PGM5 is a promising biomarker and may predict the prognosis of colorectal cancer patients

Phosphoglucomutase 5 gene transcripts are expressed by the human placenta and differentially regulated in placental dysfunction

The placenta plays an essential role facilitating nutrient, gas and waste exchange between the maternal and fetal systems for optimal fetal growth. When placental development is impaired and the placenta dysfunctional, serious pregnancy complications such as fetal growth restriction and preeclampsia may arise. Previously, phosphoglucomutase-5 (PGM5) transcripts were found to be highly elevated in the blood of patients whose pregnancies were complicated by fetal growth restriction and preeclampsia. As both conditions feature placental insufficiency, here we aimed to characterise PGM5 levels in the healthy and dysfunctional placenta. PGM5 expression was detectable in all placental samples across gestation, in cases of preterm preeclampsia, fetal growth restriction and controls. PGM5 mRNA expression was significantly downregulated in the pathological placentas compared to controls, but PGM5 protein production was not dysregulated. Isolated cytotrophoblast and placental explant tissue exposed to hypoxia (modelling placental dysfunction) demonstrated significantly increased PGM5 expression, but again did not change protein levels. Silencing PGM5 expression under hypoxic conditions in primary cytotrophoblast did not alter anti-angiogenic sFLT-1 secretion but increased expression of multiple genes associated with cell growth, apoptosis and oxidative stress, whilst also increasing cell viability. Expression of PGM5 in all placental samples assessed suggests that PGM5 has functions in the placenta. However, further investigation could be performed to explore the discrepancies in protein and mRNA expression, as well as the precise function of PGM5 in the placenta, and whether altered PGM5 levels may be important for placental development.

Genomic analysis of surgical patients to identify patients at risk for postoperative sepsis and surgical site infection

BACKGROUND

Early and accurate diagnosis of sepsis and the ensuing organ dysfunction remain a challenge in the postoperative setting. Susceptibility to infections, as well as the subsequent immunological response, are driven to some extent by the genetic predisposition of the patient. The purpose of this study was to identify novel genetic variants associated with postoperative sepsis (POS) and surgical site infections (SSIs).

METHODS

We conducted genome-wide association studies for POS and SSIs in the Electronic Medical Records and Genomics Network database. All patients with surgical and genomic information in Electronic Medical Records and Genomics were identified. Patients with a new diagnosis of sepsis/SSIs after surgery were classified as cases, and those without as controls. Analyses were performed using PLINK 2.0's logistic regression function. A p value of <5 × 10 -8 was considered statistically significant.

RESULTS

A total of 59,755 participants were included in the analysis. Genetic regions on chromosomes 9 and 14 reached statistical significance for POS ( p < 5 × 10 -8 ). The most significant single-nucleotide polymorphisms (SNPs) were rs9413988 ( p = 5.59 × 10 -12 ) on chromosome 9 and rs35407594 ( p = 1.43 × 10 -10 ) on chromosome 14. The rs9413988 region is downstream to the phosphoglucomutase 5 pseudogene ( PGM5P2 ) and Zn-regulated GTPase metalloprotein activator 1F ( ZNGF1 ) and likely plays a role in transcription regulation, while rs35407594 corresponds to the olfactory receptor gene family, OR11 . Similar SNPs were also associated with SSIs.

CONCLUSION

We have identified two genetic regions containing SNPs associated with POS and SSIs. These findings provide new avenues for investigation, which may help identify and guide point-of-care management for at-risk patients.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Cell Senescence-Related Genes as Biomarkers for Prognosis and Immunotherapeutic Response in Colon Cancer

