Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkers

Roles of K(H)SRP in modulating gene transcription throughout cancer progression: Insights from cellular studies to clinical perspectives

The KH-type splicing regulatory protein (KHSRP), also known as KSRP, is an RNA-binding protein that regulates gene expressions through various mechanisms, including messenger (m)RNA degradation, micro (mi)RNA maturation, and transcriptional activity. KSRP has been implicated in a wide range of physiological and pathological processes, with emerging evidence highlighting its role in modulating diverse aspects of cancer behaviors. In this review, we provide a comprehensive overview of KSRP's clinical relevance and its multifaceted regulatory mechanisms in cancer. Our extensive pan-cancer analysis uncovers associations of KSRP with clinical outcomes and identifies cell cycle progression as a key signaling pathway correlated with KSRP expression. Furthermore, we identify miR-17-5p as critical miRNAs positively correlated with KSRP, and it is associated with poor survival in various cancers. Collectively, this review offers new insights into the potential of KSRP as a target for therapeutic strategies in cancer treatment.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

Clinical significance of nonerythrocytic spectrin Beta 1 (SPTBN1) in human kidney renal clear cell carcinoma and uveal melanoma: a study based on Pan-Cancer Analysis

BACKGROUND

Nonerythrocytic spectrin beta 1 (SPTBN1) is an important cytoskeletal protein that involves in normal cell growth and development via regulating TGFβ/Smad signaling pathway, and is aberrantly expressed in various cancer types. But, the exact role of SPTBN1 in pan-cancer is still unclear. This report aimed to display expression patterns and prognostic landscapes of SPTBN1 in human cancers, and further assess its prognostic/therapeutic value and immunological role in kidney renal carcinoma (KIRC) and uveal melanoma (UVM).

METHODS

We firstly analyzed expression patterns and prognostic landscapes of SPTBN1 in human cancers using various databases and web-based tools. The relationships between SPTBN1 expression and survival/tumor immunity in KIRC and UVM were further investigated via R packages and TIMER 2.0 platform. The therapeutic roles of SPTBN1 in KIRC and UVM were also explored via R software. Following this, the prognostic value and cancer immunological role of SPTBN1 in KIRC and UVM were validated in our cancer patients and GEO database.

RESULTS

Overall, cancer tissue had a lower expression level of SPTBN1 frequently in pan-cancer, compared with those in adjacent nontumor one. SPTBN1 expression often showed a different effect on survival in pan-cancer; upregulation of SPTBN1 was protective to the survival of KIRC individuals, which was contrary from what was found in UVM patients. In KIRC, there were significant negative associations between SPTBN1 expression and pro-tumor immune cell infiltration, including Treg cell, Th2 cell, monocyte and M2-macrophage, and expression of immune modulator genes, such as tumor necrosis factor superfamily member 9 (TNFSF9); while, in UVM, these correlations exhibited opposite patterns. The following survival and expression correlation analysis in our cancer cohorts and GEO database confirmed these previous findings. Moreover, we also found that SPTBN1 was potentially involved in the resistance of immunotherapy in KIRC, and the enhance of anti-cancer targeted treatment in UVM.

CONCLUSIONS

The current study presented compelling evidence that SPTBN1 might be a novel prognostic and therapy-related biomarker in KIRC and UVM, shedding new light on anti-cancer strategy.

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses

Introduction

Lung cancer is one of the most common cancers and a significant cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancer cases. Therefore, it is crucial to identify effective diagnostic and therapeutic methods. In addition, transcription factors are essential for eukaryotic cells to regulate their gene expression, and aberrant expression transcription factors are an important step in the process of oncogenesis in NSCLC.

Methods

Differentially expressed transcription factors between NSCLC and normal tissues by analyzing mRNA profiling from The Cancer Genome Atlas (TCGA) database program were identified. Weighted correlation network analysis (WGCNA) and line plot of least absolute shrinkage and selection operator (LASSO) were performed to find prognosis-related transcription factors. The cellular functions of transcription factors were performed by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay, cell invasion assay in lung cancer cells.

