Abstract
Cancer is an intricate disease with inherent intra-tumor heterogeneity at the cellular level because of genetic changes and environmental differences. Cellular heterogeneity exists even within the same tumor type. Small deviations in a genome or transcriptome can lead to significant differences in function. Conventional bulk population sequencing, which produces admixed populations of cells, can only provide an average expression signal for one cell population, ignoring differences between individual cells. Important advances in sequencing have been made in recent years. Single cell sequencing starts in a single cell, thereby increasing our capability to characterize intratumor heterogeneity. This technology has been used to analyze genetic variation, specific metabolic activity, and evolutionary processes in tumors, which may help us understand tumor occurrence and development and improve our understanding of the tumor microenvironment. In addition, it provides a theoretical basis for the development of clinical treatments, especially for personalized medicine. In this article, we briefly introduce Single cell sequencing technology, summarize the application of Single cell sequencing to study the tumor microenvironment, as well as its therapeutic application in different clinical procedures.
Highlights
Malignant tumors are a common disease, and the incidence is increasing yearly
We describe the recent application of Single cell sequencing (SCS) to tumors and we compare the differences between sensitive and inert tumor microenvironments
SCS deepens our understanding of tumors and promotes the progress of oncology
Summary
Malignant tumors are a common disease, and the incidence is increasing yearly. Cancer has become a considerable threat to human health [1]. The 10X Genomics platform has developed the 10X Genomics Single Cell Immune Profiling Solution technology, which allows simultaneous high-throughput sequencing of transcriptomic gene expression and adaptive immune receptor libraries at the individual cell level. SCS technology can detect different cell groups in tumor samples and gain information about the typical gene expression patterns of every cell type, as well as determine the interactions between cells [102]. This provides a technical basis to identify potential therapeutic targets and explore mechanisms of tumor resistance. The prognosis of the gastric type was poor clinical proof is needed, we believe that SCS has a promising future in predicting tumor prognosis. (Table 5)
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