Characterization of potential driver mutations involved in human breast cancer by computational approaches

Exploring the prognostic significance of arm-level copy number alterations in triple-negative breast cancer

Somatic copy number alterations (SCNAs) are prevalent in cancer and play a significant role in both tumorigenesis and therapeutic resistance. While focal SCNAs have been extensively studied, the impact of larger arm-level SCNAs remains poorly understood. Here, we investigated the association between arm-level SCNAs and overall survival in triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer lacking targeted therapies. We identified frequent arm-level SCNAs, including 21q gain and 7p gain, which correlated with poor overall survival in TNBC patients. Further, we identified the expression of specific genes within these SCNAs associated with survival. Notably, we found that the expression of RIPK4, a gene located on 21q, exhibited a strong correlation with poor overall survival. In functional assays, we demonstrated that targeting Ripk4 in a murine lung metastatic TNBC model significantly reduced tumor burden, improved survival, and increased CD4+ and CD8+ T cell infiltration. RIPK4 enhanced the survival of triple-negative breast cancer cells at secondary sites, thereby facilitating the formation of metastatic lesions. Our findings highlight the significance of arm-level SCNAs in breast cancer progression and identify RIPK4 as a putative driver of TNBC metastasis and immunosuppression.

A latent variable model for evaluating mutual exclusivity and co-occurrence between driver mutations in cancer

A key challenge in cancer genomics is understanding the functional relationships and dependencies between combinations of somatic mutations that drive cancer development. Such driver mutations frequently exhibit patterns of mutual exclusivity or co-occurrence across tumors, and many methods have been developed to identify such dependency patterns from bulk DNA sequencing data of a cohort of patients. However, while mutual exclusivity and co-occurrence are described as properties of driver mutations, existing methods do not explicitly disentangle functional, driver mutations from neutral, passenger mutations. In particular, nearly all existing methods evaluate mutual exclusivity or co-occurrence at the gene level, marking a gene as mutated if any mutation - driver or passenger - is present. Since some genes have a large number of passenger mutations, existing methods either restrict their analyses to a small subset of suspected driver genes - limiting their ability to identify novel dependencies - or make spurious inferences of mutual exclusivity and co-occurrence involving genes with many passenger mutations. We introduce DIALECT, an algorithm to identify dependencies between pairs of driver mutations from somatic mutation counts. We derive a latent variable mixture model for drivers and passengers that combines existing probabilistic models of passenger mutation rates with a latent variable describing the unknown status of a mutation as a driver or passenger. We use an expectation maximization (EM) algorithm to estimate the parameters of our model, including the rates of mutually exclusivity and co-occurrence between drivers. We demonstrate that DIALECT more accurately infers mutual exclusivity and co-occurrence between driver mutations compared to existing methods on both simulated mutation data and somatic mutation data from 5 cancer types in The Cancer Genome Atlas (TCGA).

Whole-Genome Sequencing Analysis of Male Breast Cancer Unveils Novel Structural Events and Potential Therapeutic Targets

The molecular characterization of male breast cancer (MaBC) has received limited attention in research, mostly because of its low incidence rate, accounting for only 0.5% to 1% of all reported cases of breast cancer each year. Managing MaBC presents significant challenges, with most treatment protocols being adapted from those developed for female breast cancer. Utilizing whole-genome sequencing (WGS) and state-of-the-art analyses, the genomic features of 10 MaBC cases (n = 10) were delineated and correlated with clinical and histopathologic characteristics. Using fluorescence in situ hybridization, an additional cohort of 18 patients was interrogated to supplement WGS findings. The genomic landscape of MaBC uncovered significant genetic alterations that could influence diagnosis and treatment. We found common somatic mutations in key driver genes, such as FAT1, GATA3, SMARCA4, and ARID2. Our study also mapped out structural variants that impact cancer-associated genes, such as ARID1A, ESR1, GATA3, NTRK1, and NF1. Using a WGS-based classifier, homologous recombination deficiency (HRD) was identified in 2 cases, both presenting with deleterious variants in BRCA2. Noteworthy was the observation of FGFR1 amplification in 21% of cases. Altogether, we identified at least 1 potential therapeutic target in 8 of the 10 cases, including high tumor mutational burden, FGFR1 amplification, and HRD. Our study is the first WGS characterization of MaBC, which uncovered potentially relevant variants, including structural events in cancer genes, HRD signatures, and germline pathogenic mutations. Our results demonstrate unique genetic markers and potential treatment targets in MaBC, thereby underlining the necessity of tailoring treatment strategies for this understudied patient population. These WGS-based findings add to the growing knowledge of MaBC genomics and highlight the need to expand research on this type of cancer.

Comprehensive somatic mutational analysis in glioblastoma: Implications for precision medicine approaches

Glioblastoma multiforme (GBM), a malignant neoplasm originating from glial cells, remains challenging to treat despite the current standard treatment approach that involves maximal safe surgical resection, radiotherapy, and adjuvant temozolomide chemotherapy. This underscores the critical need to identify new molecular targets for improved therapeutic interventions. The current study aimed to explore the somatic mutations and potential therapeutic targets in GBM using somatic mutational information from four distinct GBM datasets including CGGA, TCGA, CPTAC and MAYO-PDX. The analysis included the evaluation of whole exome sequencing (WES) of GBM datasets, tumor mutation burden assessment, survival analysis, drug sensitivity prediction, and examination of domain-specific amino acid changes. The results identified the top ten commonly altered genes in the aforementioned GBM datasets and patients with mutations in OBSCN and AHNAK2 alone or in combination had a more favorable overall survival (OS). Also, the study identified potential drug sensitivity patterns in GBM patients with mutations in OBSCN and AHNAK2, and evaluated the impact of amino acid changes in specific protein domains on the survival of GBM patients. These findings provide important insights into the genetic alterations and somatic interactions in GBM, which could have implications for the development of new therapeutic strategies for this aggressive malignancy.

p120 RasGAP and ZO-2 are essential for Hippo signaling and tumor-suppressor function mediated by p190A RhoGAP

ARHGAP35, which encodes p190A RhoGAP (p190A), is a major cancer gene. p190A is a tumor suppressor that activates the Hippo pathway. p190A was originally cloned via direct binding to p120 RasGAP (RasGAP). Here, we determine that interaction of p190A with the tight-junction-associated protein ZO-2 is dependent on RasGAP. We establish that both RasGAP and ZO-2 are necessary for p190A to activate large tumor-suppressor (LATS) kinases, elicit mesenchymal-to-epithelial transition, promote contact inhibition of cell proliferation, and suppress tumorigenesis. Moreover, RasGAP and ZO-2 are required for transcriptional modulation by p190A. Finally, we demonstrate that low ARHGAP35 expression is associated with shorter survival in patients with high, but not low, transcript levels of TJP2 encoding ZO-2. Hence, we define a tumor-suppressor interactome of p190A that includes ZO-2, an established constituent of the Hippo pathway, and RasGAP, which, despite strong association with Ras signaling, is essential for p190A to activate LATS kinases.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Cancer-keeper genes as therapeutic targets

