Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and its Application in Early Diagnosis of Colorectal Cancer

Li, Peilong; Chen, Jiaci; Chen, Yuqing; Song, Shangling; Huang, Xiaowen; Yang, Yang; Li, Yanru; Yao, Takeshi; Xie, Yuan; Li, Juan; Li, Shunxiang; Wang, Jiayi; Qian, Kun; Wang, Chuanxin; Li, Du

doi:10.1002/smll.202207381

Cited by 20 publications

(17 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the findings in Figure 3C, hsa_circ_0124554 may be more useful than CA19-9 in the diagnosis of patients with suspected CRC. Studies have reported that the AUC of CEA in the diagnosis of CRC ranged from 0.709 to 0.739, [25][26][27] but our data showed that the AUC of CEA was 0.831, which may be related to the insufficient sample size in our study. In addition to evaluating the performance of each single marker in detection, we also combined 2 or 3 tumor markers to find the optimal diagnostic combination.…”

Section: Discussioncontrasting

confidence: 65%

Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study

Li,

et al. 2023

Medicine

View full text Add to dashboard Cite

Circular RNAs (circRNAs) play important roles in the occurrence and development of cancer, and have been shown with diagnostic values in various cancers. The latest research showed that hsa_circ_0124554 is closely related to liver metastasis and vascular invasion in colorectal cancer (CRC). This study aimed to investigate whether hsa_circ_0124554 can be used as a diagnostic marker for CRC. In this study, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was used to detect hsa_circ_0124554 expression levels in 40 pairs of CRC tissues and adjacent non-tumor intestinal tissues derived from CRC patients and 32 paired plasma specimens. The relationship between the expression of hsa_circ_0124554 and the clinicopathological features of CRC patients was analyzed by t-test and chi-square test. Receiver operating characteristic (ROC) curve analysis was established to explore the diagnostic value of hsa_circ_0124554 in CRC. The results showed that hsa_circ_0124554 was substantially expressed in CRC tissues (P < .001) and that there were variations in pathological differentiation, perineural invasion and invasion. The expression of hsa_circ_0124554 in CRC patients was considerably higher than healthy controls (P < .001). The area under the receiver operating characteristic (ROC) curve (AUC) of tissue and plasma hsa_circ_0124554 was 0.703 and 0.742. The AUC of the expression combined hsa_circ_0124554, carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) had the best diagnostic performance (AUC = 0.899) in the CRC groups, and the sensitivity and specificity were 0.844 and 0.844. The expression of hsa_circ_0124554 was up-regulated in the tissues and plasma in CRC patients, which may be a new biomarker for the diagnosis of CRC. The combination hsa_circ_0124554, CEA and CA199 has the best diagnostic efficacy in CRC.

show abstract

Section: Discussioncontrasting

confidence: 65%

Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study

Li,

et al. 2023

Medicine

View full text Add to dashboard Cite

show abstract

“…The results showed that the approach had a high accuracy with an area under curve (AUC) of 0.81 in diagnosing pancreatic cancer, indicating its potential for use in clinical settings as a non-invasive diagnostic tool. As another example, Li et al [ 79 ] developed a new method for detecting colorectal cancer using exosomes as a specific protein biomarker. They created a microfluidic chip with a 3D porous sponge structure and functionalized it with CD9 antibodies to capture exosomes flowing through the microfluidic channel.…”

Section: Lab-on-a-chip In Cancer Detectionmentioning

confidence: 99%

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Kokabi,

Tahir,

Singh

et al. 2023

Biosensors

View full text Add to dashboard Cite

Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods for cancer detection often have limitations in identifying the disease in its early stages, and they can be expensive and time-consuming. Since cancer typically lacks symptoms and is often only detected at advanced stages, it is crucial to use affordable technologies that can provide quick results at the point of care for early diagnosis. Biosensors that target specific biomarkers associated with different types of cancer offer an alternative diagnostic approach at the point of care. Recent advancements in manufacturing and design technologies have enabled the miniaturization and cost reduction of point-of-care devices, making them practical for diagnosing various cancer diseases. Furthermore, machine learning (ML) algorithms have been employed to analyze sensor data and extract valuable information through the use of statistical techniques. In this review paper, we provide details on how various machine learning algorithms contribute to the ongoing development of advanced data processing techniques for biosensors, which are continually emerging. We also provide information on the various technologies used in point-of-care cancer diagnostic biosensors, along with a comparison of the performance of different ML algorithms and sensing modalities in terms of classification accuracy.

show abstract

“…Extracellular vesicles derived from tumor cells, which can be stably detected in various body fluids and reflect the tumor burden status in real time, are considered a promising tool for liquid biopsy. Li et al functionalized a 3D porous PDMS sponge structure with CD9 antibody to capture extracellular vesicles imported into a microfluidic chip [ 234 ]. This work is based on a 3D porous microfluidic chip platform and is used as a new non-invasive diagnostic tool for the early detection of colorectal cancer.…”

Section: Microfluidic Devices Based On Porous Media For Biomedical An...mentioning

confidence: 99%

Porous Structural Microfluidic Device for Biomedical Diagnosis: A Review

et al. 2023

View full text Add to dashboard Cite

Microfluidics has recently received more and more attention in applications such as biomedical, chemical and medicine. With the development of microelectronics technology as well as material science in recent years, microfluidic devices have made great progress. Porous structures as a discontinuous medium in which the special flow phenomena of fluids lead to their potential and special applications in microfluidics offer a unique way to develop completely new microfluidic chips. In this article, we firstly introduce the fabrication methods for porous structures of different materials. Then, the physical effects of microfluid flow in porous media and their related physical models are discussed. Finally, the state-of-the-art porous microfluidic chips and their applications in biomedicine are summarized, and we present the current problems and future directions in this field.

show abstract

Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and its Application in Early Diagnosis of Colorectal Cancer

Cited by 20 publications

References 65 publications

Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study

Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Porous Structural Microfluidic Device for Biomedical Diagnosis: A Review

Contact Info

Product

Resources

About