bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 1742: Molecular characterization of CRPC pathogenesis and development of a novel anti-PSMA-drug conjugated hybrid nanoparticle therapy with reduced cellular toxicity
Authors: Chellappagounder Thangavel
Published: June 2022

Background: Metastatic castration-resistant prostate cancer (mCRPC) is responsible for most of PCa deaths. Androgen deprivation therapy (ADT), taxanes and enzalutamide are the standard care for CRPC and mCRPC. Unfortunately, these approaches often fail to prevent tumor relapse due to at least in part, the inherently low oxygen levels within the prostate tumor environment. In addition to this, lower drug stability and fast drug clearance among ADT patients are the major therapeutic limitations in drug delivery and drug efficacy. Therefore, it is clinically warranted to develop an increased drug stability system to enhance the drug efficacy. Recent developments in drug delivery system including our earlier report, nanoparticle loaded drugs shows greater stability and better drug efficacy with sub-optimal drug concentrations in vitro. It is an essential to develop an ideal CRPC preclinical model system to test the anti-PSMA-drug conjugated hybrid nanoparticle efficacy with high drug stability with limited cellular toxicity.

Materials and Methods: CRPC lines were developed from PSMA proficient LNCaP, LAPC4, C4-2, 22Rv1, and PSMA deficient PC3-ML cells with intermittent hypoxia. CRPC cells were analyzed for proliferation, RB status, AR signaling, migration invasion and drug resistance in both in vitro and in vivo. Further, CRPC bone metastases clinical samples from Thomas Jefferson University Hospital were compared with preclinical CRPC model. Efficient anti-PSMA-drug conjugated hybrid nanoparticle therapy was established.

Results: Hypoxia resistance models show CRPC, RB loss, hormone therapy resistance in vitro and in vivo. Anti-PSMA-drug conjugated hybrid nanoparticle shows enhanced drug stability and drug efficacy in vitro and in vivo. Interestingly we observed fibrosis, immune impairment and inactive RB in bone metastatic CRPC samples correlated with our preclinical studies. Further, our clinical bone metastases samples present osteoblastic, osteolytic and osteoblastic & osteolytic nature. Anti-PSMA conjugated-drug loaded hybrid nanoparticles localized to PSMA specific cells in vitro & in vivo, causing cell cycle arrest. Drug loaded anti-PSMA conjugated hybrid nanoparticles did not cause major toxicities in mice.

Conclusion: Hypoxia resistant mCRPC models are ideal and are comparable with CRPC induced bone metastases in patient’s samples. Drug-loaded anti-PSMA conjugated hybrid nanoparticles targets PSMA specific prostate cancer cells and show enhanced drug stability and drug efficacy in CRPC preclinical model.

Citation Format: Thangavel Chellappagounder. Molecular characterization of CRPC pathogenesis and development of a novel anti-PSMA-drug conjugated hybrid nanoparticle therapy with reduced cellular toxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1742.
Abstract 177: Ex vivo 3D culture of adenoid cystic carcinoma PDX models recapitulate disease biomarkers and predict drug response
Authors: Millard Melissa , DesRochers Teresa M. , Wick Michael J. , Kaufman Jeffrey , Burr Nicole Spardy
Published: June 2022

Adenoid cystic carcinoma (ACC) is a rare, glandular cancer whose incidence rate and limited 2D cell culture capability make it difficult to study primary patient samples. Although well characterized ACC patient-derived xenografts (PDX) have proven to be a useful model to study disease mechanisms and therapeutic sensitives, animal drug studies are relatively low throughput, costly, and take months to accomplish. Ex vivo 3D cell culture can provide a high-throughput, less costly, and significantly faster platform for these drug studies but are hampered by the rarity of tissue. To address this unmet need for models of rare tumor types we developed 3D spheroid (3D-XPDXs™) and microtumor (3D-XPDXmt™) models of ACC using PDX as the primary tissue source. ACC PDX cells readily formed spheroids in our 3D-XPDXs™ platform, remained viable for up to 14 days, and maintained disease-relevant biomarkers such as MYB and c-kit. 3D-XPDXmt™ represent a more complex model of ACC by incorporating extracellular matrix. ACC 3D-XPDXmt™ displayed tumor-like morphologies concordant with the parental tumors and exhibited MYB and c-kit biomarker expression for up to 56 days in culture. Drug response profiling (DRP) was performed using the 3D-XPDXs™ ACC model with KIYATEC’s validated KIYA-PREDICT™ DRP platform. The screening panel consisted of drugs and drug-like compounds currently in use or under investigation for use in ACC, including broad-spectrum chemotherapies and targeted agents. Individualized drug responses were noted for each model as they exhibited differential sensitivities to DNA-damaging agents, microtubule stabilizers, and c-kit targeting kinase inhibitors mirroring the diversity of clinical outcomes. KIYA-PREDICT™ also identified drugs and drug-like compounds that uniformly inhibited viability. This is significant because there is currently no standard of care drugs for ACC, as few, if any have demonstrated homogenous responses in test populations. Monensin has been shown to inhibit activity of the MYB transcription factor, making it an attractive candidate drug for the treatment of ACCs which have a high prevalence of MYB activating alterations. In our study, monensin was effective in all three models with IC50 concentrations in the low micromolar range. These results correlate well with immunohistochemical staining of MYB in ACC 3D-XPDXs™ and 3D-XPDXmt™. Taken together, this data represents a new ex vivo 3D cell culture platform for the study of ACC biology and potential therapies.