Colon adenocarcinoma (COAD) stands out as the most prevalent malignancy diagnosed within the gastrointestinal tract, bearing substantial incidence and mortality rates. The processes of ageing and senescence intricately intertwine with tumorigenesis and immune regulation, concurrently exerting influence on the remodelling of the tumor microenvironment (TME). This phenomenon, in turn, significantly impacts the efficacy of immunotherapeutic interventions. Despite this awareness, the comprehensive understanding of the intricate interplay between cellular senescence and TME in the context of COAD remains elusive. Further inquiry is imperative to comprehensively gauge the relevance of cellular senescence-related genes (CSGs) in the realms of immune infiltration and the prognostication of COAD. Differentially expressed cell senescence-related genes (DE-CSGs) within COAD tumors and normal specimens were discerned through analysis of the TCGA-COAD dataset. Leveraging univariate, LASSO, and multivariate Cox regression analyses, we formulated a prognostic risk signature. Subsequent validation utilised two independent GEO datasets. Furthermore, a nomogram was devised to gauge the prognostic significance of this signature. Additionally, the immune landscape of the Cell Senescence-related Signature (CSS) was characterised using CIBERSORT and TIMER algorithms. The expression levels of CSGs were quantified through RT-PCR in COAD specimens. Drawing upon mRNA expression profiles of 191 DE-CSGs, we successfully established a 9-gene CSS, demonstrating its autonomy as a prognostic determinant for COAD patients. Those assigned high-risk scores exhibited an immunosuppressive phenotype, marked by elevated proportions of resting CD4+memory T cells and macrophages M0, correlating with diminished overall survival. Subsequent analyses uncovered that the amalgamation of CSS with the expression profiles of immune checkpoint key genes effectively predicted patient prognosis. Furthermore, patients with low-risk scores demonstrated a potential association with more favourable therapeutic outcomes in the context of immunotherapy. This study has culminated in the development of a prognostic risk signature grounded in cell senescence-related genes for COAD. We posit that the CSS plays a regulatory role in immune infiltration, emerging as a robust biomarker for prognosis and a predictive indicator for immunotherapeutic responsiveness within the COAD landscape.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

Label-free proteomic analysis and functional analysis in patients with intrauterine adhesion

Intrauterine adhesion (IUA) is one of the principal causes of secondary infertility in women of reproductive age, which seriously affects female reproductive function and quality of life. In recent years, the incidence of IUA has been increasing year by year, but its pathological mechanism has not yet been clarified. This study intended to reveal the pathogenesis of IUA and find new therapeutic targets by analyzing the proteomic differences between intrauterine adhesion tissues and normal human endometrial tissues. In the label-free quantitative proteomics, we identified 789 up-regulated differentially expressed proteins (DEPs) and 539 down-regulated DEPs. These DEPs were further analyzed by Gene Ontology (GO) annotation and enrichment analysis, Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis to preliminarily clarify the biomarkers involved in the pathogenesis of the IUA. The DEPs were further verified by parallel reaction monitoring (PRM) to confirm the results of proteomics. Finally, 7 target proteins may be candidates for treatment and elucidating the pathophysiology of IUA. SIGNIFICANCE: IUA is a fertility complication, which has increasing incidence recently. Until now, only a little research paid attention to the proteomic changes of IUA. This is the first study focused on the comparative analysis of endometrial tissue between IUA patients and normal women. We found 7 key proteins that may become the potential biomarkers of IUA.

Meta-analysis of the effect of PGM on survival prognosis of tumor patients

Objective

A systematic evaluation of the impact of phosphoglucose translocase PGM on the survival prognosis of tumor patients was conducted to understand its impact on tumors so as to improve the quality of survival and to find effective therapeutic targets for tumor patients.

Methods

The following were searched in the databases China National Knowledge Infrastructure (CNKI), Wanfang, Wipu, PubMed, EMBASE, ScienceDirect, Web of Science, and Cochrane Library: "PGM1", "PGM2", "PGM3", "PGM4", and "PGM5" as Chinese keywords and "PGM1", "PGM2", "PGM3", "PGM4", "PGM5", "PGM1 cancer", "PGM2 cancer", "PGM3 cancer", "PGM4 cancer", "PGM5 cancer", and "phosphoglucomutase". Relevant studies published from the database establishment to April 2022 were collected. Studies that met the inclusion criteria were extracted and evaluated for quality with reference to the Cochrane 5.1.0 systematic evaluation method, and quality assessment was performed using RevMan 5.3 software.

