Association of TP53 Mutation Status and Sex with Clinical Outcome in Non–Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors: A Retrospective Cohort Study

Article information

Cancer Res Treat. 2025;57(1):70-82
Publication date (electronic) : 2024 August 7
doi : https://doi.org/10.4143/crt.2024.046
1Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
2Precision Medicine Center, Seoul National University Bundang Hospital, Seongnam, Korea
Correspondence: Se Hyun Kim, Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro, Bundang-gu, Seongnam 13620, Korea Tel: 82-31-787-7071 Fax: 82-31-787-4098 E-mail: sehyunkim@snubh.org
Received 2024 January 15; Accepted 2024 August 6.

Abstract

Purpose

Some studies suggest that TP53 mutations are associated with the response to immune checkpoint inhibitors (ICI) in patients with non–small cell lung cancer (NSCLC) and also contribute to sex disparities in several cancers. Thus, we hypothesized that TP53 mutations might serve as sex-dependent genomic biomarkers of ICI treatment response in patients with NSCLC.

Materials and Methods

Clinical data of 100 patients with metastatic NSCLC treated with ICI monotherapy at Seoul National University Bundang Hospital (SNUBH) were retrospectively reviewed. Genomic and clinical datasets of The Cancer Genome Atlas and an ICI-treated lung cancer cohort (cBioPortal) were also analyzed.

Results

In SNUBH cohort, no statistically significant difference was observed in the median progression-free survival (PFS) according to TP53 mutation status (p=0.930); however, female patients with TP53 mutations (MT) had a significantly prolonged median PFS compared to wild-type (WT) (6.1 months in TP53 MT vs. 2.6 months in TP53 WT; p=0.021). Programmed death-ligand 1 (PD-L1) high (≥ 50%) expression was significantly enriched in female patients with TP53 MT (p=0.005). The analysis from publicly available dataset also revealed that females with NSCLC with TP53 MT showed significantly longer PFS than those with TP53 WT (p < 0.001). In The Cancer Genome Atlas analysis, expression of immune-related genes, and tumor mutation burden score in TP53 MT females were higher than in males without TP53 MT.

Conclusion

Female patients with NSCLC with TP53 mutations had high PD-L1 expression and showed favorable clinical outcomes following ICI therapy, suggesting a need for further research to explore the role of TP53 mutations for sex disparities in response to ICI therapy.

Introduction

Lung cancer is one of the leading causes of cancer-related mortality worldwide, with a 5-year survival rate of only 19%. Most patients with lung cancer (85%) suffer from non–small cell lung cancer (NSCLC) [1,2]. Immunotherapy, especially immune checkpoint inhibitor (ICI), has significantly improved clinical outcomes in patients with advanced NSCLC, achieving an outstanding duration of disease control compared to standard cytotoxic chemotherapy approaches [3-5].

Currently, only a small group (up to 20%) of patients achieve a long-standing response to ICIs, indicating the need to identify more effective biomarkers. Specific biomarkers such as programmed death-ligand 1 (PD-L1) expression, tumor mutation burden (TMB), immune signature, and mismatch repair are potential predictive factors of the benefits of ICI treatment [6]. To date, microsatellite instability status and strong PD-L1 expression in tumor cells are the only clinically recommended predictive biomarkers of ICI efficacy, as determined by polymerase chain reaction and immunohistochemistry, respectively [5,7]. Among the various known potential factors, specific genomic alterations can improve the efficacy of immunotherapy. An in-depth understanding of genetic alterations and molecular profiling based on next-generation sequencing (NGS) has dramatically changed the landscape of precision therapy for lung cancer.

The tumor suppressor gene TP53 is the most frequently observed mutated gene in cancer, resulting in the loss of tumor suppressor function or gain of oncogenic activity [8]. In addition to its role in DNA damage response, the p53 protein has also been attributed to intracellular metabolism, genetic and epigenetic stability, inflammatory remodeling, and integration with various pathways [9,10]. Therefore, understanding the relationship between p53 modification and tumor microenvironment (TME) may contribute to more effective cancer treatment. Recent studies have suggested TP53 mutations as prognostic biomarkers associated with longer survival in patients with NSCLC receiving ICI therapy [6,11]. In particular, multi-center data have shown that TP53 missense and nonsense mutations were significantly different in terms of associations with PD-L1 expression, interferon γ (IFN-γ) score, and TME composition [12]. However, the association between TP53 mutations and immunotherapy efficacy remains unclear.

Recent studies have suggested that TP53 mutations affect sex disparities in several types of cancers, including NSCLC [13], particularly causing sex-based differences in the immune features of the TME. Moreover, a meta-analysis of multiple immune features in patients with NSCLC provided a more comprehensive perspective for investigating sex bias in immunotherapy [14]. These observations emphasize the importance of sex in stratifying patients using molecular markers. While the association between TP53 mutations and immune responses is emerging, the impact of patient sex on clinical outcomes is yet to be determined. Therefore, in this study, we hypothesized that TP53 mutation might serve as a sex-dependent genomic biomarker for ICI treatment response in patients with NSCLC.

