Mechanisms of Genomic Instability in Breast Cancer

A new insight into the impact of copy number variations on cell cycle deregulation of luminal-type breast cancer

Breast cancer is the most prevalent neoplasm in women. ER+ (Luminal subtype), representing over 70% of breast tumors, is a genetically diverse group. Structural and Numerical-Chromosomal instability initiates tumor development and is recognized as the primary driver of genetic alteration in luminal breast tumors. Genomic instability refers to the increased tendency of cancer cells to accumulate genomic alterations during cell proliferation. The cell cycle check-point response to constant and stable genomic alterations in tumor cells drives this process. The impact of CNV patterns and aneuploidies in cell cycle and proliferation perturbation has recently been highlighted by scientists in Luminal breast tumors. The impact of chromosomal instability on cancer therapy and prognosis is not a new concept. Still, the degree of emerging genomic instability leads to prognosis alteration following cell cycle deregulation by chromosomal instability could be predicted by CNVs-based reclassification of breast tumors. In this review, we try to explain the effect of CIN in the cell cycle that ended with genomic instability and altered prognosis and the impact of CIN in decision-making for a therapy strategy for patients with luminal breast cancer.

Interaction of breast cancer-relevant DNA repair genes and air pollution in relation to breast cancer risk in UK biobank

We investigated if selected polymorphisms in DNA repair genes modify the association between exposure to particulate matter ≤ 10 micron in diameter (PM10) and breast cancer (BCa) risk. We included 150,929 postmenopausal women (5,969 with BCa) from UK Biobank, a population-based prospective cohort. Cancer diagnoses were ascertained through the linkage to the UK National Health Service Central Registers. Information on BCa risk factors was collected at baseline. Blood samples were collected from participants at enrollment and genotyped using the Applied Biosystems UK BiLEVE Axiom Array or the Applied Biosystems UK Biobank Axiom Array. Cox proportional hazards regression was used to examine interactions of exposure (2007 PM10 and cumulative average PM10) with 14 SNPs, adjusting for BCa risk factors. The positive associations of 2007 PM10 and cumulative average PM10 with BCa risk were stronger in women with one or two copies of XRCC2 rs3218536 C allele vs. none (2007 PM10 Hazard Ratio [HR] per 10 µg/m3 = 1.54, 95% Confidence Interval [CI] 1.22, 1.95 or HR = 1.14, 95% CI 1.03, 1.30 vs. HR = 0.52, 95% CI 0.16, 1.75, p-interaction = 0.02; cumulative average PM10 HR per 10 µg/m3 = 2.80, 95% CI 1.99, 3.96 or HR = 1.89, 95% CI 1.64, 2.18 vs. HR = 0.45, 95% CI 0.08, 2.37, p-interaction = 0.05). We observed no interactions of PM10 with other SNPs. Our results suggest stronger associations of 2007 PM10 and cumulative average PM10 with postmenopausal BCa risk in carriers of XRCC2 rs3218536 C allele.

asmbPLS: biomarker identification and patient survival prediction with multi-omics data

Introduction

With the advancement of high-throughput studies, an increasing wealth of high-dimensional multi-omics data is being collected from the same patient cohort. However, leveraging this multi-omics data to predict survival outcomes poses a significant challenge due to its complex structure.

Methods

In this article, we present a novel approach, the Adaptive Sparse Multi-Block Partial Least Squares (asmbPLS) Regression model, which introduces a dynamic assignment of penalty factors to distinct blocks within various PLS components, facilitating effective feature selection and prediction.

Results

We compared the proposed method with several state-of-the-art algorithms encompassing prediction performance, feature selection and computation efficiency. We conducted comprehensive evaluations using both simulated data with various scenarios and a real dataset from the melanoma patients to validate the effectiveness and efficiency of the asmbPLS method. Additionally, we applied the lung squamous cell carcinoma (LUSC) dataset from The Cancer Genome Atlas (TCGA) to further assess the feature selection capability of asmbPLS.

Discussion

The inherent nature of asmbPLS imparts it with higher sensitivity in feature selection compared to other methods. Furthermore, an R package called asmbPLS implementing this method is made publicly available.

Liquid-liquid Phase Separation in Aging: Novel Insights in the Pathogenesis and Therapeutics

The intricate organization of distinct cellular compartments is paramount for the maintenance of normal biological functions and the orchestration of complex biochemical reactions. These compartments, whether membrane-bound organelles or membraneless structures like Cajal bodies and RNA transport granules, play crucial roles in cellular function. Liquid-liquid phase separation (LLPS) serves as a reversible process that elucidates the genesis of membranelles structures through the self-assembly of biomolecules. LLPS has been implicated in a myriad of physiological and pathological processes, encompassing immune response and tumor genesis. But the association between LLPS and aging has not been clearly clarified. A recent advancement in the realm of aging research involves the introduction of a new edition outlining the twelve hallmarks of aging, categorized into three distinct groups. By delving into the role and mechanism of LLPS in the formation of membraneless structures at a molecular level, this review encapsulates an exploration of the interaction between LLPS and these aging hallmarks, aiming to offer novel perspectives of the intricate mechanisms underlying the aging process and deeper insights into aging therapeutics.

Single-Sample Networks Reveal Intra-Cytoband Co-Expression Hotspots in Breast Cancer Subtypes

Breast cancer is a heterogeneous disease comprising various subtypes with distinct molecular characteristics, clinical outcomes, and therapeutic responses. This heterogeneity evidences significant challenges for diagnosis, prognosis, and treatment. Traditional genomic co-expression network analyses often overlook individual-specific interactions critical for personalized medicine. In this study, we employed single-sample gene co-expression network analysis to investigate the structural and functional genomic alterations across breast cancer subtypes (Luminal A, Luminal B, Her2-enriched, and Basal-like) and compared them with normal breast tissue. We utilized RNA-Seq gene expression data to infer gene co-expression networks. The LIONESS algorithm allowed us to construct individual networks for each patient, capturing unique co-expression patterns. We focused on the top 10,000 gene interactions to ensure consistency and robustness in our analysis. Network metrics were calculated to characterize the topological properties of both aggregated and single-sample networks. Our findings reveal significant fragmentation in the co-expression networks of breast cancer subtypes, marked by a change from interchromosomal (TRANS) to intrachromosomal (CIS) interactions. This transition indicates disrupted long-range genomic communication, leading to localized genomic regulation and increased genomic instability. Single-sample analyses confirmed that these patterns are consistent at the individual level, highlighting the molecular heterogeneity of breast cancer. Despite these pronounced alterations, the proportion of CIS interactions did not significantly correlate with patient survival outcomes across subtypes, suggesting limited prognostic value. Furthermore, we identified high-degree genes and critical cytobands specific to each subtype, providing insights into subtype-specific regulatory networks and potential therapeutic targets. These genes play pivotal roles in oncogenic processes and may represent important keys for targeted interventions. The application of single-sample co-expression network analysis proves to be a powerful tool for uncovering individual-specific genomic interactions.

Construction of a prognostic model based on cuproptosis-related patterns for predicting survival, immune infiltration, and immunotherapy efficacy in breast cancer: Cuproptosis-based prognostic modeling in breast cancer

Breast cancer is the most common and lethal malignancy among women worldwide. Cuproptosis, a newly identified copper-dependent cell death, is closely associated with cancer development. However, its regulatory mechanisms in breast cancer are not well studied. This study aims to establish a prognostic model for breast cancer to improve risk stratification. The mRNA expression data was downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering identified patterns based on cuproptosis-related genes. Key genes were screened using Weighted Gene Co-Expression Network Analysis and differentially expressed gene analysis. A prognostic model was constructed using Cox regression and evaluated with time-dependent receiver operating characteristic and Kaplan-Meier analyses. Functional pathways, immune cell infiltration, and other tumor characteristics were also analyzed. Two distinct cuproptosis patterns were identified. The top 21 differentially expressed genes, significantly associated with survival, were used to construct the prognostic model. The risk score has a negative correlation with survival. Enrichment analysis showed immune-related pathways enriched in the low-risk group, which also had more immune cell infiltration, higher stromal component, lower tumor purity, and lower tumor heterogeneity. Finally, significant differences of half maximal inhibitory concentration were also observed between patients in high- and low-risk groups who received chemotherapy and targeted therapy drugs. These findings in our study may provide evidence for further research and individualized management of breast cancer.

