Literature DB >> 32676324

Integrating clinical and biological prognostic biomarkers in patients with advanced NSCLC treated with immunotherapy: the DEMo score system.

Arsela Prelaj1,2, Claudia Proto1, Giuseppe Lo Russo1, Diego Signorelli1, Roberto Ferrara1, Mavis Mensah3, Giulia Galli1, Alessandro De Toma1, Giuseppe Viscardi1, Marta Brambilla1, Riccardo Lobefaro1, Benedetta Trevisan1, Francesco Trovò2, Valter Torri4, Gabriella Sozzi3, Marina Chiara Garassino1, Mattia Boeri3.   

Abstract

BACKGROUND: Several biomarkers have been separately described to select patients for immunotherapy (IO), but few studies integrate these markers. Di Maio, EPSILoN and the plasma microRNA signature classifier (MSC), are three different clinico, biochemical and molecular markers able to independently predict prognosis in non-small cell lung cancer (NSCLC).
METHODS: Complete data such as sex, histology, ECOG-PS, stage, smoking status, presence of liver metastasis, LDH and neutrophils-to-lymphocyte ratio were collected to generate Di Maio and EPSILoN. The MSC risk level was prospectively assessed in plasma samples collected at baseline IO. The 3 markers were integrated into the DEMo score system prospectively tested in a cohort of 200 advanced NSCLC patients treated with IO. Endpoints were overall survival (OS), progression-free survival (PFS) and overall response rate (ORR).
RESULTS: DEMo separated patients in 7-risk groups whose median OS had a trend ranging from 29.7 to 1.5 months (P<0.0001). When comparing patients with the lowest (n=29) and the highest (n=35) DEMo scores ORR was 45% and 3%, respectively (P<0.0001). Considering the 53 PD-L1 ≥50% patients, DEMo identified a group of 13 (25%) patients who benefit less from IO in terms of both OS (HR: 8.81; 95% CI: 2.87-20.01) and PFS (HR: 6.82; 95% CI: 2.57-18.10). Twelve out of 111 (11%) patients who most benefit from IO according to OS (HR: 0.21; 95% CI: 0.07-0.62) and PFS (HR: 0.28; 95% CI: 0.12-0.65) were identified by DEMo in the PD-L1 <50% group.
CONCLUSIONS: The DEMo prognostic score system stratified NSCLC patients treated with IO better than each single marker. The proper use of DEMo according to PD-L1 could improve selection in IO regimens. 2020 Translational Lung Cancer Research. All rights reserved.

Entities:  

Keywords:  Non-small cell lung cancer (NSCLC); biomarker; immunotherapy; plasma microRNA; prognosis

Year:  2020        PMID: 32676324      PMCID: PMC7354114          DOI: 10.21037/tlcr-20-231

Source DB:  PubMed          Journal:  Transl Lung Cancer Res        ISSN: 2218-6751


Introduction

Despite the improvement in overall survival (OS) of unselected advanced non-small cell lung cancer (NSCLC) patients treated with the immunotherapy (IO), biomarkers able to identify ideal candidate patients with adequate accuracy remain an unmet need. Continuous changes of the IO suggestion scenery, moving from second or further to first-line therapy or from single agent to the combination therapy with other companions [IO + chemotherapy (CHT), IO + CHT + bevacizumab or IO + IO], are among the main delay causes on finding the optimal biomarkers (1-8). Up to today, the expression of the programmed-death ligand one (PD-L1) on tumor cells by immunohistochemistry (IHC) is the only approved biomarker. Indeed, despite patients expressing high levels of PD-L1 (≥50%) respond better to IO, some of them do not benefit from single agent IO. Conversely, a subgroup of patients with low PD-L1 (1–49%) still may benefit from IO alone, thus avoiding the toxicity added by other possibly companions such as chemotherapy. Another aspect includes the possibility to identify subjects with a non-negligible risk of early clinical failure (ICF) or hyper-progressive disease independently of PD-L1 expression (4-8). According to literature, many attempts to discover predictive biomarkers outside PD-L1 have been made so far. The tumour mutation burden, CD8-positive tumour-infiltrating lymphocytes and immune gene signatures showed promising results as tissue biomarkers (9). However, tumor heterogeneity and the difficulties to obtain adequate tissue samples from aNSCLC patients, prompt for the use of scores systems based on clinical information or circulating biochemical and molecular factors. In this respect, markers such as the Lung Immune Prognostic Index (LIPI), based on the lactate dehydrogenase (LDH) levels and neutrophil-to-lymphocyte ratio (NLR), were created and associated with clinical outcome in IO settings (10,11). By adding information about the Eastern Cooperative Oncology Group Performance Status (ECOG-PS), sex, smoking habits and metastases sites, more complexes prognostic score systems such as Di Maio and EPSILoN were further generated (12-14). Among molecular biomarkers, the plasma microRNA signature classifier (MSC), developed for early lung cancer detection and reflecting an immunesuppressive host status (15,16), has recently shown its prognostic value also in aNSCLC patients treated with single agent IO (17). The 3 markers were here compared and integrated in a unique score system called DEMo (Di Maio, EPSILoN, MSC). The aim of this prospective study was to assess if DEMo score is able to better categorize outcome of aNSCLC patients treated with IO and if the combination of these three biomarkers could improve the performance prediction compared to each single biomarker alone potentially helping clinical decision making.

