Clinical importance of high-mannose, fucosylated and complex N-glycans in breast cancer metastasis

Breast cancer metastasizes to lymph nodes or other organs, which determine the prognosis of patients. It is difficult to cure the breast cancer patients with distant metastasis due to resistance to drug therapies. Elucidating the underlying mechanisms of breast cancer metastasis and drug resistance is expected to provide new therapeutic targets. Sphingosine-1-phosphate (S1P) is a pleiotropic, bioactive lipid mediator that regulates many cellular functions, including proliferation, migration, survival, angiogenesis/lymphangiogenesis, and immune responses. S1P is formed in cells by sphingosine kinases and released from them, which acts in an autocrine, paracrine, and/or endocrine manner. S1P in extracellular space, such as interstitial fluid, interacts with components in the tumor microenvironment, which may be important for metastasis. Importantly, recent translational research has demonstrated an association between S1P levels in breast cancer patients and clinical outcomes, highlighting the clinical importance of S1P in breast cancer. We suggest that S1P is one of the key molecules to overcome the resistance to the drug therapies, such as hormonal therapy, anti-HER2 therapy, or chemotherapy, all of which are crucial aspects of a breast cancer treatment.

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Mechanisms of bone metastases of breast cancer

Endocrine Related Cancer ◽

10.1677/erc-09-0012 ◽

2009 ◽

Vol 16 (3) ◽

pp. 703-713 ◽

Cited By ~ 66

Author(s):

Larry J Suva ◽

Robert J Griffin ◽

Issam Makhoul

Keyword(s):

Breast Cancer ◽

Stem Cells ◽

Molecular Mechanisms ◽

Cancer Metastasis ◽

Clinical Importance ◽

Metastatic Breast ◽

Genetic Alterations ◽

Breast Cancer Metastasis ◽

Molecular Events ◽

Metastatic Sites

Cancer development is a multi-step process driven by genetic alterations that elicit the progressive transformation of normal human cells into highly malignant derivatives. The altered cell proliferation phenotype of cancer involves a poorly characterized sequence of molecular events, which often result in the development of distant metastasis. In the case of breast cancer, the skeleton is among the most common of metastatic sites. In spite of its clinical importance, the underlying cellular and molecular mechanisms driving bone metastasis remain elusive. Despite advances in our understanding of the phenotype of cancer cells, the increased focus on the contribution of the tumor microenvironment and the recent revival of interest in the role of tumor-propagating cells (so called cancer stem cells) that may originate or be related to normal stem cells produced in the bone marrow, many important questions remain unanswered. As such, a more complete understanding of the influences of both the microenvironment and the tumor phenotype, which impact the entire multi-step metastatic cascade, is required. In this review, the importance of tumor heterogeneity, tumor-propagating cells, the microenvironment of breast cancer metastasis to bone as well as many current endocrine therapies for the prevention and treatment of metastatic breast cancer is discussed.

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Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis

Bioinformatics ◽

10.1093/bioinformatics/btaa396 ◽

2020 ◽

Vol 36 (Supplement_1) ◽

pp. i407-i416

Author(s):

Yifeng Tao ◽

Haoyun Lei ◽

Xuecong Fu ◽

Adrian V Lee ◽

Jian Ma ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Metastasis ◽

Clonal Evolution ◽

Evolutionary Process ◽

Clinical Importance ◽

Breast Cancer Metastasis ◽

Accurate Solution ◽

Supplementary Information ◽

Gene Module ◽

Evolutionary Mechanisms

Abstract Motivation Cancer develops and progresses through a clonal evolutionary process. Understanding progression to metastasis is of particular clinical importance, but is not easily analyzed by recent methods because it generally requires studying samples gathered years apart, for which modern single-cell sequencing is rarely an option. Revealing the clonal evolution mechanisms in the metastatic transition thus still depends on unmixing tumor subpopulations from bulk genomic data. Methods We develop a novel toolkit called robust and accurate deconvolution (RAD) to deconvolve biologically meaningful tumor populations from multiple transcriptomic samples spanning the two progression states. RAD uses gene module compression to mitigate considerable noise in RNA, and a hybrid optimizer to achieve a robust and accurate solution. Finally, we apply a phylogenetic algorithm to infer how associated cell populations adapt across the metastatic transition via changes in expression programs and cell-type composition. Results We validated the superior robustness and accuracy of RAD over alternative algorithms on a real dataset, and validated the effectiveness of gene module compression on both simulated and real bulk RNA data. We further applied the methods to a breast cancer metastasis dataset, and discovered common early events that promote tumor progression and migration to different metastatic sites, such as dysregulation of ECM-receptor, focal adhesion and PI3k-Akt pathways. Availability and implementation The source code of the RAD package, models, experiments and technical details such as parameters, is available at https://github.com/CMUSchwartzLab/RAD. Supplementary information Supplementary data are available at Bioinformatics online.

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