DNA Methylation and Bladder Cancer: Where Genotype does not Predict Phenotype

Non-oncology drug (meticrane) shows anti-cancer ability in synergy with epigenetic inhibitors and appears to be involved passively in targeting cancer cells

Emerging evidence suggests that chemotherapeutic agents and targeted anticancer drugs have serious side effects on the healthy cells/tissues of the patient. To overcome this, the use of non-oncology drugs as potential cancer therapies has been gaining momentum. Herein, we investigated one non-oncology drug named meticrane (a thiazide diuretic used to treat essential hypertension), which has been reported to indescribably improve the therapeutic efficacy of anti-CTLA4 in mice with AB1 HA tumors. In our hypothesis-driven study, we tested anti-cancer potential meticrane in hematological malignance (leukemia and multiple myeloma) and liver cancer cell lines. Our analysis showed that: 1) Meticrane induced alteration in the cell viability and proliferation in leukemia cells (Jurkat and K562 cells) and liver cancer (SK-hep-1), however, no evidence of apoptosis was detectable. 2) Meticrane showed additive/synergistic effects with epigenetic inhibitors (DNMT1/5AC, HDACs/CUDC-101 and HDAC6/ACY1215). 3) A genome-wide transcriptional analysis showed that meticrane treatment induces changes in the expression of genes associated with non-cancer associated pathways. Of importance, differentially expressed genes showed favorable correlation with the survival-related genes in the cancer genome. 4) We also performed molecular docking analysis and found considerable binding affinity scores of meticrane against PD-L1, TIM-3, CD73, and HDACs. Additionally, we tested its suitability for immunotherapy against cancers, but meticrane showed no response to the cytotoxicity of cytokine-induced killer (CIK) cells. To our knowledge, our study is the first attempt to identify and experimentally confirm the anti-cancer potential of meticrane, being also the first to test the suitability of any non-oncology drug in CIK cell therapy. Beyond that, we have expressed some concerns confronted during testing meticrane that also apply to other non-oncology drugs when considered for future clinical or preclinical purposes. Taken together, meticrane is involved in some anticancer pathways that are passively targeting cancer cells and may be considered as compatible with epigenetic inhibitors.

Assessing the Effects of a Perioperative Nutritional Support and Counseling in Gastrointestinal Cancer Patients: A Retrospective Comparative Study with Historical Controls

The aim of this study was to investigate the effects of perioperative nutritional therapy care in gastrointestinal (esophageal, gastric, gastroesophageal) cancer patients on nutritional status and disease progression (complications, hospitalization, mortality). We considered 62 gastrointestinal cancer patients treated at the Center for Integrated Oncology (CIO), University Hospital Bonn, Germany (August 2017-July 2019). Of these, 42 patients (as intervention group: IG) received pre- and postoperative nutritional support with counseling, while 20 patients (as historical control group CG) received only postoperative nutritional therapy. Several clinical parameters, such as Body Mass Index (BMI), nutritional risk screening (NRS), phase angle, postoperative complications, length of hospital stay, and mortality, were determined. There were significantly fewer patients with gastric cancer/CDH1 gene mutation and more with esophageal cancer in IG (p = 0.001). Significantly more patients received neoadjuvant therapy in IG (p = 0.036). No significant differences were found between the groups regarding BMI, NRS, complications, length of hospital stay, and mortality. However, the comparison of post- and preoperative parameters in IG showed a tendency to lose 1.74 kg of weight (p = 0.046), a decrease in phase angle by 0.59° (p = 0.004), and an increase in NRS of 1.34 points (p < 0.001). Contrary to prior reports, we found no significant effect of perioperative nutritional therapy care in gastrointestinal cancer patients; however, the small cohort size and infrequent standardization in nutritional status may possibly account for the variance. Considering that oncological pathways and metabolic nutritional pathways are interrelated, dividing patients into subgroups to provide a personalized nutritional approach may help in improving their treatment.

