Analysis of the ATR-Chk1 and ATM-Chk2 pathways in male breast cancer revealed the prognostic significance of ATR expression

Enhancing radiotherapy techniques for Triple-Negative breast cancer treatment

Breast cancer is the most prevalent cancer among women worldwide, with various subtypes that require distinct treatment approaches. Among these, Triple-Negative Breast Bancer (TNBC) is recognized as the most aggressive form, often associated with poor prognosis due to its lack of targeted therapeutic options. This review specifically focuses on Radiotherapy (RT) as a treatment modality for TNBC, evaluating recent advancements and ongoing challenges, particularly the issue of radioresistance. RT remains an essential part in the management of breast cancer, including TNBC. Over the years, multiple improvements have been made to enhance RT effectiveness and minimize resistance. The introduction of advanced techniques such as Stereotactic Body Radiation Therapy (SBRT) and Stereotactic Radiosurgery (SRS) has significantly improved precision and reduced toxicity. More recently, proton radiation therapy, a novel RT modality, has been introduced, offering enhanced dose distribution and reducing damage to surrounding healthy tissues. Despite these technological advancements, a subset of TNBC patients continues to exhibit resistance to RT, leading to recurrence and poor treatment outcomes. To overcome radioresistance, there is an increasing interest in combining RT with targeted therapeutic agents that sensitize cancer cells to radiation. Radiosensitizing drugs have been explored to enhance the efficacy of RT by making cancer cells more susceptible to radiation-induced damage. Potential candidates include DNA damage repair inhibitors, immune checkpoint inhibitors, and small-molecule targeted therapies that interfere with key survival pathways in TNBC cells. In conclusion, while RT remains a crucial modality for TNBC treatment, radioresistance remains a significant challenge. Future research should focus on optimizing RT techniques while integrating radiosensitizing agents to improve treatment efficacy. By combining RT with targeted drug therapy, a more effective and personalized treatment approach can be developed, ultimately improving patient outcomes and reducing recurrence rates in TNBC.

Signaling pathway dysregulation in breast cancer

This article provides a comprehensive analysis of the signaling pathways implicated in breast cancer (BC), the most prevalent malignancy among women and a leading cause of cancer-related mortality globally. Special emphasis is placed on the structural dynamics of protein complexes that are integral to the regulation of these signaling cascades. Dysregulation of cellular signaling is a fundamental aspect of BC pathophysiology, with both upstream and downstream signaling cascade activation contributing to cellular process aberrations that not only drive tumor growth, but also contribute to resistance against current treatments. The review explores alterations within these pathways across different BC subtypes and highlights potential therapeutic strategies targeting these pathways. Additionally, the influence of specific mutations on therapeutic decision-making is examined, underscoring their relevance to particular BC subtypes. The article also discusses both approved therapeutic modalities and ongoing clinical trials targeting disrupted signaling pathways. However, further investigation is necessary to fully elucidate the underlying mechanisms and optimize personalized treatment approaches.

Genome sequencing enhances the diagnostic yield and expands the genetic landscape of male breast cancer

Purpose

To understand the broader genetic landscape of male breast cancer (MBC), focusing on the utility of genome sequencing (GS) beyond BRCA1/2 (HGNC: 1100, 1101) variants.

Methods

Twenty-four patients with MBC underwent a multistep genetic analysis. Initial screening targeted BRCA1/2 variants followed by GS to identify pathogenic/likely pathogenic germline variants through a 3-tiered classification. Polygenic risk score analysis was further incorporated using a model for female breast cancer with 2666 noncancer controls. Exome sequencing was used to transition from germline to somatic investigations, assessing second-hit variant and mutational signatures.

