Checkpoint Inhibitor Immunotherapy Research Articles

Integrating Novel Agents Into the Clinical Management of Classic Hodgkin Lymphoma.

Classic Hodgkin lymphoma (cHL) is highly curable at all stages. Research efforts over the past few decades have largely focused on interim PET-adapted strategies for therapy de-escalation or intensification. The overarching goals have been to increase cure rates, minimize potential therapy-related effects, and optimize survivorship. Better understanding of the biology of cHL has led to the development and approval of effective novel agents including the antibody-drug conjugate brentuximab vedotin and the checkpoint inhibitor immunotherapies. In this review, we discuss recent trial results and how these agents are integrated into clinical practice with the goal of further optimizing outcomes.

Promising Therapeutic Strategies for Hematologic Malignancies: Innovations and Potential.

In this review we explore innovative approaches in the treatment of hematologic cancers by combining various therapeutic modalities. We discuss the synergistic potential of combining inhibitors targeting different cellular pathways with immunotherapies, molecular therapies, and hormonal therapies. Examples include combining PI3K inhibitors with proteasome inhibitors, NF-κB inhibitors with immunotherapy checkpoint inhibitors, and neddylation inhibitors with therapies targeting the tumor microenvironment. Additionally, we discuss the potential use of small molecules and peptide inhibitors in hematologic cancer treatment. These multidimensional therapeutic combinations present promising strategies for enhancing treatment efficacy and overcoming resistance mechanisms. However, further clinical research is required to validate their effectiveness and safety profiles in hematologic cancer patients.

Cancer and Hidradenitis Suppurativa

Hidradenitis suppurativa patients have an increased risk of developing cancer. This includes not only hematologic malignancies and solid tumors, but also cutaneous squamous cell carcinoma originating within the hidradenitis suppurativa lesions. The development of squamous cell carcinoma is most commonly associated with Caucasian men who smoke and have severe gluteal or perianal lesions of more than 25 years duration. Other factors that have occasionally been associated with hidradenitis suppurativa-related squamous cell carcinoma include treatment with a tumor necrosis factor-alpha inhibitor (such as infliximab and adalimumab), genodermatoses (such as keratitis-ichthyosis-deafness syndrome and Dowling-Degos disease), and paraneoplastic syndromes (such as hypercalcemia, hypercalcemia-leukocytosis, and paraneoplastic neuropathy). The tumor may demonstrate the presence of human papillomavirus; even after treatment, patients have a poor prognosis since cancer metastasis, or recurrence, or both commonly occurs. The potential role of human papillomavirus vaccination for cancer prevention and early treatment of squamous cell carcinoma with targeted therapy (with an epidermal growth factor inhibitor such as cetuximab) and/or checkpoint inhibitor immunotherapy (such as cemiplimab and pembrolizumab) remains to be determined. Rarely, hidradenitis suppurativa lesions have mimicked cutaneous metastases in patients with visceral malignancy by demonstrating an increased uptake of fluorine-18 fluorodeoxyglucose on positron emission tomography and/or computerized tomography scans. Also, both primary cancers (such as cutaneous squamous cell carcinoma and mucinous adenocarcinoma) and breast cancer skin metastases can masquerade as hidradenitis suppurativa lesions. Therefore, when a lesion is located at a current or prior site of hidradenitis suppurativa that is new or rapidly growing and/or does not respond to hidradenitis suppurativa-directed therapy, prompt evaluation to establish or exclude the diagnosis of cancer should be considered.

Disulfidptosis and ferroptosis related genes define the immune microenvironment and NUBPL serves as a potential biomarker for predicting prognosis and immunotherapy response in bladder cancer

