Patient Selection For Clinical Trials Research Articles

Obstruktive Schlafapnoe: Modell zur Vorhersage des Loop Gains aus polysomnographischen Routinedaten

<b>Background:</b> High loop gain (unstable ventilatory control) is an important – but difficult to measure – contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain. <b>Methods:</b> A retrospective cohort of consecutive adults with OSA (apnea–hypopnea index, AHI > 5/hour) based on in-laboratory polysomnography 01/2017–12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm («reference standard») loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high > 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set. <b>Results:</b> The total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P < .001) and lower hypopnea-percentage (beta = -0.0019; P < .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38–0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67–0.80). <b>Conclusion:</b> To our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.

A simple additive staging system for newly diagnosed multiple myeloma

Risk stratification in multiple myeloma is important for prognostication, patient selection for clinical trials, and comparison of treatment approaches. We developed and validated a staging system that incorporates additional FISH abnormalities not included in the R-ISS and reflects the additive effects of co-occurring high-risk disease features. We first evaluated the prognostic value of predefined cytogenetic and laboratory abnormalities in 2556 Mayo Clinic patients diagnosed between February 2004 and June 2019. We then used data from 1327 patients to develop a risk stratification model and validated this in 502 patients enrolled in the MMRF CoMMpass study. On multivariate analysis, high-risk IgH translocations [risk ratio (RR): 1.7], 1q gain/amplification (RR: 1.4), chromosome17 abnormalities (RR: 1.6), ISS III (RR: 1.7), and elevated LDH (RR: 1.3) were independently associated with decreased overall survival (OS). Among 1327 evaluable patients, OS was 11.0 (95% CI: 9.2–12.6), 7.0 (95% CI: 6.3–9.2), and 4.5 (95% CI: 3.7–5.2) years in patients with 0 (stage I), 1 (stage II), and ≥2 (stage III) high-risk factors, respectively. In the MMRF cohort, median OS was 7.8 (95% CI: NR-NR), 6.0 (95% CI: 5.7-NR), and 4.3 (95% CI: 2.7-NR) years in the 3 groups, respectively (P < 0.001). This 5-factor, 3-tier system is easy to implement in practice and improves upon the current R-ISS.

Stratifying patients for polypharmacy interventions: The case for a new biomarker?

Stratifying patients for polypharmacy interventions: The case for a new biomarker?

The Significance of MET Expression and Strategies of Targeting MET Treatment in Advanced Gastric Cancer.

BackgroundAccurate assessment of predictive biomarker expression is critical in patient selection in clinical trials or clinical practice. However, changes in biomarker expression may occur after treatment. The aim of the present study was to evaluate the effects of chemotherapy on MET expression in gastric cancer (GC).MethodsMET expression was examined immunohistochemically before and after treatment in 122 patients with unresectable or recurrent GC, and was evaluated according to H-score or the scoring criteria used in the MetMAb trial. MET gene amplification was assessed by chromogenic in situ hybridization (CISH). The antitumor effect of MET targeted therapy was investigated in human gastric cancer cells in vitro and in vivo, and the underlying molecular mechanisms were analyzed by western blot.ResultsMET expression was associated with Lauren classification as well as tumor differentiation by either scoring system. MET amplification was not associated with clinical characteristics. Of the 71 patients who had paired pre- and post-treatment tumor tissues, 28 patients (39%) were initially positive for MET expression, and 43 (61%) were negative. Twenty-five patients (35%) showed significant changes in MET expression after treatment (P=0.007). Additionally, there was a concomitant overexpression of MET and HER2 in a subset of GC patients. MET inhibitor volitinib could significantly inhibit cell proliferation and xenograft growth in vitro and in vivo in MKN45 cells with MET and phosphorylated MET (pMET) high expressions via suppressing downstream PI3K/Akt and MAPK signaling pathways. Furthermore, combination therapy targeting both MET and HER2 demonstrated a synergistic antitumor activity.ConclusionsMET expression is altered post chemotherapy and MET status should be evaluated in real-time. Both MET and pMET expressions might need to be considered for patients suitable for volitinib treatment.

