Targeting mutant p53: Evaluation of novel anti-p53R175H monoclonal antibodies as diagnostic tools
2025

New Antibodies for Cancer Diagnosis Targeting Mutant p53

Sample size: 8 publication 10 minutes Evidence: moderate

Author Information

Author(s): Diana Spiegelberg, Le-Ann Hwang, Khian Hong Pua, Sashwini Chandra Kumar, Xin Yu Koh, Xiao Hui Koh, Ram Kumar Selvaraju, Kanaga Sabapathy, Marika Nestor, David Lane

Primary Institution: Uppsala University

Hypothesis

Can novel anti-p53R175H monoclonal antibodies be effective diagnostic tools for cancer?

Conclusion

The study suggests that molecular imaging with anti-p53R175H tracers could enhance cancer diagnostics and treatment monitoring.

Supporting Evidence

  • About 50% of all cancers have a mutation in p53, making it a key target for cancer diagnostics.
  • The antibodies showed high specificity for the p53R175H mutation without cross-reactivity to wild-type p53.
  • Both antibodies demonstrated suitable imaging characteristics for molecular imaging.
  • Significantly higher uptake was observed in tumors expressing the mutant p53 compared to control tumors.
  • Repeated imaging showed the best contrast at 48 hours post-injection.
  • Long shelf life and stability of the radioiodinated antibodies were confirmed.
  • Immunohistochemistry confirmed the specificity of the antibodies in tumor tissues.
  • The study highlights the potential of monoclonal antibodies for precision medicine in cancer.

Takeaway

Scientists created special antibodies to find a common cancer mutation, which could help doctors see and treat cancer better.

Methodology

The study involved in vitro and in vivo evaluations of two monoclonal antibodies targeting the p53R175H mutation, including SPECT/CT imaging and biodistribution analysis.

Potential Biases

Potential bias due to the use of a specific mouse model that may not fully represent human cancer.

Limitations

The study used a double tumor model which may not be ideal for direct comparisons due to size differences.

Statistical Information

P-Value

p<0.05

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1038/s41598-024-83871-w

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