Rekord i forskningsrapporter

Idag publicerades ytterligare forskningsrapporter,nämligen bestämt 2 st.Med dessa 2 kan vi på 1 månad (33 dagar) räkna in 9 studier som offentliggjorts,samtliga såklart baserade på PHI`s excellenta HoloMonitor.
Detta är ett rekord och borde uppmärksammas på fler ställen än här på bloggen.
Med detta tempo på 1 forskningsrapport nästan var 3e dag (9/33) kan man ju inte annat säga än att vi nu ser den beryktade ketchupeffekten.Frågan är om även branschens större aktörer,dvs bjässarna,noterar detta formliga crescendo i HoloMonitorbaserade studier.Nån slags reaktion tror jag vi kan förvänta oss.Men när och i vilken form återstår att se.Vi är de facto inne i semestertider vilket kan påverka.Men när den perioden är över..då ....
Men till dagens skörd av forskningsrapporter.
Först har vi en studie där PHI`s Svenska ambassadör Professor Stina Oredsson medverkar.
Förutom Stina ser vi idel kända namn som Sofia Kamlund, Birgit Janicke och Kersti Alm.
Denna studie kan vara en förlaga till det som komma skall : Kombon Holo/Fluo-instrumentet.
Det eftersom forskarna medvetet samkört bägge teknikerna.
Som de skriver i inledningen : The aim of the present study is to use longitudinal tracking of cells in images acquired using digital holographic microscopy in a unique combination with fluorescence microscopy to identify the expression of CD24 and E-cadherin on the tracked cells.
 

Salinomycin Treatment Specifically Inhibits Cell Proliferation of Cancer Stem Cells Revealed by Longitudinal Single Cell Tracking in Combination with Fluorescence Microscopy

Published: 9 July 2020 

Abstract

A cell line derived from a tumor is a heterogeneous mixture of phenotypically different cells. Such cancer cell lines are used extensively in the search for new anticancer drugs and for investigating their mechanisms of action. Most studies today are population-based, implying that small subpopulations of cells, reacting differently to the potential drug go undetected. This is a problem specifically related to the most aggressive single cancer cells in a tumor as they appear to be insensitive to the drugs used today. These cells are not detected in population-based studies when developing new anticancer drugs. Thus, to get a deeper understanding of how all individual cancer cells react to chemotherapeutic drugs, longitudinal tracking of individual cells is needed. Here we have used digital holography for long time imaging and longitudinal tracking of individual JIMT-1 breast cancer cells. To gain further knowledge about the tracked cells, we combined digital holography with fluorescence microscopy. We grouped the JIMT-1 cells into different subpopulations based on expression of CD24 and E-cadherin and analyzed cell proliferation and cell migration for 72 h. We investigated how the cancer stem cell (CSC) targeting drug salinomycin affected the different subpopulations. By uniquely combining digital holography with fluorescence microscopy we show that salinomycin specifically targeted the CD24⁻ subpopulation, i.e., the CSCs, by inhibiting cell proliferation, which was evident already after 24 h of drug treatment. We further found that after salinomycin treatment, the surviving cells were more epithelial-like due to the selection of the CD24⁺ cells.

Keywords: digital holographic microscopy; fluorescence microscopy; single cell tracking; cancer stem cells; salinomycin; JIMT-1 breast cancer cells

1. Introduction

The importance of cancer stem cells (CSCs) in the development and recurrence of cancer has gained increased attention in cancer research during the last decade. A tumor contains a mixture of phenotypically heterogeneous cancer cells. Only a few cells in a tumor belong to the CSC population, but it appears that for many tumors of different origin it is mainly the CSCs that can give rise to new tumors with similar phenotypic composition as the original tumor. Since the CSCs are drug resistant and favor cancer metastasis there is an increased need for new drugs and therapeutic strategies that reduce the CSCs specifically. In breast cancer, a high expression of the cell surface marker CD44 in combination with a low expression of the cell surface marker CD24 have been used to identify CSCs.

