Clinica Chimica Acta 440 (2015) 44–48
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Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Personalized biomarkers to monitor disease progression in advanced non-small-cell lung cancer patients treated with icotinib Gaoguang Song a, Yujie Liu a, Yanying Wang a, Guanjun Ren b, Shuai Guo a, Junling Ren a, Li Zhang b,⁎, Zhili Li a,⁎ a Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China b Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
a r t i c l e
i n f o
Article history: Received 17 September 2014 Received in revised form 8 November 2014 Accepted 10 November 2014 Available online 15 November 2014 Keywords: Immunoinflammation-related protein complexes Non-small-cell lung cancer Time length of humoral immune and inflammatory response Time length of disease progression Progression-free survival
a b s t r a c t Background: Disease-specific humoral immune response-related protein complexes in blood are associated with disease progression. Methods: Thirty-one patients with stage IIIB and IV non-small-cell lung cancer (NSCLC) were administered with oral dose of icotinib hydrochloride (150 mg twice daily or 125 mg 3 times daily) for a 28-continuous-day cycle until diseases progressed or unacceptable toxicity occurred. The levels of immunoinflammation-related protein complexes (IIRPCs) in a series of plasma samples from 31 NSCLC patients treated with icotinib hydrochloride were determined by an optimized native polyacrylamide gel electrophoresis. Results: Three characteristic patterns of the IIRPCs, named as patterns a, b, and c, respectively, were detected in plasma samples from 31 patients. Prior to the treatment, there were 18 patients in pattern a consisting of 5 IIRPCs, 9 in pattern b consisting of six IIRPCs, and 4 in pattern c without the IIRPCs. The levels of the IIRPCs in 27 patients were quantified. Our results indicate that the time length of humoral immune and inflammation response (TLHIIR) was closely associated with disease progression, and the median TLHIIR was 22.0 weeks, 95% confidence interval: 16.2 to 33.0 weeks, with a lead time of median 11 weeks relative to clinical imaging evidence confirmed by computed tomography or magnetic resonance imaging (the median progression-free survival, 34.0 weeks, 95% confidence interval: 27.9 to 49.0 weeks). Conclusions: The complex relationships between humoral immune response, acquired resistance, and disease progression existed. Personalized IIRPCs could be indicators to monitor the disease progression. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Lung cancer is a leading cause of cancer-related mortality worldwide [1], which is mainly classified into non-small-cell lung cancer (NSCLC, about 85% of lung cancer) and small cell lung cancer (about 15%) [2]. Treatment plans have been prescribed to patients based on clinicopathological criteria. In recent years, advances in personalized lung cancer treatment have been made to targeting epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors (TKIs) (e.g., erlotinib, gefitinib, and icotinib) in NSCLC [3]. Unfortunately, only a small number of the patients with advanced lung cancer responded to EGFR-TKI therapy, and finally also acquired drug-resistance [4]. Acquired drug-resistance Abbreviations: NSCLC, non-small-cell lung cancer; IIRPCs, immunoinflammationrelated protein complexes; TLHIIR, time length of humoral immune and inflammation response; TLDP, time length of the disease progression; EGFR, epidermal growth factor receptor; TKI, tyrosine kinase inhibitor. ⁎ Corresponding authors at: Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, 5 Dongdan San Tiao, Beijing 100005, China. Tel./fax: +86 10 69156479. E-mail address: [email protected] (Z. Li).
http://dx.doi.org/10.1016/j.cca.2014.11.010 0009-8981/© 2014 Elsevier B.V. All rights reserved.
to EGFR-TKI therapy was also associated with T790M mutation in exon 20 of EGFR and overexpression of hepatocyte growth factor [5–7]. Previous study on disease progression has revealed that inflammation regulated by immunoglobulin and immune complexes might be a functionally significant factor of cancer promotion and progression [8]. Previous study has also indicated that the development of EGFRTKI-induced skin inflammation was associated with prolonged survival [9]. However, the mechanisms of these processes in the cancer development have not yet been fully understood. Recently, genomic alterations in solid cancers have been characterized by sequencing cell-free DNA in the blood of cancer patients [10], but it is impossible to use these assays to monitor each individual's disease progression due to their high cost. Clinical challenges in the treatment outcome of the patients with advanced lung cancer may require the determination of serological treatment response-related biomarkers to monitor disease progression and/or acquired drug-resistance and to improve therapeutic outcome. Serological biomarkers may be the products of cancer cells, tumor microenvironment, and host response, along with their dynamic interactions [11]. Therefore, it is important to develop less invasive methods to monitor the disease progression, instead of detecting tumor cells or tissue DNA. It has been observed that, in the advanced NSCLC patients
G. Song et al. / Clinica Chimica Acta 440 (2015) 44–48
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treated with gefitinib, serum surfactant protein D may be a new surrogate marker for predicting the response to gefitinib [12]. In addition, biomarkers should be of personal, less invasive, sensitive, and economic features, along with higher reproducibility. Our previous study has provided insight into the association of the levels and patterns of circulating immunoinflammation-related protein complexes (IIRPCs), which include immune-related proteins, inflammation-related proteins, and complement-related proteins [13], with cancers. 2. Materials and methods 2.1. Patients From August 2007 to March 2010, 31 patients with advanced NSCLC were enrolled in stage I and II clinical trials of icotinib hydrochloride on the basis of the eligibility criteria as previously described (BPI-2009H) [14,15]. Briefly, eligible patients were required to have histologically or cytologically confirmed stage IIIB or IV NSCLC and had received chemotherapy based on the American Joint Committee on Cancer system, 6th edition at the tumor-node-metastasis classification of staging system. Measurable tumors with the response evaluation criteria in solid tumors (RECIST, version 1.0) were designed as 0 or 1. The patients had disease progression after 1 or 2 platinum-based chemotherapy regimen, and there was no chemotherapy for N 3 weeks. In addition, the patients with the following clinical symptoms, such as interstitial pneumonia or pulmonary fibrosis, severe infection, intestinal paralysis or obstruction, women with pregnancy or lactation, and other serious medical conditions, were excluded. Radiological assessment of tumor size was performed once every 8 weeks by computed tomography or magnetic resonance imaging according to the RECIST. All participants have provided written informed consent in the study. The study was proved by the Ethics Committee of Peking Union Medical College Hospital and the Ethics Committee of Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences. All experiments were performed in accordance with relevant guidelines and regulations.
