Next-generation Sequencing-based genomic profiling: Fostering innovation in cancer care?

OBJECTIVES: With the development of next-generation sequencing (NGS) technologies, DNA sequencing has been increasingly utilized in clinical practice. Our goal was to investigate the impact of genomic evaluation on treatment decisions for heavily pretreated patients with metastatic cancer. METHODS: We analyzed metastatic cancer patients from a single institution whose cancers had progressed after all available standard-of-care therapies and whose tumors underwent next-generation sequencing analysis. We determined the percentage of patients who received any therapy directed by the test, and its efficacy. RESULTS: From July 2013 to December 2015, 185 consecutive patients were tested using a commercially available next-generation sequencing-based test, and 157 patients were eligible. Sixty-six patients (42.0%) were female, and 91 (58.0%) were male. The mean age at diagnosis was 52.2 years, and the mean number of pre-test lines of systemic treatment was 2.7. One hundred and seventy-seven patients (95.6%) had at least one identified gene alteration. Twenty-four patients (15.2%) underwent systemic treatment directed by the test result. Of these, one patient had a complete response, four (16.7%) had partial responses, two (8.3%) had stable disease, and 17 (70.8%) had disease progression as the best result. The median progression-free survival time with matched therapy was 1.6 months, and the median overall survival was 10 months. CONCLUSION: We identified a high prevalence of gene alterations using an next-generation sequencing test. Although some benefit was associated with the matched therapy, most of the patients had disease progression as the best response, indicating the limited biological potential and unclear clinical relevance of this practice.

Next-generation Sequencing-based genomic profiling: Fostering innovation in cancer care?

OBJECTIVES: With the development of next-generation sequencing (NGS) technologies, DNA sequencing has been increasingly utilized in clinical practice. Our goal was to investigate the impact of genomic evaluation on treatment decisions for heavily pretreated patients with metastatic cancer. METHODS: We analyzed metastatic cancer patients from a single institution whose cancers had progressed after all available standard-of-care therapies and whose tumors underwent next-generation sequencing analysis. We determined the percentage of patients who received any therapy directed by the test, and its efficacy. RESULTS: From July 2013 to December 2015, 185 consecutive patients were tested using a commercially available next-generation sequencing-based test, and 157 patients were eligible. Sixty-six patients (42.0%) were female, and 91 (58.0%) were male. The mean age at diagnosis was 52.2 years, and the mean number of pre-test lines of systemic treatment was 2.7. One hundred and seventy-seven patients (95.6%) had at least one identified gene alteration. Twenty-four patients (15.2%) underwent systemic treatment directed by the test result. Of these, one patient had a complete response, four (16.7%) had partial responses, two (8.3%) had stable disease, and 17 (70.8%) had disease progression as the best result. The median progression-free survival time with matched therapy was 1.6 months, and the median overall survival was 10 months. CONCLUSION: We identified a high prevalence of gene alterations using an next-generation sequencing test. Although some benefit was associated with the matched therapy, most of the patients had disease progression as the best response, indicating the limited biological potential and unclear clinical relevance of this practice.

Estrogen metabolism in the human lung: impact of tumorigenesis, smoke, sex and race/ethnicity.

Previous data from this group demonstrate that the murine lung metabolizes estrogen. Production of the putative carcinogen 4-hydroxyestrogen (4-OHE) is elevated within the lungs of female vs. male mice and accelerated by tobacco smoke. The goal of this study was to determine if the human lung metabolizes estrogen and evaluate the impact of tumor formation, smoke, sex and race/ethnicity on metabolism. Urine and lung tissue (normal, tumor) were obtained from 49 non-small cell lung cancer patients. Healthy postmenopausal Caucasian (n = 19) and Chinese (n = 20) American women (never-smokers) donated urine. Quantitative RT-PCR analyses indicate that multiple estrogen synthesis and metabolism genes are expressed in human bronchoalveolar cells. Estrogen and its metabolites were measured in lung tissue and urine using liquid chromatography/tandem mass spectrometry. Wilcoxon rank tests were used for statistical comparisons. E1, E2, E3 and estrogen metabolites 2-OHE1, 2-OHE2, 4-OHE1, 4-OHE2, 2-OME1 and 2-OME2 were detected at higher levels in tumor vs. adjacent normal tissue and in women vs. men (P < 0.05). The proportion of 4-OHEs was higher in tumors than in normal lung tissue (P < 0.05), and elevated in normal tissue from current- vs. never-smoking women (P = 0.006); similar trends were observed in urine. The proportion of 4-OHEs in the urine of postmenopausal Chinese American women was 1.8-fold higher than that of Caucasian women (P = 0.015). These data indicate that estrogen metabolites are present in the human lung. A shift towards 4-hydroxylation during lung tumorigenesis may contribute to the risk conferred by smoking, sex or race/ethnicity.

Early changes in gene expression induced by tobacco smoke: Evidence for the importance of estrogen within lung tissue.

