Biomarkers Of Treatment Response Research Articles

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes in patients. The clinical challenge lies in identifying those patients at highest risk for developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathologic, histologic or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality of OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Machine-learning based biomarkers, such as S100A7, demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry (mIHC) workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Updates on the natural history and clinical characteristics of NSAID-ERD

Nonsteroidal Anti-Inflammatory Drug Exacerbated Respiratory Disease (NSAID-ERD) is a distinct clinical syndrome characterized by NSAID hypersensitivity, asthma, and nasal polyposis. Its diagnosis is challenging due to variable presentations and a lack of simple tests, leading to diagnostic delays. Recent research has revealed its genetic predispositions, environmental triggers, and associations with atopy and second-hand tobacco smoke exposure or smoking cessation. Despite its severity, diagnostic awareness remains low, leading to the delay in effective management. Therapeutically, NSAID-ERD necessitates multidisciplinary approaches, often combining surgical interventions with medical management, including aspirin desensitization and biologic agents. However, predictive biomarkers for treatment response remain elusive. Understanding the underlying mechanisms driving NSAID-ERD pathogenesis and identifying reliable biomarkers are crucial for enhancing diagnostic accuracy and refining targeted therapeutic strategies for this debilitating condition. This review aims to provide a thorough understanding of NSAID-ERD, covering its history, clinical features, epidemiology, diagnosis, systemic and molecular biomarkers, available treatment options, and avenues for future research.

Advances in metabolomics in critically ill patients with Sepsis and Septic Shock.

Sepsis accounts for high cases of morbidity and mortality in hospitalized patients. It has a very complex pathophysiology and swiftly progresses to a severe form of the disease, such as septic shock leading to organ dysfunction, organ failure, and death. Metabolomics has transformed sepsis's clinical and research topography with its application in prognosis, diagnosis, and risk assessment in patients with sepsis and septic shock. Metabolites in blood and urine are detected and analyzed, which helps in understanding the pathogenesis of the disease and aid in better disease management by identifying biomarkers early on. Metabolomics, sepsis and septic shock were the keywords were searched in PubMed and Scopus, from its inception to Dec 2023. This article provides information regarding metabolic profiling performed in sepsis and septic shock We demonstrated that metabolomics will change the world of sepsis by analyzing and detecting the diagnosis, prognosis, mortality, and treatment response biomarkers.

N100 as a response prediction biomarker for accelerated 1 Hz right DLPFC-rTMS in major depression

Background and objectiveRepetitive transcranial magnetic stimulation (rTMS) is a safe and effective treatment for major depressive disorder (MDD); however, this treatment currently lacks reliable biomarkers of treatment response. TMS-evoked potentials (TEPs), measured using TMS-electroencephalography (TMS-EEG), have been suggested as potential biomarker candidates, with the N100 peak being one of the most promising. This study investigated the association between baseline N100 amplitude and 1 Hz right dorsolateral prefrontal cortex (R-DLPFC) accelerated rTMS (arTMS) treatment in MDD. MethodsBaseline TMS-EEG sessions were performed for 23 MDD patients. All patients then underwent 40 sessions of 1 Hz R-DLPFC (F4) arTMS over 5 days and a follow-up TMS-EEG session one week after the end of theses arTMS sessions. ResultsBaseline N100 amplitude at F4 showed a strong positive association (p < .001) with treatment outcome. The association between the change in N100 amplitude (baseline to follow-up) and treatment outcome did not remain significant after Bonferroni correction (p = .06, corrected; p = .03, uncorrected). Furthermore, treatment responders had a significantly larger mean baseline F4 TEP amplitude during the N100 time frame compared to non-responders (p < .001). Topographically, after Bonferroni correction, F4 is the only electrode at which its baseline N100 amplitude showed a significant positive association (p < .001) with treatment outcome. LimitationsLack of control group and auditory masking. ConclusionBaseline N100 amplitude showed a strong association with treatment outcome and thus demonstrated great potential to be utilized as a cost-effective and widely adoptable biomarker of rTMS treatment in MDD.

