Bile-volatile organic compounds in the diagnostics of pancreatic cancer and biliary obstruction: A prospective proof-of-concept study

Volatile Organic Compounds in Biological Matrices as a Sensitive Weapon in Cancer Diagnosis

Diagnosis and intervention at the earliest stages of cancer are imperative for maximizing patient recovery outcomes and substantially increasing survival rates and quality of life. Recently, to facilitate cancer diagnosis, volatile organic compounds (VOCs) have shown potential with unique characteristics as cancer biomarkers. Various insects with sophisticated sensitivities of odor can be quickly and readily trained to recognize such VOCs using olfactory-linked skills. Furthermore, the approach to analyzing VOCs can be made using electronic noses, commonly referred to as e-noses. Using analytical instruments like GC-MS, LC-MS/MS, etc., chemical blends are separated into their constituent parts. The significance of odorant receptors in triggering neural responses to ambient compounds has received great attention in the last twenty years, particularly in the investigation of insect olfaction. Sensilla, a sophisticated olfactory neural framework, is regulated by a neuronal receptor composed of neuronal, non-neuronal, extracellular lymphatic fluid with an effectively generated shell. This review provides an in-depth exploration of the structural, functional, and signaling mechanisms underlying odorant sensitivities and chemical odor detection in the excretory products of cancer patients, addressing current challenges in VOC-based cancer diagnostics and innovative strategies for advancement while also envisioning the transformative role of artificial olfactory systems in the future of cancer detection. Furthermore, the article emphasizes recent preclinical and clinical advancements in VOC applications, highlighting their potential to redefine early diagnostic approaches in oncology.

Risk comparison of adverse reactions between gemcitabine monotherapy and gemcitabine combined with albumin-bound paclitaxel in pancreatic cancer: insights from the FDA Adverse Event Reporting System (FAERS) database

BACKGROUND

Pancreatic cancer (PC) is a highly aggressive malignancy with limited treatment options. Although gemcitabine monotherapy (G treatment) has long been a standard treatment, combination therapies, such as gemcitabine with albumin-bound paclitaxel (AG treatment), have shown improved outcomes and were approved by the FDA for the PC. However, the AG treatment is also associated with increased adverse events (AEs), which remain inadequately evaluated in real-world settings.

METHODS

We utilized the FDA Adverse Event Reporting System (FAERS) to conduct a large-scale pharmacovigilance analysis comparing the safety profiles of G and AG treatments for PC. By analyzing adverse event data from the third quarter of 2013 to the second quarter of 2024 and quantifying AE signals with reporting odds ratio (ROR) and proportional reporting ratio (PRR) methods, we compared the risk of AEs between the groups. Time to onset (TTO), subgroup and logistic regression analyses were also performed.

RESULTS

The study revealed a higher proportion of male (n = 2307, 54.1%) and elderly patients (age ≥ 65years, n = 2172, 50.9%) in the AG treatment group compared to the G treatment group. We found 17 preferred terms with positive signals at the top 50 common AEs, especially in gastrointestinal and blood systems. Cardiac and neurological AEs also needed to be vigilant. Biliary sepsis and infectious enterocolitis were newly identified AEs and deserve attention. Median TTO was 34 (IQR: 8-103) days (G) and 41 (IQR: 10-104) days (AG), with most AEs occurring within the first month (48.3% and 44%). Subgroup analysis revealed that male patients using the AG treatment had the highest risk of immune-mediated hepatitis (ROR = 23.51, 95% CI = 3.21-172.1), while elderly patients had elevated risks for presyncope (ROR = 24.84, 95% CI = 3.40-181.28) and falls (ROR = 18.60, 95% CI = 2.53-136.97). Logistic regression showed higher-risk fatal outcomes in males (adjusted OR = 1.42, 95% CI = 1.15-1.76, P < 0.01) and elderly patients (adjusted OR = 1.36, 95% CI = 1.10-1.69, P < 0.01).

CONCLUSION

This research offers critical safety insights in real-world settings, emphasizing patients at heightened AEs risk and informing clinical decision-making in PC treatment.

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

A Systematic Review and Meta-Analysis: Volatile Organic Compound Analysis in the Detection of Hepatobiliary and Pancreatic Cancers

BACKGROUND

Hepatobiliary cancers are notoriously difficult to detect, frequently leading to diagnosis in later stages of disease when curative treatment is not an option. The currently used biomarkers such as AFP (alpha-fetoprotein) and CA19.9 lack sensitivity and specificity. Hence, there is an unmet need for an alternative biomarker.

AIM

To evaluate the diagnostic accuracy of volatile organic compounds (VOCs) for the detection of hepatobiliary and pancreatic cancers.

METHODS

A systematic review of VOCs' use in the detection of hepatobiliary and pancreatic cancers was performed. A meta-analysis was performed using the software R. Heterogeneity was explored through meta-regression analysis.

RESULTS

A total of 18 studies looking at 2296 patients were evaluated. Pooled sensitivity and specificity of VOCs for the detection of hepatobiliary and pancreatic cancer were 0.79 (95% CI, 0.72-0.85) and 0.81 (97.5% CI, 0.76-0.85), respectively. The area under the curve was 0.86. Meta-regression analysis showed that the sample media used contributed to heterogeneity. Bile-based VOCs showed the highest precision values, although urine and breath are preferred for their feasibility.

CONCLUSIONS

Volatile organic compounds have the potential to be used as an adjunct tool to aid in the early diagnosis of hepatobiliary cancers.