SRGN-Triggered Aggressive and Immunosuppressive Phenotype in a Subset of TTF-1-Negative Lung Adenocarcinomas.

BACKGROUND: Approximately 20% of lung adenocarcinoma (LUAD) is negative for the lineage-specific oncogene Thyroid transcription factor 1 (TTF-1) and exhibits worse clinical outcome with a low frequency of actionable genomic alterations. To identify molecular features associated with TTF-1-negative LUAD, we compared the transcriptomic and proteomic profiles of LUAD cell lines. SRGN , a chondroitin sulfate proteoglycan Serglycin, was identified as a markedly overexpressed gene in TTF-1-negative LUAD. We therefore investigated the roles and regulation of SRGN in TTF-1-negative LUAD. METHODS: Proteomic and metabolomic analyses of 41 LUAD cell lines were done using mass spectrometry. The function of SRGN was investigated in 3 TTF-1-negative and 4 TTF-1-positive LUAD cell lines and in a syngeneic mouse model (n = 5 to 8 mice per group). Expression of SRGN was evaluated in 94 and 105 surgically resected LUAD tumor specimens using immunohistochemistry. All statistical tests were 2-sided. RESULTS: SRGN was markedly overexpressed at mRNA and protein levels in TTF-1-negative LUAD cell lines (P < .001 for both mRNA and protein levels). Expression of SRGN in LUAD tumor tissue was associated with poor outcome (hazard ratio = 4.22, 95% confidence interval = 1.12 to 15.86, likelihood ratio test, P = .03), and with higher expression of Programmed cell death 1 ligand 1 (PD-L1) in tumor cells and higher infiltration of Programmed cell death protein 1-positive lymphocytes. SRGN regulated expression of PD-L1 as well as proinflammatory cytokines, including Interleukin-6, Interleukin-8, and C-X-C motif chemokine 1 in LUAD cell lines; increased migratory and invasive properties of LUAD cells and fibroblasts; and enhanced angiogenesis. SRGN was induced by DNA demethylation resulting from Nicotinamide N-methyltransferase-mediated impairment of methionine metabolism. CONCLUSIONS: Our findings suggest that SRGN plays a pivotal role in tumor-stromal interaction and reprogramming into an aggressive and immunosuppressive tumor microenvironment in TTF-1-negative LUAD.

Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy.

The field of artificial intelligence (AI) is experiencing a period of intense progress due to the consolidation of several key technological enablers. AI is already deployed widely and has a high impact on work and daily life activities. The continuation of this process will likely contribute to deep economic and social changes. To realise the tremendous benefits of AI while mitigating undesirable effects will require enlightened responses by many stakeholders. Varying national institutional, economic, political, and cultural conditions will influence how AI will affect convenience, efficiency, personalisation, privacy protection, and surveillance of citizens. Many expect that the winners of the AI development race will dominate the coming decades economically and geopolitically, potentially exacerbating tensions between countries. Moreover, nations are under pressure to protect their citizens and their interests-and even their own political stability-in the face of possible malicious or biased uses of AI. On the one hand, these different stressors and emphases in AI development and deployment among nations risk a fragmentation between world regions that threatens technology evolution and collaboration. On the other hand, some level of differentiation will likely enrich the global AI ecosystem in ways that stimulate innovation and introduce competitive checks and balances through the decentralisation of AI development. International cooperation, typically orchestrated by intergovernmental and non-governmental organisations, private sector initiatives, and by academic researchers, has improved common welfare and avoided undesirable outcomes in other technology areas. Because AI will most likely have more fundamental effects on our lives than other recent technologies, stronger forms of cooperation that address broader policy and governance challenges in addition to regulatory and technological issues may be needed. At a time of great challenges among nations, international policy coordination remains a necessary instrument to tackle the ethical, cultural, economic, and political repercussions of AI. We propose to advance the emerging concept of technology diplomacy to facilitate the global alignment of AI policy and governance and create a vibrant AI innovation system. We argue that the prevention of malicious uses of AI and the enhancement of human welfare create strong common interests across jurisdictions that require sustained efforts to develop better, mutually beneficial approaches. We hope that new technology diplomacy will facilitate the dialogues necessary to help all interested parties develop a shared understanding and coordinate efforts to utilise AI for the benefit of humanity, a task whose difficulty should not be underestimated.

