Therapy Response Research Articles

Predictors of response to bDMARDs and tsDMARDs in psoriatic arthritis: a pilot study on the role of musculoskeletal ultrasound

ObjectivesThis pilot study aimed to identify early predictors of drug retention in patients with clinically active peripheral psoriatic arthritis who initiated or switched to therapy with biologic and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs).MethodsClinical and ultrasound assessments were conducted at baseline (t0) and subsequently at 1 (t1), 3 (t3), and 6 (t6) months. Ultrasound evaluations targeted joints/entheses according to PsASon-Score13 and the most clinically involved joint/enthesis/tendon or the two most clinically involved joints/entheses/tendons (MIJET and 2MIJET). After 6 months of follow-up, patients were divided into two groups based on drug retention, determined by the clinician's assessment of treatment efficacy (cResponder vs. non-cResponder). Main endpoints were ultrasound changes in MIJET, 2MIJET, and GUIS (Global US Inflammation Subscore) derived from PsASon-13.ResultsTwenty-nine patients were enrolled, 22 cResponders and 7 non-cResponders at t6. In the comparison between cResponders and non-cResponders, GUIS variation significantly differed in Δt6-t0, while MIJET and 2MIJET variations were significant as early as Δt3-t0 and confirmed in Δt6-t0. The ultrasound response of MIJET and 2MIJET was faster in cResponders treated with JAKi vs. those treated with TNFi and IL-17/12-23i, significant in Δt1-t0.ConclusionsUltrasound imaging of clinically involved joint sites may be a valuable early predictor of therapy response for predicting drug retention at 6 months in patients with psoriatic arthritis.

Limited Efficacy of Anti-EGFR Monoclonal Antibodies in Colorectal Cancer Patients with Rare RAS Variants: Analysis of the C-CAT Database.

Epidermal growth factor receptor (EGFR) inhibition is crucial in treating RAS wild-type metastatic colorectal cancer, yet current testing methods may miss rare RAS variants affecting treatment efficacy. We analyzed 4122 colorectal cancer patients receiving anti-EGFR antibodies from the Center for Cancer Genomics and Advanced Therapeutics database, identifying 54 patients (1.3%) with rare RAS variants undetectable by standard testing. These patients showed significantly lower response rates to anti-EGFR therapy (28.3%) compared to RAS wild-type cases (44.6%, p = 0.003). Disease control rates were also lower in rare variant cases (60.9%) versus wild-type cases (80.0%). Most common rare variants included KRAS Q22K, A59E, and A11_G12insGA. Comprehensive genomic profiling revealed additional alterations in TP53 (90.7%), APC (87.0%), and non-V600E BRAF mutations (25.9%). Our findings suggest that rare RAS variants predict poor anti-EGFR therapy response, highlighting the potential benefit of comprehensive genomic profiling before treatment initiation. This study provides real-world evidence supporting the clinical relevance of rare RAS variants in treatment decision-making for colorectal cancer. Future studies should focus on developing cost-effective comprehensive testing strategies and evaluating alternative treatment approaches for patients with rare RAS variants.

Isolation of Plasma Extracellular Vesicles for High-Depth Analysis of Proteomic Biomarkers in Metastatic Castration-Resistant Prostate Cancer Patients.

