Non-responding Patients Research Articles

First-line immunochemotherapy modulates peripheral immune landscape in advanced gastric cancer and gastroesophageal junction cancer (GC/GEJC): Prediction of response to combination therapy.

e14540 Background: The use of immunochemotherapy has brought about a change in the treatment of advanced or metastatic GC/GEJC, but only a subset of patients could benefit substantially. Therefore, seeking efficacious biomarkers to identify favorable populations for the regimen is imperative. This study aims to explore predictive markers and potential mechanism of combination therapy for GC/GEJC in real-world settings based on blood proteomic biopsy. Methods: This is a prospective, single-center trial in which all patients are adults with advanced or metastatic GC/GEJC confirmed by pathology or imaging. 30 eligible patients will receive PD-1 mab (sintilimab/nivolumab (NIVO) Q3W) and chemotherapy (SOX/XELOX Q3W) regardless of programmed death ligand-1 status. Blood samples were collected before treatment and after every two treatment cycles for Olink Target 96 IO analysis. CT scans were performed after every two cycles and will be categorized as responding (complete response plus primary response) or non-responding (progress disease plus stable disease) according to RECIST 1.1. Results: As of January 17, 2024, a total of 21 patients were enrolled. Eight of these patients received 16 samples before and after treatment, with 4 each of the 8 patients responding and non-responding. By analyzing the baseline samples comparing the responding and non-responding groups, it was found that patients in the responding group had lower expression of serum PD-L1 (sPD-L1) ( p=0.015). In the post-treatment samples, angiopoietin 1 was found to be poorly expressed in the responding patients ( p<0.001). In contrast, high expression of angiopoietin 2 in post-treatment blood samples was more pronounced in non-responders compared to pre-treatment ( p=0.020). Additionally, we observed that immunotherapy can modify the immune microenvironment by up-regulating the T cell receptor signaling and NK cell-mediated toxic effects pathways. These pathways may be potential targets for treatment. Conclusions: In summary, low sPD-L1 level before treatment may be a predictive biomarker for better efficacy of immuno-combination chemotherapy in advanced GC/GEJC; whereas elevation of angiopoietin after treatment predicts poor efficacy and suggests that antiangiogenic therapy may subsequently be added in non-responding patients. We are further recruiting more patients to obtain more accurate conclusions. Clinical trial information: ChiCTR2300078000 .

Old and New Strategies in the Treatment of Pediatric Multiple Sclerosis: A Personal View for a New Treatment Approach.

Up to 10 years ago the most common approach to the treatment of pediatric MS (ped-MS) was to start with IFNB or GA (so-called first-line therapies or moderate-efficacy disease-modifying therapies [ME-DMTs]) and to switch to more aggressive treatments (or high-efficacy disease-modifying therapies [HE-DMTs]) in non-responder patients. The use of HE-DMTs as first choice was recommended in selected cases with an active, aggressive form of MS. Indications for the treatment of ped-MS were essentially derived from data of observational studies. Recently, results of three randomized clinical trials have been published as well as data from many observational studies evaluating the effect of new and more active DMTs, with clear evidence that HE-DMTs are more effective than ME-DMTs. Therefore, the paradigm of treatment for patients with MS onset before 18years of age should be changed, offering treatment with HE-DMTs as first option, because of their superior effectiveness to prevent relapses and disease progression. HE-DMTs present an overall reassuring safety profile and obtain better adherence to treatment.

Exploring gut microbiome markers in predicting efficacy of immunotherapy against lung cancer.

8525 Background: Immunotherapy has profoundly changed the treatment landscape for lung cancer (LC) due to its tolerable safety profile and longer sustained therapeutic response. However, only about 20% of patients with locally advanced and metastatic disease can derive long-term clinical benefit from ICIs. Previous studies have suggested that the microbiome is involved in the development of LC in some way. We aimed to use the gut microbiome (GM) to model the benefit of immunotherapy and to mine the biomarkers with a global impact on immune response. Methods: We performed human gut metagenomic analysis on the responder patients and non-responder patients with immunotherapy. A total of 296 fecal samples, including baseline samples (71 responders, 98 non-responders and 72 healthy controls), and 55 samples during treatment were enrolled in our study, the taxonomic and functional features of these samples also were excavated. A machine-learning model was developed to identify responders and non-responders. At the same time, we also explored the influence of antibiotic use on the above results. Results: Specific species, Bacteroides caccae and Bacteroides uniformis, were positively correlated with responders. In non-responders, Prevotella copri was the main enrichment species. The α diversity of microbiota in responding patients was significantly higher than that in non-responding groups, and antibiotic use increased this trend. There was no significant difference in β diversity between the two groups, but LEFSE analysis also could obtain biomarkers of biological significance between the two groups. We used the biomarkers from the above analysis to construct a random forest model, and the area under the receiver operating characteristic curve (AUC) (species level: 82.10%; genus level: 79.4%). In addition, our studies suggested that metabolism such as amino acid metabolism, valine, leucine might be important in regulating the immunotherapy response that warrants further investigation. Conclusions: Overall, our study explored the relationship between microbial composition and immunotherapy efficacy in LC patients and mined relevant markers, and further research is needed to investigate the mechanisms of action of these key strains in influencing immunotherapy in the future.

