Urine Biopsy as Dynamic Biomarker to Enhance Clinical Staging of Bladder Cancer in Radical Cystectomy Candidates.

PURPOSE: There is significant interest in identifying complete responders to neoadjuvant chemotherapy (NAC) before radical cystectomy (RC) to potentially avoid removal of a pathologically benign bladder. However, clinical restaging after NAC is highly inaccurate. The objective of this study was to develop a next-generation sequencing-based molecular assay using urine to enhance clinical staging of patients with bladder cancer. METHODS: Urine samples from 20 and 44 patients with bladder cancer undergoing RC were prospectively collected for retrospective analysis for molecular correlate analysis from two clinical trials, respectively. The first cohort was used to benchmark the assay, and the second was used to determine the performance characteristics of the test as it correlates to responder status as measured by pathologic examination. RESULTS: First, to benchmark the assay, known mutations identified in the tissue (MT) of patients from the Accelerated Methotrexate, Vinblastine, Doxorubicin, Cisplatin trial (ClinicalTrials.gov identifier: NCT01611662, n = 16) and a cohort from University of California-San Francisco (n = 4) were cross referenced against mutation profiles from urine (MU). We then determined the correlation between MU persistence and residual disease in pre-RC urine samples from a second prospective clinical trial (The pT0 trial; ClinicalTrials.gov identifier: NCT02968732). Residual MU status correlated strongly with residual disease status (pT0 trial; n = 44; P = .0092) when MU from urine supernatant and urine pellet were assessed separately and analyzed in tandem. The sensitivity, specificity, PPV, and NPV were 91%, 50%, 86%, and 63% respectively, with an overall accuracy of 82% for this second cohort. CONCLUSION: MU are representative of MT and thus can be used to enhance clinical staging of urothelial carcinoma. Urine biopsy may be used as a reliable tool that can be further developed to identify complete response to NAC in anticipation of safe RC avoidance.

Identification of Low-Complexity Domains by Compositional Signatures Reveals Class-Specific Frequencies and Functions Across the Domains of Life.

Low-complexity domains (LCDs) in proteins are typically enriched in one or two predominant amino acids. As a result, LCDs often exhibit unusual structural/biophysical tendencies and can occupy functional niches. However, for each organism, protein sequences must be compatible with intracellular biomolecules and physicochemical environment, both of which vary from organism to organism. This raises the possibility that LCDs may occupy sequence spaces in select organisms that are otherwise prohibited in most organisms. Here, we report a comprehensive survey and functional analysis of LCDs in all known reference proteomes (>21k organisms), with added focus on rare and unusual types of LCDs. LCDs were classified according to both the primary amino acid and secondary amino acid in each LCD sequence, facilitating detailed comparisons of LCD class frequencies across organisms. Examination of LCD classes at different depths (i.e., domain of life, organism, protein, and per-residue levels) reveals unique facets of LCD frequencies and functions. To our surprise, all 400 LCD classes occur in nature, although some are exceptionally rare. A number of rare classes can be defined for each domain of life, with many LCD classes appearing to be eukaryote-specific. Certain LCD classes were consistently associated with identical functions across many organisms, particularly in eukaryotes. Our analysis methods enable simultaneous, direct comparison of all LCD classes between individual organisms, resulting in a proteome-scale view of differences in LCD frequencies and functions. Together, these results highlight the remarkable diversity and functional specificity of LCDs across all known life forms.

A PAK family kinase and the Hippo/Yorkie pathway modulate WNT signaling to functionally integrate body axes during regeneration.

Successful regeneration of missing tissues requires seamless integration of positional information along the body axes. Planarians, which regenerate from almost any injury, use conserved, developmentally important signaling pathways to pattern the body axes. However, the molecular mechanisms which facilitate cross talk between these signaling pathways to integrate positional information remain poorly understood. Here, we report a p21-activated kinase (smed-pak1) which functionally integrates the anterior-posterior (AP) and the medio-lateral (ML) axes. pak1 inhibits WNT/ß-catenin signaling along the AP axis and, functions synergistically with the ß-catenin-independent WNT signaling of the ML axis. Furthermore, this functional integration is dependent on warts and merlin-the components of the Hippo/Yorkie (YKI) pathway. Hippo/YKI pathway is a critical regulator of body size in flies and mice, but our data suggest the pathway regulates body axes patterning in planarians. Our study provides a signaling network integrating positional information which can mediate coordinated growth and patterning during planarian regeneration.

Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.

Efforts to develop an individualized treatment rule (ITR) to optimize major depressive disorder (MDD) treatment with antidepressant medication (ADM), psychotherapy, or combined ADM-psychotherapy have been hampered by small samples, small predictor sets, and suboptimal analysis methods. Analyses of large administrative databases designed to approximate experiments followed iteratively by pragmatic trials hold promise for resolving these problems. The current report presents a proof-of-concept study using electronic health records (EHR) of n = 43,470 outpatients beginning MDD treatment in Veterans Health Administration Primary Care Mental Health Integration (PC-MHI) clinics, which offer access not only to ADMs but also psychotherapy and combined ADM-psychotherapy. EHR and geospatial databases were used to generate an extensive baseline predictor set (5,865 variables). The outcome was a composite measure of at least one serious negative event (suicide attempt, psychiatric emergency department visit, psychiatric hospitalization, suicide death) over the next 12 months. Best-practices methods were used to adjust for nonrandom treatment assignment and to estimate a preliminary ITR in a 70% training sample and to evaluate the ITR in the 30% test sample. Statistically significant aggregate variation was found in overall probability of the outcome related to baseline predictors (AU-ROC = 0.68, S.E. = 0.01), with test sample outcome prevalence of 32.6% among the 5% of patients having highest predicted risk compared to 7.1% in the remainder of the test sample. The ITR found that psychotherapy-only was the optimal treatment for 56.0% of patients (roughly 20% lower risk of the outcome than if receiving one of the other treatments) and that treatment type was unrelated to outcome risk among other patients. Change in aggregate treatment costs of implementing this ITR would be negligible, as 16.1% fewer patients would be prescribed ADMs and 2.9% more would receive psychotherapy. A pragmatic trial would be needed to confirm the accuracy of the ITR.

Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors: A Precision Treatment Analysis.

Importance: Psychiatric hospitalization is the standard of care for patients presenting to an emergency department (ED) or urgent care (UC) with high suicide risk. However, the effect of hospitalization in reducing subsequent suicidal behaviors is poorly understood and likely heterogeneous. Objectives: To estimate the association of psychiatric hospitalization with subsequent suicidal behaviors using observational data and develop a preliminary predictive analytics individualized treatment rule accounting for heterogeneity in this association across patients. Design, Setting, and Participants: A machine learning analysis of retrospective data was conducted. All veterans presenting with suicidal ideation (SI) or suicide attempt (SA) from January 1, 2010, to December 31, 2015, were included. Data were analyzed from September 1, 2022, to March 10, 2023. Subgroups were defined by primary psychiatric diagnosis (nonaffective psychosis, bipolar disorder, major depressive disorder, and other) and suicidality (SI only, SA in past 2-7 days, and SA in past day). Models were trained in 70.0% of the training samples and tested in the remaining 30.0%. Exposures: Psychiatric hospitalization vs nonhospitalization. Main Outcomes and Measures: Fatal and nonfatal SAs within 12 months of ED/UC visits were identified in administrative records and the National Death Index. Baseline covariates were drawn from electronic health records and geospatial databases. Results: Of 196 610 visits (90.3% men; median [IQR] age, 53 [41-59] years), 71.5% resulted in hospitalization. The 12-month SA risk was 11.9% with hospitalization and 12.0% with nonhospitalization (difference, -0.1%; 95% CI, -0.4% to 0.2%). In patients with SI only or SA in the past 2 to 7 days, most hospitalization was not associated with subsequent SAs. For patients with SA in the past day, hospitalization was associated with risk reductions ranging from -6.9% to -9.6% across diagnoses. Accounting for heterogeneity, hospitalization was associated with reduced risk of subsequent SAs in 28.1% of the patients and increased risk in 24.0%. An individualized treatment rule based on these associations may reduce SAs by 16.0% and hospitalizations by 13.0% compared with current rates. Conclusions and Relevance: The findings of this study suggest that psychiatric hospitalization is associated with reduced average SA risk in the immediate aftermath of an SA but not after other recent SAs or SI only. Substantial heterogeneity exists in these associations across patients. An individualized treatment rule accounting for this heterogeneity could both reduce SAs and avert hospitalizations.

