Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non‐small cell lung cancer

Abstract Background This study aimed to explore the prognostic value of tumor mutational burden (TMB) combined with smoking status in advanced non‐small cell lung cancer (NSCLC) patients who received immune checkpoint inhibitor therapy (anti PD‐1/PD‐L1 therapy) combined with chemotherapy or anti‐angiogenesis therapy. Methods We conducted a retrospective analysis of NSCLC patients who underwent next‐generation sequencing test (either 295‐gene panel NGS or 1021‐gene panel NGS) from September 2017 to November 2020. The relationship between TMB and smoking status was investigated. Kaplan–Meier survival analysis was used to compare progression‐free survival (PFS) of the NSCLC patients who received combination immunotherapy grouped by TMB value and smoking status. Results We enrolled 323 cases and 388 cases of NSCLC patients in the 295‐gene panel cohort and 1021‐gene panel cohort, respectively. Positive correlation between TMB and smoking status was found in lung adenocarcinoma, but not in lung squamous cell carcinoma. Participants with both high TMB and smoking status who received immune checkpoint therapy combined with chemotherapy or anti‐angiogenesis therapy had longer PFS than other participants (p < 0.05). Conclusions The combination of TMB with smoking status might be a potential predictor for the efficacy of combination immunotherapy in advanced NSCLC.


| INTRODUCTION
Immune checkpoint inhibitors (ICIs) for programmed cell death 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) blockade have become one of the effective treatments for advanced non-small cell lung cancer (NSCLC). 1 Tumor mutational burden (TMB) has been shown to predict the efficacy of ICI in the clinical studies of CheckMate 026 2 and CheckMate 227 3 in NSCLC, but it was controversial in KEYNOTE-021 4 /158 5 /189 6 /407 7 studies. Therefore, the predictive value of TMB for ICI treatment in NSCLC still needs further investigation. In addition, due to the lack of standardized detection procedures of TMB, the definition of TMB high from different next-generation sequencing (NGS) platforms needs further clinical investigation and comparison as well.
Currently the combination of ICI with chemotherapy or anti-angiogenesis therapy has become a hotspot in the clinical treatment of advanced NSCLC. Some patients have benefited from such combination therapy, including the patients with low PD-L1 expression [6][7][8] ; however, the clinical efficacy prediction markers are lacking for such combination therapy. 9 Further study is needed to determine if TMB could predict the clinical efficacy in NSCLC patients receiving ICI combined with chemotherapy or anti-angiogenesis therapy.
Smoking is well known as the primary cause of NSCLC. 10 However, the correlation between smoking history and TMB is still contentious, and its role in efficacy prediction in ICI treatment of NSCLC needs additional study as well. 11,12 One study showed that NSCLC patients who smoked could benefit more from second-line immunotherapy than non-smoking patients after resistance to first-line targeted therapy. 13 Therefore, the relationship between smoking status and TMB, and the predictive value of combining smoking status with TMB for combination immunotherapy in NSCLC still needs further investigation.
In the present study, two advanced NSCLC cohorts from our hospital who received either 295-gene panel NGS test or 1021-gene panel NGS test were utilized to analyze the correlation between the smoking status and TMB and their roles in efficacy prediction in NSCLC patients who received ICI combined chemotherapy or antiangiogenesis therapy.

| TMB detection
Tumor mutational burden value was calculated from the high-throughput sequencing data from both 295gene panel and 1021-gene panel. 14,15 The gene list for each panel is listed in Table S2 and S3. The NGS library preparation and sequencing protocol were performed as follows. In brief, the genomic DNA was fragmented by Covaris M220 focused ultrasonicator (Covaris, Inc.), converted to an NGS library by end repair, A-tailing, and adapter ligation. Then, DNA library was purified and quantified using Qubit 2.0 fluorimeter with the dsDNA high-sensitivity assay kit (Life Technologies). The samples tested with 295-gene panel were indexed and sequenced on Nextseq500 (Illumina, Inc.) and 1021-gene panel indexed samples were sequenced on Gene+Seq-2000 (Geneplus-Beijing Institute) with paired-end reads. In both 295-gene and 1021-gene panels, TMB was calculated by the number of somatic missense mutations, nonsense mutations, and coding indels and displayed as the number of mutations per Mb of captured genome. Fusions, copy number variations, and non-coding mutations were not counted. According to x-tile software, 16 the optimal cutoff value used to define high TMB is 6.1 mutations/Mb in 295-gene panel and 15.4 mutations/Mb in 1021-gene panel, respectively.

