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The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
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Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.

Mohamed A A A Hegazi¹, Marta Noemi Monari², Fabio Pasqualini¹

¹Department of Immunology and Inflammation, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy.

Life (Basel, Switzerland)

|May 27, 2026

Summary

Volatile organic compounds (VOCs) offer a promising, non-invasive method for prostate cancer (PCa) detection. Dogs, invertebrates, and electronic noses show potential in identifying PCa-related VOC signatures for early diagnosis.

Keywords:

artificial intelligence diagnosis eNose prostate cancer volatile organic compound

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A Murine Orthotopic Bladder Tumor Model and Tumor Detection System

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Published on: January 12, 2017

Area of Science:

Biochemistry
Oncology
Analytical Chemistry

Background:

Prostate cancer (PCa) is a leading cause of cancer mortality in men globally.
Early detection of PCa is critical for effective treatment and improved patient outcomes.
Non-invasive, accurate, and cost-effective screening strategies are highly sought after.

Purpose of the Study:

To review recent advances in using volatile organic compounds (VOCs) for prostate cancer diagnosis.
To evaluate the clinical reproducibility and robustness of VOC-based PCa detection methods.
To identify challenges and areas for future development in VOC analysis for PCa screening.

Main Methods:

Review of current literature on volatolomics for PCa detection.
Analysis of biological systems (trained dogs, invertebrates) and technological platforms (electronic noses) for identifying PCa-associated VOC signatures.
Evaluation of diagnostic performance, including sensitivity and specificity.

Main Results:

Volatile organic compounds (VOCs) show significant potential as non-invasive biomarkers for PCa.
Trained dogs, invertebrates, and electronic noses have demonstrated ability to detect PCa-related olfactory patterns.
Electronic noses (eNoses) utilizing sensor arrays and neural networks are rapidly evolving diagnostic tools.

Conclusions:

Biologically inspired and technology-driven strategies using VOCs are reshaping PCa diagnostics.
These approaches offer a foundation for rapid, non-invasive, and clinically translatable PCa detection methods.
Standardization of sampling, storage, analysis, larger cohorts, external validation, and regulatory integration are key challenges for clinical translation.