GSK-3β Regulates the Expression of P21 to Promote the Progression of Chordoma

Unraveling molecular signatures in rare bone tumors and navigating the cancer pathway landscapes for targeted therapeutics

Rare cancers (RCs), which account for over 20% of cancer cases, face significant research and treatment challenges due to their limited prevalence. This results in suboptimal outcomes compared to more common malignancies. Rare bone tumors (RBTs) constitute 5-10% of rare cancer cases and pose unique diagnostic complexities. The therapeutic potential of anti-cancer drugs for RBTs remains largely unexplored. Identifying molecular alterations in cancer-related genes and their associated pathways is essential for precision medicine in RBTs. Small molecule inhibitors and monoclonal antibodies targeting specific RBT-associated proteins show promise. Ongoing clinical trials aim to define RBT biomarkers, subtypes, and optimal treatment contexts, including combination therapies and immunotherapeutic agents. This review addresses the challenges in diagnosing, treating, and studying RBTs, shedding light on the current state of RBT biomarkers, potential therapeutic targets, and promising inhibitors. Rare cancers demand attention and innovative solutions to improve clinical outcomes.

Exploring gene-patient association to identify personalized cancer driver genes by linear neighborhood propagation

BACKGROUND

Driver genes play a vital role in the development of cancer. Identifying driver genes is critical for diagnosing and understanding cancer. However, challenges remain in identifying personalized driver genes due to tumor heterogeneity of cancer. Although many computational methods have been developed to solve this problem, few efforts have been undertaken to explore gene-patient associations to identify personalized driver genes.

RESULTS

Here we propose a method called LPDriver to identify personalized cancer driver genes by employing linear neighborhood propagation model on individual genetic data. LPDriver builds personalized gene network based on the genetic data of individual patients, extracts the gene-patient associations from the bipartite graph of the personalized gene network and utilizes a linear neighborhood propagation model to mine gene-patient associations to detect personalized driver genes. The experimental results demonstrate that as compared to the existing methods, our method shows competitive performance and can predict cancer driver genes in a more accurate way. Furthermore, these results also show that besides revealing novel driver genes that have been reported to be related with cancer, LPDriver is also able to identify personalized cancer driver genes for individual patients by their network characteristics even if the mutation data of genes are hidden.

CONCLUSIONS

LPDriver can provide an effective approach to predict personalized cancer driver genes, which could promote the diagnosis and treatment of cancer. The source code and data are freely available at https://github.com/hyr0771/LPDriver .

Hinokitiol Protects Cardiomyocyte from Oxidative Damage by Inhibiting GSK3β-Mediated Autophagy

More and more attention has been paid to the use of traditional phytochemicals. Here, we first verified the therapeutic potential of a natural bioactive compound called Hinokitiol in myocardial ischemia reperfusion injury. Hinokitiol exerts cardioprotective effect through inhibition of GSK-3β and subsequent elimination of excessive autophagy, tuning autophagic activity in moderate extent for remedial profit in acute myocardial infarction and myocardial ischemia reperfusion injury. Overall, our study establishes Hinokitiol as a novel available interventional treatment for myocardial ischemia reperfusion injury.

CMTM3 suppresses chordoma progress through EGFR/STAT3 regulated EMT and TP53 signaling pathway

BACKGROUND

Chordomas are rare, slow-growing and locally aggressive bone sarcomas. At present, chordomas are difficult to manage due to their high recurrence rate, metastasis tendency and poor prognosis. The underlying mechanisms of chordoma tumorigenesis and progression urgently need to be explored to find the effective therapeutic targets. Our previous data demonstrates that EGFR plays important roles in chordoma development and CKLF-like MARVEL transmembrane domain containing (CMTM)3 suppresses gastric cancer metastasis by inhibiting the EGFR/STAT3/EMT signaling pathway. However, the roles and mechanism of CMTM3 in chordomas remain unknown.

METHODS

Primary chordoma tissues and the paired adjacent non-tumor tissues were collected to examine the expression of CMTM3 by western blot. The expression of CMTM3 in chordoma cell lines was tested by Real-time PCR and western blot. CCK-8 and colony forming unit assay were performed to delineate the roles of CMTM3 in cell proliferation. Wound healing and Transwell assays were performed to assess cell migration and invasion abilities. A xenograft model in NSG mice was used to elucidate the function of CMTM3 in vivo. Signaling pathways were analyzed by western blot and IHC. RNA-seq was performed to further explore the mechanism regulated by CMTM3 in chordoma cells.

RESULTS

CMTM3 expression was downregulated in chordoma tissues compared with paired normal tissues. CMTM3 suppressed proliferation, migration and invasion of chordoma cells in vitro and inhibited tumor growth in vivo. CMTM3 accelerated EGFR degradation, suppressed EGFR/STAT3/EMT signaling pathway, upregulated TP53 expression and enriched the TP53 signaling pathway in chordoma cells.

CONCLUSIONS

CMTM3 inhibited tumorigenesis and development of chordomas through activating the TP53 signaling pathway and suppressing the EGFR/STAT3 signaling pathway, which suppressed EMT progression. CMTM3 might be a potential therapeutic target for chordomas.