Prognostic Marker For Pancreatic Cancer Research Articles

Anoikis-related genes linked with patient outcome in pancreatic cancer

Anoikis is programmed cell death occurring upon cell detachment from the extracellular matrix. Cancer cells need to evade anoikis to be able to metastasize to distant sites. However, the molecular features and prognostic value of anoikis-related genes (ARGs) in pancreatic cancer remain unclear. In this study, we utilized transcriptome data from the TCGA and GSE102238 databases to identify 64 ARGs significantly associated with prognosis. We used the “ConsensusClusterPlus” R package to stratify patients into high and low-risk prognostic subgroups. The KEGG and GSEA analyses revealed that the clusters with poor prognosis were enriched for the ECM receptor interaction pathway, the TP53 signaling pathway, and the galactose metabolism pathway, and that the cell cycle pathway was upregulated. A prognostic model consisting of seven ARGs (SERPINE1, EGF, E2F1, MSLN, RAB27B, ETV7, MST1) was constructed using LASSO regression and when combined with clinicopathological parameters using Cox regression, a prognostic Nomogram was created, which demonstrated high prognostic utility. Among the biomarker candidates, we report ETV7 as a novel, independent prognostic marker in pancreatic cancer. ETV7 was highly expressed in KRAS and TP53 co-occurrent mutant TCGA patients, indicating that it may be regulated by the two major driver genes of pancreatic cancer.Therefore, targeting ETV7 could be a potential focus for future therapeutic studies.

REEP3 is a potential diagnostic and prognostic biomarker correlated with immune infiltration in pancreatic cancer

Receptor Expression-Enhancing Protein 3 (REEP3) serves as a pivotal enzyme crucial for endoplasmic reticulum (ER) clearance during mitosis and is implicated in the advancement of diverse malignancies. Nonetheless, the biological role and mechanisms of REEP3 in pancreatic cancer patients, along with its interplay with immune infiltration, remain inadequately elucidated. In this study, we initially analyzed the differential expression of REEP3 between pancreatic cancer tissues and normal pancreas tissues using the Cancer Genome Atlas (TCGA), GTEx and Gene Expression Omnibus (GEO) databases. Subsequently, we utilized Kaplan–Meier analysis, Cox regression and ROC curve to determine the predictive value of REEP3 for the clinical outcomes of pancreatic cancer patients. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), were conducted to explore the potential signaling pathways and biological functions associated with pancreatic cancer. Furthermore, we investigated the PPI network, miRNA, RBP and transcription factor interactions of REEP3 using databases such as GeneMania, STRING, StarBase, KnockTK, ENCODE, Jaspar and hTFtarget. Lastly, the “ssGSEA” algorithm and TIMER database were employed to investigate the correlation between REEP3 expression and immune infiltration as well as immune checkpoints. The expression of REEP3 in pancreatic cancer showed a significantly higher level compared to that in normal tissues. ROC curve analysis indicated that REEP3 holds substantial diagnostic potential for pancreatic cancer patients. Elevated REEP3 expression correlated with unfavorable outcomes in terms of both overall survival and relapse-free survival, establishing it as a notable adverse prognostic marker in pancreatic cancer. Moreover, both univariate and multivariate Cox regression analyses demonstrated that REEP3 maintained an independent association with overall survival. Functional enrichment analyses revealed pathways significantly linked to REEP3, including cytoplasmic translation, wound healing, viral processes, regulation of cellular component size and actin filament organization. Additionally, REEP3 expression displayed a significant positive correlation with CD8+ T cells, B cells, natural killer cells, dendritic cells and macrophages. REEP3 is a potential diagnostic, prognostic marker and immunotherapeutic target for pancreatic cancer.

Automatic quantification of tumor-stroma ratio as a prognostic marker for pancreatic cancer.

