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The management of cancer patients has markedly improved with the advent of personalised medicine where treatments are given based on tumour antigen expression amongst other. Within this remit, liquid biopsies will no doubt improve this personalised cancer management. Identifying circulating tumour cells in blood allows a better assessment for tumour screening, staging, response to treatment and follow up. However, methods to identify/capture these circulating tumour cells using cancer cells' antigen expression or their physical properties are not robust enough. Thus, a methodology that can identify these circulating tumour cells in blood regardless of the type of tumour is highly needed. Fourier Transform Infrared (FTIR) microspectroscopy, which can separate cells based on their biochemical composition, could be such technique. In this feasibility study, we studied lung cancer cells (squamous cell carcinoma and adenocarcinoma) mixed with peripheral blood mononuclear cells (PBMC). The data obtained shows, for the first time, that FTIR microspectroscopy together with Random Forest classifier is able to identify a single lung cancer cell in blood. This separation was easier when the region of the IR spectra containing lipids and the amide A (2700 to 3500 cm-1) was used. Furthermore, this work was carried out using glass coverslips as substrates that are widely used in pathology departments. This allows further histopathological cell analysis (staining, immunohistochemistry, …) after FTIR spectra are obtained. Hence, although further work is needed using blood samples from patients with cancer, FTIR microspectroscopy could become another tool to be used in liquid biopsies for the identification of circulating tumour cells, and in the personalised management of cancer., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Dowling et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The clinical translation of Fourier transform infrared (FT-IR) microspectroscopy in pathology will require bringing this technique as close as possible to standard practice in pathology departments. An important step is sample preparation for both FT-IR microspectroscopy and pathology. This should entail minimal disruption of standard clinical practice while achieving good quality FT-IR spectral data. In fact, the recently described possibility of obtaining FT-IR spectra of cells placed on glass substrates brings FT-IR microspectroscopy closer to a clinical application. We have now furthered this work in order to identify two different types of lung cancer cells placed on glass coverslips. Two types of sample preparation which are widely used in pathology, cytospin and smear, have been used. Samples were fixed with either methanol, used in pathology, or formalin (4% paraformaldehyde) used widely in spectroscopy. Fixation with methanol (alcohol-based fixative) removed lipids from cells causing a decrease in intensity of the peaks at 2850 cm -1 and 2920 cm -1 . Nevertheless, we show for the first time that using either type of sample preparation and fixation on thin glass coverslips allowed to differentiate between two different types of lung cancer cells using either the lipid region or the fingerprint region ranging from 1800 cm -1 to 1350 cm -1 . We believe that formalin-fixed cytospin samples would be preferred to study cells on thin coverslips using FT-IR microspectroscopy. This work presents a clear indication for future advances in clinical assessment of samples within pathology units to gain a deeper understanding of cells/tissues under investigation.

The rising incidence of cancer worldwide is causing an increase in the workload in pathology departments. This, coupled with advanced analysis methodologies, supports a developing need for techniques that could identify the presence of cancer cells in cytology and tissue samples in an objective, fast, and automated way. Fourier transform infrared (FT-IR) microspectroscopy can identify cancer cells in such samples objectively. Thus, it has the potential to become another tool to help pathologists in their daily work. However, one of the main drawbacks is the use of glass substrates by pathologists. Glass absorbs IR radiation, removing important mid-IR spectral data in the fingerprint region (1800 cm -1 to 900 cm -1 ). In this work, we hypothesized that, using glass coverslips of differing compositions, some regions within the fingerprint area could still be analyzed. We studied three different types of cells (peripheral blood mononuclear cells, a leukemia cell line, and a lung cancer cell line) and lymph node tissue placed on four different types of glass coverslips. The data presented here show that depending of the type of glass substrate used, information within the fingerprint region down to 1350 cm -1 can be obtained. Furthermore, using principal component analysis, separation between the different cell lines was possible using both the lipid region and the fingerprint region between 1800 cm -1 and 1350 cm -1 . This work represents a further step towards the application of FT-IR microspectroscopy in histopathology departments.