Results

The GS analysis unveiled previously unrecognized pathogenic/likely pathogenic germline variants in BARD1, ATR, BRIP1, and CHEK2 (HGNC: 952, 882, 20473, 16627) among 21 BRCA1/2-negative patients with MBC, elevating the diagnostic yield from 12.5% to 33.0% in all MBC. Elevated average polygenic risk score was noted compared with controls, with a significant correlation to early-onset MBC when combined with high-penetrance germline pathogenic variants (P = 1.10 × 10-4). Exome sequencing analysis further identified significant somatic oncogenic drivers and revealed a dominant mutational signature SBS3 across BRCA1/2-negative samples, reinforcing the contribution of omologous recombination deficiency underlying the MBC development.

Conclusion

Our findings extended the MBC genetic spectrum beyond BRCA1/2 and highlighted the intricate interplay of monogenic and polygenic predispositions, presenting a comprehensive MBC genomic profile.

DNA Damage Response in Early Breast Cancer: A Phase III Cohort in the Phobos Study

We assessed the impact of DNA damage response and repair (DDR) biomarker expressions in 222 node-positive early breast cancer (BC) patients from a previous Phase III GOIM 9902 trial of adjuvant taxanes. At a median follow-up of 64 months, the original study showed no disease-free survival (DFS) or overall survival (OS) differences with the addition of docetaxel (D) to epirubicine-cyclophosphamide (EC). Immunohistochemistry was employed to assess the expression of DDR phosphoproteins (pATM, pATR, pCHK1, γH2AX, pRPA32, and pWEE1) in tumor tissue, and their association with clinical outcomes was evaluated through the Cox elastic net model. Over an extended follow-up of 234 months, we confirmed no significant differences in DFS or OS between patients treated with EC and those receiving D → EC. A DDR risk score, inversely driven by ATM and ATR expression, emerged as an independent prognostic factor for both DFS (HR = 0.41, p < 0.0001) and OS (HR = 0.61, p = 0.046). Further validation in a public adjuvant BC cohort was possible only for ATM, confirming its protective role. Overall, our findings confirm the potential role of the DDR pathway in BC prognostication and in shaping treatment strategies advocating for an integrated approach, combining molecular markers with clinical-pathological factors.

Outcome-guided Bayesian clustering for disease subtype discovery using high-dimensional transcriptomic data

Due to the tremendous heterogeneity of disease manifestations, many complex diseases that were once thought to be single diseases are now considered to have disease subtypes. Disease subtyping analysis, that is the identification of subgroups of patients with similar characteristics, is the first step to accomplish precision medicine. With the advancement of high-throughput technologies, omics data offers unprecedented opportunity to reveal disease subtypes. As a result, unsupervised clustering analysis has been widely used for this purpose. Though promising, the subtypes obtained from traditional quantitative approaches may not always be clinically meaningful (i.e. correlate with clinical outcomes). On the other hand, the collection of rich clinical data in modern epidemiology studies has the great potential to facilitate the disease subtyping process via omics data and to discovery clinically meaningful disease subtypes. Thus, we developed an outcome-guided Bayesian clustering (GuidedBayesianClustering) method to fully integrate the clinical data and the high-dimensional omics data. A Gaussian mixed model framework was applied to perform sample clustering; a spike-and-slab prior was utilized to perform gene selection; a mixture model prior was employed to incorporate the guidance from a clinical outcome variable; and a decision framework was adopted to infer the false discovery rate of the selected genes. We deployed conjugate priors to facilitate efficient Gibbs sampling. Our proposed full Bayesian method is capable of simultaneously (i) obtaining sample clustering (disease subtype discovery); (ii) performing feature selection (select genes related to the disease subtype); and (iii) utilizing clinical outcome variable to guide the disease subtype discovery. The superior performance of the GuidedBayesianClustering was demonstrated through simulations and applications of breast cancer expression data and Alzheimer's disease. An R package has been made publicly available on GitHub to improve the applicability of our method.