Materials and Methods

1. Patients and methods

This was a single-center retrospective study of patients with metastatic NSCLC treated with ICI therapy at Seoul National University Bundang Hospital (SNUBH), between January 2016 and July 2021. Initial samples of 142 patients were identified through a database. Eligibility criteria for participation in this study included patients aged ≥ 20 years with histologically confirmed NSCLC—metastatic or recurrent disease—and ≥ 1 measurable lesion according to the Response Evaluation Criteria in Solid Tumors (RECIST) ver. 1.1 [15], with NGS results using three different NGS assays including ver. 1 (n=43), ver. 2 (n=37) or TruSight Oncology 500 Assay (n=20). Patients were excluded if they had any systemic diseases or other malignancies that could influence the survival analysis, received only one treatment cycle of ICI, or had no information on tumor response. The final cohort included in the data analysis were 100 patients and clinical, biological, pathological, and molecular data, including tumor PD-L1 expression and TP53 mutation status assessed by NGS, were retrospectively collected from the patient’s electronic medical records (Fig. 1). PD-L1 expression was evaluated in all tumors by assessing the percentage of tumor cells with membranous staining [16].

Fig. 1.

Diagrammatic representation of the study cohort selection process. NGS, next-generation sequencing; NSCLC, non–small cell lung cancer.

2. Clinical outcomes

The primary endpoint was progression-free survival (PFS), defined as the time from ICI treatment initiation to disease progression or death due to any cause, whichever occurred first. Patients who exhibited no progression were censored at the last follow-up. Secondary endpoints included overall survival (OS), defined as time from ICI initiation to death due to any cause, objective response rate (ORR: complete response [CR] or partial response [PR]), and disease control rate (DCR: CR, PR or stable disease [SD] that lasted > 6 months). The radiographic best response was determined based on RECIST ver. 1.1 criteria. Patients who were surviving at the last follow-up were censored.

3. Publicly available dataset

Genomic and clinical data of a Memorial Sloan Kettering Cancer Center (MSKCC) ICI-treated cohort were obtained from the cBioPortal database [17,18]. This cohort included 240 patients with advanced NSCLC who were treated with anti–PD-L1 monotherapy or combination therapy with anti–cytotoxic T-cell lymphocyte-4, between April 2011 and January 2017. Patients with tumors molecularly profiled using MSK-IMPACT were included in the study. Demographic data, including age, smoking status, histologic subtype, ICI treatment type, number of treatment lines, and PD-L1 expression were provided; TMB and molecular data of TP53 mutation status were retrieved from the NGS data. Clinical outcomes included durable clinical benefit (DCB), which was defined as PR/SD that lasted for > 6 months, and PFS. To assess the differences in immune-related gene mutations between sex and TP53 mutation status, we obtained The Cancer Genome Atlas (TCGA)–Lung Adenocarcinoma (LUAD) and TCGA–Lung Squamous Cell Carcinoma (LUSC) cohorts, including mRNA expression profiling data and somatic mutation data after the removal of epidermal growth factor receptor (EGFR) somatic variants and anaplastic lymphoma kinase fusion cases. TCGA-LUAD and TCGA-LUSC cohorts were combined into the TCGA-NSCLC cohort for subsequent analysis. We evaluated IFNG, CXCL9, PD-L1, LAG3 genes, IFN-γ signature score, and TMB; the unit of gene expression was pan-cancer normalized log2 (fragments per kilobase of exon model per million mapped fragments+1).

4. Statistical analysis

The mean and median values of continuous variables were calculated for the population description, whereas categorical variables were described as frequencies and percentages. For baseline categorical variables, the four groups of patients with NSCLC based on TP53 mutation status and sex were compared using the chi-squared test, or Fisher’s exact test for smaller sample sizes. Kaplan-Meier analysis and the log-rank test were used to estimate the median survival times and their 95% confidence intervals (CI) and statistical significance for the four subgroups: TP53-mutated (MT) females, TP53 MT males, TP53 wild-type (WT) females, and TP53 WT males. Hazard ratios (HR) and their 95% CI were calculated using univariate analysis with Cox proportional hazard models. Variables with > 5% missing data were not included in the multivariate analysis. The variables tested in the univariate analyses of PFS were age, sex, smoking status, histological subtype, the number of lines of prior treatment line, PD-L1 expression level, ICI treatment type, and EGFR mutation status. Only variables that showed an association with survival (p < 0.10) were introduced in the multivariate models of PFS, with three additional clinical variables (age, smoking status, and PD-L1 expression level) forced into the PFS multivariate model because of their clinical interest. Survival curves were plotted using GraphPad Prism (ver. 8.0.1, GraphPad Software Inc., San Diego, CA). The Mann-Whitney U test was performed between subgroups from TCGA for gene expression analysis. The findings were considered statistically significant if the two-sided p-value was < 0.05. All statistical analyses were performed using the IBM SPSS ver. 26 (Armonk, New York, NY).

Results

1. Baseline characteristics of SNUBH cohorts

In total, 100 patients were included in this study, as shown in Table 1. At ICI initiation, 45 (45.0%) patients were over 65 years old; 63 (63.0%) were male, and 63 (63.0%) were former smokers. Seventy-four patients (74.0%) had adenocarcinoma, 15 (15.0%) had squamous cell carcinoma, and 11 (11.0%) had other histological subtypes. Most patients (n=96) had distant metastases. ICI was administered as first-line therapy in 19 patients (19.0%), while the remaining patients (n=81) had received one or more treatments before receiving ICI treatment. The majority of patients (n=88, 88.0%) received ICI monotherapy. Fifteen patients (15.0%) harbored EGFR-activating mutations and 59 patients (59.0%) harbored TP53 mutations. We compared the distribution of clinical features between TP53 mutant type and WT patients. There were no significant differences in the characteristics between patients with and without TP53 mutations according to age, performance status, histologic type, initial TNM stage, a type of treatment, number of prior treatments, PD-L1 expression level, or EGFR mutation status. However, male patients (71.2% vs. 51.2%, p=0.042) and former smokers (72.9% vs. 48.8%, p=0.014) were more frequent in the TP53 mutation group. To evaluate the sex differences in the immunotherapy response based on TP53 mutation status, we divided the patients into four groups: female patients with TP53 MT (n=17, 17.0%), female patients with TP53 WT (n=20, 20.0%), male patients with TP53 MT (n=42, 42.0%), and male patients with TP53 WT (n=21, 21.0%) (Fig. 1).

