Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

FOXM1 and Cancer: Faulty Cellular Signaling Derails Homeostasis

Forkhead box transcription factor, FOXM1 is implicated in several cellular processes such as proliferation, cell cycle progression, cell differentiation, DNA damage repair, tissue homeostasis, angiogenesis, apoptosis, and redox signaling. In addition to being a boon for the normal functioning of a cell, FOXM1 turns out to be a bane by manifesting in several disease scenarios including cancer. It has been given an oncogenic status based on several evidences indicating its role in tumor development and progression. FOXM1 is highly expressed in several cancers and has also been implicated in poor prognosis. A comprehensive understanding of various aspects of this molecule has revealed its role in angiogenesis, invasion, migration, self- renewal and drug resistance. In this review, we attempt to understand various mechanisms underlying FOXM1 gene and protein regulation in cancer including the different signaling pathways, post-transcriptional and post-translational modifications. Identifying crucial molecules associated with these processes can aid in the development of potential pharmacological approaches to curb FOXM1 mediated tumorigenesis.

Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques

Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the nutritional status have determined that the adoption of a food pattern-based primarily on a Mediterranean diet (MD) has a preventive role, as well as the ability to mitigate the negative effects of certain pathologies. A group of more than 500 adults aged over 40 years from our cohort in Northwestern Spain was surveyed. Under our experimental design, 10 experiments were run with four different machine-learning algorithms and the predictive factors most relevant to the adherence of a MD were identified. A feature selection approach was explored and under a null hypothesis test, it was concluded that only 16 measures were of relevance, suggesting the strength of this observational study. Our findings indicate that the following factors have the highest predictive value in terms of the degree of adherence to the MD: basal metabolic rate, mini nutritional assessment questionnaire total score, weight, height, bone density, waist-hip ratio, smoking habits, age, EDI-OD, circumference of the arm, activity metabolism, subscapular skinfold, subscapular circumference in cm, circumference of the waist, circumference of the calf and brachial area.

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer

BACKGROUND

Kinesin superfamily (KIFs) has a long-reported significant influence on the initiation, development, and progress of breast cancer. However, the prognostic value of whole family members was poorly done. Our study intends to demonstrate the value of kinesin superfamily members as prognostic biomarkers as well as a therapeutic target of breast cancer.

METHODS

Comprehensive bioinformatics analyses were done using data from TCGA, GEO, METABRIC, and GTEx. LASSO regression was done to select tumor-related members. Nomogram was constructed to predict the overall survival (OS) of breast cancer patients. Expression profiles were testified by quantitative RT-PCR and immunohistochemistry. Transcription factor, GO and KEGG enrichments were done to explore regulatory mechanism and functions.

RESULTS

A total of 20 differentially expressed KIFs were identified between breast cancer and normal tissue with 4 (KIF17, KIF26A, KIF7, KIFC3) downregulated and 16 (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF20B, KIF22, KIF23, KIF24, KIF26B, KIF2C, KIF3B, KIF4A, KIFC1) overexpressed. Among which, 11 overexpressed KIFs (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF23, KIF2C, KIF4A, KIFC1) significantly correlated with worse OS, relapse-free survival (RFS) and distant metastasis-free survival (DMFS) of breast cancer. A 6-KIFs-based risk score (KIF10, KIF15, KIF18A, KIF18B, KIF20A, KIF4A) was generated by LASSO regression with a nomogram validated an accurate predictive efficacy. Both mRNA and protein expression of KIFs are experimentally demonstrated upregulated in breast cancer patients. Msh Homeobox 1 (MSX1) was identified as transcription factors of KIFs in breast cancer. GO and KEGG enrichments revealed functions and pathways affected in breast cancer.

CONCLUSION

Overexpression of tumor-related KIFs correlate with worse outcomes of breast cancer patients and can work as potential prognostic biomarkers.

Upregulation of FOXP4 in breast cancer promotes migration and invasion through facilitating EMT

Background

Family of forkhead box transcription factors has been found to play key roles in multiple types of cancer.

Materials and methods

Our study is to decipher the effects of FOXP4 in human breast cancer (BC). Quantitative real-time polymerase chain reaction and Western blot analyses were performed to determine the mRNA and protein expressions of FOXP4 in BC tissue samples and cell lines. The gain and loss of function assay were used to explore the detailed roles of FOXP4 in breast cell lines, including MDA-MB-231 and MCF-7 cells. Its effect on BC growth, migration, and invasion were evaluated by colony formation assay, CCK-8 assay, wound-healing assay, and transwell invasion assay, respectively.

Results

Our findings revealed that FOXP4 promotes cell proliferation, migration, as well as invasion of BC cells. Furthermore, FOXP4 also facilitates epithelial-mesenchymal transition. ChIP, qChIP assay, and dual luciferase reporter assay were used to examine whether Snail is a downstream target of FOXP4. Moreover, overexpression of Snail could partially rescue the effects of FOXP4 inhibition on cancer cell migration and invasion.

Conclusion

Our findings revealed that FOXP4 is a critical regulator in BC.

