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Early Assessment of Colorectal Cancer by Quantifying Circulating Tumor Cells in Peripheral Blood: ECT2 in Diagnosis of Colorectal Cancer.

ABSTRACT: Circulating tumor cells (CTCs) in peripheral blood is an indication of poor prognosis for patients with different cancer types. However, most of the available technologies for detecting CTCs show low sensitivity and specificity. Therefore, we attempted to find an alternative marker for CTCs of colorectal cancer. We have directly extracted RNA from CTCs contained in 1.5 mL peripheral blood from 90 colorectal cancer patients and 151 healthy donors, and screened these samples for candidate marker genes by nested real-time quantitative polymerase chain reaction (PCR). From genes selected from a public database of microarray analyses, we successfully identified epithelial cell transforming sequence 2 oncogene (ECT2) as a gene that exhibits high differential expression ratios (p < 0.01). ECT2 displays good sensitivity and specificity, with an area under the curve (AUC) value of 0.821. This marker gene also has a high detection rate in patients with serum carcinoembryonic antigen (CEA) concentrations below the diagnostic threshold of 5 ng/mL. The expression of ECT2 can therefore serve as an alternative measurement that can compensate for the inadequacy of the current CEA test in the diagnosis and monitoring of colorectal cancer patients.

SUBMITTER: Chen CJ

PROVIDER: S-EPMC5412328 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Early Assessment of Colorectal Cancer by Quantifying Circulating Tumor Cells in Peripheral Blood: ECT2 in Diagnosis of Colorectal Cancer.

Chen Chih-Jung CJ Sung Wen-Wei WW Chen Hung-Chang HC Chern Yi-Jye YJ Hsu Hui-Ting HT Lin Yueh-Min YM Lin Shu-Hui SH Peck Konan K Yeh Kun-Tu KT

International journal of molecular sciences 20170331 4

Circulating tumor cells (CTCs) in peripheral blood is an indication of poor prognosis for patients with different cancer types. However, most of the available technologies for detecting CTCs show low sensitivity and specificity. Therefore, we attempted to find an alternative marker for CTCs of colorectal cancer. We have directly extracted RNA from CTCs contained in 1.5 mL peripheral blood from 90 colorectal cancer patients and 151 healthy donors, and screened these samples for candidate marker g ...[more]

PMID: 28362321

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Project description:BackgroundOne of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin).MethodsA combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets.ResultsUltradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC.ConclusionMS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Project description:BackgroundSystemic inflammation seems to be involved in the pathogenetic pathways of colorectal cancer (CRC). Analytical markers that reflect the inflammatory status, such as neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) or systemic immune-inflammation index (SII), have been proposed as tools for the prognosis of CRC. Nevertheless, their use for diagnosis has been scarcely investigated.AimsTo analyze the ability of these markers and of a new marker combining SII and hemoglobin concentration, named NP/LHb = [neutrophils x platelets]/[lymphocytes x hemoglobin], as tools for CRC diagnosis. Furthermore, we studied their association with CRC-related variables.MethodsCase-control study including 214 CRC patients and 214 controls without CRC, matched by age (±5 years) and sex. We collected demographic, CRC-related and laboratory variables to calculate NLR, PLR, SII, and NP/LHb. In the case group, the laboratory variables were collected at two different period times, 6 months (IQR 4-8) before the CRC diagnosis and at the time of the diagnosis. ROC analysis was performed to evaluate the discriminatory accuracy of each index and we calculated Se, Sp, PPV, NPV, and OR to identify the diagnostic performance of each positive marker.ResultsNP/LHb showed high Sp (92.06%) and PPV (87.50%) to diagnose patients with CRC. This index exhibited an OR of 14.52 (8.26-25.52) and the best area under the curve (AUC: 0.78) for a positive CRC diagnosis. We found significant differences in all indices according to the presence of CRC, observing the highest values in CRC patients at time of diagnosis, in comparison with the analysis performed in the previous months to diagnosis or with control patients. There were significant differences in all ratios according to TNM stages (p < 0.05). PLR, SII and NP/LHb (but not NLR) showed significant differences according to tumor location (p < 0.05). Right-sided colon cancers presented the highest values, in comparison with left-sided and rectal cancers.ConclusionsSystemic inflammatory cell ratios (especially NP/LHb) change over time with the development of CRC, so they could be useful in its early diagnosis. We suggest that they could be routinely measured in patients with suspicion of CRC, to identify those ones with a higher risk of cancer, considering the high positive predictive value they have shown in our study.

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Project description:Early diagnosis of lung cancer is critically important to reduce disease severity and improve overall survival. Newer, minimally invasive biopsy procedures often fail to provide adequate specimens for accurate tumor subtyping or staging which is necessary to inform appropriate use of molecular targeted therapies and immune checkpoint inhibitors. Thus newer approaches to diagnosis and staging in early lung cancer are needed. This exploratory pilot study obtained peripheral blood samples from 139 individuals with clinically evident pulmonary nodules (benign and malignant), as well as ten healthy persons. They were divided into three cohorts: original cohort (n = 99), control cohort (n = 10), and validation cohort (n = 40). Average RNAseq sequencing of leukocytes in these samples were conducted. Subsequently, data was integrated into artificial intelligence (AI)-based computational approach with system-wide gene expression technology to develop a rapid, effective, non-invasive immune index for early diagnosis of lung cancer. An immune-related index system, IM-Index, was defined and validated for the diagnostic application. IM-Index was applied to assess the malignancies of pulmonary nodules of 109 participants (original + control cohorts) with high accuracy (AUC: 0.822 [95% CI: 0.75-0.91, p < 0.001]), and to differentiate between phases of cancer immunoediting concept (odds ratio: 1.17 [95% CI: 1.1-1.25, p < 0.001]). The predictive ability of IM-Index was validated in a validation cohort with a AUC: 0.883 (95% CI: 0.73-1.00, p < 0.001). The difference between molecular mechanisms of adenocarcinoma and squamous carcinoma histology was also determined via the IM-Index (OR: 1.2 [95% CI 1.14-1.35, p = 0.019]). In addition, a structural metabolic behavior pattern and signaling property in host immunity were found (bonferroni correction, p = 1.32e - 16). Taken together our findings indicate that this AI-based approach may be used for "Super Early" cancer diagnosis and amend the current immunotherpay for lung cancer.

Dataset Information

Early Assessment of Colorectal Cancer by Quantifying Circulating Tumor Cells in Peripheral Blood: ECT2 in Diagnosis of Colorectal Cancer.

Publications

Early Assessment of Colorectal Cancer by Quantifying Circulating Tumor Cells in Peripheral Blood: ECT2 in Diagnosis of Colorectal Cancer.

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