Finding cancer-driver genes has been a central theme of cancer research. We took a different perspective; instead of considering normal cells, we focused on cancerous cells and genes that maintained abnormal cell growth, which we named cancer-keeper genes (CKGs). Intervening CKGs may rectify aberrant cell growth, making them potential cancer therapeutic targets. We introduced control-hub genes and developed an efficient algorithm by extending network controllability theory. Control hub are essential for maintaining cancerous states and thus can be taken as CKGs. We applied our CKG-based approach to bladder cancer (BLCA). All genes on the cell-cycle and p53 pathways in BLCA were identified as CKGs, showing their importance in cancer. We discovered that sensitive CKGs - genes easily altered by structural perturbation - were particularly suitable therapeutic targets. Experiments on cell lines and a mouse model confirmed that six sensitive CKGs effectively suppressed cancer cell growth, demonstrating the immense therapeutic potential of CKGs.

Mutation-derived, genomic instability-associated lncRNAs are prognostic markers in gliomas

Background

Gliomas are the most commonly-detected malignant tumors of the brain. They contain abundant long non-coding RNAs (lncRNAs), which are valuable cancer biomarkers. LncRNAs may be involved in genomic instability; however, their specific role and mechanism in gliomas remains unclear. LncRNAs that are related to genomic instability have not been reported in gliomas.

Methods

The transcriptome data from The Cancer Genome Atlas (TCGA) database were analyzed. The co-expression network of genomic instability-related lncRNAs and mRNA was established, and the model of genomic instability-related lncRNA was identified by univariate Cox regression and LASSO analyses. Based on the median risk score obtained in the training set, we divided the samples into high-risk and low-risk groups and proved the survival prediction ability of genomic instability-related lncRNA signatures. The results were verified in the external data set. Finally, a real-time quantitative polymerase chain reaction assay was performed to validate the signature.

Results

The signatures of 17 lncRNAs (LINC01579, AL022344.1, AC025171.5, LINC01116, MIR155HG, AC131097.3, LINC00906, CYTOR, AC015540.1, SLC25A21.AS1, H19, AL133415.1, SNHG18, FOXD3.AS1, LINC02593, AL354919.2 and CRNDE) related to genomic instability were identified. In the internal data set and Gene Expression Omnibus (GEO) external data set, the low-risk group showed better survival than the high-risk group (P < 0.001). In addition, this feature was identified as an independent risk factor, showing its independent prognostic value with different clinical stratifications. The majority of patients in the low-risk group had isocitrate dehydrogenase 1 (IDH1) mutations. The expression levels of these lncRNAs were significantly higher in glioblastoma cell lines than in normal cells.

Conclusions

Our study shows that the signature of 17 lncRNAs related to genomic instability has prognostic value for gliomas and could provide a potential therapeutic method for glioblastoma.

Eribulin inhibits growth of cutaneous squamous cell carcinoma cell lines and a novel patient-derived xenograft

Advanced cutaneous squamous cell carcinoma (cSCC) is treated with chemotherapy and/or radiotherapy, but these typically fail to achieve satisfactory clinical outcomes. There have been no preclinical studies to evaluate the effectiveness of eribulin against cSCC. Here, we examine the effects of eribulin using cSCC cell lines and a novel cSCC patient-derived xenograft (PDX) model. In the cSCC cell lines (A431 and DJM-1 cells), eribulin was found to inhibit tumor cell proliferation in vitro as assessed by cell ATP levels. DNA content analysis by fluorescence-activated cell sorting (FACS) showed that eribulin induced G2/M cell cycle arrest and apoptosis. In xenograft models of cSCC cell lines, the administration of eribulin suppressed tumor growth in vivo. We also developed a cSCC patient-derived xenograft (PDX) which reproduces the histological and genetic characteristics of a primary tumor. Pathogenic mutations in TP53 and ARID2 were detected in the patient's metastatic tumor and in the PDX tumor. The cSCC-PDX responded well to the administration of eribulin and cisplatin. In conclusion, the present study shows the promising antineoplastic effects of eribulin in cSCC. Also, we established a novel cSCC-PDX model that preserves the patient's tumor. This PDX could assist researchers who are exploring innovative therapies for cSCC.

p120 RasGAP and ZO-2 are essential for Hippo signaling and tumor suppressor function mediated by p190A RhoGAP

ARHGAP35 , which encodes p190A RhoGAP (p190A), is a major cancer gene. p190A is a tumor suppressor that activates the Hippo pathway. p190A was originally cloned via direct binding to p120 RasGAP (RasGAP). Here, we determine that a novel interaction of p190A with the tight junction-associated protein ZO-2 is dependent on RasGAP. We establish that both RasGAP and ZO-2 are necessary for p190A to activate LATS kinases, elicit mesenchymal-to-epithelial transition, promote contact inhibition of cell proliferation and suppress tumorigenesis. Moreover, RasGAP and ZO-2 are required for transcriptional modulation by p190A. Finally, we demonstrate that low ARHGAP35 expression is associated with shorter survival in patients with high, but not low, transcript levels of TJP2 encoding ZO-2. Hence, we define a tumor suppressor interactome of p190A that includes ZO-2, an established constituent of the Hippo pathway, and RasGAP, which despite strong association with Ras signaling, is essential for p190A to activate LATS kinases.

Harnessing Epigenetics for Breast Cancer Therapy: The Role of DNA Methylation, Histone Modifications, and MicroRNA

Breast cancer exhibits various epigenetic abnormalities that regulate gene expression and contribute to tumor characteristics. Epigenetic alterations play a significant role in cancer development and progression, and epigenetic-targeting drugs such as DNA methyltransferase inhibitors, histone-modifying enzymes, and mRNA regulators (such as miRNA mimics and antagomiRs) can reverse these alterations. Therefore, these epigenetic-targeting drugs are promising candidates for cancer treatment. However, there is currently no effective epi-drug monotherapy for breast cancer. Combining epigenetic drugs with conventional therapies has yielded positive outcomes and may be a promising strategy for breast cancer therapy. DNA methyltransferase inhibitors, such as azacitidine, and histone deacetylase inhibitors, such as vorinostat, have been used in combination with chemotherapy to treat breast cancer. miRNA regulators, such as miRNA mimics and antagomiRs, can alter the expression of specific genes involved in cancer development. miRNA mimics, such as miR-34, have been used to inhibit tumor growth, while antagomiRs, such as anti-miR-10b, have been used to inhibit metastasis. The development of epi-drugs that target specific epigenetic changes may lead to more effective monotherapy options in the future.

