- freely available
Diagnostics 2013, 3(1), 13-32; doi:10.3390/diagnostics3010013
Abstract: Lung cancer is the leading cause of cancer-related death in the United States. Here, we evaluated the potential clinical utility of soluble human epidermal growth factor receptor 2 (sHER2) for the risk assessment, screening, and diagnosis of non-small cell lung cancer (NSCLC) using an unmatched case-control study design. Serum sHER2 concentrations were measured by immunoassay in 244 primary NSCLC cases and 218 healthy controls. Wilcoxon rank-sum tests, logistic regression models, and receiver operating characteristic plots were used to assess whether sHER2 is associated with lung cancer. Median serum sHER2 concentrations are higher in patients with adenocarcinoma than squamous cell carcinoma regardless of gender, and sHER2 is a weak, independent biomarker of adenocarcinoma, but not of squamous cell carcinoma, adjusted for age and gender. The age-adjusted relative risk (odds) of adenocarcinoma is 3.95 (95% CI: 1.22, 12.81) and 7.93 (95% CI: 2.26, 27.82) greater for women and men with high sHER2 concentrations (≥6.60 ng/mL) vs. low sHER2 concentrations (≤1.85 ng/mL), respectively. When adjusted for each other, sHER2, age, and gender discern healthy controls from patients with primary adenocarcinomas of the lung with 85.9% accuracy. We conclude that even though serum sHER2 is not a strong, stand-alone discriminatory biomarker of adenocarcinoma, sHER2 may be a useful, independent covariate in multivariate risk assessment, screening, and diagnostic models of lung cancer.
Lung cancer is the leading cause of cancer-specific mortality for men and women in the U.S. [1,2,3]. The National Cancer Institute’s (NCI) Surveillance Epidemiology and End Results program estimated that 226,160 new lung cancer cases were diagnosed in the U.S. in 2012, and that 160,340 individuals died of this disease. Of all lung cancers, 99% consist of either small cell carcinomas (13.9%) or non-small cell carcinomas (85.1%). Histological subtypes of non-small cell lung cancer (NSCLC) include adenocarcinomas (37.5%), squamous and transitional cell carcinomas (19.8%), large cell carcinomas (3.3%), and other tumor subtypes (24.5%). Patients diagnosed with localized, early stage lung cancer have a 5-year survival rate of 49.5% and may be cured by surgical resection [4,5]. However, 77% of lung cancer patients have advanced stage disease at diagnosis, and their 5-year survival rate is only 20.6% for disease that has spread to the regional lymph nodes or 2.8% for disease that has metastasized to distant anatomical sites. Because patients who are diagnosed with early stage lung cancer have a significantly better prognosis, screening (i.e., early detection) represents a practical public health approach for decreasing lung cancer mortality.
Throughout the 1960s and 1970s, chest x-ray (CXR) alone or in conjunction with sputum cytology were evaluated to detect early stage lung cancer [4,5]. To assess the feasibility, validity, and efficacy of CXR for lung cancer screening, the NCI sponsored the Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized screening trial, which was designed with a “no-screening” study arm and 89% power to detect a 10% reduction in lung cancer mortality [6,7]. While awaiting PLCO trial results [8,9], contemporary researchers have focused on developing low dose computed tomography and biomarkers as potential lung cancer screening modalities [10,11,12,13,14,15,16].
The human epidermal growth factor receptor 2 (HER2/ERBB2/neu) proto-oncogene encodes a cell surface receptor tyrosine kinase (RTK) that functions to regulate cell proliferation and survival . HER2 amplification and protein overexpression have been implicated in the etiology and pathogenesis of several human malignancies including lung cancer . HER2 is overexpressed in 10–20% of NSCLC cases and in perhaps as many as 30% of lung adenocarcinomas [19,20,21,22,23], where overexpression is associated with adverse tumor characteristics and poor patient prognosis [24,25]. In addition to full-length HER2, cells synthesize “soluble” HER2 (sHER2) isoforms [26,27,28,29,30]. These sHER2 isoforms are produced either by alternate mRNA splicing or by proteolytic cleavage, and, are either secreted or proteolytically shed from the plasma membrane into extracellular body fluids. Alternate splicing results in mRNA transcripts that encode 68-kDa  and 100-kDa  sHER2 isoforms; whereas, proteolytic cleavage results in 105-kDa  and 110-kDa  shed isoforms of sHER2 that encompass only extracellular subdomains of this RTK. While it is widely assumed that the 105-kDa sHER2 isoform represents the major constituent of human blood, a careful biochemical characterization of serum sHER2 isoforms has not yet been performed. Nonetheless, multiple assays to quantify sHER2 have been developed and used to assess the potential clinical utility of serum sHER2 in cancer patients across disease sites [31,32]. In particular, serum sHER2 has been examined in preliminary studies of lung cancer, but has not yet been rigorously validated as a potential risk assessment, screening, and/or diagnostic biomarker. Initial reports suggest that serum sHER2 is elevated in 5–64% of lung cancer cases [23,32,33,34,35,36] and may be elevated many months prior to clinical diagnosis .
In this study, we evaluated 244 primary NSCLC cases and 218 healthy controls using an unmatched, retrospective, case-control study design to determine whether age and/or gender are confounders or effect modifiers of the relationship between sHER2 and NSCLC. We observed that sHER2 concentrations are associated with age among healthy men, and differ between healthy men and women. Although sHER2 concentrations do not differ between healthy controls and patients with NSCLC overall, they are slightly higher in patients with adenocarcinoma regardless of gender, but not squamous cell carcinoma. Logistic regression models further demonstrate that sHER2 is a weak, independent classifier of adenocarcinoma but not of squamous cell carcinoma, and when adjusted for age and gender, the risk of adenocarcinoma increases with higher sHER2 concentrations. Moreover, when mutually adjusted for each other, sHER2, age, and gender distinguish healthy controls from patients with adenocarcinoma with 85.9% accuracy. These data suggest that albeit serum sHER2 is not a strong, stand-alone discriminatory classifier of adenocarcinoma, its independence of age and gender may confer some limited utility to sHER2 as a covariate in multivariate models for the risk assessment, screening, and/or diagnosis of lung adenocarcinoma.
2. Materials and Methods
2.1. Serum Samples
Serum samples were collected at the Mayo Clinic, Olmsted County, Rochester, MN, and stored at −80 °C, as described in detail previously, from 218 healthy controls between 1981 to 1984, and 244 primary NSCLC cases between 1997 to 2002 through a “Normal Values Study”  and “Comprehensive Lung Cancer Resource” , respectively; both protocols were approved by the Mayo Clinic Institutional Review Board. Written informed consent was obtained from each participant and all biospecimens were redacted of the patient’s identity. Each control was annotated with age and, if female, menopausal status at venipuncture; and each lung cancer case was annotated with age, tumor histological subtype, and, if female, menopausal status at diagnosis. Information concerning disease stage and tumor grade were unavailable. The cases included 79 patients with squamous cell carcinoma (SCC) and 165 with adenocarcinoma.
