Detecting cancer from our fingerprints?

14th March 2023 - Last modified 19th October 2023

By Ashley Hayes PhD, Account Executive/Science Writer

What if there was a way to diagnose cancer – quite literally – at the tip of our fingers? Amazingly, recent work has found that the analysis of bodily fluids present on our fingerprints can be used to detect breast cancer with high levels of accuracy. In this blog, we’ll talk about how the analysis of the chemical composition of our bodily fluids can also detect other types of cancer – a development that could pave the way for quicker and less invasive screening methods.

The need for less invasive breast cancer screening

Breast cancer affects an estimated 2.3 million women per year, causing 685,000 deaths [1]. Like with many other types of cancers, a timely diagnosis is key to improving the prognosis.

Mammograms are viewed as the ‘gold standard’ for breast cancer detection, and are capable of early-stage diagnosis. However, this method for breast cancer screening often causes physical discomfort and exposes individuals to radiation.

And worryingly, around 1.2 million women in the UK missed their mammogram appointments between 2020 and 2021, due to the increased strain that the COVID-19 pandemic placed on the NHS [2].

With global healthcare systems facing greater pressure than ever, more efficient, less invasive screening methods for breast cancer detection are desperately required. And this is true for many other types of cancer too, with screening often involving invasive procedures such as biopsies, endoscopies and colonoscopies, which place further pressure on healthcare systems and cause patient discomfort.

Sweating the small things: analysing the molecules in our perspiration

The good news is that a promising cancer screening method may be just around the corner, and it’s based on a well-known technology called MALDI MS (matrix-assisted laser desorption/ionization mass spectrometry).

In a nutshell, MALDI MS involves the separation and ionisation of molecules that are collected from bodily fluids, like sweat, that are present on our fingertip smears. The electrical charge emitted by the ionised molecules is analysed by the MALDI MS equipment, which determines the spectrum of molecular weights present in the sample. This gives scientists the ability to identify the molecules present in our bodily fluids.

MALDI MS can detect a whole range of molecules from fingertip smears and other bodily samples, such as DNA, proteins, carbohydrates and other complex metabolites. For this reason, this technique has been widely used in forensics over the past decade. MALDI MS can detect the presence of metabolised drugs and traces of explosives, for example, on an individual’s fingertips [3].

From crime scenes to hospitals: fingertip smears can accurately diagnose breast cancer

Professor Simona Francese and her research team at Sheffield Hallam University have pioneered the method of fingerprint analysis using MALDI MS, and have been key to developing this method for use in forensics. Recently, the team have also helped this technique move into the field of cancer diagnostics.

So, we know that MALDI MS can characterise the molecules present in our fingertip smears. But how can this technique detect cancer? The answer lies in our metabolism, with an array of metabolites being released from cancerous cells into bodily fluids including sweat. From this knowledge, it was hypothesised that the sweat analysed from fingertip smears is different between those that have cancer and those that don’t.

In a recently published proof-of-concept study [4], Prof. Francese and her team used fingertip smears to detect breast cancer with MALDI MS. The fingerprints between fifteen women were analysed – five of these women were known to have benign breast growths, five had early-stage breast cancer, and five had metastatic breast cancer.

From the data obtained from the MALDI MS using fingertip smears, a machine learning algorithm was built to accurately detect breast cancer, and also distinguish between the benign, early-stage and metastatic samples with 98% accuracy. This is higher than mammograms, which can only identify breast cancer in around 87% of cases [5].

A new wave of cancer diagnostics

In addition to breast cancer, MALDI MS has shown the promising ability to detect several other types of cancers.

Instead of fingertip smears, the majority of these studies have used tissue samples to detect colon cancer [6], esophageal cancer [7], stomach cancer [7] and several more types of cancer with high levels of accuracy.

Moving away from tissue biopsies for MALDI MS and towards less invasive samples allows for a quicker and more efficient cancer screening. In addition to the fingerprint smears used to detect breast cancer [4], MALDI MS has been carried out using urine samples to detect bladder cancer [8] and prostate cancer [9], and also using saliva samples to detect ovarian cancer [10] and blood samples to detect lung cancer [11].