DNA Methylation Biomarkers in Cancer: Current Clinical Utility and Future Perspectives

Epigenetic alterations are related to inherited but reversible changes in modifications that regulate gene activity beyond the DNA sequence. DNA methylation is the best characterized epigenetic modification, controlling DNA stability, DNA structure, transcription, and regulation, contributing to normal development and differentiation. In this section, we first discuss the cellular functions of DNA methylation and focus on how this fundamental biological process is impaired in cancer. Changes in DNA methylation status in cancer have been heralded as promising targets for the development of diagnostic, prognostic, and predictive biomarkers due to their noninvasive accessibility in bodily fluids (such as blood, urine, stool), reversibility, stability, and frequency. The absence of markers for definitive diagnosis of most types of cancer and, in some cases, DNA methylation biomarkers being more specific and sensitive than commonly used protein biomarkers indicate a strong need for continued research to expand DNA methylation markers. Although the information on changes in DNA methylation status in cancer and research on its clinical relevance is rapidly increasing, the number of DNA methylation biomarkers currently available as commercial tests is very small. Here, we focus on the importance of DNA methylation location and target genes likely to be developed in the future for the development of biomarkers in addition to existing commercial tests. Following a detailed study of possible target genes, we summarize the current clinical application status of the most studied and validated DNA methylation biomarkers, including SEPT9, SDC2, BMP3, NDRG4, SFRP2, TFPI2, VIM and MGMT.

Anti-CD40 predominates over anti-CTLA-4 to provide enhanced antitumor response of DC-CIK cells in renal cell carcinoma

Cytokine-induced killer cells (CIK) in combination with dendritic cells (DCs) have shown favorable outcomes in renal cell carcinoma (RCC), yet some patients exhibit recurrence or no response to this therapy. In a broader perspective, enhancing the antitumor response of DC-CIK cells may help to address this issue. Considering this, herein, we investigated the effect of anti-CD40 and anti-CTLA-4 antibodies on the antitumor response of DC-CIK cells against RCC cell lines. Our analysis showed that, a) anti-CD40 antibody (G28.5) increased the CD3+CD56+ effector cells of CIK cells by promoting the maturation and activation of DCs, b) G28.5 also increased CTLA-4 expression in CIK cells via DCs, but the increase could be hindered by the CTLA-4 inhibitor (ipilimumab), c) adding ipilimumab was also able to significantly increase the proportion of CD3+CD56+ cells in DC-CIK cells, d) anti-CD40 antibodies predominated over anti-CTLA-4 antibodies for cytotoxicity, apoptotic effect and IFN-γ secretion of DC-CIK cells against RCC cells, e) after ipilimumab treatment, the population of Tregs in CIK cells remained unaffected, but ipilimumab combined with G28.5 significantly reduced the expression of CD28 in CIK cells. Taken together, we suggest that the agonistic anti-CD40 antibody rather than CTLA-4 inhibitor may improve the antitumor response of DC-CIK cells, particularly in RCC. In addition, we pointed towards the yet to be known contribution of CD28 in the crosstalk between anti-CTLA-4 and CIK cells.

Identification of the integrated prognostic signature associated with immuno-relevant genes and long non-coding RNAs in acute myeloid leukemia

BACKGROUND

Like other cancers, considerable effort has been made in acute myeloid leukemia (AML) to identify prognostic genes and long non-coding RNAs (lncRNAs) with their potential clinical applications. However, to date, no integrated prognostic model has been developed that combines both gene expression and lncRNAs as a singular approach in AML.

METHOD

Comprehensive bioinformatic approaches (Weighted gene co-expression network analysis, Univariate Cox regression analyses, Pearson correlation, LASSO-Cox regression, Wilcoxon test) were used to construct the signature and to define high- and low-risk groups in AML datasets. ESTIMATE and CIBERSORT algorithms were applied to investigate the potential impact of infiltrating immune cells based on the obtained signature in tumor microenvironment. In addition, gene ontology (GO) and KEGG enrichment were applied to explore the potential function of the signature.

RESULTS

Herein, we focused on immune-related genes (IRGs) and immune-related long non-coding RNAs (IRlncRNAs) and constructed an integrated prognostic immunorelevant signature in AML. The obtained signature exhibit five IRGs (DAXX, PSMB8, CSRP1, RAC2 and PTPN6) and one IRlncRNA (AC080037.2), and is strictly associated with age and FAB (French-American-British classification). Importantly, the high-risk AML group (defined by the signature) correlated positively with three types of scores (immune score, stroma score, and ESTIMATE score). We also identified a few immune cells (resting mast cells and monocytes) potentially involved in the correlation between signature and survival of AML patients. The prognostic ability of the obtained signature was tested in the training cohort and then validated in both test and total cohorts. The pathway enrichment analysis confirmed the possible immune- related role of the signature.

