Literature DB >> 36183093

Circulating tumor DNA integrating tissue clonality detects minimal residual disease in resectable non-small-cell lung cancer.

Siwei Wang1, Ming Li1, Jingyuan Zhang2, Peng Xing1,3, Min Wu4, Fancheng Meng1, Feng Jiang1, Jie Wang5,6, Hua Bao4, Jianfeng Huang1, Binhui Ren1, Mingfeng Yu1, Ninglei Qiu1, Houhuai Li1, Fangliang Yuan1, Zhi Zhang1, Hui Jia1, Xinxin Lu1, Shuai Zhang1, Xiaojun Wang1, Youtao Xu1, Wenjia Xia1, Tongyan Liu1, Weizhang Xu1, Xinyu Xu2, Mengting Sun5,6, Xue Wu4, Yang Shao4, Qianghu Wang7,8, Juncheng Dai7,9,10, Mantang Qiu11, Jinke Wang12, Qin Zhang1, Lin Xu1,7, Hongbing Shen7,9,10, Rong Yin13,14,15,16.   

Abstract

BACKGROUND: Circulating tumor DNA (ctDNA) has been proven as a marker for detecting minimal residual diseases following systemic therapies in mid-to-late-stage non-small-cell lung cancers (NSCLCs) by multiple studies. However, fewer studies cast light on ctDNA-based MRD monitoring in early-to-mid-stage NSCLCs that received surgical resection as the standard of care.
METHODS: We prospectively recruited 128 patients with stage I-III NSCLCs who received curative surgical resections in our Lung Cancer Tempo-spatial Heterogeneity prospective cohort. Plasma samples were collected before the surgery, 7 days after the surgery, and every 3 months thereafter. Targeted sequencing was performed on a total of 628 plasma samples and 645 matched tumor samples using a panel covering 425 cancer-associated genes. Tissue clonal phylogeny of each patient was reconstructed and used to guide ctDNA detection.
RESULTS: The results demonstrated that ctDNA was more frequently detected in patients with higher stage diseases pre- and postsurgery. Positive ctDNA detection at as early as 7 days postsurgery identified high-risk patients with recurrence (HR = 3.90, P < 0.001). Our results also show that longitudinal ctDNA monitoring of at least two postsurgical time points indicated a significantly higher risk (HR = 7.59, P < 0.001), preceding radiographic relapse in 73.5% of patients by a median of 145 days. Further, clonal ctDNA mutations indicated a high-level specificity, and subclonal mutations informed the origin of tumor recurrence.
CONCLUSIONS: Longitudinal ctDNA surveillance integrating clonality information may stratify high-risk patients with disease recurrence and infer the evolutionary origin of ctDNA mutations.
© 2022. The Author(s).

Entities:  

Keywords:  Circulating tumor DNA; Liquid biopsy; Minimal residual disease; Non-small-cell lung cancer

Mesh:

Substances:

Year:  2022        PMID: 36183093      PMCID: PMC9526343          DOI: 10.1186/s13045-022-01355-8

Source DB:  PubMed          Journal:  J Hematol Oncol        ISSN: 1756-8722            Impact factor:   23.168


To the editor

Approximately 30–55% of non-small-cell lung cancer (NSCLC) patients developed recurrence despite curative resection [1]. Circulating tumor DNA (ctDNA) is shed by tumor cells and may serve as an effective prognostic marker following multiple therapeutic modalities [2-5]. However, it remained not fully understood to what extent serial ctDNA monitoring could help identify the risk of recurrence in resectable NSCLC. In this study, a total of 128 patients with resectable NSCLC were enrolled (Fig. 1A). Primary tumor and lymph node metastasis (LNM) samples were collected from curative surgeries as standard of care. Plasma samples were collected before surgery, 7 days after surgery, and every three months thereafter. Both tissue and plasma samples were sequenced using a comprehensive 425-gene panel (Fig. 1A, B). One patient was excluded during quality control (Additional files 1, 2: Table S1 and S2).
Fig. 1

