Immune cell score in pancreatic cancer-comparison of hotspot and whole-section techniques

Clinical Evaluation of the Pancreatic Cancer Microenvironment: Opportunities and Challenges

Advances in our understanding of pancreatic ductal adenocarcinoma (PDAC) and its tumor microenvironment (TME) have the potential to transform treatment for the hundreds of thousands of patients who are diagnosed each year. Whereas the clinical assessment of cancer cell genetics has grown increasingly sophisticated and personalized, current protocols to evaluate the TME have lagged, despite evidence that the TME can be heterogeneous within and between patients. Here, we outline current protocols for PDAC diagnosis and management, review novel biomarkers, and highlight potential opportunities and challenges when evaluating the PDAC TME as we prepare to translate emerging TME-directed therapies to the clinic.

CD3-CD8 immune score associated with a clinical score stratifies PDAC prognosis regardless of adjuvant or neoadjuvant chemotherapy

Stratification of the prognosis of pancreatic cancer (PDAC) patients treated by surgery is based solely on clinical variables, such as tumor stage and node status. The development of biomarkers of relapse is needed, especially to drive administration of adjuvant therapy in this at-risk population. Our study evaluates the prognostic performance of a CD3- and CD8-based immune score. CD3, CD8 and Foxp3 expression were evaluated on whole slides in two retrospective PDAC cohorts totaling 334 patients. For this study, we developed an immune score to estimate CD3 and CD8 infiltration in both tumor core and invasive margin using computer-guided analysis with QuPath software. Variables were combined in a dichotomous immune score. The association between immune and clinical scores, and both PFS and OS was investigated. We observed that a dichotomous immune score predicts both PFS and OS of localized PDAC. By univariate and multivariate analysis, immune score, tumor grade, adjuvant therapy, lymph node status, and adjuvant chemotherapy administration were associated with PFS and OS. We subsequently associated the PDAC immune score and clinical variables in a combined score. This combined score predicted patient outcomes independently of adjuvant or neoadjuvant treatment, and improved patient prognostic prediction compared to clinical variables or immune score alone.

The molecular mechanism of actions and clinical utilities of tumor infiltrating lymphocytes in gastrointestinal cancers: a comprehensive review and future prospects toward personalized medicine

Gastrointestinal (GI) cancers remain a significant global health burden, accounting for a substantial number of cases and deaths. Regrettably, the inadequacy of dependable biomarkers hinders the precise forecasting of patient prognosis and the selection of appropriate therapeutic sequencing for individuals with GI cancers, leading to suboptimal outcomes for numerous patients. The intricate interplay between tumor-infiltrating lymphocytes (TILs) and the tumor immune microenvironment (TIME) has been shown to be a pivotal determinant of response to anti-cancer therapy and consequential clinical outcomes across a multitude of cancer types. Therefore, the assessment of TILs has garnered global interest as a promising prognostic biomarker in oncology, with the potential to improve clinical decision-making substantially. Moreover, recent discoveries in immunotherapy have progressively changed the landscape of cancer treatment and significantly prolonged the survival of patients with advanced cancers. Nonetheless, the response rate remains constrained within solid tumor sufferers, even when TIL landscapes appear comparable, which calls for the development of our understanding of cellular and molecular cross-talk between TIME and tumor. Hence, this comprehensive review encapsulates the extant literature elucidating the TILs' underlying molecular pathogenesis, prognostic significance, and their relevance in the realm of immunotherapy for patients afflicted by GI tract cancers. Within this review, we demonstrate that the type, density, and spatial distribution of distinct TIL subpopulations carries pivotal implications for the prediction of anti-cancer treatment responses and patient survival. Furthermore, this review underscores the indispensable role of TILs in modulating therapeutic responses within distinct molecular subtypes, such as those characterized by microsatellite stability or programmed cell death ligand-1 expression in GI tract cancers. The review concludes by outlining future directions in TIL-based personalized medicine, including integrating TIL-based approaches into existing treatment regimens and developing novel therapeutic strategies that exploit the unique properties of TILs and their potential as a promising avenue for personalized cancer treatment.

