TYMS presents a novel biomarker for diagnosis and prognosis in patients with pancreatic cancer

From gene modules to gene markers: an integrated AI-human approach selects CD38 to represent plasma cell-associated transcriptional signatures

Background

Knowledge-driven prioritization of candidate genes derived from large-scale molecular profiling data for targeted transcriptional profiling assays is challenging due to the vast amount of biomedical literature that needs to be harnessed. We present a workflow leveraging Large Language Models (LLMs) to prioritize candidate genes within module M12.15, a plasma cell-associated module from the BloodGen3 repertoire, by integrating knowledge-driven prioritization with data-driven analysis of transcriptome profiles.

Methods

The workflow involves a two-step process: (1) high-throughput screening using LLMs to score and rank the 17 genes of module M12.15 based on six predefined criteria, and (2) prioritization employing high-resolution scoring and fact-checking, with human experts validating and refining AI-generated scores.

Results

The first step identified five candidate genes (CD38, TNFRSF17, IGJ, TOP2A, and TYMS). Following human-augmented LLM scoring and fact checking, as part of the second step, CD38 and TNFRSF17 emerged as the top candidates. Next, transcriptome profiling data from three datasets was incorporated in the workflow to assess expression levels and correlations with the module average across various conditions and cell types. It is on this basis that CD38 was prioritized as the top candidate, with TNFRSF17 and IGJ identified as promising alternatives.

Conclusion

This study introduces a systematic framework that integrates LLMs with human expertise for gene prioritization. Our analysis identified CD38, TNFRSF17, and IGJ as the top candidates within the plasma cell-associated module M12.15 from the BloodGen3 repertoire, with their relative rankings varying systematically based on specific evaluation criteria, from plasma cell biology to therapeutic relevance. This criterion-dependent ranking demonstrates the ability of the framework to perform nuanced, multi-faceted evaluations. By combining knowledge-driven analysis with data-driven metrics, our approach provides a balanced and comprehensive method for biomarker selection. The methodology established here offers a reproducible and scalable approach that can be applied across diverse biological contexts and extended to analyze large module repertoires.

WGCNA and integrative network analysis identify CHRNA5 and CTLA4 as potential therapeutic targets against angiosarcoma

Angiosarcomas are a type of soft-tissue sarcoma characterized by aggressive malignant tumors originating from endothelial cells of blood vessels or lymphatic vessels. Limited studies have been done to explore the molecular pathophysiology of the disease, with rather limited studies involving transcriptomic analyzes. This study was undertaken to identify the shared molecular signatures and gene modules associated with angiosarcomas of various origin. Transcriptomic data analysis of publicly available data was done followed by WGCNA to identify shared signature gene modules. The Maximal Clique Centrality algorithm was applied to gene modules, and unclustered network analysis was conducted on differentially expressed genes to identify true hub genes. The expression of candidate genes in various cancer types was analyzed using GEPIA. WGCNA analysis identified five significant modules, with the most enriched module being associated with angiogenesis and cell junction regulators. The intersection of true hub genes from MCC analysis of WGCNA modules and high-degree nodes from an unclustered network revealed eight consistently overexpressed genes in all angiosarcoma samples.Among the eight enriched genes, CHRNA5 and CTLA4, are exclusively overexpressed in angiosarcoma and not in other cancers of the same tissue origin, with significant drug-protein interactions suggesting their potential as therapeutic targets.

Genome-Wide CRISPR Screen Identifies Genes Involved in Metastasis of Pancreatic Ductal Adenocarcinoma

Background/Objectives: Early and aggressive metastasis is a major feature of pancreatic ductal adenocarcinoma. Understanding the processes underlying metastasis is crucial for making a difference to disease outcome. Towards these ends, we looked in a comprehensive manner for genes that are metastasis-specific. Methods: A genome-wide CRISPR-Cas9 gene knockout screen with 259,900 single guide RNA constructs was performed on pancreatic cancer cell lines with very high or very low metastatic capacity, respectively. Functional aspects of some of the identified genes were analysed in vitro. The injection of tumour cells with or without a gene knockout into mice was used to confirm the effect on metastasis. Results: The knockout of 590 genes-and, with higher analysis stringency, 67 genes-affected the viability of metastatic cells substantially, while these genes were not vital to non-metastasizing cells. Further evaluations identified different molecular processes related to this observation. One of the genes was MYBL2, encoding for a well-known transcription factor involved in the regulation of cell survival, proliferation, and differentiation in cancer tissues. In our metastasis-focussed study, no novel functional activity was detected for MYBL2, however. Instead, a metastasis-specific transformation of its genetic interaction with FOXM1 was observed. The interaction was synergistic in cells of low metastatic capacity, while there was a strong switch to a buffering mode in metastatic cells. In vivo analyses confirmed the strong effect of MYBL2 on metastasis. Conclusions: The genes found to be critical for the viability of metastatic cells form a basis for further investigations of the processes responsible for triggering and driving metastasis. As shown for MYBL2, unexpected processes of regulating metastasis might also be involved.

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

Image-guided metabolomics and transcriptomics reveal tumour heterogeneity in luminal A and B human breast cancer beyond glucose tracer uptake

BACKGROUND

Breast cancer is a metabolically heterogeneous disease, and although the concept of heterogeneous cancer metabolism is known, its precise role in human breast cancer is yet to be fully elucidated.

