A glycolysis-related gene expression signature in predicting recurrence of breast cancer

A protein-based prognostic model for pancreatic ductal adenocarcinoma: Construction and validation

BACKGROUND

Probing relevant proteomic biomarkers may facilitate effective pancreatic adenocarcinoma (PDAC) diagnosis, treatment and prevention. Here, we developed a protein-based prognostic model for PDAC by using relevant proteomic biomarkers data from The Cancer Genome Atlas (TCGA).

METHODS

We obtained PDAC's proteomic and clinical data from TCGA and used various analytical tools to identify differentially expressed proteins between normal and cancer tissues. We constructed our protein-based prognostic model and confirmed its accuracy using receiver operating characteristic curve and Kaplan-Meier survival analyses. We elucidated clinical factor-signature protein correlations by clinical correlation assessments and protein coexpression networks. We also used immunohistochemistry (protein expression assessment), Gene Set Enrichment Analysis (protein role identification) and CIBERSORT (infiltrating immune cell distribution assessment).

RESULTS

CIITA, BRAF_pS445, AR, YTHDF2, IGFBP2 and CDK1_pT14 were identified as PDAC-associated prognostic proteins. All risk scores calculated using our model provided 1-, 3-, 5-year survival probability at 70 % accuracy. The reliability of our model was validated by the GEO as well. In high- and low-risk groups, age, sex, T- and N- stage disparities were significant, and prognostic and coexpressed proteins correlated. PDAC tissues demonstrated significant CDK1_pT14 overexpression but significant BRAF_pS445, YTHDF2, and IGFBP2 underexpression. Downstream proteins of BRAF were validated by IHC. Low-risk tissues demonstrated more naïve B cells, eosinophils, activated NK cells and regulatory T cells, whereas high-risk tissues demonstrated more activated memory T cells, monocytes, neutrophils, dendritic cells and resting NK cells.

CONCLUSIONS

Our protein-based prognostic model for PDAC, along with six signature proteins, might aid in predicting PDAC prognosis and therapeutic targets.

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Background

High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.

Materials and methods

Microarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package 'Limma'. We used the Metascape tool for enrichment analyses, and 'WGCNA' was utilized to establish co-expression networks, selecting the soft threshold power with the 'pickSoftThreshold' algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.

Results

Our analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60-6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95-0.86), with a C-index of 0.85 (95% CI: 0.81-0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.

Conclusion

This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

Prognostic value of amino acid metabolism-related gene expression in invasive breast carcinoma

BACKGROUND

An increasing number of studies indicated that metabolic reprogramming of amino acid metabolism may either promote or inhibit tumor progression. The purpose of this study was to investigate the ability of a gene risk signature associated with amino acid metabolism to predict the prognosis and immune characteristics of invasive breast carcinoma.

METHODS

LASSO Cox regression analysis was performed to construct and validate the prognostic risk signature based on the expression of 9 amino acid metabolism-related genes. The predictive value of the signature, immune characteristics, and chemotherapeutic drugs was also predicted. Finally, 9 significant genes were examined in MDA-MB-231 and MCF-7 cells, and the predicted chemotherapeutic drugs were also verified.

RESULTS

The prognosis of the low-risk group was better than that of the high-risk group. The areas under the curve (AUCs) at 1, 2, and 3 years were 0.852, 0.790, and 0.736, respectively. In addition, the GSEA results for KEGG and GO revealed that samples with a high-risk score exhibited a variety of highly malignant manifestations. The high-risk group was characterized by an increased number of M2 macrophages, a high level of tumor purity, low levels of APC co-stimulation, cytolytic activity, HLA, para-inflammation, and type I IFN response. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) confirmed that MDA-MB-231 and MCF-7 cells express 9 amino acid metabolism-related genes differently. In addition, cell experiments were conducted to examine the effect of cephaeline-induced on cell viability, migration ability, and protein expression of the PI3K/AKT signaling pathway and HIF-1α.

CONCLUSION

We established a risk signature based on 9 amino acid metabolism-related genes for invasive breast carcinoma. Further analyses revealed that this risk signature is superior to other clinical indexes in survival prediction and that the subgroups identified by the risk signature exhibit distinct immune characteristics. Cephaeline was determined to be a superior option for patients in high-risk groups.

