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Stand-alone transcriptional immune response prediction in primary triple-negative breast cancer

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Název: Stand-alone transcriptional immune response prediction in primary triple-negative breast cancer
Autoři: Roostee, Suze, Killander, Fredrika, Saghir, Hani, Nacer, Deborah F, Häkkinen, Jari, Sasiain, Iñaki, Veerla, Srinivas, Vallon-Christersson, Johan, Loman, Niklas, Ohlsson, Mattias, Staaf, Johan
Přispěvatelé: Lund University, Faculty of Science, Centre for Environmental and Climate Science (CEC), Computational Science for Health and Environment, Lunds universitet, Naturvetenskapliga fakulteten, Centrum för miljö- och klimatvetenskap (CEC), Beräkningsvetenskap för hälsa och miljö, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Breast/lungcancer, Research Group Lung Cancer, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Bröst/lungcancer, Forskningsgrupp Lungcancer, Originator, Lund University, Faculty of Medicine, Department of Laboratory Medicine, Division of Translational Cancer Research, Breast/lung cancer, Lunds universitet, Medicinska fakulteten, Institutionen för laboratoriemedicin, Avdelningen för translationell cancerforskning, Bröst/lungcancer, Originator, Lund University, Profile areas and other strong research environments, Other Strong Research Environments, LUCC: Lund University Cancer Centre, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Övriga starka forskningsmiljöer, LUCC: Lunds universitets cancercentrum, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Breast cancer treatment, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Bröstcancerbehandling, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Breast/ovarian cancer, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Bröst/ovarialcancer, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Breast/ovarian cancer, Breast and Ovarian Cancer Genomics, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Bröst/ovarialcancer, Bröst- och ovarialcancer, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section I, Breastcancer-genetics, Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion I, Bröstcancer-genetik, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Natural and Artificial Cognition, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Naturlig och artificiell kognition, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Section II, Thoracic Surgery, Artificial Intelligence in CardioThoracic Sciences (AICTS), Lunds universitet, Medicinska fakulteten, Institutionen för kliniska vetenskaper, Lund, Sektion II, Thoraxkirurgi, Artificiell intelligens och thoraxkirurgisk vetenskap (AICTS), Originator
Zdroj: Cancer Research Communications.
Témata: Medical and Health Sciences, Clinical Medicine, Cancer and Oncology, Medicin och hälsovetenskap, Klinisk medicin, Cancer och onkologi
Popis: Triple-negative breast cancer (TNBC) accounts for 10-20% of primary breast cancers and often has early relapses and aggressive progression. An activated tumour immune response can be prognostic in treatment-naive and chemotherapy-treated TNBC patients and may be assessed using gene expression data. We derived a stand-alone predictor for a proposed immunomodulatory transcriptional TNBC subtype in a training cohort of 235 patients with primary disease based on random forest modelling of RNA-sequencing data. Validation in independent TNBC cohorts totalling more than 1200 patients demonstrated that the classifier recapitulates the immunomodulatory mRNA subtype classification, is associated with elevated immune expression and diversity of T-cell receptor genes, is associated with response to neoadjuvant chemotherapy, and can separate patients into subgroups with better or worse prognosis after adjuvant chemotherapy. The availability of stand-alone classifiers for mRNA-based prediction may further enhance RNA-sequencing's usability in a more routine clinical context and for translational endpoints in clinical trials.
Přístupová URL adresa: https://doi.org/10.1158/2767-9764.CRC-25-0453
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  Data: Triple-negative breast cancer (TNBC) accounts for 10-20% of primary breast cancers and often has early relapses and aggressive progression. An activated tumour immune response can be prognostic in treatment-naive and chemotherapy-treated TNBC patients and may be assessed using gene expression data. We derived a stand-alone predictor for a proposed immunomodulatory transcriptional TNBC subtype in a training cohort of 235 patients with primary disease based on random forest modelling of RNA-sequencing data. Validation in independent TNBC cohorts totalling more than 1200 patients demonstrated that the classifier recapitulates the immunomodulatory mRNA subtype classification, is associated with elevated immune expression and diversity of T-cell receptor genes, is associated with response to neoadjuvant chemotherapy, and can separate patients into subgroups with better or worse prognosis after adjuvant chemotherapy. The availability of stand-alone classifiers for mRNA-based prediction may further enhance RNA-sequencing's usability in a more routine clinical context and for translational endpoints in clinical trials.
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