Diagnostic and prognostic implications of ribosomal protein transcript expression patterns in human cancers

Ribosome specialization in cancer: a spotlight on ribosomal proteins

In the past few decades, our view of ribosomes has changed substantially. Rather than passive machines without significant variability, it is now acknowledged that they are heterogeneous, and have direct regulatory capacity. This 'ribosome heterogeneity' comes in many flavors, including in both the RNA and protein components of ribosomes, so there are many paths through which ribosome specialization could arise. It is easy to imagine that specialized ribosomes could have wide physiological roles, through the translation of specific mRNA populations, and there is now evidence for this in several contexts. Translation is highly dysregulated in cancer, needed to support oncogenic phenotypes and to overcome cellular stress. However, the role of ribosome specialization in this is not clear. In this review we focus on specialized ribosomes in cancer. Specifically, we assess the impact that post-translational modifications and differential ribosome incorporation of ribosomal proteins (RPs) have in this disease. We focus on studies that have shown a ribosome-mediated change in translation of specific mRNA populations, and hypothesize how such a process could be driving other phenotypes. We review the impact of RP-mediated heterogeneity in both intrinsic and extrinsic oncogenic processes, and consider how this knowledge could be leveraged to benefit patients.

Mucus production, host-microbiome interactions, hormone sensitivity, and innate immune responses modeled in human cervix chips

Modulation of the cervix by steroid hormones and commensal microbiome play a central role in the health of the female reproductive tract. Here we describe organ-on-a-chip (Organ Chip) models that recreate the human cervical epithelial-stromal interface with a functional epithelial barrier and production of mucus with biochemical and hormone-responsive properties similar to living cervix. When Cervix Chips are populated with optimal healthy versus dysbiotic microbial communities (dominated by Lactobacillus crispatus and Gardnerella vaginalis, respectively), significant differences in tissue innate immune responses, barrier function, cell viability, proteome, and mucus composition are observed that are similar to those seen in vivo. Thus, human Cervix Organ Chips represent physiologically relevant in vitro models to study cervix physiology and host-microbiome interactions, and hence may be used as a preclinical testbed for development of therapeutic interventions to enhance women's health.

Glioblastoma biomarkers in urinary extracellular vesicles reveal the potential for a 'liquid gold' biopsy

BACKGROUND

Biomarkers that reflect glioblastoma tumour activity and treatment response are urgently needed to help guide clinical management, particularly for recurrent disease. As the urinary system is a major clearance route of circulating extracellular vesicles (EVs; 30-1000 nm nanoparticles) we explored whether sampling urinary-EVs could serve as a simple and non-invasive liquid biopsy approach for measuring glioblastoma-associated biomarkers.

METHODS

Fifty urine specimens (15-60 ml) were collected from 24 catheterised glioblastoma patients immediately prior to primary (n = 17) and recurrence (n = 7) surgeries, following gross total resection (n = 9), and from age/gender-matched healthy participants (n = 14). EVs isolated by differential ultracentrifugation were characterised and extracted proteomes were analysed by high-resolution data-independent acquisition liquid chromatography tandem mass spectrometry (DIA-LC-MS/MS).

RESULTS

Overall, 6857 proteins were confidently identified in urinary-EVs (q-value ≤ 0.01), including 94 EV marker proteins. Glioblastoma-specific proteomic signatures were determined, and putative urinary-EV biomarkers corresponding to tumour burden and recurrence were identified (FC ≥ | 2 | , adjust p-val≤0.05, AUC > 0.9).

CONCLUSION

In-depth DIA-LC-MS/MS characterisation of urinary-EVs substantiates urine as a viable source of glioblastoma biomarkers. The promising 'liquid gold' biomarker panels described here warrant further investigation.

DNA methylation-mediated epigenetic regulation of oncogenic RPS2 as a novel therapeutic target and biomarker in hepatocellular carcinoma

Ribosomal Protein S2 (RPS2) has emerged as a potential prognostic biomarker due to its involvement in key cellular processes and its altered expression pattern in certain types of cancer. However, its role in hepatocellular carcinoma (HCC) has yet to be investigated. Herein, we analyzed RPS2 mRNA expression and promoter methylation in HCC patient samples and HepG2 cells. Subsequently, loss-of-function experiments were conducted to determine the function of RPS2 in HCC cells in vitro. Our results revealed that RPS2 mRNA expression is significantly elevated, and its promoter is hypomethylated in HCC patient samples compared to controls. In addition, 5-Azacytidine treatment in HepG2 cells decreased RPS2 promoter methylation level and increased its mRNA expression. RPS2 knockdown in HepG2 cells suppressed cell proliferation and promoted apoptosis. Functional pathway analysis of genes positively and negatively associated with RPS2 expression in HCC showed enrichment in ribosomal biogenesis, translation machinery, cell cycle regulation, and DNA processing. Furthermore, utilizing drug-protein 3D docking, we found that doxorubicin, sorafenib, and 5-Fluorouracil, showed high affinity to the active sites of RPS2, and in vitro treatment with these drugs reduced RPS2 expression. For the first time, we report on DNA methylation-mediated epigenetic regulation of RPS2 and its oncogenic role in HCC. Our findings suggest that RPS2 plays a significant role in the development and progression of HCC, hence its potential prognostic and therapeutic utility. Moreover, as epigenetic changes happen early in cancer development, RPS2 may serve as a potential biomarker for tumor progression.

Decoding Ribosome Heterogeneity: A New Horizon in Cancer Therapy

The traditional perception of ribosomes as uniform molecular machines has been revolutionized by recent discoveries, revealing a complex landscape of ribosomal heterogeneity. Opposing the conventional belief in interchangeable ribosomal entities, emerging studies underscore the existence of specialized ribosomes, each possessing unique compositions and functions. Factors such as cellular and tissue specificity, developmental and physiological states, and external stimuli, including circadian rhythms, significantly influence ribosome compositions. For instance, muscle cells and neurons are characterized by distinct ribosomal protein sets and dynamic behaviors, respectively. Furthermore, alternative forms of ribosomal RNA (rRNAs) and their post-transcriptional modifications add another dimension to this heterogeneity. These variations, orchestrated by spatial, temporal, and conditional factors, enable the manifestation of a broad spectrum of specialized ribosomes, each tailored for potentially distinct functions. Such specialization not only impacts mRNA translation and gene expression but also holds significant implications for broader biological contexts, notably in the realm of cancer research. As the understanding of ribosomal diversity deepens, it also paves the way for exploring novel avenues in cellular function and offers a fresh perspective on the molecular intricacies of translation.

WD Repeat Domain 5 Inhibitors for Cancer Therapy: Not What You Think

WDR5 is a conserved nuclear protein that scaffolds the assembly of epigenetic regulatory complexes and moonlights in functions ranging from recruiting MYC oncoproteins to chromatin to facilitating the integrity of mitosis. It is also a high-value target for anti-cancer therapies, with small molecule WDR5 inhibitors and degraders undergoing extensive preclinical assessment. WDR5 inhibitors were originally conceived as epigenetic modulators, proposed to inhibit cancer cells by reversing oncogenic patterns of histone H3 lysine 4 methylation-a notion that persists to this day. This premise, however, does not withstand contemporary inspection and establishes expectations for the mechanisms and utility of WDR5 inhibitors that can likely never be met. Here, we highlight salient misconceptions regarding WDR5 inhibitors as epigenetic modulators and provide a unified model for their action as a ribosome-directed anti-cancer therapy that helps focus understanding of when and how the tumor-inhibiting properties of these agents can best be understood and exploited.

Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems

Metastasis is a nonrandom process with varying degrees of organotropism-specific source-acceptor seeding. Understanding how patterns between source and acceptor tumors emerge remains a challenge in oncology. We hypothesize that organotropism results from the macronutrient niche of cells in source and acceptor organs. To test this, we constructed and analyzed a metastatic network based on 9303 records across 28 tissue types. We found that the topology of the network is nested and modular with scale-free degree distributions, reflecting organotropism along a specificity/generality continuum. The variation in topology is significantly explained by the matching of metastatic cells to their stoichiometric niche. Specifically, successful metastases are associated with higher phosphorus content in the acceptor compared to the source organ, due to metabolic constraints in proliferation crucial to the invasion of new tissues. We conclude that metastases are codetermined by processes at source and acceptor organs, where phosphorus content is a limiting factor orchestrating tumor ecology.

In Vivo Investigation of the Effect of Dietary Acrylamide and Evaluation of Its Clinical Relevance in Colon Cancer

Dietary exposure to acrylamide (AA) has been linked with carcinogenicity in the gastrointestinal (GI) tract. However, epidemiologic data on AA intake in relation to cancer risk are limited and contradictory, while the potential cancer-inducing molecular pathways following AA exposure remain elusive. In this study, we collected mechanistic information regarding the induction of carcinogenesis by dietary AA in the colon, using an established animal model. Male Balb/c mice received AA orally (0.1 mg/kg/day) daily for 4 weeks. RNA was extracted from colon tissue samples, followed by RNA sequencing. Comparative transcriptomic analysis between AA and mock-treated groups revealed a set of differentially expressed genes (DEGs) that were further processed using different databases through the STRING-DB portal, to reveal deregulated protein-protein interaction networks. We found that genes implicated in RNA metabolism, processing and formation of the ribosomal subunits and protein translation and metabolism are upregulated in AA-exposed colon tissue; these genes were also overexpressed in human colon adenocarcinoma samples and were negatively correlated with patient overall survival (OS), based on publicly available datasets. Further investigation of the potential role of these genes during the early stages of colon carcinogenesis may shed light into the underlying mechanisms induced by dietary AA exposure.

Molecular differences in renal cell carcinoma between males and females

PURPOSE

The disparity in renal cell carcinoma (RCC) risk and treatment outcome between males and females is well documented, but the underlying molecular mechanisms remain poorly elucidated.

METHODS

We performed a narrative review synthesizing contemporary evidence on sex-specific molecular differences in healthy kidney tissue and RCC.

RESULTS

In healthy kidney tissue, gene expression differs significantly between males and females, including autosomal and sex-chromosome-linked genes. The differences are most prominent for sex-chromosome-linked genes and attributable to Escape from X chromosome-linked inactivation and Y chromosome loss. The frequency distribution of RCC histologies varies between the sexes, particularly for papillary, chromophobe, and translocation RCC. In clear-cell and papillary RCC, sex-specific gene expressions are pronounced, and some of these genes are amenable to pharmacotherapy. However, for many, the impact on tumorigenesis remains poorly understood. In clear-cell RCC, molecular subtypes and gene expression pathways have distinct sex-specific trends, which also apply to the expression of genes implicated in tumor progression.

CONCLUSION

Current evidence suggests meaningful genomic differences between male and female RCC, highlighting the need for sex-specific RCC research and personalized sex-specific treatment approaches.

Life span-associated ferroptosis-related genes identification and validation for hepatocellular carcinoma patients as hepatitis B virus carriers

BACKGROUND

Hepatitis B virus (HBV)-infected population accounts for approximately 50% of all hepatocellular carcinoma (HCC) cases and has a relatively poor prognosis. Although the significant role of ferroptosis in the development and therapeutic response of various cancers has been validated, the key ferroptosis-related genes (FRGs) on the stratification of HBV-associated HCC are still unclear.

METHODS

Through the random forest, GSVA and Cox regression analyses, we established a comprehensive prognostic system covering multiple FRGs to elevate the predictive accuracy for the survival rate of HBV-related HCC using information obtained from public databases. The association between key FRGs and the immune microenvironment was evaluated, and the molecular mechanism was identified by GSEA and SNV analyses. Finally, the differential expression of key FRGs was validated by immunohistochemistry staining of patient tissue microarrays.

RESULTS

Within the top 10 key FRGs, EPAS1 and GABARAPL1 were taken as protective factors, and SQLE, RAD51AP1, RPL8, CAPG, RRM2, SLC1A5, SLC38A1, and SRC were the other eight dangerous markers. Cox regression analysis combined with clinicopathological features indicated the independent prognostic efficacy of GSVA complex score based on these FRGs. In addition, key FRGs were related to immune and metabolic-related functions. Especially, the immunohistochemical analysis of SQLE in 50 clinical samples showed significantly higher expression in HBV+ HCC tissues.

CONCLUSIONS

These results indicate that 10 FRGs may be potential biomarkers and therapeutic targets for long-term survival in HBV-related HCC.

Identification of Altered Primary Immunodeficiency-Associated Genes and Their Implications in Pediatric Cancers

BACKGROUND

Cancer is the leading cause of disease-related mortality in children and malignancies are more frequently observed in individuals with primary immunodeficiencies (PIDs). This study aimed to identify and highlight the molecular mechanisms, such as oncogenesis and immune evasion, by which PID-related genes may lead to the development of pediatric cancers.

METHOD

We implemented a novel bioinformatics framework using patient data from the TARGET database and performed a comparative transcriptome analysis of PID-related genes in pediatric cancers between normal and cancer tissues, gene ontology enrichment, and protein-protein interaction analyses, and determined the prognostic impacts of commonly mutated and differentially expressed PID-related genes.

RESULTS

From the Fulgent Genetics Comprehensive Primary Immunodeficiency panel of 472 PID-related genes, 89 genes were significantly differentially expressed between normal and cancer tissues, and 20 genes were mutated in two or more patients. Enrichment analysis highlighted many immune system processes as well as additional pathways in the mutated PID-related genes related to oncogenesis. Survival outcomes for patients with altered PID-related genes were significantly different for 75 of the 89 DEGs, often resulting in a poorer prognosis.

CONCLUSIONS

Overall, multiple PID-related genes demonstrated the connection between PIDs and cancer development and should be studied further, with hopes of identifying new therapeutic targets.

Regulation of RNA Polymerase I Stability and Function

RNA polymerase I is a highly processive enzyme with fast initiation and elongation rates. The structure of Pol I, with its in-built RNA cleavage ability and incorporation of subunits homologous to transcription factors, enables it to quickly and efficiently synthesize the enormous amount of rRNA required for ribosome biogenesis. Each step of Pol I transcription is carefully controlled. However, cancers have highjacked these control points to switch the enzyme, and its transcription, on permanently. While this provides an exceptional benefit to cancer cells, it also creates a potential cancer therapeutic vulnerability. We review the current research on the regulation of Pol I transcription, and we discuss chemical biology efforts to develop new targeted agents against this process. Lastly, we highlight challenges that have arisen from the introduction of agents with promiscuous mechanisms of action and provide examples of agents with specificity and selectivity against Pol I.

Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations

Subcellular localization of messenger RNAs (mRNAs) plays a key role in the spatial regulation of gene activity. The functions of mRNAs have been shown to be closely linked with their localizations. As such, understanding of the subcellular localizations of mRNAs can help elucidate gene regulatory networks. Despite several computational methods that have been developed to predict mRNA localizations within cells, there is still much room for improvement in predictive performance, especially for the multiple-location prediction. In this study, we proposed a novel multi-label multi-class predictor, termed Clarion, for mRNA subcellular localization prediction. Clarion was developed based on a manually curated benchmark dataset and leveraged the weighted series method for multi-label transformation. Extensive benchmarking tests demonstrated Clarion achieved competitive predictive performance and the weighted series method plays a crucial role in securing superior performance of Clarion. In addition, the independent test results indicate that Clarion outperformed the state-of-the-art methods and can secure accuracy of 81.47, 91.29, 79.77, 92.10, 89.15, 83.74, 80.74, 79.23 and 84.74% for chromatin, cytoplasm, cytosol, exosome, membrane, nucleolus, nucleoplasm, nucleus and ribosome, respectively. The webserver and local stand-alone tool of Clarion is freely available at http://monash.bioweb.cloud.edu.au/Clarion/.

Defocus Corrected Large Area Cryo-EM (DeCo-LACE) for label-free detection of molecules across entire cell sections

A major goal of biological imaging is localization of biomolecules inside a cell. Fluorescence microscopy can localize biomolecules inside whole cells and tissues, but its ability to count biomolecules and accuracy of the spatial coordinates is limited by the wavelength of visible light. Cryo-electron microscopy (cryo-EM) provides highly accurate position and orientation information of biomolecules but is often confined to small fields of view inside a cell, limiting biological context. In this study, we use a new data-acquisition scheme called Defocus-Corrected Large-Area cryo-EM (DeCo-LACE) to collect high-resolution images of entire sections (100- to 250-nm-thick lamellae) of neutrophil-like mouse cells, representing 1-2% of the total cellular volume. We use 2D template matching (2DTM) to determine localization and orientation of the large ribosomal subunit in these sections. These data provide maps of ribosomes across entire sections of mammalian cells. This high-throughput cryo-EM data collection approach together with 2DTM will advance visual proteomics and provide biological insight that cannot be obtained by other methods.

Panels of mRNAs and miRNAs for decoding molecular mechanisms of Renal Cell Carcinoma (RCC) subtypes utilizing Artificial Intelligence approaches

Renal Cell Carcinoma (RCC) encompasses three histological subtypes, including clear cell RCC (KIRC), papillary RCC (KIRP), and chromophobe RCC (KICH) each of which has different clinical courses, genetic/epigenetic drivers, and therapeutic responses. This study aimed to identify the significant mRNAs and microRNA panels involved in the pathogenesis of RCC subtypes. The mRNA and microRNA transcripts profile were obtained from The Cancer Genome Atlas (TCGA), which were included 611 ccRCC patients, 321 pRCC patients, and 89 chRCC patients for mRNA data and 616 patients in the ccRCC subtype, 326 patients in the pRCC subtype, and 91 patients in the chRCC for miRNA data, respectively. To identify mRNAs and miRNAs, feature selection based on filter and graph algorithms was applied. Then, a deep model was used to classify the subtypes of the RCC. Finally, an association rule mining algorithm was used to disclose features with significant roles to trigger molecular mechanisms to cause RCC subtypes. Panels of 77 mRNAs and 73 miRNAs could discriminate the KIRC, KIRP, and KICH subtypes from each other with 92% (F1-score ≥ 0.9, AUC ≥ 0.89) and 95% accuracy (F1-score ≥ 0.93, AUC ≥ 0.95), respectively. The Association Rule Mining analysis could identify miR-28 (repeat count = 2642) and CSN7A (repeat count = 5794) along with the miR-125a (repeat count = 2591) and NMD3 (repeat count = 2306) with the highest repeat counts, in the KIRC and KIRP rules, respectively. This study found new panels of mRNAs and miRNAs to distinguish among RCC subtypes, which were able to provide new insights into the underlying responsible mechanisms for the initiation and progression of KIRC and KIRP. The proposed mRNA and miRNA panels have a high potential to be as biomarkers of RCC subtypes and should be examined in future clinical studies.

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.

AKT1 Transcriptomic Landscape in Breast Cancer Cells

Overexpression and hyperactivation of the serine/threonine protein kinase B (AKT) pathway is one of the most common cellular events in breast cancer progression. However, the nature of AKT1-specific genome-wide transcriptomic alterations in breast cancer cells and breast cancer remains unknown to this point. Here, we delineate the impact of selective AKT1 knock down using gene-specific siRNAs or inhibiting the AKT activity with a pan-AKT inhibitor VIII on the nature of transcriptomic changes in breast cancer cells using the genome-wide RNA-sequencing analysis. We found that changes in the cellular levels of AKT1 lead to changes in the levels of a set of differentially expressed genes and, in turn, imply resulting AKT1 cellular functions. In addition to an expected positive relationship between the status of AKT1 and co-expressed cellular genes, our study unexpectedly discovered an inherent role of AKT1 in inhibiting the expression of a subset of genes in both unstimulated and growth factor stimulated breast cancer cells. We found that depletion of AKT1 leads to upregulation of a subset of genes—many of which are also found to be downregulated in breast tumors with elevated high AKT1 as well as upregulated in breast tumors with no detectable AKT expression. Representative experimental validation studies in two breast cancer cell lines showed a reasonable concurrence between the expression data from the RNA-sequencing and qRT-PCR or data from ex vivo inhibition of AKT1 activity in cancer patient-derived cells. In brief, findings presented here provide a resource for further understanding of AKT1-dependent modulation of gene expression in breast cancer cells and broaden the scope and significance of AKT1 targets and their functions.

Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data

The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.

Identification and validation of a prognostic signature related to hypoxic tumor microenvironment in cervical cancer

Background

Hypoxia is a common microenvironment condition in most malignant tumors and has been shown to be associated with adverse outcomes of cervical cancer patients. In this study, we investigated the effects of hypoxia-related genes on tumor progress to characterize the tumor hypoxic microenvironment.

Methods

We retrieved a set of hypoxia-related genes from the Molecular Signatures Database and evaluated their prognostic value for cervical cancer. A hypoxia-based prognostic signature for cervical cancer was then developed and validated using tumor samples from two independent cohorts (TCGA-CESC and CGCI-HTMCP-CC cohorts). Finally, we validated the hypoxia prediction of ccHPS score in eight human cervical cancer cell lines treated with the hypoxic and normoxic conditions, and 286 tumor samples with hypoxic category (more or less) from Gene Expression Omnibus (GEO) database with accession GSE72723.

Results

A risk signature model containing nine hypoxia-related genes was developed and validated in cervical cancer. Further analysis showed that this risk model could be an independent prognosis factor of cervical cancer, which reflects the condition of the hypoxic tumor microenvironment and its remodeling of cell metabolism and tumor immunity. Furthermore, a nomogram integrating the novel risk model and lymphovascular invasion status was developed, accurately predicting the 1-, 3- and 5-year prognosis with AUC values of 0.928, 0.916 and 0.831, respectively. These findings provided a better understanding of the hypoxic tumor microenvironment in cervical cancer and insights into potential new therapeutic strategies in improving cancer therapy.

