{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["17(2)"],"submitter":["Bhat P"],"pubmed_abstract":["<b>Background/Objectives:</b> Predicting the behavior of clear cell renal cell carcinoma (ccRCC) is challenging using standard-of-care histopathologic examination. Indeed, pathologic RCC tumor grading, based on nuclear morphology, performs poorly in predicting outcomes of patients with International Society of Urological Pathology/World Health Organization grade 2 and 3 tumors, which account for most ccRCCs. <b>Methods:</b> We applied spatial point process modeling of H&E-stained images of patients with grade 2 and grade 3 ccRCCs (<i>n</i> = 72) to find optimum separation into two groups. <b>Results:</b> One group was associated with greater spatial randomness and clinical metastasis (<i>p</i> < 0.01). Notably, spatial analysis outperformed standard pathologic grading in predicting clinica"],"journal":["Cancers"],"pagination":["249"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11763402"],"repository":["biostudies-literature"],"pubmed_title":["Spatial Distribution of Tumor Cells in Clear Cell Renal Cell Carcinoma Is Associated with Metastasis and a Matrisome Gene Expression Signature."],"pmcid":["PMC11763402"],"pubmed_authors":["Sircar K","Kannan K","Tamboli P","Bhat P"],"additional_accession":[]},"is_claimable":false,"name":"Spatial Distribution of Tumor Cells in Clear Cell Renal Cell Carcinoma Is Associated with Metastasis and a Matrisome Gene Expression Signature.","description":"<b>Background/Objectives:</b> Predicting the behavior of clear cell renal cell carcinoma (ccRCC) is challenging using standard-of-care histopathologic examination. Indeed, pathologic RCC tumor grading, based on nuclear morphology, performs poorly in predicting outcomes of patients with International Society of Urological Pathology/World Health Organization grade 2 and 3 tumors, which account for most ccRCCs. <b>Methods:</b> We applied spatial point process modeling of H&E-stained images of patients with grade 2 and grade 3 ccRCCs (<i>n</i> = 72) to find optimum separation into two groups. <b>Results:</b> One group was associated with greater spatial randomness and clinical metastasis (<i>p</i> < 0.01). Notably, spatial analysis outperformed standard pathologic grading in predicting clinica","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2025-04-18T14:27:48.946Z","creation":"2025-04-07T00:38:04.351Z"},"accession":"S-EPMC11763402","cross_references":{"pubmed":["39858031"],"doi":["10.3390/cancers17020249"]}}