Evidence map›Paper›PMID 32523802›Full record

ArticleOncoimmunology2020

HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer.

Yingxue Ren, Yesesri Cherukuri, Daniel P Wickland, Vivekananda Sarangi, Shulan Tian, Jodi M Carter, Aaron S Mansfield, Matthew S Block, Mark E Sherman, Keith L Knutson and 2 more

Open access · goldAbstract read
In one paragraph

Article in Oncoimmunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Public neoantigens in breast cancer immunotherapy (Review).International journal of molecular medicine · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Breast cancer vaccines for treatment and prevention.Breast cancer research and treatment · 2022
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Yingxue RenDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
Yesesri CherukuriDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
Daniel P WicklandDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
Vivekananda SarangiDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Shulan TianDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Jodi M CarterDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Aaron S MansfieldDivision of Medical Oncology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0002-9483-6903
Matthew S BlockDivision of Medical Oncology, Mayo Clinic, Rochester, MN, USA.
Mark E ShermanDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
Keith L KnutsonDepartment of Immunology, Mayo Clinic, Jacksonville, FL, USA.
Yi LinDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Yan W AsmannDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
WinnMed · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumors acquire numerous mutations during development and progression. When translated into proteins, these mutations give rise to neoantigens that can be recognized by T cells and generate antibodies, representing an exciting direction of cancer immunotherapy. While neoantigens have been reported in many cancer types, the profiling of neoantigens often focused on the class-I subtype that are presented to CD8 + T cells, and the relationship between neoantigen load and clinical outcomes was often inconsistent among cancer types. In this study, we described an informatics workflow, REAL-neo, for identification, quality control (QC), and prioritization of both class-I and class-II human leukocyte antigen (HLA) bound neoantigens that arise from somatic single nucleotide mutations (SNM), small insertions and deletions (INDEL), and gene fusions. We applied REAL-neo to 835 primary breast tumors in the Cancer Genome Atlas (TCGA) and performed comprehensive profiling and characterization of the detected neoantigens. We found recurrent HLA class-I and class-II restricted neoantigens across breast cancer cases, and uncovered associations between neoantigen load and clinical traits. Both class-I and class-II neoantigen loads from SNM and INDEL were found to predict overall survival independent of tumor mutational burden (TMB), breast cancer subtypes, tumor-infiltrating lymphocyte (TIL) levels, tumor stage, and age at diagnosis. Our study highlighted the importance of accurate and comprehensive neoantigen profiling and QC, and is the first to report the predictive value of neoantigen load for overall survival in breast cancer.

Indexed as

Antigens, NeoplasmBreast NeoplasmsFemaleHistocompatibility Antigens Class IHistocompatibility Antigens Class IIHumansImmunotherapyLymphocytes, Tumor-InfiltratingSurvival RateAntigens, NeoplasmHistocompatibility Antigens Class IHistocompatibility Antigens Class IIBreast cancerneoantigenoverall survivaltumor mutational burden

Identifiers

PMID32523802
PMCPMC7255108
OpenAlexW3015063619

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.