Nature Blockbuster: Refresh the perception that p53 mutations drive cancer! MSKCC scientists have found that p53 deletions induce predictable, orderly, and definite scientific discoveries in the evolution of the cancer genome

*For medical professionals only

In 1979, scientists discovered the p53 protein, and since then the p53 protein has been active in the field of biomedicine, especially in the field of oncology research
.

The human p53 protein is encoded by the tumor suppressor gene TP53, and many studies have found that inactivated mutations in TP53 are closely related to the aggressiveness and refractory nature of cancer [1,2
].

Numerous studies have shown that p53 inactivation is a predisposing cause of genomic confusion, and that TP53 mutations usually precede other genomic rearrangement events[3].

However, the relationship between TP53 mutations and the chronological and biological transitions of cancer progression is unclear
.
Exploring the relationship between TP53 mutations, genomic instability and cancer progression can be used to guide and implement cancer treatment interventions as early as possible
.

Recently, Scott W.
Lowe's team at the Memorial Sloan Kettering Cancer Research Center (MSKCC) published a study on the relationship between TP53 mutations and cancer development in the top international journal Nature
.

The researchers found that when cells lose p53, while causing genetic confusion, it induces a predictable, orderly, and definite evolution
of the cancer genome.
This breakthrough finding undoubtedly provides new ideas
for cancer treatment.

Screenshot of the first page of the paper

Pancreatic ductal carcinoma (PDAC) is a fatal disease with frequent genetic mutations, and TP53 mutations are a prominent feature
.
TP53 deletion is a key inflection point in PDAC progression, such as TP53 heterozygous deletion (LOH) is closely linked to cancer progression, invasion, and heterogeneity [5,6
].

However, due to the limited tissue availability of patients before and after tumor development and the difficulty of sampling and analysis of human tumor samples in the early stages of tumorigenesis [7,8], the dynamic relationship between the TP53 mutation lineage and cancer development has been difficult to demystify
.
To figure out the above questions, Lowe's team conducted the study
.

The Lowe team selected a single allele driven PDAC mouse model (KPC mice) driven by Kras G12D allele activation and Trp53 (the encoding gene for the mouse p53 protein) to establish a lineage tracking model of double-fluorescence PDAC and trace the cells in mice in order to directly observe the dynamic process
from p53 inactivation to the gradual development of cells into malignant tumors.

The model observes and records specific genetic events
through a set of fluorescent markers.
Red fluorescence represents the presence of mutations in the KRAS gene that promote the development of cancer; Green fluorescence represents green fluorescently labeled shRNA that reflects the deletion of p53
.

In the case of a mutation in the KRAS gene, p53 is not missing, the cells present double fluorescence positive, and the cells at this time are recorded as double positive cells (DP cells); At p53 LOH, cells will appear single fluorescence positive, which is recorded as single positive cells (SP cells
).

This model allows researchers to visually identify specific cell populations
in mice where p53 is missing but has not developed into cancer cells.

Trace the model schematic

The researchers analyzed the pancreas of mice during PDAC progression by means of immunohistochemistry and immunofluorescence, and the results showed that SP cells had malignant features, while DP cells only showed features
of precancerous tissue.

However, SP cells in precancerous lesions exhibit a low rate of value-added, with poor colony formation and ability to initiate malignancies, suggesting that p53 deficiency alone is not sufficient to promote cancer development
.

In mouse PDAC models, lineage tracking of early cancer cells after sporadic p53 inactivation

To determine the effect of p53 inactivation on genome evolution during PDAC progression, the researchers performed whole-genome sequencing to compare changes in copy number in SP and DP cell populations
.

The results showed that the DP cell genome was always present in diploid form with little change
in copy number.
However, SP cell genomes are prone to highly rearranged genomes and appear
in polyploid form.
In addition, isolated SP cells exhibit repeated losses on chromosomes 4, 7, 9, 11 and 13, as well as gains
on chromosomes 3, 5, 6, 8, and 15.

