Background: Lung cancer is the number one cancer killer in the world with more than 142,670 deaths estimated in the United States alone in the year 2019. Consequently, there is an overreaching need to identify the key biomarkers for lung cancer. The aim of this study is to computationally identify biomarker genes for lung cancer that can aid in its diagnosis and treatment. The gene expression profiles of two different types of studies, namely non-treatment and treatment, are considered for discovering biomarker genes. In non-treatment studies healthy samples are control and cancer samples are cases. Whereas, in treatment studies, controls are cancer cell lines without treatment and cases are cancer cell lines with treatment. Results: The Differentially Expressed Genes (DEGs) for lung cancer were isolated from Gene Expression Omnibus (GEO) database using R software tool GEO2R. A total of 407 DEGs (254 upregulated and 153 downregulated) from non-treatment studies and 547 DEGs (133 upregulated and 414 downregulated) from treatment studies were isolated. Two Cytoscape apps, namely, CytoHubba and MCODE, were used for identifying biomarker genes from functional networks developed using DEG genes. This study discovered two distinct sets of biomarker genes – one from non-treatment studies and the other from treatment studies, each set containing 16 genes. Survival analysis results show that most non-treatment biomarker genes have prognostic capability by indicating low-expression groups have higher chance of survival compare to high-expression groups. Whereas, most treatment biomarkers have prognostic capability by indicating high-expression groups have higher chance of survival compare to low-expression groups. Conclusion: A computational framework is developed to identify biomarker genes for lung cancer using gene expression profiles. Two different types of studies – non-treatment and treatment – are considered for experiment. Most of the biomarker genes from non-treatment studies are part of mitosis and play vital role in DNA repair and cell-cycle regulation. Whereas, most of the biomarker genes from treatment studies are associated to ubiquitination and cellular response to stress. This study discovered a list of biomarkers, which would help experimental scientists to design a lab experiment for further exploration of detail dynamics of lung cancer development.

Background: Lung cancer is the number one cancer killer worldwide. A major drawback in the lung cancer treatment field is the lack of realistic mouse models that replicate the complexity of human malignancy and immune contexture within the tumor microenvironment. Such models are urgently needed. Mutations of the tumor protein p53 are among the most common alterations in human lung cancers. Methods: Previously, we developed a line of lung cancer mouse model where mutant human TP53-273H is expressed in a lung specific manner in FVB/N background. To investigate whether the human TP53 mutant has a similar oncogenic potential when it is expressed in another strain of mouse, we crossed the FVB/N-SPC-TP53-273H mice to A/J strain and created A/J-SPC-TP53-273H transgenic mice. We then compared lung tumor formation between A/J-SPC-TP53-273H and FVB/N-SPC-TP53-273H. Results: We found the TP53-273H mutant gene has a similar oncogenic potential in lung tumor formation in both mice strains, although A/J strain mice have been found to be a highly susceptible strain in terms of carcinogen-induced lung cancer. Both transgenic lines survived more than 18 months and developed age related lung adenocarcinomas. With micro CT imaging, we found the FVB-SPC-TP53-273H mice survived more than 8 weeks after initial detection of lung cancer, providing a sufficient window for evaluating new anti-cancer agents. Conclusions: Oncogenic potential of the most common genetic mutation, TP53-273H, in human lung cancer is unique when it is expressed in different strains of mice. Our mouse models are useful tools for testing novel immune checkpoint inhibitors or other therapeutic strategies in the treatment of lung cancer.

Lung squamous cell carcinoma (LUSC) accounts for one of three of non–small cell lung carcinoma (NSCLC) and 30% of LUSC patients present with locally advanced, unresectable/medically inoperable disease, who are commonly treated with definitive chemoradiation. However, disease relapse in the radiation fields occurs in one of three cases. We aim to explore the underlying molecular mechanisms of chemoradiation resistance of LUSC. Patient-derived xenograft (PDX) models of LUSC were established in immunodeficient mice, followed by treatment with cisplatin in combination with clinically relevant courses of ionizing radiation (20, 30, and 40 Gy). The recurrent tumors were extracted for functional proteomics using reverse phase protein analysis (RPPA). We found that phospho-AKT-S473, phospho-AKT-T308, phospho-S6-S235/6, and phospho-GSK3β-S9 were upregulated in the chemoradiation-resistant 20 Gy + cisplatin and 40 Gy + cisplatin tumors compared with those in the control tumors. Ingenuity pathway analysis of the RPPA data revealed that AKT–mTOR signaling was the most activated signaling pathway in the chemoradiation-resistant tumors. Similarly, elevated AKT–mTOR signaling was observed in stable 40 Gy and 60 Gy resistant HARA cell lines compared with the parental cell line. Accordingly, pharmacologic inhibition of mTOR kinase by Torin2 significantly sensitized LUSC cell lines to ionizing radiation. In conclusion, using chemoradiation-resistant PDX models coupled with RPPA proteomics analysis, we revealed that deregulation of AKT–mTOR signaling may contribute to the chemoradiation resistance of LUSC. Implications: Clonal selection of subpopulations with high AKT–mTOR signaling in heterogeneous tumors may contribute to relapse of LUSC after chemoradiation. mTOR kinase inhibitors may be promising radiosensitizing agents in upfront treatment to prevent acquired resistance.

The Fanconi Anemia (FA) pathway is essential for human cells to maintain genomic integrity following DNA damage. This pathway is involved in repairing damaged DNA through homologous recombination. Cancers with a defective FA pathway are expected to be more sensitive to cross-link based therapy or PARP inhibitors. To evaluate downstream effectors of the FA pathway, we studied the expression of 734 different micro RNAs (miRNA) using NanoString nCounter miRNA array in two FA defective lung cancer cells and matched control cells, along with two lung tumors and matched non-tumor tissue samples that were deficient in the FA pathway. Selected miRNA expression was validated with real-time PCR analysis. Among 734 different miRNAs, a cluster of microRNAs were found to be up-regulated including an important cancer related micro RNA, miR-200C. MiRNA-200C has been reported as a negative regulator of epithelial-mesenchymal transition (EMT) and inhibits cell migration and invasion by promoting the upregulation of E-cadherin through targeting ZEB1 and ZEB2 transcription factors. miRNA-200C was increased in the FA defective lung cancers as compared to controls. AmpliSeq analysis showed significant reduction in ZEB1 and ZEB2 mRNA expression. Our findings indicate the miRNA-200C potentially play a very important role in FA pathway downstream regulation.

Supplementary Data from Deregulation of AKT–mTOR Signaling Contributes to Chemoradiation Resistance in Lung Squamous Cell Carcinoma