Baseline characteristics of the study population by TP53 mutation status

2. ORR and DCR of SNUBH cohorts

Overall, ORR was 20.0% and DCR was 43.0%. In subgroup analysis, there was no difference in ORR based on TP53 mutation status in both female patients and male patients (female: 35.3% in TP53 MT vs. 10.0% in TP53 WT, p=0.109; male: 16.7% in TP53 MT vs. 23.8% in TP53 WT, p=0.513). However, in female patients, the DCR was significantly higher in the TP53 mutated group than in the TP53 WT group (76.5% vs. 25.0%, p=0.002). In contrast, no significant difference in DCR was observed between TP53 mutated and TP53 WT male patients (33.3% vs. 52.4%, p=0.145) (Table 2).

Objective response rate and disease control rate by patients’ sex and TP53 mutations status

3. Survival outcomes of SNUBH cohorts

Overall, the median follow-up was 32.1 months (95% CI, 18.1 to 46.1). Median OS was 13.6 months (95% CI, 10.0 to 17.1), and median PFS was 3.4 months (95% CI, 2.3 to 4.4). According to the TP53 mutation status, median PFS in the TP53 mutated group was 3.0 months (95% CI, 1.6 to 4.4) versus 3.9 months in the TP53 WT group (95% CI, 1.3 to 6.6; p=0.930) (Fig. 2A). In a univariate analysis for PFS, there was no significant difference in the median PFS between patients with or without TP53 mutations in all patients (S1 Table). Moreover, the multivariable analysis suggested that female sex had no significant effect on ICI benefit (HR, 0.42; 95% CI, 0.13 to 1.44; p=0.168) (S1 Table). However, when stratified by both TP53 and sex, female patients with TP53 mutation had a significantly prolonged median PFS compared to WT female patients (female with TP53 MT, 6.1 months; 95% CI, 2.2 to 10.1 and TP53 WT, 2.6 months; 95% CI, 1.5 to 3.7; p=0.021) (Fig. 2B). In multivariable analysis, female sex was independently associated with longer PFS in TP53 mutant patients (HR, 0.15; 95% CI, 0.03 to 0.82; p=0.029) (Table 3). Whereas no significant difference in median PFS was found between males with TP53 mutation and TP53 WT (male with TP53 MT, 2.2 months; 95% CI, 1.6 to 2.9 and TP53 WT, 6.6 months; 95% CI, 0.0 to 14.6 months; p=0.183) (Fig. 2C). OS was significantly higher in patients with TP53 WT compared to TP53 mutated patients (patients with TP53 MT, 12.2 months; 95% CI, 8.8 to 15.5 and TP53 WT, 25.1 months; 95% CI, 7.0 to 38.8). However, we did not find any statistically significant interaction between TP53 status and patients’ sex for OS (S2 Fig.).

Fig. 2.

Kaplan-Meier plots showing progression-free survival (PFS) of all patients with and without TP53 mutations after immune checkpoint inhibitor (ICI) treatment initiation (A), PFS of male patients with and without TP53 mutations after ICI treatment initiation (B), PFS of female patients with and without TP53 mutations after ICI treatment initiation (C), and progression-free survival of all patients (n=240) treated at Memorial Sloan Kettering Cancer Center stratified by TP53 mutation status and patients’ sex (D). CI, confidence interval; MT, mutated; WT, wild-type.

Univariable and multivariable Cox regression analysis for PFS according to TP53 mutation status

4. MSKCC public data analysis

To avoid accidental bias caused by a single cohort, we further verified the association between TP53 mutations and sex in the ICI-treated cohort from the MSKCC. We used cBioPortal to collect a published cohort study of patients with NSCLC, including 240 patients receiving ICIs with available mutational and clinical data, to further explore the relationship between gene mutations and ICI prognosis. Overall, more than half of the patients were aged over 65 years old at ICI initiation, and 50.8% of the patients were female. There were 141 (58.8%) TP53 mutations and 99 (41.2%) were TP53 WT (S3 Table). The analysis showed that, when stratified by sex, female patients with TP53 mutation showed significantly longer PFS than that of TP53 WT female patients, while there was no significant difference in PFS between male patients with or without vs. female with TP53 mutations (female with TP53 MT, 5.4 months [95% CI, 3.3 to 7.5], vs. female with TP53 WT, 2.4 months [95% CI, 2.0 to 2.8]; p < 0.001 and male with TP53 MT, 3.6 months [95% CI, 2.7 to 4.6], vs. male with TP53 WT, 2.8 months [95% CI, 0.0 to 5.7]; p=0.760) (Fig. 2D). These results are consistent with the univariate results of our cohorts. Similar to our results, when stratified by sex and TP53 mutation status, a significantly higher DCB was observed in female patients with TP53 mutations than in those with TP53 WT (38.2% vs. 20.4%, p=0.003) (Table 4). Moreover, in multivariate analysis performed in the TP53 mutant group, the female sex showed an independent prognostic factor for longer PFS (HR, 0.67 [95% CI, 0.45 to 1.00]; p=0.048) (Table 5).

