Satomi Yamamoto

Is Consolidation Chemotherapy after Concurrent Chemo-Radiotherapy Beneficial for Patients with Locally Advanced Non–Small-Cell Lung Cancer?: A Pooled Analysis of the Literature

Introduction: The purpose of this study was to evaluate whether consolidation chemotherapy (CCT) after concurrent chemo-radiotherapy is beneficial for patients with locally advanced non–small-cell lung cancer (LA-NSCLC). Methods: We systematically searched PubMed for phase II/III trials published before December 31, 2011, examining survival of LA-NSCLC treated with concurrent chemo-radiotherapy. Median overall survival and other study characteristics were collected from each study and pooled. We extracted log-transformed hazards and standard errors under the assumption that survival follows an exponential distribution, and computed a pooled median overall survival and a 95% confidence interval (CI) using random-effects model. Collected trial arms were categorized as having CCT or not having it, CCT+ and CCT−, respectively. Results: Forty-one studies were identified including seven phase III studies and 34 phase II studies with 45 arms (CCT+: 25; CCT−: 20). Clinical data were comparable for clinical stage, performance status, cancer histology, sex, and median age between the two groups. There was no statistical difference in pooled mOS between CCT+ (19.0 month; 95% CI, 17.3−21.0) and CCT− (17.9 month; 95% CI, 16.1−19.9). Predicted hazard ratio of CCT+ to CCT− was 0.94 (95% CI, 0.81−1.09; p = 0.40). There were no differences between the two groups with regard to grade 3−5 toxicities in pneumonitis, esophagitis, and neutropenia. These models estimated that addition of CCT could not lead to significant survival prolongation or risk reduction in death for LA-NSCLC patients. Conclusion: The pooled analysis based on a publication basis failed to provide evidence that CCT yields significant survival benefit for LA-NSCLC.

Human papilloma virus in non-small cell lung cancer in never smokers: A systematic review of the literature

Non-small cell lung cancer (NSCLC) in never smokers has emerged as a global public health issue. The cause is still unclear, and few studies have focused on the prevalence of human papillomavirus (HPV) in the never smokers. We performed a systematic search of PubMed for articles of HPV infection in human subjects with NSCLC up to September 2012. Although smoking status was not fully reported in all studies, we contacted the authors by e-mail to supplement this information. Differences in the distribution of patients with and without HPV infection were tested with the Chi squared test. We identified 46 eligible articles, including 23 from Asian countries (N=2337 NSCLC cases), 19 from European countries (N=1553) and 4 from North and South America (N=160). The HPV prevalence was 28.1% (95% confidence interval (CI) 26.6-30.3%), 8.4% (95% CI 7.1-9.9%) and 21.3% (95% CI 15.2-28.4%), respectively. Eleven studies from East Asia (N=1110) and 4 from Europe (N=569) provided information on smoking status. The number of never smoker was 392 patients (33.9%) in East Asia and 54 patients (14.8%) in Europe. The HPV prevalence in East Asian countries was similar between never and ever smokers (33.9% vs 39.2%, P=0.080). Based on the literature confirming the presence of HPV in lung cancer in never smokers, the virus plays a role in carcinogenesis in the disease. There were different patterns of HPV prevalence between Asian and European countries in the never smokers as well as in ever smokers.

The role of smoking status on the progression-free survival of non-small cell lung cancer patients harboring activating epidermal growth factor receptor (EGFR) mutations receiving first-line EGFR tyrosine kinase inhibitor versus platinum doublet chemotherapy: a meta-analysis of prospective randomized trials.

BACKGROUND Univariate analyses from several randomized phase III trials seemed to suggest ever-smokers with advanced mutated epidermal growth factor receptor (EGFRm) non-small cell lung cancer (NSCLC) did not seem to benefit from EGFR tyrosine kinase inhibitors (TKIs) as first-line treatment when compared with platinum-doublet chemotherapy as measured by progression-free survival (PFS). METHODS A literature-based meta-analysis of PFS outcomes as measured by log-transformed pooled hazard ratio (HR) was performed using a random-effect model. Pooled HRs for smoking status, age, gender, ethnicity, type of EGFR mutation, and EGFR TKI were obtained. Comparison of the pooled HR was performed by metaregression analysis. RESULTS Among the 1,649 EGFRm NSCLC patients analyzed from 7 prospective randomized trials (WJTOG3405, NEJ002, EURTAC, OPTIMAL, LUX Lung-3, LUX Lung-6, and ENSURE), 83.7% were Asians, and 30.0% were ever-smokers. An equal percentage of ever-smokers received doublet chemotherapy (30.2%) or EGFR TKI (30.0%). The pooled HR for PFS was 0.29 (95% confidence interval [CI]: 0.21-0.39) for never-smokers and 0.54 (95% CI: 0.38-0.76) for ever-smokers (p < .007 by metaregression). The pooled PFS HR for exon 19 deletion was 0.25 (95% CI: 0.19-0.31) and 0.44 for exon 21 substitution (95% CI: 0.34-0.57) (p < .001 by metaregression analysis). The pooled PFS HR was 0.33 (95% CI: 0.24-0.46) for Asians and 0.48 for non-Asians (95% CI: 0.28-0.84) (p = .261 by metaregression analysis). CONCLUSION EGFRm NSCLC patients derived significant PFS benefit from TKI over platinum-doublet chemotherapy as first-line treatment regardless of smoking status; however, PFS benefit is significantly better in never-smokers by metaregression analysis.