Extensive review on breast cancer its etiology, progression, prognostic markers, and treatment

As the most frequent and vulnerable malignancy among women, breast cancer universally manifests a formidable healthcare challenge. From a biological and molecular perspective, it is a heterogenous disease and is stratified based on the etiological factors driving breast carcinogenesis. Notably, genetic predispositions and epigenetic impacts often constitute the heterogeneity of this disease. Typically, breast cancer is classified intrinsically into histological subtypes in clinical landscapes. These stratifications empower physicians to tailor precise treatments among the spectrum of breast cancer therapeutics. In this pursuit, numerous prognostic algorithms are extensively characterized, drastically changing how breast cancer is portrayed. Therefore, it is a basic requisite to comprehend the multidisciplinary rationales of breast cancer to assist the evolution of novel therapeutic strategies. This review aims at highlighting the molecular and genetic grounds of cancer additionally with therapeutic and phytotherapeutic context. Substantially, it also renders researchers with an insight into the breast cancer cell lines as a model paradigm for breast cancer research interventions.

ATR inhibition sensitizes liposarcoma to doxorubicin by increasing DNA damage

Liposarcomas account for approximately 20% of all adult sarcomas and have limited therapeutic options outside of surgery. Inhibition of ataxia-telangiectasia and Rad3 related protein kinase (ATR) has emerged as a promising chemotherapeutic strategy in various cancers. However, its activation, expression, and function in liposarcoma remain unkown. In this study, we investigated the expression, function, and potential of ATR as a therapeutic target in liposarcoma. Activation and expression of ATR in liposarcoma was analyzed by immunohistochemistry, which was further explored for correlation with patient clinical characteristics. ATR-specific siRNA and the ATR inhibitor VE-822 were applied to determine the effect of ATR inhibition on liposarcoma cell proliferation and anti-apoptotic activity. Migration activity and clonogenicity were examined using wound healing and clonogenic assays. ATR (p-ATR) was overexpressed in 88.1% of the liposarcoma specimens and correlated with shorter overall survival in patients. Knockdown of ATR via specific siRNA or inhibition with VE-822 suppressed liposarcoma cell growth, proliferation, migration, colony-forming ability, and spheroid growth. Importantly, ATR inhibition significantly and synergistically enhanced liposarcoma cell line chemosensitivity to doxorubicin. Our findings support ATR as critical to liposarcoma proliferation and doxorubicin resistance. Therefore, the addition of ATR inhibition to a standard doxorubicin regimen is a potential treatment strategy for liposarcoma.

The seminal plasma proteins Peptidyl arginine deaminase 2, rRNA adenine N (6)-methyltransferase and KIAA0825 are linked to better motility post thaw in stallions

Seminal plasma plays an important role in sperm physiology. Seminal plasma proteins vehiculated in microvesicles, carry RNAs and proteins with a potential role in early embryo development. Additionally, proteins present in seminal plasma participate in redox regulation and energy metabolism. In view of these facts, we hypothesized that differences in protein composition of the seminal plasma among stallions may help to explain differences in freeze-ability seen among them. Three independent ejaculates from 10 different stallions of varying breeds were frozen using standard protocols in our laboratory. Aliquots of the ejaculate were separated and stored at -80 °C until further proteomic analysis. Semen analysis was performed using computer assisted sperm analysis and flow cytometry. Significant differences in proteome composition of seminal plasma were observed in the group of stallions showing better motility post thaw. 3116 proteins were identified, and of these, 34 were differentially expressed in stallions with better motility post thaw, 4 of them were also differentially expressed in stallions with different percentages of linearly motile sperm post thaw and 1 protein, Midasin, was expressed in stallions showing high circular velocity post thaw. Seminal plasma proteins may play a major role in sperm functionality; being vehiculated through extracellular vesicles and participating in sperm physiology. Bioinformatic analysis identifies discriminant proteins able to predict the outcome of cryopreservation, identifying potential new biomarkers to assess ejaculate quality.

