Non-malignant Tissues Research Articles

Role of Periostin Expression in Non-Small Cell Lung Cancer: Periostin Silencing Inhibits the Migration and Invasion of Lung Cancer Cells via Regulation of MMP-2 Expression.

The involvement of periostin (POSTN) in non-small-cell lung cancer (NSCLC) migration, invasion, and its underlying mechanisms has not been well established. The present study aims to determine epithelial POSTN expression in NSCLC and to assess associations with clinicopathological factors and prognosis as well as to explore the effects of POSTN knockdown on tumor microenvironment and the migration and invasion of lung cancer cells. Immunohistochemistry was used to evaluate epithelial POSTN expression in NSCLC. POSTN mRNA expression in the dissected lung cancer cells was confirmed by laser capture microdissection and real-time PCR. A549 cells were used for transfecting shRNA-POSTN lentiviral particles. Wound healing and Transwell invasion assays were used to assess the migratory and invasive abilities of A549 cells transfected with POSTN-specific short hairpin (sh)RNA. The results demonstrated significantly higher cytoplasmic POSTN expression in the whole NSCLC group compared to non-malignant lung tissue (NMLT). POSTN expression in cancer cells may be considered to be an independent prognostic factor for survival in NSCLC. POSTN knockdown significantly inhibited A549 cell migration and invasion capabilities in vitro. The activity and the expression level of matrix metalloproteinase-2 (MMP-2) were significantly decreased in A549.shRNA compared to control cells. In summary, POSTN may regulate lung cancer cell invasiveness by modulating the expression of MMP-2 and may represent a potential target for novel therapeutic intervention for NSCLC.

Prevalence of Co-infection by Human Papillomavirus, Epstein- Barr Virus and Merkel Cell Polyomavirus in Iranian Oral Cavity Cancer and Pre-malignant Lesions.

Human papillomavirus (HPV) is recognized as the most important risk factor in oral cavity cancer and pre-malignant lesions; however, the etiological association of concomitant infection with other oncogenic viruses as a co-factor has not been definitively proven. The present study aimed to determine the prevalence of co-infection with HPV, Epstein-Barr virus (EBV) and Merkel Cell PolyomaVirus (MCPyV) in oral cavity lesions in Iranian patients. One hundred and fourteen oral cavity samples, including 33 oral squamous cell carcinoma, 28 oral lichen planus, 16 oral epithelial dysplasia and 37 oral irritation fibromas were analyzed for the HPV, EBV and MCPyV infection by quantitative real-time PCR. According to histological features 32.5% and 28.9% of cases were oral irritation fibroma and oral squamous cell carcinoma, respectively. Infection with at least two viruses was detected in 21.1% of patients. In this group, co-infection with HPV/EBV was identified in 37.5% of cases, HPV/MCPyV in 29.2%, EBV/MCPyV in 12.5%, and HPV/EBV/MCPyV in 20.8%. There was no statistically significant difference between multiple infections and anatomical locations of cancer. The prevalence of triple viral infection (HPV/EBV/MCPyV) in well differentiated tumors was higher than EBV or MCPyV single infection. This study revealed that co-infection of HPV, EBV and MCPyV can be detected in both malignant and non-malignant oral cavity tissues, and co-infection with all three viruses in well differentiated tumors can be shown as a synergistic hypothesis of the pathogenic role of these viruses in oral malignant transformation.

Comprehensive analysis reveals an arachidonic acid metabolism-related gene signature in patients with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is highly heterogeneous, making its prognosis prediction difficult. The arachidonic acid (AA) cascade is involved in carcinogenesis. Therefore, the metabolic enzymes of the AA cascade consist of lipoxygenases (LOXs), phospholipase A2s (PLA2s), and cyclooxygenases (COXs) along with their metabolic products, including leukotrienes. Nevertheless, the prognostic potential of AA metabolism-associated PDAC has not been explored. Herein, the mRNA expression patterns and the matching clinical information of individuals with PDAC were abstracted from online data resources. We employed the LASSO Cox regression model to develop a multigene clinical signature in the TCGA queue. The GEO queue and the ICGC queue were employed as the validation queue. There was differential expression of a significant number of AA metabolism-associated genes (56.8%) between PDAC and neighboring nonmalignant tissues in the TCGA queue. Univariate Cox regression demonstrated that 13 of the differentially expressed genes (DEGs) were linked to overall survival (OS) (p < 0.05). A 6-gene clinical signature was developed for stratifying the PDAC patients into two risk groups, with the high-risk group patients exhibiting remarkably lower OS than the low-risk group patients (p < 0.001 in the TCGA data set and the ICGC queue, and p = 0.001 in the GEO data set). The multivariate Cox data revealed the risk score as an independent OS predictor (HR > 1, p < 0.01). The receiver operating characteristic (ROC) curve verified the predictive potential of our signature. The expression and alteration of the six genes in PDAC were also validated using online databases. Functional analyses demonstrated that immune-linked cascades were enriched, and the immune status was remarkably different between the high- and low-risk groups. In summary, an AA metabolism-associated clinical gene signature can be applied for prognostic estimation in PDAC.

