# deltaHED predicts survival and immune evasion in PD‐1 blockade therapy: A multi‐cohort study across three cancer types

**Authors:** Jianying Xu, Xiaoli Wei, Jicheng Yao, Ujjwal Mukund Mahajan, Ulf Dietrich Kahlert, Run Shi, Kaiying Zhang, Ahmed Alnatsha, Zhengyi Qian, Fei Han, Fenghua Wang

PMC · DOI: 10.1002/ctm2.70595 · Clinical and Translational Medicine · 2026-01-28

## TL;DR

A new metric called deltaHED helps predict how well patients respond to PD-1 immunotherapy by measuring changes in immune-related genes across three cancer types.

## Contribution

deltaHED is a novel metric that integrates germline and tumour HLA-I divergence to predict immune evasion and survival in PD-1 therapy.

## Key findings

- High deltaHED correlates with increased tumour mutational burden and neoantigen load across three cancer types.
- High deltaHED predicts worse progression-free and overall survival in PD-1 blockade therapy.
- In esophageal cancer, high deltaHED is linked to immunotherapy outcomes but not chemotherapy.

## Abstract

The prognostic relevance of HLA class I (HLA‐I)‐mediated immunity in cancer immunotherapy remains unclear. We introduce deltaHED, a novel metric that quantifies evolutionary divergence between germline and tumour‐acquired HLA‐I alleles, integrating both inherited and somatic immunogenetic variation. Using whole‐exome sequencing, we analysed deltaHED across three independent cohorts: 164 patients with recurrent/metastatic nasopharyngeal carcinoma (RM/NPC) from the POLARIS‐02 trial (PD‐1 monotherapy), 88 melanoma patients receiving PD‐1 monotherapy, and 477 esophageal squamous cell carcinoma (ESCC) patients from the JUPITER‐06 trial (PD‐1 plus chemotherapy vs. chemotherapy alone). High deltaHED was significantly associated with increased tumour mutational burden and neoantigen load (p < .001), but predicted worse progression‐free survival (PFS) and overall survival (OS) in patients receiving PD‐1 blockade across all three cancers. In ESCC, this association was observed only in the immunotherapy arm, not in patients treated with chemotherapy alone. High deltaHED also correlated with increased mutations in antigen‐processing and T‐cell receptor pathways. These findings establish deltaHED as a clinically relevant biomarker of immune divergence with potential to improve patient stratification and guide personalised immunotherapy strategies.

deltaHED predicts survival and immune evasion in PD‐1 blockade therapy: a multi‐cohort study across three cancer types. deltaHED quantifies germlinesomatic HLA‐I divergence and predicts survival and immune evasion in PD‐1 blockade therapy. Across nasopharyngeal carcinoma, melanoma, and esophageal squamous cell carcinoma, high deltaHED is associated with poor prognosis and increased mutations affecting antigen presentation and T‐cell activation. (A) Germline HLA evolutionary divergence (HED) reflects the inherited diversity of human leukocyte antigen (HLA) alleles (e.g., HLA‐A:01:01, HLA‐A:02:01, HLA‐B:07:02, HLA‐B:08:01, HLA‐C:03:03, HLA‐C:07:01), enabling the presentation of diverse immunogenic antigens (different colour in ball) and potential of broad T‐cell activation. (B) Somatic HED: tumour cells undergo loss of heterozygosity (LOH), leading to the loss of specific HLA alleles (e.g., HLA‐A:01:01 LOH, HLA‐B :08:01 LOH, HLA‐C:07:01 LOH) and reduced antigen presentation, resulting in immune evasion. (C) deltaHED (quantifying HLA diversity loss): deltaHED is calculated as the difference between germline HED and somatic HED, reflecting the extent of tumour‐mediated HLA diversity loss. High deltaHED is associated with higher mutation percentage of antigen presentation pathway and poor survival in patients receiving PD‐1 blockade therapy (validated in nasopharyngeal carcinoma [NPC], melanoma, and esophageal squamous cell carcinoma [ESCC] cohorts). HLA alleles: red (HLA‐A), blue (HLA‐B), green (HLA‐C). T cells: green (activated), grey (inactivated). The abstract graph is created in https://BioRender.com.

## Linked entities

- **Genes:** HLA-A (major histocompatibility complex, class I, A) [NCBI Gene 3105], HLA-B (major histocompatibility complex, class I, B) [NCBI Gene 3106], HLA-C (major histocompatibility complex, class I, C) [NCBI Gene 3107]
- **Diseases:** nasopharyngeal carcinoma (MONDO:0015459), melanoma (MONDO:0005105), esophageal squamous cell carcinoma (MONDO:0005580)

## Full-text entities

- **Genes:** RNF113B (ring finger protein 113B) [NCBI Gene 140432] {aka RNF161, ZNF183L1, bA10G5.1}, TRBV20OR9-2 (T cell receptor beta variable 20/OR9-2 (non-functional)) [NCBI Gene 6962] {aka CDR3, TCRBV20S2, TCRBV2O, TCRBV2S2O}, HLA-B (major histocompatibility complex, class I, B) [NCBI Gene 3106] {aka AS, B-4901, HLAB}, EDA (ectodysplasin A) [NCBI Gene 1896] {aka ECTD1, ED1, ED1-A1, ED1-A2, EDA-A1, EDA-A2}, BPTF (bromodomain PHD finger transcription factor) [NCBI Gene 2186] {aka FAC1, FALZ, NEDDFL, NURF301}, BLM (BLM RecQ like helicase) [NCBI Gene 641] {aka BS, MGRISCE1, RECQ2, RECQL2, RECQL3}, CD274 (CD274 molecule) [NCBI Gene 29126] {aka ADMIO5, B7-H, B7H1, PD-L1, PDCD1L1, PDCD1LG1}, PDCD1 (programmed cell death 1) [NCBI Gene 5133] {aka ADMIO4, AIMTBS, CD279, PD-1, PD1, SLEB2}, HLA-A (major histocompatibility complex, class I, A) [NCBI Gene 3105] {aka HLAA}, ABCB5 (ATP binding cassette subfamily B member 5) [NCBI Gene 340273] {aka ABCB5alpha, ABCB5beta, EST422562}, HLA-C (major histocompatibility complex, class I, C) [NCBI Gene 3107] {aka D6S204, HLA-JY3, HLAC, HLC-C, MHC, PSORS1}, MORC1 (MORC family CW-type zinc finger 1) [NCBI Gene 27136] {aka CT33, MORC, ZCW6}
- **Diseases:** cancer (MESH:D009369), melanoma (MESH:D008545), ESCC (MESH:D000077277), NPC (MESH:D052556), gastrointestinal and non-small cell lung cancers (MESH:D002289), nasopharyngeal carcinoma (MESH:D000077274), OS (MESH:D011475), immune dysfunction (MESH:D007154), death (MESH:D003643)
- **Chemicals:** TMB (-), toripalimab (MESH:C000656314), acids (MESH:D000143)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12848521/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/PMC12848521/full.md

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Source: https://tomesphere.com/paper/PMC12848521