🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade

Science(2017)10.1126/science.aan6733Source: DataRank Database

Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade is a research paper published in Science (2017). On theSindex it has a DataRank of 1.3. It has been cited 6,550 times.

N/A
1.3DataRank · unranked
1.3
6550 citations · base score 8.8
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

The genomes of cancers deficient in mismatch repair contain exceptionally high numbers of somatic mutations. In a proof-of-concept study, we previously showed that colorectal cancers with mismatch repair deficiency were sensitive to immune checkpoint blockade with antibodies to programmed death receptor-1 (PD-1). We have now expanded this study to evaluate the efficacy of PD-1 blockade in patients with advanced mismatch repair-deficient cancers across 12 different tumor types. Objective radiographic responses were observed in 53% of patients, and complete responses were achieved in 21% of patients. Responses were durable, with median progression-free survival and overall survival still not reached. Functional analysis in a responding patient demonstrated rapid in vivo expansion of neoantigen-specific T cell clones that were reactive to mutant neopeptides found in the tumor. These data support the hypothesis that the large proportion of mutant neoantigens in mismatch repair-deficient cancers make them sensitive to immune checkpoint blockade, regardless of the cancers' tissue of origin.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 100%Citation Network 0%

        Base Score Contribution

        1.3

        From this paper's citation signal

        Citation Network Contribution

        0

        Citation network not refreshed for this result

        This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

        Learn more about DataRank methodology →
        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.

        Base score B(p)
        log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
        Network N(p)
        Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
        Damping factor d = 0.85
        DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
        Self-citations excluded
        Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

        Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

        Read the full methodology →

        Authors (51)

        Related Papers (10)

        Nature Biotechnology(2015)
        co-cited
        10.1038/nbt.3192