Do Ahlbäck scores identify subgroups with different magnitudes of cartilage thickness loss in patients with moderate to severe radiographic osteoarthritis? One-year follow-up data from the Osteoarthritis Initiative.

Kellgren-Lawrence grades (KLG) are frequently used for patient selection in clinical trials. The Ahlbäck radiographic grading system has been developed for moderate and severe knee OA. KLG 3 is comparable to Ahlbäck 1 and KLG 4 is subdivided into Ahlbäck 2-5. The objective of this study was to investigate if the Ahlbäck scoring system is able to subdivide patients with moderate to severe knee OA (KLG 3/4) into groups with different sensitivity to change in cartilage thickness. This study was based on 108 Osteoarthritis Initiative (OAI) participants with KLG 3/4. Baseline KLG scores were available from the OAI database; Ahlbäck scores were performed using the same x-rays. Cartilage thickness change in the weight-bearing femorotibial cartilage was analysed from baseline and year 1 3D FLASH MRI for the entire femorotibial joint (FTJ), the medial (MFTC) and the lateral compartment (LFTC) and for the location-independent ordered values 1 and 16 (OV 1/OV 16) representing the subregions with largest loss (OV 1) and gain (OV 16) within each knee. Of the 108 patients, n = 30/78 had KLG 3/4. The corresponding Ahlbäck scores (1-5) were n = 30/33/36/9/10. Cartilage thickness changes between Ahlbäck groups showed no statistically significant difference for FTJ, MFTC, LFTC and OV 1, but change in OV 16 was significantly higher in Ahlbäck 4 knees (p = 0.03) compared to Ahlbäck 1-3 knees. Radiographic knee OA grading with Ahlbäck scores was not superior to KLG for prediction of cartilage thickness loss over 1year, in patients with moderate and severe knee OA supporting the continuous use of the easier and more widely used KLG.

Abstract 2218: MET alterations are enriched in lung adenocarcinoma brain metastases and define a distinct molecular and transcriptomic subtype

Abstract Lung cancer has the highest incidence of metastases to the brain, with up to 40% of non-small cell lung cancer (NSCLC) patients developing brain metastases (BM). There is a critical need to develop novel treatments to effectively prevent and treat NSCLC BM. MET is a receptor tyrosine kinase that upon binding hepatocyte growth factor (HGF), mediates proliferation, epithelial-mesenchymal transition (EMT), invasion, angiogenesis and metastasis. Recent studies have suggested that the MET pathway may be a significant determinant of metastatic potential to the brain. We evaluated 125 lung adenocarcinoma (LUAD) BM and 477 primary LUAD for MET amplification (amp) by FISH (MET/CEP &amp;gt; 2) as well as other molecular alterations using targeted next-generation sequencing in a subset of LUAD BM (N=74) and primary LUAD (N=171) samples, including 13 paired primary and brain sets. We identified a significant enrichment of MET amp in LUAD BM (19%) compared to primary LUAD (3%; p&amp;lt;0.00001) or liver metastases (4%, N=80; p=0.002). High MET amp (MET/CEP7 ratio &amp;gt;5) was present in 6.5% of BM compared to 1.3% of primary LUAD cases (p=0.0006). In matched samples, BM-specific MET amp was observed. Non-exon 14 skipping MET activating mutations were also significantly more frequent in LUAD BM (22%) compared to primary LUAD (12%; p=0.05), as well as TP53, KRAS, SMAD4, APC, RB1, RET, ABL1, ALK, and VHL variants (adj. p values &amp;lt;0.02). VHL and IDH1 mutations were significantly increased in MET altered compared to non-MET altered BM. In addition, KRAS Q61X variants were more common in LUAD BM compared to LUAD and specifically more common in MET amp BM. We also examined MET activation in paired tumors using an HGF-MET proximity binding, dual-antibody assay. MET expression was increased in the majority of BM compared to the paired LUAD, and there were brain-specific MET activation was observed. RNASeq analysis identified distinct gene signatures in MET amplified (N=11) versus non-MET amplified (N=24) LUAD BM, including upregulation of the EMT and glycolytic pathways. We validated the importance of the EMT transcription factor, TWIST1 in MET-driven NSCLC tumorigenesis preclinically and confirmed activation of the glycolytic pathway in MET amplified NSCLC. Finally, non-invasive strategies to detect brain-specific MET alterations will be needed to identify BM patients who can benefit from MET inhibitors. Therefore, we examined 277 metastatic NSCLC patients that underwent standard of care circulating tumor DNA testing with the Guardant360 platform, and found that both MET mutation and/or amp were more frequently detected in LUAD patients with BM (p=0.04). Together, we show that over a third of LUAD BM patients have MET alterations compared to primary LUAD and may be responsive to MET inhibitors. Further, our liquid biopsy approach may allow us to identify BM-specific alterations for patient selection in clinical trials. Citation Format: Timothy F. Burns, Sanja Dacic, Maria A. Velez, Ashwin Somasundaram, Saveri Bhattacharya, Anish Chakka, Zachary A. Yochum, Jingxiao Jin, Ethan Miller, Brenda F. Kurland, Riyue Bao, Danielle P. Normolle, Sameer Agnihotri, Uma R. Chandran, Laura P. Stabile. MET alterations are enriched in lung adenocarcinoma brain metastases and define a distinct molecular and transcriptomic subtype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2218.

