To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones
mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the …

Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …

Colon cancer is the third most common cancer worldwide. Most colorectal cancer
occurrences are sporadic, not related to genetic predisposition or family history; however, 20 …

Neuroblastoma, the most frequent solid tumor in infants, shows very diverse outcomes from
spontaneous regression to fatal disease. When these different tumors originate and how …

Most cancer genomic data are generated from bulk samples composed of mixtures of cancer
subpopulations, as well as normal cells. Subclonal reconstruction methods based on …

Subclonal architectures are prevalent across cancer types. However, the temporal
evolutionary dynamics that produce tumor subclones remain unknown. Here we measure …

Recurrent successions of genomic changes, both within and between patients, reflect
repeated evolutionary processes that are valuable for the anticipation of cancer progression …

Background & Aims Copy number alterations (CNAs), elicited by genome instability, are a
major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma …

Epigenetic regulations play a crucial role in the expression of various genes that are
important in the normal cell function. Any alteration in these epigenetic mechanisms can …

Advanced colorectal cancer harbors extensive intratumor heterogeneity shaped by neutral
evolution; however, intratumor heterogeneity in colorectal precancerous lesions has been …