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.

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.

Application of perturbation gene expression profiles in drug discovery—From mechanism of action to quantitative modelling

High dimensional characterization of drug targets, compound effects and disease phenotypes are crucial for increased efficiency of drug discovery. High-throughput gene expression measurements are one of the most frequently used data acquisition methods for such a systems level analysis of biological phenotypes. RNA sequencing allows genome wide quantification of transcript abundances, recently even on the level of single cells. However, the correct, mechanistic interpretation of transcriptomic measurements is complicated by the fact that gene expression changes can be both the cause and the consequence of altered phenotype. Perturbation gene expression profiles, where gene expression is measured after a genetic or chemical perturbation, can help to overcome these problems by directly connecting the causal perturbations to their gene expression consequences. In this Review, we discuss the main large scale perturbation gene expression profile datasets, and their application in the drug discovery process, covering mechanisms of action identification, drug repurposing, pathway activity analysis and quantitative modelling.

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.

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.

Applying a computational transcriptomics-based drug repositioning pipeline to identify therapeutic candidates for endometriosis.. [DOI: 10.1101/2022.12.20.22283736] [Cited by in Crossref: 0] [Impact Index Per Article: 0] Endometriosis is a common, inflammatory pain disorder comprised of disease in the pelvis and abnormal uterine lining and ovarian function that affects ∼200 million women of reproductive age worldwide and up to 50% of those with pelvic pain and/or infertility. Existing medical treatments for endometriosis-related pain are often ineffective, with individuals experiencing minimal or transient pain relief or intolerable side effects limiting long-term use - thus underscoring the pressing need for new drug treatment strategies. In this study, we applied a computational drug repurposing pipeline to endometrial gene expression data in the setting of endometriosis and controls in an unstratified manner as well as stratified by disease stage and menstrual cycle phase in order to identify potential therapeutics from existing drugs, based on expression reversal. Out of the 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308, or 9.8%, were in common. Similarities were more pronounced when looking at therapeutic predictions: 221 out of 299 drugs identified across the six signatures, or 73.9%, were shared, and the majority of predicted compounds were concordant across disease stage-stratified and cycle phase-stratified signatures. Our pipeline returned many known treatments as well as novel candidates. We selected the NSAID fenoprofen, the top therapeutic candidate for the unstratified signature and among the top-ranked drugs for the stratified signatures, for further investigation. Our drug target network analysis shows that fenoprofen targets PPARG and PPARA which affect the growth of endometrial tissue, as well as PTGS2 (i.e., COX2), an enzyme induced by inflammation with significantly increased gene expression demonstrated in patients with endometriosis who experience severe dysmenorrhea. NSAIDs are widely prescribed for endometriosis-related dysmenorrhea and nonmenstrual pelvic pain. Our analysis of clinical records across University of California healthcare systems revealed that while NSAIDs have been commonly prescribed to the 61,306 patients identified with diagnoses of endometriosis, dysmenorrhea, or chronic pelvic pain (36,543, 59.61%), fenoprofen was infrequently prescribed to those with these conditions (5, 0.008%). We tested the effect of fenoprofen in an established rat model of endometriosis and determined that it successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a potential endometriosis therapeutic and suggest the utility of future investigation into additional drug targets identified

Endometriosis is a common, inflammatory pain disorder comprised of disease in the pelvis and abnormal uterine lining and ovarian function that affects ∼200 million women of reproductive age worldwide and up to 50% of those with pelvic pain and/or infertility. Existing medical treatments for endometriosis-related pain are often ineffective, with individuals experiencing minimal or transient pain relief or intolerable side effects limiting long-term use - thus underscoring the pressing need for new drug treatment strategies. In this study, we applied a computational drug repurposing pipeline to endometrial gene expression data in the setting of endometriosis and controls in an unstratified manner as well as stratified by disease stage and menstrual cycle phase in order to identify potential therapeutics from existing drugs, based on expression reversal. Out of the 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308, or 9.8%, were in common. Similarities were more pronounced when looking at therapeutic predictions: 221 out of 299 drugs identified across the six signatures, or 73.9%, were shared, and the majority of predicted compounds were concordant across disease stage-stratified and cycle phase-stratified signatures. Our pipeline returned many known treatments as well as novel candidates. We selected the NSAID fenoprofen, the top therapeutic candidate for the unstratified signature and among the top-ranked drugs for the stratified signatures, for further investigation. Our drug target network analysis shows that fenoprofen targets PPARG and PPARA which affect the growth of endometrial tissue, as well as PTGS2 (i.e., COX2), an enzyme induced by inflammation with significantly increased gene expression demonstrated in patients with endometriosis who experience severe dysmenorrhea. NSAIDs are widely prescribed for endometriosis-related dysmenorrhea and nonmenstrual pelvic pain. Our analysis of clinical records across University of California healthcare systems revealed that while NSAIDs have been commonly prescribed to the 61,306 patients identified with diagnoses of endometriosis, dysmenorrhea, or chronic pelvic pain (36,543, 59.61%), fenoprofen was infrequently prescribed to those with these conditions (5, 0.008%). We tested the effect of fenoprofen in an established rat model of endometriosis and determined that it successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a potential endometriosis therapeutic and suggest the utility of future investigation into additional drug targets identified.