| Follow-up
The clinical information of all patients was retrospectively obtained from their medical records. Treatment efficacy was evaluated according to the response evaluation criteria in solid tumors (RECIST) 1.1 criteria. The endpoint of follow-up was the last visit or disease progression after participants who received combination immunotherapy, and the end point of this study was progression-free survival (PFS).

| Statistical analysis
Statistical analysis was performed using the statistical software SPSS 20.0 (IBM Corp.). Measurement data were expressed as means ± SD, and comparisons between groups were performed by t-test. A p < 0.05 was considered to be statistically significant. One-way ANOVA was used between the three groups of data, and p < 0.05 was considered to be statistically different. Kaplan-Meier analysis was used to estimate PFS after receiving combination therapy. GraphPad Prism 7.0 (GraphPad Software) was used for graphing.

| Study population
This study enrolled 323 cases of NSCLC patients in the 295 cohort and 388 cases in the 1021 cohort. The characteristics of participants in the two cohorts are displayed in Table 1. Among them, there were 32 and 58 patients from 295 cohort and 1021 cohort, respectively, who received ICI combined with chemotherapy or anti-angiogenesis therapy (detailed information of these patients is shown in the Table S1).
The TMB value in smoking LUAD patients was significantly higher than that in non-smokers in both cohorts (295 cohort, 10.430 ± 7.468 mutations/Mb in 84 cases smoking patients vs. 6.452 ± 6.366 mutations/ Mb in 154 cases non-smoking patients, p = 0.0002; 1021 cohort, 9.374 ± 8.479 mutations/Mb in 108 cases smoking patients vs. 5.010 ± 5.048 mutations/Mb in 201 cases non-smoking patients, p < 0.0001) ( Figure 1A,B) Figure 1A,B). The TMB value of LUAD patients with a smoking index greater than 30 packs × years was significantly greater than that of non-smoking patients ( Figure  2). Although the TMB value of smoking LUSC patients in the two cohorts was higher than that in non-smoking patients, the difference was not statistically significant (295 cohort, 11.950 ± 9.066 mutation/Mb in 35 cases smoking patients vs. 5.034 ± 3.094 mutations/Mb in 5 cases non-smoking patients, p = 0.3503; 1021 cohort, 9.374 ± 8.479 mutations/Mb in 33 cases smoking patients vs. 5.010 ± 5.048 mutations/Mb in 12 cases nonsmoking patients, p = 0.2278) ( Figure 1C,D).

| Clinical outcomes
The median follow-up time of the 295 cohort and the 1021 cohort was 6.47 and 6.17 months, respectively. In the 295 cohort, the PFS of smoking patients was slightly longer than that of non-smoking patients, but the difference was not statistically significant (9.17 months in smoking patients vs. 6.00 months in non-smoking patients, p = 0.1070). The PFS of patients with TMB high (TMB-H) was similar to that of patients with TMB low (TMB-L) (6.93 months in TMB-H vs. 7.77 months in TMB-L, p = 0.7030). In the 1021 cohort, the PFS of non-smokers was slightly longer than that of smokers, but the difference was not statistically significant (9.03 months in smoking patients vs. 10.23 months in non-smoking patients, p = 0.1240). Patients with TMB-H had a slightly longer PFS than patients with TMB-L, but the difference was not statistically

