The BRAFV600E mutation and BRAF inhibitor responsiveness characterize ∼50% of patients with the non-Langerhans cell histiocytosis (non-LCH) Erdheim–Chester disease (ECD). We interrogated the non-LCH molecular landscape [ECD, n = 35; Rosai–Dorfman disease (RDD), n = 3; mixed ECD/RDD, n = 1] using BRAFV600E PCR and/or next-generation sequencing [tissue and cell-free DNA (cfDNA) of plasma and/or urine]. Of 34 evaluable patients, 17 (50%) had the BRAFV600E mutation. Of 31 patients evaluable for non-BRAFV600E alterations, 18 (58%) had ≥1 alteration and 12 putative non-BRAFV600E MAPK pathway alterations: atypical BRAF mutation; GNAS, MAP2K1, MAP2K2, NF1, and RAS mutations; RAF1 or ERBB2 amplifications; LMNA-NTRK1 (TRK inhibitor-sensitive) and CAPZA2–BRAF fusions. Four patients had JAK2, MPL ASXL1, U2AF1 alterations, which can correlate with myeloid neoplasms, a known ECD predisposition, and one developed myelofibrosis 13 months after cfDNA testing. Therefore, our multimodal comprehensive genomics reveals clinically relevant alterations and suggests that MAPK activation is a hallmark of non-LCH.

This article is featured in Highlights of This Issue, p. 1023

Non-Langerhans cell histiocytosis (non-LCH) includes rare disorders such as Erdheim–Chester disease (ECD) and Rosai–Dorfman disease (RDD; ref. 1). ECD is a rare CD68-positive, CD1a-negative “L-Group” non-LCH with multiorgan involvement that was initially described in 1930 (1–3). RDD, an “R-group” non-LCH also known as sinus histiocytosis with massive lymphadenopathy, is defined by the accumulation of CD68-positive, S100-positive, CD1a-negative histiocytes in lymph nodes, the dura, and less frequently other areas such as skin, bones, and soft tissue (1, 2). Non-LCH can coexist with LCH (4). Patients with ECD are usually Caucasian men diagnosed in the fifth to seventh decades of life (3, 5). The most frequent presentation of ECD includes bone pain due to diffuse sclerotic lesions, which demonstrate foamy lipid-laden histiocytes that predominantly affect the diaphysis of appendicular long bones and often spare the epiphyses. Other common features include orbital infiltration with proptosis, lung, kidney, retroperitoneal and cardiac involvement, diabetes insipidus, and skin lesions (3, 6). RDD is more common in children and young adults of African descent (1). The typical of RDD includes bilateral bulky painless cervical lymphadenopathy associated with fatigue, weight loss, pyrexia, and night sweats. Mediastinal, inguinal, and retroperitoneal nodes may also be involved (1, 7). Extranodal involvement is present in about 40% of patients with RDD and can include the skin, nasal cavity, bone, soft tissue, dura, and retro-orbital tissue.

Therapies that have been used successfully for ECD and RDD include IFNα, anakinra (IL1 receptor antagonist), cladribine, and imatinib (8–11). Of interest, about half of the patients with ECD have the BRAFV600E (12). Patients with BRAFV600-mutated ECD respond to BRAF inhibitors such as dabrafenib or vemurafenib, which was recently approved for ECD by the FDA (13, 14). In addition, translational studies and anecdotal clinical reports suggested that patients with ECD without BRAFV600E mutation and patients with RDD can have other molecular alterations in the MAPK pathway such as KRAS, NRAS, and MAP2K1 mutations and potentially respond to MEK inhibitors (15–18).

To date, however, the clinical molecular profiling reported on patients with non-LCH has been mainly confined to small gene sets. In addition, molecular testing of tumor tissue has been complicated due to low percentage of tumor cells present in the archival samples, which is a frequent problem in the case of ECD, especially when bone biopsies containing a stroma-rich microenvironment are sampled (19, 20). Herein, we describe, the molecular profiling by PCR and next-generation sequencing (NGS) of tissue and/or blood and/or urine cell-free DNA (cfDNA) from 39 patients with non-LCH (Fig. 1).

Patients

We identified patients with non-LCH (ECD, RDD), who were treated at MD Anderson Cancer Center (MD Anderson), Memorial Sloan Kettering Cancer Center (MSK), or the University of California San Diego Moores Cancer Center (UCSD) and whose tumor tissue and/or plasma- and/or urine-derived cfDNA was subject to clinical molecular testing. Patients' demographic information was obtained from their electronic medical records. This study was conducted in compliance with the Declaration of Helsinki and the clinical protocols (MD Anderson LAB10-0334, LAB10-0441, and RCR04-567; UCSD NCT02478931; and MSK 14-201) were approved by the institutional review boards. Written informed consent was obtained from all patients before any study-related procedures were performed.

Molecular profiling

All molecular profiling of tumor tissue and plasma- or urine-derived cfDNA sequencing was performed in Clinical Laboratory Improvement Amendment (CLIA)-certified laboratories.

Tumor tissue.

DNA was extracted from microdissected paraffin-embedded tumor sections and analyzed using a PCR-based DNA-sequencing method for the BRAFV600 mutation and/or with the targeted Foundation One or Foundation One Heme NGS assay (Foundation Medicine, Cambridge, MA; http://www.foundationone.com/; hybrid-capture-based comprehensive genomic profiling to a median depth of coverage of >500× testing for 182, 236, 315, or 406 genes, depending on the time and panel) or targeted NGS with the 468 genes MSKCC IMPACT assay (21–23). Alterations captured by targeted NGS included base-pair substitutions, insertions/deletions, copy-number alterations, and rearrangements. Alterations likely or known to be bona fide oncogenic drivers were included and germline polymorphisms were excluded.

