Changes in Plasma Mass-Spectral Profile in Course of Treatment of Non-small Cell Lung Cancer Patients with Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors

Increased c‑SRC expression is involved in acquired resistance to lenvatinib in hepatocellular carcinoma

Lenvatinib, a multi-kinase inhibitor, serves a crucial role in the treatment of unresectable hepatocellular carcinoma (HCC). However, >50% of patients receiving lenvatinib therapy experience tumor growth or metastasis within 1 year, highlighting the need to address acquired resistance as a critical clinical challenge. To elucidate the factors associated with acquired resistance to lenvatinib, a lenvatinib-resistant HCC cell line (JHH-7_LR) was established by exposing a lenvatinib-sensitive HCC cell line, JHH-7, to lenvatinib. The changes in protein expression associated with the development of resistance were analyzed using a proteomic approach, detecting 1,321 proteins and significant changes in the expression of 267 proteins. Using Ingenuity Pathway Analysis bioinformatics software, it was revealed that the activity of multiple signaling pathways varied alongside the changes in expression of these proteins, and c-SRC was identified as a protein involved in a number of these signaling pathways, with its activity varying markedly upon the acquisition of resistance. When co-administering dasatinib, a c-SRC inhibitor, the partial restoration of lenvatinib sensitivity in the JHH-7_LR cell line was observed. The present study demonstrated that increased c-SRC expression was partially associated with HCC resistance to lenvatinib, suggesting that c-SRC inhibition could reduce the resistance of HCC to lenvatinib.

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer

The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment.

The Role of Genomics and Proteomics in Lung Cancer Early Detection and Treatment

Lung cancer is the leading cause of cancer-related death worldwide, with non-small-cell lung cancer (NSCLC) being the primary type. Unfortunately, it is often diagnosed at advanced stages, when therapy leaves patients with a dismal prognosis. Despite the advances in genomics and proteomics in the past decade, leading to progress in developing tools for early diagnosis, targeted therapies have shown promising results; however, the 5-year survival of NSCLC patients is only about 15%. Low-dose computed tomography or chest X-ray are the main types of screening tools. Lung cancer patients without specific, actionable mutations are currently treated with conventional therapies, such as platinum-based chemotherapy; however, resistances and relapses often occur in these patients. More noninvasive, inexpensive, and safer diagnostic methods based on novel biomarkers for NSCLC are of paramount importance. In the current review, we summarize genomic and proteomic biomarkers utilized for the early detection and treatment of NSCLC. We further discuss future opportunities to improve biomarkers for early detection and the effective treatment of NSCLC.

Real-world performance of blood-based proteomic profiling in first-line immunotherapy treatment in advanced stage non-small cell lung cancer

Purpose

Immune checkpoint inhibition (ICI) therapy has improved patient outcomes in advanced non-small cell lung cancer (NSCLC), but better biomarkers are needed. A clinically validated, blood-based proteomic test, or host immune classifier (HIC), was assessed for its ability to predict ICI therapy outcomes in this real-world, prospectively designed, observational study.

Materials and methods

The prospectively designed, observational registry study INSIGHT (Clinical Effectiveness Assessment of VeriStrat® Testing and Validation of Immunotherapy Tests in NSCLC Subjects) (NCT03289780) includes 35 US sites having enrolled over 3570 NSCLC patients at any stage and line of therapy. After enrolment and prior to therapy initiation, all patients are tested and designated HIC-Hot (HIC-H) or HIC-Cold (HIC-C). A prespecified interim analysis was performed after 1-year follow-up with the first 2000 enrolled patients. We report the overall survival (OS) of patients with advanced stage (IIIB and IV) NSCLC treated in the first-line (ICI-containing therapies n=284; all first-line therapies n=877), by treatment type and in HIC-defined subgroups.

Results

OS for HIC-H patients was longer than OS for HIC-C patients across treatment regimens, including ICI. For patients treated with all ICI regimens, median OS was not reached (95% CI 15.4 to undefined months) for HIC-H (n=196) vs 5.0 months (95% CI 2.9 to 6.4) for HIC-C patients (n=88); HR=0.38 (95% CI 0.27 to 0.53), p<0.0001. For ICI monotherapy, OS was 16.8 vs 2.8 months (HR=0.36 (95% CI 0.22 to 0.58), p<0.0001) and for ICI with chemotherapy OS was unreached vs 6.4 months (HR=0.41 (95% CI 0.26 to 0.67), p=0.0003). HIC results were independent of programmed death ligand 1 (PD-L1). In a subgroup with PD-L1 ≥50% and performance status 0–1, HIC stratified survival significantly for ICI monotherapy but not ICI with chemotherapy.

Conclusion

Blood-based HIC proteomic testing provides clinically meaningful information for immunotherapy treatment decision in NSCLC independent of PD-L1. The data suggest that HIC-C patients should not be treated with ICI alone regardless of their PD-L1 expression.

Mass spectrometry-based serum proteomic signature as a potential biomarker for survival in patients with non-small cell lung cancer receiving immunotherapy

Background

VeriStrat test is a serum assay which uses a mass spectrometry (MS)-based proteomic signature derived from machine learning. It is currently used as a prognostic marker for patients with non-small cell lung cancer (NSCLC) receiving chemotherapy. However, little is known about its role for NSCLC patients receiving immune checkpoint inhibitors (ICIs).

