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Showing 1–9 of 9 results
Advanced filters: Author: Stephane Chevrier Clear advanced filters

  • In the Tumor Profiler proof-of-concept observational study, a multiomics approach for profiling tumors from patients with melanoma was feasible, returning data within 4 weeks and informing treatment recommendations in 75% of cases.

    • Nicola Miglino
    • Nora C. Toussaint
    • Andreas Wicki
    ResearchOpen Access
    Nature Medicine
    Volume: 31, P: 2430-2441

  • The molecular mechanisms underlying drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML) remain to be explored. Here, the use of bulk and single cell multi-omics and ex vivo drug profiling for 21 rrAML patients reveals mechanisms of resistance to the Bcl-2 inhibitor venetoclax and treatment vulnerabilities.

    • Rebekka Wegmann
    • Ximena Bonilla
    • Alexandre P. A. Theocharides
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-18

  • HistoPlexer, a deep learning model, generates multiplexed protein expression maps from H&E images, capturing tumour–immune cell interactions. It outperforms baselines, enhances immune subtyping and survival prediction and offers a cost-effective tool for precision oncology.

    • Sonali Andani
    • Boqi Chen
    • Gunnar Rätsch
    ResearchOpen Access
    Nature Machine Intelligence
    Volume: 7, P: 1292-1307

  • Here, the authors use Raman spectroscopy on circular graphene drums to demonstrate dynamical softening of optical phonons induced by the macroscopic flexural motion of graphene, and find evidence that the strain in graphene is enhanced under non-linear driving.

    • Xin Zhang
    • Kevin Makles
    • Stéphane Berciaud
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-9

  • Long-read single-cell RNA sequencing is capable of detecting isoform-level gene expression and genomic alterations such as mutations and gene fusions, thereby providing cell-specific genotype-phenotype information. Here, the authors use long-read scRNA-seq on metastatic ovarian cancer samples and detect cell-type specific isoforms and gene fusions that may otherwise be misclassified in short-read data.

    • Arthur Dondi
    • Ulrike Lischetti
    • Niko Beerenwinkel
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-19

  • The authors present a robust diagnostic algorithm based on digital pathology and image analysis that quantifies intratumoral and stromal CD8+ T-cell densities in the tumor center and invasive margin compartment in metastatic melanoma. Spatial CD8+ T-cell densities are translated into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”. Their approach also allows efficient immune phenotyping of metastatic lesions, on biopsy material or even in the absence of material from the invasive margin.

    • Bettina Sobottka
    • Marta Nowak
    • Viktor Hendrik Koelzer
    ResearchOpen Access
    Laboratory Investigation
    Volume: 101, P: 1561-1570