Evidence map›Paper›PMID 34895481›Full record

ArticleThe Lancet. Oncology2022

HLA-A*03 and response to immune checkpoint blockade in cancer: an epidemiological biomarker study.

Vivek Naranbhai, Mathias Viard, Michael Dean, Stefan Groha, David A Braun, Chris Labaki, Sachet A Shukla, Yuko Yuki, Parantu Shah, Kevin Chin and 7 more

Open access · greenAbstract read
In one paragraph

Article in The Lancet. Oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
8.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 1 synthesis or guideline pooled it, 125 citations in OpenAlex.

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  16. Regulatory polymorphisms ofJournal for immunotherapy of cancer · 2025
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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 8 institutions in 3 countries.

Vivek NaranbhaiMassachusetts General Hospital, Boston, MA, USA; Dana-Farber Cancer Institute, Boston, MA, USA; Centre for the AIDS Programme of Research In South Africa, Durban, South Africa.
Mathias ViardBasic Science Programme, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, USA.
Michael DeanLaboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Stefan GrohaDana-Farber Cancer Institute, Boston, MA, USA.
David A BraunDana-Farber Cancer Institute, Boston, MA, USA.
Chris LabakiDana-Farber Cancer Institute, Boston, MA, USA.
Sachet A ShuklaDana-Farber Cancer Institute, Boston, MA, USA.
Yuko YukiBasic Science Programme, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, USA.
Parantu ShahBioinformatics, Department of Translational Medicine and Global Clinical Development, EMD Serono Research and Development Institute, Merck KGaA, Darmstadt, Germany.
Kevin ChinImmunooncology, EMD Serono Research and Development Institute, Merck KGaA, Darmstadt, Germany.
Megan Wind-RotoloBristol-Myers Squibb, New York, NY, USA.
Xinmeng Jasmine MuComputational Biology, Pfizer, San Diego, CA, USA.
Paul B RobbinsTranslational Oncology, Pfizer, San Diego, CA, USA.
Alexander GusevDana-Farber Cancer Institute, Boston, MA, USA.
Toni K ChoueiriDana-Farber Cancer Institute, Boston, MA, USA.
James L GulleyGenitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Mary CarringtonBasic Science Programme, Frederick National Laboratory for Cancer Research in the Laboratory of Integrative Cancer Immunology, National Cancer Institute, Bethesda, MD, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA. Electronic address: carringm@mail.nih.gov.
Dana-Farber Cancer Institute · USFrederick National Laboratory for Cancer Research · USMerck (Germany) · DENational Cancer Institute · USPfizer (United States) · USBristol-Myers Squibb (United States) · USMassachusetts General Hospital · USNational Institutes of Health · US

Funding

Treating the P13-Kinase/AKTP50CA101942 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI David McDermott · 2003 to 2026
$53.4M
Cancer Therapy Clinical Trials Using Novel Recombinant VaccinesZIABC010666 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GULLEY, JAMES L. · 2009 to 2025
$22.4M
Effects of genetic polymorphism in MHC, KIR, and related loci on human diseaseZIABC010791 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI CARRINGTON, MARY N. · 2009 to 2025
$18.2M
(PQ3) A functional genomic approach to identification and interpretation of germline-tumor genetic interactionsR01CA227237 · NCI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER, ZAITLEN, NOAH A · 2018 to 2022
$3.5M
Cellular TherapyZIABC012067 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GULLEY, JAMES L. · 2022 to 2022
$286k
CCR NIH HHS HHSN261200800001CIntramural NIH HHS Z99 CA999999NCI NIH HHS HHSN261200800001ENCI NIH HHS P50 CA101942NCI NIH HHS R01 CA227237
6 · The paper itself

Abstract

backgroundPredictive biomarkers could allow more precise use of immune checkpoint inhibitors (ICIs) in treating advanced cancers. Given the central role of HLA molecules in immunity, variation at the HLA loci could differentially affect the response to ICIs. The aim of this epidemiological study was to determine the effect of HLA-A*03 as a biomarker for predicting response to immunotherapy.

methodsIn this epidemiological study, we investigated the clinical outcomes (overall survival, progression free survival, and objective response rate) after treatment for advanced cancer in eight cohorts of patients: three observational cohorts of patients with various types of advanced tumours (the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets [MSK-IMPACT] cohort, the Dana-Farber Cancer Institute [DFCI] Profile cohort, and The Cancer Genome Atlas) and five clinical trials of patients with advanced bladder cancer (JAVELIN Solid Tumour) or renal cell carcinoma (CheckMate-009, CheckMate-010, CheckMate-025, and JAVELIN Renal 101). In total, these cohorts included 3335 patients treated with various ICI agents (anti-PD-1, anti-PD-L1, and anti-CTLA-4 inhibitors) and 10 917 patients treated with non-ICI cancer-directed therapeutic approaches. We initially modelled the association of HLA amino-acid variation with overall survival in the MSK-IMPACT discovery cohort, followed by a detailed analysis of the association between HLA-A*03 and clinical outcomes in MSK-IMPACT, with replication in the additional cohorts (two further observational cohorts and five clinical trials).

findingsHLA-A*03 was associated in an additive manner with reduced overall survival after ICI treatment in the MSK-IMPACT cohort (HR 1·48 per HLA-A*03 allele [95% CI 1·20-1·82], p=0·00022), the validation DFCI Profile cohort (HR 1·22 per HLA-A*03 allele, 1·05-1·42; p=0·0097), and in the JAVELIN Solid Tumour clinical trial for bladder cancer (HR 1·36 per HLA-A*03 allele, 1·01-1·85; p=0·047). The HLA-A*03 effect was observed across ICI agents and tumour types, but not in patients treated with alternative therapies. Patients with HLA-A*03 had shorter progression-free survival in the pooled patient population from the three CheckMate clinical trials of nivolumab for renal cell carcinoma (HR 1·31, 1·01-1·71; p=0·044), but not in those receiving control (everolimus) therapies. Objective responses were observed in none of eight HLA-A*03 homozygotes in the ICI group (compared with 59 [26·6%] of 222 HLA-A*03 non-carriers and 13 (17·1%) of 76 HLA-A*03 heterozygotes). HLA-A*03 was associated with shorter progression-free survival in patients receiving ICI in the JAVELIN Renal 101 randomised clinical trial for renal cell carcinoma (avelumab plus axitinib; HR 1·59 per HLA-A*03 allele, 1·16-2·16; p=0·0036), but not in those receiving control (sunitinib) therapy. Objective responses were recorded in one (12·5%) of eight HLA-A*03 homozygotes in the ICI group (compared with 162 [63·8%] of 254 HLA-A*03 non-carriers and 40 [55·6%] of 72 HLA-A*03 heterozygotes). HLA-A*03 was associated with impaired outcome in meta-analysis of all 3335 patients treated with ICI at genome-wide significance (p=2·01 × 10

fundingNational Institutes of Health, Merck KGaA, and Pfizer.

Indexed as

AllelesBiomarkersEpidemiologic StudiesHLA-A3 AntigenHumansImmune Checkpoint InhibitorsNeoplasmsBiomarkersHLA-A*03 antigenHLA-A3 AntigenImmune Checkpoint Inhibitors

Identifiers

PMID34895481
PMCPMC8742225
OpenAlexW4200548051

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.