Study design and ctDNA detection. a Workflow of sample collection, sample exclusion, and data analysis. b Schematic diagram illustrating the timeline for sample collection and the number of plasma samples available for analyses at each time point. c Proportions of patients that showed different presurgical and postsurgical ctDNA status. The results of ctDNA detection of all postsurgical samples were included. d Proportions of patients positive for presurgical (upper panel) and postsurgical (lower panel) plasma samples, stratified by pathology histology, TNM stage, LNM status, and smoking history

Study design and ctDNA detection. a Workflow of sample collection, sample exclusion, and data analysis. b Schematic diagram illustrating the timeline for sample collection and the number of plasma samples available for analyses at each time point. c Proportions of patients that showed different presurgical and postsurgical ctDNA status. The results of ctDNA detection of all postsurgical samples were included. d Proportions of patients positive for presurgical (upper panel) and postsurgical (lower panel) plasma samples, stratified by pathology histology, TNM stage, LNM status, and smoking history A total of 611 plasma and 593 tissue samples were included in the analyses (Fig. 1A, Additional file 4: Fig. S1). We reconstructed the clonal phylogeny of each patient from multi-region tissue sequencing to buttress the ctDNA detection (See Additional file 11: Methods). Near half (46.4%, 59/127) of the patients were ctDNA-negative throughout the investigation period. In 32.3% (41/127) of the patients, ctDNA was detected in at least one postsurgical plasma sample, most of whom (65.9%, 27/41) were ctDNA-positive in presurgical samples (Fig. 1C; Additional file 5: Fig. S2). As shown in Fig. 1D, patients with lung squamous cell carcinoma (LUSC) were more frequently ctDNA-positive than those with lung adenocarcinoma (LUAD). The detection rate correlated with TNM stages and LNM status, and smokers were found with a higher ctDNA-positive rate than non-smokers in presurgical instead of postsurgical results. Postsurgical ctDNA detection at as early as seven days after surgeries could indicate high risk of recurrence (HR = 3.90, P = 0.00011; Fig. 2A), independently of clinicopathological characteristics (multivariate-Cox: HR = 5.49, P = 0.002; Fig. 2B). ctDNA detection at following time points (3 months and 6 months) could also serve as prognostic markers (3 months—HR = 4.32, P < 0.0001; 6 months—HR = 6.19, P < 0.0001) and remained statistically significant after adjusted for clinicopathological characteristics (multivariate-Cox: 3 months—HR = 4.17, P < 0.001; 6 month—HR = 4.59, P < 0.003; Additional file 6: Fig. S3). Longitudinal ctDNA detection accurately identified high risk of disease recurrence (univariate Cox: HR = 7.59, P < 0.0001, Fig. 2B; multivariate-Cox: HR = 8.33, P < 0.001, Fig. 2C) and covered the most of relapsed cases (73.5%, 25/34). In these cases, ctDNA detection led radiographic relapse by a median of 145 days. The time intervals were similar between LUAD and LUSC (144 and 150 days, respectively) (Fig. 2D, E; Additional files 7, 8, 9: Figure S4-6). Other results were shown in Additional files 10 and 13.
Fig. 2

