Translational genomics in pancreatic ductal adenocarcinoma: A review with re-analysis of TCGA dataset

A pancreatic adenocarcinoma mimicking hepatoid carcinoma of uncertain histogenesis: A case report and literature review

In rare cases, metastatic adenocarcinomas of different origin may exhibit the features of hepatoid carcinoma (HC), a rare malignant epithelial tumor, most commonly occurring in the ovaries and stomach, as well as in the pancreas and biliary ducts. A case of a 72-year-old female patient who developed a highly aggressive, poorly differentiated pancreatic ductal adenocarcinoma with peritoneal carcinomatosis, demonstrating hepatoid differentiation upon conventional hematoxylin and eosin staining is reported in the present study. The patient presented with severe abdominal pain, and the radiological investigations performed revealed ovarian and hepatic tumor masses and peritoneal lesions, which were surgically removed. The gross examination of the peritoneum and omentum revealed multiple solid, firm, grey-white nodules, diffusely infiltrating the adipose tissue. The microscopic examination revealed a malignant epithelial proliferation, composed of polygonal cells with abundant eosinophilic cytoplasm and irregular, pleomorphic nuclei. Certain cells presented with intracytoplasmic mucus inclusions, raising suspicion of a HC with an uncertain histogenesis. Immunohistochemical staining was performed, and the tumor cells were found to be positive for cytokeratin (CK)7, CK18 and mucin 5AC, whereas negative staining for CK20, caudal-type homeobox transcription factor 2, α-fetoprotein, paired box gene 8, GATA-binding protein 3 and Wilms tumor 1 were documented. Thus, the diagnosis of metastatic pancreatic adenocarcinoma was established. The main aim of the present study was to provide further knowledge concerning poorly differentiated metastatic adenocarcinoma resembling HC, emphasizing the histopathological and immunohistochemical features of these malignant lesions and raising awareness of the diagnostic difficulties that may arise, as well as the importance of the use immunohistochemistry in differentiating carcinomas of uncertain histogenesis.

Pancreatic Cancer: Genetic Conditions and Epigenetic Alterations

BACKGROUND

Pancreatic cancer is a lethal proliferative disease driven by multiple genetic and epigenetic alterations. Microarrays and omics-based sequencing techniques are potent tools that have facilitated a broader understanding of the complex biological processes that drive pancreatic ductal adenocarcinoma (PDAC). In turn, these tools have resulted in the identification of novel disease markers, prognostic factors, and therapeutic targets. Herein, we provide a review of the genetic and epigenetic drivers of PDAC relative to recent discoveries that impact patient management.

METHODS

A review of PubMed, Medline, Clinical Key, and Index Medicus was conducted to identify literature from January 1995 to July 2022 that is related to PDAC genetics and epigenetics. Articles in Spanish and English were considered during selection.

RESULTS

Molecular, genetic, and epigenetic diagnostic tools, novel biomarkers, and promising therapeutic targets have emerged in the treatment of pancreatic cancer. The implementation of microarray technology and application of large omics-based data repositories have facilitated recent discoveries in PDAC. Multiple molecular analyses based on RNA interference have been instrumental in the identification of novel therapeutic targets for patients with PDAC. Moreover, microarrays and next-generation omics-based discoveries have been instrumental in the characterization of subtypes of pancreatic cancer, thereby improving prognostication and refining patient selection for available targeted therapies.

CONCLUSION

Advances in molecular biology, genetics, and epigenetics have ushered in a new era of discovery in the pathobiology of PDAC. Current efforts are underway to translate these findings into clinical tools and therapies to improve outcomes in patients with PDAC.

Deubiquitinase ubiquitin-specific peptidase 10 maintains cysteine rich angiogenic inducer 61 expression via Yes1 associated transcriptional regulator to augment immune escape and metastasis of pancreatic adenocarcinoma

Pancreatic adenocarcinoma (PAAD) remains an extremely fatal malignancy with a high mortality rate worldwide. This study focuses on the roles of ubiquitin-specific peptidase 10 (USP10) and cysteine rich angiogenic inducer 61 (Cyr61) in macrophage polarization, immune escape, and metastasis of PAAD. USP10 showed a positive correlation with Yes1 associated transcriptional regulator (YAP1), which, according to the TCGA-PAAD database, is highly expressed in PAAD and indicates poor patient prognosis. USP10 knockdown increased ubiquitination and degradation of YAP1, which further decreased the programmed cell death ligand 1 (PD-L1) and Galectin-9 expression, suppressed immune escape, and reduced the proliferation and metastasis of PAAD cells in vitro and in vivo. Cyr61, a downstream factor of YAP1, was overexpressed in PAAD cells after USP10 silencing for rescue experiments. Overexpression of Cyr61 restored the PD-L1 and Galectin-9 expression in cells and triggered M2 polarization of macrophages, which enhanced the immune escape and maintained the proliferation and metastasis ability of PAAD cells. In conclusion, this work demonstrates that USP10 inhibits YAP1 ubiquitination and degradation to promote Cyr61 expression, which induces immune escape and promotes growth and metastasis of PAAD.

