Literature DB >> 29509748

PD-L1 mRNA expression in plasma-derived exosomes is associated with response to anti-PD-1 antibodies in melanoma and NSCLC.

Marzia Del Re1, Riccardo Marconcini2, Giulia Pasquini2, Eleonora Rofi1, Caterina Vivaldi2, Francesco Bloise2, Giuliana Restante1, Elena Arrigoni1, Chiara Caparello2, Maria Grazia Bianco2, Stefania Crucitta1, Iacopo Petrini3, Enrico Vasile2, Alfredo Falcone2, Romano Danesi1.   

Abstract

This corrects the article DOI: 10.1038/bjc.2017.85.

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Year:  2018        PMID: 29509748      PMCID: PMC5886129          DOI: 10.1038/bjc.2018.9

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Immunotherapy has substantially improved the clinical outcome of several tumours, including cancers poorly responsive to chemotherapy (Robert ; Reck ). PD-L1 assessment in tumour tissue (i.e., NSCLC) allows to identify a patient population with higher likelihood of response with respect to chemotherapy (Reck ). However, changes in the activity of signal transduction patways (i.e., MAPK) (Jiang ) may affect PD-L1 levels, thus impairing its predictive value if assessed on a single-tissue biopsy. For these reasons, the interest of the scientific community is turning towards other potential biomarkers, such as mutational load and microsatellite instability (Rizvi ; Dudley ). Exosomes are microvesicles actively released from cancer cells; they have a size range of 40–150 nm and a lipid bilayer membrane and they carry proteins, RNA and DNA of cells from which they are originated (Kalluri, 2016). Their involvement in immune signalling, reprogramming of surrounding cells, as well as their ability to influence tumour microenvironment in favour of immune escape, therapy resistance, tumour growth and metastasis have been demonstrated (Kalluri, 2016). For these reasons, the present study was aimed at evaluating PD-L1 mRNA expression in plasma-derived exosomes to monitor response to the anti-PD-1 agents nivolumab and pembrolizumab in melanoma and NSCLC.

Patients and methods

Patients

Patients affected by locally advanced or metastatic melanoma or NSCLC given nivolumab (240 mg i.v. every 2 weeks) or pembrolizumab (200 mg i.v. every 3 weeks) as per approved schedule were enroled. The experimental part of the study consisted of two blood drawings from each patient for the measurement of exosomal mRNA levels of PD-L1 at time 0 (baseline) and at the time of radiological assessment of disease status, i.e., after 2 months of treatment. Complete or partial responses (CR, PR), disease stabilisation (SD) and disease progression (PD) were defined following RECIST (v. 1.1) criteria.

Measurement of exosomal PD-L1

A blood sample of 6 ml was collected in EDTA tubes and centrifuged for 10 min at 1900 g within 2 hours. The isolation of exosomes from plasma and extraction of RNA was previously described (Del Re ) and performed using the exoRNeasy kit (Qiagen, Valencia, CA). The analysis of PD-L1 mRNA was performed by the QX100 ddPCR (Bio-Rad, Hercules, CA, USA) using the One-Step RT-ddPCR kit. The PrimePCR ddPCR Expression Probe Assay for CD274 (human) was used to assess PD-L1 expression and the human ß-actin ddPCR assay was used as internal control. Fluorescence signal quantification was performed by the droplet reader and the QuantaSoft software (Bio-Rad). The ratio of positive vs negative droplets was used to determine the number of mRNA copies per ml of the target molecule in the input reaction. Droplets with a fluorescence intensity threshold higher than 4000 were considered positive. Each plasma sample was extracted once and triplicate ddPCR analyses were performed per sample. The values reported below (copies per ml) represent the mean of the triplicate.

Statistical analysis

Inferential statistics was used to assess the significance of differences between paired samples (PD-L1 levels at time 0 vs 2 months; paired t-test) and unpaired groups (time 0 PR+CR vs SD+PD; unpaired t-test); the significance level was set at 5%. The GraphPad software (GraphPad Software, La Jolla, CA, USA online version) was used for statistical calculations.

