Methylomics of breast cancer: Seeking epimarkers in peripheral blood of young subjects

A Rab-bit hole: Rab40 GTPases as new regulators of the actin cytoskeleton and cell migration

The regulation of machinery involved in cell migration is vital to the maintenance of proper organism function. When migration is dysregulated, a variety of phenotypes ranging from developmental disorders to cancer metastasis can occur. One of the primary structures involved in cell migration is the actin cytoskeleton. Actin assembly and disassembly form a variety of dynamic structures which provide the pushing and contractile forces necessary for cells to properly migrate. As such, actin dynamics are tightly regulated. Classically, the Rho family of GTPases are considered the major regulators of the actin cytoskeleton during cell migration. Together, this family establishes polarity in the migrating cell by stimulating the formation of various actin structures in specific cellular locations. However, while the Rho GTPases are acknowledged as the core machinery regulating actin dynamics and cell migration, a variety of other proteins have become established as modulators of actin structures and cell migration. One such group of proteins is the Rab40 family of GTPases, an evolutionarily and functionally unique family of Rabs. Rab40 originated as a single protein in the bilaterians and, through multiple duplication events, expanded to a four-protein family in higher primates. Furthermore, unlike other members of the Rab family, Rab40 proteins contain a C-terminally located suppressor of cytokine signaling (SOCS) box domain. Through the SOCS box, Rab40 proteins interact with Cullin5 to form an E3 ubiquitin ligase complex. As a member of this complex, Rab40 ubiquitinates its effectors, controlling their degradation, localization, and activation. Because substrates of the Rab40/Cullin5 complex can play a role in regulating actin structures and cell migration, the Rab40 family of proteins has recently emerged as unique modulators of cell migration machinery.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

A methylomics-associated nomogram predicts the overall survival risk of stage III to IV ovarian cancer

Accumulating studies demonstrated that DNA methylation may be potential prognostic hallmarks of various cancers. However, few studies have focused on the power of DNA methylation for prognostic prediction in patients with stage III to IV ovarian cancer (OC). Therefore, constructing a methylomics-related indicator to predict overall survival (OS) of stage III to IV OC was urgently required. A total of 520 OC patients with 485,577 DNA methylation sites from TCGA database were selected to develop a robust DNA methylation signature. The 520 patients were clustered into a training group (70%, n = 364 samples) and an internal validation group (30%, n = 156). The training group was used for digging a prognostic predictor based on univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) as well as multivariate Cox regression analysis. The internal and external validation group (ICGC OV-AU project) were used for validating the predictive robustness of the predictor based on receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis. We identified a 21-DNA methylation signature-based classifier for stage III-IV OC patients' OS. According to ROC analysis in the internal validation, external validation and entire TCGA set, we proved the high power of the 21-DNA methylation signature for predicting OS (area under the curve [AUC] at 1, 3, 5 years in internal validation set (0.782, 0.739, 0.777, respectively), external validation set (0.828, 0.760, 0.741, respectively), entire TCGA set (0.741, 0.748, 0.781, respectively). Besides, a nomogram was developed via methylation risk score as well as a few clinical variables, and the result showed a high ability of the predictive nomogram. In summary, we used integrated bioinformatics approaches to successfully identified a DNA methylation-associated nomogram, which can predict effectively the OS of patients with stage III to IV OC.

An Integrative Analysis Identifying RAB40C as an Oncogenic Immune Protein and Prognostic Marker of Lung Squamous Cell Carcinoma

Background

RAB40C, a member of the Ras oncogene family, is a protein with GTPase and GTP-binding activity and is also predicted to be important in immunomodulation. However, the link between RAB40C and lung squamous cell carcinoma (LUSC) has not yet been elucidated. Exploring the relationship between RAB40C and LUSC could help expand the repertoire of immunotherapeutic targets for LUSC and provide more effective therapeutic options for LUSC patients, which behalf of our aim for our study.

