Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Complexities of pharmacogenomic interactions in cancer

Genetic and genomic alterations drive cancer development. However, they may also constitute vulnerabilities, including increased drug sensitivity, which could be harnessed for precision medicine purposes. We discuss the highly complex pharmacogenomic interactions that are beginning to be disentangled and hurdles that may need to be overcome before cancer patients could benefit

Mitotic slippage: an old tale with a new twist

Targeting the mitotic machinery using anti-mitotic drugs for elimination of cancer cells is a century-old concept, which continues to be routinely used as a first line of treatment in the clinic. However, patient response remains unpredictable and drug resistance limits effectiveness of these drugs. Cancer cells exit from drug-induced mitotic arrest (mitotic slippage) to avoid subsequent cell death which is thought to be a major mechanism contributing to this resistance. The tumor cells that acquire resistance to anti-mitotic drugs have chromosomal instability (CIN) and are often aneuploid. In this review, we outline the key mechanisms involved in dictating the cell fate during perturbed mitosis and how these processes impede the efficacy of anti-mitotic therapies. Further, we emphasize the recent work from our laboratory, which highlights the functional role of CEP55 in protecting aneuploid cells from death. We also discuss the rationale of targeting CEP55 in vivo, which could prove to be a novel and effective therapeutic strategy for sensitizing cells to microtubule inhibitors and might offer significantly improved patient outcome. Abbreviations: APC/C: Anaphase-Promoting Complex/Cyclosome; BAD: BCL2‐Associated agonist of cell Death; BAK1: BCL2 Antagonist Kinase1; BAX: BCL2‐Associated X; BCL2: B-cell Chronic Lymphocytic Leukaemia (CLL)/Lymphoma 2; BH: BCL2 Homology Domain; BID: BH3‐Interacting domain Death agonist; BIM: BCL2‐Interacting Mediator of cell death; BUB: Budding Uninhibited by Benzimidazoles; CDC: Cell Division Cycle; CDH1: Cadherin-1; CDK1: Cyclin-Dependent Kinase 1; CEP55: Centrosomal Protein (55 KDa): CIN: Chromosomal Instability; CTA: Cancer Testis Antigen; EGR1: Early Growth Response protein 1; ERK: Extracellular Signal-Regulated Kinase; ESCRT: Endosomal Sorting Complexes Required for Transport; GIN: Genomic Instability; MAD2: Mitotic Arrest Deficient 2; MCL1: Myeloid Cell Leukemia sequence 1; MPS1: Monopolar Spindle 1 Kinase; MYT1: MYelin Transcription factor 1; PLK1: Polo Like Kinase 1; PUMA: p53-Upregulated Mediator of Apoptosis; SAC: Spindle Assembly Checkpoint; TAA: Tumor-Associated Antigen

Clinical use and mechanisms of resistance for PARP inhibitors in homologous recombination-deficient cancers

Cells are continuously subjected to DNA damaging agents. DNA damages are repaired by one of the many pathways guarding genomic integrity. When one or several DNA damage pathways are rendered inefficient, cells can accumulate mutations, which modify normal cellular pathways, favoring abnormal cell growth. This supports malignant transformation, which can occur when cells acquire resistance to cell cycle checkpoints, apoptosis, or growth inhibition signals. Mutations in genes involved in the repair of DNA double strand breaks (DSBs), such as BRCA1, BRCA2, or PALB2, significantly increase the risk of developing cancer of the breast, ovaries, pancreas, or prostate. Fortunately, the inability of these tumors to repair DNA breaks makes them sensitive to genotoxic chemotherapies, allowing for the development of therapies precisely tailored to individuals’ genetic backgrounds. Unfortunately, as with many anti-cancer agents, drugs used to treat patients carrying a BRCA1 or BRCA2 mutation create a selective pressure, and over time tumors can become drug resistant. Here, we detail the cellular function of tumor suppressors essential in DNA damage repair pathways, present the mechanisms of action of inhibitors used to create synthetic lethality in BRCA carriers, and review the major molecular sources of drug resistance. Finally, we present examples of the many strategies being developed to circumvent drug resistance.</p