The Role of Genetic Mutations in Mitochondrial-Driven Cancer Growth in Selected Tumors: Breast and Gynecological Malignancies

There is an increasing understanding of the molecular and cytogenetic background of various tumors that helps us better conceptualize the pathogenesis of specific diseases. Additionally, in many cases, these molecular and cytogenetic alterations have diagnostic, prognostic, and/or therapeutic applications that are heavily used in clinical practice. Given that there is always room for improvement in cancer treatments and in cancer patient management, it is important to discover new therapeutic targets for affected individuals. In this review, we discuss mitochondrial changes in breast and gynecological (endometrial and ovarian) cancers. In addition, we review how the frequently altered genes in these diseases (BRCA1/2, HER2, PTEN, PIK3CA, CTNNB1, RAS, CTNNB1, FGFR, TP53, ARID1A, and TERT) affect the mitochondria, highlighting the possible associated individual therapeutic targets. With this approach, drugs targeting mitochondrial glucose or fatty acid metabolism, reactive oxygen species production, mitochondrial biogenesis, mtDNA transcription, mitophagy, or cell death pathways could provide further tailored treatment.

OBSCN restoration via OBSCN-AS1 long-noncoding RNA CRISPR-targeting suppresses metastasis in triple-negative breast cancer

Mounting evidence implicates the giant, cytoskeletal protein obscurin (720 to 870 kDa), encoded by the OBSCN gene, in the predisposition and development of breast cancer. Accordingly, prior work has shown that the sole loss of OBSCN from normal breast epithelial cells increases survival and chemoresistance, induces cytoskeletal alterations, enhances cell migration and invasion, and promotes metastasis in the presence of oncogenic KRAS. Consistent with these observations, analysis of Kaplan-Meier Plotter datasets reveals that low OBSCN levels correlate with significantly reduced overall and relapse-free survival in breast cancer patients. Despite the compelling evidence implicating OBSCN loss in breast tumorigenesis and progression, its regulation remains elusive, limiting any efforts to restore its expression, a major challenge given its molecular complexity and gigantic size (~170 kb). Herein, we show that OBSCN-Antisense RNA 1 (OBSCN-AS1), a novel nuclear long-noncoding RNA (lncRNA) gene originating from the minus strand of OBSCN, and OBSCN display positively correlated expression and are downregulated in breast cancer biopsies. OBSCN-AS1 regulates OBSCN expression through chromatin remodeling involving H3 lysine 4 trimethylation enrichment, associated with open chromatin conformation, and RNA polymerase II recruitment. CRISPR-activation of OBSCN-AS1 in triple-negative breast cancer cells effectively and specifically restores OBSCN expression and markedly suppresses cell migration, invasion, and dissemination from three-dimensional spheroids in vitro and metastasis in vivo. Collectively, these results reveal the previously unknown regulation of OBSCN by an antisense lncRNA and the metastasis suppressor function of the OBSCN-AS1/OBSCN gene pair, which may be used as prognostic biomarkers and/or therapeutic targets for metastatic breast cancer.

The RUNX/CBFβ Complex in Breast Cancer: A Conundrum of Context

Dissecting and identifying the major actors and pathways in the genesis, progression and aggressive advancement of breast cancer is challenging, in part because neoplasms arising in this tissue represent distinct diseases and in part because the tumors themselves evolve. This review attempts to illustrate the complexity of this mutational landscape as it pertains to the RUNX genes and their transcription co-factor CBFβ. Large-scale genomic studies that characterize genetic alterations across a disease subtype are a useful starting point and as such have identified recurring alterations in CBFB and in the RUNX genes (particularly RUNX1). Intriguingly, the functional output of these mutations is often context dependent with regards to the estrogen receptor (ER) status of the breast cancer. Therefore, such studies need to be integrated with an in-depth understanding of both the normal and corrupted function in mammary cells to begin to tease out how loss or gain of function can alter the cell phenotype and contribute to disease progression. We review how alterations to RUNX/CBFβ function contextually ascribe to breast cancer subtypes and discuss how the in vitro analyses and mouse model systems have contributed to our current understanding of these proteins in the pathogenesis of this complex set of diseases.

Insights of Endocytosis Signaling in Health and Disease

Endocytosis in mammalian cells is a fundamental cellular machinery that regulates vital physiological processes, such as the absorption of metabolites, release of neurotransmitters, uptake of hormone cellular defense, and delivery of biomolecules across the plasma membrane. A remarkable characteristic of the endocytic machinery is the sequential assembly of the complex proteins at the plasma membrane, followed by internalization and fusion of various biomolecules to different cellular compartments. In all eukaryotic cells, functional characterization of endocytic pathways is based on dynamics of the protein complex and signal transduction modules. To coordinate the assembly and functions of the numerous parts of the endocytic machinery, the endocytic proteins interact significantly within and between the modules. Clathrin-dependent and -independent endocytosis, caveolar pathway, and receptor mediated endocytosis have been attributed to a greater variety of physiological and pathophysiological roles such as, autophagy, metabolism, cell division, apoptosis, cellular defense, and intestinal permeabilization. Notably, any defect or alteration in the endocytic machinery results in the development of pathological consequences associated with human diseases such as cancer, cardiovascular diseases, neurological diseases, and inflammatory diseases. In this review, an in-depth endeavor has been made to illustrate the process of endocytosis, and associated mechanisms describing pathological manifestation associated with dysregulated endocytosis machinery.

mTOR pathway as a potential therapeutic target for cancer stem cells in canine mammary carcinoma

Mammary adenocarcinoma, the most common cancer in female dogs, often exhibits the lymph node and lung metastases and has a higher mortality rate. However, mammary adenocarcinoma has no established treatment, except early surgical excision. Canine mammary carcinoma has many common features with human mammary carcinoma, including clinical characteristics, heterogeneity, and genetic aberrations, making it an excellent spontaneous tumor model for human breast cancer. Diverse cancers comprised heterogeneous cell populations originating from cancer stem cells (CSCs) with self-renewal ability. Therefore, in addition to conventional therapy, therapeutic strategies targeting CSCs are essential for cancer eradication. The present study aimed to extract inhibitors of canine mammary CSCs that suppress their self-renewal ability. Sphere-formation assay, which evaluates self-renewal ability, was performed for the canine mammary cancer cell lines CTBp and CNMp. The spheres formed in this assay were used in inhibitor library screening, which identified various signaling pathways such as proteosome, stress inducer, and mammalian target of rapamycin (mTOR). The present study focused on the mTOR signaling pathway. Western blotting showed higher levels of phosphorylated mTOR in sphere-forming CTBp and CNMp cells than in adherent cells. Drug sensitivity examination using the mTOR inhibitors everolimus and temsirolimus revealed dose-dependent reductions in viability among both sphere-forming cells and adherent cells. Expression of phosphorylated mTOR in adherent and sphere-forming cells decreased by everolimus and temsirolimus treatment. In mice transplanted with CTBp-derived spheres, everolimus treatment significantly decreased tumor volume compared to control. These results reveal that the mTOR signaling pathway may be a potential to be a therapeutic target in both cancer cells and CSCs. Novel therapeutic strategies for canine mammary carcinoma are expected to benefit to human breast carcinoma as well.

