Landscape of genome-wide age-related DNA methylation in breast tissue

Non-coding 886 (nc886/vtRNA2-1), the epigenetic odd duck - implications for future studies

Non-coding 886 (nc886, vtRNA2-1) is the only human polymorphically imprinted gene, in which the methylation status is not determined by genetics. Existing literature regarding the establishment, stability and consequences of the methylation pattern, as well as the nature and function of the nc886 RNAs transcribed from the locus, are contradictory. For example, the methylation status of the locus has been reported to be stable through life and across somatic tissues, but also susceptible to environmental effects. The nature of the produced nc886 RNA(s) has been redefined multiple times, and in carcinogenesis, these RNAs have been reported to have conflicting roles. In addition, due to the bimodal methylation pattern of the nc886 locus, traditional genome-wide methylation analyses can lead to false-positive results, especially in smaller datasets. Herein, we aim to summarize the existing literature regarding nc886, discuss how the characteristics of nc886 give rise to contradictory results, as well as to reinterpret, reanalyse and, where possible, replicate the results presented in the current literature. We also introduce novel findings on how the distribution of the nc886 methylation pattern is associated with the geographical origins of the population and describe the methylation changes in a large variety of human tumours. Through the example of this one peculiar genetic locus and RNA, we aim to highlight issues in the analysis of DNA methylation and non-coding RNAs in general and offer our suggestions for what should be taken into consideration in future analyses.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

A novel approach toward optimal workflow selection for DNA methylation biomarker discovery

DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.

Promoter hypermethylation of RARB and GSTP1 genes in plasma cell-free DNA as breast cancer biomarkers in Peruvian women

BACKGROUND

Promoter hypermethylation is one of the enabling mechanisms of hallmarks of cancer. Tumor suppressor genes like RARB and GSTP1 have been reported as hypermethylated in breast cancer tumors compared with normal tissues in several populations. This case-control study aimed to determine the association between the promoter methylation ratio (PMR) of RARB and GSTP1 genes (separately and as a group) with breast cancer and its clinical-pathological variables in Peruvian patients, using a liquid biopsy approach.

METHODS

A total of 58 breast cancer patients and 58 healthy controls, matched by age, participated in the study. We exacted cell-free DNA (cfDNA) from blood plasma and converted it by bisulfite salts. Methylight PCR was performed to obtain the PMR value of the studied genes. We determined the association between PMR and breast cancer, in addition to other clinicopathological variables. The sensitivity and specificity of the PMR of these genes were obtained.

RESULTS

A significant association was not found between breast cancer and the RARB PMR (OR = 1.90; 95% CI [0.62-6.18]; p = 0.210) or the GSTP1 PMR (OR = 6.57; 95% CI [0.75-307.66]; p = 0.114). The combination of the RARB + GSTP1 PMR was associated with breast cancer (OR = 2.81; 95% CI [1.02-8.22]; p = 0.026), controls under 50 years old (p = 0.048), patients older than 50 (p = 0.007), and postmenopausal (p = 0.034). The PMR of both genes showed a specificity of 86.21% and a sensitivity of 31.03%.

CONCLUSION

Promoter hypermethylation of RARB + GSTP1 genes is associated with breast cancer, older age, and postmenopausal Peruvian patients. The methylated promoter of the RARB + GSTP1 genes needs further validation to be used as a biomarker for liquid biopsy and as a recommendation criterion for additional tests in asymptomatic women younger than 50 years.

Loss of epigenetic suppression of retrotransposons with oncogenic potential in aging mammary luminal epithelial cells

