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@ARTICLE{Lahusen:303089,
      author       = {A. Lahusen and M. P. Lutz and R. Fang$^*$ and M. Kirchner
                      and S. Albus and K. Kluck and M. Karthaus and A. Schwarzer
                      and G. Siegler and A. Kleger and T. J. Ettrich and A. Becher
                      and S. Höfling and J. T. Siveke$^*$ and J. Budczies and A.
                      Tannapfel and A. Stenzinger and P. F. Cheung$^*$ and T.
                      Eiseler and T. Seufferlein},
      title        = {{A}n immune responsive tumor microenvironment imprints into
                      {PBMC}s and predicts outcome in advanced pancreatic cancer:
                      lessons from the {PREDICT} trial.},
      journal      = {Molecular cancer},
      volume       = {24},
      number       = {1},
      issn         = {1476-4598},
      address      = {London},
      publisher    = {Biomed Central},
      reportid     = {DKFZ-2025-01514},
      pages        = {202},
      year         = {2025},
      abstract     = {Prognosis in advanced pancreatic ductal adenocarcinoma
                      (aPDAC) is particularly poor, only few patients benefit from
                      treatment, and there are few biomarkers. The PREDICT trial
                      examined whether first-line time-to-treatment failure (TTF1)
                      predicts second-line treatment failure (TTF2) in aPDAC
                      patients but found no association. We hypothesized that the
                      tumor immune microenvironment (TiME) could correlate with
                      the outcome in this trial and assessed whether tissue
                      features were reflected in peripheral blood.PREDICT patients
                      received 5-FU/LV plus nanoliposomal irinotecan as
                      second-line treatment. We stratified patients by shortest
                      vs. longest TTF2 and analyzed 20 treatment-naïve tumor
                      tissues samples via transcriptomics and
                      immunohistochemistry. Peripheral blood mononuclear cells
                      (PBMCs) from 82 patients collected prior to second-line
                      therapy underwent flow cytometry and gene expression
                      profiling. A machine learning pipeline integrated PBMC and
                      clinical data to predict second-line outcome including
                      external validation in 30 patients.Long-TTF2 tumors
                      exhibited an immune-active ('hot') TiME with cytotoxic
                      CXCR3+CD8+-T-cell infiltration. PBMC analysis showed that
                      these immune features were reflected in peripheral blood
                      after one line of treatment. A novel 7-feature PBMC-based
                      model ('TTF2Pred') accurately predicted TTF2 and overall
                      survival, outperforming clinical or CA19-9 models and was
                      confirmed in an external validation cohort. Long-TTF2
                      patients exhibited more circulating CXCR3⁺-T-cells and
                      plasmacytoid dendritic cells. Short-TTF2 patients had more
                      platelet-leukocyte aggregates.An immune-active,
                      treatment-naïve TiME predicts a better second-line outcome,
                      and these characteristics imprinted into PBMCs obtained
                      after one line of chemotherapy. We here first describe a
                      minimally invasive, PBMC-based predictor of second-line
                      outcome as a powerful prognostic tool for triaging
                      patients.ClinicalTrials.gov NCT03468335 (registered March
                      15, 2018).},
      keywords     = {Aged / Female / Humans / Male / Middle Aged /
                      Antineoplastic Combined Chemotherapy Protocols: therapeutic
                      use / Biomarkers, Tumor / Carcinoma, Pancreatic Ductal: drug
                      therapy / Carcinoma, Pancreatic Ductal: immunology /
                      Carcinoma, Pancreatic Ductal: pathology / Gene Expression
                      Profiling / Leukocytes, Mononuclear: immunology /
                      Leukocytes, Mononuclear: metabolism / Pancreatic Neoplasms:
                      immunology / Pancreatic Neoplasms: drug therapy / Pancreatic
                      Neoplasms: pathology / Pancreatic Neoplasms: mortality /
                      Prognosis / Treatment Outcome / Tumor Microenvironment:
                      immunology / Advanced pancreatic ductal adenocarcinoma
                      (Other) / Immunophenotyping (Other) / Liquid biomarkers
                      (Other) / Machine learning (Other) / Peripheral blood
                      mononuclear cells (Other) / Second-line chemotherapy (Other)
                      / Tumor immune microenvironment (Other) / Biomarkers, Tumor
                      (NLM Chemicals)},
      cin          = {ED01},
      ddc          = {570},
      cid          = {I:(DE-He78)ED01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40696453},
      doi          = {10.1186/s12943-025-02406-7},
      url          = {https://inrepo02.dkfz.de/record/303089},
}