Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease.

Periampullary cancers, including pancreatic ductal adenocarcinoma, ampullary-, cholangio-, and duodenal carcinoma, are frequently diagnosed in an advanced stage and are associated with poor overall survival. They are difficult to differentiate from each other and challenging to distinguish from benign periampullary disease preoperatively. To improve the preoperative diagnostics of periampullary neoplasms, clinical or biological markers are warranted.In this study, 28 blood plasma amino acids and derivatives from preoperative patients with benign (N = 45) and malignant (N = 72) periampullary disease were analyzed by LC-MS/MS.Principal component analysis and consensus clustering both separated the patients with cancer and the patients with benign disease. Glutamic acid had significantly higher plasma expression and 15 other metabolites significantly lower plasma expression in patients with malignant disease compared with patients having benign disease. Phenylalanine was the only metabolite associated with improved overall survival (HR = 0.50, CI 0.30-0.83, P < 0.01).Taken together, plasma metabolite profiles from patients with malignant and benign periampullary disease were significantly different and have the potential to distinguish malignant from benign disease preoperatively.

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers.

Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer.

Different miRNA profiling protocols and technologies introduce differences in the resulting quantitative expression profiles. These include differences in the presence (and measurability) of certain miRNAs. We present and examine a method based on quantile normalization, Adjusted Quantile Normalization (AQuN), to combine miRNA expression data from multiple studies in breast cancer into a single joint dataset for integrative analysis. By pooling multiple datasets, we obtain increased statistical power, surfacing patterns that do not emerge as statistically significant when separately analyzing these datasets. To merge several datasets, as we do here, one needs to overcome both technical and batch differences between these datasets. We compare several approaches for merging and jointly analyzing miRNA datasets. We investigate the statistical confidence for known results and highlight potential new findings that resulted from the joint analysis using AQuN. In particular, we detect several miRNAs to be differentially expressed in estrogen receptor (ER) positive versus ER negative samples. In addition, we identify new potential biomarkers and therapeutic targets for both clinical groups. As a specific example, using the AQuN-derived dataset we detect hsa-miR-193b-5p to have a statistically significant over-expression in the ER positive group, a phenomenon that was not previously reported. Furthermore, as demonstrated by functional assays in breast cancer cell lines, overexpression of hsa-miR-193b-5p in breast cancer cell lines resulted in decreased cell viability in addition to inducing apoptosis. Together, these observations suggest a novel functional role for this miRNA in breast cancer. Packages implementing AQuN are provided for Python and Matlab: https://github.com/YakhiniGroup/PyAQN.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Clinicopathological factors associated with tumour-specific mutation detection in plasma of patients with RAS-mutated or BRAF-mutated metastatic colorectal cancer.

Detection of tumour-specific circulating cell-free DNA in plasma (ctDNA) fails in a significant number of cases depending on the clinical context. The primary aim was to investigate clinicopathological factors associated with detection of ctDNA in patients with RAS-/BRAF-mutated metastatic colorectal cancer (mCRC) prior to first-line therapy. A secondary aim was to evaluate the prognostic impact of ctDNA compared to other biomarkers. Patients were included from the NORDIC-VII study (N = 253). ctDNA was sampled prior to treatment and analysed for hotspot tissue mutations (KRAS, NRAS, and BRAF) using droplet digital PCR. Multivariable regression models were constructed to predict the probability of mutation detection and survival. Increasing radiological size of target lesions by increments of 1 cm (odds ratio [OR] = 1.18; 95% confidence interval [CI] 1.09-1.27; P < .001), intact primary tumour (OR = 3.17; 95% CI 1.22-8.22; P = .018) and more than one metastatic site (OR = 3.08; 95% CI 1.32-7.19; P = .009) were associated with mutation detection in plasma. Metastatic involvement of the lung was associated with non-detection (OR = 0.26; 95% CI 0.12-0.58; P = .001). Preanalytical and analytical factors modulated detection. High allele frequencies of ctDNA indicated poor prognosis independently of CEA and CA19-9 (hazard ratio [HR] = 2.38; 95% CI 1.74-3.26; P < .001; N = 206). Clinicopathological characteristics should be carefully considered when evaluating ctDNA results from mCRC patients, especially when confronted with a plasma negative result. ctDNA may prove to be a clinically useful marker in the evaluation of mCRC treatment.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors.

