases showed that LCN2, LRG1, S100P, and TACSTD2 were highly expressed in CRC tissue compared with controls. The DNA promoter methylation levels of LCN2, LRG1, and S100P were lower in CRC tissue than in normal control tissue. Conclusion The present findings suggest that abnormality in cell-free DNA hydroxylation in plasma may be associated with CRC. In addition, the 5-hmC levels of LCN2, LRG1, S100P, and TACSTD2 in circulating cfDNA may be used as potential noninvasive markers for CRC.

Proteomic Analyses of Fibroblast- and Serum-Derived Exosomes Identify QSOX1 as a Marker for Non-invasive Detection of Colorectal Cancer.

Simple SummaryEarly diagnosis of colorectal cancer (CRC) is crucial to improve patient outcomes. The tumour microenvironment immediately adapts to malignant transformations, including the activation of fibroblasts in the connective tissue nearby. In this study, we investigated fibroblast activity-related protein secretion via extracellular vesicles (EVs). QSOX1, a protein identified to be significantly reduced in activated fibroblasts and derived EVs, was also found to be significantly reduced in circulating blood plasma EVs of CRC patients as compared to control patients. Hence, blood plasma EV-associated QSOX1 represents a promising platform for diagnostic CRC screening.The treatment of colorectal cancer (CRC) has improved during the last decades, but methods for crucial early diagnosis are yet to be developed. The influence of the tumour microenvironment on liquid biopsies for early cancer diagnostics are gaining growing interest, especially with emphasis on exosomes (EXO), a subgroup of extracellular vesicles (EVs). In this study, we established paired cancer-associated (CAFs) and normal fibroblasts (NF) from 13 CRC patients and investigated activation status-related protein abundance in derived EXOs. Immunohistochemical staining of matched patient tissue was performed and an independent test cohort of CRC patient plasma-derived EXOs was assessed by ELISA. A total of 11 differentially abundant EV proteins were identified between NFs and CAFs. In plasma EXOs, the CAF-EXO enriched protein EDIL3 was elevated, while the NF-EXO enriched protein QSOX1 was diminished compared to whole plasma. Both markers were significantly reduced in patient-matched CRC tissue compared to healthy colon tissue. In an independent test cohort, a significantly reduced protein abundance of QSOX1 was observed in plasma EXOs from CRC patients compared to controls and diagnostic ROC curve analysis revealed an AUC of 0.904. In conclusion, EXO-associated QSOX1 is a promising novel marker for early diagnosis and non-invasive risk stratification in CRC.

Fecal Multidimensional Assay for Non-Invasive Detection of Colorectal Cancer: Fecal Immunochemical Test, Stool DNA Mutation, Methylation, and Intestinal Bacteria Analysis.

BackgroundFecal immunochemical test (FIT), DNA mutation, DNA methylation, and microbial dysbiosis all showed promising in colorectal cancer (CRC) non-invasive detection. We assessed CRC detection with an assay combining all these strategies and investigated the effect of clinical features on the performance of this comprehensive test.MethodsWe performed a multidimensional analysis study using stool samples collected from 108 patients with CRC, 18 patients with colorectal adenoma, and 36 individuals with no evidence of colorectal disease. The multidimensional analysis of stool samples including FIT, stool DNA (sDNA) tests for three methylated genes (Septin9, NDRG4, BMP3) and three mutated genes (KRAS, BRAF, PI3KCA) using next generation sequencing as well as detection of stool bacteria level of Fusobacterium nucleatum and Parvimonas micra using qPCR method. We used a linear support vector classification model to analyze the data.ResultsThe sensitivity of FIT alone was 69.4% for CRC and 11.1% for adenoma. Separately, the sensitivity of the detection of intestinal bacteria, DNA mutation, and DNA methylation for CRC was 58.3, 50.0, and 51.9%, respectively. The combination of FIT and sDNA tests had a sensitivity of 81.5% for CRC (AUC: 0.93, better than FIT alone, P = 0.017) and 27.8% for adenoma with 94.4% specificity. Sensitivity of the multidimensional test to detect CRC with stage II (84.6%) and III (91.9%) CRC was relatively higher (88.2%) than that of patients with stage I (60.0%) and stage IV (75.0%) (P = 0.024). The rate of CRC detection increased with tumor size (P = 0.008) and age (P = 0.04). Interestingly, the rate of CRC detection was higher in smoking persons than non-smokers with marginal significance (P = 0.08).ConclusionsThe multidimensional assay of stool samples combining FIT and stool DNA tests further improved the diagnostic sensitivity for CRC. This could provide new approach for improvement of CRC screening and further demonstrations are warranted.

