Expression profile of COL2A1 and the pseudogene SLC6A10P predicts tumor recurrence in high-grade serous ovarian cancer

Data-driven energy landscape reveals critical genes in cancer progression

The evolution of cancer is a complex process characterized by stable states and transitions among them. Studying the dynamic evolution of cancer and revealing the mechanisms of cancer progression based on experimental data is an important topic. In this study, we aim to employ a data-driven energy landscape approach to analyze the dynamic evolution of cancer. We take Kidney renal clear cell carcinoma (KIRC) as an example. From the energy landscape, we introduce two quantitative indicators (transition probability and barrier height) to study critical shifts in KIRC cancer evolution, including cancer onset and progression, and identify critical genes involved in these transitions. Our results successfully identify crucial genes that either promote or inhibit these transition processes in KIRC. We also conduct a comprehensive biological function analysis on these genes, validating the accuracy and reliability of our predictions. This work has implications for discovering new biomarkers, drug targets, and cancer treatment strategies in KIRC.

Identification of gene profiles related to the development of oral cancer using a deep learning technique

BACKGROUND

Oral cancer (OC) is a debilitating disease that can affect the quality of life of these patients adversely. Oral premalignant lesion patients have a high risk of developing OC. Therefore, identifying robust survival subgroups among them may significantly improve patient therapy and care. This study aimed to identify prognostic biomarkers that predict the time-to-development of OC and survival stratification for patients using state-of-the-art machine learning and deep learning.

METHODS

Gene expression profiles (29,096 probes) related to 86 patients from the GSE26549 dataset from the GEO repository were used. An autoencoder deep learning neural network model was used to extract features. We also used a univariate Cox regression model to select significant features obtained from the deep learning method (P < 0.05). High-risk and low-risk groups were then identified using a hierarchical clustering technique based on 100 encoded features (the number of units of the encoding layer, i.e., bottleneck of the network) from autoencoder and selected by Cox proportional hazards model and a supervised random forest (RF) classifier was used to identify gene profiles related to subtypes of OC from the original 29,096 probes.

RESULTS

Among 100 encoded features extracted by autoencoder, seventy features were significantly related to time-to-OC-development, based on the univariate Cox model, which was used as the inputs for the clustering of patients. Two survival risk groups were identified (P value of log-rank test = 0.003) and were used as the labels for supervised classification. The overall accuracy of the RF classifier was 0.916 over the test set, yielded 21 top genes (FUT8-DDR2-ATM-CD247-ETS1-ZEB2-COL5A2-GMAP7-CDH1-COL11A2-COL3A1-AHR-COL2A1-CHORDC1-PTP4A3-COL1A2-CCR2-PDGFRB-COL1A1-FERMT2-PIK3CB) associated with time to developing OC, selected among the original 29,096 probes.

CONCLUSIONS

Using deep learning, our study identified prominent transcriptional biomarkers in determining high-risk patients for developing oral cancer, which may be prognostic as significant targets for OC therapy. The identified genes may serve as potential targets for oral cancer chemoprevention. Additional validation of these biomarkers in experimental prospective and retrospective studies will launch them in OC clinics.

Analysis of Breast Cancer Differences between China and Western Countries Based on Radiogenomics

Using radiogenomics methods, the differences between tumor imaging data and genetic data in Chinese and Western breast cancer (BC) patients were analyzed, and the correlation between phenotypic data and genetic data was explored. In this paper, we analyzed BC patients' image characteristics and transcriptome data separately, then correlated the magnetic resonance imaging (MRI) phenotype with the transcriptome data through a computational method to develop a radiogenomics feature. The data was fed into the designed random forest (RF) model, which used the area under the receiver operating curve (AUC) as the evaluation index. Next, we analyzed the hub genes in the differentially expressed genes (DEGs) and obtained seven hub genes, which may cause Chinese and Western BC patients to behave differently in the clinic. We demonstrated that combining relevant genetic data and imaging features could better classify Chinese and Western patients than using genes or imaging characteristics alone. The AUC values of 0.74, 0.81, and 0.95 were obtained separately using the image characteristics, DEGs, and radiogenomics features. We screened SYT4, GABRG2, CHGA, SLC6A17, NEUROG2, COL2A1, and MATN4 and found that these genes were positively or negatively correlated with certain imaging characteristics. In addition, we found that the SLC6A17, NEUROG2, CHGA, and MATN4 genes were associated with clinical features.

