Prognostic gene expression signature revealed the involvement of mutational pathways in cancer genome

Pla2g5 contributes to viral-like-induced lung inflammation through macrophage proliferation and LA/Ffar1 lung cell recruitment

Macrophages expressing group V phospholipase A2 (Pla2g5) release the free fatty acid (FFA) linoleic acid (LA), potentiating lung type 2 inflammation. Although Pla2g5 and LA increase in viral infections, their role remains obscure. We generated Pla2g5flox/flox mice, deleted Pla2g5 by using the Cx3cr1cre transgene, and activated bone marrow-derived macrophages (BM-Macs) with poly:IC, a synthetic double-stranded RNA that triggers a viral-like immune response, known Pla2g5-dependent stimuli (IL-4, LPS + IFNγ, IL-33 + IL-4 + GM-CSF) and poly:IC + LA followed by lipidomic and transcriptomic analysis. Poly:IC-activated Pla2g5flox/flox;Cx3cr1cre/+ BM-Macs had downregulation of major bioactive lipids and critical enzymes producing those bioactive lipids. In addition, AKT phosphorylation was lower in poly:IC-stimulated Pla2g5flox/flox;Cx3cr1cre/+ BM-Macs, which was not restored by adding LA to poly:IC-stimulated BM-Macs. Consistently, Pla2g5flox/flox;Cx3cr1cre/+ mice had diminished poly:IC-induced lung inflammation, including inflammatory macrophage proliferation, while challenging Pla2g5flox/flox;Cx3cr1cre/+ mice with poly:IC + LA partially restored lung inflammation and inflammatory macrophage proliferation. Finally, mice lacking FFA receptor-1 (Ffar1)-null mice had reduced poly:IC-induced lung cell recruitment and tissue macrophage proliferation, not corrected by LA. Thus, Pla2g5 contributes to poly:IC-induced lung inflammation by regulating inflammatory macrophage proliferation and LA/Ffar1-mediated lung cell recruitment and tissue macrophage proliferation.

Cytokine-Induced Killer Cells in Combination with Heat Shock Protein 90 Inhibitors Functioning via the Fas/FasL Axis Provides Rationale for a Potential Clinical Benefit in Burkitt's lymphoma

Constant efforts are being made to develop methods for improving cancer immunotherapy, including cytokine-induced killer (CIK) cell therapy. Numerous heat shock protein (HSP) 90 inhibitors have been assessed for antitumor efficacy in preclinical and clinical trials, highlighting their individual prospects for targeted cancer therapy. Therefore, we tested the compatibility of CIK cells with HSP90 inhibitors using Burkitt's lymphoma (BL) cells. Our analysis revealed that CIK cytotoxicity in BL cells was augmented in combination with independent HSP90 inhibitors 17-DMAG (17-dimethylaminoethylamino-17-demethoxygeldanamycin) and ganetespib. Interestingly, CIK cell cytotoxicity did not diminish after blocking with NKG2D (natural killer group 2, member D), which is a prerequisite for their activation. Subsequent analyses revealed that the increased expression of Fas on the surface of BL cells, which induces caspase 3/7-dependent apoptosis, may account for this effect. Thus, we provide evidence that CIK cells, either alone or in combination with HSP90 inhibitors, target BL cells via the Fas-FasL axis rather than the NKG2D pathway. In the context of clinical relevance, we also found that high expression of HSP90 family genes (HSP90AA1, HSP90AB1, and HSP90B1) was significantly associated with the reduced overall survival of BL patients. In addition to HSP90, genes belonging to the Hsp40, Hsp70, and Hsp110 families have also been found to be clinically significant for BL survival. Taken together, the combinatorial therapy of CIK cells with HSP90 inhibitors has the potential to provide clinical benefits to patients with BL.

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.

Regulator of G Protein Signaling 20 Correlates with Long Intergenic Non-Coding RNA (lincRNAs) Harboring Oncogenic Potential and Is Markedly Upregulated in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is at the forefront of the global cancer burden, and biomarkers for HCC are constantly being sought. Interestingly, RGS (Regulators of G protein signaling) proteins, which negatively regulate GPCR signaling, have been associated with various cancers, with some members of the RGS family being associated with liver cancer as well. Considering this, we investigated the role of RGS20 as a potential prognostic marker in 28 different cancer types with special emphasis on HCC. By using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data, our analysis revealed that (a) RGS20 was strongly upregulated in tumor tissue compared with adjacent normal tissue of HCC patients; (b) RGS20 was strongly associated with some important clinical parameters such as alpha-fetoprotein and tumor grade in the HCC patients; (c) besides HCC (p < 0.001), RGS20 was found to be an important factor for survival in four other cancers (clear renal cell carcinoma: p < 0.001, lung adenocarcinoma: p = 0.004, mesothelioma: p = 0.039, ovarian serous cystadenocarcinoma: p = 0.048); (d) RGS20 was found to be significantly associated with some tumor-related signaling pathways and long intergenic non-coding RNAs (lincRNAs: LINC00511, PVT1, MIR4435-2HG, BCYRN1, and MAPKAPK5-AS1) that exhibit oncogenic potential. Taken together, we showed that RGS20 correlates with a few HCC-associated lincRNAs harboring oncogenic potential and is markedly upregulated in HCC patients. Our analysis further supports the putative function of RGS proteins, particularly RGS20, in cancer.

