Patent Publication Number: US-2009220985-A1

Title: Rapid efficacy assessment method for lung cancer therapy

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     Under 37 CFR § 120, this application is a division of U.S. application Ser. No. 11/306,532 filed Dec. 31, 2005, which claims the benefit of U.S. Provisional Application No. 60/596,104, filed Sep. 1, 2005, which is incorporated herein by reference. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates generally to methods for assessment of carcinoma cancer therapy and relapse detection, and more specifically it relates to an efficacy assessment method for lung cancer therapy to rapidly predict the outcome of lung cancer therapy so treatment with higher likelihood of success can be selected to prevent invalid treatment from wrecking patents, and a routine monitoring method for cancer relapse after the treatment. 
     2. Description of the Related Art 
     Lung cancer is the leading cause of cancer-related death and non-small cell lung cancer (NSCLC) accounts for ˜80% of the cases. Attempts to use serum protein markers for the early diagnosis of lung cancer have not yielded satisfactory results for routine screening, and newly developed early diagnostic methods using serum DNA as a diagnostic marker await further validation. Current therapeutic measures remain unable to lower the mortality rate of late-stage lung cancer patients. Surgical resection is still the best cure for the early-stage patients. The tumor, node, metastasis (TNM) classification has been used for cancer staging and prognosis for decades. A large portion of early-stage patients, defined by the current staging system and available imaging modalities, still develop distant metastases although they received surgical removal of the tumor mass. The inability to detect disseminated tumor cells with the current imaging techniques is a major obstacle to accurate cancer staging. 
     NSCLC is heterogeneous with respect to histology and biological characteristics. Individual NSCLC cells within a tumor and in different patients&#39; tumors express different amounts of marker gene transcripts. The heterogeneity of marker gene expression levels in NSCLC cells limits the reliability of an assay method with a single-marker detection scheme. Several literature reports have described PCR methods for the detection of tumor cells dispersed in the circulation. However, not one tumor marker is consistently and specifically expressed in all of the primary tumors of a particular malignancy. Literature reports have also shown that a panel of marker genes provides a more reliable and informative approach than a single-marker assay for the detection of melanoma and breast cancer cells in blood. Such assays for lung cancer have been limited by the availability of molecular markers. 
     The presence of epithelial cancer cells in the bone marrow and in the peripheral blood of patients with carcinoma has been reported in literature reports and prior arts. In contrast to bone marrow aspirates, peripheral blood samples can be obtained routinely and more readily. Carcinoma accounts for around 85% of human cancers and the carcinoma cells are of epithelial cell lineage. Techniques such as immunocytology and flow cytometry have been employed in prior arts to detect circulating cancer cells in the peripheral blood. However, both techniques are based on extracting or labeling intact carcinoma cells in circulation by antibodies targeting specifically to the epithelial cell surface antigens such as EpCAM and others. Malignant carcinoma cancer cells often are de-differentiated and lose the characteristic epithelial cell surface antigens. In addition, it is known in cancer research field that EpCAM gene expression is often suppressed to facilitate tumor metastasis. Therefore, the antibody based detection methods have been reported to have low positive detection rates or high false negative rates. Polymerase chain reaction (PCR) has been employed to detect disseminated tumor cells in peripheral blood. Several literature reports have described the use of PCR for detecting circulating cancer cells in the peripheral blood of patients of various cancers. For instance, Peck et al., reported the use of cytokeratin 19 as the maker gene for detecting circulating cancer cells in NSCLC patients with an overall positive detection rate around 40%. 
