Transcriptome sequencing of tumor subpopulations reveals a spectrum of therapeutic options for squamous cell lung cancer

Pre-clinical lung squamous cell carcinoma mouse models to identify novel biomarkers and therapeutic interventions

Primary lung carcinoma or lung cancer (LC) is classified into small-cell or non-small-cell (NSCLC) lung carcinoma. Lung squamous cell carcinoma (LSCC) is the second most common subtype of NSCLC responsible for 30% of all LCs, and its survival remains low with only 24% of patients living for five years or longer post-diagnosis primarily due to the advanced stage of tumors at the time of diagnosis. The pathogenesis of LSCC is still poorly understood and has hampered the development of effective diagnostics and therapies. This review highlights the known risk factors, genetic and epigenetic alterations, miRNA biomarkers linked to the development and diagnosis of LSCC and the lack of therapeutic strategies to target specifically LSCC. We will also discuss existing animal models of LSCC including carcinogen induced, transgenic and xenograft mouse models, and their advantages and limitations along with the chemopreventive studies and molecular studies conducted using them. The importance of developing new and improved mouse models will also be discussed that will provide further insights into the initiation and progression of LSCC, and enable the identification of new biomarkers and therapeutic targets.

Abnormal alternative splicing promotes tumor resistance in targeted therapy and immunotherapy

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Abnormal alternative splicing is involve in abnormal expression of genes in cancer.

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Abnormal alternative splicing events promote malignant progression of cancer.

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Abnormal alternative splicing develops tumor resistance to targeted therapy by changing the target point and signal transduction pathway.

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Abnormal alternative splicing develops tumor resistance to immunotherapy by changing cell surface antigens and protein structure.

Abnormally alternative splicing events are common hallmark of diverse types of cancers. Splicing variants with aberrant functions play an important role in cancer development. Most importantly, a growing body of evidence has supported that alternative splicing might play a significant role in the therapeutic resistance of tumors. Targeted therapy and immunotherapy are the future directions of tumor therapy; however, the loss of antigen targets on the tumor cells surface and alterations in drug efficacy have resulted in the failure of targeted therapy and immunotherapy. Interestingly, abnormal alternative splicing, as a strategy to regulate gene expression, is reportedly involved in the reprogramming of cell signaling pathways and epitopes on the tumor cell surface by changing splicing patterns of genes, thus rendering tumors resisted to targeted therapy and immunotherapy. Accordingly, increased knowledge regarding abnormal alternative splicing in tumors may help predict therapeutic resistance during targeted therapy and immunotherapy and lead to novel therapeutic approaches in cancer. Herein, we provide a brief synopsis of abnormal alternative splicing events in cancer progression and therapeutic resistance.

Insights into new mechanisms and models of cancer stem cell multidrug resistance

The acquisition of genetic alterations, clonal evolution, and the tumor microenvironment promote cancer progression, metastasis and therapy resistance. These events correspond to the establishment of the great phenotypic heterogeneity and plasticity of cancer cells that contribute to tumor progression and resistant disease. Targeting resistant cancers is a major challenge in oncology; however, the underlying processes are not yet fully understood. Even though current treatments can reduce tumor size and increase life expectancy, relapse and multidrug resistance (MDR) ultimately remain the second cause of death in developed countries. Recent evidence points toward stem-like phenotypes in cancer cells, promoted by cancer stem cells (CSCs), as the main culprit of cancer relapse, resistance (radiotherapy, hormone therapy, and/or chemotherapy) and metastasis. Many mechanisms have been proposed for CSC resistance, such as drug efflux through ABC transporters, overactivation of the DNA damage response (DDR), apoptosis evasion, prosurvival pathways activation, cell cycle promotion and/or cell metabolic alterations. Nonetheless, targeted therapy toward these specific CSC mechanisms is only partially effective to prevent or abolish resistance, suggesting underlying additional causes for CSC resilience. This article aims to provide an integrated picture of the MDR mechanisms that operate in CSCs' behavior and to propose a novel model of tumor evolution during chemotherapy. Targeting the pathways mentioned here might hold promise and reveal new strategies for future clinical therapeutic approaches.

Molecular histology of lung cancer: from targets to treatments

Lung cancer is the leading cause of cancer-related death worldwide with a 5-year survival rate of less than 15%, despite significant advances in both diagnostic and therapeutic approaches. Combined genomic and transcriptomic sequencing studies have identified numerous genetic driver mutations that are responsible for the development of lung cancer. In addition, molecular profiling studies identify gene products and their mutations which predict tumour responses to targeted therapies such as protein tyrosine kinase inhibitors and also can offer explanation for drug resistance mechanisms. The profiling of circulating micro-RNAs has also provided an ability to discriminate patients in terms of prognosis/diagnosis and high-throughput DNA sequencing strategies are beginning to elucidate cell signalling pathway mutations associated with oncogenesis, including potential stem cell associated pathways, offering the promise that future therapies may target this sub-population, preventing disease relapse post treatment and improving patient survival. This review provides an assessment of molecular profiling within lung cancer concerning molecular mechanisms, treatment options and disease-progression. Current areas of development within lung cancer profiling are discussed (i.e. profiling of circulating tumour cells) and future challenges for lung cancer treatment addressed such as detection of micro-metastases and cancer stem cells.