Identifying Breast Cancer-Related Genes Based on a Novel Computational Framework Involving KEGG Pathways and PPI Network Modularity

Complex diseases, such as breast cancer, are often caused by mutations of multiple functional genes. Identifying disease-related genes is a critical and challenging task for unveiling the biological mechanisms behind these diseases. In this study, we develop a novel computational framework to analyze the network properties of the known breast cancer–associated genes, based on which we develop a random-walk-with-restart (RCRWR) algorithm to predict novel disease genes. Specifically, we first curated a set of breast cancer–associated genes from the Genome-Wide Association Studies catalog and Online Mendelian Inheritance in Man database and then studied the distribution of these genes on an integrated protein–protein interaction (PPI) network. We found that the breast cancer–associated genes are significantly closer to each other than random, which confirms the modularity property of disease genes in a PPI network as revealed by previous studies. We then retrieved PPI subnetworks spanning top breast cancer–associated KEGG pathways and found that the distribution of these genes on the subnetworks are non-random, suggesting that these KEGG pathways are activated non-uniformly. Taking advantage of the non-random distribution of breast cancer–associated genes, we developed an improved RCRWR algorithm to predict novel cancer genes, which integrates network reconstruction based on local random walk dynamics and subnetworks spanning KEGG pathways. Compared with the disease gene prediction without using the information from the KEGG pathways, this method has a better prediction performance on inferring breast cancer–associated genes, and the top predicted genes are better enriched on known breast cancer–associated gene ontologies. Finally, we performed a literature search on top predicted novel genes and found that most of them are supported by at least wet-lab experiments on cell lines. In summary, we propose a robust computational framework to prioritize novel breast cancer–associated genes, which could be used for further in vitro and in vivo experimental validation.

Vasculogenic Mimicry Formation Predicts Tumor Progression in Oligodendroglioma

Vasculogenic mimicry (VM) has been identified as an important vasculogenic mechanism in malignant tumors, but little is known about its clinical meanings and mechanisms in oligodendroglioma. In this study, VM-positive cases were detected in 28 (20.6%) out of 136 oligodendroglioma samples, significantly associated with higher WHO grade, lower Karnofsky performance status (KPS) scores, and recurrent tumor (p < 0.001, p = 0.040, and p = 0.020 respectively). Patients with VM-positive oligodendroglioma had a shorter progress-free survival (PFS) compared with those with VM-negative tumor (p < 0.001), whereas no significant difference was detected in overall survival (OS) between these patients. High levels of phosphorylate serine/threonine kinases Ataxia-telangiectasia mutated (pATM) and phosphorylate Ataxia-telangiectasia and Rad3-Related (pATR) were detected in 31 (22.8%) and 34 (25.0%), respectively out of 136 oligodendroglioma samples. Higher expressions of pATM and pATR were both associated with a shorter PFS (p < 0.001 and p < 0.001). VM-positive oligodendroglioma specimens tended to exhibit higher pATM and pATR staining than VM-negative specimens (r_s = 0.435, p < 0.001 and r_s = 0.317, p < 0.001). Besides, Hypoxia-inducible factor-1α (HIF1α) expression was detected in 14(10.3%) samples, correlated with higher WHO grade and non-frontal lobe (p = 0.010 and p = 0.029). However, no obvious connection was detected between HIF1α expression and VM formation (p = 0.537). Finally, either univariate or multivariate analysis suggested that VM was an independent unfavorable predictor for oligodendroglioma patients (p < 0.001, HR = 7.928, 95%CI: 3.382-18.584, and p = 0.007, HR = 4.534, 95%CI: 1.504-13.675, respectively). VM is a potential prognosticator for tumor progression in oligodendroglioma patients. Phosphorylation of ATM and ATR linked to treatment-resistance may be associated with VM formation. The role of VM in tumor progression and the implication of pATM/pATR in VM formation may provide potential therapeutic targets for oligodendroglioma treatment.

