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.

Background Extensive sequencing of tumor tissues has greatly improved our understanding of cancer biology over the past years. The integration of genomic and clinical data is increasingly used to select personalized therapies in dedicated tumor boards (Molecular Tumor Boards) or to identify patients for basket studies. Genomic alterations and clinical information can be stored, integrated and visualized in the open-access resource cBioPortal for Cancer Genomics. cBioPortal can be run as a local instance enabling storage and analysis of patient data in single institutions, in the respect of data privacy. However, uploading clinical input data and genetic aberrations requires the elaboration of multiple data files and specific data formats, which makes it difficult to integrate this system into clinical practice. To solve this problem, we developed cbpManager. Results cbpManager is an R package providing a web-based interactive graphical user interface intended to facilitate the maintenance of mutations data and clinical data, including patient and sample information, as well as timeline data. cbpManager enables a large spectrum of researchers and physicians, regardless of their informatics skills to intuitively create data files ready for upload in cBioPortal for Cancer Genomics on a daily basis or in batch. Due to its modular structure based on R Shiny, further data formats such as copy number and fusion data can be covered in future versions. Further, we provide cbpManager as a containerized solution, enabling a straightforward large-scale deployment in clinical systems and secure access in combination with ShinyProxy. cbpManager is freely available via the Bioconductor project at https://bioconductor.org/packages/cbpManager/ under the AGPL-3 license. It is already used at six University Hospitals in Germany (Mainz, Gießen, Lübeck, Halle, Freiburg, and Marburg). Conclusion In summary, our package cbpManager is currently a unique software solution in the workflow with cBioPortal for Cancer Genomics, to assist the user in the interactive generation and management of study files suited for the later upload in cBioPortal.

Synchronous primary malignancies occur in a small proportion of head and neck squamous cell carcinoma (HNSCC) patients. Here, we analysed three synchronous primaries and a recurrence from one patient by comparing the genomic and transcriptomic profiles among the tumour samples and determining the recurrence origin. We found remarkable levels of heterogeneity among the primary tumours, and through the patterns of shared mutations, we traced the origin of the recurrence. Interestingly, the patient carried germline variants that might have predisposed him to carcinogenesis, together with a history of alcohol and tobacco consumption. The mutational signature analysis confirmed the impact of alcohol exposure, with Signature 16 present in all tumour samples. Characterisation of immune cell infiltration highlighted an immunosuppressive environment in all samples, which exceeded the potential activity of T cells. Studies such as the one described here have important clinical value and contribute to personalised treatment decisions for patients with synchronous primaries and matched recurrences.

Head and neck cancer squamous cell carcinomas (HNSCCs) are heterogeneous in terms of origin and aetiology. In addition, there is uncertainty about the spatiotemporal genetic evolution from initial diagnosis to recurrence/metastasis (R/M) after primary treatments and further disease progression following systemic treatment. Changes in the genetic profile have implications on the selection of appropriate treatments for patients, especially in the era of targeted therapies and immunotherapies. Here, we analysed a cohort of 11 HNSCC patients with metachronous R/M, among whom nine had paired primary and R/M samples suitable for next-generation sequencing (multiple R/M samples collected at different time points were available for some of the patients). At the genomic level, the R/M samples shared a fraction of the somatic single nucleotide variants (SNVs) with the index primary tumours, but they also acquired many additional mutations, while losing only a few others. A similar behaviour was also observed when examining the changes of mutational signatures between primary and R/M samples. Overall, R/M appeared thus more genetically diverse than the respective primary tumours. The transcriptomic analysis showed that R/M samples had lower immune cell infiltration and several genes related to immune response were significantly downregulated compared to the primary samples. Our results underline the importance of analysing multiple samples per patient to obtain a more complete picture of the patient’s tumour and advocates a re-biopsy in the event of R/M and treatment failure, in order to select the most appropriate therapeutic strategy.

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