Predictive Signatures Inform the Effective Repurposing of Decitabine to Treat KRAS-Dependent Pancreatic Ductal Adenocarcinoma

The type of DNA damage response after decitabine treatment depends on the level of DNMT activity

Decitabine and azacytidine are considered as epigenetic drugs that induce DNA methyltransferase (DNMT)-DNA crosslinks, resulting in DNA hypomethylation and damage. Although they are already applied against myeloid cancers, important aspects of their mode of action remain unknown, highly limiting their clinical potential. Using a combinatorial approach, we reveal that the efficacy profile of both compounds primarily depends on the level of induced DNA damage. Under low DNMT activity, only decitabine has a substantial impact. Conversely, when DNMT activity is high, toxicity and cellular response to both compounds are dramatically increased, but do not primarily depend on DNA hypomethylation or RNA-associated processes. By investigating proteome dynamics on chromatin, we show that decitabine induces a strictly DNMT-dependent multifaceted DNA damage response based on chromatin recruitment, but not expression-level changes of repair-associated proteins. The choice of DNA repair pathway hereby depends on the severity of decitabine-induced DNA lesions. Although under moderate DNMT activity, mismatch (MMR), base excision (BER), and Fanconi anaemia-dependent DNA repair combined with homologous recombination are activated in response to decitabine, high DNMT activity and therefore immense replication stress induce activation of MMR and BER followed by non-homologous end joining.

In silico approaches for drug repurposing in oncology: a scoping review

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

Synergistic cytotoxicity of histone deacetylase and poly-ADP ribose polymerase inhibitors and decitabine in pancreatic cancer cells: Implications for novel therapy

Histone deacetylase inhibitors (HDACi) can modulate the acetylation status of proteins, influencing the genomic instability exhibited by cancer cells. Poly (ADP ribose) polymerase (PARP) inhibitors (PARPi) have a direct effect on protein poly (ADP-ribosyl)ation, which is important for DNA repair. Decitabine is a nucleoside cytidine analogue, which when phosphorylated gets incorporated into the growing DNA strand, inhibiting methylation and inducing DNA damage by inactivating and trapping DNA methyltransferase on the DNA, thereby activating transcriptionally silenced DNA loci. We explored various combinations of HDACi and PARPi +/- decitabine (hypomethylating agent) in pancreatic cancer cell lines BxPC-3 and PL45 (wild-type BRCA1 and BRCA2) and Capan-1 (mutated BRCA2). The combination of HDACi (panobinostat or vorinostat) with PARPi (talazoparib or olaparib) resulted in synergistic cytotoxicity in all cell lines tested. The addition of decitabine further increased the synergistic cytotoxicity noted with HDACi and PARPi, triggering apoptosis (evidenced by increased cleavage of caspase 3 and PARP1). The 3-drug combination treatments (vorinostat, talazoparib, and decitabine; vorinostat, olaparib, and decitabine; panobinostat, talazoparib, and decitabine; panobinostat, olaparib, and decitabine) induced more DNA damage (increased phosphorylation of histone 2AX) than the individual drugs and impaired the DNA repair pathways (decreased levels of ATM, BRCA1, and ATRX proteins). The 3-drug combinations also altered the epigenetic regulation of gene expression (NuRD complex subunits, reduced levels). This is the first study to demonstrate synergistic interactions between the aforementioned agents in pancreatic cancer cell lines and provides preclinical data to design individualized therapeutic approaches with the potential to improve pancreatic cancer treatment outcomes.

Repositioning of Montelukast to inhibit proliferation of mutated KRAS pancreatic cancer through a novel mechanism that interfere the binding between KRAS and GTP/GDP

Pancreatic cancer is one of the most lethal cancer types with 5-year survival rate of ∼10.8%. Various KRAS mutations exist in ∼85% pancreatic cancer cell lines. Mutated KRAS is a major cause that leads cancer cell proliferation. Chemotherapy is still the major treatment for pancreatic cancer. Alternatively, repositioning old drug to inhibit mutated KRAS may be a cost-effective way for pancreatic cancer treatment. In this study, we choose mutated KRAS (G12D) as a target. Based on mutated KRAS GTP binding domain (hydrolyze GTP to GDP), we perform virtual screening on FDA-approved drugs. Montelukast shows strong binding affinity to mutated KRAS as well as interfering both GTP and GDP binding to mutated KRAS. Furthermore, Montelukast shows very strong anti-proliferation effect on mutated KRAS pancreatic cancer cells both in vitro and in vivo. Our results support repositioning of Montelukast as single agent for pancreatic cancer treatment.