2.2. sHER2 ELISA
Serum sHER2 concentrations were measured using the sp185HER-2 ELISA (Bender MedSystems Diagnostics GmbH, Vienna, Austria) according to the manufacturer’s instructions. The manufacturer reports an analytical detection limit of 0.06 ng/mL sHER2 (two standard deviations above the mean absorbance observed with sample buffer), mean intra-assay coefficient of variation of 1.9%, mean inter-assay coefficient of variation of 5.8%, and mean spike recovery of 89% with serum for this ELISA. In addition, the manufacturer reports no significant loss of serum sHER2 immunoreactivity after five freeze-thaw cycles at −20 °C or following a 24 h storage period at −20 °C, 2–8 °C, 24 °C, or 37 °C, indicating that sHER2 is not an inherently unstable serum protein.
All serum samples in the present study were initially quantified in quadruplicate at a 1:20 dilution. Serum samples yielding absorbance values outside the linear range of the assay’s standard curve, below the biological detection limit (four standard deviations above the mean absorbance observed with sample buffer), or with a coefficient of variation ≥20% were re-assayed at either a 1:10, 1:40, 1:80, or 1:120 dilution to obtain accurate estimates of serum sHER2 concentrations. We report a mean inter-assay analytical detection limit of 0.02 ng/mL, mean inter-assay biological detection limit of 0.05 ng/mL, mean intra-assay coefficient of variation of 8.27% and 8.45% with normal serum sample controls estimated to contain 3.2 and 7.7 ng/ml sHER2, respectively, and mean inter-assay coefficient of variation of 4.11% and 2.26% with low and high quality control standards supplied by the manufacturer estimated to contain 20.9 and 146.6 ng/ml sHER2, respectively.
2.3. Statistical Analysis
Statistical analyses were performed using “R” (R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org) and SAS version 9.2 (SAS Institute, Cary, NC, USA). Descriptive statistics were calculated, and the nonparametric Wilcoxon rank-sum test was used to determine whether sHER2 concentrations differ significantly between healthy controls and patients with primary NSCLC, before and after stratification by gender, tumor histology, and menopausal status. Nonparametric local weighted regression and Spearman’s rank-order correlation coefficients (ρ) were calculated to determine whether associations exist between sHER2 concentrations and age for healthy controls or patients with NSCLC by gender. Univariate and multivariate logistic regression analyses were performed to assess whether log-transformed sHER2 concentrations, age, and gender are associated with lung cancer. Logistic regression models were compared for their ability to discriminate NSCLC from control patients and adenocarcinoma from SCC tumors using the area under the curve (AUC) of receiver operating characteristic (ROC) plots, and to assess the age- and gender-adjusted effect of sHER2 on cancer risk. Statistical adjustment for multiple comparisons was performed with the step-up procedure developed by Benjamini and Hockberg (1995) to control the false discovery rate (FDR) [39,40]. FDR p-values <0.05 differ significantly between diagnostic groups; however, because this is an exploratory hypothesis generating study of a small sample size, after stratification by gender and tumor histological subtype, FDR p-values between 0.10 and 0.05 were considered to be of borderline significance.
3.1. sHER2 Concentrations Are Associated with Age in Healthy Men
This unmatched, retrospective, case-control study consists of 218 healthy controls (81 men, 137 women) and 244 patients with primary NSCLC (139 men, 105 women). The healthy men and women in this study are younger (median age: 47 and 38 years, respectively) than the men and women with NSCLC (median age: 68 and 64 years, respectively, p < 0.0001; FDR p < 0.0005, Table 1). Since the cases and controls are unbalanced with regard to both gender and age, these parameters represent potential confounders or effect modifiers of the association between serum sHER2 concentrations and a classification of NSCLC. Therefore, we assessed whether sHER2 is associated with age among healthy participants or patients with NSCLC in this study population by gender (Figure 1). These analyses show that sHER2 concentrations are not associated with age among healthy women (Figure 1(B); ρ = 0.055; p = 0.515; FDR p = 0.649), women with NSCLC (Figure 1(D); ρ = −0.082; p = 0.405; FDR p = 0.537), or men with NSCLC (Figure 1(C); ρ = −0.110; p = 0.197; FDR p = 0.298). In contrast, sHER2 concentrations decrease with age in healthy men (Figure 1(A); ρ = −0.354; p = 0.001; FDR p = 0.004). Furthermore, sHER2 concentrations do not differ between healthy premenopausal vs. postmenopausal women (p = 0.731; FDR p = 0.824), or between healthy premenopausal (p = 0.966; FDR p = 0.966) and postmenopausal (p = 0.102; FDR p = 0.169) women vs. women with NSCLC of the same menopausal status (Table 1). Stratification of NSCLC cases by histological subtype further shows that sHER2 concentrations are not associated with age among all patients with SCC (ρ = −0.045; p = 0.692; FDR p = 0.815) or adenocarcinoma (ρ = −0.063; p = 0.421; FDR p = 0.544), men with SCC (ρ = −0.095; p = 0.530; FDR p = 0.653) or adenocarcinoma (ρ = −0.113; p = 0.281; FDR p = 0.414), and women with SCC (ρ = −0.008; p = 0.963; FDR p = 0.966) or adenocarcinoma (ρ = −0.042; p = 0.726; FDR p = 0.824).
3.2. sHER2 Concentrations are Higher in Patients with Adenocarcinoma
Although sHER2 concentrations do not differ between healthy controls vs. patients with NCSLC (Table 1; p = 0.172; FDR p = 0.276), men vs. women with NSCLC (p = 0.958; FDR p = 0.966), or healthy men vs. men with NSCLC (Figure 2(A); p = 0.573; FDR p = 0.690) in univariate analyses, they are slightly higher in healthy men than healthy women (p = 0.022; FDR p = 0.051). In addition, sHER2 concentrations trend towards being higher in women with NSCLC compared to healthy women (Figure 2(B); p = 0.052; FDR p = 0.098).
|Quintiles of Serum sHER2||OR (95% CI) for Women||OR (95% CI) for Men|
|≤1.85 ng/mL||referent||1.01 (0.57, 1.78)|
|2.40 ng/mL||1.48 (1.09, 2.02)||1.49 (0.79, 2.82)|
|3.00 ng/mL||2.06 (1.16, 3.66)||2.08 (0.94, 4.62)|
|3.65 ng/mL||2.77 (1.23, 6.22)||2.79 (1.05, 7.74)|
|≥6.60 ng/mL||6.74 (1.48, 30.67)||6.78 (1.36, 33.79)|
Further comparison of NSCLC cases by histological subtype shows that serum sHER2 concentrations are slightly higher in patients with adenocarcinoma than SCC among men (Figure 2(C); Table 2; p = 0.035; borderline significance, FDR p = 0.074), among women (Figure 2(D); p = 0.044; borderline significance, FDR p = 0.086), and both genders combined (p = 0.004; FDR p = 0.012). Although sHER2 concentrations do not differ between healthy controls and patients with SCC among men (borderline significance, p = 0.084; FDR p = 0.144) or among women (p = 0.838; FDR p = 0.906), sHER2 concentrations are higher in women (p = 0.008; FDR p = 0.022) but not in men with adenocarcinoma (p = 0.794; FDR p = 0.877) compared to healthy controls of the same gender. Logistic regression models and ROC curves (Figure 3) demonstrate that unadjusted for age, log-transformed sHER2 concentrations have a statistically significant, but weak ability to differentiate patients with adenocarcinoma from SCC among men (AUC = 0.610) and women (AUC = 0.623). Furthermore, both men and women with high serum sHER2 concentrations have higher risk of having adenocarcinoma than SCC (Table 3).