Molecular and Pathobiology of Canine Mammary Tumour: Defining a Translational Model for Human Breast Cancer.

Canine mammary tumours (CMT) have histological, clinicopathological and molecular resemblances to human breast cancer (HBC), positioning them as viable models for studying the human disease. CMT initiation and progression occur spontaneously in immune-competent animals, which challenge the suggested limitations of genetically modified mice, also enabling the evaluation of immunotherapies in canine patients. Dogs have shorter life expectancy compared to humans, and cancer advances more rapidly in this species. This makes it possible to perform studies about the clinical efficacy of new therapeutic modalities in a much shorter time than in human patients. The identification of biomarkers for tumour subtypes, progression and treatment response paves the way for the development of novel therapeutic and diagnostic approaches. This review addresses the similarities between CMT and HBC and the molecular signatures identified in CMT samples that have been explored to date. We proposed a detailed molecular exploration of the CMT stroma using state-of-the-art methods in transcriptomics and proteomics. Using CMT as an analog for HBC not only helps to understand the complexities of the disease, but also to advance comparative oncology to the next level to prove the claim of dogs as a valid translational model.

Metabolic Response to Small Molecule Therapy in Colorectal Cancer Tracked with Raman Spectroscopy and Metabolomics.

Despite numerous screening tools for colorectal cancer (CRC), 25% of patients are diagnosed with advanced disease. Novel diagnostic technologies that are early, accurate, and rapid are imperative to assess the therapeutic efficacy of clinical drugs and identify new biomarkers of treatment response. Here Raman spectroscopy (RS) was used to track metabolic reprogramming in KRAS-mutant HCT116 and SW837 cells, and KRAS wild-type CC cells. RS combined with multivariate analysis methods distinguished nonresponsive, partially responsive, and responsive cells treated with cetuximab, a monoclonal antibody for EGFR inhibition, sotorasib, a clinically approved KRAS inhibitor, and various doses of trametinib, an inhibitor of the MAPK pathway. Cells treated with a combination of subtoxic doses of trametinib and BKM120, an inhibitor of the PI3K pathway, showed a synergistic response between the two pathways. Using a supervised machine learning regression model, we established a scoring methodology trained to a priori predict therapeutic response to new treatment combinations. RS metabolites were verified with mass spectrometry, and enrichment pathways were identified, including amino acid, purine, and nicotinate and nicotinamide metabolism that differentiated monotherapy from combination therapy. Our approach may ultimately be applicable to patient-derived primary cells and cultures of patient tumors to predict effective drugs for individualized care.

Association of autoantibody concentrations and trajectories with lupus nephritis histological features and treatment response.

Autoantibodies are a hallmark of lupus nephritis (LN), but their association with LN classes and treatment response are not adequately known. In this study, we quantified circulating autoantibodies in the Accelerating Medicines Partnership (AMP) LN longitudinal cohort to identify serological biomarkers of LN histological classification and treatment response, and how these biomarkers change over time based on treatment response. Peripheral blood samples were collected from 279 SLE patients undergoing diagnostic kidney biopsy based on proteinuria. Of these, 268 were diagnosed with LN. Thirteen autoantibody specificities were measured by bead-based assays (Bio-Rad Bioplex 2200) and anti-C1q by ELISA at the time of biopsy (baseline) and at 3-, 6-, and 12-months post-biopsy. Clinical response was determined at 12 months. Proliferative LN (ISN/RPS class III/IV+V, n=160) was associated with higher concentrations of anti-C1q, -chromatin, -dsDNA, and -ribosomal P autoantibodies compared to non-proliferative LN (classes I/II/V/VI, n=108). Anti-C1q and-dsDNA were independently associated with proliferative LN. In proliferative LN, higher baseline anti-C1q levels predicted complete response (AUC, 0.72; p, 0.002) better than baseline proteinuria (0.59; 0.21). Furthermore, all autoantibody levels, except for anti-La/SSB, decreased over 12 months in proliferative, but not membranous, LN patients with a complete response. Baseline levels of anti-C1q and -dsDNA may serve as noninvasive biomarkers of proliferative LN, and anti-C1q may predict complete response at the time of kidney biopsy. In addition, tracking autoantibodies over time may provide further insights into treatment response and pathogenic mechanisms in proliferative LN patients.

