Journal of Oncology

Journal of Oncology / 2019 / Article
Special Issue

Immunotherapy: A New Hope for Cancer Patients

View this Special Issue

Research Article | Open Access

Volume 2019 |Article ID 8970645 |

Alessandra Rossi, Minna Voigtlaender, Hans Klose, Hartmut Schlüter, Gerhard Schön, Sonja Loges, Moreno Paolini, Carsten Bokemeyer, Martin Reck, Giulio Tarro, Mascha Binder, "High Aldehyde Dehydrogenase Levels Are Detectable in the Serum of Patients with Lung Cancer and May Be Exploited as Screening Biomarkers", Journal of Oncology, vol. 2019, Article ID 8970645, 11 pages, 2019.

High Aldehyde Dehydrogenase Levels Are Detectable in the Serum of Patients with Lung Cancer and May Be Exploited as Screening Biomarkers

Guest Editor: Shalini Gupta
Received24 Dec 2018
Revised20 May 2019
Accepted04 Jul 2019
Published22 Aug 2019


Objectives. Since early detection improves overall survival in lung cancer, identification of screening biomarkers for patients at risk represents an area of intense investigation. Tumor liberated protein (TLP) has been previously described as a tumor-associated antigen (complex) present in the sera from lung cancer patients. Here, we set out to identify the nature of TLP to develop this as a potential biomarker for lung cancer screening. Materials and Methods. Beginning from the peptide epitope RTNKEASI previously identified from the TLP complex, we produced a rabbit anti-RTNKEASI serum and evaluated it in the lung cancer cell line A549 by means of immunoblot and peptide completion assay (PCA). The TLP sequence identification was conducted by mass spectrometry. The detected protein was, then, analyzed in patients with non-small cell lung cancer (NSCLC) and benign lung pathologies and healthy donors, by ELISA. Results. The anti-RTNKEASI antiserum detected and immunoprecipitated a 55 kDa protein band in the lysate of A549 cells identified as aldehyde dehydrogenase isoform 1A1, revealing the molecular nature of at least one component of the previously described TLP complex. Next, we screened blood samples from a non-tumor cohort of 26 patients and 45 NSCLC patients with different disease stages for the presence of ALDH1A1 and global ALDH. This analysis indicated that serum positivity was highly restricted to patients with NSCLC (ALDH ; ALDH1A1 ). Interestingly, the global ALDH test resulted positive in more NSCLC samples compared to the ALDH1A1 test, suggesting that other ALDH isoforms might add to the sensitivity of the assay. Conclusion. Our data indicate that ALDH levels are elevated in the sera of NSCLC patients, even with early stage disease, and may thus be evaluated as part of a marker panel for non-invasive detection of NSCLC.

1. Introduction

Despite various treatment approaches such as surgery, radiotherapy, and chemotherapy, lung cancer remains the most common cancer-related cause of death in the world with a 15% 5-year survival rate of about [13]. Non-small cell lung cancer (NSCLC) represents the most frequent histology and accounts for 80–85% of newly diagnosed cases. The standard of care for functionally operable early-stage and resectable stage IIIA NSCLC is surgery which possesses a potential for cure. Nevertheless, only 20% of NSCLC are diagnosed at early stage and can be resectable; thus, early detection strategies remain an unmet clinical need [46].

So far, numerous studies investigated mainly the potential effects of chest X-rays and low-dose helical computed tomography (CT) for imaging alongside with sputum cytology on lung cancer detection. Although these studies showed encouraging results about stage distribution in favor of earlier stage disease, better surgical resection of the tumors, and also an increased survival rate, an improvement on overall mortality could not be determined [716]. Serological markers such as Carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and Cyfra 21-1 are serological markers used for the monitoring of treatment response in lung cancer patients, but their application as screening biomarkers is still a challenging question [1719]. Theoretically, an ideal biomarker should be 100% sensitive and specific, a goal that is almost never accomplished. One strategy potentially increasing both parameters is to putting different biomarkers together into a screening marker panel. This approach, along with other noninvasive methods, may allow for further improvement of NSCLC screening [20].

In 1983, a tumor-associated antigen was isolated from NSCLC and named tumor liberated protein (TLP) by Tarro et al. and immunohistochemically localized in small and large granules into the cytoplasm [4, 2125]. Given that it was also detected in the lumen of atypical glands and in the bronchial secretions of some specimens, TLP could be considered a secretory product of cancer cells. It has been shown that when TLP is isolated and purified from a patient’s tumor and reintroduced into the body, it boosts an immune response in the host [4]. Starting from the partial sequence analysis of this protein, corresponding antigenic peptides have been synthetized and used to generate antisera in rabbits. Among the four TLP-derived peptides identified by Tarro, anti-RTNKEASI rabbit sera reacted specifically with NSCLC tumor extracts and sera from lung cancer patients [26]. TLP was detected in the sera of NSCLC patients above all at the early stage of disease.