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.

Impact of 5HydroxyMethylCytosine (5hmC) on reverse/direct association of cell-cycle, apoptosis, and extracellular matrix pathways in gastrointestinal cancers

Background

Aberrant levels of 5-hydroxymethylcytosine (5-hmC) can lead to cancer progression. Identification of 5-hmC-related biological pathways in cancer studies can produce better understanding of gastrointestinal (GI) cancers.

We conducted a network-based analysis on 5-hmC levels extracted from circulating free DNAs (cfDNA) in GI cancers including colon, gastric, and pancreatic cancers, and from healthy donors. The co-5-hmC network was reconstructed using the weighted-gene co-expression network method. The cancer-related modules/subnetworks were detected. Preservation of three detected 5-hmC-related modules was assessed in an external dataset. The 5-hmC-related modules were functionally enriched, and biological pathways were identified. The relationship between modules was assessed using the Pearson correlation coefficient (p-value < 0.05). An elastic network classifier was used to assess the potential of the 5-hmC modules in distinguishing cancer patients from healthy individuals. To assess the efficiency of the model, the Area Under the Curve (AUC) was computed using five-fold cross-validation in an external dataset.

Results

The main biological pathways were the cell cycle, apoptosis, and extracellular matrix (ECM) organization. Direct association between the cell cycle and apoptosis, inverse association between apoptosis and ECM organization, and inverse association between the cell cycle and ECM organization were detected for the 5-hmC modules in GI cancers. An AUC of 92% (0.73–1.00) was observed for the predictive model including 11 genes.

Conclusion

The intricate association between biological pathways of identified modules may reveal the hidden significance of 5-hmC in GI cancers. The identified predictive model and new biomarkers may be beneficial in cancer detection and precision medicine using liquid biopsy in the early stages.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01061-x.

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.

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.

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.

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.

Reversal of cancer gene expression identifies repurposed drugs for diffuse intrinsic pontine glioma

Diffuse intrinsic pontine glioma (DIPG) is an aggressive incurable brainstem tumor that targets young children. Complete resection is not possible, and chemotherapy and radiotherapy are currently only palliative. This study aimed to identify potential therapeutic agents using a computational pipeline to perform an in silico screen for novel drugs. We then tested the identified drugs against a panel of patient-derived DIPG cell lines. Using a systematic computational approach with publicly available databases of gene signature in DIPG patients and cancer cell lines treated with a library of clinically available drugs, we identified drug hits with the ability to reverse a DIPG gene signature to one that matches normal tissue background. The biological and molecular effects of drug treatment was analyzed by cell viability assay and RNA sequence. In vivo DIPG mouse model survival studies were also conducted. As a result, two of three identified drugs showed potency against the DIPG cell lines Triptolide and mycophenolate mofetil (MMF) demonstrated significant inhibition of cell viability in DIPG cell lines. Guanosine rescued reduced cell viability induced by MMF. In vivo, MMF treatment significantly inhibited tumor growth in subcutaneous xenograft mice models. In conclusion, we identified clinically available drugs with the ability to reverse DIPG gene signatures and anti-DIPG activity in vitro and in vivo. This novel approach can repurpose drugs and significantly decrease the cost and time normally required in drug discovery.

Liver transplantation for hepatocellular carcinoma: Historical evolution of transplantation criteria

Liver transplantation (LT) for hepatocellular carcinoma is still a hot topic, and the main factor that is associated with the success of treatment is to determine the patients who will benefit from LT. Milan criteria have been defined 25 years ago and still is being used for patient selection for LT. However, in living donor LT, the Milan criteria is being extended. Current criteria for patient selection do not only consider morphologic characteristics such as tumor size and number of tumor nodules but also biologic markers that show tumor aggressiveness is also being considered. In the present review article, we have summarized all the criteria and scoring systems regarding LT for hepatocellular carcinoma. All criteria have 5-year overall survival rates that were comparable to the Milan Criteria and ranged between 60%-85%. On the other hand, it was seen that the recurrence rates had increased as the Milan criteria were exceeded; the 5-year recurrence rates ranged between 4.9% to 39.9%. Treatment of hepatocellular carcinoma needs a multidisciplinary approach. Ideal selection criteria are yet to be discovered. The same is true for treatment modalities. The goal will be achieved by a harmonic interplay between basic science researchers and clinicians.

5-Hydroxymethylation alterations in cell-free DNA reflect molecular distinctions of diffuse large B cell lymphoma at different primary sites

Background

5-Hydroxymethylcytosine (5hmC), an important DNA epigenetic modification, plays a vital role in tumorigenesis, progression and prognosis in many cancers. Diffuse large B cell lymphoma (DLBCL) can involve almost any organ, but the prognosis of patients with DLBCL at different primary sites varies greatly. Previous studies have shown that 5hmC displays a tissue-specific atlas, but its role in DLBCLs at different primary sites remains unknown.

Results

We found that primary gastric DLBCL (PG-DLBCL) and lymph node-involved DLBCL (LN-DLBCL) patients had a favorable prognosis, while primary central nervous system DLBCL (PCNS-DLBCL) patients faced the worst prognosis, followed by primary testicular DLBCL (PT-DLBCL) and primary intestinal DLBCL (PI-DLBCL) patients. Thus, we used hmC-CATCH, a bisulfite-free and cost-effective 5hmC detection technology, to first generate the 5hmC profiles from plasma cell-free DNA (cfDNA) of DLBCL patients at these five different primary sites. Specifically, we found robust cancer-associated features that could be used to distinguish healthy individuals from DLBCL patients and distinguish among different primary sites. Through functional enrichment analysis of the differentially 5hmC-enriched genes, almost all DLBCL patients were enriched in tumor-related pathways, and DLBCL patients at different primary sites had unique characteristics. Moreover, 5hmC-based biomarkers can also highly reflect clinical features.

Conclusions

Collectively, we revealed the primary site differential 5hmC regions of DLBCL at different primary sites. This new strategy may help develop minimally invasive and effective methods to diagnose and determine the primary sites of DLBCL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01344-1.

Hydroxymethylation profile of cell-free DNA is a biomarker for early colorectal cancer

Early detection of cancer will improve survival rates. The blood biomarker 5-hydroxymethylcytosine has been shown to discriminate cancer. In a large covariate-controlled study of over two thousand individual blood samples, we created, tested and explored the properties of a 5-hydroxymethylcytosine-based classifier to detect colorectal cancer (CRC). In an independent validation sample set, the classifier discriminated CRC samples from controls with an area under the receiver operating characteristic curve (AUC) of 90% (95% CI [87, 93]). Sensitivity was 55% at 95% specificity. Performance was similar for early stage 1 (AUC 89%; 95% CI [83, 94]) and late stage 4 CRC (AUC 94%; 95% CI [89, 98]). The classifier could detect CRC even when the proportion of tumor DNA in blood was undetectable by other methods. Expanding the classifier to include information about cell-free DNA fragment size and abundance across the genome led to gains in sensitivity (63% at 95% specificity), with similar overall performance (AUC 91%; 95% CI [89, 94]). We confirm that 5-hydroxymethylcytosine can be used to detect CRC, even in early-stage disease. Therefore, the inclusion of 5-hydroxymethylcytosine in multianalyte testing could improve sensitivity for the detection of early-stage cancer.