Development of a model to predict antidepressant treatment response for depression among Veterans.

BACKGROUND: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. RESULTS: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. CONCLUSIONS: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

Phase II Randomized Trial of Carboplatin, Pemetrexed, and Bevacizumab With and Without Atezolizumab in Stage IV Nonsquamous Non-Small-Cell Lung Cancer Patients Who Harbor a Sensitizing EGFR Mutation or Have Never Smoked.

INTRODUCTION: Patients with non-small-cell lung cancer (NSCLC) who have never smoked or have tumors with mutations in EGFR generally derive minimal benefit from single-agent PD-1/PD-L1 checkpoint inhibitors. Prior data indicate that adding PD-L1 inhibition to anti-VEGF and cytotoxic chemotherapy may be a promising approach to overcoming immunotherapy resistance in these patients, however prospective validation is needed. This trial in progress (NCT03786692) is evaluating patients with stage IV NSCLC who have never smoked or who have tumors with sensitizing EGFR alterations to determine if a 4-drug combination of atezolizumab, carboplatin, pemetrexed, and bevacizumab can improve outcomes compared to carboplatin, pemetrexed and bevacizumab without atezolizumab. METHODS: This is a randomized, phase II, multicenter study evaluating carboplatin, pemetrexed, bevacizumab with and without atezolizumab in 117 patients with stage IV nonsquamous NSCLC. Randomization is 2 to 1 favoring the atezolizumab containing arm. Eligible patients include: 1) those with tumors with sensitizing EGFR alterations in exons 19 or 21 or 2) patients who have never smoked and have wild-type tumors (ie, no EGFR, ALK or ROS1 alterations). Patients are defined as having never smoked if they have smoked less than 100 cigarettes in a lifetime. Patients with EGFR-mutated tumors must have disease progression or intolerance to prior tyrosine kinase inhibitor (TKI) therapy. The primary endpoint is progression-free survival (PFS). Secondary endpoints include overall survival (OS), response rate, duration of response, and time to response. CONCLUSION: This phase II trial is accruing patients at U.S. sites through the National Comprehensive Cancer Network (NCCN). The trial opened in August 2019 and accrual is expected to be completed in the Fall of 2024.

Exogenous interleukin-1 beta stimulation regulates equine tenocyte function and gene expression in three-dimensional culture which can be rescued by pharmacological inhibition of interleukin 1 receptor, but not nuclear factor kappa B, signaling.

We investigated how Interleukin 1 beta (IL-1ß) impacts equine tenocyte function and global gene expression in vitro and determined if these effects could be rescued by pharmacologically inhibiting nuclear factor-κB (NF-KB) or interleukin 1 signalling. Equine superficial digital flexor tenocytes were cultured in three-dimensional (3D) collagen gels and stimulated with IL-1ß for two-weeks, with gel contraction and interleukin 6 (IL6) measured throughout and transcriptomic analysis performed at day 14. The impact of three NF-KB inhibitors on gel contraction and IL6 secretion were measured in 3D culture, with NF-KB-P65 nuclear translocation by immunofluorescence and gene expression by qPCR measured in two-dimensional (2D) monolayer culture. In addition, daily 3D gel contraction and transcriptomic analysis was performed on interleukin 1 receptor antagonist-treated 3D gels at day 14. IL-1ß increased NF-KB-P65 nuclear translocation in 2D culture and IL6 secretion in 3D culture, but reduced daily tenocyte 3D gel contraction and impacted > 2500 genes at day 14, with enrichment for NF-KB signaling. Administering direct pharmacological inhibitors of NF-KB did reduce NF-KB-P65 nuclear translocation, but had no effect on 3D gel contraction or IL6 secretion in the presence of IL-1ß. However, IL1Ra restored 3D gel contraction and partially rescued global gene expression. Tenocyte 3D gel contraction and gene expression is adversely impacted by IL-1ß which can only be rescued by blockade of interleukin 1 receptor, but not NF-KB, signalling.