Plasma-derived cfDNA.

Circulating cfDNA was extracted from whole blood collected in 10 mL cfDNA BCT tubes (Streck). After double ultracentrifugation, 5 to 30 ng of cfDNA was isolated for digital sequencing (54 to 73 genes) in a CLIA-certified, College of American Pathologists-accredited laboratory using the Guardant360 assay (Guardant Health) as described previously (24). Both leukocyte- and tumor-derived cfDNA fragments were simultaneously sequenced. The variant allele fraction was calculated as the proportion of cfDNA harboring the variant in the background context of wild-type cfDNA. The analytical sensitivity of the methodology permitted the identification of one to two mutant fragments in a 10 mL blood sample (0.1% limit of detection) with an analytic specificity >99.9999%. Gene copy number in plasma is a function of both copy number in tissues and the degree to which tumor DNA was shed into circulation. Gene copy number of 2.5 to 4.0 are reported as ++ amplification, and those over 4.0 are reported as +++ amplification, representing the 50th to 90th and >90th percentiles, respectively of the copy number call in the Guardant360 database (24).

Urine-derived cfDNA.

Urine-derived cfDNA was isolated and tested for the presence of the BRAFV600E mutation using a droplet digital PCR (ddPCR; QX-100, Bio-Rad) assay for cfDNA quantification and rare BRAFV600E allele detection (19, 20). The RainDrop ddPCR instrument (RainDance) was used for PCR droplet separation, fluorescent reading, and counting droplets containing mutant sequences, wild-type sequences, or unreacted probes. For a given patient sample, the assay reported the BRAFV600E mutation fragments it detected as a percentage of the wild-type BRAF. Thresholds were defined as no detection—wild-type (<0.05%), indeterminate (0.05%–0.107%), and detected—BRAFV600E (>0.107%). All testing was performed in a CLIA-certified laboratory (Trovagene).

Patients

We evaluated 39 patients, treated at MD Anderson (n = 24), MSK (n = 9), or UCSD (n = 6). Of these 39 patients, 35 (90%) had ECD, 3 (8%) had RDD, and one (2%) had mixed ECD and RDD. Most patients were men (n = 22, 56%), Caucasians (n = 27, 69%), and had disease involving multiple organ systems (n = 20, 51%). The median patient age was 49 years (range, 15–76). Patients' characteristics are listed in Table 1.

Table 1.

Characteristics of patients and genomic sequencing (N = 39)

Median age at diagnosis (range) in years49 (15–76)
Sex 
 Men 22 
 Women 17 
Ethnicity  
 Caucasian 27 
 African American 
 Hispanic 
 Middle Eastern 
 Asian 
 Other 
Type of non-LCH 
 ECD 35 
 RDD 
 ECD/RDD 
Classification 
 Multisystem 20 
 CNS dominant 
 Bone dominant 
 Cutaneous dominant 
 Orbital-craniofacial dominant 
 Unknown 
 Cardiac 
 Retroperitoneal dominant 
Molecular testing (No. of patients) 
 Successful molecular testing by any method 34 
 Failures 
BRAFV600E mutation 17 
BRAFV600E wild-type 17 
 Tissue PCR/Sanger sequencing attempted 18 
 Tissue PCR/Sanger sequencing failed 
 Tissue PCR/Sanger sequencing succeeded 14 
 Tissue PCR/Sanger not attempted 21 
BRAFV600E mutation by tissue PCR/Sanger sequencing 10 
Median turnaround time in days (range) for tissue PCR/Sanger sequencing 10 (5–41) 
 Tissue NGS attempted 29 
 Tissue NGS failure 
 Tissue NGS succeeded 22 
 Tissue NGS not attempted 10 
BRAFV600E mutation by tissue NGS 
Median turnaround time in days (range) for tissue NGS 29 (10–116) 
 Urine PCR attempted 
 Urine PCR failure 
 Urine PCR succeeded 
 Urine PCR not attempted 34 
BRAFV600E mutation by urine PCR 
Median turnaround time in days (range) for urine PCR 16.5 (7–25) 
 Plasma cfDNA attempted 27 
 Plasma cfDNA failed 
 Plasma cfDNA succeeded 27 
 Plasma cfDNA not attempted 12 
BRAFV600E mutation by plasma cfDNA 
Median turnaround time (days) for plasma cfDNA 13 (8–18) 
Median age at diagnosis (range) in years49 (15–76)
Sex 
 Men 22 
 Women 17 
Ethnicity  
 Caucasian 27 
 African American 
 Hispanic 
 Middle Eastern 
 Asian 
 Other 
Type of non-LCH 
 ECD 35 
 RDD 
 ECD/RDD 
Classification 
 Multisystem 20 
 CNS dominant 
 Bone dominant 
 Cutaneous dominant 
 Orbital-craniofacial dominant 
 Unknown 
 Cardiac 
 Retroperitoneal dominant 
Molecular testing (No. of patients) 
 Successful molecular testing by any method 34 
 Failures 
BRAFV600E mutation 17 
BRAFV600E wild-type 17 
 Tissue PCR/Sanger sequencing attempted 18 
 Tissue PCR/Sanger sequencing failed 
 Tissue PCR/Sanger sequencing succeeded 14 
 Tissue PCR/Sanger not attempted 21 
BRAFV600E mutation by tissue PCR/Sanger sequencing 10 
Median turnaround time in days (range) for tissue PCR/Sanger sequencing 10 (5–41) 
 Tissue NGS attempted 29 
 Tissue NGS failure 
 Tissue NGS succeeded 22 
 Tissue NGS not attempted 10 
BRAFV600E mutation by tissue NGS 
Median turnaround time in days (range) for tissue NGS 29 (10–116) 
 Urine PCR attempted 
 Urine PCR failure 
 Urine PCR succeeded 
 Urine PCR not attempted 34 
BRAFV600E mutation by urine PCR 
Median turnaround time in days (range) for urine PCR 16.5 (7–25) 
 Plasma cfDNA attempted 27 
 Plasma cfDNA failed 
 Plasma cfDNA succeeded 27 
 Plasma cfDNA not attempted 12 
BRAFV600E mutation by plasma cfDNA 
Median turnaround time (days) for plasma cfDNA 13 (8–18) 

