Transcriptome Analysis of BAFF/BAFF-R System in Murine Nephrotoxic Serum Nephritis.

Chronic kidney disease (CKD) is an emerging cause for morbidity and mortality worldwide. Acute kidney injury (AKI) can transition to CKD and finally to end-stage renal disease (ESRD). Targeted treatment is still unavailable. NF-κB signaling is associated with CKD and activated by B cell activating factor (BAFF) via BAFF-R binding. In turn, renal tubular epithelial cells (TECs) are critical for the progression of fibrosis and producing BAFF. Therefore, the direct involvement of the BAFF/BAFF-R system to the pathogenesis of CKD is conceivable. We performed non-accelerated nephrotoxic serum nephritis (NTN) as the CKD model in BAFF KO (B6.129S2-Tnfsf13btm1Msc/J), BAFF-R KO (B6(Cg)-Tnfrsf13ctm1Mass/J) and wildtype (C57BL/6J) mice to analyze the BAFF/BAFF-R system in anti-glomerular basement membrane (GBM) disease using high throughput RNA sequencing. We found that BAFF signaling is directly involved in the upregulation of collagen III as BAFF ko mice showed a reduced expression. However, these effects were not mediated via BAFF-R. We identified several upregulated genes that could explain the effects of BAFF in chronic kidney injury such as Txnip, Gpx3, Igfbp7, Ccn2, Kap, Umod and Ren1. Thus, we conclude that targeted treatment with anti-BAFF drugs such as belimumab may reduce chronic kidney damage. Furthermore, upregulated genes may be useful prognostic CKD biomarkers.

NMDA Receptors in Health and Diseases: New Roles and Signaling Pathways-Anti-N-Methyl-D-Aspartate Receptor (NMDAR) Autoantibodies as Potential Biomarkers of Fatigue in Patients with Rheumatic Diseases.

Fatigue is a widespread and complex symptom with motor and cognitive components; it is diagnosed predominantly by questionnaire. We recently published a correlation between anti-N-methyl-D-aspartate receptor (NMDAR) antibodies and fatigue in patients with SLE (systemic lupus erythematosus). In the present study, we examined whether this association also applies to patients with other rheumatic diseases. Serum samples of 88 patients with different rheumatic diseases were analyzed for the presence of anti-NR2 antibodies and Neurofilament light chain (NfL) protein. The severity of fatigue was determined according to the FSMC questionnaire (Fatigue Scale for Motor and Cognitive Functions) and correlated with the circulating antibody titer and NfL level accordingly. Positive titers of anti-NR2 antibodies were detected in patients with both autoimmune and non-autoimmune rheumatic diseases. These patients suffer predominantly from severe fatigue. The circulating NfL level did not correlate with the anti-NR2 titer and the fatigue severity in all patient groups. The association of severe fatigue with circulating anti-NR2 antibodies in patients with rheumatic diseases, independently from the main disease, suggests an individual role of these autoantibodies in fatigue pathophysiology. Thus, the detection of these autoantibodies might be a helpful diagnostic tool in rheumatic patients with fatigue.

Definitive evidence for Club cells as progenitors for mutant Kras/Trp53-deficient lung cancer.

Accumulating evidence suggests that both the nature of oncogenic lesions and the cell-of-origin can strongly influence cancer histopathology, tumor aggressiveness and response to therapy. Although oncogenic Kras expression and loss of Trp53 tumor suppressor gene function have been demonstrated to initiate murine lung adenocarcinomas (LUADs) in alveolar type II (AT2) cells, clear evidence that Club cells, representing the second major subset of lung epithelial cells, can also act as cells-of-origin for LUAD is lacking. Equally, the exact anatomic location of Club cells that are susceptible to Kras transformation and the resulting tumor histotype remains to be established. Here, we provide definitive evidence for Club cells as progenitors for LUAD. Using in vivo lineage tracing, we find that a subset of Kras12V -expressing and Trp53-deficient Club cells act as precursors for LUAD and we define the stepwise trajectory of Club cell-initiated tumors leading to lineage marker conversion and aggressive LUAD. Our results establish Club cells as cells-of-origin for LUAD and demonstrate that Club cell-initiated tumors have the potential to develop aggressive LUAD.

