Objective:Occult breast cancer (OBC) accounts for 0.3%-1.0%of all breast cancers. Because of the rarity of this dis-ease, its treatment and prognosis remain unclear. Our study evaluated the treatment outcomes and prognostic factors associated with OBC. Methods:A total of 82 patients diagnosed with OBC based on available criteria were treated at the Cancer Hospital of Chinese Academy of Medical Sciences, Beijing, China, between January 1968 and June 2014. Except for 16 patients who were treated by needle biopsy or excisional biopsy only and were subsequently excluded, all of the cases reported were included in the study. Of the remaining 66 patients, one was male. Patient data, tumor characteristics, and treatment and outcome variables were evaluated. Overall survival (OS) and disease-free survival (DFS) were analyzed. A unicentric retrospective review of 66 patients with OBC was performed. Re-sults:The median follow-up was 75.5 months (7.0-328.0). No significant differences in OS and DFS were observed between patients who underwent mastectomy plus axillary lymph node dissection (Mast+ALND) and those who underwent breast conservation surgery (P>0.05). Univariate analysis revealed that nodal status is a significant prognosis factor of DFS (P=0.031). Conclusion:No significant difference in treatment outcomes between mastectomy+ALND and breast conservation surgery was observed. Nodal status may be an independent predictor of poor outcomes in OBC patients.

A stable and reliable infected necrotizing pancreatitis (INP) model in rats was established in order to study the pathophysiological mechanism and pathological development rule of INP and explore the new therapeutic methods for the diseases. Forty-six SD rats were randomly divided into 5 groups. The animals in group A received the injection of 5% sodium taurocholate into the pancreatic duct and those in group B underwent that of E. coli into the pancreatic duct. The rats in groups C, D and E were subjected to the injection of 5% sodium taurocholate in combination with different concentrations of E. coli (10(3), 10(4), 10(5)/mL, respectively) into the pancreatic duct. The dose of injection was 0.1 mL/100 g and the velocity of injection was 0.2 mL/min in all the 5 groups. Eight h after the injection, the survival rate of animals was recorded and the surviving rats were killed to determine the serum content of amylase and perform pathological examination and germ cultivation of the pancreatic tissue. The results showed that acute necrotizing pancreatitis model was induced by injection of 5% sodium taurocholate into the pancreatic duct. The positive rate of germ cultivation in group A was 12.5%. The acute necrotizing pancreatitis model was not induced by injection of E. coli into the pancreatic duct and the positive rate of germ cultivation in group B was 0. The INP model was established in groups C to E. The positive rate of germ cultivation was 60%, 100% and 100% and 8-h survival rate 100%, 100% and 70% in groups C, D and E, respectively. It was concluded that a stable and reliable model of INP was established by injection of 5% sodium taurocholate in combination with 10(4)/mL E. coli into the pancreatic duct with a dose of 0.1 mL/100 g and a velocity of 0.2 mL/min. The pathogenesis of INP might be that the hemorrhage and necrosis of pancreatic tissue induced by sodium taurocholate results in weakness of pancreatic tissue in fighting against the germs. Meanwhile, the necrotic pancreatic tissue provides a good proliferative environment for the germs.
Cholagogues and Choleretics/*pharmacology ; Disease Models, Animal ; Escherichia coli/*metabolism ; Injections, Intraperitoneal ; Pancreas/enzymology ; Pancreas/microbiology ; Pancreatic Ducts/enzymology ; Pancreatic Ducts/microbiology ; Pancreatitis, Acute Necrotizing/*chemically induced ; Pancreatitis, Acute Necrotizing/*microbiology ; Rats, Sprague-Dawley ; Taurocholic Acid/*pharmacology ; Time Factors

Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell lymphoma, and its etiology and molecular mechanism has not been fully elucidated. Recently, increasing evidence has indicated that long non-coding RNA (LncRNA) participates in the occurrence, development, invasion and metastasis of DLBCL. This article reviews lncRNA-related genes and signaling pathways as well as the molecular mechanism of DLBCL.