Results

Eighteen patients with melanoma were enroled (Table 1); there were 2 CR, 8 PR, 2 SD and 6 PD. The number of mRNA copies per ml of PD-L1 in plasma-derived exosomes decreased in patients with CR/PR (mean 793.5 vs 231, time 0 vs 2 months, respectively), while it increased in patients with PD (mean 143.3 vs 326.7, time 0 vs 2 months, respectively). Two patients died, one due to PD (mRNA PD-L1 copies per ml increased from 90 to 360), and the other because of acute myocardial infarction, while on CR (PD-L1 mRNA decreased from 2000 to 1000 copies per ml). Table 2 reports a detailed description of PD-L1 changes.
Table 1

Clinical characteristics of patients

 Melanoma (n=18)NSCLC (n=8)
Age  
 Median (range)71 (45−87)64 (52−77)
Gender  
 Male/female12/65/3
ECOG PS  
 0/1−210/85/3
Tumour type  
 Squamous/adenocarcinoma 1/7
BRAF mutation  
 Yes/no5/13 
EGFR mutation  
 Yes/no 1/7
ALK translocation  
 Yes/no 0/8
First line immunotherapy11/180/8

Abbreviations: ALK=anaplastic lymphoma kinase; BRAF=v-RAF murine sarcoma viral oncogene homolog B1; ECOG PS=Eastern Cooperative Oncology Group performance status; EGFR=epidermal growth factor receptor; NSCLC=non-small cell lung cancer.

Table 2

PD-L1 copies per ml in plasma-derived exosomes vs tumour response in patients treated with pembrolizumab or nivolumab for melanoma or NSCLC

PatientTumour typeTreatmentPD-L1 time 0 (copies per ml)PD-L1 2 months (copies per ml)Response
1MelanomaNivolumab500240CR
2aMelanomaPembrolizumab20001000CR
3MelanomaPembrolizumab14070PR
4MelanomaPembrolizumab25000PR
5MelanomaPembrolizumab180220PR
6MelanomaPembrolizumab1045520PR
7MelanomaPembrolizumab21580PR
8MelanomaPembrolizumab60080PR
9MelanomaPembrolizumab4050PR
10MelanomaPembrolizumab350100PR
11NSCLCNivolumab1700400PR
12NSCLCNivolumab330200PR
Mean±s.e.m.  830.4±231.3242.5±82.5P=0.016
13MelanomaPembrolizumab190160SD
14MelanomaPembrolizumab95260SD
15NSCLCNivolumab380280SD
16NSCLCNivolumab530290SD
Mean±s.e.m.  298.8±97.2247.5±29.8P=0.586
17bMelanomaPembrolizumab90360PD
20MelanomaPembrolizumab90200PD
21MelanomaPembrolizumab0140PD
22MelanomaPembrolizumab70500PD
18MelanomaNivolumab115210PD
19MelanomaNivolumab495550PD
23NSCLCNivolumab270700PD
24NSCLCNivolumab0140PD
25NSCLCNivolumab260360PD
26bNSCLCNivolumab6501000PD
Mean±s.e.m.  204.0±68.8416.0±87.8P=0.001

Abbreviations: CR=complete response; NSCLC=non-small cell lung cancer; PD=progression of disease; PR=partial response; SD=stable disease.

Patients were grouped on the basis of tumour response and mean±s.e.m. values of PD-L1 copies per ml are reported; P-values were calculated by paired t-test.

Death due to acute myocardial infarction.

Death due to PD.

Patients 4 and 9 reported a PR during treatment with pembrolizumab; perhaps unexpectedly, PD-L1 was undetectable in plasma at tumour re-assessment. However, exosomal ß-actin mRNA was detectable in these two patients (8.1 and 9.0 × 106 copies per ml, respectively), thus excluding a false negative result. Eight patients with NSCLC were enroled in the study (Table 1); there were 2 PR, 2 SD and 4 PD. The mRNA copies per ml of PD-L1 were correlated with tumour response, with a clear increase in patients with PD (mean, 295 vs 550 copies per ml, time 0 vs 2 months, respectively) and decrease in patients who achieved a PR (mean, 1015 vs 300 copies per ml, time 0 vs 2 months, respectively). A modest variation was seen in patients with SD (mean 455 vs 285, time 0 vs 2 months, respectively) (Table 2). Figure 1 reports the data of 2 representative patients with NSCLC showing a PR and a PD; PD-L1 plasma levels varied in accordance with disease response or progression.
Figure 1

Effect of treatment with anti-PD-1 antibodies on exosomal PD-L1 expression and clinical response in NSCLC and melanoma. (A) Mean values of PD-L1 (copies per ml) evaluated in baseline (time 0, dark grey) and at tumour re-assessment after 2 months of treatment (light grey) in patients grouped according to tumour response (CR+PR, SD and PD); P-values are reported on top of the columns. ddPCR plots (B and C) showing PD-L1 exosomal mRNA variations during the follow up of 2 non-small cell lung cancer patients. The blue dots circled in blue represent PD-L1, whereas the green dots represent ß-actin. (B) PD-L1 expression at the time of patient entry into the study (1700 copies per ml) and reduction after 2 months (400 copies per ml); the patient showed a partial response. (C) detection of PD-L1 expression at baseline (270 copies per ml) and increase after 2 months (700 copies per ml); the subject had disease progression. CR=complete response; PD=progression of disease; PR=partial response; SD=stable disease.