One Step Nucleic Acid Amplification (OSNA) Lysate Samples Are Suitable to Establish a Transcriptional Metastatic Signature in Patients with Early Stage Hormone Receptors-Positive Breast Cancer

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7, VTCN1, CD44, GATA3, ALOX15B, RORC, NECTIN2, LRG1, CD276, FOXM1 and IGF1R. Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.

Hormonal Crosstalk Between Thyroid and Breast Cancer

Differentiated thyroid cancer and breast cancer account for a significant portion of endocrine-related malignancies and predominately affect women. As hormonally responsive tissues, the breast and thyroid share endocrine signaling. Breast cells are responsive to thyroid hormone signaling and are affected by altered thyroid hormone levels. Thyroid cells are responsive to sex hormones, particularly estrogen, and undergo protumorigenic processes upon estrogen stimulation. Thyroid and sex hormones also display significant transcriptional crosstalk that influences oncogenesis and treatment sensitivity. Obesity-related adipocyte alterations-adipocyte estrogen production, inflammation, feeding hormone dysregulation, and metabolic syndromes-promote hormonal alterations in breast and thyroid tissues. Environmental toxicants disrupt endocrine systems, including breast and thyroid homeostasis, and influence pathologic processes in both organs through hormone mimetic action. In this brief review, we discuss the hormonal connections between the breast and thyroid and perspectives on hormonal therapies for breast and thyroid cancer. Future research efforts should acknowledge and further explore the hormonal crosstalk of these tissues in an effort to further understand the prevalence of thyroid and breast cancer in women and to identify potential therapeutic options.

Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer

PURPOSE

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects women of African ancestry (WAA) and is often associated with poor survival. Although there is a high prevalence of TNBC across West Africa and in women of the African diaspora, there has been no comprehensive genomics study to investigate the mutational profile of ancestrally related women across the Caribbean and West Africa.

METHODS

This multisite cross-sectional study used 31 formalin-fixed paraffin-embedded (FFPE) samples from Barbadian and Nigerian TNBC participants. High-resolution whole exome sequencing (WES) was performed on the Barbadian and Nigerian TNBC samples to identify their mutational profiles and comparisons were made to African American, European American and Asian American sequencing data obtained from The Cancer Genome Atlas (TCGA). Whole exome sequencing was conducted on tumors with an average of 382 × coverage and 4335 × coverage for pooled germline non-tumor samples.

RESULTS

Variants detected at high frequency in our WAA cohorts were found in the following genes NBPF12, PLIN4, TP53 and BRCA1. In the TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-African American; 67% in TCGA-European American; 63% in TCGA-Asian). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-African American cohort. For copy number variants, high frequency alterations were observed in PIK3CA, TP53, FGFR2 and HIF1AN genes.

CONCLUSION

This study provides novel insights into the underlying genomic alterations in WAA TNBC samples and shines light on the importance of inclusion of under-represented populations in cancer genomics and biomarker studies.

Giant obscurin regulates migration and metastasis via RhoA-dependent cytoskeletal remodeling in pancreatic cancer

Obscurins, encoded by the OBSCN gene, are giant cytoskeletal proteins with structural and regulatory roles. Large scale omics analyses reveal that OBSCN is highly mutated across different types of cancer, exhibiting a 5-8% mutation frequency in pancreatic cancer. Yet, the functional role of OBSCN in pancreatic cancer progression and metastasis has to be delineated. We herein show that giant obscurins are highly expressed in normal pancreatic tissues, but their levels are markedly reduced in pancreatic ductal adenocarcinomas. Silencing of giant obscurins in non-tumorigenic Human Pancreatic Ductal Epithelial (HPDE) cells and obscurin-expressing Panc5.04 pancreatic cancer cells induces an elongated, spindle-like morphology and faster cell migration via cytoskeletal remodeling. Specifically, depletion of giant obscurins downregulates RhoA activity, which in turn results in reduced focal adhesion density, increased microtubule growth rate and faster actin dynamics. Although OBSCN knockdown is not sufficient to induce de novo tumorigenesis, it potentiates tumor growth in a subcutaneous implantation model and exacerbates metastasis in a hemispleen murine model of pancreatic cancer metastasis, thereby shortening survival. Collectively, these findings reveal a critical role of giant obscurins as tumor suppressors in normal pancreatic epithelium whose loss of function induces RhoA-dependent cytoskeletal remodeling, and promotes cell migration, tumor growth and metastasis.

De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens

Current understandings of individual disease etiology and therapeutics are limited despite great need. To fill the gap, we propose a novel computational pipeline that collects potent disease gene cooperative pathways to envision individualized disease etiology and therapies. Our algorithm constructs individualized disease modules de novo, which enables us to elucidate the importance of mutated genes in specific patients and to understand the synthetic penetrance of these genes across patients. We reveal that importance of the notorious cancer drivers TP53 and PIK3CA fluctuate widely across breast cancers and peak in tumors with distinct numbers of mutations and that rarely mutated genes such as XPO1 and PLEKHA1 have high disease module importance in specific individuals. Furthermore, individualized module disruption enables us to devise customized singular and combinatorial target therapies that were highly varied across patients, showing the need for precision therapeutics pipelines. As the first analysis of de novo individualized disease modules, we illustrate the power of individualized disease modules for precision medicine by providing deep novel insights on the activity of diseased genes in individuals.