Real-World and Clinical Trial Data in Relapsed/Refractory Multiple Myeloma (RRMM): Evaluating Treatment Duration and Comparing Effectiveness and Efficacy

Real-World and Clinical Trial Data in Relapsed/Refractory Multiple Myeloma (RRMM): Evaluating Treatment Duration and Comparing Effectiveness and Efficacy

Explainable AI enables clinical trial patient selection to retrospectively improve treatment effects in schizophrenia

BackgroundHeterogeneity among patients’ responses to treatment is prevalent in psychiatric disorders. Personalized medicine approaches—which involve parsing patients into subgroups better indicated for a particular treatment—could therefore improve patient outcomes and serve as a powerful tool in patient selection within clinical trials. Machine learning approaches can identify patient subgroups but are often not “explainable” due to the use of complex algorithms that do not mirror clinicians’ natural decision-making processes.MethodsHere we combine two analytical approaches—Personalized Advantage Index and Bayesian Rule Lists—to identify paliperidone-indicated schizophrenia patients in a way that emphasizes model explainability. We apply these approaches retrospectively to randomized, placebo-controlled clinical trial data to identify a paliperidone-indicated subgroup of schizophrenia patients who demonstrate a larger treatment effect (outcome on treatment superior than on placebo) than that of the full randomized sample as assessed with Cohen’s d. For this study, the outcome corresponded to a reduction in the Positive and Negative Syndrome Scale (PANSS) total score which measures positive (e.g., hallucinations, delusions), negative (e.g., blunted affect, emotional withdrawal), and general psychopathological (e.g., disturbance of volition, uncooperativeness) symptoms in schizophrenia.ResultsUsing our combined explainable AI approach to identify a subgroup more responsive to paliperidone than placebo, the treatment effect increased significantly over that of the full sample (p < 0.0001 for a one-sample t-test comparing the full sample Cohen’s d = 0.82 and a generated distribution of subgroup Cohen’s d’s with mean d = 1.22, std d = 0.09). In addition, our modeling approach produces simple logical statements (if–then-else), termed a “rule list”, to ease interpretability for clinicians. A majority of the rule lists generated from cross-validation found two general psychopathology symptoms, disturbance of volition and uncooperativeness, to predict membership in the paliperidone-indicated subgroup.ConclusionsThese results help to technically validate our explainable AI approach to patient selection for a clinical trial by identifying a subgroup with an improved treatment effect. With these data, the explainable rule lists also suggest that paliperidone may provide an improved therapeutic benefit for the treatment of schizophrenia patients with either of the symptoms of high disturbance of volition or high uncooperativeness.Trial Registration: clincialtrials.gov identifier: NCT 00,083,668; prospectively registered May 28, 2004