Objective:To compare the clinical, pathological features and prognosis of patients who underwent pancreaticoduodenectomy with standard or extended lymph node dissection for pancreatic ductal adenocarcinoma.Methods:A retrospective study was performed on 158 pancreatic head cancer patients who underwent radical resection at the First Affiliated Hospital of Nanjing Medical University from Jul 2017 to Feb 2019. The clinicopathological characteristics and prognosis between the standard dissection group and the extended dissection group were compared. The relationship between the number of examined lymph nodes, positive lymph nodes, and the lymph node ratio, together with their relationship with survival were analyzed.Results:Survival analysis showed no statistical difference in survival between the standard resection group and the extended resection group ( P=0.99). There were statistical differences in gender and age composition between the two group, but no significant differences in operation time, blood loss, or postoperative complications were found. Patients with less examined lymph nodes tended to be of stage N0. examined lymph nodes is positively correlated with positive lymph nodes but is not significantly correlated with lymph node ratio. Positive lymph nodes is strongly correlated with lymph node ratio. The location of lymph node metastasis was not survival-related. Conclusions:There is no prognostic difference between standard lymph node dissection and extended lymph node dissection in pancreatic cancinoma patients after Whipple procedure.

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma, with high clinical and biological heterogeneity. Only 60% of patients can benefit from standard immunochemotherapy. Looking for new clinical parameters and biomarkers to better classify and stratify the prognosis of DLBCL patients has been the focused area in recent years. This article reviews the classifications and their prognostic significances of DLBCL by analyzing the related studies of genome and transcriptome.

OBJECTIVETo explore the clinicopathological features and prognostic factors of three rare and poor-prognostic pathological subtypes of primary liver carcinoma, and improve the clinical diagnosis and surgical treatment.

METHODSA retrospective analysis of clinicopathological data of 69 patients with rare pathological subtypes of primary liver carcinoma, diagnosed by postoperative pathology in our hospital from October 1998 to June 2013 was carried out. The data of 80 cases of common poorly differentiated hepatocellular carcinoma treated in the same period were collected as control group. Kaplan-Meier method was used to analyze the survival rate, and Cox proportional hazards model was used for prognostic analysis in the patients.

RESULTSThirty-four cases were combined hepatocellular carcinoma and cholangiocarcinoma (CCC, 28 males, 6 females), with a median age of 52 years (range, 33 to 73). Ninteen cases were giant cell carcinoma (GCC, 16 males and 3 females), with a median age of 59 years (range, 38 to 66). Sixteen cases were sarcomatoid carcinoma (SC, 14 males and 2 females), with a median age of 57 years (range, 46 to 70). The survival analysis revealed that median survival time and the 1-, 3-, 5-year survival rates for these 3 groups were 20 months, 61.8%, 29.4%, and 20.6% in the CCC patients, 13 months, 52.6%, 31.6%, and 0% in the GCC patients, and 8 months, 31.3%, 0%, 0% in the SC patients, respectively. The median survival time and survival rate of the SC group were significantly lower than those of the other three groups (P < 0.05). However, in the SC group, the incidences of hilar lymph nodes metastasis, vascular tumor emboli and invasion of adjacent organs were significantly higher than those in the other three groups (P < 0.05). There were no statistically significant differences among the other three groups (P > 0.05). The levels of carcino-embryonic antigen were higher in the three rare subtype groups than that of the control group. The incidences of multiple tumors of the three rare subtype groups were higher than that of the control group (P < 0.05). Positive surgical margin was an independent unfavorable prognostic factor.

CONCLUSIONSThe combined hepatocellular carcinoma and cholangiocarcinoma, giant cell carcinoma and sarcomatoid carcinoma have a poor prognosis. Among them sarcomatoid carcinoma is the most malignant and poor prognostic one. Radical resection is recommended.

