Abstract: Cytometry Part AVolume 95, Issue 6 p. 655-656 EditorialFree Access Apoptosis and autophagy Jessica P. Houston, Corresponding Author Jessica P. Houston [email protected] orcid.org/0000-0001-8201-6396 Chemical and Materials Engineering, New Mexico State University, Las Cruces, New Mexico Correspondence to: Jessica P. Houston, Chemical and Materials Engineering, New Mexico State University, Las Cruces, NM 88003. Email: [email protected]Search for more papers by this author Jessica P. Houston, Corresponding Author Jessica P. Houston [email protected] orcid.org/0000-0001-8201-6396 Chemical and Materials Engineering, New Mexico State University, Las Cruces, New Mexico Correspondence to: Jessica P. Houston, Chemical and Materials Engineering, New Mexico State University, Las Cruces, NM 88003. Email: [email protected]Search for more papers by this author First published: 17 June 2019 https://doi.org/10.1002/cyto.a.23837Citations: 5AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL In the March issue of this year, a collection of articles on cancer and cytometry 1-3 were published together and highlighted by Editor in Chief, Prof. Attila Tárnok. Our particular focus on those published articles made obvious the fact that flow cytometry continues to play an essential role in the fundamental understanding of cancer progression. The publications had foci that ranged from studies of cancer at a fundamental level to use of mass and imaging cytometry for clinical/therapeutic outcomes. Yet beyond that single issue and our journal as a whole, there exists a massive assemblage of published work (see Fig. 1) that chronicle the salient partnership between cancer and cytometry. Therefore, it is unsurprising that several more articles on the subject of cancer can again be found in the current issue of Cytometry Part A. Hence, we found it not only appropriate to compile a special section related to cancer this month, but also consequential, because of the particular commonality in the research presented. That is, each paper included in our special section demonstrates a new approach for understanding and/or detecting intracellular mechanisms that malfunction during cancer progression—of course, when revealed by flow cytometry. Figure 1Open in figure viewerPowerPoint Results from a PubMed search when querying: "cytometry and cancer" across different decades We draw your attention to a group of four original articles on apoptosis and autophagy. These regulatory processes are often studied in cancer cells because they require staged intracellular mechanisms, which if fully understood can be exploited as therapeutic targets. Cytometry as a multiparametric tool has been employed for decades to study these mechanisms (see a few recent publications on these subjects in References 4-8), and the publications we highlight herein exemplify modern approaches toward that end. Four papers in this issue focus on evaluating differences in cells that are either treated with compounds to initiate apoptosis, autophagy, or that circulate in vivo after intravenous injection into anesthetized mice. In the latter case, two articles are featured in which cell counting instruments are designed to detect fluorescence from cells (apoptotic and nonapoptotic) in vivo, as they move through the blood stream after injection. Many of these reports present multiparametric measurements from either in vivo events or from treated cell suspensions, and in doing so demonstrate unique advances to how cytometry can be exploited for diagnosis of cancer or identification of functional traits that occur at the onset of regulated cell death. The paper by Halicka and colleagues (this issue, pp. 683) discusses how multiparametric cytometry (side scatter and fluorescence) is used on apoptosis-induced cells to quantify function of transglutaminase 2 (TG2) and the activation of lysosomal proton pumps as a result of cell treatment by a variety of compounds known to induce DNA damage or cytotoxic outcomes. When detecting the lack of accumulation of acridine orange in compromised lysosomes and protein crosslinking activity of TG2 via scattered light signals, both phenomena can be measured simultaneously with cytometry. This led to the ability to find that the rupture of lysosomes during apoptosis and subsequent release of calcium or proton ions, trigger the activation of TG2 and the crosslinking of cytoplasmic proteins. These experiments are promising in that they show how features of apoptosis can be evaluated during screening of a variety of compounds that affect DNA and initiate apoptosis. We find the paper by Popat (this issue, pp. 672) just as compelling