| Lung cancer is currently the most common malignancy,of which the mortality and morbidity have increased in all regions of the world.In China,lung cancer is the first male cancer incidence and mortality rate,the second rate of female cancer incidence,the first mortality rate.Lung cancer is divided into small cell lung cancer and non-small cell lung cancer.NSCLC is the most common pathological type of lung cancer,accounting for more than 80% of new lung cancer cases.The pathological types of NSCLC include: lung squamous cell carcinoma and lung adenocarcinoma.At present,the 5-year survival rate of NSCLC patients is approximately 10%-15%,but the 10-year survival rate can be as high as 92% with the early diagnosis and surgery in stage I NSCLC patients.However,early clinical manifestations of lung cancer patients are not obvious,resulting in more than 70% of newly diagnosed patients loss of surgical opportunities.So early detection,early diagnosis and early treatment are the key to extend the survival of patients,improving the quality of life.The current commonly used methods to diagnosis lung cancer include pathology,medical imaging and lung cancer markers.The most commonly used method of pathology diagnosis is fine needle aspiration biopsy.However,some patients are not easy to take biopsy through the puncture because of its risk.Film degree exam,which is the most commonly used means of the initial diagnosis in lung cancer,is expensive and patients have to be exposed to the rays.Early lung cancer patients with cancer cells is far less than imaging markers can be measured as the minimum threshold.tumor markers as the most commonly used lung cancer screening means,the sensitivity and specificity are not enough clinical needs.The above three conventional methods to diagnose lung cancer are difficult to achieve early diagnosis of lung cancer.Therefore,a convenient means for early diagnosis of NSCLC is needed.Although anti-angiogenesis therapy,immunotherapy and targeted therapy have been approved by the FDA as a second-line or multi-line treatment for patients with advanced lung squamous cell carcinoma,the clinical treatment of advanced lung squamous cell carcinoma still remain in the stage of traditional chemotherapy.Chemotherapy with platinum is still the main first-line treatment for patients with advanced squamous cell carcinoma.Clinical observations have found that some patients with lung squamous cell carcinoma exposed to the toxic effects of chemotherapy but failed to benefit from treatment.Individual gene markers such as ERCC1,RRM1,TUBB3 and XRCC1 were less predictive for the efficacy of cytotoxic drug responses,which need expand the sample validation.Therefore,finding effective means to predict chemotherapy efficacy for patients with lung squamous cell carcinoma plays an important role in benefitting from chemotherapy and reducing the toxicity of chemotherapy.Now proteomics has been widely used in blood,urine and other body fluids in a variety of tumor research.In this study,We studied the role of proteomics in the diagnosis and treatment of lung cancer patientsin order to achieve a better diagnose and treat in patients with NSCLC.First Part Detection of serum and urine specific differential peptides between non-small cell lung cancer patients and healthy person by MALDI-TOF mass spectrometerPurpose:In this study,the difference of peptides between NSCLC patients and healthy subjects was detected by matrix-assisted laser ionization time-of-flight mass spectrometry(MALDI-TOF-MS).Furthermore,we established the diagnostic model and pathological classification model of NSCLC patients.Content:Blood and urine samples collected from NSCLC patients,who have been diagnosed in histopathology or cytology from October 2014 to April 2016 in the Department of Lung Cancer in our Hospital.There were 82 cases of serum samples and 41 cases of urine samples collected from lung squamous cell carcinoma,82 cases of serum samples and 41 cases of urine samples of lung adenocarcinoma.Healthy serum and urine samples were taken from volunteers,including 115 samples of serum samples and 74 cases of urine samples.MALDI-TOF-MS was used to detect the serum and urine samples.The diagnostic model and pathological classification model of NSCLC were obtained by CPT software analysis.The established model can be used for early screening of patients with NSCLC,making diagnosis and pathology more accurate.Method:Serum and urine samples of NSCLC patients were randomly divided into training group and validation group according to the ratio of 3: 1.The training group was used to establish the diagnosis and pathological classification model of NSCLC patients.The validation group was used to validate the