Back

Pre-existing levels of pro-survival proteins and induction of BCL-XL dictate cell fate after p53 activation

Huang, A. S.; Lieschke, E.; Baldoni, P. L.; Thomas, A. F.; Marchingo, J. M.; Whelan, L.; Khuu, G.; Marca, E. L.; Milevskiy, M.; Ross, A. M.; Johanson, T.; Potts, M.; Gibson, L.; Vaibhav, V.; Dagley, L.; Balihodcik, A.; Dengler, M.; Liu, Z.; Li, K.; Smyth, G. K.; Kelly, G.; Strasser, A.

2026-07-09 cancer biology
10.64898/2026.07.01.735749 bioRxiv
Show abstract

TP53 (also called TRP53 or p53) is a critical tumour suppressor that prevents cancer development by inducing a transcriptional program which can lead to diverse cellular responses, most prominently, cell proliferation arrest/senescence with survival of cells or cell death by apoptosis. Why distinct cell types undergo different outcomes after p53 activation remains unclear. Using integrated RNA-sequencing, proteomic and functional analyses across a diverse range of murine primary cell types, we demonstrate that cell fate is governed by the balance between pro-survival BCL-2 and pro-apoptotic BH3-only proteins. Cells resistant to apoptosis displays a higher starting ratio of pro-survival BCL-2 to pro-apoptotic BH3-only proteins, along with transcriptional upregulation of the pro-survival gene Bcl2l1, encoding BCL-XL. This control of cell fate is also seen in human wild-type p53 cancer cell lines. These findings reveal the mechanism for understanding p53-driven cell fate decisions, suggest therapeutic strategies to shift p53-induced cell proliferation arrest/senescence toward apoptotic cell death and allowed generation of an RNAseq data-based predictor of outcome for cancer cells after p53 activation.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
Nature Communications
5641 papers in training set
Top 23%
7.0%
2
Scientific Reports
3612 papers in training set
Top 12%
6.5%
3
Cell Death Discovery
58 papers in training set
Top 0.1%
5.0%
4
Cell Reports
1498 papers in training set
Top 8%
5.0%
5
Cell Death & Differentiation
48 papers in training set
Top 0.1%
4.7%
6
Cell Death & Disease
126 papers in training set
Top 0.5%
4.7%
7
Biochemical Journal
91 papers in training set
Top 0.2%
4.7%
8
eLife
5828 papers in training set
Top 31%
3.9%
9
Molecular Cell
350 papers in training set
Top 2%
3.9%
10
Journal of Biological Chemistry
690 papers in training set
Top 3%
3.1%
11
Molecular Oncology
55 papers in training set
Top 0.3%
3.1%
50% of probability mass above
12
Science Signaling
65 papers in training set
Top 0.4%
2.6%
13
Redox Biology
70 papers in training set
Top 0.5%
2.3%
14
Cell Death & Disease
21 papers in training set
Top 0.2%
1.9%
15
Molecular Cancer Research
49 papers in training set
Top 0.6%
1.8%
16
EMBO Reports
263 papers in training set
Top 3%
1.8%
17
PLOS ONE
5266 papers in training set
Top 50%
1.7%
18
Science Advances
1243 papers in training set
Top 21%
1.7%
19
Molecular and Cellular Biology
47 papers in training set
Top 0.5%
1.7%
20
Communications Biology
993 papers in training set
Top 16%
1.6%
21
EMBO Molecular Medicine
95 papers in training set
Top 1%
1.4%
22
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 33%
1.3%
23
Developmental Cell
196 papers in training set
Top 3%
1.1%
24
Nucleic Acids Research
1281 papers in training set
Top 12%
1.1%
25
Life Science Alliance
285 papers in training set
Top 6%
1.1%
26
International Journal of Molecular Sciences
494 papers in training set
Top 13%
1.0%
27
Oncogene
85 papers in training set
Top 2%
1.0%
28
PLOS Genetics
862 papers in training set
Top 11%
1.0%
29
Cancer Gene Therapy
11 papers in training set
Top 0.1%
1.0%
30
iScience
1154 papers in training set
Top 37%
0.8%