Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CCR Focus Archive
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Breast Cancer
      • Clinical Trials
      • Immunotherapy: Facts and Hopes
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Clinical Cancer Research
Clinical Cancer Research
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CCR Focus Archive
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Breast Cancer
      • Clinical Trials
      • Immunotherapy: Facts and Hopes
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Precision Medicine and Imaging

Detection of NRG1 Gene Fusions in Solid Tumors

Sushma Jonna, Rebecca A. Feldman, Jeffrey Swensen, Zoran Gatalica, Wolfgang M. Korn, Hossein Borghaei, Patrick C. Ma, Jorge J. Nieva, Alexander I. Spira, Ari M. Vanderwalde, Antoinette J. Wozniak, Edward S. Kim and Stephen V. Liu
Sushma Jonna
1Georgetown University, Washington, DC.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rebecca A. Feldman
2Caris Life Sciences, Phoenix, Arizona.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jeffrey Swensen
2Caris Life Sciences, Phoenix, Arizona.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zoran Gatalica
2Caris Life Sciences, Phoenix, Arizona.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wolfgang M. Korn
2Caris Life Sciences, Phoenix, Arizona.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hossein Borghaei
3Fox Chase Cancer Center, Philadelphia, Pennsylvania.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Patrick C. Ma
4WVU Cancer Institute, West Virginia University, Morgantown, West Virginia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jorge J. Nieva
5University of Southern California, Los Angeles, California.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexander I. Spira
6Virginia Health Specialists, Fairfax, Virginia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ari M. Vanderwalde
7West Cancer Center, Memphis, Tennessee.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Antoinette J. Wozniak
8University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Edward S. Kim
9Atrium Healthcare, Levine Cancer Institute, Charlotte, North Carolina.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephen V. Liu
1Georgetown University, Washington, DC.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: stephen.v.liu@gunet.georgetown.edu
DOI: 10.1158/1078-0432.CCR-19-0160 Published August 2019
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Purpose: NRG1 gene fusions are rare but potentially actionable oncogenic drivers that are present in some solid tumors. Details regarding the incidence of these gene rearrangements are lacking. Here, we assessed the incidence of NRG1 fusions across multiple tumor types and described fusion partners.

Experimental Design: Tumor specimens submitted for molecular profiling at a Clinical Laboratory Improvement Amendments (CLIA)–certified genomics laboratory and that underwent fusion testing by anchored multiplex PCR for targeted RNA sequencing were retrospectively identified. The overall and tumor-specific incidence was noted, as was the specific fusion partner.

Results: Out of 21,858 tumor specimens profiled from September 2015 to December 2018, 41 cases (0.2%) harbored an NRG1 fusion. Multiple fusion partners were identified. Fusion events were seen across tumor types. The greatest incidence was in non–small cell lung cancer (NSCLC, 25), though this represented only 0.3% of NSCLC cases tested. Other tumor types harboring an NRG1 fusion included gallbladder cancer, renal cell carcinoma, bladder cancer, ovarian cancer, pancreatic cancer, breast cancer, neuroendocrine tumor, sarcoma, and colorectal cancer.

Conclusions: NRG1 fusions can be detected at a low incidence across multiple tumor types with significant heterogeneity in fusion partner.

See related commentary by Dimou and Camidge, p. 4865

Translational Relevance

NRG1 fusions are potentially actionable genomic events seen in various tumor types. While there are reports of therapeutic efficacy with agents that target Erb-B2/Erb-B3, little is known about the characteristics of these fusions. Here, we report the incidence of NRG1 fusions in a large cohort of solid tumors that underwent RNA sequencing. NRG1 fusions were detected at a low incidence across many solid tumor types. Multiple fusion partners were identified, which will influence the development of strategies to detect these events on a large scale.

Introduction

Appropriate management of advanced non–small cell lung cancer (NSCLC) is guided by the presence or absence of specific molecular drivers. The identification of activating genomic alterations in EGFR, ALK, ROS1, or BRAF not only provides insight into the underlying biology but also directs initial and subsequent therapeutic decisions (1–5). It is now standard-of-care to search for these mutations and fusions in all patients with nonsquamous NSCLC (6). It has also become clear that some molecular drivers will serve as therapeutic targets across multiple tumor types (7), including the tumor agnostic approval of larotrectinib for tumors with a gene fusion in NTRK1, NTRK2, or NTRK3 (8). As our understanding of cancer grows increasingly sophisticated, additional drivers have surfaced that may have a similar impact on evolving treatment paradigms.

