Haemostatic Proteins as Markers of Disease Progression and Prognosis in Breast Cancer

Review preprint OA: closed CC-BY-4.0

Abstract

BACKGROUND: Breast cancer is a leading cause of cancer death in women worldwide. One of the major causes of death from breast cancer is metastatic disease which results from the malignant cells invading and migrating through blood vessels to distant sites. TEXT: Several studies have shown that metastasis is facilitated by haemostatic proteins. Breast cancer is characterized by haemostatic imbalance which is tilted more to a procoagulant state with resultant thrombotic complications. These elements that are involved in thrombosis also play key roles in different aspects of breast cancer growth including cancer proliferation and progression, cancer survival, angiogenesis and metastasis. Some of these elements include platelets, endothelial cells, coagulation factors and fibrinolytic proteins. There is a close relationship between cancer and many of the haemostatic elements. They are usually increased in metastatic breast cancer, and have found use as predictive and prognostic markers. Some have been validated in breast cancer. Due to their seemingly active roles in breast cancer progression, some of the haemostatic proteins are being developed as diagnostic tools in the management of breast cancer. They are equally being seen as potential targets for the development of novel therapies in breast cancer or repurposing drugs in current use for the same gain. CONCLUSION: This review highlights the role haemostatic proteins play in breast cancer progression, and their diagnostic and therapeutic relevance.
Full text 621 characters · extracted from oa-doi-fallback · click to expand
There is a newer version available for this {{ publicationType }}. View latest version {{ publication.field_name }} {{ publication.subfield_name }} Copyright: © {{ publicationYear }} {{ publication.presentation_authors[0].full_name + (publication.presentation_authors.length > 1 ? ' et al' : '') }}. This is an open access publication distributed under the terms of the CC BY 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Check the {{ publicationType | capitalize }} Source for copyright and license information. Listen on

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

⚙ Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback ⓘ

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-08-14T06:25:32.811723+00:00
License: CC-BY-4.0