In the overall population, the difference between PD-L1 mRNA copies per ml was significant both in patients with CR+PR (830.4±231.3 at time 0 vs 242.5±82.5 after 2 months, P=0.016) and with PD (204.0±68.8 vs 416.0±87.8, time 0 vs 2 months thereafter, P=0.001), but not, as expected, in patients with SD (298.8±97.2 at time 0 vs 247.5±29.8 after 2 months, P=0.586; Table 2). At time 0, subjects with CR and PR showed a significantly higher number of copies per ml of PD-L1 mRNA compared to subjects with SD and PD (830.4±231.3 vs 231.1±55.7, P=0.012; Table 2).

Discussion

This study first demonstrates exosomal PD-L1 expression changes during treatment with anti-PD-1 antibodies. Furthermore, the results show that PD-L1 levels in plasma-derived exosomes significantly decreased in patients responding to treatment and increased in subjects with disease progression, while, as expected, no significant changes were observed in patients with SD. The issue of variability of PD-L1 expression in relation to its predictive role has been addressed in tissue biopsies collected in the same patients at different time-points (Cho ). The predictive role of PD-L1 expression in tumour tissue is still a matter of debate, since cancers with low expression of PD-L1 may respond to nivolumab and survival is longer than patients treated with chemotherapy (Borghaei ). Moreover, it is not known which effect other therapies, including chemotherapy and radiotherapy, may have on PD-L1 expression. Thus, its assessment in primary tumour at the time of diagnosis may not inform on changes which will occur during clonal evolution and selective pressure of treatments. Studies on circulating biomarkers are increasing in number because they can provide important information on dynamic response to treatment. Although they are not aimed at selecting patients for the administration of anti-PD-1/PD-L1 treatments, they have the potential to provide relevant information on clinical outcome. The assessment of PD-L1 expression in circulating tumour cells has been evaluated in bladder cancer and NSCLC for its potential capability to guide the selection of patients to be treated with anti-PD-1 or PD-L1 antibodies (Anantharaman ; Nicolazzo ). Other studies evaluating tumour mutational burden or microsatellite instability may also be suitable to personalise treatment, although they follow a different strategy and PD-L1 expression is not specifically addressed (Rizvi ; Dudley ). The strategy of using exosomes in this study was suggested by their ability to preserve intact mRNA. Exosomes have an intriguing role in cancer signalling and immunity; they are involved in cell-to-cell communication, they reflect changes induced by treatment and, most importantly, they are involved in immune escape (Liu ). The ability of exosomes to communicate inhibitory signals to effector cells, including NK, macrophages, dendritic cells and T cells, may explain why the decline of PD-L1 in responding patients is associated with tumour response and possibly a restoration of cellular immunity. To confirm this hypothesis, larger cohorts of patients will be required, as well as a comparison of PD-L1 expression in paired tissue and plasma-derived exosomes. In conclusion, the present work demonstrates in a limited population that dynamic measurement of PD-L1 expression in plasma-derived exosomes is feasible and may provide useful information on the response to treatment with anti-PD-1 antibodies.
  12 in total

1.  Nivolumab in previously untreated melanoma without BRAF mutation.

Authors:  Caroline Robert; Georgina V Long; Benjamin Brady; Caroline Dutriaux; Michele Maio; Laurent Mortier; Jessica C Hassel; Piotr Rutkowski; Catriona McNeil; Ewa Kalinka-Warzocha; Kerry J Savage; Micaela M Hernberg; Celeste Lebbé; Julie Charles; Catalin Mihalcioiu; Vanna Chiarion-Sileni; Cornelia Mauch; Francesco Cognetti; Ana Arance; Henrik Schmidt; Dirk Schadendorf; Helen Gogas; Lotta Lundgren-Eriksson; Christine Horak; Brian Sharkey; Ian M Waxman; Victoria Atkinson; Paolo A Ascierto
Journal:  N Engl J Med       Date:  2014-11-16       Impact factor: 91.245

2.  The Detection of Androgen Receptor Splice Variant 7 in Plasma-derived Exosomal RNA Strongly Predicts Resistance to Hormonal Therapy in Metastatic Prostate Cancer Patients.