| DISCUSSION
In the clinical treatment of advanced NSCLC, ICI targeting PD1/PD-L1 has made rapid progress, 17  PD-L1 inhibitor monotherapy or combination therapy with chemotherapy/antiangiogenic therapy has become one of the main treatment especially for NSCLC patients without the presence of driver gene mutation. 18 However, currently there is no effective biomarkers for the efficacy prediction of combination immunotherapy, and the relationship between TMB and smoking status in NSCLC is controversial. 11,19 In this study, we retrospectively recruited 711 cases NSCLC patients who received two different NGS panel tests to analyze the relationship between TMB and smoking status, and we further evaluated the efficacy predictive value of smoking status and TMB in 90 cases NSCLC patients who received ICI therapy combined with chemotherapy/anti-angiogenesis therapy.
Tumor mutational burden as a predictive marker of ICI efficacy is controversial in multiple studies, moreover, there is a lack of evidence for its application in ICI combination therapy. [4][5][6][7] Chen et al. found that TMB could not predict treatment efficacy in advanced NSCLC patients treated with camrelizumab combined with apatinib. 20 Another study showed that TMB could not predict the efficacy of sintilimab combined with dual-drug chemotherapy. 21 In addition, the definition of high TMB measured by different NGS detection platforms (different gene panels) might be different. 22 Our results also found in the two different patients cohorts that TMB alone could not predict the prognosis of advanced NSCLC patients receiving ICI combination therapy in both cohorts.
Smoking NSCLC patients may carry more gene mutations, especially TP53, KRAS, and PIK3. 19,23 Therefore, the TMB value in smoking patients is supposed to be increased. 24 However, the correlation between the smoking index and the TMB value of NSCLC patients is still controversial. 11 Previous studies have shown that smoking patients receiving ICI monotherapy have better response rates and PFS than non-smokers, but there is no difference in overall survival between two groups. 25 In ICI combined chemotherapy/anti-angiogenesis therapy, it has also been shown that both smokers and non-smokers could benefit from combination therapy compared to chemotherapy alone. 26,27 Another study also showed that in patients with PD-L1 expression ≥50%, non-smokers had shorter PFS than heavysmokers, but the difference was not statistically significant. 12 Our study also found that TP53, KRAS, and PIK3 gene mutations in smoking patients were increased compared with non-smoking patients. In the two cohorts, the TMB value in F I G U R E 1 The smoking patients had higher TMB value than non-smoking patients in LUAD. Plot showing TMB values of NSCLC patients with different smoking status in the 295 cohort (A, C) and the 1021 cohort (B, D). LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; TMB, tumor mutational burden LUAD was correlated with the smoking index (295 cohort, r 2 = 0.0771, p < 0.0001; 1021 cohort, r 2 = 0.0884, p < 0.0001). However, the TMB value of LUSC has nothing to do with the smoking index. Our results also found that smoking status alone cannot predict the prognosis of NSCLC patients treated with ICI combination therapy. Taken together, our results showed that neither TMB alone nor smoking status alone could predict the efficacy of ICI combination therapy in advanced NSCLC.
Next, we speculated that combining the two indicators may predict the efficacy of ICI combination therapy. After combining TMB value with smoking status, we found that TMB-H/smoking patients had much better PFS than other patients in both 295 cohort and 1021 cohort, suggesting that TMB combined with smoking status might be an efficient predictor of NSCLC patients receiving ICI combination therapy. Meanwhile the PFS of TMB-H/non-smoking patients was the shortest in both cohorts, suggesting that these patients may have different resistance mechanisms of ICI combination therapy.
Interestingly, the PFS of TMB-L/non-smoking patients and TMB-H/smoking patients was quite similar, and the difference was not statistically significant (295 cohort, p = 0.5608; 1021 cohort, p = 0.0549). Previous study has found that patients with low TMB have better efficacy than those with moderate TMB after receiving ICI treatment. 28 This suggests that the role of TMB in predicting the efficacy of ICI may not be a purely linear relationship, and further research is needed to elucidate its role in ICI combination therapy.
Although our study found that TMB combined with smoking status was a potential predictor of efficacy in advanced NSCLC patients receiving ICI combination therapy, the study had the following shortcomings: (1) The sample size in this study was small, which may lead to bias; (2) About 10% of patients had driver gene mutations; and 3. Different ICI (different PD-1 antibodies or PD-L1 antibodies) and combination therapy (chemotherapy and/or anti-angiogenesis therapy) included in this study, and the potential different effects of such drugs cannot be ruled out.

| CONCLUSIONS
This study retrospectively analyzed advanced NSCLC patients receiving ICI combined with chemotherapy/ anti-angiogenesis therapy in two different NGS detection cohorts. The TMB value correlated with smoking status F I G U R E 2 TMB values correlated with the smoking index in the 295 cohort and the 1021 cohort. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NSCLC, non-small cell lung cancer; TMB, tumor mutational burden in LUAD patients, but not in LUSC patients. The results showed that TMB value combined with smoking status could be used as a potential prognostic indicator for advanced NSCLC patients receiving ICI combination therapy. This study provided a potential prognostic indicator for the personalized immunotherapy of advanced NSCLC.