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Tumor Progression02:07

Tumor Progression

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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
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Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts

Agustina Sabater1,2,3, Pablo Sanchis1,2,3, Rocio Seniuk1,2

  • 1Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires C1428EGA, Argentina.

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A new seven-gene signature predicts aggressive prostate cancer (PCa) and neuroendocrine prostate cancer (NEPC) progression. This discovery aids in personalized medicine and improved treatment strategies for PCa patients.

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Prostate cancer (PCa) is a major global health concern.
  • Progression to aggressive neuroendocrine prostate cancer (NEPC) presents significant challenges.
  • Accurate prognostic tools are crucial for effective PCa management.

Purpose of the Study:

  • To develop and validate a stemness-associated gene signature for PCa.
  • To identify patients at high risk for aggressive disease progression.
  • To enhance personalized treatment strategies in PCa.

Main Methods:

  • Utilized machine learning (Random Forest, Lasso regression) on large-scale transcriptomic data.
  • Developed a seven-gene signature (KMT5C, DPP4, TYMS, CDC25B, IRF5, MEN1, DNMT3B).
  • Validated the signature in independent cohorts and patient-derived xenograft (PDX) models.

Main Results:

  • The seven-gene signature demonstrated strong prognostic value across multiple survival endpoints.
  • Successfully identified NEPC subtypes and predicted poor outcomes in non-NEPC PCa with the signature.
  • The signature showed dual prognostic and classifier capabilities.

Conclusions:

  • The validated seven-gene signature is a robust tool for predicting PCa progression and identifying NEPC.
  • This signature supports personalized medicine by guiding treatment strategies.
  • Offers a valuable resource for improving PCa patient outcomes.