Adult ; Aged ; Carcinoembryonic Antigen ; metabolism ; Carcinoma, Giant Cell ; metabolism ; pathology ; surgery ; Carcinoma, Hepatocellular ; metabolism ; pathology ; surgery ; Carcinosarcoma ; metabolism ; pathology ; surgery ; Cholangiocarcinoma ; metabolism ; pathology ; surgery ; Female ; Follow-Up Studies ; Hepatectomy ; methods ; Humans ; Liver Neoplasms ; metabolism ; pathology ; surgery ; Lymph Node Excision ; Lymphatic Metastasis ; Male ; Middle Aged ; Neoplasm Invasiveness ; Neoplastic Cells, Circulating ; Proportional Hazards Models ; Retrospective Studies ; Risk Factors ; Survival Rate

A stable and reliable infected necrotizing pancreatitis (INP) model in rats was established in order to study the pathophysiological mechanism and pathological development rule of INP and explore the new therapeutic methods for the diseases. Forty-six SD rats were randomly divided into 5 groups. The animals in group A received the injection of 5% sodium taurocholate into the pancreatic duct and those in group B underwent that of E. Coli into the pancreatic duct. The rats in groups C, D and E were subjected to the injection of 5% sodium tanrocholate in combination with different con-centrations of E. Coli (103, 104, 105/mL, respectively) into the pancreatic duct. The dose of injection was 0.1 mL/100 g and the velocity of injection was 0.2 mL/min in all the 5 groups. Eight h after the injection, the survival rate of animals was recorded and the surviving rats were killed to determine the serum content of amylase and perform pathological examination and germ cultivation of the pancre-atic tissue. The results showed that acute necrotizing panereatitis model was induced by injection of 5% sodium taurocholate into the pancreatic duct. The positive rate of germ cultivation in group A was 12.5%. The acute necrotizing pancreatitis model was not induced by injection of E. Coli into the pan-creatic duct and the positive rate of germ cultivation in group B was 0. The INP model was estab-lished in groups C to E. The positive rate of germ cultivation was 60%, 100% and 100% and 8-h sur-vival rate 100%, 100% and 70% in groups C, D and E, respectively. It was concluded that a stable and reliable model of INP was established by injection of 5% sodium taurocholate in combination with 104/mL E. Coli into the pancreatic duct with a dose of 0.1 mL/100 g and a velocity of 0.2 mL/min. The pathogenesis of INP might he that the hemorrhage and necrosis of pancreatic tissue in-duced by sodium taurocholate results in weakness of pancreatic tissue in fighting against the germs.Meanwhile, the necrotic pancreatic tissue provides a good proliferative environment for the germs.

Objective: To investigate the clinical value of intraoperative radiofrequency ablation (RFA) in the treatment of colorectal liver metastasis (CLM). Methods: A retrospectively analysis of 187 patients with CLM who underwent liver resection with or without RFA from January 2009 to August 2016 in Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences was performed. According to whether RFA was used intraoperatively, patients were divided into resection only group and combined treatment group. The clinical and pathological characteristics of the two groups were compared to explore factors influencing survival and recurrence. Imbalance of background characteristics between the two groups was further overcome by propensity score matching method (PSM). Results: The number of liver metastases (267), simultaneous liver metastases (100%), bilobar involvement (73.3%) and preoperative chemotherapy (93.3%) rates were significantly higher in the combined treatment group than those in the resection only group(471, 74.7%, 42.0% and 63.1%)(all P<0.05). In the combined treatment group, median overall survival (OS) was 25.7 months; and 3-year and 5-year OS were 47.9% and 28.8%, respectively. In the resection only group, the median survival time was 46.9 months; and 3-year and 5-year OS rate was 59.1% and 42.4%, respectively (χ²=4.579, P=0.034). Median disease-free survival (DFS) was 5.4 months in the combined treatment group, and 10.1 months in the resection only group (χ²=5.399, P=0.023). In multivariate analysis, intraoperative RFA was not an independent prognostic factor for OS and DFS (HR=0.98, 95%CI: 0.47-2.08, P=0.965; HR=1.21, 95%CI: 0.71-2.07, P=0.465). After PSM, the median OS of the resection only and the combined treatment groups were 30.2 and 25.7 months (χ²=0.876, P=0.350). The median DFS in the two groups was 5.3 and 4.2 months, respectively (χ²=0.199, P=0.650). Conclusion In patients with similar tumor burden, liver resection combined with intraoperative RFA for unresectable CLM can achieve long-term outcomes similar to hepatectomy alone for resectable CLM.