Methods

Study population

From July 2015 to June 2019, we conducted a prospective observational study (Apollo, INT 22_15) enrolling 200 consecutive aNSCLC patients who received single-agent anti-PD-(L)1 inhibitors in 1L (n=70) or further-line therapy (n=130). Complete data were collected for both clinical scores. Whole blood samples were collected to assess LDH and NLR. The MSC test was prospectively assessed in plasma samples collected at baseline IO. Eligible patients fulfilled the following inclusion criteria: cytological/histological diagnosis of aNSCLC, patients (relapsed or stage IIIB to IV) that had received at least one infusion of anti PD-(L)1 single agent in 1L or further-line. This prospective study was conducted at the Fondazione IRCCS Istituto Nazionale Tumori of Milan in Italy and was accomplished in accordance with the Declaration of Helsinki, Good Clinical Practice and local ethical guideline. The present ongoing study was approved from local ethical committee and all included patients signed informed consent.

Treatment and response evaluation

IO was administered intravenously as monotherapy; Nivolumab was administered initially at a dose of 3 mg/kg and later, since May 2018 in Italy, at a fixed dose of 240 mg every 2 weeks (w); pembrolizumab at a dose of 2 mg/kg every 3 w in PD-L1 1–49% and at a fix dose of 200 mg in those patients with PD-L1 ≥50%; atezolizumab at a fixed dose of 1,200 mg every 3w and durvalumab at a dose 10 mg/kg every 2 w. Response Evaluation Criteria in Solid Tumors (RECIST) v.1.1 criteria was used to assess tumor response (18). Response to IO was not valuable (NV) in patients who discontinued therapy after one cycle due to adverse effects or clinical deterioration. Therapy was continued until disease progression (PD), intolerable toxicity, withdrawal or death. Treatment beyond PD was allowed, if there was a clinical benefit according to clinician’s decision. Baseline radiological evaluations comprised a baseline total body computed tomography (TB-CT) scan, subsequently performed every 3–4 cycles or every 9–12 weeks, or whenever PD was clinically suspected.

Clinical and molecular markers

The Di Maio score combined clinico-pathological information such as sex, histology, ECOG-PS stage, uses of first-line platinum-based therapy and relative response (13,14). It stratified patients in three distinctive groups with a well-balanced cut-off along the range of values: <5, 5–9, >9 for the best (DiM_1), the intermediate (DiM_2) and the worst category (DiM_3), respectively (13,14). EPSILoN combines clinical and biochemical information such as ECOG-PS, smoking status, presence of liver metastasis, lactate dehydrogenase (LDH) levels and the neutrophils-to-lymphocyte ratio (NLR) (19). Similarly to Di Maio, EPSILoN separated patients in three different prognostic categories: <1 for best (E_1), 1-–2 intermediate (E_2) and >2 worst category (E_3), respectively. The optimal cut-off for LDH and NLR values were determined using a statistic method enables calculation of both the cut-off value and its significance as previously described (19). The plasma MSC test analyzed the reciprocal levels among 24 circulating microRNAs by quantitative reverse transcription PCR (RT-qPCR) as previously described (20). It stratified lung cancer patients in two main different prognostic groups, being MSC low/intermediate risk patients, with a better outcome compared to MSC high risk patients (17,21). Due to unspecific released of microRNAs in presence of cell lyses, highly heamolyzed plasma samples were undetermined for MSC and thus excluded from relative single marker analysis (22).

Data integration

A two-step data integration approach based on clinical evidence was adopted to generate the DEMo score system. In order to combine data from different sources into a single score, each group of patients identified by the 3 single markers received a score ranging from 1 to 3 according to their established prognostic value (12-14,21): score 1 for the DiM_1, E_1 and MSC intermediate/low risk groups with best prognosis (BP); score 2 for DiM_2, E_2 and MSC undetermined; score 3 for the DiM_3, E_3 and MSC high risk groups with worst prognosis (WP). The raw DEMo score system given by the sum of the three individual scores stratified patients in 7 risk groups with values ranging from 3 to 9. A second data elaboration step was then adopted to better evaluate the clinical utility of the DEMo score system. Indeed, 3 major DEMo groups were identified according to the balance between BP and WP groups according to the single markers: patients with DEMo score 3, exclusively composed by BP groups; patients with DEMo score from 4 to 6, where BP ≥ WP groups; and patients with DEMo score from 7 to 9, where BP < WP groups.

