Table 1.

The analysis tested in 276 pairs between the 24 tracks in the OncoPrint to reveal the connections among immunotherapies related genes.

A	B	A Not B	B Not A	Both	Log2	P value	q value
TNFSF4	TNFSF18	5	4	70	> 3	< 0.001	< 0.001
TNFSF18	CD48	11	40	63	> 3	< 0.001	< 0.001
TNFSF4	CD48	14	42	61	> 3	< 0.001	< 0.001
CD274	PDCD1LG2	3	1	20	> 3	< 0.001	< 0.001
ERBB2	TP53	369	1345	441	1.409	< 0.001	< 0.001
PVR	NECTIN2	3	9	12	> 3	< 0.001	< 0.001
ERBB2	LGALS9	120	9	27	> 3	< 0.001	< 0.001
TNFSF9	CD70	1	3	7	> 3	< 0.001	< 0.001
HHLA2	CD200	6	3	6	> 3	< 0.001	< 0.001
KRAS	TP53	47	1717	69	1.501	< 0.001	< 0.001
CD80	CD200	2	5	4	> 3	< 0.001	< 0.001
CD86	CD200	7	5	4	> 3	< 0.001	< 0.001
CD274	TP53	10	1013	27	2.355	< 0.001	< 0.001
CD80	CD86	3	8	3	> 3	< 0.001	< 0.001
CD80	HHLA2	3	9	3	> 3	< 0.001	< 0.001
NECTIN2	CD48	12	94	9	2.902	< 0.001	0.001
CD86	HHLA2	8	9	3	> 3	< 0.001	0.003
PVR	CD48	8	96	7	> 3	< 0.001	0.004
CD44	TP53	10	332	19	1.984	< 0.001	0.005
VSIR	TP53	5	338	13	2.421	< 0.001	0.011
CD200	TP53	1	343	8	> 3	< 0.001	0.012
PDCD1LG2	TP53	7	484	14	2.138	< 0.001	0.012
VTCN1	TNFRSF14	27	19	3	> 3	0.001	0.015
CD274	PVR	18	12	3	> 3	0.003	0.031
HHLA2	TP53	3	342	9	2.614	0.004	0.041
ALDH1A1	CD44	10	26	3	> 3	0.004	0.048

The close connections among the candidate immune checkpoints, and the connections among checkpoints and malignancy stimulators of either KRAS, TP53, ERBB2, ALDH1A1, CD44, were all calculated and exhibited. The close connections strongly suggested the crucial roles of candidate immune checkpoints in therapy response, and also suggested the potential effects they may exert.