Neuregulin-1 (NRG1) gene fusions are an emerging, potentially actionable oncogenic driver (9). NRG1 fusions can promote pathologic signaling via MAPK and other canonical pathways (10). When NRG1 fusions are present, targeting ERBB2 and ERBB3 has been an effective treatment strategy in vitro. Recently, clinical responses to tyrosine kinase inhibitors and mAbs have also been reported (9, 11–13).

The interest in evaluating the prevalence of NRG1 fusions has increased given the potential therapeutic implications of this genetic alteration. Because the original description of the CD74–NRG1 gene fusion in invasive mucinous lung adenocarcinoma, detection has been noted in other tumor types, both de novo and as a resistance mechanism in ALK-rearranged NSCLC (9, 14–16). Here, we report the incidence and characteristics of NRG1 fusions across a variety of tumor types based on a large molecular profiling experience.

Materials and Methods

Patient cohort

An institutional review board (IRB)–approved, retrospective assessment of a deidentified molecular profiling database was surveyed for solid tumors that underwent fusion testing. From a cohort including all cases submitted to a Clinical Laboratory Improvement Amendments (CLIA)–certified laboratory (Caris Life Sciences) for comprehensive genomic profiling from September 2015 to December 2018, all unique cases that underwent successful fusion testing for targeted RNA sequencing were identified. In addition, all histologic characteristics were reviewed by a board-certified pathologist (Z. Gatalica).

Gene fusion detection

Prior to any molecular analysis, H&E-stained sections of formalin-fixed paraffin-embedded (FFPE) tumor tissue were manually assessed by board-certified pathologists for tumor cell populations and harvested using manual microdissection to enrich the sample to at least 20% tumor nuclei. Anchored multiplex PCR was performed for targeted RNA sequencing using the ArcherDx fusion assay (Archer FusionPlex Solid Tumor Panel). RNA sequencing was performed on mRNA that was isolated and reverse transcribed into complementary DNA from FFPE tumor tissues. Unidirectional gene-specific primers were used to enrich for target regions, followed by next-generation sequencing (NGS; Illumina MiSeq platform). Targets included 52 genes, and the full list can be found at http://archerdx.com/fusionplex assays/solid-tumor (accessed 12/27/18). Reads that were matched to a database of known fusions and other oncogenic isoforms (Quiver database, ArcherDx), as well as those novel isoforms or fusions with high reads (>10% of total reads) and high confidence after bioinformatic filtering, were analyzed. Samples with less than 4,000 unique RNA reads were reported as indeterminate and excluded from analysis. All NRG1 transcript variants were investigated whereby splice junctions were analyzed using the UCSC Genome Browser to predict the likelihood of the mRNA transcript to encode a functional protein (17). The detection sensitivity of the assay allows for detection of a fusion that is present in at least 10% of the cells in the samples tested.

Frame retention prediction

NRG1 fusions were predicted to be (i) in-frame variants, (ii) out of frame variants of unknown significance, or (iii) translated variants where exon 2 of NRG1 is spliced to upstream noncoding exons with confirmed presence of internal initiation sites, (e.g., methionine codon; refs. 17, 18). Inclusion of these variants was based on the retention of the EGF-like domain of NRG1, the functional domain which facilitates its oncogenic potential (19).

NGS

NGS was performed on isolated genomic DNA using the Illumina NextSeq platform. A custom-designed SureSelect XT assay was used to enrich 592 whole-gene targets (Agilent Technologies). All variants were detected with >99% confidence based on allele frequency and amplicon coverage, with an average sequencing depth of coverage of >500 and an analytic sensitivity of 5%. For variant classification, variants of genes that were predetermined for their cancer-related and clinical significance were interpreted by board-certified molecular geneticists and categorized as pathogenic, presumed pathogenic, variant of unknown significance, presumed benign, or benign according to American College of Medical Genetics and Genomics (ACMG) standards. Only pathogenic or presumed pathogenic mutations were considered deleterious and included for assessment of comutation patterns with NRG1 fusion–positive cases.

