Dissecting the Tumor-Immune Landscape in Chimeric Antigen Receptor T-cell Therapy: Key Challenges and Opportunities for a Systems Immunology Approach

Intelligent solution predictive networks for non-linear tumor-immune delayed model

In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required for molecule formation, cell growth, segregation, and transportation, among other factors by exploiting the knacks of soft computing paradigm utilizing neural networks with back propagation Levenberg Marquardt approach (NNLMA). The governing differential delayed system of non-linear TID, which comprised the densities of the tumor population, cytotoxic T lymphocytes and T helper cells, is represented by non-linear delay ordinary differential equations with three classes. The baseline data is formulated by exploiting the explicit Runge-Kutta method (RKM) by diverting the transmutation rate of Tc to Th of the Tc population, transmutation rate of Tc to Th of the Th population, eradication of tumor cells through Tc cells, eradication of tumor cells through Th cells, Tc cells' natural mortality rate, Th cells' natural mortality rate as well as time delay. The approximated solution of the non-linear TID model is determined by randomly subdividing the formulated data samples for training, testing, as well as validation sets in the network formulation and learning procedures. The strength, reliability, and efficacy of the designed NNLMA for solving non-linear TID model are endorsed by small/negligible absolute errors, error histogram studies, mean squared errors based convergence and close to optimal modeling index for regression measurements.

Combination of chidamide and PD-1 blockade in Refractory/Relapsed aggressive large B-cell lymphomas with high risk of failing CAR-T therapy

BACKGROUND

Refractoriness and relapse after chimeric antigen receptor T-cell therapy have emerged as major challenges for immunotherapy of aggressive large B-cell lymphoma. Thus far, there is no consensus on how to address treatment failure and whether to administer maintenance therapy following CAR-T cell therapy.

METHODS

From August 2017 through November 2022, 52 patients with refractory/relapsed aggressive LBCL who had a high risk of resistance to CAR-T cell therapy were given chidamide in combination with a PD-1 inhibitor as maintenance therapy following either CAR19/22 T-cell cocktail therapy or CAR19/22 T-cell cocktail therapy plus autologous stem cell transplantation (ASCT). Another 52 aggressive LBCL patients who had comparable baseline characteristics and received similar therapeutic regimens but did not receive any interventions following CAR-T cell therapy or CAR-T cell therapy plus ASCT were regarded as the control group to evaluate the efficacy and safety of the combination of chidamide and a PD-1 inhibitor.

RESULTS

Among the 52 patients who received chidamide and a PD-1 inhibitor as maintenance therapy, with a median follow-up of 26.5 months (range: 1.1-53.8), neither the median progression-free survival (PFS) nor overall survival (OS) was reached, and the expected 2-year OS and PFS rates were 89 % and 77 %, respectively, which were superior to those of the control group (p < 0.001). Long-term chidamide administration and a specific genetic subtype of EZB were strongly associated with a better response after chidamide plus PD-1 blockade therapy. Additionally, long-term chidamide administration was significantly associated with prolonged persistence and reactivation of CD19-directed CAR-T cells in the peripheral blood. Adverse effects (AEs) were moderate and reversible, and no treatment-related deaths occurred.

CONCLUSION

Our results indicate that the combination of chidamide and PD-1 blockade as maintenance therapy could improve the outcomes of aggressive LBCL patients at high risk of failing CAR-T cell therapy.

Implications of High Tumor Burden on Chimeric Antigen Receptor T-Cell Immunotherapy: A Review

Importance

Chimeric antigen receptor (CAR) T-cell therapy has redefined the therapeutic landscape of several hematologic malignant tumors. Despite its clinical efficacy, many patients with cancer experience nonresponse to CAR T-cell treatment, disease relapse within months, or severe adverse events. Furthermore, CAR T-cell therapy has demonstrated minimal to no clinical efficacy in the treatment of solid tumors in clinical trials.

Observations

A complex interplay between high tumor burden and the systemic and local tumor microenvironment on clinical outcomes of CAR T-cell therapy is emerging from preclinical and clinical data. The hallmarks of advanced cancers-namely, inflammation and immune dysregulation-sustain cancer progression. They negatively affect the production, expansion, antitumor activity, and persistence of CAR T-cell products. Understanding of CAR T-cell therapy, mechanisms underlying its failure, and adverse events under conditions of high tumor burden is critical for realizing the full potential of this novel treatment approach.

Conclusions and Relevance

This review focuses on linking the efficacy and safety of CAR T-cell therapy with tumor burden. Its limitations relative to high tumor burden, systemic inflammation, and immune dysregulation are discussed. Emerging clinical approaches to overcome these obstacles and more effectively incorporate this therapeutic strategy into the treatment paradigm of patients with solid malignant tumors are also described.

