Adenocarcinoma Samples Research Articles

An Innovative Approach to Tissue Processing and Cell Sorting of Fixed Cells for Subsequent Single-Cell RNA Sequencing.

Although single-cell RNA sequencing (scRNA-seq) is currently the gold standard for the analysis of cell-specific expression profiles, the options for processing, staining, and preserving fresh cells remain very limited. Immediate and correct tissue processing is a critical determinant of scRNA-seq success. One major limitation is the restricted compatibility of fixation approaches, which must not destabilize or alter antibody labeling or RNA content or interfere with cell integrity. An additional limitation is the availability of expensive, high-demand cell-sorting equipment to exclude debris and dead or unwanted cells before proceeding with sample sequencing. The goal of this study was to develop a method that allows cells to be fixed and stored prior to FACS sorting for scRNA-seq without compromising the quality of the results. Finally, the challenge of preserving as many living cells as possible during tissue processing is another crucial issue addressed in this study. Our study focused on pancreatic ductal adenocarcinoma samples, where the number of live cells is rather limited, as in many other tumor tissues. Harsh tissue dissociation methods and sample preparation for analysis can negatively affect cell viability. Using the murine pancreatic cancer model Pan02, we evaluated the semi-automated mechanical/enzymatic digestion of solid tumors by gentleMACS Dissociator and compared it with mechanical dissociation of the same tissue. Moreover, we investigated a type of cell fixation that is successful in preserving cell RNA integrity yet compatible with FACS and subsequent scRNA-sequencing. Our protocol allows tissue to be dissociated and stained in one day and proceeds to cell sorting and scRNA-seq later, which is a great advantage for processing clinical patient material.

Ionizing Radiation Promotes Epithelial-Mesenchymal Transition Phenotype and Stem Cell Marker in The Lung adenocarcinoma: In Vitro and Bioinformatic Studiesc.

Objective Ionizing radiation (IR) is one of the major therapeutic approaches in the non-small cell lung cancer (NSCLC); however, it can paradoxically result in cancer progression likely through promoting epithelial-mesenchymal transition (EMT) and the cancer stem cell phenotype. Therefore, we aimed to determine whether IR promote EMT/CSC and to investigate the clinical relevance of EMT/CSC hallmark genes. Materials and Methods In this experimental and bioinformatic study, A549 cell line was irradiated with a high dosage (6 Gy) or a fractionated regimen (2 Gy/day for 15 fractions). The EMT-related features, including cellular morphology, migratory and invasive capacities were evaluated using scratch assay and transwell migration/invasion assays. The mRNA levels of EMT-related genes (CDH1, CDH2, SNAI1 and TWIST1), stemness-related markers (CD44, PROM1, and ALDH1A1) and the CDH2/CDH1 ratio were evaluated via real-time polymerase chain reaction (PCR). The clinical significance of these genes was assessed in the lung adenocarcinoma (LUAD) samples using online databases. Results Irradiation resulted in a dramatic elongation of cell shape and enhanced invasion and migration capabilities. These EMT-like alterations were accompanied with enhanced levels of SNAI1, CDH2, TWIST1, CD44, PROM1, and ALDH1A1 as well as an enhanced CDH2/CDH1 ratio. TCGA analysis revealed that, TWIST1, CDH1, PROM1 and CDH2 were upregulated; whereas, CD44, SNAI1 and ALDH1A1 were downregulated. Additionally, correlations between SNAI1-TWIST1, CDH2- TWIST1, CDH2-SNAI1, and ALDH1A1-PROM1 was positive. Kaplan-Meier survival analysis identified lower expression of CDH1, PROM1 and ALDH1A1 and increased expression of CDH2, SNAI1, and TWIST1 as well as CDH2/CDH1 ratio predict overall survival. Additionally, downregulation of ALDH1A1 and upregulation of CDH2, SNAI1 and TWIST1 could predict a shorter first progression. ConclusionAltogether, these findings demonstrated that IR promotes EMT phenotype and stem cell markers in A549 cell line and these genes could function as diagnostic or prognostic indicators in LUAD samples.