Results

The final results of nine articles and 10 studies with a total of 3,806 patients were included, including 272 patients in the PGM1 group, 541 patients in the PGM2 group, 1,775 patients in the PGM3 group, and 1,585 patients in the PGM5 group. Results of the meta-analysis: after determining the results of the nine articles, it was found that the difference was statistically significant with a p-value <0.05 (hazard ratio (HR) = 0.89, 95% CI 0.69-1.09, p = 0.000). To find the sources of heterogeneity, the remaining eight papers were tested after removing the highly sensitive literature, and the results showed I² = 26.5%, p < 0.001, a statistically significant difference. The HR for high expression of PGM1 and PGM2 and PGM5 was <1, while the HR for high expression of PGM3 was >1.

Conclusion

Although PGM1, PGM2, PGM3, and PGM5 are enzymes of the same family, their effects on tumors are different. High expression of PGM1, PGM2, and PGM5 can effectively prolong the overall survival of patients. In contrast, high expression of PGM3 reduced the overall survival of patients. This study of PGM family enzymes can assist in subsequent tumor diagnosis, treatment, and prognostic assessment.

Pervasive conditional selection of driver mutations and modular epistasis networks in cancer

Cancer driver mutations often display mutual exclusion or co-occurrence, underscoring the key role of epistasis in carcinogenesis. However, estimating the magnitude of epistasis and quantifying its effect on tumor evolution remains a challenge. We develop a method (Coselens) to quantify conditional selection on the excess of nonsynonymous substitutions in cancer genes. Coselens infers the number of drivers per gene in different partitions of a cancer genomics dataset using covariance-based mutation models and determines whether coding mutations in a gene affect selection for drivers in any other gene. Using Coselens, we identify 296 conditionally selected gene pairs across 16 cancer types in the TCGA dataset. Conditional selection affects 25%-50% of driver substitutions in tumors with >2 drivers. Conditionally co-selected genes form modular networks, whose structures challenge the traditional interpretation of within-pathway mutual exclusivity and across-pathway synergy, suggesting a more complex scenario where gene-specific across-pathway epistasis shapes differentiated cancer subtypes.

Human Blood Serum Inhibits Ductal Carcinoma Cells BT474 Growth and Modulates Effect of HER2 Inhibition

Trastuzumab, a HER2-targeted antibody, is widely used for targeted therapy of HER2-positive breast cancer (BC) patients; yet, not all of them respond to this treatment. We investigated here whether trastuzumab activity on the growth of HER2-overexpressing BT474 cells may interfere with human peripheral blood endogenous factors. Among 33 individual BC patient blood samples supplemented to the media, BT474 sensitivity to trastuzumab varied up to 14 times. In the absence of trastuzumab, human peripheral blood serum samples could inhibit growth of BT474, and this effect varied ~10 times for 50 individual samples. In turn, the epidermal growth factor (EGF) suppressed the trastuzumab effect on BT474 cell growth. Trastuzumab treatment increased the proportion of BT474 cells in the G0/G1 phases of cell cycle, while simultaneous addition of EGF decreased it, yet not to the control level. We used RNA sequencing profiling of gene expression to elucidate the molecular mechanisms involved in EGF- and human-sera-mediated attenuation of the trastuzumab effect on BT474 cell growth. Bioinformatic analysis of the molecular profiles suggested that trastuzumab acts similarly to the inhibition of PI3K/Akt/mTOR signaling axis, and the mechanism of EGF suppression of trastuzumab activity may be associated with parallel activation of PKC and transcriptional factors ETV1-ETV5.