IHC

IHC was performed using commercially available detection kits and automated staining techniques (Benchmark XT, Ventana; and AutostainerLink 48, Dako). Primary antibodies tested were as follows: Her2/neu (4B5, Ventana), pan-TRK (C17F1, Cell Signaling Technology), and ALK (D5F3, Ventana). Cutoffs for positive staining: (3) pan-TRK, ≥1+ and ≥1% of cells, (4) Her2, ≥3+ and ≥10%, and (5) ALK, ≥3+ and ≥10%.

Results

Sample population

From September 2015 to December 2018, a total of 21,858 tumor specimens from unique patients were successfully evaluated. The tumor types included NSCLC (n = 9,592), glioma (n = 1,997), colorectal cancer (n = 1,690), breast cancer (n = 1,106), bladder cancer (n = 945), ovarian cancer (n = 686), sarcoma (n = 627), pancreatic adenocarcinoma (n = 623), gallbladder cancer (n = 580), other gynecologic malignancies (e.g., uterine, cervical, vulvar; n = 524), melanoma (n = 360), prostate cancer (n = 261), gastric adenocarcinoma (n = 239), head and neck squamous cell carcinoma (n = 236), thyroid cancer (n = 219), renal cell carcinoma (n = 211), neuroendocrine tumors (n = 203), esophageal cancer (n = 202), small-cell lung cancer (n = 107), extrahepatic bile duct cancer (n = 98), small bowel cancer (n = 98), gastrointestinal stromal tumor (n = 83), hepatocellular carcinoma (n = 83), thymic cancer (n = 31), testicular cancer (n = 25), and other malignancies (n = 1,032).

Incidence

The incidence of NRG1 fusions in the entire tested population was 0.2% (41/21,858). Incidence varied by tumor type (Fig. 1): 0.5% gallbladder cancer (3/580), 0.5% pancreatic cancer (3/623), 0.5% renal cell carcinoma (1/211), 0.4% ovarian cancer (3/686), 0.3% NSCLC (25/9,592), 0.2% breast cancer (2/1,106), 0.2% sarcoma (1/627), 0.1% bladder cancer (1/945), and 0.1% colorectal cancer (1/1,690). The remaining identified NRG1 fusion was in a patient with a neuroendocrine tumor of the nasopharynx. Table 1 describes the characteristics of the 41 patients found to have an NRG1 fusion. The most common histologic subtype was adenocarcinoma (70%), of which 24% were classified as mucinous adenocarcinoma and another 8% had a mixed histology with a mucinous component (Supplementary Fig. S1). The majority of cases were stage IV at the time of fusion detection. NRG1 fusion events were more frequently identified in females (66%) versus males, and most specimens were procured from the primary site (68%) compared with a distant metastasis (32%). In the total cohort, 51% (11,228/21,858) of patients were females and 59% (12,798/21,858) of specimens profiled were from primary sites.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Rate of NRG1 fusions by tumor type. The tumor type with NRG1 fusion in the other category is a neuroendocrine tumor of the nasopharynx. CRC, colorectal cancer; GBC, gallbladder cancer (cholangiocarcinoma); PDAC, pancreatic ductal adenocarcinoma; RCC, renal cell carcinoma.

View this table:
  • View inline
  • View popup
Table 1.

Patient and tumor characteristics for NRG1 fusion–positive cases

Fusion partners

The specific fusion partners were also diverse within and across malignancies (Supplementary Table S1; Figs. 2–5; Supplementary Fig. S2). In NSCLC, CD74 was the most common fusion partner (n = 12), but other detected partners in NSCLC cases included SDC4 (n = 3), SLC3A2 (n = 1), TNC (n = 1), MDK (n = 1), ATP1B1 (n = 1), DIP2B (n = 1), RBPMS (n = 1), MRPL13 (n = 1), ROCK1 (n = 1), DPYSL2 (n = 1), and PARP8 (n = 1). In the other malignancies, the identified fusion partners were as follows: SETD4, TSHZ2, and ZMYM2 in ovarian cancer; ADAM9 and COX10-AS1 in breast cancer; ATP1B1, CDH1, and VTCN1 in pancreatic cancer; NOTCH2 and ATP1B1 (n = 2) in gall bladder cancer; POMK in colorectal cancer; RBPMS in renal cell carcinoma; GDF15 in urothelial bladder cancer; WHSC1L1 in sarcoma; and HMBOX1 in neuroendocrine tumor of the nasopharynx. Of the 41 NRG1 fusions identified, 34 were in-frame, three were out-of-frame variants of unknown significance, and four were translated variants.