STNM1 in human cancers: role, function and potential therapy sensitizer

STMN1 belongs to the stathmin gene family, it encodes a cytoplasmic phosphorylated protein, stathmin1, which is commonly observed in vertebrate cells. STMN1 is a structural microtubule-associated protein (MAP) that binds to microtubule protein dimers rather than microtubules, with each STMN1 binding two microtubule protein dimers and preventing their aggregation, leading to microtubule instability. STMN1 expression is elevated in a number of malignancies, and inhibition of its expression can interfere with tumor cell division. Its expression can change the division of tumor cells, thereby arresting cell growth in the G2/M phase. Moreover, STMN1 expression affects tumor cell sensitivity to anti-microtubule drug analogs, including vincristine and paclitaxel. The research on MAPs is limited, and new insights on the mechanism of STMN1 in different cancers are emerging. The effective application of STMN1 in cancer prognosis and treatment requires further understanding of this protein. Here, we summarize the general characteristics of STMN1 and outline how STMN1 plays a role in cancer development, targeting multiple signaling networks and acting as a downstream target for multiple microRNAs, circRNAs, and lincRNAs. We also summarize recent findings on the function role of STMN1 in tumor resistance and as a therapeutic target for cancer.

A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma

Background

Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a glycometabolic gene signature to forecast the prognosis, and provide therapeutic options for patients with OS.

Methods

Univariate and multivariate Cox regression, LASSO Cox regression, overall survival analysis, receiver operating characteristic curve, and nomogram were adopted to develop the glycometabolic gene signature, and further evaluate the prognostic values of this signature. Functional analyses including Gene Ontology (GO), kyoto encyclopedia of genes and genomes analyses (KEGG), gene set enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), and competing endogenous RNA (ceRNA) network, were used to explore the molecular mechanisms of OS and the correlation between immune infiltration and gene signature. Moreover, these prognostic genes were further validated by immunohistochemical staining.

Results

A total of four genes including PRKACB, SEPHS2, GPX7, and PFKFB3 were identified for constructing a glycometabolic gene signature which had a favorable performance in predicting the prognosis of patients with OS. Univariate and multivariate Cox regression analyses revealed that the risk score was an independent prognostic factor. Functional analyses indicated that multiple immune associated biological processes and pathways were enriched in the low-risk group, while 26 immunocytes were down-regulated in the high-risk group. The patients in high-risk group showed elevated sensitivity to doxorubicin. Furthermore, these prognostic genes could directly or indirectly interact with other 50 genes. A ceRNA regulatory network based on these prognostic genes was also constructed. The results of immunohistochemical staining showed that SEPHS2, GPX7, and PFKFB3 were differentially expressed between OS tissues and adjacent normal tissues.

Conclusion

The preset study constructed and validated a novel glycometabolic gene signature which could predict the prognosis of patients with OS, identify the degree of immune infiltration in tumor microenvironment, and provide guidance for the selection of chemotherapeutic drugs. These findings may shed new light on the investigation of molecular mechanisms and comprehensive treatments for OS.

Isoliquiritin modulates ferroptosis via NF-κB signaling inhibition and alleviates doxorubicin resistance in breast cancer

CONTEXT

Breast cancer (BC) is the most prevalent diagnosed tumor and the major reason for tumor-related death in females around the world. Isoliquiritin, a type of plant extract, has exhibited a probable inhibitory effect in a variety of cancers. However, the anti-tumor effect on BC is still unclear.

OBJECTIVE

To reveal the effect and potential mechanism of Isoliquiritin on BC.

MATERIALS AND METHODS

The cell viabilities were detected by CCK-8 assay. The levels of indicators of ferroptosis, oxidative stress, glycolysis, and inflammation were evaluated by commercial kits, flow cytometry, western blot, spectrophotometry, and ELISA assays. Mechanically, the expressions expression of the NF-κB pathway was determined by western blot. In vivo assay was also yielded on the BALB/c nude mice.

RESULTS

Iso induced a concentration and time-dependent decrease of viability in both MDA-MB-231 and MCF-7 cells. Iso treatment significantly increased the levels of Fe²⁺, ROS, and MDA, and decreased the GSH level, and the relative protein expressions of GPX4 and xCT. Furthermore, Iso modulated oxidative stress, glycolysis, and inflammation through ferroptosis. In addition, Iso induced a concentration-dependent decrease in cell viability and a concentration-dependent increase in apoptosis rate in both MDA-MB-231/Dox and MCF-7/Dox cells. Iso notably counteracted the LPS-induced relative protein levels of p-p50/p50, p-p65/p65, and IκB, and the levels of ferroptosis, oxidative stress, glycolysis, and inflammation. The same results were also verified in vivo.

CONCLUSION

Iso inhibited the NF-κB signaling to regulate ferroptosis and improved Dox-resistance in breast cancer.