     Compared with immunocytology and flow cytometry, PCR has the advantages that it is more readily available, less involved in the operating procedures, less instrument cost, and others. On the other hand, PCR is not able to yield the number of counts of circulating cancer cell in a sample like the other two techniques. 
     To overcome the current technology difficulties in achieving high positive detection rate and rapid assessment of lung cancer therapy efficacy and relapse detection, a panel of marker genes for achieving high positive detection rate by qPCR and a quantitative analysis method for predicting lung cancer treatment outcome and for prognosis are needed. 
     SUMMARY OF THE INVENTION 
     The present invention fulfills the needs in lung cancer treatment by teaching a rapid efficacy assessment method for lung cancer therapy and relapse detection. 
     The purpose of the present invention is to teach an assessment method for lung cancer therapy. More especially, it teaches a rapid efficacy assessment method for lung cancer therapy by identifying and employing a panel of marker genes for real-time quantitative PCR (qPCR) assay to quantitatively measure the amount of circulating lung cancer cells in body fluids. 
     Another purpose of the present method is to teach a method for cancer relapse detection by using real time qPCR with a panel of marker genes for detecting circulating lung cancer cells in body fluids. 
     The present invention identifies a panel of markers for the detection of circulating cancer cells in NSCLC patients by in silico analysis of the National Cancer Institute-Cancer Genome Anatomy Project database. The present invention also teaches a quantitative analysis method to calculate load of cancer cells in the circulation. The quantitative analysis method yields results that are highly correlated with the treatment outcomes of lung cancer patients and serves to predict the treatment outcome in a short time after the treatment is administered. 
     The method of assessing lung cancer therapy comprises: collecting a body fluid from a subject, extracting total RNA of the body fluid sample, employing qPCR to amplify marker gene transcripts of total RNA for detecting cancer cells in body fluid, and analyzing qPCR threshold cycle number with a set of mathematical formulae. 
     The present invention further teaches a method to translate expression level of multiple gene transcripts measured by qPCR to the amount of circulating lung cancer cells which is termed cancer cell load (Lc) in this invention. 
     The present invention further teaches a scoring method and mathematical formulae for calculating cancer cell load, Lc, and predicting lung cancer treatment outcome with the Lc value. 
     The present invention now will be described more fully hereinafter with reference to the accompanying drawings, which are intended to be read in conjunction with both this summary, the detailed description and any preferred and/or particular embodiments specifically discussed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention will become apparent upon reading the following detailed description of the present invention in conjunction with the drawings, as follows: 
         FIG. 1  shows the analysis of positive detection rates with a panel of 4 marker genes. A, positive detection rate for the individual four marker genes. B, positive detection rate increases with the number of marker genes used in the assay. 
         FIG. 2  shows the correlation of Lc value with the concentration of cancer cell number in peripheral blood. A, plot to show that Lc value is linearly correlated with the number of circulating cancer cells. Inset, Lc value versus the number of cancer cells between 0 and 480 cells/mL of peripheral blood. B, median survival time for patients of various TNM stages and with high (≧1) or low (&lt;1) Lc values. Inset, survival time of patient classified by the TNM staging method. Bars, standard deviation (SD). 
         FIG. 3  shows the survival analysis of late stage patients with high (≧1) or low (&lt;1) Lc values. A, Kaplan-Meier survival plots of late TNM stage patients (IIIb and IV). B, Kaplan-Meier survival plots for the same late stage patients grouped by the Lc value. C, Kaplan-Meier survival plots for the stage IIIb patients grouped by the Lc value. D, Kaplan-Meier survival plots for the stage IV patients grouped by the Lc value. 
