Analysis of clinical and genomic features in a Chinese cohort with NRG1 variations: a retrospective study

Introduction

The therapeutic strategy of non-small cell lung cancer (NSCLC) is mainly determined by particular molecular changes in genes such as EGFR, ALK, and KRAS. Although these classic driver genes remain central to clinical testing and therapy, rarer genetic variations such as neuregulin 1 (NRG1) fusions have emerged as a potentially actionable oncogenic driver (1). NRG1 is essential for several physiological functions, including nervous system development (2), maintenance of cardiac homeostasis (3) and mammary gland differentiation (4). Most chimeric NRG1 fusion proteins retain the extracellular epidermal growth factor (EGF)-like domain of NRG1 and the transmembrane domain of their fusion partner (5). These hybrid proteins serve as ligands for the ERBB3 (erb-b2 receptor tyrosine kinase 3, also known as human epidermal growth factor receptor 3, HER3) receptors, leading to the formation of HER2-HER3 heterodimers (6). This interaction leads to continuous activation of downstream signaling pathways, mainly phosphoinositide 3-kinase-protein kinase B (PI3K-AKT) and mitogen-activated protein kinase (MAPK) pathways, which then promote tumor cell growth and survival (7,8).

To date, over 18 fusion partners for NRG1 have been identified, with CD74 predominating (35%), followed by SLC3A2 (14%), ATP1B1 (11%), and SDC4 (7%) (9). Overall, NRG1 fusions are relatively rare, occurring in less than 1% of solid tumors and approximately 0.3% of unselected NSCLC. However, they are significantly enriched in invasive mucinous adenocarcinoma (IMA) with the frequency up to 32% (10,11). Multicenter analyses further reveal that NRG1 fusion-positive NSCLC occurs more frequently in non-smokers (57%) and patients without metastatic disease (71%) at diagnosis (12).

To date, no therapeutic drugs specifically targeting NRG1 alterations have been approved by the U.S. Food and Drug Administration (FDA). Case studies indicated that afatinib, a broad spectrum HER tyrosine kinase inhibitor, has partial therapeutic effect on NRG1 fusion-positive NSCLC, with an overall response rate (ORR) of 25% (12,13). Zenocutuzumab, a humanized HER2/HER3 bispecific antibody, worked through a unique “dock-and-block” mechanism (14). By docking onto HER2 with high affinity and blocking the NRG1-HER3 interaction, zenocutuzumab disrupts downstream oncogenic signaling (15). In December 2024, the FDA granted accelerated approval to zenocutuzumab for advanced NRG1 fusion-positive NSCLC and pancreatic cancer (16).

However, there are few studies on the clinicopathological spectrum and other types of genetic variations besides NRG1 fusion, especially single nucleotide variants (SNVs). Furthermore, data on the prevalence, fusion partner distribution, and associated clinical features of NRG1 alterations in a large group of Chinese NSCLC patients are lacking. To fill this gap, we retrospectively analyzed next-generation sequencing (NGS) data of 3,132 Chinese NSCLC patients, aiming to clarify the correlations between specific NRG1 variants, fusion partners, and clinicopathological characteristics. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-aw-1293/rc).

Methods

Study design and cohort characteristics

This retrospective study analyzed NGS data from a consecutive set of 3,132 patients with histologically confirmed NSCLC who were treated at Peking University Cancer Hospital & Institute between May 2017 and April 2024. Clinical information, including patients’ age, sex, smoking and drinking status, pathological subtype, and clinical stage according to the American Joint Committee on Cancer (AJCC) 8th edition, was collected from electronic health records. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study got ethical permission from the Medical Ethics Committee of the Peking University Cancer Hospital & Institute (No. 2016XJS01). Written informed consent was obtained from all participants before NGS testing.

NGS and bioinformatics analysis

Fresh or formalin-fixed paraffin-embedded (FFPE) tissue samples were collected, with plasma cell-free DNA used as an alternative when tissue was unavailable. For all patients, matched peripheral blood leukocytes were analyzed to filter out germline variants. DNA was extracted using Qiagen kits: the QIAamp DNA FFPE Tissue Kit (tissue), QIAamp Circulating Nucleic Acid Kit (plasma), and QIAamp DNA Blood Mini Kit (leukocytes). DNA concentration was quantified using Picogreen fluorescence assays (Invitrogen) with lambda DNA standards.

Due to the retrospective nature of the study, samples were tested using several commercially available targeted NGS panels, which ranged in size from 139 to 831 genes. To ensure a consistent core gene set for analysis, we focused on the 89 genes common to all panels used (Table S1). Library preparation was performed using hybrid capture-based methods according to the respective manufacturer’s protocols. Sequencing was conducted on Illumina platforms (including HiSeq 2000, HiSeq 4000, and NovaSeq systems). Minimum sequencing depth thresholds were strictly applied: ≥500× for tissue, ≥10,000× for cfDNA, and ≥200× for matched leukocyte.

