High Concordance of Different Assays in the Determination of Homologous Recombination Deficiency-Associated Genomic Instability in Ovarian Cancer.

PURPOSE: Poly(ADP-ribose) polymerase inhibitors (PARPi) have shown promising clinical results in the treatment of ovarian cancer. Analysis of biomarker subgroups consistently revealed higher benefits for patients with homologous recombination deficiency (HRD). The test that is most often used for the detection of HRD in clinical studies is the Myriad myChoice assay. However, other assays can also be used to assess biomarkers, which are indicative of HRD, genomic instability (GI), and BRCA1/2 mutation status. Many of these assays have high potential to be broadly applied in clinical routine diagnostics in a time-effective decentralized manner. Here, we compare the performance of a multitude of alternative assays in comparison with Myriad myChoice in high-grade serous ovarian cancer (HGSOC). METHODS: DNA from HGSOC samples was extracted from formalin-fixed paraffin-embedded tissue blocks of cases previously run with the Myriad myChoice assay, and GI was measured by multiple molecular assays (CytoSNP, AmoyDx, Illumina TSO500 HRD, OncoScan, NOGGO GISv1, QIAseq HRD Panel and whole genome sequencing), applying different bioinformatics algorithms. RESULTS: Application of different assays to assess GI, including Myriad myChoice, revealed high concordance of the generated scores ranging from very substantial to nearly perfect fit, depending on the assay and bioinformatics pipelines applied. Interlaboratory comparison of assays also showed high concordance of GI scores. CONCLUSION: Assays for GI assessment not only show a high concordance with each other but also in correlation with Myriad myChoice. Thus, almost all of the assays included here can be used effectively to assess HRD-associated GI in the clinical setting. This is important as PARPi treatment on the basis of these tests is compliant with European Medicines Agency approvals, which are methodologically not test-bound.

Normalized LST Is an Efficient Biomarker for Homologous Recombination Deficiency and Olaparib Response in Ovarian Carcinoma.

PURPOSE: The efficiency of the Myriad Homologous Recombination Deficiency (HRD) test to guide the use of poly (ADP-ribose) polymerase (PARP) inhibitors has been demonstrated in several phase III trials. However, a need exists for alternative clinically validated tests. METHODS: A novel biomarker for HRD was developed using The Cancer Genome Atlas database and, as part of the ENGOT HRD European Initiative, applied to 469 samples from the PAOLA-1/ENGOT-ov25 trial. Results were compared with the Myriad myChoice Genomic Instability Score (GIS) with respect to the progression-free survival in the olaparib + bevacizumab and placebo + bevacizumab arms. RESULTS: Analysis of the TCGA cohort revealed that a normalization of the number of large-scale state transitions by the number of whole-genome doubling events allows a better separation and classification of HRD samples than the GIS. Analysis of the PAOLA-1 samples, using the Geneva test (OncoScan + nLST), yielded a lower failure rate (27 of 469 v 59 of 469) and a hazard ratio of 0.40 (95% CI, 0.28 to 0.57) compared with 0.37 for Myriad myChoice (BRCAm or GIS+) in the nLST-positive samples. In patients with BRCAwt, the Geneva test identified a novel subpopulation of patients, with a favorable 1-year PFS (85%) but a poor 2-year PFS (30%) on olaparib + bevacizumab treatment. CONCLUSION: The proposed test efficiently separates HRD-positive from HRD-negative patients, predicts response to PARP inhibition, and can be easily deployed in a clinical laboratory for routine practice. The performance is similar to the available commercial test, but its lower failure rate allows an increase in the number of patients who will receive a conclusive laboratory result.

SF3B1 facilitates HIF1-signaling and promotes malignancy in pancreatic cancer.

Mutations in the splicing factor SF3B1 are frequently occurring in various cancers and drive tumor progression through the activation of cryptic splice sites in multiple genes. Recent studies also demonstrate a positive correlation between the expression levels of wild-type SF3B1 and tumor malignancy. Here, we demonstrate that SF3B1 is a hypoxia-inducible factor (HIF)-1 target gene that positively regulates HIF1 pathway activity. By physically interacting with HIF1α, SF3B1 facilitates binding of the HIF1 complex to hypoxia response elements (HREs) to activate target gene expression. To further validate the relevance of this mechanism for tumor progression, we show that a reduction in SF3B1 levels via monoallelic deletion of Sf3b1 impedes tumor formation and progression via impaired HIF signaling in a mouse model for pancreatic cancer. Our work uncovers an essential role of SF3B1 in HIF1 signaling, thereby providing a potential explanation for the link between high SF3B1 expression and aggressiveness of solid tumors.