METHODS

We investigated in an explorative approach a cohort of 42 primary mamma carcinoma patients with positron emission tomography/magnetic resonance imaging (PET/MR) prior to surgery, followed by histopathology and molecular diagnosis. From a subset of patients, which showed high metabolic heterogeneity based on tracer uptake and pathology classification, tumour centre and periphery specimen tissue samples were further investigated by a targeted breast cancer gene expression panel and quantitative metabolomics by nuclear magnetic resonance (NMR) spectroscopy. All data were analysed in a combinatory approach.

RESULTS

[18 F]FDG (2-deoxy-2-[fluorine-18]fluoro-d-glucose) tracer uptake confirmed dominance of glucose metabolism in the breast tumour centre, with lower levels in the periphery. Additionally, we observed differences in lipid and proliferation related genes between luminal A and B subtypes in the centre and periphery. Tumour periphery showed elevated acetate levels and enrichment in lipid metabolic pathways genes especially in luminal B. Furthermore, serine was increased in the periphery and higher expression of thymidylate synthase (TYMS) indicated one-carbon metabolism increased in tumour periphery. The overall metabolic activity based on [18 F]FDG uptake of luminal B subtype was higher than that of luminal A and the difference between the periphery and centre increased with tumour grade.

CONCLUSION

Our analysis indicates variations in metabolism among different breast cancer subtypes and sampling locations which details the heterogeneity of the breast tumours. Correlation analysis of [18 F]FDG tracer uptake, transcriptome and tumour metabolites like acetate and serine facilitate the search for new candidates for metabolic tracers and permit distinguishing luminal A and B. This knowledge may help to differentiate subtypes preclinically or to provide patients guide for neoadjuvant therapy and optimised surgical protocols based on individual tumour metabolism.

Regulatory mechanisms of one-carbon metabolism enzymes

One-carbon metabolism is a central metabolic pathway critical for the biosynthesis of several amino acids, methyl group donors, and nucleotides. The pathway mostly relies on the transfer of a carbon unit from the amino acid serine, through the cofactor folate (in its several forms), and to the ultimate carbon acceptors that include nucleotides and methyl groups used for methylation of proteins, RNA, and DNA. Nucleotides are required for DNA replication, DNA repair, gene expression, and protein translation, through ribosomal RNA. Therefore, the one-carbon metabolism pathway is essential for cell growth and function in all cells, but is specifically important for rapidly proliferating cells. The regulation of one-carbon metabolism is a critical aspect of the normal and pathological function of the pathway, such as in cancer, where hijacking these regulatory mechanisms feeds an increased need for nucleotides. One-carbon metabolism is regulated at several levels: via gene expression, posttranslational modification, subcellular compartmentalization, allosteric inhibition, and feedback regulation. In this review, we aim to inform the readers of relevant one-carbon metabolism regulation mechanisms and to bring forward the need to further study this aspect of one-carbon metabolism. The review aims to integrate two major aspects of cancer metabolism-signaling downstream of nutrient sensing and one-carbon metabolism, because while each of these is critical for the proliferation of cancerous cells, their integration is critical for comprehensive understating of cellular metabolism in transformed cells and can lead to clinically relevant insights.

Evening Primrose Extract Modulates TYMS Expression via SP1 Transcription Factor in Malignant Pleural Mesothelioma

PURPOSE

To determine the mechanism of EPE in downregulating TYMS in MPM cancer.

METHODS

The TYMS mRNA expression with epithelial-to-mesenchymal transition biomarkers and nuclear factor SP1 was assessed using the GEO database in a data set of MPM patients (GSE51024). Invasive MPM cell lines were in vitro models for the investigation of TYMS expression after EPE treatment. The tyms promoter SP1 binding sequences were determined using Genomatix v 3.4 software Electrophoretic mobility shift and dual-luciferase reporter assays revealed specific SP1 motifs in the interaction of EPE and reference compounds. Chromatin immunoprecipitation and Re-ChIP were used for the co-occupancy study.

RESULTS

In MPM patients, a positive correlation of overexpressed TYMS with mesenchymal TWIST1, FN1 and N-cadherin was observed. EPE and its major components, gallic and ellagic acid (GA and EA, respectively), downregulated TYMS in invasive MPM cells by interacting with particular SP1 motifs on the tyms promoter. The luciferase constructs confirmed the occupation of two SP1 regulatory regions critical for the promotion of TYMS expression. Both EPE and reference standards influenced SP1 translocation into the nucleus.

CONCLUSION

EPE components reduced TYMS expression by occupation of SP1 motifs on the tyms promoter and reversed the EMT phenotype of invasive MPM cells. Further in-depth analysis of the molecular docking of polyphenol compounds with SP1 regulatory motifs is required.

A Novel HOXA10-Associated 5-Gene-Based Prognostic Signature for Stratification of Short-term Survivors of Pancreatic Ductal Adenocarcinoma

PURPOSE

Despite the significant association of molecular subtypes with poor prognosis in patients with pancreatic ductal adenocarcinoma (PDAC), few efforts have been made to identify the underlying pathway(s) responsible for this prognosis. Identifying a clinically relevant prognosis-based gene signature may be the key to improving patient outcomes.

EXPERIMENTAL DESIGN

We analyzed the transcriptomic profiles of treatment-naïve surgically resected short-term survivor (STS) and long-term survivor (LTS) tumors (GSE62452) for expression and survival, followed by validation in several datasets. These results were corroborated by IHC analysis of PDAC-resected STS and LTS tumors. The mechanism of this differential survival was investigated using CIBERSORT and pathway analyses.