The Impact of an Electromagnetic Seed Localization Device Versus Wire Localization on Breast-Conserving Surgery: A Matched-Pair Analysis.

BACKGROUND: For breast-conserving surgery (BCS), several alternatives to wire localization (WL) have been developed. The newest, electromagnetic seed localization (ESL), provides three-dimensional navigation using the electrosurgical tool. This study assessed operative times, specimen volumes, margin positivity, and re-excision rates for ESL and WL. METHODS: Patients who had ESL-guided breast-conserving surgery between August 2020 and August 2021 were reviewed and matched one-to-one with patients who had WL based on surgeon, procedure type, and pathology. Variables were compared between ESL and WL using Wilcoxon rank-sum and Fisher's exact tests. RESULTS: The study matched 97 patients who underwent excisional biopsy (n = 20) or partial mastectomy with (n = 53) or without (n = 24) sentinel lymph node biopsy (SLNB) using ESL. The median operative time for ESL versus WL for lumpectomy was 66 versus 69 min with SLNB (p = 0.76) and 40 versus 34.5 min without SLNB (p = 0.17). The median specimen volume was 36 cm3 using ESL versus 55 cm3 using WL (p = 0.001). For the patients with measurable tumor volume, excess tissue was greater using WL versus ESL (median, 73.2 vs. 52.5 cm3; p = 0.017). The margins were positive for 10 (10 %) of the 97 ESL patients and 18 (19 %) of the 97 WL patients (p = 0.17). In the ESL group, 6 (6 %) of the 97 patients had a subsequent re-excision compared with 13 (13 %) of the 97 WL patients (p = 0.15). CONCLUSIONS: Despite similar operative times, ESL is superior to WL, as evidenced by decreased specimen volume and excess tissue excised. Although the difference was not statistically significant, ESL resulted in fewer positive margins and re-excisions than WL. Further studies are needed to confirm that ESL is the most advantageous of the two methods.

Pluripotency retention and exogenous mRNA introduction in planarian stem cells in culture.

Planarians possess naturally occurring pluripotent adult somatic stem cells (neoblasts) required for homeostasis and whole-body regeneration. However, no reliable neoblast culture methods are currently available, hindering mechanistic studies of pluripotency and the development of transgenic tools. We report robust methods for neoblast culture and delivery of exogenous mRNAs. We identify optimal culture media for the short-term maintenance of neoblasts in vitro and show via transplantation that cultured stem cells retain pluripotency for two days. We developed a procedure that significantly improves neoblast yield and purity by modifying standard flow cytometry methods. These methods enable the introduction and expression of exogenous mRNAs in neoblasts, overcoming a key hurdle impeding the application of transgenics in planarians. The advances in cell culture reported here create new opportunities for mechanistic studies of planarian adult stem cell pluripotency, and provide a systematic framework to develop cell culture techniques in other emerging research organisms.

A Phase II Trial of Guadecitabine plus Atezolizumab in Metastatic Urothelial Carcinoma Progressing after Initial Immune Checkpoint Inhibitor Therapy.

