Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

Search

Type in a keyword to search

On page 1 showing 1 ~ 7 papers out of 7 papers

Replication the association of 2q32.2-q32.3 and 14q32.11 with hepatocellular carcinoma.

  • Wei Chen‎ et al.
  • Gene‎
  • 2015‎

Hepatocellular carcinoma (HCC) is a malignant tumor. The morbidity and mortality of HCC tend to ascend and become a serious threat to the population health. Genetic studies of HCC have identified several susceptibility loci of HCC. In this study, we aim to replicate the association of these loci in our samples from Chinese population and further investigate the genetic interaction. We selected 16 SNPs within 1p36.22, 2q32.2-q32.3, 3p21.33, 8p12, 14q32.11 and 21q21.3 and genotyped in 507 HCC patients and 3014 controls by using Sequenom MassARRAY system. Association analyses were performed by using PLINK 1.07. We observed that the STAT4 (2q32.2-q32.3) at rs7574865 (P=1.17×10(-3), OR=0.79) and EFCAB11 (14q32.11) at rs8013403 (P=1.54×10(-3), OR=0.80) were significantly associated with HCC in this study. In 3p21.33, genetic variant rs6795737 within GLB1 was also observed with suggestive evidence (P=9.98×10(-3), OR=0.84). In the interaction analysis, the pair of associated SNPs (rs7574865 within STAT4, rs8013403 within EFCAB11) generated evidence for interaction (P=4.10×10(-3)). In summary, our work first reported the association of 14q32.11 (EFCAB11) with HCC in Chinese Han population and revealed the genetic interaction between STAT4 (2q32.2-q32.3) and EFCAB11 (14q32.11) in HCC.


CTSG Suppresses Colorectal Cancer Progression through Negative Regulation of Akt/mTOR/Bcl2 Signaling Pathway.

  • Shixin Chan‎ et al.
  • International journal of biological sciences‎
  • 2023‎

Colorectal cancer (CRC) is the most common gastrointestinal tumor worldwide, which is a severe malignant disease that threatens mankind. Cathepsin G (CTSG) has been reported to be associated with tumorigenesis, whereas its role in CRC is still unclear. This investigation aims to determine the function of CTSG in CRC. Our results indicated that CTSG was inhibited in CRC tissues, and patients with CTSG low expression have poor overall survival. Functional experiments revealed that CTSG overexpression suppressed CRC cell progression in vitro and in vivo, whereas CTSG suppression supports CRC development cells in vitro and in vivo. Mechanistically, CTSG overexpression suppressed Akt/mTOR signaling mechanism and elevated apoptotic-associated markers, and CTSG silencing activated Akt/mTOR signaling mechanisms and inhibited apoptotic-associated markers. Furthermore, the Akt suppression signaling pathway by MK2206 abolishes CTSG-silenced expression-induced cell viability and Bcl2 up-regulation in vitro and in vivo. Altogether, these outcomes demonstrate that CTSG may act as a tumor suppressor gene via Akt/mTOR/Bcl2-mediated anti-apoptotic signaling inactivation, and CTSG represents a potential therapeutic target in CRC.


Rutaecarpine suppresses the proliferation and metastasis of colon cancer cells by regulating the STAT3 signaling.

  • Shixin Chan‎ et al.
  • Journal of Cancer‎
  • 2022‎

Colorectal cancer (CRC) is a malignant disease that is a serious threat to human health. Rutaecarpine (RUT) is an important bioactive alkaloid of Evodia rutaecarpa. According to previous studies, RUT suppressed the proliferation of several human tumors. However, its role in colorectal tumorigenesis remained unknown. The aim of the present study was to determine the functions of RUT in CRC. Here, we have demonstrated that RUT inhibited the proliferation, migration and invasion of CRC cells in vitro. Further, RUT was found to induce the apoptosis of CRC cells. Mechanistically, RUT decreased the phosphorylation levels of NF-κB and STAT3. Moreover, treatment with RUT upregulated the expression of cleaved-Caspase3 and downregulated the expression of Bcl-2 in CRC. In addition, our findings suggested that RUT inhibited the growth and lung metastasis of CRC Cells in vivo. Based on immunofluorescence analysis, the expression of Ki67 was downregulated while that of cleaved-Caspase3 was upregulated in RUT-treated tumors compared with control-treated tumors. Taken together, our findings indicate that RUT can inhibit the proliferation and migration of CRC cells, and induce the apoptosis of CRC cells by inactivating NF-κB/STAT3 signaling. Our study highlights the potential clinical application of RUT for the treatment of CRC.