Durable clinical benefits of patients treated at Memorial Sloan Kettering Cancer Center by patients’ sex and TP53 mutation status

Univariable and multivariable Cox regression analysis for patients treated at Memorial Sloan Kettering Cancer Center by TP53 mutation status

5. Differences in PD-L1 expression level between male and female patients from SNUBH cohorts

Comparing groups divided by sex in each group with or without TP53 mutation status, PD-L1 high (≥ 50%) expression was significantly enriched in female patients with TP53 mutation compared to those with male patients (58.8% vs. 16.7%, p=0.005), whereas there was no significant difference in PD-L1 expression between the male and female patients in TP53 WT group (p=0.161) (Table 6). Fig. 3 shows that the distribution of TP53 mutations differed significantly in terms of their association with PD-L1 expression between male and female patients (p=0.005). Among the TP53 missense mutant group, the proportion of patients with a PD-L1 score ≥ 50 was prominently higher in the female group than in the male group (p=0.033). Moreover, none of the female patients with TP53 nonsense mutations had a PD-L1 score of < 1.

PD-L1 expression level according to TP53 mutations status and patients’ sex

Fig. 3.

Comparison of the distribution of programmed death-ligand 1 (PD-L1) expression level between male and female patients of Seoul National University Bundang Hospital cohorts (n=100) according to subgroups of patients with TP53 wild-type (A), TP53 mutations (B), TP53 missense mutations (C), and TP53 non-missense mutations (D).

6. Expression level of immune-related genes, INF-γ signature, and TMB score from TCGA

Given the potential sex differences in TP53 mutation, we explored the correlation of IFNG, CXCL9, LAG3, and PDL1 expression levels, IFN-γ signature, and TMB score stratified by sex (Sub1: female patients with TP53 mutation; Sub2: female patients without TP53 mutation; Sub3: male patients with TP53 mutation; Sub4: male patients without TP53 mutation). In the TCGA-NSCLC cohort, both female and male patients with TP53 mutations had higher TMB than TP53 WT patients (Sub1 vs. Sub2, p < 0.001; Sub3 vs. Sub4, p < 0.001). TP53 mutant male patients showed higher LAG3 expression and IFN-γ signature scores than TP53 WT male patients. However, there were no significant differences in IFNG, CXCL9, LAG3, and PDL1 gene expression levels, and IFN-γ signature score between female patients with or without TP53 mutation. We found that the expression of IFNG, CXCL9, LAG3, PDL1, and IFN-γ signature score, and TMB score in TP53 mutant female patients were higher than in male patients without TP53 mutation (Fig. 4).

Fig. 4.

The boxplot of immune-related gene expression and tumor mutation burden (TMB) score in non–small cell lung cancer from The Cancer Genome Atlas subgroups stratified by TP53 mutations and patients’ sex. (A-E) Elevated expression of anticancer immunity gene expression level was observed in female patients with TP53 mutation. (F) Correlation of TP53 mutation with TMB expression stratified by sex (Sub 1: female TP53 MT; Sub 2: female TP53 WT; Sub 3: male TP53 MT; Sub 4: male TP53 WT). MT, mutated; PD-L1, programmed death-ligand 1; WT, wild-type.

Discussion

In this study, we showed that female patients with TP53 mutations had higher PD-L1 expression, increased immune-related gene expression, and favorable clinical benefits of ICI treatment. Female NSCLC patients with TP53 mutations had a significantly higher DCR and longer PFS than those with TP53 WT, while no significant difference was observed in male patients. Multivariate analysis further demonstrated that female sex was a significant prognostic factor for longer PFS in the TP53 mutation group. These findings suggest that female sex could potentially serve as a predictive biomarker for ICI therapy in TP53 mutant patients with metastatic NSCLC. Moreover, analysis of an independent dataset from the MSKCC cohort further supported our results that female NSCLC patients with TP53 mutations had a better prognosis than female patients without TP53 mutations in NSCLC.

To the best of our knowledge, this is the first study to demonstrate that TP53 mutations induce sex-dependent ICI responses. In our study, we observed a notable increase in the prevalence of PD-L1 high (≥ 50%) expression among female patients with TP53 mutations, as compared to male patients (58.8% vs. 7.0%, p=0.005). In addition, PD-L1 expression did not correlate with survival, whereas multivariate analysis showed that female sex was independently associated with better PFS in TP53 mutant patients, suggesting that PD-L1 did not represent a confounding factor. These results suggest that TP53 mutations in female patients could be involved in regulating PD-L1 expression.

TP53, a tumor suppressor, is commonly mutated in cancers. Recently, several studies have provided compelling evidence that TP53 mutations are potential prognostic biomarkers for patients with cancers such as head and neck squamous cell cancer and lung adenocarcinoma who undergo ICI treatment [6,11,19]. Dong et al. [6] retrospectively showed that in 30 metastatic NSCLC patients treated with pembrolizumab, the median PFS was significantly longer in the TP53-mutated group than in the TP53 WT group (14.5 months vs. 3.5 months, p=0.042). Additionally, Assoun et al. [11] demonstrated that TP53 gene mutations in patients with metastatic NSCLC (n=72) treated with ICI were associated with better OS, PFS, and ORR. In contrast, survival analysis of the MSK-IMPACT cohort of 350 NSCLC patients who received immunotherapy showed that NSCLC patients with TP53 truncating mutations had a significantly lower OS than those with WT TP53 (9 months vs. 14 months; p=0.019) [20]. Therefore, the association between TP53 mutations and immunotherapy efficacy remains controversial. In our study, overall patients with TP53 mutations showed no survival benefit from immunotherapy compared to those with TP53 WT. However, among TP53 mutant patients, when stratified with patients’ sex, the female patients experienced significantly longer PFS compared to male patients (6.1 months vs. 2.2 months, p=0.039). In addition, we observed the prognostic role of TP53 mutations in the context of sex from survival analysis of the MSKCC cohort of 240 patients with metastatic NSCLC who were treated with ICIs. This suggested that there might be sex biases of TP53 mutation, in particular for female NSCLC patients who were treated with immunotherapy.