Therapeutic drug repositioning with special emphasis on neurodegenerative diseases: Threats and issues

Drug repositioning or repurposing is the process of discovering leading-edge indications for authorized or declined/abandoned molecules for use in different diseases. This approach revitalizes the traditional drug discovery method by revealing new therapeutic applications for existing drugs. There are numerous studies available that highlight the triumph of several drugs as repurposed therapeutics. For example, sildenafil to aspirin, thalidomide to adalimumab, and so on. Millions of people worldwide are affected by neurodegenerative diseases. According to a 2021 report, the Alzheimer’s disease Association estimates that 6.2 million Americans are detected with Alzheimer’s disease. By 2030, approximately 1.2 million people in the United States possibly acquire Parkinson’s disease. Drugs that act on a single molecular target benefit people suffering from neurodegenerative diseases. Current pharmacological approaches, on the other hand, are constrained in their capacity to unquestionably alter the course of the disease and provide patients with inadequate and momentary benefits. Drug repositioning–based approaches appear to be very pertinent, expense- and time-reducing strategies for the enhancement of medicinal opportunities for such diseases in the current era. Kinase inhibitors, for example, which were developed for various oncology indications, demonstrated significant neuroprotective effects in neurodegenerative diseases. This review expounds on the classical and recent examples of drug repositioning at various stages of drug development, with a special focus on neurodegenerative disorders and the aspects of threats and issues viz. the regulatory, scientific, and economic aspects.

Circulating biomarkers in the diagnosis and management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal causes of cancer-related death worldwide. The treatment of HCC remains challenging and is largely predicated on early diagnosis. Surveillance of high-risk groups using abdominal ultrasonography, with or without serum analysis of α-fetoprotein (AFP), can permit detection of early, potentially curable tumours, but is limited by its insensitivity. Reviewed here are two current approaches that aim to address this limitation. The first is to use old re-emerged empirically derived biomarkers such as AFP, now applied within statistical models. The second is to use circulating nucleic acid biomarkers, which include cell-free DNA (for example, circulating tumour DNA, cell-free mitochondrial DNA and cell-free viral DNA) and cell-free RNA, applying modern molecular biology-based technologies and machine learning techniques closely allied to the underlying biology of cancer. Taken together, these approaches are likely to be complementary. Both hold considerable promise for achieving earlier diagnosis as well as offering additional functionalities including improved monitoring of therapy and prediction of response thereto.

Effective drug combinations targeting driver KRAS mutations in non-small cell lung cancer.. [DOI: 10.1101/2022.09.21.508953] [Cited by in Crossref: 0] [Impact Index Per Article: 0] 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 with 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 proliferation 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. 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

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 with 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 proliferation 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. 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.

Regional gain and global loss of 5-hydroxymethylcytosine coexist in genitourinary cancers and regulate different oncogenic pathways

BACKGROUND

DNA 5-hydroxymethylcytosine (5hmC) is produced by dynamic 5mC oxidation process contributing to tissue specification, and loss of 5hmC has been reported in multiple cancers including genitourinary cancers. However, 5hmC is also cell-type specific, and its variability may exist between differentiated tumor cells and cancer stem cells. Thus, cancer-associated changes in 5hmC may be contributed by distinct sets of tumor cells within the tumor tissues.

RESULTS

Here, we applied a sensitive immunoprecipitation-based method (hMeDIP-seq) to analyze 5hmC changes during genitourinary carcinogenesis (including prostate, urothelial and kidney). We confirmed the tissue-specific distribution of 5hmC in genitourinary tissues and identified regional gain and global loss of 5hmC coexisting in genitourinary cancers. The genes with gain of 5hmC during tumorigenesis were functionally enriched in regulating stemness and hypoxia, whereas were associated with poor clinical prognosis irrespective of their differences in tumor type. We identified that gain of 5hmC occurred in soft fibrin gel-induced 3D tumor spheres with a tumor-repopulating phenotype in two prostate cancer cell lines, 22RV1 and PC3, compared with conventional two-dimensional (2D) rigid dishes. Then, we defined a malignant signature derived from the differentially hydroxymethylated regions affected genes of cancer stem-like cells, which could predict a worse clinical outcome and identified phenotypically malignant populations of cells from prostate cancer tumors. Notably, an oxidation-resistant vitamin C derivative, ascorbyl phosphate magnesium, restored 5hmC and killed the cancer stem cell-like cells leading to apoptosis in prostate cancer cell lines.

CONCLUSIONS

Collectively, our study dissects the regional gain of 5hmC in maintaining cancer stem-like cells and related to poor prognosis, which provides proof of concept for an epigenetic differentiation therapy with vitamin C by 5hmC reprogramming.

