GPI Is a Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma

Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics

High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SIGNIFICANCE: OC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate.

Plasma GPI and PGD are associated with vascular normalization and may serve as novel prognostic biomarkers for lung adenocarcinoma: Multi-omics and multi-dimensional analysis

The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SIGNIFICANT: We identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.

Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression

BACKGROUND

Due to the unfavorable prognosis associated with lung adenocarcinoma (LUAD), the development of targeted therapies and immunotherapies is essential. Cuproptosis, an emerging form of regulated cell death, is implicated in mitochondrial metabolism and is induced by copper ions. This study aimed to explore the prognostic value of cuproptosis- and immune-related genes (CIRGs) in LUAD.

METHODS

We used The Cancer Genome Atlas database to develop a prognostic prediction model for LUAD patients based on eight CIRGs. Using Cox regression analysis, we determined that the CIRG signature is a reliable, independent prognostic factor. We further identified PSMD11 as a critical CIRG and performed immunohistochemistry to study the protein expression levels of PSMD11 in LUAD tissues. We also investigated the impact of PSMD11 on the biological behavior of lung cancer cell lines.

RESULTS

We found that patients with low PSMD11 expression levels displayed an improved prognosis compared with those with high PSMD11 expression levels. Overexpression of PSMD11 enhanced proliferation, migration, invasion, and tumor growth of lung carcinoma cell line A549, while PSMD11 knockdown diminished proliferation, migration, invasion, and tumor growth of lung carcinoma cell line PC9. Additionally, we discovered that PSMD11 expression was positively correlated with the infiltration of myeloid-derived suppressor cells and the increased expression of immunosuppressive molecules.

CONCLUSION

These findings suggest that PSMD11 may serve as a valuable prognostic biomarker and therapeutic target for LUAD.

Nuclear protein NOP2 serves as a poor-prognosis predictor of LUAD and aggravates the malignancy of lung adenocarcinoma cells

Recent studies have shown that NOP2, a nucleolar protein, is up-regulated in various cancers, suggesting a potential link to tumor aggressiveness and unfavorable outcomes. This study examines NOP2's role in lung adenocarcinoma (LUAD), a context where its implications remain unclear. Utilizing bioinformatics, we assessed 513 LUAD and 59 normal tissue samples from The Cancer Genome Atlas (TCGA) to explore NOP2's diagnostic and prognostic significance in LUAD. Additionally, in vitro experiments compared NOP2 expression between Beas-2b and A549 cells. Advanced databases and analytical tools, including LINKEDOMICS, STRING, and TISIDB, were employed to further elucidate NOP2's association with LUAD. Our findings indicate a significantly higher expression of NOP2 mRNA and protein in A549 cells compared to Beas-2b cells (P < 0.001). In LUAD, elevated NOP2 levels were linked to decreased Overall Survival (OS) and advanced clinical stages. Univariate Cox analysis revealed that high NOP2 expression correlated with poorer OS in LUAD (P < 0.01), a finding independently supported by multivariate Cox analysis (P < 0.05). The relationship between NOP2 expression and LUAD risk was presented via a Nomogram. Additionally, Gene Set Enrichment Analysis (GSEA) identified seven NOP2-related signaling pathways. A focal point of our research was the interplay between NOP2 and tumor-immune interactions. Notably, a negative correlation was observed between NOP2 expression and the immune infiltration levels of macrophages, neutrophils, mast cells, Natural Killer (NK) cells, and CD8 + T cells in LUAD. Moreover, the expression of NOP2 was related to the sensitivity of various chemotherapeutic drugs. In vitro, we found that downregulating NOP2 can decrease the proliferation, migration and invasion of A549 cells. Furthermore, NOP2 can regulate Caspase3-mediated apoptosis. Collectively, particularly regarding prognosis, immune infiltration and vitro experiments, these findings suggest NOP2's potential of serving as a poor-prognostic biomarker for LUAD and aggravating the malignancy of lung adenocarcinoma cells.

Comprehensive analysis of the prognosis and biological significance of RORβ in head and neck squamous cell carcinoma

Recent studies have shown that abnormal expression of the core circadian clock gene, retinoic acid-related orphan receptor β (RORβ ), is closely associated with the occurrence and progression of various malignant tumors. However, the expression and function of RORβ in head and neck squamous cell carcinoma (HNSCC) remains unclear. Here, we comprehensively investigated the altered expression, clinical significance, prognostic value, and biological functions of RORβ in HNSC, as well as its correlation with changes in the tumor immune microenvironment. We found that RORβ expression was decreased in HNSC and 19 other cancers. Low RORβ expression was significantly associated with tumor size, clinical stage, and survival time in HNSC patients, indicating that it may have diagnostic and prognostic value in HNSCC. Epigenetic analysis showed that the promoter methylation level of RORβ was significantly higher in HNSCC compared to adjacent noncancerous tissues. Furthermore, RORβ hypermethylation was significantly associated with low expression levels of RORβ and poor prognosis in HNSCC patients (p < 0.05). Enrichment analysis found that RORβ was involved in immune system regulation and T-cell activation, as well as the PI3K/AKT and ECM receptors interaction pathways. In vitro assays revealed that RORβ regulated the proliferation, migration and invasion ability of HNSCC cells. Additionally, we found that RORβ expression was significantly correlated with changes in the tumor immune microenvironment, suggesting it may affect prognosis by regulating immune infiltration in HNSC patients. Therefore, RORβ may serve as a potential prognostic biomarker and therapeutic target for HNSCC patients.

