Mechanisms of Genomic Instability in Breast Cancer

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.

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.

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.

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.

Genomic Instability in Cerebrospinal Fluid Cell-Free DNA Predicts Poor Prognosis in Solid Tumor Patients with Meningeal Metastasis

Simple Summary

We established a genomic instability score using unfiltered sequencing data from meningeal metastasis (MM) cell-free circulating tumor DNA (ctDNA) samples and found that substantial genomic instability (GI) was present in cerebrospinal fluid ctDNA rather than plasma ctDNA, implying that MM lesions have a significantly increased GI status compared to primary tumors or extracranial metastatic lesions, which may suggest tumor clonal evolution. We also found that high GI status was an independent poor prognostic factor in lung adenocarcinoma MM patients, including meningeal metastasis-free survival (MFS) and overall survival (OS). Considering that genomically unstable tumors are more sensitive to PARP inhibitors, targeting GI alone or in combination with conventional therapy may be a promising treatment strategy for solid tumor patients with MM.

Abstract

Genomic instability (GI), which leads to the accumulation of DNA loss, gain, and rearrangement, is a hallmark of many cancers such as lung cancer, breast cancer, and colon cancer. However, the clinical significance of GI has not been systematically studied in the meningeal metastasis (MM) of solid tumors. Here, we collected both cerebrospinal fluid (CSF) and plasma samples from 56 solid tumor MM patients and isolated cell-free ctDNA to investigate the GI status using a next-generation sequencing-based comprehensive genomic profiling of 543 cancer-related genes. According to the unfiltered heterozygous mutation data-derived GI score, we found that 37 (66.1%) cases of CSF and 3 cases (6%) of plasma had a high GI status, which was further validated by low-depth whole-genome sequencing analysis. It is demonstrated that a high GI status in CSF was associated with poor prognosis, high intracranial pressure, and low Karnofsky performance status scores. More notably, a high GI status was an independent poor prognostic factor of poor MM-free survival and overall survival in lung adenocarcinoma MM patients. Furthermore, high occurrences of the co-mutation of TP53/EGFR, TP53/RB1, TP53/ERBB2, and TP53/KMT2C were found in MM patients with a high GI status. In summary, the GI status in CSF ctDNA might be a valuable prognostic indicator in solid tumor patients with MM.

Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Genome instability is a hallmark of cancer, and the function of lncRNAs in regulating genomic stability has been gradually characterized. However, the prognostic value of lncRNAs related to genetic instability has not been found in breast cancer. Here we constructed a genetic instability-related lncRNA model including U62317.4, SEMA3B-AS1, MAPT-AS1, AC115837.2, LINC01269, AL645608.7, and GACAT2. This model can evaluate the risk and predict the survival outcomes of patients. Further analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immunity and cornified envelope formation pathways. In addition, M2 macrophages infiltrated more obviously in the high-risk group. In summary, lncRNAs related to genetic instability may influence the development of breast cancer through immune infiltration and keratinization. This study provides a wider insight into breast cancer development and treatment.

Identification of genomic instability related lncRNA signature with prognostic value and its role in cancer immunotherapy in pancreatic cancer

Background: Increasing evidence suggested the critical roles of lncRNAs in the maintenance of genomic stability. However, the identification of genomic instability-related lncRNA signature (GILncSig) and its role in pancreatic cancer (PC) remains largely unexplored.

Methods: In the present study, a systematic analysis of lncRNA expression profiles and somatic mutation profiles was performed in PC patients from The Cancer Genome Atlas (TCGA). We then develop a risk score model to describe the characteristics of the model and verify its prediction accuracy. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the correlation between tumor immune microenvironment, immune infiltration, immune checkpoint blockade (ICB) therapy, and GILncSig in PC.

Results: We identified 206 GILnc, of which five were screened to develop a prognostic GInLncSig model. Multivariate Cox regression analysis and stratified analysis revealed that the prognostic value of the GILncSig was independent of other clinical variables. Receiver operating characteristic (ROC) analysis suggested that GILncSig is better than the existing lncRNA-related signatures in predicting survival. Additionally, the prognostic performance of the GILncSig was also found to be favorable in patients carrying wild-type KRAS, TP53, and SMAD4. Besides, a nomogram exhibited appreciable reliability for clinical application in predicting the prognosis of patients. Finally, the relationship between the GInLncSig model and the immune landscape in PC reflected its application value in clinical immunotherapy.

Conclusion: In summary, the GILncSig identified by us may serve as novel prognostic biomarkers, and could have a crucial role in immunotherapy decisions for PC patients.

