Molecular targets and signaling pathways regulated by interleukin (IL)-24 in mediating its antitumor activities

Cancer remains a major health issue in the world and the effectiveness of current therapies is limited resulting in disease recurrence and resistance to therapy. Therefore to overcome disease recurrence and have improved treatment efficacy there is a continued effort to develop and test new anticancer drugs that are natural or synthetic - (conventional chemotherapeutics, small molecule inhibitors) and biologic (antibody, tumor suppressor genes, oligonucleotide) product. In parallel, efforts for identifying molecular targets and signaling pathways to which cancer cells are “addicted” are underway. By inhibiting critical signaling pathways that is crucial for cancer cell survival, it is expected that the cancer cells will undergo a withdrawal symptom akin to “de-addiction” resulting in cell death. Thus, the key for having an improved and greater control on tumor growth and metastasis is to develop a therapeutic that is able to kill tumor cells efficiently by modulating critical signaling pathways on which cancer cells rely for their survival.Currently several small molecule inhibitors targeted towards unique molecular signaling pathways have been developed and tested in the clinic. Few of these inhibitors have shown efficacy while others have failed. Thus, targeting a single molecule or pathway may be insufficient to completely block cancer cell proliferation and survival. It is therefore important to identify and test an anticancer drug that can inhibit multiple signaling pathways in a cancer cell, control growth of both primary and metastatic tumors and is safe.One biologic agent that has the characteristics of serving as a potent anticancer drug is interleukin (IL)-24. IL-24 suppresses multiple signaling pathways in a broad-spectrum of human cancer cells leading to tumor cell death, inhibition of tumor angiogenesis and metastasis. Additionally, combining IL-24 with other therapies demonstrated additive to synergistic antitumor activity. Clinical testing of IL-24 as a gene-based therapeutic for the treatment of solid tumors demonstrated that IL-24 is efficacious and is safe. The unique features of IL-24 support its further development as an anticancer drug for cancer treatment.In this review we summarize the current understanding on the molecular targets and signaling pathways regulated by IL-24 in mediating its anticancer activity.     

Post-translational modification of RAS proteins

Mutations of RAS genes drive cancer more frequently than any other oncogene. RAS proteins integrate signals from a wide array of receptors and initiate downstream signaling through pathways that control cellular growth. RAS proteins are fundamentally binary molecular switches in which the off/on state is determined by the binding of GDP or GTP, respectively. As such, the intrinsic and regulated nucleotide-binding and hydrolytic properties of the RAS GTPase were historically believed to account for the entirety of the regulation of RAS signaling. However, it is increasingly clear that RAS proteins are also regulated by a vast array of post-translational modifications (PTMs). The current challenge is to understand what are the functional consequences of these modifications and which are physiologically relevant. Because PTMs are catalyzed by enzymes that may offer targets for drug discovery, the study of RAS PTMs has been a high priority for RAS biologists.     

Mammalian target of rapamycin: master regulator of cell growth in the nervous system

The mammalian target of rapamycin (mTOR) is a highly conserved serine/threonine protein kinase that regulates a number of diverse biologic processes important for cell growth and proliferation, including ribosomal biogenesis and protein translation. In this regard, hyperactivation of the mTOR signaling pathway has been demonstrated in numerous human cancers, including a number of inherited cancer syndromes in which individuals have an increased risk of developing benign and malignant tumors. Three of these inherited cancer syndromes (Lhermitte-Duclos disease, neurofibromatosis type 1, and tuberous sclerosis complex) are characterized by significant central nervous system dysfunction and brain tumor formation. Each of these disorders is caused by a genetic mutation that disrupts the expression of proteins which negatively regulate mTOR signaling, indicating that the mTOR signaling pathway is critical for appropriate brain development and function. In this review, we discuss our current understanding of the mTOR signaling pathway and its role in promoting ribosome biogenesis and cell growth. We suggest that studies of this pathway may prove useful in identifying molecular targets for biologically-based therapies of brain tumors associated with these inherited cancer syndromes as well as sporadic central nervous system tumors.     

e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks

Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate ‘edgetic’ mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.     