Identification of the consistently differential expressed hub mRNAs and proteins in lung adenocarcinoma and construction of the prognostic signature: a multidimensional analysis

BACKGROUND

This study aimed to elucidate the consistency of differentially expressed hub mRNAs and proteins in lung adenocarcinoma (LUAD) across populations and to construct a comprehensive LUAD prognostic signature.

METHODS

The transcriptomic and proteomics data from different populations were standardized and analyzed using the same criteria to identify the consistently differential expressed mRNAs and proteins across genders and races. We then integrated prognosis-related mRNAs with clinical, pathological, and EGFR (epidermal growth factor receptor) mutation data to construct a survival model, subsequently validating it across populations. Through plasma proteomics, plasma proteins that consistently differential expressed with LUAD tissues were screened and validated, with their associations discerned by measuring expressions in tumor tissues and tumor vascular normalization.

RESULTS

The consistency rate of differentially expressed mRNAs and proteins was ~20-40%, with ethnic factors leading to about 40-60% consistency of differentially expressed mRNA or protein across populations. The survival model based on the identified eight hub mRNAs as well as stage, smoking status, and EGFR mutations, demonstrated good prognostic prediction capabilities in both Western and East Asian populations, with a higher number of unfavorable variables indicating poorer LUAD prognosis. Notably, GPI expression in tumor tissues was inversely correlated with vascular normalization and positively correlated with plasma GPI expression.

CONCLUSION

Our study underscores the significance of integrating transcriptomics and proteomics data, emphasizing the need to account for genetic diversity among ethnic groups. The developed survival model may offer a holistic perspective on LUAD progression, enhancing prognosis and therapeutic strategies.

Single-cell RNA-seq analyses inform necroptosis-associated myeloid lineages influence the immune landscape of pancreas cancer

Introduction

Tumor-infiltrating myeloid cells (TIMs) are key regulators in tumor progression, but the similarity and distinction of their fundamental properties in pancreatic ductal adenocarcinoma (PDAC) remain elusive.

Method

In this study, we conducted scRNA-seq data analysis of cells from 12 primary tumor (PT) tissues, 4 metastatic (Met) tumor tissues, 3 adjacent normal pancreas tissues (Para), and PBMC samples across 16 PDAC patients, and revealed a heterogeneous TIMs environment in PDAC.

Result

Systematic comparisons between tumor and non-tumor samples of myeloid lineages identified 10 necroptosis-associated genes upregulated in PDAC tumors compared to 5 upregulated in paratumor or healthy peripheral blood. A novel RTM (resident tissue macrophages), GLUL-SQSTM1- RTM, was found to act as a positive regulator of immunity. Additionally, HSP90AA1+HSP90AB1+ mast cells exhibited pro-immune characteristics, and JAK3+TLR4+ CD16 monocytes were found to be anti-immune. The findings were validated through clinical outcomes and cytokines analyses. Lastly, intercellular network reconstruction supported the associations between the identified novel clusters, cancer cells, and immune cell populations.

Conclusion

Our analysis comprehensively characterized major myeloid cell lineages and identified three subsets of myeloid-derived cells associated with necroptosis. These findings not only provide a valuable resource for understanding the multi-dimensional characterization of the tumor microenvironment in PDAC but also offer valuable mechanistic insights that can guide the design of effective immuno-oncology treatment strategies.

RHBDF1 deficiency suppresses melanoma glycolysis and enhances efficacy of immunotherapy by facilitating glucose-6-phosphate isomerase degradation via TRIM32