Trojan-horse silk fibroin nanocarriers loaded with a re-call antigen to redirect immunity against cancer

BACKGROUND

The current challenge for immunotherapies is to generate effective antitumor immunity. Since tumor immune escape mechanisms do not impact pre-existing and consolidated immune responses, we tested the hypothesis of redirecting a pregenerated immunity to cancer: to recall a non-tumor antigen response against the tumor, silk fibroin nanoparticles (SFNs) have been selected as 'Trojan-horse' carriers, promoting the antigen uptake by the tumor cells.

METHODS

SFNs have been loaded with either ovalbumin (OVA) or CpG oligonucleotide (CpG) as antigen or adjuvant, respectively. In vitro uptake of SFNs by tumor (B16/F10 melanoma and MB49 bladder cancer) or dendritic cells, as well as the presence of OVA-specific T cells in splenic and tumor-infiltrating lymphocytes, were assessed by cytometric analyses. Proof-of-concept of in vivo efficacy was achieved in an OVA-hyperimmune B16/F10 murine melanoma model: SFNs-OVA or SFNs-CpG were injected, separately or in association, into the subcutaneous peritumoral area. Cancer dimensions/survival time were monitored, while, at the molecular level, system biology approaches based on graph theory and experimental proteomic data were performed.

RESULTS

SFNs were efficiently in vitro uptaken by cancer and dendritic cells. In vivo peritumor administration of SFNs-OVA redirected OVA-specific cytotoxic T cells intratumorally. Proteomics and systems biology showed that peritumoral treatment with either SFNs-OVA or SFNs-CpG dramatically modified tumor microenvironment with respect to the control (CTR), mainly involving functional modules and hubs related to angiogenesis, inflammatory mediators, immune function, T complex and serpins expression, redox homeostasis, and energetic metabolism. Both SFNs-OVA and SFNs-CpG significantly delayed melanoma growth/survival time, and their effect was additive.

CONCLUSIONS

Both SFNs-OVA and SFNs-CpG induce effective anticancer response through complementary mechanisms and show the efficacy of an innovative active immunotherapy approach based on the redirection of pre-existing immunity against cancer cells. This approach could be universally applied for solid cancer treatments if translated into the clinic using re-call antigens of childhood vaccination.

Prognostic implication and immunotherapy response prediction of a ubiquitination-related gene signature in breast cancer

Breast cancer (BC) is one of the most common tumor types and has poor outcomes. In this study, a ubiquitination-related prognostic signature was constructed, and its association with immunotherapy response in BC was explored. A list of ubiquitination-related genes was obtained from the molecular signatures database, and a ubiquitination-related gene signature was obtained by least absolute shrinkage and selection operator Cox regression. The genes, TCN1, DIRAS3, and IZUMO4, had significant influence on BC outcomes. Patients were categorized into two clusters-a high-risk group with poor survival and a low-risk group with greater chances of controlling BC progression. Univariate and multivariate Cox regression analyses revealed that the risk signature was an independent prognostic factor for BC. Gene set enrichment analysis suggested that the high-risk group was enriched in cell cycle and DNA replication pathways. The risk score was positively linked to the tumor microenvironment and negatively correlated with the immunotherapy response. The IC50 values for rapamycin were higher in the low-risk group, whereas those for axitinib, AZD6244, erlotinib, GDC0941, GSK650394, GSK269962A, lapatinib, and PD0325901 were higher in the high-risk group. Therefore, the ubiquitination-related signature is considered a promising tool for predicting a BC patient's immunotherapy response.

A Novel Glycolysis-Related Gene Signature Predicts Prognosis For Cutaneous Melanoma

BACKGROUND

There exists a lack of effective tools predicting prognosis for cutaneous melanoma patients. Glycolysis plays an essential role in the carcinogenesis process.

OBJECTIVE

We intended to construct a new prognosis model for cutaneous melanoma.

METHODS

Based on the data from the TCGA database, we conducted a univariate Cox regression analysis and identified prognostic glycolysis-related genes (GRGs). Meanwhile, the GSE15605 dataset was used to identify differentially expressed genes (DEGs). The intersection of prognostic GRGs and DEGs was extracted for the subsequent multivariate Cox regression analysis.

RESULTS

A prognostic signature containing ten GRGs was built, and the TCGA cohort was classified into high and low risk subgroups based on the risk score of each patient. K-M analysis manifested that the overall survival of the high-risk group was statistically worse than that of the lowrisk group. Further study indicated that the risk-score could be used as an independent prognostic factor that effectively predicted the clinical prognosis in patients of different ages, genders, and stages. GO and KEGG enrichment analysis showed DEGs between high and low risk groups were enriched in immune-related functions and pathways. In addition, a significant difference existed between high and low risk groups in infiltration pattern of immune cells and expression levels of inhibitory immune checkpoint genes.

