Chromosomal instability (CIN) drives cell-to-cell heterogeneity, and the development of genetic diseases, including cancer. Impaired homologous recombination (HR) has been implicated as a major driver of CIN, however, the underlying mechanism remains unclear. Using a fission yeast model system, we establish a common role for HR genes in suppressing DNA double-strand break (DSB)-induced CIN. Further, we show that an unrepaired single-ended DSB arising from failed HR repair or telomere loss is a potent driver of widespread CIN. Inherited chromosomes carrying a single-ended DSB are subject to cycles of DNA replication and extensive end-processing across successive cell divisions. These cycles are enabled by Cullin 3-mediated Chk1 loss and checkpoint adaptation. Subsequent propagation of unstable chromosomes carrying a single-ended DSB continues until transgenerational end-resection leads to fold-back inversion of single-stranded centromeric repeats and to stable chromosomal rearrangements, typically isochromosomes, or to chromosomal loss. These findings reveal a mechanism by which HR genes suppress CIN and how DNA breaks that persist through mitotic divisions propagate cell-to-cell heterogeneity in the resultant progeny.

Background PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers. Methods Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging. Results A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis (‘GLYC-GLUC’) which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance. Conclusions In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K , but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

The effect of radiation therapy on tumor vasculature has long been a subject of debate. Increased oxygenation and perfusion have been documented during radiation therapy. Conversely, apoptosis of endothelial cells in irradiated tumors has been proposed as a major contributor to tumor control. To examine these contradictions, we use multiphoton microscopy in two murine tumor models: MC38, a highly vascularized, and B16F10, a moderately vascularized model, grown in transgenic mice with tdTomato‐labeled endothelium before and after a single (15 Gy) or fractionated (5 × 3 Gy) dose of radiation. Unexpectedly, even these high doses lead to little structural change of the perfused vasculature. Conversely, non‐perfused vessels and blind ends are substantially impaired after radiation accompanied by apoptosis and reduced proliferation of their endothelium. RNAseq analysis of tumor endothelial cells confirms the modification of gene expression in apoptotic and cell cycle regulation pathways after irradiation. Therefore, we conclude that apoptosis of tumor endothelial cells after radiation does not impair vascular structure. The effects of ionizing radiation on tumor vasculature are disputed. This study shows that radiation of murine tumors using either single (15 Gy) or fractionated (5 × 3 Gy) doses fails to result in significant structural changes of the perfused tumor vasculature. Because apoptosis mainly occurs in non‐perfused vessels and blind ends, the main structural network remains. Radiation of murine tumors using either single (15 Gy) or fractionated (5 × 3 Gy) doses fails to result in significant structural changes of the perfused tumor vasculature. Because apoptosis mainly occurs in non‐perfused vessels and blind ends, the main structural network remains.

Tumour hypoxia is associated with poor patient prognosis and therapy resistance. A unique transcriptional response is initiated by hypoxia which includes the rapid activation of numerous transcription factors in a background of reduced global transcription. Here, we show that the biological response to hypoxia includes the accumulation of R-loops and the induction of the RNA/DNA helicase SETX. In the absence of hypoxia-induced SETX, R-loop levels increase, DNA damage accumulates, and DNA replication rates decrease. Therefore, suggesting that, SETX plays a role in protecting cells from DNA damage induced during transcription in hypoxia. Importantly, we propose that the mechanism of SETX induction in hypoxia is reliant on the PERK/ATF4 arm of the unfolded protein response. These data not only highlight the unique cellular response to hypoxia, which includes both a replication stress-dependent DNA damage response and an unfolded protein response but uncover a novel link between these two distinct pathways.

Persistent DNA damage arising from unrepaired broken chromosomes or telomere loss can promote DNA damage checkpoint adaptation, and cell cycle progression, thereby increasing cell survival but also genome instability. However, the nature and extent of such instability is unclear. We show, using , that inherited broken chromosomes, arising from failed homologous recombination repair, are subject to cycles of gregation, DNA eplication and extensive end-rocessing, termed here SERPent cycles, by daughter cells, over multiple generations. Following Chk1 loss these post-adaptive cycles continue until extensive processing through inverted repeats promotes annealing, fold-back inversion and a spectrum of chromosomal rearrangements, typically isochromosomes, or chromosome loss, in the resultant population. These findings explain how persistent DNA damage drives widespread genome instability, with implications for punctuated evolution, genetic disease and tumorigenesis.

