Potential effect of tumor-specific Treg-targeted antibodies in the treatment of human cancers: A bioinformatics analysis

Figures & data

Figure 1. Infiltration of tumors by T cells and T cell subsets. (A) The T cell infiltration score was calculated by evaluating the mRNA expression of genes included in the T cell signature proposed by Bindea et al.³¹ However, the genes TRA and TRAC are not included in the Affymetrix platform and therefore were not considered. The ratio of the expression in the patient's tumor sample and the mean expression in the HTs was calculated for each gene. Then, the mean ratio of the genes in each patient was expressed as log(2). The mean normalized expression of genes included in the T cell signature in tumors T1, T2, T3 and T4 was found to be significantly higher as compared to T6, T7, T8 and T9 (####, p<0.0001). (B) The CTL activity score was calculated by evaluating the mRNA expression of genes included in the CTL signature³¹ normalized to the expression of CD8α. The ratio of the expression in the patient's tumor sample and the mean expression in the PBMCs of HDs was calculated for each gene. Then, the mean ratio of the genes in each patient was expressed as log(2). The mean normalized expression of genes included in the CTL signature in each tumor was found to be significantly lower (##, p<0.01; ###, p<0.001; ####, p<0.0001) or not significantly different (n.s.) as compared to the mean normalized expression in PBMCs of HDs. (C) The suppressive score was calculated by evaluating FOXP3, IL-10 and TGFβ mRNA expression normalized to the expression of CD4. The ratio of the expression in the patient's tumor sample and the mean expression in the PBMCs of HDs was calculated for each gene. Then, the mean ratio of the genes in each patient was expressed as log(2). The mean normalized expression of FOXP3, IL-10 and TGFβ in each tumor was found to be significantly higher as compared to the mean normalized expression in PBMCs of HDs (####, p<0.0001). (D) Correlation of TGFβ mRNA expression and CD4 mRNA expression in patients with non-squamous NSCLC. The Spearman coefficient (ρ) and p value are reported. (E) Correlation of IL-10 mRNA expression and CD4 mRNA expression in patients with renal cell carcinoma. Spearman coefficient (ρ) and p value are reported. All box-and-whisker plots (A-C) represent values within the interquartile range (boxes), and whiskers represent the highest and the lowest values.

Table 1. Decrease in the CD8⁺/CD4⁺ ratio in cancer specimens as compared to PBMCs from HDs.

	CD8α/CD4 ratio^1	Decrease factor	p-value^2
Non-squamous NSCLC	↓	1.2	0.0289
Squamous NSCLC	↓	1.4	0.0026
Renal cell carcinoma	↓	1.4	0.0025
Breast infiltrating ductal carcinoma	↓	2.0	< 0.0001
Colorectal carcinoma	↓	1.9	< 0.0001
Liver carcinoma	↓	1.7	< 0.0001
Prostate carcinoma	↓	1.9	< 0.0001
Ovarian clear cell carcinoma	↓	1.8	0.0001
Ovarian serous carcinoma	↓	2.4	< 0.0001

¹ Ratio refers to mRNA expression of CD8α and CD4 chains in tumors compared to that in PBMCs from HDs.

² Student's t-test (p-value) was used for statistical analysis in the comparison between the CD8α/CD4 ratio in the tumor and the CD8α/CD4 ratio in PBMCs from HDs.

Table 2. Correlation between mRNA expression of the regulatory cytokines and the mRNA expression of CD4 in cancer specimens.

	TGFβ vs. CD4		IL-10 vs. CD4
	ρ^1	p-value^1	ρ^1	p-value^1
Non-squamous NSCLC	0.81	<0.0001	0.16	<0.0001
Squamous NSCLC	0.74	<0.0001
Renal cell carcinoma	0.56	<0.0001	0.44	<0.0001
Breast infiltrating ductal carcinoma	0.68	<0.0001
Colorectal carcinoma	0.76	<0.0001
Liver carcinoma	0.77	<0.0001	0.17	0.0080
Prostate carcinoma	0.39	0.0002
Ovarian clear cell carcinoma	0.66	0.0002
Ovarian serous carcinoma	0.56	<0.0001	0.20	0.0030

¹ Spearman correlation coefficients (ρ) and p-values evaluated by Student's t-test are reported when p<0.05 and ρ≥0.15 or ρ≤−0.15.

Table 3. Correlation between the mean mRNA expression of genes representing T cells (see Figure S1) and the mean mRNA expression of genes representing CTL, normalized by CD8α expression, in cancer specimens.

