Epigenomic profiling of non-small cell lung cancer xenografts uncover LRP12 DNA methylation as predictive biomarker for carboplatin resistance

Cancer, metastasis, and the epigenome

Cancer is the second leading cause of death worldwide and disease burden is expected to increase globally throughout the next several decades, with the majority of cancer-related deaths occurring in metastatic disease. Cancers exhibit known hallmarks that endow them with increased survival and proliferative capacities, frequently as a result of de-stabilizing mutations. However, the genomic features that resolve metastatic clones from primary tumors are not yet well-characterized, as no mutational landscape has been identified as predictive of metastasis. Further, many cancers exhibit no known mutation signature. This suggests a larger role for non-mutational genome re-organization in promoting cancer evolution and dissemination. In this review, we highlight current critical needs for understanding cell state transitions and clonal selection advantages for metastatic cancer cells. We examine links between epigenetic states, genome structure, and misregulation of tumor suppressors and oncogenes, and discuss how recent technologies for understanding domain-scale regulation have been leveraged for a more complete picture of oncogenic and metastatic potential.

Targeted inhibition of the PI3K/AKT/mTOR pathway by (+)-anthrabenzoxocinone induces cell cycle arrest, apoptosis, and autophagy in non-small cell lung cancer

Non-small cell lung cancer (NSCLC), characterized by low survival rates and a high recurrence rate, is a major cause of cancer-related mortality. Aberrant activation of the PI3K/AKT/mTOR signaling pathway is a common driver of NSCLC. Within this study, the inhibitory activity of (+)-anthrabenzoxocinone ((+)-ABX), an oxygenated anthrabenzoxocinone compound derived from Streptomyces, against NSCLC is demonstrated for the first time both in vitro and in vivo. Mechanistically, it is confirmed that the PI3K/AKT/mTOR signaling pathway is targeted and suppressed by (+)-ABX, resulting in the induction of S and G2/M phase arrest, apoptosis, and autophagy in NSCLC cells. Additionally, the augmentation of intracellular ROS levels by (+)-ABX is revealed, further contributing to the inhibition of the signaling pathway and exerting inhibitory effects on tumor growth. The findings presented in this study suggest that (+)-ABX possesses the potential to serve as a lead compound for the treatment of NSCLC.

Comprehensive Analysis of the Prognostic Marker and Immune Infiltrates of LDLR-Related Proteins Family Members in Breast Cancer

Background & Objective

Breast cancer (BC) is one of the most frequent tumors worldwide, accounting for 15% of all cancer-related deaths. A timely diagnosis of BC is essential for optimal treatment and increasing patients' survival rates. LRP family proteins are important components of cell-surface receptors involved in numerous biological activities. Expression of LRP is related to breast malignancy. In this study, we initially studied the expression of LRPs in BC tissues compared to normal tissues-the relation of LRP expression with relapse-free survival (RFS) and overall survival (OS). Then, we investigated the association of LRPs relation and immune infiltrating abundance.

Methods

We analyzed the LDLR family expression and prognostic value in BC by mining UALCAN, TIMER, and Kaplan-Meier plotter databases. Subsequently, we explored the association of LDLR expression and immune infiltrating abundance via the TIMER database.

Results

Expression levels of LRP1/2/4/9/10 were found to be higher in the cases with positive estrogen receptors. There was a positive association between LRP1/6 expression and the infiltration of CD8+ T cells, CD4+ T Cell, Macrophage, Dendritic Cell, and Neutrophil.

Conclusion

Our study recommends LDLR as a potential prognostic biomarker that can be promising to improve the survival of BC patients' survival. However, further investigations are needed to evaluate the studied LDLR members in more detail.

Link between m6A modification and infiltration characterization of tumor microenvironment in lung adenocarcinoma

N6-methyladenosine (m6A) RNA methylation plays a pivotal role in immune responses and the onset and advancement of cancer. Nonetheless, the precise impact of m6A modification in lung adenocarcinoma (LUAD) and its associated tumor microenvironment (TME) remains to be fully elucidated. Here, we distinguished distinct m6A modification patterns within two separate LUAD cohorts using a set of 21 m6A regulators. The TME characteristics associated with these two patterns align with the immune-inflamed and immune-excluded phenotypes, respectively. We identified 2064 m6A-related genes, which were used as a basis to divide all LUAD samples into three distinct m6A gene clusters. We applied a scoring system to evaluate the m6A gene signature of the m6A modification pattern in individual patients. To authenticate the categorization significance of m6A modification patterns, we established a correlation between m6A score and TME infiltration profiling, tumor somatic mutations, and responses to immunotherapy. A high level of m6A modification may be associated with the aggressiveness and poor prognosis of LUAD. Further studies should investigate the mechanism of action of m6A regulators and m6A-related genes to improve the diagnosis and treatment of patients with LUAD.