The cationic ionophore salinomycin was found to target CSCs, in a high throughput screening study aimed to find drugs that target this subpopulation in breast cancer. Subsequently, salinomycin has been found to target CSCs in many other human cancer types including leukemia, gastric cancer , colorectal cancer , osteosarcoma , pancreatic cancer , prostate cancer , head and neck squamous cell carcinoma, and lung cancer . Many different mechanisms of action have been ascribed to salinomycin, such as disruption of actin stress fibers , downregulation of mRNAs and proteins related to stemness , impaired mitochondrial function, induction of autophagy, decreased ATP levels and increased reactive oxygen species production, sequestration of iron in lysosomes , and induction of reactive oxygen species , with outcomes like decreased cell viability, proliferation, and migration, as well as stimulation of mesenchymal-to-epithelial-transition . Salinomycin has also been shown to increase the expression of E-cadherin , a calcium-dependent cell adhesion glycoprotein molecule found on the surface of epithelial cells . The expression level of E-cadherin was inversely correlated with the tumorigenicity of different cell lines, where a high expression of E-cadherin correlated to low tumorigenicity and vice versa . However, for clinical outcomes the role and correlation of E-cadherin is unclear  and the level of expression has been found to vary between tumors of different classification .

We have previously found evidence for the molecular initiating event that explains most down-stream effects observed after salinomycin treatment . Salinomycin was shown to almost immediately after addition to the cell culture medium localize to the endoplasmic reticulum (ER) of breast cancer cells, leading to increased cytosolic Ca²⁺ levels followed by ER stress. This effect was down-stream linked to inhibition of the Wnt signaling pathway, which has previously been reported as an effect of salinomycin treatment. These findings are deduced from population-based studies, but to increase our understanding of CSCs as well as how they can be targeted, more studies of single cell sensitivity are required.

Digital holography is a quantitative phase imaging technique, which can be used to generate large amounts of information about individual cells based on the phase shift of light. The method is label free, thus eliminating possible chemical toxicity, and no phototoxicity has been found. Therefore, the technique allows for long time imaging and when images are acquired with high time resolution they can be used for longitudinal tracking of individual cells, which is a powerful tool to investigate how individual cells in a population react to treatment over time. It can also be used to detect and over time trace subpopulations that react differently than the bulk of cells to drugs, e.g., that are drug insensitive and may therefore be the cause of metastasis. Using digital holography, we have previously shown that JIMT-1 breast cancer cells contain a subpopulation of cells with a decreased response to salinomycin compared to the other subpopulations , an effect that was hidden among the total population data.

Much work is ongoing trying to find holography-derived parameters, such as morphological for cell behavior features, or combinations thereof that can be used to characterize subpopulations among the bulk of cells . It has been shown that a number of empirically-derived parameters obtained by digital holographic microscopy, actually can be applied to computational machine learning to identify effects of drug treatment on individual cells . However, still more work is needed to elucidate if digital holography alone can be used to truly identify different cell populations and subpopulations.

The aim of the present study is to use longitudinal tracking of cells in images acquired using digital holographic microscopy in a unique combination with fluorescence microscopy to identify the expression of CD24 and E-cadherin on the tracked cells. This was used to investigate differences in cell cycle length and migratory behavior between subpopulations of JIMT-1 cells, as well as the effect of salinomycin on those parameters in the different subpopulations. We have used the JIMT-1 breast cancer cell line in studies of the effect of different compounds including salinomycin and salinomycin analogues on CSCs as well in studies using digital holographic microscopy . 

The cell line contains a high proportion of CSCs that are sensitive to different treatments. Here we deepen our insight into dynamics of how the salinomycin treatment decreases the CSC subpopulation of JIMT-1 cells. Altogether the data show that the main difference between subpopulations of JIMT-1 cells is related to cell proliferation and that the initial effect of salinomycin treatment was a decrease in the proliferation of CD24⁻ cells.

2. Materials and Methods (urval)

2.4. Digital Holographic Time-Lapse Imaging in Combination with Fluorescence and Tracking

For digital holographic microscopy (DHM), the HoloMonitor^® M4 (Phase Holographic Imaging AB (PHI), Lund, Sweden), with a motorized stage was used for time-lapse imaging. Images were acquired using the software Hstudio™ (PHI). To increase image quality, the standard lid of the Petri dish was replaced with HoloLid™ 71 110 (PHI) prior to the start of imaging.

The imaging was done using two different time setups. First, the method for combining digital holographic microscopy with fluorescence was evaluated using 24 h-time-lapses as illustrated in the upper part of Figure 1A. Cells were seeded in a number of Petri dishes, of which some were used in time-lapse imaging 24–48 h after seeding (i.e., time-lapse/treatment time 0–24 h) and some in time-lapse imaging 48–72 h after seeding (i.e., time-lapse/treatment time 24–48 h). Thus, a 48-h time-span was divided into two consecutive 24-h time-lapses where parallel samples were imaged for the different time-spans. For the other set-up, samples were imaged uninterrupted for 48 h, i.e., from 24–72 h after seeding (i.e., time-lapse/treatment time 0–48), as illustrated in the lower part of Figure 1A.