This study aims to introduce an innovative multi-step pipeline for automatic tumor-stroma ratio (TSR) quantification as a potential prognostic marker for pancreatic cancer, addressing the limitations of existing staging systems and the lack of commonly used prognostic biomarkers. The proposed approach involves a deep-learning-based method for the automatic segmentation of tumor epithelial cells, tumor bulk, and stroma from whole-slide images (WSIs). Models were trained using five-fold cross-validation and evaluated on an independent external test set. TSR was computed based on the segmented components. Additionally, TSR's predictive value for six-month survival on the independent external dataset was assessed. Median Dice (inter-quartile range (IQR)) of 0.751(0.15) and 0.726(0.25) for tumor epithelium segmentation on internal and external test sets, respectively. Median Dice of 0.76(0.11) and 0.863(0.17) for tumor bulk segmentation on internal and external test sets, respectively. TSR was evaluated as an independent prognostic marker, demonstrating a cross-validation AUC of 0.61±0.12 for predicting six-month survival on the external dataset. Our pipeline for automatic TSR quantification offers promising potential as a prognostic marker for pancreatic cancer. The results underscore the feasibility of computational biomarker discovery in enhancing patient outcome prediction, thus contributing to personalized patient management.

E2F transcription factors promote tumorigenicity in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with limited treatment options, illustrating an urgent need to identify new drugable targets in PDACs. Using the similarities between tumor development and normal embryonic development, which is accompanied by rapid cell expansion, we aimed to identify and characterize embryonic signaling pathways that were reinitiated during tumor formation and expansion. Here, we report that the transcription factors E2F1 and E2F8 are potential key regulators in PDAC. E2F1 and E2F8 RNA expression is mainly localized in proliferating cells in the developing pancreas and in malignant ductal cells in PDAC. Silencing of E2F1 and E2F8 in PANC-1 pancreatic tumor cells inhibited cell proliferation and impaired cell spreading and migration. Moreover, loss of E2F1 also affected cell viability and apoptosis with E2F expression in PDAC tissues correlating with expression of apoptosis and mitosis pathway genes, suggesting that E2F factors promote cell cycle regulation and tumorigenesis in PDAC cells. Our findings illustrate that E2F1 and E2F8 transcription factors are expressed in pancreatic progenitor and PDAC cells, where they contribute to tumor cell expansion by regulation of cell proliferation, viability, and cell migration making these genes attractive therapeutic targets and potential prognostic markers for pancreatic cancer.

BZW1 is a prognostic and immunological biomarker in pancreatic adenocarcinoma.

Pancreatic adenocarcinoma is the most common malignant tumor of the digestive system and is called the "king of cancer" because it has been labeled with high malignancy, rapid progression, poor survival, and poor prognosis. Previously, it was reported that the basic leucine zipper and W2 domains 1 (BZW1) is involved in the progression of many tumors. However, its research in digestive system tumors such as pancreatic cancer is rarely studied. To explore potential biomarkers related to survival and prognosis of pancreatic cancer and provide a new targeted therapy for it. We first analyzed the mRNA and protein expression of BZW1 in pancreatic cancer. We then explored the correlation of BZW1 with survival prognosis and immune infiltration in pancreatic cancer patients. Finally, we explored BZW1-related gene enrichment analysis, including protein-protein interaction networks, gene ontology functional enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The mRNA and protein expression of the BZW1 gene in pancreatic cancer tissues were higher than those in adjacent normal tissues, and pancreatic cancer patients with high BZW1 expression had a poor prognosis. In addition, the expression of BZW1 was positively or negatively correlated with different immune cells of pancreatic cancer, such as CD4 + T lymphocytes, CD8 + T lymphocytes, B cells, macrophages, neutrophils, etc. Correlation enrichment analysis showed that we obtained 50 available experimentally determined BZW1-binding proteins and 100 targeted genes related to BZW1, and the intersection genes were eukaryotic translation termination factor 1 and Guanine nucleotide binding protein, alpha inhibiting activity polypeptide 3. Moreover, there was a positive correlation between BZW1 and eukaryotic translation termination factor 1 and Guanine nucleotide binding protein, alpha inhibiting activity polypeptide 3 genes in pancreatic cancer. Gene ontology enrichment analysis showed BZW1 was mainly related to biological processes such as "mRNA processing," "RNA splicing," "regulation of translational initiation," and "activation of innate immune response." The results of Kyoto Encyclopedia of Genes and Genomes pathway analysis further indicated that BZW1 may be involved in pancreatic carcinogenesis through the "spliceosome" and "ribosome." The BZW1 gene may be a potential immunotherapy target and a promising prognostic marker for pancreatic cancer.

A glycosylation-related signature predicts survival in pancreatic cancer.

Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models. The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature. Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines. This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.

