Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD) data

<p>Abstract</p> <p>Background</p> <p>The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by <it>in-silico</it> methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability.</p> <p>Results</p> <p>Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4).</p> <p>Conclusions</p> <p>Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.</p

Plausible role of INPP4A dysregulation in idiopathic pulmonary fibrosis

Abstract INPP4A has been shown to be involved in the regulation of cell proliferation and apoptosis of multiple cell types including fibroblasts. Previous reports from our group have demonstrated the role of inositol polyphosphate 4‐phosphatase Type I A (INPP4A) in these functions. Though existing evidences suggest a critical role for INPP4A in the maintenance of lung homeostasis, its role in chronic lung diseases is relatively under explored. In the current study, we made an attempt to understand the regulation of INPP4A in idiopathic pulmonary fibrosis (IPF). Through integration of relevant INPP4A gene expression data from public repositories with our results from in vitro experiments and mouse models, we show that INPP4A is altered in IPF. Interestingly, the direction of the change is dependent both on the disease stage and the region of the lung used. INPP4A was found to be upregulated when analyzed in lung sample representative of the whole lung, but was downregulated in the fibrotic regions of the lung. Similarly, INPP4A was found to be high, compared to controls, only in the early stage of the disease. Though the observed increase in INPP4A was found to be negatively correlated to physiological indices, FVC, and DLCO, of lung function, treatment with anti‐INPP4A antibody worsened the condition in bleomycin treated mice. These contrasting results taken together are suggestive of a nuanced regulation of INPP4A in IPF which is dependent on the disease stage, cellular state and extent of fibrosis in the lung region being analyzed