Methods

This is a retrospective study that includes 47 patients with advanced stage NSCLC without an activating EGFR mutation, who underwent the VeriStrat test from 2016 to 2018. Spectra from blood samples were evaluated to assign patients into the VeriStrat ‘Good’ (VS-G) or VeriStrat ‘Poor’ (VS-P) risk group. The clinical outcomes of 32 patients who received programmed cell death 1 (PD-1) inhibitors nivolumab or pembrolizumab were analyzed by VeriStrat status.

Results

The VS-G group demonstrated significantly higher progression-free survival (PFS) and overall survival (OS) compared to the VS-P group among overall NSCLC patients regardless of treatment (median PFS of 7.1 vs. 4.2 months, P=0.013, and median OS, not reached vs. 17.2 months, P=0.012). Among NSCLC patients treated with ICIs, VS-G classification was associated with significantly increased PFS in comparison to VS-P classification (median PFS of 6.2 vs. 3.0 months, P=0.012), while the differences in OS trended towards significance (median OS, not reached vs. 16.5 months P=0.076). Multivariate analysis showed that the VeriStrat status was significantly correlated with PFS and OS in NSCLC patients treated with ICIs (P=0.017, P=0.034, respectively).

Conclusions

MS-based serum proteomic signature has potential as a biomarker for survival outcome in NSCLC patients receiving immunotherapy.

Prognostic performance of proteomic testing in advanced non-small cell lung cancer: a systematic literature review and meta-analysis

OBJECTIVE

Timely assessment of patient-specific prognosis is critical to oncology care involving a shared decision-making approach, but clinical prognostic factors traditionally used in NSCLC have limitations. We examine a proteomic test to address these limitations.

METHODS

This study examines the prognostic performance of the VeriStrat blood-based proteomic test that measures the inflammatory disease state of patients with advanced NSCLC. A systematic literature review (SLR) was performed, yielding cohorts in which the hazard ratio (HR) was reported for overall survival (OS) of patients with VeriStrat Poor (VSPoor) test results versus VeriStrat Good (VSGood). A study-level meta-analysis of OS HRs was performed in subgroups defined by lines of therapy and treatment regimens.

RESULTS

Twenty-four cohorts met SLR criteria. Meta-analyses in five subgroups (first-line platinum-based chemotherapy, second-line single-agent chemotherapy, first-line EGFR-tyrosine kinase inhibitor (TKI) therapy, and second- and higher-line TKI therapy, and best supportive care) resulted in statistically significant (p ≤ .001) summary effect sizes for OS HRs of 0.42, 0.54, 0.41, 0.52, and 0.50, respectively, indicating increased OS by about two-fold for patients who test VSGood. No significant heterogeneity was seen in any subgroup (p > .05).

CONCLUSIONS

Advanced NSCLC patients classified VSGood have significantly longer OS than those classified VSPoor. The summary effect size for OS HRs around 0.4-0.5 indicates that the expected median survival of those with a VSGood classification is approximately 2-2.5 times as long as those with VSPoor. The robust prognostic performance of the VeriStrat test across various lines of therapy and treatment regimens has clinical implications for treatment shared decision-making and potential for novel treatment strategies.

The clinical role of VeriStrat testing in patients with advanced non-small cell lung cancer considered unfit for first-line platinum-based chemotherapy

Purpose

We previously demonstrated that the median survival of patients with poor prognosis non–small cell lung cancer (NSCLC) considered unfit for first-line platinum chemotherapy was <4 months. We evaluated whether VeriStrat could be used as a prognostic or predictive biomarker in this population.

Experimental design

We conducted a randomised double-blind trial among patients with untreated advanced NSCLC considered unfit for platinum chemotherapy because of poor performance status (PS) or multiple comorbidities. All patients received active supportive care (ASC) and were treated with either oral erlotinib or placebo daily. Five hundred twenty-seven patients had plasma samples for VeriStrat classification: good (VeriStrat Good [VSG]) or poor (VeriStrat Poor [VSP]). Main end-point was overall survival.

Results

Fifty-five percent patients had VSG, and 83% had Eastern Cooperative Oncology Group (ECOG) 2–3 at baseline. VeriStrat was strongly associated with survival. Among patients managed with ASC only, the adjusted hazard ratio (HR) was 0.54 (p < 0.001) for VSG versus VSP. The association was consistent across patient factors: HR = 0.25 (p = 0.004) and HR = 0.56 (p < 0.001) for ECOG 0–1 and 2–3, respectively, HR = 0.49 (0070 < 0.001) for age≥75 years and HR = 0.59 (p = 0.007) for stage IV. Several ECOG 2–3 patients had long survival: 2-year survival was 8% for VSG patients who had ASC, compared with 0% for VSP. VeriStrat status did not predict benefit from erlotinib treatment because the HRs for erlotinib versus placebo were similar between VSG and VSP patients.

Conclusions

VeriStrat was not a predictive marker for survival when considering first-line erlotinib for patients with NSCLC who had poor PS and were not recommended for platinum doublet therapies. However, VeriStrat was an independent prognostic marker of survival. It represents an objective measurement that could be considered alongside other patient factors to provide a more refined assessment of prognosis for this particular patient group. VSG patients could be selected for treatment trials because of better survival, while VSP patients can continue to be treated conservatively or offered trials of less toxic agents.

Trial registration ISRCTN Number

ISRCTN02370070.

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83% advanced NSCLC patients unfit for chemotherapy have poor performance status.

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VeriStrat (proteomic blood test) is an independent prognostic marker for survival.

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Patients classified as VeriStrat Good were less likely to die than those classified as VeriStrat Poor.

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VeriStrat can refine patient prognosis in order to alter treatment management.

