Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100–1,000 cells s−1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.


Statistics
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For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g.Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection We used ShapeIn (ShapeIn2; commercially available from Zellmechanik Dresden GmbH) for the acquisition of the RT-FDC data.

Data analysis
Python 3.7 was used.The Python library dclab is open-source and available on github (https://github.com/ZELLMECHANIK-DRESDEN/dclab);package version 0.32.3 was used for data analysis.We performed statistical analyses with the SciPy 1.3.0package.Additional data analysis was performed with Scikit learn 0.23.2 package (https://scikit-learn.org/stable/).The Python code for the processing and visualisation of RT-FDC data is available at https://github.com/marketakub/physical_phenotyping_tissues.
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Population characteristics
Surgically resected human biopsy samples from male and female patients of age range 57-88 were obtained from the Pathology Institute, Erlangen.All samples used were obtained from leftover biopsy samples.Therefore, this work did not interfere with standard practices of care or with sample-collection procedures.We provide the main population characteristics, including age, gender, diagnosis, localization of biopsy, histology, pT and pN stage, tumour grade, resection status, and the characteristics of the stroma and invasion state, in the Supplementary Information.

Recruitment
No active recruitment was needed.We used leftover biopsy samples that were obtained (subject to availability) from the Pathology Institute, Erlangen, following patient surgery.The biopsy samples were not collected specifically for this research study but were part of the standard practices of patient care.Informed consent was obtained from the patients providing samples.The participants were not compensated.All experiments were carried out in accordance with the declaration of Helsinki.

Ethics oversight
The study is covered by ethic votes of the University Hospital of the Friedrich-Alexander University Erlangen-Nurnberg (24.01.2005, 18.01.2012).The Institutional Review Board of the University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg approved the study (ID: Re.-No.4607).
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Field-specific reporting
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Life sciences study design
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Sample size
No statistical method was used to predetermine sample sizes.The sample sizes used in the study are in accordance with past experience and with standard sizes used in real-time deformability-cytometry measurements, which are of the order of several hundreds of cells per measurement per condition.The number of mice used in the animal studies were estimated according to the Resource Equation method [Charan et al. (2013), J Pharmacol Pharmacother].For human biopsies, sample sizes were determined by the number of patient samples available.
Data exclusions For the analysis of real-time deformability-cytometry data, we excluded debris by filtering out events smaller than 20 μm^2 in cross-sectional area, a procedure commonly used in real-time deformability cytometry.An additional area-ratio filter of 1.0-1.1 was used to ensure that only events with correctly fitted contours are used in the data analysis, as previously established by ZellMechanik Dresden GMBH, Dresden, Germany.

nature portfolio | reporting summary
March 2021

Blinding
For blind data analysis, samples were numerically tagged.The investigator running the analysis was unaware of which sample corresponded to tumour or healthy tissue.Only the investigators acquiring the data were aware of the status of the biopsy.Owing to the appearance of the biopsy samples, it was in some cases clear to the investigator performing the experiments which sample corresponded to tumour or healthy tissue.It was therefore impossible to perform blind data acquisition.

Reporting for specific materials, systems and methods
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Wild animals
The study did not involve wild animals.

Reporting on sex
Male (N=3) and female (N=4) animals were used for the comparison of enzymatic dissociation and tissue grinding.For each tissue extracted, half were used for enzymatic dissociation and half for tissue grinding.
Only female animals were used for the transfer colitis experiments (N=14), as described in the original publication (DOI: 10.1093/intimm/5.11.1461) If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research, and Sex and Gender in Research Laboratory animalsFor the comparison of enzymatic and tissue grinding: C57BL/6J females and males, age 8-19 weeks; For the transfer colitis model: Mus musculus, Rag1-/-, female, 8-12 weeks at the start of the experiment.For the tumour model: Mus musculus, female and male mice, 30-40 weeks.Animals were housed in 12-hour light-dark cycle, at 20-23°C and 40-60 % humidity.