Identification of novel T cell proliferation patterns, potential biomarkers and therapeutic drugs in colorectal cancer.

  • Xu Wang‎ et al.
  • Journal of Cancer‎
  • 2024‎

Background: T cells are crucial components of antitumor immunity. A list of genes associated with T cell proliferation was recently identified; however, the impact of T cell proliferation-related genes (TRGs) on the prognosis and therapeutic responses of patients with colorectal cancer (CRC) remains unclear. Methods: 33 TRG expression information and clinical information of patients with CRC gathered from multiple datasets were subjected to bioinformatic analysis. Consensus clustering was used to determine the molecular subtypes associated with T cell proliferation. Utilizing the Lasso-Cox regression, a predictive signature was created and verified in external cohorts. A tumor immune environment analysis was conducted, and potential biomarkers and therapeutic drugs were identified and confirmed via in vitro and in vivo studies. Results: CRC patients were separated into two TRG clusters, and differentially expressed genes (DEGs) were identified. Patient information was divided into three different gene clusters, and the determined molecular subtypes were linked to patient survival, immune cells, and immune functions. Prognosis-associated DEGs in the three gene clusters were used to evaluate the risk score, and a predictive signature was developed. The ability of the risk score to predict patient survival and treatment response has been successfully validated using multiple datasets. To discover more possible biomarkers for CRC, the weighted gene co-expression network analysis algorithm was utilized to screen key TRG variations between groups with high- and low-risk. CDK1, BATF, IL1RN, and ITM2A were screened out as key TRGs, and the expression of key TRGs was confirmed using real-time reverse transcription polymerase chain reaction. According to the key TRGs, 7,8-benzoflavone was identified as the most significant drug molecule, and MTT, colony formation, wound healing, transwell assays, and in vivo experiments indicated that 7,8-benzoflavone significantly suppressed the proliferation and migration of CRC cells. Conclusion: T cell proliferation-based molecular subtypes and predictive signatures can be utilized to anticipate patient results, immunological landscape, and treatment response in CRC. Novel biomarker candidates and potential therapeutic drugs for CRC were identified and verified using in vitro and in vivo tests.


Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma.

  • Rui Sun‎ et al.
  • Frontiers in genetics‎
  • 2022‎

Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan-Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan-Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC.


5-Fluorouracil Combined with Rutaecarpine Synergistically Suppresses the Growth of Colon Cancer Cells by Inhibiting STAT3.

  • Zhen Yu‎ et al.
  • Drug design, development and therapy‎
  • 2023‎

To evaluate the effect of 5-fluorouracil (5-FU) combined with rutaecarpine (RUT) on the antiproliferative, anti-migratory, and apoptosis-promoting ability of colorectal cancer (CRC) cells and explore the underlying mechanism.


Development and validation of a novel T cell proliferation-related prognostic model for predicting survival and immunotherapy benefits in melanoma.

  • Jiajie Chen‎ et al.
  • Aging‎
  • 2023‎

T cell plays a crucial role in the occurrence and progression of Skin cutaneous melanoma (SKCM). This research aims to identify the actions of T cell proliferation-related genes (TRGs) on the prognosis and immunotherapy response of tumor patients.


  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Facets

    Here are the facets that you can filter your papers by.

  9. Options

    From here we'll present any options for the literature, such as exporting your current results.

  10. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

Publications Per Year

X

Year:

Count: