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  • Author: Gang Yuan x
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Open access

Xu Han, Xuefeng Xu, Hongyun Ma, Yuan Ji, Dansong Wang, Tiantao Kuang, Wenchuan Wu, Bin Song, Gang Li, Gang Jin and Wenhui Lou

Purpose

Emerging evidence suggests G3 pancreatic neuroendocrine neoplasms (pNENs) present heterogeneous morphology and biology. The 2017 WHO classification has introduced a new category of well-differentiated pancreatic neuroendocrine tumors (WD-pNETs) G3, compared with poorly differentiated pancreatic neuroendocrine carcinomas (PD-pNECs) G3. We aim to analysis the demographics and outcomes of patients with resectable 2017 WHO G3 pNENs to facilitate the distinction between two entities.

Methods

The multi-institutional retrospective cohort involving 57 surgically treated patients affected by 2017 WHO G3 pNENs were morphologically identified and clinically analyzed. Patients having WD-pNETs G3 and those having PD-pNECs G3 were compared.

Results

Thirty patients had WD-pNETs and 27 patients had PD-pNECs. The distributions of Ki-67 and mitotic count in patients with PD-pNECs or WD-pNETs showed remarkable disparities. ROC indicated cut-off value of Ki-67 was 45. PD-pNECs were more common in patients with elevated Ki-67 and mitotic count, advanced AJCC TNM stage, vascular invasion, regional lymph-node metastases, elevated NSE and decreased CgA levels compared with WD-pNETs (P < 0.05). The association between 2017 WHO G3 grade and TTR was statistically significant (P < 0.05). Univariate analysis indicated OS rates were associated with morphologic differentiation (WD-pNETs vs PD-pNECs), Ki-67, TNM staging, synchronous distant metastases, initial treatments, vascular invasion, regional lymph nodes metastases, mitotic count and age (P < 0.05). Multivariate analyses illustrated Ki-67, differentiation, TNM staging and vascular invasion were independent predictors (P < 0.05).

Conclusions

PD-pNECs G3 presented malignant biological behavior and dismal outcome compared with WD-pNETs G3. These findings challenge 2010 WHO classification and suggest the categorization can be improved by refined tumor grading.

Open access

Qiuli Liu, Gang Yuan, Dali Tong, Gaolei Liu, Yuting Yi, Jun Zhang, Yao Zhang, Lin-ang Wang, Luofu Wang, Dianzheng Zhang, Rongrong Chen, Yanfang Guan, Xin Yi, Weihua Lan and Jun Jiang

Context

Von Hippel–Lindau (VHL) disease manifests as a variety of benign and malignant neoplasms. Previous studies of VHL disease have documented several genotype–phenotype correlations; however, many such correlations are still unknown. Increased identification of new mutations and patients with previously described mutations will allow us to better understand how VHL mutations influence disease phenotypes.

Patients and design

A total of 45 individuals from five unrelated families were evaluated, of which 21 patients were either diagnosed with VHL disease or showed strong evidence related to this disease. We compared the patients’ gene sequencing results with their medical records including CT or MRI scans, eye examinations and laboratory/pathological examinations. Patients were also interviewed to obtain information regarding their family history.

Results

We identified four missense mutations: c.239G>T (p.Ser80Ile), linked with VHL Type 2B, was associated with renal cell carcinoma, pheochromocytoma and hemangioma in the cerebellum; c.232A>T (p.Asn78Tyr) manifested as RCC alone and likely caused VHL Type 1; c.500G>A (p.Arg167Gln) mutation was more likely to cause VHL Type 2 than Type 1 as it preferentially induced Pheo and HB in the retina, cerebellum and spinal cord; c.293A>G (p.Try98Cys) was associated with Pheo and thus likely induced VHL Type 2.

Conclusions

Characterizing VHL disease genotype–phenotype correlations can enhance the ability to predict the risk of individual patients developing different VHL-related phenotypes. Ultimately, such insight will improve the diagnostics, surveillance and treatment of VHL patients.

Precis

Four missense mutations in VHL have been identified in 21 individuals when five unrelated Chinese families with VHL disease were analyzed; VHL mutations are highly associated with unique disease phenotypes.