A Phase II Open Label Study of Everolimus in Combination With Endocrine Therapy in Resistant Hormone Receptor-Positive HER2-Negative Advanced Breast Cancer

BACKGROUND

Therapies targeting estrogen receptor signaling are standard for patients with hormone receptor (HR)-positive (HR⁺) metastatic breast cancer (MBC). Dysregulation of the phosphoinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway is associated with treatment resistance. Addition of the mTOR inhibitor, everolimus, to exemestane doubled progression-free survival (PFS) in HR⁺/HER2^- MBC patients whose disease had previously progressed during endocrine therapy. In this phase II study, we used everolimus in addition to the most recent endocrine therapy during which a patient's disease progressed, in an attempt to restore and extend the benefit of the antiestrogen therapy in patients with HR⁺/HER2^- MBC.

PATIENTS AND METHODS

Patients with HR⁺ MBC who progressed on antiestrogen therapy received everolimus (10 mg orally daily) in combination with the antiestrogen therapy most recently administered. Treatment was administered in 4-week cycles and continued until disease progression or unacceptable toxicity. Blood and archival tumor specimens were collected for VeriStrat (Biodesix, Inc) and Foundation One (Foundation Medicine) assays, respectively. Accrual of 42 evaluable patients allowed detection of improvement in median PFS from 2.8 months (expected with hormonal treatment alone) to 5 months (power 80%, α = 5%).

RESULTS

Forty-seven patients were enrolled and treated. After a median follow-up of 22.2 months, median PFS was 6.6 months. Secondary efficacy end points included: overall response rate, 6%; clinical benefit rate, 40%; and median overall survival, 21.1 months. No unexpected toxicity was observed. Efficacy could not be correlated with PI3K/AKT/mTOR alterations or VeriStrat (Biodesix, Inc) prognostic signatures.

CONCLUSION

After progression during antiestrogen therapy, the addition of everolimus, without changing the hormonal therapy, resulted in a median PFS of 6.6 months, suggesting efficacy in patients with HR⁺/HER2^- MBC.

L-Lactate dehydrogenase B may be a predictive marker for sensitivity to anti-EGFR monoclonal antibodies in colorectal cancer cell lines

Recently, proteins derived from cancer cells have been widely investigated as biomarkers for predicting the efficacy of chemotherapy. In this study, to identify a sensitive biomarker for the efficacy of anti-epidermal growth factor receptor monoclonal antibodies (anti-EGFR mAbs), proteins derived from 6 colorectal cancer (CRC) cell lines with different sensitivities to cetuximab, an anti-EGFR mAb, were analyzed. Cytoplasmic and membrane proteins extracted from each CRC cell line were digested using trypsin and analyzed comprehensively using mass spectrometry. As a result, 148 and 146 peaks from cytoplasmic proteins and 363 and 267 peaks from membrane proteins were extracted as specific peaks for cetuximab-resistant and -sensitive CRC cell lines, respectively. By analyzing the proteins identified from the peptide peaks, cytoplasmic L-lactate dehydrogenase B (LDHB) was detected as a marker of cetuximab sensitivity, and it was confirmed that LDHB expression was increased in cetuximab-resistant CRC cell lines. Furthermore, LDHB expression levels were significantly upregulated with the acquisition of resistance to cetuximab in cetuximab-sensitive CRC cell lines. In conclusion, LDHB was identified as an important factor affecting cetuximab sensitivity using comprehensive proteome analysis for the first time.

Serum peptide expression and treatment responses in patients with advanced non-small-cell lung cancer

Epidermal growth factor receptor (EGFR) mutation is an important predictor for response to personalized treatments of patients with advanced non-small-cell lung cancer (NSCLC). However its usage is limited due to the difficult of obtaining tissue specimens. A novel prediction system using matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been reported to be a perspective tool in European countries to identify patients who are likely to benefit from EGFR tyrosine kinase inhibitor (TKI) treatment. In the present study, MALDI-TOF MS was used on pretreatment serum samples of patients with advanced non-small-cell lung cancer to discriminate the spectra between disease control and disease progression groups in one cohort of Chinese patients. The candidate features for classification were subsequently validated in a blinded fashion in another set of patients. The correlation between plasma EGFR mutation status and the intensities of representative spectra for classification was evaluated. A total of 103 patients that were treated with EGFR-TKIs were included. It was determined that 8 polypeptides peaks were significant different between the disease control and disease progression group. A total of 6 polypeptides were established in the classification algorithm. The sensitivity of the algorithm to predict treatment responses was 76.2% (16/21) and the specificity was 81.8% (18/22). The accuracy rate of the algorithm was 79.1% (34/43). A total of 3 polypeptides were significantly correlated with EGFR mutations (P=0.04, P=0.03 and P=0.04, respectively). The present study confirmed that MALDI-TOF MS analysis can be used to predict responses to EGFR-TKI treatment of the Asian population where the EGFR mutation status differs from the European population. Furthermore, the expression intensities of the three polypeptides in the classification model were associated with EGFR mutation.

Mass spectrometry-based serum peptidome profiling accurately and reliably predicts outcomes of pemetrexed plus platinum chemotherapy in patients with advanced lung adenocarcinoma

BACKGROUND

Although pemetrexed plus cis/carboplatin has become the most effective chemotherapy regimen for patients with advanced lung adenocarcinoma, predictive biomarkers are not yet available, and new tools to identify chemosensitive patients who would likely benefit from this treatment are desperately needed. In this study, we constructed and validated predictive peptide models using the serum peptidome profiles of two datasets.