CONCLUSION

A new glycolysis-related gene signature was established for identifying cutaneous melanoma patients with poor prognoses and formulating individualized treatment.

Inhibition of glycolysis represses the growth and alleviates the endoplasmic reticulum stress of breast cancer cells by regulating TMTC3

Considering the role of glycolysis inhibition as a novel therapeutic strategy for cancer, including breast cancer (BC), we wondered whether glycolysis could affect BC progression by regulating transmembrane O-mannosyltransferase-targeting cadherins 3 (TMTC3). Following the intervention, lactic acid production in BC cells was monitored, and viability, proliferation, and apoptosis assays were performed. The expressions of TMTC3 and endoplasmic reticulum (ER) stress- and apoptosis-related factors Caspase-12, C/EBP homologous protein (CHOP), glucose-regulated protein 78 (GRP78), B-cell lymphoma-2 (Bcl-2), and Bcl-2 associated X (Bax) were quantified. TMTC3 was lowly expressed in BC tissue and cell. The promotion of glycolysis via glucose represses TMTC3 expression and apoptosis yet enhances lactic acid production and growth of BC cell, along with promoted levels of Caspase-12, CHOP, GRP78, and Bcl-2 yet repressed level of Bax, while the contrary results were evidenced after 2-deoxyglycouse intervention. Overexpressed TMTC3 additionally abrogated the effects of glycolysis on increasing the viability and proliferation yet inhibiting the apoptosis of BC cells, with the increased expressions of Caspase-12, CHOP, and GRP78, and Bcl-2 yet decreased level of Bax. Collectively, inhibiting glycolysis restrained the growth and attenuated the ER stress of BC cell by regulating TMTC3.

Identification of Circular RNA Circ_0003256 as a Novel Player in Pediatric Acute Myeloid Leukemia

BACKGROUND

Aberrant expression of circular RNAs (circRNAs) is tightly associated with the pathogenesis of human cancers, including pediatric acute myeloid leukemia (AML). In this report, we sought to define the precise action of circ_0003256 in the pathogenesis of pediatric AML.

MATERIALS AND METHODS

Circ_0003256, microRNA (miR)-582-3p, and protein kinase cAMP-activated catalytic subunit beta (PRKACB) were quantified by quantitative real-time polymerase chain reaction and Western blot. Cell proliferation, cycle distribution, and apoptosis were estimated by MTT, 5-ethynyl-2'-deoxyuridine, and flow cytometry assays, respectively. Direct relationships among circ_0003256, miR-582-3p, and PRKACB were verified by a dual-luciferase reporter and RNA pull-down assays.

RESULTS

Our data indicated that circ_0003256 was highly expressed in pediatric AML patients and cells. Suppression of circ_0003256 hindered cell proliferation and promoted apoptosis in THP-1 and MV4-11 cells. Mechanistically, circ_0003256 contained functional binding sites for miR-582-3p, and circ_0003256 suppression influenced cell behaviors by upregulating miR-582-3p. MiR-582-3p directly targeted and inhibited PRKACB and the inhibition of PRKACB phenocopied miR-582-3p overexpression in regulating cell functional behaviors. Moreover, circ_0003256 involved the posttranscriptional regulation of PRKACB through miR-582-3p.

CONCLUSION

Our findings identify that suppression of circ_0003256 impedes the malignant behaviors of pediatric AML cells by regulating PRKACB expression by competing for shared miR-582-3p.

Docetaxel suppressed cell proliferation through Smad3/HIF-1α-mediated glycolysis in prostate cancer cells

BACKGROUND

Tumor glycolysis is a critical event for tumor progression. Docetaxel is widely used as a first-line drug for chemotherapy and shown to have a survival advantage. However, the role of docetaxel in tumor glycolysis remained poorly understood.

METHODS

The effect of Docetaxel in tumor glycolysis and proliferation were performed by CCK-8, Western blotting, real-time PCR, glucose, and lactate detection and IHC. ChIP and luciferase assay were used to analyze the mechanism of Docetaxel on Smad3-mediated HIF-1α transactivity.