Epigenetic Reprogramming and Landscape of Transcriptomic Interactions: Impending Therapeutic Interference of Triple-Negative Breast Cancer in Molecular Medicine

The mechanisms governing the development and progression of cancers are believed to be the consequence of hereditary deformities and epigenetic modifications. Accordingly, epigenetics has become an incredible and progressively explored field of research to discover better prevention and therapy for neoplasia, especially triple-negative breast cancer (TNBC). It represents 15-20% of all invasive breast cancers and will, in general, have bellicose histological highlights and poor clinical outcomes. In the early phases of triple-negative breast carcinogenesis, epigenetic deregulation modifies chromatin structure and influences the plasticity of cells. It up-keeps the oncogenic reprogramming of malignant progenitor cells with the acquisition of unrestrained selfrenewal capacities. Genomic impulsiveness in TNBC prompts mutations, copy number variations, as well as genetic rearrangements, while epigenetic remodeling includes an amendment by DNA methylation, histone modification, and noncoding RNAs of gene expression profiles. It is currently evident that epigenetic mechanisms assume a significant part in the pathogenesis, maintenance, and therapeutic resistance of TNBC. Although TNBC is a heterogeneous malaise that is perplexing to describe and treat, the ongoing explosion of genetic and epigenetic research will help to expand these endeavors. Latest developments in transcriptome analysis have reformed our understanding of human diseases, including TNBC at the molecular medicine level. It is appealing to envision transcriptomic biomarkers to comprehend tumor behavior more readily regarding its cellular microenvironment. Understanding these essential biomarkers and molecular changes will propel our capability to treat TNBC adequately. This review will depict the different aspects of epigenetics and the landscape of transcriptomics in triple-negative breast carcinogenesis and their impending application for diagnosis, prognosis, and treatment decision with the view of molecular medicine.

Role of Calcium Homeostasis in Modulating EMT in Cancer

Calcium is essential for cells to perform numerous physiological processes. In cancer, the augmentation of calcium signaling supports the more proliferative and migratory cells, which is a characteristic of the epithelial-to-mesenchymal transition (EMT). By genetically and epigenetically modifying genes, channels, and entire signaling pathways, cancer cells have adapted to survive with an extreme imbalance of calcium that allows them to grow and metastasize in an abnormal manner. This cellular remodeling also allows for the evasion of immune surveillance and the development of drug resistance, which lead to poor prognosis in patients. Understanding the role calcium flux plays in driving the phenotypes associated with invasion, immune suppression, metastasis, and drug resistance remains critical for determining treatments to optimize clinical outcomes and future drug discovery.

Obscurin: A multitasking giant in the fight against cancer

Giant obscurins (720-870 kDa), encoded by OBSCN, were originally discovered in striated muscles as cytoskeletal proteins with scaffolding and regulatory roles. Recently though, they have risen to the spotlight as key players in cancer development and progression. Herein, we provide a timely prudent synopsis of the expanse of OBSCN mutations across 16 cancer types. Given the extensive work on OBSCN's role in breast epithelium, we summarize functional studies implicating obscurins as potent tumor suppressors in breast cancer and delve into an in silico analysis of its mutational profile and epigenetic (de)regulation using different dataset platforms and sophisticated computational tools. Lastly, we formally describe the OBSCN-Antisense-RNA-1 gene, which belongs to the long non-coding RNA family and discuss its potential role in modulating OBSCN expression in breast cancer. Collectively, we highlight the escalating involvement of obscurins in cancer biology and outline novel potential mechanisms of OBSCN (de)regulation that warrant further investigation.

A clinical case of multiple primary cancers in a carrier of rare SDK2 and NOTCH2 gene mutations

Background

Genetic predisposition is one of the risk factors for the development of multiple primary cancers (MPCs), the frequency of which increases and ranges from 2 to 17%. This study describes a combination of rare mutations, rs746551843 in the NOTCH2 gene and rs144933006 in the SDK2 gene, in a woman with breast cancer and leiomyosarcoma without a clearly burdened family history.

Case presentation

A 55-year-old Caucasian woman received complex treatment on the basis of the National Medical Research Centre for Oncology for left breast cancer and leiomyosarcoma of soft tissues of the left thigh. The patient was referred for consultation with a geneticist. Among direct relatives, a maternal aunt with a history of kidney cancer was not a carrier of the studied single nucleotide polymorphisms (SNPs). The healthy son of the patient inherited both mutations.

Conclusion

Thus, perhaps in the described case, there is a synergistic effect of two alleles of moderate and low penetrance, which led to the phenotype of multiple primary cancers.

Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into Genomic Workflows

In cancer research, genomic profiles are often extracted from homogenized macrodissections of tissues, with the histological context lost and a large fraction of material underutilized. Pertinently, the spatial genomic landscape provides critical complementary information in deciphering disease heterogeneity and progression. Microscale sampling methods such as microdissection to obtain such information are often destructive to a sizeable fraction of the biopsy sample, thus showing limited multiplexability and adaptability to different assays. A modular microfluidic technology is here implemented to recover cells at the microscale from tumor tissue sections, with minimal disruption of unsampled areas and tailored to interface with genome profiling workflows, which is directed here toward evaluating intratumoral genomic heterogeneity. The integrated workflow-GeneScape-is used to evaluate heterogeneity in a metastatic mammary carcinoma, showing distinct single nucleotide variants and copy number variations in different tumor tissue regions, suggesting the polyclonal origin of the metastasis as well as development driven by multiple location-specific drivers.

Assessing the readiness of Turkish health information systems for integrating genetic/genomic patient data: System architecture and available terminologies, legislative, and protection of personal data

Advances in genetic/genomic research and translational studies drive the progress on molecular diagnosis, personalised treatment, and monitoring. Healthcare professionals and governments are encouraged to set administrative regulations and implement structured and interoperable representation to utilise the genetic/genomic data, which will support precision medicine approaches through Health Information Systems (HIS). Clear regulations and careful legislation are also crucial for the security and privacy of genetic/genomic test data. In this article, we present a review of the National Health Information System of Turkey (NHIS-T) about interoperable health data representation for genetic tests. We discuss the content of rules and regulations related to genetic/genomic testing and structured data representation in Turkey. A brief comparison of the Turkish "Law on the Protection of Personal Data" (LPPD) in genetic/genomic data privacy with its counterparts is presented. The final discussion about the shortcomings of Turkey is transferable to health information systems worldwide. Constructing a national reference database and IT infrastructure to enable data integration and exchange between genomic data, metadata, and health records will improve genetics studies' utility and outcomes. The critical success factors behind integration are establishing broadly accepted terminologies and government guidance. The governments should set clear a transparent policy defining the legal and ethical framework, workforce training, clinical decision-support tools, public engagement, and education concurrently.

Discovering novel driver mutations from pan-cancer analysis of mutational and gene expression profiles

As the genomic profile across cancers varies from person to person, patient prognosis and treatment may differ based on the mutational signature of each tumour. Thus, it is critical to understand genomic drivers of cancer and identify potential mutational commonalities across tumors originating at diverse anatomical sites. Large-scale cancer genomics initiatives, such as TCGA, ICGC and GENIE have enabled the analysis of thousands of tumour genomes. Our goal was to identify new cancer-causing mutations that may be common across tumour sites using mutational and gene expression profiles. Genomic and transcriptomic data from breast, ovarian, and prostate cancers were aggregated and analysed using differential gene expression methods to identify the effect of specific mutations on the expression of multiple genes. Mutated genes associated with the most differentially expressed genes were considered to be novel candidates for driver mutations, and were validated through literature mining, pathway analysis and clinical data investigation. Our driver selection method successfully identified 116 probable novel cancer-causing genes, with 4 discovered in patients having no alterations in any known driver genes: MXRA5, OBSCN, RYR1, and TG. The candidate genes previously not officially classified as cancer-causing showed enrichment in cancer pathways and in cancer diseases. They also matched expectations pertaining to properties of cancer genes, for instance, showing larger gene and protein lengths, and having mutation patterns suggesting oncogenic or tumor suppressor properties. Our approach allows for the identification of novel putative driver genes that are common across cancer sites using an unbiased approach without any a priori knowledge on pathways or gene interactions and is therefore an agnostic approach to the identification of putative common driver genes acting at multiple cancer sites.

