A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer.

BACKGROUND: Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors. METHODS: Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively. RESULTS: A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression ("Stromal-UP" (SU) and "Stromal-DOWN" (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival. CONCLUSIONS: A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.

Prognostic value of midkine, syndecan-1, hyaluronan synthase-2, sestrin-1, laminin subunit alpha-4 and fibulin-3 for malignant pleural mesothelioma.

Introduction: The prognosis of malignant pleural mesothelioma (MPM) is poor, with a limited survival time. In this study, we aimed to examine expression levels of genes selected from relevant literature and to utilize in silico methods to determine genes whose expression could reflect the prognosis of patients with MPM by ex-vivo validation experiments. Material and methods: The study group consisted of 54 MPM patients treated with chemotherapy. Expression of 6 genes - midkine (MDK), syndecan-1 (SDC1), hyaluronan synthase-2 (HAS2), sestrin-1 (SESN1), laminin subunit alpha-4 (LAMA4), and fibulin-3 (FBLN3) - was examined by qPCR in tumor tissues. Sestrin-1 and LAMA4 were identified using an in house R-based script: Unsupervised Survival Analysis Tool. Midkine, SDC1, HAS2, and FBLN3 were selected from current literature. We used two housekeeping genes, i.e. glucose-6-phosphate dehydrogenase and TATA-box binding protein, as controls. Results: Of the patients, 43 (79.6%) had epithelioid mesothelioma. The median survival for all patients was 10 (±1.2 SE) months (95% CI: 7.7-12.3). In multivariate analyses, MDK (p = 0.007), HAS2 (p = 0.008) and SESN1 (p = 0.014) expression levels were related to survival time in the whole group. In epithelioid type MPM patients, MDK (p = 0.014), FBLN3 (p = 0.029), HAS2 (p = 0.014) and SESN1 (p = 0.045) expression was related to survival time in multivariate analyses. Conclusions: High HAS2 and SESN1 expressions and low MDK are potential biomarkers of good prognosis in MPM. High HAS2 and SESN1 expression and low MDK and FBLN3 can also be utilized as biomarkers of good prognosis for epithelioid MPM. Those results should be further investigated in sera, plasma, and pleural effusions.

A positive feedback loop driven by fibronectin and IL-1ß sustains the inflammatory microenvironment in breast cancer.

Inflammatory alterations of the extracellular matrix shape the tumor microenvironment and promote all stages of carcinogenesis. This study aims to determine the impact of cellular fibronectin on inflammatory facets of tumor-associated macrophages (TAMs) in breast cancer. Cellular fibronectin (FN) harboring the alternatively spliced extra domain A (FN-EDA) was determined to be a matrix component produced by the triple-negative breast cancer (TNBC) cells. High levels of FN-EDA correlated with poor survival in breast cancer patients. The proinflammatory cytokine IL-1ß enhanced the expression of cellular fibronectin including FN-EDA. TAMs were frequently observed in the tumor areas rich in FN-EDA. Conditioned media from TNBC cells induced the differentiation of CD206+CD163+ macrophages and stimulated the STAT3 pathway, ex vivo. In the macrophages, the STAT3 pathway enhanced FN-EDA-induced IL-1ß secretion and NF-κB signaling. In conclusion, our data indicate a self-reinforcing mechanism sustained by FN-EDA and IL-1ß through NF-κB and STAT3 signaling in TAMs which fosters an inflammatory environment in TNBC.

Transcriptomic Analysis of Hepatitis B Infected Liver for Prediction of Hepatocellular Carcinoma.

Hepatocellular cancer (HCC) is a leading cause of cancer-related mortality worldwide, and chronic hepatitis B virus infection (CHB) has been a major risk factor for HCC development. The pathogenesis of HBV-related HCC has been a major focus revealing the interplay of a multitude of intracellular signaling pathways, yet the precise mechanisms and their implementations to clinical practice remain to be elucidated. This study utilizes publicly available transcriptomic data from the livers of CHB patients in order to identify a population with a higher risk of malignant transformation. We report the identification of a novel list of genes (PCM1) which can generate clear transcriptomic sub-groups among HBV-infected livers. PCM1 includes genes related to cell cycle activity and liver cancer development. In addition, markers of inflammation, M1 macrophages and gamma delta T cell infiltration are present within the signature. Genes within PCM1 are also able to differentiate HCC from normal liver, and some genes within the signature are associated with poor prognosis of HCC at the mRNA level. The analysis of the immunohistochemical stainings validated that proteins coded by a group of PCM1 genes were overexpressed in liver cancer, while minimal or no expression was detected in normal liver. Altogether, our findings suggest that PCM1 can be developed into a clinically applicable method to identify CHB patients with a higher risk of HCC development.