Targeting Ribosome Biogenesis to Combat Tamoxifen Resistance in ER+ve Breast Cancer

Simple Summary

Resistance to tamoxifen treatment is an obstacle for ER+ve breast cancer therapy. The overexpression of c-MYC is a known driver of cancer progression and is associated with tamoxifen resistance. Through mediating the up-regulation of ribosome biogenesis and alteration of the transcriptome, c-MYC modulates the translation profile to facilitate the development of tamoxifen resistance. c-MYC is, however, undruggable. Thus, targeting downstream mechanisms mediated by c-MYC might be a more feasible approach. Studies have demonstrated that inhibition of ribosome biogenesis can achieve tumour suppression. Targeting ribosome biogenesis may thus be a feasible strategy to reverse tamoxifen resistance. This article reviews the current evidence to support the feasibility of suppressing ribosome biogenesis to reverse tamoxifen resistance in ER+ve breast cancer.

Abstract

Breast cancer is a heterogeneous disease. Around 70% of breast cancers are estrogen receptor-positive (ER+ve), with tamoxifen being most commonly used as an adjuvant treatment to prevent recurrence and metastasis. However, half of the patients will eventually develop tamoxifen resistance. The overexpression of c-MYC can drive the development of ER+ve breast cancer and confer tamoxifen resistance through multiple pathways. One key mechanism is to enhance ribosome biogenesis, synthesising mature ribosomes. The over-production of ribosomes sustains the demand for proteins necessary to maintain a high cell proliferation rate and combat apoptosis induced by therapeutic agents. c-MYC overexpression can induce the expression of eIF4E that favours the translation of structured mRNA to produce oncogenic factors that promote cell proliferation and confer tamoxifen resistance. Either non-phosphorylated or phosphorylated eIF4E can mediate such an effect. Since ribosomes play an essential role in c-MYC-mediated cancer development, suppressing ribosome biogenesis may help reduce aggressiveness and reverse tamoxifen resistance in breast cancer. CX-5461, CX-3543 and haemanthamine have been shown to repress ribosome biogenesis. Using these chemicals might help reverse tamoxifen resistance in ER+ve breast cancer, provided that c-MYC-mediated ribosome biogenesis is the crucial factor for tamoxifen resistance. To employ these ribosome biogenesis inhibitors to combat tamoxifen resistance in the future, identification of predictive markers will be necessary.

Normal and Neoplastic Growth Suppression by the Extended Myc Network

Among the first discovered and most prominent cellular oncogenes is MYC, which encodes a bHLH-ZIP transcription factor (Myc) that both activates and suppresses numerous genes involved in proliferation, energy production, metabolism and translation. Myc belongs to a small group of bHLH-ZIP transcriptional regulators (the Myc Network) that includes its obligate heterodimerization partner Max and six "Mxd proteins" (Mxd1-4, Mnt and Mga), each of which heterodimerizes with Max and largely opposes Myc's functions. More recently, a second group of bHLH-ZIP proteins (the Mlx Network) has emerged that bears many parallels with the Myc Network. It is comprised of the Myc-like factors ChREBP and MondoA, which, in association with the Max-like member Mlx, regulate smaller and more functionally restricted repertoires of target genes, some of which are shared with Myc. Opposing ChREBP and MondoA are heterodimers comprised of Mlx and Mxd1, Mxd4 and Mnt, which also structurally and operationally link the two Networks. We discuss here the functions of these "Extended Myc Network" members, with particular emphasis on their roles in suppressing normal and neoplastic growth. These roles are complex due to the temporal- and tissue-restricted expression of Extended Myc Network proteins in normal cells, their regulation of both common and unique target genes and, in some cases, their functional redundancy.

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). However, patients afflicted with pancreatic ductal carcinoma (PDAC), one of the deadliest malignancies, overwhelmingly exhibit negative responses to checkpoint therapy. We sought to combine data analysis and machine learning to differentiate the putative mechanisms of BCC and PDAC non-response. We discover that increased MHC-I expression in malignant cells and suppression of MHC and PD-1/PD-L expression in CD8⁺ T cells is associated with nonresponse to treatment. Furthermore, we leverage machine learning to predict response to PD-1 blockade on a cellular level. We confirm divergent resistance mechanisms between BCC, PDAC, and melanoma and highlight the potential for rapid and affordable testing of gene expression in BCC patients to accurately predict response to checkpoint therapies. Our findings present an optimistic outlook for the use of quantitative cross-cancer analyses in characterizing immune responses and predicting immunotherapy outcomes.

Deregulation of ribosomal proteins in human cancers

The ribosome, the site for protein synthesis, is composed of ribosomal RNAs (rRNAs) and ribosomal proteins (RPs). The latter have been shown to have many ribosomal and extraribosomal functions. RPs are implicated in a variety of pathological processes, especially tumorigenesis and cell transformation. In this review, we will focus on the recent advances that shed light on the effects of RPs deregulation in different types of cancer and their roles in regulating the tumor cell fate.

Construction of a Pearson- and MIC-Based Co-expression Network to Identify Potential Cancer Genes

The weighted gene co-expression network analysis (WGCNA) method constructs co-expressed gene modules based on the linear similarity between paired gene expressions. Linear correlations are the main form of similarity between genes, however, nonlinear correlations still existed and had always been ignored. We proposed a modified network analysis method, WGCNA-P + M, which combines Pearson's correlation coefficient and the maximum information coefficient (MIC) as the similarity measures to assess the linear and nonlinear correlations between genes, respectively. Taking two real datasets, GSE44861 and liver hepatocellular carcinoma (TCGA-LIHC), as examples, we compared the gene modules constructed by WGCNA-P + M and WGCNA from four perspectives: the "Usefulness" score, GO enrichment analysis on genes in the gray module, prediction performance of the top hub gene, survival analysis and literature reports on different hub genes. The results showed that the modules obtained by WGCNA-P + M are more biological meaningful, the hub genes obtained from WGCNA-P + M have more potential cancer genes.

Predicting chemotherapy response using a variational autoencoder approach

Background

Multiple studies have shown the utility of transcriptome-wide RNA-seq profiles as features for machine learning-based prediction of response to chemotherapy in cancer. While tumor transcriptome profiles are publicly available for thousands of tumors for many cancer types, a relatively modest number of tumor profiles are clinically annotated for response to chemotherapy. The paucity of labeled examples and the high dimension of the feature data limit performance for predicting therapeutic response using fully-supervised classification methods. Recently, multiple studies have established the utility of a deep neural network approach, the variational autoencoder (VAE), for generating meaningful latent features from original data. Here, we report the first study of a semi-supervised approach using VAE-encoded tumor transcriptome features and regularized gradient boosted decision trees (XGBoost) to predict chemotherapy drug response for five cancer types: colon, pancreatic, bladder, breast, and sarcoma.