Breast Cancer and Tamoxifen: A Nigerian Perspective to Effective Personalised Therapy

Estrogen-receptor positivity in tumour, often requiring long-term tamoxifen therapy, is thought to characterise between 43% and 65% of breast cancer cases in Nigeria. The patient population is further marked by late-stage diagnosis which significantly heightens the tendency for tumour relapse in the course of tamoxifen therapy. Despite tamoxifen being considered a reliable chemopreventive in high-risk individuals and an effective adjuvant therapy for hormone-sensitive tumours, mortality has remained high among breast cancer patients in the West African region where Nigeria belongs. The Nigerian breast cancer population, like other similar patient-populations in the West African region, provides a mix of intrinsic genome-diversity and perhaps unique tumour biology and evolution. These peculiarities suggest the need for a rational approach to tumour management and a personalised delivery of therapy in Nigeria's dominant estrogen-receptor-positive patient population. Herein, critical indices of tamoxifen-therapy success are discussed in the context of the Nigerian breast cancer population with emphasis on salient aspects of tamoxifen-biotransformation, host- and tumour-genomics, and epigenetics.

Alternative methylation of intron motifs is associated with cancer-related gene expression in both canine mammary tumor and human breast cancer

Background

Canine mammary tumor (CMT) has long been considered as a good animal model for human breast cancer (HBC) due to their pathological and biological similarities. However, only a few aspects of the epigenome have been explored in both HBC and CMT. Moreover, DNA methylation studies have mainly been limited to the promoter regions of genes.

Results

Genome-wide methylation analysis was performed in CMT and adjacent normal tissues and focused on the intron regions as potential targets for epigenetic regulation. As expected, many tumor suppressors and oncogenes were identified. Of note, most cancer-associated biological processes were enriched in differentially methylated genes (DMGs) that included intron DMRs (differentially methylated regions). Interestingly, two PAX motifs, PAX5 (tumor suppressive) and PAX6 (oncogenic), were frequently found in hyper- and hypomethylated intron DMRs, respectively. Hypermethylation at the PAX5 motifs in the intron regions of CDH5 and LRIG1 genes were found to be anti-correlated with gene expression, while CDH2 and ADAM19 genes harboring hypomethylated PAX6 motifs in their intron region were upregulated. These results were validated from the specimens originally MBD-sequenced as well as additional clinical samples. We also comparatively investigated the intron methylation and downstream gene expression of these genes using human breast invasive carcinoma (BRCA) datasets in TCGA (The Cancer Genome Atlas) public database. Regional alteration of methylation was conserved in the corresponding intron regions and, consequently, gene expression was also altered in HBC.

Conclusions

This study provides good evidence for the conservation of epigenetic regulation in CMT and HBC, and suggests that intronic methylation can be an important factor in better understanding gene regulation in both CMT and HBC.

Nik-related kinase is targeted for proteasomal degradation by the chaperone-dependent ubiquitin ligase CHIP

Nik-related kinase (Nrk) is a member of the germinal center kinase IV family and suppresses Akt signaling. In vivo, Nrk prevents placental hyperplasia and breast cancer formation. Here, we show that Nrk is regulated by the chaperone-dependent ubiquitin ligase carboxyl terminus of heat-shock protein (Hsp)70-interacting protein (CHIP). Immunoprecipitation and liquid chromatography-tandem mass spectrometry analysis reveal that Nrk preferentially interacts with CHIP and Hsp70/90 family proteins. Nrk protein levels are decreased by CHIP overexpression and increased by siRNA-mediated CHIP knockdown. Our results indicate that Nrk is ubiquitinated by CHIP in a chaperone-dependent manner, resulting in its proteasomal degradation. CHIP targets a fraction of Nrk molecules that have lost the ability to regulate Akt signaling. We conclude that CHIP plays an important role in regulating Nrk protein levels.

Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data

MOTIVATION

Association studies to discover links between genetic markers and phenotypes are central to bioinformatics. Methods of regularized regression, such as variants of the Lasso, are popular for this task. Despite the good predictive performance of these methods in the average case, they suffer from unstable selections of correlated variables and inconsistent selections of linearly dependent variables. Unfortunately, as we demonstrate empirically, such problematic situations of correlated and linearly dependent variables often exist in genomic datasets and lead to under-performance of classical methods of variable selection.

RESULTS

To address these challenges, we propose the Precision Lasso. Precision Lasso is a Lasso variant that promotes sparse variable selection by regularization governed by the covariance and inverse covariance matrices of explanatory variables. We illustrate its capacity for stable and consistent variable selection in simulated data with highly correlated and linearly dependent variables. We then demonstrate the effectiveness of the Precision Lasso to select meaningful variables from transcriptomic profiles of breast cancer patients. Our results indicate that in settings with correlated and linearly dependent variables, the Precision Lasso outperforms popular methods of variable selection such as the Lasso, the Elastic Net and Minimax Concave Penalty (MCP) regression.

AVAILABILITY AND IMPLEMENTATION

Software is available at https://github.com/HaohanWang/thePrecisionLasso.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ribosome elongating footprints denoised by wavelet transform comprehensively characterize dynamic cellular translation events

Translation is dynamically regulated during cell development and stress response. In order to detect actively translated open reading frames (ORFs) and dynamic cellular translation events, we have developed a computational method, RiboWave, to process ribosome profiling data. RiboWave utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes and precisely locate their footprint denoted as Periodic Footprint P-site (PF P-site). Such high-resolution footprint is found to capture the full track of actively elongating ribosomes, from which translational landscape can be explicitly characterized. We compare RiboWave with several published methods, like RiboTaper, ORFscore and RibORF, and found that RiboWave outperforms them in both accuracy and usage when defining actively translated ORFs. Moreover, we show that PF P-site derived by RiboWave shows superior performance in characterizing the dynamics and complexity of cellular translatome by accurately estimating the abundance of protein levels, assessing differential translation and identifying dynamic translation frameshift.

Patterns of Mutation Enrichment in Metastatic Triple-Negative Breast Cancer

Background:

Triple-negative breast cancer (TNBC) is a heterogeneous disease with aggressive biology and complex tumor evolution. Our purpose was to identify enrichment patterns of genomic alterations in metastatic triple-negative breast cancer (mTNBC).

