Pros and Cons of Pharmacological Manipulation of cGMP-PDEs in the Prevention and Treatment of Breast Cancer

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Objective

Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements.

Methods

Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets.

Results

We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Lessons from the physiological role of guanosine in neurodegeneration and cancer: Toward a multimodal mechanism of action?

Neurodegenerative diseases and brain tumours represent important health challenges due to their severe nature and debilitating consequences that require substantial medical care. Interestingly, these conditions share common physiological characteristics, namely increased glutamate, and adenosine transmission, which are often associated with cellular dysregulation and damage. Guanosine, an endogenous nucleoside, is safe and exerts neuroprotective effects in preclinical models of excitotoxicity, along with cytotoxic effects on tumour cells. However, the lack of well-defined mechanisms of action for guanosine hinders a comprehensive understanding of its physiological effects. In fact, the absence of specific receptors for guanosine impedes the development of structure-activity research programs to develop guanosine derivatives for therapeutic purposes. Alternatively, given its apparent interaction with the adenosinergic system, it is plausible that guanosine exerts its neuroprotective and anti-tumorigenic effects by modulating adenosine transmission through undisclosed mechanisms involving adenosine receptors, transporters, and purinergic metabolism. Here, several potential molecular mechanisms behind the protective actions of guanosine will be discussed. First, we explore its potential interaction with adenosine receptors (A1R and A2AR), including the A1R-A2AR heteromer. In addition, we consider the impact of guanosine on extracellular adenosine levels and the role of guanine-based purine-converting enzymes. Collectively, the diverse cellular functions of guanosine as neuroprotective and antiproliferative agent suggest a multimodal and complementary mechanism of action.

Phosphodiesterase Inhibition to Sensitize Non-Small-Cell Lung Cancer to Pemetrexed: A Double-Edged Strategy

Phosphosidesterases (PDEs) are key regulators of cyclic nucleotide signaling, controlling many hallmarks of cancer and playing a role in resistance to chemotherapy in non-small-cell lung cancer (NSCLC). We evaluated the anti-tumor activity of the anti-folate agent pemetrexed (PMX), alone or combined with biochemical inhibitors of PDE5, 8, 9, or 10, against squamous and non-squamous NCSLC cells. Genomic alterations to PDE genes (PDEmut) or PDE biochemical inhibition (PDEi) can sensitize NSCLC to PMX in vitro (observed in 50% NSCLC evaluated). The synergistic activity of PDEi with PMX required microdosing of the anti-folate drug. As single agents, none of the PDEis evaluated have anti-tumor activity. PDE biochemical inhibitors, targeting either cAMP or cGMP signaling (or both), resulted in significant cross-modulation of downstream pathways. The use of PDEi may present a new strategy to overcome PMX resistance of PDEwt NSCLC tumors but comes with important caveats, including the use of subtherapeutic PMX doses.

Exploring the Synergistic Effect of Sildenafil and Green Tea Polyphenols on Breast Cancer Stem Cell-like Cells and their Parental Cells: A Potential Novel Therapeutic Approach

BACKGROUND

Many cancer studies have intensely focused on the role of diet, among other factors involved in cancer establishment. The positive effect of green tea polyphenols (GTP) on controlling breast cancer cells has been reported in several studies. Cancer stem cell-like cells (CSC-LCs) possessing self-renewal, metastatic, and drug-resistant capacities are considered prominent therapeutic targets. In many tumors, inducible nitric oxide synthase (iNOS) expression levels are high; however, they have a dual effect on breast cancer pathogenesis.

OBJECTIVE

This study aimed to investigate the cytotoxicity of the iNOS agonist (Sildenafil) and antagonist (LNAME), both alone and in combination with GTP, on MDA-MB-231, CD44+/CD24- CSC-LCs, and their parental cells (MCF-7).

METHODS

The cell viability assay has been studied using the MTT assay. To analyze drug-drug combinations, CompuSyn and Combenefit software were used. The cytotoxicity mechanism was determined using flow cytometric analysis.

RESULTS

L-NAME and GTP showed a synergistic effect on MDA-MB-231 and CSC-LCs. Such an effect was not observed on MCF-7. Sildenafil and GTP, on the other hand, showed synergistic cytotoxicity in all the cells mentioned above. Flow cytometric tests resulted in more than 70% apoptosis in MDA-MB-231 and MCF-7. Also, sub-G1 arrest among MCF-7 cells and a considerable decrease in ROS production by MDA-MB-231 cells following treatment with Sildenafil and GTP were observed.

CONCLUSION

Sildenafil, in combination with flavonoids, may be considered a novel strategy for cancer treatment.