Results

We found: (1) VAE-encoding of the tumor transcriptome preserves the cancer type identity of the tumor, suggesting preservation of biologically relevant information; and (2) as a feature-set for supervised classification to predict response-to-chemotherapy, the unsupervised VAE encoding of the tumor’s gene expression profile leads to better area under the receiver operating characteristic curve and area under the precision-recall curve classification performance than the original gene expression profile or the PCA principal components or the ICA components of the gene expression profile, in four out of five cancer types that we tested.

Conclusions

Given high-dimensional “omics” data, the VAE is a powerful tool for obtaining a nonlinear low-dimensional embedding; it yields features that retain biological patterns that distinguish between different types of cancer and that enable more accurate tumor transcriptome-based prediction of response to chemotherapy than would be possible using the original data or their principal components.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04339-6.

Dysregulation of ribosome-related genes in ankylosing spondylitis: a systems biology approach and experimental method

Background

Ankylosing spondylitis (AS) is an autoimmune rheumatic disease. Few candidate gene associations have been reported for AS and the current understanding of its pathogenesis remains still poor. Thus, the exact mechanism of AS is needed to urgently be disclosed. The purpose of this study was to identify candidate genes involving in AS disease.

Methods and results

GSE25101 publicly available microarray and GSE117769 RNA-seq datasets of AS patients were obtained for bioinformatics analyses. Gene set enrichment analysis showed that in the microarray dataset, the ribosome pathway was significantly up-regulated in AS compared with controls. Furthermore, some ribosomal components demonstrated overexpression in patients in the RNA-seq dataset. To confirm the findings, 20 AS patients and 20 matching controls were selected from the Rheumatology Research Center clinic, Shariati Hospital. PBMCs were separated from whole blood and RNA contents were extracted. Following the results of datasets analysis, the expression level of rRNA5.8S pseudogene, rRNA18S pseudogene, RPL23, RPL7, and RPL17 genes were measured through real-time PCR. Our findings showed dysregulation of rRNA5.8S and rRNA18S pseudogenes, and also the RPL17 gene in patients.

Conclusion

Considering that genes involved in ribosome biogenesis contributed to some AS-associated biological processes as well as diseases that have comorbidities with AS, our results might advance our understanding of the pathological mechanisms of ankylosing spondylitis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04662-2.

Effects of Cancer Presence and Therapy on the Platelet Proteome

Platelets are involved in tumor angiogenesis and cancer progression. Previous studies indicated that cancer could affect platelet content. In the current study, we investigated whether cancer-associated proteins can be discerned in the platelets of cancer patients, and whether antitumor treatment may affect the platelet proteome. Platelets were isolated from nine patients with different cancer types and ten healthy volunteers. From three patients, platelets were isolated before and after the start of antitumor treatment. Mass spectrometry-based proteomics of gel-fractionated platelet proteins were used to compare patients versus controls and before and after treatment initiation. A total of 4059 proteins were detected, of which 50 were significantly more abundant in patients, and 36 more in healthy volunteers. Eight of these proteins overlapped with our previous cancer platelet proteomics study. From these data, we selected potential biomarkers of cancer including six upregulated proteins (RNF213, CTSG, PGLYRP1, RPL8, S100A8, S100A9) and two downregulated proteins (GPX1, TNS1). Antitumor treatment resulted in increased levels of 432 proteins and decreased levels of 189 proteins. In conclusion, the platelet proteome may be affected in cancer patients and platelets are a potential source of cancer biomarkers. In addition, we found in a small group of patients that anticancer treatment significantly changes the platelet proteome.

Biomarker Categorization in Transcriptomic Meta-Analysis by Concordant Patterns With Application to Pan-Cancer Studies

With the increasing availability and dropping cost of high-throughput technology in recent years, many-omics datasets have accumulated in the public domain. Combining multiple transcriptomic studies on related hypothesis via meta-analysis can improve statistical power and reproducibility over single studies. For differential expression (DE) analysis, biomarker categorization by DE pattern across studies is a natural but critical task following biomarker detection to help explain between study heterogeneity and classify biomarkers into categories with potentially related functionality. In this paper, we propose a novel meta-analysis method to categorize biomarkers by simultaneously considering the concordant pattern and the biological and statistical significance across studies. Biomarkers with the same DE pattern can be analyzed together in downstream pathway enrichment analysis. In the presence of different types of transcripts (e.g., mRNA, miRNA, and lncRNA, etc.), integrative analysis including miRNA/lncRNA target enrichment analysis and miRNA-mRNA and lncRNA-mRNA causal regulatory network analysis can be conducted jointly on all the transcripts of the same category. We applied our method to two Pan-cancer transcriptomic study examples with single or multiple types of transcripts available. Targeted downstream analysis identified categories of biomarkers with unique functionality and regulatory relationships that motivate new hypothesis in Pan-cancer analysis.

DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism

Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives precise and efficient control for the translation process. There is mounting evidence for the important roles of this process in a variety of cellular events. Computational methods for mRNA subcellular localization prediction provide a useful approach for studying mRNA functions. However, few computational methods were designed for mRNA subcellular localization prediction and their performance have room for improvement. Especially, there is still no available tool to predict for mRNAs that have multiple localization annotations. In this paper, we propose a multi-head self-attention method, DM3Loc, for multi-label mRNA subcellular localization prediction. Evaluation results show that DM3Loc outperforms existing methods and tools in general. Furthermore, DM3Loc has the interpretation ability to analyze RNA-binding protein motifs and key signals on mRNAs for subcellular localization. Our analyses found hundreds of instances of mRNA isoform-specific subcellular localizations and many significantly enriched gene functions for mRNAs in different subcellular localizations.

Systematic integrated analyses of methylomic and transcriptomic impacts of early combined botanicals on estrogen receptor-negative mammary cancer

Dietary botanicals such as the cruciferous vegetable broccoli sprouts (BSp) as well as green tea polyphenols (GTPs) have shown exciting potential in preventing or delaying breast cancer (BC). However, little is known about their impact on epigenomic aberrations that are centrally involved in the initiation and progression of estrogen receptor-negative [ER(−)] BC. We have investigated the efficacy of combined BSp and GTPs diets on mammary tumor inhibition in transgenic Her2/neu mice that were administered the diets from prepubescence until adulthood. Herein, we present an integrated DNA methylome and transcriptome analyses for defining the early-life epigenetic impacts of combined BSp and GTPs on mammary tumors and our results indicate that a combinatorial administration of BSp and GTPs have a stronger impact at both transcriptome and methylome levels in comparison to BSp or GTPs administered alone. We also demonstrated a streamlined approach by performing an extensive preprocessing, quality assessment and downstream analyses on the genomic dataset. Our identification of differentially methylated regions in response to dietary botanicals administered during early-life will allow us to identify key genes and facilitate implementation of the subsequent downstream functional analyses on a genomic scale and various epigenetic modifications that are crucial in preventing ER(−) mammary cancer. Furthermore, our realtime PCR results were also found to be consistent with our genome-wide analysis results. These results could be exploited as a comprehensive resource for understanding understudied genes and their associated epigenetic modifications in response to these dietary botanicals.

