Feasibility of Integrating Canine Olfaction with Chemical and Microbial Profiling of Urine to Detect Lethal Prostate Cancer

AbstractProstate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs’ diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

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Feasibility of integrating canine olfaction with chemical and microbial profiling of urine to detect lethal prostate cancer

PLoS ONE ◽

10.1371/journal.pone.0245530 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0245530

Author(s):

Claire Guest ◽

Rob Harris ◽

Karen S. Sfanos ◽

Eva Shrestha ◽

Alan W. Partin ◽

...

Keyword(s):

Prostate Cancer ◽

16S Rdna ◽

Urine Samples ◽

Microbial Profiling ◽

Rdna Sequencing ◽

Urinary Microbiota ◽

Machine Olfaction ◽

Negative Controls ◽

Lethal Prostate Cancer ◽

Canine Olfaction

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs’ diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70–76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

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Faculty Opinions recommendation of Nuclear Pores Promote Lethal Prostate Cancer by Increasing POM121-Driven E2F1, MYC, and AR Nuclear Import.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.733793591.793551033 ◽

2018 ◽

Author(s):

Thomas Kodadek

Keyword(s):

Prostate Cancer ◽

Nuclear Import ◽

Nuclear Pores ◽

Lethal Prostate Cancer

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ONECUT2 Is a Targetable Master Regulator of Lethal Prostate Cancer That Suppresses the Androgen Axis

SSRN Electronic Journal ◽

10.2139/ssrn.3155552 ◽

2018 ◽

Author(s):

Mirja Rotinen ◽

Sungyong You ◽

Julie Yang ◽

Simon Coetzee ◽

Wen-Chin Huang ◽

...

Keyword(s):

Prostate Cancer ◽

Master Regulator ◽

Lethal Prostate Cancer

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Metabolite fingerprinting of novel Streptomyces UK-238 from the Himalayan forest

Current Pharmaceutical Analysis ◽

10.2174/1573412916666200206160836 ◽

2020 ◽

Vol 16 ◽

Author(s):

Nidhi Srivastava ◽

Indira P. Sarethy

Keyword(s):

Ethyl Acetate ◽

16S Rdna ◽

Retention Index ◽

Ethyl Acetate Extract ◽

Similarity Index ◽

Antimicrobial Drug ◽

16S Rdna Sequencing ◽

Metabolite Fingerprinting ◽

Streptomyces Sp ◽

Rdna Sequencing

Aims: Characterization of antimicrobial metabolites of novel Streptomyces sp. UK-238. Background: Novel antimicrobial drug discovery is urgently needed due to emerging multi antimicrobial drug resistance among pathogens. Since many years, natural products have provided the basic skeletons for many therapeutic compounds including antibiotics. Bioprospection of un/under explored habitats and focussing on selective isolation of actinobacteria as major reservoir of bio and chemodiversity has yielded good results. Objective: The main objectives of the study were the identification of UK-238 by 16S rDNA sequencing and antimicrobial metabolite fingerprinting of culture extracts. Method: In the present study, a promising isolate, UK-238, has been screened for antimicrobial activity and metabolite fingerprinting from the Himalayan Thano Reserve forest. It was identified by 16S rDNA sequencing. Ethyl acetate extract was partially purified by column chromatography. The pooled active fractions were fingerprinted by GC-MS and compounds were tentatively identified by collated data analysis based on Similarity Index, observed Retention Index from Databases and calculated Retention Index. Results: UK-238 was identified as Streptomyces sp. with 98.4% similarity to S. niveiscabiei. It exhibited broad-spectrum antibacterial and antifungal activity. GC-MS analysis of active fractions of ethyl acetate extract showed the presence of eighteen novel antimicrobial compounds belonging to four major categories- alcohols, alkaloid, esters and peptide. Conclusion: The study confirms that bioprospection of underexplored habitats can elaborate novel bio and chemodiversity.

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Detection of Prostate Cancer via IR Spectroscopic Analysis of Urinary Extracellular Vesicles: A Pilot Study

Membranes ◽

10.3390/membranes11080591 ◽

2021 ◽

Vol 11 (8) ◽

pp. 591

Author(s):

Xin-Le Yap ◽

Bayden Wood ◽

Teng-Aik Ong ◽

Jasmine Lim ◽

Bey-Hing Goh ◽

...

Keyword(s):

Prostate Cancer ◽

Extracellular Vesicles ◽

Cancer Progression ◽

Prostate Cancer Screening ◽

Principal Component ◽

Urine Samples ◽

Cancer Type ◽

Marker Proteins ◽

Novel Strategy ◽

Ir Spectroscopic

Extracellular vesicles (EVs) are membranous nanoparticles naturally released from living cells which can be found in all types of body fluids. Recent studies found that cancer cells secreted EVs containing the unique set of biomolecules, which give rise to a distinctive absorbance spectrum representing its cancer type. In this study, we aimed to detect the medium EVs (200–300 nm) from the urine of prostate cancer patients using Fourier transform infrared (FTIR) spectroscopy and determine their association with cancer progression. EVs extracted from 53 urine samples from patients suspected of prostate cancer were analyzed and their FTIR spectra were preprocessed for analysis. Characterization of morphology, particle size and marker proteins confirmed that EVs were successfully isolated from urine samples. Principal component analysis (PCA) of the EV’s spectra showed the model could discriminate prostate cancer with a sensitivity of 59% and a specificity of 81%. The area under curve (AUC) of FTIR PCA model for prostate cancer detection in the cases with 4–20 ng/mL PSA was 0.7, while the AUC for PSA alone was 0.437, suggesting the analysis of urinary EVs described in this study may offer a novel strategy for the development of a noninvasive additional test for prostate cancer screening.

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