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. Cancer cell lines have made significant contributions to the development of various chemotherapeutic agents. Recent advances in multi-omics technologies have facilitated detailed characterizations of the genomic, transcriptomic, proteomic, and epigenomic profiles of these cancer cell lines. An increasing number of studies employ the power of a cancer cell line panel to provide predictive biomarkers for targeted and cytotoxic agents, including those that are already used in clinical practice. Different types of statistical and machine learning algorithms have been developed to analyze the large-scale data sets that have been produced. However, much work remains to address the discrepancies in drug assay results from different platforms and the frequent failures to translate discoveries from cell line models to the clinic. Nevertheless, continuous expansion of cancer cell line panels should provide unprecedented opportunities to identify new candidate targeted therapies, particularly for the so-called "dark matter" group of cancers, for which pharmacologically tractable driver mutations have not been identified.
Algorithms ; Antineoplastic Agents/*therapeutic use ; Biomarkers, Tumor/*analysis/blood ; Cell Line, Tumor/*drug effects ; Genomics ; Humans ; Neoplasms/*drug therapy ; *Precision Medicine ; Proteomics

PURPOSE: BioPATH is a non-interventional study evaluating the relationship of molecular biomarkers (PTEN deletion/downregulation, PIK3CA mutation, truncated HER2 receptor [p95HER2], and tumor HER2 mRNA levels) to treatment responses in Asian patients with HER2+ advanced breast cancer treated with lapatinib and other HER2-targeted agents. MATERIALS AND METHODS: Female Asian HER2+ breast cancer patients (n=154) who were candidates for lapatinib-based treatment following metastasis and having an available primary tumor biopsy specimen were included. The primary endpoint was progression-free survival (PFS). Secondary endpoints were response rate, overall survival on lapatinib, correlation between biomarker status and PFS for any previous trastuzumab-based treatment, and conversion/conservation rates of the biomarker status between tissue samples collected at primary diagnosis and at recurrence/metastasis. Potential relationships between tumor mRNA levels of HER2 and response to lapatinib-based therapy were also explored. RESULTS: p95HER2, PTEN deletion/downregulation, and PIK3CA mutation did not demonstrate any significant co-occurrence pattern and were not predictive of clinical outcomes on either lapatinib-based treatment or any previous trastuzumab-based therapy in the metastatic setting. Proportions of tumors positive for p95HER2 expression, PIK3CA mutation, and PTEN deletion/down-regulation at primary diagnosis were 32%, 31.2%, and 56.2%, respectively. Despite limited availability of paired samples, biomarker status patterns were conserved in most samples. HER2 mRNA levels were not predictive of PFS on lapatinib. CONCLUSION: The prevalence of p95HER2 expression, PIK3CA mutation, and PTEN deletion/downregulation at primary diagnosis were similar to previous reports. Importantly, no difference was observed in clinical outcome based on the status of these biomarkers, consistent with reports from other studies.
Asian Continental Ancestry Group ; Biomarkers ; Biopsy ; Breast Neoplasms ; Breast ; Diagnosis ; Disease-Free Survival ; Female ; Humans ; Neoplasm Metastasis ; Prevalence ; RNA, Messenger ; Trastuzumab