Comprehensive analysis of the SLC16A gene family in pancreatic cancer via integrated bioinformatics

Gut-derived lactic acid enhances tryptophan to 5-hydroxytryptamine in regulation of anxiety via Akkermansia muciniphila

The gut microbiota plays a pivotal role in anxiety regulation through pathways involving neurotransmitter production, immune signaling, and metabolic interactions. Among these, gut-derived serotonin (5-hydroxytryptamine, 5-HT), synthesized from tryptophan metabolism, has been identified as a key mediator. However, it remains unclear whether specific microbial factors regulate tryptophan metabolism to influence 5-HT production and anxiety regulation. In this study, we analyzed 110 athletes undergoing closed training and found that fecal lactate levels were significantly associated with anxiety indicators. We observed a significant negative correlation between Akkermansia abundance and anxiety levels in athletes. Co-supplementation with lactate and Akkermansia muciniphila (A. muciniphila) modulated tryptophan metabolism by increasing key enzyme TPH1 and reducing IDO1, thus shifting metabolism from kynurenine (Kyn) to 5-HT. In addition, lactate enhanced the propionate production capacity of A. muciniphila, potentially contributing to anxiety reduction in mice. Taken together, these findings suggest that enteric lactate and A. muciniphila collaboratively restore the imbalance in tryptophan metabolism, leading to increased 5-HT activity and alleviating anxiety phenotypes. This study highlights the intricate interplay between gut metabolites and anxiety regulation, offering potential avenues for microbiota-targeted therapeutic strategies for anxiety.

Comprehensive pan-cancer analysis identified SLC16A3 as a potential prognostic and diagnostic biomarker

SLC16A3, belonging to the SLC16 gene family, is involved in the transportation of monocarboxylate. SLC16A family members play important roles in tumorigenesis, nonetheless, the specific involvement of SLC16A3 in tumor prognosis and diagnosis in human cancers remains unelucidated. This study dealt with the exploration of SLC16A3 expression in human pan-cancer and its significance regarding disease prognosis. For this investigation, the mRNA expression data of SLC16A3 were acquired from the TCGA and the GTEx datasets. The Kaplan-Meier plots, univariate Cox regression, and the ROC curve were employed for assessing the prognostic and diagnostic significance of SLC16A3 in pan-cancer. Furthermore, the cBioPortal database was used to analyze the SLC16A3 genomic alterations. Moreover, the association of the infiltration of immune cells and immune checkpoint genes with SLC16A3 was analyzed by the TIMER database. Gene Ontology and KEGG pathway analysis were employed to explore the function of SLC16A3 in pan-cancer. The resulting data demonstrated that SLC16A3 mRNA expression was overexpressed in most cancers and its protein expression was also high across diverse cancer types. Moreover, upregulated SLC16A3 expression was linked to poor OS and PFI of certain cancers. Cox regression analysis further indicated that SLC16A3 is a risk factor for patients with PAAD, CESC, LUSC, LUAD, CHOL, LGG, MESO, and OSCC. The ROC curve revealed that SLC16A3 exhibited a high accuracy (AUC > 0.9) in BRCA, CHOL, ESCA, GBM, and KIRC prediction. Moreover, the acquired data indicated that in pan-cancer, the SLC16A3 expression exhibited correlations with immune checkpoint genes and immune cells. These findings collectively suggest that SLC16A3 holds promise as a biomarker for diagnostic and prognostic purposes in pan-cancer.

Impact of SLC16A8 on tumor microenvironment and angiogenesis in colorectal cancer: New therapeutic target insights

BACKGROUND

SLC16A8, a lactate efflux transporter, is upregulated in various cancers, but its effects on tumor microenvironments remain understudied. This research explores its role in colorectal cancer (CRC) and the impact on the associated microenvironment consisting of vascular endothelial cells.

AIM

To explore the role in CRC and the impact on the associated microenvironment consisting of vascular endothelial cells.

METHODS

Hypoxic conditions prompted examination of SLC16A8 expression, glycolysis, lactate efflux, and Warburg effect correlations in CRC cell lines. Co-culture with HUVEC allowed for endothelial-mesenchymal transition (EndMT) characterization, revealing lactate efflux's influence. Knockdown of SLC16A8 in CRC cells enabled relevant phenotype tests and tumorigenesis experiments, investigating tumor growth, blood vessel distribution, and signaling pathway alterations.

RESULTS

SLC16A8 expression was significantly upregulated in CRC tissues compared to adjacent normal tissues and correlated with disease progression (P < 0.05). Under hypoxic conditions, HIF-1α induced SLC16A8 expression, leading to enhanced metabolic reprogramming and increased lactate production. siRNA-mediated SLC16A8 knockdown effectively reversed hypoxia-induced changes, including reduced glucose consumption and lactate production. Co-culture experiments revealed that SLC16A8 knockdown significantly inhibited hypoxia-induced EndMT in HUVEC cells. In vivo studies demonstrated that SLC16A8 knockdown suppressed tumor growth, reduced Ki67 expression, and decreased HIF-1α levels. Furthermore, SLC16A8 silencing led to decreased expression of key metabolic enzymes PKM2 and LDHA, indicating its role in glycolytic regulation.

CONCLUSION

Our findings reveal that SLC16A8 functions as a critical mediator of hypoxia-induced metabolic reprogramming in CRC progression.

Identifying Genes Associated with the Anticancer Activity of a Fluorinated Chalcone in Triple-Negative Breast Cancer Cells Using Bioinformatics Tools

Fluorinated chalcones are molecules reported to possess potent anticancer properties against triple-negative breast cancer (TNBC) cells. However, their molecular mechanisms have not yet been fully explored. Using bioinformatics tools, we analyzed the transcriptomes of MDA-MB-231 cells treated with either a novel fluorinated chalcone (compound 3) or a control in order to identify differentially expressed (DE) genes associated with its anticancer activity and determine the biological processes in which these genes are involved. A fluorinated chalcone was synthesized using the Claisen-Schmidt method. The transcriptome of MDA-MB-231 cells was then analyzed on an Illumina NextSeq500, and DE genes with significant changes in expression were identified using the DESeq2 v1.38.0 bioinformatics tool under the strict detection criteria of |log2FC| ≥  2 and adjusted p < 0.05. We identified 504 DE genes, which were enriched in terms related to "regulation of cell death", "cation transport", "response to topologically incorrect proteins", and "response to unfolded proteins". Surprisingly, these genes were involved in "the HSF1-dependent transactivation pathway" and "the attenuation phase pathway". This bioinformatics-based study suggests that the tested fluorinated chalcone could influence HSF-1 silencing in addition to promoting the up-regulation of several genes involved in stress-induced apoptosis. Therefore, the tested compound could have enormous potential as a novel approach for TNBC treatment.

Identification of Differentially Expressed Genes in the Hypothalamus of Broilers Under Heat Stress Using Transcriptome Analysis

The hypothalamus is the advanced center that regulates visceral activities under the cerebral cortex. It plays some key roles, such as regulating body temperature, assessing feed intake, and balancing blood glucose and endocrine gland activities. Heat stress is known to trigger a series of detrimental consequences, prominently featuring a reduction in feed intake, an elevation in body temperature, and other related phenomena. To understand the mechanisms of how heat stress affects the function of the hypothalamus, broilers were allocated to three groups: the normal control (NC) group, the heat-stress (HS) group, and the pair-fed (PF) group. The PF group was established with the aim of eliminating the confounding effect of reduced feed intake. The trial lasted for two weeks, from the age of 28 to 42 d. A total of 280 differential expressed genes (DEGs) were identified (padj < 0.05, |log2(FC)| ≥ 1) among three groups, including 3 up-regulated and 112 down-regulated genes in the HS group compared to the NC group, and 3 up-regulated and 13 down-regulated genes between the PF and NC groups. Compared with the HS group, a total of 149 genes were identified in the PF group, of which 125 genes were up-regulated and 24 genes were down-regulated. Gene Ontology enrichment indicated that a subset of DEGs was involved in brain development, the central nervous system (CNS), nerve signal transduction, and calcium homeostasis. The solute carrier family 1 member A6 and solute carrier family 6 member 13, identified as down-regulated genes (padj < 0.05) in the HS group, were considered as key genes in Gamma-aminobutyric acid (GABA) transportation, the normal expression of which ensures that extracellular GABA is maintained at a certain level and provides the amino acids needed for metabolism. Simultaneously, the solute carrier family 13 member 4 and solute carrier family 16 member 8 were also identified as down-regulated, which indicated that heat stress resulted in disorder and physiologic derangement in the hypothalamus. Meanwhile, the anorexigenic part of pro-opiomelanocortin genes was up-regulated significantly in the HS group. The transcriptome sequencing results can help us understand the regulatory mechanism of feed intake decline in broilers under heat stress at the genetic level.