Recent developments in photodynamic therapy and its application against multidrug resistant cancers

Recently, photodynamic therapy (PDT) has received a lot of attention for its potential use in cancer treatment. It enables the therapy of a multifocal disease with the least amount of tissue damage. The most widely used prodrug is 5-aminolevulinic acid, which undergoes heme pathway conversion to protoporphyrin IX, which acts as a photosensitizer (PS). Additionally, hematoporphyrin, bacteriochlorin, and phthalocyanine are also studied for their therapeutic potential in cancer. Unfortunately, not every patient who receives PDT experiences a full recovery. Resistance to different anticancer treatments is commonly observed. A few of the resistance mechanisms by which cancer cells escape therapeutics are genetic factors, drug-drug interactions, impaired DNA repair pathways, mutations related to inhibition of apoptosis, epigenetic pathways, etc. Recently, much research has been conducted to develop a new generation of PS based on nanomaterials that could be used to overcome cancer cells' multidrug resistance (MDR). Various metal-based, polymeric, lipidic nanoparticles (NPs), dendrimers, etc, have been utilized in the PDT application against cancer. This article discusses the detailed mechanism by which cancer cells evolve towards MDR as well as recent advances in PDT-based NPs for use against multidrug-resistant cancers.

LRP12 is an endogenous transmembrane inactivator of α4 integrins

Dynamic regulation of integrin activation and inactivation is critical for precisely controlled cell adhesion and migration in physiological and pathological processes. The molecular basis for integrin activation has been intensively studied; however, the understanding of integrin inactivation is still limited. Here, we identify LRP12 as an endogenous transmembrane inhibitor for α4 integrin activation. The LRP12 cytoplasmic domain directly binds to the integrin α4 cytoplasmic tail and inhibits talin binding to the β subunit, thus keeping integrin inactive. In migrating cells, LRP12-α4 interaction induces nascent adhesion (NA) turnover at the leading-edge protrusion. Knockdown of LRP12 leads to increased NAs and enhanced cell migration. Consistently, LRP12-deficient T cells show an enhanced homing capability in mice and lead to aggravated chronic colitis in a T cell-transfer colitis model. Altogether, LRP12 is a transmembrane inactivator for integrins that inhibits α4 integrin activation and controls cell migration by maintaining balanced NA dynamics.

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.

DNA Methylation Biomarkers for Prediction of Response to Platinum-Based Chemotherapy: Where Do We Stand?

Simple Summary

Platinum-based agents are one of the most widely used chemotherapy drugs for various types of cancer. However, one of the main challenges in the application of platinum drugs is resistance, which is currently being widely investigated. Epigenetic DNA methylation-based biomarkers are promising to aid in the selection of patients, helping to foresee their platinum therapy response in advance. These biomarkers enable minimally invasive patient sample collection, short analysis, and good sensitivity. Hence, improved methodologies for the detection and quantification of DNA methylation biomarkers will facilitate their use in the choice of an optimal treatment strategy.

Abstract

Platinum-based chemotherapy is routinely used for the treatment of several cancers. Despite all the advances made in cancer research regarding this therapy and its mechanisms of action, tumor resistance remains a major concern, limiting its effectiveness. DNA methylation-based biomarkers may assist in the selection of patients that may benefit (or not) from this type of treatment and provide new targets to circumvent platinum chemoresistance, namely, through demethylating agents. We performed a systematic search of studies on biomarkers that might be predictive of platinum-based chemotherapy resistance, including in vitro and in vivo pre-clinical models and clinical studies using patient samples. DNA methylation biomarkers predictive of response to platinum remain mostly unexplored but seem promising in assisting clinicians in the generation of more personalized follow-up and treatment strategies. Improved methodologies for their detection and quantification, including non-invasively in liquid biopsies, are additional attractive features that can bring these biomarkers into clinical practice, fostering precision medicine.

Clinicopathological implications of lncRNAs, immunotherapy and DNA methylation in lung squamous cell carcinoma: a narrative review

Objective

To explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in lung squamous cell carcinoma (LUSC), emphasizing their exact roles in carcinogenesis and modes of action.

Background

LUSC is the second most prevalent form, accounting for around 30% of non-small cell lung cancer (NSCLC). To date, molecular-targeted treatments have significantly improved overall survival in lung adenocarcinoma patients but have had little effect on LUSC therapy. As a result, there is an urgent need to discover new treatments for LUSC that are based on existing genomic methods.

Methods

In this review, we summarized and analyzed recent research on the biological activities and processes of lncRNA, immunotherapy, and DNA methylation in the formation of LUSC. The relevant studies were retrieved using a thorough search of Pubmed, Web of Science, Science Direct, Google Scholar, and the university's online library, among other sources.

