Predictors Of Clinical Response Research Articles

The issue of heterogeneity of MSC-based advanced therapy medicinal products-a review.

Mesenchymal stromal stem cells (MSCs) possess a remarkable potential for numerous clinical applications due to their unique properties including self-renewal, immunomodulation, paracrine actions and multilineage differentiation. However, the translation of MSC-based Advanced Therapy Medicinal Products (ATMPs) into the clinic has frequently met with inconsistent outcomes. One of the suspected reasons for this issue is the inherent and extensive variability that exists among such ATMPs, which makes the interpretation of their clinical efficacy difficult to assess, as well as to compare the results of various studies. This variability stems from numerous reasons including differences in tissue sources, donor attributes, variances in manufacturing protocols, as well as modes of administration. MSCs can be isolated from various tissues including bone marrow, umbilical cord, adipose tissue and others, each with its unique phenotypic and functional characteristics. While MSCs from different sources do share common features, they also exhibit distinct gene expression profiles and functional properites. Donor-specific factors such as age, sex, body mass index, and underlying health conditions can influence MSC phenotype, morphology, differentiation potential and function. Moreover, variations in preparation of MSC products introduces additional heterogeneity as a result of cell culture media composition, presence or absence of added growth factors, use of different serum supplements and culturing techniques. Once MSC products are formulated, storage protocols play a pivotal role in its efficacy. Factors that affect cell viability include cell concentration, delivery solution and importantly, post-thawing protocols where applicable. Ensuing, differences in administration protocols can critically affect the distribution and functionallity of administered cells. As MSC-based therapies continue to advance through numerous clinical trials, implication of strategies to reduce product heterogeneity is imperative. Central to addressing these challenges is the need for precise prediction of clinical responses, which require well-defined MSC populations and harmonized assessment of their specific functions. By addressing these issues by meaningful approaches, such as, e.g., MSC pooling, the field can overcome barriers to advance towards more consistent and effective MSC-based therapies.

Clinical outcomes of deep brain stimulation for obsessive-compulsive disorder: Insight as a predictor of symptom changes.

Deep brain stimulation (DBS) is a safe and effective treatment option for people with refractory obsessive-compulsive disorder (OCD). Yet our understanding of predictors of response and prognostic factors remains rudimentary, and long-term comprehensive follow-ups are lacking. We aim to investigate the efficacy of DBS therapy for OCD patients, and predictors of clinical response. Eight OCD participants underwent DBS stimulation of the nucleus accumbens (NAc) in an open-label longitudinal trial, duration of follow-up varied between 9 months and 7 years. Post-operative care involved comprehensive fine tuning of stimulation parameters and adjunct multidisciplinary therapy. Six participants achieved clinical response (35% improvement in obsessions and compulsions on the Yale Brown Obsessive Compulsive Scale (YBOCS)) within 6-9 weeks, response was maintained at last follow up. On average, the YBOCS improved by 45% at last follow up. Mixed linear modeling elucidated directionality of symptom changes: insight into symptoms strongly predicted (P = 0.008) changes in symptom severity during DBS therapy, likely driven by initial changes in depression and anxiety. Precise localization of DBS leads demonstrated that responders most often had their leads (and active contacts) placed dorsal compared to non-responders, relative to the Nac. The clinical efficacy of DBS for OCD is demonstrated, and mediators of changes in symptoms are proposed. The symptom improvements within this cohort should be seen within the context of the adjunct psychological and biopsychosocial care that implemented a shared decision-making approach, with flexible iterative DBS programming. Further research should explore the utility of insight as a clinical correlate of response. The trial was prospectively registered with the ANZCTR (ACTRN12612001142820).

Bioprinted Organoids Platform with Tumor Vasculature for Implementing Precision Personalized Medicine Targeted Towards Gastric Cancer

AbstractAccurate prediction of treatment response for cancer patients is essential for overcoming intrinsic therapy resistance that results from genetic heterogeneity, varying tumor growth kinetics, and the complex tumor microenvironment. To achieve this goal, there is an urgent need for effective preclinical in vitro models that recapitulate the molecular–pathologic features and intricate ecology of native tumors for precision medicine. In this study, a vascularized organoid model (VOM) composed of patient‐derived gastric cancer organoids (PDOs), perfusable endothelium, and stomach decellularized extracellular matrix is presented that enables the prediction of clinical response to VEGFR2‐targeted therapy in gastric cancer patients. The results indicate that VOMs are dependent on the PDO molecular subtype. Moreover, VOMs accurately reproduce the clinically observed responses of patients treated with VEGFR2 inhibitor. Therefore, VOMs represent a valuable platform for providing clinical predictions for personalized testing and potential discovery of therapeutic drugs in various cancers that lack standardized regimens.