Statistical analysis

The endpoints were progression-free survival (PFS), overall survival (OS) and overall response rate (ORR) in strata of each single marker and the DEMo combined scores. OS was intended from the IO start date until death (event) or last follow-up (censored). Median PFS (mPFS) was considered from the IO start date until PD, death due to any cause (events), or last follow-up visit for patients alive without PD (censored). Survival curves were estimated using the Kaplan-Meier method and compared by the log-rank test (23). Cox’s proportional hazards models were used to perform multivariate analyses. Overall response rate (ORR) was defined as the percentage of complete and partial response (R) among all patients. Patients with NV response to IO were excluded from ORR analysis. The continuous variables were given as the median values and interquartile range (IQR). Interrater agreement of categorical variables was evaluated by the Cohen’s kappa statistic. All tests were two-sided, and P value <0.05 was considered statistically significant. Statistical analyses were performed using MEDCALC v.19.1.3 and PRISM–GraphPad v.5.02 software. was generated using Matlab script program v.R2019b.
Figure 1

Group score class for patients with (A) progressive disease (PR), (B) stable disease (SD), (C) progressive disease (PD) and (D) not valuable (NV) response due to adverse effects or clinical deterioration. Dot size is proportional with the number of patients in the respective score classes.

Group score class for patients with (A) progressive disease (PR), (B) stable disease (SD), (C) progressive disease (PD) and (D) not valuable (NV) response due to adverse effects or clinical deterioration. Dot size is proportional with the number of patients in the respective score classes.

Results

Patients’ characteristics

Two hundred aNSCLC patients treated with anti-PD-(L)1 in 1L or further-line therapy were included in the analysis (). Most patients were male (65%) and smokers (79.5%) with median pack-year of 35 (IQR: 20–50). Median age was 67 years (range, 60–74 years) and 38% of patients were older than 70 years. Median ECOG-PS was 1 (range, 0–1) with an ECOG PS 2 in 14.5% of patients. All patients had a histological diagnosis of NSCLC (77% non-squamous and 23% squamous) and were EGFR non-mutated and ALK non-translocated. At baseline ICIs liver metastases were present 17.5% of patients. More than one third of patients (35%) received IO in 1L, while 65% received anti-PD-(L)1 therapy in second or further-lines. All 200 patients included in the study were assessable for survival analysis, but only 176 were evaluable for ORR. At the time of data cut-off (June 2019), 165 patients (82.5%) had disease progression and 142 patients had died (71%). The median follow-up for alive patients in the present cohort was 14.9 months.
Table S1

Clinco-pathological characteristics of 200 consecutive advanced NSCLC patients treated with single agent immune checkpoint inhibitors

Characteristics# patients%
Total200100
Female7035
Median age [IQR]67 [60–74]
Pack-year [IQR]35 [20–50]
Histology
   Adenocarcinoma13065
   Squamous cell carcinoma4824
   Others2111
Stage
   IIIB–IIIC52.5
   IV19597.5
ECOG-PS
   05829
   111356.5
   22914.5
PD-L1
   ≥50%5326.5
   <50%11155.5
   N.A.3618
IO as first line therapy7035
Presence of liver metastasis3517.5
Median NLR (IQR)4.2 (2.8–6.8)
Median LDH (IQR)361 (309–445)
Median follow-up for alive pts14.9 (7.5–26.0)

NSCLC, non-small cell lung cancer; IQR, interquartile range; ECOG-PS, Eastern Cooperative Oncology Group Performance Status; PD-L1, programmed death-ligand 1; IO, immunotherapy; NLR, neutrophil-to-lymphocyte ratio; LDH, lactate dehydrogenase level.

The single markers’ prognostic value ()

Both Di Maio and EPSILoN clinical scores divided patients into three categories with different prognosis: mOS was 21.3, 5.0 and 2.8 months for the 83 (41.5%) patients with DiM_1, the 94 (47%) DiM_2 and the 23 (11.5%) DiM_3, respectively (P<0.0001; Figure S1A). The mOS according to the EPSILoN score was 22.4 months for the 49 (24.5%) E_1, 8.3 months for the 107 (53.5%) E_2 and 2.9 months for the 44 (22%) E_3 (P<0.0001; Figure S1C). Adequate plasma samples to run the MSC test were available for 159 (79.5%) patients: mOS was 12.4 months in the group of 118 (59%) patients with MSC low or intermediate risk level and 4.7 months for the 41 (20.5%) patients with MSC high risk level (P<0.0001; Figure S1E). The remaining 41 (20.5%) patients had highly haemolyzed plasma samples and were thus not analyzable for the MSC test. Similar results were obtained when considering PFS as endpoint (Figure S1B,D,F).