CSRP1 expression is associated with a mesenchymal, stroma-rich tumor profile and poor prognosis in colon cancer.

Background/aim: Cysteine and glycine-rich protein 1 (CSRP1) is involved in the cysteine-rich protein family and is a marker of smooth muscle lineages. In colon cancer, the expression of this gene is associated with poor prognosis. In this study, the aim was to reevaluate its prognostic relationship in independent cohorts and explore potential underlying biological processes that are linked to aggressive behavior in tumors with high CSRP1 expression, such as epithelial-to-mesenchymal transition (EMT), stromal fractions in the tumor microenvironment, and consensus molecular subtypes (CMSs). Materials and methods: RNA sequencing (RNAseq)-, microarray-, and single-cell RNAseq (scRNAseq)-based transcriptomic data were obtained from public databases. The EMT score was calculated based on the expression of E-cadherin and vimentin genes using a previously published method. The stromal score generated by the ESTIMATE method was utilized for the analysis of correlation with the CSRP1 expression. The scRNAseq data were analyzed via the Seurat R package. The immunohistochemistry-based protein level expression of CSRP1 was evaluated using the Human Protein Atlas database. Results: Lower CSRP1 expression was noted in colon tumors compared to normal colon tissue. Patients with a high CSRP1 expression had shorter recurrence-free, overall, and disease-specific survivals in the GSE39582 and GSE17536 datasets (p < 0.05). The methylation level of the CSRP1 gene was negatively correlated (r = -0.57, p < 0.0001) with CSRP1 expression in The Cancer Genome Atlas colon adenocarcinoma dataset. CSRP1 expression was positively correlated with the expression of mesenchymal markers, EMT score, and stromal score obtained via the ESTIMATE method. CMS4 colon tumors had a significantly higher CSRP1 expression compared to other CMSs. Analysis of the scRNAseq data revealed that CSRP1 was expressed by epithelial cells and cancer-associated fibroblasts in the colorectal tumor microenvironment, which was also confirmed by the protein expression data from the Human Protein Atlas database. Conclusion: CSRP1 expression is associated with CMS4, a more mesenchymal stroma-rich molecular profile, and poor prognosis in colon cancer.

Gastric Carcinoma with Lymphoid Stroma: A Combination of Mismatch Repair Deficient Medullary Type and Epstein-Barr Virus-associated Gastric Carcinomas.

Gastric carcinomas consist of a heterogeneous group of neoplasms with broad cytological and architectural variations. Gastric carcinomas with lymphoid stroma show poor correlation between their histomorphology and biological behavior. This contrast causes a need for more detailed analysis and molecular exploration of lymphoid stroma-rich gastric carcinomas with medullary like features and lack of glandular differentiation. In this study, we performed a detailed retrospective analysis of 53 gastric carcinomas among 654 gastric tumors from surgical resection specimens, all of which had no prominent glandular differentiation. Morphological and clinical data were compared with immunohistochemistry (MLH1, PMS2, MSH2 and MSH6 for mismatch repair mechanism deficiency; CD2, CD8 and CD163 for immune infiltration; and PD-1, PD-L1, LMP-1, ERBB2 and ki-67) besides EBER in situ hybridization and molecular studies (PCR based microsatellite instability and BRAF V600E mutation analysis). Morphological, immunohistochemical and molecular findings lead us to classify lymphoid stroma-rich advanced gastric carcinomas (n = 40/53) into two distinct entities originating from two different pathogenetic pathway: one is gastric carcinomas revealing predominantly medullary type morphology with defective DNA mismatch repair mechanism (n = 30/53) and the other is EBV associated carcinomas (n = 10/53). In addition, we suggest that biomarker based classification algorithms besides morphological evaluation are necessary to identify these two entities. Distinguishing these entities is crucial to apply different treatment strategies, including alternative treatments such as immunotherapy.

Quality assurance: Evaluation and comparison of methods for electron microscopic measurement of GBM width and the effect of in-lab calibration in diagnostic renal pathology.