Abstract LB_A02: Predicting breast cancer patients’ response to neoadjuvant chemotherapy from the deconvolved transcriptome of different cell types in the tumor microenvironment

Abstract Introduction: The tumor microenvironment (TME) constitutes a multifaceted ecosystem that influences tumor growth and clinical response via dynamic interactions between diverse cell types. Considerable attention has been devoted in recent years in exploring the TME’s impact on clinical response following immunotherapy, warranting further investigation into its impact in the context of chemotherapy. To address this, we present a novel computational framework called DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning). Through DECODEM, we investigate the association of cell-type-specific transcriptomic profiles within the TME with response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Methods: DECODEM leverages cellular deconvolution of bulk transcriptomics data to extract cell-type-specific transcriptomics profiles for different cell types present in the TME, and further utilizes machine learning to build cell-type-specific predictors of clinical response. Using DECODEM, we analyzed the bulk transcriptomics data across three publicly available cohorts of HER2-negative BC patients who underwent NAC. We compared the predictive powers of these cell types, both individually and in concert with each other, against a state-of-the-art predictor employing clinical and transcriptomic features. We then validated our findings in a single-cell chemotherapy cohort of triple-negative breast cancer. Furthermore, we extended DECODEM to DECODEMi that can incorporate the cell-cell interactions (CCIs) among the prominent cell types to predict clinical response, hinting at the underlying mechanism at play. Results: Our analysis revealed that the diverse cell types within the TME significantly contribute to the prediction of chemotherapy response in HER2-negative BC, thus extending beyond the impact of malignant tumor cells alone. Notably, our key findings are: 1. We demonstrated the superior predictive powers of immune cells (myeloid, plasmablasts, B-cells) and stromal cells (endothelial, normal epithelial, cancer-associated fibroblasts), as compared to the bulk mixture and the state-of-the-art predictor. 2. We illustrated the complementary impacts of the prominent cell types via building highly accurate multi-cell-ensembles, where, remarkably, a three-cell-ensemble of endothelial, myeloid, and plasmablasts displayed the best predictive capability across cohorts. 3. We displayed that DECODEMi can capture the regulatory roles of CCIs and identified new CCIs likely to mediate chemotherapy response in HER2-negative BC. Conclusion: We provide an unprecedented computational approach to objectively delineate the cell-type-specific impacts of the TME in clinical response. Our analysis provides comprehensive insights into the intricate interplay of the cells in TME and their associations with chemotherapy response in HER2-negative BC, contributing to a deeper understanding of BC treatment efficacy. Citation Format: Saugato Rahman Dhruba, Sahil Sahni, Binbin Wang, Di Wu, Yael Schmidt, Eldad Shulman, Sanju Sinha, Stephen-John Sammut, Carlos Caldas, Kun Wang, Eytan Ruppin. Predicting breast cancer patients’ response to neoadjuvant chemotherapy from the deconvolved transcriptome of different cell types in the tumor microenvironment [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr LB_A02.

Determinants of clinical response to empirical antibiotic treatment in patients with cirrhosis and bacterial and fungal infections-Results from the ICA "Global Study" (EABCIR-Global Study).

The administration of an appropriate empirical antibiotic treatment is essential in cirrhosis and severe bacterial infections. We aimed to investigate the predictors of clinical response of empirical antibiotic treatment in a prospective cohort of patients with cirrhosis and bacterial and fungal infections included in the International Club of Ascites "Global Study." Patients hospitalized with cirrhosis and bacterial/fungal infection were prospectively enrolled at 46 centers. Clinical response to antibiotic treatment was defined according to changes in markers of infection/inflammation, vital signs, improvement of organ failure, and results of cultures. From October 2015 to September 2016, 1302 patients were included at 46 centers. A clinical response was achieved in only 61% of cases. Independent predictors of lack of clinical response to empirical treatment were C-reactive protein (OR = 1.16; 95% CI = 1.02-1.31), blood leukocyte count (OR = 1.39;95% CI = 1.09-1.77), serum albumin (OR = 0.70; 95% CI = 0.55-0.88), nosocomial infections (OR = 1.96; 95% CI = 1.20-2.38), pneumonia (OR = 1.75; 95% CI = 1.22-2.53), and ineffective treatment according to antibiotic susceptibility test (OR = 5.32; 95% CI = 3.47-8.57). Patients with a lack of clinical response to first-line antibiotic treatment had a significantly lower resolution rate of infections (55% vs. 96%; p < 0.001), a higher incidence of second infections (29% vs. 15%; p < 0.001), shock (35% vs. 7%; p < 0.001) and new organ failures (52% vs. 19 %; p < 0.001) than responders. Clinical response to empirical treatment was an independent predictor of 28-day survival ( subdistribution = 0.20; 95% CI = 0.14-0.27). Four out of 10 patients with cirrhosis do not respond to the first-line antibiotic therapy, leading to lower resolution of infections and higher mortality. Broader-spectrum antibiotics and strategies targeting systemic inflammation may improve prognosis in patients with a high degree of inflammation, low serum albumin levels, and severe liver impairment.