The tumor-stroma ratio and the immune microenvironment improve the prognostic prediction of pancreatic ductal adenocarcinoma

Tumor-infiltrating immune cells and fibroblasts are significant components of the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC), and they participate in tumor progression as closely as tumor cells. However, the relationship between the features of the TME and patient outcomes and the interactions among TME components are still unclear. In this study, we evaluated the PDAC TME in terms of the quantity and location of cluster of differentiation (CD)4⁺ T cells, CD8⁺ T cells, macrophages, stromal maturity, and tumor-stroma ratio (TSR), as evaluated by immunohistochemical staining of serial whole-tissue sections from 116 patients with PDAC. The density of T cells and macrophages (mainly activated macrophages) was significantly higher at the invasive margins (IMs) than at the tumor center (TC). CD4⁺ T cells were significantly association with all the other tumor-associated immune cells (TAIs) including CD8, CD68 and CD206 positive cells. Tumors of the non-mature (intermediate and immature) stroma type harbored significantly more CD8⁺ T cells at the IMs and more CD68⁺ macrophages at the IMs and the TC. The density of CD4⁺, CD8⁺, and CD206⁺ cells at the TC; CD206⁺ cells at the IMs; and tumor-node-metastasis (TNM) staging were independent risk factors for patient outcomes, and the c-index of the risk nomogram for predicting the survival probability based on the TME features and TNM staging was 0.772 (95% confidence interval: 0.713-0.832). PDAC harbored a significantly immunosuppressive TME, of which the IMs were the hot zones for TAIs, while cells at the TC were more predictive of prognosis. Our results indicated that the model based on the features of the TME and TNM staging could predict patient outcomes.

The PD-L1 Expression and Tumor-Infiltrating Immune Cells Predict an Unfavorable Prognosis in Pancreatic Ductal Adenocarcinoma and Adenosquamous Carcinoma

The tumor microenvironment (TME) plays a vital role in the development, progression, and metastasis of pancreatic cancer (PC). The composition of the TME and its potential prognostic value remains to be fully understood, especially in adenosquamous carcinoma of pancreas (ASCP) patients. Immunohistochemistry was used to explore the clinical significance of CD3, CD4, CD8, FoxP3, and PD-L1 expression within the TME and to identify correlations with the prognosis of PC in a series of 29 patients with ASCP and 54 patients with pancreatic ductal adenocarcinoma (PDAC). Data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) were accessed to obtain the scRNA-seq data and transcriptome profiles. Seurat was used to process the scRNA-seq data, and CellChat was used to analyze cell-cell communication. CIBERSORT was used to approximate the constitution of tumor-infiltrating immune cell (TICs) profiles. Higher levels of PD-L1 were linked with a shorter overall survival in ASCP (p = 0.0007) and PDAC (p = 0.0594). A higher expression of CD3+ and CD8+ T-cell infiltration was significantly correlated with a better prognosis in PC. By influencing the composition of tumor-infiltrating immune cells (TICs), high levels of PD-L1 expression are linked with a shorter overall survival in ASCP and PDAC.

High expression of p62/SQSTM1 predicts shorter survival for patients with pancreatic cancer

BACKGROUND

Accumulation of the signal adaptor protein p62 has been demonstrated in many forms of cancer, including pancreatic ductal adenocarcinoma (PDAC). Although data from experimental studies suggest that p62 accumulation accelerates the development of PDAC, the association between p62 protein expression and survival in PDAC patients is unclear.

METHODS

Thirty-three tumor specimens from PDAC patients treated by primary surgery were obtained. Immunohistochemical expression of p62, microtubule-associated protein 1A/1B-light chain 3 (LC3), and nuclear factor-erythroid factor 2-related factor 2 (NRF2) in tumor tissue was examined for associations with clinicopathological characteristics and disease-specific survival (DSS).

RESULTS

There was no association between p62 expression and any of the clinicopathological variables. However, high p62 protein expression in tumor cells was significantly associated with shorter DSS (7 months vs. 29 months, p = 0.017). The hazard ratio for death in patients with high p62 protein expression in tumor cells was 2.88 (95% confidence interval: 1.17-7.11, p = 0.022). In multivariable analysis, high p62 expression was an independent prognostic factor for shorter DSS (p = 0.020) when follow up time was more than 5 years. LC3 and NRF2 staining was not associated with survival or other clinicopathological parameters.

CONCLUSION

Our results show that high p62 protein expression in tumor cells is associated with shorter survival following pancreatic tumor resection. This association supports a role for p62 as a prognostic marker in patients with PDAC treated by primary surgery.

