Comparative analysis of the mutational landscape and evolutionary patterns of pancreatic ductal adenocarcinoma metastases in the liver or peritoneum
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SUBMITTER: Yao G
PROVIDER: S-EPMC11336646 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
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Project description:PurposePancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease that can be separated into distinct subtypes based on molecular signatures. Identifying PDAC subtype-specific therapeutic vulnerabilities is necessary to develop precision medicine approaches to treat PDAC.Experimental designA total of 56 PDAC liver metastases were obtained from the UNMC Rapid Autopsy Program and analyzed with quantitative proteomics. PDAC subtypes were identified by principal component analysis based on protein expression profiling. Proteomic subtypes were further characterized by the associated clinical information, including but not limited to survival analysis, drug treatment response, and smoking and drinking status.ResultsOver 3,960 proteins were identified and used to delineate four distinct PDAC microenvironment subtypes: (i) metabolic; (ii) progenitor-like; (iii) proliferative; and (iv) inflammatory. PDAC risk factors of alcohol and tobacco consumption correlate with subtype classifications. Enhanced survival is observed in FOLFIRINOX treated metabolic and progenitor-like subtypes compared with the proliferative and inflammatory subtypes. In addition, TYMP, PDCD6IP, ERAP1, and STMN showed significant association with patient survival in a subtype-specific manner. Gemcitabine-induced alterations in the proteome identify proteins, such as serine hydroxymethyltransferase 1, associated with drug resistance.ConclusionsThese data demonstrate that proteomic analysis of clinical PDAC liver metastases can identify molecular signatures unique to disease subtypes and point to opportunities for therapeutic development to improve the treatment of PDAC.
| S-EPMC7056493 | biostudies-literature
Project description:BackgroundPatients with resectable (R) or borderline resectable (BR) pancreatic ductal adenocarcinoma (PDAC) sometimes show unexpected liver, peritoneal, and para-aortic lymph node metastases intraoperatively. Despite radical pancreatectomy, a nonnegligible number of patients relapse within 6 months after surgery. The aim of this study was to identify the preoperative predictors of occult metastases (OM), defined as intraoperative distant metastases or within 6 months after pancreatectomy.Materials and methodsThis study included patients with R and BR PDAC who underwent curative-intent pancreatectomy or staging laparoscopy between 2006 and 2021. Multivariate logistic regression and Cox hazard analyses were performed to identify the preoperative predictors of OM and to assess the impact of these factors on prognosis after pancreatectomy.ResultsOf the 279 patients, OM was observed intraoperatively in 47 and postoperatively in 34. In the OM group, there were no differences in prognosis between patients who had intraoperative metastases and recurrence within 6 months (median survival time [MST], 18.1 vs. 12.9 months), and between patients who underwent pancreatectomy and those who did not (MST, 13.9 vs. 18.1 months). Preoperative tumor size ≥22 mm (odds ratio [OR], 2.03; 95 % confidence interval [CI], 1.16-3.53; p = 0.013) and preoperative CA19-9 level ≥ 118.8 U/mL (OR, 2.64; 95 % CI, 1.22-5.73; p = 0.014) were significant predictors of OM. Additionally, positive OM predictors were strong independent prognostic factors for overall survival after pancreatectomy (hazard ratio, 2.47; 95 % CI, 1.54-3.98; p < 0.001).ConclusionMultidisciplinary treatment strategies should be considered for patients with predictors of OM to avoid inappropriate surgical interventions.