High prevalence of chromosome 17 in breast cancer micronuclei: a means to get rid of tumor suppressors?

Micronuclei (MN), defined as small extra-nuclear chromatin bodies enclosed by a nuclear envelope, serve as noticeable markers of chromosomal instability (CIN). The MN have been used for breast cancer (BC) screening, diagnosis, and prognosis. However, more recently they have gained attention as seats for active chromosomal rearrangements. BC subtypes exhibit differential CIN levels and aggressiveness. This study aimed to investigate MN chromosomal contents across BC subtypes, exploring its potential role in aggressiveness and pathogenesis. Immunostaining of BC cells was performed with anti-centromeric antibody followed by confocal microscopy. Further, fluorescence in situ hybridization (FISH) was done to check the presence of specific chromosomes in the MN. The real time PCR was also done from the RNA isolated from MN to check the expression of TP53 gene. BC cell lines (CLs) showed the presence of both centromere-positive ( +) and -negative ( -) MN, with significant variation in frequency among hormone and human epidermal growth factor receptor positive and triple-negative (TN) BC cells. FISH targeting chromosomes 1, 3, 8, 11, and 17 detected centromeric signals for all the above chromosomes in MN with a relatively higher prevalence of chromosome 17 in all the CLs. Out of all the CLs, TNBC cells demonstrated the highest frequency of centromere + and chromosome 17 + MN. TP53 expression could also be demonstrated inside the MN by FISH and real time PCR. Patient sample imprints also confirmed the presence of chromosome 17 in MN with polysomy of the same in corresponding nuclei. The high prevalence of chromosome 17 in BC MN may connote the importance of its rearrangements in the pathogenesis of BC. Further, the higher prevalence of chromosome 17 and 1 signals in TNBC MN point towards the significance of pathogenetic events involving the genes located in these chromosomes in evolution of this more aggressive phenotype.

Micro-RNAs in breast cancer progression and metastasis: A chromatin and metabolic perspective

Breast cancer is a highly complex disease with multiple subtypes. While many of the breast cancer cases are sporadic some can be familial or hereditary. Genomic integrity is closely monitored by several mechanisms, such as DNA damage machinery and mitotic checkpoints. Any defect in the key genes involved in the regulation of these mechanisms often results in genomic instability, predisposing the cells to malignancy. This results in altered expression of many coding and noncoding genes. The noncoding RNAs especially the long noncoding RNA (lncRNAs) and microRNA (miRNAs) act as key regulators of cancer gene networks. Some miRNAs repress the expression of the heterochromatin-associated proteins, inducing the formation of open chromatin, and promoting the expression of genes required for oncogenesis. Additionally, specific miRNAs may also favour cancer progression and metastasis by regulating the expression of genes that support the metabolic microenvironment essential for cancer cell growth and proliferation. Understanding how these noncoding RNAs contribute to breast cancer development opens potential avenues for therapeutic intervention, targeting their dysregulated activity.

The value of chromosome instability detected by low-pass whole-genome sequencing in preoperative prediction of sentinel lymph node metastasis in breast cancer

Background

Breast cancer is a malignancy characterized by chromosomal instability (CIN). This study aimed to examine the potential diagnostic value of chromosomal instability, detected by low-pass whole-genome sequencing (LPWGS), in the preoperative evaluation of sentinel lymph node metastasis (SLNM) in breast cancer.

Methods

A retrospective investigation of clinical records from 29 patients with breast cancer revealed two distinct groups based on sentinel lymph node biopsy (SLNB) results: the SLN metastasis group (24 cases) and the SLN non-metastasis group (five cases). CIN and CIN scores were evaluated using LPWGS. An analysis of univariate data and binary logistic regression was employed to identify factors influencing SLNM, and a curve with receiver operating characteristics (ROC) was constructed to assess the diagnostic utility of CIN in predicting SLNM.

Results

A significant association between the SLNM and CIN high groups was observed in breast cancer (P=0.011). The CIN score in the metastasis group (17,665.055 ± 8,630.691) was higher than that in the non-metastasis group (9,247.973 ± 3,692.873), demonstrating a significant difference (P=0.044). Univariate binary logistic regression analysis indicated that CIN was a significant predictor for SLNM (odds ratio: 4.036, 95% CI: 1.015-16.047, P=0.048). The AUC of CIN for preoperative diagnosis of SLNM was 0.808 (95%CI: 0.635-0.982, P=0.033), with a sensitivity value of 67.0% and specificity of 100.0% at a threshold of 13,563.

Conclusion

Detecting CIN through LPWGS demonstrates diagnostic potential in predicting SLNM in patients with breast cancer before surgery. This approach offers a novel method for assessing axillary lymph node status in clinical practice.

Mechanism of immune activation mediated by genomic instability and its implication in radiotherapy combined with immune checkpoint inhibitors

Various genetic and epigenetic changes associated with genomic instability (GI), including DNA damage repair defects, chromosomal instability, and mitochondrial GI, contribute to development and progression of cancer. These alterations not only result in DNA leakage into the cytoplasm, either directly or through micronuclei, but also trigger downstream inflammatory signals, such as the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. Apart from directly inducing DNA damage to eliminate cancer cells, radiotherapy (RT) exerts its antitumor effects through intracellular DNA damage sensing mechanisms, leading to the activation of downstream inflammatory signaling pathways. This not only enables local tumor control but also reshapes the immune microenvironment, triggering systemic immune responses. The combination of RT and immunotherapy has emerged as a promising approach to increase the probability of abscopal effects, where distant tumors respond to treatment due to the systemic immunomodulatory effects. This review emphasizes the importance of GI in cancer biology and elucidates the mechanisms by which RT induces GI remodeling of the immune microenvironment. By elucidating the mechanisms of GI and RT-induced immune responses, we aim to emphasize the crucial importance of this approach in modern oncology. Understanding the impact of GI on tumor biological behavior and therapeutic response, as well as the possibility of activating systemic anti-tumor immunity through RT, will pave the way for the development of new treatment strategies and improve prognosis for patients.

ATR/Chk1 interacting lncRNA modulates DNA damage response to induce breast cancer chemoresistance

The ATR-Chk1 pathway is essential in cellular responses to DNA damage and replication stress, whereas the role of long noncoding RNAs (lncRNAs) in regulating this pathway remains largely unknown. In this study, we identify an ATR and Chk1 interacting lncRNA (ACIL, also known as LRRC75A-AS1 or SNHG29), which promotes the phosphorylation of Chk1 by ATR upon DNA damages. High ACIL levels are associated with chemoresistance to DNA damaging agents and poor outcome of breast cancer patients. ACIL knockdown sensitizes breast cancer cells to DNA damaging drugs in vitro and in vivo. ACIL protects cancer cells against DNA damages by inducing cell cycle arrest, stabilizing replication forks and inhibiting unscheduled origin firing, thereby guarding against replication catastrophe and contributing to DNA damage repair. These findings demonstrate a lncRNA-dependent mechanism of activating the ATR-Chk1 pathway and highlight the potential of utilizing ACIL as a predictive biomarker for chemotherapy sensitivity, as well as targeting ACIL to reverse chemoresistance in breast cancer.

Transient splicing inhibition causes persistent DNA damage and chemotherapy vulnerability in triple-negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive type of breast cancer. While most TNBCs are initially sensitive to chemotherapy, a substantial fraction acquires resistance to treatments and progresses to more advanced stages. Here, we identify the spliceosome U2 small nuclear ribonucleoprotein particle (snRNP) complex as a modulator of chemotherapy efficacy in TNBC. Transient U2 snRNP inhibition induces persistent DNA damage in TNBC cells and organoids, regardless of their homologous recombination proficiency. U2 snRNP inhibition pervasively deregulates genes involved in the DNA damage response (DDR), an effect relying on their genomic structure characterized by a high number of small exons. Furthermore, a pulse of splicing inhibition elicits long-lasting repression of DDR proteins and enhances the cytotoxic effect of platinum-based drugs and poly(ADP-ribose) polymerase inhibitors (PARPis) in multiple TNBC models. These findings identify the U2 snRNP as an actionable target that can be exploited to enhance chemotherapy efficacy in TNBCs.