3.3. sHER2 is a Weak, Independent Discriminatory Biomarker of Adenocarcinoma
Univariate logistic regression models show that both age (p < 0.0001; FDR p < 0.0005) and gender (p < 0.0001; FDR p < 0.0005), but not log-transformed sHER2 concentrations (p = 0.191; FDR p = 0.298) are associated with NSCLC when adenocarcinoma and SCC are combined (Table 4). Likewise, age (p < 0.0001; FDR p < 0.0005) and gender (p = 0.002; FDR p = 0.007), but not sHER2 concentrations (p = 0.290; FDR p = 0.415) are associated with SCC. In contrast, sHER2 concentrations (p = 0.026; borderline significance, FDR p = 0.057), age (p < 0.0001; FDR p < 0.0005), and gender (p = 0.0003; FDR p = 0.0012) are associated with adenocarcinoma. Multivariate logistic regression models further demonstrate that log-transformed sHER2 remains independently associated with adenocarcinoma (p = 0.022; FDR p = 0.051), but not SCC (p = 0.891; FDR p = 0.945) or all NSCLC tumors combined (borderline significance, p = 0.082; FDR p = 0.144) when adjusted for age and gender. ROC curves derived from univariate logistic regression models illustrate that age is a strong discriminator of healthy controls from all NSCLC tumors combined (AUC = 0.858), as well as cases diagnosed with SCC (AUC = 0.895) or adenocarcinoma (AUC = 0.840), potentially reflecting ascertainment bias; while gender is a weak discriminator of all NSCLC tumors combined (AUC = 0.594), SCC (AUC = 0.601) or adenocarcinoma (AUC = 0.591) (Table 4 and Figure 4). In contrast, log-transformed sHER2 alone does not discriminate healthy controls from all NSCLC cases combined (AUC = 0.537) or SCC (AUC = 0.539), but weakly discriminates adenocarcinoma (AUC = 0.573). When mutually adjusted for each other, sHER2, age, and gender yield 85.9% accuracy (AUC) to discern healthy controls from patients with lung adenocarcinoma across all cut-off thresholds of sHER2 (Table 4). Notably, the ability to discern healthy controls from patients with adenocarcinoma is contributed mainly by age rather than sHER2 or gender (AUC = 0.840 with age alone vs. AUC = 0.859 with age, gender, and sHER2 combined). These ROC curves further demonstrate that gender is an important confounder of age for discerning healthy controls from patients with adenocarcinoma, but not SCC (compare Figure 4(F) to 4(E) and 4(I) to 4(H)), whereby being male is a stronger determinant of adenocarcinoma than being female. For example, ROC curves that include age and sHER2 (or age alone, Figure 4(F)) show statistically significantly better discrimination of healthy controls vs. patients with adenocarcinoma among men (AUC = 0.91) than among women (AUC = 0.78) (Figure 4(I)); notably, the sensitivity to detect adenocarcinoma is 60% for men, but only 30% for women at 95% specificity (Figure 4(I)). Adjusted for age and gender, the risk of adenocarcinoma increase with higher serum sHER2 concentrations (Table 5). For example, adjusted for age, the odds of adenocarcinoma are 3.95 (95% CI: 1.22, 12.81) among women and 7.93 (95% CI: 2.26, 27.82) among men at a value of >6.60 ng/mL sHER2 compared to the referent value of <1.85 ng/mL. The confounding effect of gender on age is not observed in logistic regression models that include age and sHER2 (or age alone) for patients with SCC (Figure 4(E)); i.e., men (AUC = 0.91) and women (AUC = 0.91) with SCC are discriminated equally well from healthy controls of the same gender by age alone (Figure 4(H)). Finally, no evidence of effect modification by age or gender on the association between serum sHER2 and NSCLS, adenocarcinoma, or SCC is observed in this dataset (not shown). Taken together, these analyses show that age and gender are classifiers of NSCLC, SCC, and adenocarcinoma; as well as confounders of the association between sHER2 and adenocarcinoma in this dataset. Nevertheless, serum sHER2 remains a weak, statistically significant, independent discriminatory biomarker of lung adenocarcinoma, but not of SCC, after adjusting for age and gender.
|Univariate Logistic Regression Models|
|Patient GroupsParameters||Maximum Likelihood Estimate||Standard Error||Wald Χ2||Χ2/FDRPvalue||AUC|
|All Lung Cancer Cases vs. Controls|
|Squamous Cell Carcinomas vs. Controls|
|Adenocarcinomas vs. Controls|
|Multivariate Logistic Regression Models|
|Patient GroupsParameters||Maximum Likelihood Estimate||Standard Error||Wald Χ2||Χ2/FDRPvalue||AUC|
|All Lung Cancer Cases vs. Controls|
|Squamous Cell Carcinomas vs. Controls|
|Adenocarcinomas vs. Controls|
|Quintiles of Serum sHER2||OR (95% CI) for Women||OR (95% CI) for Men|
|≤1.85 ng/mL||referent||2.01 (1.19, 3.39)|
|2.40 ng/mL||1.32 (1.04, 1.68)||2.66 (1.52, 4.66)|
|3.00 ng/mL||1.69 (1.08, 2.64)||3.38 (1.74, 6.57)|
|3.65 ng/mL||2.08 (1.11, 3.90)||4.18 (1.90, 9.21)|
|≥6.60 ng/mL||3.95 (1.22, 12.81)||7.93 (2.26, 27.82)|
Steroid hormones have been implicated in the regulation of HER2 expression; however, the age and gender specific effects of steroids on HER2 expression, as well as on sHER2 shedding is not completely understood. In human breast cancer cells in vitro, estradiol is a potent inhibitor of HER2 expression and sHER2 shedding [41,42,43,44]; whereas, progesterone positively regulates HER2 expression . In contrast, neither estrogen nor progesterone regulates HER2 expression in ovarian cancer cells . Among men with prostate cancer, high HER2 expression has been associated with androgen ablation therapy and androgen independent prostate carcinoma . Among healthy women, oral contraceptive use and hormone replacement therapy have been associated with lower serum sHER2 concentrations . In pregnant women, serum sHER2 concentrations are lower during the first and second trimester in pregnant women, which is when estrogen concentrations increase, but are higher during the third trimester [49,50,51]. Finally, elevated serum sHER2 concentrations among women with preeclampsia vs. a normal pregnancy suggest the possibility of fetomaternal transfer during the third trimester of pregnancy [49,52]. Together, these observations suggest that steroid hormones may regulate both the biosynthesis and shedding of sHER2 into circulatory fluids. Our observations that sHER2 concentrations decrease with age in healthy men, and that age and gender confound the relationship between sHER2 concentrations and lung adenocarcinoma are consistent with hormonal regulation of HER2 expression and/or shedding. These observations underscore the importance of adjusting for age, gender, and other potential confounding variables that may affect steroid hormone biosynthesis, such as body mass and smoking [53,54], when evaluating the utility of sHER2 for the risk assessment, early detection, and diagnosis of adenocarcinoma using epidemiological study designs and multivariate statistical methods.
