Page 19 - EJMO-9-2

Eurasian Journal of
Medicine and Oncology Single-cell sequencing for lung cancer

poor prognosis. Furthermore, CRD was associated with sequencing. For example, isolating a sufficient number
resistance to anticancer treatments, such as chemotherapy of intact single cells from lung cancer tissue is a complex
and tyrosine kinase inhibitors. The proposed mechanism process, and mechanical or chemical manipulation may
suggests that CRD facilitates the change of malignant cells damage cells, reducing the precision of analyses. In
into persistent, drug-resistant populations. addition, the high cost and complicated experimental
Despite its advantages, single-cell sequencing faces procedures limit its application in broader clinical
several challenges that must be addressed for broader and settings. The bioinformatics analysis of single-cell
more reliable applications. Experimental limitations, such sequencing technology is also a great challenge.
as amplification bias, differences in library sizes, and DNA Processing and interpreting huge amounts of data require
damage during processing, can lead to inaccuracies in data efficient and accurate algorithms, yet existing analytical
interpretation. In addition, the lack of standardization techniques are not yet fully optimized to meet research
across various techniques complicates the comparison needs. The development of more advanced algorithms to
and integration of results. The small starting material in enhance the capability of single-cell analysis, especially
single-cell sequencing also contributes to low capture in digitizing and visualizing the TME, is crucial for
efficiency and sequencing variability, further adding to the making findings more relevant to real-world scientific
technical noise. Combined with high biological variation, and clinical settings. Many of the current single-cell
these factors complicate data analysis. The large-scale, sequencing results provide only theoretical insights,
noisy, and sparse nature of single-cell data poses additional necessitating further validation in larger patient
challenges for computational analysis, often requiring populations, the development of targeted drugs, and
methods like imputation and clustering to handle missing the advancement of clinical translation. The refinement
values. Furthermore, low-quality data from broken, dead, of these aspects will require extensive research and
or aggregated cells can interfere with downstream analysis, practice. As single-cell sequencing is still an emerging
leading to misinterpretations. Many conventional bulk technology, its clinical application in identifying lung
sequencing tools are not directly applicable, necessitating cancer biomarkers remains limited, with only a few
specialized methods for tasks such as cell clustering and biomarkers currently in the early stages of development.
87
gene regulatory network inference. The high cost of single- However, with continuous advancements in single-cell
cell sequencing remains a limitation, but advancements analysis and clinical validation, the potential of this
in sequencing technologies, library preparation, and technology in precision oncology remains promising,
computational tools are gradually overcoming these offering hope for more effective and personalized lung
challenges. These innovations are making single-cell cancer treatments in the future.
sequencing more affordable and accessible, paving the way Nevertheless, single-cell sequencing remains a
for larger studies and broader clinical applications. hotspot for future lung cancer research. This technology

5. Conclusion has revolutionized lung cancer treatment by enabling
the extraction of crucial insights from the TME. The
Single-cell sequencing technology provides a powerful advantages of single-cell sequencing are particularly
tool for lung cancer research with its high-resolution and evident in the context of immunotherapy, which is
multidimensional analysis capabilities. It has demonstrated becoming the mainstream of cancer treatment. With the
great potential in revealing lung cancer heterogeneity, continuous advancement of sequencing technology and
resolving the TME, early diagnosis, invasion, and metastasis analysis methods, the application of single-cell sequencing
mechanisms, as well as exploring therapeutic and drug will continue to expand. In the future, the integration of
resistance. These advancements have greatly enhanced the multi-omics data and single-cell technologies will further
understanding of lung cancer. In recent years, many studies promote the development of lung cancer research and
have demonstrated the value of single-cell sequencing in treatment. Single-cell sequencing is expected to become
lung cancer research. By integrating single-cell sequencing an indispensable tool, providing a stronger scientific
technologies, such as combining scRNA-seq with genomics, foundation for improving the prognosis and quality of
epigenomics, proteomics, metabolomics, and spatial life of lung cancer patients while offering comprehensive
transcriptomics, researchers can overcome the limitations and reliable data to support precision medicine and
of traditional sequencing methods while addressing certain individualized treatment.
shortcomings of single-cell sequencing itself.
Acknowledgments
Despite its significant advantages, many challenges
hinder the widespread practical application of single-cell None.

Volume 9 Issue 2 (2025) 11 doi: 10.36922/ejmo.6883