Search Results (316)

Background: Potent androgen receptor pathway inhibitors induce small cell neuroendocrine prostate cancer (SCNC), a highly aggressive subtype of metastatic androgen deprivation-resistant prostate cancer (ARPC) with limited treatment options and poor survival rates. Patients with metastases in the liver have a poor prognosis relative to those with bone metastases alone. The mechanisms that underlie the different behavior of ARPC in bone vs. liver may involve factors intrinsic to the tumor cell, tumor microenvironment, and/or systemic factors, and identifying these factors is critical to improved diagnosis and treatment of SCNC. Metabolic reprogramming is a fundamental strategy of tumor cells to colonize and proliferate in microenvironments distinct from the primary site. Understanding the metabolic plasticity of cancer cells may reveal novel approaches to imaging and treating metastases more effectively. Methods: Using magnetic resonance (MR) imaging and spectroscopy, we interrogated the physiological and metabolic characteristics of SCNC patient-derived xenografts (PDXs) propagated in the bone and liver, and used correlative biochemical, immunohistochemical, and transcriptomic measures to understand the biological underpinnings of the observed imaging metrics. Results: We found that the influence of the microenvironment on physiologic measures using MRI was variable among PDXs. However, the MR measure of glycolytic capacity in the liver using hyperpolarized ¹³C pyruvic acid recapitulated the enzyme activity (lactate dehydrogenase), cofactor (nicotinamide adenine dinucleotide), and stable isotope measures of fractional enrichment of lactate. While in the bone, the congruence of the glycolytic components was lost and potentially weighted by the interaction of cancer cells with osteoclasts/osteoblasts. Conclusion: While there was little impact of microenvironmental factors on metabolism, the physiological measures (cellularity and perfusion) are highly variable and necessitate the use of combined hyperpolarized ¹³C MRI and multiparametric (anatomic, diffusion-, and perfusion- weighted) ¹H MRI to better characterize pre-treatment tumor characteristics, which will be crucial to evaluate treatment response. Full article

Background: Symbiotic gut microbiota can enhance cancer therapy efficacy, while treatment-induced dysbiosis may reduce effectiveness or increase toxicity. Our preclinical study compared the anticancer effects and impact on fecal microbiota and metabolites of two water-soluble SN-38 derivatives (BN-MePPR and BN-MOA), with those observed after treatment with Irinotecan, and the FOLFOX regimen in NOD scid gamma mice bearing patient-derived colon adenocarcinoma xenografts (CRC PDX). Methods: Five individual experiments with Irinotecan and its derivatives and eight individual experiments with FOLFOX were conducted using eight CRC PDX models. Chemotherapeutics were administered intraperitoneally 4–5 times at 5-day intervals. Fecal samples were collected before and after treatment. Microbiota composition was analyzed by 16S rRNA gene (V3–V4 regions) sequencing. Mass spectrometry was used to quantify short-chain fatty acids (SCFAs) and amino acids (AAs). Results: All treatments significantly inhibited tumor growth versus controls. However, no significant changes were observed in gut microbiota α- and β-diversity between treated and untreated groups. Tumor progression in controls was associated with increased abundance of Marvinbryantia, Lactobacillus, Ruminococcus, and [Eubacterium] nodatum group. FOLFOX-treated mice showed increased Marvinbryantia, Bacteroides, and Candidatus Arthromitus, and decreased Akkermansia. No distinct taxa changes were found in the Irinotecan or derivative groups. SCFA levels remained unchanged across groups, while BN-MePPR, BN-MOA, and Irinotecan all increased AA concentrations. Conclusions: Contrary to earlier toxicological data, these findings indicate a relatively limited impact of the tested chemotherapeutics on the gut microbiome and metabolome, emphasizing the importance of research method selection in preclinical studies. Full article

