Posted in | News | Biosensors

Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells

In a recent article published in the journal Biosensors and Bioelectronics, researchers introduced a novel platform that combines single-cell capture, tumor-targeted silver (Ag) nanoprobes, and Raman spectroscopy to enhance the sensitivity and specificity of pancreatic cancer diagnosis. By leveraging surface-enhanced Raman spectroscopy (SERS), the researchers aim to provide a more accurate molecular analysis of individual tumor cells, which could lead to better understanding and management of the disease.

Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells
Study: Microfluidic platform for single-cell detection of pancreatic cancer using SERS. Image Credit: Nemes Laszlo/Shutterstock.com

Background

Pancreatic cancer is one of the most deadly forms of cancer, primarily due to its late-stage diagnosis and the challenges in effective treatment. Early detection is crucial for improving patient outcomes, highlighting the need for innovative diagnostic tools. The complexity of pancreatic cancer, characterized by its heterogeneous nature, makes traditional diagnostic methods, which often depend on bulk tissue analysis, less effective.

Recent advancements in microfluidic technology and single-cell analysis offer promising new approaches for cancer diagnostics. Microfluidic devices enable precise manipulation and analysis of individual cells, helping to address the issue of cellular heterogeneity. Raman spectroscopy, particularly when enhanced by surface-enhanced Raman spectroscopy (SERS), provides a non-invasive way to capture molecular fingerprints of cells. This technique reveals critical information about the biochemical composition of cells.

By integrating these technologies, researchers aim to develop a platform capable of detecting early-stage pancreatic cancer by identifying subtle changes in tumor cells. This approach has the potential to significantly improve early diagnosis and, consequently, patient outcomes.

The Current Study

The microfluidic device was created using polydimethylsiloxane (PDMS). To fabricate it, a silicon wafer was first coated with photoresist and exposed to UV light through a photomask, which was then developed to form a negative mold. PDMS was poured over this mold and cured at high temperatures. After curing, the PDMS was bonded to a glass slide through oxygen plasma treatment, allowing for optical access to the channels.

Pancreatic cancer cell lines were cultured and harvested using trypsinization, followed by centrifugation to create a single-cell suspension. The cell concentration was adjusted to ensure optimal flow through the microfluidic device, which was connected to a syringe pump to maintain a constant flow rate. The channel design was optimized to enhance cell capture while minimizing shear stress.

Silver (Ag) nanoprobes were synthesized via a chemical reduction method using silver nitrate. These nanoparticles were characterized for uniformity using transmission electron microscopy (TEM). To improve biocompatibility, the Ag nanoparticles were PEGylated and then functionalized with antibodies targeting pancreatic cancer biomarkers (mesothelin and IMP3) using EDC/NHS chemistry.

A 785 nm laser was employed to excite the Ag nanoprobes and the cells within the microfluidic channels. The laser light was directed through a tapered multimode optical fiber to focus on the target area. The Raman scattered light was then collected and sent to a spectrometer equipped with a CCD detector, which was optimized for capturing high-quality spectra.

The Raman spectra were analyzed to identify characteristic peaks corresponding to various molecular components. To validate the findings and gain further insights into pancreatic cancer progression, high-throughput RNA sequencing was performed on the same cell lines. This enabled the researchers to correlate the Raman spectral features with transcriptomic data.

Results and Discussion

The results demonstrated that the integrated platform successfully captured single pancreatic cancer cells and provided high-quality Raman spectra. The characteristic peaks associated with collagen proteins and phospholipids were significantly more pronounced in the early tumor (ET) stage compared to the metastatic tumor (MT) stage, indicating a correlation between the Raman spectral features and the biological characteristics of the tumor. This finding suggests that the platform can effectively differentiate between various stages of pancreatic cancer based on molecular signatures.

The study also highlighted the importance of transcriptomic analysis in conjunction with Raman spectroscopy. By correlating the spectral data with transcriptomic profiles obtained from high-throughput gene screening, the researchers were able to link specific molecular components to cellular behavior. This comprehensive approach not only enhances the understanding of the molecular composition of pancreatic cancer cells but also provides insights into their biological functions.

Conclusion

In conclusion, this study represents a significant advancement in pancreatic cancer diagnostics through the development of a highly sensitive microfluidic sensor. By integrating optical fiber technology with real-time single-cell Raman spectroscopy, the platform offers a novel approach to detecting pancreatic cancer at earlier stages by analyzing the molecular signatures of individual tumor cells. The use of SERS-active silver nanoprobes further enhances the Raman signal, enabling rapid and precise analysis while reducing background noise.

While further clinical validation is needed, the results highlight the potential of combining advanced technologies to improve diagnostic accuracy and patient outcomes in pancreatic cancer. This research lays the groundwork for future studies focused on refining this technology and establishing its clinical utility, with the goal of advancing more effective and personalized treatment strategies for patients facing this challenging disease.

Journal Reference

Ni R., Ge K., et al. (2024). Microfluidic platform for single-cell detection of pancreatic cancer using SERS. Biosensors and Bioelectronics 264, 116616. DOI: 10.1016/j.bios.2024.116616, https://www.sciencedirect.com/science/article/pii/S0956566324006225

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Jain, Noopur. (2024, August 15). Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells. AZoSensors. Retrieved on October 06, 2024 from https://www.azosensors.com/news.aspx?newsID=15953.

  • MLA

    Jain, Noopur. "Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells". AZoSensors. 06 October 2024. <https://www.azosensors.com/news.aspx?newsID=15953>.

  • Chicago

    Jain, Noopur. "Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells". AZoSensors. https://www.azosensors.com/news.aspx?newsID=15953. (accessed October 06, 2024).

  • Harvard

    Jain, Noopur. 2024. Sensitive Microfluidic Sensors Detect Pancreatic Cancer Cells. AZoSensors, viewed 06 October 2024, https://www.azosensors.com/news.aspx?newsID=15953.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.