In this study, we show that TLP (or a component of this putative complex) corresponds to aldehyde dehydrogenase (ALDH) isoform 1A1 (ALDH1A1). ALDHs are a broad family of intracellular enzymes that are involved in cellular detoxification, differentiation, and drug resistance processes by means of the conversion of exogenous and endogenous aldehydes to carboxylic acids [4, 6, 2730]. Numerous studies have investigated the biological role of ALDH in cancers including breast cancer, colon cancer, head and neck, papillary thyroid carcinoma, and mainly lung cancer, where they have given supportive evidence for the correlation between ALDH activity and lung cancer stem cells [4, 3137]. Moreover, Cao et al. showed that ALDH1A1 levels were elevated in the sera of NSCLC patients. The combination of serum ALDH1A1 and CEA significantly increased the screening sensitivity of single CEA test [38]. Here, we show that ALDH isoforms other than 1A1 may be released into the blood of NSCLC patients, and thus, screening sensitivity may be even more improved by employing an isoform-unspecific global ALDH assay without apparently lowering specificity. Diagnostic sensitivity and specificity will, however, have to be prospectively validated in larger cohorts of patients with early-stage NSCLC and in healthy subjects at risk for NSCLC as well as in other cancer patient cohorts.

2. Materials and Methods

2.1. Patient Characteristics and Materials

Blood samples from 45 newly diagnosed NSCLC patients, 17 patients with benign lung pathologies, and 9 healthy donors were collected during routine diagnostic workup. The work has been carried out in accordance with the declaration of Helsinki. All patients consented to the use of their biological material for this investigation as approved by the Landesärztekammer Hamburg (ethics committee) (project number PV4382). Patients with lung cancer stages I-IIIA were considered as early-stage disease, as previously published [30]. Clinical characteristics (type of lung cancer, patient age, sex, smoking, tumor histology, tumor stage, and secondary diagnosis) of this cohort are displayed in Table 1.

Healthy controls (n = 9)Benign lung disease (n = 17)Early-stage lung cancer (n = 25)Advanced-stage lung cancer (n = 20)

Age in years, mean ± SD42.7 ± 18.053.1 ± 18.368.5 ± 8.262.3 ± 8.8
Male, no. (%)2 (22.2)10 (58.8)12 (48.0)10 (50)
Smoker, no. (%)011 (64.7)20 (80.0)15 (88.0)
Smoking in pack-years, mean ± SD028.4 ± 29.543.6 ± 30.647.3 ± 22.05
Type of lung cancer, no. (%)
 NSCLC25 (100.0)20 (100.0)
  Adenocarcinoma15 (60.0)13 (65)
  Squamous cell carcinoma8 (32.0)2 (10)
  Large cell carcinoma2 (8.0)1 (5)
UICC classification, no. (%)
 IA5 (20.0)
 IB8 (32.0)
 IIA6 (24.0)
 IIB5 (20.0)
 IIIA1 (4.0)
 IIIB1 (5.0)
 IV15 (75.0)
Type of benign lung diseases, no. (%)
 COPD8 (47.1)
 Cystic fibrosis4 (23.5)
 Other benign lung diseases5 (29.4)

NSCLC: non-small cell lung cancer; COPD: chronic obstructive pulmonary disease. Smoking status of 3 patients unknown. Other benign lung diseases comprise precapillary pulmonary hypertension (n = 2), interstitial lung disease (n = 1), sarcoidosis (n = 1), and mucoid impaction (n = 1).
2.2. Antigen Synthesis and Antibody Production

The production of two different rabbit polyclonal anti-RTNKEASI immune sera and the synthesis of TLP-derived peptide RTNKEASI [26] were both conducted at Rockland Immunochemicals Inc. (Gilbertsville, PA, USA) and at BioGenes GmbH (Berlin, Germany). We further purified the anti-RTNKEASI immune serum produced at Rockland by means of chromatography against the RTNKEASI peptide.

2.3. Cell Culture

The human cell lines MRC-5, A549, Hela, CA46, HL60, PC3, and MCF-7 were obtained from American Type Culture Collection (ATCC; Manassas, VA, USA). Cell lines were cultured at 37°C in a humidified atmosphere of 5% CO2 in air under the following conditions: CA46 cell line in Glutamax RPMI 1640; PC3 cell line in Glutamax HAM’s F-12; MRC-5, HL60, MCF-7, A549, and Hela cell lines in Glutamax Dulbecco’s Modified Eagle’s Medium. All the media (Gibco, Life Technologies) were supplemented with 10% fetal bovine serum (Biochrom GmbH, Berlin, Germany) [39].

2.4. Western Blot

We prepared cell pellets and lysates from MCF-7, CA46, HL60, PC3 MRC-5, A549, and Hela cell lines as described previously [39, 40].

Cell culture supernatant from A549 cells (5 × 106) was treated on ice with 10% trichloroacetic acid (TCA) and then incubated with ice-cold 90% acetone at −20°C. Subsequently, the sample was centrifuged and the pellet dried at 65°C for 30 minutes.

The isolated proteins were mixed in Laemmli sample buffer (20% glycerol, 4% sodium dodecyl sulfate (SDS), 100 mM Tris-HCl, 200 mM dithiothreitol (DTT), and 0.01% bromophenol blue) and boiled before loading into SDS-PAGE gel. Finally, the proteins were blotted onto membranes and blocked in nonfat dry milk 8% + PBS + 0.1% Tween-20 before hybridization with the anti-RTNKEASI serum diluted 1 : 1000 in PBS + 0.1% Tween-20 + BSA 5% buffer or β-actin 1 : 20000 (Biolegend, San Diego, CA), overnight at 4°C. After primary antibodies, the membranes were probed with a secondary antibody (1 : 30000 in PBS + 0.1% Tween-20 + BSA 5%), and then, proteins were visualized by enhanced chemiluminescence (GE Healthcare, Little Chalfont, UK).