BACKGROUND: Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes. METHODS: Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data. RESULTS: The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes. CONCLUSIONS: The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Human ectoparasites and the spread of plague in Europe during the Second Pandemic.

Plague, caused by the bacterium Yersinia pestis, can spread through human populations by multiple transmission pathways. Today, most human plague cases are bubonic, caused by spillover of infected fleas from rodent epizootics, or pneumonic, caused by inhalation of infectious droplets. However, little is known about the historical spread of plague in Europe during the Second Pandemic (14-19th centuries), including the Black Death, which led to high mortality and recurrent epidemics for hundreds of years. Several studies have suggested that human ectoparasite vectors, such as human fleas (Pulex irritans) or body lice (Pediculus humanus humanus), caused the rapidly spreading epidemics. Here, we describe a compartmental model for plague transmission by a human ectoparasite vector. Using Bayesian inference, we found that this model fits mortality curves from nine outbreaks in Europe better than models for pneumonic or rodent transmission. Our results support that human ectoparasites were primary vectors for plague during the Second Pandemic, including the Black Death (1346-1353), ultimately challenging the assumption that plague in Europe was predominantly spread by rats.

Immune phenotype of tumor microenvironment predicts response to bevacizumab in neoadjuvant treatment of ER-positive breast cancer.

Antiangiogenic drugs are potentially a useful supplement to neoadjuvant chemotherapy for a subgroup of patients with human epidermal growth factor receptor 2 (HER2) negative breast cancer, but reliable biomarkers for improved response are lacking. Here, we report on a randomized phase II clinical trial to study the added effect of bevacizumab in neoadjuvant chemotherapy with FEC100 (5-fluorouracil, epirubicin and cyclophosphamide) and taxanes (n = 132 patients). Gene expression from the tumors was obtained before neoadjuvant treatment, and treatment response was evaluated by residual cancer burden (RCB) at time of surgery. Bevacizumab increased the proportion of complete responders (RCB class 0) from 5% to 20% among patients with estrogen receptor (ER) positive tumors (P = .02). Treatment with bevacizumab was associated with improved 8-year disease-free survival (P = .03) among the good responders (RCB class 0 or I). Patients treated with paclitaxel (n = 45) responded better than those treated with docetaxel (n = 21; P = .03). Improved treatment response was associated with higher proliferation rate and an immune phenotype characterized by high presence of classically activated M1 macrophages, activated NK cells and memory activated CD4 T cells. Treatment with bevacizumab increased the number of adverse events, including hemorrhage, hypertension, infection and febrile neutropenia, but despite this, the ECOG status was not affected.

Molecularly matched therapy in the context of sensitivity, resistance, and safety; patient outcomes in end-stage cancer - the MetAction study.

Background: In precision cancer medicine, the challenge is to prioritize DNA driver events, account for resistance markers, and procure sufficient information for treatment that maintains patient safety. The MetAction project, exploring how tumor molecular vulnerabilities predict therapy response, first established the required workflow for DNA sequencing and data interpretation (2014-2015). Here, we employed it to identify molecularly matched therapy and recorded outcome in end-stage cancer (2016-2019).Material and methods: Metastatic tissue from 26 patients (16 colorectal cancer cases) was sequenced by the Oncomine assay. The study tumor boards interpreted called variants with respect to sensitivity or resistance to matched therapy and recommended single-agent or combination treatment if considered tolerable. The primary endpoint was the rate of progression-free survival 1.3-fold longer than for the most recent systemic therapy. The objective response rate and overall survival were secondary endpoints.Results: Both common and rare actionable alterations were identified. Thirteen patients were found eligible for therapy following review of tumor sensitivity and resistance variants and patient tolerability. The interventions were inhibitors of ALK/ROS1-, BRAF-, EGFR-, FGFR-, mTOR-, PARP-, or PD-1-mediated signaling for 2-3 cases each. Among 10 patients who received treatment until radiologic evaluation, 6 (46% of the eligible cases) met the primary endpoint. Four colorectal cancer patients (15% of the total study cohort) had objective response. The only serious adverse event was a transient colitis, which appeared in 1 of the 2 patients given PD-1 inhibitor with complete response. Apart from those two, overall survival was similar for patients who did and did not receive study treatment.Conclusions: The systematic MetAction approach may point forward to a refined framework for how to interpret the complexity of sensitivity versus resistance and patient safety that resides in tumor sequence data, for the possibly improved outcome of precision cancer medicine in future studies. ClinicalTrials.gov, identifier: NCT02142036.

Intra-patient Inter-metastatic Genetic Heterogeneity in Colorectal Cancer as a Key Determinant of Survival after Curative Liver Resection.

Chromosomal instability is a well-defined hallmark of tumor aggressiveness and metastatic progression in colorectal cancer. The magnitude of genetic heterogeneity among distinct liver metastases from the same patient at the copy number level, as well as its relationship with chemotherapy exposure and patient outcome, remains unknown. We performed high-resolution DNA copy number analyses of 134 liver metastatic deposits from 45 colorectal cancer patients to assess: (i) intra-patient inter-metastatic genetic heterogeneity using a heterogeneity score based on pair-wise genetic distances among tumor deposits; and (ii) genomic complexity, defined as the proportion of the genome harboring aberrant DNA copy numbers. Results were analyzed in relation to the patients' clinical course; previous chemotherapy exposure and outcome after surgical resection of liver metastases. We observed substantial variation in the level of intra-patient inter-metastatic heterogeneity. Heterogeneity was not associated with the number of metastatic lesions or their genomic complexity. In metachronous disease, heterogeneity was higher in patients previously exposed to chemotherapy. Importantly, intra-patient inter-metastatic heterogeneity was a strong prognostic determinant, stronger than known clinicopathological prognostic parameters. Patients with a low level of heterogeneity (below the median level) had a three-year progression-free and overall survival rate of 23% and 66% respectively, versus 5% and 18% for patients with a high level (hazard ratio0.4, 95% confidence interval 0.2-0.8, P = 0.01; and hazard ratio0.3,95% confidence interval 0.1-0.7, P = 0.007). A low patient-wise level of genomic complexity (below 25%) was also a favorable prognostic factor; however, the prognostic association of intra-patient heterogeneity was independent of genomic complexity in multivariable analyses. In conclusion, intra-patient inter-metastatic genetic heterogeneity is a pronounced feature of metastatic colorectal cancer, and the strong prognostic association reinforces its clinical relevance and places it as a key feature to be explored in future patient cohorts.

chimeraviz: a tool for visualizing chimeric RNA.

SUMMARY: Advances in high-throughput RNA sequencing have enabled more efficient detection of fusion transcripts, but the technology and associated software used for fusion detection from sequencing data often yield a high false discovery rate. Good prioritization of the results is important, and this can be helped by a visualization framework that automatically integrates RNA data with known genomic features. Here we present chimeraviz , a Bioconductor package that automates the creation of chimeric RNA visualizations. The package supports input from nine different fusion-finder tools: deFuse, EricScript, InFusion, JAFFA, FusionCatcher, FusionMap, PRADA, SOAPfuse and STAR-FUSION. AVAILABILITY AND IMPLEMENTATION: chimeraviz is an R package available via Bioconductor ( https://bioconductor.org/packages/release/bioc/html/chimeraviz.html ) under Artistic-2.0. Source code and support is available at GitHub ( https://github.com/stianlagstad/chimeraviz ). CONTACT: rolf.i.skotheim@rr-research.no. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Breast Cancer Molecular Stratification: From Intrinsic Subtypes to Integrative Clusters.

Breast carcinomas can be stratified into different entities based on clinical behavior, histologic features, and/or by biological properties. A classification of breast cancer should be based on underlying biology, which we know must be determined by the somatic genomic landscape of mutations. Moreover, because the latest generations of anticancer agents are founded on biological mechanisms, a detailed molecular stratification is a requirement for appropriate clinical management. Such stratification, based on genomic drivers, will be important for selecting patients for clinical trials. It will also facilitate the discovery of novel drivers, the study of tumor evolution, and the identification of mechanisms of treatment resistance. Assays for risk stratification have focused mainly on response prediction to existing treatment regimens. Molecular stratification based on gene expression profiling revealed that breast cancers could be classified in so-called intrinsic subtypes (luminal A and B, HER2-enriched, basal-like, and normal-like), which mostly corresponded to hormone receptor and HER2 status, and further stratified luminal tumors based on proliferation. The realization that a significant proportion of the gene expression landscape is determined by the somatic copy number alterations that drive expression in cis led to the newer classification of breast cancers into integrative clusters. This stratification of breast cancers into integrative clusters reveals prototypical patterns of single-nucleotide variants and is associated with distinct clinical courses and response to therapy.

