
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12563-7
10.1016/j.heliyon.2024.e36532
e36532
Research Article
TP53 and EGFR amplification are negative predictors of overall survival in patients diagnosed with non-small cell lung cancer with brain metastases
Lin Tao a1
Tang Xusheng b1
Yang Wanli c1
Yang Hainan d
Zhou Zhaoming e
Chen Zhijie a
Zeng Yongqin a
Hong Weiping e
Ye Minting e
Cai Linbo e
Liu Da daliu0104_dr@126.com
a⁎⁎⁎
Li Minying lmy.69@163.com
f⁎⁎
Wen Lei wenlei1998@sina.com
ge⁎
a Department of Neurosurgery, Guangdong Sanjiu Brain Hospital, Guangzhou, China
b Department of Radiation Oncology, Shanghai GoBroad Cancer Hospital, Shanghai, China
c The First Rehabilitation Hospital of Shanghai, Department of Medical Genetics, School of Medicine, Tongji University, Shanghai, China
d Department of Critical Care Medicine, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, 358 Datong Road, Pudong New District, Shanghai, 200137, China
e Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
f Department of Radiation Oncology, Zhongshan People's Hospital, Zhongshan, China
g Department of Radiation Oncology, Zhujiang Hospital, Southern Medical University, 253 Gongye Dadao, Guangdong, 510280, Guangzhou, China
⁎ Corresponding author. Department of Radiation Oncology, Zhujiang Hospital, Southern Medical University, 253 Gongye Dadao, Guangdong, 510280, Guangzhou, China. wenlei1998@sina.com
⁎⁎ Corresponding author. Department of Radiation Oncology, Zhongshan People's Hospital, No. 2 Sunwen Middle Road, Zhongshan, 528403, Guangdong, China. lmy.69@163.com
⁎⁎⁎ Corresponding author. daliu0104_dr@126.com
1 Contributed equally.

19 8 2024
30 8 2024
19 8 2024
10 16 e3653219 3 2023
3 7 2024
18 8 2024
© 2024 The Authors. Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Background

The discovery of driver genes such as EGFR, KRAS, and ALK, has dramatically shifted treatment patterns in patients harboring these oncogenes. However, dissemination into the central nervous system (CNS) is a severe complication. In addition, the particular anatomical structure of the CNS has made it difficult to obtain tissue specimens from brain metastases (BM) to generate a gene map, as such, potential predictive markers for survival in patients with non-small cell lung cancer (NSCLC) and BM (NSCLC-BM) remain unclear.

Methods

Data from 28 patients diagnosed with NSCLC-BM between June 2019 and May 2021 at Guangdong Sanjiu Brain Hospital (Guangzhou, China), were reviewed. Targeted next-generation sequencing (NGS) of a 168 cancer-related gene panel was available for surgically resected brain tissues from all patients. In addition, molecular characteristics and overall survival (OS) were analyzed to determine potential predictive markers.

Results

Among patients with NSCLC-BM, NGS revealed that TP53 was the most frequent mutation (61 %), with a detection rate of 39 %, closely by EGFR amplification. Additionally, CDKN2A, MYC, LRP1B, and RNF43 were frequently observed (18 %). The median OS was significantly shorter in the TP53 mutation group than in the wildtype group (14 versus undefined months, p = 0.014). Similar results were also found in the genetic alteration of EGFR amplification, suggesting that EGFR amplification was associated with worse OS (14 vs. 24 months, p = 0.039). Interestingly, NGS revealed that gene alternations such as TP53, EGFR amplification, and CDKN2A, tended to coexist and such a co-alteration panel indicated worse clinical outcomes (median OS, 5 months). In addition, the detection rate of negative survival genes, including TP53 or EGFR amplification, was much higher in tumor tissues than in plasma samples, indicating the limited predictive value of matched PLA samples.

Conclusions

Gene signatures, such as TP53 or EGFR amplification, were associated with worse survival in patients diagnosed with NSCLC-BM. These valuable findings may shed light on new strategies for the prognostic assessment of specific patient groups.