M6A-related lncRNAs as potential biomarkers and the lncRNA ELFN1-AS1/miR-182-5p/BCL-2 regulatory axis in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid subtype. However, unsatisfactory survival outcomes remain a major challenge, and the underlying mechanisms are poorly understood. N6-methyladenosine (m6A), the most common internal modification of eukaryotic mRNA, participates in cancer pathogenesis. In this study, m6A-associated long non-coding RNAs (lncRNA) were retrieved from publicly available databases. Univariate, LASSO, and multivariate Cox regression analyses were performed to establish an m6A-associated lncRNA model specific to DLBCL. Kaplan-Meier curves, principal component analysis, functional enrichment analyses and nomographs were used to study the risk model. The underlying clinicopathological characteristics and drug sensitivity predictions against the model were identified. Risk modelling based on the three m6A-associated lncRNAs was an independent prognostic factor. By regrouping patients using our model-based method, we could differentiate patients more accurately for their response to immunotherapy. In addition, prospective compounds that can target DLBCL subtypes have been identified. The m6A-associated lncRNA risk-scoring model developed herein holds implications for DLBCL prognosis and clinical response prediction to immunotherapy. In addition, we used bioinformatic tools to identify and verify the ceRNA of the m6A-associated lncRNA ELFN1-AS1/miR-182-5p/BCL-2 regulatory axis. ELFN1-AS1 was highly expressed in DLBCL and DLBCL cell lines. ELFN1-AS1 inhibition significantly reduced the proliferation of DLBCL cells and promoted apoptosis. ABT-263 inhibits proliferation and promotes apoptosis in DLBCL cells. Invitro and invivo studies have shown that ABT-263 combined with si-ELFN1-AS1 can inhibit DLBCL progression.

Ex Vivo Mathematical Myeloma Advisor (EMMA) - a Clinical, Molecular, and Phenotypic Platform to Tailor Personalized Therapeutic Strategies for Multiple Myeloma

Multiple myeloma (MM) is a genetically heterogeneous disease, lacking molecular markers for patient stratification and prediction of clinical response. We have created a unique platform for clinical-informed decisions, research advancement, and preclinical compound testing called the “Ex Vivo Mathematical Myeloma Advisor” (EMMA). In this pipeline, MM patients who undergo bone marrow (BM) biopsy and consent to participate in the Total Cancer Care protocol have their clinical data (demographics, therapies received, lab results, clinical history, etc.) abstracted, along with the molecular characterization (FISH/cytogenetics, RNA-Seq, and WES) of their disease. In parallel, fresh BM-derived MM blasts are combined with stromal cells in a collagen-based matrix containing patient plasma and used in an ex vivo drug screening assay. The cells are seeded into 384 or 1536-well plates and exposed to serial dilutions of up to 127 single agents and combinations. The entire setup is imaged in bright field every 30 minutes for a duration of 6 days. Image analysis is used to convert membrane integrity into survival curves, and AUC and LD50 values are estimated. The pattern of these curves facilitates the identification of resistant subclones. This data is further combined with augmented synergy models that are parameterized with PK/PD data for each drug. This integration permits the simulation of “in silico clinical trials”, which are compiled into reports that assist clinicians in selecting the best treatment for their patients. In addition, the immune population of the BM aspirate is characterized by flow cytometry, and soluble factors in the patient's BM plasma are quantified by ELISA. The integration of clinical, molecular, and phenotypic data with image analysis and machine learning tools presents a unique opportunity for finding molecular signatures of drug response (Fig. 1). For instance, our pipeline can be utilized to identify clinical factors (such as ethnicity, age, etc.) and molecular features (mutations, cytogenetic abnormalities, enriched transcription factors, differentially expressed biological pathways, etc.) associated with drug resistance/sensitivity. Additionally, it enables the determination of the mechanisms of action of new compounds and the prediction of potential synergistic/antagonistic drug combinations. The longitudinal acquisition of data in our non-destructive ex vivo drug screen assay facilitates the exploration of drug interaction dynamics over time, enabling the pinpointing of the moment when synergism occurs at maximum intensity. This, in turn, allows us to propose optimized temporal-based therapeutic regimens for clinical use. Up to this point, our pipeline has molecularly characterized nearly 1,000 MM samples, and EMMA has been applied to over 600 samples, forming one of the world's most extensive and comprehensively characterized MM cohorts. While EMMA has proven effective in quantifying the activity of monoclonal antibodies, ongoing efforts are focusing on incorporating individual immune cell components to assess ex vivo activity in the context of evolving cellular immunotherapies. As a proof of principle, we demonstrate the system's capability to measure the effect of daratumumab (CD38+ antibody) on autologous macrophage-mediated MM cell death, thereby distinguishing it from apoptosis caused by direct antibody binding (Fig. 2). Additionally, we evaluate the influence of teclistamab (T-cell engager CD3/BCMA bispecific antibody) on CD8+ T cell activity against autologous MM cells, as well as the efficacy of CAR-T cells in killing MM cells. Through the testing of standard-of-care drugs alongside immune agents, our pipeline has identified the combination of bortezomib + daratumumab as a synergistic approach with significant translational potential, warranting further investigation. In summary, our state-of-the-art platform facilitate drug discovery and unravel the intricate biological phenomena underlying drug interactions in MM. The advantages offered by our system are threefold: i) it enables pharmaceutical companies to test new compounds in a bona fide, patient-derived model; ii) it assists clinicians in selecting the best therapy for their patients, and iii) it helps prevent cancer patients from receiving non-suitable therapies. This approach can also be promptly applied to other liquid cancers, such as leukemia and lymphoma.