Replacing equipment and software can improve efficiency and allow updates to laboratory procedures, but has the potential to introduce changes in established values for a laboratory. Replacement of an electron microscope (EM), fitted with an updated digital camera, and use of new software for imaging and analysis prompted this QA study to ensure that new equipment, imaging, and measurement of the glomerular basement membrane (GBM) produced data consistent with the laboratory's established range of normal width. GBM measurements from 14 randomly selected human renal biopsies were compared using five different approaches. Original measurements of GBMs obtained on the laboratory's previous EM were compared to images collected on the new microscope with measurements performed using new software, as well as the original images and the new images measured using a separate software method as a control. The widths obtained by five approaches were compared to each other. While measurements showed minor variability between the approaches, significant difference in GBM width was noted in three of the paired comparisons. In some cases, these differences suggested slight diagnostic changes. Evaluation of new equipment, software, and techniques is important for a laboratory's quality assurance. While new equipment and/or procedures can introduce errors in test outcomes, we found that different EMs, cameras, and software made slight differences in our laboratory's values for kidney GBM width. However, a few cases showed enough difference in GBM width to suggest a change in diagnosis, illustrating the necessity of calibration adjustments in the setting of new equipment and software.

DNA Methylation of PI3K/AKT Pathway-Related Genes Predicts Outcome in Patients with Pancreatic Cancer: A Comprehensive Bioinformatics-Based Study.

Pancreatic cancer (PCA) is one of the most lethal malignancies worldwide with a 5-year survival rate of 9%. Despite the advances in the field, the need for an earlier detection and effective therapies is paramount. PCA high heterogeneity suggests that epigenetic alterations play a key role in tumour development. However, only few epigenetic biomarkers or therapeutic targets have been identified so far. Here we explored the potential of distinct DNA methylation signatures as biomarkers for early detection and prognosis of PCA. PI3K/AKT-related genes differentially expressed in PCA were identified using the Pancreatic Expression Database (n = 153). Methylation data from PCA patients was obtained from The Cancer Genome Atlas (n = 183), crossed with clinical data to evaluate the biomarker potential of the epigenetic signatures identified and validated in independent cohorts. The majority of selected genes presented higher expression and hypomethylation in tumour tissue. The methylation signatures of specific genes in the PI3K/AKT pathway could distinguish normal from malignant tissue at initial disease stages with AUC > 0.8, revealing their potential as PCA diagnostic tools. ITGA4, SFN, ITGA2, and PIK3R1 methylation levels could be independent prognostic indicators of patients' survival. Methylation status of SFN and PIK3R1 were also associated with disease recurrence. Our study reveals that the methylation levels of PIK3/AKT genes involved in PCA could be used to diagnose and predict patients' clinical outcome with high sensitivity and specificity. These results provide new evidence of the potential of epigenetic alterations as biomarkers for disease screening and management and highlight possible therapeutic targets.

Epithelial-to-Mesenchymal Transition Is Not a Major Modulating Factor in the Cytotoxic Response to Natural Products in Cancer Cell Lines.

Numerous natural products exhibit antiproliferative activity against cancer cells by modulating various biological pathways. In this study, we investigated the potential use of eight natural compounds (apigenin, curcumin, epigallocatechin gallate, fisetin, forskolin, procyanidin B2, resveratrol, urolithin A) and two repurposed agents (fulvestrant and metformin) as chemotherapy enhancers and mesenchymal-to-epithelial (MET) inducers of cancer cells. Screening of these compounds in various colon, breast, and pancreatic cancer cell lines revealed anti-cancer activity for all compounds, with curcumin being the most effective among these in all cell lines. Although some of the natural products were able to induce MET in some cancer cell lines, the MET induction was not related to increased synergy with either 5-FU, irinotecan, gemcitabine, or gefitinib. When synergy was observed, for example with curcumin and irinotecan, this was unrelated to MET induction, as assessed by changes in E-cadherin and vimentin expression. Our results show that MET induction is compound and cell line specific, and that MET is not necessarily related to enhanced chemosensitivity.

Renin angiotensin system genes are biomarkers for personalized treatment of acute myeloid leukemia with Doxorubicin as well as etoposide.