Objective To investigate the clinical features,diagnosis and treatment strategies for primary retroperitoneal neurofibromas.Methods The clinical data of 7 patients with primary retroperitoneal neurofibromas admitted to Cancer Institute & Hospital,Chinese Academy of Medical Sciences,from Jan 2000 to Jul 2017,were retrospectively analyzed.Results The average age was (42 ± 11) years and six were female.6 cases were with solitary tumor and 1 case was with multiple tumors.Clinical symptoms and imaging were of no help in determining tumor type.All patients underwent surgical resection.Postoperative pathology confirmed retroperitoneal neurofibroma in all seven patients,including 1 case with neurofibromatosis type Ⅰ and retroperitoneal malignant peripheral nerve sheath tumor.On immunohistochemistry all of the tumors were S-100 protein positive.At the end of the follow-up period ranging from 14 months to 166 months,sevent patients were alive and two patients experienced tumor recurrence.The longest disease-free survival time was 166 months.Conclusion Primary retroperitoneal neurofibromas are a rare type of primary retroperitoneal tumors that require diagnosis at pathology.Clinical symptoms and imaging of primary retroperitoneal neurofibromas patients were found to be ineffective at determining tumor type.Patients had a good prognosis after tumor resection.

Objective:To investigate the application value of machine learning algorithms and COX nomogram in the survival prediction of hepatocellular carcinoma (HCC) after resection.Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 375 patients with HCC who underwent radical resection in the Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College from January 2012 to January 2017 were collected. There were 304 males and 71 females, aged from 21 to 79 years, with a median age of 57 years. According to the random numbers showed in the computer, 375 patients were divided into training dataset consisting of 300 patients and validation dataset consisting of 75 patients, with a ratio of 8∶2. Machine learning algorithms including logistic regression (LR), supporting vector machine (SVM), decision tree (DT), random forest (RF), and artificial neural network (ANN) were used to construct survival prediction models for HCC after resection, so as to identify the optimal machine learning algorithm prediction model. A COX nomogram prediction model for predicting postoperative survival in patients with HCC was also constructed. Comparison of performance for predicting postoperative survival of HCC patients was conducted between the optimal machine learning algorithm prediction model and the COX nomogram prediction model. Observation indicators: (1) analysis of clinicopathological data of patients in the training dataset and validation dataset; (2) follow-up and survival of patients in the training dataset and validation dataset; (3) construction and evaluation of machine learning algorithm prediction models; (4) construction and evaluation of COX nomogram prediction model; (5) evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model. Follow-up was performed using outpatient examination or telephone interview to detect survival of patients up to December 2019 or death. Measurement data with normal distribution were expressed as Mean± SD, and comparison between groups was analyzed by the paired t test. Measurement data with skewed distribution were expressed as M ( P25, P75) or M (range), and comparison between groups was analyzed by the Mann-Whitney U test. Count data were represented as absolute numbers. Comparison between groups was performed using the chi-square test when Tmin ≥5 and N ≥40, using the calibration chi-square test when 1≤ Tmin ≤5 and N ≥40, and using Fisher exact probability when Tmin <1 or N <40. The Kaplan-Meier method was used to calculate survival rate and draw survival curve. The COX proportional hazard model was used for univariate analysis, and variables with P<0.2 were included for the Lasso regression analysis. According to the lambda value, variables affecting prognosis were screened for COX proportional hazard model to perform multivariate analysis. Results:(1) Analysis of clinicopathological data of patients in the training dataset