Mutant MHC class II epitopes drive therapeutic immune responses to cancer.

Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient's tumour possesses a unique set of mutations ('the mutanome') that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient's individual tumour-specific mutations. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4(+) T cells. Vaccination with such CD4(+) immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4(+) T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient's tumour with vaccines produced 'just in time'.

Immunomic, genomic and transcriptomic characterization of CT26 colorectal carcinoma.

BACKGROUND: Tumor models are critical for our understanding of cancer and the development of cancer therapeutics. Here, we present an integrated map of the genome, transcriptome and immunome of an epithelial mouse tumor, the CT26 colon carcinoma cell line. RESULTS: We found that Kras is homozygously mutated at p.G12D, Apc and Tp53 are not mutated, and Cdkn2a is homozygously deleted. Proliferation and stem-cell markers, including Top2a, Birc5 (Survivin), Cldn6 and Mki67, are highly expressed while differentiation and top-crypt markers Muc2, Ms4a8a (MS4A8B) and Epcam are not. Myc, Trp53 (tp53), Mdm2, Hif1a, and Nras are highly expressed while Egfr and Flt1 are not. MHC class I but not MHC class II is expressed. Several known cancer-testis antigens are expressed, including Atad2, Cep55, and Pbk. The highest expressed gene is a mutated form of the mouse tumor antigen gp70. Of the 1,688 non-synonymous point variations, 154 are both in expressed genes and in peptides predicted to bind MHC and thus potential targets for immunotherapy development. Based on its molecular signature, we predicted that CT26 is refractory to anti-EGFR mAbs and sensitive to MEK and MET inhibitors, as have been previously reported. CONCLUSIONS: CT26 cells share molecular features with aggressive, undifferentiated, refractory human colorectal carcinoma cells. As CT26 is one of the most extensively used syngeneic mouse tumor models, our data provide a map for the rationale design of mode-of-action studies for pre-clinical evaluation of targeted- and immunotherapies.

Transcriptome analysis of renal ischemia/reperfusion (I/R) injury in BAFF and BAFF-R deficient mice.

Acute kidney injury (AKI) accompanies with high morbidity and mortality. Incomplete renal recovery can lead to chronic and finally end-stage kidney disease, which results in the requirement of lifelong dialysis or kidney transplantation. Consequently, finding predictive biomarker and therefore developing preventive therapeutic approaches is an urgent need. For this purpose, a better understanding of the mechanism underlying AKI is necessary. The cytokine BAFF (B cell activating factor) is related to AKI by supporting B cells, which in turn play an important role in inflammatory processes and the production of antibodies. In our study, we investigated the role of BAFF and its receptor BAFF-R in the early phase of AKI. Therefore, we performed the well-established ischemia/reperfusion (I/R) model in BAFF (B6.129S2-Tnfsf13btm1Msc/J) and BAFF-R (B6(Cg)-Tnfrsf13ctm1Mass/J) deficient mice. Transcriptome of ischemic and contralateral control kidneys was analyzed and compared to wildtype littermates. We detected the upregulation of Lcn2, Lyz2, Cd44, Fn1 and Il1rn in ischemic kidneys as well as the downregulation of Kl. Furthermore, we revealed different expression patterns in BAFF and BAFF-R knockout mice. Compared to wildtype littermates, up- and downregulation of each investigated gene were higher in BAFF-R knockout and lower in BAFF knockout. Our findings indicate a positive impact of BAFF knockout in early phase of AKI, while BAFF-R knockout seems to worsen I/R injury. In addition, our study shows for the first time a remarkable renal upregulation of Lyz2 in a murine I/R model. Therefore, we consider Lyz2 as conceivable predictive or early biomarker in case of I/R and AKI.

Current status of use of high throughput nucleotide sequencing in rheumatology.

OBJECTIVE: Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples. METHODS: We performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data. RESULTS: Of the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data. CONCLUSION: HTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

Multi-Omics Characterization of the 4T1 Murine Mammary Gland Tumor Model.

