Evidence map›Paper›PMID 33202676›Full record

ArticleCancers2020

Tumor MHC Expression Guides First-Line Immunotherapy Selection in Melanoma.

Elena Shklovskaya, Jenny H Lee, Su Yin Lim, Ashleigh Stewart, Bernadette Pedersen, Peter Ferguson, Robyn Pm Saw, John F Thompson, Brindha Shivalingam, Matteo S Carlino and 5 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.5field-weighted citation impact, top 8% 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

33 citing papers in PubMed, 41 citations in OpenAlex.

  1. Trial
  2. Trial
  3. CD47 and FOXP3Cancers · 2026
    Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. MHC-I-Driven Antitumor Immunity Counterbalances Low Absorbed Doses of Radiopharmaceutical Therapy.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Review
  19. Article
  20. 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

15 authors at 1 institution in 1 country.

Elena ShklovskayaFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Jenny H LeeFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Su Yin LimFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Ashleigh StewartFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Bernadette PedersenFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Peter FergusonMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.ORCID 0000-0002-8335-0406
Robyn Pm SawMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.
John F ThompsonMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.ORCID 0000-0002-2816-2496
Brindha ShivalingamMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.
Matteo S CarlinoMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.
Richard A ScolyerMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.ORCID 0000-0002-8991-0013
Alexander M MenziesMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.
Georgina V LongMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia.
Richard F KeffordFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Helen RizosFaculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.ORCID 0000-0002-2094-9198
The University of Sydney · AU

Funding

National Health and Medical Research Council of Australia (NHMRC) Program Grant 10930
6 · The paper itself

Abstract

Immunotherapy targeting T-cell inhibitory receptors, namely programmed cell death-1 (PD-1) and/or cytotoxic T-lymphocyte associated protein-4 (CTLA-4), leads to durable responses in a proportion of patients with advanced metastatic melanoma. Combination immunotherapy results in higher rates of response compared to anti-PD-1 monotherapy, at the expense of higher toxicity. Currently, there are no robust molecular biomarkers for the selection of first-line immunotherapy. We used flow cytometry to profile pretreatment tumor biopsies from 36 melanoma patients treated with anti-PD-1 or combination (anti-PD-1 plus anti-CTLA-4) immunotherapy. A novel quantitative score was developed to determine the tumor cell expression of antigen-presenting MHC class I (MHC-I) molecules, and to correlate expression data with treatment response. Melanoma MHC-I expression was intact in all tumors derived from patients who demonstrated durable response to anti-PD-1 monotherapy. In contrast, melanoma MHC-I expression was low in 67% of tumors derived from patients with durable response to combination immunotherapy. Compared to MHC-I high tumors, MHC-I low tumors displayed reduced T-cell infiltration and a myeloid cell-enriched microenvironment. Our data emphasize the importance of robust MHC-I expression for anti-PD-1 monotherapy response and provide a rationale for the selection of combination immunotherapy as the first-line treatment in MHC-I low melanoma.

Indexed as

anti-PD-1combination immunotherapyimmune checkpoint blockademajor histocompatibility (MHC) class Imetastatic melanoma

Identifiers

PMID33202676
PMCPMC7696726
OpenAlexW3099522598

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.