Lung cancer is the leading cause of cancer deaths in the United States, surpassing breast cancer as the primary cause of cancer-related mortality in women. The goal of the present study was to identify early molecular changes in the lung induced by exposure to tobacco smoke and thus identify potential targets for chemoprevention. Female A/J mice were exposed to either tobacco smoke or HEPA-filtered air via a whole-body exposure chamber (6 h/d, 5 d/wk for 3, 8, and 20 weeks). Gene expression profiles of lung tissue from control and smoke-exposed animals were established using a 15K cDNA microarray. Cytochrome P450 1b1, a phase I enzyme involved in both the metabolism of xenobiotics and the 4-hydroxylation of 17beta-estradiol (E(2)), was modulated to the greatest extent following smoke exposure. A panel of 10 genes were found to be differentially expressed in control and smoke-exposed lung tissues at 3, 8, and 20 weeks (P < 0.001). The interaction network of these differentially expressed genes revealed new pathways modulated by short-term smoke exposure, including estrogen metabolism. In addition, E(2) was detected within murine lung tissue by gas chromatography-coupled mass spectrometry and immunohistochemistry. Identification of the early molecular events that contribute to lung tumor formation is anticipated to lead to the development of promising targeted chemopreventive therapies. In conclusion, the presence of E(2) within lung tissue when combined with the modulation of cytochrome P450 1b1 and other estrogen metabolism genes by tobacco smoke provides novel insight into a possible role for estrogens in lung cancer.

Population-based trends in lung cancer incidence in women.

Lung cancer is the leading cause of cancer mortality in women worldwide. Although the rise and growing epidemic status of lung cancer are overwhelmingly attributed to tobacco use, its rank in nonsmokers as the seventh most common cause of cancer worldwide suggests that other factors contribute to this disease. The majority of lung cancers among nonsmokers occur in women. Aside from geographic, cultural, and genetic differences, hormonal and possibly infectious factors also may play etiologic roles. This review aims to discuss the epidemiology of lung cancer in women, as well as the incidence of second primaries, and presents current opinions on the myriad of causes.

Successful application of microarray technology to microdissected formalin-fixed, paraffin-embedded tissue.

The establishment of a reliable method for using RNA from formalin-fixed, paraffin-embedded (FFPE) tissue would provide an opportunity to obtain novel gene expression data from the vast amounts of archived tissue. A custom-designed 22,000 oligonucleotide array was used in the present study to compare the gene expression profile of colonic epithelial cells isolated by laser capture microdissection from FFPE-archived samples with that of the same cell population from matched frozen samples, the preferred source of RNA. Total RNA was extracted from FFPE tissues, amplified, and labeled using the Paradise Reagent System. The quality of the input RNA was assessed by the Bioanalyzer profile, reverse transcriptase-polymerase chain reaction, and agarose gel electrophoresis. The results demonstrate that it is possible to obtain reliable microarray data from FFPE samples using RNA acquired by laser capture microdissection. The concordance between matched FFPE and frozen samples was evaluated and expressed as a Pearson's correlation coefficient, with values ranging from 0.80 to 0.97. The presence of ribosomal RNA peaks in FFPE-derived RNA was reflected by a high correlation with paired frozen samples. A set of practical recommendations for evaluating the RNA integrity and quality in FFPE samples is reported.

Molecular classifiers for gastric cancer and nonmalignant diseases of the gastric mucosa.

High incidence of gastric cancer-related death is mainly due to diagnosis at an advanced stage in addition to the lack of adequate neoadjuvant therapy. Hence, new tools aimed at early diagnosis would have a positive impact in the outcome of the disease. Using cDNA arrays having 376 genes either identified previously as altered in gastric tumors or known to be altered in human cancer, we determined expression signature of 99 tissue fragments representing normal gastric mucosa, gastritis, intestinal metaplasia, and adenocarcinomas. We first validated the array by identifying molecular markers that are associated with intestinal metaplasia, considered as a transition stage of gastric adenocarcinomas of the intestinal type as well as markers that are associated with diffuse type of gastric adenocarcinomas. Next, we applied Fisher's linear discriminant analysis in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Many classifiers could distinguish between normal and tumor samples, whereas, for the distinction of gastritis from tumor and for metaplasia from tumor, fewer classifiers were identified. Statistical validations showed that trios that discriminate between normal and tumor samples are powerful classifiers to distinguish between tumor and nontumor samples. More relevant, it was possible to identify samples of intestinal metaplasia that have expression signature resembling that of an adenocarcinoma and can now be used for follow-up of patients to determine their potential as a prognostic test for malignant transformation.

Differentially expressed genes in gastric tumors identified by cDNA array.

Using cDNA fragments from the FAPESP/lICR Cancer Genome Project, we constructed a cDNA array having 4512 elements and determined gene expression in six normal and six tumor gastric tissues. Using t-statistics, we identified 80 cDNAs whose expression in normal and tumor samples differed more than 3.5 sample standard deviations. Using Self-Organizing Map, the expression profile of these cDNAs allowed perfect separation of malignant and non-malignant samples. Using the supervised learning procedure Support Vector Machine, we identified trios of cDNAs that could be used to classify samples as normal or tumor, based on single-array analysis. Finally, we identified genes with altered linear correlation when their expression in normal and tumor samples were compared. Further investigation concerning the function of these genes could contribute to the understanding of gastric carcinogenesis and may prove useful in molecular diagnostics.