Results

We identified 725 differentially expressed transcription factors between NSCLC and normal tissues. Three highly related modules for survival were discovered, and transcription factors highly associated with survival were obtained by using WGCNA. Then line plot of LASSO was applied to screen transcription factors related to prognosis and build a prognostic model. Consequently, SETDB2, SNAI3, SCML4, and ZNF540 were identified as prognosis-related transcription factors and validated in multiple databases. The low expression of these hub genes in NSCLC was associated with poor prognosis. The deletions of both SETDB2 and SNAI3 were found to promote proliferation, invasion, and stemness in lung cancer cells. Furthermore, there were significant differences in the proportions of 22 immune cells between the high- and low-score groups.

Discussion

Therefore, our study identified the transcription factors involved in regulating NSCLC, and we constructed a panel for the prediction of prognosis and immune infiltration to inform the clinical application of transcription factor analysis in the prevention and treatment of NSCLC.

Phosphoproteomics data-driven signalling network inference: Does it work?

The advent of global phosphoproteome profiling has led to wide phosphosite coverage and therefore the opportunity to predict kinase-substrate associations from these datasets. However, the regulatory kinase is unknown for most substrates, due to biased and incomplete database annotations. In this study we compare the performance of six pairwise measures to predict kinase-substrate associations using a data driven approach on publicly available time resolved and perturbation mass spectrometry-based phosphoproteome data. First, we validated the performance of these measures using as a reference both a literature-based phosphosite-specific protein interaction network and a predicted kinase-substrate (KS) interactions set. The overall performance in predicting kinase-substrate associations using pairwise measures across both these reference sets was poor. To expand into the wider interactome space, we applied the approach on a network comprising pairs of substrates regulated by the same kinase (substrate-substrate associations) but found the performance to be equally poor. However, the addition of a sequence similarity filter for substrate-substrate associations led to a significant boost in performance. Our findings imply that the use of a filter to reduce the search space, such as a sequence similarity filter, can be used prior to the application of network inference methods to reduce noise and boost the signal. We also find that the current gold standard for reference sets is not adequate for evaluation as it is limited and context-agnostic. Therefore, there is a need for additional evaluation methods that have increased coverage and take into consideration the context-specific nature of kinase-substrate associations.

Nucleoside transporters and immunosuppressive adenosine signaling in the tumor microenvironment: Potential therapeutic opportunities

Adenosine compartmentalization has a profound impact on immune cell function by regulating adenosine localization and, therefore, extracellular signaling capabilities, which suppresses immune cell function in the tumor microenvironment. Nucleoside transporters, responsible for the translocation and cellular compartmentalization of hydrophilic adenosine, represent an understudied yet crucial component of adenosine disposition in the tumor microenvironment. In this review article, we will summarize what is known regarding nucleoside transporter's function within the purinome in relation to currently devised points of intervention (i.e., ectonucleotidases, adenosine receptors) for cancer immunotherapy, alterations in nucleoside transporter expression reported in cancer, and potential avenues for targeting of nucleoside transporters for the desired modulation of adenosine compartmentalization and action. Further, we put forward that nucleoside transporters are an unexplored therapeutic opportunity, and modulation of nucleoside transport processes could attenuate the pathogenic buildup of immunosuppressive adenosine in solid tumors, particularly those enriched with nucleoside transport proteins.

Identification of Genes Related to Hair Follicle Cycle Development in Inner Mongolia Cashmere Goat by WGCNA

Cashmere goat from Inner Mongolia is an excellent local breed in China, and the related cashmere product is a kind of precious textile raw material with high price. Cashmere is generated from secondary hair follicles, which has obvious annual periodicity and includes three different stages: anagen, catagen, and telogen. Therefore, we investigated skin transcriptome data for 12 months using weighted gene co-expression network analysis (WGCNA) to explore essential modules, pathways, and genes responsible for the periodic growth and development of secondary hair follicles. A total of 17 co-expression modules were discovered by WGCNA, and there is a strong correlation between steelblue module and month (0.65, p = 3E−09), anagen (0.52, p = 1E−05), telogen (−0.6, p = 8E−08). Gene expression was generally high during late anagen to catagen (June to December), while expression was downregulated from telogen to early anagen (January–May), which is similar to the growth rule of hair follicle cycle. KEGG pathway enrichment analyses of the genes of steelblue module indicated that genes are mainly enriched in Cell cycle, Wnt signaling pathway, p53 signaling pathway and other important signal pathways. These genes were also significantly enriched in GO functional annotation of the cell cycle, microtubule movement, microtubule binding, tubulin binding, and so on. Ten genes (WIF1, WNT11, BAMBI, FZD10, NKD1, LEF1, CCND3, E2F3, CDC6, and CDC25A) were selected from these modules, and further identified as candidate biomarkers to regulate periodic development of hair follicles using qRT-PCR. The Wnt signaling pathway and Cell cycle play an important role in the periodic development of hair follicles. Ten genes were identified as essential functional molecules related to periodic development of hair follicle. These findings laid a foundation for understanding molecular mechanisms in biological functions such as hair follicle development and hair growth in cashmere goats.