Melanoma is a dangerous form of skin cancer, making it important to investigate new mechanisms and approaches to enhance the effectiveness of treatment. Here, we establish a positive correlation between the human rhomboid family-1 (RHBDF1) protein and melanoma malignancy. We demonstrate that the melanoma RHBDF1 decrease dramatically inhibits tumor growth and the development of lung metastases, which may be related to the impaired glycolysis. We show that RHBDF1 function is essential to the maintenance of high levels of glycolytic enzymes, especially glucose-6-phosphate isomerase (GPI). Additionally, we discover that the E3 ubiquitin ligase tripartite motif-containing 32 (TRIM32) mediates the K27/K63-linked ubiquitination of GPI and the ensuing lysosomal degradation process. We prove that the multi-transmembrane domain of RHBDF1 is in competition with GPI, preventing the latter from interacting with NCL1-HT2A-LIN41 (NHL) domain of TRIM32. We also note that the mouse RHBDF1's R747 and Y799 are crucial for competitive binding and GPI protection. Artificially silencing the Rhbdf1 gene in a mouse melanoma model results in declined lactic acid levels, elevated cytotoxic lymphocyte infiltration, and improved tumor responsiveness to immunotherapy. These results provide credence to the hypothesis that RHBDF1 plays a significant role in melanoma regulation and suggest that blocking RHBDF1 may be an efficient technique for reestablishing the tumor immune microenvironment (TIME) in melanoma and halting its progression.

Two-Dimensional-PAGE Coupled with nLC-MS/MS-Based Identification of Differentially Expressed Proteins and Tumorigenic Pathways in MCF7 Breast Cancer Cells Transfected for JTB Protein Silencing

The identification of new cancer-associated genes/proteins, the characterization of their expression variation, the interactomics-based assessment of differentially expressed genes/proteins (DEGs/DEPs), and understanding the tumorigenic pathways and biological processes involved in BC genesis and progression are necessary and possible by the rapid and recent advances in bioinformatics and molecular profiling strategies. Taking into account the opinion of other authors, as well as based on our own team's in vitro studies, we suggest that the human jumping translocation breakpoint (hJTB) protein might be considered as a tumor biomarker for BC and should be studied as a target for BC therapy. In this study, we identify DEPs, carcinogenic pathways, and biological processes associated with JTB silencing, using 2D-PAGE coupled with nano-liquid chromatography tandem mass spectrometry (nLC-MS/MS) proteomics applied to a MCF7 breast cancer cell line, for complementing and completing our previous results based on SDS-PAGE, as well as in-solution proteomics of MCF7 cells transfected for JTB downregulation. The functions of significant DEPs are analyzed using GSEA and KEGG analyses. Almost all DEPs exert pro-tumorigenic effects in the JTBlow condition, sustaining the tumor suppressive function of JTB. Thus, the identified DEPs are involved in several signaling and metabolic pathways that play pro-tumorigenic roles: EMT, ERK/MAPK, PI3K/AKT, Wnt/β-catenin, mTOR, C-MYC, NF-κB, IFN-γ and IFN-α responses, UPR, and glycolysis/gluconeogenesis. These pathways sustain cancer cell growth, adhesion, survival, proliferation, invasion, metastasis, resistance to apoptosis, tight junctions and cytoskeleton reorganization, the maintenance of stemness, metabolic reprogramming, survival in a hostile environment, and sustain a poor clinical outcome. In conclusion, JTB silencing might increase the neoplastic phenotype and behavior of the MCF7 BC cell line. The data is available via ProteomeXchange with the identifier PXD046265.

A whole exome sequencing study to identify rare variants in multiplex families with alcohol use disorder

Background

Alcohol use disorder (AUD) runs in families and is accompanied by genetic variation. Some families exhibit an extreme susceptibility in which multiple cases are found and often with an early onset of the disorder. Large scale genome-wide association studies have identified several genes with impressive statistical probabilities. Most of these genes are common variants. Our goal was to perform exome sequencing in families characterized by multiple cases (multiplex families) to determine if rare variants might be segregating with disease status.

Methods

A case-control approach was used to leverage the power of a large control sample of unrelated individuals (N = 8,983) with exome sequencing [Institute for Genomic Medicine (IGM)], for comparison with probands with AUD (N = 53) from families selected for AUD multiplex status. The probands were sequenced at IGM using similar protocols to those used for the archival controls. Specifically, the presence of a same-sex pair of adult siblings with AUD was the minimal criteria for inclusion. Using a gene-based collapsing analysis strategy, a search for qualifying variants within the sequence data was undertaken to identify ultra-rare non-synonymous variants.

Results

We searched 18,666 protein coding genes to identify an excess of rare deleterious genetic variation using whole exome sequence data in the 53 AUD individuals from a total of 282 family members. To complete a case/control analysis of unrelated individuals, probands were compared to unrelated controls. Case enrichment for 16 genes with significance at 10-4 and one at 10-5 are plausible candidates for follow-up studies. Six genes were ultra rare [minor allele frequency (MAF) of 0.0005]: CDSN, CHRNA9, IFT43, TLR6, SELENBP1, and GMPPB. Eight genes with MAF of 0.001: ZNF514, OXGR1, DIEXF, TMX4, MTBP, PON2, CRHBP, and ANKRD46 were identified along with three protein-truncating variants associated with loss-of-function: AGTRAP, ANKRD46, and PPA1. Using an ancestry filtered control group (N = 2,814), nine genes were found; three were also significant in the comparison to the larger control group including CHRNA9 previously implicated in alcohol and nicotine dependence.