Identifying Breast Cancer-Related Genes Based on a Novel Computational Framework Involving KEGG Pathways and PPI Network Modularity

Complex diseases, such as breast cancer, are often caused by mutations of multiple functional genes. Identifying disease-related genes is a critical and challenging task for unveiling the biological mechanisms behind these diseases. In this study, we develop a novel computational framework to analyze the network properties of the known breast cancer-associated genes, based on which we develop a random-walk-with-restart (RCRWR) algorithm to predict novel disease genes. Specifically, we first curated a set of breast cancer-associated genes from the Genome-Wide Association Studies catalog and Online Mendelian Inheritance in Man database and then studied the distribution of these genes on an integrated protein-protein interaction (PPI) network. We found that the breast cancer-associated genes are significantly closer to each other than random, which confirms the modularity property of disease genes in a PPI network as revealed by previous studies. We then retrieved PPI subnetworks spanning top breast cancer-associated KEGG pathways and found that the distribution of these genes on the subnetworks are non-random, suggesting that these KEGG pathways are activated non-uniformly. Taking advantage of the non-random distribution of breast cancer-associated genes, we developed an improved RCRWR algorithm to predict novel cancer genes, which integrates network reconstruction based on local random walk dynamics and subnetworks spanning KEGG pathways. Compared with the disease gene prediction without using the information from the KEGG pathways, this method has a better prediction performance on inferring breast cancer-associated genes, and the top predicted genes are better enriched on known breast cancer-associated gene ontologies. Finally, we performed a literature search on top predicted novel genes and found that most of them are supported by at least wet-lab experiments on cell lines. In summary, we propose a robust computational framework to prioritize novel breast cancer-associated genes, which could be used for further in vitro and in vivo experimental validation.

DNA Repair Pathways in Cancer Therapy and Resistance

DNA repair pathways are triggered to maintain genetic stability and integrity when mammalian cells are exposed to endogenous or exogenous DNA-damaging agents. The deregulation of DNA repair pathways is associated with the initiation and progression of cancer. As the primary anti-cancer therapies, ionizing radiation and chemotherapeutic agents induce cell death by directly or indirectly causing DNA damage, dysregulation of the DNA damage response may contribute to hypersensitivity or resistance of cancer cells to genotoxic agents and targeting DNA repair pathway can increase the tumor sensitivity to cancer therapies. Therefore, targeting DNA repair pathways may be a potential therapeutic approach for cancer treatment. A better understanding of the biology and the regulatory mechanisms of DNA repair pathways has the potential to facilitate the development of inhibitors of nuclear and mitochondria DNA repair pathways for enhancing anticancer effect of DNA damage-based therapy.

Multi-omics reveals the anticancer mechanism of asparagus saponin-asparanin A on endometrial cancer Ishikawa cells

Multi-omics reveals that AA not only induced apoptosis, but also triggered autophagy in Ishikawa cells through ER stress and DNA damage-related pathways.

ATR and p-ATR are emerging prognostic biomarkers and DNA damage response targets in ovarian cancer

Background:

Although ataxia-telangiectasia and Rad3 related (ATR) has an established role in the DNA damage response of various cancers, its clinical and prognostic significance in ovarian cancer remains largely unknown. The aims of this study were to assess the expression, function, and clinical prognostic relationship of ATR and phospho-ATR ser428 (p-ATR) in ovarian cancer.

Methods:

We confirmed ATR and p-ATR expression by immunohistochemistry (IHC) in a unique ovarian cancer tissue microarray constructed of paired primary, recurrent, and metastatic tumor tissues from 26 individual patients. ATR-specific small interfering RNA (siRNA) and ATR inhibitor VE-822 were applied to determine the effects of ATR inhibition on ovarian cancer cell proliferation, apoptosis, and DNA damage. ATR expression and the associated proteins of the ATR/Chk1 pathway in ovarian cancer cell lines were evaluated by Western blotting. The clonogenicity was also examined using clonogenic assays. A three dimensional (3D) cell culture model was performed to mimic the in vivo ovarian cancer environment to further validate the effects of ATR inhibition on ovarian cancer cells.

Results:

We show recurrent ovarian cancer tissues express higher levels of ATR and p-ATR than their patient-matched primary tumor counterparts. Additionally, higher expression of p-ATR correlates with decreased survival in ovarian cancer patients. Treatment of ovarian cancer cells with ATR specific siRNA or ATR inhibitor VE-822 led to significant apoptosis and inhibition of cellular proliferation, with reduced phosphorylation of Chk1 (p-Chk1), Cdc25c (p-Cdc25c), Cdc2 (p-Cdc2), and increased expression of cleaved PARP and γH2AX. Inhibition of ATR also suppressed clonogenicity and spheroid growth of ovarian cancer cells.