Association Between Polymorphisms in DNA Damage Repair Pathway Genes and Female Breast Cancer Risk

Breast cancer risk have been discussed to be associated with polymorphisms in genes as well as abnormal DNA damage repair function. This study aims to assess the relationship between genes single nucleotide polymorphisms (SNPs) related to DNA damage repair and female breast cancer risk in Chinese population. A case-control study containing 400 patients and 400 healthy controls was conducted. Genotype was identified using the sequence MassARRAY method and expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was analyzed by immunohistochemistry assay. The results revealed that ATR rs13091637 decreased breast cancer risk influenced by ER, PR (CT/TT vs. CC: adjusted odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.04-2.27, p = 0.032; CT/TT vs. CC: adjusted OR = 1.63, 95%CI: 1.14-2.35, p = 0.008) expression. Stratified analysis revealed that PALB2 rs16940342 increased breast cancer risk in response to menstrual status (AG/GG vs. AA: adjusted OR = 1.72, 95%CI: 1.13-2.62, p = 0.011) and age of menarche (AG/GG vs. AA: adjusted OR = 1.54, 95%CI: 1.03-2.31, p = 0.037), whereas ATM rs611646 and Ku70 rs132793 were associated with reduced breast cancer risk influenced by menarche (GA/AA vs. GG: adjusted OR = 0.50, 95%CI: 0.30-0.95, p = 0.033). In a summary, PALB2 rs16940342, ATR rs13091637, ATM rs611646, and Ku70 rs132793 were associated with breast cancer risk.

Measurement of chromosomal instability and level of DNA damage in peripheral blood mononuclear cells of endometrial cancer patients

Endometrial cancer is one of the most common invasive gynecologic malignancies in developed countries. The aim of this study was to evaluate chromosomal instability and level of DNA damage in peripheral blood mononuclear cells (PBMCs) of newly diagnosed endometrial cancer patients in relation to health status (diagnosis), age, histological grade of cancer, residence, smoking, number of pregnancies, miscarriages, and abortions. The analyzed sample consisted of 60 individuals, 30 endometrial cancer patients with an average age of 64.37 ± 7.08, and 30 healthy control women with an average age of 60.23 ± 11.55. Chromosomal instability was evaluated by the cytokinesis-block micronucleus (CBMN) assay, and the level of DNA damage by the single-cell gel electrophoresis (comet) assay in PBMCs. The average frequencies of micronuclei (MNi), nucleoplasmic bridges (NPBs) as well as nuclear buds (NBUDs) were significantly higher in cancer patients compared to controls (P < .0005). There was no difference in the nuclear division index (NDI) among the analyzed samples. The comet assay showed that the patients had a significantly increased genetic damage index (GDI) compared with controls (P < .0005). Using linear regression analysis, we found that health status (diagnosis) had the strongest influence on the MN frequency as well as GDI (P < .0005). Our results indicated that there is a high level of genetic damage in both the level of DNA and the level of chromosomes in the PBMCs of newly diagnosed patients with endometrial cancer, where the frequency and level of damage were significantly affected by health status, grade of cancer, residence, number of pregnancies, miscarriages, and abortions.

Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era

Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.

Identification of potential therapeutic targets for breast cancer using Mendelian randomization analysis and drug target prediction

Breast cancer stands as the foremost cause of cancer-related mortality among women, presenting a substantial economic impact on society. The limitations in current therapeutic options, coupled with poor patient tolerance, underscore the urgent need for novel treatments. Our study embarked on a genomic association exploration of breast cancer, leveraging whole-genome sequencing data from the Finngen database, complemented by expression quantitative trait loci (eQTL) insights from the eQTLGen and GTEx Consortiums. An initial investigation was conducted through summary-based Mendelian randomization (MR) to pinpoint primary eQTLs. Analysis of blood specimens revealed 103 eQTLs significantly correlated with breast cancer. Focusing our efforts, we identified 19 candidates with potential therapeutic significance. Further scrutiny via two-sample MR pinpointed UROD, LMO4, HORMAD1, and ZSWIM5 as promising targets for breast cancer therapy. Our research sheds light on new avenues for the treatment of breast cancer, highlighting the potential of genomic association studies in uncovering viable therapeutic targets.

Blocking LBH expression causes replication stress and sensitizes triple-negative breast cancer cells to ATR inhibitor treatment

Triple-negative (ER-PR-HER2-) breast cancers (TNBC) are highly aggressive and difficult to treat. TNBC exhibit high genomic instability, which enables them to adapt and become resistant to chemo/radiation therapy, leading to rapid disease relapse and mortality. The pro-survival factors that safeguard genome integrity in TNBC cells are poorly understood. LBH is an essential mammary stem cell-specific transcription regulator in the WNT pathway that is aberrantly overexpressed in TNBC, correlating with poor prognosis. Herein, we demonstrate a novel role for LBH in promoting TNBC cell survival. Depletion of LBH in multiple TNBC cell models triggered apoptotic cell death both in vitro and in vivo and led to S-G2M cell cycle delays. Mechanistically, LBH loss causes replication stress due to DNA replication fork stalling, leading to ssDNA breaks, ɣH2AX and 53BP1 nuclear foci formation, and activation of the ATR/CHK1 DNA damage response. Notably, ATR inhibition in combination with LBH downmodulation had a synergistic effect, boosting TNBC cell killing and blocking in vivo tumor growth. Our findings demonstrate, for the first time, that LBH protects the genome integrity of cancer cells by preventing replicative stress. Importantly, they uncover new synthetic lethal vulnerabilities in TNBC that could be exploited for future multi-modal precision medicine.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

A deep-learning-based genomic status estimating framework for homologous recombination deficiency detection from low-pass whole genome sequencing

Genome-wide sequencing allows for prediction of clinical treatment responses and outcomes by estimating genomic status. Here, we developed Genomic Status scan (GSscan), a long short-term memory (LSTM)-based deep-learning framework, which utilizes low-pass whole genome sequencing (WGS) data to capture genomic instability-related features. In this study, GSscan directly surveys homologous recombination deficiency (HRD) status independent of other existing biomarkers. In breast cancer, GSscan achieved an AUC of 0.980 in simulated low-pass WGS data, and obtained a higher HRD risk score in clinical BRCA-deficient breast cancer samples (p = 1.3 × 10-4, compared with BRCA-intact samples). In ovarian cancer, GSscan obtained higher HRD risk scores in BRCA-deficient samples in both simulated data and clinical samples (p = 2.3 × 10-5 and p = 0.039, respectively, compared with BRCA-intact samples). Moreover, HRD-positive patients predicted by GSscan showed longer progression-free intervals in TCGA datasets (p = 0.0011) treated with platinum-based adjuvant chemotherapy, outperforming existing low-pass WGS-based methods. Furthermore, GSscan can accurately predict HRD status using only 1 ng of input DNA and a minimum sequencing coverage of 0.02 × , providing a reliable, accessible, and cost-effective approach. In summary, GSscan effectively and accurately detected HRD status, and provide a broadly applicable framework for disease diagnosis and selecting appropriate disease treatment.

An inflamed tumor cell subpopulation promotes chemotherapy resistance in triple negative breast cancer

Individual cancers are composed of heterogeneous tumor cells with distinct phenotypes and genotypes, with triple negative breast cancers (TNBC) demonstrating the most heterogeneity among breast cancer types. Variability in transcriptional phenotypes could meaningfully limit the efficacy of monotherapies and fuel drug resistance, although to an unknown extent. To determine if transcriptional differences between tumor cells lead to differential drug responses we performed single cell RNA-seq on cell line and PDX models of breast cancer revealing cell subpopulations in states associated with resistance to standard-of-care therapies. We found that TNBC models contained a subpopulation in an inflamed cellular state, often also present in human breast cancer samples. Inflamed cells display evidence of heightened cGAS/STING signaling which we demonstrate is sufficient to cause tumor cell resistance to chemotherapy. Accordingly, inflamed cells were enriched in human tumors taken after neoadjuvant chemotherapy and associated with early recurrence, highlighting the potential for diverse tumor cell states to promote drug resistance.