Targeting Ras-ERK cascade by bioactive natural products for potential treatment of cancer: an updated overview

MAPK (mitogen-activated protein kinase) or ERK (extracellular-signal-regulated kinase) pathway is an important link in the transition from extracellular signals to intracellular responses. Because of genetic and epigenetic changes, signaling cascades are altered in a variety of diseases, including cancer. Extant studies on the homeostatic and pathologic behavior of MAPK signaling have been conducted; however, much remains to be explored in preclinical and clinical research in terms of regulation and action models. MAPK has implications for cancer therapy response, more specifically in response to experimental MAPK suppression, compensatory mechanisms are activated. The current study investigates MAPK as a very complex cell signaling pathway that plays roles in cancer treatment response, cellular normal conduit maintenance, and compensatory pathway activation. Most MAPK inhibitors, unfortunately, cause resistance by activating compensatory feedback loops in tumor cells and tumor microenvironment components. As a result, innovative combinatorial treatments for cancer management must be applied to limit the likelihood of alternate pathway initiation as a possibility for generating novel therapeutics based on incorporation in translational research. We summarize current knowledge about the implications of ERK (MAPK) in cancer, as well as bioactive products from plants, microbial organisms or marine organisms, as well as the correlation with their chemical structures, which modulate this pathway for the treatment of different types of cancer.

PLK3 amplification and tumor immune microenvironment of metastatic tumors are linked to adjuvant treatment outcomes in uterine serous cancer

Uterine serous carcinoma (USC), an aggressive variant of endometrial cancer representing approximately 10% of endometrial cancer diagnoses, accounts for ∼39% of endometrial cancer-related deaths. We examined the role of genomic alterations in advanced-stage USC associated with outcome using paired primary-metastatic tumors (n = 29) treated with adjuvant platinum and taxane chemotherapy. Comparative genomic analysis of paired primary-metastatic patient tumors included whole exome sequencing and targeted gene expression. Both PLK3 amplification and the tumor immune microenvironment (TIME) in metastatic tumors were linked to time-to-recurrence (TTR) risk without any such association observed with primary tumors. TP53 loss was significantly more frequent in metastatic tumors of platinum-resistant versus platinum-sensitive patients and was also associated with increased recurrence and mortality risk. Increased levels of chr1 breakpoints in USC metastatic versus primary tumors co-occur with PLK3 amplification. PLK3 and the TIME are potential targets for improving outcomes in USC adjuvant therapy.

Multi-modal Profiling of the Extracellular Matrix of Human Fallopian Tubes and Serous Tubal Intraepithelial Carcinomas

Recent evidence supports the fimbriae of the fallopian tube as one origin site for high-grade serous ovarian cancer (HGSOC). The progression of many solid tumors is accompanied by changes in the microenvironment, including alterations of the extracellular matrix (ECM). Therefore, we sought to determine the ECM composition of the benign fallopian tube and changes associated with serous tubal intraepithelial carcinomas (STICs), precursors of HGSOC. The ECM composition of benign human fallopian tube was first defined from a meta-analysis of published proteomic datasets that identified 190 ECM proteins. We then conducted de novo proteomics using ECM enrichment and identified 88 proteins, 7 of which were not identified in prior studies (COL2A1, COL4A5, COL16A1, elastin, LAMA5, annexin A2, and PAI1). To enable future in vitro studies, we investigated the levels and localization of ECM components included in tissue-engineered models (type I, III, and IV collagens, fibronectin, laminin, versican, perlecan, and hyaluronic acid) using multispectral immunohistochemical staining of fimbriae from patients with benign conditions or STICs. Quantification revealed an increase in stromal fibronectin and a decrease in epithelial versican in STICs. Our results provide an in-depth picture of the ECM in the benign fallopian tube and identified ECM changes that accompany STIC formation. (J Histochem Cytochem XX: XXX-XXX, XXXX).