Despite the availability of various treatment protocols, response to therapy in patients with Acute Myeloid Leukemia (AML) remains largely unpredictable. Transcriptomic profiling studies have thus far revealed the presence of molecular subtypes of AML that are not accounted for by standard clinical parameters or by routinely used biomarkers. Such molecular subtypes of AML are predicted to vary in response to chemotherapy or targeted therapy. The Renin-Angiotensin System (RAS) is an important group of proteins that play a critical role in regulating blood pressure, vascular resistance and fluid/electrolyte balance. RAS pathway genes are also known to be present locally in tissues such as the bone marrow, where they play an important role in leukemic hematopoiesis. In this study, we asked if the RAS genes could be utilized to predict drug responses in patients with AML. We show that the combined in silico analysis of up to five RAS genes can reliably predict sensitivity to Doxorubicin as well as Etoposide in AML. The same genes could also predict sensitivity to Doxorubicin when tested in vitro. Additionally, gene set enrichment analysis revealed enrichment of TNF-alpha and type-I IFN response genes among sensitive, and TGF-beta and fibronectin related genes in resistant cancer cells. However, this does not seem to reflect an epithelial to mesenchymal transition per se. We also identified that RAS genes can stratify patients with AML into subtypes with distinct prognosis. Together, our results demonstrate that genes present in RAS are biomarkers for drug sensitivity and the prognostication of AML.

Evaluation of an aldo-keto reductase gene signature with prognostic significance in colon cancer via activation of epithelial to mesenchymal transition and the p70S6K pathway.

AKR1B1 and AKR1B10, members of the aldo-keto reductase family of enzymes that participate in the polyol pathway of aldehyde metabolism, are aberrantly expressed in colon cancer. We previously showed that high expression of AKR1B1 (AKR1B1HIGH) was associated with enhanced motility, inflammation and poor clinical outcome in colon cancer patients. Using publicly available datasets and ex vivo gene expression analysis (n = 51, Ankara cohort), we have validated our previous in silico finding that AKR1B1HIGH was associated with worse overall survival (OS) compared with patients with low expression of AKR1B1 (AKR1B1LOW) samples. A combined signature of AKR1B1HIGH and AKR1B10LOW was significantly associated with worse recurrence-free survival (RFS) in microsatellite stable (MSS) patients and in patients with distal colon tumors as well as a higher mesenchymal signature when compared with AKR1B1LOW/AKR1B10HIGH tumors. When the patients were stratified according to consensus molecular subtypes (CMS), AKR1B1HIGH/AKR1B10LOW samples were primarily classified as CMS4 with predominantly mesenchymal characteristics while AKR1B1LOW/AKR1B10HIGH samples were primarily classified as CMS3 which is associated with metabolic deregulation. Reverse Phase Protein Array carried out using protein samples from the Ankara cohort indicated that AKR1B1HIGH/AKR1B10LOW tumors showed aberrant activation of metabolic pathways. Western blot analysis of AKR1B1HIGH/AKR1B10LOW colon cancer cell lines also suggested aberrant activation of nutrient-sensing pathways. Collectively, our data suggest that the AKR1B1HIGH/AKR1B10LOW signature may be predictive of poor prognosis, aberrant activation of metabolic pathways, and can be considered as a novel biomarker for colon cancer prognostication.

A novel 20-gene prognostic score in pancreatic adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Known risk factors for this disease are currently insufficient in predicting mortality. In order to better prognosticate patients with PDAC, we identified 20 genes by utilizing publically available high-throughput transcriptomic data from GEO, TCGA and ICGC which are associated with overall survival and event-free survival. A score generated based on the expression matrix of these genes was validated in two independent cohorts. We find that this "Pancreatic cancer prognostic score 20 -PPS20" is independent of the confounding factors in multivariate analyses, is dramatically elevated in metastatic tissue compared to primary tumor, and is higher in primary tumors compared to normal pancreatic tissue. Transcriptomic analyses show that tumors with low PPS20 have overall more immune cell infiltration and a higher CD8 T cell/Treg ratio when compared to those with high PPS20. Analyses of proteomic data from TCGA PAAD indicated higher levels of Cyclin B1, RAD51, EGFR and a lower E-cadherin/Fibronectin ratio in tumors with high PPS20. The PPS20 score defines not only prognostic and biological sub-groups but can predict response to targeted therapy as well. Overall, PPS20 is a stronger and more robust transcriptomic signature when compared to similar, previously published gene lists.