Predictive Biomarkers Of Response Research Articles

Randomized, open-label, phase 2 study of nivolumab plus ipilimumab or nivolumab monotherapy in patients with advanced or metastatic solid tumors of high tumor mutational burden

BackgroundCheckpoint inhibitor therapy has demonstrated overall survival benefit in multiple tumor types. Tumor mutational burden (TMB) is a predictive biomarker for response to immunotherapies. This study evaluated the efficacy of...

Comprehensive pancancer analysis reveals that LPCAT1 is a novel predictive biomarker for prognosis and immunotherapy response.

Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is a crucial enzyme involved in phospholipid metabolism and is essential for maintaining the structure and functionality of biofilms. However, a comprehensive examination of the role of LPCAT1 across various cancer types is lacking. Multiple public databases have been utilized to examine LPCAT1 expression, genetic alterations, methylation, prognosis, biological function, and its relationship with antitumor immunity in different cancer types. The function of LPCAT1 in glioma, breast cancer and liver cancer cells was further verified using in vitro experiments. Our research indicated that LPCAT1 is upregulated in various cancers and is accompanied by a wide range of amplification mutations. Higher LPCAT1 expression was associated with poorer prognosis across multiple cancers. Further in vitro experiments demonstrated that interfering with LPCAT1 expression increased apoptosis in glioma, breast cancer and liver cancer cells and concurrently suppressed their proliferation and migration. Functional enrichment analysis revealed that LPCAT1-associated genes were primarily enriched in immune and cancer progression pathways, such as the JAK/STAT, MYC, and EMT, etc. Moreover, LPCAT1 expression was closely associated with immune cell infiltration and immune checkpoint-related gene expression. Interestingly, LPCAT1 expression levels were generally higher in patients in the immunotherapy response group. The combination of LPCAT1 and PDL1 serves as an effective predictor of immunotherapy response. In conclusion, LPCAT1 is involved in immune regulation and tumor progression and holds promise as a biomarker for predicting patient outcomes and immunotherapy efficacy.

Interventional Oncology: 2024 Update.

Interventional Oncology (IO) stands at the forefront of transformative cancer care, leveraging advanced imaging technologies and innovative interventions. This narrative review explores recent developments within IO, highlighting its potential impact facilitated by artificial intelligence (AI), personalized medicine and imaging innovations. The integration of AI in IO holds promise for accelerating tumour detection and characterization, guiding treatment strategies and refining predictive models. Imaging modalities, including functional MRI, PET and cone beam CT are reshaping imaging and precision. Navigation, fusion imaging, augmented reality and robotics have the potential to revolutionize procedural guidance and offer unparalleled accuracy. New developments are observed in embolization and ablative therapies. The pivotal role of genomics in treatment planning, targeted therapies and biomarkers for treatment response prediction underscore the personalization of IO. Quality of life assessment, minimizing side effects and long-term survivorship care emphasize patient-centred outcomes after IO treatment. The evolving landscape of IO training programs, simulation technologies and workforce competence ensures the field's adaptability. Despite barriers to adoption, synergy between interventional radiologists' proficiency and technological advancements hold promise in cancer care.

Comparison of PD-L1 assays in head and neck carcinoma

Programmed cell death-ligand 1 (PD-L1) expression is a predictive biomarker for response to immune checkpoint inhibitor in head and neck squamous cell carcinoma. Given the range of antibodies and platforms for PD-L1 testing, it is essential to understand the performance of different staining and scoring methods. PD-L1 expression in 156 head and neck mucosal squamous cell carcinoma (HNmSCC) cases at Asan Medical Center was assessed using 106 tissue microarray (TMA) cores and 50 whole slides. Three standardised PD-L1 assays (22C3 pharmDx, SP263, and 28-8 pharmDx) and one laboratory-developed test (22C3 LDT) were evaluated: the combined positive score (CPS) with ≥1, ≥20, and ≥50 cut-offs, and the tumour positive score (TPS) with ≥1%, ≥20%, ≥50% cut-offs. Concordance on a continuous scale among the assays was good to excellent for CPS [intraclass correlation coefficient (ICC) range 0.73-0.94] and TPS (ICC range 0.70-0.94) and in both TMA and whole slides cohorts. Stratification by variable cut-offs demonstrated moderate to good agreement among most assays, as analysed by Gwet's AC1. PD-L1 expression was significantly correlated with tumour location using the 22C3 pharmDx assay (CPS, p=0.014; TPS, p=0.033). Notable concordance was found among PD-L1 assays, suggesting their potential interchangeability in HNmSCC.