Expression of CXCR4 and CXCR7 in papillary thyroid carcinoma and adjacent tissues and their relationship with pathologic indicators of tumor aggressiveness

The receptors of chemokines play a significance role in the aggressiveness of tumor. CXCR4/CXCR7 promote metastasis of papillary thyroid carcinoma (PTC). This study examined the expresssion of chemokine receptors CXCR4/CXCR7 in human tissue specimens of PTC and peritumoral nonmalignant tissues. The correlation between CXCR4/CXCR7 and the clinicopathological factors in PTC was also determined. CXCR4/CXCR7 were examined in 115 PTC tissues from 115 patients using immunohistochemistry. Staining intensity was compared with patients and tumor characteristics including gender, age, tumor size, capsule invasion, multifocality, lymph node metastasis, and nature of paracancerous tissue. [Statistics: rank sum test, Spearman rank order correlation test; p < 0.05]. Higher expression rates of CXCR4/CXCR7 exhibited in PTC compared with peritumoral nonmalignant tissues. The expression of them was correlated in cancer and paracancerous specimens. A trend toward higher CXCR4/CXCR7 expression was found among tumors showing positive lymph nodes and capsule invasion, while no association with sex, age, tumor size, and nature of paracancerous tissue. Number of lymph nodes was associated with higher intensity IHC staining for CXCR4/CXCR7. Intense staining for CXCR4 was also associated with multifocality. Expression of CXCR4/CXCR7 by PTCs was correlated with lymph node metastasis and capsule invasion. Although multiple bias, they were thought to play a significance role in the aggressiveness of PTC, which provides potential targets for therapeutic interventions.

CNV Hotspots in Testicular Seminoma Tissue and Seminal Plasma.

Simple SummaryTesticular seminoma represents the most common type of testicular germ cell tumours, which are the most prevalent malignancies among the male population in reproductive age. Thus, it is crucial to find novel biomarkers for early detection and improve patient management. Copy number variation (CNV) is associated with various cancers including seminoma. Therefore, the current study aims to investigate CNV of specific genes and determine their potential as a possible seminoma biomarker. CNVs were investigated in genomic DNA from seminoma tissue, as well as in cell-free DNA (cfDNA) from seminal plasma as liquid biopsy. We detected increased CNVs in tissue samples, as well as in cfDNA from seminal plasma. According to obtained data, seminoma CNV hotspots are present and are reflected in seminal plasma. Although clinical value is yet to be determined, presented data emphasize a potential use of CNV as an SE biomarker.Seminoma (SE) is the most frequent type of testicular tumour, affecting predominantly young men. Early detection and diagnosis of SE could significantly improve life quality and reproductive health after diagnosis and treatment. Copy number variation (CNV) has already been associated with various cancers as well as SE. In this study, we selected four genes (MAGEC2, NANOG, RASSF1A, and KITLG) for CNV analysis in genomic DNA (gDNA), which are located on chromosomes susceptible to gains, and whose aberrant expression was already detected in SE. Furthermore, CNV was analysed in cell-free DNA (cfDNA) from seminal plasma. Analysis was performed by droplet digital polymerase chain reaction (ddPCR) on gDNA from SE and nonmalignant testicular tissue. Seminal plasma cfDNA from SE patients before and after surgery was analysed, as well as from healthy volunteers. The CNV hotspot in gDNA from SE tissue was detected for the first time in all analysed genes, and for two genes, NANOG and KITLG it was reflected in cfDNA from seminal plasma. Although clinical value is yet to be determined, presented data emphasize a potential use of CNV as a potential SE biomarker from a liquid biopsy.