RESULTS

We identified a short-surviving prognostic subtype of PDAC with a high degree of significance (P = 0.018). One hundred thirty genes in this novel subtype were found to be regulated by a master regulator, homeobox gene HOXA10, and a 5-gene signature derived from these genes, including BANF1, EIF4G1, MRPS10, PDIA4, and TYMS, exhibited differential expression in STSs and a strong association with poor survival. This signature was further associated with the proportion of T cells and macrophages found in STSs and LTSs, demonstrating a potential role in PDAC immunosuppression. Pathway analyses corroborated these findings, revealing that this HOXA10-driven prognostic signature is associated with immune suppression and enhanced tumorigenesis.

CONCLUSIONS

Overall, these findings reveal the presence of a HOXA10-associated prognostic subtype that can be used to differentiate between STS and LTS patients of PDAC and inform on the molecular interactions that play a role in this poor prognosis.

Integrated Bioinformatics Investigation of Novel Biomarkers of Uterine Leiomyosarcoma Diagnosis and Outcome

Uterine leiomyosarcomas (uLMS) have a poor prognosis and a high percentage of recurrent disease. Bioinformatics has become an integral element in rare cancer studies by overcoming the inability to collect a large enough study population. This study aimed to investigate and highlight crucial genes, pathways, miRNAs, and transcriptional factors (TF) on uLMS samples from five Gene Expression Omnibus datasets and The Cancer Genome Atlas Sarcoma study. Forty-one common differentially expressed genes (DEGs) were enriched and annotated by the DAVID software. With protein-protein interaction (PPI) network analysis, we selected ten hub genes that were validated with the TNMplotter web tool. We used the USCS Xena browser for survival analysis. We also predicted TF-gene and miRNA-gene regulatory networks along with potential drug molecules. TYMS and TK1 correlated with overall survival in uLMS patients. Finally, our results propose further validation of hub genes (TYMS and TK1), miR-26b-5p, and Sp1 as biomarkers of pathogenesis, prognosis, and differentiation of uLMS. Regarding the aggressive behavior and poor prognosis of uLMS, with the lack of standard therapeutic regimens, in our opinion, the results of our study provide enough evidence for further investigation of the molecular basis of uLMS occurrence and its implication in the diagnosis and therapy of this rare gynecological malignancy.

A gene-nutrient interaction between vitamin B6 and serine hydroxymethyltransferase (SHMT) affects genome integrity in Drosophila

Pyridoxal 5'-phosphate (PLP), the catalytically active form of vitamin B6, participates as a cofactor to one carbon (1C) pathway that produces precursors for DNA metabolism. The concerted action of PLP-dependent serine hydroxymethyltransferase (SHMT) and thymidylate synthase (TS) leads to the biosynthesis of thymidylate (dTMP), which plays an essential function in DNA synthesis and repair. PLP deficiency causes chromosome aberrations (CABs) in Drosophila and human cells, rising the hypothesis that an altered 1C metabolism may be involved. To test this hypothesis, we used Drosophila as a model system and found, firstly, that in PLP deficient larvae SHMT activity is reduced by 40%. Second, we found that RNAi-induced SHMT depletion causes chromosome damage rescued by PLP supplementation and strongly exacerbated by PLP depletion. RNAi-induced TS depletion causes severe chromosome damage, but this is only slightly enhanced by PLP depletion. dTMP supplementation rescues CABs in both PLP-deficient and PLP-proficient SHMT^RNAi . Altogether these data suggest that a reduction of SHMT activity caused by PLP deficiency contributes to chromosome damage by reducing dTMP biosynthesis. In addition, our work brings to light a gene-nutrient interaction between SHMT decreased activity and PLP deficiency impacting on genome stability that may be translated to humans.

Comprehensive serum metabolomics and network analysis to reveal the mechanism of gypenosides in treating lung cancer and enhancing the pharmacological effects of cisplatin

Gypenosides (GYP) exerted anticancer activity against various cancers. However, the mechanism of GYP against lung cancer (LC) in vivo remains unclear. This study aims to reveal the potential mechanism of GYP against LC and enhancing cisplatin efficacy using a comprehensive analysis of metabolomics, network analysis. Pharmacodynamic results showed that GYP inhibited tumor growth, reduced tumor volume and tumor weight, and alleviated pathological symptoms in Lewis tumor-bearing mice, and GYP could enhance the anti-LC effects of cisplatin. Using serum metabolomics methods, 53 metabolites were found to be significantly altered in the model group, and the levels of 23 biomarkers were significantly restored after GYP treatment. GYP-related metabolic pathways involved six pathways, including alpha-linolenic acid metabolism, glutathione metabolism, sphingolipid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and primary bile acid biosynthesis. 57 genes associated with differential metabolites of GYP recovery and 7 genes of 11 saponins of GYP against LC were screened by network analysis, the STRING database was used to find the association between 57 genes and 7 genes, and a compound-intersection gene-metabolite related gene-metabolite-pathway network was constructed, and STAT3, MAPK14, EGFR and TYMS might be the crucial targets of GYP against LC. Western blot results showed that GYP restored the levels of STA3, MAPK14, EGFR, and TYMS in the model group, and GYP also restored the levels of STAT3 and MAPK14 in the cisplatin group, indicating that GYP might exert anti-LC effects and enhance the pharmacological effects of cisplatin through MAPK14/STAT3 signaling pathway. Our method revealed the effect and mechanism of GYP on LC and the pharmacological effects of GYP-enhanced chemotherapeutic agent cisplatin, which provided some reference for the development of anti-cancer drugs.