Fig. 1. Representative patterns of plasma IIRPCs. The patterns of the IIRPCs are classified into patterns a, b, c, d, and e, respectively.
intolerable toxicity. The time length of humoral immune and inflammation response (TLHIIR) is the time interval between the beginning of icotinib treatment and the time point at the 2-fold increase (or 0.5-fold decrease) in the IIRPC levels relative to their individual baseline. A p value of less than 0.05 was considered to be statistically significant. All statistical analyses were performed using SPSS software (version 16.0, SPSS Inc.).
2.2. Icotinib treatment and sample collection 3. Results The patients took oral icotinib at a dose of 150 mg twice daily or 125 mg 3 times daily for a 28-continuous-day cycle followed by the intermission of 3 days until diseases progressed, unacceptable toxicity occurred, or patients refused further treatment. A series of plasma samples of each patient were collected before the treatment as the baseline and during the treatment after an overnight fasting period of about 10 h. 2.3. Quantification of plasma IIRPCs Plasma protein complexes were isolated as our own previous study [13]. Briefly, native polyacrylamide gel electrophoresis with a gradient from 4 to 10% was used to separate plasma IIRPCs. Each run included nine test samples and one quality control sample in a single native polyacrylamide gel. The quality control sample was a mixture of 5 random patient plasma. Representative patterns of plasma IIRPCs are showed in Fig. 1. The gel bands labeled by a1, a2, a3, a4, a5, b1, b2, b3, b4, b5, b6, d1, d2, d3, e1, e2, and e3, correspond to the IIRPCs and the band labeled by the TRPC corresponds to transferrin-related protein complex. The levels of these protein complexes were quantified and their components were also identified as described previously [13]. 2.4. Statistical analysis Kaplan–Meier method was performed to determine survival. PFS is defined as the time interval between the beginning of icotinib treatment and the earliest occurrence of disease progression detected by computed tomography or magnetic resonance imaging or apparently
3.1. Patients Thirty-one advanced NSCLC patients were enrolled in this study, and their clinicopathological characteristics are listed in Table 1. The mean age was 56.8 y (range 41–71 y). Eleven (35.5%) patients were male, 27 patients (87.1%) showed stage IV, nineteen patients (61.3%) had ECOG performance status of 0, 25 (80.6%) had adenocarcinoma, nine patients had EGFR mutations, 22 patients (70.9%) were neversmokers, 10 patients (32.3%) had radiotherapy and the median PFS was 34.0 weeks (95% confidential interval: 27.9 to 49.0 weeks) based on the determination of computed tomography or magnetic resonance imaging. After 2-month icotinib treatment, the response to the initial icotinib treatment was complete response in one patient, partial response in eight patients, stable disease in nineteen patients, and disease progression in 3 patients (Fig. 2A). No severe toxicity was observed and no treatment-related death occurred in this study. 3.2. Distribution of plasma protein complexes of interest During icotinib treatment, a series of plasma samples from 31 advanced NSCLC patients were collected, and plasma protein complexes were isolated by the native polyacrylamide gel. As shown in Fig. 1, 3 patterns of plasma IIRPCs in the plasma samples collected before the treatment are observed, and 19, 8, and 4 patients were assigned as patterns (or groups) a, b and c, respectively (Table 1). For pattern a, 5 diseasespecific IIRPCs were detected and labeled by a1, a2, a3, a4, and a5, respectively. For pattern b, 6 disease-specific IIRPCs were detected and
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G. Song et al. / Clinica Chimica Acta 440 (2015) 44–48 Table 1 Baseline characteristics of 31 patients with non-small-cell lung cancer treated with icotinib. Characteristic
Value (%)
Male, no. (%) Age, y Mean Range Stage, no. (%) IIIB IV ECOG performance status, no.(%) 0 1 EGFR mutations Wild type Histology, no. (%) Adenocarcinoma Non-adenocarcinoma Previous chemotherapies, no. (%) 1 ≥2 Previous radiotherapy, no. (%) Smoking history, no. (%) Never-smoker Current- or ex-smoker Patterns of the IIRPCs, no. (%) Pattern a Pattern b Pattern c
11 (35.5) 56.8 41–71
during icotinib treatment in all patient plasmas. These results indicate that the TRPC should be an internal reference for quantifying the IIRPCs, which is consistent with our own previous study [13]. Statistical analysis also indicated that the patterns of the IIRPCs in different patients were not associated with PFS (p N 0.05, Fig. 2B). 3.4. Association of the TLHIIR with changes in the IIRPC levels
labeled by b1, b2, b3, b4, b5, and b6, respectively. But for pattern c, no disease-specific IIRPCs was observed. As shown in Fig. 1, one common protein complex in five patterns (a, b, c, d, and e), with the highest intensity in all plasma samples, is the TRPC. Their components were identified using mass spectrometry, and there are immunoglobulin G1, immunoglobulin A1, haptoglobin, complement component 3, complement component 4A, complement component 5, complement component 7, complement factor H, transferrin, and apolipoprotein A–I.