Proteomic Profile Mapping and Differential Expression of Protein in Ovarian Cancer

This study aimed to characterize differentially expressed proteins in malignant ovarian tissue to find out potential novel biomarkers in ovarian cancer (OC). We enrolled 20 ovarian cancer patients (40-65 years) and an equal number of age-matched healthy women to get malignant and healthy ovarian tissue samples for protein extraction and quantification after tissue lysis. The protein profile was analyzed using two-dimensional gel electrophoresis followed by MALDI-TOF mass spectrometry. Based on the information thus obtained, the proteins were identified using the relevant software and protein databank to analyze the malignant and non-malignant ovarian tissue samples (n = 20/group). In this proteomic analysis of the ovarian tissue, 112 proteins were detected. Based on a minimum of ≥ 1.5-fold expression difference (p-value ≤ 0.05; FDR ≤ 0.05 and PMF ≥ 79), 17 proteins were found to be upregulated while 27 were downregulated in the malignant ovarian tissue. Six of these proteins have not been previously reported in ovarian cancer. Out of these, three are upregulated while the other three are downregulated. The upregulated proteins are centrosomal protein of 290 kDa (Cep290), uncharacterized protein C1orf109 (C1orf109) and GTPase-activating Rap/Ran-GAP domain-like protein 3 (GARNL3), and the three downregulated proteins identified are actin-related protein 3 (ARP3), cytosolic carboxypeptidase 3 (AGBL3) and NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10 (NDUFA10). This proteomic mapping not only provides data on protein profiling of ovarian cancer in Pakistani population for the first time but also reports six novel differentially expressed proteins, which have not been previously reported in ovarian cancer patients. They may serve as potential novel biomarkers after further validation for early diagnosis and prognosis of ovarian cancer. It also provides additional data to improve existing knowledge of already reported protein ovarian cancer biomarkers.

Comprehensive Metabolomics and Lipidomics Profiling of Prostate Cancer Tissue Reveals Metabolic Dysregulations Associated with Disease Development

Prostate cancer (PCa) is a global health problem that affects millions of men every year. In the past decade, metabolomics and related subareas, such as lipidomics, have demonstrated an enormous potential to identify novel mechanisms underlying PCa development and progression, providing a good basis for the development of new and more effective therapies and diagnostics. In this study, a multiplatform metabolomics and lipidomics approach, combining untargeted mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based techniques, was applied to PCa tissues to investigate dysregulations associated with PCa development, in a cohort of 40 patients submitted to radical prostatectomy for PCa. Results revealed significant alterations in the levels of 26 metabolites and 21 phospholipid species in PCa tissue compared with adjacent nonmalignant tissue, suggesting dysregulation in 13 metabolic pathways associated with PCa development. The most affected metabolic pathways were amino acid metabolism, nicotinate and nicotinamide metabolism, purine metabolism, and glycerophospholipid metabolism. A clear interconnection between metabolites and phospholipid species participating in these pathways was observed through correlation analysis. Overall, these dysregulations may reflect the reprogramming of metabolic responses to produce high levels of cellular building blocks required for rapid PCa cell proliferation.

Abstract PR-006: Integrative genomic characterization of therapeutic targets for pancreatic cancer