BackgroundFerroptosis and disulfidptosis are regulatory forms of cell death that play an important role in tumorigenesis and progression. However, few biomarkers about disulfidptosis and ferroptosis related genes (DFRGs) have been developed to predict the prognosis of bladder cancer (BC). MethodsWe conducted a bioinformatics analysis using public BC datasets to examine the prognostic significance of differentially expressed DFRGs. A Lasso regression was employed to create a prognostic prediction model from these DFRGs. Hub DFRGs that play a role in immunotherapy response and immunoregulation were pinpointed. Immunohistochemistry (IHC) experiment was performed to assess NUBPL and c-MYC expression in BC patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy at Peking University Cancer Hospital. ResultsWe constructed a valid model to predict the prognosis of BC based on DFRGs and performed relevant validation, the results demonstrated that the model was an independent prognostic factor for BC. Further analysis indicated that the model score, combined with the expression of various immune factors and tumor mutation burden (TMB), could predict the prognosis for BC. In addition, we also found that NUBPL was strongly associated with prognosis and response to ICI treatment, and NUBPL may influence BC malignant progression through the c-MYC pathway. ConclusionsOur research findings highlight the satisfactory predictive value of DFRGs in the immune microenvironment and suggest that NUBPL may be a highly promising biomarker for predicting the prognosis and efficacy of ICI treatment in BC patients.

Validation of the C-X-C chemokine receptor 3 (CXCR3) as a target for PET imaging of T cell activation

PurposeCXCR3 is expressed on activated T cells and plays a crucial role in T-cell recruitment to the tumor microenvironment (TME) during cell-based and immune checkpoint inhibitor (ICI) immunotherapy. This study utilized a 64Cu-labeled NOTA-α-CXCR3 antibody to assess CXCR3 expression in the TME and validate it as a potential T cell activation biomarker in vivo.ProceduresCXCR3+ cells infiltrating MC38 tumors (B57BL/6 mice, untreated and treated with αPD-1/αCTLA-4 ICI) were quantified using fluorescence microscopy and flow cytometry. A commercial anti-mouse CXCR3 antibody (α-CXCR3) was site-specifically conjugated with 2,2,2-(1,4,7-triazacyclononane-1,4,7-triyl)triacetic acid (NOTA) and radiolabeled with 64Cu. Saturation binding of [64Cu]Cu-NOTA-α-CXCR3 was investigated using CHO cells stably transfected with murine CXCR3. Biodistribution and PET imaging studies both at baseline and after 1 to 3 cycles of ICI, respectively, were carried out using different molar activities (10 GBq/µmol to 300 GBq/µmol) of [64Cu]Cu-NOTA-α-CXCR3.ResultsFlow cytometry analysis at baseline confirmed the presence of CXCR3 + T-cells in MC38 tumors, which was significantly increased at day five after ICI (treated 33.8 ± 17.4 vs. control 8.8 ± 6.2 CD3+CXCR3+ cells/mg). These results were qualitatively and quantitatively confirmed by immunofluorescence of tumor cryoslices. In vivo PET imaging of MC38 tumor bearing mice before, during and after ICI using [64Cu]Cu-NOTA-α-CXCR3 (Kd = 3.3 nM) revealed a strong dependence of CXCR3-specificity of tracer accumulation in secondary lymphoid organs on molar activity. At 300 GBq/µmol (1.5 µg of antibody/mouse), a specific signal was observed in lymph nodes (6.33 ± 1.25 control vs. 3.95 ± 1.23%IA/g blocking) and the spleen (6.04 ± 1.02 control vs. 3.84 ± 0.79%IA/g blocking) at 48 h p.i. Spleen-to-liver ratios indicated a time dependent systemic immune response showing a steady increase from 1.08 ± 0.19 (untreated control) to 1.54 ± 0.14 (three ICI cycles).ConclusionsThis study demonstrates the feasibility of in vivo imaging of CXCR3 upregulation under immunotherapy using antibodies. However, high molar activities and low antibody doses are essential for sensitive detection in lymph nodes and spleen. Detecting therapy-induced changes in CXCR3+ T cell numbers in tumors was challenging due to secondary antibody-related effects. Nonetheless, CXCR3 remains a promising target for imaging T cell activation, with anticipated improvements in sensitivity using alternative tracers with high affinities and favorable pharmacokinetics.

