1 加载单细胞数据

library(Seurat)
library(tidyverse)

# 读取数据
sce <- readRDS("G_project_R/combined_seurat_qc.rds")
sce

2 质控与标准化

# 计算线粒体基因比例
sce[["percent.mt"]] <- PercentageFeatureSet(sce, pattern = "^MT-")

# 质控过滤
sce <- subset(sce,
              subset = nFeature_RNA > 200 &
                       nFeature_RNA < 6000 &
                       percent.mt < 20)

# 标准化
sce <- NormalizeData(sce)
sce <- FindVariableFeatures(sce)
sce <- ScaleData(sce)
sce <- RunPCA(sce)
sce <- RunUMAP(sce, dims = 1:20)
sce <- FindNeighbors(sce, dims = 1:20)
sce <- FindClusters(sce, resolution = 0.5)
图1 质控小提琴图

图1 质控小提琴图

图2 全细胞UMAP聚类

图2 全细胞UMAP聚类

3 细胞类型注释

# 使用ACT平台注释结果导入
# 或手动设置marker基因进行注释
marker_genes <- list(
  Macrophage = c("CD68", "CD163", "MRC1"),
  T_cell     = c("CD3D", "CD3E", "CD8A"),
  B_cell     = c("CD19", "MS4A1"),
  NK_cell    = c("GNLY", "NKG7")
)
图3 细胞类型注释UMAP

图3 细胞类型注释UMAP

图4 标记基因DotPlot

图4 标记基因DotPlot

4 提取巨噬细胞

# 提取巨噬细胞群体
mac <- subset(sce, subset = celltype == "Macrophage")
# 共提取到1610个巨噬细胞
mac

5 巨噬细胞再聚类与剔除离群簇

# 巨噬细胞单独重新降维聚类
mac <- FindVariableFeatures(mac)
mac <- ScaleData(mac)
mac <- RunPCA(mac)
mac <- RunUMAP(mac, dims = 1:15)
mac <- FindNeighbors(mac, dims = 1:15)
mac <- FindClusters(mac, resolution = 0.3)

# 剔除UMAP上空间孤立、各功能模块评分低的离群小簇（27个细胞）
# 该簇M1/M2/C1Q/SPP1/增殖评分均无显著富集，缺乏可归类的功能极化状态
mac <- subset(mac, subset = seurat_clusters != "目标cluster编号")
# 最终保留1583个巨噬细胞
图5 巨噬细胞再聚类UMAP

图5 巨噬细胞再聚类UMAP

6 最终巨噬亚群注释（5个亚群）

# 根据标记基因与功能评分对五个亚群进行注释
# C0: C1Q高表达，富集抗原加工提呈通路
# C1: C1Q高表达，富集淋巴细胞活化通路，免疫调节枢纽
# C2: C1Q低表达，偏向翻译代谢
# C3: C1Q最低，染色体分离相关，发育起点
# C4: 高增殖小亚群

new_labels <- c(
  "0" = "C0",
  "1" = "C1",
  "2" = "C2",
  "3" = "C3",
  "4" = "C4"
)
mac$subtype <- new_labels[as.character(mac$seurat_clusters)]
图6 五个巨噬亚群UMAP

图6 五个巨噬亚群UMAP

图7 亚群标记基因热图

图7 亚群标记基因热图

7 功能模块得分计算

library(UCell)

# 定义各功能基因集
M1_genes    <- c("TNF", "CXCL9", "IL1B", "CXCL10")
M2_genes    <- c("MRC1", "CD163", "MSR1","IL10", "TGFB1","CCL2")
C1Q_genes   <- c("C1QA", "C1QB", "C1QC","APOE")
SPP1_genes  <- c("SPP1","GPNMB","CCL18")
Prolif_genes <- c("MKI67", "TOP2A")

mac <- AddModuleScore(mac,
                      features = list(M1_genes, M2_genes,
                                      C1Q_genes, SPP1_genes, Prolif_genes),
                      name     = c("M1_score", "M2_score",
                                   "C1Q_score", "SPP1_score", "Prolif_score"))
图8 各亚群功能模块得分小提琴图

图8 各亚群功能模块得分小提琴图

图9 功能模块得分UMAP投影

图9 功能模块得分UMAP投影

8 差异表达与GO富集分析

library(clusterProfiler)
library(org.Hs.eg.db)

# 各亚群差异表达基因
mac_markers <- FindAllMarkers(mac,
                               only.pos   = TRUE,
                               min.pct    = 0.25,
                               logfc.threshold = 0.25)