ASXL1 Mutation and Leukocytosis Undermine Spleen Response to Pacritinib in Myelofibrosis

Background: Non-transplant treatment options in myelofibrosis (MF) are palliative in scope and include JAK2 inhibitors (JAKi): ruxolitinib, fedratinib, pacritinib, and momelotinib. All four JAKi are effective in reducing spleen size and alleviating symptoms. In addition, pacritinib and momelotinib exhibit erythropoietic effect, attributed to alleviation of ineffective erythropoiesis through inhibition of activin A receptor type-I. In the current study, we sought to identify molecular or clinical predictors of response to pacritinib in MF patients treated outside of clinical trials. Methods: The current study was conducted under an institutional review board approved minimum risk protocol that allowed retrospective collection and analysis of data from patient records (Mayo Clinic, Rochester, MN; Scottsdale, AZ; and Jacksonville, FL). Anemia response assignment was restricted to patients with baseline hemoglobin level of &amp;lt;10 g/dL and required, for transfusion dependent cases, achieving transfusion independence and, for transfusion-independent cases, an increase in hemoglobin of ≥1.5 g/dL, both sustained for a minimum 2 months; spleen response was clinically vetted but was also supported by radiologic imaging when available and required a ≥50% decrease in palpable splenomegaly for spleen size &amp;gt;10 cm or the spleen becoming not palpable for a spleen size 5-10 cm at base line. Symptom response was adjudicated by central review and required a marked or moderate improvement to qualify as response; because of the retrospective nature of the study, symptom burden assessment by formal criteria was not attempted. Leukocyte cutoff level used for response analysis was determined by receiver operating characteristic curve analysis. Conventional statistical methods were applied using JMP Pro 16.0.0 software (SAS Institute, Cary, NC, USA). Results: We identified 36 NGS-annotated patients with MF who received pacritinib therapy between April,2022 and June,2023 (median age 66 years; 56% males). Twenty-five (69%) patients had failed previous JAKi therapy while 11 (31%) were JAKi-naïve. Eighteen (50%) patients were transfusion-dependent while the median (range) counts were 106 x 10(9)/L (14-578) for platelets, 6.6 x 10(9)/L (1.2-112.8) for leukocytes, and 9 x 10(9)/L (5-12.4) for hemoglobin; leukocyte count was ≥15 x 10(9)/L in 11 (31%) patients and hemoglobin &amp;lt;10 g/dL in 29 (81%). Karyotype was unfavorable in 12 (34%) patients. Driver mutation distribution was JAK2 55%, CALR 27%, MPL 11%, and triple-negative 5%. NGS revealed mutations involving ASXL1 36%, U2AF1 13%, IDH1 13%, SF3B1 13%, K/NRAS 5%, SRSF2 8%, and EZH2 5%. Pacritinib was started at 200 mg BID in 9 (25%) patients and at lower doses in the remaining. Median duration of pacritinib therapy was 4 months (range 1-15). Anemia response was documented in 5 (17%) of the 29 patients with baseline hemoglobin &amp;lt;10 g/dL, spleen response in 12 of 28 evaluable (42%) and symptom response in 18 (50%). Improvement in symptoms was always accompanied by both anemia (p=0.008) and spleen (p=0.01) response; by contrast, there was no significant correlation between anemia and spleen responses (p=0.9) (Table 1). Significant correlations with molecular or clinical variables were mostly apparent for spleen response, which was more likely to occur in the absence of ASXL1 mutation (61% vs 10%; p=0.006), with leukocyte count &amp;lt;15 x 10 (9)/L (55% vs 0%; p=0.005), and in JAKi-naïve vs previously-exposed cases (75% vs 30%; p=0.03; Table 1); significance was sustained by all three risk factors during multivariable analysis; the prognostic impact of ASXL1 (p=0.02 vs 0.01) and leukocytosis (p=0.01 vs 0.07) was apparent in both JAKi-naïve vs JAKi-exposed cases. Anemia response was non-significantly (p=0.27) higher in transfusion-independent (27%) vs dependent (11%) cases, at baseline, and was more likely (p=0.04) to occur in patients starting at lower dose levels. Treatment-emergent adverse events included diarrhea 44%, nausea/vomiting 19%, and grade-3/4 thrombocytopenia 38% or neutropenia (11%). Conclusions: ASXL1 mutation and leukocytosis (&amp;gt;15 x 10 9/L) are independently associated with inferior spleen response to pacritinib, in both JAKi-naïve and JAKi-exposed myelofibrosis. These observations are important for individualized treatment selection.

Abstract 14478: Electrocardiographic Predictors of Response to Sacubitril/Valsartan Therapy in Heart Failure With Reduced Ejection Fraction: A Retrospective Cohort Study