Prognostic values of ctDNA mutation. a, b Analysis of recurrence-free survival of patients stratified by 7-day postsurgical (a) and longitudinal (b) ctDNA detection. Univariate Cox regression results were shown. c The results of multivariate-Cox regression for recurrence-free disease in patients stratified by longitudinal ctDNA detection. d Swimmer plot illustrating the ctDNA status, adjuvant therapy, and pathological events of cases with disease recurrence (n = 34). e Time of the earliest ctDNA detection and radiographic relapse, measured by days from the surgery. f Analysis of recurrence-free survival of patients stratified by the clonality of longitudinal ctDNA detection. The ctDNA-positive (Clone) group comprised patients with at least one clonal mutation detected in at least one postsurgical plasma sample. The ctDNA-positive (Subclone) group comprised patients with at least one subclonal mutation detected in at least one postsurgical plasma sample and no clonal mutation detected in any postsurgical samples. The ctDNA-negative group comprised patients with no mutation detected in any postsurgical plasma samples. g, h Clonal phylogenetic information of tissue and plasma samples of Patient 60 (g) and Patient 53 (h). Heatmaps denote mutation profiles of multi-regionally resected primary tumors, lymph node metastasis, and plasma samples with clonal annotation (leftmost column) representing mutation clusters. Phylo-groups comprise samples having identical clonal phylogeny. Colored nodes denote the detection of ctDNA mutations in respective clones, whereas gray nodes denote that no mutation in respective clones was detected