Predictive and Prognostic Molecular Biomarkers for Response to Neoadjuvant Chemoradiation in Rectal Cancer.

The standard of care in locally advanced rectal cancer is neoadjuvant chemoradiation (nCRT) followed by radical surgery. Response to nCRT varies among patients and pathological complete response is associated with better outcome. However, there is a lack of effective methods to select rectal cancer patients who would or would not have a benefit from nCRT. The utility of clinicopathological and radiological features are limited due to lack of adequate sensitivity and specificity. Molecular biomarkers have the potential to predict response to nCRT at an early time point, but none have currently reached the clinic. Integration of diverse types of biomarkers including clinicopathological and imaging features, identification of mechanistic link to tumor biology, and rigorous validation using samples which represent disease heterogeneity, will allow to develop a sensitive and cost-effective molecular biomarker panel for precision medicine in rectal cancer. Here, we aim to review the recent advance in tissue- and blood-based molecular biomarker research and illustrate their potential in predicting nCRT response in rectal cancer.

Proteomic level changes associated with S3I201 treated U87 glioma cells.

Glioblastoma multiforme is Grade IV brain tumor associated with high mortality and limited therapeutics. Signal Transducer and Activator of Transcription 3 (STAT3) is persistently active in several cancers including gliomas, and plays a major role in disease progression and survival of glioma patients, thus being a potential therapeutic target for treatment. S3I201 and its analogs inhibit the transcriptional functions of STAT3 and reduce growth of tumor tissues. Here we have studied proteomic alteration associated with S3I201 treated U87 cells using 2-DE and Isobaric tags for relative and absolute quantitation coupled with mass spectrometry. This analysis revealed 136 differentially expressed proteins which were functionally classified with gene ontology analysis. Results showed metabolism, apoptosis, cytoskeletal behaviour, cell redox homeostasis and immune response as the most affected biological processes on S3I201 treatment. Apoptosis-inducing factor 1 mitochondrial, cyclophilin A and chloride intra-cellular channel protein 1 were found to be up-regulated which possibly contributes to its anti-tumorigenic function. Several glycolytic enzymes like phosphoglycerate mutase 1 were also found to be up-regulated and its expression was validated using immunoblot. Conclusively, our study shows the downstream effects of S3I201 in U87 glioma cells and suggests its therapeutic potential. SIGNIFICANCE: Gliomas with constitutive expression can be treated with STAT3 inhibitors. S3I201, a STAT3 inhibitor, reduces the growth of glioma cells thus could be studied further for its application as anti-glioma agent. This study investigated proteomic alteration associated with S3I201 in U87 cells using complementary proteomic approaches, and our findings suggest that S3I201 influences central metabolism, apoptosis, cytoskeletal behaviour, cell redox homeostasis and immune response as the most affected biological processes which altogether contribute to its anti-tumorigenic activity. Several proteins were identified which may serve as prognostic or predictive markers in GBM. Apoptosis-inducing factor 1 mitochondrial and cyclophilin A were identified as potential therapeutic targets and further investigations on these candidates may facilitate therapeutic development and suggests that GBM therapy can be improved by targeting cellular metabolism and by using immunotherapy.

Protein microarray applications: Autoantibody detection and posttranslational modification.

The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein-protein interactions, protein-ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

Thanatophoric Dysplasia: A Case Report.