CAMSAP1 Mutation Correlates With Improved Prognosis in Small Cell Lung Cancer Patients Treated With Platinum-Based Chemotherapy

Platinum-based chemotherapy is the first-line treatment for small cell lung cancer (SCLC). However, due to patients developing a resistance to the drug, most experience relapse and their cancer can become untreatable. A large number of recent studies have found that platinum drug sensitivity of various cancers is affected by specific gene mutations, and so with this study, we attempted to find an effective genetic biomarker in SCLC patients that indicates their sensitivity to platinum-based drugs. To do this, we first analyzed whole exome sequencing (WES) and clinical data from two cohorts to find gene mutations related to the prognosis and to the platinum drug sensitivity of SCLC patients. The cohorts used were the Zhujiang cohort (N = 138) and the cohort reported by George et al. (N = 101). We then carried out gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to investigate possible molecular mechanisms through which these gene mutations affect patient prognosis and platinum drug sensitivity. We found that for SCLC patients, CAMSAP1 mutation can activate anti-tumor immunity, mediate tumor cell apoptosis, inhibit epithelial-mesenchymal transition (EMT), improve prognosis, and improve platinum drug sensitivity, suggesting that CAMSAP1 mutation may be a potential biomarker indicating platinum drug sensitivity and patient prognosis in SCLC.

The World of Pseudogenes: New Diagnostic and Therapeutic Targets in Cancers or Still Mystery Molecules?

Pseudogenes were once considered as “junk DNA”, due to loss of their functions as a result of the accumulation of mutations, such as frameshift and presence of premature stop-codons and relocation of genes to inactive heterochromatin regions of the genome. Pseudogenes are divided into two large groups, processed and unprocessed, according to their primary structure and origin. Only 10% of all pseudogenes are transcribed into RNAs and participate in the regulation of parental gene expression at both transcriptional and translational levels through senseRNA (sRNA) and antisense RNA (asRNA). In this review, about 150 pseudogenes in the different types of cancers were analyzed. Part of these pseudogenes seem to be useful in molecular diagnostics and can be detected in various types of biological material including tissue as well as biological fluids (liquid biopsy) using different detection methods. The number of pseudogenes, as well as their function in the human genome, is still unknown. However, thanks to the development of various technologies and bioinformatic tools, it was revealed so far that pseudogenes are involved in the development and progression of certain diseases, especially in cancer.

Tumor Microenvironmental Competitive Endogenous RNA Network and Immune Cells Act as Robust Prognostic Predictor of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is malignant hematologic tumors with frequent recurrence and cause high mortality. Its fate is determined by abnormal intracellular competitive endogenous RNA (ceRNA) network and extracellular tumor microenvironment (TME). This study aims to build a ceRNA network related to AML TME to explore new prognostic and therapeutic targets. The RNA expression data of AML were obtained from The Cancer Genome Atlas (TCGA) database. First, we used the ESTIMATE algorithm to calculate the immune cells and stromal cells infiltration scores in the TME and found that all scores were highly correlated with AML’s prognostic characteristics. Subsequently, differentially expressed mRNAs and lncRNAs between high and low score groups were identified to construct a TME-related ceRNA network. Further, the Cox-lasso survival model was employed to screen out the hub prognostic ceRNA network composed of two mRNAs (EPB41L3, COL2A1), three miRNAs (hsa-mir-26a-5p, hsa-mir-148b-3p, hsa-mir-148a-3p), and two lncRNAs (CYP1B1-AS1, C9orf106), and construct nomograms. Finally, we used CIBERSORT algorithm and Kaplan-Meier survival analysis to identify the prognostic TME immune cells and found that naive B cells, M2-type macrophages, and helper follicular T cells were related to prognosis, and the hub ceRNAs were highly correlated with immune cell infiltration. This study provided a new perspective to elucidate how TME regulates AML process and put forward the new therapy strategies combining targeting tumor cells with disintegrating TME.

Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets

Background

Malignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC.

Methods

We collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1.

Results

Differential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1, p = 0.0009 and AUC = 0.8256, p = 0.0015 respectively).

