Histone deacetylases: A novel class of therapeutic targets for pancreatic cancer

Xiang, Xuesong; Li, Pengcheng; Wang, Wenquan; Liu, Liang

doi:10.1016/j.bbcan.2022.188676

Cited by 12 publications

(19 citation statements)

References 262 publications

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“…For example, the synergistic interaction between DNMT1 inhibitor and pan-HDACi was recently described on MiaPaCa2 cells. 13 Sorafenib is one of the kinase inhibitors (BRAF; FLT3; KDR;RAF1) with preclinical data on synergism with HDACi and this combination is currently under clinical investigations for usage in PDAC 8,14 .…”

Section: Possible Combinations Between Hdaci and Small Molecule Inter...mentioning

confidence: 99%

“…6 Considering the very modest improvement in 5-years survival rate since 1970s from 3% to 11%, 2 there is an urgent need to develop non-surgical therapeutic approaches for effective treatment of pancreatic cancer. 7,8 Gemcitabine, with or without additional chemotherapeutics, is considered as a first line option in chemotherapy of PDAC. Being one of the most chemoresistant cancers, efficacy of currently available chemotherapeutics for PDAC is seriously compromised by promptly developing chemoresistence.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a major approach for future developments in HDACi-based therapy is oriented towards application of these potent anticancer agents in combination with other chemotherapeutics. 8,9 Despite significant breakthroughs in the cancer research during the last decades, high mortality remains major issue which highlights the urgent need for novel therapeutic approaches to the PDAC. Combination therapy holds the promise for advancing treatment of PDAC, but number of possible combinations considering all approved drugs and drug candidates in clinical trials is too large to be explored empirically.…”

Section: Introductionmentioning

confidence: 99%

“…6 Considering the very modest improvement in 5-years survival rate since 1970s from 3% to 11%, there is an urgent need to develop non-surgical therapeutic approaches for effective treatment of pancreatic cancer. 7,8…”

Section: Introductionmentioning

confidence: 99%

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Correlating basal gene expression across chemical sensitivity data to screen for novel synergistic interactors of HDAC inhibitors in pancreatic carcinoma

Djoković

Djurić

Srdiċ-Rajiċ

et al. 2022

Preprint

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Pancreatic ductal adenocarcinoma (PDAC) is considered as one of the most aggressive and lethal malignancies. Development of chemoresistance in PDAC is one of the key contributors for the poor survival outcomes of PDAC patients and the major reason for urgent development of novel pharmacological approaches for effective treatment of PDAC. Systematically tailored combination therapy holds the promise for advancing the treatment of PDAC, but number of possible combinations considering all approved drugs and drug candidates is too large to be explored empirically. In respect to the many epigenetic alterations in PDAC, epigenetic drugs including histone deacetylase inhibitors (HDACi) could be seen as a game changers but available data indicates their efficacy only in combined therapy settings. In this work, we explored possibility of using drug-sensitivity data together with basal gene expression data on pancreatic cell lines to predict the combinatorial options available for HDACi and developed bioinformatics screening protocol for predictions of synergistic drug combinations in PDAC. Our results identified sphingolipid signaling pathway with associated downstream effectors as a promising novel target for future development of multi-target therapeutics or combined therapy with HDACi. Through the process of experimental validation of the methodology, we have characterized novel synergism between HDACi and Rho-associated protein kinase (ROCK) inhibitors.

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Section: Possible Combinations Between Hdaci and Small Molecule Inter...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Correlating basal gene expression across chemical sensitivity data to screen for novel synergistic interactors of HDAC inhibitors in pancreatic carcinoma

Djoković

Djurić

Srdiċ-Rajiċ

et al. 2022

Preprint

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show abstract

“…Due to a lack of early diagnosis and effective treatments, even if patients undergo complete resection and receive chemotherapy and radiotherapy, the 5-year survival rate is less than 26% [1]. Great effort has been dedicated to understanding the mechanisms of this disease [2][3][4][5]. PDAC remains difficult to treat due to the high heterogeneity, suggesting that no single targeted therapy will work for all PDAC patients [6].…”

Section: Introductionmentioning

confidence: 99%

Tumour inhibitory activity on pancreatic cancer by bispecific nanobody targeting PD-L1 and CXCR4

Hao

et al. 2022

BMC Cancer

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Background: Antibodies and derivative drugs targeting immune checkpoints have been approved for the treatment of several malignancies, but there are fewer responses in patients with pancreatic cancer. Here, we designed a nanobody molecule with bi-targeting on PD-L1 and CXCR4, as both targets are overexpressed in many cancer cells and play important roles in tumorigenesis. We characterized the biochemical and anti-tumour activities of the bispecific nanobodies in vitro and in vivo. Methods: A nanobody molecule was designed and constructed. The nanobody sequences targeting PD-L1 and CXCR4 were linked by the (G4S)3 flexible peptide to construct the anti-PD-L1/CXCR4 bispecific nanobody. The bispecific nanobody was expressed in E. coli cells and purified by affinity chromatography. The purified nanobody was biochemically characterized by mass spectrometry, Western blotting and flow cytometry to confirm the molecule and its association with both PD-L1 and CXCR4. The biological function of the nanobody and its anti-tumour effects were examined by an in vitro tumour cell-killing assay and in vivo tumour inhibition in mouse xenograft models. Results: A novel anti-PD-L1/CXCR4 bispecific nanobody was designed, constructed and characterized. The molecule specifically bound to two targets on the surface of human cancer cells and inhibited CXCL12-induced Jurkat cell migration. The bispecific nanobody increased the level of IFN-γ secreted by T-cell activation. The cytotoxicity of human peripheral blood mononuclear cells (hPBMCs) against pancreatic cancer cells was enhanced by the molecule in combination with IL-2. In a human pancreatic cancer xenograft model, the anti-PD-L1/CXCR4 nanobody markedly inhibited tumour growth and was superior to the combo-treatment by anti-PD-L1 nanobody and anti-CXCR4 nanobody or treatment with atezolizumab as a positive control. Immunofluorescence and immunohistochemical staining of xenograft tumours showed that the anti-tumour effects were associated with the inhibition of angiogenesis and the infiltration of immune cells. Conclusion: These results clearly revealed that the anti-PD-L1/CXCR4 bispecific nanobody exerted anti-tumour efficacy in vitro and inhibited tumour growth in vivo. This agent can be further developed as a therapeutic reagent to treat human pancreatic cancer by simultaneously blocking two critical targets.

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Low-dose SAHA enhances CD8+ T cell-mediated antitumor immunity by boosting MHC I expression in non-small cell lung cancer

Dong,

He,

Cao

et al. 2024

Cell Oncol.

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Histone deacetylases: A novel class of therapeutic targets for pancreatic cancer

Cited by 12 publications

References 262 publications

Correlating basal gene expression across chemical sensitivity data to screen for novel synergistic interactors of HDAC inhibitors in pancreatic carcinoma

Correlating basal gene expression across chemical sensitivity data to screen for novel synergistic interactors of HDAC inhibitors in pancreatic carcinoma

Tumour inhibitory activity on pancreatic cancer by bispecific nanobody targeting PD-L1 and CXCR4

Low-dose SAHA enhances CD8+ T cell-mediated antitumor immunity by boosting MHC I expression in non-small cell lung cancer

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