Identification of Rad51 as a prognostic biomarker correlated with immune infiltration in hepatocellular carcinoma

Figures & data

Figure 1. Flowchart of filtration process to identify target genes

Figure 2. Differentially expressed DNA repair genes. A. Heatmap of the screened genes. B. Survival analysis of Rad51 in the patient with HCC from ICGC cohort

Figure 3. The expression level and survival analysis of Rad51 in HCC. A. The expression level of Rad51 in HCC from TCGA cohort. B. The expression level of Rad51 in HCC from GEPIA database. C. The protein expression of Rad51 in HCC from HPA database. D-G. Survival analysis of OS, RFS, PFS and DSS (n = 364, n = 316, n = 370, n = 362) in liver cancer

Figure 4. The prognostic value of Rad51 in HCC. Expression of Rad51 correlated significantly with clinical stage (a), pathologic T stage (b), grade (c) and age (d). Univariate COX analysis (e) and multivariate COX analysis (f) revealed the correlation between Rad51 and clinicopathological features in HCC patients

Table 1. Kaplan-Meier plotter to determine the effect of different clinicopathologic variables on the expression of Rad51 gene and clinical prognosis in HCC

Clinicopathological characteristics	Overall survival (OS)			Relapse free survival (RFS)
	N	HR	P	N	HR	P
Stage
1	170	1.87(0.93–3.73)	0.0735	153	1.76(1.02–3.02)	0.04
2	83	4.84(1.45–16.16)	*	74	0.65(0.33–1.31)	0.23
3	83	2.13(1.09–4.16)	0.024	68	2.14(1.07–4.27)	0.028
4	54	– –	– –	0	– –	– –
Grade
1	55	3.04(1.16–7.97)	0.018	45	2.76(0.99–7.69)	0.044
2	174	2.01(1.07–3.8)	0.028	147	2.23(1.32–3.76)	*
3	118	1.72(0.88–3.34)	0.11	106	1.74(0.97–3.14)	0.059
4	12	– –	– –	11	– –	– –
ATCC
1	180	1.81(0.95–3.45)	0.7	160	1.85(1.07–3.2)	0.026
2	90	3.73(1.32–10.85)	*	79	1.57(0.76–3.17)	0.2
3	78	1.70(0.84–3.41)	0.13	65	1.81(0.91–3.59)	0.085
4	13	– –	– –	6	– –	– –
Vascular invasion
N	203	1.93(1.08–3.44)	0.023	175	1.49(0.89–2.5)	0.13
micro	90	1.57(0.7–3.51)	0.27	81	2.22(1.12–4.4)	0.019
macro	16	– –	– –	14	– –	– –
Gender
male	246	2.83(1.59–5.05)	**	208	1.73(1.15–2.62)	*
female	118	1.84(1.05–3.23)	0.032	105	1.78(0.99–3.21)	0.05
Race
white	181	1.58(0.95–2.62)	0.073	147	1.96(1.24–3.11)	*
Asian	155	3.92(2.05–6.77)	***	143	2.66(1.57–4.51)	**
black	17	– –	– –	13	– –	– –
Alcohol consumption
yes	115	2.02(1.02–4.02)	0.04	98	3.21(1.48–6.93)	*
no	202	2.02(1.25–3.25)	*	182	1.72(1.09–2.72)	0.019
HBV
yes	150	1.48(0.72–3.06)	0.29	138	1.39(0.8–2.4)	0.24
no	167	2.37(1.5–3.74)	**	142	2.45(1.47–4.08)	**

Figure 5. The relationship between Rad51 expression levels and immune filtrates in HCC. A. Rad51 expression level is significantly positive correlated with immune cells. Correlation analysis between Rad51 expression and immunological markers in HCC: B. Monocyte; C. T cell (general); D. Treg; E. T cell exhaustion

Table 2.  Correlation analysis between Rad51 and relate genes and markers of immune cells in TIMER