Pyroptosis is related to immune infiltration and predictive for survival of colon adenocarcinoma patients

Pyroptosis is a novel type of programmed cell death, initiated by inflammasome. Pyroptosis inhibits the development and metastasis of colon cancer and is associated with patients’ prognosis. However, how the pyroptosis-related genes predict the survival of patients is still unclear. In the study, colon adenocarcinoma (COAD) patients were divided into two groups according to the expression of pyroptosis-related regulators through consensus clustering. DEGs between two clusters were analyzed by using COX and Lasso regression. Then, regression coefficients in Lasso were used to calculate the risk score for every patient. Patients were classified into two types: low- and high-risk group according to their risk score. The difference of immune microenvironment infiltration and clinicopathological characteristics between subgroups was performed. Moreover, the nomogram model was built on the bases of risk model and clinicopathological factors. The TCGA-COAD cohort and GEO cohort were used as training and validating set respectively. 398 COAD patients in TCGA training set were identified as two regulation patterns via unsupervised clustering method. Patients in cluster 2 showed better prognosis (P = 0.002). Through differentiated expression analysis, COX and Lasso regression, a 5-gene prognostic risk model was constructed. This risk model was significantly associated with OS (HR: 2.088, 95% CI: 1.183–3.688, P = 0.011), validated in GEO set (HR:1.344, 95%CI: 1.061–1.704, P = 0.014), and patients with low risk had better prognosis (P < 0.001 in TCGA; P = 0.038 in GEO). Through ROC analysis, it can be found that this model presented better predictive accuracy for long-term survival. Clinical analyses demonstrated that high-risk group had more advanced N stage, higher risk of metastasis and later pathological stage. Immune-related analysis illustrated that low-risk group had more immune cell infiltration and more activated immune pathways. The pyroptosis-related risk model can be predictive for the survival of COAD patients. That patients with higher risk had poorer prognosis was associated with more advanced tumor stage and higher risk of metastasis, and resulted from highly activated pro-tumor pathways and inhibited immune system and poorer integrity of intestinal epithelial. This study proved the relationship between pyroptosis and immune, which offered basis for future studies.

PGM1 suppresses colorectal cancer cell migration and invasion by regulating the PI3K/AKT pathway

BACKGROUND

Phosphoglucomutase 1 (PGM1) is known for its involvement in cancer pathogenesis. However, its biological role in colorectal cancer (CRC) has remained unknown. Here, we studied the functions and mechanisms of PGM1 in CRC.

METHODS

We verified PGM-1 as a differentially expressed gene (DEG) by employing a comprehensive strategy of TCGA-COAD dataset mining and computational biology. Relative levels of PGM-1 in CRC tumors and adjoining peritumoral tissues were determined by qRT-PCR, western blotting (WB), and immunohistochemical (IHC) staining in a tissue microarray. PGM1 functions were analyzed by CCK8, EdU, colony formation, cell cycle, apoptosis, and Transwell migration and invasion assays. The influence of PGM1 was further investigated by studying tumor formation in vivo.

RESULTS

The levels of PGM1 mRNA and protein were both reduced in CRC tissues, and the reductions were related to CRC pathology and overall survival. PGM1 knockdown stimulated both cell proliferation and colony formation, and inhibited cell cycle arrest and apoptosis, while overexpression of PGM1 produced the opposite effects in CRC cells both in vivo and in vitro. Furthermore, the effects of PGM1 were related to the PI3K/ AKT pathway.

CONCLUSION

We verified that PGM1 suppresses CRC progression via the PI3K/AKT pathway. These results suggest the potential for targeting PGM1 in treatment of CRC.