Conclusion:

Our results support the ATR and p-ATR pathway as a prognostic biomarker, and targeting the ATR machinery is an emerging therapeutic approach in the treatment of ovarian cancer.

The role of CDC25C in cell cycle regulation and clinical cancer therapy: a systematic review

One of the most prominent features of tumor cells is uncontrolled cell proliferation caused by an abnormal cell cycle, and the abnormal expression of cell cycle-related proteins gives tumor cells their invasive, metastatic, drug-resistance, and anti-apoptotic abilities. Recently, an increasing number of cell cycle-associated proteins have become the candidate biomarkers for early diagnosis of malignant tumors and potential targets for cancer therapies. As an important cell cycle regulatory protein, Cell Division Cycle 25C (CDC25C) participates in regulating G2/M progression and in mediating DNA damage repair. CDC25C is a cyclin of the specific phosphatase family that activates the cyclin B1/CDK1 complex in cells for entering mitosis and regulates G2/M progression and plays an important role in checkpoint protein regulation in case of DNA damage, which can ensure accurate DNA information transmission to the daughter cells. The regulation of CDC25C in the cell cycle is affected by multiple signaling pathways, such as cyclin B1/CDK1, PLK1/Aurora A, ATR/CHK1, ATM/CHK2, CHK2/ERK, Wee1/Myt1, p53/Pin1, and ASK1/JNK-/38. Recently, it has evident that changes in the expression of CDC25C are closely related to tumorigenesis and tumor development and can be used as a potential target for cancer treatment. This review summarizes the role of CDC25C phosphatase in regulating cell cycle. Based on the role of CDC25 family proteins in the development of tumors, it will become a hot target for a new generation of cancer treatments.

Prognostic relevance of DNA damage and repair biomarkers in elderly patients with hormone-receptor-positive breast cancer treated with neoadjuvant hormone therapy: evidence from the real-world setting

Background:

The logic behind the outcome of endocrine therapy in breast cancer has long remained poorly understood. The prognostic role of DNA damage and repair biomarkers (DDR) was explored in postmenopausal, hormone-receptor-positive breast cancer patients treated with neoadjuvant hormone therapy (NAHT).

Methods:

Data on 55 patients were included. The phosphorylated ataxia-teleangectasia and Rad3-related protein (pATR), phosphorylated ataxia-telangiectasia mutated (ATM) kinase, and phosphorylated H2A Histone Family Member X (γ-H2AX) were evaluated by immunohistochemistry in paired tissues collected at baseline and following NAHT. Biomarkers were considered both singularly and within signatures. Ki-67 percentage change was the primary biomarker endpoint. Classical endpoints were also considered.

Results:

The most favorable Ki-67 outcome was associated with the γ-H2AX/pATM signature (p = 0.011). In models of Ki-67 reduction, ‘luminal B’ subtype, higher grade of anaplasia, and the γ-H2AX/pATM signature tested as significant (p < 0.05 for all). Results were confirmed in multivariate analysis. No association was observed with pathologic response. An increase of ∆γ-H2AX in paired breast tissues was associated with longer event-free survival (p = 0.027) and overall survival (p = 0.042). In Cox models, both survival outcomes were solely affected by grade of anaplasia, with less favorable prognosis in the highest grades (p < 0.05 for both).

Conclusions:

We report novel evidence of the prognostic role of DDR biomarkers on important patient outcomes in postmenopausal hormone-receptor-positive breast cancer patients treated with NAHT. If confirmed in future and adequately sized trials, our results may help inform therapeutic decisions and clarify underlying biological mechanisms.