Interactions between sex and p53 pathway genes have been observed in the following literature. Firstly, non-expressed mutations (NEMs) in the X chromosome are more common in females than in males, and a significant number of these NEMs are found in genes related to the p53 network, such as E3 Ubiquitin Protein Ligase 1 (HUWE1) and ATP-dependent helicase ATRX (ATRX). This suggests that females have a protective effect that limits the expression of somatic mutations [13]. Secondly, WT p53 can inhibit tumor development through various pathways [8]. However, the loss of p53 as a tumor suppressor leads to the stochastic reactivation of the inactive X chromosome (Xi) and the expression of X-linked genes from both alleles. By increasing the likelihood of stochastic transcriptional events in Xi, p53 may contribute to the sex bias observed in various cancer types [21].

Notably, immunity differs between the sexes. Females generally exhibit better adaptive and innate immune responses than males, resulting in enhanced antiviral T-cell immunity and anticancer responses [22,23]. Moreover, immune infiltration is more abundant in female tumors, and all T-cell subpopulations are significantly enriched in the TME of females [24]. In females, the TME of NSCLC is distinguished by a higher prevalence of T-cell dysfunction, increased expression of inhibitory immune checkpoint molecules, and a greater presence of immunosuppressive cells. By contrast, the TME of NSCLC in males is characterized by a lower abundance of several innate and adaptive immune cell subsets [24].

We also have analyzed the TCGA-NSCLC data for the gene expression of immune-related genes (such as IFNG, CXCL9, LAG3, and PDL1), IFN-γ signature, and TMB score considering sex and TP53 mutation status. The results showed that NSCLC with TP53 mutation had high immune-related gene expression and high TMB as noted by previous studies. However, the gene expression of immune-related genes seemed similar regardless of TP53 mutation status in female patients. TP53 mutant female patients showed higher PD-L1 expression levels than male TP53 WT patients (p=0.002). The correlation of high PD-L1 expression level and clinical benefit in TP53 mutant female patients might be a possible explanation for sex disparities in TP53 mutant NSCLC patients treated with ICI.

Our study has several limitations. First, it was retrospective in nature, with a lack of blinded independent assessment of response, although ORR and DCR were secondary endpoints. Second, PFS prolongation in female patients with TP53 mutations has not translated into a longer OS. Although we cannot directly answer this point, post-progression survival of the patients was probably affected by other prognostic factors, including subsequent treatment. Third, the limited size of our single-center series could have resulted in bias and a lack of statistical power. In the current study, a profound difference was observed in the median PFS between male patients with TP53 mutation and TP53 WT, but the p-value was not statistically significant. This could be due to the small sample size of the group. Moreover, co-mutations in TP53 and KRAS were proven to be promising biomarkers for ICI response [6]. However, the presence of co-mutations was not evaluated in this study. Future studies with larger sample sizes and prospective designs are needed to confirm these findings and evaluate the clinical implications of TP53 mutation status as a predictive biomarker for ICI therapy in patients with NSCLC.

In conclusion, we found that female NSCLC patients with TP53 mutation had high PD-L1 expression levels and showed favorable clinical outcomes after ICI therapy. The role of TP53 mutations in the sex disparities in patients with NSCLC treated with ICI needs to be further validated.

Electronic Supplementary Material

Supplementary materials are available at Cancer Research and Treatment website (https://www.e-crt.org).

Notes

Ethical Statement

This study was approved by the Institutional Review Board of the SNUBH (IRB number: B-2104-681-104), and the requirement for informed consent was waived because of the retrospective nature of this study. This study was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines.

Author Contributions

Conceived and designed the analysis: Choi S, Kim SH, Lee S.

Collected the data: Choi S, Kim SH.

Contributed data or analysis tools: Choi S, Kim SH, Lee S, Seo J, Kang M, Jung EH, Kim SA, Suh KJ, Lee JY, Kim JW (Ji-Won Kim), Kim JW (Jin Won Kim), Lee JO, Kim YJ, Lee KW, Kim JH, Bang SM, Lee JS.

Performed the analysis: Choi S, Kim SH, Lee S.

Wrote the paper: Choi S, Kim SH.

Conflicts of Interest

Conflict of interest relevant to this article was not reported.

Acknowledgements

This study was supported by the SNUBH Research Fund [grant no.: 02-2020-0048].