Methods:

Genomic data were retrieved (mutations and copy number variations) from 550 primary TNBC tumors from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) data sets and 58 mTNBC tumors from “Mutational Profile of Metastatic Breast Cancers” and “The Metastatic Breast Cancer Project.” Statistical analysis of microarray data between primary and metastatic tumors was performed using a chi-square test, and the percentage of mutation enrichment in mTNBC cases was estimated. P-values were adjusted for multiple testing with Benjamini-Hochberg method with a false-discovery rate (FDR) <.05. In addition, we identified dominant hallmarks of cancer in mTNBC.

Results:

Seven genes with mutations were enriched in mTNBC after correcting for multiple testing. These included TTN, HMCN1, RELN, PKHD1L1, DMD, FRAS1, and RYR3. Only RPS6KB2 amplification was statistically significant in mTNBC; on the contrary, deletion of the genes TET1, RHOA, EPHA5, SET, KCNJ5, ABCG4, NKX3-1, SDHB, IGF2, and BRCA1 were the most frequent. The molecular alterations related to the hallmark of “genetic instability and mutation” were predominant in mTNBC. Interestingly, the hallmark of “activating immune destruction” was the least represented in mTNBC.

Conclusion:

Despite the study limitations, we identified recurrent patterns of genomic alterations with potential contribution to tumor evolution. Deletions were the aberrations more commonly found in mTNBC. Several molecular alterations are potentially targetable.

Cellular plasticity and metastasis in breast cancer: a pre- and post-malignant problem

As a field we have made tremendous strides in treating breast cancer, with a decline in the past 30 years of overall breast cancer mortality. However, this progress is met with little affect once the disease spreads beyond the primary site. With a 5-year survival rate of 22%, 10-year of 13%, for those patients with metastatic breast cancer (mBC), our ability to effectively treat wide spread disease is minimal. A major contributing factor to this ineffectiveness is the complex make-up, or heterogeneity, of the primary site. Within a primary tumor, secreted factors, malignant and pre-malignant epithelial cells, immune cells, stromal fibroblasts and many others all reside alongside each other creating a dynamic environment contributing to metastasis. Furthermore, heterogeneity contributes to our lack of understanding regarding the cells' remarkable ability to undergo epithelial/non-cancer stem cell (CSC) to mesenchymal/CSC (E-M/CSC) plasticity. The enhanced invasion & motility, tumor-initiating potential, and acquired therapeutic resistance which accompanies E-M/CSC plasticity implicates a significant role in metastasis. While most work trying to understand E-M/CSC plasticity has been done on malignant cells, recent evidence is emerging concerning the ability for pre-malignant cells to undergo E-M/CSC plasticity and contribute to the metastatic process. Here we will discuss the importance of E-M/CSC plasticity within malignant and pre-malignant populations of the tumor. Moreover, we will discuss how one may potentially target these populations, ultimately disrupting the metastatic cascade and increasing patient survival for those with mBC.

Tumor-associated antigens identified early in mouse mammary tumor development can be effective vaccine targets

Breast cancer vaccines composed of antigens identified by serological analysis of cDNA expression libraries (SEREX) induce antigen specific immune responses in patients but have had disappointing clinical benefits. While many attempts to modify the adjuvants and vaccine method have been tried, one issue not addressed was whether the SEREX tumor-associated antigens identified from late stages of disease were ideal targets. We questioned in the transgenic TgMMTV-neu mouse model whether the antigen repertoire is distinct between early and late stage breast cancer and whether the antigens identified via SEREX from transgenic mice with early or late stage tumors would elicit differential anti-tumor effects to address this question. Three early stage antigens, Pdhx, Stk39, and Otud6B, were identified from a SEREX screen of mice prior to development of palpable lesions. Formulated into a vaccine, each early antigen inhibited tumor growth (p < 0.0001). The antigens identified from mice with late stage tumors (Swap70, Gsn, and Arhgef2) were unable to inhibit tumor growth when used as vaccines (for example Gsn p = 0.26). Each of the three early stage antigens were essential for tumor survival in syngeneic mouse tumor cells and in human breast cancer cell lines across breast cancer subtypes. Silencing protein expression of the early antigens increased apoptosis (p < 0.0001 for all antigens in mouse and p < 0.05 for all antigens in human triple negative breast cancer) and decreased survival (p < 0.0001 for all antigens in mouse and human triple negative and HER2 positive breast cancer). Overexpression of the early stage antigens in women with breast cancer predicted worse prognosis (p = 0.03) while overexpression of late stage antigens did not impact prognosis (p = 0.09). These data suggest that antigens expressed earlier in breast tumor development and functionally relevant to breast tumor growth may be more effective targets for therapeutic breast cancer vaccines than antigens identified in later disease.

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

Use case driven evaluation of open databases for pediatric cancer research

BACKGROUND

A plethora of Web resources are available offering information on clinical, pre-clinical, genomic and theoretical aspects of cancer, including not only the comprehensive cancer projects as ICGC and TCGA, but also less-known and more specialized projects on pediatric diseases such as PCGP. However, in case of data on childhood cancer there is very little information openly available. Several web-based resources and tools offer general biomedical data which are not purpose-built, for neither pediatric nor cancer analysis. Additionally, many Web resources on cancer focus on incidence data and statistical social characteristics as well as self-regulating communities.

METHODS

We summarize those resources which are open and are considered to support scientific fundamental research, while we address our comparison to 11 identified pediatric cancer-specific resources (5 tools, 6 databases). The evaluation consists of 5 use cases on the example of brain tumor research and covers user-defined search scenarios as well as data mining tasks, also examining interactive visual analysis features.

RESULTS

Web resources differ in terms of information quantity and presentation. Pedican lists an abundance of entries with few selection features. PeCan and PedcBioPortal include visual analysis tools while the latter integrates published and new consortia-based data. UCSC Xena Browser offers an in-depth analysis of genomic data. ICGC data portal provides various features for data analysis and an option to submit own data. Its focus lies on adult Pan-Cancer projects. Pediatric Pan-Cancer datasets are being integrated into PeCan and PedcBioPortal. Comparing information on prominent mutations within glioma discloses well-known, unknown, possible, as well as inapplicable biomarkers. This summary further emphasizes the varying data allocation. Tested tools show advantages and disadvantages, depending on the respective use case scenario, providing inhomogeneous data quantity and information specifics.

CONCLUSIONS

Web resources on specific pediatric cancers are less abundant and less-known compared to those offering adult cancer research data. Meanwhile, current efforts of ongoing pediatric data collection and Pan-Cancer projects indicate future opportunities for childhood cancer research, that is greatly needed for both fundamental as well as clinical research.