Harnessing gene fusion-derived neoantigens for 'cold' breast and prostate tumor immunotherapy

Breast and prostate cancers are generally considered immunologically 'cold' tumors due to multiple mechanisms rendering them unresponsive to immune checkpoint blockade therapies. With little success in garnering positive outcomes in modern immunotherapeutic clinical trials, it is prudent to re-examine the role of immunogenic neoantigens in these cold tumors. Gene fusions are driver mutations in hormone-driven cancers that can result in alternative mutation-specific neoantigens to promote immunotherapy sensitivity. This review focuses on 1) gene fusion formation mechanisms in neoantigen generation; 2) gene fusion neoantigens in cancer immunotherapeutic strategies and associated clinical trials; and 3) challenges and opportunities in computational and liquid biopsy technologies. This review is anticipated to initiate further research into gene fusion neoantigens of cold tumors for further experimental validation.

A Genomic Instability-Related Long Noncoding RNA Signature for Predicting Hepatocellular Carcinoma Prognosis

Background. Long noncoding RNAs (lncRNAs) are found to be novel biomarkers for hepatocellular carcinoma (HCC) and play an important role in tumor progression. We established a genomic instability-related long noncoding RNA signature (GIlncSig) as an independent prognosis factor and also investigated its impact on prognosis significance. Method. Somatic mutation profiles, clinical characteristics, and RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database. Lasso regression was used to construct GIlncSig. KEGG was used to identify the possible biological pathways. ESTIMATE and CIBERSORT algorithms were used to calculate the immune microenvironment scores and proportion of immune cells in HCC patients. The expression of LINC00501 was conducted by qRT-PCR. Cell proliferation was measured by EdU, CCK-8, and colony formation assay, and cell migration and invasion ability were measured by wound healing and transwell assay. Results. 135 genomic instability-related lncRNAs were identified, and GIlncSig was constructed using 13 independent lncRNAs with significant prognosis values. Based on the GIlncSig, high-risk group had worse clinical outcomes than low-risk group, while high-risk group also had higher UBQLN4, KRAS, ARID1A, and PIK3CA expression. Moreover, the efficiency of GIlncSig combining single-gene mutation was higher than single-gene mutation alone such as TP53. The results of CIBERSORT and ESTIMATE showed that GS group and GU group had significantly different immune infiltration. In addition, LINC00501 was identified as a potential biomarker in HCC with strong relationship with clinical characteristics. In vitro assays validated that LINC00501 promoted proliferation and migration of HCC cell lines. Conclusion. Our results showed that GIlncSig serves as a potential independent prognosis factor to predict HCC patients’ prognosis for exploring potential mechanism and therapy strategy. Besides, LINC00501 plays an important role in the progression of HCC, which may be a potential therapy target.

The correlation between neutrophil-to-lymphocyte ratio, carcinoembryonic antigen, and carbohydrate antigen 153 levels with chemotherapy-related cognitive impairment in early-stage breast cancer patients

Background

The changes in inflammation and tumor biomarkers are associated with the anti-tumor immunological processes. Early detection and intervention are of great significance to the clinical management of cancer-related diseases. Peripheral blood biomarkers [e.g., neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), and carbohydrate antigen 153 (CA153)] are obtained in real-timely, conveniently, and less invasively, and proved to availably predicted the disease states and prognosis of various cancers, including breast cancer (BC). Inflammation and poor disease management promote cognitive impairment. Chemotherapy-related cognitive impairment (CRCI) hazard long-term survival and quality of life (QOL) of BC patients, but its correlation with NLR, CEA, and CA153 is not clear.

Purpose

This study aimed to investigate changes in NLR, CEA, and CA153 levels before and after chemotherapy and their correlation with CRCI in patients with early-stage BC.

Materials and methods

The 187 patients with BC who were measured for NLR, CEA, and CA153 values within the first 24 hours of admission, were assigned into two groups: the before/after chemotherapy group (BCG/ACG). The ACG was assigned into two subgroups based on the cognitive assessment results: the cognitive normal/impaired group (CNG/CIG). Patients’ self-perceived cognitive impairments were evaluated using a mini-mental state examination (MMSE), prospective and retrospective memory (PM and RM) questionnaire (PRMQ), and functional assessment of cancer therapy-cognitive function version 3 (FACT-Cog, version 3, including CogPCI, CogOth, CogPCA, and CogQOL). Their QOL was also evaluated.

Results

The NLR and CA153 levels were elevated after chemotherapy (BCG vs ACG: Z = −1.996 and −1.615, P = 0.046 and 0.106, respectively), and significantly elevated in patients with CRCI (BCG vs CIG: Z = −2.444 and -2.293, P = 0.015 and 0.022; respectively). However, there was not reach significant difference in CEA levels between the four groups. In addition, there was a weak to moderate correlation between peripheral blood biomarkers (NLR, CEA, and CA153) levels and CRCI (r = −0.404, −0.205, −0.322; respectively; P < 0.001). Cognitive impairment scores (MMSE, PM, RM, and FACT-Cog) had a strong correlation with QOL in patients with early-stage BC (r = −0.786, 0.851, 0.849, and 0.938; respectively; P < 0.001).