	T cell infiltration vs CTL activity
	ρ^1	p-value^1
Non-squamous NSCLC	−0.62	<0.0001
Squamous NSCLC	−0.61	<0.0001
Renal cell carcinoma	−0.64	<0.0001
Breast infiltrating ductal carcinoma	−0.66	<0.0001
Colorectal carcinoma	−0.46	<0.0001
Liver carcinoma	−0.65	<0.0001
Prostate carcinoma	−0.33	0.0019
Ovarian clear cell carcinoma	−0.70	<0.0001
Ovarian serous carcinoma	−0.52	<0.0001

¹ Spearman correlation coefficients (ρ) and p-values evaluated by Student's t-test are reported.

Figure 2. Expression of Treg markers in tumors vs. HTs. The ratio of expression of the marker in the tumor to its expression in HTs is shown on a log(2) scale. Markers with higher than two-fold expression in the tumor compared to the corresponding HTs (#, p<0.05) or higher than 1.5-fold expression in the tumor compared to both the corresponding HTs (#, p<0.05, as evaluated by Student's t-test) and the mean expression in HTs (#, p<0.05) were selected for further analysis (markers within grey boxes). As a rescue strategy (prostate carcinoma), markers showing higher than 1.5-fold expression in the tumor as compared to the corresponding HTs (#, p<0.05) were selected for further analysis (marker within grey dotted boxes). Markers that met the expression conditions but were not selected because the difference between tumors and HTs was not significant (n.s.) are shown within white boxes.

Table 4. Overexpression of Treg markers in specific tumors.

	Non-squamous NSCLC		Squamous NSCLC		Renal cell carcinoma		Breast infiltrating ductal carcinoma		Colorectal carcinoma		Liver carcinoma		Prostate carcinoma		Ovarian clear cell carcinoma		Ovarian serous carcinoma
	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2	Patients^1	p-value^2
4-1BB	16%	< 0.0001			33%	< 0.0001	62 %	< 0.0001
CD103													19%	< 0.0001
CD27	11%	0.0005			30%	< 0.0001	28%	< 0.0001
CD39					83%	< 0.0001
CD69					10%	< 0.0001	21%	< 0.0001
CD73	47%	< 0.0001
CTLA-4	39%	< 0.0001	30%	< 0.0001			20%	< 0.0001	34%	< 0.0001
Galectin-9					44%	< 0.0001	49%	< 0.0001									62%	< 0.0001
GITR	41%	< 0.0001	71%	< 0.0001			42%	< 0.0001
ICOS							56%	< 0.0001
IL-21R	47%	< 0.0001	25%	< 0.0001			45%	< 0.0001
LAG3	22%	< 0.0001	29%	< 0.0001
LAP					73%	< 0.0001	22%	< 0.0001							93%	< 0.0001	91%	< 0.0001
Neuropilin-1					41%	< 0.0001			22%	< 0.0001					26%	0.0002
TIGIT	60%	< 0.0001	57%	< 0.0001			72%	< 0.0001
TIM3					27%	< 0.0001					38%	0.02
TNFR2					53%	< 0.0001

¹ Percentage of patients showing overexpression of the Treg marker (i.e., the patients in whom the Treg marker expression level was higher than the mean+2SD value of the Treg marker expression in HTs) (see Figure 3 and S2-S7). Treg markers selected through the procedure described in Figure 2 (grey boxed genes) are reported. Treg markers overexpressed in more than 40% of the patients are shown in a grey background and were subjected to further analysis.

² Student's t-test (p-value) was used for statistical analysis in the comparison between the expression level of the Treg marker mRNA in the tumor samples vs. the corresponding HT samples.

Figure 3. mRNA expression of the best Treg marker in tumor samples and the corresponding HTs. Mean±SD values of expression of the Treg marker in HTs and expression of the marker in each tumor sample are shown. The percentage of patients with expression greater than the mean+2SD value (dotted line) of the corresponding HTs is reported. The best Treg marker for each tumor is shown (the expression of the other selected Treg markers are shown in supplemental Figures S2−S7). Student's t-test was used for statistical analysis in the comparison between the expression level of the Treg marker mRNA in tumors vs. the corresponding HT samples.

Figure 4. Correlation between the expression of GITR and suppressive cytokines. Correlation of GITR mRNA expression with TGFβ (A) and IL-10 (B) mRNA expression in patients with non-squamous NSCLC. Spearman coefficients (ρ) and p values are reported.

Table 5. Correlation of the expression of Treg markers with that of the suppressive cytokines in tumor samples.