Basic principles and new advances in kidney imaging

Over the past few years, clinical renal imaging has seen great advances, allowing assessments of kidney structure and morphology, perfusion, function and metabolism, and oxygenation, as well as microstructure and the interstitium. Medical imaging is becoming increasingly important in the evaluation of kidney physiology and pathophysiology, showing promise in management of patients with renal disease, in particular with regard to diagnosis, classification, and prediction of disease development and progression, monitoring response to therapy, detection of drug toxicity, and patient selection for clinical trials. A variety of imaging modalities, ranging from routine to advanced tools, are currently available to probe the kidney both spatially and temporally, particularly ultrasonography, computed tomography, positron emission tomography, renal scintigraphy, and multiparametric magnetic resonance imaging. Given that the range is broad and varied, kidney imaging techniques should be chosen based on the clinical question and the specific underlying pathologic mechanism, taking into account contraindications and possible adverse effects. Integration of various modalities providing complementary information will likely provide the greatest insight into renal pathophysiology. This review aims to highlight major recent advances in key tools that are currently available or potentially relevant for clinical kidney imaging, with a focus on non-oncological applications. The review also outlines the context of use, limitations, and advantages of various techniques, and highlights gaps to be filled with future development and clinical adoption.

Cervical and thoracic cord atrophy in multiple sclerosis phenotypes: Quantification and correlation with clinical disability

ObjectiveWe sought to characterize spinal cord atrophy along the entire spinal cord in the major multiple sclerosis (MS) phenotypes, and evaluate its correlation with clinical disability. MethodsAxial T1-weighted images were automatically reformatted at each point along the cord. Spinal cord cross‐sectional area (SCCSA) were calculated from C1-T10 vertebral body levels and profile plots were compared across phenotypes. Average values from C2-3, C4-5, and T4-9 regions were compared across phenotypes and correlated with clinical scores, and then categorized as atrophic/normal based on z-scores derived from controls, to compare clinical scores between subgroups. In a subset of relapsing-remitting cases with longitudinal scans these regions were compared to change in clinical scores. ResultsThe cross-sectional study consisted of 149 adults diagnosed with relapsing-remitting MS (RRMS), 49 with secondary-progressive MS (SPMS), 58 with primary-progressive MS (PPMS) and 48 controls. The longitudinal study included 78 RRMS cases. Compared to controls, all MS groups had smaller average regions except RRMS in T4-9 region. In all MS groups, SCCSA from all regions, particularly the cervical cord, correlated with most clinical measures. In the RRMS cohort, 22% of cases had at least one atrophic region, whereas in progressive MS the rate was almost 70%. Longitudinal analysis showed correlation between clinical disability and cervical cord thinning. ConclusionsSpinal cord atrophy was prevalent across MS phenotypes, with regional measures from the RRMS cohort and the progressive cohort, including SPMS and PPMS, being correlated with disability. Longitudinal changes in the spinal cord were documented in RRMS cases, making it a potential marker for disease progression. While cervical SCCSA correlated with most disability and progression measures, inclusion of thoracic measurements improved this correlation and allowed for better subgrouping of spinal cord phenotypes. Cord atrophy is an important and easily obtainable imaging marker of clinical and sub-clinical progression in all MS phenotypes, and such measures can play a key role in patient selection for clinical trials.