# GO富集分析（以C1亚群为例）
C1_genes <- mac_markers %>%
  filter(cluster == "C1") %>%
  pull(gene)

ego <- enrichGO(gene         = C1_genes,
                OrgDb        = org.Hs.eg.db,
                keyType      = "SYMBOL",
                ont          = "BP",
                pAdjustMethod = "BH",
                pvalueCutoff  = 0.05)
图10 各亚群差异基因热图

图10 各亚群差异基因热图

图11 各亚群GO富集分析（BP）图11 各亚群GO富集分析（BP）图11 各亚群GO富集分析（BP）图11 各亚群GO富集分析（BP）图11 各亚群GO富集分析（BP）

图11 各亚群GO富集分析（BP）

9 伪时间轨迹分析

library(monocle3)

# 将Seurat对象转换为CellDataSet
cds <- as.cell_data_set(mac)
cds <- cluster_cells(cds)
cds <- learn_graph(cds)

# 以C3亚群（C1Q评分最低、功能静息）为根节点
cds <- order_cells(cds, root_cells = colnames(cds[, cds$subtype == "C3"]))
图12 伪时间轨迹图

图12 伪时间轨迹图

图13 C1Q评分沿伪时间的变化

图13 C1Q评分沿伪时间的变化

10 CellChat细胞通讯分析

library(CellChat)

# 创建CellChat对象
cellchat <- createCellChat(object  = mac@assays$RNA@data,
                           meta    = mac@meta.data,
                           group.by = "subtype")

# 加载人类配体受体数据库
CellChatDB <- CellChatDB.human
cellchat@DB  <- CellChatDB

# 推断细胞通讯网络
cellchat <- subsetData(cellchat)
cellchat <- identifyOverExpressedGenes(cellchat)
cellchat <- identifyOverExpressedInteractions(cellchat)
cellchat <- computeCommunProb(cellchat)
cellchat <- computeCommunProbPathway(cellchat)
cellchat <- aggregateNet(cellchat)
图14 巨噬细胞分类前配体-受体互作热图

图14 巨噬细胞分类前配体-受体互作热图

图15 巨噬细胞分类后配体-受体互作热图

图15 巨噬细胞分类后配体-受体互作热图

图16 C1亚群相对C0上调受体（log2FC条形图）

图16 C1亚群相对C0上调受体（log2FC条形图）

11 TCGA预后与免疫浸润分析

library(survival)
library(survminer)
library(GSVA)

# 读取TCGA-KIRC表达矩阵与临床信息
tcga_expr <- read.csv("G_project_R/TCGA_KIRC_expr.csv", row.names = 1)
tcga_cli  <- read.csv("G_project_R/TCGA_KIRC_clinical.csv")

# 计算C1亚群特征基因评分
C1_signature <- mac_markers %>%
  filter(cluster == "C1", avg_log2FC > 0.5) %>%
  pull(gene)

gsva_score <- gsva(as.matrix(tcga_expr),
                   list(C1 = C1_signature),
                   method = "ssgsea")

# 生存分析
tcga_cli$C1_score <- as.numeric(gsva_score["C1", ])
tcga_cli$C1_group <- ifelse(tcga_cli$C1_score > median(tcga_cli$C1_score),
                             "High", "Low")

fit <- survfit(Surv(OS_time, OS_status) ~ C1_group, data = tcga_cli)
图17 C1特征基因高低表达组KM生存曲线