         FIG. 4  shows lung cancer therapy efficacy assessment with circulating cancer cell detection for six different NSCLC patients. Median survival time of each patient is indicated in the figure panels. The designations for the treatment and sampling day are described in the text. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The present invention is directed to a method for lung cancer therapy assessment and a method of cancer relapse detection. Unlike current imaging assessment methods, the present invention provides a rapid assessment that uses multiple marker genes in qPCR assay for detecting circulating lung cancer cells in body fluids. 
     Compared with immunohistology and flow cytometry assessment methods, the present invention requires no additional antibody antigen interaction process. Extra molecular recognition process reduces the detection rate. Compared with the RT-PCR detection method for circulating cancer cell in prior art, using a panel of marker genes instead of a single marker gene improves the detection rate. On the other hand, it is not trivial to quantitatively analyze and integrate the expression level of multiple transcripts in a qPCR assay and correlating the analysis results to predict treatment outcome. The present invention teaches a set of mathematical formulae which yield results well correlated with lung cancer treatment outcome. 
     The multiple marker genes that may be selected include, but are not limited to, keratin 19 (KRT19), ubiquitin thiolesterase (UCHL1), fibronectin 1 (FN1), and tripartite motif-containing 28 (TRIM28). 
     The method of the present invention for rapid lung cancer therapy efficacy assessment comprises the following steps: 
     collecting a body fluid sample from a human subject; 
     extracting total RNA from said body fluid sample; 
     amplifying a panel of gene transcripts of said total RNA by qPCR; 
     measuring the expression level of each gene transcript in said panel of gene transcripts of said total RNA from a number of healthy controls and lung cancer patients, wherein a qPCR threshold cycle number is used to represent the expression level of the gene transcripts; 
     deriving a reference threshold score using the qPCR threshold cycle numbers of the gene transcripts in the panel measured for healthy controls and lung cancer patients; 
     calculating an indicative score using the qPCR threshold cycle numbers of the gene transcripts in the panel measured for a lung cancer patient both before and after therapy; and 
     determining therapy efficacy by comparing the indicative scores obtained before and after therapy. 
     The formulae used in this invention to calculate the values in these steps can be found in the section “Quantitative Analysis (Scoring) of the PCR Results” below. 
     In the present invention, the body fluids are collected from, but not limit to, peripheral blood or pleural effusion. 
     In the present invention, the number of multiple gene transcripts selected for amplification is more than two. 
     In the present invention, the nucleic acid extraction is done without prior antibody/antigen interaction or other molecular recognition processes to isolate cancer cells from normal blood cells. 
     In the present invention, the quantitative analysis for therapy efficacy is performed as early as one day after the therapeutic regimen is administered. 
     The method of the present invention for cancer relapse detection comprises the following steps: 
     collecting a body fluid sample from a human subject; 
     extracting total RNA from said body fluid sample; 
     amplifying a panel of gene transcripts of said total RNA by qPCR; 
     measuring the expression level of each gene transcript in said panel of gene transcripts of said total RNA from a number of healthy controls and lung cancer patients, wherein a qPCR threshold cycle number is used to represent the expression level of the gene transcripts; 
     deriving a reference threshold score using the qPCR threshold cycle numbers of the gene transcripts in the panel measured for healthy controls and lung cancer patients; 
     calculating an indicative score using the qPCR threshold cycle numbers of the gene transcripts in the panel measured for a lung cancer patient; and 
     determining the presence of circulating lung cancer cells by comparing the indicative scores with the reference threshold score. 
     Without further elaboration, it is believed that one skilled in the art can, using the preceding description, utilize the present invention to its fullest extent. The practice of the present invention will employ, unless otherwise indicated, conventional techniques of cell biology, molecular biology, and biochemistry which are within the skill of the art. Such techniques are explained fully in the literature. The following examples are, therefore, to be considered as merely illustrative, and not limitative of the remainder of the disclosure in any way. 