Eukaryotic translation initiation factor 2α kinase 2 in pancreatic cancer: An approach towards managing clinical prognosis and molecular immunological characterization.

Most patients with pancreatic cancer are already in the late stages of the disease when they are diagnosed, and pancreatic cancer is a deadly disease with a poor prognosis. With the advancement of research, immunotherapy has become a new focus in the treatment of tumors. To the best of our knowledge, there is currently no reliable diagnostic or prognostic marker for pancreatic cancer; therefore, the present study investigated the potential of eukaryotic translation initiation factor 2α kinase 2 (EIF2AK2) as a predictive and diagnostic marker for pancreatic cancer. Immunohistochemical staining of clinical samples independently verified that EIF2AK2 expression was significantly higher in clinically operated pancreatic cancer tissues than in adjacent pancreatic tissues., and EIF2AK2 expression and differentially expressed genes (DEGs) were identified using downloadable RNA sequencing data from The Cancer Genome Atlas and Genomic Tumor Expression Atlas. In addition, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analyses and immune cell infiltration were used for functional enrichment analysis of EIF2AK2-associated DEGs. The clinical importance of EIF2AK2 was also determined using Kaplan-Meier survival, Cox regression and time-dependent survival receiver operating characteristic curve analyses, and a predictive nomogram model was generated. Finally, the functional role of EIF2AK2 was assessed in PANC-1 cells using a short hairpin RNA-EIF2AK2 knockdown approach, including CCK-8, wound healing assay, cell cycle and apoptosis assays. The findings suggested that EIF2AK2 may have potential as a diagnostic and prognostic biomarker for patients with pancreatic cancer. Furthermore, EIF2AK2 may provide a new therapeutic target for patients with pancreatic cancer.

T cells in pancreatic cancer stroma: Tryptophan metabolism plays an important role in immunoregulation.

Several studies have shown that the immune system is highly regulated by tryptophan metabolism, which serves as an immunomodulatory factor. The indoleamine 2,3-dioxygenase 1 (IDO1), as an intracellular enzyme that participates in metabolism of the essential amino acid tryptophan in the kynurenine pathway, is an independent prognostic marker for pancreatic cancer (PC). First, overexpression of IDO1 inhibits the maturation of dendritic cells and T-cell proliferation in the liver and spleen. Second, the high expression of kynurenine induces and activates the aryl hydrocarbon receptor, resulting in upregulated programmed cell death protein 1 expression. Third, the induction of IDO1 can lead to loss of the T helper 17 cell/regulatory T cell balance, mediated by the proximal tryptophan catabolite from IDO metabolism. In our study, we found that overexpression of IDO1 upregulated CD8+ T cells and reduced natural killer T cells in pancreatic carcinoma in mice. Hence, it may be essential to pay more attention to tryptophan metabolism in patients, especially those who are tolerant to immunotherapy for PC.

Abstract 378: Ferritin regulates oxaliplatin sensitivity and immunosuppression in pancreatic ductal adenocarcinoma

Abstract Oxaliplatin, a third-generation of platinum analog, has been used for the treatment of colorectal, gastric, and advanced pancreatic ductal adenocarcinoma (PDAC); however, its relatively high toxicity reduced its efficacy in clinical use. Recently, we found that organic cation transporter 2 (OCT2) expression is positively correlated to Oxaliplatin sensitivity in PDAC cells and better survival outcomes in PDAC patients with chemotherapy, suggesting that OCT2 level is important not only in predicting sensitivity to oxaliplatin but also in guiding dose adjustments to minimize toxicity. Here, we observed the significance of serum Ferritin as a prognostic marker for pancreatic cancer, and further identified Ferritin heavy chain (FTH1) down-regulated OCT2 level and reduced Oxaliplatin sensitivity of advanced PDAC cells in vitro and in vivo. Our study reveals the negative correlation between FTH1 and OCT2 levels in PDAC database analysis and reducing FTH1 expression with Deferasirox (DFX), which is an agent that has been widely used for patients with iron overload, reversed OCT2 expression and Oxaliplatin sensitization in metastatic PDAC cells. Additionally, we identified that exosomal Ferritin/FTH1 from PDAC cells may enhance M1-type to M2-type macrophage polarization to build up immunosuppression in the tumor microenvironment. Citation Format: Ching-Feng Chiu. Ferritin regulates oxaliplatin sensitivity and immunosuppression in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 378.

