Cytoplasmic p53β Isoforms Are Associated with Worse Disease-Free Survival in Breast Cancer

TP53 mutations are associated with tumour progression, resistance to therapy and poor prognosis. However, in breast cancer, TP53′s overall mutation frequency is lower than expected (~25%), suggesting that other mechanisms may be responsible for the disruption of this critical tumour suppressor. p53 isoforms are known to enhance or disrupt p53 pathway activity in cell- and context-specific manners. Our previous study revealed that p53 isoform mRNA expression correlates with clinicopathological features and survival in breast cancer and may account for the dysregulation of the p53 pathway in the absence of TP53 mutations. Hence, in this study, the protein expression of p53 isoforms, transactivation domain p53 (TAp53), p53β, Δ40p53, Δ133p53 and Δ160p53 was analysed using immunohistochemistry in a cohort of invasive ductal carcinomas (n = 108). p53 isoforms presented distinct cellular localisation, with some isoforms being expressed in tumour cells and others in infiltrating immune cells. Moreover, high levels of p53β, most likely to be N-terminally truncated β variants, were significantly associated with worse disease-free survival, especially in tumours with wild-type TP53. To the best of our knowledge, this is the first study that analysed the endogenous protein levels of p53 isoforms in a breast cancer cohort. Our findings suggest that p53β may be a useful prognostic marker

Effect of p53 and its N-terminally truncated isoform, Δ40p53, on breast cancer migration and invasion

Breast cancer is the most diagnosed malignancy in women, with over half a million women dying from this disease each year. In our previous studies, ∆40p53, an N‐terminally truncated p53 isoform, was found to be upregulated in breast cancers, and a high ∆40p53 : p53α ratio was linked with worse disease‐free survival. Although p53α inhibits cancer migration and invasion, little is known about the role of ∆40p53 in regulating these metastasis‐related processes and its role in contributing to worse prognosis. The aim of this study was to assess the role of ∆40p53 in breast cancer migration and invasion. A relationship between Δ40p53 and gene expression profiles was identified in oestrogen‐receptor‐positive breast cancer specimens. To further evaluate the role of Δ40p53 in oestrogen‐receptor‐positive breast cancer, MCF‐7 and ZR75‐1 cell lines were transduced to knockdown p53α or Δ40p53 and overexpress Δ40p53. Proliferation, migration and invasion were assessed in the transduced sublines, and gene expression was assessed through RNA‐sequencing and validated by reverse‐transcription quantitative PCR. Knockdown of both p53α and ∆40p53 resulted in increased proliferation, whereas overexpression of ∆40p53 reduced proliferation rates. p53α knockdown was also associated with increased cell mobility. ∆40p53 overexpression reduced both migratory and invasive properties of the transduced cells. Phenotypic findings are supported by gene expression data, including differential expression of LRG1, HYOU1, UBE2QL1, SERPINA5 and PCDH7. Taken together, these results suggest that, at the basal level, ∆40p53 works similarly to p53α in suppressing cellular mobility and proliferation, although the role of Δ40p53 may be cell context‐specific

Alterations in the p53 isoform ratio govern breast cancer cell fate in response to DNA damage

Our previous studies have shown that p53 isoform expression is altered in breast cancer and related to prognosis. In particular, a high ∆40p53:p53α ratio is associated with worse disease-free survival. In this manuscript, the influence of altered Δ40p53 and p53α levels on the response to standard of care DNA-damaging agents used in breast cancer treatment was investigated in vitro. Our results revealed that a high Δ40p53:p53α ratio causes cells to respond differently to doxorubicin and cisplatin treatments. Δ40p53 overexpression significantly impairs the cells’ sensitivity to doxorubicin through reducing apoptosis and DNA damage, whereas Δ40p53 knockdown has the opposite effect. Further, a high Δ40p53:p53α ratio inhibited the differential expression of several genes following doxorubicin and promoted DNA repair, impairing the cells’ canonical response. Overall, our results suggest that the response of breast cancer cells to standard of care DNA-damaging therapies is dependent on the expression of p53 isoforms, which may contribute to outcomes in breast cancer

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Comparison of the QuantiGene 2.0 Assay and Real-Time RT-PCR in the Detection of p53 Isoform mRNA Expression in Formalin-Fixed Paraffin-Embedded Tissues- A Preliminary Study

<div><p>p53 is expressed as multiple smaller isoforms whose functions in cancer are not well understood. The p53 isoforms demonstrate abnormal expression in different cancers, suggesting they are important in modulating the function of full-length p53 (FLp53). The quantification of relative mRNA expression has routinely been performed using real-time PCR (qPCR). However, there are serious limitations when detecting p53 isoforms using this method, particularly for formalin-fixed paraffin-embedded (FFPE) tissues. The use of FFPE tumours would be advantageous to correlate expression of p53 isoforms with important clinical features of cancer. One alternative method of RNA detection is the hybridization-based QuantiGene 2.0 Assay, which has been shown to be advantageous for the detection of RNA from FFPE tissues. In this pilot study, we compared the QuantiGene 2.0 Assay to qPCR for the detection of FLp53 and its isoform Δ40p53 in matched fresh frozen (FF) and FFPE breast tumours. FLp53 mRNA expression was detected using qPCR in FF and FFPE tissues, but Δ40p53 mRNA was only detectable in FF tissues. Similar results were obtained for the QuantiGene 2.0 Assay. FLp53 relative mRNA expression was shown to be strongly correlated between the two methods (R² = 0.9927, p = 0.0031) in FF tissues, however Δ40p53 was not (R² = 0.4429, p = 0.3345). When comparing the different methods for the detection of FLp53 mRNA from FFPE and FF samples, no correlation (R² = 0.0002, p = 0.9863) was shown using the QuantiGene 2.0 Assay, and in contrast, the level of expression was highly correlated between the two tissues using qPCR (R² = 0.8753, p = 0.0644). These results suggest that both the QuantiGene 2.0 Assay and qPCR methods are inadequate for the quantification of Δ40p53 mRNA in FFPE tissues. Therefore, alternative methods of RNA detection and quantification are required to study the relative expression of Δ40p53 in FFPE samples.</p></div

Comparison of the relative mRNA expression of Δ40p53 and FLp53 using the QuantiGene 2.0 Assay (QG 2.0) and real-time PCR (qPCR).

<p>(A) The relative expression of (A) FLp53 or (B) Δ40p53 from either FF or FFPE tissues, using real-time PCR (qPCR; black) or the QuantiGene 2.0 Assay (QG2.0; grey). Sample quantitation using the QuantiGene 2.0 Assay was performed in triplicate and normalised to β-Actin, and FFPE samples using real-time PCR were normalised to β2-Microglobulin.The bars represent the mean ± SD.</p

Location of the Probe Sets designed for the target genes used in the QuantiGene 2.0 Assay.

<p>Location of the Probe Sets designed for the target genes used in the QuantiGene 2.0 Assay.</p

Average detected signal for three genes tested in fresh frozen (FF) and FFPE tissues.

<p>Average detected signal for three genes tested in fresh frozen (FF) and FFPE tissues.</p