The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance.

The extracellular signals regulating mammary epithelial cell growth are of relevance to understanding the pathophysiology of mammary epithelia, yet they remain poorly characterized. In this study, we applied an unbiased approach to understanding the functional role of signalling molecules in several models of normal physiological growth and translated these results to the biological understanding of breast cancer subtypes.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.

Mutations in human Atrophin1, a transcriptional corepressor, cause dentatorubral-pallidoluysian atrophy, a neurodegenerative disease. Drosophila Atrophin (Atro) mutants display many phenotypes, including neurodegeneration, segmentation, patterning and planar polarity defects. Despite Atro's critical role in development and disease, relatively little is known about Atro's binding partners and downstream targets. We present the first genomic analysis of Atro using ChIP-seq against endogenous Atro. ChIP-seq identified 1300 potential direct targets of Atro including engrailed, and components of the Dpp and Notch signaling pathways. We show that Atro regulates Dpp and Notch signaling in larval imaginal discs, at least partially via regulation of thickveins and fringe. In addition, bioinformatics analyses, sequential ChIP and coimmunoprecipitation experiments reveal that Atro interacts with the Drosophila GAGA Factor, Trithorax-like (Trl), and they bind to the same loci simultaneously. Phenotypic analyses of Trl and Atro clones suggest that Atro is required to modulate the transcription activation by Trl in larval imaginal discs. Taken together, these data indicate that Atro is a major Trl cofactor that functions to moderate developmental gene transcription.

Mll5 is currently a member of the Mll family of SET domain histone methyltransferase proteins but studies have also showed that it could be part of the SET3 branch of proteins. Recently, constitutive knock out animal studies have shown that Mll5 is required for proper haematopoietic stem cell differentiation, and loss of Mll5 results in synthetic lethality for genome de-methylation. Mll5 deficient male mice are infertile and here we analyse the consequences of Mll5 deficiency for spermatogenesis.

Loss of heterozygosity (LOH) and copy number alteration (CNA) feature prominently in the somatic genomic landscape of tumors. As such, karyotypic aberrations in cancer genomes have been studied extensively to discover novel oncogenes and tumor-suppressor genes. Advances in sequencing technology have enabled the cost-effective detection of tumor genome and transcriptome mutation events at single-base-pair resolution; however, computational methods for predicting segmental regions of LOH in this context are not yet fully explored. Consequently, whole transcriptome, nucleotide-level resolution analysis of monoallelic expression patterns associated with LOH has not yet been undertaken in cancer. We developed a novel approach for inference of LOH from paired tumor/normal sequence data and applied it to a cohort of 23 triple-negative breast cancer (TNBC) genomes. Following extensive benchmarking experiments, we describe the nucleotide-resolution landscape of LOH in TNBC and assess the consequent effect of LOH on the transcriptomes of these tumors using RNA-seq-derived measurements of allele-specific expression. We show that the majority of monoallelic expression in the transcriptomes of triple-negative breast cancer can be explained by genomic regions of LOH and establish an upper bound for monoallelic expression that may be explained by other tumor-specific modifications such as epigenetics or mutations. Monoallelically expressed genes associated with LOH reveal that cell cycle, homologous recombination and actin-cytoskeletal functions are putatively disrupted by LOH in TNBC. Finally, we show how inference of LOH can be used to interpret allele frequencies of somatic mutations and postulate on temporal ordering of mutations in the evolutionary history of these tumors.

Modeling bifurcations in single-cell transcriptomics data has become an increasingly popular field of research. Several methods have been proposed to infer bifurcation structure from such data, but all rely on heuristic non-probabilistic inference. Here we propose the first generative, fully probabilistic model for such inference based on a Bayesian hierarchical mixture of factor analyzers. Our model exhibits competitive performance on large datasets despite implementing full Markov-Chain Monte Carlo sampling, and its unique hierarchical prior structure enables automatic determination of genes driving the bifurcation process. We additionally propose an Empirical-Bayes like extension that deals with the high levels of zero-inflation in single-cell RNA-seq data and quantify when such models are useful. We apply or model to both real and simulated single-cell gene expression data and compare the results to existing pseudotime methods. Finally, we discuss both the merits and weaknesses of such a unified, probabilistic approach in the context practical bioinformatics analyses.

Growing evidence shows that dysregulation of miRNAs plays a significant role in papillary thyroid cancer (PTC) tumorigenesis and development. The abnormal expression of miR-384 has been acknowledged in the proliferation or metastasis of some cancers. However, the function and the underlying mechanism of miR-384 in PTC progression remain largely unknown.

SARS-CoV-2 has infected over 200 million people worldwide, resulting in more than 4 million deaths. Randomized controlled trials are the single best tool to identify effective treatments against this novel pathogen.

