BCAR4 Expression as a Predictive Biomarker for Endocrine Therapy Resistance in Breast Cancer.

BACKGROUND: Breast cancer, particularly the estrogen receptor positive (ER+) subtype, remains a leading cause of cancer-related death among women. Endocrine therapy is the most effective treatment for ER+ breast cancer; however, the development of resistance presents a significant challenge. This study explored the role of the breast cancer antiestrogen resistance 4 (BCAR4) gene as a potential driver of resistance and a pivotal biomarker in breast cancer. PATIENTS AND METHODS: The researchers undertook a comprehensive analysis of 1743 patients spanning 6 independent cohorts. They examined the association of BCAR4 expression with patient outcomes across all breast cancer types and the PAM50 molecular subtypes. The relationship between elevated BCAR4 expression and resistance to endocrine therapy including AIs, the prevailing standard-of-care for endocrine therapy, was also investigated. RESULTS: This meta-analysis corroborated the link between BCAR4 expression and adverse outcomes as well as resistance to endocrine therapy in breast cancer. Notably, BCAR4 expression is clinically significant in luminal A and B subtypes. Additionally, an association between BCAR4 expression and resistance to AI treatment was discerned. CONCLUSION: This study expands on previous findings by demonstrating that BCAR4 expression is associated with resistance to newer therapies. The identification of patients with intrinsic resistance to hormone therapy is crucial to avoid ineffective treatment strategies. These findings contribute to our understanding of endocrine therapy resistance in breast cancer and could potentially guide the development of more effective treatment strategies.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in AR -altered lethal prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor (AR)-targeted agents is often lethal. Unfortunately, biomarkers for this deadly disease remain under investigation, and underpinning mechanisms are ill-understood. Here, we applied deep sequencing to ∼100 mCRPC patients prior to the initiation of first-line AR-targeted therapy, which detected AR /enhancer alterations in over a third of patients, which correlated with lethality. To delve into the mechanism underlying why these patients with cell-free AR /enhancer alterations developed more lethal prostate cancer, we next performed genome-wide cell-free DNA epigenomics. Strikingly, we found that binding sites for transcription factors associated with developmental stemness were nucleosomally more accessible. These results were corroborated using cell-free DNA methylation data, as well as tumor RNA sequencing from a held-out cohort of mCRPC patients. Thus, we validated the importance of AR /enhancer alterations as a prognostic biomarker in lethal mCRPC, and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness.

INTEGRATE-Circ and INTEGRATE-Vis: unbiased detection and visualization of fusion-derived circular RNA.

MOTIVATION: Backsplicing of RNA results in circularized rather than linear transcripts, known as circular RNA (circRNA). A recently discovered and poorly understood subset of circRNAs that are composed of multiple genes, termed fusion-derived circular RNAs (fcircRNAs), represent a class of potential biomarkers shown to have oncogenic potential. Detection of fcircRNAs eludes existing analytical tools, making it difficult to more comprehensively assess their prevalence and function. Improved detection methods may lead to additional biological and clinical insights related to fcircRNAs. RESULTS: We developed the first unbiased tool for detecting fcircRNAs (INTEGRATE-Circ) and visualizing fcircRNAs (INTEGRATE-Vis) from RNA-Seq data. We found that INTEGRATE-Circ was more sensitive, precise and accurate than other tools based on our analysis of simulated RNA-Seq data and our tool was able to outperform other tools in an analysis of public lymphoblast cell line data. Finally, we were able to validate in vitro three novel fcircRNAs detected by INTEGRATE-Circ in a well-characterized breast cancer cell line. AVAILABILITY AND IMPLEMENTATION: Open source code for INTEGRATE-Circ and INTEGRATE-Vis is available at https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC and https://www.github.com/ChrisMaherLab/INTEGRATE-Vis.

PACT: a pipeline for analysis of circulating tumor DNA.

MOTIVATION: Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small-scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants. RESULTS: We developed a unified pipeline for the analysis of ctDNA [Pipeline for the Analysis of ctDNA (PACT)] that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments. AVAILABILITY AND IMPLEMENTATION: PACT is freely available at https://github.com/ChrisMaherLab/PACT.

Characterization of cell-type specific circular RNAs associated with colorectal cancer metastasis.

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and a leading cause of cancer deaths in the United States. More than half of CRC patients develop metastatic disease (mCRC) with an average 5-year survival rate of 13%. Circular RNAs (circRNAs) have recently emerged as important tumorigenesis regulators; however, their role in mCRC progression remains poorly characterized. Further, little is known about their cell-type specificity to elucidate their functions in the tumor microenvironment (TME). To address this, we performed total RNA sequencing (RNA-seq) on 30 matched normal, primary and metastatic samples from 14 mCRC patients. Additionally, five CRC cell lines were sequenced to construct a circRNA catalog in CRC. We detected 47 869 circRNAs, with 51% previously unannotated in CRC and 14% novel candidates when compared to existing circRNA databases. We identified 362 circRNAs differentially expressed in primary and/or metastatic tissues, termed circular RNAs associated with metastasis (CRAMS). We performed cell-type deconvolution using published single-cell RNA-seq datasets and applied a non-negative least squares statistical model to estimate cell-type specific circRNA expression. This predicted 667 circRNAs as exclusively expressed in a single cell type. Collectively, this serves as a valuable resource, TMECircDB (accessible at https://www.maherlab.com/tmecircdb-overview), for functional characterization of circRNAs in mCRC, specifically in the TME.

