1
Identification of deleterious NOTCH mutation as novel predictor to efficacious 1
immunotherapy in NSCLC 2
Running title: NOTCH mutation and efficacious immunotherapy in NSCLC 3
4
Kai Zhang1*, Xiaohua Hong
1*, Zhengbo Song
2*, Yu Xu
2*, Chengcheng Li
3, Guoqiang Wang
3, Yuzi 5
Zhang3, Xiaochen Zhao
3, Zhengyi Zhao
3, Jing Zhao
3, Mengli Huang
3, Depei Huang
3, Chuang Qi
3, 6
Chan Gao3, Shangli Cai
3, Feifei Gu
1, Yue Hu
1, Chunwei Xu
4, Wenxian Wang
5, Zhenkun Lou
6#, Yong 7
Zhang7# and Li Liu
1# 8
1Cancer Center, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science 9
and Technology, Hubei, P.R. China; 2Zhejiang Cancer Hospital, Zhejiang, P.R. China;
3The Medical 10
Department, 3D Medicines Inc., Shanghai, P.R. China; 4Department of Pathology, Fujian Cancer 11
Hospital, Fujian Medical University Cancer Hospital, Fujian, P.R. China; 5Department of 12
Chemotherapy, Chinese Academy of Sciences University Cancer Hospital (Zhejiang Cancer 13
Hospital), Zhejiang, P.R. China; 6Department of Oncology, Mayo Clinic, Rochester, Minnesota, 14
USA; 7Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, 15
Huazhong University of Science and Technology, Hubei, P.R. China. 16
17
*These authors contributed equally to this work. 18
#Corresponding author: 19
Zhenkun Lou, Ph.D., Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA; Email: 20
Yong Zhang, M.D., Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical 22
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2
College, Huazhong University of Science and Technology, Hubei, P.R. China; Email: 23
Li Liu, M.D., Cancer Center, Wuhan Union Hospital, Tongji Medical College, Huazhong University 25
of Science and Technology, Wuhan, P.R. China; Email: [email protected]. 26
27
Conflict of interest 28
The authors declare no potential conflicts of interest. 29
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Translational relevance 30
This study involving 5 cohorts (n=1557) identifies NOTCH mutation, especially deleterious 31
NOTCH mutation (del-NOTCHmut
), as novel, frequent determinant of sensitivity to immune 32
checkpoint inhibitor (ICI) in EGFR/ALKWT
NSCLC. ICI, compared to chemotherapy, conferred 33
limited benefit in the NOTCH-wild-type patients, but remarkably prolonged PFS and OS in the 34
patients harboring del-NOTCHmut
. These results indicate the potential that del-NOTCHmut
might 35
impact on the treatment choice (ICI vs. chemotherapy) in advanced EGFR/ALKWT
NSCLC. 36
More importantly, del-NOTCHmut
downregulates NOTCH signaling and is correlated with better 37
ICI efficacy, which unravels a possibility that the monoclonal antibodies or small chemicals aiming 38
NOTCH members or their ligands might enhance the response to ICI. This inference might lead 39
future research to explore the efficacy of adding NOTCH inhibitor to ICI regimen in NSCLC, for the 40
optimization of ICI treatment in clinical practice. 41
42
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Abstract 43
Purpose: NOTCH signaling is associated with tumorigenesis, mutagenesis, and immune tolerance in 44
NSCLC, indicating its association with the clinical benefit of immune checkpoint inhibitors (ICIs). 45
We hypothesized that NOTCH mutation in NSCLC might be a robust predictor of 46
immunotherapeutic efficacy. 47
Experimental Design: Multiple-dimensional data including genomic, transcriptomic, and clinical 48
data from cohorts of NSCLC internal and public cohorts involving immunotherapeutic patients were 49
analyzed. PolyPhen-2 system was performed to determine deleterious NOTCH mutation (del-50
NOTCHmut
). Further investigation on molecular mechanism was performed in TCGA data via 51
CIBERSORT and GSEA. 52
Results: Our 3DMed cohort (n=58) and other four cohorts (Rizvi, POPLAR/OAK, Van Allen, and 53
MSKCC [n=1499]) uncovered marked correlation between NOTCH1/2/3 mutation and better ICI 54
outcomes in EGFR/ALKWT
population, including ORR (2.20-fold, P=0.001), PFS (HR=0.61, 95%CI 55
0.46-0.81, P=0.001) and OS (HR=0.56, 95%CI 0.32-0.96, P=0.035). Del-NOTCHmut
exhibited better 56
predictive function than non-deleterious NOTCH mutation (non-del-NOTCHmut
), potentially via 57
greater transcription of genes related to DDR and immune activation. Del-NOTCHmut
was not linked 58
with prognosis in TCGA cohorts and chemotherapeutic response, but was independently associated 59
with immunotherapeutic benefit, delineating the predictive, but not prognostic utility of del-60
NOTCHmut
. 61
Conclusions: This work distinguishes del-NOTCHmut
as a potential predictor to favorable ICI 62
response in NSCLC, highlighting the importance of genomic profiling in immunotherapy. More 63
importantly, our results unravel a possibility of personalized combination immunotherapy as adding 64
NOTCH inhibitor to ICI regimen in NSCLC, for the optimization of ICI treatment in clinical 65
practice. 66
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67
Keyword: Non-small cell lung cancer; NOTCH; immunotherapy; predictive biomarker 68
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Introduction 69
Immune checkpoint inhibitors (ICIs) have renovated the standard treatment for patients with 70
non-small cell lung cancer (NSCLC), by virtue of the unprecedented prolongation of life (1-3). 71
Despite this, durable response of ICIs merely occurs in a tiny minority, which necessitates further 72
investigation into the biomarkers predicting the clinical benefit. 73
To date, two critical biomarkers, programmed death ligand 1 (PD-L1) expression and tumour 74
mutational burden (TMB) have been validated prospectively in random controlled trials (RCTs) 75
concerning NSCLC (4-6). Meanwhile, retrospective analyses of genomic profiles identified potential 76
biomarkers that are associated with better outcome such as DNA damage response (DDR) pathways 77
co-mutations and TP53/KRAS co-mutations (7,8). The genomic landscape that is associated with 78
better clinical outcome of ICIs has not been fully explored. 79
NOTCH pathway, a highly conserved signaling system, is regulated by short-range cell–cell 80
interaction between NOTCH receptor (NOTCH1–4) and “canonical” ligand (Jagged1, Jagged2, delta 81
like canonical NOTCH ligand 1 [DLL1], DLL3, or DLL4) (9), or non-canonically through activation 82
of other pathways such as nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), 83
WNT, transforming growth factor-β (TGF-β), and signal transducers and activators of transcription 3 84
(STAT3) (10). 85
Of great importance is the irreplaceable action of NOTCH in the development of multiple 86
organs at early stage (11), including the longitudinal regulation of lung growth from trachea/bronchi 87
differentiation during embryogenesis (proximal) to mature alveoli formation in postnatal period 88