Eukaryotic protein uS19: a component of the decoding site of ribosomes and a player in human diseases

Proteins belonging to the universal ribosomal protein (rp) uS19 family are constituents of small ribosomal subunits, and their conserved globular parts are involved in the formation of the head of these subunits. The eukaryotic rp uS19 (previously known as S15) comprises a C-terminal extension that has no homology in the bacterial counterparts. This extension is directly implicated in the formation of the ribosomal decoding site and thereby affects translational fidelity in a manner that has no analogy in bacterial ribosomes. Another eukaryote-specific feature of rp uS19 is its essential participance in the 40S subunit maturation due to the interactions with the subunit assembly factors required for the nuclear exit of pre-40S particles. Beyond properties related to the translation machinery, eukaryotic rp uS19 has an extra-ribosomal function concerned with its direct involvement in the regulation of the activity of an important tumor suppressor p53 in the Mdm2/Mdmx-p53 pathway. Mutations in the RPS15 gene encoding rp uS19 are linked to diseases (Diamond Blackfan anemia, chronic lymphocytic leukemia and Parkinson's disease) caused either by defects in the ribosome biogenesis or disturbances in the functioning of ribosomes containing mutant rp uS19, likely due to the changed translational fidelity. Here, we review currently available data on the involvement of rp uS19 in the operation of the translational machinery and in the maturation of 40S subunits, on its extra-ribosomal function, and on relationships between mutations in the RPS15 gene and certain human diseases.

Small nucleolar RNA and its potential role in breast cancer - A comprehensive review

Small Nucleolar RNAs (snoRNAs) are known for their canonical functions, including ribosome biogenesis and RNA modification. snoRNAs act as endogenous sponges that regulate miRNA expression. Thus, precise snoRNA expression is critical for fine-tuning miRNA expression. snoRNAs processed into miRNA-like sequences play a crucial role in regulating the expression of protein-coding genes similar to that of miRNAs. Recent studies have linked snoRNA deregulation to breast cancer (BC). Inappropriate snoRNA expression contributes to BC pathology by facilitating breast cells to acquire cancer hallmarks. Since snoRNAs show significant differential expression in normal and cancer conditions, measuring snoRNA levels could be useful for BC prognosis and diagnosis. The present article provides a comprehensive overview of the role of snoRNAs in breast cancer pathology. More specifically, we have discussed the regulation, biological function, signaling pathways, and clinical utility of abnormally expressed snoRNAs in BC. Besides, we have also discussed the role of snoRNA host genes in breast tumorigenesis and emerging and future research directions in the field of snoRNA and cancer.

Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

Sequence variation, common tissue expression patterns and learning models: a genome-wide survey of vertebrate ribosomal proteins

Ribosomal genes produce the constituents of the ribosome, one of the most conserved subcellular structures of all cells, from bacteria to eukaryotes, including animals. There are notions that some protein-coding ribosomal genes vary in their roles across species, particularly vertebrates, through the involvement of some in a number of genetic diseases. Based on extensive sequence comparisons and systematic curation, we establish a reference set for ribosomal proteins (RPs) in eleven vertebrate species and quantify their sequence conservation levels. Moreover, we correlate their coordinated gene expression patterns within up to 33 tissues and assess the exceptional role of paralogs in tissue specificity. Importantly, our analysis supported by the development and use of machine learning models strongly proposes that the variation in the observed tissue-specific gene expression of RPs is rather species-related and not due to tissue-based evolutionary processes. The data obtained suggest that RPs exhibit a complex relationship between their structure and function that broadly maintains a consistent expression landscape across tissues, while most of the variation arises from species idiosyncrasies. The latter may be due to evolutionary change and adaptation, rather than functional constraints at the tissue level throughout the vertebrate lineage.

Ribosomal Protein L10: From Function to Dysfunction

Eukaryotic cytoplasmic ribosomes are highly structured macromolecular complexes made up of four different ribosomal RNAs (rRNAs) and 80 ribosomal proteins (RPs), which play a central role in the decoding of genetic code for the synthesis of new proteins. Over the past 25 years, studies on yeast and human models have made it possible to identify RPL10 (ribosomal protein L10 gene), which is a constituent of the large subunit of the ribosome, as an important player in the final stages of ribosome biogenesis and in ribosome function. Here, we reviewed the literature to give an overview of the role of RPL10 in physiologic and pathologic processes, including inherited disease and cancer.

Moonlight human ribosomal protein L13a downregulation is associated with p53 and HER2/neu expression in breast cancer

Breast cancer is the most common malignancy among females worldwide. Recent studies have shown extra-ribosomal roles of the moonlight ribosomal proteins in the development of human cancers. Accurate quantification of the gene expression level is based on the selection of the reference genes whose expression is independent of cancer properties and patient's characteristics. The aim of this study was the evaluation of the expression level of a previously proposed ribosomal protein as moonlight, L13a (RPL13A), in breast cancer samples and their adjacent tissues. Its association with genes of known roles in developing cancers was also investigated. Traditionally used housekeeping genes were selected and their expression was analyzed in 80 surgically excised breast tissue specimens (40 tumors and 40 tumor-adjacent tissues) by applying three software tools including GeNorm, NormFinder, and BestKeeper to select the most stable reference genes. Then, mRNA expression levels of RPL13A and p53 were evaluated. Additionally, protein expression levels of RPL13A were measured. It was demonstrated that PUM1 and ACTB are the most reliable reference genes and RPL13A is the least stable gene. There was a positive correlation between RPL13A and p53 mRNA expression levels in all the tumor samples. Moreover, significant downregulation of RPL13A expression levels was revealed in HER2+ tumor samples compared to HER2- ones. There was also a marked decrease in p53 mRNA expression levels in HER2+ tumor subtypes. Our results suggest that there is a probable relationship between RPL13A decreased expression with p53 and HER2/neu expression in the breast cancer.

Ribosomes as a nexus between translation and cancer progression: Focus on ribosomal Receptor for Activated C Kinase 1 (RACK1) in breast cancer

Ribosomes coordinate spatiotemporal control of gene expression, contributing to the acquisition and maintenance of cancer phenotype. The link between ribosomes and cancer is found in the roles of individual ribosomal proteins in tumorigenesis and cancer progression, including the ribosomal protein, receptor for activated C kinase 1 (RACK1). RACK1 regulates cancer cell invasion and is localized in spreading initiation centres, structural adhesion complexes containing RNA binding proteins and poly-adenylated mRNAs that suggest a local translation process. As RACK1 is a ribosomal protein directly involved in translation and in breast cancer progression, we propose a new molecular mechanism for breast cancer cell migration and invasion, which considers the molecular differences between epithelial and mesenchymal cell profiles in order to characterize and provide novel targets for therapeutic strategies. Hence, we provide an analysis on how ribosomes translate cancer progression with a final focus on the ribosomal protein RACK1 in breast cancer.

Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples

We give results from a detailed analysis of human Ribosomal Protein (RP) levels in normal and cancer samples and cell lines from large mRNA, copy number variation and ribosome profiling datasets. After normalizing total RP mRNA levels per sample, we find highly consistent tissue specific RP mRNA signatures in normal and tumor samples. Multiple RP mRNA-subtypes exist in several cancers, with significant survival and genomic differences. Some RP mRNA variations among subtypes correlate with copy number loss of RP genes. In kidney cancer, RP subtypes map to molecular subtypes related to cell-of-origin. Pan-cancer analysis of TCGA data showed widespread single/double copy loss of RP genes, without significantly affecting survival. In several cancer cell lines, CRISPR-Cas9 knockout of RP genes did not affect cell viability. Matched RP ribosome profiling and mRNA data in humans and rodents stratified by tissue and development stage and were strongly correlated, showing that RP translation rates were proportional to mRNA levels. In a small dataset of human adult and fetal tissues, RP protein levels showed development stage and tissue specific heterogeneity of RP levels. Our results suggest that heterogeneous RP levels play a significant functional role in cellular physiology, in both normal and disease states.