Annotation and functional characterization of long noncoding RNAs deregulated in pancreatic adenocarcinoma

PURPOSE

Transcriptome analysis of pancreatic ductal adenocarcinoma (PDAC) has been useful to identify gene expression changes that sustain malignant phenotypes. Yet, most studies examined only tumor tissues and focused on protein-coding genes, leaving long non-coding RNAs (lncRNAs) largely underexplored.

METHODS

We generated total RNA-Seq data from patient-matched tumor and nonmalignant pancreatic tissues and implemented a computational pipeline to survey known and novel lncRNAs. siRNA-mediated knockdown in tumor cell lines was performed to assess the contribution of PDAC-associated lncRNAs to malignant phenotypes. Gene co-expression network and functional enrichment analyses were used to assign deregulated lncRNAs to biological processes and molecular pathways.

RESULTS

We detected 9,032 GENCODE lncRNAs as well as 523 unannotated lncRNAs, including transcripts significantly associated with patient outcome. Aberrant expression of a subset of novel and known lncRNAs was confirmed in patient samples and cell lines. siRNA-mediated knockdown of a subset of these lncRNAs (LINC01559, LINC01133, CCAT1, LINC00920 and UCA1) reduced cell proliferation, migration and invasion. Gene co-expression network analysis associated PDAC-deregulated lncRNAs with diverse biological processes, such as cell adhesion, protein glycosylation and DNA repair. Furthermore, UCA1 knockdown was shown to specifically deregulate co-expressed genes involved in DNA repair and to negatively impact DNA repair following damage induced by ionizing radiation.

CONCLUSIONS

Our study expands the repertoire of lncRNAs deregulated in PDAC, thereby revealing novel candidate biomarkers for patient risk stratification. It also provides a roadmap for functional assays aimed to characterize novel mechanisms of action of lncRNAs in pancreatic cancer, which could be explored for therapeutic development.

Exploring Human Milk Dynamics: Interindividual Variation in Milk Proteome, Peptidome, and Metabolome

Human milk is a dynamic biofluid, and its detailed composition receives increasing attention. While most studies focus on changes over time or differences between maternal characteristics, interindividual variation receives little attention. Nevertheless, a comprehensive insight into this can help interpret human milk studies and help human milk banks provide targeted milk for recipients. This study aimed to map interindividual variation in the human milk proteome, peptidome, and metabolome and to investigate possible explanations for this variation. A set of 286 milk samples was collected from 29 mothers in the third month postpartum. Samples were pooled per mother, and proteins, peptides, and metabolites were analyzed. A substantial coefficient of variation (>100%) was observed for 4.6% and 36.2% of the proteins and peptides, respectively. In addition, using weighted correlation network analysis (WGCNA), 5 protein and 11 peptide clusters were obtained, showing distinct characteristics. With this, several associations were found between the different data sets and with specific sample characteristics. This study provides insight into the dynamics of human milk protein, peptide, and metabolite composition. In addition, it will support future studies that evaluate the effect size of a parameter of interest by enabling a comparison with natural variability.

Identification of PYGL as a key prognostic gene of glioma by integrated bioinformatics analysis

Aim: PYGL has been reported to have carcinogenic effects in a variety of tumors. This study is the first to reveal the relationship between PYGL and the prognosis of glioma. Materials & methods: Analyzing the Chinese Glioma Genome Atlas database, the authors revealed the expression status and prognostic value of PYGL in gliomas and used RT-qPCR to verify PYGL expression again. Subsequently, they used Gene Set Enrichment Analysis to explore the biological pathways that PYGL may participate in. The authors also used the tumor immune estimation resource database to explore the relationship between PYGL and tumor immune cells. Results: PYGL is involved in the malignant progression of glioma. Conclusions: PYGL can be used as a new biomarker and molecular target for evaluating the prognosis and immunotherapy of glioma.