Epigenetics in Pancreatic Ductal Adenocarcinoma: Impact on Biology and Utilization in Diagnostics and Treatment

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies with high potential of metastases and therapeutic resistance. Although genetic mutations drive PDAC initiation, they alone do not explain its aggressive nature. Epigenetic mechanisms, including aberrant DNA methylation and histone modifications, significantly contribute to inter- and intratumoral heterogeneity, disease progression and metastasis. Thus, increased understanding of the epigenetic landscape in PDAC could offer new potential biomarkers and tailored therapeutic approaches. In this review, we shed light on the role of epigenetic modifications in PDAC biology and on the potential clinical applications of epigenetic biomarkers in liquid biopsy. In addition, we provide an overview of clinical trials assessing epigenetically targeted treatments alone or in combination with other anticancer therapies to improve outcomes of patients with PDAC.

Enhancing an Oxidative "Trojan Horse" Action of Vitamin C with Arsenic Trioxide for Effective Suppression of KRAS-Mutant Cancers: A Promising Path at the Bedside

The turn-on mutations of the KRAS gene, coding a small GTPase coupling growth factor signaling, are contributing to nearly 25% of all human cancers, leading to highly malignant tumors with poor outcomes. Targeting of oncogenic KRAS remains a most challenging task in oncology. Recently, the specific G12C mutant KRAS inhibitors have been developed but with a limited clinical outcome because they acquire drug resistance. Alternatively, exploiting a metabolic breach of KRAS-mutant cancer cells related to a glucose-dependent sensitivity to oxidative stress is becoming a promising indirect cancer targeting approach. Here, we discuss the use of a vitamin C (VC) acting in high dose as an oxidative "Trojan horse" agent for KRAS-mutant cancer cells that can be potentiated with another oxidizing drug arsenic trioxide (ATO) to obtain a potent and selective cytotoxic impact. Moreover, we outline the advantages of VC's non-natural enantiomer, D-VC, because of its distinctive pharmacokinetics and lower toxicity. Thus, the D-VC and ATO combination shows a promising path to treat KRAS-mutant cancers in clinical settings.

Identification of potential biological targets of oxindole scaffolds via in silico repositioning strategies

Background: Drug repurposing is an alternative strategy to traditional drug discovery that aims at predicting new uses for already existing drugs or clinical candidates. Drug repurposing has many advantages over traditional drug development, such as reduced attrition rates, time and costs. This is especially the case considering that most drugs investigated for repurposing have already been assessed for their safety in clinical trials. Repurposing campaigns can also be designed for libraries of already synthesized molecules at different levels of biological experimentation, from null to in vitro and in vivo. Such an extension of the "repurposing" concept is expected to provide significant advantages for the identification of novel drugs, as the synthetic accessibility of the desired compounds is often one of the limiting factors in the traditional drug discovery pipeline. Methods: In this work, we performed a computational repurposing campaign on a library of previously synthesized oxindole-based compounds, in order to identify potential new targets for this versatile scaffold. To this aim, ligand-based approaches were firstly applied to evaluate the similarity degree of the investigated compound library, with respect to ligands extracted from the DrugBank, Protein Data Bank (PDB) and ChEMBL databases. In particular, the 2D fingerprint-based and 3D shape-based similarity profiles were evaluated and compared for the oxindole derivates. Results: The analyses predicted a set of potential candidate targets for repurposing, some of them emerging by consensus of different computational analyses. One of the identified targets, i.e., the vascular endothelial growth factor receptor 2 (VEGFR-2) kinase, was further investigated by means of docking calculations, followed by biological testing of one candidate. Conclusions: While the compound did not show potent inhibitory activity towards VEGFR-2, the study highlighted several other possibilities of therapeutically relevant targets that may be worth of consideration for drug repurposing.