Development of a Multiplex Immunofluorescence Assay for Tumor Microenvironment Studies of Human and Murine Merkel Cell Carcinoma

Merkel cell carcinoma (MCC) is an aggressive cutaneous neuroendocrine carcinoma. Checkpoint inhibitor immunotherapy plays an essential role in management of advanced MCC; however, predictors of immunotherapy response remain poorly defined. Syngeneic mouse models suitable for testing novel immunotherapy and combination therapy approaches are likely to soon become available and will require assays for evaluating the tumor microenvironment (TME). Multiplex immunofluorescence (mIF) is a powerful approach to characterize the TME for understanding immunotherapy responses and immune surveillance. In this method article, we provide detailed instructions on assay development for mIF, using as examples 2 new mIF panels for TME investigations of human and murine MCC tumors. Specifically, we demonstrate panels that allow simultaneous visualization of the Merkel cell master transcription factor SOX2 for tumor cell identification, alongside T-cell markers (CD3, CD8, and FOXP3), macrophage markers (F4/80 for mouse and CD163 for human tumors), together with the checkpoint marker PD-L1 for human tumors, and the myeloid-derived suppressor cell marker Arg1 for mouse tumors. We provide detailed protocols for investigators to incorporate these mIF panels into their investigations of human and murine MCC. We also provide fundamental guidance for mIF assay development that will be broadly useful for investigators who consider modifying the panels presented in this study or developing their own mIF panels.

Transcriptomic observations of intra and extracellular immunotherapy targets for pediatric brain tumors

ABSTRACT Objectives Despite surgical resection, chemoradiation, and targeted therapy, brain tumors remain a leading cause of cancer-related death in children. Immunotherapy has shown some promise and is actively being investigated for treating childhood brain tumors. However, a critical step in advancing immunotherapy for these patients is to uncover targets that can be effectively translated into therapeutic interventions. Methods In this study, our team performed a transcriptomic analysis across pediatric brain tumor types to identify potential targets for immunotherapy. Additionally, we assessed components that may impact patient response to immunotherapy, including the expression of genes essential for antigen processing and presentation, inhibitory ligands and receptors, interferon signature, and overall predicted T cell infiltration. Results We observed distinct expression patterns across tumor types. These included elevated expression of antigen genes and antigen processing machinery in some tumor types while other tumors had elevated inhibitory checkpoint receptors, known to be associated with response to checkpoint inhibitor immunotherapy. Conclusion These findings suggest that pediatric brain tumors exhibit distinct potential for specific immunotherapies. We believe our findings can guide investigators in their assessment of appropriate immunotherapy classes and targets in pediatric brain tumors.

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy

We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in increasing prediction accuracy, further supporting the advantage of our hybrid approach.

Future Treatment Strategies for Cancer Patients Combining Targeted Alpha Therapy with Pillars of Cancer Treatment: External Beam Radiation Therapy, Checkpoint Inhibition Immunotherapy, Cytostatic Chemotherapy, and Brachytherapy.

Cancer is one of the most complex and challenging human diseases, with rising incidences and cancer-related deaths despite improved diagnosis and personalized treatment options. Targeted alpha therapy (TαT) offers an exciting strategy emerging for cancer treatment which has proven effective even in patients with advanced metastatic disease that has become resistant to other treatments. Yet, in many cases, more sophisticated strategies are needed to stall disease progression and overcome resistance to TαT. The combination of two or more therapies which have historically been used as stand-alone treatments is an approach that has been pursued in recent years. This review aims to provide an overview on TαT and the four main pillars of therapeutic strategies in cancer management, namely external beam radiation therapy (EBRT), immunotherapy with checkpoint inhibitors (ICI), cytostatic chemotherapy (CCT), and brachytherapy (BT), and to discuss their potential use in combination with TαT. A brief description of each therapy is followed by a review of known biological aspects and state-of-the-art treatment practices. The emphasis, however, is given to the motivation for combination with TαT as well as the pre-clinical and clinical studies conducted to date.

Targeting Hdm2 and Hdm4 in Anticancer Drug Discovery: Implications for Checkpoint Inhibitor Immunotherapy.