Authors:  Marzia Del Re; Elisa Biasco; Stefania Crucitta; Lisa Derosa; Eleonora Rofi; Cinzia Orlandini; Mario Miccoli; Luca Galli; Alfredo Falcone; Guido W Jenster; Ron H van Schaik; Romano Danesi
Journal:  Eur Urol       Date:  2016-10-10       Impact factor: 20.096

3.  Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer.

Authors:  Martin Reck; Delvys Rodríguez-Abreu; Andrew G Robinson; Rina Hui; Tibor Csőszi; Andrea Fülöp; Maya Gottfried; Nir Peled; Ali Tafreshi; Sinead Cuffe; Mary O'Brien; Suman Rao; Katsuyuki Hotta; Melanie A Leiby; Gregory M Lubiniecki; Yue Shentu; Reshma Rangwala; Julie R Brahmer
Journal:  N Engl J Med       Date:  2016-10-08       Impact factor: 91.245

4.  The activation of MAPK in melanoma cells resistant to BRAF inhibition promotes PD-L1 expression that is reversible by MEK and PI3K inhibition.

Authors:  Xiaofeng Jiang; Jun Zhou; Anita Giobbie-Hurder; Jennifer Wargo; F Stephen Hodi
Journal:  Clin Cancer Res       Date:  2012-10-24       Impact factor: 12.531

5.  Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.

Authors:  Naiyer A Rizvi; Matthew D Hellmann; Alexandra Snyder; Pia Kvistborg; Vladimir Makarov; Jonathan J Havel; William Lee; Jianda Yuan; Phillip Wong; Teresa S Ho; Martin L Miller; Natasha Rekhtman; Andre L Moreira; Fawzia Ibrahim; Cameron Bruggeman; Billel Gasmi; Roberta Zappasodi; Yuka Maeda; Chris Sander; Edward B Garon; Taha Merghoub; Jedd D Wolchok; Ton N Schumacher; Timothy A Chan
Journal:  Science       Date:  2015-03-12       Impact factor: 47.728

6.  Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer.

Authors:  Hossein Borghaei; Luis Paz-Ares; Leora Horn; David R Spigel; Martin Steins; Neal E Ready; Laura Q Chow; Everett E Vokes; Enriqueta Felip; Esther Holgado; Fabrice Barlesi; Martin Kohlhäufl; Oscar Arrieta; Marco Angelo Burgio; Jérôme Fayette; Hervé Lena; Elena Poddubskaya; David E Gerber; Scott N Gettinger; Charles M Rudin; Naiyer Rizvi; Lucio Crinò; George R Blumenschein; Scott J Antonia; Cécile Dorange; Christopher T Harbison; Friedrich Graf Finckenstein; Julie R Brahmer
Journal:  N Engl J Med       Date:  2015-09-27       Impact factor: 91.245

Review 7.  The biology and function of exosomes in cancer.

Authors:  Raghu Kalluri
Journal:  J Clin Invest       Date:  2016-04-01       Impact factor: 14.808

Review 8.  Microsatellite Instability as a Biomarker for PD-1 Blockade.

Authors:  Jonathan C Dudley; Ming-Tseh Lin; Dung T Le; James R Eshleman
Journal:  Clin Cancer Res       Date:  2016-02-15       Impact factor: 12.531

9.  Programmed Death Ligand 1 Expression in Paired Non-Small Cell Lung Cancer Tumor Samples.

Authors:  Jong Ho Cho; Steffen Filskov Sorensen; Yoon-La Choi; Yu Feng; Tae-Eun Kim; Heyjoo Choi; Jeanette Baehr Georgsen; Marisa Dolled-Filhart; Kenneth Emancipator; Peter Meldgaard; Jong-Mu Sun; Hong Kwan Kim; Yong Soo Choi; Young Mog Shim; Wei Zhou; Henrik Hager; Jhingook Kim
Journal:  Clin Lung Cancer       Date:  2017-04-24       Impact factor: 4.840

10.  Monitoring PD-L1 positive circulating tumor cells in non-small cell lung cancer patients treated with the PD-1 inhibitor Nivolumab.