Prognosis recovery score of apical surgery Guided Bone Regeneration using cone beam computed tomography and digital bioinformatics

ObjectiveGuided Bone Regeneration (GBR) is a dental surgical procedure that uses barrier membranes to prevent soft tissue invasion and conduct new bone growth. This study aimed to define a Prognosis Recovery score (PR score) to objectively classify post-surgery responders from non-responder patients who underwent GBR using Cone Beam Computed Tomography (CBCT). MethodsThis prospective-observational-longitudinal-cohort study recruited 250 individuals who were assigned to: Conventional-Apical-Surgery (CAS, n = 39), Apical-Surgery using human fascia lata Membrane placement (ASM, n = 42), and Apical-Surgery using human fascia lata Membrane placement and lyophilized allograft Bone powder (ASMB, n = 39); and Apical-Surgery using collagen membrane Porcine origin and Bovine Bone-matrix (ASPBB, n = 130), an independent external validation cohort. Surgery was performed, and evolution was monitored by CBCTs at 0, 6-, 12-, 18-, and 24 months post-surgery. ResultsNormalized lesion volumes were calculated, and non-linear time evolution morphology curves were characterized. The three-time evolution bone growth patterns were: a linear tendency (PR0), “S'' shaped log-logistic (PR1), and “C" cellular growth (PR2). The treatment success rates were PR2-46 %, PR2-88 %, and PR2-95 %/PR1-5% for CAS, ASM, and ASMB groups. The xenograft ASPBB counterpart achieved PR2-92 % and PR1-8%. The score PR had a sensitivity, specificity, and accuracy of 100 %. ConclusionsPatients' treatment success can be quantitatively, objectively, and precisely predicted with the Prognosis Recovery score (using only two CBCTs), according to their biological response to allograft or xenograft materials (time-evolution bone growth curves), reducing cost and radiation exposure. Clinical significanceThrough digital imaging and bioinformatic analysis of bone regeneration observed in CBCTs, we defined a Prognosis Recovery (PR) score using only two CBCT volume assessments (0 and 6 months). The PR score allowed us to define three time-evolution curves depending on the biomaterials used and to classify patients in a quantitative, objective, and accurate way.

Whole transcriptome analysis to reveal epithelial-mesenchymal transition after neoadjuvant therapy with or without additional anti-EGFR treatment: Subgroup analysis of esophageal squamous cell carcinomas of the SAKK 75/08 and the EORTC AIO POWER study.

4071 Background: In localized disease of esophageal squamous cell cancer (ESCC), a trend in higher pathological response rates and longer time to treatment failure was seen by addition of anti-EGFR treatment to radio-chemotherapy (RCTX) compared to RCTX alone (SAKK 75/08 trial and others). On the contrary, the effect of anti-EGFR treatment to chemotherapy (CTX) remains unclear as no survival benefit was detected within advanced patients (EORTC-AIO-POWER study). Since perfect discrimination and selection of subgroups with highest benefit for anti-EGFR treatment (AB) is missing, we investigated the predictive values of whole transcriptomic gene expression analysis (WTGE) applied on biopsy tissue. Methods: 50 pretherapeutic formalin fixed paraffin embedded specimens of ESCC patients from SAKK 75/08 study were analyzed for the effect of RCTX with and without anti-EGFR AB. As well as 26 historic controls of primary resected tumor stage equally distributed ESCC were analyzed. For the advanced setting, we analyzed 28 additional pretherapeutic biopsies and compared groups from CTX to CTX plus AB. The HTG EdgeSeq method was used for NGS-based WTGE. Response to treatment was assessed by histopathological tumor regression in localized disease and clinical courses. Response to treatment in the advanced tumor setting was assessed to the clinical course of stable disease and partial response versus non-responders. Results: Firstly, NGS-based WTGE failed to show significant differences in expression patterns between responding and non-responding ESCC patients, irrespective of treatment protocols and EGFR AB in the localized as well in advanced disease setting. Secondly however, comparison between pre-treatment biopsies and posttreatment residual tumor tissues detected 781 genes that were upregulated and 623 that were downregulated with gene sets associated with muscle processes and epithelial-mesenchymal transition (EMT) in the localized disease. EMT genes were also enriched in residual tumors after neoadjuvant RCTX compared to primary resection in an independent control cohort. Additionally performed immunohistochemical studies showed lower numbers of ZEB-1 positive ESCC in an independent collection of tumors treated by neoadjuvant RCTX compared to primary resection. Conclusions: Our Whole transcriptomic gene expression analyses suggest that EMT is involved in responses to neoadjuvant protocols including EGFR targeting therapies. Targeting EMT may be a molecular pathway to increase complete responses after neoadjuvant RCTX in ESCC.