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin 2020;70:7–30.
2. Duma N, Santana-Davila R, Molina JR. Non-small cell lung cancer: epidemiology, screening, diagnosis, and treatment. Mayo Clin Proc 2019;94:1623–40.
3. Brahmer J, Reckamp KL, Baas P, Crino L, Eberhardt WE, Poddubskaya E, et al. Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med 2015;373:123–35.
4. Borghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Ready NE, et al. Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med 2015;373:1627–39.
5. Reck M, Rodriguez-Abreu D, Robinson AG, Hui R, Csoszi T, Fulop A, et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. N Engl J Med 2016;375:1823–33.
6. Dong ZY, Zhong WZ, Zhang XC, Su J, Xie Z, Liu SY, et al. Potential predictive value of TP53 and KRAS mutation status for response to PD-1 blockade immunotherapy in lung adenocarcinoma. Clin Cancer Res 2017;23:3012–24.
7. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 2015;372:2509–20.
8. Bykov VJN, Eriksson SE, Bianchi J, Wiman KG. Targeting mutant p53 for efficient cancer therapy. Nat Rev Cancer 2018;18:89–102.
9. Mello SS, Attardi LD. Deciphering p53 signaling in tumor suppression. Curr Opin Cell Biol 2018;51:65–72.
10. Jiang L, Hickman JH, Wang SJ, Gu W. Dynamic roles of p53-mediated metabolic activities in ROS-induced stress responses. Cell Cycle 2015;14:2881–5.
11. Assoun S, Theou-Anton N, Nguenang M, Cazes A, Danel C, Abbar B, et al. Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer. Lung Cancer 2019;132:65–71.
12. Sun H, Liu SY, Zhou JY, Xu JT, Zhang HK, Yan HH, et al. Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma. EBioMedicine 2020;60:102990.
13. Haupt S, Caramia F, Herschtal A, Soussi T, Lozano G, Chen H, et al. Identification of cancer sex-disparity in the functional integrity of p53 and its X chromosome network. Nat Commun 2019;10:5385.
14. Ye Y, Jing Y, Li L, Mills GB, Diao L, Liu H, et al. Sex-associated molecular differences for cancer immunotherapy. Nat Commun 2020;11:1779.
15. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45:228–47.
16. Rimm DL, Han G, Taube JM, Yi ES, Bridge JA, Flieder DB, et al. A prospective, multi-institutional, pathologist-based assessment of 4 immunohistochemistry assays for PD-L1 expression in non-small cell lung cancer. JAMA Oncol 2017;3:1051–8.
17. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2012;2:401–4.
18. Rizvi H, Sanchez-Vega F, La K, Chatila W, Jonsson P, Halpenny D, et al. Molecular determinants of response to anti-programmed cell death (PD)-1 and anti-programmed death-ligand 1 (PD-L1) blockade in patients with non-small-cell lung cancer profiled with targeted next-generation sequencing. J Clin Oncol 2018;36:633–41.
19. Lyu H, Li M, Jiang Z, Liu Z, Wang X. Correlate the TP53 mutation and the HRAS mutation with immune signatures in head and neck squamous cell cancer. Comput Struct Biotechnol J 2019;17:1020–30.
20. Zhao L, Qu X, Wu Z, Li Y, Zhang X, Guo W. TP53 somatic mutations are associated with poor survival in non-small cell lung cancer patients who undergo immunotherapy. Aging (Albany NY) 2020;12:14556–68.
21. Delbridge AR, Kueh AJ, Ke F, Zamudio NM, El-Saafin F, Jansz N, et al. Loss of p53 causes stochastic aberrant X-chromosome inactivation and female-specific neural tube defects. Cell Rep 2019;27:442–54.
22. Conforti F, Pala L, Bagnardi V, De Pas T, Martinetti M, Viale G, et al. Cancer immunotherapy efficacy and patients’ sex: a systematic review and meta-analysis. Lancet Oncol 2018;19:737–46.
23. Wallis CJ, Butaney M, Satkunasivam R, Freedland SJ, Patel SP, Hamid O, et al. Association of patient sex with efficacy of immune checkpoint inhibitors and overall survival in advanced cancers: a systematic review and meta-analysis. JAMA Oncol 2019;5:529–36.
24. Klein SL, Flanagan KL. Sex differences in immune responses. Nat Rev Immunol 2016;16:626–38.

Article information Continued

Fig. 1.

Diagrammatic representation of the study cohort selection process. NGS, next-generation sequencing; NSCLC, non–small cell lung cancer.

Fig. 2.

Kaplan-Meier plots showing progression-free survival (PFS) of all patients with and without TP53 mutations after immune checkpoint inhibitor (ICI) treatment initiation (A), PFS of male patients with and without TP53 mutations after ICI treatment initiation (B), PFS of female patients with and without TP53 mutations after ICI treatment initiation (C), and progression-free survival of all patients (n=240) treated at Memorial Sloan Kettering Cancer Center stratified by TP53 mutation status and patients’ sex (D). CI, confidence interval; MT, mutated; WT, wild-type.

Fig. 3.

Comparison of the distribution of programmed death-ligand 1 (PD-L1) expression level between male and female patients of Seoul National University Bundang Hospital cohorts (n=100) according to subgroups of patients with TP53 wild-type (A), TP53 mutations (B), TP53 missense mutations (C), and TP53 non-missense mutations (D).

Fig. 4.

The boxplot of immune-related gene expression and tumor mutation burden (TMB) score in non–small cell lung cancer from The Cancer Genome Atlas subgroups stratified by TP53 mutations and patients’ sex. (A-E) Elevated expression of anticancer immunity gene expression level was observed in female patients with TP53 mutation. (F) Correlation of TP53 mutation with TMB expression stratified by sex (Sub 1: female TP53 MT; Sub 2: female TP53 WT; Sub 3: male TP53 MT; Sub 4: male TP53 WT). MT, mutated; PD-L1, programmed death-ligand 1; WT, wild-type.

Table 1.