Conclusion

This study implicates ultra-rare loss-of-function genes in AUD cases. Among the genes identified include those previously reported for nicotine and alcohol dependence (CHRNA9 and CRHBP).

Comprehensive analysis of the lncRNAs-related immune gene signatures and their correlation with immunotherapy in lung adenocarcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs)-related immune genes (lrRIGs) play a crucial role in the development and progression of lung adenocarcinoma (LUAD). However, reliable prognostic signatures based on lrRIGs have not yet been identified.

METHODS

We screened lrRIGs associated with the prognosis of LUAD using The Cancer Genome Atlas (TCGA) database and then established a novel prognostic nine-gene signature composed of CD79A, INHA, SHC3, LIFR, TNFRSF11A, GPI, F2RL1, SEMA7A and WFDC2 through bioinformatic approaches. A risk score derived from this gene signature was used to divide LUAD patients into the low- and high-risk groups. The latter was confirmed to have markedly worse overall survival (O.S.). A nomogram was developed using the risk score and other independent prognostic elements, demonstrating excellent performance in predicting the O.S. rate of LUAD patients.

RESULTS

We observed that the infiltration of diverse immune cell subtypes and response to immunotherapy and chemotherapy significantly differed between the low- and high-risk groups.

CONCLUSIONS

Overall, stratification based on this gene signature could be used to guide better therapeutic management and improve outcomes for LUAD patients.

Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study

Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.

Pan-cancer analysis identified OAS1 as a potential prognostic biomarker for multiple tumor types

Background

2',5'-oligoadenylate synthetase 1 (OAS1), has been reported as a tumor driver gene in breast carcinoma and pancreatic carcinoma. However, the role of OAS1 in most tumors has not been reported.

Methods

The original data of 35 tumor types were down load from the TCGA (The Cancer Genome Atlas) database and Human Protein Atlas (HPA) database. TIMER2, Kmplot, UALCAN, and TISIDB tools were used to investigate the expression and function of OAS1, and the role of OAS1 in prognosis, diagnostic value, and immune characteristics of pan-cancer. LUAD and PRAD cell lines, A549, H1975, PC-3 and C4-2 were utilized to perform cell function tests.

Results

OAS1 expression was up-regulated in 12 tumor types and down-regulated in 2 tumor types. High OAS1 expression was correlated with poor prognosis in 6 tumor types, while high OAS1 expression was correlated with good prognosis in 2 tumor types. OAS1 was correlated with molecular subtypes in 8 tumor types and immune subtypes in 12 tumor types. OAS1 was positively associated with the expression of numerous immune checkpoint genes and tumor mutational burden (TMB). OAS1 had potential diagnostic value in 15 tumor types. Silence of OAS1 significantly inhibited the cell proliferation ability, and promoted G2/M cell cycle arrest of LUAD and PRAD cells. Meanwhile, silence of OAS1 enhanced cisplatin-induced apoptosis of LUAD and PRAD cells, but weakened cell migration.

Conclusion

This pan-cancer study suggests that OAS1can be used as a molecular biomarker for prognosis in pan-cancer and may play an important role in tumor immune response.

DARS2 overexpression is associated with PET/CT metabolic parameters and affects glycolytic activity in lung adenocarcinoma

BACKGROUND

This study investigated the correlation between the expression of DARS2 and metabolic parameters of 18F-FDG PET/CT, and explored the potential mechanisms of DARS2 affecting the proliferation and glycolysis of lung adenocarcinoma (LUAD) cells.

METHODS

This study used genomics and proteomics to analyze the difference in DARS2 expression between LUAD samples and control samples. An analysis of 62 patients with LUAD who underwent 18F-FDG PET/CT examinations before surgery was conducted retrospectively. The correlation between DARS2 expression and PET/CT metabolic parameters, including SUVmax, SUVmean, MTV, and TLG, was examined by Spearman correlation analysis. In addition, the molecular mechanism of interfering with DARS2 expression in inhibiting LUAD cell proliferation and glycolysis was analyzed through in vitro cell experiments.

RESULTS

DARS2 expression was significantly higher in LUAD samples than in control samples (p < 0.001). DARS2 has high specificity (98.4%) and sensitivity (95.2%) in the diagnosis of LUAD. DARS2 expression was positively correlated with SUVmax, SUVmean, and TLG (p < 0.001). At the same time, the sensitivity and specificity of SUVmax in predicting DARS2 overexpression in LUAD were 88.9% and 65.9%, respectively. In vitro cell experiments have shown that interfering with DARS2 expression can inhibit the proliferation and migration of LUAD cells, promote cell apoptosis, and inhibit the glycolytic activity of tumor cells by inhibiting the expression of glycolytic related genes SLC2A1, GPI, ALDOA, and PGAM1.