Introduction: Prostate cancer treatment has been revolutionized by targeted therapies, including PARP inhibitors, checkpoint immunotherapies, and PSMA-targeted radiotherapies. Despite such advancements, accurate patient stratification remains a challenge, with current methods relying on genomic markers, tissue staining, and imaging. Extracellular vesicle (EV)-derived proteins offer a novel non-invasive alternative for biomarker discovery, holding promise for improving treatment precision. However, the characterization of plasma-derived EVs in prostate cancer patients remains largely unexplored. Methods: We conducted proteomic analyses on EVs isolated from plasma in 27 metastatic castration-resistant prostate cancer (mCRPC) patients. EVs were purified using ultracentrifugation and analyzed via mass spectrometry. Proteomic data were correlated with clinical markers such as serum prostate-specific antigen (PSA) and bone lesion counts. Statistical significance was assessed using Mann-Whitney t-tests and Spearman correlation. Results: The median age of patients was 74 (range: 44-94) years. At the time of blood collection, the median PSA level was 70 (range: 0.5-1000) ng/mL. All patients had bone metastasis. A total of 5213 proteins were detected, including EV-related proteins (CD9, CD81, CD63, FLOT1, TSG101) and cancer-related proteins (PSMA, B7-H3, PD-L1). Proteomic profiling of plasma EVs revealed a significant correlation between specific EV-derived proteins and clinical prognostic markers. B7-H3, LAT1, and SLC29A1 showed a strong association with serum PSA levels and number of bone lesions, indicating potential for these proteins to serve as biomarkers of disease burden and therapy response. Conclusions: Our findings demonstrate the potential of EV-based proteomics for identifying biomarkers in mCRPC patients. Proteins such as B7-H3 and LAT1 could guide precision oncology approaches, improving patient stratification. Future research incorporating outcomes data and EV subpopulation analysis is needed to establish clinical relevance.

Prognostic Significance of Immunohistochemical Expression of Cyclin D1 and β-Catenin in Invasive Ductal Carcinoma (IDC)

Introduction: Invasive ductal carcinoma (IDC) is the most prevalent subtype of breast cancer, distinguished by diverse clinical manifestations and molecular heterogeneity. Prognostic outcomes are influenced by multiple factors, including the patient’s age at diagnosis, tumor size, histological grade, disease stage, lymph node metastasis (LNM), and hormone receptor status (ER, PR, HER2). This research has highlighted the potential of emerging molecular biomarkers such as Cyclin D1 and β-Catenin in enhancing prognostic precision. Methodology: This retrospective, cross-sectional study analyzed the medical records of female patients diagnosed with IDC. Tumor size, grade, and stage were examined alongside lymph node involvement to assess the extent of disease dissemination. Immunohistochemistry (IHC) was employed to determine the expression of ER, PR, and HER2 receptors. Additionally, emerging biomarkers such as Cyclin D1 and β-Catenin were evaluated to explore their prognostic value. A total of 150 tumor samples were collected from multiple cancer treatment facilities across Rawalpindi, Punjab, Pakistan. Findings and Discussion: The mean age at diagnosis was 50.6 years, with the majority of patients (68%) between 36 and 55 years. Tumor analysis revealed that 76.7% of lesions were <30 mm in size, and 46.7% were classified as grade II. LNM was detected in 39.3% of patients, indicating significant metastatic potential. Regarding receptor expression, 45.5% of tumors were ER-positive, 42.9% PR-positive, and 54.8% HER2-positive, aligning with global incidence trends. The investigation of molecular markers showed Cyclin D1 overexpression in 60% of cases, predominantly in ER-positive tumors, suggesting better endocrine therapy responsiveness. β-Catenin was detected in 33.3% of samples and correlated with aggressive tumor phenotypes, emphasizing its potential role in identifying high-risk patients. These molecular markers align with globally research. Conclusion: This study emphasizes the significance of early detection and comprehensive molecular profiling in IDC management. Smaller tumors and receptor-positive cases are generally associated with more favorable outcomes. Additionally, emerging biomarkers such as Cyclin D1 and β-Catenin hold promise for refining prognostic models and optimizing individualized treatment plans. Incorporating these biomarkers into clinical practice can further enhance therapeutic decision-making and patient care.

CD69 Expression is Negatively Associated With T-Cell Immunity and Predicts Antiviral Therapy Response in Chronic Hepatitis B.