Exosomal miR-361-3p promotes the viability of breast cancer cells by targeting ETV7 and BATF2 to upregulate the PAI-1/ERK pathway

BACKGROUND

Malignant progression is the major cause of poor prognosis in breast cancer (BC) patients. Plasma exosomal miRNAs have been reported to be involved in tumor progression, but their roles in BC remain unclear.

METHODS

We performed plasma exosomal miRNA sequencing on 45 individuals, including healthy controls and nonmetastatic and metastatic BC patients. We examined the correlation between miRNA expression in tumor tissues and plasma exosomes in BC patients by qRT‒PCR. The effects of exosomal miR-361-3p on BC cells were determined by CellTiter-Glo, migration and wound healing assays. The target genes of miR-361-3p and downstream pathways were explored by dual-luciferase reporter assay, RNA knockdown, rescue experiments, and western blotting. We utilized murine xenograft model to further assess the impact of plasma exosomal miR-361-3p on the malignant progression of BC.

RESULTS

We found that the expression level of plasma exosomal miR-361-3p gradually increased with malignant progression in BC patients, and the expression of miR-361-3p in plasma exosomes and BC tissues was positively correlated. Consistently, exosomal miR-361-3p enhanced the migration and proliferation of two BC cell lines, MDA-MB-231 and SK-BR-3. Furthermore, our data showed that miR-361-3p inhibited two novel target genes, ETV7 and BATF2, to activate the PAI-1/ERK pathway, leading to increased BC cell viability. Finally, the consistency of the in vivo experimental results supported that elevated plasma exosomal miR-361-3p promote the malignant progression of BC.

CONCLUSIONS

We found for the first time that plasma exosomal miR-361-3p was associated with malignant progression in BC patients. Mechanistically, exosomal miR-361-3p can enhance the migration and proliferation of BC cells by targeting the ETV7 and BATF2/PAI-1/ERK pathways. Our data suggest that plasma exosomal miR-361-3p has the potential to serve as a biomarker for predicting malignant progression in BC patients.

Genomic instability-associated two-miRNA signature as a novel prognostic biomarker in breast cancer

BACKGROUND

Breast cancer (BC) is the most common cancer among women worldwide and a leading cause of cancer-associated deaths among women. However, there is a lack of accurate prognostic biomarkers for BC. In the present study, we aimed to identify a genomic instability (GI)-associated microRNA signature as a novel potential prognostic biomarker in BC.

METHODS

We performed an integrative analysis to investigate the relationship between GI and BC and identify GI-associated microRNAs (miRNAs). Subsequently, we conducted a discovery and validation study using multicenter cohorts. The GI-associated miRNA signature was developed in the discovery cohort and independently validated in internal and external cohorts.

RESULTS

GI-associated miRNAs expression in BC showed heterogeneity and was significantly correlated with BC prognosis. We identified a GI-associated two-miRNA signature (miR-105-5p and miR-767-5p), termed GI2miR, that stratified BC patients into high-risk and low-risk groups with significantly different clinical outcomes (log-rank p = 0.027) in The Cancer Genome Atlas (TCGA) discovery cohort (n = 763). The prognostic value of GI2miR was further validated in internal TCGA validation cohort (n = 253) (log-rank p = 0.035) and independent GSE22216 cohort (n = 210) (log-rank p = 0.036). The GI2miR demonstrated independent prognostic value in multivariate Cox proportional hazard regression analyses and stratification analysis.

CONCLUSIONS

We have developed a novel prognostic signature based on GI-associated two miRNAs for BC, which may lay the foundation for BC to improve prognosis prediction.

CIP2A coordinates phosphosignaling, mitosis, and the DNA damage response

Human cancers share requirements for phosphorylation-dependent signaling, mitotic hyperactivity, and survival after DNA damage. The oncoprotein CIP2A (cancerous inhibitor of PP2A) can coordinate all these cancer cell characteristics. In addition to controlling cancer cell phosphoproteomes via inhibition of protein phosphatase PP2A, CIP2A directly interacts with the DNA damage protein TopBP1 (topoisomerase II-binding protein 1). Consequently, CIP2A allows DNA-damaged cells to enter mitosis and is essential for mitotic cells that are defective in homologous recombination (HR)-mediated DNA repair (e.g., BRCA mutants). The CIP2A-TopBP1 complex is also important for clustering fragmented chromosomes at mitosis. Clinically, CIP2A is a disease driver for basal-like triple-negative breast cancer (BL-TNBC) and a promising cancer therapy target across many cancer types.

Somatic mutations in a multigene panel and impact on prognosis based on TP53 status in Chinese HER2-positive patients undergoing neoadjuvant therapy: A single-institution retrospective cohort

BACKGROUND

Gene mutations play a crucial role in the occurrence and development of tumors, particularly in breast cancer (BC). Neoadjuvant therapy (NAT) has shown greater clinical benefit in HER2-positive breast cancer. However, further clinical investigation is needed to fully understand the correlation between genetic mutations and NAT efficacy and the long-term prognosis in HER2-positive BC.

METHODS

This was a retrospective cohort study of 222 patients receiving NAT between 2017 and 2021 in the Department of Breast Surgery of Fudan University Shanghai Cancer Center. Tumor samples from these patients were subjected to Next Generation Sequencing (NGS) to analyze mutations in 513 cancer-related genes. This study aimed to investigate the association between these genetic mutations and postoperative pathological complete response (pCR), as well as their impact on disease-free survival (DFS).

RESULTS

In total, 48.65% patients reached pCR, ER-negative status (p < 0.001), PR-negative status (p < 0.001), Ki67 ≥ 20 (p = 0.011), and dual-targeted therapy (p < 0.001) were all associated with enhanced pCR rates. The frequency of somatic alterations in TP53 (60%), PIK3CA (15%), and ERBB2 (11%) was highest. In the HER2+/HR- cohort, patients who achieved pCR had a significant benefit in prognosis (HR = 3.049, p = 0.0498). KMT2C (p = 0.036) and TP53 (p = 0.037) mutations were significantly increased in patients with DFS events. Moreover, TP53 mutations had prognostic significance in HER2-positive BC patients with HR-negative (HR = 3.712, p = 0.027) and pCR (HR = 6.253, p = 0.027) status and who received herceptin-only targeted therapy (HR = 4.145, p = 0.011).

CONCLUSIONS

The genetic mutation profiles of Chinese HER2+ patients who received NAT were discrepant with respect to HR status or DFS events. TP53 mutations have significant prognostic value in patients with NAT for HER2-positive BC and patients benefit differently depending on HR status, the neoadjuvant regimen and response, which highlights the significance of genetic factors in treatment customization based on individual genetic and clinical characteristics.

Understanding the mechanistic pathways and clinical aspects associated with protein and gene based biomarkers in breast cancer

Cancer is one of the most widespread and severe diseases with a huge mortality rate. In recent years, the second-leading mortality rate of any cancer globally has been breast cancer, which is one of the most common and deadly cancers found in women. Detecting breast cancer in its initial stages simplifies treatment, decreases death risk, and recovers survival rates for patients. The death rate for breast cancer has risen to 0.024 % in some regions. Sensitive and accurate technologies are required for the preclinical detection of BC at an initial stage. Biomarkers play a very crucial role in the early identification as well as diagnosis of women with breast cancer. Currently, a wide variety of cancer biomarkers have been discovered for the diagnosis of cancer. For the identification of these biomarkers from serum or other body fluids at physiological amounts, many detection methods have been developed. In the case of breast cancer, biomarkers are especially helpful in discovering those who are more likely to develop the disease, determining prognosis at the time of initial diagnosis and choosing the best systemic therapy. In this study we have compiled various clinical aspects and signaling pathways associated with protein-based biomarkers and gene-based biomarkers.