Methods

We analyzed the RAB40C expression in different tumor types and stages based on the TCGA database. Subsequently, we explored the differences in RAB40C expression in LUSC versus paracancerous tissues through immunohistochemical analysis. The prognostic value of RAB40C was assessed by Cox regression and Kaplan-Meier analysis. Gene set enrichment analysis-based RAB40C impact pathways and the correlation between RAB40C expression and immune infiltration were obtained using the TIMER2.0 and the CIBERSORT analytical tools. Tumor mutational load and microsatellite instability (MSI) were assessed by the Spearman correlation analysis. Finally, the close association of RAB40C with LUSC was explored by correlating immune cell infiltration with immunomodulator expression, assessing risk scores in combination with other factors, and analyzing prognostic nomogram.

Results

The expression of RAB40C was significantly elevated in LUSC. RAB40C expression was significantly associated with immune factors, immune-related pathways, and MSI. Moreover, RAB40C significantly negatively correlated with LUSC-associated immune infiltrating cells, CD4 memory-activated cells, γδ T cells, M1-like macrophages, and the immune regulator CD28, while it positively associated with the activation of Tregs and natural killer cells. Further, a risk model constructed from RAB40C and its associated immune genes showed that RAB40C might be an independent prognostic factor for LUSC.

Conclusion

RAB40C can be used as an effective prognostic biomarker and a potential immunotherapeutic target for the treatment of LUSC.

Prediagnostic breast milk DNA methylation alterations in women who develop breast cancer

Prior candidate gene studies have shown tumor suppressor DNA methylation in breast milk related with history of breast biopsy, an established risk factor for breast cancer. To further establish the utility of breast milk as a tissue-specific biospecimen for investigations of breast carcinogenesis, we measured genome-wide DNA methylation in breast milk from women with and without a diagnosis of breast cancer in two independent cohorts. DNA methylation was assessed using Illumina HumanMethylation450k in 87 breast milk samples. Through an epigenome-wide association study we explored CpG sites associated with a breast cancer diagnosis in the prospectively collected milk samples from the breast that would develop cancer compared with women without a diagnosis of breast cancer using linear mixed effects models adjusted for history of breast biopsy, age, RefFreeCellMix cell estimates, time of delivery, array chip and subject as random effect. We identified 58 differentially methylated CpG sites associated with a subsequent breast cancer diagnosis (q-value <0.05). Nearly all CpG sites associated with a breast cancer diagnosis were hypomethylated in cases compared with controls and were enriched for CpG islands. In addition, inferred repeat element methylation was lower in breast milk DNA from cases compared to controls, and cases exhibited increased estimated epigenetic mitotic tick rate as well as DNA methylation age compared with controls. Breast milk has utility as a biospecimen for prospective assessment of disease risk, for understanding the underlying molecular basis of breast cancer risk factors and improving primary and secondary prevention of breast cancer.

Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response

The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.

Development and validation of the first consensus gene-expression signature of operational tolerance in kidney transplantation, incorporating adjustment for immunosuppressive drug therapy

BACKGROUND

Kidney transplant recipients (KTRs) with "operational tolerance" (OT) maintain a functioning graft without immunosuppressive (IS) drugs, thus avoiding treatment complications. Nevertheless, IS drugs can influence gene-expression signatures aiming to identify OT among treated KTRs.

METHODS

We compared five published signatures of OT in peripheral blood samples from 18 tolerant, 183 stable, and 34 chronic rejector KTRs, using gene-expression levels with and without adjustment for IS drugs and regularised logistic regression.

FINDINGS

IS drugs explained up to 50% of the variability in gene-expression and 20-30% of the variability in the probability of OT predicted by signatures without drug adjustment. We present a parsimonious consensus gene-set to identify OT, derived from joint analysis of IS-drug-adjusted expression of five published signature gene-sets. This signature, including CD40, CTLA4, HSD11B1, IGKV4-1, MZB1, NR3C2, and RAB40C genes, showed an area under the curve 0⋅92 (95% confidence interval 0⋅88-0⋅94) in cross-validation and 0⋅97 (0⋅93-1⋅00) in six months follow-up samples.

INTERPRETATION

We advocate including adjustment for IS drug therapy in the development stage of gene-expression signatures of OT to reduce the risk of capturing features of treatment, which could be lost following IS drug minimisation or withdrawal. Our signature, however, would require further validation in an independent dataset and a biomarker-led trial.