PURPOSE: On the basis of preclinical evidence of epigenetic contribution to sensitivity and resistance to immune checkpoint inhibitors (ICI), we hypothesized that guadecitabine (hypomethylating agent) and atezolizumab [anti-programmed cell death ligand 1 (PD-L1)] together would potentiate a clinical response in patients with metastatic urothelial carcinoma (UC) unresponsive to initial immune checkpoint blockade therapy. PATIENTS AND METHODS: We designed a single arm phase II study (NCT03179943) with a safety run-in to identify the recommended phase II dose of the combination therapy of guadecitabine and atezolizumab. Patients with recurrent/advanced UC who had previously progressed on ICI therapy with programmed cell death protein 1 or PD-L1 targeting agents were eligible. Preplanned correlative analysis was performed to characterize peripheral immune dynamics and global DNA methylation, transcriptome, and immune infiltration dynamics of patient tumors. RESULTS: Safety run-in enrolled 6 patients and phase II enrolled 15 patients before the trial was closed for futility. No dose-limiting toxicity was observed. Four patients, with best response of stable disease (SD), exhibited extended tumor control (8-11 months) and survival (>14 months). Correlative analysis revealed lack of DNA demethylation in tumors after 2 cycles of treatment. Increased peripheral immune activation and immune infiltration in tumors after treatment correlated with progression-free survival and SD. Furthermore, high IL6 and IL8 levels in the patients' plasma was associated with short survival. CONCLUSIONS: No RECIST responses were observed after combination therapy in this trial. Although we could not detect the anticipated tumor-intrinsic effects of guadecitabine, the addition of hypomethylating agent to ICI therapy induced immune activation in a few patients, which associated with longer patient survival.

Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans.

BACKGROUND: Although research shows that more depressed patients respond to combined antidepressants (ADM) and psychotherapy than either alone, many patients do not respond even to combined treatment. A reliable prediction model for this could help treatment decision-making. We attempted to create such a model using machine learning methods among patients in the US Veterans Health Administration (VHA). METHODS: A 2018-2020 national sample of VHA patients beginning combined depression treatment completed self-report assessments at baseline and 3 months (n = 658). A learning model was developed using baseline self-report, administrative, and geospatial data to predict 3-month treatment response defined by reductions in the Quick Inventory of Depression Symptomatology Self-Report and/or in the Sheehan Disability Scale. The model was developed in a 70 % training sample and tested in the remaining 30 % test sample. RESULTS: 30.0 % of patients responded to treatment. The prediction model had a test sample AUC-ROC of 0.657. A strong gradient was found in probability of treatment response from 52.7 % in the highest predicted quintile to 14.4 % in the lowest predicted quintile. The most important predictors were episode characteristics (symptoms, comorbidities, history), personality/psychological resilience, recent stressors, and treatment characteristics. LIMITATIONS: Restrictions in sample definition, a low recruitment rate, and reliance on patient self-report rather than clinician assessments to determine treatment response limited the generalizability of results. CONCLUSIONS: A machine learning model could help depressed patients and providers predict likely response to combined ADM-psychotherapy. Parallel information about potential harms and costs of alternative treatments would be needed, though, to inform optimal treatment selection.

Development of a model to predict psychotherapy response for depression among Veterans.

BACKGROUND: Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. METHODS: This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018-2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. RESULTS: 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. CONCLUSIONS: Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

Real-world progression-free survival (rwPFS) and the impact of PD-L1 and smoking in driver-mutated non-small cell lung cancer (NSCLC) treated with immunotherapy.

PURPOSE: Prior data suggest driver-mutated NSCLC, especially EGFR and ALK tumors, poorly respond to immunotherapy. However, little research using real-world cohorts have been performed, nor is it clear whether PD-L1 and smoking history are predictive of outcomes in such tumors. This study assessed rwPFS in a large cohort with driver-mutated advanced NSCLC treated with single-agent PD-1/PDL-1 inhibitors. METHODS: Real-world data from 1746 patients were analyzed and rwPFS with immunotherapy was determined for EGFR, ALK, BRAF, and KRAS tumors. Kaplan-Meier curves characterized rwPFS and correlated with PD-L1 and smoking history. Comparisons were tested using log-rank. RESULTS: Median rwPFS and the percent progression-free at 12 months were greater among KRAS (3.3 months, 21.1%) and BRAF (3.6 months, 20.6%) as compared to EGFR (2.5 months, 8.1%) and ALK tumors (2.3 months, 11.2%). KRAS tumors with PD-L1 ≥ 1% had longer rwPFS than PD-L1 < 1% tumors (4.1 versus 3.2 months, p = 0.001). PD-L1 positivity did not predict rwPFS in EGFR, ALK, or BRAF tumors. However, a smoking history was associated with longer rwPFS in EGFR (2.6 versus 2.3 months, p = 0.048) and ALK tumors (3.0 versus 2.1 months, p = 0.049) as compared to no smoking history. CONCLUSION: Real-world PFS with immunotherapy was greater in KRAS and BRAF as compared to EGFR and ALK tumors. PD-L1 positivity was predictive in KRAS and not associated with rwPFS in other mutation types. While median rwPFS was short for EGFR and ALK tumors, small subsets were progression-free at 12 months. Better characterizing these subsets that benefit, along with developing strategies to overcome immunotherapy resistance in EGFR/ALK tumors are needed.