Conclusions

LncRNAs are the primary components of the mammalian transcriptome and are emerging as master regulators of a number of cellular processes, including the cell cycle, differentiation, apoptosis, and growth, and are implicated in the pathogenesis of a variety of cancers, including LUSC. Understanding their role in LUSC in detail may help develop innovative treatment methods and tactics for LUSC. Meanwhile, immunotherapy has transformed the LUSC treatment and is now considered the new standard of care. To get a better knowledge of LUSC biology, it is critical to develop superior modeling systems. Preclinical models, particularly those that resemble human illness by preserving the tumor immune environment, are essential for studying cancer progression and evaluating novel treatment targets. DNA methylation, similarly, is a component of epigenetic alterations that regulate cellular function and contribute to cancer development. By methylating the promoter regions of tumor suppressor genes, abnormal DNA methylation silences their expression. DNA methylation indicators are critical in the early detection of lung cancer, predicting therapy efficacy, and tracking treatment resistance. As such, this review seeks to explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in LUSC, emphasizing their exact roles in carcinogenesis and modes of action.

Recent Multiomics Approaches in Endometrial Cancer

Endometrial cancer is the most common gynecological cancers in developed countries. Many of the mechanisms involved in its initiation and progression remain unclear. Analysis providing comprehensive data on the genome, transcriptome, proteome, and epigenome could help in selecting molecular markers and targets in endometrial cancer. Multiomics approaches can reveal disturbances in multiple biological systems, giving a broader picture of the problem. However, they provide a large amount of data that require processing and further integration prior to analysis. There are several repositories of multiomics datasets, including endometrial cancer data, as well as portals allowing multiomics data analysis and visualization, including Oncomine, UALCAN, LinkedOmics, and miRDB. Multiomics approaches have also been applied in endometrial cancer research in order to identify novel molecular markers and therapeutic targets. This review describes in detail the latest findings on multiomics approaches in endometrial cancer.

Breaking the crosstalk of the Cellular Tumorigenic Network by low-dose combination therapy in lung cancer patient-derived xenografts

Non-small cell lung cancer (NSCLC) is commonly diagnosed at advanced stages limiting treatment options. Although, targeted therapy has become integral part of NSCLC treatment therapies often fail to improve patient's prognosis. Based on previously published criteria for selecting drug combinations for overcoming resistances, NSCLC patient-derived xenograft (PDX) tumors were treated with a low dose combination of cabozantinib, afatinib, plerixafor and etoricoxib. All PDX tumors treated, including highly therapy-resistant adeno- and squamous cell carcinomas without targetable oncogenic mutations, were completely suppressed by this drug regimen, leading to an ORR of 81% and a CBR of 100%. The application and safety profile of this low dose therapy regimen was well manageable in the pre-clinical settings. Overall, this study provides evidence of a relationship between active paracrine signaling pathways of the Cellular Tumorigenic Network, which can be effectively targeted by a low-dose multimodal therapy to overcome therapy resistance and improve prognosis of NSCLC.

Multi-CpG linear regression models to accurately predict paclitaxel and docetaxel activity in cancer cell lines

The microtubule-targeting paclitaxel (PTX) and docetaxel (DTX) are widely used chemotherapeutic agents. However, the dysregulation of apoptotic processes, microtubule-binding proteins, and multi-drug resistance efflux and influx proteins can alter the efficacy of taxane drugs. In this review, we have created multi-CpG linear regression models to predict the activities of PTX and DTX drugs through the integration of publicly available pharmacological and genome-wide molecular profiling datasets generated using hundreds of cancer cell lines of diverse tissue of origin. Our findings indicate that linear regression models based on CpG methylation levels can predict PTX and DTX activities (log-fold change in viability relative to DMSO) with high precision. For example, a 287-CpG model predicts PTX activity at R² of 0.985 among 399 cell lines. Just as precise (R²=0.996) is a 342-CpG model for predicting DTX activity in 390 cell lines. However, our predictive models, which employ a combination of mRNA expression and mutation as input variables, are less accurate compared to the CpG-based models. While a 290 mRNA/mutation model was able to predict PTX activity with R² of 0.830 (for 546 cell lines), a 236 mRNA/mutation model could calculate DTX activity at R² of 0.751 (for 531 cell lines). The CpG-based models restricted to lung cancer cell lines were also highly predictive (R²≥0.980) for PTX (74 CpGs, 88 cell lines) and DTX (58 CpGs, 83 cell lines). The underlying molecular biology behind taxane activity/resistance is evident in these models. Indeed, many of the genes represented in PTX or DTX CpG-based models have functionalities related to apoptosis (e.g., ACIN1, TP73, TNFRSF10B, DNASE1, DFFB, CREB1, BNIP3), and mitosis/microtubules (e.g., MAD1L1, ANAPC2, EML4, PARP3, CCT6A, JAKMIP1). Also represented are genes involved in epigenetic regulation (HDAC4, DNMT3B, and histone demethylases KDM4B, KDM4C, KDM2B, and KDM7A), and those that have never been previously linked to taxane activity (DIP2C, PTPRN2, TTC23, SHANK2). In summary, it is possible to accurately predict taxane activity in cell lines based entirely on methylation at multiple CpG sites.

