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by Keyword: retrieval

Cañellas-Socias A, Cortina C, Hernando-Momblona X, Palomo-Ponce S, Mulholland EJ, Turon G, Mateo L, Conti S, Roman O, Sevillano M, Slebe F, Stork D, Caballé-Mestres A, Berenguer-Llergo A, Álvarez-Varela A, Fenderico N, Novellasdemunt L, Jiménez-Gracia L, Sipka T, Bardia L, Lorden P, Colombelli J, Heyn H, Trepat X, Tejpar S, Sancho E, Tauriello DVF, Leedham S, Attolini CS, Batlle E, (2022). Metastatic recurrence in colorectal cancer arises from residual EMP1+ cells Nature 611, 603-+

Around 30-40% of patients with colorectal cancer (CRC) undergoing curative resection of the primary tumour will develop metastases in the subsequent years1. Therapies to prevent disease relapse remain an unmet medical need. Here we uncover the identity and features of the residual tumour cells responsible for CRC relapse. An analysis of single-cell transcriptomes of samples from patients with CRC revealed that the majority of genes associated with a poor prognosis are expressed by a unique tumour cell population that we named high-relapse cells (HRCs). We established a human-like mouse model of microsatellite-stable CRC that undergoes metastatic relapse after surgical resection of the primary tumour. Residual HRCs occult in mouse livers after primary CRC surgery gave rise to multiple cell types over time, including LGR5+ stem-like tumour cells2-4, and caused overt metastatic disease. Using Emp1 (encoding epithelial membrane protein 1) as a marker gene for HRCs, we tracked and selectively eliminated this cell population. Genetic ablation of EMP1high cells prevented metastatic recurrence and mice remained disease-free after surgery. We also found that HRC-rich micrometastases were infiltrated with T cells, yet became progressively immune-excluded during outgrowth. Treatment with neoadjuvant immunotherapy eliminated residual metastatic cells and prevented mice from relapsing after surgery. Together, our findings reveal the cell-state dynamics of residual disease in CRC and anticipate that therapies targeting HRCs may help to avoid metastatic relapse.© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

JTD Keywords: colonization, defines, human colon, mutations, plasticity, retrieval, stem-cells, subtypes, underlie, Animal, Animal cell, Animal experiment, Animal model, Animal tissue, Animals, Article, Cancer, Cancer growth, Cancer immunotherapy, Cancer inhibition, Cancer recurrence, Cancer staging, Cell, Cell adhesion, Cell migration, Cell population, Cell surface receptor, Cohort analysis, Colorectal cancer, Colorectal neoplasms, Colorectal tumor, Comprehensive molecular characterization, Controlled study, Crispr-cas9 system, Cytoskeleton, Disease exacerbation, Disease progression, Dynamics, Emp1 gene, Epithelial membrane protein-1, Extracellular matrix, Flow cytometry, Fluorescence intensity, Gene expression, Genetics, Human, Human cell, Humans, Immune response, Immunofluorescence, In situ hybridization, Marker gene, Metastasis potential, Mice, Minimal residual disease, Mouse, Neoplasm proteins, Neoplasm recurrence, local, Neoplasm, residual, Nonhuman, Pathology, Phenotype, Prevention and control, Protein, Receptors, cell surface, Single cell rna seq, Tumor, Tumor protein, Tumor recurrence


Estefan, DP, Zucca, R, Arsiwalla, X, Principe, A, Zhang, H, Rocamora, R, Axmacher, N, Verschure, PFMJ, (2021). Volitional learning promotes theta phase coding in the human hippocampus Proceedings Of The National Academy Of Sciences Of The United States Of America 118, e2021238118

© 2021 National Academy of Sciences. All rights reserved. Electrophysiological studies in rodents show that active navigation enhances hippocampal theta oscillations (4–12 Hz), providing a temporal framework for stimulus-related neural codes. Here we show that active learning promotes a similar phase coding regime in humans, although in a lower frequency range (3–8 Hz). We analyzed intracranial electroencephalography (iEEG) from epilepsy patients who studied images under either volitional or passive learning conditions. Active learning increased memory performance and hippocampal theta oscillations and promoted a more accurate reactivation of stimulus-specific information during memory retrieval. Representational signals were clustered to opposite phases of the theta cycle during encoding and retrieval. Critically, during active but not passive learning, the temporal structure of intracycle reactivations in theta reflected the semantic similarity of stimuli, segregating conceptually similar items into more distant theta phases. Taken together, these results demonstrate a multilayered mechanism by which active learning improves memory via a phylogenetically old phase coding scheme.

JTD Keywords: active learning, dynamics, gamma-power, hippocampus, intracranial eeg, movement, navigation, neural phase coding, oscillations, representations, retrieval, rhythm, theta oscillations, toolbox, Active learning, Theta oscillations, Working-memory