Network neighborhood operates as a drug repositioning method for cancer treatment

Computational drug repositioning approaches are important, as they cost less compared to the traditional drug development processes. This study proposes a novel network-based drug repositioning approach, which computes similarities between disease-causing genes and drug-affected genes in a network topology to suggest candidate drugs with highest similarity scores. This new method aims to identify better treatment options by integrating systems biology approaches. It uses a protein-protein interaction network that is the main topology to compute a similarity score between candidate drugs and disease-causing genes. The disease-causing genes were mapped on this network structure. Transcriptome profiles of drug candidates were taken from the LINCS project and mapped individually on the network structure. The similarity of these two networks was calculated by different network neighborhood metrics, including Adamic-Adar, PageRank and neighborhood scoring. The proposed approach identifies the best candidates by choosing the drugs with significant similarity scores. The method was experimented on melanoma, colorectal, and prostate cancers. Several candidate drugs were predicted by applying AUC values of 0.6 or higher. Some of the predictions were approved by clinical phase trials or other in-vivo studies found in literature. The proposed drug repositioning approach would suggest better treatment options with integration of functional information between genes and transcriptome level effects of drug perturbations and diseases.

Niclosamide (NA) overcomes cisplatin resistance in human ovarian cancer

Ovarian cancer (OC) is one of the most lethal malignancies of the female reproductive system. OC patients are usually diagnosed at advanced stages due to the lack of early diagnosis. The standard treatment for OC includes a combination of debulking surgery and platinum-taxane chemotherapy, while several targeted therapies have recently been approved for maintenance treatment. The vast majority of OC patients relapse with chemoresistant tumors after an initial response. Thus, there is an unmet clinical need to develop new therapeutic agents to overcome the chemoresistance of OC. The anti-parasite agent niclosamide (NA) has been repurposed as an anti-cancer agent and exerts potent anti-cancer activities in human cancers including OC. Here, we investigated whether NA could be repurposed as a therapeutic agent to overcome cisplatin-resistant (CR) in human OC cells. To this end, we first established two CR lines SKOV3CR and OVCAR8CR that exhibit the essential biological characteristics of cisplatin resistance in human cancer. We showed that NA inhibited cell proliferation, suppressed cell migration, and induced cell apoptosis in both CR lines at a low micromole range. Mechanistically, NA inhibited multiple cancer-related pathways including AP1, ELK/SRF, HIF1, and TCF/LEF, in SKOV3CR and OVCAR8CR cells. NA was further shown to effectively inhibit xenograft tumor growth of SKOV3CR cells. Collectively, our findings strongly suggest that NA may be repurposed as an efficacious agent to combat cisplatin resistance in chemoresistant human OC, and further clinical trials are highly warranted.

Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA

BACKGROUND & AIMS

Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma.

METHODS

Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs.

RESULTS

5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%).

CONCLUSIONS

The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Transcriptomics-driven drug repositioning for the treatment of diabetic foot ulcer

Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU.

Repurposing of neprilysin inhibitor 'sacubitrilat' as an anti-cancer drug by modulating epigenetic and apoptotic regulators

Modifications in the epigenetic landscape have been considered a hallmark of cancer. Histone deacetylation is one of the crucial epigenetic modulations associated with the aggressive progression of various cancer subtypes. Herein, we have repurposed the neprilysin inhibitor sacubitrilat as a potent anticancer agent using in-silico protein-ligand interaction profiler (PLIP) analysis, molecular docking, and in vitro studies. The screening of PLIP profiles between vorinostat/panobinostat and HDACs/LTA4H followed by molecular docking resulted in five (Sacubitrilat, B65, BDS, BIR, and NPV) FDA-approved, experimental and investigational drugs. Sacubitrilat has demonstrated promising anticancer activity against colorectal cancer (SW-480) and triple-negative breast cancer (MDA-MB-231) cells, with IC₅₀ values of 14.07 μg/mL and 23.02 μg/mL, respectively. FACS analysis revealed that sacubitrilat arrests the cell cycle at the G0/G1 phase and induces apoptotic-mediated cell death in SW-480 cells. In addition, sacubitrilat inhibited HDAC isoforms at the transcriptomic level by 0.7-0.9 fold and at the proteomic level by 0.5-0.6 fold as compared to the control. Sacubitrilat increased the protein expression of tumor-suppressor (p53) and pro-apoptotic makers (Bax and Bid) by 0.2-2.5 fold while decreasing the expression of anti-apoptotic Bcl2 and Nrf2 proteins by 0.2-0.5 fold with respect to control. The observed cleaved PARP product indicates that sacubitrilat induces apoptotic-mediated cell death. This study may pave the way to identify the anticancer potential of sacubitrilat and can be explored in human clinical trials.

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

Introduction

Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes.

Methods

In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival.

Results

We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.

Conclusion

We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

Rational design, synthesis and structural characterization of peptides and peptidomimetics to target Hsp90/Cdc37 interaction for treating hepatocellular carcinoma

Heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) work together as a molecular chaperone complex to regulate the activity of a multitude of client protein kinases. These kinases belong to a wide array of intracellular signaling networks that mediate multiple cellular processes including proliferation. As a result, Hsp90 and Cdc37 represent innovative therapeutic targets in various cancers (such as leukemia, multiple myeloma, and hepatocellular carcinoma (HCC)) in which their expression levels are elevated. Conventional small molecule Hsp90 inhibitors act by blocking the conserved adenosine triphosphate (ATP) binding site. However, by targeting less conserved sites in a more specific manner, peptides and peptidomimetics (modified peptides) hold potential as more efficacious and less toxic alternatives to the conventional small molecule inhibitors. Using a rational approach, we herein developed bioactive peptides targeting Hsp90/Cdc37 interaction. A six amino acid linear peptide derived from Cdc37, KTGDEK, was designed to target Hsp90. We used in silico computational docking to first define its mode of interaction, and binding orientation, and then conjugated the peptide with a cell penetrating peptide, TAT, and a fluorescent dye to confirm its ability to colocalize with Hsp90 in HCC cells. Based on the parent linear sequence, we developed a peptidomimetics library of pre-cyclic and cyclic derivatives. These peptidomimetics were evaluated for their binding affinity to Hsp90, and bioactivity in HCC cell lines. Among them, a pre-cyclic peptidomimetic demonstrates high binding affinity and bioactivity in HCC cells, causing reduced cell proliferation that is associated with induction of cell apoptosis, and down-regulation of phosphorylated MEK1/2. Overall, this generalized approach of rational design, structural optimization, and cellular validation of 'drug-like' peptidomimetics against Hsp90/Cdc37 offers a feasible and promising way to design novel therapeutic agents for malignancies and other diseases that are dependent on this molecular chaperone complex.

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

BACKGROUND

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable.

METHODS

We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples.

RESULTS

In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220-500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (88.52% and 82.35%, respectively).

CONCLUSION

We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.

Effects of adjuvant huaier granule therapy on survival rate of patients with hepatocellular carcinoma

Objective: Clinical trials have reported that Huaier granule inhibits the recurrence of hepatocellular carcinoma (HCC) after resection. However, its efficacy in patients at different clinical stages of HCC remains unknown. We investigated the effects of Huaier granule on the 3-year overall survival (OS) rate of patients at different clinical stages. Design: This cohort study included 826 patients with HCC, screened between January 2015 and December 2019. The patients were divided into Huaier (n = 174) and control groups (n = 652), and the 3-year OS rates were compared between the two groups. To eliminate bias caused by confounding factors, propensity score matching (PSM) was performed. We used the Kaplan-Meier method to estimate OS rate and tested the difference using the log-rank test. Results: Multivariable regression analysis revealed that Huaier therapy was an independent protective factor for 3-year survival rate. After PSM (1:2), the Huaier and control groups comprised 170 and 340 patients, respectively. The 3-year OS rate was remarkably higher in the Huaier group than in the control group (adjusted hazard ratio [aHR]: 0.36; 95% confidence interval: 0.26-0.49; p < 0.001). The aHR for Huaier use for 3-12, 12-24, and >24 months was 0.48, 0.23, and 0.16, respectively, indicating a dose-response pattern. For the 3-12-, 12-24-, and >24-month groups, the 3-year OS rate was 54.1%, 68.6%, and 90.4%, respectively. Multivariate stratified analysis confirmed that the mortality risk in Huaier users was lower than that in non-Huaier users in most subgroups. Conclusion: Adjuvant Huaier therapy improved the OS rate in patients with HCC. However, these findings require further verification through prospective clinical studies.

Role of lncRNAs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is among the deadliest cancer in human malignancies. It is the most common and severe type of primary liver cancer. However, the molecular mechanisms underlying HCC pathogenesis remain poorly understood. Long non-coding RNAs (lncRNAs), a new kind of RNA and epigenetic factors, play a crucial role in tumorigenesis and the progression of HCC. LncRNAs are capable of promoting the autophagy, proliferation, and migration of tumor cells by targeting and modulating the expression of downstream genes in signaling pathways related to cancer; these transcripts modify the activity and expression of various tumor suppressors and oncogenes. LncRNAs could act as biomarkers for treatment approaches such as immunotherapy, chemotherapy, and surgery to effectively treat HCC patients. Improved knowledge regarding the aetiology of HCC may result from an advanced understanding of lncRNAs. Enhanced oxidative stress in the mitochondrial and Endoplasmic reticulum leads to the activation of unfolded protein response pathway that plays a crucial role in the pathophysiology of hepatocellular carcinoma. The mutual regulation between LncRNAs and Endoplasmic reticulum (ER) stress in cancer and simultaneous activation of the unfolded protein response (UPR) pathway determines the fate of tumor cells in HCC. Mitochondria-associated lncRNAs work as essential components of several gene regulatory networks; abnormal regulation of mitochondria-associated lncRNAs may lead to oncogenesis, which provides further insight into the understanding of tumorigenesis and therapeutic strategies.

Neutrophil-to-high-density-lipoprotein-cholesterol ratio and mortality among patients with hepatocellular carcinoma

Background

Inflammatory responses and lipid metabolism disorders contribute to the development and prognosis of hepatocellular carcinoma (HCC). This study aimed to investigate the prognostic value of lipid-related inflammatory parameters in patients with HCC.

Methods

From January 2010 to June 2017, we enrolled 1,639 patients with HCC at Beijing Ditan Hospital. Multivariate Cox regression analysis and area under the receiver operating characteristic (AUC) analysis were used to evaluate and compare the predictability and reliability of high-density lipoprotein cholesterol (HDL-C), neutrophil-to-HDL-C ratio (NHR), monocyte-to-HDL-C ratio (MHR), and lymphocyte-to-HDL-C ratio (LHR) values. A restricted cubic spline was used to explore the association between the NHR and 3-year mortality in patients with HCC. Differences in survival rates were estimated using the Kaplan-Meier method and compared using the log-rank test. The results were validated in an internal cohort between July 2017 and October 2019 (n = 373).

Results

After adjusting for confounding variables, NHR was independently associated with 3-year mortality, both as a continuous and categorical variable (both p < 0.05). The correlation between the mortality and the MHR and LHR was not statistically significant. The NHR showed a suitable prognostic value (AUC at 3 years: 0.740), similar to that of the Model for End-stage Liver Disease (MELD) (AUC at 3 years: 0.761). In the validation cohort, the AUC of the NHR was 0.734 at 3 years. The optimal cut-off values of NHR and MELD were 3.5 and 9, respectively. The 3-year survival rates in the low- (NHR < 3.5 and MELD <9) and high-risk (NHR ≥ 3.5 and MELD ≥9) groups were 81.8 and 19.4%, respectively, in the training cohort, and 84.6 and 27.5%, respectively, in the validation cohort.

Conclusion

Baseline NHR is a promising prognostic parameter for mortality in patients with HCC and patients with NHR ≥ 3.5 and MELD ≥9 have a high mortality rate.

Liquid biopsy in hematological malignancies: current and future applications

The assessment of the cancer mutational profile is crucial for patient management, stratification, and therapeutic decisions. At present, in hematological malignancies with a solid mass, such as lymphomas, tumor genomic profiling is generally performed on the tissue biopsy, but the tumor may harbor genetic lesions that are unique to other anatomical compartments. The analysis of circulating tumor DNA (ctDNA) on the liquid biopsy is an emerging approach that allows genotyping and monitoring of the disease during therapy and follow-up. This review presents the different methods for ctDNA analysis and describes the application of liquid biopsy in different hematological malignancies. In diffuse large B-cell lymphoma (DLBCL) and Hodgkin lymphoma (HL), ctDNA analysis on the liquid biopsy recapitulates the mutational profile of the tissue biopsy and can identify mutations otherwise absent on the tissue biopsy. In addition, changes in the ctDNA amount after one or two courses of chemotherapy significantly predict patient outcomes. ctDNA analysis has also been tested in myeloid neoplasms with promising results. In addition to mutational analysis, liquid biopsy also carries potential future applications of ctDNA, including the analysis of ctDNA fragmentation and epigenetic patterns. On these grounds, several clinical trials aiming at incorporating ctDNA analysis for treatment tailoring are currently ongoing in hematological malignancies.

Noninvasive detection of brain gliomas using plasma cell-free DNA 5-hydroxymethylcytosine sequencing

Liquid biopsy techniques based on deep sequencing of plasma cell-free DNA (cfDNA) could detect the low-frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5-hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe-Seal). We first constructed a dataset including 180 glioma patients and 229 non-glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild-type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P = .01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma-specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors.