CONCLUSIONS

Overexpression of DARS2 is associated with metabolic parameters on 18F-FDG PET/CT, which can improve LUAD diagnosis accuracy. DARS2 may be a useful biomarker to diagnose, prognosis, and target treatment of LUAD patients.

Proteomic response of A549 lung cancer cell line to protein-polysaccharide complex Venetin-1 isolated from earthworm coelomic fluid

Earthworms' celomic fluid has long attracted scientists' interest due to their toxic properties. It has been shown that the elimination of coelomic fluid cytotoxicity to normal human cells was crucial for the generation of the non-toxic Venetin-1 protein-polysaccharide complex, which exhibits selective activity against Candida albicans cells as well as A549 non-small cell lung cancer cells. To find the molecular mechanisms behind the anti-cancer properties of the preparation, this research investigated the proteome response of A549 cells to the presence of Venetin-1. The sequential window acquisition of all theoretical mass spectra (SWATH-MS) methodology was used for the analysis, which allows for a relative quantitative analysis to be carried out without radiolabelling. The results showed that the formulation did not induce significant proteome responses in normal BEAS-2B cells. In the case of the tumour line, 31 proteins were up regulated, and 18 proteins down regulated. Proteins with increased expression in neoplastic cells are mainly associated with the mitochondrion, membrane transport and the endoplasmic reticulum. In the case of altered proteins, Venetin-1 interferes with proteins that stabilise the structures, i.e., keratin, glycolysis/gluconeogenesis and metabolic processes.

Evaluation of the proteomic landscape of HPV E7‑induced alterations in human keratinocytes reveal therapeutically relevant pathways for cervical cancer

The lack of specific and accurate therapeutic targets poses a challenge in the treatment of cervical cancer (CC). Global proteomics has the potential to characterize the underlying and intricate molecular mechanisms that drive the identification of therapeutic candidates for CC in an unbiased manner. The present study assessed human papillomavirus (HPV)‑induced proteomic alterations to identify key cancer hallmark pathways and protein‑protein interaction (PPI) networks, which offered the opportunity to evaluate the possibility of using these for targeted therapy in CC. Comparative proteomic profiling of HPV‑transfected (HPV16/18 E7), HPV‑transformed (CaSki and HeLa) and normal human keratinocyte (HaCaT) cells was performed using the liquid chromatography‑tandem mass spectrometry (LC‑MS/MS) technique. Both label‑free quantification and differential expression analysis were performed to assess differentially regulated proteins in HPV‑transformed and ‑transfected cells. The present study demonstrated that protein expression was upregulated in HPV‑transfected cells compared with in HPV‑transformed cells. This was probably due to the ectopic expression of E7 protein in the former cell type, in contrast to its constitutive expression in the latter cell type. Subsequent pathway visualization and network construction demonstrated that the upregulated proteins in HPV16/18 E7‑transfected cells were predominantly associated with a diverse array of cancer hallmarks, including the mTORC1 signaling pathway, MYC targets V1, hypoxia and glycolysis. Among the various proteins present in the cancer hallmark enrichment pathways, phosphoglycerate kinase 1 (PGK1) was present across all pathways. Therefore, PGK1 may be considered as a potential biomarker. PPI analysis demonstrated a direct interaction between p130 and polyubiquitin B, which may lead to the degradation of p130 via the ubiquitin‑proteasome proteolytic pathway. In summary, elucidation of the key signaling pathways in HPV16/18‑transfected and ‑transformed cells may aid in the design of novel therapeutic strategies for clinical application such as targeted therapy and immunotherapy against cervical cancer.

Analysis of Akkermansia muciniphila in Mulberry Galacto-Oligosaccharide Medium via Comparative Transcriptomics

Akkermansia muciniphila is a common member of the human gut microbiota and belongs to the phylum Verrucomicrobia. Decreased levels of A. muciniphila are associated with many diseases, so it is thought to be a beneficial resident of the intestinal mucosal layer. In this study, we found that different prebiotics promoted the proliferation of A. muciniphila, and mulberry galacto-oligosaccharide (MGO) had the greatest effect. We cultured A. muciniphila in a brian heart infusion (BHI) medium containing 5% galactooligosaccharides (GOS), mulberry polysaccharide solution (MPS), and MGO, and transcriptomic analyses were performed. The results revealed that, after 6 days of cultivation, the numbers of upregulated functional genes (based on Gene Ontology) were approximately 0.7 and 19% higher with MPS and MGO, respectively, than with GOS. Analysis using the Kyoto Encyclopedia of Genes and Genomes showed that, when A. muciniphila was cultured with MGO, genes that were upregulated were enriched in the carbohydrate metabolism, the metabolism of cofactors and vitamins, the energy metabolism, the amino acid metabolism, and the lipid metabolism. Upregulated genes included galM and pfkA in the galactose metabolism, and pgi, pfk, fbaA, tpiA, gapA, pgk, gpml, eno, pyk, and lpd in the glycolysis/gluconeogenesis pathway. Real-time quantitative PCR results were consistent with the RNA-Seq data. This work provides valuable knowledge which can be available for the functional application of A. muciniphila and MGO.