Bringing Down Cancer Aircraft: Searching for Essential Hypomutated Proteins in Skin Melanoma

We propose an approach to detection of essential genes/proteins required for cancer cell survival. A gene is considered essential if a mutation with high impact upon the function of encoded protein causes death of the cancer cell. We draw an analogy between essential cancer proteins and well-known Abraham Wald’s work on estimating the plane critical areas using data on survivability of aircraft encountering enemy fire. Wald reasoned that parts with no bullet holes on the airplanes returned to the airbase from a combat flight are the most crucial ones for the airplane functioning: a hit in one of these parts downs an airplane, so it does not return back for the survey. We have envisaged that the airplane surface is a cancer genome and the bullets are somatic mutations with high impact upon protein function. Similarly we propose that genes specifically essential for tumor cell survival should carry less high-impact mutations in cancer cells compared to polymorphisms found in normal cells. We used data on mutations from the Cancer Genome Atlas and polymorphisms found in healthy humans (from 1000 Genomes Project) to predict 91 protein-coding genes essential for melanoma. These genes were selected according to several criteria, including negative selection, expression in melanocytes and decrease in the proportion of high-impact mutations in cancer compared with normal cells. The Gene Ontology analysis revealed enrichment of essential proteins related to membrane and cell periphery. We speculate that this could be a sign of immune system-driven negative selection of cancer neo-antigens. Another finding is the overrepresentation of semaphorin receptors, which can mediate distinctive signaling cascades and are involved in various aspects of tumor development. Cytokine receptors CCR5 and CXCR1 were also identified as cancer essential proteins and this is confirmed by other studies. Overall, our goal was to illustrate the idea of detecting proteins whose sequence integrity and functioning is important for cancer cell survival. Hopefully, this prediction of essential cancer proteins may point to new targets for anti-tumor therapies.     

Structural and Logical Analysis of a Comprehensive Hedgehog Signaling Pathway to Identify Alternative Drug Targets for Glioma,Colon and Pancreatic Cancer

Hedgehog is an evolutionarily conserved developmental pathway, widely implicated in controlling various cellular responses such as cellular proliferation and stem cell renewal in human and other organisms, through external stimuli. Aberrant activation of this pathway in human adult stem cell line may cause different types of cancers. Hence, targeting this pathway in cancer therapy has become indispensable, but the non availability of detailed molecular interactions, complex regulations by extra- and intra-cellular proteins and cross talks with other pathways pose a serious challenge to get a coherent understanding of this signaling pathway for making therapeutic strategy. This motivated us to perform a computational study of the pathway and to identify probable drug targets. In this work, from available databases and literature, we reconstructed a complete hedgehog pathway which reports the largest number of molecules and interactions to date. Using recently developed computational techniques, we further performed structural and logical analysis of this pathway. In structural analysis, the connectivity and centrality parameters were calculated to identify the important proteins from the network. To capture the regulations of the molecules, we developed a master Boolean model of all the interactions between the proteins and created different cancer scenarios, such as Glioma, Colon and Pancreatic. We performed perturbation analysis on these cancer conditions to identify the important and minimal combinations of proteins that can be used as drug targets. From our study we observed the under expressions of various oncoproteins in Hedgehog pathway while perturbing at a time the combinations of the proteins GLI1, GLI2 and SMO in Glioma; SMO, HFU, ULK3 and RAS in Colon cancer; SMO, HFU, ULK3, RAS and ERK12 in Pancreatic cancer. This reconstructed Hedgehog signaling pathway and the computational analysis for identifying new combinatory drug targets will be useful for future in-vitro and in-vivo analysis to control different cancers.     