The function of CD69 expressed on T cells in chronic hepatitis B (CHB) remains unclear. We aimed to elucidate the roles of CD69 on T cells in the disease process and in antiviral therapy for CHB. We enrolled 335 treatment-naive patients with CHB and 93 patients with CHB on antiviral therapy. CD69, antiviral cytokine production by T cells, T-helper (Th) cells, and inhibitory molecules of T cells were measured using flow cytometry, and clinical-virological characteristics were examined dynamically during antiviral therapy. CD69 expression on CD3+, CD4+, and CD8+ T cells was the lowest in the immune-active phase and was negatively correlated with liver transaminase activity, fibrosis features, inflammatory cytokine production by T cells, and Th-cell frequencies but positively with inhibitory molecules on T cells. CD69 expression on CD3+, CD4+, and CD8+ T cells decreased after 48 weeks of antiviral therapy, and patients with hepatitis B e antigen (HBeAg) seroconversion in week 48 showed lower CD69 expression on T cells at baseline and week 48. The area under the ROC curve of CD69 expression on T cells at baseline for predicting HBeAg seroconversion in week 48 was 0.870, the sensitivity was 0.909, and the specificity was 0.714 (P =0.002). CD69 negatively regulates T-cell immunity during CHB, and its expression decreases with antiviral therapy. CD69 expression predicts HBeAg seroconversion in week 48. CD69 may play an important negative role in regulating T cells and affect the efficacy of antiviral therapy.

The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer’s response to endocrine therapies and explore resistance mechanisms.

Asciminib add-on to imatinib demonstrates sustained high rates of ongoing therapy and deep molecular responses with prolonged follow-up in the ASC4MORE study

BackgroundUp to 65% of patients with chronic myeloid leukemia (CML) who are treated with imatinib do not achieve sustained deep molecular response, which is required to attempt treatment-free remission. Asciminib is the only approved BCR::ABL1 inhibitor that Specifically Targets the ABL Myristoyl Pocket. This unique mechanism of action allows asciminib to be combined with adenosine triphosphate–competitive tyrosine kinase inhibitors to prevent resistance and enhance efficacy. The phase II ASC4MORE trial investigated the strategy of adding asciminib to imatinib in patients who have not achieved deep molecular response with imatinib.MethodsIn ASC4MORE, 84 patients with CML in chronic phase not achieving deep molecular response after ≥ 1 year of imatinib therapy were randomized to asciminib 40 or 60 mg once daily (QD) add-on to imatinib 400 mg QD, continued imatinib 400 mg QD, or switch to nilotinib 300 mg twice daily.ResultsMore patients in the asciminib 40- and 60-mg QD add-on arms (19.0% and 28.6%, respectively) achieved MR4.5 (BCR::ABL1 ≤ 0.0032% on the International Scale) at week 48 (primary endpoint) than patients in the continued imatinib (0.0%) and switch to nilotinib (4.8%) arms. Fewer patients discontinued asciminib 40- and 60-mg QD add-on treatment (14.3% and 23.8%, respectively) than imatinib (76.2%, including crossover patients) and nilotinib (47.6%). Asciminib add-on was tolerable, with rates of AEs and AEs leading to discontinuation less than those with nilotinib, although higher than those with continued imatinib (as expected in these patients who had already been tolerating imatinib for ≥ 1 year). No new or worsening safety signals were observed with asciminib add-on vs the known asciminib monotherapy safety profile.ConclusionsOverall, these results support asciminib add-on as a treatment strategy to help patients with CML in chronic phase stay on therapy to safely achieve rapid and deep response, although further investigation is needed before this strategy is incorporated into clinical practice.Trial registrationNCT03578367

Imaging of tumor-associated macrophage dynamics during immunotherapy using a CD163-specific nanobody-based immunotracer

Immunotherapies have emerged as an effective treatment option for immune-related diseases, such as cancer and inflammatory diseases. However, variations in patient responsiveness limit the broad applicability and success of these immunotherapies. Noninvasive whole-body imaging of the immune status of individual patients during immunotherapy could enable the prediction and monitoring of the patient's response, resulting in more personalized treatments. In this study, we developed a nanobody-based immunotracer targeting CD163, a receptor specifically expressed on macrophages. This anti-CD163 immunotracer bound to human and mouse CD163 with high affinity and specificity without competing for ligand binding. Furthermore, the tracer showed no unwanted immune cell activation and was nonimmunogenic. Upon radiolabeling of the anti-CD163 immunotracer, specific imaging of CD163+ macrophages using micro-single-photon emission computerized tomography/computed tomography or micro-positron emission tomography/CT was performed. The anti-CD163 immunotracer was able to stratify immunotherapy responders from nonresponders (NR) by visualizing differences in the intratumoral CD163+ TAM distribution in Lewis lung carcinoma-ovalbumin tumor-bearing mice receiving an anti-programmed cell death protein-1 (PD-1)/CSF1R combination treatment. Immunotherapy-responding mice showed a more homogeneous distribution of the PET signal in the middle of the tumor, while CD163+ TAMs were located at the tumor periphery in NR. As such, visualization of CD163+ TAM distribution in the tumor microenvironment could allow a prediction or follow-up of therapy response. Altogether, this study describes an immunotracer, specific for CD163+ macrophages, that allows same-day imaging and follow-up of these immune cells in the tumor microenvironment, providing a good basis for the prediction and follow-up of immunotherapy responses in cancer patients.