Although the levels of the IIRPCs in individual patients with pattern a or b had different baselines before the icotinib treatment, change trends in their levels were significantly associated with the disease progression during the treatment. It should be noted that change profiles in the IIRPC levels have exhibited two significant characteristics during the entire treatment period: peak and valley (Fig. 3). As exemplified by the protein complex a4 from patient #30 in Fig. 3A, the level of the complex a4 was first increased, maximized, and then returned to the baseline with the disease progression. But for patient #11, as exemplified by the complex a4, its level was decreased first, disappeared, and then returned to the baseline with the disease progression. If the time point at 2-fold increase in the IIRPCs levels for pattern a or b in Fig. 3A or 0.5-fold decrease in the IIRPC levels for pattern a or b in Fig. 3B, the beginning point of the IIRPCs response to the disease progression, which are labeled by T1 in Fig. 3A and T3 in Fig. 3B, respectively, is defined. The time point of the disease progression confirmed by computed tomography or magnetic resonance imaging is labeled by T2 in Fig. 3A and T4 in Fig. 3B, respectively. The time interval between the beginning point of the treatment and T1 in Fig. 3A (or T3 in Fig. 3B) is defined as the time length of humoral immune and inflammation response (TLHIIR), and the time interval between T1 and T2 in Fig. 3A or between T3 and T4 in Fig. 3B is defined as the time length of the disease progression (TLDP). Statistical analysis indicated that the median TLHIIR was 22.0 weeks (95% confidential interval: 16.2 to 33.0), with a lead time of median 11 weeks (TLDP) relative to the PFS (the median PFS, 34.0 weeks, 95% confidential interval: 27.9 to 49.0) obtained by computed tomography or magnetic resonance imaging. The median TLDP was 11.0 weeks (95% confidential interval: 10.6 to 17.2).
3.3. Characteristics of plasma protein complexes of interest
3.5. Changes in the patterns of the IIRPCs during icotinib treatment
Statistical analysis indicated that the level of the TRPC was not associated with the types of the IIRPCs patterns, EGFR mutations, drug dose, smoker, stages, histological characteristics, age, sex, and ECOG (p N 0.05, Table 2), suggesting that the level of the TRPC had a stable expression
As shown in Fig. 3C, as exemplified by the complex a4 from patient #30, the formation of a peak shown in Fig. 3A was due to an increase in the level of the complex a4 during the treatment. As shown in Fig. 3D, exemplified by the complex a4 from patient #11, the formation
4 (12.9) 27 (87.1) 19 (61.3) 12 (38.7) 9 17 25 (80.6) 6 (19.4) 21 (67.7) 10 (32.2) 10 (32.3) 22 (70.9) 9 (29.1) 19 (61.3) 8 (25.8) 4 (12.9)
Fig. 2. Duration of treatment and the association of the PFS with the patterns of the IIRPCs. (A) The treatment duration of 31 advanced non-small-cell cancer patients treated with icotinib. (B) Kaplan–Meier curve of the PFS of patterns a, b, and c of the IIRPCs.
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Fig. 3. Change trends in the levels of the IIRPCs during the entire treatment with icotinib. (A) As exemplified by the protein complex a4 from patient #30, the level of a4 at certain time point was gradually increased, maximized, and then decreased close to the baseline with the disease progression. (B) As exemplified by the protein complex a4 from patient #11, the level of a4 at certain time point was gradually decreased, disappeared, and then increased gradually to the baseline with the disease progression. (C) The pattern of the IIRPCs in the native polyacrylamide gels at the different time points of patient #30 during the treatment. (D) The pattern of the IIRPCs in the native polyacrylamide gels at the different time points of patient #11 during the treatment.
of a valley shown in Fig. 3B was due to a change in the pattern of the IIRPCs (pattern a was changed into pattern d, Fig. 3D), but not due to a decrease in the levels of the IIRPCs during the treatment. It should be noted that pattern a of 7 patients was changed into pattern d and pattern b of 2 patients became pattern e during the entire treatment (Fig. 1), but all patterns were finally returned to their respective original patterns with the disease progression. This is the reason why the valley could be observed during the entire treatment process (Fig. 3B). It is Table 2 Plasma levels of the TRPC in 31 patients with advanced non-small-cell lung cancer. Characteristics Sex Male Female Age (y) ≤60 N60 Pattern Pattern a Pattern b Histology Adenocarcinoma Non-adenocarcinoma Smoking history Never-smoker Current- or ex-smoker EGFR gene EGFR mutations Wild type
Levelsa
p valueb
0.92 ± 0.06 0.93 ± 0.03
0.672
0.92 ± 0.44 0.92 ± 0.05
0.576
0.92 ± 0.47 0.94 ± 0.40
0.286
0.92 ± 0.05 0.95 ± 0.03
0.063
0.92 ± 0.04 0.93 ± 0.06
0.670
0.92 ± 0.04 0.92 ± 0.06
0.888
TRPC, transferrin-related protein complex. a Data are expressed as mean ± SD unless stated otherwise. All statistical tests were two-sided. b Student's t test was performed for the comparison of the TRPC level with sex, age, pattern, histology, smoking history or EGFR gene.