MBRS-02. BET BROMODOMAIN PROTEIN-KINASE INHIBITOR COMBINATIONS FOR THE TREATMENT OF MEDULLOBLASTOMA

Recent sequencing studies have implicated many epigenetic regulators in medulloblastoma. The epigenetic reader protein Brd4 has been implicated in various cancers including medulloblastoma. Brd4 controls expression of the medulloblastoma essential genes MYC in G3 medulloblastomas, which have poor prognosis as well as GLI1 and GLI2 levels in Sonic hedgehog (SHH) driven medulloblastomas, which have intermediate prognosis. Highly selective Brd4 inhibitors have been developed that reduce MYC, GLI1 and GLI2 levels. These inhibitors have gone into clinical trials for multiple cancer indications including medulloblastoma. However, resistance is common for Brd4 inhibitors warranting combination therapies for improved clinical outcome. We have developed a computational pipeline termed SynergySeq that predicts patient specific combinations of Brd4 inhibitors along with kinase inhibitors. We demonstrate that Brd4-kinase inhibitors robustly reduce proliferation of Shh and MYC driven medulloblastoma cells. Improved efficacy is related to dampening the adaptive kinome reprogramming response that occurs after Brd4 inhibition. Our findings suggest that SynergySeq can be utilized to inform patient selection for clinical trials utilizing Brd4 inhibitors in medulloblastoma and other brain tumors.

Amyloid, pTau, NfL, and GFAP as biomarkers for Alzheimer’s disease

AbstractBackgroundAlzheimer's disease (AD) is a multifactorial disease, with ongoing amyloid and tau accumulation, axonal damage and astrocytosis. Blood‐based biomarkers reflecting these processes are potentially valuable for patient selection for clinical trials, for monitoring disease progression and treatment effects, and for the differential diagnosis of AD. Several studies have shown that plasma amyloid beta (Abeta) 42 and 40 concentrations, phosphorylated tau (pTau) at amino acid 181 or 217, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) are changed in AD. Therefore, our studies are driven by the idea that combination of several markers will provide a more complete picture of the full complexity of AD.MethodThe results presented were obtained in several retrospective clinical cohort studies in memory clinics. Plasma Abeta 42 and 40, GFAP, and NfL were measured with Simoa technology, using homebrew assays (Amyblood, ADx), and commercial kits (Quanterix). pTau181 and 217 were measured using MSD technology with Lilly antibodies. Based on positive Amyblood and GFAP results, a novel 4‐plex assay was developed (AUMC, Quanterix, ADx). Results will be presented on the use pTau217 and of the measurement of combinations of Abeta isoforms, GFAP, and NfL for differential diagnosis of AD, Lewy body dementia, and Frontotemporal lobar degeneration (FTLD).ResultThe plasma markers are analyzed in over 1100 subjects. The Abeta 42/40 ratio decreased 1.2 fold in cases in the AD spectrum with a positive amyloid‐PET status, compared to amyloid negative cases. pTau181 concentrations were increased 2.4 fold in cases with tau accumulation measured with FTP‐PET, and pTau181 was increased 2.3 fold in AD compared to FTLD. NfL was increased 1.4‐2.3 fold in AD and FTLD patients compared to controls. GFAP levels were increased 1.8 fold in amyloid‐PET cases. Combining GFAP and the Abeta 42/40 ratio together with APOE e4 carriership resulted in an AUC of 88% differentiating amyloid‐PET positive from negative cases.ConclusionIndividual blood‐based biomarkers reflect different physiological processes in the brain. Creating a panel of t markers could provide a more complete picture of ongoing pathological processes and likely increases diagnostic accuracy to be suitable for blood‐based screening of AD and enable personalized medicine.

Phenotypes and personalized medicine in the acute respiratory distress syndrome.

Although the acute respiratory distress syndrome (ARDS) is well defined by the development of acute hypoxemia, bilateral infiltrates and non-cardiogenic pulmonary edema, ARDS is heterogeneous in terms of clinical risk factors, physiology of lung injury, microbiology, and biology, potentially explaining why pharmacologic therapies have been mostly unsuccessful in treating ARDS. Identifying phenotypes of ARDS and integrating this information into patient selection for clinical trials may increase the chance for efficacy with new treatments. In this review, we focus on classifying ARDS by the associated clinical disorders, physiological data, and radiographic imaging. We consider biologic phenotypes, including plasma protein biomarkers, gene expression, and common causative microbiologic pathogens. We will also discuss the issue of focusing clinical trials on the patient’s phase of lung injury, including prevention, administration of therapy during early acute lung injury, and treatment of established ARDS. A more in depth understanding of the interplay of these variables in ARDS should provide more success in designing and conducting clinical trials and achieving the goal of personalized medicine.

