Evidence map›Paper›PMID 34999837›Full record

ArticleNeuro-oncology2022

Clinical reliability of genomic data obtained from spinal metastatic tumor samples.

Ori Barzilai, Axel Martin, Anne S Reiner, Ilya Laufer, Adam Schmitt, Mark H Bilsky

Abstract read
In one paragraph

Article in Neuro-oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Review
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  10. 2023 Canadian Urological Association guideline: Genetic testing in prostate cancer.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2023
    Article
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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

6 authors.

Ori BarzilaiDepartment of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.ORCID 0000-0002-4037-8716
Axel MartinDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Anne S ReinerDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.ORCID 0000-0002-1258-6112
Ilya LauferDepartment of Neurosurgery, New York University School of Medicine, New York, New York, USA.
Adam SchmittDepartment of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Mark H BilskyDepartment of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundThe role of tumor genomic profiling is rapidly growing as it results in targeted, personalized, cancer therapy. Though routinely used in clinical practice, there are no data exploring the reliability of genomic data obtained from spine metastases samples often leading to multiple biopsies in clinical practice. This study compares the genomic tumor landscape between spinal metastases and the corresponding primary tumors as well as between spinal metastases and visceral metastases.

methodsSpine tumor samples, obtained for routine clinical care from 2013 to 2019, were analyzed using MSK-IMPACT, a next-generation sequencing assay. These samples were matched to primary or metastatic tumors from the corresponding patients. A concordance rate for genomic alterations was calculated for matching sample pairs within patients for the primary and spinal metastatic tumor samples as well as for the matching sample pairs within patients for the spinal and visceral metastases. For a more robust and clinically relevant estimate of concordance, subgroup analyses of previously established driver mutations specific to the main primary tumor histologies were performed.

resultsEighty-four patients contributed next-generation sequencing data from a spinal metastasis and at least one other site of disease: 54 from the primary tumor, 39 had genomic tumor data from another, nonspinal metastasis, 12 patients participated in both subsets. For the cohort of matched primary tumors and spinal metastases (n = 54) comprised of mixed histologies, we found an average concordance rate of 96.97% for all genetic events, 97.17% for mutations, 100% for fusions, 89.81% for deletions, and 97.01% for amplifications across all matched samples. Notably, >25% of patients harbored at least one genetic variant between samples tested, though not specifically for known driver mutations. The average concordance rate of driver mutations was 96.99% for prostate cancer, 95.69% (P = .0004513) for lung cancer, and 96.43% for breast cancer. An average concordance of 99.02% was calculated for all genetic events between spine metastases and non-spinal metastases (n = 41) and, more specifically, a concordance rate of 98.91% was calculated between spine metastases and liver metastases (n = 12) which was the largest represented group of nonspine metastases.

conclusionSequencing data performed on spine tumor samples demonstrate a high concordance rate for genetic alterations between the primary tumor and spinal metastasis as well as between spinal metastases and other, visceral metastases, particularly for driver mutations. Spine tumor samples may be reliably used for genomic-based decision making in cancer care, particularly for prostate, NSCLC, and breast cancer.

Indexed as

Breast NeoplasmsLung NeoplasmsSpinal NeoplasmsGenomicsHigh-Throughput Nucleotide SequencingHumansMaleMutationReproducibility of Resultsgenomicmetastasesnext generation sequencingspinetumor

Identifiers

PMID34999837
PMCPMC9248391

What OpenQuestion holds

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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.