Radiogenomics study to predict the nuclear grade of renal clear cell carcinoma

He, Xuan-ming; Zhao, Jian-Xin; He, Di-liang; Ren, Jialiang; Zhao, Lianping; Huang, Gang

doi:10.1016/j.ejro.2023.100476

Cited by 2 publications

(1 citation statement)

References 39 publications

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“…Radiotranscriptomics, an emerging discipline in recent years, integrates radiomics and genomics to provide a noninvasive and relatively efficient prediction of tumor molecules and the tumor microenvironment [ 9 ]. Radiotranscriptomics has demonstrated significant potential in various aspects of cancer research, including gene mutation, subtype differentiation, metastasis prediction, and prognosis assessment [ 10 , 11 ]. In our previous study, we identified three subtypes (proliferation, metabolism, and immune activation) by integrating radiomics and transcriptomics analyses, which confirmed that the radiotranscriptomics strategy helped stratify non-small cell lung cancer patients and provided radiomics features with molecular explanations and prognostic prediction [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Gao,

Pang,

Lin

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Gao,

Pang,

Lin

et al. 2024

Heliyon

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Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic

Lyskjær,

Iisager,

Axelsen

et al. 2023

Clinical Cancer Research

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The incidence of renal cell carcinoma (RCC) is increasing worldwide, yet research within this field is lagging behind other cancers. Despite increased detection of early disease as a consequence of the widespread use of diagnostic CT scans, 25% of patients have disseminated disease at diagnosis. Similarly, around 25% progress to metastatic disease following curatively intended surgery. Surgery is the cornerstone in the treatment of RCC, however when the disease is disseminated, immunotherapy or immunotherapy in combination with a tyrosine kinase inhibitor is the patient's best option. Immunotherapy is a potent treatment with durable treatment responses and potential to cure the patient, but only half of the patients benefit from the administered treatment, and there are currently no methods that can identify which patients will respond to immunotherapy. Moreover, there is a need to identify the patients in greatest risk of relapsing after surgery for localized disease and direct adjuvant treatment there. Even though several molecular biomarkers have been published to date, we are still lacking routinely used biomarkers to guide optimal clinical management. The purpose of this review is to highlight some of the most promising biomarkers, discuss the efforts made within this field to date and to describe the barriers needed to be overcome to have reliable and robust predictive and prognostic biomarkers in the clinic for renal cancer.

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Radiogenomics study to predict the nuclear grade of renal clear cell carcinoma

Cited by 2 publications

References 39 publications

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic

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