Conclusion

NLR and CA153 m be valuable diagnostic adjuncts of CRCI, and CRCI has a strong correlation with QOL in patients with early-stage BC.

Novel insights into RB1 mutation

Since the discovery of the retinoblastoma susceptibility gene (RB1) decades ago, RB1 has been regarded as a prototype tumor suppressor gene providing a paradigm for tumor genetic research. Constant research has updated the understanding of RB1-related pathways and their impact on tumor and nontumor diseases. Mutation of RB1 gene has been observed in multiple types of malignant tumors including prostate cancer, lung cancer, breast cancer, and almost every familial and sporadic case of retinoblastoma. Even if well-known and long-investigated, the application potential of RB1 mutation has not been fully tapped. In this review, we focus on the mechanism underlying RB1 mutation during oncogenesis. Therapeutically, we have further discussed potential clinical strategies by targeting RB1-mutated cancers. The unsolved problems and prospects of RB1 mutation are also discussed.

A genomic instability-related lncRNA model for predicting prognosis and immune checkpoint inhibitor efficacy in breast cancer

Breast cancer has overtaken lung cancer as the most frequently diagnosed cancer type and is the leading cause of death for women worldwide. It has been demonstrated in published studies that long non-coding RNAs (lncRNAs) involved in genomic stability are closely associated with the progression of breast cancer, and remarkably, genomic stability has been shown to predict the response to immune checkpoint inhibitors (ICIs) in cancer therapy, especially colorectal cancer. Therefore, it is of interest to explore somatic mutator-derived lncRNAs in predicting the prognosis and ICI efficacy in breast cancer patients. In this study, the lncRNA expression data and somatic mutation data of breast cancer patients from The Cancer Genome Atlas (TCGA) were downloaded and analyzed thoroughly. Univariate and multivariate Cox proportional hazards analyses were used to generate the genomic instability-related lncRNAs in a training set, which was subsequently used to analyze a testing set and combination of the two sets. The qRT-PCR was conducted in both normal mammary and breast cancer cell lines. Furthermore, the Kaplan–Meier and receiver operating characteristic (ROC) curves were applied to validate the predictive effect in the three sets. Finally, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to evaluate the association between genomic instability-related lncRNAs and immune checkpoints. As a result, a six-genomic instability-related lncRNA signature (U62317.4, MAPT-AS1, AC115837.2, EGOT, SEMA3B-AS1, and HOTAIR) was identified as the independent prognostic risk model for breast cancer patients. Compared with the normal mammary cells, the qRT-PCR showed that HOTAIR was upregulated while MAPT-AS1, EGOT, and SEMA3B-AS1 were downregulated in breast cancer cells. The areas under the ROC curves at 3 and 5 years were 0.711 and 0.723, respectively. Moreover, the patients classified in the high-risk group by the prognostic model had abundant negative immune checkpoint molecules. In summary, this study suggested that the prognostic model comprising six genomic instability-related lncRNAs may provide survival prediction. It is necessary to identify patients who are suitable for ICIs to avoid severe immune-related adverse effects, especially autoimmune diseases. This model may predict the ICI efficacy, facilitating the identification of patients who may benefit from ICIs.

The cell cycle, cancer development and therapy

The process of cell division plays a vital role in cancer progression. Cell proliferation and error-free chromosomes segregation during mitosis are central events in life cycle. Mistakes during cell division generate changes in chromosome content and alter the balances of chromosomes number. Any defects in expression of TIF1 family proteins, SAC proteins network, mitotic checkpoint proteins involved in chromosome mis-segregation and cancer development. Here we discuss the function of organelles deal with the chromosome segregation machinery, proteins and correction mechanisms involved in the accurate chromosome segregation during mitosis.

The structural maintenance of chromosomes 5 is a possible biomarker for individualized treatment of colorectal cancer

BACKGROUND

Although the understanding of resistance to oxaliplatin (OXA) chemotherapy in colorectal cancer (CRC) has been sought for many years, drug tolerance remains a major challenge for cancer therapy. Revealing the molecular mechanism of OXA resistance could help to explain the poor prognosis of patients.

METHODS

Gene expression omnibus (GEO) database was searched, GSE83129, which contains RNA profiling in metastatic CRC patients treated first-line with OXA, was chosen for the following analysis. Differential expressed genes (DEGs) between the adenocarcinoma and adjacent_normal team, respectively, in the OXA responders and no-responders were analyzed. The Gene Ontology (GO) and hub genes in the protein-protein interaction (PPI) network were used for the molecular mechanism of OXA resistance. Tumor-related databases were used for the clinical relevance of the structural maintenance of chromosomes 5 (SMC5) in CRC. The in vitro assays were used to detect the molecular function of SMC5 in CRC cells. Quantitative real-time PCR (qRT-PCR) and western blot were used to detect the expression of the structural maintenance of chromosomes 5/6 (SMC5/6) complex components upon OXA and raltitrexed (RTX) treatment. CCK-8 was used to detect the cell viability of cells with different treatment.