Mechanism of Key Ingredient of Astragalus membranaceus on Lung Adenocarcinoma via PI3K/AKT Signaling Clarified by Utilizing Network Pharmacology Approach and Experimental Validation.

To investigate the mechanism of the effect of Astragalus membranaceus (A. membranaceus) on lung adenocarcinoma at the molecular level to elucidate the specific targets according to the network pharmacology approach. The active components of A. membranaceus and their potential targets were collected from the Traditional Chinese Medicine Systems Pharmacology Database. Lung adenocarcinoma-associated genes were acquired based on GeneCards, Online Mendelian Inheritance in Man (OMIM), PharmGKB, and Therapeutic Targets databases. The PI3K/AKT signaling pathway-related genes were obtained using Reactome portal. Networks of "ingredient-target" and "ingredient-target-pathway-disease" were constructed using the Cytoscape3.6.0 software. The relationships among targets were analyzed according protein-protein interaction (PPI) network. Finally, molecular docking was applied to construct the binding conformation between active ingredients and core targets. Cell counting kit 8 (CCK8) and Western blot assays were performed to determine the mechanism of the key ingredient of A. membranaceus. A total of 20 active components and their 329 targets, and 7,501 lung adenocarcinoma-related genes and 130 PI3K/AKT signaling pathway-related genes were obtained. According to Venn diagram and PPI network analysis, 2 mainly active ingredients, including kaempferol and quercetin, and 6 core targets, including TP53, MAPK1, EGF, AKT1, ERBB2, and EGFR, were identified. The two important active ingredients of A. membranaceus, kaempferol and quercetin, exert the therapeutic effect in lung adenocarcinoma partly by acting on the 6 core targets (TP53, MAPK1, EGF, AKT1, ERBB2, and EGFR) of PI3K/AKT signaling pathway. Expressions of potential targets in lung adenocarcinoma and normal samples were analyzed by using UALCAN portal and found that ERBB2 was overexpressed in lung adenocarcinoma tissues and upregulation of it correlated with clinicopathological characteristics. Finally, quercetin repressed viabilities of lung adenocarcinoma cells by targeting ERBB2 on PI3K/AKT signaling confirmed by CCK8 and Western blot. Our finding unraveled that an active ingredient of A. membranaceus, quercetin, significantly inhibited the lung adenocarcinoma cells proliferation by repressing ERBB2 level and inactivating the PI3K/AKT signaling pathway.

Screening and Biological Function Analysis of miRNA and mRNA Related to Lung Adenocarcinoma Based on Bioinformatics Technology.

Objective To screen the differentially expressed miRNAs (DEMs) and the differentially expressed gene mRNAs (DEGs) in lung adenocarcinoma (LUAD) from the TCGA database and to explore the relationship between miRNAs and the prognosis of lung adenocarcinoma and their biological functions. Methods The RNA-seq and miRNA-seq data of lung adenocarcinoma samples were downloaded from the TCGA database for analysis, and the R program was used to screen for differentially expressed miRNAs and mRNAs. Then, the molecular functions, biological processes, cellular components, and signaling pathways involved in the occurrence and development of LUAD were analyzed using the functional accumulation analysis software of GSEA. The relationship between the integrated differentially expressed RNAs was analyzed by miRcode, TargetScan, and miRTarbase databases, and the miRNA-mRNA network was constructed. Result A total of 516 differentially expressed miRNAs and 5464 differentially expressed mRNAs were identified in LUAD. The GSEA enrichment analysis showed that miRNAs and mRNAs were mainly enriched in extracellular structure organization, external encapsulating structure organization, extracellular matrix organization, and gated channel activity. They were mainly involved in neuroactive ligand-receptor interaction signaling pathway. Some miRNAs and mRNAs in clustering modules were found to be associated with the prognosis of LUAD. Four targeting networks consisting of 22 miRNAs and 531 mRNAs were constructed. Conclusion The miRNA and mRNA related to the prognosis of LUAD were screened out, which provided a valuable preliminary basis for the follow-upin-depth clinical research and basic experimental research of LUAD.

Development and validation of a prognosis prediction model based on 18 endoplasmic reticulum stress-related genes for patients with lung adenocarcinoma.