Circulating Tumor DNA Is an Accurate Diagnostic Tool and Strong Prognostic Marker in Pancreatic Cancer.

The objectives of the study are to investigate the sensitivity and specificity of circulating tumor DNA (ctDNA) for the diagnosis of pancreatic cancer and to assess the utility of ctDNA as a prognostic marker in this disease. Cell-free DNA was extracted from plasma of patients who underwent endoscopic ultrasound fine-needle aspiration or surgical resections for pancreatic cancer. The cell-free DNA was then analyzed using droplet digital polymerase chain reaction for KRAS G12/13 mutations. Eighty-one patients with pancreatic cancer and 30 patients with benign pancreatic disease were analyzed. ctDNA KRAS G12/13 mutations were detected in 63% of all patients with pancreatic cancer and in 76% of those patients who also had KRAS G12/13 mutations detected in the pancreatic primary. Specificity and tissue concordance were both 100%. Circulating tumor DNA corresponded with tumor size and stage, and high ctDNA was associated with significantly worse prognosis on both univariate and multivariate testing. Our study shows that ctDNA is an accurate diagnostic tool and strong prognostic marker in patients with pancreatic cancer. The continued investigation of ctDNA will enable its implementation in clinical practice to optimize the care and survival outcomes of patients with pancreatic cancer.

Quantification and Characterization of CTCs and Clusters in Pancreatic Cancer by Means of the Hough Transform Algorithm

Circulating Tumor Cells (CTCs) are considered a prognostic marker in pancreatic cancer. In this study we present a new approach for counting CTCs and CTC clusters in patients with pancreatic cancer using the IsofluxTM System with the Hough transform algorithm (Hough-IsofluxTM). The Hough-IsofluxTM approach is based on the counting of an array of pixels with a nucleus and cytokeratin expression excluding the CD45 signal. Total CTCs including free and CTC clusters were evaluated in healthy donor samples mixed with pancreatic cancer cells (PCCs) and in samples from patients with pancreatic ductal adenocarcinoma (PDAC). The IsofluxTM System with manual counting was used in a blinded manner by three technicians who used Manual-IsofluxTM as a reference. The accuracy of the Hough-IsofluxTM approach for detecting PCC based on counted events was 91.00% [84.50, 93.50] with a PCC recovery rate of 80.75 ± 16.41%. A high correlation between the Hough-IsofluxTM and Manual-IsofluxTM was observed for both free CTCs and for clusters in experimental PCC (R2 = 0.993 and R2 = 0.902 respectively). However, the correlation rate was better for free CTCs than for clusters in PDAC patient samples (R2 = 0.974 and R2 = 0.790 respectively). In conclusion, the Hough-IsofluxTM approach showed high accuracy for the detection of circulating pancreatic cancer cells. A better correlation rate was observed between Hough-IsofluxTM approach and with the Manual-IsofluxTM for isolated CTCs than for clusters in PDAC patient samples.

High level of ANO1 promotes pancreatic cancer growth in concert with oncogenic KRAS.

Anoctamin-1 (ANO1) was identified as an unfavorable prognostic marker in pancreatic cancer. However, the exact implication of ANO1 in pancreatic cancer is still poorly understood. Here we investigated the effect of ANO1 in pancreatic cancer progression under the context of oncogenic KRAS, aiming at finding a new therapeutic target. Knockdown and overexpression of oncogenic KRAS as well as ANO1 in PDAC cell lines were performed by lentivirus infection. Cell proliferation and migration assay, RNA seq analysis were performed in PDAC cells bearing different status of ANO1 and KRAS. In vivo mice model was used to investigate the xenograft tumor growth with different status of KRAS and ANO1. Our results showed that ANO1 expression level is elevated in poorly differentiated cancer cells. Overexpression of ANO1 in PDAC cancer cells was found to promote cancer cell proliferation in vitro and in vivo, which synergized with the introduction of oncogenic KRAS. Consistently, knockdown of ANO1 expression was found to suppress cancer growth in vitro and in vivo. RNA seq analysis revealed that the observed synergistic cancer-promoting effect from ANO1 and oncogenic KRAS is likely due to concurrent activating key genes involved in lipid metabolism including HMGCS1. The outcome from our study suggests that ANO1 plays an important role in promoting pancreatic cancer development, especially at the presence of oncogenic KRAS. Considering the prevalence of KRAS mutation in pancreatic cancer patients, suppression ANO1 may represent a potential effective therapeutic measure in pancreatic cancer treatment.