Comprehensive analyses of one-carbon metabolism related genes and their association with prognosis, tumor microenvironment, chemotherapy resistance and immunotherapy in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is a global public health concern. One-carbon (1C) metabolism plays a crucial role in the occurrence and development of multiple cancer types. However, there are limited studies investigating 1C metabolism in LUAD. This study aims to evaluate the prognostic value of 1C metabolism-related genes in LUAD and to explore the potential correlation of these genes with gene methylation, the tumor microenvironment, and immunotherapy. Methods: We identified 26 1C metabolism-related genes and performed a Kaplan-Meier and Cox regression analysis to evaluate the prognostic value of these genes. Consensus clustering was further performed to determine the 1C metabolism-related gene patterns in LUAD. The clinical and molecular characteristics of subgroups were investigated based on consensus clustering. CIBERSORT and ssGSEA algorithms were used to calculate the relative infiltration levels of multiple immune cell subsets. The relationship between 1C metabolism-related genes and drug sensitivity to immunotherapy was evaluated using the CellMiner database and IMvigor210 cohort, respectively. Results: The expression levels of 23 1C metabolism-related genes were significantly different between LUAD tumor tissues and normal tissues. Seventeen of these genes were related to prognosis. Two clusters (cluster 1 and cluster 2) were identified among 497 LUAD samples based on the expression of 7 prognosis-related genes. Distinct expression patterns were observed between the two clusters. Compared to cluster 2, cluster 1 was characterized by inferior overall survival (OS) (median OS = 41 vs. 60 months, p = 0.00031), increased tumor mutation burden (15.8 vs. 7.5 mut/Mb, p < 0.001), high expression of PD-1 (p < 0.001) and PD-L1 (p < 0.001), as well as enhanced immune infiltration. 1C metabolism-related genes were positively correlated with the expression of methylation enzymes, and a lower methylation level was observed in cluster 1 (p = 0.0062). Patients in cluster 1 were resistant to chemotherapy drugs including pemetrexed, gemcitabine, paclitaxel, etoposide, oxaliplatin, and carboplatin. The specific expression pattern of 1C metabolism-related genes was correlated with a better OS in patients treated with immunotherapy (median OS: 11.2 vs. 7.8 months, p = 0.0034). Conclusion: This study highlights that 1C metabolism is correlated with the prognosis of LUAD patients and immunotherapy efficacy. Our findings provide novel insights into the role of 1C metabolism in the occurrence, development, and treatment of LUAD, and can assist in guiding immunotherapy for LUAD patients.

The Implication of Serum Autoantibodies in Prognosis of Canine Mammary Tumors

Canine mammary tumor (CMT) is the most prevalent neoplasm in female dogs. Tumor recurrence and metastasis occur in malignant CMT (MMT) dogs after surgery. Identification of serum prognostic biomarkers holds the potential to facilitate prediction of disease outcomes. We have identified CMT-associated autoantibodies against thymidylate synthetase (TYMS), insulin-like growth factor-binding protein 5 (IGFBP5), hyaluronan and proteoglycan link protein 1 (HAPLN1), and anterior gradient 2 (AGR2), i.e., TYMS-AAb, IGFBP5-AAb, HAPLN1-AAb, and AGR2-AAb, respectively, by conducting serological enzyme-linked immunosorbent assays (ELISA). Herein we assessed serum AAb levels in 11 MMT dogs before and after surgery, demonstrating that IGFBP5-AAb and HAPLN1-AAb significantly decrease at 3- and 12-months post-surgery (p < 0.05). We evaluated the correlation between the presurgical AAb level and overall survival (OS) of 90 CMT dogs after surgery. Kaplan-Meier survival analysis reveals that IGFBP5-AAbHIgh and TYMS-AAbHigh are significantly correlated with worse OS (p = 0.017 and p = 0.029, respectively), while AGR2-AAbLow is correlated with somewhat poorer OS (p = 0.086). Areas under a time-dependent receiver operating characteristic curve (AUC) of IGFBP5-AAb and TYMS-AAb in predicting OS of MMT dogs are 0.611 and 0.616, respectively. Notably, MMT dogs presenting TYMS-AAbHigh/IGFBP5-AAbHigh/AGR2-AAbLow have worst OS (p = 0.0004). This study reveals an association between the serum AAb level and CMT prognosis.

Prognostic value of metabolic genes in lung adenocarcinoma via integrative analyses

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common malignant lung tumor. Metabolic pathway reprogramming is an important hallmark of physiologic changes in cancers. However, the mechanisms through which these metabolic genes and pathways function in LUAD as well as their prognostic values have not been fully established.

METHODS

Four publicly available datasets from GEO and TCGA were used to identify differentially expressed genes (DEGs) in LUAD, which were then subjected to GO and KEGG pathway enrichment analysis. Associations between metabolic gene expressions with overall survival, tumor stage, TP53 mutation status, and infiltrated immune cells were investigated. Protein-protein interactions were evaluated using GeneMANIA and Metascape.

RESULTS

By integrating four public datasets, 247 DEGs were identified in LUAD. These DEGs were significantly enriched in regulation of chromosome segregation, centromeric region, and histone kinase activity GO terms, as well as in cell cycle, p53 signaling pathway, metabolic pathways, and other KEGG pathways. Elevated expressions of ten metabolic genes in LUAD were significantly associated with poor survival outcomes. These metabolic genes were highly expressed in more advanced tumor stage and TP53 mutated patients. Moreover, expression levels were significantly correlated with tumor-infiltrating immune cells. PPI interaction analysis revealed that the top 20 genes interacting with each metabolic gene were significantly enriched in DNA replication, response to radiation, and central carbon metabolism in cancer.

CONCLUSION

This study elucidates on molecular changes in metabolic genes in LUAD, which may inform the development of genetically oriented diagnostic approaches and effective treatment options.

