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. 2021 Nov;164(3):507-523.
doi: 10.1111/imm.13384. Epub 2021 Jun 21.

B2M gene expression shapes the immune landscape of lung adenocarcinoma and determines the response to immunotherapy

Affiliations

B2M gene expression shapes the immune landscape of lung adenocarcinoma and determines the response to immunotherapy

Yu Zhao et al. Immunology. 2021 Nov.

Abstract

Loss of the B2M gene is associated with tumour immune escape and resistance to immunotherapy. However, genetic alterations of the B2M gene are rare. We performed an integrative analysis of the mutational and transcriptional profiles of large cohorts of non-small-cell lung cancer (NSCLC) patients and found that epigenetic downregulation of B2M is common. B2M-low tumours exhibit a suppressive immune microenvironment characterized by reduced infiltration of immune cells of various lineages; in B2M-high tumours, more T and natural killer cells are present, but their activities are constrained by immune checkpoint molecules, indicating the diverse mechanisms of immune evasion. High levels of B2M mRNA, but not PD-L1, are correlated with an enhanced response to PD-1-based immunotherapy, suggesting its value for immunotherapy response prediction in solid tumours. Notably, a high tumour mutation burden (TMB) is associated with low B2M expression, which may explain the poor predictive value of the TMB in some situations. In syngeneic mouse models, genetic ablation of B2M in tumour cells causes resistance to PD-1-based immunotherapy, and B2M knockdown also diminishes the therapeutic efficacy. Moreover, forced expression of B2M in tumour models improves the response to immunotherapy, suggesting that B2M levels have significant impacts on treatment outcomes. Finally, we provide insight into the roles of transcription factors and KRAS mutations in B2M expression and the anticancer immune response. In conclusion, genetic and epigenetic regulation of B2M fundamentally shapes the NSCLC immune microenvironment and may determine the response to checkpoint blockade-based immunotherapy.

Keywords: B2M; immunotherapy; lung cancer; transcriptional regulation; tumour microenvironment.

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Conflict of interest statement

The authors declare that they have no potential conflicts of interest.

Figures

FIGURE 1
FIGURE 1
B2M downregulation in LUAD. B2M expression in LUAD tissues (a) or their paired adjacent normal lung tissues (b). (c–d) B2M expression in LUAD tissues compared with adjacent normal tissues in GSE116959 and ICGC data sets. (e) Protein levels of B2M in LUAD tissues compared with adjacent normal tissues in the CPTAC data set. (f) Representative images of IHC staining for B2M in LUAD tissues and adjacent normal lung tissues. (g) Quantification of the results in Figure (f)
FIGURE 2
FIGURE 2
B2M levels affect the immune landscape of lung cancer. (a) GSEA of B2Mhi LUAD tumours compared with B2Mlo tumours. (b, c) Stromal scores and immune scores in B2Mhi LUAD tumours vs. B2Mlo tumours. (d) B2M expression in the LUAD tumours of immunity‐H, ‐M, or ‐L. (e,f) CIBERSORT analysis of the fractions of infiltrated immune cells in the LUAD and GSE116959 datasets. (g) Differentially expressed immune‐related genes in LUAD B2Mhi tumours vs. B2Mlo tumours
FIGURE 3
FIGURE 3
Value of B2M levels in predicting the response to immunotherapy. (a,b) Levels of B2M or PD‐L1mRNA in melanoma patients treated with PD‐1 inhibition. (c,d) TMB scores in the LUAD tumours divided by the levels of B2M or PD‐L1. E, The average numbers of CD8+ T cells in five random images of IHC staining for CD8A in LUAD tissues. (f) The stacked histogram shows the numbers of patients with different levels of B2M and PD‐L1 based on IHC staining. (g) Representative images of LUAD tumours from two patients. (h–i) FACS analysis of B2M and PD‐L1 expression in MC38, B16, and CT26 cells. (j–k) Tumour volumes of subcutaneously implanted MC38 or CT26 tumours treated with α‐PD‐L1 or PBS as a control (*p < 0·05, **p < 0·01, ***p < 0·001, ****p < 0·0001 vs. control)
FIGURE 4
FIGURE 4
Modulation of B2M expression can determine the outcome of immunotherapy. (a) FACS analysis validated the loss of B2M expression on the cell surface in a proportion of cells infected with lentivirus carrying pLenti‐CRISPR‐mB2M‐sgRNA‐GFP (MC38‐sgB2M); cells infected with lentivirus carrying a nonspecific sgRNA (MC38‐sgNS) were used as a control. (b,c) Subcutaneously implanted MC38‐sgNS or MC38‐sgB2M tumours were treated with α‐PD‐L1 or PBS as a control. (d) FACS analysis validated B2M knockdown in MC38 cells (MC38‐shB2M) infected with lentivirus shRNA. (e,f) Mice bearing MC38‐shB2M or MC38‐shNS control tumours were treated with α‐PD‐L1 or PBS. (g–i) FACS analysis of T cells in single‐cell suspensions from MC38‐sgNS, MC38‐sgB2M, and MC38‐sgB2M‐2 tumours. (j) FACS analysis validated the overexpression of B2M in CT26 cells (B2MOE) compared to control cells (CON). (k–l) Subcutaneously implanted B2MOE or CON tumours were treated with anti‐PD‐L1 or PBS. (m) FACS analysis of T cells in B2MOE or CON tumours (*p < 0·05, **p < 0·01, ***p < 0·001, ****p < 0·0001 vs. control)
FIGURE 5
FIGURE 5
STAT5 may regulate B2M expression in lung cancer. (a) The TFs that are positively (red) or negatively (blue) correlated with B2M expression in the LUAD dataset (left panel) and their potential binding sites on the B2M promoter region (right panel). (b–e) H1975 lung cancer cells or NK92 cells were treated with the STAT5 inhibitor SH454 for 24 and 48 h, and the levels of STAT5, p‐STAT5, and B2M were assessed by Western blotting and real‐time PCR; GAPDH was used as an internal control (**p < 0·01 vs. control)
FIGURE 6
FIGURE 6
The association between B2M expression and recurrent mutations in lung cancer. (a) Recurrent mutations and their alteration profiles in the LUAD data set. (b) The levels of B2M in tumours with or without the indicated mutations in the LUAD data set
FIGURE 7
FIGURE 7
KRAS mutations suppress B2M expression in lung cancer. (a) Cell viability assay for H358 and H23 cells treated with ARS‐1620 at various concentrations for 96 h. (b,c) FACS analysis of B2M on the surface of H23 and H358 cells treated with AMG510 for 24 h. (d) Western blot demonstrating the levels of p‐ERK, ERK and B2M, with β‐catenin as a loading control. (e,f) Real‐time PCR results indicating B2M transcription upon AMG510 treatment for 24 h in H358 and H23 cells. (g) Mutant KRASG12V was introduced into the BEAS‐2B normal bronchial epithelial cell line, and B2M transcription was assessed by real‐time PCR. (h) Western blot showing the reduced B2M in BEAS‐2B cells overexpressing KRASG12V. (i–j) GSEA of the RNA‐seq results and the top 10 upregulated pathways upon treatment with ARS‐1620. (k) Tumour volumes of H358 xenografts in mice treated with AMG510 or vehicle (n = 5). (l) IHC staining for B2M in H358 xenografts treated with AMG510 or control (**p < 0·01 vs. control)

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