Early ctDNA kinetics as a dynamic biomarker of cancer treatment response.

Circulating tumor DNA assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. We develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes, and utilize them to simulate randomized virtual patient cohorts to test candidate biomarkers. Using this approach, we propose specific biomarkers, based on ctDNA longitudinal features, for targeted therapy, chemotherapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort dataset. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation - which we hypothesize to hold valuable prognostic information on longer-term treatment response. This study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biological mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment, and generates hypotheses for further clinical testing.

Evaluating the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic and treatment response biomarkers in stage IV colorectal cancer patients

Evaluating the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic and treatment response biomarkers in stage IV colorectal cancer patients

Asymmetric Dimethylarginine and NT-proBNP Levels Provide SynergisticInformation in PulmonaryArterial Hypertension.

Plasma asymmetric dimethylarginine (ADMA) is elevated in pulmonary arterial hypertension (PAH) and is associated with unfavorable outcomes. The aim of this study was to assess changes in ADMA plasma levels for monitoring disease progression and outcomes during PAH-specific therapy. ADMA was measured at baseline and after at least 6months of follow-up using enzyme-linked immunosorbent assay and high-performance liquid chromatography. Changes in ADMA were analyzed in relation to changes in established PAH markers, including hemodynamic status, N-terminal pro-brain natriuretic peptide (NT-proBNP) and risk assessment scores. Impact on survival was assessed using Kaplan-Meier curves and Cox proportional hazards models. Between 2008 and 2019, ADMA samples were collected prospectively from 215 patients with PAH. Change in ADMA plasma level was a predictor of disease progression and survival. ΔADMA (median-0.03μmol/L; 95%CI:-0.145 to 0.0135) was correlated with change in mean pulmonary arterial pressure (P< 0.005; rS=0.287) but was not significantly correlated with ΔNT-proBNP (P=0.056; rS=0.135). Patients with decreased ADMA plasma levels at follow-up had better 3-year and 5-year survival rates (88% and 80%, respectively, vs 72% and 53% in those without decreases in ADMA) (P< 0.005; pulmonary hypertension-related mortality or lung transplantation). Patients with decreases in both ADMA and NT-proBNP had better survival rates compared with patients in whom only 1 parameter improved (P< 0.005). ΔADMA was a significant predictor of survival in Cox regression analysis and also when corrected for ΔNT-proBNP (HRs: 1.27 and 1.35, respectively; P< 0.005). ADMA and NT-proBNP provide synergistic prognostic information for patients with PAH. ADMA could be used as an objective and distinct biomarker for monitoring treatment response in PAH.

Potentiation of the muscarinic acetylcholine receptor 1 modulates neurophysiological features in a mouse model of Rett syndrome

Rett syndrome (RTT) is a neurodevelopmental disorder primarily caused by mutations in the X chromosome-linked gene Methyl-CpG Binding Protein 2 (MECP2). Restoring MeCP2 expression after disease onset in a mouse model of RTT reverses phenotypes, providing hope for development of treatments for RTT. Translatable biomarkers of improvement and treatment responses have the potential to accelerate both preclinical and clinical evaluation of targeted therapies in RTT. Studies in people with and mouse models of RTT have identified neurophysiological features, such as auditory event-related potentials, that correlate with disease severity, suggesting that they could be useful as biomarkers of disease improvement or early treatment response. We recently demonstrated that treatment of RTT mice with a positive allosteric modulator (PAM) of muscarinic acetylcholine subtype 1 receptor (M1) improved phenotypes, suggesting that modulation of M1 activity is a potential therapy in RTT. To evaluate whether neurophysiological features could be useful biomarkers to assess the effects of M1 PAM treatment, we acutely administered the M1 PAM VU0486846 (VU846) at doses of 1, 3, 10 and 30 ​mg/kg in wildtype and RTT mice. This resulted in an inverted U-shaped dose response with maximal improvement of AEP features at 3 ​mg/kg but with no marked effect on basal EEG power or epileptiform discharges in RTT mice and no significant changes in wildtype mice. These findings suggest that M1 potentiation can improve neural circuit synchrony to auditory stimuli in RTT mice and that neurophysiological features have potential as pharmacodynamic or treatment-responsive biomarkers for preclinical and clinical evaluation of putative therapies in RTT.