Hdm2 and Hdm4 are structural homologs that regulate the tumor suppressor protein, p53. Since some tumors express wild-type p53, Hdm2 and Hdm4 are plausible targets for anticancer drugs, especially in tumors that express wild-type p53. Hdm4 can enhance and antagonize the activity of Tp53, thereby playing a critical role in the regulation of p53's activity and stability. Moreover, Hdm2 and Hdm4 are overexpressed in many cancers, some expressing wild-type Tp53. Due to experimental evidence suggesting that the activation of wild-type Tp53 can augment the antitumor activity by some checkpoint inhibitors, drugs targeting Hdm2 and Hdm4 may be strong candidates for combining with checkpoint inhibitor immunotherapy. However, other evidence suggests that the overexpression of Hdm2 and Hdm4 may indicate poor response to immune checkpoint inhibitors. These findings require careful examination and scrutiny. In this article, a comprehensive analysis of the Hdm2/Hdm4 partnership will be conducted. Furthermore, this article will address the current progress of drug development regarding molecules that target the Hdm2/Hdm4/Tp53 partnership.

JAK inhibition enhances checkpoint blockade immunotherapy in patients with Hodgkin lymphoma.

Unleashing antitumor T cell activity by checkpoint inhibitor immunotherapy is effective in cancer patients, but clinical responses are limited. Cytokine signaling through the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway correlates with checkpoint immunotherapy resistance. We report a phase I clinical trial of the JAK inhibitor ruxolitinib with anti-PD-1 antibody nivolumab in Hodgkin lymphoma patients relapsed or refractory following checkpoint inhibitor immunotherapy. The combination yielded a best overall response rate of 53% (10/19). Ruxolitinib significantly reduced neutrophil-to-lymphocyte ratios and percentages of myeloid suppressor cells but increased numbers of cytokine-producing T cells. Ruxolitinib rescued the function of exhausted T cells and enhanced the efficacy of immune checkpoint blockade in preclinical solid tumor and lymphoma models. This synergy was characterized by a switch from suppressive to immunostimulatory myeloid cells, which enhanced T cell division.

A novel biomimetic nanoplasmonic sensor for rapid and accurate evaluation of checkpoint inhibitor immunotherapy.

Immune checkpoint inhibitors (ICIs) emerged as promising immunotherapies for cancer treatment, harnessing the patient's immune system to fight and eliminate tumor cells. However, despite their potential and proven efficacies, checkpoint inhibitors still face important challenges such as the tumor heterogeneity and resistance mechanisms, and the complex in vitro testing, which limits their widespread applicability and implementation to treat cancer. To address these challenges, we propose a novel analytical technique utilizing biomimetic label-free nanoplasmonic biosensors for rapid and reliable screening and evaluation of checkpoint inhibitors. We have designed and fabricated a low-density nanostructured plasmonic sensor based on gold nanodisks that enables the direct formation of a functional supported lipid bilayer, which acts as an artificial cell membrane for tumor ligand immobilization. With this biomimetic scaffold, our biosensing approach provides real-time, highly sensitive analysis of immune checkpoint pathways and direct assessment of the blocking effects of monoclonal antibodies in less than 20min/test. We demonstrate the accuracy of our biomimetic sensor for the study of the programmed cell death protein 1 (PD1) checkpoint pathway, achieving a limit of detection of 6.7ng/mL for direct PD1/PD-L1 interaction monitoring. Besides, we have performed dose-response inhibition curves for an anti-PD1 monoclonal antibody, obtaining a half maximal inhibitory concentration (IC50) of 0.43nM, within the same range than those obtained with conventional techniques. Our biomimetic sensor platform combines the potential of plasmonic technologies for rapid label-free analysis with the reliability of cell-based assay in terms of ligand mobility. The biosensor is integrated in a compact user-friendly device for the straightforward implementation in biomedical and pharmaceutical laboratories.

Basement membrane-related MMP14 predicts poor prognosis and response to immunotherapy in bladder cancer