2.5. PCA

The anti-RTNKEASI serum (1 : 1000) was subjected to preincubation with peptide RTNKEASI (500-fold molar excess) or KDSGNEQTFLPP as a control peptide, before hybridization with blotted A549 sample for 2 hours, according to Rockland procedure. The membranes were probed with a secondary antibody, and immunoreactive bands were detected by enhanced chemiluminescence.

2.6. 2D Polyacrylamide Gel Electrophoresis

Protein isolation from cell lines was performed as described previously [41]. For the first dimension isoelectric focusing, we used 7 cm immobilized pH gradient (IPG) dry strips with a linear pH 4–7 gradient (GE Healthcare). Solubilized proteins (50 μg) were put onto the strips, rehydrated, and incubated over night [41]. Proteins were resolved by the PROTEAN IEF system (Bio-Rad) (voltage gradient at 20°C with a current limit of 50 μA) under the following conditions: 4 h at 250 V, 8000 V linear gradient to 15000 V·h, and rapid 8000 V to 75000 V h, for a total of 90 kV·h [41]. After equilibration in buffer 1 (130 mM DTT, 6 M urea, 20% glycerol, 0.05 M Tris-HCl, 2% SDS) and buffer 2 containing iodoacetamide in place of DTT, the first dimension strips were positioned to the upper part of 8% acrylamide (Applichem GmbH, Darmstadt, Germany), for performing the second dimension [41]. The separated proteins were stained by silver or blotted onto the membrane and probed with the pre-serum or anti-RTNKEASI serum.

2.7. Protein Identification by LC-MS/MS

The gel spots were treated with DTT (10 mM, 56°C, 30 min) and with iodoacetamide (55 mM, at room temperature, 20 min, in the dark). Subsequently, the proteins were digested by 13 ng/μl trypsin (sequencing grade modified trypsin, Promega) in 50 mM ammonium bicarbonate, 37°C, 16 h. Tryptic digested peptides were extracted in 65% acetonitrile (ACN)/5% formic acid (FA), vacuum-dried, and dissolved in 15 μL 0.1% FA. Tryptic digested peptides were separated on an UltiMate 3000 Rapid Separation liquid chromatography (RSLC) system (Dionex, Thermo Scientific, Bremen, Germany) coupled online via electrospray-ionization (ESI) to an Orbitrap Fusion Tribrid mass spectrometer (Thermo Scientific, Bremen, Germany). The samples were loaded with a flow rate of 5 μl/min on a trapping column (Acclaim PepMap μ-precolumn, C18, 300 μm × 5 mm, 5 μm, 100 Ǻ, Thermo Scientific, Bremen, Germany; nanoACQUITY-UPLC Symmetry C18 trap column, 180 μm × 20 mm, 5 μm, 100 Ǻ; buffer A: 0.1% FA in HPLC-H2O; buffer B: 0.1% FA in ACN) with 2% buffer B. The loaded samples on the trapping column were washed firstly for 5 min with 2% buffer B (5 μl/min) and subsequently the peptides were eluted (200 nl/min) onto the separation column. Tryptic digested peptides were separated on a reversed-phase C18 column (Acclaim PepMap 100, 75 μm × 25 mm, 2 μm, 100 Å; Thermo Scientific, Bremen, Germany; nanoACQUITY-UPLC column, BEH 130 C18, Waters; 75 μm × 250 mm, 1.7 μm, 100 Ǻ) with a flow rate 200 nl/μm with a binary buffer system of solvent A (0.1% FA in HPLC-H2O) and solvent B (0.1% FA in ACN). The peptides were eluted with a gradient of 2–30% Solvent B in 30 min. MS analysis was performed in the positive ion mode and was programmed to acquire by data-dependent mode (DDA). The full scans were acquired in the Orbitrap mass analyzer of Fusion with a resolution of 120,000 FWHM at m/z 200 on the MS level over a m/z range from 400 to 1500 (maximum injection time: 50 ms and automatic gain control target: 4e5). The fragmentation was carried out with an intensity threshold of 1e4, and the fragmented ions were accumulated in the linear ion trap in the rapid mode. Only precursors with charge states between +2 and +5 and the most intense precursors were selected for fragmentation. The top intense ions were isolated to a target value of 1e4 with a maximum injection time of 50–150 ms. The raw data were processed with Proteome Discoverer, v1.4.1.14 (Thermo Scientific). Protein identification was performed by using UniProt FASTA database.

2.8. ALDH and ALDH1A1 ELISA Assay

Serum samples from patients with NSCLC and benign lung pathologies and healthy donors were collected and stored at −80°C. The sera were subsequently assayed according to the manual instructions of the global ALDH ELISA kit with a monoclonal antibody specific for different ALDH isoforms (Bluegene, Biotech, Shanghai, China) and the ALDH1A1 ELISA kit with a monoclonal antibody specific for the isoform 1A1 (Cloud-Clone Corp. Houston, TX, USA). Three independent sera patients’ samples are analyzed. Data are expressed as means ± SD of 3 independent experiments.

2.9. Statistics

Data were presented as means ± standard deviation (SD). We used backward stepwise linear-regression modelling to analyze differences in the ALDH- and ALDH1A1 serum levels, respectively, between patients with and without NSCLC under consideration of age, sex, and smoking (in pack-years). Correlation coefficients were according to the method of Pearson. All analyses were carried out using IBM® SPSS® version 22 or GraphPad Prism™ version 5 software. A value of <0.05 was considered statistically significant.