Abbreviation: CNS, central nervous system.

Molecular profiling

Molecular profiling with tumor tissue targeted NGS and/or tumor tissue PCR sequencing and/or plasma-derived cfDNA targeted NGS and/or urine-derived cfDNA PCR was attempted for all 39 patients and yielded at least one valid result (meaning successful test) for the BRAFV600E mutation and/or other alterations for 34 (87%) patients (Fig. 1). The median turnaround times from request to results were 29 days (range, 10–116 days) for tumor tissue targeted NGS, 10 days (5–41 days) for tumor tissue PCR, 13 days (8–18 days) for plasma cfDNA targeted NGS and 16.5 days (7–25 days) for urine cfDNA PCR (P < 0.001, Table 1).

Figure 1.

Of 39 patients with ECD (n = 35), RDD (n = 3), and mixed ECD/RDD (n = 1), the valid results from at least one method of molecular testing were available for 34 patients. The diagram depicts the distribution and overlap of the testing methods used such as tumor tissue targeted NGS, tumor tissue PCR for the BRAFV600E mutation, plasma-derived cfDNA targeted NGS, and urine-derived cfDNA PCR for the BRAFV600E mutation.

Figure 1.

Of 39 patients with ECD (n = 35), RDD (n = 3), and mixed ECD/RDD (n = 1), the valid results from at least one method of molecular testing were available for 34 patients. The diagram depicts the distribution and overlap of the testing methods used such as tumor tissue targeted NGS, tumor tissue PCR for the BRAFV600E mutation, plasma-derived cfDNA targeted NGS, and urine-derived cfDNA PCR for the BRAFV600E mutation.

Close modal

Tumor tissue targeted NGS.

Tumor tissue targeted NGS was attempted for 29 patients and yielded valid results for 22 (76%). The median number of alterations detected excluding variants of unknown significance (VUS) was 1 (range, 0–3 alterations; Table 2). Only 3 (10%) of the 29 patients who were successfully tested had ≥2 alterations (Fig. 2).

Table 2.

Genomic alterations detected by tissue NGS or plasma-derived cfDNA

VariableTissue (NGS only), 29 patientsacfDNA NGS, 27 patientsa
Median (range) number of alterations detected 1 (0–3) 1 (0–5) 
Number of patients with 0 alterations detected 11 
Number of patients with 1 alteration detected 13 11 
Number of patients with 2 alterations detected 
Number of patients with 3 alterations detected 
Number of patients with ≥4 alterations detected 1 (5 alterations) 
Number of failures 
Types of alterations (VUS are excluded) 
 Cumulative number of tissue alterations = 30a (includes tissue NGS or PCR) Cumulative number of cfDNA alterations = 25a 
APC — 
ASXL1 — 
BRAF 18 (17 with BRAFV600E; 1 with a CAPZA2-BRAF fusion) 8 (BRAFV600E in 7 patients; one of the 7 patients had BRAFV600E and BRAFL485W
CCNE1 — 
CD36 — 
ERBB2 — 
GNAS — 
JAK2 — 
KRAS — 
MAP2K1 — 
MAP2K2 
MIR143HG-NOTCH2 fusion — 
MITF — 
MPL — 
NF1 — 
NRAS 
NTRK1 FUSION (LMNA-NTRK1) — 
RAF1 — 
RIT1 — 
SOX2 — 
TP53 — 
U2AF1 — 
VariableTissue (NGS only), 29 patientsacfDNA NGS, 27 patientsa
Median (range) number of alterations detected 1 (0–3) 1 (0–5) 
Number of patients with 0 alterations detected 11 
Number of patients with 1 alteration detected 13 11 
Number of patients with 2 alterations detected 
Number of patients with 3 alterations detected 
Number of patients with ≥4 alterations detected 1 (5 alterations) 
Number of failures 
Types of alterations (VUS are excluded) 
 Cumulative number of tissue alterations = 30a (includes tissue NGS or PCR) Cumulative number of cfDNA alterations = 25a 
APC — 
ASXL1 — 
BRAF 18 (17 with BRAFV600E; 1 with a CAPZA2-BRAF fusion) 8 (BRAFV600E in 7 patients; one of the 7 patients had BRAFV600E and BRAFL485W
CCNE1 — 
CD36 — 
ERBB2 — 
GNAS — 
JAK2 — 
KRAS — 
MAP2K1 — 
MAP2K2 
MIR143HG-NOTCH2 fusion — 
MITF — 
MPL — 
NF1 — 
NRAS 
NTRK1 FUSION (LMNA-NTRK1) — 
RAF1 — 
RIT1 — 
SOX2 — 
TP53 — 
U2AF1 — 

aVUSs were excluded.