Prognostic markers of ferroptosis-related long non-coding RNA in lung adenocarcinomas

Ferroptosis is a recently established type of iron-dependent programmed cell death. Growing studies have focused on the function of ferroptosis in cancers, including lung adenocarcinoma (LUAD). However, the factors involved in the regulation of ferroptosis-related genes are not fully understood. In this study, we collected data from lung adenocarcinoma datasets of the Cancer Genome Atlas (TCGA-LUAD). The expression profiles of 60 ferroptosis-related genes were screened, and two differentially expressed ferroptosis subtypes were identified. We found the two ferroptosis subtypes can predict clinical outcomes and therapeutic responses in LUAD patients. Furthermore, key long non-coding RNAs (lncRNAs) were screened by single factor Cox and least absolute shrinkage and selection operator (LASSO) based on which co-expressed with the 60 ferroptosis-related genes. We then established a risk score model which included 13 LUAD ferroptosis-related lncRNAs with a multi-factor Cox regression. The risk score model showed a good performance in evaluating the outcome of LUAD. What's more, we divided TCGA-LUAD tumor samples into two groups with high- and low-risk scores and further explored the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration among different LUAD tumor risk score groups and evaluate the predictive ability of risk score for immunotherapy benefit. Our findings provide good support for immunotherapy in LUAD in the future.

DLGAP4 acts as an effective prognostic predictor for hepatocellular carcinoma and is closely related to tumour progression

Disc large associated protein 4 (DLGAP4) plays an important role in neurological diseases, but the role and mechanism of DLGAP4 in hepatocellular carcinoma (HCC) remain unclear. In this study, the prognostic effect of DLGAP4 on HCC patients was investigated by means of bioinformatics. The correlation of DLGAP4 expression with the prognosis of HCC patients was evaluated by TCGA data analysis, and the correlation between DLGAP4 expression and the clinical characteristics of HCC patients was evaluated by the Wilcoxon signed rank test and logistic regression analysis. Kaplan‒Meier and Cox regression methods were used to assess the effect of DLGAP4 expression level on overall survival, and nomograms were used to illustrate the correlation between DLGAP4 gene expression and HCC risk. The genes related to DLGAP4 in HCC were screened, and GO/KEGG enrichment analysis was performed. Furthermore, in vitro and in vivo experiments were conducted to detect the effect of DLGAP4 expression on the proliferation, migration and metastasis of HCC cells. We also examined the effect of DLGAP4 expression on enriched pathway proteins to explore the possible mechanism. The expression levels of DLGAP4 were significantly higher in HCC cell lines and tissue samples than in normal liver cell lines and tissues. The expression of DLGAP4 was significantly associated with clinical characteristics. Survival analysis showed that high expression of DLGAP4 was associated with a poor prognosis in HCC. Multivariate analysis showed that high expression of DLGAP4 was an independent risk factor affecting the overall survival rate in HCC patients. By means of ROC curve analysis and nomograms, we determined the value of DLGAP4 expression in the diagnosis and prognosis evaluation of HCC. GO/KEGG enrichment analysis showed that the PPAR signalling pathway was differentially enriched in patients with high expression of DLGAP4. According to in vitro and in vivo experiments, DLGAP4 knockdown inhibited the proliferation and metastasis of HCC cells and decreased the expression of PPARβ/δ protein. In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cell, and increased the expression of PPARβ/δ protein.In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cells and increased the expression of PPARβ/δ protein. The results show a close correlation between DLGAP4 expression and clinicopathological features of HCC, and DLGAP4 can be used as a prediction biomarker of HCC.

Recognition of driver genes with potential prognostic implications in lung adenocarcinoma based on H3K79me2

•

The efficacy of H3K79me2 on gene expression regulation is affirmed in LUAD.

•

An open-source algorithm for identifying LUAD-related driver genes is presented.

•

12 H3K79me2-targeted driver genes with clinical values are verified by qPCR.

•

The regions with obvious H3K79me2 signals changes on driver genes are pinpointed.

