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FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.
Lu, W, Fu, D, Kong, X, Huang, Z, Hwang, M, Zhu, Y, Chen, L, Jiang, K, Li, X, Wu, Y, et al
Cancer medicine. 2020;(4):1419-1429
Abstract
Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5-FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta-analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy.
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Non-genetic biomarkers and colorectal cancer risk: Umbrella review and evidence triangulation.
Zhang, X, Gill, D, He, Y, Yang, T, Li, X, Monori, G, Campbell, H, Dunlop, M, Tsilidis, KK, Timofeeva, M, et al
Cancer medicine. 2020;(13):4823-4835
Abstract
Several associations between non-genetic biomarkers and colorectal cancer (CRC) risk have been detected, but the strength of evidence and the direction of associations are not confirmed. We aimed to evaluate the evidence of these associations and integrate results from different approaches to assess causal inference. We searched Medline and Embase for meta-analyses of observational studies, meta-analyses of randomized clinical trials (RCTs), and Mendelian randomization (MR) studies measuring the associations between non-genetic biomarkers and CRC risk and meta-analyses of RCTs on supplementary micronutrients. We repeated the meta-analyses using random-effects models and categorized the evidence based on predefined criteria. We described each MR study and evaluated their credibility. Seventy-two meta-analyses of observational studies and 18 MR studies on non-genetic biomarkers and six meta-analyses of RCTs on micronutrient intake and CRC risk considering 65, 42, and five unique associations, respectively, were identified. No meta-analyses of RCTs on blood level biomarkers have been found. None of the associations were classified as convincing or highly suggestive, three were classified as suggestive, and 26 were classified as weak. For three biomarkers explored in MR studies, there was evidence of causality and seven were classified as likely noncausal. For the first time, results from both observational and MR studies were integrated by triangulating the evidence for a wide variety of non-genetic biomarkers and CRC risk. At blood level, lower vitamin D, higher homeostatic model assessment-insulin resistance, and human papillomavirus infection were associated with higher CRC risk while increased linoleic acid and oleic acid and decreased arachidonic acid were likely causally associated with lower CRC risk. No association was found convincing in both study types.
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S100A1 promotes cell proliferation and migration and is associated with lymph node metastasis in ovarian cancer.
Tian, T, Li, X, Hua, Z, Ma, J, Liu, Z, Chen, H, Cui, Z
Discovery medicine. 2017;(127):235-245
Abstract
S100A1 is a calcium-binding protein belonging to the family of S100 proteins, and is highly expressed in ovarian cancer. However, its role in ovarian cancer has not yet been fully elucidated. In this study, we examined S100A1 expression in ovarian cancer tissues and normal tissue controls and analyzed the correlation between S100A1 expression and clinicopathological parameters. We found that S100A1 expression was significantly upregulated in ovarian cancer tissues compared with fallopian and normal ovarian epithelium tissues and was significantly associated with lymph node metastasis and International Federation of Gynecology and Obstetrics (FIGO) stages and tumor grades. We then investigated the biological functions of S100A1 in ovarian cancer by cell proliferation, fluorescence-activated cell sorting (FACS), and migration and invasion assays. The results indicated that S100A1 enhanced the ovarian cancer cell proliferation and migration. Together, our findings demonstrated that S100A1 plays an important role in the malignancy of ovarian cancer, and serves as a useful marker for the detection of ovarian malignancy.
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Folate Receptor-Positive Circulating Tumor Cell Detected by LT-PCR-Based Method as a Diagnostic Biomarker for Non-Small-Cell Lung Cancer.
Chen, X, Zhou, F, Li, X, Yang, G, Zhang, L, Ren, S, Zhao, C, Deng, Q, Li, W, Gao, G, et al
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer. 2015;(8):1163-71
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Abstract
INTRODUCTION To investigate the diagnostic performance of folate receptor-positive circulating tumor cells in distinguishing non-small-cell lung cancer (NSCLC) from lung benign disease by using a novel ligand-targeted polymerase chain reaction (PCR) detection technique. METHODS Circulating tumor cells were enriched from 3-ml peripheral blood by immunomagnetic depletion of leukocytes and then labeled with a conjugate of a tumor-specific ligand folic acid and a synthesized oligonucleotide. After washing off free conjugates, the stripped bound conjugates were analyzed by quantitative PCR. RESULTS Seven hundred fifty-six participants (473 patients with NSCLC, 227 patients with lung benign disease, and 56 healthy donors) were randomly assigned to a training set and a test set. The circulating tumor cell (CTC) levels in patients with NSCLC were significant higher than those with lung benign disease (p < 0.001) and healthy donors (p < 0.001). Compared with carcinoembryonic antigen, neuron-specific enolase, and Cyfra21-1, CTCs displayed the highest area under the receiver operating characteristic curve (training set, 0.815; validation set, 0.813) in the diagnosis of NSCLC, with a markedly sensitivity (training set, 72.46%; validation set, 76.37%) and specificity (training set, 88.65%; validation set, 82.39%). The model combining CTCs with carcinoembryonic antigen, neuron-specific enolase, and Cyfra21-1 was more effective for the diagnosis of NSCLC than tumor makers alone (sensitivity and specificity in the training set, 84.21% and 83.91%; validation set, 88.78% and 87.36%, respectively). In addition, the CTC levels were higher in patients with stage III/IV NSCLC compared with those with stage I/II disease. CONCLUSION Ligand-targeted PCR technique was feasible and reliable for detecting folate receptor-positive CTCs in patients with NSCLC, and CTC levels could be used as a useful biomarker for the diagnosis of NSCLC.