Integration of RNA Editing with Multiomics Data Improves Machine Learning Models for Predicting Drug Responses in Breast Cancer Patients.

Background: The integration of conventional omics data such as genomics and transcriptomics data into artificial intelligence models has advanced significantly in recent years; however, their low applicability in clinical contexts, due to the high complexity of models, has been limited in their direct use inpatients. We integrated classic omics, including DNA mutation and RNA gene expression, added a novel focus on promising omics methods based on A>I(G) RNA editing, and developed a drug response prediction model. Methods: We analyzed 104 patients from the Breast Cancer Genome-Guided Therapy Study (NCT02022202). This study was used to train (70%) with 10-fold cross-validation and test (30%) the drug response classification models. We assess the performance of the random forest (RF), generalized linear model (GLM), and support vector machine (SVM) with the Caret package in classifying therapy response via various combinations of clinical data, tumoral and germline mutation data, gene expression data, and RNA editing data via the LASSO and PCA strategies. Results: First, we characterized the cohort on the basis of clinical data, mutation landscapes, differential gene expression, and RNAediting sites in 69 nonresponders and 35 responders to therapy. Second, regarding the prediction models, we demonstrated that RNA editing data improved or maintained the performance of the RF model for predicting drug response across all combinations. To select the final model, we compared the F1 score between models with different data combinations, highlighting an F1 score of 0.96 (95% CI: 0.957--0.961) and an AUC of 0.922, using LASSO for feature selection. Finally, we developed a nonresponse risk score on the basis of features that contributed to the selected model, focusing on three RNA-edited sites in the genes KDM4B, miRNA200/TTLL10-AS1, and BEST1. The score was created to facilitate the clinical translation of our findings, presenting a probability of therapy response according to RNA editing site patterns. Conclusion: Our study highlights the potential of RNA editing as a valuable addition to predictive modeling for drug response in patients with breast cancer. The nonresponse risk score could represent a tool for clinical translation, offering a probability-based assessment of therapy response. These findings suggest that incorporating RNA editing into predictive models could enhance personalized treatment strategies and improve decision-making in oncology.

Collagen remodeling in murine melanoma therapy response through second-harmonic generation imaging

Collagen remodeling in murine melanoma therapy response through second-harmonic generation imaging

C-Reactive Protein Facilitates Premetastatic Niche Formation in the Lungs.

C-reactive protein (CRP) has long been recognized as a marker of inflammation, but its evolving role in immunomodulation and cancer has increasingly been recognized. In recent years, multiple studies have explored CRP as a biomarker for prognosis and therapy response, particularly in the context of cancer immunotherapy. In this issue of Cancer Research, Feng and colleagues investigate the role of CRP in the development of lung metastasis. They provide evidence for a direct role of CRP acting together with commensal bacteria to instruct an immune-tolerant state of pulmonary macrophages through Fc gamma receptor IIb signaling. By suppressing immune surveillance in the lungs, CRP facilitates the formation of a premetastatic niche, allowing circulating tumor cells to establish metastases. See related article by Feng et al., p. 4184.

Androgen receptor drives polyamine synthesis creating a vulnerability for prostate cancer.

