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At least 19 recordsLinked to original sources
PubMed2025

Targeting RAD52 overcomes PARP inhibitor resistance in preclinical Brca2-deficient ovarian cancer model.

BRCA-mutated ovarian cancer commonly develops resistance to poly (ADP-ribose) polymerase (PARP) inhibitors. Here, we investigated the DNA repair protein RAD52 as a potential target to overcome resistance. In analysis of The Cancer Genome Atlas datasets and immunohistochemistry of tissue microarrays, elevated RAD52 expression correlated with poor overall survival in patients with high-grade serous ovarian cancers. We tested two PARP inhibitor-resistant Brca2-deficient mouse ovarian cancer models, ID8-OR and HGS2-OR. HGS2-OR cells had higher RAD52 expression than parental lines. Rad52 knockout or knockdown restored PARP inhibitor sensitivity in both models. In syngeneic mice, ID8-OR cells in which Rad52 was knocked out yielded lower tumor burden and longer overall survival than control cells. Rad52 depletion impaired single-strand annealing and homologous recombination and led to accumulation of DNA double-strand breaks after PARP inhibitor treatment. RNA sequencing demonstrated that PARP inhibitor treatment induced Polq expression in Brca2- and Rad52-deficient cells, suggesting a switch to microhomology-mediated end joining. Finally, the RAD52 inhibitor D-I03 synergized with a PARP inhibitor to reduce cell viability and tumor burden and prolong survival. Collectively, our findings establish RAD52 as a promising therapeutic target to overcome PARP inhibitor resistance in BRCA2-mutated ovarian cancer and offer mechanistic insights to inform future clinical strategies.

Journal Article↗
PubMed2025

Rat somatic genome editing enables ER+ breast cancer modeling.

Genetically engineered mouse models have advanced cancer research but often fail to capture key features of certain human tumors. Rats, with distinct physiology and tumor biology, offer a powerful alternative, yet their use has been constrained by technical barriers to genome editing. Here, we report efficient somatic genome editing in rats, enabling both Indel and substitution mutations. We then apply this approach to model estrogen receptor (ER)-positive breast cancer, which accounts for ~70% of human cases but remains poorly represented in mice. The resulting rat tumors reproduce hallmarks of human ER+ breast cancer, including ductal histology, hormone responsiveness, and immune-microenvironmental features. By contrast, identical genetic alterations in mice failed to yield ER+ tumors, underscoring critical species differences in tumorigenesis. Together, this work establishes a versatile platform for rapid generation of clinically relevant rat tumor models, opening new avenues to dissect tumor biology, therapeutic response, and immune interactions in previously inaccessible cancer subtypes.

Journal Article↗
PubMed2025

Integrating network pharmacology and experimental validation to uncover the synergistic effects of Huangqi ()-Ezhu () with 5-fluorouracil in colorectal cancer models.