3. Results

3.1. Peptide RTNKEASI Mimics a 55 kDa Protein Highly Expressed in Lung Cancer Cell Line A549

To identify the complete protein sequence or major component of TLP, we produced two polyclonal antibody sera (BioGenes GmbH, Berlin, Germany; Rockland Immunochemicals, PA, USA) by using the peptide epitope mimic RTNKEASI derived from TLP as previously published [25]. Compared to the preimmune sera, both anti-RTNKEASI sera detected one differential protein band in the NSCLC cell line A549 at 55 kDa (Figures 1(a) and 1(b)).

Based on these results, we performed a peptide competition assay (PCA) with limiting concentrations of detection antiserum and an excess of blocking RTNKEASI or control peptide. A partial extinction of the 55 kDa protein band in the presence of the specifically blocking RTNKEASI peptide compared to the control peptide confirmed that the 55 kDa band was specifically recognized by RTNKEASI-directed antibodies from the antiserum (Figure 1(c)).

In order to analyze specificity of the 55 kDa protein for lung cancer, we subjected protein lysates from a variety of tumor cell lines and normal lung tissue to western blot analysis with the anti-RTNKEASI serum. Our western blot results showed very high levels of this 55 kDa protein in the lung cancer cell line A549, whereas all other cell lines showed either no or faint bands at 55 kDa (Figure 2(a)).

We also analyzed the supernatant from A549 cell line to verify cell ability to secrete ALDH outside. Our western blot showed a specific band at 55 kDa with a considerable amount of this protein corresponding to ALDH, as confirmed by mass spectrometry analysis (Figure 2(b) and Table 2).

Gene symbolProtein descriptionUnique peptidesScoreMW (kDa)

55 kDa band from A549 cell lysate excised from 1D gel
 ALDH1A1Retinal dehydrogenase2668755.4
 ALDH3A1Aldehyde dehydrogenase, dimeric NADP-preferring1540750.8
 UGDHUDP-glucose 6-dehydrogenase314055.7
 GSRGlutathione reductase mitochondrial413456.8
 PDIA3Protein disulfide-isomerase A339357.1
 ALDH2Aldehyde dehydrogenase, mitochondrial38356.9

55 kDa band from A549 supernatant excised from 1D gel
 ALDH1A1Retinal dehydrogenase 12974255.5
 G6PDGlucose-6-phosphate 1-dehydrogenase2659959.7
 ALDH3A1Aldehyde dehydrogenase, dimeric NADP-preferring1030350.8

55 kDa band from A549 immunoprecipitation excised from 1D gel
 ALDH1A1Retinal dehydrogenase 12835155.5
 G6PDGlucose-6-phosphate 1-dehydrogenase1222359.7
 ALDH3A1Aldehyde dehydrogenase, dimeric NADP-preferring37050.8

55 kDa spot 1 from A549 lysate excised from 2D gel
 ALDH3A1Aldehyde dehydrogenase, dimeric NADP-preferring2051550.4
 CCT2T-complex protein 1 subunit beta18100.857.5
 ALDH1A1Retinal dehydrogenase 11257.454.8
 ALDH1B1Aldehyde dehydrogenase X, mitochondrial115257.2

55 kDa spot 2 from A549 lysate excised from 2D gel
 ALDH3A1Aldehyde dehydrogenase, dimeric NADP-preferring19494.850.4
 ALDH1A1Retinal dehydrogenase 119120.4554.8

MW: molecular weight.
3.2. Mass Spectrometric Identification of ALDH1A1 as Parental Antigen Mimicked by Peptide RTNKEASI

In order to identify the 55 kDa protein by mass spectrometry (MS), we conducted a two-dimensional (2D) gel electrophoresis of protein extracts from A549 and MCF-7 (negative control) followed by western blotting and detection with the anti-RTNKEASI serum (Figure 3). We observed two neighboring spots at the same molecular weight of 55 kDa but with slightly different isoelectric points, 6.54 and 6.73 respectively, which exhibited reactivity with the anti-RTNKEASI serum. These spots were neither detected by the preimmune serum nor by the anti-RTNKEASI serum in the control cell lysate (Figure 3). These two spots were matched to and excised from 2D protein gels followed by MS. Our results showed that the 55 kDa protein corresponds to ALDH isoform 1A1 which is highly expressed in different tumors including NSCLC. This result was also confirmed by MS of one dimensionally (1D) separated protein extracts from A549 cells, A549 cell culture supernatant, and immunprecipitations with anti-RTNKEASI serum from the A549 lysate (Table 2). Sequence alignment of ALDH1A1 with the peptide RTNKEASI revealed no linear matches, suggesting that this peptide only structurally mimics ALDH1A1.