A primary function of DNA methylation in mammalian genomes is to repress transposable elements (TEs). The widespread methylation loss that is commonly observed in cancer cells results in the loss of epigenetic repression of TEs. The aging process is similarly characterized by changes to the methylome. However, the impact of these epigenomic alterations on TE silencing and the functional consequences of this have remained unclear. To assess the epigenetic regulation of TEs in aging, we profiled DNA methylation in human mammary luminal epithelial cells (LEps)-a key cell lineage implicated in age-related breast cancers-from younger and older women. We report here that several TE subfamilies function as regulatory elements in normal LEps, and a subset of these display consistent methylation changes with age. Methylation changes at these TEs occurred at lineage-specific transcription factor binding sites, consistent with loss of lineage specificity. Whereas TEs mainly showed methylation loss, CpG islands (CGIs) that are targets of the Polycomb repressive complex 2 (PRC2) show a gain of methylation in aging cells. Many TEs with methylation loss in aging LEps have evidence of regulatory activity in breast cancer samples. We furthermore show that methylation changes at TEs impact the regulation of genes associated with luminal breast cancers. These results indicate that aging leads to DNA methylation changes at TEs that undermine the maintenance of lineage specificity, potentially increasing susceptibility to breast cancer.

Overexpression of C19orf48 correlates with poor prognosis in breast cancer

As one of the most commonly diagnosed cancers in women around the world, breast cancer has been detailed studied. This study aimed to identify the expression of c19orf48 in several kinds of cancers including liver, lung and breast cancers etc. The driving factors behind it were analysed and it found that the amplification of c19orf48 may relate with the elevated expression. At the same time, the correlation between the expression of it and the survival time in breast cancer patients was explored. It was found that the c19orf48 expression at transcriptional level elevated in breast cancer tissue samples compared with the normal. It was inferred that the c19orf48 play its oncogenic role in development of breast cancer by involving in cell-cycle related biological process. In conclusion, c19orf48 may be a useful and predictive biomarker for the prognosis of breast cancer patients. To the best of our knowledge, this is the first report describing the expression of c19orf48, the potential driving factor led to this and its effect.

CA916798 predicts poor prognosis and promotes Gefitinib resistance for lung adenocarcinoma

Background

Our previous studies have identified CA916798 as a chemotherapy resistance-associated gene in lung cancer. However, the histopathological relevance and biological function of CA916798 in lung adenocarcinoma (LUAD) remains to be delineated. In this study, we further investigated and explored the clinical and biological significance of CA916798 in LUAD.

Methods

The relationship between CA916798 and clinical features of LUAD was analyzed by tissue array and online database. CCK8 and flow cytometry were used to measure cell proliferation and cell cycle of LUAD after knockdown of CA916798 gene. qRT-PCR and western blotting were used to detect the changes of cell cycle-related genes after knockdown or overexpression of CA916798. The tumorigenesis of LUAD cells was evaluated with or without engineering manipulation of CA916798 gene expression. Response to Gefitinib was evaluated using LUAD cells with forced expression or knockdown of CA916798.

Results

The analysis on LUAD samples showed that high expression of CA916798 was tightly correlated with pathological progression and poor prognosis of LUAD patients. A critical methylation site in promoter region of CA916798 gene was identified to be related with CA916798 gene expression. Forced expression of CA916798 relieved the inhibitory effects of WEE1 on CDK1 and facilitated cell cycle progression from G2 phase to M phase. However, knockdown of CA916798 enhanced WEE1 function and resulted in G2/M phase arrest. Consistently, chemical suppression of CDK1 dramatically inhibited G2/M phase transition in LUAD cells with high expression of CA916798. Finally, we found that CA916798 was highly expressed in Gefitinib-resistant LUAD cells. Exogenous expression of CA916798 was sufficient to endow Gefitinib resistance with tumor cells, but interference of CA916798 expression largely rescued response of tumor cells to Gefitinib.

Conclusions

CA916798 played oncogenic roles and was correlated with the development of Gefitinib resistance in LUAD cells. Therefore, CA916798 could be considered as a promising prognostic marker and a therapeutic target for LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-023-10735-3.

Integrative multi-omic analysis identifies genetically influenced DNA methylation biomarkers for breast and prostate cancers

