Small-cell lung cancer-associated autoantibodies: potential applications to cancer diagnosis, early detection, and therapy

Small-cell lung cancer (SCLC) is the most aggressive lung cancer subtype and lacks effective early detection methods and therapies. A number of rare paraneoplastic neurologic autoimmune diseases are strongly associated with SCLC. Most patients with such paraneoplastic syndromes harbor high titers of antibodies against neuronal proteins that are abnormally expressed in SCLC tumors. These autoantibodies may cross-react with the nervous system, possibly contributing to autoimmune disease development. Importantly, similar antibodies are present in many SCLC patients without autoimmune disease, albeit at lower titers. The timing of autoantibody development relative to cancer and the nature of the immune trigger remain to be elucidated. Here we review what is currently known about SCLC-associated autoantibodies, and describe a recently developed mouse model system of SCLC that appears to lend itself well to the study of the SCLC-associated immune response. We also discuss potential clinical applications for these autoantibodies, such as SCLC diagnosis, early detection, and therapy

DNA methylation-based biomarkers for early detection of non-small cell lung cancer: an update

Lung cancer is the number one cancer killer in the United States. This disease is clinically divided into two sub-types, small cell lung cancer, (10–15% of lung cancer cases), and non-small cell lung cancer (NSCLC; 85–90% of cases). Early detection of NSCLC, which is the more common and less aggressive of the two sub-types, has the highest potential for saving lives. As yet, no routine screening method that enables early detection exists, and this is a key factor in the high mortality rate of this disease. Imaging and cytology-based screening strategies have been employed for early detection, and while some are sensitive, none have been demonstrated to reduce lung cancer mortality. However, mortality might be reduced by developing specific molecular markers that can complement imaging techniques. DNA methylation has emerged as a highly promising biomarker and is being actively studied in multiple cancers. The analysis of DNA methylation-based biomarkers is rapidly advancing, and a large number of potential biomarkers have been identified. Here we present a detailed review of the literature, focusing on DNA methylation-based markers developed using primary NSCLC tissue. Viable markers for clinical diagnosis must be detectable in 'remote media' such as blood, sputum, bronchoalveolar lavage, or even exhaled breath condensate. We discuss progress on their detection in such media and the sensitivity and specificity of the molecular marker panels identified to date. Lastly, we look to future advancements that will be made possible with the interrogation of the epigenome

The importance of detailed epigenomic profiling of different cell types within organs.

The human body consists of hundreds of kinds of cells specified from a single genome overlaid with cell type-specific epigenetic information. Comprehensively profiling the body's distinct epigenetic landscapes will allow researchers to verify cell types used in regenerative medicine and to determine the epigenetic effects of disease, environmental exposures and genetic variation. Key marks/factors that should be investigated include regions of nucleosome-free DNA accessible to regulatory factors, histone marks defining active enhancers and promoters, DNA methylation levels, regulatory RNAs, and factors controlling the three-dimensional conformation of the genome. Here we use the lung to illustrate the importance of investigating an organ's purified cell epigenomes, and outline the challenges and promise of realizing a comprehensive catalog of primary cell epigenomes

Transcriptomic profiling of primary alveolar epithelial cell differentiation in human and rat

AbstractCell-type specific gene regulation is a key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how changes in transcriptional activation during alveolar epithelial cell (AEC) differentiation determine phenotype. We performed transcriptomic profiling using in vitro differentiation of human and rat primary AEC. This model recapitulates in vitro an in vivo process in which AEC transition from alveolar type 2 (AT2) cells to alveolar type 1 (AT1) cells during normal maintenance and regeneration following lung injury. Here we describe in detail the quality control, preprocessing, and normalization of microarray data presented within the associated study (Marconett et al., 2013). We also include R code for reproducibility of the referenced data and easily accessible processed data tables

Kinetic analysis of the role of the tyrosine 13, phenylalanine 56 and glutamine 54 network in the U1A/U1 hairpin II interaction

The A protein of the U1 small nuclear ribonucleoprotein particle, interacting with its stem–loop RNA target (U1hpII), is frequently used as a paradigm for RNA binding by recognition motif domains (RRMs). U1A/U1hpII complex formation has been proposed to consist of at least two steps: electrostatically mediated alignment of both molecules followed by locking into place, based on the establishment of close-range interactions. The sequence of events between alignment and locking remains obscure. Here we examine the roles of three critical residues, Tyr13, Phe56 and Gln54, in complex formation and stability using Biacore. Our mutational and kinetic data suggest that Tyr13 plays a more important role than Phe56 in complex formation. Mutational analysis of Gln54, combined with molecular dynamics studies, points to Arg52 as another key residue in association. Based on our data and previous structural and modeling studies, we propose that electrostatic alignment of the molecules is followed by hydrogen bond formation between the RNA and Arg52, and the sequential establishment of interactions with loop bases (including Tyr13). A quadruple stack, sandwiching two bases between Phe56 and Asp92, would occur last and coincide with the rearrangement of a C-terminal helix that partially occludes the RRM surface in the free protein

