Co-stimulatory and co-inhibitory Immune Markers in Solid Tumors With MET Alterations

Figures & data

Table 1. Patient characteristics.

Characteristics
	Total	Lung	Breast	Genitourinary	Colorectal
Sex
Female	8	3	5	0	0
Male	13	7	0	3	3
Age at diagnosis
Age range	27–81	53–81	42–56	62–66	27–67
Median age	66	68	56	65	59
<60	9	3	5	0	1
≥60	12	7	0	3	2
Stage
I	0	0	0	0	0
II	0	0	0	0	0
III	2	1	1	0	0
IV	19	9	4	3	3
Race
Caucasian	13	6	2	3	2
Asian	5	2	2	0	1
African American	3	2	1	0	0

Table 2. MET mutation therapies.

Primary site of disease	Histology	MET mutation	Other molecular markers	Treatment received	PFS, months	Outcome
Thoracic	Adenocarcinoma	D1010Y	CDK4 amplification, MDM2 amplification, RANBP2 I656M	Cisplatin and etoposide	3	Developed progression with new bony metastases and pleural effusion.
				Glesatinib	8	Tolerated well and had partial response; patient continued on treatment for 2 years.
Thoracic	Adenocarcinoma	D1373H	EGFR E746_A750del, CDK4 amplification, MDM2 amplification, FRS2 amplification, GLI1 amplification	Carboplatin and docetaxel	2	Completed four cycles and tolerated well; patient was then switched to erlotinib.
				Crizotinib	2	Upon detection of MET amplification, crizotinib was added to osimertinib but progressed in less than 3 months.
Thoracic	Large cell carcinoma with adenocarcinoma and squamous differentiation	exon 14 splice site 3028+1G>T	RBM10 E820 ^† , TP53 H193R-subclonal ^†	Crizotinib	6	Patient discontinued because of fluid retention and severe fatigue.
Thoracic	Adenocarcinoma	exon 14 splice site D1010H		Crizotinib	6	Continued for a year and tolerated well but unfortunately progressed with pleural effusion and increase in primary tumor.
Thoracic	Squamous cell carcinoma	exon 14 splice site 3028+1G>A	PIK3CA E545K, CTNNB1 W25 ^† , DNMT3A Y735C, MLL2 Q1023 ^†	Atezolizumab	N/A	Patient tolerated well and had exceptional response, with no recurrence of disease; continues with surveillance.

† It signifies that the mutation led to a premature stop codon and thus the protein is truncated.

N/A: Not applicable; PFS: Progression-free survival.

Figure 1. MET IHC scores.

(A) Box plot representing the staining intensity IHC scores of c-MET, p-MET, PD-L1 and CD4 per disease type (lung, colorectal, breast and GU cancer). IHC staining of lung, colorectal, breast and GU tumor tissue with MET, p-MET, CD4 and PD-L1 antibodies was scored on a scale from 0 (no staining/no protein expression) to 3+ (strong staining/high protein expression). Staining intensity scores of MET, p-MET, CD4 and PD-L1 are mean ± SE. Statistical analyses were conducted using GraphPad Prism 8 by one-way ANOVA, followed by Tukey's multiple comparison test. No significant differences were seen between groups. (B) IHC staining of MET, p-MET, CD4 and PD-L1 for each disease type (colorectal, breast, GU and lung cancer).

ANOVA: Analysis of variance; GU: Genitourinary; IHC: Immunohistochemical; SE: Standard error.

Figure 2. Mutational profile of MET patients.

MET patients are categorized by cancer primary site. The heatmap demonstrates the genomic profile of each patient's tumor as well as the total number of mutations identified through NGS testing. The number of mutations per patient is shown in the bar chart at the top, with a heatmap of the genomic alterations identified underneath. The different types of genomic alterations identified in this cohort were classified as amplification, deletion, frameshift, fusion, insertion, loss, non-sense, rearrangement, splice site and substitution.

NGS: Next-generation sequencing; GU: Genitourinary; NO: Number.

Figure 3. Immune gene expression across MET-mutated and MET wild-type tumors.

Z-scores for 770 genes assayed using the multiplex gene expression panel in each tumor sample, annotated with cancer type and MET status.

Figure 4. Summary of genes identified as differentially expressed by the nSolver and NanoStringDiff tools.

All genes passing the FDR cutoff p < 0.05 for both tools are plotted. See Supplementary Tables for full lists of genes identified by each individual tool.

FDR: False discovery rate.