BackgroundEndoplasmic reticulum (ER) stress had a crucial impact on cell survival, proliferation, and metastasis in various cancers. However, the role of ER stress in lung adenocarcinoma remains unclear.MethodGene expression and clinical data of lung adenocarcinoma (LUAD) samples were extracted from The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. ER stress score (ERSS) was constructed based on hub genes selected from 799 ER stress-related genes by least absolute shrinkage and selection operator (LASSO) regression. A Cox regression model, integrating ERSS and the TNM stage, was developed to predict overall survival (OS) in TCGA cohort and was validated in GEO cohorts. Gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA), and gene mutation analyses were performed to further understand the molecular features of ERSS. The tumor immune infiltration was evaluated by ESTIMATE, CIBERSORT, and xCell algorithms. The receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the risk model. p< 0.05 was considered statistically significant.ResultsOne hundred fifty-seven differentially expressed genes (DEGs) were identified between tumor and para-carcinoma tissues, and 45 of them significantly correlated with OS. Next, we identified 18 hub genes and constructed ERSS by LASSO regression. Multivariate analysis demonstrated that higher ERSS (p< 0.0001, hazard ratio (HR) = 3.8, 95%CI: 2.8–5.2) and TNM stage (p< 0.0001, HR = 1.55, 95%CI: 1.34–1.8) were independent predictors for worse OS. The prediction model integrating ERSS and TNM stage performed well in TCGA cohort (area under the curve (AUC) at five years = 0.748) and three GEO cohorts (AUC at 5 years = 0.658, 0.717, and 0.739). Pathway enrichment analysis showed that ERSS significantly correlated with unfolded protein response. Meanwhile, pathways associated with the cell cycle, growth, and metabolism were significantly enriched in the high ERSS group. Patients with SMARCA4, TP53, and EGFR mutations showed significantly higher ERSS (p = 4e−04, 0.0027, and 0.035, respectively). Tissues with high ERSS exhibited significantly higher infiltration of M1 macrophages, activated dendritic cells, and lower infiltration of CD8+ T cells and B cells, which indicate an activated tumor antigen-presenting but suppressive immune response status.ConclusionWe developed and validated an ER stress-related risk model that exhibited great predictive value for OS in patients with LUAD. Our work also expanded the understanding of the role of ER stress in LUAD.

Development and validation of a competing risk model for second primary pancreatic ductal adenocarcinoma: A population-based study.

BackgroundWith advances in early diagnosis and treatment, the number of cancer survivors continues to grow, and more and more cancer survivors face the threat of second primary cancer (SPM). Second primary pancreatic ductal adenocarcinoma (spPDAC) is an important subclass of SPM, but its prognostic characteristics are poorly understood.MethodsA total of 5,439 spPDAC samples and 67,262 primary pancreatic ductal adenocarcinoma (pPDAC) samples were extracted from the SEER database for this study. Survival differences between spPDAC and pPDAC samples were compared using Kaplan–Meier curves and log-rank tests. The Fine and Gray proportional subdistributed hazard method was used to analyze potential associations between clinical variables and pancreatic ductal adenocarcinoma-specific death (PDACSD) and death from other causes. After that, the clinical variables significantly related to PDACSD were screened out to construct a competing risk nomogram, which was used to evaluate the probability of the occurrence of PDACSD. The C-index was used to evaluate the discriminative ability of the model. The area under the curve (AUC) was used to verify the discrimination of the model. The calibration curve was used to verify the calibration of the model. Decision curve analysis (DCA) was used to validate the clinical utility of the model.ResultsCompared with patients with spPDAC, the pPDAC sample had a better prognosis (p = 0.0017). Across all spPDAC samples, the three most common sites of first-present cancer were the prostate, breast, and digestive system. Age (p < 0.001), race (p = 0.006), interval (p = 0.016), location (p < 0.001), T stage (p = 0.003), M stage (p < 0.001), chemotherapy (p < 0.001), and radiotherapy (p = 0.006) were the clinical variables associated with PDACSD screened by multivariate competing risks analysis. The concordance index values for the training and validation sets were 0.665 (95% CI, 0.655, 0.675) and 0.666 (95% CI, 0.650, 0.682), respectively. AUC, calibration curve, and DCA indicated that the model we constructed had good discrimination, calibration, and clinical utility.ConclusionsIn conclusion, we first analyzed the impact of previous cancer history on prognosis. We then constructed a competing risk model that can predict the probability of developing PDACSD in spPDAC. This model has good discriminative ability, calibration, and clinical practicability and has certain guiding value for clinical decision-making.