Identification of a panel of sensitive and specific DNA methylation markers for lung adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>Lung cancer is the number one cancer killer of both men and women in the United States. Three quarters of lung cancer patients are diagnosed with regionally or distantly disseminated disease; their 5-year survival is only 15%. DNA hypermethylation at promoter CpG islands shows great promise as a cancer-specific marker that would complement visual lung cancer screening tools such as spiral CT, improving early detection. In lung cancer patients, such hypermethylation is detectable in a variety of samples ranging from tumor material to blood and sputum. To date the penetrance of DNA methylation at any single locus has been too low to provide great clinical sensitivity. We used the real-time PCR-based method MethyLight to examine DNA methylation quantitatively at twenty-eight loci in 51 primary human lung adenocarcinomas, 38 adjacent non-tumor lung samples, and 11 lung samples from non-lung cancer patients.</p> <p>Results</p> <p>We identified thirteen loci showing significant differential DNA methylation levels between tumor and non-tumor lung; eight of these show highly significant hypermethylation in adenocarcinoma: CDH13, CDKN2A EX2, CDX2, HOXA1, OPCML, RASSF1, SFPR1, and TWIST1 (p-value << 0.0001). Using the current tissue collection and 5-fold cross validation, the four most significant loci (CDKN2A EX2, CDX2, HOXA1 and OPCML) individually distinguish lung adenocarcinoma from non-cancer lung with a sensitivity of 67–86% and specificity of 74–82%. DNA methylation of these loci did not differ significantly based on gender, race, age or tumor stage, indicating their wide applicability as potential lung adenocarcinoma markers. We applied random forests to determine a good classifier based on a subset of our loci and determined that combined use of the same four top markers allows identification of lung cancer tissue from non-lung cancer tissue with 94% sensitivity and 90% specificity.</p> <p>Conclusion</p> <p>The identification of eight CpG island loci showing highly significant hypermethylation in lung adenocarcinoma provides strong candidates for evaluation in patient remote media such as plasma and sputum. The four most highly ranked loci, CDKN2A EX2, CDX2, HOXA1 and OPCML, which show significant DNA methylation even in stage IA tumor samples, merit further investigation as some of the most promising lung adenocarcinoma markers identified to date.</p

The role of positively charged amino acids and electrostatic interactions in the complex of U1A protein and U1 hairpin II RNA

Previous kinetic investigations of the N-terminal RNA recognition motif (RRM) domain of spliceosomal protein U1A, interacting with its RNA target U1 hairpin II, provided experimental evidence for a ‘lure and lock’ model of binding in which electrostatic interactions first guide the RNA to the protein, and close range interactions then lock the two molecules together. To further investigate the ‘lure’ step, here we examined the electrostatic roles of two sets of positively charged amino acids in U1A that do not make hydrogen bonds to the RNA: Lys20, Lys22 and Lys23 close to the RNA-binding site, and Arg7, Lys60 and Arg70, located on ‘top’ of the RRM domain, away from the RNA. Surface plasmon resonance-based kinetic studies, supplemented with salt dependence experiments and molecular dynamics simulation, indicate that Lys20 predominantly plays a role in association, while nearby residues Lys22 and Lys23 appear to be at least as important for complex stability. In contrast, kinetic analyses of residues away from the RNA indicate that they have a minimal effect on association and stability. Thus, well-positioned positively charged residues can be important for both initial complex formation and complex maintenance, illustrating the multiple roles of electrostatic interactions in protein–RNA complexes

Identification of a panel of sensitive and specific DNA methylation markers for squamous cell lung cancer

<p>Abstract</p> <p>Background</p> <p>Lung cancer is the leading cause of cancer death in men and women in the United States and Western Europe. Over 160,000 Americans die of this disease every year. The five-year survival rate is 15% – significantly lower than that of other major cancers. Early detection is a key factor in increasing lung cancer patient survival. DNA hypermethylation is recognized as an important mechanism for tumor suppressor gene inactivation in cancer and could yield powerful biomarkers for early detection of lung cancer. Here we focused on developing DNA methylation markers for squamous cell carcinoma of the lung. Using the sensitive, high-throughput DNA methylation analysis technique MethyLight, we examined the methylation profile of 42 loci in a collection of 45 squamous cell lung cancer samples and adjacent non-tumor lung tissues from the same patients.</p> <p>Results</p> <p>We identified 22 loci showing significantly higher DNA methylation levels in tumor tissue than adjacent non-tumor lung. Of these, eight showed highly significant hypermethylation in tumor tissue (p < 0.0001): GDNF, MTHFR, OPCML, TNFRSF25, TCF21, PAX8, PTPRN2 and PITX2. Used in combination on our specimen collection, this eight-locus panel showed 95.6% sensitivity and specificity.</p> <p>Conclusion</p> <p>We have identified 22 DNA methylation markers for squamous cell lung cancer, several of which have not previously been reported to be methylated in any type of human cancer. The top eight markers show great promise as a sensitive and specific DNA methylation marker panel for squamous cell lung cancer.</p

Genome-scale screen for DNA methylation-based detection markers for ovarian cancer.

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer