Evidence map›Paper›PMID 34599029›Full record

ArticleJournal for immunotherapy of cancer2021

Indication-specific tumor evolution and its impact on neoantigen targeting and biomarkers for individualized cancer immunotherapies.

Amy A Lo, Andrew Wallace, Daniel Oreper, Nicolas Lounsbury, Charles Havnar, Ximo Pechuan-Jorge, Thomas D Wu, Richard Bourgon, Ryan Jones, Katrina Krogh and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal for immunotherapy of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Neoantigen immunotherapy: a novel treatment for bladder cancer.Exploration of targeted anti-tumor therapy · 2025
    Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Sources of Cancer Neoantigens beyond Single-Nucleotide Variants.International journal of molecular sciences · 2022
    Review
  9. Article
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.

Amy A LoDepartment of Research Pathology, Genentech Inc, South San Francisco, California, USA lo.amy@gene.com oliver@init.bio.ORCID 0000-0002-8614-6734
Andrew WallaceDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA.
Daniel OreperDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA.
Nicolas LounsburyDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA.
Charles HavnarDepartment of Research Pathology, Genentech Inc, South San Francisco, California, USA.
Ximo Pechuan-JorgeDepartment of Cancer Immunology, Genentech Inc, South San Francisco, California, USA.
Thomas D WuDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA.
Richard BourgonDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA.
Ryan JonesDepartment of Pathology, Northwestern University, Chicago, Illinois, USA.
Katrina KroghDepartment of Pathology, Northwestern University, Chicago, Illinois, USA.
Guang-Yu YangDepartment of Pathology, Northwestern University, Chicago, Illinois, USA.
Oliver A ZillDepartment of Oncology Bioinformatics, Genentech Inc, South San Francisco, California, USA lo.amy@gene.com oliver@init.bio.ORCID 0000-0002-4329-2790
Northwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types.

methodsWe combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting.

resultsBranching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. In colorectal, renal, and bladder cancer, most tumors had few globally clonal neoantigens. Prioritizing mutations with higher purity-adjusted and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases.

conclusionsWe show that tumor type, multilesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection, and may also be important factors to consider in the development of biomarker strategies.

Indexed as

AdultAgedAged, 80 and overAnimalsAntigens, NeoplasmBiomarkers, TumorFemaleHumansImmunotherapyMaleMiceMiddle AgedNeoplasmsAntigens, NeoplasmBiomarkers, Tumorantigen-mediatedantigensbiomarkersclonal selectioncomputational biologyneoplasmtumorurinary bladder neoplasms

Identifiers

PMID34599029
PMCPMC8488717
OpenAlexW3202537907

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.