scholarly journals MP88-14 CANCER STEM CELL FEATURE CAN INDUCE RESISTANCE TO MTOR INHIBITORS VIA THE NOTCH PATHWAY IN RENAL CELL CARCINOMAS

2018 ◽  
Vol 199 (4S) ◽  
Author(s):  
Kazuyuki Numakura ◽  
Jesse Novac ◽  
Jean-Christophe Pignon ◽  
Toni Choueiri ◽  
Sabina Signoretti
2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Arezoo Rasti ◽  
Mitra Mehrazma ◽  
Zahra Madjd ◽  
Maryam Abolhasani ◽  
Leili Saeednejad Zanjani ◽  
...  

2021 ◽  
Vol 11 ◽  
Author(s):  
Hongzhi Wang ◽  
Hanjiang Xu ◽  
Quan Cheng ◽  
Chaozhao Liang

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and is characterized by high rates of metastasis. Cancer stem cell is a vital cause of renal cancer metastasis and recurrence. However, little is known regarding the change and the roles of stem cells during the development of renal cancer. To clarify this problem, we developed a novel stem cell clustering strategy. Based on The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) genomic datasets, we used 19 stem cell gene sets to classify each dataset. A machine learning method was used to perform the classification. We classified ccRCC into three subtypes—stem cell activated (SC-A), stem cell dormant (SC-D), and stem cell excluded (SC-E)—based on the expressions of stem cell-related genes. Compared with the other subtypes, C2(SC-A) had the highest degree of cancer stem cell concentration, the highest level of immune cell infiltration, a distinct mutation landscape, and the worst prognosis. Moreover, drug sensitivity analysis revealed that subgroup C2(SC-A) had the highest sensitivity to immunotherapy CTLA-4 blockade and the vascular endothelial growth factor receptor (VEGFR) inhibitor sunitinib. The identification of ccRCC subtypes based on cancer stem cell gene sets demonstrated the heterogeneity of ccRCC and provided a new strategy for its treatment.


Author(s):  
Eun-Jin Yun ◽  
Jiancheng Zhou ◽  
Chun-Jung Lin ◽  
Elizabeth Hernandez ◽  
John Santoyo ◽  
...  

2017 ◽  
Vol 23 (14) ◽  
pp. 3871-3883 ◽  
Author(s):  
Jose Manuel Garcia-Heredia ◽  
Antonio Lucena-Cacace ◽  
Eva M. Verdugo-Sivianes ◽  
Marco Pérez ◽  
Amancio Carnero

2012 ◽  
Vol 22 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Gulperi Oktem ◽  
Muzaffer Sanci ◽  
Ayhan Bilir ◽  
Yusuf Yildirim ◽  
Sibel D. Kececi ◽  
...  

ObjectivesEmbryonic molecules and cancer stem cell signaling resemble each other, and they organize cancer modality. We hypothesized that similar immunohistochemical expressions between tumor spheroids and patients’ samples compared with clinical relevance would give an important clue in patients’ prognosis.MethodsImmunohistochemical expression of c-kit, Notch1, Jagged1, and Delta1 in 50 cases of primary ovarian tumors (10 endometrioid, 10 serous, 10 mucinous adenocarcinoma, 10 borderline serous, and 10 borderline mucinous tumors) and MDAH-2774 spheroids were investigated. Results were compared in both spheroids and tumor samples with morphologic parameters (histological grade) and clinical data (age, stage, tumor size, and metastasis).ResultsHigh c-kit and Notch1 immunoreactivity was shown in spheroids, but interestingly immunoreactivity of these molecules in tumor samples was different from patients’ clinicopathological characteristics. In serous carcinoma, metastasis correlated with Notch1 immunoexpression; in mucinous carcinoma, Jagged1 immunohistochemistry correlated with grade, stage, and metastasis of tumor; in borderline serous and mucinous tumors, Jagged1 correlated with high grade. Moreover, Jagged1 correlated with stage and Notch1 with size in borderline mucinous tumor. Endometrioid carcinoma statistics showed that there was a correlation between age and Notch1 expression.ConclusionNotch1, Jagged1, and Delta1 expressions might be useful markers for clinical prognosis of ovarian carcinomas; and Notch pathway, one of the most intensively studied putative therapeutic targets, may be a useful marker for cancer. Consequently, Jagged1 could be a marker for tumor grades and Notch1 as a marker for metastases.


PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e75463 ◽  
Author(s):  
Kosuke Ueda ◽  
Sachiko Ogasawara ◽  
Jun Akiba ◽  
Masamichi Nakayama ◽  
Keita Todoroki ◽  
...  

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