Abstract Targeted therapies for molecularly-defined subtypes have led to immense clinical benefit for many cancer types but have generally not been successful for pancreatic cancer. Given that the mainstay of treatment remains multi-agent chemotherapy with FOLFIRINOX or gemcitabine/nab-paclitaxel, there remains an urgent need to identify novel actionable vulnerabilities for subsets of PDAC patients. Toward this end, we conducted an integrative, genome-scale examination of genetic dependencies and cell surface targets for PDAC by leveraging CRISPR and RNAi screening data from The Cancer Dependency Map Project, genomic data of bulk patient tumors from The Cancer Genome Atlas, and custom single-nucleus RNA-seq of a 43-patient cohort comprised of untreated and treated specimens. Our results re-affirm the prominence of Ras/MAPK signaling and a synthetically-lethal interaction between VPS4A/B, but also reveal recurrent susceptibilities to genes within the fatty acid metabolism, vesicular transport and exocytosis, and nucleobase synthesis pathways that otherwise have minor to moderate depleting effects on the majority of cell lines. Aberrations in frequent tumor suppressor genes and chromosomal arm-level variations appear to modify the strength of dependencies, including that of KRAS, CCND1, and GPX4, and may serve as predictive biomarkers of response. In addition, we leveraged mRNA profiling of bulk primary tumors as well as metastatic organoid models to conduct a genome-wide search for cell surface targets that are highly-expressed in tumors while lowly or not expressed in other toxicity-prone, non-malignant tissues. These putative drug targets do not need to be cancer dependencies and can be compatible with antibody-based therapeutic strategies that leverage alternative modes of cellular toxicity. Our approach identifies MSLN, NECTIN4, TROP2, and other antigens which have previously been shown to be largely tumor-specific but also reveals the expression of multiple putative targets within the CEACAM, claudin, and tetraspanin families. Finally, molecular subtyping efforts over the past decade have yielded classical and basal-like as consensus subtypes with variations therein, but genetic dependencies and cell surface expression patterns unique to either are insufficiently understood. We identified CLDN18, CEACAM5, and CEACAM6 as cell surface antigens for the classical subtype and MSLN, AQP5, and SLC6A14 for basal-like. Dependency on TLK2 and CCND1 is associated with the basal-like and classical subtype, respectively. Taken together, our integrative genomic approach may provide a precision medicine blueprint for stratifying and targeting pancreatic cancer. Citation Format: Jimmy A. Guo, Daniel Zhao, Scott P. Ginebaugh, Steven Wang, Ananya D. Jambhale, Patrick Z. Yu, Westley W. Wu, Peter Chen, Maryann Zhao, Kristen E. Lowder, Kevin S. Kapner, Hannah I. Hoffman, Stephanie W. Cheng, Daniel Y. Kim, Rebecca Boiarsky, Francois Aguet, Brenton Paolella, John M. Krill-Burger, James M. McFarland, Tobiloba Oni, Tyler Jacks, Aviv Regev, Gad Getz, William L. Hwang, Harshabad Singh, Andrew J. Aguirre. Integrative genomic characterization of therapeutic targets for pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PR-006.

Diagnostic and Prognostic Value of Three microRNAs in Environmental Asbestiform Fibers-Associated Malignant Mesothelioma.

Fluoro-edenite (FE) is an asbestiform fiber identified in Biancavilla (Sicily, Italy). Environmental exposure to FE has been associated with a higher incidence of malignant mesothelioma (MM). The present study aimed to validate the predicted diagnostic significance of hsa-miR-323a-3p, hsa-miR-101-3p, and hsa-miR-20b-5p on a subset of MM patients exposed to FE and matched with healthy controls. For this purpose, MM tissues vs. nonmalignant pleura tissues were analyzed through droplet digital PCR (ddPCR) to evaluate differences in the expression levels of the selected miRNAs and their MM diagnostic potential. In addition, further computational analysis has been performed to establish the correlation of these miRNAs with the available online asbestos exposure data and clinic-pathological parameters to verify the potential role of these miRNAs as prognostic tools. ddPCR results showed that the three analyzed miRNAs were significantly down-regulated in MM cases vs. controls. Receiver operating characteristic (ROC) analysis revealed high specificity and sensitivity rates for both hsa-miR-323a-3p and hsa-miR-20b-5p, which thus acquire a diagnostic value for MM. In silico results showed a potential prognostic role of hsa-miR-101-3p due to a significant association of its higher expression and increased overall survival (OS) of MM patients.

Abstract PR-015: Cancer-associated fibroblasts sustain critical dependency of pancreatic cancer cells on exogenous lipids

Abstract Pancreatic ductal adenocarcinoma (PDAC) cells derive their resistance to therapy and aggressive clinical course from the symbiotic signaling and metabolic interactions with cancer-associated fibroblasts (CAFs). CAFs have been shown to provide to metabolically “parasitic” PDAC cells with water-soluble metabolites such as glucose and amino acids, or bulk protein via micropinocytosis. To meet the elevated demands for cellular membrane lipids, cancer cells rely on uptake of the exogenous lipids. However, the mechanism by which PDAC cells obtain water-insoluble essential lipids, such as cholesterol, remains poorly understood. Here, we define CAFs as a main source of lipids for PDAC cells by direct “feeding” of the CAF plasma membrane (PM) to cancer cells via heterotypic cellular contacts, a phenomenon known as trogocytosis. To gain insights into the mechanisms of regulation of CAF trogocytosis, we engineered cholesterol-auxotrophic human and mouse PDAC cells. In the absence of exogenously provided cholesterol, these cancer cells undergo apoptosis, which is completely rescued in CAF co-cultures. Using CRISPRi-mediated depletion in CAFs of select genes involved in cholesterol trafficking, membrane fusion and membrane protrusions, we found that CAFs deficient in CD81, TMEM16F, or ARF6 exhibited markedly reduced ability to support the viability of cholesterol-auxotrophic PDAC cells in lipid-poor media. As a promising therapy target, TMEM16F is a Ca2+-regulated scramblase increasing phosphatidylserine (PtdSer) on the outer leaflet of the PM. TMEM16F protein is highly expressed in human PDAC CAFs compared to fibroblasts isolated from the adjacent non-malignant pancreatic tissues. The TMEM16F-null CAFs are unable to sustain of cholesterol-auxotrophic PDAC cells in lipid-poor co-cultures. Our overall model is that, to initiate trogocytosis, PDAC cells release paracrine “feed me” signals activating Ca2+-dependent phospholipid scramblase TMEM16F. As the result, increased outward expression of PtdSer on CAF PM is a hallmark “eat me” signal that is recognized by the trogocytic PDAC cells. We conclude that trogocytosis is the critical metabolic dependency in PDAC, and nominated TMEM16F as a plausible PDAC therapy target. Re-purposing of clinically available TMEM16 inhibitors will make a tangible impact on treatment of PDAC patients in the near term. Citation Format: Charline Ogier, Alena Klochkova, Linara Gabitova, Battuya Bayarmagnai, Diana Restifo, Aizhan Surumbayeva, Janusz Franco-Barraza, Ralph Francescone, Debora B. Barbosa Vendramini-Costa, Jaye Gardiner, Emmanuelle Nicolas, Elizabeth A. Handorf, Kathy Q. Cai, Edna Cukierman, Igor Astsaturov. Cancer-associated fibroblasts sustain critical dependency of pancreatic cancer cells on exogenous lipids [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PR-015.

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.

Evidence for age-related contributions of DNA damage and epigenetics in brain tumorigenesis.

Glioblastoma (GBM) is a highly malignant primary brain tumour displaying rapid cell proliferation and infiltration. GBM primarily occurs at older age; however, younger populations have also been affected. In GBM and other cancers, genetic and epigenetic alterations promote tumorigenesis causing increased cell proliferation and invasiveness. This investigation explored epigenetic events as contributing factors, especially in gliomas that arise in patients aged 40-60years. Furthermore, DNA damage in tumours with respect to age was assessed. Archival fixed tissues from 88 cases of glioblastoma and adjacent non-malignant tissues were tested. Global methylation and DNA damage were measured using ELISA detection of 5-methyl cytosine and 8-hydroxy guanine, respectively. IDH mutations and CDKN2 promoter hypermethylation were analysed by pyrosequencing. Tumour tissue was hypomethylated compared with non-malignant tissue (P=.001), and there was a trend towards increased methylation with increasing age. There was a significant increase in DNA damage in patients older than forty years compared with those aged forty years or younger (P=.035). CDKN2 promoter methylation levels followed the age trends of global methylation in this patient group. Patients younger than 60 had more frequently mutated IDH (P=.004). Conclusions: The data support the potential of epigenetic factors in promoting tumorigenesis in younger patients, while increased DNA damage contributes to tumorigenesis in the older patients.

MiR-34a-5p suppresses colorectal cancer cell proliferation through silencing Microtubule Actin Crosslinking Factor 1 (MACF1) gene

BackgroundColorectal cancer (CRC) is the third most frequent cancer in both males and females. CRC results from multiple causes including genetic, epigenetic, and environmental insults. One of the newly identified oncogenes is the Microtubule Actin Crosslinking Factor 1 (MACF1) gene. MACF1 plays a critical role in colon cancer cell proliferation and progression through Wnt /β catenin pathway. Accordingly, we hypothesized that targeting MACF1 would affect CRC progression. Methodsbioinformatics analysis revealed that MACF1 is a target of miR-34a-5p. miR-34a-5p and MACF1 relative expression were measured in 40 colorectal cancers, 40 nonmalignant colon tissue samples using RT- qPCR. "CaCo2" cells line was transfected with miR-34a-5p mimic to assess the effect of MACF1 gene silencing on colorectal cell growth in vitro. ResultsmiR-34a-5p relative expression was significantly lowered in the colorectal cancer group than its expression in nonmalignant groups (P < 0.01). While MACF1 expression was significantly overexpressed in the colorectal cancer group as compared to the nonmalignant groups (P < 0.01). CaCo2 cells' proliferation significantly inhibited after transfection with miR-34a-5p mimic. This inhibited growth was associated with a significant decrease in MACF1 expression. ConclusionThese findings suggest that miR-34a-5p may inhibit colorectal cancer cell proliferation through downregulation of MACF1a member of Wnt/β catenin signaling. This study highlights the novel role of MACF1 as an indicative biomarker and therapeutic goal in colorectal cancer.

