B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer.

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.

A multi-omic single-cell landscape of human gynecologic malignancies.

Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression. We show that malignant cells acquire previously unannotated regulatory elements to drive hallmark cancer pathways. Moreover, malignant cells from within the same patients show substantial variation in chromatin accessibility linked to transcriptional output, highlighting the importance of intratumoral heterogeneity. Finally, we infer the malignant cell type-specific activity of transcription factors. By defining the regulatory logic of cancer cells, this work reveals an important reliance on oncogenic regulatory elements and highlights the ability of matched scRNA-seq/scATAC-seq to uncover clinically relevant mechanisms of tumorigenesis in gynecologic cancers.

The Immune Landscape of Cancer.

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-ß dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.

ZFX Mediates Non-canonical Oncogenic Functions of the Androgen Receptor Splice Variant 7 in Castrate-Resistant Prostate Cancer.

Androgen receptor splice variant 7 (AR-V7) is crucial for prostate cancer progression and therapeutic resistance. We show that, independent of ligand, AR-V7 binds both androgen-responsive elements (AREs) and non-canonical sites distinct from full-length AR (AR-FL) targets. Consequently, AR-V7 not only recapitulates AR-FL's partial functions but also regulates an additional gene expression program uniquely via binding to gene promoters rather than ARE enhancers. AR-V7 binding and AR-V7-mediated activation at these unique targets do not require FOXA1 but rely on ZFX and BRD4. Knockdown of ZFX or select unique targets of AR-V7/ZFX, or BRD4 inhibition, suppresses growth of castration-resistant prostate cancer cells. We also define an AR-V7 direct target gene signature that correlates with AR-V7 expression in primary tumors, differentiates metastatic prostate cancer from normal, and predicts poor prognosis. Thus, AR-V7 has both ARE/FOXA1 canonical and ZFX-directed non-canonical regulatory functions in the evolution of anti-androgen therapeutic resistance, providing information to guide effective therapeutic strategies.

Genome-wide cancer-specific chromatin accessibility patterns derived from archival processed xenograft tumors.

Chromatin accessibility states that influence gene expression and other nuclear processes can be altered in disease. The constellation of transcription factors and chromatin regulatory complexes in cells results in characteristic patterns of chromatin accessibility. The study of these patterns in tissues has been limited because existing chromatin accessibility assays are ineffective for archival formalin-fixed, paraffin-embedded (FFPE) tissues. We have developed a method to efficiently extract intact chromatin from archival tissue via enhanced cavitation with a nanodroplet reagent consisting of a lipid shell with a liquid perfluorocarbon core. Inclusion of nanodroplets during the extraction of chromatin from FFPE tissues enhances the recovery of intact accessible and nucleosome-bound chromatin. We show that the addition of nanodroplets to the chromatin accessibility assay formaldehyde-assisted isolation of regulatory elements (FAIRE), does not affect the accessible chromatin signal. Applying the technique to FFPE human tumor xenografts, we identified tumor-relevant regions of accessible chromatin shared with those identified in primary tumors. Further, we deconvoluted non-tumor signal to identify cellular components of the tumor microenvironment. Incorporation of this method of enhanced cavitation into FAIRE offers the potential for extending chromatin accessibility to clinical diagnosis and personalized medicine, while also enabling the exploration of gene regulatory mechanisms in archival samples.

An integrated model for predicting KRAS dependency.