Limitations and caveats of this retrospective study include: (a) an inability to assess the effect of long term storage at −80 °C on serum sHER2 stability, (b) an inability to assess potential differences in serum sHER2 concentrations between non-small cell adenocarcinomas compared to large or small cell carcinomas; (c) an inability to assess potential differences in serum sHER2 concentrations by disease stage or tumor grade; (d) lack of data on potential confounders or effect modifiers of sHER2 concentrations such as smoking status, body mass, personal and family cancer history, carcinogen exposure, menstrual cycle phase, parity, and exogenous hormone use among women; (e) potential ascertainment and cohort bias of the control group, which was not selected using the same enrollment criteria (e.g., age and smoking status) or at random during the same time period from the source population as the cases; and (f) an inability to assess the risk of developing lung adenocarcinoma among asymptomatic individuals with pre-diagnostic serum samples. Given these caveats and limitations, it will be important to conduct well-designed transitional studies to assess the effects of storage at −80 °C on serum sHER2 concentrations, and prospective case-control studies to further validate sHER2 as a weak, independent biomarker of lung adenocarcinoma using multivariate models. Such studies should include incident cases of lung adenocarcinoma, other malignant and benign lung neoplasms, and healthy controls selected randomly from the study population.
Several reports indicate that serum sHER2 concentrations have 5–64% sensitivity to detect lung cancer of various histological subtypes using cut-off thresholds that correctly classify healthy controls with 95% specificity [23,32,33,34,35,36]. Sensitivity was reported to be higher for patients with late stage lung cancer and for patients with adenocarcinoma compared to SCC, large cell carcinoma, and small cell carcinoma [23,32,34,35]. In general, these studies were small, used disparate immunoassays, or used previously established cut-off thresholds from an external control study group . Additionally, most of these studies did not control for confounding by age, gender, and other variables such as smoking by using a matched, case-control study design or by adjusting for confounding in an unmatched, case-control study design with multivariate logistic regression methods [23,32,34,35,36]. Notably, the highest reported sensitivity (64%) and specificity (95%) of sHER2 concentrations to discern healthy controls from lung cancer cases was reported for a small age-, gender-, ethnic group-, and smoking-matched case-control study . That age might be a potential confounder or effect modifier of the association between sHER2 and cancer is supported by our observation that sHER2 concentrations decrease with age in healthy men, and by a previous report showing that sHER2 concentrations increase with age in healthy women independently of menopausal status . Here, it is observed that sHER2 concentrations are higher in primary NSCLC patients with adenocarcinoma than SCC, thus confirming that biological differences exist between these histological subtypes. Moreover, we report that the ability of sHER2 concentrations to discern healthy controls from patients with adenocarcinoma, but not SCC, is indeed confounded by age and gender in our dataset (Table 4 and Figure 4). When mutually adjusted for each other, sHER2, age, and gender yield 85.9% accuracy to classify controls from primary adenocarcinoma patients (Table 4). However, the strength to discern healthy controls from patients with adenocarcinoma is contributed mainly by age, not sHER2 and gender (AUC = 0.840 with age alone vs. AUC = 0.859 with age, gender, and sHER2 combined). The accuracy to discern adenocarcinoma patients from controls with age-adjusted sHER2 concentrations is 91% among men, but only 78% among women (Figure 4(I)), suggesting that additional confounders may be influencing the association between sHER2 and adenocarcinoma among women. Notably, at 95% specificity, the sensitivity to detect adenocarcinoma is 60% for men and 30% for women; these statistics are similar to those reported by Brandt-Rauf and colleagues, who used a matched case-control study design to control for confounding by age, gender, ethnicity, and smoking . Importantly, the data reported here show that sHER2 is a weak, but statistically significant, independent classifier of adenocarcinoma. Although sHER2 is not a strong, stand-alone classifier of adenocarcinoma, its independence of age and gender may make sHER2 a useful covariate (with age, gender, and other biomarkers) in multivariate screening and diagnostic models of lung adenocarcinoma.
Risk prediction models that include smoking are useful for advising patients about their propensity to develop lung cancer. However, while smoking is a well-known risk factor for lung cancer, considered alone, smoking history has limited ability to predict which smokers will develop lung cancer. Other contributing epidemiological, clinical, and biological (i.e., biomarkers) factors may improve lung cancer risk prediction among smokers and even non-smokers [56,57]. Several groups have developed lung cancer risk models using the variables of age, smoking history, carcinogen exposure, and family history [58,59,60,61,62,63,64]. However, few of these studies included serum biomarkers, despite our understanding that biomarkers represent promising risk assessment tools [56,57,59,64]. Recently, Spitz and colleagues modestly improved their risk model, which included environmental tobacco smoke, family cancer history, dust exposure, prior respiratory disease, hay fever, and smoking history variables by adding two in vitro markers of DNA repair capacity (host-cell reactivation and mutagen sensitivity) . Adding these markers significantly improved the model’s accuracy to discriminate between lung cancer cases and controls from 67% to 70% among former smokers (p = 0.006), and from 68% to 73% among current smokers (p = 0.0048). Similarly, Prindiville and colleagues found that sputum samples characterized by moderate to worse cytological atypia defined a cohort of high-risk patients who were at increased risk of developing lung cancer . Notably, we observe that, adjusted for age, the relative risk (odds) of adenocarcinoma is 3.95 (95% CI: 1.22, 12.81) among women and 7.93 (95% CI: 2.26, 27.82) among men with high sHER2 concentrations (≥6.60 ng/mL) compared to women or men with low sHER2 concentrations (≤1.85 ng/mL; Table 5). These data are consistent, but not conclusive, with a role for serum sHER2 as a biological marker of risk for primary non-small cell lung adenocarcinoma.