Thymidylate Synthase Overexpression Drives the Invasive Phenotype in Colon Cancer Cells

Thymidylate synthase (TYMS) is the crucial enzymatic precursor for DNA biosynthesis and, therefore, the critical target for numerous types of chemotherapy, including the most frequently applied agent in colon cancer treatment 5-fluorouracil (5-FU). TYMS also seems to be associated with cancer metastasis and acquiring mesenchymal character by tumor cells during epithelial–mesenchymal transition (EMT). Based on that knowledge, we decided to investigate the role of TYMS in the modulation of invasive ability in colon cancer cells, where its effect on cancer metastasis has not been studied in detail before. We employed colon cancer cells isolated from different stages of tumor development, cells undergoing EMT, and TYMS overexpressing cells. The elongation ratio, cell migration, invasion assay, and MMP-7 secretion were applied to analyze the cell behavior. Important epithelial and mesenchymal markers characteristic of EMT were examined at the protein level by Western blot assay. Overall, our study showed a correlation between TYMS level and invasion ability in colon cancer cells and, above all, a crucial role of TYMS in the EMT regulation. We postulate that chemotherapeutics that decrease or inhibit TYMS expression could increase the effectiveness of the therapy in patients with colon cancer, especially in the metastatic stage.

TYMS-TM4SF4 axis promotes the progression of colorectal cancer by EMT and upregulating stem cell marker

BACKGROUND

The expression of thymidylate synthase (TYMS) is significantly up-regulated in various cancers and associated with the poor prognosis of patients. However, the role of TYMS in the progression of colorectal cancer (CRC) is unclear.

METHODS

Cell function assay, biology information analysis, and RNA sequencing were used to investigate the role of TYMS in the progression of CRC and underlining molecular mechanism. SPSS22.0 statistical software and GraphPad Prism 5 (Graphpad software) were used for statistical analysis.

RESULTS

Our results showed that TYMS expression was higher in CRC tissues than that in non-tumor colorectal mucosa tissues. TYMS knockdown inhibited the proliferation, migration and invasion of HCT116 and HT29 cells, and the spheroid formation of HCT116 cells. The underling mechanism demonstrated that TYMS promoted the progression of CRC by regulating EMT-related proteins including E-cadherin, Vimentin, MMP-9 and stem cell biomarkers including CD133 and CD44. Furthermore, DEG sequencing showed that TYMS knockdown enriched the pathways of metastasis and metabolism by GO and KEGG analysis. We identified TM4SF4 was the downstream target of TYMS in CRC cells. TM4SF4 overexpression increased migration and invasion of CRC cells by regulating EMT and CD133 expression.

CONCLUSIONS

Our findings suggest that TYMS-TM4SF4 axis may promote the progression of CRC by EMT and upregulating stem cell markers.

FOXM1-induced TYMS upregulation promotes the progression of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and one of the major causes of cancer-related death. Thymidylate synthase (TYMS) catalyzes the methylation of deoxy guanosine to deoxy thymidylate, which is a crucial gene for DNA repair and replication. Thus, TYMS was reported to be closely associated with developing a variety of tumors, but it has been poorly studied in HCC.

Materials and methods

We used the cell counting kit-8 (CCK-8), BrdU, and CFSE assay to measure cell proliferation. The flow cytometry assay and the TUNEL assay were used for assessing cell apoptosis. The flow cytometry assay was used to analyze the cell cycle. The Transwell invasion assay and the wound healing assay were conducted to determine the invasive ability of the cells. RT-qPCR and Western blot analyses were performed to evaluate the mRNA and protein expression levels of specific genes, respectively.

Results

TYMS was found to be upregulated in both HCC cells and patient samples. High expression of TYMS was associated with an unfavorable prognosis in HCC patients based on the TCGA-LIHC dataset. Cell proliferation, apoptosis, and invasion assays revealed that TYMS promoted the proliferation and invasion of HCC cells as well as inhibited apoptosis. In addition, TYMS is a downstream target of FOXM1. TYMS knockdown reversed the 5-FU resistance caused by FOXM1 overexpression and re-sensitized HCC cells to 5-FU treatment.

Conclusion

This study suggested that TYMS serves as an oncogene in HCC, and targeting the FOXM1-TYMS axis may help improve the survival of HCC patients as well as provide new insights for treating advanced HCC patients.

Artificial Intelligence Analysis of Gene Expression Predicted the Overall Survival of Mantle Cell Lymphoma and a Large Pan-Cancer Series

Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and conventional statistics, correlated 20,862 genes with 28 MCL prognostic genes for dimensionality reduction, to predict the patients' overall survival and highlight new markers. As a result, 58 genes predicted survival with high accuracy (area under the curve = 0.9). Further reduction identified 10 genes: KIF18A, YBX3, PEMT, GCNA, and POGLUT3 that associated with a poor survival; and SELENOP, AMOTL2, IGFBP7, KCTD12, and ADGRG2 with a favorable survival. Correlation with the proliferation index (Ki67) was also made. Interestingly, these genes, which were related to cell cycle, apoptosis, and metabolism, also predicted the survival of diffuse large B-cell lymphoma (GSE10846, n = 414), and a pan-cancer series of The Cancer Genome Atlas (TCGA, n = 7289), which included the most relevant cancers (lung, breast, colorectal, prostate, stomach, liver, etcetera). Secondly, survival was predicted using 10 oncology panels (transcriptome, cancer progression and pathways, metabolic pathways, immuno-oncology, and host response), and TYMS was highlighted. Finally, using machine learning, C5 tree and Bayesian network had the highest accuracy for prediction and correlation with the LLMPP MCL35 proliferation assay and RGS1 was made. In conclusion, artificial intelligence analysis predicted the overall survival of MCL with high accuracy, and highlighted genes that predicted the survival of a large pan-cancer series.