Background: Tumor models are critical for our understanding of cancer and the development of cancer therapeutics. The 4T1 murine mammary cancer cell line is one of the most widely used breast cancer models. Here, we present an integrated map of the genome, transcriptome, and immunome of 4T1. Results: We found Trp53 (Tp53) and Pik3g to be mutated. Other frequently mutated genes in breast cancer, including Brca1 and Brca2, are not mutated. For cancer related genes, Nav3, Cenpf, Muc5Ac, Mpp7, Gas1, MageD2, Dusp1, Ros, Polr2a, Rragd, Ros1, and Hoxa9 are mutated. Markers for cell proliferation like Top2a, Birc5, and Mki67 are highly expressed, so are markers for metastasis like Msln, Ect2, and Plk1, which are known to be overexpressed in triple-negative breast cancer (TNBC). TNBC markers are, compared to a mammary gland control sample, lower (Esr1), comparably low (Erbb2), or not expressed at all (Pgr). We also found testis cancer antigen Pbk as well as colon/gastrointestinal cancer antigens Gpa33 and Epcam to be highly expressed. Major histocompatibility complex (MHC) class I is expressed, while MHC class II is not. We identified 505 single nucleotide variations (SNVs) and 20 insertions and deletions (indels). Neoantigens derived from 22 SNVs and one deletion elicited CD8+ or CD4+ T cell responses in IFNγ-ELISpot assays. Twelve high-confidence fusion genes were observed. We did not observe significant downregulation of mismatch repair (MMR) genes or SNVs/indels impairing their function, providing evidence for 6-thioguanine resistance. Effects of the integration of the murine mammary tumor virus were observed at the genome and transcriptome level. Conclusions: 4T1 cells share substantial molecular features with human TNBC. As 4T1 is a common model for metastatic tumors, our data supports the rational design of mode-of-action studies for pre-clinical evaluation of targeted immunotherapies.

Bioinformatic methods for cancer neoantigen prediction.

Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition.

In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads.

Next-Generation Sequencing (NGS) enables the rapid generation of billions of short nucleic acid sequence fragments (i.e., "sequencing reads"). Especially, the adoption of gene expression profiling using whole transcriptome sequencing (i.e., "RNA-Seq") has been rapid. Here, we describe an in silico method, seq2HLA, that takes standard RNA-Seq reads as input and determines a sample's (classical and non-classical) HLA class I and class II types as well as HLA expression. We demonstrate the application of seq2HLA using publicly available RNA-Seq data from the Burkitt's lymphoma cell line DAUDI and the choriocarcinoma cell line JEG-3.

HLA and proteasome expression body map.

BACKGROUND: The presentation of HLA peptide complexes to T cells is a highly regulated and tissue specific process involving multiple transcriptionally controlled cellular components. The extensive polymorphism of HLA genes and the complex composition of the proteasome make it difficult to map their expression profiles across tissues. METHODS: Here we applied a tailored gene quantification pipeline to 4323 publicly available RNA-Seq datasets representing 55 normal tissues and cell types to examine expression profiles of (classical and non-classical) HLA class I, class II and proteasomal genes. RESULTS: We generated the first comprehensive expression atlas of antigen presenting-related genes across 56 normal tissues and cell types, including immune cells, pancreatic islets, platelets and hematopoietic stem cells. We found a surprisingly heterogeneous HLA expression pattern with up to 100-fold difference in intra-tissue median HLA abundances. Cells of the immune system and lymphatic organs expressed the highest levels of classical HLA class I (HLA-A,-B,-C), class II (HLA-DQA1,-DQB1,-DPA1,-DPB1,-DRA,-DRB1) and non-classical HLA class I (HLA-E,-F) molecules, whereas retina, brain, muscle, megakaryocytes and erythroblasts showed the lowest abundance. In contrast, we identified a distinct and highly tissue-restricted expression pattern of the non-classical class I gene HLA-G in placenta, pancreatic islets, pituitary gland and testis. While the constitutive proteasome showed relatively constant expression across all tissues, we found the immunoproteasome to be enriched in lymphatic organs and almost absent in immune privileged tissues. CONCLUSIONS: Here, we not only provide a reference catalog of tissue and cell type specific HLA expression, but also highlight extremely variable expression of the basic components of antigen processing and presentation in different cell types. Our findings indicate that low expression of classical HLA class I molecules together with lack of immunoproteasome components as well as upregulation of HLA-G may be of key relevance to maintain tolerance in immune privileged tissues.

Enhanced protection of C57 BL/6 vs Balb/c mice to melanoma liver metastasis is mediated by NK cells.