Upregulation of nuclear division cycle 80 contributes to therapeutic resistance via the promotion of autophagy-related protein-7-dependent autophagy in lung cancer.

Lung cancer remains the leading cause of malignant mortality worldwide. Hence, the discovery of novel targets that can improve therapeutic effects in lung cancer patients is an urgent need. In this study, we screened differentially expressed genes using isobaric tags for relative and absolute quantitation (iTRAQ) analysis and datasets from the cancer genome atlas database, and found that nuclear division cycle 80 (NDC80) might act as a novel prognostic indicator of lung cancer. The expression of NDC80 was significantly increased in lung cancer tissues, as compared to normal tissues, and high expression levels of NDC80 were correlated with unfavorable survival rates. Furthermore, an in vitro analysis showed that the stable knockdown of NDC80 decreased the cell viability and increased therapeutic sensitivity in two lung cancer cell lines, A549-IRR and H1246-IRR. Moreover, gene set enrichment analysis results showed that NDC80 was enriched in autophagy-related pathways. The downregulation of NDC80 inhibited the formation of autophagosomes, and reduced the expression of autophagy-related proteins such as LC3II, Beclin-1, and p62 in lung cancer cells. To further clarify the role of NDC80 as a downstream regulator of autophagy, we validated autophagic mediators through iTRAQ analysis and real-time polymerase chain reaction arrays. Autophagy-related protein7 (ATG7) was observed to be downregulated after the knockdown of NDC80 in lung cancer cells. Immunohistochemistry assay results revealed that both NDC80 and ATG7 were upregulated in an array of lung adenocarcinoma samples, compared to normal tissues, and the expression of NDC80 was identified to be positively associated with the levels of ATG7. Our findings suggest that NDC80 promotes the development of lung cancer by regulating autophagy, and might serve as a potential target for increasing the therapeutic sensitivity of lung cancer.

Phospholipase A/acyltransferase 4 is a prognostic biomarker and correlated with immune infiltrates in pancreatic cancer

BackgroundPhospholipase A/acyltransferase (PLAAT) family exhibits O- and N-acyltransferase activity and biosynthesize N-acylated ethanolamine phospholipids. Previously, PLAAT4 was seen as a tumor suppressor, but the exact function of PLAAT4 in pancreatic cancer was still unknown. In this study, we investigated the relationship of PLAAT4 and pancreatic cancer. MethodsUsing the data from the cancer genome atlas (TCGA), Genotype-Tissue Expression (GTEx) database and Gene Expression Omnibus (GEO) datasets we compared the expression of PLAAT4 in normal and tumor tissues and analyzed the connections between PLAAT4 and several clinicopathological factors. Further, we conducted Gene ontology (GO) analysis, Gene set enrichment analysis (GSEA), single sample gene set enrichment analysis (ssGSEA) and estimate analysis to explore the association between PLAAT4 and biological function and immune infiltration. In addition, Kaplan-Meier (KM) analysis, univariate and multivariate Cox analysis were used to explore the association between PLAAT4 and prognosis. In addition, we plotted a nomogram according to the multivariate cox analysis visualizing the predictive ability of PLAAT4 on prognosis. In addition, we explore the influence of PLAAT4 on malignant behaviors of the pancreatic cancer cells in vitro. ResultsAfter comparing the expression of PLAAT4 in normal and tumor tissues, we found that the expression of PLAAT4 was significantly high in pancreatic ductal adenocarcinoma (PDAC) samples. In addition, the results of GO and GSEA found that the expression of PLAAT4 was related to cell cycle checkpoints, M phase, regulation by p53, cell cycle mitotic and etc. Further, ssGSEA has shown that PLAAT4 was positively related to the abundance of aDC, Th1 cells, Th2 cells and negatively related to the Th17 cells. Subsequently, KM analysis, univariate and multivariate Cox analysis were used to analyze the correlation between PLAAT4 and prognosis. Additionally, we found that higher expression of PLAAT4 was related to T stage, N stage, histologic grade, etc (P < 0.05) and has a significant correlation with poor Overall Survival (OS), Disease-Specific Survival (DSS) and Progression-Free Interval (PFI). At last, we proved that PLAAT4 contributed to the malignant behaviors of the pancreatic cancer cells. ConclusionThis study indicated PLAAT4 as a novel prognostic biomarker and an important molecular that mediated immune response in pancreatic cancer.