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Genomic features observed in NRG1 fusion–positive solid tumors. Oncoprint plot illustrating co-occurrence of driver events, genes with any pathogenic variant detected in the cohort, and other clinically relevant protein markers. Each NRG1 fusion–positive sample corresponds to one row in the table; frame prediction of the fusion, cancer type, and fusion partner is provided. Fill of boxes correlates with gene/protein status: (i) red, pathogenic variant detected or positive expression, (ii) gray, wild-type or low/negative expression, and (iii) white, test was not performed or indeterminate. Pathogenic variants in oncogenes were rare, but at least one mutation in tumor suppressor genes, including TP53, occurred in all but nine samples. CDS, coding sequence; CRC, colorectal cancer; DNA-seq, DNA sequencing; GBC, gallbladder cancer (cholangiocarcinoma); HR+ breast, hormone receptor-positive breast; NET, neuroendocrine tumor of the nasopharynx; PDAC, pancreatic ductal adenocarcinoma; RCC, renal cell carcinoma; RNA-seq, RNA sequencing; TN breast, triple-negative breast; UC, urothelial bladder cancer; VUS, fusion variant of unknown significance.

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

NRG1 fusion partners. Pie chart showing the proportion and variety of fusion partners for NRG1.

Figure 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 4.

Circos plot depicting NRG1 fusion genes and partners from Supplementary Table S1. NRG1 and partners in NSCLC (A) and all other tumors (B). chr, chromosome.

Figure 5.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 5.

Schematic diagram of NRG1 fusion variants in solid tumors. A, Genomic structure of wild-type NRG1. B, Fusion variants identified with 5′ partners joined to 3′ NRG1. Bars depict the predicted functional domains (not shown to scale) of interest, and red dashed line indicates fusion breakpoints. The EGF domain is preserved in all fusion variants. UTR, untranslated region.

Co-occurrence with other genetic aberrations

NRG1 fusions were mutually exclusive with oncogenic alterations in EGFR, KRAS, ALK, ROS1, and RET (Fig. 2). One case co-occurred with a BRAF G466A mutation, one with a KRAS G12D mutation, and three with NF1 or NF2 mutations (NF1, Q616fs, NSCLC and c.204+1G>T, ovarian; NF2 H242fs, NSCLC). Most cases (n = 30) also demonstrated concurrent mutations in tumor suppressor genes, including TP53.

Survival

Limited survival analysis is shown in Supplementary Fig. S3 for patients with full annotation (n = 7). Median survival for the entire cohort was 638 days and varied by tumor type, although analysis is limited by the small sample size.

Discussion

NRG1 gene fusions represent a novel oncogenic driver across cancer types. These rare genomic events can generate proteins that retain the extracellular EGF-like domain of NRG1 and the transmembrane domain of the specific fusion partner. These proteins then serve as ligands for ERBB3 (HER3) and ERBB4 (HER4) receptors (10). ERBB3 can then be activated through juxtacrine signaling from the EGF-like domain and autocrine signaling of secreted NRG1 (19). Subsequent heterodimerization of ERBB3 with ERBB2 activates downstream signaling important in tumorigenesis mediated by pathways including ERK, PI3K, AKT, and NFκB, described in cell models (9, 19).

In this report, we retrospectively analyzed over 21,000 specimens after RNA sequencing using the ArcherDx platform to detect NRG1 fusions. As previously reported, our study confirmed the occurrence of NRG1 fusions in NSCLC, breast cancer, cholangiocarcinoma, ovarian cancer, and pancreatic cancer with a low overall incidence. Here, we also detected NRG1 fusions in colorectal cancer, sarcoma, and a neuroendocrine tumor of the nasopharynx, which had not been previously reported. In this report, the majority of these tumors (70%) were adenocarcinoma. NRG1 fusions in NSCLC had been described more frequently in the invasive mucinous adenocarcinoma subtype; in this series, 32% (8/25) of the NRG1+ NSCLC cases had a mucinous histology or a mucinous component (Table 1). The use of broad molecular profiling in this series was based on clinician discretion and may be influenced by patient and tumor characteristics. Thus, the actual incidence may not be entirely representative of the general population. Despite these shortcomings, the detection of such rare genetic alterations across different tumor types supports broader use of NGS.