The B16F10 murine melanoma cell line displays a low expression of MHC class I molecules favoring immune evasion and metastases in immunocompetent C57 BL/6 wild-type mice. Here, we generated metastases to the liver, an organ that is skewed towards immune tolerance, by intrasplenic injection of B16F10 cells in syngeneic C57 BL/6 compared to allogeneic Balb/c mice. Surprisingly, Balb/c mice, which usually display a pronounced M2 macrophage and Th2 T cell polarization, were ∼3 times more susceptible to metastasis than C57 BL/6 mice, despite a much higher M1 and Th1 T cell immune response. The anti-metastatic advantage of C57 BL/6 mice could be attributed to a more potent NK-cell mediated cytotoxicity against B16F10 cells. Our findings highlight the role of NK cells in innate anti-tumor immunity in the context of the liver - particularly against highly aggressive MHC I-deficient cancer cells. Moreover, the B16F10 model of melanoma liver metastasis is suited for developing novel therapies targeting innate NK cell related immunity in liver metastases and liver cancer.

MHC class I loaded ligands from breast cancer cell lines: A potential HLA-I-typed antigen collection.

To build a catalog of peptides presented by breast cancer cells, we undertook systematic MHC class I immunoprecipitation followed by elution of MHC class I-loaded peptides in breast cancer cells. We determined the sequence of 3196 MHC class I ligands representing 1921 proteins from a panel of 20 breast cancer cell lines. After removing duplicate peptides, i.e., the same peptide eluted from more than one cell line, the total number of unique peptides was 2740. Of the unique peptides eluted, more than 1750 had been previously identified, and of these, sixteen have been shown to be immunogenic. Importantly, half of these immunogenic peptides were shared between different breast cancer cell lines. MHC class I binding probability was used to plot the distribution of the eluted peptides in accordance with the binding score for each breast cancer cell line. We also determined that the tested breast cancer cells presented 89 mutation-containing peptides and peptides derived from aberrantly translated genes, 7 of which were shared between four or two different cell lines. Overall, the high throughput identification of MHC class I-loaded peptides is an effective strategy for systematic characterization of cancer peptides, and could be employed for design of multi-peptide anticancer vaccines. SIGNIFICANCE: By employing proteomic analyses of eluted peptides from breast cancer cells, the current study has built an initial HLA-I-typed antigen collection for breast cancer research. It was also determined that immunogenic epitopes can be identified using established cell lines and that shared immunogenic peptides can be found in different cancer types such as breast cancer and leukemia. Importantly, out of 3196 eluted peptides that included duplicate peptides in different cells 89 peptides either contained mutation in their sequence or were derived from aberrant translation suggesting that mutation-containing epitopes are on the order of 2-3% in breast cancer cells. Finally, our results suggest that interfering with MHC class I function is one of the mechanisms of how tumor cells escape immune system attack.

Mutanome directed cancer immunotherapy.

Somatic mutations are important drivers of cancer development. Accumulating evidence suggests that a significant subset of mutations result in neo-epitopes recognized by autologous T cells and thus may constitute the Achilles' heel of tumor cells. T cells directed against mutations have been shown to have a key role in clinical efficacy of potent cancer immunotherapy modalities, such as adoptive transfer of autologous tumor infiltrating lymphocytes and immune checkpoint inhibitors. Whereas these findings strengthen the idea of a prominent role of neo-epitopes in tumor rejection, the systematic therapeutic exploitation of mutations was hampered until recently by the uniqueness of the repertoire of mutations ('the mutanome') in every patient's tumor. This review highlights insights into immune recognition of neo-epitopes and novel concepts for comprehensive identification and immunotherapeutic exploitation of individual mutations.

In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.

Next-generation sequencing (NGS) enables high-throughput transcriptome profiling using the RNA-Seq assay, resulting in billions of short sequence reads. Worldwide adoption has been rapid: many laboratories worldwide generate transcriptome sequence reads daily. Here, we describe methods for obtaining a sample's human leukocyte antigen (HLA) class I and II types and HLA expression using standard NGS RNA-Seq sequence reads. We demonstrate the application using our algorithm, seq2HLA, and a publicly available RNA-Seq dataset from the Burkitt lymphoma cell line Raji.