RESULTS

In this study, we showed that docetaxel treatment led to a significant inhibition of cell proliferation in prostate cancer cells through PFKP-mediated glycolysis. Addition of lactate, a production of glycolysis, could reverse the inhibitory effect of docetaxel on cell proliferation. Further analysis has demonstrated that phosphorylation of Smad3 (Ser213) was drastically decreased in response to docetaxel stimulation, leading to reduce Smad3 nuclear translocation. Luciferase and Chromatin immunoprecipitation (ChIP) analysis revealed that docetaxel treatment inhibited the binding of Smad3 to the promoter of the HIF-1α gene, suppressing transcriptional activation of HIF-1α. Moreover, ectopic expression of Smad3 in prostate cancer cells could overcome the decreased HIF-1α expression and its target gene PFKP caused by docetaxel treatment. Most importantly, endogenous Smad3 regulated and interacted with HIF-1α, and this interaction was destroyed in response to docetaxel treatment. What's more, both HIF-1α and PFKP expression were significantly reduced in prostate cancer received docetaxel treatment in vivo.

CONCLUSION

These findings extended the essential role of docetaxel and revealed that docetaxel inhibited cell proliferation by targeting Smad3/HIF-1α signaling-mediated tumor Warburg in prostate cancer cells. Video Abstract.

Increased tumor glycolysis is associated with decreased immune infiltration across human solid tumors

Response to immunotherapy across multiple cancer types is approximately 25%, with some tumor types showing increased response rates compared to others (i.e. response rates in melanoma and non-small cell lung cancer (NSCLC) are typically 30-60%). Patients whose tumors are resistant to immunotherapy often lack high levels of pre-existing inflammation in the tumor microenvironment. Increased tumor glycolysis, acting through glucose deprivation and lactic acid accumulation, has been shown to have pleiotropic immune suppressive effects using in-vitro and in-vivo models of disease. To determine whether the immune suppressive effect of tumor glycolysis is observed across human solid tumors, we analyzed glycolytic and immune gene expression patterns in multiple solid malignancies. We found that increased expression of a glycolytic signature was associated with decreased immune infiltration and a more aggressive disease across multiple tumor types. Radiologic and pathologic analysis of untreated estrogen receptor (ER)-negative breast cancers corroborated these observations, and demonstrated that protein expression of glycolytic enzymes correlates positively with glucose uptake and negatively with infiltration of CD3⁺ and CD8⁺ lymphocytes. This study reveals an inverse relationship between tumor glycolysis and immune infiltration in a large cohort of multiple solid tumor types.

A novel risk score model based on glycolysis-related genes and a prognostic model for predicting overall survival of osteosarcoma patients

This study aims to construct a novel risk score model based on glycolysis-related genes in osteosarcoma and to build and validate a prognostic model for predicting overall survival of patients with osteosarcoma. The transcriptome data and corresponding clinical data of patients with osteosarcoma were obtained from The Cancer Genome Atlas (TCGA) as the training set, and from Gene Expression Omnibus (GEO) database as the validation set. Univariate Cox regression analysis was used to screen the prognostic glycolysis-related genes. The risk coefficient of each glycolysis-related gene was calculated using LASSO regression analysis. Using the median risk score as the cut-off point, patients were divided into high-risk and low-risk groups. Kaplan-Meier survival analysis was used to determine whether there was a significant difference in the overall survival between the two groups. The nomogram was constructed according to the results of multivariate Cox regression. The C-index was calculated, the calibration chart, clinical decision curve and receiver operating characteristic curve were drawn to evaluate the predictive performance of the nomogram. We performed Gene Ontology and Kyoto encyclopedia of genes and genomics enrichment analysis to explore the potential mechanism of prognostic-related glycolysis genes in osteosarcoma. A total of 88 and 53 cases were obtained from the TCGA and GEO database, respectively. A total of 10 key glycolytic genes related to prognosis were screened out. The Kaplan-Meier survival curve revealed that the overall survival of the high-risk group was significantly shorter than that of the low-risk group. The C indices of the training set and the verification set were 0.882 and 0.828, respectively. Our findings will provide further understanding of clinical prognostic outcomes of osteosarcoma patients.

STMN1 as a novel prognostic biomarker in HCC correlating with immune infiltrates and methylation

Background

Upregulation of Stathmin 1 (STMN1), a cytoplasmic phosphoprotein that controls the dynamics of cellular microtubules, is linked to malignant behavior and poor prognosis in a range of malignancies. However, little research has been done on STMN1’s potential role in HCC as a single factor in DNA methylation, m⁶A, or immunological modulation.

Results

STMN1 is overexpressed in hepatocellular carcinoma, where it is related to clinicopathological parameters and affects the prognosis of HCC patients. STMN1 overexpression plays an important role in the diagnosis and prognosis of hepatocellular carcinoma. Meanwhile, methylation of 7 CpG sites of STMN1 in HCC was correlated with prognosis, and STMN1 expression was closely related to m⁶A modification. In addition, STMN1 expression is associated with immune cell infiltration, immune molecules, and immune checkpoints in HCC.