Rapid and label-free urine test based on surface-enhanced Raman spectroscopy for the non-invasive detection of colorectal cancer at different stages.

The concept of being able to urinate in a cup and screen for colorectal cancer (CRC) is fascinating to the public at large. Here, a simple and label-free urine test based on surface-enhanced Raman spectroscopy (SERS) was employed for CRC detection. Significant spectral differences among normal, stages I-II, and stages III-IV CRC urines were observed. Using discriminant function analysis, the diagnostic sensitivities of 95.8%, 80.9%, and 84.3% for classification of normal, stages I-II, and stages III-IV CRC were achieved in training model, indicating the great promise of urine SERS as a rapid, convenient and noninvasive method for CRC staging detection.

Combinatorial cell surface display system in Escherichia coli for noninvasive colorectal cancer detection

Abstract Navigation and recognition of disease lesions remain challenging during colorectal cancer diagnosis and treatment, given that the precision and capacity of using specific surface antigens as recognition sites are relatively lacking. Moreover, the low penetration rate of noninvasive detection methods has delayed disease diagnosis in developing countries. We developed a bacterial device targeting the Thomsen–Friedenreich antigen, which is abundant on lesion tissue, and produced vesicles that serve as markers for ultrasonic detection. The device uses a bacterial cell surface display system and acoustic reporter gene to function as a screening device for colorectal cancer detection. The diagnostic efficiency of this device was determined by flow cytometry, immunohistochemistry, microfluidic chip-based assay, and ultrasonic examinations on both cellular and tissue scales. In all scales and experiments, our device showed great feasibility upon differentiating disease lesion and normal tissue, while foundation of the usage of vesicle reporter system as noninvasive method has also been laid. The application of this device provides insight into the practicability and prospect of bacterial detecting agents in the field of diagnostics. All animal studies were approved by the Institutional Animal Care and Use Committee of Shanghai Jiao Tong University, China (approval No. 201801015) on February 23, 2018.

Abstract 4213: Stool-derived eukaryotic RNA (seRNA) assay for noninvasive detection of colorectal cancer and high-risk adenomas

Abstract Colorectal cancer (CRC) is the second leading cause of cancer related deaths in the United States. The high mortality rate for CRC is largely attributable to the frequency of late-stage diagnoses, caused by low patient compliance with screening guidelines. A novel nucleic acid extraction method that isolates stool-derived eukaryotic RNA (seRNA) has permitted development of a colorectal cancer stool diagnostic test (CRC-SDT) that uses a fecal immunochemical test (FIT) and 11 seRNA transcripts to serve as a reliable and noninvasive screening alternative to lower mortality associated with CRC. Stool samples were obtained from 190 individuals prior to undergoing a screening colonoscopy. Patients were diagnosed as either having colorectal cancer, having high-risk adenomas (high-grade dysplasia, villous growth pattern, or >1.0cm in size), or healthy (low-risk adenomas, benign polyps, and/or no findings on a colonoscopy). FITs were obtained for each sample. Samples that had a positive FIT were considered positive for the CRC-SDT. Samples that had a negative FIT underwent seRNA isolation, library preparation (Illumina TruSeq Targeted RNA) and subsequent sequencing (Illumina NextSeq 550). A random forest model was built using 11 transcripts that were differentially expressed (log2 fold-change > 1; ANOVA p < 0.05) between diseased patients (CRC and high-risk adenomas) relative to the healthy cohort. Internal 10-fold cross-validation was performed for the training set and a receiver operating characteristic (ROC) area under the curve (AUC) determined model accuracy for cancer and high-risk adenomas relative to the healthy cohort. Model predictions for an independent hold-out test set were used to determine model accuracy for colorectal cancer and high-risk adenomas. Internal cross-validation for 154 samples attained a ROC AUC of 0.82. The trained model was employed on the independent hold-out test set of 36 samples and model predictions were compared to colonoscopy results. The model attained a 100% sensitivity for CRC (n = 7), a 60% sensitivity for high-risk adenomas (n = 5), and an 88% combined specificity for the healthy cohort (n = 24). CRC-SDT uses 12 biomarkers (FIT and expression from 11 seRNA transcripts) to accurately detect CRC and high-risk adenomas. Use of seRNA biomarkers dramatically improves detection of high-risk adenomas relative to existing noninvasive screening methods for CRC. Citation Format: Erica K. Barnell, Yiming Kang, Katie M. Campbell, Kimberly R. Kruse, Andrew R. Barnell, Elizabeth M. Wurtzler. Stool-derived eukaryotic RNA (seRNA) assay for noninvasive detection of colorectal cancer and high-risk adenomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4213.