Expression profiles of 151 pediatric low-grade gliomas reveal molecular differences associated with location and histological subtype

BACKGROUND

Pediatric low-grade gliomas (PLGGs), the most frequent pediatric brain tumor, comprise a heterogeneous group of diseases. Recent genomic analyses suggest that these tumors are mostly driven by mitogene-activated protein kinase (MAPK) pathway alterations. However, little is known about the molecular characteristics inherent to their clinical and histological heterogeneity.

METHODS

We performed gene expression profiling on 151 paraffin-embedded PLGGs from different locations, ages, and histologies. Using unsupervised and supervised analyses, we compared molecular features with age, location, histology, and BRAF genomic status. We compared molecular differences with normal pediatric brain expression profiles to observe whether those patterns were mirrored in normal brain.

RESULTS

Unsupervised clustering distinguished 3 molecular groups that correlated with location in the brain and histological subtype. "Not otherwise specified" (NOS) tumors did not constitute a unified class. Supratentorial pilocytic astrocytomas (PAs) were significantly enriched with genes involved in pathways related to inflammatory activity compared with infratentorial tumors. Differences based on tumor location were not mirrored in location-dependent differences in expression within normal brain tissue. We identified significant differences between supratentorial PAs and diffuse astrocytomas as well as between supratentorial PAs and dysembryoplastic neuroepithelial tumors but not between supratentorial PAs and gangliogliomas. Similar expression patterns were observed between childhood and adolescent PAs. We identified differences between BRAF-duplicated and V600E-mutated tumors but not between primary and recurrent PLGGs.

CONCLUSION

Expression profiling of PLGGs reveals significant differences associated with tumor location, histology, and BRAF genomic status. Supratentorial PAs, in particular, are enriched in inflammatory pathways that appear to be tumor-related.

Revealing Biological Pathways Implicated in Lung Cancer from TCGA Gene Expression Data Using Gene Set Enrichment Analysis

Analyzing biological system abnormalities in cancer patients based on measures of biological entities, such as gene expression levels, is an important and challenging problem. This paper applies existing methods, Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis, to pathway abnormality analysis in lung cancer using microarray gene expression data. Gene expression data from studies of Lung Squamous Cell Carcinoma (LUSC) in The Cancer Genome Atlas project, and pathway gene set data from the Kyoto Encyclopedia of Genes and Genomes were used to analyze the relationship between pathways and phenotypes. Results, in the form of pathway rankings, indicate that some pathways may behave abnormally in LUSC. For example, both the cell cycle and viral carcinogenesis pathways ranked very high in LUSC. Furthermore, some pathways that are known to be associated with cancer, such as the p53 and the PI3K-Akt signal transduction pathways, were found to rank high in LUSC. Other pathways, such as bladder cancer and thyroid cancer pathways, were also ranked high in LUSC.

MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing

Background

Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome.

Results

For optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients.

Conclusions

Our software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://bioinformaticstools.mayo.edu/research/maprseq/.

Whole transcriptome sequencing enables discovery and analysis of viruses in archived primary central nervous system lymphomas

Primary central nervous system lymphomas (PCNSL) have a dramatically increased prevalence among persons living with AIDS and are known to be associated with human Epstein Barr virus (EBV) infection. Previous work suggests that in some cases, co-infection with other viruses may be important for PCNSL pathogenesis. Viral transcription in tumor samples can be measured using next generation transcriptome sequencing. We demonstrate the ability of transcriptome sequencing to identify viruses, characterize viral expression, and identify viral variants by sequencing four archived AIDS-related PCNSL tissue samples and analyzing raw sequencing reads. EBV was detected in all four PCNSL samples and cytomegalovirus (CMV), JC polyomavirus (JCV), and HIV were also discovered, consistent with clinical diagnoses. CMV was found to express three long non-coding RNAs recently reported as expressed during active infection. Single nucleotide variants were observed in each of the viruses observed and three indels were found in CMV. No viruses were found in several control tumor types including 32 diffuse large B-cell lymphoma samples. This study demonstrates the ability of next generation transcriptome sequencing to accurately identify viruses, including DNA viruses, in solid human cancer tissue samples.