Role of multidrug resistance-associated proteins in cancer therapeutics: past, present, and future perspectives

Cancer, a major public health problem, is one of the world's top leading causes of death. Common treatments for cancer include cytotoxic chemotherapy, surgery, targeted drugs, endocrine therapy, and immunotherapy. However, despite the outstanding achievements in cancer therapies during the last years, resistance to conventional chemotherapeutic agents and new targeted drugs is still the major challenge. In the present review, we explain the different mechanisms involved in cancer therapy and the detailed outlines of cancer drug resistance regarding multidrug resistance-associated proteins (MRPs) and their role in treatment failures by common chemotherapeutic agents. Further, different modulators of MRPs are presented. Finally, we outlined the models used to analyze MRP transporters and proposed a future impact that may set up a base or pave the way for many researchers to investigate the cancer MRP further.

Resistance to platinum-based cancer drugs: a special focus on epigenetic mechanisms

Chemoresistance is a significant clinical challenge, limiting the drug response in cancer. Several mechanisms associated with drug resistance have been characterized, and the role of epigenetics in generating resistance to platinum-based drugs has been clarified. Epigenetic mechanisms such as DNA methylation, histone modification, long noncoding RNA, and microRNA affect the expression of genes implicated in absorption, distribution, metabolism and excretion (ADME) of drugs, and other non-ADME genes that encode enzymes involved in the processes of cell proliferation, DNA repair, apoptosis and signal transduction key in the development of chemoresistance in cancer, specifically in platinum-based drugs. This review summarizes current discoveries in epigenetic regulation implicated in platinum drug resistance in cancer and the main clinical trials based on epigenetic therapy, evaluating their potential synergy with platinum-based drugs.

Pathogenesis and therapeutic strategy in platinum resistance lung cancer

Platinum compounds (cisplatin and carboplatin) represent the most active anticancer agents in clinical use both of lung cancer in mono-and combination therapies. However, platinum resistance limits its clinical application. It is necessary to understand the molecular mechanism of platinum resistance, identify predictive markers, and develop newer, more effective and less toxic agents to treat platinum resistance in lung cancer. Here, it summarizes the main molecular mechanisms associated with platinum resistance in lung cancer and the development of new approaches to tackle this clinically relevant problem. Moreover, it could lead to the development of more effective treatment for refractory lung cancer in future.

Pericentromeric Satellite III transcripts induce etoposide resistance

Non-coding RNA from pericentromeric satellite repeats are involved in stress-dependent splicing processes, maintenance of heterochromatin, and are required to protect genome stability. Here we show that the long non-coding satellite III RNA (SatIII) generates resistance against the topoisomerase IIa (TOP2A) inhibitor etoposide in lung cancer. Because heat shock conditions (HS) protect cells against the toxicity of etoposide, and SatIII is significantly induced under HS, we hypothesized that the protective effect could be traced back to SatIII. Using genome methylation profiles of patient-derived xenograft mouse models we show that the epigenetic modification of the SatIII DNA locus and the resulting SatIII expression predict chemotherapy resistance. In response to stress, SatIII recruits TOP2A to nuclear stress bodies, which protects TOP2A from a complex formation with etoposide and results in decreased DNA damage after treatment. We show that BRD4 inhibitors reduce the expression of SatIII, restoring etoposide sensitivity.

MeImmS: Predict Clinical Benefit of Anti-PD-1/PD-L1 Treatments Based on DNA Methylation in Non-small Cell Lung Cancer

Immunotherapy has become an effective therapy for cancer treatment. However, the development of biomarkers to predict immunotherapy response still remains a challenge. We have developed the DNA Methylation Immune Score, named “MeImmS,” which can predict clinical benefits of non-small cell lung cancer (NSCLC) patients based on DNA methylation of 8 CpG sites. The 8 CpG sites regulate the expression of immune-related genes and MeImmS was related to immune-associated pathways, exhausted T cell markers and immune cells. Copy-number loss in 1p36.33 may affect the response of cancer patients to immunotherapy. In addition, SAA1, CXCL10, CCR5, CCL19, CXCL11, CXCL13, and CCL5 were found to be key immune regulatory genes in immunotherapy. Together, MeImmS discovered the heterogeneous of NSCLC patients and guided the immunotherapy of cancer patients in the future.

Systematic Investigation of DNA Methylation Associated With Platinum Chemotherapy Resistance Across 13 Cancer Types

Background: Platinum resistance poses a significant problem for oncology clinicians. As a result, the role of epigenetics and DNA methylation in platinum-based chemoresistance has gained increasing attention from researchers in recent years. A systematic investigation of aberrant methylation patterns related to platinum resistance across various cancer types is urgently needed.

Methods: We analyzed the platinum chemotherapy response-related methylation patterns from different perspectives of 618 patients across 13 cancer types and integrated transcriptional and clinical data. Spearman’s test was used to evaluate the correlation between methylation and gene expression. Cox analysis, the Kaplan-Meier method, and log-rank tests were performed to identify potential risk biomarkers based on differentially methylated positions (DMPs) and compare survival based on DMP values. Support vector machines and receiver operating characteristic curves were used to identify the platinum-response predictive DMPs.