图17 C1特征基因高低表达组KM生存曲线

图18 C1评分与免疫细胞浸润相关性

图18 C1评分与免疫细胞浸润相关性

补充材料

以下补充材料为正文分析的延伸与支撑，包括质控前原始分布、额外功能评分结果、功能富集汇总、及局限性相关分析。

补充图1 质控前原始数据分布

补充图1 质控前各样本基因数、UMI数及线粒体比例分布

补充图1 质控前各样本基因数、UMI数及线粒体比例分布

补充图2 五亚群功能模块得分条形图

补充图2 各巨噬细胞亚群M1/M2/C1Q/SPP1/增殖模块平均得分条形图

补充图2 各巨噬细胞亚群M1/M2/C1Q/SPP1/增殖模块平均得分条形图

补充图3 C1Q模块得分高低组生存曲线

补充图3 TCGA-KIRC队列中C1Q模块得分高低组总生存期比较（log-rank p = 0.0045）

补充图3 TCGA-KIRC队列中C1Q模块得分高低组总生存期比较（log-rank p = 0.0045）

注：此处以C1Q模块得分中位数为界将患者分为高低两组，与正文图17（C1亚群特征基因评分）为独立的两种评分策略，结果方向一致，互为佐证。

补充图4 伪时间基因表达热图

补充图4 沿伪时间轨迹（根节点=C3）的关键基因表达热图，示C4亚群MKI67/TOP2A显著富集

补充图4 沿伪时间轨迹（根节点=C3）的关键基因表达热图，示C4亚群MKI67/TOP2A显著富集

补充图5 C1亚群比例与免疫细胞浸润相关性

补充图5 C1亚群比例与各免疫细胞类型浸润的Spearman相关性

补充图5 C1亚群比例与各免疫细胞类型浸润的Spearman相关性

注：上述相关性在多重比较校正后均未达到统计显著性（p.adj > 0.05），提示该趋势性结果有待在更大规模队列中验证，为本研究局限性之一。

补充图6 转录因子活性热图（三分类）

补充图6 巨噬细胞按C1Q-TAM / M1-like / SPP1+TAM三类划分时的转录因子活性热图

补充图6 巨噬细胞按C1Q-TAM / M1-like / SPP1+TAM三类划分时的转录因子活性热图

注：此图为对巨噬细胞进行粗分类（三类）时的转录因子活性分析结果，C1Q-TAM呈现出有别于M1-like及SPP1⁺TAM的独特转录因子特征，支持C1亚群作为独立功能状态的合理性。

补充表1 患者来源与亚群细胞数统计

补充表1 三例ccRCC患者各巨噬细胞亚群细胞数分布
orig.ident Macro_C0 Macro_C1 Macro_C2 Macro_C3 Macro_C4
GSM3440844 685 7 247 202 26
GSM3440845 6 3 3 3 1
GSM3440846 25 325 13 13 23