Prognostic values of ctDNA mutation. a, b Analysis of recurrence-free survival of patients stratified by 7-day postsurgical (a) and longitudinal (b) ctDNA detection. Univariate Cox regression results were shown. c The results of multivariate-Cox regression for recurrence-free disease in patients stratified by longitudinal ctDNA detection. d Swimmer plot illustrating the ctDNA status, adjuvant therapy, and pathological events of cases with disease recurrence (n = 34). e Time of the earliest ctDNA detection and radiographic relapse, measured by days from the surgery. f Analysis of recurrence-free survival of patients stratified by the clonality of longitudinal ctDNA detection. The ctDNA-positive (Clone) group comprised patients with at least one clonal mutation detected in at least one postsurgical plasma sample. The ctDNA-positive (Subclone) group comprised patients with at least one subclonal mutation detected in at least one postsurgical plasma sample and no clonal mutation detected in any postsurgical samples. The ctDNA-negative group comprised patients with no mutation detected in any postsurgical plasma samples. g, h Clonal phylogenetic information of tissue and plasma samples of Patient 60 (g) and Patient 53 (h). Heatmaps denote mutation profiles of multi-regionally resected primary tumors, lymph node metastasis, and plasma samples with clonal annotation (leftmost column) representing mutation clusters. Phylo-groups comprise samples having identical clonal phylogeny. Colored nodes denote the detection of ctDNA mutations in respective clones, whereas gray nodes denote that no mutation in respective clones was detected We further found that clonal mutations in ctDNA were more prognostically informative than subclonal ones. During the longitudinal ctDNA surveillance, patients with clonal mutation exhibited a worse prognosis than ctDNA-negative ones (HR = 10.07, P < 0.0001), and no significantly differential survival was observed between those with only subclonal mutations (See Additional file 11: Methods) detected and the ctDNA-negative group (HR = 1.94, P = 0.305) (Fig. 2F). Nonetheless, tracking subclonal dynamics in ctDNA may inform the source of relapse. In Patient 60, at the six-month time point, three mutations from subclones 1 and 2 were detected in plasma. Subclones 1 and 2 were specific to three regions of primary tumor 2, suggesting that primary tumor 2 may be the active source of ctDNA. Later the sequencing of the relapse lesion confirmed primary tumor 2 as its clonal origin (Fig. 2G). In Patient 53, clonal EGFR 19Del and subclonal SMAD4 mutations were detected in plasma shortly before disease relapse. The subclonal SMAD4 mutation was absent from LNM, whereas LNM-specific STK11 mutation was undetectable in ctDNA, together suggesting that LNM may not be an active source of ctDNA or disease recurrence (Fig. 2H). In summary, we found that ctDNA could serve as a promising biomarker for risk of recurrence in NSCLC patients who receive curative surgeries, and the results were further discussed in Additional files 3 and 12. As early as 7 days after the surgery, ctDNA detection identified patients at high risk. Longitudinal ctDNA surveillance could reliably predict recurrence, which opens a window of almost 145 days for optimal disease management. Furthermore, our results showed that tracking subclonal dynamics could inform the origin of tumor recurrence. Additional file 1. Table S1: Patient demography. Additional file 2. Table S2: Adjuvant treatment information. Additional file 3. Table S3: Performance of three strategies. Additional file 4. Figure S1: Availability of plasma samples. The availability of plasma samples for analysis at each schedule collection time point. Blue and red blocks denote samples collected before and after disease recurrence, respectively. Abbreviations: LUAD – lung adenocarcinoma, LUSC - lung squamous-cell carcinoma, RFS – recurrence-free survival, AT – adjuvant therapy, RT – radiotherapy, LNM – lymph node metastasis. Additional file 5. Figure S2: Mutational profile of plasma samples. Gene mutations detected in tissue and plasma samples in each patient. Colors denote different variant types. Horizontal and vertical bars denote the detection of tissue mutations in presurgical and postsurgical plasma samples, respectively. Twenty most prevalent gene mutations in tissue samples were shown. Additional file 6. Figure S3: Prognostic values of postsurgical ctDNA detection at 3 months and 6 months. A-B) The recurrence-free survival analysis (top panel) and multi-variant Cox regression (bottom panel) of postsurgical ctDNA detection at 3 months (A) and 6 months (B). For the analysis at 6 months after surgeries, only patients with plasma samples available at this scheduled point and followed-up for more than 6 months were included. Abbreviations: RFS – recurrence-free survival, LNM – lymph node metastasis, LUAD – lung adenocarcinoma, LUSC - lung squamous-cell carcinoma. Additional file 7. Figure S4: ctDNA statuses and disease-related events of patients during follow-up periods. Swimmer plot illustrating the ctDNA statuses, adjuvant therapies, and pathological events of all patients. Abbreviations: LUAD – lung adenocarcinoma, LUSC - lung squamous-cell carcinoma, AT – adjuvant therapy. Additional file 8. Figure S5: Prognostic values of ctDNA detection based on clonal and subclonal mutations. A). The recurrence-free survival analysis of patients stratified by ctDNA detection based on only clonal mutation profiles. B). The recurrence-free survival analysis of patients stratified by ctDNA detection based on all clonal and subclonal mutations. Additional file 9. Figure S6: ctDNA testing, LDCT scans, and disease-related events of patients during follow-up periods. . Swimmer plot illustrating the first positive ctDNA testing, the last negative LDCT scans, and pathological events of patients that experienced recurrence or deceased. B). The original and adjusted time intervals between the first positive ctDNA testing and final LDCT scans that detected disease recurrence. Abbreviations: LDCT – low-dose computed tomography, LUAD – lung adenocarcinoma, LUSC - lung squamous-cell carcinoma. Additional file 10. Figure S7: Prognostic value of presurgical ctDNA detection. A). The recurrence-free survival analysis of patients stratified by presurgical ctDNA detection. B). The multi-variant Cox regression for presurgical ctDNA detection. Abbreviations: RFS – recurrence-free survival, LNM – lymph node metastasis, LUAD – lung adenocarcinoma, LUSC - lung squamous-cell carcinoma. Additional file 11. Methods. Additional file 12. Supplementary discussion. Additional file 13. Supplementary results.
  5 in total

Review 1.  Recurrence after surgery in patients with NSCLC.

Authors:  Hidetaka Uramoto; Fumihiro Tanaka
Journal:  Transl Lung Cancer Res       Date:  2014-08

2.  Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling.