METHODS

One hundred eighty-three patients treated with first-line platinum-based pemetrexed treatment for advanced lung adenocarcinoma were retrospectively enrolled and randomized into the training (n = 92) or validation (n = 91) set, and pre-treatment serum samples were analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinProTools software. Serum peptidome profiles from the training set were used to identify potential predictive peptide biomarkers and construct a predictive peptide model for accurate group discrimination; which was then used to classify validation samples into "good" and "poor" outcome groups. The clinical outcomes of objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were analyzed based on the classification result.

RESULTS

Eight potential peptide biomarkers were identified. A predictive peptide model based on four distinct m/z features (2,142.12, 3,316.19, 4,281.94, and 6,624.02 Da) was developed based on the clinical outcomes of training set patients after first-line pemetrexed plus platinum treatment. In the validation set, the good group had significantly higher ORR (49.1% vs. 8.3%, P <0.001) and DCR (96.4% vs. 47.2%, P <0.001), and longer PFS (7.3 months vs. 2.7 months, P <0.001) vs. the poor group. However, the model did not predict OS (13.6 months vs. 12.7 months, P = 0.0675).

CONCLUSION

Our predictive peptide model could predict pemetrexed plus platinum treatment outcomes in patients with advanced lung adenocarcinoma and might thus facilitate appropriate patient selection. Further studies are needed to confirm these findings.

Impact of a multivariate serum-based proteomic test on physician treatment recommendations for advanced non-small-cell lung cancer

OBJECTIVE

The VeriStrat ¹ (VS) test is intended to help guide treatment decisions for patients with advanced non-small-cell lung cancer (NSCLC) without an EGFR-sensitizing mutation, classifying patients into two categories. Patients classified as VSGood have a favorable prognosis and significant clinical response to EGFR tyrosine kinase inhibitors (TKIs). Patients classified as VSPoor have a less favorable prognosis and exhibit no significant response to EGFR-TKIs. The objective of this paper is to assess the real-world impact of VS test results on physicians' treatment recommendations including referrals for best supportive care (BSC).

METHODS

Between 1 January 2012 and 1 November 2016, physician respondents were asked to complete standardized questionnaires before and after receiving VS results in patients meeting criteria for the intended use of the VS test. This study evaluated three endpoints: whether physicians followed VS test results in making treatment recommendations, the extent to which tests results changed these treatment recommendations, and the patterns of care subsequent to VS testing.

RESULTS

Of the tests ordered by 989 physicians, 2494 VS tests had completed treatment recommendation questionnaires both prior to and after testing. Prior to VS testing, physicians were considering treatment with EGFR-TKIs for 2250 patients (90%). The VS test classified 1950 patients as VSGood and 544 patients as VSPoor. For patients classified as VSPoor, physicians recommended BSC for 25% of patients and standard systemic treatments such as chemotherapies for 65% of patients. Consistent with previous publications, physicians recommended EGFR-TKI therapy for only 10% of VSPoor patients but for 89% of VSGood patients. Overall, physician's treatment recommendations were consistent with test results in 98% of cases. Availability of test results decreased ineffective treatment recommendations by 89% for VSPoor patients.

CONCLUSIONS

Among physicians ordering VS, the test significantly influenced treatment recommendations for patients with NSCLC, reducing ineffective and expensive treatment at the end of life.

Biology and patterns of response to EGFR-inhibition in squamous cell cancers of the lung and head & neck

The identification of common molecular aberrations that drive cancer progression has led to targeted therapies that improve treatment efficacy in many tumor types. Epidermal growth factor receptor (EGFR) inhibitors have been used to treat both lung and head and neck cancers with squamous cell histology. These tumors often show high EGFR expression and/or increased gene copy number, but low incidence of the activating kinase domain mutations common to adenocarcinomas of the lung. In this manuscript, we review clinical trial data on EGFR-inhibitors in the treatment of squamous cell carcinoma (SqCC) of the lung and head and neck (SCCHN), including both efficacy and biomarker analyses. Although some efficacy with use of EGFR inhibitors is observed, the level of benefit varies within and across tumor types, and the predictive capacity of high EGFR protein expression and/or gene amplification, if any, is limited. Due to the lack of candidate biomarkers that consistently predict response to EGFR-inhibitor therapy across treatment setting and class of agent in SqCC of the lung and SCCHN, we explore the biology, genomics and patterns of response to EGFR-inhibitors to inform identification of potential biomarkers, highlighting several key molecules that have shown promise in preclinical studies and clinical trials across multiple cancer sites.

Randomized Phase III Trial of Erlotinib versus Docetaxel in Patients with Advanced Squamous Cell Non-Small Cell Lung Cancer Failing First-Line Platinum-Based Doublet Chemotherapy Stratified by VeriStrat Good versus VeriStrat Poor. The European Thoracic Oncology Platform (ETOP) EMPHASIS-lung Trial

INTRODUCTION

Docetaxel and erlotinib are registered second-line treatments for wild-type EGFR NSCLC. Previous studies suggested a predictive value of the VeriStrat test in second-line therapy of NSCLC, classifying patients as either VeriStrat good or VeriStrat poor. EMPHASIS-lung aimed at exploring this predictive effect in patients with squamous cell NSCLC. The trial closed prematurely because of low accrual and results from other trials. Our analysis includes an exploratory combined analysis with results from the PROSE trial.

METHODS

EMPHASIS-lung was a randomized phase III multicenter trial exploring the differential effect of second-line erlotinib versus docetaxel on progression-free survival (PFS) in VeriStrat good versus VeriStrat poor patients with squamous cell NSCLC.