The clinical approvals of KRAS G12C inhibitors have been a revolutionary advance in precision oncology, but response rates are often modest. To improve patient selection, we developed an integrated model to predict KRAS dependency. By integrating molecular profiles of a large panel of cell lines from the DEMETER2 dataset, we built a binary classifier to predict a tumor's KRAS dependency. Monte Carlo cross validation via ElasticNet within the training set was used to compare model performance and to tune parameters α and λ. The final model was then applied to the validation set. We validated the model with genetic depletion assays and an external dataset of lung cancer cells treated with a G12C inhibitor. We then applied the model to several Cancer Genome Atlas (TCGA) datasets. The final "K20" model contains 20 features, including expression of 19 genes and KRAS mutation status. In the validation cohort, K20 had an AUC of 0.94 and accurately predicted KRAS dependency in both mutant and KRAS wild-type cell lines following genetic depletion. It was also highly predictive across an external dataset of lung cancer lines treated with KRAS G12C inhibition. When applied to TCGA datasets, specific subpopulations such as the invasive subtype in colorectal cancer and copy number high pancreatic adenocarcinoma were predicted to have higher KRAS dependency. The K20 model has simple yet robust predictive capabilities that may provide a useful tool to select patients with KRAS mutant tumors that are most likely to respond to direct KRAS inhibitors.

Ezh2 orchestrates gene expression for the stepwise differentiation of tissue-specific stem cells.

Although in vitro studies of embryonic stem cells have identified polycomb repressor complexes (PRCs) as key regulators of differentiation, it remains unclear as to how PRC-mediated mechanisms control fates of multipotent progenitors in developing tissues. Here, we show that an essential PRC component, Ezh2, is expressed in epidermal progenitors but diminishes concomitant with embryonic differentiation and with postnatal decline in proliferative activity. We show that Ezh2 controls proliferative potential of basal progenitors by repressing the Ink4A-Ink4B locus and tempers the developmental rate of differentiation by preventing premature recruitment of AP1 transcriptional activator to the structural genes that are required for epidermal differentiation. Together, our studies reveal that PRCs control epigenetic modifications temporally and spatially in tissue-restricted stem cells. They maintain their proliferative potential and globally repressing undesirable differentiation programs while selectively establishing a specific terminal differentiation program in a stepwise fashion.

Peripheral Blood IL5RA Gene Expression as a Diagnostic Biomarker for Eosinophilic Esophagitis.

Eosinophilic esophagitis (EoE) is an allergic inflammatory condition of the esophagus, often diagnosed late because of its challenging symptoms and costly and invasive diagnostic methods.1,2 To address the need for more accessible biomarkers in EoE,3 we aimed to investigate the potential of whole-blood RNA expression as a noninvasive biomarker for diagnosing and monitoring EoE, hypothesizing that genetic signatures in blood could distinguish EoE cases, correlate with disease activity, and predict treatment responses.

Sequencing of genes of drug response in tumor DNA and implications for precision medicine in cancer patients.

Tumor DNA sequencing is becoming standard-of-care for patient treatment decisions. We evaluated genotype concordance between tumor DNA and genomic DNA from blood and catalogued functional effects of somatic mutations in 21 drug response genes in 752 solid tumor patients. Using a threshold of 10% difference between tumor and blood DNA variant allele fraction (VAF), concordance for heterogenous genotype calls was 78% and increased to 97.5% using a 30% VAF threshold. Somatic mutations were observed in all 21 drug response genes, and 44% of patients had at least one somatic mutation in these genes. In tumor DNA, eight patients had a frameshift mutation in CYP2C8, which metabolizes taxanes. Overall, somatic copy number losses were more frequent than gains, including for CYP2C19 and CYP2D6 which had the most frequent copy number losses. However, copy number gains in TPMT were more than four times as common as losses. Seven % of patients had copy number gains in ABCB1, a multidrug resistance transporter of anti-cancer agents. These results demonstrate tumor-only DNA sequencing might not be reliable to call germline genotypes of drug response variants.

Cistrome analysis of YY1 uncovers a regulatory axis of YY1:BRD2/4-PFKP during tumorigenesis of advanced prostate cancer.

