Viral Vectors Expressing Interleukin 2 for Cancer Immunotherapy

Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups

Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Overcoming effector T cell exhaustion in ovarian cancer ascites with a novel adenovirus encoding for a MUC1 bispecific antibody engager and IL-2 cytokine

T cell-focused cancer immunotherapy including checkpoint inhibitors and cell therapies has been rapidly evolving over the past decade. Nevertheless, there remains a major unmet medical need in oncology generally and immuno-oncology specifically. We have constructed an oncolytic adenovirus, Ad5/3-E2F-d24-aMUC1aCD3-IL-2 (TILT-322), which is armed with a human aMUC1aCD3 T cell engager and IL-2. TILT-322 treatment stimulated T cell cytotoxicity through the increased presence of granzyme B, perforin, and interferon-gamma. Additional immune profiling indicated TILT-322 increased gamma delta T cell activation and impacted other cell types such as natural killer cells and natural killer-like T cells that are traditionally involved in cancer immunotherapy. TILT-322 treatment also decreased the proportion of exhausted CD8+ T cells as demarked by immune checkpoint expression in ovarian ascites samples. Overall, our data showed that TILT-322 treatment led to an enhanced T cell activation and reversed T cell exhaustion translating into high antitumor efficacy when given locally or intravenously. The analysis of blood and tumors isolated from an in vivo patient-derived ovarian cancer xenograft model suggested TILT-322 mediated tumor control through improved T cell functions. Therefore, TILT-322 is a promising novel anti-tumor agent for clinical translation.

Oncolytic herpes simplex virus expressing IL-2 controls glioblastoma growth and improves survival

BACKGROUND

Glioblastoma (GBM), a highly immunosuppressive and often fatal primary brain tumor, lacks effective treatment options. GBMs contain a subpopulation of GBM stem-like cells (GSCs) that play a central role in tumor initiation, progression, and treatment resistance. Oncolytic viruses, especially oncolytic herpes simplex virus (oHSV), replicate selectively in cancer cells and trigger antitumor immunity-a phenomenon termed the "in situ vaccine" effect. Although talimogene laherparepvec (T-VEC), an oHSV armed with granulocyte macrophage-colony stimulating factor (GM-CSF), is Food and Drug Administration (FDA)-approved for melanoma, its use in patients with GBM has not been reported. Interleukin 2 (IL-2) is another established immunotherapy that stimulates T cell growth and orchestrates antitumor responses. IL-2 is FDA-approved for melanoma and renal cell carcinoma but has not been widely evaluated in GBM, and IL-2 treatment is limited by its short half-life, minimal tumor accumulation, and significant systemic toxicity. We hypothesize that local intratumoral expression of IL-2 by an oHSV would avoid the systemic IL-2-related therapeutic drawbacks while simultaneously producing beneficial antitumor immunity.

METHODS

We developed G47Δ-mIL2 (an oHSV expressing IL-2) using the flip-flop HSV BAC system to deliver IL-2 locally within the tumor microenvironment (TME). We then tested its efficacy in orthotopic mouse GBM models (005 GSC, CT-2A, and GL261) and evaluated immune profiles in the treated tumors and spleens by flow cytometry and immunohistochemistry.

RESULTS

G47Δ-mIL2 significantly prolonged median survival without any observable systemic IL-2-related toxicity in the 005 and CT-2A models but not in the GL261 model due to the non-permissive nature of GL261 cells to HSV infection. The therapeutic activity of G47Δ-mIL2 in the 005 GBM model was associated with increased intratumoral infiltration of CD8+ T cells, critically dependent on the release of IL-2 within the TME, and CD4+ T cells as their depletion completely abrogated therapeutic efficacy. The use of anti-PD-1 immune checkpoint blockade did not improve the therapeutic outcome of G47Δ-mIL2.

CONCLUSIONS

Our findings illustrate that G47Δ-mIL2 is efficacious, stimulates antitumor immunity against orthotopic GBM, and may also target GSC. OHSV expressing IL-2 may represent an agent that merits further exploration in patients with GBM.

Efficacy and Safety Assessment of Intrathoracic Perfusion Chemotherapy Combined with immunological factor Interleukin-2 in the Treatment of Advanced Non-Small Cell Lung Cancer: A Retrospective Cohort Study

Objective: This study evaluated the efficacy and safety of the gemcitabine and oxaliplatin intrathoracic perfusion chemotherapy (IPCGOR) regimen combined with interleukin-2 (IL-2) for advanced non-small cell lung cancer (NSCLC). Methods: We conducted a retrospective analysis of 460 advanced NSCLC patients from the Yunnan Province Early Cancer Diagnosis and Treatment Project (June 2020-October 2022), assessing the IPCGOR and IL-2 combination. Outcomes were measured based on RECIST 1.1 criteria, focusing on objective response rate (ORR), disease control rate (DCR), median progression-free survival (mPFS), median overall survival (MOS), and treatment safety. Results: The treatment demonstrated an ORR of 67.4%, a DCR of 97.4%, an mPFS of 8.5 months, and an MOS of 12.5 months. 14 patients underwent successful surgery post-treatment. Common adverse reactions were manageable, with no treatment-related deaths reported. Conclusion: The IPCGOR combined with IL-2 regimen shows promising efficacy and a tolerable safety profile for advanced NSCLC. These findings suggest its potential as a reference for treating advanced NSCLC. However, the study's retrospective nature and single-center design pose limitations. Future research should focus on prospective studies, randomized controlled trials, and long-term outcome assessments, particularly in diverse patient subgroups, to further validate and refine the clinical application of this regimen.

Peripheral blood inflammatory indexes in breast cancer: A review

Immune and inflammatory responses play an important role in tumorigenesis and metastasis. Inflammation is an important component of the tumor microenvironment, and the changes in inflammatory cells may affect the occurrence and development of tumors. Complete blood count at the time of diagnosis and treatment can reflect the inflammatory status within the tumor. Studies have shown that the number of certain inflammatory cells in peripheral blood and their ratios are important prognostic factors for many malignancies, including neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index and pan-immune-inflammation-value. The value of peripheral blood inflammation indexes in predicting the efficacy and prognosis of breast cancer neoadjuvant therapy is worth recognizing. This review details the application of peripheral blood inflammation indexes in the evaluation of efficacy and prediction of prognosis in neoadjuvant therapy for breast cancer, aiming to provide a more comprehensive reference for the comprehensive diagnosis and treatment of breast cancer.

Mathematical and Machine Learning Models of Renal Cell Carcinoma: A Review

This review explores the multifaceted landscape of renal cell carcinoma (RCC) by delving into both mechanistic and machine learning models. While machine learning models leverage patients' gene expression and clinical data through a variety of techniques to predict patients' outcomes, mechanistic models focus on investigating cells' and molecules' interactions within RCC tumors. These interactions are notably centered around immune cells, cytokines, tumor cells, and the development of lung metastases. The insights gained from both machine learning and mechanistic models encompass critical aspects such as signature gene identification, sensitive interactions in the tumors' microenvironments, metastasis development in other organs, and the assessment of survival probabilities. By reviewing the models of RCC, this study aims to shed light on opportunities for the integration of machine learning and mechanistic modeling approaches for treatment optimization and the identification of specific targets, all of which are essential for enhancing patient outcomes.