Authors:  Chiara Nicolazzo; Cristina Raimondi; MariaLaura Mancini; Salvatore Caponnetto; Angela Gradilone; Orietta Gandini; Maria Mastromartino; Gabriella Del Bene; Alessandra Prete; Flavia Longo; Enrico Cortesi; Paola Gazzaniga
Journal:  Sci Rep       Date:  2016-08-24       Impact factor: 4.379

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  62 in total

Review 1.  Extracellular vesicles as cancer liquid biopsies: from discovery, validation, to clinical application.

Authors:  Zhen Zhao; Jia Fan; Yen-Michael S Hsu; Christopher J Lyon; Bo Ning; Tony Y Hu
Journal:  Lab Chip       Date:  2019-03-27       Impact factor: 6.799

Review 2.  Multimodal detection of PD-L1: reasonable biomarkers for immune checkpoint inhibitor.

Authors:  Qiao Yang; Zihan Xu; Linpeng Zheng; Luping Zhang; Qiai You; Jianguo Sun
Journal:  Am J Cancer Res       Date:  2018-09-01       Impact factor: 6.166

Review 3.  Circulating biomarkers predictive of tumor response to cancer immunotherapy.

Authors:  Ernest Y Lee; Rajan P Kulkarni
Journal:  Expert Rev Mol Diagn       Date:  2019-09-10       Impact factor: 5.225

4.  Exosomal PD-L1 confers chemoresistance and promotes tumorigenic properties in esophageal cancer cells via upregulating STAT3/miR-21.

Authors:  Haojie Wang; Yijun Qi; Zijun Lan; Qiwei Liu; Juanjuan Xu; Mengxi Zhu; Tingting Yang; Ruolin Shi; Shegan Gao; Gaofeng Liang
Journal:  Gene Ther       Date:  2022-04-19       Impact factor: 5.250

Review 5.  Immunoregulatory Roles of Extracellular Vesicles and Associated Therapeutic Applications in Lung Cancer.

Authors:  Zhengrong Yin; Jinshuo Fan; Juanjuan Xu; Feng Wu; Yang Li; Mei Zhou; Tingting Liao; Limin Duan; Sufei Wang; Wei Geng; Yang Jin
Journal:  Front Immunol       Date:  2020-08-28       Impact factor: 7.561

Review 6.  Study and analysis of antitumor resistance mechanism of PD1/PD-L1 immune checkpoint blocker.

Authors:  Zhengyi Wang; Xiaoying Wu
Journal:  Cancer Med       Date:  2020-09-02       Impact factor: 4.452

Review 7.  Emerging role of tumor cell plasticity in modifying therapeutic response.

Authors:  Siyuan Qin; Jingwen Jiang; Yi Lu; Edouard C Nice; Canhua Huang; Jian Zhang; Weifeng He
Journal:  Signal Transduct Target Ther       Date:  2020-10-07

Review 8.  PD-L1 as a biomarker of response to immune-checkpoint inhibitors.

Authors:  Deborah Blythe Doroshow; Sheena Bhalla; Mary Beth Beasley; Lynette M Sholl; Keith M Kerr; Sacha Gnjatic; Ignacio I Wistuba; David L Rimm; Ming Sound Tsao; Fred R Hirsch
Journal:  Nat Rev Clin Oncol       Date:  2021-02-12       Impact factor: 66.675

9.  uPAR+ extracellular vesicles: a robust biomarker of resistance to checkpoint inhibitor immunotherapy in metastatic melanoma patients.

Authors:  Letizia Porcelli; Michele Guida; Simona Serratì; Amalia Azzariti; Simona De Summa; Roberta Di Fonte; Ivana De Risi; Marianna Garofoli; Mariapia Caputo; Antonio Negri; Sabino Strippoli
Journal:  J Immunother Cancer       Date:  2021-05       Impact factor: 13.751

10.  A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC.

Authors:  Camillo Porta; Romano Danesi; Marzia Del Re; Federico Cucchiara; Eleonora Rofi; Lorenzo Fontanelli; Iacopo Petrini; Nicole Gri; Giulia Pasquini; Mimma Rizzo; Michela Gabelloni; Lorenzo Belluomini; Stefania Crucitta; Raffaele Ciampi; Antonio Frassoldati; Emanuele Neri
Journal:  Cancer Immunol Immunother       Date:  2020-12-14       Impact factor: 6.968

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