CONCLUSION

We constructed an integrated prognostic signature comprising five immune-related protein-coding genes (IRPCG) (DAXX, PSMB8, CSRP1, RAC2, and PTPN6) and one immune-related lncRNA (AC080037.2) that may serve as potential biomarkers for predicting survival and further stratifying AML patients.

WNT/β-Catenin-Mediated Resistance to Glucose Deprivation in Glioblastoma Stem-like Cells

Isocitrate dehydrogenase (IDH)-wildtype glioblastoma is the most common primary malignant brain tumor. It is associated with a particularly poor prognosis, as reflected by an overall median survival of only 15 months in patients who undergo a supramarginal surgical reduction of the tumor mass followed by combined chemoradiotherapy. The highly malignant nature of IDH-wildtype glioblastoma is thought to be driven by glioblastoma stem-like cells (GSCs) that harbor the ability of self-renewal, survival, and adaptability to challenging environmental conditions. The wingless (WNT) signaling pathway is a phylogenetically highly conserved stemness pathway, which promotes metabolic plasticity and adaptation to a nutrient-limited tumor microenvironment. To unravel the reciprocal regulation of the WNT pathway and the nutrient-limited microenvironment, glioblastoma cancer stem-like cells were cultured in a medium with either standard or reduced glucose concentrations for various time points (24, 48, and 72 h). Glucose depletion reduced cell viability and facilitated the survival of a small population of starvation-resistant tumor cells. The surviving cells demonstrated increased clonogenic and invasive properties as well as enhanced chemosensitivity to pharmacological inhibitors of the WNT pathway (LGK974, berberine). Glucose depletion partially led to the upregulation of WNT target genes such as CTNNB1, ZEB1, and AXIN2 at the mRNA and corresponding protein levels. LGK974 treatment alone or in combination with glucose depletion also altered the metabolite concentration in intracellular compartments, suggesting WNT-mediated metabolic regulation. Taken together, our findings suggest that WNT-mediated metabolic plasticity modulates the survival of GSCs under nutrient-restricted environmental conditions.

A Combination of Cytokine-Induced Killer Cells With PD-1 Blockade and ALK Inhibitor Showed Substantial Intrinsic Variability Across Non-Small Cell Lung Cancer Cell Lines

Background

Cancer heterogeneity poses a serious challenge concerning the toxicity and adverse effects of therapeutic inhibitors, especially when it comes to combinatorial therapies that involve multiple targeted inhibitors. In particular, in non-small cell lung cancer (NSCLC), a number of studies have reported synergistic effects of drug combinations in the preclinical models, while they were only partially successful in the clinical setup, suggesting those alternative clinical strategies (with genetic background and immune response) should be considered. Herein, we investigated the antitumor effect of cytokine-induced killer (CIK) cells in combination with ALK and PD-1 inhibitors in vitro on genetically variable NSCLC cell lines.

Methods

We co-cultured the three genetically different NSCLC cell lines NCI-H2228 (EML4-ALK), A549 (KRAS mutation), and HCC-78 (ROS1 rearrangement) with and without nivolumab (PD-1 inhibitor) and crizotinib (ALK inhibitor). Additionally, we profiled the variability of surface expression multiple immune checkpoints, the concentration of absolute dead cells, intracellular granzyme B on CIK cells using flow cytometry as well as RT-qPCR. ELISA and Western blot were performed to verify the activation of CIK cells.

Results

Our analysis showed that (a) nivolumab significantly weakened PD-1 surface expression on CIK cells without impacting other immune checkpoints or PD-1 mRNA expression, (b) this combination strategy showed an effective response on cell viability, IFN-γ production, and intracellular release of granzyme B in CD3⁺ CD56⁺ CIK cells, but solely in NCI-H2228, (c) the intrinsic expression of Fas ligand (FasL) as a T-cell activation marker in CIK cells was upregulated by this additive effect, and (d) nivolumab induced Foxp3 expression in CD4⁺CD25⁺ subpopulation of CIK cells significantly increased. Taken together, we could show that CIK cells in combination with crizotinib and nivolumab can enhance the anti-tumor immune response through FasL activation, leading to increased IFN-γ and granzyme B, but only in NCI-H2228 cells with EML4-ALK rearrangement. Therefore, we hypothesize that CIK therapy may be a potential alternative in NSCLC patients harboring EML4-ALK rearrangement, in addition, we support the idea that combination therapies offer significant potential when they are optimized on a patient-by-patient basis.