worth noting that, in fact, the levels of the IIRPCs in pattern d or e were also significantly increased (Figs. 1 and 3D), suggesting that humoral immune and inflammation responses were always increased in a personal way due to the disease progression. 4. Discussion Activation of the EGFR pathway has been implicated in NSCLC tumorigenesis, and EGFR has become an important target for the development of personalized therapy. However, acquired drug-resistance always occurred during the treatment. Recently, several molecular biomarkers such as EGFR expression and EGFR mutations have been investigated as potential indicators of the treatment response to EGFRTKIs in NSCLC [6,16,17]. Predicting or monitoring disease progression may influence ultimate therapeutic management of patients with the hope of halting or more importantly preventing progression to severe states. The determination of humoral immune reactivity-related molecules may be very important to evaluate the potential predictive value of humoral immune responses to disease progression. However, a direct link between humoral immune responses and lung cancer has not yet been established in human. Our findings indicate that changes in the levels of the IIRPCs, which included more than ten proteins related to immunity system, inflammation system, and complement system, were closely associated with the disease progression during icotinib treatment, suggesting that the circulating IIRPCs may be a powerful biomarker panels to perform personalized predicting and/or monitoring of the cancer recurrence. This novel type of humoral immune complexes may play multiple important roles in pathogenesis of disease. In addition, it is worth noting that 27 patients (87%) treated with icotinib had their personalized patterns of the IIRPCs and the personalized change trends in the IIRPC levels, suggesting that the IIRPCs can be supramolecular biomarker panels for individually
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monitoring the disease progression. The IIRPCs can be helpful in warning disease progression and in guiding the subsequent therapeutic management because changes in their levels occurred prior to clinical imaging evidences obtained by computed tomography or magnetic resonance imaging. In addition, our results further confirm that the magnitude of humoral immune reactivity was closely correlated with the disease progression, and increased levels of humoral immune reactivity might reflect a loss of tolerance to specific medicine. Our findings have also suggested that humoral immune responses apart from autoantibodies were also associated with the disease progression. So far, no study has investigated that acquired drug-resistance (or disease progression) is associated with humoral IIRPCs in the patients treated with EGFR-TKIs. The limitation of this study is a small number of the patients, not enough to provide a final conclusion. An investigation is also necessary to determine the mechanisms of the interactions of multiple components of the IIRPCs in the disease progression. More importantly, the measurement of the IIRPCs levels is convenient using our optimized native polyacrylamide gel [13]. 5. Conclusions Our results demonstrate that changes in the IIRPC levels occurred with the development of cancer and that monitoring IIRPCs can be helpful in guiding therapeutic management of cancer patients. The detection of the IIRPCs may supplement routine procedures, such as clinical imaging or other biomarkers that have already been adopted in routine clinical practice. Conflicts of interest Drs Z. Li and Y. Wang are listed as the inventors on a patent (WO2012/109977A1) filed in 2012 for Protein Complexes and Profiles Thereof and Uses Thereof in the Diagnosis, Progression Evaluation of Diseases and Potency Evaluation of Compounds. The patent is owned by the Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences. No other potential conflicts of interest were disclosed. Acknowledgments This study was funded by the Research Fund for the Doctoral Program of Higher Education (grant no. 20121106110023) and the
National Natural Science Foundation of China (grant no. 21075137) to Z. Li.
References [1] Siegel R, Naishadham D, Jemal A. Cancer statistics. CA Cancer J Clin 2013;63:11–30. [2] Herbst RS, Heymach JV, Lippman SM. Lung cancer. N Engl J Med 2008;359:1367–80. [3] Pallis AG, Syrigos KN. Epidermal growth factor receptor tyrosine kinase inhibitors in the treatment of NSCLC. Lung Cancer 2013;80:120–30. [4] Lurje G, Lenz HJ. EGFR signaling and drug discovery. Oncology 2009;77:400–10. [5] Tartarone A, Lazzari C, Lerose R, Conteduca V, Improta G, Zupa A, et al. Mechanisms of resistance to EGFR tyrosine kinase inhibitors gefitinib/erlotinib and to ALK inhibitor crizotinib. Lung Cancer 2013;81:328–36. [6] Onitsuka T, Uramoto H, Nose N, Takenoyama M, Hanagiri T, Sugio K, et al. Acquired resistance to gefitinib: the contribution of mechanisms other than the T790M, MET, and HGF status. Lung Cancer 2010;68:198–203. [7] Yu HA, Arcila ME, Rekhtman N, Sima CS, Zakowski MF, Pao W, et al. Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res 2013;19:2240–7. [8] Tan TT, Coussens LM. Humoral immunity, inflammation and cancer. Curr Opin Immunol 2007;19:209–16. [9] Guttman-Yassky E, Mita A, De Jonge M, Matthews L, McCarthy S, Iwata KK, et al. Characterisation of the cutaneous pathology in non-small cell lung cancer (NSCLC) patients treated with the EGFR tyrosine kinase inhibitor erlotinib. Eur J Cancer 2010;46:2010–9. [10] Murtaza M, Dawson SJ, Tsui DW, Gale D, Forshew T, Piskorz AM, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013;497:108–12. [11] Hanash SM, Baik CS, Kallioniemi O. Emerging molecular biomarkers—blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol 2011;8:142–50. [12] Yamaguchi H, Soda H, Nakamura Y, Takasu M, Tomonaga N, Nakano H, et al. Serum levels of surfactant protein D predict the anti-tumor activity of gefitinib in patients with advanced non-small cell lung cancer. Cancer Chemother Pharmacol 2011;67: 331–8. [13] Wang YY, Song GG, Wang YM, Qiu L, Qin XZ, Liu H, et al. Elevated serum levels of circulating immunoinflammation-related protein complexes are associated with cancer. J Proteome Res 2014;13:710–9. [14] Ren GJ, Zhao YY, Zhu YJ, Xiao Y, Xu JS, Shan B, et al. Tumor gene mutations and messenger RNA expression: correlation with clinical response to icotinib hydrochloride in non-small cell lung cancer. Chin Med J (Engl) 2011;124:19–25. [15] Shi Y, Zhang L, Liu X, Zhou C, Zhang S, Wang D, et al. Icotinib versus gefitinib in previously treated advanced non-small-cell lung cancer (ICOGEN): a randomised, double-blind phase 3 non-inferiority trial. Lancet Oncol 2013;14:953–61. [16] O'Byrne K, Paz-Ares L, Pereira JR, von Pawel J, Ramlau R, Storkel S, et al. Epidermal growth factor receptor (EGFR) expression as a predictive biomarker of survival in patients with advanced non-small cell lung cancer (NSCLC) receiving first-line therapy with cetuximab combined with chemotherapy in the FLEX trial. Eur J Cancer 2011;47:S591-S91. [17] Dahabreh IJ, Linardou H, Kosmidis P, Bafaloukos D, Murray S. EGFR gene copy number as a predictive biomarker for patients receiving tyrosine kinase inhibitor treatment: a systematic review and meta-analysis in non-small-cell lung cancer. Ann Oncol 2011;22:545–52.
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Personalized biomarkers to monitor disease progression in advanced non-small-cell lung cancer patients treated with icotinib Gaoguang Song a, Yujie Liu a, Yanying Wang a, Guanjun Ren b, Shuai Guo a, Junling Ren a, Li Zhang b,⁎, Zhili Li a,⁎ a Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China b Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
a r t i c l e
i n f o
Article history: Received 17 September 2014 Received in revised form 8 November 2014 Accepted 10 November 2014 Available online 15 November 2014 Keywords: Immunoinflammation-related protein complexes Non-small-cell lung cancer Time length of humoral immune and inflammatory response Time length of disease progression Progression-free survival
a b s t r a c t Background: Disease-specific humoral immune response-related protein complexes in blood are associated with disease progression. Methods: Thirty-one patients with stage IIIB and IV non-small-cell lung cancer (NSCLC) were administered with oral dose of icotinib hydrochloride (150 mg twice daily or 125 mg 3 times daily) for a 28-continuous-day cycle until diseases progressed or unacceptable toxicity occurred. The levels of immunoinflammation-related protein complexes (IIRPCs) in a series of plasma samples from 31 NSCLC patients treated with icotinib hydrochloride were determined by an optimized native polyacrylamide gel electrophoresis. Results: Three characteristic patterns of the IIRPCs, named as patterns a, b, and c, respectively, were detected in plasma samples from 31 patients. Prior to the treatment, there were 18 patients in pattern a consisting of 5 IIRPCs, 9 in pattern b consisting of six IIRPCs, and 4 in pattern c without the IIRPCs. The levels of the IIRPCs in 27 patients were quantified. Our results indicate that the time length of humoral immune and inflammation response (TLHIIR) was closely associated with disease progression, and the median TLHIIR was 22.0 weeks, 95% confidence interval: 16.2 to 33.0 weeks, with a lead time of median 11 weeks relative to clinical imaging evidence confirmed by computed tomography or magnetic resonance imaging (the median progression-free survival, 34.0 weeks, 95% confidence interval: 27.9 to 49.0 weeks). Conclusions: The complex relationships between humoral immune response, acquired resistance, and disease progression existed. Personalized IIRPCs could be indicators to monitor the disease progression. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Lung cancer is a leading cause of cancer-related mortality worldwide [1], which is mainly classified into non-small-cell lung cancer (NSCLC, about 85% of lung cancer) and small cell lung cancer (about 15%) [2]. Treatment plans have been prescribed to patients based on clinicopathological criteria. In recent years, advances in personalized lung cancer treatment have been made to targeting epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors (TKIs) (e.g., erlotinib, gefitinib, and icotinib) in NSCLC [3]. Unfortunately, only a small number of the patients with advanced lung cancer responded to EGFR-TKI therapy, and finally also acquired drug-resistance [4]. Acquired drug-resistance Abbreviations: NSCLC, non-small-cell lung cancer; IIRPCs, immunoinflammationrelated protein complexes; TLHIIR, time length of humoral immune and inflammation response; TLDP, time length of the disease progression; EGFR, epidermal growth factor receptor; TKI, tyrosine kinase inhibitor. ⁎ Corresponding authors at: Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, 5 Dongdan San Tiao, Beijing 100005, China. Tel./fax: +86 10 69156479. E-mail address: [email protected] (Z. Li).
http://dx.doi.org/10.1016/j.cca.2014.11.010 0009-8981/© 2014 Elsevier B.V. All rights reserved.
