Anti-tissue factor antibody conjugated with monomethyl auristatin E or deruxtecan in pancreatic cancer models

Ryo Tsumura1, Takahiro Anzai1,2, Yoshikatsu Koga1

  • 1Division of Developmental Therapeutics, EPOC, National Cancer Center, Kashiwa, Japan.

Cancer Science
|September 25, 2024
PubMed

Insights

Payload choice for antibody-drug conjugates (ADCs) targeting tissue factor (TF) impacts efficacy. Deruxtecan (DXd)-ADCs may offer better pancreatic cancer treatment due to heterogeneous TF expression, unlike MMAE-ADCs.

Area of Science:

  • Oncology
  • Pharmacology
  • Biotechnology

Background:

  • Antibody-drug conjugates (ADCs) are a promising cancer therapy class.
  • Tissue factor (TF) is implicated in cancer, with anti-TF ADCs showing clinical utility.
  • Payload optimization is crucial for ADC efficacy, yet comparisons of different cytotoxic mechanisms are lacking.

Purpose of the Study:

  • To compare the efficacy of anti-TF ADCs with different payloads (MMAE and DXd) in pancreatic cancer models.
  • To investigate the influence of TF expression levels and heterogeneity on ADC response.
  • To determine optimal payload selection strategies for anti-TF ADCs.

Main Methods:

  • Humanized anti-TF antibody (clone.1084) conjugated with either MMAE or DXd.
  • Evaluation of ADC efficacy in pancreatic cancer cell line and patient-derived xenograft models.
  • Analysis of TF expression in pancreatic cancer tissue array.

Main Results:

  • Optimizing the drug-to-antibody ratio was essential for each payload to ensure pharmacokinetics and delivery.
  • Anti-TF ADC with MMAE demonstrated superior efficacy in tumors with strong, homogeneous TF expression.
  • Anti-TF ADC with DXd showed greater effectiveness in tumors with weak, heterogeneous TF expression, common in pancreatic cancer.

Conclusions:

  • Payload selection for anti-TF ADCs should be tailored to TF expression patterns.
  • DXd-conjugated anti-TF ADCs may be more suitable for pancreatic cancer treatment due to prevalent weak and heterogeneous TF expression.
  • Individualized optimization of ADC payloads holds potential for maximizing therapeutic outcomes.

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