Recombinant Viral Capsid Protein L2 (rVL2) of HPV 16 Suppresses Cell Proliferation and Glucose Metabolism via ITGB7/C/EBPβ Signaling Pathway in Cervical Cancer Cell Lines

DPEP Inhibits Cancer Cell Glucose Uptake, Glycolysis and Survival by Upregulating Tumor Suppressor TXNIP

We have designed cell-penetrating peptides that target the leucine zipper transcription factors ATF5, CEBPB and CEBPD and that promote apoptotic death of a wide range of cancer cell types, but not normal cells, in vitro and in vivo. Though such peptides have the potential for clinical application, their mechanisms of action are not fully understood. Here, we show that one such peptide, Dpep, compromises glucose uptake and glycolysis in a cell context-dependent manner (in about two-thirds of cancer lines assessed). These actions are dependent on induction of tumor suppressor TXNIP (thioredoxin-interacting protein) mRNA and protein. Knockdown studies show that TXNIP significantly contributes to apoptotic death in those cancer cells in which it is induced by Dpep. The metabolic actions of Dpep on glycolysis led us to explore combinations of Dpep with clinically approved drugs metformin and atovaquone that inhibit oxidative phosphorylation and that are in trials for cancer treatment. Dpep showed additive to synergistic activities in all lines tested. In summary, we find that Dpep induces TXNIP in a cell context-dependent manner that in turn suppresses glucose uptake and glycolysis and contributes to apoptotic death of a range of cancer cells.

EccDNA-oriented ITGB7 expression in breast cancer

Background

Extrachromosomal circular DNA (eccDNA) is omnipresent in cancers and related to the progression of tumors and oncogene amplification. However, its function in breast cancer (BC) is unclear.

Methods

After constructing the DNA library, CLeavage Effects by Circularization for In vitro Reporting of sequencing was performed for eccDNA detection using 1 BC tissue sample. Fastqc was used to evaluate the quality of the original data. Burrows-Wheeler-Alignment Tool was used to compare the original data to the reference genome. A Circle-MAP was subsequently performed to detect eccDNA, and Bedtools was used to annotate the eccDNA genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted by ClusterProfiler. The Genotype-Tissue Expression and the Cancer Genome Atlas databases were used to collect the ribonucleic acid-sequencing data of the BC and normal samples. A Gene Expression Profiling Interactive Analysis, the University of Alabama at Birmingham CANcer data analysis Portal, and Kaplan-Meier survival curves were used to analyze the Cancer Genome Atlas data.

Results

A total of 200 eccDNA genes, including IGTB7, were obtained. About the biological processes (BPs), these 200 genes were mainly enriched in actin cytoskeleton reorganization and axon guidance. Concerning the molecular functions (MFs), these 200 genes were mainly enriched in sodium ion transmembrane transporter activity and metal ion transmembrane transporter activity. As for cellular components (CCs), these 200 genes were mainly enriched in the transcription regulator complex and focal adhesion. ITGB7 was significantly enriched in cell-matrix adhesion and localization within the membrane in the BPs, integrin binding in the MFs, and cell-substrate junction and focal adhesion in the CCs. The 200 eccDNA genes were mainly enriched in the PI3K-Akt signaling pathway and focal adhesion. Notably, ITGB7 was enriched in focal adhesion, ECM-receptor interaction, the PI3K-Akt signaling pathway, and human papillomavirus infection. Besides, ITGB7 was significantly upregulated in BC patients and was associated with the menopause status of the BC patients.

Conclusions

ITGB7 might serve as a prognostic marker for BC patients. ITGB7 has important implications for the individualized clinical treatment of BC patients.

In silico development and experimental validation of a novel 7-gene signature based on PI3K pathway-related genes in bladder cancer

Although bladder cancer (BLCA) is the 10th most common tumor worldwide, particularly practical markers and prognostic models that might guide therapy are needed. We used a non-negative matrix factorization algorithm to classify PI3K pathway-related genes into molecular subtypes. A weighted gene co-expression network analysis (WGCNA) was generated to identify co-expression modules. Univariate Cox regression, least absolute shrinkage sum selection operator-Cox regression, and multivariate Cox regression were utilized to develop a prognostic score model. Kaplan-Meier analysis and receiver operating characteristics were utilized to measure the model's effectiveness. A nomogram was constructed to improve the predictive ability of the model based on clinical parameters and risk. Decision curve analysis (DCA) was used to evaluate the nomogram. To evaluate the immune microenvironment, an estimate algorithm was used. Drug sensitivity was identified using the R package "pRRophetic." UM-UC-3 cell line was used to measure the effect of CDK6 in Western blotting, proliferation assay, and 5-ethynyl-20-deoxyuridine assay. Based on PI3K pathway-related genes, The Cancer Genome Atlas (TCGA)-BLCA and GSE32894 patients were divided into two subtypes. Twenty-five co-expression modules were established using the WGCNA algorithm. A seven-gene signature (CDK6, EGFR, IGF1, ITGB7, PDGFRA, RPS6, and VWF) demonstrated robustness in TCGA and GSE32894 datasets. Expression levels of CDK6 and risk positively correlated with M2 macrophages and IgG. Cisplatin, gemcitabine, methotrexate, mitomycin C, paclitaxel, and vinblastine are sensitive to different groups based on the expression of CDK6 and risk. Functional experiments suggested that CDK6 promotes the proliferation of UM-UC-3 cells. We constructed a seven-gene prognostic signature as an effective marker to predict the outcomes of BLCA patients and guide individual treatment.