Figure 2.

Number of the genomic alterations detected by the targeted NGS of tumor tissue (A) and plasma-derived cfDNA (C). Distribution of the genomic alterations detected by the targeted NGS of tumor tissue (B) and plasma-derived cfDNA (D).

Figure 2.

Number of the genomic alterations detected by the targeted NGS of tumor tissue (A) and plasma-derived cfDNA (C). Distribution of the genomic alterations detected by the targeted NGS of tumor tissue (B) and plasma-derived cfDNA (D).

Close modal

Tumor tissue PCR for the BRAFV600E mutation.

Of 18 patients tested, 14 (78%) yielded valid results and 10 (56%) showed BRAFV600E mutation.

Plasma-derived cfDNA targeted NGS.

Testing of plasma samples from all 27 patients yielded a valid result. In addition, 18 (67%) of these 27 patients also had successful tumor tissue targeted NGS testing and 11 (41%) tumor tissue PCR for the BRAFV600E mutation (Table 3). The median number of alterations detected in plasma-derived cfDNA excluding VUS was 1 (range, 0–5 alterations; Table 2). Only 5 (19%) of the 27 patients tested had ≥2 alterations (Fig. 2).

Table 3.

Genomic profiles (VUS excluded)a

Case ID/DiagnosisTissue PCR for BRAFV600ETissue NGS**Plasma cfDNA NGS (Variant allele frequency or level of amplification)Urine cfDNA PCR for BRAFV600EInstitution
1/ECD Not done MAP2K1Q56P Not done Wild-type MDACC 
2/ECD BRAFV600E Failed Not done Not done MDACC 
3/ECD Wild-type Not done Not done Not done MDACC 
4/ECD Failed Not done Not done Not done MDACC 
5/ECD Failed Not done Not done Not done MDACC 
6/ECD Not done BRAFV600E Not done Not done MDACC 
7/ECD Failed Not done Not done Not done MDACC 
8/ECD Failed Not done Not done Not done MDACC 
9/ECD Not done BRAFV600E BRAFV600E, 0.3% BRAFV600E MDACC 
   KRASG12R, 0.3%   
10/ECD Not done LMNA- NTRK1 fusion Not done Not done MDACC 
11/ECD Not done BRAFV600E Not done Not done MDACC 
12/ECD Wild-type Failed NF1R1132H, 0.5% Not done MDACC 
13/ECD Not done Failed Not done Not done MDACC 
14/ECD Wild-type Failed None Not done MDACC 
15/ECD BRAFV600E Not done Not done Wild-type MDACC 
16/ECD Wild-type Failed None Wild-type MDACC 
17/ECD Not done BRAFV600E BRAFV600E, 1.2% Not done MDACC 
  ASXL1E635fs*15 CCNE1P396L, 0.2%   
18/ECD Not done BRAFV600E BRAFV600E, 1.7% Not done MDACC 
19/ECD BRAFV600E ASXL1G646fs*12 BRAFV600E, 0.6% Not done MDACC 
   BRAFL485W, 0.3%   
   ERBB2 amplification, 1+   
20/ECD Not done Failed None Not done MDACC 
21/ECD Not done NRASQ61R MPLW515L, 1.8% Not done MDACC 
22/RDD Not done CAPZA2-BRAF fusion RAF1 amplification, 3+ Not done MDACC 
23/RDD Not done Not done APCE1157fs, 0.4% Not done MDACC 
24/RDD Not done Not done GNASR201C, 0.1% Not done MDACC 
25/ECD BRAFV600E Not done BRAFV600E, 0.2% Not done UCSD 
   NF1H1494Y, 0.1%   
26/ECD BRAFV600E None None Not done UCSD 
27/ECD Not done Failed None Not done UCSD 
28/ECD BRAFV600E None None Not done UCSD 
29/ECD Not done BRAFV600E BRAFV600E, 0.06% Not done UCSD 
  ASXL1R693 RITM90V, 4.0%   
  U2AF1Q157P JAK2V617F, 2.9%   
   KRASA59T, 2.8%   
   NRASG60R, 0.3%   
30/ECD Not done CD36L360a NF1I679fs, 0.3% Not done UCSD 
31/ECD BRAFV600E None TP53R273H, 0.4% Not done MSKCC 
32/ECD Not done None None Not done MSKCC 
33/ECD Not done None None Not done MSKCC 
34/ECD Not done Not done None Not done MSKCC 
35/ECD BRAFV600E None TP53H179R, 3.5% Wild-type MSKCC 
36/ECD-RDD Not done MIR143HG-NOTCH2 fusion None Not done MSKCC 
37/ECD Not done BRAFV600E BRAFV600E, 0.3% Not done MSKCC 
38/ECD BRAFV600E SOX2 amplification MITF amplification None Not done MSKCC 
39/ECD BRAFV600E MAP2K2Y134H MAP2K2Y134H, 20.3% Not done MSKCC 
Case ID/DiagnosisTissue PCR for BRAFV600ETissue NGS**Plasma cfDNA NGS (Variant allele frequency or level of amplification)Urine cfDNA PCR for BRAFV600EInstitution
1/ECD Not done MAP2K1Q56P Not done Wild-type MDACC 
2/ECD BRAFV600E Failed Not done Not done MDACC 
3/ECD Wild-type Not done Not done Not done MDACC 
4/ECD Failed Not done Not done Not done MDACC 
5/ECD Failed Not done Not done Not done MDACC 
6/ECD Not done BRAFV600E Not done Not done MDACC 
7/ECD Failed Not done Not done Not done MDACC 
8/ECD Failed Not done Not done Not done MDACC 
9/ECD Not done BRAFV600E BRAFV600E, 0.3% BRAFV600E MDACC 
   KRASG12R, 0.3%   
10/ECD Not done LMNA- NTRK1 fusion Not done Not done MDACC 
11/ECD Not done BRAFV600E Not done Not done MDACC 
12/ECD Wild-type Failed NF1R1132H, 0.5% Not done MDACC 
13/ECD Not done Failed Not done Not done MDACC 
14/ECD Wild-type Failed None Not done MDACC 
15/ECD BRAFV600E Not done Not done Wild-type MDACC 
16/ECD Wild-type Failed None Wild-type MDACC 
17/ECD Not done BRAFV600E BRAFV600E, 1.2% Not done MDACC 
  ASXL1E635fs*15 CCNE1P396L, 0.2%   
18/ECD Not done BRAFV600E BRAFV600E, 1.7% Not done MDACC 
19/ECD BRAFV600E ASXL1G646fs*12 BRAFV600E, 0.6% Not done MDACC 
   BRAFL485W, 0.3%   
   ERBB2 amplification, 1+   
20/ECD Not done Failed None Not done MDACC 
21/ECD Not done NRASQ61R MPLW515L, 1.8% Not done MDACC 
22/RDD Not done CAPZA2-BRAF fusion RAF1 amplification, 3+ Not done MDACC 
23/RDD Not done Not done APCE1157fs, 0.4% Not done MDACC 
24/RDD Not done Not done GNASR201C, 0.1% Not done MDACC 
25/ECD BRAFV600E Not done BRAFV600E, 0.2% Not done UCSD 
   NF1H1494Y, 0.1%   
26/ECD BRAFV600E None None Not done UCSD 
27/ECD Not done Failed None Not done UCSD 
28/ECD BRAFV600E None None Not done UCSD 
29/ECD Not done BRAFV600E BRAFV600E, 0.06% Not done UCSD 
  ASXL1R693 RITM90V, 4.0%   
  U2AF1Q157P JAK2V617F, 2.9%   
   KRASA59T, 2.8%   
   NRASG60R, 0.3%   
30/ECD Not done CD36L360a NF1I679fs, 0.3% Not done UCSD 
31/ECD BRAFV600E None TP53R273H, 0.4% Not done MSKCC 
32/ECD Not done None None Not done MSKCC 
33/ECD Not done None None Not done MSKCC 
34/ECD Not done Not done None Not done MSKCC 
35/ECD BRAFV600E None TP53H179R, 3.5% Wild-type MSKCC 
36/ECD-RDD Not done MIR143HG-NOTCH2 fusion None Not done MSKCC 
37/ECD Not done BRAFV600E BRAFV600E, 0.3% Not done MSKCC 
38/ECD BRAFV600E SOX2 amplification MITF amplification None Not done MSKCC 
39/ECD BRAFV600E MAP2K2Y134H MAP2K2Y134H, 20.3% Not done MSKCC 