Crosstalk between β-Catenin and CCL2 Drives Migration of Monocytes towards Glioblastoma Cells

Isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is a fast growing and highly heterogeneous tumor, often characterized by the presence of glioblastoma stem cells (GSCs). The plasticity of GSCs results in therapy resistance and impairs anti-tumor immune response by influencing immune cells in the tumor microenvironment (TME). Previously, β-catenin was associated with stemness in GBM as well as with immune escape mechanisms. Here, we investigated the effect of β-catenin on attracting monocytes towards GBM cells. In addition, we evaluated whether CCL2 is involved in β-catenin crosstalk between monocytes and tumor cells. Our analysis revealed that shRNA targeting β-catenin in GBMs reduces monocytes attraction and impacts CCL2 secretion. The addition of recombinant CCL2 restores peripheral blood mononuclear cells (PBMC) migration towards medium (TCM) conditioned by shβ-catenin GBM cells. CCL2 knockdown in GBM cells shows similar effects and reduces monocyte migration to a similar extent as β-catenin knockdown. When investigating the effect of CCL2 on β-catenin activity, we found that CCL2 modulates components of the Wnt/β-catenin pathway and alters the clonogenicity of GBM cells. In addition, the pharmacological β-catenin inhibitor MSAB reduces active β-catenin, downregulates the expression of associated genes and alters CCL2 secretion. Taken together, we showed that β-catenin plays an important role in attracting monocytes towards GBM cells in vitro. We hypothesize that the interactions between β-catenin and CCL2 contribute to maintenance of GSCs via modulating immune cell interaction and promoting GBM growth and recurrence.

A Low Dose of Pure Cannabidiol Is Sufficient to Stimulate the Cytotoxic Function of CIK Cells without Exerting the Downstream Mediators in Pancreatic Cancer Cells

Despite numerous studies conducted over the past decade, the exact role of the cannabinoid system in cancer development remains unclear. Though research has focused on two cannabinoid receptors (CB1, CB2) activated by most cannabinoids, CB2 holds greater attention due to its expression in cells of the immune system. In particular, cytokine-induced killer cells (CIKs), which are pivotal cytotoxic immunological effector cells, express a high-level of CB2 receptors. Herein, we sought to investigate whether inducing CIK cells with cannabidiol can enhance their cytotoxicity and if there are any possible counter effects in its downstream cascade of phosphorylated p38 and CREB using a pancreatic ductal adenocarcinoma cell line (PANC-1). Our results showed that IL-2 modulates primarily the expression of the CB2 receptor on CIK cells used during ex vivo CIK expansion. The autophagosomal-associated scaffold protein p62 was found to co-localize with CB2 receptors in CIK cells and the PANC-1 cell line. CIK cells showed a low level of intracellular phospho-p38 and, when stimulated with cannabidiol (CBD), a donor specific variability in phospho-CREB. CBD significantly decreases the viability of PANC-1 cells presumably by increasing the cytotoxicity of CIK cells. Taken together, in our preclinical in vitro study, we propose that a low effective dose of CBD is sufficient to stimulate the cytotoxic function of CIK without exerting any associated mediator. Thus, the combinatorial approach of non-psychoactive CBD and CIK cells appears to be safe and can be considered for a clinical perspective in pancreatic cancer.

Immunoautophagy-Related Long Noncoding RNA (IAR-lncRNA) Signature Predicts Survival in Hepatocellular Carcinoma

BACKGROUND

The dysregulation of autophagy and immunological processes has been linked to various pathophysiological conditions, including cancer. Most notably, their particular involvement in hepatocellular carcinoma (HCC) is becoming increasingly evident. This has led to the possibility of developing a prognostic signature based on immuno-autophagy-related (IAR) genes. Given that long non-coding RNAs (lncRNAs) also play a special role in HCC, a combined signature utilizing IAR genes and HCC-associated long noncoding RNAs (as IARlncRNA) may potentially help in the clinical scenario.