Correction to: A systematic comparison of copy number alterations in four types of female cancer.

After publication of the original article [1] the authors found that the article contained an incorrect version of Fig. 4. This does not affect the results and conclusions of the article.

Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome.

BACKGROUND: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. METHODS: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. RESULTS: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. CONCLUSIONS: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.

Patterns of constitutively phosphorylated kinases in B cells are associated with disease severity in common variable immunodeficiency.

Patients with common variable immunodeficiency (CVID) constitute a clinically and immunologically heterogeneous group characterized by B-cell dysfunction with hypogammaglobulinemia and defective immunoglobulin class switch of unknown etiology. Current classification systems are insufficient to achieve precise disease management. Characterization of signaling pathways essential for B-cell differentiation and class switch could provide new means to stratify patients. We evaluated constitutive and induced signaling by phospho-specific flow cytometry in 26 CVID patients and 18 healthy blood donors. Strong responses were induced both in CVID and healthy donor B cells upon activation. In contrast, constitutive phosphorylation levels of STAT3,-5,-6, Erk, PLC-γ and Syk were significantly increased in CVID B cells only. Hierarchical clustering revealed a subgroup of CVID patients with elevated constitutive phosphorylation of Syk and PLC-γ. All these patients had non-infectious complications, indicating that a distinct phosphorylation pattern of kinases in B cells identifies a clinically important subgroup of CVID patients.

The tumour microenvironment influences survival and time to transformation in follicular lymphoma in the rituximab era.

The tumour microenvironment influences outcome in patients with follicular lymphoma (FL), but its impact on transformation is less studied. We investigated the prognostic significance of the tumour microenvironment on transformation and survival in FL patients treated in the rituximab era. We examined diagnostic and transformed biopsies from 52 FL patients using antibodies against CD3, CD4, CD8, CD21 (CR2), CD57 (B3GAT1), CD68, FOXP3, TIA1, PD-1 (PDCD1), PD-L1 (CD274) and PAX5. Results were compared with a second cohort of 40 FL patients without signs of transformation during a minimum of five years observation time. Cell numbers and localization were semi-quantitatively assessed. Better developed CD21+  follicular dendritic cell (FDC) meshworks at diagnosis was a negative prognostic factor for overall survival (OS), progression-free survival (PFS) and time to transformation (TTT) in patients with subsequently transformed FL. Remnants of FDC meshworks at transformation were associated with shorter OS and PFS from transformation. High degrees of intrafollicular CD68+ and PD-L1+  macrophage infiltration, high total area scores and an extrafollicular/diffuse pattern of FOXP3+  T cells and high intrafollicular scores of CD4+  T cells at diagnosis were associated with shorter TTT. Scores of several T-cell subset markers from the combined patient cohorts were predictive for transformation, especially CD4 and CD57.

Whole-genome integrative analysis reveals expression signatures predicting transformation in follicular lymphoma.

Transformation of follicular lymphoma (FL) to a more aggressive disease is associated with rapid progression and death. Existing molecular markers for transformation are few and their clinical impact is limited. Here, we report on a whole-genome study of DNA copy numbers and gene expression profiles in serial FL biopsies. We identified 698 genes with high correlation between gene expression and copy number, and the molecular network most enriched for these cis-associated genes. This network includes 14 cis-associated genes directly related to the nuclear factor κB (NF-κB) pathway. For each of these 14 genes, the correlated NF-κB target genes were identified and corresponding expression scores were defined. The scores for 6 of the cis-associated NFκB pathway genes (BTK, IGBP1, IRAK1, ROCK1, TMED7-TICAM2, and TRIM37) were significantly associated with transformation. The results suggest that genes regulating B-cell survival and activation are involved in transformation of FL.

A systematic comparison of copy number alterations in four types of female cancer.

BACKGROUND: Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways. METHODS: In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets. RESULTS AND DISCUSSION: Analyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways. CONCLUSIONS: Our results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types.