Introduction: Sacubitril/valsartan (SV) therapy is currently recommended as first-line therapy in patients with heart failure and reduced ejection fraction (HFrEF) due to its significant clinical and prognostic benefit; however, not all patients respond to therapy and predictors of clinical response to SV remain under-studied. Hypothesis: Certain electrocardiographic (ECG) parameters may predict response to SV therapy in HFrEF patients. Methods: Retrospective analysis of a hospital heart failure registry was undertaken. Consecutive HFrEF patients (NHYA class II - III) on maximal-dose SV were studied. Response to SV was defined as ≥10% relative improvement in left ventricular ejection fraction (LVEF) at 3-months post-therapy. Pre-therapy ECGs were retrospectively analyzed for axes and standard wave and interval durations. Logistic regression was used to estimate odds ratios and 95% confidence intervals for associations between predictors and therapeutic response. For P-wave duration (PWD), the reference level was set to &lt;100ms; for the remaining variables, reference levels were set as: (a) the normal range for ECG variables; (b) absence for bundle branch blocks; and (c) the other category for binary variables. Calibration and discriminative performance of the models were also assessed. Results: In the 102 patients studied, PWD 100 - 120ms, PWD &gt;120ms, and QTc &gt;460ms were independently associated with response to SV therapy: OR 18.00 (4.45 - 122.90), 5.00 (1.47 - 20.42), and 3.10 (1.18 - 9.22) respectively. A multivariate logistic regression model including these predictors, and adjusting for pre-therapy LVEF, was both highly selective (area under the ROC curve = .840) and well-calibrated (Hosmer-Lemeshow p = .973). Conclusions: Prolongation of both PWD and QTc interval on baseline ECG in HFrEF patients is predictive of therapeutic response to maximal-dose SV therapy and may indicate early cardiac remodeling that is highly amenable to reversal.

Baseline markers of cortical excitation and inhibition predict response to theta burst stimulation treatment for youth depression

Theta burst stimulation (TBS), a specific form of repetitive transcranial magnetic stimulation (TMS), is a promising treatment for youth with Major Depressive Disorder (MDD) who do not respond to conventional therapies. However, given the variable response to TBS, a greater understanding of how baseline features relate to clinical response is needed to identify which patients are most likely to benefit from this treatment. In the current study, we sought to determine if baseline neurophysiology, specifically cortical excitation and/or inhibition, is associated with antidepressant response to TBS. In two independent open-label clinical trials, youth (aged 16–24 years old) with MDD underwent bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment. Clinical trial one and two consisted of 10 and 20 daily sessions of bilateral DLPFC TBS, respectively. At baseline, single-pulse TMS combined with electroencephalography was used to assess the neurophysiology of 4 cortical sites: bilateral DLPFC and inferior parietal lobule. Measures of cortical excitation and inhibition were indexed by TMS-evoked potentials (i.e., P30, N45, P60, N100, and P200). Depression severity was measured before, during and after treatment completion using the Hamilton Rating Scale for Depression—17. In both clinical trials, the baseline left DLPFC N45 and P60, which are believed to reflect inhibitory and excitatory mechanisms respectively, were predictors of clinical response. Specifically, greater (i.e., more negative) N45 and smaller P60 baseline values were associated with greater treatment response to TBS. Accordingly, cortical excitation and inhibition circuitry of the left DLPFC may have value as a TBS treatment response biomarker for youth with MDD.Clinical trial 1 registration number: NCT02472470 (June 15, 2015).Clinical trial 2 registration number: NCT03708172 (October 17, 2018).

Population Pharmacodynamic Modelling of the CD19+ Suppression Effects of Rituximab in Paediatric Patients with Neurological and Autoimmune Diseases.

Limited pharmacotherapy and the failure of conventional treatments in complex pathologies in children lead to increased off-label use of rituximab. We aimed to characterize the time course of CD19+ B lymphocytes (CD19+) under treatment with intravenous rituximab in children with neurologic and autoimmune diseases and to evaluate the impact of covariates (i.e., demographics, diagnosis and substitution between innovator and biosimilar product) on rituximab pharmacodynamics and disease activity. Pre- and post-drug infusion CD19+ in peripheral blood were prospectively registered. A population pharmacodynamic model describing the time course of CD19+ was developed with NONMEM v7.4. Simulations of three different rituximab regimens were performed to assess the impact on CD19+. Logistic regression analysis was performed to identify predictors of clinical response recorded through disease activity scores. 281 measurements of CD19+ lymphocyte counts obtained from 63 children with neurologic (n = 36) and autoimmune (n = 27) diseases were available. The time course of CD19+ was described with a turn-over model in which the balance between synthesis and degradation rates is disrupted by rituximab, increasing the latter process. The model predicts half-lives (percent coefficient of variation, CV(%)) of rituximab and CD19+ of 11.6 days (17%) and 173.3 days (22%), respectively. No statistically significant effect was found between any of the studied covariates and model parameters (p > 0.05). Simulations of different regimens showed no clinically significant differences in terms of CD19+ repopulation times. A trend towards a lack of clinical response was observed in patients with lower CD19+ repopulation times and higher areas under the CD19+ versus time curve. Rituximab pharmacodynamics was described in a real-world setting in children suffering from autoimmune and neurologic diseases. Diagnosis, substitution between innovator rituximab and its biosimilars or type of regimen did not affect rituximab-induced depletion of CD19+ nor the clinical response in this cohort of patients. According to this study, rituximab frequency and dosage may be chosen based on clinical convenience or safety reasons without affecting CD19+ repopulation times. Further studies in larger populations are required to confirm these results.