Pyrroline-5-carboxylate reductase 1 reprograms proline metabolism to drive breast cancer stemness under psychological stress

Cancer stem-like cells (CSCs) contribute to cancer metastasis, drug resistance and tumor relapse, yet how amino acid metabolism promotes CSC maintenance remains exclusive. Here, we identify that proline synthetase PYCR1 is critical for breast cancer stemness and tumor growth. Mechanistically, PYCR1-synthesized proline activates cGMP-PKG signaling to enhance cancer stem-like traits. Importantly, cGMP-PKG signaling mediates psychological stress-induced cancer stem-like phenotypes and tumorigenesis. Ablation of PYCR1 markedly reverses psychological stress-induced proline synthesis, cGMP-PKG signaling activation and cancer progression. Clinically, PYCR1 and cGMP-PKG signaling components are highly expressed in breast tumor specimens, conferring poor survival in breast cancer patients. Targeting proline metabolism or cGMP-PKG signaling pathway provides a potential therapeutic strategy for breast patients undergoing psychological stress. Collectively, our findings unveil that PYCR1-enhanced proline synthesis displays a critical role in maintaining breast cancer stemness.

Heterogeneity of cGMP signalling in tumour cells and the tumour microenvironment: Challenges and chances for cancer pharmacology and therapeutics

The second messenger cyclic guanosine monophosphate (cGMP) is an important regulator of human (patho-)physiology and has emerged as an attractive drug target. Currently, cGMP-elevating drugs are mainly used to treat cardiovascular diseases, but there is also increasing interest in exploring their potential for cancer prevention and therapy. In this review article, we summarise recent findings in cancer-related cGMP research, with a focus on melanoma, breast cancer, colorectal cancer, prostate cancer, glioma, and ovarian cancer. These studies indicate tremendous heterogeneity of cGMP signalling in tumour tissue. It appears that different tumour and stroma cells, and perhaps different sexes, express different cGMP generators, effectors, and degraders. Therefore, the same cGMP-elevating drug can lead to different outcomes in different tumour settings, ranging from inhibition to promotion of tumourigenesis or therapy resistance. These findings, together with recent evidence that increased cGMP signalling is associated with worse prognosis in several human cancers, challenge the traditional view that cGMP elevation generally has an anti-cancer effect. As cGMP pathways appear to be more stable in the stroma than in tumour cells, we suggest that cGMP-modulating drugs should preferentially target the tumour microenvironment. Indeed, there is evidence that phosphodiesterase 5 inhibitors like sildenafil enhance anti-tumour immunity by acting on immune cells. Moreover, many in vivo results obtained with cGMP-modulating drugs could be explained by effects on the tumour vasculature rather than on the tumour cells themselves. We therefore propose a model that incorporates the NO/cGMP signalling pathway in tumour vessels as a key target for cancer therapy. Deciphering the multifaceted roles of cGMP in cancer is not only a challenge for basic research, but also provides a chance to predict potential adverse effects of cGMP-modulating drugs in cancer patients and to develop novel anti-tumour therapies by precision targeting of the relevant cells and molecular pathways.

A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer

Precision medicine has emerged as an important paradigm in oncology, driven by the significant heterogeneity of individual patients' tumour. A key prerequisite for effective implementation of precision oncology is the development of companion biomarkers that can predict response to anti-cancer therapies and guide patient selection for clinical trials and/or treatment. However, reliable predictive biomarkers are currently lacking for many anti-cancer therapies, hampering their clinical application. Here, we developed a novel machine learning-based framework to derive predictive multi-gene biomarker panels and associated expression signatures that accurately predict cancer drug sensitivity. We demonstrated the power of the approach by applying it to identify response biomarker panels for an Hsp90-based therapy in prostate cancer, using proteomic data profiled from prostate cancer patient-derived explants. Our approach employs a rational feature section strategy to maximise model performance, and innovatively utilizes Boolean algebra methods to derive specific expression signatures of the marker proteins. Given suitable data for model training, the approach is also applicable to other cancer drug agents in different tumour settings.

Low Expression of Phosphodiesterase 2 (PDE2A) Promotes the Progression by Regulating Mitochondrial Morphology and ATP Content and Predicts Poor Prognosis in Hepatocellular Carcinoma