3.3. Detection of ALDH1A1 and Global ALDH in Sera of Patients with Lung Cancer and Benign Lung Pathologies

To explore the utility of serum ALDH1A1 as potential biomarker for lung cancer, we tested ALDH1A1 protein levels in sera from 25 NSCLC patients with early-stage disease, 20 NSCLC patients with advanced stage disease, 17 patients with nonneoplastic pulmonary diseases and 9 healthy donors. The baseline characteristics of this cohort are shown in Table 1. We compared ALDH serum levels in NSCLC patients with benign lung pathologies and healthy donors groups as negative controls to set the threshold of background and normalize the measurements, according to previous studies [4244]. We found ALDH1A1 serum levels above a sensitivity threshold of 10 ng/ml (reflecting the estimated background noise) in only three of 45 NSCLC patients (6.7%), while all other NSCLC patients showed ALDH1A1 serum levels comparable with the control cohorts (Figures 4(a) and 4(b)). However, after precluding age, sex, and smoking (in pack-years) as nonsignificant parameters associated with the concentration of ALDH1A1 in the backward stepwise linear-regression analysis, overall, ALDH1A1 serum levels differed significantly between the lung cancer and the no-lung cancer patient groups. The mean difference in the ALDH1A1 concentration between no lung cancer and lung cancer is 2.10 ng/ml, 95% CI: 0.23 ng/ml to 3.98 ng/ml; .

Since the MS analysis had also revealed matches with other ALDH isoforms (such as ALDH3A1), we hypothesized that these might add to the sensitivity of the assay. To this end, we performed further ELISA testings using a global ALDH assay without isoform specificity (Figures 4(c) and 4(d)). Remarkably, 33 out of 45 serum samples (73.3%) showed positivity for global serum ALDH (>10 ng/ml). Only one patient from the cohort of patients with benign lung diseases showed ALDH serum positivity above this threshold, and all healthy donors were serum ALDH-negative. Interestingly, of 25 patients with early-stage NSCLC, 15 patients (60%) showed elevated ALDH levels. Overall, serum ALDH levels were significantly elevated in the cohort of patients with NSCLC compared to patients without lung cancer. The mean difference in the ALDH concentration between no lung cancer and lung cancer is 13.90 ng/ml, 95% CI: 8.45 ng/ml to 19.35 ng/ml; . All the statistical analysis values are reported in Supplementary Materials (Table 1S and 2S).

According to the method of Pearson, neither ALDH1A1 nor ALDH concentration correlated significantly with the UICC stage ( and , respectively).

4. Discussion

Worldwide, NSCL patients have the highest mortality between patients with solid tumors, and their prognosis is tightly stage-correlated. Nevertheless, conventional methods for the diagnosis of NSCLC have high costs and produce potentially false-positive outcomes. Thus, the discovery of highly sensitive, specific, noninvasive, and cost-effective lung cancer biomarkers to use in association with conventional approaches may increase the sensitivity of NSCLC screening [4, 6, 4547].

In this study, we show that the previously described TLP corresponds to ALDH1A1 and potentially other ALDH isoforms, which are highly expressed in NSCLC tissues [28, 33, 3538, 4649]. Since the peptide RTNKEASI did not linearly match ALDH isoform amino acid sequences, we concluded that it may structurally mimic these ALDH isoforms.

In our blood-based ELISA assays, we show that ALDH and, in accordance with Cao et al. [38], ALDH1A1 protein levels are statistically higher in patients with NSCLC compared to our nontumor cohort. However, only a small percentage of NSCLC patients (6.7%) display high ALDH1A1 serum levels, whereas sensitivity of the global ALDH test seems encouraging (73.3%). This suggested that other ALDH isoforms are also released in the sera of NSCLC patients potentially adding to the sensitivity of this global assay. This finding is in accordance with previous studies showing that several ALDH isoforms are involved in NSCLC [38]. ALDH3A1 is highly expressed in two types of NSCLC, adenocarcinoma and squamous cell carcinoma [48, 49]. ALDH3B1 expression was also found to be upregulated in a high percentage of human tumors, particularly in lung cancer [50]. Given the limited sample sizes of our cohorts, predictions on sensitivity and specificity of this marker are unreliable. However, it seems that the global ALDH test may not significantly decrease specificity as compared to the ALDH1A1-specific test.

ALDH1A1 and ALDH3A1 expression levels in normal pneumocytes are significantly higher in tobacco smokers versus nonsmokers [48]. Although we did not identify any significant association between ALDH levels and smoking status across the cohorts, the higher expression levels in smokers may explain the trend towards higher ALDH levels in patients with benign lung pathologies (including a high percentage of patients with chronic obstructive pulmonary disease) compared to our nonsmoking healthy donors.

Our very small percentage of ALDH1A1-positive NSCLC patients (6.7%) clearly contrasts with previously published work by Cao et al. [38] who detected a much higher percentage of ALDH1A1-positive NSCLC patients (55%). This may be due to differences in ALDH1A1 kits, which presumably contain monoclonal antibodies with different specificity for ALDH1A1 but may also be explained in part by differences in the patient cohorts or different cut-off levels. Moreover, our results showed that some patients positive with ALDH1A1 were not with global ALDH, probably due to a potential degradation of these samples as global ALDH was performed later in time.

In conclusion, elevated ALDH serum levels can be detected in the vast majority of patients with early- and advanced-stage disease. Therefore, serum ALDH should be evaluated as part of a marker panel for noninvasive detection of early NSCLC in a larger cohort of patients at risk.


TLP:Tumor liberated protein
ALDH:Aldehyde dehydrogenase
NSCLC:Non-small cell lung cancer
CT:Computed tomography
CEA:Carcinoembryonic antigen
NSE:Neuron-specific enolase
ALDH1A1:Aldehyde dehydrogenase isoform 1A1
PCA:Peptide completion assay
PVDF:Polyvinylidene difluoride
CHAPS:3-[(3-Cholamidopropyl) dimethylammonio]-1-propanesulfonate
FA:Formic acid
RSLC:Rapid separation liquid chromatography
DDA:Data-dependent mode
LC/MS:Liquid chromatography-mass spectrometry.