Citation Format: Melissa Millard, Teresa M. DesRochers, Michael J. Wick, Jeffrey Kaufman, Nicole Spardy Burr. Ex vivo 3D culture of adenoid cystic carcinoma PDX models recapitulate disease biomarkers and predict drug response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 177.
Abstract 1800: Novel NSDHL inhibitor (Compound 9) exerts anti-proliferative and cytotoxic activity in breast cancer cells
Authors: Yoon So-Hyun , Kim Hoe Suk , Baek Moonjou , Ryu Seungyeon , Lee Sangeun , Lee Han-Byoel , Lee Bong-Jin , Han Wonshik
Published: June 2022

Background: NAD(P) Dependent Steroid Dehydrogenase-Like (NSDHL) is an enzyme involved in post-squalene cholesterol biosynthesis. We recently suggest new insights into the critical role of the NSDHL involved in breast tumor growth and metastasis and its potential for targeted cancer therapy. Compound 9, which is a novel inhibitor of NSDHL, was kindly provided by Dr. Lee B-J in Seoul National University College of Pharmacy. This study aimed to investigate the anti-cancer potential of Compound 9 in breast cancer.

Methods: Therapeutic potential of Compound 9 (10~100 μM) was investigated in several human breast cancer cell lines. Total intracellular cholesterol level was measured using Total Cholesterol Assay Kit. Cell cycle analysis using DNA staining with PI, apoptosis analysis using Annexin V/PI-labeling, and transwell migration assay were performed. The Synergistic anticancer effect of compound-9 and paclitaxel was evaluated by crystal violet assay. Western blot and immunofluorescent staining were assessed for investigating the mechanism by which Compound 9 exerts the anti-cancer effect.

Results: Time-dependent intracellular uptake of Compound 9 by breast cancer cells was observed. Compound 9 induced cytotoxic, anti-proliferative, and apoptotic effects and cell cycle arrest (G0/G1), and suppressed migration activity on diverse breast cancer cell lines in a time- and dose-dependent manner. Total intracellular cholesterol level was reduced by Compound 9. Combination with Compound-9 and Paclitaxel led to synergistic cytotoxicity. Compound-9 increased the autophagy-related proteins (P62, LC3II) but decreased the anti-apoptotic proteins (XIAP, BCL2).

Conclusion: Our data show that Compound 9 exerts strong anti-proliferative and cytotoxic activity in breast cancer cells, suggesting potential additional utility as an anti-cancer drug. Further studies are necessary to validate the potential anti-cancer effect of Compound-9 in breast tumor mice models.

Citation Format: So-Hyun Yoon, Hoe Suk Kim, Moonjou Baek, Seungyeon Ryu, Sangeun Lee, Han-Byoel Lee, Bong-Jin Lee, Wonshik Han. Novel NSDHL inhibitor (Compound 9) exerts anti-proliferative and cytotoxic activity in breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1800.
Abstract 1803: Lethal synthesis: Potent anticancer activity of a glycine uptake inhibitor in tumor cells with mitochondrial methylenetetrahydrofolate dehydrogenase (MTHFD2) knocked down
Authors: Rather Gulam Mohmad , Bertino Joseph R.
Published: June 2022

Methylene tetrahydrofolate dehydrogenase 2 (MTHFD2) is a mitochondrial bifunctional enzyme with dehydrogenase and cyclohydrolase activity. MTHFD2 is expressed in embryonic tissues and not in adult tissues, and by generating formate for purine biosynthesis, enhances proliferation. It is over expressed in many cancers, including breast cancer, and has become an important cancer drug target. Knockdown (KD) of MTHFD2 in breast cancer cell lines MCF7 and T47D, slowed proliferation and resulted in an increase in early apoptosis and a S-phase block. Lack of MTHFD2 causes a dependence on glycine, and in the absence of glycine, proliferation of the MCF-7 cell line with MTHFD2 knocked down was inhibited even further. A known specific glycine transporter type-I (GlyT1) inhibitor, ORG 25935 potently inhibited growth of MCF7 cell with MTHFD2 KD, while it had less of an effect on T47D cells with MTHFD2 KD. Furthermore, both cell lines with MTHFD2 KD showed increase in expression of GlyT1 (SLC6A9) at both mRNA and protein level, using the qPCR and western blotting, respectively. The metabolomics studies showed that intracellular glycine, and NAD+ pools are more reduced in control cells compared to MTHFD2 KD cells on treatment with GlyT1 inhibitor, suggesting that this inhibitor causes glycine depletion in the cells. These data encourage the development of inhibitors of MTHFD2 for use in combination with glycine transport inhibitors.