Comparison of clinical and molecular markers

A score from 1 to 3 was attributed to each group of patients identified by the 3 individual markers, being 1 the group at best prognosis (BP) and 3 the groups at worst prognosis (WP). Analysis of the inter-rater reliability among the markers revealed a slight agreement when comparing both the Di Maio and EPSILoN scores vs. the MSC score (K≤0.10), while a moderate agreement (K=0.42) was observed when comparing Di Maio vs. EPSILoN (). Their independence was also confirmed by fitting Cox models for OS and PFS adjusted for the 3 markers. Results indicated that each marker maintained its prognostic significance while controlling for the other two: OS HR were 2.39 (95% CI: 1.82–3.16), 1.71 (95% CI: 1.30–2.26) and 1.42 (95% CI: 1.15–1.75) form Di Maio, EPSILoN and MSC, respectively ().
Table S2

Inter-rater reliability between Di Maio and Epsilon scores and the microRNA signature classifier (MSC). Concerning the MSC risk level patients with intermediate and low risk level were considered as score 1, patients with undetermined result as score 2 and patients with high risk level as score 3. To evaluate the agreement between each couple of marker the Cohen Kappa statistics (K) was applied

ScoreMSCEPSILoN
123K123K
Di Maio0.090.43
   155181036389
   2522022136021
   311390914
EPSILoN0.10
   13883
   2622124
   3181214
Table S3

Cox proportional hazards models for overall survival and progression free survival on 200 NSCLC patients stratified according to Di Maio and EPSILoN scores and the molecular microRNA signature classifier (MSC)

ScoreUnivariateMultivariate
HR95% CIP valueHR95% CIP value
Overall survival
   Di Maio2.972.28–3.87<0.00012.391.82–3.16<0.0001
   EPSILoN2.261.77–2.89<0.00011.711.30–2.260.0001
   MSC1.651.35–2.02<0.00011.421.15–1.750.0009
Progression free survival
   Di Maio1.981.57–2.49<0.00011.541.20–1.970.0008
   EPSILoN2.151.70–2.71<0.00011.751.35–2.27<0.0001
   MSC1.541.28–1.86<0.00011.351.11–1.630.0022

NSCLC, non-small cell lung cancer; HR, hazard ratio; CI, confidence interval.

By stratifying patients according to response to IO, 13 out of 36 (36%) responder (R) and 14 out of 48 (39%) patients with stable disease (SD) were in the BP group for the 3 markers simultaneously, but no one was in the WP group for more than 1 marker (). Conversely, among patients with progressive disease (PD) only 2 out of 116 (2%) were included in all the 3 BP group, while 17 (15%) were in the WP group for at least 2 markers (). Similarly, when considering the 24 patients who discontinued therapy after one cycle due to adverse effects or clinical deterioration, no one patient had 3 markers with score 1, while 8 (33%) had at least 2 markers with score 3 ().

The integrated DEMo prognostic score system

The raw DEMo score system generated by the integration of the 3 single prognostic markers, stratified patients in 7 groups with a score ranging from 3 to 9. Throughout these groups, mOS had a trend ranging from 29.7 to 1.5 months (P<0.0001; ) and mPFS from 12.4 to 1.1 months (P<0.0001; ).
Figure 2

Kaplan-Meier curves in strata of the seven DEMo score groups according to (A) overall survival (OS) and (B) progression free survival (PFS). Log-rank test P values are reported.

Kaplan-Meier curves in strata of the seven DEMo score groups according to (A) overall survival (OS) and (B) progression free survival (PFS). Log-rank test P values are reported. For further analysis, patients were combined in three major DEMo groups according to the balance between BP and WP groups for the 3 single markers: 29 patients were included in the DEMo score 3 group, patients with DEMo scores from 4 to 6 were 136 and 35 patients had DEMo scores from 7 to 9. Hazard ratio (HR) from multivariate OS analysis adjusted for age, sex, smoking status, ECOG-PS and line of therapy were 5.37 (95% CI: 1.55–18.62), 3.14 (95% CI: 1.48–6.66), 2.13 (95% CI: 1.36–3.34) and 13.13 (95% CI: 3.85–44.81) when comparing the two extreme prognostic groups according to Di Maio, EPSILoN, MSC and DEMo, respectively (). Comparable results in terms of PFS were obtained for each marker, being the HR in strata of the DEMo score system the highest one (HR: 7.46; 95% CI: 2.61–21.29).
Table 1

Progression free and overall survival from the adjusted Cox proportional hazards models on 200 NSCLC patients (pts) stratified according to clinical and molecular scores individually and integrated into the DEMo score system

Score# ptsOverall survivalProgression free survival
HR*95% CIP valueHR*95% CIP value
Di Maio
   DiM_1831 (ref)1 (ref)
   DiM_2942.611.49–4.570.00081.701.04–2.770.0349
   DiM_3235.371.55–18.620.00802.290.77–6.870.1380
EPSILoN
   E_1491 (ref)1 (ref)
   E_21072.461.46–4.160.00072.671.38–3.720.0012
   E_3443.141.48–6.660.00292.681.30–5.560.0078
MSC risk levelǂ
Low/intermediate1181 (ref)1 (ref)
   High412.131.36–3.340.00091.721.12–2.640.0126
DEMo
   3291 (ref)1 (ref)
   4 to 61242.881.44–5.790.00293.431.85–6.360.0001
   7 to 94713.133.85–44.81<0.00017.462.61–21.290.0002

*, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, 41 patients with undetermined MSC results were excluded from the analysis. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference.

*, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, 41 patients with undetermined MSC results were excluded from the analysis. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference. When considering the ORR as end-point (), analysis between the two extreme prognostic groups resulted in a relative risk of response (RR) of 0.19 (0.03–1.33), 0.28 (0.09–0.88) and 0.33 (0.11–1.02) for Di Maio, EPSILoN and MSC markers, respectively. On the other hand, the corresponding analysis comparing ORR in the 35 patients with DEMo scores 7 to 9 versus the 29 patients within the DEMo score 3 group resulted in a RR =0.06 (95% CI: 0.01–0.46).
Table S4

Overall response rate (ORR) and relative risk of response (RR) in patients stratified according to clinical and molecular scores individually or integrated into the DEMo score system

Score# patients*ORRRR95% CI
Di Maio
   DiM_17930%1 (ref)
   DiM_28014%0.450.24–0.86
   DiM_3176%0.190.03–1.33
EPSILoN
   E_14933%1 (ref)
   E_29418%0.550.31–1.00
   E_3339%0.280.09–0.88
MSC risk levelǂ
   Low/intermediate11028%1 (ref)
   High329%0.330.11-1.02
DEMo
   32945%1 (ref)
   4 to 611220%0.440.25–0.76
   7 to 9353%0.060.01–0.46

*, 24 patients with not evaluable response rate were excluded from the analyses; ǂ, 34 patients with undetermined MSC results were excluded from the analysis. MSC, microRNA signature classifier; CI, confidence interval; ref, reference.

DEMo models according to PD-L1 status

PD-L1 status was available in 164 (82%) patients of the present series. In order to evaluate the clinical utility of the 3 single markers and the DEMo score system according to PD-L1 expression levels, two distinct models were adopted. Model_1 was defined to identify PD-L1 ≥50% patients (n=53) who less benefit from single agent IO by comparing patients in the WP group vs. all other patients. The mOS and mPFS were respectively 2.4 and 1.9 months for the 13 (25%) aNSCLC patients with DEMo scores 7 to 9, while not reached and 11.4 months for the other 40 patients (). Conversely, in order to identify PD-L1 <50% patients (n=111) who may still benefit of single agent IO, the Model_2 compared patients in the BP group vs. all other patients. According to Model_2, a not reached mOS and a 10.3 months mPFS for the 12 (11%) aNSCLC patients with DEMo score 3 were compared to the 5.7 months mOS (P=0.0005) and 2.1 months mPFS (P<0.0001) of the remaining 99 patients with higher scores ().
Figure 3

Kaplan-Meier curves in strata of (A,B) DEMo Model 1 in PD-L1 ≥50% patients and (B,C) DEMo Model 2 in PD-L1 <50% patients according to both (A,C) overall survival (OS) and (B,D) progression free survival (PFS). Log-rank test P values are reported.

Kaplan-Meier curves in strata of (A,B) DEMo Model 1 in PD-L1 ≥50% patients and (B,C) DEMo Model 2 in PD-L1 <50% patients according to both (A,C) overall survival (OS) and (B,D) progression free survival (PFS). Log-rank test P values are reported. In PD-L1 ≥50% patients, the Model_1 adjusted HR from multivariate analysis for OS was 4.70 (95% CI: 0.61–35.5), 2.56 (95% CI: 0.91–7.23), 4.78 (95% CI: 1.84–12.46) and 8.81 (95% CI: 2.87–20.01) for Di Maio, EPSILoN, MSC and DEMo, respectively (). By stratifying PD-L1 <50% patients according to Model_2, the adjusted OS HR for the BP groups were 0.26 (95% CI: 0.13–0.54) for Di Maio, 0.43 (95% CI: 0.22–0.85) for EPSILoN, 0.57 (95% CI: 0.36–0.91) for MSC and 0.21 (95% CI: 0.07–0.62) for DEMo (). Similar results were obtained when considering PFS ().
Table 2

Progression free and overall survival from the adjusted Cox proportional hazards models on 53 PD-L1 ≥50% NSCLC patients (pts) stratified according to clinical and molecular scores individually and integrated into the DEMo score system

Model_1# ptsOverall survivalProgression free survival
HR*95% CIP valueHR*95% CIP value
Di Maio
   DiM_1&2511 (ref)1 (ref)
   DiM_324.700.61–35.500.13655.510.85–35.800.074
EPSILoN
   E_1&2411 (ref)1 (ref)
   E_3122.560.91–7.230.07512.621.14–6.040.0238
MSC risk level
   Othersǂ451 (ref)1 (ref)
   High84.781.84–12.460.00134.481.89–10.600.0006
DEMo score
   3 to 6401 (ref)1 (ref)
   7 to 9138.812.87–20.010.00016.822.57–18.100.0001

*, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, patients with intermediate/low MSC risk level or undetermined results were included. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference.