Pancreatic cancer is the third leading cause of cancer-related death in the US. First-line chemotherapy regimens for pancreatic ductal adenocarcinoma (PDAC) include FOLFIRINOX or gemcitabine (Gem) with or without paclitaxel (Ptx); however, 5-year survival with these regimens remains poor. Previous work has demonstrated protein arginine methyltransferase 5 (PRMT5) to be a promising therapeutic target in combination with Gem for the treatment of PDAC; however, these findings have yet to be confirmed in relevant preclinical models of PDAC. To test the possibility of PRMT5 as a viable therapeutic target, clinically relevant orthotopic and metastatic patient-derived xenograft (PDX) mouse models of PDAC growth were utilized to evaluate the effect of PRMT5 knockout (KO) or pharmacologic inhibition on treatment with Gem alone or Gem with Ptx. Primary endpoints included tumor volume, tumor weight, or metastatic tumor burden as appropriate. The results showed that Gem-treated PRMT5 KO tumors exhibited decreased growth and were smaller in size compared to Gem-treated wild-type (WT) tumors. Similarly, the Gem-treated PRMT5 KO metastatic burden was lower than the Gem-treated WT metastatic burden. The addition of a PRMT5 pharmacologic inhibitor to Gem and Ptx therapy resulted in a lower final tumor weight and fewer metastatic tumors. The depletion of PRMT5 results in increased DNA damage in response to Gem and Ptx treatment. Thus, PRMT5 genetic depletion or inhibition in combination with Gem-based therapy improved the response in primary and metastatic PDAC in clinically relevant mouse models, suggesting that PRMT5 is a viable therapeutic target for combination therapy in PDAC. Full article

We have previously reported on a novel monoclonal antibody (mAb) we designated F5, which was raised against a glycopeptide derived from the tandem repeat (TR) region of Mucin-4 (MUC4), a heavily O-glycosylated protein that is overexpressed in many pancreatic cancer cells. This mAb was highly specific for the MUC4 glycopeptide antigen in glycan microarrays, ELISA and SPR assays, selectively stained tissue derived from advanced-stage tumors, and bound MUC4⁺ tumor cells in flow cytometry assays. The mAb was also unique in that it did not cross-react with other commercial anti-MUC4 mAbs that were raised in a similar but non-glycosylated TR sequence. Here we describe the selective conjugation of a novel near-infrared dye to this mAb and in vivo biodistribution of this labeled mAb to various MUC4-expressing tumors in mice. The labeled mAb were selectively distributed to both cell-derived xenograft (CDX) flank tumors and patient-derived xenograft (PDX) tumors that expressed MUC4 compared to those that were MUC4-negative. Organ distribution analysis showed high uptake in MUC4⁺ relative to MUC4⁻ tumors. These results suggest that mAb F5 may be used to develop MUC4-targeted, passive antibody-based immunotherapies against Pancreatic Ductal Adenocarcinomas (PDACs) which are notorious for being refractory to many chemo- and radiotherapies Full article

