Unraveling tumour microenvironment heterogeneity in nasopharyngeal carcinoma identifies biologically distinct immune subtypes predicting prognosis and immunotherapy responses

Abstract

Currently, there is no strong evidence of the well-established biomarkers for immune checkpoint inhibitors (ICIs) in nasopharyngeal carcinoma (NPC). Here, we aimed to reveal the heterogeneity of tumour microenvironment (TME) through virtual microdissection of gene expression profiles. An immune-enriched subtype was identified in 38% (43/113) of patients, which was characterized by significant enrichment of immune cells or immune responses. The remaining patients were therefore classified as a non-Immune Subtype (non-IS), which exhibited highly proliferative features. Then we identified a tumour immune evasion state within the immune-enriched subtype (18/43, 42%), in which high expression of exclusion- and dysfunction-related signatures was observed. These subgroups were designated the Evaded and Active Immune Subtype (E-IS and A-IS), respectively. We further demonstrated that A-IS predicted favourable survival and improved ICI response as compared to E-IS and non-IS. In summary, this study introduces the novel immune subtypes and demonstrates their feasibility in tailoring immunotherapeutic strategies.

Keywords: Gene expression profiles; Immunotherapy responses; Nasopharyngeal carcinoma; Prognosis; Tumour microenvironment; Virtual microdissection.

Fig. 1

Identification of three distinct tumour microenvironment-based immune subtypes. a An immune-enriched subtype (43/113, 38%; green bar) and a non-Immune Subtype (non-IS) (70/113, 62%; grey bar) were identified using an NMF algorithm in the training cohort. The immune-enriched subtype was further subdivided into Evaded (18/113, 16%; purple bar) and Active (25/113, 22%; orange bar) Immune Subtypes (E-IS and A-IS, respectively), using nearest template prediction (NTP) analysis with a signature identifying the activated stroma response. In the heatmap, high and low ssGSEA scores are represented in red and blue, respectively. The presence of an activated stroma signature is indicated in red and its absence is in grey. b-d Box plots showing expression of exclusion-related (b), dysfunctional-related (c), and ICI response-related (d) signatures between E-IS, A-IS, and non-IS. The box plot centre corresponds to the median, with the box and whiskers corresponding to the interquartile range and 1.5 × interquartile range, respectively. P-values were based on the Kruskal–Wallis rank-sum test. CAF, cancer-associated fibroblast; ECM, extracellular matrix; GEP, gene expression profile; ICI, immune checkpoint inhibitor; MDSC, myeloid-derived suppressor cell; NMF, non-negative matrix factorization; NPC, nasopharyngeal carcinoma; ssGSEA, single-sample gene set enrichment analysis; TAM, tumour-associated macrophage

Fig. 2

Verification of the immune subtypes in validation cohort 1. a Heatmap representation of the expression of immune-related signatures between A-IS, E-IS, and non-IS in validation cohort 1 (n = 150). In the heatmap, high and low ssGSEA scores are represented in red and blue, respectively. The presence and molecular characteristics of the immune subtypes were successfully validated. b–e Kaplan–Meier curves for progression-free survival (b), overall survival (c), distant failure-free survival (d), and locoregional failure-free survival (e) according to immune subtypes in validation cohort 1 (n = 150). Cox regression HRs and 95% CIs obtained after correcting for age (>45 vs. ≤45 years), sex (male vs. female), T (T3–4 vs. T1–2) and N (N3–4 vs. N0–1) categories, and plasma EBV DNA (>2,000 vs. ≤2,000 copies/mL) are shown along with the corresponding Cox regression P-values. A-IS, active immune subtype; CAF, cancer-associated fibroblast; EBV, Epstein–Barr virus; ECM, extracellular matrix; E-IS, evaded immune subtype; MDSC, myeloid-derived suppressor cell; non-IS, non-immune subtype; ssGSEA, single-sample gene set enrichment analysis; TAM, tumour-associated macrophage

Fig. 3

Verification of the immune subtypes in validation cohort 2 (ICI). a Heatmap representation of the tumour response and expression of immune-related signatures in A-IS, E-IS, and non-IS in 32 NPC patients receiving anti-PD-1 antibody combined with chemotherapy from validation cohort 2 (ICI). Tumour response was assessed after three cycles of ICI plus chemotherapy. In the heatmap, high and low ssGSEA scores are represented in red and blue, respectively. The presence and molecular characteristics of the immune subtypes were successfully validated. b Change in plasma EBV DNA levels in A-IS, E-IS, and non-IS during the treatment course in the 32 patients with ICI plus chemotherapy treatment. c Waterfall plot showing changes from baseline in the sum of longest target lesion diameters for each of the 32 patients with ICI plus chemotherapy treatment. PR was defined as a ≥30% decrease from baseline in the sum of diameters. d Box plots showing changes from baseline in the sum of longest target lesion diameters in A-IS, E-IS, and non-IS for the 32 patients receiving ICI plus chemotherapy (left) and the 32 matched patients receiving chemotherapy alone (right). The box plot centre corresponds to the median, with the box and whiskers corresponding to the interquartile range and 1.5× interquartile range, respectively. P-values were based on the Kruskal–Wallis rank-sum test. A significant P-value in the interaction test between ICI treatment (ICI plus chemotherapy versus chemotherapy alone) and the immune subtypes on tumour shrinkage was identified (P = 0.045). A-IS, active immune subtype; CAF, cancer-associated fibroblast; Chemo, chemotherapy; CR, complete response; ECM, extracellular matrix; E-IS, evaded immune subtype; ICI, immune checkpoint inhibitor; MDSC, myeloid-derived suppressor cell; non-IS, non-immune subtype; PR, partial response; SD, stable disease; ssGSEA, single-sample gene set enrichment analysis; TAM, tumour-associated macrophage