TROP2 Represents a Negative Prognostic Factor in Colorectal Adenocarcinoma and Its Expression Is Associated with Features of Epithelial-Mesenchymal Transition and Invasiveness.

Simple SummaryColorectal cancer (CRC) is one of the most common cancers worldwide. While the systemic treatment of CRC is based on chemotherapy, subsequent therapeutic options are far less effective. Trophoblast cell surface antigen 2 (TROP2) is highly expressed in many carcinomas, including CRC, where its expression correlates with a poor prognosis. Anti-TROP2-targeted therapy was approved for the treatment of breast and urothelial carcinomas. We aimed to determine whether TROP2 is a suitable target for the treatment of CRC. We demonstrated that TROP2 expression in CRC correlates with lymph node metastasis and poor tumor differentiation. An analysis of mouse tumor models, patient-derived organoids, and tumor cells revealed that TROP2 expression is associated with features related to epithelial–mesenchymal transition and invasiveness. Our results suggest that TROP2 targeting may be a promising approach, especially in the early phase of treatment.Trophoblastic cell surface antigen 2 (TROP2) is a membrane glycoprotein overexpressed in many solid tumors with a poor prognosis, including intestinal neoplasms. In our study, we show that TROP2 is expressed in preneoplastic lesions, and its expression is maintained in most colorectal cancers (CRC). High TROP2 positivity correlated with lymph node metastases and poor tumor differentiation and was a negative prognostic factor. To investigate the role of TROP2 in intestinal tumors, we analyzed two mouse models with conditional disruption of the adenomatous polyposis coli (Apc) tumor-suppressor gene, human adenocarcinoma samples, patient-derived organoids, and TROP2-deficient tumor cells. We found that Trop2 is produced early after Apc inactivation and its expression is associated with the transcription of genes involved in epithelial–mesenchymal transition, the regulation of migration, invasiveness, and extracellular matrix remodeling. A functionally similar group of genes was also enriched in TROP2-positive cells from human CRC samples. To decipher the driving mechanism of TROP2 expression, we analyzed its promoter. In human cells, this promoter was activated by β-catenin and additionally by the Yes1-associated transcriptional regulator (YAP). The regulation of TROP2 expression by active YAP was verified by YAP knockdown in CRC cells. Our results suggest a possible link between aberrantly activated Wnt/β-catenin signaling, YAP, and TROP2 expression.

Low-cost and clinically applicable copy number profiling using repeat DNA

BackgroundSomatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell’s genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling.ResultsWe present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman’s rank correlation coefficient, rs=0.94) between conliga’s inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga’s hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information.ConclusionsWe show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data.

In the tumor microenvironment (TME), functional interactions among tumor, immune, and stromal cells and the extracellular matrix play key roles in tumor progression, invasion, immune modulation, and response to treatment. Intratumor heterogeneity is ubiquitous not only at the genetic and transcriptomic levels but also in the composition and characteristics of TME. However, quantitative inference on spatial heterogeneity in the TME is still limited. Here, we propose a framework to use network graph-based spatial statistical models on spatially annotated molecular data to gain insights into modularity and spatial heterogeneity in the TME. Applying the framework to spatial transcriptomics data from pancreatic ductal adenocarcinoma samples, we observed significant global and local spatially correlated patterns in the abundance score of tumor cells; in contrast, immune cell types showed dispersed patterns in the TME. Hypoxia, EMT, and inflammation signatures contributed to intra-tumor spatial variations. Spatial patterns in cell type abundance and pathway signatures in the TME potentially impact tumor growth dynamics and cancer hallmarks. Tumor biopsies are integral to the diagnosis and clinical management of cancer patients; our data suggest that owing to intra-tumor non-genetic spatial heterogeneity, individual biopsies may underappreciate the extent of clinically relevant, functional variations across geographic regions within tumors.