FUNDING

FP7-HEALTH-2012-INNOVATION-1 [305147:BIO-DrIM] (SC,IR-M,PM,DSt); MRC [G0801537/ID:88245] (MPH-F); MRC [MR/J006742/1] (IR-M); Guy's&StThomas' Charity [R080530]&[R090782]; CONICYT-Bicentennial-Becas-Chile (EN-L); EU:FP7/2007-2013 [HEALTH-F5-2010-260687: The ONE Study] (MPH-F); Czech Ministry of Health [NV19-06-00031] (OV); NIHR-BRC Guy's&StThomas' NHS Foundation Trust and KCL (SC); UK Clinical Research Networks [portfolio:7521].

Investigation of promoter methylation of MCPH1 gene in circulating cell-free DNA of brain tumor patients

INTRODUCTION

Despite advanced diagnostic and therapeutic techniques, many brain tumors are still diagnosed at high grades and, therefore finding novel molecular markers may assist in early detection and reducing brain tumors-related mortality rate. Owing to the previous reports on the importance of MCPH1 gene in tumorigenesis, the present study was aimed to study the promoter methylation of MCPH1 gene in paired circulating cell-free DNA (cfDNA) and tumor tissues of brain tumor patients.

MATERIALS AND METHODS

Fourteen fresh paired serum and tumor tissue samples in addition to 18 isolated serum samples were collected from patients affected by different grades of brain tumor. Genomic DNA and cfDNA was isolated from tissue and serum samples using QIAamp DNA Mini Kit Norgen Bioteck Kit, respectively. Methylation DNA immunoprecipitation Real-time polymerization chain reaction (MeDIP-Real-time PCR) was performed on isolated DNA samples using EpiQuik MeDIP Ultra Kit and specific primer pairs. cfDNA quantity was determined through Real-time PCR analysis using specific primer pairs designed for GAPDH gene.

RESULTS

MCPH1 was methylated in 54% of cfDNA samples which was significantly associated with tumor grade, as well (P-value = 0.02). The methylation rate of MCPH1 was found as 78% in the tissue samples which was meaningfully associated with tumor grade (P-value = 0.03). Moreover, methylation of the MCPH1 gene was consistent in 57% of the same cfDNA and tissue samples. Methylation of MCPH1 gene in neither tumor tissues nor cfDNA was not correlated with age and sex of the patients.

DISCUSSION AND CONCLUSION

Due to the conformity of methylation of MCPH1 gene in cfDNA and tissue samples in more than half of the enrolled patients, especially in higher grades of tumors, it seems that MCPH1 promoter methylation could be a potential epimarker in not only detection of brain tumors but also in response to chemo- and radiotherapy which warranted further assessment.

Expression levels of breast cancer-related GAS5 and LSINCT5 lncRNAs in cancer-free breast tissue: Molecular associations with age at menarche and obesity

Long noncoding RNAs (lncRNAs) constitute a major class of the human transcriptome which play crucial roles in the key biological processes of both normal and malignant breast cells. Although the aberrant expression of lncRNAs has been well-documented in breast cancer (BC), little is currently known about the association between their expression levels in the breast tissue of healthy women and BC risk factors, especially the reproductive or demographic characteristics that are among the most well-known BC risk modifiers. This study was an attempt to investigate the correlation between the expression levels of 2 breast cancer-related lncRNAs, including GAS5 and LSINCT5, and reproductive and demographic characteristics in 145 normal breast tissues that were obtained from women without breast cancer undergoing cosmetic surgery. Total RNA was extracted from fresh normal breast tissues, and the expression level of target lncRNAs was quantified using real-time qPCR. Differences in the mean normalized gene expression among the subgroups of different variables were analyzed. The expression levels of both genes was lower in the overweight-obese (BMI ≥ 25) subgroup than that in the normal BMI (BMI < 25) subgroup (GAS5 P = .019, LSINCT5 P = .036). Moreover, the expression level of GAS5 was negatively correlated with BMI (r: -.170, P: .041). The expression level of GAS5 was higher in women with late menarche (>13 years) than that with early menarche (≤13 years; P = .017). These findings may assist to obtain insights into the molecular mechanisms through which the reproductive or obesity-related estrogen changes contribute to the breast carcinogenesis. In conclusion, this study presents the first evidence for the presence of a link between the lncRNA expression and the reproductive or obesity related factors in the breast tissue of healthy women.