Treg marker class in reference to a suppressive microenvironment	A									B						C					D
# of tumors in which Treg marker correlates with the expression of suppressive cytokines	9	9	8	9	8	8	8	8	8	7	7	7	7	6	6	5	5	5	5	5	4	4	4	3
OVERALL SCORE^1	38	37	31	30	30	29	29	28	26	24	22	22	19	16	10	16	11	8	8	7	8	6	−1	−2
Non-squamous NSCLC^1	3	3	6	4	6	0	4	6	6	6	−1	6	−3	4	−1	4	6	1	−2	−3	0	−3	4	2
Squamous NSCLC^1	3	4	4	2	3	1	0	4	2	3	3	3	0	4	1	2	2	0	2	0	2	0	2	1
Renal cell carcinoma^1	4	6	2	4	4	6	4	3	2	2	3	2	4	1	1	0	−4	4	4	2	0	1	−2	−2
Breast infiltrating ductal carcinoma^1	4	3	3	4	2	2	2	3	3	2	2	1	3	3	1	3	3	2	1	3	2	1	2	0
Colorectal carcinoma^1	6	6	6	4	6	6	6	6	6	6	6	6	2	3	1	4	4	−3	2	1	4	0	1	−1
Liver carcinoma^1	3	2	4	3	4	4	3	4	3	4	4	3	4	0	3	3	1	0	−1	0	−1	0	−4	2
Prostate carcinoma^1	3	4	0	3	3	1	3	1	3	1	0	0	2	1	0	0	0	0	0	2	0	3	0	0
Ovarian clear cell carcinoma^1	6	3	3	3	0	3	3	0	0	0	3	0	3	0	0	0	0	3	0	0	0	0	−3	0
Ovarian serous carcinoma^1	6	6	3	3	2	6	4	1	1	0	2	1	4	0	4	0	−1	1	2	2	1	4	−1	−4
	Tim-3	TNFR2	4-1BB	Galectin-9	TIGIT	CD39	LAP	OX40	CD27	LAG3	Neuropilin-1	GITR	CD69	CD25	CD73	PD-L2	CCR8	CD103	IL-21R	ICOS	CD226	CTLA-4	CD30	PD-1

¹ The score was calculated for each marker in each tumor as specified in Table S4. Positive scores are shown in the white background (direct correlation between marker expression and suppressive cytokine expression, i.e., suppressive microenvironment), neutral scores are shown in the grey background (no correlation between marker expression and suppressive cytokine expression), and negative scores are shown in the black background (inverse correlation between marker expression and suppressive cytokine expression). The overall score is the sum of the scores of the marker in all the tumors.

Figure 5. Expression of activating FcγR mRNA in tumors vs. lymph nodes from HDs. The ratio of the mRNA expression of the specified activating FcγR in the tumor specimen and the mean (±SD) mRNA expression in the lymph nodes of HDs is shown on a log(2) scale. In the histogram on the right, the mean of the ratios [expressed as log(2)] of the four activating FcγRs is shown. The mean expression of each FcγR in each tumor as compared to the mean expression in HD lymph nodes was found to be significantly different (#, p<0.05: ##, p<0.01: ###, p<0.001; ####, p<0.0001).

Figure 6. Algorithm used to calculate the ADCC index of Treg markers in a cancer. To evaluate the probability of a Treg marker being successfully used as a target to induce ADCC, we established the ADCC index. The ADCC index was calculated for each marker in each cancer as described in the material and methods. Half of the score is derived from evaluation of overexpression of the marker in the responder patients (i.e., the patients in whom the Treg marker expression level was higher than the mean+2SD value of the Treg marker expression in HTs), one-fourth from the expression of activating FcγR in the cancer sample of the responder patients, and one-fourth from the correlation of the marker expression with the suppressive microenvironment (i.e., the probability that the marker was mainly expressed in Tregs). The final score was obtained by multiplying each of these four scores. The ADCC scores of the markers in specific cancers are shown in Table 6.

Table 6. ADCC index of the markers overexpressed in more than 40% of the patients.

	Non-squamous NSCLC		Squamous NSCLC		Renal cell carcinoma		Breast infiltrating ductal carcinoma		Ovarian clear cell carcinoma		Ovarian serous carcinoma
	Responder patients^1	ADCC index^2	Responder patients^1	ADCC index^2	Responder patients^1	ADCC index^2	Responder patients^1	ADCC index^2	Responder patients^1	ADCC index^2	Responder patients^1	ADCC index^2
4-1BB							62 %	54
CD39					83 %	48
CD73	47 %	36
Galectin-9					44 %	48	49 %	36			62 %	12
GITR	41 %	192	71 %	144			42 %	54
ICOS							56 %	9
IL-21R	47 %	32					45 %	54
LAP					73 %	256			93 %	36	91 %	32
Neuropilin-1					41 %	72
TIGIT	60 %	192	57 %	96			72 %	54
TNFR2					53 %	48

¹ Percentage of the patients who showed overexpression of the marker (i.e., the patients in whom Treg marker expression level was higher than the mean+2SD value of Treg marker expression in HTs) and thus had a good probability of responding to the treatment. The marker for which the percentage of responder patients was higher than 40% are shown.

² The ADCC index was calculated as shown in Figure 6. An ADCC index equal or higher than 48 was considered relevant and reported in a grey background.

Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, Angell H, Fredriksen T, Lafontaine L, Berger A, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39:782–95. doi:10.1016/j.immuni.2013.10.003. PMID:24138885

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