The Roles of Drug Metabolism-Related ADH1B in Immune Regulation and Therapeutic Response of Ovarian Cancer

High-grade serous carcinoma of the fallopian tube in a young woman with chromosomal 4q abnormality: A case report

BACKGROUND

Few studies have reported an association between an increased risk of acquiring cancers and survival in patients with 4q deletion syndrome. This study presents a rare association between chromosome 4q abnormalities and fallopian tube high-grade serous carcinoma (HGSC) in a young woman.

CASE SUMMARY

A 35-year-old woman presented with acute dull abdominal pain and a known chromosomal abnormality involving 4q13.3 duplication and 4q23q24 deletion. Upon arrival at the emergency room, her abdomen appeared ovoid and distended with palpable shifting dullness. Ascites were identified through abdominal ultrasound, and computed tomography revealed an omentum cake and an enlarged bilateral adnexa. Blood tests showed elevated CA-125 levels. Paracentesis was conducted, and immunohistochemistry indicated that the cancer cells favored an ovarian origin, making us suspect ovarian cancer. The patient underwent debulking surgery, which led to a diagnosis of stage IIIC HGSC of the fallopian tube. Subsequently, the patient received adjuvant chemotherapy with carboplatin and paclitaxel, resulting in stable current condition.

CONCLUSION

This study demonstrates a rare correlation between a chromosome 4q abnormality and HGSC. UBE2D3 may affect crucial cancer-related pathways, including P53, BRCA, cyclin D, and tyrosine kinase receptors, thereby possibly contributing to cancer development. In addition, ADH1 and DDIT4 may be potential influencers of both carcinogenic and therapeutic responses.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma

BACKGROUND

Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO.

METHOD

Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation.

RESULT

A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation.

CONCLUSION

Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

Multi-omics analysis reveals critical metabolic regulators in bladder cancer

BACKGROUND

The crosstalk between genomic alterations and metabolic dysregulation in bladder cancer is largely unknown. A deep understanding of the interactions between cancer drivers and cancer metabolic changes will provide novel opportunities for targeted therapeutic strategies.

METHODS

Three primary bladder cancer specimens with paired normal tissues or blood samples were subjected to whole-exome sequencing, DNA methylation array and whole-transcriptome sequencing by next-generation sequencing technology. We applied the methods to multi-omics data combining the Cancer Genome Atlas (TCGA) bladder cancer samples, including somatic mutation, DNA copy number, DNA methylation and gene expression profile for validation.

RESULTS

We identified 34 mutated cancer driver genes in bladder cancer. KDM6A was the most significantly mutated cancer driver gene. Metabolic pathways were enriched in both differentially methylated regions (DMRs) and differentially expressed genes. Twenty-nine DMRs in the TSS200 region were highly correlated with the upregulation of gene expression, and 24 DMRs in the genome were highly correlated with the downregulation of gene expression. A total of 201 genes had highly correlated DNA methylation and expression. Thirty-four genes, including the known metabolic genes CXXC5, PRR5, ABCB8 and BAHD1, were further validated in the TCGA cohort. Multi-omics alterations identified two new candidate driver genes, WIPI2 and GFM2, that warrant future studies.

CONCLUSIONS

This study provides a comprehensive and systematic analysis, focusing on identifying key regulatory factors that may lead to cancer metabolic heterogeneity. Further understanding and verification of the cancer genes driving metabolic reprogramming and their role in the progression of bladder cancer will help to identify new therapeutic targets.