RESULTS

A total of 80 patients were randomized, with 72.5% categorized as VeriStrat good. Patient characteristics were balanced between VeriStrat status and treatment groups. The median PFS times with docetaxel and erlotinib treatment in the VeriStrat good cohort were 4.1 and 1.6 months, respectively, versus 1.9 and 2.1 months, respectively, in the VeriStrat poor cohort. The median overall survival (OS) times with docetaxel and erlotinib treatment in the VeriStrat good cohort were 7.8 and 8.4 months, respectively, and 4.4 and 5.2 months, respectively, in the VeriStrat poor cohort. An additional exploratory analysis was performed; in it, 47 patients from the squamous cell subgroup of PROSE were included in a combined analysis, contributing with 45 PFS and 41 OS events.

CONCLUSIONS

The final analysis of EMPHASIS-lung did not show a differential effect on PFS for erlotinib versus docetaxel stratified by VeriStrat status. Similarly, in the combined analysis, no significant treatment by VeriStrat status interaction was observed (interaction p = 0.24 for PFS and 0.45 for OS, stratified by study).

Proteomic profiling predicts drug response to novel targeted anticancer therapeutics

Most recently approved anti-cancer drugs by the US FDA are targeted therapeutic agents and this represents an important trend for future anticancer therapy. Unlike conventional chemotherapy that rarely considers individual differences, it is crucial for targeted therapies to identify the beneficial subgroup of patients for the treatment. Currently, genomics and transcriptomics are the major 'omic' analytics used in studies of drug response prediction. However, proteomic profiling excels both in its advantages of directly detecting an instantaneous dynamic of the whole proteome, which contains most current diagnostic markers and therapeutic targets. Moreover, proteomic profiling improves understanding of the mechanism for drug resistance and helps finding optimal combination therapy. This article reviews the recent success of applications of proteomic analytics in predicting the response to targeted anticancer therapeutics, and discusses the potential avenues and pitfalls of proteomic platforms and techniques used most in the field.

Personalized Medicine in Respiratory Disease: Role of Proteomics

Respiratory diseases affect humanity globally, with chronic lung diseases (e.g., asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, among others) and lung cancer causing extensive morbidity and mortality. These conditions are highly heterogeneous and require an early diagnosis. However, initial symptoms are nonspecific, and the clinical diagnosis is made late frequently. Over the last few years, personalized medicine has emerged as a medical care approach that uses novel technology aiming to personalize treatments according to the particular patient's medical needs. This review highlights the contributions of proteomics toward the understanding of personalized medicine in respiratory disease and its potential applications in the clinic.

Nanoparticle colloidal stability in cell culture media and impact on cellular interactions

Nanomaterials are finding increasing use for biomedical applications such as imaging, diagnostics, and drug delivery. While it is well understood that nanoparticle (NP) physico-chemical properties can dictate biological responses and interactions, it has been difficult to outline a unifying framework to directly link NP properties to expected in vitro and in vivo outcomes. When introduced to complex biological media containing electrolytes, proteins, lipids, etc., nanoparticles (NPs) are subjected to a range of forces which determine their behavior in this environment. One aspect of NP behavior in biological systems that is often understated or overlooked is aggregation. NP aggregation will significantly alter in vitro behavior (dosimetry, NP uptake, cytotoxicity), as well as in vivo fate (pharmacokinetics, toxicity, biodistribution). Thus, understanding the factors driving NP colloidal stability and aggregation is paramount. Furthermore, studying biological interactions with NPs at the nanoscale level requires an interdisciplinary effort with a robust understanding of multiple characterization techniques. This review examines the factors that determine NP colloidal stability, the various efforts to stabilize NP in biological media, the methods to characterize NP colloidal stability in situ, and provides a discussion regarding NP interactions with cells.

An exploratory comparative analysis of tyrosine kinase inhibitors or docetaxel in second-line treatment of EGFR wild-type non-small-cell lung cancer: a retrospective real-world practice review at a single tertiary care centre

BACKGROUND

Treatment for advanced non-small-cell lung cancer (nsclc), especially in patients with wild-type EGFR, remains limited. Recently, erlotinib, a tyrosine kinase inhibitor (tki) targeting EGFR mutation, was approved as second-line treatment in EGFR wild-type nsclc. Despite evidence of better overall survival (os) with chemotherapy than with tki in second-line treatment, data on the use of tki in the real-life clinical setting remain limited. The present practice review of tki use for second- and third-line treatment in EGFR wild-type nsclc also compares clinical outcomes for tki and single-agent docetaxel as second-line treatment.

METHODS

Our retrospective cohort study included patients with EGFR wild-type nsclc treated at the Jewish General Hospital (Montreal, QC) between 2003 and 2013. Patients received a tki (erlotinib or gefitinib) in the second and third line or docetaxel in the second line. For each group, we determined os, disease control rate, progression-free survival (pfs), and event-free survival (efs).

RESULTS

The tki group included 145 patients, with 92 receiving second-line treatment. In the control group, 53 patients received docetaxel as second-line therapy. In the tki group, os was 6.0 months; pfs, 2.7 months; and efs, 3.0 months. Comparing second-line treatments, os was 5.3 and 5.0 months respectively (p = 0.88), pfs was 2.5 and 1.8 months respectively (p = 0.041), and efs was 3.0 and 1.7 months respectively (p = 0.009).

CONCLUSIONS

In our study cohort, second-line therapy for EGFR wild-type nsclc with tki (compared with docetaxel) was associated with statistically better pfs and efs and noninferior os. Those findings raise the question of whether efs should also be considered when choosing second-line treatment in this patient population.