Pan-Cancer Analysis Reveals Recurrent BCAR4 Gene Fusions across Solid Tumors.

Chromosomal rearrangements often result in active regulatory regions juxtaposed upstream of an oncogene to generate an expressed gene fusion. Repeated activation of a common downstream partner-with differing upstream regions across a patient cohort-suggests a conserved oncogenic role. Analysis of 9,638 patients across 32 solid tumor types revealed an annotated long noncoding RNA (lncRNA), Breast Cancer Anti-Estrogen Resistance 4 (BCAR4), was the most prevalent, uncharacterized, downstream gene fusion partner occurring in 11 cancers. Its oncogenic role was confirmed using multiple cell lines with endogenous BCAR4 gene fusions. Furthermore, overexpressing clinically prevalent BCAR4 gene fusions in untransformed cell lines was sufficient to induce an oncogenic phenotype. We show that the minimum common region to all gene fusions harbors an open reading frame that is necessary to drive proliferation. IMPLICATIONS: BCAR4 gene fusions represent an underappreciated class of gene fusions that may have biological and clinical implications across solid tumors.

Phase 1 study combining alisertib with nab-paclitaxel in patients with advanced solid malignancies.

AIM: Aurora kinase A (AURKA) is a pleiotropic serine/threonine kinase that orchestrates mitotic progression. Paclitaxel stabilises microtubules and disrupts mitotic spindle assembly. The combination of AURKA inhibitor (alisertib) plus paclitaxel may be synergistic in rapidly proliferative cancers. We evaluated the safety and maximum tolerated dose (MTD) of alisertib in combination with nab-paclitaxel and its preliminary efficacy in patients with refractory high-grade neuroendocrine tumours (NETs). METHOD: This is a two-part, Phase 1 study. In Part A (dose escalation), a standard 3 + 3 design was used to determine MTD. In Part B (dose expansion), patients with predominantly refractory high-grade NETs were enrolled. RESULTS: In total, 31 patients were enrolled and treated (16 in Part A and 15 in Part B). The MTD of alisertib was 40 mg BID on D1-3 per week and nab-paclitaxel 100mg/m2 weekly: 3 weeks, 1 week off. Dose-limiting toxicity was neutropenia, and other common side-effects included fatigue, mucositis, and diarrhoea. In Part A, a patient with small-cell lung cancer with partial response (PR) was treated for more than 2 years, whereas four other patients with pancreatic ductal adenocarcinoma (one patient), small cell lung cancer (SCLC) (two patients), or high-grade NET (one patient) achieved stable disease (SD). In Part B, 13 of 15 enrolled patients had high-grade NETs. Of these, one had PR, and four had SD for more than 10 months. CONCLUSIONS: The combination of alisertib and nab-paclitaxel has manageable side-effect profile and showed promising preliminary efficacy in high-grade NETs, warranting further testing. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01677559.

A natural product biflavonoid scaffold with anti-tryptase activity.

Tryptase is a serine protease that is released from mast cells during allergic responses. Tryptase inhibitors are being explored as treatments for allergic inflammation in the skin and respiratory system, most notably asthma. Here we report direct tryptase inhibition by natural product compounds. Candidate inhibitors were identified by computational screening of a large (98,000 compounds) virtual library of natural product compounds for tryptase enzymatic site binding. Biochemical assays were used to validate the predicted anti-tryptase activity in vitro, revealing a high (four out of six) success rate for predicting binding using the computational docking model. We further assess tryptase inhibition by a biflavonoid scaffold, whose structure-activity relationship is partially defined by assessing the potency of structurally similar analogs.

Resistance mechanisms and cross-resistance for a pyridine-pyrimidine amide inhibitor of microtubule polymerization.

Despite their clinical importance, drug resistance remains problematic for microtubule targeting drugs. D4-9-31, a novel microtubule destabilizing agent, has pharmacology that suggests it can overcome common resistance mechanisms and has been shown to remain efficacious in cell and animal models with acquired taxane resistance. To better understand resistance mechanisms and the breadth of cross-resistance with D4-9-31, this study examines the A2780 ovarian cancer cell line as it develops acquired resistance with continuous exposure to D4-9-31. Analyzing cellular responses to D4-9-31 reveals that D4-9-31 resistance is associated with increased mitochondrial respiration, but no cross-resistance to other microtubule targeting agents is observed. Sequencing of transcripts of parental cells and resistant counterparts reveals mutations and altered expression of microtubule-associated genes, but not in genes commonly associated with resistance to microtubule targeting drugs. Additionally, our findings suggest distinct mechanisms drive short- and long-term drug resistance.