Combination adjuvant improves influenza virus immunity by downregulation of immune homeostasis genes in lymphocytes

Adjuvants play a central role in enhancing the immunogenicity of otherwise poorly immunogenic vaccine antigens. Combining adjuvants has the potential to enhance vaccine immunogenicity compared with single adjuvants, although the cellular and molecular mechanisms of combination adjuvants are not well understood. Using the influenza virus hemagglutinin H5 antigen, we define the immunological landscape of combining CpG and MPLA (TLR-9 and TLR-4 agonists, respectively) with a squalene nanoemulsion (AddaVax) using immunologic and transcriptomic profiling. Mice immunized and boosted with recombinant H5 in AddaVax, CpG+MPLA, or AddaVax plus CpG+MPLA (IVAX-1) produced comparable levels of neutralizing antibodies and were equally well protected against the H5N1 challenge. However, after challenge with H5N1 virus, H5/IVAX-1-immunized mice had 100- to 300-fold lower virus lung titers than mice receiving H5 in AddaVax or CpG+MPLA separately. Consistent with enhanced viral clearance, unsupervised expression analysis of draining lymph node cells revealed the combination adjuvant IVAX-1 significantly downregulated immune homeostasis genes, and induced higher numbers of antibody-producing plasmablasts than either AddaVax or CpG+MPLA. IVAX-1 was also more effective after single-dose administration than either AddaVax or CpG+MPLA. These data reveal a novel molecular framework for understanding the mechanisms of combination adjuvants, such as IVAX-1, and highlight their potential for the development of more effective vaccines against respiratory viruses.

The Six-Transmembrane Enzyme GDE2 Is Required for the Release of Molecularly Distinct Small Extracellular Vesicles from Neurons

Extracellular vesicles (EVs) are implicated in a multitude of physiological and pathophysiological processes in the nervous system; however, their biogenesis and cargoes are not well defined. Glycerophosphodiester Phosphodiesterase 2 (GDE2 or GDPD5) is a six-transmembrane protein that cleaves the Glycosylphosphatidylinositol (GPI)-anchor that tethers some proteins to the membrane and has important roles in neurodevelopment and disease-relevant pathways of neuronal survival. We show here that GDE2 regulates the number of small EVs (sEVs) released from the cell surface of neurons via its GPI-anchor cleavage activity and contributes to the loading of protein cargo through enzymatic and non-enzymatic mechanisms. Proteomic profiling reveals that GDE2 releases at least two distinct EV populations, one containing GDE2 itself and the other harboring the putative ectosomal markers CD9 and BSG. sEVs released by GDE2 are enriched in cytoskeletal and actin-remodeling proteins, suggesting a potential mechanism for GDE2-dependent EV release. Further, sEV populations released by GDE2 are enriched in proteins responsible for modulating synaptic activity and proteins that are critical for cellular redox homeostasis. These studies identify GDE2 as a novel regulator of molecularly distinct sEV populations from neurons with potential roles in the synaptic and redox pathways required for neuronal function and survival.

A deep learning method for classification of HNSCC and HPV patients using single-cell transcriptomics

Background

Head and Neck Squamous Cell Carcinoma (HNSCC) is the seventh most highly prevalent cancer type worldwide. Early detection of HNSCC is one of the important challenges in managing the treatment of the cancer patients. Existing techniques for detecting HNSCC are costly, expensive, and invasive in nature.

Methods

In this study, we aimed to address this issue by developing classification models using machine learning and deep learning techniques, focusing on single-cell transcriptomics to distinguish between HNSCC and normal samples. Furthermore, we built models to classify HNSCC samples into HPV-positive (HPV+) and HPV-negative (HPV-) categories. In this study, we have used GSE181919 dataset, we have extracted 20 primary cancer (HNSCC) samples, and 9 normal tissues samples. The primary cancer samples contained 13 HPV- and 7 HPV+ samples. The models developed in this study have been trained on 80% of the dataset and validated on the remaining 20%. To develop an efficient model, we performed feature selection using mRMR method to shortlist a small number of genes from a plethora of genes. We also performed Gene Ontology (GO) enrichment analysis on the 100 shortlisted genes.

Results

Artificial Neural Network based model trained on 100 genes outperformed the other classifiers with an AUROC of 0.91 for HNSCC classification for the validation set. The same algorithm achieved an AUROC of 0.83 for the classification of HPV+ and HPV- patients on the validation set. In GO enrichment analysis, it was found that most genes were involved in binding and catalytic activities.

Conclusion

A software package has been developed in Python which allows users to identify HNSCC in patients along with their HPV status. It is available at https://webs.iiitd.edu.in/raghava/hnscpred/.

The Pivotal Function of SLC16A1 and SLC16A1-AS1 in Cancer Progress: Molecular Pathogenesis and Prognosis

More than 300 membranes make up the SLC family of transporters, utilizing an ion gradient or electrochemical potential difference to move their substrates across biological membranes. The SLC16 gene family contains fourteen members. Proton-linked transportation of monocarboxylates can be promoted by the transporters MCT1, which the SLC16A1 gene family encodes. Glycolysis is constitutively up-regulated in cancer cells, and the amount of lactate produced as a result is correlated with prognosis. Further speaking, SLC16A1 plays an essential role in controlling the growth and spread of tumors, according to mounting evidence. Additionally, LncRNAs are the collective term for all genes that produce RNA transcripts longer than 200 nucleotides but do not convert into proteins. It has steadily developed into a hub for research, offering an innovative approach to tumor study as technology related to molecular biology advances. The growing study has uncovered SLC16A1-AS1, an RNA that acts as an antisense to SLC16A1, which is erroneously expressed in various types of cancers. Therefore, we compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. We compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. Relevant studies were retrieved and collected through the PubMed system. After determining SLC16A1 and SLC16A1-AS1 as the research object, we found a close relationship between SLC16A1 and tumorigenesis as well as the influencing factors through the analysis of the research articles. SLC16A1 regulates lactate chemotaxis while uncovering SLC16A1- AS1 as an antisense RNA acting through multiple pathways; they affect the metabolism of tumor cells and have an impact on the prognosis of patients with various cancers.