Keywords

Non-small cell lung cancer
Brain metastases
TP53
EGFR amplification
==== Body
pmc1 Introduction

Lung cancer is the most commonly diagnosed cancer worldwide [1], and is broadly classified into two categories of small, and non-small cell lung cancer (NSCLC), with approximately 80%–85 % of lung cancer cases being NSCLC [2]. The discovery of driver genes, such as epidermal growth factor receptor (EGFR), KRAS, and anaplastic lymphoma kinase (ALK), has changed the therapeutic approach for selected patients with NSCLC. In patients with EGFR mutations, treatment with EGFR tyrosine kinase inhibitors (EGFR-TKIs) is associated with longer progression-free survival (PFS) than chemotherapy [[3], [4], [5]]. ALK gene rearrangement occurs in 3%–5% of patients with NSCLC patients, and the presence of ALK is a strong predictor of better outcomes for the targeted inhibitor crizotinib [6,7]. Although some patients can benefit from targeted molecular therapies, central nervous system (CNS) dissemination remains a severe complication. The incidence of brain metastasis (BM) has been reported to be 24.4 % in patients with EGFR mutations at the time of diagnosis. However, this percentage rises to 46.7 % three years after diagnosis [8].

Evidence from previous research indicated that patients with NSCLC who harbor EGFR mutation were more likely to develop BM than without such alternations [9]. A similar study found that EGFR protein overexpression indicates tumor progression, with higher levels of EGFR protein overexpression in metastatic sites than primary tumors [10]. In addition, Lynette M. Sholl et al. reported that lung adenocarcinomas with EGFR amplification are more likely to have coexisting exon 19 deletion (19del) mutations, and overall survival (OS) was significantly poorer in patients with EGFR amplification than in those without [11].

TP53 mutation have been correlated with shorter OS in previous research in lung adenocarcinoma patients [12], and another similar finding also showed that TP53 mutation and EGFR amplification were inferior prognostic factors for recurrence-free survival (RFS) [13]. However, whether TP53 and EGFR amplification are associated with worse prognosis for patients with BM has not been extensively studied. As such, the present study performed targeted next-generation sequencing (NGS) on metastatic brain tumor from 28 patients diagnosed with NSCLC and pathologically confirmed BM to identify potential prognostic factors.

2 Methods

2.1 Study design and patients

This retrospective analysis included twenty-eight NSCLC-BM patients diagnosed with NSCLC-BM between June 2019 and May 2021 at the Guangdong Sanjiu Brain Hospital (Guangzhou, China). The inclusion criteria were as follows: diagnosis of NSCLC patients, surgical resection of a brain tumor and confirmed by histopathological testing, and removed tumor tissues underwent NGS of a panel of 168 cancer-related genes. Among these patients, seventeen patients had available plasma (PLA) samples that were collected simultaneously. This study was approved by the Ethics Committee of Guangdong Sanjiu Brain Hospital.

2.2 Next-generation sequencing (NGS)

Genetic DNA was purified from FFPE tumor samples using a commercially available kit (QIA amp DNA FFPE Tissue Kit, Qiagen, Hilden, Germany). Cell-free DNA was extraction from PLA samples using a commercially available kit (QIA amp Circulating Nucleic Acid Kit, Qiagen). Targeted NGS of a 168-gene panel was performed on all collected samples, and the genomic profiles were identified using the core panel from Burning Rock Biotech (Guangzhou, China).

2.3 Statistical analysis

The detection rate was calculated as the number of patients with these alterations divided by the total number of patients in each cohort. Categorical variables were analyzed using chi-squared or Fisher's exact tests, and descriptive variables were assessed using descriptive tests. OS was defined as the time from initial diagnosis of BM to death or the last follow-up and was assessed using the Kaplan–Meier method. Statistical analyses and survival curves were performed using SPSS version 21(IBM Corp., Armonk, NY, USA), Graph Pad Prism 6 (GraphPad Inc., San Diego, CA, USA), and R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria). Differences with p < 0.05 were considered to be statistically significant.

3 Results

3.1 Patient characteristics

Date from 28 patients diagnosed with NSCLC-BM were reviewed in this study. The median age was 56.5 years (range, 40–76 years), and 12 (43 %) patients were female. Driver genes were detected in 20 (71 %) patients in the study cohort: EGFR L858R mutations were found in 4 (14 %), EGFR 19del mutations were observed in 5 (18 %), and EGFR L861Q was found in 2 (7 %). Two patients exhibited coexisting EGFR mutations: 1 with EGFR L861Q and EGFR G719S; and the other with concurrent EGFR R776H and EGFR G719A mutations. KRAS was detected in 3 (11 %) patients, ALK in 3 (11 %), and BRAF in 1 (4 %). Seventeen (61 %) patients with NSCLC-BM had matched PLA samples for further analysis (Table 1).Table 1 Baseline patient characteristics (N = 28).