BackgroundBasement membrane (BM) is an important component of the extracellular matrix, which plays an important role in the growth and metastasis of tumor cells. However, few biomarkers based on BM have been developed for prognostic assessment and prediction of immunotherapy in bladder cancer (BLCA).MethodsIn this study, we used the BLCA public database to explore the relationship between BM-related genes (BMRGs) and prognosis. A novel molecular typing of BLCA was performed using consensus clustering. LASSO regression was used to construct a signature based on BMRGs, and its relationship with prognosis was explored using survival analysis. The pivotal BMRGs were further analyzed to assess its clinical characteristics and immune landscape. Finally, immunohistochemistry was used to detect the expression of the hub gene in BLCA patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy in our hospital.ResultsWe comprehensively analyzed the relationship between BMRGs and BLCA, and established a prognostic-related signature which was an independent influence on the prognostic prediction of BLCA. We further screened and validated the pivotal gene-MMP14 in public database. In addition, we found that MMP14 expression in muscle invasive bladder cancer (MIBC) was significantly higher and high MMP14 expression had a poorer response to ICI treatment in our cohort.ConclusionsOur findings highlighted the satisfactory value of BMRGs and suggested that MMP14 may be a potential biomarker in predicting prognosis and response to immunotherapy in BLCA.

The role of response adapted therapy in the era of novel agents

The optimal treatment of classic Hodgkin Lymphoma (cHL) requires an individualized approach, with therapy guided by pretreatment clinical risk stratification and interim response assessment with positron emission tomography (PET). The overall goal is to achieve high cure rates while minimizing acute toxicity and late therapy-related effects. Interim PET-adapted strategies (iPET) were initially developed with traditional chemotherapy, reducing intensity after interim complete response and escalating treatment for patients with iPET+ disease. Recently, novel agents including brentuximab vedotin and the checkpoint inhibitor immunotherapies (CPIs) pembrolizumab and nivolumab have been adopted into the front-line treatment of cHL, and PET-adapted approaches may be relevant for these drugs as well. In this review we discuss response-adapted strategies utilizing novel agents, consider challenges including indeterminate radiographic findings with CPIs, and address emerging techniques for response assessment including new PET-based imaging metrics and the role of circulating tumor DNA.

Prediction of immune-related adverse events in urological cancer during checkpoint inhibitor immunotherapy through immunohistochemical analysis of tumorous LCP1/ADPGK.

e14699 Background: The expanded utilization of immune checkpoint inhibitors (ICIs) have successfully improved the outcome of cancer patients, yet the concomitant immune-related adverse events (irAEs) can lead to fulminant unfavorable consequences. Currently, a comprehensive approach to predict irAEs is lacking. Some relevant biomarkers derived from database analyses are still in the early stages of investigation and lack robust validation in clinical samples, including LCP1/ADPGK. Herein, we validated the performance of LCP1 and ADPGK in a retrospective patient cohort with advanced urological cancers undergoing ICIs treatment, while comparing the predictive efficacy between different algorithmic models. Methods: We retrospectively collected clinical data of patients with renal cell carcinoma (RCC), upper urinary tract epithelial carcinoma (UTUC), bladder cancer (BC) receiving anti-PD-1/PD-L1 treatment from 2020 to 2023 in Peking University First Hospital. Patients were categorized into irAEs and non-irAEs groups, with irAE assessments conducted by two expert urological oncologists. Immunohistochemistry (IHC) was performed on 5-µm-thick pre-treated FFPE tumor tissue sections. Results: A total of 112 patients were included in the study, comprising 60 with RCC, 21 with UTUC, and 31 with BC. Among them, 51 (45.5%) patients experienced irAEs, with 9 exhibiting severe irAEs of grade III-IV. Immunohistochemical analysis revealed higher expression levels of LCP1 and ADPGK in patients with irAEs compared to those without irAEs. The area under the receiver-operating characteristic curve (AUC) for predicting irAEs using LCP1 and ADPGK individually was 0.82 (p < 0.0001, 95%CI = 0.74-0.90) and 0.86 (p < 0.0001, 95%CI = 0.80-0.93), respectively. The combination of LCP1 and ADPGK demonstrated an improved AUC of 0.89 (p < 0.0001, 95%CI = 0.83-0.95). Among different algorithms, the bivariate linear-regression and the geometric mean model show similar prediction effects. Notably, the combined LCP1+ADPGK model successfully predicted irAEs in RCC (AUC = 0.89, p < 0.0001, 95%CI = 0.81-0.98), UTUC (AUC = 0.81, p = 0.0063, 95%CI = 0.63-0.99), and BC (AUC = 0.88, p = 0.0004, 95%CI = 0.75-1.00). The expression of LCP1/ADPGK was not associated with the type of cancers. Conclusions: The bivariate linear-regression model of LCP1 and ADPGK could accurately predict irAEs in patients with urological cancers, which may allow us to improve the risk-benefit balance for individuals considered for ICIs therapy.