Platinum resistance represents an urgent medical need in the management of ovarian cancer. The activity of the combinations of onvansertib, an inhibitor of polo-like kinase 1, with gemcitabine or carboplatin was tested using patient-derived xenografts of high-grade serous ovarian carcinoma resistant to cisplatin (DDP). Two PDX models were selected from our xenobank: one with acquired resistance to DDP (#266R) and the other (#315) with intrinsic DDP resistance. Tumor-bearing mice were randomized to receive vehicle, single onvansertib, gemcitabine and carboplatin, and their combinations. Onvansertib/gemcitabine and onvansertib/carboplatin combinations were well tolerated. In the #266R model, single drug treatments were completely inactive, while the combinations of onvansertib/gemcitabine and onvansertib/carboplatin resulted in a significant increase in survival compared to controls and single drugs (p < 0.001 versus control, onvansertib, gemcitabine and carboplatin). Similar efficacy was observed in the s.c. #315 PDX model; indeed, onvansertib and carboplatin monotherapies were inactive, gemcitabine monotherapy was marginally active, while both combinations were highly active. The molecular mechanism underlying the efficacy of the combinations suggests a higher induction of DNA damage which seems plausible considering that, in both cases, gemcitabine and carboplatin, respectively, interfere with DNA metabolism and induce alkylation damage. The results suggest that the combinations of onvansertib/gemcitabine and onvansertib/carboplatin are safe and were shown to be of therapeutic value in the platinum-resistant setting of ovarian carcinoma, strongly supporting their clinical translatability. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, highlighting the need for a deeper understanding of the genetic mechanisms driving its development and progression. Identifying genetic mutations that affect key molecular pathways is crucial for advancing CRC diagnosis, prognosis, and treatment. Patient-derived xenograft (PDX) models are essential tools in precision medicine and preclinical research, aiding in the development of personalized therapeutic strategies. In this study, a comparative analysis was conducted on the most frequently mutated genes—APC, TP53, KRAS, BRAF, NRAS, and ERBB2—using data from publicly available databases (n = 7894) and models from University Medicine Rostock (n = 139). The aim of this study was to evaluate the accuracy of these models in reflecting the mutational landscape observed in patient-derived samples, with a focus on both individual mutations and co-occurring mutational patterns. Our comparative analysis demonstrated that while the ranking of individual mutations remained consistent, their overall frequencies were slightly lower in the PDX models. Interestingly, we observed a notably higher prevalence of BRAF mutations in the PDX cohort. When examining co-occurring mutations, TP53 and APC mutations—both individually and in combination with other alterations—were the most frequent in both datasets. While the PDX models showed a greater prevalence of single mutations and a slightly higher proportion of tumors without detectable mutations compared to the public dataset, these findings present valuable insights into CRC’s mutational landscape. The discrepancies highlight important considerations, such as selective engraftment bias favoring more aggressive tumors, differences in sample size between the two cohorts, and potential bottleneck effects during PDX engraftment. Understanding these factors can help refine the use of PDX models in CRC research, enhancing their potential for more accurate and relevant applications in precision oncology. Full article

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid progression, high metastatic potential, and limited therapeutic options. Lysine-specific demethylase 1 (LSD1) has been identified as a promising epigenetic target in SCLC. RG6016 (ORY-1001) is a selective LSD1 inhibitor currently under clinical investigation for its antitumor activity. In this study, publicly available RNA-Seq datasets from SCLC patient-derived xenograft (PDX) models treated with RG6016 were reanalyzed using bioinformatic approaches. Differential gene expression analysis was conducted to identify genes responsive to LSD1 inhibition. Candidate genes showing significant downregulation were further evaluated by molecular docking to assess their potential interaction with RG6016. The analysis identified a set of differentially expressed genes following RG6016 treatment, including notable downregulation of MYC, UCHL1, and TSPAN8. In silico molecular docking revealed favorable docking poses between RG6016 and the proteins encoded by these genes, suggesting potential direct or indirect targeting. These findings support a broader mechanism of action for RG6016 beyond its known interaction with LSD1. This study demonstrates that RG6016 may exert its antitumor effects through the modulation of additional molecular targets such as MYC, UCHL1, and TSPAN8 in SCLC. The combined bioinformatic and molecular docking analyses provide new insights into the potential multi-target profile of RG6016 and indicate the need for further experimental validation. Full article

