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Jiang-Kun Liu

Researcher at Harbin Medical University

Publications -  18
Citations -  83

Jiang-Kun Liu is an academic researcher from Harbin Medical University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 1, co-authored 1 publications receiving 25 citations.

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Targeting cell death pathways for cancer therapy: recent developments in necroptosis, pyroptosis, ferroptosis, and cuproptosis research

TL;DR: In this article , a review of the potential agents and nanoparticles that induce or inhibit RCD pathways and their therapeutic effects on cancer based on evidence from in vivo and in vitro studies and reports clinical trials in which RCD inducers have been evaluated as treatments for cancer patients.
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Sphere-forming tumor cells possess stem-like properties in human fibrosarcoma primary tumors and cell lines.

TL;DR: The data suggest the presence of a stem-like cell population in human fibrosarcoma tumors, which provides more evidence for the cancer stem cell hypothesis and assistance in designing new therapeutic strategies against human fibrous tissue tumors.
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Signaling pathways in cancer‐associated fibroblasts: recent advances and future perspectives

TL;DR: A comprehensive understanding of the signaling cascades in CAFs might help us better understand the roles of CAFs and the tumor microenvironment in cancer progression and may facilitate the development of more efficient and safer stroma-targeted cancer therapies as discussed by the authors .
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Comprehensive analysis of the prognosis and immune infiltration landscape of RNA methylation-related subtypes in pancreatic cancer

TL;DR: Wang et al. as mentioned in this paper used consensus clustering algorithm to identify two remarkably different subtypes, and a feasible risk stratification method was established to accurately estimate prognosis and the efficacy of immune therapy and chemotherapy.
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Comprehensive analysis of the prognosis and immune infiltration landscape of RNA methylation-related subtypes in pancreatic cancer

TL;DR: Wang et al. as mentioned in this paper used consensus clustering algorithm to identify two remarkably different subtypes, and a feasible risk stratification method was established to accurately estimate prognosis and the efficacy of immune therapy and chemotherapy.