Baseline characteristics of the study population by TP53 mutation status

Variable Total (n=100) TP53 MT (n=59) TP53 WT (n=41) p-value
Age (yr)a)
 < 65 55 (55.0) 32 (54.2) 23 (56.1) 0.854
 ≥ 65 45 (45.0) 27 (45.8) 18 (43.9)
Sex
 Male 63 (63.0) 42 (71.2) 21 (51.2) 0.042
 Female 37 (37.0) 17 (28.8) 20 (48.8)
ECOG performance status
 0-1 74 (74.0) 40 (67.8) 34 (82.9) 0.090
 ≥ 2 26 (26.0) 19 (32.2) 7 (17.1)
Smoking status
 Never smoker 37 (37.0) 16 (27.1) 21 (51.2) 0.014
 Former smoker 63 (63.0) 43 (72.9) 20 (48.8)
TNM stage
 IIIB 4 (4.0) 2 (3.4) 2 (4.9) > 0.99
 IV 96 (96.0) 57 (96.6) 39 (95.1)
Histologic type
 Adenocarcinoma 74 (74.0) 43 (72.9) 31 (75.6) 0.344
 Squamous cell carcinoma 15 (15.0) 11 (18.6) 4 (9.8)
 Othersb) 11 (11.0) 5 (8.5) 6 (14.6)
EGFR mutation status
 Negative 85 (85.0) 52 (88.1) 33 (80.5) 0.292
 Positive 15 (15.0) 7 (11.9) 8 (19.5)
Type of ICI
 Monotherapy 88 (88.0) 54 (91.5) 34 (82.9) 0.222
 Combinationc) 12 (12.0) 5 (8.5) 7 (17.1)
Prior treatment line
 0 19 (19.9) 11 (18.6) 8 (19.5) 0.913
 ≥ 1 81 (81.0) 48 (81.4) 33 (80.5)
TMB score
 < 10 mut/Mb 32 (32.0) 22 (37.3) 10 (24.4) 0.952
 ≥ 10 mut/Mb 25 (25.0) 17 (28.8) 8 (19.5)
 Unknown 43 (43.0) 20 (33.9) 23 (56.1)
PD-L1 expression
 < 1% 42 (42.0) 21 (35.6) 21 (51.2) 0.234
 1%-49% 34 (34.0) 21 (35.6) 13 (31.7)
 ≥ 50% 24 (24.0) 17 (28.8) 7 (17.1)

Values are presented as number (%) unless otherwise indicated. ECOG, Eastern Cooperative Oncology Group; EGFR, epidermal growth factor receptor; ICI, immune checkpoint inhibitor; MT, mutated; PD-L1, programmed death-ligand 1; TMB, tumor mutation burden; WT, wild-type.

a)

At ICI initiation,

b)

This includes poorly differentiated (n=6), sarcomatoid carcinoma (n=4), and large-cell neuroendocrine type (n=1),

c)

ICI treatment combined with cytotoxic chemotherapy.

Table 2.

Objective response rate and disease control rate by patients’ sex and TP53 mutations status

Best response Total (n=100) Female (n=37)
Male (n=63)
TP53 MT (n=17) TP53 WT (n=20) p-value TP53 MT (n=42) TP53 WT (n=21) p-value
CR 0 0 0 - 0 0 -
PR 20 (20.0) 6 (35.3) 2 (10.0) - 7 (16.7) 5 (23.8) -
SD 36 (36.0) 8 (47.1) 9 (45.0) - 12 (28.6) 7 (33.3) -
PD 44 (44.0) 3 (17.6) 9 (45.0) - 23 (54.8) 9 (42.9) -
ORR (%)a) 20.0 35.3 10.0 0.109 16.7 23.8 0.513
DCR (%)b) 43.0 76.5 25.0 0.002 33.3 52.4 0.145

Values are presented as number (%) unless otherwise indicated. CR, complete response; DCR, disease control rate; MT, mutated; ORR, objective response rate; PD, progressive disease; PR, partial response; SD, stable disease; WT, wild-type.

a)

ORR: CR or PR,

b)

DCR: CR, PR or SD that lasted > 6 months.

Table 3.

Univariable and multivariable Cox regression analysis for PFS according to TP53 mutation status

Variable TP53 MT (n=59)
TP53 WT (n=41)
No. of patients Univariable
Multivariable
No. of patients Univariable
Multivariable
HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value
Agea) (yr)
 < 65 32 1 1 23 1 1
 ≥ 65 27 1.17 (0.66-2.07) 0.592 1.55 (0.84-2.88) 0.162 18 0.70 (0.36-1.36) 0.297 0.72 (0.34-1.52) 0.387
Sex
 Male 42 1 1 21 1 1
 Female 17 0.51 (0.23-0.98) 0.044 0.15 (0.03-0.82) 0.029 20 2.01 (1.03-3.92) 0.041 0.61 (0.06-5.87) 0.664
Smoking status
 Never smoker 16 1 1 21 1 1
 Former smoker 43 1.59 (0.82-3.09) 0.166 0.25 (0.05-1.40) 0.114 20 0.49 (0.25-0.96) 0.037 0.23 (0.21-2.40) 0.218
Histologic type
 Othersb) 5 1 - 6 1 1
 Adenocarcinoma 43 1.34 (0.41-4.37) 0.628 - - 31 1.67 (0.68-4.09) 0.266 0.22 (0.02-2.73) 0.240
 Squamous cell carcinoma 11 1.34 (0.41-4.37) 0.123 - - 4 5.14 (1.34-19.74) 0.017 1.19 (0.08-18.32) 0.902
EGFR mutation status
 Negative 52 1 - 33 1 -
 Positive 7 1.63 (0.73-3.65) 0.238 - - 8 1.49 (0.67-3.32) 0.329 - -
Type of ICI
 Monotherapy 54 1 - 34 1 -
 Combinationc) 5 1.15 (0.45-2.94) 0.773 - - 7 0.84 (0.37-1.93) 0.682 - -
Prior treatment line
 1 11 1 - 8 1 -
 ≥ 2 48 1.63 (0.79-3.37) 0.188 - - 33 1.18 (0.54-2.60) 0.681 - -
PD-L1 expression
 < 1% 21 1 1 21 1 1
 1%-49% 21 1.40 (0.74-2.66) 0.301 1.68 (0.87-3.21) 0.121 13 0.95 (0.47-1.96) 0.897 0.87 (0.42-1.83) 0.964
 ≥ 50% 17 0.69 (0.33-1.43) 0.320 0.91 (0.40-2.07) 0.818 7 0.35 (0.14-0.89) 0.027 0.09 (0.01-1.20) 0.068