Lung adenocarcinoma is a malignancy with a low overall survival and a poor prognosis. Studies have shown that lung adenocarcinoma progression relates to locus-specific/global changes in histone modifications. To explore the relationship between histone modification and gene expression changes, we focused on 11 histone modifications and quantitatively analyzed their influences on gene expression. We found that, among the studied histone modifications, H3K79me2 displayed the greatest impact on gene expression regulation. Based on the Shannon entropy, 867 genes with differential H3K79me2 levels during tumorigenesis were identified. Enrichment analyses showed that these genes were involved in 16 common cancer pathways and 11 tumors and were target-regulated by trans-regulatory elements, such as Tp53 and WT1. Then, an open-source computational framework was presented (https://github.com/zlq-imu/Identification-of-potential-LUND-driver-genes). Twelve potential driver genes were extracted from the genes with differential H3K79me2 levels during tumorigenesis. The expression levels of these potential driver genes were significantly increased/decreased in tumor cells, as assayed by RT–qPCR. A risk score model comprising these driver genes was further constructed, and this model was strongly negatively associated with the overall survival of patients in different datasets. The proportional hazards assumption and outlier test indicated that this model could robustly distinguish patients with different survival rates. Immune analyses and responses to immunotherapeutic and chemotherapeutic agents showed that patients in the high and low-risk groups may have distinct tendencies for clinical selection. Finally, the regions with clear H3K79me2 signal changes on these driver genes were accurately identified. Our research may offer potential molecular biomarkers for lung adenocarcinoma treatment.

Increased Expression of NXPH4 Correlates with Immune Cell Infiltration and Unfavorable Prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading malignant carcinomas. Despite the advancement in the treatment for HCC, such as precise hepatectomy, radiotherapy, transarterial therapies, chemotherapy, targeted treatments, and immunotherapy, the 5-year overall survival rate of HCC is extremely low. Hence, novel biomarkers are urgently needed for advancing the therapy and prognosis of HCC. Neurexophilin 4 (NXPH4) is a neuropeptide-like glycoprotein. The study is designed to investigate the function of NXPH4 in HCC through a comprehensive bioinformatics analysis. NXPH4 expression status and prognostic values were analyzed via multiple datasets, such as TCGA, GEO, and ICGC. The association between NXPH4 and immune cell infiltration was estimated by TIMER, TISIDB, and CIBERSORT. In vitro, we explored the biological function of NXPH4 in JHH7 and SNU182 cells through knocking down the expression of NXPH4 via siRNA. In general, NXPH4 was predominantly upregulated in HCC tumors, and increased NXPH4 expression predicted unfavorable prognosis. The gene enrichment analysis displayed that NXPH4 was related with metabolic pathways. NXPH4 expression was correlated with immune cell infiltration. NXPH4 knockdown significantly suppressed proliferation, migration, and invasion of JHH7 and SNU182 cells. This study suggested that the upregulation of NXPH4 is associated with adverse prognosis and immune cell infiltration in HCC. NXPH4 could be a novel biomarker of unfavorable prognosis and an underlying target for immunotherapy in HCC.

Glycolysis in tumor microenvironment as a target to improve cancer immunotherapy

Cancer cells and immune cells all undergo remarkably metabolic reprogramming during the oncogenesis and tumor immunogenic killing processes. The increased dependency on glycolysis is the most typical trait, profoundly involved in the tumor immune microenvironment and cancer immunity regulation. However, how to best utilize glycolytic targets to boost anti-tumor immunity and improve immunotherapies are not fully illustrated. In this review, we describe the glycolytic remodeling of various immune cells within the tumor microenvironment (TME) and the deleterious effects of limited nutrients and acidification derived from enhanced tumor glycolysis on immunological anti-tumor capacity. Moreover, we elucidate the underlying regulatory mechanisms of glycolytic reprogramming, including the crosstalk between metabolic pathways and immune checkpoint signaling. Importantly, we summarize the potential glycolysis-related targets that are expected to improve immunotherapy benefits. Our understanding of metabolic effects on anti-tumor immunity will be instrumental for future therapeutic regimen development.

Significance of ZEB2 in the immune microenvironment of colon cancer

Background: ZEB2 is a protein-coding gene that is differentially expressed in tumors and can regulate the growth of tumor cells. This study investigated the specific regulatory mechanism of ZEB2 in COAD, a common cancer with high rates of morbidity and mortality.

Methods: Multi-omics panoramic display of expression and function of ZEB2 in colon cancer. R software was used to study the expression of ZEB2 in 33 types of cancer. Furthermore, RT-PCR was used to detect the expression of ZEB2 in colon cancers and para-cancer tissues, as well as in colon cancer cells and normal cells. The ssGSEA was then used to explore the relationship between ZEB2 and immune cells, with UALCAN, EWAS and MEXPRESS applied to explore the methylation of ZEB2. The relationship between immunomodulators and chemokines (or receptors) based on expression data, copy number data, methylation data, and mutation data of ZEB2 was investigated using TISIDB. Finally, a protein interaction network of ZEB2 was constructed, and GO and KEGG analyses were performed on the differentially expressed genes.

