Objective: To investigate the clinicopathological characteristics of superior mediastinal lymph node metastases (sMLNM) in medullary thyroid carcinoma (MTC). Methods: This retrospective analysis enrolled the patients who were treated for sMLNM of MTC in our hospital from May 2012 to January 2021. All patients were suspected of sMLNM due to preoperative imaging. According to the pathological results, the patients were divided into two groups named sMLNM group and the negative superior-mediastinal-lymph-node group. We collected and analyzed the clinical features, pathological features, pre- and post-operative calcitonin (Ctn), and carcinoembryonic antigen (CEA) levels of the two groups. Logistic regression analysis was used to analyze risk factors, and receiver operation characteristic (ROC) curves were drawn to determine the optimal cut-off values of preoperative Ctn and preoperative CEA for predicting sMLNM. Results: Among the 94 patients, 69 cases were in the sMLNM group and 25 cases were in the non-SMLNM group. Preoperative Ctn level (P=0.003), preoperative CEA level (P=0.010), distant metastasis (P=0.022), extracapsular lymph node invasion (P=0.013), the number of central lymph node metastases (P=0.002) were related to sMLNM, but the multivariate analysis did not find any independent risk factors. The optimal threshold for predicting sMLNM by pre-operative Ctn is 1500 pg/ml and AUC is 0.759 (95% CI: 0.646, 0.872). The sensitivity, specificity, positive predictive value, and negative predictive value of diagnosis are 61.2%, 77.3%, 89.1%, 39.5%, respectively. In patients who underwent mediastinal lymph node dissection through transsternal approach, the metastatic possibility of different levels from high to low were level 2R (82.3%, 28/34), level 2L (58.8%, 20/34), level 4R (58.8%, 20/34), level 3 (23.5%, 8/34), level 4L (11.8%, 4/34). Postoperative complications occurred in 41 cases (43.6%), and there was no perioperative death in all cases. 14.8% (12/81) of the patients achieved biochemical complete response (Ctn≤12 pg/ml) one month after surgery, 5 of these patients were in sMLNM group. Conclusions: For patients who have highly suspicious sMLNM through imaging, combining with preoperative Ctn diagnosis can improve the accuracy of diagnosis, especially for patients with preoperative Ctn over 1 500 pg/ml. The superior mediastinal lymph node dissection for the primary sternotomy should include at least the superior mediastinal levels 2-4 to avoid residual lesions. The strategy of surgery needs to be cautiously performed. Although the probability of biochemical cure in sMLNM cases is low, nearly 40% of patients can still benefit from the operation at the biochemical level.
Humans ; Carcinoembryonic Antigen ; Lymphatic Metastasis/pathology* ; Retrospective Studies ; Lymph Nodes/pathology* ; Thyroid Neoplasms/pathology* ; Carcinoma, Neuroendocrine/pathology* ; Lymph Node Excision/methods*

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.
Humans ; Carcinoma, Non-Small-Cell Lung/surgery* ; Lung Neoplasms/diagnosis* ; Retrospective Studies ; Autoantibodies ; Bayes Theorem ; Tumor Suppressor Protein p53 ; Carcinoembryonic Antigen ; Antigens, Neoplasm ; Biomarkers, Tumor ; Algorithms ; Pneumonia