Investigating the role of GTPase in inhibiting HBV replication and enhancing interferon therapy efficacy in chronic hepatitis B patients

BackgroundInterferon-alpha (IFNα) is a common treatment for chronic hepatitis B virus (HBV) infection, but its efficacy varies widely among patients. GTPASE, an interferon-stimulated gene (ISG), has recently been identified as a factor in antiviral immunity, though its role in HBV infection is not fully understood. ObjectiveThis study investigates the role of GTPASE in enhancing the antiviral effects of IFNα against HBV and elucidates its mechanism of action. MethodsWe analyzed the impact of GTPASE overexpression and silencing on HBV replication and clearance in HBV-infected cells. Molecular docking studies assessed the interaction between GTPASE and HBV surface antigens (HBs). Clinical samples from HBV patients undergoing Peg-IFNα treatment were also evaluated for GTPASE expression and its correlation with treatment efficacy. ResultsOverexpression of GTPASE led to significant inhibition of HBV replication, increased HBeAg seroconversion, and enhanced HBsAg clearance. GTPASE directly bound to HBs proteins, reducing their levels and affecting viral particle formation. Silencing GTPASE reduced these effects, while combined treatment with Peg-IFNα and GTPASE overexpression further improved antiviral outcomes. Mutational analysis revealed that specific sites in GTPASE are crucial for its antiviral activity. ConclusionsGTPASE acts as a positive regulator in IFNα-induced antiviral immunity against HBV. It enhances the therapeutic efficacy of IFNα by targeting HBs and modulating viral replication. GTPASE levels may serve as a predictive biomarker for response to Peg-IFNα therapy, highlighting its potential for improving individualized treatment strategies for chronic HBV infection.

SingleNucleotide Polymorphisms as Biomarkers of Mepolizumab and Benralizumab Treatment Response in Severe Eosinophilic Asthma.

The most promising treatment options for severe uncontrolled asthma (SUA) have emerged in recent years with the development of monoclonal antibodies for blocking selective targets responsible for the underlying inflammation, such as mepolizumab and benralizumab. However, there is variability in treatment response that is not fully controlled. The variability of the response to mepolizumab and benralizumab could be influenced by single-nucleotide polymorphisms (SNPs), and it would be useful to detect these and use them as predictive biomarkers of response. We conducted a retrospective observational cohort study of 72 Caucasian patients recruited from a tertiary hospital with severe uncontrolled eosinophilic asthma treated with mepolizumab and benralizumab. Polymorphisms in the IL5 (rs4143832, rs17690122), RAD50 (rs11739623, rs4705959), IL1RL1 (rs1420101, rs17026974, rs1921622), GATA2 (rs4857855), IKZF2 (rs12619285), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs569108), and ZNF415 (rs1054485) genes were analyzed by real-time polymerase chain reaction (PCR) using Taqman probes. The response was analyzed after 12 months of treatment. In patients under mepolizumab treatment, a treatment response defined as a reduction in exacerbations was associated with ZNF415 rs1054485-T (p = 0.042; OR = 5.33; 95% CI = 1.06-30.02), treatment response defined as a reduction in oral corticosteroids use was associated with the number of exacerbations in the previous year (p = 0.029; OR = 3.89; 95% CI = 1.24-14.92), and treatment response defined as improvement in lung function was associated with the age at the beginning of biological therapy (p = 0.002; OR = 1.10; 95% CI = 1.04-1.18), FCER1B rs569108-AA (p < 0.001; OR = 171.06; 95% CI = 12.94-6264.11), and FCER1A rs2427837-A (p = 0.021; OR = 8.61; 95% CI = 1.71-76.62). On the other hand, in patients under benralizumab treatment, treatment response, defined as a reduction in exacerbations, was associated with ZNF415 rs1054485-T (p = 0.073; OR = 1.3 × 108; 95% CI = 1.8 × 10-19-NA), FCER1B rs569108-AA (p = 0.050; OR = 11.51; 95% CI = 1.19-269.78), allergies (p = 0.045; OR = 4.02; 95% CI = 1.05-16.74), and sex (p = 0.028; OR = 4.78; 95% CI = 1.22-20.63); and treatment response defined as improvement in lung function was associated with polyposis (p = 0.027; OR = 9.16; 95% CI = 1.58-91.4), IKZF2 rs12619285-AA (p = 0.019; OR = 9.1; 95% CI = 1.7-75.78), IL5 rs4143832-T (p = 0.017; OR = 11.1; 95% CI = 1.9-112.17), and FCER1B rs1441586-C (p = 0.045; OR = 7.81; 95% CI = 1.16-73.45). The results of this study show the potential influence of the studied polymorphisms on the response to mepolizumab and benralizumab and the clinical benefit that could be obtained by defining predictive biomarkers of treatment response.