In summary, this research is driving forward the use of MALDI MS as a promising new non-invasive and accurate technique for cancer diagnosis, using fingertip smears and bodily fluids. This has the potential to increase the detection of several types of cancers, ultimately improving cancer prognosis and relieving pressure on healthcare systems.

At Alto, we love science news! Talking about it, reading about it – and of course writing about it. To find out more about our science writing expertise, contact us!

References

(1) S. Lei, R. Zheng, S. Zhang, S. Wang, R. Chen, K. Sun, H. Zeng, J. Zhou and W. Wei, “Global patterns of breast cancer incidence and mortality: A population-based cancer registry data analysis from 2000 to 2020.,” Cancer communications (London, England), vol. 41, no. 11, pp. 1183-1194, November 2021.

(2) [Online]. Available: https://digital.nhs.uk/data-and-information/publications/statistical/breast-screening-programme/england—2020-21.

(3) S. Francese, R. Bradshaw and N. Denison, “An update on MALDI mass spectrometry based technology for the analysis of fingermarks – stepping into operational deployment.,” The Analyst, vol. 142, no. 14, pp. 2518-2546, July 2017.

(4) C. Russo, L. Wyld, M. Da Costa Aubreu, C. S. Bury, C. Heaton, L. M. Cole and S. Francese, “Non-invasive screening of breast cancer from fingertip smears–a proof of concept study,” Scientific Reports, vol. 13, p. 1868, 2023.

(5) C. D. Lehman, R. F. Arao, B. L. Sprague, J. M. Lee, D. S. M. Buist, K. Kerlikowske, L. M. Henderson, T. Onega, A. N. A. Tosteson, G. H. Rauscher and D. L. Miglioretti, “National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium.,” Radiology, vol. 283, no. 1, pp. 49-58, April 2017.

(6) P. Mittal, M. R. Condina, M. Klingler-Hoffmann, G. Kaur, M. K. Oehler, O. M. Sieber, M. Palmieri, S. Kommoss, S. Brucker, M. D. McDonnell and P. Hoffmann, “Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging.,” Cancers, vol. 13, no. 21, October 2021.

(7) R. Singhal, J. B. Carrigan, W. Wei, P. Taniere, R. K. Hejmadi, C. Forde, C. Ludwig, J. Bunch, R. L. Griffiths, P. J. Johnson, O. Tucker, D. Alderson, U. L. Günther and D. G. Ward, “MALDI profiles of proteins and lipids for the rapid characterisation of upper GI-tract cancers.,” Journal of proteomics, vol. 80, pp. 207-15, March 2013.

(8) F. Li, Z. Yu, P. Chen, G. Lin, T. Li, L. Hou, Y. Du and W. Tan, “The increased excretion of urinary orosomucoid 1 as a useful biomarker for bladder cancer.,” American journal of cancer research, vol. 6, no. 2, pp. 331-40, 2016.

(9) C. D. Calvano, A. Aresta, M. Iacovone, G. E. De Benedetto, C. G. Zambonin, M. Battaglia, P. Ditonno, M. Rutigliano and C. Bettocchi, “Optimization of analytical and pre-analytical conditions for MALDI-TOF-MS human urine protein profiles.,” Journal of pharmaceutical and biomedical analysis, vol. 51, no. 4, pp. 907-14, March 2010.

(10) M. Tajmul, F. Parween, L. Singh, S. R. Mathur, J. B. Sharma, S. Kumar, D. N. Sharma and S. Yadav, “Identification and validation of salivary proteomic signatures for non-invasive detection of ovarian cancer.,” International journal of biological macromolecules, vol. 108, pp. 503-514, March 2018.

(11) Y. Song, X. Xu, N. Wang, T. Zhang and C. Hu, “MALDI-TOF-MS analysis in low molecular weight serum peptidome biomarkers for NSCLC.,” Journal of clinical laboratory analysis, vol. 36, no. 4, p. e24254, April 2022.