Background/Objectives: Magrolimab (Magro) is a humanized naked anti-CD47 monoclonal antibody that blocks the SIRPα CD47 interaction, allowing macrophages to target and destroy cancer cells. To evaluate its preclinical efficacy in vivo, Magro was tested as a single agent and in combination with conventional chemotherapy drugs, Cytarabine (Ara-C) or Azacitidine (Aza), in three pediatric AML (pAML) patient-derived xenograft (PDX) models—AML006 (KMT2A::MLLT1), AML010 (+10, WT1), and AML013 (KMT2A::MLLT4). Methods: After PDX model establishment, mice were assigned to treatment groups hulgG4 (VC, vehicle control for Magro), Magro, Ara-C + VC, Aza + VC, Ara-C + Magro, and Aza + Magro, and then followed for survival. Mice that met humane euthanasia endpoints and at the culmination of experimental timelines had tissues harvested to measure disease burden. Results: Magro alone significantly improved survival in AML006 (p < 0.0001) and AML013 (p = 0.003) and decreased bone marrow (BM) disease burden in AML006 (p = 0.009) and AML013 (p = 0.002). Ara-C + Magro therapy led to significantly improved survival in all three models and significantly decreased BM disease burden in AML006 (p < 0.0001) and AML013 (p = 0.048). Aza + Magro therapy led to significantly improved survival in AML013 (p = 0.047) and AML010 (p = 0.017) and significantly lower BM disease burden in AML010 (p = 0.001). Conclusions: Interestingly, the two models that demonstrated improvement in survival with Magro harbored KMT2A rearrangements, suggesting a subset of patients that may be more responsive to the effects of CD47 blockade. As this drug is being evaluated for use in other malignancies, future studies may focus on investigating the importance of biomarker-based patient selection. Full article

Background/Objectives: Clear-cell renal cell carcinoma (ccRCC) is a heterogenous disease that can be classified into multiple molecular subtypes with differential prognosis and sensitivities to treatments based on their genomic, transcriptomic, proteomic, and metabolic profiles. Patient-derived xenografts (PDXs) are high-fidelity cancer models because they maintain similar genotypes and immunohistologic phenotypes to the parental tumors and respond to standard-of-care therapies as expected. However, whether the molecular subtypes identified in ccRCC patient samples are preserved in PDX models is not clear. Our objective is to compare the transcriptional and proteomic profiles of our PDX models to those of ccRCC patients and identify both similarities and distinctions between molecular profiles of PDX subtypes and corresponding ccRCC patient subtypes, so that proper PDX subtypes can be used when investigating the corresponding ccRCC patient subtypes. Methods: To match PDXs to the human ccRCC molecular subtypes, we compared the transcriptomic and proteomic profiles of five ccRCC PDX models established in our lab to those of the human ccRCC molecular subtypes reported by our group, as well as other groups, using hierarchical analysis, Principal Component Analysis (PCA), and Permutation Correlation Analysis. The enrichment of key molecular pathways in PDXs and ccRCC subtypes was determined using Gene Set Enrichment Analysis. Results: We found that each PDX resembles one of the molecular subtypes closely at both transcript and protein levels. In addition, PDXs representing different molecular subtypes show unique metabolic characteristics. Moreover, molecular subtypes of PDXs correlated with ccRCC patient subtypes in key pathway activities implicated in ccRCC progression and therapy resistance. Conclusions: Our results suggest that PDX subtypes should be used when investigating the molecular mechanism of cancer progression and therapy resistance for corresponding ccRCC patient subtypes. This “matching” strategy will greatly facilitate the clinical translation of positive findings into the optimal management of ccRCC patients. Full article

Background: Fibroblast growth factor (FGF) signaling plays a crucial role in several cellular functions in cancer cells. Tasurgratinib, formerly known as E7090, is an orally available FGF receptor (FGFR)1–3 selective inhibitor. Here, we present the effects of tasurgratinib on the resistance to CDK4/6 inhibitors and endocrine therapy (ET) in a preclinical model. Methods: Estrogen receptor (ER)⁺ breast cancer (BC) patient-derived xenograft (PDX) models harboring ESR1 wild-type or ESR1 mutation were used as animal models. An in vitro cell proliferation assay of ER⁺ BC cell lines treated with fulvestrant or palbociclib + fulvestrant was conducted in the presence of FGF2 and FGF10, with or without tasurgratinib. Results: Among five ER⁺ BC PDX models, OD-BRE-0438 and OD-BRE-0704 showed higher sensitivities to tasurgratinib with prior palbociclib + fulvestrant than without it. In these models, palbociclib + fulvestrant treatment upregulated the expression of several FGF ligand mRNAs. In vitro, FGF2 and FGF10 decreased the sensitivity to both fulvestrant and palbociclib + fulvestrant, which was restored by co-treatment with tasurgratinib. Consistently, fulvestrant + tasurgratinib and elacestrant + tasurgratinib showed antitumor activity in ER⁺ BC PDX models harboring ESR1 wild-type and ESR1 mutation, respectively. In these models, fulvestrant or elacestrant upregulated the expression of several FGF ligand mRNAs. Conclusions: FGF signaling plays a role in resistance to CDK4/6 inhibitors and ET in ER⁺ BC. Tasurgratinib has the potential to exhibit significant antitumor activity in combination with ET against ER⁺ BC via FGF signaling inhibition. These findings indicate the therapeutic potential of tasurgratinib in treating ER⁺ BC. Full article