Prediction of severe CRS and determination of biomarkers in B cell-acute lymphoblastic leukemia treated with CAR-T cells

Introduction

CAR-T cell therapy is a novel approach in the treatment of hematological tumors. However, it is associated with life-threatening side effects, such as the severe cytokine release syndrome (sCRS). Therefore, predicting the occurrence and development of sCRS is of great significance for clinical CAR-T therapy. The study of existing clinical data by artificial intelligence may bring useful information.

Methods

By analyzing the heat map of clinical factors and comparing them between severe and non-severe CRS, we can identify significant differences among these factors and understand their interrelationships. Ultimately, a decision tree approach was employed to predict the timing of severe CRS in both children and adults, considering variables such as the same day, the day before, and initial values.

Results

We measured cytokines and clinical biomarkers in 202 patients who received CAR-T therapy. Peak levels of 25 clinical factors, including IFN-γ, IL6, IL10, ferritin, and D-dimer, were highly associated with severe CRS after CAR T cell infusion. Using the decision tree model, we were able to accurately predict which patients would develop severe CRS consisting of three clinical factors, classified as same-day, day-ahead, and initial value prediction. Changes in serum biomarkers, including C-reactive protein and ferritin, were associated with CRS, but did not alone predict the development of severe CRS.

Conclusion

Our research will provide significant information for the timely prevention and treatment of sCRS, during CAR-T immunotherapy for tumors, which is essential to reduce the mortality rate of patients.

A systems and computational biology perspective on advancing CAR therapy

In the recent decades, chimeric antigen receptor (CAR) therapy signaled a new revolutionary approach to cancer treatment. This method seeks to engineer immune cells expressing an artificially designed receptor, which would endue those cells with the ability to recognize and eliminate tumor cells. While some CAR therapies received FDA approval and others are subject to clinical trials, many aspects of their workings remain elusive. Techniques of systems and computational biology have been frequently employed to explain the operating principles of CAR therapy and suggest further design improvements. In this review, we sought to provide a comprehensive account of those efforts. Specifically, we discuss various computational models of CAR therapy ranging in scale from organismal to molecular. Then, we describe the molecular and functional properties of costimulatory domains frequently incorporated in CAR structure. Finally, we describe the signaling cascades by which those costimulatory domains elicit cellular response against the target. We hope that this comprehensive summary of computational and experimental studies will further motivate the use of systems approaches in advancing CAR therapy.

Predictive short/long-term efficacy biomarkers and resistance mechanisms of CD19-directed CAR-T immunotherapy in relapsed/refractory B-cell lymphomas

Genetically modified T-cell immunotherapies are revolutionizing the therapeutic options for hematological malignancies, especially those of B-cell origin. Impressive efficacies of CD19-directed chimeric antigen receptor (CAR)-T therapy have been reported in refractory/relapsed (R/R) B-cell non-Hodgkin lymphoma (NHL) patients who were resistant to current standard therapies, with a complete remission (CR) rate of approximately 50%. At the same time, problems of resistance and relapse following CAR-T therapy have drawn growing attention. Recently, great efforts have been made to determine various factors that are connected to the responses and outcomes following CAR-T therapy, which may not only allow us to recognize those with a higher likelihood of responding and who could benefit most from the therapy but also identify those with a high risk of resistance and relapse and to whom further appropriate treatment should be administered following CAR-T therapy. Thus, we concentrate on the biomarkers that can predict responses and outcomes after CD19-directed CAR-T immunotherapy. Furthermore, the mechanisms that may lead to treatment failure are also discussed in this review.

Late relapse after CAR-T cell therapy for adult patients with hematologic malignancies: a definite evidence from Systematic Review and Meta-Analysis on individual data

Chimeric Antigen Receptor (CAR)-modified T lymphocytes represent one of the most innovative and promising approaches to treating hematologic malignancies. CAR-T cell therapy is currently being used for the treatment of relapsed/refractory (r/r) B-cell malignancies including Acute Lymphoblastic Leukemia, Large B-Cell Lymphoma, Follicular Lymphoma, Multiple Myeloma and Mantle Cell Lymphoma. Despite the unprecedented clinical success, one of the major issues of the approved CAR-T cell therapy - tisagenlecleucel, axicabtagene, lisocabtagene, idecabtagene, ciltacabtagene and brexucabtagene - is the uncertainty about its persistence which in turn could lead to weak or no response to therapy with malignancy recurrence. Here we show that the prognosis of patients who do not respond to CAR-T cell therapy is still an unmet medical need. We performed a systematic review and meta-analysis collecting individual data on Duration of Response from at least 12-month follow-up studies. We found that the pooled prevalence of relapse within the first 12 months after CAR-T infusion was 61% (95% CI, 43%-78%); moreover, one year after the infusion, the analysis highlighted a pooled prevalence of relapse of 24% (95% CI, 11%-42%). Our results suggest that identifying potential predictive biomarkers of response to CAR-T therapy, especially for patients affected by the advanced stage of blood malignancies, could lead to stratification of the eligible population to that therapy, recognizing which patients will benefit and which will not, helping regulators to make decision in that way.