Aberrant DNA methylation has emerged as a hallmark in several cancers and contributes to risk, oncogenesis, progression, and prognosis. In this study, we performed imputation-based and conventional methylome-wide association analyses for breast cancer (BrCa) and prostate cancer (PrCa). The imputation-based approach identified DNA methylation at cytosine-phosphate-guanine sites (CpGs) associated with BrCa and PrCa risk utilising genome-wide association summary statistics (N_BrCa = 228,951, N_PrCa = 140,254) and prebuilt methylation prediction models, while the conventional approach identified CpG associations utilising TCGA and GEO experimental methylation data (N_BrCa = 621, N_PrCa = 241). Enrichment analysis of the association results implicated 77 and 81 genetically influenced CpGs for BrCa and PrCa, respectively. Furthermore, analysis of differential gene expression around these CpGs suggests a genome-epigenome-transcriptome mechanistic relationship. Conditional analyses identified multiple independent secondary SNP associations (P_cond < 0.05) around 28 BrCa and 22 PrCa CpGs. Cross-cancer analysis identified eight common CpGs, including a strong therapeutic target in SREBF1 (17p11.2)—a key player in lipid metabolism. These findings highlight the utility of integrative analysis of multi-omic cancer data to identify robust biomarkers and understand their regulatory effects on cancer risk.

Methylome-wide association studies identify genetically-influenced CpGs associated with breast and prostate cancer risk and (epi)genome-transcriptome mechanistic relationships, with lipid metabolism genes implicated as potential therapeutic targets.

Deep proteome profiling of human mammary epithelia at lineage and age resolution

Age is the major risk factor in most carcinomas, yet little is known about how proteomes change with age in any human epithelium. We present comprehensive proteomes comprised of >9,000 total proteins and >15,000 phosphopeptides from normal primary human mammary epithelia at lineage resolution from ten women ranging in age from 19 to 68 years. Data were quality controlled and results were biologically validated with cell-based assays. Age-dependent protein signatures were identified using differential expression analyses and weighted protein co-expression network analyses. Upregulation of basal markers in luminal cells, including KRT14 and AXL, were a prominent consequence of aging. PEAK1 was identified as an age-dependent signaling kinase in luminal cells, which revealed a potential age-dependent vulnerability for targeted ablation. Correlation analyses between transcriptome and proteome revealed age-associated loss of proteostasis regulation. Age-dependent proteome changes in the breast epithelium identified heretofore unknown potential therapeutic targets for reducing breast cancer susceptibility.

Changes in Immune Cell Types with Age in Breast are Consistent with a Decline in Immune Surveillance and Increased Immunosuppression

A majority of breast cancers (BC) are age-related and we seek to determine what cellular and molecular changes occur in breast tissue with age that make women more susceptible to cancer initiation. Immune-epithelial cell interactions are important during mammary gland development and the immune system plays an important role in BC progression. The composition of human immune cell populations is known to change in peripheral blood with age and in breast tissue during BC progression. Less is known about changes in immune populations in normal breast tissue and how their interactions with mammary epithelia change with age. We quantified densities of T cells, B cells, and macrophage subsets in pathologically normal breast tissue from 122 different women who ranged in age from 24 to 74 years old. Donor-matched peripheral blood from a subset of 20 donors was analyzed by flow cytometry. Tissue immune cell densities and localizations relative to the epithelium were quantified in situ with machine learning-based image analyses of multiplex immunohistochemistry-stained tissue sections. In situ results were corroborated with flow cytometry analyses of peri-epithelial immune cells from primary breast tissue preparations and transcriptome analyses of public data from bulk tissue reduction mammoplasties. Proportions of immune cell subsets in breast tissue and donor-matched peripheral blood were not correlated. Density (cells/mm²) of T and B lymphocytes in situ decreased with age. T cells and macrophages preferentially localized near or within epithelial bilayers, rather than the intralobular stroma. M2 macrophage density was higher than M1 macrophage density and this difference was due to higher density of M2 in the intralobular stroma. Transcriptional signature analyses suggested age-dependent decline in adaptive immune cell populations and functions and increased innate immune cell activity. T cells and macrophages are so intimately associated with the epithelia that they are embedded within the bilayer, suggesting an important role for immune-epithelial cell interactions. Age-associated decreased T cell density in peri-epithelial regions, and increased M2 macrophage density in intralobular stroma suggests the emergence of a tissue microenvironment that is simultaneously immune-senescent and immunosuppressive with age.