Analysis of Molecular Imaging and Laboratory Baseline Biomarkers in PSMA-RLT: Whole-Body Total Lesion PSMA (TLP) Predicts Overall Survival.

The aim of this retrospective study was to identify pre-therapeutic predictive laboratory and molecular imaging biomarkers for response and overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT). Pre-therapeutic laboratory and [68Ga]Ga-PSMA-11 PET/CT data of n = 102 mCRPC patients receiving [177Lu]Lu-PSMA-617 RLT within a prospective registry (REALITY Study, NCT04833517) were analyzed including laboratory parameters such as alkaline phosphatase (ALP), prostate-specific antigen (PSA), gamma glutamyl transferase (GGT), glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT), neuron specific enolase (NSE), hemoglobin (Hb), and imaging parameters such as maximum standardized uptake value of the tumor lesions (SUVmax), the mean standardized uptake value of all tumor lesions (SUVmean), the whole-body molecular tumor volume (MTV), and the whole-body total lesion PSMA (TLP). Mann-Whitney U test, univariate and multivariable Cox-regression were performed to test for association of the parameters with response and OS. The SUVmean of all lesions was significantly different between responders and non-responders (SUVmean responders 8.95 ± 2.83 vs. non-responders 7.88 ± 4.46, p = 0.003), whereas all other tested biochemical and imaging parameters did not reveal significant differences. Hb and the molecular imaging parameters MTV and TLP showed a significant association with OS (p = 0.013, p = 0.005; p = 0.009) in univariant Cox regression; however, only TLP remained significant in multivariable analysis (Hazard ratio 1.033, p = 0.009). This study demonstrates a statistically significant association between the quantitative PET/CT imaging parameter SUVmean and PSA response, as well as between the baseline TLP and OS of mCRPC patients undergoing RLT.

Predictive biomarkers for response to TGF- β inhibition in resensitizing chemo(radiated) esophageal adenocarcinoma

Epithelial-mesenchymal transition (EMT) has been identified as a driver of therapy resistance, particularly in esophageal adenocarcinoma (EAC), where transforming growth factor beta (TGF-β) can induce this process. Inhibitors of TGF-β may counteract the occurrence of mesenchymal, resistant tumor cell populations following chemo(radio)therapy and improve treatment outcomes in EAC. Here, we aimed to identify predictive biomarkers for the response to TGF-β targeting. In vitro approximations of neoadjuvant treatment were applied to publicly available primary EAC cell lines. TGF-β inhibitors fresolimumab and A83–01 were employed to inhibit EMT, and mesenchymal markers were quantified via flow cytometry to assess efficacy. Our results demonstrated a robust induction of mesenchymal cell states following chemoradiation, with TGF-β inhibition leading to variable reductions in mesenchymal markers. The cell lines were clustered into responders and non-responders. Genomic expression profiles were obtained through RNA-seq analysis. Differentially expressed gene (DEG) analysis identified 10 positively- and 23 negatively-associated hub genes, which were bioinformatically identified. Furthermore, the correlation of DEGs with response to TGF-β inhibition was examined using public pharmacogenomic databases, revealing 9 positively associated and 11 negatively associated DEGs. Among these, ERBB2, EFNB1, and TNS4 were the most promising candidates. Our findings reveal a distinct gene expression pattern associated with the response to TGF-β inhibition in chemo(radiated) EAC. The identified DEGs and predictive markers may assist patient selection in clinical studies investigating TGF-β targeting.

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling. Methods A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence. Results Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype. Conclusions In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

SIRT1 Promotes Chemoradiotherapy Resistance in Esophageal Squamous Cell Carcinoma.

