More Like this

1. Integrated human organ-on-a-chip model for predictive studies of anti-tumor drug efficacy and cardiac safety

   https://doi.org/10.1039/d0lc00424c  

   Chramiec, Alan ; Teles, Diogo ; Yeager, Keith ; Marturano-Kruik, Alessandro ; Pak, Joseph ; Chen, Timothy ; Hao, Luke ; Wang, Miranda ; Lock, Roberta ; Tavakol, Daniel Naveed ; et al ( November 2020 , Lab on a Chip)

   Traditional drug screening models are often unable to faithfully recapitulate human physiology in health and disease, motivating the development of microfluidic organs-on-a-chip (OOC) platforms that can mimic many aspects of human physiology and in the process alleviate many of the discrepancies between preclinical studies and clinical trials outcomes. Linsitinib, a novel anti-cancer drug, showed promising results in pre-clinical models of Ewing Sarcoma (ES), where it suppressed tumor growth. However, a Phase II clinical trial in several European centers with patients showed relapsed and/or refractory ES. We report an integrated, open setting, imaging and sampling accessible, polysulfone-based platform, featuring minimal hydrophobic compound binding. Two bioengineered human tissues – bone ES tumor and heart muscle – were cultured either in isolation or in the integrated platform and subjected to a clinically used linsitinib dosage. The measured anti-tumor efficacy and cardiotoxicity were compared with the results observed in the clinical trial. Only the engineered tumor tissues, and not monolayers, recapitulated the bone microenvironment pathways targeted by linsitinib, and the clinically-relevant differences in drug responses between non-metastatic and metastatic ES tumors. The responses of non-metastatic ES tumor tissues and heart muscle to linsitinib were much closer to those observed in the clinical trial for tissues cultured in an integrated setting than for tissues cultured in isolation. Drug treatment of isolated tissues resulted in significant decreases in tumor viability and cardiac function. Meanwhile, drug treatment in an integrated setting showed poor tumor response and less cardiotoxicity, which matched the results of the clinical trial. Overall, the integration of engineered human tumor and cardiac tissues in the integrated platform improved the predictive accuracy for both the direct and off-target effects of linsitinib. The proposed approach could be readily extended to other drugs and tissue systems. 

   more » « less
2. PDJ amplicon in triple negative breast cancer

   https://doi.org/10.1038/s41598-023-27887-8  

   Roesler, Alexander S. ; Malasi, Smriti ; Koslosky, Lori ; Hartmayer, Peter ; Naab, Tammey J. ; Carter, Jodi M. ; Zahrieh, David ; Hillman, David ; Leon-Ferre, Roberto A. ; Couch, Fergus J. ; et al ( December 2023 , Scientific Reports)

   Abstract Amplification of chromosome 9p24.1 targeting PD-L1 , PD-L2 , and JAK2 (PDJ amplicon) is present in subsets of triple negative breast cancers (TNBCs) and is associated with poor clinical outcomes. However, the prevalence of PDJ+ TNBCs varies extensively across studies applying different methods for interrogating samples of interest. To rigorously assess the prevalence of PDJ amplicons in TNBC, its prognostic value and whether it is enriched by chemotherapy, we interrogated 360 TNBC samples including 74 surgical resections from patients treated in the neoadjuvant setting, and tissue microarrays (TMAs) with 31 cases from African American women and 255 resected non-metastatic cases, with a 3 color fluorescence in situ hybridization (FISH) assay targeting the 9p24.1 PDJ amplicon, 9q24.3, and 9q34.1. Samples with mean PDJ signal of > 4.5 copies, and ratios of PDJ/9q24 ≥ 2 and/or PDJ/9q34.1 ≥ 2 were called amplified (PDJ+). Correlative analyses included the association of tumor infiltrating lymphocytes (TILs) with PDJ amplicons in TNBCs. In addition, we investigated intratumor copy number of PDJ amplicons in PDJ+ and PDJ− TNBCs. Matched pre- and post-neoadjuvant treatment biopsies were available from patients (n = 6) to evaluate the effects of therapy on PDJ status. Our study provides a rigorous analysis of the prevalence, distribution, and clinical correlatives of the PDJ amplicon in TNBC. 