Data Availability

All data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

MB and AR designed the study. AR collected the data. MV and AR analyzed the data. MV performed the statistical analysis. MB, AR, and MV interpreted the results. MB and AR drafted the manuscript with critical revisions from SL, SH, CB, and MR. SH conducted the mass spectrometry analysis. All authors approved the final version.


This study was supported by the T. & L. de Beaumont Bonelli Foundation for Cancer Research (to MB), a fellowship of the T. & L. de Beaumont Bonelli Foundation for Cancer Research (to AR), and a professorship for immunological cancer research (to MB) of the Hubertus Wald Foundation, Hamburg. The authors also thank Parnian Kiani for the assistance with the protein analysis via tandem MS and Astrid Huengsberg for the collection of patient samples.

Supplementary Materials

The first table describes the backward stepwise linear-regression analysis of the ALDH and ALDH1A1 ELISA assays, and the second table shows the mean values obtained in the related assay. (Supplementary Materials)


  1. R. Siegel, D. Naishadham, and A. Jemal, “Cancer statistics, 2013,” CA: A Cancer Journal for Clinicians, vol. 63, no. 1, pp. 11–30, 2013. View at: Publisher Site | Google Scholar
  2. A. Jemal, F. Bray, M. M. Center, J. Ferlay, E. Ward, and D. Forman, “Global cancer statistics,” CA: A Cancer Journal for Clinicians, vol. 61, no. 2, pp. 69–90, 2011. View at: Publisher Site | Google Scholar
  3. M. Yuxia, T. Zhennan, and Z. Wei, “Circulating miR-125b is a novel biomarker for screening non-small-cell lung cancer and predicts poor prognosis,” Journal of Cancer Research and Clinical Oncology, vol. 138, no. 12, pp. 2045–2050, 2012. View at: Publisher Site | Google Scholar
  4. G. Tarro, “Immuno-therapy research,” Immunotherapy Reseach Journal, vol. 1, pp. 1-2, 2017. View at: Google Scholar
  5. S. Zhao, T. Jiang, L. Zhang et al., “Clinicopathological and prognostic significance of regulatory T cells in patients with non-small cell lung cancer: a systematic review with meta-analysis,” Oncotarget, vol. 7, no. 24, pp. 36065–36073, 2016. View at: Publisher Site | Google Scholar
  6. G. Tarro, M. Paolini, and A. Rossi, “Molecular biology of lung cancer and future perspectives for screening,” in Mass Spectrometry—Future Perceptions and Applications, pp. 1–16, IntechOpen, London, UK, 2019. View at: Publisher Site | Google Scholar
  7. N. I. Berlin, C. R. Buncher, R. S. Fontana, J. K. Frost, and M. R. Melamed, “The national cancer institute cooperative early lung cancer detection program. Results of the initial screen (prevalence). Early lung cancer detection: introduction,” American Review of Respiratory Disease, vol. 130, no. 4, pp. 545–549, 1984. View at: Google Scholar
  8. B. J. Flehinger, M. R. Melamed, M. B. Zaman, R. T. Heelan, W. B. Perchick, and N. Martini, “Early lung cancer detection: results of the initial (prevalence) radiologic and cytologic screening in the Memorial Sloan-Kettering study,” American Review of Respiratory Disease, vol. 130, no. 4, pp. 555–560, 1984. View at: Google Scholar
  9. J. K. Frost, W. C. Ball Jr., M. L. Levin et al., “Early lung cancer detection: results of the initial (prevalence) radiologic and cytologic screening in the Johns Hopkins study,” American Review of Respiratory Disease, vol. 130, no. 4, pp. 549–554, 1984. View at: Google Scholar
  10. R. S. Fontana, D. R. Sanderson, W. F. Taylor et al., “Early lung cancer detection: results of the initial (prevalence) radiologic and cytologic screening in the Mayo Clinic study,” American Review of Respiratory Disease, vol. 130, no. 4, pp. 561–565, 1984. View at: Google Scholar
  11. M. R. Melamed and B. J. Flehinger, “Screening for lung cancer,” Chest, vol. 86, no. 1, pp. 2-3, 1984. View at: Publisher Site | Google Scholar
  12. R. S. Fontana, D. R. Sanderson, L. B. Woolner, W. F. Taylor, W. E. Miller, and J. R. Muhm, “Lung cancer screening: the Mayo program,” Journal of Occupational and Environmental Medicine, vol. 28, no. 8, pp. 746–750, 1986. View at: Publisher Site | Google Scholar
  13. A. Kubík and J. Polák, “Lung cancer detection results of a randomized prospective study in Czechoslovakia,” Cancer, vol. 57, no. 12, pp. 2427–2437, 1986. View at: Publisher Site | Google Scholar
  14. P. M. Marcus, E. J. Bergstralh, R. M. Fagerstrom et al., “Lung cancer mortality in the Mayo Lung Project: impact of extended follow-up,” JNCI Journal of the National Cancer Institute, vol. 92, no. 16, pp. 1308–1316, 2000. View at: Publisher Site | Google Scholar
