The Impact of Immune Microenvironment on the Prognosis of Pancreatic Ductal Adenocarcinoma Based on Multi-Omics Analysis

Single-cell and bulk RNA sequencing identifies T cell marker genes score to predict the prognosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the lethal malignancies, with limited biomarkers identified to predict its prognosis and treatment response of immune checkpoint blockade (ICB). This study aimed to explore the predictive ability of T cell marker genes score (TMGS) to predict their overall survival (OS) and treatment response to ICB by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Multi-omics data of PDAC were applied in this study. The uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification. The non-negative matrix factorization (NMF) algorithm was applied to molecular subtypes clustering. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was adopted for TMGS construction. The prognosis, biological characteristics, mutation profile, and immune function status between different groups were compared. Two molecular subtypes were identified via NMF: proliferative PDAC (C1) and immune PDAC (C2). Distinct prognoses and biological characteristics were observed between them. TMGS was developed based on 10 T cell marker genes (TMGs) through LASSO-Cox regression. TMGS is an independent prognostic factor of OS in PDAC. Enrichment analysis indicated that cell cycle and cell proliferation-related pathways are significantly enriched in the high-TMGS group. Besides, high-TMGS is related to more frequent KRAS, TP53, and CDKN2A germline mutations than the low-TMGS group. Furthermore, high-TMGS is significantly associated with attenuated antitumor immunity and reduced immune cell infiltration compared to the low-TMGS group. However, high TMGS is correlated to higher tumor mutation burden (TMB), a low expression level of inhibitory immune checkpoint molecules, and a low immune dysfunction score, thus having a higher ICB response rate. On the contrary, low TMGS is related to a favorable response rate to chemotherapeutic agents and targeted therapy. By combining scRNA-seq and bulk RNA-seq data, we identified a novel biomarker, TMGS, which has remarkable performance in predicting the prognosis and guiding the treatment pattern for patients with PDAC.

Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer

Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, who may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics among the primary tumor, recurrent tumor, and metastatic tumor in different stages of cancer, which may be caused by the molecular level. Moreover, the importance of predicting early cancer recurrence and metastasis is emphasized by survival analyses. Next, we used a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and discovered that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazard model and Fisher's exact test, were used to identify specific genes or immune characteristics associated with early cancer recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B-cell infiltration levels are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are all linked to early cancer metastasis. These findings have led us to construct classifiers, and the average area under the curve (AUC) of these classifiers was greater than 0.75 in The Cancer Genome Atlas (TCGA) cancer patients, confirming that the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment-sensitive targets can be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.

A Mouse Model of Damp-Heat Syndrome in Traditional Chinese Medicine and Its Impact on Pancreatic Tumor Growth

Background

Damp-heat syndrome is one of the most important syndrome types in the traditional Chinese medicine (TCM) syndrome differentiation and treatment system, as well as the core pathogenesis of pancreatic cancer (PC) which remains a challenge to medical researchers due to its insidious onset and poor prognosis. Great attention has been given to the impact of damp-heat syndrome on tumorigenesis and progression, but less attention has been given to damp-heat modeling per se. Studying PC in a proper damp-heat syndrome animal model can recapitulate the actual pathological process and contribute to treatment strategy improvement.

Methods

Here, an optimized damp-heat syndrome mouse model was established based on our prior experience. The Fibonacci method was applied to determine the maximum tolerated dosage of alcohol for mice. Damp-heat syndrome modeling with the old and new methods was performed in parallel of comparative study about general appearance, food intake, water consumption and survival. Major organs, including the liver, kidneys, lungs, pancreas, spleen, intestines and testes, were collected for histological evaluation. Complete blood counts and biochemical tests were conducted to characterize changes in blood circulation. PC cells were subcutaneously inoculated into mice with damp-heat syndrome to explore the impact of damp-heat syndrome on PC growth. Hematoxylin-eosin staining, Masson staining and immunohistochemistry were performed for pathological evaluation. A chemokine microarray was applied to screen the cytokines mediating the proliferation-promoting effects of damp-heat syndrome, and quantitative polymerase chain reaction and Western blotting were conducted for results validation.

Results

The new modeling method has the advantages of mouse-friendly features, easily accessible materials, simple operation, and good stability. More importantly, a set of systematic indicators was proposed for model evaluation. The new modeling method verified the pancreatic tumor-promoting role of damp-heat syndrome. Damp-heat syndrome induced the proliferation of cancer-associated fibroblasts and promoted desmoplasia. In addition, circulating and tumor-located chemokine levels were altered by damp-heat syndrome, characterized by tumor promotion and immune suppression.

Conclusions

This study established a stable and reproducible murine model of damp-heat syndrome in TCM with systematic evaluation methods. Cancer associated fibroblast-mediated desmoplasia and chemokine production contribute to the tumor-promoting effect of damp-heat syndrome on PC.

Impact of the tumor immune microenvironment on the outcome of pancreatic cancer: a retrospective study based on clinical pathological analysis

BACKGROUND

The cancerous microenvironment, characterized by the infiltration of CD4+ and CD8+ T cells, play a critical role in regulating the progression of cancer and treating efficiency of immunotherapy. However, the distribution of these cells and their associated cytokines in the tumor microenvironment of pancreatic cancer (PC) are not yet fully understood. Our study aims to analyze the contents of CD4+IL-17+ and CD8+ T cells in PC and their relationship with the clinicopathological features and survival outcomes of patients.

METHODS

PC tissues and adjacent tissues were retrospectively collected from 40 patients in our hospital. The expression of CD4, IL-17, and CD8 in histological samples was measured by immunohistochemistry. The correlation between CD4, IL-17, and CD8 expression and clinical characteristics was analyzed using Kaplan-Meier survival analysis. The risk factors affecting the outcome of PC were examined by the Cox proportional hazards model, then a nomogram predicting the survival of PC using these risk factors was established.

RESULTS

The content of CD4+IL-17+ T cells in PC tissues was significantly higher than that in adjacent normal tissues, while the number of CD8+ T cells was significantly lower than that in adjacent normal tissues (P<0.01). CD4+ T cells in PC tissues was significantly associated with TNM stage and lymph node metastasis (P<0.05). IL-17 and CD8 were significantly associated with histological grade, TNM stage, local infiltration, and lymph node metastasis (P<0.05). The median survival times (MSTs) of CD4 positive and negative patients were 13.2 and 21.4 months, respectively. The MSTs of IL-17 positive and negative patients were 10.4 and 24.8 months, respectively. The MSTs were 21.9 and 11.8 months for CD8 positive and negative patients, respectively (P<0.05). The Cox regression model demonstrated that TNM staging, lymph node metastasis, and CD4+IL-17+ and CD8+ T cells affected PC prognosis (P<0.05). The nomogram showed that the survival probability was reduced in patients with TNM stage III to IV, lymph node metastasis, high CD4+IL-17+ level, and low CD8+ expression.

CONCLUSIONS

CD4+IL-17+ and CD8+ T cells in PC tissues are associated with TNM staging, lymph node metastasis, and MST, and can be used as new prognostic indicators for PC.