Development of a prognostic model for glioblastoma multiforme based on the expression levels of efferocytosis-related genes

Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. The microenvironment of GBM is characterized by its highly immunosuppressive nature with infiltration of immunosuppressive cells and the expression levels of cytokines. Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. Efferocytosis plays a noticeable function in the formation of immunosuppressive environment. This study aimed to develop an efferocytosis-related prognostic model for GBM. The bioinformatic methods were utilized to analyze the transcriptomic data of GBM and normal samples. Clinical and RNA-seq data were sourced from TCGA database comprising 167 tumor samples and 5 normal samples, and 167 tumor samples for which survival information was available. Transcriptomic data of 1034 normal samples were collected from the Genotype-Tissue Expression (GTEx) database as a control sample supplement to the TCGA database. In the end, 167 tumor samples and 1039 normal samples were obtained for transcriptome analysis. Efferocytosis-related differentially expressed genes (ERDEGs) were obtained by intersecting 7487 differentially expressed genes (DEGs) between GBM and normal samples along with 1189 hub genes. Functional enrichment analyses revealed that ERDEGs were mainly involved in cytokine-mediated immune responses. Moreover, 9 prognosis-related genes (PRGs) were identified by the least absolute shrinkage and selection operator (LASSO) regression analysis, and a prognostic model was therefore developed. The nomogram combining age and risk score could effectively predict GBM patients' prognosis. GBM patients in the high-risk group had higher immune infiltration, invasion, epithelial-mesenchymal transition, angiogenesis scores and poorer tumor purity. In addition, the high-risk group exhibited higher half maximal inhibitory concentration (IC50) values for temozolomide, carmustine, and vincristine. Expression analysis indicated that PRGs were overexpressed in GBM cells. PDIA4 knockdown reduced efferocytosis in vitro. In summary, the proposed prognostic model for GBM based on efferocytosis-related genes exhibited a robust performance.

Monocarboxylate Transporter-1 (MCT1)-Mediated Lactate Uptake Protects Pancreatic Adenocarcinoma Cells from Oxidative Stress during Glutamine Scarcity Thereby Promoting Resistance against Inhibitors of Glutamine Metabolism

Metabolic compartmentalization of stroma-rich tumors, like pancreatic ductal adenocarcinoma (PDAC), greatly contributes to malignancy. This involves cancer cells importing lactate from the microenvironment (reverse Warburg cells) through monocarboxylate transporter-1 (MCT1) along with substantial phenotype alterations. Here, we report that the reverse Warburg phenotype of PDAC cells compensated for the shortage of glutamine as an essential metabolite for redox homeostasis. Thus, oxidative stress caused by glutamine depletion led to an Nrf2-dependent induction of MCT1 expression in pancreatic T3M4 and A818-6 cells. Moreover, greater MCT1 expression was detected in glutamine-scarce regions within tumor tissues from PDAC patients. MCT1-driven lactate uptake supported the neutralization of reactive oxygen species excessively produced under glutamine shortage and the resulting drop in glutathione levels that were restored by the imported lactate. Consequently, PDAC cells showed greater survival and growth under glutamine depletion when utilizing lactate through MCT1. Likewise, the glutamine uptake inhibitor V9302 and glutaminase-1 inhibitor CB839 induced oxidative stress in PDAC cells, along with cell death and cell cycle arrest that were again compensated by MCT1 upregulation and forced lactate uptake. Our findings show a novel mechanism by which PDAC cells adapt their metabolism to glutamine scarcity and by which they develop resistance against anticancer treatments based on glutamine uptake/metabolism inhibition.

Chemical inhibitors of hexokinase-2 enzyme reduce lactate accumulation, alter glycosylation processing, and produce altered glycoforms in CHO cell cultures

Chinese hamster ovary (CHO) cells, predominant hosts for recombinant biotherapeutics production, generate lactate as a major glycolysis by-product. High lactate levels adversely impact cell growth and productivity. The goal of this study was to reduce lactate in CHO cell cultures by adding chemical inhibitors to hexokinase-2 (HK2), the enzyme catalyzing the conversion of glucose to glucose 6-phosphate, and examine their impact on lactate accumulation, cell growth, protein titers, and N-glycosylation. Five inhibitors of HK2 enzyme at different concentrations were evaluated, of which 2-deoxy- d-glucose (2DG) and 5-thio- d-glucose (5TG) successfully reduced lactate accumulation with only limited impacts on CHO cell growth. Individual 2DG and 5TG supplementation led to a 35%-45% decrease in peak lactate, while their combined supplementation resulted in a 60% decrease in peak lactate. Inhibitor supplementation led to at least 50% decrease in moles of lactate produced per mol of glucose consumed. Recombinant EPO-Fc titers peaked earlier relative to the end of culture duration in supplemented cultures leading to at least 11% and as high as 32% increase in final EPO-Fc titers. Asparagine, pyruvate, and serine consumption rates also increased in the exponential growth phase in 2DG and 5TG treated cultures, thus, rewiring central carbon metabolism due to low glycolytic fluxes. N-glycan analysis of EPO-Fc revealed an increase in high mannose glycans from 5% in control cultures to 25% and 37% in 2DG and 5TG-supplemented cultures, respectively. Inhibitor supplementation also led to a decrease in bi-, tri-, and tetra-antennary structures and up to 50% lower EPO-Fc sialylation. Interestingly, addition of 2DG led to the incorporation of 2-deoxy-hexose (2DH) on EPO-Fc N-glycans and addition of 5TG resulted in the first-ever observed N-glycan incorporation of 5-thio-hexose (5TH). Six percent to 23% of N-glycans included 5TH moieties, most likely 5-thio-mannose and/or 5-thio-galactose and/or possibly 5-thio-N-acetylglucosamine, and 14%-33% of N-glycans included 2DH moieties, most likely 2-deoxy-mannose and/or 2-deoxy-galactose, for cultures treated with different concentrations of 5TG and 2DG, respectively. Our study is the first to evaluate the impact of these glucose analogs on CHO cell growth, protein production, cell metabolism, N-glycosylation processing, and formation of alternative glycoforms.

Targeting monocarboxylate transporters (MCTs) in cancer: How close are we to the clinics?

As a result of metabolic reprogramming, cancer cells display high rates of glycolysis, causing an excess production of lactate along with an increase in extracellular acidity. Proton-linked monocarboxylate transporters (MCTs) are crucial in the maintenance of this metabolic phenotype, by mediating the proton-coupled lactate flux across cell membranes, also contributing to cancer cell pH regulation. Among the proteins codified by the SLC16 gene family, MCT1 and MCT4 isoforms are the most explored in cancers, being overexpressed in many cancer types, from solid tumours to haematological malignancies. Similarly to what occurs in particular physiological settings, MCT1 and MCT4 are able to mediate lactate shuttles among cancer cells, and also between cancer and stromal cells in the tumour microenvironment. This form of metabolic cooperation is responsible for important cancer aggressiveness features, such as cell proliferation, survival, angiogenesis, migration, invasion, metastasis, immune tolerance and therapy resistance. The growing understanding of MCT functions and regulation is offering a new path to the design of novel inhibitors that can be foreseen in clinical practices. This review provides an overview of the role of MCT isoforms in cancer and summarizes the recent advances in their pharmacological targeting, highlighting the potential of new potent and selective MCT1 and/or MCT4 inhibitors in cancer therapeutics, and anticipating its inclusion in clinical practice.

Comprehensive analysis of pan-cancer reveals the potential of SLC16A1 as a prognostic and immunological biomarker

SLC16A1 plays an important role in the development of multiple cancer types. Pan-cancer analysis may have significant impacts on the exploration of the relationship between SLC16A1 gene expression, prognosis and the molecular mechanisms of tumorigenesis. In this study, through the analysis of TCGA and GEO datasets, we explored the expression level and survival prognosis of SLC16A1 in pan-cancer, and further explored the differences in SLC16A1 gene mutation, methylation, and phosphorylation between tumor and normal tissues. In addition, we focused on the biological function of this gene and the relationship between the prognosis and immune infiltration by immune infiltration analysis and enrichment analysis, in order to evaluate the diagnostic and prognostic significance of SLC16A1 in carcinomas. The study found that SLC16A1 was highly expressed in 14 kinds of tumors, and there were statistically significant differences in the prognosis of 9 tumors. The phosphorylation level of S467 increased in OV, RCC, and UCEC. There was a statistically negative correlation between the CD8+ T-cell infiltration level and the SLC16A1 expression in HNSC, LUSC, SARC, TGCT, and KIRC. The cancer-related fibroblasts were positively correlated with SLC16A1 expression in BLCA, BRCA, KIRC, KIRP, PAAD, PCPG, and THCA. The enrichment analysis indicated that the tumorigenesis mechanism of this gene was mainly related to "glycolysis and glucose metabolism synthesis." SLC16A1 was a promising prognostic and immunological biomarker in pan-cancer.