Cancer treatment is undergoing a paradigm shift from the use of broad-spectrum cytotoxic chemotherapeutics to biologically targeted therapeutics , including HER-targeted drugs . The HER family of receptors, EGFR/HER1, HER2, HER3, and HER4 are rational targets for anti-cancer drugs because they activate complex signal transduction pathways that lead to tumor cell proliferation, survival, and metastasis . In patients with NSCLC, EGFR-targeted RTK inhibitors, such as gefitinib and erlotinib, have produced objective response rates in about 10% of patients with advanced stage disease and modest improvements in patient survival [70,71,72]. Clinical trials with HER2-targeted monoclonal antibodies, trastuzumab and pertuzumab, also have shown efficacy in some NSCLC patients [70,73,74]; however, trials with trastuzumab have been insufficiently powered to determine whether NSCLC patients with HER2 gene amplification or overexpression as determined by immunohistochemistry may benefit from treatment [75,76]. Notably, responsiveness and efficacy toward HER-targeted therapeutics is dependent on the selection of patients who present with the active target of choice, and accurate methods to identify these patients [77,78]. Here, we observe that serum sHER2 concentrations detected by ELISA are higher in a subset of primary NSCLC patients with adenocarcinoma (adjusted for age, 60% of men and 30% of women had sHER2 concentrations above the 95th cut-off threshold for healthy controls), suggesting that sHER2 may warrant investigation as a theragnostic biomarker to select a subset of patients with lung adenocarcinoma for treatment with HER2-targeted drugs.
In summary, we have observed that serum sHER2 concentrations are higher in a subset of patients with primary adenocarcinoma compared to patients with SCC or healthy controls, and weakly, but independently associated with adenocarcinoma even after adjusting for confounding by age and gender. These results are consistent with the hypothesis that sHER2 may have some limited clinical utility as a serum biomarker of non-small cell lung adenocarcinoma, if properly adjusted for confounding by age, gender, and variables that affect circulating and tissue steroid hormone concentrations (e.g., body mass, smoking, oral contraceptive use, and hormone replacement therapy) or circulating steroid hormones themselves. We conclude that even though serum sHER2 is not a strong, stand-alone discriminatory biomarker of adenocarcinoma, sHER2 may be a useful, independent covariate in multivariate regression models that warrants further investigation for the risk assessment, screening, and diagnosis of lung adenocarcinoma in well-designed epidemiological studies that control for confounding by age, gender, and other demographical, epidemiological, behavioral, and environmental variables using multivariate regression methods or a matched case-control study design.
The authors thank Jason Wilken, Bethany Cox, Ben Mauhgan, Nathan Vanderford, and Susan Ernst for a careful editorial review of this manuscript. Grant support: National Institutes of Health/National Cancer Institute grants K07 CA76170, R21 CA82520, and RO3 CA82091 (to A.T. Baron); U01 CA85133 and the Prospect Creek Foundation (to N.J. Maihle); and RO1 CA80127 and RO3 CA77118 (to P. Yang).
- Altekruse, S.F.; Kosary, C.L.; Krapcho, M.; Neyman, N.; Aminou, R.; Waldron, W.; Ruhl, J.; Howlader, N.; Tatalovich, Z.; Cho, H.; et al. SEER Cancer Statistics Review, 1975–2007. Available online: http://seer.cancer.gov/csr/1975_2007 (accessed on 17 November 2012).
- Siegel, R.; Naishadham, D.; Jemal, A. Cancer statistics, 2012. CA Cancer J. Clin. 2012, 62, 10–29. [Google Scholar] [CrossRef]
- Jemal, A.; Siegel, R.; Xu, J.; Ward, E. Cancer statistics, 2010. CA Cancer J. Clin. 2010, 60, 277–300. [Google Scholar] [CrossRef]
- Bach, P.B.; Kelley, M.J.; Tate, R.C.; McCrory, D.C. Screening for lung cancer: A review of the current literature. Chest 2003, 123, 72–82. [Google Scholar] [CrossRef]
- Bach, P.B.; Niewoehner, D.E.; Black, W.C. Screening for lung cancer: The guidelines. Chest 2003, 123, 83–88. [Google Scholar] [CrossRef]
- Gohagan, J.K.; Prorok, P.C.; Hayes, R.B.; Kramer, B.S. The prostate, lung, colorectal and ovarian (PLCO) cancer screening trial of the national cancer institute: History, organization, and status. Control. Clin. Trials 2000, 21, 251–272. [Google Scholar] [CrossRef]
- Prorok, P.C.; Andriole, G.L.; Bresalier, R.S.; Buys, S.S.; Chia, D.; Crawford, E.D.; Fogel, R.; Gelmann, E.P.; Gilbert, F.; Hasson, M.A.; et al. Design of the prostate, lung, colorectal and ovarian (PLCO) cancer screening trial. Control. Clin. Trials 2000, 21, 273–309. [Google Scholar] [CrossRef]
- Oken, M.M.; Marcus, P.M.; Hu, P.; Beck, T.M.; Hocking, W.; Kvale, P.A.; Cordes, J.; Riley, T.L.; Winslow, S.D.; Peace, S.; et al. Baseline chest radiograph for lung cancer detection in the randomized prostate, lung, colorectal and ovarian cancer screening trial. J. Natl. Cancer Inst. 2005, 97, 1832–1839. [Google Scholar] [CrossRef]
- Pinsky, P.F.; Miller, A.; Kramer, B.S.; Church, T.; Reding, D.; Prorok, P.; Gelmann, E.; Schoen, R.E.; Buys, S.; Hayes, R.B.; Berg, C.D. Evidence of a healthy volunteer effect in the prostate, lung, colorectal, and ovarian cancer screening trial. Am. J. Epidemiol. 2007, 165, 874–881. [Google Scholar] [CrossRef]