Current Progress and Future Directions for Tau-Based Fluid Biomarker Diagnostics in Alzheimer's Disease.

Despite continued efforts, there remain no disease-modifying drugs approved by the United States Food and Drug Administration (FDA) or European Medicines Agency (EMA) to combat the global epidemic of Alzheimer’s disease. Currently approved medicines are unable to delay disease progression and are limited to symptomatic treatment. It is well established that the pathophysiology of this disease remains clinically silent for decades prior to symptomatic clinical decline. Identifying those at risk of disease progression could allow for effective treatment whilst the therapeutic window remains open for preservation of quality of life. This review aims to evaluate critically the current advances in the interpretation of tau-based biomarkers and their use to provide insights into the onset and progression of Alzheimer’s disease, whilst highlighting important future directions for the field. This review emphasises the need for a more comprehensive analysis and interrogation of tau within biological fluids, to aid in obtaining a disease specific molecular signature for each stage of Alzheimer’s disease. Success in achieving this could provide essential utility for presymptomatic patient selection for clinical trials, monitoring disease progression, and evaluating disease modifying therapies.

Deliberating the Diagnostic Dilemma of Heart Failure With Preserved Ejection Fraction.

There is a lack of consensus on how we define heart failure with preserved ejection fraction (HFpEF), with wide variation in diagnostic criteria across society guidelines. This lack of uniformity in disease definition stems in part from an incomplete understanding of disease pathobiology, phenotypic heterogeneity, and natural history. We review current knowledge gaps and existing diagnostic tools and algorithms. We present a simple approach to implement these tools within the constraints of the current knowledge base, addressing separately (1) hospitalized individuals with rest congestion, where diagnosis is more straightforward; and (2) individuals with exercise intolerance, where diagnosis is more complex. Here, a potential role for advanced or provocative testing, including evaluation of hemodynamic responses to exercise is considered. More importantly, we propose focus areas for future studies to develop accurate and feasible diagnostic tools for HFpEF, including animal models that recapitulate human HFpEF, and human studies that both address a fundamental understanding of HFpEF pathobiology, and new diagnostic approaches and tools, as well. In sum, there is an urgent need to more accurately define the syndrome of HFpEF to inform diagnosis, patient selection for clinical trials, and, ultimately, future therapeutic approaches.

Abstract PO-51: Drug combination analytics platform for accurate prediction of treatment response in refractory and relapsed lymphomas

Abstract While 5-year survival rates for non-Hodgkin lymphoma have improved with effective first-line therapies, refractory and relapsed lymphomas continue to suffer from poor response rates and low median overall survival. The increased availability of targeted therapies has been critical to improving response rates in lymphomas. As the number of therapeutic options increases, however, identifying the most appropriate patient-specific drug combination from among a range of available drug sets is virtually impossible by conventional methods due to the large search space. Further complicating this clinical decision is the diversity in interpatient therapeutic responses due to lymphoma patient heterogeneity. Math and AI-based analytical tools are beginning to positively impact all facets of drug development and personalized medicine. Rather than aggregating large datasets from other sources (data repositories, text mining, etc.) to develop predictive models, we developed an experimentally driven small dataset analytics platform, Quadratic Phenotypic Optimization Platform (QPOP), to identify and rank drug combinations from a specific drug set search space. QPOP identifies optimal drug combinations from queried drug sets against specific biologic systems of interests, including patient-derived primary cancer cells. Utilizing small datasets built from drug combination tests designed by orthogonal array composite design, QPOP analyzes drug combination sensitivity data to identify and rank possible drug combinations. Recently, we applied QPOP towards patient-specific clinical decision support applications in refractory and relapsed non-Hodgkin lymphoma. Utilizing 1 million patient-derived primary lymphoma cells for 155 drug combination tests, QPOP ranked 531,441 possible therapeutic options from a 12-drug search set within 6 days of patient sample biopsy. Across a series of refractory and relapsed T-cell lymphoma patients, effective treatment options were accurately predicted that included both standard salvage regimens, such as gemcitabine-dexamethasone-cisplatin, as well as targeted regimens, such as bortezomib-panobinostat. For a hepatosplenic T-cell lymphoma case that had previously progressed following 6 lines of treatment, analysis by QPOP was able to accurately identify patient-specific bortezomib-panobinostat treatment that resulted in a complete response. Furthermore, QPOP-predicted drug combination sensitivity results from our study were compared to historical outcomes of a phase 2 trial of bortezomib-panobinostat in peripheral T-cell lymphoma (NCT00901147), with 20% predicted response in our QPOP-analyzed cohort mirroring 21.7% complete response observed in the previous trial. These results provide evidence that ex vivo drug combination sensitivity platforms may be useful tools for clinical decision support, for both personalized medical applications as well as enhanced clinical trial patient selection and parallel outcome tracking. Citation Format: Jasmine Goh, Sanjay de Mel, Anand D. Jeyasekharan, Edward K.H. Chow. Drug combination analytics platform for accurate prediction of treatment response in refractory and relapsed lymphomas [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-51.