Stochastic epithelial-mesenchymal transitions diversify non-cancerous lung cell behaviours

Epithelial-mesenchymal plasticity (EMP) is a hallmark of cancer. By enabling cells to shift between different morphological and functional states, EMP promotes invasion, metastasis and therapy resistance. We report that near-diploid non-cancerous human epithelial lung cells spontaneously shift along the EMP spectrum without genetic changes. Strikingly, more than half of single cell-derived clones adopt a mesenchymal morphology. We independently characterise epithelial-like and mesenchymal-like clones. Mesenchymal clones lose epithelial markers, display larger cell aspect ratios and lower motility, with mostly unaltered proliferation rates. Stemness marker expression and metabolic rewiring diverge independently of phenotypes. In 3D culture, more epithelial clones become mesenchymal-like. Thus, non-cancerous epithelial cells may acquire cancer metastasis-associated features prior to genetic alterations and cancerous transformation.

The trichotomy of HER2 expression confers new insights into the understanding and managing for breast cancer stratified by HER2 status

Human epidermal growth factor receptor 2 (HER2) is a tyrosine kinase receptor that plays a carcinogenic role in breast cancer (BC) through gene amplification, mutation, or overexpression. Traditional methods of HER2 detection were divided into positive (immunohistochemistry (IHC) 3+/fluorescence in situ hybridization (FISH) amplification) and negative (IHC 2+/FISH-, IHC 1+, IHC 0) according to the dichotomy method. Anti-HER2-targeted therapies, such as trastuzumab and pertuzumab, have significantly improved the prognosis of HER2-positive patients. However, up to 75% to 85% of patients remain HER2-negative. In recent years, with the rapid development of molecular biology, gene detection technology, targeted therapy, and immunotherapy, researchers have actively explored the clinicopathological characteristics, molecular biological characteristics, treatment methods, and HER2 detection methods of HER2-low/zero breast cancer. With the clinical efficacy of new anti-HER2 targeted drugs, accurate classification of breast cancer is very important for the treatment choice. Therefore, the following review summarizes the necessity of developing HER2 detection methods, and the clinicopathological and drug treatment characteristics of patients with HER2-low/zero, to light the dawn of the treatment of breast cancer patients with HER2-low/zero expression.

Amplification of Wild-Type RET Represents a Novel Molecular Subtype of Several Cancer Types With Clinical Response to Selpercatinib

PURPOSE

RET rearrangements and RET activating point mutations represent targetable genomic alterations in advanced solid tumors. However, the frequency and clinicopathologic characteristics of wild-type RET amplification in cancer and its potential role as a targetable oncogenic driver are not well-characterized.

METHODS

In two institutional cohorts of patients with solid cancers from the Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering Cancer Center (MSKCC) whose tumors underwent next-generation sequencing (NGS), the frequency and clinicopathologic features of wild-type RET amplification in the absence of RET rearrangements or activating mutations was assessed. The findings were validated using merged data from The Cancer Genome Atlas (TCGA), Genomics Evidence Neoplasia Information Exchange (GENIE), and China Pan-Cancer data sets.

RESULTS

The frequency of wild-type RET amplification across all solid cancers was 0.08% (26 of 32,505) in the DFCI cohort, 0.05% (26 of 53,152) in the MSKCC cohort, and 0.25% (71 of 28,623) in the cohort from TCGA, GENIE, and China Pan-Cancer. Cancer types with RET amplification included non-small-cell lung cancer (NSCLC), hepatobiliary cancer, prostate cancer, breast cancer, and others. The median RET copy number in RET-amplified cases was 7.5 (range, 6-36) in the DFCI cohort and 5.7 (range, 4-27.7) in the MSKCC cohort. Among 11 RET-amplified NSCLCs, eight had no other concurrent driver mutations. Finally, we report on a 69-year-old man with recurrent NSCLC harboring high-level wild-type RET amplification (22-28 copies) as the only identified putative genomic driver who experienced both a systemic and intracranial confirmed response to the RET inhibitor selpercatinib.

CONCLUSION

Amplification of wild-type RET represents a novel, targetable molecular subset of cancer.

BRCA1 and NORE1A Form a Her2/Ras Regulated Tumor Suppressor Complex Modulating Senescence

BRCA1 is a tumor suppressor with a complex mode of action. Hereditary mutations in BRCA1 predispose carriers to breast cancer, and spontaneous breast cancers often exhibit defects in BRCA1 expression. However, haploinsufficiency or suppression of BRCA1 expression leads to defects in DNA repair, which can induce DNA damage responses, leading to senescence. Activating mutation or overexpression of the Her2 oncoprotein are also frequent drivers of breast cancer. Yet, over-activation of Her2, working through the RAS oncoprotein, can also induce senescence. It is thought that additional defects in the p53 and Rb tumor suppressor machinery must occur in such tumors to allow an escape from senescence, thus permitting tumor development. Although BRCA1 mutant breast cancers are usually Her2 negative, a significant percentage of Her2 positive tumors also lose their expression of BRCA1. Such Her2+/BRCA1- tumors might be expected to have a particularly high senescence barrier to overcome. An important RAS senescence effector is the protein NORE1A, which can modulate both p53 and Rb. It is an essential senescence effector of the RAS oncoprotein, and it is often downregulated in breast tumors by promotor methylation. Here we show that NORE1A forms a Her2/RAS regulated, endogenous complex with BRCA1 at sites of replication fork arrest. Suppression of NORE1A blocks senescence induction caused by BRCA1 inactivation and Her2 activation. Thus, NORE1A forms a tumor suppressor complex with BRCA1. Its frequent epigenetic inactivation may facilitate the transformation of Her2+/BRCA1- mediated breast cancer by suppressing senescence.

Elevated APE1 Dysregulates Homologous Recombination and Cell Cycle Driving Genomic Evolution, Tumorigenesis, and Chemoresistance in Esophageal Adenocarcinoma

BACKGROUND & AIMS

The purpose of this study was to identify drivers of genomic evolution in esophageal adenocarcinoma (EAC) and other solid tumors.

METHODS

An integrated genomics strategy was used to identify deoxyribonucleases correlating with genomic instability (as assessed from total copy number events in each patient) in 6 cancers. Apurinic/apyrimidinic nuclease 1 (APE1), identified as the top gene in functional screens, was either suppressed in cancer cell lines or overexpressed in normal esophageal cells and the impact on genome stability and growth was monitored in vitro and in vivo. The impact on DNA and chromosomal instability was monitored using multiple approaches, including investigation of micronuclei, acquisition of single nucleotide polymorphisms, whole genome sequencing, and/or multicolor fluorescence in situ hybridization.

RESULTS

Expression of 4 deoxyribonucleases correlated with genomic instability in 6 human cancers. Functional screens of these genes identified APE1 as the top candidate for further evaluation. APE1 suppression in EAC, breast, lung, and prostate cancer cell lines caused cell cycle arrest; impaired growth and increased cytotoxicity of cisplatin in all cell lines and types and in a mouse model of EAC; and inhibition of homologous recombination and spontaneous and chemotherapy-induced genomic instability. APE1 overexpression in normal cells caused a massive chromosomal instability, leading to their oncogenic transformation. Evaluation of these cells by means of whole genome sequencing demonstrated the acquisition of changes throughout the genome and identified homologous recombination as the top mutational process.

CONCLUSIONS

Elevated APE1 dysregulates homologous recombination and cell cycle, contributing to genomic instability, tumorigenesis, and chemoresistance, and its inhibitors have the potential to target these processes in EAC and possibly other cancers.

Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosis

Background

Lung adenocarcinoma (LUAD) as a frequent type of lung cancer has a 5-year overall survival rate of lower than 20% among patients with advanced lung cancer. This study aims to construct a risk model to guide immunotherapy in LUAD patients effectively.