Prebiotic Galactooligosaccharide Supplementation in Adults with Ulcerative Colitis: Exploring the Impact on Peripheral Blood Gene Expression, Gut Microbiota, and Clinical Symptoms

Prebiotics may promote immune homeostasis and reduce sub-clinical inflammation in humans. This study investigated the effect of prebiotic galactooligosaccharide (GOS) supplementation in colonic inflammation. Seventeen patients with active ulcerative colitis (UC) consumed 2.8 g/d GOS for 6 weeks. At baseline and 6 weeks, gene expression (microarray), fecal calprotectin (ELISA), microbiota (16S rRNA), short-chain fatty acids (SCFAs; gas-liquid chromatography), and clinical outcomes (simple clinical colitis activity index (SCCAI), gastrointestinal symptom rating scale (GSRS), and Bristol stool form scale (BSFS)) were measured. Following prebiotics, clinical scores (SCCAI), fecal calprotectin, SCFAs, and pH were unchanged. Five genes were upregulated and two downregulated. Normal stool proportion (BSFS) increased (49% vs. 70%, p = 0.024), and the incidence (46% vs. 23%, p = 0.016) and severity (0.7 vs. 0.5, p = 0.048) of loose stool (GSRS), along with urgency (SCCAI) scores (1.0 vs. 0.5, p = 0.011), were reduced. In patients with a baseline SCCAI ≤2, prebiotics increased the relative abundance of Bifidobacterium from 1.65% (1.97) to 3.99% (5.37) (p = 0.046) and Christensenellaceae from 0.13% (0.33) to 0.31% (0.76) (p = 0.043). Prebiotics did not lower clinical scores or inflammation but normalized stools. Bifidobacterium and Christensenellaceae proportions only increased in patients with less active diseases, indicating that the prebiotic effect may depend on disease activity. A controlled study is required to validate these observations.

miR-1293 acts as a tumor promotor in lung adenocarcinoma via targeting phosphoglucomutase 5

Background

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Studies have found that miR-1293 is related to the survival of LUAD patients. Unfortunately, its role in LUAD remains not fully clarified.

Methods

miR-1293 expression and its association with LUAD patients’ clinical characteristics were analyzed in TCGA database. Also, miR-1293 expression was detected in LUAD cell lines. Cell viability, migration, invasion and expression of MMP2 and MMP9 were measured in LUAD cells following transfection with miR-1293 mimic or antagomir. Phosphoglucomutase (PGM) 5 was identified to be negatively related to miR-1293 in LUAD patients in TCGA database, and their association was predicated by Targetscan software. Hence, we further verified the relationship between miR-1293 and PGM5. Additionally, the effect and mechanism of miR-1293 were validated in a xenograft mouse model.

Results

We found miR-1293 expression was elevated, but PGM5 was decreased, in LUAD patients and cell lines. Higher miR-1293 expression was positively related to LUAD patients’ pathologic stage and poor overall survival. miR-1293 mimic significantly promoted, whereas miR-1293 antagomir suppressed the viability, migration, invasion, and expression of MMP2 and MMP9 in LUAD cells. PGM5 was a target of miR-1293. Overexpression of PGM5 abrogated the effects of miR-1293 on the malignant phenotypes of LUAD cells. Administration of miR-1293 antagomir reduced tumor volume and staining of Ki-67 and MMP9, but elevated PGM5 expression in vivo.

Conclusions

miR-1293 promoted the proliferation, migration and invasion of LUAD cells via targeting PGM5, which indicated that miR-1293 might serve as a potential therapeutic target for LUAD patients.

A Metabolic-associated Nomogram Predicts Recurrence Survival of Thyroid Cancer

OBJECTIVE

Various studies have suggested that metabolic genes play a significant role in papillary thyroid cancer (PTC). The current study aimed to identify a metabolic signature related biomarker to predict the prognosis of patients with PTC.

METHODS

We conducted a comprehensive analysis on the data obtained from the Cancer Genome Atlas (TCGA) database. The correlation between survival result and metabolic genes was evaluated based on the univariate Cox analyses, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses. The performance of a 7-gene signature was assessed according to Kaplan-Meier and receiver operating characteristic (ROC) analysis. Multivariate Cox regression analysis was adopted to unearth clinical factors related to the recurrence free survival (RFS) of patients with PTC. Finally, a prognostic nomogram was developed based on risk score, cancer status and cancer width to improve the prediction for RFS of PTC patients.