Citation Format: Gulam Mohmad Rather, Joseph R. Bertino. Lethal synthesis: Potent anticancer activity of a glycine uptake inhibitor in tumor cells with mitochondrial methylenetetrahydrofolate dehydrogenase (MTHFD2) knocked down [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1803.
Abstract 1805: RAB10, a new target to tackle SMAD4 deficient cancers
Authors: Marcireau Christophe , Erasimus Hélène , Kolnik Vanessa , Lacroix Frederic , D’agostino Stephane , Lemaitre Olivier , Rohaut Alexandre , sanchez Isabelle , Sidhu Sukhvinder , Thill Gilbert , Debussche Laurent , Didier Michel
Published: June 2022

TGFb pathway is an important signaling process that regulates the homeostasis of epithelial, stromal or immune cells. Misregulations of this pathway contribute to different pathologies such as cancer, fibrosis, nash or inflammatory diseases. SMAD4 genetic alterations, either via genomic loss or via mutations, can be found in many cancer types. SMAD4 is mutated or deleted in 10-15% of colorectal cancers and in 20-50% of pancreatic cancer. The poorer prognosis of colorectal cancers and pancreatic cancers patients harboring SMAD4 alterations makes SMAD4 deficiency interesting to harness for therapy. Anticancer opportunity created by loss of SMAD4 function/protein could be addressed by identifying synthetic lethal genes that encode for druggable proteins. CRISPR/CAS9 is a revolutionary discovery to produce gene knockout. CRISPR/CAS9 viability screen is a tool of choice to pinpoint new synthetic lethality interactions. In this work, to extend the genetic vulnerabilities of SMAD4-deficient tumors, we conducted a pooled genome-wide loss of function CRISPR/Cas9 screen in sets of 4 non-isogenic colorectal and pancreatic cancers cancer cell lines harboring wild-type and mutant SMAD4. We identified known and novel genetic alterations that make SMAD4-altered colorectal cancers & pancreatic cancers cells vulnerable. We will present the validation of the Ras-related protein Rab-10 (RAB10) as synthetic lethal gene with SMAD4 alteration.

Citation Format: Christophe Marcireau, Hélène Erasimus, Vanessa Kolnik, Frederic Lacroix, Stephane D’agostino, Olivier Lemaitre, Alexandre Rohaut, Isabelle sanchez, Sukhvinder Sidhu, Gilbert Thill, Laurent Debussche, Michel Didier. RAB10, a new target to tackle SMAD4 deficient cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1805.
Abstract 1808: Impact of nanoengineering on redox regulation and CXCR4-mediated homing of mesenchymal stem cells
Authors: Sehgal Drishti , Nethi Susheel Kumar , Merali Carmen , Merali Salim , Panyam Jayanth , Prabha Swayam
Published: June 2022

Mesenchymal stem cells (MSCs) are being investigated for several therapeutic applications, including cancer, inflammation, tissue repair, and transplantation because of their ability to home to injured and inflamed tissues. Despite the large number of preclinical studies investigating engineered MSCs as therapeutic agents and numerous clinical trials investigating MSCs for other therapeutic applications, there have only been a handful of clinical trials investigating MSCs for treating solid tumors, and none have progressed beyond Phase I/II. Inefficient tumor homing ability and a lack of understanding of fundamental mechanisms may contribute to the limited translational success of MSC-based therapies. We hypothesized that nanoengineering MSCs with anticancer drugs induces oxidative stress, and MSCs counteract this stress by activating Nrf2, which increases the expression of various antioxidant proteins, including CXCR4, a key mediator of MSC tumor homing. We performed global label-free, unbiased proteomics on nanoengineered MSCs using modified in-Stage technology. Our studies indicated that MSCs nanoengineered with paclitaxel underwent significant changes in the overall proteome compared to either untreated MSCs or MSCs loaded with blank nanoparticles. Analysis of molecular function profile revealed that loading paclitaxel in MSCs significantly enhanced the expression of proteins involved in the antioxidant and catalytic activity and protein binding. The biological process profile also showed a similar increase in defense response and an increase in metabolic processes. It was further found that MSCs nanoengineered with PTX lead to significant upregulation of nrf2, the master regulator of antioxidant responses, and CXCR4, a direct target of Nrf2 and a key mediator of tumor homing. Also, an increase in CXCR4 expression was directly proportional to paclitaxel loading in cells. These studies suggest nanoengineering of MSCs impacts their biology, which likely contributes to their improved tumor homing capacity in vivo.

