Evidence map›Paper›PMID 31578273›Full record

ReviewThe oncologist2020

Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence.

Samuel J Klempner, David Fabrizio, Shalmali Bane, Marcia Reinhart, Tim Peoples, Siraj M Ali, Ethan S Sokol, Garrett Frampton, Alexa B Schrock, Rachel Anhorn and 1 more

Open access · bronzeAbstract readReview
In one paragraph

Review in The oncologist, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 249 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
249citing papers in PubMed, 6 pooled it
18.4field-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

249 citing papers in PubMed, 6 syntheses or guidelines pooled it, 399 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Guideline
  7. TAPISTRY: A Phase II Study of Atezolizumab in Patients with Tumor Mutational Burden-High Tumors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Trial
  8. Trial
  9. MRTX-500 Phase 2 Trial: Sitravatinib With Nivolumab in Patients With Nonsquamous NSCLC Progressing On or After Checkpoint Inhibitor Therapy or Chemotherapy.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2023
    Trial
  10. Trial
  11. Trial
  12. Review
  13. Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Article

189 more citing papers are in PubMed but not listed here.

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

11 authors at 5 institutions in 1 country.

Samuel J KlempnerThe Angeles Clinic and Research Institute, Los Angeles, California, USA.ORCID 0000-0002-4062-0808
David FabrizioFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Shalmali BaneAnalysis Group, Inc., Menlo Park, California, USA.ORCID 0000-0002-4074-3437
Marcia ReinhartAnalysis Group, Inc., Menlo Park, California, USA.
Tim PeoplesAmgen Inc., Thousand Oaks, California, USA.
Siraj M AliFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Ethan S SokolFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Garrett FramptonFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Alexa B SchrockFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Rachel AnhornFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Prasanth ReddyFoundation Medicine, Inc., Cambridge, Massachusetts, USA.
Foundation Medicine (United States)Amgen (United States) · USAnalysis Group (United States) · USCedars-Sinai Medical Center · USMenlo School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment with immune checkpoint inhibitors (ICPIs) extends survival in a proportion of patients across multiple cancers. Tumor mutational burden (TMB)-the number of somatic mutations per DNA megabase (Mb)-has emerged as a proxy for neoantigen burden that is an independent biomarker associated with ICPI outcomes. Based on findings from recent studies, TMB can be reliably estimated using validated algorithms from next-generation sequencing assays that interrogate a sufficiently large subset of the exome as an alternative to whole-exome sequencing. Biological processes contributing to elevated TMB can result from exposure to cigarette smoke and ultraviolet radiation, from deleterious mutations in mismatch repair leading to microsatellite instability, or from mutations in the DNA repair machinery. A variety of clinical studies have shown that patients with higher TMB experience longer survival and greater response rates following treatment with ICPIs compared with those who have lower TMB levels; this includes a prospective randomized clinical trial that found a TMB threshold of ≥10 mutations per Mb to be predictive of longer progression-free survival in patients with non-small cell lung cancer. Multiple trials are underway to validate the predictive values of TMB across cancer types and in patients treated with other immunotherapies. Here we review the rationale, algorithm development methodology, and existing clinical data supporting the use of TMB as a predictive biomarker for treatment with ICPIs. We discuss emerging roles for TMB and its potential future value for stratifying patients according to their likelihood of ICPI treatment response. IMPLICATIONS FOR PRACTICE: Tumor mutational burden (TMB) is a newly established independent predictor of immune checkpoint inhibitor (ICPI) treatment outcome across multiple tumor types. Certain next-generation sequencing-based techniques allow TMB to be reliably estimated from a subset of the exome without the use of whole-exome sequencing, thus facilitating the adoption of TMB assessment in community oncology settings. Analyses of multiple clinical trials across several cancer types have demonstrated that TMB stratifies patients who are receiving ICPIs by response rate and survival. TMB, alongside other genomic biomarkers, may provide complementary information in selecting patients for ICPI-based therapies.

Indexed as

Antibodies, MonoclonalBiomarkers, TumorHumansImmunotherapyMutationTreatment OutcomeTumor BurdenAntibodies, MonoclonalBiomarkers, TumorAntibodies/therapeutic useDNADNA mutational analysisGenesNeoplasmProgrammed cell death 1 receptorSequence analysis

Identifiers

PMID31578273
PMCPMC6964127
OpenAlexW2978209487

What OpenQuestion holds

Textmetadata
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.