Objective: To investigate the cytomorphological and immunocytochemical features of tumor cells in the ascites of ovarian plasmacytoma (SOC). Methods: Specimens of serous cavity effusions were collected from 61 tumor patients admitted to the Affiliated Wuxi People's Hospital of Nanjing Medical University from January 2015 to July 2021, including ascites from 32 SOC, 10 gastrointestinal adenocarcinomas, 5 pancreatic ductal adenocarcinomas, 6 lung adenocarcinomas, 4 benign mesothelial hyperplasia and 1 malignant mesothelioma patients, pleural effusions from 2 malignant mesothelioma patients and pericardial effusion from 1 malignant mesothelioma. Serous cavity effusion samples of all patients were collected, conventional smears were made through centrifugation, and cell paraffin blocks were made through centrifugation of remaining effusion samples. Conventional HE staining and immunocytochemical staining were applied to observe and summarize cytomorphological characteristics and immunocytochemical characteristics. The levels of serum tumor markers carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were detected. Results: Of the 32 SOC patients, 5 had low-grade serous ovarian carcinoma (LGSOC) and 27 had high-grade serous ovarian carcinoma (HGSOC). 29 (90.6%) SOC patients had elevated serum CA125, but the difference was not statistically significant between them and patients with non-ovarian primary lesions included in the study (P>0.05); The serum CEA was positive in 9 patients with gastrointestinal adenocarcinoma and 5 patients with lung adenocarcinoma, and the positive rate was higher than that in SOC patients (P<0.001); The serum CA19-9 was positive in 5 patients with gastrointestinal adenocarcinoma and 5 patients with pancreatic ductal adenocarcinoma, and the positive rate was higher than that in SOC patients (P<0.05). The serum CA125, CEA and CA19-9 were within the normal range in 4 patients with benign mesothelial hyperplasia. LGSOC tumor cells were less heterogeneous and aggregated into small clusters or papillary pattern, and psammoma bodies could be observed in some LGSOC cases. The background cells were fewer and lymphocytes were predominant; the papillary structure was more obvious after making cell wax blocks. HGSOC tumor cells were highly heterogeneous, with significantly enlarged nuclei and varying sizes, which could be more than 3-fold different, and nucleoli and nuclear schizophrenia could be observed in some cases; tumor cells were mostly clustered into nested clusters, papillae and prune shapes; there were more background cells, mainly histiocytes. Immunocytochemical staining showed that AE1/AE3, CK7, PAX-8, CA125, and WT1 were diffusely positively expressed in 32 SOC cases. P53 was focally positive in all 5 LGSOCs, diffusely positive in 23 HGSOCs, and negative in the other 4 HGSOCs. Most of adenocarcinomas of the gastrointestinal tract and lung had a history of surgery, and tumor cells of pancreatic ductal adenocarcinoma tend to form small cell nests. Immunocytochemistry can assist in the differential diagnosis of mesothelial-derived lesions with characteristic "open window" phenomenon. Conclusion: Combining the clinical manifestations of the patient, the morphological characteristics of the cells in the smear and cell block of the ascites can provide important clues for the diagnosis of SOC, and the immunocytochemical tests can further improve the accuracy of the diagnosis.
Female ; Humans ; Carcinoembryonic Antigen ; Ascites ; CA-19-9 Antigen ; Mesothelioma, Malignant/diagnosis* ; Hyperplasia ; Adenocarcinoma/pathology* ; Cystadenocarcinoma, Serous/diagnosis* ; Biomarkers, Tumor ; Carcinoma, Ovarian Epithelial ; Diagnosis, Differential ; Ovarian Neoplasms/pathology* ; Carbohydrates

Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
Humans ; Lung Neoplasms/diagnostic imaging* ; Biomarkers, Tumor ; Retrospective Studies ; Antigens, Neoplasm ; Keratin-19 ; Carcinoembryonic Antigen ; Adenocarcinoma/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Phosphopyruvate Hydratase ; Tomography, X-Ray Computed

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.
Humans ; Carcinoma, Non-Small-Cell Lung/surgery* ; Lung Neoplasms/diagnosis* ; Retrospective Studies ; Autoantibodies ; Bayes Theorem ; Tumor Suppressor Protein p53 ; Carcinoembryonic Antigen ; Antigens, Neoplasm ; Biomarkers, Tumor ; Algorithms ; Pneumonia

Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
Humans ; Lung Neoplasms/diagnostic imaging* ; Biomarkers, Tumor ; Retrospective Studies ; Antigens, Neoplasm ; Keratin-19 ; Carcinoembryonic Antigen ; Adenocarcinoma/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Phosphopyruvate Hydratase ; Tomography, X-Ray Computed

