Preclinical Evaluation of 89Zr-Df-IAB22M2C PET as an Imaging Biomarker for the Development of the GUCY2C-CD3 Bispecific PF-07062119 as a T Cell Engaging Therapy

Guanylate cyclase-C Signaling Axis as a theragnostic target in colorectal cancer: a systematic review of literature

Introduction

Colorectal cancer (CRC) is a devastating disease that affects millions of people worldwide. Recent research has highlighted the crucial role of the guanylate cyclase-C (GC-C) signaling axis in CRC, from the early stages of tumorigenesis to disease progression. GC-C is activated by endogenous peptides guanylin (GU) and uroguanylin (UG), which are critical in maintaining intestinal fluid homeostasis. However, it has been found that these peptides may also contribute to the development of CRC. This systematic review focuses on the latest research on the GC-C signaling axis in CRC.

Methods

According to the aim of the study, a systematic literature search was conducted on Medline and PubMed databases. Ultimately, a total of 40 articles were gathered for the systematic review.

Results

Our systematic literature search revealed that alterations in GC-C signaling compartments in CRC tissue have demonstrated potential as diagnostic, prognostic, and therapeutic markers. This research highlights a potential treatment for CRC by targeting the GC-C signaling axis. Promising results from recent studies have explored the use of this signaling axis to develop new vaccines and chimeric antigen receptors that may be used in future clinical trials.

Conclusion

The findings presented in this review provide compelling evidence that targeting the GC-C signaling axis may be an advantageous approach for treating CRC.

Using Machine Learning Methods to Study Colorectal Cancer Tumor Micro-Environment and Its Biomarkers

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide, and the identification of biomarkers can improve early detection and personalized treatment. In this study, RNA-seq data and gene chip data from TCGA and GEO were used to explore potential biomarkers for CRC. The SMOTE method was used to address class imbalance, and four feature selection algorithms (MCFS, Borota, mRMR, and LightGBM) were used to select genes from the gene expression matrix. Four machine learning algorithms (SVM, XGBoost, RF, and kNN) were then employed to obtain the optimal number of genes for model construction. Through interpretable machine learning (IML), co-predictive networks were generated to identify rules and uncover underlying relationships among the selected genes. Survival analysis revealed that INHBA, FNBP1, PDE9A, HIST1H2BG, and CADM3 were significantly correlated with prognosis in CRC patients. In addition, the CIBERSORT algorithm was used to investigate the proportion of immune cells in CRC tissues, and gene mutation rates for the five selected biomarkers were explored. The biomarkers identified in this study have significant implications for the development of personalized therapies and could ultimately lead to improved clinical outcomes for CRC patients.

Fibroblast Activation Protein-Targeting Minibody-IRDye700DX for Ablation of the Cancer-Associated Fibroblast with Photodynamic Therapy

Fibroblast activation protein (FAP), expressed on cancer-associated fibroblasts, is a target for diagnosis and therapy in multiple tumour types. Strategies to systemically deplete FAP-expressing cells show efficacy; however, these induce toxicities, as FAP-expressing cells are found in normal tissues. FAP-targeted photodynamic therapy offers a solution, as it acts only locally and upon activation. Here, a FAP-binding minibody was conjugated to the chelator diethylenetriaminepentaacetic acid (DTPA) and the photosensitizer IRDye700DX (DTPA-700DX-MB). DTPA-700DX-MB showed efficient binding to FAP-overexpressing 3T3 murine fibroblasts (3T3-FAP) and induced the protein's dose-dependent cytotoxicity upon light exposure. Biodistribution of DTPA-700DX-MB in mice carrying either subcutaneous or orthotopic tumours of murine pancreatic ductal adenocarcinoma cells (PDAC299) showed maximal tumour uptake of ¹¹¹In-labelled DTPA-700DX-MB at 24 h post injection. Co-injection with an excess DTPA-700DX-MB reduced uptake, and autoradiography correlated with FAP expression in the stromal tumour region. Finally, in vivo therapeutic efficacy was determined in two simultaneous subcutaneous PDAC299 tumours; only one was treated with 690 nm light. Upregulation of an apoptosis marker was only observed in the treated tumours. In conclusion, DTPA-700DX-MB binds to FAP-expressing cells and targets PDAC299 tumours in mice with good signal-to-background ratios. Furthermore, the induced apoptosis indicates the feasibility of targeted depletion of FAP-expressing cells with photodynamic therapy.

Recent Trends in Diagnostic Biomarkers of Tumor Microenvironment

The tumor microenvironment (TME) play critical roles in tumor survival, progression, and metastasis and can be considered potential targets for molecular imaging of cancer. The targeting agents for imaging of TME components (e.g., fibroblasts, mesenchymal stromal cells, immune cells, extracellular matrix, blood vessels) provide a promising strategy to target these biomarkers for the early diagnosis of cancers. Moreover, various cancer types have similar tumor immune microenvironment (TIME) features that targeting those biomarkers and offer clinically translatable molecular imaging of cancers. In this review, we categorize and summarize the components in TME which have been targeted for molecular imaging. Moreover, this review updated the recent progress in targeted imaging of TIME biological molecules by various modalities for the early detection of cancer.

Novel PET Imaging of Inflammatory Targets and Cells for the Diagnosis and Monitoring of Giant Cell Arteritis and Polymyalgia Rheumatica

Giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) are two interrelated inflammatory diseases affecting patients above 50 years of age. Patients with GCA suffer from granulomatous inflammation of medium- to large-sized arteries. This inflammation can lead to severe ischemic complications (e.g., irreversible vision loss and stroke) and aneurysm-related complications (such as aortic dissection). On the other hand, patients suffering from PMR present with proximal stiffness and pain due to inflammation of the shoulder and pelvic girdles. PMR is observed in 40-60% of patients with GCA, while up to 21% of patients suffering from PMR are also affected by GCA. Due to the risk of ischemic complications, GCA has to be promptly treated upon clinical suspicion. The treatment of both GCA and PMR still heavily relies on glucocorticoids (GCs), although novel targeted therapies are emerging. Imaging has a central position in the diagnosis of GCA and PMR. While [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) has proven to be a valuable tool for diagnosis of GCA and PMR, it possesses major drawbacks such as unspecific uptake in cells with high glucose metabolism, high background activity in several non-target organs and a decrease of diagnostic accuracy already after a short course of GC treatment. In recent years, our understanding of the immunopathogenesis of GCA and, to some extent, PMR has advanced. In this review, we summarize the current knowledge on the cellular heterogeneity in the immunopathology of GCA/PMR and discuss how recent advances in specific tissue infiltrating leukocyte and stromal cell profiles may be exploited as a source of novel targets for imaging. Finally, we discuss prospective novel PET radiotracers that may be useful for the diagnosis and treatment monitoring in GCA and PMR.