Cancer discovery最新文献

An artificial intelligence model that incorporates a range of tumor and patient data proved significantly more accurate in retrospectively predicting breast cancer recurrence than a commonly used genomic test, suggesting that multimodal models could be leveraged to more accurately assess recurrence risk and guide patient care.

Aneuploidy is near-ubiquitous in cancer and contributes to tumor biology. However, the temporal evolutionary dynamics that select for aneuploidy remain uncharacterized. We performed longitudinal genomic analysis of 755 samples from 167 patients with colorectal-derived neoplasias from different stages through metastasis and treatment. Adenomas had few copy number alterations (CNA) and most were subclonal, whereas cancers had many clonal CNAs, suggesting that progression goes through a CNA bottleneck. Individual colorectal cancer glands from the same tumor had similar karyotypes, despite evidence of ongoing instability at the cell level. CNAs in metastatic lesions, after therapy, and in late recurrences were similar to the primary. Mathematical modeling indicated that these data are consistent with the action of negative selection on CNAs that "trap" cancer genomes on a fitness peak characterized by specific CNAs. Hence, progression to colorectal cancer requires traversing a rugged fitness landscape, whereas subsequent CNA evolution is constrained by negative selection.

Significance: We profiled 167 long-term responders longitudinally (755 samples), documenting long-term cancer evolution. We found that a genetic bottleneck is required for progression and is associated with dramatic increase in CNAs but decrease in clonal diversity. After initiation, copy number evolution is constrained by negative selection through metastasis and treatment. See related commentary by Okada et al., p. 192.

Pediatric cancers are unique diseases in many aspects, including their genomic driver alterations and resulting unique biology, as well as the attendant challenges posed thereby. We focus on challenges including the need for increased funding to pursue novel therapy development for pediatric cancer-specific driver alterations and their testing in clinical trials, as well as the underappreciated economic impact of pediatric cancer on families and patients and on society at large.

The global demographic shift toward an aging population has positioned cancer as a preeminent challenge in public health, with the incidence of most malignancies increasing precipitously with advancing age. By targeting the bidirectional nexus of cancer and aging, we can pioneer precision interventions to improve outcomes for the growing geriatric oncology population.

Natural killer (NK) and innate lymphoid cells (ILCs) regulate tissue homeostasis and immune responses, by acting as early sensors of cellular stress and tissue dysfunction. Their functions are tightly controlled by regulatory circuits, often referred to as checkpoints, and are profoundly shaped by local environments. In cancer, tissue perturbations cause immune cell recruitment, spatial re-distribution, and accordant functional adaptations. Here, we discuss how tissue-specific cues regulate NK/ILC functions in cancer, and how local regulatory circuits shape their cellular states and effector programs. We address how targeting innate checkpoints could aid existing, and inform novel strategies for treating solid malignancies.