Castration-resistant prostate cancer (CRPC) is a terminal disease and the molecular underpinnings of CRPC development need to be better understood in order to improve its treatment. Here, we report that a transcription factor Yin Yang 1 (YY1) is significantly overexpressed during prostate cancer progression. Functional and cistrome studies of YY1 uncover its roles in promoting prostate oncogenesis in vitro and in vivo, as well as sustaining tumor metabolism including the Warburg effect and mitochondria respiration. Additionally, our integrated genomics and interactome profiling in prostate tumor show that YY1 and bromodomain-containing proteins (BRD2/4) co-occupy a majority of gene-regulatory elements, coactivating downstream targets. Via gene loss-of-function and rescue studies and mutagenesis of YY1-bound cis-elements, we unveil an oncogenic pathway in which YY1 directly binds and activates PFKP, a gene encoding the rate-limiting enzyme for glycolysis, significantly contributing to the YY1-enforced Warburg effect and malignant growth. Altogether, this study supports a master regulator role for YY1 in prostate tumorigenesis and reveals a YY1:BRD2/4-PFKP axis operating in advanced prostate cancer with implications for therapy.

Pre-treatment differential correlation of gene expression and response to topical steroids in eosinophilic esophagitis.

Few predictors of response to topical corticosteroid (tCS) treatment have been identified in eosinophilic esophagitis (EoE). We aimed to determine whether baseline gene expression predicts histologic response to tCS treatment for EoE. We analyzed prospectively collected samples from incident EoE cases who were treated with tCS for 8 weeks in a development cohort (prospective study) or in an independent validation cohort (clinical trial). Whole transcriptome RNA expression was determined from a baseline (pre-treatment) RNA-later preserved esophageal biopsy. Baseline expression was compared between histologic responders (<15 eos/hpf) and non-responders (≥15 eos/hpf), and differential correlation was used to assess baseline gene expression by response status. In 87 EoE cases analyzed in the development set, there were no differentially expressed genes associated with treatment response (at false discovery rate = 0.1). However, differential correlation identified a module of 22 genes with statistically significantly high pairwise correlation in non-responders (mean correlation coefficient = 0.7) compared to low correlation in responders (coefficient = 0.3). When this 22-gene module was applied to the 89 EoE cases in the independent cohort, it was not validated to predict tCS response at the 15 eos/hpf threshold (mean correlation coefficient = 0.32 in responders and 0.25 in nonresponders). Exploration of other thresholds also did not validate any modules. Though we identified a 22 gene differential correlation module measured pre-treatment that was strongly associated with subsequent histologic response to tCS in EoE, this was not validated in an independent population. Alternative methods to predict steroid response should be explored.

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide.

Cells exhibiting strong p16INK4a promoter activation in vivo display features of senescence.

The activation of cellular senescence throughout the lifespan promotes tumor suppression, whereas the persistence of senescent cells contributes to aspects of aging. This theory has been limited, however, by an inability to identify and isolate individual senescent cells within an intact organism. Toward that end, we generated a murine reporter strain by "knocking-in" a fluorochrome, tandem-dimer Tomato (tdTom), into exon 1α of the p16INK4a locus. We used this allele (p16tdTom ) for the enumeration, isolation, and characterization of individual p16INK4a -expressing cells (tdTom+). The half-life of the knocked-in transcript was shorter than that of the endogenous p16INK4a mRNA, and therefore reporter expression better correlated with p16INK4a promoter activation than p16INK4a transcript abundance. The frequency of tdTom+ cells increased with serial passage in cultured murine embryo fibroblasts from p16tdTom/+ mice. In adult mice, tdTom+ cells could be readily detected at low frequency in many tissues, and the frequency of these cells increased with aging. Using an in vivo model of peritoneal inflammation, we compared the phenotype of cells with or without activation of p16INK4a and found that tdTom+ macrophages exhibited some features of senescence, including reduced proliferation, senescence-associated ß-galactosidase (SA-ß-gal) activation, and increased mRNA expression of a subset of transcripts encoding factors involved in SA-secretory phenotype (SASP). These results indicate that cells harboring activation of the p16INK4a promoter accumulate with aging and inflammation in vivo, and display characteristics of senescence.

