High gamma-glutamyl hydrolase and low folylpolyglutamate synthetase expression as prognostic biomarkers in patients with locally advanced gastric cancer who were administrated postoperative adjuvant chemotherapy with S-1

Multimodal AI for prediction of distant metastasis in carcinoma patients

Metastasis of cancer is directly related to death in almost all cases, however a lot is yet to be understood about this process. Despite advancements in the available radiological investigation techniques, not all cases of Distant Metastasis (DM) are diagnosed at initial clinical presentation. Also, there are currently no standard biomarkers of metastasis. Early, accurate diagnosis of DM is however crucial for clinical decision making, and planning of appropriate management strategies. Previous works have achieved little success in attempts to predict DM from either clinical, genomic, radiology, or histopathology data. In this work we attempt a multimodal approach to predict the presence of DM in cancer patients by combining gene expression data, clinical data and histopathology images. We tested a novel combination of Random Forest (RF) algorithm with an optimization technique for gene selection, and investigated if gene expression pattern in the primary tissues of three cancer types (Bladder Carcinoma, Pancreatic Adenocarcinoma, and Head and Neck Squamous Carcinoma) with DM are similar or different. Gene expression biomarkers of DM identified by our proposed method outperformed Differentially Expressed Genes (DEGs) identified by the DESeq2 software package in the task of predicting presence or absence of DM. Genes involved in DM tend to be more cancer type specific rather than general across all cancers. Our results also indicate that multimodal data is more predictive of metastasis than either of the three unimodal data tested, and genomic data provides the highest contribution by a wide margin. The results re-emphasize the importance for availability of sufficient image data when a weakly supervised training technique is used. Code is made available at: https://github.com/rit-cui-lab/Multimodal-AI-for-Prediction-of-Distant-Metastasis-in-Carcinoma-Patients.

Study on the role and pharmacology of cuproptosis in gastric cancer

Objective

Gastric cancer has a poor prognosis and high mortality. Cuproptosis, a novel programmed cell death, is rarely studied in gastric cancer. Studying the mechanism of cuproptosis in gastric cancer is conducive to the development of new drugs, improving the prognosis of patients and reducing the burden of disease.

Methods

The TCGA database was used to obtain transcriptome data from gastric cancer tissues and adjacent tissues. GSE66229 was used for external verification. Overlapping genes were obtained by crossing the genes obtained by differential analysis with those related to copper death. Eight characteristic genes were obtained by three dimensionality reduction methods: lasso, SVM, and random forest. ROC and nomogram were used to estimate the diagnostic efficacy of characteristic genes. The CIBERSORT method was used to assess immune infiltration. ConsensusClusterPlus was used for subtype classification. Discovery Studio software conducts molecular docking between drugs and target proteins.

Results

We have established the early diagnosis model of eight characteristic genes (ENTPD3, PDZD4, CNN1, GTPBP4, FPGS, UTP25, CENPW, and FAM111A) for gastric cancer. The results are validated by internal and external data, and the predictive power is good. The subtype classification and immune type analysis of gastric cancer samples were performed based on the consensus clustering method. We identified C2 as an immune subtype and C1 as a non-immune subtype. Small molecule drug targeting based on genes associated with cuproptosis predicts potential therapeutics for gastric cancer. Molecular docking revealed multiple forces between Dasatinib and CNN1.

Conclusion

The candidate drug Dasatinib may be effective in treating gastric cancer by affecting the expression of the cuproptosis signature gene.

Interaction between glycolysis‒cholesterol synthesis axis and tumor microenvironment reveal that gamma-glutamyl hydrolase suppresses glycolysis in colon cancer

Background

Metabolic reprogramming is a feature of cancer. However, colon cancer subtypes based on the glycolysis‒cholesterol synthesis axis have not been identified, and little is known about connections between metabolic features and the tumor microenvironment.

Methods

Data for 430 colon cancer cases were extracted from The Cancer Genome Atlas, including transcriptome data, clinical information, and survival outcomes. Glycolysis and cholesterol synthesis-related gene sets were obtained from the Molecular Signatures Database for a gene set variation analysis. The relationship between the genomic landscape and immune landscape were investigated among four metabolic subtypes. Hub genes were determined. The clinical significance of candidate hub gene was evaluated in 264 clinical samples and potential functions were validated in vitro and in vivo.

Results

Colon cancer cases were clustered into four metabolic subtypes: quiescent, glycolytic, cholesterogenic, and mixed. The metabolic subtypes differed with respect to the immune score, stromal score, and estimate score using the ESTIMATE algorithm, cancer-immunity cycle, immunomodulator signatures, and signatures of immunotherapy responses. Patients in the cholesterogenic group had better survival outcomes than those for other subtypes, especially glycolytic. The glycolytic subtype was related to unfavorable clinical characteristics, including high mutation rates in TTN, APC, and TP53, high mutation burden, vascular invasion, right colon cancer, and low-frequency microsatellite instability. GGH, CACNG4, MME, SLC30A2, CKMT2, SYN3, and SLC22A31 were identified as differentially expressed both in glycolytic-cholesterogenic subgroups as well as between colon cancers and healthy samples, and were involved in glycolysis‒cholesterol synthesis. GGH was upregulated in colon cancer; its high expression was correlated with CD4⁺ T cell infiltration and longer overall survival and it was identified as a favorable independent prognostic factor. The overexpression of GGH in colon cancer-derived cell lines (SW48 and SW480) inhibited PKM, GLUT1, and LDHA expression and decreased the extracellular lactate content and intracellular ATP level. The opposite effects were obtained by GGH silencing. The phenotype associated with GGH was also validated in a xenograft nude mouse model.

Conclusions

Our results provide insight into the connection between metabolism and the tumor microenvironment in colon cancer and provides preliminary evidence for the role of GGH, providing a basis for subsequent studies.

HDAC7 inhibits cell proliferation via NudCD1/GGH axis in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. In the absence of effective molecular markers for TNBC, there is an urgent clinical need for promising therapeutic target for TNBC. Histone deacetylases (HDACs), key regulators for chromatin remodeling and gene expression, have been suggested to play critical roles in cancer development. However, little is known ~the functions and implications of HDACs in TNBC treatment in the future. By analyzing the expression and prognostic significance of HDAC family members in TNBC through TCGA and METABRIC databases, HDAC7 was found to be downregulated in TNBC samples and the survival of patients with lower expression of HDAC7 was shorter. Furthermore, HDAC7 was negatively associated with NudC domain containing 1 (NudCD1) and γ-glutamyl hydrolase (GGH). Loss of NudCD1 or GGH predicted improved overall survival time (OS) of patients with TNBC. In vitro experiments showed that silencing of HDAC7 enhanced TNBC cell proliferation, while overexpression HDAC7 inhibited TNBC cell proliferation. The results of functional experiments confirmed that HDAC7 negatively modulated GGH and NudCD1 expression. Furthermore, decrease of NudCD1 or GGH inhibited cell proliferation. Notably, the HDAC7-NudCD1/GGH axis was found to be associated with NK cell infiltration. Overall, the present study revealed a novel role of HDAC7-NudCD1/GGH axis in TNBC, which might provide a promising treatment strategy for patients with TNBC.

Elevated Expression of Gamma-Glutamyl Hydrolase Is Associated With Poor Prognosis and Altered Immune Signature in Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is a common malignant tumor of the female reproductive system with poor prognosis in advanced, recurrent, and metastatic cases. Identification of reliable molecular markers will help in the development of clinical strategies for early detection, diagnosis, and intervention. Gamma-glutamyl hydrolase (GGH) is a key enzyme in folate metabolism pathway. High expression of GGH is associated with severe clinicopathological features and poor prognosis of several cancers. High GGH expression is also related to cell resistance to antifolate drugs such as methotrexate. In this study we focused on the prognostic value of immunohistochemical GGH expression level in UCEC tissue and RNA-seq data from The Cancer Genome Atlas to establish associations with clinical features and outcomes. Further, we conducted comprehensive bioinformatics analyses to identify and functionally annotate differentially expressed genes (DEGs) associated with UCEC upregulation and assessed the effects of upregulation on immune infiltration. Both GGH mRNA and protein expression levels were elevated in tumor tissues, and higher expression was significantly associated with advanced clinicopathological features and poor prognosis by univariate analysis. Further multivariate analysis identified elevated GGH expression as an independent risk factor for poor outcome. Nomograms including GGH expression yielded a c-index for disease-specific survival prediction of 0.884 (95% confidence interval: 0.861–0.907). A total of 520 DEGs (111 upregulated and 409 downregulated) were identified between high and low GGH expression groups. Analysis using Gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, Gene set enrichment analysis, and protein‒protein interaction indicated significant associations of altered GGH expression with cell proliferation, immune response, and the occurrence and development of UCEC tumors. Finally, GGH expression level was associated with high Th2 cell and low natural killer CD56bright cell infiltration. Collectively, these findings indicate that GGH drives UCEC progression and could be a useful biomarker for survival prediction as well as a therapeutic target.

