Evidence map›Paper›PMID 31463717›Full record

ArticleJournal of cancer research and clinical oncology2019

Co-occurring genetic alterations predict distant metastasis and poor efficacy of first-line EGFR-TKIs in EGFR-mutant NSCLC.

Li-Li Deng, Ge Gao, Hong-Bin Deng, Feng Wang, Zhi-Hui Wang, Yu Yang

Abstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Cancers · 2020
    Article
  11. Article
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.

Li-Li Deng *Department of Oncology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150086, Heilongjiang, People's Republic of China.
Ge Gao *Department of Oncology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150086, Heilongjiang, People's Republic of China.
Hong-Bin Deng *Dental Hospital, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Nangang District, Harbin, 150001, Heilongjiang, People's Republic of China.
Feng WangDepartment of Oncology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150086, Heilongjiang, People's Republic of China.
Zhi-Hui WangDepartment of Oncology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150086, Heilongjiang, People's Republic of China.
Yu YangDepartment of Oncology, The Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Nangang District, Harbin, 150086, Heilongjiang, People's Republic of China. yangyuyyyy@126.com.ORCID http://orcid.org/0000-0002-3785-8663

Funding

Postdoctoral Scientific Research Developmental Fund provided by the Administration Office of Heilongjiang Postdoctoral Program Grant No. LBH-Q16143Wu Jieping medical foundation Grant No.320.6750.18050
6 · The paper itself

Abstract

purposeTo determine the frequency of co-occurring genes in non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation and the predictive effect of co-mutations on the efficacy of EGFR tyrosine kinase inhibitors (EGFR-TKIs).

methods54 patients with advanced NSCLC were tested for 422 clinically relevant genes by next-generation sequencing (NGS) before treatment. Among them, patients with EGFR mutation received first-line treatment of EGFR-TKIs. Progression-free survival (PFS) and objective response rate (ORR) were evaluated using Kaplan-Meier methods and compared between two groups using log-rank test.

resultsAmong 24 EGFR mutant and 30 EGFR wild-type patients, co-mutation rate was lower in patients with EGFR mutation (62.5% [15/24] vs 93.3% [28/30], p = 0.005). There was lower frequency for co-alterations in BRAF (0% [0/24] vs 20% [7/30], p = 0.033), NF1 (4.2% [1/24] vs 30% [9/30], p = 0.038) and RAS-RAF-MAPK pathway genes (16.6% [4/24] vs 56.7% [17/30], p = 0.003) in EGFR mutation group. 24 patients with EGFR mutation received first-line treatment of gefitinib or erlotinib, with an ORR of 83.3% and a median PFS of 12.3 months (95% CI 10.00-14.60). Co-mutation was associated with shorter median PFS (10.2 months [95% CI 5.20-15.20] vs 15.3 months [95% CI 12.09-15.81]; HR 0.29 [95% CI 0.10-0.82]; p = 0.014) in EGFR mutation cohort. Among patients with EGFR mutation and distant metastasis, median PFS was decreased in those with co-mutations (6.3 months [95% CI 3.25-9.35] vs 22.0 months[95% CI 12.10-31.90]; HR 0.12 [95% CI 0.00-5.87]; p = 0.007) and frequency of PIK3CA (0% [0/12] vs 41.7% [5/12], p = 0.037) and PI3K/AKT/mTOR pathway genes (0% [0/12] vs 50% [6/12], p = 0.014) was lower.

conclusionThe presence of co-mutations was lower in the EGFR mutation patients and reduces the efficacy of EGFR-TKI, especially in patients with distant metastases. Lower frequency of co-mutation in PIK3CA and PI3K/AKT/mTOR pathway genes may be responsible for promoting metastasis and limiting the efficacy of EGFR-TKIs.

Indexed as

Biomarkers, TumorMutationAgedAged, 80 and overAntineoplastic AgentsCarcinoma, Non-Small-Cell LungErbB ReceptorsFemaleHumansLung NeoplasmsMaleMiddle AgedNeoplasm MetastasisNeoplasm StagingPrognosisProtein Kinase InhibitorsAntineoplastic AgentsBiomarkers, TumorEGFR protein, humanErbB ReceptorsProtein Kinase InhibitorsCo-mutationEGFREGFR-TKIsNSCLC

Identifiers

PMID31463717
PMCPMC11810358

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.