(distal) (12). In developed lung, NOTCH modulates the homeostasis between secretory cells (Clara 89
and goblet cells) and ciliated cells, extracellular matrix production and subepithelial fibrosis, 90
myofibroblast differentiation, epithelial-mesenchymal transition (EMT), and pulmonary vascular 91
remodeling, contributing to the initiation and progression of multiple pulmonary diseases, such as 92
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asthma and chronic obstructive pulmonary disease (COPD) (11,12). Of the NOTCH-related 93
pathogenesis mentioned above, EMT, in which epithelial cells lose polarity together with cell-cell 94
adhesion and acquire properties of mesenchymal cells (13), frequently associates with stemness 95
property (as cancer stem cell) (14,15), and resistance to chemotherapy (16,17), radiotherapy (17-19), 96
and even targeted therapy in NSCLC (17,20,21). 97
As for immunotherapy, plenty of molecular research concerning tumor initiation, 98
immunogenicity, and immune microenvironment strongly support the possible association between 99
NOTCH and immunotherapeutic efficacy. Firstly, tumor initiation via suppressing TP53 requires the 100
regulation of NOTCH1 on MDM2 (22), a robust biomarker related to hyper-progression in 101
immunotherapy (23). Secondly, tumor immunogenicity regulated by DDR pathways might be 102
enhanced by NOTCH1 inhibition (22), possibly via the direct binding between NOTCH1 and ataxia-103
telengiectasia mutated (ATM) (24,25). Thirdly, in immune microenvironment, the NOTCH ligands 104
on myeloid-derived suppressor cells (MDSCs) interact with the NOTCH receptor on tumor cells and 105
thereby improve the CSC capacity (26), which in turn increases the expression of NOTCH ligands on 106
MDSCs (27), constituting a positive feedback eventually resulting in immune tolerance (28). Based 107
on these observations, we hypothesized that NOTCH mutation in NSCLC might predict the clinical 108
benefit from immunotherapy. 109
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Methods 110
Patients 111
Patients with NSCLC treated with PD-1/PD-L1 inhibitors in the Wuhan Union Hospital who 112
had genomic profiling of circulating tumor DNA (150-gene panel, Supplementary Table S1) before 113
treatment were included in our 3DMed cohort. The patient characteristic of our cohort was shown in 114
Supplementary Table S2. Another 4 independent public cohorts were also used in the present study, 115
including Rizvi, POPLAR/OAK, Van Allen, and MSKCC cohorts. 116
The data for the 4 independent cohorts were retrieved from published articles (detailed features 117
were displayed in Supplementary Table S3). (1) The Rizvi cohort contains 240 advanced NSCLC 118
patients treated with anti-PD-1/PD-L1 monotherapy or combination therapy with anti-CTLA-4, and 119
their tumor tissues were profiled with MSK-IMPACT panel (341-gene panel, 0.98 Mb, 56 pts; 410-120
gene panel, 1.06 Mb, 164 pts; 468-gene panel, 1.22 Mb, 20 pts) (29). (2) The POPLAR/OAK cohort 121
of 853 advanced NSCLC patients who had received 1 or 2 cytotoxic chemotherapy from a phase II 122
trial, POPLAR (NCT01903993) (30), and a phase III trial, OAK (NCT02008227) (31), includes two 123
different regimens, atezolizumab and docetaxel. All patients in the POPLAR/OAK trial implemented 124
a genomic profiling of ctDNA with Foundation One panel (315-gene panel, 1.1Mb) (32). (3) The Van 125
Allen cohort was defined as the NSCLC subpopulation of the pan-cancer research on micro-satellite 126
stable (MSS) patients with clinically annotated outcomes to immune checkpoint therapy (33). All 56 127
MSS NSCLC samples and matched normal tissues were profiled by whole-exome sequencing (WES) 128
(33). (4) The MSKCC cohort was identified as the NSCLC subpopulation of the pan-cancer research 129
on the relation between TMB and immunotherapeutic OS. Tumor tissues from 350 NSCLC patients 130
were profiled with MSK-IMPACT panel (341-gene panel, 0.98 Mb, 56 pts; 410-gene panel, 1.06 Mb, 131
239 pts; 468-gene panel, 1.22 Mb, 55 pts) (34). Of note, overlapped patients identified between the 132
Rizvi and MSKCC cohorts do not affect the independence of their clinical outcomes, for the reason 133
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that the Rizvi study displayed ORR and PFS data and the MSKCC study published OS data (29,34). 134
All human sample collection and usage were in accordance with the principles of the 135
Declaration of Helsinki and approved by the Institution Review Board of Huazhong University of 136
Science and Technology. The written consents were received from all the participated patients. 137
Study assessment 138
In the 3DMed cohort, the objective response rate (ORR) was defined as the percentage of 139
patients with confirmed complete response (CR) or partial response (PR) by Response Evaluation 140
Criteria in Solid Tumors, version 1.1 (RECIST v1.1). PFS was defined as the time from the start of 141
anti-PD-1/PD-L1 treatment until disease progression (assessed by an investigator using RECIST 142
version 1.1) or death from any cause. In other 4 independent cohorts, tumor response was assessed 143
by thoracic radiologists (Rizvi, Van Allen) or investigators (POPLAR/OAK) using RECIST v1.1. 144
PD-L1 expression on tumor cells was assessed by VENTANA PD-L1 (SP263) assay in the 145
3DMed cohort, and the PD-L1 status were characterized as negative or positive. In the OAK trial, 146
PD-L1 expression on tumor cells or immune cells were evaluated simultaneously by VENTANA PD-147
L1 (SP142) assay. Detailed definition of PD-L1 status in tumor cells (TC1/2/3) and immune cells 148
(IC1/2/3) was described in the original article (31). 149
The testing of circulating tumor DNA (ctDNA) in the 3DMed cohort followed the method that 150
had been previously published (35). 151
PolyPhen-2 system evaluating the mutational impact on protein structure 152
PolyPhen-2 (Polymorphism Phenotyping v2) is a software tool from Harvard University which 153
predicts possible impact of amino acid substitutions on the structure and function of human proteins 154
using straightforward physical and evolutionary comparative considerations (36). PolyPhen-2 155
predictions were calculated for all resulting amino acid residue substitutions in human UniProtKB 156
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proteins with the maximum CDS sequence overlap and identity. PolyPhen-2 uses eight sequence-157
based and three structure-based predictive features which were selected automatically by an iterative 158
greedy algorithm. 159
PolyPhen-2 calculates the naive Bayes posterior probability that a given mutation is damaging 160
and reports estimates of false positive (the chance that the mutation is classified as damaging when it 161