METHOD

We used Pearson correlation analysis, Kaplan-Meier survival curves, univariate and multivariate Cox regression, and ROC curves to generate and validate a prognostic immuno-autophagy-related long non-coding RNA (IARlncRNA) signature. The Chi-squared test was utilized to investigate the correlation between the obtained signature and the clinical characteristics. CIBERSORT algorithms and the Wilcoxon rank sum test were applied to investigate the correlation between signature and infiltrating immune cells. GO and KEGG analyses were performed to derived signature-dependent pathways.

RESULTS

Herein, we build an IAR-lncRNA signature (as first in the literature) and demonstrate its prognostic ability in hepatocellular carcinoma. Primarily, we identified three IARlncRNAs (MIR210HG, AC099850.3 and CYTOR) as unfavorable prognostic determinants. The obtained signature predicted the high-risk HCC group with shorter overall survival, and was further associated with clinical characteristics such as tumor grade (t = 10.918, p = 0.001). Additionally, several infiltrating immune cells showed varied fractions between the low-risk group and the high-risk HCC groups in association with the obtained signature. In addition, pathways analysis described by the signature clearly distinguishes both risk groups in HCC.

CONCLUSIONS

The immuno-autophagy-related long non-coding RNA (IARlncRNA) signature we established exhibits a prognostic ability in hepatocellular carcinoma. To our knowledge, this is the first attempt in the literature to combine three determinants (immune, autophagy and LnRNAs), thus requiring molecular validation of this obtained signature in clinical samples.

NKG2D Engagement Alone Is Sufficient to Activate Cytokine-Induced Killer Cells While 2B4 Only Provides Limited Coactivation

Cytokine-induced killer (CIK) cells are an ex vivo expanded heterogeneous cell population with an enriched NK-T phenotype (CD3+CD56+). Due to the convenient and relatively inexpensive expansion capability, together with low incidence of graft versus host disease (GVHD) in allogeneic cancer patients, CIK cells are a promising candidate for immunotherapy. It is well known that natural killer group 2D (NKG2D) plays an important role in CIK cell-mediated antitumor activity; however, it remains unclear whether its engagement alone is sufficient or if it requires additional co-stimulatory signals to activate the CIK cells. Likewise, the role of 2B4 has not yet been identified in CIK cells. Herein, we investigated the individual and cumulative contribution of NKG2D and 2B4 in the activation of CIK cells. Our analysis suggests that (a) NKG2D (not 2B4) is implicated in CIK cell (especially CD3+CD56+ subset)-mediated cytotoxicity, IFN-γ secretion, E/T conjugate formation, and degranulation; (b) NKG2D alone is adequate enough to induce degranulation, IFN-γ secretion, and LFA-1 activation in CIK cells, while 2B4 only provides limited synergy with NKG2D (e.g., in LFA-1 activation); and (c) NKG2D was unable to costimulate CD3. Collectively, we conclude that NKG2D engagement alone suffices to activate CIK cells, thereby strengthening the idea that targeting the NKG2D axis is a promising approach to improve CIK cell therapy for cancer patients. Furthermore, CIK cells exhibit similarities to classical invariant natural killer (iNKT) cells with deficiencies in 2B4 stimulation and in the costimulation of CD3 with NKG2D. In addition, based on the current data, the divergence in receptor function between CIK cells and NK (or T) cells can be assumed, pointing to the possibility that molecular modifications (e.g., using chimeric antigen receptor technology) on CIK cells may need to be customized and optimized to maximize their functional potential.

From Cellular Infiltration Assessment to a Functional Gene Set-Based Prognostic Model for Breast Cancer

Background

Cancer heterogeneity is a major challenge in clinical practice, and to some extent, the varying combinations of different cell types and their cross-talk with tumor cells that modulate the tumor microenvironment (TME) are thought to be responsible. Despite recent methodological advances in cancer, a reliable and robust model that could effectively investigate heterogeneity with direct prognostic/diagnostic clinical application remained elusive.

