High Expression of SLC16A1 as a Biomarker to Predict Poor Prognosis of Urological Cancers

Zhang, Ling; Song, Zhengshuai; Wang, Zhishun; Guo, Yonglian; Xu, Changgeng; Shen, Hao

doi:10.3389/fonc.2021.706883

Cited by 8 publications

(6 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…29 Additional candidates are reported to be involved in cancer prognosis and progression, including TSPAN11, 30 NKX6-1, 31 and SLC16A1. 32 Gene enrichment analysis 33 identified significant associations (adjusted p < 0.05) between our gene candidates and macular thickness and degeneration, as seen in previous human GWAS studies 34 and cataract formation (Elsevier pathway collection), 35 as well as non-eye related diseases such as bone mineralization, tumor suppression, and Amyloid Precursor Protein pathways (Biocarta). 36 Gene Ontology (GO) term analysis of our gene candidates revealed significant enrichment (adjusted p < 0.05) for protein tyrosine kinase activator activity, gap junction channel activity, and wide pore channel activity (Figure 4B).…”

Section: Gwas and Experimental Validation Of Alksupporting

confidence: 65%

See 1 more Smart Citation

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Ahadi

Wilson

Babenko

et al. 2022

Preprint

View full text Add to dashboard Cite

Biological age, distinct from an individual's chronological age, has been studied extensively through predictive aging clocks. However, these clocks have limited accuracy in short time-scales. Deep learning approaches on imaging datasets of the eye have proven powerful for a variety of quantitative phenotype inference tasks and provide an opportunity to explore organismal aging and tissue health. Here we trained deep learning models on fundus images from the EyePACS dataset to predict individuals' chronological age. These predictions led to the concept of a retinal aging clock, eyeAge, which we employed for a series of downstream longitudinal analyses. eyeAge was used to predict chronological age on timescales under a year using longitudinal fundus imaging data from a subset of patients. To further validate the model, it was applied to a separate cohort from the UK Biobank. The difference between individuals' eyeAge and their chronological age, hereafter eyeAgeAccel, was computed and used for genome-wide association analysis (GWAS). EyeAge predicted chronological age more accurately than other aging clocks (mean absolute error of 2.86 and 3.30 years on quality-filtered data from EyePACS and UKBiobank, respectively). Additionally, eyeAgeAccel was highly independent of blood marker-based measures of biological age (e.g. phenotypic age), maintaining an all-cause mortality hazard ratio of 1.026 even in the presence of phenotypic age. Longitudinal studies showed that the resulting models were able to predict individuals' aging, in time-scales less than a year, with 71% accuracy. The individual-specific component to this prediction was confirmed with the identification of multiple GWAS hits in the independent UK Biobank cohort. The knockdown of the fly homolog to the top hit, ALKAL2, which was previously shown to extend lifespan in flies, also slowed age-related decline in vision in flies. In conclusion, predicted age from retinal images can be used as a biomarker of biological aging that is independent from assessment based on blood markers. This study demonstrates the potential utility of a retinal aging clock for studying aging and age-related diseases and quantitatively measuring aging on very short time-scales, opening avenues for quick and actionable evaluation of gero-protective therapeutics.

show abstract

Section: Gwas and Experimental Validation Of Alksupporting

confidence: 65%

“…29 Additional candidates are reported to be involved in cancer prognosis and progression, including TSPAN11 , 30 NKX6-1 , 31 and SLC16A1 . 32…”

Section: Resultsmentioning

confidence: 99%

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Ahadi

Wilson

Babenko

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…MEF2C has reported roles in numerous age-related conditions, including Alzheimer’s disease ( Xue et al, 2021 ) and muscle wasting in cancer ( Judge et al, 2020 ) and GRM is associated with age-related hearing loss ( Liu et al, 2021b ). Additional candidates are reported to be involved in cancer prognosis and progression, including TSPAN11 ( Liu et al, 2021a ), NKX6-1 ( Su et al, 2021 ), and SLC16A1 ( Zhang et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Ahadi

