Evidence map›Paper›PMID 38425989›Full record

ArticleTherapeutic advances in medical oncology2024

Methylated ctDNA predicts early recurrence risk in patients undergoing resection of initially unresectable colorectal cancer liver metastases.

Zhi-Gang Chen, Xiao-Meng Ji, Yu-Xia Xu, William Pat Fong, Xiao-Yun Liu, Jie-Ying Liang, Qiong Tan, Lei Wen, Yan-Yu Cai, De-Shen Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Zhi-Gang ChenState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Xiao-Meng JiState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Yu-Xia XuState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
William Pat FongState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Xiao-Yun LiuState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Jie-Ying LiangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Qiong TanState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Lei WenState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
Yan-Yu CaiState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.
De-Shen WangState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.ORCID https://orcid.org/0000-0001-9657-4380
Yu-Hong LiState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, P.R. China.ORCID https://orcid.org/0000-0002-5710-9096
Sun Yat-sen University · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with initially unresectable colorectal cancer liver metastases (IU-CRLM) might benefit from using an effective systemic treatment followed by resection of liver metastases but the curative success rate is quite low. Indeed, nearly one-third of patients exhibit early recurrence within the first 6 months after surgery, and these individuals often have poor overall survival. Objectives: This study aims to clarify the application value of serial circulating tumor DNA (ctDNA) analysis in predicting the clinical outcome of IU-CRLM patients following liver metastasectomy. Design: A retrospective study was conducted on a cohort of patients with IU-CRLM between February 2018 and April 2021. Methods: Plasma samples at different time points during CRLM treatment [baseline (BL), preoperation (PRE), postoperation (POST), end-of-treatment (EOT), and progressive disease (PD)] were retrospectively collected from patients with initially unresectable CRLM enrolled at the Sun Yat-sen University Cancer Center. Dynamic changes of SEPTIN 9 (SEPT9) and Neuropeptide Y (NPY) methylated circulating tumor DNA (MetctDNA) levels in serial plasma samples were detected using droplet-digital PCR (ddPCR). Results: SEPT9 and NPY genes were hypermethylated in colon cancer cell lines and tissues while no difference was observed between primary and metastatic tumors. Patients with MetctDNA positive at POST or EOT had significantly lower recurrence-free survival (RFS) compared to patients with MetctDNA negative at these time points [POST: Hazard ratio (HR) 9.44, 95% confidence interval (CI) 5.15-17.30, Conclusion: Our study confirmed that serial ctDNA analysis of NPY and SEPT9 gene methylation could effectively predict early recurrence in IU-CRLM patients, especially at POST and EOT.

Indexed as

circulating tumor DNAcolorectal liver metastasesearly recurrenceinitially unresectableprognosis

Identifiers

PMID38425989
PMCPMC10903215
OpenAlexW4392250475

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LicenceCC BY-NC
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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.