The specific NRG1 fusion partners are variable within and across tumor types (11–15, 20). Several novel fusion partners detected in this report include TNC, MRPL13, MDK, and DIP2B in NSCLC. Previous reports suggest fusion partners may influence localization of NRG1 to the plasma membrane (20), although the exact significance remains unclear, and the variety of partners observed may introduce challenges for widespread detection efforts.

Splice junctions of all candidate NRG1 fusions were analyzed to predict likelihood to encode functional proteins. Most were predicted to be in-frame; however, a recurrent novel fusion class was identified whereby exon 2 of NRG1 is spliced to upstream noncoding exons of fusion partner genes. In each of these cases (n = 4; Supplementary Table S1), a codon encoding for methionine is present a short distance into exon 2 of NRG1 that could potentially act as a translation initiation codon; if functional, the fusion partner could be providing the promoter for a likely N-terminal truncated version of NRG1. These observations are consistent with similar studies where NRG1 fusion variants included chimeric proteins and cases where expression of NRG1 is controlled by the promoter of the 5′ partner (21). Alternative methodologies are needed to confirm expression of the transcript s identified in this study to determine their significance.

Additional studies describing NRG1 fusions suggest these events are mutually exclusive with other known molecular drivers (14). This was consistent with the findings in this report. Specifically, all NSCLC cases were ALK, ROS, RET fusion–negative, and KRAS wild-type, and all pancreatic adenocarcinomas were KRAS wild-type. The exception was one colorectal cancer case that also harbored a KRAS G12D mutation. The remainder of the cases studied harbored several pathogenic variants in tumor suppressor genes including TP53 and DNA damage and response genes (CHEK2, BRCA2, WRN).

NRG1 fusions are detected in a variety of tumor types. In 2014, Fernandez-Cuesta and colleagues first described the CD74–NRG1 gene fusion in five female never-smokers whose tumors lacked known activating mutations (10). As comprehensive molecular profiling and RNA sequencing has become more prevalent, NRG1 fusions have been detected in a variety of other tumor types, including breast, ovarian, and pancreatic cancer (14, 15). Analysis of MSK-IMPACT dataset including NGS and the MSK solid fusion assay identified 10 patients with NRG1 fusions (out of 17,485 tested): seven in lung adenocarcinoma, two in pancreatic cancer, and one in breast cancer. Further analysis with RNA sequencing revealed additional fusions in other tumor types including ovarian cancer, uterine carcinosarcoma, renal clear cell carcinoma, prostate cancer, and head and neck cancer (9).

As NRG1 alterations activate the ERBB2/ERBB3 signaling pathway, targeted treatment with inhibitors of this pathway is an appealing therapeutic strategy. Dual targeting of ERBB2 and ERBB3 has also been evaluated in preclinical models (22, 23). Afatinib, a pan-ERBB inhibitor, was successfully utilized in this manner, and several patients with tumor harboring an NRG1 fusion achieved durable benefit with afatinib (11–13). Response to an ERBB3 mAb, GSK2849330, has also been reported (9). Combining an ERBB3 mAb and an EGFR tyrosine kinase inhibitor was also effective in a small case series (24). Prospective studies are needed to define the role of targeted therapy for patients with tumors harboring NRG1 fusions, but these data suggest that NRG1 fusions represent a novel potential target across many tumor types that warrant further study.