RESULTS

Seven metabolic genes were used to establish the prognostic model. The ROC curve and C-index exhibited high value in training, testing and the whole TCGA datasets. The established nomogram, incorporating the 7-metabolic gene signature and clinical factors, was able to predict the RFS with high effectiveness. The 7-metabolic gene signature-based nomogram had a good performance to predict the RFS of patients with PTC.

CONCLUSION

Our study identified a 7-metabolic gene signature and established a prognostic nomogram, which were useful in predicting the RFS of PTC.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients.

Methods

Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature.

Results

A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis.

Conclusion

Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01975-z.

miR-1224-3p Promotes Breast Cancer Cell Proliferation and Migration through PGM5-Mediated Aerobic Glycolysis

Metabolic reprogramming of aerobic glycolysis is a hallmark of cancer cells. Regulators of aerobic glycolysis have become targets for cancer diagnosis and therapy. However, the regulators of aerobic glycolysis in breast cancer development have not been well elucidated. Here, we show that the phosphoglucomutase (PGM) family member PGM5 promotes conversion of glucose-1-phosphate (G1P) into glucose-6-phosphate (G6P) and inhibits breast cancer cell proliferation and migration through regulating aerobic glycolysis. In breast cancer patients, PGM5 is significantly downregulated, and its low expression is a predictor of poor prognosis. MicroRNA-1224-3p (miR-1224-3p) inhibits the PGM5 level through directly targeting its 3'-untranslated region and suppresses PGM5-mediated breast cancer cell proliferation, migration, and glycolytic function. Moreover, the miR-1224-3p/PGM5 axis regulates the expression of cell cycle- and apoptosis-related genes and the markers of epithelial-mesenchymal transition (EMT), a process involved in migration and metastasis of cancer cells. Taken together, our results indicate that miR-1224-3p/PGM5 axis plays important roles in breast cancer cell proliferation, migration, and aerobic glycolysis and may be a potential target for breast cancer therapy.

Comprehensive Analysis of mRNA Expression Profiles in Head and Neck Cancer by Using Robust Rank Aggregation and Weighted Gene Coexpression Network Analysis

Background

Head and neck squamous cell cancer (HNSCC) is the sixth most common cancer in the world; its pathogenic mechanism remains to be further clarified.

Methods

Robust rank aggregation (RRA) analysis was utilized to identify the metasignature dysregulated genes, which were then used for potential drug prediction. Weighted gene coexpression network analysis (WGCNA) was performed on all metasignature genes to find hub genes. DNA methylation analysis, GSEA, functional annotation, and immunocyte infiltration analysis were then performed on hub genes to investigate their potential role in HNSCC.

Result

A total of 862 metasignature genes were identified, and 6 potential drugs were selected based on these genes. Based on the result of WGCNA, six hub genes (ITM2A, GALNTL1, FAM107A, MFAP4, PGM5, and OGN) were selected (GS > 0.1, MM > 0.75, GS p value < 0.05, and MM p value < 0.05). All six genes were downregulated in tumor tissue (FDR < 0.01) and were related to the clinical stage and prognosis of HNSCC in different degrees. Methylation analysis showed that the dysregulation of ITM2A, GALNTL1, FAM107A, and MFAP4 may be caused by hypermethylation. Moreover, the expression level of all 6 hub genes was positively associated with immune cell infiltration, and the result of GSEA showed that all hub genes may be involved in the process of immunoregulation.

Conclusion

All identified hub genes could be potential biomarkers for HNSCC and provide a new insight into the diagnosis and treatment of head and neck tumors.