Towards a Synthesis of the Non-Genetic and Genetic Views of Cancer in Understanding Pancreatic Ductal Adenocarcinoma Initiation and Prevention

While much of the research in oncogenesis and cancer therapy has focused on mutations in key cancer driver genes, more recent work suggests a complementary non-genetic paradigm. This paradigm focuses on how transcriptional and phenotypic heterogeneity, even in clonally derived cells, can create sub-populations associated with oncogenesis, metastasis, and therapy resistance. We discuss this complementary paradigm in the context of pancreatic ductal adenocarcinoma. A better understanding of cellular transcriptional heterogeneity and its association with oncogenesis can lead to more effective therapies that prevent tumor initiation and slow progression.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

The Role of WNT Pathway Mutations in Cancer Development and an Overview of Therapeutic Options

It is well established that mutations in the canonical WNT-signalling pathway play a major role in various cancers. Critical to developing new therapeutic strategies is understanding which cancers are driven by WNT pathway activation and at what level these mutations occur within the pathway. Some cancers harbour mutations in genes whose protein products operate at the receptor level of the WNT pathway. For instance, tumours with RNF43 or RSPO mutations, still require exogenous WNT ligands to drive WNT signalling (ligand-dependent mutations). Conversely, mutations within the cytoplasmic segment of the Wnt pathway, such as in APC and CTNNB1, lead to constitutive WNT pathway activation even in the absence of WNT ligands (ligand-independent). Here, we review the predominant driving mutations found in cancer that lead to WNT pathway activation, as well as explore some of the therapeutic interventions currently available against tumours harbouring either ligand-dependent or ligand-independent mutations. Finally, we discuss a potentially new therapeutic avenue by targeting the translational apparatus downstream from WNT signalling.

Pyridine-Based 1,2,4-Triazolo-Tethered Indole Conjugates Potentially Affecting TNKS and PI3K in Colorectal Cancer

A library of pyridine-based 1,2,4-triazolo-tethered indole conjugates were designed, synthesized, and evaluated for anti-proliferative activity against a panel of six human cancer cell lines. All the synthesized conjugates (14a-q) were found to be effective against the HT-29 cell line. Particularly conjugates 14a, 14n, and 14q exhibited promising cytotoxicity, with IC50 values of 1 μM, 2.4 μM, and 3.6 μM, respectively, compared to the standard 5-fluorouracil (IC50 = 5.31 μM). Cell cycle arrest at the G0/G1 phase was observed with these compounds, the mitochondrial membrane potential was interrupted, and the total ROS production was enhanced. Western blot and immunofluorescence experiments illustrated that these compounds inhibit the expression of markers that are involved in β-catenin and PI3K pathways. Molecular dynamics simulations demonstrated that compound 14a has major hydrophobic interactions and few H-bonding interactions with both PI3K and tankyrase proteins.

A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods

The robustness of a breast cancer gene signature, the super-proliferation set (SPS), is initially tested and investigated on breast cancer cell lines from the Cancer Cell Line Encyclopaedia (CCLE). Previously, SPS was derived via a meta-analysis of 47 independent breast cancer gene signatures, benchmarked on survival information from clinical data in the NKI dataset. Here, relying on the stability of cell line data and associative prior knowledge, we first demonstrate through Principal Component Analysis (PCA) that SPS prioritizes survival information over secondary subtype information, surpassing both PAM50 and Boruta, an artificial intelligence-based feature-selection algorithm, in this regard. We can also extract higher resolution 'progression' information using SPS, dividing survival outcomes into several clinically relevant stages ('good', 'intermediate', and 'bad) based on different quadrants of the PCA scatterplot. Furthermore, by transferring these 'progression' annotations onto independent clinical datasets, we demonstrate the generalisability of our method on actual patient data. Finally, via the characteristic genetic profiles of each quadrant/stage, we identified efficacious drugs using their gene reversal scores that can shift signatures across quadrants/stages, in a process known as gene signature reversal. This confirms the power of meta-analytical approaches for gene signature inference in breast cancer, as well as the clinical benefit in translating these inferences onto real-world patient data for more targeted therapies.

An Innovative Drug Repurposing Approach to Restrain Endometrial Cancer Metastatization

BACKGROUND

Endometrial cancer (EC) is the most common gynecologic tumor and the world's fourth most common cancer in women. Most patients respond to first-line treatments and have a low risk of recurrence, but refractory patients, and those with metastatic cancer at diagnosis, remain with no treatment options. Drug repurposing aims to discover new clinical indications for existing drugs with known safety profiles. It provides ready-to-use new therapeutic options for highly aggressive tumors for which standard protocols are ineffective, such as high-risk EC.

METHODS

Here, we aimed at defining new therapeutic opportunities for high-risk EC using an innovative and integrated computational drug repurposing approach.

RESULTS

We compared gene-expression profiles, from publicly available databases, of metastatic and non-metastatic EC patients being metastatization the most severe feature of EC aggressiveness. A comprehensive analysis of transcriptomic data through a two-arm approach was applied to obtain a robust prediction of drug candidates.

CONCLUSIONS

Some of the identified therapeutic agents are already successfully used in clinical practice to treat other types of tumors. This highlights the potential to repurpose them for EC and, therefore, the reliability of the proposed approach.

EBS-seq: enrichment-based method for accurate analysis of 5-hydroxymethylcytosine at single-base resolution

BACKGROUND

A growing body of research has emphasized 5-hydroxymethylcytosine (5hmC) as an important epigenetic mark. High-resolution methods to detect 5hmC require high sequencing depth and are therefore expensive. Many studies have used enrichment-based methods to detect 5hmC; however, conventional enrichment-based methods have limited resolution. To overcome these limitations, we developed EBS-seq, a cost-efficient method for 5hmC detection with single-base resolution that combines the advantages of high-resolution methods and enrichment-based methods.

RESULTS

EBS-seq uses selective labeling of 5hmC, deamination of cytosine and 5-methylcytosine, pull-down of labeled 5hmC, and C-to-T conversion during DNA amplification. Using this method, we profiled 5hmC in HEK293T cells and two colorectal cancer samples. Compared with conventional enrichment-based 5hmC detection, EBS-seq improved 5hmC signals by localizing them at single-base resolution. Furthermore, EBS-seq was able to determine 5hmC levels in CpG-dense regions where distortion of signals can occur, such as CpG islands and CpG shores. Comparing EBS-seq and conventional high-resolution 5hmC detection by ACE-seq, we showed that EBS-seq is more effective at finding 5hmC sites. Using EBS-seq, we found strong associations between gene expression and gene-body 5hmC content in both HEK293T cells and colorectal cancer samples.

CONCLUSIONS

EBS-seq is a reliable and cost-efficient method for 5hmC detection because it simultaneously enriches 5hmC-containing DNA fragments and localizes 5hmC signals at single-base resolution. This method is a promising choice for 5hmC detection in challenging clinical samples with low 5hmC levels, such as cancer tissues.

Epigenetic reprogramming in cancer: From diagnosis to treatment

Disruption of the epigenetic program of gene expression is a hallmark of cancer that initiates and propagates tumorigenesis. Altered DNA methylation, histone modifications and ncRNAs expression are a feature of cancer cells. The dynamic epigenetic changes during oncogenic transformation are related to tumor heterogeneity, unlimited self-renewal and multi-lineage differentiation. This stem cell-like state or the aberrant reprogramming of cancer stem cells is the major challenge in treatment and drug resistance. Given the reversible nature of epigenetic modifications, the ability to restore the cancer epigenome through the inhibition of the epigenetic modifiers is a promising therapy for cancer treatment, either as a monotherapy or in combination with other anticancer therapies, including immunotherapies. Herein, we highlighted the main epigenetic alterations, their potential as a biomarker for early diagnosis and the epigenetic therapies approved for cancer treatment.