Conclusions

Our study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

Cancer, Retrogenes, and Evolution

This review summarizes the knowledge about retrogenes in the context of cancer and evolution. The retroposition, in which the processed mRNA from parental genes undergoes reverse transcription and the resulting cDNA is integrated back into the genome, results in additional copies of existing genes. Despite the initial misconception, retroposition-derived copies can become functional, and due to their role in the molecular evolution of genomes, they have been named the “seeds of evolution”. It is convincing that retrogenes, as important elements involved in the evolution of species, also take part in the evolution of neoplastic tumors at the cell and species levels. The occurrence of specific “resistance mechanisms” to neoplastic transformation in some species has been noted. This phenomenon has been related to additional gene copies, including retrogenes. In addition, the role of retrogenes in the evolution of tumors has been described. Retrogene expression correlates with the occurrence of specific cancer subtypes, their stages, and their response to therapy. Phylogenetic insights into retrogenes show that most cancer-related retrocopies arose in the lineage of primates, and the number of identified cancer-related retrogenes demonstrates that these duplicates are quite important players in human carcinogenesis.

A comprehensive analysis of somatic alterations in Chinese ovarian cancer patients

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Reverse engineering a predictive signature characterized by proliferation, DNA damage, and immune escape from stage I lung adenocarcinoma recurrence

Identifying early-stage cancer patients at risk for progression is a major goal of biomarker research. This report describes a novel 19-gene signature (19-GCS) that predicts stage I lung adenocarcinoma (LAC) recurrence and response to therapy and performs comparably in pancreatic adenocarcinoma (PAC), which shares LAC molecular traits. Kaplan-Meier, Cox regression, and cross-validation analyses were used to build the signature from training, test, and validation sets comprising 831 stage I LAC transcriptomes from multiple independent data sets. A statistical analysis was performed using the R language. Pathway and gene set enrichment were used to identify underlying mechanisms. 19-GCS strongly predicts overall survival and recurrence-free survival in stage I LAC (P=0.002 and P<0.001, respectively) and in stage I-II PAC (P<0.0001 and P<0.0005, respectively). A multivariate cox regression analysis demonstrated the independence of 19-GCS from significant clinical factors. Pathway analyses revealed that 19-GCS high-risk LAC and PAC tumors are characterized by increased proliferation, enhanced stemness, DNA repair deficiency, and compromised MHC class I and II antigen presentation along with decreased immune infiltration. Importantly, high-risk LAC patients do not appear to benefit from adjuvant cisplatin while PAC patients derive additional benefit from FOLFIRINOX compared with gemcitabine-based regimens. When validated prospectively, this proof-of-concept biomarker may contribute to tailoring treatment, recurrence reduction, and survival improvements in early-stage lung and pancreatic cancers.

RNA Immune Signatures from Pan-Cancer Analysis Are Prognostic for High-Grade Serous Ovarian Cancer and Other Female Cancers

Immune cell infiltrates within the tumor microenvironment can influence treatment response and outcome in several cancers. In this study, we developed RNA-based immune signatures from pan-cancer analysis that could serve as potential markers across tumor types and tested them for association with outcome in high-grade serous ovarian cancer (HGSOC) and other female cancers. Pan-cancer RNA-Seq cluster analysis of immune-related gene expression profiles in The Cancer Genome Atlas (TCGA) from 29 different solid tumors (4446 specimens) identified distinct but concordant gene signatures. Among these immune signatures, Cytotoxic Lymphocyte Immune Signature (CLIS), T-cell trafficking (TCT), and the TCT to M2 tumor-associated macrophage (M2TAM) ratio (TCT:M2TAM) were significantly (p < 0.05) associated with overall survival (OS), using multivariable Cox proportional hazards regression models, in a discovery cohort and two independent validation cohorts of HGSOC patients. Notably, the TCT:M2TAM ratio was highly significant (p ≤ 0.000001) in two HGSOC cohorts. Immune signatures were also significant (p < 0.05) in the presence of tumor cytoreduction, BRCA1/2 mutation, and COL2A1 expression. Importantly, the CLIS and TCT signatures were also validated for prognostic significance (p < 0.05) in TCGA cohorts for endometrial and high tumor mutational burden (Hi-TMB) breast cancer. These immune signatures also have the potential for being predictive in other cancers and for patients following different treatment strategies.