HPB P59 Is the lymph node ratio a relevant prognostic score neo-adjuvant chemotherapy for pancreatic cancer?

Abstract Background Lymph node ratio (LNR) is a strong prognostic marker in pancreatic cancer (PDAC). In recent years, use of neoadjuvant chemotherapy (NAT) has increased, where it is associated with a higher rate of N0 resections, compared with a surgery first approach. The prognostic accuracy of the LNR after NAT has not been assessed. Methods Retrospective review of prospectively collected data from 2008–2020 of all patients undergoing pancreaticoduodenectomy (PD) for PDAC. Basic demographics, pathological and clinical outcomes were analysed using standard statistical tests. Cox regression and Kaplan-Meier analyses were performed. Results Retrospective review of prospectively collected data from 2008–2020 of all patients undergoing pancreaticoduodenectomy (PD) for PDAC. Basic demographics, pathological and clinical outcomes were analysed using standard statistical tests. Cox regression and Kaplan-Meier analyses were performed. Conclusions NAT reduces the predictive accuracy of the LNR in resected pancreatic cancer; alternative prognostic models will require development.

Abstract B049: Comparison of keratin 17 and GATA6 as prognostic markers in pancreatic cancer

Abstract Background: Clinically and histologically identical pancreatic ductal adenocarcinomas (PDACs) differ in response to treatment, disease progression, and survival. Clinical trials are testing the use of either keratin 17 (K17) or GATA6 as surrogate prognostic and predictive biomarkers of PDAC. Still, there is a need to contrast their expression and prognostic value in the same cohort of cases. K17, a biomarker of the most aggressive subtype of PDAC, promotes tumor growth and chemoresistance. GATA6 is a transcription factor necessary for normal pancreatic development, and a surrogate marker of the classical subtype of PDAC, associated with longer-term survival. Our goal was to test the hypothesis that there is a reciprocal relationship between K17 and GATA6 expression and that their detection informs prognostic stratification. Methods: Stony Brook University Hospital PDAC patients were selected, and representative sections were processed for dual-staining by indirect immunoperoxidase methods using antibodies to K17 (KDx Diagnostics) and GATA6 (R&D Systems AF1700). Manual scoring of the proportion of cells with strong (2+) nuclear and/or cytoplasmic staining was determined for K17 versus nuclear staining for GATA6 (PathSQ). Automated image analysis of GATA6 expression was further scored using QuPath v0.3.2 on annotated PDAC sections. Cut-off values for the best COX model for each marker were established to stratify for survival. Results: K17 expression was observed in cancer epithelial cells and in few benign proliferative ducts of chronic pancreatitis but no staining was detected in stromal or acinar cells. By contrast, GATA6 was detected in the nuclei of most cancer epithelial cells and was also consistently detected in benign ductal cells, acinar cells, and stromal cells. Defining high K17 cases as those with staining in ≥10% of tumor cells, high K17 correlated with shorter overall survival (p=0.03), supporting its use as a negative prognostic biomarker. Due to the high level of expression of GATA6 in PDAC cells (range 60-100% of tumor cells across all cases), however, no threshold was found to provide prognostic value. By dual-color IHC, K17 positive cells almost always had strong GATA6 nuclear staining but GATA6 was also detected in all K17-negative tumor cells. Computational analysis demonstrated 98% concordance with manual scoring for high GATA6 and 90% concordance with manual scoring for low GATA6. Conclusions: GATA6 was expressed in most PDAC tumor cells, as well as in benign stromal and epithelial cells. However, K17 expression was focal, relatively tumor cell-specific, and was not detected in most benign cellular components. Although high K17 status identified cases with relatively short survival, a survival threshold for GATA6 could not be detected. Contradiction in our observations of GATA6 compared to previous reports could result from differences in case selection or immunohistochemical protocol. Thus, further work is needed to explore the relationship between K17 and GATA6 as complementary biomarkers of PDAC patient survival. Citation Format: Michael Horowitz, Lyanne Oblein, Jaymie Oentoro, Saumya Kasliwal, Natalia D. Marchenko, Luisa F. Escobar-Hoyos, Kenneth R. Shroyer. Comparison of keratin 17 and GATA6 as prognostic markers in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B049.