Robotic bronchoscopic needle-based confocal laser endomicroscopy to diagnose peripheral lung nodules.

BACKGROUND AND OBJECTIVE: Robotic bronchoscopy has demonstrated high navigational success in small peripheral lung nodules but the diagnostic yield is discrepantly lower. Needle based confocal laser endomicroscopy (nCLE) enables real-time microscopic imaging at the needle tip. We aim to assess feasibility, safety and needle repositioning based on real-time nCLE-guidance during robotic bronchoscopy in small peripheral lung nodules. METHODS: Patients with suspected peripheral lung cancer underwent fluoroscopy and radial EBUS assisted robotic bronchoscopy. After radial EBUS nodule identification, nCLE-imaging of the target area was performed. nCLE-malignancy and airway/lung parenchyma criteria were used to identify the optimal sampling location. In case airway was visualized, repositioning of the biopsy needle was performed. After nCLE tool-in-nodule confirmation, needle passes and biopsies were performed at the same location. MEASUREMENTS AND MAIN RESULTS: Twenty patients were included (final diagnosis n = 17 (lung) cancer) with a median lung nodule size of 14.5 mm (range 8-28 mm). No complications occurred. In 19/20 patients, good quality nCLE-videos were obtained. In 9 patients (45%), real-time nCLE-imaging revealed inadequate positioning of the needle and repositioning was performed. After repositioning, nCLE-imaging provided tool-in-nodule-confirmation in 19/20 patients. Subsequent ROSE demonstrated representative material in 9/20 patients (45%) and overall diagnostic yield was 80% (16/20). Of the three patients with malignant nCLE-imaging but inadequate pathology, two were diagnosed with malignancy during follow-up. CONCLUSION: Robotic bronchoscopic nCLE-imaging is feasible and safe. nCLE-imaging in small, difficult-to-access lung nodules provided additional real-time feedback on the correct needle positioning with the potential to optimize the sampling location and diagnostic yield.

ONC201/TIC10 plus TLY012 anti-cancer effects via apoptosis inhibitor downregulation, stimulation of integrated stress response and death receptor DR5 in gastric adenocarcinoma.