The RAS subfamily Evolution – tracing evolution for its utmost exploitation

In the development of multicellularity, signaling proteins has played a very important role. Among them, RAS family is one of the most widely studied protein family. However, evolutionary analysis has been carried out mainly on super family level leaving sub family information in scanty. Thus, a subfamily evolutionary study on RAS evolutionary expansion is imperative as it will aid in better drug designing against dreadful diseases like Cancer and other developmental diseases. The present study was aimed to understand RAS evolution on both holistic as well as reductive level. All human RAS family genes and protein were subjected to BLAST tools to find orthologs and paralogs with different parameters followed by phylogenetic tree generation. Our results clearly showed that H-RAS is the most primitive RAS in higher eukaryotes and then diverged into other RAS family members due to different gene modification events. Furthermore, a site specific selection pressure analysis was carried out using SELECTON server which showed that H-RAS, M-RAS and N-RAS are evolving faster than K-RAS and R-RAS. Thus, the results ascertain a new ground to cancer biologists to exploit negatively selected K-RAS and R-RAS as potent drug targets in cancer therapeutics.     

General approach to identifying potential targets for cancer imaging by integrated bioinformatics analysis of publicly available genomic profiles

Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map "focused" interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases.     

Somatic variation and cancer: therapies lost in the mix

Cancer arises as a consequence of mutations in genomes of cancer cells, which over time allow them to proliferate and spread to distant sites. Large-scale sequencing of cancer genomes is revealing an increasing number of potential driver mutations that may allow specific targeting of cancer genes, proteins, and pathways. Comprehensive views of cancer genomes are also revealing enormous heterogeneity of mutation profiles, even among tumours derived from the same organs and having similar pathological characteristics. There are now many examples where mutation profiles observed in tumours have been shown to correlate with clinical features of disease, drug response, and patient outcomes. When ignored, molecular heterogeneity can lead to failures in drug development, as drugs that may have efficacy in subgroups of patients with specific molecular phenotypes may show marginal response when tested in large groups of unselected patients. This article explores issues relevant to the clinical translation of sequence-based mutation profiles in the clinical development of targeted therapies and in the future management of cancer patients.     

Metadegradomics: toward in vivo quantitative degradomics of proteolytic post-translational modifications of the cancer proteome

Post-translational modifications enable extra layers of control of the proteome, and perhaps the most important is proteolysis, a major irreversible modification affecting every protein. The intersection of the protease web with a proteome sculpts that proteome, dynamically modifying its state and function. Protease expression is distorted in cancer, so perturbing signaling pathways and the secretome of the tumor and reactive stromal cells. Indeed many cancer biomarkers are stable proteolytic fragments. It is crucial to determine which proteases contribute to the pathology versus their roles in homeostasis and in mitigating cancer. Thus the full substrate repertoire of a protease, termed the substrate degradome, must be deciphered to define protease function and to identify drug targets. Degradomics has been used to identify many substrates of matrix metalloproteinases that are important proteases in cancer. Here we review recent degradomics technologies that allow for the broadly applicable identification and quantification of proteases (the protease degradome) and their activity state, substrates, and interactors. Quantitative proteomics using stable isotope labeling, such as ICAT, isobaric tags for relative and absolute quantification (iTRAQ), and stable isotope labeling by amino acids in cell culture (SILAC), can reveal protease substrates by taking advantage of the natural compartmentalization of membrane proteins that are shed into the extracellular space. Identifying the actual cleavage sites in a complex proteome relies on positional proteomics and utilizes selection strategies to enrich for protease-generated neo-N termini of proteins. In so doing, important functional information is generated. Finally protease substrates and interactors can be identified by interactomics based on affinity purification of protease complexes using exosite scanning and inactive catalytic domain capture strategies followed by mass spectrometry analysis. At the global level, the N terminome analysis of whole communities of proteases in tissues and organs in vivo provides a full scale understanding of the protease web and the web-sculpted proteome, so defining metadegradomics.