Primary lung mucoepidermoid carcinoma: analysis of prognostic factors using surveillance, epidemiology and end results program

Mucoepidermoid carcinoma (MEC) primarily occurs in salivary glands, but can also arise in other organs; however, the impact of primary location on patient prognosis is largely unknown.

Molecular analysis of human papillomavirus in never-smokers with non-small cell lung cancer

The causes of lung cancer in never-smokers remain unclear. The potential contribution of human papillomavirus (HPV) to the carcinogenesis of non-small cell lung cancer (NSCLC) has been reported. In 2008, a prospective registry of never-smokers with NSCLC was established at the Kinki-Chuo Chest Medical Center, Sakai, Osaka, Japan. Never-smokers with NSCLC were consecutively enrolled onto the registry. Of these patients, 114 with large tumor specimens, the majority of which were surgical tissues, were selected. In total, 23 of the most clinically relevant HPV types were assayed using polymerase chain reaction amplification of the viral genome. Following exclusion of samples with suboptimal quality, DNA was extracted from 96 formalin-fixed paraffin-embedded samples. These 96 cases consisted of 82 females (85.4%) and 14 males (14.6%), with a median age of 67 years (range, 29–83). Almost all cases (93.8%) were of the adenocarcinoma histological subtype. Despite confirmation of the quality and amount of DNA, HPV type 6 was detected in only one case (1.1%). Furthermore, no other samples examined were positive for any other HPV types. The results therefore suggest that HPV does not play a major role as the driving oncogenic event in never-smokers with NSCLC.

Potential of boron neutron capture therapy (BNCT) for malignant peripheral nerve sheath tumors (MPNST)

Malignant peripheral nerve sheath tumors (MPNST) are relatively rare neoplasms with poor prognosis. At present there is no effective treatment for MPNST other than surgical resection. Nonetheless, the anti-tumor effect of boron neutron capture therapy (BNCT) was recently demonstrated in two patients with MPNST. Subsequently, tumor-bearing nude mice subcutaneously transplanted with a human MPNST cell line were injected with p-borono-L-phenylalanine (L-BPA) and subjected to BNCT. Pathological studies then revealed that the MPNST cells were selectively destroyed by BNCT.

Prognostic and Predictive Value of KRAS Mutation in NSCLC

untreated advanced ALK-positive NSCLC, the current case was intrinsically refractory to crizotinib. Reportedly, EML4-ALK variants have different sensitivities to crizotinib, which correlates with differences in protein stability in EML4-ALK–expressing cells. The significance of ALK exon 18 fusion variants observed in our case is currently unknown, but interestingly, the ALK transmembrane domain (Fig. 1H) is expressed, unlike in ALK exon 20 fusion variants. The transmembrane domain in exon 18–containing variants may be related to the differences in protein stability and resistance to crizotinib, although further studies—including of the function and subcellular localization of this variant—are necessary. For diagnosis of ALK-translocated lung cancer, screening by immunohistochemical analysis and verification by fluorescence in situ hybridization are currently recommended for convenience and cost. However, our case suggests that ALK fusion variants, except for exon 20 fusion variants, have a different therapeutic response to ALK inhibitors, although further studies are required for our variant. The guidance for ALK gene testing in patients with lung cancer by the Japan Lung Cancer Society also suggests that RT-PCR can provide reliable verification of ALK fusion status if chimeric transcripts can be verified by direct base determination, and ALK inhibitors can be indicated on the basis of this verification. In fact, we experienced an 80% response rate (four of five patients) for crizotinib in the ALK-positive patients who were identified only by RT-PCR because of technical problems. Therefore, use of RT-PCR may be a reasonable precaution to

Drug screening to target nuclear orphan receptor NR4A2 for cancer therapeutics

Background Our previous study suggested NR4A2, a subfamily member of orphan nuclear receptors, is essential for survival of human cancer cells such as mucoepidermoid carcinoma (MEC). Methods We conducted high throughput drug screening for NR4A2 inhibitors as a novel therapeutic modality. Positive screening was performed using a luciferase reporter vector containing NR4A2 binding sequence, and a CRE-reporter control vector was used to eliminate false positives. In vitro assays for positive hits were conducted. Results A total of 23 Food and Drug Administration (FDA) and 43 Life Science Library compounds were identified, including several epidermal growth factor inhibitors and Src inhibitors. Subsequent in vitro assays confirmed that identified compounds were preferentially active in NR4A2+ cancer cells. Several candidate compounds appeared to suppress NR4A2 via inhibition of p-ERK, whereas a novel compound KU0171309 may act as a more direct inhibitor. Conclusions Further research should focus on homologue selectivity, in vivo activity, and definitively deciphering the mechanism of action of KU0171309.