Hydroxymethylation and Epigenetic Drugs: New Insights into the Diagnosis and Treatment in Epigenetics of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly lethal and heterogeneous malignancy with multiple genetic alternations and complex signaling pathways. The complexity and multifactorial nature of HCC pose a tremendous challenge regarding its diagnosis and treatment. Emerging evidence has indicated an important regulatory role of epigenetic modifications in HCC initiation and progression. Epigenetic modifications are stably heritable gene expression traits caused by changing the accessibility of chromatin structure and genetic activity without alteration in the DNA sequence and have been gradually recognized as a hallmark of cancer. In addition, accumulating data suggest a potential value of altered hydroxymethylation in epigenetic modifications and therapeutics targeting the epigenetically mediated regulation. As such, probing the epigenetic field in the era of precision oncology is a valid avenue for promoting the accuracy of early diagnosis and improving the oncological prognosis of HCC patients. This review focuses on the diagnostic performance and clinical utility of 5-hydroxymethylated cytosine, the primary intermediate product of the demethylation process, for early HCC diagnosis and discusses the promising applications of epigenetic-based therapeutic regimens for HCC.

Multiplexed, single-molecule, epigenetic analysis of plasma-isolated nucleosomes for cancer diagnostics

The analysis of cell-free DNA (cfDNA) in plasma provides information on pathological processes in the body. Blood cfDNA is in the form of nucleosomes, which maintain their tissue- and cancer-specific epigenetic state. We developed a single-molecule multiparametric assay to comprehensively profile the epigenetics of plasma-isolated nucleosomes (EPINUC), DNA methylation and cancer-specific protein biomarkers. Our system allows for high-resolution detection of six active and repressive histone modifications and their ratios and combinatorial patterns on millions of individual nucleosomes by single-molecule imaging. In addition, our system provides sensitive and quantitative data on plasma proteins, including detection of non-secreted tumor-specific proteins, such as mutant p53. EPINUC analysis of a cohort of 63 colorectal cancer, 10 pancreatic cancer and 33 healthy plasma samples detected cancer with high accuracy and sensitivity, even at early stages. Finally, combining EPINUC with direct single-molecule DNA sequencing revealed the tissue of origin of colorectal, pancreatic, lung and breast tumors. EPINUC provides multilayered information of potential clinical relevance from limited (<1 ml) liquid biopsy material.

Niclosamide Revitalizes Sorafenib through Insulin-like Growth Factor 1 Receptor (IGF-1R)/Stemness and Metabolic Changes in Hepatocellular Carcinoma

Sorafenib is the first approved systemic targeting agent for advanced HCC; however, when used alone, drug resistance can result in considerably reduced efficacy. Here, we demonstrate that niclosamide, an antihelminthic agent approved by the US Food and Drug Administration, can be repurposed to increase sorafenib sensitivity in sorafenib-resistant HCC cells. We generated sorafenib-resistant HCC cell lines (HepG2215_R and Hep3B_R) with elevated IGF-1R levels and strong properties in terms of stemness and epithelial-mesenchymal transition. Niclosamide was found to increase sorafenib sensitivity effectively in both cell lines and their organoids. The underlying mechanism involves the modulation of cancer stemness, IGF-1R/p-IGF1R/OCT4, and metabolic changes. The combination of sorafenib and niclosamide, but not linsitinib, effectively suppressed the IGF-1R/OCT4 expressions, yielded a synergistic combination index (CI), and attenuated stemness-related properties such as secondary tumor sphere formation and cell migration in sorafenib-resistant HCC cells. Notably, niclosamide significantly suppressed the sorafenib-induced IGF-1R phosphorylation prompted by IGF-1 treatment. Niclosamide effectively downregulated the sorafenib-induced gene expression associated with glycolysis (GLUT1, HK2, LDHA, and PEPCK), stemness (OCT4), and drug resistance (ABCG2) and enhanced the ability of sorafenib to reduce the mitochondrial membrane potential in vitro. The synergistic effect of a combination of niclosamide and sorafenib in vivo was further demonstrated by the decreased tumor size and tumor volume resulting from apoptosis regulation. Our results suggest that niclosamide can enhance sorafenib sensitivity in sorafenib-resistant HCC cells through IGF-1R/stemness regulation and metabolic changes. Our findings highlight a practical clinical strategy for enhancing sorafenib sensitivity in HCC.

Circulating Tumor DNA Methylation Biomarkers for Characterization and Determination of the Cancer Origin in Malignant Liver Tumors

Malignant liver tumors include primary malignant liver tumors and liver metastases. They are among the most common malignancies worldwide. The disease has a poor prognosis and poor overall survival, especially with liver metastases. Therefore, early detection and differentiation between malignant liver tumors are critical for patient treatment selection. The detection of cancer and the prediction of its origin is possible with a DNA methylation profile of the tumor DNA compared to that of normal cells, which reflects tissue differentiation and malignant transformation. New technologies enable the characterization of the tumor methylome in circulating tumor DNA (ctDNA), providing a variety of new ctDNA methylation biomarkers, which can provide additional information to clinical decision-making. Our review of the literature provides insight into methylation changes in ctDNA from patients with common malignant liver tumors and can serve as a starting point for further research.

Advances in biomarker discovery using circulating cell-free DNA for early detection of hepatocellular carcinoma

The past several decades have witnessed unprecedented progress in basic and clinical cancer research, and our understanding of the molecular mechanisms and pathogenesis of cancers have been greatly improved. More recently, with the availability of high-throughput sequencing and profiling platforms as well as sophisticated analytical tools and high-performance computing capacity, there have been tremendous advances in the development of diagnostic approaches in clinical oncology, especially the discovery of novel biomarkers for cancer early detection. Although tissue biopsy-based pathology has been the "gold standard" for cancer diagnosis, notable limitations such as the risk due to invasiveness and the bias due to intra-tumoral heterogeneity have limited its broader applications in oncology (e.g., screening, regular disease monitoring). Liquid biopsy analysis that exploits the genetic and epigenetic information contained in DNA/RNA materials from body fluids, particularly circulating cell-free DNA (cfDNA) in the blood, has been an intriguing alternative approach because of advantageous features such as sampling convenience and minimal invasiveness. Taking advantage of innovative enabling technologies, cfDNA has been demonstrated for its clinical potential in cancer early detection, including hepatocellular carcinoma (HCC), the most common liver cancer that causes serious healthcare burden globally. Hereby, we reviewed the current advances in cfDNA-based approaches for cancer biomarker discovery, with a focus on recent findings of cfDNA-based early detection of HCC. Future clinical investigations and trials are warranted to further validate these approaches for early detection of HCC, which will contribute to more effective prevention, control, and intervention strategies with the ultimate goal of reducing HCC-associated mortality. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics.