In spite of new drugs, lung cancer is associated with a very poor prognosis. While targeted therapies are improving outcomes, it is not uncommon for many patients to have only a partial response, and relapse during follow-up. Thus, new drugs or re-evaluation of existing therapies used to treat other non-malignant diseases (drug repurposing) are still needed. While this research both in vitro and in vivo is being carried out, it is important to be attentive to patients where the disease responds to treatments not considered standard in clinical practice. We report here a patient with adenocarcinoma of the lung who, after declining chemotherapy and radiotherapy, presented with tumour response following self-administration of cannabidiol, a non-psychoactive compound present in Cannabis sativa . Prior work has shown that cannabidiol may have anti-neoplastic properties and enhance the immune response to cancer. The data presented here indicate that cannabidiol might have led to a striking response in a patient with lung cancer., Competing Interests: Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Over the last few years, great effort has been placed on developing Fourier Transform Infrared (FTIR) microspectroscopy as a tool to help in the histopathological diagnosis of cancer. The ever increasing workload in pathology departments is calling for a technique that could identify the presence of cancer cells in cytology and tissue samples in an objective, fast and automated way. However, pathologists use glass slides which absorb infrared (IR) radiation thus removing important mid-IR spectral data in the fingerprint region (proteins, DNA, RNA; 1800 cm-1 to 900 cm-1). To this purpose, we hypothesised whether using thinner glass slides, i.e., glass coverslips, would allow us to obtain spectral data not only from the lipid region (3100 cm-1 to 2700 cm-1) but also from the fingerprint region. To this purpose, we studied peripheral blood mononuclear cells (PBMC), a leukaemia cell line (K562) and a lung cancer cell line (CALU-1). Cells were placed on DAKO coverslips and their FTIR spectra obtained at MIRAS beamline, Alba synchrotron light source (Barcelona, Catalonia). The data presented here not only shows for the first time that it is possible to obtain spectral data from most of the amide I region (1800 cm-1 to 1570 cm-1) of cells placed on glass coverslips but more important, principal component analysis was able to separate between the three types of cells for both the lipid and the amide I regions. The methodology here described is a further step in the application of FTIR microspectroscopy in histopathology departments.

Over the last few years, FTIR spectroscopy has become a potential analytical method in tissue and cell studies for cancer diagnosis. This has opened a way towards clinical applications such as a tool that would scan samples to assess the presence or absence of malignant cells in biopsies, or as an aid to help pathologists to better characterise those cells that are suspicious but not diagnostic for cancer. The latter application has the problem that in order to assess these cells pathologists would have already dealt with stained samples. Therefore, it is important to understand how staining would affect the spectra of cells. To this purpose, we have conducted this study in order to clarify, first, how haematoxylin and eosin (H&E) and Papanicolau (Pap) stainings affect the spectra of single cells and, second, whether FTIR spectroscopy could differentiate between stained lung cancer cells and their normal counterparts. Furthermore, different cell preparations (cytospin, and smear) used in cytological diagnosis were assessed. Experiments performed using a bright infrared (IR) source (synchrotron) showed that both H&E and Pap staining induced marked changes in the lipid and amide-II band regions. Despite this, FTIR spectroscopy of already stained cells is capable of differentiating between lung cancer cells and their normal counterparts. The clinical applications of this methodology are discussed.

We present an approach for estimating and correcting Mie scattering occurring in infrared spectra of single cells, at diffraction limited probe size, as in synchrotron based microscopy. The Mie scattering is modeled by extended multiplicative signal correction (EMSC) and subtracted from the vibrational absorption. Because the Mie scattering depends non-linearly on alpha, the product of the radius and the refractive index of the medium/sphere causing it, a new method was developed for estimating the Mie scattering by EMSC for unknown radius and refractive index of the Mie scatterer. The theoretically expected Mie contributions for a range of different alpha values were computed according to the formulae developed by Van de Hulst (1957). The many simulated spectra were then summarized by a six-dimensional subspace model by principal component analysis (PCA). This subspace model was used in EMSC to estimate and correct for Mie scattering, as well as other additive and multiplicative interference effects. The approach was applied to a set of Fourier transform infrared (FT-IR) absorbance spectra measured for individual lung cancer cells in order to remove unwanted interferences and to estimate ranges of important alpha values for each spectrum. The results indicate that several cell components may contribute to the Mie scattering.