OBJECTIVE: To evaluate the diagnostic value of the serum tumor markers carcinoembryonic antigen (CEA), cytokeratin-19-fragment (CYFRA21-1), squamous cell carcinoma associated antigen (SCCAg), neuron-specificenolase (NSE) and pro-gastrin-releasing peptide (ProGRP) for lung cancers of different pathological types. METHODS: This study was conducted among patients with established diagnoses of lung adenocarcinoma (LADC, n=137), lung squamous cell carcinoma (LSCC, n=82), small cell lung carcinoma (SCLC, n=59), and benign chest disease (BCD, n=102). The serum tumor markers were detected for all the patients for comparison of the positivity rates and their serum levels. ROC curve was used for analysis of the diagnostic efficacy of these tumor markers either alone or in different combinations. RESULTS: In patients with LADC, the positivity rate and serum level of CEA were significantly higher than those in the other groups (P < 0.05); the patients with LSCC had the highest positivity rate and serum level of SCCAg among the 4 groups (P < 0.05). The positivity rates and serum levels of ProGRP and NSE were significantly higher in SCLC group than in the other groups (P < 0.05). CYFRA21-1 showed the highest positivity rate and serum level in LADC group and LSCC group. With the patients with BCD as control, CEA showed a diagnostic sensitivity of 62.8% and a specificity of 93.1% for LADC, and the sensitivity and specificity of SCCAg for diagnosing LSCC were 64.6% and 91.2%, respectively. CYFRA21-1 had the highest diagnostic sensitivity for LADC and LSCC. The diagnostic sensitivity and specificity of ProGRP for SCLC were 83.1% and 98.0%, respectively. When combined, CYFRA21-1 and CEA showed a high sensitivity (78.8%) and specificity (86.3%) for diagnosing LADC with an AUC of 0.891; CYFRA21-1 and SCCAg had a high sensitivity (84.1%) and specificity (87.3%) for diagnosing LSCC with an AUC of 0.912. NSE combined with ProGRP was highly sensitive (88.1%) and specific (98.0%) for diagnosis of SCLC, with an AUC of 0.952. For lung cancers of different pathological types, the combination of all the 5 tumor markers showed no significant differences in the diagnostic power from a combined detection with any two of the markers (P>0.05). CONCLUSION CEA, CYFRA21-1, SCCAg, NSE and ProGRP are all related to the pathological type of lung cancers and can be used in different combinations as useful diagnostic indicators for lung cancers.
Antigens, Neoplasm ; Biomarkers, Tumor ; Carcinoembryonic Antigen ; Humans ; Keratin-19 ; Lung Neoplasms/pathology* ; Peptide Fragments ; Peptide Hormones ; Recombinant Proteins ; Small Cell Lung Carcinoma/diagnosis*

Patients with lung cancer at the same stage may have markedly different overall outcome and a lack of specific biomarker to predict lung cancer outcome. Heat-shock protein 90 β (HSP90β) is overexpressed in various tumor cells. In this study, the ELISA results of HSP90β combined with CEA, CA125, and CYFRA21-1 were used to construct a recursive partitioning decision tree model to establish a four-protein diagnostic model and predict the survival of patients with lung cancer. Survival analysis showed that the recursive partitioning decision tree could distinguish the prognosis between high- and low-risk groups. Results suggested that the joint detection of HSP90β, CEA, CA125, and CYFRA21-1 in the peripheral blood of patients with lung cancer is plausible for early diagnosis and prognosis prediction of lung cancer.
Antigens, Neoplasm ; Biomarkers, Tumor ; CA-125 Antigen ; Carcinoembryonic Antigen ; Carcinoma, Non-Small-Cell Lung/pathology* ; Humans ; Keratin-19 ; Lung Neoplasms ; Prognosis

Objective: To investigate the expression of cortactin in colorectal cancer and its correlation with clinicopathological parameters and prognosis. Methods: The expressions of cortactin in normal colorectal mucosal tissue and colorectal cancer tissue in paraffin-embedded tissue microarray from 319 patients who were diagnosed as colorectal cancer and treated in Cancer Hospital of Chinese Academy of Medical Sciences from 2006 to 2009 was detected by immunohistochemistry. Kaplan-Meier method and Log rank test were used for survival analysis, and Cox proportional risk regression model was used for multivariate analysis. Results: The positive expression rates of cortactin in colorectal cancer tissue and normal colorectal mucosal tissue were 61.1% (195/319) and 5.6% (18/319, P<0.001), respectively. T-stage, N-stage, American Joint Committee on Cancer (AJCC) stage, degree of tumor differentiation, neural invasion and preoperative carcinoembryonic antigen (CEA) levels were associated with the expression of cortactin (P<0.05). The positive expression of cortactin was associated with poorer disease-free survival (P=0.036) and overall survival (P=0.043), and the effect was more significant in patients with stage Ⅱ to Ⅲ. For patients with stage Ⅱ-Ⅲ colorectal cancer, postoperative adjuvant therapy was associated with disease-free survival (P=0.007) and overall survival (P=0.015). The vascular tumor embolus, pathological type, preoperative CEA level and cortactin expression were independent influencing factors for disease-free survival (P<0.05). The age, AJCC stage, preoperative CEA level and cortactin expression were independent influencing factors for overall survival (P<0.05). Preoperative CEA level and cortactin expression were independent influencing factors for disease-free survival and overall survival (P<0.05). Conclusion: Cortactin is expressed in colorectal cancer and in stage Ⅱ-Ⅲ patients, it is a potential predictor of colorectal cancer prognosis.
Biomarkers, Tumor/metabolism* ; Carcinoembryonic Antigen/metabolism* ; Colorectal Neoplasms/pathology* ; Cortactin/metabolism* ; Humans ; Prognosis ; Retrospective Studies