Disclosure of Potential Conflicts of Interest

W.M. Korn is a consultant/advisory board member for Merck Sharp & Dohme. H. Borghaei reports receiving commercial research grants from Bristol-Myers Squibb and Lilly, and is a consultant/advisory board member for Bristol-Myers Squibb, Lilly, AstraZeneca, Merck, Genentech, Regeneron, Celgene, Genmab, Amgen, EMD Serono, Boehringer Ingelheim, and Takeda. P.C. Ma reports receiving speakers bureau honoraria from AstraZeneca, Merck, Bristol-Myers Squibb, Bayer, and Takeda, and is a consultant/advisory board member for AstraZeneca, Apollomics, and Caris Life Sciences. A.I. Spira is a consultant/advisory board member for Foundation Medicine. A.M. Vanderwalde reports receiving commercial research grants from Amgen and Caris Life Sciences, and is a consultant/advisory board member for AstraZeneca, Bristol-Myers Squibb, Genentech, Compugen, and Immunocore. A.J. Wozniak reports receiving commercial research grants from Boehringer Ingelheim and Genentech, and is a consultant/advisory board member for AstraZeneca, Boehringer Ingelheim, Takeda, Coherus, Karyopharm, Premier, HUYA Bioscience, and BeyondSpring. S.V. Liu reports receiving commercial research grants from AstraZeneca, Bayer, Blueprint, Bristol-Myers Squibb, Clovis, Esanex, Genentech/Roche, Ignyta, Lilly, Lycera, Merck, Molecular Partners, OncoMed, Pfizer, Rain Therapeutics, and Threshold, and is a consultant/advisory board member for Apollomics, AstraZeneca, Bristol-Myers Squibb, Celgene, Genentech/Roche, Heron, Ignyta, Janssen, Lilly, Merck, Pfizer, Regeneron, Taiho, Takeda, and G1 Therapeutics. No potential conflicts of interest were disclosed by the other authors.

Authors' Contributions

Conception and design: S. Jonna, R.A. Feldman, Z. Gatalica, A.M. Vanderwalde, S.V. Liu

Development of methodology: S. Jonna, R.A. Feldman, Z. Gatalica, S.V. Liu

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S. Jonna, R.A. Feldman, Z. Gatalica, H. Borghaei, P.C. Ma, J.J. Nieva, A.M. Vanderwalde, A.J. Wozniak, S.V. Liu

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S. Jonna, R.A. Feldman, J. Swensen, Z. Gatalica, W.M. Korn, H. Borghaei, P.C. Ma, J.J. Nieva, A.I. Spira, A.M. Vanderwalde, E.S. Kim, S.V. Liu

Writing, review, and/or revision of the manuscript: S. Jonna, R.A. Feldman, Z. Gatalica, W.M. Korn, H. Borghaei, P.C. Ma, J.J. Nieva, A.I. Spira, A.M. Vanderwalde, A.J. Wozniak, E.S. Kim, S.V. Liu

Administrative, technical, or mate rial support (i.e., reporting or organizing data, constructing databases): S. Jonna, R.A. Feldman, J. Swensen, S.V. Liu

Study supervision: A.M. Vanderwalde, S.V. Liu

Acknowledgments

The authors thank Alfredo Moreno for support designing the figures and Michele Saul for the analysis of survival data. The authors received no specific funding for this work.

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.

Footnotes

  • Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

  • Clin Cancer Res 2019;25:4966–72

  • Received January 15, 2019.
  • Revision received March 4, 2019.
  • Accepted April 8, 2019.
  • Published first April 15, 2019.
  • ©2019 American Association for Cancer Research.

