Genomic alterations and transcriptional phenotypes in circulating free DNA and matched metastatic tumor

Abstract

Background: Profiling circulating cell-free DNA (cfDNA) has become a fundamental practice in cancer medicine, but the effectiveness of cfDNA at elucidating tumor-derived molecular features has not been systematically compared to standard single-lesion tumor biopsies in prospective cohorts of patients. The use of plasma instead of tissue to guide therapy is particularly attractive for patients with small cell lung cancer (SCLC), due to the aggressive clinical course of this cancer, which makes obtaining tumor biopsies exceedingly challenging.

Methods: In this study, we analyzed a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent SCLC. We conducted cfDNA low-pass whole genome sequencing (0.1X coverage), comparing it with time-point matched tumor characterized using whole-exome (130X) and transcriptome sequencing.

Results: A direct comparison of cfDNA and tumor biopsy revealed that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor but also identifies clinically relevant resistance mechanisms and cancer driver alterations not detected in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Sequencing coverage of plasma DNA fragments around transcription start sites showed distinct treatment-related changes and captured the expression of key transcription factors such as NEUROD1 and REST in the corresponding SCLC tumors. This allowed for the prediction of SCLC neuroendocrine phenotypes and treatment responses.

Conclusions: cfDNA captures a comprehensive view of tumor heterogeneity and evolution. These findings have significant implications for the non-invasive stratification of SCLC, a disease currently treated as a single entity.

Keywords: Circulating cell-free DNA; Circulating tumor DNA; Transcription factor binding site; Whole genome sequencing.

Fig. 1

Study schema. Abbreviations: cfDNA: circulating free DNA; SNV; single-nucleotide variant; indels: insertions and deletions; TF: transcription factor

Fig. 2

Mutation profiles are highly concordant between cfDNA and tumor. A cfDNA tumor fraction in healthy donors and patients with CRPC, MBC, and SCLC. ****: P < 0.0001 by Kruskal–Wallis test followed by Dunn’s multiple comparison test. B TMB between cfDNA and tumor samples. ns: P > 0.05 by Mann–Whitney U test. C, D Distributions of SNVs in cfDNA (C) and tumor (D). E Clinical characteristics, TMB, SNVs, and SCNAs in cfDNA and tumor. Abbreviations: cfDNA: circulating cell-free DNA; CRPC: castration resistant prostate cancer; MBC: metastatic breast cancer; TMB: tumor mutational burden; ns: not significant; SNV: single nucleotide variant; CNV: copy number variant; TIL: tumor infiltrating lymphocytes; CR: complete response; PR: partial response; SD: stable disease; PD: progressive disease; NA: not assessed; SCNA: somatic copy number alteration; SCLC: small cell lung cancer; Ins: insertion; Del: deletion. The genes in the heatmap are recurrently altered genes in SCLC [23, 68]. Platinum-sensitive is defined as disease progression ≥ 90 days after first-line platinum–based chemotherapy, and platinum-resistant as disease progression < 90 days or during first-line chemotherapy. TIL was evaluated by immunohistochemistry staining [34]