补充表2 各亚群差异表达基因Top10

Supplementary Table 2: Top marker genes per subcluster
Content
0:TCF7,TSHZ2,TRABD2A,MAL,LEF1,FHIT,SH3YL1,CAMK4,CCR7,MYC,AP3M2,SERINC5,NOSIP,INPP4B,AQP3,IL7R,FLT3LG,RCAN3,LTB,SELL,LDHB,SGTB,KCNA3,CD28,SFXN1,S1PR1,TMEM123,PDE3B,TNFSF8,SATB1,TRAT1,DGKA,MGAT4A,LEPROTL1,TESPA1,CD5,CD6,IL6ST,CCDC109B,LINC00861,TMEM256-PLSCR3,TTC39C,TC2N,CTD-3184A7.4,THEM4,MAML2,ARHGAP15,THOC3,RASA3,GIMAP7
1:CD160,KLRF1,SPON2,FGFBP2,S1PR5,CLIC3,SH2D1B,TTC38,GNLY,NCR1,YES1,MYOM2,IGFBP7,AKR1C3,KLRC1,PTGDR,NCR3,KLRB1,GZMB,KLRD1,GK5,TRDC,MATK,HOPX,CTSW,CTB-31O20.2,CEP78,WDR74,PRSS23,GZMM,IL2RB,HSH2D,FCRL6,PRF1,LAIR2,C1orf21,NKG7,CD247,KLRC3,TFDP2,TMIGD2,MVD,ITGAM,TGFBR3,CD7,MCTP2,ZBP1,FKBP11,NFKBIB,GNPTAB
2:S100A12,S100A8,S100A9,VCAN,MGST1,NRG1,ASGR2,RBP7,BST1,RP11-1143G9.4,RETN,CD36,CDA,RNASE2,CSF3R,NRGN,FCN1,CSTA,LGALS2,LYZ,PLBD1,CKAP4,CD300E,TMEM170B,FAM198B,F13A1,ASGR1,PID1,PYGL,MTMR11,RASGRP4,NCF2,LMO2,SULF2,TNFAIP2,DMXL2,RAB3D,LRP1,HRH2,PRAM1,CFP,BCL6,ANPEP,CD93,MPEG1,CLEC12A,QPCT,MNDA,DOK3,DUSP6
3:VPREB3,RP11-731F5.2,LINC00926,FCRL1,FCER2,MS4A1,FAM129C,AC079767.4,IGHD,BANK1,FCRLA,CD19,TNFRSF13C,TCL1A,IGHM,CD22,CD79A,BLK,CD24,COBLL1,KIAA0125,PKIG,POU2AF1,CXCR5,AFF3,RALGPS2,KIAA0226L,STAP1,GNG7,HLA-DOB,BLNK,SPIB,ARHGAP24,PDLIM1,BACH2,CD79B,ADAM28,HVCN1,TCF4,CD40,RAB30,SWAP70,PLPP5,MEF2C,LY9,IFT57,IRF8,TMEM156,CHPT1,MARCH1
4:RP11-291B21.2,GZMH,KLRG1,LYAR,FCRL6,ZNF683,TGFBR3,CD8B,GNLY,C12orf75,GZMM,CD8A,C1orf21,CD320,SYNE1,SAMD3,AC092580.4,PPP2R5C,NKG7,FGFBP2,CD3G,CCL5,MATK,S1PR5,CDC25B,RORA,FYN,KLF3,KLRD1,DSTN,MRPL10,SYNE2,CD3E,PIK3R1,PPP3CC,CTSW,LIME1,LINC00869,TSEN54,CD99,RASSF1,CD52,P2RY8,BIN2,CD3D,FKBP11,TC2N,RNF125,C9orf142,FLNA
5:TOX2,VCAM1,TNFRSF9,CD200R1,PDCD1,CD8A,TMEM155,GZMK,FXYD2,CD8B,CRTAM,CCDC141,AC069363.1,DUSP4,MIR155HG,TTN,CD27,SIT1,TOX,SNAP47,TNFSF9,MAP1LC3A,SIRPG,CTLA4,LAG3,HNRNPLL,GALM,CLECL1,RGS1,ITM2A,FAM3C,CDKN2A,EOMES,TRAF5,PRR5L,LYST,CD82,NELL2,CCL4L2,MT1F,SEMA4A,PTMS,GTPBP8,APOBEC3C,JAKMIP1,SLF1,SH2D2A,CXCR3,MSI2,HAVCR2
6:LMNA,HSPA1A,HSPA6,DNAJB1,TUBB2A,LDLR,ZNF683,DNAJA1,HSPA1B,RGCC,NEU1,HSPE1,OASL,ZFAND2A,CACYBP,HSPH1,HSP90AA1,ICOS,BAG3,TOB1,YIPF5,FKBP4,PNP,ANXA1,HSPD1,TUBA4A,AHSA1,TUBB4B,THEMIS,CD5,HSP90AB1,GZMH,FAM177A1,YPEL5,RORA,CHORDC1,ZC3H12A,DNAJB4,CREM,ANKRD37,CDKN1A,PDE4B,CD6,IFRD1,FOSB,MYADM,TNF,EIF4A3,TUBA1C,HSPA8