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice

Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim to identify a pseudogene-based prognosis signature for HNSCC by machine learning. RNA-seq data were downloaded from The Cancer Genome Atlas, and 700 differentially-expressed pseudogenes were identified. The survival-related pseudogenes were screened through COX-regression analysis, which includes univariate regression, least absolute shrinkage and selection operator regression, and multivariate regression, and a five-pseudogene signature was constructed. The value of prediction for the signature was validated in multiple subgroups in terms of survival. Gene set enrichment analysis (GSEA) and coexpression analysis were used to determine the underlying biological functions. Seven hundred dysregulated pseudogenes were identified, and the five-pseudogene signature can distinguish the low-risk and high-risk patients for both training and testing sets and predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different genders, ages, stages, and grades. Coexpression analysis revealed that the five-pseudogene is associated with immune system. GSEA showed cancer-related biological process and pathways the five-pseudogene involved in. The five-pseudogene signature is not only a novel marker for prognosis but also a promising signature for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

A Comprehensive Review on MAPK: A Promising Therapeutic Target in Cancer

The mitogen-activated protein kinase (MAPK) pathway is an important bridge in the switch from extracellular signals to intracellular responses. Alterations of signaling cascades are found in various diseases, including cancer, as a result of genetic and epigenetic changes. Numerous studies focused on both the homeostatic and the pathologic conduct of MAPK signaling; however, there is still much to be deciphered in terms of regulation and action models in both preclinical and clinical research. MAPK has implications in the response to cancer therapy, particularly the activation of the compensatory pathways in response to experimental MAPK inhibition. The present paper discusses new insights into MAPK as a complex cell signaling pathway with roles in the sustenance of cellular normal conduit, response to cancer therapy, and activation of compensatory pathways. Unfortunately, most MAPK inhibitors trigger resistance due to the activation of compensatory feed-back loops in tumor cells and tumor microenvironment components. Therefore, novel combinatorial therapies have to be implemented for cancer management in order to restrict the possibility of alternative pathway activation, as a perspective for developing novel therapies based on integration in translational studies.

The role of collagen in cancer: from bench to bedside

Collagen is the major component of the tumor microenvironment and participates in cancer fibrosis. Collagen biosynthesis can be regulated by cancer cells through mutated genes, transcription factors, signaling pathways and receptors; furthermore, collagen can influence tumor cell behavior through integrins, discoidin domain receptors, tyrosine kinase receptors, and some signaling pathways. Exosomes and microRNAs are closely associated with collagen in cancer. Hypoxia, which is common in collagen-rich conditions, intensifies cancer progression, and other substances in the extracellular matrix, such as fibronectin, hyaluronic acid, laminin, and matrix metalloproteinases, interact with collagen to influence cancer cell activity. Macrophages, lymphocytes, and fibroblasts play a role with collagen in cancer immunity and progression. Microscopic changes in collagen content within cancer cells and matrix cells and in other molecules ultimately contribute to the mutual feedback loop that influences prognosis, recurrence, and resistance in cancer. Nanoparticles, nanoplatforms, and nanoenzymes exhibit the expected gratifying properties. The pathophysiological functions of collagen in diverse cancers illustrate the dual roles of collagen and provide promising therapeutic options that can be readily translated from bench to bedside. The emerging understanding of the structural properties and functions of collagen in cancer will guide the development of new strategies for anticancer therapy.

Induction of ALP and MMP9 activity facilitates invasive behavior in heterogeneous human BMSC and HNSCC 3D spheroids

Mesenchymal stem cells (MSCs) are multipotent progenitor cells capable of differentiating into adipocytic, osteogenic, chondrogenic, and myogenic lineages. There is growing evidence that MSCs home into the tumor microenvironment attracted by a variety of signals such as chemokines, growth factors, and cytokines. Tumor-homing stem cells may originate from bone marrow-derived MSCs (BMSCs) or adipose tissue-derived MSCs. Recent scientific data suggest that MSCs in combination with tumor cells can either promote or inhibit tumorigenic behavior. In head and neck squamous cell carcinoma (HNSCC), BMSCs are reported to be enriched with a potential negative role. Here, we evaluated the effect of BMSCs from 4 different donors in combination with 4 HNSCC cell lines in a 3-dimensional multicellular spheroid model. Heterogeneous combinations revealed an up-regulation of gene and protein expression of osteogenic markers runt-related transcription factor 2 (RUNX2) and alkaline phosphatase (ALP) together with a substantial secretion of matrix metalloproteinase 9. Moreover, heterogenous BMSC/tumor spheroids showed increased invasion compared with homogenous spheroids in a Boyden chamber invasion assay. Furthermore, inhibition of ALP resulted in a substantially decreased spreading of heterogeneous spheroids on laminin-rich matrix. In summary, our data suggest a prometastatic effect of BMSCs combined with HNSCC.-Wessely, A., Waltera, A., Reichert, T. E., Stöckl, S., Grässel, S., Bauer, R. J. Induction of ALP and MMP9 activity facilitates invasive behavior in heterogeneous human BMSC and HNSCC 3D-spheroids.