Authors:  Aadel A Chaudhuri; Jacob J Chabon; Alexander F Lovejoy; Aaron M Newman; Henning Stehr; Tej D Azad; Michael S Khodadoust; Mohammad Shahrokh Esfahani; Chih Long Liu; Li Zhou; Florian Scherer; David M Kurtz; Carmen Say; Justin N Carter; David J Merriott; Jonathan C Dudley; Michael S Binkley; Leslie Modlin; Sukhmani K Padda; Michael F Gensheimer; Robert B West; Joseph B Shrager; Joel W Neal; Heather A Wakelee; Billy W Loo; Ash A Alizadeh; Maximilian Diehn
Journal:  Cancer Discov       Date:  2017-09-24       Impact factor: 39.397

3.  The clinical utility of dynamic ctDNA monitoring in inoperable localized NSCLC patients.

Authors:  Yin Yang; Tao Zhang; Jingbo Wang; Jianyang Wang; Yang Xu; Xiaotian Zhao; Qiuxiang Ou; Yang Shao; Xin Wang; Yuqi Wu; Linfang Wu; Xin Xu; Kunpeng Xu; Jingjing Zhao; Luhua Wang; Nan Bi
Journal:  Mol Cancer       Date:  2022-05-19       Impact factor: 27.401

4.  Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

Authors:  Christopher Abbosh; Nicolai J Birkbak; Gareth A Wilson; Mariam Jamal-Hanjani; Tudor Constantin; Raheleh Salari; John Le Quesne; David A Moore; Selvaraju Veeriah; Rachel Rosenthal; Teresa Marafioti; Eser Kirkizlar; Thomas B K Watkins; Nicholas McGranahan; Sophia Ward; Luke Martinson; Joan Riley; Francesco Fraioli; Maise Al Bakir; Eva Grönroos; Francisco Zambrana; Raymondo Endozo; Wenya Linda Bi; Fiona M Fennessy; Nicole Sponer; Diana Johnson; Joanne Laycock; Seema Shafi; Justyna Czyzewska-Khan; Andrew Rowan; Tim Chambers; Nik Matthews; Samra Turajlic; Crispin Hiley; Siow Ming Lee; Martin D Forster; Tanya Ahmad; Mary Falzon; Elaine Borg; David Lawrence; Martin Hayward; Shyam Kolvekar; Nikolaos Panagiotopoulos; Sam M Janes; Ricky Thakrar; Asia Ahmed; Fiona Blackhall; Yvonne Summers; Dina Hafez; Ashwini Naik; Apratim Ganguly; Stephanie Kareht; Rajesh Shah; Leena Joseph; Anne Marie Quinn; Phil A Crosbie; Babu Naidu; Gary Middleton; Gerald Langman; Simon Trotter; Marianne Nicolson; Hardy Remmen; Keith Kerr; Mahendran Chetty; Lesley Gomersall; Dean A Fennell; Apostolos Nakas; Sridhar Rathinam; Girija Anand; Sajid Khan; Peter Russell; Veni Ezhil; Babikir Ismail; Melanie Irvin-Sellers; Vineet Prakash; Jason F Lester; Malgorzata Kornaszewska; Richard Attanoos; Haydn Adams; Helen Davies; Dahmane Oukrif; Ayse U Akarca; John A Hartley; Helen L Lowe; Sara Lock; Natasha Iles; Harriet Bell; Yenting Ngai; Greg Elgar; Zoltan Szallasi; Roland F Schwarz; Javier Herrero; Aengus Stewart; Sergio A Quezada; Karl S Peggs; Peter Van Loo; Caroline Dive; C Jimmy Lin; Matthew Rabinowitz; Hugo J W L Aerts; Allan Hackshaw; Jacqui A Shaw; Bernhard G Zimmermann; Charles Swanton
Journal:  Nature       Date:  2017-04-26       Impact factor: 49.962

5.  Dynamic recurrence risk and adjuvant chemotherapy benefit prediction by ctDNA in resected NSCLC.

Authors:  Bin Qiu; Wei Guo; Fan Zhang; Fang Lv; Ying Ji; Yue Peng; Xiaoxi Chen; Hua Bao; Yang Xu; Yang Shao; Fengwei Tan; Qi Xue; Shugeng Gao; Jie He
Journal:  Nat Commun       Date:  2021-11-19       Impact factor: 14.919

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.