Identification of Prognostic Genes in Gliomas Based on Increased Microenvironment Stiffness

With a median survival time of 15 months, glioblastoma multiforme is one of the most aggressive primary brain cancers. The crucial roles played by the extracellular matrix (ECM) stiffness in glioma progression and treatment resistance have been reported in numerous studies. However, the association between ECM-stiffness-regulated genes and the prognosis of glioma patients remains to be explored. Thus, using bioinformatics analysis, we first identified 180 stiffness-dependent genes from an RNA-Seq dataset, and then evaluated their prognosis in The Cancer Genome Atlas (TCGA) glioma dataset. Our results showed that 11 stiffness-dependent genes common between low- and high-grade gliomas were prognostic. After validation using the Chinese Glioma Genome Atlas (CGGA) database, we further identified four stiffness-dependent prognostic genes: FN1, ITGA5, OSMR, and NGFR. In addition to high-grade glioma, overexpression of the four-gene signature also showed poor prognosis in low-grade glioma patients. Moreover, our analysis confirmed that the expression levels of stiffness-dependent prognostic genes in high-grade glioma were significantly higher than in low-grade glioma, suggesting that these genes were associated with glioma progression. Based on a pathophysiology-inspired approach, our findings illuminate the link between ECM stiffness and the prognosis of glioma patients and suggest a signature of four stiffness-dependent genes as potential therapeutic targets.

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.

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.

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.

Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models

Colorectal cancer (CRC) is one of the most common cancers worldwide, and a leading cause of cancer deaths. Better classifying multicategory outcomes of CRC with clinical and omic data may help adjust treatment regimens based on individual's risk. Here, we selected the features that were useful for classifying four-category survival outcome of CRC using the clinical and transcriptomic data, or clinical, transcriptomic, microsatellite instability and selected oncogenic-driver data (all data) of TCGA. We also optimized multimetric feature selection to develop the best multinomial logistic regression (MLR) and random forest (RF) models that had the highest accuracy, precision, recall and F1 score, respectively. We identified 2073 differentially expressed genes of the TCGA RNASeq dataset. MLR overall outperformed RF in the multimetric feature selection. In both RF and MLR models, precision, recall and F1 score increased as the feature number increased and peaked at the feature number of 600-1000, while the models' accuracy remained stable. The best model was the MLR one with 825 features based on sum of squared coefficients using all data, and attained the best accuracy of 0.855, F1 of 0.738 and precision of 0.832, which were higher than those using clinical and transcriptomic data. The top-ranked features in the MLR model of the best performance using clinical and transcriptomic data were different from those using all data. However, pathologic staging, HBS1L, TSPYL4, and TP53TG3B were the overlapping top-20 ranked features in the best models using clinical and transcriptomic, or all data. Thus, we developed a multimetric feature-selection based MLR model that outperformed RF models in classifying four-category outcome of CRC patients. Interestingly, adding microsatellite instability and oncogenic-driver data to clinical and transcriptomic data improved models' performances. Precision and recall of tuned algorithms may change significantly as the feature number changes, but accuracy appears not sensitive to these changes.

Recent Development in NKT-Based Immunotherapy of Glioblastoma: From Bench to Bedside

Glioblastoma multiforme (GBM) is an aggressive and dismal disease with a median overall survival of around 15 months and a 5-year survival rate of 7.2%. Owing to genetic mutations, drug resistance, disruption to the blood–brain barrier (BBB)/blood–brain tumor barrier (BBTB), and the complexity of the immunosuppressive environment, the therapeutic approaches to GBM represent still major challenges. Conventional therapies, including surgery, radiotherapy, and standard chemotherapy with temozolomide, have not resulted in satisfactory improvements in the overall survival of GBM patients. Among cancer immunotherapeutic approaches, we propose that adjuvant NKT immunotherapy with invariant NKT (iNKT) and cytokine-induced killer (CIK) cells may improve the clinical scenario of this devastating disease. Considering this, herein, we discuss the current strategies of NKT therapy for GBM based primarily on in vitro/in vivo experiments, clinical trials, and the combinatorial approaches with future therapeutic potential.

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.

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.

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.