is in fact nondamaging) and true positive (the chance that the mutation is classified as damaging 162
when it is indeed damaging) rates. Based on the final score assessing the harm of missense mutation, 163
we set the cut-off value as 0.800 to categorized NOTCH missense mutation as higher impact group 164
or lower impact group, and thereafter explore to better predictive efficacy of deleterious NOTCH 165
mutation, compared to non-deleterious NOTCH mutation. 166
Gene set enrichment analysis (GSEA) 167
For GSEA (37), the javaGSEA Desktop Application (GSEA 4.0.1) was downloaded from 168
http://software.broadinstitute.org/gsea/index.jsp. GSEA was used to associate the gene signature with 169
deleterious and non-deleterious NOTCH mutation. The signatures tested in the present study was 170
shown in Supplementary Table S4. The genes identified to be on the leading edge of the enrichment 171
profile were subject to pathway analysis. Fold-change values were exported for all genes and 172
analyzed with version 4.0.1 of GSEA, using the GSEA pre-ranked module. The normalized 173
enrichment score (NES) is the primary statistic for examining gene set enrichment results. The 174
nominal P value estimates the statistical significance of the enrichment score. A gene set with 175
nominal P<0.05 was determined to be significantly enriched in genes. 176
The leading edge analysis allows for the GSEA to determine which subsets (referred to as the 177
leading edge subset) of genes contributed the most to the enrichment signal of a given gene set's 178
leading edge or core enrichment. In the present study, leading edge analyses were performed in 179
GSEA 4.0.1 to discern whether a small number of DDR members contribute to multiple significance 180
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of enrichment of DDR signature in the del-NOTCHmut
group. 181
Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) 182
CIBERSORT, an online method (https://cibersort.stanford.edu/index.php) for characterizing cell 183
composition of complex tissues from their gene expression profiles (38), was applied to enumeration 184
of hematopoietic subsets in mRNA mixtures from TCGA database. CIBERSORT outperformed other 185
methods with respect to noise, unknown mixture content and closely related cell types (38). 186
mRNA expression profiling analysis 187
The association between deleterious NOTCH mutation and relevant immune-related genes were 188
analyzed in TCGA database, where both DNA-seq and RNA-seq data are available. The list of DNA 189
damage response-related genes was determined by the leading edge analysis of GSEA in DDR 190
pathways (Supplemental Table S5). The immune gene list was mainly based on a published article 191
that summarized the genes related to activated T cells, immune cytolytic activity, and IFNγ release 192
(8). Other immune genes were added according to two relevant clinical trials (39,40). A list of 47 193
immune genes is provided in Supplementary Table S5. Statistical significance was determined by 194
the DESeq2 method in RStudio 3.6.1 and the normal p value was given in the figure. 195
Statistical analysis 196
The significance with categorical variables (e.g., ORR, PD-L1 status) were evaluated by Fisher 197
exact test. Kaplan-Meier method was performed to delineate the curve of PFS and OS, and Log-rank 198
method was used to assess their significance. Cox regression was implemented to calculate the 199
hazard ratio (HR) on PFS and OS, in both univariable and multivariable analyses and interaction 200
tests exploring the interaction effect between NOTCH mutation and treatment choice (atezolizumab 201
vs. docetaxel). The variables with p value below 0.10 in the univariable analyses were included in the 202
following multivariable analyses. The method of random-effect inverse-variance-weighted were used 203
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to pool outcomes, which is calculated by HR and its 95% confidence interval (CI) to estimate the 204
size of influence on the clinical benefits including ORR, PFS and OS. Heterogeneity assessment 205
between different studies was applied using the I2 statistics. A result of P > 0.1 and I
2 < 50% indicates 206
that no significant between-study heterogeneity was present. The significance with continuous 207
variables (e.g., tumour mutational burden/count and fraction of copy number alteration) were 208
assessed by one-way ANOVA or two-way ANOVA, with Tukey post-test, with the requirement of 209
homoscedasticity between different groups. If the data failed to meet the criteria for parametric test, 210
non-parametric analyses would be implemented, i.e., chi-square test, and rank sum tests. All 211
statistical analyses mentioned above were performed using IBM SPSS Statistics 22 or Stata/SE 15.1, 212
and the graphs in the present study were drawn by GraphPad Prism 8. We set the nominal level of 213
significance as 10% for heterogeneity test and 5% for the rest statistical analysis, and all 95% CIs 214
were 2-sided. 215
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Results 216
Association between NOTCH mutation and better clinical benefit to ICIs in the 3DMed cohort. 217
In the present study, 58 NSCLC patients with ctDNA sequencing before anti-PD-1/PD-L1 218
treatment were included to investigate the association between ICI efficacy and genomic alterations. 219
The baseline characteristics are described in Supplementary Table S2. In brief, this cohort was 220
representative of the general population of advanced NSCLC patients with median age of 59 (range, 221
36-72), major proportion of male (74.1%), and high percentage of ever-smokers (56.9%). In this 222
cohort, 86.2% of the patients received anti-PD-1 and the rest underwent anti-PD-L1 treatment. The 223
lines of anti-PD-1/PD-L1 immunotherapy varied from first to seventh (first-line, 20.7%; second-line, 224
39.7%; third-line or later, 39.7%), and the overall response rate reached 20.7% in total. The median 225
PFS and OS were comparable to previously published trials, as 3.1 months and 16.0 months 226
respectively. 227
The genomic mutational landscape of 58 NSCLC patients categorized according to response in 228
the 3DMed cohort is displayed in Fig. 1A. Consistent with previous studies, higher mutational rate of 229
TP53 and KRAS were shown in responders, relative to non-responders (8). Besides these, NOTCH 230
mutation discovered to be enriched in responders as well (Fig. 1B). 231
Due to the limited efficacy of ICIs in NSCLC patients with EGFR or ALK driver mutation, we 232
excluded these individuals in the following exploration. The mutation of NOTCH1/2/3 was 233
significantly associated with higher ORR (60.0% vs. 11.9%, P=0.003), longer PFS (HR 0.30, 94%CI 234