Table 3

Progression free and overall survival from the adjusted Cox proportional hazards models on 111 PD-L1 <50% NSCLC patients (pts) stratified according to clinical and molecular scores individually and integrated into the DEMo score system

Model_2ptsProgression free survivalOverall survival
HR*95% CIP valueHR*95% CIP value
Di Maio
   DiM_1370.260.13–0.540.00030.360.20–0.670.0012
   DiM_2&3741 (ref)1 (ref)
EPSILoN
   E_1250.430.22–0.850.01480.550.31–0.990.0451
   E_2&3861 (ref)1 (ref)
MSC risk level
   Low/intermediate640.570.36–0.910.01770.730.48–1.120.1495
   Othersǂ471 (ref)1 (ref)
DEMo score
   3120.210.07–0.620.00490.280.12–0.650.0031
   4 to 9991 (ref)1 (ref)

*, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, patients with high MSC risk level or undetermined results were included. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference.

*, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, patients with intermediate/low MSC risk level or undetermined results were included. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference. *, adjusted for age, sex, pack-year, line of therapy and ECOG performance status; ǂ, patients with high MSC risk level or undetermined results were included. NSCLC, non-small cell lung cancer; MSC, microRNA signature classifier; HR, hazard ratio; CI, confidence interval; ref, reference.

Discussion

The DEMo score system resulting from the combination of three different bio/markers: the Di Maio and EPSILoN clinical scores and the MSC molecular test. As prognostic marker in aNSCLC patients treated with IO, DEMo was able to perform better compared to each single bio/marker alone. The DiM prognostic score was initially developed (13) and validated (14) in patients with aNSCLC receiving 2L CHT and included only clinical features: ECOG-PS, sex, histology, stage, uses of platinum-based therapy at 1L and response to 1L. Authors concluded that patients in the worst category could have a slight chance to benefit from active anti-tumour treatments and probably best supportive care might be the best choice (14). Here we reported that the prognostic value of Di Maio was maintained also in patients receiving IO by identifying a subgroup with very short life expectancy. Similarly, the EPSILoN score, composed by both clinical (ECOG PS, smoking history and presence of liver metastases) and biochemical (NLR and LDH) factors, was trained in a cohort of aNSCLC patients treated with CHT and was recently validated in aNSCLC patients treated with IO (12). The plasma MSC molecular test was developed for early lung cancer detection in samples collected from LC patients and healthy volunteers enrolled in low-dose computed tomography screening trials (24). It stratified LC patients in 3 levels according to the risk to develop lung cancer in its aggressive form (16). The MSC diagnostic (high and intermediate vs. low risk level) and prognostic (high vs. intermediate and low risk level) value was independent to tumor characteristics such as stage, histology or mutational load (12). On the other hand, changes in circulating microRNA levels composing the MSC were associated to a protumorigenic and immunosuppressive phenotype of stromal and haematopoietic lineages such as fibroblasts, macrophages, polymorphonuclear and endothelial cells (15,25). Combining and integrating different markers in a unique composite score could potentially ameliorate patient selection. The LIPI score developed by Mezquita et al. (11 trials and 3,987 pts with aNSCLC) was created using two variables (NLR and LDH). This score was able to separate 3 different survival groups (good, intermediate and poor) in aNSCLC patients treated with IO compared to chemo- (10) and target-therapy (11) (controls arms); A recent paper on 21 different cancer types and 7,187 patients using anti-PD-1/PD-L1 agents showed that among 36 (multiomics prediction) the three top variables which better correlate with ORR were estimated CD8+ T-cell abundance, TMB and high PD-L1 gene expression (26). Here, the DEMo score system divided patients in 7 categories based on the combination of the three prognostic bio/markers previously reported (12-14,21). Each marker maintained its prognostic value in the present series by identifying BP and WP groups of aNSCLC patients treated with IO single agent. Patients included in the 3 BP groups (DEMo score 3) most benefit from IO. Conversely, patients included in more WP than BP groups (DEMo scores 7, 8 and 9) less benefit from IO single agent. In order to assess the clinical utility of the DEMo score system, a sub-group analysis adding information on PD-L1 status was also performed. Indeed, considering the results of recent clinical trials such as Keynote-189 and checkmate-227 (27,28), PD-L1 expression would drive therapy selection in daily practice (i.e., in our country, still, patients with high PD-L1 expression undergo pembrolizumab alone as first line therapy, while patients with non-squamous NSCLC and low PD-L1 expression perform CHT + IO, IO remain still a second line for patients with squamous-NSCLC and low PD-L1). With the idea to identify PD-L1 strong positive aNSCLC patients who could probably benefit more from combination therapy (CHT + IO or CHT + IO + anti-angiogenic drugs), the DEMo Model_1 was developed. In this context, DEMo identified a 25% of patients who poorly benefit from single agent IO. On the contrary, among patients with low PD-L1 expression the DEMo Model_2 identified a small percentage of patients (11%) who could still benefit from single-agent IO and could thus avoid unnecessary toxicity from the combo-therapy. The main limitation of our study was given by the impossibility to analyze a control arm, and thus to evaluate if DEMo could also be considered a predictive marker. In fact, when the Apollo prospective study started in 2015, the vast majority of aNSCLC patients underwent IO or were included in double blind clinical trials testing IO or IO-based combination therapies. The remaining aNSCLC patients treated with CHT were those excluded from clinical trials as not in compliance with enrolment criteria such as age or ECOG PS and, for the same reasons, cannot be used as control arm. Furthermore, only by testing the DEMo score system in aNSCLC patients treated with the recently approved IO combination therapies, we will understand the real clinical utility of such a test.