OBJECTIVE: To evaluate the effects of Huangqi (Radix Astragali Mongolici)-Ezhu (Rhizoma Curcumae Phaeocaulis) (HQEZ) on colorectal cancer therapies and to elucidate the potential mechanisms of HQEZ, especially in combination with 5-Fluorouracil (5-FU). METHODS: The anti-tumor effects of HQEZ were evaluated in colorectal cancer models both in vivo and in vitro. The network pharmacological assay was used to investigate potential mechanisms of HQEZ. Potential target genes were selected by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction network (PPI) and molecular docking. Within key targets, potential targets related to drug sensitivity, especially the sensitivity to 5-FU, were evaluated in HCT116 in vitro by immunofluorescence, quantitative real-time polymerase chain reaction (qPCR) and Western-blot. Then, changes in potential targets were assessed in tumors from tumor-bearing mice and the expression of these targets was also evaluated in colorectal cancer (COAD) patients from the Cancer Genome Atlas Program (TCGA) database. RESULTS: HQEZ significantly enhanced the anti-tumor activity of 5-FU in vivo and inhibit the growth of HCT116 in vitro. By network pharmacological analysis, key targets, such as protein kinase B (AKT1), epidermal growth factor receptor (EGFR), adenosine triphosphate (ATP) binding cassette subfamily B member 1 (ABCB1, also named multidrug resistance protein 1, MDR1), ATP binding cassette subfamily G member 2 (ABCG2), thymidylate synthetase (TYMS, also named TS), prostaglandin-endoperoxide synthase 2 (PTGS2), matrix metallopeptidase 2 (MMP2), MMP9, toll like receptor 4 (TLR4), TLR9 and dihydropyrimidine dehydrogenase (DPYD), were identified. Additionally, 4 potential core active ingredients (Folate, Curcumin, quercetin and kaempferol) were identified to be important for the treatment of colorectal cancer with HQEZ. In key targets, chemoresistance related targets were validated to be affected by HQEZ. Furthermore, 5-FU sensitivity related targets, including MDR1, TS, EGFR, ribonucleotide reductase catalytic subunit M1, Breast and Ovarian Cancer Susceptibility Protein 1 (BRCA1) and mutl homolog 1 were also significantly reduced by HQEZ both in vitro and in vivo. Finally, these validated key targets and 5-FU sensitivity related targets were demonstrated to be up-regulated in COAD patients based on TCGA database. CONCLUSION: HQEZ has synergistic effects on the anti-tumor activity of 5-FU in the treatment of colorectal cancer both in vivo and in vitro. The beneficial effect of HQEZ results from the inhibition of the drug sensitivity targets associated with 5-FU. The combination therapy of HQEZ with 5-FU or other chemotherapeutic drugs will also improve the anti-tumor efficacy of chemotherapy.

Humans↗
PubMed1977

Improvement of pancreatic cancer model by modified treatment with N-nitroso-bis (2-oxopropyl) amine.

Comparative studies were conducted in 2 groups of Syrian golden hamsters treated with N-nitroso-bis (2-oxopropyl)amine (BOP) weekly for life (group A) or weekly for 6 weeks (group B), and sacrificed at 2-week intervals. Pancreatic neoplasms developed as early as 8 weeks (group B) and 10 weeks (group A); however, in group B there were fewer, smaller lesions, well-differentiated morphologically. Liver neoplasms occurred only in group A, while gallbladder and kidney tumors were seen in both groups. A lower incidence of pulmonary adenomas was found in group B than in group A, which also had pulmonary carcinomas. The results indicate a further advance in the development of a pancreatic cancer model.

Adenocarcinoma↗
PubMed2026

Endobronchial Ultrasound-Guided Biopsy-Derived Lung Cancer Models: A Platform for Precision Therapy.

BACKGROUND: Endobronchial ultrasound-guided transbronchial needle aspiration is used for clinical diagnosis and staging in patients with lung cancer. Nevertheless, establishing patient-derived preclinical models using needle biopsy samples remains challenging. This study describes the establishment and utility of patient-derived organoid (PDO) from endobronchial ultrasound-guided (EBUS) specimens and EBUS patient-derived xenograft (PDX). METHODS: A total of 175 EBUS specimens were used to establish PDO and PDX. "Stable establishment" organoids with passage numbers of 10 or greater were used for genomic, transcriptome, and pathologic assessment. Drug sensitivity of EBUS organoids and PDX tumors were compared with those of the matched patient. Drug screening was performed using stably established organoid models. RESULTS: We successfully established a total of 20 EBUS organoids: six EBUS-PDOs and 14 EBUS-xenograft derived organoids. These stable cancer organoid models were validated for cancer cell enrichment and pathologic assessment. Pathologic findings, exome, and transcriptome analysis found a high correlation between EBUS organoids and parental samples. EBUS organoids and PDX indicated consistent drug response patterns with their corresponding patients. A drug screening conducted on an EBUS organoid led to the discovery of potent activity of trametinib to a rare MAP2K1 K57N mutation. CONCLUSIONS: EBUS-PDO and -xenograft‒derived organoids are good options to generate stable organoids in patients with advanced stage lung cancer. The models were consistent with the genetic and pathologic features of patient tumors, and the patient's responses to treatment, supporting their utility for novel therapeutic research.

Humans↗
PubMed1977

Corynebacterium parvum as an immunotherapeutic agent in an ovarian cancer model.

