Search Results (245)

Background/Objectives: Cadherin-6 (CDH6), also known as K-cadherin, is a type II classic cadherin molecule that plays an important role in the embryonic development of the kidney but has very limited expression in adult tissues. It is overexpressed in several human malignancies, primarily in ovarian cancer, renal cell carcinoma, as well as, less frequently, cholangiocarcinoma, uterine serous carcinoma, glioma, lung, pancreatic and thyroid cancers. The characteristic of limited expression in normal tissues, high expression in tumor tissues, and rapid internalization upon antibody binding makes CDH6 a well-suited antibody-drug conjugate (ADC) target. Methods: We developed a novel CDH6-targeting ADC, CUSP06, consisting of a proprietary humanized antibody selective for CDH6, a protease cleavable linker, and an exatecan payload, with a drug-to-antibody ratio (DAR) of 8. We further characterized the pharmacological activities of CUSP06 in multiple in vitro and in vivo models. Results: CUSP06 was selectively bound to cell surface CDH6 and was efficiently internalized into CDH6-positive ovarian cancer cells, and led to the induction of DNA damage and apoptosis of CDH6-positive cancer cells. CUSP06 exhibited strong antiproliferative activity against several CDH6-positive cancer cell lines and demonstrated strong bystander cell killing effect in the cell mixing experiments in vitro. CUSP06 exhibits excellent in vivo antitumor efficacy in CDH6-high or -low cell line-derived xenograft (CDX) or patient-derived xenograft (PDX) models from human ovarian, renal and uterine cancers, as well as cholangiocarcinoma. CUSP06 demonstrated a favorable safety profile in GLP-compliant toxicology studies in Sprague Dawley rats and cynomolgus monkeys. Conclusions: The preclinical data highlighted the therapeutic potential of CUSP06 in multiple CDH6-positive human cancers. Full article

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

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/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: RAC1 aberrations in head and neck squamous cell carcinoma (HNSCC) remain clinically inactionable today. Methods: Here, we investigated the clinical significance and potential druggability of RAC1 genomic aberrations in HNSCC. Results: Notably, HPV(−)HNSCC patients bearing the unique HNSCC-prevalent RAC1-A159V hotspot mutation, P29S hotspot and G-box domain mutations, and RAC1 copy number increases all displayed dismal overall survival (TCGA-HNSCC). Here, we demonstrated that all five HNSCC patient-relevant RAC1 aberrations tested (A159V and P29S hotspot mutations, K116N, G15S, and N39S) could significantly drive HNSCC tumoroid growth and/invasion, with A159V, P29S, and K116N mutants being the most potent drivers. Interestingly, transcriptomics analyses revealed that RAC1 mutations and copy increase could both drive PI3K pathway activation, with the A159V mutant associated with the prominent intra-tumoral upregulation of phospho-RPS6(Ser235/236) in patient tumors. Importantly, proof-of-principle Rac targeting with EHop-016 resulted in remarkable antitumor activity in vivo against RAC1-A159V-mutated and RAC1-amplified HNSCC patient-derived xenografts (PDXs) and/engineered models. Lastly, melanoma and endometrial xenograft models bearing endogenous RAC1-amplification and RAC1-A159V mutation were also sensitive to EHop-016 targeting. Conclusions: In principle, RAC1 genomic aberrations in HNSCC can be potentially harnessed for precision drugging. Full article

Hepatocellular carcinoma (HCC) cells critically depend on PARP1 and CHK1 activation for survival. Combining the PARP inhibitor (PARPi) olaparib with a CHK1 inhibitor (MK-8776, CHK1i) produced a synergistic effect, reducing cell viability and inducing marked oxidative stress and DNA damage, particularly in the HepG2 cells. This dual treatment significantly increased apoptosis markers, including γH2AX and caspase-3/7 activity. Both HCC cell lines exhibited heightened sensitivity to the combined treatment. The effect of drugs on the expression of proliferation markers in an olaparib-resistant patient-derived xenograft (PDX) model of ovarian cancer was also investigated. Ovarian tumors displayed reduced tissue growth, as reflected by a drop in proliferation marker Ki-67 levels in response to PARPi combined with CHK1i. No changes were observed in corresponding liver tissues using Ki-67 and pCHK staining, which indicates the absence of metastases and a hepatotoxic effect. Thus, our results indicate that the dual inhibition of PARP and CHK1 may prove to be a promising therapeutic approach in the treatment of primary HCC as well as OC tumors without the risk of liver metastases, especially in patients with olaparib-resistant tumor profiles. Full article

Patient-centered precision oncology strives to deliver individualized cancer care. In lung cancer, preclinical models and technological innovations have become critical in advancing this approach. Preclinical models enable deeper insights into tumor biology and enhance the selection of appropriate systemic therapies across chemotherapy, targeted therapies, immunotherapies, antibody–drug conjugates, and emerging investigational treatments. While traditional human lung cancer cell lines offer a basic framework for cancer research, they often lack the tumor heterogeneity and intricate tumor–stromal interactions necessary to accurately predict patient-specific clinical outcomes. Patient-derived xenografts (PDXs), however, retain the original tumor’s histopathology and genetic features, providing a more reliable model for predicting responses to systemic therapeutics, especially molecularly targeted therapies. For studying immunotherapies and antibody–drug conjugates, humanized PDX mouse models, syngeneic mouse models, and genetically engineered mouse models (GEMMs) are increasingly utilized. Despite their value, these in vivo models are costly, labor-intensive, and time-consuming. Recently, patient-derived lung cancer organoids (LCOs) have emerged as a promising in vitro tool for functional precision oncology studies. These LCOs demonstrate high success rates in growth and maintenance, accurately represent the histology and genomics of the original tumors and exhibit strong correlations with clinical treatment responses. Further supported by advancements in imaging, spatial and single-cell transcriptomics, proteomics, and artificial intelligence, these preclinical models are reshaping the landscape of drug development and functional precision lung cancer research. This integrated approach holds the potential to deliver increasingly accurate, personalized treatment strategies, ultimately enhancing patient outcomes in lung cancer. Full article