Upadacitinib effectiveness and factors associated with minimal disease activity achievement in patients with psoriatic arthritis: preliminary data of a real-life multicenter study

BackgroundUpadacitinib (UPA) is a selective JAK inhibitor recently approved for the treatment of psoriatic arthritis (PsA). In this post-approval study, we aimed to evaluate the effectiveness and safety of UPA over 24 weeks and identify clinical predictors of response, in a multicentric cohort of patients affected by PsA.MethodsOne hundred and twenty-six patients with PsA treated with UPA were enrolled in 10 Italian centres. UPA effectiveness outcomes, such as the proportion of patients with MDA status, DAPSA remission, and low disease activity, ASDAS-CRP inactive and low disease activity, and change from baseline in DAPSA and ASDAS-CRP scores, were evaluated every 12 weeks until week 24. The proportion of DAPSA minor, moderate, and major improvement, and ASDAS clinically important improvement (CII) and major improvement (MI) were considered as well. All treatment-related adverse events were collected during the observation period. Clinical predictors of MDA response at week 24 were evaluated through multivariate analysis.ResultsAt baseline, 124/126 (98%) and 54/126 (43%) patients showed peripheral and axial involvement, respectively; 110 (87%) patients were intolerant or resistant to biologic DMARDs. At 24 weeks, MDA status, DAPSA remission, and ASDAS-CRP inactive disease were achieved in 47%, 23%, and 48% of patients, respectively. Minor, moderate, and major DAPSA improvement was observed in 67%, 39%, and 23%, respectively; while 65% and 35% achieved ASDAS-CRP CII and MI, respectively. The mean change from baseline was 15.9 ± 13.5 (p < 0.001) for DAPSA and 1.21 ± 0.97 (p < 0.001) for ASDAS-CRP. Thirteen patients (10%) discontinued UPA due to a lack of efficacy or non-serious adverse events. No serious adverse events were observed. Male gender (OR 2.54, 95% CI 1.03–6.25 p = 0.043), being naïve to biological DMARDs (OR 4.13, 95% CI 1.34–12.71, p = 0.013) and elevated baseline CRP (OR 2.49, 95% CI 1.02–6.12, p = 0.046) were associated with MDA response at week 24.ConclusionsThis is one of the first real-life studies supporting the effectiveness of UPA and its safety profile in PsA patients. Furthermore, the study identifies predictors of MDA response to UPA treatment at 6 months.

Predictor of clinical response to subcutaneous immunotherapy with dust mites in polysensitized allergic rhinitis patients

Objective: To evaluate the efficacy of 1-year subcutaneous immunotherapy (SCIT) with dust mites in polysensitized allergic rhinitis (AR) patients and to analyze the serological markers associated with clinical response. Methods: A retrospective analysis of data from 69 polysensitized AR patients who completed 1-year SCIT with dust mites from Oct 2020 to Mar 2022 in Shandong Provincial ENT Hospital was conducted. The median patient age was 21 years, including 41 males and 28 females. The changes in symptoms and serum IgE, IgG4 assessed before and after treatment were evaluated. The differences in serological markers between effective and ineffective groups were analyzed. Multivariate regression analysis was used to investigate the predictors of clinical response. SPSS 22.0 software was used for data processing. Results: After immunotherapy, there was a significant reduction in symptom scores and a substantial improvement in the quality of life of polysensitized AR patients (all P<0.001). Dust mite specific IgG4 (sIgG4) significantly increased and dust mite specific IgE (sIgE)/sIgG4 significantly decreased (all P<0.05). sIgE, total IgE (tIgE), sIgE/tIgE and sIgE/sIgG4 were significantly lower in ineffective group than effective group (all P<0.05). The clinical response of SCIT related only to dust mite sIgE (r=0.29, P=0.036), and sIgE≥53.86 kU/L had the best sensitivity (77.78%) and specificity (57.89%) to predict effective SCIT in polysensitized AR patients. Conclusions: One-year dust mite SCIT is effective for polysensitized AR patients. Pre-treatment serum dust mite sIgE≥53.86 kU/L may play a role in predicting clinical response of dust mite SCIT in polysensitized AR patients.

Clot-based time attenuation curve as a novel imaging predictor of mechanical thrombectomy functional outcome in acute ischemia stroke.