Supplementary Materials

Figure S1. Representative images from DHM time-lapses and fluorescence. (A) Images from timepoint 0, 24 and 48 h of a representative DHM time-lapse of JIMT-1 cells in the absence (control) or presence of 0.5 µM salinomycin. The salinomycin was added immediately before the start of the timelapse. The scale bar on top represents 300 µm for control and 400 µm in salinomysin-treated samples, and the scalebar to the left represents the optical thickness 0-46 µm in control and 0-48 µm in salinomycin-treated samples. (B) Fluorescence images of samples fixed after DHM imaging. The cells were labelled with anti-CD24-PE and anti-CD44-FITC or anti-CD24-PE and anti-E-cadherin-Alexa Flour 488 after 24 or 48 h of treatment.

4. Discussion

Most of our current knowledge of how cells react to different kinds of perturbations is based on analysis of the response of an entire cell population. Individual cells may be analyzed e.g., by using flow cytometry as an end response assay, which may display heterogeneity of the studied entity. However, a challenge in biology is to understand the kinetics in the processes of each individual cell that causes the heterogeneity in the end response. Microscopic techniques like confocal microscopy, immunofluorescence microscopy, phase contrast microscopy, and DHM are today used to follow the behavior of live individual cells through time-lapse imaging. All methods have their advantages and disadvantages. Here we have used DHM because of the advantage of low photo toxicity and because it is label-free. The disadvantage of label free microscopy is that there are questions around cell identification. Here we address such questions by analyzing different subpopulations of JIMT-1 breast cancer cells identified by combining DHM with fluorescence microscopy.

5. Conclusions

In conclusion, the combination of DHM and fluorescence microscopy is powerful. 

It allowed us to show for the first time that the decrease in the CD24⁻ CSC subpopulation already after 24 h of salinomycin treatment is caused by specific inhibition of proliferation of the CD24⁻ population while the CD24⁺ population is not affected. This implies that the phenotypic shift towards less stemness caused by salinomycin treatment is due to positive selection of the CD24⁺ cells.

Min kommentar

Överlåter jag till granskaren av denna studie.

"The manuscript by Kamlund et al is interesting, as it shows an original perspective allowing to see how individual cells in a population can be affected by a drug. Something, that would be difficult to observe with classical methods looking at averages in bulk populations."

Värt att ytterligare notera är vilka som finansierat denna studie.
"This work was supported by funding from the Swedish Research Council (VR), Forska Utan Djurförsök, by a donation from Carolina LePrince with the “Kalenderflickorna” and associated sponsors, and by donations to Stina Oredsson’s research group at Lund University (http://biology.lu.se/cancer-stem-cells)."

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Studie nr 2 som offentliggjorts idag ser ut att vara en fortsättning på Robert L. Judsons arbete med att konstruera ett "verktyg" i att känna igen karakteristika för olika typer av cancer. Robert medverkar så jag kan ha rätt i det antagandet,men som vanligt : jag är bara 99% säker:-D

Men till studien benämnd 

Quantifying the Rate, Degree, and Heterogeneity of Morphological Change during an Epithelial to Mesenchymal Transition Using Digital Holographic Cytometry

 Published: 9 July 2020

Abstract

Cells in complex organisms can transition between epithelial and mesenchymal phenotypes during both normal and malignant physiological events. These two phenotypes are not binary, but rather describe a spectrum of cell states along an axis. Mammalian cells can undergo dynamic and heterogenous bidirectional interconversions along the epithelial–mesenchymal phenotypic (EMP) spectrum, and such transitions are marked by morphological change. Here, we exploit digital holographic cytometry (DHC) to develop a tractable method for monitoring the degree, kinetics, and heterogeneity of epithelial and mesenchymal phenotypes in adherent mammalian cell populations. First, we demonstrate that the epithelial and mesenchymal states of the same cell line present distinct DHC-derived morphological features. Second, we identify quantitative changes in these features that occur hours after induction of the epithelial to mesenchymal transition (EMT). We apply this approach to achieve label-free tracking of the degree and the rate of EMP transitions. We conclude that DHC is an efficient method to investigate morphological changes during transitions between epithelial and mesenchymal states. 