Predicting immunotherapy toxicity through single-cell sequencing of peripheral immune cells: A pilot study.

e14538 Background: Immune checkpoint inhibitors are widely used in oncology. However, immune-related adverse events (iRAEs) are idiosyncratic and can be severe. The overall incidence is 27%, with severe iRAEs occurring in 6% of patients. We hypothesised that distinct immune cell phenotypes (gene expression) correlate with immune-related toxicity from checkpoint inhibitor immunotherapy. Single-cell RNA sequencing (scRNA-seq) is a powerful tool that can assay the gene expression of thousands of individual cells. RPS26 expression mediates CD4/CD8 T cell activation through a known trans-expressive quantitative trait locus at rs1131017 and is linked with autoimmunity. FOS and JUN encode for c-Fos and c-Jun, which dimerise to create the activator protein-1 complex, a well-established transcriptional factor of the immune system. c-Fos is an immunoregulator known to suppress pro-inflammatory cytokines, suggesting that c-FOS deficiency plays a crucial role in developing autoimmunity. We aimed to analyse the transcriptomic differences of peripheral immune cells between patients who experienced severe checkpoint inhibitor therapy iRAE and those who did not. Methods: We identified a pilot cohort of eight patients who developed grade three or above toxicity due to immune checkpoint inhibitors and eight controls who were matched for age, cancer and treatment type. Peripheral blood mononuclear cells were collected prospectively at baseline and two subsequent treatment cycles. Cells were captured on the 10x Chromium platform, and libraries were sequenced to 30,000 reads per cell. Samples were demultiplexed, and the data was analysed with the Seurat package on R statistical software (version 4.3.0). Results: Five patients had baseline samples only, two patients had two samples from two cycles, and one patient had samples from three cycles. After quality control filtering, we identified 36,288 cells from 16 individuals and 24 samples. Immune cells were annotated with the Azimuth package into 29 subtypes. We identified differences in cell proportions of immune cell subsets in the toxicity vs control group, including B naive cells (5.57% vs 3.71% p=0.01) and reduced cytotoxic CD4 T lymphocyte cells (0.66% vs 2.26%, p=0.005). Differential gene expression analysis identified a significantly high expression of ribosomal genes, particularly RPS26, in multiple cell types at baseline (p<0.01) and reduced expression of FOS and JUN-related genes in CD14 and CD16 monocytes, CD4 and CD8 T cells in the toxicity cohort (p<0.01). Conclusions: Overexpression of ribosomal genes and reduced expression of FOS/ JUN genes amongst PBMCs at baseline are potentially predictive biomarkers of severe checkpoint inhibitor immunotherapy toxicity. Validation of these findings in a larger cohort is in progress.

Immuno-related cardiac toxicity in patients with cancer: A prospective study applying multiparametric cardiac MRI.