Des-gamma-carboxy prothrombin (DCP) as a prognostic biomarker in patients with advanced hepatocellular carcinoma treated with atezolizumab/bevacizumab.

e16167 Background: Causes of variable disease response to first-line treatment with atezolizumab plus bevacizumab in patients with advanced hepatocellular carcinoma (HCC) remain unclear. Identifying tumor markers that predict treatment response and provide prognostic information may help clinicians optimize treatment strategies and patient outcomes. The role of des-gamma-carboxy prothrombin (DCP) is not well established in Hepatitis B Virus non-endemic areas. This study aimed to investigate DCP as a predictive biomarker of treatment response as well as explore prognostic implications of DCP in patients with advanced HCC. Methods: This single-center retrospective analysis evaluated DCP and radiographic response in patients with advanced HCC who received atezolizumab/bevacizumab in the first-line setting. DCP was measured at the time of best response, determined by radiographic evaluation, and compared to day one of atezolizumab/bevacizumab initiation. Elevated DCP was defined as &gt; = 7.5 ng/mL. DCP response was defined as a decrease of &gt; = 50% at response assessment compared with baseline. Comparisons of treatment effects were performed using two-tailed Fisher Exact Probability Test. Overall survival (OS) was defined as the interval between the first treatment and either the date of death or the last follow-up visit. OS was analyzed using the Kaplan–Meier method and compared between groups using the log-rank test. Results: A total of 53 patients with advanced HCC treated with atezolizumab/bevacizumab were included. Radiographic treatment responses were complete response 3.8%, partial response 22.6%, stable disease 52.8% and progression of disease 20.8%, respectively. On day one of treatment 70% of patients had an elevated DCP. Patients with DCP response had ORR of 69% (odds ratio, 15.75; 95% CI, 3.50 – 70.9; p = 0.0002) and disease control rate of 100% (p = 0.047). Conversely, patients with &gt; = 50% increase in DCP at response evaluation compared to day one of treatment had ORR of 4.5% and no response rate of 95% (p = 0.0035). Furthermore, patients who had &gt; = 50% increase in DCP had median OS of 15.4 months compared to patients without &gt; = 50% increase in DCP who had median OS of 28.4 months (HR = 2.48; 95% CI, 1.035 – 5.93; p = 0.042). There was no difference in ORR, or OS, between patients who had elevated DCP on day one of treatment and those who did not. Conclusions: DCP response correlates with objective radiographic response in patients with advanced HCC treated with atezolizumab plus bevacizumab in the first-line setting. DCP increase of &gt; = 50% correlates with decreased median OS and may serve as a negative prognostic biomarker in such patients.

Clinical and analytical validation for HRD status using targeted panel sequencing.