Identification of Potential Hub Genes and miRNA-mRNA Pairs Related to the Progression and Prognosis of Cervical Cancer Through Integrated Bioinformatics Analysis

In recent years, the incidence and mortality of cervical cancer have increased worldwide. At the same time, increasing data have confirmed that miRNA-mRNA plays a positive or negative regulatory role in many cancers. This study attempted to screen effective miRNA-mRNA in the progression of cervical cancer, and to study the mechanism of miRNA-mRNA in the progression of cervical cancer. The expression profile data of GSE7410, GSE 63514, GSE 86100 and TCGA-CESC were downloaded, and 34 overlapping differentially expressed genes (22 up-regulated and 12 down-regulated) and 166 miRNAs (74 down-regulated and 92 up-regulated) were screened through limma package. Then, miR-197-3p/TYMS pairs were obtained by PPI, functional enrichment, Kaplan-Meier plotter analysis, Cox univariate and multivariate analysis, risk modeling, WGCNA, qPCR and dual-luciferase experiments. The results showed that TYMS was an independent prognostic factor of cervical cancer, and its expression level was negatively correlated with cervical cancer tissue grade (TMN), tumor grade, age, microsatellite stability and tumor mutation load, and positively correlated with methyl expression in DNMT1, DNMT2, DNMT3A and DNMT3B. Functional experiments showed that TYMS knockout could promote the proliferation, migration and invasion of HeLa cells and reduce apoptosis. Overexpression of TYMS showed the opposite trend, miR-197-3p was negatively correlated with the expression of TYMS. MiR-197-3p inhibitor reversed the effect of si-TYMS on the proliferation of HeLa cells. In conclusion, these results reveal that TYMS plays a very important role in the prognosis and progression of cervical cancer, and has the potential to be thought of as cervical cancer biomarkers. At the same time, miR-197-3p/TYMS axis can regulate the deterioration of cervical cancer cells, which lays a foundation for the molecular diagnosis and treatment of cervical cancer.

Evening primrose seed extract rich in polyphenols modulates the invasiveness of colon cancer cells by regulating the TYMS expression

Natural polyphenols are plant metabolites exhibiting a broad range of biological activities.

Advances in the Detection of Pancreatic Cancer Through Liquid Biopsy

Pancreatic cancer refers to the development of malignant tumors in the pancreas: it is associated with high mortality rates and mostly goes undetected in its early stages for lack of symptoms. Currently, surgical treatment is the only effective way to improve the survival of pancreatic cancer patients. Therefore, it is crucial to diagnose the disease as early as possible in order to improve the survival rate of patients with pancreatic cancer. Liquid biopsy is a unique in vitro diagnostic technique offering the advantage of earlier detection of tumors. Although liquid biopsies have shown promise for screening for certain cancers, whether they are effective for early diagnosis of pancreatic cancer is unclear. Therefore, we reviewed relevant literature indexed in PubMed and collated updates and information on advances in the field of liquid biopsy with respect to the early diagnosis of pancreatic cancer.

Identification and Validation of TYMS as a Potential Biomarker for Risk of Metastasis Development in Hepatocellular Carcinoma

Metastasis is the major cause of hepatocellular carcinoma (HCC) mortality. Unfortunately, there are few reports on effective biomarkers for HCC metastasis. This study aimed to discover potential key genes of HCC, which could provide new insights for HCC metastasis. GEO (Gene Expression Omnibus) microarray and TCGA (The Cancer Genome Atlas) datasets were integrated to screen for candidate genes involved in HCC metastasis. Differentially expressed genes (DEGs) were screened, and then we performed enrichment analysis of Gene Ontology (GO), together with Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction network was then built and analyzed utilizing STRING and Cytoscape, followed by the identification of 10 hub genes by cytoHubba. Four genes were associated with survival, their prognostic value was verified by prognostic signature analysis. Thymidylate synthase (TYMS) gene was identified as significant HCC metastasis-associated genes after mRNA expression validation and IHC analysis. TYMS silencing in HCC cells remarkedly inhibited growth and invasion. Finally, we found TYMS silencing dramatically decrease DNA synthesis and extracellular matrix (ECM) degradation, resulting in the inhibition of HCC metastasis, indicating TYMS had close associations with HCC development. These findings provided new insights into HCC metastasis and identified candidate gene prognosis signatures for HCC metastasis.

Pancreatic cancer in 2021: What you need to know to win

Pancreatic cancer is one of the solid tumors with the worst prognosis. Five-year survival rate is less than 10%. Surgical resection is the only potentially curative treatment, but the tumor is often diagnosed at an advanced stage of the disease and surgery could be performed in a very limited number of patients. Moreover, surgery is still associated with high post-operative morbidity, while other therapies still offer very disappointing results. This article reviews every aspect of pancreatic cancer, focusing on the elements that can improve prognosis. It was written with the aim of describing everything you need to know in 2021 in order to face this difficult challenge.

