May 27, 2024

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Cell: Comprehensive analysis of intratumoral heterogeneity

Cell: Comprehensive analysis of intratumoral heterogeneity


Cell: Comprehensive analysis of intratumoral heterogeneity.  38 cancer types, 2658 cancer samples paving the way for the fight against cancers.

In recent years, with economic development and scientific progress, medical technology has been highly developed, and the average life expectancy of humans has also been greatly improved. However, due to the increase in life expectancy and environmental factors, the incidence of human cancer has also increased.

According to the World Health Organization’s International Agency for Research on Cancer (IARC) released the latest global cancer burden data for 2020, there were 19.29 million new cancer cases worldwide in 2020 and 9.96 million cancer deaths worldwide in 2020. Cancer has become the number one threat to human health. .

Humans have not been able to completely overcome cancer. Tumor heterogeneity is one of the major obstacles. Tumor tissue contains a variety of different cells, which have different phenotypic characteristics, and therefore have different sensitivities to treatment. To completely cure cancer, the first thing is to fully understand the tumor heterogeneity genes in the human cancer genome and develop new cancer treatment methods based on this.

On April 7, 2021, a joint team from the United Kingdom, the United States and Canada headed by the Francis Crick Institute published a research paper on Cell titled: Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes.

This study described the intratumoral heterogeneity (ITH) of the whole genome sequence of 2,658 cancer samples spanning 38 cancer types. The results emphasized the importance of ITH and its driving factors in tumorigenesis and development. It also provides a pan-cancer resource that comprehensively annotates intra-tumor heterogeneity from whole-genome sequencing data.

Cell: Comprehensive analysis of intratumoral heterogeneity

Cancer cells will continue to accumulate somatic mutations during their division and proliferation. Some of these mutations give cancer cells a stronger adaptive advantage and may lead to genetically different tumor cell populations. Specific tumor cell subgroups carry specific This is called intratumoral heterogeneity (ITH).

It is worth noting that intratumoral heterogeneity is a mechanism that leads to the emergence of drug resistance in cancer treatments, and it is also an important clinical challenge. However, in different cancer types, humans still have little knowledge of the scope, origin, and driving factors of intratumoral heterogeneity.

Although previous studies have shown that intratumoral heterogeneity can be characterized by a large amount of parallel sequencing data, in different cancer types, intratumoral heterogeneity still lacks characteristics, and there are great differences in the selection pressure of subclonal populations. Certainty.

In this study, the research team developed a powerful research strategy-calling copy number and cluster mutations to assess intratumoral heterogeneity and its origin, driving factors and role in tumor development. Based on this strategy, the researchers sequenced the whole genome of 2,658 cancer samples spanning 38 cancer types.

Cell: Comprehensive analysis of intratumoral heterogeneity
Characterization of intratumoral heterogeneity (ITH) based on whole-genome sequencing

Compared with exomes, whole-genome sequencing provides more orders of magnitude point mutation information, higher resolution for detecting copy number changes (CNAs), and the ability to call structural variants (SVs). This increases the breadth and depth of research and analysis, and reveals the prevalence of cancer types.

Cell: Comprehensive analysis of intratumoral heterogeneity
Use mutation staging to further characterize intratumoral heterogeneity (ITH)

The researchers found that almost all cancer samples (95.1%) contained obvious evidence of subclonal expansion, and there were frequent branching relationships between subclones. Not only that, they also observed positive selection of subcloning driver gene mutations in most cancer types, and identified cancer type-specific subcloning patterns of driver gene mutations, fusions, structural variations, and copy number changes, as well as subclones. Dynamic changes between the mutation process.

This means that tumor subclonal expansion can be used as evidence of the mutation process that changes in time and space, thus showing that the abundant tumor subclonal architecture has linear and branched evolution.

Cell: Comprehensive analysis of intratumoral heterogeneity
Driver mutation and selection of subcloned genes

In addition, the research team also found that only 11% of tumor subclones carry known single nucleotide variants (SNV) or indel (insertions or deletions) driver mutations. They speculate that this is because the late driver gene mutation pool is too large. , So far it has not been possible to conduct sufficiently extensive sampling.

Finally, in order to assess the potential impact of intratumoral heterogeneity on clinical treatment, the researchers evaluated the clonality of activity-driven mutations (STAR ​​method), and concluded that targeting subclonal mutations may lead to treatment failure. They found that 60.1% of tumors had at least one clinically active site, of which 9.7% contained at least one subclonal activity driver, and 4.7% showed only subclonal active sites.

This shows that it is important to consider intratumoral heterogeneity and its driving factors in clinical research.

All in all, this study shows that intratumoral heterogeneity (ITH) is widespread in cancer and manifests as a specific pattern of cancer types. The development of tumor subclonal branching systems is very common, and the subclonal mutation process is dynamic. . This study confirmed and emphasized the importance of intratumoral heterogeneity (ITH) and its driving factors in tumorigenesis and development, and provided detailed insights into the dynamics of tumor evolution.





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