e24014 Background: Since Immune checkpoint inhibitor (ICI) immunotherapy has emerged as a cornerstone of modern oncology, oncologists are facing a new spectrum of ‘immune-related adverse events’ (irAEs), potentially affecting every tissue and organ. ICI-induced symptomatic myocarditis occurs only in around 1% of ICI-treated patients (pts), but is fatal in 50% of cases. Methods: Pts undergoing ICI therapy at the Humanitas Cancer Center from May 2021 to December 2023 were prospectively recruited and assigned to three study groups: 1) ICI given as monotherapy (Mono) 2) ICI given in combination (Combo) 3) history of cardiac disease or two cardiological risk factors other than smoke (Cardio). Exclusion criteria were: previous exposure to any immunotherapy, combination with other cardiotoxic therapies, and acute (in the last 3 months) cardiac events. All pts underwent a complete cardiological assessment with clinical visit, 12-lead ECG, and multiparametric cardiac MRI (cMRI) at two time-points: prior initiation of the ICI therapy, and around 8 weeks later. Peripheral blood samples for immunophenotyping analyses were collected at the same time-points. cMRI scans were performed using a 1.5 Tesla scanner. Chi-square, Fisher exact and paired t-test were used to compare groups; all analyses were performed using SAS v9.4. Objectives of the study were: detection of subclinical cardiac damage and identification of groups of patients at major risk, who may benefit from cardiological pre- or/and on-treatment assessment. Results: We present data on the first 47 pts enrolled, diagnosed with a wide range of solid tumors, including 16 renal carcinoma, 11 melanoma and 3 NSCLC; 15 (32%), 16 (34%) and 16 (34%) pts were assigned to the Mono, Combo and Cardio group, respectively. Most pts (42, 89%) were treated with ICI for locally advanced/metastatic disease (26 as first-line therapy, 16 from second-line on), while 5 (11%) as adjuvant therapy. All pts received an anti-PD-(L)1, either as single agent (25, 53%) or in combination, with ICI plus a TKI being the most frequent combinatorial strategy (16; 34%). Overall, the cMRI analysis showed a statistically significant left ventricle ejection fraction (LVEF) reduction pre- versus post-ICI treatment (p < 0.001), with 18 (38%) pts experiencing a loss of > 3 points of LVEF. No statistically significant differences in LVEF reduction were observed considering the three different groups (p = 0.6), tumor types (p = 0.2), or occurrence of any grade non-cardiological irAEs (p = 0.6). Conclusions: Our study was able to show a statistically significant reduction in LVEF, with more than 3% LVEF loss in a clinically significant proportion of ICI-treated patients (18; 38%), not selected for suspected cardiac symptoms, warranting prospective evaluation to eventually identify pts at higher risk. The trial is continuing prospective enrollment and immunophenotyping analyses are ongoing.

A phase II, multicenter, open-label study of polyPEPI1018 in combination with atezolizumab in participants with relapsed or refractory microsatellite-stable metastatic colorectal (MSS mCRC) cancer (Oberto-301).

3594 Background: The efficacy of checkpoint inhibitor immunotherapy in MSI-H mCRC has not been replicated in MSS mCRC. Therefore, additional interventions are needed to convert immunologically “cold” MSS CRC to “hot” tumors resembling MSI-H tumors. PolyPEPI1018 is an off-the-shelf, multi-peptide vaccine containing 12 immunogenic epitopes derived from 7 shared tumor antigens which demonstrated early evidence of clinical activity in first-line MSS mCRC. Methods: Patients with MSS mCRC who have progressed on 2-3 lines of prior chemotherapy regimen received PolyPEPI1018 (1.2 mg, sc) and atezolizumab (1,200 mg, iv) Q3W until disease progression or unacceptable toxicity. The primary endpoint was safety. A Simon 2-stage design was applied. Data on objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and correlation studies will be presented. Results: 18 patients (66 % female) were enrolled for stage 1 of the study. Median age was 54 years (range 38–79), 50% had liver metastases and 67% received at least 3 lines of prior therapies. PD-L1 expression was <1% for 85% of patients. The combination was well-tolerated; most common side effect related to treatment was Grade (Gr) 1-2 local skin reaction (n=22). Gr 2 events (n=2) at least possibly related to treatment were nausea, pyrexia and increased blood alkaline phosphatase. There were no Gr 3-5 events or study discontinuation due to treatment AE. The ORR was 0% and the DCR was 61%. The mPFS was 2.7 months (95%CI 1.4-4.0) and the mOS was not reached (95%CI 8.75 – NE months) at the data cut-off date. Ex-vivo FluoroSpot identified 13/16 subjects with robust, vaccine-specific CD8+ and/or CD4+ T cell responses detected against multiple vaccine antigens. For patients with available biopsy pairs (n=8), both the average PD-L1 expression (IC%, p=0.029) and the density of CD8+ tumor-infiltrating lymphocytes (TILs, p=0.019) were significantly increased, post-treatment. Patients with increased PFS (> 12 weeks) had both higher levels of post-treatment PD-L1 (p=0.007) and TILs (p=0.016) than patients with PFS ≤ 12 weeks. Conclusions: PolyPEPI1018 in combination with atezolizumab was well-tolerated with no Grade 3 AEs observed. Despite no objective tumor responses could be detected, correlative data suggest contribution of PolyPEPI1018-induced immune responses to the modulation of tumor microenvironment and to improved disease control. The study did not proceed to stage 2; it is on-going for the collection of survival data. Clinical trial information: NCT05243862 .