Breast-Specific Molecular Clocks Comprised of ELF5 Expression and Promoter Methylation Identify Individuals Susceptible to Cancer Initiation

A robust breast cancer prevention strategy requires risk assessment biomarkers for early detection. We show that expression of ELF5, a transcription factor critical for normal mammary development, is downregulated in mammary luminal epithelia with age. DNA methylation of the ELF5 promoter is negatively correlated with expression in an age-dependent manner. Both ELF5 methylation and gene expression were used to build biological clocks to estimate chronological ages of mammary epithelia. ELF5 clock-based estimates of biological age in luminal epithelia from average-risk women were within three years of chronological age. Biological ages of breast epithelia from BRCA1 or BRCA2 mutation carriers, who were high risk for developing breast cancer, suggested they were accelerated by two decades relative to chronological age. The ELF5 DNA methylation clock had better performance at predicting biological age in luminal epithelial cells as compared with two other epigenetic clocks based on whole tissues. We propose that the changes in ELF5 expression or ELF5-proximal DNA methylation in luminal epithelia are emergent properties of at-risk breast tissue and constitute breast-specific biological clocks. PREVENTION RELEVANCE: ELF5 expression or DNA methylation level at the ELF5 promoter region can be used as breast-specific biological clocks to identify women at higher than average risk of breast cancer.

Gene expression profile of normal breast tissue and body mass index

BACKGROUND

In human breast, adipose tissue represents up to 80% of the total volume and plays a critical role in mammary gland remodeling. Given the emerging role of obesity in breast cancer growth and development, we explored the relationship between body mass index (BMI), as a proxy of woman's obesity status, and the expression in normal breast tissue from healthy women of a selected panel of genes, known to be involved in mammary gland homeostasis.

METHODS

Two independent publicly available datasets, composed of 180 specimens of normal breast tissue from reduction mammoplasty were interrogated. Differential gene expression among BMI classes was evaluated by ANOVA, and partial correlation coefficient was used to assay the correlation between genes controlling for BMI.

RESULTS

Despite the differences in microarray platforms and analytical procedures, the two datasets shared a core of 9 genes differentially expressed in BMI classes and significantly correlated with BMI. Four (44%) of these genes belong to the functional class of cytokines and cytokine receptors (IL1R1, IL2RA, IL12A, and IL12RB2). The others belong to the functional class of the epigenetic regulation (MEDAG and SETD7), signal transduction (STAT1), cell adhesion (ITGAV), and enzymatic activity (STS).

CONCLUSIONS

Although exploratory, present findings are in agreement with the role of inflammation modulators in the homeostasis of normal breast tissue and the believe that an increase in body adipose tissue may have a potentially dangerous local effect, through the increased expression of inflammation-related genes and the establishment of a low-grade chronic inflammation.

Age-related DNA methylation in paired normal and tumour breast tissue in Chinese breast cancer patients

Age-related DNA methylation is a potential mechanism contributing to breast cancer development. Studies of primarily Caucasian women have identified many CpG sites of age-related methylation in non-diseased breast tissue possibly driving cancer development over time. There is a paucity of studies involving Asian women whose ages at breast cancer onset are usually younger than Caucasians. We identified the 181 most consistent age-related methylation events in non-diseased breast tissue across published studies. Age-related methylation events were measured in adjacent normal and breast tumour tissue in an exclusively Asian population at the previously identified age-related methylation sites. Age-related methylation was found in 118 probes in adjacent normal breast tissue. Methylation of 99% of these sites was increased with age and predominantly located on CpG islands in promoter regions. To ascertain biological relevance to breast cancer, we focused on the 37 sites with overall higher methylation in tumour compared to adjacent normal samples. Some sites positively related to age, including AQP5 and CORO6, inversely correlated with gene expression. Several others have known involvement in suppression of carcinogenesis including GPC5 and SST, suggesting that perturbation of epigenetic regulation at these sites due to ageing may contribute to the progression of carcinogenesis. This study highlights an age-related methylation landscape in non-tumour tissue, consistent not just across studies, but also across different populations. We present candidate age-related methylation sites warranting further investigation as potential epigenetic drivers of breast cancer. They may serve as potential targets of site-specific demethylation intervention strategies for the prevention of age-related breast cancer.