Keywords: digital holographic cytometry; quantitative phase imaging; epithelial to mesenchymal transition

1. Introduction

During tumour progression, cancer cells interconvert between epithelial and mesenchymal states with a high degree of plasticity based upon environmental signals. These bidirectional transitions are known as epithelial to mesenchymal transitions (EMT) and mesenchymal to epithelial transitions (MET). Both transitions are required for the complex series of processes that result in metastatic dissemination. For example, EMT is involved in both tumour cell migration and the transformation of cancer cells into a cancer stem cell (CSC) phenotype, each of which promotes growth of new tumours at distant locations. However, the repression of EMT and induction of MET is also essential for metastatic colonization.  

Since metastases cause most cancer-related deaths  it is of vital importance to understand the EMT/MET processes. Efforts to identify candidate therapeutics that interfere with the process are underway. However, dependent on the stage and identity of each cancer cell within a tumour or a patient, inhibition of either EMT or MET could be beneficial or harmful. 

Given the complexity of the transitions and their relationship to metastatic dissemination, more comprehensive characterization of the effect of candidate therapeutics on EMT and MET are needed.

Characterization of EMT and MET is challenging due to several types of substantial heterogeneity. First, the processes of EMT/MET do not describe a binary toggling between two discrete states, but rather transitions along an “epithelial-mesenchymal phenotypic (EMP) spectrum” from more epithelial-like states to more mesenchymal-like states. Second, cells are heterogenous in the ease with which they can transverse this spectrum, often referred to as plasticity. Each cell line and individual cells within a cell line population can occupy distinct locations along the EMP spectrum and possess varying degrees of plasticity dependent on contextual signals. Third, the intracellular gene circuits and morphological changes that define the EMP spectrum differ from cell line to cell line. Finally, the EMP spectrum is only one of many transcriptional programs that define a cell. Some cancers, such as melanoma, are not derived from epithelial cells but, nevertheless, undergo an “EMT-like” transition during metastasis. Thus, simply defining the EMP spectrum for any specific cellular context is non-trivial and it cannot be assumed that parameters that accurately define EMP in one cell line apply to another.

To further develop the candidate therapeutics for clinical application, it is first essential to develop assays capable of capturing and quantifying the degree, kinetics, heterogeneity and cell-line specificities of transitions along the EMP axis. Defined changes in morphology, specifically the acquisition of a spindle-like shape, constitute one hallmark of EMT that could serve as an informative feature. EMT has been monitored in real time by fluorescence imaging of vimentin by Maier et al. Both EMT and MET have been monitored by time-lapse imaging giving insights into the ongoing process. Digital holographic cytometry (DHC) has emerged as a complementary technique to obtain time-lapsed imaging for label free long-term cell analysis. The quantitative 3D images acquired can be used to follow morphological changes or changes in cell movement induced by therapeutic treatment. It has also been presented as a technique suitable for classifying distinct cell phenotypes . We have previously suggested that DHC can be used as a tool for identifying and monitoring EMT or MET  by characterizing the change in cell movements. Recently, it has been suggested that the application of machine learning techniques to DHC-derived features can detect epithelial and mesenchymal characteristics in cell lines of unknown EMP status. However, due to substantial morphological heterogeneity between cell lines, cell types, and species, it is not obvious whether a single model that classifies EMP status based solely on DHC-derived morphological features can be universally applied.

In this study, we evaluated the use of DHC to track the rate, degree, and heterogeneity of transitions within the EMP spectrum based on morphological features. Importantly, we aimed to create an accessible approach for assessing EMP status that could be easily adjusted for different cell systems and was not at risk of over-training as introduced by machine learning approaches. First, we monitored mouse mammary epithelial cells undergoing EMT. Next, we trained a model to classify the degree of EMT using DHC-derived features and applied our model to live-imaged cultures undergoing EMT. Finally, we applied the model to five human and mouse cell lines of known EMP state and observed substantial line-to-line variability. Our data show that DHC-derived morphological parameters can be used to monitor the degree, rate, and heterogeneity of EMP transitions, while highlighting the necessity for developing cell-line specific classifiers.

2. Materials and Methods (urval)

2.3. Digital Holographic Imaging and Analysis

The cells were allowed to attach for 24 h prior to start of the experiment. For NMuMG cells, compounds were added as described above immediately before imaging. The standard lid of the Petri dish was replaced with a HoloLid™ 71,110 for Petri dishes with 35 mm diameter (Phase Holographic Imaging AB (PHI), Lund, Sweden) or HoloLid™ 71,120 for 6-well plates (PHI). The cells were then imaged using the HoloMonitor^® M4 with a motorized stage (PHI). 