to EGFR-TKI therapy was also associated with T790M mutation in exon 20 of EGFR and overexpression of hepatocyte growth factor [5–7]. Previous study on disease progression has revealed that inflammation regulated by immunoglobulin and immune complexes might be a functionally significant factor of cancer promotion and progression [8]. Previous study has also indicated that the development of EGFRTKI-induced skin inflammation was associated with prolonged survival [9]. However, the mechanisms of these processes in the cancer development have not yet been fully understood. Recently, genomic alterations in solid cancers have been characterized by sequencing cell-free DNA in the blood of cancer patients [10], but it is impossible to use these assays to monitor each individual's disease progression due to their high cost. Clinical challenges in the treatment outcome of the patients with advanced lung cancer may require the determination of serological treatment response-related biomarkers to monitor disease progression and/or acquired drug-resistance and to improve therapeutic outcome. Serological biomarkers may be the products of cancer cells, tumor microenvironment, and host response, along with their dynamic interactions [11]. Therefore, it is important to develop less invasive methods to monitor the disease progression, instead of detecting tumor cells or tissue DNA. It has been observed that, in the advanced NSCLC patients
G. Song et al. / Clinica Chimica Acta 440 (2015) 44–48
45
treated with gefitinib, serum surfactant protein D may be a new surrogate marker for predicting the response to gefitinib [12]. In addition, biomarkers should be of personal, less invasive, sensitive, and economic features, along with higher reproducibility. Our previous study has provided insight into the association of the levels and patterns of circulating immunoinflammation-related protein complexes (IIRPCs), which include immune-related proteins, inflammation-related proteins, and complement-related proteins [13], with cancers. 2. Materials and methods 2.1. Patients From August 2007 to March 2010, 31 patients with advanced NSCLC were enrolled in stage I and II clinical trials of icotinib hydrochloride on the basis of the eligibility criteria as previously described (BPI-2009H) [14,15]. Briefly, eligible patients were required to have histologically or cytologically confirmed stage IIIB or IV NSCLC and had received chemotherapy based on the American Joint Committee on Cancer system, 6th edition at the tumor-node-metastasis classification of staging system. Measurable tumors with the response evaluation criteria in solid tumors (RECIST, version 1.0) were designed as 0 or 1. The patients had disease progression after 1 or 2 platinum-based chemotherapy regimen, and there was no chemotherapy for N 3 weeks. In addition, the patients with the following clinical symptoms, such as interstitial pneumonia or pulmonary fibrosis, severe infection, intestinal paralysis or obstruction, women with pregnancy or lactation, and other serious medical conditions, were excluded. Radiological assessment of tumor size was performed once every 8 weeks by computed tomography or magnetic resonance imaging according to the RECIST. All participants have provided written informed consent in the study. The study was proved by the Ethics Committee of Peking Union Medical College Hospital and the Ethics Committee of Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences. All experiments were performed in accordance with relevant guidelines and regulations.
Fig. 1. Representative patterns of plasma IIRPCs. The patterns of the IIRPCs are classified into patterns a, b, c, d, and e, respectively.
intolerable toxicity. The time length of humoral immune and inflammation response (TLHIIR) is the time interval between the beginning of icotinib treatment and the time point at the 2-fold increase (or 0.5-fold decrease) in the IIRPC levels relative to their individual baseline. A p value of less than 0.05 was considered to be statistically significant. All statistical analyses were performed using SPSS software (version 16.0, SPSS Inc.).
2.2. Icotinib treatment and sample collection 3. Results The patients took oral icotinib at a dose of 150 mg twice daily or 125 mg 3 times daily for a 28-continuous-day cycle followed by the intermission of 3 days until diseases progressed, unacceptable toxicity occurred, or patients refused further treatment. A series of plasma samples of each patient were collected before the treatment as the baseline and during the treatment after an overnight fasting period of about 10 h. 2.3. Quantification of plasma IIRPCs Plasma protein complexes were isolated as our own previous study [13]. Briefly, native polyacrylamide gel electrophoresis with a gradient from 4 to 10% was used to separate plasma IIRPCs. Each run included nine test samples and one quality control sample in a single native polyacrylamide gel. The quality control sample was a mixture of 5 random patient plasma. Representative patterns of plasma IIRPCs are showed in Fig. 1. The gel bands labeled by a1, a2, a3, a4, a5, b1, b2, b3, b4, b5, b6, d1, d2, d3, e1, e2, and e3, correspond to the IIRPCs and the band labeled by the TRPC corresponds to transferrin-related protein complex. The levels of these protein complexes were quantified and their components were also identified as described previously [13]. 2.4. Statistical analysis Kaplan–Meier method was performed to determine survival. PFS is defined as the time interval between the beginning of icotinib treatment and the earliest occurrence of disease progression detected by computed tomography or magnetic resonance imaging or apparently
