Relevance of Immune Infiltration and Clinical Outcomes in Pancreatic Ductal Adenocarcinoma Subtypes

The mechanism of USP43 in the development of tumor: a literature review

Ubiquitination of the proteins is crucial for governing protein degradation and regulating fundamental cellular processes. Deubiquitinases (DUBs) have emerged as significant regulators of multiple pathways associated with cancer and other diseases, owing to their capacity to remove ubiquitin from target substrates and modulate signaling. Consequently, they represent potential therapeutic targets for cancer and other life-threatening conditions. USP43 belongs to the DUBs family involved in cancer development and progression. This review aims to provide a comprehensive overview of the existing scientific evidence implicating USP43 in cancer development. Additionally, it will investigate potential small-molecule inhibitors that target DUBs that may have the capability to function as anti-cancer medicines.

Cytokeratin 6 identifies basal-like subtypes of pancreatic ductal adenocarcinoma with decreased survival

PURPOSE

Rising incidence of pancreatic ductal adenocarcinoma (PDAC) bind with insufficient therapy options showcases a great medical challenge. Further biomarkers are required to identify patients, who will benefit from more aggressive therapy.

METHODS

320 patients were included by the PANCALYZE study group. Cytokeratin 6 (CK6) immunohistochemical staining as a putative marker for the basal-like subtype of PDAC was performed. The correlation between CK6 expression patterns and survival data, as well as various markers of the (inflammatory) tumor microenvironment, were analyzed.

RESULTS

We divided the study population based on the expression pattern of CK6. Patients with a high CK6 tumor expression had a significantly shorter survival (p = 0.013), confirmed in a multivariate cox regression model. CK6-expression is an independent marker for a decreased overall survival (HR = 1.655, 95% CI 1.158-2.365, p = 0.006). In addition, the CK6-positive tumors showed significantly less plasma cell infiltration and more cancer-associated fibroblasts (CAFs) expressing Periostin and SMA.

CONCLUSIONS

CK6 could be considered as an independent biomarker for a shorter overall survival. CK6 is a clinically easily accessible biomarker for the identification of the basal-like subtype of PDAC. Therefore, it could be taken into consideration in deciding for the more aggressive therapy regimes. Prospectively, studies addressing the chemosensitive characteristics of this subtype are required.

TIGIT Expression Delineates T-cell Populations with Distinct Functional and Prognostic Impact in Pancreatic Cancer

PURPOSE

Immunotherapy has led to a fundamental shift in the treatment of several cancers. However, its efficacy in pancreatic ductal adenocarcinoma (PDAC) is limited. Understanding the expression of inhibitory immune checkpoint receptors (ICR) by intratumoral T cells may help to unravel their involvement in insufficient T-cell-mediated antitumor immunity.

EXPERIMENTAL DESIGN

Using multicolor flow cytometry, we analyzed circulating and intratumoral T cells from blood (n = 144) and matched tumor samples (n = 107) of patients with PDAC. We determined the expression of programmed cell death protein 1 (PD-1) and T-cell immunoreceptor with Ig and immunoreceptor tyrosine-based inhibition motif (ITIM) domains (TIGIT) by CD8+ T-cells, conventional CD4+ T-cells (Tconv) and regulatory T cells (Treg) and their association with T-cell differentiation, tumor reactivity, and cytokine expression. A comprehensive follow-up was used to determine their prognostic value.

RESULTS

Intratumoral T cells were characterized by increased PD-1 and TIGIT expression. Both markers delineated distinct T-cell subpopulations. PD-1+TIGIT- T cells highly expressed proinflammatory cytokines and markers of tumor reactivity (CD39, CD103), whereas TIGIT expression was linked to antiinflammatory and exhausted phenotypes. In addition, the enhanced presence of intratumoral PD-1+TIGIT- Tconv was associated with improved clinical outcomes, while high ICR expression on blood T cells was a significant hazard for overall survival (OS).

CONCLUSIONS

Our results uncover the association between ICR expression and T-cell functionality. PD-1 and TIGIT characterized intratumoral T cells with highly divergent phenotypes linked to clinical outcomes, further underscoring the relevance of TIGIT for immunotherapeutic approaches in PDAC. The prognostic value of ICR expression in patient blood may be a valuable tool for patient stratification.