Prognostic Implications of Intratumoral and Peritumoral Infiltrating Lymphocytes in Pancreatic Ductal Adenocarcinoma

This study aimed to elucidate the prognostic implications of intratumoral and peritumoral infiltrating T-lymphocytes in pancreatic ductal adenocarcinoma (PDAC) through a meta-analysis. A total of 18 eligible studies and 2453 PDAC patients were included in the present study. Intratumoral and peritumoral infiltrating lymphocytes were evaluated using various markers, such as CD3, CD4, CD8, FOXP3, and immune cell score. The correlations between these parameters and overall and disease-free survival were investigated and used in the meta-analysis. High intratumoral infiltration of CD3-, CD4-, and CD8-expressing lymphocytes was significantly correlated with better overall survival (hazard ratio (HR) 0.747, 95% confidence interval (CI) 0.620-0.900, HR 0.755, 95% CI 0.632-0.902, and HR 0.754, 95% CI 0.611-0.930, respectively). However, there was no significant correlation between PDAC prognosis and intratumoral FOXP3 or immune cell score (HR 1.358, 95% CI 1.115-1.655 and HR 0.776, 95% CI 0.566-1.065, respectively). Moreover, there was no significant correlation between the prognosis and peritumoral infiltrating T-lymphocytes. In evaluations of disease-free survival, only high intratumoral CD4 infiltration was correlated with a better prognosis (HR 0.525, 95% CI 0.341-0.810). Our results showed that high intratumoral infiltrating lymphocytes were significantly correlated with a better PDAC prognosis. However, among the tumor-infiltrating lymphocytes, CD3, CD4, and CD8 had prognostic implications, but not FOXP3 and immune cell score.

XGBoost Classifier Based on Computed Tomography Radiomics for Prediction of Tumor-Infiltrating CD8+ T-Cells in Patients With Pancreatic Ductal Adenocarcinoma

OBJECTIVES

This study constructed and validated a machine learning model to predict CD8+ tumor-infiltrating lymphocyte expression levels in patients with pancreatic ductal adenocarcinoma (PDAC) using computed tomography (CT) radiomic features.

MATERIALS AND METHODS

In this retrospective study, 184 PDAC patients were randomly assigned to a training dataset (n =137) and validation dataset (n =47). All patients were divided into CD8+ T-high and -low groups using X-tile plots. A total of 1409 radiomics features were extracted from the segmentation of regions of interest, based on preoperative CT images of each patient. The LASSO algorithm was applied to reduce the dimensionality of the data and select features. The extreme gradient boosting classifier (XGBoost) was developed using a training set consisting of 137 consecutive patients admitted between January 2017 and December 2017. The model was validated in 47 consecutive patients admitted between January 2018 and April 2018. The performance of the XGBoost classifier was determined by its discriminative ability, calibration, and clinical usefulness.

RESULTS

The cut-off value of the CD8+ T-cell level was 18.69%, as determined by the X-tile program. A Kaplan-Meier analysis indicated a correlation between higher CD8+ T-cell levels and better overall survival (p = 0.001). The XGBoost classifier showed good discrimination in the training set (area under curve [AUC], 0.75; 95% confidence interval [CI]: 0.67-0.83) and validation set (AUC, 0.67; 95% CI: 0.51-0.83). Moreover, it showed a good calibration. The sensitivity, specificity, accuracy, positive and negative predictive values were 80.65%, 60.00%, 0.69, 0.63, and 0.79, respectively, for the training set, and 80.95%, 57.69%, 0.68, 0.61, and 0.79, respectively, for the validation set.

CONCLUSIONS

We developed a CT-based XGBoost classifier to extrapolate the infiltration levels of CD8+ T-cells in patients with PDAC. This method could be useful in identifying potential patients who can benefit from immunotherapies.

Gene coexpression network approach to develop an immune prognostic model for pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a nonimmunogenic tumor, and very little is known about the relationship between the host immune response and patient survival. We aimed to develop an immune prognostic model (IPM) and analyze its relevance to the tumor immune profiles of patients with PAAD.

METHODS

We investigated differentially expressed genes between tumor and normal tissues in the TCGA PAAD cohort. Immune-related genes were screened from highly variably expressed genes with weighted gene correlation network analysis (WGCNA) to construct an IPM. Then, the influence of IPM on the PAAD immune profile was comprehensively analyzed.

