bims-pimaco 2024-02-04 papers

Issue of 2024‒02‒04
four papers selected by
Lucas B. Zeiger, Beatson Institute for Cancer Research

Front Pharmacol. 2023 ;14 1337732

OTUD3 suppresses the mTORC1 signaling by deubiquitinating KPTN.

Jiatao Li, Dan Yang, Yan Lin, Wei Xu, Shi-Min Zhao, Chenji Wang.

Background: Ubiquitination and deubiquitination modifications play pivotal roles in eukaryotic life processes, regulating protein dynamics via the ubiquitin-proteasome pathway. Dysregulation can impact disease development, including cancer and neurodegenerative disorders. Increasing evidence highlights their role in tumorigenesis, modulating key proteins. OTUD3, a deubiquitinase, stabilizes PTEN, suppressing tumor growth by inhibiting PI3K-AKT signaling. Yet, further OTUD3 substrates remain underexplored. Methods: We employed the In vivo ubiquitination assay to investigate the ubiquitination role of OTUD3 on KPTN within the cellular context. Additionally, CRISPR/Cas9 editing and Immunofluorescence were utilized to study the impact of OTUD3 on the mTOR signaling pathway in cells. Furthermore, Cell proliferation assay and NMR were employed to explore the effects of OTUD3 on cellular growth and proliferation. Results: OTUD3 serves as a deubiquitinase for KPTN. OTUD3 interacts with KPTN, facilitated by the OTU domain within OTUD3. Further investigations confirmed KPTN's ubiquitination modification, primarily at lysine residue 49. Ubiquitination experiments demonstrated OTUD3's ability to mediate KPTN's deubiquitination without affecting its protein levels. This suggests KPTN's ubiquitination is a function-regulated, non-degradable modification. Under various amino acid starvation or stimulation conditions, overexpressing OTUD3 reduces mTORC1 signaling activation, while knocking out OTUD3 further enhances it. Notably, OTUD3's regulation of mTORC1 signaling relies on its deubiquitinase activity, and this effect is observed even in PTEN KO cells, confirming its independence from PTEN, a reported substrate. OTUD3 also promotes GATOR1's lysosomal localization, a process requiring KPTN's involvement. Ultimately, OTUD3 affects cellular metabolic pool products by downregulating the mTORC1 pathway, significantly inhibiting tumor cell growth and proliferation. Discussion: Our experiments shed light on an alternative perspective regarding the intrinsic functions of OTUD3 in inhibiting tumor development. We propose a novel mechanism involving KPTN-mediated regulation of the mTORC1 signaling pathway, offering fresh insights into the occurrence and progression of tumor diseases driven by related genes. This may inspire new approaches for drug screening and cancer treatment, potentially guiding future therapies for relevant tumors.

Keywords: KICSTOR; KPTN; OTU domain-containing protein 3; deubiquitination; mTORC1

DOI: https://doi.org/10.3389/fphar.2023.1337732

Cell Commun Signal. 2024 Jan 30. 22(1): 85

K-Ras(V12) differentially affects the three Akt isoforms in lung and pancreatic carcinoma cells and upregulates E-cadherin and NCAM via Akt3.

Rebekka Geißert, Angela Lammert, Stefanie Wirth, Rabea Hönig, Dirk Lohfink, Monika Unger, Denis Pek, Konstantin Schlüter, Theresa Scheftschik, Daniel J Smit, Manfred Jücker, Andre Menke, Klaudia Giehl.

K-Ras is the most frequently mutated Ras variant in pancreatic, colon and non-small cell lung adenocarcinoma. Activating mutations in K-Ras result in increased amounts of active Ras-GTP and subsequently a hyperactivation of effector proteins and downstream signaling pathways. Here, we demonstrate that oncogenic K-Ras(V12) regulates tumor cell migration by activating the phosphatidylinositol 3-kinases (PI3-K)/Akt pathway and induces the expression of E-cadherin and neural cell adhesion molecule (NCAM) by upregulation of Akt3. In vitro interaction and co-precipitation assays identified PI3-Kα as a bona fide effector of active K-Ras4B but not of H-Ras or N-Ras, resulting in enhanced Akt phosphorylation. Moreover, K-Ras(V12)-induced PI3-K/Akt activation enhanced migration in all analyzed cell lines. Interestingly, Western blot analyses with Akt isoform-specific antibodies as well as qPCR studies revealed, that the amount and the activity of Akt3 was markedly increased whereas the amount of Akt1 and Akt2 was downregulated in EGFP-K-Ras(V12)-expressing cell clones. To investigate the functional role of each Akt isoform and a possible crosstalk of the isoforms in more detail, each isoform was stably depleted in PANC-1 pancreatic and H23 lung carcinoma cells. Akt3, the least expressed Akt isoform in most cell lines, is especially upregulated and active in Akt2-depleted cells. Since expression of EGFP-K-Ras(V12) reduced E-cadherin-mediated cell-cell adhesion by induction of polysialylated NCAM, Akt3 was analyzed as regulator of E-cadherin and NCAM. Western blot analyses revealed pronounced reduction of E-cadherin and NCAM in the Akt3-kd cells, whereas Akt1 and Akt2 depletion upregulated E-cadherin, especially in H23 lung carcinoma cells. In summary, we identified oncogenic K-Ras4B as a key regulator of PI3-Kα-Akt signaling and Akt3 as a crucial regulator of K-Ras4B-induced modulation of E-cadherin and NCAM expression and localization.

Keywords: Akt3; Carcinoma cell migration; Cell-cell adhesion; E-cadherin; K-Ras; NCAM; PI3-kinase; PKB/Akt isoforms; Ras oncogene

DOI: https://doi.org/10.1186/s12964-024-01484-2

Cell Rep Med. 2024 Jan 30. pii: S2666-3791(24)00008-9. [Epub ahead of print] 101399

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Keywords: FOLR2(+) macrophages; artificial intelligence; colorectal cancer; immuno module; tumor microenvironment

DOI: https://doi.org/10.1016/j.xcrm.2024.101399

Mol Divers. 2024 Feb 02.

A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Muhammad Shafiq, Zaid Anis Sherwani, Mamona Mushtaq, Mohammad Nur-E-Alam, Aftab Ahmad, Zaheer Ul-Haq.

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition.

Keywords: In silico drug discovery; Isoform-selective inhibitors; Machine learning; Molecular dynamics simulation; Multilayer perceptron; Phosphoinositide 3-kinase alpha

DOI: https://doi.org/10.1007/s11030-023-10799-0