7:CD40LG,IL7R,SOCS1,EGR1,TNF,THEMIS,TUBA4A,TC2N,KLRG1,CD69,CXCR3,AC092580.4,AIM1,ZFP36L2,CXCR4,CD5,TNFAIP3,BTG2,FKBP5,CD2,SH2D1A,THEM4,PTGER4,OXNAD1,SLFN5,FAM46C,SCML4,PARP8,JUNB,FAM129A,PDE4B,DDIT4,CD6,PDCD4,JUN,FOS,DUSP2,CITED2,FYN,KIAA1551,GZMK,CD8A,RGCC,STAT4,ODC1,SIT1,ZFP36,TMEM173,TRAT1,CCNH
8:SEPP1,GPNMB,WBP5,PMP22,SDS,APOE,PLEK2,SEMA6B,NRP2,APOC1,C15orf48,LGMN,CLEC5A,FN1,MMP14,GPR84,SNAI1,C1QC,RP11-212I21.2,MACC1,OLFML2B,G0S2,FPR3,TREM2,GAL3ST4,PLAU,C1QB,C1QA,CD1E,FCER1A,PLA2G7,HLA-DQB2,CD9,SLCO2B1,A2M,HMOX1,SLC37A2,P2RY6,CLEC10A,STAB1,LINC01094,VEGFA,CTSL,DOCK4,PLTP,AXL,NRP1,TMEM51,CXCL2,LTC4S
9:KRT81,KRT86,KIR2DL4,RGS16,XCL1,TNFSF14,ZNF683,KLRC1,TRDC,XCL2,TMIGD2,HSPA6,TNFRSF18,SH2D1B,AC092580.4,ABCB1,KLRC2,KLRC3,HSPA1A,LDLRAD4,CD160,ATP1B1,FASLG,DNAJB1,HSPE1,HOPX,MATK,NCR1,IL2RB,CTD-3252C9.4,NEU1,HSPA1B,KLRB1,CD7,DNAJB4,DNAJA1,SERTAD1,TRGV9,BPGM,HSPH1,CACYBP,IFNG,ANKRD37,PCID2,TXK,KLRD1,NCR3,ZFAND2A,ZC3H12A,HSPD1
10:ALOX15B,ANKRD22,SH3BP4,PKP2,IL1R2,SRGAP1,APOC4-APOC2,APOC2,DEPTOR,CPM,CD1E,PKIB,PDK4,EREG,ECHDC3,FILIP1L,SLC1A3,FCER1A,FLT3,CD1C,IL18,PALD1,CLEC4E,SERPINF2,NLRP3,P2RY13,ADORA3,SLAMF8,AXL,KCNMB1,CD163,GPX3,TNFRSF21,RNASE6,CLEC10A,GAPT,CLIC2,GPX1,SERPING1,IL13RA1,CH25H,SGK1,FPR3,PLTP,FMN1,CXCL2,VSIG4,TM6SF1,AREG,CXCL8
11:TRDV1,RP11-492E3.2,PMCH,TRGV8,RTKN2,TRBV24-1,CADM1,TRGV2,AC017002.1,TMEM155,AC133644.2,TNIP3,LAG3,FXYD2,LAYN,TSC22D1,BHLHE40-AS1,VCAM1,CD200R1,CCDC64,CSF1,TRGV4,SNAP47,ADTRP,PCSK1N,TRGC2,AC069363.1,PDCD1,PTMS,GZMK,SIRPG,DUSP16,HAVCR2,CTLA4,TRG-AS1,TNFRSF9,IKZF2,CD27,JMJD4,MAP1LC3A,NAB1,CCR5,FAM3C,TOX2,PRR5L,CDKN2A,TNFSF9,AC104820.2,CCDC141,EOMES
12:CDKN1C,CTD-2006K23.1,ICAM4,CKB,TCF7L2,NEURL1,CALML4,CDH23,BATF3,LINC01272,TPTEP1,GPBAR1,RP11-362F19.1,LST1,HES4,LILRA1,LRRC25,TAGLN,RP11-750H9.5,ZNF703,P2RX1,LILRA5,HK3,SECTM1,IFITM3,SLC2A6,APOBEC3A,LILRB2,ZDHHC1,CDK2AP1,SERPINA1,LILRA2,FAM110A,SIGLEC10,CD300LF,RRAS,PILRA,MYOF,MTMR11,SIRPB1,LILRB1,MXD3,C19orf38,CAMK1,HCK,CFD,CD300C,SIDT2,AIF1,PLXNB2
13:FPR2,CDC42EP2,THBS1,RP11-362F19.1,HES4,FCAR,LINC01272,ZNF703,G0S2,PAPSS2,AQP9,IL1B,LINC00877,MEFV,LILRA5,APOBEC3A,DNAJA4,TBC1D8,LILRB2,C5AR1,EREG,TREM1,TIMP1,THBD,CLEC4E,TCF7L2,GPBAR1,CXCL8,BCL2A1,CALML4,RNF144B,LILRA1,CHST15,HK3,CDKN1C,CD300E,SLC11A1,PTGS2,CCRL2,ETS2,PLAUR,LILRB1,MARCO,HCK,SECTM1,LILRA6,NAMPT,TLR4,CFP,NLRP3
