Schematic overview of the cellular and molecular mechanisms involved in the cancer progression, including the proposed cellular and molecular mechanisms in cancer cells trajectory. AT1: alveolar type 1 cells; AT2: alveolar type 2 cells; AAH: atypical adenomatous hyperplasia; AIS: adenocarcinoma in situ; MIA: minimally invasive adenocarcinoma; IA: invasive adenocarcinoma; EMT: epithelial-mesenchymal transition

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Tissue samples summary

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Annotation details for different cell compartments

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Cell type statistics by disease state

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Cell type dynamics in malignant transformation

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Cell lineage trajectory inference

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TF regulatory network analysis

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Cell-cell interaction analysis

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Stemness, Senescence, Metaplasia and NeoTCR signature analysis

Tissue: Lung

Tissue samples summary

check button Cell type statistics by tissue samples.
EpitheliaImmuneStromal
Bar plot representation of the fraction of all Epithelial cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.Bar plot representation of the fraction of all Immune cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.Bar plot representation of the fraction of all Stromal cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.
∗Bar plot representation of the fraction of all Epithelial, Immune and Stromal cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Lung tissue. Each row represents a single sample, with each color representing a different cell type present in the sample.

check button Tissue summary table.
TissueDisease StateReplicatesEpithelia UMAPPMIDSourcePlatform
LungIACLUNG_T18Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N30Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T34Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T31Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N34Projection

32385277

GSE203360

10X Genomics
LungIACEBUS_28Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N19Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N06Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N18Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T28Projection

32385277

GSE203360

10X Genomics
LungIACBRONCHO_58Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T19Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T20Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T30Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N09Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N28Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N08Projection

32385277

GSE203360

10X Genomics
LungADJLUNG_N31Projection

32385277

GSE203360

10X Genomics
LungIACLUNG_T09Projection

32385277

GSE203360

10X Genomics
LungIACEBUS_06Projection

32385277

GSE203360

10X Genomics
∗Projection of epithelial scRNA-seq cells from Lung diseased tissue samples into the manifold of normal tissue epithelial cells. Projected cells are colored by nearest normal cells in the projection and normal epithelial cells are colored gray.
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Annotation details for different cell compartments

check button Single-cell atlas of expresion.
UMAP representations and annotations of Epithelial cells in the integrated scRNA-seq data of the selected tissue.UMAP representations and annotations of Immune cells in the integrated scRNA-seq data of the selected tissue.UMAP representations and annotations of Stromal cells in the integrated scRNA-seq data of the selected tissue.
∗UMAP representations and annotations of Epithelial, Immune, Stromal cells in the integrated scRNA-seq data of Lung tissue. Colors represent cell types of each compartment.

