The relationship between SPARC expression in primary tumor and metastatic lymph node of resected pancreatic cancer patients and patients' survival.

BACKGROUND: Previous researches in pancreatic cancer demonstrated a negative correlation between secreted protein acidic and rich in cysteine (SPARC) expression in primary tumor and survival, but not for SPARC expression in lymph node. In the present study, we aimed to evaluate the SPARC expression in various types of tissues and its impact on patients' prognosis. METHODS: The expression of SPARC was examined by immunohistochemistry in resected pancreatic cancer specimens. Kaplan-Meier analyses and Cox proportional hazards regression were applied to assess the mortality risk. RESULTS: A total of 222 tissue samples from 73 patients were collected to evaluate the SPARC expression, which included 73 paired primary tumor and adjacent normal tissues, 38 paired metastatic and normal lymph nodes. The proportion of positive SPARC expression in metastatic lymph node was high (32/38), whereas in normal lymph node it was negative (0/38). Positive SPARC expression in primary tumor cells was associated with a significantly decreased overall survival (P=0.007) and disease-free survival (P=0.003), whereas in other types of tissues it did not show a predictive role for prognosis. Univariate and multivariate analyses both confirmed this significance. CONCLUSION: SPARC can serve a dual function role as both predictor for prognosis and potentially biomarker for lymph node metastasis in resected pancreatic cancer patients.

Clinicopathological characteristics and prognostic factors of patients with primary gallbladder neuroendocrine carcinomas.

OBJECTIVES: Primary gallbladder neuroendocrine carcinomas (GB-NEC) are malignant neoplasms that remained to be studied. In this study we aimed to summarize their clinicopathological characteristics, effective treatment and prognostic factors for patients with GB-NEC. METHODS: Patients with GB-NEC admitted to Shanghai Jiao Tong University Affiliated Sixth People's Hospital and Renji Hospital, School of Medicine, Shanghai Jiao Tong University from October 2012 to August 2020 were enrolled. Clinicopathological characteristics of our patients and those reported in previous studies were recorded. The Kaplan-Meier method and univariate and multivariate Cox regression analyses were used for survival analysis. RESULTS: Altogether 15 patients from our hospitals and 47 patients from previous studies were included. A total of 55 patients who underwent surgical resection, including R0 and non-R0 resection, had significantly longer overall survival compared with the other seven patients. A univariate analysis indicated that patients aged 60 years or older, with jaundice, carcinoid syndrome, non-R0 resection, and advanced stage were associated with worse survival. A multivariate analysis showed that patients aged 60 years or older, carcinoid syndrome and non-R0 resection, but not lymphadenectomy and adjuvant chemotherapy, were independently related to reduced survival. CONCLUSIONS: R0 resection should be the first-line treatment for GB-NEC. Older age, carcinoid syndrome and non-R0 resection are independently associated with reduced survival after surgical resection.

[Application of SELDI-TOF-MS in detection of liver metastasis from colorectal cancer].

OBJECTIVE: To establish a serum protein fingerprint model for prediction of liver metastasis from colorectal cancer by SELDI-TOF-MS analysis, and to determine the differentiatial proteins associated with the metastatic liver cancers. METHODS: Data were collected from the Department of General Surgery in Zhongshan Hospital. A group of patients with colorectal cancer (CRC) without liver metastasis (n = 36) and another group with liver metastasis (n = 36) were included in this study. Serum samples were collected from peripheral venous blood before operation. Special serum protein or peptide fingerprint was determined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The obtained data were analyzed by Biomarker Wizard software to screen the serum protein markers discriminating colorectal cancer patients with and without liver metastasis. A serum protein fingerprint model was established. This model was blindly verified in of CRC patients with and 44 cases without liver metastasis. RESULTS: Comparing the characteristic proteins in those two groups of patients, 10 specific protein peaks were identified with statistical significance (P < 0.05). According to m/z growing from small to large, they were: 2398, 2814, 4084, 4289, 4465, 6422, 6619, 11 482, 11 649 and 13 714. The predictive model had a sensitivity of 91.7% and a specificity of 97.2%. The validation showed a sensitivity of 75.0% and a specificity of 81.8%. CONCLUSION: A predictive model based on differentiatial serum protein fingerprint with high sensitivity and specificity has been successfully established. It should be a very useful tool in detection and diagnosis of liver metastasis in colorectal cancer patients.

[Establish predictive model of colorectal cancer by using surface enhanced laser desorption/ionization-time of flight-mass spectrometry].

OBJECTIVE: To establish serum proteome fingerprinting predictive models and search for proteins associated with colorectal cancer. METHODS: Thirty-six randomly selected colorectal cancer patients and 36 cases with hernia or gall bladder diseases scheduled for elective operation were enrolled as cancer group and control group respectively. Peripheral venous blood samples were collected before the operations. Special serum protein or peptide fingerprint was investigated by using surface enhanced laser desorption/ ionization-time of flight-mass spectrometry (SELDI-TOF-MS) measurement after blood sample had been treated with weak cation exchange protein chip (CM10) for each case. The obtained data were analyzed by Biomarker Wizard software to screen serum proteome tumor markers and set up diagnosis predictive model for colorectal cancer. Blind validation of the model with 44 healthy controls and 88 colorectal cancer patients were carried out by using Biomarker Patterns Software. RESULTS: In comparing colorectal cancer group with control group, 5 specific protein peaks (P < 0.05) were found. The predictive model had a sensitivity of 100% and a specificity of 97.2%. A sensitivity of 71.6% and a specificity of 72.7% was got with the blind validation. The specific protein peaks with a mass-to-charge ratio (m/z) of 8908 and 13,707 showed in all the results and it showed their strong relationship with colorectal cancer. CONCLUSIONS: The predictive models built by the differences of serum proteome fingerprint could be a very useful diagnostic tool in colorectal cancer. Proteins with m/z of 8908 and 13,707 would possibly be the tumor markers of colorectal cancer.