Automated Detection of Arm-Level Alterations for Individual Cancer Patients in the Clinical Setting.

Copy number alterations are genetic events that promote tumor initiation and progression and are used in clinical care as diagnostic, prognostic, and predictive biomarkers. Based on the length of the alteration, they are roughly classified as focal and arm-level alterations. Although genome-wide techniques to detect arm-level alterations are gaining momentum in hospital laboratories, the high precision and novelty of these techniques pose new challenges: there is no consensus on the definition of an arm-level alteration and there is a lack of tools to compute them for individual patients. Based on 376 clinical samples analyzed with the OncoScan formalin-fixed, paraffin-embedded assay, a bimodal distribution of the percentage of bases with copy number alterations within a chromosomal arm was observed, with the second peak starting at 90% of arm length. Two approaches were tested for the definition of arm-level alterations: sum of altered segments (SoS) >90%, or the longest segment (LS) >90%. These approaches were validated against expert annotation of 25 clinical cases. The SoS method outperformed the LS method as indicated by a higher concordance (SoS, 95.2%; LS, 79.9%). Some of the discordances ultimately were attributed to human error, highlighting the advantages of automation. The increase in reliability led to the development of publicly available software and its inclusion into routine clinical practice at Geneva University Hospitals.

Ovarian cancer with high-level focal ERBB2 amplification responds to trastuzumab and pertuzumab.

Epithelial ovarian cancer (EOC) is usually diagnosed at an advanced stage and significantly contributes to cancer mortality in women. Despite multimodal treatment associating chemotherapy and surgery, most patients ultimately progress and require palliative systemic therapy. In EOC, the efficacy of anti-HER2 agents is minimal even after selecting patients for HER2 expression. ERBB2 gene amplification is observed in 3-10% of patients, depending on the specific method of detection and cutoffs. We report the case of a young woman with a FIGO stage IV high-grade serous ovarian cancer with an amplification of ERBB2. She was treated with the association of trastuzumab - pertuzumab after two lines of standard treatment and presented an excellent long-lasting partial response after 36 months of treatment. The association of trastuzumab and pertuzumab, without chemotherapy, has not been previously tested in this context and could be more efficacious than monotherapy with either agent. In addition, the significant benefit observed in this case could be attributed to the presence of a high-level focal amplification that is relatively rare and probably more specific than an increase in HER2 expression. In conclusion, prospective trials of the trastuzumab and pertuzumab combination should be considered in an appropriately selected EOC patient population.

Reliability of liquid biopsy analysis: an inter-laboratory comparison of circulating tumor DNA extraction and sequencing with different platforms.

Liquid biopsy, the analysis of circulating tumor DNA (ctDNA), is a promising tool in oncology, especially in personalized medicine. Although its main applications currently focus on selection and adjustment of therapy, ctDNA may also be used to monitor residual disease, establish prognosis, detect relapses, and possibly screen at-risk individuals. CtDNA represents a small and variable proportion of circulating cell-free DNA (ccfDNA) which is itself present at a low concentration in normal individuals and so analyzing ctDNA is technically challenging. Various commercial systems have recently appeared on the market, but it remains difficult for practitioners to compare their performance and to determine whether they yield comparable results. As a first step toward establishing national guidelines for ctDNA analyses, four laboratories in Switzerland joined a comparative exercise to assess ccfDNA extraction and ctDNA analysis by sequencing. Extraction was performed using six distinct methods and yielded ccfDNA of equally high quality, suitable for sequencing. Sequencing of synthetic samples containing predefined amounts of eight mutations was performed on three different systems, with similar results. In all four laboratories, mutations were easily identified down to 1% allele frequency, whereas detection at 0.1% proved challenging. Linearity was excellent in all cases and while molecular yield was superior with one system this did not impact on sensitivity. This study also led to several additional conclusions: First, national guidelines should concentrate on principles of good laboratory practice rather than recommend a particular system. Second, it is essential that laboratories thoroughly validate every aspect of extraction and sequencing, in particular with respect to initial amount of DNA and average sequencing depth. Finally, as software proved critical for mutation detection, laboratories should validate the performance of variant callers and underlying algorithms with respect to various types of mutations.

Tissue-Plasma TMB Comparison and Plasma TMB Monitoring in Patients With Metastatic Non-small Cell Lung Cancer Receiving Immune Checkpoint Inhibitors.