Validation of reference genes for whole blood gene expression analysis in cord blood of preterm and full-term neonates and peripheral blood of healthy adults.

BACKGROUND: Preterm birth is the leading cause of neonatal morbidity and mortality, but research efforts in neonatology are complicated due to the unavailability of large volume blood samples. Whole blood assays can be used to overcome this problem by performing both functional and gene expression studies using small amounts of blood. Gene expression studies using RT-qPCR estimate mRNA-levels of target genes normalized to reference genes. The goal of this study was to identify and validate stable reference genes applicable to cord blood samples obtained from developing neonates of different gestational age groups as well as to adult peripheral blood samples. Eight reference gene candidates (ACTB, B2M, GAPDH, GUSB, HPRT, PPIB, RPLP0, RPL13) were analyzed using the three published software algorithms Bestkeeper, GeNorm and NormFinder. RESULTS: A normalization factor consisting of ACTB and PPIB allows for comparative expression analyses of neonatal samples from different gestational age groups. Normalization factors consisting of GAPDH and PPIB or ACTB and GAPDH are suitable when samples from preterm and full-term neonates and adults are compared. However, all candidate reference genes except RPLP0 exhibited significant intergroup gene expression variance and a higher gene expression towards an older age which resulted in a small but statistically significant systematic bias. Systematic analysis of RNA-seq data revealed new reference gene candidates with potentially superior stability. CONCLUSIONS: The current study identified suitable normalization factors and proposed the use of the additional single gene RPLP0 to avoid systematic bias. This combination will enable comparative analyses not only between neonates of different gestational ages, but also between neonates and adults, as it facilitates more detailed investigations of developmental gene expression changes. The use of software algorithms did not prevent unintended systematic bias. This generally highlights the need for careful validation of such results to prevent false interpretation of potential age-dependent changes in gene expression. To identify the most stable reference genes in the future, RNA-seq based global approaches are recommended.

Subependymal giant cell astrocytomas are characterized by mTORC1 hyperactivation, a very low somatic mutation rate, and a unique gene expression profile.

Subependymal giant-cell astrocytomas (SEGAs) are slow-growing brain tumors that are a hallmark feature seen in 5-10% of patients with Tuberous Sclerosis Complex (TSC). Though histologically benign, they can cause serious neurologic symptoms, leading to death if untreated. SEGAs consistently show biallelic loss of TSC1 or TSC2. Herein, we aimed to define other somatic events beyond TSC1/TSC2 loss and identify potential transcriptional drivers that contribute to SEGA formation. Paired tumor-normal whole-exome sequencing was performed on 21 resected SEGAs from 20 TSC patients. Pathogenic variants in TSC1/TSC2 were identified in 19/21 (90%) SEGAs. Copy neutral loss of heterozygosity (size range: 2.2-46 Mb) was seen in 76% (16/21) of SEGAs (44% chr9q and 56% chr16p). An average of 1.4 other somatic variants (range 0-7) per tumor were identified, unlikely of pathogenic significance. Whole transcriptome RNA-sequencing analyses revealed 190 common differentially expressed genes in SEGA (n = 16, 13 from a prior study) in pairwise comparison to each of: low grade diffuse gliomas (n = 530) and glioblastoma (n = 171) from The Cancer Genome Atlas (TCGA) consortium, ganglioglioma (n = 10), TSC cortical tubers (n = 15), and multiple normal tissues. Among these, homeobox transcription factors (TFs) HMX3, HMX2, VAX1, SIX3; and TFs IRF6 and EOMES were all expressed >12-fold higher in SEGAs (FDR/q-value < 0.05). Immunohistochemistry supported the specificity of IRF6, VAX1, SIX3 for SEGAs in comparison to other tumor entities and normal brain. We conclude that SEGAs have an extremely low somatic mutation rate, suggesting that TSC1/TSC2 loss is sufficient to drive tumor growth. The unique and highly expressed SEGA-specific TFs likely reflect the neuroepithelial cell of origin, and may also contribute to the transcriptional and epigenetic state that enables SEGA growth following two-hit loss of TSC1 or TSC2 and mTORC1 activation.