Background/Objective: Longitudinal in vivo studies of murine xenograft models are widely utilized in oncology to study cancer biology and develop therapies. Magnetic resonance imaging (MRI) of these tumors is an invaluable tool for monitoring tumor growth and characterizing the tumors as well. Methods: In this work, a pipeline for automating the segmentation of xenografts in mouse models was developed. T₂-weighted (T2-wt) MRI images from mice implanted with six different prostate cancer patient-derived xenografts (PDX) in the kidneys, liver, and tibia were used. The segmentation pipeline included a slice classifier to identify the slices that had tumors and subsequent training and validation using several U-Net-based segmentation architectures. Multiple combinations of the algorithm and training images for different sites were evaluated for inference quality. Results and Conclusions: The slice classifier network achieved 90% accuracy in identifying slices containing tumors. Among the various segmentation architectures tested, the dense residual recurrent U-Net achieved the highest performance in kidney tumors. When evaluated across the kidneys, tibia, and liver, this architecture performed the best when trained on all data as compared to training on only data from a single site (and inferring on a multi-site tumor images), achieving a Dice score of 0.924 across the test set. Full article

Patient-derived xenograft (PDX) models are powerful tools in cancer research, offering an accurate platform for evaluating cancer treatment efficacy and predicting responsiveness. However, these models necessitate surgical techniques for tumor tissue transplantation and face challenges with non-uniform tumor growth among animals. To address these issues, we attempted to develop a new PDX modeling method using high-grade serous ovarian cancer (HGSC), a fatal disease with a 5-year survival rate of 29%, which requires personalized research due to its morphological, genetic, and molecular heterogeneities. In this study, we developed a new patient-derived cancer cell xenograft (PDCX) model with high engraftment efficiency (64%) that utilizes primary cancer cells instead of patient tissues. Primary cancer cells can be stably cryopreserved for extended periods (up to 485 days), and when transplanted into female NSGA mice, they maintain morphological and molecular characteristics without significant genetic differences compared to their original primary tumors. Furthermore, PDCX models can be easily produced using a syringe, allowing for uniform tumor sizes across multiple animals. Additionally, M2 PDCXs exhibited a significantly faster growth rate compared to M2 PDTXs. Consequently, our PDCX model offers a streamlined approach for evaluating personalized cancer treatments with minimal experimental variability. Full article

Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with a poor prognosis and limited effective treatment options. This study investigates the therapeutic potential of Deferasirox (DFO), an iron chelator, in ESCC by targeting TAOK1, an STE20-type kinase implicated in cancer development. We demonstrate that DFO significantly inhibits the proliferation and colony formation of ESCC cells in a dose- and time-dependent manner. Mechanistic investigations reveal that DFO binds directly to TAOK1 and reduces its kinase activity. Proteomics and phosphorylated proteomic sequencing analysis further reveal that TAOK1 knocking down dramatically increased p53-mediated apoptosis. Moreover, the inhibition of TAOK1 by DFO or lenti-virus infection induces apoptosis in ESCC cells, as evidenced by the increased expression of p53, p-p53 (S15), p-p53 (S46), Puma, Noxa, and Bax, and the decreased expression of Bcl-2. Furthermore, in vivo studies using patient-derived xenograft (PDX) mouse models show that DFO treatment significantly reduces tumor volume without observable toxicity. Histological and immunohistochemical analyses confirm the down-regulation of TAOK1 and Ki-67, and the up-regulation of p53 expression in DFO-treated tumors. Our findings suggest that DFO exerts its antitumor effects in ESCC by targeting TAOK1, providing a potential therapeutic strategy for ESCC patients. Full article