Identification of Biomarkers Related to Prognosis of Bladder Transitional Cell Carcinoma

Bladder transitional cell carcinoma (BTCC) is highly fatal and generally has a poor prognosis. To improve the prognosis of patients with BTCC, it is particularly important to identify biomarkers related to the prognosis. In this study, differentially expressed messenger RNAs were obtained by analyzing relevant data of BTCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Next, hub genes that were suitable for correlation analysis with prognosis were determined through constructing a protein-protein interaction (PPI) network of differentially expressed genes and screening of major modules in the network. Finally, survival analysis of these hub genes found that three of them (CCNB1, ASPM, and ACTC1) were conspicuously related to the prognosis of patients with BTCC (p < 0.05). By combining the clinical features of BTCC and the expression levels of the three genes, univariate Cox and multivariate Cox regression analyses were performed and denoted that CCNB1 could be used as an independent prognostic factor for BTCC. This study provided potential biomarkers for the prognosis of BTCC as well as a theoretical basis for subsequent prognosis-related research.

Expression and gene regulation network of TYMS and BCL2L1 in colorectal cancer based on data mining

Background

The purpose of this study was to study the role of thymidylate synthetase (TYMS) and B-cell lymphoma-2 like 1 (BCL2L1) in the occurrence and development of colorectal cancer and its potential regulatory mechanism.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to examine the expression and prognostic value of TYMS and BCL2L1 in colorectal cancer. C-BioPortal analysis was used to detect the TYMS and BCL2L1 alterations. Through The Human Protein Atlas (THPA), the TYMS and BCL2L1 protein levels were also assessed. The protein protein interaction (PPI) network was built using GeneMANIA analysis, while co-expression genes correlated with TYMS and BCL2L1 were identified using LinkedOmics analysis. Finally, we collected clinical samples to verify the expressions of TYMS and BCL2L1 in colorectal cancer.

Results

TYMS and BCL2L1 were up-regulated, and TYMS and BCL2L1 genomic alterations were not associated with the occurrence of colorectal cancer. TYMS and BCL2L1 were significantly connected with the prognosis of colorectal cancer patients. The genes interacted with TYMS and BCL2L1 were linked to functional networks involving pathway of apoptosis, apoptosis-multiple species, colorectal cancer, platinum drug resistance and p53 signaling pathway. qRT-PCR verification results of TYMS were consistent with the result of TCGA and GEO analysis.

Conclusions

This study display that data mining can efficiently provide information on expression of TYMS and BCL2L1, correlated genes of TYMS and BCL2L1, core pathways and potential functional networks in colorectal cancer, suggesting that TYMS and BCL2L1 may become new prognostic and therapeutic targets for colorectal cancer.

Immune-related long non-coding RNAs can serve as prognostic biomarkers for clear cell renal cell carcinoma

Background

The immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC.

Methods

The raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.

Results

There were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC. We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine.

Conclusions

Our study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.

Serum Exosomal EphA2 is a Prognostic Biomarker in Patients with Pancreatic Cancer

Background

Pancreatic cancer (PC) is one of the worst prognoses amongst all malignant diseases. It is therefore of great significance to identify biomarkers with predictive clinical value for the prognosis and recurrence of PC.

Methods

In our study, enzyme-linked immunosorbent assays (ELISA) were used to detect the expression of Exo-EphA2 in the serum of PC patients and controls. Kaplan–Meier curve and Cox regression analyses were used to evaluate the prognostic value of Exo-EphA2 expression in patients with primary and recurrent PC.

Results

The level of serum Exo-EphA2 was significantly higher in the PC group when compared to that of the control group. High expression of Exo-EphA2 in PC was associated with shorter overall survival (OS) and proved to be a significant negative prognostic factor in the multivariate analysis (HR = 1.04, 95% CI: 1.00–1.09, P <0.001). Additionally, we found that the level of serum Exo-EphA2 in recurrent PC patients (first recurrence < 12 months) was positively correlated with the level of Exo-EphA2 at primary diagnosis. Multivariate analysis showed that a high expression of Exo-EphA2 in recurrent PC was associated with shorter recurrence-free survival (RFS) (HR = 1.41, 95% CI: 1.10–1.70, P < 0.001).

Conclusion

High expression of serum Exo-EphA2 represents a novel biomarker for a poor prognosis in PC patients.

Extensive analysis of the molecular biomarkers excision repair cross complementing 1, ribonucleotide reductase M1, β-tubulin III, thymidylate synthetase, and topoisomerase IIα in breast cancer: Association with clinicopathological characteristics

Excision repair cross complementing 1 (ERCC1), ribonucleotide reductase M1 (RRM1), β-tubulin III (TUBB3), thymidylate synthetase (TYMS), and topoisomerase IIα (TOP2A) genes have been shown to be associated with the pathogenesis and prognosis of various types of carcinomas; however, their roles in breast cancer have not been fully validated. In this study, we evaluated the correlations among these biomarkers and the associations between their expression intensity and the clinicopathological characteristics to investigate whether the above genes are underlying biomarkers for patients with breast cancer.Ninety-seven tissue specimens collected from breast cancer patients. The expression levels of these biomarkers were measured by the multiplex branched DNA liquidchip (MBL) technology and clinicopathological characteristics were collected simultaneously.The expression levels of ERCC1, TUBB3, TYMS, and TOP2A were significantly associated with the characteristics of menopausal status, tumor size, lymph node metastasis, hormone receptor status, triple-negative status, Ki-67 index, and epidermal growth factor receptor. The expression intensity of ERCC1 negatively associated with that of TUBB3 and TYMS, and positively associated with that of RRM1. The expression intensity of TOP2A positively associated with that of TYMS. Hierarchical clustering analysis and difference test indicated that breast cancer with higher levels of TUBB3, TYMS, and TOP2A, as well as lower levels of ERCC1 and RRM1 tended to have higher histological grade and Ki-67 index.Our studies showed that ERCC1, TYMS, TUBB3, and TOP2A may be potential biomarkers for prognosis and individualized chemotherapy guidance, while there may be interactions between ERCC1 and RRM1, or TUBB3, or TYMS, as well as between TOP2A and TYMS in pathogenesis and development of breast cancer.