Escaping KRAS: Gaining Autonomy and Resistance to KRAS Inhibition in KRAS Mutant Cancers

Simple Summary

While KRAS is a driver oncogene, tumor cells can acquire mutant KRAS independency by activating pathways that functionally substitute for mutant KRAS. These KRAS-independent tumor cells exhibit a mesenchymal phenotype, readily primed for potential metastasis. The activation of YAP and/or RSK-mTOR pathways and mutations in LKB1, KEAP1, and/or NRF2 are associated with mutant KRAS autonomy. These alterations rewire survival signaling and metabolic processes originally governed by mutant KRAS. The presence of KRAS-independent cells is associated with the heterogeneity of KRAS mutant cancers, as well as variable responses to therapies. Notably, KRAS G12C-specific inhibitors appear to be effective only in tumors dependent on mutant KRAS for their survival. Therefore, determining KRAS dependency will be critical for selecting patients who should be treated with mutant-specific inhibitors. Furthermore, elucidating underlying mechanisms of KRAS autonomy is crucial towards developing optimal treatment strategies for KRAS-independent tumors.

Abstract

Activating mutations in KRAS are present in 25% of human cancers. When mutated, the KRAS protein becomes constitutively active, stimulating various effector pathways and leading to the deregulation of key cellular processes, including the suppression of apoptosis and enhancement of proliferation. Furthermore, mutant KRAS also promotes metabolic deregulation and alterations in the tumor microenvironment. However, some KRAS mutant cancer cells become independent of KRAS for their survival by activating diverse bypass networks that maintain essential survival signaling originally governed by mutant KRAS. The proposed inducers of KRAS independency are the activation of YAP1 and/or RSK-mTOR pathways and co-mutations in SKT11 (LKB1), KEAP1, and NFE2L2 (NRF2) genes. Metabolic reprogramming, such as increased glutaminolysis, is also associated with KRAS autonomy. The presence or absence of KRAS dependency is related to the heterogeneity of KRAS mutant cancers. Epithelial-to-mesenchymal transition (EMT) in tumor cells is also a characteristic phenotype of KRAS independency. Translationally, this loss of dependence is a cause of primary and acquired resistance to mutant KRAS-specific inhibitors. While KRAS-dependent tumors can be treated with mutant KRAS inhibitor monotherapy, for KRAS-independent tumors, we need an improved understanding of activated bypass signaling pathways towards leveraging vulnerabilities, and advancing therapeutic options for this patient subset.

Prognostic value of Glypican family genes in early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy and possible mechanisms

Background

This study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).

Methods

A total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis.

Results

In TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway.

Conclusion

GPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.

KRAS wild-type pancreatic ductal adenocarcinoma: molecular pathology and therapeutic opportunities

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease, whose main molecular trait is the MAPK pathway activation due to KRAS mutation, which is present in 90% of cases.The genetic landscape of KRAS wild type PDAC can be divided into three categories. The first is represented by tumors with an activated MAPK pathway due to BRAF mutation that occur in up to 4% of cases. The second includes tumors with microsatellite instability (MSI) due to defective DNA mismatch repair (dMMR), which occurs in about 2% of cases, also featuring a high tumor mutational burden. The third category is represented by tumors with kinase fusion genes, which marks about 4% of cases. While therapeutic molecular targeting of KRAS is an unresolved challenge, KRAS-wild type PDACs have potential options for tailored treatments, including BRAF antagonists and MAPK inhibitors for the first group, immunotherapy with anti-PD-1/PD-L1 agents for the MSI/dMMR group, and kinase inhibitors for the third group.This calls for a complementation of the histological diagnosis of PDAC with a routine determination of KRAS followed by a comprehensive molecular profiling of KRAS-negative cases.