Short Chain Fatty Acid Metabolism in Relation to Gut Microbiota and Genetic Variability

It is widely accepted that the gut microbiota plays a significant role in modulating inflammatory and immune responses of their host. In recent years, the host-microbiota interface has gained relevance in understanding the development of many non-communicable chronic conditions, including cardiovascular disease, cancer, autoimmunity and neurodegeneration. Importantly, dietary fibre (DF) and associated compounds digested by the microbiota and their resulting metabolites, especially short-chain fatty acids (SCFA), were significantly associated with health beneficial effects, such as via proposed anti-inflammatory mechanisms. However, SCFA metabolic pathways are not fully understood. Major steps include production of SCFA by microbiota, uptake in the colonic epithelium, first-pass effects at the liver, followed by biodistribution and metabolism at the host's cellular level. As dietary patterns do not affect all individuals equally, the host genetic makeup may play a role in the metabolic fate of these metabolites, in addition to other factors that might influence the microbiota, such as age, birth through caesarean, medication intake, alcohol and tobacco consumption, pathogen exposure and physical activity. In this article, we review the metabolic pathways of DF, from intake to the intracellular metabolism of fibre-derived products, and identify possible sources of inter-individual variability related to genetic variation. Such variability may be indicative of the phenotypic flexibility in response to diet, and may be predictive of long-term adaptations to dietary factors, including maladaptation and tissue damage, which may develop into disease in individuals with specific predispositions, thus allowing for a better prediction of potential health effects following personalized intervention with DF.

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.

Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.

Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p &lt; 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p &lt; 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.

Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.

Cancer-Associated Stromal Fibroblast-Derived Transcriptomes Predict Poor Clinical Outcomes and Immunosuppression in Colon Cancer

Background: Previous studies revealed that colonic cancer-associated fibroblasts (CAFs) are associated with the modulation of the colon tumor microenvironment (TME). However, identification of key transcriptomes and their correlations with the survival prognosis, immunosuppression, tumor progression, and metastasis in colon cancer remains lacking. Methods: We used the GSE46824, GSE70468, GSE17536, GSE35602, and the cancer genome atlas (TCGA) colon adenocarcinoma (COAD) datasets for this study. We identified the differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, hub genes, and survival-associated genes in colon cancer. Finally, we investigated the correlation of key genes with the survival prognosis, immunosuppression, and metastasis. Results: We identified 246 common DEGs between the GSE46824 and GSE70468 datasets of colonic CAFs, which included 72 upregulated and 174 downregulated genes. The upregulated pathways are mainly involved with cancers and cellular signaling, and downregulated pathways are involved with immune regulation and cellular metabolism. The search tool for the retrieval of interacting genes (STRING)-based analysis identified 15 hub genes and 9 significant clusters in colonic CAFs. The upregulation of CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 and downregulation of FBN2 are correlated with a shorter survival time in colon cancer. The CTHRC1, PDGFC, PDLIM3, and NTM genes are positively correlated with the infiltration of tumor-associated macrophages (TAM), macrophages, M2 macrophages, the regulatory T cells (Tregs), T cell exhaustion, and myeloid-derived suppressor cells (MDSCs), indicating the immunosuppressive roles of these transcriptomes in colon cancer. Moreover, the CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 genes are gradually increased from normal tissue to the tumor and tumor to the metastatic tumor, and FBN2 showed the reverse pattern. Furthermore, the CTHRC1, FBN2, PDGFC, PDLIM3, and NTM genes are positively correlated with the metastatic scores in colon cancer. Then, we revealed that the expression value of CTHRC1, FBN2, PDGFC, PDLIM3, NTM, and SLC16A3 showed the diagnostic efficacy in colonic CAFs. Finally, the expression level of CTHRC1, PDGFC, and NTM genes are consistently altered in colon tumor stroma as well as in the higher CAFs-group of TCGA COAD patients. Conclusion: The identified colonic CAFs-derived key genes are positively correlated with survival prognosis, immunosuppression, tumor progression, and metastasis.

MicroRNAs in the Regulation of Solute Carrier Proteins Behind Xenobiotic and Nutrient Transport in Cells

Altered metabolism, such as aerobic glycolysis or the Warburg effect, has been recognized as characteristics of tumor cells for almost a century. Since then, there is accumulating evidence to demonstrate the metabolic reprogramming of tumor cells, addiction to excessive uptake and metabolism of key nutrients, to support rapid proliferation and invasion under tumor microenvironment. The solute carrier (SLC) superfamily transporters are responsible for influx or efflux of a wide variety of xenobiotic and metabolites that are needed for the cells to function, as well as some medications. To meet the increased demand for nutrients and energy, SLC transporters are frequently dysregulated in cancer cells. The SLCs responsible for the transport of key nutrients for cancer metabolism and energetics, such as glucose and amino acids, are of particular interest for their roles in tumor progression and metastasis. Meanwhile, rewired metabolism is accompanied by the dysregulation of microRNAs (miRNAs or miRs) that are small, noncoding RNAs governing posttranscriptional gene regulation. Studies have shown that many miRNAs directly regulate the expression of specific SLC transporters in normal or diseased cells. Changes of SLC transporter expression and function can subsequently alter the uptake of nutrients or therapeutics. Given the important role for miRNAs in regulating disease progression, there is growing interest in developing miRNA-based therapies, beyond serving as potential diagnostic or prognostic biomarkers. In this article, we discuss how miRNAs regulate the expression of SLC transporters and highlight potential influence on the supply of essential nutrients for cell metabolism and drug exposure toward desired efficacy.

The Emerging Role of MTHFD Family Genes in Regulating the Tumor Immunity of Oral Squamous Cell Carcinoma

Objective

To investigate the function and regulatory mechanisms of methylenetetrahydrofolate dehydrogenase (MTHFD) family genes in oral squamous cell carcinoma (OSCC), especially focus on their regulating role in tumor immunity.

Methods

The publicly available data from the TCGA database were used to investigate the expression pattern and regulatory role of MTHFD family genes in OSCC. More importantly, the involvement of MTHFD family genes in tumor immunity was investigated in terms of immune and stromal cell infiltration in tumor microenvironment, tumor-infiltrating immune cells, and immunomodulatory genes (e.g., immunoinhibitory genes and immunostimulatory genes). Statistical analysis was performed using R software packages and public web servers.

Results

MTHFD family genes were considerably upregulated in OSCC as compared with normal oral tissue. Patients with high MTHFD2 expression presented worse survival outcomes than those with low MTHFD2 expression. Functional enrichment analysis showed that the top 100 positively and negatively correlated genes of the MTHFD family genes were significantly enriched in several KEGG pathways, including cell cycle, spliceosome, DNA replication, and Th17 cell differentiation. As a result of tumor immunity analysis, MTHFD2L expression was found to be negatively related to the Estimate-Stromal-Immune score in OSCC; however, there was no statistical significance between the Estimate-Stromal-Immune score and MTHFD1, MTHFD1L, or MTHFD2 in OSCC. Additionally, MTHFD family genes were found to be significantly positively correlated with tumor-infiltrating immune cells, including Treg and Th17 cells. Moreover, MTHFD family genes were significantly correlated with several immune inhibitory genes such as CD274 and CTLA4 and several immune-stimulatory genes such as CXCL12, CXCR4, and TMIGD2.

Conclusion

Given the expression pattern, prognostic value, biological functions, and involvement in tumor immunity, MTHFD family genes could serve as potential therapeutic biomarkers in targeting tumor immunity in oral cancer.

