Methodological advances of bioanalysis and biochemical targeting of intracellular G‐quadruplexes

Teng, Xianliang; Dai, Yicong; Li, Shanpeng

doi:10.1002/exp.20210214

Cited by 9 publications

(5 citation statements)

References 149 publications

(201 reference statements)

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“…Patients with EO-CRC differ from those with later-onset CRC in underlying molecular mechanisms ( 37 – 40 ), clinical features, and treatment ( 41 ). This special population warrants further attention in the future.…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early−onset colorectal cancer

Yin,

Pei,

et al. 2024

Front. Oncol.

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PurposeThis study aimed to identify prognostic factors and develop a nomogram for predicting overall survival (OS) in stage III/IV early-onset colorectal cancer (EO-CRC).MethodsStage III/IV EO-CRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The datasets were randomly divided (2:1) into training and validation sets. A nomogram predicting OS was developed based on the prognostic factors identified by Cox regression analysis in the training cohort. Moreover, the predictive performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Subsequently, the internal validation was performed using the validation cohort. Finally, a risk stratification system was established based on the constructed nomogram.ResultsOf the 10,387 patients diagnosed with stage III/IV EO-CRC between 2010 and 2015 in the SEER database, 8,130 patients were included. In the training cohort (n=3,071), sex, marital status, race/ethnicity, primary site, histologic subtypes, grade, T stage, and N stage were identified as independent prognostic variables for OS. The 1-, 3-, and 5-year area under the curve (AUC) values of the nomogram were robust in both the training (0.751, 0.739, and 0.723) and validation cohorts (0.748, 0.733, and 0.720). ROC, calibration plots, and DCA indicated good predictive performance of the nomogram in both the training and validation sets. Furthermore, patients were categorized into low-, middle-, and high-risk groups based on the nomogram risk score. Kaplan-Meier curve showed significant survival differences between the three groups.ConclusionWe developed a prognostic nomogram and risk stratification system for stage III/IV EO-CRC, which may facilitate clinical decision-making and individual prognosis prediction.

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Section: Discussionmentioning

confidence: 99%

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early−onset colorectal cancer

Yin,

Pei,

et al. 2024

Front. Oncol.

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“…Fourth, our research primarily concentrated on demographic and clinical factors. Some researchers have already initiated studies on the impact of molecular biological factors on cancer ( 34 ). Therefore, incorporating these relevant factors in the future could enhance the depth of our predictive model.…”

Section: Discussionmentioning

confidence: 99%

A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy

Zhang,

Sheng,

Qiao

et al. 2024

Front. Oncol.

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IntroductionThis study aimed to assess factors affecting the prognosis of early-stage hepatocellular carcinoma (HCC) patients undergoing ablation therapy and create a nomogram for predicting their 3-, 5-, and 8-year overall survival (OS).MethodsThe research included 881 early-stage HCC patients treated at Beijing You’an Hospital, affiliated with Capital Medical University, from 2014 to 2022. A nomogram was developed using independent prognostic factors identified by Lasso and multivariate Cox regression analyses. Its predictive performance was evaluated with concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).ResultsThe study identified age, tumor number, tumor size, gamma-glutamyl transpeptidase (GGT), international normalized ratio (INR), and prealbumin (Palb) as independent prognostic risk factors. The nomogram achieved C-indices of 0.683 (primary cohort) and 0.652 (validation cohort), with Area Under the Curve (AUC) values of 0.776, 0.779, and 0.822 (3-year, 5-year, and 8-year OS, primary cohort) and 0.658, 0.724, and 0.792 (validation cohort), indicating that the nomogram possessed strong discriminative ability. Calibration and DCA curves further confirmed the nomogram’s predictive accuracy and clinical utility. The nomogram can effectively stratify patients into low-, intermediate-, and high-risk groups, particularly identifying high-risk patients.ConclusionsThe established nomogram in our study can provide precise prognostic information for HCC patients following ablation treatment and enable physicians to accurately identify high-risk individuals and facilitate timely intervention.

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“…Noncanonical base pairing occurs when bases interact differently from the standard Watson–Crick rules, which enriches the diversity of DNA structure and facilitates the development of functional modules. , Several DNA conformations function as natural gene regulators in specific pathological conditions, particularly the G-quadruplex and the i-motif, which form unique secondary structures through Hoogsteen base pairing or C:C + base pairing. For instance, the low stability of G-quadruplex in K + -deprived environments is advantageous for gene transcription in invasive cancer cells containing the c-Myc protooncogene .…”

Section: Dynamic Assembly/disassembly Of Ncs For Biomedical Imagingmentioning

confidence: 99%

DNA-Driven Dynamic Assembly/Disassembly of Inorganic Nanocrystals for Biomedical Imaging

Yang

Wang

et al. 2023

Chemical & Biomedical Imaging

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DNA-mediated programming is emerging as an effective technology that enables controlled dynamic assembly/disassembly of inorganic nanocrystals (NC) with precise numbers and spatial locations for biomedical imaging applications. In this review, we will begin with a brief overview of the rules of NC dynamic assembly driven by DNA ligands, and the research progress on the relationship between NC assembly modes and their biomedical imaging performance. Then, we will give examples on how the driven program is designed by different interactions through the configuration switching of DNA-NC conjugates for biomedical applications. Finally, we will conclude with the current challenges and future perspectives of this emerging field. Hopefully, this review will deepen our knowledge on the DNA-guided precise assembly of NCs, which may further inspire the future development of smart chemical imaging devices and high-performance biomedical imaging probes.

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Methodological advances of bioanalysis and biochemical targeting of intracellular G‐quadruplexes

Cited by 9 publications

References 149 publications

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early−onset colorectal cancer

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early−onset colorectal cancer

A novel nomogram to predict the overall survival of early-stage hepatocellular carcinoma patients following ablation therapy

DNA-Driven Dynamic Assembly/Disassembly of Inorganic Nanocrystals for Biomedical Imaging

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