Phosphodiesterase 2 (PDE2A) modulates the levels of cAMP/cGMP and was recently found to be involved in mitochondria function regulation, closely related to multiple types of tumor progression. This study aimed to estimate the prognostic significance and biological effects of PDE2A on hepatocellular carcinoma (HCC). We comprehensively analyzed the PDE2A mRNA expression in HCC based on The Cancer Genome Atlas (TCGA) database and investigated the effects of PDE2A on the proliferation and metastatic capacity of HCC cells. PDE2A was downregulated in 25 cancer types, including HCC. Lower PDE2A expression was a protective factor in HCC and was negatively associated with serum AFP levels, tumor status, vascular invasion, histologic grade, and pathologic stage of HCC. Moreover, tumors with low PDE2A expression displayed a decreased immune function. Then, the ROC curve was used to assess the diagnostic ability of PDE2A in HCC (AUC = 0.823 in TCGA and AUC = 0.901 in GSE76427). Patients with low PDE2A expression exhibited worse outcomes compared with those with high PDE2A expression. Additionally, GO functional annotations demonstrated the involvement of PDE2A in the ECM organization, systems development, and ERK-related pathways, indicating that PDE2A might regulate HCC growth and metastasis. The in vitro experiments confirmed that overexpression of PDE2A inhibited proliferation, colony formation, migration, and invasion in two HCC cell lines (HLF and SNU-368), while inhibition of PDE2A has the opposite results. The mechanism of PDE2A's effect on HCC cells is attributed to the change of mitochondrial morphology and ATP content. These data demonstrated that PDE2A closely participated in the regulation of HCC proliferation and metastasis and can be used as a predictive marker candidate and a potential therapeutic target for HCC.

Functional characteristics and research trends of PDE11A in human diseases (Review)

cAMP and cGMP are important secondary messengers involved in cell regulation and metabolism driven by the G protein-coupled receptor. cAMP is converted via adenylyl cyclase (AC) and activates protein kinase A to phosphorylate intracellular proteins that mediate specific responses. cAMP signaling serves a role at multiple steps in tumorigenesis. The level of cAMP is increased in association with cancer cell formation through activation of AC-stimulatory G protein by mutation. Phosphodiesterases (PDEs) hydrolyze cAMP and cGMP to AMP and GMP. PDEs are composed of 11 families, and each can hydrolyze cAMP and cGMP or both cAMP and cGMP. PDEs perform various roles depending on their location and expression site, and are involved in several diseases, including male erectile dysfunction, pulmonary hypertension, Alzheimer's disease and schizophrenia. PDE11A is the 11th member of the PDE family and is characterized by four splice variants with varying tissue expression and N-terminal regulatory regions. Among tissues, the expression of PDE11A was highest in the prostate, and it was also expressed in hepatic skeletal muscle, pituitary, pancreas and kidney. PDE11A is the first PDE associated with an adrenocortical tumor associated genetic condition. In several studies, three PDE11A mutations have been reported in patients with Cushing syndrome with primary pigmented nodular adrenocortical disease or isolated micronodular adrenocortical disease without other genetic defects. It has been reported that an increase in PDE11A expression affects the proliferation of glioblastoma and worsens patient prognosis. The present mini-review summarizes the location of PDE11A expression, the impact of structural differences and disease relevance.

Editorial of the Special Issue: cGMP-Signaling in Cells and Tissues: Molecular, Functional and Pharmacological Aspects

Several important and novel aspects regarding signaling by cGMP were reported in the various publications of this Special Issue [...].

Repurposing PDE5 inhibitor tadalafil and sildenafil as anticancer agent against hepatocellular carcinoma via targeting key events of glucose metabolism and multidrug resistance

Hepatocellular carcinoma (HCC) has emerged as one of the most common and lethal cancers worldwide and is caused due to contamination of diets with aflatoxin B1 and chronic viral hepatitis. Recent reports suggest that phosphodiesterase-5 inhibitor (PDE5i) exhibits anticancer properties against several forms of cancer but till now has not been evaluated against HCC. We aimed to evaluate the anticancer property of phosphodiesterase-5 inhibitors (PDE5i) tadalafil and sildenafil against aflatoxin B1 HCC. Rats of HCC group were fed with 5% alcohol via drinking water for 3 weeks, followed by administration of AFB1 (1 mg/kg/bw, i.p.) at an interval of two subsequent days. PDE5i (tadalafil and sildenafil, 10 mg/kg bw) was administered along with drinking water after 6 weeks of treatment with AFB1 for 2 weeks. In the present investigation, in HCC elevation in the level of SGOT, SGPT, ALP, and urea vis-à-vis activity of key glycolytic enzyme LDH and mRNA expression of c-myc, Akt, LDH-A, and PFKFB3 was noted. Similarly, the level of multidrug resistance protein (MDR) and breast cancer resistance protein (BCRP/ABCG2) was elevated along with increased expression of angiogenesis marker (HIF-1α, VEGF, and TGF-β1) in HCC. Post-treatment with PDE5 inhibitor (tadalafil and sildenafil) downregulated and brought back the above parameters towards normal and out of two PDE5i (tadalafil and sildenafil), sildenafil effect was more potent as compared to tadalafil. Our findings demonstrate for the first time that PDE5 inhibitors tadalafil and sildenafil are able to prohibit the development and progression of aflatoxin B1 induced HCC.