Therapeutic response in human cancers : the dual role of STAT signalling

STAT proteins were discovered as the mediators of interferon (IFN) signalling in response to viral infections. Later, it has become evident that STATs are activated by many stimuli and that they exert multifaceted effects by regulating gene transcription. Of seven members of the STAT family, my thesis dealt with STAT1, STAT2, and STAT3 and the genes regulated by transcriptional complexes containing them. STAT1 and STAT3 were believed to regulate the opposing functions, the former acting as a tumour suppressor and the latter being an oncogene. Type I IFNs have been used for the treatment of infectious diseases and some types of cancer. In Paper I, we investigated pathways involved in the IFN-induced apoptosis in a myeloma cell line, and what role the STAT1 phosphorylation plays in this model. We used chemical inhibitors of pSTAT1, Akt, mTOR, and cells with a dominant-negative mutant form of STAT1 to evaluate which pathways are essential for the pro-apoptotic effect of IFNα. We have found that pSTAT1 is important, but cooperation with other signalling pathways is necessary to maximize the pro- apoptotic effect of IFNα. In paper II, we used multicellular spheroids (3D culture) as a model to study a gene signature associated with drug resistance. We have found that STAT1, STAT2, and IRF9, as well as IFN- stimulated genes (ISGs), have increased expression in this drug resistance model. Moreover, a similar gene signature is induced in cells cultured for a prolonged time with no trace of IFN detected. The expression of ISGs was not STAT1 dependent but was controlled by STAT2 and IRF9. Overexpression of IRF9 alone was sufficient to drive the transcription of the ISGs and to induce drug resistance in the cells. Therefore, IRF9-induced gene signature can be explored as a marker for therapy response in cancer. In Paper III, we studied the role of the constitutively activated STAT3 in the sensitivity of multiple myeloma cells to the Hsp90 inhibitors treatment. We used a panel of cell lines categorised by different basal levels of the pTyr705STAT3 and of CD45 and found that the sensitivity of myeloma cells to an Hsp90 inhibitor correlated with the presence of pSTAT3. Using samples from multiple myeloma patients, we have demonstrated that it is the pSTAT3+CD45+ cell population that undergoes apoptosis in response to the Hsp90 inhibitor treatment. Thus, pSTAT3/CD45 can be used as a stratification marker for the use of these drugs. In Paper IV, we attempted to develop new inhibitors targeting STAT3. After the screening campaign, we have chosen several inhibitors that preferentially affect the viability in STAT3-dependent cell lines. The inhibitors have different effects on the phosphorylation of STAT3 and STAT1, but regardless of that, all the compounds interfere with the STAT3-driven gene transcription. One of the compounds, KI16, preferentially inhibits the phosphorylation of STAT3 over STAT1. It also docks well to the SH2-domain of STAT3 and has a potential to be developed as a STAT3-targeting drug. Other compounds act through a different mechanism(s), but are also plausible for chemical modifications and development, both as drugs and as molecular probes to identify novel targets important for the full oncogenic function of STAT3. Taken together, our findings demonstrate that the roles of STAT1 and STAT3 in cancer are not strictly determined, but are highly context-dependent. It appears that the IFN/STAT1 signalling can be both pro-apoptotic and pro-survival, whereas the oncogenic JAK/STAT3 axis can be targeted to induce cancer cell death

談話における結束性とその指導(1) : 同一物指示について

英語の話し手は，ある一節を読んだり，聞いたりすると，それがテクストを成しているか，そうでないか容易に判断することができる。このことから，テクストには，そのまとまりを保証している何らかの特徴が存在し，話し手はこれを手がかりにして判断していると考えることができる。それでは，何がテクストであり，何がテクストでないかを判断する客観的な言語的特徴とはどのようなものなのか。本稿では，英語の文章を正しく理解したり，さらに進んで英語で話をしたり，文章を書いたりするときに，まとまりのあるものにするために必要な言語的な手段を具体例を挙げて見ていくことにする。This paper presents a comparative pragmatic analysis of cohesion in English and Japanese discourse. If a speaker of English or Japanese hears or reads a passage of the language which is more than one sentence in length, the speaker usually identifies without difficulty whether it forms a text or is just a collection of fragments of sentences. This paper inquires into what makes the difference between the two with special reference to reference in the framework of Halliday and Hasan (1976)

Identification of novel small molecules that inhibit STAT3-dependent transcription and function

Activation of Signal Transducer and Activator of Transcription 3 (STAT3) has been linked to several processes that are critical for oncogenic transformation, cancer progression, cancer cell proliferation, survival, drug resistance and metastasis. Inhibition of STAT3 signaling has shown a striking ability to inhibit cancer cell growth and therefore, STAT3 has become a promising target for anti-cancer drug development. The aim of this study was to identify novel inhibitors of STAT-dependent gene transcription. A cellular reporter-based system for monitoring STAT3 transcriptional activity was developed which was suitable for high-throughput screening (Z’ = 0,8). This system was used to screen a library of 28,000 compounds (the ENAMINE Drug-Like Diversity Set). Following counter-screenings and toxicity studies, we identified four hit compounds that were subjected to detailed biological characterization. Of the four hits, KI16 stood out as the most promising compound, inhibiting STAT3 phosphorylation and transcriptional activity in response to IL6 stimulation. In silico docking studies showed that KI16 had favorable interactions with the STAT3 SH2 domain, however, no inhibitory activity could be observed in the STAT3 fluorescence polarization assay. KI16 inhibited cell viability preferentially in STAT3-dependent cell lines. Taken together, using a targeted, cell-based approach, novel inhibitors of STAT-driven transcriptional activity were discovered which are interesting leads to pursue further for the development of anti-cancer therapeutic agents