Immuno-oncology is an ever growing field that has seen important progress across the spectrum of cancers. Responses can be deep and durable. However, as only a minority of patients respond to checkpoint inhibition, predictive biomarkers are needed. Cancer is a genetic disease arising from the accumulation of somatic mutations in the DNA of affected cells. Tumor mutational burden (TMB), represents the number of somatic mutations in a tumor that form neoantigens, responsible for the immunogenicity of tumors. Randomized controlled trials have so far failed to show a survival benefit when stratifying patients by tissue TMB. TMB has also been evaluated in plasma (PTMB). PTMB is anticipated to represent the biology of the entire cancer, whereas obtaining tissue of an amenable primary or a metastatic lesion may be prone to sampling bias because of tumor heterogeneity. For this reason, we are evaluating the correlation between TMB and PTMB, and prospectively evaluating the impact of these biomarkers on clinical outcomes. We also discuss the technical difficulties inherent to performing and comparing these analyses. Furthermore, we evaluate the correlation between the evolution of PTMB during an immunotherapy treatment and response at 3 and 6 months, as we believe PTMB may be a dynamic biomarker. In this paper, we present results from the first 4 patients in this project.

Durable response to palbociclib and letrozole in ovarian cancer with CDKN2A loss.

Alterations of the Retinoblastoma (Rb) pathway are frequent in ovarian cancer, typically resulting from CDKN2A down-regulation, CCNE1 amplification, CCND1/2 amplification, and RB1 loss. However, bi-allelic CDKN2A mutation or homozygous deletion is a very rare event, concerning less than 5% of patients.Initial trials with palbociclib in serous ovarian cancer have shown very modest benefit in unselected patient populations, thus underlining the need for a biomarker predicting response. We report the case of a heavily pre-treated patient with a serous ovarian tumor harboring a homozygous deletion of the CDKN2A gene that derived significant, prolonged clinical benefit from palbociclib, a CDK4/6 oral inhibitor, with letrozole. Treatment with palbociclib and letrozole started on February 2018, with an ongoing response after 12 months.In conclusion, homozygous CDKN2A deletion is rare and could be used to predict response to CDK4/6 inhibitors in association with other genomic features. We encourage further trials in this direction.

BRAF inhibition sensitizes melanoma cells to α-amanitin via decreased RNA polymerase II assembly.

Despite the great success of small molecule inhibitors in the treatment of patients with BRAFV600E mutated melanoma, the response to these drugs remains transient and patients eventually relapse within a few months, highlighting the need to develop novel combination therapies based on the understanding of the molecular changes induced by BRAFV600E inhibitors. The acute inhibition of oncogenic signaling can rewire entire cellular signaling pathways and thereby create novel cancer cell vulnerabilities. Here, we demonstrate that inhibition of BRAFV600E oncogenic signaling in melanoma cell lines leads to destabilization of the large subunit of RNA polymerase II POLR2A (polymerase RNA II DNA-directed polypeptide A), thereby preventing its binding to the unconventional prefoldin RPB5 interactor (URI1) chaperone complex and the successful assembly of RNA polymerase II holoenzymes. Furthermore, in melanoma cell lines treated with mitogen-activated protein kinase (MAPK) inhibitors, α-amanitin, a specific and irreversible inhibitor of RNA polymerase II, induced massive apoptosis. Pre-treatment of melanoma cell lines with MAPK inhibitors significantly reduced IC50 values to α-amanitin, creating a state of collateral vulnerability similar to POLR2A hemizygous deletions. Thus, the development of melanoma specific α-amanitin antibody-drug conjugates could represent an interesting therapeutic approach for combination therapies with BRAFV600E inhibitors.

Targeted RNA-sequencing identifies FBXW4 instead of MGEA5 as fusion partner of TGFBR3 in pleomorphic hyalinizing angiectatic tumor.

Pleomorphic hyalinizing angiectatic tumor (PHAT) is a rare mesenchymal tumor of intermediate malignancy. PHAT, and the related hemosiderotic fibrolipomatous tumor, show a recurrent t(1;10)(p22;q24). Fluorescence in situ hybridization (FISH) and BAC (bacterial artificial chromosome) clones have previously identified TGFBR3 and MGEA5 as fusion partners. However, targeted RNA-sequencing allowed for the correct identification of FBXW4 and not MGEA5 as the fusion partner of TGFBR3 in a subcutaneous PHAT, a finding further confirmed by RT-PCR. FBXW4 and MGEA5 share a common cytogenetic location at 10q24.32, thereby suggesting that the use of less precise technology may have led to inaccurate gene identification. The study of additional cases is however required.

jSplice: a high-performance method for accurate prediction of alternative splicing events and its application to large-scale renal cancer transcriptome data.