NONMMUT140591.1 may serve as a ceRNA to regulate Gata5 in UT-B knockout-induced cardiac conduction block

We intended to explore the potential molecular mechanisms underlying the cardiac conduction block inducted by urea transporter (UT)-B deletion at the transcriptome level. The heart tissues were harvested from UT-B null mice and age-matched wild-type mice for lncRNA sequencing analysis. Based on the sequencing data, the differentially expressed mRNAs (DEMs) and lncRNAs (DELs) between UT-B knockout and control groups were identified, followed by function analysis and mRNA-lncRNA co-expression analysis. The miRNAs were predicted, and then the competing endogenous RNA (ceRNA) network was constructed. UT-B deletion results in the aberrant expression of 588 lncRNAs and 194 mRNAs. These DEMs were significantly enriched in the inflammation-related pathway. A lncRNA-mRNA co-expression network and a ceRNA network were constructed on the basis of the DEMs and DELs. The complement 7 (C7)-NONMMUT137216.1 co-expression pair had the highest correlation coefficient in the co-expression network. NONMMUT140591.1 had the highest degree in the ceRNA network and was involved in the ceRNA of NONMMUT140591.1-mmu-miR-298-5p-Gata5 (GATA binding protein 5). UT-B deletion may promote cardiac conduction block via inflammatory process. The ceRNA NONMMUT140591.1-mmu-miR-298-5p-Gata5 may be a potential molecular mechanism of UT-B knockout-induced cardiac conduction block.

Placental Gene Co-expression Network for Maternal Plasma Lipids Revealed Enrichment of Inflammatory Response Pathways

Maternal dyslipidemia during pregnancy has been associated with suboptimal fetal growth and increased cardiometabolic diseasse risk in offspring. Altered placental function driven by placental gene expression is a hypothesized mechanism underlying these associations. We tested the relationship between maternal plasma lipid concentrations and placental gene expression. Among 64 pregnant women from the NICHD Fetal Growth Studies–Singleton cohort with maternal first trimester plasma lipids we extracted RNA-Seq on placental samples obtained at birth. Placental gene co-expression networks were validated by regulatory network analysis that integrated transcription factors and gene expression, and genome-wide transcriptome analysis. Network analysis detected 24 gene co-expression modules in placenta, of which one module was correlated with total cholesterol (r = 0.27, P-value = 0.03) and LDL-C (r = 0.31, P-value = 0.01). Genes in the module (n = 39 genes) were enriched in inflammatory response pathways. Out of the 39 genes in the module, three known lipid-related genes (MPO, PGLYRP1 and LTF) and MAGEC2 were validated by the regulatory network analysis, and one known lipid-related gene (ALX4) and two germ-cell development-related genes (MAGEC2 and LUZP4) were validated by genome-wide transcriptome analysis. Placental gene expression signatures associated with unfavorable maternal lipid concentrations may be potential pathways underlying later life offspring cardiometabolic traits.

Clinical Trial Registration:ClinicalTrials.gov, identifier NCT00912132.

