Colorectal cancer (CRC) is a dangerous form of cancer that affects the gastrointestinal tract. It is a major global health concern, and the aggressive behavior of tumor cells makes it difficult to treat, leading to poor survival rates for patients. One major challenge in treating CRC is the metastasis, or spread, of the cancer, which is a major cause of death. In order to improve the prognosis for patients with CRC, it is necessary to focus on ways to inhibit the cancer's ability to invade and spread. Epithelial-mesenchymal transition (EMT) is a process that is linked to the spread of cancer cells, also known as metastasis. The process transforms epithelial cells into mesenchymal ones, increasing their mobility and ability to invade other tissues. This has been shown to be a key mechanism in the progression of colorectal cancer (CRC), a particularly aggressive form of gastrointestinal cancer. The activation of EMT leads to increases in the spread of CRC cells, and during this process, levels of the protein E-cadherin decrease while levels of N-cadherin and vimentin increase. EMT also contributes to the development of resistance to chemotherapy and radiation therapy in CRC. Non-coding RNAs, such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), play a role in regulating EMT in CRC, often through their ability to "sponge" microRNAs. Anti-cancer agents have been shown to suppress EMT and reduce the progression and spread of CRC cells. These findings suggest that targeting EMT or related mechanisms may be a promising approach for treating CRC patients in the clinic. 

Unraveling the function of epithelial-mesenchymal transition (EMT) in colorectal cancer: Metastasis, therapy response, and revisiting molecular pathways.

Network pharmacology-based mechanism prediction and pharmacological validation of Xiaoyan Lidan formula on attenuating alpha-naphthylisothiocyanate induced cholestatic hepatic injury in rats.

Colorectal cancer (CRC) is a prevalent malignant tumor of the digestive tract. Circular RNAs may play important roles in the progression of CRC. In this study, we investigated the roles and mechanisms of action of circ-MALAT1 in CRC. Gene expression and protein abundance were determined using qRT-PCR and western blot, respectively. Cell proliferation and migration were assessed by MTT, clone formation, and wound-healing assays. The interactions among the long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (circ-MALAT1), miR-506-3p, and lysine acetyltransferase 6B (KAT6B) were predicted using the StarBase software and confirmed by the luciferase activity assay. Circ-MALAT1 and KAT6B were upregulated, while miR-506-3p was downregulated in CRC cells. We validated that knocking down of circ-MALAT1 suppressed proliferation, migration, and epithelial-mesenchymal transition (EMT) of CRC cells, and these effects were abolished by miR-506-3p downregulation or KAT6B sufficiency. Our study suggests that circ-MALAT1 could sponge miR-506-3p to regulate the expression of KAT6B. Moreover, KAT6B sufficiency could neutralize miR-506-3p-dependent growth arrest, migration, and EMT. Circ-MALAT1 promotes cell proliferation, migration, and EMT of CRC cells via the miR-506-3p/KAT6B axis, thereby acting as a novel potential therapeutic target for the treatment of colorectal cancer.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/kjm2.12698

Circ-MALAT1 accelerates cell proliferation and epithelial mesenchymal transformation of colorectal cancer through regulating miR-506-3p/KAT6B axis.

Multi-Source Domain Adaptation (MSDA) is widely used in various machine learning scenarios for domain shifts between labeled source domains and unlabeled target domains. Conventional MSDA methods are built on a strong hypothesis that data samples from the same source belong to the same domain with the same latent distribution. However, in practice sources and their latent domains are not necessarily one-to-one correspondence. To tackle this problem, a novel Multi-source Reconstructed Domain Adaptation (MRDA) framework for MSDA is proposed. We use an Expectation-Maximization (EM) mechanism that iteratively reconstructs the source domains to recover the latent domains and performs domain adaptation on the reconstructed domains. Specifically, in the E-step, we cluster the samples from multiple sources into different latent domains, and a soft assignment strategy is proposed to avoid cluster imbalance. In the M-step, we freeze the latent domains clustered in the E-step and optimize the objective function for domain adaptation, and a global-specific feature extractor is used to capture both domain-invariant and domain-specific features. Extensive experiments demonstrate that our approach can reconstruct source domains and perform domain adaptation on the reconstructed domains effectively, thus significantly outperforming state-of-the-art (SOTA) baselines (e.g., 1% to 3.1% absolute improvement in AUC).

