Prognostic impact of p53 protein overexpression in patients with node-negative lung adenocarcinoma

Tumor mutation burden and immunological, genomic, and clinicopathological factors as biomarkers for checkpoint inhibitor treatment of patients with non-small-cell lung cancer

Cancer treatment using immune checkpoint inhibitors is widely used, although biomarkers predictive of response are not well established. However, both the expressions of programmed cell death ligand 1 (PD-L1) and the tumor mutation burden (TMB) hold promise as such biomarkers for immune checkpoint inhibitors; however, its characteristics and clinical and immunological impacts have not been fully analyzed. We, therefore, evaluated the clinical and immunological parameters related to TMB to identify potential new biomarkers. We enrolled 92 patients with non-small-cell lung cancer who underwent surgery at Fukushima Medical University Hospital from 2013 to 2016. TMB of individual tumors was calculated by whole-exome sequencing analysis. Major cancer-related gene mutations were evaluated using panel sequencing. Expression of PD-L1 and abundance of tumor-infiltrating lymphocytes were evaluated by immunohistochemistry using surgical samples. The median TMB value was 60. TMB was significantly higher in men, current or former smokers, and in patients with squamous cell carcinoma, tumor size ≥ 2.8 cm, wild-type EGFR, TP53 gene mutation-positive status, and cyclin-dependent kinase-inhibitor gene 2A mutation-positive status. According to multivariate analysis, TMB was significantly associated with EGFR gene mutation-negative status (p = 0.0111) and TP53 gene mutation-positive status (p = 0.0425). If TMB is identified as a robust biomarker for immune checkpoint inhibitor administration, analysis of TP53 and EGFR mutations may provide a relatively rapid and easy proxy for predicting TMB.

Genome-scale analysis to identify prognostic markers and predict the survival of lung adenocarcinoma

Lung cancer is one of the most malignant cancers worldwide, and lung adenocarcinoma (LAC) remains the most common histologic subtype. However, the functional significance of RNA expression-based prognosis prediction in LAC is still unclear and needs to be further studied. By utilizing the Cox multivariate regression, we established a risk score staging system to predict the outcome of patients with LAC and subsequently identified 10 genes, including PTPRH, OGFRP1, LDHA, AL365203.1, LINC02178, AL512488.1, LINC01312, AL353746.1, DRAXINP1, and LINC02310, which were closely related to the prognosis of patients with LAC. The identified genes allowed us to classify patients into high-risk group with poor outcome and low-risk group with better outcome. Compared with other clinical factors, the risk score performs better in predicting the outcome of LAC patients. We used Gene-Set Enrichment Analysis to identify the differences between the 2 groups in biological pathways. In conclusion, we identified 10 genes by utilizing Cox regression model and developed a risk staging model for LAC, which might prove significant for the clinical management of LAC patients.

Prediction of recurrence for non-small cell lung cancer by combined analysis of molecular markers and 18F 2-fluoro-2-deoxy-D-glucose positron emission tomography

PURPOSE

Numerous biomarkers have been reported to reflect prognosis in patients with non-small cell lung cancer, but most of them remain controversial in terms of the clinical benefits. The aim of this study is to establish a novel procedure in combined analyses of molecular markers and biomedical image for precise prediction for patient prognosis of non-small cell lung cancer.

EXPERIMENTAL DESIGN

Molecular markers related to cell cycle and proliferation and (18)F 2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) were retrospectively analyzed for their utility as prognostic parameters in 54 patients with non-small cell lung cancer. Expression of ten representative molecular markers (Glut-1, proliferating cell nuclear antigen, Ki-67, cyclin B1, cyclin D1, cyclin E, E2F-1, p21, p27, and p53) were immunohistochemically analyzed using tissue microarray. The maximum standardized uptake value (SUVmax) on FDG-PET was analyzed as a semiquantitative value of FDG uptake of the primary tumor.

RESULTS

Several molecular markers were significantly correlated with some of clinicopathological parameters, whereas none of each marker were correlated with recurrence or survival. Hierarchical clustering analysis in combination of immunohistochemical analysis of molecular expressions and SUVmax divided them into three subgroups significantly different in two-year recurrent-free survival (Cluster A, 56.3%; B, 100%; C 93.8%). These clustering subgroups were also significantly correlated with disease recurrence (p=0.0282).

CONCLUSIONS

Hierarchical clustering analysis, based on molecular markers and FDG accumulation, could be an efficient tool for prediction of recurrence and survival in patients with non-small cell lung cancer.

Molecular profiling in non-small cell lung cancer: a step toward personalized medicine

CONTEXT

Lung carcinoma is the result of sequential accumulation of genetic and epigenetic changes. Lung adenocarcinoma is a heterogeneous disease with diverse somatic mutations, and several of them include the so-called driver mutations, which may serve as "druggable" therapeutic targets. Thus, development of personalized approaches for the treatment of non-small cell lung carcinoma (NSCLC) mandates that pathologists make a precise histologic classification inclusive of routine molecular analysis of such tumors.

OBJECTIVE

To address the molecular mechanisms underlying NSCLC and how this knowledge reflects the multidisciplinary approach in the diagnosis and management of these patients. We will also summarize the current available and investigational personalized therapies for patients with resectable early-stage, unresectable locally advanced, and metastatic NSCLC.

DATA SOURCES

Peer-reviewed published literature and personal experience.

CONCLUSIONS

There are multiple mechanisms involved in the pathogenesis of lung cancer, which operate in parallel and involve pathways of activation and inhibition of various cellular events. Further research is essential to characterize the histologic and mutational profiles of lung carcinomas, which will ultimately translate into improved and more personalized therapeutic management of patients with lung cancer.

Expression and prognostic significance of centromere protein A in human lung adenocarcinoma

BACKGROUND

Centromere protein A (CENP-A), one of the fundamental components of the human active kinetochore, is frequently upregulated in many cancers and plays important roles in cell cycle regulation, cell survival, and genetic stability. The aim of the present study was to explore the expression and prognostic significance of CENP-A in lung adenocarcinoma.

EXPERIMENTAL DESIGN

The expression of CENP-A was detected in 20 fresh human lung adenocarcinoma specimens and corresponding non-tumorous lung tissues by real-time polymerase chain reaction (RT-PCR) and Western blotting analysis. Using immunohistochemistry, we analyzed CENP-A protein expression in additional 309 lung adenocarcinomas. The clinicopathological and prognostic significance of CENP-A expression was analyzed.

RESULTS

RT-PCR and Western blotting analysis revealed an enhanced expression of CENP-A in lung adenocarcinomas relative to adjacent non-tumorous lung tissues at both transcriptional and translational levels. Immunohistochemistry showed that 146 of 309 lung adenocarcinomas (47.3%) had high expression of CENP-A. CENP-A overexpression was significantly correlated with pathological grade (P=0.009), pT status (P=0.017), pN status (P=0.002), pleural invasion (P=0.013), high Ki-67 expression (P=0.003), and P53 positivity (P=0.001). Patients with high CENP-A expression had shorter overall survival time compared with those with low CENP-A expression. Multivariate analysis identified CENP-A as an independent prognostic factor for lung adenocarcinoma.

CONCLUSION

Our results demonstrate that elevated CENP-A expression is closely associated with lung adenocarcinoma progression and has an independent prognostic value in predicting overall survival for patients with lung adenocarcinoma.

[High resolution melting analysis for detecting p53 gene mutations in patients with non-small cell lung cancer]

背景与目的

p53基因与人类多种肿瘤相关，突变型具有致癌作用，主要分布在外显子5-8。本研究旨在建立高分辨熔解曲线（high resolution melting, HRM）检测非小细胞肺癌（non-small cell lung cancer, NSCLC）患者p53基因突变的方法，探讨p53基因突变的特点及其在NSCLC发生发展中的演变规律。

方法

采用HRM法检测264例NSCLC患者肿瘤组织和54例癌旁肺组织p53基因外显子5-8的突变，突变样品进一步使用PCR产物直接测序法分析确定突变类型；HRM法检测阳性而PCR产物直接测序法检测阴性的样品，进一步进行亚克隆测序证实。

结果

54例对照未发现突变。264例肿瘤组织中，HRM法检出p53基因突变104例，102例得到PCR产物直接测序法证实，突变率为39.4%；95例为点突变，7例为碱基插入和缺失导致的移码突变。p53外显子5-8的突变率分别为11.7%、8%、12.5%和10.6%，差异无统计学意义（P=0.35）。p53基因突变与性别有关，与其它临床病理特征无关。

结论

HRM法筛选p53基因突变样品，具有操作简便、快速、敏感、单管避免污染等优点，值得推广。p53基因的突变特点提示，p53基因突变是自发性突变，可能是DNA合成和修复过程中的随机错误所致。

Genetic and epigenetic changes in lung carcinoma and their clinical implications

Lung cancer is the leading cause of cancer deaths worldwide. Recent advance in targeted therapy for lung cancer patients with epidermal growth factor receptor (EGFR) mutations has demonstrated a promising development toward personalized therapy for lung cancer patients. The development of lung cancer is a complex process, involving a series of genetic and epigenetic changes. Tobacco smoke is the predominant etiologic risk factor for lung cancer. However, some lung cancers, especially adenocarcinomas, arise in patients who have never smoked, suggesting the importance of host genetic/epigenetic susceptibility in the occurrence and development of lung cancer. Understanding of these genetic and epigenetic changes will further aid in the biomarker-driven personalized therapy for lung cancer patients. In this review, we summarize the genetic and epigenetic alterations observed in lung cancers, including chromosomal loss of heterozygosity, tumor-suppressor gene mutation, gene methylation, histone modification, and microRNA expression changes. Clinical and preclinical studies have implied specific genetic/epigenetic changes for clinical application in lung cancer patients. However, more efforts are required in validation of the identified molecular markers in lung cancer patients for early detections, assessment for treatment response, and survival predictions.