Time out for TNM

Benson, JR

doi:10.1016/0140-6736(92)91176-9

Cited by 2 publications

(2 citation statements)

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“…Clinically, the TNM system is frequently used to classify cancers by the size of the primary tumor (T), presence or not in lymph nodes (N), and metastases (M). 5 On the basis of receptor protein status, the molecular classification divides human breast cancer into five intrinsic subtypes: Luminal A, Luminal B, basal-like, HER-2, and normal-like. 4 However, as a highly heterogeneous and complex human disease, this classification system based only on several molecules has frequently become less successful in choosing treatment methods and predicting the consequences.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Clinically, the TNM system is frequently used to classify cancers by the size of the primary tumor (T), presence or not in lymph nodes (N), and metastases (M) . On the basis of receptor protein status, the molecular classification divides human breast cancer into five intrinsic subtypes: Luminal A, Luminal B, basal-like, HER-2, and normal-like .…”

Section: Introductionmentioning

confidence: 99%

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Integrated Proteomic and N-Glycoproteomic Analyses of Human Breast Cancer

et al. 2020

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Breast cancer is one of the most common cancers in women worldwide. In the past decades, many advances have been made in understanding and treating breast cancer. However, due to the highly heterogeneous nature of this disease, a precise characterization of breast cancer on the molecular level is of great importance but not yet readily available. In the present study, we systematically profiled proteomes and N-glycoproteomes of cancerous, paracancerous, and distal noncancerous tissues from patients with breast cancer. The data revealed distinct proteomic and N-glycoproteomic landscapes between different tissues, showing biological insights obtained from the two data sets were complementary. Specifically, the complement and angiogenesis pathways in the paracancerous tissues were activated. Taken together, the changes that occurred in paracancer tissue and N-glycoproteomics are important complements to the conventional proteomic analysis of cancer tissue. Their combination provides more precise and sensitive molecular correlates of breast cancer. Our data and strategy shed light on precisely defining breast cancer, providing valuable information for individual patient diagnosis and treatment. The MS data of this study have been deposited under the accession number IPX0001924000 at iProX.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%