Cardiac Resynchronization Therapy. Long-Term Evolution of Responder and Non-Responder Patients

Background: Cardiac resynchronization therapy (CRT) is an effective treatment in patients with heart failure (HF), low left ventricular ejection fraction (LVEF) and wide QRS. However, there are a percentage of these patients who are non-responders, implying worse clinical outcomes. Objectives: The aim of this study was to assess the differences in echocardiographic parameters of reverse remodeling and event rates [hospitalization for heart failure (HHF), all-cause mortality (ACM), heart transplantation (HTX) and appropriate therapies (AT)] between responder vs. non-responder patients to CRT. Methods: A total of 343 patients with CRT, classified into responders and non-responders according to clinical and echocardiographic parameters, were included in the study. A 2-year follow-up was performed, in which reverse remodeling and the incidence of HHF, ACM, HTX and AT were evaluated. Results: Among the 343 patients, 17% were non-responders and 83% responders. At 6 and 12 months there were no significant differences in ventricular diameters, but significant differences in LVEF (p<0.001), with greater increase in responders. At 24 months, responders had smaller diastolic diameter (p=0.004), smaller systolic diameter (p=0.003) and higher LVEF (p<0.001). Non-responders had significantly higher incidence of HHF (p<0.001), HTX (p=0.001) and AT (p=0.002), and an excess of ACM at the limit of statistical significance (p= 0.056). Conclusions: Patients responding to CRT presented greater reverse remodeling and better clinical evolution, in accordance with the results of international observational studies.

Association of artificial intelligence–derived collagen disorder architecture (CoDA) features with survival outcome and objective response to immune checkpoint inhibitors in patients with head and neck squamous cell carcinoma.

6061 Background: In several cancers, including head and neck squamous cell carcinoma (HNSCC), the immunosuppressive components of the tumor microenvironment (TME) can impact the effectiveness of immune checkpoint inhibitors (ICI). One significant component of the TME is the extracellular matrix, which is rich in collagen fibers. In this work we used machine learning and image analysis approaches on whole slide images (WSIs) to characterize collagen disorder architecture (CoDA) features and evaluated their association with outcomes in HNSCC patients receiving ICI. Methods: WSIs of HNSCC patients treated with ICI were obtained from University Hospitals (S1, n=43) and Emory University (S2, n=31). Tiles from the tumor annotated regions of the WSIs were extracted, and a derivative-of-Gaussian model was used to identify collagen fibers in the stroma of these tiles. Various CoDA features were then calculated as follows: (1) collagen fiber fragmentation measure, (2) collagen fiber bundling percentage, (3) collagen fiber rigidity measure, (4) collagen fiber anisotropy index and (5) collagen fiber density index. CoDA features of S1and S2 were combined and split into 50:50 for training and validation. For survival analysis using overall survival (OS) as endpoint, the median risk score in the training set was applied for risk stratification in the validation set by means of a Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression model. For predictive analysis, CoDA features from patients with objective response (OR) to ICI were identified (S1, non-responder=23, responder=20), (S2, non-responder=23, responder=8). The top features were then selected using the LASSO and combined with a Generalized Linear Model classifier. A 5-fold cross-validation assessed Area Under the Receiver Operating Characteristics Curve (AUC) for predicting OR, with average AUC as the final performance metric in the validation set. Results: For survival analysis, high risk patients in the validation set had worse survival than low risk patients (HR=2.7 (95% CI=1.1-6.6, p=0.02)). For predicting OR, the selected top CoDA features were collagen fiber fragmentation measure, collagen fiber bundling percentage, collagen fiber rigidity measure and collagen fiber density index and the average AUC was 0.64±0.16. More fragmentation of the collagen fibers along with dense thick bundles and straightened fibers were observed in the WSIs of non-responder patients to ICI. Conclusions: High risk CoDA features correlated with worse survival in patients with HNSCC receiving ICI. Also, we established a correlation of specific CoDA features with OR to ICI. The prognostic and predictive value of CoDA deserves additional exploration with confirmatory data from larger, independent multi-site validation.

An MRI-based multi-parameter clinical decision support system (NeoMDSS) for early prediction of pathological complete response after the first cycle of neoadjuvant therapy in breast cancer: A multi-center prospective observational cohort study.