Complex RNA-seq signatures involving the transcription factors ASCL1, NEUROD1, and POU2F3 classify Small Cell Lung Cancer (SCLC) into four subtypes: SCLC-A, SCLC-N, SCLC-P, and SCLC-I (triple negative or inflamed). Preliminary studies suggest that identifying these subtypes can guide targeted therapies and potentially improve outcomes. This study aims to evaluate whether the expression levels of these three key transcription factors can effectively classify SCLC subtypes, comparable to the use of individual antibodies in immunohistochemical (IHC) analysis of formalin-fixed, paraffin-embedded (FFPE) tumor samples. We analyzed preclinical models of increasing complexity, including eleven human and five mouse SCLC cell lines, six patient-derived xenografts (PDXs), and two circulating tumor cell (CTC)-derived xenografts (CDXs) generated in our laboratory. RT-qPCR conditions were established to detect the expression levels of ASCL1, NEUROD1, and POU2F3. Additionally, protein-level analysis was performed using Western blot for cell lines and IHC for FFPE samples of PDX and CDX tumors, following our experience with patient tumor samples from the CANTABRICO trial (NCT04712903). We found that the analyzed SCLC cell line models predominantly expressed ASCL1, NEUROD1, and POU2F3, or showed no expression, as identified by RT-qPCR, consistently matching the previously assigned subtypes for each cell line. The classification of PDX and CDX models demonstrated consistency between RT-qPCR and IHC analyses of the transcription factors. Our results show that single-gene analysis by RT-qPCR from FFPE-extracted RNA simplifies SCLC subtype classification. This approach provides a cost-effective alternative to IHC staining or expensive multi-gene RNA sequencing panels, making SCLC subtyping more accessible for both preclinical research and clinical applications. Full article

Objective: To investigate the preclinical efficacy and identify predictive biomarkers of polo-like kinase 1 (PLK1) inhibitors in small cell lung cancer (SCLC) models. Methods: We tested the cytotoxicity of selective PLK1 inhibitors (rigosertib, volasertib, and onvansertib) in a panel of SCLC cell lines. We confirmed the therapeutic efficacy of subcutaneous xenografts of representative cell lines and in four patient-derived xenograft models generated from patients with platinum-sensitive and platinum-resistant SCLC. We employed an integrated analysis of genomic and transcriptomic sequencing data to identify potential biomarkers of the activity and mechanisms of resistance in laboratory-derived resistance models. Results: Volasertib, rigosertib, and onvansertib showed strong in vitro cytotoxicity at nanomolar concentrations in human SCLC cell lines. Rigosertib, volasertib, and onvansertib showed equivalent efficacy to that of standard care agents (irinotecan and cisplatin) in vivo with significant growth inhibition superior to cisplatin in PDX models of platinum-sensitive and platinum-resistant SCLC. There was an association between YAP1 expression and disruptive or inactivation TP53 gene mutations, with greater efficacy of PLK1 inhibitors. Comparison of lab-derived onvansertib-resistant H526 cells to parental cells revealed differential gene expression with upregulation of NAP1L3, CYP7B1, AKAP7, and FOXG1 and downregulation of RPS4Y1, KDM5D, USP9Y, and EIF1AY highlighting the potential mechanisms of resistance in the clinical setting. Conclusions: We established the efficacy of PLK1 inhibitors in vitro and in vivo using PDX models of platinum-sensitive and resistant relapsed SCLC. An ongoing phase II trial is currently testing the efficacy of onvansertib in patients with SCLC (NCT05450965). Full article