Tu1010 – Validation of a Stool-Derived Eukaryotic Rna Assay for Noninvasive Detection of Colorectal Cancer and High-Risk Adenomas

Tu1010 – Validation of a Stool-Derived Eukaryotic Rna Assay for Noninvasive Detection of Colorectal Cancer and High-Risk Adenomas

Epigenetic biomarkers for noninvasive detection of colorectal cancer.

45 Background: Aberrant DNA hypermethylation is known to be a major mechanism for inactivation of cancer-associated genes, including tumor suppressor genes, in colorectal cancer (CRC) and in other human cancers. Cancer-specific DNA methylation patterns of cell-free DNA (cfDNA) isolated from blood samples is a non-invasive method to obtain representative epigenetic information from solid tumors. In the present study, we identified and validated colorectal cancer-specific methylation markers for diagnosis of the disease with high sensitivity and specificity. We also compared the relative amount of DNA methylation at these target sites in relation to colorectal cancer stage. Methods: For marker validation, a total of 154 samples drawn from 68 subjects diagnosed with colorectal cancer (Stage I to IV), 42 healthy donors, 14 subjects with benign colorectal diseases, and 30 subjects diagnosed with other cancer types (breast, liver and lung cancer: 10 cases each) were obtained for a randomized, blinded study. Cell-free DNA was then extracted from the samples, bisulfite converted, and DNA methylation was quantified by using the IvyGene Platform. Results: By quantifying DNA methylation at the target sites, colorectal cancer samples were differentiated from samples drawn from healthy subjects or subjects with benign disease with an overall sensitivity of 93% (95% CI: 86-99) and specificity of 100% (95% CI: 85-100). All stages (I to IV) of colorectal cancer were identified with sensitivities ranging from 67% to 100%. None of the 30 samples drawn from subjects diagnosed with breast, liver or lung cancers were incorrectly identified as a colorectal cancer by the assay, for a calculated analytical specificity of 100%. Conclusions: These results demonstrate the high diagnostic potential of cfDNA methylation markers isolated from blood for the detection of colorectal cancer. Taken together, these findings establish the utility of methylation biomarkers for the detection of colorectal cancers as early as Stage I. In addition, a quantitative analysis of cfDNA provides an opportunity for non-invasive detection and monitoring of disease.

Issue Highlights

Issue Highlights

Global and targeted circulating microRNA profiling of colorectal adenoma and colorectal cancer.