Identifying accurate biomarkers for predicting response to chemoradiotherapy (CRT) in patients with esophageal squamous cell carcinoma (ESCC) is a critical challenge. The protein SIRT1, recognized for its implications in longevity, has been associated with tumor promotion in ESCC. However, data regarding its correlation with CRT sensitivity remain unreported. Therefore, in this study, we aimed to investigate the relationship between SIRT1 expression and CRT sensitivity and concurrently assess the effect of SIRT1 knockdown on CRT sensitivity in ESCC. This study included 73 patients who underwent radical esophagectomy after CRT. SIRT1 expression in pre-treatment endoscopic biopsies was assessed through immunostaining, followed by a comparative analysis of CRT effects on surgical specimens. Small interfering RNA was used to attenuate SIRT1 expression in TE5 and TE10 cells, which were then subjected to cisplatin treatment at varying doses and concentrations and irradiation with X-rays, respectively. High SIRT1 tissue expression was significantly associated with CRT resistance. Multivariate analysis identified high SIRT1 expression as an independent biomarker for poor CRT response. In TE-5 and TE-10 cells, SIRT1 knockdown significantly decreased cell viability and increased sensitivity to cisplatin and radiation treatment compared to that of the negative control. Our study results demonstrate the potential of SIRT1 as a predictive biomarker for CRT response in ESCC, highlighting the heightened sensitivity to CRT upon the transcriptional inactivation of SIRT1. Targeting SIRT1 emerges as a promising strategy for enhancing the efficacy of CRT for ESCC.

1H and 31P Magnetic Resonance Spectroscopic Metabolomic Imaging: Assessing Mitogen-Activated Protein Kinase Inhibition in Melanoma.

The MAPK signaling pathway with BRAF mutations has been shown to drive the pathogenesis of 40-60% of melanomas. Inhibitors of this pathway's BRAF and MEK components are currently used to treat these malignancies. However, responses to these treatments are not always successful. Therefore, identifying noninvasive biomarkers to predict treatment responses is essential for personalized medicine in melanoma. Using noninvasive 1H magnetic resonance spectroscopy (1H MRS), we previously showed that BRAF inhibition reduces lactate and alanine tumor levels in the early stages of effective therapy and could be considered as metabolic imaging biomarkers for drug response. The present work demonstrates that these metabolic changes observed by 1H MRS and those assessed by 31P MRS are also found in preclinical human melanoma models treated with MEK inhibitors. Apart from 1H and 31P MRS, additional supporting in vitro biochemical analyses are described. Our results indicate significant early metabolic correlations with response levels to MEK inhibition in the melanoma models and are consistent with our previous study of BRAF inhibition. Given these results, our study supports the potential clinical utility of noninvasive MRS to objectively image metabolic biomarkers for the early prediction of melanoma's response to MEK inhibition.

Nasal Epithelium Transcriptomics Predict Clinical Response to Elexacaftor/Tezacaftor/Ivacaftor.

Elexacaftor/tezacaftor/ivacaftor (ETI) has made a substantial positive impact for people living with CF (pwCF). However, there can be substantial variability in efficacy, and we lack adequate biomarkers to predict individual response. We thus aimed to identify transcriptomic profiles in nasal respiratory epithelium that predict clinical response to ETI treatment. We obtained nasal epithelial samples from pwCF prior to ETI initiation and performed a transcriptome-wide analysis of baseline gene expression to predict changes in FEV1 (∆FEV1), year's best FEV1 (∆ybFEV1), and body mass index (∆BMI). Using the top differentially expressed genes (DEGs), we generated transcriptomic risk scores (TRS) and evaluated their predictive performance. The study included 40 pwCF aged ≥6 years (mean 27.7 [SD=15.1] years; 40% female). After ETI initiation, FEV1 improved ≥5% in 22 (61.1%) participants and ybFEV1 improved ≥5% in 19 (50%). TRS were constructed using top over-expressed and under-expressed genes for each. Adding the ∆FEV1 TRS for to a model with age, sex, and baseline FEV1 increased the AUC from 0.41 to 0.88; the ∆ybFEV1 TRS increased the AUC from 0.51 to 0.88; and the ∆BMI TRS increased the AUC from 0.46 to 0.92. Average accuracy was thus ~85% in predicting the response to the three outcomes. Results were similar in models further adjusted for F508del zygosity and previous CFTR modulator use. In conclusion, we identified nasal epithelial transcriptomic profiles that help accurately predict changes in FEV1 and BMI with ETI treatment. These novel TRS could serve as predictive biomarkers for clinical response to modulator treatment in pwCF.

Blood Tumor Mutational Burden Alone Is Not a Good Predictive Biomarker for Response to Immune Checkpoint Inhibitors in Patients With Gastrointestinal Tumors.