592 Background: Currently, there is no reliable and convenient way to predict response rates in early stages of neoadjuvant therapy (NAT) for breast cancer, which can affect the prognosis of non-responsive patients. Methods: In this prospective multi-center observational study, eligible participants who underwent NAT followed by radical surgery were recruited. All patients underwent magnetic resonance imaging (MRI) examination before and after the first cycle of NAT (1st-NAT). We analyzed the effects of clinicopathological features, such as histological grade, hormone receptor (HR) and HER2 status, Ki-67 expression, blood cell analysis, and MRI parameters including the reduction ratio of tumor diameter (ΔD%), apparent diffusion coefficient (ADC), and early enhancement ratio (EER) on NAT. By incorporating independent influencing factors, we developed a multiparametric clinical decision support system (NeoMDSS) model based on a retrospective cohort and validated its accuracy in both a prospective single-center internal cohort and a prospective multi-center external cohort. Relevant clinical trial details can be found under the identifier NCT04909554. Results: A total of 301 breast cancer patients were enrolled between January 2019 and December 2023, including 140 patients in the training cohort, 120 patients in the internal validation cohort, and 41 patients in the external validation cohort. The NeoMDSS model demonstrated excellent performance in predicting pathological complete response (pCR) at 1st-NAT, with an AUC of 0.874 (95% CI 0.813-0.935) in the training cohort, 0.845 (95% CI 0.771-0.919) in the internal validation cohort, and 0.867 (95% CI 0.742-0.992) in the external validation cohort. The NeoMDSS model exhibited a sensitivity, specificity, and accuracy of 80.0%, 81.3%, and 80.5%, respectively, in the internal validation cohort, and 87.0%, 83.3%, and 85.4%, respectively, in the external validation cohort. Calibration curves and decision curve analysis (DCA) further supported the clinical value of the NeoMDSS model. To facilitate the clinical application of the NeoMDSS model, a nomogram and an online website ( www.gdphneomdss.com ) were developed to calculate the probability of pCR, which the sensitivity, specificity, and accuracy of the NeoMDSS model were all 80.0% in the internal validation cohort and 80.0%, 81.3%, and 80.5% in the external validation cohort. Conclusions: The NeoMDSS model serves as a convenient tool in clinical practice at 1st-NAT to calculate and accurately predict the probability of pCR after NAT. This assists clinicians in determining whether to modify the treatment plan and improving personalized treatment for patients with poor response to NAT. Clinical trial information: NCT04909554 .

Cannabidiol-enriched oil for adult patients with drug-resistant epilepsy: Prospective clinical and electrophysiological study.

Cannabidiol-enriched oil (CBDO) is being used increasingly to improve seizure control in adult patients with drug-resistant epilepsy (DRE), despite the lack of large-scale studies supporting its efficacy in this patient population. We aimed to assess the effects of add-on CBDO on seizure frequency as well as on gait, cognitive, affective, and sleep-quality metrics, and to explore the electrophysiological changes in responder and non-responder DRE patients treated with add-on CBDO. We prospectively recruited adult DRE patients who were treated with add-on CBDO. Patients were evaluated prior to treatment and following 4 weeks of a maintenance daily dose of ≈260 mg CBD and ≈12 mg Δ9-tetrahydrocannabinol (THC). The outcome measures included seizure response to CBDO (defined as ≥50% decrease in seizures compared to pre-CBDO baseline), gait testing, Montreal Cognitive Assessment (MoCA), Hospital Anxiety and Depression Scale (HADS), and sleep-quality questionnaire assessments. Patients underwent electroencephalography (EEG) recording during rest as well as event-related potentials (ERPs) during visual Go/NoGo task while sitting and while walking. Nineteen patients were recruited, of which 16 finished pre- and post-CBDO assessments. Seven patients (43.75%) were responders demonstrating an average reduction of 82.4% in seizures, and nine patients (56.25%) were non-responders with an average seizure increase of 30.1%. No differences in demographics and clinical parameters were found between responders and non-responders at baseline. However, responders demonstrated better performance in the dual-task walking post-treatment (p = .015), and correlation between increase in MoCA and seizure reduction (r = .810, p = .027). Post-CBDO P300 amplitude was lower during No/Go-sitting in non-responders (p = .028) and during No/Go-walking in responders (p = .068). CBDO treatment can reduce seizures in a subset of patients with DRE, but could aggravate seizure control in a minority of patients; yet we found no specific baseline clinical or electrophysiological characteristics that are associated with response to CBDO. However, changes in ERPs in response to treatment could be a promising direction to better identify patients who could benefit from CBDO treatment.

A predictive study of the efficacy of transcutaneous auricular vagus nerve stimulation in the treatment of major depressive disorder: An fMRI-based machine learning analysis

BackgroundIn order to improve taVNS efficacy, the usage of fMRI to explore the predictive neuroimaging markers would be beneficial for screening the appropriate MDD population before treatment. MethodsA total of 86 MDD patients were recruited in this study, and all subjects were conducted with the clinical scales and resting-state functional magnetic resonance imaging (fMRI) scan before and after 8 weeks’ taVNS treatment. A two-stage feature selection strategy combining Machine Learning and Statistical was used to screen out the critical brain functional connections (FC) that were significantly associated with efficacy prediction, then the efficacy prediction model was constructed for taVNS treating MDD. Finally, the model was validated by separated the responding and non-responding patients. ResultsThis study showed that taVNS produced promising clinical efficacy in the treatment of mild and moderate MDD. Eleven FCs were selected out and were found to be associated with the cortico-striatal-pallidum-thalamic loop, the hippocampus and cerebellum and the HAMD-17 scores. The prediction model was created based on these FCs for the efficacy prediction of taVNS treatment. The R-square of the conducted regression model for predicting HAMD-17 reduction rate is 0.44, and the AUC for classifying the responding and non-responding patients is 0.856. ConclusionThe study demonstrates the validity and feasibility of combining neuroimaging and machine learning techniques to predict the efficacy of taVNS on MDD, and provides an effective solution for personalized and precise treatment for MDD.