e17501 Background: In cancer therapy, understanding homologous recombination deficiency (HRD) is paramount, particularly due to its positive association with sensitivity to PARP inhibitor (PARPi) therapy. We propose using a targeted sequencing approach as a cost-effective and efficient alternative to the current standard of whole genome sequencing (WGS). In this study, we determine the sensitivity and clinical applications of a panel of 437 genes and over 12000 heterozygous SNP loci for evaluating HRD. Methods: HRD positivity for this assay was set at an HRD score of ≥38. To determine the limit of detection (LOD), we diluted 19 samples (4 tiers, 20 repeats each) with known HRD status. Accuracy of the assay was determined by comparing HRD status calls of 40 samples with those obtained through whole genome sequencing. Reproducibility of the assay was tested by measuring variance of HRD status for 30 samples between experimental conditions (2 operators* 3 repeats). Samples were obtained from 85 ovarian cancer (OC) patients undergoing platinum-based (Pt) chemotherapy and were profiled using our targeted sequencing assay. Results: The LOD for BRAC1/2 copy number deletions was established at a tumor purity (TP) of 30%. On the level of individual mutations, LODs range between 1.74% to 5.85% AF with a median of 2.26% AF. Repeatability analysis yields high concordance (APA= 97.83%, 95%CI= 95.34% - 99.00%; ANA= 97.73%, 95%CI= 95.13% - 98.95%), which emphasizes the precision of the assay. Comparisons against WGS based HRD scores reveal strong correlations, with Pearson coefficients of 0.975 for single sample (tumor sample only) and 0.987 for paired sample (tumor + normal sample) HRD score analysis. Through tumor profiling, we identified novel gene mutations associated with resistance to PARPi therapy in the HRD-positive population of our cohort. In the clinical setting, HRD-positive OC patients were found to experience longer progression free survival than their HRD-negative counterparts (median PFS = 18.3 vs 11.4 months, p&lt;0.05). Upon further investigation, we observed that HRD-positive patients who did not carry pathogenic alterations on BRCA1/2 gene showed significantly longer PFS than HRD-negative patients without pathogenic BRCA1/2 alterations (median PFS = 18.5 vs 11.6 months, p&lt;0.05). Conclusions: In summary, this targeted panel offers enhanced sensitivity, reliability, and precision in the assessment of HRD status for informed cancer therapy decisions. In practice, we showed that the targeted sequencing approach is a viable solution for determining HRD status of OC patients and can potentially serve as a predictive biomarker for treatment response. We believe that out assay emerges as a cornerstone in the advancement of personalized cancer care, and offers a sensitive, reliable, and precise approach to HRD assessment for improving patient outcomes.

A phase II trial of olaparib and durvalumab in patients with recurrent IDH-mutated gliomas.

2013 Background: Isocitrate dehydrogenase mutations (IDHmt) define astrocytomas and oligodendrogliomas. IDHmt results in accumulation of R-2-hydroxyglutarate (2HG), leading to epigenetic dysregulation and defective homologous recombination repair, providing a rationale for poly (adenosine 5’-diphophate-ribose) polymerase (PARP) inhibitors. PARP inhibition upregulates PD-L1 so the combination with immune checkpoint inhibition is potentially synergistic. Methods: Patients (pts) with recurrent high-grade IDHmt gliomas were enrolled in this phase II open-label study (NCT03991832). Eligibility included progressive disease with up to 2 prior lines of systemic therapies and ECOG 0–1. Pts received olaparib 300 mg twice daily continuously and durvalumab 1500 mg IV every 4 weeks. Simon’s optimal two-stage design was used. The primary objective was overall response rate (ORR) and disease control rate (DCR) by RANO criteria. Secondary objectives included overall survival (OS), progression free survival (PFS) and safety.Exploratory biomarkers of response and resistance were assessed with serial blood samples using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as well as multiplex-immunohistochemistry. Results: In the 29 pts enrolled between January 2020–February 2023, median age was 40.5 (range 23–66) and 41% were female. Initial tumor grade was 2 in 9, 3 in 8 and 4 in 12 pts, respectively. Median time to enrollment from tumour diagnosis was 5.9 years. All had prior resection and median number of prior systemic therapies was 2. One patient clinically deteriorated before starting treatment. ORR was 10%, 95% CI 2.2–27%, with responses in 3 pts. One pt with grade 4 astrocytoma had a complete response and remains on treatment after 33 months. The other 2 responders with grade 4 astrocytoma had response durations of 4.1 and 9.8 months. DCR was 28% (95% CI 12.7–47.2%) with 5 additional pts demonstrating stable disease. With a median follow-up of 33 months, mOS was 9.5 months (95% CI 4.3–19.3) and mPFS was 1.9 months (95% CI 1.8–3.0). There was no treatment-related grade 3–4 toxicities. Any grade toxicities included fatigue (48%), nausea (17%), diarrhea (10%), and cytopenias (3%). Using serial cfMeDIP-seq, cell free DNA methylomes comparing responders versus progressors using the top differentially methylated regions can predict treatment response with high accuracy (AUC 0.833). Post progression, differentially methylated genes converge on TGF-β and signal transduction pathways, suggesting possible mechanisms of resistance. Multi-modal analysis of long-term responders will additionally be presented. Conclusions: Combination treatment with olaparib and durvalumab for pts with IDHmt glioma is well tolerated but has limited efficacy in unselected pts. cfMeDIP-seq can reliably predict tumour progression providing a blood-based biomarker of treatment response. Clinical trial information: NCT03991832 .

