Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.

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.

CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.

MOTIVATION: Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity. RESULTS: To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE's potential to advance our understanding of genetic alterations and their impact on disease advancement. AVAILABILITY AND IMPLEMENTATION: CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.

Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer.

BACKGROUND: Overexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab. METHODS: This retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS). RESULTS: The analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels. CONCLUSIONS: Our findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.

The Importance of Sex in the Discovery of Colorectal Cancer Prognostic Biomarkers.

Colorectal cancer (CRC) is the third leading cause of cancer deaths. Advances within bioinformatics, such as machine learning, can improve biomarker discovery and ultimately improve CRC survival rates. There are clear sex differences in CRC characteristics, but the impact of sex has not been considered with regards to CRC biomarkers. Our aim here was to investigate sex differences in the transcriptome of a normal colon and CRC, and between paired normal and tumor tissue. Next, we attempted to identify CRC diagnostic and prognostic biomarkers and investigate if they are sex-specific. We collected paired normal and tumor tissue, performed RNA-seq, and applied feature selection in combination with machine learning to identify the top CRC diagnostic biomarkers. We used The Cancer Genome Atlas (TCGA) data to identify sex-specific CRC diagnostic biomarkers and performed an overall survival analysis to identify sex-specific prognostic biomarkers. We found transcriptomic sex differences in both the normal colon tissue and in CRC. Forty-four of the top-ranked biomarkers were sex-specific and 20 biomarkers showed a sex-specific prognostic value. Our data show the importance of sex in the discovery of CRC biomarkers. We propose 20 sex-specific CRC prognostic biomarkers, including ESM1, GUCA2A, and VWA2 for males and CLDN1 and FUT1 for females.

Identification and targeting of selective vulnerability rendered by tamoxifen resistance.

BACKGROUND: The estrogen receptor (ER)-positive breast cancer represents over 80% of all breast cancer cases. Even though adjuvant hormone therapy with tamoxifen (TMX) is saving lives of patients with ER-positive breast cancer, the acquired resistance to TMX anti-estrogen therapy is the main hurdle for successful TMX therapy. Here we address the mechanism for TMX resistance and explore the ways to eradicate TMX-resistant breast cancer in both in vitro and ex vivo experiments. EXPERIMENTAL DESIGN: To identify compounds able to overcome TMX resistance, we used short-term and long-term viability assays in cancer cells in vitro and in patient samples in 3D ex vivo, analysis of gene expression profiles and cell line pharmacology database, shRNA screen, CRISPR-Cas9 genome editing, real-time PCR, immunofluorescent analysis, western blot, measurement of oxidative stress using flow cytometry, and thioredoxin reductase 1 enzymatic activity. RESULTS: Here, for the first time, we provide an ample evidence that a high level of the detoxifying enzyme SULT1A1 confers resistance to TMX therapy in both in vitro and ex vivo models and correlates with TMX resistance in metastatic samples in relapsed patients. Based on the data from different approaches, we identified three anticancer compounds, RITA (Reactivation of p53 and Induction of Tumor cell Apoptosis), aminoflavone (AF), and oncrasin-1 (ONC-1), whose tumor cell inhibition activity is dependent on SULT1A1. We discovered thioredoxin reductase 1 (TrxR1, encoded by TXNRD1) as a target of bio-activated RITA, AF, and ONC-1. SULT1A1 depletion prevented the inhibition of TrxR1, induction of oxidative stress, DNA damage signaling, and apoptosis triggered by the compounds. Notably, RITA efficiently suppressed TMX-unresponsive patient-derived breast cancer cells ex vivo. CONCLUSION: We have identified a mechanism of resistance to TMX via hyperactivated SULT1A1, which renders selective vulnerability to anticancer compounds RITA, AF, and ONC-1, and provide a rationale for a new combination therapy to overcome TMX resistance in breast cancer patients. Our novel findings may provide a strategy to circumvent TMX resistance and suggest that this approach could be developed further for the benefit of relapsed breast cancer patients.

Tumor viruses and replicative immortality--avoiding the telomere hurdle.

Tumor viruses promote cell proliferation in order to gain access to an environment suitable for persistence and replication. The expression of viral products that promote growth transformation is often accompanied by the induction of multiple signs of telomere dysfunction, including telomere shortening, damage of telomeric DNA and chromosome instability. Long-term survival and progression to full malignancy require the bypassing of senescence programs that are triggered by the damaged telomeres. Here we review different strategies by which tumor viruses interfere with telomere homeostasis during cell transformation. This frequently involves the activation of telomerase, which assures both the integrity and functionality of telomeres. In addition, recent evidence suggests that oncogenic viruses may activate a recombination-based mechanism for telomere elongation known as Alternative Lengthening of Telomeres (ALT). This error-prone strategy promotes genomic instability and could play an important role in viral oncogenesis.