- Marcus, P.M. Lung cancer screening: An update. J. Clin. Oncol. 2001, 19, 83–86. [Google Scholar]
- Nawa, T.; Nakagawa, T.; Kusano, S.; Kawasaki, Y.; Sugawara, Y.; Nakata, H. Lung cancer screening using low-dose spiral CT*: Results of baseline and 1-year follow-up studies. Chest 2002, 122, 15–20. [Google Scholar] [CrossRef]
- Ma, P.C.; Blaszkowsky, L.; Bharti, A.; Ladanyi, A.; Kraeft, S.K.; Bruno, A.; Skarin, A.T.; Chen, L.B.; Salgia, R. Circulating tumor cells and serum tumor biomarkers in small cell lung cancer. Anticancer Res. 2003, 23, 49–62. [Google Scholar] [PubMed]
- Brambilla, C.; Fievet, F.; Jeanmart, M.; de Fraipont, F.; Lantuejoul, S.; Frappat, V.; Ferretti, G.; Brichon, P.Y.; Moro-Sibilot, D. Early detection of lung cancer: Role of biomarkers. Eur. Respir. J. Suppl. 2003, 39, 36–44. [Google Scholar]
- Chanin, T.D.; Merrick, D.T.; Franklin, W.A.; Hirsch, F.R. Recent developments in biomarkers for the early detection of lung cancer: perspectives based on publications 2003 to present. Curr. Opin. Pulm. Med. 2004, 10, 242–247. [Google Scholar] [CrossRef]
- Hilbe, W.; Dirnhofer, S.; Greil, R.; Woll, E. Biomarkers in non-small cell lung cancer prevention. Eur. J. Cancer Prev. 2004, 13, 425–436. [Google Scholar] [CrossRef]
- Yang, S.Y.; Xiao, X.Y.; Zhang, W.G.; Zhang, L.J.; Zhang, W.; Zhou, B.; Chen, G.; He, D.C. Application of serum SELDI proteomic patterns in diagnosis of lung cancer. BMC Cancer 2005, 5. [Google Scholar] [CrossRef]
- Hirsch, F.R.; Varella-Garcia, M.; Cappuzzo, F. Predictive value of EGFR and HER2 overexpression in advanced non-small-cell lung cancer. Oncogene 2009, 28 Suppl 1, S32–S37. [Google Scholar] [PubMed]
- Hynes, N.E.; Stern, D.F. The biology of erbB-2/neu/HER-2 and its role in cancer. Biochim Biophys Acta 2009, 1198, 165–184. [Google Scholar]
- Shi, D.; He, G.; Cao, S.; Pan, W.; Zhang, H.Z.; Yu, D.; Hung, M.C. Overexpression of the c-erbB-2/neu-encoded p185 protein in primary lung cancer. Mol. Carcinog. 1992, 5, 213–218. [Google Scholar] [CrossRef]
- Harpole, D.H., Jr.; Marks, J.R.; Richards, W.G.; Herndon, J.E., II; Sugarbaker, D.J. Localized adenocarcinoma of the lung: Oncogene expression of erbB-2 and p53 in 150 patients. Clin. Cancer Res. 1995, 1, 659–664. [Google Scholar] [PubMed]
- Scheurle, D.; Jahanzeb, M.; Aronsohn, R.S.; Watzek, L.; Narayanan, R. HER-2/neu expression in archival non-small cell lung carcinomas using FDA-approved Hercep test. Anticancer Res. 2000, 20, 2091–2096. [Google Scholar] [PubMed]
- Pellegrini, C.; Falleni, M.; Marchetti, A.; Cassani, B.; Miozzo, M.; Buttitta, F.; Roncalli, M.; Coggi, G.; Bosari, S. HER-2/Neu alterations in non-small cell lung cancer: A comprehensive evaluation by real time reverse transcription-PCR, fluorescence in situ hybridization, and immunohistochemistry. Clin. Cancer Res. 2003, 9, 3645–3652. [Google Scholar] [PubMed]
- Heinmoller, P.; Gross, C.; Beyser, K.; Schmidtgen, C.; Maass, G.; Pedrocchi, M.; Ruschoff, J. HER2 status in non-small cell lung cancer: results from patient screening for enrollment to a phase II study of herceptin. Clin. Cancer Res. 2003, 9, 5238–5243. [Google Scholar] [PubMed]
- Tateishi, M.; Ishida, T.; Mitsudomi, T.; Kaneko, S.; Sugimachi, K. Prognostic value of c-erbB-2 protein expression in human lung adenocarcinoma and squamous cell carcinoma. Eur. J. Cancer 1991, 27, 1372–1375. [Google Scholar] [CrossRef] [PubMed]
- Kern, J.A.; Slebos, R.J.; Top, B.; Rodenhuis, S.; Lager, D.; Robinson, R.A.; Weiner, D.; Schwartz, D.A. C-erbB-2 expression and codon 12 K-ras mutations both predict shortened survival for patients with pulmonary adenocarcinomas. J. Clin. Invest. 1994, 93, 516–520. [Google Scholar] [CrossRef] [PubMed]
- Zabrecky, J.R.; Lam, T.; McKenzie, S.J.; Carney, W. The extracellular domain of p185/neu is released from the surface of human breast carcinoma cells, SK-BR-3. J. Biol. Chem. 1991, 266, 1716–1720. [Google Scholar] [PubMed]
- Pupa, S.M.; Menard, S.; Morelli, D.; Pozzi, B.; De Palo, G.; Colnaghi, M.I. The extracellular domain of the c-erbB-2 oncoprotein is released from tumor cells by proteolytic cleavage. Oncogene 1993, 8, 2917–2923. [Google Scholar] [PubMed]
- Scott, G.K.; Robles, R.; Park, J.W.; Montgomery, P.A.; Daniel, J.; Holmes, W.E.; Lee, J.; Keller, G.A.; Li, W.L.; Fendly, B.M. A truncated intracellular HER2/neu receptor produced by alternative RNA processing affects growth of human carcinoma cells. Mol. Cell. Biol. 1993, 13, 2247–2257. [Google Scholar] [CrossRef] [PubMed]
- Codony-Servat, J.; Albanell, J.; Lopez-Talavera, J.C.; Arribas, J.; Baselga, J. Cleavage of the HER2 ectodomain is a pervanadate-activable process that is inhibited by the tissue inhibitor of metalloproteases-1 in breast cancer cells. Cancer Res. 1999, 59, 1196–1201. [Google Scholar] [PubMed]
- Doherty, J.K.; Bond, C.; Jardim, A.; Adelman, J.P.; Clinton, G.M. The HER-2/neu receptor tyrosine kinase gene encodes a secreted autoinhibitor. Proc. Natl. Acad. Sci. USA 1999, 96, 10869–10874. [Google Scholar] [CrossRef] [PubMed]
- Brandt-Rauf, P.W. The c-erbB transmembrane growth factor receptors as serum biomarkers in human cancer studies. Mutat. Res. 1995, 333, 203–208. [Google Scholar] [CrossRef] [PubMed]
- Molina, R.; Jo, J.; Filella, X.; Bruix, J.; Castells, A.; Hague, M.; Ballesta, A.M. Serum levels of C-erbB-2 (HER-2/neu) in patients with malignant and non-malignant diseases. Tumour Biol. 1997, 18, 188–196. [Google Scholar] [CrossRef]
