Mass spectrometry-based proteomics of single cells and organoids: The new generation of cancer research

Organoid: Bridging the gap between basic research and clinical practice

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy. In addition, we also put forward some practical suggestions on how to construct a new generation of organoid platform, which is destined to vigorously promote the reform of basic-translational medicine.

Single-cell ICP-MS to address the role of trace elements at a cellular level

The heterogeneity properties shown by cells or unicellular organisms have led to the development of analytical methods at the single-cell level. In this sense, considering the importance of trace elements in these biological systems, the inductively coupled plasma mass spectrometer (ICP-MS) configured for analyzing single cell has presented a high potential to assess the evaluation of elements in cells. Moreover, advances in instrumentation, such as coupling laser ablation to the tandem configuration (ICP-MS/MS), or alternative mass analyzers (ICP-SFMS and ICP-TOFMS), brought significant benefits, including sensitivity improvement, high-resolution imaging, and the cell fingerprint. From this perspective, the single-cell ICP-MS has been widely reported in studies involving many fields, from oncology to environmental research. Hence, it has contributed to finding important results, such as elucidating nanoparticle toxicity at the cellular level and vaccine development. Therefore, in this review, the theory of single-cell ICP-MS analysis is explored, and the applications in this field are pointed out. In addition, the instrumentation advances for single-cell ICP-MS are addressed.

Metabolomics-based mass spectrometry methods to analyze the chemical content of 3D organoid models

Metabolomics, the study of metabolites present in biological samples, can provide a global view of sample state as well as insights into biological changes caused by disease or environmental interactions. Mass spectrometry (MS) is commonly used for metabolomics analysis given its high-throughput capabilities, high sensitivity, and capacity to identify multiple compounds in complex samples simultaneously. MS can be coupled to separation methods that can handle small volumes, making it well suited for analyzing the metabolome of organoids, miniaturized three-dimensional aggregates of stem cells that model in vivo organs. Organoids are being used in research efforts to study human disease and development, and in the design of personalized drug treatments. For organoid models to be useful, they need to recapitulate morphological and chemical aspects, such as the metabolome, of the parent tissue. This review highlights the separation- and imaging-based MS-based metabolomics methods that have been used to analyze the chemical contents of organoids. Future perspectives on how MS techniques can be optimized to determine the accuracy of organoid models and expand the field of organoid research are also discussed.

Mass spectrometry-based proteomics of 3D cell culture: A useful tool to validate culture of spheroids and organoids

Worldwide obesity, defined as abnormal or excessive fat accumulation that may result in different comorbidities, is considered a pandemic condition that has nearly tripled in the last 45 years. Most studies on obesity use animal models or adipocyte monolayer cell culture to investigate adipose tissue. However, besides monolayer cell culture approaches do not fully recapitulate the physiology of living organisms, there is a growing need to reduce or replace animals in research. In this context, the development of 3D self-organized structures has provided models that better reproduce the in vitro aspects of the in vivo physiology in comparison to traditional monolayer cell culture. Besides, recent advances in omics technologies have allowed us to characterize these cultures at the proteome, metabolome, transcription factor, DNA-binding and transcriptomic levels. These two combined approaches, 3D culture and omics, have provided more realistic data about determined conditions. Thereby, here we focused on the development of an obesity study pipeline including proteomic analysis to validate adipocyte-derived spheroids. Through the combination of collected mass spectrometry data from differentiated 3T3-L1 spheroids and from murine white adipose tissue (WAT), we identified 1732 proteins in both samples. By using a comprehensive proteomic analysis, we observed that the in vitro 3D culture of differentiated adipocytes shares important molecular pathways with the WAT, including expression of proteins involved in central metabolic process of the adipose tissue. Together, our results show a combination of an orthogonal method and an image-based analysis that constitutes a useful pipeline to be applied in 3D adipocyte culture.

Automation of single-cell proteomic sample preparation

Molecular heterogeneity exists at different spatial scales in biological samples and is an important parameter in the development of pathologies and resistances to therapies. When aiming to reach molecular heterogeneity of cells at extremely low spatial scales, single-cell analysis can be the ultimate choice. Proteomics performed in bulk population of cells (macroproteomics) is prone to mask molecular heterogeneity. Mass spectrometry-based single cell proteomics (SCP-MS) is the right solution to overcome this issue. Three main problems can be identified using SCP-MS: (i) analytical loss during sample preparation, (ii) inefficient microinjection/delivery of proteins/peptides from samples to MS and (iii) low analytical throughput. Technologies for automation of SCP have recently gained attention to improve methods accuracy, sensitivity, throughput and in-depth and low-biased proteome analysis. In this minireview, we therefore overview the state-of-the-art of automation of SCP-MS sample preparation approaches.