Identification of Myoferlin Expression for Prediction of Subsequent Primary Malignancy in Patients With Clear Cell Renal Cell Carcinoma

[Treatment and prognosis of multiple primary malignant neoplasms complicated with renal cell carcinoma]

OBJECTIVE

To investigate the treatment and prognosis of multiple primary malignant neoplasms (MPMN) complicated with renal cell carcinoma (RCC), and to make risk stratification.

METHODS

A retrospective study of 27 cases of MPMN with RCC in two centers, including the different tumors of MPMN, specific treatment methods, and the interval between primary cancers. At the same time, the survival conditions, including recurrence, metastasis and survival, were followed up for statistical analysis. The interval between the two kinds of primary cancer within 6 months was simultaneous MPMNs, and more than 6 months was metachronous MPMNs. For simple risk stratification of cases, as long as one of the MPMNs had a stage Ⅲ or higher malignancy, which was defined as high risk.

RESULTS

Among the 27 patients, 20 were male and 7 were female, with age at the time of diagnosis was 42-82 years, with an average age of (61.3±11.7) years. The age at the diagnosis of renal cancer was 43-87 years, with an average age of (66.0±11.3) years. There were 21 cases with duplex primary malignant neoplasms, 4 cases with triple primary malignant neoplasms, and 2 cases with quadruple primary malignant neoplasms. The interval between first cancer and second cancer was 0-360 months, with a median of 18 months. There were 17 cases of metachronous multiple primary malignant neoplasms and 10 cases of simultaneous multiple primary malignant neoplasms. The most common system of MPMN with comorbid RCC involved urologic system, digestive system and respiratory system. The most common locations of MPMN with comorbid RCC were bladder cancer, lung cancer and colon cancer. Follow-up time calcu- lated from the last cancer was 2-156 months, with a median of 32 months. And 14 cases survived and 13 cases died, with 11 cases being tumor related. Tumor stage was the risk factor of prognosis. Any kind of tumor stage in stage Ⅲ or above had a relatively poor prognosis.

CONCLUSION

MPMN complicated with RCC is relatively rare. Standard treatment should be used for each cancer type during the treatment process. The prognosis mainly depends on the highest stage of each tumor. Simple risk stratification shows that the prognosis of the high-risk group is worse. This simple stratification method may be helpful to predict the prognosis.

[Treatment and prognosis of multiple primary malignant neoplasms complicated with renal cell carcinoma]

OBJECTIVE

To investigate the treatment and prognosis of multiple primary malignant neoplasms (MPMN) complicated with renal cell carcinoma (RCC), and to make risk stratification.

METHODS

A retrospective study of 27 cases of MPMN with RCC in two centers, including the different tumors of MPMN, specific treatment methods, and the interval between primary cancers. At the same time, the survival conditions, including recurrence, metastasis and survival, were followed up for statistical analysis. The interval between the two kinds of primary cancer within 6 months was simultaneous MPMNs, and more than 6 months was metachronous MPMNs. For simple risk stratification of cases, as long as one of the MPMNs had a stage Ⅲ or higher malignancy, which was defined as high risk.

RESULTS

Among the 27 patients, 20 were male and 7 were female, with age at the time of diagnosis was 42-82 years, with an average age of (61.3±11.7) years. The age at the diagnosis of renal cancer was 43-87 years, with an average age of (66.0±11.3) years. There were 21 cases with duplex primary malignant neoplasms, 4 cases with triple primary malignant neoplasms, and 2 cases with quadruple primary malignant neoplasms. The interval between first cancer and second cancer was 0-360 months, with a median of 18 months. There were 17 cases of metachronous multiple primary malignant neoplasms and 10 cases of simultaneous multiple primary malignant neoplasms. The most common system of MPMN with comorbid RCC involved urologic system, digestive system and respiratory system. The most common locations of MPMN with comorbid RCC were bladder cancer, lung cancer and colon cancer. Follow-up time calcu- lated from the last cancer was 2-156 months, with a median of 32 months. And 14 cases survived and 13 cases died, with 11 cases being tumor related. Tumor stage was the risk factor of prognosis. Any kind of tumor stage in stage Ⅲ or above had a relatively poor prognosis.

CONCLUSION

MPMN complicated with RCC is relatively rare. Standard treatment should be used for each cancer type during the treatment process. The prognosis mainly depends on the highest stage of each tumor. Simple risk stratification shows that the prognosis of the high-risk group is worse. This simple stratification method may be helpful to predict the prognosis.

Five-gene signature predicts acute kidney injury in early kidney transplant patients

Patients with acute kidney injury (AKI) show high morbidity and mortality, and a lack of effective biomarkers increases difficulty in its early detection. Weighted gene co-expression network analysis (WGCNA) detected a total of 22 gene modules and 6 miRNA modules, of which 4 gene modules and 3 miRNA modules were phenotypically co-related. Functional analysis revealed that these modules were related to different molecular pathways, which mainly involved PI3K-Akt signaling pathway and ECM-receptor interaction. The brown modules related to transplantation mainly involved immune-related pathways. Finally, five genes with the highest AUC were used to establish a diagnosis and prediction model of AKI. The model showed a high area under curve (AUC) in the training set and validation set, and their prediction accuracy for AKI was as high as 100%. Similarly, the prediction accuracy of AKI after 24 h in the 0 h transplant sample was 100%. This study may provide new features for the diagnosis and prediction of AKI after kidney transplantation, and facilitate the diagnosis and drug development of AKI in kidney transplant patients.

Myoferlin, a Membrane Protein with Emerging Oncogenic Roles

Myoferlin (MYOF), initially identified in muscle cells, is a member of the Ferlin family involved in membrane fusion, membrane repair, and membrane trafficking. Dysfunction of this protein is associated with muscular dysfunction. Recently, a growing body of studies have identified MYOF as an oncogenic protein. It is overexpressed in a variety of human cancers and promotes tumorigenesis, tumor cell motility, proliferation, migration, epithelial to mesenchymal transition, angiogenesis as well as metastasis. Clinically, MYOF overexpression is associated with poor outcome in various cancers. It can serve as a prognostic marker of human malignant disease. MYOF drives the progression of cancer in various processes, including surface receptor transportation, endocytosis, exocytosis, intercellular communication, fit mitochondrial structure maintenance and cell metabolism. Depletion of MYOF demonstrates significant antitumor effects both in vitro and in vivo, suggesting that targeting MYOF may produce promising clinical benefits in the treatment of malignant disease. In the present article, we reviewed the physiological function of MYOF as well as its role in cancer, thus providing a general understanding for further exploration of this protein.

Ferlin Overview: From Membrane to Cancer Biology

In mammal myocytes, endothelial cells and inner ear cells, ferlins are proteins involved in membrane processes such as fusion, recycling, endo- and exocytosis. They harbour several C2 domains allowing their interaction with phospholipids. The expression of several Ferlin genes was described as altered in several tumoural tissues. Intriguingly, beyond a simple alteration, myoferlin, otoferlin and Fer1L4 expressions were negatively correlated with patient survival in some cancer types. Therefore, it can be assumed that membrane biology is of extreme importance for cell survival and signalling, making Ferlin proteins core machinery indispensable for cancer cell adaptation to hostile environments. The evidences suggest that myoferlin, when overexpressed, enhances cancer cell proliferation, migration and metabolism by affecting various aspects of membrane biology. Targeting myoferlin using pharmacological compounds, gene transfer technology, or interfering RNA is now considered as an emerging therapeutic strategy.