Structure and Characterization of Phosphoglucomutase 5 from Atlantic and Baltic Herring-An Inactive Enzyme with Intact Substrate Binding

Phosphoglucomutase 5 (PGM5) in humans is known as a structural muscle protein without enzymatic activity, but detailed understanding of its function is lacking. PGM5 belongs to the alpha-D-phosphohexomutase family and is closely related to the enzymatically active metabolic enzyme PGM1. In the Atlantic herring, Clupea harengus, PGM5 is one of the genes strongly associated with ecological adaptation to the brackish Baltic Sea. We here present the first crystal structures of PGM5, from the Atlantic and Baltic herring, differing by a single substitution Ala330Val. The structure of PGM5 is overall highly similar to structures of PGM1. The structure of the Baltic herring PGM5 in complex with the substrate glucose-1-phosphate shows conserved substrate binding and active site compared to human PGM1, but both PGM5 variants lack phosphoglucomutase activity under the tested conditions. Structure comparison and sequence analysis of PGM5 and PGM1 from fish and mammals suggest that the lacking enzymatic activity of PGM5 is related to differences in active-site loops that are important for flipping of the reaction intermediate. The Ala330Val substitution does not alter structure or biophysical properties of PGM5 but, due to its surface-exposed location, could affect interactions with protein-binding partners.

Computational gene expression profiling in the exploration of biomarkers, non-coding functional RNAs and drug perturbagens for COVID-19

The coronavirus disease, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a global health crisis that is being endured with an increased alarm of transmission each day. Though the pandemic has activated innumerable research attention to decipher an antidote, fundamental understanding of the molecular mechanisms is necessary to halt the disease progression. The study focused on comparison of the COVID-19 infected lung tissue gene expression datasets -GSE155241 and GSE150316 with the GEO2R-limma package. The significant up- and downregulated genes were annotated. Further evaluation of the enriched pathways, transcription factors, kinases, noncoding RNAs and drug perturbations revealed the significant molecular mechanisms of the host response. The results revealed a surge in mitochondrial respiration, cytokines, neurodegenerative mechanisms and deprived oxygen, iron, copper, and glucose transport. Hijack of ubiquitination by SARS-CoV-2, hox gene differentiation, histone modification, and miRNA biogenesis were the notable molecular mechanisms inferred. Long non-coding RNAs such as C058791.1, TTTY15 and TPTEP1 were predicted to be efficient in regulating the disease mechanisms. Drugs-F-1566-0341, Digoxin, Proscillaridin and Linifanib that reverse the gene expression signatures were predicted from drug perturbations analysis. The binding efficiency and interaction of proscillaridin and digoxin as obtained from the molecular docking studies confirmed their therapeutic potential. Two overlapping upregulated genes MDH1, SGCE and one downregulated gene PFKFB3 were appraised as potential biomarkers candidates. The upregulation of PGM5, ISLR and ANK2 as measured from their expressions in normal lungs affirmed their possible prognostic biomarker competence. The study explored significant insights for better diagnosis, and therapeutic options for COVID-19.

Communicated by Ramaswamy H. Sarma

Development of cancer prognostic signature based on pan-cancer proteomics

Utilizing genomic data to predict cancer prognosis was insufficient. Proteomics can improve our understanding of the etiology and progression of cancer and improve the assessment of cancer prognosis. And the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has generated extensive proteomics data of the vast majority of tumors. Based on CPTAC, we can perform a proteomic pan-carcinoma analysis. We collected the proteomics data and clinical features of cancer patients from CPTAC. Then, we screened 69 differentially expressed proteins (DEPs) with R software in five cancers: hepatocellular carcinoma (HCC), children’s brain tumor tissue consortium (CBTTC), clear cell renal cell carcinoma (CCRC), lung adenocarcinoma (LUAD) and uterine corpus endometrial carcinoma (UCEC). GO and KEGG analysis were performed to clarify the function of these proteins. We also identified their interactions. The DEPs-based prognostic model for predicting over survival was identified by least absolute shrinkage and selection operator (LASSO)-Cox regression model in training cohort. Then, we used the time-dependent receiver operating characteristics analysis to evaluate the ability of the prognostic model to predict overall survival and validated it in validation cohort. The results showed that the DEPs-based prognostic model could accurately and effectively predict the survival rate of most cancers.