RESULTS

A total of 4902 genes highly variably expressed among primary tumors were used to construct a weighted gene coexpression network. One hundred seventy-five hub genes in the immune-related module were used for machine learning. Then, we established an IPM with four core genes (FCGR2B, IL10RA, and HLA-DRA) to evaluate the prognosis. The risk score predicted by IPM was an independent prognostic factor and had a high predictive value for the prognosis of patients with PAAD. Moreover, we found that the patients in the low-risk group had higher cytolytic activity and lower innate anti-PD-1 resistance (IPRES) signatures than patients in the high-risk group.

CONCLUSIONS

Unlike the traditional methods that use immune-related genes listed in public databases to screen prognostic genes, we constructed an IPM through WGCNA to predict the prognosis of PAAD patients. In addition, an IPM prediction of low risk indicated enhanced immune activity and a decreased anti-PD-1 therapeutic response.

Next-Generation Digital Histopathology of the Tumor Microenvironment

Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology-which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning.

Immunotyping and Quantification of Melanoma Tumor-Infiltrating Lymphocytes

The density of tumour-infiltrating lymphocytes (TILs) in melanoma is correlated with improved clinical prognosis; however, standardized TIL immunotyping and quantification protocols are lacking. Herein, we provide a review of the technologies being utilized for the immunotyping and quantification of melanoma TILs.

Clinical correlates for immune checkpoint therapy: significance for CNS malignancies

Immune checkpoint inhibitors (ICIs) have revolutionized the field of cancer immunotherapy. Most commonly, inhibitors of PD-1 and CTLA4 are used having received approval for the treatment of many cancers like melanoma, non-small-cell lung carcinoma, and leukemia. In contrast, to date, clinical studies conducted in patients with CNS malignancies have not demonstrated promising results. However, patients with CNS malignancies have several underlying factors such as treatment with supportive medications like corticosteroids and cancer therapies including radiation and chemotherapy that may negatively impact response to ICIs. Although many clinical trials have been conducted with ICIs, measures that reproducibly and reliably indicate that treatment has evoked an effective immune response have not been fully developed. In this article, we will review the history of ICI therapy and the correlative biology that has been performed in the clinical trials testing these therapies in different cancers. It is our aim to help provide an overview of the assays that may be used to gauge immunologic response. This may be particularly germane for CNS tumors, where there is currently a great need for predictive biomarkers that will allow for the selection of patients with the highest likelihood of responding.

Implementing biological markers as a tool to guide clinical care of patients with pancreatic cancer

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A major obstacle for the effective treatment of PDAC is its molecular heterogeneity.

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Stratification of PDAC using markers highly specific, reproducible, sensitive, easily measurable and inexpensive is necessary.

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At the early stages, clinician’s priority lies in rapid diagnosis, so that the patient receives surgery without delay.

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At advanced disease stages, priority is to determine the tumor subtype and select a suitable effective treatment.

A major obstacle for the effective treatment of pancreatic ductal adenocarcinoma (PDAC) is its molecular heterogeneity, reflected by the diverse clinical outcomes and responses to therapies that occur. The tumors of patients with PDAC must therefore be closely examined and classified before treatment initiation in order to predict the natural evolution of the disease and the response to therapy. To stratify patients, it is absolutely necessary to identify biological markers that are highly specific and reproducible, and easily measurable by inexpensive sensitive techniques. Several promising strategies to find biomarkers are already available or under development, such as the use of liquid biopsies to detect circulating tumor cells, circulating free DNA, methylated DNA, circulating RNA, and exosomes and extracellular vesicles, as well as immunological markers and molecular markers. Such biomarkers are capable of classifying patients with PDAC and predicting their therapeutic sensitivity. Interestingly, developing chemograms using primary cell lines or organoids and analyzing the resulting high-throughput data via artificial intelligence would be highly beneficial to patients. How can exploiting these biomarkers benefit patients with resectable, borderline resectable, locally advanced, and metastatic PDAC? In fact, the utility of these biomarkers depends on the patient's clinical situation. At the early stages of the disease, the clinician's priority lies in rapid diagnosis, so that the patient receives surgery without delay; at advanced disease stages, where therapeutic possibilities are severely limited, the priority is to determine the PDAC tumor subtype so as to estimate the clinical outcome and select a suitable effective treatment.

Immunophenotype based on inflammatory cells, PD-1/PD-L1 signalling pathway and M2 macrophages predicts survival in gastric cancer

Background

Immune response against cancer has prognostic impact but its role in gastric cancer is poorly known. The aim of the study was to assess the prognostic significance of immune cell score (CD3+, CD8+), tumour immune escape (PD-L1, PD-1) and immune tolerance (Clever-1).