Objective: To compare the prognostic evaluation value of preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII) in rectal cancer patients. Nomogram survival prediction model based on inflammatory markers was constructed. Methods: The clinical and survival data of 585 patients with rectal cancer who underwent radical resection in the First Affiliated Hospital of Xi'an Jiao tong University from January 2013 to December 2016 were retrospectively analyzed. The optimal cut-off values of NLR, PLR, LMR, and SII were determined by the receiver operating characteristic (ROC) curve. The relationship between different NLR, PLR, LMR and SII levels and the clinic pathological characteristics of the rectal cancer patients were compared. Cox proportional risk model was used for univariate and multivariate regression analysis. Nomogram prediction models of overall survival (OS) and disease-free survival (DFS) of patients with rectal cancer were established by the R Language software. The internal validation and accuracy of the nomograms were determined by the calculation of concordance index (C-index). Calibration curve was used to evaluate nomograms' efficiency. Results: The optimal cut-off values of preoperative NLR, PLR, LMR and SII of OS for rectal cancer patients were 2.44, 134.88, 4.70 and 354.18, respectively. There was statistically significant difference in tumor differentiation degree between the low NLR group and the high NLR group (P<0.05), and there were statistically significant differences in T stage, N stage, TNM stage, tumor differentiation degree and preoperative carcinoembryonic antigen (CEA) level between the low PLR group and the high PLR group (P<0.05). There was statistically significant difference in tumor differentiation degree between the low LMR group and the high LMR group (P<0.05), and there were statistically significant differences in T stage, N stage, TNM stage, tumor differentiation degree and preoperative CEA level between the low SII group and the high SII group (P<0.05). The multivariate Cox regression analysis showed that the age (HR=2.221, 95%CI: 1.526-3.231), TNM stage (Ⅲ grade: HR=4.425, 95%CI: 1.848-10.596), grade of differentiation (HR=1.630, 95%CI: 1.074-2.474), SII level (HR=2.949, 95%CI: 1.799-4.835), and postoperative chemoradiotherapy (HR=2.123, 95%CI: 1.506-2.992) were independent risk factors for the OS of patients with rectal cancer. The age (HR=2.107, 95%CI: 1.535-2.893), TNM stage (Ⅲ grade, HR=2.850, 95%CI: 1.430-5.680), grade of differentiation (HR=1.681, 95%CI: 1.150-2.457), SII level (HR=2.309, 95%CI: 1.546-3.447), and postoperative chemoradiotherapy (HR=1.837, 95%CI: 1.369-2.464) were independent risk factors of the DFS of patients with rectal cancer. According to the OS and DFS nomograms predict models of rectal cancer patients established by multivariate COX regression analysis, the C-index were 0.786 and 0.746, respectively. The calibration curve of the nomograms showed high consistence of predict and actual curves. Conclusions: Preoperative NLR, PLR, LMR and SII levels are all correlated with the prognosis of rectal cancer patients, and the SII level is an independent prognostic risk factor for patients with rectal cancer. Preoperative SII level can complement with the age, TNM stage, differentiation degree and postoperative adjuvant chemoradiotherapy to accurately predict the prognosis of rectal cancer patients, which can provide reference and help for clinical decision.
Biomarkers, Tumor ; Carcinoembryonic Antigen ; Humans ; Inflammation/classification* ; Lymphocytes ; Neutrophils ; Nomograms ; Preoperative Period ; Prognosis ; Rectal Neoplasms/surgery* ; Retrospective Studies