Fig. 3

Somatic copy number alterations (SCNAs) and mutational signature profiles are highly concordant between circulating cell-free DNA (cfDNA) and tumor. A Heatmap of SCNAs in cfDNA and tumor. In each row, samples from each patient are aligned tumor followed by cfDNA from top to bottom as indicated on the left. B Spearman’s coefficients of correlations between cfDNA and tumor SCNA at matched or different time points. C Representative correlation of SCNAs between pre-treatment tumor (x-axis) and pre-treatment cfDNA (y-axis) in patient CL0106. Spearman’s correlation coefficient (R) and P value are indicated. D Representative correlation of SCNAs between pre-treatment cfDNA (x-axis) and post-treatment cfDNA (y-axis) in patient CL0106. Spearman’s correlation coefficient (R) and P value are indicated. E Clinical characteristics, TMB, HRD score, and mutational signature profiles in cfDNA and tumor COSMIC mutational signature version 3.2 [40] is computed and shown in the heatmap. Platinum-sensitive defined as disease progression ≥ 90 days after first-line platinum-based chemotherapy, and platinum-resistant disease progression < 90 days or during first-line chemotherapy. F Correlation of mutational signature proportions between tumor (x-axis) and cfDNA (y-axis). G Distribution of Jaccard index of mutational signatures between cfDNA and tumor at matched or different time points. H Correlation of HRD scores in pre-treatment cfDNA (x-axis) and tumor (y-axis). Abbreviations: SCNA: somatic copy number alteration; cfDNA: circulating cell-free DNA; cfDNA: circulating free DNA; SCNA: somatic copy number alteration; TMB: tumor mutational burden; HRD: homologous recombination repair deficiency; TIL: tumor infiltrating lymphocytes; CR: complete response; PR: partial response; SD: stable disease; PD: progressive disease; NE: not evaluable; NA: not assessed; COSIMIC: Catalogue of Somatic Mutations in Cancer: Psensitive: platinum sensitivity; prior IO: prior immunotherapy

Fig. 4

cfDNA tracks the clinical course and reveal mechanisms of treatment response and resistance. A Correlation between cfDNA tumor fraction and volumetric measurements in time point-matched computed tomography. The y-axis (volumetric measurement) is logarithm transformed. B, C Kaplan–Meier curves of PFS (B) and OS (C) in patients with high vs. low cfDNA tumor fraction. High or low cfDNA tumor fraction is defined as patients whose cfDNA tumor fraction is higher or lower than the median of the cfDNA tumor fraction among all 20 samples pre-treatment. P values are evaluated by log-rank test. D Changes of cfDNA tumor fractions in patients who had CR or PR as best response. E Changes of cfDNA tumor fraction (red solid line, left y-axis) and radiological volumetric tumor measurement (green dash line, right y-axis) through treatment time course in a patient who had CR followed by brain only progression (NCI0422). Red circles in CT images indicate right supraclavicular lymph node metastases. F, G CT images of para-aortic lymph node metastasis (top, light blue arrowheads), left breast metastasis (bottom, small yellow arrowheads), and left mediastinal lymph node metastasis (bottom, large yellow arrowheads) in a patient who had PD as best response and with B2M Asn103fs variant in cfDNA and tumor (CL0191). “Bx” in panel F indicates the biopsy site for tumor sequencing. MAF changes of the B2M Asn103fs variant from pre-treatment to post-treatment cfDNA is indicated in panel G. P value is evaluated by Fisher’s exact test. H Comparison of HRD scores derived from pre-treatment cfDNA between patients with SD or PD (= Non-responder, NR) vs. those with CR or PR (= Responder, R). P value is evaluated by Mann–Whitney U test. Abbreviations: cfDNA: circulating cell-free DNA; Tfx: tumor fraction; PFS: progression-free survival; OS: overall survival; CI: confidence interval; m: months; SCLC: small cell lung cancer; CR: complete response; PR: partial response; SD; stable disease; PD: progressive disease; HRD: homologous recombination repair deficiency; CT: computed tomography; MAF; mutation allele frequency; Bx: biopsy; cfDNA; circulating free DNA

Fig. 5

Longitudinal profiling of cfDNA reveal SCLC clonal architecture and track treatment responses. A Mutation frequencies of variants at different time points in cfDNA and tumor from a patient who achieved complete response followed by brain only progression (NCI0422). B Correlations of mutation frequencies between cfDNA vs. tumor pre-treatment (top) and pre-treatment vs at disease progression tumors (bottom) in a patient who achieved complete response followed by brain only progression (NCI0422). Spearman’s coefficients (R) and P values are indicated. C Visualization of genomic clones through treatment time course in a patient who achieved complete response followed by brain only progression (NCI0422). D Mutation frequencies of variants at different time points in cfDNA and tumor in a patient who had disease progression as the best response (CL0116). E Correlations of mutation frequencies between pre-treatment vs. post-treatment tumors (top), pre-treatment tumor vs. cfDNA (middle), and cfDNA pre-treatment vs at disease progression (bottom) in a patient who had disease progression as the best response (CL0116). F Visualization of genomic clones through treatment time course in a patient who had disease progression as the best response (CL0116). Abbreviations: cfDNA: circulating cell-free DNA; cfDNA: circulating free DNA; SCLC: small cell lung cancer; Mut. freq: mutation frequency; MAF: mutation allele frequency