Methods

After exclusion of Epstein-Barr virus positive (n = 4) and microsatellite instable (n = 6) tumours, the study included 122 patients with GC undergoing D2 gastrectomy. CD3+ and CD8+ based ICS, PD-L1, PD-1 and Clever-1 expressions were evaluated. Differences in survival were examined using Cox regression adjusted for confounders. The primary outcome was 5-year survival.

Results

The 5-year overall survival rate was 43.4%. High ICS was associated with improved overall survival (adjusted HR 0.48 (95% CI 0.26–0.87)) compared to low ICS. In the high ICS group, patients with PD-L1 expression (5-year survival 69.2 vs. 53.1%, p = 0.317), high PD-1 (5-year survival 70.6 vs. 55.3% p = 0.312) and high Clever-1 (5-year survival 72.0% vs. 45.5% (p = 0.070) had poor prognosis.

Conclusions

High ICS was associated with improved survival. In the high ICS group, patients with high PD-L1, PD-1 and Clever-1 had poor prognosis highlighting the importance of immune escape and immune tolerance in GC.

The prognostic value of tumour-infiltrating lymphocytes in pancreatic cancer: a systematic review and meta-analysis

IMPORTANCE

Tumour-infiltrating lymphocytes (TILs) have previously been found to influence patient prognosis in other gastrointestinal cancers, for instance in colorectal cancer. An immunosuppressive phenotype often characterizes pancreatic cancer with a low degree of immune cell infiltration. Cytotoxic CD8⁺ T cell infiltration in tumours is found to be the best predictive variable for response to immune checkpoint inhibitor therapy, emphasizing the importance of investigating TILs in pancreatic cancer, especially focussing on CD8⁺ T cells.

OBJECTIVE

Here, we systematically review the literature and perform meta-analyses to examine the prognostic value of TILs in human pancreatic ductal adenocarcinomas (PDAC). Secondarily, we review the literature regarding the histological localization of TILs and the impact on survival in PDAC.

EVIDENCE REVIEW

A literature search was conducted on PubMed, Embase, The Cochrane Library and Web of Science. Studies examining patients with PDAC and the impact of high vs. low infiltration of immune cells on long-term oncological survival measures were included. Time-to-event meta-analysis and frequency analysis were conducted using a random effects model. The risk of bias was assessed using the Newcastle-Ottowa Scale. Quality of the cumulative evidence was evaluated using the GRADE approach for prognostic studies.

FINDINGS

In total, 1971 articles were screened, of which 43 studies were included in the systematic review and 39 in the meta-analysis. High infiltration of CD8+ lymphocytes was significantly associated with improved overall survival (OS) [hazard ratio (HR) = 0.58, 95% confidence intervals (CIs): 0.50-0.68], disease-free survival (DFS) [HR = 0.64, 95% CI: 0.52-0.78], progression-free survival [HR = 0.66, 95% CI: 0.51-0.86] and cancer-specific survival [HR = 0.56, 95% CI: 0.32-0.99]. A high infiltration of CD3+ T cells was correlated with increased OS [HR = 0.58, 95% CI: 0.50-0.68] and DFS [HR = 0.74, 95% CI: 0.38-1.43]. Infiltration of CD4+ lymphocytes was associated with improved 12-months OS [risk ratio = 0.59, 95% CI: 0.35-0.99] and DFS [risk ratio = 0.68, 95% CI: 0.53-0.88]. High expression of FoxP3+ lymphocytes was associated with poor OS [HR = 1.48, 95% CI: 1.20-1.83]. The greatest impact on survival was observed in the CD8+ T cell and OS group, when infiltration was located to the tumour centre [HR = 0.53, 95% CI: 0.45-0.63]. However, subgroup analysis on the impact of the histological location of infiltration revealed no significant differences between the subgroups (tumour centre, invasive margin, stroma and all locations) in any of the examined cell types and outcomes.

CONCLUSIONS AND RELEVANCE

Subsets of TILs, especially CD3⁺, CD8⁺ and FoxP3⁺ T cells are strongly associated with long-term oncological outcomes in patients with PDAC. To our knowledge, this is the first systematic review and meta-analysis on the prognostic value of TILs in pancreatic cancer.

Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma

OBJECTIVE

The tumour microenvironment is one of the significant factors driving the carcinogenesis of Pancreatic adenocarcinoma (PAAD). However, the underlying mechanism of how the tumour microenvironment impacts the prognosis of PAAD is not completely clear.