Mechanisms of genomic instability in breast cancer

Breast cancer is the most common cancer among women globally. Genomic instability (GI) refers to the increased tendency to accrue genomic alterations. It drives heterogeneity and is a hallmark of cancer. Genomic integrity is closely guarded by several mechanisms, including DNA damage checkpoints, the DNA repair machinery, and the mitotic checkpoint. Alterations in these surveillance mechanisms cause GI. In breast cancer, several pathways maintaining genomic integrity are distinctly altered, including some that have been successfully exploited for therapeutic targeting. In this review, we comprehensively discuss the recent advances on the mechanisms of GI in breast cancer, highlighting DNA repair defects and chromosome segregation errors during mitosis. We further review the clinical implications and therapeutic potential of targeting GI in the era of precision medicine

MicroRNAs in cancer cell death pathways: apoptosis and necroptosis

To protect tissues and the organism from disease, potentially harmful cells are removed through programmed cell death processes, including apoptosis and necroptosis. These types of cell death are critically controlled by microRNAs (miRNAs). MiRNAs are short RNA molecules that target and inhibit expression of many cellular regulators, including those controlling programmed cell death via the intrinsic (Bcl-2 and Mcl-1), extrinsic (TRAIL and Fas), p53-and endoplasmic reticulum (ER) stress-induced apoptotic pathways, as well as the necroptosis cell death pathway. In this review, we discuss the current knowledge of apoptosis and necroptosis pathways and how these are impaired in cancer cells. We focus on how miRNAs disrupt apoptosis and necroptosis, thereby critically contributing to malignancy. Understanding which and how miRNAs and their targets affect cell death pathways could open up novel therapeutic opportunities for cancer patients. Indeed, restoration of pro-apoptotic tumor suppressor miRNAs (apoptomiRs) or inhibition of oncogenic miRNAs (oncomiRs) represent strategies that are currently being trialed or are already applied as miRNA-based cancer therapies. Therefore, better understanding the cancer type-specific expression of apoptomiRs and oncomiRs and their underlying mechanisms in cell death pathways will not only advance our knowledge, but also continue to provide new opportunities to treat cancer

Multi-omics characterization of the spontaneous mesenchymal–epithelial transition in the PMC42 breast cancer cell lines

Epithelial-mesenchymal plasticity (EMP), encompassing epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET), are considered critical events for cancer metastasis. We investigated chromosomal heterogeneity and chromosomal instability (CIN) profiles of two sister PMC42 breast cancer (BC) cell lines to assess the relationship between their karyotypes and EMP phenotypic plasticity. Karyotyping by GTG banding and exome sequencing were aligned with SWATH quantitative proteomics and existing RNA-sequencing data from the two PMC42 cell lines; the mesenchymal, parental PMC42-ET cell line and the spontaneously epithelially shifted PMC42-LA daughter cell line. These morphologically distinct PMC42 cell lines were also compared with five other BC cell lines (MDA-MB-231, SUM-159, T47D, MCF-7 and MDA-MB-468) for their expression of EMP and cell surface markers, and stemness and metabolic profiles. The findings suggest that the epithelially shifted cell line has a significantly altered ploidy of chromosomes 3 and 13, which is reflected in their transcriptomic and proteomic expression profiles. Loss of the TGFβR2 gene from chromosome 3 in the epithelial daughter cell line inhibits its EMT induction by TGF-β stimulus. Thus, integrative 'omics' characterization established that the PMC42 system is a relevant MET model and provides insights into the regulation of phenotypic plasticity in breast cancer

Interactions between cancer stem cells, immune system and some environmental components: Friends or foes