     Materials and Methods 
     Patients and Specimens 
     Peripheral blood samples were obtained with informed consent from 54 patients with histologically documented NSCLC in the National Taiwan University Hospital. Staging procedures included chest radiography, bronchoscopy, brain and thoracic computed tomography, sonography, and bone scintigraphy. The follow-up period of the lung cancer patients was up to 85 months for stage I patients who were still alive in May 2003. The normal control population consisted of 24 healthy volunteers with no history or present diagnosis of malignancy. Among the 54 patients, 32 were men and 22 were women with median age of 65 years (SD=11, range=28-81). In the healthy control group, 16 were men and 8 were women with median age of 57.5 years (SD=15.1, range=27-78). Adenocarcinoma lung cancer cell lines (A549, CL3, H928, CL1-0, CL1-5, CRL-5865, CRL-5806, and CRL-5807) and squamous carcinoma lung cancer cell lines (NCI-H520, H2981, CRL-5802, and HTB-54) were used to validate the candidate markers and for analyzing the correlation between Lc value and cancer cell number. 
     Sample Collection and RNA Preparation 
     The blood sample collection and RNA preparation methods were the same as described by Peck et al. (Peck, Cancer Res. 58:2761-2765, 1998) Briefly, two samples were collected from each subject with Vacutainers (Becton Dickinson, Rutherford, N.J.). The first tube with 1 to 2 mL of peripheral blood was discarded and only the second tube with 3 to 4 mL of blood was assayed to avoid epithelial cell contamination by the needle when it pierced through the skin. Total RNA was extracted with the QIAamp RNA Blood Mini kit (Qiagen, Hiden, Germany) within 2 hours after the blood samples were collected. 
     Identification of Candidate Marker Genes 
     To take advantage of the vast information of the expressed sequence tags databases generated with cancer cell lines, we used the cDNA Digital Gene Expression Displayer developed by the Cancer Genome Anatomy Project (Strausberg, J. Pathol, 195:31-40, 2001) to identify genes that were differentially expressed between lung cancer cells and leukocytes. The Digital Gene Expression Displayer program identified differentially expressed genes among 47,036 sequences in five lung cancer cDNA libraries and 21,460 sequences in six leukocyte cDNA libraries with a P filter set at 0.01. The differentially expressed genes were ranked by sequence odds ratio. The genes with the highest sequence odds ratios were selected as candidate marker genes for quantitative PCR (qPCR) assay. The in silico Digital Gene Expression Displayer program search of the National Cancer Institute-Cancer Genome Anatomy Project database yielded 85 overexpressed genes with a sequence odds ratio &gt;16 between the lung cancer cDNA libraries and the leukocyte cDNA libraries. These candidate genes were further verified by real-time quantitative PCR (qPCR). All of the cancer cell lines are listed as above and pooled and peripheral blood mononuclear cells from 12 healthy controls were used as samples in the first round verification. Fifty-nine candidate marker genes showed &gt;2-fold differential expression ratios, but only 19 genes had differential expression ratios &gt;100,000. Marker genes with large differential expression ratios are required to detect rare circulating cancer cells in blood samples containing millions of peripheral blood mononuclear cells. By using qPCR to detect the presence of 19 candidate genes in the clinical specimens of 54 NSCLC patients and 24 normal controls, four marker genes including KRT19 were identified to show positive detection in at least two NSCLC patients. The four marker genes are listed in Table 1. 
     The first three marker genes had negligible expression in the blood samples of normal controls by the qPCR assay and are labeled as genes A to C. The fourth gene, labeled as gene D, had high expression in the cancer patient group versus the normal control group, but had residual expression in normal peripheral blood mononuclear cells. Therefore, the present invention sets the positive detection threshold at 99% confidence interval in the normal control group to avoid false positive detection. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 List of a panel of four marker genes 
               