The value of proteomics in lung cancer

Many studies have identified the prognostic and predictive value of proteins or peptides in lung cancer but most failed to provide strong evidence for their clinical applicability. The strongest predictive proteins seem to be fatty acid-binding protein heart (H-FABP), and the 8-peak mass spectrography signature of VeriStrat. When focusing on VeriStrat, a 'VeriStrat good' profile did not discriminate between chemotherapy and erlotinib. The 'VeriStrat poor' profile showed a better outcome to chemotherapy than to erlotinib. VeriStrat is a prognostic test and only the "poor profile" discriminates for the type of therapy that should be chosen. Whether it adds useful information in patients with advanced non-small cell lung cancer (NSCLC) and wild type EGFR mutations is still doubtful. The position of the VeriStrat test in clinical practice is still not clear and we are waiting for prospective studies where biomarker test are involved in clinical decision.

Respiratory proteomics: from descriptive studies to personalized medicine

Respiratory diseases are highly prevalent and affect humankind worldwide, causing extensive morbidity and mortality with the environment playing an important role. Given the complex structure of the airways, sophisticated tools are required for early diagnosis; initial symptoms are nonspecific, and the clinical diagnosis is made frequently late. Over the past few years, proteomics has made high technological progress in mass-spectrometry-based protein identification and has allowed us to gain new insights into disease mechanisms and identify potential novel therapeutic targets. This review will highlight the contributions of proteomics toward the understanding of the respiratory proteome listing potential biomarkers and its potential application to the clinic. We also outline the contributions of proteomics to creating a personalized approach in respiratory medicine.

Current clinical application of genomic and proteomic profiling in non-small-cell lung cancer

BACKGROUND

Genomic or proteomic profiling of cancer can be broadly defined as a systematic grouping of cancer based on its genetic or protein makeup. In the management of non-small-cell lung cancer (NSCLC), genomic and proteomic profiling applications have become useful in early disease detection, diagnosis, treatment, and prognostication.

METHODS

We reviewed the recent literature on the applications of genomic and proteomic profiling in NSCLC. Important applications were summarized into those already adopted as standard care and those still under investigation.

RESULTS

For genomic profiling, testing for EGFR mutation and ALK rearrangement has become routine for adenocarcinoma. Multiplex assay and malignancy-risk gene signature are both important applications in development. A test to predict outcome after treatment with an epidermal growth factor rector/tyrosine kinase inhibitor and a screening blood test for lung cancer are being investigated for use in proteomic profiling.

CONCLUSIONS

Genomic profiling is routine in patients with NSCLC, and proteomic profiling shows promise. Additional genomic and proteomic profiling applications may also prove to be useful contributions in the care of these patients.

Predictive value of a serum-based proteomic test in non-small-cell lung cancer patients treated with epidermal growth factor receptor tyrosine kinase inhibitors: a meta-analysis

OBJECTIVE

Several studies have demonstrated that a serum-based proteomic test (VeriStrat * ) is able to predict the clinical outcome of non-small-cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). However, these studies have limited power to draw a precise conclusion because of their small sample sizes and inconsistent results. Therefore, a meta-analysis was carried out in an attempt to provide more persuasive evidence.

RESEARCH DESIGN AND METHODS

Electronic searches for relevant articles in PubMed, Embase, Medline, and Web of Science published up to May 2013 were conducted. Stata Statistical Software version 12.0 was applied for statistical analysis. The combined hazard ratio (HR) and 95% confidence interval (CI) were estimated using fixed-effects models.

RESULTS

Eleven cohorts involving 706 patients collected from seven studies were subjected to final analysis. This serum-based proteomic test's 'good' status predicted a better clinical outcome with a pooled HR of 0.40 (95% CI 0.32 to 0.49; p < 0.001) for overall survival (OS), and 0.49 (95% CI 0.39 to 0.60; p < 0.001) for progression-free survival (PFS). There was no significant heterogeneity, but a slight publication bias in this study.

CONCLUSIONS

Our meta-analysis demonstrated that this serum-based proteomic test has a predictive value for NSCLC patients treated with EGFR-TKIs. Future data are needed to validate and update our results.

Tumor heterogeneity and resistance to EGFR-targeted therapy in advanced nonsmall cell lung cancer: challenges and perspectives

Lung cancer, mostly nonsmall cell lung cancer, continues to be the leading cause of cancer-related death worldwide. With the development of tyrosine kinase inhibitors that selectively target lung cancer-related epidermal growth factor receptor mutations, management of advanced nonsmall cell lung cancer has been greatly transformed. Improvements in progression-free survival and life quality of the patients were observed in numerous clinical studies. However, overall survival is not prolonged because of later-acquired drug resistance. Recent studies reveal a heterogeneous subclonal architecture of lung cancer, so it is speculated that the tumor may rapidly adapt to environmental changes via a Darwinian selection mechanism. In this review, we aim to provide an overview of both spatial and temporal tumor heterogeneity as potential mechanisms underlying epidermal growth factor receptor tyrosine kinase inhibitor resistance in nonsmall cell lung cancer and summarize the possible origins of tumor heterogeneity covering theories of cancer stem cells and clonal evolution, as well as genomic instability and epigenetic aberrations in lung cancer. Moreover, investigational measures that overcome heterogeneity-associated drug resistance and new assays to improve tumor assessment are also discussed.

Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies

INTRODUCTION

Treatment selection tools are needed to enhance the efficacy of targeted treatment in patients with solid malignancies. Providing a readout of aberrant signaling pathways and proteolytic events, mass spectrometry-based (MS-based) peptidomics enables identification of predictive biomarkers, whereas the serum or plasma peptidome may provide easily accessible signatures associated with response to treatment. In this systematic review, we evaluate MS-based peptide profiling in blood for prompt clinical implementation.

METHODS

PubMed and Embase were searched for studies using a syntax based on the following hierarchy: (a) blood-based matrix-assisted or surface-enhanced laser desorption/ionization time-of-flight MS peptide profiling (b) in patients with solid malignancies (c) prior to initiation of any treatment modality, (d) with availability of outcome data.

RESULTS

Thirty-eight studies were eligible for review; the majority were performed in patients with non-small cell lung cancer (NSCLC). Median classification prediction accuracy was 80% (range: 66%-93%) in 11 models from 14 studies reporting an MS-based classification model. A pooled analysis of 9 NSCLC studies revealed clinically significant median progression-free survival in patients classified as "poor outcome" and "good outcome" of 2.0 ± 1.06 months and 4.6 ± 1.60 months, respectively; median overall survival was also clinically significant at 4.01 ± 1.60 months and 10.52 ± 3.49 months, respectively.

CONCLUSION

Pretreatment MS-based serum and plasma peptidomics have shown promising results for prediction of treatment outcome in patients with solid tumors. Limited sample sizes and absence of signature validation in many studies have prohibited clinical implementation thus far. Our pooled analysis and recent results from the PROSE study indicate that this profiling approach enables treatment selection, but additional prospective studies are warranted.

Predictive value of a proteomic signature in patients with non-small-cell lung cancer treated with second-line erlotinib or chemotherapy (PROSE): a biomarker-stratified, randomised phase 3 trial

BACKGROUND

An established multivariate serum protein test can be used to classify patients according to whether they are likely to have a good or poor outcome after treatment with EGFR tyrosine-kinase inhibitors. We assessed the predictive power of this test in the comparison of erlotinib and chemotherapy in patients with non-small-cell lung cancer.

METHODS

From Feb 26, 2008, to April 11, 2012, patients (aged ≥18 years) with histologically or cytologically confirmed, second-line, stage IIIB or IV non-small-cell lung cancer were enrolled in 14 centres in Italy. Patients were stratified according to a minimisation algorithm by Eastern Cooperative Oncology Group performance status, smoking history, centre, and masked pretreatment serum protein test classification, and randomly assigned centrally in a 1:1 ratio to receive erlotinib (150 mg/day, orally) or chemotherapy (pemetrexed 500 mg/m(2), intravenously, every 21 days, or docetaxel 75 mg/m(2), intravenously, every 21 days). The proteomic test classification was masked for patients and investigators who gave treatments, and treatment allocation was masked for investigators who generated the proteomic classification. The primary endpoint was overall survival and the primary hypothesis was the existence of a significant interaction between the serum protein test classification and treatment. Analyses were done on the per-protocol population. This trial is registered with ClinicalTrials.gov, number NCT00989690.

FINDINGS

142 patients were randomly assigned to chemotherapy and 143 to erlotinib, and 129 (91%) and 134 (94%), respectively, were included in the per-protocol analysis. 88 (68%) patients in the chemotherapy group and 96 (72%) in the erlotinib group had a proteomic test classification of good. Median overall survival was 9·0 months (95% CI 6·8-10·9) in the chemotherapy group and 7·7 months (5·9-10·4) in the erlotinib group. We noted a significant interaction between treatment and proteomic classification (pinteraction=0·017 when adjusted for stratification factors; pinteraction=0·031 when unadjusted for stratification factors). Patients with a proteomic test classification of poor had worse survival on erlotinib than on chemotherapy (hazard ratio 1·72 [95% CI 1·08-2·74], p=0·022). There was no significant difference in overall survival between treatments for patients with a proteomic test classification of good (adjusted HR 1·06 [0·77-1·46], p=0·714). In the group of patients who received chemotherapy, the most common grade 3 or 4 toxic effect was neutropenia (19 [15%] vs one [<1%] in the erlotinib group), whereas skin toxicity (one [<1%] vs 22 [16%]) was the most frequent in the erlotinib group.

INTERPRETATION

Our findings indicate that serum protein test status is predictive of differential benefit in overall survival for erlotinib versus chemotherapy in the second-line setting. Patients classified as likely to have a poor outcome have better outcomes on chemotherapy than on erlotinib.

FUNDING

Italian Ministry of Health, Italian Association of Cancer Research, and Biodesix.

Molecular pathways and therapeutic targets in lung cancer

Lung cancer is still the leading cause of cancer death worldwide. Both histologically and molecularly lung cancer is heterogeneous. This review summarizes the current knowledge of the pathways involved in the various types of lung cancer with an emphasis on the clinical implications of the increasing number of actionable molecular targets. It describes the major pathways and molecular alterations implicated in the development and progression of non-small cell lung cancer (adenocarcinoma and squamous cancer), and of small cell carcinoma, emphasizing the molecular alterations comprising the specific blueprints in each group. The approved and investigational targeted therapies as well as the immune therapies, and clinical trials exploring the variety of targeted approaches to treatment of lung cancer are the main focus of this review.

Serum proteomic study on EGFR-TKIs target treatment for patients with NSCLC

Background

Although epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are widely used for EGFR mutated non-small-cell lung cancer (NSCLC) patients, tumor sample availability and heterogeneity of the tumor remain challenging for physicians’ selection of these patients. Here, we developed a serum proteomic classifier based on matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) to predict the clinical outcome of patients treated with EGFR-TKIs.