Joint Transcriptome and Metabolome Analysis Prevails the Biological Mechanisms Underlying the Pro-Survival Fight in In Vitro Heat-Stressed Granulosa Cells

Previous studies reported the physical, transcriptome, and metabolome changes in in vitro acute heat-stressed (38 °C versus 43 °C for 2 h) bovine granulosa cells. Granulosa cells exhibited transient proliferation senescence, oxidative stress, an increased rate of apoptosis, and a decline in steroidogenic activity. In this study, we performed a joint integration and network analysis of metabolomic and transcriptomic data to further narrow down and elucidate the role of differentially expressed genes, important metabolites, and relevant cellular and metabolic pathways in acute heat-stressed granulosa cells. Among the significant (raw p-value < 0.05) metabolic pathways where metabolites and genes converged, this study found vitamin B6 metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism, arginine biosynthesis, tryptophan metabolism, arginine and proline metabolism, histidine metabolism, and glyoxylate and dicarboxylate metabolism. Important significant convergent biological pathways included ABC transporters and protein digestion and absorption, while functional signaling pathways included cAMP, mTOR, and AMPK signaling pathways together with the ovarian steroidogenesis pathway. Among the cancer pathways, the most important pathway was the central carbon metabolism in cancer. Through multiple analysis queries, progesterone, serotonin, citric acid, pyridoxal, L-lysine, succinic acid, L-glutamine, L-leucine, L-threonine, L-tyrosine, vitamin B6, choline, and CYP1B1, MAOB, VEGFA, WNT11, AOX1, ADCY2, ICAM1, PYGM, SLC2A4, SLC16A3, HSD11B2, and NOS2 appeared to be important enriched metabolites and genes, respectively. These genes, metabolites, and metabolic, cellular, and cell signaling pathways comprehensively elucidate the mechanisms underlying the intricate fight between death and survival in acute heat-stressed bovine granulosa cells and essentially help further our understanding (and will help the future quest) of research in this direction.

Identification and Validation of a Prognostic Model Based on Three MVI-Related Genes in Hepatocellular Carcinoma

MVI has significant clinical value for treatment selection and prognosis evaluation in hepatocellular carcinoma (HCC). We aimed to construct a model based on MVI-Related Genes (MVIRGs) for risk assessment and prognosis prediction in patients with HCC. This study utilized various statistical analysis methods for prognostic model construction and validation in the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts, respectively. In addition, immunohistochemistry and qRT-PCR were used to analyze and identify the value of the model in our cohort. After the analyses, 153 differentially expressed MVIRGs were identified, and three key genes were selected to construct a prognostic model. The high-risk group showed significantly lower overall survival (OS), and this trend was observed in all subgroups: different age groups, genders, stages, and grades. Risk score was a risk factor independent of age, gender, stage, and grade. Moreover, the ICGC cohort validated the prognostic value of the model corresponding to the TCGA. In our cohort, qRT-PCR and immunohistochemistry showed that all three genes had higher expression levels in HCC samples than in normal controls. High expression levels of genes and high-risk scores showed significantly lower recurrence-free survival (RFS) and OS, especially in MVI-positive HCC samples. Therefore, the prognostic model constructed by three MVIRGs can reliably predict the RFS and OS of patients with HCC and is valuable for guiding clinical treatment selection and prognostic assessment of HCC.

The Regulatory Role of Neuropeptide Gene Glucagon in Colorectal Cancer: A Comprehensive Bioinformatic Analysis

Background

Colorectal cancer is highly prevalent and causes high global mortality, and glucagon axis has been implicated in colon cancer. The present study is aimed at investigating the regulating mechanisms of glucagon involvement in colorectal cancer.

Methods

Publicly available data from the TCGA database was utilized to explore the expression pattern and regulating role of glucagon (GCG) in colorectal cancer (COADREAD) including colon adenocarcinomas (COAD) and rectum adenocarcinomas (READ). Statistical analyses were performed using the R software packages and public web servers. The expression pattern and prognostic significance of GCG gene in pan-cancer and TCGA-COADREAD data were investigated by performing unpaired and paired sample analyses. The association of GCG expression with clinical characteristics was investigated using logistic regression analysis. Univariate cox regression analysis was performed to test the prognostic value of GCG expression for overall survival in COADREAD patients. GCG-significantly correlated genes were obtained. Biological functions and signaling pathways were identified by performing functional enrichment analysis and Gene Set Enrichment Analysis (GSEA). Additionally, the potential involvement of GCG in tumor immunity was researched by investigating the correlation between GCG expression and 24 tumor infiltrating immune cells.

Results

GCG was found to be significantly downregulated in COADREAD tumor samples compared with healthy control samples. GCG gene was shown to be associated with the prognostic outcomes of COADREAD, whereby its upregulation predicted improved survival outcomes. Functional enrichment analysis showed that the top 100 positively and top 100 negatively GCG-correlated genes were mainly enriched in three signaling pathways including ribosome, nitrogen metabolism, and proximal tubule bicarbonate reclamation. The GSEA showed that GCG-significantly correlated genes were mainly enriched in cell cycle-related pathways (reactome cell cycle, reactome cell cycle mitotic, reactome cell cycle checkpoints, reactome M phase, Reactome G2 M DNA damage checkpoint, and Reactome G2 M checkpoints), neuropeptide ligand receptor interaction, RHO GTPases signaling, WNT signaling, RUNX1 signaling, NOTCH signaling, ESR signaling, HCMV infection, and oxidative stress-related signaling. GCG was positively correlated with Th17 cells, pDC, macrophages, TFH cells, iDC, Tem, B cells, dendritic cells, neutrophils, mast cells, and eosinophils and was negatively associated with NK cells.

Conclusions

GCG dysregulation with high prognostic value in COADREAD was noted. Several tumor progression-related pathways and tumor immune-modulatory cells were linked to GCG expression in COADREAD. Therefore, GCG may be regarded as a potential therapeutic target for treating colorectal cancer.

Monocarboxylate Transporters Are Involved in Extracellular Matrix Remodelling in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a five-year survival rate of <8%. PDAC is characterised by desmoplasia with an abundant extracellular matrix (ECM) rendering current therapies ineffective. Monocarboxylate transporters (MCTs) are key regulators of cellular metabolism and are upregulated in different cancers; however, their role in PDAC desmoplasia is little understood. Here, we investigated MCT and ECM gene expression in primary PDAC patient biopsies using RNA-sequencing data obtained from Gene Expression Omnibus. We generated a hypernetwork model from these data to investigate whether a causal relationship exists between MCTs and ECMs. Our analysis of stromal and epithelial tissues (n = 189) revealed nine differentially expressed MCTs, including the upregulation of SLC16A2/6/10 and the non-coding SLC16A1-AS1, and 502 ECMs, including collagens, laminins, and ECM remodelling enzymes (false discovery rate < 0.05). A causal hypernetwork analysis demonstrated a bidirectional relationship between MCTs and ECMs; four MCT and 255 ECM-related transcripts correlated with 90% of the differentially expressed ECMs (n = 376) and MCTs (n = 7), respectively. The hypernetwork model was robust, established by iterated sampling, direct path analysis, validation by an independent dataset, and random forests. This transcriptomic analysis highlights the role of MCTs in PDAC desmoplasia via associations with ECMs, opening novel treatment pathways to improve patient survival.

Implications of Human Antimicrobial Peptide Defensin Beta-1 in Clinical Oral Squamous Cell Carcinoma Patients via an Integrated Bioinformatics Approach

BACKGROUND

The human antimicrobial peptide defensin beta 1 (DEFB1) has been found to play antimicrobial and anti-inflammatory roles in oral diseases; however, its tumor-regulating role in oral squamous cell carcinoma (OSCC) has not yet been researched by using an integrative bioinformatics approach.

OBJECTIVE

To investigate the regulating mechanisms of the DEFB1 gene in OSCC in terms of its expression patterns, prognostic values, biological functions, and implication for tumor immunity.

METHODS

The DEFB1 gene expression pattern and regulatory involvement in OSCC were investigated using publically accessible data from TCGA database. R software tools and public web servers were utilized to conduct statistical analysis of data from cancer and noncancerous samples.