   more » « less
3. A nanoengineered topical transmucosal cisplatin delivery system induces anti-tumor response in animal models and patients with oral cancer

   https://doi.org/10.1038/s41467-022-31859-3  

   Goldberg, Manijeh ; Manzi, Aaron ; Birdi, Amritpreet ; Laporte, Brandon ; Conway, Peter ; Cantin, Stefanie ; Mishra, Vasudha ; Singh, Alka ; Pearson, Alexander T. ; Goldberg, Eric R. ; et al ( August 2022 , Nature Communications)

   Despite therapeutic advancements, oral cavity squamous cell carcinoma (OCSCC) remains a difficult disease to treat. Systemic platinum-based chemotherapy often leads to dose-limiting toxicity (DLT), affecting quality of life. PRV111 is a nanotechnology-based system for local delivery of cisplatin loaded chitosan particles, that penetrate tumor tissue and lymphatic channels while avoiding systemic circulation and toxicity. Here we evaluate PRV111 using animal models of oral cancer, followed by a clinical trial in patients with OCSCC. In vivo, PRV111 results in elevated cisplatin retention in tumors and negligible systemic levels, compared to the intravenous, intraperitoneal or intratumoral delivery. Furthermore, PRV111 produces robust anti-tumor responses in subcutaneous and orthotopic cancer models and results in complete regression of carcinogen-induced premalignant lesions. In a phase 1/2, open-label, single-arm trial (NCT03502148), primary endpoints of efficacy (≥30% tumor volume reduction) and safety (incidence of DLTs) of neoadjuvant PRV111 were reached, with 69% tumor reduction in ~7 days and over 87% response rate. Secondary endpoints (cisplatin biodistribution, loco-regional control, and technical success) were achieved. No DLTs or drug-related serious adverse events were reported. No locoregional recurrences were evident in 6 months. Integration of PRV111 with current standard of care may improve health outcomes and survival of patients with OCSCC.

    

   more » « less
4. Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy

   https://doi.org/10.3390/cancers11050714  

   Soundararajan, Rama ; Fradette, Jared ; Konen, Jessica ; Moulder, Stacy ; Zhang, Xiang ; Gibbons, Don ; Varadarajan, Navin ; Wistuba, Ignacio ; Tripathy, Debasish ; Bernatchez, Chantale ; et al ( May 2019 , Cancers)

   Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors. 

   more » « less
5. A spatial attention guided deep learning system for prediction of pathological complete response using breast cancer histopathology images

   https://doi.org/10.1093/bioinformatics/btac558  

   Duanmu, Hongyi ; Bhattarai, Shristi ; Li, Hongxiao ; Shi, Zhan ; Wang, Fusheng ; Teodoro, George ; Gogineni, Keerthi ; Subhedar, Preeti ; Kiraz, Umay ; Janssen, Emiel A. M. ; et al ( August 2022 , Bioinformatics)

   Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of overall survival. In this work, we propose a deep learning system to predict pCR to NAC based on serial pathology images stained with hematoxylin and eosin and two immunohistochemical biomarkers (Ki67 and PHH3). To support human prior domain knowledge-based guidance and enhance interpretability of the deep learning system, we introduce a human knowledge-derived spatial attention mechanism to inform deep learning models of informative tissue areas of interest. For each patient, three serial breast tumor tissue sections from biopsy blocks were sectioned, stained in three different stains and integrated. The resulting comprehensive attention information from the image triplets is used to guide our prediction system for prognostic tissue regions.

   The experimental dataset consists of 26 419 pathology image patches of 1000×1000 pixels from 73 TNBC patients treated with NAC. Image patches from randomly selected 43 patients are used as a training dataset and images patches from the rest 30 are used as a testing dataset. By the maximum voting from patch-level results, our proposed model achieves a 93% patient-level accuracy, outperforming baselines and other state-of-the-art systems, suggesting its high potential for clinical decision making.

   The codes, the documentation and example data are available on an open source at: https://github.com/jkonglab/PCR_Prediction_Serial_WSIs_biomarkers

   Supplementary data are available at Bioinformatics online.

    

   more » « less