Tumor hypoxia is associated with poor patient outcomes in estrogen receptor-α (ERα) positive breast cancer. Hypoxia is known to affect tumor growth by reprogramming metabolism and regulating amino acid (AA) uptake. Here we show that the glutamine transporter, SNAT2, is the AA transporter most frequently induced by hypoxia in breast cancer and it is regulated by HIF1α both in-vitro and in-vivo in xenografts. SNAT2 induction in MCF7 cells was also regulated by ERα but it became predominantly a HIF-1α-dependent gene under hypoxia. Relevant to this, binding sites for both HIF-1α and ERα overlap in SNAT2’s cis-regulatory elements. In addition, the downregulation of SNAT2 by the ER antagonist fulvestrant was reverted in hypoxia. Overexpression of SNAT2 in-vitro to recapitulate the levels induced by hypoxia caused enhanced growth, particularly after ERα inhibition, in hypoxia, or when glutamine levels were low. SNAT2 upregulation in-vivo caused complete resistance to anti-estrogen and, partially, anti-VEGF therapies. Finally, high SNAT2 expression levels correlate with HIF-1α and worse outcome in patients given anti-estrogen therapy. Our findings show a switch in regulation of SNAT2 between ERα and HIF-1α, leading to endocrine resistance in hypoxia. Development of drugs targeting SNAT2 may be of value for a subset of hormone-resistant breast cancer.

With the increased use of next-generation sequencing generating large amounts of genomic data, gene expression signatures are becoming critically important tools for the interpretation of these data, and are poised to have a substantial effect on diagnosis, management, and prognosis for a number of diseases. It is becoming crucial to establish whether the expression patterns and statistical properties of sets of genes, or gene signatures, are conserved across independent datasets. Conversely, it is necessary to compare established signatures on the same dataset to better understand how they capture different clinical or biological characteristics. Here we describe how to use sigQC, a tool that enables a streamlined, systematic approach for the evaluation of previously obtained gene signatures across multiple gene expression datasets. We implemented sigQC in an R package, making it accessible to users who have knowledge of file input/output and matrix manipulation in R and a moderate grasp of core statistical principles. SigQC has been adopted in basic biology and translational studies, including, but not limited to, the evaluation of multiple gene signatures for potential clinical use as cancer biomarkers. This protocol uses a previously obtained signature for breast cancer metastasis as an example to illustrate the critical quality control steps involved in evaluating its expression, variability, and structure in breast tumor RNA-sequencing data, a different dataset from that in which the signature was originally derived. We demonstrate how the outputs created from sigQC can be used for the evaluation of gene signatures on large-scale gene expression datasets.

Background Epidemiological studies suggest that metformin may reduce the incidence of cancer in patients with diabetes and multiple late phase clinical trials assessing the potential of repurposing this drug are underway. Transcriptomic profiling of tumour samples is an excellent tool to understand drug bioactivity, identify candidate biomarkers and assess for mechanisms of resistance to therapy. Methods Thirty-six patients with untreated primary breast cancer were recruited to a window study and transcriptomic profiling of tumour samples carried out before and after metformin treatment. Results Multiple genes that regulate fatty acid oxidation were upregulated at the transcriptomic level and there was a differential change in expression between two previously identified cohorts of patients with distinct metabolic responses. Increase in expression of a mitochondrial fatty oxidation gene composite signature correlated with change in a proliferation gene signature. In vitro assays showed that, in contrast to previous studies in models of normal cells, metformin reduces fatty acid oxidation with a subsequent accumulation of intracellular triglyceride, independent of AMPK activation. Conclusions We propose that metformin at clinical doses targets fatty acid oxidation in cancer cells with implications for patient selection and drug combinations. Clinical Trial Registration NCT01266486.

Background: Hypoxia is associated with a poor prognosis in prostate cancer. This work aimed to derive and validate a hypoxia-related mRNA signature for localized prostate cancer. Method: Hypoxia genes were identified in vitro via RNA-sequencing and combined with in vivo gene co-expression analysis to generate a signature. The signature was independently validated in eleven prostate cancer cohorts and a bladder cancer phase III randomized trial of radiotherapy alone or with carbogen and nicotinamide (CON). Results: A 28-gene signature was derived. Patients with high signature scores had poorer biochemical recurrence free survivals in six of eight independent cohorts of prostatectomy-treated patients (Log rank test P < .05), with borderline significances achieved in the other two (P < .1). The signature also predicted biochemical recurrence in patients receiving post-prostatectomy radiotherapy (n = 130, P = .007) or definitive radiotherapy alone (n = 248, P = .035). Lastly, the signature predicted metastasis events in a pooled cohort (n = 631, P = .002). Prognostic significance remained after adjusting for clinic-pathological factors and commercially available prognostic signatures. The signature predicted benefit from hypoxia-modifying therapy in bladder cancer patients (intervention-by-signature interaction test P = .0026), where carbogen and nicotinamicle was associated with improved survival only in hypoxic tumours. Conclusion: A 28-gene hypoxia signature has strong and independent prognostic value for prostate cancer patients. (C) 2018 Published by Elsevier B.V.