RESULTS

DEFB1 was found to be significantly downregulated in OSCC tumor samples compared with healthy control oral samples. The DEFB1 gene was found associated with the prognostic outcomes of OSCC, and its upregulation represented better survival outcome. Gene set enrichment analysis (GSEA) results showed that DEFB1-significantly correlated genes were mainly enriched in four signaling pathways mediating the antitumor role of DEFB1 in OSCC, including extracellular matrix-related pathway, RTK/PI3K/AKT/mTOR pathway, keratinization, and cytokine-related pathway. The gene-gene interaction network showed that DEFB1 was closely correlated with several genes, for example, CCR6 (C-C motif chemokine receptor 6), CXCL1 (C-X-C motif chemokine ligand 1), MAP4K2 (mitogen-activated protein kinase kinase kinase kinase 2), PTGER3 (prostaglandin E receptor 3), and MMP7 (matrix metallopeptidase 7). Moreover, DEFB1 was found to be involved in the tumor immunity of OSCC by regulating the function of tumor macrophage cells, mast cells, T cells, and NK cells.

CONCLUSIONS

Given the dysregulation, prognostic value, and tumor progression-related biological pathway alteration, indicating the tumor immune-modulatory role of DEFB1 in OSCC, the DEFB1 gene should be regarded as a potential therapeutic target for treating oral cancer.

Construction and validation of a novel gene signature for predicting the prognosis of osteosarcoma

Osteosarcoma (OS) is the most common type of primary malignant bone tumor. The high-throughput sequencing technology has shown potential abilities to illuminate the pathogenic genes in OS. This study was designed to find a powerful gene signature that can predict clinical outcomes. We selected OS cases with gene expression and survival data in the TARGET-OS dataset and GSE21257 datasets as training cohort and validation cohort, respectively. The univariate Cox regression and Kaplan–Meier analysis were conducted to determine potential prognostic genes from the training cohort. These potential prognostic genes underwent a LASSO regression, which then generated a gene signature. The harvested signature’s predictive ability was further examined by the Kaplan–Meier analysis, Cox analysis, and receiver operating characteristic (ROC curve). More importantly, we listed similar studies in the most recent year and compared theirs with ours. Finally, we performed functional annotation, immune relevant signature correlation identification, and immune infiltrating analysis to better study he functional mechanism of the signature and the immune cells’ roles in the gene signature’s prognosis ability. A seventeen-gene signature (UBE2L3, PLD3, SLC45A4, CLTC, CTNNBIP1, FBXL5, MKL2, SELPLG, C3orf14, WDR53, ZFP90, UHRF2, ARX, CORT, DDX26B, MYC, and SLC16A3) was generated from the LASSO regression. The signature was then confirmed having strong and stable prognostic capacity in all studied cohorts by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GO and KEGG annotations uncovered the specifically mechanism of action related to the gene signature. Six immune signatures, including PRF1, CD8A, HAVCR2, LAG3, CD274, and GZMA were identified associating with our signature. The immune-infiltrating analysis recognized the vital roles of T cells CD8 and Mast cells activated, which potentially support the seventeen-gene signature’s prognosis ability. We identified a robust seventeen-gene signature that can accurately predict OS prognosis. We identified potential immunotherapy targets to the gene signature. The T cells CD8 and Mast cells activated were identified linked with the seventeen-gene signature predictive power.

Feature, Function, and Information of Drug Transporter-Related Databases

With the rapid progress in pharmaceutical experiments and clinical investigations, extensive knowledge of drug transporters (DTs) has accumulated, which is valuable data for the understanding of drug metabolism and disposition. However, such data are largely dispersed in the literature, which hampers its utility and significantly limits its possibility for comprehensive analysis. A variety of databases have, therefore, been constructed to provide DT-related data, and they were reviewed in this study. First, several knowledge bases providing data regarding clinically important drugs and their corresponding transporters were discussed, which constituted the most important resources of DT-centered data. Second, some databases describing the general transporters and their functional families were reviewed. Third, various databases offering transporter information as part of their entire data collection were described. Finally, customized database functions that are available to facilitate DT-related research were discussed. This review provided an overview of the whole collection of DT-related databases, which might facilitate research on precision medicine and rational drug use. SIGNIFICANCE STATEMENT: A collection of well established databases related to drug transporters were comprehensively reviewed, which were organized according to their importance in drug absorption, distribution, metabolism, and excretion research. These databases could collectively contribute to the research on rational drug use.

A Comprehensive Bioinformatic Analysis of NOTCH Pathway Involvement in Stomach Adenocarcinoma

Background

Activation of NOTCH signaling pathways, which are key regulators of multiple cellular functions, has been frequently implicated in cancer pathogenesis, and NOTCH inhibitors have received much recent focus in the context of cancer therapeutics. However, the role and possible involvement of NOTCH pathways in stomach adenocarcinoma (STAD) are unclear. Here, putative regulatory mechanisms and functions of NOTCH pathways in STAD were investigated.

Methods

Publicly available data from the TCGA-STAD database were utilized to explore the involvement of canonical NOTCH pathways in STAD by analyzing RNA expression levels of NOTCH receptors, ligands, and downstream genes. Statistical analysis of the data pertaining to cancer and noncancerous samples was performed using R software packages and public databases/webservers.

Results

Significant differential gene expression between control and STAD samples was noted for all NOTCH receptors (NOTCH1, 2, 3, and 4), the delta-like NOTCH ligands (DLL-3 and 4), and typical downstream genes (HES1 and HEY1). Four genes (NOTCH1, NOTCH2, NOTCH3, and HEY1) presented prognostic values for the STAD outcome in terms of overall survival. Functional enrichment analysis indicated that NOTCH family genes-strongly correlated genes were mainly enriched in several KEGG signaling pathways such as the PI3K-Akt signaling pathway, human papillomavirus infection, focal adhesion, Rap1 signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis (GSEA) results showed that NOTCH family genes-significantly correlated genes were mainly enriched in four signaling pathways, ECM (extracellular matrix), tumor angiogenesis, inflammatory response, and immune regulation.

Conclusions

NOTCH family genes may play an essential role in the progression of STAD by modulating immune cells and mediating ECM synthesis, angiogenesis, focal adhesion, and PI3K-Akt signaling. Multiple NOTCH family genes are valuable candidate biomarkers or therapeutic targets for the management of STAD.

Comprehensive Analysis of Monocarboxylate Transporter 4 (MCT4) expression in breast cancer prognosis and immune infiltration via integrated bioinformatics analysis

Lactate blunts the anticancer immune response in breast cancer (BC). However, little is known about the exact effect of lactate transporters such as monocarboxylate transporter 4 (MCT4) on immunotherapy. In this study, we investigated the expression status and prognostic value of MCT4 in BC through large-scale transcriptome data. Our results showed that MCT4 was overexpressed in BC, particularly in the basal-like molecular subtype. Overexpression of MCT4 was significantly correlated with high BC lesion grade and poor prognosis. Enrichment analysis indicated that the MCT4-related genes were involved in immune- and metabolism-related bioprocesses, such as myeloid leukocyte activation, the adaptive immune system, and catabolic process. We also found that the expression of MCT4 in BC lesions was associated with immune cell infiltration and glycolytic rate-limiting enzymes like pyruvate kinase M2 (PKM2) and hexokinases-3 (HK3). Our observations indicate that MCT4 may play a pivotal role in the maintenance of the tumor immune microenvironment (TIME) through metabolic reprogramming. The enzymes of the glycolysis pathway (MCT4, PKM2, and HK3) may thus serve as new targets to modulate the TIME and enhance immunotherapy efficiency.[Figure: see text].

Prognostic Value of SLC16A3(MCT4) in Lung Adenocarcinoma and Its Clinical Significance

BACKGROUND

Currently, lung adenocarcinoma is the most common form of lung cancer. Although the pathogenesis of lung adenocarcinoma is progressing rapidly, the mortality rate of lung adenocarcinoma is still high. Therefore, it is necessary to search for a new biomarker to guide the prognosis of lung adenocarcinoma.