0.12-0.78, log-rank P=0.009, Fig. 1C) and OS (HR 0.21, 95%CI 0.05-0.91, log-rank P=0.020, Fig. 235
1D) in EGFR/ALKWT
NSCLC patients. These results suggest that NOTCH mutation might be 236
associated with the clinical benefit of immunotherapy. 237
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Association between NOTCH1/2/3, but not NOTCH4 mutation and better benefit to ICIs in 238
NSCLC patients from independent cohorts 239
To further evaluate the predictive value of NOTCH family, another 4 public cohorts of ICIs 240
with adequate information of the genomic alterations in tumor tissue or ctDNA and survival were 241
analyzed, including the cohorts from Rizvi, POPLAR/OAK, Van Allen, and MSKCC (characteristics 242
displayed in Supplementary Table S3). 243
NOTCH family consists of 4 members, with potentially distinct mechanisms underlying the 244
development of NSCLC. Among the samples from the OAK/POPLAR and Rizvi/MSKCC cohorts, 245
the mutational rates of NOTCH were 6.11% (NOTCH1), 5.19% (NOTCH2), 4.12% (NOTCH3) and 246
6.72% (NOTCH4), which exhibited similar distribution in lung squamous cell carcinoma and lung 247
adenocarcinoma (Supplementary Fig. S1). Univariable and multivariable analyses of the impact 248
from non-synonymous mutation in each NOTCH gene on PFS and OS benefit from ICI were 249
performed in the POPLAR/OAK, Rizvi and MSKCC cohorts. In each cohort, the multivariable HR 250
value of NOTCH4 mutation exceeded 1, and on the contrary, the HR values of NOTCH1, NOTCH2, 251
and NOTCH3 mutations were inferior to 1 (Supplementary Fig. S2), which indicates the 252
contradictory predictive value of NOTCH4 mutation to NOTCH1/2/3 mutation. Thus, we further 253
focused on the potential of predictive function of NOTCH1/2/3 mutation in these cohorts. 254
Among the EGFR/ALKWT
population, the beneficial trend of NOTCH1/2/3 mutation in 255
immunotherapeutic ORR (Fig. 2A-C), PFS (Fig. 2A-C), and OS (Fig. 2E-G) were observed in all 256
cohorts. Pooled estimates demonstrated that compared to the NOTCHWT
group, the NOTCH1/2/3mut
257
group exhibited better ORR (RR 2.2, 95% CI 1.39-3.51, P=0.001, Fig. 2D), longer PFS (HR 0.61, 258
95% CI 0.46-0.81, P=0.001, Fig. 2D) and OS (HR 0.56, 95% CI 0.32-0.96, P=0.035, Fig. 2H). 259
Statistical analyses for heterogeneity were insignificant in all pooled estimates (P>0.10), indicating 260
the consistency of the association between NOTCH1/2/3 mutation and favorable benefit to ICIs 261
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across these cohorts. 262
Enrichment of deleterious NOTCH mutation in EGFR/ALKWT
NSCLC with higher TMB, 263
irrespective of PD-L1 status 264
As illustrated in Fig. 3A, missense mutations were predominant among all kinds of NOTCH 265
mutations in the POPLAR/OAK and MSKCC cohorts. Unlike truncating mutations that strikingly 266
impact upon tumour cells by the loss of gene expression, missense mutations might be deleterious or 267
benign, on account of their effects on protein structure. To rule out the benign mutations that 268
generally do not affect the protein function, PolyPhen-2 analysis was implemented to distinguish 269
between the missense mutations of NOTCH with higher or lower probability of impact on protein 270
structure (abbreviated as NOTCHmis-high
and NOTCHmis-low
, respectively). Since both truncating and 271
mis-high mutations explicitly affect the biological function of the involved gene, we hereby 272
combined these two kinds of alterations and defined them as deleterious NOTCH mutations (del-273
NOTCHmut
). Relatively, mis-low mutations of NOTCH1/2/3 and all NOTCH4 mutations were 274
identified as non-deleterious NOTCH mutations (non-del-NOTCHmut
) and the patients without any 275
NOTCH mutation were categorized as the control group (NOTCHWT
). The work flow is illustrated in 276
Fig. 3B. 277
To investigate the possible mechanism underlying the predictive role of NOTCH mutation, we 278
firstly aimed to ascertain whether co-occurrence takes place between del-NOTCHmut
with robust 279
predictors in EGFR/ALKWT
NSCLC, including PD-L1 expression and higher TMB. We identified a 280
cohort from the OAK trial where the data of both ctDNA and PD-L1 testing is available (n=637). In 281
this cohort, participants were divided into 9 subgroups by the two variables, bTMB (bTMB-L: 282
bTMB<8; bTMB-I: 8≤bTMB<16; bTMB-H: bTMB≥16) and PD-L1 expression (negative: TC0 and 283
IC0; intermediate: TC1/2 and/or IC1/2; strong expression: TC3 or IC3). As illustrated in Fig. 3C, the 284
digits in these nine squares representing nine subgroups are the incidence rates of del-NOTCHmut
, 285
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which was enriched in bTMB-H subgroups, irrespective of PD-L1 expression. Furthermore, the 286
distribution of PD-L1 status (SP142 antibody) was parallel among three groups (Fig. 3D), but the 287
level of bTMB was significantly higher in the del-NOTCHmut
and non-del-NOTCHmut
groups, 288
compared to NOTCHWT
individuals (Fig. 3E). In addition, a similar trend of TMB was observed in 289
the EGFR/ALKWT
NSCLC patients of TCGA database. 290
Impact of deleterious NOTCH mutation on DNA damage response 291
Despite the similar levels of mutational burden were discovered in the del-NOTCHmut
and non-292
del-NOTCHmut
groups, the underlying mechanisms to repair the miscoding DNA, i.e., DNA damage 293
response (DDR) pathways, might be dissimilar between these two groups. GSEA revealed prominent 294
enrichment of signatures related to DNA repair in the del-NOTCHmut
group, compared to the non-del-295
NOTCHmut
(P<0.001, Fig. 3G) and NOTCHWT
(P<0.001, Fig. 3G) groups. In detail, DDR could be 296
defined as 8 different pathways according to their diverse functions, including homologous 297
recombination repair (HRR), mismatch repair (MMR), base excision repair (BER), nucleotide 298
excision repair (NER), Fanconi anemia pathway (FA), translesion DNA synthesis (TLS), non-299
homologous end-joining (NHEJ), and checkpoint factors (CPF). Here we further explored that the 300
signatures of all pathways except NHEJ displayed enrichment in the del-NOTCHmut
group, relative to 301
the NOTCHWT
(Fig. 3H) and non-del-NOTCHmut
(Fig. 3I) groups, while no difference was found 302
between the non-del-NOTCHmut
group and the NOTCHWT
group (Fig. 3J). There are members 303
shared among different DDR pathways, and to exclude the possibility that identical genes contribute 304
to multiple significances in several DDR pathways, leading edge analyses were performed and 305
merely limited DDR genes were found to impact various enrichments (Supplementary Fig. S3). In 306
addition, the expression of all genes in the leading edge analysis (113 genes in total) was further 307