Conclusion

STMN1 has a significant role in hepatocellular carcinoma diagnosis and prediction. STMN1 is implicated not just in the onset and course but also in the immunological modulation of the disease. DNA methylation and m⁶A are both linked to STMN1. Therefore, STMN1 could be used as a diagnostic and prognostic biomarker for HCC, as well as a target for immunotherapy.

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq

Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

CFDP1 promotes hepatocellular carcinoma progression through activating NEDD4/PTEN/PI3K/AKT signaling pathway

BACKGROUND AND AIMS

It is being increasingly reported that the Cranio Facial Development Protein 1 (CFDP1) plays a significant role in the onset and progression of tumors. Nonetheless, the underlying mechanisms associated with CFDP1 that contribute to hepatocellular carcinoma (HCC) and the specific biological role of CFDP1 remain vague.

METHODS

The Gene Expression Omnibus (GEO) database was analyzed to obtain the gene expression profiles as well as the matching clinical data of HCC patients. The gene co-expression network was developed by means of weighted gene co-expression network analysis (WGCNA) to screen for possible biomarkers that could be used for the purpose of predicting prognosis. The Cancer Genome Atlas (TCGA) and Gene Expression Profile Interaction Analysis (GEPIA) databases were used to assess the relationship between survival and expression. In addition, we identified the underlying mechanism associated with CFDP1 by analyzing the KEGG pathway database, applying the GSEA and GeneCards analysis method. We performed a sequence of experiments (in vivo and in vitro) for the purpose of investigating the specific function of CFDP1 in liver cancer.

RESULTS

The obtained results revealed high expression of CFDP1 in HCC tissues and cell lines. A positive correlation between the overexpression of CFDP1 and the adverse clinicopathological features was observed. Moreover, we observed that the low recurrence-free survival and overall survival were associated with CFDP1 overexpression. In addition, GeneCards and GSEA analysis showed that CFDP1 may interact with NEDD4 and participate in PTEN regulation. Meanwhile, CFDP1 can promote the malignant development of liver cancer in vivo and in vitro. The western blotting technique was also employed so as to examine the samples, and the findings demonstrated that CFDP1 enhanced the malignancy of HCC via the NEDD4-mediated PTEN/PI3K/AKT pathway.

CONCLUSION

We highlighted that CFDP1 played an oncogenic role in HCC and was identified as a possible clinical prognostic factor and a potential novel therapeutic target for HCC.

N7-Methylguanosine Regulatory Genes Profoundly Affect the Prognosis, Progression, and Antitumor Immune Response of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a common abdominal cancer with poor survival outcomes. Although there is growing evidence that N7-methylguanosine (m7G) is closely associated with tumor prognosis, development, and immune response, few studies focus on this topic.

Methods

The novel m7G risk signature was constructed through the Lasso regression analysis. Its prognostic value was evaluated through a series of survival analyses and was tested in ICGC-LIRI, GSE14520, and GSE116174 cohorts. CIBERSORT, ssGSEA, and ESTIMATE methods were applied to explore the effects of the m7G risk score on tumor immune microenvironment (TIM). The GSEA method was used to evaluate the impacts of the m7G risk score on glycolysis, ferroptosis, and pyroptosis. The human protein atlas (HPA) database was used to clarify the histological expression levels of five m7G signature genes. The biofunctions of NCBP2 in hepatocellular cancer (HC) cells were confirmed through qPCR, CCK8, and transwell assays.

Results

Five m7G regulatory genes comprised the novel risk signature. The m7G risk score was identified as an independent prognostic factor of HCC and could increase the decision-making benefit of traditional prognostic models. Besides, we established a nomogram containing the clinical stage and m7G risk score to predict the survival rates of HCC patients. The prognostic value of the m7G model was successfully validated in ICGC and GSE116174 cohorts. Moreover, high m7G risk led to a decreased infiltration level of CD8+ T cells, whereas it increased the infiltration levels of Tregs and macrophages. The glycolysis and pyroptosis processes were found to be enriched in the HCC patients with high m7G risk. Finally, overexpression of NCBP2 could promote the proliferation, migration, and invasion of HC cells.

Conclusions

The m7G risk score was closely related to the prognosis, antitumor immune process, glycolysis, and malignant progression of HCC. NCBP2 has pro-oncogenic abilities, showing promise as a novel treatment target.

Predicting Differences in Treatment Response and Survival Time of Lung Adenocarcinoma Patients Based on a Prognostic Risk Model of Glycolysis-Related Genes

Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified.

Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score.

Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups.

Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.

Prognostic significance of a 4-lncRNA glycolysis-related signature in oral squamous cell carcinoma

BACKGROUND/PURPOSE

Oral squamous cell carcinoma (OSCC) is a highly malignant tumor, and the overall survival (OS) time of patients with OSCC varies considerably. This study aimed to identify reliable biomarkers for OSCC and construct a new prognostic signature, which may guide personalized precision treatment.

MATERIALS AND METHODS

Transcriptome array data of 317 patients with OSCC from The Cancer Genome Atlas Project (TCGA) cohort were retrospectively analyzed. Single-sample gene set enrichment analysis (ssGSEA) and univariate Cox regression were performed to identify the prognostic significance of the hallmarks of each tumor in OSCC. Subsequently, lncRNAs related to glycolysis were identified through co-expression analysis. A glycolysis-related prognostic signature was constructed by combining univariate Cox regression, least absolute shrinkage and selection operator (Lasso) regression, and multivariate Cox regression analyses. Additionally, the infiltration of immune cells in OSCC was evaluated based on data from ssGSEA and TIMER databases.

RESULTS

Glycolysis was identified as the main risk factor for OS in a variety of cancer hallmarks. The 4-lncRNA glycolysis prognostic signature could distinguish high and low-risk patients. This risk signature was found to be an independent prognostic risk factor for OSCC, showing good predictive power compared with other clinicopathological indicators. Immune correlation analysis showed that patients in the low-risk group exhibited higher levels of immune cell infiltration.

CONCLUSION

The novel 4-lncRNA prognostic signature can predict the clinical outcome of patients with OSCC well, and it is expected to become a promising prognostic biomarker as well as a potential therapeutic target in the future.

Circ_0001955 plays a carcinogenic role in breast cancer via positively regulating GLUT1 via decoying miR-1299

BACKGROUND

Breast cancer is widespread in females. The role of circular RNA (circRNA) in breast cancer has aroused much attention. However, the function of several circRNAs remain unclear. The aim of our study was to determine the role of circ_0001955 in breast cancer.

METHODS

Quantitative real-time PCR (qPCR) and western blot was employed for expression analysis of circ_0001955, miR-1299 and glucose transporter 1 (GLUT1). Cell functions including proliferation, apoptosis, migration, invasion and angiogenesis, were assessed using EdU, flow cytometry, transwell and tube formation assays. Glycolysis metabolism was assessed according to glucose consumption, lactate production and ATP content. Dual-luciferase reporter assay and RIP assay were utilized to validate the binding between miR-1299 and circ_0001955 or GLUT1. The effects of circ_0001955 in vivo were observed by animal study.

RESULTS

Upregulation of circ_0001955 was detected in breast cancer. Knockdown of circ_0001955 inhibited breast cancer cell proliferation, migration, invasion, angiogenesis and glycolysis. MiR-1299 was a target of circ_0001955, and its repression reversed the effects of circ_0001955 knockdown. Moreover, circ_0001955 targeted miR-1299 to positively regulate GLUT1 expression. GLUT1 overexpression reversed the effects of miR-1299 enrichment. GLUT1 knockdown was verified to block tumor growth in vivo.

CONCLUSIONS

Circ_0001955 was found to promote breast cancer malignant development via targeting of the miR-1299/GLUT1 pathway, which contributes to our understanding of the pathogenesis of breast cancer.

Identification and Verification of Necroptosis-Related Gene Signature and Associated Regulatory Axis in Breast Cancer

Background: Breast invasive carcinoma (BRCA) is the second leading cause of malignancy death among women. Necroptosis is a newly discovered mechanism of cell death involved in the progression and prognosis of cancer. The role of necroptosis-related genes (NRGs) in BRCA is still a mystery.

Methods: LASSO Cox regression analysis was performed to construct a prognostic necroptosis-related signature. A ceRNA was constructed to explore the potential lncRNA-miRNA-mRNA regulatory axis in BRCA.

Results: A total of 63 necroptosis-related genes were differentially expressed in BRCA. We also summarized the genetic mutation landscape of NRGs in BRCA. BRCA patients with low expression of BCL2 and LEF1, as well as high expression of PLK1 and BNIP3, had a poor OS, DSS, and DFS. A necroptosis-related prognostic signature with four genes (BCL2, LEF1, PLK1, and BNIP3) was constructed, and it could serve as a prognosis biomarker in BRCA, predicting the OS rate with medium to high accuracy. Moreover, the risk score was correlated with immune infiltration in BRCA. Further comprehensive analysis revealed that the expression of BCL2, LEF1, PLK1, and BNIP3 was correlated with tumor mutation burden, microsatellite instability, drug sensitivity, and pathology stage. Previous studies have been extensively studied. The roles of LEF1, PLK1, and BNIP3 in BRCA and BCL2 were selected for further analysis. We then constructed a ceRNA network, which identified an lncRNA LINC00665/miR-181c-5p/BCL2 regulatory axis for BRCA.