MOTIVATION: Alternative splicing represents a prime mechanism of post-transcriptional gene regulation whose misregulation is associated with a broad range of human diseases. Despite the vast availability of transcriptome data from different cell types and diseases, bioinformatics-based surveys of alternative splicing patterns remain a major challenge due to limited availability of analytical tools that combine high accuracy and rapidity. RESULTS: We describe here a novel junction-centric method, jSplice, that enables de novo extraction of alternative splicing events from RNA-sequencing data with high accuracy, reliability and speed. Application to clear cell renal carcinoma (ccRCC) cell lines and 65 ccRCC patients revealed experimentally validatable alternative splicing changes and signatures able to prognosticate ccRCC outcome. In the aggregate, our results propose jSplice as a key analytic tool for the derivation of cell context-dependent alternative splicing patterns from large-scale RNA-sequencing datasets. AVAILABILITY AND IMPLEMENTATION: jSplice is a standalone Python application freely available at http://www.mhs.biol.ethz.ch/research/krek/jsplice CONTACT: wilhelm.krek@biol.ethz.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Colorectal cancer cells display chaperone dependency for the unconventional prefoldin URI1.

Chaperone dependency of cancer cells is an emerging trait that relates to the need of transformed cells to cope with the various stresses associated with the malignant state. URI1 (unconventional prefoldin RPB5 interactor 1) encodes a member of the prefoldin (PFD) family of molecular chaperones that acts as part of a heterohexameric PFD complex, the URI1 complex (URI1C), to promote assembly of multiprotein complexes involved in cell signaling and transcription processes. Here, we report that human colorectal cancer (CRCs) cell lines demonstrate differential dependency on URI1 and on the URI1 partner PFD STAP1 for survival, suggesting that this differential vulnerability of CRC cells is directly linked to URI1C chaperone function. Interestingly, in URI1-dependent CRC cells, URI1 deficiency is associated with non-genotoxic p53 activation and p53-dependent apoptosis. URI1-independent CRC cells do not exhibit such effects even in the context of wildtype p53. Lastly, in tumor xenografts, the conditional depletion of URI1 in URI1-dependent CRC cells was, after tumor establishment, associated with severe inhibition of subsequent tumor growth and activation of p53 target genes. Thus, a subset of CRC cells has acquired a dependency on the URI1 chaperone system for survival, providing an example of 'non-oncogene addiction' and vulnerability for therapeutic targeting.

HIF-driven SF3B1 induces KHK-C to enforce fructolysis and heart disease.

Fructose is a major component of dietary sugar and its overconsumption exacerbates key pathological features of metabolic syndrome. The central fructose-metabolising enzyme is ketohexokinase (KHK), which exists in two isoforms: KHK-A and KHK-C, generated through mutually exclusive alternative splicing of KHK pre-mRNAs. KHK-C displays superior affinity for fructose compared with KHK-A and is produced primarily in the liver, thus restricting fructose metabolism almost exclusively to this organ. Here we show that myocardial hypoxia actuates fructose metabolism in human and mouse models of pathological cardiac hypertrophy through hypoxia-inducible factor 1α (HIF1α) activation of SF3B1 and SF3B1-mediated splice switching of KHK-A to KHK-C. Heart-specific depletion of SF3B1 or genetic ablation of Khk, but not Khk-A alone, in mice, suppresses pathological stress-induced fructose metabolism, growth and contractile dysfunction, thus defining signalling components and molecular underpinnings of a fructose metabolism regulatory system crucial for pathological growth.

Integrated genomic analysis identifies subclasses and prognosis signatures of kidney cancer.

PURPOSE: To define robust miRNA-based molecular classifiers for human clear cell renal cell carcinoma (ccRCC) subgrouping and prognostication. EXPERIMENTAL DESIGN: Multidimensional data of over 500 clear cell renal cell carcinoma (ccRCC) patients were retrieved from The Cancer Genome Atlas (TCGA) archive. Data analysis was based on a novel computational approach that selectively considers patients with extreme expression values of miRNAs to detect survival-associated molecular signatures. RESULTS: Our in silico analysis unveiled a novel ccRCC-specific 5-miRNA (miR-10b, miR-21, miR-143, miR-183, and miR-192) signature able, when combined with information from conventional TNM staging and the age of the patient, to prognosticate ccRCC outcome more accurately than known ccRCC miRNA signatures or TNM staging alone. Furthermore, our approach revealed the existence of 6 distinct subgroups of ccRCC characterized by discrete differences in overall survival, tumor stage, and mutational spectra in key ccRCC tumor suppressor genes. It also demonstrated that BAP1 mutations correlate with tumor progression rather than overall survival. CONCLUSION: Integrated analysis of multidimensional data from the TCGA archive allowed to draw a portrait of distinct molecular subclasses of human ccRCC and to define signatures for prognosticating disease outcome. Together, these results offer new prospects for more accurate stratification and prognostication of ccRCC.

miR-28-5p promotes chromosomal instability in VHL-associated cancers by inhibiting Mad2 translation.