check button Cell markers.
TissueMajor Cell TypeMinor Cell TypeFull NameMarkers
LungEpiSTMStem-like cellsLGR5,CD44,ABCG2,CD24,CD200,ITGA6,SOX2
LungEpiBASBasal cellsKRT5,TP63,KRT14
LungEpiAT1Alveolar type 1 cellsPDPN,AGER,HOPX
LungEpiAT2Alveolar type 2 cellsHHIP,SFTPC,ABCA3
LungEpiAT2LAT2-like cellsMDK,SFTPB,LPCAT1,PTGER3,MUC1,SOX9,KRT5
LungEpiCLUBClub cellsSCGB1A1,CP
LungEpiCILIACiliated cellsFOXJ1,CCDC78,DNAH5,TTC25
LungEpiABPAlveolar basal progenitorSOX2,SOX9
LungEpiGOBGobletMUC5AC,MUC5B
LungImmNEUTNeutriphilsCEACAM3,FCGR3B,CXCR2
LungImmMMCMucosal Mast CellsTPSB2,CMA1,MS4A2
LungImmMASTMast cellsTPSAB1,CPA3,HDC,CTSG,TPSB2,CMA1,MS4A2
LungImmcDCConventinal dendritic cellsHLA-DQA1,HLA-DQB1,CLEC10A,CLEC9A,FCER1A,CST3,CD1C
LungImmLCLangerhansCD1A,CD207,LAMP3
LungImmpDCPlasmacytoid dendritic cellsIL3RA,CLEC4C,NRP1,KLRD1
LungImmNKNatural killer cellsKLRF1,SH2D1B,NCAM1,FCGR3A,GNLY,NKG7,GZMH,FGFBP2,CX3CR1,NCR1,NCR3,B3GAT1
LungImmMDSCMyeloid-derived suppressor cellsITGAM,LY6G6C,IL4R,ARG1
LungImmM1MACM1 macrophagesFOLR2,FABP3,PLA2G2D,ITGAM,ITGAX,CSF1R,CD68,CD163,THBD
LungImmALVMACAlveolar macrophagesCD14,CD68,CD163,MARCO
LungImmINMONInflamotory monocytesCD14,CLEC9A,FCGR1A,LILRB2,CD209,CD1E,FCN1,VCAN,S100A8,S100A9
LungImmM2MACM2 macrophagesCSF1R,CSF3R,MRC1,IL10,CCL18,VSIG4,CHI3L1
LungImmBNNaive B cellsCD19,IGHD,IGLL1,CD27,CD38
LungImmMALTBMucosa-Associated Lymphoid Tissue B cellsCXCR4,CD80,CCR6,ITGB7
LungImmBMEMMemory B cellsPAX5,MS4A1,CD19,IGLL5,VPREB3,CD79A,CD79B,IGKC,CD74,HLA-DRA,CD37,CD22
LungImmGCGerminal center B cellsSERPINA9,HRK,HTR3A,BCL6,CD180,FCRLA
LungImmPLAPlasma cellsSSR4,IGLL5,IGLL1,AMPD1,IGHA1,IGHA2,JCHAIN,CD38,TNFRSF17,SDC1,IGHG1,MZB1
LungImmGDTGamma-delta T cellsTRDC,TRGC1,TRGC2,NKG7,TIGIT
LungImmCD4TNNaive CD4+ T cellsIL7R,SELL,CCR7,S100A4,TCF7
LungImmTH1T-helper 1CXCL13,IFNG,CXCR3,BHLHE40,GZMB,PDCD1,HAVCR2,ICOS,IGFLR1,ITGAE
LungImmTFHT follicular helperCXCR5,BCL6,ICA1,TOX,TOX2,IL6ST,MAGEH1,BTLA,ICOS,PDCD1,CD200
LungImmTREGRegulatory T cellsBATF,TNFRSF4,FOXP3,CTLA4,LAIR2,IL2RA
LungImmMAITMucosal-associated invariant T cellsSLC4A10,DPP4,KLRB1,ZBTB16,NCR3,RORC,RORA
LungImmCD8TEXPProgenitor exhausted CD8+ T cellsPDCD1,IL7R,GPR183,NR4A3,REL,TCF7
LungImmCD8TEXINTIntermediate exhausted CD8+ T cellsPDCD1,LAG3,CD101,CD38,CXCR6,TIGIT
LungImmCD8TEREXTerminally exhausted CD8+ T cellsTOX,GZMB,ENTPD1,ITGAE,HAVCR2,CXCL13,PDCD1,LAYN,TOX,IFNG,GZMB,MIR155HG,TNFRSF9,ITGAE
LungImmCD8TCMCentral memory CD8+ T cellsCCR7,SELL,IL7R,CD27,CD28,PRF1,GZMA,CCL5,GPR183,S1PR1
LungImmCD8TEFFEffector CD8+ T cellsCX3CR1,FCGR3A,FGFBP2,PRF1,GZMH,TBX21,EOMES,S1PR1
LungStrENDEndothelial cellsPECAM1,PLVAP,VWF,CLDN5,FLT1,RAMP2,FAM110D,INHBB,NPR1,NOVA2,GPIHBP1,SOX17
LungStrLYMENDLymphatic endothelial cellsPROX1,LYVE1,PDPN,PROCR,FLT4
LungStrMEGAMegakaryocytesPF4,VWF,MPL,GP9,GP1BA,GP1BB,CD9,CD36,ITGA2B
LungStrMSCMesenchymal stem cellsNT5E,THY1,ENG,CD44,ITGB1,MCAM,ENDOD1
LungStrFIBFibroblastsTGFB1,BMP7,MAP3K2,COL6A1,CD36,CD44,FAP,CBLN2,SPOCK1,ACSS3,COL1A1,FN1,COL1A2,COL3A1,BGN,DCN,POSTN,C1R,ACTA2,MMP2,FGF7,MME,CD47
LungStrMYOFIBMyofibroblastsSYT10,SOSTDC1,DES,TAGLN,MYH11,TPM4
LungStrPERIPericytesPDGFRA,CSPG4,RGS5,MCAM,COX4I2,KCNJ8,HIGD1B,NOTCH3,HEYL,FAM162B
LungStrADIPOAdipocytesPPARG,FABP4,ADIPOQ,LEP,CD36,PLIN1
LungStrPVAPost capillary venulesSELP,ZNF385D,FAM155A,GALNT15,MADCAM1,CORT
LungStrMVAMicrovascular cellsPLVAP,CD36,DYSF,NRP1,SH3BP5,EXOC3L2,FABP5,VWA1,BAALC,PRSS23,RAPGEF4,APLN,HTRA1
LungStrECMExtracellular matrixFBLN1,PCOLCE2,MFAP5
LungStrINCAFIntermediate cancer-associated fibroblastsPDGFRA,POSTN,ID1,ID3
LungStrICAFInflammatory cancer-associated fibroblastsTWIST1,WNT2,FAP,CXCL1,CXCL2,CYR61,IL1B,IL6,HGF