Alkylating histone deacetylase inhibitors may have therapeutic value in experimental myeloperoxidase-ANCA vasculitis

Current therapies for treating antineutrophil cytoplasm autoantibody (ANCA)-associated vasculitis include cyclophosphamide and corticosteroids. Unfortunately, these agents are associated with severe adverse effects, despite inducing remission in most patients. Histone deacetylase inhibitors are effective in rodent models of inflammation and act synergistically with many pharmacological agents, including alkylating agents like cyclophosphamide. EDO-S101 is an alkylating fusion histone deacetylase inhibitor molecule combining the DNA alkylating effect of Bendamustine with a pan-histone deacetylase inhibitor, Vorinostat. Here we studied the effects of EDO-S101 in two established rodent models of ANCA-associated vasculitis: a passive mouse model of anti-myeloperoxidase IgG-induced glomerulonephritis and an active rat model of myeloperoxidase-ANCA microscopic polyangiitis. Although pretreatment with EDO-S101 reduced circulating leukocytes, it did not prevent the development of passive IgG-induced glomerulonephritis in mice. On the other hand, treatment in rats significantly reduced glomerulonephritis and lung hemorrhage. EDO-S101 also significantly depleted rat B and T cells, and induced DNA damage and apoptosis in proliferating human B cells, suggesting a selective effect on the adaptive immune response. Thus, EDO-S101 may have a role in treatment of ANCA-associated vasculitis, operating primarily through its effects on the adaptive immune response to the autoantigen myeloperoxidase.

The relationship of CDK18 expression in breast cancer to clinicopathological parameters and therapeutic response

Background

Cyclin-Dependent Kinases (CDKs) are established anti-cancer drug targets and a new generation of CDK inhibitors are providing clinical benefits to a sub-set of breast cancer patients. We have recently shown that human CDK18 promotes efficient cellular responses to replication stress. In the current study, we have investigated the clinicopathological and functional significance of CDK18 expression levels in breast cancers.

Results

High CDK18 protein expression was associated with a triple negative and basal-like phenotype (p = 0.021 and 0.027 respectively) as well as improved patient survival, which was particularly significant in ER negative breast cancers (n = 594, Log Rank 6.724, p = 0.01) and those treated with chemotherapy (n = 270, Log Rank 4.575, p = 0.03). In agreement with these clinical findings, breast cancer cells genetically manipulated using a dCRISPR approach to express high levels of endogenous CDK18 exhibited an increased sensitivity to replication stress-inducing chemotherapeutic agents, as a consequence to defective replication stress signalling at the molecular level.

Conclusions

These data reveal that CDK18 protein levels may predict breast cancer disease progression and response to chemotherapy, and provide further rationale for potential targeting of CDK18 as part of novel anti-cancer strategies for human cancers.

Materials and Methods

CDK18 protein expression was evaluated in 1650 breast cancers and correlated to clinicopathological parameters and survival outcomes. Similar analyses were carried out for genetic and transcriptomic changes in CDK18 within several publically available breast cancer cohorts. Additionally, we used a deactivated CRISPR/Cas9 approach (dCRISPR) to elucidate the molecular consequences of heightened endogenous CDK18 expression within breast cancer cells.

A New Way to Treat Brain Tumors: Targeting Proteins Coded by Microcephaly Genes?: Brain tumors and microcephaly arise from opposing derangements regulating progenitor growth. Drivers of microcephaly could be attractive brain tumor targets

New targets for brain tumor therapies may be identified by mutations that cause hereditary microcephaly. Brain growth depends on the repeated proliferation of stem and progenitor cells. Microcephaly syndromes result from mutations that specifically impair the ability of brain progenitor or stem cells to proliferate, by inducing either premature differentiation or apoptosis. Brain tumors that derive from brain progenitor or stem cells may share many of the specific requirements of their cells of origin. These tumors may therefore be susceptible to disruptions of the protein products of genes that are mutated in microcephaly. The potential for the products of microcephaly genes to be therapeutic targets in brain tumors are highlighted hereby reviewing research on EG5, KIF14, ASPM, CDK6, and ATR. Treatments that disrupt these proteins may open new avenues for brain tumor therapy that have increased efficacy and decreased toxicity.