A tumor microenvironment preoperative nomogram for prediction of lymph node metastasis in bladder cancer

Chen, Zhenghao; Qin, Chuan; Wang, Gang; Shang, Donghao; Yuan, Lushun; Cao, Rui

doi:10.3389/fonc.2022.1099965

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…This limitation of technology creates an uncertainty for CLNs akin to Schrodinger's cat, where metastasis is hard to determine before lymph nodes are removed and examined histopathologically. Emerging non‐invasive methods for assessing CLNs primarily include artificial intelligence‐assisted predictive models, 86,87 nanoparticle‐based lymphatic system imaging, 88 and biomarker‐based liquid biopsies 89 . These studies are still in the experimental stage, and their widespread clinical application remains a distant goal.…”

Section: Dilemmas and Prospectsmentioning

confidence: 99%

Lymph node metastasis in oral squamous cell carcinoma: Where we are and where we are going

Cao

Zhong

et al. 2023

Clinical and Translational Dis

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BackgroundOral cancer is a common malignant tumour in the head and neck region, with over 90% of cases being oral squamous cell carcinoma (OSCC). Lymph node metastasis (LNM) is a significant adverse prognostic factor in OSCC; however, the mechanism of LNM in OSCC remains unclear, while the strategies for managing cervical lymph nodes (CLNs) in OSCC continue to evolve. At present, neck dissection is necessary for the vast majority of OSCC patients, but complications of surgery can significantly impair patients’ postoperative quality of life. A recent clinical trial discovery indicates that immunotherapy can activate anti‐tumour T cells in nearby lymph nodes, leading to vibrant discussions among clinicians about the importance of preserving lymph nodes during surgical treatment.AimThis review aims to provide an overview of where we are: the current knowledge of OSCC LNM patterns and management strategies, and where we are going: prospects for clinical and basic research on the issue of OSCC LNM in the era of cancer immunotherapy.ResultWe summarize the general patterns and management strategies of OSCC LNM. The process of LNM in OSCC encompasses four stages: Preparation, Unleash, Migration, and Planting (‘PUMP’ principle). We propose adopting the ‘PRECISE’ model, an overall workflow that includes seven elements—prevention, radiology, preoperative evaluation, chemotherapy, immunotherapy, surgery, and postoperative evaluation—for neck management in OSCC, promoting personalized precision medicine augmented by neoadjuvant therapy. We further discussed recent advances in clinical and basic research on OSCC LNM and provided an outlook on future research directions.ConclusionOver the past two centuries, our understanding and management strategies of LNM in OSCC have evolved, seeking more precise and personalized approaches to reduce patient burden and enhance survival and quality of life. Further research should explore lymph nodes’ role in cancer immunotherapy and OSCC interactions, leading to better, less invasive treatments and improved outcomes.

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Section: Dilemmas and Prospectsmentioning

confidence: 99%

Lymph node metastasis in oral squamous cell carcinoma: Where we are and where we are going

Cao

Zhong

et al. 2023

Clinical and Translational Dis

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Roles of non-coding RNAs in the metabolism and pathogenesis of bladder cancer

Sanya

Onésime

2023

Human Cell

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Evaluation of gene expression-based predictors of lymph node metastasis in bladder cancer

Johansson,

Liedberg,

Bernardo

et al. 2024

Preprint

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The presence of cancer in pelvic lymph nodes removed during radical surgery for muscle-invasive bladder cancer (MIBC) is a key determinant of patient outcome. It would be beneficial to predict node status preoperatively to individually tailor the use of neoadjuvant chemotherapy and extent of lymph node dissection. Several studies have published node status predictors based on RNA expression signatures in the primary tumor, but none have been successfully validated in subsequent reports. We use gene expression data and node status from the two largest available MIBC cohorts to evaluate 12 published node-predictive signatures. Additionally, we examine the extent of overlap between differentially expressed genes and signatures across the two datasets, and we train new prediction models which we evaluate in cross-validation and by application to the independent cohort. All published node status predictors performed either no better than chance or only slightly better than chance in two independent validation datasets (maximal AUC 0.59 and 0.65 and maximum balanced accuracy 0.54 and 0.57 in the two cohorts). Most differentially expressed genes and signatures were only identified in one dataset and only a few, such as upregulation of interferon-response in node negative cases, were enriched in the same direction in both datasets. Transcriptomic predictors trained in one dataset performed poorly when applied to the other independent dataset (AUC 0.60 and 0.62). In this systematic evaluation, neither the 12 published signatures nor our own models reached an adequate performance for clinical node status prediction in independent data. This indicates that the biological determinants of nodal spread are poorly captured by bulk tumor RNA expression profiles.

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A tumor microenvironment preoperative nomogram for prediction of lymph node metastasis in bladder cancer

Cited by 3 publications

References 45 publications

Lymph node metastasis in oral squamous cell carcinoma: Where we are and where we are going

Lymph node metastasis in oral squamous cell carcinoma: Where we are and where we are going

Roles of non-coding RNAs in the metabolism and pathogenesis of bladder cancer

Evaluation of gene expression-based predictors of lymph node metastasis in bladder cancer

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