Cuproptosis predicts the risk and clinical outcomes of lung adenocarcinoma

Copper is an essential microelement for the body and a necessary coregulator for enzymatic reactions, yet an unbalanced copper level promotes reactive oxidation and cytotoxicity, which ultimately induces cell death. Several small molecules targeting copper-induced cell death have been investigated, yet few showed promising therapeutic effects in clinical trials. In March 2022, Science first introduced the concept and mechanisms of cuproptosis, suggesting that copper-induced cell death targets the tricarboxylic acid (TCA) cycle via protein lipoylation. Does this novel form of cell death take part in tumorigenesis or tumor progression? Is cuproptosis related to clinical outcomes of diseases? Is there a cuproptosis-related panel for clinical practice in cancer treatment? Herein, based on 942 samples of lung adenocarcinoma (LUAD), we analyzed on gene set level the existence and predictive value of cuproptosis in disease diagnosis and treatment. We screened out and identified the “cupLA” panel which indicates the risk of LUAD occurrence, clinicopathological features of LUAD patients, and could guide clinicians to refine LUAD subtypes and make treatment choices.

Upregulation of XIAP promotes lung adenocarcinoma brain metastasis by modulating ceRNA network.

Dysregulation of XIAP has been shown to affect the progression of a variety of cancers, including lung adenocarcinoma (LUAD). However, the function and mechanisms of XIAP in lung adenocarcinoma with brain metastasis (LUAD-BM) remains poorly understood. In this study, we analyzed the differential mRNA of 58 lung adenocarcinomas samples and 28 lung adenocarcinomas with brain metastases in GEO database. 191 differentially expressed mRNAs were significantly associated with immune response, the proliferation of the immune cell, cell-cell adhesion. Subsequent analyzed by lasso and SVM found that XIAP was significantly elevated in LUAD-BM and significantly associated with LUAD grade and metastasis. Then we constructed a molecular regulatory network of ncRNA-miRNA-mRNA ceRNA by Cystoscope based on the correlation obtained from Starbase. It was found that SBF2-AS1 or RUNDC3A-AS1, has-miR-338-3p and XIAP may have a regulatory relationship. Furthermore, we also initially found that XIAP was closely correlation with T cells, B cells, Mast cells, macrophages, and dendritic cells. In conclusion, we found that XIAP was significantly higher expressed in LUAD-BM compared with LUAD without brain metastasis, suggesting that XIAP may play an important role in the future prediction and clinical treatment of LUAD-BM.

Construction of a Pyroptosis-Related Genes Signature to Improve the Prognostic Prediction and Therapeutic Drugs Selection in Patients with Pancreatic Cancer.

BackgroundEffective prognostic assessment and appropriate drug selection are important for the clinical management of pancreatic cancer (PaC). Here, we aimed to establish a pyroptosis-associated genes (PRGs) signature to predict the prognostic outcomes of PaC and guide clinical drug therapy.MethodsWe identified the differentially expressed PRGs between pancreatic adenocarcinoma (n = 178) and control pancreas samples (n = 171) obtained from different databases, and performed Lasso and Cox regression analysis to create a prognosis signature. Kaplan–Meier (K-M) survival curves and time-dependent receiver operating characteristics were further constructed to assess the utility of the risk model. The International Cancer Genome Consortium (ICGC) PACA-AU cohort (n = 95) was used as a validation dataset to examine the validity of this prognostic model. The correlations of risk score (RS) with clinical features, immune cell infiltration, tumor mutation burden and half-maximal inhibitory concentrations (IC50) of chemotherapeutic drugs were analyzed, and the expression levels of PRGs in cell lines were detected.ResultsA prognostic signature was constructed, which consisted of 4 PRGs (AIM2, IL18, GSMDC and PLCG1). K-M analysis demonstrated a remarkable difference in overall survival (OS) time between low-risk (LR) and high-risk (HR) groups (P < 0.001). The RS contributed to the progression of PaC, and could be a significant independent factor for prognostic prediction. The validation of the ICGC cohort confirmed the effectiveness of the proposed signature. The patients with a HR score in the TCGA cohort had higher tumor mutation burden and more sensitivity to paclitaxel, gemcitabine, 5-fluorouracil and cisplatin than those with a LR score. The differential expression levels of signature genes were verified in vitro.ConclusionThe PRGs signature can be applied for predicting the prognosis of PaC, and may provide useful information for selection of therapeutic drugs.