CI, confidence interval; EGFR, epidermal growth factor receptor; HR, hazard ratio; ICI, immune checkpoint inhibitor; MT, mutated; PD-L1, programmed death-ligand 1; PFS, progression-free survival; WT, wild type.

a)

At ICI initiation,

b)

This includes poorly differentiated (n=6), sarcomatoid carcinoma (n=4), and large-cell neuroendocrine type (n=1),

c)

ICI treatment combined with cytotoxic chemotherapy.

Table 4.

Durable clinical benefits of patients treated at Memorial Sloan Kettering Cancer Center by patients’ sex and TP53 mutation status

Clinical benefit Total (n=240)
Female (n=122)
Male (n=118)
TP53 MT TP53 WT p-value TP53 MT TP53 WT p-value TP53 MT TP53 WT p-value
DCBa) 45 (31.9) 24 (24.2) 0.041 26 (38.2) 11 (20.4) 0.003 19 (26.0) 13 (28.9) 0.903
NDB 85 (60.3) 73 (73.7) 36 (52.9) 43 (79.6) 49 (67.1) 30 (66.7)
N/A 11 (7.8) 2 (2.0) 6 (8.8) 0 6 (8.8) 0

Values are presented as number (%). DCB, durable clinical benefit; MT, mutated; N/A, not available; NDB; no durable benefit; WT, wild-type.

a)

DCB: complete response, partial response, or stable disease that lasted > 6 months.

Table 5.

Univariable and multivariable Cox regression analysis for patients treated at Memorial Sloan Kettering Cancer Center by TP53 mutation status

Variable TP53 MT (n=141)
TP53 WT (n=99)
No. of patients Univariable
Multivariable
No. of patients Univariable
Multivariable
HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value
Agea) (yr)
 < 65 69 1 1 42 1 1
 ≥ 65 72 1.28 (0.87-1.89) 0.213 1.25 (0.84-1.85) 0.273 57 0.78 (0.51-1.18) 0.242 0.77 (0.502-1.17) 0.212
Sex
 Male 73 1 1 45 1 1
 Female 68 0.70 (0.47-1.02) 0.065 0.67 (0.45-1.00) 0.048 54 1.45 (0.95-2.21) 0.086 1.41 (0.91-2.18) 0.123
Smoking status
 Never smoker 21 1 1 26 1 1
 Former smoker 120 0.53 (0.32-0.88) 0.014 0.41 (0.24-0.70) 0.001 73 1.06 (0.66-1.68) 0.821 1.03 (0.63-1.67) 0.910
Histologic type
 Othersb) 13 1 - 7 1 -
 Adenocarcinoma 102 1.75 (0.76-4.02) 0.186 - 84 0.46 (0.21-1.01) 0.052 -
 Squamous cell carcinoma 26 2.03 (0.81-5.06) 0.129 - - 8 0.44 (0.15-1.27) 0.130 - -
Prior treatment line
 1 34 1 - 17 1 -
 ≥ 2 107 0.84 (0.57-1.23) 0.367 - - 82 1.00 (0.51-1.93) 0.989 - -
Type of ICI
 Monotherapy 120 1 1 86 1 1
 Combinationc) 21 0.54 (0.30-0.99) 0.044 0.50 (0.27-0.91) 0.023 13 0.53 (0.28-1.01) 0.054 0.57 (0.29-1.11) 0.098
TMB score
 < 10 mut/Mb 71 1 - 87 1 -
 ≥ 10 mut/Mb 70 0.84 (0.57-1.23) 0.367 - - 12 1.00 (0.51-1.93) 0.989 - -

CI, confidence interval; HR, hazard ratio; ICI, immune checkpoint inhibitor; MT, mutated; TMB, tumor mutation burden; WT, wild type.

a)

At ICI initiation,

b)

This includes non–small cell lung cancer (n=13), and large-cell neuroendocrine type (n=7),

c)

ICI treatment combined with cytotoxic T-cell lymphocyte-4 inhibitor.

Table 6.

PD-L1 expression level according to TP53 mutations status and patients’ sex

Variable Total (n=100) TP53 MT (n=59)
TP53 WT (n=41)
Female (n=17) Male (n=42) p-value Female (n=20) Male (n=21) p-value
PD-L1 expression
 < 1% 42 (42.0) 3 (17.6) 18 (42.9) 0.005 12 (60.0) 9 (42.9) 0.161
 1%-49% 34 (34.0) 4 (23.5) 17 (40.5) 7 (35.0) 6 (28.6)
 ≥ 50% 24 (24.0) 10 (58.8) 7 (16.7) 1 (5.0) 6 (28.6)

Values are presented as number (%). MT, mutated; PD-L1, programmed death-ligand 1; WT, wild-type.