Unexpected drug efficacy or resistance is poorly understood in cancers because of the lack
of systematic analyses of drug response profiles in cancer tissues of various genotypic …

Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic
alterations. Often, these changes underlie cancer development, progression, and drug …

Background Clinical responses to anti-cancer therapies often only benefit a defined subset
of patients. Predicting the best treatment strategy hinges on our ability to effectively translate …

The development of reliable predictive models for individual cancer cell lines to identify an
optimal cancer drug is a crucial step to accelerate personalized medicine, but vast …

Chemotherapy is a mainstream cancer treatment, but has a constant challenge of drug
resistance, which consequently leads to poor prognosis in cancer treatment. For better …

Over the past decade, we have witnessed an increasing number of large-scale studies that
have provided multi-omics data by high-throughput sequencing approaches. This has …

Accurate prediction of patient drug response is required for successful personalized
medicine. Cancer is a disease resulting from myriad genetic alterations. Accordingly, it …

In vitro human cell line models have been widely used for cancer pharmacogenomic studies
to predict clinical response, to help generate pharmacogenomic hypothesis for further …

Since the first human cancer cell line, HeLa, was established in the early 1950s, there has
been a steady increase in the number and tumor type of available cancer cell line models …

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of
cancer and the complex mechanism of drug action. Personalized treatment that stratifies …