Base calling was performed using bcl2fastq (v2.19.0.316). Raw reads were quality-trimmed using Trimmomatic (v0.36) to remove adapter sequences and low-quality bases. Quality-controlled reads were aligned to the human reference genome (hg19/GRCh37) using the Burrows-Wheeler Aligner (BWA, v0.7.12). Duplicate reads were marked, and local realignment and base quality score recalibration were performed using the Genome Analysis Toolkit (GATK, v3.2). Somatic SNVs were identified using VarScan2 with the following key parameters: minimum variant allele frequency threshold of 1% for tissue and 0.5% for plasma; minimum supporting reads of 5. Gene fusions, including NRG1 fusions, were identified using DELLY and Factera with a minimum split read threshold of 3. After manually reviewed via integrative genomics viewers, all non-synonymous somatic alterations were reported. The oncogenicity classification and clinical significance of these variants were assessed in accordance with the joint guidelines from the Association for Molecular Pathology (AMP), American Society of Clinical Oncology (ASCO), and College of American Pathologists (CAP) for the interpretation of somatic variants in cancer (17,18). To ensure accurate tumor mutation burden (TMB) assessment, we restricted the calculation to panels with a target region exceeding 1 megabase (Mb).

Statistical analysis

Categorical variables were compared using the χ² test or Fisher’s exact test. Continuous variables were reported as median [interquartile range (IQR)] and compared with the Mann-Whitney U test. Multivariable logistic regression was used to determine whether NRG1 SNVs retain independent associations with the reported clinical features. Kaplan-Meier curves were generated to compare disease-free survival (DFS) between patients with NRG1 fusions and those with NRG1 SNVs. Cases with missing data were excluded from the respective analyses. All analyses were performed using R 4.3.2, and SPSS version 22.0. All tests were two-sided, and a P value <0.05 was considered statistically significant.

Results

Demographics and clinical characteristics

Comprehensive genomic profiling of 3,132 consecutive NSCLC tumor samples identified NRG1 fusions in 6 cases (0.2%) and NRG1 SNVs in 22 cases (0.7%). Five cases of NRG1 fusions were found in the lung adenocarcinoma, including two cases of IMA and three of non-mucinous adenocarcinoma. The other one fusion-positive case was discovered in a patient with sarcomatoid carcinoma, which emphasized the histologic variety of NSCLC with NRG1-fusions (Table 1). Meanwhile, an obvious increase in NRG1 fusion was observed in the IMA when compared to NRG1 wild-type cases (P<0.001). Because of the limited number of fusion-positive cases, it was difficult to find statistically significant differences in other clinical factors when they were compared to the NRG1 wild-type cohort.

The analysis of SNVs in NRG1 unveiled a distinctive clinicopathological hallmark. These genetic variants had a strong correlation with being male (P=0.007) and having a history of cigarette smoking (P=0.01). When compared with patients with NRG1 wild-type and fusions, the proportion of lung squamous cell carcinoma (LUSC) in patients with NRG1 SNVs was significantly increased (P=0.03). Another noticeable finding was that NRG1 SNVs-positive cases had a much higher TMB compared to both NRG1 wild-type and NRG1 fusion-positive patients (P<0.001). After multivariable adjustment, a high TMB remained significantly associated with NRG1 SNVs, whereas associations with sex, smoking history, and histology were no longer statistically significant (Table S2). This different feature indicates a fundamental biological diversity between NRG1 fusions and SNVs, suggesting that these changes might play a part in the development of different disease subtypes.

Co-mutation landscape of patients with NRG1 fusions or SNVs

Analysis of the co-mutation landscape revealed TP53 mutations as the most frequent concurrent alteration across both NRG1-altered subgroups, occurring in 59.1% of NRG1 SNVs and 50.0% of NRG1 fusion carriers (Figure 1). The co-occurring alterations in classic lung adenocarcinoma driver genes were the main molecular feature of patients with NRG1 fusions. These genes included KRAS (33.3%), EGFR (16.7%), PIK3CA (16.7%), and ALK (16.7%). In contrast, the NRG1 SNVs cohort demonstrated numerically lower frequencies of KRAS (9.1%, P=0.19) and PIK3CA (13.6%, P>0.99) mutations compared with the NRG1 fusion cohort; however, these differences did not reach statistical significance. EGFR mutation was 18.2% in the SNVs group. Obvious differences were observed in epigenetic regulator genes. In the patients with NRG1 SNVs, a significant enrichment of mutations in chromatin and histone modifiers, including SETD2 (31.8%), SMARCA4 (27.3%), and KMT2A (27.3%), was observed. Conversely, NRG1 fusion-positive tumors were particularly associated with mutations in genes associated with small cell lung cancer, such as EP300 (33.3%), NOTCH2 (16.7%), and CREBBP (16.7%). This unique co-mutation feature indicated that the oncogenic processes behind these two types of NRG1 alterations may be fundamentally different. NRG1 SNVs occurred in the context of widespread epigenetic dysregulation, while fusion was associated with neuroendocrine-like transcriptional environments.