The clinical assessment of changes in bone density in rheumatoid arthritis patients': Role of DEXA scan and bone turnover biomarkers

In addition to generalised of bone loss and a higher fracture risk, rheumatoid arthritis (RA) causes periarticular bone erosions. Improvements in bone density/erosion and turnover may not go hand in hand with a positive clinical response to biological anti-inflammatory drugs assesed by disease activity score 28 (DAS28) in RA patients. This study aimed to understand how biologic anti-inflammatory drugs affect bone density, erosion, and turnover in RA patients. We examined bone mineral density (BMD) and bone turnover biomarkers. The study population consisted of 62 RA patients, 49 (79%) of whom were female and 13 (21%) of whom were male. The patients ranged in age from 40 to 79 years old. The patients' BMD was measured using a DEXA scan, and their plasma levels of bone turnover biomarkers CTX and osteocalcin were quantified utilizing an ELISA. BMD of the hip and lumbar spine in responder patients rose after therapy by 0.001g/cm2 (0.11 percent, p0.001 vs. before treatment) and 0.0396g/cm2 (3.96 percent, p0.001 vs. before treatment), respectively. Clinically non-responder patients' DAS28 revealed minor reductions in hip BMD values of −0.008g/cm2 (−0.78 percent, p0.001 vs. before therapy), as well as an improvement in lumbar spine BMD of 0.03g/cm2 (3.03 percent, p0.001 vs. before treatment). After 12 weeks of therapy, the CTX levels in responder patients dropped from 164 125 pg/ml to 131 129 pg/ml. Osteocalcin levels in non-responder patients increased substantially from 11.6 ng/ml to 14.9 ng/ml after 12 weeks of therapy compared to baseline (p = 0.01). Treatment with biologic anti-inflammatory medicines decreases widespread bone loss in RA patients' hip and lumbar spine. The beneficial effects of therapy on BMD were not associated with changes in disease activity of RA patients. Changes in plasma levels of bone turnover biomarkers such as sCTX and osteocalcin confirmed the treatment's beneficial effects.

#509 Idiopathic nephrotic syndrome in children in Chad

Abstract Background and Aims The objective of our study was to describe the characteristics and outcomes of Nephrotic Syndrome (SN) in children from three major hospitals in one of the world's poorest countries, Chad. Method This observational, cross-sectional, descriptive, and multicenter study took place over a period of 36 months (1 January 2019–31 December 2021) and was carried out in three hospitals in N'Djamena, Chad. Children aged 1–15 years presenting with NS were included in the study. Results Out of 16,776 children hospitalized or followed up with in outpatient clinics, 24 cases of NS were identified, yielding a prevalence of 0.14%. The median age at presentation was 6.16 years (1–10). Nineteen children were male (sex ratio 3.8). Eight cases were classified as impure NS (33.3%). Edema was present in all patients, while oliguria was present in 29.16% (n = 7), and arterial hypertension was present in 20.83% (n = 5) of cases. Mean proteinuria, albuminemia, and total proteins were 2.86 g/L, 19.13 g/L and 30.41 g/L, respectively. The median serum creatinine was 87.3 µmol/L (75–1375 µmol/L). Three patients experienced acute renal failure upon admission. Four patients had secondary NS. All idiopathic NS patients (n = 20) who had received corticosteroid therapy had a 90% response rate to steroids. Non-responsive or relapsed patients underwent kidney biopsy (n = 7), revealing focal segmental glomerulosclerosis (FSGS; n = 4) as the most common histological lesion, followed by minimal change disease (n = 2) and membranoproliferative glomerulonephritis (n = 1). The median length of hospitalization stay was 10.67 (5–27) days. None of the patients with idiopathic NS died. At the last follow-up, sixteen patients (80%) achieved long-term complete remission with normal renal function; however, four of those had subsequent relapses. One patient with secondary NS died. Conclusion In Chad, childhood idiopathic nephrotic syndrome predominantly affects young males; steroid sensitivity is as high as 95%, and in the long-term, 80% of patients achieve remission with normal renal function.

Plasma microRNA Signature as Companion Diagnostic for Abiraterone Acetate Treatment in Metastatic Castration-Resistant Prostate Cancer: A Pilot Study.

Abiraterone acetate (AA) serves as a medication for managing persistent testosterone production in patients with metastatic castration-resistant prostate cancer (mCRPC). However, its efficacy varies among individuals; thus, the identification of biomarkers to predict and follow treatment response is required. In this pilot study, we explored the potential of circulating microRNAs (c-miRNAs) to stratify patients based on their responsiveness to AA. We conducted an analysis of plasma samples obtained from a cohort of 33 mCRPC patients before and after three, six, and nine months of AA treatment. Using miRNA RT-qPCR panels for candidate discovery and TaqMan RT-qPCR for validation, we identified promising miRNA signatures. Our investigation indicated that a signature based on miR-103a-3p and miR-378a-5p effectively discriminates between non-responder and responder patients, while also following the drug's efficacy over time. Additionally, through in silico analysis, we identified target genes and transcription factors of the two miRNAs, including PTEN and HOXB13, which are known to play roles in AA resistance in mCRPC. In summary, our study highlights two c-miRNAs as potential companion diagnostics of AA in mCRPC patients, offering novel insights for informed decision-making in the treatment of mCRPC.