Prognostic Impact of Cytotoxic CD4 T Cells in Tumor Immune Microenvironment of Patients with Breast Cancer.

Prognostic Impact of Cytotoxic CD4 T Cells in Tumor Immune Microenvironment of Patients with Breast Cancer.

An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes.

Prostate cancer (PCa) in dogs is a highly malignant disease akin to its human counterpart. In contrast to the situation in humans, multi-gene approaches facilitating risk stratification of canine PCa are barely established. The aims of this study were the characterization of the transcriptional landscape of canine PCa and the identification of diagnostic, prognostic and/or therapeutic biomarkers through a multi-step screening approach. RNA-Sequencing of ten malignant tissues and fine-needle aspirations (FNA), and 14 nonmalignant tissues and FNAs was performed to find differentially expressed genes (DEGs) and deregulated pathways. The 4098 observed DEGs were involved in 49 pathways. These 49 pathways could be grouped into five superpathways summarizing the hallmarks of canine PCa: (i) inflammatory response and cytokines; (ii) regulation of the immune system and cell death; (iii) cell surface and PI3K signaling; (iv) cell cycle; and (v) phagosome and autophagy. Among the highly deregulated, moderately to strongly expressed DEGs that were members of one or more superpathways, 169 DEGs were listed in relevant databases and/or the literature and included members of the PCa pathway, oncogenes, prostate-specific genes, and druggable genes. These genes are novel and promising candidate diagnostic, prognostic and/or therapeutic canine PCa biomarkers.

Whole-exome sequencing identifies biosignatures that predict adverse survival outcomes in surgically treated patients with oral cavity squamous cell carcinoma

ObjectivesThe postoperative outcomes of patients with oral cavity squamous cell carcinoma (OCSCC) vary greatly. To improve risk stratification, we sought to identify genetic biosignatures by whole-exome sequencing (WES). Materials and MethodsWe retrieved patients with OCSCC patients with paired freshly frozen malignant and non-malignant tissue specimens and performed WES by Illumina HiSeq4000 platform. We further applied a tree-based method to analyze copy number variations and obtain signature classification and driver-gene identification. We further confirmed the prognostic impact of the WES biosignature in an external independent validation set. ResultsWe examined 168 paired samples from patients with surgically treated OCSCC. Similar to the literature, the most commonly mutated genes were TP53 (66%), FAT1 (32%), and NOTCH1 (24%). The signatures 13 (APOBEC Cytidine deaminase [C > G]), 1 (spontaneous deamination of 5-methylcytosine), and 7 (UV exposure) showed the highest concordance rates. Using the MutSigCV, MuSiC, 20/20+, OncodriveFML, e-Driver, OncodriveCLUST, and tree-based methods, we identified a nine-gene OCSCC panel (RYR1, HLA-B, TSHZ2, PCDH17, DNAH17, GRID1, SBNO2, KSR2, and GCN1L1) predicting survival outcomes in our sample. We used the TCGA database to validate the prognostic value of the panel independently. Furthermore, gene-gene covariance analysis confirmed the coexistence of several gene alterations. ConclusionWe identified and independently validated a WES biosignature that predicts outcomes in surgically treated OCSCC in Taiwan, a betel-quid-chewing-prevent area. We proposed that the panel might help clinical trial designation for adjuvant therapy based on the risk stratification from the novel gene panel and identify targets for liquid biopsy monitoring during surveillance.

Pelvic Lipomatosis: A Rare and Technically Demanding Benign Disease—Tips and Tricks for Robotic Management

Abstract Introduction and Objectives: Pelvic lipomatosis (PL) is a rare condition characterized by diffuse pelvic overgrowth of nonmalignant but infiltrative adipose tissue in perivesical and perir...