Late-phase clinical trials investigating metformin as a cancer therapy are underway. However, there remains controversy as to the mode of action of metformin in tumors at clinical doses. We conducted a clinical study integrating measurement of markers of systemic metabolism, dynamic FDG-PET-CT, transcriptomics, and metabolomics at paired time points to profile the bioactivity of metformin in primary breast cancer. We show metformin reduces the levels of mitochondrial metabolites, activates multiple mitochondrial metabolic pathways, and increases 18-FDG flux in tumors. Two tumor groups are identified with distinct metabolic responses, an OXPHOS transcriptional response (OTR) group for which there is an increase in OXPHOS gene transcription and an FDG response group with increased 18-FDG uptake. Increase in proliferation, as measured by a validated proliferation signature, suggested that patients in the OTR group were resistant to metformin treatment. We conclude that mitochondrial response to metformin in primary breast cancer may define anti-tumor effect.

5 Background: Hypoxia is an important regulatory factor in tumorigenesis and is associated with a poor prognosis. Patients with high risk locally advanced disease account for 13-21% of prostate cancer cases and the ten year cancer specific survival rate for these patients is 62%. Patients with hypoxic tumours could benefit from hypoxia modifying therapeutics in addition to radiotherapy. Clinical companion biomarkers are needed to stratify patients who would benefit from hypoxia modifying therapy in addition to radiotherapy. Methods: RNA-seq analysis was performed on prostate cell lines (PNT2-C2, PC-3, LNCaP and DU145) exposed to 1% hypoxia for 24 hrs. A prostate cancer hypoxia gene signature was derived in silico using publicly available prostate gene expression data sets and the RNA-seq data. The biomarker was then independently validated in multiple cohorts of prostate cancer patients with localized diseases receiving prostatectomy alone, prostatectomy plus adjuvant radiotherapy, prostatectomy plus salvage radiotherapy, or definitive radiotherapy alone. Results: In vitro the hypoxia inducible expression of the hypoxia gene signature was tested at 1% and 0.1% oxygen of which 21 of the 28 genes were regulated by hypoxia. Patients stratified as high hypoxia were associated with significantly poorer 5-year biochemical recurrence free survival in patients undergoing prostatectomy alone, prostatectomy plus adjuvant radiotherapy and definitive radiotherapy alone. In multivariable analysis, the biomarker retained significance after correcting for confounding factors including Gleason group, PSA, a molecular classifier, etc. In another cohort of prostatectomy and salvage radiotherapy treated patients, the mRNA signature predicts metastasis free survival in both univariable and multivariable analyses. Conclusions: We derived a de novo mRNA signature based on hypoxia-regulated genes. The biomarker consistently predicts biochemical failure and metastasis for prostate cancer patients with localized disease.

With the increase in next generation sequencing generating large amounts of genomic data, gene expression signatures are becoming critically important tools, poised to make a large impact on the diagnosis, management and prognosis for a number of diseases. Increasingly, it is becoming necessary to determine whether a gene expression signature may apply to a dataset, but no standard quality control methodology exists. In this work, we introduce the first protocol, implemented in an R package sigQC, enabling a streamlined methodological and standardised approach for the quality control validation of gene signatures on independent data sets. The emphasis in this work is in showing the critical quality control steps involved in the generation of a clinically and biologically useful, transportable gene signature, including ensuring sufficient expression, variability, and autocorrelation of a signature. We demonstrate the application of the protocol in this work, showing how the outputs created from sigQC may be used for the evaluation of gene signatures on large-scale gene expression data in cancer.