Ubiquitin-Specific Protease 43 Impacts Pancreatic Ductal Adenocarcinoma Prognosis by Altering Its Proliferation and Infiltration of Surrounding Immune Cells

Background

Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer, and the therapy options for PDAC remain restricted. The distinctive tumor immunological microenvironment (TIME) of PDAC, comprising a high number of stromal cells and a limited infiltration of cytotoxic T lymphocytes (CTLs), rendered immunotherapy ineffective. The protein level of ubiquitin-specific protease 43 (USP43) was a prognostic predictor in numerous cancers; however, its function in PDAC is limited. This article focuses on the influence of USP43 expression on PDAC prognosis and TIME alteration.

Methods

Based on TCGA database and tissue microarray staining, the expression of USP43 in PDAC was evaluated. The association between USP43 and prognosis was then investigated using tissue samples and online databases. In PDAC tumor tissues, the correlation between USP43 expression and clinicopathological characteristics, immune cell infiltration, and prognosis was investigated. The expression of USP43 in PDAC cell lines was evaluated using quantitative polymerase chain reaction. Using a cell counting kit-8 (CCK-8) and a cell colony formation test, the viability of the cells was determined. On the basis of online databases and tissue samples, the link between USP43 and immune cell infiltration around PDAC was also examined. For statistical analyses, the software GraphPad, R, and SPSS 26.0 were utilized.

Results

The expression of USP43 was considerably higher in PDAC compared to normal pancreatic tissue in both the TCGA database and the tissue microarrays of PDAC patients (P < 0.001). High USP43 expression was associated with poor overall survival in both the TCGA database and the tissue microarray of PDAC patients (P = 0.046 and 0.021, respectively). USP43 overexpression promoted PANC-1 cell proliferation (P = 0.0018), but USP43 knockdown decreased PANC02 cell proliferation (P < 0.001). According to the TCGA database, USP43 is associated with T cell activation and inhibits CD8⁺ T cell activation in PDAC, as proven by a study of cell lines. Moreover, in both TCGA and PDAC cell lines, USP43 expression was negatively linked with the chemokine signaling pathway.

Conclusions

Overexpression of USP43 is a potential prognostic indicator for PDAC patients. USP43 is a potential biomarker associated with T cell activation, suppression of CD8⁺ T cell enrichment, and the cytokine signal pathway. Future multicenter studies are needed to confirm our findings and their potential application in the treatment of PDAC patients.

Spatially resolved deconvolution of the fibrotic niche in lung fibrosis

A defining pathological feature of human lung fibrosis is localized tissue heterogeneity, which challenges the interpretation of transcriptomic studies that typically lose spatial information. Here we investigate spatial gene expression in diagnostic tissue using digital profiling technology. We identify distinct, region-specific gene expression signatures as well as shared gene signatures. By integration with single-cell data, we spatially map the cellular composition within and distant from the fibrotic niche, demonstrating discrete changes in homeostatic and pathologic cell populations even in morphologically preserved lung, while through ligand-receptor analysis, we investigate cellular cross-talk within the fibrotic niche. We confirm findings through bioinformatic, tissue, and in vitro analyses, identifying that loss of NFKB inhibitor zeta in alveolar epithelial cells dysregulates the TGFβ/IL-6 signaling axis, which may impair homeostatic responses to environmental stress. Thus, spatially resolved deconvolution advances understanding of cell composition and microenvironment in human lung fibrogenesis.

Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma

Lung cancer has the highest tumor incidence in China. Lung squamous cell carcinoma (LUSC) is the most common type, accounting for 40–51% of primary lung cancers. LUSC is slow in growth and late in metastasis. Immune-related genes (IRGs) and immune infiltrating cells play a vital role in the clinical outcomes of LUSC. It is important to systematically study its immune gene map to help the prognosis of cancer patients. In this study, we combined the prognostic landscape and expression status of IRGs downloaded from the TCGA and InnatedDB databases and systematically analyzed the prognostic information of LUSC patients to obtain IRGs. After systematically exploring the survival analysis, prognosis-related genes were found, and the PPI network revealed that a total of 11 genes were hub genes. A two-gene prognosis risk model was established by multivariate Cox analysis. Two IRGs were closely correlated with the prognosis of LUSC. Based on these two genes, a new independent prognostic risk model was established, and this model was further verified in the GEO database. Moreover, the risk score of the model was correlated with sex, survival status, and lymphatic metastasis in LUSC patients, and the predictive risk of the prognostic risk model was significantly positively correlated with five kinds of immune cells (CD4 T cells, CD8 T cells, neutrophils, macrophages, and dendritic cells). This study comprehensively analyzed immunogenomics and presented immune-related prognostic biomarkers for LUSC.

Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer

Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients’ outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV.

T cell receptor (TCR) signaling in health and disease

Interaction of the T cell receptor (TCR) with an MHC-antigenic peptide complex results in changes at the molecular and cellular levels in T cells. The outside environmental cues are translated into various signal transduction pathways within the cell, which mediate the activation of various genes with the help of specific transcription factors. These signaling networks propagate with the help of various effector enzymes, such as kinases, phosphatases, and phospholipases. Integration of these disparate signal transduction pathways is done with the help of adaptor proteins that are non-enzymatic in function and that serve as a scaffold for various protein-protein interactions. This process aids in connecting the proximal to distal signaling pathways, thereby contributing to the full activation of T cells. This review provides a comprehensive snapshot of the various molecules involved in regulating T cell receptor signaling, covering both enzymes and adaptors, and will discuss their role in human disease.

Assessment of immune status of laryngeal squamous cell carcinoma can predict prognosis and guide treatment

BACKGROUND

In the past few years, immunotherapy has changed the way we treat solid tumors. People pay more and more attention to the immune microenvironment of laryngeal squamous cell carcinoma (LSCC). In this study, our immunotherapy research took advantage of the clinical database and focused our in-depth analysis on the tumor microenvironment (TME).

METHODS

This study evaluated the relationship between the clinical outcome and the local tissue and overall immune status in 412 patients with primary LSCC. We constructed and validated a risk model that could predict prognosis, assess immune status, identify high-risk patients, and develop personalized treatment plans through bioinformatics. In addition, through immunohistochemical analysis, we verified the differential expression of CTSL and KDM5D genes with the largest weight coefficients in the model in LSCC tissues and their influence on the prognosis and tumor-infiltrating lymphocytes (TILs).

RESULTS

We found that interstitial tumor-infiltrating lymphocytes, tumor parenchymal-infiltrating lymphocyte volume, tumor infiltrates lymphocytes of frontier invasion, and the platelet-to-lymphocyte ratio (PLR) were independent factors affecting the prognosis of patients with LSCC. A novel risk model can guide clinicians to accurately predict prognosis, identify high-risk patients, and formulate personalized treatment plans. The differential expression of genes such as CTSL and KDM5D has a significant correlation with the TILs of LSCC and the prognosis of patients.

CONCLUSION

Local and systemic inflammatory markers in patients with laryngeal squamous cell carcinoma are reliable prognostic factors. The risk model and CTSL, KDM5D gene have important potential research value.

Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model

Simple Summary

Osteosarcoma is a rare type of cancer with poor prognoses. However, to the best of our knowledge, there are no mathematical models that study the impact of chemotherapy treatments on the osteosarcoma microenvironment. In this study, we developed a data driven mathematical model to analyze the dynamics of the important players in three groups of osteosarcoma tumors with distinct immune patterns in the presence of the most common chemotherapy drugs. The results indicate that the treatments’ start times and optimal dosages depend on the unique growth rate of the tumor, which implies the necessity of personalized medicine. Furthermore, the developed model can be extended by others to build models that can recommend individual-specific optimal dosages.

Abstract

Since all tumors are unique, they may respond differently to the same treatments. Therefore, it is necessary to study their characteristics individually to find their best treatment options. We built a mathematical model for the interactions between the most common chemotherapy drugs and the osteosarcoma microenvironments of three clusters of tumors with unique immune profiles. We then investigated the effects of chemotherapy with different treatment regimens and various treatment start times on the behaviors of immune and cancer cells in each cluster. Saliently, we suggest the optimal drug dosages for the tumors in each cluster. The results show that abundances of dendritic cells and HMGB1 increase when drugs are given and decrease when drugs are absent. Populations of helper T cells, cytotoxic cells, and IFN-γ grow, and populations of cancer cells and other immune cells shrink during treatment. According to the model, the MAP regimen does a good job at killing cancer, and is more effective than doxorubicin and cisplatin combined or methotrexate alone. The results also indicate that it is important to consider the tumor’s unique growth rate when deciding the treatment details, as fast growing tumors need early treatment start times and high dosages.