analyzed in comparison between the del-NOTCHmut
group and the NOTCHWT
group. The heatmap 308
and box plots of the most significant 30 DDR genes were displayed in Supplementary Fig. S4. 309
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Taken together, these results demonstrate the potentially intensified activation of DDR pathways 310
in the EGFR/ALKWT
NSCLC with deleterious NOTCH mutation, in comparison with the one with 311
non-deleterious NOTCH mutation, despite the comparable level of TMB in these two clusters. Tumor 312
mutational burden is the consequence of the confront between mutagenesis and DNA repair. The 313
comparable TMB but higher activation of DDR system in the del-NOTCHmut
NSCLC might suggest 314
the possibility of more drastic mutagenesis in the NSCLC harboring deleterious NOTCH mutation. 315
Impact of deleterious NOTCH mutation on immune infiltration and response 316
Using CIBERSORT, we estimated the degree of infiltrated immune cells, discovering an 317
increase of M1 macrophage in the EGFR/ALKWT
NSCLC with deleterious NOTCH mutation, 318
relative to those without NOTCH mutation (Supplemental Fig. S5). Despite no distinctions that 319
were uncovered in other subsets of immune cells, the immune reaction to tumoral neoantigens might 320
be higher in patients with deleterious NOTCH mutation, which was explored by GSEA in the 321
following section. 322
Displayed in Fig. 4A, multiple significant enrichments of immune activation were revealed in 323
the del-NOTCHmut
group, compared to the NOTCHWT
group, including antigen processing and 324
presentation, BCR/TCR downstream signaling, activation of CD4/CD8 T cell and NKT cell, 325
inhibition of regulatory T cell (Treg), programmed cell death, and metabolism of steroid hormones. 326
In contrast, the non-del-NOTCHmut
group has much less enrichment compared to the NOTCHWT
327
group. Detailed curves of GSEA were shown in Supplemental Fig. S6-9. 328
In addition, the interleukin pathways were also taken into consideration. GSEA of interleukin 329
signatures unmasked the activations of IL-1 and IL-12 pathways in the del-NOTCHmut
group, and the 330
activations of IL-6 family, IL-10, and IL-12 family in the non-del-NOTCHmut
group, relative to the 331
NOTCHWT
group. Of great importance, the IL-10 signaling enriched in the non-del-NOTCHmut
332
NSCLC associated with an anti-inflammatory and immunosuppressive microenvironment, in 333
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accordance with the previous result of a Treg activation in the non-del-NOTCHmut
NSCLC. 334
To sum up, deleterious NOTCH mutation was positively associated with infiltration of M1 335
macrophage, antigen processing via degradation in proteasome, cross presentation of antigen, 336
BCR/TCR downstream signaling, activation of CD4 T cell/CD8 T cell/NKT cell, deactivation of 337
Treg, programmed cell death of tumor cell, and metabolism of steroid hormones. These results 338
delineate the hyper-active immune microenvironment and the robust immune reaction in the 339
EGFR/ALKWT
NSCLC with deleterious NOTCH mutation, relative to the ones with non-deleterious 340
NOTCH mutation or without any NOTCH mutation, which might be linked with the larger benefit 341
from immunotherapy in the del-NOTCHmut
patients with EGFR/ALKWT
NSCLC. 342
Deleterious NOTCH1/2/3 mutation is predictive, not prognostic biomarker of ICI benefit 343
As shown above, del-NOTCHmut
, compared to non-del-NOTCHmut
, exhibited greater association 344
with potentially higher transcription of DDR genes and activated immune microenvironment, which 345
is plausibly linked with better efficacy of immunotherapy. We next sought to firstly validate this 346
hypothesis in the POPLAR/OAK cohort, where the PFS/OS data of both ICI (atezolizumab) and 347
chemotherapeutic agent (docetaxel) are available and of high credibility due to the RCT setting. 348
Previously in Supplemental Figure S2, we ruled out the probability of better ICI outcome 349
associated with NOTCH4 mutation. Here we further distinguished NOTCH4 mutation by Polyphen-2 350
to explore whether deleterious NOTCH4 mutation could be beneficial. The patients harboring 351
deleterious NOTCH1, NOTCH2 or NOTCH3 mutations exhibited a trend of better ORR and PFS 352
than the patients with wildtype NOTCH genes (Supplemental Figure S10A-C). However, as 353
illustrated in Supplemental Figure S10D, the lines representing deleterious NOTCH4 mutation and 354
wildtype NOTCH are mingled, and none of the patients with NOTCH4 mutation acquired objective 355
response, regardless of the deleterious status of the mutation. Taken together, this further analysis 356
supports the results in Supplemental Fig. S2 that unlike the mutations in NOTCH1/2/3, NOTCH4 357
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mutation might not be associated with immunotherapeutic outcomes in EGFR/ALKWT
NSCLC. 358
To directly evaluate the utility of deleterious NOTCH mutation in clinical decision on 359
immunotherapy or chemotherapy in advanced EGFR/ALKWT
NSCLC, the PFS and OS benefits from 360
atezolizumab relative to docetaxel in the del-NOTCHmut
, non-del-NOTCHmut
, and NOTCHWT
groups 361
were separately calculated and compared. As shown in Fig. 5A, in ITT population, limited ORR and 362
PFS benefits were observed (ORR: 15.6% vs. 12.3%, P=0.204; PFS: HR 0.84, 95%CI 0.72-0.98, 363
P=0.025), and this weak improvement became even milder and insignificant in the NOTCHWT
364
subpopulation (ORR: 14.5% vs. 13.3%, P=0.726; PFS: HR 0.91, 95%CI 0.77-1.08, P=0.279). In 365
contrast, moderate benefit was observed in the non-del-NOTCHmut
group (ORR: 10.7% vs. 10.3%, 366
P>0.999; PFS: HR 0.65, 95% CI 0.37-1.13, P=0.126), and remarkably, considerable benefit was 367
achieved in the del-NOTCHmut
group (ORR: 29.4% vs. 9.3%, P=0.008; HR 0.45, 95% CI 0.27-0.77, 368
P=0.004). As a result, the interaction effect on PFS between NOTCH mutation (del-NOTCHmut
vs. 369
non-del-NOTCHmut
vs. WT) and treatment choice (atezolizumab vs. docetaxel) was significant (HR 370
0.73, 95% CI 0.57-0.93, Pinteraction=0.012), recognizing del-NOTCHmut
mutation as a predictive 371
biomarker of PFS benefit from immunotherapy over chemotherapy. 372
Identical analyses were performed on OS benefit (Fig. 5B). Compared to docetaxel, 373
atezolizumab monotherapy decreased the hazard of death by 33% in the NOTCHWT
group (HR 0.67, 374
95% CI 0.55-0.80, P<0.001), 49% in the non-del-NOTCHmut
group (HR 0.51, 95% CI 0.27-0.96, 375
P=0.038), and by higher proportion as 52% in the del-NOTCHmut
group (HR 0.48, 95% CI 0.28-0.85, 376
P=0.011). 377
Furthermore, multivariable analyses were performed to explore whether deleterious NOTCH 378
mutation is independently associated with immunotherapeutic efficacy. In the POPLAR/OAK cohort 379