Materials and methods

LUAD Bulk RNA-seq data for the construction of a model, single-cell RNA sequencing (scRNA-seq) data (GSE203360) for cell cluster analysis, and microarray data (GSE31210) for validation were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used the Seurat R package to filter and process scRNA-seq data. Sample clustering was performed in the ConsensusClusterPlus R package. Differentially expressed genes (DEGs) between two groups were mined by the Limma R package. MCP-counter, CIBERSORT, ssGSEA, and ESTIMATE were employed to evaluate immune characteristics. Stepwise multivariate analysis, Univariate Cox analysis, and Lasso regression analysis were conducted to identify key prognostic genes and were used to construct the risk model. Key prognostic gene expressions were explored by RT-qPCR and Western blot assay.

Results

A total of 27 immune cell marker genes associated with prognosis were identified for subtyping LUAD samples into clusters C3, C2, and C1. C1 had the longest overall survival and highest immune infiltration among them, followed by C2 and C3. Oncogenic pathways such as VEGF, EFGR, and MAPK were more activated in C3 compared to the other two clusters. Based on the DEGs among clusters, we confirmed seven key prognostic genes including CPA3, S100P, PTTG1, LOXL2, MELTF, PKP2, and TMPRSS11E. Two risk groups defined by the seven-gene risk model presented distinct responses to immunotherapy and chemotherapy, immune infiltration, and prognosis. The mRNA and protein level of CPA3 was decreased, while the remaining six gene levels were increased in clinical tumor tissues.

Conclusion

Immune cell markers are effective in clustering LUAD samples into different subtypes, and they play important roles in regulating the immune microenvironment and cancer development. In addition, the seven-gene risk model may serve as a guide for assisting in personalized treatment in LUAD patients.

The postulated innocuity of lifetime exposure to aluminium should be reappraised

Because of its chemical versatility and abundance in nature, aluminium is employed in a myriad of frequently used products - including cosmetics and food additives - and applications - drinking water purification procedures being an example. Despite what its widespread use might suggest, aluminium's harmlessness is a matter of debate in the scientific community. In this article we trace the lines of a growing questioning about the potential mutagenic effects of this metal, due to the data produced over the recent years, and with an eye to the discussions currently underway in this regard between the scientific community, industry, and regulatory bodies.

Changes in the mammary gland during aging and its links with breast diseases

The functional capacity of organisms declines in the process of aging. In the case of breast tissue, abnormal mammary gland development can lead to dysfunction in milk secretion, a primary function, as well as the onset of various diseases, such as breast cancer. In the process of aging, the terminal duct lobular units (TDLUs) within the breast undergo gradual degeneration, while the proportion of adipose tissue in the breast continues to increase and hormonal levels in the breast change accordingly. Here, we review changes in morphology, internal structure, and cellular composition that occur in the mammary gland during aging. We also explore the emerging mechanisms of breast aging and the relationship between changes during aging and breast-related diseases, as well as potential interventions for delaying mammary gland aging and preventing breast disease.

Design of a novel aptamer/molecularly imprinted polymer hybrid modified Ag-Au@Insulin nanoclusters/Au-gate-based MoS2 nanosheet field-effect transistor for attomolar detection of BRCA1 gene

Early detection of breast cancer, the first main cause of death in women, with robust assay platforms using appropriate biomarkers is of great importance for diagnosis and follow-up of the disease progression. This paper introduces an extra selective and sensitive label-free aptasensor for the screening of BRCA1 gene biomarker by taking advantage of a gate modified with aptamer and molecularly imprinted polymer hybrid (MIP) as a new synthetic receptor film coupled with an electrolyte-gated molybdenum disulfide (MoS2) field-effect transistor (FET). The Au gate surface of FET was modified with insulin stabilized bimetallic Ag-Au@nanoclusters (Ag-Au@InsNCs), after which, the immobilization of the hybridized aptamer and o-phenylenediamine was electropolymerized to form an aptamer-MIP hybrid receptor. The output characteristics of Apta-MIP hybrid modified Au gate MoS2 FET device were followed as a result of change in electrical double layer capacitance of electrolye-gate interface. The magnitude of decrease in the drain current showed a linear response over a wide concentration range of 10 aM to 1 nM of BRCA1 ssDNA with a sensitivity as high as 0.4851 μA/decade of concentration and a limit of detection (LOD) of 3.0 aM while very low responses observed for non-imprinted polymer. The devised aptasensor not only was capable to the discrimination of the complementary versus one-base mismatch BRCA1 ssDNA sequence, but also it could detect the complementary BRCA1 ssDNA in spiked human serum samples over a wide concentration range of 10 aM to 1.0 nM with a low LOD of 6.4 aM and a high sensitivity 0.3718 μA/decade.

CNVs in 8q24.3 do not influence gene co-expression in breast cancer subtypes

Gene co-expression networks are a useful tool in the study of interactions that have allowed the visualization and quantification of diverse phenomena, including the loss of co-expression over long distances in cancerous samples. This characteristic, which could be considered fundamental to cancer, has been widely reported in various types of tumors. Since copy number variations (CNVs) have previously been identified as causing multiple genetic diseases, and gene expression is linked to them, they have often been mentioned as a probable cause of loss of co-expression in cancerous networks. In order to carry out a comparative study of the validity of this statement, we took 477 protein-coding genes from chromosome 8, and the CNVs of 101 genes, also protein-coding, belonging to the 8q24.3 region, a cytoband that is particularly active in the appearance of breast cancer. We created CNVS-conditioned co-expression networks of each of the 101 genes in the 8q24.3 region using conditional mutual information. The study was carried out using the four molecular subtypes of breast cancer (Luminal A, Luminal B, Her2, and Basal), as well as a case corresponding to healthy samples. We observed that in all cancer cases, the measurement of the Kolmogorov-Smirnov statistic shows that there are no significant differences between one and other values of the CNVs for any case. Furthermore, the co-expression interactions are stronger in all cancer subtypes than in the control networks. However, the control network presents a homogeneously distributed set of co-expression interactions, while for cancer networks, the highest interactions are more confined to specific cytobands, in particular 8q24.3 and 8p21.3. With this approach, we demonstrate that despite copy number alterations in the 8q24 region being a common trait in breast cancer, the loss of long-distance co-expression in breast cancer is not determined by CNVs.

CINmetrics: an R package for analyzing copy number aberrations as a measure of chromosomal instability

Genomic instability is an important hallmark of cancer and more recently has been identified in others like neurodegenrative diseases. Chromosomal instability, as a measure of genomic instability, has been used to characterize clinical and biological phenotypes associated with these diseases by measuring structural and numerical chromosomal alterations. There have been multiple chromosomal instability scores developed across many studies in the literature; however, these scores have not been compared because of the lack of a single tool available to calculate and facilitate these various metrics. Here, we provide an R package CINmetrics, that calculates six different chromosomal instability scores and allows direct comparison between them. We also demonstrate how these scores differ by applying CINmetrics to breast cancer data from The Cancer Genome Atlas (TCGA). The package is available on CRAN at https://cran.rproject.org/package=CINmetrics and on GitHub at https://github.com/lasseignelab/CINmetrics.

COMMD3 loss drives invasive breast cancer growth by modulating copper homeostasis

BACKGROUND

Despite overall improvement in breast cancer patient outcomes from earlier diagnosis and personalised treatment approaches, some patients continue to experience recurrence and incurable metastases. It is therefore imperative to understand the molecular changes that allow transition from a non-aggressive state to a more aggressive phenotype. This transition is governed by a number of factors.

METHODS

As crosstalk with extracellular matrix (ECM) is critical for tumour cell growth and survival, we applied high throughput shRNA screening on a validated '3D on-top cellular assay' to identify novel growth suppressive mechanisms.