Mutanome Engineered RNA Immunotherapy: Towards Patient-Centered Tumor Vaccination.

Advances in nucleic acid sequencing technologies have revolutionized the field of genomics, allowing the efficient targeting of mutated neoantigens for personalized cancer vaccination. Due to their absence during negative selection of T cells and their lack of expression in healthy tissue, tumor mutations are considered as optimal targets for cancer immunotherapy. Preclinical and early clinical data suggest that synthetic mRNA can serve as potent drug format allowing the cost efficient production of highly efficient vaccines in a timely manner. In this review, we describe a process, which integrates next generation sequencing based cancer mutanome mapping, in silico target selection and prioritization approaches, and mRNA vaccine manufacturing and delivery into a process we refer to as MERIT (mutanome engineered RNA immunotherapy).

TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression.

Human cancer cell lines are an important resource for research and drug development. However, the available annotations of cell lines are sparse, incomplete, and distributed in multiple repositories. Re-analyzing publicly available raw RNA-Seq data, we determined the human leukocyte antigen (HLA) type and abundance, identified expressed viruses and calculated gene expression of 1,082 cancer cell lines. Using the determined HLA types, public databases of cell line mutations, and existing HLA binding prediction algorithms, we predicted antigenic mutations in each cell line. We integrated the results into a comprehensive knowledgebase. Using the Django web framework, we provide an interactive user interface with advanced search capabilities to find and explore cell lines and an application programming interface to extract cell line information. The portal is available at http://celllines.tron-mainz.de.

A catalog of HLA type, HLA expression, and neo-epitope candidates in human cancer cell lines.

Cancer cell lines are a tremendous resource for cancer biology and therapy development. These multipurpose tools are commonly used to examine the genetic origin of cancers, to identify potential novel tumor targets, such as tumor antigens for vaccine devel-opment, and utilized to screen potential therapies in preclinical studies. Mutations, gene expression, and drug sensitivity have been determined for many cell lines using next-generation sequencing (NGS). However, the human leukocyte antigen (HLA) type and HLA expression of tumor cell lines, characterizations necessary for the development of cancer vaccines, have remained largely incomplete and, such information, when available, has been distributed in many publications. Here, we determine the 4-digit HLA type and HLA expression of 167 cancer and 10 non-cancer cell lines from publically available RNA-Seq data. We use standard NGS RNA-Seq short reads from "whole transcriptome" sequencing, map reads to known HLA types, and statistically determine HLA type, heterozygosity, and expression. First, we present previously unreported HLA Class I and II genotypes. Second, we determine HLA expression levels in each cancer cell line, providing insights into HLA downregulation and loss in cancer. Third, using these results, we provide a fundamental cell line "barcode" to track samples and prevent sample annotation swaps and contamination. Fourth, we integrate the cancer cell-line specific HLA types and HLA expression with available cell-line specific mutation information and existing HLA binding prediction algorithms to make a catalog of predicted antigenic mutations in each cell line. The compilation of our results are a fundamental resource for all researchers selecting specific cancer cell lines based on the HLA type and HLA expression, as well as for the development of immunotherapeutic tools for novel cancer treatment modalities.

Mutated tumor alleles are expressed according to their DNA frequency.

The transcription of tumor mutations from DNA into RNA has implications for biology, epigenetics and clinical practice. It is not clear if mutations are in general transcribed and, if so, at what proportion to the wild-type allele. Here, we examined the correlation between DNA mutation allele frequency and RNA mutation allele frequency. We sequenced the exome and transcriptome of tumor cell lines with large copy number variations, identified heterozygous single nucleotide mutations and absolute DNA copy number, and determined the corresponding DNA and RNA mutation allele fraction. We found that 99% of the DNA mutations in expressed genes are expressed as RNA. Moreover, we found a high correlation between the DNA and RNA mutation allele frequency. Exceptions are mutations that cause premature termination codons and therefore activate nonsense-mediated decay. Beyond this, we did not find evidence of any wide-scale mechanism, such as allele-specific epigenetic silencing, preferentially promoting mutated or wild-type alleles. In conclusion, our data strongly suggest that genes are equally transcribed from all alleles, mutated and wild-type, and thus transcribed in proportion to their DNA allele frequency.