Supraphysiological androgen (SPA) treatment can paradoxically restrict growth of castration-resistant prostate cancer with high androgen receptor (AR) activity, which is the basis for use of Bipolar Androgen Therapy (BAT) for patients with this disease. While androgens are widely appreciated to enhance anabolic metabolism, how SPA-mediated metabolic changes alter prostate cancer progression and therapy response is unknown. Here, we report that SPA markedly increased intracellular and secreted polyamines in prostate cancer models. This occurred through AR binding at enhancer sites upstream of the ODC1 promoter to increase abundance of ornithine decarboxylase (ODC), a rate-limiting enzyme of polyamine synthesis, and de novo synthesis of polyamines from arginine. SPA-stimulated polyamines enhance prostate cancer fitness, as dCas9-KRAB-mediated inhibition of AR regulation of ODC1 or direct ODC inhibition by difluoromethylornithine (DFMO) increased efficacy of SPA. Mechanistically, this occurred in part due to increased activity of S-adenosylmethionine decarboxylase 1 (AMD1), which was stimulated both by AR and by loss of negative feedback by polyamines, leading to depletion of its substrate S-adenosylmethionine and global protein methylation. These data provided the rationale for a clinical trial testing the safety and efficacy of BAT in combination with DFMO for patients with metastatic castration-resistant prostate cancer. Pharmacodynamic studies of this drug combination in the first five patients on trial indicated that the drug combination resulted in effective polyamine depletion in plasma. Thus, the AR potently stimulates polyamine synthesis, which constitutes a vulnerability in prostate cancer treated with SPA that can be targeted therapeutically.

Cholesterol Targeted Catalytic Hydrogel Fueled by Tumor Debris can Enhance Microwave Ablation Therapy and Anti-Tumor Immune Response.

The immunosuppressive residual tumor microenvironment (IRTM) is a key factor in the high recurrence and metastasis rates of hepatocellular carcinoma (HCC) after microwave ablation (MWA). Cholesterol-rich tumor fragments significantly contribute to IRTM deterioration. This study developed a cholesterol-targeted catalytic hydrogel, DA-COD-OD-HCS, to enhance the synergy between MWA and immune checkpoint inhibitors (ICIs) for HCC treatment. Cholesterol oxidase (COD), modified with dimethyl maleic anhydride (DA) for release in acidic IRTM, is used to degrade cholesterol. Oxydextran (OD) and hemin-chitosan (HCS) formed a dual network gel, ensuring long-term fixation of COD and hemin in the IRTM post-MWA. In both in vitro and in vivo HCC models, DA-COD-OD-HCS effectively released COD, degraded cholesterol, and induced tumor cell ferroptosis, enhancing the antitumor immune response. Combined with anti-PD-L1 immunotherapy, this strategy inhibited primary tumor growth and distant metastases, without side effects on adjacent tissues. This work highlights that cholesterol-targeting catalytic hydrogels fueled by tumor debris can significantly improve the efficacy of MWA and ICIs, offering a novel therapeutic approach for HCC.

A Simple Morphometric Analysis of Preoperative Therapy Response for Esophageal Adenocarcinoma.

Histologic assessment of tumor regression grade (TRG) on esophagogastrectomy specimens after neoadjuvant therapy is an excellent predictor of local recurrence rate and long-term survival in esophageal adenocarcinomas. Although several grading systems exist globally, the modified Ryan system suggested by the College of American Pathologists (CAP) is widely used in North America. Most systems rely on quantitative percentage estimation of the residual tumor with or without additional qualitative descriptors, which is relatively subjective with poor interobserver agreement. To test a morphometric-based approach using the microscopic objective lens to estimate the size of the largest focus of the residual tumor. A total of 69 esophageal specimens post neoadjuvant therapy were evaluated. Tumor size was morphometrically determined by the microscopic field, using an Olympus microscope with ×10/×22 eyepieces. Residual viable tumor was categorized into 4 groups, using ×2, ×4, and ×10 objectives: less than or equal to an ×10 field; larger than an ×10 field but less than or equal to an ×4 field; larger than an ×4 field but less than an ×2 field; and larger than or equal to an ×2 field. Morphometric measurements significantly correlated with the CAP treatment effect scores. There was no significant difference in overall survival between larger than or equal to ×2 and ×2 to ×4 groups; however, a 3-tier system (TRG1: ≤ ×10, TRG2: > ×10 and ≤ ×4, and TRG3: > ×4) showed significant survival differences (P = .01). Significant differences in the percentage of lymphovascular and perineural invasion, advanced TNM stage, and lymph node metastasis were identified among the 3 groups. The proposed 3-tier morphometric approach based on microscopic field size is a simple and easy-to-use method, which helps stratify patients into 3 groups with distinct histopathologic features and overall survival.