Fig. 6

cfDNA transcription factor occupancy predicts SCLC phenotypes and treatment response. A–E Aggregate cfDNA occupancy profiles around binding sites of NRF1, REST, and CTCF pre-treatment (red), post-treatment (black) and at disease progression (blue). A Computationally predicted NRF1 binding sites inside regions which where cfDNA occupancy increases post-treatment. B cfDNA occupancy profiles around computationally predicted REST binding sites inside regions where cfDNA occupancy increases post-treatment. C cfDNA occupancy profiles around experimentally determined REST binding sites in A549 SCLC cells. D cfDNA occupancy profiles around CTCF binding motifs inside experimentally determined CTCF binding sites in A549 SCLC cells. E cfDNA occupancy profiles around a subset of CTCF binding sites from D, which do not overlap with CTCF sites bound in healthy lungs. F, G cfDNA occupancy at TFBSs of REST and NEUROD1. TFBSs occupancies are shown for the three time points of individual patients, along with group averages. Patients were split into two groups which were sensitive (grey circles and connecting lines) and resistant (red circles and lines) to platinum-based chemotherapy. Top: individual TFBS activity in REST (F) or NEUROD1 (G) are shown. Bottom: averages within the groups of platinum-sensitive (Pt-sensitive) and resistant (Pt-resistant) in REST (F) or NEUROD1 (G) are shown. REST sites are defined based on chromatin immunoprecipitation sequencing in A549 cells. NEUROD1 motifs are defined computationally inside regions with increased cfDNA occupancy post-treatment vs pre-treatment. Platinum-sensitive defined as disease progression ≥ 90 days after first-line platinum-based chemotherapy, and platinum-resistant disease progression < 90 days or during first-line chemotherapy. P values are evaluated by Mann-Whitney U test. H, I cfDNA occupancy profiles at different timepoints around computationally predicted TP53 binding sites inside regions which have increased cfDNA occupancy post-treatment, in samples with (H) vs. without (I) mutations in TP53. J Correlation between cfDNA read depth of NEUROD1 binding sites (x-axis) and NEUROD1 gene expression (TMM-FPKM) in timepoint-matched tumors (y-axis). Higher read depth indicates less TF binding, predicting less gene expression. K Correlation between NEUROD1 cfDNA read depth at TFBS (x-axis) and the PID_MYC_ACTIV_PATHWAY scores by ssGSEA in timepoint-matched tumors (y-axis). Higher read depth indicates less TF binding, predicting less gene expression. L Correlation between cfDNA read depth at TFBS (x-axis) and gene expression of tumor RNA sequencing (TMM-FPKM, y-axis) in the gene REST. Higher read depth indicates less TF binding, predicting less gene expression. M A Kaplan-Meier curve of PFS in patients with high vs. low predicted REST expression. N Correlation between cfDNA tumor fraction and nucleosome occupancy at ASCL1 binding sites, the pre-treatment samples. Pearson’s r = −0.61, P = 0.03. High vs. low predicted REST expression is defined as higher or lower than median predicted REST expression by cfDNA read depth among 13 patients whose pre-treatment cfDNA was successfully processed for the TFBS analysis. Higher predicted REST expression was defined as lower read depth and vice versa, given that higher read depth indicates less TF binding, predicting less gene expression. P value is evaluated by Log-rank test. Abbreviations: cfDNA: circulating cell-free DNA; bp: base pair; TFBS: transcriptional factor binding site; Pt: platinum-based chemotherapy; TMM-FPKM: Trimmed Mean of M-values-normalized Fragments per kilo base per million mapped reads; ssGSEA; single sample gene set enrichment analysis; PFS; progression-free survival; HR: hazard ratio; CI: confidence interval