Results: A total of 3,703 DMPs (p value < 0.001 and absolute delta beta >0.10) were identified, and the DMP numbers of each cancer type varied. A total of 39.83% of DMPs were hypermethylated and 60.17% were hypomethylated in platinum-resistant patients. Among them, 405 DMPs (Benjamini and Hochberg adjusted p value < 0.05) were found to be associated with prognosis in tumor patients treated with platinum-based regimens, and 664 DMPs displayed the potential to predict platinum chemotherapy response. In addition, we defined six DNA DMPs consisting of four gene members (mesothelin, protein kinase cAMP-dependent type II regulatory subunit beta, msh homeobox 1, and par-6 family cell polarity regulator alpha) that may have favorable prognostic and predictive values for platinum chemotherapy.

Conclusion: The methylation-transcription axis exists and participates in the complex biological mechanism of platinum resistance in various cancers. Six DMPs and four associated genes may have the potential to serve as promising epigenetic biomarkers for platinum-based chemotherapy and guide clinical selection of optimal treatment.

An integrated epigenomic-transcriptomic landscape of lung cancer reveals novel methylation driver genes of diagnostic and therapeutic relevance

Background: Aberrant DNA methylation occurs commonly during carcinogenesis and is of clinical value in human cancers. However, knowledge of the impact of DNA methylation changes on lung carcinogenesis and progression remains limited.

Methods: Genome-wide DNA methylation profiles were surveyed in 18 pairs of tumors and adjacent normal tissues from non-small cell lung cancer (NSCLC) patients using Reduced Representation Bisulfite Sequencing (RRBS). An integrated epigenomic-transcriptomic landscape of lung cancer was depicted using the multi-omics data integration method.

Results: We discovered a large number of hypermethylation events pre-marked by poised promoter in embryonic stem cells, being a hallmark of lung cancer. These hypermethylation events showed a high conservation across cancer types. Eight novel driver genes with aberrant methylation (e.g., PCDH17 and IRX1) were identified by integrated analysis of DNA methylome and transcriptome data. Methylation level of the eight genes measured by pyrosequencing can distinguish NSCLC patients from lung tissues with high sensitivity and specificity in an independent cohort. Their tumor-suppressive roles were further experimentally validated in lung cancer cells, which depend on promoter hypermethylation. Similarly, 13 methylation-driven ncRNAs (including 8 lncRNAs and 5 miRNAs) were identified, some of which were co-regulated with their host genes by the same promoter hypermethylation. Finally, by analyzing the transcription factor (TF) binding motifs, we uncovered sets of TFs driving the expression of epigenetically regulated genes and highlighted the epigenetic regulation of gene expression of TCF21 through DNA methylation of EGR1 binding motifs.

Conclusions: We discovered several novel methylation driver genes of diagnostic and therapeutic relevance in lung cancer. Our findings revealed that DNA methylation in TF binding motifs regulates target gene expression by affecting the binding ability of TFs. Our study also provides a valuable epigenetic resource for identifying DNA methylation-based diagnostic biomarkers, developing cancer drugs for epigenetic therapy and studying cancer pathogenesis.

A novel DNA methylation-based model that effectively predicts prognosis in hepatocellular carcinoma

PURPOSE

To build a novel predictive model for hepatocellular carcinoma (HCC) patients based on DNA methylation data.

METHODS

Four independent DNA methylation datasets for HCC were used to screen for common differentially methylated genes (CDMGs). Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to explore the biological roles of CDMGs in HCC. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were performed to identify survival-related CDMGs (SR-CDMGs) and to build a predictive model. The importance of this model was assessed using Cox regression analysis, propensity score-matched (PSM) analysis and stratification analysis. A validation group from the Cancer Genome Atlas (TCGA) was constructed to further validate the model.

RESULTS

Four SR-CDMGs were identified and used to build the predictive model. The risk score of this model was calculated as follows: risk score = (0.01489826 × methylation level of WDR69) + (0.15868618 × methylation level of HOXB4) + (0.16674959 × methylation level of CDKL2) + (0.16689301 × methylation level of HOXA10). Kaplan-Meier analysis demonstrated that patients in the low-risk group had a significantly longer overall survival (OS; log-rank P-value =0.00071). The Cox model multivariate analysis and PSM analysis identified the risk score as an independent prognostic factor (P<0.05). Stratified analysis results further confirmed this model performed well. By analyzing the validation group, the results of receiver operating characteristic (ROC) curve analysis and survival analysis further validated this model.

CONCLUSION

Our DNA methylation-based prognosis predictive model is effective and reliable in predicting prognosis for patients with HCC.