References

  1. 1.↵
    1. Mok TS,
    2. Wu Y-L,
    3. Ahn M-J,
    4. Garassino MC,
    5. Kim HR,
    6. Ramalingam SS,
    7. et al.
    Osimertinib or platinum-pemetrexed in EGFR T790M-positive lung cancer. N Engl J Med 2017;376:629–40.
    OpenUrlCrossRefPubMed
  2. 2.↵
    1. Hida T,
    2. Nokihara H,
    3. Kondo M,
    4. Kim YH,
    5. Azuma K,
    6. Seto T,
    7. et al.
    Alectinib versus crizotinib in patients with ALK-positive non-small-cell lung cancer (J-ALEX): an open-label, randomised phase 3 trial. Lancet 2017;390:29–39.
    OpenUrl
  3. 3.↵
    1. Solomon BJ,
    2. Mok T,
    3. Kim D-W,
    4. Wu Y-L,
    5. Nakagawa K,
    6. Mekhail T,
    7. et al.
    First-line crizotinib versus chemotherapy in ALK-positive lung cancer. N Engl J Med 2014;371:2167–77.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Planchard D,
    2. Smit EF,
    3. Groen HJM,
    4. Mazieres J,
    5. Besse B,
    6. Helland Å,
    7. et al.
    Dabrafenib plus trametinib in patients with previously untreated BRAFV600E-mutant metastatic non-small-cell lung cancer: an open-label, phase 2 trial. Lancet Oncol 2017;18:1307–16.
    OpenUrl
  5. 5.↵
    1. Mayekar MK,
    2. Bivona TG.
    Current landscape of targeted therapy in lung cancer. Clin Pharmacol Ther 2017;102:757–64.
    OpenUrl
  6. 6.↵
    1. Lindeman NI,
    2. Cagle PT,
    3. Aisner DL,
    4. Arcila ME,
    5. Beasley MB,
    6. Bernicker EH,
    7. et al.
    Updated molecular testing guideline for the selection of lung cancer patients for treatment with targeted tyrosine kinase inhibitors. J Mol Diagnos 2018;20:129–59.
    OpenUrl
  7. 7.↵
    1. Liu SV,
    2. Macke LA,
    3. Colton BS,
    4. Imran SS,
    5. Christiansen J,
    6. Chow-Maneval E,
    7. et al.
    Response to entrectinib in differentiated thyroid cancer with a ROS1 fusion. JCO Precis Oncol 2017;1:1–5.
    OpenUrl
  8. 8.↵
    1. Drilon A,
    2. Laetsch TW,
    3. Kummar S,
    4. DuBois SG,
    5. Lassen UN,
    6. Demetri GD,
    7. et al.
    Efficacy of larotrectinib in TRK fusion-positive cancers in adults and children. N Engl J Med 2018;378:731–9.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Drilon A,
    2. Somwar R,
    3. Mangatt BP,
    4. Edgren H,
    5. Desmeules P,
    6. Ruusulehto A,
    7. et al.
    Response to ERBB3-directed targeted therapy in NRG1-rearranged cancers. Cancer Discov 2018;8:686–95.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Fernandez-Cuesta L,
    2. Plenker D,
    3. Osada H,
    4. Sun R,
    5. Menon R,
    6. Leenders F,
    7. et al.
    CD74-NRG1 fusions in lung adenocarcinoma. Cancer Discov 2014;4:415–22.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. Gay ND,
    2. Wang Y,
    3. Beadling C,
    4. Warrick A,
    5. Neff T,
    6. Corless CL,
    7. et al.
    Durable response to afatinib in lung adenocarcinoma harboring NRG1 gene fusions. J Thorac Oncol 2017;12:e107–10.
    OpenUrl
  12. 12.↵
    1. Jones MR,
    2. Lim H,
    3. Shen Y,
    4. Pleasance E,
    5. Ch'ng C,
    6. Reisle C,
    7. et al.
    Successful targeting of the NRG1 pathway indicates novel treatment strategy for metastatic cancer. Ann Oncol 2017;28:3092–7.
    OpenUrlCrossRef
  13. 13.↵
    1. Cheema PK,
    2. Doherty M,
    3. Tsao M-S
    . A case of invasive mucinous pulmonary adenocarcinoma with a CD74-NRG1 fusion protein targeted with afatinib. J Thorac Oncol 2017;12:e200–2.
    OpenUrl
  14. 14.↵
    1. Heining C,
    2. Horak P,
    3. Uhrig S,
    4. Codo PL,
    5. Klink B,
    6. Hutter B,
    7. et al.
    NRG1 fusions in KRAS wild-type pancreatic cancer. Cancer Discov 2018;8:1087–95.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Huang H-E,
    2. Chin S-F,
    3. Ginestier C,
    4. Bardou V-J,
    5. Adélaïde J,
    6. Iyer NG,
    7. et al.
    A recurrent chromosome breakpoint in breast cancer at the NRG1/neuregulin 1/heregulin gene. Cancer Res 2004;64:6840–4.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. McCoach CE,
    2. Le AT,
    3. Gowan K,
    4. Jones K,
    5. Schubert L,
    6. Doak A,
    7. et al.
    Resistance mechanisms to targeted therapies in ROS1+ and ALK+ non-small cell lung cancer. Clin Cancer Res 2018;24:3334–47.