RNA sequencing (RNAseq) has been widely used to generate bulk gene expression measurements collected from pools of cells. Only relatively recently have single-cell RNAseq (scRNAseq) methods provided opportunities for gene expression analyses at the single-cell level, allowing researchers to study heterogeneous mixtures of cells at unprecedented resolution. Tumors tend to be composed of heterogeneous cellular mixtures and are frequently the subjects of such analyses. Extensive method developments have led to several protocols for scRNAseq but, owing to the small amounts of RNA in single cells, technical constraints have required compromises. For example, the majority of scRNAseq methods are limited to sequencing only the 3' or 5' termini of transcripts. Other protocols that facilitate full-length transcript profiling tend to capture only polyadenylated mRNAs and are generally limited to processing only 96 cells at a time. Here, we address these limitations and present a novel protocol that allows for the high-throughput sequencing of full-length, total RNA at single-cell resolution. We demonstrate that our method produced strand-specific sequencing data for both polyadenylated and non-polyadenylated transcripts, enabled the profiling of transcript regions beyond only transcript termini, and yielded data rich enough to allow identification of cell types from heterogeneous biological samples.

CX-5461 is a G-quadruplex (G4) ligand currently in trials with initial indications of clinical activity in cancers with defects in homologous recombination repair. To identify more genetic defects that could sensitize tumors to CX-5461, we tested synthetic lethality for 480 DNA repair and genome maintenance genes to CX-5461, pyridostatin (PDS), a structurally unrelated G4-specific stabilizer, and BMH-21, which binds GC-rich DNA but not G4 structures. We identified multiple members of HRD, Fanconi Anemia pathways, and POLQ, a polymerase with a helicase domain important for G4 structure resolution. Significant synthetic lethality was observed with UBE2N and RNF168, key members of the DNA damage response associated ubiquitin signaling pathway. Loss-of-function of RNF168 and UBE2N resulted in significantly lower cell survival in the presence of CX-5461 and PDS but not BMH-21. RNF168 recruitment and histone ubiquitination increased with CX-5461 treatment, and nuclear ubiquitination response frequently co-localized with G4 structures. Pharmacological inhibition of UBE2N acted synergistically with CX-5461. In conclusion, we have uncovered novel genetic vulnerabilities to CX-5461 with potential significance for patient selection in future clinical trials.

Genomic and phenotypic analyses indicate extensive intra- as well as intertumoral heterogeneity in primary human malignant cell populations despite their clonal origin. Cellular DNA barcoding offers a powerful and unbiased alternative to track the number and size of multiple subclones within a single human tumour xenograft and their response to continued in vivo passaging. Using this approach we find clone-initiating cell frequencies that vary from ~1/10 to ~1/10,000 cells transplanted for two human breast cancer cell lines and breast cancer xenografts derived from three different patients. For the cell lines, these frequencies are negatively affected in transplants of more than 20,000 cells. Serial transplants reveal five clonal growth patterns (unchanging, expanding, diminishing, fluctuating or of delayed onset), whose predominance is highly variable both between and within original samples. This study thus demonstrates the high growth potential and diverse growth properties of xenografted human breast cancer cells.

Platinum-based combination chemotherapy is the standard treatment for advanced non-small cell lung cancer (NSCLC). While cisplatin is effective, its use is not curative and resistance often emerges. As a consequence of microenvironmental heterogeneity, many tumour cells are exposed to sub-lethal doses of cisplatin. Further, genomic heterogeneity and unique tumor cell sub-populations with reduced sensitivities to cisplatin play a role in its effectiveness within a site of tumor growth. Being exposed to sub-lethal doses will induce changes in gene expression that contribute to the tumour cell's ability to survive and eventually contribute to the selective pressures leading to cisplatin resistance. Such changes in gene expression, therefore, may contribute to cytoprotective mechanisms. Here, we report on studies designed to uncover how tumour cells respond to sub-lethal doses of cisplatin. A microarray study revealed changes in gene expressions that occurred when A549 cells were exposed to a no-observed-effect level (NOEL) of cisplatin (e.g. the IC10). These data were integrated with results from a genome-wide siRNA screen looking for novel therapeutic targets that when inhibited transformed a NOEL of cisplatin into one that induced significant increases in lethality. Pathway analyses were performed to identify pathways that could be targeted to enhance cisplatin activity. We found that over 100 genes were differentially expressed when A549 cells were exposed to a NOEL of cisplatin. Pathways associated with apoptosis and DNA repair were activated. The siRNA screen revealed the importance of the hedgehog, cell cycle regulation, and insulin action pathways in A549 cell survival and response to cisplatin treatment. Results from both datasets suggest that RRM2B, CABYR, ALDH3A1, and FHL2 could be further explored as cisplatin-enhancing gene targets. Finally, pathways involved in repairing double-strand DNA breaks and INO80 chromatin remodeling were enriched in both datasets, warranting further research into combinations of cisplatin and therapeutics targeting these pathways.