ALDH2 is a novel biomarker and exerts an inhibitory effect on melanoma

Melanoma is a malignant skin tumor. This study aimed to explore and assess the effect of novel biomarkers on the progression of melanoma. Differently expressed genes (DEGs) were screened from GSE3189 and GSE46517 datasets of Gene Expression Omnibus database using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted based on the identified DEGs. Hub genes were identified and assessed using protein-protein interaction networks, principal component analysis, and receiver operating characteristic curves. Quantitative real-time polymerase chain reaction was employed to measure the mRNA expression levels. TIMER revealed the association between aldehyde dehydrogenase 2 (ALDH2) and tumor immune microenvironment. The viability, proliferation, migration, and invasion were detected by cell counting kit-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Total 241 common DEGs were screened out from GSE3189 and GSE46517 datasets. We determined 6 hub genes with high prediction values for melanoma, which could distinguish tumor samples from normal samples. ALDH2, ADH1B, ALDH3A2, DPT, EPHX2, and GATM were down-regulated in A375 and SK-MEL-2 cells, compared with the human normal melanin cell line (PIG1 cells). ALDH2 was selected as the candidate gene in this research, presenting a high diagnostic and predictive value for melanoma. ALDH2 had a positive correlation with the infiltrating levels of immune cells in melanoma microenvironment. Overexpression of ALDH2 inhibited cell viability, proliferation, migration, and invasion of A375/SK-MEL-2 cells. ALDH2 is a new gene biomarker of melanoma, which exerts an inhibitory effect on melanoma.

Association of TOP2A and ADH1B with lipid levels and prognosis in patients with lung adenocarcinoma and squamous cell carcinoma

BACKGROUND

Although lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) have different pathological and clinical features, they may share common driver genes. It was found that lipid levels can be used for early diagnosis of NSCLC; however, the relationship between driver genes and genes regulating lipid metabolism and their relationship with patient prognosis needs further investigation.

METHODS

Genes whose expression was up- or down-regulated in both LUAD and LUSC were identified using the GEO database. Online tools like GEPIA 2, PrognoScan, UALCAN, and TIMER2.0 were used to investigate the association of these gene expressions with the patient's prognosis and lipid regulatory genes. The association between clinical lipid levels and the risk of LUAD and LUSC was analyzed by using a multiple logistic regression model.

RESULTS

Topoisomerase II alpha (TOP2A) and alcohol dehydrogenase 1B (ADH1B) were identified as the only genes up- and down-regulated in both LUAD and LUSC. TOP2A and ADH1B expression levels significantly correlated with the patient's gender, age, individual cancer stage, histological subtype, nodal metastasis status, and TP53 mutation status. Additionally, only LUAD patients with higher TOP2A or lower ADH1B expressions displayed poor overall and relapse-free survival rates. Moreover, TOP2A levels exhibited a negative correlation with adipose triglyceride lipase (ATGL) and ATP-binding cassette transporter A1 (ABCA1) in both LUAD and LUSC. However, ADH1B showed inverse associations with the above-mentioned genes when compared to TOP2A expressions in both LUAD and LUSC. Furthermore, elevated triglyceride (OR = 1.59; 95% CI = 1.01 to 2.49; P < 0.05) and total cholesterol (OR = 2.45; 95% CI = 1.08 to 5.57; P < 0.05) levels might increase the risk of LUAD.

CONCLUSIONS

TOP2A and ADH1B can be used as diagnostic markers for LUAD and LUSC, but only as independent prognostic factors for LUAD, and may be involved in lipid metabolism in LUAD patients but not in LUSC. Thus, combining genetic diagnostics with lipid panel tests might be an effective method for an early diagnosis and improved prognosis of LUAD.

The downregulated drug-metabolism related ALDH6A1 serves as predictor for prognosis and therapeutic immune response in gastric cancer

Drug metabolism-associated genes have been clarified to play a vital role in the process of cancer cell growth and migration. Nevertheless, the correlation between drug metabolism-associated genes and gastric cancer (GC) has not been fully explored and clarified. This paper has focused on the role of aldehyde dehydrogenase 6 family member A1 (ALDH6A1), a drug metabolism-associated gene, in the immune regulation and prognosis of GC patients. Using several bioinformatics platforms and immunohistochemistry (IHC) assay, we found that ALDH6A1 expression was significantly down-regulated in GC tissues. Moreover, higher expression of ALDH6A1 was related to the better prognosis of GC patients. ALDH6A1 was also found to be involved in the regulation of several immune-associated signatures, including immunoinhibitors. In conclusion, the above results have concluded that aberrant expression of ALDH6A1 might be served as the promising predictor for prognosis and clinical immunotherapy response in GC patients.