To investigate whether a novel assessment of thrombus permeability obtained from perfusion computed tomography (CTP) can act as a more accurate predictor of clinical response to mechanical thrombectomy (MT) in acute ischemic stroke (AIS). We performed a study including two cohorts of AIS patients who underwent MT admitted to a single-center between April 2018 and February 2022: a retrospective development cohort (n = 71) and a prospective independent validation cohort (n = 96). Thrombus permeability was determined in terms of entire thrombus time-attenuation curve (TAC) on CTP. Association between thrombus TAC distributions and histopathological results was analyzed in the development cohort. Logistic regression was used to assess the performance of the TAC for predicting 90-day modified Rankin Scale (mRS) score, and good outcome was defined as a mRS score of ≤ 2. Basic clinical characteristics was used to build a routine clinical model. A combined model gathered TAC and basic clinical characteristics was also developed. The performance of the three models is compared on the independent validation set. Two TAC distributions were observed-unimodal (uTAC) and linear (lTAC). TAC distributions achieved strong correlations (|r|= 0.627, p < 0.001) with histopathological results, in which uTAC associated with fibrin- and platelet-rich clot while lTAC associated with red blood cell-rich clot. The uTAC was independently associated with poor outcome (odds ratio, 0.08 [95% confidence interval (CI), 0.02-0.31]; p < 0.001). TAC distributions yielded an AUC of 0.78 (95% CI, 0.70-0.87) for predicting clinical outcome. When combined clinical characteristics, the performance was significantly improved (AUC, 0.85 [95% CI, 0.76-0.93]; p < 0.001) and higher than routine clinical model (AUC, 0.69 [95% CI, 0.59-0.83]; p < 0.001). Thrombus TAC on CTP were found to be a promising new imaging biomarker to predict the outcomes of MT in AIS. This study revealed that clot-based time attenuation curve based on admission perfusion CT could reflect the permeability and composition of thrombus and, also, provide valuable information to predict the clinical outcomes of mechanical thrombectomy in patients with acute ischemia stroke. • Two time-attenuation curves distributions achieved strong correlations (|r|= 0.627, p < 0.001) with histopathological results. • The unimodal time-attenuation curve was independently associated with poor outcome (odds ratio, 0.08 [0.02-0.31]; p < 0.001). • The time-attenuation curve distributions yielded a higher performance for detecting clinical outcome than routine clinical model (AUC, 0.78 [0.70-0.87] vs 0.69 [0.59-0.83]; p < 0.001).

HER2 status as a potential predictive biomarker for ovarian clear cell carcinoma.

Ovarian clear cell carcinoma (OCCC) is a subtype of ovarian carcinoma characterized by unique biological features and highly malignant characteristics including low chemosensitivity. Therefore, new therapeutic targets are needed. These could include the downstream pathways of receptor tyrosine kinases, especially the human epidermal growth factor receptor 2 (HER2). Our main objective was to characterize the HER2 status using immunohistochemistry (IHC) and FISH on 118 OCCCs, also considering the novel paradigm of HER2-zero and HER2-low status. Other aims included determination of the association between HER2 status and survival, HER2 gene DNA and RNA NGS analysis, HER2 gene expression analysis, and correlation between IHC and gene expression in HER2-zero and HER2-low cases. Cases with HER2 overexpression/amplification accounted for 5.1% (6/118), with additional 3% harbouring HER2 gene mutation. The remaining 112 (94.9%) cases were HER2-negative. Of these, 75% were classified as HER2-zero and 25% as HER2-low. This percentage of HER2 aberrations is significant concerning their possible therapeutic influence. Cases from the HER2-zero group showed significantly better survival. Although this relationship lost statistical significance in multivariate analysis, the results have potential therapeutic significance. HER2 gene expression analysis showed a significant correlation with HER2 IHC status in the entire cohort (HER2-positive vs. HER2-negative), while in the cohort of only HER2-negative cases, the results did not reach statistical significance, suggesting that gene expression analysis would not be suitable to confirm the subdivision into HER2-low and HER2-zero. Our results also emphasize the need for standardized HER2 testing in OCCC to determine the best predictor of clinical response.

Systemic and functional effects of continuous azithromycin treatment in patients with severe chronic obstructive pulmonary disease and frequent exacerbations.

Continuous treatment with azithromycin may lead to fewer acute exacerbations of chronic obstructive pulmonary disease (AECOPD), but little is known of its impact on systemic and functional outcomes in real-life settings. This was a multicenter prospective observational study of patients with severe COPD who started treatment with azithromycin. Tests were compared at baseline and after 3 and 12 months of treatment. These included lung function tests, a 6-min walking test (6MWT), and enzyme-linked immunosorbent assays of serum and sputum markers, such as interleukins (IL-6, IL-8, IL-13, IL-5), tumor necrosis factor receptor 2 (TNFR2), and inflammatory markers. Incidence rate ratios (IRR) and their 95% confidence intervals (95% CI) are reported. Of the 478 eligible patients, the 42 who started azithromycin experienced reductions in AECOPDs (IRR, 0.34; 95% CI, 0.26-0.45) and hospitalizations (IRR, 0.39; 95% CI, 0.28-0.49). Treatment was also associated with significant improvement in the partial arterial pressure of oxygen (9.2 mmHg, 95% CI 1.4-16.9) at 12 months. While TNFR2 was reduced significantly in both serum and sputum samples, IL-13 and IL-6 were only significantly reduced in serum samples. Moreover, an elevated serum and sputum IL-8 level significantly predicted good clinical response to treatment. Continuous azithromycin treatment in a cohort of patients with severe COPD and frequent exacerbations can significantly reduce the number and severity of exacerbations and improve gas exchange. Treatment changes the pattern of microorganism isolates and decreases the inflammatory response. Of note, IL-8 may have utility as a predictor of clinical response to azithromycin treatment.

