Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts

Mandal, Subhrangsu S.; Tejaswi, Tanishq; Janivara, Rohini; Srikrishnan, Syamanthak; Thakur, Pradipti; Sahoo, Sarthak; Chakraborty, Priyanka; Sohal, Sukhwinder Singh; Levine, Herbert; George, Jason T.; Jolly, Mohit Kumar

doi:10.3390/biom12010029

Cited by 11 publications

(11 citation statements)

References 105 publications

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“…Improvements in patient stratification and therapeutic approaches for lung fibrosis will be contingent on the capacity to reprogram EMT ( 38 ). EMT has been hypothesized as a source of myofibroblast also in SSc ( 39 ) and EMT-related pathways ( 40 ).…”

Section: Discussionmentioning

confidence: 99%

Single cell meta-analysis of EndMT and EMT state in COVID-19

et al. 2022

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COVID-19 prognoses suggests that a proportion of patients develop fibrosis, but there is no evidence to indicate whether patients have progression of mesenchymal transition (MT) in the lungs. The role of MT during the COVID-19 pandemic remains poorly understood. Using single-cell RNA sequencing, we profiled the transcriptomes of cells from the lungs of healthy individuals (n = 45), COVID-19 patients (n = 58), and idiopathic pulmonary fibrosis (IPF) patients (n = 64) human lungs to map the entire MT change. This analysis enabled us to map all high-resolution matrix-producing cells and identify distinct subpopulations of endothelial cells (ECs) and epithelial cells as the primary cellular sources of MT clusters during COVID-19. For the first time, we have identied early and late subgroups of endothelial mesenchymal transition (EndMT) and epithelial-mesenchymal transition (EMT) using analysis of public databases for single-cell sequencing. We assessed epithelial subgroups by age, smoking status, and gender, and the data suggest that the proportional changes in EMT in COVID-19 are statistically significant. Further enumeration of early and late EMT suggests a correlation between invasive genes and COVID-19. Finally, EndMT is upregulated in COVID-19 patients and enriched for more inflammatory cytokines. Further, by classifying EndMT as early or late stages, we found that early EndMT was positively correlated with entry factors but this was not true for late EndMT. Exploring the MT state of may help to mitigate the fibrosis impact of SARS-CoV-2 infection.

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Section: Discussionmentioning

confidence: 99%

Single cell meta-analysis of EndMT and EMT state in COVID-19

et al. 2022

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“…Two of those metrics are KS (Tan et al 2014) and 76GS (Byers et al 2013) scores. Both these metrics use distinct sets of gene lists corresponding to epithelial and mesenchymal phenotypes and generate a score to identify the position of samples along the epithelial-hybrid-mesenchymal spectrum (Chakraborty et al 2020; Mandal et al 2022). EMT is a non-linear process where cells can take multiple trajectories in the high-dimensional gene expression space, and the loss of epithelial and gain of mesenchymal traits need not always be completed coupled, as is often tacitly assumed (Watanabe et al 2019).…”

Section: Resultsmentioning

confidence: 99%

“…Epithelial-mesenchymal transition (EMT) scores were generated using KS and 76GS scores (Chakraborty et al 2020; Mandal et al 2022), and single-sample Gene Set Enrichment Analysis (ssGSEA). PD-L1 activity scores were also obtained using ssGSEA.…”

Section: Methodsmentioning

confidence: 99%

Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

Sehgal¹,

Ray²,

Vaz

et al. 2022

Preprint

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Oncoviruses exploit diverse host mechanisms to survive and proliferate. These adaptive strategies overlap with mechanisms employed by malignant cells during their adaptation to dynamic micro-environments and for evasion of immune attack. While the role of individual oncoviruses in mediating cancer progression has been extensively characterized, little is known about the common gene regulatory features of oncovirus-induced cancers. Here, we focus on defining the interplay between several cancer hallmarks, including Epithelial- Mesenchymal Transition (EMT), metabolic alterations, and immune evasion across major oncoviruses by examining publicly-available transcriptomics data sets containing both oncovirus-positive and oncovirus-negative samples. We observe that oncovirus-positive samples display varying degrees of EMT and metabolic reprogramming. While the progression of EMT generally associated with an enriched glycolytic metabolic program and suppressed fatty acid oxidation (FAO) and oxidative phosphorylation (OXPHOS), partial EMT correlated well with glycolysis. Furthermore, oncovirus-positive samples had higher activity and/or expression levels of immune checkpoint molecules, such as PD-L1, which was associated with a partial EMT program. These analyses thus decode common pathways in oncovirus-positive samples that may be used in pinpointing new therapeutic vulnerabilities for oncovirus-associated cancer cell plasticity.

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“…EMT scores of the transcriptomic profiles of samples from patients with breast cancer were calculated using previously developed methods, GS76, MLR and KS [16,25,26]. A well-defined set of gene signatures along with a classification algorithm forms the basis for EMT score calculation in these methods.…”

Section: Emt Score Calculationmentioning

confidence: 99%

In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

Parthasarathi

Mandal

Singh

et al. 2022

Cancers

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Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.

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Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts

Cited by 11 publications

References 105 publications

Single cell meta-analysis of EndMT and EMT state in COVID-19

Single cell meta-analysis of EndMT and EMT state in COVID-19

Partial EMT and associated changes in cellular plasticity in oncovirus-positive samples

In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

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