Results: ZEB2 is downregulated in most cancers, including COAD. The infiltration of the immune cells NK CD56 and Th17 cells was negatively correlated with ZEB2 expression, while the other 22 cells were positively correlated with ZEB2 expression. The DNA methylation of ZEB2 and the methylation of the ZEB2 protein on the EWAS website increased significantly. Analysis of the methylation levels and ZEB2 expression revealed that only the DNA methylation level and the expression of ZEB2 were significantly negatively correlated. The tumor-infiltrating lymphocytes positively correlated with the expression of ZEB2 but negatively correlated with the methylation of ZEB2. The same trend was observed for immunomodulators, chemokines, and receptors. The network showed that the protein performed certain biological functions, thereby affecting disease symptoms.

Conclusion: These findings provide evidence that ZEB2-based therapy may represent a powerful treatment strategy for COAD.

Endometrial Carcinoma: Molecular Cytogenetics and Transcriptomic Profile

Endometrial carcinomas (ECs) are histologically classified as endometrioid and nonendometrioid tumors, with each subgroup displaying different molecular profiles and clinical outcomes. Considerable biological and clinical heterogeneity exists within this scheme, however, reflecting its imperfection. We aimed to gather additional data that might help clarify the tumors’ pathogenesis and contribute toward a more meaningful classification scheme. In total, 33 ECs were examined for the presence of chromosomal aberrations, genomic imbalances, pathogenic variants, microsatellite instability, and expression profiles at both gene and miRNA levels. Chromosome 1 was the most frequently rearranged chromosome, showing a gain of all or part of the long arm. Pathogenic variants were found for PTEN (53%), PDGFRA (37%), PIK3CA (34%), and KIT (31%). High microsatellite instability was identified in 15 ECs. Comparing tumors and controls, we identified 23 differentially expressed genes of known importance in carcinogenesis, 15 genes involved in innate and adaptative immune responses, and altered expression of 7 miRNAs. miR-32-5p was the most upregulated. Our series showed a high degree of heterogeneity. Tumors were well-separated from controls, but there was no clear-cut separation between endometrioid and nonendometrioid ECs. Whether this means that the current phenotypic classification is of little relevance or if one still has not detected which genomic parameters to enter into correlation analyses remains unknown.

Identification and Validation of an Apoptosis-Related Gene Prognostic Signature for Oral Squamous Cell Carcinoma

To identify an apoptosis-related gene (ARG) prediction model for oral squamous cell carcinoma (OSCC), we analyzed and validated the data from TCGA and GEO, respectively. Kaplan–Meier survival analysis and ROC curves showed a good prognostic ability of the model both in the internal training set and in the external testing set. Furthermore, we built a nomogram using these ARGs to forecast the survival probability of OSCC patients. Moreover, we evaluated the rate of immune cells infiltrating in the tumor samples and found obvious, different patterns between the high and low risk groups. GO and KEGG analyses demonstrated multiple molecular biological processes and signaling pathways connecting with this prognostic model in OSCC. The expression of these risk genes in clinical specimens was higher in the non-survival patients than in the well-survival patients by immunohistochemical staining analysis. In conclusion, we established a signature made up of six risk apoptosis-related genes to predict the survival rate of OSCC. These genes could also be targets for the treatment of OSCC.

GPI: An indicator for immune infiltrates and prognosis of human breast cancer from a comprehensive analysis

Glucose-6-phosphate isomerase (GPI) plays an important part in gluconeogenesis and glycolysis through the interconversion of d-glucose-6-phosphate and d-fructose-6-phosphate, and its clinical significance still remains unclear in breast cancer (BRCA). We analyzed the expressions of GPI in BRCA patients to determine prognostic values. Our results showed that the expression levels of GPI were upregulated in BRCA patients, and a high GPI expression is correlated with poor overall survival (OS) in BRCA. At the same time, a high GPI expression is correlated with poor clinicopathological characteristics, such as stage III, over 60 years old, N3, HER2 negative, and estrogen receptor (ER) positive. Further analysis of the influence of GPI on the prognosis of BRCA suggested that 50 genes and 10 proteins were positively correlated with GPI, and these genes and proteins were mainly involved in cell cycle signaling pathways. In addition, in this study, we observed that GPI was closely related to N ⁶-methyladenosine (m6A) RNA methylation modification and immune cell infiltration and ferroptosis-related gene expression in BRCA, and there was a difference in m6A RNA methylation alterations, immune cell infiltration, and ferroptosis-related gene expression between the high GPI expression group and the low GPI expression group. Finally, we found that GPI in BRCA had 2.6% gene alterations, and BRCA patients with gene alteration of GPI had a poor prognosis in disease-free survival (DFS). Altogether, our work strongly suggested that GPI may serve as a new prognostic biomarker for BRCA patients.