EXT1 methylation promotes proliferation and migration and predicts the clinical outcome of non-small cell lung carcinoma via WNT signalling pathway

DNA methylation is important for lung cancer prognosis. In this work, it is aimed to seek novel biomarkers with DNA methylation‐expression‐pathway pattern and explore its underlying mechanism. Prognostic DNA methylation sites and mRNAs were screened in NSCLC data set from TCGA, and further validated using the samples retrospectively collected, and EXT1 was identified as a potential target. Gene body methylation of three CpG sites (cg03276982, cg11592677, cg16286281) on EXT1 was significantly associated with clinical outcome, and the EXT1 gene expression also predicted prognosis. The expression level of EXT1 was also correlated with its DNA methylation level. This observation was further validated in a new data set consist of 170 samples. Knocking down of EXT1 resulted in decreased proliferation and migration. EXT1 targets were analysed using GSEA. It is found that the WNT signalling is the potential downstream target of EXT1. Further analyses revealed that the EXT1 targets the beta‐catenin and effect migration rate of NSCLC cell lines. The WNT signalling inhibitor, XAV‐939, effectively disrupted the migration promotion effect induced by EXT1. In summary, EXT1 methylation regulates the gene expression, effects the proliferation and migration via WNT pathway and predicted a poor prognosis for NSCLC.

RNA methyltransferase METTL3 induces intrinsic resistance to gefitinib by combining with MET to regulate PI3K/AKT pathway in lung adenocarcinoma

Clinical research data show that gefitinib greatly improves the progression‐free survival of patients, so it is used in advanced non‐small cell lung cancer patients with EGFR mutation. However, some patients with EGFR sensitive mutations do not have good effects on initial gefitinib treatment, and this mechanism is rarely studied. METTL3, a part of N6‐adenosine‐methyltransferase, has been reported to play an important role in a variety of tumours. In this study, we found that METTL3 is up‐regulated in gefitinib‐resistant tissues compared to gefitinib‐sensitive tissues. Cell function experiments have proved that under the treatment of gefitinib, METTL3 knockdown promotes apoptosis and inhibits proliferation of lung cancer cells. Mechanistic studies have shown that METTL3 combines with MET and causes the PI3K/AKT signalling pathway to be manipulated, which affects the sensitivity of lung cancer cells to gefitinib. Therefore, our research shows that METTL3 can be used as a molecular marker to predict the efficacy of EGFR‐TKI therapy in patients, and METTL3 may be a potential therapeutic target.

Use of DNA methylation profiling in translational oncology

DNA methylation is a highly regulated process that has a critical role in human development and homeostatic control of the cell. The number of genes affected by anomalous DNA methylation in cancer-associated pathways is swiftly accelerating and with the advancement of molecular technologies, new layers of complexity are opening up and refining our strategies to combat cancer. DNA methylation profiling is an essential facet to understanding malignant transformation and is becoming an increasingly important tool for cancer diagnosis, prognosis and therapy monitoring. In this review, the role of DNA methylation in normal cellular function is discussed, as well as how epigenetic aberrations override normal cellular cues that lead to tumor initiation and propagation. The review also focuses on the latest advancements in DNA methylation profiling as a biomarker for early cancer detection, predicting patient clinical outcomes and responses to treatment and provides new insights into epigenetic-based therapy in clinical oncology.

CAVIN2 is frequently silenced by CpG methylation and sensitizes lung cancer cells to paclitaxel and 5-FU

Aim: To explore the biological functions and clinical significance of CAVIN2 in lung cancer. Materials & methods: Methylation-specific PCR was used to measure promoter methylation of CAVIN2. The function of CAVIN2 was tested by Cell Counting Kit-8, colony formation, Transwell, flow cytometric analysis, acridine orange/ethidium bromide, chemosensitivity assay and xenograft assay. Results: CAVIN2 is significantly downregulated by promoter methylation in lung cancer. CAVIN2 overexpression inhibits lung cancer cell migration and invasion. Furthermore, ectopic expression of CAVIN2 inhibits cell proliferation in vivo and in vitro by inducing G2/M cell cycle arrest, which sensitizes the chemosensitivity of lung cancer cells to paclitaxel and 5-fluorouracil, but not cisplatin. Conclusion: CAVIN2 is a tumor suppressor in non-small-cell lung cancer and can sensitize lung cancer cells to paclitaxel and 5-fluorouracil.