A comparison of epigenetic mitotic-like clocks for cancer risk prediction

Background

DNA methylation changes that accrue in the stem cell pool of an adult tissue in line with the cumulative number of cell divisions may contribute to the observed variation in cancer risk among tissues and individuals. Thus, the construction of epigenetic “mitotic” clocks that can measure the lifetime number of stem cell divisions is of paramount interest.

Methods

Building upon a dynamic model of DNA methylation gain in unmethylated CpG-rich regions, we here derive a novel mitotic clock (“epiTOC2”) that can directly estimate the cumulative number of stem cell divisions in a tissue. We compare epiTOC2 to a different mitotic model, based on hypomethylation at solo-WCGW sites (“HypoClock”), in terms of their ability to measure mitotic age of normal adult tissues and predict cancer risk.

Results

Using epiTOC2, we estimate the intrinsic stem cell division rate for different normal tissue types, demonstrating excellent agreement (Pearson correlation = 0.92, R² = 0.85, P = 3e−6) with those derived from experiment. In contrast, HypoClock’s estimates do not (Pearson correlation = 0.30, R² = 0.09, P = 0.29). We validate these results in independent datasets profiling normal adult tissue types. While both epiTOC2 and HypoClock correctly predict an increased mitotic rate in cancer, epiTOC2 is more robust and significantly better at discriminating preneoplastic lesions characterized by chronic inflammation, a major driver of tissue turnover and cancer risk. Our data suggest that DNA methylation loss at solo-WCGWs is significant only when cells are under high replicative stress and that epiTOC2 is a better mitotic age and cancer risk prediction model for normal adult tissues.

Conclusions

These results have profound implications for our understanding of epigenetic clocks and for developing cancer risk prediction or early detection assays. We propose that measurement of DNAm at the 163 epiTOC2 CpGs in adult pre-neoplastic lesions, and potentially in serum cell-free DNA, could provide the basis for building feasible pre-diagnostic or cancer risk assays. epiTOC2 is freely available from 10.5281/zenodo.2632938

DHRS12 inhibits the proliferation and metastasis of osteosarcoma via Wnt3a/β-catenin pathway

Aim: This experimental design was based on DHRS12 to explore its biological effects on osteosarcoma (OS). Materials & methods: The expression level of endogenous DHRS12 was analyzed by immunohistochemical analysis. DHRS12 was overexpressed in MG-63 and HOS cells by plasmid transfection. Cell proliferation, invasion, migration, apoptosis and western blot were used in the experiment. Results: The expression of DHRS12 was significantly reduced in OS. Overexpression of DHRS12 inhibited the proliferation, migration and invasion of MG-63 and HOS cells and induced apoptosis of OS cells. Overexpression of DHRS12 upregulated Bax, Caspase 9 and Caspase 3. Overexpression of DHRS12 resulted in inactivation of the Wnt3a/β-catenin signaling pathway. Conclusion: Overexpression of DHRS12 inhibited the progression of OS via the Wnt3a/β-catenin pathway.

Absence of an embryonic stem cell DNA methylation signature in human cancer

BACKGROUND

Differentiated cells that arise from stem cells in early development contain DNA methylation features that provide a memory trace of their fetal cell origin (FCO). The FCO signature was developed to estimate the proportion of cells in a mixture of cell types that are of fetal origin and are reminiscent of embryonic stem cell lineage. Here we implemented the FCO signature estimation method to compare the fraction of cells with the FCO signature in tumor tissues and their corresponding nontumor normal tissues.

METHODS

We applied our FCO algorithm to discovery data sets obtained from The Cancer Genome Atlas (TCGA) and replication data sets obtained from the Gene Expression Omnibus (GEO) data repository. Wilcoxon rank sum tests, linear regression models with adjustments for potential confounders and non-parametric randomization-based tests were used to test the association of FCO proportion between tumor tissues and nontumor normal tissues. P-values of < 0.05 were considered statistically significant.

RESULTS

Across 20 different tumor types we observed a consistently lower FCO signature in tumor tissues compared with nontumor normal tissues, with 18 observed to have significantly lower FCO fractions in tumor tissue (total n = 6,795 tumor, n = 922 nontumor, P < 0.05). We replicated our findings in 15 tumor types using data from independent subjects in 15 publicly available data sets (total n = 740 tumor, n = 424 nontumor, P < 0.05).