Minimal Change Disease and Focal Segmental Glomerulosclerosis Are Associated with Good Kidney Prognosis and Thrombotic Microangiopathy with Poor Kidney Survival in Patients with COVID-19-Associated Nephropathies

Introduction: The kidney is a frequent target of SARS-CoV-2, potentially developing lesions in glomeruli, vessels, and tubulointerstitium in response to this infection. Herein, we present the analysis of the first large Latin American cohort of adult patients undergoing kidney biopsy due to COVID-19-associated kidney disorders. Methods: This retrospective, multicenter, national study was based on the collection of information on demographics, comorbidities, laboratory data, kidney histology, therapy, and therapeutic response. Patients diagnosed with collapsing glomerulopathy (CG) were genotyped for APOL1. Results: Our cohort included 94 patients, most male (62.8%). The median age was 44 (33–52) years, and 50% of them were previously hypertensive. The time between COVID-19 diagnosis and kidney biopsy was 30 (15–60) days. Most patients had decreased kidney function at diagnosis, 43.5% required dialysis upon diagnosis, 77.6% received immunosuppression, and 2/3 achieved a clinical remission. CG was the most common kidney involvement (18 cases), reproducing previous findings. Focal segmental glomerulosclerosis (FSGS), thrombotic microangiopathy (TMA), and IgA nephropathy were also frequent, with 10 cases each. FSGS and minimal change disease (MCD) were associated with the best cumulative kidney survival; none started dialysis. In contrast, patients with TMA/C3 glomerulopathy presented a poor kidney prognosis, with more than half progressing to kidney replacement therapy. Conclusion: A novel and striking finding of our study, therefore, was the association of FSGS and MCD with the best kidney outcome among all COVID-19-related histological patterns. Moreover, the overall distribution of histological profiles showed significant particularities in the analyzed patient cohort, the most important being the higher frequency of TMA cases.

Precision models in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) represents a global health challenge, and ranks among one of the most prevalent and deadliest cancers worldwide. Therapeutic advances have expanded the treatment armamentarium for patients with advanced HCC, but obstacles remain. Precision oncology, which aims to match specific therapies to patients who have tumours with particular features, holds great promise. However, its implementation has been hindered by the existence of numerous 'HCC influencers' that contribute to the high inter-patient heterogeneity. HCC influencers include tumour-related characteristics, such as genetic alterations, immune infiltration, stromal composition and aetiology, and patient-specific factors, such as sex, age, germline variants and the microbiome. This Review delves into the intricate world of HCC, describing the most innovative model systems that can be harnessed to identify precision and/or personalized therapies. We provide examples of how different models have been used to nominate candidate biomarkers, their limitations and strategies to optimize such models. We also highlight the importance of reproducing distinct HCC influencers in a flexible and modular way, with the aim of dissecting their relative contribution to therapy response. Next-generation HCC models will pave the way for faster discovery of precision therapies for patients with advanced HCC.

Single-Cell Transcriptomics Sheds Light on Tumor Evolution: Perspectives from City of Hope's Clinical Trial Teams.

Tumor heterogeneity is a significant factor influencing cancer treatment effectiveness and can arise from genetic, epigenetic, and phenotypic variations among cancer cells. Understanding how tumor heterogeneity impacts tumor evolution and therapy response can lead to more effective treatments and improved patient outcomes. Traditional bulk genomic approaches fail to provide insights into cellular-level events, whereas single-cell RNA sequencing (scRNA-seq) offers transcriptomic analysis at the individual cell level, advancing our understanding of tumor growth, progression, and drug response. However, implementing single-cell approaches in clinical trials involves challenges, such as obtaining high-quality cells, technical variability, and the need for complex computational analysis. Effective implementation of single-cell genomics in clinical trials requires a collaborative "Team Medicine" approach, leveraging shared resources, expertise, and workflows. Here, we describe key technical considerations in implementing the collection of research biopsies and lessons learned from integrating scRNA-seq into City of Hope's clinical trial design, highlighting collaborative efforts between computational and clinical teams across breast, brain, and ovarian cancer studies to understand the composition, phenotypic state, and underlying resistance mechanisms within the tumor microenvironment.