Intra-tumor heterogeneity for endometrial cancer and its clinical significance

BACKGROUND

Management of tumors has become more complex owing to tumor heterogeneity. Fewer studies have been performed on intra-tumor heterogeneity of endometrial cancer (EC) until now. Therefore, it is of great clinical value to explore the intra-tumor heterogeneity of EC based on clinical features and gene expression profiles.

METHODS

A total of 1688 patients with EC were screened and 114 patients were finally selected, including specimens from 84 patients with primary EC without relapse (PE) and the paired metastases (P-M) specimens, as well as specimens from 30 patients with primary EC with relapse (RPE) and the paired relapsed EC (P-RE) specimens. Microarray and RNA-seq were used to detect gene expression of EC samples. Clinicopathological characteristics and molecular data were compared between PE and P-M groups and between RPE and P-RE groups to explore the intra-tumor heterogeneity of EC.

RESULTS

The clinical intra-tumor spatial heterogeneity of pathological type, grade, ER status, and PR status between PE and P-M were 17.9%, 13.1%, 28.6%, and 28.6%, respectively. The clinical intra-tumor spatiotemporal heterogeneity of pathological type, grade, ER status, and PR status between RPE and P-RE were 16.7%, 33.3%, 25.0%, and 37.5%, respectively. Cluster analysis sorts EC samples based on progression type of lesion and their pathological type. There were differentially expressed genes between PE and P-M and between RPE and P-RE, of which gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were mainly enriched in cell proliferation, the p53 signaling pathway, etc. CONCLUSIONS:: Clinical and molecular data showed that there was spatiotemporal heterogeneity in intra-tumor of EC, which may add to the complexity of diagnosis and therapeutics for EC. Considering the intra-tumor heterogeneity, sequential chemotherapy and precision medicine may be a more suitable treatment plan for EC.

A Four-Pseudogene Classifier Identified by Machine Learning Serves as a Novel Prognostic Marker for Survival of Osteosarcoma

Osteosarcoma is a common malignancy with high mortality and poor prognosis due to lack of predictive markers. Increasing evidence has demonstrated that pseudogenes, a type of non-coding gene, play an important role in tumorigenesis. The aim of this study was to identify a prognostic pseudogene signature of osteosarcoma by machine learning. A sample of 94 osteosarcoma patients’ RNA-Seq data with clinical follow-up information was involved in the study. The survival-related pseudogenes were screened and related signature model was constructed by cox-regression analysis (univariate, lasso, and multivariate). The predictive value of the signature was further validated in different subgroups. The putative biological functions were determined by co-expression analysis. In total, 125 survival-related pseudogenes were identified and a four-pseudogene (RPL11-551L14.1, HR: 0.65 (95% CI: 0.44–0.95); RPL7AP28, HR: 0.32 (95% CI: 0.14–0.76); RP4-706A16.3, HR: 1.89 (95% CI: 1.35–2.65); RP11-326A19.5, HR: 0.52(95% CI: 0.37–0.74)) signature effectively distinguished the high- and low-risk patients, and predicted prognosis with high sensitivity and specificity (AUC: 0.878). Furthermore, the signature was applicable to patients of different genders, ages, and metastatic status. Co-expression analysis revealed the four pseudogenes are involved in regulating malignant phenotype, immune, and DNA/RNA editing. This four-pseudogene signature is not only a promising predictor of prognosis and survival, but also a potential marker for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

Clinical significance of LOXL4 expression and features of LOXL4-associated protein-protein interaction network in esophageal squamous cell carcinoma