Mixed Lineage Leukemia 5 (MLL5) is a histone methyltransferase that plays a key role in hematopoiesis, spermatogenesis and cell cycle progression. In addition to its catalytic domain, MLL5 contains a PHD finger domain, a protein module that is often involved in binding to the N-terminus of histone H3. Here we report the NMR solution structure of the MLL5 PHD domain showing a variant of the canonical PHD fold that combines conserved H3 binding features from several classes of other PHD domains (including an aromatic cage) along with a novel C-terminal α-helix, not previously seen. We further demonstrate that the PHD domain binds with similar affinity to histone H3 tail peptides di- and tri-methylated at lysine 4 (H3K4me2 and H3K4me3), the former being the putative product of the MLL5 catalytic reaction. This work establishes the PHD domain of MLL5 as a bone fide 'reader' domain of H3K4 methyl marks suggesting that it may guide the spreading or further methylation of this site on chromatin.

We have reported a high expression of IGF-I in pancreatic islet β-cells of transgenic mice under the metallothionein promoter. cDNA microarray analysis of the islets revealed that the expression of 82 genes was significantly altered compared to wild-type mice. Of these, 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1), which is responsible for the conversion of inert cortisone (11-dehydrocorticosterone, DHC in rodents) to active cortisol (corticosterone) in the liver and adipose tissues, has not been identified previously as an IGF-I target in pancreatic islets. We characterized the changes in its protein level, enzyme activity and glucose-stimulated insulin secretion. In freshly isolated islets, the level of 11β-HSD1 protein was significantly lower in MT-IGF mice. Using dual-labeled immunofluorescence, 11β-HSD1 was observed exclusively in glucagon-producing, islet α-cells but at a lower level in transgenic vs. wild-type animals. MT-IGF islets also exhibited reduced enzymatic activities. Dexamethasone (DEX) and DHC inhibited glucose-stimulated insulin secretion from freshly isolated islets of wild-type mice. In the islets of MT-IGF mice, 48-h pre-incubation of DEX caused a significant decrease in insulin release, while the effect of DHC was largely blunted consistent with diminished 11β-HSD1 activity. In order to establish the function of intracrine glucocorticoids, we overexpressed 11β-HSD1 cDNA in MIN6 insulinoma cells, which together with DHC caused apoptosis and a significant decrease in proliferation. Both effects were abolished with the treatment of an 11β-HSD1 inhibitor. Our results demonstrate an inhibitory effect of IGF-I on 11β-HSD1 expression and activity within the pancreatic islets, which may mediate part of the IGF-I effects on cell proliferation, survival and insulin secretion.

Targeting cancers with amplified or abnormally activated c-Met (hepatocyte growth factor receptor) may have therapeutic benefit based on nonclinical and emerging clinical findings. However, the eventual emergence of drug resistant tumors motivates the pre-emptive identification of potential mechanisms of clinical resistance. We rendered a MET amplified gastric cancer cell line, GTL16, resistant to c-Met inhibition with prolonged exposure to a c-Met inhibitor, PF-04217903 (METi). Characterization of surviving cells identified an amplified chromosomal rearrangement between 7q32 and 7q34 which overexpresses a constitutively active SND1-BRAF fusion protein. In the resistant clones, hyperactivation of the downstream MAPK pathway via SND1-BRAF conferred resistance to c-Met receptor tyrosine kinase inhibition. Combination treatment with METi and a RAF inhibitor, PF-04880594 (RAFi) inhibited ERK activation and circumvented resistance to either single agent. Alternatively, treatment with a MEK inhibitor, PD-0325901 (MEKi) alone effectively blocked ERK phosphorylation and inhibited cell growth. Our results suggest that combination of a c-Met tyrosine kinase inhibitor with a BRAF or a MEK inhibitor may be effective in treating resistant tumors that use activated BRAF to escape suppression of c-Met signaling.

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

Mature mammary epithelial cells are generated from undifferentiated precursors through a hierarchical process, but the molecular mechanisms involved, particularly in the human mammary gland, are poorly understood. To address this issue, we isolated highly purified subpopulations of primitive bipotent and committed luminal progenitor cells as well as mature luminal and myoepithelial cells from normal human mammary tissue and compared their transcriptomes obtained using three different methods. Elements unique to each subset of mammary cells were identified, and changes that accompany their differentiation in vivo were shown to be recapitulated in vitro. These include a stage-specific change in NOTCH pathway gene expression during the commitment of bipotent progenitors to the luminal lineage. Functional studies further showed NOTCH3 signaling to be critical for this differentiation event to occur in vitro. Taken together, these findings provide an initial foundation for future delineation of mechanisms that perturb primitive human mammary cell growth and differentiation.

Basal-like breast cancers (BLBCs) are very aggressive, and present serious clinical challenges as there are currently no targeted therapies available. We determined the regulatory role of Y-box binding protein-1 (YB-1) on epidermal growth factor receptor (EGFR) overexpression in BLBC, and the therapeutic potential of inhibiting EGFR. We pursued this in light of our recent work showing that YB-1 induces the expression of EGFR, a new BLBC marker.