Role of DNA Methylation in the Resistance to Therapy in Solid Tumors

Despite the recent advances in chemotherapeutic treatments against cancer, some types of highly aggressive and invasive cancer develop drug resistance against conventional therapies, which continues to be a major problem in the fight against cancer. In recent years, studies of alterations of DNA methylome have given us a better understanding of the role of DNA methylation in the development of tumors. DNA methylation (DNAm) is an epigenetic change that promotes the covalent transfer of methyl groups to DNA. This process suppresses gene expression through the modulation of the transcription machinery access to the chromatin or through the recruitment of methyl binding proteins. DNAm is regulated mainly by DNA methyltransferases. Aberrant DNAm contributes to tumor progression, metastasis, and resistance to current anti-tumoral therapies. Aberrant DNAm may occur through hypermethylation in the promoter regions of tumor suppressor genes, which leads to their silencing, while hypomethylation in the promoter regions of oncogenes can activate them. In this review, we discuss the impact of dysregulated methylation in certain genes, which impact signaling pathways associated with apoptosis avoidance, metastasis, and resistance to therapy. The analysis of methylome has revealed patterns of global methylation, which regulate important signaling pathways involved in therapy resistance in different cancer types, such as breast, colon, and lung cancer, among other solid tumors. This analysis has provided gene-expression signatures of methylated region-specific DNA that can be used to predict the treatment outcome in response to anti-cancer therapy. Additionally, changes in cancer methylome have been associated with the acquisition of drug resistance. We also review treatments with demethylating agents that, in combination with standard therapies, seem to be encouraging, as tumors that are in early stages can be successfully treated. On the other hand, tumors that are in advanced stages can be treated with these combination schemes, which could sensitize tumor cells that are resistant to the therapy. We propose that rational strategies, which combine specific demethylating agents with conventional treatment, may improve overall survival in cancer patients.

Identification and Analysis of Dysfunctional Genes and Pathways in CD8+ T Cells of Non-Small Cell Lung Cancer Based on RNA Sequencing

Lung cancer, the most common of malignant tumors, is typically of the non-small cell (NSCLC) type. T-cell-based immunotherapies are a promising and powerful approach to treating NSCLCs. To characterize the CD8⁺ T cells of non-small cell lung cancer, we re-analyzed the published RNA-Seq gene expression profiles of 36 CD8⁺ T cell isolated from tumor (TIL) samples and 32 adjacent uninvolved lung (NTIL) samples. With an advanced Monte Carlo method of feature selection, we identified the CD8⁺ TIL specific expression patterns. These patterns revealed the key dysfunctional genes and pathways in CD8⁺ TIL and shed light on the molecular mechanisms of immunity and use of immunotherapy.

Involvement of ER stress and reactive oxygen species generation in anti-cancer effect of CKD-516 for lung cancer

PURPOSE

CKD-516 (Valecobulin), a vascular-disrupting agent, inhibits microtubule elongation. We evaluated the effect of CKD-516 on lung cancer cells and the underlying molecular mechanisms.

METHODS

The effects of S516, an active metabolite of CKD-516, were evaluated in HUVECs and three lung cancer cell lines and by a microtubule polymerization assay. Tubulin cross-linking was used to identify the binding site of S516 on tubulin, and Western blotting was performed to identify the intracellular pathways leading to cell death. Subcutaneous lung cancer xenograft models were used to assess the in vivo effect of CKD-516 on tumor growth.

RESULTS

S516 targeted the colchicine binding site on β-tubulin. In lung cancer cells, S516 increased endoplasmic reticulum (ER) stress and induced reactive oxygen species (ROS) generation by mitochondria and the ER. In addition, CKD-516 monotherapy strongly inhibited the growth of lung cancer xenograft tumors and exerted a synergistic effect with carboplatin.

CONCLUSION

The findings suggest that CKD-516 exerts an anticancer effect in company with inducing ER stress and ROS production via microtubule disruption in lung cancer cells. CKD-516 may thus have therapeutic potential for lung cancer.

Epigenetic activation of FOXF1 confers cancer stem cell properties to cisplatin‑resistant non‑small cell lung cancer

The underlying molecular mechanisms of cisplatin resistance in non‑small cell lung cancer (NSCLC) are unclear. In this study, a novel differential methylation region located in the upstream regulatory region of the forkhead box F1 (FOXF1) gene was identified. The abnormal hypomethylation of FOXF1 increased the expression of FOXF1, and the high expression of FOXF1 promoted cell proliferation and inhibited cell apoptosis induced by cisplatin, which resulted in cisplatin resistance in NSCLC cells. In addition, FOXF1 promoted the expression of stem cell markers and self‑renewal capability, indicating that FOXF1 regulated cisplatin resistance by promoting cancer stem cell properties in NSCLC cells. Moreover, a strong association was observed between FOXF1 upregulation and the presence of platinum‑based chemotherapy resistance in patients with NSCLC. On the whole, the findings of this study indicate the regulatory mechanisms of cisplatin resistance by FOXF1 in NSCLC, and suggest that FOXF1 may be used as a prognostic biomarker of platinum‑based chemotherapy resistance in NSCLC.

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

The vast majority of mortality in breast cancer results from distant metastasis. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Pre-clinical animal models that reliably reflect the biology of breast cancer brain metastasis are needed to develop and test new treatments for this deadly condition. The patient-derived xenograft (PDX) model maintains many features of a donor tumor, such as intra-tumor heterogeneity, and permits the testing of individualized treatments. However, the establishment of orthotopic PDXs of brain metastasis is procedurally difficult. We have developed a method for generating such PDXs with high tumor engraftment and growth rates. Here, we describe this method and identify variables that affect its outcomes. We also compare the brain-orthotopic PDXs with ectopic PDXs grown in mammary pads of mice, and show that the responsiveness of PDXs to chemotherapeutic reagents can be dramatically affected by the site that they are in.