Results

To investigate cancer heterogeneity, we took advantage of single-cell transcriptome data and constructed the first indication- and cell type-specific reference gene expression profile (RGEP) for breast cancer (BC) that can accurately predict the cellular infiltration. By utilizing the BC-specific RGEP combined with a proven deconvolution model (LinDeconSeq), we were able to determine the intrinsic gene expression of 15 cell types in BC tissues. Besides identifying significant differences in cellular proportions between molecular subtypes, we also evaluated the varying degree of immune cell infiltration (basal-like subtype: highest; Her2 subtype: lowest) across all available TCGA-BRCA cohorts. By converting the cellular proportions into functional gene sets, we further developed a 24 functional gene set-based prognostic model that can effectively discriminate the overall survival (P = 5.9 × 10-33, n = 1091, TCGA-BRCA cohort) and therapeutic response (chemotherapy and immunotherapy) (P = 6.5 × 10-3, n = 348, IMvigor210 cohort) in the tumor patients.

Conclusions

Herein, we have developed a highly reliable BC-RGEP that adequately annotates different cell types and estimates the cellular infiltration. Of importance, the functional gene set-based prognostic model that we have introduced here showed a great ability to screen patients based on their therapeutic response. On a broader perspective, we provide a perspective to generate similar models in other cancer types to identify shared factors that drives cancer heterogeneity.

X-Linked Tumor Suppressor Genes Act as Presumed Contributors in the Sex Chromosome-Autosome Crosstalk in Cancers

Since the human genome contains about 6% of tumor suppressor genes (TSGs) and the X chromosome alone holds a substantial share (2%), herein, we have discussed exclusively the relative contribution of X-linked human TSGs that appear to be primarily involved in 32 different cancer types. Our analysis showed that, (a) the majority of X-linked TSGs are primarily involved in the dysregulation of breast cancer, followed by prostate cancer, (b) Despite being escaped from X chromosome inactivation (XCI), a clear pattern of altered promoter methylation linked to the mutational burden was observed among them. (c) X-linked TSGs (mainly on the q-arm) maintain spatial and genetic interactions with certain autosomal loci. Corroborating our previous findings that loss/gain of entire sex chromosomes (in XO and XXY syndromes) can profoundly affect the epigenetic status of autosomes we herein suggest that X-linked TSGs alone can also contribute significantly in the dynamics this sex chromosome-autosome crosstalk to restructure the cancer genome.

PPAR-Responsive Elements Enriched with Alu Repeats May Contribute to Distinctive PPARγ-DNMT1 Interactions in the Genome

Simple Summary

This study aimed to explore the potential role of PPARγ–DNMT1 interaction through PPAR-responsive elements (PPREs), which we have found to be enriched with Alu repeats. Apart from protein–protein interactions and co-expression in multiple cancer types, we exclusively described a prognostic role for PPARγ in uveal melanoma (UM).

Abstract

Background: PPARγ (peroxisome proliferator-activated receptor gamma) is involved in the pathology of numerous diseases, including UM and other types of cancer. Emerging evidence suggests that an interaction between PPARγ and DNMTs (DNA methyltransferase) plays a role in cancer that is yet to be defined. Methods: The configuration of the repeating elements was performed with CAP3 and MAFFT, and the structural modelling was conducted with HDOCK. An evolutionary action scores algorithm was used to identify oncogenic variants. A systematic bioinformatic appraisal of PPARγ and DNMT1 was performed across 29 tumor types and UM available in The Cancer Genome Atlas (TCGA). Results: PPAR-responsive elements (PPREs) enriched with Alu repeats are associated with different genomic regions, particularly the promotor region of DNMT1. PPARγ–DNMT1 co-expression is significantly associated with several cancers. C-terminals of PPARγ and DNMT1 appear to be the potential protein–protein interaction sites where disease-specific mutations may directly impair the respective protein functions. Furthermore, PPARγ expression could be identified as an additional prognostic marker for UM. Conclusions: We hypothesize that the function of PPARγ requires an additional contribution of Alu repeats which may directly influence the DNMT1 network. Regarding UM, PPARγ appears to be an additional discriminatory prognostic marker, in particular in disomy 3 tumors.