where mutations were detected in ctDNA, del-NOTCHmut
independently associated with better 380
immunotherapeutic PFS (HR 0.57, 95% CI 0.38-0.86, P=0.006, Table 1) and OS (HR=0.63, 95% CI 381
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0.40-0.99, P=0.045, Table 1), but not chemotherapeutic benefit (PFS: HR 1.04, 95% CI 0.73-1.49, 382
P=0.840; OS: HR=0.86, 95% CI 0.58-1.29, P=0.462, Supplemental Table S6). These results 383
demonstrate that deleterious NOTCH mutation is a predictive, not prognostic biomarker in the 384
POPLAR/OAK cohort. 385
In other two immunotherapeutic cohorts (Rizvi and MSKCC) where mutations were detected in 386
tissue sample, TMB was significantly associated with immunotherapeutic outcomes in the 387
univariable analyses and therefore was involved in the further multivariable analyses. The 388
association between del-NOTCHmut
and immunotherapeutic benefits remained significant after the 389
adjustment for TMB (Rizvi-PFS: HR 0.56, 95%CI 0.32-0.99, P=0.047, Supplemental Table S7; 390
MSKCC-OS: HR 0.54, 95%CI 0.29-1.00, P=0.049, Supplemental Table S8), suggesting that the 391
predictive utility of del-NOTCHmut
is independent of TMB in EGFR/ALKWT
NSCLC. Taking TCGA 392
cohort as a comparison, which includes the NSCLC patients with predominantly early-stage and 393
surgically-resected tumors without receiving immunotherapy, we discovered no significant 394
association between deleterious NOTCH mutation and both the DFS and OS in EGFR/ALKWT
395
NSCLC (Supplemental Fig. S11). 396
Taken together, deleterious NOTCH mutation detected by either ctDNA or tumour tissue was 397
independently associated with significant improvement of immunotherapy and was not linked with 398
prognosis, delineating the predictive, but not prognostic value of del-NOTCHmut
in 399
immunotherapeutic treatment against NSCLC. 400
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Discussion 401
In this study, NOTCH mutation, especially del-NOTCHmut
, was identified as tumor cell-intrinsic 402
determinant of better response to ICI treatment in five cohorts, involving 1557 advanced NSCLC 403
patients in total. Of great attention are their noticeable correlations with better clinical outcome of 404
ICI, instead of chemotherapeutic agents, elucidating the predictive, but not prognostic role in 405
immunotherapy. Of all kinds of NOTCH mutations, deleterious, relative to non-deleterious alteration, 406
might possess more predictive power. Furthermore, we distinguished greater transcription of genes 407
related to DDR and immune activation as potential mechanisms underlying the predictive value of 408
del-NOTCHmut
in NSCLC population (diagram shown in Supplementary Fig. S12). 409
This study represents the one of the first reports to examine the association between ICI 410
response and NOTCH family. As reported by a previous study mainly involving melanoma and 411
NSCLC, NOTCH1 mutation seldom occurred in patients who hyper-progressed while 412
immunotherapy (23). Based on the similarity among different NOTCH members, we took all 4 413
members of NOTCH family into consideration and discovered that the mutation in NOTCH1/2/3, 414
instead of NOTCH4, was associated with higher ORR and longer PFS/OS with ICI treatment in 415
EGFR/ALKWT
NSCLC. 416
Of the NOTCH mutations in these cohorts, frameshift and nonsense mutations are overtly loss-417
of-function, while missense mutations might be damageable or merely benign as nonpathogenic 418
passenger events. Earlier NSCLC studies in NOTCH1 implemented PolyPhen-2 to distinguish 419
detrimental mutations, and confirmed their down-regulating function on transcriptional activity of 420
NOTCH1 by both reporter gene assay and electrophoretic mobility shift assay (41), suggesting the 421
missense mutations of NOTCH might mainly be inhibitory in NSCLC, similar to truncating 422
mutations. In addition, in light of the data in COSMIC database, the pattern of mutational loci in 423
NSCLC is sporadic, unlike the enriched distribution in hematopoietic and lymphoid where NOTCH 424
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22
mutations are recognized to be oncogenic and gain-of-function, which further suggests that the 425
NOTCH mutation in NSCLC may be dominated by inhibitory function. Inhibition of NOTCH1 was 426
discovered to stabilize TP53 via downregulating the phosphorylation and protein level of MDM2 427
(42), a prominent biomarker linked with ICI-induced hyper-progression across multiple tumor types 428
(23). These results indicate the possibility that deactivation of MDM2 might account for the 429
predictive function of inhibitory NOTCH mutation in immunotherapy. 430
Further analyses in the POPLAR/OAK cohort comparing atezolizumab and docetaxel revealed 431
that relative to the limited benefit in the NOTCHWT
group, moderate ICI benefit was shown in the 432
non-del-NOTCHmut
group, and remarkable immunotherapeutic outcome was observed in the del-433
NOTCHmut
individuals (detailed comparisons shown in Supplementary Fig. S12). Many missense 434
mutations may have little or no effect on protein function; this is likely the basis for the weaker 435
correlation between clinical outcomes and identified non-del-NOTCHmut
. 436
Consistent with clinical benefit, similar PD-L1 staining but higher TMB was uncovered in both 437
del-NOTCHmut
and non-del-NOTCHmut
groups. The PD-L1 antibody used in the OAK trial is SP142, 438
which was indicated to be poorly consistent to other antibodies including FDA-approved 439
standardized assays, 22C3 and SP263, especially in the high-staining samples (43,44), which might 440
reduce the credibility of the PD-L1 analysis in the present study. As for tumor mutational burden, it 441
is the consequence of the confront between mutagenesis and DNA repair. In the present study, 442
similar level of TMB was revealed in NSCLC with deleterious or non-deleterious NOTCH mutation, 443
while the DNA damage response is much stronger in the NSCLC with del-NOTCHmut
, relative to 444
non-del-NOTCHmut
, suggesting a possibility of fiercer mutagenesis in NSCLC with deleterious 445
NOTCH mutation. Multivariable analyses in the Rizvi and the MSKCC cohorts, where tissue TMB 446
was significantly associated with immunotherapeutic outcome, indicating the predictive utility of 447
del-NOTCHmut
is independent to the level of TMB. 448
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After the translation of mutated protein, immune procedures including processing and 449
presentation of neoantigen, BCR and TCR downstream signaling, activation of CD4 T cell, CD8 T 450
cell, and NKT cell, inhibition of Treg, contributing to the superior degree of programmed cell death 451
and the success of immunity-induced tumor rejection. Here in the present study, we observed the 452
