Current studies and future promises of PD-1 signal inhibitors in cervical cancer therapy

Immune cell infiltration and prognostic index in cervical cancer: insights from metabolism-related differential genes

Background

Cervical cancer remains a significant gynecologic malignancy in both China and the United States, posing a substantial threat to women's lives and health due to its high morbidity and mortality rates. Altered energy metabolism and dysregulated mitochondrial function play crucial roles in the development, growth, metastasis, and recurrence of malignant tumors. In this study, we aimed to predict prognosis and assess efficacy of anti-tumor therapy in cervical cancer patients based on differential genes associated with mitochondrial metabolism.

Methods

Transcriptomic data and clinical profiles of cervical cancer patients were retrieved from the TCGA and GEO databases. Differential gene-related cellular pathways were identified through GO, KEGG, and GSEA analyses. Prognostic indices were constructed using LASSO regression analysis. Immune cell infiltration was assessed using CIBERSORT and ssGSEA, and the correlation between immune checkpoint inhibitor genes and differential genes was examined. Tumor mutation load (TMB) and its association with prognostic indices were analyzed using nucleotide variant data from the TCGA database. Patient response to immunotherapy and sensitivity to antitumor drugs were determined using the TIDE algorithm and the oncoPredic algorithm, respectively.

Results

A prognostic index based on metabolism-related differential genes was developed to predict the clinical outcome of cervical cancer patients, enabling their classification into two distinct subtypes. The prognostic index emerged as an independent risk factor for unfavorable prognosis. The high-index group exhibited a significantly worse overall prognosis, along with elevated tumor mutation burden (TMB), increased immune cell infiltration, and lower TIDE scores, indicating a potential benefit from immunotherapy. Conversely, the low-index group demonstrated increased sensitivity to metabolism-related antitumor agents, specifically multikinase inhibitors.

Conclusion

The aim of this study was to develop a prognostic index based on differential genes associated with mitochondrial metabolism, which could be used to predict cervical cancer patients' prognoses. When combined with TIDE and TMB analyses, this prognostic index offers insights into the immune cell infiltration landscape, as well as the potential efficacy of immunotherapy and targeted therapy. Our analysis suggests that the Iron-Sulfur Cluster Assembly Enzyme (ISCU) gene holds promise as a biomarker for cervical cancer immunotherapy.

Small molecule and PROTAC molecule experiments in vitro and in vivo, focusing on mouse PD-L1 and human PD-L1 differences as targets

In recent years, several monoclonal antibodies (mAbs) targeting PD-L1 have been licensed by the FDA for use in the treatment of cancer, demonstrating the effectiveness of blocking immune checkpoints, particularly the PD-1/PD-L1 pathway. Although mAb-based therapies have made great strides, they still have their limitations, and new small-molecule or PROTAC-molecule inhibitors that can block the PD-1/PD-L1 axis are desperately needed. Therefore, it is crucial to translate initial in vitro discoveries into appropriate in vivo animal models when creating PD-L1-blocking therapies. Due to their widespread availability and low experimental expenses, classical immunocompetent mice are appealing for research purposes. However, it is yet unclear whether the mouse (m) PD-L1 interaction with human (h) PD-1 in vivo would produce a functional immunological checkpoint. In this review, we summarize the in vitro and in vivo experimental studies of small molecules and PROTAC molecules, particularly the distinctions between mPD-L1 as a target and hPD-L1 as a target.

Mapping Cellular Interactions from Spatially Resolved Transcriptomics Data

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between γδ T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

PD-1 and PD-L1: architects of immune symphony and immunotherapy breakthroughs in cancer treatment

PD-1 (Programmed Cell Death Protein-1) and PD-L1 (Programmed Cell Death Ligand-1) play a crucial role in regulating the immune system and preventing autoimmunity. Cancer cells can manipulate this system, allowing them to escape immune detection and promote tumor growth. Therapies targeting the PD-1/PD-L1 pathway have transformed cancer treatment and have demonstrated significant effectiveness against various cancer types. This study delves into the structure and signaling dynamics of PD-1 and its ligands PD-L1/PD-L2, the diverse PD-1/PD-L1 inhibitors and their efficacy, and the resistance observed in some patients. Furthermore, this study explored the challenges associated with the PD-1/PD-L1 inhibitor treatment approach. Recent advancements in the combination of immunotherapy with chemotherapy, radiation, and surgical procedures to enhance patient outcomes have also been highlighted. Overall, this study offers an in-depth overview of the significance of PD-1/PD-L1 in cancer immunotherapy and its future implications in oncology.

Cancer cell-intrinsic PD-1: Its role in malignant progression and immunotherapy

Programmed cell death protein-1 (PD-1), also called CD279, is coded by the PDCD1 gene and is constitutively expressed on the surface of immune cells. As a receptor and immune checkpoint, PD-1 can bind to programmed death ligand-1/programmed death ligand-2 (PD-L1/PD-L2) in tumor cells, leading to tumor immune evasion. Anti-PD-1 and anti-PD-L1 are important components in tumor immune therapy. PD-1 is also expressed as an intrinsic variant (iPD-1) in cancer cells where it plays important roles in malignant progression as proposed by recent studies. However, iPD-1 has received much less attention compared to PD-1 expressed on immune cells although there is an unmet medical need for fully elucidating the mechanisms of actions to achieve the best response in tumor immunotherapy. iPD-1 suppresses tumorigenesis in non-small cell lung cancer (NSCLC) and colon cancer, whereas it promotes tumorigenesis in melanoma, hepatocellular carcinoma (HCC), pancreatic ductal adenocarcinoma (PDAC), thyroid cancer (TC), glioblastoma (GBM), and triple-negative breast cancer (TNBC). In this review, we focus on the role of iPD-1 in tumorigenesis and development and its molecular mechanisms. We also deeply discuss nivolumab-based combined therapy in common tumor therapy. iPD-1 may explain the different therapeutic effects of anti-PD-1 treatment and provide critical information for use in combined anti-tumor approaches.

Novel Pyrazolopyrazine Compounds as SHP2 Inhibitors for Treating Glioblastoma

Provided herein are novel pyrazolopyrazine compounds as SHP2 inhibitors, pharmaceutical compositions, use of such compounds in treating glioblastoma, and processes for preparing such compounds.