Influence of FPGS, ABCC4, SLC29A1, and MTHFR genes on the pharmacogenomics of fluoropyrimidines in patients with gastrointestinal cancer from the Brazilian Amazon

PURPOSE

Fluoropyrimidines are one of the most used drug class to treat cancer patients, although they show high levels of associated toxicity. This study analyzed 33 polymorphisms in 17 pharmacogenes involved with the pharmacogenomics of fluoropyrimidines, in gastrointestinal cancer patients undergoing fluoropyrimidine-based treatment in the Brazilian Amazon.

METHODS

The study population was composed of 216 patients, 92 of whom have an anatomopathological diagnosis of gastric cancer and 124 of colorectal cancer. The single nucleotide polymorphisms (SNP) were genotyped by allelic discrimination using the TaqMan OpenArray Genotyping technology, with a panel of 32 customized assays, run in a QuantStudio ™ 12K Flex Real-Time PCR System (Applied Biosystems, Life Technologies, Carlsbad USA). Ancestry analysis was performed using 61 autosomal ancestry informative markers (AIMs).

RESULTS

The study population show mean values of 48.1% European, 31.1% Amerindian, and 20.8% African ancestries. A significant risk association for general and severe toxicity was found in the rs4451422 of FPGS (p = 0.001; OR 3.40; CI 95% 1.65-7.00 and p = 0.006; OR 4.63; CI 95% 1.56-13.72, respectively) and the rs9524885 of ABCC4 (p = 0.023; OR 2.74; CI 95% 1.14-6.65 and p = 0.024; OR 5.36; IC 95% 1.24-23.11, respectively) genes. The rs760370 in the SLC29A1 gene (p = 0.009; OR 6.71; CI 95% 1.16-8.21) and the rs1801133 in the MTHFR toxicity (p = 0.023; OR 3.09; CI 95% 1.16-8.21) gene also demonstrated to be significant, although only for severe toxicity. The results found in this study did not have statistics analysis correction.

CONCLUSION

Four polymorphisms of the ABCC4, FPGS, SLC29A1, and MTHFR genes are likely to be potential predictive biomarkers for precision medicine in fluoropyrimidine-based treatments in the population of the Brazilian Amazon, which is constituted by a unique genetic background.

A clinical study of Yiqi Huayu Jiedu decoction reducing the risk of postoperative gastric cancer recurrence and metastasis: Study protocol for a randomized controlled trail

BACKGROUND

Gastric cancer is a common gastrointestinal tumor, seriously threatening human health. Radical surgery is the preferred treatment for gastric cancer. However, due to the late diagnosis and postoperative recurrence and metastasis, the prognosis is dismal. In China, traditional Chinese medicine (TCM) has been used to treat gastric cancer for many years. The purpose of this study is to explore the efficacy and safety of Yiqi Huayu Jiedu decoction in the treatment of postoperative gastric caner.

METHODS/DESIGN

226 eligibility patients altogether will be randomly allocated to the treatment group and the control group at a ratio of 1:1. After enrollment, every patients will obtain 6 months of treatment, as well as 2 years of follow-up. At the end of this study, primary outcomes including 1-year progression-free survival rate, 2-year progression-free survival rate and disease-free survival, secondary outcomes containing tumor markers, TCM syndrome points, quality of life scale, imageological examination and the safety indicators will be assessed.

DISCUSSION

This study will provide the evidence-based evidence for the efficacy of Yiqi Huayu Jiedu decoction reducing the risk of postoperative gastric cancer recurrence and metastasis, which will be beneficial to form the therapeutic regimen in postoperative gastric cancer with integrated TCM and Western medicine.

TRAIL REGISTRATION

ChiCTR2000032802.