association between del-NOTCHmut
and these procedures, which might be part of the mechanism of 453
del-NOTCHmut
in predicting better immunotherapeutic outcome. 454
As for limitations, the retrospective setting and pooled-estimate methodology of this study 455
might introduce multiple biases. The limitation from retrospective setting could be greatly minimized 456
by the large sample size (5 cohorts involving 1557 patients), by which the experimental features 457
might be balanced, such as race, ICI regimen, treatment line, and the platform/panel/used sample of 458
NGS testing, etc. However, the pooled-estimate methodology does probably weaken the credibility 459
of the conclusion to some extent, where the included studies with larger sample size tend to possess 460
more weight in the final pooled estimate. In the present study, the predictive utility of NOTCH 461
mutation was mainly driven by small datasets, which introduce minor-to-moderate heterogeneity to 462
the pooled estimates. 463
In our 3DMed cohort, merely NOTCH1-3, instead of NOTCH4, were involved in the gene 464
panel, and the comparison among of 4 NOTCH genes were comprehensively analyzed in the public 465
cohorts. Fortunately, the further analyses indicate that NOTCH4 mutation was not associated with 466
better immunotherapeutic outcome, making it logical to put all the cohorts together for a meta-cohort 467
analysis. In addition, our attempts to recruit functional NOTCH mutations was handicapped by the 468
limited information available regarding the functions of different mutations and the lack of hotspots 469
in NOTCH gene mutations, as illustrated in TCGA and COSMIC databases. To alleviate this 470
limitation, we used PolyPhen-2 system which provides powerful evaluation of the mutational 471
functions on NOTCH protein, assisting us to distinguish the del-NOTCHmut
out of all NOTCH 472
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24
missense mutations. However, this system fails to decipher the precise function of missense mutation 473
as activation or deactivation. Despite the similar trend of increased ICI benefit in patients with 474
missense or nonsense mutations, we cannot simply assume that missense mutations at different loci 475
are all inactivating, due to the lack of direct functional data in the present study. Activating and 476
inactivating mutations might lead to distinct influences on immunotherapeutic efficacy, which might 477
be addressed by further molecular studies in cell line and xenograft model. 478
Despite the identification of deleterious NOTCH mutation, the predictive efficacy in cohort 479
(POPLAR/OAK) using the similar detection methods with our cohort is not ideal, which might 480
decrease the robustness of this biomarker. This poorer result might be explained from two angles. 481
Firstly, the confounding variables significantly associated with the PFS and OS in the atezolizumab 482
arm (including sex, race, histology, ECOG, number of metastatic sites, mutations of STK11, KEAP1, 483
and TP53) might influence the predictive efficacy of NOTCH mutation in univariable analysis. After 484
adjusting these factors, the association between del-NOTCHmut
and OS became significant. Secondly, 485
unlike routine administration of ICI in our cohort, the POPLAR/OAK trial allowed the continuation 486
of atezolizumab despite of radiological progression, if the investigator deemed the patient to be 487
receiving clinical benefit which might cover part of the predictive utility of NOTCH mutation in the 488
OS benefit. Taken together, the poorer result in the POPLAR/OAK cohort might be partially 489
attributed to its special procedure and the confounding factors. The significant multivariable p values 490
among multiple cohorts demonstrate the robustness of del-NOTCHmut
in predicting favorable ICI 491
benefit. 492
In summary, our data identified NOTCH mutation, especially del-NOTCHmut
, as a novel, 493
frequent determinant of sensitivity to immune checkpoint blockade in EGFR/ALKWT
NSCLC. More 494
importantly, our results unravel a possibility of personalized combination immunotherapy as adding 495
NOTCH inhibitor to ICI regimen in NSCLC, for the optimization of ICI treatment in clinical 496
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practice. 497
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26
Author contributions 498
Conception and design: Zhengbo Song, Yu Xu, Guoqiang Wang, Zhenkun Lou, Yong Zhang and Li 499
Liu 500
Development of methodology: Yu Xu and Guoqiang Wang 501
Acquisition of data: Kai Zhang, Xiaohua Hong, Yu Xu, Yuzi Zhang, Xiaochen Zhao, Zhengyi Zhao, 502
Jing Zhao, Mengli Huang, Depei Huang, Chuang Qi, Chan Gao, Shangli Cai, Feifei Gu, Yue Hu and 503
Chunwei Xu 504
Analysis and interpretation of data: Kai Zhang, Yu Xu, Chengcheng Li, Guoqiang Wang and 505
Wenxian Wang 506
Writing, review, and/or revision of the manuscript: Kai Zhang, Yu Xu, Chengcheng Li, Guoqiang 507
Wang, Yuzi Zhang, Xiaochen Zhao, Zhengyi Zhao, Jing Zhao, Mengli Huang, Depei Huang, Chuang 508
Qi, Chan Gao, Shangli Cai, Yue Hu, Chunwei Xu and Li Liu 509
Administrative, technical, or material support: Zhengbo Song, Shangli Cai and Li Liu 510
Study supervision: Wenxian Wang and Li Liu 511
Final approval of manuscript: All authors 512
513
Acknowledgments 514
This work was supported by the National Key Research and Development Program of China 515
(2016YFC13038) and National Natural Science Foundation of China (81773056). 516
517
Competing interests 518
The authors declare no competing interests. 519
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659
660
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Figure legend 661
Fig 1. NOTCH1/2/3 mutations are associated with better response to ICIs in NSCLC. A. 662
Stacked plots show mutational burden (histogram, top), mutations in TP53, LRP1B, KRAS, AR, 663
RBM10, CDKN2A, EGFR, FAT1, IRS2, NOTCH2, NOTCH1, NOTCH3, BRCA1, FAM135B, RB1 664
(tile plot, middle), their mutational rates in patients having achieved objective response or 665
progressive disease (histogram, right), and mutational marks (bottom). B. Scatter diagram displays 666
the mutational rate in patients having achieved objective response or progressive disease. NOTCH 667
members are highlighted in orange. C. Best response of the patients with available radiographic 668
assessment. NOTCH1/2/3 mutations are emphasized in orange, pink and purple, respectively. 669
Individuals with mutations in 2 NOTCH members are marked with the intermingled color. D-E. ORR 670
(D) and Kaplan-Meier curves of PFS (D) and OS (E) in the EGFR/ALKWT
patients with or without 671
NOTCH mutations. Ticks represent the censored data. 672