RESULTS

SMC5 was downregulated in CRC tissues of OXA no-response patients. Lower expression of SMC5 was correlated with a poor prognosis in CRC patients, improved this gene expression, inhibited the CRC cell growth and invasion in vitro. Furthermore, SMC5 was downregulated upon OXA treatment in CRC cells, while RTX would reverse its expression, and the combination of these two drugs restored the SMC5 level to the normal situation. Finally, RTX treatment enhanced the OXA cytotoxicity.

CONCLUSION

SMC5 is a tumor suppressor, that low expression of this gene is benefit for the development of CRC. Combination treatment with RTX and OXA may be more suitable for those OXA no-responders with lower SMC5.

Identification of the prognostic signature based on genomic instability-related alternative splicing in colorectal cancer and its regulatory network

Background: Colorectal cancer (CRC) is a heterogeneous disease with many somatic mutations defining its genomic instability. Alternative Splicing (AS) events, are essential for maintaining genomic instability. However, the role of genomic instability-related AS events in CRC has not been investigated.

Methods: From The Cancer Genome Atlas (TCGA) program, we obtained the splicing profiles, the single nucleotide polymorphism, transcriptomics, and clinical information of CRC. Combining somatic mutation and AS events data, a genomic instability-related AS signature was constructed for CRC. Mutations analyses, clinical stratification analyses, and multivariate Cox regression analyses evaluated this signature in training set. Subsequently, we validated the sensitivity and specificity of this prognostic signature using a test set and the entire TCGA dataset. We constructed a nomogram for the prognosis prediction of CRC patients. Differentially infiltrating immune cells were screened by using CIBERSORT. Inmmunophenoscore (IPS) analysis was used to evaluate the response of immunotherapy. The AS events-related splicing factors (SF) were analyzed by Pearson’s correlation. The effects of SF regulating the prognostic AS events in proliferation and migration were validated in Caco2 cells.

Results: A prognostic signature consisting of seven AS events (PDHA1-88633-ES, KIAA1522-1632-AP, TATDN1-85088-ES, PRMT1-51042-ES, VEZT-23786-ES, AIG1-77972-AT, and PHF11-25891-AP) was constructed. Patients in the high-risk score group showed a higher somatic mutation. The genomic instability risk score was an independent variable associated with overall survival (OS), with a hazard ratio of a risk score of 1.537. The area under the curve of receiver operator characteristic curve of the genomic instability risk score in predicting the OS of CRC patients was 0.733. Furthermore, a nomogram was established and could be used clinically to stratify patients to predict prognosis. Patients defined as high-risk by this signature showed a lower proportion of eosinophils than the low-risk group. Patients with low risk were more sensitive to anti-CTLA4 immunotherapy. Additionally, HSPA1A and FAM50B were two SF regulating the OS-related AS. Downregulation of HSPA1A and FAM50B inhibited the proliferation and migration of Caco2 cells.

Conclusion: We constructed an ideal prognostic signature reflecting the genomic instability and OS of CRC patients. HSPA1A and FAM50B were verified as two important SF regulating the OS-related AS.

Crosstalk among m6A RNA methylation, hypoxia and metabolic reprogramming in TME: from immunosuppressive microenvironment to clinical application

The tumor microenvironment (TME), which is regulated by intrinsic oncogenic mechanisms and epigenetic modifications, has become a research hotspot in recent years. Characteristic features of TME include hypoxia, metabolic dysregulation, and immunosuppression. One of the most common RNA modifications, N6-methyladenosine (m⁶A) methylation, is widely involved in the regulation of physiological and pathological processes, including tumor development. Compelling evidence indicates that m⁶A methylation regulates transcription and protein expression through shearing, export, translation, and processing, thereby participating in the dynamic evolution of TME. Specifically, m⁶A methylation-mediated adaptation to hypoxia, metabolic dysregulation, and phenotypic shift of immune cells synergistically promote the formation of an immunosuppressive TME that supports tumor proliferation and metastasis. In this review, we have focused on the involvement of m⁶A methylation in the dynamic evolution of tumor-adaptive TME and described the detailed mechanisms linking m⁶A methylation to change in tumor cell biological functions. In view of the collective data, we advocate treating TME as a complete ecosystem in which components crosstalk with each other to synergistically achieve tumor adaptive changes. Finally, we describe the potential utility of m⁶A methylation-targeted therapies and tumor immunotherapy in clinical applications and the challenges faced, with the aim of advancing m⁶A methylation research.