Menopausal Status and Outcomes of BRCA Mutation Carriers with Breast Cancer

Outcomes based on menopausal status of breast cancer (BC) patients who are BRCA mutations carriers (BRCAm) are not well known. A prospective database identified 88 BRCAm with BC from 2005 to 2015. Of the 88 patients, 68 (77.3%) women were premenopausal (Pre-M) and 20 (22.7%) were postmenopausal (Post-M). In the Pre-M group, 52.9 per cent of patients had triple-negative (TN) BC, whereas in the Post-M group, there were more estrogen receptor +(65%; P = 0.129) and less TN (25%; P = 0.041) tumors. Median tumor size was significantly larger in the Pre-M group compared with the Post-M group ( P <0.001). Pre-M women were more likely to present with stage III cancers (14.7% vs 0%, respectively, P = 0.082). Ten-year overall survival was 87.9 per cent in the Pre-M group and 93.8 per cent in the Post-M group ( P = 0.44), and 25.3 per cent of Pre-M women had recurrences compared with 11.5 per cent of Post-M women ( P = 0.24). Premenopausal BRCAm with BC are more likely to have TN, higher stage disease, and twice the number of recurrences at 10 years than Post-M BRCAm. Our study is the first to show worse BC outcomes for Pre-M BRCAm compared with Post-M BRCAm women.

Effects of RSF-1 on proliferation and apoptosis of breast cancer cells

Effect of interference with chromatin remodeling and spacing factor-1 (RSF-1) on proliferation and apoptosis of breast cancer cells was investigated. MCF-7 and SKBR-3 cells were cultured in vitro and were divided into 3 groups: control group, negative siRNA control group (NC) and RSF-1 siRNA group. Western blot analysis was used to detect the expression of RSF protein after interference. Cell Counting Kit-8 (CCK-8) method was used to detect the effect of RSF-1 siRNA on cell proliferation. Plate cloning assay was used to detect the effect of RSF-1 siRNA on cell clone formation ability. Annexin V/PI double staining method was used to detect the effect of RSF-1 siRNA on cell apoptosis. Effect of RSF-1 siRNA on nuclear factor-κB (NF-κB) and its downstream signaling pathway were detected by western blot analysis. Western blot analysis showed that RSF-1 siRNA significantly downregulated the expression of RSF-1 protein in MCF-7 and SKBR-3 cells at 72 h after transfection (P<0.01). Cell proliferation assay showed that RSF-1 siRNA significantly reduced the proliferation ability and clone formation ability of MCF-7 and SKBR-3 cells compared with the control group (P<0.01). Annexin V/PI double staining assay results showed that compared with the control group, RSF-1 siRNA significantly increased the apoptosis rate of MCF-7 and SKBR-3 cells (P<0.01). Helenalin and Rsf-1 siRNA significantly reduced the expression levels of p-p65, Bcl-2, and XIAP proteins (P<0.01). Interfering with the expression of RSF-1, gene can effectively inhibit the proliferation of MCF-7 and SKBR-3 cells and promote their apoptosis. RSF-1 can be used as a potential new therapeutic target for the treatment of breast cancer.

Integrated genomics and functional validation identifies malignant cell specific dependencies in triple negative breast cancer

Triple negative breast cancers (TNBCs) lack recurrent targetable driver mutations but demonstrate frequent copy number aberrations (CNAs). Here, we describe an integrative genomic and RNAi-based approach that identifies and validates gene addictions in TNBCs. CNAs and gene expression alterations are integrated and genes scored for pre-specified target features revealing 130 candidate genes. We test functional dependence on each of these genes using RNAi in breast cancer and non-malignant cells, validating malignant cell selective dependence upon 37 of 130 genes. Further analysis reveals a cluster of 13 TNBC addiction genes frequently co-upregulated that includes genes regulating cell cycle checkpoints, DNA damage response, and malignant cell selective mitotic genes. We validate the mechanism of addiction to a potential drug target: the mitotic kinesin family member C1 (KIFC1/HSET), essential for successful bipolar division of centrosome-amplified malignant cells and develop a potential selection biomarker to identify patients with tumors exhibiting centrosome amplification.

Personalized Cancer Care: Risk Prediction, Early Diagnosis, Progression, and Therapy

At the annual prestigious International Symposium of the Fritz-Bender Foundation, Munich, 18-20 May, 2016, researchers, clinicians, and students discussed the state of the art and future perspectives of genomic medicine in cancer. Genomic medicine (also known as precision medicine/oncology) should help clinicians to provide a more precise diagnosis and therapy in oncology for individual patients. The meeting focused on next-generation sequencing methods, analytical computational analysis of big data, and data mining on the way to translational and evidence-based medicine. The meeting covered the social and ethical impact of genomic medicine as well as news and views on antibody targeting of intracellular proteins, on the architecture of intracellular proteins and their impact on carcinogenesis, and on the adaptation of tumor therapy in due consideration of tumor evolution. Subheadings like "Genetic Profiling of Patients and Risk Prediction," "Molecular Profiling of Tumors and Metastases," "Tumor-Host Microenvironment Interaction and Metabolism," and "Targeted Therapy" were subsumed under the main heading of "Personalized Cancer Care."