Evidence map›Paper›PMID 35038827›Full record

ArticleCancer research and treatment2022

Histopathologic and Molecular Biomarkers of PD-1/PD-L1 Inhibitor Treatment Response among Patients with Microsatellite Instability‒High Colon Cancer.

Jaewon Hyung, Eun Jeong Cho, Jihun Kim, Jwa Hoon Kim, Jeong Eun Kim, Yong Sang Hong, Tae Won Kim, Chang Ohk Sung, Sun Young Kim

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 3 institutions in 1 country.

Jaewon HyungDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Eun Jeong ChoAsan Center for Cancer Genome Discovery, Asan Institute for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Jihun KimDepartment of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Jwa Hoon KimDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Jeong Eun KimDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Yong Sang HongDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Tae Won KimDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Chang Ohk SungAsan Center for Cancer Genome Discovery, Asan Institute for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Sun Young KimDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Asan Medical Center · KRUlsan College · KRUniversity of Ulsan · KR

Funding

Korea Health Industry Development InstituteMinistry of Health and Welfare HI18C2383
6 · The paper itself

Abstract

purposeRecent clinical trials have reported response rates < 50% among patients treated with programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors for microsatellite instability‒high (MSI-H) colorectal cancer (CRC), and factors predicting treatment response have not been fully identified. This study aimed to identify potential biomarkers of PD-1/PD-L1 inhibitor treatment response among patients with MSI-H CRC. MATERIALS AND

methodsMSI-H CRC patients enrolled in three clinical trials of PD-1/PD-L1 blockade at Asan Medical Center (Seoul, Republic of Korea) were screened and classified into two groups according to treatment response. Their histopathologic features and expression of 730 immune-related genes from the NanoString platform were evaluated, and a machine learning-based classification model was built to predict treatment response among MSI-H CRCs patients.

resultsA total of 27 patients (15 responders, 12 non-responders) were included. A high degree of lymphocytic/neutrophilic infiltration and an expansile tumor border were associated with treatment response and prolonged progression-free survival (PFS), while mucinous/signet-ring cell carcinoma was associated with a lack of treatment response and short PFS. Gene expression profiles revealed that the interferon-γ response pathway was enriched in the responder group. Of the top eight differentially expressed immune-related genes, PRAME had the highest fold change in the responder group. Higher expression of PRAME was independently associated with better PFS along with histologic subtypes in the multivariate analysis. The classification model using these genes showed good performance for predicting treatment response.

conclusionWe identified histologic and immune-related gene expression characteristics associated with treatment response in MSI-H CRC, which may contribute to optimal patient stratification.

Indexed as

Colonic NeoplasmsColorectal NeoplasmsB7-H1 AntigenBiomarkers, TumorHumansImmune Checkpoint InhibitorsInterferon-gammaMicrosatellite InstabilityProgrammed Cell Death 1 ReceptorB7-H1 AntigenBiomarkers, TumorImmune Checkpoint InhibitorsInterferon-gammaProgrammed Cell Death 1 ReceptorBiomarkerColonic neoplasmsHistologyImmune checkpoint inhibitorsMachine learningMicrosatellite instabilityTranscriptome profiles

Identifiers

PMID35038827
PMCPMC9582482
OpenAlexW4205689050

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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.