A precision oncology-focused deep learning framework for personalized selection of cancer therapy.

Precision oncology matches tumors to targeted therapies based on the presence of actionable molecular alterations. However, most tumors lack actionable alterations, restricting treatment options to cytotoxic chemotherapies for which few data-driven prioritization strategies currently exist. Here, we report an integrated computational/experimental treatment selection approach applicable for both chemotherapies and targeted agents irrespective of actionable alterations.

Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses.

Combination chemotherapy remains essential for clinical management of triple-negative breast cancer (TNBC). Consequently, responses to individual agents cannot be easily delineated at the single patient level, even though some patients might not require all drugs in the combination. Herein, we conduct multi-omic analyses of orthotopic TNBC patient-derived xenografts (PDXs) treated with single agent carboplatin, docetaxel, or the combination.

UBA1 inhibition sensitizes cancer cells to PARP inhibitors.

Therapeutic strategies targeting the DNA damage response, such as poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi), have revolutionized cancer treatment in tumors deficient in homologous recombination (HR). However, overcoming innate and acquired resistance to PARPi remains a significant challenge. Here, we employ a genome-wide CRISPR knockout screen and discover that the depletion of ubiquitin-activating enzyme E1 (UBA1) enhances sensitivity to PARPi in HR-proficient ovarian cancer cells.

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis.

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response.

Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations.

Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and assessing a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

A novel treatment strategy utilizing panobinostat for high-risk and treatment-refractory hepatoblastoma.

Background & Aims: Patients with metastatic, treatment-refractory, and relapsed hepatoblastoma (HB) have survival rates of less than 50% due to limited treatment options. To develop new therapeutic strategies for these patients, our laboratory has developed a preclinical testing pipeline. Given that histone deacetylase (HDAC) inhibition has been proposed for HB, we hypothesized that we could find an effective combination treatment strategy utilizing HDAC inhibition.

The Power and Promise of Patient-Derived Xenografts of Human Breast Cancer.

In 2016, a group of researchers engaged in the development of patient-derived xenografts (PDXs) of human breast cancer provided a comprehensive review of the state of the field. In that review, they summarized the clinical problem that PDXs might address, the technical approaches to their generation (including a discussion of host animals and transplant conditions tested), and presented transplantation success (take) rates across groups and across transplantation conditions. At the time, there were just over 500 unique PDX models created by these investigators representing all three clinically defined subtypes (ER, HER2, and TNBC).

The interferon/STAT1 signaling axis is a common feature of tumor-initiating cells in breast cancer.

Unlabelled: A tumor cell subpopulation of tumor-initiating cells (TIC), or "cancer stem cells", are associated with therapeutic resistance, as well as both local and distant recurrence. Enriched populations of TIC are identified by markers including aldehyde dehydrogenase (ALDH1) activity, the cell surface marker combination CD44 /CD24 , or fluorescent reporters for signaling pathways that regulate TIC function. We showed previously that S ignal T ransducer and A ctivator of T ranscription (STAT)-mediated transcription allows enrichment for TIC in claudin-low models of human triple-negative breast cancer using a STAT-responsive reporter.

Deconvolution of cancer cell states by the XDec-SM method.

Proper characterization of cancer cell states within the tumor microenvironment is a key to accurately identifying matching experimental models and the development of precision therapies. To reconstruct this information from bulk RNA-seq profiles, we developed the XDec Simplex Mapping (XDec-SM) reference-optional deconvolution method that maps tumors and the states of constituent cells onto a biologically interpretable low-dimensional space. The method identifies gene sets informative for deconvolution from relevant single-cell profiling data when such profiles are available.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials.

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species.

An Online Repository for Pre-Clinical Imaging Protocols (PIPs).

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis.

Kinome Reprogramming Is a Targetable Vulnerability in ESR1 Fusion-Driven Breast Cancer.

Unlabelled: Transcriptionally active ESR1 fusions (ESR1-TAF) are a potent cause of breast cancer endocrine therapy (ET) resistance. ESR1-TAFs are not directly druggable because the C-terminal estrogen/anti-estrogen-binding domain is replaced with translocated in-frame partner gene sequences that confer constitutive transactivation. To discover alternative treatments, a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) was deployed to identify druggable kinases that are upregulated by diverse ESR1-TAFs.

RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer.

Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor-negative, ER ) from four independent cohorts. RANK protein expression was more frequent in ER tumors, where it associated with poor outcome and poor response to chemotherapy.

Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom.

Relevant to co-clinical trials, the goal of this work was to assess repeatability, reproducibility, and bias of the apparent diffusion coefficient (ADC) for preclinical MRIs using standardized procedures for comparison to performance of clinical MRIs. A temperature-controlled phantom provided an absolute reference standard to measure spatial uniformity of these performance metrics. Seven institutions participated in the study, wherein diffusion-weighted imaging (DWI) data were acquired over multiple days on 10 preclinical scanners, from 3 vendors, at 6 field strengths.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach.

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response.

Immunologically "cold" triple negative breast cancers engraft at a higher rate in patient derived xenografts.

TNBC is a heterogeneous subtype of breast cancer, and only a subset of TNBC can be established as PDXs. Here, we show that there is an engraftment bias toward TNBC with low levels of immune cell infiltration. Additionally, TNBC that failed to engraft show gene expression consistent with a cancer-promoting immunological state, leading us to hypothesize that the immunological state of the tumor and possibly the state of the immune system of the host may be essential for engraftment.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Unlabelled: Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components.

Genomic and epigenomic alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas.

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with promoter methylation (meth) respond more poorly to alkylating agents compared to those bearing mutations in and (mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines.