Gene Expression of the EGF System-a Prognostic Model in Non-Small Cell Lung Cancer Patients Without Activating EGFR Mutations

cGAS-STING pathway expression as a prognostic tool in NSCLC

Background

Disease recurrence in localized lung adenocarcinoma is a major obstacle for improving the overall outcome of lung cancer. Thus, better prognostic biomarkers are needed to identify patients at risk. In order to clear cancer, immune detection of tumor cells is of vital importance. DNA-leakage into the cytosol and tumor environment is one important tumor-associated danger signal and cGAS is a pivotal DNA-sensor that detects misplaced DNA and initiates an innate immune response. In this study, we investigate the cGAS-STING-pathway expression in tumor tissue and circulating immune cells from lung adenocarcinoma patients in relation to stage of disease and overall survival (OS).

Methods

Gene expression was measured using target specific droplet digital polymerase chain reaction (ddPCR) assays in a cohort of 80 patients with lung adenocarcinoma and 45 patients suspected of lung cancer, but determined to be cancer-free. The expression values were correlated to stage of disease. For further exploration of stage dependent expression, we used a publicly available gene expression data set to stratify patients by stage and correlate gene expression to OS.

Results

In both tumor tissue and peripheral blood mononuclear cells (PBMCs) from cancer patients, we observed differential expression of cGAS-STING pathway components compared to cancer-free individuals. Furthermore, cGAS-STING pathway expression was elevated in PBMCs from patients with localized disease (stage I and II) compared to patients with metastatic disease (stage III and IV). Survival analysis based on publicly available gene expression data sets demonstrated a superior OS for patients with localized disease and high levels of cGAS, STING and TBK1.

Conclusions

The expression of the cGAS-STING pathway is stage dependent and high expression is correlated with localized adenocarcinoma. For patients with localized disease, high cGAS, STING and TBK1 expression correlated with improved OS and may be a potential biomarker for this patient subgroup.

Genomic Profiling of Circulating Tumor DNA Predicts Outcome and Demonstrates Tumor Evolution in ALK-Positive Non-Small Cell Lung Cancer Patients

With the rapid development of targeted therapies for the treatment of cancer, methods for predicting response and outcome are in high demand. Non-small cell lung cancer driven by genomic rearrangements of the anaplastic lymphoma kinase (ALK) gene can be successfully treated with ALK-targeted therapy. Unfortunately, a subset of patients does not respond, and all patients ultimately acquire resistance, highlighting the need for better clinical tools to manage these patients. Here, we performed targeted next-generation sequencing on plasma circulating tumor DNA (ctDNA) from 24 patients to assess the clinical utility of ctDNA genomic profiling. Patients with detectable ctDNA prior to treatment had worse progression-free survival (PFS) than those without (median 8.7 vs. 15.2 months, p = 0.028). In addition, the presence of ctDNA within two months after treatment initiation predicted inferior PFS (median 4.6 vs. 14.5 months, p = 0.028). Longitudinal monitoring of ctDNA with droplet digital PCR during treatment reflected the radiological response and revealed potential acquired resistance mutations. Interestingly, an increase in the ctDNA concentration was evident prior to the determination of progressive disease by conventional radiological imaging, with a median lead time of 69 days (range 30-113). Genomic profiling of ctDNA is a promising tool for predicting outcome and monitoring response to targeted therapy.

The prognostic role of inflammation-scores on overall survival in lung cancer patients

OBJECTIVE

Inflammation has been validated as a host-related prognostic marker in cancer. The Glasgow Prognostic score (GPS) and neutrophil-to-lymphocyte ratio (NLR) are suggested measures of inflammation. However, the allocation of patients has been questioned. Hence, optimized inflammation-scores has been developed, such as the combined NLR and GPS (CNG) system, and the Aarhus composite biomarker score (ACBS). So far, these optimized inflammation-scores have not been validated in lung cancer patients. We evaluated if the optimized inflammation-scores were prognostic markers of inferior survival in lung cancer patients. Furthermore, we tested which of the optimized inflammation-scores led to better patient-allocation.

MATERIAL AND METHODS

The cohort of this prospective study composed of 275 non-small cell lung cancer patients. We evaluated pre-diagnostic serum biomarkers for GPR, NLR, platelet-to-lymphocyte ratio as well as the optimized inflammation-scores CNG and ABCS as predictors of overall survival (OS), and we examined the patient-allocation derived from each inflammation-score.

RESULTS

Each of the evaluated inflammation-scores could predict the overall survival even when adjustments were made for comorbidity and clinicopathological characteristics. When comparing the scores, the optimized inflammation-scores CNG and ACBS led to a better and more balanced patient-allocation. In the early clinical stages I & II, the optimized scores could reveal a subgroup of patients with poorer survival that is similar to stage III.

CONCLUSION

In this cohort of lung cancer patients, we demonstrate that inflammation-scores are prognostic markers of inferior survival. Furthermore, we demonstrate that the optimized inflammation-scores CNG and ACBS lead to better patient-allocation independently of the clinicopathological characteristics and comorbidity.

The promise of stem cell markers in the diagnosis and therapy of epithelial dysplasia and oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancer. Epithelial dysplasia is often initiated in the cells and cell nuclei adjacent to the epithelial cell membrane. Reduced cell-cell adhesions enable cancer cells to detach from the tumor and disseminate to other organs. The mutations in epithelial dysplasia markers such as E-cadherin and epithelial cell adhesion molecules (CD326) can lead to proliferation, growth and survival of the tumor cells and persistence of numerous malignancies that play a key role in epithelial dysplasia of OSCC. Accordingly, these genes can be considered prognostic markers or potential therapeutic targets for the tailored management of patients with OSCC. The gene expression profile of OSCC stem cells indicates a differential pattern that facilitates establishing a cell signature. Owing to the highly tumorigenic behavior of cancer stem cells and the role of these cells in tumor differentiation, treatment resistance, relapse, and metastasis, we reviewed the role of stem cell markers in epithelial dysplasia and OSCC.

Prognostic value of cancer antigen -125 for lung adenocarcinoma patients with brain metastasis: A random survival forest prognostic model

Using random survival forest, this study was intended to evaluate the prognostic value of serum markers for lung adenocarcinoma patients with brain metastasis (BM), and tried to integrate them into a prognostic model. During 2010 to 2015, the patients were retrieved from two medical centers. Besides the Cox proportional hazards regression, the random survival forest (RSF) were also used to develop prognostic model from the group A (n = 142). In RSF of the group A, the factors, whose minimal depth were greater than the depth threshold or had a negative variable importance (VIMP), were firstly excluded. Subsequently, C-index and Akaike information criterion (AIC) were used to guide us finding models with higher prognostic ability and lower overfitting possibility. These RSF models, together with the Cox, modified-RPA and lung-GPA index were validated and compared, especially in the group B (CAMS, n = 53). Our data indicated that the KSE125 model (KPS, smoking, EGFR-20 (exon 18, 19 and 21) and Ca125) was the best in survival prediction, and performed well in internal and external validation. In conclusions, for lung adenocarcinoma patients with brain metastasis, a validated prognostic nomogram (KPS, smoking, EGFR-20 and Ca125) can more accurately predict 1-year and 2-year survival of the patients.

Progression inference for somatic mutations in cancer

Computational methods were employed to determine progression inference of genomic alterations in commonly occurring cancers. Using cross-sectional TCGA data, we computed evolutionary trajectories involving selectivity relationships among pairs of gene-specific genomic alterations such as somatic mutations, deletions, amplifications, downregulation, and upregulation among the top 20 driver genes associated with each cancer. Results indicate that the majority of hierarchies involved TP53, PIK3CA, ERBB2, APC, KRAS, EGFR, IDH1, VHL, etc. Research into the order and accumulation of genomic alterations among cancer driver genes will ever-increase as the costs of nextgen sequencing subside, and personalized/precision medicine incorporates whole-genome scans into the diagnosis and treatment of cancer.