Conclusion: The bioinformatics method was performed to develop a prognostic necroptosis-related prognostic signature containing four genes (BCL2, LEF1, PLK1, and BNIP3) in BRCA. We also constructed a ceRNA network and identified an lncRNA LINC00665/miR-181c-5p/BCL2 regulatory axis for BRCA. Further in vivo and in vitro studies should be conducted to verify these results.

Male Breast Carcinoma Metastatic to the Choroid: A Case Report and Opinions of Management

Male breast carcinoma metastatic to the choroid is very rare and often related to poor prognosis. Herein, we report the findings in a Chinese male breast cancer patient who developed choroidal metastasis, and give opinions on systemic treatments. A 45-year-old Chinese male represented with difficulty breathing and visual impairment in the left eye 6 years after his breast cancer surgery and postoperative adjuvant treatment. PET/CT revealed multi-organs metastasis of the patient. The IHC indicated the lung lesion to be originated from the breast (ER+/PR+/HER2-). Eye examination provided evidence for breast cancer choroidal metastasis. Two cycles of TX (docetaxel + capecitabine) followed by two courses of GP (gemcitabine + cis-platinum) were applied as salvage chemotherapy. Metastases in his lung and bone remained stable. As for choroidal metastasis, a regimen of CDK4/6 inhibitor (Palbociclib) plus fulvestrant was recommended to the patient, which led to a good response. Notably, CDK4/6 inhibitor combined with endocrine therapy may be considered as an effective treatment for hormonal receptor-positive breast cancer patients with choroidal metastasis. We recommend that eye examination should not be neglected in breast cancer patients.

STMN1 is highly expressed and contributes to clonogenicity in acute promyelocytic leukemia cells

Stathmin 1 (STMN1) is a microtubule-destabilizing protein highly expressed in hematological malignancies and involved in proliferation and differentiation. Although a previous study found that the PML-RARα fusion protein, which contributes to the pathophysiology of acute promyelocytic leukemia (APL), positively regulates STMN1 at the transcription and protein activity levels, little is known about the role of STMN1 in APL. In this study, we aimed to investigate the STMN1 expression levels and their associations with laboratory, clinical, and genomic data in APL patients. We also assessed the dynamics of STMN1 expression during myeloid cell differentiation and cell cycle progression, and the cellular effects of STMN1 silencing and pharmacological effects of microtubule-stabilizing drugs on APL cells. We found that STMN1 transcripts were significantly increased in samples from APL patients compared with those of healthy donors (all p < 0.05). However, this had no effect on clinical outcomes. STMN1 expression was associated with proliferation- and metabolism-related gene signatures in APL. Our data confirmed that STMN1 was highly expressed in early hematopoietic progenitors and reduced during cell differentiation, including the ATRA-induced granulocytic differentiation model. STMN1 phosphorylation was predominant in a pool of mitosis-enriched APL cells. In NB4 and NB4-R2 cells, STMN1 knockdown decreased autonomous cell growth (all p < 0.05) but did not impact ATRA-induced apoptosis and differentiation. Finally, treatment with paclitaxel (as a single agent or combined with ATRA) induced microtubule stabilization, resulting in mitotic catastrophe with repercussions for cell viability, even in ATRA-resistant APL cells. This study provides new insights into the STMN1 functions and microtubule dynamics in APL.

Therapeutic Targeting of Cancer: Epigenetic Homeostasis

A large number of studies have revealed that epigenetics plays an important role in cancer development. However, the currently-developed epigenetic drugs cannot achieve a stable curative effect. Thus, it may be necessary to redefine the role of epigenetics in cancer development. It has been shown that embryonic development and tumor development share significant similarities in terms of biological behavior and molecular expression patterns, and epigenetics may be the link between them. Cell differentiation is likely a manifestation of epigenetic homeostasis at the cellular level. In this article, we introduced the importance of epigenetic homeostasis in cancer development and analyzed the shortcomings of current epigenetic treatment regimens. Understanding the dynamic process of epigenetic homeostasis in organ development can help us characterize cancer according to its differentiation stages, explore new targets for cancer treatment, and improve the clinical prognosis of patients with cancer.