Results 191 to 200 of about 1,083,966 (327)

Multiplex single‐cell profiling of putative cancer stem cell markers ALDH1, SOX9, SOX2, CD44, CD133 and CD15 in endometrial cancer

open access: yesMolecular Oncology, EarlyView.
Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien   +7 more
wiley   +1 more source

On the Sectional Curvature of Holomorphic Curvature Operators [PDF]

open access: yesProceedings of the American Mathematical Society, 1981
Stanley M. Zoltek, Ignacio Guerrero
openaire   +1 more source

Stroma gene signature predicts responsiveness to chemotherapy in pancreatic ductal adenocarcinoma patient‐derived xenograft models

open access: yesMolecular Oncology, EarlyView.
Pancreatic ductal adenocarcinoma patient‐derived xenografts (PDAC‐PDXs) engrafted orthotopically in the pancreas of immunodeficient mice retain the main genetic and histopathological characteristics of the original human tumors. A 294 stroma gene signature differentiates between PDAC‐PDXs that are responsive to gemcitabine plus nab‐paclitaxel versus ...
Alessia Anastasia   +13 more
wiley   +1 more source

Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression

open access: yesMolecular Oncology, EarlyView.
Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park   +6 more
wiley   +1 more source

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

open access: yesMolecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song   +13 more
wiley   +1 more source

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