Tracking the FDA precision oncology drug approval landscape in OncoKB.

e13507 Background: OncoKB ( www.oncokb.org ), Memorial Sloan Kettering's (MSK) precision oncology knowledge base, is a comprehensive database that provides curated information about the oncogenic effect and clinical implications of genomic alterations in cancer. OncoKB assigns evidence-based levels of clinical actionability to individual mutational events in a tumor type-specific context and is the first somatic variant database to be partially recognized by the US-FDA. As of February 2024, OncoKB contains annotations for &gt;7600 alterations in &gt;840 cancer-associated genes, including 59 level-1 or 2 genes (standard care, specified in the FDA-drug label or professional guidelines), 8 level-3A and 12 level-4 genes (predictive of drug response based on well-powered clinical studies or compelling biological evidence respectively). As the field of precision oncology continues to evolve with the identification of new molecular targets and development of novel drug/drug combinations, we sought to provide OncoKB users with a resource that quantitates the landscape of FDA-approved precision oncology therapies in real-time. Methods: To provide clinicians with an easily accessible and transparent list of FDA-approved drugs that require molecular biomarker testing to determine patient eligibility for use of the drug, we curated and categorized all FDA-approved oncology drugs from the FDA’s Oncology / Hematologic Malignancies Approval Notifications webpage from 1998 to present. For each drug we recorded its mechanism of action and whether it qualifies as a targeted therapy (a cancer drug that binds to or inhibits a specific protein target) or a precision oncology therapy (a drug that is most effective in a molecularly defined subset of patients and for which pre-treatment molecular profiling is required for optimal patient selection). For all precision oncology therapies we further listed the FDA-recognized biomarker(s) from the FDA-drug label and determined whether a DNA-based method could be used for biomarker detection. The data are publicly available via an interactive and downloadable table on OncoKB’s Oncology Therapies page , which is updated on a bi-monthly basis. Results: Between June 1998 and January 2024, 217 novel oncology drugs were FDA-approved, 83.4% (n=181) of which were classified as targeted therapies. Greater than half (51.9%, n=94) of targeted therapies were classified as precision oncology therapies. Currently, 52 genes as well as MSI-H and TMB-H status are FDA-recognized biomarkers of treatment response. Over the past five years, 75 novel oncology drugs were FDA-approved, 46 (61.3%) of which were precision oncology therapies. Conclusions: OncoKB’s publicly available Oncology Therapies page provides insight into the pace of growth of the precision oncology drug landscape and serves as a complementary tool for clinicians who utilize OncoKB to determine whether a patient with cancer should receive biomarker testing.

Targeting replication stress in pancreatic cancer: A phase II trial investigating azenosertib in combination with gemcitabine in second-line advanced pancreatic cancer.