Integrated multiomic approach for identification of novel immunotherapeutic targets in AML

BACKGROUND

Immunotherapy of acute myeloid leukemia has experienced considerable advances, however novel target antigens continue to be sought after. To this end, unbiased approaches for surface protein detection are limited and integration with other data types, such as gene expression and somatic mutational burden, are poorly utilized. The Cell Surface Capture technology provides an unbiased, discovery-driven approach to map the surface proteins on cells of interest. Yet, direct utilization of primary patient samples has been limited by the considerable number of viable cells needed.

METHODS

Here, we optimized the Cell Surface Capture protocol to enable direct interrogation of primary patient samples and applied our optimized protocol to a set of samples from patients with acute myeloid leukemia (AML) to generate the AML surfaceome. We then further curated this AML surfaceome to exclude antigens expressed on healthy tissues and integrated mutational burden data from hematologic cancers to further enrich for targets which are likely to be essential to leukemia biology. Finally, we validated our findings in a separate cohort of AML patient samples.

RESULTS

Our protocol modifications allowed us to double the yield in identified proteins and increased the specificity from 54 to 80.4% compared to previous approaches. Using primary AML patient samples, we were able to identify a total of 621 surface proteins comprising the AML surfaceome. We integrated this data with gene expression and mutational burden data to curate a set of robust putative target antigens. Seventy-six proteins were selected as potential candidates for further investigation of which we validated the most promising novel candidate markers, and identified CD148, ITGA4 and Integrin beta-7 as promising targets in AML. Integrin beta-7 showed the most promising combination of expression in patient AML samples, and low or absent expression on healthy hematopoietic tissue.

CONCLUSION

Taken together, we demonstrate the feasibility of a highly optimized surfaceome detection method to interrogate the entire AML surfaceome directly from primary patient samples and integrate this data with gene expression and mutational burden data to achieve a robust, multiomic target identification platform. This approach has the potential to accelerate the unbiased target identification for immunotherapy of AML.

Integrated analysis reveals the participation of IL4I1, ITGB7, and FUT7 in reshaping the TNBC immune microenvironment by targeting glycolysis

BACKGROUND

The overall response rate of immunotherapy in triple-negative breast cancer (TNBC) remains unsatisfactory. Accumulating evidence indicated that glucose metabolic reprogramming could modulate immunotherapy efficacy. However, transcriptomic evidence remains insufficient.

METHODS

Genes' relationship with glucose metabolism and TNBC-specific immune was demonstrated by weighted gene co-expression network analysis (WGCNA). The glucose metabolic capability was estimated by standardised uptake value (SUV), an indicator of glucose uptake in 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET), and a reflection of cancer metabolic behaviour. PD-(L)1 expression was used to reflect the efficacy of immunotherapy. Additionally, immune infiltration, survival, and gene coexpression profiles were provided.

RESULTS

Comprehensive analysis revealing that IL4I1, ITGB7, and FUT7 hold the potential to reinforce immunotherapy by reshaping glucose metabolism in TNBC. These results were verified by functional enrichment analysis, which demonstrated their relationships with immune-related signalling pathways and extracellular microenvironment reprogramming. Their expressions have potent positive correlations with Treg and Macrophage cell infiltration and exhausted T cell markers. Meanwhile, their overexpression also lead to poor prognosis.

CONCLUSION

IL4I1, ITGB7, and FUT7 may be the hub genes that link glucose metabolism, and cancer-specific immunity. They may be potential targets for enhancing ICB treatment by reprogramming the tumour microenvironment and remodelling tumour metabolism.

From infection to cancer: how DNA tumour viruses alter host cell central carbon and lipid metabolism

Infections cause 13% of all cancers globally, and DNA tumour viruses account for almost 60% of these cancers. All viruses are obligate intracellular parasites and hijack host cell functions to replicate and complete their life cycles to produce progeny virions. While many aspects of viral manipulation of host cells have been studied, how DNA tumour viruses manipulate host cell metabolism and whether metabolic alterations in the virus life cycle contribute to carcinogenesis are not well understood. In this review, we compare the differences in central carbon and fatty acid metabolism in host cells following infection, oncogenic transformation, and virus-driven cancer of DNA tumour viruses including: Epstein-Barr virus, hepatitis B virus, human papillomavirus, Kaposi's sarcoma-associated herpesvirus and Merkel cell polyomavirus.

Oncogenic function of TRIM2 in pancreatic cancer by activating ROS-related NRF2/ITGB7/FAK axis

Evidence suggests that tripartite motif-containing 2 (TRIM2) is associated with carcinogenic effects in several malignancies. However, the expression patterns and roles of TRIM2 in pancreatic cancer are rarely studied. Our study demonstrated that TRIM2 was expressed in a high percentage of pancreatic tumors. High TRIM2 expression was negatively correlated with the outcome of pancreatic cancer. TRIM2 silencing significantly inhibited the proliferation, migration, invasion, and in vivo tumorigenicity of pancreatic cancer cells. Regarding the mechanism involved, TRIM2 activated ROS-related E2-related factor 2 (NRF2)/antioxidant response element (ARE) signaling and the integrin/focal adhesion kinase (FAK) pathway. Treatment of pancreatic cancer cells with the antioxidant N-acetyl-L-cysteine decreased ROS activity and expression level of NRF2 and ITGB7. Increased translocation of NRF2 protein into nucleus further rescued the inhibited ITGB7 transcription. Moreover, NRF2 bound to the potential ARE on the promoter region and enhanced the transcriptional activity of ITGB7, indicating the bridging effect of NRF2 between the two signaling pathways. In summary, our study provides evidence that upregulated TRIM2 in pancreatic cancer predicts short survival for pancreatic cancer patients. TRIM2 accelerates pancreatic cancer progression via the ROS-related NRF2/ITGB7/FAK axis.