established diagnostic and pathological classification model.MB-IMAC-Cu2+ was used to extract the peptides from serum and urine samples.MALDI-TOF-MS was used to detect serum and urine peptide fingerprints of NSCLC patients compared with healthy person.Three different biological algorithms of the Clin Pro Tools(CPT)software were used to establish the diagnostic model.Select the optimal algorithm for the establishment of NSCLC patients with serum and urine diagnostic models.The application validation group performs blind verification of the established diagnostic model.Result:All the 164 cases of NSCLC patients' serum(82 cases of squamous cell carcinoma of the squamous cell carcinoma),82 cases of NSCLC patients' urine(41 cases of squamous cell carcinoma of the squamous cell carcinoma)and 115 cases of healthies' serum,and 74 cases of healthies' urine were randomly divided into training group and validation group according to the ratio of 3: 1.The training group consisted of 124 patients with NSCLC patients' serum samples(62 cases of squamous cell carcinoma of squamous cell carcinoma),62 cases of NSCLC patients' urine samples(31 cases of squamous cell carcinoma of squamous cell carcinoma)and 85 cases of healthies' serum samples,54 cases of healthies' urine samples to establish the diagnosis and pathological classification model of NSCLC patients.The validation group consisted of 40 cases of NSCLC patients' serum samples(20 cases of squamous cell carcinoma of squamous cell carcinoma)and 20 cases of NSCLC patients' urine samples(10 cases of squamous cell carcinoma of squamous cell carcinoma)and 30 cases of healthies' serum samples,20 cases of healthies' urine samples to verify the established diagnosis and pathological classification model.The training group sought differential peptides in the range of 800-10000 Da and found statistically significant difference polypeptide(p <0.001).NSCLC patients vs healthy people,searching serum samples found 107 differentiated peptides,including 52 statistically significant differentiated peptides.The optimal algorithm for the diagnostic model was GA.The diagnostic model of the NSCLC model is composed of five peptides(2105.93 Da,867.25 Da,4093.08 Da,7651.25 Da,5341.39Da).The recognition rate of the model is 96.77%,and the cross validation rate is 89.86%.The accuracy of the model was 92.9%(65/70),the sensitivity was 95.0%(38/40),and the sensitivity was 95.9%(38/40),the specificity was 90%(27/30).There were 131 differentially expressed peptides in the urine samples,and 19 peptides were statistically significant.The optimal algorithm for the diagnostic model was SNN.The diagnostic model of the NSCLC model is composed of five peptides(1718.26 Da,2193.17 Da,1378.24 Da,812.56 Da,2376.22 Da,5954.38 Da,5810.98 Da,2812.4Da,2438.33Da).The recognition rate of the model was 98.25% and the cross validation rate was 91.74%.The accuracy of the model was 90%(36/40),the sensitivity was 95%(19/20)and the specificity was 85.0%(17/20).Comparison of serum and urine peptides found a same statistical significant peptide: 3242 Da,identified as fibrinogen ?.Lung squamous cell carcinoma vs lung adenocarcinoma,96 differentially expressed peptides were found in blood samples.There were 20 differential peptides with statistical significance.The optimal model of the classification model was GA.The pathologic model was established by five peptides(9312.15 Da,3242.37 Da,4213.52 Da,5297.33 Da,4645.83Da).The recognition rate of the model is 90.1% and the cross validation rate is 75.65%.The model is verified by the verification model with the accuracy rate is 82.5 %(33/40).The sensitivity was 85.0%(17/20)and the specificity was 80.0%(16/20).There were 119 differentially expressed peptides in the urine samples and none were statistically significant,failing to establish a pathological classification model.Conclusion:This study shows that differential peptide between NSCLC patients and healthy person,lung squamous cell carcinoma and lung adenocarcinoma patients in serum and urine.MALDI-TOF-MS was used to establish the diagnostic model and pathological classification model of NSCLC patients,which have high sensitivity and specificity.The established model can be used in the early diagnosis and distinguished pathology of NSCLC patients.However,it needs to expand the cohort to improve and verify the forecast model.Second Part Detection of serum peptides in patients with lungsquamous cell carcinoma by MALDI-TOF-MS and analysis oftheir correlation with chemotherapy efficacyPurpose:In this study,we use matrix-assisted laser desorption time-of-flight mass spectrometry(MALDI-TOF-MS)to detect serum peptides in patients with advanced lung squamous cell carcinoma before paclitaxel