Proteomic analysis of low- and high-grade human colon adenocarcinoma tissues and tissue-derived primary cell lines reveals unique biological functions of tumours and new protein biomarker candidates

BackgroundColon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.MethodsFour low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.ResultsA total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.ConclusionsThe differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.

Characterization of the Tumor Microenvironment and the Biological Processes with a Role in Prostatic Tumorigenesis.

Prostate intratumoral heterogeneity, driven by epithelial–mesenchymal plasticity, contributes to the limited treatment response, and it is therefore necessary to use the biomarkers to improve patient prognostic survival. We aimed to characterize the tumor microenvironment (T lymphocyte infiltration, intratumoral CD34, and KI-67 expressions) by immunohistochemistry methods and to study the biological mechanisms (cell cycle, cell proliferation by adhesion glycoproteins, cell apoptosis) involved in the evolution of the prostate tumor process by flow-cytometry techniques. Our results showed that proliferative activity (S-phase) revealed statistically significant lower values of prostate adenocarcinoma (PCa) and benign prostatic hyperplasia (BPH) reported at non-malignant adjacent cell samples (PCa 4.32 ± 4.91; BPH 2.35 ± 1.37 vs. C 10.23 ± 0.43, p < 0.01). Furthermore, 68% of BPH cases and 88% of patients with PCa had aneuploidy. Statistically increased values of cell proliferation (CD34+ CD61+) were observed in prostate adenocarcinoma and hyperplasia cases reported to non-malignant adjacent cell samples (PCa 28.79 ± 10.14; BPH 40.65 ± 11.88 vs. C 16.15 ± 2.58, p < 0.05). The CD42b+ cell population with a role in cell adhesion, and metastasis had a significantly increased value in PCa cases (38.39 ± 11.23) reported to controls (C 26.24 ± 0.62, p < 0.01). The intratumoral expression of CD34 showed a significantly increased pattern of PCa tissue samples reported to controls (PCa 26.12 ± 6.84 vs. C 1.50 ± 0.70, p < 0.01). Flow cytometric analysis of the cell cycle, apoptosis, and adhesion glycoproteins with a critical role in tumoral cell proliferation, T cell infiltrations, Ki-67, and CD 34 expressions by IHC methods are recommended as techniques for the efficient means of measurement for adenocarcinoma and hyperplasia prostate tissue samples and should be explored in the future.

Intratumoral Heterogeneity and Immune Modulation in Lung Adenocarcinoma in Female Smokers and Never Smokers.

Single-cell analysis of healthy lung tissue and lung cancer reveals distinct tumor cell populations, including cells with differential immune modulating capacity between smokers and never smokers, which could guide future therapeutic strategies.

DNA Methylation Profiling Identifies Subgroups of Lung Adenocarcinoma with Distinct Immune Cell Composition, DNA Methylation Age, and Clinical Outcome.

