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Evaluation of displayed tumor cells and going around tumor tissues throughout patients together with cancer of the breast acquiring adjuvant zoledronic acidity.
Background With the increasing use of immune checkpoint inhibitors, tumor mutation burden (TMB) assessment is now routinely included in reports generated from targeted sequencing with large gene panels; however, not all patients require comprehensive profiling with large panels. Our study aims to explore the feasibility of using a small 56-gene panel as a screening method for TMB prediction. Methods TMB from 406 non-small cell lung cancer (NSCLC) patients was estimated using a large 520-gene panel simulated with the prospective TMB status for the small panel. This information was then used to determine the optimal cut-off. An independent cohort of 30 NSCLC patients was sequenced with both panels to confirm the cut-off value. Results By comparing sensitivity, specificity, and positive predictive value (PPV), the cut-off was set up as 10 mutations/megabase, yielding 81.4% specificity, 83.6% sensitivity, and 62.4% PPV. Further validation with an independent cohort sequenced with both panels using the same cut-off achieved 95.7% sensitivity, 71.4% specificity and 91.7% PPV. The decreasing trend of sensitivity with the increasing trend of both specificity and PPV with a concomitant increase in the cut-off for the small panel suggests that TMB is overestimated but highly unlikely to yield false-positive results. Hence, patients with low TMB ( less then 10) can be reliably stratified from patients with high TMB (≥10). Conclusions The small panel, more cost-effective, can be used as a screening method to screen for patients with low TMB, while patients with TMB ≥10 are recommended for further validation with a larger panel. 2020 Translational Lung Cancer Research. All rights reserved.Background Sequencing artifacts, clonal hematopoietic mutations of indeterminate potential (CHIP) and tumor heterogeneity have been hypothesized to contribute to the low concordance between tissue and cell-free DNA (cfDNA) molecular profiling with targeted sequencing. Methods We analyzed by targeted sequencing cfDNA from 30 healthy individuals, and cfDNA and matched tumor samples from 30 EGFR-mutant and 77 EGFR wild-type metastatic non-small-cell lung cancer (mNSCLC) patients. Discordant cases were solved by droplet digital PCR (ddPCR). Results By testing cfDNA from healthy donors, we developed an algorithm to recognize sequencing artifacts. Applying this method to cfDNA from mNSCLC patients, EGFR mutations were detected with a good sensitivity (76.7%) and specificity (97.4%). In contrast, sensitivity and specificity for KRAS variants were 61.5% and 93.8%, respectively. All EGFR and KRAS variants detected in plasma but not in tissue were confirmed by ddPCR, thus excluding sequencing artifacts. In a fraction of cases, KRAS mutations found in plasma samples were confirmed in tumor tissue suggesting tumor heterogeneity. KRAS variants were found to be more likely sub-clonal as compared with EGFR mutations, and a correlation between clonal origin and frequency of detection in plasma was found. In a case with both EGFR and KRAS variants in cfDNA, we could demonstrate the presence of the KRAS variant in tumor tissue associated with lack of response to tyrosine kinase inhibitors (TKIs). Conclusions Although sequencing artifacts can be identified in targeted sequencing of cfDNA, tumor heterogeneity and CHIP are likely to influence the concordance between plasma and tissue testing. 2020 Translational Lung Cancer Research. All rights reserved.Background Although many studies have determined that PD-L1 expression by immunohistochemistry can be somewhat predictive of a response to checkpoint inhibitor the impact of specific genomic changes and smoking history in the context of PD-L1 expression is limited. This single-center study examined clinical and genomic factors beyond STK11 and EGFR in patients with advanced non-small cell lung cancer (NSCLC) to determine which patients benefit from therapy with immune checkpoint inhibitors (ICIs). Methods Clinical and genomic features of patients with NSCLC treated with immunotherapy were compiled into a database. Genomic information collected included gene mutations via next generation sequencing, tumor mutation burden (TMB), and PD-L1 tumor proportional scores. Results A total of 131 patients with advanced NSCLC treated with ICIs were examined. Race was not associated with response. A positive response to immunotherapy was associated with smoke year increase (P=0.042). KRAS mutation and MYC amplification were associated with a positive response to immunotherapy while EGFR, RB1, and NF1 mutations were associated with a lack of response. KRAS mutation (P=0.007) and high TMB (P=0.070) were positively associated with smoking history. EGFR mutation was negatively associated with smoking history (P=0.002) . In multivariate analysis controlling for age and smoking history, MYC amplification continued to be the only predictive genomic marker with a trend toward response to therapy (P=0.092) beyond the smoking history. Conclusions Among the clinical and genomic factors examined in this study, smoking status is the most predictive of response to ICIs. Only MYC amplification continued to predict a trend toward response to immunotherapy when controlling for smoking history. Other genomic predictors such as EGFR and KRAS simply reflect their association with smoking. PF-05221304 research buy Detailed smoking history and MYC amplification alone can predict response to ICI. 2020 Translational Lung Cancer Research. All rights reserved.Background Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare clinical subtype of lung cancer which has a poor prognosis for patients. This study aimed to explore the relationship between blood-based inflammatory markers, namely neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and the prognosis for pulmonary LCNEC. Methods Peripheral leukocyte and platelet counts of 106 LCNEC patients were measured within the week leading up to their surgery. Serum neuron specific enolase (NSE) was detected by ELISA. Overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test. Results The NLR and PLR cut-off values based on survival receiver operating characteristic curve (ROC) were 2.52 and 133.6, respectively. A correlation was found between dichotomized NLR and tumor size (P=0.006), and PLR and NLR were significantly correlated with each other (P less then 0.001). Patients with high NLR or PLR had shorter survival than those with low NLR (HR =2.46, 95% CI 1.
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