Corynebacterium parvum, an anaerobic diptheroid, has been demonstrated to be therapeutic in several tumor models by stimulating immunologic defenses. Formalin-killed C. parvum was investigated in the present study as an immunotherapeutic agent in the treatment of murine ovarian cancer, a model that closely simulates the activity of clinical disease. C. parvum successfully prolonged survival in murine ovarian cancer and its effectiveness improved with increasing dosage. The efficacy of C. parvum was further enhanced by a multiple-dose regimen. A previous report demonstrated the efficacy of heterologous tumor antisera in the serologic treatment of murine ovarian cancer. At the dosages investigated, the combination of C. parvum and heterologous tumor antisera (SG-200) provided longer survival than either modality independently. C. parvum is an effective anti-cancer agent in murine ovarian cancer and may find utility in a clinical setting.

Animals↗
PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗
PubMed1976

Carcinoembryonic antigen and glucose phosphate isomerase in a human colonic cancer model (GW-39).

Levels of carcinoembryonic antigen (CEA) and glucose phosphate isomerase (GPI) have been compared in the circulating blood of hamsters bearing intra-muscular grafts of GW-39 human colonic tumour. CEA in the sera of GW-39 tumour-bearing hamsters ranged from 2-6 to 8-4 ng/ml (mean = 4-5 +/- 1-7 ng/ml). GPI in the sera of normal hamsters ranged from 332 to 749 iu/1 (mean = 602 +/- 110 iu/1) while those with 14-week-old intra-muscular grafts of a hamster amelanotic melanoma, (A.Mel.3), or GW-39 human colonic carcinoma had a range of 664 to 1267 iu/1 (mean = 1024 +/- 220 iu/1) and 1430 to 4719 iu/1 (mean = 2065 +/- 601 iu/1) respectively. Thus, the ratio of enzyme activity in GW-39, A.Mel.3, and normal hamsters was 3-4:1-7:1, indicating a significant elevation (P less than 0-01) in animals bearing a human colon carcinoma or a hamster melanoma, with particularly high values obtained in hamsters with GW-39. Sequential determinations of CEA and GPI in a group of hamsters transplanted intra-muscularly with GW-39 tumours revealed that both markers increased proportionately with duration of tumour growth, suggesting that both serum CEA and GPI may be used as measures of tumour growth. The concentration of GPI in GW-39 human colonic carcinoma xenografts was also significantly higher than that measured in normal human colon, primary human colonic cancer, or normal hamster tissues. These results support the view that GPI, in addition to CEA, is a quantitatively increased marker in this tumour model, and is liberated into the circulation in proportion to the increase in tumour mass.

Animals↗
PubMed1977

Cell surface antigens in a rat colon cancer model: correlation with inhibition of tumor growth.

Chemically induced bowel tumors in Wistar/Furth (W/F) rats possess surface antigens analogous to those demonstrated in humans with colon carcinoma. To determine if these in vitro tumors markers have any in vivo significance, tumor isograft challenge experiments were performed. Groups of animals received three immunizing doses of 10(7) cells from chemically induced colon carcinomas NG-W1, DMH-W49, or DMH-W9 or small-bowel adenocarcinoma DMH-W7. Control rats were immunized with a noncross-reacting, virally induced mammary fibroadenoma A9-W1. Six weeks after immunization, all animals were challenged with 1 X 10(5) or 3 X 10(4) colon carcinoma NG-W1 cells. None of the NG-W1-immunized animals developed tumors after either NG-W1 challenge dose. In contrast to this strong protection by "private" tumor rejection antigen (TRA), protection by common or "tissue type specific" antigens was evident only if tumor volumes were measured. Twenty-two days after low-dose NG-W1 challenge, mean tumor volume (m) in animals immunized with colon tumor DMH-W9 (m=0.25 cu cm) and DMH-W49 (m=0.17 cu cm) were less (p less than 0.05) than in animals untreated (m=1.0 cu cm) or immunized with mammary fibroadenoma A9-W1 (m=0.9 cu cm). Embryonic antigens also may function as weak TRAs. NG-W1 challenge tumor volumes in fetal-gut-immunized (m=0.9 cu cm) and whole embryo-immunized animals (m=0.9 cu cm) were less (p less than 0.05) than in fetal-kidney-immunized (m=2.5 cu cm) or adult-colon-immunized animals (m=1.8 cu cm). Low-dose NG-W1 challenge tumor volumes were less (p less than 0.01) in multiparous females (m=0.3 cu cm) than in either untreated (m=1.2 cu cm) or age-matched virgins (m=1.4 cu cm). In vitro tumor markers in this model may serve an important function in vivo as TRAs.