Abstract PR011: Imaging mass cytometry captures patient heterogeneity enabling BCG response stratification in non-muscle invasive bladder cancer

Abstract BCG immunotherapy is the standard of care for high-risk non-muscle invasive bladder cancer (NMIBC). The mechanisms of response to BCG are not fully understood. Patient response to BCG is highly variable with ~30-40% of individuals experiencing recurring or progressing disease after treatment within 24 months. Prognostic markers of response to treatment are not fully understood and remain insufficient for patient stratification. In order to develop an understanding of BCG response by comprehensive assessment of the tumor context. We performed single cell spatial proteomic profiling via imaging mass cytometry (IMC) on tissue microarrays of tumor biopsies from 53 bladder cancer patients (36 responding and 17 non-responding). We then validated our finding on an external cohort of whole pathology slides from 10 patients (4 responding and 6 non-responding). The IMC panel was developed based on scRNAseq profiles of bladder tumor samples to provide an unbiased cellular context of NMIBC. Additionally, IMC data is accompanied by hematoxylin and eosin (H&E) images of adjacent cuts and annotated by a clinical pathologist to distinguish tumor, immune, and stromal regions. We first developed a convolutional neural network (CNN) to reproduce pathologist annotations of tumor, stroma, and immune regions from H&E data with high accuracy (AUC>93%). We then registered IMC and annotated H&E images to train a random forest model to predict pathologist annotations using IMC data (AUC>95%). To determine the cellular composition of TMA spots, we used sparse non-negative matrix factorization (sNMF) to encode and cluster IMC data within tumor, stroma, and immune regions. NMF analysis revealed that a component defined primarily by KRT5, CD11b, and CD14, specifically within tumor-annotated regions adjoining COL1A1+ stromal regions, is a prognostic marker of poor response (p-value<0.05). This is consistent with previous findings that tumor-associated myeloid cells indicate poor prognosis. Additional NMF components of the immune annotated region showed weak associations with response. Immune regions defined by CD68, CD11b, CD31, and PDPN corresponded with poor BCG response, indicating myeloid-stromal-vascular interactions outside the tumor influence outcome, while vascular immune regions defined by high aSMA presence correspond with better response. Collectively, combining NMF components to generate a single response score for responding and non-responding patients (p-value<0.05) proved more effective at patient stratification than any single NMF component alone. The external cohort validated our random forest model for separating tumor, stroma, and immune regions, our sNMF model for clustering IMC images, and our response score (p-value<0.1). Citation Format: Ali Foroughi Pour, Dylan Baker, Santhosh Sivajothi, Bonnie Choy, Khyati Meghani, Yanni Yu, Leigh A. Fall, Benjamin Ristau, Joshua J. Meeks, Paul Robson, Jeffrey H. Chuang. Imaging mass cytometry captures patient heterogeneity enabling BCG response stratification in non-muscle invasive bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr PR011.

Study of lncRNAs expression profile in the response to biological drugs in Psoriatic Arthritis: MEG3 could be a potential genomic biomarker of therapy efficacy

We aimed to identify an expression profile of lncRNAs potentially related to treatment response in Psoriatic arthritis (PsA) patients, to be used as potential genomic biomarkers predictors of drug treatment effectiveness. In addition, we evaluated a possible association between lncRNAs genetic variants and the response to therapy using the clinical parameter of Disease Activity Index. For the expression study, we collected 48 treated PsA patients, monitoring the treatment response for 12 months. We initially used PCR Array and, then, we validated the results with qRT-PCR. We also retrospectively genotyped 163 treated PsA patients. Firstly, we observed a significant difference in the expression level between Responder and non-Responder patients, of 4 lncRNAs in the group of PsA patients treated with TNFi and of 3 lncRNAs in the group of patients treated with IL17i. Then, we confirmed a significant decrease of MEG3 expression in non-Responder patients compared to Responders, also considering separately the single groups of patients treated with TNFi and IL17i. In addition, our results seem to highlight a potential dose-dependent effect of rs941576 (MEG3) variant allele on Disease Activity Index. Our study suggests a possible role of the lncRNA MEG3 in the treatment response to biological drugs.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (). In addition, the change in normalized tumor upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

Abstract PO4-05-05: Immune Activation Signatures for predicting CDKi primary response in advanced breast cancer patients