  15. P. M. Marcus, E. J. Bergstralh, M. H. Zweig, A. Harris, K. P. Offord, and R. S. Fontana, “Extended lung cancer incidence follow-up in the Mayo Lung Project and overdiagnosis,” JNCI: Journal of the National Cancer Institute, vol. 98, no. 11, pp. 748–756, 2006. View at: Publisher Site | Google Scholar
  16. D. R. Aberle, S. DeMello, C. D. Berg et al., “Results of the two incidence screenings in the national lung screening trial,” New England Journal of Medicine, vol. 369, no. 10, pp. 920–931, 2013. View at: Publisher Site | Google Scholar
  17. P. Leidinger, A. Keller, S. Heisel et al., “Identification of lung cancer with high sensitivity and specificity by blood testing,” Respiratory Research, vol. 11, no. 1, p. 18, 2010. View at: Publisher Site | Google Scholar
  18. D. Schottenfeld, “Patient risk factors and the detection of early cancer,” Preventive Medicine, vol. 1, no. 3, pp. 335–351, 1972. View at: Publisher Site | Google Scholar
  19. H.-Y. Wu, Y.-G. Goan, Y.-H. Chang et al., “Qualification and verification of serological biomarker candidates for lung adenocarcinoma by targeted mass spectrometry,” Journal of Proteome Research, vol. 14, no. 8, pp. 3039–3050, 2015. View at: Publisher Site | Google Scholar
  20. S. Begum, M. Brait, S. Dasgupta et al., “An epigenetic marker panel for detection of lung cancer using cell-free serum DNA,” Clinical Cancer Research, vol. 17, no. 13, pp. 4494–4503, 2011. View at: Publisher Site | Google Scholar
  21. G. Tarro, C. Esposito, A. Perna, P. P. Claudio, and A. Giordano, “Immunohistochemical characterization of tumor liberated particles (TLP) expression pattern in lung cancer,” Anticancer Research, vol. 18, no. 4A, pp. 2365–2370, 1998. View at: Google Scholar
  22. G. Tarro, A. Pederzini, G. Flaminio, and S. Maturo, “Human tumor antigens inducing in vivo delayed hypersensitivity and in vitro mitogenic activity,” Oncology, vol. 40, no. 4, pp. 248–254, 1983. View at: Publisher Site | Google Scholar
  23. G. Tarro, “Tumor liberated protein from lung cancer and perspectives for immunotherapy,” Journal of Cellular Physiology, vol. 221, no. 1, pp. 26–30, 2009. View at: Publisher Site | Google Scholar
  24. G. Tarro, “Characterization of a fragment containing a putative TLP cDNA sequence,” Anticancer Research, vol. 22, no. 5, pp. 2693–2696, 2002. View at: Google Scholar
  25. C. Esposito, G. Tarro, N. Cuomo, A. Di Spirito, and F. Morelli, “Anti-TLP antibodies in lung cancer patients,” Internal Medicine, vol. 5, pp. 191–194, 1997. View at: Google Scholar
  26. G. Tarro, A. Perna, and C. Esposito, “Early diagnosis of lung cancer by detection of tumor liberated protein,” Journal of Cellular Physiology, vol. 203, no. 1, pp. 1–5, 2005. View at: Publisher Site | Google Scholar
  27. N. A. Sophos, A. Pappa, T. L. Ziegler, and V. Vasiliou, “Aldehyde dehydrogenase gene superfamily: the 2000 update,” Chemico-Biological Interactions, vol. 130–132, no. 1–3, pp. 323–337, 2001. View at: Publisher Site | Google Scholar
  28. E. Meng, A. Mitra, K. Tripathi et al., “ALDH1A1 maintains ovarian cancer stem cell-like properties by altered regulation of cell cycle checkpoint and DNA repair network signaling,” PLoS One, vol. 9, no. 9, Article ID e107142, 2014. View at: Publisher Site | Google Scholar
  29. N. E. Sládek, “Human aldehyde dehydrogenases: potential pathological, pharmacological, and toxicological impact,” Journal of Biochemical and Molecular Toxicology, vol. 17, no. 1, pp. 7–23, 2003. View at: Publisher Site | Google Scholar
  30. Q. Zhang, A. Taguchi, M. Schliekelman et al., “Comprehensive proteomic profiling of aldehyde dehydrogenases in lung adenocarcinoma cell lines,” International Journal of Proteomics, vol. 2011, Article ID 145010, 8 pages, 2011. View at: Publisher Site | Google Scholar
  31. D. Liang and Y. Shi, “Aldehyde dehydrogenase-1 is a specific marker for stem cells in human lung adenocarcinoma,” Medical Oncology, vol. 29, no. 2, pp. 633–639, 2012. View at: Publisher Site | Google Scholar
  32. A. López-González, C. Salas, M. Provencio, M. Córdoba, and C. Gamallo, “Aldehyde dehydrogenases in early stage lung cancer: nuclear expression,” Clinical and Translational Oncology, vol. 16, no. 10, pp. 931–934, 2014. View at: Publisher Site | Google Scholar
  33. Y. Qiu, T. Pu, L. Li et al., “The expression of aldehyde dehydrogenase family in breast cancer,” Journal of Breast Cancer, vol. 17, no. 1, pp. 54–60, 2014. View at: Publisher Site | Google Scholar
  34. D. Ran, M. Schubert, I. Taubert et al., “Heterogeneity of leukemia stem cell candidates at diagnosis of acute myeloid leukemia and their clinical significance,” Experimental Hematology, vol. 40, no. 2, pp. 155–165.e1, 2012. View at: Publisher Site | Google Scholar