Lung adenocarcinoma (LUAD) is a clinically heterogeneous disease, which is highlighted by the unpredictable recurrence in low-stage tumors and highly variable responses observed in patients treated with immunotherapies, which cannot be explained by mutational profiles. DNA methylation-based classification and understanding of microenviromental heterogeneity may allow stratification into clinically relevant molecular subtypes of LUADs. We characterize the genome-wide DNA methylation landscape of 88 resected LUAD tumors. Exome sequencing focusing on a panel of cancer-related genes was used to genotype these adenocarcinoma samples. Bioinformatic and statistical tools, the immune cell composition, DNA methylation age (DNAm age), and DNA methylation clustering were used to identify clinically relevant subgroups. Deconvolution of DNA methylation data identified immunologically hot and cold subsets of LUADs. In addition, concurrent factors were analyzed that could affect the immune microenvironment, such as smoking history, ethnicity, or presence of KRAS or TP53 mutations. When the DNAm age was calculated, a lower DNAm age was correlated with the presence of a set of oncogenic drivers, poor overall survival, and specific immune cell populations. Unsupervised DNA methylation clustering identified six molecular subgroups of LUAD tumors with distinct clinical and microenvironmental characteristics. Our results demonstrate that DNA methylation signatures can stratify LUAD into clinically relevant subtypes, and thus such classification of LUAD at the time of resection may lead to better methods in predicting tumor recurrence and therapy responses.

Clinical and pathologic characteristics of gastric adenocarcinoma associated with Epstein-Barr virus in a region with a high incidence of gastric cancer in Colombia

Introduction and aimsEpstein-Barr virus (EBV) infection is an etiologic factor in EBV-associated gastric carcinoma (EBVaGC). The aim of our study was to describe the clinical and histopathologic characteristics of EBV infection in intestinal-type gastric adenocarcinoma samples. Material and methodsOf 180 paraffin-embedded gastrectomy samples, 28 were studied. Chromogenic in situ hybridization was performed to detect EBV. Sociodemographic and histopathologic data were obtained from the patients’ clinical histories. ResultsA total of 21.4% of the samples were positive for EBV. The predominant morphologic characteristic was the lace pattern, with dense inflammatory infiltration. Fifty percent of the EBVaGC+ patients were men, and the median age of the positive patients was 59 years (range: 50–75); 77.2% of the EBVaGC− patients were men, and the median age of the negative patients was 66 years (range: 34–89). Helicobacter pylori infection was associated with 10.7% of the EBVaGC+ patients and 53.6% of the EBVaGC− patients. In the EBVaGC+ patients, the cardia was the most frequent tumor location (17.9%), 7.1% had histologic grades 2 and 3, and 17.9% presented with Borrmann classification type III. In the EBVaGC− patients, the cardia and fundus were the most frequent tumor locations (71.4%), 35.7% had histologic grade 2, and 39.3% and 21.4% presented with Borrmann classification type III and IV, respectively. ConclusionsThe present study describes the clinical and histopathologic characteristics associated with EBVaGC positivity. Those data may aid in the selection of cases that are candidates for analysis through molecular methods aimed at identifying EBV infection in intestinal-type gastric adenocarcinoma.

Clinicopathological and prognostic significance of DNA mismatch-repair protein expression in gastric adenocarcinoma

Although the significance of DNA mismatch repair (MMR) protein expression in colorectal cancer is well-established, it remains contentious in extra-colorectal cancers and mainly in gastric adenocarcinoma. Data from Africa and Arab world remain limited. This study explored the MMR expression in gastric adenocarcinoma and evaluated its clinicopathological and prognostic signification among Tunisian patients. A retrospective study of 72 gastric adenocarcinomas was carried out. Clinicopathological particularities and patient outcomes were recorded. MMR expression was determined by immunohistochemistry on whole sections of archived material. Survival analysis was realized utilizing the Kaplan-Meier estimates and Log-Rank test. Expression of MMR proteins was observed in 84.7% of gastric adenocarcinoma samples. The 11 remaining samples (15.3%) exhibited an altered pattern of MMR protein. A significant association was identified between deficient MMR expression and advanced age (p = 0.03), intestinal type (p = 0.04) and lymph node metastases (p = 0.04). No other significant relationship was observed with the remaining selected tumor features. Patient survival was significantly associated with lymph node invasion (p = 0.002), distant metastases (p = 0.02) and tumor differentiation (p = 0.03), but not with MMR status (p = 0.83). MMR deficiency was related to advanced-age, intestinal type and nodal metastasis, but not to survival of Tunisian patients with gastric adenocarcinoma. Larger multicenter studies with additional molecular investigation are required to more explore these tumors.