Cancer stem cells (CSCs) are a subgroup of tumor cells that are characterized by their tumor initiating capacity,low proliferation rate, self-renewal capacity, pluripotency and chemoresistance. The immune system, includinginnate and adaptive immune cells, plays pro-tumorigenic and anti-tumorigenic roles in cancer biology.Immunosurveillance often initially successfully eradicates tumor cells. However, following a phenomenon re-ferred to as immunoediting, cancer cells may ultimately evade immune destruction, thus enabling tumor pro-gression. Here, we review how CSCs both escape immune destruction and foster establishment of an im-munosuppressive tumor microenvironment through intricate interactions with and recruitment of a broad rangeof immune cells, including natural killer (NK) cells, myeloid-derived suppressor cells (MDSCs), regulatory T cells(Tregs), tumor-associated macrophages (TAMs), cytotoxic T-lymphocytes (CTLs) and T helper (Th) cells. Furtherelucidation of CSC-immune cell interactions and the underlying signaling mechanisms will open up novel op-portunities to improve cancer immunotherap

The SWI/SNF subunit SMARCD3 regulates cell cycle progression and predicts survival outcome in ER+ breast cancer

Purpose: Chromatin remodeling plays an essential role in regulating transcriptional networks and timing of gene expression. Chromatin remodelers such as SWItch/Sucrose Non-Fermentable (SWI/SNF) harbor many protein components, with the catalytic subunit providing ATPase activity to displace histones along or from the DNA molecules, and associated subunits ensuring tissue specificity and transcriptional or co-transcriptional activities. Mutations in several of the SWI/SNF subunits have been linked to cancer. Here, we investigate between SMARCD3/Baf60c expression and hormone-positive (ER+) breast cancer. Methods: The level of SMARCD3 was detected by immunohistochemistry in breast cancer patient samples, and expression levels of SMARCD1, SMARCD2, and SMARCD3 were investigated using publicly available datasets from large cohorts of breast cancer patients. Using molecular biology and microscopy, we interrogated the cellular consequences of lower SMARCD3 expression. Results: Lower proliferation rates were observed in SMARCD3-depleted cells, which reflects a failure of the cell cycle progression and an increase in endoreplication. In the absence of SMARCD3, p21 accumulates in cells, but does not halt the cell cycle, and DNA damage accumulates and remains unrepaired. Conclusion: Taken together, our data begin to explain why ER+ breast cancer patients with low-SMARCD3 expressing tumors exhibit reduced survival rates compared to patients expressing normal or higher levels of SMARCD3. SMARCD3 might act as a tumor suppressor through regulation of cell cycle checkpoints and could be a reliable and specific breast cancer prognostic biomarker.</p

Translocation breakpoints preferentially occur in euchromatin and acrocentric chromosomes

Chromosomal translocations drive the development of many hematological and some solid cancers. Several factors have been identified to explain the non-random occurrence of translocation breakpoints in the genome. These include chromatin density, gene density and CCCTC-binding factor (CTCF)/cohesin binding site density. However, such factors are at least partially interdependent. Using 13,844 and 1563 karyotypes from human blood and solid cancers, respectively, our multiple regression analysis only identified chromatin density as the primary statistically significant predictor. Specifically, translocation breakpoints preferentially occur in open chromatin. Also, blood and solid tumors show markedly distinct translocation signatures. Strikingly, translocation breakpoints occur significantly more frequently in acrocentric chromosomes than in non-acrocentric chromosomes. Thus, translocations are probably often generated around nucleoli in the inner nucleoplasm, away from the nuclear envelope. Importantly, our findings remain true both in multivariate analyses and after removal of highly recurrent translocations. Finally, we applied pairwise probabilistic co-occurrence modeling. In addition to well-known highly prevalent translocations, such as those resulting in BCR-ABL1 (BCR-ABL) and RUNX1-RUNX1T1 (AML1-ETO) fusion genes, we identified significantly underrepresented translocations with putative fusion genes, which are probably subject to strong negative selection during tumor evolution. Taken together, our findings provide novel insights into the generation and selection of translocations during cancer development