Table 1Characteristic	Pts (n = 28)	
Tissue type	Brain tumor	
Number	28	
Age (year)	
 Median	56.5	
 Range	40–76	
Gender	
 Female	12 (43)	
 Male	16 (57)	
Driver oncogene	
EGFR	12	
 L858R	4 (14)	
 19del	5 (18)	
 L861Q	2a (7)	
 G719S	1 (4)	
 G719A	1b (4)	
 R776H	1 (4)	
KRAS	3 (11)	
ALK	3 (11)	
RET	1 (4)	
BRAF	1 (4)	
Wild Type	8 (29)	
Matched samples	
 PLA	17 (61)	
 CSF		
Diagnose of BM	
Pathology	28 (100)	
Histologic type	
 Adenocarcinoma	24 (86)	
 Squamous	4 (14)	
Abbreviations: EGFR: epidermal growth factor receptor; ALK: anaplastic lymphoma kinase; PLA: plasma.

a One patient has co-existing of EGFR L861Q and EGFR G719S.

b One patient has concurrent of EGFR R776H and EGFR G719A.

3.2 Gene landscape of patients with NSCLC-BM

To explore the genetic profiles of BM tumors, NGS was performed on 28 patients with NSCLC-BM. Driver genes, including EGFR, KRAS, ALK, BRAF, and RET, were identified in 71 % (20/28) of patients with EGFR 19del, EGFR L858R, EGFR L861Q, EGFR G719A, EGFR G719S, KRAS, and ALK were seen 18 %, 14 %, 7 %, 4 %, 4 %, 11 %, and 11 % of patients, respectively. Multiple copy number variations (CNVs) were identified in BM tumors, TP53 was the most frequent mutation (17/28, 61 %), closely followed by EGFR amplification (11/28, 39 %). CDKN2A, or CDKN2B were detected in 5 (18 %) or 4 (14 %) patients, respectively. MYC copy number gains were identified in 5 (18 %) patients; LRP1B and RNF43 were also frequently observed, yielding the same percentage (18 %). In addition, CCND1, FGF4, PMS2, and CSMD3 were frequently observed (14 % [4/28]) (Fig. 1).Fig. 1 Next-generation sequencing results of 28 brain parenchymal metastases tumors in NSCLC patients. The top bar demonstrated the overall number of mutations in each patient. The right-side bar demonstrates the percentage of a patient harboring a specific mutation. Different colors denote different types of mutation.

Fig. 1

3.3 Different distribution of gene alteration between group one and group two according to median OS

To better assess the underlying genomic alterations correlated with worse survival in patients with NSCLC-BM, patients in this study were classified into group 1 (n = 18) and group 2 (n = 10) according to median OS (10 vs. 24 months, respectively; p = 0.0018) (Fig. 2). Comparison of genetic variation between groups 1 and 2 revealed that the detection rates of TP53 mutation and EGFR amplification were higher in group 1 compared with group 2: 67 % vs. 50 % (12/18 vs. 5/10) and 56 % vs. 10 % (10/18 vs. 1/10), respectively. In addition, mutations in CDKN2A were exclusively identified in group 1. These findings indicate that genetic alterations in TP53, EGFR amplification, and CDKN2A may be putative negative predictors of OS in patients with NSCLC-BM. In contrast, the detection rates of MYC and RNF43 were comparable between groups 1 and 2, with similar detection rates of 17 % (3/18) and 20 % (2/10), respectively (Table 2).Fig. 2 Patients were classified into 2 groups (Group 1 and Group 2) by the median (18 months) of overall survival, assessed by Kaplan-Meier method.

Fig. 2

Table 2 Different distribution of negative genes in group one and group two.

Table 2	Group one (n = 18)	Group two (n = 10)	pts (n = 28)	
TP53 mutation	67 (12)	50 (5)	61 (17)	
EGFR amplification	56 (10)	10 (1)	39 (11)	
CDKN2A	28 (5)	0	18 (5)	
MYC	17 (3)	20 (2)	18 (5)	
RNF43	17 (3)	20 (2)	18 (5)	