Multi-Source Domain Adaptation via Latent Domain Reconstruction

Abstract Background : Bladder cancer (BC) is a highly heterogeneous stem cell disease. Cancer stem cells (CSCs) are the drivers of tumor growth and recurrence, with the ability to self-renew, metastasize, and resist chemotherapy. However, the specific molecular mechanisms of CSCs driving BC recurrence and progression remains unclear. Objective : To explore the underlying molecular mechanism of CSCs driving BC recurrence and progression. Methods : Tumor xenograft model in vivo was established after 4-6-week-old male nude mice were subcutaneously injected with 5×10 6 of T24 and 5637 cells in 0.1 mL 50% Matrigel. Pearson correlation analysis analyzed the correlation between miR-582-5p and CD81, and which was furtherly verified by dual-luciferase reporter gene assay. Sphere formation assay, flow cytometry, immunohistochemistry (IHC), qRT-PCR and Western blot were carried to examine sphere formation, ALDH high populations, the level of genes and proteins. Multivariate analysis was carried to explore the factors associated with recurrence free survival of BC patients. Results : MiR-582-5p was down-regulated in patients with BC, and miR-582-5p overexpression negatively correlated with BC stemness. Mechanically, miR-582-5p negatively targeted to CD81. Functionally, miR-582-5p overexpression inhibited BC stemness and recurrence via targeting CD81. Conclusion : Our study illustrated that miR-582-5p inhibited cell stemness and recurrence via targeting CD81 in BC. Our findings illustrated the specific molecular mechanism of miR-582-5p inhibiting BC progression. MiR-582-5p may serve as the novel biomarker for BC clinical therapeutics and prognosis. 

miR-582-5p regulates cell stemness and recurrence in bladder cancer via targeting CD81

Laparoscopic cholecystectomy combined with Xiaoyanlidan tablets for treatment of acute cholecystitis patients: Curative effect and impact on prognosis and serological indicators

AbstractMulti-task learning (MTL), which jointly tackles multiple tasks through information sharing, has been widely applied to many recommendation applications. Recently, current efforts targeted for recommendation focus on learning task relationships based on the Multi-gate Mixture-of-Experts (MMoE) architecture with shared input features (i.e., subtle feature engineering for user-item interaction). Recent evidences suggest the Graph Neural Network (GNN) as a powerful component in characterizing deep interaction context for recommendation, greatly contributing to easing the data sparseness issue in online advertising services. Hence, we make the first attempt to explore the GNN towards multi-task recommendation, by designing Mixture of Graph enhanced Expert Networks (MoGENet). Specifically, we propose a novel multi-channel graph neural network to jointly model high-order information with the user-item bipartite graph as well as derived collaborative similarity graphs for users and items. On the top of the learned deep interaction context, a group of graph enhanced expert networks are introduced for contributing to the multi-task recommendation in a cooperative manner. Experimental results on three real-world datasets show that MoGENet consistently and significantly outperforms state-of-the-art baselines across all target tasks. KeywordsMulti-task learningGraph learningRecommender system 

Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation

Metastasis and chemo-resistance are still important factors that limit the overall efficacy of colorectal cancer treatment. Understanding the detailed molecular mechanism and identifying potential biomarkers are of great value in prognosis prediction and risk stratification. We investigated the role of miR-582-5p in colorectal cancer pathogenesis, progression and chemo-resistance. Furthermore, we explored the underlying molecular mechanism of miR-582-5p in modulation of malignant behaviors of colorectal cancer cells. Clinical samples and colorectal cancer cell lines were applied to explore miR-582-5p expression level and its significance on tumor cell metastasis and chemo-resistance. Transwell study and cellular survivability study were performed to explore the influences of miR-582-5p expression modulation on tumor cell chemo-resistance and invasion/migration. Dual-luciferase reporter gene assay was conducted to explore the influences of miR-582-5p on its target gene TNKS2. Colorectal cancer patients with lymph node or distal organ metastatic diseases exhibited significantly lower level of miR-582-5p. In vitro studies have indicated that miR-582-5p inhibition significantly increased migration and chemo-resistant capabilities of tumor cells. And dual-luciferase reporter gene assay demonstrated that miR-582-5p exhibited its influences on the biological behavior of tumor cells by targeting TNKS2. Our study demonstrated for the first time that miR-582-5p played an important role for colorectal tumor cell metastasis and chemo-resistance. Our research also indicated that miR-582-5p and its target gene TNKS2 could be novel biomarkers for metastatic disease prediction, overall prognosis evaluation, as well as potential therapeutic target for colorectal cancer patients.

miR-582-5p inhibits migration and chemo-resistant capabilities of colorectal cancer cells by targeting TNKS2.

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Laparoscopic cholecystectomy combined with Xiaoyanlidan tablets for treatment of acute cholecystitis patients: Curative effect and impact on prognosis and serological indicators

Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation

miR-582-5p inhibits migration and chemo-resistant capabilities of colorectal cancer cells by targeting TNKS2.