Description	Gene markers	None		Purity
		Cor	P	Cor	p
B cell	CD19	0.31	***	0.351	***
	CD79A	0.224	***	0.299	***
Monocyte	CD86	0.397	***	0.507	***
	CD115(CSF1R)	0.262	***	0.366	***
T cell(general)	CD3D	0.346	***	0.426	***
	CD3E	0.365	***	0.371	***
	CD2	0.282	***	0.379	***
TAM	CCL2	0.147	*	0.216	***
	CD68	0.268	***	0.323	***
	IL10	0.285	***	0.362	***
M1	INOS(NOS2)	−0.041	0.432	0.037	0.48
	IRF5	0.372	***	0.367	***
	COX2(PTGS2)	0.123	0.019	0.2	**
M2	CD163	0.164	*	0.234	***
	VSIG4	0.193	**	0.266	***
	MS4A4A	0.187	0.029	0.099	0.06
Neutrophils	CD66 b(CEACAM8)	0.103	0.048	0.128	0.01
	CD11b(ITGAM)	0.366	***	0.434	***
	CCR7	0.121	0.02	0.208	***
Natural killer cell	KIR2DL1	0.01	0.84	0.025	0.64
	KIR2DL3	0.165	*	0.194	**
	KIR2DL4	0.261	***	0.272	***
	KIR3DL1	0.021	0.68	0.022	0.67
	KIR3DL2	0.126	0.01	0.14	*
	KIR3DL3	0.065	0.21	0.05	0.35
	KIR2DS4	0.097	0.06	0.097	0.07
Dendritic cell	HLA-DPB1	0.266	***	0.347	***
	HLA-DQB1	0.248	***	0.316	***
	HLA-DRA	0.255	***	0.332	***
	HLA-DRA1	0.223	***	0.304	***
	BCDA-1(CD1C)	0.129	0.01	0.184	**
	BDCA-4(NRP1)	0.203	***	0.215	***
	CD11c(ITGAX)	0.372	***	0.461	***
Th1	T-bet(TBX21)	0.12	0.01	0.193	**
	STAT4	0.298	***	0.331	***
	STAT1	0.398	***	0.421	***
	IFN-γ(IFNG)	0.317	***	0.368	***
	TNF-α(TNF)	0.302	***	0.394	***
Th2	GATA3	0.26	***	0.353	***
	STAT6	0.117	0.02	0.108	0.04
	STAT5A	0.369	***	0.397	***
	IL13	0.091	0.07	0.089	0.09
Tfh	BCL6	0.089	0.07	0.096	0.07
	IL21	0.15	*	0.194	**
Th17	STAT3	0.092	0.07	0.102	0.05
	IL17A	0.052	0.31	0.063	0.24
Treg	FOXP3	0.172	**	0.229	***
	CCR8	0.365	***	0.426	***
	STAT5B	0.189	**	0.186	**
	TGFβ(TGFB1)	0.307	***	0.378	***
T cell exhaustion	PD-1(PDCD1)	0.369	***	0.444	***
	CTLA4	0.405	***	0.479	***
	LAG3	0.364	***	0.381	***
	TIM-3(HAVCR2)	0.403	***	0.517	***
	GZMB	0.168	*	0.2	**

Table 3.  Correlation analysis between Rad51 and relate genes and markers of monocyte, T(general), Treg and T Cell exhaustion in GEPIA

	tumor		normal
	R	P	R	P
monocyte
CD86	0.55	***	0.4	***
CD86(CSFIR)	0.39	***	0.46	***
T(general)
CD3D	0.5	***	0.3	***
CD3E	0.36	***	0.22	*
CD2	0.41	***	0.19	0.016
Treg
FOXP3	0.28	***	0.13	0.11
CCR8	0.48	***	0.19	0.017
STAT5B	0.086	0.06	0.15	0.064
TGFβ(TGFB1)	0.38	***	0.4	***
T Cell exhaustion
PD-1(PDCD1)	0.4	***	0.28	**
CTLA4	0.47	***	0.26	*
TIM3(HAVCR2)	0.42	***	0.41	***

Figure 6. Functional enrichment analysis of differentially co-expressed genes of Rad51 in HCC. A. Volcano plots of differentially co-expressed genes of Rad51. The heatmap visualized the top 50 positively (b) and negatively (c) differentially co-expressed genes. GO terms of biological process (d), cell component (e) and molecular function(f)