After p53 inactivation, the cycle and copy number changes targeting PDAC drivers shaped the evolution of the malignant genome

Next, the researchers found through bulk and single-cell sequencing that DP cells are mostly homoploid, occasionally containing a gain
in chromosome 6.
However, PDAC-SP lesions always have frequent copy number changes and the appearance of polyploids
.

This revealed that the genome is constantly evolving during the transition from cells to malignancies, and p53 LOH reduces cellular genomic stability and promotes changes in
copy number.

Different and ordered stages of genomic evolution are accompanied by a transition from benign to malignant tumors

So, what is the evolutionary pattern of the genome during the development of PDAC?

Through further study of the number of single cells, Lowe's team found that precancerous SP cells showed a distinct breakpoint pattern on chromosome 11, suggesting that tumors had an independent competitive p53 LOH lineage
during the transition from benign to malignant.

Based on the above results, it is not difficult to find that Lowe's team has gradually uncovered the evolutionary pattern of genomic certainty of PDAC: First, the cells appear p53 LOH; Subsequently, gene deletions accumulate and polyploids form; Finally, chromosome gain amplification yields more copy number changes
.

The principle of certainty governs selective rearrangement of the genome after p53 LOH

What are the results in the human PDAC model?

Finally, Lowe's team analyzed human PDAC samples using whole-genome sequencing, and by analyzing targeted capture sequencing and single-cell sequencing numbers, they found that human PDACs also exhibited diploid and polyploid gains and amplification caused by early TP53 mutations
.
These results suggest that human PDAC evolution is similar
to the evolutionary patterns observed in mouse models.

Whole genome sequencing, targeted capture, and single-cell sequencing confirm the evolutionary principles of human disease

In summary, the study revealed the relationship between TP53 mutations and cancer development, and researchers explored predictable genomic evolution patterns caused by p53 inactivation, subverting people's understanding of
the relationship between p53 mutations and cancer.

P53 deletion does not necessarily lead to cancer, only on the basis of the deletion of p53, the cell then accumulates this genetic change in an orderly manner, and eventually develops into cancer as the genome is unstable and gradually out of
control, and this pattern is predictable, orderly, and deterministic.

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This research provides new ideas
for cancer treatment.
For example, intervention before the TP53 mutant genome is doubled can achieve early tumor suppression, solve the refractory problem of malignant tumor in the later stage, and improve the treatment effect
of cancer.

References:

[1] ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium.
Pan-cancer analysis of whole genomes.
Nature.
2020; 578(7793):82-93.
doi:10.
1038/s41586-020-1969-6

[2] Kastenhuber ER, Lowe SW.
Putting p53 in Context.
Cell.
2017; 170(6):1062-1078.
doi:10.
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[3] Gerstung M, Jolly C, Leshchiner I, et al.
The evolutionary history of 2,658 cancers.
Nature.
2020; 578(7793):122-128.
doi:10.
1038/s41586-019-1907-7

[4] Baslan T, Morris JP 4th, Zhao Z, et al.
Ordered and deterministic cancer genome evolution after p53 loss.
Nature.
2022; 608(7924):795-802.
doi:10.
1038/s41586-022-05082-5

[5] Rozenblum E, Schutte M, Goggins M, et al.
Tumor-suppressive pathways in pancreatic carcinoma.
Cancer Res.
1997; 57(9):1731-1734.

[6] Notta F, Chan-Seng-Yue M, Lemire M, et al.
A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns [published correction appears in Nature.
2017 Feb 2; 542(7639):124].
Nature.
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doi:10.
1038/nature19823

[7] Litchfield K, Stanislaw S, Spain L, et al.
Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.
Cell Rep.
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doi:10.
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107550

[8] Baslan T, Hicks J.
Unravelling biology and shifting paradigms in cancer with single-cell sequencing.
Nat Rev Cancer.
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doi:10.
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