Citation Format: Drishti Sehgal, Susheel Kumar Nethi, Carmen Merali, Salim Merali, Jayanth Panyam, Swayam Prabha. Impact of nanoengineering on redox regulation and CXCR4-mediated homing of mesenchymal stem cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1808.
Abstract 1822: Selective inhibition of ZCCHC11/ZCCHC6 TUTases with genetic and pharmacological tools supports a role in glioblastoma cell growth
Authors: Triboulet Robinson , Sadykov Khikmet , Johnson Jessica L. , Snyder Andrew R. , Knutson Sarah K. , Kumar Pavan , Mayo Christopher B. , Hawley Dillon , Madanjian Andrew , Stein Ross L. , Wilson David M. , Harvey Darren M. , Ghosh Shomir , Campbell Robert M.
Published: June 2022

The purpose of the study was to determine if genetic and pharmacological inhibition of terminal uridyltransferases (TUTases) ZCCHC11 and ZCCHC6 could modulate Glioblastoma (GBM) cell growth in vitro. ZCCHC11 (also known as TUT4 and TENT3A) and ZCCHC6 (also known as TUT7 and TENT3B) catalyze uridylation of diverse RNA species. Recent evidence indicates that genetic perturbation of ZCCHC11/6 expression can disrupt cell proliferation of both immortalized and patient-derived primary GBM cell lines (Kim et al., Mol Cell 2020). We confirmed that genetic inhibition of ZCCHC11/6 with siRNA or CRISPR can decrease viability of U-87 MG and A-172 GBM cell lines, and we identified DK-MG as another GBM cell line with sensitivity to ZCCHC11/6 knockdown. Herein, we report the first novel, potent, and selective inhibitor of ZCCHC11/6, TS-1. Biochemically, TS-1 can block ZCCHC11/6-mediated uridylation of an RNA substrate in vitro (IC50 = 0.65 nM for recombinant ZCCHC11 protein; IC50 = 9.6 nM for recombinant ZCCHC6 protein). ZCCHC11/6 inhibitor TS-1 could decrease cell viability in U-87 MG, A-172 and DK-MG cells (cell viability IC50s ranging between 0.7-1.5 μM) and induce apoptosis and cell cycle arrest. A cellular assay detecting uridylation of miR-191 as a marker for ZCCHC11/6 activity was developed and validated. TS-1 strongly decreased uridylation of miR-191 in U-87 MG, A-172 and DK-MG cells (IC50 ranging between 10-40 nM). In contrast, TS-2, a weakly active enantiomer of TS-1 (enzyme IC50 = 0.15 μM and 1.8 μM against ZCCHC11 and ZCCHC6, respectively), had less impact on cell viability, apoptosis, cell cycle and uridylation in cells. In conclusion, we have verified ZCCHC11/6-dependency in a set of GBM cell lines and we have also developed a first-in class potent and selective small molecule that reduces in vitro Glioblastoma cell proliferation through selective inhibition of TUTases activity.

Citation Format: Robinson Triboulet, Khikmet Sadykov, Jessica L. Johnson, Andrew R. Snyder, Sarah K. Knutson, Pavan Kumar, Christopher B. Mayo, Dillon Hawley, Andrew Madanjian, Ross L. Stein, David M. Wilson, Darren M. Harvey, Shomir Ghosh, Robert M. Campbell. Selective inhibition of ZCCHC11/ZCCHC6 TUTases with genetic and pharmacological tools supports a role in glioblastoma cell growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1822.
Abstract 1860: NP-ALT, a liposomal:peptide drug, blocks p27Kip1 phosphorylation to cause cell death in CDK4i-resistant breast cancer
Authors: Blain Stacy Wister , Chand Arianna , Pedraza-Ortiz Lina , VanInwegen Allison , Yan Lingyu , Wu Yun , Chen Grace , Jilishitz Irina
Published: June 2022

Resistance to cyclin D-cdk4/6 inhibitors (CDK4/6i) is frequently caused by compensatory CDK2 activity. We have developed a novel strategy to kill CDK4i resistant tumor cells using a therapeutic liposomal:peptide formulation, NP-ALT, to inhibit the tyrosine phosphorylation of p27Kip1(CDKN1B), which in turn inhibits both CDK4/6 and CDK2. IpY is specific for p27, and this reduces toxicity relative to that seen with the small molecule ATP-competitive CDK4/6i or CDK2i. NP-ALT blocks DNA replication in HR+ breast cancer (BC) cells and mouse models, but unlike CDK4/6i or CDK2i treatment, it induces ROS-dependent necroptosis to kill the tumor cells. This RIPK1/RIPK3-dependent cell death is more specific for HR+ lineages, but the combination of NP-ALT and palbociclib in TNBC cells causes synergy to induce necroptosis. We found that NP-ALT was still able to induce necroptosis in cell lines resistant to palbociclib, including those harboring genetic perturbations detected clinically in patients resistant to palbociclib. HR+ cell lines engineered to overexpress CDK6, FGFR, cyclin E, or cyclin D or ones that have loss of FAT1 or RB were still sensitive to NP-ALT. We tested other CDK2i, including CYC065, a CDK2/9 inhibitor and PF-06873600, a CDK4/6/2 inhibitor, and and found that while they were able to block DNA replication, only NP-ALT was able to induce ROS-dependent death in the resistant lines. We have shown that IpY reduces tumor volumes in resistant in vivo models as well, without causing adverse effects. Thus, NP-ALT and p27 targeting has several differentiators, which might provide clinical advantages: a) its low toxicity due to the tight specificity of the peptide for the p27 target and b) its ability to kill tumor cells as opposed to just causing cytostasis. Concarlo is currently developing NP-ALT into a therapeutic lead for the treatment of drug-resistant breast cancer.