3.4 TP53 and EGFR amplification are associated with worse prognosis

Kaplan-Meier analysis was applied to each cohort with or without such alterations, to further assess the predictive value of TP53, EGFR amplification, and CDKN2A. The median OS was significantly shorter in the TP53 mutation group than in the wildtype group (14 vs. undefined months, p = 0.014, Fig. 3A), Mutations of oncogenes, such as ALK, EGFR, and KRAS, were identified as mutually exclusive in a previous study [14], and in this study cohort EGFR amplification was detected uniquely concurrent with driver gene of EGFR or wild type patients. Therefore, it was we reasoned that the predictive value of EGFR amplification should be assessed in this selected group (n = 20). Results from Kaplan–Meier curves for OS revealed that concomitant EGFR amplification was associated with worse OS compared with wildtype group (14 vs 24 months, p = 0.039, Fig. 3B). CDKN2A was uniquely identified in group one, with copy number deletion detected in 3 patients and splice variant identified in 2 patients; however, given the limited number of patients (n = 5), there Kaplan-Meier analysis of such genetic alternation could not be performed. Interestingly, NGS revealed that gene alterations, such as TP53, EGFR amplification, and CDKN2A tended to coexist and such a co-alteration panel indicated worse clinical outcomes (median OS, 5 months, Table 3).Fig. 3 Overall survival in patients with and without A. TP53 and B. EGFR amplification, assessed by Kaplan-Meier curves. A: The median OS was significant worse in patients with TP53 mutation than in patients with wild type (p = 0.014). B: The median OS was significantly worse in patients with EGFR amplification than in patients without such alternation (p = 0.039).

Fig. 3

Table 3 Co-alterations panel of the negative predictor of overall survival.

Table 3Survival	OS (months)	Mutation genes	
TP53	EGFR amplification	CDKN2A	
1	5	+	+	+	
1	4	+	+	+	
0	13	+	+	+	
0	8	–	+	+	
Abbreviations: 1 in survival columns indicated the patients had already dead, whereas, 0 in survival columns indicated the patients are alive. + in mutation genes columns mean the patient with such mutation, and – representative the patient without such alternation.

3.5 Limited predictive value of matched PLA samples for NSCLC-BM

The common activating mutations of EGFR L858R and EGFR 19del, as well as the uncommon activating mutations of EGFR G719A, were similar among brain tumor matched PLA, showing EGFR 19del and EGFR L858R identified the same 12 % (2/17) or 24 % (4/17) in paired tumors and PLA, respectively. In addition, the detection rate of EGFR G719A was the same (6 %) between matched tissue and PLA samples. However, the detection rate of negative survival genes, including TP53 or EGFR amplification, was much higher in tumor tissues than in PLA samples, at 59 % (10/17), 35 % (6/17), 41 % (7/17), and 6 % (1/17), respectively. Moreover, CDKN2A or CDKN2B genomic mutations were detected exclusively in tumor tissues (Fig. 4). These results reflected the limited predictive value of matched PLA samples in patients diagnosed with NSCLC-BM.Fig. 4 Different distribution of mutation profiles identified in matched brain metastases tumors and PLA samples. The top bar represents the total number of mutations in each patient. The right-side bar demonstrates the percentage of patients harboring a specific mutation. The bottom bar denotes patients grouped by paired brain tumor and PLA samples. Different types of mutations were represented by different colors.

Fig. 4

4 Discussion

Due to limited access to CNS tissue specimens, genomic analysis of metastases in the CNS remains elusive. In our study, NGS results from 28 BM specimens revealed that, aside from driver gene mutations, TP53 was the most frequent aberration in brain tumors, and gene signatures such as EGFR amplification, CDKN2A, CDKN2B, MYC, LRP1B, RNF43, CCND1, FGF4, PMS2, CSMD3, EPHA3, FGF3, FGF19, TERT, CDK4 and RB1 were also frequently detected (>10 %). Previously, targeted sequencing of 15 lung adenocarcinoma brain metastases (LCBM) samples revealed that the most frequently mutated genes in LCBM tissues was TP53, with a detection rate of 66.7 %, closely followed by mutation of EGFR, with a detection rate of 40.0 % [15]. Findings of the present investigation are consistent with those of previous research studies, reporting that TP53 was the most common genetic alternation with a detection rate of 61 % (17/28). To identify the putative negative markers of survival, patients were classified into group one and group two according to median OS (10 vs. 24 months, p = 0.0018). Further analysis of gene alteration from NGS revealed that the rates of TP53 mutation and EGFR amplification were higher in group one than in group two. Kaplan-Meier analysis revealed that OS was significantly poorer in patients with TP53 than in those without such mutations (p = 0.014). Similar findings were also found in the EGFR amplification subgroup, revealing that the median OS was significantly worse in patients with EGFR amplification than in those without amplification (p = 0.039). The results of our study were consistent with those of previous studies that concluded that TP53 mutations, especially exon 8 mutations, are a risk factor influencing the effectiveness of osimertinib and further exploration revealed that TP53 mutations were an independent prognostic factor [16]. Fred R. Hirsch and his colleagues investigated the correlation between EGFR gene copy number and its impact on prognosis and reported that high gene copy numbers are a risk factor for poor prognosis [17]. A similar trend was observed in patients with stage I testicular germ cell tumors, demonstrating that patients with EGFR expression have a high risk for recurrence [18]. Based on these findings, it is important to evaluate TP53 and EGFR gene status in patients with NSCLC-BM.