aVUSs were excluded.

Urine-derived cfDNA for BRAF V600E.

Samples from all five patients yielded a valid result and one sample had the BRAFV600E mutation.

BRAFV600E mutation.

Of 39 patients, 34 (87%) had valid molecular testing results for the BRAFV600E mutation by any method. Of these 34 patients, 17 (50%) had the BRAFV600E mutation. All patients with the BRAFV600E mutation had ECD. Tumor tissue testing by either PCR or NGS detected the BRAFV600E mutation in all 17 patients. Of interest, seen patients had valid results for the BRAFV600E mutation from both tissue PCR and tissue NGS and although all PCR results revealed BRAFV600E mutation, none of the targeted NGS results did (Table 3).

Among the 27 patients for whom plasma-derived cfDNA targeted NGS demonstrated valid results, seven (26%) had the BRAFV600E mutation, which was confirmed by tumor tissue PCR or NGS (Table 3). Overall, plasma-derived cfDNA and tumor tissue PCR or NGS yielded valid test results for the BRAFV600E mutation for 22 patients, resulting in an agreement rate between plasma and tumor tissue of 73% [kappa, 0.49; 95% confidence interval (CI), 0.19–0.79], a sensitivity for plasma of 54%, and a specificity for plasma of 100% (Table 4). Of interest, the median time between sample collection for tumor tissue testing (NGS and/or PCR) and plasma-derived cfDNA testing for seven patients with the BRAFV600E mutation in both plasma-derived cfDNA and tumor tissue (0 weeks; range, −2 to 164 weeks) was shorter than the median time between sample collection for six patients with the BRAFV600E mutation in tumor tissue but not plasma-derived cfDNA (21 weeks; range, −2 to 69 weeks, P = 0.045). In addition, three of the six patients with the BRAFV600E mutation in tumor tissue but not plasma-derived cfDNA received a BRAF or MEK inhibitor between the times of tissue and plasma collection.

Table 4.

