Exomics and immunogenics

Figures & data

Table 1. PD-1 and PD-L1 overall response rates across solid tumors

		ORR
		anti-PD1 agent		anti-PD-L1 agent
	mutation rate median frequency of somatic mutations per Mb	Nivolumab BMS-936558	Lambrolizumab MK 34-75	BMS-936559 MDX-1105 MEDI 4736	MPDL 3280 A	PD-L1 expression
Melanoma	13,2	28% (26/94)	38% (44/117)	17% (9/52)	29% (11/38)	40–100 %
NSCLC former/current smoker	10,5				26% (11/43)
NSCLC squamous	8,17	33%  (6/18)		8% (1/13)	27% (3/11)	35–95 %
NSCLC non squamous	6,43	12% (7/56)		11% (4/36)	21%  (9/42)	35–95 %
Colorectal	3,2	0%  (0/19)		0% (0/18)		53%
Ovarian	1,65			6% (1/17)		33–80 %
Renal Cell Carcinoma	1,53	27% (9/33)		12% (2/17)	13% (6/47)	15–24 %
Prostate	0,73	0% (0/13)
NSCLC never smoker	0,6				10% (1/10)
References	Lawrence et al. 2013 Govindan et al. 2012	Topalian et al. 2012	Hamid et al. 2013	Brahmer et al. 2012	Hamid et al. 2013 Soria et al. 2013 Cho et al. 2013	Chen et al. 2012

Figure 1. Link between mutational heterogeneity and response to immune checkpoint blockers. (A) Mutational heterogeneity of tumors and overall response rates (ORRs) to PD-1/PD-L1-targeting agents. Colored bars indicate the median frequency of somatic mutations per megabase (Mb) reported for patients affected by different solid tumors. Yellow arrows represent the ORRs of these patients to anti-PD-1/PD-L1 antibodies, as detailed in Table 1. NSCLC, non-small cell lung carcinoma. (B) Correlation between median frequency of somatic mutations and ORR to PD-1/PD-L1-targeting agents in solid tumors. Dot size is proportional to the number of patients in which the efficacy of anti-PD-1/PD-L1 antibodies was tested. The red dashed line represents the LOESS regression curve. The P value is derived from a linear univariate model (median somatic mutation frequency ~ORR to anti-PD-1/PD-L1 agents).