The HoloMonitor^® M4 is a quantitative imaging system based on digital holographic microscopy. For imaging, the software Hstudio™ (PHI) was used. Images were acquired at three to five locations (image frames) per well, at time-intervals ranging from every hour to every 24 h, for a total time of 48–72 h.

The images were analyzed using Hstudio™ as follows. First, each image was segmented using thresholding that identified each individual cell in that image. Second, based upon this segmentation, morphological parameters for each cell in each image frame were computationally calculated. 

In the Hstudio™ analysis tool, values for the 27 morphological parameters considered here are presented for each individual cell. To develop the EMP score, we used the average values for each image frame at each timepoint. Data were analyzed for correlations using the free software R (R Core Team, 2015). To generate the score, we first selected four features that positively correlated with mesenchymal conditions in the dataset obtained from a 72-hour time-lapse imaging of NMuMG cells with and without exposure to 0.5 ng/mL TGFβ: average cell eccentricity, average cell hull convexity, average cell roughness skewness, and average cell optical thickness max. We centered each feature set by dividing each value within that set by the mean feature value in control conditions. We then performed standard min max feature scaling (Equation (1)) to restrict all values to the range 0–1 that were then summed to generate a score in the range 0–4 with increasing values correlating with a more mesenchymal phenotype. 

5. Conclusions

We conclude that DHC can be applied to the study of EMP transitions. Specifically, consideration of DHC-derived morphological features permits efficient monitoring of the rate, degree, and heterogeneity of the transition in a label-free manner. We further provide evidence that the morphological changes associated with EMP status are not universal across lines, emphasizing the need to optimize and validate DHC-derived classifiers for each cell system. 

Min kommentar

Stämmer mitt antagande (99% säker) att studien är en utveckling av Roberts tidigare arbete med att "katalogisera" kännetecken på olika typer av cancrar med tekniken HoloMonitor medger är detta en veritabel infobomb.Det under förutsättning att forskarvärlden tar till sig studien och ger det sin acceptans.Konkret skulle det i så fall innebära 2 saker. Det första är att forskare får ett verktyg i att snabbt identifiera vilken cancertyp det handlar om när de startar sina cellstudier.De hoppar alltså över en massa steg i att behöva identifiera och kan istället gå direkt till "andra halvan" i studierna.

För det andra är det oerhört betydelsefullt för forskare som bedriver studier kring läkemedel som är verkningsfulla mot specifik typ av cancer. Med verktyget behöver de inte köra uteslutningsmetoden för att till slut hitta vilken cancer det handlar om,och sen fortsätta forska vilka substanser som är effektiva som bot.Med ett verktyg som ger möjligheten att utgå direkt från cancertyp sparas tid och resurser.Det borde attrahera de större läkemedelstillverkarna (med egna forskningsavdelningar) skulle jag tippa.

Summasummarum.

Dessa 2 forskningsrapporter är nånting utöver det vanliga.

Skulle jag ha 100% rätt i mina antaganden bör de var för sig ha stor betydelse för PHI.

Kombon holo-fluo kommer när den är färdigutvecklad av NIH redan ha fakta ute som bekräftar dess unika funktionalitet vilket borde rendera i förhandsbokningar i den bästa av världar.

Ett verktyg som definierar cancertyp vid forskningsstadiets början kommer mottas med stor tacksamhet,även det i den bästa av världar.

Att verktyget är framtaget med HoloMonitor bör innebära att det fungerar bäst i vidare forskning med just HoloMonitor.

Som extra grädde på moset kommer dessa 2 studier finnas med i den specialutgåva jag berättade om igår.
Gissa om den kommer läsas av världens forskare! Späckad med helt nya fakta som kommer vara högst användbara för framförallt cancerforskare,men troligtvis även andra.

Min spontana tanke med detta sanslösa flöde av forskningsrapporter och en specialutgåva i vardande är att PHI har ett finger med i detta och med det en klar strategi för det som utvecklar sig vid samtalen med sina friare.
Man har väntat in denna "ammunition" och kommer använda den vid de fortsatta förhandlingarna.
Spekulation från bloggens sida? Absolut,och till 100%.Men som pusselgillare är senaste tidens händelser för bra pusselbitar i det stora pusslet för att ignoreras.

                                                 Mvh (en superexcited) the99