Citation Format: Stacy Wister Blain, Arianna Chand, Lina Pedraza-Ortiz, Allison VanInwegen, Lingyu Yan, Yun Wu, Grace Chen, Irina Jilishitz. NP-ALT, a liposomal:peptide drug, blocks p27Kip1 phosphorylation to cause cell death in CDK4i-resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1860.
Abstract 1863: Mouse strain variations in drug-induced lung stromal responses
Authors: Leon Carlos M. , Gong Zheng , Li Qing , Shi Jiayuan , Zuo Wulin , Hasham Muneer G. , Shultz Lenny , Li Sheng , Ren Guangwen
Published: June 2022

Chemotherapy has significantly improved the survival of cancer patients. However, the vast variation in treatment responses remains a major issue in the clinic. It is imperative to understand the molecular mechanisms underlying treatment failure in specific populations of patients. Genetic diversity has been recognized to mainly account for the differences in drug responses among patients. Yet, it is not feasible to map the responsible genetic variants within millions of single-nucleotide polymorphisms in the human genome in clinical settings with a limited number of subjects and insufficient genomic information. Genetically diverse mice are an ideal tool to overcome the limitations in clinical studies and model drug responses in hosts that require genetic susceptibility and resistance factors. Recent studies have also implicated a critical role for host cells (i.e., the tissue microenvironment) in building a protective “niche” for tumor cells enabling their escape from chemotherapeutic treatments. Notably, the host regenerative response upon chemotherapy “injury,” which is regarded as an intrinsic host mechanism to repair damaged tissues, may be exploited by tumor cells for their local recurrence or distant metastases. In this study, using a lung injury model, we determined how drug-induced lung stromal wound healing responses differed among eight inbred mouse strains (BALB/cJ, NSG, C57BL/6J, CH3/HeJ, CBA/J, SJL/J, A/J, and NOD/ShiLtJ). Upon either cisplatin or doxorubicin stimulation, the wound healing-associated genes Il-6, Spp1, Cxcl1, and Ccl2 were all found upregulated in lung stromal cells but showed a great variation across different strains. Furthermore, we performed single-cell RNA sequencing on the lung stromal cells and immune cells isolated from three selected mouse strains (BALB/cJ, C57BL/6J, and NOD/ShiLtJ) without and with doxorubicin treatment in vivo. The transcriptomic analyses revealed strain-specific and non-specific therapy-elicited gene signatures in different types of lung tissue cells. Collectively, our results signify an association between genetic backgrounds and drug-induced host responses in mice. The next steps of the study aim to understand how genetic diversity would functionally impact drug-induced lung tissue regeneration, lung inflammation, and post-therapy tumor relapse or metastasis in the lung.

Citation Format: Carlos M. Leon, Zheng Gong, Qing Li, Jiayuan Shi, Wulin Zuo, Muneer G. Hasham, Lenny Shultz, Sheng Li, Guangwen Ren. Mouse strain variations in drug-induced lung stromal responses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1863.
Abstract 187: High-throughput screening of cancer spheroids demonstrates sensitivity to combination chemotherapy
Authors: Katz Elad , Deehan Maureen R. , Petty Russell D. , Davies Paul
Published: June 2022

We have designed and manufactured a miniaturized 3D cell culture format called NaviPlate. The NaviPlate contains a novel geometry to support the generation of cancer spheroids for robust and sensitive complex biological assays. Cells added to the NaviPlate spontaneously form spheroids, consistent with the cell line phenotype reported in the literature when using U-bottom multi-well formats. In addition, we have been able to perform assays such as cytotoxicity with a minimum number of 200 cells/well, representing a 5-50-fold improvement on existing 3D cell culture assays.Using the NaviPlate, we examined the response to chemotherapy of four commonly used cancer cell lines: LNCaP, AR mutant lymph-node derived prostate cancer; A549, KRAS mutant/EGFR wt NSCLC; HCT116, KRAS mutant/p53 wt colon cancer; and MDA-MB-231 triple negative breast cancer. First, the lines were exposed to three types of chemotherapy with distinct modes of action: 5-FU (DNA damage), Docetaxel (inhibition of microtubular polymerization) and Flavopiridiol (pan-CDK inhibition). Except for Flavopiridiol in A549 cells, all cell lines were resistant to chemotherapy, when grown in 3D, inside the NaviPlate. Furthermore, we were able to show that this resistance was dependent on the 3D formation of spheroids, as HCT116 cells exposed to chemotherapy before forming spheroids were still sensitive to treatment. Interestingly, in A549 cells, which form less tight spheroids, the effect of 3D clustering was less profound on the response to monotherapy. Lastly, we explored NaviPlate as a platform to identify best chemotherapy combination partners. We combined the three chemotherapies in all cell lines, with most combinations efficiently killing the spheroids. On note, the commonly used combination of 5-FU and Docetaxel had no statistically significant effect on the viability of either A549 or MDA-MB-231 cells.In conclusion, NaviPlate is an easy to use, cancer spheroid platform for the identification of chemotherapy combination partners and thus a useful tool for exploring personalized oncology approaches in the clinic.