DNA methylation analysis explores the molecular basis of plasma cell-free DNA fragmentation

Plasma cell-free DNA (cfDNA) are small molecules generated through a non-random fragmentation procedure. Despite commendable translational values in cancer liquid biopsy, however, the biology of cfDNA, especially the principles of cfDNA fragmentation, remains largely elusive. Through orientation-aware analyses of cfDNA fragmentation patterns against the nucleosome structure and integration with multidimensional functional genomics data, here we report a DNA methylation - nuclease preference - cutting end - size distribution axis, demonstrating the role of DNA methylation as a functional molecular regulator of cfDNA fragmentation. Hence, low-level DNA methylation could increase nucleosome accessibility and alter the cutting activities of nucleases during DNA fragmentation, which further leads to variation in cutting sites and size distribution of cfDNA. We further develop a cfDNA ending preference-based metric for cancer diagnosis, whose performance has been validated by multiple pan-cancer datasets. Our work sheds light on the molecular basis of cfDNA fragmentation towards broader applications in cancer liquid biopsy.

Role of epigenetics in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, associated with poor survival outcomes. Lack of early diagnosis, resistance to conventional therapeutic treatments (including immunotherapy) and recurrence are some of the major hurdles in PDAC and contribute to its poor survival rate. While the risk of genetic predisposition to cancers is widely acknowledged and understood, recent advances in whole-genome and next-generation sequencing techniques have led to the acknowledgment of the role played by epigenetics, especially in PDAC. Epigenetic changes are heritable genetic modifications that influence gene expression without altering the DNA sequence. Epigenetic mechanisms (e.g., DNA methylation, post-translational modification of histone complexes and ncRNA) that result in reversible changes in gene expression are increasingly understood to be responsible for tumor initiation, development and even escape from immune surveillance. Our review seeks to highlight the various components of the epigenetic machinery that are known to be implicated in PDAC initiation and development and the feasibility of targeting these components to identify novel pharmacological strategies that could potentially lead to breakthroughs in PDAC treatment.

A comprehensive tool for tumor precision medicine with pharmaco-omics data analysis

Background: Cancer precision medicine is an effective strategy to fight cancers by bridging genomics and drug discovery to provide specific treatment for patients with different genetic characteristics. Although some public databases and modelling frameworks have been developed through studies on drug response, most of them only considered the ramifications of the drug on the cell line and the effects on the patient still require a huge amount of work to integrate data from various databases and calculations, especially concerning precision treatment. Furthermore, not only efficacy but also the adverse effects of drugs on patients should be taken into account during cancer treatment. However, the adverse effects as essential indicators of drug safety assessment are always neglected. Method: A holistic estimation explores various drugs' efficacy levels by calculating their potency both in reversing and enhancing cancer-associated gene expression change. And a method for bridging the gap between cell culture and living tissue estimates the effectiveness of a drug on individual patients through the mappings of various cell lines to each person according to their genetic mutation similarities. Result: We predicted the efficacy of FDA-recommended drugs, taking into account both efficacy and toxicity, and obtained consistent results. We also provided an intuitive and easy-to-use web server called DBPOM (http://www.dbpom.net/, a comprehensive database of pharmaco-omics for cancer precision medicine), which not only integrates the above methods but also provides calculation results on more than 10,000 small molecule compounds and drugs. As a one-stop web server, clinicians and drug researchers can also analyze the overall effect of a drug or a drug combination on cancer patients as well as the biological functions that they target. DBPOM is now public, free to use with no login requirement, and contains all the data and code. Conclusion: Both the positive and negative effects of drugs during precision treatment are essential for practical application of drugs. DBPOM based on the two effects will become a vital resource and analysis platform for drug development, drug mechanism studies and the discovery of new therapies.

Sex-Specific miRNA Differences in Liquid Biopsies from Subjects with Solid Tumors and Healthy Controls

Dysregulation of epigenetic mechanisms has been recognized to play a crucial role in cancer development, but these mechanisms vary between sexes. Therefore, we focused on sex-specific differences in the context of cancer-based data from a recent study. A total of 12 cell-free DNA methylation targets in CpG-rich promoter regions and 48 miRNAs were analyzed by qPCR in plasma samples from 8 female and 7 male healthy controls as well as 48 female and 80 male subjects with solid tumors of the bladder, brain, colorectal region (CRC), lung, stomach, pancreas, and liver. Due to the small sample size in some groups and/or the non-balanced distribution of men and women, sex-specific differences were evaluated statistically only in healthy subjects, CRC, stomach or pancreas cancer patients, and all cancer subjects combined (n female/male-8/7, 14/14, 8/15, 6/6, 48/80, respectively). Several miRNAs with opposing expressions between the sexes were observed for healthy subjects (miR-17-5p, miR-26b-5p); CRC patients (miR-186-5p, miR-22-3p, miR-22-5p, miR-25-3p, miR-92a-3p, miR-16-5p); stomach cancer patients (miR-133a-3p, miR-22-5p); and all cancer patients combined (miR-126-3p, miR-21-5p, miR-92a-3p, miR-183-5p). Moreover, sex-specific correlations that were dependent on cancer stage were observed in women (miR-27a-3p) and men (miR-17-5p, miR-20a-5p). Our results indicate the complex and distinct role of epigenetic regulation, particularly miRNAs, depending not only on the health status but also on the sex of the patient. The same miRNAs could have diverse effects in different tissues and opposing effects between the biological sexes, which should be considered in biomarker research.

Multiscale Analysis and Validation of Effective Drug Combinations Targeting Driver KRAS Mutations in Non-Small Cell Lung Cancer

Pharmacogenomics is a rapidly growing field with the goal of providing personalized care to every patient. Previously, we developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to screen optimal compounds for any indication/disease by performing analytics on their interactions using large protein libraries. We implemented a comprehensive precision medicine drug discovery pipeline within the CANDO platform to determine which drugs are most likely to be effective against mutant phenotypes of non-small cell lung cancer (NSCLC) based on the supposition that drugs with similar interaction profiles (or signatures) will have similar behavior and therefore show synergistic effects. CANDO predicted that osimertinib, an EGFR inhibitor, is most likely to synergize with four KRAS inhibitors.Validation studies with cellular toxicity assays confirmed that osimertinib in combination with ARS-1620, a KRAS G12C inhibitor, and BAY-293, a pan-KRAS inhibitor, showed a synergistic effect on decreasing cellular proliferation by acting on mutant KRAS. Gene expression studies revealed that MAPK expression is strongly correlated with decreased cellular proliferation following treatment with KRAS inhibitor BAY-293, but not treatment with ARS-1620 or osimertinib. These results indicate that our precision medicine pipeline may be used to identify compounds capable of synergizing with inhibitors of KRAS G12C, and to assess their likelihood of becoming drugs by understanding their behavior at the proteomic/interactomic scales.