Role of DNA De-methylation intermediate '5-hydroxymethylcytosine' in ovarian cancer management: A comprehensive review

Ovarian cancer remains the most eminent silent killer, with high morbidity and mortality among all gynaecological cancers. The advanced-stage patient's diagnosis has a low survival rate caused by its asymptomatic progression and diverse histopathological sub-types, wherefore in poor prognosis and highly recurring malignancy with multidrug resistance towards chemotherapy. Epigenetic biomarkers open promising avenues of intriguing research to combat OC malignancy, furthermore a tool for its early diagnosis. 5-hydroxymethycytosine (5-hmC), alias the sixth base of the genome, is an intermediate formed during the recently established DNA demethylation process and catalysed via ten-eleven translocation (TET) family of enzymes. It plays a significant role in regulating gene expression and has sparked interest in various cancer types. This review summarizes the role of active DNA demethylation process, its enzymes and intermediate 5-hmC in epigenetic landscape of ovarian cancer as a potent biomarker for clinical translation in identification of therapeutic targets, diagnostic and prognostic evaluation.

In Vivo and in vitro antitumor activity of tomatine in hepatocellular carcinoma

Background: There is abundant ethnopharmacological evidence the uses of regarding Solanum species as antitumor and anticancer agents. Glycoalkaloids are among the molecules with antiproliferative activity reported in these species.

Purpose: To evaluate the anticancer effect of the Solanum glycoalkaloid tomatine in hepatocellular carcinoma (HCC) in vitro (HepG2 cells) and in vivo models.

Methods: The resazurin reduction assay was performed to detect the effect of tomatine on cell viability in human HepG2 cell lines. Programmed cell death was investigated by means of cellular apoptosis assays using Annexin V. The expression of cancer related proteins was detected by Western blotting (WB). Reactive oxygen species (ROS) and calcium were determined by 2,7-dichlorodihydrofluorescein diacetate and Fluo-4, respectively. Intrahepatic HepG2 xenograft mouse model was used to elucidate the effect of tomatine on tumor growth in vivo.

Results and Discussion: Tomatine reduced HepG2 cell viability and induced the early apoptosis phase of cell death, consistently with caspase-3, -7, Bcl-2 family, and P53 proteins activation. Furthermore, tomatine increased intracellular ROS and cytosolic Ca⁺² levels. Moreover, the NSG mouse xenograft model showed that treating mice with tomatine inhibited HepG2 tumor growth.

Conclusion: Tomatine inhibits in vitro and in vivo HCC tumorigenesis in part via modulation of p53, Ca⁺², and ROS signalling. Thus, the results suggest the potential cancer therapeutic use of tomatine in HCC patients.

New Perspectives on the Importance of Cell-Free DNA Biology

Body fluids are constantly replenished with a population of genetically diverse cell-free DNA (cfDNA) fragments, representing a vast reservoir of information reflecting real-time changes in the host and metagenome. As many body fluids can be collected non-invasively in a one-off and serial fashion, this reservoir can be tapped to develop assays for the diagnosis, prognosis, and monitoring of wide-ranging pathologies, such as solid tumors, fetal genetic abnormalities, rejected organ transplants, infections, and potentially many others. The translation of cfDNA research into useful clinical tests is gaining momentum, with recent progress being driven by rapidly evolving preanalytical and analytical procedures, integrated bioinformatics, and machine learning algorithms. Yet, despite these spectacular advances, cfDNA remains a very challenging analyte due to its immense heterogeneity and fluctuation in vivo. It is increasingly recognized that high-fidelity reconstruction of the information stored in cfDNA, and in turn the development of tests that are fit for clinical roll-out, requires a much deeper understanding of both the physico-chemical features of cfDNA and the biological, physiological, lifestyle, and environmental factors that modulate it. This is a daunting task, but with significant upsides. In this review we showed how expanded knowledge on cfDNA biology and faithful reverse-engineering of cfDNA samples promises to (i) augment the sensitivity and specificity of existing cfDNA assays; (ii) expand the repertoire of disease-specific cfDNA markers, thereby leading to the development of increasingly powerful assays; (iii) reshape personal molecular medicine; and (iv) have an unprecedented impact on genetics research.