Endothelial BMPR2 Loss Drives a Proliferative Response to BMP (Bone Morphogenetic Protein) 9 via Prolonged Canonical Signaling.

Pulmonary arterial hypertension is a disease of proliferative vascular occlusion that is strongly linked to mutations in BMPR2-the gene encoding the BMPR-II (BMP [bone morphogenetic protein] type II receptor). The endothelial-selective BMPR-II ligand, BMP9, reverses disease in animal models of pulmonary arterial hypertension and suppresses the proliferation of healthy endothelial cells. However, the impact of BMPR2 loss on the antiproliferative actions of BMP9 has yet to be assessed. Approach and Results: BMP9 suppressed proliferation in blood outgrowth endothelial cells from healthy control subjects but increased proliferation in blood outgrowth endothelial cells from pulmonary arterial hypertension patients with BMPR2 mutations. This shift from growth suppression to enhanced proliferation was recapitulated in control human pulmonary artery endothelial cells following siRNA-mediated BMPR2 silencing, as well as in mouse pulmonary endothelial cells isolated from endothelial-conditional Bmpr2 knockout mice (Bmpr2EC-/-). BMP9-induced proliferation was not attributable to altered metabolic activity or elevated TGFβ (transforming growth factor beta) signaling but was linked to the prolonged induction of the canonical BMP target ID1 in the context of BMPR2 loss. In vivo, daily BMP9 administration to neonatal mice impaired both retinal and lung vascular patterning in control mice (Bmpr2EC+/+) but had no measurable effect on mice bearing a heterozygous endothelial Bmpr2 deletion (Bmpr2EC+/-) and caused excessive angiogenesis in both vascular beds for Bmpr2EC-/- mice. BMPR2 loss reverses the endothelial response to BMP9, causing enhanced proliferation. This finding has potential implications for the proposed translation of BMP9 as a treatment for pulmonary arterial hypertension and suggests the need for focused patient selection in clinical trials.

Tissue biomarker for the detection of dementia with Levi bodies

Scientists from the Banner Sun Health research institute (Sun City, Arizona, USA) studied 228 histological preparations obtained by postmortem examination, including samples with diseases of Levi bodies: 46 with Parkinson's disease, 28 with dementia with Levi bodies, 9 with concomitant disease of Levi bodies, 33 with Alzheimer's disease with Levi bodies and two with progressive supranuclear palsy with Levi bodies. The drugs of the control group, defined as people without synucleopathy associated with Levy's disease of the body affecting the central nervous system, included 79 samples from healthy elderly people, 15 from people with Alzheimer's disease, 12 from people with progressive supranuclear palsy, 2 from individuals with corticobasal degeneration and 2 from individuals with multiple systemic atrophy. Tissue sections of the submandibular gland of exposed people were stained with an immunohistochemical method to detect serine phosphorylated α-synuclein 129. Researchers found a submandibular alpha-synuclein pathology in 42/47 (89%) of exposed patients with Parkinson's disease and in 20/28 (71% ) opened patients with dementia with Levy bodies, but not one of 110 representatives of the control group. The authors concluded that the findings could help with further clinical studies of a diagnostic biopsy of the submandibular gland in vivo to detect Parkinson's disease and dementia with Levi bodies. Accurate diagnosis using a peripheral biopsy will help select patients for clinical trials and can be used to check other biomarkers.Low diagnostic accuracy made it difficult to conduct effective clinical trials involving living people in the search for new drugs. With better diagnostic accuracy, clinical trials would have a higher chance of success and could be completed faster and have lower cost. In the next step, biopsy of the submandibular gland will be necessary for living people with dementia with Levi bodies to confirm the autopsy results.

