Evidence map›Paper›PMID 38859855›Full record

ArticleAmerican journal of cancer research2024

The transcriptomic expression pattern of immune checkpoints shows heterogeneity between and within cancer types.

Hirotaka Miyashita, Nicholas J Bevins, Kartheeswaran Thangathurai, Suzanna Lee, Sarabjot Pabla, Mary K Nesline, Sean T Glenn, Jeffrey M Conroy, Paul DePietro, Eitan Rubin and 3 more

Abstract read
In one paragraph

Article in American journal of cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Pancancer Analysis and the Oncogenic Role ofInternational journal of molecular sciences · 2026
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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

13 authors.

Hirotaka MiyashitaDepartment of Hematology and Oncology, Dartmouth Hitchcock Medical Center Lebanon, NH, USA.
Nicholas J BevinsDepartment of Pathology, University of California San Diego La Jolla, CA, USA.
Kartheeswaran ThangathuraiThe Shraga Segal Department for Microbiology, Immunology and Genetics, Ben-Gurion University of The Negev Beer Sheva, Israel.
Suzanna LeeCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center La Jolla, CA, USA.
Sarabjot PablaOmniSeq Inc. Buffalo, NY, USA.
Mary K NeslineOmniSeq Inc. Buffalo, NY, USA.
Sean T GlennOmniSeq Inc. Buffalo, NY, USA.
Jeffrey M ConroyOmniSeq Inc. Buffalo, NY, USA.
Paul DePietroOmniSeq Inc. Buffalo, NY, USA.
Eitan RubinThe Shraga Segal Department for Microbiology, Immunology and Genetics, Ben-Gurion University of The Negev Beer Sheva, Israel.
Jason K SicklickDivision of Surgical Oncology, Department of Surgery and Center for Personalized Cancer Therapy, University of California San Diego, La Jolla, CA, USA.
Shumei KatoCenter for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, UC San Diego Moores Cancer Center La Jolla, CA, USA.
Razelle KurzrockWorldwide Innovative Network (WIN) for Personalized Cancer Therapy Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptomic expression profiles of immune checkpoint markers are of interest in order to decipher the mechanisms of immunotherapy response and resistance. Overall, 514 patients with various solid tumors were retrospectively analyzed in this study. The RNA expression levels of tumor checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) were ranked from 0-100 percentile based on a reference population. The expression of each checkpoint was correlated with cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) by immunohistochemistry (IHC). The cohort included 30 different tumor types, with colorectal cancer being the most common (27%). When RNA percentile rank values were categorized as "Low" (0-24), "Intermediate" (25-74), and "High" (75-100), each patient had a distinctive portfolio of the categorical expression of 16 checkpoint markers. Association between some checkpoint markers and cancer types were observed; NOS2 showed significantly higher expression in colorectal and stomach cancer (P < 0.001). Principal component analysis demonstrated no clear association between combined RNA expression patterns of 16 checkpoint markers and cancer types, TMB, MSI or PD-L1 IHC. Immune checkpoint RNA expression varies from patient to patient, both within and between tumor types, though colorectal and stomach cancer showed the highest levels of NOS2, a mediator of inflammation and immunosuppression. There were no specific combined expression patterns correlated with MSI, TMB or PD-L1 IHC. Next generation immunotherapy trials may benefit from individual analysis of patient tumors as selection criteria for specific immunomodulatory approaches.

Indexed as

Immune checkpointmicrosatellite instabilityprincipal component analysisprogrammed death ligand 1transcriptometumor mutational burden

Identifiers

PMID38859855
PMCPMC11162686

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