Chromosomal instability enables tumor development, enabled in part by aberrant expression of the mitotic checkpoint protein Mad2. Here we identify a novel regulatory mechanism for Mad2 expression involving miR-28-5p-mediated inhibition of Mad2 translation, and we demonstrate that this mechanism is triggered by inactivation of the tumor suppressor VHL, the most common event in clear cell renal cell carcinoma (ccRCC). In VHL-positive cancer cells, enhanced expression of miR-28-5p diminished Mad2 levels and promoted checkpoint weakness and chromosomal instability. Conversely, in checkpoint-deficient VHL-negative renal carcinoma cells, inhibition of miR-28-5p function restored Mad2 levels, mitotic checkpoint proficiency, and chromosomal stability. Notably, chromosome missegregation errors and aneuploidy that were produced in a mouse model of acute renal injury (as a result of kidney-specific ablation of pVHL function) were reverted in vivo also by genetic inhibition of miR-28-5p. Finally, bioinformatic analyses in human ccRCC associated loss of VHL with increased miR-28-5p expression and chromosomal instability. Together, our results defined miR-28-5p as a critical regulator of Mad2 translation and mitotic checkpoint function. By identifying a potential mediator of chromosomal instability in VHL-associated cancers, our work also suggests a novel microRNA-based therapeutic strategy to target aneuploid cells in VHL-associated cancers.

A transcript perspective on evolution.

Alternative splicing is now recognized as a major mechanism for transcriptome and proteome diversity in higher eukaryotes, yet its evolution is poorly understood. Most studies focus on the evolution of exons and introns at the gene level, while only few consider the evolution of transcripts. In this paper, we present a framework for transcript phylogenies where ancestral transcripts evolve along the gene tree by gains, losses, and mutation. We demonstrate the usefulness of our method on a set of 805 genes and two different topics. First, we improve a method for transcriptome reconstruction from ESTs (ASPic), then we study the evolution of function in transcripts. The use of transcript phylogenies allows us to double the precision of ASPic, whereas results on the functional study reveal that conserved transcripts are more likely to share protein domains than functional sites. These studies validate our framework for the study of evolution in large collections of organisms from the perspective of transcripts; for this purpose, we developed and provide a new tool, TrEvoR.

Inferring transcript phylogenies.

Alternative splicing, an unknown mechanism 20 years ago, is now recognized as a major mechanism for proteome and transcriptome diversity, particularly in mammals­some researchers conjecture that up to 90% of human genes are alternatively spliced. Despite much research on exon and intron evolution, little is known about the evolution of transcripts. In this paper, we present a model of transcript evolution and an associated algorithm to reconstruct transcript phylogenies. The evolution of the gene structure­exons and introns­is used as basis for the reconstruction of transcript phylogenies. We apply our model and reconstruction algorithm on two well-studied genes, MAG and PAX6, obtaining results consistent with current knowledge and thereby providing evidence that a phylogenetic analysis of transcripts is feasible and likely to be informative.

Gene expression data analysis using a novel approach to biclustering combining discrete and continuous data.

Many different methods exist for pattern detection in gene expression data. In contrast to classical methods, biclustering has the ability to cluster a group of genes together with a group of conditions (replicates, set of patients or drug compounds). However, since the problem is NP-complex, most algorithms use heuristic search functions and therefore might converge towards local maxima. By using the results of biclustering on discrete data as a starting point for a local search function on continuous data, our algorithm avoids the problem of heuristic initialization. Similar to OPSM, our algorithm aims to detect biclusters whose rows and columns can be ordered such that row values are growing across the bicluster's columns and vice-versa. Results have been generated on the yeast genome (Saccharomyces cerevisiae), a human cancer dataset and random data. Results on the yeast genome showed that 89% of the one hundred biggest non-overlapping biclusters were enriched with Gene Ontology annotations. A comparison with OPSM and ISA demonstrated a better efficiency when using gene and condition orders. We present results on random and real datasets that show the ability of our algorithm to capture statistically significant and biologically relevant biclusters.