Immunohistochemical Expression of “c-MET” in Breast Carcinomas

BACKGROUND: Targeted therapies achieved great success in managing breast cancer, however, triple negative breast cancers (TNBCs) lack the expression of traditional therapeutic targets, and other subtypes develop resistance to current therapies. The c-MET receptor emerged as a potential target with well documented pro-proliferative pro-motility downstream signals and wide network of crosstalk with other effectors. Some reports describe a preferential expression of c-MET in TNBCs and promising results in early anti-c-MET clinical trials. However, the main cause of failure of these trials was attributed to patient selection.&#x0D; AIM: The objectives of the study were to assessment of c-MET in subtypes of breast cancer and its association with other clinicopathological variables that may predict its expression and possibly establish other rationales to refine patient selection for clinical trials.&#x0D; MATERIALS AND METHODS: Retrospective immunohistochemical study assessing c-MET (clone SP44) in 55 cases of breast carcinoma. The expression of c-MET&gt; 5% was considered positive.&#x0D; RESULTS: c-MET was detected in 42% of cases. A statistically significant association of c-MET with extremes of age, advanced prognostic stage, carcinoma with medullary features, and high tumor infiltrating lymphocytes (TILs) was observed for the first time in our study. Grade III, hormone receptor negativity and TNBCs were also significantly associated with c-MET. Only negative progesterone receptor (PR) and high TILs were independently associated with c-MET in a multivariate analysis (p &lt; 0.05). No significant association between c-MET and multifocality, size, node status, anatomic stage, lymphovascular or perineural invasion, and Ki-67 expression.&#x0D; CONCLUSION: PR negativity and high TILs might be useful c-MET predictors and selection tools for clinical trials but further studies are needed to validate the unprecedented findings which may not only aid in patient selection but may also inspire new paradigms in future studies.

A Genome-Wide Pooled shRNA Screen Identifies PPP2R2A as a Predictive Biomarker for the Response to ATR and CHK1 Inhibitors.

There is currently a lack of precise predictive biomarkers for patient selection in clinical trials of inhibitors targeting replication stress (RS) response proteins ATR and CHK1. The objective of this study was to identify novel predictive biomarkers for the response to these agents in treating non-small cell lung cancer (NSCLC). A genome-wide loss-of-function screen revealed that tumor suppressor PPP2R2A, a B regulatory subunit of protein phosphatase 2 (PP2A), determines sensitivity to CHK1 inhibition. A synthetic lethal interaction between PPP2R2A deficiency and ATR or CHK1 inhibition was observed in NSCLC in vitro and in vivo and was independent of p53 status. ATR and CHK1 inhibition resulted in significantly increased levels of RS and altered replication dynamics, particularly in PPP2R2A-deficient NSCLC cells. Mechanistically, PPP2R2A negatively regulated translation of oncogene c-Myc protein. c-Myc activity was required for PPP2R2A deficiency-induced alterations of replication initiation/RS and sensitivity to ATR/CHK1 inhibitors. We conclude that PPP2R2A deficiency elevates RS by upregulating c-Myc activity, rendering cells reliant on the ATR/CHK1 axis for survival. Our studies show a novel synthetic lethal interaction and identify PPP2R2A as a potential new predictive biomarker for patient stratification in the clinical use of ATR and CHK1 inhibitors. SIGNIFICANCE: This study reveals new approaches to specifically target PPP2R2A-deficient lung cancer cells and provides a novel biomarker that will significantly improve treatment outcome with ATR and CHK1 inhibitors.