- Brandt-Rauf, P.W.; Luo, J.C.; Carney, W.P.; Smith, S.; De Vivo, I.; Milling, C.; Hemminki, K.; Koskinen, H.; Vainio, H.; Neugut, A.I. Detection of increased amounts of the extracellular domain of the c-erbB-2 oncoprotein in serum during pulmonary carcinogenesis in humans. Int. J. Cancer 1994, 56, 383–386. [Google Scholar] [CrossRef]
- Osaki, T.; Mitsudomi, T.; Oyama, T.; Nakanishi, R.; Yasumoto, K. Serum level and tissue expression of c-erbB-2 protein in lung adenocarcinoma. Chest 1995, 108, 157–162. [Google Scholar] [CrossRef]
- Yoshimura, C.; Nomura, S.; Yamaoka, M.; Ohtani, T.; Matsuzakiz, T.; Yamaguchi, K.; Fukuharal, S. Analysis of serum ErbB-2 protein and HLA-DRB1 in Japanese patients with lung cancer. Cancer Lett. 2000, 152, 87–95. [Google Scholar] [CrossRef]
- Filiberti, R.; Marroni, P.; Paganuzzi, M.; Izzo, V.; Padovani, P.; Cafferata, M.; Ardizzoni, A.; Neri, M.; Raimondi, L.; Puntoni, R. c-erbB-2 protein in serum of primary lung cancer patients. Cancer Detect. Prev. 2002, 26, 64–68. [Google Scholar] [CrossRef]
- Baron, A.T.; Lafky, J.M.; Connolly, D.C.; Peoples, J.; O'Kane, D.J.; Suman, V.J.; Boardman, C.H.; Podratz, K.C.; Maihle, N.J. A sandwich type acridinium-linked immunosorbent assay (ALISA) detects soluble ErbB1 (sErbB1) in normal human sera. J. Immunol. Method. 1998, 219, 23–43. [Google Scholar] [CrossRef]
- Yang, P.; Allen, M.S.; Aubry, M.C.; Wampfler, J.A.; Marks, R.S.; Edell, E.S.; Thibodeau, S.; Adjei, A.A.; Jett, J.; Deschamps, C. Clinical features of 5,628 primary lung cancer patients: experience at Mayo Clinic from 1997 to 2003. Chest 2005, 128, 452–462. [Google Scholar] [CrossRef]
- Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B 1995, 57, 289–300. [Google Scholar]
- Storey, J.D.; Tibshirani, R. Statistical methods for identifying differentially expressed genes in DNA microarrays. Meth. Mol. Biol. 2003, 224, 149–157. [Google Scholar]
- Dati, C.; Antoniotti, S.; Taverna, D.; Perroteau, I.; De Bortoli, M. Inhibition of c-erbB-2 oncogene expression by estrogens in human breast cancer cells. Oncogene 1990, 5, 1001–1006. [Google Scholar] [PubMed]
- Read, L.D.; Keith, D., Jr.; Slamon, D.J.; Katzenellenbogen, B.S. Hormonal modulation of HER-2/neu protooncogene messenger ribonucleic acid and p185 protein expression in human breast cancer cell lines. Cancer Res. 1990, 50, 3947–3951. [Google Scholar] [PubMed]
- Warri, A.M.; Laine, A.M.; Majasuo, K.E.; Alitalo, K.K.; Harkonen, P.L. Estrogen suppression of erbB2 expression is associated with increased growth rate of ZR-75-1 human breast cancer cells in vitro and in nude mice. Int. J. Cancer 1991, 49, 616–623. [Google Scholar] [CrossRef] [PubMed]
- Warri, A.M.; Isola, J.J.; Harkonen, P.L. Anti-oestrogen stimulation of ERBB2 ectodomain shedding from BT-474 human breast cancer cells with ERBB2 gene amplification. Eur. J. Cancer 1996, 32A, 134–140. [Google Scholar] [PubMed]
- Taverna, D.; Antoniotti, S.; Maggiora, P.; Dati, C.; De Bortoli, M.; Hynes, N.E. erbB-2 expression in estrogen-receptor-positive breast-tumor cells is regulated by growth-modulatory reagents. Int. J. Cancer. 1994, 56, 522–528. [Google Scholar] [CrossRef] [PubMed]
- Jones, J.; Lagasse, L.D.; Karlan, B.Y. Steroid hormonal independence of HER-2/neu mRNA expression in four human ovarian carcinoma cell lines. Gynecol. Oncol. 1994, 55, 421–426. [Google Scholar] [CrossRef]
- Shi, Y.; Brands, F.H.; Chatterjee, S.; Feng, A.C.; Groshen, S.; Schewe, J.; Lieskovsky, G.; Cote, R.J. Her-2/neu expression in prostate cancer: High level of expression associated with exposure to hormone therapy and androgen independent disease. J. Urol. 2001, 166, 1514–1519. [Google Scholar] [CrossRef] [PubMed]
- Meden, H.; Mielke, S.; Marx, D.; Wuttke, W.; Kuhn, W. Hormonal treatment with sex steroids in women is associated with lower p105 serum concentrations. Anticancer Res. 1997, 17, 3075–3077. [Google Scholar] [PubMed]
- Meden, H.; Mielke, S.; Schauer, A.; Kuhn, W. Serum levels of the c-erbB-2 (HER2/neu) encoded oncoprotein fragment p105 in normal pregnancies. In Vivo 1997, 11, 51–54. [Google Scholar] [PubMed]
- Meden, H.; Mielke, S.; Wuttke, W.; Kuhn, W. Elevated serum levels of the c-erbB-2 encoded oncoprotein fragment in cases of pure preeclampsia and HELLP syndrome. J. Obstet Gynaecol. Res. 1997, 23, 213–217. [Google Scholar] [CrossRef] [PubMed]
- Mielke, S.; Meden, H.; Kuhn, W. Expression of the c-erbB-2-encoded oncoprotein p185 (HER-2/neu) in pregnancy as a model for oncogene-induced carcinogenesis. Med. Hypotheses 1998, 50, 359–362. [Google Scholar] [CrossRef]
- Meden, H.; Mielke, S.; Wuttke, W.; Kuhn, W. Increased serum level of c-erbB-2-coded protein p105 in patients with pre-eclampsia. Gynakologisch-geburtshilfliche Rundschau 1995, 35 Suppl 1, 157–160. [Google Scholar] [CrossRef] [PubMed]
- Windham, G.C.; Mitchell, P.; Anderson, M.; Lasley, B.L. Cigarette smoking and effects on hormone function in premenopausal women. Environ. Health Perspect. 2005, 113, 1285–1290. [Google Scholar] [CrossRef] [PubMed]
- Shiels, M.S.; Rohrmann, S.; Menke, A.; Selvin, E.; Crespo, C.J.; Rifai, N.; Dobs, A.; Feinleib, M.; Guallar, E.; Platz, E.A. Association of cigarette smoking, alcohol consumption, and physical activity with sex steroid hormone levels in US men. Cancer Cause. Control 2009, 20, 877–886. [Google Scholar] [CrossRef]