Fig. 2. NOTCH1/2/3 mutations are associated with higher ORR, longer PFS and OS with ICI in 673
EGFR/ALKWT
NSCLC. A-C. ORR and Kaplan-Meier curves of PFS in the EGFR/ALKWT
patients 674
with or without NOTCH mutations of the Van Allen (A), POPLAR/OAK (B), and Rizvi cohorts (C). 675
D. Pooled estimates of ORR (left panel) and PFS (right panel). E-G. Kaplan-Meier curves of OS in 676
the EGFR/ALKWT
patients with or without NOTCH mutations of the Van Allen (E), POPLAR/OAK 677
(F), and MSKCC cohorts (G). H. Pooled estimate of OS. In the Kaplan-Meier curves, ticks represent 678
the censored data. In the images of pooled estimates, the squares in light orange represent study-679
specific HRs, and the squares in orange and dashed vertical lines indicate the pooled HRs. Horizontal 680
lines indicate the 95% CIs. The P values for heterogeneity and the values of I2 are from the meta-681
analyses of study-specific HRs. 682
Fig. 3. Deleterious NOTCH mutation on tumour mutational burden and DNA damage response 683
in EGFR/ALKWT
NSCLC. A. Proportion of NOTCH mutations in the POPLAR/OAK and MSKCC 684
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34
cohorts classified by different NOTCH members and mutational forms. B. Flow diagram of the 685
identification of deleterious and non-deleterious NOTCH mutations by mutational forms and 686
PolyPhen-2 system. C. Percentages of patients with deleterious NOTCH mutations in subgroups 687
classified by PD-L1 expression (negative, TC0 and IC0; intermediate, TC1/2 and/or IC1/2; high, 688
TC3 or IC3) and bTMB (bTMB-H, ≥16; bTMB-I, ≥8 and <16; bTMB-L, <8). D. PD-L1 expression 689
in EGFR/ALKWT
patients classified by NOTCH mutations (deleterious NOTCH mutation, non-690
deleterious NOTCH mutation, and no NOTCH mutation). E. bTMB in EGFR/ALKWT
patients from 691
POPLAR and OAK trials classified by NOTCH mutations (deleterious NOTCH mutation, non-692
deleterious NOTCH mutation, and no NOTCH mutation). F. TMB in EGFR/ALKWT
patients from 693
TCGA database classified by NOTCH mutations (deleterious NOTCH mutation, non-deleterious 694
NOTCH mutation, and no NOTCH mutation). G. GSEA of DNA repair-related gene signature, in 695
comparisons between NSCLC samples with deleterious NOTCH mutation, non-deleterious NOTCH 696
mutation, and no NOTCH mutation. H-J. Comparisons of signatures related to multiple pathways of 697
DNA damage response between del-NOTCHmut
and NOTCHWT
(H), del-NOTCHmut
and non-del-698
NOTCHmut
(I), and non-del-NOTCHmut
and NOTCHWT
(J). ***P<0.001. 699
Fig. 4. Deleterious NOTCH mutation on expression of immune genes in EGFR/ALKWT
NSCLC. 700
A. GSEA of gene signatures related to immune activation (upper panel) and interleukin pathways 701
(lower panel) in comparisons between del-NOTCHmut
, non-del-NOTCHmut
, and NOTCHWT
groups of 702
EGFR/ALKWT
NSCLC samples. The yellow-blue scale represents normalized enrichment score. The 703
red scale represents p value. B. Heatmap (left panel) and box plot (right panel) of the expression of 704
immune-related genes in comparison of del-NOTCHmut
and NOTCHWT
groups of EGFR/ALKWT
705
NSCLC samples. For the tags representing groups, blue represents the del-NOTCHmut
group and 706
yellow represents the NOTCHWT
group. For the colour indicating mRNA level, red represents higher 707
expression and blue represents lower expression. 708
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Fig. 5. Deleterious NOTCH mutation as predictive biomarker of ICI treatment in 709
EGFR/ALKWT
NSCLC. A-B. ORR (A) and Kaplan-Meier curves of PFS (A) and OS (B) in the 710
EGFR/ALKWT
patients classified by NOTCH mutations (deleterious NOTCH mutation, orange; non-711
deleterious NOTCH mutation, light blue; no NOTCH mutation, grey) and treatment choice 712
(atezolizumab, solid line; docetaxel, dashed line). ICI benefit comparing atezolizumab and docetaxel 713
is shown in the upper right corner. Circles reflect the HR value and horizontal lines indicate the 95% 714
CIs. The HR values of intention-to-treat population are highlighted in black. 715
716
717
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Table 1. Univariable and multivariable analysis of PFS and OS in EGFR/ALKWT
NSCLC receiving atezolizumab in POPLAR/OAK cohort
Atezolizumab group Progression-free survival Overall survival
*PD-L1 IHC performed in OAK cohort Univariable analysis Multivariable analysis Univariable analysis Multivariable analysis
Parameter HR (95%CI) P value HR (95%CI) P value HR (95%CI) P value HR (95%CI) P value
Age (≥65 vs. <65) 0.97 (0.78-1.21) 0.811 0.99 (0.77-1.27) 0.925
Sex (male vs. female) 0.80 (0.64-1.01) 0.065 0.84 (0.66-1.06) 0.135 0.79 (0.60-1.03) 0.080 0.88 (0.66-1.17) 0.383
Race (white vs. non-white) 0.89 (0.70-1.14) 0.351 1.37 (1.02-1.84) 0.039 1.44 (1.07-1.95) 0.018
Histology (LUSC vs. non-LUSC) 1.13 (0.89-1.42) 0.311 1.41 (1.08-1.83) 0.010 1.49 (1.13-1.96) 0.004
ECOG (1 vs. 0) 1.36 (1.08-1.72) 0.010 1.45 (1.14-1.84) 0.003 1.81 (1.38-2.39) <0.001 1.90 (1.44-2.52) <0.001
Smoke (ever vs. never) 0.94 (0.68-1.29) 0.697 1.38 (0.92-2.06) 0.116
Lines (3 vs. 2) 0.81 (0.64-1.03) 0.089 0.70 (0.55-0.90) 0.005 0.95 (0.72-1.25) 0.717
Metastatic sites (≥3 vs. <3) 1.38 (1.10-1.72) 0.005 1.28 (1.02-1.61) 0.033 1.46 (1.12-1.89) 0.005 1.32 (1.01-1.72) 0.043
bTMB (≥16 vs. <16) 0.83 (0.65-1.07) 0.151 1.00 (0.76-1.33) 0.987
PD-L1 (TC1/2/3 or IC1/2/3 vs. TC0 and IC0) 0.93 (0.72-1.19) 0.551 0.94 (0.70-1.26) 0.676
PD-L1 (TC3 or IC3 vs. TC0/1/2 and IC0/1/2) 0.82 (0.59-1.13) 0.217 0.66 (0.47-0.99) 0.043
STK11 (mut vs. WT) 1.53 (1.06-2.22) 0.024 1.51 (1.03-2.19) 0.033 1.58 (1.06-2.34) 0.024 1.54 (1.02-2.32) 0.038
KEAP1 (mut vs. WT) 1.84 (1.37-2.47) <0.001 1.88 (1.39-2.53) <0.001 1.93 (1.41-2.66) <0.001 1.92 (1.39-2.67) <0.001
TP53 (mut vs. WT) 1.11 (0.90-1.38) 0.337 1.40 (1.09-1.80) 0.008 1.20 (0.92-1.57) 0.171
KRAS (mut vs. WT) 1.17 (0.82-1.68) 0.383 1.24 (0.83-1.87) 0.295
TP53 & KRAS (co-mut vs. mono-mut + WT) 0.75 (0.45-1.26) 0.273 0.78 (0.41-1.46) 0.430
del-NOTCHmut
(del-NOTCHmut
vs. the rest) 0.62 (0.41-0.92) 0.018 0.57 (0.38-0.86) 0.006 0.79 (0.51-1.24) 0.305 0.63 (0.40-0.99) 0.045
Abbreviations: bTMB, blood tumor mutational burden; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; IHC,
immunohistochemistry; KEAP1, Kelch-like ECH-associated protein 1; LUSC, lung squamous carcinoma; NSCLC, non-small cell lung cancer; PD-L1,
programmed cell death ligand 1; PFS, progression-free survival; STK11, serine/threonine kinase 11; TP53, tumor protein p53; WT, wildtype.
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Published OnlineFirst April 2, 2020.Clin Cancer Res Kai Zhang, Xiaohua Hong, Zhengbo Song, et al. predictor to efficacious immunotherapy in NSCLC
mutation as novelNOTCHIdentification of deleterious
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