Ling Han

Malignant transformation of endometriosis in a laparoscopic trocar site a case report

Abstract Background Malignant transformation of endometriosis is infrequent at the laparoscopic trocar site. Although malignant transformation is uncommon, it must be acknowledged in order to achieve radical resection. Case presentation We report on a 54-year-old woman with trocar site endometriosis 2 years after laparoscopic ovarian endometrial resection. Physical examination revealed a subcutaneous solid tumor with a diameter of 3 cm surrounding the scar of laparoscopic surgery in the right lower abdomen. Transabdominal ultrasonography showed a cystic tumor in the subcutaneous adipose layer of the right lower abdomen. The pathological diagnosis was poorly differentiated endometrioid carcinoma. Hysterectomy, bilateral salpingo-oophorectomy and pelvic lymphadenectomy were then performed. Histological examination revealed mixed endometrioid carcinoma and clear cell carcinoma. After six cycles of chemotherapy, computed tomography showed no signs of recurrence. Conclusions Malignant transformation of laparoscopic endometriosis is very uncommon, and the diagnosis and stage are determined by clinical manifestations and imaging examination. The main therapy methods are radical surgery combined with neoadjuvant chemotherapy and adjuvant radiotherapy. At the same time, reducing iatrogenic abdominal incision implantation is an effective prevention method.

Graphene-Based Biosensors with High Sensitivity for Detection of Ovarian Cancer Cells

Ovarian cancer has the highest mortality rate in the world. Therefore, it is urgent but still challenging to develop an efficient circulating tumor cell (CTC) detection method to sensitively detect ovarian cancer. To address such issues, herein, for the first time, we present a novel CTC detection method for ovarian cancer cells by designing sensitive and rapid graphene-based biosensors. This graphene-based sensor, consisting of a cell pool and two electrodes, can be prepared by a conventional chip fabrication process. It demonstrates high-sensitivity detection even for several ovarian cancer cells by comparing the electrical signal before and after adding cell solution. Moreover, the graphene-based biosensors can perform rapid detection with good repeatability. This suggests that this novel method is possible to use for the early detection of ovarian cancer with very low CTC cell concentration. This work provides a novel and quick strategy to detect ovarian cancer and further judge or predict the risk of the transfer of ovarian cancer.