    OpenUrlAbstract/FREE Full Text
  17. 17.↵
    1. Kent WJ,
    2. Sugnet CW,
    3. Furey TS,
    4. Roskin KM,
    5. Pringle TH,
    6. Zahler AM,
    7. et al.
    The human genome browser at UCSC. Genome Res 2002;12:996–1006.
    OpenUrlAbstract/FREE Full Text
  18. 18.↵
    1. Panigrahi P,
    2. Jere A,
    3. Anamika K
    . FusionHub: a unified web platform for annotation and visualization of gene fusion events in human cancer. PLoS One 2018;13:e0196588.
    OpenUrl
  19. 19.↵
    1. Wen D,
    2. Suggs SV,
    3. Karunagaran D,
    4. Liu N,
    5. Cupples RL,
    6. Luo Y,
    7. et al.
    Structural and functional aspects of the multiplicity of Neu differentiation factors. Mol Cell Biol 1994;14:1909–19.
    OpenUrlAbstract/FREE Full Text
  20. 20.↵
    1. Murayama T,
    2. Nakaoku T,
    3. Enari M,
    4. Nishimura T,
    5. Tominaga K,
    6. Nakata A,
    7. et al.
    Oncogenic fusion gene CD74-NRG1 confers cancer stem cell-like properties in lung cancer through a IGF2 autocrine/paracrine circuit. Cancer Res 2016;76:974–83.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Dhanasekaran SM,
    2. Balbin OA,
    3. Chen G,
    4. Nadal E,
    5. Kalyana-Sundaram S,
    6. Pan J,
    7. et al.
    Transcriptome meta-analysis of lung cancer reveals recurrent aberrations in NRG1 and Hippo pathway genes. Nat Commun 2014;5:5893.
    OpenUrlCrossRefPubMed
  22. 22.↵
    1. Jo JY,
    2. Shin DH,
    3. Han J-Y
    . Abstract 3989: dual targeting of ErbB2/ErbB3 for treatment of SCL3A2-NRG1-mediated lung cancer. Cancer Res 2018;78:3989.
    OpenUrlCrossRef
  23. 23.↵
    1. Shin DH,
    2. Jo JY,
    3. Han J-Y
    . Dual targeting of ERBB2/ERBB3 for the treatment of SLC3A2-NRG1-mediated lung cancer. Mol Cancer Ther 2018;17:2024–33.
    OpenUrlAbstract/FREE Full Text
  24. 24.↵
    1. Kim HS,
    2. Han J-Y,
    3. Shin DH,
    4. Lim KY,
    5. Lee GK,
    6. Kim JY,
    7. et al.
    EGFR and HER3 signaling blockade in invasive mucinous lung adenocarcinoma harboring an NRG1 fusion. Lung Cancer 2018;124:71–5.
    OpenUrl
PreviousNext
Back to top
Clinical Cancer Research: 25 (16)
August 2019
Volume 25, Issue 16
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Editorial Board (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Clinical Cancer Research article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Detection of NRG1 Gene Fusions in Solid Tumors
(Your Name) has forwarded a page to you from Clinical Cancer Research
(Your Name) thought you would be interested in this article in Clinical Cancer Research.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Detection of NRG1 Gene Fusions in Solid Tumors
Sushma Jonna, Rebecca A. Feldman, Jeffrey Swensen, Zoran Gatalica, Wolfgang M. Korn, Hossein Borghaei, Patrick C. Ma, Jorge J. Nieva, Alexander I. Spira, Ari M. Vanderwalde, Antoinette J. Wozniak, Edward S. Kim and Stephen V. Liu
Clin Cancer Res August 15 2019 (25) (16) 4966-4972; DOI: 10.1158/1078-0432.CCR-19-0160

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Detection of NRG1 Gene Fusions in Solid Tumors
Sushma Jonna, Rebecca A. Feldman, Jeffrey Swensen, Zoran Gatalica, Wolfgang M. Korn, Hossein Borghaei, Patrick C. Ma, Jorge J. Nieva, Alexander I. Spira, Ari M. Vanderwalde, Antoinette J. Wozniak, Edward S. Kim and Stephen V. Liu
Clin Cancer Res August 15 2019 (25) (16) 4966-4972; DOI: 10.1158/1078-0432.CCR-19-0160
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosure of Potential Conflicts of Interest
    • Authors' Contributions
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • CONDOR Trial
  • A Novel Mouse Model of Radiation-Induced Cardiotoxicity
  • Protein Multi-marker Panel for Pancreatic Cancer Diagnosis
Show more Precision Medicine and Imaging
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook  Twitter  LinkedIn  YouTube  RSS

Articles

  • Online First
  • Current Issue
  • Past Issues
  • CCR Focus Archive
  • Meeting Abstracts

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Clinical Cancer Research

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Clinical Cancer Research
eISSN: 1557-3265
ISSN: 1078-0432

Advertisement