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers

Background

Long-term survival in numerous cancers often correlates with specific whole transcriptome profiles or the expression patterns of smaller numbers of transcripts. In some instances, these are better predictors of survival than are standard classification methods such as clinical stage or hormone receptor status in breast cancer. Here, we have used the method of “t-distributed stochastic neighbor embedding” (t-SNE) to show that, collectively, the expression patterns of small numbers of functionally-related transcripts from fifteen cancer pathways correlate with long-term survival in the vast majority of tumor types from The Cancer Genome Atlas (TCGA). We then ask whether the sequential application of t-SNE using the transcripts from a second pathway improves predictive capability or whether t-SNE can be used to refine the initial predictive power of whole transcriptome profiling.

Methods

RNAseq data from 10,227 tumors in TCGA were previously analyzed using t-SNE-based clustering of 362 transcripts comprising 15 distinct cancer-related pathways. After showing that certain clusters were associated with differential survival, each relevant cluster was re-analyzed by t-SNE with a second pathway’s transcripts. Alternatively, groups with differential survival identified by whole transcriptome profiling were subject to a second, t-SNE-based analysis.

Results

Sequential analyses employing either t-SNE➔t-SNE or whole transcriptome profiling➔t-SNE analyses were in many cases superior to either individual method at predicting long-term survival. We developed a dynamic and intuitive R Shiny web application to explore the t-SNE based transcriptome clustering and survival analysis across all TCGA cancers and all 15 cancer-related pathways in this analysis. This application provides a simple interface to select specific t-SNE clusters and analyze survival predictability using both individual or sequential approaches. The user can recreate the relationships described in this analysis and further explore many different cancer, pathway, and cluster combinations. Non-R users can access the application on the web at https://chpupsom19.shinyapps.io/Survival_Analysis_tsne_umap_TCGA. The application, R scripts performing survival analysis, and t-SNE clustering results of TCGA expression data can be accessed on GitHub enabling users to download and run the application locally with ease (https://github.com/RavulaPitt/Sequential-t-SNE/).

Conclusions

The long-term survival of patients correlated with expression patterns of 362 transcripts from 15 cancer-related pathways. In numerous cases, however, survival could be further improved when the cohorts were re-analyzed using iterative t-SNE clustering or when t-SNE clustering was applied to cohorts initially segregated by whole transcriptome-based hierarchical clustering.

Loss of Estrogen Receptors is Associated with Increased Tumor Aggression in Laryngeal Squamous Cell Carcinoma

Laryngeal squamous cell carcinoma (LSCC) responds to 17β-estradiol via estrogen-receptor (ER, transcribed from ESR1) dependent mechanisms, but is not recognized as a hormonally responsive cancer. 17β-estradiol production by LSCC cell lines UM-SCC-11A and UM-SCC-12 was examined. Wild type (WT) and ESR1-silenced LSCC cultures and xenografts were examined for 17β-estradiol responsiveness in vivo. 14 LSCC and surrounding epithelial samples at various pathological stages were obtained from patients; ERα and ERβ expression were verified using data from the total cancer genome atlas. UM-SCC-11A and UM-SCC-12 both produce 17β-estradiol, but only UM-SCC-12, not UM-SCC-11A, xenograft tumors grow larger in vivo in response to systemic 17β-estradiol treatments. ERα66 and ERα36 expression inversely correlated with clinical cancer stage and tumor burden. LSCC ERα66 expression was higher compared to surrounding epithelia in indolent samples but lower in aggressive LSCC. ERβ expression was highly variable. High ESR1 expression correlated with improved survival in LSCC. Loss of ERα66 expression inversely correlated with prognosis in LSCC. ERα66 may be a histopathological marker of aggression in LSCC.

Identification of key regulators in prostate cancer from gene expression datasets of patients

Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k ≥ 65) were selected from the PCa network, traced, and 19 of them was identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism.

β-Catenin mutations as determinants of hepatoblastoma phenotypes in mice

Hepatoblastoma (HB) is the most common pediatric liver cancer. Although long-term survival of HB is generally favorable, it depends on clinical stage, tumor histology, and a variety of biochemical and molecular features. HB appears almost exclusively before the age of 3 years, is represented by seven histological subtypes, and is usually associated with highly heterogeneous somatic mutations in the catenin β1 (CTNNB1) gene, which encodes β-catenin, a Wnt ligand-responsive transcriptional co-factor. Numerous recurring β-catenin mutations, not previously documented in HB, have also been identified in various other pediatric and adult cancer types. Little is known about the underlying factors that determine the above HB features and behaviors or whether non-HB-associated β-catenin mutations are tumorigenic when expressed in hepatocytes. Here, we investigated the oncogenic properties of 14 different HB- and non-HB-associated β-catenin mutants encoded by Sleeping Beauty vectors following their delivery into the mouse liver by hydrodynamic tail-vein injection. We show that all β-catenin mutations, as well as WT β-catenin, are tumorigenic when co-expressed with a mutant form of yes-associated protein (YAP). However, tumor growth rates, histologies, nuclear-to-cytoplasmic partitioning, and metabolic and transcriptional landscapes were strongly influenced by the identities of the β-catenin mutations. These findings provide a context for understanding at the molecular level the notable biological diversity of HB.

Comprehensive characterization of the rRNA metabolism-related genes in human cancer

Although rRNA metabolism-related genes have been reported to be associated with human cancer, a systematic assessment of rRNA metabolism-related genes across human cancers is lacking. Thus, we performed a Pan-cancer analysis of rRNA metabolism-related genes across 20 human cancers. Here, we examined mRNA expression, mutation, DNA methylation, copy number variation (CNV) and clinical landscape of rRNA metabolism-related genes in more than 8600 patients across 20 human cancers from The Cancer Genome Atlas (TCGA) dataset. Besides, ten independent Gene Expression Omnibus (GEO) datasets, Cancer Cell Line Encyclopedia (CCLE) dataset and Project Achilles dataset were used to verify our study. A landscape of rRNA metabolism-related genes was established across 20 human cancers. The results suggest that rRNA metabolism-related genes are upregulated in multiple cancers, particularly in digestive and respiratory system cancers. Most of the upregulated genes were driven by CNV gain rather than mutation or DNA hypomethylation. We systematically identified CNV-driven rRNA metabolism-related genes with clinical relevance, including EXOSC8. Finally, functional experiments confirmed the oncogenic roles of EXOSC8 in colorectal carcinoma. Our study highlights the important roles of rRNA metabolism-related genes in tumorigenesis as prognostic biomarkers.