PD-1 blockade enhances cytokine-induced killer cell-mediated cytotoxicity in B-cell non-Hodgkin lymphoma cell lines

The clinical utility of immune checkpoint inhibitors, such as programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors used alone or in combination with other therapies, is currently gaining attention. In this particular scenario, the inclusion of cytokine-induced killer (CIK) cells has proven to be a novel therapeutic approach. CIK cells have shown anticancer activity in various hematopoietic malignancies, but their defined cytotoxicity in B-cell non-Hodgkin lymphoma (B-NHL) remains to be fully elucidated. The present study investigated the role of PD-1/PD-L1 blockades on the cytotoxic efficacy of CIK cells primarily in B-NHL cell lines. The current analysis revealed that CIK cells prompted cytotoxicity against B-NHL cell lines (DAUDI and SU-DHL-4), and a significant increase in PD-L1 expression was observed when CIK cells were co-cultured with B-NHL cells. Additionally, a combination of PD-1 and PD-L1 antibodies with CIK cells significantly decreased cell viability only in DAUDI cells. Furthermore, IFN-γ elevation was observed in both cell lines treated with CIK alone or with PD-1 antibody, but this tendency was not observed for PD-L1. Since PD-1 can suppress immune inactivation, whereas CD40L can promote it, the effects of CD40L blockade were also examined; however, no significant changes in cell viability were observed. Overall, the present in vitro data suggested that CIK cells exerted a cytotoxic function in B-NHL cells, and a combination of PD-1 inhibitors with CIK cells may provide a potential therapeutic option for this type of lymphoma. Nevertheless, in vivo experiments are warranted to undermine the extent to which PD-1 inhibitors may be used to enhance the antitumor activity of CIK cells in B-NHL.

Epigenetic Regulatory Enzymes: mutation Prevalence and Coexistence in Cancers

Epigenetic regulation is an important layer of transcriptional control with the particularity to affect the broad spectrum of genome. Over the years, largely due to the substantial number of recurrent mutations, there have been hundreds of novel driver genes characterized in various cancers. Additionally, the relative contribution of two dysregulated epigenomic entities (DNA methylation and histone modifications) that gradually drive the cancer phenotype remains in the research focus. However, a complex scenario arises when the disease phenotype does not harbor any relevant mutation or an abnormal transcription level. Although the cancer landscape involves the contribution of multiple genetic and non-genetic factors, herein, we discuss specifically the mutation spectrum of epigenetically-related enzymes in cancer. In addition, we address the coexistence of these two epigenetic entities in malignant human diseases, especially cancer. We suggest that the study of epigenetically-related somatic mutations in the early cellular differentiation stage of embryonic development might help to understand their later-staged footprints in the cancer genome. Furthermore, understanding the co-occurrence and/or inverse association of different disease types and redefining the general definition of "healthy" controls could provide insights into the genome reorganization.

DeconPeaker, a Deconvolution Model to Identify Cell Types Based on Chromatin Accessibility in ATAC-Seq Data of Mixture Samples

While our understanding of cellular and molecular processes has grown exponentially, issues related to the cell microenvironment and cellular heterogeneity have sparked a new debate concerning the cell identity. Cell composition (chromatin and nuclear architecture) poses a strong risk for dynamic changes in the diseased condition. Since chromatin accessibility patterns play a major role in human diseases, it is therefore anticipated that a deconvolution tool based on open chromatin data will provide better performance in identifying cell composition. Herein, we have designed the deconvolution tool "DeconPeaker," which can precisely define the uniqueness among subpopulations of cells using open chromatin datasets. Using this tool, we simultaneously evaluated chromatin accessibility and gene expression datasets to estimate cell types and their respective proportions in a mixture of samples. In comparison to other known deconvolution methods, we observed the lowest average root-mean-square error (RMSE = 0.042) and the highest average correlation coefficient (r = 0.919) between the prediction and "true" proportion. As a proof-of-concept, we also tested chromatin accessibility data from acute myeloid leukemia (AML) and successfully obtained unique cell types associated with AML progression. Furthermore, we showed that chromatin accessibility represents more essential characteristics in the identification of cell types than gene expression. Taken together, DeconPeaker as a powerful tool has the potential to combine different datasets (primarily, chromatin accessibility and gene expression) and define different cell types in mixtures. The Python package of DeconPeaker is now available at https://github.com/lihuamei/DeconPeaker.