Citation Format: Elad Katz, Maureen R. Deehan, Russell D. Petty, Paul Davies. High-throughput screening of cancer spheroids demonstrates sensitivity to combination chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 187.
Abstract 1884: Optical coherence tomography for label-free real 3D imaging of ex-vivo tumor cultures
Authors: Mitsi Maria , Urbane Riccardo , Simon Benjamin , Kuromi Yasushi , Hasebe Ryo , Dhar Sumeer
Published: June 2022

The use of advanced ex-vivo human organotypic cultures is rapidly growing in the field of oncology research and diagnostics, with a focus on patient-derived organoids and tumor tissue specimens cultured in artificial systems capable of replicating tumor development mechanisms. These mechanisms include metastasis, angiogenesis and formation of dysplasia. Our objective is to enhance the label-free imaging and analytical capabilities of these complex tissue samples to enable screening and diagnostics applications.SCREEN Holdings Inc., has developed a unique infrared laser-based optical coherence tomography (OCT) technology enabling non-invasive, label-free, three-dimensional (3D) imaging of tumoroids, epithelial cystic organoids, sprouting endothelial neo-vasculature and metastatic single cells. The imaging is carried out on the 3DProSeed hydrogel plates developed by Ectica Technologies, a glass-bottom 96-well plate featuring pre-casted, synthetic and optically clear hydrogels for ex-vivo tumor cultures.Here we present culture and imaging protocols with the resulting 3D tomographic reconstructions of endothelial sprouting vessels, cystic epithelial organoids of the colon and 3D invasion assays of highly metastatic glioma cells.

Citation Format: Maria Mitsi, Riccardo Urbane, Benjamin Simon, Yasushi Kuromi, Ryo Hasebe, Sumeer Dhar. Optical coherence tomography for label-free real 3D imaging of ex-vivo tumor cultures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1884.
Abstract 1888: Identification and optimization of novel small molecule modulators of immune checkpoint resistance with a unified representation space for genomic and chemical perturbations
Authors: Bhandari Ashish , Cuccarese Michael F. , Fales Kevin , Nadella Kiran , Basso Rebecca Sarto , Beshnova Daria , Donnella Hayley , Shamloo Bahar , Cooper Jacob , Haque Imran , Alfa Ron , Rinaldi Jacob
Published: June 2022

Immune checkpoint inhibitors have revolutionized cancer treatment, producing a durable response consistent with immunologic memory in a subset of patients. However, the majority of patients demonstrate innate or acquired resistance that must be characterized and overcome to induce successful treatment. Advancements in human reverse translation and scaled in vivo CRISPR screening have uncovered novel molecular and genomic correlates of resistance, and promising druggable mechanisms - driven by highly complex interactions between tumor cells and the immune system. It is this core biology that must be disentangled to build the treatment paradigms of the future. Here we demonstrate a technique for massively parallel prioritization of new immuno-oncology hypotheses using industrial-scale experimentation and machine learning. Leveraging high-content imaging data from whole-genome CRISPR knockout and a library of >250,000 compounds, a deep learning model was trained to construct a batch-invariant low dimensional representation of each perturbation. Millions of perturbations in multiple cell types were embedded in a unified representation space that was leveraged to increase the rate of discovery, accelerate reverse translation, yield novel biological insights, and guide the advancement of lead molecular series through SAR. Here we highlight multiple discovery programs driven by inferred relationships between small molecules and gene knockout with translation from inference to in vivo efficacy. Specifically, we prioritize molecules with activity in STK11-deficient tumors and additional immune checkpoint sensitizers.

Citation Format: Ashish Bhandari, Michael F. Cuccarese, Kevin Fales, Kiran Nadella, Rebecca Sarto Basso, Daria Beshnova, Hayley Donnella, Bahar Shamloo, Jacob Cooper, Imran Haque, Ron Alfa, Jacob Rinaldi. Identification and optimization of novel small molecule modulators of immune checkpoint resistance with a unified representation space for genomic and chemical perturbations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1888.
Abstract 1897: Systematic methods to identify cancer vulnerabilities from genome-wide loss-of-function screens: An interactive framework for target discovery
Authors: Krill-Burger John M. , Borah Ashir A. , Paolella Brenton R. , McFarland James M. , Vazquez Francisca
Published: June 2022

Over a thousand genome-scale loss-of-function screens have been performed, as part of efforts such as The Cancer Dependency Map (DepMap), to establish the landscape of genetic dependencies across a diverse set of cancer cell lines. A key challenge to using this resource for therapeutic target discovery is discerning common or tissue-related gene dependencies from those that represent true cancer-specific vulnerabilities. Although many successful cancer-specific targets have been identified by synthetic lethality with patient-prevalent driver mutations, the number of novel synthetic lethals identified as more cancer cell lines are screened has been limited compared to the total number of newly observed selective dependencies. Better understanding of how these selective dependencies are connected to molecular features of the sensitive cell lines could unlock a wealth of potential targets. As part of the DepMap project at the Broad Institute, we created a software pipeline and interactive web-tool for researchers to interrogate the compendium of CRISPR and RNAi screens and systematically rank potential targets by several key factors, most notably selectivity, disease indication, and predictability from multi-omics features (WES, RNAseq, methylation, proteomics). A strength of our framework is the ability to explore the relationships between a dependency and its top predictive features since this could provide insights into the mechanism underlying the cellular dependency and aid in generating therapeutic hypotheses. Additionally, users can perform disease-specific analyses and incorporate annotations for small molecule tractability or drug availability. We anticipate this tool will lower the barrier to systematic genome-wide target discovery using DepMap and provide insights into strategies and best practices for nominating promising targets.