TPS4211 Background: A major unmet need in pancreatic cancer (PDAC) is molecularly targeted treatment options for patients who develop resistance to first-line platinum chemotherapy. While combined gemcitabine and nab-paclitaxel is commonly used after progression with first-line therapy, the efficacy in the second-line setting is fair, with recent phase clinical trial data demonstrating a median progression-free survival (PFS) of 2.7 months and a median overall survival of 6.6 months (1). In recent years, preclinical work has identified that replication stress is a potential PDAC vulnerability. The WEE1 kinase regulates the checkpoint governing the G2/M transition of the cell cycle to compensate for replication stress. The G2/M checkpoint is critically important in malignancies like PDAC where over 75% of tumors have p53 pathway deficits. Therapies that inhibit cancer cells’ ability to compensate for replication stress are particularly attractive in cancers that have genomic alterations that generate replication stress. It has been demonstrated that in vitro and in vivo PDAC models were exquisitely sensitive to WEE1 inhibition in combination with gemcitabine. Azenosertib (Zn-c3) is an orally available, highly selective, nanomolar inhibitor of the WEE1 kinase and when combined with gemcitabine in PDAC cell lines, synergistic cytotoxicity is observed. Methods: NCT06015659 is an ongoing phase II clinical trial with safety lead-in that is testing the azenosertib WEE1 inhibitor combined with gemcitabine in patients with advanced pancreatic cancer after progression or intolerance with FOLFIRINOX. Subjects are dosed once daily, days 1-5, 8-12, and 15-19 with azenosertib and receive gemcitabine 800 mg/m2 on days 1 and 8 of 21-day cycles. Up to 12 subjects are expected to enroll in the safety lead-in portion based on a typical 3 + 3 design. Once the recommended phase 2 dose is confirmed, we will use a Simon two-stage minimax design to evaluate efficacy where the null hypothesis is that the true 6-month PFS rate is ≤ 24% (unacceptable historical control data) and the alternative hypothesis is that the true 6-month PFS is ≥ 44%. Pretreatment and on-treatment tumor biopsies are incorporated into the trial to identify potential biomarkers of treatment response. Subjects must be able to swallow oral tablets and have measurable disease by RECIST v1.1; prior exposure to gemcitabine is not allowed. Enrollment began November 21, 2023, and is ongoing. 1. Huffman BM, Basu Mallick A, Horick NK, et al. JAMA Netw Open. 2023;6(1):e2249720. Clinical trial information: NCT06015659 .

Evaluating Mineral Biomarkers as Mediators and Moderators of Behavioural Improvements in a Randomized Controlled Trial of Multinutrients for Children with ADHD.

Essential minerals are cofactors for synthesis of neurotransmitters supporting cognition and mood. An 8-week fully-blind RCT of multinutrients for ADHD demonstrated three times as many children (age 6-12) had significantly improved behavior ("treatment responders") on multinutrients (54%) compared to placebo (18%). The aim of this secondary study was to evaluate changes in fasted plasma and urinary mineral concentrations following the intervention, and their role as mediators and moderators of treatment response. Fourteen essential or trace minerals were measured in plasma and/or urine at baseline and week 8 from 86 participants (49 multinutrient, 37 placebo). Two-sample t-tests/Mann-Whitney U-tests compared 8-week change between treatment and placebo groups, which were also evaluated as potential mediators. Baseline levels were evaluated as potential moderators, using logistic regression models with clinical treatment response as the outcome. After 8 weeks, plasma boron, chromium (in females only), lithium, molybdenum, selenium, and vanadium, and urinary iodine, lithium, and selenium increased more with multinutrients than placebo, while plasma phosphorus decreased. These changes did not mediate treatment response. However, baseline urinary lithium trended toward moderation: participants with lower baseline urinary lithium were more likely to respond to multinutrients (p=0.058). Additionally, participants with higher baseline iron were more likely to be treatment responders regardless of treatment group (p=0.036.) These results show that multinutrient treatment response among children with ADHD is independent of their baseline plasma mineral levels, while baseline urinary lithium levels show potential as a non-invasive biomarker of treatment response requiring further study.

Clinical predictive factors and imaging biomarkers of treatment response to half dose PDT in patients with chronic central serous chorioretinopathy

PurposeTo determine the clinical and imaging biomarkers of the response to half-dose photodynamic therapy (HD-PDT) in patients with central serous chorioretinopathy (CSC) MethodsClinical records and baseline ophthalmic images of 67 chronic CSC patients who underwent HD-PDT were assessed. In addition to demographic data, optical coherence tomography (OCT), fluorescein angiography (FA) and fundus autofluorescence (FAF) images were analyzed for specific biomarkers. The patients were categorized to early responder and late responder based on the time needed for complete resolution of subretinal fluid after PDT (less than 1 month vs. more than 1 month). The baseline clinical and imaging biomarkers were compared between the two groups. ResultsSeventy-three eyes of 67 patients were included in the study. The mean response time to PDT was 1.63 ± 1.48 months with 82.2% (60/73) of eyes categorized as early responder. The mean response time to PDT in delayed-response group was 4.15±1.51 months. In multivariate analysis, delayed response to PDT was associated with lacking history of systemic corticosteroid consumption, lacking history of pretreatment with eplerenone or acetazolamide before PDT and presence of hyperreflective foci in baseline OCT images (all p values < 0.05). There was no association between final visual outcome and late response to PDT. ConclusionThe presence of inflammatory biomarkers such as hyperreflective foci in baseline OCT images might be indicative of resistance to PDT. Moreover, the effect of pretreatment with mineralocorticoid antagonist on the response to PDT in chronic CSC should be explored in future prospective studies.