Figure 1 Clinicogenomic profile of NSCLC patients with NRG1 alterations. An integrated overview of patient demographics and genomic alterations in the NRG1 alterations cohort. Patients were classified by age range, sex, smoking and drinking history, clinical stage, and pathological subtype. The top 30 most frequently altered genes are shown. The bar plot on the left illustrates the alteration frequency for each gene. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer.

NRG1 fusion partners and SNVs distribution

Molecular features showed that all identified chimeric NRG1 fusion proteins preserved the complete neuregulin and transmembrane domains. Approximately 83.3% (5 out of 6) of these chimeric proteins kept the vital EGF domain (Figure 2A). CD74 was the main fusion partner being present in 50% (3 out of 6) of the cases, with two occurrences in IMA and one in non-mucinous adenocarcinoma. All CD74::NRG1 chimeric proteins retained the class II histocompatibility complex (MHC2) interaction domain, MHC2-associated invariant chain trimerization domain, and thyroglobulin type-1 repeats of CD74. The other fusion partners were ASH2L, RNF216, and the non-coding RNA LOC124900850. The RNF216::NRG1 fusion maintained all NRG1 structural domains. Due to the unclear function of this non coding RNA partner, the biological significance of LOC124900850::NRG1 fusion remains to be clarified.

Figure 2 Schematic representations of NRG1 fusions and SNVs. (A) Fusion partners and predicted domain architecture of NRG1 chimeric proteins. The N-terminal regions encoded by the fusion partners are colored in light gray, and the C-terminal regions encoded by the truncated NRG1 are colored in dark gray. As LOC124900850 is a non-coding RNA, its potential to encode a protein product remains unknown. Numbers in parentheses indicate the exon breakpoint. (B) Domain structure of the NRG1 gene and distribution of SNVs. The schematic illustrates the functional domains of NRG1 and maps the locations of all identified single nucleotide variants. EGF, epidermal growth factor; I-set, immunoglobulin I-set domain; MHC-trimer, class II MHC-associated invariant chain trimerisation domain; MHC2-interact, chain-associated peptide (CLIP) class II histocompatibility complex (MHC2) interacting; SNVs, single nucleotide variants; Thyroglobulin, thyroglobulin type-1 repeat; TM, transmembrane.

In analyzing the distribution of SNVs of NRG1, no hotspot mutation regions were found. Given the absence of prior reports and database entries for NRG1 SNVs, all such variants in our cohort were classified as Variants of Uncertain Significance (VUS; Tier III) according to the AMP/ASCO/CAP guidelines for somatic variant interpretation (available online: https://cdn.amegroups.cn/static/public/tlcr-2025-aw-1293-1.xlsx). The distribution pattern revealed that 59.1% of SNVs localized to the neuregulin domain, but no mutations were detected within the EGF or transmembrane domains (Figure 2B). This special mutation pattern suggested that there might be different ways in which NRG1 SNVs lead to cancer, separate from the well-known activation process caused by exposing the EGF domain through fusions.

Treatment response and prognosis of NRG1 gene alteration carriers

No NRG1-altered patients in this cohort received agents specifically targeting NRG1 alterations, instead underwent traditional forms of treatment such as surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy, which were tailored according to their individual TNM stage, histological features, and co-mutation situations. The complete dataset, encompassing detailed therapeutic histories, durations of response, and extensive clinical annotations, is available in Table S3. Even in the absence of specific treatments for NRG1, the overall objective response rate among all patients were reached 73.9% (17/23) indicating a strong reaction to the existing treatment methods (Table 2). Without considering clinical stage or specific treatment regimens, there was no difference in DFS in response to existing first-line therapies between patients with NRG1 fusions and those with NRG1 SNVs (P=0.19; Figure 3).

Figure 3 Comparison of DFS between patients with NRG1 fusions and those with NRG1 SNVs using Kaplan-Meier analysis. DFS, disease-free survival; SNVs, single nucleotide variants.

Half of the patients with NRG1 fusions (3 out of 6) and 27.2% of those with NRG1 SNVs (6/22) had the opportunity for surgical treatment (Table 2). These patients remained in remission, with a response duration ranging from 6 to 29 months post-surgery. On the hand, the outcomes for patients with advanced stage cancers varied greatly depending on their molecular characteristics. One patient with both a LOC124900850::NRG1 fusion and an EGFR activating mutation responded well to a series of EGFR tyrosine kinase inhibitors and the effectiveness lasted for 18 months through multiple lines of therapy. Similarly, another NRG1 SNVs carrier with co-occurring ALK fusion initially responded to crizotinib, though with limited duration.