Conclusions

We created this composite clinical-molecular combined score called DEMo in order to test its prognostic utility in aNSCLC patients treated with first or further-line IO. Results indicated that DEMo identifies those patients who better or who are less likely to benefit from IO single-agent. To our knowledge, this is the first prospective exploratory study which tried to combine clinical, biochemical and molecular markers in order to create a composite score which take into account baseline characteristics that potentially predicts survival outcomes in IO regimens. Moreover, we successfully apply different DEMo models in appropriate clinical settings in order to potentially improve the patients’ selection given by PD-L1 status. Given the prospective nature of the study, here we integrated previously identified markers composed of several different features. Nevertheless, in the era of big data, artificial intelligence should be used as an efficient approach to help clinicians to manage lot amounts of data from different sources in order to create better predictive models to choose the most efficient IO-based therapy and sequence. Kaplan-Meier curves in strata of (A,B) DiMaio, (C,D) EPSILoN and (E,F) the microRNA signature classifier (MSC) according to (A,C,E) overall survival (OS) and (B,D,F) progression free survival (PFS). Log-rank test P values are reported. NSCLC, non-small cell lung cancer; IQR, interquartile range; ECOG-PS, Eastern Cooperative Oncology Group Performance Status; PD-L1, programmed death-ligand 1; IO, immunotherapy; NLR, neutrophil-to-lymphocyte ratio; LDH, lactate dehydrogenase level. NSCLC, non-small cell lung cancer; HR, hazard ratio; CI, confidence interval. *, 24 patients with not evaluable response rate were excluded from the analyses; ǂ, 34 patients with undetermined MSC results were excluded from the analysis. MSC, microRNA signature classifier; CI, confidence interval; ref, reference. The article’s supplementary files as
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1.  A note on quantifying follow-up in studies of failure time.

Authors:  M Schemper; T L Smith
Journal:  Control Clin Trials       Date:  1996-08

2.  Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial.

Authors:  Achim Rittmeyer; Fabrice Barlesi; Daniel Waterkamp; Keunchil Park; Fortunato Ciardiello; Joachim von Pawel; Shirish M Gadgeel; Toyoaki Hida; Dariusz M Kowalski; Manuel Cobo Dols; Diego L Cortinovis; Joseph Leach; Jonathan Polikoff; Carlos Barrios; Fairooz Kabbinavar; Osvaldo Arén Frontera; Filippo De Marinis; Hande Turna; Jong-Seok Lee; Marcus Ballinger; Marcin Kowanetz; Pei He; Daniel S Chen; Alan Sandler; David R Gandara
Journal:  Lancet       Date:  2016-12-13       Impact factor: 79.321

3.  Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial.

Authors:  Roy S Herbst; Paul Baas; Dong-Wan Kim; Enriqueta Felip; José L Pérez-Gracia; Ji-Youn Han; Julian Molina; Joo-Hang Kim; Catherine Dubos Arvis; Myung-Ju Ahn; Margarita Majem; Mary J Fidler; Gilberto de Castro; Marcelo Garrido; Gregory M Lubiniecki; Yue Shentu; Ellie Im; Marisa Dolled-Filhart; Edward B Garon
Journal:  Lancet       Date:  2015-12-19       Impact factor: 79.321

Review 4.  Predictive biomarkers of response for immune checkpoint inhibitors in non-small-cell lung cancer.

