Molecular therapeutic advances in personalized therapy of melanoma and non-small cell lung cancer

Clinical Outcomes of TP53 Mutations in Cancers

High-throughput sequencing of cancer genomes is increasingly becoming an essential tool of clinical oncology that facilitates target identification and targeted therapy within the context of precision medicine. The cumulative profiles of somatic mutations in cancer yielded by comprehensive molecular studies also constitute a fingerprint of historical exposures to exogenous and endogenous mutagens, providing insight into cancer evolution and etiology. Mutational signatures that were first established by inspection of the TP53 gene somatic landscape have now been confirmed and expanded by comprehensive sequencing studies. Further, the degree of granularity achieved by deep sequencing allows detection of low-abundance mutations with clinical relevance. In tumors, they represent the emergence of small aggressive clones; in normal tissues, they signal a mutagenic exposure related to cancer risk; and, in blood, they may soon become effective surveillance tools for diagnostic purposes and for monitoring of cancer prognosis and recurrence.

Serum neuron specific enolase levels correlate with patient prognosis for advanced lung cancer

To analyze the clinical and prognostic value of neuron specific enolase (NSE) levels in serum of advanced lung cancer patients, we analyzed serum NSE level of 110 advanced lung cancer patients (case group), 100 benign lung disease patients (benign disease group), and 100 healthy persons (control group). Case group patients were divided by NSE level into ≥25 ng/mL (52 cases) and <25 ng/mL (58 cases) groups to analyze overall survival (OS) and progression-free survival (PFS). The results showed the serum NSE levels of case group patients were significantly higher than those of control or benign disease group patients (P<0.05). Serum NSE levels of small cell lung cancer patients were significantly higher than those of patients with other tumor pathologies (all P<0.05). Median OS significantly differed between patients with NSE levels ≥25 ng/mL (23.7 months) and <25 ng/mL (31.4 months) (P<0.05). Median PFS also significantly differed between patients with NSE levels ≥25 ng/mL (13.5 months) and <25 ng/mL (17.6 months) (χ (2)=9.992; P<0.05). Tumor pathology (RR=4.136), patient performance status score (RR=2.903), and serum NSE level (RR=2.338) were factors influencing OS (P<0.05). Patient performance status score (RR=2.903), number of chemotherapy lines (RR=1.776), and serum NSE level (RR=2.075) were influencing factors in patients' PFS (P<0.05). In brief, serum NSE level significantly correlates with advanced lung cancer patient prognosis and may be useful as an auxiliary index to predict prognosis.

Mutation of the epidermal growth factor receptor gene and its impact on the efficacy of gefitinib in advanced non-small cell lung cance

Mutations in the epidermal growth factor receptor (EGFR) gene are associated with subsets of non-small cell lung cancer (NSCLC). Some patients with EGFR mutations are responsive to targeted therapy with the EGFR tyrosine kinase inhibitor gefitinib. Here, the mutation status of EGFR was assessed in advanced-stage NSCLC patients to determine how mutation status influences the clinical efficacy of gefitinib. The study included 106 patients with advanced NSCLC who were treated with gefitinib. Exons 19 and 21 of EGFR were sequenced from tumor tissues samples by PCR, and patient clinical characteristics, short-term outcomes (partial response, stable disease, progressive disease), and survival [overall survival (OS) and progression-free survival (PFS)] were compared. EGFR mutations in either exon 19 or exon 21 were detected in 54.7% of cases. The EGFR gene mutation rate was significantly different in patients with different pathological types (χ(2)=6.612, P<0.05). The distribution of short-term outcomes differed significantly by EGFR gene mutation status, history of smoking, and bone metastasis (χ(2)=6.481~35.938, P<0.05). Further, OS and PFS was significantly higher following gefitinib in patients with EGFR mutations than those without EGFR mutation (χ(2)=19.135, 6.953, P<0.05). OS was also significantly higher in patients with an exon 19 deletion mutation than in those with the exon 21 point mutation (χ(2)=8.575, P<0.05). Cox multivariate regression analysis indicated that OS was correlated with the pathological type of the tumor (HR=4.877), US Eastern Cooperative Oncology Group Physical Status (ECOG PS) score (HR=3.087), and EGFR mutation status (HR=1.876) (all P<0.05), while PFS was correlated with ECOG PS score (HR=2.218), cycles of chemotherapy (HR=1.829), and EGFR mutation status (HR=1.840) (all P<0.05). Only mild adverse events were reported during gefitinib treatment. The findings indicate that gefitinib treatment can improve the clinical outcomes of NSCLC patients with EGFR mutation, prolonging their survival time with only mild adverse events.

Omics and drug response

A new generation of technologies commonly named omics permits assessment of the entirety of the components of biological systems and produces an explosion of data and a major shift in our concepts of disease. These technologies will likely shape the future of health care. One aspect of these advances is that the data generated document the uniqueness of each human being in regard to disease risk and treatment response. These developments have reemphasized the concept of personalized medicine. Here we review the impact of omics technologies on one key aspect of personalized medicine: the individual drug response. We describe how knowledge of different omics may affect treatment decisions, namely drug choice and drug dose, and how it can be used to improve clinical outcomes.