Citation Format: John M. Krill-Burger, Ashir A. Borah, Brenton R. Paolella, James M. McFarland, Francisca Vazquez. Systematic methods to identify cancer vulnerabilities from genome-wide loss-of-function screens: An interactive framework for target discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1897.
Abstract 1934: An artificial intelligence-based framework for BLEACH&STAIN mfIHC facilitates automated prognosis marker assessment in breast cancer
Authors: Mandelkow Tim , Bady Elena , Lurati Magalie C. , Hube-Magg Claudia , Lennartz Maximilian , Sauter Guido , Blessin Niclas C. , Simon Ronald
Published: June 2022

The assessment of prognostic markers in routine clinical practice of breast cancer is currently performed using multi gene RNA panels. However, the unknown proportion of normal breast tissue in relation to malignant breast tissue can reduce the predictive value of such tests. Immunohistochemistry holds the potential for a better assessment of tumors because tumor cells can be separately analyzed. To enable automated prognosis marker detection (i.e. HER2, GATA3, progesterone receptor [PR], estrogen receptor [ER], androgen receptor [AR], TOP2A, Ki-67, TROP2, Mammaglobin), we have developed and validated a framework for automated breast cancer identification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of 12+1 marker BLEACH&STAIN multiplex fluorescence immunohistochemistry staining, in 2004 breast cancers. The optimal distance between Myosin+ basal cells and benign panCK+ benign cells was identified as 31µm and used to exclude benign glands from the analysis combined with and deep learning-based algorithm for benign gland detection. Our deep learning-based framework discriminated normal glands from malignant glands with an area under receiver-operating characteristic curves (AUC) of 0.96 (95% confidence interval [CI], 0.92 to 0.99). The accuracy of the approach was also validated by several well-characterized biological findings, such as the identification of 13% HER2+, 73% PR+/ER+, and 14% triple negative cases in the study cohort as well as a significant higher Fraction of TOP2A in the HER2+ cases as compared to the HER2- cases (p<0.001). Furthermore, the automated assessment of GATA3, PR, ER, TOP2A-LI, Ki-67-LI, TROP2, and Mammaglobin was significantly liked to the tumor grade (p<0.001 each). Furthermore, a high expression level of HER2, GATA3, PR, and ER was associated with a prolonged overall survival (p≥0.002 each). In conclusion, a deep learning-based framework for automated breast cancer identification using BLEACH&STAIN multiplex fluorescence IHC facilitates automated prognosis marker quantification in breast cancer.

Citation Format: Tim Mandelkow, Elena Bady, Magalie C. Lurati, Claudia Hube-Magg, Maximilian Lennartz, Guido Sauter, Niclas C. Blessin, Ronald Simon. An artificial intelligence-based framework for BLEACH&STAIN mfIHC facilitates automated prognosis marker assessment in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1934.
Abstract 1937: DIME-CT: Self-supervised learning for medical image analysis using patch-based embeddings
Authors: Fedden Leon , Zhang Zhenning , Baykaner Khan , Li Qin , Bordeaux Lucas
Published: June 2022

Whether tracking patient progress for clinical decision making, or investigating novel therapies, automated analysis of Computed Tomography (CT) imaging data is essential for the future of digital radiomics. In digital radiomics, as in all medical imaging, well annotated data is scarce, whereas unlabelled images are relatively plentiful. In other fields of image processing and medical imaging, the application of self-supervised learning (SSL) to large quantities of unlabelled data has resulted in great strides forward for fast, scalable, and interpretable image analysis. In this work we present a new approach applying SSL to CT imaging data which allows for: 1) Improved performance on image classification tasks, based on 2) dramatically reduced quantity of annotated CT imaging data, whilst also 3) enabling easy exploration and interpretation of the image regions.

We applied a selection of self-supervised approaches (BYOL, DINO, SimCLR, & inpainting) to CT imaging data. Because the high dimensionality of CT data prevents us from using them directly to out-of the box SSL models, we adopt a 3D patching approach to reduce the dimensionality of the neural net input, and process each patch independently.

We train our self-supervised models on public datasets (DeepLesion, NSCLC), and we specialize these models for tumor classification tasks that we evaluate on AstraZeneca sponsored clinical trials. The specialization is done in two different ways: 1) we use the pre-trained SSL model as an encoder that transforms the images of the clinical study into embeddings, on which we apply supervised classification models; 2) we use transfer learning to fine-tune supervised classification models that take the patches directly as inputs.

We find that self-supervised pre-training significantly improves the accuracy on tumor classification tasks compared against a supervised learning baseline. Additionally, using the SSL embeddings we build an interactive map of CT imaging data enabling quick and intuitive inspection of the relevant regions.