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Cell type statistics by disease state

Stacked bar graph representation of the fraction of each epithelial cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.Stacked bar graph representation of the fraction of each immune cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.Stacked bar graph representation of the fraction of each stromal cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.
∗Stacked bar graph representation of the fraction of each epithelial cell type derived from samples with different Disease States in the integrated dataset of Lung tissue. Cells from each Disease State sample have a different color.

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Cell type dynamics in malignant transformation

Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
∗Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in Lung tissue. Samples are colored based on if they are derived from different Disease States. Cell fractions are computed by dividing the number of cells of a given cell type by the total number of cells in the compartment (epithelial versus immune versus stromal).
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Cell lineage trajectory inference

Disease StateEpitheliaImmuneStromal
HealthyTrajectory analysis of cells of epithelial compartment in Healthy-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in Healthy-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in Healthy-derived samples of Lung tissue by using scvelo package in Python.
ADJTrajectory analysis of cells of epithelial compartment in ADJ-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in ADJ-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in ADJ-derived samples of Lung tissue by using scvelo package in Python.
AAHTrajectory analysis of cells of epithelial compartment in AAH-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in AAH-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in AAH-derived samples of Lung tissue by using scvelo package in Python.
AISTrajectory analysis of cells of epithelial compartment in AIS-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in AIS-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in AIS-derived samples of Lung tissue by using scvelo package in Python.
MIACTrajectory analysis of cells of epithelial compartment in MIAC-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in MIAC-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in MIAC-derived samples of Lung tissue by using scvelo package in Python.
IACTrajectory analysis of cells of epithelial compartment in IAC-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in IAC-derived samples of Lung tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in IAC-derived samples of Lung tissue by using scvelo package in Python.
∗RNA velocity maps for epithelial, immune and stromal compartments of Lung tissue with different disease states.

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TF regulatory network analysis

Disease StateEpitheliaImmuneStromal
HealthyHeatmap representation of significantly different TFs among all cell types of epithelial compartment in Healthy-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in Healthy-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in Healthy-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
ADJHeatmap representation of significantly different TFs among all cell types of epithelial compartment in ADJ-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in ADJ-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in ADJ-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
AAHHeatmap representation of significantly different TFs among all cell types of epithelial compartment in AAH-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in AAH-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in AAH-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
AISHeatmap representation of significantly different TFs among all cell types of epithelial compartment in AIS-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in AIS-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in AIS-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
MIACHeatmap representation of significantly different TFs among all cell types of epithelial compartment in MIAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in MIAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in MIAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
IACHeatmap representation of significantly different TFs among all cell types of epithelial compartment in IAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in IAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in IAC-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
∗Heatmap: Heatmap representation of significantly different TFs among all cell types of epithelial compartment in Healthy-derived samples of Lung tissue by comparing their average AUC by using pySCENIC in Python. Regulon specific score for each cell type is colored.
∗Network: TF target network created from Healthy-derived samples of Lung tissue using Top 50 predicted target genes of each regulon. Edge lengths are the inferred TF-target weightings.