Agreement between testing for BRAFV600E mutation in plasma cfDNA testing and tumor tissue (NGS or PCR)

Patients with BRAFV600E mutation testing of plasma cfDNA and tumor tissue (n = 22)BRAFV600E mutation in tumor tissueBRAF wild-type in tumor tissue
BRAFV600E mutation in plasma cfDNA 
BRAF wild type in plasma cfDNA 
Agreement between plasma and tissue 73% (16/22; κ = 0.49; 95% CI, 0.19–0.79) 
Sensitivity for plasma cfDNA 54% (95% CI, 0.25–0.81) 
Specificity for plasma cfDNA 100% (95% CI, 0.66–1.00) 
Patients with BRAFV600E mutation testing of plasma cfDNA and tumor tissue (n = 22)BRAFV600E mutation in tumor tissueBRAF wild-type in tumor tissue
BRAFV600E mutation in plasma cfDNA 
BRAF wild type in plasma cfDNA 
Agreement between plasma and tissue 73% (16/22; κ = 0.49; 95% CI, 0.19–0.79) 
Sensitivity for plasma cfDNA 54% (95% CI, 0.25–0.81) 
Specificity for plasma cfDNA 100% (95% CI, 0.66–1.00) 

Finally, of the five patients whose urine-derived cfDNA was tested for the BRAFV600E mutation by PCR, one had the BRAFV600E mutation; this patient also had the BRAFV600E mutation in tumor tissue (detected by NGS) and in plasma-derived cfDNA (Table 3). Of the four remaining patients, who did not have the BRAFV600E mutation in urine-derived cfDNA two had the BRAFV600E mutation in tumor tissue (detected by PCR).

Genomic alterations other than BRAFV600E mutation.

Of 39 patients, 31 (79%) had valid molecular testing results for alterations other than the BRAFV600E mutation by any method and 18 (58%) had one or more such alterations (Tables 2 and 3). Interestingly, we observed atypical alterations affecting BRAF, including a CAPZA2-BRAF fusion in an RDD patient and atypical activating BRAFL485W mutation in an ECD with the BRAFV600E mutation. We also detected fusions such as MIR143HG–NOTCH2 and LMNANTRK1. Of 18 patients with molecular alterations other than (n = 7) or in addition to the BRAFV600E mutation (n = 5), 12 (67%) had one or more alterations that putatively, directly or indirectly activate the MAPK pathway including KRAS mutations (n = 2), NRAS mutations (n = 2), NF1 mutations (n = 3), a BRAF atypical mutation or fusion (n = 2), a GNAS mutation (n = 1), an ERBB2 amplification (n = 1), a RAF1 amplification (n = 1), an LMNA-NTRK1 fusion (n = 1), a MAP2K1 mutation (n = 1), and a MAP2K2 mutation (n = 1). In addition, we detected several other unique alterations, such as an MITF amplification (previously described in melanoma); a SOX2 amplification (associated with squamous tumors); JAK2V617F and MPLW515L mutations (usually seen in myelofibrosis); ASXL1 mutations, which can occur in clonal hematopoiesis of indeterminate potential; and a U2AF1 mutation (associated with myelodysplastic syndrome; refs. 25–29).

Overall, of 18 patients with valid tumor tissue and plasma-derived cfDNA test results for alterations other than the BRAFV600E mutation, seven (39%) had plasma-derived cfDNA and tumor tissue NGS results that were in complete agreement (Table 3). Of interest, the median time between sample collection for tumor tissue and plasma-derived cfDNA testing for these seven patients was 0 weeks [range, −2(ctDNA collected before the tissue biopsy) to 69 weeks), whereas the median time between sample collection for tumor tissue and plasma-derived cfDNA testing for 11 patients whose tumor tissue and plasma-derived cfDNA NGS results for alterations other than the BRAFV600E mutation were in disagreement was 17 weeks (range, −2 to 164 weeks, P = 0.08).

Of interest, three patients had RDD, and one had mixed ECD and RDD. The patient with mixed ECD and RDD had an osteosclerotic tibial lesion typical of ECD, and biopsy of two disparate bone lesions demonstrated areas of RDD-like histopathology (large histiocyte with pale cytoplasm, strong S100 positivity, emperipolesis) and areas of ECD histopathology (scant S100 positivity in abundant foamy histiocytes). This patient had a MIR143HG-NOTCH2 fusion as the sole alteration. One RDD patient harbored a CAPZA2-BRAF fusion (detected by tumor tissue NGS) and a RAF1 amplification (detected in plasma cfDNA); the other two patients with RDD had a GNASR201C and APCE1157fs mutation, respectively (detected in plasma-derived cfDNA).

We interrogated the molecular profiles of 39 patients with non-LCH using tissue and/or plasma- and/or urine-derived cfDNA with NGS and/or PCR-based sequencing technologies. In five patients, all testing that was attempted failed owing to inadequate specimens. The median number of characterized alterations per patient was one (range, 0–3 alterations) for tissue NGS and one (range, 0–5 alterations) for plasma-derived cfDNA NGS. Among the 34 patients with at least one valid test result (including 30 patients with ECD, three patients with RDD, and one patient with mixed ECD/RDD), 22 distinct genes were found to harbor characterized somatic alterations (VUS excluded).