CRISPR Technology for Breast Cancer: Diagnostics, Modeling, and Therapy

Molecularly, breast cancer represents a highly heterogenous family of neoplastic disorders, with substantial interpatient variations regarding genetic mutations, cell composition, transcriptional profiles, and treatment response. Consequently, there is an increasing demand for alternative diagnostic approaches aimed at the molecular annotation of the disease on a patient-by-patient basis and the design of more personalized treatments. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) technology enables the development of such novel approaches. For instance, in diagnostics, the use of the RNA-specific C2c2 system allows ultrasensitive nucleic acid detection and could be used to characterize the mutational repertoire and transcriptional breast cancer signatures. In disease modeling, CRISPR/Cas9 technology can be applied to selectively engineer oncogenes and tumor-suppressor genes involved in disease pathogenesis. In treatment, CRISPR/Cas9 can be used to develop gene-therapy, while its catalytically-dead variant (dCas9) can be applied to reprogram the epigenetic landscape of malignant cells. As immunotherapy becomes increasingly prominent in cancer treatment, CRISPR/Cas9 can engineer the immune cells to redirect them against cancer cells and potentiate antitumor immune responses. In this review, CRISPR strategies for the advancement of breast cancer diagnostics, modeling, and treatment are highlighted, culminating in a perspective on developing a precision medicine-based approach against breast cancer.

Patterns of copy number alterations in primary breast tumors of South African patients and their impact on functional cellular pathways

Breast cancer is the most common and the leading cause of female mortality among South African (SA) women. Several non‑biological and biological risk factors may be attributed to their observed high mortality rate; however, the molecular profiles associated with their breast tumors are poorly characterized. The present study examined the patterns of genome-wide copy number alterations (CNAs) and their potential impact on functional cellular pathways targeted by cancer driver genes in patients with breast cancer from the Western Cape region of SA. Array-comparative genomic hybridization analysis, performed in 28 cases of invasive breast cancer, revealed a mean number of 8.68±6.18 CNAs per case, affecting primarily the Xp22.3 and 6p21-p25 cytobands (57.14% of the cases), followed by 19p13.3-p13.11 (35.7%), 2p25.3-p24.3, 4p16.3-p15.3, 8q11.1-q24.3 and 16 p13.3-p11.2 (32.14%). Functional enrichment analysis of genes and microRNA targets mapped in these affected cytobands revealed critical cancer-associated pathways, including fatty acid biosynthesis and metabolism, extracellular matrix-receptor interaction, hippo and tumor protein p53 signaling pathways, which are regulated by known cancer genes, including CCND1, CDKN1A, MAPK1, MDM2, TP53 and SMAD2. An inverse correlation was observed among the number of CNAs and tumor size and grade; CNAs on the 4p and 6p cytobands were also inversely correlated with tumor grade. No association was observed in the number of CNAs and/or the affected cytobands and the different ethnic groups of the SA patients, indicating that their tumor genome is affected by CNAs, irrespectively of their genetic descent. Additional genomic tumor profiling in SA and other Sub-Saharan African patients with breast cancer is required to determine the associations of the CNAs observed with prognosis and clinical outcome.

Unraveling obscurins in heart disease

Obscurins, expressed from the single OBSCN gene, are a family of giant, modular, cytoskeletal proteins that play key structural and regulatory roles in striated muscles. They were first implicated in the development of heart disease in 2007 when two missense mutations were found in a patient diagnosed with hypertrophic cardiomyopathy (HCM). Since then, the discovery of over a dozen missense, frameshift, and splicing mutations that are linked to various forms of cardiomyopathy, including HCM, dilated cardiomyopathy (DCM), and left ventricular non-compaction (LVNC), has highlighted OBSCN as a potential disease-causing gene. At this time, the functional consequences of the identified mutations remain largely elusive, and much work has yet to be done to characterize the disease mechanisms of pathological OBSCN variants. Herein, we describe the OBSCN mutations known to date, discuss their potential impact on disease development, and provide future directions in order to better understand the involvement of obscurins in heart disease.

Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications

Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis. We also discuss the challenges that are faced while developing novel in silico approaches in the future. The development of better methods for mutation analysis-related protein PTMs will help to facilitate the development of personalized precision medicine.

Breast cancer vaccination comes to age: impacts of bioinformatics

Introduction: Breast cancer, as one of the major causes of cancer death among women, is the central focus of this study. The recent advances in the development and application of computational tools and bioinformatics in the field of immunotherapy of malignancies such as breast cancer have emerged the new dominion of immunoinformatics, and therefore, next generation of immunomedicines .

Methods: Having reviewed the most recent works on the applications of computational tools, we provide comprehensive insights into the breast cancer incidence and its leading causes as well as immunotherapy approaches and the future trends. Furthermore, we discuss the impacts of bioinformatics on different stages of vaccine design for the breast cancer, which can be used to produce much more efficient vaccines through a rationalized time- and cost-effective in silico approaches prior to conducting costly experiments.

Results: The tools can be significantly used for designing the immune system-modulating drugs and vaccines based on in silico approaches prior to in vitro and in vivo experimental evaluations. Application of immunoinformatics in the cancer immunotherapy has shown its success in the pre-clinical models. This success returns back to the impacts of several powerful computational approaches developed during the last decade.

Conclusion: Despite the invention of a number of vaccines for the cancer immunotherapy, more computational and clinical trials are required to design much more efficient vaccines against various malignancies, including breast cancer.

A comprehensive genomic meta-analysis identifies confirmatory role of OBSCN gene in breast tumorigenesis

The giant multifunctional protein "OBSCURIN" is encoded by OBSCN gene and is mostly expressed in cardiac and other skeletal muscles responsible for myofibrils organization. Loss of OBSCURIN affects the entire downstream pathway proteins vital for various cellular functions including cell integration and cell adhesion. The OBSCN gene mutations are more frequently observed in various muscular diseases, and cancers. Nevertheless, the direct role of OBSCN in tumorigenesis remains elusive. Interestingly, in clinical breast cancer samples a significant number of function changing mutations have been identified in OBSCN gene. In this study, we identified a significant role of OBSCN by conducting an integrative analysis of copy number alterations, functional mutations, gene methylation and expression data from various BRCA cancer projects data available on cBioPortal and TCGA firebrowse portal. Finally, we carried out genetic network analysis, which revealed that OBSCN gene plays a significant role in GPCR, RAS, p75 or Wnt signaling pathways. Similarly, OBSCN gene interacts with many cancer-associated genes involved in breast tumorigenesis. The OBSCN gene probably regulates breast cancer progression and metastasis and the prognostic molecular signatures such as copy number alterations and gene expression of OBSCN may serve as a tool to identify breast tumorigenesis and metastasis.