Signature-Based Computational Drug Repurposing for Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a late-onset fatal neurodegenerative disease characterized by progressive loss of the upper and lower motor neurons. There are currently limited approved drugs for the disorder, and for this reason the strategy of repositioning already approved therapeutics could exhibit a successful outcome. Herein, we used CMAP and L1000CDS2 databases which include gene expression profiles datasets (genomic signatures) to identify potent compounds and classes of compounds which reverse disease's signature which could in turn reverse its phenotype. ALS signature was obtained by comparing gene expression of muscle biopsy specimens between diseased and healthy individuals. Statistical analysis was conducted to explore differentially transcripts in patients' samples. Then, the list of upregulated and downregulated genes was used to query both databases in order to determine molecules which downregulate the genes which are upregulated by ALS and vice versa. These compounds, based on their chemical structure along with known treatments, were clustered to reveal drugs with novel and potentially more effective mode of action with most of them predicted to affect pathways heavily involved in ALS. This evidence suggests that these compounds are strong candidates for moving to the next phase of the drug repurposing pipeline which is in vitro and in vivo experimental evaluation.

Drug repositioning prediction for psoriasis using the adverse event reporting database

Introduction

Inverse signals produced from disproportional analyses using spontaneous drug adverse event reports can be used for drug repositioning purposes. The purpose of this study is to predict drug candidates using a computational method that integrates reported drug adverse event data, disease-specific gene expression profiles, and drug-induced gene expression profiles.

Methods

Drug and adverse events from 2015 through 2020 were downloaded from the United States Food and Drug Administration Adverse Event Reporting System (FAERS). The reporting odds ratio (ROR), information component (IC) and empirical Bayes geometric mean (EBGM) were used to calculate the inverse signals. Psoriasis was selected as the target disease. Disease specific gene expression profiles were obtained by the meta-analysis of the Gene Expression Omnibus (GEO). The reverse gene expression scores were calculated using the Library of Integrated Network-based Cellular Signatures (LINCS) and their correlations with the inverse signals were obtained.

Results

Reversal genes and the candidate compounds were identified. Additionally, these correlations were validated using the relationship between the reverse gene expression scores and the half-maximal inhibitory concentration (IC50) values from the Chemical European Molecular Biology Laboratory (ChEMBL).

Conclusion

Inverse signals produced from a disproportional analysis can be used for drug repositioning and to predict drug candidates against psoriasis.

Wnt signaling in liver regeneration, disease, and cancer

The liver exhibits the highest recovery rate from acute injuries. However, in chronic liver disease, the long-term loss of hepatocytes often leads to adverse consequences such as fibrosis, cirrhosis, and liver cancer. The Wnt signaling plays a pivotal role in both liver regeneration and tumorigenesis. Therefore, manipulating the Wnt signaling has become an attractive approach to treating liver disease, including cancer. Nonetheless, given the crucial roles of Wnt signaling in physiological processes, blocking Wnt signaling can also cause several adverse effects. Recent studies have identified cancer-specific regulators of Wnt signaling, which would overcome the limitation of Wnt signaling target approaches. In this review, we discussed the role of Wnt signaling in liver regeneration, precancerous lesion, and liver cancer. Furthermore, we summarized the basic and clinical approaches of Wnt signaling blockade and proposed the therapeutic prospects of cancer-specific Wnt signaling blockade for liver cancer treatment.

Niclosamide as a Promising Therapeutic Player in Human Cancer and Other Diseases

Niclosamide is an FDA-approved anthelmintic drug for the treatment of parasitic infections. However, over the past few years, increasing evidence has shown that niclosamide could treat diseases beyond parasitic diseases, which include metabolic diseases, immune system diseases, bacterial and viral infections, asthma, arterial constriction, myopia, and cancer. Therefore, we systematically reviewed the pharmacological activities and therapeutic prospects of niclosamide in human disease and cancer and summarized the related molecular mechanisms and signaling pathways, indicating that niclosamide is a promising therapeutic player in various human diseases, including cancer.

Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

BACKGROUND

DNA methylation (5-mC) signals in cell-free DNA (cfDNA) of cancer patients represent promising biomarkers for minimally invasive tumor detection. The high abundance of cancer-associated 5-mC alterations permits parallel and highly sensitive assessment of multiple 5-mC biomarkers. Here, we performed genome-wide 5-mC profiling in the plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis, and therapy monitoring.

METHODS

Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples was available from previous studies.

RESULTS

We devised a strategy that identified tumor-specific 5-mC biomarkers by reducing 5-mC background signals derived from hematopoietic cells. This was followed by differential methylation analysis (cases vs. controls) and biomarker validation using 5-mC profiles of ALK-positive tumor tissues. The resulting 245 differentially methylated regions were enriched for lung adenocarcinoma-specific 5-mC patterns in TCGA data and indicated transcriptional repression of several genes described to be silenced in NSCLC (e.g., PCDH10, TBX2, CDO1, and HOXA9). Additionally, 5-mC-based tumor DNA (5-mC score) was highly correlated with other genomic alterations in cell-free DNA (Spearman, ρ > 0.6), while samples with high 5-mC scores showed significantly shorter overall survival (log-rank p = 0.025). Longitudinal 5-mC scores reflected radiologic disease assessments and were significantly elevated at disease progression compared to the therapy start (p = 0.0023). In 7 out of 8 instances, rising 5-mC scores preceded imaging-based evaluation of disease progression.

CONCLUSION

We demonstrated a strategy to identify 5-mC biomarkers from the plasma of cancer patients and integrated them into a quantitative measure of cancer-associated 5-mC alterations. Using longitudinal plasma samples of ALK-positive NSCLC patients, we highlighted the suitability of cfDNA methylation for prognosis and therapy monitoring.

Validation of transcriptome signature reversion for drug repurposing in oncology

Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types. TSR relies on the assumption that a drug that can revert gene expression changes induced by a disease back to original, i.e. healthy, levels is likely to be therapeutically active in treating the disease. Here, we aimed to validate the concept of TSR using the PRISM repurposing data set, which is-as of writing-the largest pharmacogenomic data set. The predictive utility of the TSR approach as it has currently been used appears to be much lower than previously reported and is completely nullified after the drug gene expression signatures are adjusted for the general anti-proliferative downstream effects of drug-induced decreased cell viability. Therefore, TSR mainly relies on generic anti-proliferative drug effects rather than on targeting cancer pathways specifically upregulated in tumor types.

Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors

BACKGROUND

Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution to this area of research is CancerOmicsNet, an AI-based system to predict the therapeutic effects of multitargeted kinase inhibitors across various cancers. This approach was previously demonstrated to outperform other deep learning methods, graph kernel models, molecular docking, and drug binding pocket matching.

METHODS

CancerOmicsNet integrates multiple heterogeneous data by utilizing a deep graph learning model with sophisticated attention propagation mechanisms to extract highly predictive features from cancer-specific networks. The AI-based system was devised to provide more accurate and robust predictions than data-driven therapeutic discovery using gene signature reversion.

RESULTS

Selected CancerOmicsNet predictions obtained for "unseen" data are positively validated against the biomedical literature and by live-cell time course inhibition assays performed against breast, pancreatic, and prostate cancer cell lines. Encouragingly, six molecules exhibited dose-dependent antiproliferative activities, with pan-CDK inhibitor JNJ-7706621 and Src inhibitor PP1 being the most potent against the pancreatic cancer cell line Panc 04.03.