            
           
           
               
               
               
               
            
               
                 Gene 
                 Title 
                 RefSeq no. 
                 GeneID 
               
               
                   
               
            
           
           
               
               
               
               
            
               
                 A 
                 keratin 19 (KRT19) 
                 NM_002276 
                 3880 
               
               
                 B 
                 ubiquitin thiolesterase (UCHL1) 
                 NM_004181 
                 7345 
               
               
                 C 
                 fibronectin 1 (FN1) 
                 NM_054034 
                 2335 
               
               
                 D 
                 tripartite motif-containing 28 (TRIM28) 
                 NM_005762 
                 10155 
               
               
                   
               
            
           
         
       
     
     Quantitative PCR Assay 
     To detect a few cancer cells in the circulation, a highly sensitive PCR amplification is necessary. cDNA was derived from 1 to 2 μg of total RNA by random primed reverse transcription, and nested PCR was used to amplify the candidate marker gene transcripts for detection. The primer sets for qPCR amplification are listed in Table 1 of U.S. Provisional Application No. 60/596,104, filed Sep. 1, 2005, from which priority benefit is claimed by this application and which is incorporated herein. The first round (outer) of the nested PCR was done using 1 μL of 20-fold diluted cDNA with a PCR mixture containing 0.1 μmol/L outer primer pair, 0.2 mmol/L deoxynucleotide triphosphate, 50 mmol/L Tris-HCl (pH 8.3), 10 mmol/L KCl, 5 mmol/L (NH 4 ) 2 SO 4 , 2 mmol/L MgCl 2 , and 0.75 units of FastStart Taq DNA polymerase (Roche, Mannheim, Germany) in a total volume of 12.5 μL. The PCR conditions were one cycle at 94° C. for 7 minutes followed by 25 cycles at 94° C. for 50 seconds, 60° C. for 50 seconds, 72° C. for 35 seconds, and a final extension at 72° C. for 10 minutes. 
     For the second round (inner) of the nested PCR amplification, quantitative measurement was performed with qPCR assay. The reaction mixture contained 2 μL of the first round PCR product, 0.25 μmol/L inner primers, and SYBR Green PCR master mix (Applied Biosystems, Foster City, Calif.) in a total volume of 20 μL. The qPCR assays were done with an ABI prism 7000 SDS (Applied Biosystems) instrument. The qPCR condition was 95° C. for 10 minutes followed by 40 cycles at 95° C. for 15 seconds, 60° C. for 25 seconds, and 72° C. for 35 seconds. 
     Quantitative Analysis (Scoring) of the PCR Results 
     By using a qPCR instrument, the threshold cycle (C T ), the fractional cycle number at which the SYBR Green I fluorescence exceeded a set level above baseline, was determined. We used GAPDH mRNA as an internal control. The relative amount of mRNA, normalized against the GAPDH mRNA, was expressed as  C T =C T   (GAPDH) −C T   (marker gene) . If the fluorescence signal was undetected after 40 cycles, the C T  value was given the maximum cycle number of 40 for analysis convenience. The differential expression ratio of a candidate marker gene, Q, for patients versus normal controls was calculated by Q=2   mean of      in normal . To estimate the number of circulating cancer cells, we normalized the differential expression ratio of each marker gene to take into account the different amount of the marker gene transcripts in cancer cells. We then summed up the expression ratios of the marker genes to estimate the cancer cell load in the circulation in a semi-quantitative way. Cancer cells and their gene expression profiles are heterogeneous in individuals. To take the heterogeneity of gene expression in different patients into account, the expression of marker genes need to be normalized among test subjects. The formula for normalizing the expression ratio, E ij , of a marker gene is E ij =(Q ij −Q j )/σ j , where i is the patient index, j is the marker gene index, Q ij  is the differential expression ratio of marker gene j in patient i, Q j  is the mean and σ j  is the standard deviation (SD) of the expression ratios of the 54 patients for marker gene j. The load of cancer cells, Lc, in the circulation of a patient is defined as Lc=ΣE j  where n is the number of marker genes. In this study, the load of cancer cell, Lc, is used as an indicative score for the amount of circulating cancer cells. The value of Lc ranged between −2.2 and 8.4. 
     Statistical Analysis 
     Fisher&#39;s exact test and Student&#39;s t test were used to compare the clinicopathologic characteristics of patients with low and high Lc values. All statistical tests were two sided. Survival time of the patients was calculated from the day of specimen collection. Survival curves were obtained by the Kaplan-Meier method. The difference of survival times between two groups was analyzed with the log-rank test. P&lt;0.05 was considered statistically significant. 
     Embodiment 1 
     Enhancement of Positive Detection Rate with Multiple Marker Genes 
     As shown in  FIG. 1A , the positive detection rate of circulating cancer cells in NSCLC patients was 41%, 11%, 39%, and 11% for genes A to D, respectively. The fractions of positives among all the patients are indicated in the columns. 
