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Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction

Chen, Xinsong (author)
Karolinska Institutet
Sifakis, Emmanouil G. (author)
Karolinska Institutet
Robertson, Stephanie (author)
Karolinska Institutet
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Neo, Shi Yong (author)
Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden
Jun, Seong-Hwan (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab
Tong, Le (author)
Karolinska Institutet
Min, Apple Tay Hui (author)
Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden; School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore
Lövrot, John (author)
Karolinska Institutet
Hellgren, Roxanna (author)
Karolinska Institutet
Margolin, Sara (author)
Karolinska Institutet
Bergh, Jonas (author)
Karolinska Institutet
Foukakis, Theodoros (author)
Karolinska Institutet
Lagergren, Jens (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab,Department of Computational Biology, Royal Institute of Technology, Science for Life Laboratory, Stockholm 17165, Sweden
Lundqvist, Andreas (author)
Karolinska Institutet
Ma, Ran (author)
Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17164, Sweden
Hartman, Johan (author)
Karolinska Institutet
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 (creator_code:org_t)
2022-12-27
2023
English.
In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 120:1
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

Keyword

breast cancer
drug profiling
ex vivo culture
precision oncology
whole-tumor cell culture

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ref (subject category)
art (subject category)

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