Wilson

Babenko

et al. 2023

eLife

View full text Add to dashboard Cite

Biological age, distinct from an individual's chronological age, has been studied extensively through predictive aging clocks. However, these clocks have limited accuracy in short time-scales. Here we trained deep learning models on fundus images from the EyePACS dataset to predict individuals' chronological age. Our retinal aging clocking, 'eyeAge', predicted chronological age more accurately than other aging clocks (mean absolute error of 2.86 and 3.30 years on quality-filtered data from EyePACS and UK Biobank, respectively). Additionally, eyeAge was independent of blood marker-based measures of biological age, maintaining an all-cause mortality hazard ratio of 1.026 even when adjusted for phenotypic age. The individual-specific nature of eyeAge was reinforced via multiple GWAS hits in the UK Biobank cohort. The top GWAS locus was further validated via knockdown of the fly homolog, Alk, which slowed age-related decline in vision in flies. This study demonstrates the potential utility of a retinal aging clock for studying aging and age-related diseases and quantitatively measuring aging on very short time-scales, opening avenues for quick and actionable evaluation of gero-protective therapeutics.

show abstract

“…In the present study and for the first time, hsa_circ_0013561 (circ-SLC16A1) was investigated in tissues from patients with NSCLC, and circ-SLC16A1 expression levels were demonstrated to be significantly upregulated in NSCLC tissues and cell lines. Previous studies have confirmed that SLC16A1 is expressed in almost all human tissues and overexpressed in many cancers, indicating poor prognosis [ 13 – 15 ]. Also, circ-SLC16A1 was mainly located in the cytoplasm, similar to other circRNAs [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

Oncogenic circ-SLC16A1 promotes progression of non-small cell lung cancer via regulation of the miR-1287-5p/profilin 2 axis

Jin,

Yuan,

Tian

et al. 2024

Cell Mol Biol Lett

View full text Add to dashboard Cite

Background Circular RNAs (circRNAs) are single-stranded RNAs with covalently closed structures that have been implicated in cancer progression. However, the regulatory mechanisms remain largely unclear. So, the aim of this study was to reveal the role and regulatory mechanisms of circ-SLC16A1. Methods In this study, next-generation sequencing was used to identify abnormally expressed circRNAs between cancerous and para-carcinoma tissues. Fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction were performed to assess the expression patterns of circ-solute carrier family 16 member 1 (SLC16A1) in non-small cell lung cancer (NSCLC) cells and tissue specimens. The dual-luciferase reporter assay was utilized to identify downstream targets of circ-SLC16A1. Transwell migration, wound healing, 5-ethynyl-2′-deoxyuridine incorporation, cell counting, and colony formation assays were conducted to assess the proliferation and migration of NSCLC cells. A mouse tumor xenograft model was employed to determine the roles of circ-SLC16A1 in NSCLC progression and metastasis in vivo. Results The results found that circ-SLC16A1 was upregulated in NSCLC cells and tissues. Downregulation of circ-SLC16A1 inhibited tumor growth by reducing proliferation, lung metastasis, and lymphatic metastasis of NSCLC cells, and arrested the cell cycle in the G1 phase. Also, silencing of circ-SLC16A1 promoted apoptosis of NSCLC cells. The results of bioinformatics analysis and the dual-luciferase reporter assay confirmed that microRNA (miR)-1287-5p and profilin 2 (PFN2) are downstream targets of circ-SLC16A1. PFN2 overexpression or circ-SLC16A1 inhibition restored proliferation and migration of NSCLC cells after silencing of circ-SLC16A1. PFN2 overexpression restored migration and proliferation of NSCLC cells post miR-1287-5p overexpression. Conclusions Collectively, these findings show that miR-1287-5p/PFN2 signaling was associated with downregulation of circ-SLC16A1 and reduced invasion and proliferation of NSCLC cells. So, circ-SLC16A1 is identified as a mediator of multiple pro-oncogenic signaling pathways in NSCLC and can be targeted to suppress tumor progression.

show abstract

High Expression of SLC16A1 as a Biomarker to Predict Poor Prognosis of Urological Cancers

Cited by 8 publications

References 37 publications

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Oncogenic circ-SLC16A1 promotes progression of non-small cell lung cancer via regulation of the miR-1287-5p/profilin 2 axis

Contact Info

Product

Resources

About