     Increasing the number of marker genes raised the positive detection rate for NSCLC patients to 72% (39 of 54) compared with 41% (22 of 54) positive detection rate using the KRT19 marker gene alone ( FIG. 1B ). These results prove that using multiple markers indeed improves the positive detection rate. The B marker gene was not detected in squamous cell lung cancer patients, but the other three genes were detected in patients with adenocarcinoma or squamous cell carcinoma. 
     Embodiment 2 
     Circulating Cancer Cell Load and Patient Outcome 
     To investigate the correlation between the number of circulating cancer cells and patient outcome, the present invention used cancer cell load Lc (see MATERIALS AND METHODS) as a measure to indicate the number of cancer cells in circulation. 
     By definition, Lc increases with the number of circulating cells. The correlation between the number of circulating cancer cells and Lc values can be determined by spiking different numbers of lung cancer cells (CL1-0) into peripheral blood mononuclear cells ( FIG. 2A ). The present invention shows a good correlation (r=0.99) between cancer cell number and Lc value. 
     The data shown in  FIGS. 2B and 3  indicate that patients of the same stage who had higher Lc had worse outcomes. The results indicate that Lc measurement is a supplementary tool to the traditional TNM staging method to better predict the outcome of cancer patients. 
     To determine whether Lc can be used as an indicator of patient outcome, the present invention analyzed the Lc value versus the survival time of stage I to IIIa patients who received surgical resection. We found that patients who survived for more than 5 years had Lc values less than 1. Therefore, we set Lc=1 as the reference threshold score for the subsequent prognosis studies in the 54 lung cancer patients. The study divided the patients at different stages into two groups (Lc≧1 or Lc&lt;1) and examined their survival time. As expected, late-stage patients had shorter survival times than did early-stage patients ( FIG. 2B , inset). The cancer load (Lc) study further distinguished that for patients of the same stage, those with low Lc had longer survival time than those with high Lc value ( FIG. 2B ). For the operable early-stage patients, the survival time is highly correlated (P=0.002) with Lc value. The Lc value was then used to analyze the prognosis of late-stage patients (stages IIIb and IV) with Kaplan-Meier survival plots. The survival time difference was more significant by using Lc as a classification parameter ( FIG. 3B , P=0.006) than by using the traditional TNM classification ( FIG. 3A , P=0.03). The number of patients in each group is shown in parentheses in the figures. We further used the Lc parameter to divide the patients of the same stage into low (Lc&lt;1) and high (Lc≧1) value groups and examined the survival plots. The survival time of stage IIIb patients with low and high Lc value was significantly different ( FIG. 3C , P=0.026). The same analysis on stage IV patients did not achieve statistical significance ( FIG. 3D , P=0.09). These prognosis studies establish using Lc=1 as the reference threshold score for detecting the presence of circulating lung cancer cells. 
     Using the four marker genes and setting the reference threshold score to 1, the positive detection rates of patients with circulating cancer cells were 67% (4 of 6) for stage I, 100% (4 of 4) for stage II, 67% (6 of 9) for stage IIIa, 67% (14 of 21) for stage IIIb, and 79% (11 of 14) for stage IV. The detection rate indicates the sensitivity of using the four markers for detecting the presence of circulating NSCLC cells. 
     Embodiment 3 
     Assessment of Therapy Efficacy 
       FIG. 4  shows the assessment of six patients before and after therapy. The stage I, II, and IIIa patients received surgical resection, whereas the stage IIIb and IV patients received chemotherapy. “d-n” indicates that the samples were collected n days before therapy, “dn” indicates that the samples were collected on the nth day after therapy, and “n/” indicates the course number of chemotherapy. The stage I patient had negative Lc values before and after treatment and was still alive on the last follow-up date (72.3 months). The Lc values decreased for the stage II and IIIb patients after therapy. The stage IIIa and IV patients had higher Lc values after the last course of treatment and had short survival times. These results suggest that measurement of the cancer cell load, Lc, can be used to reveal whether therapy is efficacious. 
     Embodiment 4 
     Relapse Detection 
     In  FIG. 4  the stage IIIb patient&#39;s treatment was efficacious and the Lc value decreased after the first treatment. However, the Lc value went back up to exceed 1 and the patient was given a second course of treatment on the next day. The second treatment for the stage IIIb was assessed to be effective by the method disclosed in this invention on the fifth day after the treatment. The survival time was 60.8 months for the patient. The last example in  FIG. 4  was a stage IV patient. The Lc value decreased on the second day of the treatment. The Lc value of the patient went up again to exceed 1 in a follow-up examination and a second treatment was given on the next day. However, the second treatment failed to completely eradicate the cancer cells and the Lc value kept rising with time. The patient had a survival time of 8.6 months. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Clinicopathologic characteristics and their 
               