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

BACKGROUND

The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding even the most complex heterogeneity in tumor tissue and mapping the spatial cartography of the tumor immunity allows the best and optimized selection of immune modulating agents to (re-)activate the patient's immune system and direct it against the individual cancer in the most effective way.

RECENT FINDINGS

Primary cancer and metastases maintain a high degree of plasticity to escape any immune surveillance and continue to evolve depending on many intrinsic and extrinsic factors In the field of immune-oncology (IO) immune modulating agents are recognized as practice changing therapeutic modalities. Recent studies have shown that an optimal and lasting efficacy of IO therapeutics depends on the understanding of the spatial communication network and functional context of immune and cancer cells within the tumor microenvironment. Artificial intelligence (AI) provides an insight into the immune-cancer-network through the visualization of very complex tumor and immune interactions in cancer tissue specimens and allows the computer-assisted development and clinical validation of such digital biomarker.

CONCLUSIONS

The successful implementation of AI-supported digital biomarker solutions guides the clinical selection of effective immune therapeutics based on the retrieval and visualization of spatial and contextual information from cancer tissue images and standardized data. As such, computational pathology (CP) turns into "precision pathology" delivering individual therapy response prediction. Precision Pathology does not only include digital and computational solutions but also high levels of standardized processes in the routine histopathology workflow and the use of mathematical tools to support clinical and diagnostic decisions as the basic principle of a "precision oncology".

Identification of genomic signatures in bone marrow associated with clinical response of CD19 CAR T-cell therapy

CD19 CAR T-cell immunotherapy is a breakthrough treatment for B cell malignancies, but relapse and lack of response remain a challenge. The bone marrow microenvironment is a key factor in therapy resistance, however, little research has been reported concerning the relationship between transcriptomic profile of bone marrow prior to lymphodepleting preconditioning and clinical response following CD19 CAR T-cell therapy. Here, we applied comprehensive bioinformatic methods (PCA, GO, GSEA, GSVA, PAM-tools) to identify clinical CD19 CAR T-cell remission-related genomic signatures. In patients achieving a complete response (CR) transcriptomic profiles of bone marrow prior to lymphodepletion showed genes mainly involved in T cell activation. The bone marrow of CR patients also showed a higher activity in early T cell function, chemokine, and interleukin signaling pathways. However, non-responding patients showed higher activity in cell cycle checkpoint pathways. In addition, a 14-gene signature was identified as a remission-marker. Our study indicated the indexes of the bone marrow microenvironment have a close relationship with clinical remission. Enhancing T cell activation pathways (chemokine, interleukin, etc.) in the bone marrow before CAR T-cell infusion may create a pro-inflammatory environment which improves the efficacy of CAR T-cell therapy.

Enhancing Cancer Immunotherapeutic Efficacy with Sonotheranostic Strategies

Immunotherapy has revolutionized the modality for establishing a firm immune response and immunological memory. However, intrinsic limitations of conventional low responsive poor T cell infiltration and immune related adverse effects urge the coupling of cancer nanomedicines with immunotherapy for boosting antitumor response under ultrasound (US) sensitization to mimic dose-limiting toxicities for safe and effective therapy against advanced cancer. US is composed of high-frequency sound waves that mediate targeted spatiotemporal control over release and internalization of the drug. The unconventional US triggered immunogenic nanoengineered arena assists the limited immunogenic dose, limiting toxicities and efficacies. In this Review, we discuss current prospects of enhanced immunotherapy using nanomedicine under US. We highlight how nanotechnology designs and incorporates nanomedicines for the reprogramming of systematic immunity in the tumor microenvironment. We also emphasize the mechanical and biological potential of US, encompassing sonosensitizer activation for enhanced immunotherapeutic efficacies. Finally, the smartly converging combinational platform of US stimulated cancer nanomedicines for amending immunotherapy is summarized. This Review will widen scientists' ability to explore and understand the limiting factors for combating cancer in a precisely customized way.