COL17A1 facilitates tumor growth and predicts poor prognosis in pancreatic cancer

ObjectiveThis study aimed to determine the role of COL17A1 in tumor progression and predict the prognosis of pancreatic cancer (PC). MethodsRNA-seq data from The Cancer Genome Atlas and Genotype-Tissue Expression were analyzed using bioinformatics methods. “Limma” package was used to screen differentially expressed genes (DEGs). Prognostic-associated data were further analyzed using univariate Cox regression and verified using the GSE28375 and GSE62452 datasets. Protein-protein interaction (PPI) network analysis was integrated to screen for hub genes. In vitro quantitative real-time PCR (qPCR) and western blotting were used to detect gene expression. The functional attributes of PC cells were verified by wound healing assays, migration and invasion assays, Cell Counting Kit 8 (CCK8), and 5-ethynyl-2′-deoxyuridine (EdU) assay. ResultsOn analyzing PC data, 4637 DEGs were identified. Of these, 2399 genes were upregulated and 2238 were downregulated. Through PPI network analysis, we identified that COL17A1 expression was highly correlated with poor prognosis of patients with PC. Functional attribute assays in the in vitro study showed that COL17A1 knockdown inhibited PC cell proliferation, migration, and invasion. ConclusionsAccording to our results, COL17A1 promotes PC cell proliferation, migration, and invasion mediated by the epithelial-mesenchymal transition (EMT) pathway. Thus, COL17A1 could be used as a prognostic marker in PC.

TMEM92 acts as an immune-resistance and prognostic marker in pancreatic cancer from the perspective of predictive, preventive, and personalized medicine.

Pancreatic cancer presents extremely poor prognosis due to the difficulty of early diagnosis, low resection rate, and high rates of recurrence and metastasis. Immune checkpoint blockades have been widely used in many cancer types but showed limited efficacy in pancreatic cancer. The current study aimed to evaluate the landscape of tumor microenvironment (TME) of pancreatic cancer and identify the potential markers of prognosis and immunotherapy efficacy which might contribute to improve the targeted therapy strategy and efficacy in pancreatic cancer in the context of predictive, preventive, and personalized medicine (PPPM). In the current study, a total of 382 pancreatic samples from the datasets of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were selected. LM22 gene signature matrix was applied to quantify the fraction of immune cells based on "CIBERSORT" algorithm. Weighted Gene Co-expression Network Analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm was applied to confirm the hub-network of immune-resistance phenotype. A nomogram model based on COX and Logistic regression was constructed to evaluate the prognostic value and the predictive value of hub-gene in immune-response. The role of transmembrane protein 92 (TMEM92) in regulating cell proliferation was evaluated by MTS assay. Western blot and Real-time PCR were applied to assess the biological effects of PD-L1 inhibition by TMEM92. Moreover, the effect of TMEM92 in immunotherapy was evaluated with PBMC co-culture and by MTS assay. Two tumor-infiltrating immune cell (TIIC) phenotypes were identified and a weighted gene co-expression network was constructed to confirm the 167 gene signatures correlated with immune-resistance TIIC subtype. TMEM92 was further identified as a core gene of 167 gene signature network based on MCODE algorithm. High TMEM92 expression was significantly correlated with unfavorable prognosis, characterizing by immune resistance. A nomogram model and external validation confirmed that TMEM92 was an independent prognostic factor in pancreatic cancer. An elevated tumor mutation burden (TMB), mostly is consistent with commonly mutations of KRAS and TP53, was found in the high TMEM92 group. The predictive role of TMEM92 in immunotherapeutic response was also confirmed by IMvigor210 datasets. In addition, the specific biological roles of TMEM92 in cancer was explored in vitro. The results showed that abnormal overexpression of TMEM92 was significantly associated with the poor survival rate of pancreatic cancer. Moreover, we demonstrated that TMEM92 inhibit tumour immune responses of the anti-PD-1 antibody with PBMC co-culture. The current study explored for the first time the immune-resistance phenotype of pancreatic cancer and identified TMEM92 as an innovative marker in predicting clinical outcomes and immunotherapeutic efficacy. These findings not only help to recognize high-risk and immune-resistance population which could be supplied targeted prevention, but also provide personalized medical services by intervening TMEM92 function to improve the prognosis of pancreatic cancer. In addition, the biological role of TMEM92 might reveal the potential molecular mechanisms of pancreatic cancer and lead to a novel sight for development of a PPPM approach for pancreatic cancer management. The online version contains supplementary material available at 10.1007/s13167-022-00287-0.