Background: Hypoxia, lack of oxygen, is a well-known cancer phenotype associated with poor prognosis and therapeutic resistance. Understanding the tumour molecular response to hypoxia is key to developing effective therapies and generating robust classifiers. We and others have previously demonstrated large transcriptional changes, up to 10-15% of the coding genome, in response to hypoxia. Whilst several studies described the gene expression changes in response to hypoxia, there is no comprehensive study addressing the extent different isoforms of the same gene are differentially regulated. Methods: Here, we investigated which transcripts are regulated in response to hypoxia, and whether there was significant alternative splicing across different tumour types. Twenty-one cell lines were used covering the main subtypes of four solid cancer types (prostate, breast, pancreas, colon), and cultured under normoxia and hypoxia (1% oxygen, 24 hours) in triplicate. Messenger RNA was sequenced in the 126 samples (polyA selection), and estimations made of differential gene expression, transcript-level differential expression and alternative splicing. Results: Of the 198,503 transcripts considered, 11826, 11604, 8686 and 5719 transcripts were upregulated and 11179, 12308, 9390 and 6220 were downregulated in the prostate, breast, pancreas, and colon cancer cell lines respectively. Of these, 861 were significantly up-regulated, and 1,484 down-regulated across all 21 cell lines and four cancer types indicating a significant common transcriptional response to hypoxia. Notably, this transcript-level analysis identified nearly all genes which could be detected in a gene-level analysis (96%-99% of genes depending on cancer types), but also many more (43%-58% of new genes) which were not discoverable in a gene-level analysis. Interestingly, there was a high number of genes (728, enrichment p < 0.00001) which showed regulation across all cancer types, although the specific isoforms regulated in each cancer were different. We observed that up to about 40% of the genes regulated by hypoxia, showed two or more transcripts differentially expressed. In agreement with this, alternative splicing analysis indicated large global changes in transcript architecture. These included transcripts in important hypoxia-regulated genes, such as VEGFA-204, transcript of the VEGFA gene, where three alternative splicing events could be detected, but also events and genes not previously linked to hypoxia. A meta-analysis merging the results from gene-, isoform- and exon-level analyses identified 10 top alternative splicing events which were highly significant across all cancers and 21 cell lines. Importantly, a pathway analysis revealed that the pathways affected were similar across cancer types and regulation of transcription was the top one, followed by signal transduction, vesicle-mediated transport, glycolysis and cell cycle. Conclusions: This study shows for the first time the extent of hypoxia alternative splicing and differential isoform regulation in multiple cancer types, highlighting differences and commonalities, and opening an important new avenue to understand how cancers adapt to hypoxia. Legal entity responsible for the study: University of Oxford Funding: Cancer Research UK Disclosure: All authors have declared no conflicts of interest.

Background: Hypoxia, lack of oxygen, is a well-known cancer phenotype associated with poor prognosis and therapeutic resistance. Understanding the tumour molecular response to hypoxia is key to developing effective therapies and generating robust classifiers. We and others have previously demonstrated large transcriptional changes, up to 10-15% of the coding genome, in response to hypoxia. Whilst several studies described the gene expression changes in response to hypoxia, there is no comprehensive study addressing the extent different isoforms of the same gene are differentially regulated.

Approximately 160,000 cases of prostate cancer are diagnosed annually in the United States. Prostate cancer is the third leading cause of cancer death in American men. Hypoxia is associated with radiotherapy resistance and a poor prognosis in prostate cancer. There is evidence that only the most hypoxic tumors benefit from hypoxia-targeted treatment, but there is no clinically validated method identifying hypoxic prostate cancers. We aimed to derive and validate a gene expression signature reflecting hypoxia in prostate cancer. RNA sequencing was performed to identify genes induced by 1% hypoxia for 24 hours in four prostate cancer cell lines, including PNT2-C2, PC-3, LNCaP, and DU145. In vitro hypoxia gene analysis was then combined with in vivo analysis of gene co-expression network from TCGA cohort to generate a hypoxia gene expression signature. The signature was locked and independently validated in seven retrospective cohorts of low- to high-risk patients with localized disease. A 28-gene signature was derived. Twenty-one signature genes were regulated by hypoxia in vitro. In seven independent patient cohorts, the hypoxia signature score was positively correlated with pathological Gleason score and tumor stage, but not pre-treatment PSA level. Patients stratified as high hypoxia were associated with significantly poorer biochemical-relapse free survival. The hypoxia signature remained an independent predictor in a multivariate analysis after adjusting for Gleason score, tumor stage, and pre-treatment PSA. The signature also predicted benefit from hypoxia-modifying therapy with carbogen and nicotinamide in bladder cancer patients (n = 113, HR 0·54, 95% CI 0·32-0·91, P = 0·021). A 28-gene hypoxia signature has a strong and independent prognostic value for prostate cancer patients.

Background: Over 100 clinical trials are underway worldwide to investigate the anticancer effects of the diabetes drug, metformin. However, it is still not determined as to whether metformin has significant direct effects on cancer cells or solely indirect effects via modulation of host metabolism.