Authors:  Arsela Prelaj; Rebecca Tay; Roberto Ferrara; Nathalie Chaput; Benjamin Besse; Raffaele Califano
Journal:  Eur J Cancer       Date:  2018-12-05       Impact factor: 9.162

5.  Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer.

Authors:  Julie Brahmer; Karen L Reckamp; Paul Baas; Lucio Crinò; Wilfried E E Eberhardt; Elena Poddubskaya; Scott Antonia; Adam Pluzanski; Everett E Vokes; Esther Holgado; David Waterhouse; Neal Ready; Justin Gainor; Osvaldo Arén Frontera; Libor Havel; Martin Steins; Marina C Garassino; Joachim G Aerts; Manuel Domine; Luis Paz-Ares; Martin Reck; Christine Baudelet; Christopher T Harbison; Brian Lestini; David R Spigel
Journal:  N Engl J Med       Date:  2015-05-31       Impact factor: 91.245

6.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

7.  Association of the Lung Immune Prognostic Index With Immune Checkpoint Inhibitor Outcomes in Patients With Advanced Non-Small Cell Lung Cancer.

Authors:  Laura Mezquita; Edouard Auclin; Roberto Ferrara; Melinda Charrier; Jordi Remon; David Planchard; Santiago Ponce; Luis Paz Ares; Laura Leroy; Clarisse Audigier-Valette; Enriqueta Felip; Jorge Zerón-Medina; Pilar Garrido; Solenn Brosseau; Gérard Zalcman; Julien Mazieres; Caroline Caramela; Jihene Lahmar; Julien Adam; Nathalie Chaput; Jean Charles Soria; Benjamin Besse
Journal:  JAMA Oncol       Date:  2018-03-01       Impact factor: 31.777

8.  Assessment of circulating microRNAs in plasma of lung cancer patients.

Authors:  Orazio Fortunato; Mattia Boeri; Carla Verri; Davide Conte; Mavis Mensah; Paola Suatoni; Ugo Pastorino; Gabriella Sozzi
Journal:  Molecules       Date:  2014-03-10       Impact factor: 4.411

9.  EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort.

Authors:  Arsela Prelaj; Roberto Ferrara; Sara Elena Rebuzzi; Claudia Proto; Diego Signorelli; Giulia Galli; Alessandro De Toma; Giovanni Randon; Filippo Pagani; Giuseppe Viscardi; Marta Brambilla; Benedetta Trevisan; Monica Ganzinelli; Antonia Martinetti; Rosaria Gallucci; Rosa Maria Di Mauro; Giuliano Molino; Nicoletta Zilembo; Valter Torri; Filippo Maria de Braud; Marina Chiara Garassino; Giuseppe Lo Russo
Journal:  Cancers (Basel)       Date:  2019-12-05       Impact factor: 6.639

10.  MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening.

Authors:  Mavis Mensah; Cristina Borzi; Carla Verri; Paola Suatoni; Davide Conte; Ugo Pastorino; Fortunato Orazio; Gabriella Sozzi; Mattia Boeri
Journal:  J Vis Exp       Date:  2017-10-26       Impact factor: 1.355

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  3 in total

1.  Prognostic models for immunotherapy: emerging factors for an evolving treatment landscape.

Authors:  Howard West
Journal:  Transl Lung Cancer Res       Date:  2021-01

2.  Circulating CD81-expressing extracellular vesicles as biomarkers of response for immune-checkpoint inhibitors in advanced NSCLC.

Authors:  Diego Signorelli; Patrizia Ghidotti; Claudia Proto; Marta Brambilla; Alessandro De Toma; Roberto Ferrara; Giulia Galli; Monica Ganzinelli; Giuseppe Lorusso; Arsela Prelaj; Mario Occhipinti; Giuseppe Viscardi; Valentina Capizzuto; Francesca Pontis; Ilaria Petraroia; Anna Maria Ferretti; Mario Paolo Colombo; Valter Torri; Gabriella Sozzi; Marina Chiara Garassino; Elena Jachetti; Orazio Fortunato
Journal:  Front Immunol       Date:  2022-09-20       Impact factor: 8.786

3.  Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy.

Authors:  Arsela Prelaj; Mattia Boeri; Alessandro Robuschi; Roberto Ferrara; Claudia Proto; Giuseppe Lo Russo; Giulia Galli; Alessandro De Toma; Marta Brambilla; Mario Occhipinti; Sara Manglaviti; Teresa Beninato; Achille Bottiglieri; Giacomo Massa; Emma Zattarin; Rosaria Gallucci; Edoardo Gregorio Galli; Monica Ganzinelli; Gabriella Sozzi; Filippo G M de Braud; Marina Chiara Garassino; Marcello Restelli; Alessandra Laura Giulia Pedrocchi; Francesco Trovo'
Journal:  Cancers (Basel)       Date:  2022-01-16       Impact factor: 6.639

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