Method

A total of 68 patients were included in this study. All patients received EGFR-TKIs as second or third line treatment and blood samples were collected before treatment. Using magnetic bead assisted serum peptide capture coupled to MALDI-TOF-MS, pretreatment serum from 24 NSCLC patients was analyzed to develop a proteomic classifier (training set). In a blinded test set with 44 patients, each sample was classified into “good” or “poor” groups using this classifier. Survival analysis of each group was done based on this classification.

Result

A 3-peptide proteomic classifier was developed from the training set. In the testing set, the classifier was able to distinguish patients of “good” or “poor” outcomes with 93% accuracy, sensitivity, and specificity. The overall survival and progression free survival of the predicted good group were found to be significantly longer than the poor group, not only in the whole population but also in certain subgroups, such as pathological adenocarcinoma and nonsmokers. With respect to the tumor samples available for EGFR mutation detection, all eight EGFR mutant tumors and three of the 12 wild type EGFR tumors were classified as good while nine of the 12 wild type EGFR tumors were classified as poor.

Conclusion

The current study has shown that a proteomic classifier can predict the outcome of patients treated with EGFR-TKIs and may aid in patient selection in the absence of available tumor tissue. Further studies are necessary to confirm these findings.

miR-150 promotes the proliferation of lung cancer cells by targeting P53

Lung cancer is one of the most common causes for cancer-related death. Previous studies suggested that uncontrolled cell proliferation induced by activation of pro-cancer genes or inhibition of cancer suppressor genes plays an important role in the pathogenesis of lung cancer. Here, we demonstrate that miR-150 is aberrantly upregulated in lung cancer tissue and negatively correlates with the expression of the proapoptotic gene p53 but not EGR2. We show that miR-150 specifically targets the 3'-UTR of p53 and regulates its expression. Inhibition of miR-150 effectively delays cell proliferation and promotes apoptosis, accompanied by increased p53 protein expression. Our data reveals the mechanisms underlying miR-150 regulated lung cancer pathogenesis, which might be beneficial for lung cancer therapy.

VeriStrat(®) has prognostic value in advanced stage NSCLC patients treated with erlotinib and sorafenib

BACKGROUND

The serum proteomic test VeriStrat has been shown to be able to classify advanced non-small cell lung cancer (NSCLC) patients for overall survival (OS) after treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). In this study, VeriStrat was evaluated as a pre-treatment stratification tool in patients with advanced stage NSCLC for treatment with the combination of erlotinib and sorafenib, considering both OS and progression-free survival (PFS) as end points.

METHODS

Serum samples from 50 patients treated within the context of a phase II trial of first-line erlotinib and sorafenib were analysed with VeriStrat, a fully locked mass spectrometry-based test that identifies patients likely to have good or poor outcome on EGFR therapy based on eight distinct features in mass spectra. Analysis was performed fully blinded to all clinical data, and then the outcome data were analysed with respect to the obtained serum classifications.

RESULTS

VeriStrat classified pre-treatment samples into two groups, VeriStrat Good and VeriStrat Poor, which were significantly different in OS (hazard ratio (HR) 0.30, log-rank P=0.009) and in PFS (HR 0.40, log-rank P=0.035).

CONCLUSION

VeriStrat has shown its potential for stratification of unselected, advanced stage NSCLC patients treated in first line with a combination of erlotinib and sorafenib.

SAA1 is over-expressed in plasma of non small cell lung cancer patients with poor outcome after treatment with epidermal growth factor receptor tyrosine-kinase inhibitors

It has been shown that a proteomic algorithm based on 8 MALDI TOF MS signals obtained from plasma of NSCLC patients treated with EGFR TKIs, is able to predict patients' clinical outcome. In the current study, we identified the proteins originating 4 out of 8 mass signals in the classification algorithm. Plasma samples collected before the beginning of gefitinib therapy were analyzed by MALDI TOF MS and classified according to the proteomic algorithm in good and poor profiles. Two pools of good and poor classified samples were prepared using MARS and ProteoMiner Protein Enrichment kit before 2DE analysis. Proteins differentially expressed between good and poor 2DE samples were excised from gels and analyzed with MALDI TOF MS and LC MS/MS. The identified proteins were validated by Immunodepletion and Western blot analyses. serum amyloid A protein 1 (SAA1), together with its two truncated forms, was over-expressed in plasma of poor classified patients, and was identified as the protein that generates 4 out of the 8 mass signals composing the proteomic algorithm VeriStrat. SAA levels measured by ELISA in 97 NSCLC patients treated with gefitinib correlated with the clinical outcome of the patients. This article is part of a Special Issue entitled: Integrated omics.

The Evolving Role of Maintenance Therapy Using Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors (EGFR TKIs) in the Management of Advanced Non-Small-Cell Lung Cancer

The epidermal growth factor receptor (EGFR) plays an important role in the development of many cancers, including non-small cell lung cancer. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) are a class of novel biologically-targeted agents widely used in the management of recurrent non-small cell lung cancer. Erlotinib, one of the EGFR TKIs, is currently FDA approved in second and third line therapy. However, recent studies showed that erlotinib is also effective as maintenance therapy after initial chemotherapy, improving disease free survival and possibly overall survival. Our current understanding of erlotinib's mechanism of action, with the discovery that EGFR mutation confers higher response rate, has propelled this agent into the first line setting. Advances in molecular testing and clinical research of this agent and other agents in this class will eventually change the way we utilize EGFR TKIs in the near future.