| S-EPMC11327574 | biostudies-literature
Project description:Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer that typically manifests itself at an advanced stage and does not respond to most treatment modalities. The survival rate of a PDAC patient is less than 5%, with a median survival of just a couple of months. A better understanding of the molecular pathology of PDAC is needed to guide research for the development of better clinical treatment modalities for PDAC patients. Gene expression studies performed to date have identified different subtypes of PDAC with prognostic and clinical relevance. Subtypes identified to date are highly heterogeneous since pancreatic cancer is heterogeneous cancer. Tumor microenvironment and stroma constitute a major chunk of PDAC and contribute to the heterogeneity. Better subtyping methods are need of the hour for better prognosis and classification of PDAC for future personalized treatment. In this work, we have performed an integrated analysis of DNA methylation and gene expression datasets to provide better mechanistic and molecular insights into Pancreatic cancers, especially PDAC. The use of varied and diverse datasets has provided valuable insights into different cancer types and can play an integral role in revealing the complex nature of underlying biological mechanisms. We performed subtyping of TCGA-PAAD gene expression and methylation datasets into different subtypes using state-of-the-art normalization methods and unsupervised clustering methods that reveal latent hidden factors, leading to additional insights for subtyping. Differential expression and differential methylation were performed for each of the subtypes obtained from clustering. Our analysis gave a consensus of five cluster solution with relevant pathways like MAPK, MET. The five subtypes corresponded to the tumor and stromal subtypes. This analysis helps in distinguishing and identifying different subtypes based on enriched putative genes. These results help propose novel experimentally-verifiable PDAC subtyping and demonstrate that using varied data sets and integrated methods can contribute to disease prognostication and precision medicine in PDAC treatment.
| S-EPMC7820567 | biostudies-literature
Project description:PurposeHypodensity of pancreatic ductal adenocarcinoma (PDAC) during contrast-enhanced computed tomography (CECT) examination is common, but a minority of PDAC patients exhibit hyperdense images. The present study examined the clinical characteristics and protein landscape of PDAC with hyperdensity.Materials and methodsA total of 844 pathologically confirmed PDAC patients who underwent CECT before surgery were included. During the parenchymal phase of CECT, patients were assigned to the hyperdense or hypodense group based on CT values. Clinical and CT characteristics for predicting relapse-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox proportional hazards model. The expression of the tumor angiogenesis marker CD31 and stroma-related protein CTHRC1 were analyzed using immunohistochemistry (IHC) assay to evaluate differences between the two groups. Proteomics was performed to compare the possible mechanisms underlying the differential enhancement on CT scans.ResultsBased on CECT, 43 and 801 PDAC patients had hyperdense and hypodense lesions, respectively. All 43 patients presented a hyperdense lesion in the parenchymal phase. The mean CECT values of the hyperdense group were higher than the hypodense group (102.5 ± 17.4 and 53.7 ± 18.7, respectively, P < 0.001). The hyperdense group had a better prognosis than the hypodense group (median RFS, 19.97 vs. 12.34 months, P = 0.0176; median OS, 33.6 vs. 20.3 months, P = 0.047). Multivariate analysis showed that age, higher CA19-9 levels (> 300 U/ml), tumor stage, tumor differentiation, tumor CT density, and adjuvant chemotherapy were significant independent prognostic factors for OS. CD31 immunohistochemical staining showed that the hyperdense PDACs had a higher microvessel density than the hypodense group (P < 0.001). CTHRC1 expression was higher in the hypodense group (P = 0.019). Sixty-eight differentially expressed proteins were found using the tandem mass tag labeling-based quantification of the proteomes of PDAC tissue samples, and 7 proteins (POFUT1, PKP2, P0DOX4, ITPR1, HBG2, IGLC3, SAA2) were related to angiogenesis.ConclusionPatients who presented with a hyperdense mass on CECT had a higher microvessel density and better prognosis. Anti-angiogenic therapy may be suitable for these patients.
| S-EPMC7947874 | biostudies-literature
Project description:Immunotherapy approaches for pancreatic ductal adenocarcinoma (PDAC) have met with limited success. It has been postulated that a low mutation load may lead to a paucity of T cells within the tumor microenvironment (TME). However, it is also possible that while neoantigens are present, an effective immune response cannot be generated due to an immune suppressive TME. To discern whether targetable neoantigens exist in PDAC, we performed a comprehensive study using genomic profiles of 221 PDAC cases extracted from public databases. Our findings reveal that: (a) nearly all PDAC samples harbor potentially targetable neoantigens; (b) T cells are present but generally show a reduced activation signature; and (c) markers of efficient antigen presentation are associated with a reduced signature of markers characterizing cytotoxic T cells. These findings suggest that despite the presence of tumor specific neoepitopes, T cell activation is actively suppressed in PDAC. Further, we identify iNOS as a potential mediator of immune suppression that might be actionable using pharmacological avenues.