RESULTS

A number of novel candidate genes were identified. We focused on COMMD3, a previously poorly characterised gene that suppressed invasive growth of ER + breast cancer cells in the cellular assay. Analysis of published expression data suggested that COMMD3 is normally expressed in the mammary ducts and lobules, that expression is lost in some tumours and that loss is associated with lower survival probability. We performed immunohistochemical analysis of an independent tumour cohort to investigate relationships between COMMD3 protein expression, phenotypic markers and disease-specific survival. This revealed an association between COMMD3 loss and shorter survival in hormone-dependent breast cancers and in particularly luminal-A-like tumours (ER+/Ki67-low; 10-year survival probability 0.83 vs. 0.73 for COMMD3-positive and -negative cases, respectively). Expression of COMMD3 in luminal-A-like tumours was directly associated with markers of luminal differentiation: c-KIT, ELF5, androgen receptor and tubule formation (the extent of normal glandular architecture; p < 0.05). Consistent with this, depletion of COMMD3 induced invasive spheroid growth in ER + breast cancer cell lines in vitro, while Commd3 depletion in the relatively indolent 4T07 TNBC mouse cell line promoted tumour expansion in syngeneic Balb/c hosts. Notably, RNA sequencing revealed a role for COMMD3 in copper signalling, via regulation of the Na+/K+-ATPase subunit, ATP1B1. Treatment of COMMD3-depleted cells with the copper chelator, tetrathiomolybdate, significantly reduced invasive spheroid growth via induction of apoptosis.

CONCLUSION

Overall, we found that COMMD3 loss promoted aggressive behaviour in breast cancer cells.

The Cancer Genomic Integration Model for Symptom Science (CGIMSS): A Biopsychosocial Framework

Current nursing research has characterized symptom clusters and trajectories in individuals with breast cancer. The existing literature describes the relationship between symptoms and biological variables and the potential moderating effects of individual and social factors. The genomic profiling of breast cancer has also been an area of much recent research. Emerging evidence indicates that incorporating cancer genomics into symptom science research can aid in the prognostication of symptoms and elucidate targets for symptom management interventions. The aim of this paper is to outline a model to integrate cancer genomics into symptom science research, illustrated using breast cancer and psychoneurological (PN) symptoms as an example. We present a review of the current literature surrounding breast cancer genomics (specifically cancer genomic instability) and the biological underpinnings of the PN symptom cluster. Advances in both of these areas indicate that inflammation may serve as the bridge between cancer genomics and the PN symptom cluster. We also outline how the integration of cancer genomics into symptom science research synergizes with current research of individual and social factors in relation to symptoms. This model aims to provide a framework to guide future biopsychosocial symptom science research that can elucidate new predictive methods and new targets for intervention.

Identifying tumour microenvironment-related signature that correlates with prognosis and immunotherapy response in breast cancer

Tumor microenvironment (TME) plays important roles in prognosis and immune evasion. However, the relationship between TME-related genes and clinical prognosis, immune cell infiltration, and immunotherapy response in breast cancer (BRCA) remains unclear. This study described the TME pattern to construct a TME-related prognosis signature, including risk factors PXDNL, LINC02038 and protective factors SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108, as an independent prognostic factor for BRCA. We found that the prognosis signature was negatively correlated with the survival time of BRCA patients, infiltration of immune cells and the expression of immune checkpoints, while positively correlated with tumor mutation burden and adverse treatment effects of immunotherapy. Upregulation of PXDNL and LINC02038 and downregulation of SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108 in high-risk score group synergistically contribute to immunosuppressive microenvironment which characterized by immunosuppressive neutrophils, impaired cytotoxic T lymphocytes migration and natural killer cell cytotoxicity. In summary, we identified a TME-related prognostic signature in BRCA, which was connected with immune cell infiltration, immune checkpoints, immunotherapy response and could be developed for immunotherapy targets.

The progress in our understanding of CIN in breast cancer research

Chromosomal instability (CIN) is an important marker of cancer, which is closely related to tumorigenesis, disease progression, treatment efficacy, and patient prognosis. However, due to the limitations of the currently available detection methods, its exact clinical significance remains unknown. Previous studies have demonstrated that 89% of invasive breast cancer cases possess CIN, suggesting that it has potential application in breast cancer diagnosis and treatment. In this review, we describe the two main types of CIN and discuss the associated detection methods. Subsequently, we highlight the impact of CIN in breast cancer development and progression and describe how it can influence treatment and prognosis. The goal of this review is to provide a reference on its mechanism for researchers and clinicians.

Development and validation of a genomic instability-related lncRNA prognostic model for hepatocellular carcinoma

Genomic instability is a characteristic of tumors, and recent studies have shown that it is related to a poor prognosis of multiple cancers. Long non-coding RNAs (lncRNAs) have become a research hotspot in recent years, and many unknown biological functions are being explored. For example, some lncRNAs play a critical role in the initiation and progression of multiple cancer types by modulating genomic instability. However, the role of genomic instability-related lncRNAs in liver cancer remains unclear. Therefore, we screened genomic instability-related lncRNAs by combining somatic mutation data and RNA-Seq data in The Cancer Genome Atlas (TCGA) database. We established a genomic instability-related lncRNA model (GLncM) involving ZFPM2-AS1 and MIR210HG to predict the hepatocellular carcinoma (HCC) prognosis and further explore the clinical significance of these lncRNAs, and the robustness of the model was validated in the verification set. Thereafter, we calculated the immune score for each patient and explored the relationship between genome instability and the immune microenvironment. The analysis indicated that this model was better than the immune microenvironment in predicting the prognosis of HCC patients, suggesting that the GLncM may be an effective indicator of HCC prognosis and providing a new direction and strategy for estimating the prognosis of HCC patients.

Physical Exercise and the Hallmarks of Breast Cancer: A Narrative Review

Growing evidence suggests that, among the different molecular/cellular pathophysiological mechanisms associated with cancer, there are 14 hallmarks that play a major role, including: (i) sustaining proliferative signaling, (ii) evading growth suppressors, (iii) activating invasion and metastasis, (iv) enabling replicative immortality, (v) inducing angiogenesis, (vi) resisting cell death, (vii) reprogramming energy metabolism, (viii) evading immune destruction, (ix) genome instability and mutations, (x) tumor-promoting inflammation, (xi) unlocking phenotypic plasticity, (xii) nonmutational epigenetic reprogramming, (xiii) polymorphic microbiomes, and (xiv) senescent cells. These hallmarks are also associated with the development of breast cancer, which represents the most prevalent tumor type in the world. The present narrative review aims to describe, for the first time, the effects of physical activity/exercise on these hallmarks. In summary, an active lifestyle, and particularly regular physical exercise, provides beneficial effects on all major hallmarks associated with breast cancer, and might therefore help to counteract the progression of the disease or its associated burden.

Chromosomal Instability as Enabling Feature and Central Hallmark of Breast Cancer

Chromosomal instability (CIN) has become a topic of great interest in recent years, not only for its implications in cancer diagnosis and prognosis but also for its role as an enabling feature and central hallmark of cancer. CIN describes cell-to-cell variation in the number or structure of chromosomes in a tumor population. Although extensive research in recent decades has identified some associations between CIN with response to therapy, specific associations with other hallmarks of cancer have not been fully evidenced. Such associations place CIN as an enabling feature of the other hallmarks of cancer and highlight the importance of deepening its knowledge to improve the outcome in cancer. In addition, studies conducted to date have shown paradoxical findings about the implications of CIN for therapeutic response, with some studies showing associations between high CIN and better therapeutic response, and others showing the opposite: associations between high CIN and therapeutic resistance. This evidences the complex relationships between CIN with the prognosis and response to treatment in cancer. Considering the above, this review focuses on recent studies on the role of CIN in cancer, the cellular mechanisms leading to CIN, its relationship with other hallmarks of cancer, and the emerging therapeutic approaches that are being developed to target such instability, with a primary focus on breast cancer. Further understanding of the complexity of CIN and its association with other hallmarks of cancer could provide a better understanding of the cellular and molecular mechanisms involved in prognosis and response to treatment in cancer and potentially lead to new drug targets.