CONCLUSIONS

CancerOmicsNet is a promising AI-based platform to help guide the development of new approaches in precision oncology involving a variety of tumor types and therapeutics.

Epithelial to Mesenchymal Transition as Mechanism of Progression of Pancreatic Cancer: From Mice to Men

Owed to its aggressive yet subtle nature, pancreatic cancer remains unnoticed till an advanced stage so that in most cases the diagnosis is made when the cancer has already spread to other organs with deadly efficiency. The progression from primary tumor to metastasis involves an intricate cascade of events comprising the pleiotropic process of epithelial to mesenchymal transition (EMT) facilitating cancer spread. The elucidation of this pivotal phenotypic change in cancer cell morphology, initially heretic, moved from basic studies dissecting the progression of pancreatic cancer in animal models to move towards human disease, although no clinical translation of the concept emerged yet. Despite this transition, a full-blown mesenchymal phenotype may not be accomplished; rather, the plasticity of the program and its dependency on heterotopic signals implies a series of fluctuating modifications of cancer cells encompassing mesenchymal and epithelial features. Despite the evidence supporting the activation of EMT and MET during cancer progression, our understanding of the relationship between tumor microenvironment and EMT is not yet mature for a clinical application. In this review, we attempt to resume the knowledge on EMT and pancreatic cancer, aiming to include the EMT among the hallmarks of cancer that could potentially modify our clinical thinking with the purpose of filling the gap between the results pursued in basic research by animal models and those achieved in translational research by surrogate biomarkers, as well as their application for prognostic and predictive purposes.

Integrity of the editing and publishing process is the basis for improving an academic journal’s Impact Factor

BACKGROUND

Journal Impact Factor™ (JIF) is often used to evaluate the relative reputation and quality of academic journals in their respective fields, and can greatly influence the quality and scope of subsequent manuscript submissions. Therefore, many if not all academic journals are interested in increasing their JIF, to improve their academic impact.

AIM

To determine the importance of the integrity of the editorial and publication process in improving the academic influence of academic journals and the JIF of academic journals.

METHODS

In this paper, we describe our statistical analysis of bibliometric factors - including the 2021 JIFs released in the Journal Citation Report™ 2022, discipline rankings, received and published articles in 2019-2021, and webpage visits and downloads - for seven journals published by Baishideng Publishing Group (Baishideng) and indexed in Science Citation Index Expanded™; ultimately, we introduce and discuss the editing and publishing processes of Baishideng’s journals in their entirety, as they form the basis for our objective of safeguarding and bolstering integrity in academic publication.

RESULTS

For the seven journals assessed, their 2021 JIFs were basically unchanged from 2020, with the current metric ranging from 5.374 for World Journal of Gastroenterology (WJG) to 1.534 for World Journal of Clinical Cases (WJCC). Further assessments of the journals’ bibliometrics from 2019 to 2020, showed that World Journal of Stem Cells has the highest self-citation rate (1.43%) and World Journal of Gastrointestinal Surgery has the lowest (0.21%). Additionally, the total 3012 articles published during this period were cited by more than 20000 articles in approximately 8000 academic journals. Of note, the 1102 articles published in WJG were cited by articles in 3059 journals, among which 171 journals have a JIF of > 10, including internationally renowned academic journals such as CA-A Cancer Journal for Clinicians (2021 JIF 286.130, record count: 1), Lancet (2021 JIF 202.731, record count: 4), Nature Reviews Immunology (2021 JIF 108.555, record count: 2), Nature Reviews Gastroenterology & Hepatology (2021 JIF 73.082, record count: 9), Lancet Gastroenterology & Hepatology (2021 JIF 45.042, record count: 8), Gastroenterology (2021 JIF 33.883, record count: 19), and Gut (2021 JIF 31.793, record count: 21). This suggests that Baishideng’s journals have been widely recognized for their academic quality. In the Reference Citation Analysis (RCA) database, all seven Baishideng-published journals obtained a 2022 Journal Article Influence Index (JAII). For example, WJG has a 2022 JAII of 22.048, ranking 18^th out of 102 journals in the field of gastroenterology & hepatology in the RCA, with 469909 total citations (6/102) and 21313 total articles (5/102). The numbers of manuscripts received and published in 2021 were both higher than those in 2019-2020. For example, WJCC received a total of 3650 manuscripts in 2021, which is 91.1% higher than those in 2019-2020 (average: 1910 papers/year). In 2021, WJCC published 1296 articles, representing an increase of 105.1% compared to those in 2019-2020 (average: 632 articles/year). The numbers of webpage visits and downloads received by the seven journals have increased year by year. For example, the number of total visits received by WJG in 2019-2021 was 1974052 in 2019, 2317835 in 2020 (increased by 17.4% compared with that in 2019), and 2652555 in 2021 (increased by 4.4% compared with that in 2020). The visitors were from more than 220 countries and regions worldwide, such as the United States, China, and the United Kingdom. Open access (OA) plays a vital role in improving the quality, efficiency, transparency, and integrity of academic journal publishing. From 2019 to 2021, a total of 5543 OA articles were published in the seven journals, of which 2083 (37.6%) were invited and published free-of-charge. During the same period, 1683 articles were published in WJG, and the authors were from more than 70 countries and regions. For the total 5543 articles published in the seven journals from 2019 to 2021, 3903 article quality tracking reports were received after the online publication of these articles. The quality of the articles was further evaluated through the Baishideng’s article quality and author evaluation tracking system, with 4655 articles (84.0%) having received author evaluation and feedback, which contributes to tracking metrics for authors’ satisfaction with the collective publication processes. From March 25, 2021 to June 28, 2022, the seven journals received a total of 424 reader evaluations and 229 letters from readers; this subsequent reader engagement demonstrates that the popularity of the published articles and the volume of their readership audience were improved through the reader evaluation system.

CONCLUSION

Ultimately, the findings from our bibliometric assessments indicate that establishing, promoting and actively practicing processes that safeguard and bolster the integrity of the editing and publication process also help to improve the academic influence of academic journals, which itself is the cornerstone for improving JIF.

The magic bullet: Niclosamide

The term 'magic bullet' is a scientific concept proposed by the German Nobel laureate Paul Ehrlich in 1907, describing a medicine that could specifically and efficiently target a disease without harming the body. Oncologists have been looking for a magic bullet for cancer therapy ever since. However, the current therapies for cancers-including chemotherapy, radiation therapy, hormone therapy, and targeted therapy-pose either pan-cytotoxicity or only single-target efficacy, precluding their ability to function as a magic bullet. Intriguingly, niclosamide, an FDA-approved drug for treating tapeworm infections with an excellent safety profile, displays broad anti-cancer activity in a variety of contexts. In particular, niclosamide inhibits multiple oncogenic pathways such as Wnt/β-catenin, Ras, Stat3, Notch, E2F-Myc, NF-κB, and mTOR and activates tumor suppressor signaling pathways such as p53, PP2A, and AMPK. Moreover, niclosamide potentially improves immunotherapy by modulating pathways such as PD-1/PDL-1. We recently discovered that niclosamide ethanolamine (NEN) reprograms cellular metabolism through its uncoupler function, consequently remodeling the cellular epigenetic landscape to promote differentiation. Inspired by the promising results from the pre-clinical studies, several clinical trials are ongoing to assess the therapeutic effect of niclosamide in cancer patients. This current review summarizes the functions, mechanism of action, and potential applications of niclosamide in cancer therapy as a magic bullet.