Biomarkers for Chimeric Antigen Receptor T Cell Therapy in Acute Lymphoblastic Leukemia: Prospects for Personalized Management and Prognostic Prediction

Chimeric antigen receptor (CAR) T cell therapy represents a breakthrough in immunotherapy with the potential of ushering in a new era in cancer treatment. Remarkable therapeutic response and complete remission of this innovative management have been observed in patients with relapse/refractory acute lymphoblastic leukemia. With CAR-T cell therapy becoming widely used both in multicenter clinical trials and as a commercial treatment, therapeutic efficacy monitoring and management of toxicities will be indispensable for ensuring safety and improving overall survival. Biomarkers can act not only as effective indicators reflecting patients' baseline characteristics, CAR-T cell potency, and the immune microenvironment, but can also assess side effects during treatment. In this review, we will elaborate on a series of biomarkers associated with therapeutic response as well as treatment-related toxicities, and present their current condition and latent value with respect to the clinical utility. The combination of biomarker research and CAR-T cell therapy will contribute to establishing a safer and more powerful monitoring system and prolonging the event-free survival of patients.

Chimeric antigen receptor T-cell immunotherapy in breast cancer: development and challenges

Chimeric antigen receptor (CAR) T-cell therapy is an innovative form of immunotherapy wherein autologous T-cells are genetically modified to express chimeric receptors encoding an antigen-specific single-chain variable fragment and costimulatory molecules. Moreover, CAR T-cell therapy can only work successfully in patients who have an intact immune system. Therefore, patients receiving cytotoxic chemotherapy will be immunosuppressed making CAR-T therapy less effective. In adoptive CD8+ T-cell therapy (ACT), numerous tumor-specific, engineered T-cells are sourced from patients, expanded in vitro, and infused back expressing tumor-specific antigen receptors. The most successful ACT, anti-CD19 chimeric antigen receptor T-cell therapy directed against B-cell lymphoma, has proved to be efficacious. However, current efforts to utilize this approach for solid tumors, like breast cancer, have shown only modest improvement. Nevertheless, the potential efficacy of CAR-T therapy is promising in an era of immunological advances. By appropriately manipulating CAR T-cells to combat the immunosuppressive forces of the tumor microenvironment, significant eradication of the solid tumor may occur. This review discusses CAR T-cell therapy and its specificity and safety in adoptive cell transfers in breast cancer. We will highlight novel discoveries in CAR T-cell immunotherapy and the formidable barriers including suppression of T-cell function and localization at tumor sites.

Chimeric antigen receptor T-cell lymphoma immunotherapy: the next questions

PURPOSE OF REVIEW

Chimeric antigen receptor (CAR) T-cell therapy is an innovative form of adoptive cellular immunotherapy targeting CD19 in its most advanced form. Up to 30% of infused patients achieve long-term survival, meaning that 70% of patients still fail to respond or relapse after therapy. This review will address the unresolved issues relating to responders' characterization, relapse prediction, and prevention, CAR T-cell construct optimization, rational combination with other therapies and treatment toxicity, focusing on the management of relapsed/refractory lymphoma patients.

RECENT FINDINGS

Many new antigenic targets are currently investigated and raise the hope of broader successes. However, literature data report that treatment failure is not only related to CAR T construct and infusion but is also due to hostile tumor microenvironment and poor interaction with the host effector cells. Further research should not only target CAR T structure, toxicity and associated therapies, but also tumor-related and host-related microenvironment interactions that lead to treatment failure in relapsed/refractory lymphoma patients.

SUMMARY

Poor persistence of CAR T and loss of CD19 antigen are well established mechanisms of relapse in Acute Lymphoblastic Leukemia (ALL). A fourth generation of CAR T construct is currently investigated to overcome this issue. In non-Hodgkin lymphoma, mechanisms of treatment failure remain poorly understood but tumor and host microenvironment are undoubtedly involved and should be further investigated. A deeper understanding of CAR T-cell therapy failure in individuals will help personalize CAR T-cell therapy in the future.

Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma

The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cancer Genome Atlas (TCGA) program, we scored stromal and immune cells for tumor purity prediction by CIBERSORT and ESTMATE. Differential expression analysis was employed to identify 374 genes between the high-score group and the low-score group, which were utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Protein-protein interaction (PPI) and Cox regression analysis were performed on the differentially expressed genes (DEGs) to identify four key tumor microenvironment (TME) -related genes (CCR2, CCR4, P2RY12, and P2RY13). The expression levels of the four DEGs differed significantly among LUAD patients of different ages, genders, and TNM stages. We found that the infiltration of resting memory CD4+ T cells, memory B cells, and M0 macrophages into the TME was co-regulated by these four DEGs. These four genes were closely related to the prognosis of LUAD and affected the infiltration of immune cells into the TME, which had predictive prognostic value in LUAD.