Circulating microRNAs (miRNAs) are emerging as promising biomarkers for cancer. The objective of the current study was to investigate the potential of circulating cell-free miRNAs as biomarkers for colorectal cancer (CRC) and its precursor lesion, colorectal adenoma. The serum levels of 800 miRNAs were assessed in a discovery set of 21 patients with CRC, 19 patients with adenoma, and 21 healthy controls using the NanoString miRNA analysis platform. Significantly differentially expressed miRNAs were examined further in a validation cohort of 34 patients with CRC, 33 patients with adenoma, and 35 healthy controls using Fluidigm quantitative polymerase chain reaction assays. The ratios between the expression values of the differentially expressed miRNAs were computed. Three miRNA ratios (miR-17-5p/miR-135b, miR-92a-3p/miR135b, and miR-451a/miR-491-5p) were validated for discriminating patients with adenoma and those with CRC from the healthy control group, and 5 miRNA ratios (let-7b/miR-367-3p, miR-130a-3p/miR-409-3p, miR-148-3p/miR-27b, miR-148a-3p/miR-409-3p, and miR-21-5p/miR-367-3p) were validated for discriminating patients with CRC from those with adenoma and healthy controls. The area under the receiver operating characteristic curve values for the 3 miRNA ratios in discriminating patients with adenoma from healthy controls were 0.831 and 0.735, respectively, in the discovery and validation sets. The area under the receiver operating characteristic curve values for the 5 miRNA ratios in discriminating patients with CRC from those with adenoma were 0.797 and 0.732, respectively, in the discovery and validation sets. Pathway analysis revealed that target genes regulated by the miRNAs from the miRNA ratios were enriched mainly in metabolism-related and inflammation-related pathways. The data from the current study suggest that circulating miRNAs can distinguish patients with CRC and those with adenoma and may represent novel biomarkers for the early, noninvasive detection of CRC. Cancer 2018;124:785-96. © 2017 American Cancer Society.

Fecal Clostridium symbiosum for Noninvasive Detection of Early and Advanced Colorectal Cancer: Test and Validation Studies

ObjectiveCurrent non-invasive early detection of colorectal cancer (CRC) requires improvement. We aimed to identified a fecal Clostridium symbiosum-based biomarker for early and advanced colorectal cancer detection. DesignIn the test stage, the relative abundance of Clostridium symbiosum (C. symbiosum) was measured by qPCR in 781 cases including 242 controls, 212 colorectal adenoma (CRA) patients, 109 early CRC (tumor restricted to the submucosa) patients, 218 advanced CRC patients. The prediction accuracy was compared to Fusobacterium nucleatum (F. nucleatum), fecal immunochemical test (FIT) and CEA (carcinoembryonic antigen) and validated in an independent cohort of 256 subjects. Current status of the trial:ongoing/still enrolling. Primary endpoint:June, 2017 (Clinicaltrials.gov Identifier NCT02845973). ResultsSignificant stepwise increase of C. symbiosum abundance was found in CRA, early CRC and advanced CRC (P<0.01). C. symbiosum outperformed all the other markers in early CRC prediction performance. The combination of C. symbiosum and FIT achieved better performance (0.803 for test cohort and 0.707 for validation cohort). For overall discrimination of CRCs, the combination of all above markers achieved the performance of 0.876. ConclusionsFecal C. symbiosum is a promising biomarker for early and noninvasive detection of colorectal cancer, being more effective than F. nucleatum, FIT and CEA. Combining C. symbiosum and FIT or CEA may improve the diagnosis power.

Cost-effectiveness of High-performance Biomarker Tests vs Fecal Immunochemical Test for Noninvasive Colorectal Cancer Screening