  35. Y. Xing, D.-Y. Luo, M.-Y. Long, S.-L. Zeng, and H.-H. Li, “High ALDH1A1 expression correlates with poor survival in papillary thyroid carcinoma,” World Journal of Surgical Oncology, vol. 12, no. 1, p. 29, 2014. View at: Publisher Site | Google Scholar
  36. X. Qian, S. Wagner, C. Ma et al., “Prognostic significance of ALDH1A1-positive cancer stem cells in patients with locally advanced, metastasized head and neck squamous cell carcinoma,” Journal of Cancer Research and Clinical Oncology, vol. 140, no. 7, pp. 1151–1158, 2014. View at: Publisher Site | Google Scholar
  37. J. P. Sullivan, M. Spinola, M. Dodge et al., “Aldehyde dehydrogenase activity selects for lung adenocarcinoma stem cells dependent on notch signaling,” Cancer Research, vol. 70, no. 23, pp. 9937–9948, 2010. View at: Publisher Site | Google Scholar
  38. Y.-T. Cao, J.-H. Li, Y.-T. Wang, Y.-W. Fu, and J. Xu, “Serum ALDH1A1 is a tumor marker for the diagnosis of non-small cell lung cancer,” Tumori Journal, vol. 100, no. 2, pp. 214–218, 2014. View at: Publisher Site | Google Scholar
  39. G. Tarro, “From sequence of tumor liberated protein (TLP) to potential targets for diagnosis and therapy,” Integrative Molecular Medicine, vol. 4, no. 3, pp. 1–3, 2017. View at: Publisher Site | Google Scholar
  40. A. Rossi, S. Schenone, A. Angelucci et al., “New pyrazolo-3,4-d-pyrimidine derivative Src kinase inhibitors lead to cell cycle arrest and tumor growth reduction of human medulloblastoma cells,” FASEB Journal, vol. 24, no. 8, pp. 2881–2892, 2010. View at: Publisher Site | Google Scholar
  41. J. Rahlff, M. Trusch, F. Haag et al., “Antigen-specificity of oligoclonal abnormal protein bands in multiple myeloma after allogeneic stem cell transplantation,” Cancer Immunology, Immunotherapy, vol. 61, no. 10, pp. 1639–1651, 2012. View at: Publisher Site | Google Scholar
  42. G. Ak, Y. Tada, H. Shimada et al., “Midkine is a potential novel marker for malignant mesothelioma with different prognostic and diagnostic values from mesothelin,” BMC Cancer, vol. 17, no. 1, p. 212, 2017. View at: Publisher Site | Google Scholar
  43. N. Willumsen, C. L. Bager, D. J. Leeming, A.-C. Bay-Jensen, and M. A. Karsdal, “Nidogen-1 degraded by cathepsin S can be quantified in serum and is associated with non-small cell lung cancer,” Neoplasia, vol. 19, no. 4, pp. 271–278, 2017. View at: Publisher Site | Google Scholar
  44. A. Klupczynska, P. Dereziński, J. Matysiak, W. Dyszkiewicz, M. Kasprzyk, and Z. J. Kokot, “Determination of 16 serum angiogenic factors in stage I non-small cell lung cancer using a bead-based multiplex immunoassay,” Biomedicine & Pharmacotherapy, vol. 88, pp. 1031–1037, 2017. View at: Publisher Site | Google Scholar
  45. V. Brower, “Biomarker studies abound for early detection of lung cancer,” JNCI Journal of the National Cancer Institute, vol. 101, no. 1, pp. 11–13, 2009. View at: Publisher Site | Google Scholar
  46. Y. Zhou, Y. Wang, X. Ju et al., “Clinicopathological significance of ALDH1A1 in lung, colorectal, and breast cancers: a meta-analysis,” Biomarkers in Medicine, vol. 9, no. 8, pp. 777–790, 2015. View at: Publisher Site | Google Scholar
  47. P. Marcato, C. A. Dean, R.-Z. Liu et al., “Aldehyde dehydrogenase 1A3 influences breast cancer progression via differential retinoic acid signaling,” Molecular Oncology, vol. 9, no. 1, pp. 17–31, 2015. View at: Publisher Site | Google Scholar
  48. M. Patel, L. Lu, D. S. Zander, L. Sreerama, D. Coco, and J. S. Moreb, “ALDH1A1 and ALDH3A1 expression in lung cancers: correlation with histologic type and potential precursors,” Lung Cancer, vol. 59, no. 3, pp. 340–349, 2008. View at: Publisher Site | Google Scholar
  49. J. S. Moreb, H. V. Baker, L.-J. Chang et al., “ALDH isozymes downregulation affects cell growth, cell motility and gene expression in lung cancer cells,” Molecular Cancer, vol. 7, no. 1, p. 87, 2008. View at: Publisher Site | Google Scholar
  50. S. A. Marchitti, D. J. Orlicky, C. Brocker, and V. Vasiliou, “Aldehyde dehydrogenase 3B1 (ALDH3B1): immunohistochemical tissue distribution and cellular-specific localization in normal and cancerous human tissues,” Journal of Histochemistry and Cytochemistry, vol. 58, no. 9, pp. 765–783, 2010. View at: Publisher Site | Google Scholar

Copyright © 2019 Alessandra Rossi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Related articles

No related content is available yet for this article.
 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

No related content is available yet for this article.

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.