RESULTS

The transcriptome and clinical data of 182 PAAD program cases were downloaded from the TCGA database. Three hundred thirty-three differentially expressed genes (DEGs) between high and low stromal groups and 314 DEGs between high and low immune score groups were identified using ESTIMATE score. Based on the 203 genes differentially expressed simultaneously in two score-related comparisons, we established an 8-mRNA signature to evaluate the prognosis of PAAD patients. Kaplan-Meier curves showed significantly worse survival for patients with high-risk scores in both the training and validation groups. The risk score was an independent prognostic factor and had a high predictive value for the prognosis of patients with PAAD. By searching the TCGA database, we showed that CA9, CXCL9, and GIMAP7 from the 8-mRNA signature were associated with the infiltration levels of immunocytes by regulating FOXO1 expression in PAAD.

CONCLUSIONS

Unlike traditional methods of screening for differential genes in cancer and healthy tissues, we constructed a novel 8-mRNA signature to predict the prognosis of PAAD patients by applying ESTIMATE scoring to RNA-seq-based transcriptome data. Most importantly, we identified CA9, CXCL9, and GIMAP7 from the above eight genes as regulators of immunocyte infiltration by adjusting the expression of FOXO1 in PAAD. Thus, CA9, CXCL9, and GIMAP7 might be the ideal targets of immune therapy of PAAD.

METHODS

ESTIMATE scoring was used to determine the stromal and immune scores of transcriptome datasets downloaded from the TCGA database. An mRNA-based prognostic signature was built for the training cohort via the LASSO Cox regression model. The signature was verified using a validation cohort. Kaplan-Meier curves and log-rank analysis were used to identify survival differences. Western blot analysis and RT-qPCR analysis were carried out to analyze the expression of specific proteins and mRNAs. IHC was performed to assess the protein levels of Forkhead box-O 1 (FOXO1), Carbonic anhydrase 9 (CA9), C-X-C motif chemokine ligand 9 (CXCL9), and GTPase, IMAP family member 7 (GIMAP7) in the tissue microarray of PAAD.

Genetic landscape of prognostic value in pancreatic ductal adenocarcinoma microenvironment

Background

The prognosis of pancreatic ductal adenocarcinoma (PDAC) remains dismally poor and is widely considered as an intricate genetic disorder. The mutational landscape of PDAC may directly reflect cancer immunogenicity and dictate the extent and phenotype of immune cell infiltration. In adverse, the microenvironment may also effect the gene expression of cancer cells, which is associated with clinical prognosis. Thus, it is crucial to identify genomic alterations in PDAC microenvironment and its impacts on clinical prognosis.

Methods

The gene expression profiles, mutation data and clinical information of 179 pancreatic cancer patients with an initial pathologic diagnosis ranging from 2001 to 2013 were retrieved from The Cancer Genome Atlas (TCGA) database. The MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm for calculating immune scores and stromal scores and Tumor IMmune Estimation Resource (TIMER) resource for cell infiltrations were applied in this study.

Results

The average immune score or stromal score of PDAC subtype was significantly higher than that of other specific subtypes. KRAS mutant cases had significantly lower immune scores (P=0.001) and stromal scores (P=0.007), in concert with lower immune scores in TP53 mutant cases (P=0.030). However, no significant difference was found in SMAD4 and CDKN2A mutations. In the cohort OS/RFS, the infiltration levels of CD8+ T cells, B cells, Macrophages, Neutrophils and DCs in high stromal score group were higher than those in the low score group (all P<0.001), as well as in immune score groups except for Macrophages in the cohort RFS. In the cohort OS/RFS, 317/379 upregulated genes and 9/6 downregulated genes were observed in the high immune score group, while 227/205 upregulated genes and 17/6 downregulated genes in the high stromal score group. With the analysis for prognostic value of DEGs, 82 and 58 DEGs respectively in the high immune and stromal score group were verified to be significantly associated with better OS (P<0.05), while 53 and 17 DEGs respectively with longer RFS (P<0.05). Functional enrichment analysis showed genes of prognostic values were significantly related to immune response.

Conclusions

A list of genes with prognostic value in PDAC microenvironment were obtained from functional enrichment analysis based on immune and stromal scores, which indicates a series of potential auxiliary prognostic biomarkers for PDAC are available. Further research on these genes may be valuable and helpful to understand the crosstalk between tumor and microenvironment, new immune evasion mechanisms and underlying novel therapeutic targets in an integrated manner.