Prognostic value of Gustave Roussy immune score in operable pancreatic adenocarcinoma.

The Gustave Roussy immune score (GRIm score) is a laboratory index developed to predict survival in nonsmall cell lung cancer patients undergoing immunotherapy and has shown that the pretreatment value is an independent prognostic factor for survival. In this study, we aimed to determine prognostic significance of GRIm score for pancreatic adenocarcinoma that have not been determined in the literature for pancreatic cancer before. The reason for choosing this scoring is to show that the immune scoring system works as a prognostic marker in pancreatic cancer known as immune-desert tumor via immune properties of microenvironment. Medical records of patients with histologically confirmed pancreatic ductal adenocarcinoma, who were treated and followed up between December 2007 and July 2019 at our clinic, were reviewed retrospectively. GRIm scores of each patient were calculated at the time of diagnosis. Survival analysis were performed according to risk groups. A total of 138 patients were included in the study. While 111 (80.4%) patients were in the low-risk group; 27 (19.6%) were in high-risk group according to GRIm score. Median OS was 36.9 months (95% Confidence interval (CI): 25.42-48.56) in lower GRIm scores, and it was 11.1 months (95% CI: 6.83-15.44) in higher GRIm scores (P = 0.002). One-two-three-year OS rates were 85% versus 47%, 64% versus 39%, 53% versus 27% for low versus high GRIm scores, respectively. The multivariate analysis revealed that high GRIm score was an independent poor prognostic factor. GRIm can be used as a noninvasive, easily applicable, practical prognostic factor in pancreatic cancer patients.

Peripheral blood monocytes predict clinical prognosis and support tumor invasiveness through NF-κB-dependent upregulation of Snail in pancreatic cancer.

BackgroundThe tumor inflammatory microenvironment plays a vital role in the initiation and progression of pancreatic cancer (PC). Both the lymphocyte-to-monocyte ratio (LMR) and preoperative peripheral blood monocytes are related to the prognosis of PC patients. However, the direct effect of monocytes on PC cells is not fully understood. The current study aimed to assess the effect of monocytes on PC and explore its potential mechanism.MethodsThe cutoff value of peripheral blood monocytes was evaluated by the receiver operating characteristic (ROC) curve. Transwell migration and invasion assays were used to detect the mobility of PC cells. The cytokines derived from monocytes were measured by quantitative real-time polymerase chain reaction (qRT-PCR). Western blotting was utilized to assess the expression of epithelial-mesenchymal transition (EMT) related markers. The expression level of Snail in PC tissue was determined by immunohistochemical (IHC) staining.ResultsA high monocyte count was inversely correlated with lymph node status and 5-year overall survival in PC. The PC cells underwent a cellular morphology change and increased cell motility after coculture with THP-1 monocytes. The THP-1 monocytes secreted various proinflammatory cytokines, including tumor necrosis factor-α (TNF-α) and interleukin-1α (IL-1α), which activated the nuclear factor-κB (NF-κB) signaling pathway leading to the upregulation of Snail and thereby promoting the EMT of PC cells. The expression level of Snail correlated significantly with the density of peripheral blood monocytes, and their level status was significantly associated with 5-year overall survival.ConclusionsThese findings indicated that elevated monocytes counts were a poor prognostic marker in PC, and monocytes could directly induce the EMT process of PC cells by upregulating Snail expression through the NF-κB signaling pathway.

Simple prognostic markers for optimal treatment of patients with unresectable pancreatic cancer.