Immunotherapy have shown significant efficacy in certain NRG1 SNVs subgroups. Multiple LUSC patients with NRG1 SNVs had considerable and long-lasting responses to chemoimmunotherapy combinations. Notably, one patient maintained a response for over 36 months following combined chemoradiation and atezolizumab consolidation. This may be due to the patient having a high TMB (42.0 mut/Mb).

Discussion

The frequency of NRG1 fusions and SNVs in NSCLC was very low. This study analyzed 3,132 cases of NSCLC and found that the fusion occurrence rate was 0.2%, which is close to the previously reported 0.3% (10). Meanwhile, the significant enrichment of NRG1 fusion in IMA is also consistent with previous researches, which strengthens the known connection between this genomic driver and a specific pathological type (9,19,20). The fact that CD74 served as the main fusion partner (50%) of NRG1 further corroborates previous findings, and emphasizes a conserved oncogenic pathway related to the abnormal exposure of the EGF-like region, which leads to continuous HER2/HER3 signaling (21).

For NRG1 SNVs, there has been no specific research in the past. This study reports for the first time that the frequency of NRG1 SNVs in NSCLC patients was 0.7%. Unlike NRG1 fusions, which were more common in females and non-smokers, NRG1 SNVs were more common in males, smokers, and individuals with high TMB. The loss of statistical significance for sex, smoking, and histology in the multivariable model likely reflects the known correlations among these variables (e.g., male sex with higher smoking prevalence, and smoking with squamous histology and elevated TMB). The unique demographic and molecular biological characteristics suggested that NRG1 SNVs may not act as a primary driving factor to induce tumor development like NRG1 fusions, but rather tend to be a passenger event reflecting the accumulation of genetic variations. This interpretation is supported by the high prevalence of known driver mutations (TP53, EGFR, or KRAS in 81.8% of patients) and frequent co-mutations in epigenetic regulators such as SETD2, SMARCA4, and KMT2A (59.1% of patients), which collectively point to a background of widespread genomic and epigenetic instability (22-24).

Although there are currently no effective targeted therapies available for Chinese patients with NRG1-positive NSCLC, 73.9% of them benefited from existing treatment strategies. Surgery provides durable remission (6–29 months) in operable cases. Chemotherapy alone or plus immunotherapy shows a highly effective treatment for patients with advanced-stage NSCLC. Zenocutuzumab, as a humanized bispecific antibody, has brought hope for the posterior treatment of these patients. In a multicenter phase II clinical trial, the overall ORR reached 29% [95% confidence interval (CI): 20–39%] among 97 evaluable NSCLC patients, with a median progression-free survival (PFS) of 6.8 months (9). This therapeutic effect was maintained in the hard-to-treat population, with an ORR of 28% in 81 previously treated NSCLC patients. 95% of patients treated with zenocutuzumab experienced at least one adverse event, primarily grade 1 or 2. The most common serious adverse events were anemia, increased γ-glutamyltransferase level, and pneumonia. These powerful clinical results backed the FDA’s accelerated approval of zenocutuzumab for advanced NRG1-fusion-positive NSCLC (16). Once approved, zenocutuzumab may offer a targeted therapeutic strategy for patients harboring NRG1 fusions, especially in later lines of treatment. Our clinicogenomic data may help refine patient selection and inform real-world treatment sequencing in this molecular subset.

There are several limitations in this study. The retrospective single-institution design may introduce selection bias. Meanwhile, the low incidence of alterations, small cohort size, and heterogeneity in clinical characteristics limit the robust statistical comparison and clear evaluation of rare fusion partners. The functional significance of the chimeric proteins formed by NRG1 and fusion partners other than CD74 are still unclear. Future research should prioritize prospective, multi-institutional cohorts to validate these observations and facilitate stronger subgroup analyses.

Conclusions

This study revealed the distinct clinicogenomic landscapes of NRG1 fusions and SNVs within a large, real-world Chinese NSCLC cohort. NRG1 fusion propels an adenocarcinoma subtype. Conversely, our data support the hypothesis that NRG1 SNVs are likely passenger events emerging from a context of accumulated genetic variations. These different alteration types require distinct diagnostic and treatment methods showing the continuous progress of personalized medicine in lung cancer care.

Acknowledgments

The authors would like to thank the patients who participated in this study.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-aw-1293/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-aw-1293/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-aw-1293/prf

Funding: This work was supported by the National Key R&D Program of China (No. 2022YFC2406804), Beijing Municipal Administration of Hospitals Incubating Program (No. PX2023041), and Science Foundation of Peking University Cancer Hospital (No. PY202326).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-aw-1293/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Medical Ethics Committee of the Peking University Cancer Hospital & Institute (No. 2016XJS01). Written informed consent was obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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