3.1. Patients Thirty-one advanced NSCLC patients were enrolled in this study, and their clinicopathological characteristics are listed in Table 1. The mean age was 56.8 y (range 41–71 y). Eleven (35.5%) patients were male, 27 patients (87.1%) showed stage IV, nineteen patients (61.3%) had ECOG performance status of 0, 25 (80.6%) had adenocarcinoma, nine patients had EGFR mutations, 22 patients (70.9%) were neversmokers, 10 patients (32.3%) had radiotherapy and the median PFS was 34.0 weeks (95% confidential interval: 27.9 to 49.0 weeks) based on the determination of computed tomography or magnetic resonance imaging. After 2-month icotinib treatment, the response to the initial icotinib treatment was complete response in one patient, partial response in eight patients, stable disease in nineteen patients, and disease progression in 3 patients (Fig. 2A). No severe toxicity was observed and no treatment-related death occurred in this study. 3.2. Distribution of plasma protein complexes of interest During icotinib treatment, a series of plasma samples from 31 advanced NSCLC patients were collected, and plasma protein complexes were isolated by the native polyacrylamide gel. As shown in Fig. 1, 3 patterns of plasma IIRPCs in the plasma samples collected before the treatment are observed, and 19, 8, and 4 patients were assigned as patterns (or groups) a, b and c, respectively (Table 1). For pattern a, 5 diseasespecific IIRPCs were detected and labeled by a1, a2, a3, a4, and a5, respectively. For pattern b, 6 disease-specific IIRPCs were detected and
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G. Song et al. / Clinica Chimica Acta 440 (2015) 44–48 Table 1 Baseline characteristics of 31 patients with non-small-cell lung cancer treated with icotinib. Characteristic
Value (%)
Male, no. (%) Age, y Mean Range Stage, no. (%) IIIB IV ECOG performance status, no.(%) 0 1 EGFR mutations Wild type Histology, no. (%) Adenocarcinoma Non-adenocarcinoma Previous chemotherapies, no. (%) 1 ≥2 Previous radiotherapy, no. (%) Smoking history, no. (%) Never-smoker Current- or ex-smoker Patterns of the IIRPCs, no. (%) Pattern a Pattern b Pattern c
11 (35.5) 56.8 41–71
during icotinib treatment in all patient plasmas. These results indicate that the TRPC should be an internal reference for quantifying the IIRPCs, which is consistent with our own previous study [13]. Statistical analysis also indicated that the patterns of the IIRPCs in different patients were not associated with PFS (p N 0.05, Fig. 2B). 3.4. Association of the TLHIIR with changes in the IIRPC levels
labeled by b1, b2, b3, b4, b5, and b6, respectively. But for pattern c, no disease-specific IIRPCs was observed. As shown in Fig. 1, one common protein complex in five patterns (a, b, c, d, and e), with the highest intensity in all plasma samples, is the TRPC. Their components were identified using mass spectrometry, and there are immunoglobulin G1, immunoglobulin A1, haptoglobin, complement component 3, complement component 4A, complement component 5, complement component 7, complement factor H, transferrin, and apolipoprotein A–I.
Although the levels of the IIRPCs in individual patients with pattern a or b had different baselines before the icotinib treatment, change trends in their levels were significantly associated with the disease progression during the treatment. It should be noted that change profiles in the IIRPC levels have exhibited two significant characteristics during the entire treatment period: peak and valley (Fig. 3). As exemplified by the protein complex a4 from patient #30 in Fig. 3A, the level of the complex a4 was first increased, maximized, and then returned to the baseline with the disease progression. But for patient #11, as exemplified by the complex a4, its level was decreased first, disappeared, and then returned to the baseline with the disease progression. If the time point at 2-fold increase in the IIRPCs levels for pattern a or b in Fig. 3A or 0.5-fold decrease in the IIRPC levels for pattern a or b in Fig. 3B, the beginning point of the IIRPCs response to the disease progression, which are labeled by T1 in Fig. 3A and T3 in Fig. 3B, respectively, is defined. The time point of the disease progression confirmed by computed tomography or magnetic resonance imaging is labeled by T2 in Fig. 3A and T4 in Fig. 3B, respectively. The time interval between the beginning point of the treatment and T1 in Fig. 3A (or T3 in Fig. 3B) is defined as the time length of humoral immune and inflammation response (TLHIIR), and the time interval between T1 and T2 in Fig. 3A or between T3 and T4 in Fig. 3B is defined as the time length of the disease progression (TLDP). Statistical analysis indicated that the median TLHIIR was 22.0 weeks (95% confidential interval: 16.2 to 33.0), with a lead time of median 11 weeks (TLDP) relative to the PFS (the median PFS, 34.0 weeks, 95% confidential interval: 27.9 to 49.0) obtained by computed tomography or magnetic resonance imaging. The median TLDP was 11.0 weeks (95% confidential interval: 10.6 to 17.2).
3.3. Characteristics of plasma protein complexes of interest
3.5. Changes in the patterns of the IIRPCs during icotinib treatment
Statistical analysis indicated that the level of the TRPC was not associated with the types of the IIRPCs patterns, EGFR mutations, drug dose, smoker, stages, histological characteristics, age, sex, and ECOG (p N 0.05, Table 2), suggesting that the level of the TRPC had a stable expression
As shown in Fig. 3C, as exemplified by the complex a4 from patient #30, the formation of a peak shown in Fig. 3A was due to an increase in the level of the complex a4 during the treatment. As shown in Fig. 3D, exemplified by the complex a4 from patient #11, the formation
4 (12.9) 27 (87.1) 19 (61.3) 12 (38.7) 9 17 25 (80.6) 6 (19.4) 21 (67.7) 10 (32.2) 10 (32.3) 22 (70.9) 9 (29.1) 19 (61.3) 8 (25.8) 4 (12.9)
Fig. 2. Duration of treatment and the association of the PFS with the patterns of the IIRPCs. (A) The treatment duration of 31 advanced non-small-cell cancer patients treated with icotinib. (B) Kaplan–Meier curve of the PFS of patterns a, b, and c of the IIRPCs.