Accumulating evidence from previous research has demonstrated that the driver gene EGFR is highly concordant between the primary tumor and CSF [19]. However, studies investigating the detection rates of EGFR driver gene between metastatic brain tumors and matched PLA are rare. In our study, among patients with NSCLC-BM, 61 % had available PLA samples, and results from NGS testing revealed that the common activating mutations of EGFR L858R and EGFR 19del, as well as the uncommon activating mutation of EGFR G719A, were comparable among brain tumor-matched PLA, suggesting that mutation detection in PLA is a powerful molecular diagnostic tool for patients with NSCLC-BM. The detection rate of negative survival genes, including TP53 or EGFR amplification, was much higher in tumor tissues than in PLA samples.

Due to the blood-brain barrier, circulating tumor DNA from brain tumors is highly restricted from spreading to the peripheral blood, making the liquid medium of PLA most likely to represent extracranial lesions [20]. CCND1 has been widely studied in gliomas, and a previous study has shown that the tumor-promoting role of CDC42EP3 is likely regulated by the downstream targets of CCND1 [21]. Moreover, another study investigated the interaction between E2F1 and miR-107 and between miR-107 and CCND1 and found that E2F1 could reduce miR- 107 transcription and then upregulation of the expression of CCND1, which ultimately leads to progressive glioma [22]. MTAP is the most frequent mutation in (GBM), and research has found that the loss of MTAP in GBM cells is associated with an increase in M2 macrophages, which contribute to immunosuppressive effects [23]. Another study revealed that gene signatures, such as CDKN2A/CDKN2B, DMRTA1, and MTAP, were correlated with worse outcomes with a trend toward higher immune exhaustion markers [24]. In our study, genetic alterations in CCND1 and MTAP were uniquely detected in brain tumors and may predict potential molecular progression mechanisms of BMs.

Our study included a total of 28 patients with NSCLC-BM and revealed that gene signatures, such as TP53 or EGFR amplification were associated with worse survival. However, this study had two major limitations. First, only 28 patients with NSCLC-BM were enrolled, highlighting the need for further research involving a larger sample size to validate our conclusions. Second, we used a 168-target panel sequencing approach, and future studies should consider using a larger panel or Whole-Exome Sequencing to identify additional risk factors negatively associated with survival length.

In conclusion, the present study performed NGS on metastatic brain tumor samples and demonstrated that TP53 and EGFR amplification were negative predictors of OS in patients with NSCLC-BM. Further comparison of genetic alteration between metastatic brain tumors and matched PLA samples demonstrated that TP53 or EGFR amplification was much higher in tumor tissues than in matched PLA samples, and CDKN2A/B or MTAP were detected exclusively in tumor tissues, reflecting the limited predictive value of PLA samples.

Ethical approval and consent to participate

The data used in this study consists solely of previously collected information, contains no identifiable personal information, and no interventions on patients were performed. Therefore, ethical review and approval were waived for this study due to the nature of this research. This research was approved by the ethics committee of Guangdong Sanjiu brain hospital, with the approval number 20190501-3, dated May 1, 2019.

Consent for publication

Not applicable.

Availability of data and materials

The datasets analyzed for the current study are available from the corresponding author on reasonable request.

Funding

This work was supported by 10.13039/501100003785 Medical Scientific Research Foundation of Guangdong Province (No. B2021203 , No. B2021139 , No: B2023418 ). Medical discipline, Construction Project of Pudong Health Committee of Shanghai (Grant No. PWYgy2021-06 ).

CRediT authorship contribution statement

Tao Lin: Writing – original draft. Xusheng Tang: Conceptualization, Writing – review & editing. Wanli Yang: Investigation, Writing – original draft. Hainan Yang: Conceptualization, Investigation, Writing – original draft, Writing – original draft. Zhaoming Zhou: Methodology, Software. Zhijie Chen: Data curation, Formal analysis. Yongqin Zeng: Data curation, Formal analysis, Software. Weiping Hong: Data curation, Formal analysis, Software. Minting Ye: Data curation, Formal analysis. Linbo Cai: Data curation, Resources, Writing – review & editing. Da Liu: Conceptualization, Supervision, Validation, Writing – review & editing. Minying Li: Conceptualization, Validation, Writing – review & editing. Lei Wen: Conceptualization, Supervision, Validation, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Not applicable.
==== Refs
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