A novel designed anti-PD-L1/OX40 bispecific antibody augments both peripheral and tumor-associated immune responses for boosting anti-tumor immunity.

Bispecific antibodies (BsAbs) combining simultaneous PD-L1 blockade and conditional co-stimulatory receptor activation have been developed to improve immune checkpoint therapy response. However, several PD-L1-based BsAbs have encountered clinical challenges, including insufficient activity or unexpected toxicity. In this study, we propose OX40 as a more suitable target partner for PD-L1-based BsAb design compared to ongoing clinical partners (CD27 and 4-1BB). We present a novel Fc-silenced tetravalent PD-L1/OX40 BsAb (EMB-09), which efficiently blocks PD-1/PD-L1 interactions and induces PD-L1-dependent OX40 activation, leading to enhanced T cell activation. EMB-09 demonstrated improved anti-tumor activity compared to the anti-PD-L1 monoclonal antibody. Significantly, EMB-09 activated effector memory T cells in peripheral immune system, promoted the influx of stem-like CD8+ T cells into the tumor site, resulting in a more active phenotype of CD8+ tumor-infiltrating lymphocytes. In an ongoing first-in-human study in patients with advanced refractory solid tumors (NCT05263180), EMB-09 demonstrated a consistent pharmacodynamic response and early efficacy signals.

Molecular profiling in MPN: who should have it and why?

Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) are a group of blood cancers that result from somatic mutations in hematopoietic stem cells, causing constitutive activation of JAK-STAT signaling pathways with consequent overproduction of 1 or more myeloid lineages. The initiating event in MPN pathogenesis is a genetic mutation, and consequently molecular profiling is central to the diagnosis, risk stratification, and, increasingly, monitoring of therapy response in persons with MPN. In this review we summarize current approaches to molecular profiling of classical MPNs (essential thrombocythemia, polycythemia vera, and myelofibrosis), using illustrative clinical case histories to demonstrate how genetic analysis is already fully integrated into MPN diagnostic classification and prognostic risk stratification. Molecular profiling can also be used in MPN to measure response to therapy both in clinical trials and increasingly in routine clinical practice. Taking a forward look, we discuss how molecular profiling in MPN might be used in the future to select specific molecularly targeted therapies and the role of additional genetic methodologies beyond mutation analysis.

Diagnosis, treatment and oncological outcome of cervical CUP-syndrome depending on p16 status

The incidence of cervical squamous cell carcinoma (SCC)-CUP is increasing, with a significant proportion being HPV-associated. In this 10-year retrospective study, we analyzed clinical and therapeutic parameters of patients with cervical SCC-CUP. Primary tumor detection rates in patients with initial SCC-CUP (SCC-CUPinit) were assessed and mean overall survival and disease-free survival of patients without primary tumor detection after an extended diagnostic workup, i.e. definitive SCC-CUP (SCC-CUPdef), were analyzed taking p16-status into account to derive therapeutic recommendations.85% (n=131/155) of patients with CUPinit, presented with SCC followed by adenocarcinoma metastases in 7% (n=10/155). In 41% (n=54/131) of patients with SCC-CUPinit, a primary tumor was identified after an extended diagnostic workup; the primary tumor detection rate was significantly higher in p16-positive compared to p16-negative cases (63% vs. 23%, p<0,001). PET imaging specificity was 73% for both sensitivity and specificity. SCC-CUPdef were primarily treated surgically with adjuvant radio(chemo)therapy. SCC-CUPdef patients with positive vs. negative p16-status had significantly longer overall survival (53 vs. 41 Monate, p=0,037), as well as patients with cN1- vs. cN3-status and M0- vs. M1-status.p16-status influences diagnosis and therapy response in patients with SCC-CUP: in p16-positive SCC-CUPinit, primary tumor detection rates were significantly higher than in p16-negative SCC-CUPinit. In patients with SCC-CUPdef, p16-positivity was associated with improved overall survival, albeit to an extent which does not justify therapy de-escalation.