Adenocarcinoma↗
PubMed2026

Quantifying uncertainty of predictions from cancer progression models.

MOTIVATION: Cancer progresses through the accumulation of genomic events. Cancer progression models such as Mutual Hazard Networks (MHNs) describe this dynamic, enabling prediction of temporal event positions and patient-specific risks of acquiring mutations. However, current MHN analyses rely on single most likely models and do not quantify the uncertainty inherent to parameter estimation. Assessing forecast stability is essential before using them to anticipate treatment-relevant mutations, adapt targeted therapies, or prioritize monitoring of patients at elevated progression risk. RESULTS: We address a key prerequisite for the responsible clinical use of cancer progression models by making MHN-derived predictions uncertainty-aware. We present a Bayesian framework for MHN that uses Markov Chain Monte Carlo to sample from the posterior distributions of model parameters and derived predictions. For practical use we implemented the Random-Walk Metropolis, Metropolis-Adjusted Langevin Algorithm (MALA), and simplified manifold MALA samplers as part of the existing mhn Python package. Only MALA and smMALA were successful in sampling from MHN posteriors, with MALA performing best. While most MHN parameters and predictions showed low posterior variance, a small subset displayed greater variability across the posterior distribution. This differentiation cannot be obtained from a single most likely model, emphasizing the need for uncertainty quantification, especially in clinical contexts. As an illustrative example, posterior sampling identified a subgroup of STK11$-$, KRAS$+$ lung adenocarcinoma patients with a high predicted short-term risk-with low variance across posterior samples-to develop an STK11 mutation. This subgroup exhibited poorer survival under immunotherapy, resembling patterns observed in STK11+ patients. AVAILABILITY AND IMPLEMENTATION: Our implementation is part of version 1.2.0 of the mhn package (https://github.com/spang-lab/LearnMHN). All analyses including the code to produce all figures in this article can be found under https://github.com/huy29433/MCMC-sampling-for-MHN (https://doi.org/10.5281/zenodo.21160219).

Humans↗
PubMed1978

Cancer chemotherapy model using autochthonous large bowel cancer in rats.

Chemotherapy of methylnitrosourea-induced autochthonous large bowel cancer in rats, which is similar to that in man, was studied to evaluate the intrarectal administration or topical application of chemotherapeutic agents. Rats with large bowel tumors confirmed by endoscopic examination received an intrarectal instillation of 1 mg of 1-(4-amino-2-methyl-5-pyrimidinyl)methyl-3-(2-chloroethyl)-3-nitrosourea hydrochloride (ACNU), 1 mg of 1-(2-chloroethyl)-3-(4-methylcyclohexyl)-1-nitrosourea (Me-CCNU), or 5 mg of 5-fluorouracil (ir groups), or intraperitoneal injection of 2.5 mg of 5-fluorouracil (ip group) daily for 8 weeks. All the rats, including non-treated control rats, were necropsied after the treatment. The number of large bowel tumors per rat detected by endoscopy before the treatment was mostly the same among groups, whereas that observed at necropsy after the treatment was significantly smaller in ir groups, compared to non-treated group and ip group. The tumors increased significantly in rats of non-treated group and ip group between the time of endoscopy and necropsy, but not in rats of ir groups. These results showed that the maximum tolerated dosage of the agents administered intrarectally suppressed the development of new tumors after start of the treatment and also the growth of tumors which were detected by endoscopy before the treatment.

Administration, Topical↗
PubMed2026

hPSC models in cancer mechanisms and therapeutic discovery.

