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PLASMA: Partial LeAst Squares for Multiomics Analysis.
Cancers (Basel)
January 2025
Department of Biostatistics, Data Science, and Epidemiology, School of Public Health, Georgia Cancer Center at Augusta University, Augusta, GA 30912, USA.
: Recent growth in the number and applications of high-throughput "omics" technologies has created a need for better methods to integrate multiomics data. Much progress has been made in developing unsupervised methods, but supervised methods have lagged behind. : Here we present the first algorithm, PLASMA, that can learn to predict time-to-event outcomes from multiomics data sets, even when some samples have only been assayed on a subset of the omics data sets.
View Article and Find Full Text PDFHarnessing Machine Learning and Nomogram Models to Aid in Predicting Progression-Free Survival for Gastric Cancer Patients Post-Gastrectomy with Deficient Mismatch Repair(dMMR).
BMC Cancer
January 2025
Department of Gastroenterology, Shanxi Hospital Affiliated to Carcinoma Hospital, Chinese Academy of Medical SciencesShanxi Province Carcinoma Hospital, Carcinoma Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, 030013, People's Republic of China.
Objective: To assess the effectiveness of a machine learning framework and nomogram in predicting progression-free survival (PFS) post-radical gastrectomy in patients with dMMR.
Method: Machine learning models and nomograms to forecast PFS in patients undergoing radical gastrectomy for nonmetastatic gastric cancer with dMMR. Independent risk factors were identified using Cox regression analysis to develop the nomogram.
Incidence and Heritability of Gastric Carcinoma in the Belgian Shepherd Dog Population in The Netherlands.
Vet Sci
January 2025
Department of Clinical Sciences of Companion animals, Faculty of Veterinary Medicine, Utrecht University, 3584 CL Utrecht, The Netherlands.
Background: Gastric carcinoma in the Tervueren and Groenendael varieties of the Belgian Shepherd dog is commonly recognized and carries a grave prognosis. Information on incidence and heritability is necessary to design an effective selection strategy against this disease.
Methods: A database of cases and controls was built including cases with Tier 1 (confirmed via endoscopy or post-mortem) and Tier 2 evidence of gastric carcinoma.
Integrated single-cell RNA sequencing reveals the tumor heterogeneity and microenvironment landscape during liver metastasis in adenocarcinoma of esophagogastric junction.
Front Immunol
January 2025
Department of General Surgery, First Affiliated Hospital of Anhui Medical University, Hefei, China.
Background: Adenocarcinoma of the esophagogastric junction (AEGJ) is a highly aggressive tumor that frequently metastasizes to the liver. Understanding the cellular and molecular mechanisms that drive this process is essential for developing effective therapies.
Methods: We employed single-cell RNA sequencing to analyze the tumor heterogeneity and microenvironmental landscape in patients with AEGJ liver metastases.
Is it time to retire preoperative radiation for localized esophageal and gastro-esophageal adenocarcinoma?
Oncologist
January 2025
Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
Whether preoperative chemoradiotherapy (CRT) or perioperative chemotherapy is superior for localized esophageal or gastro-esophageal junction (GEJ) cancers has been a topic of long-standing debate. For years, standard of care in the United States for localized esophageal or GEJ adenocarcinoma (EAC) has been physician's choice between the 2 strategies. More recently, adjuvant immunotherapy has also been introduced into the treatment approach for those who received neoadjuvant CRT.
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