Association of Mps one binder kinase activator 1 (MOB1) expression with poor disease-free survival in individuals with non-small cell lung cancer

Background

Mps one binder kinase activator 1 (MOB1) is a core component of the Hippo signaling pathway and has been implicated as a tumor suppressor. Here, we evaluated the possible relationship of MOB1 expression in non‐small cell lung cancer (NSCLC) to prognosis.

Methods

We retrospectively analyzed 205 lung adenocarcinoma patients treated at Kyushu University Hospital between November 2007 and October 2012. MOB1 expression in tumor cells of surgical specimens was evaluated by immunohistochemistry. Invasive activity of NSCLC cell lines in vitro was measured with a transwell assay.

Results

Expression of MOB1 was classified as high in 105 of the 205 (51.2%) tumor specimens, and such high expression was significantly associated with poor disease‐free survival (P = 0.0161). Among the various clinicopathologic parameters examined, high MOB1 expression was significantly associated only with intratumoral vascular invasion (P = 0.0005). Multivariate analysis also identified high MOB1 expression as a significant independent risk factor for disease‐free survival (P = 0.0319). The invasiveness of H1299 cells in vitro was increased or attenuated by overexpression or knockdown of MOB1, respectively.

Conclusions

Our results suggest that MOB1 might promote early recurrence of NSCLC by increasing vascular invasion by tumor cells.

Key points

Significant findings of the study

We found that high MOB1 expression in surgical specimens of lung adenocarcinoma was associated with poor disease‐free survival and with intratumoral vascular invasion. MOB1 expression also promoted the invasiveness of NSCLC cells in vitro.

What this study adds

Our results thus suggest that high MOB1 expression is a risk factor for early postoperative recurrence in lung adenocarcinoma.

Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells’ viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a “proliferation metabolic signature” (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development.

Integrated analysis of miRNA and mRNA expression profiles in p53-edited PFF cells

p53 is the most frequently mutated gene in human cancers, with over half of all tumors harboring mutation at this locus. R248 and R249 (corresponding to porcine R241 and R242), are among the hotspot mutations frequently mutated in liver, lung, breast, and some other cancers. In this study, p53 gene was knocked out or point-edited (R241 and R242 were converted to 241W and 242S) in porcine fetal fibroblast (PFF) cells via CRISPR-Cas9 technique. High throughput sequencing of miRNA and mRNA uncovered a total of 225 differentially expressed miRNAs (DEMs) and 738 differentially expressed genes (DEGs) in the p53 knockout (p53-KO) cells, and a total of 211 DEMs and 722 DEGs in the point-modified (p53-241W242S) cells. Totally 28 annotated DEMs were found to overlap between p53-KO/p53-WT and p53-241W242S/p53-WT miRNAs datasets, of which miR-34 c, miR-218, miR-205, miR-105-1, miR-105-2, miR-206, miR-224 and miR-429 play important roles in p53 regulatory network. Among the top 10 DEGs in p53-KO and p53-241W242S cells, most genes were reported to be involved in tumors, cell proliferation or cell migration. p53-KO and p53-241W242S cells showed a significantly higher (P < 0.01) proliferation rate compared with p53-WT cells. In conclusion, genetic modifications of p53 gene significantly affect the expression levels of a large number of genes and miRNAs in the PFF cells. The p53-edited PFF cells could be used as non-tumor cell models for investigating the p53 signaling network, and as donor cells for somatic nuclear transfer, with the aim to develop porcine models with the corresponding p53 mutations.Abbreviations: CRISPR-Cas9: Clustered regularly interspaced short palindromic repeats-associated protein 9; PFF: porcine fetal fibroblasts; SCNT: somatic cell nuclear transfer; RNA sequencing: small RNA sequencing and mRNA sequencing; DEGs: differentially expressed mRNAs; DEMs: differentially expressed miRNAs.