There has been a controversy about the predictive value of tissue-TMB-H for immune checkpoint inhibitors (ICIs) with limited data regarding blood-TMB (bTMB) in GI tumors. We aim to evaluate the predictive value of bTMB compared with MSI-H in GI tumors. Patients with unresectable/metastatic GI cancer, harboring either MSS with bTMB-H (≥10mut/Mb) or dMMR/MSI-H who received ICI were included. We compared ICIs' efficacy between MSS-bTMB-H (N=45) versus MSI-H (N=50) in GI tumors. Ninety-five patients were identified with the majority having colorectal (49.5%) or esophagogastric (34.7%) cancers. MSS-bTMB-H group had more esophagogastric cancer and later-line ICI recipients, with no significant differences in other known prognostic variables. At a median follow-up of 9.4 months, MSI-H group showed superior ORR (58.0% vs. 26.7%), DCR (84.0% vs. 42.2%), DoR (not-reached vs. 7.6mo), PFS (22.5 vs. 3.8mo), and OS (Not-reached vs. 10.1mo) compared with MSS-bTMB-H. Multivariable analysis showed that MSI-H was an independent favorable factor over MSS-bTMB-H for PFS (HR=0.31, CI 0.15-0.63, P=0.001) and OS (HR=0.33, CI 0.14-0.80, P=0.014). MSI-H group showed favorable outcomes compared with MSS-bTMB-16+ (ORR: 58.0% vs. 26.9%; DCR: 84.0% vs. 42.3%; PFS:22.5 vs. 4.0mo) and MSS-bTMB-20+ (ORR: 58.0% vs. 31.6%; DCR: 84.0% vs. 42.1%; PFS:22.5 vs. 3.2mo). There was no difference between MSS-bTMB10-15 compared with MSS-bTMB-16+ in ORR, DCR, and PFS, or between MSS-bTMB10-19 compared with MSS-bTMB20+. Regardless of bTMB cutoff at 10, 16, or 20, bTMB-H did not appear to be a predictive biomarker in MSS GI tumors in this retrospective analysis.

Pan-cancer analysis of disulfidptosis with potential implications in prognosis, immune microenvironment, and drug resistance in human cancer.

To get a systematic assessment of disulfidptosis-related genes across human cancers and explore the predictive role of disulfidptosis in cancer drug sensitivity. We developed a score-level model to quantify the level of disulfidptosis in 33 human cancers using TCGA data. The mRNA expression and protein levels of disulfidptosis-related genes in human cancer cells and tissues were detected and retrieved from the Human Protein Atlas. Multiomics bioinformatic analyses were performed to evaluate disulfidptosis-related gene characteristics as well as the effect of disulfidptosis on the cancer immune microenvironment and drug resistance. Thirty cancers showed significantly different expression levels of disulfidptosis-related genes between normal and tumor samples. The mRNA expression and protein level of disulfidptosis-related genes were consistent with TCGA databases in lung cancer and hepatocellular carcinoma. We also found that altered levels of the disulfidptosis score expression were usually related to patient prognosis, and high expression of disulfidptosis-related genes was associated with drug resistance in different cancer types. Our study illustrates the characterization of disulfidptosis in multiple cancer types and highlights its potential value as a predictive biomarker of drug response, which can pave the way for further investigation of the prognostic and therapeutic potential of disulfidptosis.

Quantitative Measurement of HER2 Expression in Non–Small Cell Lung Cancer With a High-Sensitivity Assay

Recently, low human epidermal growth factor receptor 2 (HER2) protein expression has been proposed as a predictive biomarker for response to the antibody-drug conjugate trastuzumab deruxtecan (T-DXd) in metastatic breast cancer. HER2 expression in non–small cell lung cancer (NSCLC) patients has never been carefully measured, and little is known about the frequency of cases with unamplified but detectable levels of the protein. Although some HER2-targeted therapies have been studied in NSCLC patients, they have been restricted to those with genomic ERBB2 gene alterations, which only represent relatively rare cases of NSCLC. Still, emerging investigations of T-DXd in NSCLC have shown promise in patients with unamplified HER2. Taken together, we hypothesize that there may be many cases of NSCLC with levels of HER2 protein expression comparable with levels seen in breast cancer that benefit from T-DXd.Here, we used a previously validated, analytic, quantitative immunofluorescence (QIF) assay that is more sensitive than legacy clinical HER2 immunohistochemistry assays. We measured HER2 protein levels in NSCLC cases to determine the proportion of cases with detectable HER2 expression. Using cell line calibration microarrays alongside our QIF method enabled us to convert HER2 signal into units of attomoles per mm2. We found that over 63% of the 741 analyzed NSCLC cases exhibited HER2 expression above the limit of detection, with more than 17% of them exceeding the lower limit of quantification. Although the threshold for response to T-DXd in breast cancer is still unknown, many cases of NSCLC have expression in a range comparable to breast cancer cases with immunohistochemistry scores of 1+ or 2+. Our assay could potentially select NSCLC cases with a detectable target (ie, HER2) that might benefit from HER2 antibody-drug conjugates, irrespective of ERBB2 genomic alterations.