CONCLUSIONS

The results suggest that cancer development itself is substantially devoid of recapitulation of normal embryologic processes. Our results emphasize the distinction between DNA methylation in normal tightly regulated stem cell driven differentiation and cancer stem cell reprogramming that involves altered methylation in the service of great cell heterogeneity and plasticity.

Abrupt involution induces inflammation, estrogenic signaling, and hyperplasia linking lack of breastfeeding with increased risk of breast cancer

Background

A large collaborative analysis of data from 47 epidemiological studies concluded that longer duration of breastfeeding reduces the risk of developing breast cancer. Despite the strong epidemiological evidence, the molecular mechanisms linking prolonged breastfeeding to decreased risk of breast cancer remain poorly understood.

Methods

We modeled two types of breastfeeding behaviors in wild type FVB/N mice: (1) normal or gradual involution of breast tissue following prolonged breastfeeding and (2) forced or abrupt involution following short-term breastfeeding. To accomplish this, pups were gradually weaned between 28 and 31 days (gradual involution) or abruptly at 7 days postpartum (abrupt involution). Mammary glands were examined for histological changes, proliferation, and inflammatory markers by immunohistochemistry. Fluorescence-activated cell sorting was used to quantify mammary epithelial subpopulations. Gene set enrichment analysis was used to analyze gene expression data from mouse mammary luminal progenitor cells. Similar analysis was done using gene expression data generated from human breast samples obtained from parous women enrolled on a tissue collection study, OSU-2011C0094, and were undergoing reduction mammoplasty without history of breast cancer.

Results

Mammary glands from mice that underwent abrupt involution exhibited denser stroma, altered collagen composition, higher inflammation and proliferation, increased estrogen receptor α and progesterone receptor expression compared to those that underwent gradual involution. Importantly, when aged to 4 months postpartum, mice that were in the abrupt involution cohort developed ductal hyperplasia and squamous metaplasia. Abrupt involution also resulted in a significant expansion of the luminal progenitor cell compartment associated with enrichment of Notch and estrogen signaling pathway genes. Breast tissues obtained from healthy women who breastfed for < 6 months vs ≥ 6 months showed significant enrichment of Notch signaling pathway genes, along with a trend for enrichment for luminal progenitor gene signature similar to what is observed in BRCA1 mutation carriers and basal-like breast tumors.

Conclusions

We report here for the first time that forced or abrupt involution of the mammary glands following pregnancy and lack of breastfeeding results in expansion of luminal progenitor cells, higher inflammation, proliferation, and ductal hyperplasia, a known risk factor for developing breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1163-7) contains supplementary material, which is available to authorized users.

CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasets

Methylation datasets are affected by innumerable sources of variability, both biological (cell-type composition, genetics) and technical (batch effects). Here, we propose a reference-free method based on sparse canonical correlation analysis to separate the biological from technical sources of variability. We show through simulations and real data that our method, CONFINED, is not only more accurate than the state-of-the-art reference-free methods for capturing known, replicable biological variability, but it is also considerably more robust to dataset-specific technical variability than previous approaches. CONFINED is available as an R package as detailed at https://github.com/cozygene/CONFINED.

Increased DHRS12 expression independently predicts poor survival in patients with high-grade serous ovarian cancer

AIM

To explore the expression profile of some DHRS genes in high-grade serous ovarian cancer (SOVC) and to study their prognostic values.

PATIENTS & METHODS

A retrospective bioinformatic analysis was performed using data in the Gene Expression Omnibus, the Human Protein Atlas and the Cancer Genome Atlas-Ovarian Cancer.

RESULTS

Increased DHRS12 expression was an independent indicator of poor overall survival (hazard ratio [HR]: 1.265, 95% CI: 1.075-1.488; p = 0.005) and recurrence-free survival (RFS; HR: 2.242, 95%CI: 1.464-3.432; p < 0.001) in patients with high-grade SOVC. DNA deletion was associated with decreased DHRS12 expression, as well as the best overall survival and RFS among the three copy number alteration groups.

CONCLUSION

DHRS12 might serve as a valuable prognostic biomarker in high-grade SOVC.