Emerging Biomarkers and Clinical Implications in Endometrial Carcinoma

Daley-Brown, Danielle; Oprea‐Ilies, Gabriela; Quarshie, Alexander; Gonzalez-Perez, Ruben R.

doi:10.5772/62772

Cited by 3 publications

(2 citation statements)

References 75 publications

(124 reference statements)

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“…Uterine washing samples were collected from consenting cancer patients with diagnoses of several gynecologic conditions, including ovarian and endometrial cancers (fig. S6) (30,(62)(63)(64). To investigate the ability of the platform to detect multiple biomarkers in a patient biofluid sample, we tested the optimized platform in uterine washings.…”

Section: Uterine Lavage Patient Samplesmentioning

confidence: 99%

A perception-based nanosensor platform to detect cancer biomarkers

et al. 2021

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Section: Uterine Lavage Patient Samplesmentioning

confidence: 99%

A perception-based nanosensor platform to detect cancer biomarkers

et al. 2021

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“…S6). 30,[59][60][61] To investigate the ability of the platform to detect multiple biomarkers in a patient biofluid sample, we tested the optimized MP platform in uterine washings. We incubated the DNA-SWCNT complexes in uterine lavage samples (N=22).…”

Section: Uterine Lavage Patient Samplesmentioning

confidence: 99%

Machine-Perception Nanosensor Platform to Detect Cancer Biomarkers

Yaari

Yang

Apfelbaum

et al. 2021

Preprint

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Conventional molecular recognition elements, such as antibodies, present issues for the development of biomolecular assays for use in point-of-care devices, implantable/wearables, and under-resourced settings. Additionally, antibody development and use, especially for highly multiplexed applications, can be slow and costly. We developed a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids. We demonstrated this platform in gynecologic cancers, which are often diagnosed at advanced stages, leading to low survival rates. We investigated the platform for detection in uterine lavage samples, which are enriched with cancer biomarkers compared to blood. We found that the method enables the simultaneous detection of multiple biomarkers in patient samples, with F1-scores of ~0.95 in uterine lavage samples from cancer patients. This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements.

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Potential new biomarkers for endometrial cancer

et al. 2019

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BackgroundIncidence of endometrial cancer are rising both in the United States and worldwide. As endometrial cancer becomes more prominent, the need to develop and characterize biomarkers for early stage diagnosis and the treatment of endometrial cancer has become an important priority. Several biomarkers currently used to diagnose endometrial cancer are directly related to obesity. Although epigenetic and mutational biomarkers have been identified and have resulted in treatment options for patients with specific aberrations, many tumors do not harbor those specific aberrations. A promising alternative is to determine biomarkers based on differential gene expression, which can be used to estimate prognosis.MethodsWe evaluated 589 patients to determine differential expression between normal and malignant patient samples. We then supplemented these evaluations with immunohistochemistry staining of endometrial tumors and normal tissues. Additionally, we used the Library of Integrated Network-based Cellular Signatures to evaluate the effects of 1826 chemotherapy drugs on 26 cell lines to determine the effects of each drug on HPRT1 and AURKA expression.ResultsExpression of HPRT1, Jag2, AURKA, and PGK1 were elevated when compared to normal samples, and HPRT1 and PGK1 showed a stepwise elevation in expression that was significantly related to cancer grade. To determine the prognostic potential of these genes, we evaluated patient outcome and found that levels of both HPRT1 and AURKA were significantly correlated with overall patient survival. When evaluating drugs that had the most significant effect on lowering the expression of HPRT1 and AURKA, we found that Topo I and MEK inhibitors were most effective at reducing HPRT1 expression. Meanwhile, drugs that were effective at reducing AURKA expression were more diverse (MEK, Topo I, MELK, HDAC, etc.). The effects of these drugs on the expression of HPRT1 and AURKA provides insight into their role within cellular maintenance.ConclusionsCollectively, these data show that JAG2, AURKA, PGK1, and HRPT1 have the potential to be used independently as diagnostic, prognostic, or treatment biomarkers in endometrial cancer. Expression levels of these genes may provide physicians with insight into tumor aggressiveness and chemotherapy drugs that are well suited to individual patients.

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Emerging Biomarkers and Clinical Implications in Endometrial Carcinoma

Cited by 3 publications

References 75 publications

A perception-based nanosensor platform to detect cancer biomarkers

A perception-based nanosensor platform to detect cancer biomarkers

Machine-Perception Nanosensor Platform to Detect Cancer Biomarkers

Potential new biomarkers for endometrial cancer

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