Biomarker assays could increase the accuracy of noninvasive detection of colorectal cancer (CRC); fecal immunochemical tests (FITs) are estimated to miss 27%-47% of CRCs and 70%-80% of advanced adenomas per round of screening. We investigated the conditions under which biomarker screens would be cost-effective compared with FIT screens of average-risk individuals. We used the MISCAN-Colon microsimulation model to estimate the effects of various CRC screening test characteristics on life-years gained (LYG) and; age-specific all-cause mortality was based on the 2010 Dutch life tables. Simulated CRC incidence rate and CRC stage distribution were calibrated to observed data in The Netherlands from 1999 through 2003 (before opportunities for screening). Survival rates after diagnosis of CRC at an age younger than 75 years were based on CRC relative survival data from 1985 through 2004; survival for individuals diagnosed at an age of 75 years or older was adjusted to fit the observed age-increasing mortality/incidence ratio. We modeled FIT along with hypothetical biomarker tests with different test performance levels. For each biomarker test we calculated the maximum unit cost for the test to be cost-effective compared with FIT, assuming a willingness-to-pay threshold of €50,000 ($56,000) per LYG. Biennial FIT screening of subjects 55-75 years old provided 84.9 LYG at a cost of €122,000 ($137,000) per 1000 participants. Considering a unit cost of €7 ($8) for FIT (including kit and analysis only, excluding organizational costs), a biomarker test that detects CRC with higher levels of specificity and sensitivity (100%) and advanced adenomas at a proportionally higher level of sensitivity (53%) should never exceed a cost of €51 ($57). The threshold cost could increase to more than €200 ($224) for high-performing biomarker tests in cases of limited colonoscopy capacity or higher uptake of this test. By using the MISCAN-Colon microsimulation model to estimate effects of CRC screening tests, we found that for a biomarker test with increased overall performance to be cost-effective, it should not exceed 7-fold the unit cost of FIT. This maximum would increase substantially if colonoscopy becomes more expensive or scarce, or if the new test has higher screening uptake. These values could be used to estimate the added value of new biomarkers compared with current FIT screening.

Abstract 5303: FAIMS technology in urinary volatile organic compound analysis to detect colorectal cancer

Abstract Introduction This is an investigation of the capability of FAIMS (Field Asymmetric Ion Mobility Spectrometry) technology as a tool for non-invasive detection of Colorectal Cancer (CRC) through urinary volatile organic compound analysis. It expands on "Detection of Colorectal Cancer (CRC) by Urinary Volatile Organic Compound Analysis" (Ramesh P. Arasaradnam et al, 2014) with an increased sample population and local to Japan, also comparing in-house data of CA19-9 and carcinoembryonic antigen (CEA) markers. Experiment Conducted at Nippon Medical School Chiba Hokusoh Hospital, urine samples were collected and frozen at -80°C from 139 patients at various stages of CRC and 78 healthy control samples. The samples were thawed in batches and placed in ice hours prior to testing. 2 ml of each urine sample was aliquoted into 10 ml vials for processing with the commercial FAIMS device (Lonestar, Owlstone, UK). Each vial was heated in the device to 40°C to create headspace with sufficient VOCs then a carrier gas (clean dry air) delivered the headspace (0.5 L/min) diluted with a make-up flow (2 L/min). The FAIMS device was set to scan at 0 to 100% electric dispersion field in 51 steps and compensation voltage between -6 V and +6 V in 512 steps, producing data matrices for each sample's analysis. Principal Component Analysis (PCA) followed by Partial Least Squares Discriminant Analysis (PLS-DA) of each sample was conducted using SIMCA 13 (Umetrics, Sweden). See Table Conclusions FAIMS technology achieved a high rate of separation between the CRC and healthy control urine samples with 64.7% sensitivity and 82.1% specificity overall. As the CRC stage advances the sensitivity increased from 27.3% to 100%. Results show excellent potential to use FAIMS technology as an early screening tool for CRC, particularly impressive compared to in-house sensitivity data of CA19-9 and CEA markers. Further research into FAIMS screening of other cancer types through VOC biomarker analysis of urine, breath, and feces is recommended. &amp;gt;Detection ResultsCRC STAGEFAIMSOTHER MARKERSCA19-9CEATrue PositiveFalse NegativeSensitivityFalse PositiveTrue NegativeSpecificityNo. of SamplesSensitivitySensitivityI123227.3%146482.1%434.7%18.6%II181260.0%146482.1%3116.1%32.3%III45590.0%146482.1%5219.2%36.5%IV150100%146482.1%1735.3%64.7%ALL904964.7%146482.1%14316.1%33.6% Citation Format: Christopher Psutka, Marina Yamada, Akihisa Matsuda, Kazuya Yamahatsu, Satoshi Matsumoto, Toshihiko Kitayama, Nobuo Nakano, Jyunichi Koyano, Tohru Mikoshiba, Masao Miyashita. FAIMS technology in urinary volatile organic compound analysis to detect colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5303. doi:10.1158/1538-7445.AM2017-5303