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Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development., QC 20230626

Background Adenosine is a metabolite that suppresses antitumor immune response of T and NK cells via extracellular binding to the two subtypes of adenosine-2 receptors, A(2)ARs. While blockade of the A(2A)ARs subtype effectively rescues lymphocyte activity, with four A(2A)AR antagonists currently in anticancer clinical trials, less is known for the therapeutic potential of the other A(2B)AR blockade within cancer immunotherapy. Recent studies suggest the formation of A(2A)AR/A(2B)AR dimers in tissues that coexpress the two receptor subtypes, where the A(2B)AR plays a dominant role, suggesting it as a promising target for cancer immunotherapy. Methods We report the synthesis and functional evaluation of five potent A(2B)AR antagonists and a dual A(2A)AR/A(2B)AR antagonist. The compounds were designed using previous pharmacological data assisted by modeling studies. Synthesis was developed using multicomponent approaches. Flow cytometry was used to evaluate the phenotype of T and NK cells on A(2B)AR antagonist treatment. Functional activity of T and NK cells was tested in patient-derived tumor spheroid models. Results We provide data for six novel small molecules: five A(2B)AR selective antagonists and a dual A(2A)AR/A(2B)AR antagonist. The growth of patient-derived breast cancer spheroids is prevented when treated with A(2B)AR antagonists. To elucidate if this depends on increased lymphocyte activity, immune cells proliferation, and cytokine production, lymphocyte infiltration was evaluated and compared with the potent A(2A)AR antagonist AZD-4635. We find that A(2B)AR antagonists rescue T and NK cell proliferation, IFN gamma and perforin production, and increase tumor infiltrating lymphocytes infiltration into tumor spheroids without altering the expression of adhesion molecules. Conclusions Our results demonstrate that A(2B)AR is a promising target in immunotherapy, identifying ISAM-R56A as the most potent candidate for A(2B)AR blockade. Inhibition of A(2B)AR signal

The human gamma-herpesvirus Epstein-Barr virus (EBV) has been implicated in the pathogenesis of a broad spectrum of lymphoid and epithelial cell malignancies. A characteristic property of the virus is the capacity to establish a non-productive growthpromoting infection in B-lymphocytes. Although the induction of cell proliferation is a key feature in oncogenesis, it is not sufficient for full malignancy. In the work presented in this thesis my colleagues and I have asked whether the virus might contribute to oncogenesis by triggering additional events that are required for tumor progression. Replicative immortality is dependent on the activation of mechanisms that maintain the integrity of telomeres. Malignant cells achieve this by activating telomerase or a recombination-dependent pathway known as alternative lengthening of telomeres (ALT). We observed multiple signs of telomere dysfunction consistent with the activation of ALT in newly EBV infected Blymphocytes. These include accumulation of telomere-associated promyelocytic leukemia nuclear bodies (APBs), telomeric-sister chromatid exchange (T-SCE), and low expression of telomere associated proteins such as TRF1, TRF2, POT1, and ATRX, pointing to telomere de-protection as possible cause of telomere damage. The early phase of EBV induced B-cell immortalization is characterized by the accumulation of DNA damage and activation of a DNA damage response (DDR) that limits the efficiency of growth transformation. By comparing the response of B-lymphocytes infected with EBV or stimulated with a potent Bcell mitogen, we found that significant higher levels of damage occur in EBV infected blasts due to stronger and sustained accumulation of reactive oxygen species (ROS). Quenching of ROS did not affect the kinetics and magnitude of viral gene expression but dramatically decreased the efficiency of B-cell transformation, which correlated with selective downregulation of the viral LMP1 and the phosphorylated form of the cell

Colorectal cancer (CRC) is the third leading cause for cancer deaths, indicating the need for new diagnostic and prognostic biomarkers. The advances in omics technologies and bioinformatics can speed up and improve current biomarker discovery strategies. Machine learning has been integrated for analysis of transcriptomic data for several cancers. However, in addition to improved data-analysis, there is a need to investigate the impact of sex in the biomarker discovery since there are several sex-differences in the incidence, mortality, prognosis and tumor characteristics of CRC. First we investigated if there are any sex-differences in the transcriptome of normal colon and CRC and investigated if there are any sex-differences in the differentially expressed genes between paired-normal and CRC. In an attempt to study sex-specific biomarkers we used TCGA data and performed feature selection with Vita, Boruta and MRMR in combination with machine learning to identify top CRC biomarkers. Interestingly, we found stronger sexdifferences in the normal colon compared to in CRC. Although the sex-differences were stronger in normal colon, sex showed to have a significant impact of the prognostic value of the biomarkers. 13 of the selected features showed a sex-specific prognostic value. The previously proposed prognostic biomarkers ESM1 and GUCA2A showed a male-specific prognostic value whereas CLDN1 was specific for females. Additionally, we found some novel prognostic biomarkers including TSPAN7 (females), SLC25A23 (females) and C2orf88 (males). In conclusion, our data show the importance of sex in the discovery of CRC biomarkers and proposes 13 sex-specific CRC prognostic biomarkers., QC 20201007

QC 20220412

Current methods for epigenomic profiling are limited in the ability to obtain genome wide information with spatial resolution. Here we introduce spatial ATAC, a method that integrates transposase-accessible chromatin profiling in tissue sections with barcoded solid-phase capture to perform spatially resolved epigenomics. We show that spatial ATAC enables the discovery of the regulatory programs underlying spatial gene expression during mouse organogenesis, lineage differentiation and in human pathology., QC 20221129