Anticancer potential of Marina Crystal Minerals (MCM) against the growth of murine mammary adenocarcinoma cells in vivo

In vitro studies have shown that Marina Crystal Minerals (MCM), a crystallized mixture of minerals and trace elements from sea water, possesses apoptotic and immune modulatory effects in human breast cancer cells MDA-MB-231. The current study aimed to evaluate MCM's anticancer effect in vivo against murine mammary adenocarcinoma cells and to explore its underlying mechanisms. Mice were inoculated intramuscularly with Ehrlich ascites carcinoma (EAC) cells, a breast adenocarcinoma. Tumors became palpable within 9 days. Tumor-bearing mice were injected with MCM intraperitoneally (IP) or intratumorally (IT) at a dose of 40 mg/kg BW for 6 days/week until day 28 post-inoculation. Tumor growth, cell cycle progression, cell cycle regulatory proteins, apoptosis, apoptotic regulatory markers, mitochondrial membrane potential (MMP), natural killer (NK) cell activity, and histopathological effects were investigated. Treatment with MCM reduced tumor volume by 49.4% for IP and 59.5% for IT injection. MCM induced cancer cell apoptosis, as indicated by a sub-G1 peak and confirmed by Annexin V/PI assay and histopathological examination. This was mediated by increased Bax expression, caspase-3 activation, decreased Bcl-2 expression, and MMP disruption. Furthermore, MCM treatment induced G1 cell cycle arrest, mediated through significantly increased expression of p53, p21, and p27 and decreased expression of cyclin D1 and PCNA in cancer cells. Finally, MCM treatment markedly enhanced NK cell cytotoxicity. MCM possesses chemopreventive potential to reduce tumor growth by suppressing cell proliferation, inducing apoptosis in EAC cells via a mitochondrial dependent pathway, and activating the immune system. Our results suggest MCM's beneficial potential for treating breast adenocarcinoma.

Epigenomic and Other Evidence for Cannabis-Induced Aging Contextualized in a Synthetic Epidemiologic Overview of Cannabinoid-Related Teratogenesis and Cannabinoid-Related Carcinogenesis

BACKGROUND

Twelve separate streams of empirical data make a strong case for cannabis-induced accelerated aging including hormonal, mitochondriopathic, cardiovascular, hepatotoxic, immunological, genotoxic, epigenotoxic, disruption of chromosomal physiology, congenital anomalies, cancers including inheritable tumorigenesis, telomerase inhibition and elevated mortality.

METHODS

Results from a recently published longitudinal epigenomic screen were analyzed with regard to the results of recent large epidemiological studies of the causal impacts of cannabis. We also integrate theoretical syntheses with prior studies into these combined epigenomic and epidemiological results.

RESULTS

Cannabis dependence not only recapitulates many of the key features of aging, but is characterized by both age-defining and age-generating illnesses including immunomodulation, hepatic inflammation, many psychiatric syndromes with a neuroinflammatory basis, genotoxicity and epigenotoxicity. DNA breaks, chromosomal breakage-fusion-bridge morphologies and likely cycles, and altered intergenerational DNA methylation and disruption of both the histone and tubulin codes in the context of increased clinical congenital anomalies, cancers and heritable tumors imply widespread disruption of the genome and epigenome. Modern epigenomic clocks indicate that, in cannabis-dependent patients, cannabis advances cellular DNA methylation age by 25-30% at age 30 years. Data have implications not only for somatic but also stem cell and germ line tissues including post-fertilization zygotes. This effect is likely increases with the square of chronological age.

CONCLUSION

Recent epigenomic studies of cannabis exposure provide many explanations for the broad spectrum of cannabis-related teratogenicity and carcinogenicity and appear to account for many epidemiologically observed findings. Further research is indicated on the role of cannabinoids in the aging process both developmentally and longitudinally, from stem cell to germ cell to blastocystoids to embryoid bodies and beyond.

The signature based on seven genomic instability-related genes could predict the prognosis of acute myeloid leukemia patients

BACKGROUND

Acute myeloid leukemia (AML) is the most common acute blood malignancy in adults. The complicated and dynamic genomic instability (GI) is the most prominent feature of AML. Our study aimed to explore the prognostic value of GI-related genes in AML patients.

METHODS

The mRNA data and mutation data were downloaded from the TCGA and GEO databases. Differential expression analyses were completed in limma package. GO and KEGG functional enrichment was conducted using clusterProfiler function of R. Univariate Cox and LASSO Cox regression analyses were performed to screen key genes for Risk score model construction. Nomogram was built with rms package.

RESULTS

We identified 114 DEGs between high TMB patients and low TMB AML patients, which were significantly enriched in 429 GO terms and 13 KEGG pathways. Based on the univariate Cox and LASSO Cox regression analyses, seven optimal genes were finally applied for Risk score model construction, including SELE, LGALS1, ITGAX, TMEM200A, SLC25A21, S100A4 and CRIP1. The Risk score could reliably predict the prognosis of AML patients. Age and Risk score were both independent prognostic indicators for AML, and the Nomogram based on them could also reliably predict the OS of AML patients.

CONCLUSIONS

A prognostic signature based on seven GI-related genes and a predictive Nomogram for AML patients are finally successfully constructed.

High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders

Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform ( https://pandaomics.com/ ) to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets. Our analysis revealed that CEP135, a scaffolding protein associated with early centriole biogenesis, is commonly downregulated in DNA repair diseases with high cancer predisposition. Further screening of survival data in 33 cancers available at TCGA database identified sarcoma as a cancer type where lower survival was significantly associated with high CEP135 expression. Stratification of cancer patients based on CEP135 expression enabled us to examine therapeutic targets that could be used for the improvement of existing therapies against sarcoma. The latter was based on application of the PandaOmics target-ID algorithm coupled with in vitro studies that revealed polo-like kinase 1 (PLK1) as a potential therapeutic candidate in sarcoma patients with high CEP135 levels and poor survival. While further target validation is required, this study demonstrated the potential of in silico-based studies for a rapid biomarker discovery and target characterization.

Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications

We aimed to identify miRNAs that were closely related to breast cancer (BRCA). By integrating several methods including significance analysis of microarrays, fold change, Pearson’s correlation analysis, t test, and receiver operating characteristic analysis, we developed a decision-tree-based scoring algorithm, called Optimized Scoring Mechanism for Primary Synergy MicroRNAs (O-PSM). Five synergy miRNAs (hsa-miR-139-5p, hsa-miR-331-3p, hsa-miR-342-5p, hsa-miR-486-5p, and hsa-miR-654-3p) were identified using O-PSM, which were used to distinguish normal samples from pathological ones, and showed good results in blood data and in multiple sets of tissue data. These five miRNAs showed accurate categorization efficiency in BRCA typing and staging and had better categorization efficiency than experimentally verified miRNAs. In the Protein-Protein Interaction (PPI) network, the target genes of hsa-miR-342-5p have the most regulatory relationships, which regulate carcinogenesis proliferation and metastasis by regulating Glycosaminoglycan biosynthesis and the Rap1 signaling pathway. Moreover, hsa-miR-342-5p showed potential clinical application in survival analysis. We also used O-PSM to generate an R package uploaded on github (SuFei-lab/OPSM accessed on 22 October 2021). We believe that miRNAs included in O-PSM could have clinical implications for diagnosis, prognostic stratification and treatment of BRCA, proposing potential significant biomarkers that could be utilized to design personalized treatment plans in BRCA patients in the future.

Chromosome instability in neuroblastoma: A pathway to aggressive disease

For over 100-years, genomic instability has been investigated as a central player in the pathogenesis of human cancer. Conceptually, genomic instability includes an array of alterations from small deletions/insertions to whole chromosome alterations, referred to as chromosome instability. Chromosome instability has a paradoxical impact in cancer. In most instances, the introduction of chromosome instability has a negative impact on cellular fitness whereas in cancer it is usually associated with a worse prognosis. One exception is the case of neuroblastoma, the most common solid tumor outside of the brain in children. Neuroblastoma tumors have two distinct patterns of genome instability: whole-chromosome aneuploidy, which is associated with a better prognosis, or segmental chromosomal alterations, which is a potent negative prognostic factor. Through a computational screen, we found that low levels of the de- ubiquitinating enzyme USP24 have a highly significant negative impact on survival in neuroblastoma. At the molecular level, USP24 loss leads to destabilization of the microtubule assembly factor CRMP2 - producing mitotic errors and leading to chromosome missegregation and whole-chromosome aneuploidy. This apparent paradox may be reconciled through a model in which whole chromosome aneuploidy leads to the subsequent development of segmental chromosome alterations. Here we review the mechanisms behind chromosome instability and the evidence for the progressive development of segmental alterations from existing numerical aneuploidy in support of a multi-step model of neuroblastoma progression.