PS01.32: High Throughput Screening of Small Molecule Inhibitors for Nuclear Receptor Subfamily 4 Group A Member 2 (NR4A2) in Human Cancers

Background: We report a newly developed method for reagent-free tissue analysis, and for discovering therapeutic targets in highly heterogeneous populations. This method, referred to as infrared “spectral histopathology” (SHP), is based on measurements of the biochemical composition and compositional changes, rather than on staining patterns, tissue architecture and morphology of the specimen. This biochemical information is captured via a microscopic spectral measurement that relies on the well-known principle that every biochemical compounds exhibits a specific infrared spectrum which may be considered a fingerprint molecular signature. SHP can distinguish normal tissue types (connective tissue, fibroblasts, erythrocytes, plasma cells, macrophages, inflammatory response, etc.) by the differences in the spectral signatures, and can classify cancer types (adenocarcinoma, squamous cell carcinoma and small cell carcinoma) with high accuracy. Methods: In SHP, about 25,000 individual infrared spectra are collected for each square millimeter of tissue from pixels ca. 6 mm on edge. These pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel. The resulting spectral datasets are subsequently decoded by machine learning algorithms that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease with high spatial resolution. Thus, SHP offers the clinician novel information that complements morphological and immunohistochemical data. Results: Between a pilot study (80 cases), a large-scale follow-up study (ca. 480 cases) and a presently ongoing validation study with a National Cancer Center (420 cases), the lung cancer database at Cireca, LLC now is sufficiently large to allow the following conclusions to be made: SHP distinguishes normal and abnormal lung tissue with an accuracy of ca. 94%. Benign and malignant abnormal tissue can be classified with similar accuracy. Small cell lung cancer (SCLC), squamous cell carcinomas (SqCC) and adenocarcinomas (ADC) can be classified with accuracies ranging from ca. 94% to 88%. Inflammatory response can be detected and distal and cancer adjacent normal tissue can be distinguished. Regions identified by immunohistochemistry to overexpress given cancer markers, e.g. TTF-1 or PD-L1, often show correspondent regions of distinct spectral signatures in SHP. Conclusion: An exciting aspect of SHP is its ability to distinguish truly normal tissue types from cancer adjacent normal tissue. Detection of this cancer “field effect” may have implication in defining a tumor’s propensity to metastasize. In addition, a spectral assessment of the immunoscore [5] may be possible. Computational and data mining efforts are presently underway to exploit further applications of SHP.

Poster SessionsPS01.32: High Throughput Screening of Small Molecule Inhibitors for Nuclear Receptor Subfamily 4 Group A Member 2 (NR4A2) in Human Cancers: Topic: Medical Oncology

Background: We report a newly developed method for reagent-free tissue analysis, and for discovering therapeutic targets in highly heterogeneous populations. This method, referred to as infrared “spectral histopathology” (SHP), is based on measurements of the biochemical composition and compositional changes, rather than on staining patterns, tissue architecture and morphology of the specimen. This biochemical information is captured via a microscopic spectral measurement that relies on the well-known principle that every biochemical compounds exhibits a specific infrared spectrum which may be considered a fingerprint molecular signature. SHP can distinguish normal tissue types (connective tissue, fibroblasts, erythrocytes, plasma cells, macrophages, inflammatory response, etc.) by the differences in the spectral signatures, and can classify cancer types (adenocarcinoma, squamous cell carcinoma and small cell carcinoma) with high accuracy. Methods: In SHP, about 25,000 individual infrared spectra are collected for each square millimeter of tissue from pixels ca. 6 mm on edge. These pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel. The resulting spectral datasets are subsequently decoded by machine learning algorithms that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease with high spatial resolution. Thus, SHP offers the clinician novel information that complements morphological and immunohistochemical data. Results: Between a pilot study (80 cases), a large-scale follow-up study (ca. 480 cases) and a presently ongoing validation study with a National Cancer Center (420 cases), the lung cancer database at Cireca, LLC now is sufficiently large to allow the following conclusions to be made: SHP distinguishes normal and abnormal lung tissue with an accuracy of ca. 94%. Benign and malignant abnormal tissue can be classified with similar accuracy. Small cell lung cancer (SCLC), squamous cell carcinomas (SqCC) and adenocarcinomas (ADC) can be classified with accuracies ranging from ca. 94% to 88%. Inflammatory response can be detected and distal and cancer adjacent normal tissue can be distinguished. Regions identified by immunohistochemistry to overexpress given cancer markers, e.g. TTF-1 or PD-L1, often show correspondent regions of distinct spectral signatures in SHP. Conclusion: An exciting aspect of SHP is its ability to distinguish truly normal tissue types from cancer adjacent normal tissue. Detection of this cancer “field effect” may have implication in defining a tumor’s propensity to metastasize. In addition, a spectral assessment of the immunoscore [5] may be possible. Computational and data mining efforts are presently underway to exploit further applications of SHP.