埃及女性乳腺癌患者的循环肿瘤 DNA:检测原发病例和早期预测复发的标志物。

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
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引用次数: 0

摘要

在全球范围内,女性乳腺癌(BC)已超过肺癌,成为最常见的诊断癌症。癌症复发的早期诊断可为复发风险较高的乳腺癌患者带来巨大益处。我们旨在研究ALU 247、ALU 115、cfDNA完整性指数、CA15-3和CEA作为BC患者潜在诊断标志物和早期预测复发标志物的作用。研究对象包括50名BC患者(10名患者复发)、26名BBD患者和22名健康对照者。采用实时 q-PCR 技术测定血浆中 ALU 247 和 ALU 115 的浓度,然后计算 cfDNA 完整性指数。"ECLIA "用于测量血清中CA15-3和CEA的浓度。结果显示,与健康对照组相比,BC 患者的 ALU 247、ALU 115、CA15-3 和 CEA 水平明显更高(P=0.02、0.008、0.009)、
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Circulating tumor DNA in Egyptian women with breast Cancer: A marker for detection of primary cases and early prediction of recurrence

Worldwide, female breast cancer (BC) has surpassed lung cancer as the most commonly diagnosed cancer. Early diagnosis of cancer recurrence can provide substantial benefits for BC patients who are at high risk of relapse. We aimed to investigate the role of ALU 247, ALU 115, cfDNA integrity index, CA15-3 and CEA as potential diagnostic markers in BC patients and as markers for early prediction of recurrence. Fifty BC patients (10 patients showed recurrence), 26 BBD patients and 22 healthy controls were included. Real-time q-PCR was used to measure the concentration of ALU 247 and ALU 115 in plasma then cfDNA integrity index was calculated. “ECLIA” was used to measure the concentration of CA15-3 and CEA in serum. Our results showed significant higher levels of ALU 247, ALU 115, CA15-3 and CEA in BC patients in comparison to healthy controls (P=0.02, 0.008, <0.001 and < 0.001 respectively). Also, cfDNA integrity index was higher in BC patients in comparison to healthy controls but statistically insignificance (p = 0.46). In recurrent BC patients; ALU 247, ALU 115, cfDNA integrity index, CA15-3 and CEA levels were higher compared to non-recurrent BC patients but with no statistic significant (p = 0.46, 0.59, 0.09, 0.85 and 0.84 respectively). This may result from the short period of follow up (1–2 years) and the relatively small sample size due to exclusion of patients with chronic diseases or inflammation as well as those who received therapy or post-surgery. By using the ROC curve, the sensitivity of ALU 247, ALU 115, CA15-3 and CEA for discriminating BC patients from BBD patients and healthy controls was 79 %, 79.2 %, 76.0 % and 88.0 % respectively. This study suggested that ALU 247, ALU 115, CA15-3 and CEA could be promising non-invasive markers of BC for diagnosis and early prediction of recurrence after validation in large-scale future studies.

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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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