Our findings show that SSL constitutes an important tool for medical imaging analysis. SSL results in models that generalize better, and enable improved downstream interpretability and predictions. Furthermore, well trained SSL models can be re-applied to multiple indications because they are pre-trained on broad and diverse CT imaging data.

Citation Format: Leon Fedden, Zhenning Zhang, Khan Baykaner, Qin Li, Lucas Bordeaux. DIME-CT: Self-supervised learning for medical image analysis using patch-based embeddings [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1937.
Abstract 1941: Accurate pan-cancer tumor purity estimation from gene expression data
Authors: Revkov Egor , Sung Ken W.-K. , Skanderup Anders J.
Published: June 2022

Tumors are complex masses composed of malignant and non-malignant cells. Variation in tumor purity (malignant cell fraction) can both confound integrative analysis and enable studies of tumor heterogeneity. Here we developed PUREE, which uses a weakly supervised learning approach to infer tumor purity from a tumor gene expression profile. PUREE was trained on gene expression data and genomic consensus purity estimates from approximately 8000 solid tumor samples. Using a linear model based on 170 input genes, PUREE predicted purity with high accuracy across distinct solid tumor types and generalized to tumor samples from unseen tumor types. PUREE input genes features were further validated using single-cell RNA-seq data from distinct tumor types. In a comprehensive benchmark, PUREE outperformed all existing transcriptome-based purity estimation approaches. We also show that the accuracy of a pan-cancer model is comparable to models optimized for individual tumor types, highlighting compositional properties of the tumor microenvironment conserved across tumor types. Overall, PUREE is a highly accurate and versatile method for estimating tumor purity and interrogating tumor heterogeneity from bulk tumor gene expression data.

Citation Format: Egor Revkov, Ken W.-K. Sung, Anders J. Skanderup. Accurate pan-cancer tumor purity estimation from gene expression data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1941.
Abstract 1942: Interpretation of machine learning methods for the prediction of breast and prostate cancer risk
Authors: Klie Adam , Talwar James , Pagadala Meghana , Carter Hannah
Published: June 2022

Neural networks are powerful tools for modeling genetic contributions to cancer risk that can theoretically capture nonlinear, epistatic interactions between disease-associated loci in heritable cancers. Recent studies applying neural networks and other machine learning methods to complex trait risk prediction from single nucleotide polymorphism (SNP) array data have shown promise in improving risk stratification. However, current performance gains for neural networks when compared to traditional polygenic risk scoring (PRS) approaches and other nonlinear and linear machine learning methods have been modest. Moreover, there remains substantial debate as to the effect of capturing epistatic interactions between SNPs in risk modeling. Central to the debate has been the difficulty in interpreting the complex, nonlinear mapping learned by neural networks and other nonlinear modeling approaches.

To decipher the importance of capturing nonlinear interactions in cancer risk modeling, we first applied several PRS approaches to the prediction of breast and prostate cancer status for individuals in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) and Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) datasets respectively. Consistent with previous studies of complex disease prediction using machine learning, we noted greater predictive capability upon inclusion of more loci in our modeling but only small performance gains when nonlinearity was captured in both cancer types. We then applied machine learning interpretation methods to derive a score for each variant per method, including several neural network interpretation methods which, to our knowledge, have not been applied in this context. We noted varying degrees of concordance between the scores assigned by each method. Finally, we performed pairwise in silico perturbations on salient features and techniques from network biology to identify epistatic interactions between loci captured by each model. Our work represents a comprehensive study of methods for inferring both variant level and epistatic interaction contributions to cancer risk.

Citation Format: Adam Klie, James Talwar, Meghana Pagadala, Hannah Carter. Interpretation of machine learning methods for the prediction of breast and prostate cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1942.
Abstract 196: Leveraging linked gut microbiome and breast cancer microfluidic chips to study the role of the estrobolome in cancer progression
Authors: Brasino Danielle S. , Speese Sean D. , Emerson Beverly M.
Published: June 2022

Gut microbiota are recognized as an integral part in maintaining health, with disturbances in composition linked to disease states ranging from cancer to depression. Breast cancer patient microbiome analysis has demonstrated a correlation between dysbiosis and disease with proposed mechanisms including immune cell regulation, enhanced inflammatory signaling, and modulation of estrogen metabolism through the estrobolome. Current models lack the ability to study communication in one direction or to modulate single variables such as bacterial species or xenobiotic additions without the use of mouse models which suffer from poor translation and assessment opportunities. We have developed two microfluidic chips, one to model the gut microbiome using oxygen impermeable plastic for maintenance of anaerobic bacteria and another to culture breast cancer spheroids under constant flow. Current work has demonstrated viability and polarity maintenance in chip-cultured spheroids and initial development of polarized villus-like gut epithelium. Using these two chips, we will study the impact of breast cancer associated bacteria capable of estrogen metabolism on breast cancer tumorigenic potential.

Citation Format: Danielle S. Brasino, Sean D. Speese, Beverly M. Emerson. Leveraging linked gut microbiome and breast cancer microfluidic chips to study the role of the estrobolome in cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 196.