Long non-coding RNA AGAP2-AS1 increases the invasiveness of papillary thyroid cancer

Papillary thyroid cancer (PTC) is considered a low hazard endocrine system cancer, but a considerable number of patients have poor prognosis because of lymph node metastasis and invasion of surrounding tissues. In this study, we analyzed the expression and function of the long non-coding RNA (lncRNA) AGAP2-AS1 in PTC. We found that AGAP2-AS1 expression was significantly higher in human PTC tissues than adjacent noncancerous tissues (n=110; p<0.01) and correlated with lymph node metastasis (p=0.01) and tumor-node-metastasis stage (p=0.006). AGAP2-AS1 downregulation decreased migration and invasion by PTC cells, and reduced expression of matrix metalloproteinase-2 (MMP2). AGAP2-AS1 upregulated MMP2 expression by competitively binding to microRNA-425-5p. In addition, miR-424-5p expression was decreased in PTC tissues and correlates negatively with the AGAP2-AS1 levels. These results demonstrate that AGAP2-AS1 expression is significantly elevated in PTC tissues and that, by binding to miRNA-425-5p, it upregulates the MMP2 expression, thereby increasing the invasiveness and migration capacity of PTC cells.

Beyond the Genomic Mutation: Rethinking the Molecular Biomarkers of K-RAS Dependency in Pancreatic Cancers

Oncogenic v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (K-RAS) plays a key role in the development and maintenance of pancreatic ductal adenocarcinoma (PDAC). The targeting of K-RAS would be beneficial to treat tumors whose growth depends on active K-RAS. The analysis of K-RAS genomic mutations is a clinical routine; however, an emerging question is whether the mutational status is able to identify tumors effectively dependent on K-RAS for tailoring targeted therapies. With the emergence of novel K-RAS inhibitors in clinical settings, this question is relevant. Several studies support the notion that the K-RAS mutation is not a sufficient biomarker deciphering the effective dependency of the tumor. Transcriptomic and metabolomic profiles of tumors, while revealing K-RAS signaling complexity and K-RAS-driven molecular pathways crucial for PDAC growth, are opening the opportunity to specifically identify K-RAS-dependent- or K-RAS-independent tumor subtypes by using novel molecular biomarkers. This would help tumor selection aimed at tailoring therapies against K-RAS. In this review, we will present studies about how the K-RAS mutation can also be interpreted in a state of K-RAS dependency, for which it is possible to identify specific K-RAS-driven molecular biomarkers in certain PDAC subtypes, beyond the genomic K-RAS mutational status.

Computer-aided drug repurposing for cancer therapy: Approaches and opportunities to challenge anticancer targets

Despite huge efforts made in academic and pharmaceutical worldwide research, current anticancer therapies achieve effective treatment in a limited number of neoplasia cases only. Oncology terms such as big killers - to identify tumours with yet a high mortality rate - or undruggable cancer targets, and chemoresistance, represent the current therapeutic debacle of cancer treatments. In addition, metastases, tumour microenvironments, tumour heterogeneity, metabolic adaptations, and immunotherapy resistance are essential features controlling tumour response to therapies, but still, lack effective therapeutics or modulators. In this scenario, where the pharmaceutical productivity and drug efficacy in oncology seem to have reached a plateau, the so-called drug repurposing - i.e. the use of old drugs, already in clinical use, for a different therapeutic indication - is an appealing strategy to improve cancer therapy. Opportunities for drug repurposing are often based on occasional observations or on time-consuming pre-clinical drug screenings that are often not hypothesis-driven. In contrast, in-silico drug repurposing is an emerging, hypothesis-driven approach that takes advantage of the use of big-data. Indeed, the extensive use of -omics technologies, improved data storage, data meaning, machine learning algorithms, and computational modeling all offer unprecedented knowledge of the biological mechanisms of cancers and drugs' modes of action, providing extensive availability for both disease-related data and drugs-related data. This offers the opportunity to generate, with time and cost-effective approaches, computational drug networks to predict, in-silico, the efficacy of approved drugs against relevant cancer targets, as well as to select better responder patients or disease' biomarkers. Here, we will review selected disease-related data together with computational tools to be exploited for the in-silico repurposing of drugs against validated targets in cancer therapies, focusing on the oncogenic signaling pathways activation in cancer. We will discuss how in-silico drug repurposing has the promise to shortly improve our arsenal of anticancer drugs and, likely, overcome certain limitations of modern cancer therapies against old and new therapeutic targets in oncology.