Unleashing deep features and radiomics to enhance best overall response prediction to immunotherapy in advanced non-small cell lung cancer.

e20611 Background: Predicting immunotherapy response in advanced non-small cell lung cancer (NSCLC) through non-invasive means could be a groundbreaking advancement. Deep features extracted from medical images by deep Convolutional Neural Networks (CNNs) along with radiomics have demonstrated promising results in different oncologic diseases. However, the method for extracting these deep features influences the predictive capabilities of the model. Methods: A retrospective analysis of a multicenter study was conducted in advanced NSCLC patients with high PD-L1 expression with the aim of developing an imaging features-based model for the prediction of best overall response (BOR) to a checkpoint inhibitor immunotherapy. All visible lung lesions, beyond RECIST 1.1, were manually segmented in baseline CT scans. Radiomics features were extracted at lesion-level, and various preprocessing methods and CNN architectures were tested for deep features extraction. Radiomics and deep features were harmonized using ComBat methodology. A distinctive feature signature was created for each patient by calculating the mean across all lesions. Using this data, machine learning models were trained to predict treatment response, specifically distinguishing between complete response (CR) and partial response (PR) from stable disease (SD) and progressive disease (PD). The study compared the performance of different deep features extraction methods and assessed shapley additive explanations (SHAP) values of radiomics for interpretability. Results: In the cohort of 116 patients (mean age: 67, 93% ever-smokers, 73% male), 1024 to 5475 quantitative imaging features per lesion were extracted. Among these patients, 67 patients were CR+PR, and 49 were SD+PD. The top-performing predictive model, trained with radiomics and deep features from a deep convolutional autoencoder, achieved an average AUC of 85%. SHAP values showed that impactful radiomics features were correlated with intensity changes in adjacent pixels describing the tumor heterogeneity, along with shape features potentially associated with malignancy. Ultimately, combining both features demonstrated statistical significance, leading to a performance improvement of ~2-5% compared to models exclusively using deep features. Conclusions: Diverse techniques for extracting deep features were evaluated, revealing autoencoder training as the most effective strategy for predicting immunotherapy response. Consequently, the findings suggest that employing deep learning to extract imaging features from baseline CT scans, combined with radiomics, represents a promising non-invasive approach for the predicting immunotherapy outcomes in advanced NSCLC patients.

Factors Associated with Adoption of Immune Checkpoint Inhibitor Treatment for Advanced Melanoma: A SEER-Medicare Cohort Study

We aimed to explore differences in immune checkpoint inhibitor (ICI) immunotherapy utilization for advanced melanoma by examining patient and neighborhood characteristics.We performed a retrospective cohort study using a de-identified, random sample of SEER-Medicare beneficiaries aged ≥65 years with stage III or stage IV melanoma (2011-2017). Our primary outcome was initiation of ICI immunotherapy (ipilimumab, pembrolizumab, nivolumab, or atezolizumab) following stage III or stage IV melanoma diagnosis. We analyzed ICI usage with multivariable logistic regression. After analyzing the entire 2011-2017 cohort, we conducted a secondary analysis in which we separately analyzed the 2011-2014 and 2015-2017 cohorts to assess possible differences over time.We included 3,531 beneficiaries with mean follow-up 2.1 (SD 2.0) years. Higher likelihood of ICI usage was associated with male sex (OR 1.21, 95% CI 1.04-1.42) and higher density of medical oncologists (OR 1.02, 95% CI 1.01-1.04). Lower likelihood of ICI usage was associated with older age group and Charlson comorbidity score (score ≥2 OR 0.72, 95% CI 0.60-0.86). These associations were diminished in more recent years (no association with sex, medical oncologist density, Charlson comorbidity score, and association with only the oldest age group in years 2015-2017).We found significant sex and age-related differences in initiation among SEER-Medicare beneficiaries with stage III or stage IV melanoma, which appear to be improving over time.