METHODS

The significance of SLC16A3 in lung adenocarcinoma was investigated by multi-database analysis. GEPIA, UALCAN, TIMER, Cbioportal, and R software were used for research.

RESULTS

Our study found that SLC16A3 was highly expressed in lung adenocarcinoma and was associated with poor prognosis. Further studies have shown that SLC16A3 is involved in some metabolic pathways. Not only that, SLC16A3 is associated with immune cell infiltration and tumor mutation burden (TMB).

CONCLUSION

SLC16A3 has good prognostic significance in lung adenocarcinoma, based on which to explore treatment options may improve the prognosis of patients.

Single-Cell Transcriptomics Reveals the Expression of Aging- and Senescence-Associated Genes in Distinct Cancer Cell Populations

The human aging process is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Despite their potential correlation, the relationship between cancer- and ageing-related transcriptional changes is largely unknown. In this study, we aimed to analyze aging-associated transcriptional patterns in publicly available bulk mRNA-seq and single-cell RNA-seq (scRNA-seq) datasets for chronic myelogenous leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC), and pancreatic ductal adenocarcinoma (PDAC). Indeed, we detected that various aging/senescence-induced genes (ASIGs) were upregulated in malignant diseases compared to healthy control samples. To elucidate the importance of ASIGs during cell development, pseudotime analyses were performed, which revealed a late enrichment of distinct cancer-specific ASIG signatures. Notably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. While only minor correlations were detected between ASIGs and transcriptome-wide changes in PDAC, a high proportion of ASIGs was induced in CML, CRC, HCC, and LC samples. These unique cellular subpopulations could serve as a basis for future studies on the role of aging and senescence in human malignancies.

LINC00035 Transcriptional Regulation of SLC16A3 via CEBPB Affects Glycolysis and Cell Apoptosis in Ovarian Cancer

Objective

Ovarian cancer (OC) represents the most lethal gynecologic malignancy globally. Over the decades, lncRNAs have been considered as study focuses due to their genome-wide expression through multiple mechanisms in which regulation of target gene transcription through interaction with transcription factors or epigenetic proteins is proven. In the present work, we focus on the functional role of LINC00035 in OC and its regulation mechanism on gene expression.

Methods

We collected OC tissues and adjacent tumor-free tissues surgically resected from 67 OC patients. Cultured human OC cell lines SKOV3 and A2780 were assayed for their viability, migration, invasion, apoptosis in vitro using CCK-8 assays, transwell assays, and flow cytometric analysis. OC cell tumorigenesis in vivo was evaluated by mouse xenograft experiments. Glycolysis was evaluated by glucose uptake, lactate release, and ATP production assays. Luciferase activity assay, RNA immunoprecipitation (RIP), and RNA pull-down were performed to confirm the interactions among LINC00035, CEBPB, and SLC16A3.

Results

LINC00035 was upregulated in OC tissues. LINC00035 knockdown was shown to repress SKOV3 and A2780 cell viability, migration, invasion, induce their apoptosis, and reduce glucose uptake, lactate release, and ATP production. LINC00035 could recruit CEBPB into the SLC16A3 promoter region, thus increasing the SLC16A3 transcription. SLC16A3 was upregulated in OC tissues. SLC16A3 knockdown exerted similar effects on SKOV3 and A2780 cells as LINC00035 knockdown. Rescue experiments found SLC16A3 overexpression resisting to LINC00035 knockdown on SKOV3 and A2780 cell viability, migration, invasion, apoptosis, glucose uptake, lactate release, and ATP production. Results also showed LINC00035 knockdown could inhibit OC cell tumorigenesis in vivo.

Conclusion

The study reveals that LINC00035 promotes OC progression by regulating glycolysis and cell apoptosis through CEBPB-mediated transcriptional promotion of SLC16A3.

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Simple Summary

Squamous cell carcinoma (SCC) is the most prevalent type of human cancer worldwide and represents the majority of head and neck tumors. As SCC from aerodigestive or genitourinary tracts share not only common etiology and histological features but also molecular patterns, the major objectives of this study were the establishment of a pan-SCC-related prognostic gene signature by an integrative analysis of multi-omics data and the elucidation of underlying oncogenic pathway activities as potential vulnerabilities for a more efficient and less toxic therapy. Our approach delivers a reliable molecular classifier to identify HNSCC and other SCC patients at higher risk for treatment failure with tumors characterized by a more prominent MAPK activity, who might benefit from a targeted treatment with MEK inhibitors.

Abstract

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

Identification of Immune-Related Genes in Sepsis due to Community-Acquired Pneumonia

Background

Immunosuppression has a key function in sepsis pathogenesis, so it is of great significance to find immune-related markers for the treatment of sepsis.

Methods

Datasets of community-acquired pneumonia (CAP) with sepsis from the ArrayExpress database were extracted. Differentially expressed genes (DEGs) between the CAP group and normal group by Limma package were performed. After calculation of immune score through the ESTIMATE algorithm, the DEGs were selected between the high immune score group and the low immune score group. Enrichment analysis of the intersected DEGs was conducted. Further, the protein-protein interaction (PPI) of the intersected DEGs was drawn by Metascape tools. Related publications of the key DEGs were searched in NCBI PubMed through Biopython models, and RT-qPCR was used to verify the expression of key genes.

Results

360 intersected DEGs (157 upregulated and 203 downregulated) were obtained between the two groups. Meanwhile, the intersected DEGs were enriched in 157 immune-related terms. The PPI of the DEGs was performed, and 8 models were obtained. In sepsis-related research, eight genes were obtained with degree ≥ 10, included in the models.

Conclusion

CXCR3, CCR7, HLA-DMA, and GPR18 might participate in the mechanism of CAP with sepsis.

NUDCD1 knockdown inhibits the proliferation, migration, and invasion of pancreatic cancer via the EMT process

NudC domain containing 1 (NUDCD1) is an oncoprotein frequently activated or upregulated in various human cancers, but its role in pancreatic cancer (PC) remains unknown. Thus, we aimed to determine the function and mechanism of NUDCD1 in PC. We employed Western blot and quantitative real-time polymerase chain reaction to assess NUDCD1 expression in cells and PC tissues. NUDCD1 was knocked down in Patu8988 and PANC-1 cells. We conducted real-time cell analysis, wound healing assay, transwell assay and colony formation assay to evaluate the metastatic and proliferative abilities of PC cells. Western blot was conducted to assess the expression of markers associated with apoptosis and epithelial-mesenchymal transition (EMT). Also, we established a tumor xenograft model to determine the role of NUDCD1 in vivo. NUDCD1 was overexpressed in PC tissues and cells. NUDCD1 knockdown suppressed the invasion, migration, and proliferative abilities of the cells and induced PC cell apoptosis. The specific mechanism of NUDCD1 was related to the modulation of the EMT process. Data obtained from in vivo experiments revealed that NUDCD1 knockdown inhibited the tumor growth, proliferation, and metastasis by modulating the EMT and inducing the apoptosis of PC cells.

TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository

Background

In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis.

Methods

In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis.

Results

Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data.

Conclusion

We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02936-w.