Evaluation and Validation of Reference Genes for Quantitative Real-Time PCR in Helopeltis theivora Waterhouse (Hemiptera: Miridae)

Helopeltis theivora Waterhouse is a predominant sucking pest in many tropic economic crops, such as tea, cocoa and coffee. Quantitative real-time PCR (qRT-PCR) is one of the most powerful tools to analyze the gene expression level and investigate the mechanism of insect physiology at transcriptional level. Gene expression studies utilizing qRT-PCR have been applied to numerous insects so far. However, no universal reference genes could be used for H. theivora. To obtain accurate and reliable normalized data in H. theivora, twelve candidate reference genes were examined under different tissues, developmental stages and sexes by using geNorm, NormFinder, BestKeeper, Delta Ct and RefFinder algorithms, respectively. The results revealed that the ideal reference genes differed across the treatments, and the consensus rankings generated from stability values provided by these programs suggested a combination of two genes for normalization. To be specific, RPS3A and Actin were the best suitable reference genes for tissues, RPL13A and GAPDH were suitable for developmental stages, EF1α and RPL13A were suitable for sexes, and RPL13A and RPS3A were suitable for all samples. This study represents the first systematic analysis of reference genes for qRT-PCR experiments in H. theivora, and the results can provide a credible normalization for qRT-PCR data, facilitating transcript profiling studies of functional genes in this insect.

Expression patterns of small numbers of transcripts from functionally-related pathways predict survival in multiple cancers

BACKGROUND

Genetic profiling of cancers for variations in copy number, structure or expression of certain genes has improved diagnosis, risk-stratification and therapeutic decision-making. However the tumor-restricted nature of these changes limits their application to certain cancer types or sub-types. Tests with broader prognostic capabilities are lacking.

METHODS

Using RNAseq data from 10,227 tumors in The Cancer Genome Atlas (TCGA), we evaluated 212 protein-coding transcripts from 12 cancer-related pathways. We employed t-distributed stochastic neighbor embedding (t-SNE) to identify expression pattern difference among each pathway's transcripts. We have previously used t-SNE to show that survival in some cancers correlates with expression patterns of transcripts encoding ribosomal proteins and enzymes for cholesterol biosynthesis and fatty acid oxidation.

RESULTS

Using the above 212 transcripts, t-SNE-assisted transcript pattern profiling identified patient cohorts with significant survival differences in 30 of 34 different cancer types comprising 9350 tumors (91.4% of all TCGA cases). Small subsets of each pathway's transcripts, comprising no more than 50-60 from the original group, played particularly prominent roles in determining overall t-SNE patterns. In several cases, further refinements in long-term survival could be achieved by sequential t-SNE profiling with two pathways' transcripts, by a combination of t-SNE plus whole transcriptome profiling or by employing t-SNE on immuno-histochemically defined breast cancer subtypes. In two cancer types, individuals with Stage IV disease at presentation could be readily subdivided into groups with highly significant survival differences based on t-SNE-based tumor sub-classification.

CONCLUSIONS

t-SNE-assisted profiling of a small number of transcripts allows the prediction of long-term survival across multiple cancer types.

Inhibition of hepatocellular carcinoma by metabolic normalization

In two different mouse liver cancer models, we recently showed that a switch from oxidative phosphorylation (Oxphos) to glycolysis (the Warburg effect) is invariably accompanied by a marked decline in fatty acid oxidation (FAO) and a reciprocal increase in the activity of pyruvate dehydrogenase (PDH), which links glycolysis to the TCA cycle. We now show that short-term implementation of either medium-chain (MC) or long-chain (LC) high fat diets (HFDs) nearly doubled the survival of mice with c-Myc oncoprotein-driven hepatocellular carcinoma (HCC). Mechanistically, HFDs forced tumors to become more reliant on fatty acids as an energy source, thus normalizing both FAO and PDH activities. More generally, both MC- and LC-HFDs partially or completely normalized the expression of 682 tumor-dysregulated transcripts, a substantial fraction of which are involved in cell cycle control, proliferation and metabolism. That these same transcripts were responsive to HFDs in livers strongly suggested that the changes were the cause of tumor inhibition rather than its consequence. In seven different human cancer cohorts, patients with tumors containing high ratios of FAO-related:glycolysis-related transcripts had prolonged survival relative to those with low ratios. Furthermore, in 13 human cancer types, the expression patterns of transcripts encoding enzymes participating in FAO and/or cholesterol biosynthesis also correlated with significantly prolonged survival. Collectively, our results support the idea that the survival benefits of HFDs are due to a reversal of the Warburg effect and other tumor-associated metabolic and cell cycle abnormalities. They also suggest that short-term dietary manipulation, either alone or in combination with more traditional chemotherapeutic regimens, might be employed as a relatively non-toxic and cost-effective means of enhancing survival in certain cancer types.

Displacement of WDR5 from Chromatin by a WIN Site Inhibitor with Picomolar Affinity

The chromatin-associated protein WDR5 is a promising target for pharmacological inhibition in cancer. Drug discovery efforts center on the blockade of the "WIN site" of WDR5, a well-defined pocket that is amenable to small molecule inhibition. Various cancer contexts have been proposed to be targets for WIN site inhibitors, but a lack of understanding of WDR5 target genes and of the primary effects of WIN site inhibitors hampers their utility. Here, by the discovery of potent WIN site inhibitors, we demonstrate that the WIN site links WDR5 to chromatin at a small cohort of loci, including a specific subset of ribosome protein genes. WIN site inhibitors rapidly displace WDR5 from chromatin and decrease the expression of associated genes, causing translational inhibition, nucleolar stress, and p53 induction. Our studies define a mode by which WDR5 engages chromatin and forecast that WIN site blockade could have utility against multiple cancer types.

The roles of moonlight ribosomal proteins in the development of human cancers

"Moonlighting protein" is a term used to define a single protein with multiple functions and different activities that are not derived from gene fusions, multiple RNA splicing, or the proteolytic activity of promiscuous enzymes. Different proteinous constituents of ribosomes have been shown to have important moonlighting extra-ribosomal functions. In this review, we introduce the impact of key moonlight ribosomal proteins and dependent signal transduction in the initiation and progression of various cancers. As a future perspective, the potential role of these moonlight ribosomal proteins in the diagnosis, prognosis, and development of novel strategies to improve the efficacy of therapies for human cancers has been suggested.

The nucleolus, an ally, and an enemy of cancer cells

The rates of ribosome production by a nucleolus and of protein biosynthesis by ribosomes are tightly correlated with the rate of cell growth and proliferation. All these processes must be matched and appropriately regulated to provide optimal cell functioning. Deregulation of certain factors, including oncogenes, controlling these processes, especially ribosome biosynthesis, can lead to cell transformation. Cancer cells are characterized by intense ribosome biosynthesis which is advantageous for their growth and proliferation. On the other hand, this feature can be engaged as an anticancer strategy. Numerous nucleolar factors such as nucleolar and ribosomal proteins as well as different RNAs, in addition to their role in ribosome biosynthesis, have other functions, including those associated with cancer biology. Some of them can contribute to cell transformation and cancer development. Others, under stress evoked by different factors which often hamper function of nucleoli and thus induce nucleolar/ribosomal stress, can participate in combating cancer cells. In this sense, intentional application of therapeutic agents affecting ribosome biosynthesis can cause either release of these molecules from nucleoli or their de novo biosynthesis to mediate the activation of pathways leading to elimination of harmful cells. This review underlines the role of a nucleolus not only as a ribosome constituting apparatus but also as a hub of both positive and negative control of cancer development. The article is mainly based on original papers concerning mechanisms in which the nucleolus is implicated directly or indirectly in processes associated with neoplasia.