Table 4:

Single cell technologies used to study partial EMT in cancer progression.

Tumor type and samples	Method	Partial EMT (p-EMT) characterization	Major finding	References
Single cell RNA sequencing
Using single cell RNA sequencing (scRNA-seq) data to analyze bulk RNA sequencing (bulk RNA-seq) data.
Head and neck squamous cell carcinoma 18 treatment naive patients and 5 matched LN metastasis.	Expression programs identified from scRNA-seq data of patient tumors used to de-convolute bulk expression data.	p-EMT cells expressed EMT TF SNAIL2 but lacked other EMT TFs ZEB1/2, TWIST1/2 and SNAIL1, localized to leading edge of tumor and are highly metastatic.	Explores HNSCC heterogeneity with the identification of cell type specific expression programs and infers a strategy to extract information from bulk expression data.	Puram et al., 2017
HMLE breast cancer cell lines	scRNA-seq of cell lines used to generate breast cancer prognosis method, scPrognosis, validated in bulk breast cancer RNA sequencing data sets.	Most of the identified breast cancer signature genes peak at hybrid E/M stage.	Signature genes detected, link EMT with clinical outcomes of breast cancer.	Xiaomei et al., 2020
Single cell RNA sequencing on time course experiments
4 different cancer cell lines lung, prostate, breast and ovarian cancer	Multiplexed scRNA-seq (MULTI-seq) of 12 distinct EMT time-course experiments of cancer cells treated with different EMT inducers.	EMT transition was not a linear process but involved combinations of discrete transcriptional events indicating hybrid intermediate states.	Provides a thorough comparison of context dependent variabilities in the EMT program.	Cook et al., 2020
Single cell DNA methylation
Progressive breast cancer Matched single and clustered CTCs from 4 patients and 3 mouse-xenografts.	Combination of single-cell resolution DNA methylation and RNA expression analysis with a drug screen with 2,486 FDA-approved compounds.	Binding sites for stemness and proliferation associated transcription factors were hypomethylated compared to the single CTCs.	Demonstrate a connection between phenotypic features such as CTC clustering and DNA methylome landscape alterations.	Gkountela et al., 2019
Single cell mass cytometry
Non-small cell lung carcinoma (adenocarcinoma) 3 NSCLC adenocarcinoma cell lines and 5 fresh NSCLC adenocarcinoma patient samples.	Single cell mass cytometry time-course experiment on NSCLC cells undergoing EMT and MET was done to construct EMT-MET PHENOSTAMP for evaluating EMT and MET states of clinical samples.	Was able to identify heterogeneity within p-EMT states (co-expressed E-cadherin and Vimentin) p-EMT 1, 2, 3 with p-EMT 2 and 3 having a subgroup of Twist+ cells.	This integrated approach provides in vitro insights on EMT–MET biology and establishes a framework to translate in vitro observations to clinical samples.	Karacosta et al., 2019
High grade serous ovarian cancer Single cells from 17 newly diagnosed patient tumors.	Multiparametric single-cell mass cytometry, CyTOF.	Seven cell clusters co-expressed epithelial marker E-cadherin and mesenchymal marker Vimentin with protein deregulations in stem cell, cell cycle and metastasis.	CyTOF enabled detailed characterization of subtly differing cell populations.	Gonzalez et al., 2018

Abbreviations: LN = lymph node, sc-RNA-seq = single-cell RNA sequencing, p-EMT = partial epithelial-mesenchymal transition, EMT = epithelial-mesenchymal transition, TF = transcription factors, HNSCC = head and neck squamous cell carcinoma, HMLE = immortalized human mammary epithelial cells, CTC = circulating tumor cell, FDA = food and drug administration, NSCLC = non-small cell lung carcinoma, MET = mesenchymal to epithelial transition.