Integrated WGCNA and PPI Network to Screen Hub Genes Signatures for Infantile Hemangioma

BACKGROUND

Infantile hemangioma (IH) is characterized by proliferation and regression.

METHODS

Based on the GSE127487 dataset, the differentially expressed genes (DEGs) between 6, 12, or 24 months and normal samples were screened, respectively. STEM software was used to screen the continued up-regulated or down-regulated in common genes. The modules were assessed by weighted gene co-expression network analysis (WGCNA). The enrichment analysis was performed to identified the biological function of important module genes. The area under curve (AUC) value and protein-protein interaction (PPI) network were used to identify hub genes. The differential expression of hub genes in IH and normal tissues was detected by qPCR.

RESULTS

There were 5,785, 4,712, and 2,149 DEGs between 6, 12, and 24 months and normal tissues. We found 1,218 DEGs were up-regulated or down-regulated expression simultaneously in common genes. They were identified as 10 co-expression modules. Module 3 and module 4 were positively or negatively correlated with the development of IH, respectively. These two module genes were significantly involved in immunity, cell cycle arrest and mTOR signaling pathway. The two module genes with AUC greater than 0.8 at different stages of IH were put into PPI network, and five genes with the highest degree were identified as hub genes. The differential expression of these genes was also verified by qRTPCR.

CONCLUSION

Five hub genes may distinguish for proliferative and regressive IH lesions. The WGCNA and PPI network analyses may help to clarify the molecular mechanism of IH at different stages.

Expression Profile of GINS Complex Predicts the Prognosis of Pancreatic Cancer Patients

BACKGROUND

The GINS complex has been implicated in the prognosis of various cancers. It comprises four subunits, encoded by GINS1, GINS2, GINS3, and GINS4 genes. Based on the current understanding, no report exists on the role of the GINS complex in pancreatic cancer.

METHODS

We employed various bioinformatics databases including GEPIA, UALCAN, GEPIA2, and Kaplan Meier Plotter to identify the expression profile of the four genes (GINS1, GINS2, GINS3, and GINS4), their correlation with pancreatic cancer grade as well as their prognostic value of in pancreatic cancer. Western blotting and qRT-PCR analyses were conducted to verify the expression profiles of the four genes in pancreatic cancer. CCK8 and EdU cell experiments were conducted to reveal the role played by the four genes in pancreatic cancer cell proliferation.

RESULTS

Based on GEPIA, Western blotting, and qRT-PCR analyses, all the four genes in the GINS complex were overexpressed in pancreatic cancer. Notably, the expression of each member was significantly associated with pancreatic cancer grade. The prognostic analysis revealed that not only the whole GINS complex but also each individual were prognostic biomarkers for pancreatic cancer. CCK8 and EdU experiments demonstrated that inhibition of the expression of each GINS member lowered pancreatic cancer cell proliferation.

CONCLUSION

This work implicated GINS1, GINS2, GINS3, and GINS4 genes as critical prognostic markers for pancreatic cancer.

Correlation between polymorphism of TYMS gene and toxicity response to treatment with 5-fluoruracil and capecitabine

Tumorigenesis is a multiphasic process in which genetic alterations guide the progressive transformation in cancer cells1. In order to evaluate the possible correlation between some gene variants and the risk of the toxicity development onset, two of the polymorphisms of the thymidylate synthase (TYMS), rs34743033 (2R/3R) and rs16430 (DEL/INS) were investigated. We enrolled in our study 47 patients from the Hospital of Sicily. Our preliminary findings suggest that there could be a linkage between the genotypes discussed and the development of the toxicity following the chemotherapy treatment. These results need to be confirmed by further studies, however this short paper offers some initial insight into the relationships between genetic background and the better outcome for patients.

Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis

BACKGROUND

Cervical cancer (CC) is the second most common type of malignant tumor survival rate is low in advanced stage, metastatic, and recurrent CC patients. This study aimed at identifying potential genes and drugs for CC diagnosis and targeting therapies.

METHODS

Three GEO mRNA microarray datasets of CC tissues and non-cancerous tissues were analyzed for differentially expressed genes (DEGs) by limma package. GO (Gene Ontologies) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used to explore the relationships between the DEGs. Protein-protein interaction (PPI) of these genes was established by the STRING database. MCODE was used for screening significant modules in the PPI networks to select hub genes. Biochemical mechanisms of the hub genes were investigated with Metascape. GEPIA database was used for validating the core genes. According to these DEGs, molecular candidates for CC were recognized from the CMAP database.

RESULTS

We identified 309 overlapping DEGs in the 2 tissue-types. Pathway analysis revealed that the DEGs were involved in cell cycle, DNA replication, and p53 signaling. PPI networks between overlapping DEGs showed 68 high-connectivity DEGs that were chosen as hub genes. The GEPIA database showed that the expression levels of RRM2, CDC45, GINS2, HELLS, KNTC1, MCM2, MYBL2, PCNA, RAD54 L, RFC4, RFC5, TK1, TOP2A, and TYMS in CC tissues were significantly different from those in the healthy tissues and were significantly relevant to the OS of CC. We found 10 small molecules from the CMAP database that could change the trend of gene expression in CC tissues, including piperlongumine and chrysin.

CONCLUSIONS

The 14 DEGs identified in this study could serve as novel prognosis biomarkers for the detection and forecasting of CC. Small molecule drugs like piperlongumine and chrysin could be potential therapeutic drugs for CC treatment.