Drug repurposing using meta-analysis of gene expression in Alzheimer's disease

INTRODUCTION

Alzheimer's disease and other forms of dementia are disease that bring an increased global burden. However, the medicine developed to date remains limited. The purpose of this study is to predict drug repositioning candidates using a computational method that integrates gene expression profiles on Alzheimer's disease and compound-induced changes in gene expression levels.

METHODS

Gene expression data on Alzheimer's disease were obtained from the Gene Expression Omnibus (GEO) and we conducted a meta-analysis of their gene expression levels. The reverse scores of compound-induced gene expressions were computed based on the reversal relationship between disease and drug gene expression profiles.

RESULTS

Reversal genes and the candidate compounds were identified by the leave-one-out cross-validation procedure. Additionally, the half-maximal inhibitory concentration (IC50) values and the blood-brain barrier (BBB) permeability of candidate compounds were obtained from ChEMBL and PubChem, respectively.

CONCLUSION

New therapeutic target genes and drug candidates against Alzheimer's disease were identified by means of drug repositioning.

Constitutively Active Androgen Receptor in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the predominant type of liver cancer and a leading cause of cancer-related death globally. It is also a sexually dimorphic disease with a male predominance both in HCC and in its precursors, non-alcoholic fatty liver disease (NAFLD)/non-alcoholic steatohepatitis (NASH). The role of the androgen receptor (AR) in HCC has been well documented; however, AR-targeted therapies have failed to demonstrate efficacy in HCC. Building upon understandings of AR in prostate cancer (PCa), this review examines the role of AR in HCC, non-androgen-mediated mechanisms of induced AR expression, the existence of AR splice variants (AR-SV) in HCC and concludes by surveying current AR-targeted therapeutic approaches in PCa that show potential for efficacy in HCC in light of AR-SV expression.

Synthesis and Cytotoxic Activity of 1,2,4-Triazolo-Linked Bis-Indolyl Conjugates as Dual Inhibitors of Tankyrase and PI3K

A series of new 1,2,4-triazolo-linked bis-indolyl conjugates (15a–r) were prepared by multistep synthesis and evaluated for their cytotoxic activity against various human cancer cell lines. It was observed that they were more susceptible to colon and breast cancer cells. Conjugates 15o (IC₅₀ = 2.04 μM) and 15r (IC₅₀ = 0.85 μM) illustrated promising cytotoxicity compared to 5-fluorouracil (5-FU, IC₅₀ = 5.31 μM) against the HT-29 cell line. Interestingly, 15o and 15r induced cell cycle arrest at the G₀/G₁ phase and disrupted the mitochondrial membrane potential. Moreover, these conjugates led to apoptosis in HT-29 at 2 μM and 1 μM, respectively, and also enhanced the total ROS production as well as the mitochondrial-generated ROS. Immunofluorescence and Western blot assays revealed that these conjugates reduced the expression levels of the PI3K-P85, β-catenin, TAB-182, β-actin, AXIN-2, and NF-κB markers that are involved in the β-catenin pathway of colorectal cancer. The results of the in silico docking studies of 15r and 15o further support their dual inhibitory behaviour against PI3K and tankyrase. Interestingly, the conjugates have adequate ADME-toxicity parameters based on the calculated results of the molecular dynamic simulations, as we found that these inhibitors (15r) influenced the conformational flexibility of the 4OA7 and 3L54 proteins.

Wnt/β-Catenin Signaling as a Driver of Stemness and Metabolic Reprogramming in Hepatocellular Carcinoma

Simple Summary

Aberrant Wnt/β-catenin signaling has been reported to play crucial role in pathogenesis of hepatocellular carcinoma (HCC). In this review, we focus on the regulatory role of Wnt/β-catenin signaling in cancer stemness and metabolic reprogramming, which are two emerging hallmarks of cancer. Understanding the role of Wnt/β-catenin signaling in regulation of the above processes reveals novel therapeutic strategy against this deadly disease.

Abstract

Hepatocellular carcinoma (HCC) is a major cause of cancer death worldwide due to its high rates of tumor recurrence and metastasis. Aberrant Wnt/β-catenin signaling has been shown to play a significant role in HCC development, progression and clinical impact on tumor behavior. Accumulating evidence has revealed the critical involvement of Wnt/β-catenin signaling in driving cancer stemness and metabolic reprogramming, which are regarded as emerging cancer hallmarks. In this review, we summarize the regulatory mechanism of Wnt/β-catenin signaling and its role in HCC. Furthermore, we provide an update on the regulatory roles of Wnt/β-catenin signaling in metabolic reprogramming, cancer stemness and drug resistance in HCC. We also provide an update on preclinical and clinical studies targeting Wnt/β-catenin signaling alone or in combination with current therapies for effective cancer therapy. This review provides insights into the current opportunities and challenges of targeting this signaling pathway in HCC.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease.

SIGNIFICANCE

In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

Noninvasive approaches to detect methylation-based markers to monitor gliomas

In this review, we summarize the current approaches used to detect glioma tissue-derived DNA methylation markers in liquid biopsy specimens with the aim to diagnose, prognosticate and potentially track treatment response and evolution of patients with gliomas.

Bioinformatics roadmap for therapy selection in cancer genomics

Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.

HPV infection and 5mC/5hmC epigenetic markers in penile squamous cell carcinoma: new insights into prognostics

BACKGROUND

Penile cancer is one of the most aggressive male tumors. Although it is preventable, the main etiologic causes are lifestyle behaviors and viral infection, such as human papillomavirus (HPV). Long-term epigenetic changes due to environmental factors change cell fate and promote carcinogenesis, being an important marker of prognosis. We evaluated epidemiological aspects of penile squamous cell carcinoma (SCC) and the prevalence of HPV infection using high-risk HPV (hrHPV) and p16^INK4A expression of 224 participants. Global DNA methylation was evaluated through 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC).

RESULTS

The incidence of HPV was 53.2% for hrHPV and 22.32% for p16^INK4a. hrHPV was not related to systemic or lymph node metastasis and locoregional recurrence, nor influenced the survival rate. P16^INK4a seems to be a protective factor for death, which does not affect metastasis or tumor recurrence. Lymph node and systemic metastases and locoregional recurrence increase the risk of death. An increased 5mC mark was observed in penile SCC regardless of HPV infection. However, there is a reduction of the 5hmC mark for p16^INK4a + (P = 0.024). Increased 5mC/5hmC ratio (> 1) was observed in 94.2% of penile SCC, irrespective of HPV infection. Despite the increase in 5mC, it seems not to affect the survival rate (HR = 1.06; 95% CI 0.33-3.38).

CONCLUSIONS

P16^INK4a seems to be a good prognosis marker for penile SCC and the increase in 5mC, an epigenetic mark of genomic stability, may support tumor progression leading to poor prognosis.