Pan-Cancer Prognostic, Immunity, Stemness, and Anticancer Drug Sensitivity Characterization of N6-Methyladenosine RNA Modification Regulators in Human Cancers

N6-methyladenosine RNA modification plays a significant role in the progression of multiple tumorigenesis. Our study identified the imperative role of m6A regulators in the tumor immune microenvironment, survival, stemness score, and anticancer drug sensitivity of pan-cancer. The Wilcox test was to identify the differential expression between 17 m6A regulators across 33 TCGA cancer types and their normal tissues from UCSC Xena GDC pan-cancer. Survival analysis of m6A-related regulators in 33 TCGA cancer types was identified using the "survival" and "survminer" package. The Spearman correlation test and Pearson correlation test were used to identify the correlation relationship between m6A regulators expression and tumor microenvironment, tumor stem cell score, and drug sensitivity of anticancer drugs. ConsensusPathDB was used for exploring m6A regulators functional enrichment. The 17 (METTL3, WTAP, METTL14, RBM15, RBM15B, VIRMA, HNRNPC, HNRNPA2B1, YTHDC1, ZC3H13, YTHDF1, YTHDC2, YTHDF2, IGF2BP3, IGF2BP1, FTO, and ALKBH5) m6A regulators were differentially expressed in 18 TCGA cancer types and adjacent normal tissues. Correlation analysis indicated that the relationship between the expression of 17 m6A regulators and tumor microenvironment indicated that the higher expression of m6A regulators, the higher the degree of tumor stem cells. The anticancer drug sensitivity analysis indicated that ZC3H13 expression had a positive relationship with anticancer drugs such as selumetinib, dabrafenib, cobimetinib, trametinib, and hypothemycin (p < 0.001). YTHDF2 expression was significantly negatively correlated with the anticancer drug dasatinib (p < 0.001). The pan-cancer immune subtype analysis showed that the 17 m6A regulators were significantly different in immune subtype C1 (wound healing), C3 (inflammatory), C2 (IFN-gamma dominant), C5 (immunological quiet), C4 (lymphocyte depleted), and C6 (TGF-beta dominant) (p < 0.001). Our study provides a comprehensive insight for revealing the significant role of m6A regulators in the tumor immune microenvironment, stemness score, and anticancer drug sensitivity of human cancers.

Development of a prognostic model for hepatocellular carcinoma using genes involved in aerobic respiration

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. Currently, recent risk stratification has only focused on liver function and tumor characteristics. Thus, the purpose of this study was to develop a prognostic model based on genes involved in aerobic respiration. Matched tumor and normal tissues from TCGA and ICGC cohorts were analyzed to identify 15 overlapping differential expressed genes. Cox univariate analysis of the 15 genes in the TCGA cohort revealed they were all associated with disease-specific survival (DSS) in HCC patients. Using LASSO estimation and the optimal value for penalization coefficient lambda 12 genes were selected for the prognostic model, and then HCC patients in the TCGA cohort were dichotomized into low-risk and high-risk groups. Univariate and multivariate Cox analysis demonstrated patients in low-risk group had better survival. Validation of the risk score model with the ICGC cohort produces results consistent with those of the TCGA cohort. In conclusion, this study developed and validated a prognostic model of HCC through a comprehensive analysis of genes involved in aerobic respiration. This model may help develop personalized treatments for patients with HCC.

From Proteomic Mapping to Invasion-Metastasis-Cascade Systemic Biomarkering and Targeted Drugging of Mutant BRAF-Dependent Human Cutaneous Melanomagenesis

Simple Summary

Despite the recent advances in human malignancy therapy, metastasis and chemoresistance remain the principal causes of cancer-derived deaths. Given the fatal forms of cutaneous metastatic melanoma, we herein employed primary (WM115) and metastatic (WM266-4) melanoma cells, both obtained from the same patient, to identify novel biomarkers and therapeutic agents. Through state-of-the-art technologies including deep proteome landscaping, immunofluorescence phenotyping, and drug toxicity screening, we were able to describe new molecular programs, oncogenic drivers, and drug regimens, controlling the invasion-metastasis cascade during BRAF^V600D-dependent melanomagenesis. It proved that proteomic navigation could foster the development of systemic biomarkering and targeted drugging for successful treatment of advanced disease.

Abstract

Melanoma is classified among the most notoriously aggressive human cancers. Despite the recent progress, due to its propensity for metastasis and resistance to therapy, novel biomarkers and oncogenic molecular drivers need to be promptly identified for metastatic melanoma. Hence, by employing nano liquid chromatography-tandem mass spectrometry deep proteomics technology, advanced bioinformatics algorithms, immunofluorescence, western blotting, wound healing protocols, molecular modeling programs, and MTT assays, we comparatively examined the respective proteomic contents of WM115 primary (n = 3955 proteins) and WM266-4 metastatic (n = 6681 proteins) melanoma cells. It proved that WM115 and WM266-4 cells have engaged hybrid epithelial-to-mesenchymal transition/mesenchymal-to-epithelial transition states, with TGF-β controlling their motility in vitro. They are characterized by different signatures of SOX-dependent neural crest-like stemness and distinct architectures of the cytoskeleton network. Multiple signaling pathways have already been activated from the primary melanoma stage, whereas HIF1α, the major hypoxia-inducible factor, can be exclusively observed in metastatic melanoma cells. Invasion-metastasis cascade-specific sub-routines of activated Caspase-3-triggered apoptosis and LC3B-II-dependent constitutive autophagy were also unveiled. Importantly, WM115 and WM266-4 cells exhibited diverse drug response profiles, with epirubicin holding considerable promise as a beneficial drug for metastatic melanoma clinical management. It is the proteome navigation that enables systemic biomarkering and targeted drugging to open new therapeutic windows for advanced disease.

Development of a Prognostic Signature Based on Single-Cell RNA Sequencing Data of Immune Cells in Intrahepatic Cholangiocarcinoma

Analysis of single-cell RNA sequencing (scRNA-seq) data of immune cells from the tumor microenvironment (TME) may identify tumor progression biomarkers. This study was designed to investigate the prognostic value of differentially expressed genes (DEGs) in intrahepatic cholangiocarcinoma (ICC) using scRNA-seq. We downloaded the scRNA-seq data of 33,991 cell samples, including 17,090 ICC cell samples and 16,901 ICC adjacent tissue cell samples regarded as normal cells. scRNA-seq data were processed and classified into 20 clusters. The immune cell clusters were extracted and processed again in the same way, and each type of immune cells was divided into several subclusters. In total, 337 marker genes of macrophages and 427 marker genes of B cells were identified by comparing ICC subclusters with normal subclusters. Finally, 659 DEGs were obtained by merging B cell and macrophage marker genes. ICC sample clinical information and gene expression data were downloaded. A nine-prognosis-related-gene (PRG) signature was established by analyzing the correlation between DEGs and overall survival in ICC. The robustness and validity of the signature were verified. Functional enrichment analysis revealed that the nine PRGs were mainly involved in tumor immune mechanisms. In conclusion, we established a PRG signature based on scRNA-seq data from immune cells of patients with ICC. This PRG signature not only reflects the TME immune status but also provides new biomarkers for ICC prognosis.

SLC16A1-AS1 enhances radiosensitivity and represses cell proliferation and invasion by regulating the miR-301b-3p/CHD5 axis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a common type of human malignancies, leads to increasing incidence and fairly high mortality. An increasing number of studies have verified that long noncoding RNAs (lncRNAs) played key roles in the development of multiple human cancers. As a biomarker, SLC16A1-AS1 has been reported in non-small cell lung cancer (NSCLC) and oral squamous cell carcinoma (OSCC). Thus, we decided to investigate whether SLC16A1-AS1 exerts its biological function in HCC. In this study, we discovered that SLC16A1-AS1 was obviously downregulated in HCC tissues and cells. Overexpression of SLC16A1-AS1 inhibited HCC cell proliferation, invasion, and epithelial-mesenchymal transition (EMT) process as well as promoted cell apoptosis. Moreover, SLC16A1-AS1 was confirmed to enhance the radiosensitivity of HCC cells. Molecular mechanism exploration suggested that SLC16A1-AS1 served as a sponge for miR-301b-3p and CHD5 was the downstream target gene of miR-301b-3p in HCC cells. Rescue assays implied that CHD5 knockdown could recover the effects of SLC16A1-AS1 overexpression on HCC cellular processes. In brief, our study clarified that SLC16A1-AS1 acted as a tumor suppressor in HCC by targeting the miR-301b-3p/CHD5 axis, which may be a promising diagnostic biomarker and provide promising treatment for HCC patients.