Liver-Metastasis-Related Genes are Potential Biomarkers for Predicting the Clinical Outcomes of Patients with Pancreatic Adenocarcinoma

It is widely acknowledged that metastasis determines the prognosis of pancreatic adenocarcinoma (PAAD), and the liver is the most primary distant metastatic location of PAAD. It is worth exploring the value of liver-metastasis-related genetic prognostic signature (LM-PS) in predicting the clinical outcomes of PAAD patients post R0 resection. We collected 65 tumors and 165 normal pancreatic data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx), respectively. Differentially expressed genes (DEGs) between primary tumor and normal pancreatic samples were intersected with DEGs between primary tumor samples with liver metastasis and those without new tumor events. The intersected 45 genes were input into univariate Cox regression analysis to identify the prognostic genes. Thirty-three prognostic liver-metastasis-related genes were identified and included in least absolute shrinkage and selection operator (LASSO) analysis to develop a seven-gene LM-PS, which included six risk genes (ANO1, FAM83A, GPR87, ITGB6, KLK10, and SERPINE1) and one protective gene (SMIM32). The PAAD patients were grouped into low- and high-risk groups based on the median value of risk scores. The LM-PS harbored an independent predictive ability to distinguish patients with a high-risk of death and liver metastasis after R0 resection. Moreover, a robust prognostic nomogram based on LM-PS, the number of positive lymph nodes, and histologic grade were established to predict the overall survival of PAAD patients. Besides, a transcription factor‐microRNA coregulatory network was constructed for the seven LM-PS genes, and the immune infiltration and genomic alterations were systematically explored in the TGCA-PAAD cohort.

An Eight-Gene Hypoxia Signature Predicts Survival in Pancreatic Cancer and Is Associated With an Immunosuppressed Tumor Microenvironment

Intratumoral hypoxia is a widely established element of the pancreatic tumor microenvironment (TME) promoting immune escape, tumor invasion, and progression, while contributing to treatment resistance and poor survival. Despite this critical role, hypoxia is underrepresented in molecular signatures of pancreatic ductal adenocarcinoma (PDA) and concurrent investigations into the hypoxia-immune status are lacking. In this work a literature-based approach was applied to derive an eight-gene hypoxia signature that was validated in fourteen cancer cell lines and in a cohort of PDA. The eight-gene hypoxia signature was significantly associated with overall survival in two distinct PDA datasets and showed independent prognostic value in multivariate analysis. Comparative analysis of tumors according to their hypoxia score (high versus low) determined that tumors with high hypoxia were significantly less enriched in cytotoxic T-cells, and cytolytic activity. In addition, they had lower expression of cytokines and tumor inflammatory markers, pointing to the signature’s ability to discern an immune “cold”, hypoxic TME. Combining the signature with an immune metric highlighted a worse survival probability in patients with high hypoxia and low immune reactivity, indicating that this approach could further refine survival estimates. Hypoxia as determined by our signature, was significantly associated with certain immune checkpoint inhibitors (ICI) biomarkers, suggesting that the signature reflects an aspect of the TME that is worth pursuing in future clinical trials. This is the first work of its kind in PDA, and our findings on the hypoxia-immune tumor contexture are not only relevant for ICI but could also guide combinatorial hypoxia-mediated therapeutic strategies in this cancer type.

Identification, Validation, and Utilization of Immune Cells in Pancreatic Ductal Adenocarcinoma Based on Marker Genes

The immune response affects tumor biological behavior and progression. The specific immune characteristics of pancreatic ductal adenocarcinoma (PDAC) can determine the metastatic abilities of cancerous cells and the survival of patients. Therefore, it is important to characterize the specific immune landscape in PDAC tissue samples, and the effect of various types of therapy on that immune composition. Previously, a set of marker genes was identified to assess the immune cell composition in different types of cancer tissue samples. However, gene expression and subtypes of immune cells may vary across different types of cancers. The aim of this study was to provide a method to identify immune cells specifically in PDAC tissue samples. The method is based on defining a specific set of marker genes expressed by various immune cells in PDAC samples. A total of 90 marker genes were selected and tested for immune cell type-specific definition in PDAC; including 43 previously used, and 47 newly selected marker genes. The immune cell-type specificity was checked mathematically by calculating the “pairwise similarity” for all candidate genes using the PDAC RNA-sequenced dataset available at The Cancer Genome Atlas. A set of 55 marker genes that identify 22 different immune cell types for PDAC was created. To validate the method and the set of marker genes, an independent mRNA expression dataset of 24 samples of PDAC patients who received various types of (neo)adjuvant treatments was used. The results showed that by applying our method we were able to identify PDAC specific marker genes to characterize immune cell infiltration in tissue samples. The method we described enabled identifying different subtypes of immune cells that were affected by various types of therapy in PDAC patients. In addition, our method can be easily adapted and applied to identify the specific immune landscape in various types of tissue samples.