Project description:Central neurocytomas (CN) are intraventricular brain tumors predominantly occurring in young adults. Although prognosis is usually favorable, tumor recurrence is common, particularly following subtotal resection (STR). Currently, the risk of progression is evaluated using histopathological criteria, such as atypical features and elevated Ki67 proliferation index. However, these markers lack consistent definitions and application. Genome-wide DNA methylation profiles were examined in 136 tumors histologically classified as CN. Clinical and histopathological characteristics were assessed in 93 and 90 cases, and whole-exome sequencing was conducted in 12 cases. Clinical and molecular characteristics were integrated into a survival model to predict progression-free survival (PFS). A diagnosis of CN was epigenetically confirmed in 125 of 136 cases (92%). No DNA methylation subgroups associated with risk were identified, but global DNA hypomethylation emerged as a hallmark feature of CN. Hypomethylation at the FGFR3 locus, accompanied by increased FGFR3 protein expression, was observed in 97% of cases. Exome-sequencing revealed BCR frameshift mutations in 3/12 cases. Gross total resection was associated with significantly improved PFS compared to subtotal resected tumors (STR), while patients undergoing STR benefited from adjuvant radiotherapy (p = 0.00088). Younger patients were identified as having a higher risk of recurrence (p = 0.026). Patient age and treatment strategy were key factors influencing survival outcomes in this cohort. These findings underscore the importance of closer follow-up for younger patients and recommend radiotherapy for STR cases. Furthermore, FGFR3 represents a hallmark feature and potential therapeutic target warranting further investigation.
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.
Project description:The pathogenesis of cancer is typically driven by alterations in multiple cellular pathways that are challenging to identify and target. However, it is unclear how suitable the existing pathway analysis tools are for unbiased discovery and ranking of dysregulated and/or cancer-specific pathways. Here, we created a new platform called Benchmark to evaluate the potential of pathway analysis tools for discovery under experimental conditions. Unexpectedly, we found that despite wide-spread success in confirming hypothesized dysregulated pathways, common pathway analysis tools are less than ideal for unbiased discovery. Nevertheless, our pathway ensemble tool (PET) that combines the rank statistics from the exisiting methods significantly enhanced discovery. We applied PET to transcriptomics data from 12 independent tumor types to identify prognostic pathways. We showed that the genes from prognostic pathways are excellent biomarkers and can define cancer molecular subtypes. Moreover, drug prediction to normalize genes from prognostic pathways identified effective known and novel drugs. Finally, in vitro and/or a xenograft models of bladder cancer treated with the top predicted drug significantly restricted tumor cells. We anticipate that our unbiased approach for pathway discovery will have tangible impacts on cancer management.
Project description:The relationship between oncogenesis and embryo development are surprised similarity, early placental villi development from 6 weeks to 10 weeks of pregnancy were profiled using microarrays. Through comparative villi and mature placenta data, we identified villi-specific genes that were highly expressed in villus. The large fraction of villi-specific genes dysregulated in transcriptional level across tumors and most of villi-specific genes up-regulated in human cancers. Then by the GO enrichment results, we selected 5 immune-related genes, 6 proliferation-related genes, 8 focal adhesion-related genes that were found to have reported with genomic alterations. The expression of three group genes predicted poor prognosis of a subset of tumors. Our strategy provided a fresh idea for discovering the novel prognostic biomarkers of tumors.