Abstract Background Cyclin Dependent Kinase inhibitors (CDKi’s) in combination with Endocrine Therapy (ET) have changed the first line management of patients with the most common subtype (HR+, HER2-) of metastatic breast cancer (MBC), improving progression-free survival (PFS) and overall survival. However, in approved indications for advanced breast cancer, approximately 20% of patients have been observed to have no response to CDKi’s and ET, and to progress after starting these therapies. Unlike other targeted therapeutics, there is no companion diagnostic or other clinically reliable biomarker for clinical decision support to indicate which patients will and will not benefit from CDKi therapy. Methods We have developed a novel platform that measures the Immune Activation Signature of patient plasma samples. Via simple measurements of the total concentration of protein-incorporated amino acid residues within patient plasma samples, the platform is designed to reveal changes in the proportion of immunoglobulins and albumin, and class-switching among immunoglobulins. For that purpose, we use Bioorthogonal chemical labelling reactions to label the protein-incorporated amino acids residues within the plasma. We measured the plasma samples of N=30 HR+, HER2- MBC patients, median age 54 years old, who were baseline naïve for CDKi’s treatment (16 on palbociclib, 11 on ribociclib, and 3 on abemaciclib) and ET. Eighteen patients had metastatic visceral disease and 12 patients had bone-only MBC. All patients were prospectively followed, and response assessed according to RECIST criteria on a CT scan every 3-months. Results Non-responding patients developed objective progressive disease during the first 6 months after starting CDKis and ET. In this cohort, 4 patients (13%) were classified as non-responders. The median PFS in non-responding patients was 4.5 months (4.03-5.02) and the median PFS in the cohort of responding patients was 16.6 months (6.8 – 40.9). The Immune Activation Signatures of the Responding and Non-Responding patients are shown in table 1. We analyzed the results with classical statistics and machine learning. A multivariate analysis of variance (MANOVA) test of the null hypothesis that the Immune Activation Signatures of Non-Responders and Responders are the same gave p = 0.00388. We analyzed the measured Immune Activation Signatures using a supervised machine learning classifier and observed in a held-back validation set correct prediction of 100% of non-responding patients and 95% accurate predictions overall. Conclusions According to these results, this platform may provide a clinically helpful biomarker for clinical decision support in the advanced or aggressive breast cancer context (patients with visceral metastasis bordering on visceral crisis), or for patient stratification in new indications. Table. Immune Activation Signature measurements (mean values in Clinical Outcome) Citation Format: Luis Costa, Cong Tang, Emma Yates, Qi Shi, Wesley Sukdao, Patricia Corredeira, Gonçalo Costa, Helena Pais, Catarina Abreu, Leonor Ribeiro, Rita Teixeira de Sousa, Sofia Torres, André Mansinho, Sandra Casimiro, Ana Cavaco, Patricia Alves, Angela Rodrigues, Lisiana Szeneszi, Gonçalo Bernardes. Immune Activation Signatures for predicting CDKi primary response in advanced breast cancer patients [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-05-05.

Abstract PO5-25-03: Immune cell infiltrate profiles in primary Triple Negative Breast Cancer and co-relation with treatment response and survival outcomes

Abstract Introduction Tumor microenvironment (TME) in breast cancer is a heterogeneous landscape with multiple cell types, each modulating the tumor progression and the disease prognosis. These cell types include lymphocytes, RBCs, stromal cells, macrophages, cancer-associated fibroblasts (CAFs), and cancer stem cells. Each cell type in the TME influences tumor progression and clinical outcomes for patients in a good or bad way, depending on the interaction with tumor cells. Tumor-infiltrating lymphocytes (TILs) are shown to be prognostic for therapy response in many cancers in the western cohorts. Our recent study showed that a higher proportion of Indian TNBC patients had intra-tumoral TILs compared to Western cohorts, and these are predictive of better response to NACT and longer disease-free survival in patients, making it a distinct finding from Western reports. In the follow-up study, we are characterizing infiltrating immune cell subtypes and their comparative association with treatment response in TNBC patients. Results from preliminary analysis and comparative analysis between responders and non-responders will be presented here. We speculate that the pro- and anti-tumorigenic immune cell population and its spatial information would help us understand TME and its precise role in response to therapy. Methods A retrospective cohort of breast cancer patients from a single one-surgeon breast cancer clinic with a uniform treatment strategy was evaluated for this study. FFPE primary tissue samples with variable TILs scores (moderate to high), taken from patients who showed complete response to the NACT treatment (n=6) and non-responding group (n=8) determined by H&E stained slides from our cohort, were further stained for immune cells (Pan-B cell, Pan-T cells, Pan-macrophages) and T cells (CD4; Helper T cell marker, CD8; Cytotoxic T cell marker), FOXP; Regularly CD4+ cell marker) and PanCK (Pan-tumor marker) and counterstained with DAPI for multiplex imaging. Multispectral images for these slides were obtained using the Leica Aperio Versa system. Parameters such as individual cell types of identification and scoring, spatial proximity to tumor cells, and individual cell types will be determined by HALO software using the High plex module. Results A total of 14 TNBC samples were stained for the T-cell subtypes panel and Immune cell subtype s panel to determine the TIME. DAPI stain was used for nuclear counting based the parameters such as threshold intensity, nuclear size, roundness, and aggressiveness. The cytoplasmic size was selected as 2um beyond the outside nuclear boundary. Using Halo-Indica software, around 50000-300000 cells/tissue were evaluated across all samples from mIF whole slide scans of biopsy samples. Cell count was validated by cross-checking individual ROIs and manual cell count using Fiji. A Highplex module was used to identify individual signal positivity for each marker based on threshold intensity and cell completeness percent. Preliminary data showed a higher proportion of CD8+ cells and macrophages population are spatially closer to the tumor cells in Responders compared to non-responders. Conclusion Immune profiles are distinct among responding and non-responding patients in the Indian TNBC cohort. The association of these profiles with long-term survival in patients and various clinical and pathological parameters will help us determine the clinical relevance of these profiles and identify distinct immune subgroups as prognostic in Indian TNBCs. Citation Format: Pooja Vaid, Devaki Kelkar, LS Shashidhara, C B Koppiker, Madhura Kulkarni. Immune cell infiltrate profiles in primary Triple Negative Breast Cancer and co-relation with treatment response and survival outcomes [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-25-03.