k-core genes underpin structural features of breast cancer

Gene co-expression networks (GCNs) have been developed as relevant analytical tools for the study of the gene expression patterns behind complex phenotypes. Determining the association between structure and function in GCNs is a current challenge in biomedical research. Several structural differences between GCNs of breast cancer and healthy phenotypes have been reported. In a previous study, using co-expression multilayer networks, we have shown that there are abrupt differences in the connectivity patterns of the GCN of basal-like breast cancer between top co-expressed gene-pairs and the remaining gene-pairs. Here, we compared the top-100,000 interactions networks for the four breast cancer phenotypes (Luminal-A, Luminal-B, Her2+ and Basal), in terms of structural properties. For this purpose, we used the graph-theoretical k-core of a network (maximal sub-network with nodes of degree at least k). We developed a comprehensive analysis of the network k-core ([Formula: see text]) structures in cancer, and its relationship with biological functions. We found that in the Top-100,000-edges networks, the majority of interactions in breast cancer networks are intra-chromosome, meanwhile inter-chromosome interactions serve as connecting bridges between clusters. Moreover, core genes in the healthy network are strongly associated with processes such as metabolism and cell cycle. In breast cancer, only the core of Luminal A is related to those processes, and genes in its core are over-expressed. The intersection of the core nodes in all subtypes of cancer is composed only by genes in the chr8q24.3 region. This region has been observed to be highly amplified in several cancers before, and its appearance in the intersection of the four breast cancer k-cores, may suggest that local co-expression is a conserved phenomenon in cancer. Considering the many intricacies associated with these phenomena and the vast amount of research in epigenomic regulation which is currently undergoing, there is a need for further research on the epigenomic effects on the structure and function of gene co-expression networks in cancer.

High PYGL Expression Predicts Poor Prognosis in Human Gliomas

Background: PYGL has been reported as a glycogen degradation-related gene, which is up-regulated in many tumors. This study was designed to investigate the predictive value of high PYGL expression in patients with gliomas through bioinformatics analysis of the gene transcriptome and the single-cell sequencing data. Methods: The gene transcriptome data of 595 glioma patients from the TCGA database and the single-cell RNA sequencing data of 7,930 GBM cells from the GEO database were included in the study. Differential analysis was used to find the distribution of expression of PYGL in different groups of glioma patients. OS analysis was used to assess the influence of the high expression of PYGL on the prognosis of patients. The reliability of its prediction was evaluated by the AUC of ROC and the C-index. The GSEA be used to reveal potential mechanisms. The single-cell analysis was used to observe the high expression of PYGL in different cell groups to further analyze the mechanism of its prediction. Results: Differential analysis identified the expression level of PYGL is positively associated with glioma malignancy. OS analysis and Cox regression analyses showed high expression of PYGL was an independent factor for poor prognosis of gliomas (p < 0.05). The AUC values were 0.838 (1-year ROC), 0.864 (3-year ROC) and 0.833 (5-year ROC). The C index was 0.81. The GSEA showed that gene sets related to MTORC1 signaling, glycolysis, hypoxia, PI3K/AKT/mTOR signaling, KRAS signaling up and angiogenesis were differentially enriched in the high PYGL expression phenotype. The single-cell sequencing data analysis showed TAMs and malignant cells in GBM tissues expressed a high level of PYGL. Conclusion: The high expression of PYGL is an independent predictor of poor prognosis in patients with glioma.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

ECM2 and GLT8D2 in human pulmonary artery hypertension: fruits from weighted gene co-expression network analysis

Background

Pulmonary artery hypertension (PAH) is an incurable disease with a high mortality rate. Current medications ameliorate symptoms but cannot target adverse vascular remodeling. New therapeutic strategies for PAH need to be established.

Methods

Using the weighted gene coexpression network analysis (WGCNA) algorithm, we constructed a coexpression network of dataset GSE117261 from the Gene Expression Omnibus (GEO) database. Key modules were identified by the relationship between module eigengenes and clinical traits. Hub genes were screened out based on gene significance (GS), module membership (MM), and mean pulmonary artery pressure (mPAP). External validations were conducted in GSE48149 and GSE113439. Functional enrichment and immune cell infiltration were analyzed using Metascape and CIBERSORTx.

Results

The WGCNA analysis revealed 13 coexpression modules. The pink module had the highest correlation with PAH in terms of module eigengene (r=0.79; P=2e-18) and module significance (MS =0.43). Functional enrichment indicated genes in the pink module contributed to the immune system process and extracellular matrix (ECM). In the pink module, ECM2 (GS =0.65, MM =0.86, ρ=0.407, P=0.0019) and GLT8D2 (GS =0.63, MM =0.85, ρ=0.443, P=0.006) were identified as hub genes. For immune cells infiltration in PAH lung tissue, hub genes were positively correlated with M2 macrophages and resting mast cells, and were negatively correlated with monocytes, neutrophils, and CD4-naïve T cells.

Conclusions

Our research identified 2 hub genes ECM2 and GLT8D2 related to PAH. The functions of these hub genes were involved in the immune process and ECM, indicating that they might serve as candidate therapeutic targets for PAH.