TDCS efficacy and utility of anhedonia and rumination as clinical predictors of response to tDCS in major depressive disorder (MDD)

BackgroundAnhedonia and rumination are mental disorders' transdiagnostic features but remain difficult to treat. Transcranial direct current stimulation (tDCS) is a proven treatment for depression, but its effects on anhedonia and rumination and whether anhedonia and rumination can be used as a predictive biomarker of treatment response is not well known. This study aimed to investigate the tDCS efficacy and identify the predictive role of anhedonia and rumination in response to tDCS in patients with MDD. Methods182 patients received 10 tDCS sessions delivered at 2 mA to left (anode) dorsolateral prefrontal cortex (DLPFC). Hamilton Rating Scale for Depression (HRSD-17), Snaith–Hamilton Pleasure Scale (SHAPS), and the 10-item Ruminative Response Scale (RRS-10) was administered to patients with MDD before treatment, following it, and after two weeks of tDCS. ResultsThere was an overall significant improvement in anhedonia from pre- to post-treatment. Regression analyses revealed that responders had higher baseline anhedonia and rumination (reflective pondering) scores. We found that the reduction in HRSD scores after tDCS was significantly associated with anhedonia's baseline values while no relation was found between baseline rumination and tDCS treatment response. ConclusionThese results provide new evidence that pronounced anhedonia may be a significant clinical predictor of response to tDCS. Patients with severe or low baseline rumination had an equal chance of achieving clinical response. Prospective tDCS studies are necessary to validate the predictive value of the derived model.

DNA methyltransferase inhibitor exposure-response: Challenges and opportunities.

Although DNA methyltransferase inhibitors (DNMTis), such as azacitidine and decitabine, are used extensively in the treatment of myelodysplastic syndromes and acute myeloid leukemia, there remain unanswered questions about DNMTi's mechanism of action and predictors of clinical response. Because patients often remain on single-agent DNMTis or DNMTi-containing regimens for several months before knowing whether clinical benefit can be achieved, the development and clinical validation of response-predictive biomarkers represents an important unmet need in oncology. In this review, we will summarize the clinical studies that led to the approval of azacitidine and decitabine, as well as the real-world experience with these drugs. We will then focus on biomarker development for DNMTis-specifically, efforts at determining exposure-response relationships and challenges that remain impacting the broader clinical translation of these methods. We will highlight recent progress in liquid-chromatography tandem mass spectrometry technology that has allowed for the simultaneous measurement of decitabine genomic incorporation and global DNA methylation, which has significant potential as a mechanism-of-action based biomarker in patients on DNMTis. Last, we will cover important research questions that need to be addressed in order to optimize this potential biomarker for clinical use.

Using pre-treatment de novo threat conditioning outcomes to predict treatment response to DCS augmentation of exposure-based CBT

BackgroundOver a decade and a half of research has resulted in inconsistent evidence for the efficacy of d-cycloserine (DCS), a partial glutamatergic N-methyl-D-aspartate agonist, for augmenting exposure-based cognitive behavioral therapy (CBT) for anxiety- and fear-based disorders. These variable findings have motivated the search for moderators of DCS augmentation efficacy. MethodsIn this secondary analysis of a previous randomized clinical trial, we evaluated the value of de novo threat conditioning outcomes—degree of threat acquisition, extinction, and extinction retention—for predicting treatment response to exposure-based CBT for social anxiety disorder, applied with and without DCS augmentation in a sample of 59 outpatients. ResultsWe found that average differential skin conductance response (SCR) during extinction and extinction retention significantly moderated the prediction of clinical response to DCS: participants with poorer extinction and extinction retention showed relatively improved treatment response with DCS. No such effects were found for expectancy ratings, consistent with accounts of DCS selectively aiding lower-order but not higher-order extinction learning. ConclusionsThese findings provide support for extinction and extinction retention outcomes from threat conditioning as potential pre-treatment biomarkers for DCS augmentation benefits. Independent of DCS augmentation, the current study did not support threat conditioning outcomes as useful for predicting response to exposure-based CBT.

Heterogeneity of Response to Methylphenidate in Apathetic Patients in the ADMET 2 Trial

The Apathy in Dementia Methylphenidate Trial 2 (ADMET 2) found that methylphenidate was effective in treating apathy with a small-to-medium effect size but showed heterogeneity in response. We assessed clinical predictors of response to help determine individual likelihood of treatment benefit from methylphenidate. Univariate and multivariate analyses of 22 clinical predictors of response chosen a priori. Data from the ADMET 2 randomized, placebo controlled multi-center clinical trial. Alzheimer's disease patients with clinically significant apathy. Apathy assessed with the Neuropsychiatric Inventory apathy domain (NPI-A). In total, 177 participants (67% male, mean [SD] age 76.4 [7.9], mini-mental state examination 19.3 [4.8]) had 6-months follow up data. Six potential predictors met criteria for inclusion in multivariate modeling. Methylphenidate was more efficacious in participants without NPI anxiety (change in NPI-A -2.21, standard error [SE]:0.60) or agitation (-2.63, SE:0.68), prescribed cholinesterase inhibitors (ChEI) (-2.44, SE:0.62), between 52 and 72 years of age (-2.93, SE:1.05), had 73-80 mm Hg diastolic blood pressure (-2.43, SE: 1.03), and more functional impairment (-2.56, SE:1.16) as measured by the Alzheimer's Disease Cooperative Study Activities of Daily Living scale. Individuals who were not anxious or agitated, younger, prescribed a ChEI, with optimal (73-80 mm Hg) diastolic blood pressure, or having more impaired function were more likely to benefit from methylphenidate compared to placebo. Clinicians may preferentially consider methylphenidate for apathetic AD participants already prescribed a ChEI and without baseline anxiety or agitation.