We detected some common molecular themes, specifically the involvement of the MAPK pathway, in our patients. Indeed, 24 of 34 patients (71%) with valid genomic results had alterations in genes that directly or indirectly activate the MAPK pathway, including 12 patients with the BRAFV600E mutation only, five with the BRAFV600E mutation and other MAPK-activating alterations, and seven with other MAPK-activating alterations without the BRAFV600E mutation. Other than the BRAFV600E mutation, alterations activating the MAPK pathway included an atypical BRAF mutation and CAPZA2-BRAF fusion; mutations in genes such as GNAS, MAP2K1, MAP2K2, NF1, NRAS, and KRAS; amplifications of RAF1 and ERBB2; and an LMNA-NTRK1 fusion. We detected the BRAFV600E mutation in 50% of tested patients with non-LCH, which is consistent with previously reported data (12). Furthermore, our results validate in the clinical setting early experimental data from Diamond and colleagues(15), which also demonstrated the presence of oncogenic alterations including mutations and fusions in BRAF and other genes activating the MAPK pathway such as NRAS, KRAS, MAP2K1, and ARAF in tissue samples from patients with non-LCH. These data collectively support the hypothesis that the activation of the MAPK pathway is a hallmark of non-LCH, which can be explored therapeutically. Indeed, early clinical data reported that the MEK inhibitor cobimetinib, which effectively reduces MAPK pathway activation, can be effective in patients with ECD or RDD (18, 30). Furthermore, in addition to LMNANTRK1 fusion we observed the novel fusions CAPZA2–BRAF, and MIR143HG–NOTCH2, which have not been reported in non-LCH (15). The protein encoded by CAPZA2 is the alpha subunit of the barbed-end actin binding protein Cap Z. By capping the barbed end of actin filaments, Cap Z regulates the growth of the actin filaments (31). Previously, BRAF fusions involving the intact in‐frame BRAF kinase domain, including 20 novel BRAF fusions, were observed in 55 (0.3%) of 20,573 tumors across 12 distinct tumor types (32). To our knowledge, a CAPZA2–BRAF fusion has not been reported. MIR143–NOTCH2 fusions have been previously described in 52% of glomus tumors, which are neoplasms of perivascular smooth muscle differentiation (33). MIR143 is a miRNA coexpressed with MIR145, which functions as a potential tumor suppressor. Intriguingly, one of the patients in this study had an LMNA–NTRK1 fusion; colorectal and other cancers with such fusions can demonstrate profound responses to NTRK inhibitors (15, 34). We also detected an atypical BRAFL485W mutation, which was present alongside a BRAFV600E mutation. Although its functional consequences BRAFL485W mutation are not fully understood, early clinical data suggest sensitivity to MAPK targeting with the ERK inhibitor ulixertinib, as evidenced by radiological partial response in a patient with advanced gallbladder cancer (35). We also observed an ERBB2 amplification in one patient. Although uncommon, abnormalities in ERBB family members, as well as other genes usually associated with solid tumors, have been documented in lymphoid malignancies (36). The MITF and SOX2 amplifications observed in our dataset are known to be associated with melanoma and squamous malignancies, respectively (25, 26). These findings indicate that, despite the common theme of MAPK pathway involvement, some of our patients had unique alterations, a phenomenon that has been described across the cancer field and supports the need to perform genomic testing and individualize of therapy (37)

One of our patients had a JAK2V617F mutation; this alteration is typical of myelofibrosis. Although the patient had only ECD when the JAK2V617F mutation in cfDNA was detected, approximately 13 months later, he developed anemia, thrombocytopenia, and splenomegaly, and a bone marrow biopsy showed myelofibrosis. Interestingly, another patient had an MPLW515L mutation in plasma-derived cfDNA. The MPLW515L mutation also activates the JAK–STAT pathway and is observed in myelofibrosis; 8 months after the molecular test, the patient's blood counts were normal. We also observed other alterations in genes involving clonal hematopoiesis such as ASXL1 mutations. Finally, a U2AF1Q157P mutation (a gene anomaly sometimes found in poor-risk myelodysplastic syndrome) was also detected. Papo and colleagues (36) reported a 10% incidence of simultaneous myeloid neoplasms in a large data set of 189 patients with ECD. Our study was neither designed nor powered to elucidate the significance of the above-mentioned alterations as possible early molecular signals of myeloid malignancies, and longer follow-up to help answer this question is warranted (38).

For patients, who had both tumor tissue and plasma-derived cfDNA testing results available, plasma-derived cfDNA testing for the BRAFV600E mutation had 100% specificity but only 54% sensitivity. Of interest, the median interval between tumor tissue and plasma collection was longer for discordant samples (P = 0.045), and half of the patients with discordant results received BRAF or MEK inhibitors before the plasma collection. Both of these factors were previously reported to have a lower concordance between molecular testing of plasma-derived cfDNA and tumor tissue (39, 40). In addition, in our study, for all six patients with the BRAFV600E mutation in tumor tissue, but not plasma-derived cfDNA, the BRAFV600E mutation was detected by PCR and not NGS. The cfDNA targeted NGS method demonstrated consistency between analytical and clinical performance with sensitivity of 86% and specificity >99% through multiple clinical utility studies including assessment of concordance with the molecular testing of the tumor tissue in advanced cancers; however, there have been no data specifically for non-LCH (41, 42). Finally, complete agreement rate between plasma-derived cfDNA and tumor tissue for alterations other than the BRAFV600E mutation was low (39%) and compared with patients for whom tumor tissue and cfDNA test results for non-BRAFV600E alterations were concordant, patients for whom these test results were discordant showed a trend towards having longer times between sample collections (P = 0.08).