| S-EPMC5071896 | biostudies-literature
Project description:Pancreatic cancer is one of the most fatal cancers and is associated with limited diagnostic and therapeutic modalities. Currently, gemcitabine is the only effective drug and represents the preferred first-line treatment for chemotherapy. However, a high level of intrinsic or acquired resistance of pancreatic cancer to gemcitabine can contribute to the failure of gemcitabine treatment. To investigate the underlying molecular mechanisms for gemcitabine resistance in pancreatic cancer, we performed label-free quantification of protein expression in intrinsic gemcitabine-resistant and - sensitive human pancreatic adenocarcinoma cell lines using our improved proteomic strategy, combined with filter-aided sample preparation, single-shot liquid chromatography-mass spectrometry, enhanced spectral counting, and a statistical method based on a power law global error model. We identified 1931 proteins and quantified 787 differentially expressed proteins in the BxPC3, PANC-1, and HPDE cell lines. Bioinformatics analysis identified 15 epithelial to mesenchymal transition (EMT) markers and 13 EMT-related proteins that were closely associated with drug resistance were differentially expressed. Interestingly, 8 of these proteins were involved in glutathione and cysteine/methionine metabolism. These results suggest that proteins related to the EMT and glutathione metabolism play important roles in the development of intrinsic gemcitabine resistance by pancreatic cancer cell lines.
| S-EPMC4275706 | biostudies-literature
Project description:CXCR2 has been suggested to have both tumor-promoting and tumor-suppressive properties. Here we show that CXCR2 signaling is upregulated in human pancreatic cancer, predominantly in neutrophil/myeloid-derived suppressor cells, but rarely in tumor cells. Genetic ablation or inhibition of CXCR2 abrogated metastasis, but only inhibition slowed tumorigenesis. Depletion of neutrophils/myeloid-derived suppressor cells also suppressed metastasis suggesting a key role for CXCR2 in establishing and maintaining the metastatic niche. Importantly, loss or inhibition of CXCR2 improved T cell entry, and combined inhibition of CXCR2 and PD1 in mice with established disease significantly extended survival. We show that CXCR2 signaling in the myeloid compartment can promote pancreatic tumorigenesis and is required for pancreatic cancer metastasis, making it an excellent therapeutic target.
| S-EPMC4912354 | biostudies-literature
Project description:Immune checkpoint therapy (ICT) has shown promising potential in the treatment of multiple solid tumors. However, the role of ICT in pancreatic ductal adenocarcinoma (PDAC) remains limited. Patterns of immune checkpoints (ICs) in PDAC represent the basis for establishing a potent ICT. The aim of this study is to create a profile of IC expression and its prognostic relevance in cancer cells of PDAC. Therefore, tumor cells from peripheral and central tissue microarray (TMA) spots from histologically confirmed PDAC of 68 patients after tumor resection were investigated in terms of expressions of TIM3, IDO, B7H4, LAG3, VISTA, and PD-L1 using immunohistochemistry. The presence of the respective ICs was compared to overall survival (OS). The presence of VISTA and PD-L1 significantly correlates with shorter OS (median OS: 22 months vs. 7 months and 22 months vs. 11 months, respectively, p < 0.05). For the presence of TIM3, IDO, B7H4, and LAG3, no difference in OS was observed (p > 0.05). The analysis of OS of combined subgroups for VISTA and PD-L1 (VISTA and PD-L1 neg., VISTA pos. and PD-L1 neg., VISTA neg. and PD-L1 pos., and VISTA and PD-L1 pos.) yielded overall statistical significance difference (p = 0.02). These results suggest that the presence of VISTA and PD-L1 is of prognostic relevance and potentially qualifies them as targets for ICT.
| S-EPMC9917344 | biostudies-literature
Project description:Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.
| S-EPMC9369872 | biostudies-literature
Project description:BackgroundWe have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.MethodsFor this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.ResultsThe updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.ConclusionsThe updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/ ) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.
| S-EPMC11550539 | biostudies-literature