G. Song et al. / Clinica Chimica Acta 440 (2015) 44–48
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Fig. 3. Change trends in the levels of the IIRPCs during the entire treatment with icotinib. (A) As exemplified by the protein complex a4 from patient #30, the level of a4 at certain time point was gradually increased, maximized, and then decreased close to the baseline with the disease progression. (B) As exemplified by the protein complex a4 from patient #11, the level of a4 at certain time point was gradually decreased, disappeared, and then increased gradually to the baseline with the disease progression. (C) The pattern of the IIRPCs in the native polyacrylamide gels at the different time points of patient #30 during the treatment. (D) The pattern of the IIRPCs in the native polyacrylamide gels at the different time points of patient #11 during the treatment.
of a valley shown in Fig. 3B was due to a change in the pattern of the IIRPCs (pattern a was changed into pattern d, Fig. 3D), but not due to a decrease in the levels of the IIRPCs during the treatment. It should be noted that pattern a of 7 patients was changed into pattern d and pattern b of 2 patients became pattern e during the entire treatment (Fig. 1), but all patterns were finally returned to their respective original patterns with the disease progression. This is the reason why the valley could be observed during the entire treatment process (Fig. 3B). It is Table 2 Plasma levels of the TRPC in 31 patients with advanced non-small-cell lung cancer. Characteristics Sex Male Female Age (y) ≤60 N60 Pattern Pattern a Pattern b Histology Adenocarcinoma Non-adenocarcinoma Smoking history Never-smoker Current- or ex-smoker EGFR gene EGFR mutations Wild type
Levelsa
p valueb
0.92 ± 0.06 0.93 ± 0.03
0.672
0.92 ± 0.44 0.92 ± 0.05
0.576
0.92 ± 0.47 0.94 ± 0.40
0.286
0.92 ± 0.05 0.95 ± 0.03
0.063
0.92 ± 0.04 0.93 ± 0.06
0.670
0.92 ± 0.04 0.92 ± 0.06
0.888
TRPC, transferrin-related protein complex. a Data are expressed as mean ± SD unless stated otherwise. All statistical tests were two-sided. b Student's t test was performed for the comparison of the TRPC level with sex, age, pattern, histology, smoking history or EGFR gene.
worth noting that, in fact, the levels of the IIRPCs in pattern d or e were also significantly increased (Figs. 1 and 3D), suggesting that humoral immune and inflammation responses were always increased in a personal way due to the disease progression. 4. Discussion Activation of the EGFR pathway has been implicated in NSCLC tumorigenesis, and EGFR has become an important target for the development of personalized therapy. However, acquired drug-resistance always occurred during the treatment. Recently, several molecular biomarkers such as EGFR expression and EGFR mutations have been investigated as potential indicators of the treatment response to EGFRTKIs in NSCLC [6,16,17]. Predicting or monitoring disease progression may influence ultimate therapeutic management of patients with the hope of halting or more importantly preventing progression to severe states. The determination of humoral immune reactivity-related molecules may be very important to evaluate the potential predictive value of humoral immune responses to disease progression. However, a direct link between humoral immune responses and lung cancer has not yet been established in human. Our findings indicate that changes in the levels of the IIRPCs, which included more than ten proteins related to immunity system, inflammation system, and complement system, were closely associated with the disease progression during icotinib treatment, suggesting that the circulating IIRPCs may be a powerful biomarker panels to perform personalized predicting and/or monitoring of the cancer recurrence. This novel type of humoral immune complexes may play multiple important roles in pathogenesis of disease. In addition, it is worth noting that 27 patients (87%) treated with icotinib had their personalized patterns of the IIRPCs and the personalized change trends in the IIRPC levels, suggesting that the IIRPCs can be supramolecular biomarker panels for individually
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monitoring the disease progression. The IIRPCs can be helpful in warning disease progression and in guiding the subsequent therapeutic management because changes in their levels occurred prior to clinical imaging evidences obtained by computed tomography or magnetic resonance imaging. In addition, our results further confirm that the magnitude of humoral immune reactivity was closely correlated with the disease progression, and increased levels of humoral immune reactivity might reflect a loss of tolerance to specific medicine. Our findings have also suggested that humoral immune responses apart from autoantibodies were also associated with the disease progression. So far, no study has investigated that acquired drug-resistance (or disease progression) is associated with humoral IIRPCs in the patients treated with EGFR-TKIs. The limitation of this study is a small number of the patients, not enough to provide a final conclusion. An investigation is also necessary to determine the mechanisms of the interactions of multiple components of the IIRPCs in the disease progression. More importantly, the measurement of the IIRPCs levels is convenient using our optimized native polyacrylamide gel [13]. 5. Conclusions Our results demonstrate that changes in the IIRPC levels occurred with the development of cancer and that monitoring IIRPCs can be helpful in guiding therapeutic management of cancer patients. The detection of the IIRPCs may supplement routine procedures, such as clinical imaging or other biomarkers that have already been adopted in routine clinical practice. Conflicts of interest Drs Z. Li and Y. Wang are listed as the inventors on a patent (WO2012/109977A1) filed in 2012 for Protein Complexes and Profiles Thereof and Uses Thereof in the Diagnosis, Progression Evaluation of Diseases and Potency Evaluation of Compounds. The patent is owned by the Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences. No other potential conflicts of interest were disclosed. Acknowledgments This study was funded by the Research Fund for the Doctoral Program of Higher Education (grant no. 20121106110023) and the
National Natural Science Foundation of China (grant no. 21075137) to Z. Li.
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