and validation dataset: cases without microvascular invasion or with microvascular invasion, cases without liver cirrhosis or with liver cirrhosis of the training dataset were 292, 8, 105, 195, respectively, versus 69, 6, 37, 38 of the validation dataset, showing significant differences between the two groups ( χ2=4.749, 5.239, P<0.05). (2) Follow-up and survival of patients in the training dataset and validation dataset: all the 375 patients received follow-up. The 300 patients in the training dataset were followed up for 1.1-85.5 months, with a median follow-up time of 50.3 months. Seventy-five patients in the validation dataset were followed up for 1.0-85.7 months, with a median follow-up time of 46.7 months. The postoperative 1-, 3-year overall survival rates of the 375 patients were 91.7%, 79.5%. The postoperative 1-, 3-year overall survival rates of the training dataset were 92.0%, 79.7%, versus 90.7%, 81.9% of the validation dataset, showing no significant difference in postoperative survival between the two groups ( χ2=0.113, P>0.05). (3) Construction and evaluation of machine learning algorithm prediction models. ① Selection of the optimal machine learning algorithm prediction model: according to information divergence of variables for prediction of 3 years postoperative survival of HCC, five machine learning algorithms were used to comprehensively rank the variables of clinicopathological factors of HCC, including LR, SVM, DT, RF, and ANN. The main predictive factors were screened out, as hepatitis B e antigen (HBeAg), surgical procedure, maximum tumor diameter, perioperative blood transfusion, liver capsule invasion, and liver segment Ⅳ invasion. The rank sequence 3, 6, 9, 12, 15, 18, 21, 24, 27, 29 variables of predictive factors were introduced into 5 machine learning algorithms in turn. The results showed that the area under curve (AUC) of the receiver operating charateristic curve of LR, SVM, DT, and RF machine learning algorithm prediction models tended to be stable when 9 variables are introduced. When more than 12 variables were introduced, the AUC of ANN machine learning algorithm prediction model fluctuated significantly, the stability of AUC of LR and SVM machine learning algorithm prediction models continued to improve, and the AUC of RF machine learning algorithm prediction model was nearly 0.990, suggesting RF machine learning algorithm prediction model as the optimal machine learning algorithm prediction model. ② Optimization and evaluation of RF machine learning algorithm prediction model: 29 variables of predictive factors were sequentially introduced into the RF machine learning algorithm to construct the optimal RF machine learning algorithm prediction model in the training dataset. The results showed that when 10 variables were introduced, results of grid search method showed 4 as the optimal number of nodes in DT, and 1 000 as the optimal number of DT. When the number of introduced variables were not less than 10, the AUC of RF machine learning algorithm prediction model was about 0.990. When 10 variables were introduced, the RF machine learning algorithm prediction model had an AUC of 0.992 for postoperative overall survival of 3 years, a sensitivity of 0.629, a specificity of 0.996 in the training dataset, an AUC of 0.723 for postoperative overall survival of 3 years, a sensitivity of 0.177, a specificity of 0.948 in the validation dataset. (4) Construction and evaluation of COX nomogram prediction model. ① Analysis of postoperative survival factors of HCC patients in the training dataset. Results of univariate analysis showed that HBeAg, alpha fetoprotein (AFP), preoperative blood transfusion, maximum tumor diameter, liver capsule invasion, and degree of tumor differentiation were related factors for postoperative survival of HCC patients [ hazard ratio ( HR)=1.958, 1.878, 2.170, 1.188, 2.052, 0.222, 95% confidence interval ( CI): 1.185-3.235, 1.147-3.076, 1.389-3.393, 1.092-1.291, 1.240-3.395, 0.070-0.703, P<0.05]. Clinico-pathological data with P<0.2 were included for Lasso regression analysis, and the results showed that age, HBeAg, AFP, surgical procedure, perioperative blood transfusion, maximum tumor diameter, tumor located at liver segment Ⅴ or Ⅷ, liver