Gastric adenocarcinoma typically presents with advanced stage when inoperable. Chemotherapy options include non-targeted and toxic agents, leading to poor 5-year patient survival outcomes. Small molecule ONC201/TIC10 (TRAIL-Inducing Compound #10) induces cancer cell death via ClpP-dependent activation of the integrated stress response (ISR) and up-regulation of the TRAIL pathway. We previously found in breast cancer, pancreatic cancer and endometrial cancer that ONC201 primes tumor cells for TRAIL-mediated cell death through ISR-dependent upregulation of ATF4, CHOP and TRAIL death receptor DR5. We investigated the ability of ONC201 to induce apoptosis in gastric adenocarcinoma cells in combination with recombinant human TRAIL (rhTRAIL) or PEGylated trimeric TRAIL (TLY012). AGS (caspase 8-, KRAS-, PIK3CA-mutant, HER2-amplified), SNU-1 (KRAS-, MLH1-mutant, microsatellite unstable), SNU-5 (p53-mutant) and SNU-16 (p53-mutant) gastric adenocarcinoma cells were treated with ONC201 and TRAIL both in cell culture and in vivo. Gastric cancer cells showed synergy following dual therapy with ONC201 and rhTRAIL/TLY012 (combination indices < 0.6 at doses that were non-toxic towards normal fibroblasts). Synergy was observed with increased cells in the sub-G1 phase of the cell cycle with dual ONC201 plus TRAIL therapy. Increased PARP, caspase 8 and caspase 3 cleavage after ONC201 plus TRAIL further documented apoptosis. Increased cell surface expression of DR5 with ONC201 therapy was observed by flow cytometry, and immunoblotting revealed ONC201 upregulation of the ISR, ATF4, and CHOP. We observed downregulation of anti-apoptotic cIAP-1 and XIAP in all cells except AGS, and cFLIP in all cells except SNU-16. We tested the regimen in an organoid model of human gastric cancer, and in murine sub-cutaneous xenografts using AGS and SNU-1 cells. Our results suggest that ONC201 in combination with TRAIL may be an effective and non-toxic option for the treatment of gastric adenocarcinoma by inducing apoptosis via activation of the ISR, increased cell surface expression of DR5 and down-regulation of inhibitors of apoptosis. Our results demonstrate in vivo anti-tumor effects of ONC201 plus TLY012 against gastric cancer that could be further investigated in clinical trials.

Inflammation as a chemoprevention target in asbestos-induced malignant mesothelioma.

Malignant mesothelioma (MM) is an incurable cancer of the serosal lining that is often caused by exposure to asbestos. Therefore, novel agents for the prevention and treatment of this disease are urgently needed. Asbestos induces the release of pro-inflammatory cytokines such as IL-1ß and IL-6, which play a role in MM development. IL-6 is a component of the JAK-STAT3 pathway that contributes to inflammation-associated tumorigenesis. Glycoprotein 130 (gp130), the signal transducer of this signaling axis, is an attractive drug target because of its role in promoting neoplasia via the activation of downstream STAT3 signaling. The anticancer drug, SC144, inhibits the interaction of gp130 with the IL-6 receptor (IL6R), effectively blunting signaling from this inflammatory axis. To test whether the inflammation-related release of IL-6 plays a role in the formation of MM, we evaluated the ability of SC144 to inhibit asbestos-induced carcinogenesis in a mouse model. The ability of sulindac and anakinra, an IL6R antagonist/positive control, to inhibit MM formation in this model was tested in parallel. Asbestos-exposed Nf2+/-;Cdkn2a+/- mice treated with SC144, sulindac or anakinra showed significantly prolonged survival compared to asbestos-exposed vehicle-treated mice. STAT3 activity was markedly decreased in MM specimens from SC144-treated mice. Furthermore, SC144 inhibited STAT3 activation by IL-6 in cultured normal mesothelial cells, and in vitro treatment of MM cells with SC144 markedly decreased the expression of STAT3 target genes. The emerging availability of newer, more potent SC144 analogs showing improved pharmacokinetic properties holds promise for future trials, benefitting individuals at high risk of this disease.

The LCD-Composer webserver: high-specificity identification and functional analysis of low-complexity domains in proteins.

SUMMARY: Low-complexity domains (LCDs) in proteins are regions enriched in a small subset of amino acids. LCDs exist in all domains of life, often have unusual biophysical behavior, and function in both normal and pathological processes. We recently developed an algorithm to identify LCDs based predominantly on amino acid composition thresholds. Here, we have integrated this algorithm with a webserver and augmented it with additional analysis options. Specifically, users can (i) search for LCDs in whole proteomes by setting minimum composition thresholds for individual or grouped amino acids, (ii) submit a known LCD sequence to search for similar LCDs, (iii) search for and plot LCDs within a single protein, (iv) statistically test for enrichment of LCDs within a user-provided protein set and (v) specifically identify proteins with multiple types of LCDs. AVAILABILITY AND IMPLEMENTATION: The LCD-Composer server can be accessed at http://lcd-composer.bmb.colostate.edu. The corresponding command-line scripts can be accessed at https://github.com/RossLabCSU/LCD-Composer/tree/master/WebserverScripts.