Most patients with pancreatic cancer are ineligible for curative resection at diagnosis, resulting in poor prognosis. This study aimed to evaluate the prognostic factors in patients with unresectable pancreatic cancer.We retrospectively collected clinical data from 196 patients with unresectable pancreatic cancer who received palliative chemotherapy (N = 153) or palliative care alone (N = 43) from January 2011 to December 2013. Patients’ background data and overall survival were analyzed using the Cox proportional hazard regression model.In patients receiving palliative chemotherapy (gemcitabine-based regimen, 88.2%) and palliative care alone, the median (range) ages were 68 (43–91) and 78 (53–90) years, and metastatic diseases were present in 80% (N = 123) and 86% (N = 37), respectively. Multivariate analysis in the palliative chemotherapy patients showed that liver metastasis (hazard ratio [HR] 2.25, 95% confidence interval [CI] 1.58–3.20, P < .001), neutrophil-to-lymphocyte ratio (>4.5 vs ≤4.5; HR 3.45, 95% CI 2.22–5.36, P < .001), and cancer antigen 19-9 (CA19-9) (≥900 vs <900 U/mL; HR 1.45, 95% CI 1.02–2.05, P = .036) were independent prognostic factors. In those receiving palliative care alone, lung (HR 3.27, 95% Cl 1.46-7.35, p = 0.004) and peritoneum (HR 2.50, 95% CI 1.20–5.18, P = .014) metastases and the C-reactive protein-to-albumin ratio (≥1.3 vs <1.3; HR 3.33, 95% Cl 1.51–7.35, P = .003) were independent prognostic factors. Furthermore, patients with multiple factors had worse prognosis in both groups. Median survival time of palliative chemotherapy patients with risk factors 0, 1, 2, and 3 were 13.1 (95% CI 8.0–16.9), 9.4 (95% CI 7.9–10.1), 6.6 (95% CI 4.9–7.8), and 2.5 (95% CI 1.7–4.0) months, respectively. Similarly, median survival time was 5.7 (95% CI 1.3 -8.0), 2.1 (95% CI 1.5–3.9), and 1.3 (95% CI 0.6–1.7) months, respectively, for palliative care alone patients with risk factor 0, 1, and 2 to 3.Prognostic markers for pancreatic cancer were neutrophil-to-lymphocyte ratio, liver metastasis, and CA19-9 in patients undergoing palliative chemotherapy and C-reactive protein-to-albumin ratio and lung/peritoneum metastases in patients undergoing palliative care alone. These simple markers should be considered when explaining the prognosis and therapeutic options to patients.

The Scavenger Receptor MARCO Expressed by Tumor-Associated Macrophages Are Highly Associated With Poor Pancreatic Cancer Prognosis.

Macrophage-targeting therapies have become attractive strategies for immunotherapy. Deficiency of MARCO significantly inhibits tumor progression and metastasis in murine models of pancreatic cancer. However, the role of MARCO in patients with pancreatic cancer remains unclear. In the present study, we analyzed tumor-associated macrophage (TAM)-related changes using the Cancer Genome Atlas database. We observed a significant enrichment of M2 macrophages in pancreatic cancer tissues. We found that several pro-tumor markers are increased in cancer tissues, including CD163, CD206, SIRPα, LILRB1, SIGLEC10, AXL, MERTK, and MARCO. Crucially, MARCO is highly or exclusively expressed in pancreatic cancer across many types of solid tumors, suggesting its significant role in pancreatic cancer. Next, we investigated the expression of MARCO in relation to the macrophage marker CD163 in a treatment-naïve pancreatic cancer cohort after surgery (n = 65). MARCO and CD163 were analyzed using immunohistochemistry. We observed increased expression of CD163 and MARCO in pancreatic cancer tissues compared with paracancerous tissues. Furthermore, we observed a large variation in CD163 and MARCO expression in pancreatic cancer tissues among cases, suggesting the heterogeneous expression of these two markers among patients. Correlation to clinical data indicated a strong trend toward worse survival for patients with high CD163 and MARCO macrophage infiltration. Moreover, high CD163 and MARCO expression negatively affected the disease-free survival and overall survival rates of patients with pancreatic cancer. Univariate and multivariate analysis revealed that CD163 and MARCO expression was an independent indicator of pancreatic cancer prognosis. In conclusion, high CD163 and MARCO expression in cancer tissues is a negative prognostic marker for pancreatic cancer after surgery. Furthermore, anti-MARCO may be a novel therapy that is worth studying in depth.