In clinical practice, performing comprehensive genomic profiling on tissue, blood, and urine is not standard practice. However, these tests are extremely useful in both the diagnosis and treatment of non-LCH. We feel that both tissue and cfDNA NGS should be performed on all these patients. For the 50% to 60% percent of BRAFV600E-negative patients, NGS can find a targetable alterations allowing for effective treatment. Furthermore, serial cfDNA NGS can help identify patients at risk of developing myeloid neoplasms.

In summary, the comprehensive molecular profiling of tumor tissue and cfDNA from patients with non-LCH revealed multiple and often novel molecular alterations. Most of these alterations activate the MAPK pathway, which suggest that therapeutic targeting of this pathway is an effective strategy for further clinical development. In addition, we found other molecular alterations that can provide additional targets for matched therapies (e.g., ERBB2 and NTRK1 alterations), which supports the use of comprehensive molecular profiling technologies in the development of personalized approaches to treating non-LCH. Furthermore, we found that comprehensive molecular profiling of plasma-derived cfDNA has a good specificity for detection of the BRAFV600E mutation and can be used as an alternative to tumor tissue testing, especially when tumor tissue is in short supply; however, exposure to prior systemic therapy might reduce this sensitivity. In addition, in patients with alterations other than BRAFV600E mutations the agreement rate between plasma-derived cfDNA and tissue is relatively low and because it is unclear, which alteration is a true driver, it might be warranted to attempt testing of both sources of genomic material. Five patients had BRAFV600E mutations along with other mutations in the MAPK pathway. However, as previously reported BRAFV600E mutations and RAS mutations are usually mutually exclusive unless one of the mutations is subclonal (43–46). We suspect that some of the non-BRAFV600E MAPK pathway alterations represent either clonal hematopoiesis or minority subclones, however, we were unable to definitively prove this possibility. Finally, comprehensive molecular profiling of plasma-derived cfDNA detects molecular alterations that are known to be associated with myeloid malignancies. Therefore, given the known association between ECD and myeloid malignances, further investigation of using comprehensive molecular profiling of plasma-derived cfDNA for the early diagnosis of simultaneous myeloid neoplasia in non-LCH patients is warranted.

F. Janku reports receiving a commercial research grant from Novartis, Genentech, Asana, Usher-Smith Laboratories, Bayer, FujiFilm Corporation, BioMed Valley Discoveries, Astellas, Agios, Plexxikon, Deciphera, Piqur, Symphogen, and Bristol-Myers Squibb; has ownership interest (including stock, patents, etc.) from Trovagene; and is a consultant/advisory board member of Guardant Health, IFM Therapeutics, Synlogic, Deciphera, Trovagene, and Immunomet. O. Abdel-Wahab reports receiving a commercial research grant from H3B Biomedicine; and is a consultant/advisory board member of Janssen, H3B Biomedicine, Merck, and Foundation Medicine Inc. F. Meric-Bernstam reports receiving a commercial research grant from Novartis, AstraZeneca, Zymework, PUMA Biotechnology, Curis, Pfizer, Daiichi Sankyo, Abbive, Guardant Health, Taiho, Genentech, Calithera, Debio, Bayer, Jounce, CytoMx, and eFFECTOR; and is a consultant/advisory board member of Debio, PUMA Biotechnology, Spectrum, Samsung Bioepis, Aduro, OrigiMed, Xencor, Jackson Laboratory, Mersana, Pfizer, Inflection Biosciences, Pieris, Darwin Health, GRAIL, Clearlight Diagnostics, Dialectica, AND Sumitomo Dainippon. R. Kurzrock has equity interest at IDbyDNA, CureMatch, Inc., and Soluventis; reports receiving a commercial research grant from Incyte, Genentech, Merck Serono, Pfizer, Sequenom, Foundation Medicine, Guardant Health, Grifols, Konica Minolta, and OmniSeq; has received speakers bureau honoraria from Roche; and has ownership interest (including stock, patents, etc.) from IDbyDNA, CureMatch, Inc., and Soluventis; and is a consultant/advisory board member of Gaido, LOXO, X-Biotech, Actuate Therapeutics, Roche, and NeoMed. No conflicts of interest were disclosed by the other authors.

Conception and design: F. Janku, E.L. Diamond

Development of methodology: F. Janku

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): F. Janku, E.L. Diamond, A.M. Goodman, T.G. Barnes, S. Kato, O. Abdel-Wahab, B.H. Durham, F. Meric-Bernstam

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): F. Janku, E.L. Diamond, A.M. Goodman, V.K. Raghavan, B.H. Durham, R. Kurzrock

Writing, review, and/or revision of the manuscript: F. Janku, E.L. Diamond, A.M. Goodman, S. Kato, B.H. Durham, F. Meric-Bernstam, R. Kurzrock

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): F. Janku, V.K. Raghavan

Study supervision: F. Janku

This work was supported by the Sidney Kimmel Foundation for Cancer Research (to F. Janku), the Sheikh Khalifa Al Nahyan Ben Zayed Institute for Personalized Cancer Therapy (to F. Janku), the ECD Global Alliance Grant (to F. Janku, E.L. Diamond, O. Abdel-Wahab), the Joan and Irwin Jacobs Fund (to R. Kurzrock), the National Institutes of Health through MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, and Moores Cancer Center Support Grants [P30 CA016672 (to P.W.T. Pisters), P30 CA008748 (to C.B. Thompson), P30 CA023100 (to S.M. Lippman)].

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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