Thanatophoric Dysplasia (TD) is a congenital, sporadic and the most lethal skeletal dysplasia caused by new mutation in the FGFR3 gene. At birth, it is characterized by shortening of the limbs (micromelia), small conical thorax, platyspondyly (flat vertebral bodies) and macrocephaly. TD is divided into two clinically defined subtypes: type I and II with some clinical overlap between the two subtypes. They can be differentiated by the skull shape and femur morphology. Ultrasound examination in the second trimester is often straight forward in diagnosing the congenital anomaly. We report a case of pre term fresh stillborn baby with dysmorphic facies, macrocephaly, micromelia with short stubby fingers and deep skin creases, narrow thorax and protuberant abdomen which delivered at our hospital. The ultrasound examination showed shortening of long bones with femur shaped like telephone receiver. Dysmorphic facial features and skeletal abnormalities in the baby lead us to make the diagnosis of TD type I. Because of the rarity of this condition we report this case of thanatophoric dysplasia with a short review of literature.

Meeting Report: "Proteomics from Discovery to Function:" 6th Annual Meeting of Proteomics Society, India and International Conference-A Milestone for the Indian Proteomics Community.

Proteomics is at the epicenter of post-genomics biotechnologies that are currently driving the next generation system science. Moreover, proteomics is a truly global science. The 6(th) Annual Meeting of Proteomics Society, India (PSI) and International Conference on "Proteomics from Discovery to Function" held from December 7-9, 2014, was a transformative endeavor for global proteomics, bringing together the luminaries in the field of proteomics for the very first time in India. This meeting report presents the lessons learned and the highlights of this international scientific conference that was comprised of nine thematic sessions, pre- and post-conference workshops, and an opportunity to cultivate enduring collaborations for proteomics science to benefit both India and global society. The conference had an unforgettable impression on the participants: for the first time, India hosted past and present President and Council members from the Human Proteome Organization (HUPO), along with eminent scientists and young scholars from India and abroad in the field of proteomics at such a large scale, a major highlight of this international event. In all, the PSI 2014 was a milestone conference that has firmly poised the Indian life sciences community as a leading contributor to post-genomics life sciences, thus cultivating crucial trans-generational capacity and inspiration by recognizing the emerging scholars and omics systems scientists who can think and conduct science from cell to society.

Quantitative proteomic analysis of global effect of LLL12 on U87 cell's proteome: An insight into the molecular mechanism of LLL12.

Glioblastoma multiforme (GBM) is one of the most devastating and dreadful WHO grade IV brain tumors associated with poor survival rate and limited therapeutics. Signal transducer and activator of transcription factor 3 (STAT3) is persistently active in several cancers, including gliomas, and STAT3 inhibitors hold great promise for treatment of glioma. LLL12, a curcumin derivative, inhibits STAT3 functions, thereby reduces growth of GBM. However, the global effects of targeting STAT3 using LLL12 have not been studied well. To shed light on this aspect, we performed quantitative proteomic analyses using differential in-gel electrophoresis (2D-DIGE) and isobaric tags for relative and absolute quantitation (iTRAQ) as well as label-free mass spectrometric analysis with 0.5µM (IC50) concentration of LLL12. Through this approach, we identified a total dataset of 1012 proteins with 1% FDR, of which 143 proteins were differentially expressed associated with various cellular functions. Results suggest that LLL12 influences central cellular metabolism and cytoskeletal proteins, in addition to its apoptosis inducing and anti-angiogenic activities, which altogether contribute to its anti-tumorigenic function. Interestingly, triose phosphate isomerase (TPI), phosphoglycerate mutase 1 (PGAM1), adaptor molecule (CRK2), protein DJ-1 (PARK7) and basic transcription factor 3 (BTF3) were found to be down-regulated and can be studied further to understand their therapeutic potential in gliomas. TPI1 and PGAM1 protein expressions were validated using immunoblot. Conclusively, our results suggest the therapeutic potential of LLL12 and it can be investigated further for a significant role in glioma treatment. BIOLOGICAL SIGNIFICANCE: LLL12 holds great promise for therapeutic development in gliomas with constitutive expression of STAT3. This study investigated the global effect of LLL12 on the proteome of U87 glioma cells using complementary proteomic approaches, and our findings suggest that LLL12 influences central metabolism, translation, transport processes, and cytoskeleton of a cell in addition to its anti-angiogenic and apoptosis inducing functions which altogether contributes to anti-tumorigenic activity of LLL12. This study leads to the identification of several proteins which may serve as prognostic or predictive markers in GBM. We identified TPI1, PGAM1, CRK and BTF3 as potential therapeutic targets and further investigations on these candidates may facilitate therapeutic development.