Despite major advances in cancer genomics and immunotherapy, the field remains limited by experimental models that fail to faithfully recapitulate human tumor initiation, genetic context, and immune-tumor interactions. Traditional animal and immortalized cell models often lack predictive power for therapeutic response and toxicity. Recent advances in human pluripotent stem cell (hPSC) technology have transformed this landscape, enabling the generation of patient-specific cancer models, multicellular organoids and assembloids, and scalable immune effector cells. These platforms now permit mechanistic dissection of tumorigenesis, reconstruction of human tumor microenvironments, and development of off-the-shelf immunotherapies. This review will synthesize these emerging findings, define key technological and biological gaps, and outline future directions for integrating hPSC-based modeling into precision oncology and translational cancer research.

cancer immunotherapy↗
PubMedDate not supplied

Clinical Oncology Program: a community cancer control model.

The majority of cancer patients are diagnosed and treated in their local communities, making it imperative to upgrade cancer management at the community level. The Clinical Oncology Program has demonstrated that sophisticated cancer control programs are possible in a community setting. Moreover, if "quality of survival" data collection is included in such programs, valuable information emerges that can further improve cancer management in the community.

Hospitals, Community↗
PubMed2025

Bayesian Modeling of Cancer Outcomes Using Genetic Variables Assisted by Pathological Imaging Data.

With the increasing maturity of genetic profiling, an essential and routine task in cancer research is to model disease outcomes/phenotypes using genetic variables. Many methods have been successfully developed. However, oftentimes, empirical performance is unsatisfactory because of a "lack of information." In cancer research and clinical practice, a source of information that is broadly available and highly cost-effective comes from pathological images, which are routinely collected for definitive diagnosis and staging. In this article, we consider a Bayesian approach for selecting relevant genetic variables and modeling their relationships with a cancer outcome/phenotype. We propose borrowing information from (manually curated, low-dimensional) pathological imaging features via reinforcing the same selection results for the cancer outcome and imaging features. We further develop a weighting strategy to accommodate the scenario where information borrowing may not be equally effective for all subjects. Computation is carefully examined. Simulations demonstrate competitive performance of the proposed approach. We analyze TCGA (The Cancer Genome Atlas) LUAD (lung adenocarcinoma) data, with overall survival and gene expressions being the outcome and genetic variables, respectively. Findings different from the alternatives and with sound properties are made.

Humans↗
PubMed2026

Cross-Platform Concordance in DNA Methylation Based Classification of CNS Tumors.

DNA methylation profiling enables precise classification of pediatric central nervous system (CNS) tumors. Oxford Nanopore Technologies (ONT) offers same-day, single-sample methylation readouts, but its concordance with Illumina EPIC arrays in routine diagnostic tasks remains incompletely defined. We profiled 23 pediatric tumors (18 CNS, 5 non-CNS) by EPIC arrays and ONT. Methylation profiles from both platforms were classified with crossNN (brain model or pan-cancer model); ONT data were additionally classified with Rapid-CNS2 and Sturgeon. We compared (i) classifier agreement with integrated histology (w/o NGS) at family/class levels, (ii) pass-rate above platform-specific score cutoffs, (iii) cross-platform concordance of copy-number variation (CNV), and MGMT promoter methylation status. In CNS cases, ONT and EPIC methylation profiles demonstrated strong correlation, except for a single outlier (P2), which was excluded from further analysis. Comparative assessment of the two platforms showed that: (a) Molecular classification of CNS tumors using the crossNN classifier was consistent with histology (w/o NGS) at the family level in all cases. (b) Copy-number profiles showed high concordance between platforms. (c) MGMT promoter methylation status matched in 94% of cases (16/17). When comparing ONT-specific analysis pipelines using the ONT data, the Rapid-CNS2 pipeline yielded the most reliable class level assignments with 94% (16/17) concordance with the histopathological diagnosis, which marginally exceeded the crossNN and sturgeon classifiers. In non-CNS tumors, the pan-cancer model produced low-confidence outputs with poor agreement with histology (w/o NGS) (only 1/5 concordant), indicating limited readiness for these entities. In conclusion, ONT enables same-day, clinically reliable family-level CNS tumor classification with high concordance to arrays, while EPIC retains a modest class-level edge. A key limitation of ONT is its reliance on fresh-frozen DNA and on classifiers originally built around array-derived CpG sites, rather than on models developed natively from ONT data.

DNA methylation↗