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Cell-cell interaction analysis

Disease StateCell TypeCircleSourceTarget
HealthyADIPOThe cell-cell communications between each two interacting cell types in Healthy-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
AT1The cell-cell communications between each two interacting cell types in Healthy-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
ADJABPThe cell-cell communications between each two interacting cell types in ADJ-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
ADIPOThe cell-cell communications between each two interacting cell types in ADJ-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
AAHADIPOThe cell-cell communications between each two interacting cell types in AAH-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in AAH-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in AAH-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
AT1The cell-cell communications between each two interacting cell types in AAH-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in AAH-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in AAH-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
AISADIPOThe cell-cell communications between each two interacting cell types in AIS-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in AIS-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in AIS-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
AT1The cell-cell communications between each two interacting cell types in AIS-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in AIS-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in AIS-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
MIACABPThe cell-cell communications between each two interacting cell types in MIAC-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in MIAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in MIAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
ADIPOThe cell-cell communications between each two interacting cell types in MIAC-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in MIAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in MIAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
IACABPThe cell-cell communications between each two interacting cell types in IAC-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in IAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in IAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
ADIPOThe cell-cell communications between each two interacting cell types in IAC-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in IAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in IAC-derived samples of Lung tissue. Each row represents the significant ligand and receptor gene pairs.
∗The cell-cell communications between each two interacting cell types in different states-derived samples of Lung tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.
∗Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source and target cell population. Each row represents the significant ligand and receptor gene pairs.
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Stemness, Senescence, Metaplasia and NeoTCR signature analysis

check button Developmental potential inference using CytoTRACE.
1_developmental_potential_in_Healthy.png shows the analysis results of stemness, senescence, and metaplasia signatures2_developmental_potential_in_AAH.png shows the analysis results of stemness, senescence, and metaplasia signatures3_developmental_potential_in_AIS.png shows the analysis results of stemness, senescence, and metaplasia signatures4_developmental_potential_in_MIAC.png shows the analysis results of stemness, senescence, and metaplasia signatures5_developmental_potential_in_IAC.png shows the analysis results of stemness, senescence, and metaplasia signatures
∗Ridge plots of CytoTRACE score distributions for epithelial cells.

check button Cellular senescence signature (for three compartments).
Disease StateEpitheliaImmuneStromal
HealthyComparisons for degree of cellular senescence of epithelial compartment in Healthy-derived samples of Lung tissue.Comparisons for degree of cellular senescence of immune compartment in Healthy-derived samples of Lung tissue.Comparisons for degree of cellular senescence of stromal compartment in Healthy-derived samples of Lung tissue.
AAHComparisons for degree of cellular senescence of epithelial compartment in AAH-derived samples of Lung tissue.Comparisons for degree of cellular senescence of immune compartment in AAH-derived samples of Lung tissue.Comparisons for degree of cellular senescence of stromal compartment in AAH-derived samples of Lung tissue.
AISComparisons for degree of cellular senescence of epithelial compartment in AIS-derived samples of Lung tissue.Comparisons for degree of cellular senescence of immune compartment in AIS-derived samples of Lung tissue.Comparisons for degree of cellular senescence of stromal compartment in AIS-derived samples of Lung tissue.
MIACComparisons for degree of cellular senescence of epithelial compartment in MIAC-derived samples of Lung tissue.Comparisons for degree of cellular senescence of immune compartment in MIAC-derived samples of Lung tissue.Comparisons for degree of cellular senescence of stromal compartment in MIAC-derived samples of Lung tissue.
IACComparisons for degree of cellular senescence of epithelial compartment in IAC-derived samples of Lung tissue.Comparisons for degree of cellular senescence of immune compartment in IAC-derived samples of Lung tissue.Comparisons for degree of cellular senescence of stromal compartment in IAC-derived samples of Lung tissue.
∗Comparisons for degree of cellular senescence among epithelial, immune and stromal cell populations of Lung tissue with different disease states.

check button Metaplasia and damage response signature (for epithelial cells).
HealthyAAHAISMIACIAC
Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.
∗Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.

check button Neoantigen-specific TCR clonotypes (NeoTCR) signature.
Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.
∗Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.