Lysyl oxidase-like 4 (LOXL4), a member of the LOX family proteins, catalyzes oxidative deamination of lysine residues in collagen and elastin, which are responsible for maintaining extracellular matrix homeostasis. In this study, the mRNA expression of LOXL4 in seven esophageal squamous cell carcinoma (ESCC) cell lines and 15 ESCC pairs of clinical samples were examined. Furthermore, LOXL4 protein levels in the ESCC cell lines were determined using western blotting. With the use of immunofluorescence, LOXL4 was observed to be localized primarily in the cytoplasm, but was also present in the nucleus. In addition, the results indicated that the upregulated expression of LOXL4 was associated with poor survival in patients with ESCC even following curative resection (P = 0.010). Similar Kaplan-Meier estimator curves for proteins that interact with LOXL4, SUV39H1 (P = 0.014) and COL2A1 (P = 0.011), were plotted. The analyses based on the protein-protein interaction network depicted the expression of LOXL4 and its associated proteins as well as their functions, suggesting that LOXL4 and its associated proteins may serve a significant role in the development and progression of ESCC. In conclusion, the results of the present study suggest that LOXL4 is a potential biomarker for patients with ESCC, as well as SUV39H1 and COL2A1, and high expression levels of these genes are associated with poor prognosis in patients with ESCC.

Proteome Analyses Reveal Positive Association of COL2A1, MPO, TYMS, and IGFBP5 with Canine Mammary Gland Malignancy

PURPOSE

To identify aberrantly expressed proteins contributing to pathogenesis of canine mammary tumors (CMTs) which are the most prevalent neoplasms in female dogs and include different types.

EXPERIMENTAL DESIGN

Frozen tissue specimens of normal mammary gland (n = 7), lobular hyperplasia (n = 6), simple carcinoma (n = 6), and complex carcinoma (n = 6) are collected from 11 CMT cases. Tissue homogenates are comparatively analyzed by the isobaric tags for relative and absolute quantification (iTRAQ) combined with LC-MS/MS to identify proteins differentially expressed in different-type CMT tissues.

RESULTS

Among 3795 proteins identified and quantified among all groups, 133, 127, and 98 proteins are particularly overexpressed in simple carcinoma, complex carcinoma, and both types, respectively, compared with normal and hyperplastic tissues. Moreover, collagen type II alpha 1 chain (COL2A), myeloperoxidase (MPO), thymidylate synthetase (TYMS), and insulin-like growth factor-binding protein 5 (IGFBP5) are validated to be highly expressed in different-type CMT tissues using immunoblotting and immunohistochemistry. Notably, COL2A1 and IGFBP5 levels are correlated with clinical stages.

CONCLUSIONS AND CLINICAL RELEVANCE

COL2A1, MPO, TYMS, and IGFBP5 protein levels are positively associated with CMT development. Data expedite further investigations to improve treatment regimens for CMT.

Gene expression profiling of spontaneously occurring canine mammary tumours: Insight into gene networks and pathways linked to cancer pathogenesis

Spontaneously occurring canine mammary tumours (CMTs) are the most common neoplasms of unspayed female dogs leading to thrice higher mortality rates than human breast cancer. These are also attractive models for human breast cancer studies owing to clinical and molecular similarities. Thus, they are important candidates for biomarker studies and understanding cancer pathobiology. The study was designed to explore underlying molecular networks and pathways in CMTs for deciphering new prognostic factors and therapeutic targets. To gain an insight into various pathways and networks associated with the development and pathogenesis of CMTs, comparative cDNA microarray expression profiling was performed using CMT tissues and healthy mammary gland tissues. Upon analysis, 1700 and 1287 differentially expressed genes (DEGs, P ≤ 0.05) were identified in malignant and benign tissues, respectively. DEGs identified from microarray analysis were further annotated using the Ingenuity Systems Pathway Analysis (IPA) tool for detection of deregulated canonical pathways, upstream regulators, and networks associated with malignant, as well as, benign disease. Top scoring key networks in benign and malignant mammary tumours were having central nodes of VEGF and BUB1B, respectively. Cyclins & cell cycle regulation and TREM1 signalling were amongst the top activated canonical pathways in CMTs. Other cancer related significant pathways like apoptosis signalling, dendritic cell maturation, DNA recombination and repair, Wnt/β-catenin signalling, etc. were also found to be altered. Furthermore, seven proteins (ANXA2, APOCII, CDK6, GATC, GDI2, GNAQ and MYH9) highly up-regulated in malignant tissues were identified by two-dimensional gel electrophoresis (2DE) and MALDI-TOF PMF studies which were in concordance with microarray data. Thus, the study has uncovered ample number of candidate genes associated with CMTs which need to be further validated as therapeutic targets and prognostic markers.