Integrative analysis of DNA methylation-driven genes for the prognosis of lung squamous cell carcinoma using MethylMix

Background: DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. Materials and Methods: Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. Results: A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. Conclusion: Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC.

The Role of RASSF1 Methylation in Lung Carcinoma

Lung carcinoma is the most frequently diagnosed malignant neoplasms and mainly consists of small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC). Large number of lung carcinoma patients have poor outcomes due to the late diagnosis and the limited therapeutic options. Previous attempts have proved that the evolution of lung carcinoma is a multistep molecular aberration which various genetic or epigenetic alterations may be take part in. Among these molecular aberrations, the inactivation of tumor suppressor gene has been widely observed in all types of carcinoma including lung carcinoma. As a vital inactivated mechanism, DNA methylation of tumor suppressor gene is frequently found in lung cancer. To gain exhaustive comprehension of the carcinogenesis of lung carcinoma, we summarize our current knowledge on DNA methylation of RASSF1 (RAS-Association Domain Family 1) and its clinical significance in lung carcinoma.

The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Patient-derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next-generation preclinical models.

Epigenetic heterogeneity in cancer

Phenotypic and functional heterogeneity is one of the hallmarks of human cancers. Tumor genotype variations among tumors within different patients are known as interpatient heterogeneity, and variability among multiple tumors of the same type arising in the same patient is referred to as intra-patient heterogeneity. Subpopulations of cancer cells with distinct phenotypic and molecular features within a tumor are called intratumor heterogeneity (ITH). Since Nowell proposed the clonal evolution of tumor cell populations in 1976, tumor heterogeneity, especially ITH, was actively studied. Research has focused on the genetic basis of cancer, particularly mutational activation of oncogenes or inactivation of tumor-suppressor genes (TSGs). The phenomenon of ITH is commonly explained by Darwinian-like clonal evolution of a single tumor. Despite the monoclonal origin of most cancers, new clones arise during tumor progression due to the continuous acquisition of mutations. It is clear that disruption of the "epigenetic machinery" plays an important role in cancer development. Aberrant epigenetic changes occur more frequently than gene mutations in human cancers. The epigenome is at the intersection of the environment and genome. Epigenetic dysregulation occurs in the earliest stage of cancer. The current trend of epigenetic therapy is to use epigenetic drugs to reverse and/or delay future resistance to cancer therapies. A majority of cancer therapies fail to achieve durable responses, which is often attributed to ITH. Epigenetic therapy may reverse drug resistance in heterogeneous cancer. Complete understanding of genetic and epigenetic heterogeneity may assist in designing combinations of targeted therapies based on molecular information extracted from individual tumors.

No excessive mutations in transcription activator-like effector nuclease-mediated α-1,3-galactosyltransferase knockout Yucatan miniature pigs

OBJECTIVE

Specific genomic sites can be recognized and permanently modified by genome editing. The discovery of endonucleases has advanced genome editing in pigs, attenuating xenograft rejection and cross-species disease transmission. However, off-target mutagenesis caused by these nucleases is a major barrier to putative clinical applications. Furthermore, off-target mutagenesis by genome editing has not yet been addressed in pigs.

METHODS

Here, we generated genetically inheritable α-1,3-galactosyltransferase (GGTA1) knockout Yucatan miniature pigs by combining transcription activator-like effector nuclease (TALEN) and nuclear transfer. For precise estimation of genomic mutations induced by TALEN in GGTA1 knockout pigs, we obtained the whole-genome sequence of the donor cells for use as an internal control genome.

RESULTS

In-depth whole-genome sequencing analysis demonstrated that TALEN-mediated GGTA1 knockout pigs had a comparable mutation rate to homologous recombination-treated pigs and wild-type strain controls. RNA sequencing analysis associated with genomic mutations revealed that TALEN-induced off-target mutations had no discernable effect on RNA transcript abundance.

CONCLUSION

Therefore, TALEN appears to be a precise and safe tool for generating genome-edited pigs, and the TALEN-mediated GGTA1 knockout Yucatan miniature pigs produced in this study can serve as a safe and effective organ and tissue resource for clinical applications.

Genomic evolution of cancer models: perils and opportunities

Cancer research relies on model systems, which reflect the biology of actual human tumours to only a certain extent. One important feature of human cancer is its intra-tumour genomic heterogeneity and instability. However, the extent of such genomic instability in cancer models has received limited attention in research. Here, we review the state of knowledge of genomic instability of cancer models and discuss its biological origins and implications for basic research and for cancer precision medicine. We discuss strategies to cope with such genomic evolution and evaluate both the perils and the emerging opportunities associated with it.