14:DLGAP5,KIF20A,SPC25,HJURP,UBE2C,FAM64A,PKMYT1,KIF2C,TYMS,BIRC5,PLK1,GTSE1,KIF15,CCNB2,CENPA,AURKB,RRM2,CDC20,CDCA5,CDCA3,KIF4A,PBK,SPC24,CDC45,CCNA2,MKI67,TROAP,UHRF1,ASPM,SKA3,KIF23,KIF14,TTK,HIST1H3B,KIAA0101,CDT1,TOP2A,FOXM1,SKA1,DIAPH3,MND1,CDCA8,CDCA2,CEP55,CDC6,CDK1,TK1,NEIL3,HMMR,DEPDC1B
15:CCR8,FOXP3,TNFRSF4,HACD1,IL2RA,TNFRSF18,TBC1D4,LAYN,ICA1,SLAMF1,CUL9,FBLN7,CTLA4,NGFRAP1,CXCR6,TIGIT,BATF,AC017002.1,MAGEH1,AC133644.2,STAM,ICOS,MAST4,NDFIP2,LTA,GADD45A,LAIR2,IKZF2,PHLDA1,DNPH1,CD70,CCDC141,LIMA1,CDKN2A,ACTA2,PHTF2,IL32,ENTPD1,CD28,TNFRSF9,SGMS1,UGP2,SAMSN1,GBP5,MIR4435-2HG,ATP1B1,TRAF1,TSPAN5,PVT1,PTTG1
16:MYOM2,CCL4,CCL3,AREG,KIR2DL3,ZBTB10,IL18RAP,SH2D1B,EGR1,CCL4L2,CD69,KLRF1,SPON2,GSAP,KLRD1,OSBPL5,SOCS1,CLIC3,IER2,FCRL3,KLRC1,GZMB,AKR1C3,AF213884.2,NCR1,RP11-553L6.2,BTG2,FOS,FCGR3B,ZBTB16,GFOD1,DTHD1,IFNG,TBX21,JUN,MAPK1,CX3CR1,EGR2,S1PR5,TMIGD2,PTGDR,PRF1,DUSP2,GRASP,TTC38,NFKBIA,RP11-325F22.2,CCL3L3,RBKS,ADRB2
17:FCGBP,CCL2,HAMP,CLDN1,MMP2,OLFML3,EGR3,C3,PLAU,SPP1,RP11-834C11.4,MRC2,P2RY12,GAL3ST4,CD276,FILIP1L,BHLHE41,A2M,SLCO2B1,DOCK4,EGR2,C1QC,PALD1,TMEM52B,TREM2,P3H2,HS3ST1,SPRED1,C1QA,C1QB,MSR1,VSIG4,C2,OLR1,GPR34,GATM,FRMD4A,EPB41L2,GAS6,RP11-472N13.3,ETV5,MMP14,ADORA3,C3AR1,HBEGF,IGF1,MACC1,SDS,FMNL2,ZNF618
18:RP11-761N21.1,XCR1,PPY,RP11-798K3.3,TACSTD2,CLEC9A,IDO1,DNASE1L3,FBXO27,RFPL4A,ENPP1,RP11-244M2.1,CYYR1,ZNF366,RAB7B,EGLN3,CLNK,MYLK,BCL2L14,PPM1J,C1orf54,NEGR1,SERPINF2,FLT3,WDFY4,GPR157,PPM1H,CCND1,CCSER1,P2RY14,GPER1,NET1,P2RY6,MYCL,NAV1,CALCRL,BATF3,TLR10,SHTN1,CLEC4C,CLIC2,SCARF1,CPVL,ADGRG6,HLA-DOB,SLAMF8,LDLRAD3,PARM1,LGALS2,SERPINF1
19:IGKV2D-30,IGLV3-1,IGHGP,IGHG1,IGLC2,JCHAIN,IGHV4-61,SDC1,IGHA1,IGHG4,MIXL1,GPRC5D,IGHA2,TNFRSF17,IGLL5,IGHG2,DERL3,IGKV4-1,IGKC,MZB1,IGLC3,TXNDC5,IGHG3,AC104699.1,IGLV6-57,ABCB9,CCR10,JSRP1,IGKV1-12,BMP8B,RP11-1070N10.3,FCRL5,CNKSR1,RP11-16E12.2,RASSF6,PYCR1,C2orf88,RP11-279O9.4,PKHD1L1,POU2AF1,CPNE5,SPAG4,PDIA5,PARM1,ITM2C,B9D1,DENND5B,TNFRSF13B,ZP3,GAB1
20:LRRC26,RP11-73G16.2,SHD,SCT,PTCRA,LAMP5,CLEC4C,NLRP7,LILRA4,AC023590.1,ASIP,SMIM5,SCAMP5,PTPRS,SCN9A,KCNK17,MAP1A,TPM2,CYP46A1,EPHB1,EPHA2,PHEX,PLVAP,GPM6B,IL3RA,AC011893.3,MYBL2,CYYR1,RP11-117D22.2,PROC,C1orf186,SLC7A11,PPM1J,PACSIN1,SMPD3,RP11-385F7.1,TNFRSF21,TSPAN13,LINC00996,PLD4,PFKFB2,RP1-244F24.1,SERPINF1,PTGDS,TCL1A,TCF4,EGLN3,UGCG,IGKV1-12,PPP1R14B

补充附件：功能富集汇总表

各亚群GO（BP/CC/MF）及KEGG富集分析完整结果见附件：

enrichment_table.pdf

Analysis complete. All figures are from original analysis. Code is for display only.