A multivariable prognostic score to guide systemic therapy in early-stage HER2-positive breast cancer: a retrospective study with an external evaluation.

BACKGROUND: In early-stage HER2-positive breast cancer, escalation or de-escalation of systemic therapy is a controversial topic. As an aid to treatment decisions, we aimed to develop a prognostic assay that integrates multiple data types for predicting survival outcome in patients with newly diagnosed HER2-positive breast cancer. METHODS: We derived a combined prognostic model using retrospective clinical-pathological data on stromal tumour-infiltrating lymphocytes, PAM50 subtypes, and expression of 55 genes obtained from patients who participated in the Short-HER phase 3 trial. The trial enrolled patients with newly diagnosed, node-positive, HER2-positive breast cancer or, if node negative, with at least one risk factor (ie, tumour size >2 cm, histological grade 3, lymphovascular invasion, Ki67 >20%, age ≤35 years, or hormone receptor negativity), and randomly assigned them to adjuvant anthracycline plus taxane-based combinations with either 9 weeks or 1 year of trastuzumab. Trastuzumab was administered intravenously every 3 weeks (8 mg/kg loading dose at first cycle, and 6 mg/kg thereafter) for 18 doses or weekly (4 mg/kg loading dose in the first week, and 2 mg/kg thereafter) for 9 weeks, starting concomitantly with the first taxane dose. Median follow-up was 91·4 months (IQR 75·1-105·6). The primary objective of our study was to derive and evaluate a combined prognostic score associated with distant metastasis-free survival (the time between randomisation and distant recurrence or death before recurrence), an exploratory endpoint in Short-HER. Patient samples in the training dataset were split into a training set (n=290) and a testing set (n=145), balancing for event and treatment group. The training set was further stratified into 100 iterations of Monte-Carlo cross validation (MCCV). Cox proportional hazard models were fit to MCCV training samples using Elastic-Net. A maximum of 92 features were assessed. The final prognostic model was evaluated in an independent combined dataset of 267 patients with early-stage HER2-positive breast cancer treated with different neoadjuvant and adjuvant anti-HER2-based combinations and from four other studies (PAMELA, CHER-LOB, Hospital Clinic, and Padova) with disease-free survival outcome data. FINDINGS: From Short-HER, data from 435 (35%) of 1254 patients for tumour size (T1 vs rest), nodal status (N0 vs rest), number of tumour-infiltrating lymphocytes (continuous variable), subtype (HER2-enriched and basal-like vs rest), and 13 genes composed the final model (named HER2DX). HER2DX was significantly associated with distant metastasis-free survival as a continuous variable (p<0·0001). HER2DX median score for quartiles 1-2 was identified as the cutoff to identify low-risk patients; and the score that distinguished quartile 3 from quartile 4 was the cutoff to distinguish medium-risk and high-risk populations. The 5-year distant metastasis-free survival of the low-risk, medium-risk, and high-risk populations were 98·1% (95% CI 96·3-99·9), 88·9% (83·2-95·0), and 73·9% (66·0-82·7), respectively (low-risk vs high-risk hazard ratio [HR] 0·04, 95% CI 0·0-0·1, p<0·0001). In the evaluation cohort, HER2DX was significantly associated with disease-free survival as a continuous variable (HR 2·77, 95% CI 1·4-5·6, p=0·0040) and as group categories (low-risk vs high-risk HR 0·27, 0·1-0·7, p=0·005). 5-year disease-free survival in the HER2DX low-risk group was 93·5% (89·0-98·3%) and in the high-risk group was 81·1% (71·5-92·1). INTERPRETATION: The HER2DX combined prognostic score identifies patients with early-stage, HER2-positive breast cancer who might be candidates for escalated or de-escalated systemic treatment. Future clinical validation of HER2DX seems warranted to establish its use in different scenarios, especially in the neoadjuvant setting. FUNDING: Instituto Salud Carlos III, Save the Mama, Pas a Pas, Fundación Científica, Asociación Española Contra el Cáncer, Fundación SEOM, National Institutes of Health, Agenzia Italiana del Farmaco, International Agency for Research on Cancer, and the Veneto Institute of Oncology, and Italian Association for Cancer Research.