Clinical implications of brain asymmetries.

No two human brains are alike, and with the rise of precision medicine in neurology, we are seeing an increased emphasis on understanding the individual variability in brain structure and function that renders every brain unique. Functional and structural brain asymmetries are a fundamental principle of brain organization, and recent research suggests substantial individual variability in these asymmetries that needs to be considered in clinical practice. In this Review, we provide an overview of brain asymmetries, variations in such asymmetries and their relevance in the clinical context. We review recent findings on brain asymmetries in neuropsychiatric and neurodevelopmental disorders, as well as in specific learning disabilities, with an emphasis on large-scale database studies and meta-analyses. We also highlight the relevance of asymmetries for disease symptom onset in neurodegenerative diseases and their implications for lateralized treatments, including brain stimulation. We conclude that alterations in brain asymmetry are not sufficiently specific to act as diagnostic biomarkers but can serve as meaningful symptom or treatment response biomarkers in certain contexts. On the basis of these insights, we provide several recommendations for neurological clinical practice.

The Role of EEG microstates in predicting oxcarbazepine treatment outcomes in patients with newly-diagnosed focal epilepsy

PurposeMicrostates represent the global and topographical distribution of electrical brain activity from scalp-recorded EEG. This study aims to explore EEG microstates of patients with focal epilepsy prior to medication, and employ extracted microstate metrics for predicting treatment outcomes with Oxcarbazepine monotherapy. MethodsThis study involved 25 newly-diagnosed focal epilepsy patients (13 females), aged 12 to 68, with various etiologies. Patients were categorized into Non-Seizure-Free (NSF) and Seizure-Free (SF) groups according to their first follow-up outcomes. From pre-medication EEGs, four representative microstates were identified by using clustering. The temporal parameters and transition probabilities of microstates were extracted and analyzed to discern group differences. With generating sample method, Support Vector Machine (SVM), Logistic Regression (LR), and Naïve Bayes (NB) classifiers were employed for predicting treatment outcomes. ResultsIn the NSF group, Microstate 1 (MS1) exhibited a significantly higher duration (mean±std. = 0.092±0.008 vs. 0.085±0.008, p = 0.047), occurrence (mean±std. = 2.587±0.334 vs. 2.260±0.278, p = 0.014), and coverage (mean±std. = 0.240±0.046 vs. 0.194±0.040, p = 0.014) compared to the SF group. Additionally, the transition probabilities from Microstate 2 (MS2) and Microstate 3 (MS3) to MS1 were increased. In MS2, the NSF group displayed a stronger correlation (mean±std. = 0.618±0.025 vs. 0.571±0.034, p < 0.001) and a higher global explained variance (mean±std. = 0.083±0.035 vs. 0.055±0.023, p = 0.027) than the SF group. Conversely, Microstate 4 (MS4) in the SF group demonstrated significantly greater coverage (mean±std. = 0.388±0.074 vs. 0.334±0.052, p = 0.046) and more frequent transitions from MS2 to MS4, indicating a distinct pattern. Temporal parameters contribute major predictive role in predicting treatment outcomes of Oxcarbazepine, with area under curves (AUCs) of 0.95, 0.70, and 0.86, achieved by LR, NB and SVM, respectively. ConclusionThis study underscores the potential of EEG microstates as predictive biomarkers for Oxcarbazepine treatment responses in newly-diagnosed focal epilepsy patients.