INTERNATIONAL CONGRESS OF
CancerGenetics
Single-Cell Sequencing in Cancer Diagnosis: Investigation of Tumor Heterogeneity and Its Role in Personalized Diagnostics
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Ashkan Hajjafari,1 Soroush Partovi Moghaddam,2 Soheil Sadr,3 Mobina Pato,4 Abbas Rahdar,5,* Sadanand Pandey,6
1. Department of Pathobiology, Faculty of Veterinary Medicine Science, Science and Research Branch, Islamic Azad University, Tehran, Iran
2. Department of Pathobiology, Faculty of Veterinary Medicine Science, Science and Research Branch, Islamic Azad University, Tehran, Iran
3. Department of Pathobiology, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran
4. Department of Pathobiology, Faculty of Veterinary Medicine Science, Science and Research Branch, Islamic Azad University, Tehran, Iran
5. Department of Physics, University of Zabol, Zabol, Iran
6. Department of Chemistry, College of Natural Science, Yeungnam University, 280 Daehak‐Ro, Gyeongsan 38541, Korea School of Bioengineering and Food Technology, Faculty of Applied Sciences and Biotechnology, Shoolini University, Solan 173229, Himachal Pradesh, India
- Introduction: Single-cell sequencing and other single-cell technologies are powerful tools for identifying heterogeneity within tumors. These methods allow the detailed study of each cancer cell's genetic and transcriptional characteristics separately, thus contributing to more accurate diagnosis and personalized treatment. This research aims to investigate the role of single-cell sequencing in discovering the differences between tumor cells and the impact of this technology in the development of new and personalized cancer diagnosis methods. We specifically address the benefits of these methods in better understanding molecular pathways and responses to therapies.
- Methods: Data related to scientific articles between 2018 and 2023 from PubMed, Scopus, and Web of Science databases using keywords such as "single-cell sequencing," "cancer diagnosis," "tumor heterogeneity," "single-cell RNA," and " "Single-cell technologies" were extracted. Articles that included experimental data and analytical reviews were reviewed in this study.
- Results: The analysis of the data obtained from the articles shows that single-cell RNA sequencing (scRNA-seq) plays a vital role in diagnosing tumor heterogeneity. For example, in a study of lung cancer, single-cell sequencing revealed that the tumor was composed of different cells with different genetic and transcriptional patterns. This heterogeneity can be the reason for the resistance of some cells to conventional treatments. In another study that investigated breast cancer, single-cell sequencing succeeded in identifying different cell subtypes, each of which indicated different pathways of tumor progression and response to treatment. This technology has also been used in glioblastoma. It was found that the presence of cancer stem cells and differentiated cells within the tumor can be significant predictors of the prognosis of patients. One of the key examples in this field is the ability of this method to identify specific biomarkers of each patient and tumor, which allows doctors to prescribe personalized treatments for each patient. This technology has led to a more accurate diagnosis and has been particularly important in determining the prognosis and choosing a more effective treatment. These results suggest that single-cell sequencing could pave the way for early diagnosis and personalized cancer treatments.
- Conclusion: Single-cell sequencing is a powerful tool that can contribute to a deeper understanding of the heterogeneity within tumors, and this information is valuable for developing new diagnostic and therapeutic methods. This technology enables personalized diagnoses and more effective treatments by providing accurate biomarkers and identifying cell subtypes. It is expected that with the advancement of this technology, significant improvements will be achieved in the clinical management of cancers.
- Keywords: Single-cell sequencing, Cancer diagnosis, Tumor heterogeneity, Single-cell RNA