Virus expression detection reveals RNA-sequencing contamination in TCGA.

BACKGROUND: Contamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al., for example, found HeLa-derived human papillomavirus 18 (H-HPV18) in several of The Cancer Genome Atlas (TCGA) RNA-sequencing samples. This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years. RESULTS: We confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the "common reference", which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the "common reference". One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells. CONCLUSIONS: Altogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV.

Identifying transcriptional profiles and evaluating prognostic biomarkers of HIV-associated diffuse large B-cell lymphoma from Malawi.

Lymphoma incidence in sub-Saharan Africa (SSA) is increasing due to HIV and population aging. Diffuse Large B-cell lymphoma (DLBCL), the most common lymphoma in SSA and worldwide, is highly associated with HIV, but molecular studies of HIV-associated DLBCL are scarce globally. We describe profiling of DLBCL from Malawi, aiming to elucidate tumor biology and identify clinically meaningful biomarkers specifically for SSA. Between June 1, 2013 and June 1, 2016, 59 cases of DLBCL (32 HIV+/27 HIV-) enrolled in the Kamuzu Central Hospital Lymphoma Study were characterized, of which 54 (92%) were negative for Epstein-Barr virus. Gene expression profiling (GEP) by whole transcriptome sequencing was performed on the first 36 cases (22 HIV+/14 HIV-). Immunohistochemistry (IHC) and GEP results were compared with published data and correlated to clinical outcome and pathologic features. Unsupervised clustering strongly segregated DLBCL by HIV status (p = 0.0003, Chi-squared test), indicating a marked contribution of HIV to expression phenotype. Pathway analysis identified that HIV-associated tumors were enriched in hypoxia, oxidative stress, and metabolism related gene expression patterns. Cell-of-origin subtype, determined by sequencing and IHC, did not associate with differences in overall survival (OS), while Ki-67 proliferation index ≥80% was associated with inferior OS in HIV+ DLBCL only (p = 0.03) and cMYC/BCL2 co-expression by IHC was negatively prognostic across the entire cohort (p = 0.01). This study provides among the first molecular characterizations of DLBCL from SSA, demonstrates marked gene expression differences by HIV status, and identifies genomic and immunophenotypic characteristics that can inform future basic and clinical investigations.

Improved indel detection in DNA and RNA via realignment with ABRA2.

MOTIVATION: Genomic variant detection from next-generation sequencing has become established as an extremely important component of research and clinical diagnoses in both cancer and Mendelian disorders. Insertions and deletions (indels) are a common source of variation and can frequently impact functionality, thus making their detection vitally important. While substantial effort has gone into detecting indels from DNA, there is still opportunity for improvement. Further, detection of indels from RNA-Seq data has largely been an afterthought and offers another critical area for variant detection. RESULTS: We present here ABRA2, a redesign of the original ABRA implementation that offers support for realignment of both RNA and DNA short reads. The process results in improved accuracy and scalability including support for human whole genomes. Results demonstrate substantial improvement in indel detection for a variety of data types, including those that were not previously supported by ABRA. Further, ABRA2 results in broad improvements to variant calling accuracy across a wide range of post-processing workflows including whole genomes, targeted exomes and transcriptome sequencing. AVAILABILITY AND IMPLEMENTATION: ABRA2 is implemented in a combination of Java and C/C++ and is freely available to all from: https://github.com/mozack/abra2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.