βII spectrin (SPTBN1): biological function and clinical potential in cancer and other diseases

βII spectrin, the most common isoform of non-erythrocyte spectrin, is a cytoskeleton protein present in all nucleated cells. Interestingly, βII spectrin is essential for the development of various organs such as nerve, epithelium, inner ear, liver and heart. The functions of βII spectrin include not only establishing and maintaining the cell structure but also regulating a variety of cellular functions, such as cell apoptosis, cell adhesion, cell spreading and cell cycle regulation. Notably, βII spectrin dysfunction is associated with embryonic lethality and the DNA damage response. More recently, the detection of altered βII spectrin expression in tumors indicated that βII spectrin might be involved in the development and progression of cancer. Its mutations and disorders could result in developmental disabilities and various diseases. The versatile roles of βII spectrin in disease have been examined in an increasing number of studies; nonetheless, the exact mechanisms of βII spectrin are still poorly understood. Thus, we summarize the structural features and biological roles of βII spectrin and discuss its molecular mechanisms and functions in development, homeostasis, regeneration and differentiation. This review highlight the potential effects of βII spectrin dysfunction in cancer and other diseases, outstanding questions for the future investigation of therapeutic targets. The investigation of the regulatory mechanism of βII spectrin signal inactivation and recovery may bring hope for future therapy of related diseases.

Omics Analysis of Educated Platelets in Cancer and Benign Disease of the Pancreas

Pancreatic ductal adenocarcinoma (PDAC) is traditionally associated with thrombocytosis/hypercoagulation and novel insights on platelet-PDAC "dangerous liaisons" are warranted. Here we performed an integrative omics study investigating the biological processes of mRNAs and expressed miRNAs, as well as proteins in PDAC blood platelets, using benign disease as a reference for inflammatory noise. Gene ontology mining revealed enrichment of RNA splicing, mRNA processing and translation initiation in miRNAs and proteins but depletion in RNA transcripts. Remarkably, correlation analyses revealed a negative regulation on SPARC transcription by isomiRs involved in cancer signaling, suggesting a specific "education" in PDAC platelets. Platelets of benign patients were enriched for non-templated additions of G nucleotides (#ntaG) miRNAs, while PDAC presented length variation on 3' (lv3p) as the most frequent modification on miRNAs. Additionally, we provided an actionable repertoire of PDAC and benign platelet-ome to be exploited for future studies. In conclusion, our data show that platelets change their biological repertoire in patients with PDAC, through dysregulation of miRNAs and splicing factors, supporting the presence of de novo protein machinery that can "educate" the platelet. These novel findings could be further exploited for innovative liquid biopsies platforms as well as possible therapeutic targets.

"Open Sesame?": Biomarker Status of the Human Equilibrative Nucleoside Transporter-1 and Molecular Mechanisms Influencing its Expression and Activity in the Uptake and Cytotoxicity of Gemcitabine in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive tumor characterized by early invasiveness, rapid progression and resistance to treatment. For more than twenty years, gemcitabine has been the main therapy for PDAC both in the palliative and adjuvant setting. After the introduction of FOLFIRINOX as an upfront treatment for metastatic disease, gemcitabine is still commonly used in combination with nab-paclitaxel as an alternative first-line regimen, as well as a monotherapy in elderly patients unfit for combination chemotherapy. As a hydrophilic nucleoside analogue, gemcitabine requires nucleoside transporters to permeate the plasma membrane, and a major role in the uptake of this drug is played by human equilibrative nucleoside transporter 1 (hENT-1). Several studies have proposed hENT-1 as a biomarker for gemcitabine efficacy in PDAC. A recent comprehensive multimodal analysis of hENT-1 status evaluated its predictive role by both immunohistochemistry (with five different antibodies), and quantitative-PCR, supporting the use of the 10D7G2 antibody. High hENT-1 levels observed with this antibody were associated with prolonged disease-free status and overall-survival in patients receiving gemcitabine adjuvant chemotherapy. This commentary aims to critically discuss this analysis and lists molecular factors influencing hENT-1 expression. Improved knowledge on these factors should help the identification of subgroups of patients who may benefit from specific therapies and overcome the limitations of traditional biomarker studies.