HOXA4/HOXB3 gene expression signature as a biomarker of recurrence in patients with high-grade serous ovarian cancer following primary cytoreductive surgery and first-line adjuvant chemotherapy

OBJECTIVES

Aberrant homeobox (HOX) gene expression is reported in high-grade serous ovarian carcinoma (HGSOC), however, its prognostic significance remains unclear.

METHODS

HOX genes associated with progression-free survival (PFS) in a discovery cohort of primary HGSOC samples with RNA sequencing data, and those previously reported to be associated with clinical outcomes, were selected for qPCR testing in an independent training cohort of primary HGSOC samples (n=71). A prognostic model for PFS was developed using univariate and multivariate Cox regression. Patients were stratified into risk groups that optimized the test statistic. The model was tested in an independent HGSOC cohort from The Cancer Genome Atlas (TCGA) (n=320). The effect of selected HOX genes on drug sensitivity and reactive oxygen species (ROS) accumulation was examined in vitro.

RESULTS

Of 23 HOX genes tested in the training cohort, HOXA4 (HR=1.20, 95% CI=1.07-1.34, P=0.002) and HOXB3 (HR=1.09, 95% CI=1.01-1.17, P=0.027) overexpression were significantly associated with shorter PFS in multivariate analysis. Based on the optimal cutoff of the HOXA4/HOXB3 risk score, median PFS was 16.9months (95% CI=14.6-21.2months) and not reached (>80months) for patients with high and low risk scores, respectively (HR=8.89, 95% CI=2.09-37.74, P<0.001). In TCGA, the HOXA4/HOXB3 risk score was significantly associated with disease-free survival (HR=1.44, 95% CI=1.00-2.09, P=0.048). HOXA4 or HOXB3 overexpression in ovarian cancer cells decreased sensitivity to cisplatin and attenuated the generation of cisplatin-induced ROS (P<0.05).

CONCLUSIONS

HOXA4/HOXB3 gene expression-based risk score may be useful for prognostic risk stratification and warrants prospective validation in HGSOC patients.

Exploring the key genes and pathways in enchondromas using a gene expression microarray

Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

MiR-200c-3p inhibits cell migration and invasion of clear cell renal cell carcinoma via regulating SLC6A1

In this study, we investigated the mechanism of miR-200c-3p and SLC6A1 in regulating cell activity of clear cell renal cell carcinoma (CCRCC). The mRNA and miRNA expressions of tissue specimens were analyzed by CapitalBio Corporation (Beijing, China). The expression of SLC6A1 in CCRCC cells was examined through qRT-PCR and western blot. The migration and invasion ability of 786-O cells was testified by transwell assay after transfected. 786-O cell proliferation ability was detected by MTT assay. Dual luciferase reporter assay verified the association between SLC6A1 and miR-200c-3p. SLC6A1 was high expressed and miR-200c-3p was low expressed in CCRCC tissues and cells. Besides, lower SLC6A1 expression indicated longer survival time and higher survival rate. MiR-200c-3p could directly target at SLC6A1 and reduce its expression. MiR-200c-3p inhibited the proliferation, migration and invasion in 786-O cells by down-regulating SLC6A1 expression. The results suggested that the miR-200c-3p served as a suppressor for CCRCC via down-regulating SLC6A1.

Pseudogenes in Human Cancer

Recent advances in the analysis of RNA sequencing data have shown that pseudogenes are highly specific markers of cell identity and can be used as diagnostic and prognostic markers. Furthermore, genetically engineered mouse models have recently provided compelling support for a causal link between altered pseudogene expression and cancer. In this review, we discuss the most recent milestones reached in the pseudogene field and the use of pseudogenes as cancer classifiers.