Your browser doesn't support javascript.
loading
Predicting disease recurrence in limited disease small cell lung cancer using cell-free DNA-based mutation and fragmentome analyses.
Park, Sehhoon; Kang, Jun-Kyu; Lee, Naeun; Lee, Se-Hoon; Kim, Hwang-Phill; Kim, Su Yeon; Kim, Tae-You; Kim, Hyemin; Jung, Hyun Ae; Sun, Jong-Mu; Ahn, Jin Seok; Ahn, Myung-Ju; Park, Keunchil.
Afiliación
  • Park S; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Kang JK; IMBdx, Inc., Seoul, Republic of Korea.
  • Lee N; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Lee SH; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Kim HP; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Kim SY; IMBdx, Inc., Seoul, Republic of Korea.
  • Kim TY; IMBdx, Inc., Seoul, Republic of Korea.
  • Kim H; IMBdx, Inc., Seoul, Republic of Korea.
  • Jung HA; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Sun JM; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Ahn JS; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Ahn MJ; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Park K; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Transl Lung Cancer Res ; 13(2): 280-291, 2024 Feb 29.
Article en En | MEDLINE | ID: mdl-38496698
ABSTRACT

Background:

Limited disease (LD) small cell lung cancer (SCLC) treated with definitive concurrent chemoradiotherapy (CCRT) potentially experience disease recurrence. We investigated the feasibility of circulating-tumor DNA (ctDNA)-based genomic and fragmentome analyses to assess the risk of recurrence.

Methods:

Targeted sequencing was conducted using pre-treatment and on-treatment blood samples from definitive CCRT-treated patients with LD-SCLC (n=50). Based on 12-month recurrence-free survival (RFS), patients were categorized into persistent-response (PeR, n=29) and non-PeR (n=21) groups. Fragmentome analysis was conducted using ctDNA fragments of different lengths P1 (100-155 bp) and P2 (160-180 bp).

Results:

Patients with TP53 (n=15) and RB1 (n=11) mutation in on-treatment samples demonstrated significantly shorter RFS than patients with wild-type (WT) (P=0.05, P=0.0014, respectively). Fragmentome analysis of all available on-treatment samples (n=26) revealed that the non-PeR group (n=10) had a significantly higher P1 range (P=0.003) and lower P2 range (P=0.002). The areas under the curves for P1, P2, and the fragmentation ratio (P1/P2) in distinguishing the PeR and non-PeR were 0.850, 0.725, and 0.900, respectively. Using optimal cut-off, longer RFSs were found with the low-fragmentation-ratio group than with the high-fragmentation-ratio group (not reached vs. 7.6 months, P=0.002). Patients with both WT RB1 and a low-fragmentation-ratio (n=10) showed better outcomes than patients with both mutated RB1 and a high-fragmentation-ratio (n=10; hazard ratio, 7.55; 95% confidence interval 2.14-26.6; P=0.002).

Conclusions:

RB1 mutations and high fragmentation ratios correlated with early disease recurrence. Analyzing ctDNA could help in predicting early treatment failure and making clinical decisions for high-risk patients.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Transl Lung Cancer Res Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Transl Lung Cancer Res Año: 2024 Tipo del documento: Article