Changes of circulating tumor cells expressing CD90 and EpCAM in early-phase of atezolizumab and bevacizumab for hepatocellular carcinoma

Circulating tumor cells (CTCs) are noninvasive biomarkers that can indicate the therapeutic response and prognosis. The study aimed to investigate the cellular characteristics of CTCs focusing on monitoring during atezolizumab and bevacizumab (Atezo-Bev) therapy in patients with hepatocellular carcinoma (HCC). Peripheral blood samples were collected from 10 healthy controls and 40 patients with HCC. CTCs enriched using RosetteSep™ Human CD45 depletion cocktail were analyzed by multiparametric flow cytometry. CTC isolation was based on PanCK(+)CD45(−) cells, and CTCs exhibiting markers CD90, CD133, EpCAM, or vimentin. The total number of CTCs and the number of CTCs expressing CD90, CD133, EpCAM, and vimentin were correlated with the BCLC stage of HCC. The change in total CTC count accurately reflected the initial response to Atezo-Bev therapy. The numbers and mean fluorescence intensity of the CTC subsets expressing CD90 and EpCAM molecules decreased in patients with partial response/stable disease, and increased in patients with progressive disease and were markedly correlated with overall survival. CD90(+) and EpCAM(+) CTCs may be candidate biomarkers for the early prediction of the treatment response and the overall survival of patients with HCC receiving Atezo-Bev therapy.

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.

Pharmacological Trends in the Management of Atopic Dermatitis: A Comprehensive Review.

Atopic dermatitis (AD) is a prevalent, chronic inflammatory skin condition characterized by pruritus, erythema, and impaired skin barrier function. AD management presents significant challenges due to its complex pathophysiology involving immune dysregulation and genetic predispositions. While traditional therapies, such as topical corticosteroids and emollients, remain foundational, their limitations have spurred the development of novel pharmacological approaches. This comprehensive review explores current pharmacological trends in the management of AD, focusing on emerging therapies that target specific immunological pathways. Biologic agents, including monoclonal antibodies against interleukin (IL)-4, IL-13, and IL-31 receptors, offer targeted mechanisms to modulate immune responses implicated in AD pathogenesis. Janus kinase (JAK) and phosphodiesterase-4 (PDE-4) inhibitors represent another class of promising therapies, providing alternatives for patients resistant to conventional treatments. The review synthesizes evidence from clinical trials and studies to evaluate these pharmacological agents' efficacy and safety profiles. Considerations for personalized medicine approaches, including biomarkers for treatment response prediction and genotype-based therapies, are discussed to highlight the potential for tailored treatment strategies in AD management. In conclusion, this review underscores the evolving landscape of pharmacological interventions for AD, emphasizing the need for continued research to address unmet clinical needs and optimize patient outcomes. By delineating current advancements and future directions, this review aims to inform clinical practice and guide future research endeavours in dermatology.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives.

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

Serial Changes of Circulating Tumor Cells in Patients with Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab.

Immune checkpoint inhibitors have promising outcomes in patients with hepatocellular carcinoma (HCC); however, there is no reliable biomarker for predicting disease progression. Circulating tumor cells (CTCs) derived from peripheral blood have attracted attention in monitoring therapeutic efficacy. In this study, CTCs were serially collected from HCC patients undergoing atezolizumab plus bevacizumab (Atezo+Bev), and changes in molecular expression and CTC numbers were analyzed to identify effective biomarkers. Changes in CTC numbers during Atezo+Bev reflected the tumor volume. Targeted RNA sequencing with next-generation sequencing (NGS) revealed that patients with elevated transforming growth factor (TGF)-β signaling molecules had a poorer response, whereas those with elevated apoptosis signaling molecules had a favorable response. In addition, compared with changes in CTC counts, changes in TGF-β signaling molecule expression in CTCs accurately and promptly predicted treatment response. Overall, NGS analysis of CTC-derived RNA showed that changes in TGF-β signaling molecules predict treatment response earlier than changes in CTC counts. These findings suggest that changes in the expression of TGF-β molecules in CTCs could serve as novel biomarkers for the early prediction of therapeutic response in patients with unresectable HCC undergoing Atezo+Bev.