Predicting Malignancy of Biliary Stricture with a Nomogram in Patients with a Non-Malignant Endoscopic Tissue Diagnosis: A Retrospective Study.

PurposeThe accurate differentiation between benign and malignant biliary stricture is significant but challenging. Tissue diagnosis of biliary stricture by endoscopy sampling can provide excellent specificity but insufficient sensitivity. For patients with suspected malignant biliary stricture (MBS) but non-malignant was reported in endoscopy tissue samples, we constructed a nomogram to predict malignancy and improve the overall diagnostic performance.Patients and Methods232 patients with suspected MBS and underwent endoscopy tissue sampling from January 2017 to December 2019 were included, among which 123 patients’ endoscopy tissue samples were classified as non-malignant (including atypical, negative for malignancy, and nondiagnostic). Demographics, serum markers, radiological and sampling results of these 123 patients were collected to construct a nomogram using multivariate analysis.ResultsThe nomogram was developed based on bilirubin, CA19-9, radiological result, and atypical sampling results and provided an AUC of 0.863 (95% CI 0.795–0.930) for predicting MBS. The specificity, sensitivity, and accuracy of endoscopy tissue diagnosis were 100.00%, 59.90%, and 68.53%, respectively. With the nomogram added, the overall diagnosis specificity, sensitivity, and accuracy were 95.24%, 89.20%, and 90.23%, respectively.ConclusionThe nomogram can predict malignancy in patients whose endoscopy tissue diagnoses were non-malignant. The overall diagnostic performance was improved with the nomogram added.

The Evaluation of Methylated Septin 9 in Blood Plasma and Tissue Biopsies for the Early Detection for Asymptomatic Colon Cancer

The purpose of this study was to assess the utility of the SEPT9 genetic marker in the early detection of colon cancer patients. A case-control study was conducted on forty newly diagnosed colon cancer patients. The study was done between March 2019 and January 2020, patients from the Gastroenterology and Liver Education Hospital, Al-imamain Al-Kadhimain Medical City, and Baghdad Teaching Hospital were recruited. Colon cancer patients' mean age ± standard deviation was 54.4 ± 10.79 years while the age ± standard deviation of the mean of the control group was 55.1±8.54 years. For septin9 tissue methylation of the controls was done on the non-malignant tissues of the same patients.&#x0D; This study concluded that the percentage of Septin 9 (SEPT9) in the tissue of patients with colon cancer (CC) was the highest value, which is more significant than that of the serum of CC patients. Both of these groups were significantly higher than the percentage of SEPT9 methylation of control tissue and serum.&#x0D; Non-significant differences were obtained in the levels of CEA and CA19-9 between CC patients and controls.

Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets.

Cholangiocarcinoma is a form of hepatobiliary cancer with an abysmal prognosis. Despite advances in our understanding of cholangiocarcinoma pathophysiology and its genomic landscape, targeted therapies have not yet made a significant impact on its clinical management. The low response rates of targeted therapies in cholangiocarcinoma suggest that patient heterogeneity contributes to poor clinical outcome. Here we used mass spectrometry-based phosphoproteomics and computational methods to identify patient-specific drug targets in patient tumors and cholangiocarcinoma-derived cell lines. We analyzed 13 primary tumors of patients with cholangiocarcinoma with matched nonmalignant tissue and 7 different cholangiocarcinoma cell lines, leading to the identification and quantification of more than 13,000 phosphorylation sites. The phosphoproteomes of cholangiocarcinoma cell lines and patient tumors were significantly correlated. MEK1, KIT, ERK1/2, and several cyclin-dependent kinases were among the protein kinases most frequently showing increased activity in cholangiocarcinoma relative to nonmalignant tissue. Application of the Drug Ranking Using Machine Learning (DRUML) algorithm selected inhibitors of histone deacetylase (HDAC; belinostat and CAY10603) and PI3K pathway members as high-ranking therapies to use in primary cholangiocarcinoma. The accuracy of the computational drug rankings based on predicted responses was confirmed in cell-line models of cholangiocarcinoma. Together, this study uncovers frequently activated biochemical pathways in cholangiocarcinoma and provides a proof of concept for the application of computational methodology to rank drugs based on efficacy in individual patients. SIGNIFICANCE: Phosphoproteomic and computational analyses identify patient-specific drug targets in cholangiocarcinoma, supporting the potential of a machine learning method to predict personalized therapies.