Therapeutic implications of tumor interstitial acidification

Interstitial acidification is a hallmark of solid tumor tissues resulting from the combination of different factors, including cellular buffering systems, defective tissue perfusion and high rates of cellular metabolism. Besides contributing to tumor pathogenesis and promoting tumor progression, tumor acidosis constitutes an important intrinsic and extrinsic mechanism modulating therapy sensitivity and drug resistance. In fact, pharmacological properties of anticancer drugs can be affected not only by tissue structure and organization but also by the distribution of the interstitial tumor pH. The acidic tumor environment is believed to create a chemical barrier that limits the effects and activity of many anticancer drugs. In this review article we will discuss the general protumorigenic effects of acidosis, the role of tumor acidosis in the modulation of therapeutic efficacy and potential strategies to overcome pH-dependent therapy-resistance

CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement

Background: During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature. Objectives: We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks. Methods: We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The ''Search'' interface, which displays research trends and citation links; the ''Citation Map'' interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the ''MeSH'' interface, highlighting current MeSH trends and their associations. Results: CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. Conclusion: CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research

PLK1 as a cooperating partner for BCL2-mediated antiapoptotic program in leukemia

Abstract The deregulation of BCL2 family proteins plays a crucial role in leukemia development. Therefore, pharmacological inhibition of this family of proteins is becoming a prevalent treatment method. However, due to the emergence of primary and acquired resistance, efficacy is compromised in clinical or preclinical settings. We developed a drug sensitivity prediction model utilizing a deep tabular learning algorithm for the assessment of venetoclax sensitivity in T-cell acute lymphoblastic leukemia (T-ALL) patient samples. Through analysis of predicted venetoclax-sensitive and resistant samples, PLK1 was identified as a cooperating partner for the BCL2-mediated antiapoptotic program. This finding was substantiated by additional data obtained through phosphoproteomics and high-throughput kinase screening. Concurrent treatment using venetoclax with PLK1-specific inhibitors and PLK1 knockdown demonstrated a greater therapeutic effect on T-ALL cell lines, patient-derived xenografts, and engrafted mice compared with using each treatment separately. Mechanistically, the attenuation of PLK1 enhanced BCL2 inhibitor sensitivity through upregulation of BCL2L13 and PMAIP1 expression. Collectively, these findings underscore the dependency of T-ALL on PLK1 and postulate a plausible regulatory mechanism

Characterization of the four hit compounds.

<p><b>(A-D)</b> Compounds KI1, KI4, KI12 and KI16 and their corresponding activities in the luciferase reporter assays (center) and cell viability assays (right). Luciferase assays were performed in A4wt cells stimulated with IL6 (grey) and in A4 cells stimulated with IFNγ (red). Viability assays were conducted over 48 hours in A4wt cells (grey) and A4 cells (red). <b>(E)</b> Luciferase IC₅₀ values for lead compounds. Curves were fit using GraphPad and error bars indicate the 95% confidence intervals. <b>(F)</b> Cell viability EC₅₀ values in A4 and A4wt cells using CellTiterGlo assay (Promega Biotech AB, Sweden). Curves were fit using GraphPad and error bars indicate the 95% confidence intervals.</p

Docking assays and chemical features of the lead compounds.

<p><b>(A)</b> Chemical structures of KI1 and KI4. The quinazolone core of KI1 and KI4 is also a common feature of clinically approved EGFR- and VEGFR-targeted therapeutics Gefitinib, Erlotinib and Vandetanib. The pharmacophore portion of the clinically used compounds is highlighted in blue, which is highly similar to the structures of KI1 and KI4. <b>(B)</b> STAT3 crystal structure (blue, pdb 1BG1) with residues 702–709 of the opposing monomer shown in cyan. <b>(C)</b> (Upper panel) KI12 docked into the STAT3 SH2 domain using GLIDE docking software. (Lower panel) Ligand interaction diagram showing interactions between KI12 and residues on the STAT3 SH2 domain. KI12 hydrogen bonds with Ser611, Ser613 and Glu612 and forms cation-pi type interactions with the positively charged Lys591. An additional hydrogen bond is formed with Gln635 and a salt bridge with Lys626. <b>(D)</b> (Upper panel) KI16 docked into the STAT3 SH2 domain using GLIDE docking software. (Lower panel) Ligand interaction diagram showing interactions between KI16 and residues on the STAT3 SH2 domain. KI16 makes hydrogen bonds with Ser611, Ser613 and Gln635.</p