Caspase-1 promotes Epstein-Barr virus replication by targeting the large tegument protein deneddylase to the nucleus of productively infected cells.

The large tegument proteins of herpesviruses contain N-terminal cysteine proteases with potent ubiquitin and NEDD8-specific deconjugase activities, but the function of the enzymes during virus replication remains largely unknown. Using as model BPLF1, the homologue encoded by Epstein-Barr virus (EBV), we found that induction of the productive virus cycle does not affect the total level of ubiquitin-conjugation but is accompanied by a BPLF1-dependent decrease of NEDD8-adducts and accumulation of free NEDD8. Expression of BPLF1 promotes cullin degradation and the stabilization of cullin-RING ligases (CRLs) substrates in the nucleus, while cytoplasmic CRLs and their substrates are not affected. The inactivation of nuclear CRLs is reversed by the N-terminus of CAND1, which inhibits the binding of BPLF1 to cullins and prevents efficient viral DNA replication. Targeting of the deneddylase activity to the nucleus is dependent on processing of the catalytic N-terminus by caspase-1. Inhibition of caspase-1 severely impairs viral DNA synthesis and the release of infectious virus, pointing a previously unrecognized role of the cellular response to danger signals triggered by EBV reactivation in promoting virus replication.

Inferring clonal somatic mutations directed by X chromosome inactivation status in single cells.

Analysis of clonal dynamics in human tissues is enabled by somatic genetic variation. Here, we show that analysis of mitochondrial mutations in single cells is dramatically improved in females when using X chromosome inactivation to select informative clonal mutations. Applying this strategy to human peripheral mononuclear blood cells reveals clonal structures within T cells that otherwise are blurred by non-informative mutations, including the separation of gamma-delta T cells, suggesting this approach can be used to decipher clonal dynamics of cells in human tissues.

A phenotypic screening approach to target p60AmotL2-expressing invasive cancer cells.

BACKGROUND: Tumor cells have the ability to invade and form small clusters that protrude into adjacent tissues, a phenomenon that is frequently observed at the periphery of a tumor as it expands into healthy tissues. The presence of these clusters is linked to poor prognosis and has proven challenging to treat using conventional therapies. We previously reported that p60AmotL2 expression is localized to invasive colon and breast cancer cells. In vitro, p60AmotL2 promotes epithelial cell invasion by negatively impacting E-cadherin/AmotL2-related mechanotransduction. METHODS: Using epithelial cells transfected with inducible p60AmotL2, we employed a phenotypic drug screening approach to find compounds that specifically target invasive cells. The phenotypic screen was performed by treating cells for 72 h with a library of compounds with known antitumor activities in a dose-dependent manner. After assessing cell viability using CellTiter-Glo, drug sensitivity scores for each compound were calculated. Candidate hit compounds with a higher drug sensitivity score for p60AmotL2-expressing cells were then validated on lung and colon cell models, both in 2D and in 3D, and on colon cancer patient-derived organoids. Nascent RNA sequencing was performed after BET inhibition to analyse BET-dependent pathways in p60AmotL2-expressing cells. RESULTS: We identified 60 compounds that selectively targeted p60AmotL2-expressing cells. Intriguingly, these compounds were classified into two major categories: Epidermal Growth Factor Receptor (EGFR) inhibitors and Bromodomain and Extra-Terminal motif (BET) inhibitors. The latter consistently demonstrated antitumor activity in human cancer cell models, as well as in organoids derived from colon cancer patients. BET inhibition led to a shift towards the upregulation of pro-apoptotic pathways specifically in p60AmotL2-expressing cells. CONCLUSIONS: BET inhibitors specifically target p60AmotL2-expressing invasive cancer cells, likely by exploiting differences in chromatin accessibility, leading to cell death. Additionally, our findings support the use of this phenotypic strategy to discover novel compounds that can exploit vulnerabilities and specifically target invasive cancer cells.

Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope.