Ready to put metadata on the post-2015 development agenda? Linking data publications to responsible innovation and science diplomacy.

Metadata refer to descriptions about data or as some put it, "data about data." Metadata capture what happens on the backstage of science, on the trajectory from study conception, design, funding, implementation, and analysis to reporting. Definitions of metadata vary, but they can include the context information surrounding the practice of science, or data generated as one uses a technology, including transactional information about the user. As the pursuit of knowledge broadens in the 21(st) century from traditional "science of whats" (data) to include "science of hows" (metadata), we analyze the ways in which metadata serve as a catalyst for responsible and open innovation, and by extension, science diplomacy. In 2015, the United Nations Millennium Development Goals (MDGs) will formally come to an end. Therefore, we propose that metadata, as an ingredient of responsible innovation, can help achieve the Sustainable Development Goals (SDGs) on the post-2015 agenda. Such responsible innovation, as a collective learning process, has become a key component, for example, of the European Union's 80 billion Euro Horizon 2020 R&D Program from 2014-2020. Looking ahead, OMICS: A Journal of Integrative Biology, is launching an initiative for a multi-omics metadata checklist that is flexible yet comprehensive, and will enable more complete utilization of single and multi-omics data sets through data harmonization and greater visibility and accessibility. The generation of metadata that shed light on how omics research is carried out, by whom and under what circumstances, will create an "intervention space" for integration of science with its socio-technical context. This will go a long way to addressing responsible innovation for a fairer and more transparent society. If we believe in science, then such reflexive qualities and commitments attained by availability of omics metadata are preconditions for a robust and socially attuned science, which can then remain broadly respected, independent, and responsibly innovative. "In Sierra Leone, we have not too much electricity. The lights will come on once in a week, and the rest of the month, dark[ness]. So I made my own battery to power light in people's houses." Kelvin Doe (Global Minimum, 2012) MIT Visiting Young Innovator Cambridge, USA, and Sierra Leone "An important function of the (Global) R&D Observatory will be to provide support and training to build capacity in the collection and analysis of R&D flows, and how to link them to the product pipeline." World Health Organization (2013) Draft Working Paper on a Global Health R&D Observatory.

Serum proteome analysis of vivax malaria: An insight into the disease pathogenesis and host immune response.

Vivax malaria is the most widely distributed human malaria resulting in 80-300 million clinical cases every year. It causes severe infection and mortality but is generally regarded as a benign disease and has not been investigated in detail. The present study aimed to perform human serum proteome analysis in a malaria endemic area in India to identify potential serum biomarkers for vivax malaria and understand host response. The proteomic analysis was performed on 16 age and gender matched subjects (vivax patients and control) in duplicate. Protein extraction protocols were optimized for large coverage of the serum proteome and to obtain high-resolution data. Identification of 67 differentially expressed and statistically significant (Student's t-test; p<0.05) protein spots was established by MALDI-TOF/TOF mass spectrometry. Many of the identified proteins such as apolipoprotein A and E, serum amyloid A and P, haptoglobin, ceruloplasmin, and hemopexin are interesting from a diagnostic point of view and could further be studied as potential serum biomarkers. The differentially expressed serum proteins in vivax malaria identified in this study were subjected to functional pathway analysis using multiple software, including Ingenuity Pathway Analysis (IPA), Protein ANalysis THrough Evolutionary Relationships (PANTHER) and Database for Annotation, Visualization and Integrated Discovery (DAVID) functional annotation tool for better understanding of the biological context of the identified proteins, their involvement in various physiological pathways and association with disease pathogenesis. Functional pathway analysis of the differentially expressed proteins suggested the modulation of multiple vital physiological pathways, including acute phase response signaling, complement and coagulation cascades, hemostasis and vitamin D metabolism pathway due to this parasitic infection. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead.

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.