because, again, cells were treated with cytotoxic drugs to be able to map out the various events that occur with a special focus on endoplasmic reticulum (ER) stress. ER stress was evaluated when apoptosis was inhibited and autophagy was induced or not, prior to cell death. These types of experiments demonstrate how cytometry protocols can be used for the early measurements of ER stress to indicate the type of cell death that the cell may or may not follow. The first two papers are by Hu et al. (this issue, pp. 657), and Nolan and colleagues (this issue, pp. 664), and their focus is to improve instruments that can detect "circulating tumor cells" (CTCs). CTCs have been a focus in cytometry for several years and although they are defined differently depending on the clinical case, we continue to see contributions that describe efforts toward CTC measurements in vivo 9, 10. In fact, we recently published an entire issue focused on CTC detection (volume 93, issue 12). Both publications in this issue present data that show signals representing cells detected from within the body of small animals, who have been injected with fluorescently labeled human cancer cells. The cytometric-like instruments are optimized to detect signals noninvasively when the cells pass through a blood vessel in the mouse ear. Hu and colleagues present a confocal imaging approach to detect cells by focusing onto the ear, which is not only useful because of the increased resolution but also because of the potential to capture images of the moving cells. Nolan and colleagues also focus on the mouse ear vessel yet use photodetectors to capture signals, or "peaks" that indicate the passage of fluorescently labeled cells. They have taken this approach further by detecting more than one fluorescent color and by inducing apoptosis with the goal of detecting this with the in vivo cytometry system. It is quite evident when reviewing these publications that flow cytometry continues to be important for evaluating cell-to-cell differences during apoptosis or autophagy. When we find how intracellular organelles (e.g., lysosomes, ER) undergo changes during apoptosis or autophagy, then we can target such mechanisms and ultimately identify drugs that regulate cell death. Literature Cited 1Adams HC III, Stevenaert F, Krejcik J, Van der Borght K, Smets T, Bald J, Abraham Y, Ceulemans H, Chiu C, Vanhoof G, et al. High-parameter mass cytometry evaluation of relapsed/refractory multiple myeloma patients treated with daratumumab demonstrates immune modulation as a novel mechanism of action. Cytometry A 2019; 95(3): 279– 289. 2Chumakova AP, Hitomi M, Sulman EP, Lathia JD. High-throughput automated single-cell imaging analysis reveals dynamics of glioblastoma stem cell population during state transition. Cytometry A 2019; 95(3): 290– 301. 3Wei H, Xie L, Liu Q, Shao C, Wang X, Su X. Automatic classification of label-free cells from small cell lung cancer and poorly differentiated lung adenocarcinoma with 2D light scattering static cytometry and machine learning. Cytometry A 2019; 95(3): 302– 308. 4Rajan R, Karbowniczek M, Pugsley HR, Sabnani MK, Astrinidis A, La-Beck NM. Quantifying autophagosomes and autolysosomes in cells using imaging flow cytometry. Cytometry A 2015; 87(5): 451– 458. 5Juan G. Could the key be hidden in the lysosomes? Cytometry A 2019; 95(5). 6Alturkistany F, Nichani K, Houston KD, Houston JP. Fluorescence lifetime shifts of NAD(P)H during apoptosis measured by time-resolved flow cytometry. Cytometry A 2019; 95(1): 70– 79. 7Kessel S, Cribbes S, Bonasu S, Rice W, Qiu J, Chan LL-Y. Real-time viability and apoptosis kinetic detection method of 3D multicellular tumor spheroids using the Celigo image cytometer. Cytometry A 2017; 91(9): 883– 892. 8Mariotti S, Pardini M, Teloni R, Gagliardi MC, Fraziano M, Nisini R. A method permissive to fixation and permeabilization for the multiparametric analysis of apoptotic and necrotic cell phenotype by flow cytometry. Cytometry A 2017; 91(11): 1115– 1124. 9Sollier-Christen E, Renier C, Kaplan T, Kfir E, Crouse SC. VTX-1 liquid biopsy system for fully-automated and label-free isolation of circulating tumor cells with automated enumeration by BioView platform. Cytometry A 2018; 93(12): 1240– 1245. 10Fehm TN, Meier-Stiegen F, Driemel C, Jäger B, Reinhardt F, Naskou J, Franken A, Neubauer H, Neves RPL, van Dalum G, et al. Diagnostic leukapheresis for CTC analysis in breast cancer patients: CTC frequency, clinical experiences and recommendations for standardized reporting. Cytometry A 2018; 93(12): 1213– 1219. Citing Literature Volume95, Issue6June 2019Pages 655-656 FiguresReferencesRelatedInformation