RAD6 Positively Affects Tumorigenesis of Esophageal Squamous Cell Carcinoma by Regulating Histone Ubiquitination of CCNB1

Objective Esophageal carcinoma (ESCA) is deadly cancer worldwide with unknown etiology. This study aimed to investigate the impact and mechanism of RAD6 on the development of Esophageal squamous cell carcinoma (ESCC).

Expressions of RAD6A and RAD6B in ESCA were investigated from TCGA dataset and their expressions in tissue sample of ESCA patients and cells were determined. Functional experiments were conducted to explore the impact of RAD6A and RAD6B on malignant characteristics of several kinds of ESCC cells. Animal experiment was established and injected with RAD6A and RAD6B shRNA to evaluate the effect on tumor growth.

RAD6A and RAD6B were up-regulated in ESCC cells and tissues. Overexpressed RAD6A and RAD6B similarly increased ESCC cell proliferation, invasion and migration and silencing of RAD6 exerted opposite effects. Knockdown of RAD6A suppressed tumor growth and decreased the level of H2B, as data demonstrated positive correlation between RAD6A and CCNB1 in ESCC tissues.

Collectively, this study elucidates that RAD6 is up-regulated in ESCC and promotes the progression of ESCC through up-regulation of CCNB1 to enhance H2B ubiquitination. These evidence provide a novel insight into the pathogenesis of ESCC and might contribute to the development of targeted therapy.

Identification of an Immune-Related Signature for Predicting Prognosis in Patients With Pancreatic Ductal Adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the highest fatality rate cancers with poor survival rates. The tumor microenvironment (TME) is vital for tumor immune responses, leading to resistance to chemotherapy and poor prognosis of PDAC patients. This study aimed to provide a comprehensive evaluation of the immune genes and microenvironment in PDAC that might help in predicting prognosis and guiding clinical treatments.

METHODS

We developed a prognosis-associated immune signature (i.e., PAIS) based on immune-associated genes to predict the overall survival of patients with PDAC. The clinical significance and immune landscapes of the signature were comprehensively analyzed.

RESULTS

Owing to gene expression profiles from TCGA database, functional enrichment analysis revealed a significant difference in the immune response between PDAC and normal pancreas. Using transcriptome data analysis of a training set, we identified an immune signature represented by 5 genes (ESR2, IDO1, IL20RB, PPP3CA, and PLAU) related to the overall survival of patients with PDAC, significantly. This training set was well-validated in a test set. Our results indicated a clear association between a high-risk score and a very poor prognosis. Stratification analysis and multivariate Cox regression analysis revealed that PAIS was an important prognostic factor. We also found that the risk score was positively correlated with the inflammatory response, antigen-presenting process, and expression level of some immunosuppressive checkpoint molecules (e.g., CD73, PD-L1, CD80, and B7-H3). These results suggested that high-risk patients had a suppressed immune response. However, they could respond better to chemotherapy. In addition, PAIS was positively correlated with the infiltration of M2 macrophages in PDAC.

CONCLUSIONS

This study highlighted the relationship between the immune response and prognosis in PDAC and developed a clinically feasible signature that might serve as a powerful prognostic tool and help further optimize the cancer therapy paradigm.

Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types

Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer. By applying systems biology approaches, combined with machine learning analysis, we investigated possible frequently deregulated molecular mechanisms underlying the tumoral process. Our multi-approach analysis of 99 curated datasets, composed of 5,406 samples, revealed 47 differentially expressed genes in all analyzed cancer types, which were all in agreement with the validation using TCGA data. Results suggest that the tumoral process is more related to the overexpression of core deregulated machinery than the underexpression of a given gene set. Additionally, we identified gene expression similarities between different cancer types not described before and performed an overall survival analysis using 20 cancer types. Finally, we were able to suggest a core regulatory mechanism that could be frequently deregulated.

Identification of potential crucial genes associated with the pathogenesis and prognosis of pancreatic adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a type of malignant tumor with the highest mortality rate among all neoplasms worldwide, and its exact pathogenesis is still poorly understood. Timely diagnosis and treatment are of great importance in order to decrease the mortality rate of PAAD. Therefore, identifying new biomarkers for diagnosis and prognosis is essential to enable early detection of PAAD and to improve the overall survival (OS) rate. In order to screen and integrate differentially expressed genes (DEGs) between PAAD and normal tissues, a total of seven datasets were downloaded from the Gene Expression Omnibus database and the ‘limma’ and ‘robustrankggreg’ packages in R software were used. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery website, and the protein-protein interaction network analysis was performed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. A gene prognostic signature was constructed using the Cox regression model. A total of 10 genes (CDK1, CCNB1, CDC20, ASPM, UBE2C, TPX2, TOP2A, NUSAP1, KIF20A and DLGAP5) that may be associated with pancreatic adenocarcinoma were identified. According to the differentially expressed genes in The Cancer Genome Atlas, the present study set up four prognostic signatures (matrix metalloproteinase 12, sodium voltage-gated channel α subunit 11, tetraspanin 1 and SH3 domain and tetratricopeptide repeats-containing 2), which effectively predicted OS. The hub genes that were highly associated with the occurrence, development and prognosis of PAAD were identified, which may be helpful to further understand the molecular basis of pancreatic cancer and guide the synthesis of drugs for PPAD.

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.