capsule invasion, and degree of tumor differentiation as high differentiation, moderate-high differentiation, moderate differentiation, moderate-low differentiation were related factors for postoperative survival of HCC patients. The above factors were included for further multivariate COX analysis, and the results showed that HBeAg, surgical procedure, maximum tumor diameter were independent factors affecting postoperative survival of HCC patients ( HR=1.770, 8.799, 1.142, 95% CI: 1.049- 2.987, 1.203-64.342, 1.051-1.242, P<0.05). ② Construction and evaluation of COX nomogram prediction model: the clinicopathological factors of P≤0.1 in the COX multivariate analysis were induced to Rstudio software and rms software package to construct COX nomogram prediction model in the training dataset. The COX nomogram prediction model for predicting postoperative overall survival had an consistency index of 0.723 (se=0.028), an AUC of 0.760 for postoperative overall survival of 3 years in the training dataset, an AUC of 0.795 for postoperative overall survival of 3 years in the validation dataset. The verification of the calibration plot in the training dataset showed that the COX nomogram prediction model had a good prediction performance for postoperative survival. COX nomogram score=0.627 06×HBeAg (normal=0, abnormal=1)+ 0.134 34×maximum tumor diameter (cm)+ 2.107 58×surgical procedure (laparoscopy=0, laparotomy=1)+ 0.545 58×perioperative blood transfusion (without blood transfusion=0, with blood transfusion=1)-1.421 33×high differentiation (non-high differentiation=0, high differentiation=1). The COX nomogram risk scores of all patients were calculated. Xtile software was used to find the optimal threshold of COX nomogram risk scores. Patients with risk scores ≥2.9 were assigned into high risk group, and patients with risk scores <2.9 were assigned into low risk group. Results of Kaplan-Meier overall survival curve showed a significant difference in the postoperative overall survival between low risk group and high risk group of the training dataset ( χ2=33.065, P<0.05). There was a significant difference in the postoperative overall survival between low risk group and high risk group of the validation dataset ( χ2=6.585, P<0.05). Results of further analysis by the decision-making curve showed that COX nomogram prediction model based on the combination of HBeAg, surgical procedure, perioperative blood transfusion, maximum tumor diameter, and degree of tumor differentiation was superior to any of the above individual factors in prediction performance. (5) Evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model: prediction difference between two models was investigated by analyzing maximun tumor diameter (the important variable shared in both models), and by comparing the predictive error curve of both models. The results showed that the postoperative 3-year survival rates predicted by RF machine learning algorithm prediction model and COX nomogram prediction model were 77.17% and 74.77% respectively for tumor with maximum diameter of 2.2 cm ( χ2=0.182, P>0.05), 57.51% and 61.65% for tumor with maximum diameter of 6.3 cm ( χ2=0.394, P>0.05), 51.03% and 27.52% for tumor with maximum diameter of 14.2 cm ( χ2=12.762, P<0.05). With the increase of the maximum tumor diameter, the difference in survival rates predicted between the two models turned larger. In the validation dataset, the AUC for postoperative overall survival of 3 years of RF machine learning algorithm prediction model and COX nomogram prediction model was 0.723 and 0.795, showing a significant difference between the two models ( t=3.353, P<0.05). Resluts of Bootstrap cross-validation for prediction error showed that the integrated Brier scores of RF machine learning algorithm prediction model and COX nomogram prediction model for predicting 3-year survival were 0.139 and 0.134, respectively. The prediction error of COX nomogram prediction model was lower than that of RF machine learning algorithm prediction model. Conclusion:Compared with machine learning algorithm prediction models, the COX nomogram prediction model performs better in predicting 3 years postoperative survival of HCC, with fewer variables, which is easy for clinical use.