combined with platinum chemotherapy and analyze their correlation with chemotherapy efficacy.Establish a predictive model of chemotherapy efficacy in patients with advanced lung squamous cell carcinoma to lay the foundation for individualized chemotherapy in patients with lung squamous cell carcinoma.Content: In this study,a total of 81 patients with lung squamous cell carcinoma who underwent histopathology or cytology diagnosis were enrolled in the Department of Lung Cancer in our Hospital from October 2014 to April 2016.The patients were treated with paclitaxel combined with platinum regimen and evaluated for every 2 cycles.They were divided into chemotherapy sensitive group and chemotherapy resistant group.MALDI-TOF-MS and CPT software were used to analyze the serum samples and build the predictive model of chemotherapy efficacy.The established model can be used to predict the efficacy of paclitaxel combined with platinum regimen chemotherapy.Method:Collect serum samples from patients with advanced lung squamous cell carcinoma before treatment(paclitaxel combined with platinum regimen chemotherapy)and evaluate the efficacy of every two cycles.The chemotherapy efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors RECIST1.1.The patients with lung squamous cell carcinoma who were evaluated as CR or PR were classified as chemotherapy sensitive group and who were evaluated as PD were classified as chemotherapy resistant group.The patients were randomly divided into training group(sensitive group I and resistant group I)and validation group(sensitive group II and resistant group II)according to the ratio of 3: 1.MB-IMAC-Cu2 + was used for serum pretreatment,and the peptides from serum samples were isolated.MALDI-TOF-MS was used to detect serum peptides in the training group and the fingerprints of serum were obtained.Three different biological algorithms of the Clin Pro Tools(CPT)software(SNN,GA,QC algorithm)were used to establish the efficacy prediction model.The prediction model of lung squamous cell carcinoma was established by using the optimal algorithm.The validation group was used to verify the accuracy,sensitivity and specificity of the model.The correlation between the serum differential peptide and the PFS of the two groups was obtained by statistical analysis.Result:81 patients with advanced lung squamous cell carcinoma received paclitaxel combined with platinum regimen chemotherapy.Among them,no one achieved CR,and PR was 40 cases(49.4%,40/81).PD was 41 cases(50.6%,41/81).A total of 30 patients with drug sensitive(sensitive group I)and 31 patients with drug resistant group(resistant group I)were enrolled in the training group.Ten patients with drug sensitive(sensitive group II)and 10 patients in drug resistant group(resistant group II)were enrolled in the validation group.The median PFS in the sensitive group was 7.2 months(95% CI: 4.4-14.5)and the median PFS in the resistant group was 1.8 months(95% CI: 0.7-3.5).There were 96 differentially expressed peptides compared serum samples of the sensitive group I with the resistant group I,including sixteen peptides(p <0.001)with statistically significant differences.The optimal algorithm is the GA algorithm.The model is composed of five peptides(1897.75 Da,2023.93 Da,3683.36 Da,4269.56 Da,5341.29Da).The recognition rate of the model in the sensitive group was 95.11% and the cross validation rate was 89.18%.The accuracy of the model was 85%(17/20),the sensitivity was 90%(9/10),and the specificity was 80%(8/10).The median PFS in the sensitive group was 7.2 months(95% CI: 4.4-14.5),whereas the median PFS in the resistant group was 1.8 months(95% CI: 0.7-3.5).The correlation between the peptide peak and PFS showed that the differential peptides 4232.04 Da and 4269.56 Da were correlated with PFS in patients with lung squamous cell carcinoma(p <0.01).The 4269.56 Da peptide was also used to establish the predictive model of chemotherapy efficacy,which further explained the close relationship between the peptide and the curative effect of chemotherapy.The peptide peak was further identified in the serum of the chemotherapy resistant group.The mass ratio is1897 Da and 2023 Da respectively,identified as complement C4 a,C3f.Conclusion:This study showed that there were differences in the serum peptides of chemotherapy sensitive and chemotherapy resistant patients.MALDI-TOF-MS was used to establish the predictive model of curative effect.The model could be used to predict the efficacy of paclitaxel combined with platinum regimen and have high sensitivity and specificity.But we need to further expand the sample size to improve and verify the forecast model. |
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