Longitudinal outcomes of obeticholic acid therapy in ursodiol-nonresponsive primary biliary cholangitis: Stratifying the impact of add-on fibrates in real-world practice.

Suboptimal response to ursodeoxycholic acid occurs in 40% of primary biliary cholangitis (PBC) patients, affecting survival. Achieving a deep response (normalisation of alkaline phosphatase [ALP] and bilirubin ≤0.6 upper limit of normal) improves survival. Yet, the long-term effectiveness of second-line treatments remains uncertain. To evaluate the long-term effectiveness of obeticholic acid (OCA) ± fibrates. Focusing on biochemical response (ALP ≤1.67 times the upper limit of normal, with a decrease of at least 15% from baseline and normal bilirubin levels), normalisation of ALP, deep response and biochemical remission (deep response plus aminotransferase normalisation). We conducted a longitudinal, observational, multicentre study involving ursodeoxyccholic acid non-responsive PBC patients (Paris-II criteria) from Spain and Portugal who received OCA ± fibrates. Of 255 patients, median follow-up was 35.1 months (IQR: 20.2-53). The biochemical response in the whole cohort was 47.2%, 61.4% and 68.6% at 12, 24 and 36 months. GLOBE-PBC and 5-year UK-PBC scores improved (p < 0.001). Triple therapy (ursodeoxycholic acid plus OCA plus fibrates) had significantly higher response rates than dual therapy (p = 0.001), including ALP normalisation, deep response and biochemical remission (p < 0.001). In multivariate analysis, triple therapy remained independently associated with biochemical response (p = 0.024), alkaline phosphatase normalisation, deep response and biochemical remission (p < 0.001). Adverse effects occurred in 41.2% of cases, leading to 18.8% discontinuing OCA. Out of 55 patients with cirrhosis, 12 developed decompensation. All with baseline portal hypertension. Triple therapy was superior in achieving therapeutic goals in UDCA-nonresponsive PBC. Decompensation was linked to pre-existing portal hypertension.

Unsatisfactory response to acute medications does not affect the medication overuse headache development in pediatric chronic migraine

BackgroundChronic migraine (CM) negatively impacts the quality of life of 2 to 4% of pediatric patients. In adults, CM is frequently linked to medication overuse headache (MOH), but there is a much lower prevalence of MOH in children. A suboptimal response to acute therapies may lead to their reduced use, thus preventing MOH development in children and adolescents. The frequency of patients with CM who do not respond to acute therapies was examined in the present study. We investigated whether the prevalence of MOH was different between responders and non-responders. We also examined whether patients receiving prophylactic therapy had an improved response to acute therapy. Finally, we investigated if there was a difference in the frequency of psychiatric comorbidities between responders and non-responders.MethodsWe retrospectively analysed clinical data of all chronic pediatric migraineurs under the age of 18 referred to the Headache Centre at Bambino Gesù Children Hospital in June 2021 and February 2023. ICHD3 criteria were used to diagnose CM and MOH. We collected demographic data, including the age at onset of migraine and the age of the CM course. At baseline and after 3 months of preventive treatment, we evaluated the response to acute medications. Neuropsychiatric comorbidities were referred by the children’s parents during the first attendance evaluation.ResultsSeventy patients with CM were assessed during the chosen period. Paracetamol was tried by 41 patients (58.5%), NSAIDs by 56 patients (80.0%), and triptans by 1 patient (1.4%). Fifty-one participants (73%) were non-responder to the abortive treatment. The presence of MOH was detected in 27.1% of the whole populations. Regarding our primary aim, MOH was diagnosed in 29% of non-responder patients and 22% of responders (p > 0.05). All patients received preventative treatment. After 3 months of preventive pharmacological therapy, 65.4% of patients who did not respond to acute medications achieved a response, while 34.6% of patients who were non-responder remain non-responder (p < 0.05). Prophylactic therapy was also effective in 69% of patients who responded to acute medication (p < 0.05). Psychiatric comorbidities were detected in 68.6% of patients, with no difference between responders and non-responders (72.2% vs. 67.3%; p = 0.05).ConclusionsDespite the high prevalence of unresponsiveness to acute therapies in pediatric CM, it does not act as a protective factor for MOH. Moreover, responsiveness to acute drugs is improved by pharmacological preventive treatment and it is not affected by concomitant psychiatric comorbidities.