Spatial and genomic heterogeneity of tumors are crucial factors influencing cancer progression, treatment, and survival. However, a technology for direct mapping the clones in the tumor tissue based on somatic point mutations is lacking. Here, we propose Tumoroscope, the first probabilistic model that accurately infers cancer clones and their localization in close to single-cell resolution by integrating pathological images, whole exome sequencing, and spatial transcriptomics data. In contrast to previous methods, Tumoroscope explicitly addresses the problem of deconvoluting the proportions of clones in spatial transcriptomics spots. Applied to a reference prostate cancer dataset and a newly generated breast cancer dataset, Tumoroscope reveals spatial patterns of clone colocalization and mutual exclusion in sub-areas of the tumor tissue. We further infer clone-specific gene expression levels and the most highly expressed genes for each clone. In summary, Tumoroscope enables an integrated study of the spatial, genomic, and phenotypic organization of tumors.

Tumor-associated NK cells drive MDSC-mediated tumor immune tolerance through the IL-6/STAT3 axis.

Apart from their killer identity, natural killer (NK) cells have integral roles in shaping the tumor microenvironment. Through immune gene deconvolution, the present study revealed an interplay between NK cells and myeloid-derived suppressor cells (MDSCs) in nonresponders of immune checkpoint therapy. Given that the mechanisms governing the outcome of NK cell-to-myeloid cell interactions remain largely unknown, we sought to investigate the cross-talk between NK cells and suppressive myeloid cells. Upon contact with tumor-experienced NK cells, monocytes and neutrophils displayed increased expression of MDSC-related suppressive factors along with increased capacities to suppress T cells. These changes were accompanied by impaired antigen presentation by monocytes and increased ER stress response by neutrophils. In a cohort of patients with sarcoma and breast cancer, the production of interleukin-6 (IL-6) by tumor-infiltrating NK cells correlated with S100A8/9 and arginase-1 expression by MDSCs. At the same time, NK cell-derived IL-6 was associated with tumors with higher major histocompatibility complex class I expression, which we further validated with b2m-knockout (KO) tumor mice models. Similarly in syngeneic wild-type and IL-6 KO mouse models, we then demonstrated that the accumulation of MDSCs was influenced by the presence of such regulatory NK cells. Inhibition of the IL-6/signal transducer and activator of transcription 3 (STAT3) axis alleviated suppression of T cell responses, resulting in reduced tumor growth and metastatic dissemination. Together, these results characterize a critical NK cell-mediated mechanism that drives the development of MDSCs during tumor immune escape.

Development and characterization of a recombinant silk network for 3D culture of immortalized and fresh tumor-derived breast cancer cells.

Traditional cancer models rely on 2D cell cultures or 3D spheroids, which fail to recapitulate cell-extracellular matrix (ECM) interactions, a key element of tumor development. Existing hydrogel-based 3D alternatives lack mechanical support for cell growth and often suffer from low reproducibility. Here we report a novel strategy to make 3D models of breast cancer using a tissue-like, well-defined network environment based on recombinant spider silk, functionalized with a cell adhesion motif from fibronectin (FN-silk). With this approach, the canonical cancer cells SK-BR-3, MCF-7, and MDA-MB-231, maintain their characteristic expression of markers (i.e., ERα, HER2, and PGR) while developing distinct morphology. Transcriptomic analyses demonstrate how culture in the FN-silk networks modulates the biological processes of cell adhesion and migration while affecting physiological events involved in malignancy, such as inflammation, remodeling of the ECM, and resistance to anticancer drugs. Finally, we show that integration in FN-silk networks promotes the viability of cells obtained from the superficial scraping of patients' breast tumors.

Solid-phase capture and profiling of open chromatin by spatial ATAC.

Current methods for epigenomic profiling are limited in their ability to obtain genome-wide information with spatial resolution. 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.

Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics.

Functional characterization of the cancer clones can shed light on the evolutionary mechanisms driving cancer's proliferation and relapse mechanisms. Single-cell RNA sequencing data provide grounds for understanding the functional state of cancer as a whole; however, much research remains to identify and reconstruct clonal relationships toward characterizing the changes in functions of individual clones. We present PhylEx that integrates bulk genomics data with co-occurrences of mutations from single-cell RNA sequencing data to reconstruct high-fidelity clonal trees. We evaluate PhylEx on synthetic and well-characterized high-grade serous ovarian cancer cell line datasets. PhylEx outperforms the state-of-the-art methods both when comparing capacity for clonal tree reconstruction and for identifying clones. We analyze high-grade serous ovarian cancer and breast cancer data to show that PhylEx exploits clonal expression profiles beyond what is possible with expression-based clustering methods and clear the way for accurate inference of clonal trees and robust phylo-phenotypic analysis of cancer.

Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics.

The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.

A2B adenosine receptor antagonists rescue lymphocyte activity in adenosine-producing patient-derived cancer models.

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, A2ARs. While blockade of the A2AARs subtype effectively rescues lymphocyte activity, with four A2AAR antagonists currently in anticancer clinical trials, less is known for the therapeutic potential of the other A2BAR blockade within cancer immunotherapy. Recent studies suggest the formation of A2AAR/A2BAR dimers in tissues that coexpress the two receptor subtypes, where the A2BAR plays a dominant role, suggesting it as a promising target for cancer immunotherapy. METHODS: We report the synthesis and functional evaluation of five potent A2BAR antagonists and a dual A2AAR/A2BAR 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 A2BAR 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 A2BAR selective antagonists and a dual A2AAR/A2BAR antagonist. The growth of patient-derived breast cancer spheroids is prevented when treated with A2BAR 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 A2AAR antagonist AZD-4635. We find that A2BAR antagonists rescue T and NK cell proliferation, IFNγ and perforin production, and increase tumor infiltrating lymphocytes infiltration into tumor spheroids without altering the expression of adhesion molecules. CONCLUSIONS: Our results demonstrate that A2BAR is a promising target in immunotherapy, identifying ISAM-R56A as the most potent candidate for A2BAR blockade. Inhibition of A2BAR signaling restores T cell function and proliferation. Furthermore, A2BAR and dual A2AAR/A2BAR antagonists showed similar or better results than A2AAR antagonist AZD-4635 reinforcing the idea of dominant role of the A2BAR in the regulation of the immune system.

CD73 immune checkpoint defines regulatory NK cells within the tumor microenvironment.

High levels of ecto-5'-nucleotidase (CD73) have been implicated in immune suppression and tumor progression, and have also been observed in cancer patients who progress on anti-PD-1 immunotherapy. Although regulatory T cells can express CD73 and inhibit T cell responses via the production of adenosine, less is known about CD73 expression in other immune cell populations. We found that tumor-infiltrating NK cells upregulate CD73 expression and the frequency of these CD73-positive NK cells correlated with larger tumor size in breast cancer patients. In addition, the expression of multiple alternative immune checkpoint receptors including LAG-3, VISTA, PD-1, and PD-L1 was significantly higher in CD73-positive NK cells than in CD73-negative NK cells. Mechanistically, NK cells transport CD73 in intracellular vesicles to the cell surface and the extracellular space via actin polymerization-dependent exocytosis upon engagement of 4-1BBL on tumor cells. These CD73-positive NK cells undergo transcriptional reprogramming and upregulate IL-10 production via STAT3 transcriptional activity, suppressing CD4-positive T cell proliferation and IFN-γ production. Taken together, our results support the notion that tumors can hijack NK cells as a means to escape immunity and that CD73 expression defines an inducible population of NK cells with immunoregulatory properties within the tumor microenvironment.

Thermal Proteome Profiling Identifies Oxidative-Dependent Inhibition of the Transcription of Major Oncogenes as a New Therapeutic Mechanism for Select Anticancer Compounds.

Identification of the molecular mechanism of action (MoA) of bioactive compounds is a crucial step for drug development but remains a challenging task despite recent advances in technology. In this study, we applied multidimensional proteomics, sensitivity correlation analysis, and transcriptomics to identify a common MoA for the anticancer compounds RITA, aminoflavone (AF), and oncrasin-1 (Onc-1). Global thermal proteome profiling revealed that the three compounds target mRNA processing and transcription, thereby attacking a cancer vulnerability, transcriptional addiction. This led to the preferential loss of expression of oncogenes involved in PDGF, EGFR, VEGF, insulin/IGF/MAPKK, FGF, Hedgehog, TGFß, and PI3K signaling pathways. Increased reactive oxygen species level in cancer cells was a prerequisite for targeting the mRNA transcription machinery, thus conferring cancer selectivity to these compounds. Furthermore, DNA repair factors involved in homologous recombination were among the most prominently repressed proteins. In cancer patient samples, RITA, AF, and Onc-1 sensitized to poly(ADP-ribose) polymerase inhibitors both in vitro and ex vivo These findings might pave a way for new synthetic lethal combination therapies.Significance: These findings highlight agents that target transcriptional addiction in cancer cells and suggest combination treatments that target RNA processing and DNA repair pathways simultaneously as effective cancer therapies.