               
                 correlation with Lc value of NSCLC patients 
               
            
           
           
               
               
               
               
            
               
                   
                   
                 Lc 
                   
               
            
           
           
               
               
               
               
               
            
               
                   
                 Characteristic 
                 Low 
                 High 
                 P 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
            
               
                   
                 Age (y), mean ± SD 
                 63.6 ± 10.5 
                 61.3 ± 13.0 
                 0.549* 
               
            
           
           
               
            
               
                 Gender, no. patients 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Male 
                 20 
                 20 
                 0.03 
               
               
                   
                 Female 
                 20 
                 2 
               
            
           
           
               
            
               
                 Smoking, no. patients 
               
            
           
           
               
               
               
               
               
            
               
                   
                 No 
                 24 
                 7 
                 0.546 
               
               
                   
                 Yes 
                 16 
                 7 
               
            
           
           
               
            
               
                 Histology, no. patients 
               
            
           
           
               
               
               
               
               
            
               
                   
                 Adenocarcinoma 
                 25 
                 10 
                 0.442 
               
               
                   
                 Squamous cell 
                 12 
                 2 
               
               
                   
                 carcinoma 
               
               
                   
                 Poorly differentiated 
                 3 
                 2 
               
            
           
           
               
            
               
                 Stage† 
               
            
           
           
               
               
               
               
               
            
               
                   
                 I-IIIa 
                 14 
                 5 
                 1.0  
               
               
                   
                 IIIb-IV 
                 26 
                 9 
               
               
                   
                   
               
               
                   
                 *Derived with Student&#39;s t test; other Ps were derived with Fisher&#39;s exact test. All statistical tests were two-sided. 
               
               
                   
                 †Tumor stage was classified according to the International System for Staging Lung Cancer. 
               
            
           
         
       
     
     The percentage of patients with high Lc value is greater for the late-stage patients than for the early-stage patients except for the stage II patients. The invention study looked into this issue and found that the markers have different detection rates for different histologic types of NSCLC. The markers are more sensitive for detecting squamous carcinoma (85.7%; 12 of 14) compared with adenocarcinomas (68.6%; 24 of 35) and others (60%, 3 of 5). An investigation on the histologic types of the NSCLC patients revealed that the available stage II patients were composed of three (75%) squamous carcinoma and one (25%) adenocarcinoma patients, whereas the other stage patients were composed of 11% to 33% squamous carcinoma, 50% to 71% adenocarcinoma, and 5% to 22% poorly differentiated cell type patients. The higher detection rate of the stage II patients can therefore be attributed to the limited number of clinical samples and their histologic composition. 
     The data shows that detection of circulating cancer cells is a valid supplement to the TNM method for better cancer staging. The two methods combined together provide better information for designing lung cancer treatment strategies. In the study of this invention, the 5-year survival rate of early-stage (I-IIIa) NSCLC patients was 30% to 50% after surgical resection. This invention teaches a more precise staging method by including detection of circulating cancer cells to aid in deciding whether adjuvant therapeutic regimens in addition to tumor resection are beneficial to the patients. 
     At present, a reliable serologic biomarker assay for assessing the treatment response of NSCLC patients is not available. Two courses of chemotherapy are traditionally given before imaging is done to evaluate the treatment response of NSCLC patients. It showed in lung cancer patients that the Lc could be used for monitoring therapeutic response and relapse. Because different cancer cell types have different levels of marker gene expression, patients with higher Lc values do not necessarily have more circulating cancer cells in their peripheral blood than do patients with lower Lc values. Nevertheless, the semiquantitative approach is useful for measuring the relative cancer cell load in a patient&#39;s peripheral blood to monitor the effectiveness of treatment. The present method highlights an alternative approach to rapidly assess the treatment response of NSCLC patients. Compared with imaging methods which take weeks to detect the change of tumor size for therapy efficacy assessment, the invention teaches a method capable of assessing therapy efficacy on the next day of treatment as shown in  FIG. 4 . The method of the present invention may therefore help to design more comprehensive and reasonable therapeutic regimens at earlier dates for NSCLC patients. 
     Unless defined otherwise, the meanings of all technical and scientific terms used herein are those commonly understood by one of ordinary skill in the art to which this invention belongs. One of ordinary skill in the art will also appreciate that any methods and materials similar or equivalent to those described herein can also be used to practice or test the invention. Further, all publications mentioned herein are incorporated by reference. 
     Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.