- Breuer, B.; Smith, S.; Osborne, M.P.; Simmons, R.M.; Carney, W.P.; Brandt-Rauf, P.W. ErbB-2 protein levels in healthy, asymptomatic women. Biomarkers 1996, 1, 141–143. [Google Scholar] [CrossRef] [PubMed]
- Field, J.K. Lung cancer risk models come of age. Cancer Prev. Res. 2008, 1, 226–228. [Google Scholar] [CrossRef]
- Freedman, A.N.; Seminara, D.; Gail, M.H.; Hartge, P.; Colditz, G.A.; Ballard-Barbash, R.; Pfeiffer, R.M. Cancer risk prediction models: A workshop on development, evaluation, and application. J. Nat. Cancer Inst. 2005, 97, 715–723. [Google Scholar] [CrossRef] [PubMed]
- Bach, P.B.; Kattan, M.W.; Thornquist, M.D.; Kris, M.G.; Tate, R.C.; Barnett, M.J.; Hsieh, L.J.; Begg, C.B. Variations in lung cancer risk among smokers. J. Nat. Cancer Inst. 2003, 95, 470–478. [Google Scholar] [CrossRef]
- Cassidy, A.; Duffy, S.W.; Myles, J.P.; Liloglou, T.; Field, J.K. Lung cancer risk prediction: A tool for early detection. Int. J. Cancer 2007, 120, 1–6. [Google Scholar] [PubMed]
- Cassidy, A.; Myles, J.P.; van Tongeren, M.; Page, R.D.; Liloglou, T.; Duffy, S.W.; Field, J.K. The LLP risk model: An individual risk prediction model for lung cancer. Brit. J. Cancer 2008, 98, 270–276. [Google Scholar] [CrossRef]
- Cronin, K.A.; Gail, M.H.; Zhaohui, Z.; Bach, P.B.; Virtamo, J.; Albanes, D. Validation of a model of lung cancer risk prediction among smokers. J. Nat. Cancer Inst. 2006, 98, 637–640. [Google Scholar] [CrossRef]
- Etzel, C.J.; Kachroo, S.; Liu, M.; D’Amelio, A.; Dong, Q.; Cote, M.L.; Wenzlaff, A.S.; Hong, W.K.; Greisinger, A.J.; Schwartz, A.G.; Spitz, M.R. Development and validation of a lung cancer risk prediction model for African-Americans. Cancer Prev. Res. 2008, 1, 255–265. [Google Scholar] [CrossRef]
- Peto, R.; Darby, S.; Doll, R.; Deo, H.; Silcocks, P.; Whitley, E. Smoking, smoking cessation, and lung cancer in the UK since 1950: Combination of national statistics with two case-control studies. Brit. Med. J. 2000, 321, 323–329. [Google Scholar] [CrossRef] [PubMed]
- Spitz, M.A.; Waun Ki, H.; Amos, C.I.; Xifeng, W.; Schabath, M.B.; Qiong, D.; Sanjay, S.; Etzel, C.J. A risk model for prediction of lung cancer. J. Nat. Cancer Inst. 2007, 99, 715–726. [Google Scholar] [CrossRef]
- Spitz, M.R.; Etzel, C.J.; Dong, Q.; Amos, C.I.; Wei, Q.; Wu, X.; Hong, W.K. An expanded risk prediction model for lung cancer. Cancer Prev. Res. 2008, 1, 250–254. [Google Scholar] [CrossRef]
- Prindiville, S.A.; Byers, T.; Hirsch, F.R.; Franklin, W.A.; Miller, Y.E.; Vu, K.O.; Wolf, H.J.; Barón, A.E.; Shroyer, K.R.; Zeng, C.; et al. Sputum cytological atypia as a predictor of incident lung cancer in a cohort of heavy smokers with airflow obstruction. Canc. Epidemiol. Biomarkers Prev. 2003, 12, 987–993. [Google Scholar]
- Blay, J.-Y.; Le Cesne, A.; Alberti, L.; Ray-Coquart, I. Targeted cancer therapies. Bull. Cancer 2005, 92, E13–E18. [Google Scholar] [CrossRef]
- Bacus, S.; Spector, N.L.; Yarden, Y. The era of ErbB-receptor-targeted therapies: Advances toward personalized medicine. Personalized Med. 2005, 2, 301–315. [Google Scholar] [CrossRef]
- Baselga, J.; Albanell, J. Epithelial growth factor receptor interacting agents. Hematol. Oncol. Clin. N. Amer. 2002, 16, 1041–1063. [Google Scholar] [CrossRef]
- Metro, G.; Finocchiaro, G.; Toschi, L.; Bartolini, S.; Magrini, E.; Cancellieri, A.; Trisolini, R.; Castaldini, L.; Tallini, G.; Crino, L.; Cappuzzo, F. Epidermal growth factor receptor (EGFR) targeted therapies in non-small cell lung cancer (NSCLC). Rev. Recent Clin. Trials 2006, 1, 1–13. [Google Scholar] [CrossRef]
- Friedrich, M.J. Using EGFR status to personalize treatment: Lung cancer researchers reach a milestone. J. Nat. Cancer Inst. 2009, 101, 1039–1041. [Google Scholar] [CrossRef]
- Perez-Soler, R. Individualized therapy in non-small-cell lung cancer: Future versus current clinical practice. Oncogene 2009, 28 Suppl 1, S38–S45. [Google Scholar] [CrossRef]
- Johnson, B.E.; Jänne, P.A. Rationale for a phase II trial of pertuzumab, a HER-2 dimerization inhibitor, in patients with non-small cell lung cancer. Clin. Cancer Res. 2006, 12, 4436–4440. [Google Scholar] [CrossRef]
- Yamamoto, N.; Nambu, Y.; Fujimoto, T.; Koshiji, M. A landmark point analysis with cytotoxic agents for advanced NSCLC. J. Thoracic Oncol. 2009, 4, 697–701. [Google Scholar] [CrossRef]
- Zinner, R.G.; Glisson, B.S.; Fossella, F.V.; Pisters, K.M.; Kies, M.S.; Lee, P.M.; Massarelli, E.; Sabloff, B.; Fritsche, H.A., Jr.; Ro, J.Y.; et al. Trastuzumab in combination with cisplatin and gemcitabine in patients with Her2-overexpressing, untreated, advanced non-small cell lung cancer: report of a phase II trial and findings regarding optimal identification of patients with Her2-overexpressing disease. Lung Cancer 2004, 44, 99–110. [Google Scholar] [CrossRef]
- Swanton, C.; Futreal, A.; Eisen, T. Her2-targeted therapies in non-small cell lung cancer. Clin. Cancer Res. 2006, 12, 4377–4383. [Google Scholar] [CrossRef]
- Yatabe, Y. Molecular diagnosis of solid tumors. Nippon Rinsho. Jpn. J. Clin. Med. 2005, 63, 434–440. [Google Scholar]
- Allison, M. The HER2 testing conundrum. Nat. Biotechnol. 2010, 28, 117–119. [Google Scholar] [CrossRef] [PubMed]
© 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).