Identification of Key Factors Associated with Early- and Late-Onset Ovarian Serous Cystadenocarcinoma

Ma, Shuang; Zheng, Yang; Fei, Chengwei

doi:10.2217/fon-2020-0668

Cited by 3 publications

(3 citation statements)

References 44 publications

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“…CT45A1 shows significant over representation in breast cancer, and it has been demonstrated as a target for the development of new therapeutics [47], [48]. CT45A3 have a role in a specific ovarian cancer phenotype and is considered a prognostic factor [49]. CT45A2 is highly expressed in lung cancer and plays a protective role against this disease [50].…”

Section: Discussionmentioning

confidence: 99%

Detecting predicted cancer-testis antigens in proteomics datasets of healthy and tumoral samples

Tabosa Machado,

Da Silva Fiúza,

De Souza

et al. 2024

Preprint

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Biomarkers are molecular markers found in clinical samples which may aid disease diagnosis or prognosis. High-throughput techniques allow prospecting for such signature molecules by comparing gene expression between normal and sick cells. Cancer-testis antigens (CTAs) are promising candidates for cancer biomarkers due to their limited expression to the testis in normal conditions versus their aberrant expression in various tumors. CTAs are routinely identified by transcriptomics, but a comprehensive characterization of their protein levels in different tissues is still necessary. Mass spectrometry-based proteomics allows the characterization of many cellular types and the production of large amounts of data while computational tools allow the comparison of multiple datasets, and together those may corroborate insights obtained at the transcriptomic level. Here a computational meta-analysis explores the CTAs protein abundance in the proteomic layer of healthy and tumor tissues. The combined datasets present the expression patterns of 17,200 unique proteins, including 241 known CTAs previously described at the transcriptomic level. Those were further ranked as significantly enriched in tumor tissues (22 proteins), exclusive to tumor tissues (42 proteins) or abundant in healthy tissues (32 proteins). This analysis illustrates the possibilities for tumor proteome characterization and the consequent identification of biomarker candidates and/or therapeutic targets.

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Section: Discussionmentioning

confidence: 99%

Detecting predicted cancer-testis antigens in proteomics datasets of healthy and tumoral samples

Tabosa Machado,

Da Silva Fiúza,

De Souza

et al. 2024

Preprint

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show abstract

“…LAG-3 expression was downregulated in the subgroup of EOOSC patients. In addition, high LAG-3 expression was associated with longer overall survival [ 92 ].…”

Section: Lag-3mentioning

confidence: 99%

The Role of TIM-3 and LAG-3 in the Microenvironment and Immunotherapy of Ovarian Cancer

2022

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Ovarian cancer has the highest mortality rate among gynecologic malignancies. The main treatment options are surgical removal of the tumor and chemotherapy. Cancer treatment has been revolutionized by immunotherapy, which has developed explosively over the past two decades. Clinical anticancer strategies used in immunotherapy include therapies based on the inhibition of PD-1, PD-L1 or CTLA-4. Despite encouraging results, a large proportion of cancer patients are resistant to these therapies or eventually develop resistance. It is important to perform research that will focus on immunotherapy based on other immune checkpoint inhibitors. The aim of the review was to analyze studies considering the expression of TIM-3 and LAG-3 in the ovarian cancer microenvironment and considering immunotherapy for ovarian cancer that includes antibodies directed against TIM-3 and LAG-3. As the data showed, the expression of the described immune checkpoints was shown in different ways. Higher TIM-3 expression was associated with a more advanced tumor stage. Both TIM-3 and LAG-3 were co-expressed with PD-1 in a large proportion of studies. The effect of LAG-3 expression on progression-free survival and/or overall survival is inconclusive and certainly requires further study. Co-expression of immune checkpoints prompts combination therapies using anti-LAG-3 or anti-TIM-3. Research on immune checkpoints, especially TIM-3 and LAG-3, should be further developed.

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“… 13 Ma et al revealed that the expression of key genes varies between young patients (under 50 years old) and old patients (over 50 years old) those who diagnosed with ovarian serous cystadenocarcinoma. 14 One fly in the ointment is that the study did not testify to the sufficient reason that why 50 years old was chosen as the age threshold for AOSC.…”

Section: Introductionmentioning

confidence: 99%

Significant Prognostic Factor at Age Cut-off of 73 Years for Advanced Ovarian Serous Cystadenocarcinoma Patients: Insights from Real-World Study

Zhang,

Feng,

Wang

et al. 2024

IJWH

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Objective The objective of this research was to determine the age cut-off for worse prognosis and investigate age-related differentially expressed genes (DEGs) in patients with advanced ovarian serous cystadenocarcinoma (AOSC). Methods In this research, we included a cohort of 20,846 patients diagnosed with AOSC, along with RNA-seq data from 374 patients in publicly available databases. Then we used the X-tile software to determine the age cut-off and stratified the patients into young and old groups. We utilized propensity score matching (PSM) to balance baseline between the young and old groups. Furthermore, we conducted an enrichment analysis of DEGs between the two age groups using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) to identify dysregulated pathways. To evaluate the potential prognostic value of the DEGs, we performed survival analysis, such as Kaplan-Meier analysis and Log rank test. Results We stratified the patients into young group (n=16,336) and old group (n=4510) based on the cut-off age of 73 years by X-tile software. Age over 73 years was identified as an independent risk factor for overall survival (OS) and cancer-specific survival (CSS). Next, we identified 436 DEGs and found that the neurotrophin signaling pathway and translation factor activity were associated with prognosis outcomes. Among the top 10 hub genes ( RELA, NFKBIA, TRAF6, IRAK2, TAB3, AKT1, TBP, EIF2S2, MAPK10, and SUPT3H), RELA, TAB3, AKT1, TBP , and SUPT3H were found to be significantly associated with poor prognosis in old patients with AOSC. Conclusion Our study determined 73 years as the cutoff value for age in patients with AOSC. RELA, TAB3, AKT1, TBP , and SUPT3H were identified as age-related DEGs that could contribute to the poor prognosis of older patients with AOSC.

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Identification of Key Factors Associated with Early- and Late-Onset Ovarian Serous Cystadenocarcinoma

Cited by 3 publications

References 44 publications

Detecting predicted cancer-testis antigens in proteomics datasets of healthy and tumoral samples

Detecting predicted cancer-testis antigens in proteomics datasets of healthy and tumoral samples

The Role of TIM-3 and LAG-3 in the Microenvironment and Immunotherapy of Ovarian Cancer

Significant Prognostic Factor at Age Cut-off of 73 Years for Advanced Ovarian Serous Cystadenocarcinoma Patients: Insights from Real-World Study

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